Document ID: EPA-HQ-ORD-2006-0260-0014
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2008-03-03T05:00Z

U.S. ENVIRONMENTAL PROTECTION AGENCY

SCIENCE ADVISORY BOARD STAFF OFFICE

CLEAN AIR SCIENTIFIC ADVISORY COMMITTEE (CASAC)

SULFUR OXIDES PRIMARY

NATIONAL AMBIENT AIR QUALITY STANDARDS (NAAQS) REVIEW PANEL

PUBLIC MEETING

MARRIOTT AT RESEARCH TRIANGLE PARK

4700 Guardian Drive

Durham, North Carolina 27703

DECEMBER 5, 2007

8:32 A.M.

1	U. S. ENVIRONMENTAL PROTECTION AGENCY

2	CLEAN AIR SCIENTIFIC ADVISORY COMMITTEE (CASAC)

3	PUBLIC MEETING

4	SULFUR OXIDES PRIMARY

5	NATIONAL AMBIENT AIR QUALITY STANDARDS (NAAQS)

6	REVIEW PANEL

7	DECEMBER 5, 2007

8	DR. STALLWORTH:	Can I ask everyone

9	to take a seat, please?	We can't start without our

10	chair, so.	Tim, we're still shuffling and getting

11	settled in.	Tim, can you hear me now?

12	DR. LARSON:	Hello.

13	DR. STALLWORTH:	Hello.	Tim, can

14	you hear us?

15	DR. LARSON:	Yeah.

16	DR. STALLWORTH:	Great.	We're

17	waiting on our chair, actually.	Okay.	Good morning.

18	I want to get started.	I'm Holly Stallworth.	I'm the

19	designated federal officer for the CASAC SOx panel, and

20	I want to open with a short statement.	The CASAC SOx

21	panel is a federal advisory committee, and by EPA

22	policy its meetings and deliberations are held as

23	public meetings that meet the requirements of the

24	Federal Advisory Committee Act.	The Clean Air

25	Scientific Advisory Committee or CASAC is empowered by

1	law to provide advice to the Administrator.	Consistent

2	with requirements of FACA, that's the Federal Advisory

3	Committee Act, the deliberations of the CASAC SOx panel

4	are conducted in public meetings for which advance

5	public notice is given.	The discussions and

6	substantive	deliberations of the panel, its

7	interactions with the public are conducted in sessions

8	where I am present to ensure that requirements of FACA

9	are met.	This includes the requirements for open

10	meetings, for maintaining records, and making available

11	public summaries of meetings and providing

12	opportunities for public comment.	We do expect one

13	public commentor this morning at 9:20 from the American

14	Petroleum Institute.

15	I'll be taking minutes.	We expect to

16	have them approved by the chair and posted in about a

17	month or two, and finally I want to remind folks that

18	everyone on this panel has been approved by the SAB

19	staff office in terms of the absence of any conflict of

20	interest or appearance of a lack of impartiality.	I

21	can't think of any housekeeping issues yet.	So I'll

22	turn it over to Dr. Tony Maciorowski, the Deputy

23	Director of the SAB.

24	DR. MACIOROWSKI:	This will be very

25	brief.	I just want to -- on behalf of the

1	Administrator's Office and the Science Advisory Board,

2	we want to thank you all for being here today.	We

3	particularly want to thank Rogene for chairing this

4	meeting, as once again she's doing Yeoman's work as the

5	chair.	I want to welcome all the CASAC members and all

6	the panelists.	And we want to particularly mention the

7	EPA staff who are prepared to make presentations to

8	you.	Ila Cote is standing here.	I think she'll be the

9	first speaker.	It's my understanding that Lydia Wegman

10	and Karen Martin will not be here this morning, but Dr.

11	Michael Stewart will be sitting in for them this

12	morning.	And welcome all the members of the public,

13	and I turn the meeting over to Rogene.

14	DR. HENDERSON:	Thank you, Tony.

15	I want to emphasize to the group how important this

16	meeting is to review the ISA for the SOx.	This is the

17	second Integrated Science Assessment document we've

18	looked at.	We looked at the NOx document earlier, this

19	same committee, and as I said before, this is a new

20	process, a new way of doing things.	In place of the

21	criteria document we have this Integrated Science

22	Assessment document.	And I know in talking to Ila and

23	Mary, they're working very hard to develop this as a

24	meaningful document, and we have the privilege of being

25	in on advising them on how to make this the most

1	meaningful document for setting standards that we can.

2	So you have an important task before you here, and I

3	look forward to the discussion that's coming.

4	As we did with the NOx document, I have

5	asked specific people to be lead discussants on certain

6	sections of the report.	At the end of the day, those

7	lead discussants, the ones with their names underlined

8	-- I think they're underlined, yes -- will be

9	responsible for pulling together the consensus view of

10	the group, of the whole panel and answering, providing

11	comments on the specific chapters to which you're

12	assigned.	We are doing it a little different with SOx

13	than with NOx.	With NOx it was charge question by

14	charge question.	That resulted in some redundancy in

15	our report because there's so much overlap between the

16	charge questions.	So this time we're going chapter by

17	chapter, which is really what we've done more often in

18	the past, and that's going to avoid some of that

19	redundancy.	Are there any questions from the panel?

20	I'm not letting you introduce yourselves because we

21	just met for NOx, so I'll presume we all know each

22	other.	But if you have any question about how we're

23	doing this and who's responsible for what.	At the end

24	of the day you'll e-mail Holly your draft comments for

25	the chapter and she will collate those, and in the

1	morning we'll have that draft response to the

2	administrator ready for our review for concurrence

3	within the whole panel.

4	So that's how it happens.	It worked

5	well last time, and I expect it to work well this time.

6	Okay.	Now we're going to turn it over to Ila who is

7	going to tell us about this next ISA.

8	DR. COTE:	I actually mostly just

9	want to welcome people.	Thank you for coming to help

10	us again.	Welcome you on behalf of EPA.	If	there's

11	anybody here that doesn't know me, I'm Ila Cote.	I'm

12	the acting Division Director for the ORD effort on the

13	criteria pollutants.

14	Today we're going to talk specifically

15	about the ORD effort on the Integrated Science

16	Assessment, and tomorrow the emphasis will be on the

17	Office of Air and Radiation, OAQPS's effort.

18	So I just wanted to remind everybody a

19	bit of where we were before we went into talking about

20	highlights from the previous review.	I just want to

21	touch briefly on the current process to remind

22	everybody where we are and the schedule, and then

23	Mike's going to pick it up and talk about the history

24	and highlights from the previous review.	As you

25	remember, this is the process that we're working on. We

1	are, we have developed the integrated plan.	You looked

2	at PM, was it last week, two weeks ago?	And we're here

3	at the Integrated Science Assessment.	Tomorrow we'll

4	talk about the Risks of Exposure Assessment, which all

5	lead to the draft announced Notice of Proposed

6	Rulemaking.	So I think everybody remembers where we

7	are in the schedule or in the process.	So this is the

8	schedule.	The integrated plan is, the projected

9	completion date for the draft is April 2007, which is

10	not far away and the final in October 2007.	And the

11	projected CASAC review for the next version is in May,

12	or we've done that and then -- sorry.	My staff is

13	laughing at me.	And then the Integrated Science

14	Assessment, the first draft, is, will be completed in

15	September of '07, which we just had, and then April of

16	'08, and the final in September of '08.	And the CASAC

17	meeting is right here, and then for the final in July

18	of '08.	So that's kind of where we are in the

19	schedule.	I hope you're oriented even if I'm not.	So

20	I'll, unless there are questions, I'll turn it over to

21	Dr. Michael Stewart from the air office.

22	DR. STEWART:	Thank you, Ila.	My

23	name is Dr. Michael Stewart, and I am from OAQPS.	I'm

24	in Karen Martin's group, and she's very sorry she

25	couldn't be here today, but hopefully I'll be able to

1	give sort of a historical context to, from the previous

2	review so that we can keep in mind as we look at the

3	issues during the current review.	And the only thing

4	I'd like to point out with the schedule is that the

5	next time that there's a SOx CASAC meeting will be in

6	July of 2008.	And when we're, after they talk about

7	this second draft in the Integrated Science Assessment,

8	we'll also be looking at the first draft of the Risk

9	Exposure Assessment.	So with that -- next slide,

10	please.

11	So now I'd like to do a brief history of

12	the SO2 NAAQS, and although this slide doesn't look

13	brief, it actually is.	In 1971, EPA --

14	SPEAKER:	Excuse me.	Is it possible

15	to be a little closer to the microphone?

16	DR. STEWART:	Sure.	Is that better?

17	SPEAKER:	Yeah.	We can't hear.

18	DR. STEWART:	Can you hear now?

19	SPEAKER:	Better.

20	DR. STEWART:	Is that better?	In

21	1971, EPA promulgated the first NAAQS for sulfur

22	dioxide.	There was a primary NAAQS.	A 24-hour

23	standard would set at .14 parts per million and an

24	annual standard was set at .03 parts per million.	A

25	secondary NAAQS	is also promulgated with a three-hour

1	standard set at 0.5 parts per million.	In 1988, EPA

2	proposed not to revise the current standards but

3	requested specific comment on adding a one-hour primary

4	standard of 0.4 parts per million.	And this was to

5	protect asthmatics at elevated ventilation rates, for

6	example, while exercising, from short-term 5 to 10-

7	minutes peaks of SO2 exposure.	And this proposal as

8	well as the request for comment was based on a criteria

9	document for PM and sulfur oxides that was published in

10	1982 as well as an addendum to that document published

11	in 1986.	Now during the public comment period for the

12	proposal there were several questions raised as to

13	whether there was an underestimation of both the

14	magnitude of the health affects associated with these 5

15	to 10-minute peaks of sulfur dioxide as well as the

16	size of acceptable population.	In response to this,

17	the EPA published a supplement to the second addendum

18	to the criteria document.	And this documents focused

19	on recently available clinical exposures of asthmatics

20	to SO2, and in that document is also an exposure

21	analysis that provide an estimate of the number of

22	asthmatics at elevated ventilation rates that were

23	likely to be exposed to short-term peaks of SO2.	Based

24	partly on the information in these documents, in 1994,

25	EPA reproposed not to revise the current standards but

1	again requested comment on regulatory alternatives

2	including adding a 5-minute standard of .6 ppm or

3	establishing a new regulatory program under Section 303

4	of the Clean Air Act.	And Section 303 of the Clean Air

5	Act allows for the EPA to have intervention if they

6	find an imminent and substantial endangerment to human

7	health or welfare.	In 1996, EPA published a final

8	decision not to revise the current standards.	EPA did

9	not promulgate a 5-minute standard or any other

10	regulatory program.	This decision was challenged by

11	the American Lung Association and the Environmental

12	Defense Fund.	And a little bit later, in a later slide

13	I'll talk a little bit more about support case.	In

14	1998, the DC Circuit Court of Appeals remanded the

15	decision back to EPA, saying that EPA did not provide

16	adequate rationale for not setting a five-minute NAAQS.

17	In 2006, there was a deadline suit filed for the Center

18	for Biological Diversity stating that EPA had missed

19	its statutory deadlines for reviewing the	NAAQS, and

20	this is actually part of a larger complaint that

21	included statutory deadline misses for the NO2 primary

22	NAAQS as well as for the secondary NO2 and SO2.	And I

23	just want to also mention that currently we have a

24	consent decree in the deadline suit entered, and we

25	have deadlines that are now finalized.	So we have to

1	have a proposal by July 29, 2009 as well as a final

2	rule making by March 2nd, 2010.	And I also want to

3	mention that the current view will also address the

4	issues raised during the 1998 remand.	Next slide,

5	please.

6	So now what I would like to do is just

7	in general touch on the highlights in the previous

8	review and talk about the key health effects identified

9	during the previous review.	Increased respiratory

10	illness and symptoms were associated with long-term

11	exposure to SO2, and aggravation of bronchitis

12	increased mortality and decreased lung function in

13	children were associated with short-term exposure to

14	SO2.	And in this context when I say short-term, I'm

15	talking about more along the lines of 24 hours.	Now

16	it's important to note, and the previous staff papers

17	note that these epidemiologic studies were done at

18	times and in places where there were both high episodes

19	of PM as well as high episodes of SO2, so it was

20	difficult to delineate whether the health effects were

21	from SO2 alone, or PM alone, or some other combination.

22	Also in the previous review, it was found that

23	transient impairment of respiratory function in a

24	significant proportion of exercising asthmatics

25	following 5 to 10 minute exposures of SO2 at levels as

1	low as .6 PPM, and these lung function changes included

2	decreases in FEV1 as well as increases in specific

3	airway resistance.	So the administrators conclusions

4	from the previous review, the existing annual and 24-

5	hour standards are required to protest against health

6	effects associated with long and short-term exposure to

7	SO2, and five-minute peak SO2 levels do not cause a

8	broad public health problem when viewed from a national

9	perspective because they are localized infrequent and

10	site specific and therefore are not the appropriate

11	type of, are not the type of ubiquitous public health

12	problem for which establishing an act would be

13	appropriate.	Thus, a five-minute standard was not

14	adopted.	And also I'll talk about this conclusion

15	based on an exposure analysis conducted by the EPA.

16	Next slide, please.

17	So after the EPA, after the EPA

18	published that it was not going to promulgate a five-

19	minute NAAQS, I eluded to this in the history that the

20	American Lung Association filed a suit, and in 1998,

21	the Court of Appeals for the District of Columbia found

22	EPA failed to adequately explain determination that

23	revisions to the Sox NAAQS were not appropriate.	And,

24	again, the decision was remanded back to the EPA.	The

25	court required EPA to provide an adequate explanation

1	for the conclusions that five-minute exposures to SO2

2	do not amount to a public health problem under the

3	Clean Air Act given an exposure analyses which shows

4	that between 68,000 and 166,000 asthmatics at least

5	once per year are exposed to levels causing adverse

6	effects.	The EPA has not formally answered this

7	remand, but in the time following the remand engaged

8	the American Lung Association in the negotiations.	And

9	out of those negotiations came an increased monitoring

10	effort, and this monitoring effort was trying to get at

11	where these short-term peaks are likely to occur and

12	with what frequency.	And much of that data that has

13	been collected is going to feed into the current

14	review.	So during the current review we're going to

15	conduct a new risk exposure analysis to better estimate

16	the current size of the asthmatic population affected

17	by short-term peaks of SO2.	And we'll also consider

18	whether ruling making under 303 is appropriate.	In

19	addition to the normal, just looking at, the normal 24-

20	hour as well as the existing, the existing standards --

21	I'm sorry -- to see if any changes need to be made to

22	those.	And that's all I have.	Thank you.

23	DR. HENDERSON:	Thank you.	Are there

24	any questions for Michael?

25	DR. BALMES:	Rogene.

1	DR. HENDERSON:	Yes.

2	DR. BALMES:	Whoever is speaking has

3	to be closer to the microphone for us on the phone to

4	hear.

5	DR. HENDERSON:	And that, I'm glad

6	you reminded me.	We forgot, Holly and I forgot to, to

7	introduce people who are on the phone, and I think,

8	Holly, do you need to be the one who, who calls?

9	DR. STALLWORTH:	Could you introduce

10	yourself?

11	DR. HENDERSON:	We've got John

12	Balmes and then others have called in.	Who else is on

13	the phone?

14	DR. LARSON:	Tim Larson is here, but as

15	John said, it's difficult to hear.

16	DR. PINKERTON:	Also Kent Pinkerton

17	from Davis.

18	DR. HENDERSON:	Good.	Okay.	I

19	think people here are speaking very loudly, and so I am

20	wondering if the audio-visual people can help us a

21	little on that because he's got his hand up saying he

22	is.	So we'll, we'll try to improve that because --

23	Ila, did you have something to say?

24	DR. COTE:	Oh, okay.	Frank had --

25	DR. SPEIZER:	You sent me over here so

1	you won't have to hear me.

2	DR. HENDERSON:	No.

3	DR. SPEIZER:	I'd like to ask about

4	this additional monitoring.	Has any of this been

5	reached, reached the peer review literature?	Where are

6	the data and who is looking at them?

7	DR. STEWART:	I think we'll talk more

8	about this tomorrow during the scope and methods plan,

9	but what I can say is that what came out of the result

10	of negotiations with the American Lung Association is

11	that some of the monitors now are actually going to

12	collect 12, five-minute intervals rather than just

13	collecting the five-minute max within an hour.	But,

14	again, we will talk about this some more tomorrow.

15	DR. SPEIZER:	Wait a minute, you just

16	said "are going to."	Hasn't this been done?

17	DR. STEWART:	Well it has, yes.	Yes.

18	DR. HENDERSON:	Are there other

19	questions, and if you're to my right, I really can't --

20	I mean, on the front.	Frank and George are the only

21	ones, you'll have to call out my name.	Okay.	I think

22	you have an additional presentation, I mean, to NCEA?

23	DR. ARNOLD:	Okay.	Thank you very

24	much.	I'm going to address the Integrated Science

25	Assessment that we've been working on to support the

1	Office of Air as they try to build options for the

2	administrator to select.

3	DR. HENDERSON:	Would you give

4	your name?

5	DR. ARNOLD:	Sure, sorry.	I'm Jeff

6	Arnold.	I'm in Mary Ross's branch.	I do atmospheric

7	chemistry.

8	DR. HENDERSON:	Thank you.

9	DR. ARNOLD:	Next slide, please.

10	This is the team.	You've already met Ila Cote, Mary

11	Ross, who is sitting behind us, Dr. Jee Young Kim who

12	is sitting to my left who has been running the SO2

13	team, and the other members of the team from NCEA.

14	Next slide.	This is a list of our expert authors who

15	have contributed to individual sections, chapters of

16	the ISA and sections of the annexes, which support the

17	ISA.	Yes, please.

18	SPEAKER:	I've already recognized

19	those three.

20	DR. ARNOLD:	Great.	Next slide,

21	please.	So what I'd like to do now is just talk

22	generally about the ISA, and what we're going to

23	present today are just really the brightest highlights

24	of the things which have appeared in the ISA because we

25	know that CASAC members have had it now, and have been

1	looking at it, and have provided comments to us that

2	we've gotten and appreciated.	And the things that I

3	want to point up are things out are things that have

4	allowed us to relate the science to the policy making

5	needs of the Office of Air as they go about developing

6	options.	So in the first section we're going to look

7	at source to dose, and this is going to be looking at

8	emissions of SO2, transformations, fate, and ambient

9	concentrations.	Then we're going to try to

10	characterize those as they're important for

11	understanding the health effects, both short-term and

12	long-term exposures.	Next slide, please.

13	The Integrated Science Assessment, as

14	Ila said, and I know this panel is aware, is a new

15	process, and it's an integrated process in multiple

16	ways.	We've been integrating across scientific

17	disciplines.	We've been trying to reduce the size of

18	what was previously the criteria documents for

19	individual NAAQS criteria pollutants, and integrate

20	both across science, as I said; and then integrate more

21	closely with the Office of Air so that we understand

22	how we can best serve them as they go about designing

23	and testing these options; how we can provide the most

24	useful science that will allow them to support the

25	information that they will present to the

1	administrators.	The annexes, as I said, support the

2	ISA, which is the integrated and summary document that

3	the panel has seen and reviewed for us, and this is in

4	response to repeated calls from CASAC, which have been

5	quite useful to us to	produce a sleeker document,

6	something that's more useful, both for the Office of

7	Air and something that's more integrated, something

8	that's easier for CASAC to read and for the public to

9	digest as well.	So there are, as we've designed it

10	now, there are these two forms to the total science

11	review that ISA, which integrates across the

12	information that's been supported in the annexes.	And

13	I'd like to say that this review is for the primary

14	standard for gas phase SO2.	We will be talking a

15	little bit on the chemistry slide later	about the, one

16	of the phase of SO2, which is production of sulfate.

17	However, we're not concerned with particulate sulfate

18	in this review.	Particulate sulfate is being reviewed

19	both under the PM standard, which is now beginning, and

20	we'll be looking at welfare effects there related to

21	visibility, climate.	And we're also looking at

22	secondary effects from particulate sulfate in the

23	combined NO2/SO2 secondary standard for which we've

24	just finished the first draft of the ISA.	Next slide,

25	please.

1	These are the charge questions given to

2	CASAC members to evaluate for the first chapters on

3	exposure to dose.	I won't read them to you since I'm

4	sure you've read them and have designed your comments

5	around them.	I'll just point out that the important

6	part, important parts to us occur in the first, the

7	first bullet, things that are relative to the review of

8	the primary SO2 notes.	And then in the last bullet,

9	things that are important for the evaluation of human

10	health effects, that's sulfur oxides.	And these are

11	the considerations that have conditioned our writing in

12	the ISA, conditioned our selection of science and we've

13	collected it and reasoned through it, summarized it,

14	and then assessed it so that we can provide support to

15	the Office of Air.	Next slide, please.

16	So very generally I just want to say

17	these few summary things about SO2, chiefly produced

18	from fossil fuel combustion, mostly by electric

19	generating units, highly soluble oxidized to sulfate,

20	mostly in cloud droplets.	Dry deposition and

21	conversion to sulfate results in a lifetime SO2 of

22	roughly a few days in the atmosphere.	Sulfate then

23	circulates, depending on precipitation, for about a

24	week.	And what this means -- again, we don't want to

25	focus on sulfate itself, but what this means is

1	lifetimes for SO2 and sulfate means that the sulfur can

2	be dispersed over large areas, largely homogeneous

3	regional ambient exposures, except where you have

4	particular events.	Next slide, please.

5	You see here a depiction for the eastern

6	third of the continental US, the difference in ambient

7	SO2 concentrations from a three-year average, 1989 to

8	'91, before controls, the acid rain program controls

9	went on the large sulfur emitters and the difference in

10	the most recent period for which we have data 2003 to

11	2005.	And you can see now that in 2005 the mean

12	ambient SO2 concentration was roughly PPB.	However,

13	this dramatic improvement in ambient SO2 does still

14	result in local hotspots.	Next slide, please.

15	What we're showing here with a rather

16	busy table that is actually cut down from the table it

17	appears in the ISA is that even with the dramatic

18	reduction of almost 50% in ambient SO2 from the year

19	1990 to 2005, it is still possible to get very large

20	concentrations for one hour exposures.	So you'll see

21	all the way to the right of this slide, the max

22	concentration for one hour can be as high as 700 PPB

23	while the 24-hour and annual average are still quite

24	low, down in the single digit PPBs.	So this is

25	something that we thought would be useful and helpful

1	for the Office of Air.	Next slide, please.

2	Converting from ambient exposures to

3	personal exposures.	We have some summary points here

4	and chief among them is to realize that indoor SO2

5	comes mostly from the infiltration of outdoor air.

6	There are now a few sources of indoor SO2, and because

7	of this and because of the fact that ambient

8	concentrations are now so low, expect for these

9	infrequent peak exposures that I was showing on the

10	previous slide, only five studies have been identified

11	since the last review that characterize personal

12	exposures to present day low concentrations.	Part of

13	the problem with this, with these characterizations is

14	that personal exposures are now at or below the

15	detection limit of most passive samplers, and this

16	introduces uncertainty in the correlations between

17	ambient and personal exposures.	As you see in the

18	bullet down below that, the rations of indoor to

19	outdoor have quite a wide range due to building

20	characteristics.	Indoor heating and ventilation

21	sources varying with season; that is, there are still

22	some people who are exposed to some indoor SO2 from

23	kerosene heaters, and it is also changes with

24	ventilation rates.	People open the windows more or

25	less depending on season and latitude.	These things

1	are changing the ratios.	However, studies with well

2	characterized personal exposures at higher

3	concentrations, that is above the minimum detection

4	limit at these personal exposure batches, have

5	demonstrated positive associations.	And here is an

6	example, one from Brower et al, 1989.	Next slide.

7	DR. HENDERSON:	Before you go on, may

8	I ask a question?

9	DR. ARNOLD:	Sure.

10	DR. HENDERSON:	There's been a lot

11	of press about these sulfur oxides coming from ships,

12	you know traveling along the coast, is that something

13	that you found to be true that's a major contribution

14	or?

15	DR. ARNOLD:	Yeah.	The -- it's a very

16	good question.	The emission of sulfur oxides from,

17	from marine traffic is, is highly uncertain in the

18	current commissions inventory, and there have been

19	efforts over the last few years to look at ship tracks

20	in, ship tracks of SO2 in the transportation corridors.

21	And although this information has been, is recent and

22	we have looked at it, as I say it is very uncertain in

23	the EPA emission inventories.

24	DR. HENDERSON:	Okay.	We have another

25	question, Ed.

1	SPEAKER:	Just as a comment, we'll

2	talk about it more later, but in the context of

3	California, it's not so indecisive, certainly

4	California because we don't have coal fired plants.

5	The sulfur admissions from the harbor, from the ships

6	coming to port to Los Angeles and Long Beach accounts

7	for over half of the sulfur burden SO2 across the

8	basin.

9	DR. ARNOLD:	Yes, I'm sorry.	I

10	didn't mean to suggest that it was unimportant.	I was

11	suggesting that it was uncertain because it hasn't been

12	looked at extensively until very recently, but we have

13	looked at both, both emissions during transit and then

14	during the periods called hoteling when the ships are

15	actually idling at port when things are being moved on

16	and off.	And you're quite right.	And one of the

17	reasons I didn't mention, I alighted over the point

18	that when I was showing the eastern third, when I was

19	showing those spacial temporal plots for the change, we

20	weren't showing the west because, as you know, the SO2

21	problem is much greater in the east.	So you're quite

22	right, and we, we take that comment.	Thank you.

23	DR. HENDERSON:	Okay.	Yeah, go

24	ahead.	Do we -- no.	We've got more XX.

25	SPEAKER:	I just have a question

1	about what you meant by transportation corridor, and I

2	wondered if you had looked at the evidences with regard

3	to the operation of marine engines in the

4	Houston/Galveston/Brazoria non-attainment area?

5	DR. ARNOLD:	That information is, is

6	known to us.	We have not, we have not, we have not

7	specifically addressed that transportation corridor in

8	itself in the ISA.	As you've probably seen, we don't

9	call out a Houston/Galveston shipping channel itself,

10	but that's exactly what I mean.	And the sort of ships

11	you can look at, it's possible to trace SO2

12	concentrations from the ship stacks as they move in the

13	shipping corridors and then as they come into port for

14	these, as we're saying, for these hoteling operations

15	where they're actually idling and still producing SO2.

16	And the port, as it was pointed out in California, is a

17	very large source of that.	So certainly at places

18	where, where there are major ports, you can get a very

19	large local contribution.	Again, since this

20	information is, is new, relatively new in the last few

21	years, the emissions inventories are quite uncertain

22	about, about how to disperse those numbers across the

23	boards.

24	SPEAKER:	So the word transportation

25	corridors could be, could be translated to harbors.

1	DR. ARNOLD:	Both, both harbors and

2	then the ship tracks as they, as the ships are moving

3	into harbor; that's correct.

4	SPEAKER:	Okay.	Thank you.

5	DR. HENDERSON:	Are there any other

6	people who want to ask questions before we move on.

7	Okay.	Go right ahead.

8	DR. JOHNS:	My name is Doug Johns.

9	I'm a health scientist with NCEA, and I'm going to

10	begin the presentation of material related to charge

11	questions four through six dealing with health effects

12	of SO2.	And, again, I'm not going to read through

13	these questions, but you have them.	Next slide.

14	I'd first like to go over the

15	classification system that we use in evaluating the

16	health evidence related to SO2 exposure, and this is

17	described in Chapter 5 of the ISA.	The relationship

18	between SO2 exposure and some adverse health effect was

19	considered causal only when it was supported by strong

20	and consistent evidence from human clinical studies.

21	Where there was strong and consistent epidemiological

22	evidence along with coherent and plausible human

23	clinical or animal toxicological evidence, we

24	considered the relationship to be likely causal.	Where

25	the epidemiological findings are generally strong,

1	consistent but with limited experimental evidence for

2	coherence and plausibility, we concluded the

3	relationship was suggestive, and the relationship

4	between SO2 and health effect was judged to be

5	inconclusive where either the epidemiological evidence

6	of the experimental evidence was strong and consistent.

7	Next slide.

8	Sulfur oxide is highly water soluble and

9	is readily absorbed in the upper airways.	So for

10	individuals breathing through their nose, almost all

11	the inhaled SO2 is absorbed in the nasal passage, and

12	this is depicted in the figure on the left with the

13	yellow and red checkerboard shading representing SO2

14	and the airway.	It shows that very little of the SO2

15	reaches the lower respiratory tract.	However, with

16	exercises there's an increase in ventilation rate along

17	with a shift from nasal to oronasal breathing, which

18	causes, allows a significant fraction of the inhaled

19	SO2 to reach the lower airways, and that's shown here

20	in the figure on the right.	And this is something

21	that's important to remember as we discuss the health

22	effects of SO2. Next slide.	Controlled human studies

23	among exercising asthmatics have consistently

24	demonstrated SO2 induced decrements in FEV1, increases

25	in specific airways resistance, as well as increases in

1	respiratory symptoms following peak exposures to

2	concentrations between 0.5 and 1.0 PPM, and these

3	effects are seen within minutes of the start of

4	exposure.	And the studies conducted over the past 20

5	to 25 years typically looked at effects falling 5 to

6	15-minute exposures.	With increasing concentrations,

7	there is an increase both in severity of response as

8	well as the fraction of subjects that are affected.	It

9	is important to point out here that the effects are

10	generally not enhanced with increasing exposure

11	duration above 10 to 15 minutes, and, in fact, in many

12	studies the effects have been observed to be attenuated

13	when exposures go beyond that period or when there is a

14	repeat exposure separated by 15 to 30 minutes of rest.

15	And finally, just to point out that these respiratory

16	effects have generally not been observed in exercising

17	non-asthmatics at concentrations below 1.0 PPM.	Next

18	slide.	Thank you.

19	So as an example of what I described in

20	the previous slide, this is a study coming from, a

21	study from 1986 looking at SO2 induced changes in

22	specific airways resistance following 10-minute

23	exposures with moderate levels of exercise.	These

24	exposures were done among asthmatics, 27 asthmatics.

25	So this is a cumulative frequency plot with each point

1	along this plot representing the concentration that was

2	estimated to result in a doubling of specific airways

3	resistance for a given individual.	So in the study

4	they found that approximately 25% of the subjects

5	experience this doubling at concentrations below 0.5

6	PPM, and this is relatively, this has been observed in

7	many other studies.	In fact, in some studies up to 50%

8	of the asthmatic subjects experience moderate to severe

9	decrements in lung function at concentrations as low as

10	0.5 to 0.6 PPM, and those effects are usually

11	accompanied by significant increases in respiratory

12	symptoms.	Another thing to point out here is the

13	variability in response with some subjects affected at

14	concentrations below 0.3 PPM while others are not

15	affected at concentrations below 5 PPM.

16	So this is a brief overview of the

17	evidence from human clinical studies.	And if there are

18	any questions.	I think Dr. Jee Young Kim will be

19	discussing the epidemiological evidence.

20	DR. HENDERSON:	Do people have any

21	questions for Doug?	Yes.	Oh, good.	Hi.

22	DR. THURSTON:	Hi.	Yeah.	I really

23	have what I consider a very serious problem with this

24	which is that what you're talking about here primarily

25	is just pure SO2.	Now in the real world people aren't

1	exposed to just pure SO2, and you also, we're going to

2	have a discussion in a minute about the epidemiology,

3	and the epidemiology is showing associations, some very

4	compelling associations at much lower levels.	And one

5	of the questions that I think this document has to

6	address, really confront, is, you know, how can that be

7	with the controlled studies.	What is it that these

8	controlled studies-- and they do tell us things.	But

9	what is it they're not telling us?	And there's

10	evidence out there which is not brought forth in this

11	document about enough-- there is, I think, one study,

12	Jane Koenig's study where she has particles in there

13	and where there are no effects of SO2.	She adds in

14	sodium chloride particles and suddenly there are

15	effects at much lower levels.	This is very information

16	because that's what happens in the real world.	In the

17	real world there are always particles around, and

18	particles are a vector for gases into the lung.

19	There's Mary Anders' work.	So there's, there's

20	controlled studies that have been done.	There's also

21	toxicology in animals.	Mary Ander's work -- I know

22	some people sort of objected to looking back beyond the

23	last 5 years or 20 years, but I think good information

24	is good information whenever it occurs.	And I think

25	the salient point, salient research to be brought

1	forth, irrespective of when it was done.	So I really

2	don't have a problem.	I really don't like that -- I

3	mean, you certainly should emphasize what have we

4	learned since the last document, but you also ought to

5	be looking back and saying, giving a context, which you

6	have done to some extent.	But I really do think the

7	context is important, and studies like Mary Anders'

8	shouldn't be ignored because they're informative about

9	this dichotomy, apparently dichotomy between the

10	clinical studies.	You know, you're saying well there

11	is no effect in normal people above 1, but every one of

12	these documents should say to pure SO2, to pure.	Every

13	time you're just talking about SO2 you should say pure

14	SO2, and then the reader will know, oh, this is not

15	really like what I'm exposed to.	This is not what the

16	populations are exposed to.	And when there's a mixture

17	that's been looked at, I think that's important to note

18	too.

19	So that's, that's my, I guess, major

20	point on this, and I didn't realize we were commenting

21	section by section on a related thing.	You know, in

22	the previous one, in slide number eight, I think, there

23	was no information there about the five-minute data,

24	you know.	I went through this whole ISA, and I had no

25	idea that there were these five-minute data that had

1	been collected for years.	Then I read the other

2	document and I said, my God, look at all this data.	I

3	could really use this to inform my knowledge about what

4	people are exposed to these short -- 'cause let's face

5	it, one of the things we're looking at is should we

6	have this 5-minute or 15-minute standard, and yet those

7	data were not -- at least I didn't see them --

8	presented in the ISA.	And then the other document is

9	saying that all this data are available, so we ought to

10	have key data in there to tell us what's the

11	distribution of those data.	How many are above 50,

12	100, you know, PPD and so forth?	So that is a major

13	need, I think, in the first part, but this issue of the

14	interaction with particles, as I note in my comments, I

15	think is an important issue that needs to be brought

16	forth.	I know you want to take sulfates and put them

17	off to the side so it simplifies your life, but the

18	reality is the SO2 is never present without particles.

19	DR. HENDERSON:	Thank you, George.

20	Are there any other?

21	DR. BROWN:	I just have one quick

22	question.	The slide that gives, you know, causal

23	suggestive, and so forth.	What strikes me about that

24	is I don't even know what it meant.	Not that I don't

25	know what causal means or suggestive means.	That slide

1	in that system looks a lot to me like a sort of hazard

2	identification, which I always have trouble with

3	because everything in some level is going to cause an

4	effect.	So I don't know what causal refers to here.

5	Are we to take it that causal means causal at the

6	levels of exposure that we're going to be considering

7	in this deliberation?	Because if it means causal at

8	some level of exposure, well the answer is always yes,

9	yes, yes, yes, yes.

10	DR. COTE:	I'd like to hear from

11	John 'cause I'm going to sit.

12	DR. SAMET:	If you can go back to

13	that slide.

14	DR. COTE:	And one of the things --

15	DR. SAMET:	Let me comment on those

16	because my comments, I think follow on those.	They

17	actually --

18	SPEAKER:	There they are.

19	DR. SAMET:	So just to comment on

20	these, these bear no resemblance to any of the causal

21	classifications in the SES, and let me, let me tell you

22	what's wrong with it.	First you set up a paradigm in

23	which only experiment leads to a causal determination

24	at the top, which is certainly not consistent with

25	thinking in public health in general.	I mean, if you

1	look at some of the evidence classifications, the

2	agency health care quality and research or whatever it

3	is called these days, they pose the experiment of

4	clinical trial as the highest level of evidence, but

5	that is not required for causal inference.	This, for

6	example, would not lead to cigarette smoking be

7	classified as causally associated with anything if I

8	interrupt these criteria correctly.	Second, you used

9	the word strong.	Strong usually refers to the strength

10	of association, the magnitude of the relative risk.	I

11	would not expect "strong" associations for most of the

12	pollutants that we will be considering, so I'm not sure

13	what you mean by strong.	So, again, in epidemiological

14	discussions we often talk about relative risk of 2, 3,

15	4, 5, and so on where alternative explanations to

16	causation can be set aside, confounding and so on.

17	So I don't see that these work, and if

18	you were to go back and read Surgeon General's report

19	2004 where we looked at this very closely, I think you

20	would see that the thinking here is quite discrepant

21	with those who are thinking about causal inference and

22	public health.	So I, I just can't accept this as a

23	starting point here because this should not take on

24	legs.	This is not correct.

25	DR. COTE:	We, I think, John,

1	largely agree with you.	Unfortunately, we didn't

2	realize we agreed with you until after the NOx meeting,

3	and this document had already gone to you.	And we

4	decided in the presentation to keep it consistent with

5	what was said in the document, but the next time you

6	see this it won't, it will be different and more

7	consistent with, I think, some of the reports that

8	you've pointed out.

9	DR. SAMET:	Yeah.	And I'd be happy

10	to give you some general background.	And, in fact, I

11	recently chaired an IOM committee looking at this issue

12	around decision-making for veterans, and there's three

13	excellent chapters in that book on causal inferences in

14	the report that I'll give you reference to.	But I

15	think you really need to come into line with general

16	thinking here.

17	DR. COTE:	I agree, John.	I think

18	that we just, again, when we didn't quite think this

19	through clearly before the first NOx document and then

20	kind of set it in stone for these two drafts.	So our

21	plan is to revisit those, but I'd appreciate those

22	references also.

23	DR. BROWN:	And what was the answer

24	to mine?	Is it causal at anything remotely approaching

25	the levels we're talking about or just causal at some

1	level of exposure?

2	DR. COTE:	John can help me on this

3	because what I want to say is based on things that he

4	suggested that I read, so just in case I didn't

5	interpret it correctly.	But that question was asked at

6	the last meeting, and I gave you a different answer

7	than I think I would give you now.	At the last meeting

8	I said, yes, what we were interested in was a causal at

9	ambient concentrations, and I think that we're moving

10	more toward what I interpreted at least was laid out in

11	a smoking, Surgeon General's report on smoking.	And

12	that's to be what's the evidence that it's causal, and

13	then the, sort of the dose response assessment part is

14	more of an inference or an implication.	I can't

15	remember the term that was used.	And that's a thing to

16	talk about if that's, is that what people think is

17	appropriate that you do.	It's causal.	We know that it

18	causes these effects, and then the, does it cause it at

19	the dose or the ambient exposures are separate kind of

20	discussion.

21	DR. BROWN:	Okay.	I can go with

22	that.	All I would say is that you needn't have spent

23	any time at all answering the question can it cause

24	adverse health effects at some level of exposure

25	because the answer is always yes.	It doesn't matter

1	what the substance is.	It's always yes so.

2	DR. COTE:	That's part of the problem

3	is I think for many of the very wonderful studies that

4	have been, that have grappled with very difficult

5	issues, it wasn't so clear they were causal.	So much

6	of the emphasis was, you know, developed on having a

7	system that sorts out is it causal.	In this particular

8	case if you apply those schema it looks a little bit,

9	you know, it's kind of like, yeah, it's always causal,

10	and then you get down to discussing is it causal at

11	ambient levels.	So that's kind of a quandary for us

12	that I'd certainly like comment on.

13	DR. HENDERSON:	Well, it sounds like,

14	John, you can be a big help to them, and we will see

15	this document again, right, in --

16	DR. COTE:	Yes.	And I also want to

17	thank Dr. Cowling who had also made some good

18	suggestions on, you know, formal documents that use

19	different approaches to these problems that we've also

20	been utilizing.

21	DR. HENDERSON:	So that's, that's

22	great.	That's exactly what we're here for is to help

23	you get the best ISA possible.	So is there any, any

24	other questions before we go on to Dr. Kim?

25	DR. ARNOLD:	Rogene, if I could just,

1	if I could respond to a point, respond to a point

2	raised by George and then earlier by Frank about the

3	five-minute data and that is that until the, until the

4	new request from the Office of Air had gone out, states

5	were not, and they are still not required to report

6	five-minute data.	And so what this results in is a

7	very poor distribution of monitors that were reporting

8	five-minute data across the country, and it is not

9	actually even across the county as I'm sure you can

10	imagine.	In having looked at the information that went

11	up through the year 2000, there are a very small number

12	of monitors reporting a very small number of

13	observations.	And in those data, the very high

14	concentrations, concentrations greater than 600 PPB

15	were less than .05% even at this, from a very small

16	number of monitors.	What we are working with now in

17	the Office of Air and analysis is going on now and this

18	gets to Frank's question about whether any of this has

19	been published yet.	We're still working on an analysis

20	of the additional information that has been collected

21	since 2000, so that's why that doesn't appear in this

22	version of the ISA.

23	DR. THURSTON:	Can that make it in

24	here?

25	DR. ARNOLD:	To the extent that we

1	can include information that is produced in time for

2	the second draft, sure.

3	DR. HENDERSON:	Okay.	Dr. Kim,

4	you want to -- oh, wait a second.	No.	There's a

5	question.	I'm sorry.

6	DR. SPEIZER:	I just wanted to sort

7	of add a note of completion.	There's another mechanism

8	for exposure of the lung and that is by the absorption

9	of SO2 in the nose, and it actually gets excreted in

10	the lung.	So I think you have to sort of keep in mind

11	that it isn't just a matter of it all being absorbed

12	and goes away.	It's still there and it may very well

13	have its effect through a different kind of mechanism.

14	DR. HENDERSON:	Okay.	Ellis has a

15	point..

16	DR. COWLING:	As a supplement to what

17	George Thurston said a moment ago about the time frame

18	for publication, one of the things that CASAC has been

19	trying to emphasize is it is not just new evidence but

20	new insights about old evidence that we ought to be

21	giving attention to.	The other thing that I'd like to

22	mention has to do with the issue of -- oh, I've

23	forgotten what I wanted to say.	I must apologize to

24	the chair.	I will come back as soon as my memory is --

25	DR. HENDERSON:	Ellis, you just

1	feel free to bring it up whenever it pops up.	I'm very

2	sympathetic to that.

3	SPEAKER:	We all are.

4	DR. HENDERSON:	Okay.	Pending no

5	other questions, we'll move on to Dr. Kim.

6	DR. KIM:	Hi.	I'm Jee Young Kim and

7	I'm an epidemiologist at NCEA.	One thing I do want to

8	clarify before we went into the epi evidence --

9	actually, could you go to the next slide, please.	In

10	epi when we refer to strength, what we were talking

11	about was rather weight of evidence versus the strength

12	of effect.	So when I use the word strong, I'm meaning

13	that there was, you know, there was a lot of evidence

14	that was available that supported the conclusion that

15	we're making.

16	So I'll be presenting an overview of the

17	epidemiological evidence on SO2 health effects,

18	starting with respiratory effects with short-term

19	exposure, which in this case is generally a 24-hour

20	average.	The strongest evidence of SO2 effects in

21	epidemiology comes from the panel studies examining the

22	association between short-term exposure to SO2 and

23	increased respiratory symptoms in children.	As you can

24	see in this floor plot, with exception of that one

25	study at the bottom -- I don't have a laser thing-- at

1	the bottom by Romeo, et al, all the studies are

2	positive, and in several cases statistically

3	significant.	The two recent multi city studies are

4	Mortimer, et al., which is on the top of the figure and

5	Schildcrout, et al. near the bottom of the figure.	And

6	both of these found positive statistically significant

7	associations at the multi day lag.	Oh, thank you.

8	Yeah.	So that's Schildcrout and that's

9	Mortimer right there, and these studies did some

10	analyses or some examination of the co-pollutant

11	issue, and in multi-pollutant models of Mortimer, et al

12	they found that SO2 effect estimate was robust to

13	adjustment for PM-10, NO2 and ozone.	In the case of

14	Schildcrout, they did a combination of pollutants and

15	found that the SO2 effect was indeed most evident when

16	considered in combination with NO2 and carbon monoxide.

17	The Schwartz et al study, which is right here, is an

18	older study, the Harvard Six City study done in 1994,

19	published in 1994, and in this study, once again, there

20	was a positive significant effect that was observed.

21	But in a two pollutant model with PM-10 they found that

22	the effect estimate decreased considerably.	The one

23	thing to note about this was that the PM-10

24	concentrations were very correlated, highly correlated

25	with sulfate particles.	I believe the correlation

1	coefficient was 0.8, and in this case adjusting for PM-

2	10 may have resulted in over-adjustment in the model.

3	So moving onto the next slide, this is a

4	figure depicting studies of all respiratory and asthma

5	hospitalizations and ED visits with co-pollutant

6	adjustment.	Note that these are not all the studies

7	that looked at this association but simply the ones

8	that also presented results on multi-pollutant models.

