UNITED STATES OF AMERICA 

ENVIRONMENTAL PROTECTION AGENCY 

EIGHTH CONFERENCE ON AIR QUALITY MODELING 

_________________________________________ 

 

 

 

EPA Auditorium 

109 TW Alexander Drive 

Research Triangle Park, NC 

September 22, 2005 

 

 

 

The above entitled meeting was called to order by Tyler J. Fox 

PRESIDING OFFICER: 

TYLER J. FOX 

Group Leader 

Air Quality Modeling Group (C439-01) 

Office of Air Quality Planning and Standards 

EPA 

Research Triangle Park, NC 27711 
 Vol. 1, p. 2 

 A P P E A R A N C E S 

 _____________________ 

 

 Presiding: Tyler Fox, Leader, Air Quality Modeling 

 Group, EPA 

 

 Warren Peters, Model Clearing House 

 Director, EPA 

 ________________________________________ 

 

 

 
 Vol. 1, p. 3 

 T A B L E O F C O N T E N T S 

 _________________________________ 

 

 

 Topic Presenter Page No. 

 _____ _________ ________ 

 

 Introduction and Tyler Fox 6 

 Opening Remarks John Bachmann 

 

 AERMOD Warren Peters 33 

 

 AERMET Desmond Bailey 51 

 

 AERMAP Peter Eckhoff 60 

 

 AERSCREEN Jim Haywood by Warren Peters 68 

 

 AERSURFACE Karen Wesson 83 

 

 AERMOD Al Cimorelli 100 

 Implementation 

 

 Questions Audience 127 

 

 Lunch Recess 147 

 

 CALPUFF Mark Evangelista 148 

 

 CALPUFF Bret Anderson 187 

 

 CALPUFF Mark Evangelista 196 

 

 Questions Audience 200 

 

 Gridded Met Data Dennis Atkinson 220 

 

 AERMOD/MM5 Mark Evangelista 256 

 

 
 Vol. 1, p. 4 

 T A B L E O F C O N T E N T S 

 _________________________________ 

 

 (Continued.) 

 ____________ 

 

 Topic Presenter Page No. 

 _____ _________ ________ 

 

 Panel Discussion: 295 

 

 National Park John Vimont 295 

 Service 

 

 Alpine Geophysics Dennis McNally 300 

 

 Trinity Consultants Richard Schulze 303 

 

 US EPA Region 7 Bret Anderson 317 

 

 Questions Audience 324 

 

 Keyword Index 346 

 ________________________________________ 

 

 

 
 Vol. 1, p. 5 

 The following EIGHTH CONFERENCEE ON AIR 

 QUALITY MODELING, was held at the United States Environmental 

 Protection Agency, Building C, Auditorium C-111, Research 

 Triangle Park, North Carolina, and was reported by Manie P. 

 Currin, Court Reporter and Notary Public in and for the State 

 of North Carolina, on Thursday, September 22, 2005, 

 commencing at 8:00 a.m. 

 The following proceedings were had, to wit: 

 ________________________________________ 

 

 

 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 6 

 2 TYLER FOX: Good morning, everybody. Why don't we go ahead 

 

 3 and get started here. 

 4 I want to get -- welcome you, obviously, to 

 5 our office -- our offices. 

 6 (Participants are seated.) 

 7 Let's get started here. I hope everybody had 

 8 a safe and nice trip to RTP. We welcome you to our 

 9 Eighth Modeling Conference. 

10 We are very excited about the discussions 

11 we're going to have over the next two days, looking 

12 forward to a lot of interaction, a lot of ideas 

13 about what -- where we're going, how we're doing 

14 business and get your thoughts on that. 

15 To start off the morning, we wanted to get 

16 some opening remarks. 

17 We have John Bachmann who is the OAQPS 

18 Associate Director for Science/Policy, and New 

19 Program Initiatives. 

20 John is the key and instrumental liaison with 

21 our office of research and development, and other 

22 scientific bodies and communities throughout all 

23 the -- all the technical areas that we are involved 

24 with: health sciences, air quality modeling, 

25 emissions development, economics and things of the 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 7 

 2 like. 

 3 So John is here to give us a couple of opening 

 4 remarks, and then we'll -- we'll start the 

 5 morning. 

 6 JOHN BACHMANN: Okay. You're going to have to change that, 

 7 because I can't just wander around so everyone can 

 8 hear me. 

 9 I wanted to welcome you, obviously, to our 

10 office -- our offices. We're in the middle 

11 reorganization, and our name may change soon, so 

12 it's kind of funny to be floating. 

13 But I am here to thank you for coming and to 

14 welcome you, and to also thank you for what you do 

15 and what you contribute. 

16 But I also wanted to stretch you a little bit 

17 by talking about what we see and hear are the 

18 challenges we're facing today, and are likely going 

19 to face in the next five or ten years. And since 

20 you might not trust me to tell you what those 

21 challenges are, I'm going to rely on the National 

22 Research Council and National Academy of Sciences' 

23 summary of those challenges and then say a little 

24 bit about each of them. 

25 You're going to focus on certain areas of 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 8 

 2 modeling today that are crucial to us, and one of 

 3 the things I want to say, despite all our policy 

 4 attention of late on regional scale transport 

 5 models, it's as vital to us as we review the 

 6 standards for particulate matter as we look at air 

 7 toxics, to worry about -- about local scale 

 8 sources, and in particular, as we implement 

 9 standards and try to do things about risk 

10 management to get it right -- to get it as right as 

11 we possibly can, and I understand research is 

12 better. 

13 And lastly, we're increasingly interested in 

14 personal scale exposure, that's very, very 

15 localized scales along roadways and as the outdoors 

16 penetrates indoors. 

17 So we just want to talk a little bit about 

18 those topics, and I don't know if any of you were 

19 at EPA's NOAA conferences, but some of this is from 

20 that. 

21 This committee was established to review 

22 science and policy committee to review the process 

23 we have for air quality management in the United 

24 States, and whether it's good, whether it's 

25 working, or whether it's got problems that need to 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 9 

 2 be fixed. 

 3 And it basically said it is good. It is 

 4 working, but it also has problems, and it could be 

 5 made better and it needs to be made better, because 

 6 some of earlier problems were comparatively easy to 

 7 the problems we are facing now. 

 8 So they're the -- the issues where that -- 

 9 that we don't have as good a way to measure 

10 progress quantitatively, and therefore to confirm 

11 the goals are being met. 

12 We use models a lot to forecast what things 

13 are going to be like, but we rarely go back and use 

14 them to see, gee, did what we say happen, and if it 

15 happened, did it get better or not for the reasons 

16 we thought. I mean, it's accountability; it's 

17 checking to see did things work and understanding 

18 why they did or why they didn't, and what we need 

19 to do to make it better. 

20 I think the air program does this better than 

21 anyone, but we still don't do it well enough, and 

22 certainly the Academy was strong on that point. 

23 So accountability is a key issue. 

24 They also felt that our stovepiping of single 

25 pollutant approaches, and you know that we do that; 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 10 

 2 we -- we're allowed to make our US and more 

 3 model and measure CO and we'll do SO2 

 4 and we'll do PM and ozone. 

 5 This is all separate, and air toxics is 

 6 totally different. And then that needs to stop, 

 7 that we can't afford to be stovepipes that way in 

 8 the future, and that we need to move and organize 

 9 ourselves better to do multi-pollutant things. 

10 And you see, at least on the regional scale, 

11 the focus is increasingly on multi-pollutant 

12 models, and multi-media models that go all the 

13 way from emissions to how they fall out on land 

14 and then work their way into water bodies and 

15 coupled with other kinds of models that are -- that 

16 are modeling how things move through soils and 

17 waters. 

18 The -- we'd also like to focus on ecological 

19 effects, well, we don't even look at that stuff 

20 very often, you know, and if we have tools that 

21 look at it, then maybe we'll think about it more. 

22 And last, I'm not certain that we're doing the 

23 best job we can to maximize the net benefits or to 

24 focus on the greatest risks. 

25 So those are the kind of things that we think 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 11 

 2 we have to face. Just to -- just to refresh 

 3 everyone's memory, this is the air quality 

 4 management system in a theoretical way, and we 

 5 start with establishing goals like standards or 

 6 toxics rules, or acid rain programs, or whatever, 

 7 the goals that you're supposed to meet. 

 8 Traditionally, National Ambient Air Quality 

 9 Standards (NAAQS) is what you think about and we, the core 

10 issue first is to figure out what should you do 

11 about it, and there's sometimes an infinite number 

12 of different things that you can do to meet the 

13 standards, and you have to pick some, and you have 

14 to identify which pollutants are most effective to 

15 control. 

16 But after -- after folks that care about 

17 science and engineering decide what options there 

18 might be, other folks have to look at it and figure 

19 out what would make sense in terms of policy, what 

20 is rational, equitable, and cost effective. 

21 And that's the step of designing control 

22 strategies. We implement the strategies, we check 

23 them, you know, we usually we check them by a 

24 monitor, you know, not with a model. And if it's 

25 not enough, then we go back through it again. 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 12 

 2 So that's the air quality management system, 

 3 and it's still the backbone of the United States 

 4 program for air quality improvement, although 

 5 there's wrinkles on it. 

 6 The greatest challenges -- now, can you hear 

 7 me if I walk over here? 

 8 (Comments off record and laughter.) 

 9 Do you have a problem if I talk without the 

10 microphone? All right. 

11 Well, meeting the standards and -- what? 

12 (Comments off record re using mic and not 

13 singing for the audience.) 

14 I will have to sing, so, I can't -- 

15 FROM THE AUDIENCE: Let us hear you, John. 

16 JOHN BACHMANN: Sorry, that's too dangerous. 

17 At any rate, one of the big challenges, this 

18 is from the Academy -- National Academy of 

19 Sciences' panel report two years ago. You can see 

20 it on the web, page by page in PDF -- 

21 FROM THE AUDIENCE: Good luck! 

22 MR. BACHMANN: -- or buy it for a fortune. At any rate -- or 

23 just listen to this. 

24 Meeting the standards relative to PM. They 

25 consider that our -- one of our most important 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 13 

 2 issues, and reducing regional haze. And some of 

 3 you may know that we're on a sixty (60) year light 

 4 path, from nineteen- -- or from 2004 to 2064 to 

 5 improve visibility in Class 1 areas; parks and 

 6 wilderness areas. 

