### 202-234-4433 Neal R. Gross & Co., Inc. Page 1 U.S. ENVIRONMENTAL PROTECTION AGENCY CLEAN AIR SCIENTIFIC ADVISORY COMMITTEE (CASAC) LEAD REVIEW PANEL + + + + +

PUBLIC MEETING

+ + + + + WEDNESDAY, APRIL 11, 2012 The committee met in Salon B of the Marriott at Research Triangle Park, 4700 Guardian Drive, Durham, North Carolina, at 8:30 a.m., Dr. H. Christopher Frey, Chairman, presiding. PRESENT: DR. H. CHRISTOPHER FREY, Chair MR. GEORGE A. ALLEN DR. HERBERT ALLEN DR. RICHARD CANFIELD DR. DEBORAH CORY-SLECHTA DR. CLIFF DAVIDSON DR. PHILIP E. GOODRUM DR. SEAN HAYS*

DR. PHILIP HOPKE DR. CHRIS JOHNSON DR. SUSAN KORRICK DR. MICHAEL KOSNETT DR. ROMAN LANNO DR. DEIRDRE MURPHY MR. RICHARD L. POIROT

DR. JOEL G. POUNDS DR. MICHAEL RABINOWITZ DR. WILLIAM STUBBLEFIELD DR. IAN VON LINDERN DR. GAIL WASSERMAN DR. MICHAEL WEITZMAN* MR. AARON YEOW, DFO* MR. EDWARD HANLON, Acting DFO DR. VANESSA VU, Director, SAB Staff Office *Via telephone

### 202-234-4433 Neal R. Gross & Co., Inc. Page 2

C-O-N-T-E-N-T-S

EPA Presentation on Risk and Exposure

Information and Considerations in the Policy Assessment. . . . . . . . .7

Discussion of Key Points. . . . . . . . . . . 73

Adjournment . . . . . . . . . . . . . . . . .165

### 202-234-4433 Neal R. Gross & Co., Inc. Page 3 1 P-R-O-C-E-E-D-I-N-G-S 2 (8:32 a.m.) 3 MR. HANLON: We are going to begin 4 the meeting now. And just a quick point for 5 everyone at the meeting today. We have draft 6 key points for discussion this morning, and we 7 have hard copies for members and also for the 8 public on the table outside. We'll be showing 9 them on the screen today. In the next several 10 days, these summary points that are going to 11 be shown in the meeting today will be posted 12 on our meeting website. Chris? 13 DR. FREY: Okay. Good morning. I 14 want to thank everyone for being here on time, 15 and we're going to get started. Just to 16 review the agenda for today, we have a 17 presentation from EPA on information and 18 considerations regarding the risk and exposure 19 assessment that will be part of the policy 20 assessment. And then we will have a time 21 period after that to provide an opportunity if 22 any members of the public have any clarifying

### 202-234-4433 Neal R. Gross & Co., Inc. Page 4 1 questions. 2 Followed by that, we will discuss 3 key points. And what we might do, since we'll 4 have just recently heard about the REA, is 5 maybe we'll start with that since that will be 6 fresh in our memories. As we get later into 7 the morning, what I would like to do is circle 8 back to issues that we talked about yesterday 9 and, in particular, to see where we are on the 10 response to the charge questions. So we'll 11 review that. The goal is not to do a lot of 12 wordsmithing or editing but just at a 13 conceptual level to see if we're on track to 14 complete those responses. 15 And just something to be thinking 16 about is we do want to make sure we answer the 17 charge questions that are posed, which doesn't 18 mean that we can't go beyond that if we see 19 something significant that we want to say. 20 But we should, at a minimum, be responsive to 21 the charge questions. And I realize, you 22 know, this is a first draft of the response to

### 202-234-4433 Neal R. Gross & Co., Inc. Page 5 1 charge questions, and I think there will be 2 some need to iterate to make sure that we are 3 addressing the charge questions. And we can 4 discuss that as we go through. And also if we 5 have any reflections on what we heard 6 yesterday regarding monitoring or aviation 7 gasoline, we could spend a few minutes 8 discussing those. 9 Just to get a sense, we're 10 scheduled to adjourn at 12:30. Is there 11 anyone who needs to leave before 12:30? Okay. 12 So we have most of the panel then. So I think 13 we can presume we'll go to 12:30. We won't go 14 past 12:30. If we need it, we'll go to 12:30. 15 Okay. So any clarifications 16 either from the DFO or staff or panelists? If 17 anyone, a member of the public would like to 18 offer clarifying questions, if you're in the 19 room, it would be good if you'd let Ed Hanlon 20 know that. If you're on the telephone, I 21 guess we'll poll you for that when we get to 22 that part in the agenda.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 6 1 Okay. With that, I would like to

2 turn the floor over to Dr. Zach Pekar and Dr. 3 Deirdre Murphy, and we look forward to your 4 presentation. Thank you. 5 DR. MURPHY: Thank you very much. 6 We appreciate the opportunity to take a few 7 minutes to talk to the panel this morning. As 8 you recall from your consideration last summer 9 of the REA planning document, our review of 10 the information newly available in this review 11 concluded that that information did not 12 warrant development of a completely new risk 13 and exposure assessment. So this morning 14 we'll take a few minutes to discuss the risk 15 and exposure assessment developed for the 16 review completed in 2008 and how we'll be 17 considering the information from that 18 assessment in the policy assessment for this 19 review, and a draft of that policy assessment 20 will be the topic of discussion by this panel 21 in the next face-to-face meeting scheduled for 22 sometime this fall.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 7 1 So with that, I'll turn it over to

2 Dr. Zach Pekar. 3 DR. PEKAR: Okay. So let me just 4 make sure I'm getting this right. That's what 5 the coffee is for. Okay. So just 6 presentation objectives. Obviously, the risk 7 assessment that was completed in 2008 is a 8 pretty complicated analysis. And as we go 9 through some of the details of it, I'm going 10 to sort of move, I think, fairly quickly and 11 try not to get bogged down in details, sort of 12 a similar comment to last time. 13 But the goal of the presentation 14 today is to really talk about some of the 15 background to frame the way we're going to 16 present the 2008 risk results in the context 17 of the current policy, the current review. 18 And we're going to, for the presentation 19 today, I'm going to provide a little 20 background for the risk assessment itself, 21 going over some of the elements of the risk 22 assessment, and then discuss the way in which

### 202-234-4433 Neal R. Gross & Co., Inc. Page 8 1 the evidence published since the last risk 2 assessment, the 2008 risk assessment, will be 3 used, the degree to which it will be 4 considered in helping us to interpret those 5 risk estimates and get an additional sort of 6 refined understanding and characterization of 7 uncertainty and confidence associated with 8 those risk estimates. 9 So just a little background on 10 lead air pollution in the context of the risk 11 assessment that was completed. I think most 12 of these points will be, I think, generally 13 known by most of you. But lead occurs, 14 obviously, naturally and is emitted by many 15 anthropogenic sources. The highest levels 16 that we currently experience are generally 17 near lead smelters. Lead is emitted into the 18 air primarily in particulate form, and then it 19 can be deposited to a number of sources, and 20 that's important for us. Some of those 21 deposited, the deposition of surfaces result 22 in some of the highest exposure pathways in

### 202-234-4433 Neal R. Gross & Co., Inc. Page 9 1 terms of risk related to ambient air. 2 People exposed obviously directly, 3 if we're talking about lead in ambient air, 4 directly through inhalation, but they're also 5 importantly exposed through the ingestion of 6 soil that's been deposited to surfaces, 7 whether that's outdoor soil and, importantly, 8 in the context of the risk assessment that was 9 completed, indoor residential surfaces. 10 You'll have lead that penetrates indoors and 11 it's deposited, and then it's ingested. 12 Children are more highly exposed 13 than adults, generally speaking, in the 14 residential setting because of the higher 15 hand-to-mouth activity that children 16 experience and, because ambient air lead can 17 penetrate indoors and deposit to surfaces or 18 deposit outdoors to soil, you're going to have 19 relatively higher exposures for children. 20 Once in the body, lead can be absorbed fairly 21 readily into the bloodstream. 22 And lead is also persistent. When

### 202-234-4433 Neal R. Gross & Co., Inc. Page 10 1 we looked at designing the risk assessment and 2 completing it, we had to deal with the fact 3 that more recently released ambient air lead 4 could cause exposures, but also children could 5 be exposed to lead that had been released many 6 years ago or used even many years ago, for 7 instance through indoor paint exposure or 8 mobilization of older anthropogenic lead that 9 may have been released through autoemissions 10 in the past and becomes part of the even 11 current ambient air signal. 12 So this figure goes through the 13 ambient air-related exposure pathways, and 14 there are a number of different pathways and 15 really sort of helps us to frame the risk 16 assessment that was completed. So beginning 17 with the top of this diagram, you see that we 18 have lead in ambient air. If we start on the 19 left-hand side, we see, obviously, we have 20 direct inhalation of ambient air, lead in 21 ambient air. You also, as I mentioned, have 22 the penetration of ambient air indoors with

### 202-234-4433 Neal R. Gross & Co., Inc. Page 11 1 deposition to indoor surfaces and subsequent 2 dust, indoor dust ingestion. That's the 3 second sort of pathway there. And then on the 4 right-hand side with the unshaded boxes, and 5 I'll explain that shading in a second, you 6 have deposition to outdoor surfaces: outdoor 7 soil; even contamination potentially of food 8 crops through either leaf deposition or 9 deposition of soil and potential uptake; and 10 then drinking water contamination, 11 particularly if you have reservoirs or other

12 sort of surface water sources that are used 13 for drinking. 14 So this is sort of the range of 15 pathways that are considered. And in the risk 16 assessment, we did include all these pathways 17 in our modeling. But just to sort of go back 18 and review that for a second, when we looked 19 at an alternate lower standard level, sort of 20 dialing down the ambient air lead, the 21 pathways that were actually modeled for 22 response in terms of exposure and risk are

### 202-234-4433 Neal R. Gross & Co., Inc. Page 12 1 highlighted here with the gray shading. And 2 so you see, obviously inhalation would 3 decrease because you'd have a reduction in 4 ambient air lead that would be simulated. But 5 very importantly, the indoor dust ingestion 6 pathway was simulated to change, and there was 7 a lot of effort to really integrate or 8 complete that part of the analysis.9 The non-shaded boxes on the right10 hand side, although we modeled risk, we didn't 11 reflect reduction in ambient air in terms of 12 a reduction in those pathways. We held those 13 pathways constant, mainly because challenges 14 in completing that part of the analysis, some 15 technical challenges. 16 The green sort of central little 17 oval there is just to really emphasize the 18 point that historically released lead did play 19 an important role in driving various pathways, 20 or contributing to various pathways I should 21 say here. In certain instances, it may not be 22 possible to really tease out the fraction of

### 202-234-4433 Neal R. Gross & Co., Inc. Page 13 1 that, but it could be an important role. For 2 instance, we did have, obviously, 3 contributions from older paint and older 4 houses within some of the residential areas 5 contributing to the dust, indoor dust 6 exposures, along with ambient air. Yes? 7 DR. KOSNETT: Zach, is the gray 8 then like what they call recent lead? 9 DR. PEKAR: Yes. Yes, that's a 10 really good point. So we had the recent air 11 lead, the past air lead, and then we had sort 12 of a background exposure signal also. 13 And this is actually a good point 14 for me to raise another point that I wanted to 15 make. I think we discussed this yesterday to 16 a certain extent, and I just wanted to 17 reiterate this point. Inhalation alone is a 18 relatively insignificant, I mean, depending on 19 how you look at it, but a relatively small 20 component of overall exposure and risk. And 21 so the modeling that we conducted suggested 22 that direct inhalation usually contributed

### 202-234-4433 Neal R. Gross & Co., Inc. Page 14 1 something in the range of 0.5 to 0.6 percent, 2 so less than one percent of total exposure and 3 risk in the residential scenarios that we

4 looked at. 5 What was important is the central, 6 the indoor ingestion of dust driven directly 7 by ambient air, so the ambient air portion of 8 indoor dust exposure ranged from 12 to 28 9 percent of total exposure. So the point here 10 is that what we found is that ambient air 11 could represent up to a third or more of total 12 exposure and risk, but the majority of that 13 was driven by indoor dust ingestion with 14 loading from ambient outdoor air. And there

15 are a lot of other nuances that we'll frame 16 and obviously talk about in terms of the 17 potential that we may have underestimated 18 certain ambient air impacts in the right-hand 19 boxes since we didn't look at those. So we 20 may have actually underestimated total ambient 21 air contributions because, obviously, there 22 would be some contributions to soil that we

### 202-234-4433 Neal R. Gross & Co., Inc. Page 15 1 didn't explicitly look at. Yes? 2 DR. GOODRUM: In your model 3 simulations, did you vary that assumption 4 about the mass contribution of soil to indoor 5 dust, or did you just hold that fixated

6 constant --

7 DR. PEKAR: So there was an 8 intercept term. There were several different 9 dust models that I'll briefly mention in a 10 second. But, no, we didn't do that. We had 11 a fixed, generally, conceptually, a fixed 12 contribution, but there were non-linearities 13 in going from dust loading to concentration, 14 and so the regression equations would be used

15 for that. That could reflect a number of 16 factors that we talked about in detail at that 17 point, and we'll probably discuss some of 18 those in framing the presentation of risk 19 results in this review. 20 Okay. So now, in terms of looking 21 at the estimation of air-related exposure and 22 risk, and touching on some of the key points

### 202-234-4433 Neal R. Gross & Co., Inc. Page 16 1 here. So, obviously, our objective was to 2 evaluate or estimate IQ loss in children. 3 That was the end point that we were looking 4 at, and to relate changes in ambient air 5 levels of lead or an absolute degree of 6 ambient air lead to a degree of IQ loss. 7 That's sort of the goal of the analysis. And 8 we don't have epidemiology studies that 9 directly link ambient air lead to IQ loss. 10 You know, it's usually some kind of biometric. 11 It's blood lead, it's bone lead. And so the 12 risk assessment really needed to go from 13 ambient air lead to the biometric, in our 14 case, blood lead various concurrent lifetime 15 average metrics that we're using and then 16 translate that with the concentration/response 17 function from epi studies into IQ loss. 18 Probably most of you are clear on that point. 19 I think the point we wanted to20 make here is, importantly, there's some non21 linearities in characterizing both the 22 exposure to lead and also the response, the IQ

### 202-234-4433 Neal R. Gross & Co., Inc. Page 17 1 loss. And those non-linearities, illustrated 2 here with this little diagram, meant that we 3 had to look at total exposure. We couldn't 4 just look at the air-related exposure and talk 5 about that because where a child is on the 6 distribution of lead exposure can have an 7 effect on the magnitude of an incremental 8 change in blood lead on IQ loss. 9 And let me just make the point 10 with this graphic. If a child is closer to 11 ten where the triangle is there, an 12 incremental one unit change in blood lead will 13 have a smaller degree of IQ change, could 14 still be policy-significant, than you would 15 have if the child is at the circle where you 16 have a, potentially a steeper slope, based on 17 our epidemiology evidence. And because we 18 needed to be able to fix children on this 19 total blood lead curve, that meant that we 20 really had to look at total exposure which 21 introduced a lot of complexities into the 22 analysis that we've talked about and we will

### 202-234-4433 Neal R. Gross & Co., Inc. Page 18 1 talk about when we're framing the risk 2 assessment. So the non-linearities and the 3 need to look at total exposure through all 4 pathways is an important detail. 5 So the approach that we used in 6 completing the risk assessment was a 7 multimedia case study approach. It's 8 multimedia and multi-pathway because we needed 9 to look at total exposure, so we needed to 10 consider all pathways, as I just mentioned, 11 and because ambient air exposure exerts itself 12 through both inhalation, as I mentioned, and 13 indoor dust and other pathways. 14 We completed a probabilistic 15 population assessment for each case study 16 location because we weren't simply interested 17 in the central tendency best estimate child 18 that we could generate with an IEUBK 19 simulation of pathways at their average 20 levels. We also wanted to try to characterize 21 higher end exposure and risk, which that's 22 important, I think, in terms of looking at

### 202-234-4433 Neal R. Gross & Co., Inc. Page 19 1 more highly air-exposed children, but it also 2 introduced additional challenges, for 3 instance, how correlated are pathway exposures 4 at the high end? Do you have a child that you 5 simulate to have 15 micrograms per deciliter, 6 what's the contribution from air versus other 7 pathways? And the information on that kind of 8 correlation across exposure ranges is not, we 9 don't have a lot of information on that 10 pathway correlation, so that's another 11 challenge. 12 In terms of the populations that 13 we modeled, the case studies, I guess you can 14 look at the case studies in terms of the types 15 of populations that were modeled, second 16 bullet here. And we had, on the one hand, 17 more highly exposed populations that we 18 simulated. We had a general urban case study 19 which assumed that you had sort of a 20 neighborhood of children at a fixed level of 21 exposure near the standard level you're 22 looking at, so that's really looking at what

### 202-234-4433 Neal R. Gross & Co., Inc. Page 20 1 risks they would have if you had a group of 2 kids at that exposure level. 3 The primary lead smelter case 4 study also focused on more highly exposed 5 children because we looked at a two-kilometer 6 radius right closest to the facility in terms 7 of really focusing our analysis, and those 8 kids were exposed pretty close to the current 9 standard with some gradient but not a lot of 10 spatial gradient. That happened further from 11 the facility.

12 We looked at a broader 13 distribution of exposures by looking at the 14 urban case studies, which included Chicago, 15 St. Louis, and L.A. And those case studies 16 looked at a wider distribution.

17 DR. MURPHY: Cleveland. 18 DR. PEKAR: Cleveland. Yes, 19 Cleveland. Sorry. And those scenarios looked 20 at a greater variation in the spatial 21 distribution of ambient lead exposure, so you 22 had some kids who were exposed at higher

### 202-234-4433 Neal R. Gross & Co., Inc. Page 21 1 levels but a lot of children that weren't 2 trying to get a more representative picture of 3 a larger urban exposure scenario. 4 So this diagram illustrates these 5 three categories of case studies, the general 6 urban case study on the left being a uniform, 7 basically sort of a group of children exposed 8 at a uniform level, at the standard level. The 9 primary lead smelter, as I explained, having 10 a two kilometer radius immediately near the 11 facility; and then the location-specific urban 12 case studies looking at actual cities with a 13 wider spatial gradient in exposures. 14 DR. KOSNETT: In your case studies 15 where it says, you know, look at large urban 16 areas with varying demographics, do you take 17 into consideration that some of the areas that 18 are near these point sources may have higher 19 background levels of lead because they may 20 represent, for example, children with other 21 risk factors for higher lead exposure, like 22 older housing? They also may be more

### 202-234-4433 Neal R. Gross & Co., Inc. Page 22 1 vulnerable because they may have lower income 2 and be more iron-deficient or things like 3 that. I mean, it's a complicated approach, 4 but are you modeling that at all or 5 considering that? 6 DR. PEKAR: Well, so very, I 7 guess, briefly, and we can certainly talk 8 more, you know, if you want to about this. A 9 number of those factors, it's difficult to 10 quantitatively reflect those. I mean, if you 11 have a dietary deficiency, you have greater 12 potential uptake. We don't have necessarily, 13 with an IEUBK, for instance, the ability to 14 simulate some of these greater enhanced sort 15 of factors that can increase biometric levels, 16 I would say, like blood level values. 17 The short answer is the GSD that 18 we use, the geometric standard deviation, 19 giving you the spread of exposures around a 20 central tendency estimate would reflect some 21 of that variability to some extent. We used 22 a regionally, nationally representative indoor

### 202-234-4433 Neal R. Gross & Co., Inc. Page 23 1 dust lead value that reflected indoor paint 2 along with our modeling of air. There's some 3 complexity there that I can get into on the 4 side, if you want to talk about this. 5 One thing to keep in mind is, 6 because of the non-linear response of IQ loss, 7 ironically, if you push children higher 8 because of their background paint exposure, 9 then the relative impact of air actually 10 becomes lower. So what we were really 11 interested in is the situation we had very12 highly air-exposed kids without a lot of non13 air signal, so they're in the more potent 14 portion of the exposure range but because of 15 air. That ameliorated, to a certain extent, 16 our need to fully characterize and capture 17 kids that may have high paint. We were really 18 focusing on high air, but there's some nuances

19 there that we can talk about. It took us a 20 while to figure that out, too. 21 So a lot of complexity that I 22 think has come out in some of these questions

### 202-234-4433 Neal R. Gross & Co., Inc. Page 24 1 of the risk assessment -- and I don't want to 2 take a lot of time here because I can go on 3 about this analysis. So in terms of 4 characterizing various media concentrations, 5 there were different approaches and data sets 6 used in the different case studies. For 7 ambient air lead, we had ambient monitoring 8 data for the actual cities that we modeled. 9 We had monitored levels, and that gave us a 10 crude spatial gradient that we can incorporate 11 into our modeling. 12 For the primary lead smelter, we 13 used air dispersion modeling, again to get a 14 spatial gradient. Because we focused on a 15 very tight area around the facility, we were 16 at a fairly high level of the plume before you 17 started to see greater dropoff in 18 concentrations. That being a relative term, 19 obviously, around a primary lead smelter. 20 Then for the general urban case 21 study, we were again fixing the ambient level 22 at whatever standard we were looking at, so

### 202-234-4433 Neal R. Gross & Co., Inc. Page 25 1 there was no modeling. We were just assuming

2 a set level. 3 For indoor dust lead, there was a 4 lot of complexity in this. For the urban 5 residential case studies, which is the general 6 urban case study in the city-specific case 7 studies, we generated a fairly sophisticated, 8 developed a fairly sophisticated model that 9 combined compartmental elements and empirical 10 elements, deterministic mechanistic modeling 11 and some empirical data to sort of get at this 12 issue. 13 For the primary lead smelter, 14 because we had a lot of monitoring data across 15 various media, we generated just a regression 16 statistical model for relating outdoor air to 17 indoor dust. And then in terms of outdoor 18 soil, and I mentioned this a little bit 19 already, we used a national sort of regional 20 data set to get us a central tendency estimate 21 for urban soil for the urban settings. And 22 then the primary lead smelter had a lot of

### 202-234-4433 Neal R. Gross & Co., Inc. Page 26 1 data on soil that we used and the risk 2 assessment measure data, site-specific data. 3 So because of the complexity of 4 the analysis, if you look at the risk 5 estimates, those of you who are familiar with 6 this, there's a lot of dimensions and some 7 ranges that are presented. It's not one 8 estimate reflecting these different sort of 9 elements and dimensions of the analysis, and 10 that would be reflected in our presentation of 11 the risk estimates. We had, as I think we 12 mentioned already, several different 13 characterizations of the ambient air impact. 14 We had sort of the recent media concentrations 15 and recent ambient air impacts, sort of 16 inhalation and indoor dust which were directly 17 linked to ambient air. Then we had soil, 18 other concentrations that, while related to 19 ambient air, we weren't actually tweaking or 20 adjusting. And then we had pathways that were 21 less susceptible to impact by sort of 22 proximate ambient air. So if you're talking

### 202-234-4433 Neal R. Gross & Co., Inc. Page 27 1 about dietary exposure, clearly diet and food 2 could be impacted, but the ambient air around 3 you is probably not what's impacting your 4 diet. Unless you're growing your own food, 5 you're probably getting it from other places. 6 So we had several of these different 7 categories of risk that we would look at that 8 gave us a range all the way from total risk 9 across all pathways to just looking at the 10 inhalation of indoor dust linked to ambient 11 air, for instance.

12 And then there are other 13 dimensions, too. There were multiple dust 14 models used, as I mentioned. And we also 15 looked at several different concentration 16 response functions that handled the IQ loss at 17 lower exposure levels in different ways. So 18 we tried to reflect uncertainty, 19 characterization of uncertainty in that 20 important element of the risk assessment, too. 21 And these all sort of resulted in a 22 multidimensional characterization of risk for

### 202-234-4433 Neal R. Gross & Co., Inc. Page 28 1 each case study. We also looked at different 2 percentiles of the population. 3 So I have a hard time looking at 4 that, which means it was probably too small. 5 So one thing we're also going to do, 6 obviously, is look at how information 7 presented or published since the risk 8 assessment can be used in helping us to 9 further sort of refine our understanding and 10 characterization of uncertainty and confidence 11 in the risk estimate. That's going to be an 12 important part of presenting the risk 13 estimates in the policy assessment. And what 14 we've done is we've looked at the critical 15 modeling elements of the risk assessment in 16 which we had significant uncertainty as framed 17 and discussed in presenting the risk 18 assessments in the past, and we asked 19 ourselves, you know, if we look at each one of 20 these elements and look at information that's 21 been published relevant to that element, do we 22 think that that information, the new

### 202-234-4433 Neal R. Gross & Co., Inc. Page 29 1 information is going to help us to further 2 understand uncertainty, potential bias, and so 3 forth in this particular aspect of the risk 4 assessment? And this table sort of frames 5 that assessment, that analysis that we've done 6 of the new information, and I can quickly go 7 through this. It's mainly just to identify 8 for you areas where we think we're going to be 9 speaking to refining or improving our 10 understanding of the risk assessment using the 11 new information. 12 So beginning with ambient air, we 13 really, in our ability to characterize the 14 spatial gradient that residents may be exposed 15 to, we really don't think we're going to be in 16 a better position to do that, in a 17 demonstrably better position. But I also 18 don't think that there's significant 19 uncertainty there. One of the things to focus 20 on is that the general urban case study was 21 what we ended up putting a lot of emphasis on, 22 and that's sort of saying what happens if kids

### 202-234-4433 Neal R. Gross & Co., Inc. Page 30 1 are exposed at the standard level we're 2 looking at, and that's a really important 3 question. And that sort of then doesn't 4 depend on characterizing a gradient. You're 5 really look at some set of kids exposed at 6 that level, so that's an important point to

7 make. 8 So we do have new information, 9 obviously, on soil and drinking water levels 10 for lead, but what we don't really have is 11 better information on the correlation between 12 those pathways and air-related pathways, 13 particularly at higher levels of exposure. 14 And that, again, is really important. If we 15 characterize more highly air-exposed children, 16 to really have a better understanding, we want

17 to understand how those are correlated. 18 Having said that, we do believe 19 that the additional air and water data, I mean 20 soil and water data, will help us to look at, 21 help us characterize potential uncertainty in 22 characterizing those media concentrations in

### 202-234-4433 Neal R. Gross & Co., Inc. Page 31 1 the risk assessment and looking at whether, 2 you know, changes in those levels or better 3 information that's now available helps us to4 look at potential shifts in those pathway5 specific risk estimates that could happen, 6 potential bias in those risk assessments. 7 Simulating indoor dust lead and 8 linked to ambient air, as I mentioned, this is 9 a really important aspect of the risk 10 assessment. There's a study by Hunt 2008 that 11 looked at Herculaneum and had some interesting 12 information on cleaning efficiencies and the 13 types of lead dust, the particle size of lead 14 dust that remains. Because that's very 15 specific to Herculaneum because it focuses on 16 a hard floor surface and doesn't include 17 consideration for carpeting, while it's 18 interesting and may help us to further look at 19 whether our cleaning efficiencies are 20 reasonable, whether there may be biases in 21 those, it doesn't really help us to refine the 22 residential scenarios in the general urban

### 202-234-4433 Neal R. Gross & Co., Inc. Page 32 1 case study at all because of its focus on the 2 Herculaneum situation and because it didn't 3 consider carpeting. So I think it will be 4 useful in helping us to further understand 5 uncertainty, and we'll use it that way. 6 Pathway apportionment in lead 7 exposure. NHANES and NHEXAS had a number of 8 additional studies that have been published, 9 analyses that have been published looking at 10 pathway contributions. And I think this will, 11 again, help us to understand how our pathway 12 assessments for non-air pathways in particular

13 and dust are related to each other and the 14 degree to which sort of our assumptions or the 15 degree to which these may be correlated. 16 However, because these don't really look at 17 ambient air lead, which they don't provide 18 coverage for that in general, we're not really 19 going to be able to use them to further refine 20 that aspect of the analysis. But it still may 21 help us with some of those other pathways that 22 were included in the risk assessment.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 33 1 And the next one has to do with 2 predicting population distributions of blood 3 lead levels. This is where we simulated a 4 central tendency blood lead value and risk 5 estimate and then we used the geometric 6 standard deviations to sort of characterize 7 the spread of risk around that. There is some 8 enhanced information on GSDs which will help 9 us to understand do we think, in some of 10 these, you know, do we think that the 11 distributions of blood leads around a central 12 tendency for residential population seem to be 13 getting smaller or are they getting wider, and 14 that will help us to understand some of the 15 bias. But, once again, it doesn't really help 16 us to get at the correlational information, 17 correlational issue of pathways which is so 18 critical to characterizing air-related 19 exposure and risk. 20 And, finally, in terms of IQ loss 21 modeling in children, our evaluation is that 22 we're not really in a position to have a

### 202-234-4433 Neal R. Gross & Co., Inc. Page 34 1 demonstrably different characterization of IQ 2 loss. But we think we'll certainly look at 3 those CR functions and see if it helps us to 4 gain any additional perspective, but I don't 5 necessarily expect a lot of refinement there. 6 So the final slide here is just to 7 sort of note and to provide an overview once 8 again of how we're going to present this 9 information. So, once again, we're going to 10 definitely present the risk information and 11 the policy assessment framing the analysis 12 that was done. We're going to look at the way 13 information has been published since the last 14 assessment to help us interpret and further 15 enhance our understanding of the risk 16 estimates and uncertainties, potential biases. 17 The degree to which any additional 18 situations, exposure situations that come up 19 between now and completion of the policy 20 assessment, if we identify any of those, we've 21 talked about airports and other things, we 22 certainly would look at using the case studies

### 202-234-4433 Neal R. Gross & Co., Inc. Page 35 1 to help us get an understanding of those 2 exposure and risk situations. And then, you 3 know, we would obviously look at the public 4 health implications of the exposure and risk 5 information, including our enhanced 6 understanding of uncertainty that we would 7 gain by looking at how the evidence now helps

8 us to understand that. 9 So thank you very much. 10 DR. FREY: Yes, I would open it up 11 to some clarifications, but I wanted to ask a 12 couple of questions for clarification. So my 13 interpretation of what you've summarized is 14 that you don't see a need or a basis for 15 changing any of the structure of the exposure 16 and risk model, that there's inadequate 17 evidence to change the underlying equations or 18 algorithms in the model, and that there may be 19 some instances where more recent data are 20 available, maybe not directly relevant to 21 characterizing the transport across an 22 exposure pathway, for example, but maybe

### 202-234-4433 Neal R. Gross & Co., Inc. Page 36 1 helping interpret uncertainties. 2 I guess I was wondering if you 3 could clarify, though, is the proposal that 4 you're essentially implying here to do a 5 qualitative uncertainty assessment, or is 6 there a role for quantitative sensitivity 7 analysis or quantitative uncertainty analysis 8 related to some of the points in that last 9 slide? And related to that, could you comment 10 maybe a little more specifically on the 11 aviation gasoline exposure scenario and 12 whether or how that would really be addressed? 13 DR. PEKAR: Well, certainly, the 14 first one. I might let Deirdre handle the 15 second one. So, you know, we're still 16 continuing to evaluate the way the additional 17 information would be, in which instances it's 18 going to improve our characterization. I 19 mentioned some of these here. I expect that 20 to be primarily qualitative. I think there 21 may be some semi-quantitative, meaning, you 22 know, if you have a better characterization of

### 202-234-4433 Neal R. Gross & Co., Inc. Page 37 1 soil levels and it looks like the mean soil 2 value, residential soil value is changed or it 3 might be different in different parts of the 4 country, it might speak to the fact that that 5 component of risk might be lower or higher, 6 which would impact the fraction of risk that's 7 air-related, but it's not going to impact the 8 air-related element. 9 The point here is that I think you 10 could characterize, we do have additional 11 information now in some of the pathways, but 12 they're not air-related pathways, and that's 13 the critical element of the analysis, and we 14 would make that point. And, further, if you 15 can't really, if you don't have refined 16 information speaking to the correlation 17 between those pathways, particularly when air 18 exposures are higher, then we're really not in 19 a better position. So I would expect this to20 be more of a qualitative, maybe semi21 quantitative characterization of changes in 22 those other non-air pathways where I think

### 202-234-4433 Neal R. Gross & Co., Inc. Page 38 1 we're in a better position. 2 In terms of the aviation, I think, 3 speaking sort of off the cuff a little bit on 4 this, I think we would look at whatever 5 ambient data we had. And, you know, you can 6 say, well, if you have ambient air levels and 7 you have different types of exposures, you can 8 look at what are risk assessments across a 9 range of risk estimates assignments have 10 characterized in terms of the risk associated 11 with that level of exposure. The general 12 urban case study I think being a good example