9	You can see that in some of the studies with these wide

10	confidence intervals, the effect estimate does decrease

11	significantly when adjusting for co-pollutants and in

12	some cases becomes negative, but the other thing to

13	note about these studies is that the Yang, et al.,

14	Llorca, et al and Lin, et al studies for example, they

15	adjusted for four different co-pollutants.	And in the

16	case where these co-pollutants are probably moderately

17	to highly correlated with , this may have not been the

18	best way to examine co-pollutant interactions or

19	compounding by co-pollutants rather.	So, therefore, we

20	focus on the study that had one additional pollutant

21	added into the model and also the ones with tighter

22	confidence intervals, which give us some indication of

23	study power.	For example, in this study by Schwartz

24	here on the top, adjustment for PM-10 did not

25	appreciably affect the effect estimate in New Haven,

1	though it did decrease it in Tacoma where the SO2

2	concentrations are lower.	In Sunyer et al and Anderson

3	et al once again you'll see that the effect estimates

4	did not appreciably change with adjustment for black

5	smoke and NO2.

6	So from this we concluded that the

7	studies with tight confidence intervals, adjusting for

8	one additional pollutant, that generally the effect of

9	SO2 on respiratory health hospitalizations did not, was

10	not, I'm sorry, were generally robust and independent

11	of effects of other co-pollutants.	Next side, please.

12	So many new epidemiological studies

13	supported by evidence from animal tox studies as well

14	as some of the clinical studies provided evidence of a

15	relationship between short-term exposure to SO2 and

16	respiratory health effects ranging from respiratory

17	symptoms and increasing in severity to ED visits and

18	hospitalizations for respiratory causes.	Associations

19	were observed between ambient SO2 concentrations and

20	increased respiratory symptoms in children,

21	particularly among those with asthma or chronic

22	respiratory symptoms.	The recent US multi city studies

23	along with several other single city studies observed

24	these associations at ambient concentrations that are

25	below the current 24-hour average NAAQS, which is 0.14

1	PPM or 140 PPB.

2	One interesting thing to note was that

3	the Harvard Six City study done by Schwartz et al

4	examined the concentration response function of the

5	relationship and observed that no significant increase,

6	and that's a statistically significant increase was

7	observed in the instance of lower respiratory symptoms

8	and	until	you reach 22 PPB, which was around just

9	about the 90th percentile of the distribution of the

10	data that they have for SO2.	And this perhaps suggests

11	that the associations are maybe led by the higher or

12	peak year concentrations in the distribution.	Positive

13	but not always statistically significant associations

14	were observed between ambient SO2 concentrations and ED

15	visits and hospitalizations for all respiratory causes.

16	And these associations were particularly examined and

17	observed in children and older adults.	So from the

18	available evidence that we have, we conclude that there

19	is a likely causal association between short-term

20	exposure to SO2 and respiratory effect.	Yes, Dr.

21	Speizer?

22	DR. SPEIZER:	Yeah.	I'd like to raise

23	an issue, which will come up later again I'm sure, and

24	it has to do with how we look at these data. For the

25	last 50 years there have been studies on SO2, and in

1	probably virtually almost every one of those studies,

2	and this was mentioned earlier, there's a small segment

3	of the population, maybe 10, maybe 20, maybe up to 30

4	or 40% of the population that clearly have significant

5	positive effects.	When you put this in a population-

6	based estimate, often it is null because the dominant

7	population don't have response.	Now it's our ignorance

8	as to what makes these people more vulnerable to , but

9	I think we have to start to think about, but this has

10	sort of been shown over, and over, and over again.	And

11	to ignore it essentially by looking at the mean

12	response of the groups is to really deny the science

13	that we know.	We know that there's an effect there.

14	Now I'm not blaming you guys because that's the way

15	it's always been done, but I think we have to start

16	thinking about different ways of looking at this.	I

17	think we're just sort of sticking our heads in the sand

18	to say that these results are in general null when we

19	know that there are sub-segments of the population

20	which we can't, sometimes we can identify, but most

21	often we can't identify who they are, who are

22	responding and perhaps responding to a very significant

23	adverse effect.	How we're going to deal with this?	I

24	put it on the table because I think we need to discuss

25	it.	I'm not sure I have the answer as to how we're

1	going to deal with it, but I think it is an issue.	I

2	think it really is an issue that we have to deal with.

3	DR. KIM:	Yes.	We certainly agree

4	that there is a wide distribution of individual

5	variability and how we can use that with epi studies

6	I'm not so sure given the current database that we

7	have.	I guess some epi studies do focus on the more

8	susceptible populations such as asthmatic children, but

9	once again it's hard to keep, they don't provide

10	individual results obviously in these papers.	The best

11	data we have is from the human clinical studies

12	examining this, and, of course, those studies don't

13	examine the most susceptible populations anyway.	But

14	we'll consider your comment.

15	DR. BALMES:	This is John Balmes.

16	DR. KIM:	Yes.

17	DR. BALMES:	I would just say that I

18	appreciate the general concern that was brought up

19	about susceptible populations being sort of under, the

20	impact on susceptible populations being under-

21	appreciated, underestimated from the epi studies that

22	focus on the entire population, but I think with	we

23	actually have a better handle than perhaps with ozone

24	or NO2.	Who is most susceptible in that the clinical,

25	the human clinical studies I think clearly identify

1	that asthmatics are much more susceptible than normal

2	individuals.	So I think we're on very strong ground

3	when we say that asthmatics are a susceptible

4	population with regard to SO2 exposure.

5	DR. HENDERSON:	Thank you, John.

6	Are there any others?	I see a hand, George.

7	DR. THURSTON:	I just wanted to pick

8	up on the remark that Dr. Kim made about the multi-

9	pollutant models.	And, you know, I don't know if you

10	want to flip back to that slide, but a lot of them

11	included are what I would call a kitchen sink model.

12	They've thrown in everything but the kitchen sink, and

13	I don't really find those models meaningful because of

14	all the -- and even, you know, in the other document, I

15	quoted him in my comments that they say, "When co-

16	linearity exists," which of course it does, "inclusion

17	of multiple pollutants in models often produces

18	unstable and statistically insignificant effect as to

19	both SO2 and the co-pollutants.	So I don't, I

20	personally feel we shouldn't be showing these.	I think

21	the most you should want to put up there is that there

22	are two pollutants in a model and then look how they

23	co-value, and those should be sensitivity analyses.

24	But, you know, just because somebody publishes these

25	things doesn't mean it's meaningful or that that's what

1	you should present.	And I've run into this in the

2	past.	I wrote sections and I actually remember one

3	time Rick Burnett got on my case because he said, "Well

4	wait a second those aren't, what you have there are not

5	my conclusions from my study, and those are not all of

6	my results."	And I said, "That's right.	Those are my

7	conclusions from your study, not yours because I

8	ignored the kitchen sink models, and so it came up with

9	very different conclusions.	And that's not always

10	going to be the case, but I just think when you put a

11	lot of pollutants in there that are correlated with

12	each other oftentimes what comes out is the one

13	pollutant that is not as correlated with the other

14	pollutants; but that doesn't mean it's causal that's

15	driving the associations.	It really is not very

16	informative, so I'm not sure you should even -- I think

17	you should exclude them.

18	DR. HENDERSON:	Pat Kinney.

19	DR. KINNEY:	I would tend to disagree

20	with that, but I wanted to talk about this table also.

21	I think at least in the way the ISA is currently

22	written, I didn't, I didn't see a very good argument

23	made for this, the conclusion about general robustness

24	that you stated, although I think the way you just

25	explained it gave more detail than I saw in the

1	document.	There is some nuance about studies with

2	tight confidence intervals and studies that, you know,

3	at higher concentrations, you know, that sort of help

4	build that argument.	But, you know, when I just looked

5	at this figure and then I saw the conclusion about

6	general robustness and then, the way that got carried

7	through the entire document and then into the risk

8	assessment document as well, I just thought it really

9	needed to be pinned down much more clearly in the ISA.

10	And, you know, based on this figure, I'm still not

11	convinced that I would say there is general robustness,

12	you know, in spite of what George has said, which is a

13	good point; but I think the central question is really

14	to what extent are these results, these effects we're

15	seeing really due to SO2 as opposed to the mix of

16	pollutants, and can we even say anything about that.

17	I'm not sure that we can, but it's results like this

18	that are the only thing we can look at to help us think

19	about that.

20	DR. HENDERSON:	Yes.	And I agree

21	in this one, I, George would disagree that these

22	shouldn't be presented because I think they are

23	informant about where we are.

24	DR. KIM:	Well, I guess I did want

25	because there's sort of a disagreement here about what

1	is appropriate for multi models in terms of the number

2	of adjustments.	Can we have a little bit more

3	discussion about that to sort of guide us through.

4	Okay.	I was just told that we should probably do this

5	when we discuss Chapter 3 so.

6	DR. HENDERSON:	Well Jon Samet has

7	something to say.

8	DR. SAMET:	Well, I'll comment.	I'll

9	comment here later.	I think this comes out of the crux

10	of interpreting this.	I think the other issue that has

11	to be put on the table is publication bias and how to

12	interpret it because, again, I think statistically

13	significant associations in these sort of multi variant

14	model data are far more	likely to appear than non-

15	significant associations and that issue has to be dealt

16	with.	I think we need a pretty lengthy probably

17	discussion of how to interpret these.	Either, George,

18	either the univariant, bi-variant, or multivariant

19	models in the face of some of the real problems in

20	measurement error and everything else.	And I don't

21	know that this is the time to have that discussion, but

22	I think it should come up when we come on to Chapter 3

23	discussion and in Chapter 5.	The other just passing

24	comment, I won't let you get away with saying weight of

25	evidence and strength are equivalent, and I've never

1	known what weight of evidence means.	EPA people staff

2	love to use that term, and every now and then I do it;

3	and then I saw well like what does that really mean,

4	and if it's a couple of studies out of an infinite

5	universe of epidemiological studies showing

6	statistically significant associations, it's probably

7	not, I guess, a heavy body of evidence; is that the

8	counterpart of weight of evidence?	So be careful.

9	DR. HENDERSON:	Okay.	I thank

10	you, Jon, and I think now we should move on.	Jon has

11	pointed out that we can discuss this at greater lengths

12	later on as the, as we go through the different

13	chapters.	So we'll let you, Dr. Kim, finish your -- or

14	you --

15	DR. KIM:	A couple of findings, one

16	more, please.

17	DR. HENDERSON:	Okay.

18	DR. KIM:	So now the evidence on the

19	effect of short-term exposure of SO2 on cardiovascular

20	morbidity and mortality will be discussed.	Here the

21	effect of SO2 on cardiovascular morbidity is generally

22	inconclusive in both epi studies and human clinical

23	studies.	Some positive associations were indeed

24	observed in the studies of ED visits and

25	hospitalizations. There is a lack of supportive data

1	from panel studies and human clinical studies on

2	preclinical cardiovascular health effects that provide

3	biological plausibility for these absurd associations.

4	For the effect of	short-term exposure

5	to	mortality, we conclude that there is suggestive

6	evidence from epidemiological studies, and this is

7	because several studies observed positive associations

8	in US and Canadian multi city studies.	And probably

9	the one thing to note was that in multi-pollutant

10	models, once again the best evidence we have for, to

11	consider confounding, these effect estimates did tend

12	to decrease.	So the SO2 effect estimates did decrease

13	but in many cases remained positive and in some cases

14	remained statistically significant.	There is also an

15	intervention study from Hong Kong that provides

16	supportive evidence of a reduction in SO2 levels,

17	linking the reduction in	levels with a reduction in

18	deaths.	However, one thing that we should note is that

19	this does not preclude the possibility that it's not

20	per se but something that's emitted along with SO2 such

21	as vanadium or nickel that may be causing these

22	reductions.	Next slide, please.

23	Evidence of health effects from long-

24	term exposure to SO2 are generally inconclusive.	For

25	respiratory morbidity, effects of long-term exposure on

1	respiratory symptoms and lung function were assessed in

2	epidemiologic studies.	While some of these studies did

3	observe positive associations for respiratory symptoms

4	in particular, the general overall evidence-base was

5	inconsistent and the results were mixed.	There was

6	limited animal toxicology studies that cannot fully

7	provide strong biological plausibility.

8	There are two recent epidemiologic

9	studies that observed the association between long-term

10	exposure to SO2 and instance of cancer, and both

11	provided no evidence of an increased risk.	Their

12	animal studies also did not find that SO2 was a

13	carcinogen by itself, but there was some limited

14	evidence of cool carcinogenicity at high

15	concentrations.

16	For adverse birth outcomes, there was

17	some positive associations between SO2 and low birth

18	weight.	However, the results were inconsistent across

19	trimesters of pregnancy, and also most of these studies

20	did not adjust for important potential confounders such

21	as maternal smoking and socioeconomic status.

22	And finally, results from two major US

23	epidemiological studies observed positive and

24	statistically significant associations between long-

25	term exposure to SO2 and mortality, and those were the

1	Harvard Six City study and the American Cancer Society

2	study.	However, several other US and European studies

3	did not observe this association.	So these

4	inconsistent associations and the difficulty and

5	challenge of distinguishing effects by other co-

6	pollutants limit the interpretation of us to state a

7	causal association.	Next slide, please.

8	So these are charge questions 7 and 8,

9	and these deal with the public health impact and

10	adequacy of the ISA to provide support for future risk

11	exposure and policy effectiveness.	Last slide, please.

12	Epidemiological and human clinical studies have

13	evaluated potentially susceptible and vulnerable

14	populations and observed that subjects with respiratory

15	illness, most namely asthma are more susceptible to

16	induced respiratory health effects compared to the

17	general population.	Additional epi evidence also

18	suggests that children and older adults, that's

19	individuals who are 65 years or older, are more

20	susceptible and potentially vulnerable to respiratory

21	health effects from SO2 exposure.	The panel studies

22	found the SO2 concentrations were associated with

23	respiratory symptoms in children but not in adults.	In

24	the ED visits and hospitalizations studies observed

25	slightly larger effect estimates for children and older

1	adults compared to the general adults.	There was one

2	study that specifically examined variability by genetic

3	polymorphisms and found the greater response to SO2 was

4	associated with the homozygous wild type allele for TNF

5	Alpha, and this is in asthmatics.	However, the

6	available evidence is much, much too limited to make

7	any conclusive statements at this time regarding

8	genetic variability of SO2 effects.	And that was the

9	last slide.	If you have any quick questions, we'll

10	take them.

11	DR. HENDERSON:	We'll be

12	discussing this in detail later.	Yeah.	Dale, you

13	wanted to say something?

14	DR. HATTIS:	Yeah.	I am just

15	wondering whether you perhaps would plan in there in

16	the next draft of the ISA to have a more general

17	discussion of the strengths and weaknesses of multi-

18	pollutant epidemiological controls because it seems to

19	me that there might be a variability among the panel in

20	the strength of belief of the efficacy of statistical

21	adjustment for confounders in these multi-pollutant

22	analyses.	It seems to me some serious effort would be

23	warranted to discuss that issue as a general matter.

24	DR. KIM:	Yeah.	What we did for the,

25	both the NOx and the SOx ISA was refer heavily back to

1	the PM and the ozone documents where this was discussed

2	in much greater detail.	What we could do is sort of

3	pull out the salient points and perhaps put it either

4	into the ISA or the annex to those documents.

5	DR. BALMES:	This is a small point from

6	John Balmes, but I can't let it go by.	If you turn to

7	slide two, the list of expert authors, my colleague at

8	UC Berkeley, Kathleen Mortimer is identified as being

9	from Yale.	She got her Ph.D. from Harvard and I think,

10	you know, it would be nice to show where she actually

11	is from.	But she is currently at University of

12	California Berkeley.

13	DR. HENDERSON:	Okay.	So with

14	that I think we will, I offer my thanks to all of you

15	for making this presentation and very clear

16	presentations that's got the discussion going well.

17	We'll be talking with you throughout the day, but I

18	think now we move onto what Holly handles and that is

19	public comment.

20	DR. STALLWORTH:	Hi.	Do we have Howard

21	Feldman on the line?

22	DR. FELDMAN:	Yes.	I'm here.	Thank

23	you.

24	DR. STALLWORTH:	Okay, Howard.	You

25	have five minutes.	Howard is with the American

1	Petroleum Institute and his comments have been passed

2	out.

3	DR. FELDMAN:	Well, thank you very

4	much.	Good morning everyone.	Thank you, Dr.

5	Henderson, for allowing me to call in.	You know, we

6	have a dusting of snow here in Washington, so

7	everything is gridlocked here already.	So I'm Howard

8	Feldman.	I'm with the American Petroleum Institute and

9	API has over 400, nearly 400 member companies involved

10	in the oil and gas industry, and we'd like to thank for

11	the opportunity, for having this opportunity to comment

12	on the SOx ISA.	In conclusion right away, API

13	concludes that the significant revision of the SOx ISA

14	is necessary.	Based on the science we see presented

15	there, we don't find that this version conveys the

16	information that's useful to the Administrator to

17	evaluate the possible need to alter thes form or the

18	level of the SO2 NAAQS.	But we have already put in

19	comments to the docket which go into detail on this.

20	In summary, we find that the SOx ISA inaccurately

21	concludes that SO2 measurements from the ambient

22	monitors of good surrogates were measurement of

23	personal SO2 exposure, so that's going to confound

24	everything.	Since the ISA relies on epidemiological

25	studies to infer health effect, those studies that rely

1	on data from ambient monitors are going to lead to a

2	questionable determination of health effects.	So API

3	finds that the ISA inaccurately characterizes the epi

4	evidence as suggesting that the levels below the

5	current standards cause increased respiratory symptoms,

6	increased ED visits, and hospital admissions, and acute

7	mortality.

8	So in the time I have available today

9	I'm going to focus on two points.	First the

10	overarching finding that API does not believe that ISA

11	accurately reflects the full body of the latest

12	science, and second I'm going to discuss why the

13	available information in the ISA does not indicate that

14	SO2 measurements from ambient monitors are good

15	surrogates for measurement of personal SO2.

16	So first of all we know that under the

17	Clear Air Act the SOx ISA must "accurately reflect the

18	latest scientific knowledge useful in indicating the

19	kind and extent of all identifiable effects on public

20	health, which may be expected from the presence of SOx

21	in the ambient air in varying quantities.	So in other

22	words, the science has to be accurate.	Furthermore,

23	the SOx ISA must include the recent information that

24	will be useful to the administrator.	To do that the

25	SOx ISA must clearly set forth the criteria that led to

1	the selection of particular studies for emphasis, and

2	those criteria must be applied consistently.	And this

3	touches on, a little bit touches on, John just

4	mentioned a little while ago a publication vies.

5	That's one place where you can see some of this playing

6	out as well.	The failure of the present draft of the

7	SOx ISA to this rate is questioned about the document's

8	usefulness.	To be useful, the SOx ISA must present an

9	unbiased evaluation of the evidence.	And we talked

10	about, a little bit, you guys were just mentioning

11	through, what are the criteria?	How do you evaluate

12	things objectively?	CASAC member Douglas Crawford-

13	Brown, made the point recently when we were dealing

14	with the NOx health criteria, he said, and we're going

15	to quote this just for emphasis again, "The chapter

16	follows an EPA tendency to present the evidence as a

17	form of building a legal case in which evidence or a

18	belief is what matters most.	Throughout the chapter

19	and throughout the report there is a focus on the

20	studies that is suggestive of an adverse effect.	With

21	the conflicting studies providing a kind of

22	counterevidence that lowered the judgment from likely

23	causal down to suggestive or down to inconclusive.

24	What is needed instead is a methodology that examines

25	all studies, supportive and counter-supportive, ways of

1	findings systematically by trying to determine why

2	there are conflicting results and then yield a final

3	judgment of causality that reflects this full range."

4	And we think that was very well captured there, and we

5	do appreciate that.	Unfortunately in the SOx ISA, as

6	it's presently drafted, it doesn't meet these

7	standards.	It's scientifically inaccurate and biased

8	in several ways, and, therefore, will not be useable to

9	the administrator without substantial revision.

10	Moving on to foundation of the findings

11	on health impacts from the cited epi studies rests on

12	the assumption that SO2 measurements from ambient

13	monitors are good surrogates for measurements of

14	personal SO2, and API does not find that the ISA

15	provides evidence to support this assumption.	Yet the

16	SOx ISA relies on two long-term cohort studies to state

17	that their reasonably strong associations, okay.	This

18	conclusion is based on a 20-year-old study by Brower,

19	and in a series of more recent studies by Sonnet et al.

20	The studies do not, however, support the SOx ISA

21	conclusion.	The more recent Sonnet et al studies are

22	the most relevant as they involve SO2 ambient exposures

23	more typically found today.	Sonnet et al explains to

24	take care of the no exposure studies showing the

25	ambient SO2 to be a suitable surrogate for personal SO2

1	exposures.	Indeed as EPA recognized in a recently

2	completed NAAQS for PM, okay, the ambient SO2 exposures

3	are poorly, poorly correlated.	Ambient and personal

4	SO2 exposures are poorly correlated. Quoting, "Ambient

5	gases pollutant concentrations including SO2 are not

6	correlated with their corresponding personal exposure

7	concentrations; however, ambient gases concentrations

8	were found to be strongly associated with personal PM

9	2.5 exposures suggesting that ambient gaseous

10	concentrations of ozone, NO2 and SO2 are acting as

11	surrogates as opposed to confounders of PM 2.5 in

12	estimating PM health effects.	This is a very big

13	question this is going to touch on.	We've already

14	touched on multi-pollutant models and how those are

15	going to play through and how those need to be looked

16	at, and how you look at these data and these compounds

17	that are correlated and take them apart and find out

18	what's causing the effect and what's not is critical.

19	While API may question EPA's conclusion in the PM NAAQS

20	review that SO2 was acting as a surrogate with PM 2.5

21	multi-pollutant modeling, it is scientifically

22	incorrect for EPA to reach contrary interpretations of

23	the Sonnet et al study from the PM assessment to the

24	SO2 assessment.	This leads to the misstep of

25	attributing to SO2 exposures effects that the agency

1	has already previously attributed to PM 2.5.	So the

2	SOx ISA should be revised to be consistent with EPA's

3	finding when it reviewed the PM NAAQS that ambient SO2

4	concentrations correlate poorly with personal

5	exposures.	Moreover, the SOx ISA should acknowledge

6	that ambient SO2 measurements are a poor surrogate for

7	personal SO2 exposure in observational epi studies.

8	The time does not allow me to discuss in

9	detail other findings of API's review of the ISA.	Our

10	comments discussed is the SOx ISA inaccurately

11	concludes that there's suggestive evidence of

12	association between ambient SO2 levels and the ED

13	visits and hospitalizations for respiratory causes,

14	inaccurately characterizes the epi evidence as

15	suggestive of association between short-term exposures

16	to SO2 and premature mortality, and inaccurately

17	concludes that new epi studies provide evidence of an

18	association between short-term SO2 and respiratory

19	symptoms.	As a copy of our comments with cited

20	reference are provided with the testimony, I thank you

21	for your consideration.	I'm happy to take any

22	questions that you may have.

23	DR. HENDERSON:	Thank you.	Are

24	there questions?	Okay. Well, thank you very much, and

25	that will end our public comment period unless Holly

1	knows of anybody else.	Nope, nobody else.	I think

2	it's a good time to take a break, a 15-minute break.

3	So if you could come back about five minutes after

4	10:00, I'd appreciate it, and we'll start our

5	discussion of the individual chapters.

6	DR. FELDMAN:	And Regina, may I say

7	that I probably could have gotten a lot more than $53

8	an hour by just going right to API and written my

9	comments directly.

10	DR. HENDERSON:	It's okay.

11	(WHEREUPON, a break was taken.)

12	DR. STALLWORTH: Could everyone take a

13	seat?

14	DR. HENDERSON: We are going to be

15	getting together again, so please take your seats if

16	you will.	Thank you.	We're going to start our

17	discussions by receiving comments from the panel on

18	Chapter 2, which includes responses to charge questions

19	1 through 3, and Christian Seigneur is our first lead

20	discussant.	Christian, are you about -- I want to

21	emphasize, the people who are listed here will make

22	their points, but then it will be open for comments

23	from the whole panel.	So anyone on the panel who wants

24	to make comments on Chapter 2, feel free to do so.

25	DR. SEIGNEUR: Okay.	I'll start with my

1	comments on the ISA.	The first point I want to make is

2	that I got it to be confusing within the ISA.	It

3	starts in Chapter 1 by saying that all oxides are being

4	advised, which would include of course SO2 and sulfate.

5	And then when reading the documents at some point

6	emphasis was on SO2 and after that point then emphasis

7	was on sulfate.	So I felt there was a lack of balance.

8	So I'm not sure whether it should say in Chapter 1 that

9	the emphasis will be on SO2 because sulfate is

10	otherwise somewhere else as PM, or if not, if the

11	emphasis is really on both SO2 and sulfate, then

12	throughout the document, both compounds should be

13	advised.	Examples of sulfate not being advised is

14	point source emissions.	The emissions focus on SO2.

15	The fraction of the emissions which is sulfate is not

16	mentioned in the text, so this could be added.	You

17	know, how much of power plant SOx emissions is sulfate.

18	I think it's a small amount, maybe one person thought

19	so.	For ship emissions, which is becoming a bigger

20	deal, how much is ship emissions for instance.	The

21	preceding relevant background is advised, SO2 I didn't

22	see a value for sulfate for instance.	Another example

23	where the emphasis is on sulfate instead of SO2 is the

24	modeling.	You talk about threshold modeling which

25	would apply to SO2 conversion to sulfate at regional

1	scales, which is sort of applied to regional haze, and

2	PM 2.5.	I didn't see any descriptions of the modeling

3	for SO2 because there we are interested in SO2

4	concentrations near the source, and tomorrow we'll talk

5	about the assessment, which is going to be based on

6	AERMOD.	So I would augment the exclusions	for

7	dispersion models, which has AERMOD in the appendix.

8	So that would bring some better balance.

9	Then getting into more detailed

10	questions about the charge questions 1 through 3, which

11	is for Chapter 2.	One major revision I would like to

12	see is the descriptions of why sulfate is not in the

13	gas phase.	A statement was made that sulfuric acid is

14	water soluble and that's the reason why we find it in

15	droplets and particles.	That is true for droplets.

16	The reason we find it in particles is not because it is

17	water soluble but because it has a low, very low

18	saturation rate for pressure.	Otherwise, we would find

19	nitric acid in particles as well, and we know that we

20	only find nitrates when we have ammonia in nitric acid.

21	So that's a correction which needs to be made.

22	In Chapter 2 there is emphasis of course

23	on the coal-fired power plant source category because

24	it is the largest category right now for SO2 emissions.

25	I think it would be good to mention that this is a

1	source category which is being controlled, not too much

2	for SO2 but for acid depositions, PM 2.5, regional

3	haze, and therefore those emissions are decreasing.	As

4	this is happening other source categories may become

5	more important, and Rogene this morning mentioned ship

6	emissions.	And I think that there should be a better

7	descriptions of ship emissions in the document.

8	Obviously there are uncertainties associated with

9	those, as was mentioned this morning by EPA, but we can

10	less those uncertainties.	I think that should be

11	brought up as a source category of interest.

12	Related to that, I assume that the

13	citing of the SO2 monitors has been based historically

14	on trying to characterize the impact of the major

15	source categories, which probably was power plants.

16	But as now we may refocus on other source categories

17	such as ship emissions.	The question comes up whether

18	the monitoring network needs to be reevaluated in terms

19	of the citing of at least some of those monitors trying

20	to find out what that shows the SO2 concentrations are

21	next to those, either the harbors or the ship channels.

22	There is a need, I think, to increase the descriptions

23	of the SO2 chemistry as it is related to the power

24	plant plumes, seeing as power plants are listed as a

25	major category.	There is a single sentence which gave

1	a range of oxidation rates for SO2 to sulfate, which I

2	think is something like, you know, half to two person,

3	which I think is too simplistic, mainly because the

4	chemistry of SO2 in power plants is evolved throughout

5	the history of the plume.	Near the stack there would

6	be no sulfate formation, mainly because you don't have

7	any oxidant in the plume.	Nitrate oxide has eliminated

8	all the oxidants.	Then as the plume gets dispersed you

9	start to build up the oxidants very slowly, and then

10	you start to have a sort of reaction to sulfate.	And

11	then found downwind in rural area, you have higher NOx

12	in the plume than in the background then your SO2

13	oxidation to sulfate would be faster than it is in the

14	background.	So I think this needs to be pointed out.

15	Most of that description, of course, should go to the

16	annex or to the appendix, but since you are focusing on

17	power plants as one source category needing SO2, I

18	think there is a need for more description there.	I

19	was to be surprised when I got into the annex that the

20	description started with NOx chemistry, and I was

21	wondering actually whether we need to have NOx

22	chemistry in the ISA.	We have another document for

23	that.	Maybe we can just refer to that and then only

24	keep this document focusing on the SOx chemistry,

25	especially since we're trying to keep those documents

1	tight that maybe one good thing to do.

2	And as I mentioned earlier, I think we

3	need to have descriptions of AERMOD in this ISA because

4	it is the model you would be using when you, OAQPS

5	would be using for the methods assessment.	Those are

6	my main points.

7	DR. HENDERSON: Thank you very much,

8	Christian.	Do you have any questions for Christian, or

9	is it clear what he's saying?

10	DR.	LARSON:	I think it's clear, and

11	we appreciate those comments.	And we'll certainly

12	include them in the next draft.	Thanks very much.

13	DR. MACIOROWSKI: Sure.

14	DR. HENDERSON: Okay.	We have Tim Larson

15	next.	Are you on the phone?

16	DR. LARSON: Yes, I am.

17	DR. HENDERSON: Okay.	You have the

18	floor.	DR. LARSON: Thank you.	I will

19	just take the charge, the three charge questions in

20	sequence here.	I think the air quality

21	characterizations are clearly communicated with respect

22	to charge question one.	Again, following up on

23	Christian's comments, the preponderance of below

24	detection limit values and regulatory observations,

25	because of that it is difficult to get an accurate

1	picture of the actual concentrations in most urban

2	areas.	We know that at those monitoring sites it is

3	fairly low.	However, the spatial variability is a bit

4	of a problem because we've only got 12 metropolitan

5	statistical areas with four or more monitors, and some

6	of those are located near industrial sources.	I

7	contrast this with the SAVIAH study by Pikhart where

8	the passive samplers were deployed at over 100 cites to

9	estimate spatial variation at one location.

10	And there's a large discussion about

11	better measurement methods.	I think that's a good

12	thing.	It is not clear, however, that the focus of the

13	analysis should be on a broad regional characterization

14	because I think a lot of the levels will be very low.

15	It might be useful to focus just on areas with

16	relatively high SO2 such as pointed out in the map

17	earlier and perhaps do a more thorough air quality

18	characterization in those areas in a more limited

19	geographical region.	From an epidemiological

20	perspective, the relevant co-pollutants may be

21	different in these higher SO2 regions than in the

22	country at large or in the European and Asian cities

23	where adverse health associations are claimed.

24	I guess the second question on sulfur

25	oxides and human exposure, picking up on previous

1	comments.	I think there's a statement on page 237 that

2	says, "When personal exposure concentrations are above

3	detection limits, a reasonably strong association is

4	observed between personal exposures and ambient

5	concentrations," but this statement is essentially

6	repeated in the conclusion Chapter 5.13, and as best I

7	can tell it is based primarily on the results of Mike

8	Brower's 1989 study.	While this might be a perfectly

9	good study, it was done in one city over two seasons,

10	and it's a very important generalization, but the other

11	studies don't seem to support that, support that same

12	statement as best I can tell.	So if it's true that

13	it's based on that one Brower study, the claim of the

14	linearity, and they're some high associations, I think

15	that ought to be clear because I think right now you're

16	left with the impression that it's based on all those

17	studies.

18	I would say from an epidemiological

19	perspective, the current ambient levels are very low

20	and also poorly mentioned because they're below

21	detection limit in most locations.	I suppose from one

22	sense that's good news, but it makes epidemiology

23	difficult.	There is also insufficient information to

24	predict personal exposure levels from these low ambient

25	levels measured at most community monitors.	I think

1	you're really left perhaps with the pathological

2	perspective based on a limited number of locations and

3	short-term effects at the high end of the concentration

4	distribution, and that's why I say basically that more

5	emphasis perhaps should be focused on the air quality

6	characterization in those regions to compare and

7	contrast the other studies.	Those are my comments.

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

9	Any questions for Tim from NCEA?

10	DR. ARNOLD: Just a quick point of

11	clarification on Tim's point about the strong

12	association being based on Brower '89.	Tim, if you

13	flip back to the slide we presented this morning, we've

14	actually, in the time since we distributed the draft,

15	ISA, we've taken out the word "strong positive

16	association" there and just left that as an

17	association.

18	DR. LARSON: Okay.

19	DR. ARNOLD: It is in fact, as we cite in

20	that slide, Brower, but there is also the second study,

21	the Sarnet study in 2006, which we refer to in the ISA.

22	DR. HENDERSON: Okay.

23	DR. ARNOLD: We take that point and have

24	de-emphasized our conclusion and we'll reflect that in

25	the second draft.

1	DR. HENDERSON: Thank you.	Donna?

2	DR. KENSKI: Yeah.	Greetings, Rogene.

3	First off I guess I'd just like to --

4	DR. HENDERSON: You need to get close to

5	your mic.

6	DR. KENSKI: Oh, okay.	First off I'd

7	like to congratulate the team because I thought this

8	document was in a lot better shape overall than NOx ISA

9	that we finished a month ago, so I think it's showing

10	some real progress.

11	With respect to the specific charge

12	questions in this category, I thought they did an

13	adequate job with the chemistry, but the description of

14	the air quality data I think could be improved

15	somewhat.	It does a nice job using the CASTNET data to

16	describe regional variability, but the fact is that the

17	CASTNET data are strictly almost exclusively rural

18	monitors.	So while that does show, you know the

19	distribution of background concentrations across the

20	country, it really doesn't address urban

21	concentrations.	And those were to some extent

22	addressed by the 12 cities with the four monitors, but

23	there are other cities with additional monitors.	So I

24	guess what I was hoping for was some distinction

25	between urban concentrations and rural concentrations

1	and also a better assessment of the spatial variability

2	within those urban areas, which can be fairly extreme.

3	There was a lot made about the non-

4	correlation between sulfur dioxide and sulfate, and it

5	seemed to me that the ISA was sort of surprised that

6	those two species were not more highly correlated which

7	actually wasn't so surprising to me.	I guess thinking

8	on their sort of separation in space and time, and the

9	time between the conversion of SO2 to SO4.	But what I

10	was also hoping to see was some additional information

11	about the correlation between sulfur dioxide and its

12	co-pollutants because that's maybe more relevant to

13	helping interpret some of the epi studies.	So I would

14	like to see how those ambient concentrations of SO2

15	correlate with NO2 and CO and PM fine and PM course to

16	the extent that, that data is available.	I think that

17	would be a valuable addition.

18	And with respect to temporal patterns, I

19	think seasonally -- that whole thing with the seasonal

20	data could be summarized a little more efficiently, I

21	think, rather than showing every city and those

22	patterns, you know, annual timelines.	Those parts were

23	nice, but I think you could come up with a more

24	efficient summary of that information and in particular

25	the daily variation, you know, hour by hour, diurnal

1	variation.	That plot was not very effective, and I

2	think everybody's comments noted that particular

3	figure.	I don't know which number it was, but the one

4	that showed daily diurnal variation was not very

5	helpful.

6	I guess I liked that fact that annex two

7	had some NOx chemistry in it, but it was a little

8	disconcerting too, you know.	The only mention that it

9	was going to be there was this little footnote very

10	early on in the document, so I think that could be

11	maybe explained a little better.	But I actually liked

12	that the NOx chemistry was there.	I thought that was

13	helpful.	Oh, and I did point out in my comments with

14	respect to the urban spatial variability and urban

15	gradients, there is a brand new study that's Canadian,

16	but I think really relevant to this effort that could

17	be reviewed.	That's all.

18	DR. HENDERSON: Thank you, Donna.	And

19	Ted Russell?	Where are you Ted?

20	DR. ARNOLD: If we could, I'd just like

21	to maybe make a point of clarification.

22	DR. HENDERSON: Oh, sure.	I'm sorry.	I

23	forgot to ask you if you had questions.

24	DR. ARNOLD: Thanks very much.	Thanks

25	for your comments, Donna.	We really appreciate them,

1	and I think it points out something that we need to

2	perhaps address in terms of the emphasis that we're

3	providing.	We're certainly looking at CASTNET, and

4	we're showing the distributions for looking broadly

5	across the domain.	Table 2.4-2, however, does use the

6	AQS data, and we've split them for inside and outside

7	the CMSAs to try to get to this idea of looking at

8	distributions within cities and then outside of cities

9	as well.	But we certainly take your point, and we'll

10	provide more emphasis on looking potentially at

11	correlations, both across monitors within a CMSA where

12	we have it and then with potential co-pollutants as

13	well.	I'm sure with your experience you realize that

14	part of the problem is that SO2 is not measured

15	everywhere at the same location as the other pollutants

16	that we might be interested in looking at correlations

17	with.	And as to perhaps there was too much emphasis on

18	what you took to be our surprise in looking at the

19	correlation between SO2 and sulfate, there was some

20	perhaps differential in surprise between the

21	atmospheric scientists and the epidemiologists about

22	whether there was going to be correlation between SO2

23	and sulfate, and we were trying to address that

24	question with those plots that were in there.	So we do

25	take that comment.	We tried to make the point about

1	whether there was, we talked about the difference in

2	looking at processing time and why that would be the

3	case and why we got some difference in the correlation

4	across the cities that we did look at.	But we will go

5	back and look at the language on that and try to

6	sharpen that discussion.

7	DR. KENSKI: You know, this Table 2.4-2,

8	it wasn't, I think maybe that was a question I had in

9	here.

10	DR. ARNOLD: I saw that in your written

11	comments.	Yeah.

12	DR. KENSKI: Whether it was including

13	Casnet data or just AQS data.

14	DR. ARNOLD: AQS data from 2003 to 2005.

15	DR. KENSKI: Okay.	So that could be

16	clarified.

17	DR. ARNOLD: Yeah.	We'll certainly put

18	that in the note.	Thanks very much.

19	DR. HENDERSON: Okay.	Now we'll go to comments from Ted

20	Russell.

21	DR. RUSSELL: Okay.	Thanks.	Just a few

22	comments.	First on the measurement techniques.	You

23	talk about the positive and negative possible

24	interferences.	I think in the bottom line what we want

25	to know about are quantitatively what you think the

1	bias and uncertainty are as opposed to just what they

2	may be in that I'd suspect we're actually, this isn't

3	going to play a real role in how we interpret the

4	measurements.	And I think as we indicated on the NOx

5	case, what we really want to know is the information

6	relevant to how we might go forward and interpret the

7	various other studies towards how that would influence

8	setting of the standard, and I think they're, in this

9	case again, it's quantitative information as to the

10	uncertainties, not just what may be positive and

11	negative without really knowing to what degree.

12	We talked somewhat about providing a

13	five-minute data, and I think this should be done

14	wherever it's available, and you say that it's less

15	than 0.05% of the time it's over, whatever, 100 ppb.	I

16	can't recall exactly what it was.	That's still about

17	50 times a year, so it's not -- for a typical monitor

18	-- so it's not a insignificant number of times.	Given

19	that, what I'd do, and I think it does have to be in

20	this chapter, is a nice plot showing the five-minute

21	data, and I'd use something like a PDF so we can get a

22	good idea of the whole distribution would be the

23	approach I'd take.

24	You've got a fairly large section on

25	exposure measurement air, and I was taken actually by

1	one of the first sentences.	The sentence in the second

2	paragraph of that where you say the considerations of

3	exposure air for SO2 are somewhat simplified compared

4	to those for NOx and PM, and, you know, that's only in

5	one dimension.	And that I'd say that actually exposure

6	measurement air for SO2 is probably going to be the

7	biggest of the bunch.	Just if you look at what leads

8	to the higher concentrations, it's typically a fairly

9	localized event that, you know.	It could be a plume

10	that's all of, oh, 3, 4, 5 km if that wide.	So you're

11	actually many a time going to be measuring something

12	that's having an impact on a relatively small amount of

13	a domain, and other times you're going to be missing

14	significant exposures that just aren't being measured.

15	And this really is going to depend upon the geometry,

16	how close your major sources are, etc, and so I would

17	take a little bit more time in discussing the

18	complexities of SO2 exposure measurement air in a

19	typical domain.	One of the ways I'd approach that is

20	for the locations that you have multiple monitors

21	within a single CMSA area.	Look at correlations, the

22	five-minute, one-hour, and 24-hour average

23	concentrations just to -- and you can do one-hour max

24	concentrations -- just to see how well you think you

25	actually, or provide information.	Actually I'd hope

1	the studies themselves did this, to provide information

2	as to how to interpret these, the exposure measurement

3	there.	And you just look through the document right

4	now.	I think it underestimates the complexity there,

5	and then when you start seeing the results from the

6	Sarnet study, etc that there really are questions as to

7	how well ambient monitors really do reflect exposure.

8	And along those lines I'd also for the sites where you

9	do have co-occurring data, show and describe what

10	pollutants SO2 is currently correlating with, including

11	the medals from various PM components, not just

12	sulfate.	You know, see how well it correlates with an

13	array of other pollutants that might also have either

14	effects leading to increasing the impact of SO2 or

15	those that might be impacting the interpretation of

16	your exposure analyses and epi analyses. And I think

17	most of the other things are in my written comments.

18	DR. HENDERSON: Thank you, Ted.	Does

19	NCEA have any, do you have any questions for Ted?

20	DR. ARNOLD: Just a few short points of

21	clarification, I think.	We certainly take the general

22	feeling of the panel that information on finer term

23	ambient monitoring is important, and we will include it

24	to the extend that we can.	We were explaining a little

25	earlier about the problem in using the five-minute data

1	now, and that is that since it's not currently required

2	of the states and they reported voluntarily, they

3	reported for some monitors and not others.	And these

4	monitors come in and out year by year, so it makes it

5	difficult to look across time.	And I just wanted to be

6	a little clearer about it.	We were unclear.	I realize

7	it's hard since we don't actually present the

8	information in the ISA, but the figure of 0.5% does not

9	refer to a single monitor registering 600 ppb but

10	across all the monitors, which were reporting for 10

11	years across the time.	Now we're adding to this.

12	Again, we're extending up with our work with the

13	program office.	We're looking beyond 2000 up to the

14	most recent through 2006.	That doesn't end up

15	producing a large number of additional observations

16	simply because states are taking out monitors in places

17	because we're now so far below the standards.	So to

18	the extent that we can get this information together

19	and get the analysis done, we'll certainly include it

20	in the second draft.

21	DR. RUSSELL: And what you state

22	actually, I think there would be a nice piece you could

23	do with it is showing the correlation between the one-

24	hour average, how well it correlates with your peak

25	five-minute average.

1	DR. ARNOLD: That's right.	And that's

2	one of the things we have been looking at internally,

3	and at the few sites where we have consistent five-

4	minute data, we can certainly do, look at that.

5	DR. RUSSELL: Okay.

6	DR. ARNOLD: Our concern has been to

7	present this in a way that we can emphasize both the

8	uncertainty in the non-random distribution of these

9	observations and not use this or have this be

10	potentially misinterpreted as the basis for

11	generalization across the whole continental US.

12	DR. SPEIZER: But surely wherever you've

13	got a five-minute measurement and you have a one-hour

14	or a 24-hour, that is internally consistent, and you

15	can do an analysis of that irrespective of how

16	representative those five-minute averages are of the

17	country.

18	DR. ARNOLD: That's correct.

19	DR. SPEIZER: And we should see that.

20	DR. ARNOLD: Yes.	And we will provide

21	that.

22	DR. SPEIZER: And if I would, I would

23	suspect that if you plot the five-minute averages,

24	they're fairly logged normally distributed.

25	DR. ARNOLD: I believe that's true, but I

1	don't have that plot with me.

2	DR. SPEIZER: Okay.	In which case you

3	can actually get a lot of extra inference from what

4	distributions you currently have.

5	DR. ARNOLD: Sure.	But my concern is

6	just, I mean, we can say something locally about it,

7	but we can't say anything very regionally about it.

8	DR. HENDERSON: Okay, Ellis?

9	DR. COWLING: I finally remembered what

10	it is that I couldn't remember before, and it's

11	pertinent to these five-minute measurements, which

12	Frank brought up and Ted has emphasized and so on.	And

13	I'd like to make my comments in the context of the

14	early summary that we had about the decisions that were

15	made about the national ambient air quality standards

16	for sulfur oxides.	And on slide 5 we had this very

17	nice history of the SO2 NOx, and I think we should

18	always have a good summary of what the decisions were

19	and why they made those decisions.	Now one of the

20	things that particularly struck my interest in this

21	summary was the fact that EPA made a deal with the

22	American Lung Association.	The American Lung

23	Association have been bringing up this short-term

24	exposure business for a long time, and the EPA, not

25	wishing to change the standards said okay, we'll do

1	some monitoring.	And then we learned that the

2	monitoring was not required to be reported.	I would

3	like to know the rationale for that decision and if

4	possible to know who made that decision.

