### 202-234-4433 Neal R. Gross & Co., Inc. Page 1 U.S. ENVIRONMENTAL PROTECTION AGENCY (EPA)

+ + + + + FEDERAL INSECTICIDE, FUNGICIDE AND RODENTICIDE ACT SCIENTIFIC ADVISORY PANEL (FIFRA SAP)

+ + + + + REEVALUATION OF THE HUMAN HEALTH EFFECTS OF ATRAZINE: REVIEW OF EXPERIMENTAL ANIMAL AND IN VITRO STUDIES AND DRINKING WATER MONITORING FREQUENCY

+ + + + + DOCKET NO.: EPA-HQ-OPP-2010-0125

+ + + + +

THURSDAY, APRIL 29, 2010

+ + + + + The Panel convened at 8:30 a.m. in the Hamilton Ballroom of the Hamilton Crowne Plaza

Hotel, located at 1001 14th Street, N.W., Washington, D.C., Steven G. Heeringa, Ph.D., Chair, and Kenneth M. Portier, Ph.D., Session Chair, presiding. FIFRA SAP MEMBERS PRESENT:

STEVEN G. HEERINGA, Ph.D., Chair KENNETH M. PORTIER, Ph.D., Session Chair JOHN R. BUCHER, Ph.D., DABT JANICE E. CHAMBERS, Ph.D., DABT, ATS GERALD A. LeBLANC, Ph.D. DANIEL SCHLENK, Ph.D.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 2 FQPA SCIENCE REVIEW BOARD MEMBERS PRESENT: SUSAN F. AKANA, Ph.D. RICHARD H. COUPE, Ph.D. KENNETH BARRY DELCLOS, Ph.D. PENELOPE A. FENNER-CRISP, Ph.D., DABT ROBERT J. GILLIOM, Ph.D. RICHARD GREENWOOD, Ph.D. WILLIAM L. HAYTON, Ph.D. STEVEN D. HOLLADY, Ph.D. TERESA H. HORTON, Ph.D. KANNAN KRISHNAN, Ph.D.

HERBERT K.H. LEE, Ph.D. KEVIN T. O'BYRNE, Ph.D. NU-MAY RUBY REED, Ph.D., DABT JEAN F.L. REGAL, Ph.D. DANIEL J. SELVAGE, Ph.D. CARMEN J. WILLIAMS, M.D., Ph.D. LINDA J. YOUNG, Ph.D.

ALSO PRESENT:

JOSEPH E. BAILEY, Designated Federal Official

### 202-234-4433 Neal R. Gross & Co., Inc. Page 3 C-O-N-T-E-N-T-S Opening of Meeting and Administrative Procedures Joseph Bailey . . . . . . . . . . . . . . . .4

Introduction and Identification of Panel Members Kenneth Portier . . . . . . . . . . . . . . .4

Charge to Panel Question 1.9 continued. . . . . . . . . . . .5

Charge to Panel - Question 2

Approaches to Evaluating Water Sampling Strategies and Frequency of Monitoring

Question 2.1. . . . . . . . . . . . . . . . . . . 88

Question 2.2. . . . . . . . . . . . . . . . . . .114

Question 2.3. . . . . . . . . . . . . . . . . . .125

Question 2.4. . . . . . . . . . . . . . . . . . .136

Wrap up and Adjourn . . . . . . . . . . . . . . .169

### 202-234-4433 Neal R. Gross & Co., Inc. Page 4 1 P-R-O-C-E-E-D-I-N-G-S

2 8:34 a.m. 3 MR. BAILEY: Okay, this is the last 4 day of the FIFRA Scientific Advisory Panel 5 meeting on atrazine reevaluation. I am Joe 6 Bailey, serving as Designated Federal Official. 7 Dr. Portier is the chair and I will turn the mike 8 to him. 9 SESSION CHAIR PORTIER: Good morning. 10 Thank all of you for sticking with us into this 11 fourth day of discussion. Hopefully not a full 12 day of discussion, but it remains to be seen. 13 Just to give the panel and the 14 audience a little kind of idea of what our plans 15 are this morning, I am going to revisit Question 16 1.9, just to get any concluding remarks and kind 17 of make sure that at least the panel is clear 18 that all of our ideas have been captured. 19 We will then go to some presentations 20 from Syngenta and EPA on clarifying comments 21 related to the hydrology and the simulations that 22 they did. The panel members assigned to those

### 202-234-4433 Neal R. Gross & Co., Inc. Page 5 1 questions have been working very hard the last 2 three days to really understand what both 3 Syngenta and EPA has done so that they can make 4 sure that their remarks are to the point. 5 And while it has been nice for them to 6 have these discussions on the side, those 7 discussions need to come back into the full room 8 so they are captured into the public record. 9 That is the gist of a public meeting. 10 So we will have those presentations 11 hopefully no more than a half hour with questions 12 and then we will begin with the four hydrology 13 questions. And at that point, hopefully we will 14 be able to close the public meeting and begin to 15 write our report. 16 So with that, I am going to, I don't 17 know where we are on the slides, but we are going 18 to go back to Question 1.9 which if you remember, 19 these are the questions that relate to the risk 20 assessment and the PK and primarily deal with 21 issues of frequency and duration of water 22 monitoring as it relates to toxicological

### 202-234-4433 Neal R. Gross & Co., Inc. Page 6 1 concerns. And I have asked Dr. Reed and Dr. 2 Krishnan, I warned them that I was going to call 3 on them first to start the discussion and then we 4 will open it back up to the panel. 5 Primarily, we don't really want to 6 rehash everything we talked about yesterday but 7 we want to capture any additional thoughts you 8 may have had over the evening. It was an 9 intensive two hours yesterday afternoon and I had 10 to go back and think about a lot of it myself. 11 So with that, Dr. Reed? 12 DR. REED: Yes, the Chair gave me the 13 warning but it was five minutes ago. 14 (Laughter.) 15 SESSION CHAIR PORTIER: You don't get 16 much more for tornadoes, either. 17 DR. REED: Yes, for 1.9, the first 18 part of it, we talked about let me see. I was 19 given 30 seconds. 20 We talked about focusing on downstream 21 events to define the endpoints for risk 22 assessment. So these endpoints have to do with

### 202-234-4433 Neal R. Gross & Co., Inc. Page 7 1 something that is adverse in terms of function or 2 anything that you would define. 3 And we talked a little bit about 4 within the mode of action that we have been 5 talking about in the last three days but also any 6 possible other mode of actions. I have asked if 7 anyone who has a sense of sensitivity difference 8 between animals and humans of the particular 9 endpoint that you are interested in having used 10 risk assessment. 11 But most of the comments are really 12 just to go back and look at the entire database 13 and benchmark those analysis to form endpoints to 14 compare the sensitivity of these endpoints and to 15 include all the steps in the key events and 16 mindful about the acute and short and long-terms 17 duration of exposure and mindful about the 18 toxicity of the metabolites and so some form of 19 toxicity equivalence factor could be applied to 20 it to address all the speciation of the 21 chemicals. 22 And our sort of comments or inclusion

### 202-234-4433 Neal R. Gross & Co., Inc. Page 8 1 for this issue would be also regarding the lack 2 of data from all the previous discussions. 3 And Dr. Horton had graciously offered 4 to come up with maybe more detail. When we talk 5 about key events and I felt yesterday we were a 6 little bit ambiguous about what are the key 7 events, how many, four, eight, or additional mode 8 of action. And so Dr. Horton graciously offered 9 to come up with a new house and maybe more

10 elaborate. 11 So this will be where we want to hear

12 from her. Dr. Horton. 13 DR. HORTON: Now I know why I didn't 14 go into architecture. 15 Okay, I am still working on this new 16 figure but I can give you an idea of what it will 17 look like for the minutes. And it will be a 18 multi-part figure reflecting the charge to the 19 panel to evaluate the MOA and aid the agency in 20 its preparation for the September 2010 meeting. 21 And the goal of agency by 2010 is to 22 develop a draft weight of evidence document that

### 202-234-4433 Neal R. Gross & Co., Inc. Page 9 1 includes points of departures for evaluating risk 2 in infants and children, with the goal of 3 determining the extent to which the current data 4 indicates a need for the Agency to develop a new 5 human health assessment for atrazine and to 6 reconsider, as appropriate, the frequency of 7 drinking water sampling. 8 So to that end, the figure will be a 9 multi-part figure encapsulating the mode of 10 action or the modified mode of action as 11 discussed here, which will be a newly 12 conceptualized mode of action, taking into 13 consideration the data discussed in the last few 14 days. The weight of evidence supporting the 15 various level data that has been discussed using 16 arrows of different weights to indicate the 17 confidence in the various pieces of evidence that 18 have been discussed. 19 And the diagram will recognize that 20 organisms, especially humans, are complex systems 21 and that the systems we have discussing often 22 interact and function as feedback systems with

### 202-234-4433 Neal R. Gross & Co., Inc. Page 10 1 some degree with hierarchical organization and 2 that within that context, atrazine may act at 3 several different levels of the hierarchy. And 4 the key events may occur at any point within that 5 hierarchy. And because these are feedback 6 systems, they may ramify at different levels. 7 The diagram will also attempt to 8 identify where new areas of research may be 9 helpful or where areas of research need to be 10 strengthened. Thank you. 11 DR. MENDEZ: Could I just one second 12 please? 13 SESSION CHAIR PORTIER: Yes, sure. 14 DR. MENDEZ: I just want to clarify 15 for the panel that our intent for September, it 16 is to reevaluate the toxicity not just for 17 infants and children but for the entire 18 population. 19 SESSION CHAIR PORTIER: Sorry, this is 20 Ken Portier. Is this on? Yes, I guess so. 21 In talking with Dr. Horton about the 22 diagram, the one thing that caught me is she took

### 202-234-4433 Neal R. Gross & Co., Inc. Page 11 1 figure three and she said but the way I see it is 2 this way and with CNS at the top and functional 3 at the bottom. And I think that is one of the 4 major changes. 5 It sounds simple but when she talked 6 about top down or something at the top, you know, 7 I was looking at it as atrazine from this chart 8 and she was looking at it as CNS, looking at it 9 in the transposed way. And to me, that clarified 10 a lot of the conversations she had been making 11 all along because she sees it in this rotated 12 version with the central nervous system at the 13 top and functional capabilities at the bottom and 14 atrazine comes in from the side. 15 Dr. Horton and then Dr. Crisp.

16 DR. HORTON: You have to understand 17 that within the world of reproductive 18 endocrinologists and neuroendocrinologists, we 19 divide the world into those of us who work above

20 the belt and below the belt. 21 (Laughter.)

22 SESSION CHAIR PORTIER: Dr. Fenner-

### 202-234-4433 Neal R. Gross & Co., Inc. Page 12 1 Crisp?

2 DR. FENNER-CRISP: I don't know how to 3 top that one. 4 I might suggest that you go back and 5 look in the draft document with respect to the 6 mammary tumor MOA and the figure in there does in 7 fact start with the brain and trickle down. 8 SESSION CHAIR PORTIER: Dr. Cooper? 9 DR. COOPER: I would like to, if I 10 could, also make a comment. I think that figure 11 that you saw there was before it got to 12 Washington. 13 But I am really pleased to hear you 14 make the suggestions that you made because it is 15 an extraordinarily complex set of issues that we 16 are dealing with and the key point, you have 17 captured it, especially when you think of 18 toxicity pathways that was touched on yesterday, 19 they are not linear. That they are probably 20 masses with multiple, perhaps multiple target 21 sites. And to capture that is an extraordinarily 22 difficult thing, especially in a mixed audience

### 202-234-4433 Neal R. Gross & Co., Inc. Page 13 1 like this. 2 The other thing is that the arrows are 3 key to this also. And there is a considerable 4 amount of difference in the weight of evidence. 5 But the only thing is, is that we are preparing, 6 you are going to make suggestions about the way 7 the arrows, the thickness of them is that in this 8 case, I think there you can bring in some of the 9 in vitro data that is existing.

10 SESSION CHAIR PORTIER: Dr. Bucher? 11 DR. BUCHER: Yes, I just wanted to 12 bring up the fact I have been involved in a 13 number of discussions over the years on MOA and 14 the development of frameworks for the utilization 15 of MOA with respect to evaluating human cancer 16 information. And one of the things that I think 17 is most important is that the MOAs have to be 18 pretty well developed on, I think the words we 19 have used are compelling, scientifically 20 compelling. 21 And what I am a little worried about 22 here is that we have a very, very complicated

### 202-234-4433 Neal R. Gross & Co., Inc. Page 14 1 potential figure for an MOA that is being 2 introduced at the very end of the meeting and I 3 wouldn't want it to come out of this meeting as 4 something to the world that has been fully 5 evaluated and agreed upon by this group. 6 So I think that whatever you put 7 together should be cast in the right terms that 8 it is a very, you know, it is a suggestion of a 9 way that the agency might want to look at 10 organizing the information rather than being cast

11 as an MOA. 12 SESSION CHAIR PORTIER: Yes, we have 13 talked about that as well. Dr. Krishnan, do you 14 want to talk about PK issues? 15 DR. KRISHNAN: The second part of this 16 question related to the temporal consideration 17 based on toxicity versus monitoring frequency. 18 As much as I would like to talk about PK, I am 19 going to have to be a little bit more implicit of 20 both PK and PD. That is what I am going to try 21 to do and invite Dr. O'Bryne to complete or 22 correct me as I make my comments.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 15 1 In thinking about this, you know, 2 frequency of monitoring versus the temporal 3 profile or temporal considerations of toxicity, 4 we do it in terms of the time course of the 5 atrazine and metabolite in the body, which is 6 essentially the PK consideration, and then the 7 time course or the precursor, the key events or 8 the precursors measured, which could be altered 9 LH cortical levels. 10 First, in terms of the consideration 11 of the time course of atrazine and metabolites or 12 the internal dose. As we talked about yesterday, 13 the uptake or consumption pattern associated with 14 the drinking water combined with the 15 pharmacokinetic considerations, my colleagues 16 mentioned some of the key aspects, particularly 17 the slow absorption rate for example from the 18 drinking water or from oral administrations, the 19 relative short half-life of the parent chemical 20 combined with an extended half-life of some of 21 the metabolites, these things suggest together 22 that in the integrated measure, the internal

### 202-234-4433 Neal R. Gross & Co., Inc. Page 16 1 exposure would be relevant. 2 For example, the chloroforms, the 3 chlorinated form, atrazine plus metabolites that 4 still have the Cl in them. Or there could be an 5 average calculated based on the AUCs over a 6 particular period.

7 So the area under the curves would 8 integrate both the dose and the temporal 9 considerations together, essentially. And I have 10 not seen anything that suggests that the 11 particular Cmax of a parent chemical or 12 metabolite during a specific period is somehow 13 clearly associated with the profile of the 14 precursors measured or the outcome in tox 15 studies. 16 So given those observations, I still 17 tend to think that the overall profile or 18 consideration of pharmacokinetics does not call 19 for very narrow time-based analysis of 20 monitoring. So that is one part of it. 21 The second part is that then you think 22 about the time course of the key events are

### 202-234-4433 Neal R. Gross & Co., Inc. Page 17 1 essentially the precursor or the measurements 2 that are made between the internal dose and the 3 toxicological outcome. In this case, the time 4 course of the LH or the cortical levels. 5 The current complication, in my mind 6 at least, arises from the consideration of the 7 more recent data on the short-term changes in the 8 rats summarized in Table 3 on the HPA/HPG axis, 9 essentially in the four-day experiment. I think 10 that is where some of the discussions yesterday

11 focused on. 12 It is kind of unclear to me if the 13 four-day exposures result in an impact on the 14 precursors, for example, LH or cortical levels. 15 And since they seem to bounce back within the 16 next few days that follow, these four-day 17 experiments which lead to all the discussions of 18 a four-day monitoring frequency, for example, is 19 kind of related to an adapting response, rather 20 than an adverse response. That is a question I 21 ask myself. You know, if it is a four-day dosing 22 that causes an impact on LH and then in four days

### 202-234-4433 Neal R. Gross & Co., Inc. Page 18 1 it bounces back, then the cycle, I guess, it gets 2 back afterwards and so forth, it appears to me 3 more of an adapted response, rather than adverse 4 reproductive outcome per se. 5 Further, depending on the critical 6 effect, I mean, that is one of the reasons why we 7 revisited the MOA figure. Depending upon the 8 critical effect that is going to drive the acute 9 versus chronic assessment, I hesitate to see this 10 single MOA funnel in accommodating all of these 11 outcomes. Specifically, I don't think one MOA 12 will fit all effects acute and chronic. That is 13 where some of my concerns come. 14 So the precursor effects appear to 15 make at least convincing sense to me based on 16 chronic exposures and sustained effects on the LH 17 associated with the reproductive outcome and so 18 on which are not questioned at all. 19 But in terms of the acute exposure and 20 I am still a bit reluctant to suggest anything 21 other than an integrated or an average one, 22 rather than focusing on a four-day period based

### 202-234-4433 Neal R. Gross & Co., Inc. Page 19 1 on these points. 2 Additionally, as I was thinking about 3 this four-day discussion yesterday and some of it 4 came through during the supper time, is that you 5 know, once you take a benchmark, some level of a 6 NOAEL in a rat study, based on the effects on the 7 precursors and then use that as a basis for 8 deriving oral concentrations appropriate for 9 humans, what is the point of relating then back 10 to the four-day frequency there or the duration 11 of the effect in the rat unless we want to 12 protect the rat? Because that is where some of 13 our confusions came from.

14 The focus should be on the dose 15 because we took the dose based on the rat studies 16 and we said well we will use that as a basis to 17 protect the humans. And then you do the 18 calculations and then I don't see the obvious 19 connection of going back with these numbers, back 20 to the four-day frequency. That obvious link, I 21 mean, that is not an obvious link to me, unless 22 you want to calculate the physiological equal and

### 202-234-4433 Neal R. Gross & Co., Inc. Page 20 1 times and so forth. Even there I am not sure you 2 would say it is a worthy effort. 3 As Bob Dedrick, I think, in the '70s 4 derived some of these physiological time 5 equivalents and so forth, those sophisticated 6 calculations could be done but I don't see that 7 being a productive route. 8 So, I don't know if I confused or 9 clarified more but this is what is in my mind, 10 based on discussions we have had. 11 SESSION CHAIR PORTIER: Dr. Greenwood, 12 you wanted to add something to this? 13 DR. GREENWOOD: Yes. I think we were 14 trying to get our heads around this at the end of 15 the session yesterday afternoon. And I think 16 what we saw was that it makes a lot of sense, 17 because you have got to base your protective

18 levels on the hazard. And we saw that there was 19 a lot of sense in basing it on the rodent assay, 20 which is clear, with a clear endpoint and so on, 21 and well supported with evidence. 22 But we couldn't see then why the time

### 202-234-4433 Neal R. Gross & Co., Inc. Page 21 1 should be based on the rodent at all. I mean, 2 this is what Dr. Krishnan just said. We just 3 could not see why you would use a time based for 4 a rat effect. Okay, the dose is important. That 5 is what you use it for, to get the hazard. But I 6 don't think it was ever intended to try and set 7 an exposure time. As Dr. Krishnan said, you are 8 not trying to, a lot of people spend money trying 9 to kill rats and not trying to protect them. 10 So I think we felt that if there were 11 to be an exposure time figured in to the water 12 monitoring, it has really got to be something 13 more human-based. But what that would be is 14 difficult because, as Dr. Horton said, it could 15 be just an hour, the critical period for some 16 endpoints and you are never going to capture

17 that. 18 So we felt that if you go for the most 19 vulnerable stage, maybe during development, it 20 could just be an hour but I would prefer to let 21 Dr. Horton speak to that, I think.