13 of that. 14 So that's sort of my, you know, 15 these assessments help us to characterize 16 levels of exposure in ambient air levels, and 17 I would expect an airport scenario to be sort 18 of similar if we're talking about residential19 exposures. If we're talking about non20 residential episodic exposures, then obviously 21 that's a different kind of situation because 22 that wasn't necessarily what we were looking

### 202-234-4433 Neal R. Gross & Co., Inc. Page 39 1 at. 2 DR. FREY: Okay. 3 DR. MURPHY: Oh, sorry.

4 DR. FREY: Yes. Just a 5 clarification on what Zach mentioned. So when 6 you talk about the qualitative, is it fair to 7 assume that you would follow a structured 8 approach to that that's similar to what's been 9 done in other REAs in terms of something like 10 a modified WHO -- 11 DR. PEKAR: Exactly. No, that's 12 exactly right. In fact, in the PM analysis we 13 started doing that, and it was very useful. 14 So we would do that. That's exactly right. 15 DR. FREY: Yes, part of what I'm 16 trying to understand is what is the 17 methodological approach that you're planning -

18 - 19 DR. PEKAR: I think it would be a 20 systematic approach with each of these topical 21 areas with specific studies where we would 22 sort of say, you know, there's additional

### 202-234-4433 Neal R. Gross & Co., Inc. Page 40 1 information here we think that suggests that 2 there could be a degree of bias, and then 3 implications from sort of an interpretation of 4 the air-related perspective would frame that. 5 Obviously, my take on this is that would be 6 sort of a no in those columns, but we would 7 speak to, you know, we do believe that this 8 shows that this particular pathway may have 9 changed. But in terms of overall air risk, 10 we're not in a position to have a different 11 characterization, particularly of high-end 12 risk for instance, something like that. 13 DR. FREY: Okay. And then I 14 think, Deirdre, you wanted to add something. 15 DR. MURPHY: I was just going to 16 add clarification. I know that you and Zach 17 speak on a particular wavelength, and I just 18 want to make sure people are tuned in. Just 19 one thing we consider in looking at this is 20 that we have a data set that's available from 21 the last risk assessment, and that's really 22 what we're going to be pulling in to this

### 202-234-4433 Neal R. Gross & Co., Inc. Page 41 1 policy assessment. In the last staff paper, 2 we pulled in that data set which was brand 3 new. Now it's a little bit aged, but it's 4 still our data set that we base the primary 5 presentation on. And then it will be informed 6 by, as Zach just went through, our 7 understanding of the current situation and 8 evidence in the current situation. 9 DR. FREY: Okay. I know a number 10 of panelists wanted to ask questions. I think 11 Phil and -- okay. The order I'm aware of, I'm 12 going to say Phil, Chris, George, and Michael. 13 DR. GOODRUM: Okay. I'll try to 14 be quick. 15 DR. FREY: Okay. 16 DR. GOODRUM: Zach, can you speak 17 a little bit more about what the emphasis is 18 going to be on the risk characterization and 19 how you're qualitative or quantitative 20 uncertainty analysis will be presented, 21 especially if you're going to try to tease 22 out, for example, the gray box components, the

### 202-234-4433 Neal R. Gross & Co., Inc. Page 42 1 recent air components, the uncertainty in that 2 part of your various simulations from all the 3 other uncertainties? 4 I'll maybe try to articulate why 5 I'm asking that question. So we've talked a 6 lot in previous panel meetings about two major 7 ways to present risk. One is to focus on the 8 absolute, you know, predicted blood lead 9 distribution or the blood lead distributions 10 that are observed in the empirical data and 11 point out the relative contributions of air to 12 those discrete blood lead estimates, or you 13 can focus on more of the concept of the change 14 in the blood lead, regardless of where you are 15 in an absolute basis, the relative 16 contribution of air to that delta in blood 17 lead. And those are two different, related 18 but different ways of communicating. I'd be 19 interested in understanding a little bit about 20 which path you plan to focus on. 21 And why I'm asking about teasing 22 apart the air contribution to all the other

### 202-234-4433 Neal R. Gross & Co., Inc. Page 43 1 sources of exposure and the total exposure 2 pathways is: will you be able to tackle one 3 anticipated problem that the uncertainty in 4 the air pathway might be minor relative to the 5 uncertainty in everything else, the 6 uncertainty in everything else is swamping the 7 uncertainty in the air pathways? How do you 8 communicate that effectively? 9 DR. PEKAR: Yes. That's a really 10 well-framed question. You know, I think if we 11 talk about high population percentiles in 12 terms of air risk, that uncertainty, and we 13 talked about this, I think, in presenting the 14 risk estimates last time, part of the reason 15 we really use these as sort of supporting 16 evidence for the evidence-based calculations, 17 I mean, really what the risk assessment last 18 time, and obviously we're approaching it in a 19 fresh perspective this time, last time what we 20 said was, because of some of the 21 uncertainties, the real utility of the 22 analysis is in supporting these evidence-based

### 202-234-4433 Neal R. Gross & Co., Inc. Page 44 1 calculations and providing sort of reasonably 2 similar magnitude types of estimates that give 3 us overall greater confidence in the evidence 4 side of things. One of the things we said was 5 when we were talking about high population 6 percentiles in terms of ambient air risk, 7 because of some of these correlational issues, 8 there's a lot of uncertainty at that point

9 then. 10 I think your point of other 11 pathways driving the air or dominating 12 uncertainty is probably more relevant in a 13 central tendency estimate of risk. But when 14 you start to try to push things towards the 15 distribution, towards the outer parts of the 16 distribution, then our ability to look at 17 correlations between pathways and really tease 18 out how those things contribute becomes pretty 19 substantial, and that's where a lot of the 20 policy-relevant kind of risk estimates are. 21 And so we have a lot of uncertainty. 22 And the point I think I would make

### 202-234-4433 Neal R. Gross & Co., Inc. Page 45 1 here is: do we think that our ability to 2 better characterize soil, and maybe shift you 3 a little bit on this distribution, meaning it 4 looks like maybe things have gone down a 5 little bit, let's say, is that magnitude of 6 change and refinement going to be notable in 7 the context of the broader uncertainty we have 8 in relating these things in the higher ends of 9 the distribution? And I think the story 10 always comes to that high air risk.

11 And so whether we talk about blood 12 lead, high blood lead driven by air or high IQ 13 loss, higher relative levels of IQ loss driven 14 by air, we still come to that sort of degree 15 of confidence or fuzziness around that. If we 16 tweak individual pathways within that without 17 better correlational information, are we 18 really in a better position? And I think our 19 assessment, in giving a hard look at what 20 we've seen, is we're not really in a better 21 position. 22 That doesn't mean that the risk

### 202-234-4433 Neal R. Gross & Co., Inc. Page 46 1 information doesn't continue to play that kind 2 of critical role potentially and we're going 3 to have to interpret it. But what it does 4 mean is that sort of tweaking some of these 5 other elements wouldn't really refine that 6 uncertainty at the higher end of distribution. 7 So I'm not sure if that's an answer, but we 8 would speak to that. I would qualitatively 9 say in terms of magnitude. 10 DR. GOODRUM: Yes, that gives me a 11 really good understanding about how you're 12 going to frame the uncertainty. And can you 13 speak a little bit to the first question about 14 whether you're going to focus on the high end 15 of either the IQ deficit or the blood lead? 16 Are you going to focus on absolute estimates, 17 or are you going to focus on deltas? 18 DR. PEKAR: Well, it depends on, 19 you know, the policy question being asked. I 20 mean, if we're looking at alternate standard 21 levels, we focus usually on deltas, having 22 greater confidence in that. I think that was

### 202-234-4433 Neal R. Gross & Co., Inc. Page 47 1 a point we made last time is, you know, you 2 can look at a step down and you're not then 3 dependent also on the absolute level. 4 In terms of blood values, I think 5 we emphasized, my recollection was we 6 emphasized IQ loss increments to a greater 7 extent. But, you know, Deirdre has a better 8 memory for some of these things, so I'm going 9 to let you speak to this. 10 DR. MURPHY: Well, I'll just 11 mention a couple of things. In terms of the 12 issue of absolute versus incremental, be it 13 blood lead or IQ loss, one of the issues was 14 we're interested in the impact associated with 15 air-related lead. And as Zach pointed out, in 16 the modeling simulations that we did, when we 17 simulated alternative air quality scenarios, 18 we were only changing the air signal in some 19 pathways, although we knew it existed in other 20 pathways. 21 And so, in providing our risk 22 estimates, we did provide these ranges that we

### 202-234-4433 Neal R. Gross & Co., Inc. Page 48 1 said were bounded by those pathways, the 2 estimates for those pathways that we did 3 simulate. We knew that was a low end. We at 4 least had that much risk for each of the air 5 quality scenarios, but we also knew it was 6 higher than that because we knew we were 7 missing the air signal in these other pathways 8 because we couldn't quantify changes in soil 9 concentration as a result or a function of the 10 different air scenarios we published. So we 11 simulated. 12 So that's why we tended to say, 13 well, if we just look at differences between 14 air quality scenario one and two, you're not 15 going to see the full impact of a change in 16 the air standard because you won't see how it 17 ripples through soil and diet and all the 18 rest, which are slower and perhaps harder, 19 definitely, from our perspective, harder to 20 characterize. And so we tended to put both 21 types of information on the table, and in 22 looking at the absolute risk associated with

### 202-234-4433 Neal R. Gross & Co., Inc. Page 49 1 each of the air quality scenarios we had these 2 broad ranges, which we said the risk itself, 3 fell somewhere inside this range. It's higher 4 than the low end and it's lower than the high 5 end, but we don't know exactly where it is. 6 So that's why it's hard for us to be precise. 7 I mean, we looked at all of it and tried to 8 draw from it what we could. 9 DR. FREY: Okay. Chris? 10 DR. JOHNSON: Perhaps I just 11 didn't understand. At the very beginning of 12 your presentation when you laid out the 13 different pathways, you made a comment that, 14 if I remember correctly, was something like 15 technical challenges prevented you from 16 modeling how the changes in ambient air 17 concentrations related to what was essentially 18 deposition, I guess, to soil, crops, and 19 water, I believe. Can you explain that a 20 little bit? It doesn't seem like it ought to 21 be that difficult but . . . 22 DR. PEKAR: Sure. So it's really

### 202-234-4433 Neal R. Gross & Co., Inc. Page 50 1 -- let me be a little more clear about that.



### 2 So what we're saying is the real challenges,



### 3 if we're talking about an urban setting and we



### 4 have some, in an urban setting you will have



### 5 elevated, relative to other locations, soil



### 6 levels because of, you know, anthropogenic



### 7 historical loadings, to a certain extent. So



### 8 if we ask ourselves, in terms of residential



### 9 soil exposure of children, if we change



### 10 ambient air lead, let's predict a change in



### 11 the sort of surface soil dust that they're



### 12 going to be exposed to, that's a pretty



### 13 challenging issue because you're not talking,



### 14 it's not like indoors where there's cleaning



### 15 and there's a clean surface and you can



### 16 predict indoor dust loading and look at a lead



### 17 component that's coming in from paint, which



### 18 is what we did. Outdoors, you have a much



### 19 more complicated sort of historical signal



### 20 that's in there, and predicting how that



### 21 changes is complicated and has probably a



### 22 temporal profile that's also complicated to characterize.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 51 1 So because of some of those 2 challenges, we found it really difficult to 3 have that as part of the dial that was being 4 dialed down as we looked at alternate standard 5 levels. I'm not sure if that helps. 6 DR. JOHNSON: What about crops and

7 water then? 8 DR. PEKAR: Well, the thing about 9 that is if we're looking at a standard level 10 in like an urban setting, you have a gradient 11 of exposure, well, you know, relating that to 12 ambient levels that would be impacting crops 13 in a distant sort of agricultural area is 14 going to be a more complicated process. I 15 mean, how is the standard level here and that 16 standard going to affect necessarily a 17 generalized kind of crop exposure scenario 18 where you have commercial crops being raised? 19 So it's hard to simulate that on the one hand, 20 you know. So, I mean, obviously, in the 21 Superfund context, you can model dietary 22 exposure and uptake and other things, but I

### 202-234-4433 Neal R. Gross & Co., Inc. Page 52 1 think it's more of that what would a NAAQS 2 change mean in terms of sort of a crop market. 3 The linkage. How would you link when you have 4 dairy sheds and crop -- there's a complexity 5 there. And we also felt that, I think that if 6 you look at overall exposure, and I've had to 7 look at a fractional contribution, I think 8 you're having a pretty high driving, you know, 9 overall exposure is being driven by soil 10 outdoor ingestion and indoor dust ingestion in 11 the residential context and not so much by 12 dietary exposure. So we figured, 13 qualitatively, that probably wouldn't be as 14 critical a contribution. 15 DR. FREY: Okay. George? 16 MR. ALLEN: First, thanks for a 17 good summary of this process, part of the 18 process. I guess one question I had after 19 some spirited dinner conversation with Rich 20 last night related to the inhalation pathway, 21 which we normally and you said, I think, today 22 was, you know, very small, less than one

### 202-234-4433 Neal R. Gross & Co., Inc. Page 53 1 percent, if I recall correctly. But then we 2 have one or two studies looking at blood lead 3 near general aviation airports showing 4 something that appears to be real: there's 5 elevated blood lead within 500 meters or 6 something. 7 And since I'm assuming that it's 8 combustion mode lead and probably doesn't 9 deposit near field to the soil in that 10 scenario, then my first thought is maybe the 11 pathway is primarily inhalation. And the 12 question is, with that specific scenario, 13 which is now maybe one of the dominant 14 scenarios now that smelters are, more or less, 15 history for combustion-related lead exposures, 16 smelters and tailpipe lead, what is the 17 efficiency of inhalation of fine mode aerosol 18 lead? If you breath it in, how much of it 19 comes out? Do we have any feel for that? And 20 maybe, in this scenario, is inhalation the 21 primary pathway? 22 DR. PEKAR: Certainly, you know,

### 202-234-4433 Neal R. Gross & Co., Inc. Page 54 1 we have simulations in the case studies that 2 would look at ambient levels and direct 3 inhalation. We could look at what that means 4 in terms of blood lead and IQ impacts. The 5 question of the difference in the nature of 6 lead, you know, maybe near airports is 7 something that I think, in the context of that 8 scenario, would be something we would look at 9 and consider. Deirdre, I don't know if you

10 want to take a look at -- 11 DR. MURPHY: I'd just offer one 12 thing because one thing I did a little bit in 13 the last one was with the inputs to the IEUBK 14 model for respiration and the absorption, 15 which I think is part of what you're asking 16 about, and we did use different, I can't 17 remember the name of the element, but there's 18 essentially a different input for the urban 19 scenarios versus the smelter case study that 20 we used, which was a function of a different 21 assumption on particle size distribution. And 22 so I think that gets at what you're talking

### 202-234-4433 Neal R. Gross & Co., Inc. Page 55 1 about. The urban scenarios presumed more 2 finer particles as part of that mix, and so I 3 think that does lead to what, that would be 4 useful to look at again in the context of the 5 question that you're raising to see what that 6 particle mix and how it might relate to that. 7 But I think it, generally, was intended to 8 represent more urban mixes of particles, which 9 would tend to be I think dominated by the 10 combustion type sources. 11 MR. ALLEN: Well, urban is both 12 sizes. But in this particular case, maybe 13 it's pretty unique for urban exposures for 14 combustion mode, meaning fine mode. The only 15 source I can come up with is JA airports now, 16 now that tail pipes are clean. 17 DR. MURPHY: It will be 18 interesting to see what evidence we have on 19 that, on the particle mixtures near airports. 20 I'm not sure that there are good data sets on 21 that yet, but that would be something to look 22 at closely based on this issue.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 56 1 The other thing I'll mention is 2 just the point you said about perhaps airports 3 are now the dominant scenario. I don't know 4 that we have information that that's the case 5 either. We still have, you know, we have 21 6 areas that are not meeting the current 7 standard, and those are not near airports. 8 And so I think we still feel that some of the 9 higher concentration areas in the country are 10 near these point -- 11 MR. ALLEN: Yes, I'm sorry, I 12 should clarify that. Urban non-source, 13 assuming you don't think of GA airport as a 14 source, maybe it is, non-source scenarios, 15 then these things are everywhere next to our 16 neighborhoods. You don't have smelters 17 usually next to neighborhoods, although I 18 guess occasionally you do. And as has been 19 noted, you know, it's half the lead inventory, 20 and half to that half is assumed to be near 21 ground, not up there. And even if it is up 22 there, it comes down somewhere. So the

### 202-234-4433 Neal R. Gross & Co., Inc. Page 57 1 potential for exposure both near airports in 2 a very enhanced way and then, of course, very 3 broadly of varied background exposure is 4 there. And this lead study, okay, what's the 5 pathway of exposure? I don't think it's dirt, 6 which kind of leaves inhalation. And I'm just 7 saying I guess the message that I'm getting is 8 we don't usually think of inhalation as much 9 of an interesting pathway, but in this 10 scenario maybe it is. That's the question. 11 I can't think of any other way to have it make

12 sense. 13 DR. MURPHY: I think you're 14 raising a point that we'll need to consider in 15 the policies. 16 MR. ALLEN: Okay. Thanks. 17 DR. KOSNETT: Thanks very much for 18 your presentation. It was great, Zach. Thank 19 you. I notice that you said that there was 20 some refined information on the GSD. That's 21 always interesting because it has such an 22 impact on IUU decay. Can you just briefly

### 202-234-4433 Neal R. Gross & Co., Inc. Page 58 1 comment what that refined information is? 2 DR. PEKAR: And, actually, I could 3 comment if I actually had my other notes up 4 here, which I don't. You know, we'll be 5 talking about that. I can actually pull those 6 up, this is a very lame response that I don't 7 like to give usually up here, and I can talk 8 to you about that offline. I have notes on my 9 computer. I just didn't bring them with me up 10 here, and I don't want to speak sort of from 11 memory without looking at those. But, yes, I 12 can talk to you about that. 13 DR. KOSNETT: Thank you. 14 DR. FREY: Okay. Any -- yes, I 15 think Ed wants to make a point. 16 MR. HANLON: Zach, for the FACA 17 meeting discussions, what we'd like to do is 18 ensure that discussions with the public, which 19 would include you, with the panel members 20 occur in the open forum that we have here. 21 DR. PEKAR: Oh, sure. 22 MR. HANLON: So if we can try to

### 202-234-4433 Neal R. Gross & Co., Inc. Page 59 1 encourage those discussions, offline 2 discussions, we do not meet the requirements

3 of FACA. 4 DR. PEKAR: Sorry about that. 5 Okay. 6 DR. FREY: So I guess that's a 7 quandary then for exchanging that information. 8 DR. MURPHY: So if I could 9 interject, just to clarify, was the 10 information just to understand which studies 11 it was? I mean, we could certainly send the 12 panel --

13 DR. PEKAR: So let me at least 14 speak to what I recall. 15 DR. FREY: Zach, just to clarify, 16 if you don't have the information now and you 17 would like to provide it in an accurate way, 18 you could send it to Ed in writing, and then 19 we can receive that, I guess, essentially as 20 a public comment. 21 DR. PEKAR: Right. Okay. We can 22 do that. I can also just, for instance, even

### 202-234-4433 Neal R. Gross & Co., Inc. Page 60 1 if the mean blood lead values have been 2 decreasing, I think there's some evidence some 3 of the higher end levels are still left there, 4 which means the GSD can actually get wider 5 because you have some individuals that are 6 still left at the tails at the higher ends 7 because of paint, even if the central tendency 8 values tend to get lower, which they are. So 9 reflecting that kind of, that additional GSD 10 information, we would talk about the degree to 11 which that could be used to simulate blood 12 lead values that are higher. But, once again, 13 this sort of, I think the overall qualitative 14 conclusion that we would reach is that, even 15 if we would generate somewhat different total 16 blood lead values and total risk estimates, 17 we're still hampered, to a certain extent, by18 this uncertainty in teasing out the air19 related exposures in those high-end children. 20 And there's complexity here in the way we use 21 these GSDs and what they mean. This is 22 something that was discussed a little bit

### 202-234-4433 Neal R. Gross & Co., Inc. Page 61 1 yesterday. You know, these GSDs are really 2 characterizing variability in a neighborhood 3 to a larger population of children, depending 4 on the study which can reflect a number of 5 different factors: biokinetic variability, 6 exposure pathway variability, other factors. 7 And so even when we use these GSDs to get sort 8 of a total lead risk, which is what we do, we 9 simulate total exposure and risk for a central 10 tendency using IEUBK, we can pathway a portion 11 of that. But when we go and we put a child on 12 the high end of that distribution, we're 13 still, even if we have a different point on 14 that high-end distribution, we're still 15 hampered by our ability to tease out the 16 pathway contributions to that child. 17 So we would talk about, you know, 18 maybe it looks like the risk estimates might 19 be slightly higher for a 95th percentile child 20 let's say because if the GSD has gotten wider, 21 for instance, has gotten larger, excuse me, 22 the distribution has gotten wider, our ability

### 202-234-4433 Neal R. Gross & Co., Inc. Page 62 1 to still tease out the pathway contributions 2 might be still challenging and would remain 3 the primary source of uncertainty that really 4 isn't addressed by that new GSD. So I'm not 5 sure if that helps a little bit. 6 DR. KOSNETT: It's certainly 7 interesting, and I think we would be happy to 8 look and comment on that because, you know, 9 Phil knows this better than anyone I know that 10 my understanding is that the GSD and the IEUBK 11 should really be intended to model the 12 biokinetic variability, the variability that 13 would exist around a group of children who had 14 the same exposure. And we've been in 15 situations, we were on another panel where we 16 talked a lot about this on dust. We were on 17 the EPA's, you know, indoor dust panel. We 18 had long discussions about this. But I'm just 19 saying it becomes a big issue in the risk 20 assessment, so we'd be happy to give you input 21 if that's something we can do. 22 DR. PEKAR: I think that would be

### 202-234-4433 Neal R. Gross & Co., Inc. Page 63 1 good. And we'll be framing that. I think, 2 depending on where the GSD was derived from, 3 obviously some of the GSDs that -- we had a 4 whole discussion on this in the analysis, and 5 some of the GSDs that come from larger data 6 sets clearly are going to reflect a variety of 7 house types, ages, and other things. So you 8 get a bunch of other factors, sort of a degree 9 of cleanliness in the house, all of this kind 10 of stuff. Obviously, if you get a smaller, 11 tighter neighborhood assessment, then you hope 12 to control and have more consistency in some 13 of those other variables and just focus on 14 biokinetic variability, but I think it's hard 15 to get a pure biokinetic GSD from empirical 16 data like that, unfortunately. I mean, that's 17 my take on it. But when we make those points, 18 a comment on that would be very valuable, I 19 think, to us, particularly in the context of 20 specific GSDs from specific study data sets 21 that we cite would be very useful. 22 DR. FREY: Yes, and maybe just to

### 202-234-4433 Neal R. Gross & Co., Inc. Page 64 1 clarify when we're talking about commenting 2 and providing advice and so on, so what we 3 have in this case, we don't actually have 4 charge questions right now on the REA or the 5 policy assessment. If we, as a panel, felt 6 there were things we wanted to say now, we 7 could do that through the CASAC as a separate 8 letter from the comments on the ISA, and that 9 would be kind of analogous to a consultation 10 in that we're not responding to a charge 11 question and it's just advice. 12 I think what you're intending, 13 Michael, is that when we get the first draft 14 policy assessment we'll see more about what 15 Zach actually did compared to what he says 16 he's going to do. And at that point, we can 17 provide detailed review in response to charge 18 questions. 19 So I guess just think about if 20 there's anything you feel is important for 21 CASAC to say now versus we can wait and see 22 how, I guess, the interpretations of the REA

### 202-234-4433 Neal R. Gross & Co., Inc. Page 65 1 and the qualitative uncertainty assessment and 2 to whatever extent there's quantitative 3 assessment, how that turns out when we meet, 4 probably in October will be our next meeting. 5 And at that time, we can provide detailed 6 responses to what they've actually drafted. 7 Okay? 8 DR. KOSNETT: And if they wanted 9 to, knowing that we're going to review it, if 10 they wanted to send us stuff early, that's not 11 good, right? 12 DR. FREY: Well, there's a formal 13 review process, so when they release a draft, 14 they'll release a first draft PA, policy 15 assessment, for us to review, and that would 16 be the typical procedure. 17 DR. VU: I know that, for this 18 review, the agency deviates from the typical 19 process. I do know in the previous, when you 20 look at ozone or PM, the agency will present 21 an integrated, I mean a scoping for risk and 22 exposure assessment, and then you have a

### 202-234-4433 Neal R. Gross & Co., Inc. Page 66 1 consultation. In this particular case, 2 because the agency doesn't believe this new 3 information, so they incorporate the REA and 4 the policy assessment into one single 5 document. And this meeting is just a preview 6 of what's upcoming, and I think Dr. Frey is 7 saying is that you all have an opportunity to 8 look at the draft that they will present, the 9 agency will present in the fall. And then if 10 you're not satisfied, of course, you can ask 11 for a second draft. So this is just a 12 preview, and OAR did not ask us to do a 13 consultation of a plan. So this is, 14 basically, where we are. 15 DR. MURPHY: If I could clarify, 16 we did have a consultation on the REA planning 17 document, and we do have all of your 18 individual comments attached to the CASAC 19 consensus letter on that consultation, which 20 we will be considering as we put together the 21 presentation in the policy assessment, as well 22 as the comments that you all have raised. We

### 202-234-4433 Neal R. Gross & Co., Inc. Page 67 1 have the transcripts from this meeting, and so 2 we'll be able to consider that in putting 3 together the first draft policy assessment, 4 and there will be two drafts of the policy

5 assessment. 6 DR. VU: Deirdre, I think there's 7 a difference between the integrate plan, which 8 is the outset. I'm talking about the risk and 9 exposure assessment. 10 DR. MURPHY: And I'm not mixing 11 those either. We did develop an integrated 12 review plan. That was earlier last year. 13 Then we developed an REA planning document, 14 and that was the topic of consultation at the 15 July meeting that this panel had. And so I am 16 distinguishing those two different things. 17 DR. VU: Thank you, Deirdre. 18 DR. FREY: Okay. Any other 19 questions, comments, on the risk and exposure 20 assessment? Seeing none, I think, Deirdre, 21 you wanted to tell us a bit about the policy

22 assessment.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 68 1 DR. MURPHY: Just one or two 2 slides here to prepare you for what you will 3 see in the fall. So Zach has described a 4 house, if you will, of the policy assessment, 5 and I'm just going to give you an idea of the 6 home that that -- no, he described a room. 7 Sorry. I'll give you the home that the room 8 will be in. 9 So this is generally the outline 10 of information that will be presented in the 11 policy assessment with purpose and background 12 to orient folks. And then there will be a 13 chapter on ambient air lead, and in that we'll 14 actually be touching on some of the things you 15 talked about yesterday: information on 16 sources, including what we know about aviation 17 gas emissions; ambient air quality, what we 18 have from that information; there will be a 19 wrap-up in that chapter, as we're envisioning 20 now, that will be ambient monitoring 21 considerations, which will take on some of the 22 policy relevant questions that we identified

### 202-234-4433 Neal R. Gross & Co., Inc. Page 69 1 in the integrated review plan with regard to 2 monitoring. Our intention is to revisit them, 3 and that's why we post them in that plan. 4 Then we'll have a chapter on 5 health effects and exposure risk information 6 where we'll be summarizing information from 7 the ISA on health effects, beginning with 8 information on the predominant use of blood 9 lead as a biomarker, characterizing the nature 10 of effects, etcetera. We'll have the 11 presentation of the exposure risk information, 12 as we've briefed you on here. There will be 13 a section on public health implications, 14 trying to draw all of that together to see 15 what does it tell us about public health 16 implications of ambient air lead. 17 And then we'll go through review 18 of the primary standard for lead, the question 19 of is the current standard adequately 20 protecting public health with adequate margin 21 of safety. Then we'll move on to welfare 22 effects and the corresponding presentation

### 202-234-4433 Neal R. Gross & Co., Inc. Page 70 1 there, which will mirror how we've done it for 2 the health chapter, and a review of the 3 secondary standard. 4 So that's, generally, the 5 intention for the document that you guys will 6 be seeing in September of this year as a first 7 draft. And then this next slide, which is the 8 schedule that Lydia showed yesterday, shows 9 you that we intend to bring to you two 10 different drafts of that. The first draft 11 will be in September. And then after we 12 receive your comments and revise based in 13 consideration of those comments, we'll be 14 providing you a second draft which currently 15 is scheduled out into early 2013. 16 DR. FREY: Okay. Great. I was 17 just curious, I guess yesterday we heard a 18 presentation on monitoring from Mr. Cavender, 19 and he mentioned that I guess there's some new 20 monitors that have been collecting data in 21 2010 and those should be certified in about a 22 month. Would that data be taken into account

### 202-234-4433 Neal R. Gross & Co., Inc. Page 71 1 in the policy assessment? 2 DR. MURPHY: Right. So the issue 3 we always face is when do we do the data pull 4 is kind of a phrase that our air quality guys 5 use. And they've done a data pull for the 6 ISA, as you see in the presentation there. 7 And the window is sort of closing on that 8 presentation. But we're aware that we have a 9 longer window going into the policy 10 assessment, and so we'll be trying to do that 11 data pull when it's most effective but still 12 allows us time to present those data and write 13 them up appropriately. So it's not clear to 14 us exactly which monitors will be included in 15 that, but we'll be trying to make it as 16 inclusive as possible and also recognize that 17 there will be two drafts of that assessment. 18 So if there's some need to reconsider what 19 data are included, we can do that. 20 As Kevin mentioned, while there 21 are different dates by which monitors had to 22 be implemented, there is some lagging across

### 202-234-4433 Neal R. Gross & Co., Inc. Page 72 1 some of it. And so we may not have complete 2 data sets, and we'll be considering that, as 3 well. But there will be as much presentation 4 as we can provide. 5 DR. FREY: Okay. Yes, it seemed, 6 if I understood that correctly, that it might 7 provide some insight on the source-oriented 8 exposures and possibly, I don't know whether 9 that would have implications for the REA, but 10 it seems like something that would be good to

11 take a look at. 12 Other clarifications or questions 13 or comments from the panel on what we've heard 14 regarding the policy assessment? Okay. I 15 don't see any. Well, Dr. Pekar, Dr. Murphy, 16 thank you very much. 17 DR. MURPHY: Thank you very much. 18 DR. FREY: We're at the part of 19 the agenda where we can provide an opportunity 20 for clarifying remarks from members of the 21 public. And I think, for this purpose, I'll 22 ask the DFO if we've been contacted. Also, I

### 202-234-4433 Neal R. Gross & Co., Inc. Page 73 1 guess maybe I'll defer to Ed on checking if 2 members of the public are on the phone who

3 want to make such comments. 4 MR. HANLON: So as of this time, 5 we have not received any requests for public 6 comment or requests for clarifying comments. 7 Are there any requests from the public for 8 that? So hearing none, Chris? 9 DR. FREY: Okay. All right. So 10 we now have time in the remainder of our panel 11 meeting for discussion. And it seems to me 12 there are a number of topics that we should 13 discuss. One is, while it's fresh, is whether 14 there are any significant issues that we want 15 to raise as a panel in sort of an advisory 16 capacity regarding what we've heard on the REA 17 or the PA. And if so, then there may be a way 18 to convey that possibly separate from the 19 letter that we use to review the ISA. I think 20 we did hear that both Dr. Pekar and Dr. 21 Murphy, of course, are aware of our discussion 22 today, aware of our prior comments on the

### 202-234-4433 Neal R. Gross & Co., Inc. Page 74 1 consultation related to the REA. So the 2 extent there's anything that would go beyond 3 that, I just want to open the floor for that 4 if any members feel so moved. Phil?