5	DR. ARNOLD: As you can imagine, Ellis,

6	this is not something that we can respond to.	It might

7	be possible for someone from the Air office to respond

8	to that question, but it's not something that we would

9	consider in the ISA or would try to evaluate.	We will

10	evaluate the data that we have when we have it at the

11	time when we've reached the endpoint for the inclusion

12	of those data for various drafts of the ISA as they

13	come along.

14	DR. COWLING: Well I understand this and

15	I guess this comment should be made when the Air Office

16	people are here, and then I'll make it again, but --

17	and I hope I --

18	DR. ARNOLD: I don't mean to push things

19	off on Lydia, but I'm sure you can -- we appreciate

20	your concern in putting it on the table, but I'm sure

21	you realize it's not something that we can, we can

22	respond to or incorporate in the ISA.

23	DR. HENDERSON: Are Lydia and Karen going

24	to be here later in the day?	Tomorrow, okay.

25	DR. COWLING: Let me, in conclusion,

1	mention that Mississippi does not have an ozone problem

2	because Mississippi has no ozone monitors.

3	And you may know that I've had some

4	experience dealing with comments, and I make comments

5	about that from time to time.	Fort Bend County is the

6	most rapidly growing county within the ozone non-

7	attainment area.	There are no ozone monitors in Fort

8	Bend County.	I don't know exactly why, but it's

9	interesting that Tom Delay has his home base in Fort

10	Bend County, and it's also interesting to be aware that

11	the state of Texas does not install monitors unless the

12	monitors are welcome by the county judge and the

13	members of congress that represent that county.	So if

14	we require measurements of five minute averages or

15	exposures and make a deal with the American Lung

16	Association, and then don't require that they report

17	what they found, I should imagine that the American

18	Lung Association would be pretty T'ed off about -- and

19	I understand.

20	DR. ARNOLD: More importantly, the judge

21	might be pretty ticked off.

22	DR. COWLING: Yeah.	I -- okay.

23	DR. HENDERSON: Well --

24	DR. ARNOLD: I think I, I think I just

25	want to be clear about what's required of the states to

1	report, and that's irrespective of the agreement that

2	may have been struck for the additional findings.	We

3	will certainly use all data which we can collect from

4	the program obviously.

5	DR. COWLING:	And I guess we could

6	try to increase the willingness of the states to

7	provide this if we were to comment in some way.	You're

8	advice about these matters would be very welcome, and

9	Donna is raising her hand I think.	And I look to

10	Donna.	She regulates air quality or helps in that

11	process, and it is very welcome to have someone who

12	actually manages air quality in our CASAC discussions,

13	which are mostly scientists who don't manage anything

14	but their own affairs.

15	DR. HENDERSON: All right.	With that,

16	Donna, do you have any comment on what's required?

17	DR. KENSKI: I do have a comment.	In the

18	quest for five-minute data, one barrier to that data is

19	actually getting into AQS because it's not really set

20	up to deal with five-minute data.	But it's my sense

21	that many of the state organizations who collect, those

22	of them that report the five-minute max data may in

23	fact have the other, you know, other five-minute

24	intervals archived somewhere.	So that might be

25	something you'd want to pursue in, you know, in whether

1	it's, in the next draft of the ISA or with respect to

2	the Health and Exposure Assessment, is trying to track

3	down whether the states, you know, have that data

4	available and could share it with you.

5	DR. ARNOLD:	We'll certainly work

6	with the program offices to establish where those data

7	are and how we can get them.	Thank you.

8	DR. THURSTON: Not to dwell on this too

9	long, but routinely how long do they archive the data

10	for?	I've had a real problem with trying to get

11	filters that they archive 'cause they keep them for

12	like one year and then toss them.	Do they do the same

13	thing with data?	Do they archive them for a few years

14	and then print out a report and they're done?

15	DR. KENSKI: I mean, if there's a

16	requirement to submit, you know, data to assess the

17	NAAQS, but aside from that, then, you know, each state

18	they can throw away whatever they want if it's not

19	required to go into, you know, assessing their

20	compliance with the NAAQS.	But, I mean, states differ

21	widely in their desire to, to figure out the nature of

22	their air quality and problems.

23	DR. THURSTON: Tactfully put.

24	DR. KENSKI: Thank you.	So, you know, so

25	it varies form state to state what's archived and

1	what's available, you know.

2	DR. HENDERSON: Maybe we should go on and

3	let Jim Ultman give his comments.

4	DR. ULTMAN: Thank you.	I just have a

5	couple of things to add.	Relative to figure 2.4-5 on

6	page 213, I found this figure very useful personally.

7	It was labeled as a box plot, and it refers in the text

8	to 95% limits.	So I think there's some discrepancy

9	there.	It's more of a scattergram, but I thought it

10	would be, because it was so useful to me, I thought

11	that in considering different forms of the standard, it

12	would be nice to have consistent plots for all, for

13	three different forms that I think you're reaching for.

14	One is the annual form.	The other would be the daily

15	form, and then the third would be the hourly form. And

16	if there's, I realize that the next figure shows for

17	Steubenville shows kind of a, that kind of a plot for

18	the hourly form, but it could be three consistent

19	plots, you know, that showed scattergrams of some sort.

20	And I know this is very hard for the short standard,

21	but still as close as you could come so you can compare

22	if you use different forms what the distributions would

23	be like.	I think that would be helpful.

24	And then my other comment has to do with

25	dosimetry, dosimetry section, and I think as Frank

1	Speizer already pointed out, there's more to what

2	happens to SO2 than considering the SO2 that reaches

3	the lower airway, lower respiratory tract.	And

4	particularly there's an emphasis in the chapter in the

5	section on dosimetry on the absorption of ozone, I'm

6	sorry, of SO2 by the upper airways as a means of

7	protecting	the lower airways, but two things I wanted

8	to mention that should be stressed at probably in the

9	last part of this section.	First of all, that SO2,

10	which is absorbed by the upper airways is going to

11	circulate and can cause systemic effects.	So to the

12	extent possible, I think systemic effects should be

13	brought in because whether it's absorbed in the upper

14	or lower airways, it's not all going to be reacted

15	within the liquid lining layer.	So you're going to

16	have systemic effects.	So I don't, I'm not sure that

17	there's enough data out there to do much about it

18	quantitatively, but at least to mention, to emphasize

19	that fact.

20	The second point related to that is that

21	only a portion of the absorbed ozone in the upper

22	airways is permanently absorbed, but there's this

23	countercurrent exchange that goes on with heat, with

24	water vapor, and with these xenobiotic gases that are

25	soluble; and that is they're absorbed in the upper

1	airways during inspiration, and then they're desorbed

2	during expiration.	And this is one of the ways the

3	lungs kind of protect the whole organism from

4	xenobiotics and from heat loss.	And this is covered

5	actually.	The studies are quoted in that section on

6	dosimetry, but I think, again, it should be emphasized

7	that this is a protective mechanism and that not all

8	the ozone that's absorbed during inspiration

9	necessarily puts the person at risk because some of it

10	is desorbed.	And if nothing else, this will possibly

11	stimulate other thinking, other studies in this area,

12	even though it may not be directly useful in terms of

13	what we're discussing here.	That's it.

14	DR. HENDERSON: Okay.	Mike, do you have

15	any questions?	Nobody wants to question?	Now I'll

16	open it up to any member of the panel who wants to talk

17	or make comments on chapters, on chapter 2.	Yes, go

18	ahead?

19	DR. POSTLETHWAIT: Hi, Rogene, this is Ed

20	Postlethwait.

21	DR. HENDERSON: Oh, hi, Ed.

22	DR. POSTLETHWAIT: I actually had a

23	question for Jim, what he just brought up, which I

24	think was a great point.	Jim, have you ever looked at

25	the half-life of SO2 once it diffuses in the tissue or

1	the vascular space as to how far downstream it actually

2	might exist, especially the kind of environmental

3	concentrations we're talking about?

4	DR. ULTMAN: No.	I haven't, I haven't

5	that, Ed.	But there's two questions here in terms of

6	half-life; and one would be the decomposition or the

7	reaction of the material in the blood, and the second

8	would be removal by other organs.

9	DR. POSTLETHWAIT: Right.

10	DR. ULTMAN: So it's a pretty complex

11	issue, but I haven't looked at it, no.

12	DR. POSTLETHWAIT: Well because the

13	chapter does mention the business about delivery to the

14	lower respiratory tract via the vascular supply, and,

15	you know, when we're talking fairly low ppb

16	concentrations one wonders what in terms of a mass

17	action how much SO2 you might really be talking about.

18	I would guess the numbers are going to be pretty small.

19	DR. HENDERSON: I don't know, Jim, were

20	you thinking of the oxidation reduction situation that

21	the sulfate would be a reducing agent?

22	DR. ULTMAN: Well I hadn't really been

23	thinking of the specific chemistry involved, no.

24	DR. HENDERSON: I was just trying to --

25	I'm like Ed.	I was thinking when you said that, what

1	would you expect from the blood borne.	It could be

2	sulfite I presume.	At very low levels, what would we

3	expect, but you're right it would be there.	Dale, do

4	you want to go ahead with your comment?

5	DR. HATTIS: Yeah.	I just wanted to

6	point out the issue of the distributions for different

7	time periods was mentioned earlier, and I think that --

8	I like your Table 2.4.2 where you give the percentiles,

9	but I think you could enhance that with some log normal

10	probability plots.	And so I basically made some from

11	those data.	Basically you could see those on page 56

12	of the comments.	It's labeled Figure 1.	And basically

13	what you see there is the orderly progression of

14	increasing variability for decreasing averaging times.

15	And you see particularly that for the one-hour

16	averaging time you have a pretty good correspondence

17	with a log normal distribution as corresponding to the

18	points that fit inline and pretty parallel lines,

19	meaning the same standard deviation, geometric standard

20	deviation essentially for the one-hour maximum versus

21	the one-hour average concentration load slightly

22	translated.	And what that means is that you basically

23	have a geometric standard deviation of a little over

24	three for the one-hour maximum.	So you could do the

25	same thing in parallel with the five minutes, maybe

1	even make some inferences to how much more variable the

2	five minutes average is compared to the one-hour, and

3	that would allow you to make the national projection of

4	how often you get various levels.	So basically what

5	the log normal distribution does for you is it has a

6	convenient way of extending the data essentially to how

7	often you get very high levels versus just more common

8	levels, and that in turn can be used in conjunction

9	with your direct clinical observational data to do some

10	kind of concentration response and expectations for

11	incidents of adverse effects.

12	DR. HENDERSON: Are there -- oh, go

13	ahead, Jon.

14	DR. SAMET: In general comments, I'd like

15	to read this chapter called something like source to

16	dose, and actually see that question answered, which I

17	don't think it does.	So it deals with SO2 but then

18	raises the possibility of surrogates in true causal

19	agents, leaving them general and unspecified.	And

20	isn't this the chapter where if you think that SO2 is

21	undergoing chemical transformation, physical

22	transformation into agents that are actually injurious?

23	There should be some specificity given to that

24	discussion.	So I think this is a critical foundation

25	for determining the epidemiological studies in which

1	this issue will come up, but I don't see this question

2	as answered at all.	I think possibilities are raised

3	and, again, for example on page 241, Relationship of

4	SO2 to the True Causal Factor.	So if you're raising

5	the possibility there is some "true causal factor,"

6	what is it?	What are its physical and chemical

7	properties, and what doses are being delivered to the

8	respiratory tract or?	Also I just don't think these

9	things can be raised and then left dangling because I

10	think this is really fundamental to interpreting our

11	multi-pollutant models.	DR. HENDERSON:

12	Thank you.	Yeah.	Go ahead, Ron.

13	DR. WYZGA: One of the things I think

14	could be helpful in later chapters when we try, and I

15	think we have to do more to try to tie together the

16	information from both the epidemiological studies and

17	the human clinical studies is to have a better

18	understanding, particularly when you look at the time

19	series epidemiological studies.	What's the

20	relationship?	Those tend to use 24-hour SO2

21	measurements.	What's the relationship between those

22	and peak hourly or peak five-minutes?	So I'd like to

23	see some correlations for where we have data between

24	the 24-hour average over time and the peak five-minute

25	for that period, and the peak hourly for that period.

1	It would help me get some understanding to what extent

2	the epidemiological studies are indeed telling us some

3	of the same things as the human clinical studies.

4	DR. HENDERSON: Okay.	Is that something

5	that's possible with the data?	I'm asking NCEA.

6	DR. ARNOLD: Yes.	We think so.	We

7	certainly have epi data and we think we can construct

8	those correlations to the extent that we have.

9	Certainly it's going to, as we've heard this morning

10	already, certainly it's going to be easier with the

11	one-hour data than with the five-minute data, but

12	certainly where we have it we can take a look at that

13	as well.	Thanks very much.

14	DR. HENDERSON: Okay.	Yeah, Lianne.

15	DR. SHEPPARD: Yeah.	I wanted to suggest

16	in this chapter that the presentation needs to be

17	thoroughly revised to really deepen the understanding

18	with respect to the health studies, and so there are a

19	couple of things that I would suggest along that line.

20	One is more thorough analysis -- well also and for the

21	Health Risk Assessment that will follow.	So one is the

22	analysis that was already suggested of relating the

23	five-minute to the one-hour averages.	We also need to

24	have a much better understanding of the spatial

25	distribution of exposure.	SO2 monitors often are cited

1	right next to local sources, and in a time series study

2	that's not really representative of population exposure

3	and could be a very important aspect of measurement

4	error in a time series study.	And there's certainly

5	cities where there are only local source SO2 monitors.

6	I know Seattle is one of them.	And so you would really

7	question the interpretation of a health study that uses

8	population level data in a city like that.	And so I

9	think there needs to be a summary that classifies

10	cities into only local source monitors versus

11	population-oriented monitors versus both, so we can

12	understand how important that is.	There should also be

13	an analysis of land use characteristics so we can get a

14	sense of how important the local sources are in terms

15	of population exposure where there aren't monitors.

16	Let's see.	And then another thing we need to better

17	understand is the analyses of personal or indoor

18	concentrations versus outdoor concentrations in terms

19	of interpretation of exposures that people actually

20	have.	So there is some analysis in the chapter, but I

21	don't think it really gets at that issue clearly

22	enough, and if the apex model is going to be used in

23	the Health Assessment, we need parameters in this

24	chapter that can be brought forward into apex.

25	And then I think that, actually I

1	recommend that a thorough analysis of the AQS data in

2	the context of results that are going to be needed for

3	either the Health Assessment or the interpretation of

4	epi studies and clinical studies be added to the annex,

5	and then the tables and figures be completely revamped

6	to bring forward the key features of that analysis.	A

7	lot of the figures and tables are way too summarized

8	for what we need, and my comments will give specific

9	details on those.

10	DR. ARNOLD: Great.	If we could just add

11	a couple points of clarification to make sure we

12	understand, then we'll go back and look at your

13	comments again and consider those in consideration with

14	the letter, with the letter that comes out of the

15	panel.	If you'd say a little more about what you mean

16	by considering the analysis of land use characteristics

17	when we're looking at questions of local citing.

18	DR.	SHEPPARD: Well, I mean, monitors

19	are not put next to all local sources, and it's going

20	to be really important in terms of characterizing

21	population exposure, particularly susceptible

22	individuals, to have a sense of how much of the area in

23	the United States do you expect to have high exposures.

24	And monitors are only in a few of those places, but

25	with a geographic information system or the point

1	source database, you could, somebody could summarize in

2	a city or over the United States, for instance, which

3	census tracts are expected to have high peak exposures

4	and which aren't.	And that would be very important to

5	bring forward into the Health Assessment.

6	DR. ARNOLD: So if I just, in addition to

7	the plots, the mapped plots that we have now of SO2

8	sources, you would like to see similar plots of where

9	the monitors are and what the relationship between the

10	monitor, the distance let's say as one parameter

11	between the monitor and that source.	And then bend

12	these up.	In some kind of ways you were suggesting

13	whether these are population cited monitors or source

14	receptors.

15	DR. SHEPPARD: Well so I'm making really

16	two different points.	One is just summarizing land use

17	to bring forward into the Health Assessment.	I should

18	go back and look to see what you have in respect to the

19	sources already with respect to that to see how well

20	that's addressed for the Health Assessment.	But the

21	other point that I was making was in terms of, of

22	summarizing the monitoring data with respect to whether

23	it's local source or other important characteristics

24	about sources versus population oriented because that

25	has very important implications for interpretation.

1	For instance, of the time series studies because if you

2	use only a local source monitor in a time series study,

3	it's not representing population exposure, and it's

4	presumably that SO2 estimate is going to be subject to

5	a very high amount of classical measurement error as a

6	result of that.	And so I'd like to see summarized in

7	the document information about citing characteristics

8	with respect to the monitoring data that we have.	And

9	I would recommend that a number of the tables and

10	figures as well be separated by local source versus

11	population-oriented information.

12	DR. ARNOLD: Sure.	And we take that

13	point, and we'll work with the program office which

14	controls the regulations, as I'm sure you're aware,

15	controls the regulations that describe the citing

16	characteristic and perhaps include those in the annex?

17	Is that your idea and be able to bring forward our

18	conclusions about how those could be useful for

19	interpreting the health data.	DR.

20	SHEPPARD: Yes.	So I would suggest adding a pretty

21	extensive analysis of the AQS data in the annex with

22	respect to different questions that would be important

23	for interpreting the epi studies and for use in the

24	Health Assessment and then bringing forward the key

25	features into the ISA from that analysis.	So depending

1	on what exactly it is that you learn, then you decide

2	how to bring that forward.

3	DR. ARNOLD: Thanks very much.

4	DR. ROSS: I'd like to follow up.	And it

5	sounds like since your most interested in health

6	studies, it would be useful to focus on the cities in

7	which health studies were done.	Looking at the

8	epidemiological tables that we have at the end of

9	Chapter 5 and really focus on an in-depth look to the

10	extent data available those cities because that's where

11	you would be interpreting epidemiological --

12	DR. SHEPPARD: Well, you know, that's an

13	important point I think with respect to interpreting

14	the studies that are being recorded, but we also need

15	to keep in perspective that we have the Health

16	Assessment as well where presumably we are, the whole

17	population of the United States is relevant.	And so

18	I'd be careful about restricting that analysis too

19	early, and I would definitely, in terms of the more

20	thorough exploratory analysis that's done in the annex,

21	I would certainly look at that distinction and see if

22	there's something important that needs to be brought

23	forward with that.	But I wouldn't immediately restrict

24	attention to only those cities.

25	DR. ROSS: I was thinking more of the

1	word focus rather than restrict.

2	DR. HENDERSON: Okay.	Does anyone else

3	have comments on Chapter 2, or can we go on to Chapter

4	3?	Oh, we've got lots of comments.	Okay, Terry.

5	DR. GORDON: Something else that might be

6	added to this chapter as brought up by George Thurston

7	earlier, the inclusion -- this chapter's title is

8	Source to Dose, and it's a tremendous bias amount since

9	I was Mary Ander's last student.	But I think that the

10	work by Jacob at Hopkins, and Mary at Harvard, and MIT,

11	and NYU should be included.	I understand for both SO2

12	and NO2 once it becomes part of a particle, it's part

13	of the PM ISA, but in this case because one of the

14	issues we're going to find is the exposure levels at

15	SO2 are so low and we're finding adverse effects, is

16	biological plausibility.	So I think some of the, the

17	Jacob and the Ander data of the acid particle

18	interactions should be included in Chapter 2 and

19	integrated with Chapter 3 where it's missing also just

20	to help us get to the Chapter 4 and 5 in looking at

21	biological plausibility.

22	DR. HENDERSON: Okay.	And who else had

23	their hand up?	Yes, Frank.

24	DR. SPEIZER: I wanted to sort of second

25	what Elizabeth said about getting out the distribution

1	information, and I just wanted to add to that, that if

2	it's possible to sort of look at the population-base,

3	it is upwind and make some estimates that are going to

4	be needed in both the Exposure Risk Assessment and the

5	Health Risk Assessment to know that these monitors are,

6	in fact, either representative or not representative of

7	a population basis that are going to be used.	And I

8	wouldn't restrict them just to where the whole studies

9	are.	The other minor point that I had was that there's

10	a Figure 2.51, which I found very confusing which is

11	speaking to the issues on page 228.	Speaking to the

12	issue of indoor/outdoor exposure, if the figure is

13	truly representative of all age groups, then I don't

14	understand 1.8% of the time being spent in bars and

15	restaurants; that's one part of it.	The other part

16	that if it is indeed representative of people working

17	outside their homes, if 60% of the people work outside

18	of their homes, how come only 5.4% are in offices or

19	factories.	It doesn't quite make sense, so I ask you

20	to look at it again.

21	DR. HENDERSON: Do you all want to

22	address that?

23	DR. ARNOLD: I think Joe Pinto is going

24	to --

25	DR. PINTO: Here's part of the

1	calculation to show you where the 5.4% comes from.	So

2	this is the -- oh, thanks.	Yeah.	Those figures come

3	from the in house study, okay, and the demographics

4	were chosen to match US Census data, and the way we

5	arrived at the 5.4% is like this.	So you say that the

6	percentage of Americans between 18 and 65 is 50% and

7	60% of those work in offices and factories.	So now

8	we're down to 30% of the general population.	Now most

9	people only work 40 hours a week, so you have another

10	factor of 40 over 168, okay.	So now we're, and that

11	gives you .24, now we're down to 7.2%.	Now some people

12	also work in bars and restaurants.	They drive trucks,

13	build condos, fix cars.	So 7.2% down to 5.4% is not

14	too big a stretch, but the larger point is that we will

15	make it clearer in the text.

16	DR. HENDERSON: Okay.	Are there other

17	questions before go on to Chapter 3?	Ed.

18	MR. AVOL: Yeah.	So I just have two

19	comments really that I think, well one of which

20	probably fit here 'cause I'm not sure where else it

21	fits, and that is following up on what Dr. Cowling and

22	Sheppard said about locating stations and not having

23	stations where there may be exposures.	I'm not quite

24	sure how this gets integrated into looking forward, but

25	if in fact as we find based on the current stations

1	that the ambient levels are low, that tends to drive

2	regulatory agencies to shut down the station because

3	they've demonstrated compliance, and now we don't have

4	any information for looking for it, either for health

5	or exposure.	So we won't get both five-minute

6	information unless we somehow make some determined

7	effort to actually lay out a structure for doing so,

8	and that's particularly a problem in terms of placement

9	of stations where history was pointed out, as Christian

10	pointed out, there might have been downwind of power

11	plant and so forth.	But now, at least for example in

12	California again, port activities and goods movement

13	activities lend exposure opportunities for areas that

14	might not have been previously impacted by downwind of

15	power plant issues.	And so I'm not quite sure where

16	that gets factored into a strategy or a sampling

17	design, but in looking forward, somehow we have to sort

18	of close that loop.

19	The other minor point I wanted to point

20	out was there were comments in here about natural

21	sources of emissions and volcanos are sort of commented

22	on and then sort of dismissed as SO2 being a minor

23	component of that, but, in fact, we've been doing work

24	in Hawaii on the big island; and the USGS has been

25	making measurements by the way of volcano and for the

1	people that live in the communities around and below

2	the volcano, the ground level concentrations are often

3	in the part per million range at the ground for periods

4	of minutes or half-hours, etc.	So both the five-minute

5	concentration I'm sure is over one part per million and

6	the hourly concentrations can be quite significant too,

7	but, again, because of the placement of the placement

8	of the station and the fact that Hawaii is several

9	islands, there is not a reporting station there.	But

10	USGS in fact is making those measurements.	I'm not

11	quite sure how we'll get data for natural exposure

12	DR. HENDERSON: Okay.	Thank you, Ed.

13	Anymore?	Did you get the information you need for

14	Chapter 2 from us?

15	DR. ARNOLD: I believe that we have.

16	Thank you very much.

17	DR. HENDERSON: Okay.	Then let's go on

18	to Chapter 3, which is on the Health Effects of the

19	SOx, and Frank Speizer is the lead person on this.

20	DR. SPEIZER: Well I made a number of

21	several comments and my written remarks, but I wanted

22	to focus back on this issue of distribution of

23	responsiveness and how this is sort of being played

24	out.	As I indicated earlier, anywhere from 10% to 30%,

25	well maybe we should wait for people changing seats

1	here.



2	DR. HENDERSON: We have a changing of the

3	crew here.	I didn't give them enough time.	There we

4	go.

5	DR. SPEIZER: As I pointed out earlier,

6	anywhere from 10% to 30% of the population seems to be

7	more responsive in any population group, and I would

8	wonder whether it's possible to even look selectively

9	among the annex to find where you've got distributions

10	of responsiveness and try to identify what proportions

11	of the populations are being responsive in those

12	studies.	Even though the studies on the whole might be

13	null.	I think this will be useful to have that kind of

14	information when we come up to the risk assessment

15	aspect of things.	It also might change our thinking

16	about what the overall impact of SO2 is as a primary

17	pollutant.	I don't know how feasible that is.	I just

18	don't know how many of the studies would provide

19	distribution information.	Certainly looking at the

20	sort of summary on ratios, some of them, though these

21	are sort of calculated by confidence intervals, some of

22	them go up to potentially two-fold excess risks.	And

23	so I think trying to look at these distributions, if

24	it's possible, would be useful.

25	With regard to the figures, I had some

1	trouble with the graphics in the sense that it's

2	indicated that the size of the mean effects represents

3	something about the population.	It doesn't come

4	through effectively to me, and I think it may be just a

5	matter of better graphics. I was concerned about some

6	of the summary statements, which perhaps are all going

7	to change now if we change our classification of

8	causality, but I think that some of the statements are

9	a little too definitive in one way or the other rather

10	than indicating where there is lack of data versus

11	either negative data or positive data even.	It may be

12	just lack of data.

13	Again, I had some concerns about the

14	cardiovascular effects.	If indeed there is excess

15	mortality, and since 50+% of mortality is

16	cardiovascular, I don't think those two statements jive

17	very well to say that cardiovascular is negative and

18	total mortality is positive.	I think that has to be

19	discussed a little more.	I think the rest of my

20	comments are described in my notes.	The main one I

21	wanted to focus on was this dealing with the fact that

22	you have within virtually every population a subsegment

23	that seems to be more responsive.

24	DR. ROSS: Could we ask for clarification

25	on that because you'll have an epidemiologic study.

1	You're talking about epidemiologic studies, and then

2	there might be a distribution within the city of the

3	population group.	But you're talking about a

4	qualitative characterization of that, not trying to

5	apply it to the epidemiologic results.

6	DR. SPEIZER: Well I think I do want to

7	apply it to the epidemiologic results, perhaps in a

8	qualitative way.	I think if you can look at the

9	distributions of responsiveness and come up with a

10	general estimate of what the response of populations

11	are, and it's 10%, to 20%, to 30%, then I think we will

12	be that much further along in trying to understand when

13	we come to the risk assessment how to sort of judge

14	what might be the population at risk.	It isn't going

15	to be just the severe asthmatics or just those over 65

16	with a preexisting illness.	It's going to be bigger

17	than that, I think, and I think we need to know what

18	those numbers might be.	The only way we're going to

19	get there is to some consensus, qualitative agreement

20	as to what the at risk pool is.

21	DR. HENDERSON: Okay.	Is that okay,

22	Mary?

23	DR. ROSS: Yes.	Thank you.

24	DR. HENDERSON: Okay.	Well let's go on

25	to Pat Kinney.

1	DR. KINNEY: Well I'd like to start off

2	by saying that I think overall the chapter does a

3	pretty good job of accomplishing the goals of the

4	charge question.	I think my comments really are mostly

5	kind of quibbling around the edges, but in some cases I

6	think they're important quibbles.	And let me just run

7	through them quickly, and you have the detailed

8	comments so you can look at them more carefully.	Just

9	as a footnote, I brought up this issue earlier but I

10	just, you know, one of my concerns was, was about the

11	way robustness of SO2 effects in epidemiologic studies

12	was interpreted, and I think that needs to be done a

13	little bit more carefully.	My reading of the summaries

14	at least that were presented in the chapter didn't lead

15	to a conclusion that the SO2 effects were as robust as

16	you claim.	A second point similar to that is the

17	interpretation of the age specificity of the ED and

18	hospital admissions results from the epidemiologic

19	studies.	There are a couple strong statements here and

20	there saying that, you know, there are basically no

21	effects in sort of midrange adults, but the effects

22	were only in children or older adults.	And, you know,

23	there are some contradictory findings presented in the

24	figure there, you know, like from the Wilson study and

25	a couple of others where there's at least some positive

1	and sometimes statistically significant effects between

2	15 and 65 years old or something like that.	So I think

3	it's a little bit hard to make such a strong statement.

4	A third general point is that I thought that there was

5	just a little too much detailed study description in

6	many of the sections, at least for me.	This has always

7	been an issue with criteria documents that it's kind of

8	hard to see the forest for the trees, and I thought

9	that, you know, I was hoping that there would be a

10	little bit more integration, especially for some of the

11	outcomes that are not so well supported, either

12	plausibly or, you know, from the evidence; some of the

13	things like cerebrovascular effects and nervous system

14	effects that are just a little bit hard to sort of

15	connect the dots.	I thought that we didn't really need

16	to really understand every single study in detail, and

17	I thought it could have been summarized much more

18	briefly with some overall synthesizing comments.

19	And finally the issue of biological

20	plausibility, you know, was raised here and there, and

21	it comes up later more so in the document.	I didn't

22	really find any careful discussion of that issue.	The

23	term was used once or twice, but I thought it sort of

24	came out of the blue without adequate discussion.	And

25	I think later, not so much in this chapter, but later,

1	you know, the term coherence is another one, another

2	buzz word that shows up, which really needs, I think,

3	careful consideration, and in particular to pay very

4	close attention to the vastly different concentrations

5	that are used in the experimental studies as opposed to

6	the epidemiologic studies.	And trying to sort of

7	demonstrate biological plausibility of epidemiologic

8	results based on 2 or 3 order of magnitude higher

9	controlled studies, I think, requires some careful

10	argument, which wasn't there.

11	Other than that, just a bunch of

12	detailed comments that you have.	Thanks.

13	DR. HENDERSON: Thanks, Pat.	Any

14	clarification needed from --

15	DR. ROSS: It was very helpful.	Thank

16	you.

17	DR. HENDERSON: Okay.

18	DR. SPEIZER: Can I raise a point that I

19	neglected to raise?	I wondered about putting the

20	clinical studies and maybe even toxicology, although

21	there isn't that much, before the epi stuff because I

22	think it makes the argument for looking at the

23	subgroups a little firmer, and it allows one to sort of

24	make the logical jump as that there are subgroups.	So

25	I just, that's just a matter of revising the order of

1	things.

2	DR. KIM:	It's definitely something

3	we'll consider, especially since the issue of

4	susceptible populations has been brought up several

5	times today.

6	DR. HENDERSON: Okay.	We have Rich

7	Schlesinger, but he's not here.	I know I haven't seen

8	him.	Rich, are you on the phone.	I don't know.

9	MR.	AVOL: He told me yesterday he was

10	coming.

11	DR. POSTLETHWAIT:	It's probably a

12	traveling problem.

13	DR. HENDERSON: Well that's unfortunate.

14	We'll miss Richard.	Maybe he's, yeah, probably a

15	travel problem.	I know Ed Postlethwait is on the phone

16	'cause I've heard you.

17	DR. POSTLETHWAIT:Yeah.	I'm here,

18	Rogene.

19	DR. HENDERSON: Okay.	We're ready for

20	your comments on Chapter 3.	DR.

21	POSTLETHWAIT:Well actually some of the issues that I've

22	pointed out in my comments have already been raised,

23	and I apologize if I'm being redundant on an issue that

24	may have been discussed before I was able to call in.

25	But one of the impressions I got, especially so soon on

1	the heels of doing the NOx document, was the issue of

2	the temporal and geographic locals of the studies that

3	are reported here, especially the population-based

4	studies, and whether or not those same cohorts had been

5	used in other studies that identified differing "causal

6	agents."	And, again, because, and I guess we'll

7	discuss it more later, the issue of biological

8	plausibility and what appear to be very, very low

9	exposure concentrations, I think it would be useful in

10	a document at least to identify whether or not similar

11	populations were counted in more than one type of

12	study.	Maybe this is a moot issue and the frequency of

13	that is very small, but, you know, there are a few

14	instances where once study will point at SO2 and

15	another one points at NO2.	And, you know, you got the

16	same dead bodies that you're counting.	And so either

17	identifying that, or minimizing that, or making some

18	kind of a decision as to whether or not those studies

19	by default should be excluded, highlighted, noted,

20	whatever, I think would be useful.	But again I add, I

21	don't know how frequently that may be occurring.	Other

22	than that, I think I've heard -- I've got a few minor

23	other comments in the stuff I submitted, but I've

24	pretty much heard things that recapitulate the issues I

25	picked up.

1	DR. HENDERSON: Okay, Ed.	Thank you.

2	Any questions from NCEA?

3	DR. KIM: Well the preliminary response

4	to Dr. Postlethewait's question is that --

5	DR. HENDERSON: Can you get real close to

6	your mic?

7	DR. KIM: Yes, I'm sorry.	Yes, indeed.

8	In most of the epi studies that examine various co-

9	pollutants you see more than one co-pollutant have an

10	association with the health outcome of interest.	So I

11	don't think in this case we could eliminate those

12	studies but somehow we need to perhaps have a

13	discussion about what's the best way to sort of

14	consider confounding -- right now what we use in the

15	ISA is multi-pollutant models because at this point

16	that is sort of the best available data we have to

17	address this issue.	If there are any other suggestions

18	that the panel has, we'd love to hear them.

19	DR. POSTLETHWAIT: Well I think that was

20	really pointed out.	I'm sorry I don't have the table

21	in front of me, but, yeah, it's Figure 3.1-11, which is

22	on page 341 of the document.	If you look at some of

23	these you find a positive correlation with SO2, but

24	then when you add multi-pollutants in you reduce the

25	correlation, which kind of goes against the norm for

1	when you start adding PM and ozone and other things in

2	there. And it sort of makes me wonder whether there's

3	an issue either in the analysis or there's just

4	something kind of squirrely going on.	And so, again,

5	this linkage of plausibility and causality I think

6	needs to be considered very cautiously.

7	DR. HENDERSON: Do you want to explain to

8	Ed why what he's talking about occurs?

9	DR. KIM: Well I guess this might be a

10	good time to sort of talk about what we had brought up

11	before.	Like what I said in my presentation was that

12	we tended to focus on the ones that looked at one

13	addition of pollutant versus the ones that put in three

14	or four additional pollutants.	But I guess I wanted

15	Dr. Kinney's opinion about why he, why he thinks that

16	the other ones are also valid to consider.

17	DR. KINNEY: Yeah, the squirrely ones.

18	Could you address those?	Could you, could you just

19	restate that 'cause I was thinking about something else

20	being said?

21	DR. KIM: So in our assessment of the

22	robustness of these co-pollutant models, we tended to

23	focus on the ones that adjusted for one additional

24	pollutant because of concerns of, you know, over-

25	adjusting and the co-linearity, but I think you

1	suggested that perhaps the other one should be

2	considered as well?

3	DR. KINNEY: Well, I mean, I was just

4	reacting I think to George's comment.	There's a figure

5	that was in your presentation that's also in the

6	document that presented results from some studies that

7	only looked at co-pollutants in a multiple way.	You

8	know, they didn't, unfortunately look at one co-

9	pollutant at a time, I guess, at least that's, I

10	believe that's the case from the way you presented it.

11	And I think George is saying, you know, we shouldn't

12	look at those at all, and I was just saying leave them

13	in because even though they're not perfect, I mean, I

14	would have preferred that they looked at one co-

15	pollutant at a time, it's better than nothing because

16	we have so little co-pollutant information as it is.

17	Yeah.	I wouldn't want to set that information aside

18	but interpret it carefully, of course, because it could

19	very well be overcontrolled just as a single pollutant

20	model is probably way under-controlled or at least, you

21	know, potentially biased by lack of other measures in

22	the model, you know.	So all the information is useful

23	and each bit of it has some uncertainly associated with

24	it, but I wouldn't set any of it aside 'cause there's

25	not enough of it to waste any of it.

1	DR. KIM: Yes, sir.

2	DR. HENDERSON: Okay.	Are there other --

3	DR. THURSTON: Yeah.	Could I just follow

4	up on that?	I just think, you know, Pat and I really

5	agree on this, but it's just a question of whether we

6	show it or not, you know.	And the point that I would

7	say is a picture is worth a thousand words.	And even

8	though in the document in the writing you say well, you

9	know, and you could say it even more clearly that the

10	multi-pollutants -- I think it's more clearly stated

11	actually in the other document.	If you put those words

12	in there in the ISA that I quoted in my written

13	comments, I would be happier, but the fact is people

14	look at the picture, and that's going to get the

15	weight.	In there you're giving it equal weight, and

16	there's just no way around that.	So I just, I really,

17	I actually don't believe those results at all, and I

18	don't think people should do them.	I don't think they

19	should be presented.	I don't think they should be

20	discussed, but I'm willing to say that you could

21	discuss it, but to put it in the figure is just to give

22	it more weight and more credence.	It's given equal

23	credence to the one and two pollutant models where this

24	correlation of the x's is much less of a problem and

25	should be given much more weight.	But in this diagram

1	they're all given equal weight, and there's, that's I

2	guess my objection is to have it in the figure because

3	I just think it's not equal.

4	DR. POSTLETHWAIT:George, are you talking

5	about the Figure 3.1.11?

6	DR. THURSTON: Yes.

7	DR. POSTLETHWAIT:	Yeah.	I mean, the

8	one there to me that really jumps out is the study from

9	South Hollow where SO2 alone as a pretty substantial

10	relevant risk, and when you add PM, NO2, ozone, and CO

11	it goes away, which just to me, and maybe I'm being

12	completely nahere, but that just makes no sense.

13	DR. THURSTON: No.	You're, you're right.

14	I mean it's actually good for you in that model, which,

15	you know, I mean, it's not, it's not a good model.

16	It's a bad model, it shouldn't be done in my opinion.

17	DR. STEWART: On the other hand, just as

18	you said, George, looking at the picture tells a story.

19	I mean you can look at that picture, and you can see

20	that some particle measure is included in each of	the

21	comparisons and in some they've added some other things

22	to it.	And there is this one that looks funny, but one

23	looking funny in this context allows you to sort of

24	mentally just sort of drop it out as an important

25	component.	I mean you can see in general this gives

1	you a Gestalt.	I mean, we all know these are not

2	perfect.	This gives you a Gestalt of what's happening

3	in the two pollutant model, which that includes

4	particles and SO2.

5	DR. THURSTON: Yeah.	I'm okay with two.

6	DR. STEWART: But the other ones don't

7	add that much to it, except for that one from San

8	Carlos.

9	DR. HENDERSON: I think that most of us

10	do what Frank is suggesting.	We just kind of

11	automatically toss that one because it's poorly as they

12	say, but it's -- I think having all of them listed, and

13	it's showing, it does, it's informative in that it

14	shows you what kind of data you got.	So that's why I

15	would keep it in.	Yes, John?

16	DR. SAMET: A comment to this point.

17	It's really the same comment I made on the NOx ISA.

18	You want to establish a framework for interpreting

19	these models.	So if part of the effect of SO2 is being

20	mediated by some contribution to particles and you put

21	particle and SO2 or whatever, SO2 into the same model

22	and there's this mediation effect, then you do expect

23	the SO2	coefficient to drop and the PM coefficient to

24	remain.	Now that's based on the very simple assumption

25	that they're measured with equal error and so on, and

1	those are all very simple assumptions, but what you

2	haven't done is given guidance on how to interpret the

3	two pollutant models, and I think after you get beyond

4	two, I think it does become very, very difficult to

5	know what these models mean, but at least you have some

6	plausibility to think about the possibility that some

7	of the SO2 effect is mediated by PM in some way and

8	that ought to be set out up front as a framework for

9	interpreting the models.

10	DR. THURSTON: I mean, I agree totally.

11	I think that's right.	You need to set the rules out

12	and discuss it, but I also think that there is a

13	mindset here that says, okay, if we have SO2, we put PM

14	and the SO2 goes down, that we believe the SO2 less and

15	that it's actually picking up this PM effect.	That's a

16	negative -- but actually, if you think about the first

17	part of the document where we look and we see that the

18	SO2 effects are bigger when there's PM there to

19	facilitate it getting into the lung and to reacting to.

20	If that were your biological model, which I think is

21	the right one, that when you put PM in there the SO2

22	would go down because it would be explaining that

23	biological mechanism.	It would be picking up the fact

24	that when PM is higher, there is more of this function

25	of bringing the SO2 in, and it would look like a PM

1	effect, which in a way it is, but it's also an SO2

2	effect that it's representing.	So the fact that the

3	SO2 goes down does not mean that part of that PM effect

4	is not what was picked up by the single pollutant SO2

5	before, you know.	And really what you want is all of

6	that remaining SO2 plus a portion of that PM effect,

7	and that's probably closer to what the real total.	So

8	even the one pollutant SO2 may well be underestimating

9	the SO2 effects because you haven't properly modeled

10	the biological process in this regression model.	So I

11	think that we, that ought to also be in that

12	discussion, which is the interaction of pollutants so

13	that a decreased size of the coefficient with adding

14	another pollutant doesn't necessarily mean that the

15	first one wasn't right.

16	DR. POSTLETHWAIT: George, could you

17	explain that a bit more because the impression I get

18	from that one specific table is that, you know, in

19	general when you start adding other pollutants the

20	coefficients always go down.	They never get higher.

21	DR. THURSTON: Well I'm not sure

22	everybody wants me to explain it more.	I think I've

23	had my share of time.	But they can go up.	Generally

24	speaking, you're right.	As the -- and I've shown plots

25	of this and I probably should have published them, but,

1	you know, if you plot let's say the T statistic of PM,

2	and then you start adding other X variables in that are

3	correlated with the PM, the PM T static goes down,

4	down, down, down.	It's directly proportional to the

5	inter-correlation of the X's.	So you're basically

6	putting another indexes of particle.	So, therefore,

7	you're able to drive it.	You can make it go away if

8	you want.	You put enough variables in that are

9	correlated with your -- and the presumption of the

10	model of course is that the X's are independent of one

11	another, and so you're slowly but surely violating the

12	assumptions of the model more, and more, and more, and

13	you're getting less and less meaningful.	What you can,

14	based on what I learned about regression from Collin

15	Begg, you can estimate the linear combination of them.

16	You can get a best linear unbiased estimate of the

17	multiple pollutants together, but the coefficients

18	become relatively meaningless and their statistical

19	significance the more the X correlation goes up.

20	That's what I was saying.	Does that help or does that

21	make it worse.

22	DR. POSTLETHWAIT:	No.	I think that

23	does help, but I got back to the picture paints a 1000

24	words that to somebody who is not familiar with those

25	aspects of the field, looking at that table, it sort of

1	presents a visual different picture than what you've

2	just explained.	And Rogene, are we going to include up

3	front the scientific definition of squirrely, so that's

4	a well characterized descriptor.

5	DR. HENDERSON: We're going to -- I'll

6	assure you we will not define squirrely.	I think what

7	I get from this discussion is really mainly what Jon

8	Samet said, that there needs to be a plan by which you

9	evaluate these studies so that's it's clear, you know,

10	what's going on it.	That you explain how they're being

11	evaluated and by a preconceived plan, and that's what

12	I've heard.	Lianne?

13	DR. SHEPPARD: Yeah.	I wanted to weigh

14	in on this.	This figure 3.1-11, these multi-pollutant

15	models are, as I understand it, for the effect of SO2

16	with all other pollutants that are in the model held

17	constant, right?

18	DR. HENDERSON: Yeah.

19	DR. SHEPPARD: Which is the point that

20	George was making really because the pollutants are

21	correlated and so there is an effect on the coefficient

22	when you add multiple pollutants in the model.	The

23	problem with interpreting this is that they are

24	correlated, and they move in the atmosphere together.

25	So it becomes very difficult to interpret, and you're

1	understanding the biological mechanism.	You could

2	argue that it should be the single pollutant model or

3	the multi-pollutant model that's of interest, and

4	different people will come down different ways and

5	probably again, as George was saying, the more

6	important, the more valid way of reporting it is the

7	joint effects under the assumption, which they in fact

8	do that both pollutants change in the atmosphere at the

9	same time.	And an example of that -- it's rarely

10	recorded in the literature, so you have a challenge

11	when you're reviewing the epi studies to report it that

12	way because you don't have the information.	And so I

13	understand that, but on page 3-7, 3.1-1 is an example

14	of a study where two pollutants were changed in the

15	model simultaneously and the reporting is for the joint

16	effect, which is what George was suggesting is really a

17	better way of reporting.	Now, of course this gets in

18	to the whole difficulty with the approach to regulation

19	where we regulate each pollutant separately, and of

20	course they don't behave in the atmosphere separately.