22 SESSION CHAIR PORTIER: Dr. Horton?

### 202-234-4433 Neal R. Gross & Co., Inc. Page 22 1 DR. HORTON: Yes, this is one of the 2 things we will try to encapsulate in the new 3 diagram is the difference between developmental 4 programming effects, which may have long-term 5 outcomes which may not, while exposure may occur 6 during fetal development and may result from 7 short duration exposure but the actual effects 8 may not appear until later in life versus what 9 Dr. Krishnan referred to as an adaptive response 10 occurring in response to an acute exposure. So 11 we will try to capture those two different things 12 because in a physiological sense, the mechanisms 13 of action may be very different.

14 SESSION CHAIR PORTIER: Dr. Bucher?

15 DR. BUCHER: So I understand and I 16 agree with the comments you made about the time 17 issues. But I think that you said something 18 about the fact that if there was a four-day 19 exposure and there was an effect but it was 20 reversible, it wasn't considered an adverse 21 effect. And I would absolutely disagree with

22 that.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 23 1 And if you are talking about an 2 adaptive behavior as simply something that can be 3 reversible, I would disagree with that as well. 4 I think that is not the correct interpretation of 5 toxicology. 6 SESSION CHAIR PORTIER: Dr. Cooper? 7 DR. COOPER: This is not an atrazine 8 paper but in 1993 we published a paper with the 9 acaricide chlordimeform where we showed that a 10 single dose administered on the critical period 11 on the afternoon of proestrus and the clearance 12 of this stuff is pretty quick, blocked the LH 13 surge and delayed ovulation. And everyone said 14 well that is a reversible effect and if you block 15 ovulation, they ovulate the next day, especially

16 a rat. And rats are rats and humans are humans. 17 Well, it turns out that we went on to 18 examine that further. And when you delay 19 ovulation, the ova ages. And as the ova ages, it 20 becomes, I don't know what the right word is, the 21 viability is such that you end up with things 22 like polyspermia and you end up with polyploidy.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 24 1 I think that was Dr. Stoker's master's thesis. 2 And so when you went on and looked at 3 the mothers of those one-time dosed animals which 4 was reversible, if they became pregnant, then 5 that effect was not reversible. There was 6 delayed development, embryo anomalies, reduced 7 litter size. So sometimes a single dose, even 8 though it may apparently be reversible, may not 9 necessarily be that. 10 SESSION CHAIR PORTIER: Dr. Krishnan? 11 DR. KRISHNAN: I think I was cautious 12 in the way I phrased it, but what I had raised as 13 a question or concern was that those effects 14 during the four days on the precursors if you 15 will, the cortical and the LH, if they are 16 clearly associated with the reproductive outcome 17 or the delayed maturation on some of the other 18 whole animal affects, clearly, then I don't ask 19 question aloud. So it is obvious. 20 My understanding or at least the 21 reason why I raised the question was if it was 22 affecting a cycle on then which bounces back and

### 202-234-4433 Neal R. Gross & Co., Inc. Page 25 1 then captures, there is no demonstration of 2 reproductive outcome or other whole animal 3 effects in these studies, which doesn't seem to 4 be the case. If not, please correct me. Then I 5 will take back and I say well three or four-day 6 or even less or more frequent monitoring would be 7 required. 8 So I just want to be clear that I have 9 not misread or misinterpreted.

10 SESSION CHAIR PORTIER: Dr. Reed? 11 DR. REED: Just so that you are having 12 fun here, when I was beginning to do risk 13 assessment and our kids were very young and they 14 asked me what do you do and so I said we just do 15 experiments on rats and mice and bunnies and then 16 we bring that down by hundred-fold. And they got 17 the idea that all the field mice and field rats 18 and bunnies are all very safe. 19 And about the reversibility, I totally 20 agree with Dr. Bucher that reversible effects are 21 still adverse if it is adverse to begin with. 22 Also, a lot of times maternal effects

### 202-234-4433 Neal R. Gross & Co., Inc. Page 26 1 may be reversible. Alkaloids is an example that 2 the fetus is not, when it gets to the fetus 3 effect, fetal effects. 4 But I think, my understanding of this 5 issue about reversibility is that you have a 6 cascade of events and going through the networks 7 or the pathway of the mode of action, there may 8 be a step that you would have effect that there 9 is some sort of threshold so that it will not 10 trigger the next step, then that might be 11 something to consider as "reversible" in that

12 context. 13 But my main comments is that we talk 14 a little bit about area under the curve and blood 15 concentration and so forth. But I think it is 16 important, at least when I am doing PAPK model, 17 the hardest thing is to decide on the dose 18 metrics for rats to human equivalents. And I 19 think that when we get to PAPK or use PAPK as a 20 tool, that we should clear about what is the most 21 appropriate target sites. And I would not 22 preclude the possibility of using peak

### 202-234-4433 Neal R. Gross & Co., Inc. Page 27 1 concentration and just across the board to say 2 area under the curve is the most appropriate. In 3 terms of target site, it might not be serum but 4 could be more pertinent. Could be brain. 5 And so these are the kind of things 6 that I think we need to consider. I don't think 7 it is necessary for us to set in stone to say 8 area under the curve or what target site, or just 9 serum concentration. 10 SESSION CHAIR PORTIER: Dr. O'Byrne? 11 DR. O'BYRNE: I am just listening to 12 these conversations, I am trying to remind myself 13 why I am here. And it was my thought that we had 14 this new data of this 15-minute activation of the 15 HP axis, which was making us reconsider the 16 sampling frequency. 17 Now, my considered opinion is that 18 this 15-minute HP activation is a red herring and 19 it reminds me of Tony Blair's 45-minute weapons 20 of mass destruction argument. And I think we 21 have got to be very careful here. 22 The data, I mean, we have heard these

### 202-234-4433 Neal R. Gross & Co., Inc. Page 28 1 arguments about development and how sensitive 2 they may be but I haven't actually seen any data. 3 We are dealing here with a surge as this sort of 4 benchmark which cannot be separated from cycles. 5 If you don't have surges, you don't have cycles. 6 And the rat has got a four-day cycle and humans 7 have got a 28-day cycle. And the data that we 8 have got in front of us is that the LOEL for 9 atrazine is 3.6 milligrams over 28 weeks or 6.2 10 over four days. And that is what we have to work 11 with. So, I think these are the critical

12 factors. 13 And the discussions about how to 14 extrapolate from the rat model to humans is also 15 quite important, I think, to appreciate. And to 16 fit the physiology into the toxicology is hugely 17 difficult and we struggle with that. And I don't 18 know whether you can extrapolate from some 19 analogies and experimental data. 20 There is one that comes to my mind. 21 If you take a rat and you give it a large enough 22 dose of estrogen, then you will have an LH surge

### 202-234-4433 Neal R. Gross & Co., Inc. Page 29 1 every day at 5:00 or whatever until the thing

2 becomes exhausted. 3 If you give a large dose of estrogen 4 to a woman at any stage during the follicular 5 phase, you stop that cycle dead in its tracks and 6 you will wait 14 days for the next spontaneous LH 7 surge. So I don't know whether you can use that 8 temporal concordance or not but it is hellishly 9 difficult. 10 I don't know if that is of any value

11 at all.

12 SESSION CHAIR PORTIER: I am sure the 13 Agency is going to have to deal with that as they 14 kind of move forward and put this all together. 15 I am going to kind of end it at this 16 point. I just wanted to make a last comment that 17 as I was thinking through this and trying to make 18 the transition to the monitoring and sampling, 19 while it is nice to understand the mechanism of 20 action and understand this stuff, when you really 21 think from a population public health level, you 22 know, you start thinking about a hundred million

### 202-234-4433 Neal R. Gross & Co., Inc. Page 30 1 women, at any one point, any one day, any one 2 point in time, some of them are at the critical 3 level. So the statistic you are probably looking 4 for for monitoring is going to be some kind of 5 daily average that we are not going to exceed 6 because there is somebody at risk every day. 7 So it is nice to know the duration of 8 the impact of a concentration on an individual 9 but when you integrate it over the population, it 10 is going to be an average value that you are 11 looking at. The question is translating that 12 average to a physiologically critical dose that 13 is safe. Right? And that is the concern. 14 So I hope, Dr. Krishnan and Dr. Reed 15 are going to be able to capture this. The reason 16 for doing this is I know this is a critical 17 question and I really want to make sure as we 18 write this up we kind of capture all of this. 19 Thank you. I think, Dr. Cooper, you 20 are done. We are going to bring up the hydrology 21 point. 22 At this point, I think Syngenta is

### 202-234-4433 Neal R. Gross & Co., Inc. Page 31 1 first up. Dr. Hendley, I think has the 2 microphone, followed by Dr. Sielken, followed by 3 Mr. Thurman or Mary Frankenberry. And they 4 promised me to kind of collectively keep this 5 within 30 or 40 minutes. And we will probably, 6 at the end of this presentation, we will probably 7 take our morning break, get our coffee and then 8 go into these questions. 9 A number of pages have been handed out 10 to the panel and they are already being processed 11 to put on the docket, some of which are going to 12 be presented here and some of which have not. A 13 lot of it is clarifying material. 14 We went through the presentation on 15 Monday afternoon kind of quick and that was, I 16 think, the one reason we really want to revisit 17 and make sure we understand what was presented. 18 I know it is early in the morning but I am sure 19 the toxicology physiologists over here are going 20 to kind of sit back and relax. 21 Dr. Hendley. 22 DR. HENDLEY: Okay, this is Paul

### 202-234-4433 Neal R. Gross & Co., Inc. Page 32 1 Hendley from Syngenta again. And we would like 2 to thank you, Mr. Chairman and the panel for 3 giving us an opportunity to clarify some of the 4 handouts that were given. 5 And I think in fairness to the 6 hydrologists, for the rest of you around the 7 panel, you need to realize that between ourselves 8 and EPA, we have talked about five approaches, 9 each of which have examined data in subtly 10 different ways than the hydrologists have 11 properly asked us to clarify exactly how the data 12 were processed so they can better understand the 13 interpretations that have been made. 14 So what I am going to be doing is 15 referring or what we are going to be doing, and 16 incidentally, I have Dr. Sielken on my left and 17 Dr. Chen, the Dr. Chen from Chen et al., which 18 you have seen a number of times, on my right. 19 What we are going to do is talk about 20 the slide number from my presentation and then, 21 if I may, Mr. Chairman, I suggest after these are 22 largely one pages, if we briefly go through the

### 202-234-4433 Neal R. Gross & Co., Inc. Page 33 1 one-pager and then ask to make sure we have 2 addressed the questions, it is more efficient 3 than trying to remember what we said. Thank you 4 very much, indeed, then. 5 Okay, the first one refers to -- 6 SESSION CHAIR PORTIER: Can you make

7 that full screen? 8 DR. HENDLEY: I can. I can make it 9 bigger but I am afraid it is in Word. Where is 10 the zoom on this version of Word? It is not the 11 one where -- zoom. Thank you. Is that any 12 better? No, not really. Thank you. 13 It is amazing how Windows changes. 14 You totally forget the version as you move on. 15 Okay, the first one refers to slide 16 ten in the Syngenta presentation, which was about 17 high centiles. There is a very detailed report 18 on the docket, which is Whitmore and Mosquin. 19 The points that I think I would like 20 to clarify that I understand were questions in 21 the minds of the hydrologists were this is 22 finished water. And what we are talking about

### 202-234-4433 Neal R. Gross & Co., Inc. Page 34 1 here is an analysis that follows almost exactly 2 the process in the main report, which was done on 3 the full data set of both SDWA 50,000 data points 4 and VMP/AMP, the 48,000 data points. But this 5 time, they looked at the subsets of data based on 6 the water sources, static, flowing, and mixed. 7 And in addition, they looked at the 8 subset of data based across all community water 9 systems but recorded samples between April 1 and 10 July 31. 11 And so briefly, in that process, each 12 subset of the VMP/AMP data set was taken. The 13 data points were weighted, as described in detail 14 in the report. And we probably don't need to go 15 into that today. 16 The key question I think that was in 17 the mind of the panel was were these data points 18 interpolated. And the answer is they were not 19 interpolated. The centile estimates that were 20 given on slide ten were computed directly from 21 the population of measurements. And then the 22 confidence intervals were obtained as described

### 202-234-4433 Neal R. Gross & Co., Inc. Page 35 1 in the full report and that led to the table in 2 the handout that accompanied the slides. 3 DR. YOUNG: Linda Young. Okay, Paul, 4 I can't figure out, are you talking about this 5 handout, and this slide ten? I can't find slide

6 ten. 7 DR. HENDLEY: Okay. 8 DR. YOUNG: So, I am quite lost. 9 DR. HENDLEY: Okay. I do not have the 10 slide set up here. It is the slide set that I 11 presented. I think it is near the back of that 12 slide, that package of slides. 13 DR. YOUNG: Okay. 14 DR. HENDLEY: There you go. 15 DR. YOUNG: All right. 16 DR. HENDLEY: No, the slide set that 17 starts with potential atrazine exposure in 18 drinking water. You got it. That is slide ten. 19 So that was on the high centiles and 20 it had the data on the full data set, as well as 21 the subsets by source type, static water, the 22 flowing water. And so that was done with no

### 202-234-4433 Neal R. Gross & Co., Inc. Page 36 1 interpolation from the entire set of data points. 2 Any further questions on that one? Okay. 3 The second one refers to slide 12 in 4 that presentation, which you should find says 5 sampling frequency and then 90-day exposure. 6 Okay? Right. 7 So, this is a handout that is 8 describing in more detail the process of 9 developing the data. And the key points here, it 10 was raw water and there were 441 community water 11 system years from -- and now we can read it -- 12 from 137 community water systems. 13 This was from the atrazine monitoring 14 program. So they were seven-day intervals during 15 the growing season and every two weeks during the

16 rest of the season. And for each one of those 17 441 community water system years, linear 18 interpolation was used in this case to create a 19 365 daily concentration profile. From that 20 interpolated profile, 90-day rolling averages 21 were computed and the maximum one was selected 22 for each community water system year. That was

### 202-234-4433 Neal R. Gross & Co., Inc. Page 37 1 the true value against what we are going to 2 compare our samples. 3 There were a number of sampling 4 designs tested and just to be clear, they are as 5 shown on the table on the other side. Overleaf, 6 as the Brits would say. This is the atrazine 7 monitoring protocol, right to extreme right of 8 that table. And in January, there was one every 9 two weeks, which works out to approximately three 10 sets of samples in January, two in February, two 11 in March, and this just happens to be because of 12 calendar weeks and then you go into the weekly 13 period.14 SESSION CHAIR PORTIER: Time is a15 wasting here. 16 DR. HENDLEY: Yes. Okay. And so we 17 had weekly sampling during April to July and then 18 again went back to the two-weekly schedule for 19 the rest of the year and there were also sampling 20 regimes with 17 samples, nine and six during the 21 year. 22 The sampling design that was used in

### 202-234-4433 Neal R. Gross & Co., Inc. Page 38 1 this piece of work by Research Triangle 2 International was a series of windows were 3 created and the approach was to take one sample 4 in each simulation, one sample point within the 5 window with replacement. Each day in the window 6 had an equal probability of selection for all 7 1,000 simulations. 8 And so you took a random day within 9 the week. You moved to the next selection week, 10 took another random day. And the reason for that 11 is because that is actually the instruction that 12 was given to the plan operators, not that they 13 had to go every Tuesday, because that was an 14 unfair burden but they were to take one during 15 the calendar weeks, following that schedule in

16 the table. 17 So for each simulation there was a 18 linear interpolation between the sampled points 19 to come up with a 365-day profile and from that, 20 a 90-day rolling average was created for the days 21 and the maximum simulation 90-day rolling average 22 was obtained.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 39 1 And the difference between the 2 simulation 90-day maximum and the true maximum 3 for each of those community water system years 4 was recorded and then you had a set of maximum 5 simulated to maximum and that was worked on as a

6 full data set and as data subsets based on the 7 source-type. So that was the background to how 8 we processed the data for that piece of work. 9 And I realize you need many hands to hold all the 10 pieces of paper. 11 DR. YOUNG: So the results are in this 12 set of slides?

13 DR. HENDLEY: The results are 14 summarized on slide 12 of the presentation. The 15 90-day exposure slide, which is entitled 16 "Sampling Frequency and Confidence; 90-day 17 Exposure." 18 DR. SIELKEN: This is Dr. Sielken. 19 There is an analogous set of answers in the other 20 handout that you had that I provided that was 21 done using the procedure that I am going to 22 describe later. But there are also additional

### 202-234-4433 Neal R. Gross & Co., Inc. Page 40 1 numerical results for that type of analysis. 2 DR. HENDLEY: And of course, the full 3 background to this, Dr. Young, is in the Chen, et 4 al. 2009, the evaluation of sampling frequency 5 alternatives, which is in the docket. 6 SESSION CHAIR PORTIER: And I think 7 the key conclusion here is that when you use that 8 methodology to look at reduced sampling schemes, 9 so going from roughly 25, 26 samples in a year 10 down to six or nine samples and showed that by 11 that same methodology you got the same 12 distributions with fewer samples. 13 DR. HENDLEY: Precisely. Precisely. 14 Thank you. Any further questions on that one? 15 Okay. 16 Okay, the last one of my presentation 17 before Dr. Sielken refers to slide number 14 in 18 the presentation that I made and it is entitled 19 "Sample Frequency, Shorter Exposures." This one 20 will be quicker, Mr. Chairman. 21 The key points of it, unlike the last 22 one where we started off with atrazine monitoring

### 202-234-4433 Neal R. Gross & Co., Inc. Page 41 1 program frequency, which was basically seven days 2 apart, this is using daily data sets. And I 3 should say, there is one other data set we 4 haven't been specific about and Dr. Gilliom can 5 tell you more about it, and that is a set from 6 2001 for Lake Perry, which was done by Blomquist, 7 et al., it is submitted, it is in the EPA White 8 Paper and that had daily data for a large static 9 body. And I realize that we never actually 10 mentioned that here. 11 So as you remember, we had finished 12 data from a community water system in Missouri 13 that was daily or near daily. And we had daily 14 or near daily data from the Eco program and the 15 Heidelberg programs.

16 So for each source of data for each 17 year, we took the measured daily or near daily 18 data. We filled in any gaps with linear 19 interpolation to create a 365-day time series and 20 we identified peak and we computed point 21 estimates of the 95th and 99th centile daily 22 value. And those were the true ones against

### 202-234-4433 Neal R. Gross & Co., Inc. Page 42 1 which we compared.

2 DR. YOUNG: So how were those 3 percentiles estimated?

4 DR. HENDLEY: Dr. Chen? 5 DR. CHEN: This is Wenlin Chen, 6 Syngenta. 7 The percentile actually are calculated 8 based on the daily chemograph generated. We 9 looked at the maximum each year at each site. 10 You have a sequence of events and you keep the 11 maximum as a peak concentration for that year for 12 that site and then calculate those so the 90th 13 centile and the 99th centile. 14 DR. YOUNG: So you used, basically the 15 rate data and took the percentiles of the data? 16 DR. CHEN: Right, yes. 17 DR. YOUNG: Okay. 18 DR. HENDLEY: So again, using that 19 365-day time series for that source of data for 20 that year, we used the same simulation approach 21 using the window approach that we have just 22 discussed. And so for each resulting simulation

### 202-234-4433 Neal R. Gross & Co., Inc. Page 43 1 of those one thousand simulations, a linear 2 interpolation between the sample points generated 3 a 365-day profile as before and the peak and 95th 4 and 99th centile of daily values were obtained

5 from that. 6 And then from each distribution of a 7 thousand runs, the example in the handout that 8 was given, this was from Dr. Mosquin, shows the 9 mean, the peak, and the 95th centile daily values 10 and their percentage deviations. 11 So has that clarified the data 12 processing for that? 13 DR. SIELKEN: This is Dr. Sielken. Dr. 14 Mosquin's handout that he is referring to are the 15 two separate pages that were put in the docket 16 from Dr. Mosquin? 17 DR. HENDLEY: Yes, the last two in

18 there.