5 DR. HOPKE: Yes. I haven't heard 6 any mention of having anybody look at the 7 residual risk analyses that would have had to 8 have been done following the MACT efforts on 9 the secondary and primary lead smelter and 10 wondered whether there was some potentially 11 useful additional information in those 12 residual risk assessments that could help to 13 inform the risk assessment here. All of that 14 should be well done, you know. It may be old 15 stuff by now, but it certainly might be worth 16 a review just to make sure that there was 17 something that they spotted that wasn't in the 18 current risk assessment. 19 DR. FREY: Okay. Any thoughts? 20 So I take it by the lack of more discussion 21 that the panel is in sort of passive 22 concurrence that the premise of what EPA is

### 202-234-4433 Neal R. Gross & Co., Inc. Page 75 1 doing, to the extent that there isn't 2 substantial new evidence to support new dose 3 response models for IQ effects or to look at 4 other end points, that that is a reasonable 5 state of the science at this time and so on. 6 And if there's any disagreement with that, 7 this would be the time. But I think we did 8 discuss that a bit at our last meeting, as 9 well. Okay. All right, good. 10 Well, then I think what I'd like 11 to do is talk just a little bit reflecting on 12 some of the presentations we heard yesterday 13 morning on monitoring and aviation gas, and 14 then let's come back to the charge questions 15 on the ISA. So on the monitoring, we heard 16 both about the current work to implement some 17 additional monitors for lead using current 18 sampling and analytical methods, and then we 19 heard a presentation on the development of a 20 new sampling method for ambient lead. Are 21 there -- well, let me put it this way: as 22 CASAC, what we can potentially do, not

### 202-234-4433 Neal R. Gross & Co., Inc. Page 76 1 necessarily right away, but as that work 2 develops that Dr. Vanderpool described, we do 3 have another committee on CASAC that is the 4 AAMMS, and I never remember what that stands 5 for but I think of it as the ambient 6 monitoring committee -- yes? Ambient 7 Monitoring and Methods Subcommittee. So they 8 are I think better constituted to review 9 monitoring technology than our panel is10 because our panel is aimed at a very multi11 disciplinary look at a lot of issues. And so 12 CASAC could, for example, express interest and 13 support for what EPA is doing and also 14 interest in having an opportunity to take a 15 look at that through the monitoring committee, 16 and that's kind of my inclination is to 17 recommend that to the seven-member statutory 18 CASAC, and then that group could craft a 19 letter to the administrator that would express 20 that view. I want to just mention that and 21 see if there are any comments or discussion or 22 suggestions related to that. Yes? Phil?

### 202-234-4433 Neal R. Gross & Co., Inc. Page 77 1 DR. HOPKE: That seems like a very 2 sensible way to approach it. There's several 3 of us here who are on that subcommittee and 4 others who could bring in their expertise, and 5 I think that would be a very good way to 6 provide some additional input. 7 DR. FREY: Okay. And, George, 8 you're seconding?

9 MR. ALLEN: Yes. 10 DR. FREY: Okay. Any other 11 thoughts or discussion? Okay, good. All 12 right. And then we had a presentation 13 yesterday on aviation gasoline, and we did 14 have some clarifying discussion after that. 15 I just wanted to provide an opportunity if 16 there were any further thoughts related to 17 that topic. That did come up this morning in 18 the discussion of the risk and exposure 19 assessment, and there may be some, as George 20 suggested, some nuances to that where, you 21 know, maybe locally inhalation perhaps is more 22 important than with some of the other exposure

### 202-234-4433 Neal R. Gross & Co., Inc. Page 78 1 scenarios. But is there anything in addition 2 any of the members of the panel would like to 3 offer on that topic? I'll just open it up for 4 discussion. Rich? 5 MR. POIROT: I've just been 6 thinking that it strikes me as the kind of 7 source that may not necessarily lend itself to 8 the highest concentrations kind of an effect 9 but which is more broadly distributed than 10 many of the other kinds of sources. I'm 11 remembering from last time, you know, someone 12 suggesting, posing the question of what's the 13 overall effect on society of everybody being 14 attentive an IQ point dumber, you know, that 15 sort of a thing. At any rate, that was one 16 thing that struck me about the nature of that 17 source is that it might not lead to the 18 highest exposure at the location in accedence 19 of the current NAAQS but, on the other hand, 20 is so much more broadly distributed that it's 21 important in that way. 22 DR. FREY: Yes, I think that's a

### 202-234-4433 Neal R. Gross & Co., Inc. Page 79 1 good point. And I guess, although, at the2 same time, if we think of a landing and take3 off cycle that's producing the emissions, the 4 take-off mode is typically a high-power mode 5 that's very close to the runway at low 6 altitude and then the climb out. And often 7 with, I guess, aviation, air quality modeling, 8 once the plane gets above 3,000 feet or the 9 mixing height, then people tend not to worry 10 so much about it. But I think, as you're 11 saying, if you're dispersing a lot of 12 particles, maybe even at high altitude, and 13 some of these planes don't fly at very high 14 altitude, that there could be broader 15 dispersion at low levels, and so maybe there 16 is a low level effect. So I think, yes, 17 that's a difference in the source category 18 versus, say, a lead smelter. 19 MR. POIROT: If I could add one, 20 you know, I had suggested yesterday that the 21 idea of presenting a list of the largest 22 sources that would be, you know, a counterpart

### 202-234-4433 Neal R. Gross & Co., Inc. Page 80 1 to the largest source categories and expecting 2 probably airports are not going to show up on 3 that list of the largest sources. But to back 4 off and modify that, thinking a little bit, 5 if, on the other hand, we were doing sort of 6 a population weighted concept of large 7 sources, quite possibly airports would be 8 something that affects a large population in 9 a general way. 10 DR. FREY: Yes. So maybe just to 11 say something, and then Phil. So this may 12 have some implication for the ISA because 13 these seem like things that could be discussed 14 in the ISA, to the extent they're not in there 15 now. Phil?

16 DR. HOPKE: Yes. I know that TRB 17 had funded a study of lead from airports 18 starting last year. I don't know where it 19 stands at this point, but those are always 20 pretty short-term kinds of efforts. And so it 21 certainly would behoove the EPA to check with 22 the people at TRB, the NRC TRB people, to just

### 202-234-4433 Neal R. Gross & Co., Inc. Page 81 1 see where that study is and whether it could 2 provide some useful information to the policy

3 assessment. 4 DR. FREY: Yes, that's a good 5 point. My understanding of the timing of that 6 study is that it's going to kind of optimally 7 miss the timing of what we've heard, that it 8 will be done probably in the end of 2013 or 9 something like that. So just when everything 10 is getting finalized here, it will available. 11 But, yes, to the extent that any preliminary 12 results are available -- of course, there is 13 the criteria that's described in the preamble 14 where EPA wants to use peer-reviewed data, so 15 I don't think it will satisfy that criteria 16 during the time frame of this review cycle, 17 which is frustrating but there will be quite 18 a lot of good data probably in another year or 19 two. Yes, Mike?

20 DR. RABINOWITZ: Just a small 21 question. Do we have any data on blood lead 22 levels of pilots or people who ride these

### 202-234-4433 Neal R. Gross & Co., Inc. Page 82 1 gasoline-driven planes that use tetraethyl

2 lead? 3 DR. FREY: I personally don't. 4 I'm sorry. Rick? 5 DR. CANFIELD: Just to dispel some 6 of my ignorance, does anyone know is the 7 leaded fuel used in helicopters, as in Flight 8 for Life and those kinds of transportation 9 helicopters going back and forth over 10 Manhattan all the time? 11 DR. FREY: Phil, do you want to 12 use the mic? 13 DR. HOPKE: I thought most of 14 those were turboprops, and so they'd be 15 fueling with Jet-A, not with gasoline. 16 DR. FREY: Yes, I think that's, 17 and that's also why that what we might think 18 of as a propeller plane used for commercial 19 aviation, which is actually a turboprop, is 20 not really within the scope of what we talk 21 about with aviation leaded gas with a piston 22 engine. So, yes, to the extent, I think, I

### 202-234-4433 Neal R. Gross & Co., Inc. Page 83 1 don't know for sure, but I think they tend to 2 be more turbo than piston-driven. 3 Any other thoughts on the aviation 4 gas topic? Okay. Well, so what I'd like to 5 do then is return to the charge questions, and 6 I wonder if we could put on the screen -- do 7 you have the file for the draft responses to 8 the charge questions? Okay. So if we could 9 start with chapter three, and I think what we 10 want to keep in mind as we go through this is 11 do we answer the charge question? We want to 12 make sure to answer the charge question. 13 Something else is are there things that have 14 implications for synthesis across chapters of 15 the document and, particularly, also 16 implications for tying concepts together in 17 chapter two? And then also what are the key 18 points to distill from these charge questions 19 responses that should go in the letter to the 20 administrator? And what would be the key 21 priorities or really the essential things that 22 are critical if I think we're going to be

### 202-234-4433 Neal R. Gross & Co., Inc. Page 84 1 asking EPA to give us a third draft ISA for us 2 to review, and we don't necessarily need to 3 review the entire ISA at the same level of 4 detail. I think that review is going to focus 5 on chapter five and the correlated material in 6 chapter two. But to the extent there's 7 anything really critically deficient in the 8 current draft of the ISA, I think it would be 9 good to make sure we convey that priority to

10 EPA. 11 Okay. So perhaps the procedure 12 for this might be if the lead discussant on 13 the charge question could try to briefly 14 summarize, and we don't necessarily need to 15 read it word for word but maybe the main point 16 of each paragraph. And then we could have 17 some discussion as to whether this is 18 answering the charge question or whether it's 19 complete, whether it has implications for 20 synthesis across the document, and what are 21 the implications for the letter. So with 22 that, George, would you be ready to start us

### 202-234-4433 Neal R. Gross & Co., Inc. Page 85 1 off? 2 MR. ALLEN: Sure. Thanks, Chris. 3 All right. Well, the approach I took was, 4 indeed, to specifically address the charge 5 questions for chapter three. This first 6 paragraph with the italics refers to the list 7 of changes, which is what the first part of 8 the charge question is about. There's a bunch 9 of bullets on the administrator's, on the 10 attachment to the March 23rd administrator's 11 response to the CASAC review of the first ERD. 12 And so I didn't repeat that here because it 13 was scanned and I couldn't copy/paste it, but 14 it refers to it. 15 And what I said was, oh, okay, 16 there's a whole bunch of these and we're okay 17 with all of them except the following four, 18 which I then specifically address here. And 19 I put the section numbers in there, and the 20 first one is the issue of air lead emissions 21 from domestic wood burning. Well, sorry, wood 22 burning, but I'm talking domestic wood

### 202-234-4433 Neal R. Gross & Co., Inc. Page 86 1 burning. And I seem to be the only one 2 focusing on this, but I think there's 3 something there that needs a little more 4 attention. 5 This ties indirectly to, as John 6 Vandenberg pointed out yesterday, to a brief 7 piece in chapter four where they cite a study 8 that is actually quite interesting, despite 9 having a P of only 0.06 for the very small end 10 of 18 samples for people who had exposure. So 11 that's one piece, and I guess it will come 12 back up again in chapter four.

13 And then there's the TSB FRM 14 revisiting sampling methods, which we've 15 talked, pretty much talked to death so I won't 16 go over what I wrote here. There is always 17 the issue of is this within the scope of an 18 ISA. Traditionally or technically, no, but 19 it's the gorilla on the block, in part, 20 because it does keep coming back again and 21 again and again and again every time CASAC has 22 a chance to get near it.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 87 1 And we did hear some really good 2 material from Bob Vanderpool yesterday saying, 3 yes, we're working on it. Now, that whole 4 process of we're working on it doesn't make it 5 into the ISA, and maybe it doesn't have to. 6 But on the other hand, there's a bit of 7 disconnect if there's no mention of the 8 current activities. Again, this is very 9 untraditional ISA stuff, but, hey, it's there. 10 It's going on, and it's relevant. 11 Many people commented that we 12 didn't really want that AQS data table that 13 was in the first draft in the appendix, Table 14 3A-13, didn't want it removed. We didn't like 15 some aspects of it, but we thought it could be 16 fixed, but it just got removed. We would like 17 it put back in with the fixes described in our 18 comments on the first draft of the ISA. And 19 really this is all because there isn't much 20 information on size, ambient air lead size. 21 It's pretty limited. And there is information 22 in AQS that was summarized and is really

### 202-234-4433 Neal R. Gross & Co., Inc. Page 88 1 useful to have back, so the message is don't 2 remove it, fix it, essentially. On the same 3 lines with, okay, let's use everything we can. 4 I believe there was some discussion that there 5 might be material in the Cho paper, the 2011 6 Cho that is not included that may be relevant 7 in this context, as well as the Cavender 8 Schmidt EPA memo on this topic that was I 9 think in the first draft ISA and disappeared - 10 - no? Rich can maybe clarify that. 11 MR. POIROT: Well, yes. The 12 Cavender Schmidt memo actually came out in the 13 last NAAQS review cycle right at the end of 14 the process. But just to clarify that a bit 15 also, one of the problems we had with the size 16 distribution information presented in the last 17 draft of this ISA is that a lot of the data 18 sets were identical to those used in that 19 earlier memo but the answers were different. 20 So that was one of the problems we had with 21 it. If the more recently done comparison 22 could be repaired, there wouldn't be any need

### 202-234-4433 Neal R. Gross & Co., Inc. Page 89 1 to also bring that memo up. I suggested that 2 yesterday as if there wasn't time or 3 something, at least -- 4 MR. ALLEN: Okay. So really it's 5 just connecting those two dots and making sure 6 that's part of the fix, which, again, we just 7 need to go back to our comments from the first 8 draft. Okay. And then the background air 9 lead levels, there was some discussion of that 10 that it's kind of open-ended and that maybe 11 some constraints could be put on it. 12 Other comments, again, responding 13 to the charge in general. The material is 14 clearly presented. There's some pieces that 15 could be made more clear in terms of the 16 reading, and I kept thinking as I read it, you 17 know, as additional parsing and synthesis of 18 some of the literature results really could 19 make it much more readable and accessible, and 20 so you don't have to refer to the references 21 to understand some of the summaries of the

22 results.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 90 1 One case that comes to mind is 2 some of the methods and size distribution 3 material don't mention the methods used, and, 4 therefore, it's hard to interpret because it's 5 all about sampling method when it comes to big 6 lead particles. 7 There was a lot of discussion, 8 sometimes heated, about Spearman rank when you 9 talk about the multi-pollution material in 10 section 3.5.4. I don't know if we have 11 consensus on that, but this is maybe a good 12 time to open that up, the Spearman rank versus 13 Pearson or some other parametric for this 14 purpose or both or maybe evaluating both and 15 only presenting the one that makes sense, 16 that's defendable. And also filtering in some 17 of these results so that we're only looking at 18 the stuff that has some meaning, as opposed to 19 everything which just means you have to work 20 harder to get at the stuff that has meaning,

21 would be useful. 22 And then there's linkage in

### 202-234-4433 Neal R. Gross & Co., Inc. Page 91 1 general between chapter three and the exposure 2 part of, air exposure part of chapter four. 3 And just one example here again is that wood 4 smoke topic, and I'd just cite the two pieces 5 that are there but, actually, as John 6 mentioned, I wasn't aware of the one in 7 chapter four because I hadn't read it 8 carefully. So that's a brief overview of my 9 first effort on this. 10 DR. FREY: Anything that is 11 missing here? Does anyone think anything is 12 missing or any general comments on this draft? 13 I have a few sort of comments or questions. 14 I think on the issue of the correlation, I 15 personally think it would be okay to have both 16 Spearman and Pearson but explain what they 17 mean. And then I think part of the comment 18 was just don't use them for everything, like 19 if there's some plausible reason why you 20 expect a relationship. 21 DR. HOPKE: What relationships are 22 they trying to highlight here? I mean, what

### 202-234-4433 Neal R. Gross & Co., Inc. Page 92 1 does it mean to have a relationship with one 2 of the other criteria pollutants, you know,3 particularly ozone for example, so they co4 vary?5 DR. FREY: Right. So if they co6 vary, is there a mechanistic sort of a 7 plausible reason for that? 8 MR. ALLEN: Sometimes, pardon the 9 expression, it's throwing mud at the wall to 10 see what sticks. 11 DR. FREY: Rich? 12 MR. POIROT: Yes. I had, along 13 similar lines, it wasn't really so much the 14 occasional use of the Spearman as it was the 15 changing from one to the other and some, to 16 me, very illogical results in some of those 17 perfect 1.0 correlations between lead and some 18 of these other pollutants absolutely don't 19 make sense. So if we're going to be picking 20 on the correlations, that's a point to raise. 21 There was a table presented in there, Table 3- 22 10, that showed correlations between lead and

### 202-234-4433 Neal R. Gross & Co., Inc. Page 93 1 other pollutant species in TSP, PM10, and PM2.5 2 that had numbers in it that I absolutely don't 3 believe and can't imagine how they could have 4 possibly been published where you've got no 5 correlation between lead and an element in 6 TSP, 0.99 correlation between the same element 7 and lead in PM10, and a negative correlation 8 in PM2.5. That's just not remotely possible in 9 any way that I can imagine. So if we're going 10 to be picking on things, that's one I'd like 11 to pick on. 12 But the last point I wanted to 13 make along those lines is the one set of 14 correlation data that I thought was useful and 15 informative was the correlation using the CSN 16 data and among all the different measured 17 species. And to me, there was some 18 potentially useful information in there. And 19 in the appendix, George, that presents those 20 correlations seasonally, and for both the 21 winter and fall season the second highest 22 correlation of lead with anything is with

### 202-234-4433 Neal R. Gross & Co., Inc. Page 94 1 potassium. So if you're looking for some wood 2 smoke, you know, possible suggestive 3 information, I don't know what else you'd be 4 driving at. 5 DR. FREY: I guess on this point 6 of the mechanistic or science-based 7 interpretation of these correlations, it seems 8 like that's worth writing into the response to 9 the charge question that that's one of the 10 things that we're looking for. Phil? 11 DR. GOODRUM: I'll just weigh in 12 again because I weighed in before. I think I 13 totally agree with what I've heard in terms of 14 questioning the results that you see from the 15 correlation coefficients that look to be too 16 high or implausible. But that's different 17 from critiquing the use of the Spearman rank 18 correlation itself, so I'd like to propose 19 that in our consensus comments maybe we ask 20 EPA to provide for the reader a paragraph that 21 says, you know, some of the data in the 22 literature were reported using Spearman rank

### 202-234-4433 Neal R. Gross & Co., Inc. Page 95 1 and some are reported in Pearson R, here's 2 what the difference is, so a little bit of an 3 up-front methodology description. And then 4 I'm okay with kind of flip-flopping as they 5 discuss the literature. It's clear that, you 6 know, they're basically synthesizing the 7 information as presented, rather than doing a 8 re-analysis. But I would be opposed to 9 discarding studies that present Spearman rank 10 correlation just on the fact that they use 11 that methodology. I think it's a totally 12 acceptable correlation analysis technique. 13 DR. FREY: Okay. It sounds like 14 that's a good suggestion to fold into the -- 15 okay, great. I guess a couple of points I was 16 thinking of. I know, Phil, when we had the 17 presentation on the sampling, you expressed 18 some concern about I guess what I think of as19 a design-based sampler versus a performance20 based sampler. And I wonder if the 21 implication for the ISA is just to maybe say 22 a little bit about what those things mean,

### 202-234-4433 Neal R. Gross & Co., Inc. Page 96 1 that one could design a sampler to meet 2 certain, you know, geometrical requirements 3 and so on or one could design a sampler to 4 achieve I guess a performance goal for I guess 5 some fractional recovery of particular sizes 6 without constraining the geometry of it. I 7 don't know if that's quite what you meant, but 8 maybe just laying out what those are might be

9 useful. 10 DR. HOPKE: Well, there's two 11 issues really. One is the sins of the past 12 continue to haunt us because they fail to make 13 the performance standard for the PM10 sampler 14 sufficiently rigorous. But there's also the 15 problem now in terms of if one puts a 16 performance standard out there, will anybody 17 leap to the bait? Given the consolidation of 18 the field so that we now wind up with only two 19 companies that still actually make samplers, 20 will either of them invest in developing 21 testing and validating a sampler whereas if 22 all they have to do is follow a set of machine

### 202-234-4433 Neal R. Gross & Co., Inc. Page 97 1 drillings and they're guaranteed to have a 2 valid sampler, might that then get the sampler 3 into play quicker? That's a valid question. 4 I mean, I think, in general, it's better to 5 let the creativity of capable engineers meet 6 a design criteria because there are likely to 7 be innovations which may or may not have been 8 developed in the development of the design 9 standard. But it may be in this case, at this 10 current point in time, impractical to have a 11 performance standard. But I think there 12 should be at least some discussion of the two. 13 DR. FREY: Okay. Yes, George? 14 MR. ALLEN: A quick note. There's 15 always the option for an FEM. You can have 16 the FRM by design and FEM by performance kind 17 of a definition. 18 DR. HOPKE: Yes, if they don't 19 make the hurdles insurmountable like they did 20 for continuous -- 21 MR. ALLEN: Right. But the issue 22 is with a performance specification hurdles

### 202-234-4433 Neal R. Gross & Co., Inc. Page 98 1 are very similar to those in an FEM, about the 2 same thing. So you can have it both ways. 3 You can have your cake and eat it, too. 4 DR. FREY: Okay. I guess another 5 point on the cover letter bullets. The first 6 one I guess I'm a little unsure of, but I 7 wonder if this is a launch point for a broader 8 discussion that might cut across the chapters 9 on are there PM size ranges that we are more 10 interested in than others or is there some 11 differential in the health effects relevance 12 across PM size ranges that would inform a 13 discussion on this bullet point and that also 14 might, therefore, merit some discussion in 15 chapter two? And I wonder if anyone has any 16 thoughts about that? I think, you know, a few 17 people have brought this up kind of 18 tentatively yesterday, and I don't think 19 anyone took the bait on it and maybe we don't 20 know enough to take the bait on it, but I 21 wonder if there's something more that could be 22 said?

### 202-234-4433 Neal R. Gross & Co., Inc. Page 99 1 MR. ALLEN: I think it's hard to 2 say what needs to be said in a short 3 paragraph. I mean, this is a really kind of 4 a snake pit. There's different, I mean one 5 argument is do the best you can but have it be 6 robust and reproducible. Another argument is 7 we don't really care about particles greater 8 than 10 microns. I've heard that one, and we 9 really haven't had that discussion with the 10 entire panel, including the folks that are on 11 the back end with the health and the exposure 12 piece. So I don't know. If you said the 13 question if we could have what we wanted, 14 forgetting about the technical issues, what 15 would we want, I haven't heard that. 16 DR. FREY: Does anyone have a wish 17 list for what you would like in terms of 18 particle size? 19 MR. ALLEN: Or do we care about if 20 X microns or not, you know? 21 DR. FREY: Phil? 22 DR. HOPKE: Well, I mean,

### 202-234-4433 Neal R. Gross & Co., Inc. Page 100 1 obviously, since we know the main mechanism is 2 not inhalation and, yet, you know, particle 3 mass is a cubic function of size; therefore, 4 bigger particles could potentially carry 5 substantially more lead. If that then can 6 stick to the hands, get in, even if they 7 weren't fully dissolvable in stomach acids 8 because you start off with a lot more, that 9 represents a significant potential dose that's 10 important. 11 I mean, I think we just need to 12 have some way of connecting the dots. I mean, 13 the reason we had a TSP standard and continue 14 to talk about a TSP standard is because it's 15 not inhalation that's the primary cause of the 16 dose. And if that's the case, then we've got 17 to then come up with a metric that makes sense 18 in terms of depositing lead in places where 19 people can get it on to hands or in other ways 20 get it ingested. And so I'm not quite sure 21 how we get to that point, but there certainly 22 has to be some of that discussion.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 101 1 And then if we're going to set up 2 differential measurement tools, in one case we 3 say, oh, because we're not in source areas we 4 don't have to worry about big particles. I 5 don't fully get that, okay? Whereas, in 6 source areas I worry about big particles? I 7 mean, if my source is a combustion source, I 8 only make little particles so big particles 9 don't matter anyway. 10 So we have a disconnect between 11 the physics and chemistry of production and 12 this measurement scenario. So we've got to at 13 least have the pieces put together in some 14 sort of logical framework. 15 DR. FREY: Okay. Well, I think 16 that's helpful. I think I figured out what 17 was really kind of bugging me is that first 18 sentence. I think I would rather say data on 19 various PM sizes are useful not because we're 20 happy to have it because there isn't much 21 available. That is, in part, true. But I 22 think there's also a utility to it, I think,

### 202-234-4433 Neal R. Gross & Co., Inc. Page 1021 that Phil laid out pretty nicely for non2 inhalation pathways that we're maybe a little 3 bit less concerned about the particle size 4 itself or maybe, to say it a different way, 5 that the potential exposure is significant6 across a wide range of particle sizes for non7 inhalation and that that's one of the reasons 8 why we want to look at the larger particles. 9 MR. ALLEN: Yes, we're trying to 10 sample dirt. 11 DR. FREY: Yes, yes. Okay. Rich? 12 MR. POIROT: And also I think this 13 would be one of the specific places where we 14 would want to seek a better connection between 15 the exposure metrics as a function of particle 16 size in chapter four. 17 DR. FREY: Which leads to the next 18 point and, yes, I'm glad you mentioned that. 19 We say we need a better linkage. Can we be a 20 little more specific about what it is we're 21 looking for? I know, Rich, if you can answer 22 that or other members of the, either the

### 202-234-4433 Neal R. Gross & Co., Inc. Page 103 1 chapter three or the chapter four discussants 2 could elaborate a little bit. To just say we 3 need a better linkage, if I were EPA receiving 4 that, it would be kind of vague. Can we be 5 more specific what we're asking for? 6 DR. GOODRUM: I have a suggestion 7 on chapter four to be more specific for them, 8 just as an example. If they present summary 9 information across studies, like Table 4-3 10 does, which is a comparison of personal indoor

11 and outdoor lead PM measurements from several 12 studies, that they make sure that they present 13 some summary statistics on the size fractions. 14 That might be one place that they can start to 15 create a grouping logic that, you know, leads 16 to an understanding of air lead and blood lead 17 slope factors. Are they the same across these 18 studies that have similar distributions of 19 particles or not? So try to integrate some of 20 the, if available, particle size information 21 from those studies. 22 DR. FREY: Okay, good. Any other

### 202-234-4433 Neal R. Gross & Co., Inc. Page 104 1 suggestions there? Okay. Maybe a couple of, 2 I think these are small points. I guess, 3 Rich, you had talked about a list of key 4 sources and that those could be either high 5 emitters or maybe ones that are significant to 6 exposure, and I'm not sure I actually saw that 7 in the response to charge questions here. It 8 seems like that's something that might be 9 worth putting in here. Was it intended to be

10 here or -- 11 MR. POIROT: I'm not opposed to 12 including -- 13 DR. FREY: Okay. 14 MR. POIROT: -- a list of key 15 sources, key lead sources, just a list. 16 DR. FREY: Well, I think we had 17 talked, we had some discussion yesterday and 18 then again today about some context for what 19 are the significant either -- I guess you can 20 think of it as either the source-oriented 21 exposure combinations. And so you might have 22 some high-emitting sources, maybe they're

### 202-234-4433 Neal R. Gross & Co., Inc. Page 1051 point sources. But you might have some lower2 emitting sources, like aviation, that, because 3 of their dispersion characteristics, could 4 lead to exposures to large numbers of people 5 and some discussion of that more than is 6 currently in the documents. 7 MR. ALLEN: So it's kind of a 8 broad brush stroke picture -- 9 DR. FREY: Yes, I think so. 10 MR. ALLEN: Oh, okay, sure. That 11 makes a lot of sense. The exposure, if you 12 look under the details of all the exposures, 13 it's very complicated. But if you step back 14 a bit, it's actually, the sources are pretty 15 simple. 16 DR. FREY: Okay. Anything else on 17 chapter three or implications of chapter three 18 for other chapters or for the chapter two 19 synthesis? I think we at least have one 20 example of how chapters three and four could 21 be more closely related. 22 MR. HANLON: Just a point of

### 202-234-4433 Neal R. Gross & Co., Inc. Page 106 1 clarification on that discussion point on the 2 first page, 3.5.3, where the summary notes 3 that better use of material in the Cho paper 4 and the Cavender Schmidt paper. Rich pointed 5 out that maybe a comparison of the data would 6 be useful. Was there an agreement to suggest 7 that that comparison be done, or it was kind 8 of left open whether a comparison was

9 recommended. 10 MR. ALLEN: The memo in the table? 11 My understanding is that the consensus is if 12 we get the table fixed we don't need the memo. 13 MR. POIROT: And the Cho, et al. 14 was a literature-based review of comparative 15 data, whereas the Cavender Schmidt and the 16 comparison in the last draft of the ISA were 17 based on AQS data. 18 MR. ALLEN: Right. And that goes 19 beyond the sticking with the published 20 literature piece, but I think here that's 21 probably very appropriate because part of this 22 literature is sparse on this.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 107 1 DR. FREY: Okay. I propose we 2 take our 15-minute break. So we will resume 3 at 10:35 with chapter four. 4 (Whereupon, the above-entitled

5 matter went off the record at 10:19 a.m. and 6 resumed at 10:38 a.m.) 7 DR. FREY: Okay. Let's get 8 started. We have until 12:30, and I know a 9 number of people are leaving at 12:30. I know 10 a couple of people are leaving at 12. And we 11 have chapters four, five, six, seven, and the 12 introductory chapters to talk about. So we 13 have five charge questions. We have about a 14 hundred or so minutes, so we have about 20 15 minutes per charge question. So let's into 16 chapter four. And, yes, I wanted to just 17 double check on the phone. I think we have 18 two panel members on the phone. Michael 19 Weitzman, are you on the phone? 20 DR. WEITZMAN: Yes, I am. Hello. 21 I apologize for not being there. 22 DR. FREY: Well, we're glad you're

### 202-234-4433 Neal R. Gross & Co., Inc. Page 108 1 with us on the phone. Please feel free to 2 interrupt if you have something you want to 3 say. And, Sean Hays, are you on the phone? 4 DR. HAYS: Yes, I'm here. 5 DR. FREY: Okay. Excellent. 6 Let's see. Phil, can you walk us through the 7 key points on the chapter four?