21	But they all -- so the epi studies, the interpretation

22	of the epi studies in the context of what has, the

23	effort that's being made in the document conflict, I

24	think.	But one thing that I think that you could do

25	would be to add a discussion explicitly to help people

1	understand the distinction between interpretation of

2	estimates when you hold all other pollutants constant

3	versus when you jointly change multiple pollutants at

4	the same time.	And since there are examples of both in

5	the document, it becomes even more important to make

6	that distinction so people don't mix up the

7	interpretation for Figure 3.1-1 with the interpretation

8	of Figure 3.1-11.

9	DR. HENDERSON: I think that's an

10	excellent idea.	I'm sure that I as a toxicologist am

11	misinterpreting here because it looks like the more

12	pollutants you have the better off you are.	I mean,

13	that's what, and I know that's not what's meant, so

14	there needs to be something to explain that.

15	DR. KIM: Yeah.	In the introduction to

16	Chapter 3 we put a very, very, very brief sort of

17	description of what we thought or some caveats about

18	the multi-pollutant models while citing the PM and the

19	ozone document, but I think what Dr. Sheppard suggested

20	is exactly what we'll consider.	And we'll probably

21	expand that discussion a little bit to bring out

22	perhaps more of the limitations about multi-pollutant

23	models and just the basis of what these models do

24	versus the jointly considering models.	But as far as

25	I'm aware, the Schildcrout et al. studies are the only

1	one that really considered co-pollutants jointly in a

2	model.	Are you aware of any other studies had done

3	that?

4	DR, BALMES: Yeah.	'Cause Lianne's on

5	that study.

6	DR.	HENDERSON: Was there a voice on the

7	phone?

8	DR. BALMES: It's John Balmes.

9	DR. HENDERSON: Oh, okay.	But I think,

10	were you addressing the question to Lianne or to --

11	DR.	KIM: Or anybody who is aware of

12	such studies?

13	DR.	SHEPPARD: Yeah.	I mean, there is a

14	-- I did a paper also in '99 that does joint effects,

15	but I don't know that it's that relevant to SO2 'cause

16	it was in Seattle where our SO2 monitors next to a

17	cement plant.	So I wouldn't really put much weight on

18	that study with respect to SO2.

19	DR. BALMES: Rogene?

20	DR. HENDERSON: Yes.

21	DR.	BALMES: Part of the reason I

22	entered is that I have to do a bronchoscopy in 10

23	minutes.

24	DR. HENDERSON: Oh, my goodness.	Oh, my

25	goodness.

1	DR.	BALMES: So I was hoping to -- I

2	know it's probably a little bit out of order here since

3	we're talking about epidemiology, but I'd like to --

4	DR.	HENDERSON: It's your turn, John,

5	just go right ahead.

6	DR.	BALMES: Okay.	Well, so shifting

7	gears to the toxicology for both human and animal

8	studies -- well really it's mostly animal studies that

9	I want to talk about because I found a bit disturbing

10	the text on page 327 and 328, which is trying to

11	summarize animal literature.	And if somebody has

12	mentioned this while I was off the phone, excuse me,

13	but this is trying to use animal literature to support

14	the limited epidemiologic data about SO2 effects on

15	airway hyperresponsiveness and allergy.	And starting

16	on line 20 on page 327, "There is a limited number of

17	animal studies also suggest acute SO2 induced increases

18	in airway obstruction and hypersensitivity in allergen-

19	sensitized guinea pigs and sheep."	The text following

20	this lead sentence does not support that statement at

21	all.	These are negative studies basically, the three

22	that are listed here, Douglas, Lewis, and Curtsner and

23	Scanlin with regard to the effect of SO2 on non-

24	specific agents.	It seems like that sentence might be

25	more appropriate for the top of page 328, but here

1	there is also a problem with interpretation because the

2	Redel study and the Park study actually are not about,

3	the aims of these studies was not to show that

4	previously sensitized animals respond differently to

5	SO2 but that SO2 enhances allergic sensitization.	So

6	the animals were actually exposed to SO2 for a few days

7	and then with continued co-exposure to SO2 sensitized,

8	and there was an increased sensitization rate in

9	animals exposed to SO2 compared to animals exposed to

10	control-filtered air.	So that's a different outcome

11	than actually is suggested by that lead sentence on

12	page 327.	Now the Kodomotachi and Abraham studies did

13	use previously sensitized animals and then looked at

14	their exposures to SO2, so those two studies do support

15	that sentence.	But I feel that sentence is really

16	given too much weight given the fact there's only two

17	studies that really support it.	So I think there's

18	some hand waiving or some misinterpretation of those

19	other studies, and I guess I'm concerned about that

20	because going down on page 328 there's a sentence,

21	"Toxicologic studies that observed increased airway

22	obstruction and hypersensitivity in allergen-sensitized

23	animals provide biological plausibility to the limited

24	epidemiologic evidence about SO2 and airway

25	hyperresponsiveness."	And that sentence is repeated

1	several places in the document, including, I believe,

2	in Chapter 5, on page 9, and I think that, you know,

3	toxicologic study, we're talking about two here.	So

4	it's -- and maybe that does provide biological

5	plausibility, but I think it needs to be put in

6	context.

7	DR.	POSTLETHWAIT:	John, can I

8	interrupt you for a second?

9	DR. BALMES: Sure.

10	DR. POSTLETHWAIT:	What do you think

11	about the issue of the toxicologic exposure

12	concentration in terms of being transmogrified so to

13	speak to the real world exposure situation?

14	DR. BALMES: Well that's always an issue,

15	and

16	I --

17	DR.	POSTLETHWAIT:	I mean, are you

18	comfortable with the statement that these specific tox

19	studies lend plausibility to the other?

20	DR. BALMES: Well, not really because I

21	think (a) there's only two that are cited and (b)

22	there's always the issue of dose response and

23	extrapolation across species.	You know, the Park study

24	isn't so far off the mark.	It's a 0.1 part per million

25	SO2, but the Redel study used, you know, much higher

1	doses.	So, yeah, I think it's an issue, and I actually

2	think there's very limited toxicologic evidence to

3	support the limited epidemiologic evidence.	I don't

4	think it's all that important in the greater scheme of

5	things because the agency is not going to use airway

6	hyperresponsiveness as necessarily the main outcome of

7	concern with regard to considering a new air quality

8	standard, but I do think the document needs to

9	appropriately assess the evidence.	And I think there

10	is limited epidemiologic evidence, and I think there is

11	limited epidemiologic evidence, and I think the

12	toxicologic evidence that provides biological

13	plausibility is extremely limited based on what's

14	reviewed here.	Now I didn't do a literature search on

15	this.	There may be more papers, but if this is a

16	fairly complete literature search, and we went back to

17	Dr. Abraham's work here at UCSF in the early '80s, so I

18	assume it's a fairly extensive review.	I think there

19	isn't very much to support biological plausibility

20	here.	So the other, there was another area where I had

21	problems with interpretation of the animal toxicologic

22	studies, and that's on page 342.	In the summary of ED

23	visits and hospitalizations for respiratory disease,

24	there's a clause at the end of a sentence about

25	biological plausibility, which says, "The animal

1	toxicologic studies that observed SO2 induced altered

2	lung host offenses."	And on page 330 I think is a much

3	more correct characterization.	You know, there is

4	little toxicologic evidence to support the observed

5	relationship between ambient SO2 concentration and

6	increased respiratory illnesses.	So this is, I mean,

7	I'm not aware that there's much literature that SO2

8	alters lung host offenses, so I think this statement is

9	actually wrong and should be deleted.	And I think that

10	comes up someplace else in the document as well.	And

11	my final point -- yeah.	It came up on page 345 at the

12	top of the first sentence.

13	My final point is that with regard to

14	the effects of long-term exposure on respiratory

15	morbidity, the section on lung function I think leaves

16	out an important longitudinal study, the Krakow study

17	with multiple publications where SO2 -- there was co-

18	exposure with particulate matter, and so the ability to

19	ferret out the SO2 effect versus the particle effect is

20	probably limited.	I would defer to some of my

21	epidemiologic colleagues, but I think that Krakow

22	longitudinal study is a study that at least needs to be

23	mentioned because it suggests that SO2 does have an

24	effect on or might have an effect on lung function.	So

25	I think it needs to be included there, and it's a

1	relatively strong type of study design, a longitudinal

2	study.	And then I have a lot of other more detailed

3	comments, which I put in my write-up.

4	DR.	HENDERSON: Okay.	That's good.	Now

5	Ila Cote is here to answer some of those questions, I

6	think.

7	DR. COTE: No.	I wanted to ask another

8	one.

9	DR. HENDERSON: Oh, you want to ask

10	another one.

11	DR.	COTE: So I can wait until there's a

12	discussion regarding it.

13	DR.	HENDERSON: Well --

14	DR. COTE: Okay.	One of the things I

15	heard alluded to or talked about in the comments, I

16	wanted to ask a specific question about because I hear

17	it internally in-house and that is if a toxicologic

18	study is not done at near ambient concentrations, nor

19	provides information on mechanism of action, or perhaps

20	insight into subpopulation, those are kind of the

21	three; if it doesn't give us one of those, does that

22	mean it doesn't provide us any useful information?	So

23	either it has to give us information around ambient

24	exposures, about mechanism of action, sensi-

25	subpopulations, or it doesn't really provide us with

1	useful information?

2	DR. HENDERSON: Well I'll make a stab at

3	part of that.	I think, you know, tox studies done at

4	very high concentrations you have to look at very

5	carefully because the mechanism of action may change

6	from exposures to high levels versus exposures to low

7	levels.	But that doesn't mean you don't take it into

8	consideration.	You look at it and say now what if we

9	lower the concentration of exposure?	Does this effect

10	still occur but, you know, in a diminished form?	And

11	you just use good judgment as to whether it is

12	informing you about mechanisms.	The mechanisms may be

13	entirely different an be deceptive.	They could be that

14	you can detect the -- you know.	A mechanism at a high

15	concentration that still occurs at a very low

16	concentration.	That would be my answer.

17	DR. COTE: What I hear embedded in that,

18	Rogene, if you don't have any insight into mechanism of

19	action, it probably, the study at least doesn't inform

20	much unless you have mechanism of action.

21	DR. HENDERSON: No.	I would say that

22	would be a big red flag if there's no evidence of what

23	the mechanism of action is.

24	DR. COTE: Okay.

25	DR. BALMES: So if I might say something

1	here, and I also want to make a correction to something

2	I said.	So those two studies that I said didn't

3	support the statements that was in the text about SO2

4	inducing hypersensitivity in allergen-sensitized guinea

5	pigs and sheep, the Redel and Park studies, they

6	actually did address an important endpoint that you

7	could have enhanced allergic sensitization because of

8	SO2.	Now NO2 and ozone have been shown to do this in

9	humans.	So I think it's important information on

10	potential mechanism.	It just wasn't properly

11	interpreted in the document.	And I just wanted to

12	correct what I said in response to Ed's comment.	Both

13	studies actually found effects at 0.1 part per million

14	for this particular endpoint, so they, I think, are

15	both at near ambient concentration and provide

16	important mechanistic information.	It just wasn't the

17	mechanistic information that was appropriate to the

18	point made in the text.

19	DR. PINKERTON: Rogene, this is Kent

20	Pinkerton.	If I could just make a comment to add on to

21	John's comment as well as yours.	I think that the

22	toxicological studies, yes, there is a concern when

23	they are at very high levels relative to ambient

24	concentrations or concentrations that we see in

25	epidemiological studies, but I still think that there

1	is some value there.	I believe that there is evidence

2	that suggests that we actually do need to use a greater

3	fold concentration of a pollutant in an animal model to

4	be equivalent to that seen in the humans.	And I think

5	that the way that Chapter 3 is put together, I think it

6	just would be better if there was more of a distinction

7	between animal tox and the human epidemiology.	Again,

8	I think it's a really good chapter.	I think they're

9	very important studies, but I think John has really

10	emphasized very nicely the importance of just making

11	that distinction in the document.

12	DR. HENDERSON: Okay.	Ila, have we been

13	helpful.

14	DR. COTE: Very.

15	DR. BALMES: I had one other response to

16	Ila.

17	DR.	HENDERSON: Okay.

18	DR. BALMES: Which really fouls from

19	Kent's remarks.	I think, I didn't catch in this

20	document any reference to extrapolation modeling at

21	all.	I might missed it, but the dosimetry section in

22	Chapter 2 is only on human dosimetry, and I think that

23	the piece that is missing here is the animals are,

24	often require, as Kent said, higher levels of exposure

25	to match the cite-specific exposure of the particular

1	xenobiotic agent that they're experiencing.	And I

2	don't know if there are any specific studies for SO2

3	that are available for doing this between animals and

4	people, but just generally speaking, Ila, I think that

5	the animal, when you're evaluating the value of an

6	animal study, it should not only be looked at from a

7	mechanistic point of view in terms of coherence but

8	also just the possibility that it gives dose response

9	information in the human if you can extrapolate the

10	date to equivalent doses.	And there is certainly a lot

11	of precedence in the scientific literature as well as

12	EPA's literature to allow one to see whether such an

13	evaluation is possible, and it wasn't done in this

14	document for SO2.

15	DR. HENDERSON: Thank you, Jim.	Terry?

16	DR. GORDON: Well I, per Ila's comment, I

17	truly feel that there is some dosimetry from the early

18	Ander's stuff that shows bronchial restriction from 1

19	ppm and up, and then as John mentioned, the two studies

20	that showed sensitization was enhanced from SO2

21	exposures even as low as sub 1 ppm.	But I feel the

22	mechanism really matters and 5 ppm, 32 ppm, the whole

23	discussion in Chapter 3 on the nervous system effects,

24	I personally think they should be removed.	I don't

25	think they're anything relevant to ambient

1	concentrations or health concerns we would have in

2	human populations.

3	DR. HENDERSON: Good point.	I guess I'd

4	like to let Ed talk.	We skipped you Ed for

5	John Balmes,but --

6	MR. AVOL: Well I just have three points

7	in addition to the written comments that I previously

8	submitted regarding this chapter.	So first I wanted to

9	commend the staff for not only including US-based

10	studies but informed their studies from around the

11	world, which I think is a real improvement over the NOx

12	document 'cause I think there is good work elsewhere.

13	So I think that's informative and helpful to the

14	overall review.	Secondly, I think there is both a

15	philosophical and a practical aspect to this discussion

16	of multi-pollutant models and including them here

17	because the agency is sort of, and the position and the

18	approach is sort of meant to separate out gases from

19	particles and consider these separately.	And here in

20	the multi-pollutant models really what we're talking

21	about is SO2 or sulfate or SO2 and PM, sort of the most

22	interest of the gases certainly because as George

23	pointed out, it is never just So2 alone or very rarely

24	anyway.	So really in a practical matter it is never

25	SO2 alone.

1	So I think, you know, I think you need

2	to face the issue of SO2 and particles and say

3	something about it because it does come up in some of

4	these multi-pollutant models.	And so I think it does

5	need to be addressed because you have this dichotomy of

6	sulfur dioxide and sulfate and sort of have made the

7	decision, or the decision has been made for you to keep

8	these separate.	So I think you have to face it.

9	Thirdly, I think just as a written text,

10	the title of Chapter 3 is Integrated Health Effects of

11	Exposure, and then is goes on to de-couple all the

12	health effects and list all of them and talk about

13	them, and it doesn't ever really get back to

14	integrating the health effects of exposure.	And so I

15	think in terms of trying to pull together the 100 pages

16	of that chapter, I think it would be useful to sort of

17	synthesize at the end what the message is.	I mean, I

18	think it's appropriate inside to look at each of these

19	pieces, but it doesn't quite come back all together

20	again.	So I think you need, it needs something.	It

21	needs a section or a couple paragraphs at the end that

22	pulls this back together.

23	DR. KIM: I guess just a quick response

24	to the integration part.	The only area that we

25	intended to make an integration was for the respiratory

1	morbidity because that was where we felt the strongest

2	evidence existed in our conclusion that there was a

3	likely causal relationship.	And I think we have that

4	after the short-term respiratory morbidity section,

5	but, I mean, we'll definitely work on improving that

6	section.	But did you feel that we need to integrate

7	the other outcomes as well?

8	MR. AVOL: Well I think you point out a

9	lot of outcomes, and I think in some way if you're

10	going to integrate what we understand about the health

11	effects, we ought to say, you know, maybe with the

12	redefinition or the redefining of what the criteria

13	priorities as Jon Samet spoke about earlier would help

14	to give a framework for this.	But I think at the end

15	of the chapter we sort of need to say here is the 25

16	different outcomes we looked at.	This is what we

17	believe either in some sort of table or some sort of

18	summary so that a reader, someone trying to assess all

19	that we know now in 2007/2008 about sulfur dioxide in

20	human exposure, what do we believe to be the health

21	impacts.

22	DR. HENDERSON: I think that's a very

23	good idea.	That would be very helpful.	Now is that

24	something that seems possible for you?

25	DR. KIM: I think so.	I think we have

1	some, a little bit of that we started in Chapter 5, but

2	we could probably pull it out and do a little bit more

3	detail of it in Chapter 3.

4	DR. HENDERSON: I see.	Yeah.	It may be

5	in a separate chapter.	Okay.	Yes, Ron.

6	DR. WYZGA: I guess in my written

7	comments I gave you a list of studies that were

8	included that you should look at.	Some of them are

9	recent studies and other ones were basically SO2 was

10	sort of a foot note because it did not come up.	The

11	findings were negative, and, therefore, it was just

12	sort of mentioned but not given prominence.

13	But the other thing, I want to go back

14	to something that George Thurston raised earlier.	I

15	think there's tremendous value in a lot of human

16	clinical studies.	They're old, but there was a lot of

17	them that were undertaken; and they gave us a lot of

18	information.	We have a good sense of who was

19	responsive, at what levels they were responsive, under

20	the conditions under which they were responsive, and

21	how these responses were modulated by differing and

22	alternating environments.	And I think that although,

23	you know, it doesn't make any sense to go through these

24	studies one by one, I think at least some reference,

25	overall reference to them and a good summary of what

1	they told us would be particularly helpful as we try

2	and interpret some of the results from the

3	epidemiological studies.	Unfortunately, I think the

4	error of the human clinical studies in this area has

5	diminished greatly, so we don't really have much in

6	terms of new studies there.	But I think we really need

7	to take it down to the old studies.	They were good

8	studies.	We knew what the exposures were.	We didn't

9	have to worry about confounders, and, therefore, I

10	think the results had a lot of credibility and could

11	really help us in the future.

12	DR. KIM: I think we've already

13	considered that and are in the process of preparing a

14	table with the older studies.

15	DR. HENDERSON: Thank you.	Yeah, Jon.

16	DR.	SAMET: Just one comment about the

17	clinical studies.	I wrote one of my many ignored

18	papers along time ago, in which I looked at the

19	selection of people into the clinical studies and

20	looked for the distribution of FEV-1 in comparison to

21	the six city study and just to remember.	And I think

22	this is relevant.	I mean, healthy people were enrolled

23	in these clinical studies by and large.	I mean, I

24	think lots of college students at UNC for example in

25	California schools.	So I think in terms of

1	interpreting those studies, they may be providing a

2	look at effects in perhaps a less susceptible

3	population.	So in interpreting it, you should keep

4	that in mind.

5	DR. HENDERSON: Very good point.	Now I

6	-- yeah.	Go ahead.

7	DR.	GORDON: Jon, I was thinking the

8	same thing, but I was thinking the other extreme,

9	having been at UCSF when they were doing some of the

10	asthmatic sO2 studies and they tended to get some, you

11	know, more moderate and moderate severe asthmatics than

12	the milds.	That just happened to be, just happened to

13	be the patients who volunteered.

14	DR. COWLING: And in both cases about a

15	third of them respond.

16	DR. HENDERSON: Are there others who

17	would like to comment on Chapter 3?	Yes, Lianne.

18	DR. SHEPPARD: Yeah.	I'm concerned that

19	the ISA review and also the annex summaries gloss over

20	some very important subtle issues that affect the

21	analysis and interpretation of the studies.	I'm not

22	really sure completely how to fix this, although I have

23	a few suggestions.	I mean each study has really unique

24	strengths and weaknesses, and some of them are shared

25	by the design or the exposure data or the software

1	that's used to analyze.	But some of them are unique to

2	the individual study, and somehow we need to figure out

3	how to summarize complex, this complex set of features.

4	And I think one of the things to do is to expand the

5	details in the summary of each study and to follow a

6	strict protocol for reviewing, summarizing, and

7	evaluating each study, individual study, and expanding

8	upon the limited, on the list of detailed information

9	that's summarized on page 1.6 of the criteria document,

10	I mean of the ISA.	I think that some additional

11	information that's needed are characteristics of the

12	monitoring data that's used in the study, the specific

13	study design because that has implications for

14	interpretation.	Some are weaker.	Some are stronger

15	designed.	The summary of the analysis approach and the

16	key features of that particular analysis, for instance,

17	subtle issues in case crossover studies about whether

18	you use a time-stratified referent or symmetric

19	bidirectional referents have important implications for

20	interpretation; that's just one example.	The

21	description of the population selection criteria, any

22	major limitations or issues with the study, and then

23	discussion of the strengths, and weaknesses, and key

24	features.

25	Now that sounds like a huge amount to

1	add to the annex, and I realize how much work that

2	involves.	But I'm worried that there are important

3	issues that get lost, and sometimes we're focusing on

4	aspects of studies that should get more or less weight

5	if we really better understood what it was about an

6	individual study.

7	Give you an example, the Schildcrout et

8	al study, since I'm a coauthor on that, and I would say

9	that it's stronger than other panel studies of its type

10	because there's additional control for confounding

11	that's provided by the way the within city modeling was

12	done, and the estimates of the odds ratios, and it's

13	fairly unique focus on the joint effects of multiple

14	pollutants at the same time, which we already

15	discussed.	One of the things that's missing from the

16	summary of that study, for instance, is the average

17	number of observations per subject and some unique

18	details about the analysis.	For instance, I think the

19	minimum number of days for each subject was 30 and that

20	could have been in any season and that structure that

21	varied a little bit across the cities, and that could

22	have implications for interpretation of the results.

23	Another important feature of that study in terms of

24	interpretation is there's extensive imputation of the

25	PM data, which I would then, therefore, probably down

1	weight somewhat the interpretation of the PM results,

2	and there is also very limited availability of ozone

3	data because of the seasonal nature of the monitoring,

4	which, again, would affect interpretation of the ozone

5	results.	And in SO2, which the citing of the monitors

6	is important, for instance, again in Seattle, which is

7	one of the cities in that study, the monitor is next to

8	the cement plant.	So that's, the role of that cement

9	plant exposure is, comes into play.	So those are just

10	some examples for one particular study.	I recognize

11	the enormity of this request, but somehow I think these

12	important subtle issues need to be brought forward

13	better.

14	DR. HENDERSON: Does NCEA have any

15	questions for clarification of Lianne?

16	DR. KIM: I guess what our response would

17	be is that we'll make an effort, especially starting

18	with the studies that we highlight and decide is key

19	and move on from there.	Thank you.

20	DR. HENDERSON: Okay.	Dale?

21	DR. HATTIS: Yeah.	I think, I just

22	wanted to point out that I appreciate your putting in

23	Figure 3.1-6, which you also put in your slides showing

24	the individual thresholds for response as defined as

25	doubling of the specific airwave resistance for the 27

1	individuals in the Horseman study, but I think you have

2	a little bit of an opportunity to go a little further

3	in the analysis of that, and I basically tried to do

4	that as best I can from the data you	presented.	In my

5	Figure 2 on page 57 of the combined panel comments,

6	which shows basically a log-probit plot of those same

7	data, and basically it suggests that it supports the

8	general idea that the population distribution of

9	thresholds for this kind of response is roughly log

10	normal, and that allows you, in fact, to do some dose

11	response and population response projections in your

12	subsequent work.

13	There is a wide variability and

14	exposure, but it turns out that one of the pieces of

15	information you get from this plot is, in fact, that

16	the extent of variability from this study is not so

17	great as is present in the cases of many other kinds of

18	pollutants that also cause twitchy airways like

19	methacholine and other receptor-based agents.	So it's

20	not at all unusual.	You can get an estimate.	If you

21	also did the same kind of thing for other studies where

22	you also have panel studies with individual data, you

23	might be able to get a more coherent overall view of

24	how variable this kind of response is in the population

25	effects of exercising asthmatics, however many there

1	are of those.

2	DR. HENDERSON: Okay.	Would you like a

3	response here?

4	SPEAKER: No.	I just wanted to thank

5	you, Dale, for doing that.	And one of the things that

6	we're doing is we're going back and looking at all of

7	the studies that have reported individual data so we

8	can get some kind of data set with that, and we're

9	working with OAQPS on doing that right now.

10	DR, HATTIS: I also think it's probably

11	in order to try to compare the amount of variability

12	that you see here with that for other studies, and

13	basically I've assembled the similar data from other

14	kinds of direct irritants that I've compiled in our

15	inter -- human inter-individual variability database.

16	DR. HENDERSON: Okay.	Are there other

17	comments on Chapter 3?

18	DR. THURSTON: Well just briefly, I think

19	this is where we need to do what Jon Samet was talking

20	about and a lot of us have talked about in our comments

21	to lay out right at the start the criteria that will be

22	used, you know, and as I suggested with the NOx

23	document, the place to start is Hills criteria and go

24	through those, you know.	I think clarifying the

25	distinction between causality and biological

1	plausibility and all of these things that are sort of

2	bandied about at the end, and I like the idea of the

3	way they're trying to do it.	But I think they just

4	need to do the ground work here in Chapter 3 and lay

5	out right at the beginning how they're going to

6	evaluate causality at ambient levels, and I think

7	that's, that's the question, isn't it?	That's what

8	we're talking about, not causality at, you know, very,

9	very high levels, you know.	The high levels give us

10	insight into, you know, the toxicology studies.	The

11	human clinical studies give us insight into the

12	biological plausibility, but ultimately causality we

13	need everything and not just one part of it.	And I

14	think that's, you know, the best way to do that is here

15	in this Chapter 3 right at the beginning and then go

16	from there.

17	DR. HENDERSON: Terry?

18	DR. GORDON: Yeah.	Lunch is near so just

19	two quick comments.	The first one is I think it was

20	Ellis who brought it up at the NOx ISA review is that

21	the figures should really stand on their own.	I

22	continually, as a toxicologist I didn't know what

23	certain values were until I went down the hall and

24	asked George.	Secondly, in a couple of the

25	epidemiology studies it would give the annual means

1	ranging from 0.9 to 4.8 part per billion and then would

2	give a relative risk per increment of 10 ppb.	I didn't

3	know.	I mean, toxicology, you know, we would never do

4	that.	I don't know how that was done.	Is that normal

5	or did I just misread what the range was to have a

6	relative risk of something larger than your actual

7	range?

8	DR. KIM: Yeah.	The 10 ppb was selected

9	as -- we worked with OAQPS on this -- but it was

10	selected to sort of represent the median to 95th

11	percentile change for the recent years, 2003 to 2005.

12	We understand in some of the studies, like I think

13	there's an Australian study where you never get 10 ppb,

14	and in those studies, I think, we try to make an effort

15	to note that.	In other ones we feel that even though

16	the mean may be less than 10 ppb, there would be a

17	distribution of 10 ppb across the data within the city.

18	I guess that's why we felt that, that was a good

19	increment to use.

20	DR, HENDERSON: Okay.	Yes, go ahead,

21	Lianne.

22	DR. SHEPPARD: I just had a quick

23	question and that was do you think it's possible in

24	some of these published epi studies that use multi-

25	pollutant models to get the relevant parameter

1	estimates so that you could actually calculate joint

2	effects and say a change in PM and SO2 simultaneously?

3	I mean, you wouldn't be able to get that directly from

4	the papers to have to go back to the authors, but I

5	wonder given some of the discussion we've had about

6	multi-pollutant models if it would be worth exploring

7	whether that's feasible for not.

8	DR. KIM: I guess we'll make an effort,

9	and the only thing that we should note is that our

10	second draft is due in April, and we'll, I mean, we'll

11	make an effort to at least consider some of the key

12	studies that we've discussed repeatedly in the ISA to

13	contact those authors and try to get some information

14	from them.	But if you could put all this in your

15	comments, that will be great.	Thank you.

16	DR. HENDERSON: Yes.	I think it's time

17	to break for lunch.	The panel has their lunch next

18	door where we had breakfast, and let's come back at

19	1:15.

20	DR. HENDERSON:	ay.	We are going to

21	start our afternoon session after a wonderful lunch.

22	More food than we needed for sure.

23	SPEAKER:	Don't say that.

24	DR. HENDERSON:	Oh, don't say that.

25	We may get less food. Well try not to go to sleep is

1	all.	We're going to start out with comments now on

2	Chapter 4 and Terry Gordon is going to be the lead

3	person on that.	So do we have the NCEA people here?

4	Are we okay, Mary?	Okay, Terry.	You're on.

5	DR. GORDON:	All right.	So it's

6	Chapter 4 and charge question number seven.	So I sort

7	of feel that the respiratory facts that were

8	identified, the hospital admissions, ER visits, acute

9	bronch constriction were correctly identified,

10	discussed, and pretty well justified in the ISA.	I

11	think there is some general editing that is needed for

12	better integration with Chapter 4 and with Chapter 3.

13	Some study descriptions were repeated in both chapters,

14	but the majority of this repletion could be justified

15	because of the goals of Chapter 4.	And I think this is

16	particularly important for the section on concentration

17	response data, but there's at least one instance where

18	a study was discussed in detail in Chapter 4 that

19	really wasn't discussed in Chapter 3.	I thought

20	Chapter 3 was feeding Chapter 4.	Regarding

21	the concentration response discussion, it is really

22	very good in some sections, but then it is less so in

23	other sections.	And it might be a matter of

24	wordsmithing, but it's probably just as likely it's the

25	lack of good exposure response data for some of the epi

1	studies; so if you're a little more clear on that, then

2	it will read better.	So it's not the text but it's the

3	data.

4	The next version of the ISA, the second

5	draft, I think it should state more explicitly whether

6	effects are seen or if they're not at the current

7	annual mean and 24-hour time frames, potentially at the

8	5 and 15-minute time range.	It's one of the key

9	questions stated in Chapter 1 of the ISA, and it asks

10	at what SO2 levels do adverse health effects occur.

11	And it would be appropriate to directly answer this

12	question and to do so as fully as possible.	And I'm

13	sort of guessing it would be in 4 because 4 is talking

14	about the potential health impact, but maybe I'm wrong,

15	answering it in Chapter 5 is okay.

16	So the section in general tends to be

17	focused on discussion of evidence for threshold, and

18	they key point should be focused, I think, less on the

19	negative that there's inconclusive evidence for a

20	threshold effect, which is the final summary statement.

21	It should be more in the positive, that it looks like

22	roughly there's a linear response, and the effects may

23	be occurring below the current max.	And this is the

24	key information to feed into public health impact, or

25	at least into Chapter 5.

1	Then regarding the inclusion of the

2	susceptible subpopulation, and I saw in some other

3	people's comments, things integrate between Chapter 3

4	and 4 loosely sometimes.	And I think they have to be

5	improved, and when I looked at the susceptible

6	subpopulation, of course there was a bunch on asthma

7	and age, as it should be.	And then there was a large

8	section on the genetic susceptibility, and I'm not sure

9	all that should be in Chapter 4.	So part of me was

10	wondering why there is a Chapter 4 because I didn't see

11	why if asthma, and age, gender, everything was

12	discussed up front in Chapter 3, why was it rediscussed

13	in Chapter 4 along with the genetic susceptibility

14	issues.	It just was odd to have it in both sections.

15	That's it.	Small comments but they're

16	in my detailed comments.

17	DR. HENDERSON:	Does NCEA have

18	anything to say or is that it?	We don't require a

19	response, but if you had any clarification questions.

20	SPEAKER:	No, thank you.

21	DR. HENDERSON:	I was looking down. I

22	couldn't see.	Okay.	Let's get Dale Hattis.

23	DR. HATTIS :	Yeah.	I want to second

24	what Terry just said, but I want to go a little bit

25	further, at least in the projection of incidences of

1	effects with some fairly heroic assumptions that are

2	indicated by the current data.	Basically what I had

3	done previously is showed distributions of the

4	concentrations of the monitors at various levels for

5	one-hour exposures, and the apparent distribution of

6	the individual thresholds for response as indicated by

7	the Horseman 1986 data.	We can now put those two

8	distributions together and make an inference as, you

9	know, with some heroic assumptions, how big of an

10	effect would you expect and what concentration range is

11	it likely to be happening at.	So just the Horseman

12	data itself suggests something like 3 in 1000 effect at

13	100 parts per billion and somewhat less.	So basically

14	I think the discussion of threshold should be not a

15	single population threshold because I think it's

16	implausible that there's a single population threshold

17	that is a level below which nobody is affected.	But

18	you can talk in terms of a population distribution of

19	thresholds that essentially is estimated by the inverse

20	of that probit slope that can be derived.	So I think

21	basically, you know, why should there be a single value

22	below which nobody is affected?	There's not

23	particularly physical justification for that.	It's

24	much easier to believe that just basically there's a

25	continuous variable distribution of thresholds.

1	Anyhow, if you take the two

2	distributions derived together, then essentially, and

3	you basically say, okay, for each -- if you make the

4	assumptions that the distribution of concentrations,

5	one hour peak concentrations per day at the CMSA

6	monitors represents the population, which is not so

7	clear, but it's, you know, one basis for starting to

8	think about stuff.	And you assume that the population

9	of distribution of exercising asthmatics in the

10	Horseman study represents the individual

11	susceptibilities, then you can, by putting those

12	together, you can get the results that I show in Table

13	6, which is on page 60 of your comments.	So

14	essentially what you have here is a upper end of the

15	concentration interval in parts per billion on the left

16	hand said, and basically what you see on the right hand

17	side is the cumulative total fracture of days where you

18	would expect at least one response of the level of

19	severity as seen in that Horseman study.	Basically

20	what you get is something like three times instead of

21	the minus fourth incidents of response at that level

22	over the whole distribution.	And the other interesting

23	thing is that half or more of the total cumulative

24	response is happening above 130 parts per billion, and

25	that may be surprising to you because there's not very

1	many cases where there's, you know, one-hour

2	measurements that exceed that level.	But the point is

3	the variability in the exposure distribution is much

4	late4r than the variability in the population

5	distribution of responses.	So that means that the

6	exposure variability dominants what's happening when

7	you bring the two distributions together.	Anyhow, so

8	this can be improved but it can be done.	And I would

9	suggest something of that sort integrates the

10	variability in exposures and effect incidents.	And

11	that's part of what could be done in a chapter, in a

12	revised Chapter 4.

13	Now I've actually avoided the more

14	serious problem, which is how do you use those

15	epidemiological data; and I don't have a good answer to

16	that because I am not totally convinced that the SO2 is

17	causal in some of those epidemiological findings, but

18	I'll defer to my colleagues to make a better, offer EPA

19	some better advice on that.

20	DR. HENDERSON:	Okay.	Thank you,

21	Dale.	Steve Kleeberger sent an e-mail saying he

22	couldn't participate, right?

23	SPEAKER:	Right.

24	DR. HENDERSON:	We just heard from

25	his this morning.	So let me open this up then to

1	anybody who wants to comment on Chapter 4.	I would

2	like for NCEA, since the point came up.	Terry Gordon

3	said why have 4 in addition to 3.	You want to explain

4	that?	Just what is the difference?	What are you

5	trying to achieve and what you didn't do in 3?

6	DR. ROSS: Well that's an interesting

7	question, and I was just checking with Dr. Young

8	because this came up for the NOx document too, a lot of

9	questions about whether to separate 3 and 4.	The

10	intent was to characterize the health evidence in 3

11	over a range of endpoints, and then Chapter 4 was just

12	characterizing the sort of the susceptible populations

13	that come out of the health evidence and the size of

14	the susceptible populations.	Some general implications

15	about public health impact.	And I remember we asked

16	about, questions came up about whether to just move all

17	that evidence back into Chapter 3 and essentially lose

18	Chapter 4.	And that's something we were interested in

19	your feedback on too because it's something we would

20	certainly consider.

21	DR. HENDERSON:	And in NOx did you

22	call it the vulnerable populations or something?	You

23	had a different title; is that right?	In fact, this

24	has a lot just on the vulnerable populations.

25	DR. KIM:	The major difference

1	between this Chapter 4 and the one in NOx is that

2	there's a more extensive constitution response function

3	section in this document then there was in the NOx

4	document.	And the other one was called susceptible

5	vulnerable populations, and it focused on that

6	specifically.

7	DR. HENDERSON:	Do people have

8	comments on this?	Does anybody have --

9	DR. SPEIZER:	Yeah.	I just would

10	want to say that there's an opportunity to go further

11	and say, okay, now let's integrate in not only the

12	concentration response function but some information

13	about how, you know, what is the concentration

14	distribution in the places where people are.	That

15	could provide integrated conclusions about potential

16	public health impact.

17	DR. HENDERSON:	Do other people have

18	comments?	Okay, Ed.

19	MR. AVOL:	I had a little bit of

20	trouble with this chapter because, again, it seemed to

21	me the separation of what was presented here with the

22	previous chapter was not quite so clear.	A lot of what

23	was presented in the previous chapter showed up again

24	here, and there were some things that were here that

25	seemed to me logically should have been in Chapter 3.

1	It seemed to me I agree and accept the concept of the

2	chapter about public health impact, but that's sort of

3	different than health findings through the health

4	evidence.	And so the impact I think is more along the

5	lines of what Dale was talking about, sort of what

6	populations are exposed and what the concentrations are

7	for those and sort of down that line with the previous

8	chapter sort of setting out what we know about the

9	health outcomes.	And so I think in that sense there's

10	a good reason for having a public health impact

11	chapter, but that it ought to be a separate, slightly

12	different.	In essence, I think it sort of missed the

13	mark the way it is now.

14	DR. HENDERSON:	Okay.	Well, John had

15	something and then Lianne.

16	DR. POSTLETHWAIT:	I think my

17	comments largely follow on those of Dale around this

18	issue as a concentration response, which is critical to

19	the public health interpretation in making decisions

20	about what the risks are.	I guess I think that you

21	probably need to think more critically about the three

22	potential types of evidence there are to address

23	concentration response relationships, the

24	epidemiological data, the clinical studies, and other

25	toxicologic understanding of what mechanisms maybe

1	operative.

2	With regard to the toxicologic

3	mechanisms, there's information on SO2 and then we're

4	left with this idea that SO2 is a surrogate for

5	something.	We don't know what it is, so I'm not sure I

6	know what the mechanisms are, but you probably at least

7	ought to say that.	And then on the clinical studies

8	they're at a particular concentration range, and you

9	have additionally with that the question of

10	susceptibility.	Then I think you have to take a very

11	critical look about what epidemiological studies can

12	tell us about the likely existence of either thresholds

13	or the shape or the dose response relationship at lower

14	and lower levels.	Clearly they are less and less and

15	not particularly informative.	And for those of us who

16	have tried to look at alternative models and use model

17	fit as a guide, we don't think we learned very much

18	even from larger bodies of data then is represented in

19	these studies.

20	I think this section needs to go deeper

21	and then maybe come to some sort of closure on these

22	issues as both for part for Chapter 5 and then for the

23	risk assessment.

24	DR. HENDERSON:	Okay, Lianne.

25	DR. SHEPPARD:	Yeah.	I just wanted

1	to echo comments of others that I think there's an

2	important role for this chapter, but to step back and

3	rethink what it might be.	And with that, I think an

4	important point that came out in Chapter 3 that needs

5	to be brought forward in this chapter is discussing the

6	variable sensitivity of the population, the presence of

7	responders basically.	And that's really an important

8	issue for regulation, and we haven't figured out how to

9	define a subgroup based on characteristics yet, but

10	that doesn't mean that it's not important.	And it

11	really needs to be brought forward in this chapter

12	because of it's importance for regulation.

13	DR. HENDERSON:	Okay.	Are there

14	others?	Yeah, George.

15	DR. THURSTON:	You know, I concur

16	with what everybody's been saying here.	I was thinking

17	especially of Dr. Samet's comments about the

18	concentration response function and the opportunity you

19	have here, especially to reiterate the point about to

20	what extent is that function changed by the co-presence

21	of other pollutants.	And Ron was saying that they've

22	got lots of research that's been done, funded by EPRI

23	that's not reflected here that has to do with looking

24	at sodium chloride parts, so more studies like the

25	Koenig study.	Is it Koenig?	That's the way she

1	pronounced it, right? Koenig studies.	So in other

2	words you have this slope but then how might exercise

3	and other particles change the slope there and also

4	make it reach further down than you might expect.

5	There was in there some studies that seemed to show

6	effects of like 200 ppb.	I think that was Jane's study

7	when she added particles.	I think that was.	It was

8	like .2.	So you might end up wanting to extend the

9	relationships that you're finding at the higher levels

10	down to lower levels based on other studies that you

11	have evidence of how much the effects might be extended

12	down to lower concentrations based on factors like

13	exercise and co-exposure to particles.	And, I mean,

14	that's a lot of work, but I think it's worth taking a

15	shot at in here under the assessment of concentration

16	response and potential thresholds.	And then, of

17	course, looking at the epidemiology and, you know,

18	ultimately those are the slopes that you're going to

19	want to probably end up using for any kind of risk

20	estimation, and then, you know, do they make sense vis

21	a vis what you see from the controlled studies; I mean,

22	you know, trying to bring the two together to see if

23	they're consistent.	You know, we have to look at all

24	the information as Jon was saying.

25	Is there something else?	There was

1	something else, but I too have lost what I was going to

2	say about that so I'll pass.	I'll cede my time back to

3	everyone else.

4	DR. HENDERSON:	Okay.	Ed has

5	something to say?

6	MR. AVOL:	I just had one specific

7	comment.	In the last page of the, it's 418-419,

8	there's a paragraph that talks about information from

9	the CBC about asthma in the United States, and its goes

10	on and explains about the incidents among children and

11	so forth.	But it seemed to me, I think where you're

12	going with that was that asthma is a continuing growing

13	problem and we know that SO2 asthmatics, the previous

14	chapters have demonstrated some issue of concern in

15	terms of susceptible populations, but you never quite

16	link that back to SO2.	So I was sort of left waiting

17	for one more sentence or a couple more sentences, or

18	something, but it sort of just the paragraphs about

19	this is sort of what we know about asthma in the United

20	States sort of just hanging there.

21	DR. GORDON:	Well, as we ask for more

22	and more information I'm wondering, especially on the

23	dose response, how much are we going to start, can we

24	start asking for that in this chapter and then there's

25	the health assessment plan?	Is that all supposed to be

1	in there?	I don't know what the demarcation is.

2	DR. ROSS:	The document you're going to

3	refer to tomorrow, the risk assessment and the exposure

4	assessment is a separate pieces that's done by OAQPS

5	that will build upon what's in the integrated science

6	assessment.	I think we can look at the concentration

7	response function.	I think we've tried to do that, and

8	there's limited -- I guess I'll ask for what evidence

9	is available that you know of beyond what we have in

10	the epidemiologic studies for interpreting this?

11	DR. HATTIS:	Well, these are clinical

12	studies.

13	DR. ROSS:	The clinical studies.

14	Exposures generally don't match up with the epi

15	studies, so in terms of --

16	DR. HATTIS:	No.	So you can't do,

17	you can't really hope to get direct evidence from the

18	clinical studies, but you can, dare I say, project or a

19	less polite word is to extrapolate.	And, you know,

20	it's fairly straightforward to do that, and in other

21	walks of life risk assessors do that a lot with more or

22	less a claim from the rest of the scientific community.

23	But, you know, it can be done and it's how you can make

24	estimates.

25	DR. HENDERSON:	Okay, Pat.

1	DR. KINNEY:	I just wanted to quickly

2	reiterate the point George has been making about the

3	Kernig et al 1990 study.	That's on page 3-22 for those

4	of you who want to try to find it.	But, I mean, it

5	seems very relevant to Chapter 4 because .2 ppm SO2 for

6	just 15 minutes, it was actually after a .12 ppm ozone

7	exposure for 45 minutes.	It wasn't part of a ozone,

8	but, I mean, these are fairly relevant concentrations,

9	fairly short durations, and they had a significant

10	effect on asthmatic adolescents on SEB1.	So it was

11	kind of a nugget that got lost, I thought, in the

12	chapter and didn't get brought forward.

13	DR. HENDERSON:	Thanks, Pat.	Are

14	there others who would like to comment on Chapter 4?

15	DR. THURSTON:	Could I just interject

16	that the study I was talking about actually was on the

17	bottom of 315.	Jane's done a lot of work.