 7 Designing and implementing controls for 

 8 hazardous air pollutants -- you know -- and moving 

 9 beyond porch potatoes to things that will make the, 

10 you know, to try to really identify whatever the 

11 problems are and address them, both the ones that 

12 are persistent and travel a long way, but also the 

13 ones that are -- that are exposing people in urban 

14 areas. 

15 Protecting human health and welfare in the 

16 absence of threshold. Increasingly, even our NAAQS

17 boards, we have a hard time saying, below this 

18 level there's no effects. 

19 In fact, when we set standards today, we talk 

20 about reasonable risks. Now we don't talk about 

21 "no effects levels" anymore. 

22 And with carcinogens, we have been there for a 

23 long time, and that is a challenge. 

24 Ensuring environmental justice, which is a 

25 core value, that does require, as we talk about 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 14 

 2 programs to change things in this neighborhood 

 3 versus that neighborhood to make sure that we are 

 4 equitable in -- in that kind of protection, which 

 5 is why local models will always be important for 

 6 that problem. 

 7 Assessing and protecting core system health, 

 8 I've already mentioned. They've had -- they say 

 9 that almost every chance they get a chance to say 

10 it. 

11 Mitigating intercontinental and across 

12 borders, so at the same time we worry about local 

13 on a smaller scale and regional scale, we're 

14 worried by international scales and maintaining air 

15 quality management system efficiency in the face of 

16 a changing climate. 

17 Now, they were told not to deal with climate. 

18 But what they pointed out was, okay, we won't deal 

19 with climate in terms of what you should do to 

20 control it, because that's not air quality 

21 management, but air quality managers need to 

22 realize the probability is the climate, our weather 

23 systems, are going to change, and if they change, 

24 they may change in directions that will make it 

25 more difficult, at least in some cases, for air 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 15 

 2 quality management. 

 3 For example, if it's hotter, there will be 

 4 more VOC emissions and more ozone and maybe more 

 5 stagnation. If it's warmer in the winter, maybe 

 6 there will be a less wood smoke and less heating, 

 7 so that'll have -- that will be the other 

 8 direction. 

 9 But the bottom line is, things are going to 

10 change, and you better be ready for them. 

11 And -- and so those are the kinds of 

12 challenges. Now, let me just stress that -- that 

13 we really agree with this assessment in terms of 

14 EPA's look at what the NRC said. 

15 We really believe, that for example, 

16 particulate matter especially, is -- is our most 

17 important traditional air quality problem. Why, 

18 because it looks like it may be responsible for 

19 premature mortality in tens of thousands of 

20 Americans for millions of cases of aggravated 

21 asthma and respiratory disease in kids. 

22 It's just bad stuff and the more we learn, the 

23 more we believe it, the more it looks like it's 

24 bad. 

25 We're less clear about which pieces are the 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 16 

 2 worst, or if there are worst pieces at all. 

 3 But we are very clear that we can now 

 4 concentrate, for example, Chapel Hill air and dose 

 5 people over fifty (50) and see changes in their 

 6 heart rate variability. 

 7 We don't know the mechanism for that, but we 

 8 damn well know that we can reproduce it to show 

 9 that. 

10 If that's the case, as we see in North 

11 Carolina's state troopers, we have a reason to 

12 believe that these epidemiology studies that people 

13 criticize for being a little -- you know -- they 

14 could be confounding, there could be problems, 

15 those are all valid questions about it. 

16 We -- we have increased reason to believe 

17 these effects that we're seeing are causal. So 

18 this is a big, big deal in doing PM modeling at all 

19 scales, local, regional is -- is vital, to getting 

20 it right. 

21 And we're in the middle of a review of the 

22 standards that might increase the need to worry 

23 about short-term exposures. We don't know how 

24 that's going to turn out. 

25 Visibility, I've already mentioned, whether 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 17 

 2 it's urban or rural; doing something about that is 

 3 more regional. 

 4 Ozone itself, we now have more data that's 

 5 just come out in the last two or three months, 

 6 published that ozone in fact also contributes to 

 7 mortality, something we didn't realize when we set 

 8 the standards in 1997, and -- and yet we have a 

 9 number of other effects we are always worried about 

10 with ozone. 

11 So there is more growing evidence that ozone 

12 and PM, in fact, are our worst criteria pollutant 

13 problems, and this is what the country looks like, 

14 so these are parts of the country that at least 

15 under the current ozone and (projecting map) PM 

16 standards, have to worry about it, the red areas 

17 being both pollutants and the other areas being 

18 either PM only or ozone only. 

19 The color is not the best for trying to figure 

20 out how to distinguish this. 

21 Things sure looks better on the computer 

22 screen than it does up here. 

23 But bottom line is that there's plenty of 

24 places that have problems with both. There's fewer 

25 places that have PM alone in this view, and -- and 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 18 

 2 plenty of places where -- with persistent ozone 

 3 problems. 

 4 And we have multiple pollutant sources we have 

 5 to deal with; some of these operate on a regional 

 6 scale and secondary formation, and some of these 

 7 operate on a more local scale, direct emissions or 

 8 particles like the diesel steel mills and so forth. 

 9 And as we look at the forecast residual 

10 non-teaming areas for fine particles, for example, 

11 we're seeing again and again the kinds of places 

12 that have persistent problems, and places that have 

13 classic old rust belt type local sources like steel 

14 mills, because some of the residual non-teaming 

15 areas are a who’s who of the steel cities; for 

16 example, Pittsburgh, Cleveland, Chicago, 

17 Birmingham. 

18 All those places have residual PM problems, 

19 while giant cities like New York City meet the 

20 standard, and Philadelphia meets the standard. 

21 So we've got some explaining to do, in terms 

22 of what to do to meet the standard in those kinds 

23 of cities and advances in local scale modeling are 

24 critical to doing that. 

25 Let me just say, I've been talking about 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 19 

 2 scales all along, and we've always worried about 

 3 local scales, and we're going to continue. 

 4 We'll worry about regional and increasingly 

 5 continental scale, and also personal, as I 

 6 mentioned. 

 7 We're going to worry about not just ozone and 

 8 PM but air toxics. 

 9 (Projecting another map.) 

10 This map just gives the sense that where there 

11 are cities with lots of people, there are cancer 

12 risks as there are also noncancer risks in the same 

13 kinds of locations that -- that present enough of a 

14 problem that we need to worry about those sources 

15 in addition to the MAC sources we control. 

16 And the idea is how can we unite the 

17 similarities of this map with the map I showed you 

18 for ozone and PM and to the fact that some of these 

19 sources are PM or VOCs to do a better job. 

20 New findings on roadway pollutions, say that 

21 right next to the breathing zone, more people die, 

22 more people -- more kids get sick and the exposures 

23 of ultrafine products in those ozones are very 

24 high, and so we may have a unique problem we 

25 haven't figured out how to deal with yet. 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 20 

 2 It's not, obviously, a MAC problem. Maybe it 

 3 will get solved by the controls that we've got, 

 4 where we get -- are putting in place, but right 

 5 now, there is something strange going on there. 

 6 Another one I find a challenge for modelers is 

 7 that in the future people are going to start 

 8 looking as we get to the edge of very low 

 9 concentrations to try to take that next bite, and 

10 maybe as they think about combined strategies that 

11 involve comment in some way, we will look at 

12 indirect strategies for managing air quality. 

13 One of them, that's already been suggested, is 

14 cool cities, and that just means planting more 

15 trees and making more reflective surfaces so that, 

16 let's see, take -- in the Mediterranean, before 

17 they had air conditioning, all the buildings were 

18 white. Well, we put black tar roofs on things and 

19 it gets hotter than hell down here. 

20 So the idea is that you make white roofs and 

21 lighter color streets, it flat out cools the 

22 cities. 

23 Well, modelers -- and everybody says, oh, that 

24 will make air quality better. Well, modelers also 

25 know that that also is going to reduce the urban -- 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 21 

 2 you know -- heat island effect which is good for 

 3 reducing temperature in the city, but maybe it also 

 4 increases dispersion by doing this. 

 5 So we're going to look at those kinds of 

 6 questions. 

 7 But one of the key air policies -- policy 

 8 issues I see from this, is we know that planting 

 9 more trees reduces air pollution. What are we 

10 doing in the United States in most places? Well, 

11 we're cutting them down to make -- for sprawl. 

12 As we cut things down for sprawl, there is less 

13 -- there are fewer trees to absorb what's going 

14 on. 

15 Our forecast models go out for ten (10) and 

16 fifteen (15) years, does -- do any of them -- do we 

17 ever even think about saying, you know, you're 

18 going to have to account for that difference in 

19 absorption, in deposition, as you change the 

20 character of the landscape. 

21 Well, no, we don't, and we're going to have to 

22 pay for that. At some point we're going to have to 

23 have policies on that. I know a lot of you kind of 

24 loathe even having to think about that. 

25 International transport of air pollution is 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 22 

 2 one that's really interesting. Here's what happens 

 3 if you zero out North America, Europe and Asia for 

 4 -- for VOC, and I'm including methane here, and -- 

 5 and nox. 

 6 Turns out methane is the most important, 

 7 slowly but globally important reacting with VOC on the 

 8 global scale, because there is so much of it, and 

 9 -- and it basically suggests that, indeed, there is 

10 international transport of ozone which is important 

11 for meeting the standard as the ozone standard has 

12 been tightened, but it's also important because 

13 ozone happens to be a green house risk. 

14 Communications, clearly we are increasingly 

15 thinking about moving, as we're moving to faster 

16 and faster computational models working with NOAA, 

17 to forecast air quality, not just by empirical 

18 methods, which is a really useful way to do it 

19 today, but also by running models, we are -- we are 

20 increasingly seeing models in a day-to-day 

21 operation. 

22 And then later, let's go back and check to see 

23 how well those models did, versus reality, we'll 

24 have an awful lot of information. Thus, this idea 

25 of communication to the public, and using models in 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 23 

 2 the air quality index is -- is one that is on the 

 3 way, as we develop improved models. 

 4 Then the last one I want to mention is 

 5 expanding accountability, and that is this issue 

 6 that, you know, we've always addressed air quality 

 7 we- -- in a weaker way except for the acid rain 

 8 program where it's been, you know, brought on, done 

 9 emissions trends, but we haven't done trends in -- 

10 as much in deposition, in health effects, and we're 

11 going to start to look harder and harder for 

12 examples of that, and -- and I think we're also 

13 going to spend more time at the back end checking 

14 to see if things worked as mid-course corrections 

15 and then trying to decide what to do about it and a 

16 little less time up front, in terms of -- in terms 

17 of forecast. 