8 DR. GOODRUM: Sure. And 9 continuing with the theme I think you set out 10 which is focusing on questions that had to do 11 with recommendations for more synthesis, 12 especially across chapters, we actually have 13 a whole section just on that one topic, so 14 that's convenient. The other two that we kind 15 of grouped our overall comments into are 16 recommendations for additional discussion and 17 perspective from EPA on some of the relevance 18 of the information that's provided and then, 19 lastly, a kind of catchall for some of the 20 contradictions that we spotted. So maybe I'll 21 just focus on the first in the interest of 22 time.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 109 1 In section 4.1, there's a 2 discussion of exposure pathways. And as an 3 example, one of the subsections is on dietary 4 lead exposure, so that's 4.1.3.3. In general, 5 we felt that those short discussions about 6 pathway were good. They were factual, but 7 they still lacked some synthesis. So what is 8 the take-home message from that summary of 9 that pathway that helps to relate it back to 10 the main points of the document or at least 11 the main points in this chapter, which have to 12 do with understanding the, for example, air 13 lead/blood lead slopes. So a couple of 14 sentences maybe even that provide that 15 synthesis at the end of those sections would 16 be worthwhile. 17 Okay. There's a very good 18 presentation of the use of the IEUBK model and 19 a discussion of percent contributions of air 20 lead to blood lead, and there was a suggestion 21 to bring that information into a more readable 22 format, for example onto a table summary, that

### 202-234-4433 Neal R. Gross & Co., Inc. Page 110 1 would help the reader better understand what 2 the messages are and be able to, in one 3 snapshot, kind of get a better feel for what 4 the literature supports, what the modeling 5 estimates support. So a table that includes

6 both the IEUBK-based or other model-based 7 estimates of percent contribution, along with 8 any of the information that's available from 9 the literature on that same topic, would be 10 helpful to capture. So we like the new text, 11 and it's just add a new table to help 12 synthesize the information. 13 And then, lastly, we had talked 14 about trying to understand ultimately what the 15 implication is for some of these slope factor 16 estimates on the change in the blood lead at 17 both the geometric mean and at the higher 18 percentile. So that's not yet here but could 19 be included as a way of providing some 20 perspective on the various uncertainties in 21 those estimates of those slope factors or the 22 fact that those slope factors represent

### 202-234-4433 Neal R. Gross & Co., Inc. Page 111 1 different communities and, therefore, when you 2 extrapolate from those particular studies, you 3 know, that's an uncertainty. So to put into 4 context some of the uncertainties that are 5 well described already, it would be helpful to 6 have perhaps some figures, and we had some 7 examples that we can improve. And that would 8 carryover, as well, probably into at least 9 chapter two, the integrated summary, where 10 there might be some overall discussion of what 11 the air lead/blood lead slope factor 12 relationships appear to be and what the 13 uncertainties are and how that translates into 14 changes in the blood lead estimates. 15 So those are the summary points on 16 synthesis topics. Do you want me to go 17 through any others, Chris? 18 DR. FREY: Yes, why don't you go 19 ahead and summarize the response to charge 20 questions, and then we can open it up for 21 discussion. 22 DR. GOODRUM: We really liked

### 202-234-4433 Neal R. Gross & Co., Inc. Page 112 1 figure 4-22. That was a request before. This 2 was the figure that takes the slope factor 3 estimates that were presented in text and 4 table format and shows it graphically, and we 5 thought that was extremely helpful. Our 6 suggestion is to go one step further because 7 that figure has an X axis, which is air lead 8 concentration that I think ranges from zero to 9 four, going by memory, or zero to ten 10 possibly, there's an important discussion that 11 needs to happen on the low end of the air 12 distribution, which is where all the action is 13 right now. And so recognizing that some of 14 those slope factors are generated from 15 empirical data that had higher air lead 16 concentrations and, therefore, were kind of 17 looking at the modeled estimate at the low 18 end, understanding the implications of the 19 model choices becomes even more important. So 20 that discussion of the differences in the low 21 end should be presented and then any 22 implications for model selection.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 113 1 We picked up on the theme of 2 measurement error that was discussed yesterday 3 and just had a suggestion for bringing that 4 back into chapter four. So where it may be 5 discussed in earlier chapters, there's an 6 opportunity here to cross reference to a 7 section where, you know, measurement error in 8 historic lead TSP measurements is noted. And 9 I think it was suggested yesterday that it's 10 likely that the air that's introduced from the 11 underestimates is minor relative to other 12 sources, and that statement alone would be 13 helpful to bring forward here. 14 And this is a comment that comes 15 from Ian's individual comments on the 16 historical perspective. He got the sense, and 17 I'll speak for you, feel free to add, Ian, 18 that chapters three and four tend to highlight 19 or focus on the relationship between trends 20 and decrease in gasoline lead and blood lead 21 at the expense of not really highlighting some 22 of the other major achievements. In

### 202-234-4433 Neal R. Gross & Co., Inc. Page 114 1 reductions, for example, I would think the 2 food lead reductions in the FDA estimates of 3 exposures via diet would be another one to 4 highlight. That's been worked on quite a bit 5 and works its way into the IEUBK model in the 6 current version. 7 And then, lastly, our last 8 grouping here is the contradictions. We had 9 noted that there's an apparent contradiction 10 in some of the text compared to the figures 11 that convey the idea of the elimination rate 12 constant for blood lead, the blood lead 13 compartment. So when exposure stops, what 14 does that decline look like? The model-based 15 estimates suggest it's rapid. Some of the 16 texts suggest the opposite. So if the results 17 that we're seeing in the model are assumption 18 specific, that needs to be brought out a 19 little bit more so that it isn't such a stark

20 contrast. 21 And then, lastly, there's a couple 22 of places where one percent of the body burden

### 202-234-4433 Neal R. Gross & Co., Inc. Page 115 1 is the estimate for the contribution of the 2 blood lead compartment compared to the total 3 body burden and then other places it's 4 mentioned it's five percent, so just to make 5 those consistent. Those were the highlights. 6 DR. FREY: Okay, great. Phil, 7 that's great. So, yes, for each of these, we 8 want to make sure we're answering the charge 9 question. I think, to my interpretation, this 10 is responsive to the charge question. We want 11 to deal with synthesis across chapter, and 12 Phil has alluded to this, and so I think there 13 are implications for chapter three. There are 14 things that should be folded into chapter two 15 on the relationship between monitoring 16 measurement and implications for the slopes. 17 The key points for the letter, I 18 think maybe that's something we could discuss 19 is what really are the key things that should 20 come up to the level of the letter to the 21 administrator? And then are there things here 22 that are really critical for the next draft of

### 202-234-4433 Neal R. Gross & Co., Inc. Page 116 1 the ISA, so I'll open it to some discussion. 2 Michael? 3 DR. KOSNETT: Yes. I thought what 4 Phil did was very good, but I wanted to, I 5 realize I wanted to add one, or suggest the 6 addition of one, additional thing to perhaps 7 2A, which is that we should ask EPA, you know, 8 doing all this, looking at the issues about 9 all the different slopes, to provide a 10 critique that ultimately identifies the slope 11 that would be most appropriate to use in this 12 assessment. And as Ian pointed out, they've 13 already used the slope in the past models, but 14 someone who's reading this, without knowing 15 which one they have used, wouldn't know. So 16 I think they should just take it another step 17 forward in saying, okay, we have these 18 different slopes, this is their fidelity to 19 the empiric data, like you've said, but just 20 another sentence in that saying, based on a 21 critical analysis of these issues, identify 22 the values which are most scientifically

### 202-234-4433 Neal R. Gross & Co., Inc. Page 117 1 justified for risk assessment or for one they 2 should look and do a sensitivity and look at 3 a range of ones. 4 DR. GOODRUM: I guess my reaction 5 to that is do we, as a science body here, 6 really want to recommend that EPA isolate one 7 of the slope estimates as being the best, 8 understanding that maybe they have already. 9 If they have and that was in there, I'm not 10 sure I'd be comfortable with that without 11 really understanding the basis for that 12 selection. So I wouldn't want our comment to 13 give the impression that we're just asking the 14 EPA to document a slope factor that is among 15 the table. It would really need some solid 16 discussion and rationale for why. 17 DR. KOSNETT: I think, ultimately, 18 I think they might say that, historically, in 19 the historical development of air quality 20 standard, in the last revision they used this, 21 and that whether they still believe that is 22 the best to use and decide to justify it

### 202-234-4433 Neal R. Gross & Co., Inc. Page 118 1 scientifically. 2 DR. GOODRUM: I guess why I'm 3 uncomfortable with it is I'm not sure that I 4 agree that a single slope factor is 5 appropriate in this context.

6 DR. KOSNETT: And I'm not 7 disagreeing with that. 8 DR. GOODRUM: I know you're not. 9 I know you're not. That's why I'm

10 uncomfortable. 11 DR. FREY: It would seem like for 12 the integrated science assessment it would be 13 appropriate for a critique and maybe some 14 discussion of things like the central tendency 15 or range of plausible slope factors where the 16 evidence is stronger or the study was 17 conducted more rigorously or whatever the case 18 may be. I think in the REA, which will be 19 part of the policy assessment, the ISA should, 20 I think, provide a foundation that when the 21 choices are made in the REA it could be 22 referenced to the ISA that, well, this slope

### 202-234-4433 Neal R. Gross & Co., Inc. Page 119 1 was chosen as the best estimate, to the extent 2 there's an uncertainty analysis, whether it's 3 qualitative or quantitative, it could refer 4 back to information given in the ISA. So I 5 don't know that the ISA actually needs to be 6 so definitive on saying this is the -- unless 7 there really is, I think, a strong case for

8 that. 9 DR. KOSNETT: Yes, I'm fine with 10 that. The concern I had is, you know, they 11 say, well, here's a table and they have 12 different values. But then I was thinking, 13 well, which do you like and which do you don't 14 like for various reasons? I just think that 15 I would encourage them to take that next step. 16 DR. GOODRUM: Yes, I hear what 17 you're saying. If they already have kind of 18 considered that, it would be good to document 19 their thinking process. 20 DR. FREY: Okay. We have some 21 other panelists. Dr. Von Lindern and then Dr. 22 Pounds. Did I miss anyone? And Rich Poirot.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 120 1 DR. VON LINDERN: Well, I think 2 you came to the same conclusion I was 3 suggesting. The agency already has in both 4 promulgations in the 70s and again last year 5 picked a slope. It's just a matter of 6 reporting that. They really don't have to say 7 if it's the best one again or not, but they 8 have used one. I think that would be valuable 9 information. 10 I just had one other comment that 11 goes back to Dr. Hopke's earlier description 12 of the importance of particle size. That 13 should probably be repeated in this chapter, 14 and my own opinion is every particle size is 15 important because the smallest ones are, 16 there's those that stay in the lungs, there's 17 those that catch in the mucous and go into the 18 gut, there's those that come back out and land 19 in the dust and they're picked up on the 20 hands, and those that aren't picked up on the 21 hands stay in the soil waiting for a chance to 22 get them later. So that's why we look at TSP,

### 202-234-4433 Neal R. Gross & Co., Inc. Page 121 1 and that's important, but that's the exposure 2 that we're trying to cover and that should be 3 in this chapter, I think, as well as in 4 chapter three. 5 DR. FREY: Okay. So, Phil, I 6 assume you're making notes on -- okay. Joel? 7 DR. POUNDS: I suggest that we 8 carry the comments on consistency or apparent 9 contradictions up to the level of the 10 document. So the EPA has nicely improved the 11 cross references from one chapter to another, 12 and, as I looked at -- so we have the same, in 13 some instances, the same papers being reviewed 14 for different purposes in different chapters 15 by different authors. And I think that

16 whenever there's a cross reference for 17 important numbers, they should have someone 18 look at those to make sure that the message 19 and the data and the interpretation is 20 consistent. We found cases within chapter 21 four, in between chapter four and chapter five 22 which were not consistent or were somewhat

### 202-234-4433 Neal R. Gross & Co., Inc. Page 122 1 muddled. 2 MR. POIROT: Well, I was just 3 thinking that on item 2B, you talk about 4 comment on the importance of measurement 5 errors associated with historical lead TSP 6 measurements, the measurement errors relate to 7 the extent to which larger particles have been 8 excluded by the TSP methodology. We're 9 talking about, almost exclusively, particles 10 with greater than ten and on up, throughout as 11 large as you want to count them. But whatever 12 those errors were historically, they're 13 possibly as likely to be as large or probably 14 larger now if that's the kind of error you're 15 talking about because, historically, the lead 16 air concentrations were more dominated by the 17 gasoline combustion and fine particle lead 18 data. So my suggestion would be to just 19 reword that and, instead of talking about 20 measurement errors, refer to it as the 21 particle size characteristics of current and 22 historical TSP measurements, which I think

### 202-234-4433 Neal R. Gross & Co., Inc. Page 123 1 captures the same point. 2 DR. FREY: Okay, good. Any other 3 comments? We have a minute and 30 seconds 4 left on this charge question. Okay. I don't 5 know. Phil, do you want to try to offer any 6 thoughts on what are the most important points 7 for the letter? And this can be -- we don't 8 have to have a final answer today. 9 DR. GOODRUM: I think probably 10 focusing on the theme of needing more 11 synthesis, and then we can provide some 12 examples of that in the letter. But if we 13 have to boil it down to one paragraph for this 14 particular chapter, it would be, you know, our 15 suggestions to better synthesize the data. 16 DR. FREY: Okay. All right. 17 Well, in the interest of time, let's go on to 18 chapter five. And, Susan, could you guide us 19 through? 20 DR. KORRICK: Yes, sure. So I was 21 trying to sort of pick what I thought were 22 highlights of people's comments in yesterday's

### 202-234-4433 Neal R. Gross & Co., Inc. Page 124 1 discussion, so I apologize to others if I've 2 left out something that you think is a 3 priority, and I'm sure there are other things 4 we could add. But in sort of the big picture 5 sense, I wanted to first, up-front, 6 acknowledge areas where we thought chapter 7 five was improved, and I know there was some 8 disagreement about the group, so you all 9 should let me know if you feel this is a 10 reasonable consensus representation. 11 There were improvements in terms 12 of integration between epidemiology and 13 toxicology literature. There was improvements 14 in terms of adding a section in the nervous 15 system effects outcome regarding public health 16 significance, which was a helpful and 17 informative section. And there was good 18 consistency in acknowledging that contemporary 19 blood lead levels in adults and older children 20 do not necessarily account for observed health 21 effects because of past likely higher 22 exposures.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 125 1 So those were kind of the areas 2 where I think most of us were in agreement 3 about the improvements that have been made 4 between drafts. And then I think that, in 5 addition, for some health outcomes, 6 particularly childhood IQ, adult nervous 7 system effects, blood pressure, and 8 cardiovascular outcomes in general, the 9 critical analysis of the literature and 10 assessment of causality was done well. Again, 11 this is an area where I want to make sure 12 everybody feels that's a reasonable consensus

13 statement. 14 But for a number of other key 15 health outcomes, there were limitations that 16 we were concerned about. And so I just tried 17 to come up with a relatively short list 18 summarizing some of the key limitations, 19 realizing that there were a lot more specifics 20 that we talked about as a group. Again, 21 anyone who wants to add to how to prioritize 22 this, that would be great.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 126 1 So I think some of the more 2 fundamental ones were that the critical 3 assessment of each study reviewed for a given 4 health outcome was not done in a very measured 5 or transparent way. There was not a 6 consistent approach to looking at each study 7 and determining whether results were credible 8 based on design or concerns about residual 9 confounding, and there wasn't a good system 10 for distinguishing among studies in terms of 11 their likely robustness.

12 There was also a related lack of 13 transparency regarding causal determination. 14 So, again, there was not, for a number of 15 health outcomes, a very balanced analysis of 16 the strengths and weaknesses of the literature 17 that contributed to conclusions and then the 18 nature of how those conclusions were drawn 19 using sort of causal determination criteria 20 which are nicely outlined in the preface to 21 the document. So there's no explicit 22 description of application of those criteria

### 202-234-4433 Neal R. Gross & Co., Inc. Page 127 1 to causal determination. 2 And then I think some of the more 3 specific areas that seem to come up repeatedly 4 yesterday and in people's comments were lack 5 of clarity in both describing terminology and 6 also the conceptualization or understanding of 7 behavioral outcomes. And this was 8 particularly true with sort of confusion 9 between formal psychometric tests of attention 10 versus clinical ADHD and also true in terms of 11 trying to establish homologies between animal 12 testing protocols and human behavioral tests 13 where, in some cases, the homologies were 14 appropriate and others they weren't. 15 And then I think we didn't talk 16 about this a lot, but I think there was, in an 17 effort to be more circumspect about the role 18 of blood lead in determining health effects in 19 adults and older children, I think some of the 20 clarity regarding exposure levels at which 21 observed effects were likely to occur got lost 22 in this draft. And then I think there was an

### 202-234-4433 Neal R. Gross & Co., Inc. Page 128 1 overall appearance, which came up a couple of 2 times either in written or spoken comments, of 3 sort of a confirmation bias in the document, 4 if you will, where studies of associations 5 were not mentioned, and notable among these 6 included studies that Gail Wasserman and Rich 7 Canfield have done looking at attentional and 8 behavioral problems in kids and childhood lead

9 levels. 10 So then I sort of skipped, but 11 some examples of some of these limitations 12 were that, in particular we talked a lot about 13 the strength of the literature with childhood 14 cognition versus childhood behavior are 15 treated in the document as if they're 16 comparable, but I think the consensus is

17 that's not the case and that the text needs to 18 do a more critical review of the childhood 19 behavioral literature and a more tempered 20 conclusion would result from that. And, 21 similarly, for the review of renal outcomes, 22 the review was not balanced in terms of

### 202-234-4433 Neal R. Gross & Co., Inc. Page 129 1 identifying a number of key uncertainties in 2 our understanding of the relation of lead with 3 renal outcomes, and I've listed some of those. 4 So I think those are what I sort 5 of identified as sort of major themes, but, 6 again, I realize I've not talked about 7 everything we went over yesterday. So I 8 welcome input. 9 DR. FREY: Yes, that was a nice 10 summary. I guess, looking at the charge 11 question, one is, the very beginning is 12 comment on the extent to which the revised 13 discussion of the evidence and the causal 14 determinations accurately reflect the weight 15 of evidence. And I realize there were a 16 number of concerns about the transparency of 17 the determinations, but I wonder are there any 18 fundamental disagreements with the conclusions 19 reached as far as weight of evidence or 20 causality and are those sufficiently reflected 21 in the response? 22 DR. KORRICK: Yes. I mean, I

### 202-234-4433 Neal R. Gross & Co., Inc. Page 130 1 think that's a fair comment. I didn't 2 organize these very well for looking at the 3 specific charge questions, but I think that 4 the short answer is that for some of the key 5 health outcomes the discussion of the evidence 6 and causal determination was not adequate. 7 And those specific outcomes include behavior 8 and renal effects, and I think, to some 9 extent, in the immunology section, which we 10 didn't talk about as much yesterday. So I can 11 sort of reconfigure this a little bit to be 12 more explicit about that. 13 DR. FREY: Yes. And I guess is an 14 implication of what you just said that because 15 the discussion wasn't transparent enough there 16 isn't actually sufficient information to 17 determine whether the conclusions accurately 18 reflect the weight of evidence, or is it 19 possible to comment on whether EPA's 20 conclusions about causality weight of evidence 21 were reasonable given the knowledge basis in 22 the literature?

### 202-234-4433 Neal R. Gross & Co., Inc. Page 131 1 DR. KORRICK: Yes. I mean, I 2 think it's a little bit of both, so I think 3 sometimes they came to the wrong conclusion 4 because they didn't look at things in a 5 measured, balanced way. And sometimes they 6 may have come to the right conclusion, but 7 it's not clear how they got there. But, I 8 mean, I think the more egregious oversight is 9 to have come to the wrong conclusion and, 10 based on the panel's understanding of the 11 literature, the wrong conclusion without us 12 knowing why they came to that conclusion. 13 DR. FREY: Okay. I know, Michael, 14 you want to say something and then Rick. 15 DR. KOSNETT: I think a key 16 concern is that a lot of times the way that 17 the causal determination is expressed is 18 ambiguous. You know, like statements like the 19 weight of the evidence strongly supports the 20 association. Is it a causal association or 21 not? Just epidemiology doesn't necessarily 22 provide an answer with respect to causation

### 202-234-4433 Neal R. Gross & Co., Inc. Page 132 1 just because there's a strong association. 2 There's confounding, and if it doesn't have 3 biological plausibility or if there's 4 inconsistent findings. 5 So I think, in what I wrote in the 6 beginning for the comments on chapter two on 7 the first bullet really speaks to this in a 8 similar way on page two. I think it really 9 applies to five because it's -- so I think, I 10 don't know, you know, there's going to 11 definitely be overlap, Chris, between the 12 comments in two -- the comments on chapter two 13 and the comments on chapter, all the chapters. 14 But this particularly speaks to chapter five. 15 DR. FREY: Oh, yes, absolutely. 16 Well, I guess what I'm getting at is in the 17 response to the charge questions for chapter 18 five, to the extent that we as a panel don't

19 feel we're able to comment on whether EPA 20 reached the right conclusion because of the 21 lack of transparency, I guess it could be 22 possible that, as EPA goes through that

### 202-234-4433 Neal R. Gross & Co., Inc. Page 133 1 process of reviewing the literature in a more 2 systematic way as outlined in the chapter two 3 comment and also as alluded to here, that 4 maybe they might reach different conclusions 5 than they currently have. I just wonder to

6 what extent we want to or should address that 7 in the chapter five response to the charge 8 question. 9 DR. KOSNETT: Well, you raise 10 another key point is that should we weigh in 11 based on our reading and our knowledge of what 12 is out there about what we think with respect 13 to all these end points and a causal 14 determination? I mean, I would be prepared to 15 do that. Do you want me to discuss that now

16 further? 17 DR. FREY: We don't have time for 18 a detailed discussion. I guess if it's a 19 consensus. Part of the challenge is that if 20 we were to go that direction we really should 21 discuss it in the public as a panel. But 22 maybe the more general point that we just

### 202-234-4433 Neal R. Gross & Co., Inc. Page 134 1 alluded to that, given the lack of clarity, it 2 is possible that different determinations 3 could be reached after a revision of the ISA 4 and that, in a sense, giving EPA the latitude 5 to come to more appropriate determinations 6 after they've looked at the literature is what 7 I'm thinking is what we could say here. 8 DR. KOSNETT: How about if we said 9 this? I think that we agree, in line with 10 what we've said the last time and here, that 11 we believe that a causal determination, a 12 positive causal determination can be made for 13 low-level lead exposure and cognitive 14 decrements in children. 15 And I think that, if anyone 16 disagrees, we think that there is a positive 17 causal determination for lead and hypertension 18 and adverse cardiovascular effects, although 19 the lower end of the dose for which that's 20 associated can't yet be determined because the 21 studies that have demonstrated it have been 22 done in people who are getting heart disease

### 202-234-4433 Neal R. Gross & Co., Inc. Page 135 1 and things, which are older people whose blood 2 lead was generally in the range of 10 to 25. 3 So we think that long-term chronic exposure in 4 the range of 10 to 25 is sufficient to cause 5 high blood pressure and cardiovascular end 6 points. It's possible it could be at lower 7 levels, but we don't know yet. 8 And, personally, and I don't know 9 if anyone disagrees, but for the other end 10 points, behavioral effects, and, you know, the 11 evidence is less mature for the other end 12 points. And I don't know -- 13 DR. FREY: Right, which we did 14 talk about yesterday, and I -- 15 DR. KOSNETT: Does anyone feel 16 strongly about -- 17 DR. FREY: Well, let me do this -- 18 DR. KOSNETT: -- or does anyone 19 feel differently from what I'm saying? 20 DR. FREY: Yes. I think we did 21 discuss that yesterday. Let me, I know Rick 22 is patiently waiting, and then Deborah, and

### 202-234-4433 Neal R. Gross & Co., Inc. Page 136 1 then Gail. 2 DR. CANFIELD: So I'm in general 3 agreement with what Michael is saying. But I 4 wanted to make a point about the lack of 5 transparency and the evaluation of the 6 evidence, which is that the causal 7 determination sort of framework that's laid 8 out in the preamble is quite reasonable, and 9 much of the problem in chapter five is that 10 it's not consistently applied in every 11 section. And I have the sense that EPA knows 12 that, you know, there's still work to do. 13 There's places where the sections 14 that are really well done and clearly follow 15 the framework, and that's helpful. And I 16 think in some cases the statement of an 17 association is not intended to be the sole 18 evidence for causal determination but, rather, 19 it's along the way. That's just one piece of 20 it, and then they're moving on to mechanism 21 and et cetera. But that can get lost if it's 22 not as explicit. Obviously, it's not getting

### 202-234-4433 Neal R. Gross & Co., Inc. Page 137 1 through all the time. 2 With respect to whether the 3 conclusions are -- whether I would agree with 4 the conclusions overall, at the macro level, 5 if you look at the areas in the table, I would 6 probably move a few things from causal to 7 likely causal. That's sort of where I'm at. 8 And the basis for that is that there are a 9 number of areas in the text where there might 10 be a decision that's not well articulated or 11 something. For example, with the Bailey 12 scores. Does that add evidence or not? I 13 think it maybe doesn't, but that's a long 14 complicated thing that will be in individual 15 comments about that. So, anyway, so that's

16 where I'm at.

17 DR. FREY: Great. Deborah? 18 DR. CORY-SLECHTA: Well, I wanted 19 to follow up on the behavior and the 20 attention. Rick and I talked a little bit 21 about this yesterday. So, in a way, it's 22 covered in a very superficial way as part of

### 202-234-4433 Neal R. Gross & Co., Inc. Page 138 1 the problem. 2 So I would say that, from my point 3 of view, there may be and I think there are 4 effects on attention-related behavior. But 5 apples are being compared to oranges. We 6 don't know what domains of attention. I think 7 the document needs some expertise in attention 8 deficit, an introduction of, you know, this is 9 a construct that includes the following, and 10 some real explicit comparisons of measures of 11 the same behavioral function. Were they, in 12 fact, comparable? Are they not? And that's 13 not in there. We can't call attention a 14 single thing. That's part of the problem. 15 So I would say, in contrast to 16 Michael saying, well, maybe the evidence is, 17 you know, less compelling, I'm not sure I even 18 know. And maybe when they do this analysis, 19 we'll find out. I mean, there have been 20 studies published saying impulsivity is more 21 affected than sustained attention. Maybe 22 we'll actually find that out, which would be

### 202-234-4433 Neal R. Gross & Co., Inc. Page 139 1 an important from an intervention point of 2 view for sure. So I think they really need 3 some serious expertise in attention to go 4 through those data sets and present that 5 information. 6 DR. FREY: Okay. Well, Gail and 7 then Michael. 8 DR. WASSERMAN: I agree with what 9 Deb said, absolutely, that we need to better 10 characterize what we're talking about. It's 11 really impossible, even for someone who's 12 reasonably familiar with the literature, to 13 evaluate based on what's there, so you'd like 14 to see the pulleys and levers underneath the 15 decisions and some construct definition. 16 This is a disorder, it's based 17 upon these three pieces of information, this 18 is how we measure it, because I think this is 19 really very important. There's a lot of 20 individual and policy related decisions that 21 are going to follow from that piece in 22 particular about services for kids, so we

### 202-234-4433 Neal R. Gross & Co., Inc. Page 140 1 really need to do it carefully and well. 2 DR. FREY: Okay. Michael?

3 DR. KOSNETT: Yes. And I don't 4 know if we should say that, I mean, Susan, we 5 can work on the wording of this, but, you 6 know, when you say like a balanced approach of 7 the strength and the weaknesses, part of that 8 includes the fact that some of the studies are 9 inconsistent where, perhaps, I think sometimes 10 EPA, the author in that section said the 11 studies consistently show this, you know. And 12 really we would take issue with that. They 13 don't consistently show that. So that kind of

14 stuff. 15 DR. FREY: I guess as a general 16 comment for especially chapter five, I expect 17 that, since we had a lot of discussion on 18 chapter five yesterday and it seems like this 19 is really the kind of sort of lightning rod 20 for the need for seeing another version of the 21 ISA, that I would not be surprised and I would 22 expect that the response to the chapter five

### 202-234-4433 Neal R. Gross & Co., Inc. Page 141 1 charge questions might be more lengthy than 2 for the other chapters and that would be 3 appropriate. So don't feel that it needs to 4 be constrained to one or two pages. I mean, 5 if you find that you need four or five pages, 6 six pages, you know, it is what it is. Rick? 7 DR. CANFIELD: So along those 8 lines, I've been trying to decide how best to 9 get the feedback on the table for the revision 10 because there is expertise that's needed and 11 my document of individual comments is running 12 many, many pages, and they're important and 13 it's extremely complicated because, you know, 14 tiny little changes in one aspect of a study 15 means that they're measuring something else, 16 even though it looks like they're measuring 17 the same thing, or some authors may call 18 something attention and they're talking about 19 one type of attention and another calls it 20 attention -- so that takes a lot of work. 21 So the question is does the 22 expertise that, in a sense, I'm hoping to help

### 202-234-4433 Neal R. Gross & Co., Inc. Page 142 1 provide in my individual comments, is that the 2 only way of adding some specialty knowledge in 3 some of these areas to the revision of the 4 document or are there outside sources that EPA 5 can consult? I didn't see, for example, 6 clinical psychologist on the list of 7 contributors, and I think Debbie and I didn't 8 see an animal person. Those perspectives from 9 those sub-disciplines could be helpful in a 10 more general sense in understanding the

11 nuances of the data. 12 DR. FREY: Okay. Well, I'll give 13 you my thoughts, and then Vanessa might, since 14 she's more experienced across many panels, may 15 be able to add to this. 16 But I think, you know, it's often 17 the case that, in responding to a charge 18 question, there's more detail in an individual 19 member's comment that is really critical to 20 that response and, at the same time, we don't 21 want to have a 50-page response to the charge 22 question.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 143 1 So in practice, you know, I think 2 there are many examples where the charge 3 question does refer to, you know, for more 4 details see the individual comments of, you 5 know, Dr. Canfield. It would be good, though, 6 to highlight, you know, I think what you're 7 saying, for example, is the definitions are 8 important and the methods for doing 9 measurements are important and so on. 10 So just kind of a high-level 11 summary of what it is that's in those 12 comments, a high-level summary in the charge 13 question comment of what's in the individual 14 member comment so that it really is clear that 15 that provides a lot of value added. 16 And we talked yesterday about we 17 always have this discussion about when EPA 18 makes a revision what do they tell us about 19 what they revised, and, of course, we want 20 them to ideally give us a response how they 21 responded to the charge question. And I did 22 mention yesterday, you know, I mentioned to

### 202-234-4433 Neal R. Gross & Co., Inc. Page 144 1 Dr. Vandenberg, of course, if that charge 2 question refers to an individual member's 3 comment, we're also interested in how they 4 dealt with that information. So that's my 5 perspective on it. 6 I think on the second point, as 7 far as should EPA engage other experts in 8 revising the ISA, I'm not sure that, and this 9 is where I might ask Vanessa for her input, I 10 don't know how far we go as a CASAC in saying 11 that. I think it certainly would be 12 legitimate to say that, in this area, you 13 know, that depends on disciplinary expertise 14 in these areas and that seems to be absent 15 from the ISA and that should be incorporated 16 and then probably leave it to EPA as to how 17 they're going to engage that expertise. 18 But, Vanessa, do you want to add 19 anything? 20 DR. VU: Well, first, I agree with 21 you, Chris, in terms of your guidance to the 22 panel how you reference your consensus

### 202-234-4433 Neal R. Gross & Co., Inc. Page 145 1 response since they refer to see more detailed 2 comments from the panelists. With regard to 3 expertise needs, you know, CASAC could always 4 say that the ISA should be benefit from 5 additional expertise in these areas and it's 6 how the agency is going to get those expertise 7 as the agency's discretion because the point 8 you're trying to make was the different 9 experts needed to define these different areas 10 of behavior and ADHD. So those are the points 11 you made, and so you're just highlighting the

12 letter. 13 DR. FREY: Okay. Gail and then

14 Susan. 15 DR. WASSERMAN: But I think we 16 would ask for some more guidance in the level 17 of detail we provide. I mean, I could write 18 three pages on the definition of ADHD and what 19 I know about how we assess it. And I'm not 20 sure this is the right way to do it or if 21 that's a waste of my time. 22 I mean, I don't know if I should

### 202-234-4433 Neal R. Gross & Co., Inc. Page 146 1 be bulleting this is a problem, this is a 2 problem, this is a problem, or whether I 3 should be providing the answers to the problem 4 or whether you're going to go find that in 5 some other route. So if you could just give 6 us some guidance about how much help you want 7 on these things, that would save me from being

8 redundant. 9 DR. FREY: Well, at one level, I 10 think, to the extent that this has already 11 been written in other references, then I think 12 it would be legitimate to say EPA should 13 review the definition in Smith et al. or 14 whatever. If you feel like that's not there 15 and that this is really a synthesis that isn't 16 in the literature and you're so compelled and 17 motivated and willing to write it up, I think 18 that's great. I think if you're getting to a 19 three-page definition, for example, that that 20 probably should be in the individual member 21 comments and then in the charge question to 22 say there are many nuances to this definition

### 202-234-4433 Neal R. Gross & Co., Inc. Page 147 1 and as further developed in Dr. Wasserman's 2 individual response. 3 So I think if things are getting 4 to be lengthy that I would sort of think of 5 them more like an appendix, in which case that 6 could be in the individual member comments, 7 and try to keep the response to the charge 8 question brief but, you know, if it needs to 9 be several pages then that's fine. But if 10 it's getting bogged down on a detail, not that 11 it's not a critically important detail, but 12 that could go in the individual. That would 13 be my suggestion. But, of course, it's a 14 matter of judgment. 15 Do you want to add anything,

16 Vanessa? 17 DR. VU: Well, you've been asked 18 to provide review comments on the draft ISA, 19 so if you highlight key points that the agency 20 needs to further differentiate different terms 21 and how the different experts define whatever, 22 as Chris said, if you can provide references

### 202-234-4433 Neal R. Gross & Co., Inc. Page 148 1 or you can provide some general guidance, 2 that's fine. But you're not doing the work 3 for EPA. That's all I'm asking you. 4 DR. FREY: Okay. Anything else on 5 chapter five? We went a little long on that, 6 but I think probably for good reasons. We can 7 come back and, as we go through the other 8 chapters, you know, we want to also do 9 synthesis. 10 I guess maybe I'll just throw this 11 out. Are there synthesis implications here 12 for other chapters? So how does chapter five 13 interact with chapter seven, chapter six, 14 chapter four, chapter three? And then, 15 clearly, that would fold into chapter two. 16 Does anyone have any burning thoughts on that? 17 And if not, we can come back to that when we 18 talk about chapter two. 19 Let's go on then to chapter six, 20 and, Dr. Cory-Slechta, if you could guide us 21 through that. And if we could have chapter 22 six on the screen, that would be great. And

### 202-234-4433 Neal R. Gross & Co., Inc. Page 149 1 while we're doing that, let me just pause and 2 see if any of the panelists on the phone, is 3 there anything you want to add that you 4 haven't had a chance to, either Michael or

5 Sean? 6 DR. WEITZMAN: No, not at the 7 moment. Thank you. 8 DR. HAYS: Likewise, no comments. 9 DR. FREY: Okay, great. All 10 right. 11 DR. CORY-SLECHTA: Okay. The two 12 charge questions are up there: commenting on 13 the adequacy of the revisions to clarify the 14 consideration of potential at-risk 15 populations, recommend any revisions to 16 improve those, and comment on whether the 17 designation of some factors as having limited 18 evidence adequately reflects the knowledge

19 base. 20 As I've listed in the first two 21 bullets, I think, in general, the group felt 22 that the revision certainly better captures

### 202-234-4433 Neal R. Gross & Co., Inc. Page 150 1 the intricacies associated with at-risk 2 populations and that the reorganization of the 3 chapter in to related factors also made it 4 more cohesive and better integrated and the 5 fact that some factors were defined as having 6 limited evidence to support them in terms of 7 the strength of available evidence was also 8 adequate, so that explicitly relates to the 9 charge questions. 10 We did mention, and we got a 11 little bit into some other chapters as we went 12 through this discussion, some issues which we 13 said were still remaining and were brought up 14 by a couple of us. One was understanding, if 15 you will, the magnitude of the impacts of 16 these different risk factors. Right now, it's 17 very difficult to get any sense of whether 18 some are much more potent than others, which 19 we felt were important for risk assessment 20 policy, et cetera. 21 There were comments here, at least 22 in chapter five and in individual comments,

### 202-234-4433 Neal R. Gross & Co., Inc. Page 151 1 about comparing maternal self esteem directly 2 to stress imposed in rat models. And what I 3 included in there was that if you have that 4 kind of homology it should be limited or at 5 least qualified in terms of how you present 6 it. There were concerns about interpretation 7 of one particular study, which I mentioned. 8 And the other issue that came up 9 was the fluoride co-exposure with lead, and 10 Rick did send out an abstract that was 11 published. And so I've simply made the 12 comment there that if, in fact, there is this 13 important interaction, which was mentioned in 14 chapter two but never addressed in chapter 15 six, it should be in both. 16 So I didn't get -- I got some 17 comments back from Gail last night, but I 18 think other people didn't have a chance. So 19 if they have comments, now would be a good 20 time. But that was what I picked up from our 21 discussion. 22 DR. FREY: Okay. I just wanted to

### 202-234-4433 Neal R. Gross & Co., Inc. Page 152 1 clarify the text at the bottom of page ten and 2 on to page 11, that is the abstract of that 3 paper.