18	DR. KINNEY:	Oh, okay.	Sorry.

19	DR. THURSTON:	Yeah.	Well that's

20	important too.	That study should be looked at as well,

21	but what I was referring to was NACL.	And as I say,

22	you know, to reiterate, maybe you should conference

23	with Ron Wyzga because, you know, I think a lot of good

24	research was done, you know, over the last half a

25	century or so and some of it's still relevant, very

1	relevant, and we ought to be looking for those nuggets

2	of really good studies that teach us something.	Who

3	was it?	Was it you were saying about the particular

4	studies we should be looking for?	Maybe it's worth

5	reiterating that quote you had from the original letter

6	telling us what to do.	It was, it gave us some

7	guidance about which studies to, you know, it wasn't

8	just the new studies.

9	DR. COWLING:	The thing that George

10	is referring to is the reference that we wrote up and

11	I've communicated more than once, but it has to do with

12	what scientific evidence or scientific insights.	I

13	think that the possibility that these older studies

14	that were interpreted with a limited frame of reference

15	at that time might be reinterpreted and come to new

16	insights even though the evidence has not been changed.

17	I think that's a pretty important adjustment.	It's not

18	just new studies but new insights about older studies,

19	which is the point I think you're making.

20	DR. HENDERSON:	Okay, Dale.

21	DR. HATTIS :	Yeah.	Following right

22	along on that point, see in the old days people

23	analyzed and assessed sensitive subgroups, and the

24	implicit assumption in some of those analyses was that

25	the sensitive subgroups were themselves uniformed; and

1	that's now known to be wrong as you can see by the

2	Horseman and other work.	The sensitive subgroup is in

3	fact itself quite variable in it's individual

4	thresholds.	So now with that understanding, you can

5	reanalyze those old data, particularly those for which

6	you can harvest individual information.

7	DR. HENDERSON:	Thank you.	I think

8	now we might -- I don't know what's happening outside,

9	but I hope it doesn't affect us.	Chapter 5 --

10	DR. SHEPPARD:	Rogene?

11	DR. HENDERSON:	Yes.

12	DR. SHEPPARD:	I just had one more

13	comment.

14	DR. HENDERSON:	Go right ahead.

15	DR. SHEPPARD:	In thinking about how

16	to revise Chapter 4, it might be helpful to think about

17	what aspects of the analysis that I asked for in

18	Chapter 2 with respect to the exposure data could be

19	brought forward with respect to public health impact;

20	that might help frame some of what you need to do.

21	DR. HENDERSON:	Okay.	Any questions

22	from NCEA on that?

23	DR. KIM:	Just to sort of feedback

24	what we heard, I guess my understanding is that for

25	Chapter 4 you'd like to see more of sort of a separate

1	description of the interindividual variability response

2	and separate that out a little bit from the

3	constitution response function information we put in

4	for epi and then pull some of the susceptible and

5	vulnerable population data regarding age and asthma

6	status back to Chapter 3 where we could perhaps make

7	stronger, where we could make more conclusive

8	statements in that chapter versus here.	And then try

9	to really focus more on the public health impacts by

10	bringing in the exposure and the constitution response

11	function information; is that what we're looking for

12	here?

13	DR. HATTIS:	I would say yes.	And

14	when you start thinking along those lines, you start

15	thinking of other questions slightly.	For example,

16	there are diurnal cycles in peoples' exercise and

17	breathing rates.	So people are more active as a

18	general matter during the day then they are at

19	nighttime.	Well does it happen also that the peak

20	concentrations of the SO2 are more common during the

21	day than nighttime.	I don't know that but it's

22	possible.	But it's one of the things you could ask

23	your exposure folks that might be relevant to your

24	calculation at the end.

25	DR. HENDERSON:	Okay.	Then let's

1	move on to Chapter 5, which is a very important

2	chapter, key findings and conclusions.	Doug, you're

3	heading up that group.	Are you ready to go?

4	DR. CRAWFORD-BROWN:	Sure, be happy to.

5	Well, this follows on a comment that Donna made

6	earlier, which is that this version of Chapter 5 is

7	much better than the NOx version of Chapter 5.	If you

8	remember the issue with NOx was partially that we

9	weren't even convinced that the chapter by analog in

10	NOx brought the most important conclusions forward from

11	the earlier chapters.	This thing, I think I would say

12	that this version does bring forward the most important

13	the most important conclusions from the earlier

14	chapters, and it doesn't put a bunch of extraneous

15	conclusions into it.	So that seems to be quite an

16	improvement.	And so I'm really toying with the

17	following sort of issue.	The earlier chapters I feel

18	do draw within the caveats that we've talked about

19	here, the right conclusions from the information,

20	within those caveats, right.	And then those most

21	important ones are brought forward into Chapter 5.

22	What's missing in Chapter 5, and I don't know whether

23	it even should be in there, but what is missing in

24	Chapter 5 is a summary that points the next user, which

25	is the sort of risk assessment side, towards particular

1	answers to particular questions that the risk assessor

2	is going to ask.	Now the reason I say I'm not sure I'm

3	going to push this entirely is you could make an

4	argument that, that's not the purpose of the ISA.	The

5	ISA is not to figure, the purpose of the ISA is not to

6	figure out the answers to particular questions that a

7	risk assessor is eventually going to ask but is instead

8	just there to provide the basic scientific information

9	that might be used for any sort of risk assessment

10	question.

11	Now the reason I, the reason I raise

12	this is if I'm a risk assessor coming into Chapter 5,

13	what I'm hoping to find in there is a compendium of the

14	effects that I need to consider.	Okay.	I don't have

15	to go back into earlier chapters.	I've got a listing

16	that says, okay, these are the five effects that you

17	really need to think about.	Then what I'm looking for

18	is what do I know about the sensitive subpopulations

19	for those effects; that's kind of in there.	Then what

20	do I know about what the concentrations at which those

21	effects occur, and I'm expecting to find kind of an

22	exposure response relationship in there for each of the

23	various effects.	Well that's not there right now, and

24	maybe what I'm also looking for is are there any

25	benchmark doses, any benchmark concentrations,

1	thresholds or whatever, distributions of thresholds

2	that I might expect for each of these effects; and

3	there, again, that doesn't happen.	Chapter 5 doesn't

4	go back into the earlier chapters and say, okay, for

5	this effect, here is the slope of any sort of curve in

6	the area of ambient exposures that we currently have in

7	the United States.	Instead it's a qualitative

8	discussion of whether we think there is causality, and

9	that's why I raised the earlier question of causality

10	at what level of exposure.	Is there causality if it's

11	just broad causality at any level of exposure?	Well,

12	yes.	Yes.	You didn't even have to do the assessment

13	for that.	So the question is, is the causality ambient

14	levels?	So as I mentioned, I'm not sure I'm going to

15	push this too much because you could say that a lot of

16	the things I just asked for, that's not the role of the

17	ISA and we're all sort of going through ISAs for the

18	first time now and it's not clear what you want to put

19	into Chapter 5.	I just thought as a risk assessor I

20	would find it difficult to go from Chapter 5 over to

21	what I would have to do computationally in a risk

22	assessment.	I will come back to that in just a bit.

23	There is an issue that arises in a

24	couple of places which I think you can clear up pretty

25	easily.	It has to do with the difference between

1	relative risk and absolute risk, right.	So relative

2	risk is a phenomenon where the pollutant increases your

3	background incidence by a certain fraction, and an

4	absolute risk is one where it increases the actual

5	incidence itself almost irregardless of whatever the

6	background rate is.	And there are places in the

7	document where that's not clear.	What really draw my

8	eye to it was there's one place where it says a person

9	exposed to 10 ppb would have a percent or two

10	probability of dying.	Well I don't think that's right.

11	I don't think we'd ever have a regulation that would

12	allow a few percent of the population to die.	I

13	suspect what that was is a one or two percent increase

14	above the background rate of death.	I mean, I'm not

15	sure if that's the case, but in other words a relative

16	risk was being treated as an absolute risk there.	So I

17	would just look through and just make sure that it's

18	always clear whether it's a relative or an absolute

19	risk that's being discussed.

20	And then the only other thing I'd say

21	which I'd want to point out in addition to the

22	particular points that I give in my review here is I do

23	mention that on page 516 there's this discussion of the

24	public health impacts.	And, I mean, I sort of agree

25	with where you're going with the public health impact,

1	but there's kind of an implicit line of reasoning

2	underneath there.	What you actually do is you say look

3	there are a lot of people.	Look there are a lot of

4	people.	Well, yeah, but that doesn't mean that the

5	public health impact is large.	Your argument is really

6	we've convinced you in other chapters that there are

7	adverse effects that occur at ambient levels.	We've

8	convinced you that those effects are probably occurring

9	in susceptible subpopulations, and we're not about to

10	show you that the susceptible subpopulation is not

11	just, you know, one person living in Montana somewhere

12	up in the hills.	It is a significantly large fraction

13	of the population, but in the way that it's written,

14	all you're given is look the populations large.	Well,

15	yeah, the population is large, but that doesn't tell

16	me, absent the earlier information, that, in fact,

17	they're getting exposed at levels that are going to

18	have a public health impact.	And so somehow those

19	simply, those three things need to be brought together.

20	There are susceptible subpopulations.	We can tell you

21	it's a large susceptible population, and we can tell

22	you that there are effects occurring in susceptible

23	subpopulations at the ambient levels that we're going

24	to be discussing for a max here.	It's all in there.

25	It's all in the document somewhere, but you have to

1	sort of piece it together in your own mind.	And then I

2	just have a whole series of, you know, relatively much

3	more minor comments.	But, again, I want to stress that

4	this was a very improved ISA Chapter 5 relative to the

5	Nox one that we received.	So that's it.

6	DR. HENDERSON:	Thank you very much,

7	Doug.	Jon.

8	DR. SAMET:	As you might expect, I

9	thought the chapter was perfect, just seeing if you're

10	listening.	So a few comments, and I certainly agree

11	with what was just said.	So in a way this follows the

12	model of the NOx with a set of sort of bulleted points

13	brought forward from the earlier chapters and then this

14	summary.

15	So one issue then is that this is sort

16	of the first time that there's some discussion in this

17	chapter of these causal criteria and the basis for

18	evidence evaluation, which clearly should come up front

19	and have been discussed there.

20	Another issue, and I think this relates

21	to I guess charge question 6, is this matter of how the

22	different health effects are treated, considered, and

23	the evidence is evaluated.	And in my comments I put

24	together a table in which I tried to pull out at the

25	end of each little sort of subsection.	Within Chapter

1	3 there's a comment, you know, that the evidence is

2	robust and shows that the evidence is whatever.

3	There's a whole set of those, and I wrote those up as

4	findings.	And then the question is, in fact, what

5	would coherence be, and wouldn't it be the fact that

6	for the facts in the same organ system that might

7	reflect the same mechanism, whether it's an irritant

8	response or inflammation, that you would see something

9	similar.	And if you just sort of look at your own

10	language running down findings, there's sort of a

11	patchwork.	And one thing I see happening in Chapter 5

12	is that there's a focus on those particular health

13	outcomes where a findings provides some indication of a

14	statistically significant result, either coming from

15	the epidemiological studies or from the clinical

16	studies.	I've never quite known what coherence is.

17	I've read David Bates' paper a number of times.	I

18	think he means things fit together, and that has a

19	subset of the implications of biological plausibility

20	in line within that.	So in that regard I'm not sure

21	that coherence and biological plausibility should be

22	separated, but certainly it means that the body of

23	evidence should come together.	So looking at my table

24	or attempt to overview how the evidence is looked at, I

25	don't see that much of the kind of coherence that I

1	would like to see unless it begins to come around

2	respiratory symptoms perhaps with the children and

3	adults.	And of course the clinical studies provide us

4	a one clear signal.	So I don't think the whole story

5	gets put together, and then this very difficult

6	question as to whether adverse effects can be expected

7	at current ambient concentrations for whom is really

8	left unanswered.	So I think there's probably at least

9	two broad target populations for that.	One would be

10	persons with asthma, possibly expose them to

11	circumstance let's say of exercising which lung dose is

12	increased and whether it, based on the clinical studies

13	and perhaps some of the studies of asthmatic children,

14	effects would be expected in the ambient range.	And

15	then there's this broader set of effects coming from

16	the epidemiology studies which have used longer term,

17	largely 24-hour or longer integrated exposure measures

18	where I'm not so sure we can turn to "SO2 itself" as

19	the causal agent.	And, again, those studies have to be

20	interpreted.

21	So I think in Chapter 5 there's still

22	work to be done.

23	DR. HENDERSON:	Thank you, Jon.	Do

24	you all want to ask Jon any questions, or shall we go

25	on with the other comments?	No questions.	Okay.	Kent

1	Pinkerton, are you on the phone?

2	DR. PINKERTON:	Yes, I'm here.	And

3	thank you for the opportunity to give my comments.	I

4	also agree that Chapter 5 is really nicely organized.

5	The logic is there.	In terms of the health evidence, I

6	really think that the scope of the studies that are

7	highlighted and are reviewed do seem to be quite

8	adequate.	These studies appear to be very relevant,

9	and they're well described.	I think one of the

10	questions I have though, the difficulty is what do we

11	do with those studies that use just the 5 to 15-minute

12	exposure time frame in a policy document, in a policy

13	relevant document.	I think they're very important to

14	see, but it is unclear to me how that will then

15	translate into potentially a new air quality standard.

16	As we mentioned earlier this morning,

17	also the animal toxicology study, again, I still feel

18	that they're highly relevant, but they are done

19	typically at orders of magnitude higher than those

20	where we have human clinical or epidemiological

21	studies.	And so, again, I think if we just put those

22	into context, and I really in Chapter 5 there were some

23	references to the toxicological studies that just

24	biological plausibility.	And I think in some ways

25	there is a relevance there, but as John Balmes had

1	pointed out earlier this morning, that some of that may

2	be a bit of an overstatement.

3	I think also in looking at this

4	document, Chapter 5, one point that I read is and that

5	seems to continue to come out is the emphasizing the

6	difficulty with confounding co-pollutants and exactly

7	how we deal with this.	I think that the writing team

8	is doing a really wonderful job in trying to make that

9	clear, but it seems to be a recurring theme throughout

10	that SO2 may actually simply be a measure of some other

11	pollutant.	And so, again, that is an important part

12	for consideration.

13	I also am very interested in the

14	sensitive populations, and maybe I just missed it, but

15	I really wondered where the evidence was for health

16	effects of the children.	And perhaps it is in that

17	Chapter 3, but I didn't see anything stated in Chapter

18	5 that referred to the importance of either being a

19	child or advanced age as an issue that is something

20	that needs to be considered.	And also I think there is

21	the importance of potentially the genetics

22	susceptibility that may add to potential adverse

23	effects of SOx in the general population.	But, again,

24	I realize that it was very well done to show that there

25	might be effects, but they're just not clear-cut at

1	this point to have that be a major driver.

2	And then the final comment is just

3	simply a comment that was made about the SO2.	Now is

4	this the form of SOx that is the most critical thing

5	that we should be measuring, or are we measuring all

6	forms of SOx and are all forms of SOx being considered

7	for this next criteria document?

8	And then I lied, I have one more

9	comment. It's just the importance of mortality.	I'm

10	seeing that consistently in the document, and is

11	mortality the driving factor for reassessing SOx in our

12	environment?	And that's just simply a comment.	I'm

13	not saying that, that should be there or should not be

14	there, but those are my comments.

15	DR. HENDERSON:	Okay, Kent.	Does

16	anybody want to respond to what Kent has asked?	As far

17	as the form of SOx, I mean, I'm sure you know, Kent,

18	that the sulfate particles are being considered as part

19	of the PM document not this one.	You're aware of that,

20	right?	DR. PINKERTON:	Yes.	Yes, I am.

21	DR. HENDERSON:	Okay.

22	DR. PINKERTON:	And, again, I'm

23	assuming that's also what's adding to the confounding

24	factors in understanding health effects associated with

25	SOx.

1	DR. HENDERSON:	Yeah.	Okay.	Okay.

2	Well thank you, Kent.	And now we go to Ron Wyzga.

3	DR. WYZGA:	Thank you.	Let me say I

4	appreciate the work that you've done on Chapter 5, and

5	I think it's a good first start.	I agree with a lot of

6	the comments that are made so far on this particular

7	section.	My personal concern is I think a lot more

8	integration work needs to be done.	I sort of start

9	with and go back to the human clinical studies where I

10	think you need to basically extract as much as you

11	possibly can from them.	I then think that there needs

12	to be an attempt to try and see to what extent can we

13	explain or how do we use the findings from the

14	epidemiological studies?	To what extent can they be

15	explained by the results received from the human

16	clinical studies?	We need to -- I think Lianne raised

17	the issue of look at where the monitors were that

18	measured SO2.	We also need to realize that in the

19	epidemiological studies that look at 24-hour averages,

20	and we need to have some sense do these at all capture

21	peak exposures or not, and if so to what extent of the

22	population do they capture peak exposure.	I think one

23	of the very important questions we have to ask

24	ourselves is what we're seeing in the epidemiological

25	studies, is it sort of consistent with and simply a

1	refinement or another way of looking at the results

2	we're seeing from the human clinical studies, or are we

3	looking at something that's quite independent.	So I'd

4	like to see a lot more thought into trying to see

5	whether or nor we're basically looking at one, on a

6	sense, coherent piece of information or there are

7	several different pieces here and how strong is the

8	evidence for the several different pieces.	Clearly I

9	think, you know, when you look at end points, the

10	opportunity for greatest coherence is going to be

11	looking at some of the asthmatic responses.	I think

12	you have enough material that's available to you to

13	answer that question, but I felt it wasn't answered

14	throughout the document.	And I hope that you can pay

15	more attention, try and tie it together better in the

16	subsequent draft.

17	DR. HENDERSON:	Okay, Ron, is that

18	all for now?	Lianne, you're next.

19	DR. SHEPPARD:	Yeah.	I had just a

20	couple of additional comments.	I think that we should

21	revisit the organization of this chapter with respect

22	to both the framed policy questions and the information

23	needed for the health assessment.	And I appreciate the

24	thinking that maybe that the health assessment

25	shouldn't guide this chapter too heavily, but I think

1	that should be looked at.	And whenever possible,

2	quantities that are going to be useful for the health

3	assessment should be identified so that those

4	assumptions are not made in maybe less of a vacuum than

5	they might be otherwise or require less additional

6	later analysis.

7	So some important questions to include

8	are whether properties of the atmosphere are well

9	measured.	What's the relationship between

10	concentration and exposure?	What does the monitoring

11	data tell us about epi studies?	Those are some of the

12	things.	In addition, going over the criteria for the

13	conclusions, I think those -- we've already discussed

14	this.	They should be specified up front in the

15	chapter, and we should be revisiting, as we've already

16	discussed as well, the classification of the health

17	evidence with respect to published criteria from the

18	National Academy of Sciences.	And then also being

19	clear about which studies are being focused on and

20	evidence for coherence.	I think those are my main

21	comments.

22	In addition, I think the concluding

23	statement from the chapter needs to be better

24	substantiated.	It needs to be explicitly stated this

25	statement should be interpreted in the context of the

1	already low usual population exposure to SO2 or

2	regardless of existing levels.

3	DR. HENDERSON:	Thank you, Lianne.

4	Now do other members of the panel have on

5	Chapter 5?	DR. LARSON:	I'm Tim

6	Larson again. Just one reiteration on the exposure

7	assessment first bullet again.	I think we need to

8	consider some qualifications there because it's the

9	most important conclusion from that section and it sort

10	of underpins the epidemiology, and it's, as we've heard

11	all day, not that particularly convincing given all the

12	uncertainties we've discussed.	Thanks.

13	DR. HENDERSON:	Are you clear what

14	he's talking about?

15	SPEAKER:	Yes, we are and we heard

16	that this morning from Tim and from several others.

17	And although we have in our presentation today, excuse

18	me, downgraded our assessment of that from strong

19	association to possible association.	We will certainly

20	look at that again and de-emphasize that to the extent

21	that we think is appropriate.

22	DR. HENDERSON:	Okay.	Thank you.

23	Are there any more comments on Chapter 5?	Yes, Frank.

24	DR. SPEIZER:	This is more of a

25	question than a comment, and the question is really

1	directed toward you but perhaps needs to be directed

2	toward the risk assessors.	Whom is going to make the

3	decisions and where is the data going to be for what

4	proportion of the population is at risk?	Should there

5	be something in here that sort of concludes something

6	about the proportion of asthmatics, the proportion of

7	older people, or downwind the proportion of the general

8	population downwind from sources?	This is information

9	that we needed in the risk assessment piece, and maybe

10	they will perhaps put it in themselves, but would they

11	want to see this as part of the ISA?	That's really the

12	question I'm asking is where does it belong?

13	DR. ROSS:	I would say both places.

14	What we'll do is take some of the comments you've

15	offered today about increasing to the extent we can

16	quantitative information that we've got.	Like you've

17	talked about some air pollution today.	We'll look at

18	expanding a little bit of what we have here that can,

19	from the science side, characterize susceptible

20	populations, what kinds of susceptible population.

21	Within the exposure assessment that you'll talk about

22	next, they will do more quantitative analyses and then

23	carry that forward to possibly, you know, if there are

24	any considerations of alternatives of standard or

25	anything like that.	OAQPS would follow up with a more

1	quantitative analysis.

2	DR. SPEIZER:	Well do you have to

3	have some of that in here in terms of what numbers

4	they're going to use?	I mean, is it going to be 15% of

5	the asthmatic population of the United States, and do

6	you have to put something in here about that as to what

7	that number is going to be used?	Or who's going to

8	make the decision about that?

9	DR. ROSS:	I think that would be

10	linked, the percent of people like you saw in ozone,

11	with the ozone document, when you start calculating the

12	proportion of the population that's exposed to

13	different levels of concern, that's where the policy

14	options come in into what are the levels of concern.

15	So we could characterize asthmatics to the extent

16	possible from the data.	Asthmatics as a susceptible

17	population, and I don't know what information we have

18	about the distribution of sensitivity within asthmatics

19	that's available from the health studies.	But then how

20	many people might live within a plume, or what levels

21	you might consider?	You know, you could consider a

22	stage of levels that might be levels of concern for the

23	administrators to consider.	That would be on the

24	policy side, I believe.	Does that make sense?

25	DR. SPEIZER:	Yeah.	I just wanted to

1	make sure you guys needed, either did not or do need to

2	have some of that in here.

3	DR. HENDERSON:	Okay.	Yeah, Terry.

4	DR. GORDON:	Small question and not

5	being a person who's involved in monitoring to the

6	stupid question and embarrass myself, but I'm unclear

7	about the monitoring.	It talks about the uncertainty,

8	complicates our ability to attribute health effects,

9	and asks for, we have to get down below 3 ppm when most

10	of the health effects we're seeing are far above that.

11	So I was just curious why this is scattered throughout

12	here.	It didn't seem consistent when we may or may not

13	suggest levels at or below the current NAAQS, but going

14	to 1 ppb or lower, I didn't see the relevance or if

15	that was an uncertainty.	I understand the ambient

16	versus indoor uncertainty but not the other part.

17	DR. ARNOLD:	Yeah.	And I guess what

18	we'd say quickly is that the uncertainty comes in

19	trying to characterize what the ambient exposure would

20	have been for things that are used, for example, in the

21	epidemiological reconstructions of what those exposures

22	were.	And if they're using individual monitors or even

23	multiple monitors within a CMSA, and those monitors are

24	reporting values which are below the limit of

25	detection, then of course it's going to become very

1	difficult to construct what the actual exposure might

2	have been.	So that's the sort of first piece.	And

3	then that feeds into the uncertainty that we have to

4	try to control when looking at the infiltration from

5	the ambient level of SO2 into the indoor event because,

6	again, those passive samplers also have a relatively

7	high limited detection relative to what the current

8	ambient concentration is.	You look a little

9	dissatisfied with the response.

10	DR. GORDON:	Well I get, I mean, we

11	get non-detects in measurements in experimental studies

12	all the time, and you just put down the lowest

13	detection limit or half of it, you know, you play with

14	it that way.

15	DR. ARNOLD:	Right.

16	DR. GORDON:	And since of the values

17	for the epi are so much lower than 140 ppb, a 30 ppb, I

18	didn't see what the push to go down below 3 or 1 ppb or

19	to say there's uncertainty there.	I understand the

20	monitoring and the different sites, but it seems like

21	better data than I get sometimes in animal studies.

22	DR. ARNOLD:	And that's true.	I

23	think the other thing is that we just want to document

24	what we believe is the current level of confidence that

25	we can have in the ambient concentration.	Part of the

1	problem is that although the operational limit of

2	detection of most of the monitors which are in place

3	now is above 3 ppb, that is right at the current

4	national ambient level, they're actually reporting down

5	below that.	So that AQS, the database of all the data,

6	contain data that have been reported at less than the

7	limited detection, so I think that's part of what's

8	driving the uncertainty there.

9	DR. POSTLETHWAIT:	Hi.	This is Ed

10	Postlethwait.	That raises an issue that I picked up in

11	reading the document was that I thought the opening

12	discussion regarding the uncertainties in measurement

13	and stuff was actually quite robust and nicely written,

14	etc.	But I didn't see a link between that and the

15	subsequent environmental studies that have been done

16	where these very low concentrations were being

17	reported.	And I guess I just toss this out to the

18	group as to whether it's of value to place any kind of

19	qualifier on those studies that report levels that may

20	or may not be questionable in terms of their accuracy

21	and relative to what was stated in the opening chapter

22	of the document.	Boy, there's a huge round of

23	response.

24	DR. HENDERSON:	We've gone to sleep

25	after our heavy lunch.	No, not really.	I hope not.

1	Does anyone want to comment on Ed's question?	We're

2	not getting a response, Ed.

3	DR. POSTLETHWAIT: Obviously it's a

4	terribly important question then.	So I withdraw my

5	inanity; how's that?

6	DR. HENDERSON:	Okay.	Well, we can

7	go on to the next, the last, you know, general

8	discussion issue is charge question eight, which is

9	simply is this document adequate for rule-making, and

10	of course we've had a lot of comments on changes we

11	want to have made.	Before we go onto our writing

12	assignments, there's three people that have been asked

13	to comment on the overall adequacy of the document, and

14	George Thurston is the first one.

15	DR. THURSTON:	Well, yes, with the

16	caveat that everything that we've mentioned has to be

17	corrected, or everything that's reasonable that we've

18	mentioned I guess.	I do, you know, think that it's a

19	very good document, and close to ready.	I guess trying

20	to look at where the rubber meets the road kind of

21	thing and what do we need out of this document to go to

22	public policy.	I agree with what was said earlier

23	about the fact that we do have to consider the next

24	document, the scope, and method, and risk assessment

25	document to some extent because they're going to rely

1	on this.

2	So we have to make sure that the

3	information that they need is in this document, or

4	they're going to have to develop it on their own and

5	maybe not in a way that we would agree with; and then

6	we're going to run into problems with that document.

7	So we have to try and be clear.	So one of the things I

8	see, and other people can certainly chime in, but I

9	think one of things we mentioned -- if we're going to

10	start out -- you know, I thought of this in terms of

11	three context.	One is exposure.	The next is some sort

12	of a benchmark analysis, you know, with the human

13	clinical studies, and then using epi studies to get

14	population exposures.	In those three areas of policy

15	analysis, have we give EPA enough information in this

16	document to go forward with these endeavors.	And I

17	guess in terms of the exposure, first, I think we've

18	mentioned the five-minute exposure data.	We need to

19	present that and know something about that, both from

20	policies perspective, analyses and also from our point

21	of view trying to, let's say we decided to recommend a

22	standard.	We'd need to know, you know, have a

23	reference as to what we're talking about in terms of

24	ambient levels.	And I do think in there that, and

25	Howard Feldman brought up the issue of personal

1	exposure and central site, and I don't agree with his

2	analysis of it; but I do think that the issue needs to

3	be addressed more clearly why the fact that personal

4	monitoring not correlating always with central site is

5	not really the problem that he said it was.	I could

6	elaborate on that, but I think you know -- this has

7	gone through excruciating detail in the PM document,

8	the difference between personal exposures and

9	population exposures, and that needs to be put in the

10	document so that we don't get into that question, which

11	is, I think, not a critical issue but one that needs to

12	be addressed since it's been brought up.

13	The second part is the clinical human

14	exposure studies, and, again, you know, I don't want to

15	sound like a broken record here, but the question is

16	how low, where do they set the benchmark?	And, you

17	know, I think, we can look at the clinical studies and

18	you see some effects at 500, 600 ppb, but then there

19	are also some, again, with the particles in there that

20	are lower and with exercise that are lower.	So that's

21	why we need to have that in the document so that when

22	EPA chooses a benchmark it's something relevant and not

23	just based on what was done in a particular chamber

24	with pure SO2.	They need to consider all of the human

25	clinical exposure studies and, you know, what they

1	imply about what is a good benchmark to choose, to

2	apply those effects, relationships.

3	And then the epi studies third, epi

4	studies.	The big issue I think is the multi-pollutant

5	models which we've been talking about, which one should

6	they use for their analysis?	And so this is, I think,

7	a critical issue because it could make a big difference

8	if they choose to use a coefficient that is from a

9	model that is not useful, in my opinion anyway.	And so

10	we need to clarify that multi-pollutant, which ones do

11	we think are the best to rely on.

12	And we also have to address the question

13	of potentiation, you know, regarding, especially PM,

14	potentiation versus confounding.	Up until now in the

15	document whenever they say, oh, look there's another

16	pollutant, they're looking at and saying, oh, it's

17	taking away from SO2.	That's the implication I get

18	from it; that they're saying, oh, maybe the SO2 is not

19	real when in reality there may be potentiation going

20	on, and there may be, oh, there's an effect of another

21	pollutant.	This SO2 is worse than the pure SO2 studies

22	would imply.	So I think we need to look at the

23	distinction between confounding versus potentiation and

24	look at interactions of other pollutants in a balanced

25	way, not just how does interactions with other

1	pollutants dismiss SO2.	It's also how we learn about

2	SO2 effects.	So those are the three areas, the things

3	I thought were the most salient things as we try to go

4	to a policy relevant application.

5	DR. HENDERSON:	Thank you, George.

6	Jon, you want to give your summary?

7	DR. SAMET:	So I guess the most

8	important first question in relationship to charge a,

9	does the ISA establish that SO2 at concentrations

10	experiences in the populations causes adverse effects.

11	And I'll use the word cause because that underlies

12	everything, and when I use the word cause, at least it

13	comes with the implicit certainty that lowering the

14	concentration of ambient SO2 will result in a reduction

15	in the attributed health effects, which is sort of your

16	bottom last line, I think where you say sort of

17	regardless of what the causal pathway may be, we think

18	there are effects causally attributable to SO2.	So

19	then the question is to what extent is that bottom line

20	supported, and I think in my earlier comments I noted

21	some of the deficiencies of the analysis around

22	supporting this causal judgment.	And I think that has

23	to be improved.	The use and risk

24	assessment is then predicated on both the causal

25	determination, the hazard identification, and then

1	moving on from there to the dose response, which I

2	think remains a little bit unresolved from the full

3	document exactly what dose response relationship you

4	will choose for the risk assessment, or what will be

5	moved forward and what will be supported by the ISA.	I

6	mean, we talked about those issues.

7	And then I think the exposure issues

8	have been pretty well addressed in prior comments.	The

9	only other comment I would make that I'm not sure I've

10	sort of seen a full airing, a systematic airing of the

11	uncertainties, and I think that would be useful if you,

12	again, go back to the kinds of data you have available;

13	and this is uncertainty in the context of charge

14	question eight.

15	So for the clinical studies, in

16	extending those findings to current exposures, there's

17	the issue of the exposure or dose extrapolation.

18	There's the question of the potential susceptibility of

19	the people, the representativeness of those in the

20	clinical studies versus people with asthma in general

21	and how important that is.	And then there's also the

22	role of other pollutants, thinking about the clinical

23	study setting where there was an SO2 exposure versus

24	the real world where there's a mixture.	And I think

25	others have commented on that.	And then there's a

1	broader run of epidemiological studies, again, coming

2	with certain uncertainties.	And I think, you know, I

3	recognize that these will be also dealt with in the

4	risk assessment, but I think this document should

5	provide support for, and could do a better job of

6	taking this on systematically.

7	DR. HENDERSON:	Thank you, Jon. And,

8	Ellis, you have the last word.

9	DR. COWLING:	Well this will not, I'm

10	sure be the last word.	Several of us have indicated

11	our increased satisfaction with the processes and the

12	product that we've been asked to review in this case,

13	and my comments will support that general view.	I'd

14	like to do this in the context of a statement that our

15	chair, Rogene, wrote a year ago last May when she was

16	responding to one of the administrator's requirements

17	that we offered or addressed.	And we've made some

18	adjustments in the sentence that she wrote at that

19	time, and that sentence reads, "What scientific

20	evidence and/or scientific insight" -- I emphasize that

21	in the context of George's request earlier -- "have

22	been developed since the last review to indicate if the

23	current public health-based NAAQS need to be

24	revised" -- and this is the important part -- "or if

25	alternative levels, indicators, statistical forms, or

1	averaging times of these standards are needed to

2	protect public health with an adequate margin of

3	safety?"	When Doug began the discussion about the

4	adequacy of Chapter 5, he said that it would be nice,

5	and he was a little hesitant about whether he wanted to

6	press that very hard, but there are six policy relevant

7	questions listed in Chapter 1, and they are listed on

8	page 1-2 if you want to look them up.	And it's

9	interesting to read a couple of these, and we could

10	assess whether those original questions, which framed

11	this entire ISA process, were well articulated.	And

12	one of them says has new information altered, and we

13	would again say new information or insights altered, or

14	substantiated the scientific support for the occurrence

15	of health effects and so on, but each one of these

16	original questions, which Doug was longing to find and

17	wondered how to strong to go about, are stated as SOx.

18	And almost all the rest of our discussion today relates

19	to SO2, which is the indicator, and that's why I

20	mentioned all the four different parts of the essential

21	NAAQS, indicators, statistical form and all that.

22	So I am very, very pleased and I would

23	like to reinforce the view that has been expressed

24	earlier by others -- and one of the reasons why I'm

25	very pleased with what I see in this document is that

1	there are carefully crafted declarative sentences that

2	tell the truth about what is discussed in Chapter 2,

3	and all of those or most of them were relevant to those

4	six questions that are outlined in Chapter 1.	So this

5	is well organized, I believe, and there are 41

6	carefully crafted statements of science that are

7	relevant to these six policy questions on page 1-2.	So

8	this is the best job that I've ever seen in a criteria

9	document or in an integrated science assessment of

10	providing the essential key findings, and that's lo and

11	behold what the title of Chapter 5 is, Key Findings and

12	Conclusions.	Good for you guys.	And I'm not expert

13	enough to say now was every single one of those 41

14	statements that you prepared a brilliant execution of

15	the most important things, and you've heard comments

16	from everybody here today about this one -- well, maybe

17	they didn't focus it around the 37th statement that you

18	wrote or the 3rd or the 4th one.	But I urge you to

19	continue this process.	The more effort that you put

20	into those key scientific findings, the better off that

21	this whole process is likely to be, and I congratulate

22	you for your effort to do so.	And I hope you'll pay

23	attention to what everybody else says who knows a lot

24	more about this than I do to be sure that the sentence

25	that you've written, the 41 key scientific findings in

1	this whole document, are the most well articulated

2	formulation of the truths that you hope are contained

3	in chapters 2, 3, and 4.	We have some uncertainty

4	about what to do with 4, but we leave it to your wisdom

5	in trying to satisfy the needs of the next stage in

6	this process.	So that was the most important message I

7	wanted to leave with you.	You are concentrating on

8	what is really important,	to set the stage for a

9	decision about whether we've got a good standard, and

10	we've had the same standard for a long time now, or

11	whether we need a revision of these four parts, the

12	indicator, the statistical form -- I never can repeat

13	all four of those in an accurate way, but I could write

14	about them 'cause I've done that several times.	But

15	here, let's be sure we get them right -- the level, the

16	indicator, statistical form, and the averaging time.

17	Those are the things that are important, and the

18	American Lung Association said five minutes, that's

19	important, and you're doing the best you can to deal

20	with the agreement that was reached between the

21	American Lung Association sometime ago.

22	So I hope that you will continue to do

23	this, and I wondered if you could tell us who wrote

24	those sentences, the 41 sentences?	Now I presume, did

25	all of you?	Did every single one of you read all 41 of

1	those statements, but all 41 of you -- no, excuse me.

2	All of you did not write the sentence.	So I presume

3	that the author of Chapter 2 authored, and there were

4	four statements from Chapter 2.	So what happened when

5	the Chapter 2 was written?	Were the four sentences

6	that we see here, the ones that were produced by the

7	authors of Chapter 3.

8	DR. ARNOLD:	Yes, that's correct.

9	The members of the NCEA staff who had primary

10	responsibility for each chapter submitted what I would

11	say were the first draft conclusions.

12	DR. COWLING:	Yeah.

13	DR. ARNOLD:	And then we met as a

14	team and went across to make sure that we would

15	integrate from the early chapters into the later

16	chapters with the support that CASAC has been looking

17	for and that we're trying to provide in the new sense

18	of integrating across disciplines and integrating

19	towards the policy question would be met.	You're

20	exactly right.	Your inference is exactly right.	We

21	provided them and then everyone read across to make

22	sure that we were satisfying that.

23	DR. COWLING:	How many members of the

24	team are there altogether?

25	DR. ARNOLD:	We can show the --

1	DR. COWLING:	Yeah.	I know you can

2	do that, but is it a dozen, something like that?

3	DR. ARNOLD:	Yeah, approximately.

4	DR. COWLING:	So a dozen well-

5	informed minds were exercised over the specific words

6	that were contained in 41 sentences after they were

7	originally drafted by whoever submitted the candidate

8	draft statements; is that correct?

9	DR. ARNOLD:	I'm beginning to be

10	hesitant to respond, Ellis, because I sense a

11	precipice, but I'll say tentatively yes.

12	DR. COWLING:	I'm not trying to set

13	you up for anything.

14	DR. ARNOLD:	Okay.	I'll lean back

15	then.

16	DR. COWLING:	I'm simply trying to

17	understand how, and it seems to me you're trying to

18	form a consensus view that comes from NCEA that will be

19	used by the Air office as the foundation, as was

20	indicated when Frank made his comments, and you took

21	your best minds and exercised them together and agreed

22	that those 41 sentences were the best thing that you

23	could do at that time.	And then you had the CASAC

24	review and you got a whole bunch of other suggestions

25	now about what you can do.	Keep up that process.

1	DR. ROSS:	And to give credit where

2	credit is due, we ask for internal review, and we had

3	assistance from other labs and offices in EPA in

4	reading over these conclusions too.

5	DR. ARNOLD:	Which happens before we

6	submit to CASAC.	Yeah.	So we go across them

7	ourselves.	We then get feedback from other EPA labs

8	and centers and incorporate that before we actually

9	distribute it to you as well.

10	DR. COWLING:	So Mary says we not

11	only looked internally but we looked externally as

12	well, and I presume you got some external comments and

13	you would in almost --

14	DR. ARNOLD:	External to NCEA,

15	internal to EPA.

16	DR. COWLING:	Okay, but not -- and

17	that's what CASAC is all about.

18	DR. ARNOLD:	Since we can't circulate

19	the draft and incorporate that cost.

20	DR. COWLING:	All right.	This is

21	about -- I mean, I've made some other comments about --

22	you can read my written comments in addition.	Keep on

23	with this process.	Make it as relevant as you possibly

24	can, and if you think of things that alter those

25	original six questions, and that's why Doug was

1	hesitating.	Look at those six questions.	We in CASAC

2	ought to look at those six questions that are in

3	Chapter 1 and say do we consider them adequate, and one

4	thing I was surprised at, they're all in SOx.	SO2 is

5	not mentioned in any of those six statements.	I was

6	surprised.	So if you think of things that ought to be

7	adjusted in the wording of the framework policy

8	questions, I think you ought to offer some feedback to

9	your managers in saying, well, we had thought of this,

10	and we wondered if you might want to reconsider some

11	part of your question three.	Thank you for what you're

12	doing.	Carry on.

13	DR. HENDERSON:	Thank you, Ellis.

14	That was an upbeat comment.	I appreciate that and I'm

15	sure they did.	I would note that the title of the

16	document is Sulfur Oxide, so, I mean, and that's why

17	the SOx comes in.

18	DR. ARNOLD:	The actual standard is

19	for oxides of sulfur, and as Ellis is saying that the

20	indicator is SO2.

21	DR. HENDERSON:	Yes.

22	DR. ARNOLD:	And that's because SO2

23	is really the only, the only form of sulfur oxide

24	that's relevant in terms of --

25	DR. HENDERSON:	Yes.

1	DR. COWLING:	Except in PM and of

2	course --

3	DR. ARNOLD:	Correct, correct, but

4	we've explained that, I hope, again, how we've divided

5	up, how we're looking at gas phase versus --

6	DR. COWLING:	I think many of us in

7	CASAC who have now sat through the SOx and NOx

8	integrated reassessment of the secondary standard that

9	Ted leads.	And we've been through NOx and we've been

10	through at least through the ISA stage of things with

11	NOx, you're doing a better job with SOx.	Good for you.

12	And the decisions have been made about where to put

13	visibility, for example, and where to put nutrient

14	effects, and that separation is going to lead to some

15	gap in my judgment about what's handled where and

16	whether it's handled adequately in this document from

17	the standpoint of the issues that have been raised

18	about that other document.	And one of the most

19	important ones that I would raise as an ecologist is we

20	have a SOx standard.	We don't have a -- and we have a

21	NOx standard, but that only deals with oxidized forms

22	of nitrogen or sulfur.	And at least I would advocate

23	that having a document that would include all the

24	reduced forms, chemically reduced forms of nitrogen,

25	particularly, would be desirable.	End of comments.

1	DR. HENDERSON:	Thank you, Ellis.

2	Well we're coming now to the point where we're going to

3	have to do some summary work ourselves.	As you know,

4	the path forward now from here is that the people who's

5	names are underlined are responsible for pulling

6	together the consensus comments for the whole panel in

7	regard to their chapter or in the case of charge

8	question 8, there charge question.	And there's an

9	overlap of course of people involved in each of these.

10	So what I would suggest is that those of you who have

11	double assignments, you make sure your comments get to

12	the person's who's name is underlined.	You can e-mail

13	them what you want to go into paragraphs.	What I'm

14	envisioning is each of these different chapters will

15	have a paragraph or two in the letter to the

16	administrator, and what you're doing now is drafting

17	those paragraph or two or three.	So how do we get, how

18	does Terry Gordon get Dale Hattis comments on Chapter

19	4.	Well, you know, can work together, or if Dale wants

20	to e-mail some golden words to Terry, that's an easy

21	way to do it too.

22	SPEAKER:	They're already in the

23	comments, contributing comments, but if you need to --

24	DR. STALLWORTH:	Well we want to boil

25	it down.

1	DR. HENDERSON:	We want to boil it

2	down.	See that's important.	We want to convey

3	something to the administrator in a condensed

4	integrated form as we've been advising them to have an

5	integration, in a condensed integrated form what we

6	want to say to the administrator in the letter.	So it

7	can't be just a copy of your individual comments.	It

8	has to be some condensed form of that.

9	SPEAKER:	Is there a listing of email

10	addresses along with that?

11	DR. CRAWFORD-BROWN: Rogene, by the way

12	I've been assuming that what Jon, and Kent, and Ron,

13	and Lianne said in their comments were the ones that

14	you felt were the most important ones to be emphasized,

15	and, therefore, those are what I will focus on..

16	DR. HENDERSON:	That's good, Doug.	I

17	mean, if you've done that, you're probably a step ahead

18	of the others.	So that's, but try to work together

19	because what's going to happen is then these lead

20	discussants will e-mail the final form of this

21	paragraph, or two, or three to Holly.	And Holly is

22	going to stay up all night.	Holly is going to collate

23	those into what you might call a draft letter to the

24	administrator.	Tomorrow we will discuss that, and if

25	there's anything that, you know, people say no, no

1	that's not what I mean, we'll modify it.	And then we

2	will ask for people do you concur with this substance

3	of the letter.	After this meeting, of course, Holly

4	and I will work on the letter to smooth it out, to try

5	to remove redundancies, and make some editorial

6	changes.	And then you'll get to see it again to

7	concur.	So this isn't the last time you'll see it.

8	But what we need tomorrow is for to get concurrence on

9	the substance of the letter.	So you want to have the

10	substance in there, and it needs to be in a condensed

11	form so that it can be understood.	Yes, Lianne.

12	DR. SHEPPARD:	So this is to clarify.

13	The organization of this letter is going to be a little

14	bit different than the last one.	It will be more like

15	the outline we used today.

16	DR. HENDERSON:	That's correct.

17	DR. SHEPPARD:	Combining charge

18	questions with chapter.