18 The kinds of recommendations from the -- from 

19 the advisors that we then went to -- to look at, to 

20 talk about what to do about the Academy results in 

21 the area of interest here the scientific and 

22 technical capacity that surprisingly, a National 

23 Academy of Sciences panel recommended, what a 

24 shock!, that we ought to improve scientific and 

25 technical questions, of course, we should. 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 24 

 2 Emissions measurements and reporting; 

 3 emissions factors and estimation quantify and 

 4 reduce uncertainties. This idea of quantifying a 

 5 certainty is absolutely something that we have to, 

 6 you know, as we -- as we know more, we need to go 

 7 there in emission inventory and air quality, 

 8 modeling applications, integrated multi-pollutant 

 9 monitoring, obviously, and modeling, and developing 

10 a framework for accountability. 

11 So, at any rate, I wish you all well. I hope 

12 we're -- that we're anxious to hear what you have 

13 to say and work with you on -- on us moving forward 

14 to -- to do better air quality management against 

15 these challenges. 

16 Thanks. 

17 (Applause.) 

18 TYLER FOX: You can turn the lights up a little bit. 

19 In my rush, I forgot to actually introduce 

20 myself to everybody. 

21 You may or may not know that Joe Tikvart 

22 retired, and my name is Tyler Fox. I've been group 

23 leader for the air quality monitoring group for 

24 almost nineteen (19) months now, so, this, I 

25 believe, is the first modeling conference that Joe 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 25 

 2 has not been a part of? 

 3 FROM THE AUDIENCE: Correct. 

 4 TYLER FOX: So it's his first time not being here, it's my 

 5 first time being here. Unfortunately it's also not 

 6 going to be the first time you hear certain words 

 7 out of my mouth which is related to the status of 

 8 AERMOD. 

 9 I was talking to somebody yesterday who 

10 suggested that maybe I say it to you all in 

11 Spanish, (laughter) it would be maybe a little bit 

12 different. 

13 When I talk to my wife, my pronunciation is 

14 really bad, so I decided not to do that. 

15 Warren, where did you put -- where is -- (Mr. 

16 Peters assists Mr. Fox.) 

17 TYLER FOX: So, rather than go through the Spanish version, I 

18 figured I'd just go to Shakespeare and -- 

19 (laughter) AERMOD, oh, AERMOD, where for art thou? 

20 And I know that -- that you all, and the 

21 public in general, have been saying that for many 

22 years; 1990- something to the present. 

23 Let me -- let me just give you some -- some 

24 assurances that AERMOD is as close to being 

25 promulgated as it ever has been. 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 26 

 2 We -- 

 3 (Laughter.) 

 4 But you will know that I am -- I'm really 

 5 sincere in this. In April we moved the package and 

 6 cleared it through OAQPS, and it went up to DC. 

 7 There was a lot of things going on, CARE, CAMR the 

 8 BART rule, the confirmation of our administrator 

 9 and things did not move as fast as they typically 

10 do, unfortunately. 

11 We finally, about six to eight weeks ago, got 

12 it cleared through the office of Air and Radiation. 

13 Next step would be OPEI, Office of Policy and 

14 Economics Innovation. They're the final review 

15 before it gets to the Administrator's office. 

16 We addressed some basically bureaucratic, 

17 administrative- -- or administrative and executive 

18 order language, thought that was done, and I really 

19 thought it was going to be signed the week of Labor 

20 Day. I should have known better than that. 

21 We got some last minute, eleventh (11th) hour, 

22 comments from our friends up in DC, purely 

23 editorial, really not -- not meaningful in terms of 

24 making a difference in what's -- what's going to 

25 come out, but we've addressed those this past week, 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 27 

 2 and I would expect that it is on its way, if not 

 3 on, the Administrator's desk and getting ready to 

 4 be signed. 

 5 Humor me here and for the next two days, let's 

 6 just go to this -- we're -- we're close to the 

 7 finish line. Let's assume that we've crossed the 

 8 finish line, we're there, we're in this new era of 

 9 AERMOD, and for next two days, let's just kind of 

10 live that and take it as -- as a fact of life as we 

11 all should, and let's talk about not just the -- 

12 the new era that we'll have with AERMOD, the issues 

13 on implementing it and using it, developing it and 

14 further enhancing it, as well as the other future 

15 directions that we should think about in terms of 

16 the program area. 

17 John mentioned, you know, and nicely framed 

18 the big picture that we're -- we are looking at in 

19 terms of air quality management; broadly, the 

20 integration across programs which are going to 

21 necessitate the integration across pollutants and 

22 models and our technical capabilities. 

23 Our near-field modeling experience and 

24 expertise is critical to success in that area. And 

25 we, when I -- when I first joined, really asked the 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 28 

 2 folks in the group to really think about how we had 

 3 conducted business and what business would be like 

 4 in the future and to define that -- that future for 

 5 themselves and have us go through our management 

 6 chain and talk to, not just Peter Tsirigotis, our 

 7 division director, but Steve Page, the office 

 8 director, John, and others, and get them to, one, 

 9 understand and appreciate the importance of the 

10 work that we do, not just for permit modeling sake, 

11 but also as it relates to the bigger picture that 

12 John outlined. 

13 And, also, get them hopefully to appreciate 

14 and then look towards putting resources and making 

15 necessary investments in the program. 

16 So let me quickly just go through that as 

17 setting the stage for some of the discussions 

18 we'll have. 

19 Obviously, this morning we'll be focused on 

20 AERMOD, we'll also touch on CALPUFF. 

21 This afternoon, we'll start talking about some 

22 of the future elements in terms of gridded met 

23 data, and then tomorrow, there will be some focus 

24 on some general questions about model evaluation 

25 and acceptance and then its public statements. 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 29 

 2 But let me give you -- give you what we came 

 3 up with: Lead and provoke collaborative efforts on 

 4 near-field modeling, air quality modeling, to 

 5 improve source culpability assessments. 

 6 Again, lead, we're the air quality modeling 

 7 group, Joe is not here anymore, we lost a number of 

 8 other folks in terms of the expertise and the 

 9 experience, but that should not hold us back in 

10 terms of the leadership role that we have to you 

11 all and the community at-large. 

12 And the goal should be improving the quality 

13 and the public confidence in the assessments that 

14 we do. 

15 We can print this out and make it available to 

16 folks. 

17 And there are four elements. 

18 The first element, which is really an internal 

19 element through us; it's getting our house in order 

20 in terms of EPA and in our working relationships. 

21 It's really, foster a collaborative 

22 environment aimed at strengthening the technical 

23 expertise and working relationships across EPA, 

24 other Federal agencies, and the scientific 

25 community to regain our -- "our", in terms of the 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 30 

 2 Air Quality Modeling Group leadership role and 

 3 promote the best use of both science in modeling 

 4 applications and evaluation of those methods. 

 5 We are relooking, as I said, how we do 

 6 business. We re-energized our model clearing 

 7 house. 

 8 Warren Peters, about a year ago, well, it was 

 9 probably January that a memo went out to everybody 

10 naming Warren as the Model Clearing House Director, 

11 laying out the ideas of working in a more 

12 collaborative way. 

13 We have monthly phone calls with the -- with 

14 the EPA regions, we're pursuing and engaging in 

15 technical work groups across, not just across EPA, 

16 but also involving the states and others in this. 

17 In the -- in New Orleans, two or three months ago, 

18 we had a report out across to a number of technical 

19 work groups, and we -- we really see that given the 

20 constraints that we may be operating under now, and 

21 certainly -- you know -- given -- given the budget 

22 situation and certainly the recent incidents in the 

23 -- in the Gulf, you know, the budget certainly 

24 isn't going to get any better, and we need to 

25 understand that we need to work better together and 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 31 

 2 the -- leverage the technical expertise that 

 3 resides broadly across the community. 

 4 Second, and we'll hear about this 

 5 afternoon, is promote and facilitate the use of 

 6 gridded meteorological data, including state-of-the 

 7 practice, NWS meteorological analyses to improve 

 8 the modeling science and performance for near-field 

 9 modeling applications. 

10 And that's for permits, but also, as you heard 

11 John saying this, as many of you know, for toxics 

12 and also for direct PM. Those local sources, those 

13 areas that John mentioned; Birmingham, Pittsburgh, 

14 Chicago, Cleveland, with, you know, the fingerprint 

15 of a particular source causing the problem and 

16 resulting in those -- in those public health risks. 

17 So that will be discussed this afternoon. 

18 The third essential element is: promote 

19 continual development of the appropriate model 

20 evaluation methods to identify areas of improvement 

21 in our modeling system. 

22 That means not just the model itself, but also 

23 the emissions and the meteorological inputs that go 

24 into it, as well as the science. 

25 Prioritize the research agenda across the 
 1 Introduction/Tyler Fox/John Bachmann Vol. 1, p. 32 

 2 modeling community, scientific community, 

 3 consultants and the like, and ultimately improve 

 4 model performance in critical policy and science 

 5 areas. 

 6 We should be about improving things just for 

 7 the business of improving things, because some 

 8 little element that a researcher cares about 

 9 dearly, they want to spend their life on it. 

10 It needs to be drawn back into having a 

11 meaningful policy and/or effect on -- on public 

12 health. 

13 And we can focus on those. There are many out 

14 there, so focusing and prioritizing research is 

15 obviously a lot of the goal here. 

16 Fourth essential element here promotes a 

17 community approach to model development and 

18 acceptance that champions the use of best science, 

19 supports continual improvement in modeling science 

20 and data, and timely models acceptance for use in 

21 regulatory arena. 

22 So, the last two, the third and the fourth 

23 element, will be discussed tomorrow morning in 

24 panel discussions, and we'll get input from the 

25 panel and also have quite a bit, hopefully, 
 1 AERMOD/Warren Peters Vol. 1, p. 33 

 2 interaction between you and the panelists and us to 

 3 get information on your thoughts, concerns, issues, 

 4 and the like on -- on these. 

 5 I mean, we really do look forward to -- to 

 6 your input, and really appreciate your time coming 

 7 here, spending with us and without you, what we do 

 8 would not be successful. So we, again, appreciate 

 9 it, and let the fun begin. 