4 DR. CORY-SLECHTA: Yes. That's 5 just the abstract which I forwarded to make 6 sure people could see it. It doesn't, 7 obviously, need to be in there. 8 DR. FREY: Right. Okay, good. 9 Yes, Michael? 10 DR. KOSNETT: With respect to that 11 fluoridation issue, you know, I have not yet 12 read this article. I think we need to be 13 careful, maybe even asking -- I don't know if 14 it's a good quality article, and so I don't 15 even know if -- I don't necessarily think what 16 we want to do is say, yes, you should keep 17 that sentence and add the sentence in chapter 18 two. I don't think you mean this but -- 19 DR. CORY-SLECHTA: I think what I 20 meant, and I can revise the wording, was that 21 they should look at it and come to some 22 conclusion. That's what I'm saying. I didn't

### 202-234-4433 Neal R. Gross & Co., Inc. Page 153 1 read it either, and I'm not going to make a 2 judgment on it one way or another. I think 3 it's their role to do that. So there's the 4 inconsistency between chapter two and chapter 5 six, and I think they need to come to some 6 deliberation on it. 7 DR. KOSNETT: See, I think we all 8 agree that there was a very provocative 9 statement in chapter two that fluoridation can 10 lead to elevated blood lead concentrations or 11 blood lead exposure in children. That's an 12 incredibly provocative statement. That would 13 be on the news, I'm serious, if that gets in 14 this document, if that's EPA's position. Even 15 if they think it -- any credence they give it 16 will get picked up on.

17 I don't even know that we should 18 go there unless there's a good scientific 19 basis for it, so I basically said you only 20 cited one in vitro study up until now, so take 21 it out because that one in vitro study about 22 how much lead leaches out of brass faucets in

### 202-234-4433 Neal R. Gross & Co., Inc. Page 154 1 a beaker of water is not adequate to say that 2 lead fluoridation causes lead from pipes. 3 So I would, I felt that the whole 4 issue, and I haven't reviewed it in detail, 5 but I know other people who have and I've 6 spoken to and they don't feel that the 7 evidence currently would suggest that in a 8 document like this on lead exposure that 9 fluoridation be even highlighted as a risk. 10 I think that's so preliminary. 11 DR. FREY: Okay. I saw a bunch of 12 hands go up, and I don't know the order. But 13 Deborah and then Phil and then Michael. 14 DR. CORY-SLECHTA: I disagree with 15 taking it out. This is in vivo data in 16 humans, and I think are you just going to 17 ignore it? I think people need to look at it 18 and come to some kind of conclusion. I don't 19 think that ignoring it is the way to go, and 20 I think that's what you're suggesting 21 essentially. You've already assumed that this 22 is a bad paper, that these findings aren't

### 202-234-4433 Neal R. Gross & Co., Inc. Page 155 1 relevant, and I don't think it's correct 2 necessarily to do that. I think it's up to 3 them to look at it -- 4 DR. HOPKE: You need somebody with 5 some good chemical background reading that 6 paper. There are some issues.

7 DR. CORY-SLECHTA: And some human 8 studies and human expertise. 9 DR. KOSNETT: All right. Fair 10 enough, Debbie. I haven't read it, so it's 11 not fair for me to say not to include it. But 12 I am -- I'll read it and I'll tell you what I 13 think. Maybe we'll comment on it. But I'm 14 just saying it's such a controversial and hot 15 button area that, before it's highlighted, a 16 lot of care should be given to it. 17 DR. CORY-SLECHTA: Right. I'm not 18 saying to highlight it. I'm saying they 19 should look at it and maybe they come to the 20 conclusion that, you know, it isn't 21 sufficiently compelling to come to that 22 conclusion. But they need to acknowledge that

### 202-234-4433 Neal R. Gross & Co., Inc. Page 156 1 it's out there for sure. 2 DR. KOSNETT: It may just be this 3 one article, right? 4 DR. FREY: I think, if I 5 understand the discussion, in chapter six it 6 seems appropriate to cite this and to have 7 some critique of it. And I guess it's not so 8 clear right now if the weight of evidence 9 related to this is strong enough that it 10 really merits being in chapter two. And so I 11 think that's the question. 12 DR. KOSNETT: Okay. 13 DR. FREY: And I think, I'm not an 14 expert on lead and drinking water, but I kind 15 of asked my colleague, you know, does 16 fluoridation enhance leaching of lead in 17 drinking water, and he came back with a very 18 limited answer. So my sense is, I'm not an 19 expert, I don't know that this is a big area 20 within the drinking water community. But I 21 think in revising the ISA, EPA could look to 22 see if they find more related to this or if

### 202-234-4433 Neal R. Gross & Co., Inc. Page 157 1 this is supportable or, as Phil alludes to, 2 maybe there's some issues with the chemistry 3 here in terms of the exposure aspects. 4 Okay. Michael? Did I miss 5 somebody? I'm sorry. Was someone else 6 waiting? Michael, go ahead.

7 DR. RABINOWITZ: Dr. Pounds and I 8 were kicking this around a little bit, and I'm 9 told that it may not be just a matter of the 10 fluoride increasing plumbosolvency of the 11 plumbing system. It could be that it's 12 mediated through the bones. That is to say -- 13 well, let me ask a question. Do people with 14 fluorosis have higher or lower blood lead 15 levels than people with fluorosis? Adults, 16 children, whatever. 17 It could be that the fluoride 18 strips the lead or prevents the lead from 19 going into the bone, so it could be something 20 internal rather than exposure mediated. I 21 don't know, but there is a lot of literature 22 out there about fluorosis and blood lead

### 202-234-4433 Neal R. Gross & Co., Inc. Page 158 1 levels. I haven't had a chance to look at it, 2 but there's a fair amount of literature on it. 3 DR. FREY: Well, it seems like 4 that might be a good point to raise for EPA to 5 consider in their revision. Phil, did I skip 6 you? Did you have your hand up? 7 DR. GOODRUM: My point is already

8 made. 9 DR. FREY: Oh, okay, all right. 10 Good. Any other discussion on chapter six? 11 Yes, Rick? 12 DR. CANFIELD: This is a little 13 bit nuanced, but it relates to this issue of 14 homology and self esteem, et cetera. And I 15 just want to try this out with my colleagues 16 here and see if this works for them, which is 17 a typical model for maternal stress in an 18 animal model is restraint stress. And in many 19 models, you would tie restraint stress to 20 learned helplessness and learned helplessness 21 to lower sense of self efficacy and correlated

22 self esteem.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 159 1 So what I tried to do there is 2 make a homology from the restraint of an 3 animal and learned helplessness outcomes based 4 on learning theory, etcetera, and then the 5 notion of a maternal self esteem being related 6 to a lack of self efficacy, which is often 7 found in low income situations. 8 Anyway, so I wanted to try that 9 out because this is where the rubber meets the 10 road on all of our issues with respect to 11 these specific questions. So it's out there. 12 DR. CORY-SLECHTA: You know, I can 13 see those kinds of logic deliberations. They 14 get a little bit far removed. I personally 15 would like to see the actual self esteem 16 measurement because, yes, you can, in fact, 17 have stressors and, in fact, in female 18 offspring they typically do lead to 19 essentially those kinds of outcomes, even in 20 rodent models of anxiety, depression, et

21 cetera. 22 So it would be interesting to see

### 202-234-4433 Neal R. Gross & Co., Inc. Page 160 1 the actual questionnaire and what was actually 2 being measured. It gets into a very 3 complicated business, though, because stress 4 is not stress. So some stress is good, and 5 other stress isn't, and that's where it does 6 get very nuanced. So I think it could be 7 qualified to reflect the possibilities, but, 8 obviously, there's a long way to go at this 9 point.

10 DR. FREY: I don't know who had 11 their hand up first. I'm going to say Susan 12 and then Gail and hope I'm right. 13 DR. KORRICK: Just one, hopefully 14 brief comment. I think this is kind of 15 another example analogous in my mind to the 16 issue of how attentional outcomes are being 17 assessed because I think this is an area that 18 requires a level of expertise that may or may 19 not be currently used for this document, and 20 I suspect that self esteem was Pam Surkan's 21 paper; is that right? Yes. 22 So, you know, my guess is, and I

### 202-234-4433 Neal R. Gross & Co., Inc. Page 161 1 haven't looked at that paper in a long time, 2 this is a really challenging area to review 3 the literature in because authors oftentimes 4 muddle these concepts. I mean, and I don't 5 mean this disrespectfully, but it's just 6 complicated. 7 So stress is probably overused a 8 lot in the epi literature to categorize all 9 sorts of measures. Similarly, ADHD is used 10 too much. And so I think the bottom line is 11 I think this is another area where to really 12 do the kind of subtle, nuanced assessment, a 13 level of expertise that is difficult to come 14 by may be needed. And I think that's a 15 challenge. That's all. 16 DR. WASSERMAN: I think that 17 stress is not always restraint stress. 18 Sometimes it's like food deprivation. I mean, 19 these are very global things with animals. 20 They're also often very global with humans. 21 And just to lay out what exactly, you know, if 22 it's a duck, if it walks like a duck. I'm

### 202-234-4433 Neal R. Gross & Co., Inc. Page 162 1 back to that. Just say what it is, rather 2 than perhaps defaulting to the overarching 3 construct because when we do that too quickly 4 we may miss the nuance. 5 DR. FREY: Okay, good. So, 6 Deborah, will you incorporate this discussion? 7 Excellent. Well, I think we're at a good8 point to move to chapter seven, and also time9 wise we're at a good point to move to chapter 10 seven. So, Roman, could you guide us through

11 that? 12 DR. LANNO: Yes. Thanks, Chris. 13 Our charge question was actually quite broad, 14 so there were not a lot of details we had to 15 respond to there. Our discussion centered 16 around the fact that, you know, there was 17 quite a bit of data added and the organization 18 of each section was nicely changed to 19 incorporate an introductory paragraph that 20 related to previous AQCD documents and then a 21 brief summary was provided in each section to 22 summarize what was discussed there. And it

### 202-234-4433 Neal R. Gross & Co., Inc. Page 163 1 was broken up into the three different 2 environmental categories. So terrestrial, 3 fresh water, marine ecosystem because of the 4 differences in the environmental chemistry of 5 lead in those situations. 6 And our biggest comment was that, 7 although a lot of new information was provided 8 -- maybe I could have bulletized that a bit 9 better, but sorry about that. This is one of 10 those "oh, my God" slides. Okay. 11 I think that the information was 12 not, it needs to be summarized in a way that 13 people can quickly see what it's about and 14 integrated into a meaningful synthesis. I 15 guess if that synthesis idea comes across in 16 chapter five and may make this chapter also a 17 candidate for reevaluation after its revision 18 this time so a third reading. I don't know if 19 the rest of my group concurs with that, but I 20 think that if it's going to be synthesized, I 21 think we could look at it as a whole again. 22 So that's, I think, one of our comments.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 164 1 And the additional thing is 2 there's not that much technical evaluation of 3 the data that exists. And by technical, I'll 4 get to that in a second what we really mean by 5 that, but it's kind of defining more clearly 6 what the exposure doses were, what the 7 situations or the environmental conditions of 8 exposure were, and relating that to where at 9 an ecosystem level do these effects, could 10 they potentially occur. 11 And we provided some guidance as 12 to how they might -- so our second part of the 13 charge question there was recommend any 14 revisions to improve the discussion of key 15 information, and that's what we're trying to 16 do. So if we could get a table provided in an 17 appendix that summarize the data from all the 18 additional studies that have been included in 19 this document, that would be a place to start. 20 And then some kind of technical evaluation of 21 that data for each of the studies. In 22 particular, Dr. Allen brought up the subject

### 202-234-4433 Neal R. Gross & Co., Inc. Page 165 1 of that study that looked at I think the 2 effects of endocrine disruption effects in 3 cell culture are very, very low concentrations

4 of lead. 5 And as an example of how you might 6 approach this, I didn't read the paper, but

7 what Dr. Allen related to me was that the 8 study was conducted by taking -- 9 DR. JOHNSON: We have a problem. 10 We have a medical problem. 11 MR. HANLON: We are adjourning the 12 meeting now. We'll be sending an email to the 13 panel members with lists of milestones and 14 action items to follow up. Thank you and the 15 meeting is adjourned. 16 (Whereupon, the above-entitled 17 matter went off the record at 11:58 a.m.)

18

19

20

21

22

### 202-234-4433 Neal R. Gross & Co., Inc. Page 166

A AAMMS 76:4 AARON 1:23 ability 22:13 29:13

44:16 45:1 61:15 61:22 able 17:18 32:19

43:2 67:2 110:2 132:19 142:15 above-entitled 107:4 165:16 absent 144:14 absolute 16:5 42:8

42:15 46:16 47:3 47:12 48:22 absolutely 92:18

93:2 132:15 139:9 absorbed 9:20 absorption 54:14 abstract 151:10 152:2,5 accedence 78:18 acceptable 95:12 accessible 89:19 account70:22 124:20 accurate 59:17 accurately 129:14 130:17 achieve 96:4 achievements 113:22 acids 100:7 acknowledge 124:6 155:22 acknowledging 124:18 Acting 1:24 action 112:12 165:14 activities 87:8 activity 9:15 actual 21:12 24:8 159:15 160:1 add40:14,16 79:19 110:11 113:17 116:5 124:4 125:21 137:12 142:15 144:18 147:15 149:3 152:17 added 143:15 162:17 adding 124:14 142:2 addition78:1 116:6 125:5 additional 8:5 19:2

30:19 32:8 34:4 34:17 36:16 37:10 39:22 60:9 74:11 75:17 77:6 89:17 108:16 116:6 145:5 164:1,18 address 85:4,18 133:6 addressed 36:12

62:4 151:14 addressing 5:3 adequacy 149:13 adequate 69:20 130:6 150:8 154:1 adequately 69:19 149:18 ADHD 127:10 145:10,18 161:9 adjourn 5:10 adjourned 165:15 adjourning 165:11 Adjournment2:19 adjusting 26:20 administrator

76:19 83:20 115:21 administrator's

85:9,10 adult 125:6 adults 9:13 124:19 127:19 157:15 adverse 134:18 advice 64:2,11 advisory 1:1 73:15 aerosol 53:17 affect51:16 aged41:3 agency 1:1 65:18

65:20 66:2,9 120:3 145:6 147:19 agency's 145:7 agenda 3:16 5:22

72:19 ages 63:7 ago 10:6,6 agree 94:13 118:4 134:9 137:3 139:8 144:20 153:8 agreement 106:6 125:2 136:3 agricultural 51:13 ahead 111:19 157:6 aimed 76:10 air 1:1 8:10,18 9:1

9:3,16 10:3,11,18 10:20,21,22 11:20 12:4,11 13:6,10 13:11 14:7,7,10 14:14,18,21 16:4 16:6,9,13 18:11 19:6 23:2,9,13,15 23:18 24:7,13 25:16 26:13,15,17 26:19,22 27:2,11 29:12 30:19 31:8 32:17 37:17 38:6 38:16 40:9 42:1 42:11,16,22 43:4 43:7,12 44:6,11 45:10,12,14 47:17 47:18 48:4,7,10 48:14,16 49:1,16 50:10 60:18 68:13 68:17 69:16 71:4 79:7 85:20 87:20 89:8 91:2 103:16 109:12,19 111:11 112:7,11,15 113:10 117:19 122:16 airport 38:17 56:13 airports 34:21 53:3 54:6 55:15,19 56:2,7 57:1 80:2,7 80:17 air-exposed 19:1

23:12 30:15 air-related 10:13 15:21 17:4 30:12 33:18 37:7,8,12 40:4 47:15 al 106:13 146:13 algorithms 35:18 Allen 1:12,13 52:16

55:11 56:11 57:16 77:9 85:2 89:4 92:8 97:14,21 99:1,19 102:9 105:7,10 106:10 106:18 164:22 165:7 allows 71:12 alluded 115:12 133:3 134:1 alludes 157:1 alternate 11:19

46:20 51:4 alternative47:17 altitude 79:6,12,14 ambient9:1,3,16 10:3,11,13,18,20 10:21,22 11:20 12:4,11 13:6 14:7 14:7,10,14,18,20 16:4,6,9,13 18:11 20:21 24:7,7,21 26:13,15,17,19,22 27:2,10 29:12 31:8 32:17 38:5,6 38:16 44:6 49:16 50:10 51:12 54:2 68:13,17,20 69:16 75:20 76:5,6 87:20 ambiguous 131:18 ameliorated 23:15 amount 158:2 analogous 64:9 160:15 analyses 32:9 74:7 analysis 7:8 12:8 12:14 16:7 17:22 20:7 24:3 26:4,9 29:5 32:20 34:11 36:7,7 37:13 39:12 41:20 43:22 63:4 95:12 116:21 119:2 125:9 126:15 138:18 analytical 75:18 animal 127:11 142:8 158:18 159:3 animals 161:19 answer4:16 22:17

46:7 83:11,12 102:21 123:8 130:4 131:22 156:18 answering 84:18 115:8 answers 88:19 146:3 anthropogenic

8:15 10:8 50:6 anticipated43:3 anxiety 159:20 anybody74:6

96:16 anyway 101:9 137:15 159:8 apart42:22 apologize 107:21 124:1 apparent 114:9 121:8 appear 111:12 appearance 128:1 appears 53:4 appendix 87:13

93:19 147:5 164:17 apples 138:5 application 126:22 applied 136:10 applies 132:9

### 202-234-4433 Neal R. Gross & Co., Inc. Page 167 apportionment

32:6 appreciate 6:6 approach 18:5,7

22:3 39:8,17,20 77:2 85:3 126:6 140:6 165:6 approaches 24:5 approaching43:18 appropriate 106:21 116:11 118:5,13 127:14 134:5 141:3 156:6 appropriately

71:13 APRIL 1:6 AQCD 162:20 AQS 87:12,22 106:17 area 24:15 51:13 125:11 144:12 155:15 156:19 160:17 161:2,11 areas 13:4 21:16,17

29:8 39:21 56:6,9 101:3,6 124:6 125:1 127:3 137:5 137:9 142:3 144:14 145:5,9 argument99:5,6 article 152:12,14 156:3 articulate42:4 articulated 137:10 asked 28:18 46:19 147:17 156:15 asking42:5,21

54:15 84:1 103:5 117:13 148:3 152:13 aspect29:3 31:9

32:20 141:14 aspects 87:15 157:3 assess 145:19 assessed 160:17 assessment2:14

3:19,20 6:13,15 6:18,18,19 7:7,20 7:22 8:2,2,11 9:8 10:1,16 11:16 16:12 18:2,6,15 24:1 26:2 27:20 28:8,13,15 29:4,5 29:10 31:1,10 32:22 34:11,14,20 36:5 40:21 41:1 43:17 45:19 62:20 63:11 64:5,14 65:1,3,15,22 66:4 66:21 67:3,5,9,20 67:22 68:4,11 71:1,10,17 72:14 74:13,18 77:19 81:3 116:12 117:1 118:12,19 125:10 126:3 150:19 161:12 assessments 28:18

31:6 32:12 38:8 38:15 74:12 assignments 38:9 associated 8:7

38:10 47:14 48:22 122:5 134:20 150:1 association 131:20 131:20 132:1 136:17 associations 128:4 assume 39:7 121:6 assumed 19:19

56:20 154:21 assuming 25:1 53:7

56:13 assumption 15:3

54:21 114:17 assumptions 32:14 attached 66:18 attachment 85:10 attention 86:4 127:9 137:20 138:6,7,13,21 139:3 141:18,19 141:20 attentional 128:7 160:16 attention-related 138:4 attentive 78:14 at-risk 149:14 150:1 author 140:10 authors 121:15 141:17 161:3 autoemissions 10:9 available 6:10 31:3

35:20 40:20 81:10 81:12 101:21 103:20 110:8 150:7 average 16:15 18:19 aviation 5:6 36:11

38:2 53:3 68:16 75:13 77:13 79:7 82:19,21 83:3 105:2 aware41:11 71:8

73:21,22 91:6 axis 112:7 a.m 1:9 3:2 107:5,6 165:17 B B 1:8 back4:8 11:17

75:14 80:3 82:9 86:12,20 87:17 88:1 89:7 99:11 105:13 109:9 113:4 119:4 120:11,18 148:7 148:17 151:17 156:17 162:1 background 7:15

7:20 8:9 13:12 21:19 23:8 57:3 68:11 89:8 155:5 bad 154:22 Bailey 137:11 bait96:17 98:19,20 balanced 126:15 128:22 131:5 140:6 base41:4 149:19 based 17:16 55:22

70:12 95:20 106:17 116:20 126:8 131:10 133:11 139:13,16 159:3 basically 21:7

66:14 95:6 153:19 basis 35:14 42:15 117:11 130:21 137:8 153:19 beaker 154:1 beginning 10:16

29:12 49:11 69:7 129:11 132:6 behavior 128:14 130:7 137:19 138:4 145:10 behavioral 127:7 127:12 128:8,19 135:10 138:11 behoove 80:21 believe 30:18 40:7

49:19 66:2 88:4 93:3 117:21 134:11 benefit 145:4 best 18:17 99:5 117:7,22 119:1 120:7 141:8 better 29:16,17

30:11,16 31:2 36:22 37:19 38:1 45:2,17,18,20 47:7 62:9 76:8 97:4 102:14,19 103:3 106:3 110:1 110:3 123:15 139:9 149:22 150:4 163:9 beyond4:18 74:2 106:19 bias 29:2 31:6 33:15 40:2 128:3 biases 31:20 34:16 big 62:19 90:5 101:4,6,8 124:4 156:19 bigger 100:4 biggest 163:6 biokinetic 61:5

62:12 63:14,15 biological 132:3 biomarker 69:9 biometric 16:10,13

22:15 bit25:18 38:3 41:3

41:17 42:19 45:3 45:5 46:13 49:20 54:12 60:22 62:5 67:21 75:8,11 80:4 87:6 88:14 95:2,22 102:3 103:2 105:14 114:4,19 130:11 131:2 137:20 150:11 157:8 158:13 159:14 162:17 163:8 block 86:19 blood 16:11,14 17:8,12,19 22:16 33:2,4,11 42:8,9 42:12,14,16 45:11 45:12 46:15 47:4 47:13 53:2,5 54:4 60:1,11,16 69:8 81:21 103:16 109:20 110:16 111:14 113:20 114:12,12 115:2 124:19 125:7 127:18 135:1,5 153:10,11 157:14 157:22 bloodstream 9:21 Bob 87:2 body 9:20 114:22 115:3 117:5 bogged 7:11 147:10

### 202-234-4433 Neal R. Gross & Co., Inc. Page 168 boil 123:13 bone 16:11 157:19 bones 157:12 bottom 152:1 161:10 bounded48:1 box41:22 boxes 11:4 12:9 14:19 brand41:2 brass 153:22 break 107:2 breath 53:18 brief86:6 91:8 147:8 160:14 162:21 briefed 69:12 briefly 15:9 22:7

57:22 84:13 bring 58:9 70:9

77:4 89:1 109:21 113:13 bringing 113:3 broad49:2 105:8 162:13 broader 20:12 45:7

79:14 98:7 broadly 57:3 78:9

78:20 broken 163:1 brought98:17 114:18 150:13 164:22 brush 105:8 bugging 101:17 bullet 19:16 98:13 132:7 bulleting 146:1 bulletized 163:8 bullets 85:9 98:5 149:21 bunch 63:8 85:8,16 154:11 burden 114:22 115:3 burning 85:21,22

86:1 148:16 business 160:3 button 155:15 C cake 98:3 calculations 43:16

44:1 call 13:8 138:13 141:17 calls 141:19 candidate 163:17 Canfield 1:13 82:5

128:7 136:2 141:7 143:5 158:12 capable 97:5 capacity 73:16 capture 23:16 110:10 captures 123:1 149:22 cardiovascular 125:8 134:18 135:5 care 99:7,19 155:16 careful 152:13 carefully 91:8 140:1 Carolina 1:9 carpeting 31:17

32:3 carry 100:4 121:8 carryover 111:8 CASAC 1:2 64:7

64:21 66:18 75:22 76:3,12,18 85:11 86:21 144:10 145:3 case 16:14 18:7,15 19:13,14,18 20:3 20:14,15 21:5,6 21:12,14 24:6,20 25:5,6,6 28:1 29:20 32:1 34:22 38:12 54:1,19 55:12 56:4 64:3 66:1 90:1 97:9 100:16 101:2 118:17 119:7 128:17 142:17 147:5 cases 121:20 127:13 136:16 catch 120:17 catchall 108:19 categories 21:5

27:7 80:1 163:2 categorize 161:8 category 79:17 causal 126:13,19 127:1 129:13 130:6 131:17,20 133:13 134:11,12 134:17 136:6,18 137:6,7 causality 125:10 129:20 130:20 causation 131:22 cause 10:4 100:15 135:4 causes 154:2 Cavender70:18

88:7,12 106:4,15 cell 165:3 centered 162:15 central 12:16 14:5 18:17 22:20 25:20 33:4,11 44:13 60:7 61:9 118:14 certain 12:21 13:16 14:18 23:15 50:7 60:17 96:2 certainly 22:7 34:2

34:22 36:13 53:22 59:11 62:6 74:15 80:21 100:21 144:11 149:22 certified 70:21 cetera 136:21 150:20 158:14 159:21 Chair 1:12 Chairman 1:9 challenge 19:11 133:19 161:15 challenges 12:13 12:15 19:2 49:15 50:2 51:2 challenging 50:13

62:2 161:2 chance 86:22 120:21 149:4 151:18 158:1 change 12:6 17:8 17:12,13 35:17 42:13 45:6 48:15 50:9,10 52:2 110:16 changed 37:2 40:9 162:18 changes 16:4 31:2

37:21 48:8 49:16 50:21 85:7 111:14 141:14 changing 35:15

47:18 92:15 chapter 68:13,19

69:4 70:2 83:9,17 84:5,6 85:5 86:7 86:12 91:1,2,7 98:15 102:16 103:1,1,7 105:17 105:17,18 107:3 107:16 108:7 109:11 111:9 113:4 115:11,13 115:14 120:13 121:3,4,11,20,21 121:21 123:14,18 124:6 132:6,12,13 132:14,17 133:2,7 136:9 140:16,18 140:22 148:5,12 148:13,13,14,14 148:15,18,19,21 150:3,22 151:14 151:14 152:17 153:4,4,9 156:5 156:10 158:10 162:8,9 163:16,16 chapters 83:14

98:8 105:18,20 107:11,12 108:12 113:5,18 121:14 132:13 141:2 148:8,12 150:11 characteristics 105:3 122:21 characterization

8:6 27:19,22 28:10 34:1 36:18 36:22 37:21 40:11 41:18 characterizations

26:13 characterize 18:20

23:16 29:13 30:15 30:21 33:6 37:10 38:15 45:2 48:20 50:22 139:10 characterized

38:10 characterizing 16:21 24:4 30:4 30:22 33:18 35:21 61:2 69:9 charge4:10,17,21

5:1,3 64:4,10,17 75:14 83:5,8,11 83:12,18 84:13,18 85:4,8 89:13 94:9 104:7 107:13,15 111:19 115:8,10 123:4 129:10 130:3 132:17 133:7 141:1 142:17,21 143:2 143:12,21 144:1 146:21 147:7 149:12 150:9 162:13 164:13 check 80:21 107:17 checking 73:1 chemical 155:5 chemistry 101:11 157:2 163:4 Chicago 20:14 child 17:5,10,15 18:17 19:4 61:11

### 202-234-4433 Neal R. Gross & Co., Inc. Page 169 61:16,19 childhood 125:6 128:8,13,14,18 children 9:12,15,19 10:4 16:2 17:18 19:1,20 20:5 21:1 21:7,20 23:7 30:15 33:21 50:9 60:19 61:3 62:13 124:19 127:19 134:14 153:11 157:16 Cho 88:5,6 106:3

106:13 choices 112:19 118:21 chosen 119:1 Chris 1:17 3:12

41:12 49:9 73:8 85:2 111:17 132:11 144:21 147:22 162:12 Christopher 1:9,12 chronic 135:3 circle4:7 17:15 circumspect 127:17 cite 63:21 86:7 91:4 156:6 cited 153:20 cities 21:12 24:8 city-specific 25:6 clarification 35:12

39:5 40:16 106:1 clarifications 5:15

35:11 72:12 clarify 36:3 56:12

59:9,15 64:1 66:15 88:10,14 149:13 152:1 clarifying 3:22

5:18 72:20 73:6 77:14 clarity 127:5,20 134:1 clean 1:1 50:15

55:16 cleaning 31:12,19 50:14 cleanliness 63:9 clear 16:18 50:1

71:13 89:15 95:5 131:7 143:14 156:8 clearly 27:1 63:6

89:14 136:14 148:15 164:5 Cleveland 20:17,18

20:19 CLIFF 1:14 climb 79:6 clinical 127:10 142:6 close 20:8 79:5 closely 55:22 105:21 closer 17:10 closest20:6 closing 71:7 coefficients 94:15 coffee 7:5 cognition 128:14 cognitive 134:13 cohesive 150:4 colleague 156:15 colleagues 158:15 collecting 70:20 columns 40:6 combinations 104:21 combined 25:9 combustion 53:8

55:10,14 101:7 122:17 combustion-relat...