19	DR. HENDERSON:	That's right.

20	Because when we did it by individual charge questions

21	before we had so many redundancies because the charge

22	questions had some redundancies.	This is a little bit

23	different organization, so we can -- yes, Terry?

24	DR. GORDON:	There are, in the blue

25	packet we got all email addresses for everybody, and I

1	did what Doug did and I took notes, but if Lianne, and

2	Jonathan, and Dale, if you'd write something that I

3	could understand about modeling and responses, that'd

4	be great.

5	DR. HENDERSON:	I want to bring up

6	one other thing is that tomorrow we're going to be

7	talking about the exposure risk assessment document.

8	This is a consultation as opposed to what we're doing

9	today on the ISA.	ISA review is a peer review, so

10	we're composing a letter with our main points in it and

11	what we think are helpful suggestions.	The

12	consultation tomorrow, as we explained for the NOx, is

13	giving advice to the agency in an early stage in the

14	development of the document.	It's a very important

15	stage because if we really feel something is important

16	or them to address in the document, now is the time to

17	say it.	But we don't do a peer review -- we sent a pro

18	form, a letter, to the administrator saying this

19	consultation took place.	The advice of the CASAC panel

20	members are in the individual comments attached.	So

21	the only written form of advice to the agency for this

22	consultation is in the form of your written attached

23	comments.	They have the oral, which we will be going

24	through tomorrow, but the only written form will be in

25	your individual comments.	Therefore, this makes your

1	individual written comments very important because

2	that's where they'll be getting their advice.	So if

3	anybody has not written up their comments for the

4	consultation, please do so because otherwise we're not

5	fulfilling our --

6	DR. STALLWORTH:	There may be some

7	revisions to comments after tomorrow's --

8	DR. HENDERSON:	Exactly.	Glad you

9	brought that up, Holly.	You can, after the discussion

10	tomorrow, you may want to revise your comments, and

11	that's fine because you'll have some time after the

12	meeting to revise your comments.	But please don't just

13	ignore the request for comments because they're very,

14	very important; that's what I'm trying to get across.

15	And I would ask, we're going to take a break now and

16	then come back and start our writing.	But, and we

17	might discuss some major points.

18	DR. STALLWORTH:	Yeah.

19	DR. HENDERSON:	Yeah.	We can do

20	that.

21	But --

22	DR. SPEIZER:	May I make a comment?

23	DR. HENDERSON:	Yes.

24	DR. SPEIZER:	I did not take notes from

25	last time. Therefore, I'm going to work from the

1	written comments, and we could have some major changes.

2	DR. HENDERSON:	Good.	Thank you,

3	Frank.	I want to ask NCEA if you have some questions

4	before we start our writing assignment?	Yes, go ahead.

5	DR. SVENDSGAARD:	Dr. Thurston

6	mentioned a benchmark, and I was wondering exactly what

7	that means.	In terms of risk assessment I think of an

8	effect that is the smallest you're trying to detect and

9	finding out what concentration is associated with that.

10	Is that what Dr. Thurston had in mind?

11	DR. THURSTON:	Well I was really just

12	pulling out the term used in the scope and methods

13	where they talk in a tier two about a benchmark and

14	then looking at certain subpopulations and then saying

15	what we might expect in terms of -- whereas the tier

16	three being trying to look at the overall population.

17	So I think they were looking and saying, okay, how many

18	of these people are over this level and then what kind

19	of effects will we see.	I think that's what they're

20	talking about there, and the question I'm saying is I

21	think, you know, we'll talk about this more tomorrow,

22	but I think what they were talking about is a benchmark

23	like 500 or 600 ppb in this discussion that we'll talk

24	about tomorrow.	Based on my reading of the document,

25	it seems to me that a lower number would be

1	appropriate.	So I think the ISA needs to give some

2	guidance on, you know, what kind of benchmarks might be

3	used.	So I don't really have a good answer.

4	DR. GORDON:	George, I remembered

5	your comment, and I just think there's a different

6	definition of benchmark.	In EPA you're the guys who

7	use it the most, and it pervades the rest of us from,

8	coming from you, so what's your definition 'cause I

9	thought George misinterpreted what you thought?

10	DR. THURSTON:	Could be.

11	DR. ROSS:	This is something for the

12	exposure folks, and I see Harvey back there.	I suspect

13	benchmark did not mean benchmark dose.	It meant

14	exposure of concern in the same way it was used in

15	ozone, so policy choice about, you know, different

16	exposures to consider but not a benchmark dose in the

17	classic sense of toxicology study levels.

18	DR. THURSTON:	Right.	But they seem

19	to be basing that on the clinical studies, which

20	benchmark to choose.

21	DR. ROSS:	No.	I don't think so.

22	DR. THURSTON:	Just a coincidence.

23	DR. ROSS:	Harvey, can you go

24	ahead, or do you want to wait until tomorrow?	We can

25	--

1	DR. THURSTON:	You want to wait until

2	tomorrow.	Yeah.	So I don't have really good answer,

3	but, you know, I was just trying to say we need to get

4	the guidance on that.

5	DR. HENDERSON:	Harvey's	going to

6	give us the answer.

7	DR. THURSTON:	Good.

8	MR. RICHMOND:	I think we'll talk

9	more about it tomorrow, but the benchmark, you're

10	right, are more related to the clinical.	And at the

11	moment we said we had identified preliminarily based on

12	the current draft levels that were similar to the

13	levels that were focused on in the staff paper back in

14	the 90s.	And our perception was a lot of the evidence

15	from the clinical hadn't changed substantially, and we

16	can talk more detail and get your feedback on that

17	tomorrow.	But in ozone, for example, we had a series

18	of different benchmarks, .08, .07 and .06 eight-hour

19	averages, exposures under moderate exertion and that

20	was related to the clinical evidence.	So there wasn't

21	necessarily also a single benchmark, but the further

22	the ISA can go in characterizing what happens at

23	different levels of effects in terms of either fraction

24	of population or severity of response, we obviously

25	would like to see, you know, the ISA to go as far as it

1	can on what the science tells us about both of those

2	aspects that will help inform what choice of benchmarks

3	we use in that tier to assessment.

4	DR. THURSTON:	What he said.

5	DR. HENDERSON:	Okay.	We'll take a

6	break, and if we come back in about 15 minutes, I'm

7	going to have a brief discussion of what people

8	consider to be the major issues and that shouldn't take

9	long, and then we can get to work.	But I see, what is

10	the question?

11	DR. KIM:	Actually we just had a

12	question, it's actually kind of fundamental to what

13	we're trying to do here.	So in our conclusions we laid

14	out where we think the strength of the evidence is,

15	using the wrong definition of strength of course, and

16	we put the most emphasis on the respiratory morbidity

17	and labeled cardiovascular morbidity as inconclusive,

18	the long-term effects as inconclusive and the mortality

19	as suggested.	We just wanted the panel's opinion on

20	how they felt that classification worked.	The exact

21	wording may have to be changed but in terms of the

22	weight of the evidence and where it's lying.

23	DR. HENDERSON:	That's at the end of

24	Chapter 5, right?

25	DR. KIM:	Yes, uh-huh.

1	DR. HENDERSON:	I don't know, Jon.

2	DR. SPEIZER:	I think you got to

3	give your definitions a chance to be brought in before

4	you consider what you're going to, where you're going

5	to classify it.

6	DR. KIM:	But it's not the

7	classification but the hierarchy of the best evidence

8	for respiratory morbidity with short-term exposure

9	falling away from there.

10	DR. HENDERSON:	Well do people have

11	comments on that?	Jon Samet, I would guess you would,

12	do you have comments on that?

13	DR. SAMET:	Well I think in a way, I

14	think we've all commented on that...

15	DR. HENDERSON:	Yeah, in a way, yeah.

16	DR. SAMET:	-- and I think the --

17	you know, it's difficult because as we move from the

18	clinical studies with the experimental design in a

19	characterized exposure to the epidemiological studies

20	with, you know, a mixture, an indicator and we're not

21	sure.	I think things become less certain.	So the

22	ordering is right; the terms are wrong, and I think

23	that's probably where we can leave that.	I do think

24	what's critical is whether we can give you enough

25	guidance so that when you come back in the next version

1	that this is more clear, more transparent, and I think

2	we're going to have to write thoughtfully.

3	DR. ROSS:	But we were asking about

4	the order itself.

5	DR. SAMET:	The ordering has been

6	done.

7	DR. ROSS:	Base ordering.

8	DR. HENDERSON:	Okay.	So people seem

9	satisfied with the ordering.	Okay.	We will take a 15-

10	minute break now and come back and discuss a little bit

11	the major points to be sure they're covered.

12	(WHEREUPON, a brief break was taken.)

13	DR. HENDERSON:	Get started.	I want

14	to just briefly discuss the major issues to be sure

15	we're all in consensus on what those major issues are,

16	and it may help some of the people who are writing to

17	get started.	So if we can sit down for just a few

18	minutes, and then, then you can start your writing

19	assignment.	I'm going through -- having listened to

20	all of these, it is three major issues that come to

21	mind.	I'm not talking about the smaller issues that

22	have been very well addressed, but I came up with three

23	major issues for SO2.	One is, and you all can, this is

24	an interactive discussion here.	You can add to and

25	correct is.	One is the limitations on our monitoring

1	information.	Monitoring that, do the area monitors

2	reflect personal exposures?	If we wanted to control or

3	have a regulation for five-minute peak exposures, do we

4	have the information we need?	And what are the

5	limitations of the monitoring information?	Do people

6	agree that's a major issue?	Is there anything that you

7	want to add.	I thought you might just put one,

8	monitoring.

9	DR. STALLWORTH:	You want me to go

10	ahead, okay.

11	DR. HENDERSON:	Yeah.	Go ahead up

12	there.

13	SPEAKER:	I think there's about five

14	people we're waiting on.

15	DR. HENDERSON:	Oh, okay, here they

16	come.

17	SPEAKER:	This is what you get when

18	you get three dollars and twenty-five cents an hour.

19	We wander in when we want to come in. Well, whatever

20	the money is, I don't know.

21	DR. HENDERSON:	When I first took

22	this job, Doug, I didn't think they paid at all.

23	DR. JOHNS:	And they don't.

24	DR. HENDERSON:	I'm so used to the

25	academy.	The academy doesn't pay.

1	DR. STALLWORTH:	Greg, it's not

2	coming up.	Sorry.	I spoke too soon.

3	DR. HENDERSON:	Well I don't know if

4	we can read that.

5	DR. STALLWORTH:	It's not very clear.

6	DR. HENDERSON:	Well I'm just -- for

7	those of you who just came in, I was just starting to

8	discuss there seemed to be three major issues that we

9	need to be sure we address in our letter to the

10	administrator, and there are many smaller issues.	But

11	I wanted to discuss this with you and get some

12	interaction whether what I'm saying is correct.

13	DR. STALLWORTH:	What did you say

14	about area monitors?

15	SPEAKER:	Besides Figure 18, make it

16	18 point --

17	DR. HENDERSON:	Yeah.	Can you make

18	your -- for those of us who are ancient and couldn't

19	read that on a bet.

20	SPEAKER:	You want to select and then

21	make it 18.	There you go.

22	DR. HENDERSON:	Okay.	One thing I

23	heard throughout our discussion was the limitations on

24	our monitoring data, and one question is do the area

25	monitors reflect personal exposures?	The second

1	biggest part of that was if we want to have, set a

2	standard for a five-minute peak exposure, do we have

3	the information that would allow us to do that?	And

4	somebody held their hand up, Lianne.

5	DR. SHEPPARD:	Yeah.	I was just

6	going to say that it's not only, it's not specifically,

7	from my point of view, the limitations on the

8	monitoring data but more that the analysis needs to be

9	done to bring out the key features of the data we

10	already have that would inform a number of these

11	questions.

12	DR. HENDERSON:	Appropriate analyses

13	need to be done, so that's, well that's good, Lianne.

14	I do want to state that it's appropriate.

15	DR. SHEPPARD:	So I would say that

16	analyses need to be done to inform key questions in the

17	relevant policy setting and to the evaluation of the

18	epidemiologic studies.

19	DR. SPEIZER:	I fear we're not there

20	yet.	We haven't seen the distribution or anything

21	about where these five-minute averages are.

22	DR. SHEPPARD:	Well, right.	I'm

23	saying that the data that exists needs to be analyzed

24	to help inform what that distribution is so we can

25	start to understand what the monitoring data actually

1	tell us about properties that we would need to

2	understand in order to think about policy and to

3	interpret the health studies in the context of what we

4	know about exposure from the monitoring data.

5	DR. HENDERSON:	Yes.

6	DR. KENSKI:	We didn't talk about

7	this	so much during our previous session, but

8	I was just talking to Jeff Arnold, and some of that

9	five-minute	data and analyses of the five-minute

10	data exist but they're not in the published literature

11	yet.	So in that EPA seems reluctant to use any sources

12	that haven't been previously in the peer review

13	literature, I think this might be a case where there

14	are extenuating circumstances where that data exists

15	and have been analyzed at some level within EPA but,

16	you know, we haven't seen them because they're not in

17	the peer review literature.	But in this case they need

18	to, they need to be in the ISA or otherwise made

19	available so that people can make informed decisions.

20	DR. HENDERSON:	Well that could be something we want to

21	recommend.	Is Mary still over there?	I can't see.

22	Would that be a problem?

23	DR. ROSS:	No, not at all.	I	know

24	that one of the concerns was that the five-minute data

25	that we have available are primarily an internal report

1	that hasn't even been reviewed within EPA, and so if

2	you're comfortable with us using that or continuing to

3	develop on it at this time.

4	DR. STALLWORTH:	Donna, do you want

5	to capture that in a collection of points?

6	DR. HENDERSON:	Just say that --

7	DR. KENSKI:	Even internal EPA

8	analyses of five-minute data need to appear in this

9	document regardless of their peer review status.

10	DR. STALLWORTH:	Thank you.

11	DR. HENDERSON:	Again, we're just

12	getting the major ideas here.	We don't need to

13	wordsmith it too much.

14	DR. SHEPPARD:	Yeah.	I would expand

15	that actually to all internal analyses of all

16	monitoring data need to appear in the document.	I

17	mean, that gets back to my point.	It's not just the

18	five-minute data, which is also important.

19	DR. STALLWORTH:	Okay.

20	DR. ARNOLD:	Yeah.	For the matter

21	the data that are in the document may not be fully

22	published.

23	DR. SPEIZER:	Well if we're going

24	that route it seems to me that part of what they need

25	to do is to give us some information on the

1	correlations between the five-minute, and the hour, and

2	the 24-hour.

3	DR. HENDERSON:	Yeah.	That would be

4	great.

5	DR. WYZGA:	And I'd extend that to

6	correlations with other relevant pollutants.

7	DR. HENDERSON:	Well that was my next

8	major point for issue besides monitoring.	We've been

9	discussing, you know, at all stages of this the problem

10	of multi-pollutant exposures and how you handle that,

11	and what type of statistical analyses are required, and

12	is SO2 a surrogate or is, you know.	That's a huge

13	problem.	The elephant in the room you might say for

14	all of this is to what extent the SO2 is a causative

15	agent or is participating in a multi-pollutant effect.

16	And I seem to think that a lot of the things we've

17	looked at for criteria pollutants, a lot of them are

18	related to combustion products.	I really think it's

19	time for, and the EPA is considering taking a multi-

20	pollutant effect, but I think that has to be discussed

21	as part of our addressing the SOx ISA.	Others can say

22	what points you want to be there.	Lianne?

23	DR. SHEPPARD:	So I'd like to throw

24	out a proposal for discussion about what we might

25	recommend, and that would be that for the epi studies

1	that we see reporting of single pollutant SO2 models

2	followed by, if it's possible to get, joint effects of

3	two pollutants simultaneously followed by, in absence

4	of that or in addition to that, the effect of SO2

5	controlling, i.e. holding constant, one or possibly

6	more pollutants in addition to a discussion about the

7	differences interpretation of all three.

8	DR. HENDERSON:	Did you get all that?

9	DR. STALLWORTH:	Yes, actually.

10	DR. HENDERSON:	Good.

11	SPEAKER:	Lianne, would you also add

12	that if you're going to look at SO2 alone that other

13	pollutants be looked at alone too.

14	DR. SHEPPARD:	Well I have no --

15	SPEAKER:	So if you look at SO2 and

16	then SO2 and say PM, should you also look at PM alone

17	too?	DR. SHEPPARD:	I guess in the

18	context of an SO2 document I wasn't going to go there.

19	I mean, my personal bias would be to move to this

20	multi-pollutant framework for regulation, but we're not

21	there yet.	So in the context of a SOx document -- I

22	mean, I think that's worthy of discussion, but that

23	expands it quite a bit.

24	SPEAKER:	Because of it if you're

25	looking at SO2 alone and you look at SO2 and PM, you

1	see how that changes, but you don't know to what extent

2	the SO2 alone you would have found the same thing if

3	looked at PM alone.

4	DR. SHEPPARD:	Yeah.	So what I was

5	thinking in my recommendation of looking at SO2,

6	looking at, for instance, SO2 and PM changing

7	simultaneously and then looking at SO2 when you hold PM

8	constant.	But those are three different estimates in

9	this complex multi-pollutant framework, and maybe those

10	three different estimates would help people with the

11	interpretation.	You could argue that PM, say, along

12	would also be informative for that.

13	DR. HENDERSON:	Jon, you want to say

14	something?

15	DR. SAMET:	Just going back a little

16	bit to some of the comments that were made in the NOx

17	and thinking about the question of pairs.	So you might

18	be interested in pairs because you're concerned about

19	confounding, and in part the understanding of

20	confounding could come from change and estimates when

21	you put both in the model but also should come from

22	these correlations that maybe even Ted or somebody

23	called for, particularly on the 24-hour indicators

24	which is what is in much of the epidemiological

25	studies.	So the correlations of the 24-hour

1	concentrations of SO2 particularly with probably NO2,

2	and PM, and ozone would be of particular interest, and

3	they're going to be probably correlated to different

4	degrees, different places, and different seasons.	So

5	the question of exploring confounding becomes more

6	complicated once you do that, but those correlations

7	should be examined with the possibility of trying to

8	lay out a better picture for understanding confounding.

9	Another reason to look at the five-minute models, and

10	here I think SO2 and PM are probably of particular

11	interest because of the possibility that SO2 has

12	effects in some way to contributing to particulate

13	matter mass.	And if we knew what component of that it

14	was, I think, we don't, but I think -- again, there you

15	would be interested in the change in estimate if you

16	think the effects of SO2 are being mediated in part by

17	PM formation.	So, again, in the simplest epidemiologic

18	formulation of the model you would expect in that

19	setting that more proximal variable PM to be the one

20	that's significant and exerts the effect in the bi-

21	variant model compared to the univariant model.

22	And then the last is George's proposal

23	that we want to understand effect modification.	And

24	there it's probably a little more complicated, but the

25	interpretation of the bivariate models absent looking

1	for some sort of joint effect I think is a little more

2	difficult.	And what you would expect would depend on

3	whether there was positive effect modification or

4	synergism where perhaps something negative.	So change

5	in estimates there I think a little more difficult to

6	interpret when you, in a sense, put in a bi-variant

7	model, which is the incorrect model since there should

8	be at least statistically an interaction.	I don't know

9	whether Lianne would want to weigh in, but, again,

10	there's reasons to be very specific about laying out

11	this framework when interpreting the models.

12	DR. HATTIS:	Yeah.	I think that

13	requires a different analysis than has usually been

14	done in the literature, and, in fact, EPA might want to

15	cooperate with the investigators who actually have the

16	data in order to address that question.	This basically

17	goes on your hypothesis that the particulates, or at

18	least some of the particulates are a vector for

19	conveying the gaseous SO2 to lower in the respiratory

20	tract then they would get otherwise.	So in order to

21	investigate that you'd have to say, okay, the SO2

22	effect at this level of particulate might be different

23	than the SO2 level at a different level of particulate.

24	So you need to have some structure of dummy variables

25	in there.	So essentially that's probably is not

1	already in the literature, at least not that I know of,

2	but you could ask that question if you had a different

3	analysis of some of the available data.

4	DR. HENDERSON:	Jon, you said you had

5	three ways of looking at this, and Holly and I didn't

6	--

7	DR. STALLWORTH:	You didn't summarize

8	the three.

9	DR. SAMET:	Well so the three were

10	the confounding possibility, the mediating possibility

11	and effect modification, and then of course there's the

12	additional possibility there's a true independent

13	effect.

14	DR. LARSON:	Tim Larson, the other

15	complexity here is that the mixtures don't always occur

16	simultaneously.	It sounds strange but at least for

17	plume exposures, you could be exposed to high SO2 in

18	the relative absence of ozone, whereas immediately

19	prior to that exposure you could be breathing a lot of

20	ozone.	And it's still an open question, I think, as to

21	what is the more important mixture, the combination

22	simultaneously or in sequence.	So it's an additional

23	complexity to throw into the mix and makes it more

24	difficult.

25	DR. HENDERSON:	It's seldom that we,

1	though, inhale things in sequence.	We inhale mixtures,

2	I think.

3	DR. LARSON:	Well, except when you're

4	talking about five-minute exposures.

5	DR. HENDERSON:	Well that's true.

6	DR. LARSON:	And that's where it's

7	qualitatively different, I think than the longer term

8	averages.

9	DR. HENDERSON:	Okay, Lianne.

10	DR. SHEPPARD:	Well it seems to me

11	that the key questions with respect to interpreting the

12	multi-pollutant models are in the context of the epi

13	studies that have been published.	And so those studies

14	by and large, as far as I know, don't have effect

15	modification in them.	So while I agree that it's an

16	interesting question and that the interpretation of a

17	two-pollutant model is different in a model with effect

18	modification than not, the suggestion I was making to

19	look at the simultaneously change in two effects is, I

20	think, the only one that's really practical in the

21	context of the literature as I know it.	Even that

22	requires getting one estimate from the investigators,

23	but it doesn't require a wholesale reanalysis of the

24	data.	I guess I would, in the sense that this is a

25	review of literature, I think that has to be taken off

1	the table, but it certainly should be mentioned as an

2	important thing that could change the interpretation

3	pretty significantly.

4	DR. HENDERSON:	George, yes.

5	DR. THURSTON:	We've been, you know,

6	talking almost exclusively here about epidemiology, and

7	epidemiology is important but so is the toxicology and

8	the human clinical studies.	And there you do have

9	information on the effect modification.	So you can

10	talk about that -- you know, somehow we lost effect --

11	is interactive effects what I'm --

12	DR. GORDON:	Yeah, what, what role

13	does media have an effect?

14	DR. THURSTON:	Well but effect

15	modification is not there, so I --

16	DR. GORDON:	No, that's -- yeah,

17	that's what I mean.

18	DR. HENDERSON:	No.	That's what we

19	meant by that, sorry.

20	DR. THURSTON:	All right.	But I

21	think it's important.

22	DR. GORDON:	These, these should be

23	media, media effects.

24	DR. THURSTON:	So but I'm just saying

25	so some of this discussion would rely on the

1	epidemiology but others can, as we just pointed out we

2	don't have epidemiology like that, but we do have

3	clinical and toxicological.	So I think we can address

4	all of these using the different evidence and just not

5	everything by epidemiology.	I mean, we all love

6	epidemiology, but it doesn't answer everything.

7	DR. BALMES:	You pointed out that

8	earlier Koenig et al 1990 study, which in fact there

9	was preexposure to ozone then exposure to SO2, which

10	changed the sensitivity of the response to SO2.	So

11	that's a --

12	DR. HATTIS:	That's a substantially

13	different effect that you would never, that you won't,

14	you won't find by way of the correlation.

15	DR. BALMES:	Right.	But I'm saying

16	if you look at the toxicological literature as George

17	is suggesting, and especially relevant studies down at

18	relevant concentration, that becomes one of the few

19	that, and of course those study designs, are they're

20	there.	I mean, that's where the data is.

21	DR. HENDERSON:	Well the third thing -- this kind of

22	brings us to the third issue that I was thinking we

23	ought to be sure gets in the letter is the sensitive

24	subpopulations because this very much affects, to me,

25	in what I read, the difference between what you see

1	clinically and what you see in an epidemiology study in

2	that clinically you can pick up the sensitive

3	responders.	You can pick up the effect on asthmatics,

4	but in an epi study that might not be picked up; am I

5	right?	Is that an issue or?

6	DR. HATTIS :	Well I guess on the

7	contrary, the epi study has the whole population

8	whereas of the sensitive population you might	not get

9	the sickest of the asthmatics showing up in your study.

10	DR. HENDERSON:	No.	What I was

11	thinking would you dilute out the effect when you have

12	the whole population.	Am I not communicating here or

13	what?

14	DR. CRAWFORD-BROWN:	I think given

15	Dale's earlier comment about the distribution of

16	thresholds, for example, what you would instead end up

17	with is your low end of the exposure response curve

18	being driven precisely by --

19	DR. HENDERSON:	Oh, sure.

20	DR. CRAWFORD-BROWN:	By that census.

21	DR. HENDERSON:	Okay.	Yes, right.

22	I'm sorry.	Yes.	I did not communicate well.	It was

23	me.

24	MR. AVOL:	I would just add in the

25	context of using sensitive in the way you've been using

1	it in the document, you might also want to put and

2	vulnerable.

3	DR. HENDERSON:	Oh, yes. Vulnerable.

4	SPEAKER:	I think that would be a separate category.

5	MR. AVOL:	Yeah.	But I think if they

6	know the category of people at high risk.	It would be

7	captured here, and vulnerable or put that as a separate

8	--

9	DR. HENDERSON:	Yeah, yeah.	Okay.

10	sensitive and vulnerable makes sense.	We can make it

11	-- okay.	Now those three major issues are what jumped

12	out at me, and you all have given, there's much more

13	detailed review to indicate other things, but are these

14	the three major issues that you think about with SO2

15	or?	I'm just saying, what else should we list up

16	there.

17	DR. SHEPPARD:	I think the recording

18	of the, well, for instance, in Chapter 3 there needs to

19	be some of my comments about the consistency in

20	reporting and the more thorough capturing of subtle

21	issues in the health studies, should be recommended.

22	DR. HENDERSON:	Yeah.	And all of

23	those kinds of things should definitely be in the

24	letter, but I hate to let you start working on

25	something without us discussing major issues.	Okay,

1	Ron.



2	DR. WYZGA:	I wanted to emphasize

3	that it seems important to emphasize the need to really

4	milk as much as we can from the old clinical studies

5	data to summarize what's there.

6	DR. HENDERSON:	Yeah.	That needs to

7	be added to the document 'cause it's important

8	information that we're basing, you know, that we're

9	building on.	Okay.

10	DR. THURSTON:	You know, I think Dr.

11	Ellis' comment about new insights that could be gained

12	from old information I think is a good way to go with

13	that.

14	DR. HATTIS :	And there's a

15	substantial opportunity to do integrative analysis

16	based upon what they know about the exposure

17	distributions and what they know about the

18	susceptibility issues.

19	DR. HENDERSON:	That would really be

20	a recommendation for what should be included in the

21	ISA.	Now are there other issues before we start?	I

22	thought what, Jon Samet said something that I wrote

23	down and put a star by.	The really key thing that we

24	need to consider that needs to come out is it's too

25	early.	I mean, we did this with NOx, but do ambient

1	levels of SO2 cause health effects; is it a problem?

2	And but that will come from the risk assessment

3	exposure document; that's not part of this ISA.	Okay.

4	See, go ahead.

5	DR. SAMET:	I guess where I would

6	disagree is that the presumptions that underlie the

7	risk assessment and its interpretation hinge on what

8	you just said, which is that there is a causal effect

9	at the concentrations that the population currently

10	experiences and that reducing those concentrations will

11	result in reduction of the burden of disease.	And

12	that's underlying everything.

13	DR. HENDERSON:	No.	I guess what I

14	was thinking of was the quantitative estimations that

15	will come in the risk assessment, but the qualitative

16	--

17	DR. SAMET:	But the selection of the

18	concentration response function --

19	DR. HENDERSON:	Yeah.

20	DR. SAMET:	-- is something that

21	certainly this document will have to support.

22	DR. HENDERSON:	Okay.

23	DR. THURSTON:	And I agree with that.

24	I mean, what we're trying to get at is are these

25	associations causal?	And if they're not causal, then

1	there's no point in doing a correlative regression

2	analysis of all the numbers because -- you know, so you

3	need to come to that conclusion that the associations,

4	are the associations causal at ambient levels?

5	DR. HENDERSON:	Yeah.

6	DR. THURSTON:	Right.

7	MR. AVOL:	So now that George has

8	raised the "c" word, do we want to, is it appropriate

9	in this context here to emphasize the notion that Jon

10	Samet described about a consistency about the evidence,

11	the priority of evidence being consistent with, for

12	example, the surgeon general, and the IOM etc in terms

13	of listing causal inference, etc.

14	DR. HENDERSON:	Yes.	Would you word

15	it so that Holly can type it in?

16	DR. STALLWORTH:	Another new point?

17	DR. HENDERSON:	Maybe it's under this

18	one.	You can put it under this one.	Ed, would you

19	restate what you just said?	Are you backing off?

20	DR. COWLING:	Well didn't we sort of

21	convey that to them as sort of a task that they just

22	need to do.	It's not so much that it's a major point

23	that we need to put in the letters.	Maybe it's a one

24	sentence that says we believe the staff has to revisit

25	their definitions and descriptions of the causal chain.

1	DR. HENDERSON:	Okay.	That's good.

2	DR. STALLWORTH:	It's not a major

3	point?

4	DR. HENDERSON:	Well maybe it's time

5	for us to start working on developing our progress.	I

6	thought it would be useful to just have a general

7	discussion.	We seem to be agreeing on most points, but

8	I wanted to be sure.	So why don't we just break and

9	we'll --

10	DR. SPEIZER:	I want to ask, what do

11	you expect on this last point?	If we put that in the

12	form of a question, what are we saying?

13	DR. HENDERSON:	I see that as part of

14	the introduction of what we're trying to do, you know.

15	That the ISA after reading it should inform the Air

16	office as to whether there's a, I'm getting into, I've

17	used the wrong words, whether there's a, there's

18	evidence that ambient levels of SO2 cause health

19	effects.

20	DR. SPEIZER:	But isn't that one of

21	the six original --

22	DR. BALMES:	Rogene, this is John

23	Balmes, could you repeat that closer to the microphone?

24	I couldn't hear you.

25	DR. HENDERSON:	I'm sorry.	I was

1	away from the mic, but Frank is saying this is one of

2	the six questions that's in Chapter 1, page 2.	So if

3	it is --

4	DR. CRAWFORD-BROWN: Well, I mean, are

5	those basically charge questions that the writers of

6	the document had given to themselves and that maybe at

7	the end they should respond to each one of those based

8	on what --

9	DR. HENDERSON:	And that's what Ellis

10	said they did in Chapter 5.	Ellis?

11	DR. CRAWFORD-BROWN: But did they do it

12	explicitly, you know, respond to those six questions in

13	the document?	Did they explicitly go through and say

14	here, you know, this was the question and this was our

15	response?

16	SPEAKER:	Well, that's the point --

17	DR. COWLING:	Yeah.	I think it

18	would be well to -- and maybe we should have a

19	discussion about those six questions right here as a

20	CASAC panel.	Do we think that those six questions are

21	the six that ought to frame the ISA?	That's

22	fundamentally what I think you were getting at, Doug,

23	and there's no specific mention, for example, of those

24	four things we always have to think about, the

25	indicator -- well there is one about level but not

1	about the averaging times for example.

2	DR. HENDERSON:	Yeah.	I think the

3	six questions when I read them, I thought they were

4	well stated, and it does include what we were just

5	discussing.	Don't you think the forms, and I'll ask

6	Mary this again, the four forms are more the Air office

7	area of concern?

8	DR. ROSS:	Yeah.	Our intent is to

9	inform selection, so when you talk about averaging

10	time, we're focusing on short-term exposures and long-

11	term exposures, and we developed that further within

12	like five-minute and one-day, but we don't take it as

13	our charge to select an averaging time or make, draw

14	conclusions about an averaging time.	We lay out the

15	information in a way that then the policy office can

16	evaluate it and offer recommendations to the

17	administrator.

18	DR. HENDERSON:	Okay.	Okay.	Let's

19	break and start writing the paragraphs, and tomorrow

20	morning we will throw them up, the collated letter, all

21	the paragraphs, up on the screen, and have a chance to

22	discuss it then.

23	SPEAKER:	And we e-mail them to you

24	too. Just Holly?

25	DR. STALLWORTH:	Yeah, by 9:00 p.m.

1	DR. HENDERSON:	She turns into a

2	pumpkin at 9:00 p.m. so get your thing in.	Now --

3	SPEAKER:	Prior to going to dinner?

4	DR. STALLWORTH:	Well that's a

5	problem.

6	DR. HENDERSON:	Now tell us about

7	dinner.

8	DR. ROSS:	Actually, can I make an

9	observation about a table that was handed out to you

10	that may be confusing.	That is something that we

11	discussed just at the last minute there that Harvey

12	Richmond will address tomorrow.	It's some of the

13	analyses that Doug Johns has been working on to help

14	inform that we would serve between our office and

15	OAQPS.	And so the table needs some discussion.	You

16	can see it's a draft table with some handwritten

17	comments, so please save it for tomorrow and we'll

18	explain what it all means then.

19	DR. HENDERSON:	Okay.	Thank you,

20	Mary.

21	SPEAKER:	Rogene, for those of us on

22	the phone, if we can get initial updrafts of anything,

23	we're happy to respond as soon as possible.

24	(WHEREUPON, the Meeting was adjourned at 3:47 p.m.)

25

1	CAPTION

2

3

4	The foregoing matter was taken on the date, and at

5	the time and place set out on the Title page hereof.

6	It was requested that the matter be taken by the

7	reporter and that the same be reduced to typewritten

8	form.

9	Further, as relates to depositions, it was agreed

10	by and between counsel and the parties that the reading

11	and signing of the transcript, be and the same is

12	hereby waived.

13

14

15

16

17

18

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25

1	CERTIFICATE OF REPORTER

2	COMMONWEALTH OF VIRGINIA

3	AT LARGE:

4	I do hereby certify that the witness in the

5	foregoing transcript was taken on the date, and at the

6	time and place set out on the Title page hereof by me

7	after first being duly sworn to testify the truth, the

8	whole truth, and nothing but the truth; and that the

9	said matter was recorded stenographically and

10	mechanically by me and then reduced to typewritten form

11	under my direction, and constitutes a true record of

12	the transcript as taken, all to the best of my skill

13	and ability.

14	I further certify that the inspection, reading and

15	signing of said deposition were waived by counsel for

16	the respective parties and by the witness.

17	I certify that I am not a relative or employee of

18	either counsel, and that I am in no way interested

19	financially, directly or indirectly, in this action.

20

21

22

23

24	CHARLES HOFFMAN, COURT REPORTER / NOTARY

25	SUBMITTED ON December 5, 2007



0

0.05% 76:15

0.1 127:24 132:13

0.14 42:25

0.3 28:14

0.4 9:1

0.5 9:1 27:1 28:1,

10

0.5% 79:1

0.6 28:10

0.8 41:1

0.9 147:1

00 100:1 200:1

0002 2:1

0003 3:1

0004 4:1

0005 5:1

0006 6:1

0007 7:1

0008 8:1

0009 9:1

01 101:1 201:1

02 102:1 202:1

03 8:24 103:1 203:1

04 104:1 204:1

05 105:1 205:1

05% 37:15

06 106:1 206:1

209:18

07 7:15 107:1

207:1 209:18

08 7:16, 16, 18

108:1 208:1 209:18

09 109:1 209:1

1

1 30:11 62:19

63:1, 1 64:10 90:12

134:18, 21 150:1

184:14 185:18 194:1

195:1 200:1 233:1

1-2 195:1

1.0 27:1, 17

1.6 141:1

1.8% 100:14

10 9:1 10:1 11:25

27:11 41:1 44:1

79:10 110:1

124:22 147:1, 1,

13, 16, 17 170:1

210:1

10% 103:24 104:1

106:11

10-minute 9:15 27:22

100 31:12 68:1 76:15

136:15 152:13

1000 120:23 152:12

10:00 62:1

11 11:1 111:1 211:1

12 12:1 15:12 68:1

71:22 112:1 163:1

212:1

13 13:1 113:1 213:1

130 153:24

14 8:23 14:1 114:1

214:1

140 43:1 185:17

15 15:1 27:11, 14

108:1 115:1 163:1

210:1 212:1 215:1

15% 183:1

15-minute 27:1

31:1 62:1 150:1

175:11

16 16:1 116:1 216:1

166,000 13:1

168 101:10

17 17:1 117:1 217:1

18 18:1 101:1

118:1 214:15, 16,

21 218:1

19 19:1 119:1 219:1

1971 8:13, 21

1982 9:10

1986 9:11 27:21

152:1

1988 9:1

1989 20:1 22:1 69:1

1990 20:19 163:1

226:1

1994 9:24 40:18, 19

1996 10:1

1998 10:14 11:1

12:20

1:15 148:19

2

2 33:14 62:18, 24

64:11, 22 88:17

99:1, 18 103:14

109:1 133:22

144:1 160:1 163:1

165:18 194:1

195:1 196:1

197:1, 1, 1 233:1

2.4-2 74:1 75:1

2.4-5 86:1

2.4.2 90:1

2.5 60:1, 11, 20

61:1 64:1 65:1

2.51 100:10

20 20:1 27:1 29:23

44:1 120:1 125:16

220:1

20% 106:11

20-year-old 59:18

200 160:1

2000 37:11, 21 79:13

2003 20:10 75:14

147:11

2004 33:19

2005 20:11, 11, 19

75:14 147:11

2006 10:17 70:21

79:14

2007 2:1 7:1, 10

2007/2008 137:19

2008 8:1

2009 11:1

2010 11:1

21 21:1 121:1 221:1

22 22:1 43:1 122:1

222:1

228 100:11

23 23:1 123:1 223:1

237 69:1

24 11:15 12:1

13:19 24:1 101:11

124:1 224:1

24-hour 8:22 20:23

39:19 42:25 77:22

80:14 92:20, 24

150:1 174:17 178:19



218:1 220:23, 25

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106:16 118:18

biggest 77:1 215:1

billion 147:1 152:13

153:15, 24

biological 10:18

51:1 52:1 99:16, 21

108:19 109:1

111:1 118:20, 23

119:10 122:1 126:23

127:1 128:12, 19,

25 145:25 146:12

173:19, 21 175:24

birth 52:16, 17

bit 6:19 10:12, 13

18:15 36:1 49:1

58:1, 10 68:1 77:17

107:13 108:1, 10,

14 114:23 119:17

123:21 125:1, 1

138:1, 1 142:21

144:1 151:24 156:19

166:1 169:22

176:1 182:18

192:1 204:14, 22

212:10 219:23

220:16

bivariate 221:25 black 42:1 blaming 44:14 blood 89:1 90:1

blue 108:24 204:24

board 4:1

boards 24:23

bodies 111:16 158:18

body 50:1 57:11

173:22

boil 202:24 203:1

book 34:13

borne 90:1

bottom 39:25 40:1, 1

75:24 163:17

191:16, 19

box 86:1

boy 186:22 branch 16:1 brand 73:15

break 62:1, 1, 11

148:17 206:15 210:1

212:10, 12 232:1

234:19

breakfast 148:18

breathing 26:10,

17 166:17 223:19

brief 3:25 8:11,

13 28:16 123:16

210:1 212:12

briefly 6:21

108:18 145:18

212:14

brightest 16:23 brilliant 195:14 bring 39:1 64:1 95:1

96:1, 17 97:17 98:1

123:21 154:1 160:22

167:12 205:1 215:1

bringing 81:23 97:24

118:25 166:10

brings 226:22

broad 12:1 68:13



169:11 174:1

broader 174:15 193:1

broadly 74:1 broken 189:15 bronch 149:1 bronchial 134:18 bronchitis
11:11

bronchoscopy 124:22

brought 29:10, 25

31:15 45:18 65:11

81:12 87:13 88:23

94:24 98:22 99:1

107:1 110:1

113:10 143:12

146:20 159:1, 11

163:12 165:19

167:10, 21 171:19

172:13 188:25

189:12 206:1 211:1

brower 22:1 59:18

69:13 70:12, 20

brower's 69:1

brown 31:21 34:23

35:21 58:13

build 16:1 48:1 66:1

101:13 162:1

building 21:19 58:17

229:1

bullet 19:1, 1 21:18

181:1

bulleted 172:12

bunch 77:1 109:11

151:1 167:14 198:24

burden 23:1 230:11

burnett 47:1

business 81:24 89:13

busy 20:16

buzz 109:1

C

calculate 148:1 calculated 104:21 calculating 183:11 calculation 101:1

166:24

california 23:1, 1

24:16 55:12

102:12 139:25

cbc 161:1

canadian 51:1 73:15 cancer 52:10 53:1 candidate 198:1 capture 178:20, 22

217:1

captured 59:1 228:1 capturing 228:20 carbon 40:16 carcinogen 52:13
carcinogenicity

52:14

cardiovascular

50:19, 21 51:1

105:14, 16, 17

210:17

care 33:1 59:24

careful 50:1 98:18

108:22 109:1, 1

carefully 107:1,

13 114:18 131:1

195:1, 1

carlos 117:1

carried 48:1

carry 182:23 200:12

cars 101:13

casac 2:1, 19, 20,

25 3:1 4:1 7:11, 16

8:1 16:25 18:1, 1

19:1 38:18 58:12

84:12 197:16 198:23

199:1, 17 200:1

201:1 205:19 233:20

case 10:13 35:1 36:1

39:19 40:13 41:1,

16 47:1, 10 58:17

75:1 76:1, 1 81:1

99:13 112:11 114:10

141:17 170:15

193:12 202:1

216:13, 17

cases 40:1 41:12

51:13, 13 107:1

140:14 144:17 154:1

casnet 75:13

castnet 71:15, 17

74:1

catch 133:19

categories 65:1, 15,

16

category 64:23, 24

65:1, 11, 25

66:17 71:12

228:1, 1

causal 25:19, 24

31:22, 25 32:1,

1, 1, 1, 20, 23

33:1, 21 34:13, 24,

25 35:1, 12, 17

36:1, 1, 1, 10

43:19 47:14 53:1

58:23 91:18 92:1, 1

111:1 137:1

154:17 172:17

174:19 191:17,

22, 24 230:1, 25,

25 231:1, 13, 25

causality 59:1 105:1

113:1 145:25 146:1,

1, 12 169:1, 1, 10,

11, 13

causally 33:1 191:18 causation 33:16 causative 218:14 cause 12:1 31:1

32:1, 11 35:18,

23 57:1 85:11 87:11

101:20 110:16

113:19 114:24

124:1, 15 135:12

144:18 191:11, 12

196:14 208:1

229:1 230:1 232:18

causes 26:18 35:18

42:18 43:15 61:13

191:10

causing 13:1 51:21

60:18

cautiously 113:1 caveat 187:16 caveats 123:17

167:18, 20

cede 161:1

cement 124:17 143:1,

1

census 96:1 101:1

227:20



center 10:17

centers 199:1

central 48:13 189:1,

1

cents 213:18 century 163:25 cerebrovascular

108:13

certain 5:1 146:23

170:1 193:1

207:14 211:21

certainly 23:1 24:17

30:1 32:24 36:12

45:1 67:11 74:1,

1 75:17 78:21 79:19

80:1 84:1 85:1

93:1, 1, 10, 12

94:1 98:21 104:19

134:10 135:22

155:20 172:10

173:22 181:19 188:1

225:1 230:21

certainty 191:13 chain 231:25 chair 2:10, 17

3:16 4:1 38:24

193:15

chaired 34:11 chairing 4:1 challenge 53:1

122:10

challenged 10:10 chamber 189:23 chance 211:1 234:21 change 23:19 42:1

81:25 104:15 105:1,

1 122:1 123:1 131:1

147:11 148:1

160:1 220:20 221:15

222:1 224:19 225:1

changed 122:14

159:20 164:16

209:15 210:21

226:10

changes 12:1 13:21

21:23 27:21

187:10 204:1

207:1 220:1

changing 22:1 103:25

104:1 220:1

channel 24:1

channels 65:21

chapter 5:16, 17, 25

25:17 49:1, 22,

23 58:15, 18 62:18,

24 63:1, 1 64:11,

22 69:1 76:20

87:1 88:17 89:13

91:15, 20 93:16

94:20, 24 98:1

99:1, 1, 1, 18, 19,

20 101:17 103:14,

18 107:1, 14 108:25

110:20 123:16 127:1

133:1, 1, 22 134:23

135:1 136:10, 16

137:15 138:1, 1,

1 140:17 145:17

146:1, 15 149:1, 1,

12, 12, 15, 18, 19,

20, 20 150:1, 15,

25 151:1, 1, 10,

12, 13 154:11, 12

155:1, 11, 17, 18

156:1, 20, 22,

23, 25 157:1, 1, 11

158:22 159:1, 1, 1,

11 161:24 163:1,

12, 14 165:1, 16,

18, 25 166:1, 1

167:1, 1, 1, 1,

1, 21, 22, 24

168:12 169:1, 19,

20 172:1, 1, 17, 25

173:11 174:21

175:1, 22 176:1,

17, 17 178:1

179:21, 25

180:15, 23 181:1,

23 186:21 194:1,

1 195:1, 1, 11

197:1, 1, 1, 1,

10 200:1 202:1,

18 204:18 210:24

228:18 233:1, 10

chapter's 99:1

chapters 5:11

16:15 19:1 34:13

50:13 62:1 88:17

92:14 149:13 161:14

167:11, 14, 17

168:15 169:1

171:1 172:13

196:1 197:15, 16

202:14

characteristic 97:16

characteristics

21:20 94:13 95:16

96:23 97:1 141:11

159:1

characterization

68:13, 18 70:1

106:1 129:1

characterizations

21:13 67:21

characterize 17:10

21:11 65:14

155:10 182:19

183:15 184:19

characterized 22:1

121:1 211:19

characterizes 57:1

61:14

characterizing 95:20

155:12 209:22

charge 5:13, 14,

16 19:1 25:10

53:1 62:18 64:10

67:19, 19, 22 71:11

107:1 149:1

172:21 187:1

191:1 192:13 202:1,

1 204:17, 20, 21

233:1 234:13

checkerboard 26:13 checking 155:1 chemical 91:21 92:1 chemically 201:24
chemistry 16:1 18:15