19 SESSION CHAIR PORTIER: And the 20 conclusion from this, again getting back to the 21 conclusions of this exercise, is that when you 22 compared a once-a-week sampling to your overall,

### 202-234-4433 Neal R. Gross & Co., Inc. Page 44 1 you tend to underestimate the maximum by 20 2 percent, 20 percent to 80 percent for Missouri, 3 and 1.1 to 2.6 multipliers for the others. So as 4 we would expect, you are underestimating the 5 maximum. What you were doing here was estimating 6 the multiplier between the maximum between the 7 sample distribution to the real. Being able to 8 say, if I had sampled once a week during the 9 season and used that to create my profile, I 10 would underestimate the maximum by 20 to 80 11 percent. Right? I mean, is that kind of the 12 conclusion? 13 DR. CHEN: These systems are not -- 14 sorry. This is Wenlin Chen. You mentioned the 15 three systems. One is St. Louis which is a true 16 drinking system, the other two are at the Ohio 17 River and the eco that is not drinking water. 18 That is just ecological water system. 19 SESSION CHAIR PORTIER: And you get 20 the performance with the drinking water profile 21 and the worst performance with the well water 22 profiles, as we would expect.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 45 1 Dr. Heeringa? 2 CHAIR HEERINGA: Steve Heeringa. 3 Paul, there is a chemograph that is illustrated 4 on this handout sheet. Is that typical of one of 5 these water systems? For example, you are using 6 site-specific, year-specific data. So you have 7 seven years for this Missouri finished water 8 system. What do those chemographs look like? 9 DR. HENDLEY: Paul Hendley. The 10 Missouri chemographs have a low maximum value but 11 they are actually quite spiky. In a way, quite 12 surprisingly spiky. So some of the peaks appear 13 to be of the order of maybe three or four days. 14 DR. CHEN: Wenlin Chen. I just wanted 15 to add to that is that we are looking at the 16 ratio, not the absolute of the peak. So when you 17 look at the ratio, it should give you, it cancels 18 out where it is really spiky or not spiky. 19 CHAIR HEERINGA: Steve Heeringa. My 20 concern is that the spiky problem is the tough 21 one. And I assume the Heidelberg data, which are 22 Honey Creek and Rock Creek, that those are spiky

### 202-234-4433 Neal R. Gross & Co., Inc. Page 46 1 data as well because those are agricultural 2 drainage, mostly. 3 DR. HENDLEY: Especially for the two 4 that you have selected, which were Honey and 5 Rock, which were about 35 and I think 130 square 6 miles. 7 CHAIR HEERINGA: Thank you. 8 SESSION CHAIR PORTIER: Paul, scroll 9 down so people can see the image Dr. Heeringa was 10 talking about. I think it is further down on 11 your slide. Isn't it? 12 DR. HENDLEY: I think it is on one of 13 the others, yes. 14 SESSION CHAIR PORTIER: There it is. 15 DR. HENDLEY: There you go.

16 SESSION CHAIR PORTIER: And the red 17 lines identify the sampling bins, the periods for 18 the windows. 19 DR. HENDLEY: Absolutely correctly. 20 So what you are doing is you are getting the 21 computer to pull a sample from each of these 22 windows.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 47 1 So with that, if there is no further 2 questions from the hydrology group, we would like 3 to turn to the discussion for underlying -- Where 4 is your presentation? And this underlies slide

5 13 6 DR. SIELKEN: This is Dr. Sielken. 7 Thank you, Mr. Chairman and the rest of the 8 panel. 9 This is some supplemental explanation 10 to go with the short handout that was part of the 11 docket yesterday. There seemed to be a missing 12 link in the middle of it. And since it was no 13 simulation and no trickery or anything like that, 14 I wanted to make it clear the step-by-step 15 procedure that I was going through and also 16 differentiated a little bit from some of the -- 17 slightly different than the Mosquin procedure, 18 although our procedure and our results ended up 19 being within ten percent of each other. So they 20 were very close, even though they were slightly 21 different. 22 The procedure that I applied both to

### 202-234-4433 Neal R. Gross & Co., Inc. Page 481 all 202 CWS's as well and that was on a multi2 year profile, I also applied to the St. Louis -- 3 I'm sorry. I wasn't supposed to say that. The 4 Missouri community water supply system, which was 5 close to daily data. I did that both yearly in 6 groups and multi-year. And I also applied that 7 to, the same system, to the almost daily data in 8 the Heidelberg data sets, the Honey, the Rock, 9 Sandusky, and Maumee. 10 In all of those cases, the procedure 11 was as follows. And it is almost identical12 whether you use linear interpolation or step13 wise. So that is not really a big deal. 14 You start out, at least for data sets 15 like this where you followed this nearly weekly 16 or nearly daily sampling. It is a fairly dense 17 data set, as shown on the top of this slide. The 18 slide underneath it is the linear interpolation 19 and that is where we started. And the only 20 modeling that was done was just that linear 21 interpolation. There was nothing else that was 22 simulated.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 49 1 SESSION CHAIR PORTIER: And for those 2 who can't read it, that is about 13 years' worth 3 of time series data for one site that you are 4 showing there. 5 DR. SIELKEN: Yes, that is correct. 6 We had a variable number of years in CWSes. Most 7 of them had around ten years. Well, there were 8 351 profiles that were 13 years long; 351 CWS 9 years came from 13-year profiles. So that was 10 13-year profiles and seven-year profiles were the 11 most common length of profiles. 12 From this linear interpolated profile 13 for multi-years capturing your variability, I 14 went through and overlaid a grid of seven days 15 wide. A window, a seven-day wide window. And 16 then picture of course that seven-day window is 17 not to scale. But you know, put a grid over it 18 of seven days and then started at the beginning 19 of the profile on Monday, went to the next20 Monday, took another -- and this is in the seven21 day sampling. 22 We actually did the testing because

### 202-234-4433 Neal R. Gross & Co., Inc. Page 50 1 you were interested in perhaps changing the2 frequency of sampling. We also looked at two3 day, three-day, four-day, five-day, six-day, 4 seven-day, weekly, bi-weekly, tri-weekly, and 5 monthly. So we looked at all of those profiles 6 in exactly the same way that I am going to show 7 here and I will use as an example the seven-day 8 spacing. So analogous to what is going on now. 9 Given the linear profile, we overlay 10 a grid of the sample spacing here seven days 11 apart. Start systematically with Mondays and 12 then go to the next Monday and so forth and just 13 march through that entire profile every seven 14 days, starting with a Monday, record those 15 values, take a linear profile between those seven 16 day values -- no. Sorry. 17 Take those seven day values, find the 18 max, and then compare that max to the original 19 profile max, the data profile max. So when we 20 are looking at acute for one day, we just take 21 those seven-day spaced apart samples, compare the 22 max in that set of samples to the max in the

### 202-234-4433 Neal R. Gross & Co., Inc. Page 51 1 original profile. So there is no simulation in

2 there. 3 I did that starting on Monday, 4 starting on Tuesday, Wednesday, Thursday, you 5 know, all the seven possible starting points. So 6 there were seven sample maxes to compare to the 7 overall data profile max. And you can see the 8 variability in those numbers on this profile. 9 You know, 0.97 for Mondays, 0.96 for Tuesdays. 10 Obviously, one of those was going to hit it and 11 it was Saturday in this example, sort of. 12 I took the average of those seven 13 numbers and that is what I recorded as the single 14 number for that CWS is a ratio of the sample max 15 to the data profile max. 16 And now this next slide is the new 17 one. And that was to say what did I do with 18 those 202 numbers? Well, first of all, that is 19 what I worked with was those 202 numbers; one for 20 each CWS, just a comparison of the sample max to 21 the profile max. I took those 202 numbers and 22 found the percentiles of those 202 numbers. So

### 202-234-4433 Neal R. Gross & Co., Inc. Page 52 1 there was no simulation of anything in there. 2 And the little histogram here in the 3 center is just to hopefully eliminate confusion. 4 If there was a grid, and all of these ratios for 5 seven day spacing and trying to target an acute 6 daily value or a daily value, the ratios between 7 the sample max and the true max ranged from 0.75 8 at the low end up to one. There was 18 from 0.75 9 to 0.80; 31 in the next bin, and so forth. 10 So they were not very widely spread. 11 The worst case was around 0.75. So you were only 12 off by a quarter, 25 percent, using seven-day 13 sampling to estimate the ratio between a max one 14 day and a profile one day. So for a one-day 15 target, you can use a seven-day sampling and be 16 within 25 percent.

17 Dr. Lee? 18 DR. LEE: For the ones where it is you 19 are sampling say every seven days, did you 20 average across the possible seven starting days 21 to get the figures in the table? 22 DR. SIELKEN: Yes, I did.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 53 1 DR. LEE: Okay, thank you. 2 DR. SIELKEN: So, it was the expected 3 performance of the sampling plan. 4 Okay, that was probably the slide that 5 was most missing from your explanation before. 6 That set of percentiles computed from 7 the 202 values was tabulated in your handout for 8 both one-day sampling, of course that would have 9 been perfect; two-day sampling; three-day 10 spacing; all the way up to 28-day spacing. So 11 this is just a table repeating the analysis for 12 each sample spacing and then just recording the 13 percentile.

14 SESSION CHAIR PORTIER: If I can 15 interpret this and then if you look at the last 16 column, 28 days, it says if instead of sampling 17 every day you sample once a month, kind of on 18 average you are going to whatever it is, 22 19 percent below the kind of in the long run, you 20 are going to be 22 percent below the true daily 21 maximum. Right? 22 DR. SIELKEN: I'm not exactly sure

### 202-234-4433 Neal R. Gross & Co., Inc. Page 54 1 where you are seeing 22 -- 2 SESSION CHAIR PORTIER: I am looking 3 at the 50th percentile. I'm sorry. The median. 4 DR. SIELKEN: Oh, at the 50th 5 percentile. Okay. Going right across here, 6 0.7548, you are about 25 percent below. 7 SESSION CHAIR PORTIER: It is 0.79. 8 So it is like 21 percent. 9 DR. SIELKEN: Well okay, yes.

10 SESSION CHAIR PORTIER: You can't read 11 it from there. 12 DR. SIELKEN: Knowing that tables are 13 hard to read, regardless of the magnitude, I put 14 a little picture in and you can't read that 15 either but it gave me the idea that as you varied 16 the sample spacing between one day, which gave 17 you perfect results, to 28 days, how did your 18 ratio drop off at the 95th? Well, the orange, if 19 you can see orange is in the middle, and that is 20 the 95th, there is the 97.5 and 90 below it. So 21 those three profiles of interest, how they change 22 with sample spacing.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 55 1 And notice that if you don't like 2 pictures, I put it in numbers again. And they 3 are saying that if you take a seven-day sample 4 spacing, keep your current spacing, you are 5 within a quarter for single-day target within 20 6 percent for a three-day target, and so forth. 7 Notice that for a 90-day rolling target, you are 8 almost there all the time. 9 So this is showing that regardless of 10 your target, really, you are doing quite well 11 with the existing plan. Now this was to test the 12 sampling performance. 13 What happened? Oh, well, I reached -- 14 well how silly. I want to get back to the 15 folders. Where is the folders? Yes, here we go. 16 That showed that you could stick with 17 the current sampling plan and for finished water 18 or even doing the same example with the 19 Heidelberg Eco, getting approximately comparable 20 results. And those were shown in the first 21 handout that I gave, put on the docket a couple 22 of days ago down here. I apologize here.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 56 1 We did that same procedure as Dr. 2 Hendley mentioned, we did that not only for the 3 202 CWS collectively, we also split them up by 4 groups, flowing, mixed and static. We got pretty 5 much the same results. You can see a comparison 6 there between what we got for all the CWS 7 together with what we got for the different 8 partition. That is in the handout that you got 9 on the first day from me, which is going to look 10 like that. 11 And then because this was the 202 CWS, 12 which is a really strong database for capturing 13 year to year variability and the differences 14 between CWS in Indiana, Illinois, Ohio, Texas, 15 you know, covering that entire region and the 16 different year effects. 17 And of course, if you look at a CWS, 18 there is a lot of year to year variability. Then 19 going from that set as a test case to another set 20 that didn't hardly involve the linear 21 interpolation because you had almost daily 22 sampling, which is the CWS set in Missouri, which

### 202-234-4433 Neal R. Gross & Co., Inc. Page 57 1 is shown in this slide. Yes, well if I do that

2 then I lose where I was. 3 You can notice these numbers down 4 here. The lowest number in that table is, you 5 know, for the hardest target, which is single 6 day, those numbers are about a third. The lowest 7 number there is 65 percent or something like 8 that, 60 percent. That means you are off by 40 9 percent, not even a factor of two. 10 Okay, also you know, this was for 11 almost daily sampling of finished water. This is 12 the Heidelberg data set. Again, the two worst 13 cases and again, this is not drinking water but 14 an ecosystem, your lowest number is around 40 15 percent. So you are off by that much. So again, 16 right around at worst a factor of two. 17 DR. HENDLEY: And just if I can, this 18 is Paul Hendley again, that was why having worked 19 from the strength of the temporal and spatial 20 VMP/AMP database and from the strength of the 21 daily database and coming together and finding 22 the results were coherent was one of the points

### 202-234-4433 Neal R. Gross & Co., Inc. Page 58 1 we made earlier.

2 SESSION CHAIR PORTIER: So do we have 3 any follow-up questions of Linda or Dr. Lee? Dr. 4 Heeringa. 5 CHAIR HEERINGA: I just want 6 confirmation that the two sets of analyses, the 7 one done by RTI and then the one done by Sielken 8 and Associates, Bob you just used systematic 9 sampling throughout the year. The other just 10 used the random draw within these time windows 11 that have been set out under the plan. 12 DR. HENDLEY: That is correct. 13 CHAIR HEERINGA: That is the primary 14 difference between your treatments of these same

15 data? 16 DR. HENDLEY: Yes, that is primarily 17 the difference. The only other difference is 18 they looked at every year individually. And I 19 did, too, but I did a multi-year profile.

20 There was one other comment I wanted 21 to make because you asked it yourself, Dr. 22 Heeringa, was what durations. In the first part

### 202-234-4433 Neal R. Gross & Co., Inc. Page 59 1 of the handout, we looked at, you know, gave the 2 full numerical distributions of characteristics 3 for one day, ten day, 30 day and 90 day rolling 4 averages. We gave the concentrations, the 5 distribution of concentrations, the distribution 6 of rolling averages. We also addressed the 7 question that you raised was what about how many 8 days in a row did you exceed certain levels. 9 And there was, in that handout, I will 10 just leave it here, in that handout, there are 11 tables that do for the daily profiles the 12 concentrations and then there is just this one 13 page on page five in that handout where we did 14 look at duration, number of days above specified 15 values. And I only have the one day and the ten 16 day in here. But I can tell you that at the 99th 17 percentile, there was no CWS, none of the 202 CWS 18 for finished water that had durations above 19 twelve and a half for more than a day. And so 20 there was no duration above twelve and a half. 21 Obviously at the extremes there was a 22 little bit, I mean, there was more duration at

### 202-234-4433 Neal R. Gross & Co., Inc. Page 60 1 the max but there wasn't, you know, at the 99th 2 percentile, there was none for the day, 10-day, 3 30-day, 90-day, there were no durations above 4 that target value of like twelve and a half. 5 SESSION CHAIR PORTIER: Okay. Yes, 6 Dr. Gilliom? 7 DR. GILLIOM: I just want to make a 8 general point that we will probably come back to 9 in discussing the charge questions but it is 10 important in just interpreting all of this. 11 There is a tremendous number of numbers. And you 12 can generate tons of numbers from synthetic 13 sampling experiments and everything. 14 I just want to make the general point 15 that the importance of each sampling experiment 16 to a specific objective questions depends 17 entirely on how well the simulated truth 18 represents actual truth. 19 So, if we get to a problem where we 20 are looking at a very short-term occurrence like 21 daily, we have to be sure the starting point is a 22 confident estimate of the true daily

### 202-234-4433 Neal R. Gross & Co., Inc. Page 61 1 distribution. And there is a lot and I don't 2 even intend to jump into every individual 3 experiment that has been done by Syngenta or EPA 4 but every one of them has a little different 5 twist on how truth was defined and what time span 6 it is relevant to. 7 So my general point is, there are so 8 many possibilities here we are going to have to 9 get that objective very clearly defined so that 10 we can then evaluate which one is the right one

11 to use. 12 DR. SIELKEN: I agree with Dr. Gilliom 13 that establishing the truth is an important 14 thing. I would point out that when we did the, 15 we took the 202 CWS and took the linear profile 16 as a starting point, my intention was not that 17 that necessarily captured the max within the 18 water that was actually there but if I took those 19 values which are a representation of reality, 20 took that as a reality, it may not have been 21 quite as much of a reality as some people would 22 have wanted if they were to sample more often.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 62 1 But with that as the reality, given 2 that reality, how well did you do with your 3 monitoring program? So that was really the issue 4 was the ability or the performance of the 5 sampling. And that is also why we turned to the 6 more daily profile values and tested it there. 7 Thank you. 8 SESSION CHAIR PORTIER: Paul, you want 9 to wrap up? Final comment? No. 10 Dr. Akana had a question. 11 DR. AKANA: A small point that you can 12 clarify for me. What I understand correctly 13 though, this data treatment is equally valid on 14 say the raw samples that start much higher as 15 well as lower. For instance, the raw data here 16 mostly the points are like three or under parts 17 per billion but the treatment is equally valid if 18 your dataset runs up to 30? 19 DR. SIELKEN: Yes. Yes, because we 20 were looking at ratios between the sample max and 21 the true max, that ratio would be invariant to 22 whether we were going zero to three, zero to 30.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 63 1 You are absolutely correct. It would be 2 applicable. 3 DR. AKANA: But that does mean if your 4 estimate is say 20 percent under-represented, for 5 three, it is 20 percent and for 30 it is 20 6 percent. 7 DR. SIELKEN: Yes, that is correct. 8 DR. HENDLEY: So Mr. Chairman, I would 9 like to wrap up. I will make one comment on 10 that. Of course, that is a correct statement 11 that as we pointed out before, if you are trying 12 to understand the variability for drinking water 13 values, you are best off using drinking water 14 data where it is all possible. But the raw data 15 was a great way of getting a handle on 16 understanding variability. 17 However, we do appreciate the time you 18 gave us to try and clarify some of these issues. 19 So thank you very much. We appreciate it. 20 SESSION CHAIR PORTIER: Thank you. 21 And now Nelson Thurman and Mary Frankenberry. I 22 always get her last name wrong. I just know her