53:15 come 23:22 34:18

45:14 55:15 63:5 75:14 77:17 86:11 100:17 115:20 120:18 125:17 127:3 131:6,9 134:5 148:7,17 152:21 153:5 154:18 155:19,21 161:13 comes 45:10 53:19

56:22 90:1,5 113:14 163:15 comfortable 117:10 coming 50:17

86:20 comment7:12 36:9

49:13 58:1,3 59:20 62:8 63:18 73:6 91:17 113:14 117:12 120:10 122:4 129:12 130:1,19 132:19 133:3 140:16 142:19 143:13,14 144:3 149:16 151:12 155:13 160:14 163:6 commented 87:11 commenting 64:1 149:12 comments 64:8

66:18,22 67:19 70:12,13 72:13 73:3,6,22 76:21 87:18 89:7,12 91:12,13 94:19 108:15 113:15 121:8 123:3,22 127:4 128:2 132:6 132:12,12,13 137:15 141:11 142:1 143:4,12 145:2 146:21 147:6,18 149:8 150:21,22 151:17 151:19 163:22 commercial 51:18

82:18 committee 1:1,8

76:3,6,15 communicate43:8 communicating

42:18 communities 111:1 community 156:20 companies 96:19 comparable 128:16 138:12 comparative 106:14 compared 64:15 114:10 115:2 138:5 comparing 151:1 comparison 88:21 103:10 106:5,7,8 106:16 comparisons 138:10 compartment 114:13 115:2 compartmental

25:9 compelled 146:16 compelling 138:17 155:21 complete4:14 12:8

72:1 84:19 completed 6:16 7:7

8:11 9:9 10:16 18:14 completely 6:12 completing 10:2 12:14 18:6 completion 34:19 complexities 17:21 complexity 23:3,21

25:4 26:3 52:4 60:20 complicated 7:8

22:3 50:19,21,22 51:14 105:13 137:14 141:13 160:3 161:6 component 13:20

37:5 50:17 components 41:22

42:1 computer 58:9 concentration 15:13 27:15 48:9 56:9 112:8 concentrations

24:4,18 26:14,18 30:22 49:17 78:8 112:16 122:16 153:10 165:3 concentration/re... 16:16 concept42:13 80:6 concepts 83:16 161:4 conceptual4:13 conceptualization 127:6 conceptually 15:11 concern 95:18 119:10 131:16 concerned 102:3 125:16 concerns 126:8 129:16 151:6 concluded 6:11 conclusion 60:14 120:2 128:20 131:3,6,9,11,12 132:20 152:22 154:18 155:20,22 conclusions 126:17 126:18 129:18 130:17,20 133:4 137:3,4 concurrence 74:22 concurrent 16:14 concurs 163:19 conditions 164:7 conducted 13:21 118:17 165:8 confidence 8:7

28:10 44:3 45:15 46:22 confirmation 128:3 confounding 126:9 132:2 confusion 127:8 connecting 89:5 100:12

### 202-234-4433 Neal R. Gross & Co., Inc. Page 170 connection 102:14 consensus 66:19

90:11 94:19 106:11 124:10 125:12 128:16 133:19 144:22 consider 18:10

32:3 40:19 54:9 57:14 67:2 158:5 consideration 6:8

21:17 31:17 70:13 149:14 considerations

2:13 3:18 68:21 considered 8:4 11:15 119:18 considering 6:17

22:5 66:20 72:2 consistency 63:12 121:8 124:18 consistent 115:5 121:20,22 126:6 consistently 136:10 140:11,13 consolidation

96:17 constant 12:13 15:6 114:12 constituted 76:8 constrained 141:4 constraining 96:6 constraints 89:11 construct 138:9 139:15 162:3 consult 142:5 consultation 64:9

66:1,13,16,19 67:14 74:1 contacted 72:22 contamination 11:7,10 contemporary 124:18 context7:16 8:10

9:8 45:7 51:21 52:11 54:7 55:4 63:19 88:7 104:18 111:4 118:5 continue46:1

96:12 100:13 continuing 36:16 108:9 continuous 97:20 contradiction 114:9 contradictions 108:20 114:8 121:9 contrast 114:20 138:15 contribute44:18 contributed 13:22 126:17 contributing 12:20 13:5 contribution 15:4 15:12 19:6 42:16 42:22 52:7,14 110:7 115:1 contributions 13:3 14:21,22 32:10 42:11 61:16 62:1 109:19 contributors 142:7 control 63:12 controversial 155:14 convenient 108:14 conversation 52:19 convey 73:18 84:9 114:11 copies 3:7 copy/paste 85:13 correct 155:1 correctly 49:14

53:1 72:6 correlated 19:3

30:17 32:15 84:5 158:21 correlation 19:8,10

30:11 37:16 91:14 93:5,6,7,14,15,22 94:15,18 95:10,12 correlational 33:16 33:17 44:7 45:17 correlations 44:17

92:17,20,22 93:20 94:7 corresponding

69:22 Cory-Slechta 1:14

137:18 148:20 149:11 152:4,19 154:14 155:7,17 159:12 count 122:11 counterpart79:22 country 37:4 56:9 couple 35:12 47:11

95:15 104:1 107:10 109:13 114:21 128:1 150:14 course 57:2 66:10

73:21 81:12 143:19 144:1 147:13 cover 98:5 121:2 coverage 32:18 covered 137:22 co-exposure 151:9 CR 34:3 craft76:18 create 103:15 creativity 97:5 credence 153:15 credible 126:7 criteria 81:13,15

92:2 97:6 126:19 126:22 critical 28:14 33:18

37:13 46:2 52:14 83:22 115:22 116:21 125:9 126:2 128:18 142:19 critically 84:7 147:11 critique 116:10 118:13 156:7 critiquing 94:17 crop 51:17 52:2,4 crops 11:8 49:18

51:6,12,18 cross 113:6 121:11 121:16 crude 24:10 CSN 93:15 cubic 100:3 cuff38:3 culture 165:3 curious 70:17 current7:17,17 10:11 20:8 41:7,8 56:6 69:19 74:18 75:16,17 78:19 84:8 87:8 97:10 114:6 122:21 currently 8:16

70:14 105:6 133:5 154:7 160:19 curve 17:19 cut98:8 cycle 79:3 81:16

88:13 C-O-N-T-E-N-T-S

2:10 D dairy 52:4 data 24:5,8 25:11

25:14,20 26:1,2,2 30:19,20 35:19 38:5 40:20 41:2,4 42:10 55:20 63:5 63:16,20 70:20,22 71:3,5,11,12,19 72:2 81:14,18,21 87:12 88:17 93:14 93:16 94:21 101:18 106:5,15 106:17 112:15 116:19 121:19 122:18 123:15 139:4 142:11 154:15 162:17 164:3,17,21 dates 71:21 DAVIDSON 1:14 days 3:10 deal 10:2 115:11 dealt 144:4 death 86:15 Deb 139:9 Debbie 142:7 155:10 Deborah 1:14 135:22 137:17 154:13 162:6 decay 57:22 decide 117:22 141:8 deciliter 19:5 decision 137:10 decisions 139:15,20 decline 114:14 decrease 12:3 113:20 decreasing 60:2 decrements 134:14 defaulting 162:2 defendable 90:16 defer73:1 deficiency 22:11 deficient 84:7 deficit46:15 138:8 define 145:9 147:21 defined 150:5 defining 164:5 definitely 34:10

48:19 132:11 definition 97:17 139:15 145:18 146:13,19,22 definitions 143:7 definitive 119:6 degree 8:3 16:5,6 17:13 32:14,15 34:17 40:2 45:14 60:10 63:8 Deirdre 1:19 6:3

36:14 40:14 47:7 54:9 67:6,17,20 deliberation 153:6

### 202-234-4433 Neal R. Gross & Co., Inc. Page 171 deliberations 159:13 delta42:16 deltas 46:17,21 demographics

21:16 demonstrably

29:17 34:1 demonstrated 134:21 depend 30:4 dependent47:3 depending 13:18

61:3 63:2 depends46:18 144:13 deposit9:17,18

53:9 deposited 8:19,21

9:6,11 depositing 100:18 deposition 8:21 11:1,6,8,9 49:18 depression 159:20 deprivation 161:18 derived 63:2 described 68:3,6

76:2 81:13 87:17 111:5 describing 127:5 description 95:3 120:11 126:22 design 96:1,3 97:6

97:8,16 126:8 designation 149:17 designing 10:1 design-based 95:19 despite 86:8 detail 15:16 18:4

84:4 142:18 145:17 147:10,11 154:4 detailed 64:17 65:5 133:18 145:1 details 7:9,11 105:12 143:4 162:14 determination 126:13,19 127:1 130:6 131:17 133:14 134:11,12 134:17 136:7,18 determinations 129:14,17 134:2,5 determine 130:17 determined 134:20 determining 126:7 127:18 deterministic 25:10 develop 67:11 developed 6:15

25:8 67:13 97:8 147:1 developing 96:20 development 6:12

75:19 97:8 117:19 develops 76:2 deviates 65:18 deviation 22:18 deviations 33:6 DFO 1:23,24 5:16

72:22 diagram 10:17 17:2 21:4 dial 51:3 dialed 51:4 dialing 11:20 diet27:1,4 48:17 114:3 dietary 22:11 27:1

51:21 52:12 109:3 difference 54:5

67:7 79:17 95:2 differences 48:13 112:20 163:4 different 10:14 15:8 24:5,6 26:8 26:12 27:6,15,17 28:1 34:1 37:3,3 38:7,21 40:10 42:17,18 48:10 49:13 54:16,18,20 60:15 61:5,13 67:16 70:10 71:21 88:19 93:16 94:16 99:4 102:4 111:1 116:9,18 119:12 121:14,14,15 133:4 134:2 145:8 145:9 147:20,21 150:16 163:1 differential 98:11 101:2 differentiate 147:20 differently 135:19 difficult 22:9 49:21

51:2 150:17 161:13 dimensions 26:6,9

27:13 dinner 52:19 direct 10:20 13:22

54:2 direction 133:20 directly 9:2,4 14:6 16:9 26:16 35:20 151:1 Director 1:25 dirt57:5 102:10 disagree 154:14 disagreeing 118:7 disagreement75:6 124:8 disagreements 129:18 disagrees 134:16 135:9 disappeared 88:9 discarding 95:9 disciplinary 76:11 144:13 disconnect 87:7 101:10 discrete42:12 discretion 145:7 discuss 4:2 5:4 6:14

7:22 15:17 73:13 75:8 95:5 115:18 133:15,21 135:21 discussant 84:12 discussants 103:1 discussed 13:15

28:17 60:22 80:13 113:2,5 162:22 discussing 5:8 discussion 2:17 3:6

6:20 63:4 73:11 73:21 74:20 76:21 77:11,14,18 78:4 84:17 88:4 89:9 90:7 97:12 98:8 98:13,14 99:9 100:22 104:17 105:5 106:1 108:16 109:2,19 111:10,21 112:10 112:20 116:1 117:16 118:14 124:1 129:13 130:5,15 133:18 140:17 143:17 150:12 151:21 156:5 158:10 162:6,15 164:14 discussions 58:17

58:18 59:1,2 62:18 109:5 disease 134:22 disorder 139:16 dispel 82:5 dispersing 79:11 dispersion 24:13

79:15 105:3 disrespectfully 161:5 disruption 165:2 dissolvable 100:7 distant51:13 distill 83:18 distinguishing

67:16 126:10 distributed 78:9,20 distribution 17:6

20:13,16,21 42:9 44:15,16 45:3,9 46:6 54:21 61:12 61:14,22 88:16 90:2 112:12 distributions 33:2

33:11 42:9 103:18 document 6:9 66:5

66:17 67:13 70:5 83:15 84:20 109:10 117:14 119:18 121:10 126:21 128:3,15 138:7 141:11 142:4 153:14 154:8 160:19 164:19 documents 105:6 162:20 doing 39:13 75:1

76:13 80:5 95:7 116:8 143:8 148:2 149:1 domains 138:6 domestic 85:21,22 dominant53:13

56:3 dominated 55:9 122:16 dominating44:11 dose75:2 100:9,16 134:19 doses 164:6 dots 89:5 100:12 double 107:17 Dr 1:9,12,13,13,14 1:14,15,15,16,17 1:17,18,18,19,20 1:21,21,22,22,23 1:25 3:13 6:2,2,5 7:2,3 13:7,9 15:2 15:7 20:17,18 21:14 22:6 35:10 36:13 39:2,3,4,11 39:15,19 40:13,15 41:9,13,15,16 43:9 46:10,18 47:10 49:9,10,22 51:6,8 52:15 53:22 54:11 55:17 57:13,17 58:2,13

### 202-234-4433 Neal R. Gross & Co., Inc. Page 172 58:14,21 59:4,6,8 59:13,15,21 62:6 62:22 63:22 65:8 65:12,17 66:6,15 67:6,10,17,18 68:1 70:16 71:2 72:5,15,15,17,18 73:9,20,20 74:5 74:19 76:2 77:1,7 77:10 78:22 80:10 80:16 81:4,20 82:3,5,11,13,16 91:10,21 92:5,11 94:5,11 95:13 96:10 97:13,18 98:4 99:16,21,22 101:15 102:11,17 103:6,22 104:13 104:16 105:9,16 107:1,7,20,22 108:4,5,8 111:18 111:22 115:6 116:3 117:4,17 118:2,6,8,11 119:9,16,20,21,21 120:1,11 121:5,7 123:2,9,16,20 129:9,22 130:13 131:1,13,15 132:15 133:9,17 134:8 135:13,15 135:17,18,20 136:2 137:17,18 139:6,8 140:2,3 140:15 141:7 142:12 143:5 144:1,20 145:13 145:15 146:9 147:1,17 148:4,20 149:6,8,9,11 151:22 152:4,8,10 152:19 153:7 154:11,14 155:4,7 155:9,17 156:2,4 156:12,13 157:7,7 158:3,7,9,12 159:12 160:10,13 161:16 162:5,12 164:22 165:7,9 draft 3:5 4:22 6:19

64:13 65:13,14 66:8,11 67:3 70:7 70:10,14 83:7 84:1,8 87:13,18 88:9,17 89:8 91:12 106:16 115:22 127:22 147:18 drafted 65:6 drafts 67:4 70:10

71:17 125:4 draw49:8 69:14 drawn 126:18 drillings 97:1 drinking 11:10,13

30:9 156:14,17,20 Drive 1:9 driven 14:6,13

45:12,13 52:9 driving 12:19

44:11 52:8 94:4 dropoff24:17 duck 161:22,22 dumber78:14 Durham 1:9 dust 11:2,2 12:5 13:5,5 14:6,8,13 15:5,9,13 18:13 23:1 25:3,17 26:16 27:10,13 31:7,13,14 32:13 50:11,16 52:10 62:16,17 120:19 E E 1:15 earlier 67:12 88:19 113:5 120:11 early 65:10 70:15 eat98:3 ecosystem 163:3 164:9 Ed 5:19 58:15

59:18 73:1 editing4:12 EDWARD 1:24 effect 17:7 78:8,13

79:16 effective 71:11 effectively 43:8 effects 69:5,7,10,22

75:3 98:11 124:15 124:21 125:7 127:18,21 130:8 134:18 135:10 138:4 164:9 165:2 165:2 efficacy 158:21 159:6 efficiencies 31:12

31:19 efficiency 53:17 effort 12:7 91:9 127:17 efforts 74:8 80:20 egregious 131:8 either 5:16 11:8

46:15 56:5 67:11 96:20 102:22 104:4,19,20 128:2 149:4 153:1 elaborate 103:2 element27:20

28:21 37:8,13 54:17 93:5,6 elements 7:21 25:9

25:10 26:9 28:15 28:20 46:5 elevated 50:5 53:5 153:10 elimination 114:11 email 165:12 emissions 68:17

79:3 85:20 emitted 8:14,17 emitters 104:5 emitting 105:2 emphasis 29:21

41:17 emphasize 12:17 emphasized47:5,6 empiric 116:19 empirical 25:9,11

42:10 63:15 112:15 encourage 59:1 119:15 ended 29:21 endocrine 165:2 ends45:8 60:6 engage 144:7,17 engine 82:22 engineers 97:5 enhance 34:15 156:16 enhanced 22:14

33:8 35:5 57:2 ensure 58:18 entire 84:3 99:10 environmental 1:1 163:2,4 164:7 envisioning 68:19 EPA 2:12 3:17

74:22 76:13 80:21 81:14 84:1,10 88:8 94:20 103:3 108:17 116:7 117:6,14 121:10 132:19,22 134:4 136:11 140:10 142:4 143:17 144:7,16 146:12 148:3 156:21 158:4 EPA's 62:17 130:19 153:14 epi 16:17 161:8 epidemiology 16:8 17:17 124:12 131:21 episodic 38:20 equations 15:14

35:17 ERD 85:11 error 113:2,7 122:14 errors 122:5,6,12 122:20 especially41:21 108:12 140:16 essential 83:21 essentially 36:4

49:17 54:18 59:19 88:2 154:21 159:19 establish 127:11 esteem 151:1 158:14,22 159:5 159:15 160:20 estimate 16:2 18:17

22:20 25:20 26:8 28:11 33:5 44:13 112:17 115:1 119:1 estimates 8:5,8

26:5,11 28:13 31:5 34:16 38:9 42:12 43:14 44:2 44:20 46:16 47:22 48:2 60:16 61:18 110:5,7,16,21 111:14 112:3 114:2,15 117:7 estimation 15:21 et 106:13 136:21 146:13 150:20 158:14 159:20 etcetera 69:10 159:4 evaluate 16:2 36:16 139:13 evaluating 90:14 evaluation 33:21 136:5 164:2,20 everybody 78:13 125:12 evidence 8:1 17:17

35:7,17 41:8 43:16 44:3 55:18 60:2 75:2 118:16 129:13,15,19 130:5,18,20 131:19 135:11 136:6,18 137:12 138:16 149:18

### 202-234-4433 Neal R. Gross & Co., Inc. Page 173 150:6,7 154:7 156:8 evidence-based

43:16,22 exactly 39:11,12,14

49:5 71:14 161:21 example 21:20

35:22 38:12 41:22 76:12 91:3 92:3 103:8 105:20 109:3,12,22 114:1 137:11 142:5 143:7 146:19 160:15 165:5 examples 111:7 123:12 128:11 143:2 Excellent 108:5 162:7 exchanging 59:7 excluded 122:8 exclusively 122:9 excuse 61:21 exerts 18:11 exist 62:13 existed47:19 exists 164:3 expect 34:5 36:19

37:19 38:17 91:20 140:16,22 expecting 80:1 expense 113:21 experience 8:16

9:16 experienced 142:14 expert 156:14,19 expertise 77:4 138:7 139:3 141:10,22 144:13 144:17 145:3,5,6 155:8 160:18 161:13 experts 144:7 145:9 147:21 explain 11:5 49:19

91:16 explained 21:9 explicit 126:21 130:12 136:22 138:10 explicitly 15:1 150:8 exposed 9:2,5,12 10:5 19:17 20:4,8 20:22 21:7 29:14 30:1,5 50:12 exposure 2:12 3:18

6:13,15 8:22 10:7 10:13 11:22 13:12 13:20 14:2,8,9,12 15:21 16:22 17:3 17:4,6,20 18:3,9 18:11,21 19:8,21 20:2,21 21:3,21 23:8,14 27:1,17 30:13 32:7 33:19 34:18 35:2,4,15 35:22 36:11 38:11 38:16 43:1,1 50:9 51:11,17,22 52:6 52:9,12 57:1,3,5 61:6,9 62:14 65:22 67:9,19 69:5,11 77:18,22 78:18 86:10 91:1 91:2 99:11 102:5 102:15 104:6,21 105:11 109:2,4 114:13 121:1 127:20 134:13 135:3 153:11 154:8 157:3,20 164:6,8 exposures 9:19 10:4 13:6 19:3 20:13 21:13 22:19 37:18 38:7,19,20 53:15 55:13 60:19 72:8 105:4,12 114:3 124:22 express 76:12,19 expressed 95:17 131:17 expression 92:9 extent 13:16 22:21 23:15 47:7 50:7 60:17 65:2 74:2 75:1 80:14 81:11 82:22 84:6 119:1 122:7 129:12 130:9 132:18 133:6 146:10 extrapolate 111:2 extremely 112:5 141:13 F FACA 58:16 59:3 face 71:3 face-to-face 6:21 facility 20:6,11

21:11 24:15 fact 10:2 37:4

39:12 95:10 110:22 138:12 140:8 150:5 151:12 159:16,17 162:16 factor 110:15 111:11 112:2 117:14 118:4 factors 15:16 21:21

22:9,15 61:5,6 63:8 103:17 110:21,22 112:14 118:15 149:17 150:3,5,16 factual 109:6 fail 96:12 fair 39:6 130:1 155:9,11 158:2 fairly 7:10 9:20

24:16 25:7,8 fall 6:22 66:9 68:3

93:21 familiar 26:5 139:12 far 129:19 144:7,10 159:14 faucets 153:22 FDA 114:2 feedback 141:9 feel 53:19 56:8

64:20 74:4 108:1 110:3 113:17 124:9 132:19 135:15,19 141:3 146:14 154:6 feels 125:12 feet79:8 fell 49:3 felt52:5 64:5 109:5 149:21 150:19 154:3 FEM 97:15,16 98:1 female 159:17 fidelity 116:18 field 53:9 96:18 figure 10:12 23:20 112:1,2,7 figured 52:12 101:16 figures 111:6 114:10 file 83:7 filtering 90:16 final 34:6 123:8 finalized 81:10 finally 33:20 find 138:19,22 141:5 146:4 156:22 findings 132:4 154:22 fine 53:17 55:14 119:9 122:17 147:9 148:2 finer 55:2 first4:22 36:14

46:13 52:16 53:10 64:13 65:14 67:3 70:6,10 85:5,7,11 85:20 87:13,18 88:9 89:7 91:9 98:5 101:17 106:2 108:21 124:5 132:7 144:20 149:20 160:11 five 84:5 107:11,13 115:4 121:21 123:18 124:7 132:9,14,18 133:7 136:9 140:16,18 140:22 141:5 148:5,12 150:22 163:16 fix 17:18 88:2 89:6 fixated 15:5 fixed 15:11,11 19:20 87:16 106:12 fixes 87:17 fixing 24:21 Flight 82:7 flip-flopping 95:4 floor 6:2 31:16 74:3 fluoridation 152:11 153:9 154:2,9 156:16 fluoride 151:9 157:10,17 fluorosis 157:14,15 157:22 fly 79:13 focus 29:19 32:1

42:7,13,20 46:14 46:16,17,21 63:13 84:4 108:21 113:19 focused 20:4 24:14 focuses 31:15 focusing 20:7 23:18

86:2 108:10 123:10 fold 95:14 148:15 folded 115:14 folks 68:12 99:10 follow 39:7 96:22 136:14 137:19 139:21 165:14 Followed4:2 following74:8

85:17 138:9 food 11:7 27:1,4 114:2 161:18

### 202-234-4433 Neal R. Gross & Co., Inc. Page 174 forgetting 99:14 form 8:18 formal 65:12 127:9 format 109:22 112:4 forth 29:3 82:9 forum 58:20 forward 6:3 113:13 116:17 forwarded 152:5 found 14:10 51:2 121:20 159:7 foundation 118:20 four 85:17 86:7,12

91:2,7 102:16 103:1,7 105:20 107:3,11,16 108:7 112:9 113:4,18 121:21,21 141:5 148:14 fraction 12:22 37:6 fractional 52:7

96:5 fractions 103:13 frame 7:15 10:15 14:15 40:4 46:12 81:16 framed 28:16 frames 29:4 framework 101:14 136:7,15 framing 15:18 18:1

34:11 63:1 free 108:1 113:17 fresh4:6 43:19

73:13 163:3 Frey 1:9,12 3:13

35:10 39:2,4,15 40:13 41:9,15 49:9 52:15 58:14 59:6,15 63:22 65:12 66:6 67:18 70:16 72:5,18 73:9 74:19 77:7 77:10 78:22 80:10 81:4 82:3,11,16 91:10 92:5,11 94:5 95:13 97:13 98:4 99:16,21 101:15 102:11,17 103:22 104:13,16 105:9,16 107:1,7 107:22 108:5 111:18 115:6 118:11 119:20 121:5 123:2,16 129:9 130:13 131:13 132:15 133:17 135:13,17 135:20 137:17 139:6 140:2,15 142:12 145:13 146:9 148:4 149:9 151:22 152:8 154:11 156:4,13 158:3,9 160:10 162:5 FRM 86:13 97:16 frustrating 81:17 fuel 82:7 fueling 82:15 full48:15 fully 23:16 100:7 101:5 function 16:17 48:9

54:20 100:3 102:15 138:11 functions 27:16

34:3 fundamental 126:2 129:18 funded 80:17 further 20:10 28:9

29:1 31:18 32:4 32:19 34:14 37:14 77:16 112:6 133:16 147:1,20 fuzziness45:15 G G 1:20 GA 56:13 Gail 1:22 128:6

136:1 139:6 145:13 151:17 160:12 gain 34:4 35:7 gas 68:17 75:13

82:21 83:4 gasoline 5:7 36:11

77:13 82:15 113:20 122:17 gasoline-driven

82:1 general 19:18 21:5

24:20 25:5 29:20 31:22 32:18 38:11 53:3 80:9 89:13 91:1,12 97:4 109:4 125:8 133:22 136:2 140:15 142:10 148:1 149:21 generalized 51:17 generally 8:12,16

9:13 15:11 55:7 68:9 70:4 135:2 generate 18:18

60:15 generated 25:7,15

112:14 geometric 22:18

33:5 110:17 geometrical 96:2 geometry 96:6 George 1:12 41:12

52:15 77:7,19 84:22 93:19 97:13 getting 7:4 27:5

33:13,13 57:7 81:10 132:16 134:22 136:22 146:18 147:3,10 give44:2 58:7

62:20 68:5,7 84:1 117:13 142:12 143:20 146:5 153:15 given 96:17 119:4

126:3 130:21 134:1 155:16 gives 46:10 giving 22:19 45:19

134:4 glad 102:18 107:22 global 161:19,20 go4:18 5:4,13,13

5:14 7:8 11:17 16:12 24:2 29:6 61:11 69:17 74:2 83:10,19 86:16 89:7 111:16,18 112:6 120:17 123:17 133:20 139:3 144:10 146:4 147:12 148:7,19 153:18 154:12,19 157:6 160:8 goal4:11 7:13 16:7

96:4 God 163:10 goes 10:12 106:18

120:11 132:22 going 3:3,10,15 7:9

7:15,18,19,21 9:18 15:13 28:5 28:11 29:1,8,15 32:19 34:8,9,12 36:18 37:7 40:15 40:22 41:12,18,21 45:6 46:2,12,14 46:16,17 47:8 48:15 50:12 51:14 51:16 63:6 64:16 65:9 68:5 71:9 80:2 81:6 82:9 83:22 84:4 87:10 92:19 93:9 101:1 112:9 132:10 139:21 144:17 145:6 146:4 153:1 154:16 157:19 160:11 163:20 good 3:13 5:19

13:10,13 38:12 46:11 52:17 55:20 63:1 65:11 72:10 75:9 77:5,11 79:1 81:4,18 84:9 87:1 90:11 95:14 103:22 109:6,17 116:4 119:18 123:2 124:17 126:9 143:5 148:6 151:19 152:8,14 153:18 155:5 158:4,10 160:4 162:5,7,9 GOODRUM 1:15

15:2 41:13,16 46:10 94:11 103:6 108:8 111:22 117:4 118:2,8 119:16 123:9 158:7 gorilla 86:19 gotten 61:20,21,22 gradient20:9,10

21:13 24:10,14 29:14 30:4 51:10 graphic 17:10 graphically 112:4 gray 12:1 13:7

41:22 great57:18 70:16

95:15 115:6,7 125:22 137:17 146:18 148:22 149:9 greater 20:20

22:11,14 24:17 44:3 46:22 47:6 99:7 122:10 green 12:16 ground 56:21 group 20:1 21:7

62:13 76:18 124:8 125:20 149:21 163:19 grouped 108:15 grouping 103:15

114:8 growing 27:4 GSD 22:17 57:20

### 202-234-4433 Neal R. Gross & Co., Inc. Page 175 60:4,9 61:20 62:4 62:10 63:2,15 GSDs 33:8 60:21

61:1,7 63:3,5,20 guaranteed 97:1 Guardian 1:9 guess 5:21 19:13

22:7 36:2 49:18 52:18 56:18 57:7 59:6,19 64:19,22 70:17,19 73:1 79:1,7 86:11 94:5 95:15,18 96:4,4 98:4,6 104:2,19 117:4 118:2 129:10 130:13 132:16,21 133:18 140:15 148:10 156:7 160:22 163:15 guidance 144:21

145:16 146:6 148:1 164:11 guide 123:18

148:20 162:10 gut 120:18 guys 70:5 71:4 H H 1:9,12 half56:19,20,20 hampered 60:17

61:15 hand 12:10 19:16

51:19 78:19 80:5 87:6 158:6 160:11 handle 36:14 handled 27:16 hands 100:6,19 120:20,21 154:12 hand-to-mouth

9:15 Hanlon 1:24 3:3

5:19 58:16,22 73:4 105:22 165:11 happen 31:5 112:11 happened 20:10 happens 29:22 happy 62:7,20 101:20 hard 3:7 28:3 31:16

45:19 49:6 51:19 63:14 90:4 99:1 harder48:18,19

90:20 haunt96:12 Hays 1:15 108:3,4 149:8 health 35:4 69:5,7

69:13,15,20 70:2 98:11 99:11 124:15,20 125:5 125:15 126:4,15 127:18 130:5 hear73:20 87:1 119:16 heard4:4 5:5 70:17

72:13 73:16 74:5 75:12,15,19 81:7 94:13 99:8,15 hearing73:8 heart 134:22 heated 90:8 height79:9 held 12:12 helicopters 82:7,9 Hello 107:20 help 29:1 30:20,21

31:18,21 32:11,21 33:8,14,15 34:14 35:1 38:15 74:12 110:1,11 141:22 146:6 helpful 101:16 110:10 111:5 112:5 113:13 124:16 136:15 142:9 helping 8:4 28:8

32:4 36:1 helplessness 158:20 158:20 159:3 helps 10:15 31:3 34:3 35:7 51:5 62:5 109:9 HERBERT 1:13 Herculaneum

31:11,15 32:2 hey 87:9 high 19:4 23:17,18

24:16 43:11 44:5 45:10,12,12 46:14 49:4 52:8 61:12 79:12,13 94:16 104:4 135:5 higher 9:14,19 18:21 20:22 21:18 21:21 23:7 30:13 37:5,18 45:8,13 46:6 48:6 49:3 56:9 60:3,6,12 61:19 110:17 112:15 124:21 157:14 highest 8:15,22

78:8,18 93:21 highlight91:22 113:18 114:4 143:6 147:19 155:18 highlighted 12:1 154:9 155:15 highlighting 113:21 145:11 highlights 115:5 123:22 highly 9:12 19:1,17

20:4 23:12 30:15 high-emitting 104:22 high-end40:11

60:19 61:14 high-level 143:10 143:12 high-power79:4 historic 113:8 historical 50:7,19 113:16 117:19 122:5,22 historically 12:18 117:18 122:12,15 history 53:15 hold 15:5 home 68:6,7 homologies 127:11 127:13 homology 151:4 158:14 159:2 hope 63:11 160:12 hopefully 160:13 hoping 141:22 HOPKE 1:16 74:5

77:1 80:16 82:13 91:21 96:10 97:18 99:22 155:4 Hopke's 120:11 hot 155:14 house 63:7,9 68:4 houses 13:4 housing 21:22 human 127:12 155:7,8 humans 154:16 161:20 hundred 107:14 Hunt 31:10 hurdles 97:19,22 hypertension 134:17 I Ian 1:22 113:17 116:12 Ian's 113:15 idea 68:5 79:21 114:11 163:15 ideally 143:20 identical 88:18 identified 68:22 129:5 identifies 116:10 identify 29:7 34:20 116:21 identifying 129:1 IEUBK 18:18

22:13 54:13 61:10 62:10 109:18 114:5 IEUBK-based 110:6 ignorance 82:6 ignore 154:17 ignoring 154:19 illogical 92:16 illustrated 17:1 illustrates 21:4 imagine 93:3,9 immediately 21:10 immunology 130:9 impact23:9 26:13

26:21 37:6,7 47:14 48:15 57:22 impacted 27:2 impacting 27:3

51:12 impacts 14:18

26:15 54:4 150:15 implausible 94:16 implement75:16 implemented 71:22 implication 80:12

95:21 110:15 130:14 implications 35:4

40:3 69:13,16 72:9 83:14,16 84:19,21 105:17 112:18,22 115:13 115:16 148:11 implying 36:4 importance 120:12 122:4 important 8:20 12:19 13:1 14:5 18:4,22 27:20 28:12 30:2,6,14 31:9 64:20 77:22 78:21 100:10 112:10,19 120:15 121:1,17 123:6 139:1,19 141:12 143:8,9 147:11 150:19 151:13

### 202-234-4433 Neal R. Gross & Co., Inc. Page 176 importantly 9:5,7 12:5 16:20 imposed 151:2 impossible 139:11 impractical 97:10 impression 117:13 improve 36:18 111:7 149:16 164:14 improved 121:10 124:7 improvements 124:11,13 125:3 improving 29:9 impulsivity 138:20 inadequate 35:16 inclination 76:16 include 11:16

31:16 58:19 130:7 155:11 included 20:14

32:22 71:14,19 88:6 110:19 128:6 151:3 164:18 includes 110:5 138:9 140:8 including 35:5

68:16 99:10 104:12 inclusive 71:16 income 22:1 159:7 inconsistency 153:4 inconsistent 132:4 140:9 incorporate 24:10

66:3 162:6,19 incorporated 144:15 increase 22:15 increasing 157:10 incredibly 153:12 incremental 17:7 17:12 47:12 increments 47:6 indirectly 86:5 individual45:16 66:18 113:15 137:14 139:20 141:11 142:1,18 143:4,13 144:2 146:20 147:2,6,12 150:22 individuals 60:5 indoor 9:9 10:7 11:1,2 12:5 13:5 14:6,8,13 15:4 18:13 22:22 23:1 25:3,17 26:16 27:10 31:7 50:16 52:10 62:17 103:10 indoors 9:10,17 10:22 50:14 inform 74:13 98:12 information 2:13

3:17 6:10,11,17 19:7,9 28:6,20,22 29:1,6,11 30:8,11 31:3,12 33:8,16 34:9,10,13 35:5 36:17 37:11,16 40:1 45:17 46:1 48:21 56:4 57:20 58:1 59:7,10,16 60:10 66:3 68:10 68:15,18 69:5,6,8 69:11 74:11 81:2 87:20,21 88:16 93:18 94:3 95:7 103:9,20 108:18 109:21 110:8,12 119:4 120:9 130:16 139:5,17 144:4 163:7,11 164:15 informative 93:15 124:17 informed41:5 ingested 9:11 100:20 ingestion 9:5 11:2 12:5 14:6,13 52:10,10 inhalation 9:4 10:20 12:2 13:17 13:22 18:12 26:16 27:10 52:20 53:11 53:17,20 54:3 57:6,8 77:21 100:2,15 102:2,7 innovations 97:7 input54:18 62:20

77:6 129:8 144:9 inputs 54:13 inside49:3 insight72:7 insignificant 13:18 instance 10:7 13:2 19:3 22:13 27:11 40:12 59:22 61:21 instances 12:21