10 TYLER FOX: I believe the -- our first session is on AERMOD 

11 and Warren will chair that, and we'll have a number 

12 of presentations about the AERMOD modeling system 

13 that will be soon promulgated. 

14 WARREN PETERS: (Projects slide for audience.) 

15 Good morning, everyone. We appreciate you 

 

16 showing up this morning at nine o'clock (9:00) and 

17 going through our security procedures. See, you 

18 actually already -- everything went fairly smoothly 

19 this morning. 

20 We called the guys and asked for extra 

21 service, so it looks like it paid off. 

22 We have about a hundred people in the audience 

23 here this morning, so we appreciate your 

24 participation. 

25 As you probably know from the agenda, the 
 1 AERMOD/Warren Peters Vol. 1, p. 34 

 2 first part of the program this morning is going to 

 3 be on the AERMOD modeling system. 

 4 We actually have a team within our group 

 5 addressing AERMOD issues, and all the team members 

 6 will be making presentations this morning, so you 

 7 get a chance to meet them and see what the primary 

 8 responsibilities that they have. 

 9 I'll be giving the overall overview of the 

10 AERMOD modeling system, and that will be the first 

11 presentation this morning. 

12 First I want to introduce to you the names of 

13 the people that actually did the development work 

14 in AERMOD. It's called the AERMIC Committee and it 

15 stands for the AMS/EPA regulatory model improvement 

16 committee. 

17 Many of you had asked what does AERMIC stand 

18 for; now you understand. 

19 Jeff Weil is the chairman; Akula Venkatram, 

20 Robert Paine, Steve Perry, Alan Cimorelli, Russell 

21 Lee -- Russ Lee, Robert Wilson -- Rob Wilson and 

22 Warren Peters were all a part of that committee. 

23 And, of course, we made the special recognition to 

24 Roger Brode at MACTEC for doing a lot of the 

25 technical supports to that committee over the 
 1 AERMOD/Warren Peters Vol. 1, p. 35 

 2 years. 

 3 As you can see, we had a well balanced 

 4 committee here, because it comes from academia, 

 5 from EPA and from consulting. So, we are pleased 

 6 about that, and we hope that's a sign of things to 

 7 come for the future. 

 8 Just a brief regulatory history on AERMOD. 

 9 I'm sure most of you have at least a general idea 

10 of what's going on here. 

11 AERMOD was proposed in April of 2000. There 

12 was a Seventh modeling Conference where the AERMOD 

13 package was presented to the audience with lots of 

14 technical information about its performance and so 

15 forth. That was in June. 

16 And then in September of 2003, because of some 

17 of the significant changes we made to AERMOD, we 

18 actually put out another Notice letting people know 

19 that there was some significant changes to the 

20 consequence analysis that some of the AERMOD 

21 concentrations had changed from what was proposed 

22 and as seen by the Federal Register, and that 

23 information back in 2000, so we put out an 

24 additional Notice showing people the changes -- 

25 from the changes we made to the model, in the 
 1 AERMOD/Warren Peters Vol. 1, p. 36 

 2 science and other numbers we're looking now. 

 3 So that was a special notice of September 

 4 2003, and of course, as Tyler mentioned, any minute 

 5 now we'll have it the promulgation of Version 

 6 04300. 

 7 AERMOD has been updated since the proposal 

 8 package, as we've mentioned. We've added PRIME. 

 9 It was an overwhelming response from the community 

10 about putting PRIME into AERMOD. At the proposal 

11 we talked having ISC-PRIME and AERMOD separate 

12 packages; people said, that is really not a good 

13 idea. 

14 And so we listened, we now have PRIME into 

15 AERMOD. And it actually is -- the conclusion of 

16 PRIME, we actually have the performance evaluation 

17 looking even better in AERMOD, PRIME and ISC PRIME, 

18 so that was a job well done. 

19 And the credit should go to Roger Brode and 

20 the AERMIC committee. 

21 Also, we modified the complex terrain 

22 algorithms in there, too. We had public comments 

23 saying that we found that when you extended the 

24 domains and did other things to the AERMOD 

25 evaluation domain, it changed the results of the 
 1 AERMOD/Warren Peters Vol. 1, p. 37 

 2 complex terrain analysis. 

 3 We made adjustments for that, so it's not so 

 4 sensitive to the e-domain selection. We modified 

 5 the urban dispersion mechanism for low-level 

 6 sources, did some things with minimum mixing 

 7 heights to make sure we calculate the dispersion 

 8 very, very close down near the surface of the earth 

 9 in a more appropriate way. 

10 We've also -- we included the science by 

11 adding the meander which is an important phenomenon 

12 at low wind speeds for all stable and unstable 

13 conditions for the point and volume sources. 

14 And then for 0 four three hundred (04300), we 

15 made some minor bug fixes to the code. 

16 So there are some changes between Version 

17 02222 to 04300. But there -- to the tune of, like 

18 for instance, looking at and adjusting a numerical 

19 plume rise in the PRIME algorithms, and we found 

20 that if there was a bug in there, we'd run the 

21 consequence analysis that basically made no changes 

22 to the numbers. 

23 But there are some minor bug fixes in there. 

24 That is the background information on AERMOD. 

25 Now, let's talk about what AERRMOD really is. 
 1 AERMOD/Warren Peters Vol. 1, p. 38 

 2 It's a modeling system. AERMOD really has 

 3 three major components to it. 

 4 The AERMET meteorological preprocessor, we 

 5 have AERMAP the terrain data preprocessor, and then 

 6 AERMOD itself, which is the dispersion model. As 

 7 you can see, because the AERMOD is little bit more 

 8 sophisticated and has better science in it, these 

 9 preprocessors are to the user community, and we 

10 developed these tools to really make the job easier 

11 bringing in the terrain data and the meteorological 

12 data into AERMOD properly. 

13 We helped to develop some supports tools; 

14 now, most of you haven't seen these. These are 

15 some things that we've been working internally with 

16 other states and local modelers, but we're 

17 preparing to release these things as soon as 

18 possible. 

19 One is called the AERSURFACE, and this is a 

20 tool that processes surface characteristic data, 

21 which is now an important feature to the AERMOD. 

22 You may recall that -- maybe when you were a 

23 kid, you know, maybe you went around and maybe you 

24 had slingshots and eventually, as you got older, 

25 your dad gave you a BB gun, you know, you had a 
 1 AERMOD/Warren Peters Vol. 1, p. 39 

 2 more powerful weapon, but along with that more 

 3 power, you had responsibilities. 

 4 And here we find that's the same thing going 

 5 to be true moving from ISC to AERMOD. It's a more 

 6 powerful tool, but it also requires more work on 

 7 the preprocessing part and understanding the kinds 

 8 of data that go into AERMOD. 

 9 So AERSURFACE will help us in evaluating those 

10 kinds of information, and also, AERSCREEN now 

11 provides a screen tool where you don't have to make 

12 a full-blown AERMOD run to get estimates, or 

13 conservative estimates, to the downwind 

14 concentrations. 

15 We'll have presentations today on both those 

16 tools, as well. 

17 The documentation, I believe that AERMOD is 

18 the most documented model that the ADC has ever put 

19 out. We have gobs of documentation, so if you 

20 notice on the bottom of the screen, I made a little 

21 comment here. "Please read and use these 

22 documents". 

23 We spent so much time and money on them, and 

24 it will save you a lot of time and energy, probably 

25 will save me some time and energy, and so when you 
 1 AERMOD/Warren Peters Vol. 1, p. 40 

 2 call and you have a question, it won't be a simple 

 3 something that can be answered from the 

 4 documentation. 

 5 We have the model formulation document that's 

 6 mentioned up here as number one, that provides all 

 7 the science in the background, all the equations 

 8 that are going into AERMOD. Al Cimorelli and Steve 

 9 Perry worked real hard to keep that document up to 

10 date for us. 

11 We have users guides, very thorough users 

12 guides. 

13 We have the model evaluation report where it's 

14 showing how AERMOD does perform much better than 

15 ISC. 

16 And then we have a consequence analysis which 

17 helps to appreciate how much these concentration 

18 estimates are going to change, from using ISC to 

19 using AERMOD, and there are changes in AERMOD. 

20 We'll talk about that a little bit more -- 

21 about that later in this presentation. 

22 Basically we see better science in AERMOD, and 

23 some of the items we have near the planetary 

24 boundary layer concepts all now built into AERMOD, 

25 and there's basically a continuum of atmospheric 
 1 AERMOD/Warren Peters Vol. 1, p. 41 

 2 descriptions in here. 

 3 You remember with ISC we had classifications, 

 4 atmospheric classifications, stability 

 5 classifications in there. Now we have a continuum, 

 6 so AERMOD has much more power that way. 

 7 We have a more advanced building downwash 

 8 algorithms in here through the PRIME model. 

 9 We have the power to do better profiling in 

10 the atmosphere. We understand how the various wind 

11 speeds and temperatures change as you move away 

12 from the surface of the earth. And AERMOD 

13 understands that and can deal with that in the 

14 calculations. 

15 And we have other enhancements. Now, I hope 

16 that everyone saw that on the table out here, we 

17 had a number of handouts. 

18 One of them is a nice summary I think Bob 

19 Paine did for us a number of years ago comparing 

20 ISC to AERMOD. And it's a fairly thorough list of 

21 how the science has changed, so please look at 

22 that, take it home with you and keep that for a 

23 reference. 

24 Now we've worked real hard in the AERMOD 

25 development to make it as similar to ISC as 
 1 AERMOD/Warren Peters Vol. 1, p. 42 

 2 possible. And the good news here is that to 

 3 control across country with an AERMOD is just 

 4 exactly the same as what we had with ISC. 

 5 So if you've been running ISC for a number of 

 6 years, it shouldn't be much of a learning curve for 

 7 you to get up and get basic AERMOD up and going, 

 8 and you'll recognize alternate control features and 

 9 so forth. 

10 And virtually all the same keywords and 

11 options are there as we what we have in ISC. So 

12 we'll find out that you can make a lot easier 

13 transition to the AERMOD model. 

14 But, of course, there are differences. We 

15 have better science in here. Now, AERMOD will 

16 require more information to drive the model, but 

17 surface characteristics, the albedo, the Bowen 

18 ratio when there's surface roughness. 

19 And Karen Wesson will be talking about some of 

20 the impacts of those parameters as you do your 

21 evaluations. 