### 202-234-4433 Neal R. Gross & Co., Inc. Page 64 1 as Mary. 2 And also at the table is Don Brady, 3 the vision man. And of course we are way beyond 4 my half hour target. This is the last half hour 5 before our discussion. 6 MS. FRANKENBERRY: Thank you. And 7 again, I can go quickly I hope. Our slides I 8 think are a lot simpler than Syngenta's. We did 9 not get their handouts until one of them this 10 morning and would like to get them from Joe 11 Bailey, I think, certainly before the end of the 12 day. 13 Hopefully with these, it appears that 14 they have done at least in one or two of their 15 exercises something very similar to what we did 16 and I am hoping that these will be easy to

17 understand. 18 Step one, we took a sample chemograph. 19 That is what we get from the field, 30 to 35 20 samples. We augmented it linearly to 365 days to 21 make a true or reference profile that we are now 22 calling true.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 65 1 What we got in step two we would like 2 to consider reality. It could have been instead 3 the Heidelberg dataset that would have started 4 with, we wouldn't have had to do as many 5 interpolations but this is what we got and 6 considered as true. 7 From that we sampled this true profile 8 or what we consider reality out in the field. 9 Let's just say we will look at the example of 10 sampling every four days. We took this -- this 11 is what we do in the field. We may sample every 12 seven days, actually in the AMP program. For 13 this example, try four days. 14 What we get from number three then, is 15 what we get our as our sample dataset from 16 Syngenta or from wherever we receive a dataset. 17 And that will have 90 some values, perhaps or 30 18 to 35 if it is from the AMP. 19 For the purpose of the exercises then 20 we augmented this new sample chemograph up to 365 21 days. In some runs we ran step-wise, others 22 linearly but what we presented in the paper were

### 202-234-4433 Neal R. Gross & Co., Inc. Page 66 1 linear interpolation. 2 For that new, that sample that was 3 interpolated from step four, we calculated, as an 4 example, three-day running averages, starting 5 days one to three, two to four, all the way up to 6 363 to 365 days. We did rolling three-day 7 averages there. 8 In step six, we took the maximum 9 three-day running average from this re-sample or 10 the first re-sample, if you will. We set it 11 aside into the bootstrap pile and that is what we 12 will call it without the acronym there. 13 (Laughter.) 14 MS. FRANKENBERRY: I actually made 15 myself laugh last night and then forgot about the 16 public record. 17 (Laughter.) 18 MS. FRANKENBERRY: In step six, we 19 repeated this 4500 times with replacement until 20 our bootstrap pile contained four to five 21 thousand maximum three-day running averages. So 22 what we have there is a distribution of maximum

### 202-234-4433 Neal R. Gross & Co., Inc. Page 67 1 three-day averages, three-day running averages 2 that was derived from sampling every four days. 3 That is our bootstrap sample of maximum three-day 4 averages. 5 And in step seven what we did then was 6 we spread it out. We looked at its range from 7 minimum to maximum. We looked at the 50th 8 percentile values, low percentiles, high 9 percentiles, and we compared these to what we 10 would have gotten from the so-called true maximum 11 three-day running average. What we were looking 12 for is how often we captured the true max and 13 when we did not, when underestimated it, how 14 often did that happen and to what magnitude to

15 what extent. 16 Those are those questions. I can come 17 back to that but just to show you, again this 18 graph isn't that easy to see but what you are 19 looking at there, each of these, look at number 20 four. That is the bootstrapped distribution of 21 maximum three-day averages sampled at four-day 22 intervals.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 68 1 And we went from underestimating by 2 31.5 percent up to getting it right on with no 3 error. That is the range of our performance 4 there. We want to look down at, I think, number

5 13 was our best run or one of the best 6 chemographs. We went from minus two percent up 7 to no error. So that is a very narrow range and 8 we looked at how often. These are all again 9 maximum running three-day averages. 10 And I think in some of our, let's go 11 back up to this question. Do the highest runs 12 equal or exceed the true max? How much lower 13 than true are the lowest runs? And then if we 14 wanted to create an interval on a given CWS, let 15 me go back to this, from minus 30 to zero, that 16 is one kind of interval. If we wanted to look 17 down at our better ones, number 13, we go from 18 minus two up to no error. That is a kind of 19 interval in itself. 20 One of the questions that we will be 21 asking the panel is what do we do with these as a 22 whole? If it happens and this is totally

### 202-234-4433 Neal R. Gross & Co., Inc. Page 69 1 hypothetical, if our health effects people are 2 looking at a three-day average and they say how 3 well would we do if we sampled every four days, 4 we could say, I think on mean runs, the average 5 performance was about five percent under true. 6 Our lowest runs, I think, were on average about 7 13 percent under true for sampling every four 8 days on a three-day average. 9 Now we have asked them, can you live 10 with that if you would like a four-day interval 11 sampling strategy. The thing is we can look at 12 this and say we average 13 percent in the lowest 13 runs below true but we have some higher values 14 that were 30 percent under true. So do we want 15 to make a competence interval around our 16 performance here or do we want to take, run them 17 all as a whole, look at the lowest one percent of 18 all the CWS and say 99 percent will be at or 19 better than this kind of performance. I think 20 that is what we were getting at in asking for 21 advice on bounds for the population, what to do 22 with that, or can we produce a prediction

### 202-234-4433 Neal R. Gross & Co., Inc. Page 70 1 interval because we are looking at what we have. 2 But what do we expect on new systems? 3 Then when we go from here to 4 individual samples, I think we are relying on 5 asking your advice on things like the different 6 interpolation levels, which did make some 7 difference, we found, in how well we 8 underestimated or overestimated. It wasn't a lot 9 but I think with stair-step you can overestimate 10 more often than not. And I believe it is 11 possible to underestimate a little more in 12 magnitude but we didn't do a systematic look at

13 that. 14 That and any other methods that you 15 could, kriging, whatever that would help us on 16 the individual level. We are trying to go from 17 talking about bounds on something like this for 18 the population to then what do we do on an 19 individual level. 20 SESSION CHAIR PORTIER: Dr. Heeringa? 21 CHAIR HEERINGA: Steve Heeringa. You 22 bootstrapped this 4500 times but in a systematic

### 202-234-4433 Neal R. Gross & Co., Inc. Page 71 1 sample of 365 days, there are only 90 unique 2 samples. So are you not simply just at random 3 sort of getting an expected repetition of five of

4 these? 5 MS. FRANKENBERRY: We repeated, yes, 6 on purpose to get a larger number of samples so 7 that when we looked at the lowest one percent or 8 the highest one percent, we would have more 9 samples to deal with but definitely the finite 10 value for each of the running averages. And we 11 simply re-sampled more to be able to have more to 12 deal with.

13 CHAIR HEERINGA: There were sort of 91 14 or 92 unique values that could occur from your 15 sampling process in CWS? 16 MS. FRANKENBERRY: I think it is more 17 for four days because if you start from day one 18 to day three, then day three, two to four, three 19 to five, all the way up to 365, 363, it is 20 something like 365 minus three or four days, 21 something like that. I think the worst case is 22 with 90-day averaging. I think it is 365 minus

### 202-234-4433 Neal R. Gross & Co., Inc. Page 72 1 90. It comes around, something like that. 2 SESSION CHAIR PORTIER: Yes, Dr. 3 Gilliom? 4 DR. GILLIOM: Again, I think this will 5 come up later but just a comment briefly now 6 because of the point just made. And I think this 7 is meant as an illustration of a data analysis 8 process, more than like the final answer. So 9 this won't be meant to be particularly critical. 10 But to evaluate a short-term exposure 11 like this, the way the truth was created is not 12 appropriate, basically. 13 I am going to keep coming back. The 14 starting point in how we define truth is the 15 absolute most critical step in every one of these 16 experiments. Like here, truth on a daily basis 17 was created from samples that were 30 or 35 times 18 a year. It is missing many of the 19 characteristics of short-term fluctuation. So 20 when you simulate sampling from that, you are 21 going to do pretty well recreating what you 22 already got from a limited sampling.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 73 1 So basically the underlying data used 2 to define truth has to be denser than the type of 3 time frame you are trying to evaluate. And that 4 is why you see so much work done on these 5 relatively few sights that have daily data. And 6 we will see this as kind of a recurring -- 7 SESSION CHAIR PORTIER: This is Ken 8 Portier. Your underlying simulation model has to 9 be complex enough to capture that high resolution 10 variability. 11 DR. GILLIOM: Yes, you have to have 12 some basis to defend that your truth represents 13 truth for the timescale you are going to now 14 experiment with. 15 SESSION CHAIR PORTIER: I think most 16 people understand that. 17 MS. FRANKENBERRY: And we did 18 acknowledge that, I think, in the paper. Some of 19 the Heidelberg datasets were not quite 365 but of 20 course they were much better than 30 samples. So 21 and I think that was our next step in plans. We 22 just only got so far. I think, Nelson, did you

### 202-234-4433 Neal R. Gross & Co., Inc. Page 74 1 want to address it later?

2 SESSION CHAIR PORTIER: It doesn't 3 look like we have any additional questions. Mr. 4 Thurman, did you want to have some comments? 5 MR. THURMAN: Yes, actually I want to 6 bring us up to from, I am not going to say down 7 in the BS pile but from down in the weeds, I want 8 to bring us back a little higher elevation in 9 terms of we get into this discussion. 10 And first of all, I do want to 11 distinguish one area where we do not agree with 12 Syngenta on this. I mean, some of the contention 13 is the assumption is we should only be doing this 14 assessment based on finished water because 15 finished water through all the processes are 16 going to be more blended and smoothed out than

17 raw water. 18 However, the best data we see in 19 finished water is weekly sampling. So we don't 20 know what is happening in between. And I 21 actually was pulling up an example last night for 22 something else and it turned out to be a pretty

### 202-234-4433 Neal R. Gross & Co., Inc. Page 75 1 good example here. This is for one system in 2 Ohio in one year. The magenta are the raw water 3 samples. The dark blue triangles are the 4 finished water samples. And what you see is the 5 finished water follows the same type of pattern 6 we see in the raw water. 7 There is nothing in this that suggests 8 to me that we would expect the finished water to 9 be less variable on the days that weren't sampled 10 than we see in the raw water in this particular 11 system. 12 So this is why we are looking at as we 13 try to define the truth, what are the best 14 datasets out there to define the truth. And 15 those that have more robust sampling are what we 16 are going to work with. 17 The other thing that is interesting is 18 you look here, you see an early season shorter 19 peak and a longer season, a larger peak later in 20 the season. Very similar to the pattern we were 21 showing in the Missouri site. So this is not a 22 pattern that we would not expect to see in some

### 202-234-4433 Neal R. Gross & Co., Inc. Page 76 1 of the community water systems. And so as we are 2 going through the analysis, we are looking at 3 those that have more intensive sampling so that 4 we have a better start with what the truth is. 5 And actually the reason I pulled that 6 sample out in the first place is something Bob 7 Gilliom raised and something some other panelists 8 had asked. We have been talking about atrazine 9 and we are looking at total chlorotriazines. The 10 advantage of the AMP monitoring that Syngenta has 11 done is that they have measured not just atrazine 12 but they have measured the individual components 13 to get at the total chlorotriazines. 14 I was looking at Ohio because I know 15 there is simazine use in Ohio. So I wanted to 16 try to show you an illustration of a site where 17 we have got both atrazine and simazine detected. 18 And you can see the dark blue triangles here 19 happen to be the simazine pattern. The magenta 20 circles are atrazine and the triangles are the 21 total chlorotriazines. 22 This actually shows that simazine is

### 202-234-4433 Neal R. Gross & Co., Inc. Page 77 1 following the same pattern that we see with 2 atrazine but I think that is because it is also 3 being used on corn. In other areas of the 4 country where it has different uses, we may see 5 different timing. 6 We do have this data that we can test 7 that. We can start asking ourselves do we see a 8 different pattern with simazine than we do with 9 atrazine and what effect would that have on 10 there? So we do have that power. 11 Okay, so let's go back to where I was 12 hoping the discussion would kind of help us, and 13 I wanted to explain to the tox people why trying 14 to decide are we looking at one day short-term or 15 longer term and not knowing drives us buggy. 16 This chemograph shows the blue line is 17 your daily measurement at this site. This red 18 line shows that if we were looking at a four-day 19 average, this is what type of -- this is your 20 rolling four-day average concentrations. So you 21 see, there is still a pretty good influence of 22 the shorter day measurements in a four-day

### 202-234-4433 Neal R. Gross & Co., Inc. Page 78 1 exposure. 2 I started working on the 90-day 3 exposure and I got this far and I probably didn't 4 realize okay, I needed to go back and get more 5 data and then decided I needed to sleep more than

6 I needed that. 7 But what I wanted to show is the 8 magnitude. This data point here and moving along 9 starts here, starts whenever you get your first 10 90 days averaged in. So you can see these 11 exposures are muted, potentially missing this is 12 not going to have as big an impact on a 90-day 13 exposure period as it is on a four-day exposure 14 period. So that is why knowing what our exposure 15 window is, really helps us in terms of how we 16 decide and how we interpret the data. So I 17 wanted to put that in to keep in mind, as you go 18 along. 19 Now if we were to take a look at that 20 seven-day sampling frequency that I showed it 21 seems like weeks ago but I think it was the 22 beginning of the week, this is the red line is

### 202-234-4433 Neal R. Gross & Co., Inc. Page 79 1 the four-day rolling average profile you see 2 estimated with all the daily values. The blue 3 line here is that same four-day rolling average 4 profile estimated with the weekly sampling points 5 that you saw in that previous slide. 6 So this is kind of what we are looking 7 at. We see more of a difference, even on the 8 shorter term averages, depending on the sampling 9 frequency than we would otherwise. So this is 10 the context I want you to think about as we get 11 into these questions. And with that, I am not 12 going to throw any more slide at you.

13 SESSION CHAIR PORTIER: Dr. Akana? 14 DR. AKANA: I have a late thought for 15 you. In the HPA world -- Well, first of all, our 16 small group here decided that a one-day exposure, 17 an acute hit is probably going to be okay with 18 atrazine. But in my personal view in the HPA 19 world, a hit say the third cycle away, so you get 20 a hit on the first cycle and if you get a little 21 hit on the third cycle, we are verging into this 22 where you get an extra effect on that third

### 202-234-4433 Neal R. Gross & Co., Inc. Page 80 1 cycle. 2 So now I am interested in little 3 clusters of little spikes. So up one day, down. 4 And then say six days later there is another one 5 day little up and down spike. That, as I 6 understand it, would not be picked up by most 7 sampling of finished water because of the way the 8 water is processed. But if that actually reached 9 -- Well, in the lab you can do that. 10 It can be just as deleterious and 11 verging into an episodic repeated exposure, which 12 is one spike of chronic. Chronic is not just one 13 up-peak and sustained of say atrazine. Little 14 spikes can be bad, too. 15 Now I am wondering if in your work you 16 can detect clusters of little spikes. 17 MR. THURMAN: Boy, that just made 18 things -- 19 If you sample frequent enough, yes. 20 But that gets back to how frequent do you need to 21 sample. And if I go back, if you are looking at 22 something like this, even a creation -- but you

### 202-234-4433 Neal R. Gross & Co., Inc. Page 81 1 can start seeing that. If were say, and I am 2 going to use 20 just as an example and please 3 don't take that as this is what we are looking 4 at, but you can start to estimate how often do we 5 encroach that. And once again, how well we can 6 estimate that. The frequency above a certain 7 threshold value or a certain averaging period 8 threshold value, we can estimate that. It 9 depends on how frequently we have to sample to do 10 that. So, it can be done.

11 SESSION CHAIR PORTIER: I wanted to 12 make the point, too, you know, the spikes can be 13 artificially generated by lifestyle. So suppose 14 the background your tap water is a 20. On day 15 one half of your two-liter is from tap water. On 16 day two you are drinking bottled water. On day 17 three you are drinking tap water again. You have 18 just created that double pulse that you are 19 looking at. And so from EPA's point of view, 20 there is a lifestyle that has got to be 21 integrated into this and how people get their 22 two-liter dose every day, it is not always from

### 202-234-4433 Neal R. Gross & Co., Inc. Page 82 1 this. 2 Dr. Heeringa? 3 CHAIR HEERINGA: Steve Heeringa. For 4 Nelson, you look at this double peak pattern 5 which we have seen, particularly in some of the 6 agricultural drainages. Is this typically the 7 result of pre-emergent and post-emergent 8 application of atrazine or is it the result of 9 random rate of all events following application? 10 Because there is information. If it 11 is pre-emergent/post-emergent, you pretty much 12 know planning time and application times, in 13 terms of intensive sampling. So how much do we

14 know about that? 15 MR. THURMAN: I may give you a little 16 more complex answer. I mean, it could very well 17 be the result of when the farmer is getting out 18 of the field in relation to the rainy period. 19 And it is a conjecture because I don't have the 20 rainfall data at this point. It could be that 21 you had some initial planning going on. And so 22 you had some initial atrazine applications for

### 202-234-4433 Neal R. Gross & Co., Inc. Page 83 1 the short -- then you get a rainy period. And so 2 the farmer could not get back out in the field 3 until later. And then you see the second one 4 coming later. 5 It could be there is a difference in 6 intensities of the rainfall events that you see 7 here. This far apart suggests that you had two 8 different application periods. And it could be 9 for any number of reasons. A lot of times what 10 we have seen is that it is weather-related in 11 terms of how much can the farmer get out before 12 the rains and when do the fields dry up enough so 13 that they can get back out again? 14 SESSION CHAIR PORTIER: Dr. Krishnan? 15 DR. KRISHNAN: I just want to add to 16 the discussion that the spikes and their 17 relationship to the hits, I mean something that 18 is in-between is the internal dose measure. And 19 so these spikes may not necessarily translate to 20 the spikes of the appropriate dose measure in the 21 body that drives the sequence of events. 22 Given the rate of absorption and so

### 202-234-4433 Neal R. Gross & Co., Inc. Page 84 1 forth, the appropriate dose surrogate tends more 2 like the total chloro products. So I think one 3 of the focus would have to be, well essentially 4 because you can relate those effects more closely 5 to those internal dose measure, rather than to 6 the external spikes and the internal dose measure 7 would be more on the early end of the curve in 8 rating these.

9 And one of the focus would have to be 10 considering the integration of the drinking water 11 input with the PBPK model so that some of the 12 dose metric profiles can be evaluated in the 13 context of the detail evaluation as they go 14 forward. I think that would certainly add to the 15 science basis of qualities evaluations.

16 SESSION CHAIR PORTIER: Excuse me. I 17 have 10:17. We will take a 15 minute break and 18 then we will see if my gamble of increasing 19 understanding reduced the uncertainty in the 20 discussion time. 21 We will return at 10:35. 22 (Whereupon, the foregoing proceeding

### 202-234-4433 Neal R. Gross & Co., Inc. Page 85 1 went off the record at 10:18 a.m. and 2 resumed at 10:38 a.m.) 3 SESSION CHAIR PORTIER: Mr. Thurman, 4 I guess you are reading the questions. Hey, we 5 are not on question 1.9 anymore. Okay, Dr. 6 O'Byrne? 7 DR. O'BYRNE: Could I just ask one 8 very brief question? I was very surprised at 9 your graph that you plucked out last night from 10 wherever that the level of atrazine in the 11 finished drinking water showed the same profile 12 as raw, if I understood it properly. And you 13 sort of used that as evidence to criticize 14 Syngenta for focusing on finished water. I may 15 be misinterpreting this. 16 I am absolutely amazed that you see 17 the same profile because it depends on where that 18 finished water came from. I mean, was it a big 19 pool? A small pool? Because I would thought 20 there would have been a massive dilution of 21 anything.