35:19 36:17 121:13 insurmountable

97:19 integrate 12:7 67:7 103:19 integrated 65:21

67:11 69:1 111:9 118:12 150:4 163:14 integration 124:12 intend 70:9 intended 55:7

62:11 104:9 136:17 intending 64:12 intention 69:2 70:5 interact 148:13 interaction 151:13 intercept 15:8 interest76:12,14 108:21 123:17 interested 18:16

23:11 42:19 47:14 98:10 144:3 interesting 31:11

31:18 55:18 57:9 57:21 62:7 86:8 159:22 interject 59:9 internal 157:20 interpret 8:4 34:14

36:1 46:3 90:4 interpretation

35:13 40:3 94:7 115:9 121:19 151:6 interpretations

64:22 interrupt 108:2 intervention 139:1 intricacies 150:1 introduced 17:21 19:2 113:10 introduction 138:8 introductory 107:12 162:19 inventory 56:19 invest96:20 IQ 16:2,6,9,17,22 17:8,13 23:6 27:16 33:20 34:1 45:12,13 46:15 47:6,13 54:4 75:3 78:14 125:6 ironically 23:7 iron-deficient 22:2 ISA 64:8 69:7 71:6

73:19 75:15 80:12 80:14 84:1,3,8 86:18 87:5,9,18 88:9,17 95:21 106:16 116:1 118:19,22 119:4,5 134:3 140:21 144:8,15 145:4 147:18 156:21 isolate 117:6 issue 25:12 33:17

47:12 50:13 55:22 62:19 71:2 85:20 86:17 91:14 97:21 140:12 151:8 152:11 154:4 158:13 160:16 issues 4:8 44:7 47:13 73:14 76:11 96:11 99:14 116:8 116:21 150:12 155:6 157:2 159:10 italics 85:6 item 122:3 items 165:14 iterate 5:2 IUU 57:22 J JA 55:15 Jet-A 82:15 Joel 1:20 121:6 John 86:5 91:5 JOHNSON 1:17

49:10 51:6 165:9 judgment 147:14 153:2 July 67:15 justified 117:1 justify 117:22 K keep 23:5 83:10

86:20 147:7 152:16 kept 89:16 Kevin 71:20 key 2:17 3:6 4:3 15:22 83:17,20 104:3,14,15 108:7 115:17,19 125:14 125:18 129:1 130:4 131:15 133:10 147:19 164:14 kicking 157:8 kids 20:2,8,22

23:12,17 29:22 30:5 128:8 139:22 kilometer 21:10 kind 16:10 19:7

38:21 44:20 46:1 51:17 57:6 60:9 63:9 64:9 71:4 76:16 78:6,8 81:6

### 202-234-4433 Neal R. Gross & Co., Inc. Page 177 89:10 95:4 97:16 98:17 99:3 101:17 103:4 105:7 106:7 108:14,19 110:3 112:16 119:17 122:14 125:1 140:13,19 143:10 151:4 154:18 156:14 160:14 161:12 164:5,20 kinds 78:10 80:20

82:8 159:13,19 knew47:19 48:3,5

48:6 know4:22 5:20 16:10 21:15 22:8 28:19 31:2 33:10 35:3 36:15,22 38:5,14 39:22 40:7,16 41:9 42:8 43:10 46:19 47:1 47:7 49:5 50:6 51:11,20 52:8,22 53:22 54:6,9 56:3 56:5,19 58:4 61:1 61:17 62:8,9,17 65:17,19 68:16 72:8 74:14 77:21 78:11,14 79:20,22 80:16,18 82:6 83:1 89:17 90:10 92:2 94:2,3,21 95:6,16 96:2,7 98:16,20 99:12,20 100:1,2 102:21 103:15 107:8,9 111:3 113:7 116:7 116:15 118:8,9 119:5,10 123:5,14 124:7,9 131:13,18 132:10,10 135:7,8 135:10,12,21 136:12 138:6,8,17 138:18 140:4,6,11 141:6,13 142:16 143:1,3,5,6,22 144:10,13 145:3 145:19,22 147:8 148:8 152:11,13 152:15 153:17 154:5,12 155:20 156:15,19 157:21 159:12 160:10,22 161:21 162:16 163:18 knowing 65:9 116:14 131:12 knowledge 130:21 133:11 142:2 149:18 known 8:13 knows 62:9 136:11 KORRICK 1:17

123:20 129:22 131:1 160:13 KOSNETT 1:18

13:7 21:14 57:17 58:13 62:6 65:8 116:3 117:17 118:6 119:9 131:15 133:9 134:8 135:15,18 140:3 152:10 153:7 155:9 156:2 156:12 L L 1:19 lack74:20 126:12 127:4 132:21 134:1 136:4 159:6 lacked 109:7 lagging71:22 laid49:12 102:1 136:7 lame 58:6 land 120:18 landing79:2 LANNO 1:18 162:12 large 21:15 80:6,8 105:4 122:11,13 larger 21:3 61:3,21

63:5 102:8 122:7 122:14 largest79:21 80:1

80:3 lastly 108:19 110:13 114:7,21 latitude 134:4 launch 98:7 lay 161:21 laying 96:8 leaches 153:22 leaching 156:16 lead 1:2 8:10,13,17

8:17 9:3,10,16,20 9:22 10:3,5,8,18 10:20 11:20 12:4 12:18 13:8,11,11 16:5,6,9,11,11,13 16:14,22 17:6,8 17:12,19 20:3,21 21:9,19,21 23:1 24:7,12,19 25:3 25:13,22 30:10 31:7,13,13 32:6 32:17 33:3,4 42:8 42:9,12,14,17 45:12,12 46:15 47:13,15 50:10,16 53:2,5,8,15,16,18 54:4,6 55:3 56:19 57:4 60:1,12,16 61:8 68:13 69:9 69:16,18 74:9 75:17,20 78:17 79:18 80:17 81:21 82:2 84:12 85:20 87:20 89:9 90:6 92:17,22 93:5,7 93:22 100:5,18 103:11,16,16 104:15 105:4 109:4,13,20,20 110:16 111:11,14 112:7,15 113:8,20 113:20 114:2,12 114:12 115:2 122:5,15,17 124:19 127:18 128:8 129:2 134:13,17 135:2 151:9 153:10,10 153:11,22 154:2,2 154:8 156:14,16 157:14,18,18,22 159:18 163:5 165:4 leaded 82:7,21 leads 33:11 102:17 103:15 lead/blood 109:13 111:11 leaf 11:8 leap 96:17 learned 158:20,20 159:3 learning 159:4 leave 5:11 144:16 leaves 57:6 leaving 107:9,10 left21:6 60:3,6 106:8 123:4 124:2 left-hand 10:19 legitimate 144:12 146:12 lend 78:7 lengthy 141:1 147:4 letter 64:8 66:19

73:19 76:19 83:19 84:21 98:5 115:17 115:20 123:7,12 145:12 let's 45:5 50:10

61:20 75:14 88:3 107:7,15 108:6 123:17 148:19 level 4:13 11:19 19:20,21 20:2 21:8,8 22:16 24:16,21 25:2 30:1,6 38:11 47:3 51:9,15 79:16 84:3 115:20 121:9 137:4 145:16 146:9 160:18 161:13 164:9 levels 8:15 16:5 18:20 21:1,19 22:15 24:9 27:17 30:9,13 31:2 33:3 37:1 38:6,16,16 45:13 46:21 50:6 51:5,12 54:2 60:3 79:15 81:22 89:9 124:19 127:20 128:9 135:7 157:15 158:1 levers 139:14 Life 82:8 lifetime 16:14 lightning 140:19 liked 111:22 Likewise 149:8 limitations 125:15 125:18 128:11 limited 87:21 149:17 150:6 151:4 156:18 Lindern 1:22 119:21 120:1 line 134:9 161:10 linearities 16:21 lines 88:3 92:13

93:13 141:8 link 16:9 52:3 linkage 52:3 90:22 102:19 103:3 linked 26:17 27:10

31:8 list79:21 80:3 85:6

99:17 104:3,14,15 125:17 142:6 listed 129:3 149:20 lists 165:13 literature 89:18

94:22 95:5 106:20 106:22 110:4,9 124:13 125:9 126:16 128:13,19 130:22 131:11 133:1 134:6 139:12 146:16

### 202-234-4433 Neal R. Gross & Co., Inc. Page 178 157:21 158:2 161:3,8 literature-based 106:14 little 7:19 8:9 12:16 17:2 25:18 36:10 38:3 41:3,17 42:19 45:3,5 46:13 49:20 50:1 54:12 60:22 62:5 75:11 80:4 86:3 95:2,22 98:6 101:8 102:2,20 103:2 114:19 130:11 131:2 137:20 141:14 148:5 150:11 157:8 158:12 159:14 loading 14:14 15:13 50:16 loadings 50:7 locally 77:21 location 18:16

78:18 locations 50:5 location-specific

21:11 logic 103:15 159:13 logical 101:14 long 62:18 137:13 148:5 160:8 161:1 longer71:9 long-term 135:3 look 6:3 13:19 14:19 15:1 17:3,4 17:20 18:3,9 19:14 21:15 26:4 27:7 28:6,19,20 30:5,20 31:4,18 32:16 34:2,12,22 35:3 38:4,8 44:16 45:19 47:2 48:13 50:16 52:6,7 54:2 54:3,8,10 55:4,21 62:8 65:20 66:8 72:11 74:6 75:3 76:11,15 94:15 102:8 105:12 114:14 117:2,2 120:22 121:18 131:4 137:5 152:21 154:17 155:3,19 156:21 158:1 163:21 looked 10:1 11:18 14:4 20:5,12,16 20:19 27:15 28:1 28:14 31:11 49:7 51:4 121:12 134:6 161:1 165:1 looking 15:20 16:3 18:22 19:22,22 20:13 21:12 24:22 27:9 28:3 30:2 31:1 32:9 35:7 38:22 40:19 46:20 48:22 51:9 53:2 58:11 90:17 94:1 94:10 102:21 112:17 116:8 126:6 128:7 129:10 130:2 looks 37:1 45:4

61:18 141:16 loss 16:2,6,9,17 17:1,8 23:6 27:16 33:20 34:2 45:13 45:13 47:6,13 lost 127:21 136:21 lot4:11 12:7 14:15 17:21 19:9 20:9 21:1 23:12,21 24:2 25:4,14,22 26:6 29:21 34:5 42:6 44:8,19,21 62:16 76:11 79:11 81:18 88:17 90:7 100:8 105:11 125:19 127:16 128:12 131:16 139:19 140:17 141:20 143:15 155:16 157:21 161:8 162:14 163:7 Louis 20:15 low48:3 49:4 79:5

79:15,16 112:11 112:17,20 159:7 165:3 lower 11:19 22:1

23:10 27:17 37:5 49:4 60:8 105:1 134:19 135:6 157:14 158:21 low-level 134:13 lungs 120:16 Lydia70:8 L.A 20:15 M machine 96:22 macro 137:4 MACT 74:8 magnitude 17:7

44:2 45:5 46:9 150:15 main 84:15 100:1 109:10,11 major42:6 113:22 129:5 majority 14:12 making 89:5 121:6 Manhattan 82:10 March 85:10 margin 69:20 marine 163:3 market 52:2 Marriott 1:8 mass 15:4 100:3 material 84:5 87:2

88:5 89:13 90:3,9 106:3 maternal 151:1 158:17 159:5 matter 101:9 107:5 120:5 147:14 157:9 165:17 mature 135:11 mean4:18 13:18 22:3,10 30:19 37:1 43:17 45:22 46:4,20 49:7 51:15,20 52:2 59:11 60:1,21 63:16 65:21 91:17 91:22 92:1 95:22 97:4 99:3,4,22 100:11,12 101:7 110:17 129:22 131:1,8 133:14 138:19 140:4 141:4 145:17,22 152:18 161:4,5,18 164:4 meaning 36:21

45:3 55:14 90:18 90:20 meaningful 163:14 means 28:4 54:3

60:4 90:19 141:15 meant 17:2,19 96:7 152:20 measure 26:2 139:18 measured 93:16 126:4 131:5 160:2 measurement 101:2,12 113:2,7 115:16 122:4,6,20 159:16 measurements 103:11 113:8 122:6,22 143:9 measures 138:10 161:9 measuring 141:15 141:16 mechanism 100:1 136:20 mechanistic 25:10

92:6 94:6 media 24:4 25:15

26:14 30:22 mediated 157:12 157:20 medical 165:10 meet59:2 65:3 96:1 97:5 meeting 1:4 3:4,5

3:11,12 6:21 56:6 58:17 65:4 66:5 67:1,15 73:11 75:8 165:12,15 meetings 42:6 meets 159:9 member 5:17 143:14 146:20 147:6 members 3:7,22

58:19 72:20 73:2 74:4 78:2 102:22 107:18 165:13 member's 142:19 144:2 memo 88:8,12,19

89:1 106:10,12 memories 4:6 memory47:8 58:11 112:9 mention 15:9 47:11

56:1 74:6 76:20 87:7 90:3 143:22 150:10 mentioned 10:21 18:10,12 25:18 26:12 27:14 31:8 36:19 39:5 70:19 71:20 91:6 102:18 115:4 128:5 143:22 151:7,13 merit98:14 merits 156:10 message 57:7 88:1 109:8 121:18 messages 110:2 met 1:8 meters 53:5 method 75:20 90:5 methodological

39:17 methodology 95:3

95:11 122:8 methods 75:18

### 202-234-4433 Neal R. Gross & Co., Inc. Page 179 76:7 86:14 90:2,3 143:8 metric 100:17 metrics 16:15 102:15 mic 82:12 Michael 1:18,21,23

41:12 64:13 107:18 116:2 131:13 136:3 138:16 139:7 140:2 149:4 152:9 154:13 157:4,6 micrograms 19:5 microns 99:8,20 Mike 81:19 milestones 165:13 mind 23:5 83:10

90:1 160:15 minimum4:20 minor43:4 113:11 minute 123:3 minutes 5:7 6:7,14 107:14,15 mirror70:1 missing48:7 91:11

91:12 mix 55:2,6 mixes 55:8 mixing 67:10 79:9 mixtures 55:19 mobilization 10:8 mode 53:8,17 55:14

55:14 79:4,4 model 15:2 25:8,16

35:16,18 51:21 54:14 62:11 109:18 112:19,22 114:5,17 158:17 158:18 modeled 11:21 12:10 19:13,15 24:8 112:17 modeling 11:17 13:21 22:4 23:2 24:11,13 25:1,10 28:15 33:21 47:16 49:16 79:7 110:4 models 15:9 27:14

75:3 116:13 151:2 158:19 159:20 model-based 110:6 114:14 modified 39:10 modify 80:4 moment 149:7 monitored 24:9 monitoring 5:6

24:7 25:14 68:20 69:2 70:18 75:13 75:15 76:6,7,9,15 115:15 monitors 70:20

71:14,21 75:17 month 70:22 morning 3:6,13 4:7

6:7,13 75:13 77:17 motivated 146:17 move 7:10 69:21 137:6 162:8,9 moved 74:4 moving 136:20 mucous 120:17 mud 92:9 muddle 161:4 muddled 122:1 multi 76:10 multidimensional

27:22 multimedia 18:7,8 multiple 27:13 multi-pathway 18:8 multi-pollution

90:9 Murphy 1:19 6:3,5

20:17 39:3 40:15 47:10 54:11 55:17 57:13 59:8 66:15 67:10 68:1 71:2 72:15,17 73:21 N NAAQS 52:1 78:19 88:13 name 54:17 national 25:19 nationally 22:22 naturally 8:14 nature 54:5 69:9

78:16 126:18 near 8:17 19:21

21:10,18 53:3,9 54:6 55:19 56:7 56:10,20 57:1 86:22 necessarily 22:12

34:5 38:22 51:16 76:1 78:7 84:2,14 124:20 131:21 152:15 155:2 need 5:2,14 18:3

23:16 35:14 57:14 71:18 84:2,14 88:22 89:7 100:11 102:19 103:3 106:12 117:15 139:2,9 140:1,20 141:5 152:7,12 153:5 154:17 155:4,22 needed 16:12 17:18 18:8,9 141:10 145:9 161:14 needing 123:10 needs 5:11 86:3

99:2 112:11 114:18 119:5 128:17 138:7 141:3 145:3 147:8 147:20 163:12 negative 93:7 neighborhood 19:20 61:2 63:11 neighborhoods

56:16,17 nervous 124:14 125:6 never76:4 151:14 new 6:12 28:22 29:6,11 30:8 41:3 62:4 66:2 70:19 75:2,2,20 110:10 110:11 163:7 newly 6:10 news 153:13 NHANES 32:7 NHEXAS 32:7 nice 129:9 nicely 102:1 121:10 126:20 162:18 night52:20 151:17 non 16:20 23:12

38:19 102:1,6 non-air 32:12

37:22 non-linear 23:6 non-linearities 15:12 17:1 18:2 non-shaded 12:9 non-source 56:12

56:14 normally 52:21 North 1:9 notable45:6 128:5 note 34:7 97:14 noted 56:19 113:8 114:9 notes 58:3,8 106:2 121:6 notice 57:19 notion 159:5 NRC 80:22 nuance 162:4 nuanced 158:13 160:6 161:12 nuances 14:15

23:18 77:20 142:11 146:22 number 8:19 10:14 15:15 22:9 32:7 41:9 61:4 73:12 107:9 125:14 126:14 129:1,16 137:9 numbers 85:19

93:2 105:4 121:17 O OAR 66:12 objective 16:1 objectives 7:6 observed42:10 124:20 127:21 obviously 7:6 8:14

9:2 10:19 12:2 13:2 14:16,21 16:1 24:19 28:6 30:9 35:3 38:20 40:5 43:18 51:20 63:3,10 100:1 136:22 152:7 160:8 occasional 92:14 occasionally 56:18 occur 58:20 127:21 164:10 occurs 8:13 October 65:4 offer 5:18 54:11

78:3 123:5 Office 1:25 offline 58:8 59:1 offspring 159:18 oftentimes 161:3 oh 39:3 58:21 85:15 101:3 105:10 132:15 158:9 163:10 okay 3:13 5:11,15

6:1 7:3,5 15:20 39:2 40:13 41:9 41:11,13,15 49:9 52:15 57:4,16 58:14 59:5,21 65:7 67:18 70:16 72:5,14 73:9 74:19 75:9 77:7 77:10,11 83:4,8 84:11 85:15,16 88:3 89:4,8 91:15 95:4,13,15 97:13 98:4 101:5,15 102:11 103:22 104:1,13 105:10

### 202-234-4433 Neal R. Gross & Co., Inc. Page 180 105:16 107:1,7 108:5 109:17 115:6 116:17 119:20 121:5,6 123:2,4,16 131:13 139:6 140:2 142:12 145:13 148:4 149:9,11 151:22 152:8 154:11 156:12 157:4 158:9 162:5 163:10 old 74:14 older 10:8 13:3,3

21:22 124:19 127:19 135:1 once 9:20 33:15

34:7,9 60:12 79:8 ones 104:5 117:3 120:15 126:2 open 35:10 58:20

74:3 78:3 90:12 106:8 111:20 116:1 open-ended 89:10 opinion 120:14 opportunity 3:21

6:6 66:7 72:19 76:14 77:15 113:6 opposed 90:18 95:8 104:11 opposite 114:16 optimally 81:6 option 97:15 oranges 138:5 order41:11 154:12 organization 162:17 organize 130:2 orient 68:12 ought49:20 outcome 124:15 126:4 outcomes 125:5,8 125:15 126:15 127:7 128:21 129:3 130:5,7 159:3,19 160:16 outdoor 9:7 11:6,6 14:14 25:16,17 52:10 103:11 outdoors 9:18

50:18 outer44:15 outline 68:9 outlined 126:20 133:2 outset 67:8 outside 3:8 142:4 oval 12:17 overall 13:20 40:9

44:3 52:6,9 60:13 78:13 108:15 111:10 128:1 137:4 overarching 162:2 overlap 132:11 oversight 131:8 overused 161:7 overview 34:7 91:8 ozone 65:20 92:3 P P 86:9 PA 65:14 73:17 page 106:2 132:8 152:1,2 pages 141:4,5,6,12 145:18 147:9 paint 10:7 13:3

23:1,8,17 50:17 60:7 Pam 160:20 panel 1:2 5:12 6:7

6:20 42:6 58:19 59:12 62:15,17 64:5 67:15 72:13 73:10,15 74:21 76:9,10 78:2 99:10 107:18 132:18 133:21 144:22 165:13 panelists 5:16

41:10 119:21 145:2 149:2 panels 142:14 panel's 131:10 paper41:1 88:5 106:3,4 152:3 154:22 155:6 160:21 161:1 165:6 papers 121:13 paragraph 84:16

85:6 94:20 99:3 123:13 162:19 parametric 90:13 pardon 92:8 Park 1:8 parsing 89:17 part 3:19 5:22 10:10 12:8,14 28:12 39:15 42:2 43:14 51:3 52:17 54:15 55:2 72:18 85:7 86:19 89:6 91:2,2,17 101:21 106:21 118:19 133:19 137:22 138:14 140:7 164:12 particle 31:13

54:21 55:6,19 99:18 100:2 102:3 102:6,15 103:20 120:12,14 122:17 122:21 particles 55:2,8

79:12 90:6 99:7 100:4 101:4,6,8,8 102:8 103:19 122:7,9 particular4:9 29:3

32:12 40:8,17 55:12 66:1 96:5 111:2 123:14 128:12 139:22 151:7 164:22 particularly 11:11

30:13 37:17 40:11 63:19 83:15 92:3 125:6 127:8 132:14 particulate 8:18 parts 37:3 44:15 passive 74:21 path42:20 pathway 11:3 12:6 19:3,10 31:4 32:6 32:10,11 35:22 40:8 43:4 52:20 53:11,21 57:5,9 61:6,10,16 62:1 109:6,9 pathways 8:22 10:13,14 11:15,16 11:21 12:12,13,19 12:20 18:4,10,13 18:19 19:7 26:20 27:9 30:12,12 32:12,21 33:17 37:11,12,17,22 43:2,7 44:11,17 45:16 47:19,20 48:1,2,7 49:13 102:2 109:2 patiently 135:22 pause 149:1 Pearson 90:13

91:16 95:1 peer-reviewed

81:14 Pekar 6:2 7:2,3 13:9 15:7 20:18 22:6 36:13 39:11 39:19 43:9 46:18 49:22 51:8 53:22 58:2,21 59:4,13 59:21 62:22 72:15 73:20 penetrate 9:17 penetrates 9:10 penetration 10:22 people 9:2 40:18

79:9 80:22,22 81:22 86:10 87:11 98:17 100:19 105:4 107:9,10 134:22 135:1 151:18 152:6 154:5,17 157:13 157:15 163:13 people's 123:22 127:4 percent 14:1,2,9

53:1 109:19 110:7 114:22 115:4 percentile 61:19 110:18 percentiles 28:2

43:11 44:6 perfect92:17 performance 95:19

96:4,13,16 97:11 97:16,22 period 3:21 persistent9:22 person 142:8 personal 103:10 personally 82:3

91:15 135:8 159:14 perspective 34:4

40:4 43:19 48:19 108:17 110:20 113:16 144:5 perspectives 142:8 Phil41:11,12 62:9

74:4 76:22 80:11 80:15 82:11 94:10 95:16 99:21 102:1 108:6 115:6,12 116:4 121:5 123:5 154:13 157:1 158:5 PHILIP 1:15,16 phone73:2 107:17 107:18,19 108:1,3 149:2 phrase71:4 physics 101:11 pick 93:11 123:21 picked 113:1 120:5 120:19,20 151:20 153:16

### 202-234-4433 Neal R. Gross & Co., Inc. Page 181 picking 92:19

93:10 picture 21:2 105:8 124:4 piece 86:7,11 99:12 106:20 136:19 139:21 pieces 89:14 91:4 101:13 139:17 pilots 81:22 pipes 55:16 154:2 piston 82:21 piston-driven 83:2 pit99:4 place 103:14 164:19 places 27:5 100:18 102:13 114:22 115:3 136:13 plan42:20 66:13

67:7,12 69:1,3 plane79:8 82:18 planes 79:13 82:1 planning 6:9 39:17

66:16 67:13 plausibility 132:3 plausible 91:19

92:7 118:15 play 12:18 46:1

97:3 Please 108:1 plumbing 157:11 plumbosolvency 157:10 plume 24:16 PM 39:12 65:20

98:9,12 101:19 103:11 PM10 93:1,7 96:13 PM2.5 93:1,8 point 3:4 12:18 13:10,13,14,17 14:9 15:17 16:3 16:18,19 17:9 21:18 30:6 37:9 37:14 42:11 44:8 44:10,22 47:1 56:2,10 57:14 58:15 61:13 64:16 78:14 79:1 80:19 81:5 84:15 92:20 93:12 94:5 97:10 98:5,7,13 100:21 102:18 105:1,22 106:1 123:1 133:10,22 136:4 138:2 139:1 144:6 145:7 158:4,7 160:9 162:8,9 pointed47:15 86:6 106:4 116:12 points 2:17 3:6,10

4:3 8:12 15:22 36:8 63:17 75:4 83:18 95:15 104:2 108:7 109:10,11 111:15 115:17 123:6 133:13 135:6,10,12 145:10 147:19 Poirot 1:19 78:5

79:19 88:11 92:12 102:12 104:11,14 106:13 119:22 122:2 policies 57:15 policy 2:14 3:19

6:18,19 7:17 28:13 34:11,19 41:1 46:19 64:5 64:14 65:14 66:4 66:21 67:3,4,21 68:4,11,22 71:1,9 72:14 81:2 118:19 139:20 150:20 policy-relevant

44:20 policy-significant 17:14 poll 5:21 pollutant93:1 pollutants 92:2,18 pollution 8:10 population 18:15 28:2 33:2,12 43:11 44:5 61:3 80:6,8 populations 19:12 19:15,17 149:15 150:2 portion 14:7 23:14

61:10 posed4:17 posing78:12 position 29:16,17

33:22 37:19 38:1 40:10 45:18,21 153:14 positive 134:12,16 possibilities 160:7 possible 12:22

71:16 93:8 94:2 130:19 132:22 134:2 135:6 possibly 72:8 73:18

80:7 93:4 112:10 122:13 post 69:3 posted 3:11 potassium 94:1 potent23:13 150:18 potential 11:9 14:17 22:12 29:2 30:21 31:4,6 34:16 57:1 100:9 102:5 149:14 potentially 11:7 17:16 46:2 74:10 75:22 93:18 100:4 164:10 Pounds 1:20 119:22 121:7 157:7 practice 143:1 preamble 81:13 136:8 precise49:6 predict50:10,16 predicted42:8 predicting 33:2 50:20 predominant 69:8 preface 126:20 preliminary 81:11 154:10 premise 74:22 prepare 68:2 prepared 133:14 present 1:11 7:16

34:8,10 42:7 65:20 66:8,9 71:12 95:9 103:8 103:12 139:4 151:5 presentation 2:12

3:17 6:4 7:6,13,18 15:18 26:10 41:5 49:12 57:18 66:21 69:11,22 70:18 71:6,8 72:3 75:19 77:12 95:17 109:18 presentations

75:12 presented 26:7

28:7 41:20 68:10 88:16 89:14 92:21 95:7 112:3,21 presenting 28:12

28:17 43:13 79:21 90:15 presents 93:19 presiding 1:10 pressure 125:7 135:5 presume 5:13 presumed 55:1 pretty 7:8 20:8

44:18 50:12 52:8 55:13 80:20 86:15 87:21 102:1 105:14 prevented49:15 prevents 157:18 preview 66:5,12 previous 42:6

65:19 162:20 primarily 8:18 36:20 53:11 primary 20:3 21:9

24:12,19 25:13,22 41:4 53:21 62:3 69:18 74:9 100:15 prior73:22 priorities 83:21 prioritize 125:21 priority 84:9 124:3 probabilistic 18:14 probably 15:17 16:18 27:3,5 28:4 44:12 50:21 52:13 53:8 65:4 80:2 81:8,18 106:21 111:8 120:13 122:13 123:9 137:6 144:16 146:20 148:6 161:7 problem43:3

96:15 136:9 138:1 138:14 146:1,2,2 146:3 165:9,10 problems 88:15,20 128:8 procedure 65:16

84:11 process 51:14

52:17,18 65:13,19 87:4 88:14 119:19 133:1 producing79:3 production 101:11 profile 50:22 promulgations 120:4 propeller 82:18 proposal 36:3 propose 94:18 107:1 protecting 69:20 PROTECTION 1:1 protocols 127:12 provide 3:21 7:19

### 202-234-4433 Neal R. Gross & Co., Inc. Page 182 32:17 34:7 47:22 59:17 64:17 65:5 72:4,7,19 77:6,15 81:2 94:20 109:14 116:9 118:20 123:11 131:22 142:1 145:17 147:18,22 148:1 provided 108:18 162:21 163:7 164:11,16 provides 143:15 providing44:1

47:21 64:2 70:14 110:19 146:3 provocative 153:8 153:12 proximate 26:22 psychologist 142:6 psychometric 127:9 public 1:4 3:8,22

5:17 35:3 58:18 59:20 69:13,15,20 72:21 73:2,5,7 124:15 133:21 published 8:1 28:7

28:21 32:8,9 34:13 48:10 93:4 106:19 138:20 151:11 pull 58:5 71:3,5,11 pulled41:2 pulleys 139:14 pulling40:22 pure 63:15 purpose 68:11

72:21 90:14 purposes 121:14 push 23:7 44:14 put48:20 61:11

66:20 75:21 83:6 85:19 87:17 89:11 101:13 111:3 puts 96:15 putting 29:21 67:2 104:9 P-R-O-C-E-E-D-... 3:1 Q qualified 151:5

160:7 qualitative 36:5,20

37:20 39:6 41:19 60:13 65:1 119:3 qualitatively 46:8

52:13 quality47:17 48:5

48:14 49:1 68:17 71:4 79:7 117:19 152:14 quandary 59:7 quantify48:8 quantitative 36:6,7

37:21 41:19 65:2 119:3 quantitatively

22:10 question 30:3 42:5

43:10 46:13,19 52:18 53:12 54:5 55:5 57:10 64:11 69:18 78:12 81:21 83:11,12 84:13,18 85:8 94:9 97:3 99:13 107:15 115:9,10 123:4 129:11 133:8 141:21 142:18,22 143:3,13,21 144:2 146:21 147:8 156:11 157:13 162:13 164:13 questioning 94:14 questionnaire

160:1 questions 4:1,10,17

4:21 5:1,3,18 23:22 35:12 41:10 64:4,18 67:19 68:22 72:12 75:14 83:5,8,18 85:5 91:13 104:7 107:13 108:10 111:20 130:3 132:17 141:1 149:12 150:9 159:11 quick 3:4 41:14

97:14 quicker 97:3 quickly 7:10 29:6

162:3 163:13 quite 80:7 81:17

86:8 96:7 100:20 114:4 136:8 162:13,17 R R95:1 RABINOWITZ 1:21 81:20 157:7 radius 20:6 21:10 raise 13:14 73:15

92:20 133:9 158:4 raised 51:18 66:22 raising 55:5 57:14 range 11:14 14:1

23:14 27:8 38:9 49:3 102:6 117:3 118:15 135:2,4 ranged 14:8 ranges 19:8 26:7

47:22 49:2 98:9 98:12 112:8 rank 90:8,12 94:17

94:22 95:9 rapid 114:15 rat 151:2 rate 78:15 114:11 rationale 117:16 REA4:4 6:9 64:4

64:22 66:3,16 67:13 72:9 73:16 74:1 118:18,21 reach 60:14 133:4 reached 129:19

132:20 134:3 reaction 117:4 read 84:15 89:16 91:7 152:12 153:1 155:10,12 165:6 readable 89:19

109:21 reader 94:20 110:1 readily 9:21 reading 89:16

116:14 133:11 155:5 163:18 ready 84:22 real43:21 50:2

53:4 138:10 realize4:21 116:5

129:6,15 realizing 125:19 really 7:14 10:15

12:7,17,22 13:10 16:12 17:20 19:22 20:7 23:10,17 29:13,15 30:2,5 30:10,14,16 31:9 31:21 32:16,18 33:15,22 36:12 37:15,18 40:21 43:9,15,17 44:17 45:18,20 46:5,11 49:22 51:2 61:1 62:3,11 82:20 83:21 84:7 87:1 87:12,19,22 89:4 89:18 92:13 96:11 99:3,7,9 101:17 111:22 113:21 115:19,22 117:6 117:11,15 119:7 120:6 132:7,8 133:20 136:14 139:2,11,19 140:1 140:12,19 142:19 143:14 146:15 156:10 161:2,11 164:4 REAs 39:9 reason43:14 91:19

92:7 100:13 reasonable 31:20

75:4 124:10 125:12 130:21 136:8 reasonably44:1

139:12 reasons 102:7

119:14 148:6 recall 6:8 53:1

59:14 receive 59:19 70:12 received 73:5 receiving 103:3 recognize71:16 recognizing 112:13 recollection47:5 recommend 76:17