22 The PRIME building downwash algorithms require 

23 more information on the building dimensions, and so 

24 you'll be looking for that. It's the same as what 

25 we had in ISC-PRIME, but still it's different from 
 1 AERMOD/Warren Peters Vol. 1, p. 43 

 2 what we had in ISC. 

 3 Now, of course, with more extensive science, 

 4 there are more computations and that means longer 

 5 run times on the computer. So be expecting that. 

 6 It's about two to three times slower, as I 

 7 remember, from the ISC runs. 

 8 Here's a brief overview of some of the 

 9 consequence analyses. I have a pointer right here. 

10 I'd like to spend just a minute to give you a 

11 feel for the changes in the impacts you might see. 

12 In this scenario right here, we ran flat and simple 

13 terrain scenarios. We had point, volume and area 

14 sources. 

15 And there -- if you look at the bottom of the 

16 screen, there're forty-eight (48) cases of 

17 different source scenarios, okay? So forty-eight 

18 (48) cases here. And when I went back in -- let's 

19 -- let's focus on the one-hour table right here. 

20 An average ratio -- now, this is a table of 

21 ratios. This is the AERMOD concentration to the 

22 ISC concentration. 

23 So a value of one at AERMOD and ISC basically 

24 produce the same concentration. A value of two 

25 sets at AERMOD was twice as high. A value of point 
 1 AERMOD/Warren Peters Vol. 1, p. 44 

 2 five (.5) meant that AERMOD was half as high as 

 3 ISC. 

 4 Okay, you get the idea here, so if you know 

 5 the average for the one hour, over all forty-eight 

 6 (48) cases that AERMOD and ISC were pretty much the 

 7 same. 

 8 As you go across the different averaging times 

 9 to the three hours, about one point 0 nine (1.09) 

10 twenty-four, one point one four (1.14); and annual, 

11 one point thirty-three (1.33). 

12 So it slightly increased -- the ratios 

13 increased as we got to the longer averaging times. 

14 And we were kind of hopeful of that, because as we 

15 went through that performance evaluation, we found 

16 that ISC tended to underestimate long-term 

17 concentrations, so this actually was good news for 

18 us. 

19 But notice it was over -- day in and day out 

20 basically, you see that there AERMOD and ISC 

21 performed similarly, very similarly, but not in 

22 every case. 

23 As what the other practice here know, for the 

24 one hour, we had the high value -- most of the 

25 ratio for the mod- -- AERMOD and ISC is about as 
 1 AERMOD/Warren Peters Vol. 1, p. 45 

 2 high as four; it could be as low as point three two 

 3 (.32) which is about a third of ISC. 

 4 So there is a fairly significant range in 

 5 there. 

 6 So why are we putting consequences analyses 

 7 together? You can go back and look at the more 

 8 detailed analyses and get a feel for when you're 

 9 modeling the point source, try to find something 

10 that's similar in the consequence analysis, it will 

11 give you a feel for how this might change as you 

12 move into the AERMOD world. 

13 And again notice in the rest of the averaging 

14 times here, similar kinds of ranges from two down 

15 to a fraction of about four, are kind of falling a 

16 across the board here. 

17 Now, moving to the building downwash, those 

18 first sets of point sources had no buildings. 

19 In this case here with -- we had points with 

20 significant building downwash; that is, there was 

21 an impact definitely from the height of the 

22 building; we look at and see here, let's focus in 

23 on the three-hour second height barriers in here. 

24 We compared AERMOD to ISC3 and we compared 

25 AERMOD to ISC-PRIME. They both were a part of the 
 1 AERMOD/Warren Peters Vol. 1, p. 46 

 2 proposal package and replacement -- at in- -- in 

 3 this case, notice when we compared AERMOD to ISC, 

 4 it, again, was kind of similar on the average over 

 5 the six cases near the point seven one (.71), so 

 6 the AERMOD was presenting concentrations a little 

 7 bit lower than what we might expect from ISC in the 

 8 regulatory sense. 

 9 The range went from one point two 0 (1.20) 

10 down to a point thirty-eight (.38). So there 

11 wasn't a very wide range here. 

12 But the thing that we were doing when we 

13 brought PRIME into AERMOD, the goal was to make it, 

14 so that PRIME performs very similarly to the 

15 ISC-PRIME models. We knew when we brought PRIME 

16 into the AERMOD it would produce other kinds of 

17 problems or strenuous issues, and -- and false 

18 numbers, if you will. 

19 And here, we want AERMOD and ISC-PRIME to 

20 perform very, very similarly to ISC-PRIME. If you 

21 notice these ranges right here (indicating screen), 

22 on average it's one point 0 five (1.05); it's 

23 almost the the same gro- -- results. The high 

24 relative concentrations were one point one seven 

25 (1.17), seventeen percent (17%) higher. The lowest 
 1 AERMOD/Warren Peters Vol. 1, p. 47 

 2 point was point nine three (.93). 

 3 So I think we met our goal and did a pretty 

 4 good job here reaching the -- a very similar 

 5 performance between AERMOD and ISC-PRIME. 

 6 And if you notice as you go back to the other 

 7 averaging times, these kinds of relationships still 

 8 hold. 

 9 I believe the AERMOD presentation is -- is a 

10 part of the handouts here, so you don't have to 

11 memorize these numbers. You can carry your 

12 handouts back with you and see them. 

13 In a complex terrain, now here's one of the 

14 most dramatic results. May we call it ISC, we 

15 actually had Complex I, the screening model in 

16 there for complex terrain. 

17 AERMOD, of course, is doing much more of a 

18 science approach to the complex terrain, and we're 

19 expecting AERMOD to be quite a bit lower than 

20 AERMOD -- I'm sorry, than ISC, and indeed we find 

21 that true. Average over all the averaging times 

22 and all the point scenarios that we went through 

23 that AERMOD was about a quarter as high 

24 concentrations as what we've just seen from the 

25 ISC3 model. 
 1 AERMOD/Warren Peters Vol. 1, p. 48 

 2 And then the match by one to point seven nine 

 3 (.79) makes that point 0 seven three (.073) very 

 4 small. 

 5 And total number of cases in this case was a 

 6 hundred ninety-six, so we can see here that in all 

 7 cases AERMOD in complex terrain, produced 

 8 concentrations much lower than ISC. 

 9 On the performance, we've identified now the 

10 two models are definitely giving different 

11 concentrations, but is that seen by, or is it 

12 really backed up in the performance evaluation? 

13 Sure, the two models are going to be different, 

14 because AERMOD performed better. 

15 And as you can see in this summary right here, 

16 on the first floor, we looked at seventeen (17) 

17 different data bases in evaluating AERMOD. It was 

18 seven with the building downwash scenarios. We had 

19 ten (10) without buildings. 

20 When we had the case of no downwash, AERMOD 

21 out performed ISC in nine out of the ten 

22 evaluations, and had about the same performance in 

23 one evaluation. 

24 With the downwash scenarios, AERMOD out 

25 performed ISC-PRIME in two evaluations, had about 
 1 AERMOD/Warren Peters Vol. 1, p. 49 

 2 the same performance in four evaluations and was 

 3 outperformed in one evaluation. 

 4 So the bottom line that we kind of assumed 

 5 here, or made the conclusion, is that ISC -- oh, 

 6 I'm sorry, I got -- there is a footnote here. 

 7 We compared AERMOD to ISC-PRIME, and that's 

 8 what these relationship statements are all about. 

 9 But in the bottom, I wanted to make a note here, 

10 too, that in evaluating ISC-PRIME, and comparing 

11 ISC-PRIME to ISC, which is probably the logic or 

12 the reasoning here, ISC-PRIME slightly outperformed 

13 ISC. 

14 So what we're saying is, AERMOD outperformed 

15 ISC-PRIME; ISC-PRIME slightly outperformed ISC3. 

16 So it's a nice line of progression. 

17 Each version of the model became better and 

18 better in evaluations. 

19 That is pretty much a summary of -- of AERMOD 

20 in its comparison to ISC. We do have some ongoing 

21 activities with AERMOD that I'd like to present to 

22 the audience for a moment here, too. 

23 Because of some of the long run times on 

24 larger source scenario evaluations, when you have 

25 gobs of receptors, lots of sources, run times are 
 1 AERMOD/Warren Peters Vol. 1, p. 50 

 2 considerable, and we are trying to develop now a 

 3 version of AERMOD that will run in parallel. 

 4 We haven't been successful yet. It's been a 

 5 kind of a long journey, but we're getting close. 

 6 And I wanted to mention it to you that we're hoping 

 7 to have that version up as soon as possible. 

 8 Also, we're doing a number of minor upgrades 

 9 right now with -- through the support of MACTEC and 

10 Roger Brode, minor upgrades such as running AERMOD 

11 in multiple urban areas where you can specify an 

12 urban situation that is different from another part 

13 of the overall domain and still put that in one 

14 AERMOD run. 

15 So if you had multiple urban areas that are 

16 close by, and you wanted to run just one domain 

17 through here, you could do that with this 

18 modification to AERMOD in one run. 

19 We also have deposition with -- in a BETA test 

20 mode. As probably most of you know, it's been 

21 there for over a year, and also we have OLM and the 

22 PVMRM, the ozone limiting method and the plume 

23 volume molar racial method is also included in the 

24 AERMOD package now in BETA test mode. 

25 So those are all features that will, 
 1 AERMET/Desmond Bailey Vol. 1, p. 51 

 2 hopefully, as time goes on will become permanent 

 3 fixtures. 

 4 Okay. 

 5 So that's the overview of AERMOD and its 

 6 components. 

 7 WARREN PETERS: And next on the AERMET presentation, I'd 

 8 like to introduce Desmond Bailey who works in our 

 9 group. 

10 He's been directly responsible for the AERMET 

11 portion, and has developed all the software and has 

12 recompiled -- he's done all the work, basically, to 

13 get this to work. 

14 So it's certainly fitting for him to make this 

15 presentation this morning, but Desmond, let me ask 

16 you to help us understand AERMET. 

17 DESMOND BAILEY: I'm going to skip through the next slide 

 

18 that doesn't -- it was replaced, and -- 

19 (Comments off record concerning adjusting 

20 lighting in the meeting room.) 

21 DESMOND BAILEY: I like to keep people in the dark. 

22 (Lights are adjusted.) 