22 MR. THURMAN: And I am not sure I

### 202-234-4433 Neal R. Gross & Co., Inc. Page 86 1 would call it a criticism. I think it is a 2 distinction between the way we look at things and 3 the way we interpret things. We have some 4 smaller community water systems that don't have 5 much of a holding period where you do see the 6 atrazine moving through and unless you have 7 sufficient carbon filtration, the atrazine will 8 continue to move through the system. 9 Some of the smaller systems I think 10 you heard Alan Roberson talk about that in the 11 public comments, they do try to treat. And some 12 of the systems we do see where the treatment is 13 knocking down the atrazine levels, sometimes 14 because carbon filtration is expensive, they 15 don't necessarily have it all year round. They 16 try to time it as best as they can. Sometimes 17 they get it, sometimes they miss. 18 Sometimes you see in some of the 19 systems where for the most part it is down but 20 then you will a spike coming through. But there 21 are a few systems that we are looking at that do 22 have a similar profile to what we see.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 87 1 And the point we are making is we 2 don't necessarily want to wholesale right off 3 what we think are some valuable robust datasets 4 because they are not finished water sets. It is 5 what Bob Gilliom is talking about, how you 6 defined the truth. And if we have the robust 7 data sets that have sampling patterns and shapes 8 and patterns that are similar to what we are 9 seeing in these community water systems, we think 10 those are still very valuable. In fact, more 11 valuable to develop our statistical analysis and 12 the approach we take to evaluating the monitoring 13 strategies because they do capture that frequency 14 that is smoothed out when you have weekly 15 sampling or less frequent sampling. 16 So that was the point I wanted to try 17 to make in terms of that distinction. It is not 18 meant as a criticism but I think the reason we 19 are not writing off well water samples just 20 because they are not finished drinking water. 21 SESSION CHAIR PORTIER: This is Ken 22 Portier. It probably also reflects their

### 202-234-4433 Neal R. Gross & Co., Inc. Page 88 1 conservative nature. Right? So they look for 2 worst-case scenarios and they do their risk 3 assessment from a worst-case scenario, figuring 4 that that is going to be protective for everybody 5 else who are in better case scenarios from a 6 public health point of view. 7 Question 2.1. 8 MR. THURMAN: Okay. In conjunction 9 with the toxicological review presented in the 10 issue paper, the Agency has also discussed 11 methods for re-evaluating the sampling frequency 12 that is necessary for determining, with 13 confidence, concentrations of the pesticide in 14 water that sources drinking water. These have 15 included different methods for estimating 16 pesticide concentrations between known sampling 17 events and examining the performance of different 18 sampling strategies for averaging periods of 19 different durations. The Agency seeks feedback 20 from the Panel with regard to how the uncertainty 21 and variability in both the monitoring data and 22 in the toxicity data (i.e., the point of

### 202-234-4433 Neal R. Gross & Co., Inc. Page 89 1 departure) can be integrated to characterize and 2 to interpret the potential significance of 3 atrazine concentrations in drinking water. 4 Given the nature of the temporal 5 patterns of pesticide occurrence in surface 6 waters described in Section 5.2 of the issue 7 paper, including serial correlations from day to 8 day, periodicity in elevated concentrations 9 within seasons and from year to year, detections 10 below quantitation data, and uncertainty in the 11 shape of the pesticide distributions in surface 12 waters, what statistical approaches should the 13 Agency consider in determining confidence bounds 14 on exposure estimates from monitoring data? 15 Please comment on how the approach may vary 16 depending on the duration of concern. 17 SESSION CHAIR PORTIER: Dr. Young? 18 DR. YOUNG: Well, considering 19 confidence bounds on exposure estimates for 20 monitoring data, a key consideration is what is 21 being estimated. Now that sounds pretty simple 22 but here that seems to be quite a challenge.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 90 1 So what you do differs on whether we 2 want to estimate a specific quantile given daily 3 data, or rolling average data, or if we want to 4 estimate the peak or whatever we want to do. 5 So, I want to put that out there first 6 because what we suggest will differ depending 7 upon what the final decision is. 8 So, if say I want to -- spikes seem to 9 be important. And if I want to estimate a 10 particular quantile, say the 99.99 quantile, the 11 99th percentile over the course of a period of 12 time, and let's suppose that is my goal for right 13 now. Okay? And if I want to say -- I think 14 another question that has to come up with this 15 particular atrazine, with this particular 16 application, is whether you want that for the 17 whole year or for a concentrated period of time 18 in which the concern is greatest. In other words 19 from prior to the start of planting to harvest or 20 sometime in that time frame. Because you know 21 that in most years, it is not as great of a

22 concern.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 91 1 The easiest way to do such a sample 2 set in those confidence bounds is to know the 3 distribution. And then you take advantage of the 4 properties of the distribution to set confidence 5 intervals. 6 The problem is I don't think anyone 7 here is comfortable with knowing what that 8 distribution of values is. And when you do not 9 know that, then you are pretty much moving toward 10 non-parametric approaches. And I see that both 11 in that EPA does and Syngenta does and I think 12 that is the right approach.13 Now, in order to actually use non14 parametric approaches, one of the big things that 15 comes up is sample size. And basically, you have 16 to have enough data if you want to estimate those 17 extreme quantiles with any precision. 18 So if you want a 0.95 quantile, you 19 need at least 20 observations, at least. The 20 standard there may be unacceptably large for that 21 sample size but that is a minimum and if you want 22 a 0.99, you need a hundred. Okay? That is just

### 202-234-4433 Neal R. Gross & Co., Inc. Page 92 1 the reality of what you have to have in order to 2 do a decent job. 3 And I saw a table of the sample sizes 4 in one of the Syngenta documents somewhere here. 5 And I put a similar one but I think -- and also 6 it is in the ILSI report that you referenced in 7 the Appendix A. I thought the Appendix A in that 8 report did a very nice job of outlining options 9 and certainly those could provide great guidance. 10 In that report, some simulation was 11 done and found that based on the same thing we 12 are seeing is interpolating among values and 13 dense datasets. And what they found was that 14 there was a tendency to overestimate the 15 quantiles, the extreme quantiles. So that is a 16 little conservative. And I believe the reason 17 that is the case is that inherent in these 18 methods is the assumption of a random sample and 19 the presence or correlation results in the 20 effective sample size being smaller than that 21 taken. And so we are actually pushing it out a 22 bit more.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 93 1 And so I think work, that is a hard 2 problem, but I think work on how to actually 3 figure out what the effective sample size is and 4 refine those methods may be something you are 5 interested in but it is somewhat comforting from 6 the public standpoint that it is a conservative 7 estimate at the present time. 8 If we move to these rolling averages, 9 then the problem is further complicated because 10 normally we think in an independent sample, the 11 variance goes down. You just divide by the 12 sample size as far as the mean goes but you have 13 this positive correlation, which tends to keep 14 that variance inflated a bit.

15 And so that would need to be 16 considered in these methods. I have also thought 17 a little bit about using an extreme value theory 18 in this setting and especially on the rolling 19 averages because as soon as you begin averaging, 20 then you can begin to appeal to perhaps the 21 central limit theorem and if the data aren't too 22 skewed, then maybe you can begin to use some of

### 202-234-4433 Neal R. Gross & Co., Inc. Page 94 1 those ideas to reduce sample size. I haven't 2 fully explored that but I think it is something 3 worth looking into. 4 SESSION CHAIR PORTIER: Thank you. 5 Dr. Coupe is next. 6 DR. COUPE: Thank you. I think first 7 off I need to clear up something. This corner of 8 the table has been referred to as hydrologists or 9 hydrology. There is actually only two 10 hydrologists and two statisticians. 11 (Laughter.) 12 SESSION CHAIR PORTIER: That is an 13 important point, yes. 14 DR. COUPE: Yes, I spent an hour being 15 told what the difference between Bayesian and a 16 frequentist is. I still have no idea. 17 So my remarks are going to be, I am 18 not going to touch too much on the statistics but 19 mostly on the observations on the hydrology of 20 what we are talking about. 21 To begin so there is an issue on what 22 data should be used to determine exposure

### 202-234-4433 Neal R. Gross & Co., Inc. Page 95 1 assessments. There is data on atrazine 2 concentrations from the intake, the stream or 3 reservoir side, and then there is finished water 4 data. the U.S. EPA has decided to use the intake 5 values for assessment of human exposure. 6 The gentlemen from CropLife and 7 Syngenta suggested that the more appropriate data 8 to use to evaluate human exposure is the finished 9 water values. I can see both sides of this 10 argument as there can be considerable difference 11 between intake concentrations and the 12 concentrations in the finished water. However, 13 there are a number of studies showing that a 14 treatment plant effectiveness in removing 15 atrazine is variable depending upon many factors, 16 which includes the type of water, the organic 17 matter content or the pH, the type of treatment, 18 how well trained the treatment plant operators 19 are, the maintenance of the treatment. In some 20 cases atrazine survives the treatment process 21 relatively unaffected. Given this, I think it is 22 appropriate to use the intake values to estimate

### 202-234-4433 Neal R. Gross & Co., Inc. Page 96 1 the exposure to humans with the understanding 2 that this is a conservative estimate and that the 3 actual exposure may be less. 4 Given that, I do think Syngenta made 5 a valid point in bringing up the fact that the 6 community water system, that data that we are 7 shown by the U.S. EPA, would not have been used 8 for drinking water, as that plant selectively 9 pumps from the stream into a holding pond and 10 from there into another larger holding pond. 11 And I think this model is more common 12 in the small community water systems that take 13 directly from a stream. They don't have intakes 14 on the reservoir. And in this case, the 15 appropriate place to sample the water used by the 16 plant to evaluate human exposure, would have been 17 from the intake from the larger pond. The data 18 as shown gives a misleading impression of high 19 exposure from this community water system. 20 There are uses for these data, of 21 course, such as ecological exposure but it seems 22 inappropriate for the question being asked here.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 97 1 The duration of concern makes a big 2 difference to the sampling strategy. If the 3 duration of the concern is very short, that 4 intensive sampling during expected high 5 concentration period is probably the only real 6 answer. But as the duration of concern 7 increases, the sampling intervals can be eased 8 and if the duration gets long enough, you can 9 actually estimate it from models such as WARP. 10 And in general, it seems that most 11 sites in the AMP program run by Syngenta, the 12 variability and the amplitude of the data are not 13 that great. If you look at page 94 where it 14 states in the White Paper from the U.S. EPA, it 15 states that 90 to 96 percent of the data are less 16 than three parts per billion. And Syngenta shows 17 pretty much the same thing in their response on 18 pages seven and eight. 19 Now this is good news in the sense, 20 especially when you consider these data are 21 biased with more frequent sampling during 22 expected periods of high concentration. In fact,

### 202-234-4433 Neal R. Gross & Co., Inc. Page 98 1 the AMP data suggests that there is only a subset 2 of some 27 or so of highly vulnerable community 3 water systems. 4 And to my mind, these sites probably 5 need to be treated separately and more carefully. 6 For the other sites, the 120 or so, the 7 concentrations are relatively low and don't 8 exceed the MCL often. But I suspect that is 9 because of the storage dynamics of these 10 reservoirs and these community water systems 11 probably have low -- 12 Okay, what I wanted to say was that 13 these community water systems probably have 14 consistently low levels of atrazine in their 15 source water throughout the year because of 16 storage dynamics. And realistically, probably 17 more people are exposed to low concentrations of 18 atrazine for longer periods of time than they are 19 higher concentrations at shorter periods in time. 20 I thought of one other things when we 21 were talking, I think Dr. Akana brought it up and 22 a couple of other people were talking about the

### 202-234-4433 Neal R. Gross & Co., Inc. Page 99 1 spikes, and so far mostly what we have seen in 2 our chemographs are, I suspect just very small 3 sites. And so they show a very sharp one or two 4 peaks. 5 If you move to larger sites, you can 6 have multiple peaks. Especially if you take a 7 look at the Missouri data, you can see multiple 8 peaks during drinking water season kind of 9 depending on whether it is raining in Iowa or it 10 is raining in Missouri, or raining in Nebraska. 11 So you can have, in one community system, you can 12 have a number of small spikes but they can 13 consistently come through your system. 14 Thank you. 15 SESSION CHAIR PORTIER: Thank you. 16 Dr. Gilliom? 17 DR. GILLIOM: I'll just supplement, 18 rather than repeat some of what has been covered. 19 The first part of the question is related to what 20 approaches should be used to consider in 21 determining confidence bounds on exposure for 22 monitoring data. And so far we have talked

### 202-234-4433 Neal R. Gross & Co., Inc. Page 100 1 mostly about the use of site-specific data to 2 estimate those confidence bounds. And I just 3 want to make the point that there is also a range 4 of more indirect approaches using inference from 5 existing data. And there is basically probably 6 two categories of that. One you have heard a lot 7 about in relation to the sampling experiments of 8 taking these highly sampled data sets and driving 9 relationships that show how confidently we can 10 estimate a particular value with a given sampling 11 frequency. 12 So those are kind of categorical 13 things. The Crawford 2004 paper and the ILSI 14 appendix are good examples of that, which have 15 then been extended further by Syngenta and EPA 16 and they have plans to do even more. 17 So those give you a good initial 18 estimate in many cases of what kind of confidence 19 bounds to expect on any particular concentration 20 statistic. And you can re-do it for other ones 21 if you need to so it gives you an idea of how 22 much you have to worry about it.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 101 1 The second category which we have also 2 just had mentioned here is the WARP model type 3 approach, which is really just a multiple 4 regression approach to relate basing 5 characteristics to concentrations and create 6 predictions. That is another indirect way to 7 make, based on the data we have already 8 accumulated from many sites, make estimates of 9 both the concentration statistic and the 10 confidence bounds for unmonitored sites. 11 And I bring those type of methods up 12 mainly, and particularly the second one on the 13 regression models is that a big part of the 14 approach here in the end is going to be to 15 identify the relatively small proportion of sites 16 that need the most intense energy applied to them 17 for the high sampling problems and so forth. 18 And this gives us a direct and 19 quantitative way of getting at that, both what 20 the expected concentration statistic will be and 21 what the expected confidence bounds on that will 22 be, which can now be done.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 102 1 And then the second part of the 2 question is related to the duration of concern 3 and how the approach might vary. And I guess I 4 just want to reiterate the point that I think has 5 already been made a couple of times and it is 6 probably obvious at this point but the shorter 7 the duration of the concentration statistic, the 8 more intense data we need to get truth. 9 And it seems simple but it just 10 reiterates how much the answer that we come up 11 with on monitoring design is driven by how you 12 define very specifically the concentration 13 objective. So the Agency in the end is the one 14 who has to do that from what you all say but we 15 need to know the amount, the time frame, and the 16 confidence bounds required to meet the 17 requirements of the Agency and then you can 18 design around that. 19 SESSION CHAIR PORTIER: This is Ken 20 Portier. Just to clarify, when you say intense 21 data, you mean temporally dense measurement. 22 DR. GILLIOM: I will say in a more

### 202-234-4433 Neal R. Gross & Co., Inc. Page 103 1 general way, temporally intense in relation to 2 the sought concentration objective.

3 SESSION CHAIR PORTIER: Dr. Lee?

4 DR. LEE: I don't have too much to add 5 to what has already been said. I just want to 6 make two small points. One is that if we are 7 talking about confidence bands, I think it is 8 important to take into account some of the 9 sources of variability that we are not looking at 10 right now like measurement error. 11 You know, if you go and measure the 12 stream, if two different people do it, you are 13 going to get somewhat different answers probably. 14 And that sort of variability needs to be taken 15 into account, if you want to make a precise 16 confidence statement. And that doesn't17 necessarily have to be estimated on a stream-by18 stream basis. I think we can learn a lot about 19 that sort of measurement globally and just apply 20 an estimate there. But that sort of variability 21 should definitely be taken into account. 22 And the second point I want to make is

### 202-234-4433 Neal R. Gross & Co., Inc. Page 104 1 that sort of follow on to some of what has 2 already been said, that the way you are going to 3 estimate the confidence band really depends on 4 what sort of model you are using to fill in the 5 gaps. Assuming you are not doing daily sampling, 6 you need some sort of model to say how we are 7 going to fill in the gaps and then the type of 8 confidence band is going to follow from that. 9 So I do want to disagree somewhat with 10 Syngenta's statement that we don't need modeling. 11 It is a model of some sort, even if we are doing 12 linear interpolation. That is a model. And so 13 either we need to sample daily or we need to use 14 some sort of model to fill in in-between. And 15 most likely, it is not a need to sample daily 16 because we can fill in in-between. But it 17 requires some model and that is going to affect 18 how we are going to compute confidence bounds. 19 SESSION CHAIR PORTIER: Thank you. We 20 will open it up to the rest of the panel. 21 Comments? Dr. Hayton? 22 DR. HAYTON: Do we have any idea of

### 202-234-4433 Neal R. Gross & Co., Inc. Page 105 1 how big a daily dose is the threshold of concern? 2 Because I am showing these chemographs showing a 3 hundred parts per billion. That is a hundred 4 micrograms and in two liters, 200 microgram daily 5 dose. Would that ring any bells in the BPA/BPH 6 signaling network? And to me, if it doesn't, do 7 we need to catch those peaks? 8 SESSION CHAIR PORTIER: Dr. O'Bryne? 9 DR. O'BYRNE: I don't think we have 10 any evidence at all that the small amounts have 11 any effect. They are orders of magnitude 12 greater. 13 SESSION CHAIR PORTIER: And I think 14 that has been said a couple of times before. 15 Maybe that is a subheading to our final report. 16 Any additional comments? Yes, Dr. 17 Heeringa. 18 CHAIR HEERINGA: Steve Heeringa. The 19 question may be for EPA. Thinking about the 20 simulations that you have done and that Syngenta 21 did and we get this sort of rough projection from 22 a simulation done on some periodic sampling to at

### 202-234-4433 Neal R. Gross & Co., Inc. Page 106 1 least truth as defined in an empirical data set 2 and we get factors like 1.5 or 1.24. How would, 3 in the context of where you set these limits, we 4 have uncertainty factors, is that sort of 5 uncertainty built into what you would think of as 6 your typical uncertainty factors or is this 7 something additional? 8 MR. THURMAN: Okay, we have wrestled 9 with how you do with uncertainty. I think you 10 have heard, for instance, that atrazine you have 11 heard the value is 12.5 and 37.5 used. When we 12 are looking at the weekly monitoring of these 13 community water systems, we have been looking at 14 how is that, because it is more intensive 15 sampling, we have been comparing that to a 37.5, 16 with less intensive sampling because there is 17 uncertainty in that we have been looking at the 18 12.5. So there is kind of a 3X that has been 19 used in that regard. 20 So it is possible that we might hold 21 that monitoring uncertainty, if you will, in as 22 part of the overall uncertainty or safety factors

### 202-234-4433 Neal R. Gross & Co., Inc. Page 107 1 that we look at. 2 DR. LOWIT: Anna Lowit. Just to add 3 to that, to sort of talk about the source of 4 where that comes from, as atrazine is regulated 5 under the food quality protection act, the FQPA 6 has a provision that requires the application of

7 the 10X. And that 10X accounts for both hazard 8 and exposure and that 10X value can be reduced, 9 as Nelson was talking about, the three, based on 10 information that the Agency looks like and the 11 science supports doing that. It can also be 12 increased. 13 So I just wanted to make sure that was 14 explicit of where that would be derived from.