117:6 149:15 164:13 recommendations

108:11,16 recommended

106:9 reconfigure 130:11 reconsider71:18 record 107:5

165:17 recovery 96:5 reduction 12:3,11

12:12 reductions 114:1,2 redundant 146:8 reevaluation

163:17 refer 89:20 119:3

122:20 143:3 145:1 reference 113:6

121:16 144:22 referenced 118:22 references 89:20

121:11 146:11 147:22 refers 85:6,14

144:2 refine 28:9 31:21

32:19 46:5 refined 8:6 37:15

57:20 58:1

### 202-234-4433 Neal R. Gross & Co., Inc. Page 183 refinement 34:5

45:6 refining 29:9 reflect 12:11 15:15

22:10,20 27:18 61:4 63:6 129:14 130:18 160:7 reflected 23:1

26:10 129:20 reflecting 26:8 60:9

75:11 reflections 5:5 reflects 149:18 regard 69:1 145:2 regarding 3:18 5:6

72:14 73:16 124:15 126:13 127:20 regardless 42:14 regional 25:19 regionally 22:22 regression 15:14

25:15 reiterate 13:17 relate 16:4 55:6

109:9 122:6 related 9:1 26:18

32:13 36:8,9 42:17 49:17 52:20 60:19 74:1 76:22 77:16 105:21 126:12 139:20 150:3 156:9,22 159:5 162:20 165:7 relates 150:8

158:13 relating 25:16 45:8

51:11 164:8 relation 129:2 relationship 91:20

92:1 113:19 115:15 relationships 91:21

111:12 relative 23:9 24:18

42:11,15 43:4 45:13 50:5 113:11 relatively 9:19

13:18,19 125:17 release 65:13,14 released 10:3,5,9

12:18 relevance 98:11

108:17 relevant28:21

35:20 44:12 68:22 87:10 88:6 155:1 remain 62:2 remainder73:10 remaining 150:13 remains 31:14 remarks 72:20 remember49:14

54:17 76:4 remembering

78:11 remotely 93:8 remove 88:2 removed 87:14,16

159:14 renal 128:21 129:3

130:8 reorganization

150:2 repaired 88:22 repeat 85:12 repeated 120:13 repeatedly 127:3 reported 94:22

95:1 reporting 120:6 represent 14:11

21:20 55:8 110:22 representation

124:10 representative 21:2

22:22 represents 100:9 reproducible 99:6 request 112:1 requests 73:5,6,7 requirements 59:2

96:2 requires 160:18 Research 1:8 reservoirs 11:11 residential 9:9,14

13:4 14:3 25:5 31:22 33:12 37:2 38:18,20 50:8 52:11 residents 29:14 residual 74:7,12

126:8 respect 131:22

133:12 137:2 152:10 159:10 respiration 54:14 respond 162:15 responded 143:21 responding 64:10

89:12 142:17 response4:10,22

11:22 16:22 23:6 27:16 58:6 64:17 75:3 85:11 94:8 104:7 111:19 129:21 132:17 133:7 140:22 142:20,21 143:20 145:1 147:2,7 responses 4:14

65:6 83:7,19 responsive4:20

115:10 rest48:18 163:19 restraint 158:18,19

159:2 161:17 result 8:21 48:9

128:20 resulted 27:21 results 7:16 15:19

81:12 89:18,22 90:17 92:16 94:14 114:16 126:7 resume 107:2 resumed 107:6 return 83:5 review 1:2 3:16

4:11 6:9,10,16,19 7:17 11:18 15:19 64:17 65:9,13,15 65:18 67:12 69:1 69:17 70:2 73:19 74:16 76:8 81:16 84:2,3,4 85:11 88:13 106:14 128:18,21,22 146:13 147:18 161:2 reviewed 121:13

126:3 154:4 reviewing 133:1 revise 70:12 152:20 revised 129:12

143:19 revising 144:8

156:21 revision 117:20

134:3 141:9 142:3 143:18 149:22 158:5 163:17 revisions 149:13,15

164:14 revisit 69:2 revisiting 86:14 reword 122:19 re-analysis 95:8 Rich 52:19 78:4

88:10 92:11 102:11,21 104:3 106:4 119:22 128:6 RICHARD 1:13,19 Rick 82:4 131:14 135:21 137:20 141:6 151:10 158:11 ride 81:22 right7:4 12:9 20:6

39:12,14 59:21 64:4 65:11 71:2 73:9 75:9 76:1 77:12 85:3 88:13 92:5 97:21 106:18 112:13 123:16 131:6 132:20 135:13 145:20 149:10 150:16 152:8 155:9,17 156:3,8 158:9 160:12,21 right-hand 11:4

14:18 rigorous 96:14 rigorously 118:17 ripples 48:17 risk 2:12 3:18 6:12

6:14 7:6,16,20,21 8:1,2,5,8,10 9:1,8 10:1,15 11:15,22 12:10 13:20 14:3 14:12 15:18,22 16:12 18:1,6,21 21:21 24:1 26:1,4 26:11 27:7,8,20 27:22 28:7,11,12 28:15,17 29:3,10 31:1,5,6,9 32:22 33:4,7,19 34:10 34:15 35:2,4,16 37:5,6 38:8,9,10 40:9,12,21 41:18 42:7 43:12,14,17 44:6,13,20 45:10 45:22 47:21 48:4 48:22 49:2 60:16 61:8,9,18 62:19 65:21 67:8,19 69:5,11 74:7,12 74:13,18 77:18 117:1 150:16,19 154:9 risks 20:1 road 159:10 robust99:6 robustness 126:11 rod 140:19 rodent 159:20 role 12:19 13:1

36:6 46:2 127:17 153:3 Roman 1:18 162:10

### 202-234-4433 Neal R. Gross & Co., Inc. Page 184

room 5:19 68:6,7 route 146:5 rubber 159:9 running 141:11 runway79:5 S SAB 1:25 safety 69:21 Salon 1:8 sample 102:10 sampler 95:19,20

96:1,3,13,21 97:2 97:2 samplers 96:19 samples 86:10 sampling 75:18,20

86:14 90:5 95:17 satisfied 66:10 satisfy 81:15 save 146:7 saw 104:6 154:11 saying 29:22 50:2

57:7 62:19 66:7 79:11 87:2 116:17 116:20 119:6,17 135:19 136:3 138:16,20 143:7 144:10 152:22 155:14,18,18 says 21:15 64:15

94:21 scanned 85:13 scenario 21:3 36:11

38:17 48:14 51:17 53:10,12,20 54:8 56:3 57:10 101:12 scenarios 14:3

20:19 31:22 47:17 48:5,10 49:1 53:14 54:19 55:1 56:14 78:1 schedule70:8 scheduled 5:10

6:21 70:15 Schmidt 88:8,12

106:4,15 science 75:5 117:5 118:12 science-based 94:6 scientific 1:1 153:18 scientifically 116:22 118:1 scope 82:20 86:17 scoping 65:21 scores 137:12 screen 3:9 83:6 148:22 Sean 1:15 108:3

149:5 season 93:21 seasonally 93:20 second 11:3,5,18 15:10 19:15 36:15 66:11 70:14 93:21 144:6 164:4,12 secondary 70:3

74:9 seconding77:8 seconds 123:3 section 69:13 85:19

90:10 108:13 109:1 113:7 124:14,17 130:9 136:11 140:10 162:18,21 sections 109:15 136:13 see4:9,13,18 10:17 10:19 12:2 24:17 34:3 35:14 48:15 48:16 55:5,18 64:14,21 68:3 69:14 71:6 72:15 76:21 81:1 92:10 94:14 108:6 139:14 142:5,8 143:4 145:1 149:2 152:6 153:7 156:22 158:16 159:13,15,22 163:13 seeing 67:20 70:6 114:17 140:20 seek 102:14 seen45:20 selection 112:22 117:12 self 151:1 158:14 158:21,22 159:5,6 159:15 160:20 semi 37:20 semi-quantitative

36:21 send 59:11,18

65:10 151:10 sending 165:12 sense 5:9 57:12

90:15 92:19 100:17 105:11 113:16 124:5 134:4 136:11 141:22 142:10 150:17 156:18 158:21 sensible 77:2 sensitivity 36:6 117:2 sentence 101:18 116:20 152:17,17 sentences 109:14 separate 64:7

73:18 September70:6,11 serious 139:3 153:13 services 139:22 set25:2,20 30:5

40:20 41:2,4 93:13 96:22 101:1 108:9 sets 24:5 55:20 63:6

63:20 72:2 88:18 139:4 setting 9:14 50:3,4

51:10 settings 25:21 seven 107:11 148:13 162:8,10 seven-member 76:17 shading 11:5 12:1 sheds 52:4 shift45:2 shifts 31:4 short22:17 99:2 109:5 125:17 130:4 short-term 80:20 show 80:2 140:11 140:13 showed70:8 92:22 showing 3:8 53:3 shown 3:11 shows40:8 70:8 112:4 side 10:19 11:4 12:10 23:4 44:4 signal 10:11 13:12

23:13 47:18 48:7 50:19 significance 124:16 significant4:19

28:16 29:18 73:14 100:9 102:5 104:5 104:19 similar7:12 38:18

39:8 44:2 92:13 98:1 103:18 132:8 similarly 128:21 161:9 simple 105:15 simply 18:16 151:11 simulate 19:5

22:14 48:3 51:19 60:11 61:9 simulated 12:4,6 19:18 33:3 47:17 48:11 Simulating 31:7 simulation 18:19 simulations 15:3

42:2 47:16 54:1 single 66:4 118:4 138:14 sins 96:11 site-specific 26:2 situation 23:11

32:2 38:21 41:7,8 situations 34:18,18

35:2 62:15 159:7 163:5 164:7 six 107:11 141:6 148:13,19,22 151:15 153:5 156:5 158:10 size 31:13 54:21

87:20,20 88:15 90:2 98:9,12 99:18 100:3 102:3 102:16 103:13,20 120:12,14 122:21 sizes 55:12 96:5 101:19 102:6 skip 158:5 skipped 128:10 slide 34:6 36:9 70:7 slides 68:2 163:10 slightly 61:19 slope 17:16 103:17 110:15,21,22 111:11 112:2,14 116:10,13 117:7 117:14 118:4,15 118:22 120:5 slopes 109:13 115:16 116:9,18 slower48:18 small 13:19 28:4

52:22 81:20 86:9 104:2 smaller 17:13

33:13 63:10 smallest 120:15 smelter 20:3 21:9

24:12,19 25:13,22 54:19 74:9 79:18 smelters 8:17 53:14

53:16 56:16 Smith 146:13 smoke 91:4 94:2 snake 99:4 snapshot 110:3

### 202-234-4433 Neal R. Gross & Co., Inc. Page 185 society 78:13 soil 9:6,7,18 11:7,9 14:22 15:4 25:18 25:21 26:1,17 30:9,20 37:1,1,2 45:2 48:8,17 49:18 50:5,9,11 52:9 53:9 120:21 sole 136:17 solid 117:15 somebody 155:4 157:5 somewhat 60:15 121:22 sophisticated 25:7

25:8 sorry 20:19 39:3

56:11 59:4 68:7 82:4 85:21 157:5 163:9 sort7:10,11 8:5 10:15 11:3,12,14 11:17,19 12:16 13:11 16:7 19:19 21:7 22:14 25:11 25:19 26:8,14,15 26:21 27:21 28:9 29:4,22 30:3 32:14 33:6 34:7 38:3,14,17 39:22 40:3,6 43:15 44:1 45:14 46:4 50:11 50:19 51:13 52:2 58:10 60:13 61:7 63:8 71:7 73:15 74:21 78:15 80:5 91:13 92:6 101:14 123:21 124:4 126:19 127:8 128:3,10 129:4,5 130:11 136:7 137:7 140:19 147:4 sorts 161:9 sounds 95:13 source 55:15 56:14

62:3 78:7,17 79:17 80:1 101:3 101:6,7,7 sources 8:15,19 11:12 21:18 43:1 55:10 68:16 78:10 79:22 80:3,7 104:4,15,15,22 105:1,2,14 113:12 142:4 source-oriented

72:7 104:20 sparse 106:22 spatial 20:10,20

21:13 24:10,14 29:14 speak 37:4 40:7,17

41:16 46:8,13 47:9 58:10 59:14 113:17 speaking 9:13 29:9

37:16 38:3 speaks 132:7,14 Spearman 90:8,12

91:16 92:14 94:17 94:22 95:9 specialty 142:2 species 93:1,17 specific 31:5,15

39:21 53:12 63:20 63:20 102:13,20 103:5,7 114:18 127:3 130:3,7 159:11 specifically 36:10

85:4,18 specification 97:22 specifics 125:19 spend 5:7 spirited 52:19 spoken 128:2 154:6 spotted 74:17 108:20 spread 22:19 33:7 St20:15 staff 1:25 5:16 41:1 standard 11:19 19:21 20:9 21:8 22:18 24:22 30:1 33:6 46:20 48:16 51:4,9,15,16 56:7 69:18,19 70:3 96:13,16 97:9,11 100:13,14 117:20 stands 76:4 80:19 stark 114:19 start4:5 10:18

44:14 83:9 84:22 100:8 103:14 164:19 started 3:15 24:17

39:13 107:8 starting 80:18 state 75:5 statement 113:12 125:13 136:16 153:9,12 statements 131:18 statistical 25:16 statistics 103:13 statutory 76:17 stay 120:16,21 steeper 17:16 step 47:2 105:13 112:6 116:16 119:15 stick 100:6 sticking 106:19 sticks 92:10 stomach 100:7 stops 114:13 story45:9 strength 128:13 140:7 150:7 strengths 126:16 stress 151:2 158:17 158:18,19 160:3,4 160:4,5 161:7,17 161:17 stressors 159:17 strikes 78:6 strips 157:18 stroke 105:8 strong 119:7 132:1 156:9 stronger 118:16 strongly 131:19 135:16 struck 78:16 structure 35:15 structured 39:7 STUBBLEFIELD

1:21 studies 16:8,17 19:13,14 20:14,15 21:5,12,14 24:6 25:5,7 32:8 34:22 39:21 53:2 54:1 59:10 95:9 103:9 103:12,18,21 111:2 126:10 128:4,6 134:21 138:20 140:8,11 155:8 164:18,21 study 18:7,15 19:18

20:4 21:6 24:21 25:6 28:1 29:20 31:10 32:1 38:12 54:19 57:4 61:4 63:20 80:17 81:1 81:6 86:7 118:16 126:3,6 141:14 151:7 153:20,21 165:1,8 stuff63:10 65:10

74:15 87:9 90:18 90:20 140:14 subcommittee 76:7

77:3 subject 164:22 subsections 109:3 subsequent 11:1 substantial 44:19

75:2 substantially 100:5 subtle 161:12 sub-disciplines 142:9 sufficient 130:16 135:4 sufficiently 96:14 129:20 155:21 suggest 106:6 114:15,16 116:5 121:7 154:7 suggested 13:21

77:20 79:20 89:1 113:9 suggesting 78:12 120:3 154:20 suggestion 95:14 103:6 109:20 112:6 113:3 122:18 147:13 suggestions 76:22 104:1 123:15 suggestive 94:2 suggests 40:1 summaries 89:21 summarize 84:14 111:19 162:22 164:17 summarized 35:13

87:22 163:12 summarizing 69:6 125:18 summary 3:10

52:17 103:8,13 106:2 109:8,22 111:9,15 129:10 143:11,12 162:21 summer 6:8 superficial 137:22 Superfund 51:21 support75:2 76:13 110:5 150:6 supportable 157:1 supporting43:15

43:22 supports 110:4 131:19 sure4:16 5:2 7:4

40:18 46:7 49:22 51:5 55:20 58:21 62:5 74:16 83:1 83:12 84:9 85:2 89:5 100:20 103:12 104:6 105:10 108:8

### 202-234-4433 Neal R. Gross & Co., Inc. Page 186 115:8 117:10 118:3 121:18 123:20 124:3 125:11 138:17 139:2 144:8 145:20 152:6 156:1 surface 11:12

31:16 50:11,15 surfaces 8:21 9:6,9

9:17 11:1,6 Surkan's 160:20 surprised 140:21 Susan 1:17 123:18

140:4 145:14 160:11 susceptible 26:21 suspect 160:20 sustained 138:21 swamping43:6 synthesis 83:14

84:20 89:17 105:19 108:11 109:7,15 111:16 115:11 123:11 146:15 148:9,11 163:14,15 synthesize 110:12 123:15 synthesized 163:20 synthesizing 95:6 system 124:15 125:7 126:9 157:11 systematic 39:20 133:2 T table 3:8 29:4

48:21 87:12,13 92:21,21 103:9 106:10,12 109:22 110:5,11 112:4 117:15 119:11 137:5 141:9 164:16 tackle43:2 tail 55:16 tailpipe 53:16 tails 60:6 take 6:6,14 21:16

24:2 40:5 54:10 63:17 68:21 72:11 74:20 76:14 79:2 98:20 107:2 116:16 119:15 140:12 153:20 taken 70:22 takes 112:2 141:20 take-home 109:8 take-off79:4 talk 6:7 7:14 14:16 17:4 18:1 22:7 23:4,19 39:6 43:11 45:11 58:7 58:12 60:10 61:17 75:11 82:20 90:9 100:14 107:12 122:3 127:15 130:10 135:14 148:18 talked 4:8 15:16 17:22 34:21 42:5 43:13 62:16 68:15 86:15,15 104:3,17 110:13 125:20 128:12 129:6 137:20 143:16 talking 9:3 26:22

38:18,19 44:5 50:3,13 54:22 58:5 64:1 67:8 85:22 122:9,15,19 139:10 141:18 tease 12:22 41:21

44:17 61:15 62:1 teasing42:21 60:18 technical 12:15

49:15 99:14 164:2 164:3,20 technically 86:18 technique 95:12 technology 76:9 telephone 1:25 5:20 tell 67:21 69:15 143:18 155:12 tempered 128:19 temporal 50:22 ten 17:11 112:9 122:10 152:1 tend 55:9 60:8 79:9

83:1 113:18 tended48:12,20 tendency 18:17

22:20 25:20 33:4 33:12 44:13 60:7 61:10 118:14 tentatively 98:18 term 15:8 24:18 terminology 127:5 terms 9:1 11:22 12:11 14:16 15:20 18:22 19:12,14 20:6 24:3 25:17 33:20 38:2,10 39:9 40:9 43:12 44:6 46:9 47:4,11 50:8 52:2 54:4 89:15 94:13 96:15 99:17 100:18 124:11,14 126:10 127:10 128:22 144:21 147:20 150:6 151:5 157:3 terrestrial 163:2 testing 96:21 127:12 tests 127:9,12 tetraethyl 82:1 text 110:10 112:3 114:10 128:17 137:9 152:1 texts 114:16 thank 3:14 6:4,5

35:9 57:18 58:13 67:17 72:16,17 149:7 165:14 thanks 52:16 57:16

57:17 85:2 162:12 theme 108:9 113:1 123:10 themes 129:5 theory 159:4 they'd 82:14 thing 23:5 28:5

40:19 51:8 54:12 54:12 56:1 78:15 78:16 98:2 116:6 137:14 138:14 141:17 164:1 things 22:2 29:19

34:21 44:4,4,14 44:18 45:4,8 47:8 47:11 51:22 56:15 63:7 64:6 67:16 68:14 80:13 83:13 83:21 93:10 94:10 95:22 115:14,19 115:21 118:14 124:3 131:4 135:1 137:6 146:7 147:3 161:19 think 5:1,12 7:10

8:11,12 13:15 16:19 18:22 23:22 26:11 28:22 29:8 29:15,18 32:3,10 33:9,10 34:2 36:20 37:9,22 38:2,4,12 39:19 40:1,14 41:10 43:10,13 44:10,22 45:1,9,18 46:22 47:4 52:1,5,7,21 54:7,15,22 55:3,7 55:9 56:8,13 57:5 57:8,11,13 58:15 60:2,13 62:7,22 63:1,14,19 64:12 64:19 66:6 67:6 67:20 72:21 73:19 75:7,10 76:5,8 77:5 78:22 79:2 79:10,16 81:15 82:16,17,22 83:1 83:9,22 84:4,8 86:2 88:9 91:11 91:14,15,17 94:12 95:11,18 97:4,11 98:16,18 99:1 100:11 101:15,16 101:18,22,22 102:12 104:2,16 104:20 105:9,19 106:20 107:17 108:9 112:8 113:9 114:1 115:9,12,18 116:16 117:17,18 118:18,20 119:7 119:14 120:1,8 121:3,15 122:22 123:9 124:2 125:2 125:4 126:1 127:2 127:15,16,19,22 128:16 129:4 130:1,3,8 131:2,2 131:8,15 132:5,8 132:9 133:12 134:9,15,16 135:3 135:20 136:16 137:13 138:3,6 139:2,18 140:9 142:7,16 143:1,6 144:6,11 145:15 146:10,11,17,18 147:3,4 148:6 149:21 151:18 152:12,15,18,19 153:2,5,7,15 154:10,16,17,19 154:20 155:1,2,13 156:4,11,13,21 160:6,14,17 161:10,11,14,16 162:7 163:11,20 163:21,22 165:1 thinking4:15 78:6

80:4 89:16 95:16 119:12,19 122:3 134:7 third 14:11 84:1 163:18 thought53:10

82:13 87:15 93:14

### 202-234-4433 Neal R. Gross & Co., Inc. Page 187 112:5 116:3 123:21 124:6 thoughts 74:19

77:11,16 83:3 98:16 123:6 142:13 148:16 three 21:5 83:9

85:5 91:1 103:1 105:17,17,20 113:18 115:13 121:4 139:17 145:18 148:14 163:1 three-page 146:19 throw 148:10 throwing 92:9 tie 158:19 ties 86:5 tight24:15 tighter 63:11 time 3:14,20 7:12

24:2 28:3 43:14 43:18,19,19 47:1 65:5 71:12 73:4 73:10 75:5,7 78:11 79:2 81:16 82:10 86:21 89:2 90:12 97:10 108:22 123:17 133:17 134:10 137:1 142:20 145:21 151:20 161:1 162:8 163:18 times 128:2 131:16 timing 81:5,7 tiny 141:14 today 3:5,9,11,16

7:14,19 52:21 73:22 104:18 123:8 told 157:9 tools 101:2 top 10:17 topic 6:20 67:14

77:17 78:3 83:4 88:8 91:4 108:13 110:9 topical 39:20 topics 73:12 111:16 total 14:2,9,11,20 17:3,19,20 18:3,9 27:8 43:1 60:15 60:16 61:8,9 115:2 totally 94:13 95:11 touching 15:22

68:14 toxicology 124:13 track4:13 Traditionally

86:18 transcripts 67:1 translate 16:16 translates 111:13 transparency 126:13 129:16 132:21 136:5 transparent 126:5 130:15 transport 35:21 transportation

82:8 TRB 80:16,22,22 treated 128:15 trends 113:19 triangle 1:8 17:11 tried 27:18 49:7 125:16 159:1 true 101:21 127:8 127:10 try 7:11 18:20

41:13,21 42:4 44:14 58:22 84:13 103:19 123:5 147:7 158:15 159:8 trying 21:2 39:16

69:14 71:10,15 91:22 102:9 110:14 121:2 123:21 127:11 141:8 145:8 164:15 TSB 86:13 TSP93:1,6 100:13

100:14 113:8 120:22 122:5,8,22 tuned40:18 turbo 83:2 turboprop 82:19 turboprops 82:14 turn 6:2 7:1 turns 65:3 tweak45:16 tweaking 26:19

46:4 two 21:10 42:6,17

48:14 53:2 67:4 67:16 68:1 70:9 71:17 81:19 83:17 84:6 89:5 91:4 96:10,18 97:12 98:15 105:18 107:18 108:14 111:9 115:14 132:6,8,12,12 133:2 141:4 148:15,18 149:11 149:20 151:14 152:18 153:4,9 156:10 two-kilometer 20:5 tying 83:16 type 55:10 141:19 types 19:14 31:13

38:7 44:2 48:21 63:7 typical 65:16,18 158:17 typically 79:4 159:18U ultimately 110:14 116:10 117:17 uncertainties 34:16

36:1 42:3 43:21 110:20 111:4,13 129:1 uncertainty 8:7 27:18,19 28:10,16 29:2,19 30:21 32:5 35:6 36:5,7 41:20 42:1 43:3,5 43:6,7,12 44:8,12 44:21 45:7 46:6 46:12 60:18 62:3 65:1 111:3 119:2 uncomfortable 118:3,10 underestimated 14:17,20 underestimates 113:11 underlying 35:17 underneath 139:14 understand 29:2

30:17 32:4,11 33:9,14 35:8 39:16 49:11 59:10 89:21 110:1,14 156:5 understanding 8:6

28:9 29:10 30:16 34:15 35:1,6 41:7 42:19 46:11 62:10 81:5 103:16 106:11 109:12 112:18 117:8,11 127:6 129:2 131:10 142:10 150:14 understood 72:6 unfortunately

63:16 uniform 21:6,8 unique 55:13 unit 17:12 unshaded 11:4 unsure 98:6 untraditional 87:9 upcoming 66:6 uptake 11:9 22:12

51:22 up-front95:3 124:5 urban 19:18 20:14 21:3,6,11,15 24:20 25:4,6,21 25:21 29:20 31:22 38:12 50:3,4 51:10 54:18 55:1 55:8,11,13 56:12 use 22:18 32:5,19

43:15 54:16 60:20 61:7 69:8 71:5 73:19 81:14 82:1 82:12 88:3 91:18 92:14 94:17 95:10 106:3 109:18 116:11 117:22 useful 32:4 39:13

55:4 63:21 74:11 81:2 88:1 90:21 93:14,18 96:9 101:19 106:6 usually 13:22 16:10

46:21 56:17 57:8 58:7 utility 43:21 101:22 U.S 1:1 V vague 103:4 valid 97:2,3 validating 96:21 valuable 63:18 120:8 value 23:1 33:4

37:2,2 143:15 values 22:16 47:4

60:1,8,12,16 116:22 119:12 Vandenberg 86:6 144:1 Vanderpool 76:2

87:2 Vanessa 1:25 142:13 144:9,18 147:16 variability 22:21

61:2,5,6 62:12,12 63:14 variables 63:13

### 202-234-4433 Neal R. Gross & Co., Inc. Page 188 variation 20:20 varied 57:3 variety 63:6 various 12:19,20 16:14 24:4 25:15 42:2 101:19 110:20 119:14 vary 15:3 92:4,6 varying 21:16 version 114:6 140:20 versus 19:6 47:12

54:19 64:21 79:18 90:12 95:19 127:10 128:14 view76:20 138:3 139:2 vitro 153:20,21 vivo 154:15 Von 1:22 119:21 120:1 VU 1:25 65:17 67:6

67:17 144:20 147:17 vulnerable 22:1 W wait 64:21 waiting 120:21 135:22 157:6 walk 108:6 walks 161:22 wall 92:9 want3:14 4:16,19

22:8 23:4 24:1 30:16 40:18 54:10 58:10 73:3,14 74:3 76:20 82:11 83:10,11 87:12,14 99:15 102:8,14 108:2 111:16 115:8,10 117:6,12 122:11 123:5 125:11 131:14 133:6,15 142:21 143:19 144:18 146:6 147:15 148:8 149:3 152:16 158:15 wanted 13:14,16 16:19 18:20 35:11 40:14 41:10 64:6 65:8,10 67:21 77:15 93:12 99:13 107:16 116:4,5 124:5 136:4 137:18 151:22 159:8 wants 58:15 81:14 125:21 warrant 6:12 wasn't 38:22 74:17

89:2 91:6 92:13 126:9 130:15 Wasserman 1:22 128:6 139:8 145:15 161:16 Wasserman's 147:1 waste 145:21 water 11:10,12

30:9,19,20 49:19 51:7 154:1 156:14 156:17,20 163:3 wavelength40:17 way7:15,22 27:8

32:5 34:12 36:16 57:2,11 59:17 60:20 73:17 75:21 77:2,5 78:21 80:9 93:9 100:12 102:4 110:19 114:5 126:5 131:5,16 132:8 133:2 136:19 137:21,22 142:2 145:20 153:2 154:19 160:8 163:12 ways 27:17 42:7,18

98:2 100:19 weaknesses 126:16 140:7 website 3:12 WEDNESDAY 1:6 weigh 94:11 133:10 weighed 94:12 weight 129:14,19 130:18,20 131:19 156:8 weighted 80:6 Weitzman 1:23 107:19,20 149:6 welcome 129:8 welfare 69:21 well-framed43:10 went41:6 107:5 129:7 148:5 150:11 165:17 weren't 18:16 21:1

26:19 100:7 127:14 we'll 3:8 4:3,5,10

5:13,14,21 6:14 6:16 14:15 15:17 32:5 34:2 57:14 58:4 63:1 64:14 67:2 68:13 69:4,6 69:10,17,21 70:13 71:10,15 72:2 138:19,22 155:13 165:12 we're 3:15 4:13 5:9

7:15,18 9:3 16:15 18:1 28:5 29:8,15 30:1 32:18 33:22 34:8,9,12 36:15 37:18 38:1,18,19 40:10,22 43:18 45:20 46:2,20 47:14 50:2,3 51:9 60:17 61:12,14 64:1,10 65:9 68:19 71:8 72:18 83:22 85:16 87:3 87:4 90:17 92:19 93:9 94:10 101:1 101:3,19 102:2,9 102:20 103:5 107:22 114:17 115:8 117:13 121:2 122:8 132:19 139:10 144:3 149:1 162:7 162:9 164:15 we've 17:22 28:14

28:14 29:5 34:20 42:5 45:20 62:14 69:12 70:1 72:13 72:22 73:16 81:7 86:14 100:16 101:12 134:10 wide 102:6 wider20:16 21:13

33:13 60:4 61:20 61:22 WILLIAM 1:21 willing 146:17 wind 96:18 window71:7,9 winter93:21 wise 162:9 wish 99:16 wonder 83:6 95:20

98:7,15,21 129:17 133:5 wondered74:10 wondering 36:2 wood 85:21,21,22

91:3 94:1 word 84:15,15 wording 140:5 152:20 wordsmithing4:12 work75:16 76:1

90:19 136:12 140:5 141:20 148:2 worked 114:4 working 87:3,4 works 114:5 158:16 worry79:9 101:4,6 worth74:15 94:8 104:9 worthwhile 109:16 wouldn't46:5

52:13 88:22 116:15 117:12 wrap-up 68:19 write71:12 145:17 146:17 writing 59:18 94:8 written 128:2 146:11 wrong 131:3,9,11 wrote 86:16 132:5 X X 99:20 112:7 Y year 67:12 70:6

80:18 81:18 120:4 years 10:6,6 YEOW 1:23 yesterday4:8 5:6 13:15 61:1 68:15 70:8,17 75:12 77:13 79:20 86:6 87:2 89:2 98:18 104:17 113:2,9 127:4 129:7 130:10 135:14,21 137:21 140:18 143:16,22 yesterday's 123:22 Z Zach 6:2 7:2 13:7

39:5 40:16 41:6 41:16 47:15 57:18 58:16 59:15 64:15 68:3 zero 112:8,9 0 0.06 86:9 0.5 14:1 0.6 14:1 0.99 93:61 1.0 92:17 10 92:22 99:8 135:2

135:4 10:19 107:5

### 202-234-4433 Neal R. Gross & Co., Inc. Page 189 10:35 107:3 10:38 107:6 11 1:6 152:2 11:58 165:17 12 14:8 107:10 12:30 5:10,11,13,14

5:14 107:8,9 15 19:5 15-minute 107:2 165 2:19 18 86:10 2 2A 116:7 2B 122:3 20 107:14 2008 6:16 7:7,16

8:2 31:10 2010 70:21 2011 88:5 2012 1:6 2013 70:15 81:8 21 56:5 23rd 85:10 25 135:2,4 28 14:8 3 3 92:21 3A-13 87:14 3,000 79:8 3.5.3 106:2 3.5.4 90:10 30 123:3 4 4-22 112:1 4-3 103:9 4.1 109:1 4.1.3.3 109:4 4700 1:8 5 50-page 142:21 500 53:5 7 7 2:14 70s 120:4 73 2:17 8 8:30 1:9 8:32 3:2 9 95th 61:19NEAL R. GROSS COURT REPORTERS AND TRANSCRIBERS 1323 RHODE ISLAND AVE., N.W. (202) 234-4433 WASHINGTON, D.C. 20005-3701 www.nealrgross.com C E R T I F I C A T E

This is to certify that the foregoing transcript

In the matter of:

Before:

Date:

Place:

was duly recorded and accurately transcribed under my direction; further, that said transcript is a true and accurate record of the proceedings.

----------------------- Court Reporter 190

Clean Air Scientific Advisory Committee Lead Review Panel

US EPA

04-11-12

Durham, NC