23 I'm going to relate to, let's see -- what I'm 

24 going to relate to you is the science that goes 

25 into -- has gone into AERMET, and then get a -- get 
 1 AERMET/Desmond Bailey Vol. 1, p. 52 

 2 a little bit into the -- what's involved in running 

 3 AERMET. But basically most of it's going to be the 

 4 science. 

 5 The -- if you think it took a long time to -- 

 6 it's taking a long time to promulgate the AERMOD 

 7 system, I'd -- I think that, well, I should point 

 8 out that the science, if you look at the references 

 9 in the model formulation document for AERMOD, you 

10 see a slew of references beginning in the seventies 

11 and tailing off in the mid eighties. 

12 So the science in AERMET really was sort of 

13 like dead by the mid 1980s. 

14 AERMET is essentially a boundary layer model, 

15 and like most models there are assumptions, it's an 

16 idealization with the boundary layer. 

17 All the dispersion that we're dealing with, 

18 everything occurs in the boundary layer. It's the 

19 focus of our dispersion models. 

20 We -- we -- and on a time line during the day, 

21 we look at what we call the convective boundary 

22 layer during the day, and the stable boundary layer 

23 at night. 

24 The convective boundary layer is driven by 

25 surface heating. It's characterized by vertical 
 1 AERMET/Desmond Bailey Vol. 1, p. 53 

 2 mixing, and as I say, it occurs during the day. 

 3 Stable boundary layer is less well understood. 

 4 It occurs at night, and there is little or no 

 5 vertical mixing. 

 6 Let me see. 

 7 Well, I'm -- (searching for computer slide). 

 8 The AERMET is designed to look at, or to 

 9 produce, profiles of wind/temperature in the 

10 vertical and lateral dispersion models. 

11 What the dispersion -- the science in AERMET 

12 -- the real, excuse me, the new science are 

13 replacing the Pascal-Gifford stability 

14 coefficients. The new science looks at -- 

15 translates the turbulence into dispersion, vertical 

16 and lateral dispersion. 

17 The other properties -- that's depth of 

18 mixing. 

19 The algorithms in AERMET are -- are based on 

20 similarity theory. Similarity theory applies in 

21 the surface layer which extends up to approximately 

22 fifty (50) meters at most, varies, and surface 

23 layer we're able to -- by applying similarity 

24 theory, we can estimate scaling parameters that are 

25 necessary to derive profiles of the turbulence 
 1 AERMET/Desmond Bailey Vol. 1, p. 54 

 2 parameters. Some of the scaling parameters, these 

 3 are sort of like rulers, are the friction velocity, 

 4 a convective velocity scale, a Monin- -- what we 

 5 call Monin-Obukhov length, which is a length scale. 

 6 There is a temperature scale and then the 

 7 other important parameter is the mixing height. 

 8 The convective boundary layer in its simplest 

 9 form has two regimes. It's a surface layer, as I 

10 mentioned before, which extends to about fifty (50) 

11 meters, and this is where the similarity theory 

12 applies. 

13 It's overlain by a mixed layer and capped -- 

14 the mixed layer is capped by a stable layer. 

15 There is also a -- an entrainment layer above 

16 the mixed layer which sort of provides a transition 

17 to the free air aloft. 

18 And in the convective boundary layer, both 

19 shear and turbulence -- or both shear and blocking 

20 contribute to the generation of turbulence. The 

21 closer to the surface, the more the shear forces 

22 contribute to turbulence. 

23 The boundary of the AERMET algorithms for the 

24 boundary layer, we employ a heat budget approach to 

25 estimate the surface heat flux, and basically it's 
 1 AERMET/Desmond Bailey Vol. 1, p. 55 

 2 a surface -- the -- what drives the boundary layer 

 3 -- the convective boundary layer is the heating 

 4 from the -- heating from below. 

 5 So you -- it's a -- the heating is from solar 

 6 radiation. Some of the solar radiation is 

 7 reflected, this is where the albedo comes into 

 8 play, and Karen will be talking about the albedo, 

 9 which is one of our surface characteristics. It's 

10 -- it's the reflection of the -- of the surface. 

11 We have the solar radiation and long riv- -- 

12 wave radiation. We are able to estimate what's 

13 called the net radiation which is the net result of 

14 -- or the energy that's actually available for 

15 heating the surface. 

16 And that's partitioned the -- that's 

17 partitioned into latent and sensible heat flux. 

18 And in the AERMET, we use a Bowen ratio, it's the 

19 ratio relating to sensible heat flux to -- to get 

20 the sensible heat flux. 

21 It's sensible heat flux that drives the convective 

22 the boundary layer. 

23 We use an iterative solution, or an iterative 

24 process, once we have the heat flux, we use the 

25 iterative scheme to tease out the friction velocity 
 1 AERMET/Desmond Bailey Vol. 1, p. 56 

 2 and the Monin-Obukhov length which are the scaling 

 3 parameters that are needed to characterize 

 4 turbulence in convective boundary layers. 

 5 And the mixing height, the growth of the 

 6 convective boundary layer is -- is determined by an 

 7 integration of the sensible heat flux through the 

 8 day, so, the boundary layer grows most rapidly 

 9 during the noon -- during the middle of the day 

10 when the sensible heat flux is the largest and then 

11 plateaus during the afternoon. 

12 The characteristics of the stable boundary 

13 layer, that again, develops when the -- develops, 

14 you know, after sunset when the surface begins to 

15 cool. Turbulence is shear driven, decays with 

16 height and mixing becomes very weak and is, 

17 compared to the convective boundary layer, it's 

18 more problematic; the tolerances for measurements 

19 are -- are much greater. There is much more 

20 computationally -- computationally -- you can run 

21 into problems with -- with one that's -- and the -- 

22 in my lane(?) the convective boundary layer we kind of 

23 extend the -- the algorithm that's used in the 

24 convective boundary layer, and we have, also, this 

25 -- again I say this is problematic, because 
 1 AERMET/Desmond Bailey Vol. 1, p. 57 

 2 computationally we run into some problems. An 

 3 alternative method which we also use in AERMET is 

 4 based on the Bulk Richardson number. 

 5 One of the problem -- one of the advantages of 

 6 using a Bulk Richardson approach in the stable 

 7 boundary layers, it doesn't require -- it doesn't 

 8 require a heat flux, so you don't -- in that case 

 9 you don't need cloud cover. 

10 The measurements required for the Bulk Richardson 

11 number are a temperature difference of the inner 

12 surface layer and a wind speed at one -- at one 

13 level. 

14 There were problems in the implementation of 

15 the Bulk Richardson number, again doing -- solving 

16 the algorithm for certain limits in -- in the first 

17 release of AERMET in 2002. 

18 An evaluation was funded to resolve this 

19 problem. 

20 In the study that was done, several 

21 alternative methods were looked at and tested, 

22 using field data from Prairie Grass, Kansas, and 

23 Cinder Cone Butte. 

24 Roger Brode conducted the -- the analysis and 

25 presented a paper at the A-W-M-A AWMA conference in 
 1 AERMET/Desmond Bailey Vol. 1, p. 58 

 2 Vancouver, 2003, and a revised algorithm was 

 3 implemented which seems to -- which works much 

 4 better which is in the current version of AERMET. 

 5 In terms of running AERMET basic, you know, I 

 6 have been talking about the boundary layer model, 

 7 but there are actually -- there is a front end to 

 8 that, which involves extracting raw data from -- 

 9 from meteorological files, created -- or that were 

10 once available from the NCDC. There is a QA and a 

11 merge process within -- which is a process that 

12 actually creates the files that are used by AERMOD. 

13 There are two (2) files; one is a surface 

14 file, which contains the scaling parameters that 

15 AERMOD uses to develop profiles of turbulence 

16 parameters. 

17 The profile -- there's a vertical profile, 

18 when AERMOD goes to calculate a concentration and 

19 determines the height of the plume and then it goes 

20 to the profile to get the lateral and vertical 

21 dispersion coefficients. 

22 The types of surface data that are supported 

23 by AERMET, the oldest is the CD one forty-four 

24 (144). The Samson -- there is a Samson CD. 

25 The most recent is the -- it's called Tape 
 1 AERMET/Desmond Bailey Vol. 1, p. 59 

 2 Deck thirty-five 0 five (3505), otherwise known as 

 3 Integrated Surface Hourly Data, and it is probably 

 4 the one that's going to be most commonly used in 

 5 the near term. 

 6 There is a -- we'll be talking about the use 

 7 of gridded met data and certainly a need to add to 

 8 this ability to take gridded met data and process 

 9 it through -- through AERMET. 

10 We talked about AERMOD as -- is a local scale 

11 model, and the -- and it has -- as I say, it has -- 

12 it's a boundary layer model. It's not clear that 

13 -- certainly has features that could do a better 

14 job than some of the gridded met data they have on 

15 that. 

16 The idea would be -- we're looking at taking 

17 AERMET with gridded met data, taking what's good 

18 out of the gridded met data but using the 

19 capabilities of AERMET to tailor these -- to tailor 

20 things for a local application. 

21 The upper-air data formats that are supported 

22 by AERMET, the Forecast Systems Laboratory, FSL 

23 format, and the TD sixty-two 0 one (6201) which is 

24 an older format. 

25 I think I will conclude with that. 
 1 AERMAP/Peter Eckhoff Vol. 1, p. 60 

 2 TYLER FOX: Thank you, Desmond. 

 3 WARREN PETERS: And by the way, what we're trying to do this 

 4 morning in terms of questions, we will have a 

 5 question and answer period, but we'll do it at the 

 6 end of the whole series of AERMOD presentations, so 

 7 if you have a question, please write it down, and 

 8 we'll address it as time goes on at the end of the 

 9 morning. 

10 We mentioned that there were two (2) 

11 preprocessors in the AERMOD package. Desmond has 

12 helped us understand AERMET and its power this 

13 morning. 

14 We also have a terrain preprocessor called 

15 AERMAP, and Peter Eckhoff is involved in setting up 

16 and keeping this part of the model functional and 

17 maintaining it. 

18 And we would like to invite Peter to the 

19 podium now, this morning, to help us understand and 

20 appreciate AERMAP, Peter. 

21 PETER ECKHOFF: Thank you, Warren. I'm Peter Eckhoff, and I 

 

22 work for the Air Quality Modeling Group here at 

23 EPA, and I've been assigned to improve AERMAP. 

24 And -- well, the purpose of AERMAP is to 

25 calculate elevations for sources and receptors that 
 1 AERMAP/Peter Eckhoff Vol. 1, p. 61 

 2 are processed by AERMOD. 