15 SESSION CHAIR PORTIER: Dr. Reed? 16 MR. THURMAN: And by the way, this is 17 why you need hazard and exposure folks working 18 together on this. 19 DR. REED: I just want to put in a 20 caveat about the comparison, the water level and 21 then two liters per day and compared to the 22 animal study, there is a lot of "uncertainties"

### 202-234-4433 Neal R. Gross & Co., Inc. Page 108 1 because you have the interspecies variability 2 considered and also inter-individual 3 consideration. And so a straight comparison 4 probably is not very productive. 5 SESSION CHAIR PORTIER: Any additional 6 comments? Okay, I think we have gotten some good 7 comments, Dr. Young and the four. Dr. Heeringa? 8 CHAIR HEERINGA: Just one additional 9 comment. You know, I support what Dr. Young 10 indicated, too, and I think others that Dr. 11 Gilliom with regard to sort of differential 12 sampling over the years. I mean, if we think 13 about it simply as a sampling problem from a 14 frequentist's perspective, we would essentially 15 allocate sample to these intervals in proportion 16 to the standard deviation, the measures within 17 the intervals. And this can be adaptive, too. 18 In other words, you could start with a 19 periodicity and depending on the water system and 20 the information that is gleaned over time. So I 21 think rather than trying to hit a home run the 22 first time, try to get into the ballpark and then

### 202-234-4433 Neal R. Gross & Co., Inc. Page 109 1 think about refinement as you collect additional

2 data. 3 SESSION CHAIR PORTIER: And this kind 4 of was a question that came up as I was reading 5 this. This is Ken Portier. 6 When these community water systems 7 take these samples and process them, what is the 8 lag time between the sample and the number 9 actually being received back to the process, the 10 CWS manager? Is that hours, days or months?

11 DR. COUPE: All of the above. 12 SESSION CHAIR PORTIER: Really? What 13 is the median on that? Is that weeks? 14 (Laughter.) 15 SESSION CHAIR PORTIER: I didn't want 16 to max and min. I am more of a median. Is that 17 like weeks or days? 18 DR. COUPE: Oh, it is probably on the 19 order of days but there are some very large 20 systems that have large holding times and there 21 are very small systems that -- 22 SESSION CHAIR PORTIER: Shift it off.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 110 1 Excuse me. What was that? Weeks. 2 Because you know, -- yes, ma'am? 3 Please identify yourself. 4 MS. BISCOE: Melanie Biscoe. I am the 5 CRM or Chemical Review Manager for atrazine. 6 I think Syngenta has been talking 7 amongst themselves a little bit back here, and we 8 actually discussed this earlier this year. So 9 about ten days in the EPA, Syngenta monitoring, 10 CWS monitoring program, that you actually get the

11 numbers back. 12 SESSION CHAIR PORTIER: So this has an 13 impact for some of the things that statisticians 14 and samplers would like to say which is well, you 15 could do adaptive sampling. Once you start to 16 see it go up, you increase the sampling rate. 17 But if there is a ten-day lag and many of these 18 windows are 20 to 30 days wide, that methodology 19 is probably not feasible here. And then you are 20 stuck with kind of choosing a window of time and 21 increasing your sampling during that window of 22 expected peaks and decreasing it.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 111 1 So the current methodology is feasible 2 within the practical limits of the sampling and 3 turn around time. 4 Now of course if you had a dip stick 5 methodology and a color code that said high, you 6 could use something like that to increase your 7 sampling, even to within a day. I mean, you 8 know, if it really was moving fast, you could be 9 picking samples hourly. 10 Dr. Heeringa? 11 CHAIR HEERINGA: Steve Heeringa. Just 12 to be clear, when I was talking about being 13 adaptive, I was thinking the feedback might be 14 annual. But as usual, Dr. Portier has a shorter 15 cycle on these things than I do. 16 SESSION CHAIR PORTIER: So you are 17 talking about using last year's profile to tell - 18 - The unfortunate problem with that, of course, 19 is climate. 20 So you know, a lot of this does seem 21 to have a relationship to rainfall. And so while 22 there is a persistence in climate, it is not

### 202-234-4433 Neal R. Gross & Co., Inc. Page 112 1 strong enough that you can really use that. 2 CHAIR HEERINGA: But I would say that 3 there are multiple variables in this work model, 4 including how much crops planted, the absorption 5 of the system, flux through the system. That 6 probably has more temporal permanence than the 7 climate. We are not going to predict the 8 rainfall but we can predict roughly when people 9 are going to plant crops, when the atrazine is 10 going to go on the field and roughly how systems 11 are going to respond in the cross different 12 rainfall events. 13 So I think we are averaging over and 14 we don't want to over adapt. But I am just 15 saying that if you were in a system that clearly 16 showed much more variability than the sort of 17 averages on which you are basing your sampling 18 plans, then there might be an argument over time 19 to intensify sampling for that system, until you 20 were confident that you were getting what you 21 wanted for that system. 22 SESSION CHAIR PORTIER: This is Ken

### 202-234-4433 Neal R. Gross & Co., Inc. Page 113 1 Portier. And I think we are only repeating 2 recommendations we made at the SAP a year ago 3 when we looked at the ecological issues related 4 to environmental sampling. So you can go read

5 those. 6 Dr. Gilliom. 7 DR. GILLIOM: Just, one comment here 8 since it is not really brought up in the charge 9 questions later, and it is on this issue of 10 whether there is some short-term adaptive 11 approaches that could be taken. And I don't 12 think it is worth getting heavily into this at 13 this point. 14 But if it was to turn out that there 15 is a really short term concentration objective 16 that is extreme, like a one or two-day type of 17 thing, then it really would be possible to use a 18 quick screening process, like an amino assay test 19 for atrazine triazines and just do it in the 20 water plant and make decisions. 21 So there are tools. They can trigger 22 a laboratory analysis and they are well-known and

### 202-234-4433 Neal R. Gross & Co., Inc. Page 114 1 well-characterized. So if that becomes a big 2 issue, I think it is a discussion item that 3 should be thought through. 4 SESSION CHAIR PORTIER: Make sure you 5 add that to the report. 6 Okay, I think we have stretched this 7 one out as long as we can. Why don't we move to 8 question 2.2? 9 MR. THURMAN: I would be glad to. The 10 first two simulation methods presented in Section 11 5.5 are applicable to the specific data sets they 12 describe, although some generalities regarding 13 shape patterns appear to exist. Given this 14 information, please comment on the strengths and 15 weaknesses of the approaches and on the practical 16 merits of pursuing them or some other numerical 17 approach with a larger set of higher 18 concentration systems. Please comment on how the 19 methods for determining confidence bounds might 20 apply given these considerations. 21 SESSION CHAIR PORTIER: Dr. Gilliom. 22 DR. GILLIOM: Okay so some of this has

### 202-234-4433 Neal R. Gross & Co., Inc. Page 115 1 been talked about a lot. So I am going to kind 2 of abstract from my comments.

3 Both the methods that are referred to 4 in here follow the same concept we have talked 5 about this morning. And generally it is the 6 concept described in the Crawford paper 2004 in 7 which the actual data for selected sites are 8 interpolated between samples, and then treated as 9 truth, and then sampling experiments are done

10 from them. 11 So I think as I said before, probably 12 my comment would sum up that the approach makes 13 sense if the initial actual data are sufficient 14 to simulate reality for the problem at hand. 15 And so in this specific example, just 16 to pick on the two ones that are in here as 17 examples, is that they are not, they are examples 18 of simulated truth from real data that are not 19 adequate to address a short-term concentration 20 objective. So these were examples generated from 21 30 to 40 samples a year and then they were 22 interpolated to create a simulated truth, and

### 202-234-4433 Neal R. Gross & Co., Inc. Page 116 1 then they were subsampled to test how they did 2 for doing shorter term concentrations. It is 3 like a seven-day or four-day average or whatever. 4 So and I think everybody realizes that 5 but they are actually good examples of what to 6 watch out for. The analytical process is fine 7 but the specific application is not appropriate

8 for short-term. 9 And so I think the general point I 10 would leave it with is that yes, the basic 11 approach is good. We have to make sure that once 12 the concentration objectives are defined very 13 precisely and probably more precisely than 14 anybody is going to feel comfortable with on the 15 biology end but the Agency is still going to have 16 to do it is that then we design a sampling 17 analysis process that fits that. 18 And I think I will just leave that

19 there. 20 SESSION CHAIR PORTIER: Dr. Coupe? 21 DR. COUPE: I don't think I have too 22 much to offer to Dr. Gilliom. I just say there

### 202-234-4433 Neal R. Gross & Co., Inc. Page 117 1 isn't a great method for extrapolating these 2 data. You have what you have and if you need to 3 find a resolution then you just need to collect 4 more, collect measurements.

5 SESSION CHAIR PORTIER: Dr. Lee? 6 DR. LEE: I don't think I really have 7 anything to add to this one. I will have more to 8 say probably later about modeling and bringing it 9 in but I will hold that to number four. 10 SESSION CHAIR PORTIER: Dr. Young? 11 DR. YOUNG: This is one that probably 12 from your view, unfortunately, I feel strongly

13 about. 14 The real question that is not answered 15 that really has to be answered before we know how 16 to simulate is how important are the peaks and 17 how long do the peaks last? And we don't really 18 have that information right now. But there is 19 one thing that I think needs to be made really 20 clear and I think we have hit around it several 21 times but it so important I want to hit it again. 22 If one wants to draw inference at the

### 202-234-4433 Neal R. Gross & Co., Inc. Page 118 1 daily level, based solely on the data collected, 2 sampling must occur at least daily. If one wants 3 four-day rolling averages, you can't have a 4 rolling average without a least two values. So 5 the minimum would be two in those four days and 6 that may not be enough. 7 Simulations, models or any other 8 approach that suggests otherwise is making some 9 strong assumptions about what happens at the 10 finer timescale. 11 Now, if a good understanding of the 12 systems exists, then one may be able to model the 13 results, in which case sampling could be 14 confirmatory. But this requires knowledge of the 15 system and sufficient supporting data to 16 construct such a model for each side, something 17 that is not present here, at least not yet.

18 It does seem to be reasonable to 19 concentrate sampling effort during the time of 20 exposure. However, as Bob has noted several 21 times, the sampling scheme developed for atrazine 22 may not be applicable to other contaminants.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 119 1 The thing that bothers me about all 2 the simulations that we have seen here is that 3 they are smooth versions of reality and that is 4 true even for the daily data that we have. There 5 is no accounting for measurement error, 6 variability within the day, or all the other 7 things that happen when you are out in the field. 8 And anyone who has been there knows how bad that

9 can be.

10 It would seem to me that a more 11 reasonable approach for simulations is to try to 12 bring some modeling information such as the WARP 13 to generate chemographs with typical behavior and 14 then to bring the variability associated with 15 that modeling process to bare. So you would have 16 a realization of the chemograph followed by an 17 analysis in that realizations would be replicated 18 so you would capture all of the variability in 19 the system. You wouldn't just be hinging on one 20 particular realization of the chemograph. 21 Because even if it is real, it is dead and gone. 22 That is not about what is happening in

### 202-234-4433 Neal R. Gross & Co., Inc. Page 120 1 the future and I think we need to capture that 2 variability in the simulations because I think as 3 a consequence of doing it the way we have been 4 doing it, it makes everything look better than it 5 should and that is a little scary. 6 So that is, I think, the primary point

7 I want to make. 8 SESSION CHAIR PORTIER: Additional

9 comments? 10 This is Ken Portier. When I looked at 11 this, you know, to me the strength of the 12 methodology as Linda mentioned in the first 13 question is that is its non-parametric nature. 14 So a lot of it you are going kind of back to 15 first principles of sampling. You are 16 simulating. So to me, that is the strength of the 17 process. 18 The weakness is the starting data. It 19 is clear. You know, if the starting data is an 20 inadequate representation of what is really 21 happening that the water system, nothing that we 22 can do statistically is going to improve that

### 202-234-4433 Neal R. Gross & Co., Inc. Page 121 1 starting data with any kind of first principle 2 statistical methodology. You are going to have 3 to go to modeling or more sampling. I mean, it 4 is kind of that simple. 5 Now, I personally like the WARP 6 approach because I know that there is other data 7 out there, climate data, soil data, that is 8 sampled even more regularly than these water 9 system data is sampled. And so through modeling 10 we can use the correlation relationship and be 11 able to impute a little more of what is going on. 12 And so I do like that kind of approach 13 because it just uses more data, uses the 14 information. And that includes kind of modeling

15 from the well water to the water that comes out 16 of the community water system. I haven't seen 17 any modeling talking about the effectiveness or 18 the methodology. 19 I mean, you talk about activated 20 carbon systems but do those fail when the 21 concentrations reach a certain level. I mean, 22 you know, some of these systems work well when

### 202-234-4433 Neal R. Gross & Co., Inc. Page 122 1 there is just a little bit coming in. But then 2 if the ability of the carbon to capture these 3 molecules gets overwhelmed by the concentration, 4 you could actually have a discontinuous peak kind 5 of event happening as well. So I think you need 6 that kind of. And that is probably a whole other 7 division in EPA that you have to go and talk to. 8 Right?

9 Mr. Thurman? 10 MR. THURMAN: I do want to point out 11 on the drinking water treatment, we have actually 12 came to the SAP a number of years ago on drinking 13 water treatment and what we knew, what the state 14 of the published literature was on that. We have 15 continued to keep an eye out on that and update

16 that to the extent we do. 17 Generally when we are doing drinking 18 water exposure assessments that would be used in 19 dietary exposures, we addressed drinking water 20 treatment effects as separate at another end of 21 the process. So we didn't bring this to you 22 because we addressed them separately but it is a

### 202-234-4433 Neal R. Gross & Co., Inc. Page 123 1 point well taken. 2 In fact, I looked at it, and you are 3 starting to look at sources of variability. You 4 throw in the drinking water treatments, you start 5 to expand your sources of variability that you 6 have to address. So we were trying to take a 7 simpler approach then we can layer that on. But 8 that is a point we will. 9 SESSION CHAIR PORTIER: I mean, I 10 recognize as a public health risk assessment 11 methodology, you can put limits on raw water 12 because as long as you can argue through that raw 13 water back to a consumption and a risk. 14 So I mean I recognize that as long as 15 you have kind of got that continuum explained, we 16 can still go back and say well but we don't want 17 to see any input, raw waters above a certain 18 level because we know that gets translated for 19 all these processes, with all these uncertainties 20 into levels that are not safe. So, you know, it 21 is just that, and you guys know. 22 Any additional comments? Dr. Gilliom.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 124 1 DR. GILLIOM: Just to add to the 2 thought on the model application. I think we are 3 in a position to very effectively use the 4 available models built from existing data to 5 identify with known probability the sites that 6 need the attention for a specific objective. 7 So there is a lot of points in there 8 to follow but once the objective is defined we 9 can, in other words, estimate which specific 10 sites. And then I think we have to remember in 11 evaluating all these methods, that and it is the 12 agency's direction, I think appropriately, that 13 once you are to that point, each individual 14 system on its own becomes the focus, not some 15 aggregate statistics for that group or anything. 16 It is that system and those people that use that 17 system. 18 And at that point, the problem can be 19 further evaluated as needed, including adaptive 20 sampling or in some cases as brought up in 21 examples, differences between the intake screen 22 water, holding reservoirs and finished water.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 125 1 Because at this point, you are down to a very 2 small proportion of the community water supplies. 3 So it is a part of an overall 4 decision-making process that right now we are 5 only talking about he FIFRA add-on, that is what 6 I call it anyway, to regular compliance 7 monitoring. We haven't even, I mean, a 8 compliance monitoring is not involved yet. It is 9 still over there on quarterly sampling per year 10 but it could eventually be affected by this down 11 the road if the Office of Water chooses to do

12 that. 13 SESSION CHAIR PORTIER: Okay, I don't 14 see any additional questions. I think you got a 15 pretty good answer on that one. 16 MR. THURMAN: I think we got an

17 answer.

18 SESSION CHAIR PORTIER: Let's move to

19 2.3. 20 MR. THURMAN: As described in Section 21 5.4.2 of the issue paper, the Agency is 22 considering the use of a confidence interval or

### 202-234-4433 Neal R. Gross & Co., Inc. Page 126 1 prediction interval approach to characterize the 2 uncertainty of exposure estimates derived from 3 monitoring data of varying sampling frequencies. 4 Please comment on the strengths and weaknesses of 5 either placing confidence bounds on the rolling 6 average estimates and comparing to the upper 7 limit from monitoring against the level of 8 concern or, conversely, placing confidence bounds

9 on the LOC. 10 And I apologize. That was written by 11 committee. I hope you will be glad to clarify

12 that. 13 SESSION CHAIR PORTIER: Dr. Coupe, you 14 are first up. It looks like there were four 15 people assigned to these four questions and then 16 Joe used the random number generator to assign 17 who was first. 18 DR. COUPE: When I saw the list of 19 questions come out without names attached, I 20 looked at 2.3 and said, "Dear God, I hope I don't 21 get that one." 22 (Laughter.)