65:23 66:1, 20, 22,

24 71:13 73:1, 12

89:23

chief 21:1 chiefly 19:17 child 176:19



children 11:13 39:23

42:20 43:17 45:1

53:18, 23, 25

107:22 161:10

174:1, 13 176:16

chime 188:1

chloride 29:14

159:24

choice 208:15 210:1

choose 190:1, 1

192:1 208:20

chooses 189:22 chosen 101:1 christian 62:19,

20 67:1, 1 102:1

christian's 67:23 chronic 42:21 cigarette 33:1 circuit 10:14 circulate
87:11

199:18

circulates 19:23 circumstance 174:11 circumstances 216:14 cite 70:19

cite-specific 133:25

cited 59:11 61:19

93:25 96:13 127:21

cites 68:1

cities 68:22

71:22, 23 74:1, 1

75:1 94:1, 10 98:1,

10, 24 142:21 143:1

citing 65:13, 19

95:17 97:1, 15

123:18 143:1

city 40:1, 18 42:22,

23 43:1 51:1 53:1

69:1 72:21 94:1

96:1 106:1 139:21

142:11 147:17

claim 69:13 107:16

162:22

claimed 68:23

clarification

70:11 73:21 78:21

95:11 105:24 109:14

143:15 151:19

clarified 75:16

clarify 39:1

190:10 204:12

clarifying 145:24 classic 208:17 classical 97:1 classification 25:15

105:1 180:16 210:20

211:1

classifications

32:21 33:1

classified 33:1 classifies 94:1 classify 211:1 clause 128:24 clean 2:1,
24

10:1, 1 13:1

clear 36:1 55:15

57:17 67:1, 10

68:12 69:15 83:25

121:1 150:1 153:1

156:22 169:18, 24

170:1, 18 174:1

176:1 180:19 181:13

188:1 212:1 214:1

clear-cut 176:25 clearer 79:1 101:15 clearly 34:19 44:1

45:25 48:1 57:25

67:21 94:21

115:1, 10 158:14

172:18 179:1 189:1

climate 18:21

clinical 9:19 25:20,

23 28:17 30:10 33:1

42:14 45:11, 24, 25

50:22 51:1 53:12

91:1 92:17 93:1

95:1 109:20

138:16 139:1, 17,

19, 23 146:11

157:24 158:1

162:11, 13, 18

173:15 174:1, 12

175:20 178:1, 16

179:1 188:13

189:13, 17, 25

192:15, 20, 22

208:19 209:10,

15, 20 211:18 225:1

226:1 229:1

clinically 227:1, 1

close 71:1 77:16

86:21 102:18

109:1 112:1 187:19

closely 17:21 33:19

closer 8:15 14:1

119:1 232:23

closure 158:21

cloud 19:20

cmsa 74:11 77:21

153:1 184:23

cmsas 74:1

co 46:15 53:1

72:15 112:1

114:1, 14 116:10

129:17

co-exposure 126:1

160:13

co-linearity 113:25

co-occurring 78:1

co-pollutant 40:10

41:1, 18 112:1

113:22 114:16

co-pollutants 41:11,

15, 16, 19 42:11

46:19 68:20 72:12

74:12 114:1 124:1

176:1

co-presence 159:20

co-value 46:23

coal 23:1

coal-fired 64:23 coast 22:12 coauthor 142:1 coefficient 41:1

117:23, 23 119:13

121:21 190:1

coefficients

119:20 120:17

coherence 26:1 109:1

134:1 173:1, 16,

21, 25 179:10

180:20

coherent 25:22

144:23 179:1



cohort 59:16

cohorts 111:1 coincidence 208:22 collate 5:25 203:22 collated 234:20
colleague 55:1 colleagues 129:21

154:18

collect 15:12

84:1, 21

collected 13:13

19:13 31:1 37:20

collecting 15:13 collection 217:1 college 139:24 collin 120:14 columbia
12:21 combination 11:21

40:14, 16 120:15

223:21

combined 18:23 144:1 combining 204:17 combustion 19:18

218:18

comes 21:1 39:21

47:12 49:1 65:17

95:14 101:1

108:21 129:10 143:1

184:18 191:13

198:18 200:17

comfortable 127:18

217:1

coming 5:1 6:1 22:11

23:1 27:20 110:10

168:12 173:14

174:15 193:1

202:1 208:1 214:1

commend 135:1

comment 3:12 9:1, 1,

11 10:1 23:1, 22

32:15, 19 36:12

45:14 49:1, 1, 24

55:19 56:11 61:25

74:25 82:15 84:1,

16, 17 86:24 90:1

114:1 117:16, 17

132:12, 20, 21

134:16 139:16

140:17 155:1

161:1 163:14 165:13

167:1 173:1

177:1, 1, 1, 12

181:25 187:1, 13

192:1 200:14 206:22

208:1 227:15 229:11

commented 102:21

192:25 211:14

commenting 30:20 commentor 3:13 comments 5:11, 24

17:1 19:1 31:14

32:16 46:15 56:1,

19 61:10, 19

62:1, 17, 22, 24

63:1 67:11, 23 69:1

70:1 73:1, 13, 25

75:11, 19, 22 78:17

81:13 83:1, 1

86:1 88:17 90:12

91:14 95:1, 13

99:1, 1 101:19

102:20 103:21

105:20 107:1, 1

108:18 109:12

110:20, 22 111:23

115:13 130:1, 15

135:1 138:1 144:1

145:17, 20 146:19

148:15 149:1 151:1,

15, 16 153:13

156:1, 18 157:17

159:1, 17 172:1,

10, 23 174:25 175:1

177:14 178:1 179:20

180:21 181:23

182:14 187:10

191:20 192:1 193:13

195:15 198:20

199:12, 21, 22

201:25 202:1, 11,

18, 23, 23 203:1,

13 205:20, 23, 25

206:1, 1, 1, 10,

12, 13 207:1

211:11, 12 220:16

228:19 235:17

commissions 22:18

committee 2:1, 21,

24, 25 3:1 4:19

34:11

common 91:1 166:20 communicate 227:22 communicated 67:21

164:11

communicating 227:12 communities 103:1 community 69:25

162:22

companies 56:1

compare 70:1 86:21

145:11

compared 53:16

54:1 77:1 91:1

126:1 221:21

comparison 139:20 comparisons 116:21 compelling 29:1 compendium 168:13
compiled 145:14 complaint 10:20 complete 128:16 completed 7:14 60:1
completely 95:1

116:12 140:22

completion 7:1 38:1

complex 89:10 141:1,

1 220:1

complexities 77:18

complexity 78:1

223:15, 23

compliance 85:20

102:1

complicated 221:1,

24

complicates 184:1

component 102:23

116:25 221:13

components 78:11 composing 205:10 compounding 41:19 compounds 60:16

63:12

computationally

169:21

concentrating 196:1



concentration 20:12,

22 28:1 43:1 70:1

90:21 91:10 103:1

127:12 129:1 131:1,

15, 16 132:15 133:1

149:16, 21 152:10

153:15 156:12, 13

157:18, 23 158:1

159:18 160:15 162:1

180:10 185:1, 25

191:14 207:1 226:18

230:18

concentrations

17:1 20:1, 20 21:1,

12 22:1 24:12 27:1,

1, 17 28:1, 1,

14, 15 35:1

37:14, 14 40:24

42:1, 19, 24 43:12,

14 48:1 52:15 53:22

60:1, 1, 1, 10 61:1

64:1 65:20 68:1

69:1, 1 71:19,

21, 25, 25 72:14

77:1, 23, 24

89:1, 16 94:18,

18 103:1, 1 109:1

111:1 130:18

131:1 132:24, 24

135:1 152:1

153:1, 1 157:1

160:12 163:1 166:20

168:20, 25 174:1

186:16 191:1

221:1 230:1, 10

concept 157:1

concern 45:18 80:1

81:1 82:20 128:1

132:22 161:14 178:1

183:13, 14, 22

208:14 234:1

concerned 18:17

105:1 126:19 140:18

220:18

concerns 105:13

107:10 113:24 135:1

216:24

conclude 43:18 51:1

concluded 26:1 42:1

concludes 56:13,

21 61:11, 17 182:1

concluding 180:22

conclusion 12:14

39:14 47:23 48:1

56:12 59:18, 21

60:19 69:1 70:24

82:25 107:15

137:1 181:1 231:1

conclusions 12:1

13:1 47:1, 1, 1

97:18 156:15 167:1,

10, 13, 15, 19

180:13 195:12

197:11 199:1 210:13

234:14

conclusive 54:1

166:1

concur 159:15 204:1,

1

concurrence 6:1

204:1

condensed 203:1,

1, 1 204:10

conditioned 19:11,

12

conditions 138:20 condos 101:13 conduct 13:15 conducted 3:1, 1

12:15 27:1

conference 163:22

confidence 41:10, 22

42:1 48:1 104:21

185:24

conflict 3:19 122:23

conflicting 58:21

59:1

confound 56:23

confounders 52:20

54:21 60:11 139:1

confounding 33:16

51:11 112:14 142:10

176:1 177:23

190:14, 23

220:19, 20 221:1, 1

223:10

confront 29:1

confusing 63:1

100:10 235:10

congratulate 71:1

195:21

congress 83:13 conjunction 91:1 connect 108:15 consensus 5:1 106:19

198:18 202:1 212:15

consent 10:24

consider 13:17 28:23

45:14 51:11 82:1

95:13 110:1

112:14 113:16

123:20 135:19

148:11 155:20

168:14 181:1

183:21, 21, 23

187:23 189:24 200:1

208:16 210:1

211:1 229:24

considerably 40:22

consideration

61:21 95:13 109:1

131:1 176:12

considerations 19:11

77:1 182:24

considered 25:19, 24

40:16 113:1 114:1

124:1 139:13 172:22

176:20 177:1, 18

considering 32:1

33:12 86:11 87:1

95:16 123:24

128:1 218:19

consistency 228:19

231:10

consistent 3:1

25:20, 21 26:1, 1

32:24 34:1, 1

61:1 80:1, 14

86:12, 18 160:23

178:25 184:12

231:11

consistently 26:23

58:1 177:10

constant 121:17

123:1 219:1 220:1



constitution 156:1

166:1, 10

constriction 149:1 construct 93:1 185:1 consultation

205:1, 12, 19, 22

206:1

contact 148:13 contain 186:1 contained 196:1

198:1

context 8:1 11:14

23:1 30:1, 1

81:13 95:1 116:23

122:22 127:1 175:22

180:25 188:11

192:13 193:14, 21

216:1 219:18, 21

224:12, 21 227:25

231:1

continental 20:1

80:11

continually 146:22

continue 176:1

195:19 196:22

continued 126:1

continuing 161:12

217:1

continuous 152:25 contradictory 107:23 contrary 60:22 227:1 contrast
68:1 70:1 contributed 16:15 contributing

202:23 221:12

contribution 22:13

24:19 117:20

control 142:10 185:1

213:1

control-filtered

126:10

controlled 26:22

29:1, 1, 20 65:1

109:1 160:21

controlling 219:1

controls 20:1, 1

54:18 97:14, 15

convenient 91:1

conversion 19:21

63:25 72:1

converting 21:1 convey 203:1 231:21 conveying 222:19 conveys 56:15
convinced 48:11

154:16 167:1 171:1,

1

convincing 181:11 cool 52:14 cooperate 222:15 copy 61:19 203:1 correct
25:1 33:24

80:18 129:1

132:12 197:1

198:1 201:1, 1

204:16 212:25

214:12

corrected 187:17

correction 64:21

132:1

correctly 33:1

35:1 149:1

correlate 61:1 72:15

correlated 40:24, 24

41:17 47:11, 13

60:1, 1, 1, 17 72:1

120:1, 1 121:21, 24

221:1

correlates 78:12

79:24

correlating 78:10

189:1

correlation 40:25

72:1, 11 74:19,

22 75:1 79:23

112:23, 25 115:24

120:19 226:14

correlations 21:16

74:11, 16 77:21

92:23 93:1 218:1, 1

220:22, 25 221:1

correlative 231:1 correspondence 90:16 corresponding 60:1

90:17

corridor 24:1, 1

corridors 22:20

24:13, 25

cost 199:19

cote 4:1 6:1, 11

14:24 16:10

32:10, 14 33:25

34:17 35:1 36:1, 16

130:1, 1, 11, 14

131:17, 24 133:14

counted 111:11

counter-supportive

58:25

countercurrent 87:23

counterevidence

58:22

counterpart 50:1 counting 111:16 country 37:1 68:22

71:20 80:17

county 37:1 83:1, 1,

1, 10, 12, 13

couple 50:1, 15 86:1

93:19 95:11 107:19,

25 136:21 146:24

161:17 169:24

179:20 194:1

course 45:12 46:16

63:1 64:22 66:15

72:15 114:18 120:10

122:17, 20 151:1

160:17 174:1 184:25

187:10 201:1

202:1 204:1

210:15 223:11

226:19

court 10:14 12:21,

25

covered 88:1 212:11

cowling 36:17

38:16 81:1 82:14,

25 83:22 84:1

101:21 140:14 164:1

193:1 197:12, 23

198:1, 1, 12, 16

199:10, 16, 20

201:1, 1 231:20

233:17

crafted 195:1, 1



crawford 58:12

crawford-brown 167:1

203:11 227:14, 20

233:1, 11

credence 115:22, 23 credibility 139:10 credit 199:1, 1

crew 104:1

criteria 4:21 6:13

9:1, 18 17:18, 19

33:1 57:25 58:1,

11, 14 108:1 137:12

141:1, 21 145:21,

23 172:17 177:1

180:12, 17 195:1

218:17

critical 60:18 91:24

157:18 158:11 177:1

189:11 190:1 211:24

critically 157:21 crossover 141:17 crux 49:1 cumulative 27:25

153:17, 23

curious 184:11

current 6:21 8:1

9:1, 25 10:1 11:1

13:13, 14, 16 22:18

42:25 45:1 57:1

69:19 101:25 150:1,

23 152:1 174:1

184:13 185:1, 24

186:1 192:16 193:23

209:12

currently 10:23

47:21 55:11 78:10

79:1 81:1 169:1

230:1

curtsner 125:22 curve 169:1 227:17 cut 20:16

cycles 166:16

 	D

daily 72:25 73:1

86:14

dale 54:12 90:1

143:20 145:1 151:22

154:21 157:1, 17

164:20 202:18, 19

205:1

dale's 227:15 dangling 92:1 dare 162:18

data 13:12 15:1

20:10 30:23, 25

31:1, 1, 1, 10,

11 37:1, 1, 1, 13

43:10, 24 45:11

49:14 50:25 57:1

60:16 71:14, 15, 17

72:16, 20 74:1

75:13, 13, 14

76:13, 21 78:1,

25 80:1 82:10, 12

84:1, 18, 18, 20,

22 85:1, 1, 1,

13, 16 87:17

90:11 91:1, 1 92:23

93:1, 1, 11, 11

94:1 95:1 96:22

97:1, 19, 21

98:10 99:17 101:1

103:11 105:10,

11, 11, 12 112:16

117:14 125:14

140:25 141:12

142:25 143:1 144:1,

1, 22 145:1, 1,

13 147:17 149:17,

25 150:1 152:1,

1, 12 154:15 157:24

158:18 165:1, 18

166:1 180:11

182:1 183:16 185:21

186:1, 1 188:18

192:12 214:24

215:1, 1, 23, 25

216:1, 1, 10, 14,

24 217:1, 16, 18,

21 222:16 223:1

224:24 226:20 229:1

database 45:1 96:1

145:15 186:1

date 7:1 134:10

dc 10:14

david 173:17

davis 14:17

day 5:1, 24 21:12

40:1 55:17 82:24

153:1 166:18, 21

181:11

days 19:22 33:1

126:1 142:19 153:17

164:22

de-couple 136:11

de-emphasize 181:20 de-emphasized 70:24 dead 111:16

deadline 10:17,

21, 24

deadlines 10:19, 25

deal 44:23 45:1, 1

53:1 63:20 81:21

83:15 84:20 176:1

196:19

dealing 25:11

58:13 83:1 105:21

deals 91:17 201:21 dealt 49:15 193:1 death 170:14

deaths 51:18 december 2:1 deceptive 131:13 decide 98:1 143:18 decided
34:1 188:21 decision 10:1, 10,

15 12:24 82:1, 1

111:18 136:1, 1

183:1 196:1

decision-making

34:12

decisions 81:14, 18,

19 157:19 182:1

201:12 216:19

declarative 195:1 decomposition 89:1 decrease 41:10

42:1 51:12, 12

decreased 11:12

40:22 119:13

decreases 12:1

decreasing 65:1

90:14

decree 10:24



decrements 26:24

28:1

deepen 93:17 deeper 158:20 default 111:19 defense 10:12

defer 129:20 154:18 deficiencies 191:21 define 121:1 159:1 defined
143:24 definitely 98:19

110:1 137:1 228:23

definition 121:1

208:1, 1 210:15

definitions 211:1

231:25

definitive 105:1 degree 76:11 degrees 221:1 delay 83:1 deleted 129:1

deliberation 32:1

deliberations 2:22

3:1, 1

delineate 11:20 delivered 92:1 delivery 89:13 demarcation 162:1
demographics 101:1 demonstrate 109:1 demonstrated 22:1

26:24 102:1 161:14

deny 44:12

depend 77:15 222:1

depending 19:23

21:25 97:25

depicted 26:12 depicting 41:1 depiction 20:1 deployed 68:1 deposition
19:20 depositions 65:1 deputy 3:22

derived 152:20 153:1

describe 71:16

78:1 97:15

described 25:17

27:19 105:20

175:1 231:10

description 66:15,

18, 20 71:13

108:1 123:17 141:21

166:1

descriptions 64:1,

12 65:1, 22 67:1

149:13 231:25

descriptor 121:1

design 102:17

130:1 140:25 141:13

211:18

designated 2:19

designed 18:1 19:1

141:15

designing 17:22 designs 226:19 desirable 201:25 desire 85:21 desorbed
88:1, 10 detail 47:25 54:12

55:1 56:19 61:1

108:16 138:1 149:18

189:1 209:16

detailed 64:1

107:1 108:1

109:12 130:1

141:1 151:16 228:13

details 95:1 141:1

142:18

detect 131:14 207:1

detection 21:15 22:1

67:24 69:1, 21

184:25 185:1, 13

186:1, 1

determination

12:22 32:23 57:1

191:25

determine 59:1 determined 102:1 determining 91:25 develop 4:23 188:1

217:1

developed 7:1 36:1

193:22 234:11

developing 17:1

232:1

development 205:14

deviation 90:19, 20,

23

diagram 115:25

dichotomy 30:1, 1

136:1

die 170:12

differ 85:20

difference 20:1, 1

75:1, 1 155:1, 25

169:25 189:1

190:1 226:25

differences 219:1

different 5:12

34:1 35:1 36:19

38:13 41:15 44:16

47:1 50:12 68:21

86:11, 13, 22

90:1 96:16 97:22

109:1 121:1

122:1, 1 126:10

131:13 137:16

155:23 157:1, 12

172:22 179:1, 1

183:13 185:20

194:20 202:14

204:14, 23 208:1,

15 209:18, 23

220:1, 10 221:1, 1,

1 222:13, 22, 23

223:1 224:1, 17

226:1, 13

differential 74:20 differently 126:1 differing 111:1

138:21

difficult 11:20

14:15 36:1 67:25

69:23 79:1 118:1

121:25 169:20 174:1

185:1 211:17 222:1,

1 223:24

difficulty 53:1

122:18 175:10 176:1

diffuses 88:25 digest 18:1 digit 20:24 dilute 227:11



dimension 77:1

diminished 131:10

139:1

dinner 235:1, 1

dioxide 8:22 9:15

72:1, 11 136:1

137:19

direct 91:1 145:14

162:17

directed 182:1, 1

directly 62:1

88:12 120:1 148:1

150:11

director 3:23 6:12

disagree 47:19 48:21

230:1

disagreement 48:25

disciplines 17:17

197:18

disconcerting 73:1 discrepancy 86:1 discrepant 33:20 discuss 26:21

44:24 49:1 50:11

54:23 57:12 61:1

111:1 115:21 118:12

203:24 206:17

212:10, 14 214:1,

11 234:22

discussant 62:20

discussants 5:1, 1

203:20

discussed 50:20 55:1

61:10 105:19 110:24

115:20 142:15

148:12 149:10,

18, 19 151:12

170:19 172:19

180:13, 16 181:12

195:1 218:20 235:11

discussing 28:19

36:10 54:12 77:17

88:13 159:1

171:24 218:1 228:25

234:1

discussion 5:1

29:1 35:20 49:1,

17, 21, 23 54:17

55:16 62:1 68:10

75:1 91:24

108:22, 24 112:13

119:12 121:1 122:25

123:21 130:12

134:23 135:15

141:23 148:1 149:21

150:17 152:14 169:1

170:23 172:16

186:12 187:1 194:1,

18 206:1 207:23

210:1 212:24 214:23

218:24 219:1, 22

225:25 232:1 233:19

235:15

discussions 3:1

33:14 62:17 84:12

disease 128:23

230:11

dismiss 191:1 dismissed 102:22 disperse 24:22 dispersed 20:1 66:1
dispersion 64:1 dissatisfied 185:1 distance 96:10 distinction 71:24

98:21 123:1, 1

133:1, 11 145:25

190:23

distinguishing 53:1 distribute 199:1 distributed 70:14

80:24

distribution 31:11

37:1 43:1, 12

45:1 70:1 71:19

76:22 80:1 90:17

91:1 93:25 99:25

103:22 104:19 106:1

139:20 144:1 147:17

152:1, 18, 25

153:1, 1, 22 154:1,

1 156:14 183:18

215:20, 24 227:15

distributions

74:1, 1 81:1

86:22 90:1 104:1,

23 106:1 152:1, 1

153:1 154:1 169:1

229:17

district 12:21 disturbing 125:1 diurnal 72:25 73:1

166:16

diversity 10:18 divided 201:1 division 6:12 docket 56:19 document 4:17,
18,

21, 22, 24 5:1, 1

9:1, 10, 18, 20

18:1, 1 29:1, 11

30:1 31:1, 1

34:1, 1, 19 36:15

46:14 48:1, 1, 1

63:12 65:1 66:22,

24 71:1 73:10

78:1 97:1 108:21

111:1, 10 112:22

114:1 115:1, 11

118:17 122:23

123:1, 19 127:1

128:1 129:10 132:11

133:11, 20 134:14

135:12 141:1 145:23

155:1 156:1, 1

162:1 170:1

171:25 175:12, 13

176:1 177:1, 10, 19

179:14 183:11

185:23 186:11, 22

187:1, 13, 19,

21, 24, 25 188:1,

1, 16 189:1, 10, 21

190:15 192:1

193:1 194:25

195:1 196:1

200:16 201:16,

18, 23 205:1, 14,

16 207:24 217:1,

16, 21 219:18, 21

228:1 229:1

230:1, 21 233:1, 13

document's 58:1

documents 9:18, 24

17:18 30:12 36:18

55:1, 1 63:1



66:25 108:1

dollars 213:18

domain 74:1 77:13,

19

dominant 44:1

dominants 154:1

done 5:17 7:12 11:17

15:16 27:24 29:20

30:1, 1 40:18

43:1 44:15 69:1

76:13 79:19 85:14

98:1, 20 107:12

116:16 118:1

124:1 130:18

131:1 134:13 142:12

147:1 152:1

154:1, 11 159:22

162:1, 23 163:17,

24 174:22 175:18

176:24 178:1, 1

186:15 189:23

196:14 203:17 212:1

215:1, 13, 16

222:14

donna 71:1 73:18, 25

84:1, 10, 16

167:1 217:1

door 148:18

dose 17:1 19:1

35:13, 19 91:16

99:1 127:22 134:1

144:10 158:13

161:23 174:11

192:1, 1, 17

208:13, 16

doses 92:1 128:1

134:10 168:25

dosimetry 86:25,

25 87:1 88:1

133:21, 22 134:17

dots 108:15 double 202:11 doubling 28:1, 1

143:25

doug 25:1 28:21

167:1 172:1

194:1, 16 199:25

203:16 205:1 213:22

233:22 235:13

douglas 58:12 125:22

downgraded 181:18 downstream 89:1 downwind 66:11

102:10, 14 182:1, 1

dozen 198:1, 1

dr 2:1, 12, 13,

15, 16 3:22, 24

4:10, 14 6:1

7:21, 22, 23

8:16, 18, 20 13:23,

25 14:1, 1, 1, 1,

11, 14, 16, 18, 24,

25 15:1, 1, 1,

15, 17, 18, 23

16:1, 1, 1, 1,

11, 20 22:1, 1, 10,

15, 24 23:1, 23

24:1 25:1, 1, 1

28:18, 20, 22

31:19, 21 32:10,

12, 14, 15, 19

33:25 34:1, 17,

23 35:1, 21 36:1,

13, 16, 17, 21, 24,

25 37:23, 25

38:1, 1, 1, 14, 16,

25 39:1, 1, 1

43:20, 22 45:1, 15,

16, 17 46:1, 1, 1

47:18, 19 48:20, 24

49:1, 1 50:1, 13,

15, 17, 18 54:11,

14, 24 55:1, 13,

20, 22, 24 56:1,

1 61:23 62:1, 10,

12, 14, 25 67:1,

10, 13, 14, 16, 17,

18 70:1, 10, 18,

19, 22, 23 71:1, 1,

1, 1 73:18, 20, 22,

24 75:1, 10, 12,

14, 15, 17, 19,

21 78:18, 20

79:21 80:1, 1, 1,

12, 18, 19, 20, 22,

25 81:1, 1, 1, 1

82:1, 14, 18, 23,

25 83:20, 22, 23,

24 84:1, 15, 17

85:1, 1, 15, 23, 24

86:1, 1 88:14,

19, 21, 22 89:1, 1,

10, 12, 19, 22,

24 90:1 91:12, 14

92:11, 13 93:1,

1, 14, 15 95:10, 18

96:1, 15 97:12,

19 98:1, 1, 12,

25 99:1, 1, 22,

24 100:21, 23, 25

101:16, 21

103:12, 15, 17,

20 104:1, 1

105:24 106:1, 21,

23, 24 107:1

109:13, 15, 17,

18 110:1, 1, 11,

13, 17, 19, 20

112:1, 1, 1, 1,

1, 19 113:1, 1, 15,

17, 21 114:1 115:1,

1, 1 116:1, 1, 1,

13, 17 117:1, 1, 1,

16 118:10 119:16,

21 120:22 121:1,

13, 18, 19 123:1,

15, 19 124:1, 1, 1,

1, 11, 13, 19,

20, 21, 24 125:1,

1, 1 127:1, 1,

10, 14, 17, 20

128:17 130:1, 1, 1,

11, 13, 14 131:1,

17, 21, 24, 25

132:19 133:12,

14, 15, 17, 18

134:15, 16 135:1

136:23 137:22, 25

138:1, 1 139:12,

15, 16 140:1, 1,

14, 16, 18

143:14, 16, 20,

21 145:1, 10, 16,

18 146:17, 18

147:1, 20, 22

148:1, 16, 20, 24

149:1 151:17, 21,

23 154:20, 24



155:1, 1, 21, 25

156:1, 1, 17

157:14, 16

158:24, 25

159:13, 15, 17

161:1, 21 162:1,

11, 13, 16, 25

163:1, 13, 15,

18, 19 164:1, 20,

21 165:1, 10, 11,

12, 14, 15, 21,

23 166:13, 25 167:1

172:1, 1 174:23

175:1 177:15, 20,

21, 22 178:1, 1

179:17, 19 181:1,

1, 13, 22, 24

182:13 183:1, 1, 25

184:1, 1, 17

185:10, 15, 16,

22 186:1, 24 187:1,

1, 15 191:1, 1

193:1, 1 197:1, 12,

13, 23, 25 198:1,

1, 1, 1, 12, 14, 16

199:1, 1, 10, 14,

16, 18, 20

200:13, 18, 21, 22,

25 201:1, 1, 1

202:1, 24 203:1,

11, 16 204:12,

16, 17, 19, 24

205:1 206:1, 1, 18,

19, 22, 23, 24

207:1, 1, 1, 10, 11

208:1, 10, 11,

18, 21, 22, 23

209:1, 1, 1

210:1, 1, 11, 23,

25 211:1, 1, 1, 10,

13, 15, 16 212:1,

1, 1, 1, 13

213:1, 11, 15,

21, 23, 24 214:1,

1, 1, 1, 13, 17, 22

215:1, 12, 15,

19, 22 216:1, 1,

20, 23 217:1, 1, 1,

10, 11, 14, 19, 20,

23 218:1, 1, 1,

23 219:1, 1, 10,

14, 17 220:1, 13,

15 222:12 223:1, 1,

1, 14, 25 224:1, 1,

1, 1, 10 225:1,

1, 12, 14, 16,

18, 20, 22, 24

226:1, 12, 15, 21

227:1, 10, 14,

19, 20, 21 228:1,

1, 17, 22 229:1, 1,

10, 10, 14, 19

230:1, 13, 17,

19, 20, 22, 23

231:1, 1, 14, 16,

17, 20 232:1, 1, 1,

10, 13, 20, 22,

25 233:1, 1, 11, 17

234:1, 1, 18, 25

235:1, 1, 1, 1, 19

draft 5:24 6:1

7:1, 1, 14 8:1, 1

18:24 38:1 54:16

58:1 67:12 70:14,

25 79:20 85:1

148:10 150:1 179:16

197:11 198:1 199:19

203:23 209:12

235:16

drafted 59:1 198:1 drafting 202:16 drafts 34:20 82:12 dramatic 20:13, 17
draw 167:18 170:1

234:13

drive 101:12 102:1

120:1

driven 227:18

driver 177:1

driving 47:15 177:11

186:1

drop 116:24 117:23

droplets 19:20

64:15, 15

dry 19:20

due 21:19 48:15

148:10 199:1

dummy 222:24

duration 27:11

durations 163:1

during 8:1 9:11

11:1, 1 13:14

15:1 23:13, 14

88:1, 1, 1

166:18, 20 216:1

dusting 56:1 dwell 85:1 dying 170:10

E

e-mail 5:24 154:21

202:12, 20 203:20

234:23

earlier 4:18 37:1

44:1 67:1 68:17

78:25 90:1 99:1

103:24 104:1

107:1 137:13 138:14

167:1, 11, 13, 17

168:15 169:1, 1

171:16 172:13

175:16 176:1 187:22

191:20 193:21

194:24 226:1 227:15

early 73:10 81:14

98:19 128:17 134:17

197:15 205:13

229:25

easier 18:1 93:10

152:24

easily 169:25

east 23:21

eastern 20:1 23:18

easy 202:20

echo 159:1

ed 22:25 41:1

42:17 43:14 50:24

53:24 57:1 61:12

88:19, 21 89:1,

25 101:17 103:12

107:17 110:15 112:1

113:1 128:22 135:1,

1 156:18 161:1

186:1 187:1 231:18

ed's 132:12 187:1 ecologist 201:19 edges 107:1



editing 149:11

editorial 204:1

effect 25:18 26:1

30:11 32:1 38:13

39:12 40:12, 15,

20, 22 41:10, 25

42:1, 1 43:20

44:13, 23 46:18

50:19, 21 51:1, 11,

12 53:25 56:25

58:20 60:18 117:19,

22 118:1, 15 119:1,

1, 1, 1 121:15,

21 122:16 125:23

129:19, 19, 24,

24 131:1 150:20

152:10, 12 154:10

163:10 169:1 190:20

207:1 218:15, 20

219:1 221:20, 23

222:1, 1, 22

223:11, 13

224:14, 17 225:1,

10, 13, 14 226:13

227:1, 11 230:1

effective 73:1 effectively 105:1 effectiveness 53:11 effects 11:1, 20

12:1 13:1 17:11

18:20, 22 19:10

25:11 26:22 27:1,

1, 1, 12, 16

28:10 29:13, 15

35:18, 24 39:17,

18, 20 42:11, 16

44:1 48:14 51:1,

23, 25 53:1, 16, 21

54:1 57:1, 19

60:12, 25 70:1

78:14 87:11, 12, 16

91:11 99:15

103:18 105:1, 14

107:11, 15, 21,

21 108:1, 13, 14

118:18 119:1

122:1 124:14 125:14

129:14 132:13

134:23 136:10,

12, 14 137:11 140:1

142:13 144:25 148:1

150:1, 10, 22 152:1

160:1, 11 168:14,

16, 19, 21, 23

169:1 171:1, 1,

22 172:22 174:1,

14, 15 176:16,

23, 25 177:24

184:1, 10 189:18

190:1 191:1, 10,

15, 18 194:15

201:14 207:19

209:23 210:18 219:1

221:12, 16 224:19

225:11, 23 230:1

232:19

efficacy 54:20 efficient 72:24 efficiently 72:20 effort 6:12, 15,

17 13:10, 10

54:22 73:16 102:1

122:23 143:17

147:14 148:1, 11

195:19, 22

efforts 22:19

eight 30:22 187:1

192:14

eight-hour 209:18

either 26:1 49:17,

18 55:1 65:21 78:13

95:1 100:1 102:1

105:11 108:11

111:16 113:1 130:23

137:17 158:12

173:14 176:18 184:1

209:23

elaborate 189:1 electric 19:18 elephant 218:13 elevated 9:1, 22
eliminate 112:11 eliminated 66:1 elizabeth 99:25

ellis 38:14, 25 81:1

82:1 146:20 193:1

198:10 200:13, 19

202:1 229:11 233:1,

10

email 203:1 204:25 embarrass 184:1 embedded 131:17 emission 22:16, 23
emissions 17:1 23:13

24:21 63:14, 14,

15, 17, 19, 20

64:24 65:1, 1, 1,

17 102:21

emitted 51:20 emitters 20:1 else 14:12 49:20

62:1, 1 63:10 88:10

99:1, 1, 22

101:20 113:19

129:10 160:25

161:1, 1 195:23

228:15

elsewhere 135:12 eluded 12:19 endangerment 10:1 endeavors 188:16
endpoint 82:11

132:1, 14

endpoints 155:11

emphasis 6:16 36:1

58:1, 15 63:1, 1,

1, 11, 23 64:22

70:1 74:1, 10, 17

87:1 210:16

emphasize 4:15

30:1 38:19 62:21

80:1 87:18 193:20

229:1, 1 231:1

emphasized 81:12

88:1 133:10 203:14

emphasizing 176:1 empowered 2:25 engaged 13:1 engines 24:1 enhance 90:1

enhanced 27:10 132:1

134:20

enhances 126:1 enormity 143:11 enrolled 139:22 ensure 3:1



entered 10:24 124:22

entire 45:22 48:1

194:11

entirely 131:13

168:1

epa 2:21 4:1 6:10

8:13, 21 9:1, 17,

25 10:1, 1, 1,

15, 15, 18 12:15,

17, 17, 22, 24,

25 13:1 22:23

50:1 58:16 60:1, 22

65:1 81:21, 24

154:18 188:15

189:22 199:1, 1, 15

208:1 216:11, 15

217:1, 1 218:19

222:14

epa's 60:19 61:1

134:12

environment 177:12

environmental 2:1

10:11 89:1 186:15

environments 138:22 envisioning 202:14 epi 39:1, 10 45:1,

1, 21 50:22 53:17

57:1 59:11 61:1,

14, 17 72:13

78:16 93:1 95:1

97:23 109:21

112:1 122:11, 21,

22 147:24 149:25

162:14 166:1 180:11

185:17 188:13

190:1, 1 218:25

224:12 227:1, 1

epidemiologic

11:17 52:1, 1

105:25 106:1, 1,

1 107:11, 18 109:1,

1 125:14 126:24

128:1, 10, 11

129:21 162:10

215:18 221:17

epidemiological

25:21, 25 26:1

28:19 33:13 39:17

42:12 50:1 51:1

52:23 53:12 54:18

56:24 68:19 69:18

91:25 92:16, 19

93:1 98:1, 11

132:25 139:1

154:15, 17 157:24

158:11 173:15

175:20 178:14,

19, 24 184:21 193:1

211:19 220:24

epidemiologist 39:1

epidemiologists

74:21

epidemiology 29:1, 1

39:21 69:22 125:1

133:1 146:25 160:17

174:16 181:10

225:1, 1 226:1,

1, 1, 1 227:1

episodes 11:18, 19

epri 159:22

er 149:1

equal 115:15, 22

116:1, 1 117:25

equivalent 49:25

133:1 134:10

error 49:20 94:1

97:1 117:25 139:1

et 22:1 40:1, 1,

1, 11, 17 41:13,

14, 14 42:1, 1 43:1

59:19, 21, 23 60:23

123:25 142:1

163:1 226:1

especially 66:25

89:1 108:10

110:1, 25 111:1

143:17 159:17, 19

161:22 190:13

226:17

essence 157:12

essential 194:20

195:10

essentially 44:11

69:1 90:20 91:1

152:19 153:1, 14

155:17 222:25

establish 85:1

117:18 191:1

establishing 10:1

12:12

estimate 9:21

13:15 40:12, 22

41:10, 25 44:1 68:1

97:1 106:10 120:15,

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28:17 45:11, 25

50:22 51:1 53:12

68:25 92:17 93:1

125:1 133:1, 22

134:1 135:1

137:20 138:15 139:1

145:15 146:11

175:20 178:1, 15

179:1 188:12

189:13, 24 225:1

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hyperresponsiveness

125:15 126:25 128:1

hypersensitivity

125:18 126:22 132:1

hypothesis 222:17

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23 77:1, 19, 25

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15:24 16:1, 1

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1, 12 30:15 32:11

33:12 37:1 38:1

39:1, 1, 1, 12

42:10 43:23

44:14, 25 45:1

47:16 48:10, 17

55:22 56:1, 1 57:1,

12 61:21 63:1 73:22

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87:1, 16 89:25 93:1

96:15 97:14 101:20,

23 102:15 103:1, 10

110:17, 23 112:1,

20 115:20 116:11

117:1 119:21

123:10, 25 126:19

129:1 140:18, 21

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151:1 158:1

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168:1, 1, 12, 13,

17, 21, 24

169:14, 14 170:14

173:20 174:18 175:1

177:1, 12, 17, 22

181:1 182:12

184:1 192:1 193:1

194:24 195:12

198:1, 12, 16

200:14 202:13

206:14, 25 207:20

210:1 212:19, 21

213:24 214:1, 12

215:22 225:11, 24

226:15 227:22

228:15 232:16, 25

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111:22, 22, 23

119:22, 24 121:12

145:13, 14 154:13

164:11 168:15

173:16, 17 192:1

195:1 196:14 199:21

203:12 232:16

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32:1 191:25

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153:21 154:10

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inconsistent 52:1,

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27:1 43:1, 1

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10 42:17 78:14

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60:1 93:1 100:16

105:14 112:1

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196:12, 16 200:20

211:20 233:25

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18, 20, 22 94:17

184:16 185:1

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100:12

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27:21 53:16

125:17 129:1

inducing 132:1 industrial 68:1 industry 56:10 infer 56:25 inference
33:1, 21

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210:1 215:10, 16,

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24 30:23 37:10,

20 38:1 56:16

57:13, 23 69:23

72:10, 24 76:1, 1

77:25 78:1, 22

79:1, 18 92:16

95:25 97:1, 11

100:1 102:1, 1

103:13 104:14, 19

114:16, 17, 22

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22, 23 131:1 132:1,

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188:1, 15 194:12,

13 213:1, 1, 1

215:1 217:25

225:1 229:1, 12

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65:14 77:12 78:14

104:16 150:14, 24

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141:13, 19 142:22

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78:23 94:1, 12,

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23, 25 97:22 98:13,

22 107:1 116:24

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10 163:20 164:17

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181:1 187:1 191:1

192:21 193:24

195:15 196:1, 1,

17, 19 201:19

203:1, 14 205:14,

15 206:1, 14 217:18

223:21 225:1, 1, 21

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119:17

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154:1 172:1 191:23

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inside 74:1 136:18

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131:18 146:10, 11

193:20

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164:12, 16, 18

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inspiration 88:1, 1 install 83:11 instance 43:1

52:10 63:20, 22

96:1 97:1 141:16

142:16, 18 143:1

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1

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integration 108:10

136:24, 25 149:12

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integrative 229:15 intended 136:25 intent 155:10 234:1 inter 145:15

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120:1

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145:15

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14 130:17 199:11

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122:21 123:1, 1,

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221:25 224:16 225:1

230:1

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180:25

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92:10 97:19, 23

98:11, 13 117:18

118:1 121:23 140:1,

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41:10, 22 42:1 48:1

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24:21

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224:22

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89:23 184:1 202:1

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16:16, 17, 22, 24

18:1, 11, 24

19:12 20:17 24:1

25:17 30:24 31:1

36:23 37:22 47:21

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13, 20, 24 57:1,

10, 13, 17, 23,

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14, 16, 20 61:1, 1,

1, 10 63:1, 1 66:22

67:1 70:15, 21 71:1

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112:15 115:12

117:17 140:19

141:10 146:20

148:12 149:10

150:1, 1 168:1,

1, 1 169:17 172:1

182:11 191:1

192:1 194:11 201:10

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209:22, 25 216:18

218:21 229:21 230:1

232:15 233:21

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80:15 84:1

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17:15 22:15 23:1

24:11 35:12, 17

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10 63:18 67:10

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14, 15, 17, 18 77:1

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21 83:1, 10

84:19, 20 85:1,

18 86:1 87:13, 14

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19 100:1 104:1,

24 105:1 106:11, 16

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15, 16 117:11,

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124:1, 15 125:1, 1,

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144:19 145:10

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163:25 164:1, 17

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170:17, 18

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187:1, 18 189:12,

22 190:16 191:1

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215:1, 1, 14 217:17

218:18 219:1 221:24

223:20, 22, 25

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229:1, 24 231:17,

22, 22, 23 232:1, 1

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127:24 128:19 146:1

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34:11 38:22 40:11

43:23 45:1, 1

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107:1 108:1, 19, 22

110:1, 23 111:1, 1,

12 112:17 113:1

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167:1, 17 169:23

172:15, 20 176:19

178:17 186:10 187:1

188:25 189:1, 11

190:1, 1 192:17

213:1 218:1

226:22 227:1

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36:1 99:14 100:11

102:15 110:21

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107:1 176:1 193:1

195:1 201:11 213:22

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33:25 34:17 35:1

36:14 45:15 46:1

55:1 58:1 117:15

124:1 125:1 127:1

133:1 134:19

135:1 157:14 175:25

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219:1 222:1

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229:22 231:1

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106:13

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59:1 131:11

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133:24 174:25

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54:24 110:1

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143:16 147:1

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210:11, 25 211:1

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145:14 182:20

192:12 228:23

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106:25 107:1 113:17

114:1 163:1, 18

kinney's 113:15

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160:1 226:1

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105:10, 12 114:21

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land 94:13 95:16

96:16

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large 20:1, 1, 19

24:17, 19 68:10, 22

76:24 79:15

139:23 151:1 171:1,

12, 14, 15, 21

224:14

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157:17 174:17

larger 10:20 53:25

101:14 147:1 158:18

largest 64:24

larson 2:12, 15

14:14, 14 67:10,

14, 16, 18 70:18

181:1, 1 223:14, 14

224:1, 1

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last 6:1 7:1 19:1

21:11 22:19 24:20

29:23 30:1 35:1,

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54:1 87:1 99:1

161:1 163:24

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10, 15, 22 204:1,

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232:11 235:11

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82:24 92:14 108:21,

25, 25 111:1

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107:14 125:20

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111:10 114:1, 20

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138:24 148:11

149:17 150:25

151:25 153:18 158:1

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18 223:1, 16

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lengths 50:11 lengthy 49:16 less 21:25 37:15