 3 AERMAP uses a number of digital elevation 

 4 model computer files that contain elevations that 

 5 were assembled by the United States Geological 

 6 Survey, and they were done at various times and 

 7 have different -- different ways that they were 

 8 formulated. Some were done over the surface of the 

 9 earth, such as the North American data of 1927, and 

10 some were earth centric, such as the North American 

11 data of 1983. 

12 And so when you put the two datums together, 

13 you'll find out that there're differences for the 

14 same point on the earth, and AERMAP --we were asked 

15 in AERMAP to adjust the formula so that they were 

16 all under one datum, and there are formulations for 

17 doing that. 

18 We also calculate a critical hill height for 

19 each receptor, and the output is formatted for 

20 input into AERMOD. 

21 This is an example of an AERMAP output file, 

22 and in this case it's for a gridded polar, and you 

23 can see that it is set up for inputting into -- or 

24 directly into AERMAP -- AERMOD. 

25 I want to introduce you to some of the 
 1 AERMAP/Peter Eckhoff Vol. 1, p. 62 

 2 modifications that were made to AERMAP. 

 3 There was a problem with the critical height 

 4 receptor in the calculations, in that when you 

 5 change the domain size, the results changed. 

 6 We were asked to also process the SDTS file 

 7 format for including into AERMAP, since the cost 

 8 for those files were free over the internet. 

 9 And we were asked to use, or create, 

10 algorithms to use with mixed DEM, or datums, and 

11 also the ability to read seven-digit Northing 

12 coordinates. 

13 We were asked for better error checking and 

14 also to use XYZ terrain data inside the model, and 

15 also the nodes spacing on the DEM files has 

16 changed. 

17 And so we put a variable node spacing 

18 algorithm in there. 

19 Then I want to talk about the status of 

20 AERMAP. 

21 The first public comment was that the critical 

22 heights could vary based on the domain zones which 

23 did affect the results, and what we did, we 

24 searched for the terrain that breaks through a ten 

25 percent (10%) slope from a receptor. 
 1 AERMAP/Peter Eckhoff Vol. 1, p. 63 

 2 What do we mean by this? 

 3 (Comment from audience re not being able to 

 4 hear the speaker.) 

 5 WARREN PETERS: Pete, can you get closer to the microphone? 

 6 We're having trouble hearing. 

 7 PETER ECKHOFF: Okay. Sorry. When you have a receptor, the 

 8 algorithm now, instead of -- okay, let me say this, 

 9 that this is the DEM file one, DEM file two, three, 

10 and four. And this is a domain boundary that was 

11 superimposed over four of these DEM files, and we 

12 have an example receptor, and we have various hills 

13 represented here, and a ten percent (10%) slope 

14 from that receptor. 

15 And the mandatory inclusion of the DEM terrain 

16 for nodes above ten percent (10). And we looked 

17 for the one that had the highest a -- elevation 

18 here. 

19 And so you can see that we have one that's 

20 inside the domain, but we have one that is outside 

21 the domain. And in order -- since this is the 

22 highest one, we would need to increase the domain 

23 boundary to include that particular critical 

24 height. 

25 So if you're down, say, Death Valley, you need 
 1 AERMAP/Peter Eckhoff Vol. 1, p. 64 

 2 to include Mount Whitney, if that's a ten percent 

 3 (10%) slope from your receptor. 

 4 The next was, we were to provide the ability 

 5 to read the SDTS data formats, which stands for 

 6 Spatial Data Transfer Standard, and it's available 

 7 from several internet sites for free, although some 

 8 of the sites put some restrictions on. The SDTSs 

 9 are preprocessed, and reconstituted into the old 

10 datum DEM format using the SDTS2DEM program. 

11 And this is also available on the internet, 

12 and we also include it as part of the AERMAP 

13 package. It's a batch files system included with 

14 the AERMAP package and that automatically -- well, 

15 that manually processes the data, and you have to 

16 read the instructions, because it asks at one point 

17 for a couple of keywords that need -- that you need 

18 to interact with the patch file in order to run it 

19 successfully. 

20 We were going to use -- what we were asked for 

21 use of AERMAP were two different DEMs, and we've 

22 got two different scales. One is the seven point 

23 five (7.5) minute data, and that's represented by 

24 the North American Datum of 1927, and also 1983; 

25 and the Old Hawaiian Datum and the Puerto Rican and 
 1 AERMAP/Peter Eckhoff Vol. 1, p. 65 

 2 the Virgin Island Datum. 

 3 And we found a program called NADCOM that 

 4 allows us to take any one of these datum and 

 5 convert it into the North American Datum of 1983, 

 6 which is the current standard. 

 7 Also, we have one degree datum scales, and 

 8 with that is the world geodetic center -- service 

 9 -- system of 1972 and 1984, and the current 

10 standards are 1984. 

11 The good thing is that the world geodetic 

12 system of 1984 and the North American Datum of 1983 

13 are almost exactly the same. Very, very small 

14 difference. I think it's in the millimeter range. 

15 The only change that we had to do was, we had 

16 to add the datum code at the end of the anchor 

17 keyword, and this is to identify the datum on which 

18 the receptors were placed. 

19 So, in other words, if you use a North 

20 American Datum map of 1927, the report is code for 

21 that datum. 

22 If it was done under, say, the World Geodetic 

23 Survey of 1972, we would put a different code at 

24 the end. 

25 And these codes are in the AERMAP manual. 
 1 AERMAP/Peter Eckhoff Vol. 1, p. 66 

 2 There was a problem with reading seven-digit 

 3 Northing coordinates, and what we did was we went 

 4 to double precision on the coordinates and used 

 5 single to double and double to single precision of 

 6 functions within the Fortran code. 

 7 And that's working well. 

 8 There was also a need for better err -- error 

 9 checking. We did add some error checks to AERMAP, 

10 and also there was -- had a lot of calls from 

11 people about AERMAP not processing their data sets 

12 or bit copying and/or crashing. 

13 And anyway, I went through and I looked at all 

14 the DEM files that were sent in and apparently they 

15 were put together under various formats. Some were 

16 DOS, some were Unix, some were just a native -- 

17 some were just a main frame code, and some had 

18 variable file lengths, and I was able to go and 

19 write an algorithm to read all those -- or all with 

20 the exception of one or two, or something that was 

21 really strange. 

22 Additional debug statements were added, and 

23 additional debug strategy is now being reviewed. 

24 There was -- we were asked to add XYZ terrain 

25 data processing capabilities, and what we decided 
 1 AERMAP/Peter Eckhoff Vol. 1, p. 67 

 2 to do was have the users take an old DEM file and 

 3 incorporate their XY values into that, and this 

 4 would fall into USGS Blue Book code format, and a 

 5 copy of that Blue Book format is in the AERMAP 

 6 user's guide. 

 7 And there is a draft XYZ terrain user's guide 

 8 has been prepared. Have we put that up on the -- up 

 9 on SCRAM yet? 

10 FROM THE AUDIENCE: Not yet. 

11 PETER ECKHOFF: Not yet, okay. Thank you. 

12 And this will allow you to incorporate XYZ 

13 data on into AERMAP run, and we should function 

14 quite well, and it's also subdocumented. 

15 USGS SDTS files have node spacings of ten (10) 

16 meters that have caused AERMAP to crash. 

17 And what I've done is I have changed the fixed 

18 values that were based upon whether it was seven 

19 point five (7.5) or one degree data, to just 

20 variables based upon values read from the header of 

21 the DEM files. 

22 And this is working now, well. 

23 And status of AERMAP; I'm working on 

24 allocatable arrays and testing the preprocessor at 

25 this time. 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 68 

 2 Thank you. 

 3 WARREN PETERS: We are just a little bit past halfway through 

 4 our AERMOD presentations. 

 5 Why don't we just take a five- or ten-minute 

 6 break for a moment and come back in here. 

 7 _______________________________ 

 8 (BREAK, 10:23 - 10:43 A.M.) 

 9 _______________________________ 

10 (Announcements.) 

11 WARREN PETERS: This morning's presentation to this point has 

 

12 been an overview of AERMOD and the two preprocessors, called 

13 AERMET and AERMAP. 

14 And you may recall in my introductory slides, 

15 I also mentioned that there were two additional 

16 tools that are under development that are not as 

17 well known by the public. 

18 And we wanted to make some brief presentations 

19 this morning, giving you the status of those tools 

20 and what they can do. 

21 I think you will find them quite handy and 

22 useful. 

23 The first model that I'm going to be talking 

24 about this morning is called AERSCREEN. 

25 Jim Haywood was scheduled to make this 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 69 

 2 presentation, but he could not make it this 

 3 morning, so he's asked me to fill in for him. 

 4 The tool here, of course, as I told you is 

 5 called AERSCREEN is a screening model for AERMOD. And 

 6 we set up work that was started several years ago. 

 7 We wanted to develop some screening procedures that 

 8 will provide concentrations that are as 

 9 conservative as that which would be predicted by 

10 AERMOD in a refined mode but do it in relatively 

11 quick run time. 

12 At this stage, we have a version of one point 

13 six (1.6) in Beta tests. We've developed it, we've 

14 been testing it, and it's looking quite good at 

15 this point. It has all the desired elements for 

16 doing the point source evaluations; that is, it has 

17 a wake effect on the building, terrain features and 

18 averaging time ratios. 

19 So those are things that we want to have in 

20 the tool that we've recently added. 

21 The part that's, of course, the most difficult 

22 when you're producing something like this is the 

23 documentation, and that's the part that we're 

24 working on right now with the assistance of Roger 

25 Brode. 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 70 

 2 That's the least amount of fun, but the more 

 3 important, probably, part of the work. 

 4 And we're trying to release this in Beta test 

 5 within the next several weeks. 

 6 We'd like to have recognize members of our 

 7 work group. As I mentioned, Jim Haywood from the 

 8 State of Michigan was our chair. 

 9 Roger Brode at MACTEC has been doing technical 

10 support for us again. 

11 Herman Wong, from EPA Region Ten (10), has 

12 been the tireless director in testing some of the 

13 AERSCREEN options that we had to develop the 

14 meteorological database. 

15 I'm on the work group here. 

16 Karen Wesson, a new employee at our group, has 

17 been doing a lot of number crunching, and you will 

18 hear more from her later on today. 