### 202-234-4433 Neal R. Gross & Co., Inc. Page 127 1 DR. COUPE: I think I understand the 2 second part of this. And I will paraphrase and 3 you correct me if I am wrong but you are talking 4 about in the second part of taking the 5 uncertainty in creating an LOC and then creating 6 a bound around that and then testing your data 7 against that. 8 MR. THURMAN: That is correct. 9 DR. COUPE: So, I just leave the 10 particulars of the statistics details to my 11 colleagues doing a 95 percent confidence interval 12 slapped over another 95 percent confidence 13 interval. But I don't really think you want to 14 do that, just given the variability of how an LOC 15 is derived and the different safety factors and 16 moving from animals to humans. I think you 17 probably wanted to stick with the LOC number. 18 But I am going to move into a little 19 more broader thing. I am talking about the 20 variability of using a statistical method to 21 determine future sampling scenarios. I know we 22 had to do that. But it assumes that the

### 202-234-4433 Neal R. Gross & Co., Inc. Page 128 1 distribution, the constituent of instrument is 2 going to be the same from year to year and we 3 know it is really not true. 4 There are many things that change from 5 year to year that might change, that change the 6 distribution of atrazine in the surface water of 7 our basin. So when we talk about year to year 8 variation in rainfall as well as long-term 9 climate change, the changes in crop types, for 10 example, you get a new cold weather variety that 11 can be planted earlier or later. 12 We have a lot money going into the 13 Mississippi River Basin now for BMPs and these 14 have the ability to change how the atrazine is 15 moved into the surface water. And you are going 16 to have changes in the weed population and the 17 weed infestation which have changed your 18 herbicide use. 19 But I just wanted to give you a little 20 brief recap of herbicides in water, just kind of 21 a 101 on the distribution of atrazine in surface 22 water. The distribution of atrazine in surface

### 202-234-4433 Neal R. Gross & Co., Inc. Page 129 1 water can really be explained in two terms, a 2 source strength and a hydrology. A source 3 strength being the fact that for atrazine to be 4 detected in the surface water of a basin, it has 5 to be used in that basin. We have mentioned work 6 before but if you look in WARP, the single 7 largest parameter that explains variability and 8 explains more variability than all the rest of 9 the parameters combined was use. So, was 10 atrazine used in the basin? If it was, then some 11 small proportion of the applied amount ended up 12 in surface water. 13 And the other important factor in the 14 transport of atrazine is water. There must be 15 water to move atrazine into the stream of the 16 basin. For the most part, atrazine is also 17 transported atmospherically but the 18 concentrations here are moved off the landscape 19 by water. 20 So the EPA has stated how hard it is 21 to relate concentrations to the streams of flow 22 and I agree that it is because the concentration

### 202-234-4433 Neal R. Gross & Co., Inc. Page 130 1 is made extremely high with a very small runoff 2 event soon after application and there may be a 3 very small concentration, a large runoff event a 4 few weeks later. But I submit that hydrology can 5 explain the presence or absence of atrazine in

6 streams. 7 Additionally in larger streams, the 8 variability of concentration may be due to the 9 timing of the arrival of water at the intakes 10 from various parts of the basin. Some may be 11 having more rainfall than others. Or maybe 12 planning was further along in one area of the 13 basin than it was in another one. 14 There is an awful lot of information 15 and expertise on the transport of agricultural 16 chemicals and I am convinced, as opposed to 17 determining if, atrazine poses a health risk. It 18 is not rocket science. A program can be designed 19 that will do what is needed to do if we know what 20 is needed. What you need to know and have to 21 know to design a program is what is being 22 discussed here as what is the endpoint. At what

### 202-234-4433 Neal R. Gross & Co., Inc. Page 131 1 level does the atrazine concentration in water 2 matter to humans or the environment? It makes a 3 big difference if it is 25 ppb or 0.25 ppb. 4 That being said, here is a few more 5 random comments. I don't think a one size fits 6 all approach is necessary. Crawford showed in 7 his paper that the larger the basins, the less 8 data you need to reach precision goals. 9 Conversely, of course, the smaller the basin, the 10 flashier it is and the more samples are needed to 11 ensure precision. Given that there is 12 significant history at these sites and many have 13 shown only small levels of atrazine, I believe 14 the sampling strategy could be tailored for 15 individual community water systems, probably less 16 samples on the larger systems and maybe more on

17 the smaller ones. 18 And earlier, there was a discussion 19 about daily sampling. I just want to iterate 20 that as my colleague Linda put it. If you need 21 fine resolution, and she said it several times 22 already, then you have to sample at a fine

### 202-234-4433 Neal R. Gross & Co., Inc. Page 132 1 resolution. If you want a four-day average, I 2 thought it was a very good point, a four-day 3 average, you have to sample twice. Yes, you 4 can't really create, interpolate or model data if 5 that is what you need. I whole heartedly agree 6 with that and that goes for even sub-daily 7 sampling, which we haven't even mentioned about 8 because some of these basins may have variability 9 that relies on the sub-daily. 10 So and also just one last point as we 11 mentioned before. I would like to point out that 12 although there is a lot of very good work on the 13 toxicity of atrazine, from my own experience and 14 as the woman from NRDC stated, you never find 15 atrazine alone in a water sample. There is 16 usually a plethora of other constituents, some 17 herbicides, other kinds of materials that are in 18 there. You just never find atrazine alone. 19 So to study the toxicity of atrazine 20 alone kind of short-sheets safety. I think it is 21 a serious concern. Thank you. 22 SESSION CHAIR PORTIER: Dr. Gilliom?

### 202-234-4433 Neal R. Gross & Co., Inc. Page 133 1 DR. GILLIOM: I guess on the response 2 to that specific question, you know, my tendency 3 is to not try to put additional, this is an 4 agreement with Dr. Coupe, try to put confidence 5 bounds on the LOC. It seems by its nature it is 6 a process of putting in safety factors and coming 7 up with a conservative threshold. So at least 8 once that is all done, you do have a fixed value 9 to compare something to. I don't think we should 10 start trying to do even more with that. 11 I do think it is really important that 12 we have agreed upon and predictable ways that 13 confidence bounds are going to be put on the 14 exposure estimates. And part of the reason I say 15 that is that I think in the end we are going to 16 have a whole continuum of approaches being used 17 to estimate exposure. So you could envision 18 potentially a high probability group of sites 19 that you have very dense actual measurements on 20 and very tight estimates of confidence on one 21 hand. And those are going to have a different 22 probability of exceedance issue than if we are

### 202-234-4433 Neal R. Gross & Co., Inc. Page 134 1 using an indirect method from a model, which is 2 also going to be an important part of the 3 continuum. 4 So I would kind of view it in terms of 5 we would like to see, I would like to see the 6 objectives stated in terms of acceptable 7 probability of exceeding a given threshold. That 8 way, we can look at any method on a common 9 playing field. So in other words, if the EPA 10 gives us guidance and says okay, the moving 11 average value is seven, seven-day value of 20, 12 and it is okay with us that there is a 50 percent 13 chance that that is exceeded, then we can look at 14 any estimation method on a common basis and 15 evaluate the probability on those terms. And 16 that is not easy to do but in the end, that is 17 what it kind of comes down to, even if you have a 18 very shallow basis for estimating the numbers.

19 SESSION CHAIR PORTIER: Dr. Lee? 20 DR. LEE: Yes, I concur with my 21 colleagues here. And I just want to say that 22 statistically the problem of placing confidence

### 202-234-4433 Neal R. Gross & Co., Inc. Page 135 1 bounds on a level of concern is a harder problem 2 than just putting confidence bounds on a rolling 3 average. And there is going to be enough 4 complication perhaps in other things that we want 5 to do with this, that this may not be the place 6 to add additional complication. 7 SESSION CHAIR PORTIER: Dr. Young? 8 DR. YOUNG: I have nothing to add. 9 SESSION CHAIR PORTIER: That just 10 increased my probability of getting through this 11 morning. Anyone else? 12 Yes, I tended to concur also. I mean 13 I thought about this and I thought to myself 14 exactly as you say, it is probably a lot harder 15 to put a confidence interval in a limit of 16 concern and it leads to more public confusion. 17 The exposure estimate, everybody assumes exposure 18 is going to be variable so a probability 19 statement on exposure is probably much more 20 acceptable than one on a public health limit of 21 concern. So I think you have got a pretty clear 22 answer to this question. It kind of gives you

### 202-234-4433 Neal R. Gross & Co., Inc. Page 136 1 the direction. 2 MR. THURMAN: Yes, we appreciate that. 3 Okay, so question 2.4. We just scared Don off.

4 SESSION CHAIR PORTIER: He had warned 5 us that he had to leave for another meeting. 6 MR. THURMAN: I am just picking on 7 him. I will pay for that later.

8 SESSION CHAIR PORTIER: We won't see 9 him again. Right? 10 MR. THURMAN: Well he has got six 11 months to forget about that.12 Okay, this is, it looks like a two13 part question. I will read them both and you can 14 -- three part. Oh, gosh. Okay. I apologize in

15 advance for that. 16 Please comment on the relative merits 17 of the various modeling approaches the Agency 18 described in Sections 5.4.1 and 5.6 for 19 interpolating pesticide concentration between 20 sampling points and, in particular, on the 21 strengths and weaknesses of these methods as the 22 frequency of samples decreases.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 137 1 Considering the health endpoints being 2 considered for atrazine, particularly data for 3 the HPA axis, and the exposure time frame needed 4 to induce the health effects, which is shorter 5 than that used in the 2003 risk assessment, 6 please comment on the advantages and 7 disadvantages of each model for evaluating the 8 likely occurrence and exposure via drinking water 9 of short, moderate, and long durations. 10 Please comment on the Agency's 11 proposed approach for evaluating these methods, 12 as described in Section 5.7.1. To what extent 13 should the Agency consider other factors, such as 14 the shape of the chemograph(Section 5.5.3), 15 weather patterns, stream flow, and/or pesticide 16 use patterns in evaluating the modeling 17 approaches?

18 SESSION CHAIR PORTIER: Dr. Lee? 19 DR. LEE: You gave me the long one. 20 All right. Let's charge in. 21 Section 5.4.1 describes two basic 22 methods for filling in values between the actual

### 202-234-4433 Neal R. Gross & Co., Inc. Page 138 1 measurements one-year interpolation, stair-step 2 imputation. Neither of these methods can ever 3 give you a predicted value that is larger than 4 any of the observed values. So this clearly will 5 lead to underestimation of the maximum value, if 6 the maximum value does not occur on a sampling 7 day. And this carries over then into shorter 8 term averages or any average as well. The 9 shorter the average, the more important this peak 10 is. 11 The stair-step method has, I think, 12 further danger of missing the truth here. In 13 terms of following the curves, you are trying to 14 get an average, the stair-step method will tend 15 to overestimate a decrease in curve when it is 16 concave -- will tend to overestimate a decrease 17 in curve. Linear interpolation also will tend to 18 overestimate if the decrease is concave but by 19 not as much as the stair-step method. 20 From the examples of chemograms that 21 were given in Figure 7, I get the impression that 22 most curves generally will be concave from more

### 202-234-4433 Neal R. Gross & Co., Inc. Page 139 1 of the year then convex because there is an 2 initial peak following the application of the 3 pesticide, followed by proportional decrease from 4 the peak. And maybe my hydrologist colleagues 5 can correct me on that but that is the impression 6 I get of these shapes. 7 So among these two methods, the linear 8 interpolation does seem like it is probably going 9 to do a little bit better. But for the most 10 part, it probably doesn't matter. We are missing 11 the maximum significantly. There is the 12 potential for missing the maximum significantly

13 here. 14 For longer term averages, like a 90 15 day average or 26 week average, both the linear 16 interpolation stair-step methods seem to work 17 reasonably well because the underestimation of 18 the peak values can be balanced by overestimation 19 of post-peak values. It is not exactly a ringing 20 endorsement but central limit theorems kicking in

21 for us there. 22 But to accurately estimate a maximum

### 202-234-4433 Neal R. Gross & Co., Inc. Page 140 1 value when it is out of sample, it is going to 2 require use of a method that can predict a larger 3 value than those that are observed in the data. 4 And example of such method is an artificial 5 neural network as described in 5.6 and Appendix

6 C. 7 Let me just briefly mention again what 8 I brought up on, I guess it was Monday. Appendix 9 C does describe the importance of not using too 10 many modes because over-fitting is not good for 11 prediction. Absolutely correct. But if you are 12 using too few nodes, then you will also 13 potentially be not fitting the curve very well. 14 The shape of the peak may not be correctly 15 categorized and you may be missing the maximum 16 value as was shown in the difference between the 17 three-node fits and the four-node fits in the 18 White Paper. 19 So the importance of finding the right 20 number of nodes is critical for getting good 21 estimates and some sort of basic model selection 22 like a BIC measure would be helpful. That may

### 202-234-4433 Neal R. Gross & Co., Inc. Page 141 1 also be able to eliminate the need for fitting 2 autoregressive errors. I think the current 3 approach that involves the neural network with 4 autoregressive errors is just going to be too 5 complicated for a non-expert to implement and 6 thus, it is not necessarily a practical approach 7 but perhaps if we can eliminate the need for 8 autoregressive errors, it may become a more 9 useful approach in this context. 10 Section 5.4.1 also mentions a number 11 of other potential approaches: bootstrapping, 12 kriging, random function models, regression-based 13 models and deterministic models. Bootstrapping 14 methods again are never going to be able to 15 predict a value that is larger than you actually 16 observed. So, that leads to definite worries. 17 The other four methods do have promise alone or 18 particularly in combination. 19 Kriging, which is the basic case of 20 fitting a Gaussian process model interpolates the 21 data with a smooth curve but does allow the curve 22 to move outside the bounds of the data. And so

### 202-234-4433 Neal R. Gross & Co., Inc. Page 142 1 it could be used for estimating a maximum that 2 occurs outside of the sample base. 3 Also like a Gaussian process, like a 4 neural network can be used to smooth noisy data, 5 rather than doing strict interpolation. That is 6 an issue that I don't think has been discussed 7 here. The Agency uses interpolation a lot in the 8 White Paper but there is a difference between 9 strict interpolation which necessarily will go 10 through all the observed points and some sort of 11 curve fitting, which may discount exact values 12 because of say measurement error. And so the 13 curve will get close to the points but it will do 14 some smoothing. The neural network approach is 15 an example of smoothing approach. It is not 16 guaranteed to go through all the data points and 17 we wouldn't necessarily want it to go through all 18 the data points. But the interpolation methods, 19 the linear interpolation stair-step are, by 20 definition, interpolation. They are guaranteed 21 to go through the data points. Kriging, in its 22 basic form is an interpolation method. It will

### 202-234-4433 Neal R. Gross & Co., Inc. Page 143 1 go through all the data points but 2 generalizations to Gaussian processes allow more 3 flexibility if that is not necessarily the case. 4 Let's see. I did actually get some 5 examples of the community water system data from 6 Marry Frankenberry and was able to fit some basic 7 kriging models to them and found that well, it 8 doesn't actually do a whole lot better than 9 linear interpolation in most cases. In most 10 cases, I was not able to get a fit that gave me 11 maximum values outside the sampling days that 12 were higher than the observed ones. 13 And my guess just from really basic, 14 you know, I didn't have a whole lot of time to do 15 the analysis in the last two days, my guess is 16 that the shape of the peaks are very sharp. And 17 as such, the correlation structure is somewhat 18 different around the maximum than it is in the 19 rest of the space. And so fitting a standard 20 stationary model as kriging would do, is not 21 adequately characterizing the curve. A more full 22 analysis would involve a non-stationary

### 202-234-4433 Neal R. Gross & Co., Inc. Page 144 1 correlation model and these do exist. But again, 2 I think this is going to be far more complicated 3 than you would want to implement on an individual 4 community water system out in the field. 5 One last issue around kriging is that 6 you do need to estimate a correlation structure. 7 These are difficult to estimate. Empirical 8 chemograms are highly variable and so I would 9 recommend the estimation be done more globally, 10 pooling across years and across water systems. 11 Okay, that is kriging. 12 Random function models are another 13 approach we can use. Essentially there we are 14 picking a shape for the curve. And we do know a 15 fair amount about what these curves may look 16 like, although they differ from system to system. 17 Using those shapes can really aid in the 18 determination of a maximum value and can help 19 them say in determining if the maximum value may 20 have occurred on a sampling day or a non-sampling 21 day. And if it is a non-sampling day, be able to 22 estimate how much higher is that peak.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 145 1 And there are a number of ways to do 2 this. There is an example in the context of 3 pesticide concentrations given by Vecchia et al. 4 in a 2008 paper, essentially Dr. Gilliom is on 5 that one, essentially using the WARP model to 6 look at predicting -- it is combining the work 7 model with seasonal shaped functions to be able 8 to make predictions about where that peak might

9 be. 10 So that ties into regression-based 11 models. And there has been a number of work by 12 Dr. Gilliom and others at looking at regressions 13 to predict maxima and quantiles and there is a 14 lot of potential there. They do, however, are 15 looking at sort of the yearly total. So just 16 looking at the maxima over the whole year, it is 17 not going to give you a time series on its own 18 there. And the accuracy may not be quite at the 19 level that one would want for an individual water 20 system but I think there is a lot of potential 21 there. In particular, there is a lot of 22 potential for combining these regression-based

### 202-234-4433 Neal R. Gross & Co., Inc. Page 146 1 models with other sorts of models to get improved 2 information and help us make out-of-sample 3 predictions. 4 The final method is used, the final 5 method mentioned in the White Paper is 6 deterministic models. These are built from a 7 combination knowledge of the physical and 8 chemical laws of the process, looking at the 9 actual physical process. And those can be really 10 useful for predicting maxima and short-term 11 averages when we don't observe the data directly. 12 But an important issue there is 13 calibration, which involves the setting of inputs 14 and possible tuning parameters so that the 15 predictions do closely match observed values. 16 And there is the concern that this may need to be 17 done for each watershed individually and then 18 that becomes a complicated problem again. 19 I guess one global theme here is you 20 don't get something for nothing. If you want to 21 be able to make predictions in-between the 22 observed days that are more accurate, it takes

### 202-234-4433 Neal R. Gross & Co., Inc. Page 147 1 more work. 2 I do want to mention one other 3 category of models that has not been mentioned in 4 the White Paper and that is using extreme value 5 theory. There is a fair amount of theory in the 6 statistics literature about modeling extreme 7 events and their distributions developed around 8 those. And I think Dr. Young has mentioned some 9 of these earlier. But there are some, and there 10 is some very recent work. There is a paper that 11 just came out in the Journal of the American 12 Statistical Association that looks at methods for 13 modeling extreme values of a correlated process. 14 Most of the literature involves independent 15 samples but some of the more recent work does 16 look at correlated processes such as chemograph. 17 And so that could be really useful to be looking 18 at. It is a very new literature and I am not 19 that familiar with it but I think the EPA should 20 at least investigate that literature. 21 MR. THURMAN: If you could put that in 22 your report --

### 202-234-4433 Neal R. Gross & Co., Inc. Page 148 1 DR. LEE: I will put all the

2 references -- 3 MR. THURMAN: -- that would be great. 4 DR. LEE: -- in the minutes. 5 Absolutely. 6 Okay, so I think that gets through 7 parts one and two of this question. Part three 8 then is about the procedure for evaluating the 9 effectiveness of the different methods given in 10 Section 5.7.1. And the general approach I think 11 is sound but as mentioned before, it is important 12 to make sure that we are using a truth that is 13 realistic and so has enough level of detail and 14 variability that reflects what we will actually

15 see. 16 And then the important point is the 17 last part of the question asks about other 18 factors. And I think those really, really should 19 be looked at, taking into account possible 20 covariates, like weather patterns, stream flow, 21 pesticide use patterns, would really help in 22 being able to make better estimation or also the

### 202-234-4433 Neal R. Gross & Co., Inc. Page 149 1 shape of the chemograph. 2 So combining these sorts of other 3 pieces of information would really help. Trying 4 to estimate the maximum, just looking at the data 5 non-parametrically, we can do that but it is not 6 as powerful as bringing in other information that 7 we do have available. 8 And again, Dr. Gilliom has been 9 involved in some work that relates those pieces 10 of information and I think that would be a 11 critical direction for the agency to further 12 investigate. 13 SESSION CHAIR PORTIER: Thank you. 14 Dr. Coupe? 15 DR. COUPE: I think anything I wanted 16 to say I have already said. And that was pretty 17 comprehensive. So that is it for now. 18 SESSION CHAIR PORTIER: Dr. Gilliom? 19 DR. GILLIOM: Just I guess one thing 20 to make clear is between Dr. Lee and myself, we 21 will make sure all the references are in there 22 for the various articles. They will be included

### 202-234-4433 Neal R. Gross & Co., Inc. Page 150 1 in the write-ups. 2 One, I guess point I want to make is 3 that if the, and it is probably just a repeated 4 implication of the discussion here but if the 5 duration is on the very short end, it is going to 6 be evident pretty quick, I think that we don't 7 have enough range of conditions covered of 8 existing examples of intensively monitored sites. 9 So we have a few sites from Heidelberg College. 10 We have got a couple of drinking water sites. It 11 is growing but we don't really have the full 12 geographic range of conditions represented. So 13 there will be some important decisions to make

14 there about what that means about how far we use 15 inference from existing data. But there is no 16 point in addressing that or even trying, I think, 17 until we know the concentration objective from 18 the toxicology side from the Agency. 19 And I think that is enough to add for 20 now. Thank you. 21 SESSION CHAIR PORTIER: Dr. Young? 22 DR. YOUNG: I also thought Dr. Lee did