65:10 76:14

115:24 118:14

120:13, 13 140:1

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152:13 158:14, 14

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35:1, 24 56:18 94:1

103:1 152:17

153:18, 21 154:1

169:10, 11 185:1,

24 186:1 196:15

207:18 216:15

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233:25

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32:1 34:25 36:11

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61:12 68:14

69:19, 24, 25

90:1 91:1, 1, 1

99:14 102:1

131:1, 1 132:23

133:24 138:19

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150:10 152:1 158:14

160:1, 10 169:14

171:1, 17, 23 181:1



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22 184:13 186:19

188:24 193:25

208:17 209:12,

13, 23 230:1

231:1 232:18

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121:12 124:10

140:17 143:15

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158:24 178:16

179:18 181:1 203:13

204:11 205:1 215:1,

13 218:22 219:11

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life 31:17 162:21 lifetime 19:21 lifetimes 20:1 likely 9:23 13:11

25:24 43:19 49:14

58:22 137:1

149:24 152:11

158:12 195:21

limit 21:15 22:1

53:1 67:24 69:21

184:24 185:13 186:1

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214:23 215:1

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13 54:1 68:18

70:1 125:14, 16

126:23 128:1, 1,

10, 11, 13 129:20

141:1 143:1 162:1

164:14 185:1 186:1

limits 69:1 86:1

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75:24 93:19

125:16 157:1

171:1 173:20

191:16, 19

linear 120:15, 16

150:22

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69:14

lines 11:15 78:1

90:18 157:1 166:14

lining 87:15

link 161:16 186:14 linkage 113:1 linked 183:10 linking 51:17 liquid
87:15

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136:12 138:1

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117:12 125:22

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listened 212:19 listening 172:10 listing 168:15 203:1

231:13

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122:10 125:11, 13

128:14, 16 129:1

134:11, 12

216:10, 13, 17

222:14 223:1

224:21, 25 226:16

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10:12, 13 14:21

18:15 26:14 36:1

49:1 58:1, 1, 10

72:20 73:1, 1, 11

77:17 78:24 79:1

90:23 95:15

105:1, 19 107:13

108:1, 1, 10, 14

109:23 114:16

123:21 125:1

129:1 138:1, 1

142:21 144:1, 1

150:1 151:24 156:19

166:1 172:25 182:18

185:1 192:1 194:1

204:13, 22 212:10

220:15 221:24

222:1, 1

live 103:1 183:20 living 171:11 llorca 41:14

lo 195:10

load 90:21

local 20:14 24:19

94:1, 1, 10, 14

95:17, 19 96:23

97:1, 10

localized 12:1 77:1

locally 81:1 locals 111:1 located 68:1 locating 101:22

location 68:1 74:15

locations 69:21 70:1

77:20

log 90:1, 17 91:1

144:1

log-probit 144:1 logged 80:24 logic 175:1 logical 109:24 logically
156:25

long 12:1 23:1 51:23

52:24 81:24 85:1, 1

196:10 210:1 234:10

long-term 11:10

17:12 51:25 52:1

59:16 129:14 210:18

longer 174:16, 17

224:1

longing 194:16

longitudinal 129:16,

22 130:1

loop 102:18 loosely 151:1 los 23:1

lose 155:17

loss 88:1

lost 142:1 161:1

163:11 225:10

lot 22:10 32:1 39:13

46:10 47:11 62:1

68:14 71:1 72:1

81:1 95:1 130:1

134:10 137:1

138:15, 16, 17

139:10 145:20

155:1, 24 156:22

160:14 162:21



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171:1, 1 178:1, 1

179:1 187:10 195:23

209:14 218:16, 17

223:19

lots 99:1 139:24

159:22

loudly 14:19

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226:1

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12 28:1 52:17

64:17, 17 68:1,

14 69:19, 24

89:15 90:1 99:15

102:1 111:1

131:1, 15 134:21

181:1 186:16 189:16

227:17

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29:1, 15 42:1

43:1 87:1, 1, 1, 14

89:14 131:1 158:13,

14 160:10, 12

184:14 185:17

189:20, 20 207:25

222:19

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17, 21 186:25

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12:1, 20 13:1 15:10

28:1 29:18 38:1, 10

52:1 81:22, 22

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maciorowski 3:22, 24

67:13

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109:1 175:19

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30:19 31:12 52:22

64:11 65:14, 25

77:16 141:22 155:25

177:1 206:17

207:1 210:1 212:11,

14, 15, 20, 23

213:1 214:1

217:12 218:1

228:11, 14, 25

231:22 232:1

majority 149:14 manage 84:13 managers 200:1 manages 84:12 map 68:16

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marine 22:17 24:1 mark 127:24 157:13 martin 4:10 martin's 7:24

mary 4:23 16:1, 10

29:19, 21 30:1

99:1, 10 106:22

149:1 199:10 216:21

234:1 235:20

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162:14

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89:1 179:12

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54:23 105:1

109:25 129:18

135:24 149:23

166:18 172:21

217:20 221:13

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134:22

max 15:13 20:21

77:23 84:22

150:23 171:24

maximum 90:20, 24

may 7:11 22:1

38:12 41:1, 17

51:21 57:20 60:19

61:22 62:1 65:1, 16

68:20 76:1, 10 83:1

84:1, 22 88:12

101:23 105:1, 11

110:24 111:21 119:1

128:15 131:1, 12

138:1 140:1

147:16 148:25

150:22 153:25

176:1, 10, 22

184:12, 12

186:19, 20

190:19, 20 191:17

193:15 206:1, 10,

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217:21 235:10

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1 63:18 66:23

67:1 72:12 73:11,

21 75:1 86:1

90:25 103:25 109:20

110:14 111:12

116:11 127:1 137:11

150:14 157:25

158:21 163:22 164:1

168:24 176:14

179:24 180:1

182:1 188:1

190:18 195:16

220:1, 22 231:17,

23 232:1 233:1, 18

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23:10 24:10 30:1

32:25 33:13 44:11

46:25 47:14 50:1

81:1 82:18 85:15,

20 95:15, 18

105:1 114:1, 13

116:1, 14, 15,

19, 25 117:1 118:1,

10 119:1, 14 123:12

124:13 127:17 129:1

130:22 131:1 136:17

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140:23 141:10



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150:1 159:10

160:13, 21 163:1, 1

170:14, 24 171:1

177:17 183:1 185:10

192:1 199:21 200:16

203:17 204:1 208:13

217:17 219:19, 22

225:17 226:1, 20

229:25 230:24 233:1

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meaningful 4:24

5:1 46:13, 25

120:13

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31:25, 25 32:1, 1

50:1 87:1 90:22

146:25 154:1

173:18, 22 207:1

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123:13 135:18

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measure 116:20

176:10

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77:14 117:25 178:18

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56:22 57:15 68:11

75:22 76:25 77:1,

18 78:1 80:13

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57:14 59:12, 13

61:1 76:1 81:11

83:14 92:21

102:25 103:10 154:1

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174:17

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130:19, 24 131:1,

14, 18, 20, 23

132:10 134:22 173:1

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12 157:25 158:1, 1

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132:16, 17 134:1

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16 7:17 8:1 34:1

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3:1, 10, 11

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16:13, 25 19:1

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memory 38:24 mentally 116:24 mention 4:1 10:23

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1 67:1 69:20 90:1

125:12 129:23

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187:16, 18 188:1,

18 194:20 200:1

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197:13, 19

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methods 15:1 67:1

68:11 207:12

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23 13:24

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232:23

midrange 107:21 mike 69:1 88:14 mike's 6:23 milds 140:12 milk 229:1

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mind 8:1 38:10 140:1

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minimum 22:1 142:19

minor 100:1

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55:25 62:1 90:25

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163:1, 1 196:18

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126:18

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121:16, 22 122:1,

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158:16 172:12 190:1

220:21 221:18,

21, 21 222:1, 1

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63:24, 24 64:1

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112:15 113:22

115:23 117:19

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218:10, 15 219:20

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112:24 115:10

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129:17 142:13

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80:1

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30:11 46:1 90:1, 17

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166:1 174:1, 13

176:16 182:1, 10

222:1

period 9:11 20:10

27:13 61:25

92:25, 25

periods 23:14 90:1

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88:1 103:19 149:1

170:1 171:11 184:1

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14, 17 22:1, 1

56:23 57:15

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1, 1 61:1, 1

69:1, 1, 24 94:17

178:1 188:25 189:1,

1 213:1 214:25

219:19

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86:1 134:24

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perspective 12:1

68:20 69:19 70:1

98:15 188:20

pertinent 81:11 pervades 208:1 petroleum 3:14 56:1,

1

ph.d 55:1

phase 18:14, 16

64:13 201:1

phenomenon 170:1 philosophical 135:15 pick 6:23 46:1

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118:15, 23

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115:1, 14 116:18,

19 120:23 121:1

221:1

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67:15 110:1, 15

124:1 125:12

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172:1 179:1 182:1

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16 132:19, 20

175:1, 1 177:20, 22

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physical 91:21

92:1 152:23

placement 102:1

103:1, 1

places 11:18 24:17

79:16 95:24 127:1

156:14 169:24 170:1

182:13 221:1

plan 7:1, 1 15:1

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plant 63:17 64:23

65:24 102:11, 15

124:17 143:1, 1

plants 23:1 65:15,

24 66:1, 17

plausibility 26:1

51:1 52:1 99:16, 21

108:20 109:1

111:1 113:1 118:1

126:23 127:1, 19

128:13, 19, 25

146:1, 12 173:19,

21 175:24

plausible 25:22 plausibly 108:12 play 60:15 76:1

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12:16 16:1, 17,

21 17:12 18:25

19:15 20:1, 14 21:1

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60:1, 1, 11, 12,

19, 20, 23 61:1,

1 63:10 64:1 65:1

72:15, 15 77:1

78:11 99:13 113:1

116:10 117:23

118:1, 13, 15,

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119:1, 1 120:1,

1, 1 123:18

135:21 142:25 143:1

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11 221:1, 10, 17,

19

pm-10 40:13, 21,

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80:23 81:1 86:1, 17

120:1 144:1, 15

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86:12, 19 90:10

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plume 66:1, 1, 1, 12

77:1 183:20 223:17

plumes 65:24 plus 119:1 point 8:1 17:1

19:1 23:17 27:1,

15, 25 28:12

29:25 30:20 33:23

37:1, 1 38:15 48:13

55:1 58:13 63:1, 1,

1, 14 70:10, 11, 23

73:13, 21 74:1,

25 87:20 88:24 90:1

95:25 96:21 97:13

98:13 100:1

101:14 102:19, 19

107:16 108:1 109:18

111:14 112:15 115:1

117:16 121:19

129:11, 13 132:18

134:1 135:1 137:1

140:1 143:22 150:18

154:1 155:1

159:1, 19 163:1

164:19, 22 170:21

176:1 177:1

188:20 202:1 214:16

215:1 217:17

218:1 231:1, 16, 22

232:1, 11 233:16

pointed 24:16 34:1

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135:23 176:1 226:1,

1

points 21:1 55:1

57:1 62:22 67:1

74:1 78:20 90:18

95:11 96:16

111:15 135:1 167:24

170:22 172:12 179:1

205:10 206:17

212:11 217:1 218:22

232:1

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53:11 175:12, 12

179:22 183:13, 24

187:22 188:14 191:1

194:1 195:1

197:19 200:1 208:15

215:17 216:1 234:15

polite 162:19

pollutant 40:21

41:20 42:1 46:1

47:13 54:18 60:1

104:17 113:13, 24

114:1, 15, 19

115:23 117:1

118:1 119:1, 1,

14 122:1, 19

133:1 147:25

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190:16, 21 218:20

219:1

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17:19 33:12 40:14

46:17, 22 47:11, 14

48:16 53:1 74:15

78:10, 13 112:1

113:14 119:12, 19

120:17 121:16,

20, 22 122:1, 14

123:1, 1, 12 142:14

144:18 159:21

190:24 191:1 192:22

218:1, 17 219:1, 1,

13

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37:14 43:1, 1 76:15

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1, 13, 16, 17 160:1

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185:17, 17, 18

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13:16 44:1, 1, 1,

1, 19 45:22 46:1

53:17 94:1, 1, 15

95:21 96:13, 24

97:1 98:17 100:1

101:1 104:1, 1

105:1, 22 106:1, 14

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11, 24 152:15,

16, 18 153:1, 1

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170:12 171:13,

15, 21 176:23

178:22 181:1 182:1,

1, 20 183:1, 12, 17

188:14 189:1 207:16

209:24 227:1, 1, 12

230:1

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100:1



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111:1

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110:1 111:11

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16 102:12

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105:11, 18 107:25

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11 223:10, 10, 12

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56:17 75:23 82:1, 1

87:12 93:1 100:1

104:1, 24 134:13

137:24 147:23

150:12 166:22 180:1

181:19 183:16 219:1

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12 110:11, 15

112:19 116:1 119:16

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17 157:16 186:1, 10

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110:21

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110:17

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192:18

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20 74:10 80:10

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potentiation 190:13,

14, 19, 23

power 41:23 63:17

64:23 65:15, 23, 24

66:1, 17 102:10, 15

ppm 10:1 12:1

27:1, 17 28:1,

10, 14, 15 43:1

134:19, 21, 22,

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224:20

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28:23 30:1 36:1

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110:12, 15 115:24

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161:13 186:1

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13 230:1 235:1

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processes 193:11 processing 75:1 produce 18:1

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130:22, 25 132:15

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60:13, 19 65:17

67:22 68:24 74:24

75:1 82:1 88:15, 23

91:16 92:1 94:1

107:1 112:1 115:1

124:10 130:16 146:1

147:23 149:1 150:12

155:1 158:1

168:10 169:1, 13

172:21 173:1

174:1 179:13

181:25, 25 182:12

184:1, 1 187:1,

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190:12 191:1, 19

192:14, 18 197:19

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207:20 210:10, 12

214:24 220:17 221:1

222:16 223:1, 20

224:16 232:12

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15:19 19:1 25:1,

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20, 22 207:1

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173:16 175:1

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30:1, 1, 1, 15 31:1

34:15 44:12 45:1

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13, 15 50:1 63:11

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25 76:1, 11 77:15

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15 181:25 182:11

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reason 64:14, 16

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reasoned 19:13 reasoning 171:1 reasons 23:17 194:24

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144:19

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recommendation 220:1

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15

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25:17, 24 26:1, 1

42:15 43:1 92:1,

20, 21 96:1 129:1

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14 86:1 132:23

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1, 15, 18 172:1

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13, 18 189:22 191:1

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34:14 35:11 37:1

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research 29:25

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71:11 72:18 73:14

85:1 93:18 96:18,

19, 22 97:1, 22

98:13 124:18

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180:17 224:11

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26:15 27:1, 15

28:11 39:18, 23

41:1 42:1, 16,

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173:1 185:1

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17 216:12, 17 217:1

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167:25 168:1, 1, 1,

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121:1 124:19 131:18

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S

sab 3:18, 23 safety 194:1 salient 29:25, 25

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16 212:1 220:15

223:1 229:22 230:1,

17, 20 231:10

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scanlin 125:23 scattered 184:11 scattergram 86:1 scattergrams 86:19 save
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14 123:25 142:1

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21 6:15 7:1, 13 8:1

15:24 17:1, 13, 20,

24 18:10 19:12

44:12 56:14

57:12, 22 162:1

182:19 195:1, 1

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164:12, 12 168:1

193:19, 20 194:14

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187:24 207:12

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142:20

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33:1 38:1, 1 47:1

57:12 68:24

70:20, 25 77:1

79:20 87:20 89:1

99:24 107:16

127:1 148:10

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137:1, 1 149:16

150:16 151:1

156:1 158:20

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218:16 232:1

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104:1 105:23 125:24

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176:1, 1 185:20

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216:11 217:24

224:10 229:1

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segment 44:1 seigneur 62:19, 25 seldom 223:25 select 16:1 214:20

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139:19 141:21

230:17 234:1

selectively 104:1

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94:14 95:22

100:19 105:1 116:12

138:18, 23 157:1

160:20 178:20 179:1

183:24 197:17

198:10 208:17 222:1

224:24 228:10

sensi 130:24

sensitive 164:23, 25

165:1 168:18 176:14

226:23 227:1, 1, 25

228:10

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159:1 183:18 226:10

sensitization 126:1,

1 132:1 134:20

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126:1, 1, 13

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161:17 193:18, 19

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135:18 136:1

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20 135:19

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94:1, 1 97:1, 1

172:1 209:17

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session 148:21 216:1

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76:1 157:1 192:23

215:17 221:19

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42:23 51:1 53:1

59:1 103:1, 21

110:1 127:1

179:1, 1 181:16

193:10 196:14

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42:17 153:19 209:24

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75:1 she'll 4:1

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96:15 97:20 98:12

101:22 121:13, 19

123:19 124:13

140:18 147:22

158:25 165:10,

12, 15 179:19

204:12, 17 215:1,

15, 22 217:14

218:23 219:14, 17

220:1 224:10 228:17

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ship 22:19, 20 24:12

25:1 63:19, 20

65:1, 1, 17, 21

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24:10 25:1

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78:20 86:20 163:1

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43:19 50:19 51:1

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showed 73:1 86:19

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117:13 143:23 227:1

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65:20 86:16, 17

109:1 117:14 134:18

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26:18 28:11 40:1,

1, 20 43:1, 1, 13

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41:11 171:12 225:1

shuffling 2:10 shut 102:1 similar 96:1

107:16 111:10

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simple 117:24 118:1 simplest 221:17 simplified 77:1 simplifies 31:17
simplistic 66:1 simply 41:1 79:16

171:19 176:10

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122:15 148:1

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22 224:19

single 20:24 42:23

65:25 77:21 79:1

108:16 114:19 119:1

122:1 152:15, 16,

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size 9:16 13:16

17:17 105:1

119:13 155:13

skipped 135:1

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sleep 148:25 186:24

slide 8:1, 12

10:12 11:1 12:16

16:1, 14, 20

17:12 18:15, 24

19:15 20:1, 14,

21 21:1, 10 22:1

25:13 26:1, 22

27:18, 20 30:22

31:22, 25 32:13

39:1 41:1 46:10

51:22 53:1, 11 54:1

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10:22 11:11, 14,

19, 21, 25 12:1,

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17:1 18:14, 16

19:1, 17, 21

20:1, 1, 12, 13, 18

21:1, 1, 22 22:20

23:1, 20 24:11,

15 25:12, 16, 18

26:1, 11, 13, 14,

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28:25 29:1, 13

30:12, 13, 14 31:18

38:1 39:17, 20,

22 40:12, 15

42:1, 1, 15, 19

43:10, 14, 20, 25

46:1, 19 48:15

50:19, 21 51:12,

16, 20, 24 52:10,

12, 17, 25 53:21,

22 54:1, 1 56:18,

21, 23 57:14, 15

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25, 25 60:1, 1,

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18 63:1, 1, 1,

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87:1, 1, 1, 1 88:25

89:17 91:17, 20

92:1, 20 93:25 94:1

96:1 97:1 99:11, 15

102:22 104:16

107:11, 15 111:14

112:23 116:1 117:1,

19, 21, 21, 23

118:1, 13, 14,

14, 18, 21, 25

119:1, 1, 1, 1,

1, 1 121:15 124:15,

16, 18 125:14,

17, 23 126:1, 1, 1,

1, 1, 14, 24 127:25

129:1, 1, 1, 17,

19, 23 132:1, 1

134:1, 14, 20

135:21, 21, 23,

25 136:1 138:1

140:10 143:1

148:1 150:10 154:16

158:1, 1 161:13, 16

163:1 166:20 174:18

176:10 177:1 178:18

181:1 185:1

189:24 190:17,

18, 21, 21 191:1,

1, 1, 14, 18 192:23

194:19 200:1, 20,

22 212:23 218:12,

14 219:1, 1, 12,

15, 16, 18, 25,

25 220:1, 1, 1, 1

221:1, 10, 11, 16

222:19, 21, 23

223:17 226:1, 10

228:14 230:1 232:18

so4 72:1

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64:14, 17 87:25

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73:14 93:24

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96:1 120:24

125:11 215:1 220:22

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112:12 141:1 143:11

171:18 225:10

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someplace 129:10 sometime 196:21 somewhat 71:15 76:12

77:1 143:1 152:13

somewhere 63:10

84:24 171:11, 25

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17, 19 16:18

23:1, 25 24:24 25:1

32:18 39:1 145:1

148:23 151:20

154:23 181:15

202:22 203:1

213:13, 17

214:15, 20

219:11, 15, 24

228:1 233:16 234:23

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100:11, 11 119:24

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27:22 28:1 71:11

89:23 95:1 119:18

125:24 127:18

130:16 134:1 141:12

143:25 161:1

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99:24 103:19, 20

104:1 106:1

109:18 156:1 181:24

183:1, 25 206:22,

24 211:1 215:19

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32:1 35:13 38:1, 10

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113:1, 10 116:23,

24 120:25 123:16

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17, 17 138:10, 12

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169:1, 17 170:24

172:1, 12, 15, 25

173:1, 10 178:1, 25

181:1 182:1 185:1

188:11 191:15, 16

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65:1, 1, 11, 15, 16

66:17 91:15 94:1,

10 96:1, 11, 13, 23

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68:1 77:16 94:1, 14

95:19 96:1, 19,

24 102:21 182:1

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4:16 5:12 8:1 12:23

54:25 56:12, 13, 20

57:17, 20, 23, 25

58:1, 1 59:1, 16,

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63:17 66:24

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17 121:1, 1

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7:12 11:16 50:1

135:1 197:1

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stage 183:22

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13, 16, 18 14:1

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202:24 206:1, 18

213:1 214:1, 1,

13 217:1, 10, 19

219:1 223:1

231:16 232:1 234:25

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31:1 76:1 86:11, 20

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200:18 201:1, 20,

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start 2:1 27:1 44:1,

15 62:1, 16, 25

66:1, 10 78:1 107:1

113:1 119:19

120:1 145:21, 23

148:21 149:1

161:23, 24

166:14, 14 178:1, 1

183:11 188:10

206:16 207:1 212:18

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125:15 143:17 153:1

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180:24 186:21

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statement 2:20 64:13

69:1, 1, 12 108:1

125:20 127:18 129:1

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1 198:1 200:1

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51:14 52:24 108:1

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step 159:1 203:17 steubenville 86:17 steve 154:21 stewart 4:11 7:21,

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130:25 168:18

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subsection 172:25 subsegment 105:22 subsequent 144:12

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subset 173:19

substance 36:1

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114:1 123:19 126:11

145:22 210:19

suggesting 23:11

57:1 60:1 96:12

117:10 122:16

226:17

suggestion 224:18

suggestions 36:18

112:17 140:23

198:24 205:11

suggestive 26:1

31:23, 25 51:1

58:20, 23 61:11, 15

suggests 43:10 53:18

129:23 133:1

144:1 152:12

suit 10:17, 24 12:20 suitable 59:25 student 99:1

students 139:24

studies 11:17

21:10 22:1 25:20

26:22 27:1, 12

28:1, 1, 17 29:1,

1, 20 30:1, 10 36:1

39:21 40:1, 1, 1

41:1, 1, 1, 13,

14 42:1, 12, 13,

14, 22, 23 43:25

44:1 45:1, 1, 11,

12, 21, 25 48:1,

1 50:1, 1, 22,

23, 24 51:1, 1,

1, 1, 1 52:1, 1, 1,

1, 12, 19, 23 53:1,

12, 21, 24 56:25,

25 58:1, 20, 21, 25

59:11, 16, 19,

20, 21, 24 61:1, 17

69:11, 17 70:1

72:13 76:1 78:1

88:1, 11 91:25

92:16, 17, 19 93:1,

1, 18 95:1, 1 97:1,

23 98:1, 1, 14

100:1 104:12, 12,

18 106:1 107:11, 19

109:1, 1, 1, 20

111:1, 1, 1, 18

112:1, 12 114:1

121:1 122:11, 21,

22 123:25 124:1, 12

125:1, 1, 17, 21

126:1, 12, 14,

17, 19, 21 127:19

128:22 129:1

131:1 132:1, 1, 13,

22, 25 133:1 134:1,

19 135:10, 10

138:1, 1, 16, 24

139:1, 1, 1, 1,

1, 14, 17, 19, 23

140:1, 10, 21

141:17 142:1, 1

143:18 144:21, 22

145:1, 12 146:10,

11, 25 147:12,

14, 24 148:12 150:1

157:24 158:1, 11,

19 159:24 160:1, 1,

10, 21 162:10,

12, 13, 15, 18

164:1, 1, 1, 1, 13,

18, 18 173:15, 16

174:1, 12, 13,

16, 19 175:1, 1,

11, 21, 23 178:1,

14, 16, 19, 25

179:1 180:11, 19

183:19 185:11, 21

186:15, 19



188:13, 13

189:14, 17, 25

190:1, 1, 21

192:15, 20 193:1

208:19 211:18, 19

215:18 216:1 218:25

220:25 224:13, 13

225:1 226:17 228:21

229:1

stuff 109:21

111:23 134:18 153:1

186:13

stupid 184:1

sulfate 18:16, 17,

18, 22 19:19, 21,

22, 25 20:1 40:25

63:1, 1, 1, 11, 13,

15, 17, 22, 23,

25 64:12 66:1, 1,

10, 13 72:1

74:19, 23 78:12

89:21 135:21

136:1 177:18

sulfates 31:16

sulfite 90:1

sulfur 2:1 8:21 9:1,

15 19:10 20:1, 1

22:11, 16 23:1, 1

26:1 68:24 72:1, 11

81:16 136:1

137:19 200:16,

19, 23 201:22

sulfuric 64:13

summaries 3:11

107:13 140:19

summarize 96:1

125:11 141:1

223:1 229:1

summarized 19:13

72:20 95:1 97:1

108:17 141:1

summarizing 96:16,

22 141:1

summary 18:1 19:17

21:1 56:20 72:24

81:14, 18, 21

94:1 104:20 105:1

128:22 137:18

138:25 141:1, 15

142:16 150:20

167:24 172:14 191:1

202:1

sunyer 42:1 svendsgaard 207:1 supplement 9:17

38:16

supply 89:14

support 10:13

15:25 16:16 17:24

18:1 19:14 53:10

59:15, 20 69:11, 11

125:13, 20

126:14, 17 128:1,

19 129:1 132:1

193:1, 13 194:14

197:16 230:21

supported 18:12

25:19 39:14 42:13

108:11 191:20 192:1

supporting 191:22

supportive 50:25

51:16 58:25

supports 144:1 suppose 69:21 supposed 161:25 sure 8:16 16:1

19:1 22:1 33:12

37:1 38:1 43:23

44:25 45:1 47:16

48:17 63:1 67:13

73:22 74:13 81:1

82:19, 20 87:16

95:11 97:12, 14

101:20, 24 102:15

103:1, 11 119:21

123:10 127:1 140:22

148:22 151:1

158:1 167:1 168:1

169:14 170:15, 17

173:20 174:18

177:17 184:1

188:1 192:1

193:10 195:24

196:15 197:14, 22

200:15 202:11

211:21 212:11, 14

214:1 226:23 227:19

232:1

surely 80:12 120:11

surgeon 33:18

35:11 231:12

surprise 74:18, 20

surprised 66:19 72:1

200:1, 1

surprising 72:1

153:25

surrogate 59:25

60:20 61:1 158:1

218:12

surrogates 56:22

57:15 59:13 60:11

91:18

susceptibilities

153:11

susceptibility

151:1, 13 158:10

176:22 192:18

229:18

susceptible 45:1,

13, 19, 20, 24

46:1, 1 53:13,

15, 20 95:21

110:1 140:1

151:1, 1 155:12, 14

156:1 161:15

166:1 171:1, 10,

20, 21, 22

182:19, 20 183:16

suspect 76:1 80:23

170:13 208:12

symmetric 141:18 sympathetic 39:1 symptoms 11:10

27:1 28:12 39:23

42:17, 20, 22

43:1 52:1, 1

53:23 57:1 61:19

174:1

synergism 222:1 synthesize 136:17 synthesizing 108:18 system 25:15 32:1

36:1 95:25 108:13

134:23 173:1

systematic 192:10

systematically



59:1 193:1

systemic 87:11,

12, 16

target 174:1

task 5:1 231:21

teach 164:1

132:1, 18 136:1

150:1

thank 4:1, 1, 14 6:1

 		team 16:10, 13, 13

7:22 13:22, 23

T

table 20:16, 16

44:24 47:20 49:11

74:1 75:1 82:20

90:1 112:20

119:18 120:25

137:17 139:14

153:12 172:24

173:23 225:1 235:1,

15, 16

tables 95:1, 1

97:1 98:1

tacoma 42:1 tactfully 85:23 t'ed 83:18

taking 3:15 79:16

160:14 190:17 193:1

218:19

talk 6:14, 23 7:1

8:1 10:13 11:1

12:14 15:1, 14

16:21 23:1 33:14

35:16 47:20 63:24

64:1 75:23 88:16

113:10 125:1

135:1 136:12 152:18

182:21 207:13,

21, 23 209:1, 16

216:1 225:10 234:1

talked 58:1 75:1

76:12 130:15 145:20

167:18 182:17 192:1

talking 4:22 6:19

11:15 18:14 28:24

30:13 34:25 39:10

55:17 89:1, 15,

17 106:1, 1 113:1

116:1 125:1 127:1

135:20 145:19 146:1

150:13 157:1 163:16

181:14 188:23 190:1

205:1 207:20, 22

212:21 216:1

224:1 225:1

talks 161:1 184:1

71:1 176:1

197:14, 24

techniques 75:22

ted 73:19, 19

75:19 78:18, 19

81:12 201:1 220:22

temporal 23:19 72:18

111:1

tend 47:19 51:11

92:20

tended 113:12, 22

140:10

tendency 58:16 tends 102:1 150:16 tentatively 198:11 term 35:15 50:1

51:24 52:25 78:22

108:23 109:1 174:16

207:12 224:1 234:11

terms 3:19 49:1

65:18 74:1 88:12

89:1, 16 94:14,

18 95:20 96:21

98:19 102:1

127:12 134:1 136:15

139:1, 25 142:23

152:18 161:15

162:15 175:1

183:1 186:20

188:10, 17, 23

200:24 207:1, 15

209:23 210:21

211:22 231:12

terribly 187:1

terry 99:1 134:15

146:17 149:1, 1

151:24 155:1

184:1 202:18, 20

204:23

testimony 61:20 testing 17:23 texas 83:11

text 63:16 86:1

101:15 125:10, 19

15:23 16:1 23:22

25:1 27:18 31:19

36:17 40:1 46:1

50:1 55:22 56:1, 1,

10 61:20, 23, 24

62:16 67:1, 18 70:1

71:1 73:18 78:18

85:1, 24 86:1 92:12

103:12, 16 106:23

109:15 112:1 134:15

139:15 143:19 145:1

148:15 151:20

154:20 165:1

172:1 174:23

175:1 178:1, 1

181:1, 22 191:1

193:1 200:11, 13

202:1 207:1

217:10 235:19

thanks 55:14 67:12

73:24, 24 75:18, 21

93:13 98:1 101:1

109:12, 13 163:13

181:12

that'd 205:1

that's 3:1 5:1, 18

6:1 7:18 13:22

18:1, 1, 1, 12

19:10 22:13 24:10

25:1 26:19, 21

29:16 30:17, 17,

19, 19 35:12, 15,

16 36:1, 11, 21,

21, 22 37:21

40:1, 1 43:1

44:14 46:25 47:1,

1, 14 51:20 53:18

55:16 56:16, 23

58:1 64:14, 21

68:11 69:22 70:1

72:12 73:15, 17

76:16 77:1, 10,

12 80:1, 1, 18,

25 84:1 88:1, 13

93:1 94:1 96:20



98:10, 12, 20

100:15 102:1 109:25

110:13 114:1, 1, 10

115:14 116:1

117:14, 24

118:11, 15 119:1

120:20 121:1, 1, 11

122:1, 23 123:1,

13, 13 126:10

127:14 128:22 130:1

135:13 137:22

141:1, 1, 11, 12,

20 142:11, 15 143:1

146:1, 1, 1, 14

147:18 148:1 151:15

154:11 155:1, 18

157:1 159:1, 22,

23, 25 160:14 162:1

163:1, 19 164:17

165:1 168:1, 19, 23

169:1, 16 170:1,

10, 15, 19 172:1

177:12, 23 179:1,

12 182:11 183:12,

13, 19 185:1, 22

186:1 187:17 189:20

190:17 194:19

195:10 196:18 197:1

199:17, 25

200:16, 22, 24

202:20 203:1, 16,

18 204:1, 16, 19

206:1, 11, 14

207:19 210:23

211:23 213:1

215:13, 13 218:12

219:22 221:20

222:25 224:1, 1, 20

225:16, 17, 18

226:11, 12, 20

230:1, 12 232:1

233:1, 1, 16, 21

235:1

theme 176:1

themselves 78:1

164:25 182:10 233:1

there's 5:15 6:10

8:1 22:10 26:16

29:1, 19, 19, 19,

20 30:16 34:12

38:1, 1 44:1, 13

48:25 61:11 68:10

69:1 85:15 86:1, 16

87:1, 1, 17, 22

89:1 94:1 98:22

100:1 107:25 113:1,

1 114:1, 24

115:16 116:1 117:22

118:18 126:16,

17, 20 127:21, 22

128:1, 24 129:1

130:11 131:22

138:15 142:10, 24

147:13 149:17

150:19, 22

152:16, 22, 24

153:25 154:1 156:1,

10 157:1 158:1

159:1 161:1, 24

162:1 170:1, 23

171:1 172:16 173:1,

1, 10, 12 174:1,

15, 21 185:19

186:22 187:12

190:15, 20

192:16, 18, 21, 24,

25 202:1 203:25

208:1 213:13 222:10

223:11, 12 228:12

229:14 231:1

232:16, 17, 17

233:23

therefore 12:10

41:19 59:1 65:1

120:1 138:11

139:1 142:25 203:15

205:25 206:25

thes 56:17 they'll 206:1 they're 4:23 5:1

17:10 24:15 29:1

30:1 69:14, 20 76:1

80:24 85:14 87:25

88:1 107:1 114:13

116:1 117:25 121:10

133:1 134:1, 25

138:16 146:1, 1

150:1 151:15

158:1 160:23 171:17

175:1, 13, 18

176:25 183:1 184:22

186:1 187:25

188:1 190:16, 18

200:1 202:22 206:13

207:19 212:11

216:10, 16 221:1

226:19 230:25

they've 46:12

102:1 116:21 159:21

third 20:1 23:18

86:15 108:1

140:15 190:1

226:21, 22

thirdly 136:1

ticked 83:21

thorough 68:17 93:20

95:1 98:20 228:20

thoroughly 93:17 thoughtfully 212:1 thousand 115:1

tie 92:15 179:15

tier 207:13, 15

210:1

three-hour 8:25 three-year 20:1 threshold 63:24

150:17, 20

152:14, 15, 16

thresholds 143:24

144:1 152:1, 19, 25

158:12 160:16 165:1

169:1, 1 227:16

throughout 55:17

58:18, 19 63:12

66:1 176:1 179:14

184:11 214:23

throw 85:18 218:23

223:23 234:20

thrown 46:12

tight 42:1 48:1 67:1 tighter 41:21 thurston 28:22 37:23

38:17 46:1 85:1, 23

99:1 115:1 116:1,

13 117:1 118:10

119:21 138:14



145:18 159:15

163:15, 19

187:14, 15 207:1,

10, 11 208:10,

18, 22 209:1, 1

210:1 225:1, 14,

20, 24 229:10

230:23 231:1

thus 12:13

tim 2:10, 11, 13

14:14 67:14 70:1,

1, 12 181:1, 16

223:14

tim's 70:11

time-stratified

141:18

timelines 72:22

tissue 88:25

title 99:1 136:10

155:23 195:11

200:15

tnf 54:1

today 4:1 6:14

7:25 16:23 57:1

59:23 110:1

181:17 182:15, 17

194:18 195:16

204:15 205:1

tom 83:1

tomorrow 6:16 7:1

15:1, 14 64:1 82:24

162:1 203:24

204:1 205:1, 12, 24

206:10 207:21, 24

208:24 209:1, 1, 17

234:19 235:12, 17

tomorrow's 206:1

tony 3:22 4:14

top 32:24 40:1 41:24

125:25 129:12

toss 85:12 117:11

186:17

total 18:10 105:18

119:1 153:17, 23

totally 118:10

154:16

touch 6:21 11:1

60:13

touched 60:14

touches 58:1, 1

toward 35:10

182:1, 1

towards 76:1

167:25 197:19

tox 42:13 127:18

131:1 133:1

toxicologic 126:21

127:1, 11 128:1,

12, 21 129:1, 1

130:17 157:25 158:1

toxicological

25:23 132:22 175:23

226:1, 16

toxicologist

123:10 146:22

toxicology 29:21

52:1 109:20 125:1

146:10 147:1 175:17

208:17 225:1

toying 167:16 trace 24:11 track 85:1

tracks 22:19, 20

25:1

tract 26:15 87:1

89:14 92:1 222:20

tracts 96:1 traffic 22:17 transformation

91:21, 22

transformations 17:1 transient 11:23 transit 23:13 translate 175:15
translated 24:25

90:22

transmogrified

127:12

transparent 212:1

transportation 22:20

24:1, 1, 24

travel 110:15

traveling 22:12

110:12

treated 170:16

172:22

trees 108:1

tremendous 99:1

138:15

trial 33:1

tried 74:25 144:1

158:16 162:1 172:24

trimesters 52:19

trouble 32:1 105:1

156:20

trucks 101:12

true 22:13 64:15

69:12 80:25 91:18

92:1, 1 185:22

223:12 224:1

truly 100:13 134:17

truth 195:1 truths 196:1 try 14:22 16:1

17:1 74:1 75:1 82:1

84:1 92:14, 15

104:10 139:1 145:11

147:14 148:13, 25

163:1 166:1

178:12 179:15 185:1

188:1 191:1

203:18 204:1

trying 13:10 17:17

38:19 59:1 65:14,

19 66:25 74:23

85:1, 10 89:24

104:23 106:1, 12

109:1 125:10, 13

136:15 137:18 146:1

155:1 160:22

176:1 179:1

184:19 187:19

188:21 196:1 197:17

198:12, 16, 17

206:14 207:1, 16

209:1 210:13

221:1 230:24 232:14

turn 3:22 4:13 6:1

7:20 55:1 91:1

125:1 174:18

turns 144:14 235:1 twenty-five 213:18 twice 108:23 twitchy 144:18



two-fold 104:22

two-pollutant 224:17

type 12:11, 11

54:1 111:11 130:1

142:1 218:11 231:15

types 157:22

typical 76:17 77:19

typically 27:1 59:23

77:1 175:19

U

ubiquitous 12:11

uc 55:1

ucsf 128:17 140:1 uh-huh 210:25 ultimately 146:12

160:18

ultman 86:1, 1 89:1,

10, 22

unanswered 174:1 unbiased 58:1 120:16 unc 139:24

uncertain 22:17,

22 23:11 24:21

uncertainly 114:23

uncertainties

65:1, 10 76:10

181:12 186:12

192:11 193:1

uncertainty 21:16

76:1 80:1 184:1,

15, 16, 18 185:1,

19 186:1 192:13

196:1

unclear 79:1

175:14 184:1

under-controlled

114:20

underestimated 45:21 underestimates 78:1 underestimating

119:1

underestimation 9:13 undergoing 91:21 underlie 230:1 underlies 191:11
underlined 5:1, 1

202:1, 12

underlying 230:12

underneath 171:1 underpins 181:10 understand 17:21

82:14 83:19

94:12, 17 95:12

99:11 100:14 106:12

108:16 121:15

122:13 123:1 137:10

147:12 184:15

185:19 198:17 205:1

215:25 216:1 221:23

understanding 4:1

17:11 92:18 93:1,

17, 24 122:1 157:25

165:1, 24 177:24

220:19 221:1

understood 142:1

204:11

undertaken 138:17 unfortunate 110:13 unfortunately 34:1

59:1 114:1 139:1

uniformed 164:25 unimportant 23:10 unique 140:23

141:1 142:13, 17

united 95:23 96:1

98:17 161:1, 19

169:1 183:1

units 19:19

univariant 49:18

221:21

universe 50:1 university 55:11 unless 7:20 61:25

83:11 102:1

131:20 174:1

unresolved 192:1 unspecified 91:19 unstable 46:18 unusual 144:20 upbeat
200:14 updrafts 235:22 upon 77:15 141:1

162:1 229:16

upper 26:1 87:1, 10,

13, 21, 25 153:14

urban 68:1 71:20, 25

72:1 73:14, 14

upwind 100:1

urge 195:18

us-based 135:1

useable 59:1

useful 17:24 18:1, 1

20:25 56:16

57:18, 24 58:1

68:15 86:1, 10

88:12 97:18 98:1

104:13, 24 111:1,

20 114:22 130:22

131:1 136:16

180:1 190:1

192:11 232:1

usefulness 58:1

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usually 28:10 33:1

222:13

V

vacuum 180:1

valid 113:16 122:1 valuable 72:17 value 63:22 133:1

134:1 138:15 152:21

186:18

values 67:24

146:23 184:24

185:16

vanadium 51:21 vapor 87:24 variability 28:13

45:1 54:1, 1, 19

68:1 71:16 72:1

73:14 90:14 144:13,

16 145:11, 15

154:1, 1, 1, 10

166:1

variable 91:1 144:24

152:25 159:1

165:1 221:19

variables 120:1, 1

222:24



variant 49:13 221:21

variation 68:1 72:25

73:1, 1

varied 142:21 varies 85:25 various 76:1 78:11

82:12 91:1 112:1

152:1 168:23

varying 21:21 57:21 vascular 89:1, 14 vastly 109:1

vector 29:18 222:18

ventilation 9:1,

22 21:20, 24 26:16

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56:15 150:1

167:1, 1, 12 211:25

versus 39:11 90:20

91:1 94:10, 11,

18 96:24 97:10

105:10 113:13

123:1, 24 129:19

131:1 166:1

184:16 190:14, 23

192:20, 23 201:1

veterans 34:12

via 89:14

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view 5:1 11:1

134:1 144:23 188:21

193:13 194:23

198:18 215:1

viewed 12:1 violating 120:11 virtually 44:1

105:22

vis 160:20, 21

visibility 18:21

201:13

visits 41:1 42:17

43:15 50:24 53:24

57:1 61:13 128:23

149:1

visual 121:1

voice 124:1

volcano 102:25 103:1 volcanos 102:21 voluntarily 79:1

volunteered 140:13

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53:13, 20 155:22,

24 156:1 166:1

228:1, 1, 1, 10

W

wait 15:15 38:1 47:1

103:25 130:11

208:24 209:1

waiting 2:17

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waiving 126:18 walks 162:21 wander 213:19 warranted 54:23 washington
56:1 wasn't 36:1 72:1

75:1 109:10

119:15 132:10, 16

134:13 149:19 163:1

164:1 179:13 209:20

219:18

waste 114:25

water 26:1 64:14, 17

87:24

ways 17:16 44:16

58:25 59:1 77:19

88:1 96:12 122:1

175:24 223:1

we'd 56:10 112:18

170:11 184:18

188:22

we'll 6:1 7:1 8:1

13:17 14:22, 22

15:1 18:20 23:1

39:1 45:14 50:13

54:1, 11 55:17 62:1

64:1 67:11 70:24

74:1 75:17, 19

79:19 81:25 85:1

95:12 97:13

103:11 110:1, 14

111:1 123:20, 20

137:1 143:17 148:1,

10, 10 182:14, 17

204:1 207:21, 23

209:1 210:1 232:1

235:17

we're 2:10, 16 5:16,

22 6:1, 14, 25

7:1 8:1 13:14 16:22

17:1, 1 18:17, 21

20:15 24:14 29:1

31:1 32:1 34:25

35:1 36:22 37:19

39:15 44:17, 23, 25

46:1 48:14 58:14

62:16 66:25 74:1,

1, 1 76:1 79:11,

12, 13, 17 88:13

89:1, 15 95:17

99:14, 15 101:1,

10, 11 106:18

110:19 121:1

125:1 127:1

135:20 142:1 145:1,

1, 1 146:1 149:1

158:1 166:11 169:17

171:1, 23 178:24

179:1, 1 184:10

187:1 188:1, 1,

23 197:17 201:1

202:1, 1 205:1,

1, 10 206:1, 15

210:13 211:20

212:1, 15 213:14

215:19 217:11, 23

219:20 229:1, 1

230:24 232:14

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