### 202-234-4433 Neal R. Gross & Co., Inc. Page 151 1 a nice job in summarizing. One of the things 2 that kind of pull some ideas that have already 3 been stated that maybe pulling them together is 4 that it seems to me it makes really good sense to 5 use the WARP or some other model to identify the 6 most vulnerable community water systems. 7 And then once you found those, then it 8 is probably worth some time and effort to figure 9 out exactly what should be done for those 10 systems. And the methods that have been 11 proposed, interpolation methods, might work fine 12 as long as a 90-day rolling average is fine. But 13 if we begin shortening them up, they are not 14 going to be sufficient. 15 So some way to get a more realistic 16 chemograph is important and that would seem to 17 call for maybe the simplest I can think of is a 18 regression-type model where you put in some 19 kriging and then once you have that, you can use 20 geostatistical simulation to get an idea of the 21 true variability associated with that and maybe 22 begin putting some bounds. And then you have a

### 202-234-4433 Neal R. Gross & Co., Inc. Page 152 1 fairly good idea of what might happen within that 2 system. 3 Now that would take more time but if 4 we narrow the scope of the systems, then perhaps 5 you have more time for individual efforts. And 6 then once you get -- the first one always takes 7 the longest. So that is something to think

8 about. 9 SESSION CHAIR PORTIER: Any additional 10 comments from the panel? 11 One of the things I thought about, we 12 haven't really talked too much about the rolling 13 average methodology. But you are using a fairly 14 simple approach of just taking a couple of points 15 and doing the regular average. And there is a 16 slight improvement you can do on that, which 17 would be more of a weighted average. I was 18 thinking Linda, isn't it more like a lasso-type 19 approach that still gives you a good average? 20 But you notice on the graphs that Mr. Thurman 21 showed that with the rolling averages, their 22 average profile is always going to be shifted to

### 202-234-4433 Neal R. Gross & Co., Inc. Page 153 1 the right of the real profile and that is a 2 function of just doing a simple average, rather 3 than having a slightly wider window with some 4 weights, some decreasing weights on either side. 5 So there is kind of a weighted 6 smoothing that will give you kind of a similar 7 rolling average but one that kind of matches up 8 in terms of its peaks and its valleys with more 9 of the original profile. 10 The other thing I was thinking of, a 11 comment Dr. Gilliom mentioned about, more 12 intensive sampling from more sites, is that it 13 would be nice to have some "normal sites." The 14 interquartile range sites. You know, to sort of 15 ensure the public that we haven't just looked at 16 worst-case scenarios. We have also looked at 17 some good players, some solid citizens in the 18 middle. CWS's that don't have all these major 19 problems that are overall managed, that our 20 methodology works well in those kind of solid 21 citizen sites as well. You always aren't always 22 in the extreme because you get charged with being

### 202-234-4433 Neal R. Gross & Co., Inc. Page 154 1 too extreme at that point. Right? And not 2 really giving us a good picture. 3 And as far as the White Paper, you 4 know, when you looked at the neuro network and

5 showed us how well the smooth to the neuro 6 network worked and then you added in the 7 autoregressive two component, you didn't show 8 really how well that improved that process. And 9 the point that Dr. Lee was making on some other 10 models is that kind of adding is nice 11 statistically and it may improve the R-square 12 three percent but when you looked at the picture 13 of the smooth, it probably isn't something that 14 is really noticeable. And so if you are looking 15 to simplify, statistically that is nice but in 16 terms of complexity, it really adds a lot of 17 complexity to the estimating process to be able18 to do that. That may not pay off in the long19 run. 20 I think that is the end of my 21 comments. Dr. Heeringa. 22 CHAIR HEERINGA: Just one minor

### 202-234-4433 Neal R. Gross & Co., Inc. Page 155 1 statistical observation, too, which I think 2 people probably recognize but we didn't mention 3 and that is in the sampling process itself, 4 regardless of the periodicity with which you draw 5 single samples, the sort of every nth day 6 sampling, systematic sampling would be most 7 efficient if you had sort of long-term monotonic 8 trends, increases or decreases. But if you have 9 arbitrary fluctuations on shorter terms, that 10 systematic sampling may actually give you greater 11 variance then something that is more randomly 12 perturbed within the fixed windows. 13 And I think that between what RTI did 14 and Syngenta and what Dr. Sielken did and what 15 you have done in your simulations, you might 16 actually be able to see that one some 17 chemographs. I don't know if it has been 18 structured that way but you could actually test

19 that. 20 But it is just a small point but I 21 think systematic sampling is great if you are on 22 a monotonic trend but could in any given sample

### 202-234-4433 Neal R. Gross & Co., Inc. Page 156 1 lead to greater variance or error than a randomly 2 perturbed sort of fixed window sample. It is 3 just a minor issue but is probably something 4 technically not to lose track of in the process. 5 SESSION CHAIR PORTIER: Yes, Dr. 6 Gilliom? 7 DR. GILLIOM: Just a tangent that 8 reminded me of, that it is maybe important to how 9 we translate ultimately the monitoring 10 requirements from the toxicological requirements 11 is just to remember that all of the data we are 12 looking at so far and what is normally done are 13 instantaneous grab samples for the most part. 14 There is a few data sets that have auto samplers 15 that are doing composites either flow or time

16 waved and so forth. 17 But if it is an important thing to18 capture for instance to know that we have a time19 weighted daily value or a time-weighted two-day 20 or three-day value, that is important information 21 to have in the LOC. Because too often, that type 22 of information is left out and then the

### 202-234-4433 Neal R. Gross & Co., Inc. Page 157 1 monitoring design goes ahead with variants based 2 on instantaneous samples and all that and it may 3 not capture what you really want it to for the 4 biological effects. So I think we can deal with 5 all that, the Agency can deal with all that but 6 we need to know the specific objective from the 7 biological point of view. 8 SESSION CHAIR PORTIER: I am sitting 9 here thinking we need a synthetic drinker that 10 drinks two liters of water out of it in a day and 11 then composites that and gets an average 12 concentration. That's okay. 13 Any additional comments? 14 So that, I think is the last question. 15 MR. THURMAN: Mercifully so.

16 SESSION CHAIR PORTIER: And before I 17 close, we usually do two things, and one is I am 18 going to open it up to the panel for any final 19 comments from any panel member. If there is some 20 topic you felt that hasn't been brought up that 21 you wish to comment on, we can add this in at 22 this point. I think we pretty intensively

### 202-234-4433 Neal R. Gross & Co., Inc. Page 158 1 covered a lot of these topics but we will open it 2 up to anyone. 3 Last chance to say anything before I 4 turn it over to EPA for their closing remarks. I 5 don't see anybody dying to present a new issue. 6 Dr. Lowit, I know she has a few closing comments. 7 DR. LOWIT: Before I speak on behalf 8 of the team to give you our appreciation and our 9 sort of next, what we will be doing now, I will 10 speak on behalf of myself. 11 A little story. A number of years 12 ago, probably eight maybe nine at this point, I 13 had only been with the Agency a year or so, two 14 years at the most and it was the night before the 15 first big meeting I ever gave a big presentation. 16 A group of us were meeting with the office 17 director at the time. It was several office 18 directors ago. This person was going around the 19 table giving a little pep talk and it came to my 20 turn for a little pep talk. And the comment that 21 I was given was you will do great. Just don't be 22 flip. And I will forever hold that.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 159 1 And yesterday I think I said a couple 2 of things that were flip, unfortunately. And I 3 always think of that day because it absolutely 4 nailed my shortcomings. But I did, I think, make 5 a comment that could have, around the science 6 issues that was probably interpreted by all 20 of 7 you 20 different ways and I just want to take a 8 second and clarify something that I said. 9 At some point yesterday as we were 10 talking about the new review. I don't remember 11 if it was in the point of departure or in sort of 12 the 101 thing that Nelson and I did, I made a 13 statement to the effect that in this analysis we 14 were starting from scratch or with a new slate or 15 something to that effect. Let me just clarify 16 what I intended because there was some context

17 there. 18 Back in the fall our AA, assistant 19 administrator, announced that the Agency, the 20 Pesticides Office, would be doing this special 21 reevaluation of atrazine. As part of that, we 22 would do two major things. The first one is

### 202-234-4433 Neal R. Gross & Co., Inc. Page 160 1 focusing heavily on 2003 forward, which is the 2 hundred and plus study that you have all been 3 through and the reconsideration of the drinking 4 water monitoring. The other thing that we 5 committed to do was to ensure that the old risk

6 assessment was safe. 7 There are a lot of ways to interpret 8 that. You can interpret that that you go through 9 every single millions and millions of pages that 10 have been submitted to the Agency and that have 11 been performed by researchers all over the world 12 or other extreme is that you take the overviews 13 and you just pick them up and you go. And I 14 would think that some of you probably had that 15 interpretation or somewhere in-between depending 16 on your personal perspective. 17 I just wanted to make sure that this 18 is what we are doing and it is relevant because 19 of some comments that Penny had commented on 20 yesterday and we wanted to make sure that you 21 understood what we were doing. We have a small 22 army in pesticides terms. They are putting a lot

### 202-234-4433 Neal R. Gross & Co., Inc. Page 161 1 of resources to this and I have the honor of 2 keeping the train on the tracks. Our small army 3 has a very large task in a very short time frame. 4 And so what we are doing is doing what the AA 5 asked of us. We are going to go through the old 6 data in what we consider to be sufficient to 7 ensure that the points of departure and the 8 uncertainty factors in the new risk assessment 9 are safe for human health for every life stage we 10 can find across different durations. 11 That does not mean that we are going 12 to go through millions and millions and millions 13 of pages. What it does mean, however, is that 14 when we select our points of departure, when we 15 come back in September, that we will have been 16 through enough of those pages and pages that we 17 feel confident that we sit here to say that our 18 new proposal is safe. And our new proposal 19 covers all sensitive groups. 20 What that means in practice we have 21 four months to figure out but I can tell you we 22 will start with what we call the data evaluation

### 202-234-4433 Neal R. Gross & Co., Inc. Page 162 1 reviews. Yes, data evaluation records, what we 2 call DERs which are essentially summaries of the 3 studies that come from the guidelines. And the 4 guideline studies are submitted, literally come 5 in volumes. A chronic bioassay can have easily 6 six, seven, eight, volumes. So we are talking 7 mountains of paper. 8 And so what we do is take those 9 mountains of paper and summarize them. And 10 fairly lengthy reviews there can be easily -- 11 some of them are 50 pages. We will start with 12 those DERs and go from there. But we will 13 however, focus a great deal of attention on the 14 new studies that are coming in part because we 15 know ahead of time that the doses are lower, the 16 endpoints are precursor events, and so we are 17 pushing the dose responses to the left on the 18 dose response curve. And so that will be a large 19 part of the focus but we will go back and ensure 20 that they are safe, that we are not going to go 21 through every individual animal and submit it to 22 the Agency.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 163 1 SESSION CHAIR PORTIER: Dr. Crisp? 2 DR. FENNER-CRISP: I wasn't wishing to 3 suggest you had to go back and re-review a study

4 from scratch. 5 DR. LOWIT: No and I didn't think you 6 were. We just wanted it on the record. 7 DR. FENNER-CRISP: The point I was 8 making was we may know now something a little bit 9 more about a particular endpoint of concern, its 10 mode of action, whatever, some nuance and/or have 11 reached a stage where we now reinterpret certain 12 kinds of data. And it was that mini task that I 13 was suggesting had to be pursued in addition to 14 looking at the new information. 15 Can I ask a question since I had the 16 microphone? It reminded me in this last thing 17 about the exposure time frame needed to induce is 18 shorter than in the 2003, that refers to the 19 chronic number, I presume. 20 DR. LOWIT: No, I refer mostly to the

21 shorter term. 22 DR. FENNER-CRISP: Oh, okay. That was

### 202-234-4433 Neal R. Gross & Co., Inc. Page 164 1 what I was going to ask you. Do you have in mind 2 now, looking at the other numbers over all of the 3 course of exposure durations, two of the three 4 categories were driven by data related to our 5 discussion the last few days. The pubertal assay 6 drove the middle number, the LH surge drove the 7 chronic number, but these kinds of data did not 8 drive the acute number. 9 So, could we interpret the possibility 10 that you may be looking at this body of data 11 related to the MOA and its consequences for 12 generating an acute number?

13 DR. LOWIT: I don't know. I am not 14 going to answer that. 15 DR. FENNER-CRISP: Okay. 16 DR. LOWIT: I am sorry, Penny, but I 17 am going to answer a different question. I am 18 being flip again. 19 DR. FENNER-CRISP: I think you said

20 that data set wasn't -- 21 DR. LOWIT: Yes, and that is an 22 important point and I think we did hear a fairly

### 202-234-4433 Neal R. Gross & Co., Inc. Page 165 1 strong consensus that those single 15-minute, 30- 2 minute cort measures would not make a robust 3 regulatory implant. I think that was one message 4 that we got that was pretty clear. 5 But as I have been sitting here and I 6 went home last night digesting what some of you 7 have been talking, particularly Dr. Krishnan and 8 O'Byrne trying to blend those concepts, as I sit 9 here, I think what we really need is a different 10 kind of assessment. I actually think we are 11 asking the wrong questions. 12 And I think this is, if you follow 13 Kannan's line of thinking around the AUC and you 14 blend that with the chemograph idea. And then if 15 we can do some calculations overlaying AUC and 16 chemograph, there may be a better way of asking 17 these questions. Instead of thinking isolated 18 duration, think about it on an AUC basis. It is 19 a much more sophisticated way of thinking about 20 it and would create havoc for the risk managers. 21 But I think it would bring in some of 22 the ideas that we have heard this morning about

### 202-234-4433 Neal R. Gross & Co., Inc. Page 166 1 bringing in the level of concern idea and 2 thinking about different CWSes that seem to fit 3 in different categories of 20 some that have a 4 lot of hits, and a lot of them that don't have 5 any, and some in-between, and if you get these 6 different patterns. I think we have been 7 thinking about it on an AUC basis. We may be 8 able to get more of a better distribution of that 9 way of thinking. 10 And so how that fits into doing an 11 acute risk assessment in a short-term, or in the 12 30 days, or an intermediate term of up to 60 days 13 or six months or whatever it is, I don't know how 14 that fits but I think it is actually answering 15 the question. And I don't know how to do it but 16 we will figure it out. 17 DR. FENNER-CRISP: The other thing you 18 don't have assembled yet and we talked about it 19 today and a little bit at the end of yesterday is 20 the human biology that is relevant to the results 21 that have been gathered in the laboratory animal 22 studies. And when you have that, it will better

### 202-234-4433 Neal R. Gross & Co., Inc. Page 167 1 inform the point you have just made. 2 SESSION CHAIR PORTIER: I think Dr. 3 Horton and Dr. Akana will want to comment 4 shortly. Short comments. 5 DR. HORTON: Okay, very short comment. 6 I want to summarize some things made by other 7 people that I think all come together and one is 8 Dr. Krishnan's comment about the area under the 9 curve plus Dr. Akana's comment that she made 10 earlier today about the fact that one 15-minute 11 exposure to cort may not be a significant event 12 but multiple exposures might be. So that when 13 you start putting all of that together, it might 14 be a significant event so as to put these things 15 together. 16 And Dr. Cooper's comment that perhaps 17 we have been looking under the light post for the 18 keys and I think we were driven by a mode of 19 action based on the mammary gland tumor and the 20 LH surge but in the result of that, a lot of our 21 thinking and a lot of the experiments have led us 22 to some very interesting results and perhaps when

### 202-234-4433 Neal R. Gross & Co., Inc. Page 168 1 I finally get this figure done, we can kind of 2 move away from the lamppost and think about how 3 to use this new information in an informed way.

4 SESSION CHAIR PORTIER: Dr. Akana? 5 DR. AKANA: Here is an idea for you. 6 You take a small community water system. You are 7 measuring atrazine raw and in finished water. 8 And then in the raw sewage, you measure cortisol. 9 SESSION CHAIR PORTIER: She keeps 10 dropping these gems. I don't know what to do 11 with them. 12 DR. AKANA: It might go with the 13 bootstrap method well. 14 (Laughter.) 15 SESSION CHAIR PORTIER: Dr. Lowit, you 16 know, as I listened to all of this, you are 17 keeping things on track. The train idea. And I 18 keep wondering if these are two trains kind of 19 going along together trying to get in the station 20 at the same time or two trains coming at each 21 other and we don't know if they are even on the 22 same track. So they may come together or they

### 202-234-4433 Neal R. Gross & Co., Inc. Page 169 1 may pass in the night. So it will be interesting 2 to see when we get here in September or October. 3 DR. LOWIT: Well the train I am 4 driving is the one that the data is interesting. 5 So I don't want to sit here and speculate and 6 sort of talk free flow because that is what I was 7 starting to do with Penny.

8 SESSION CHAIR PORTIER: Just thank the 9 panel and let's go. 10 (Laughter.) 11 DR. LOWIT: Yes, I think the point is 12 well taken that we have collectively heard an 13 enormous amount of helpful feedback on a very 14 diverse almost absurdly diverse array of topics. 15 And to say that we appreciate what you have been 16 doing and that what you do whether it is a 17 permanent panel or first timers, it is a lot of 18 work to come to these meetings. We know we hand 19 you lots of pages and ask you to digest and turn 20 around feedback on something you may have just 21 learned about two weeks ago. 22 And I am always impressed when I come

### 202-234-4433 Neal R. Gross & Co., Inc. Page 170 1 to these meetings to the degree to which really 2 smart people come together and do really amazing 3 things and this is just another example of that. 4 And I want to thank each and every one of you on

5 behalf of the whole team. 6 We will be back in September with the 7 next generation of what you have seen with most 8 likely some more choices that we haven't talked 9 about here, points of departure, that sort of 10 thing. We will do a more explicit evaluation of 11 life stage sensitivity that we really haven't 12 addressed here. Peripherally we have but we will 13 head it straight on a little bit more. 14 We will also be joined by your 15 epidemiology colleagues, both on the team and 16 some people on the panel will join us. So we 17 expect a good conversation around thinking about 18 how animal and human information do and don't 19 match. And I can tell you often they don't match 20 and that is a great challenge. 21 So I will thank each and every one of 22 you. I will thank Laura, and Joe, and Charlene

### 202-234-4433 Neal R. Gross & Co., Inc. Page 171 1 and everyone else on the SAP staff. Personal 2 thanks to my team. It is an amazing group of 3 people. 4 SESSION CHAIR PORTIER: Thank you. 5 For the panel, once the DFO makes his final 6 comments, I want you to just leave all your 7 papers and your computer. We are going to go 8 next door for a short five minute process meeting 9 where we talk about how we produce the final 10 report. 11 And at this point, I want to turn it 12 over to the DFO, Joe Bailey, for final closing

13 remarks. 14 MR. BAILEY: All I want to say is to 15 thank the panel for all their hard work, for 16 agreeing to come to the meeting and I look 17 forward to working with you over the next few 18 weeks getting the report pulled together. And I 19 thank EPA for their presentations. I think they 20 were very well done. And I want to thank the 21 public commenters who came to the meeting as well 22 to present their views.

### 202-234-4433 Neal R. Gross & Co., Inc. Page 172 1 And that's it. Thank you. 2 Oh, yes, and we will get the report 3 completed within 90 days from today. 4 SESSION CHAIR PORTIER: Thank you. 5 That ends the meeting. 6 (Whereupon, at 12:14 p.m., the 7 foregoing meeting was adjourned.)

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