19 Bob Paine from ENCR has been working on this, 

20 and Annamaria Coulter from Region Two has also 

21 worked with us. 

22 (Projecting slide.) 

23 This setup for AERSCREEN is a real simple 

24 model. It's set up for interactive mode in a DOS 

25 screen, and basically when you turn on and run the 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 71 

 2 model -- and I'm going to try to present two 

 3 slides, giving you a little feel about how the 

 4 interactive session goes. 

 5 But I've actually had a computer session 

 6 going, but it's basically a question and answer 

 7 session on the DOS mode version. 

 8 At this point we have a setup only for point 

 9 source. We had wanted to set it up for volume 

10 source which should be a relatively quick change to 

11 the model. In fact, Jim's actually working on that 

12 now. 

13 We do not have area sources in there, and area 

14 sources will be a little bit more of a challenge. 

15 At this point, we can accommodate complex 

16 terrain automatically. It will automatically go to 

17 a web site, download one degree DEM data and make 

18 your runs. 

19 Now we've already done some testing; we've had 

20 comments on this, that the resolution for the one 

21 degree data probably isn't sufficient when you're 

22 in rel- -- rather complex terrain, I guess, very 

23 complex terrain. 

24 So there is a problem there that we will have 

25 to address. I will say a little bit more about 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 72 

 2 that later on. 

 3 But right now, we're in relatively flat 

 4 terrain, or simple/complex terrain, if you will, if 

 5 there is such a term. And the one degree data file 

 6 will be sufficient. That is a tool that's 

 7 available as a part of AERSCREEN. 

 8 We have in there the PRIME building downwash 

 9 mechanism. There you will have to know, however, 

10 some details about where the stack is located in 

11 relation to the building and that building's 

12 dimensions, so, still, even though it's a screening 

13 tool, you still need to have some information about the 

14 building and the stack locations. 

15 There is also a MAKEMET portion to this, where 

16 it goes through and develops, basically, a 

17 meteorological database that should cover all 

18 realistic worst case scenarios for the atmosphere, 

19 so that when you do the downwind concentration 

20 estimates here, it will be based on, you know, 

21 reasonable worst case atmospheric conditions, and 

22 that get reasonably good concentrations, that would 

23 be at least as high as AERMOD. 

24 Also, Jim has incorporated in here, which is a 

25 kind of a nice feature to the side with AERSCREEN; 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 73 

 2 when you make the run it gip- -- I'm sorry, it 

 3 develops a basic control file; something similar to 

 4 what AERMOD and ISC does, and that is, "store and 

 5 save". 

 6 So later on, if you want to go back to the 

 7 AERSCREEN run, rather than them going through the 

 8 entire interactive procedure, you can go back to 

 9 this control file and just modify the parameter or 

10 two that you need to change, and then quickly make 

11 the run. 

12 That's a nice feature I think you will 

13 appreciate the work that Jim put into that part of 

14 the model. 

15 And, also, for more flexibility here because 

16 the AERSCREEN may not do everything you want to do, 

17 or you have a really complex source scenario that 

18 you want to try to run a screen on, there is a 

19 stand alone MAKEMET version that you can run in a 

20 refined mode with AERMOD. And actually, AERMOD is 

21 turned on and put into a screen mode, as I 

22 understand, and MAKEMET will support that. 

23 So you've got yourself an AERMOD control file, 

24 and you can run MAKEMET with it. And it's a more 

25 sophisticated screening model, if you will. 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 74 

 2 (Projecting slide.) 

 3 Jim has put up a slide here. We spent a fair amount 

 4 of time in doing the scaling ratios. Right now the 

 5 AERSCREEN goes through and develops the maximum 

 6 one-hour concentration. From that one-hour 

 7 concentration we try to add just correction 

 8 factors, if you will, to that one-hour 

 9 concentration to estimate three-hour, 

10 twenty-four-hour, or annual values. 

11 Jim has done some analyses in here, and here's 

12 one of the tracks he's looked at, where we've 

13 applied off the relationships from the modeling 

14 results, actual full-blown AERMOD runs where we 

15 have buoyant and non-buoyant stacks, and these 

16 comparisons and evaluations of these results help 

17 us to produce a scaling factor that should work to 

18 produce conservative estimates for all AERSCREEN 

19 runs. 

20 And I also see in here, there is a function 

21 that -- I'm not sure you can see it from the back, 

22 but the abscissa here is stack height. 

23 So you can see that there is a range of stack 

24 heights from five to two hundred. 

25 And then the scaling factors are plotted on 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 75 

 2 the ordinate. 

 3 Here is the first screen you will see when 

 4 you're going through an AERSCREEN run. This is the 

 5 first series of questions on the interactive mode, 

 6 and applying the English and metric units. 

 7 And now, again, we have a series of questions 

 8 going on for the emissions rates, stack height, 

 9 stack diameter, all the things you leach back, 

10 and you leach those into an interactive mode, and 

11 down at the bottom here, notice here that we even 

12 go to the urban row, and you have to pick one of 

13 those. 

14 (Projecting slide.) 

15 And here is a diagram of a building that you 

16 want to evaluate. In this note -- in this case, we 

17 have to have a sense of the building dimensions, we 

18 have to understand where the stack is in relation 

19 to the center of the building, we have to 

20 understand the orientation of the building to true 

21 north. 

22 Those will all be parameters that you would 

23 put into this next screen when we go to the 

24 building downwash. Your building height, length, 

25 width, then the angle to the true north, and stack 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 76 

 2 to building center distance would have to be known 

 3 to make this model run. 

 4 Now here for -- to drive MAKEMET, you have to 

 5 recall that we have to have a minimum wind speed in 

 6 here and normally defaults to point five (.5). 

 7 There's an anemometer height, of course, for 

 8 the wind direction -- I mean for the wind speed, 

 9 again. 

10 Also, going back to the surface 

11 characterization which is now a new important 

12 parameter in the AERMOD. 

13 We have a number of options in here which are 

14 based on the tables in AERMET, and you can select 

15 one of these to describe your area. 

16 Also, there is an option in there, if you do 

17 know what your surface characteristics are already, 

18 and you don't need the table, you can enter in your 

19 other user default mode, and the sock will -- will 

20 allow that to happen. 

21 Now once the data are entered, you hit the go 

22 button, so to speak, it comes back with a data 

23 entry validation step, so you can quickly review 

24 all the information you put in here. Notice it 

25 comes out in both English and metric units, and you 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 77 

 2 can review it and be sure that you entered the 

 3 proper data at this last second check before you 

 4 make your final run. 

 5 Now here's the screen that will pop up after 

 6 you've hit the go button, and you're actually doing 

 7 the evaluation-. It will show you that it's making 

 8 progress for the four seasons of the year, and then 

 9 finally the output. 

10 The concentrations here are set up on a very 

11 simple table, and notice in this case here, the 

12 calculated value here that comes out of AERSCREEN 

13 would be the maximum one-hour concentration, this 

14 value right here. 

15 That is the output (one twenty-nine point nine 

16 sixty-seven (129.967) from AERSCREEN. 

17 And from there, scaling factors are applied to 

18 get the three-hour, the eight-hour, the 

19 twenty-four-hour, and the annual, and there were no 

20 calculations made other than the simple scaling. 

21 All -- also, notice in here -- notice there is 

22 some distance in receptor height information, 

23 giving you, again, some feedback about where the 

24 location is for the high concentration. 

25 (Projecting slide.) 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 78 

 2 Now on here, here's a second table, but in 

 3 this point -- let me see, in this point right 

 4 here, there is a feature called the ambient 

 5 boundary. 

 6 AERSCREEN will go through and calculate the 

 7 maximum concentration, I believe, starting at some 

 8 very, very close distance to the stack, but if you 

 9 have an ambient boundary or a boundary actually 

10 around your plant that you want to stop the 

11 analysis there, so to speak, so let's say you have 

12 a boundary or a fence line that goes out to a 

13 hundred meters, you want to enter that into 

14 AERSCREEN, and AERSCREEN starts calculations based 

15 on the distance to the fence line. 

16 And that's what this set of numbers is all 

17 about right here. These are fence line 

18 concentrations or boundary concentrations. So you 

19 have the option to put that into the model. 

20 Again, the one-hour concentration is 

21 calculated. These values in here are scaled. 

22 And then lastly, there's some feedback 

23 information about where ambient boundary is. It 

24 spits back the input information we have over 

25 seventy-five (75) meters. 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 79 

 2 (Projecting slide.) 

 3 This is an example of what they call the 

 4 restart file. Once you have made the AERSCREEN 

 5 run, you've entered in your data on an interactive 

 6 mode, and you want to go back, and you say, oh, I 

 7 want to change this, I either made a mistake or I 

 8 want to evaluate another situation, you go back 

 9 into this file called "restart file", and you can 

10 make changes to the information in here that's 

11 appropriate and then rerun AERSCREEN. 

12 And this saves a whole lot of time, because it 

13 does take two or three minutes to go through the 

14 interactive process, and maybe a little bit longer, 

15 depending on what options you're running. 

16 So this is an example of the restart file, and 

17 it's real obvious, and real -- quickly noted as to 

18 where you need to make the changes in the different 

19 parameters in here. 

20 They are -- they are all carefully marked. 

21 They are all free format, you know, and you don't 

22 have to be too careful in the way you change those 

23 numbers, by the way, either. 

24 (Projecting slide.) 

25 Here is some of the results when we've 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 80 

 2 compared the AERSCREEN numbers to the IS -- I'm 

 3 sorry, ISC -- (chuckling) when we've compared 

 4 AERSCREEN results to AERMOD. 

 5 And our -- again, our goal was to make sure 

 6 that AERSCREEN produced concentrations at least as 

 7 high as AERMOD, and we had a number of people that 

 8 are on the testing committee here, and as you 

 9 noticed in here, and the thing we want to focus in 

10 on is probably the minimum ratio. 

11 This is, again, a ratio of AERSCREEN to AERMOD 

12 results, so a number of one or higher is a good 

13 result. 

14 A number less than one would be something of 

15 concern, and notice in here in Jim's testing, he 

16 had seven sources, his minimum ratio is one point 0 

17 nine (1.09). 

18 When Karen was running through the stack 

19 downwash, we had one case in here, I believe, that 

20 was at point seven five (.75), which we're still 

21 looking at and reviewing. 

22 Karen, when she did the non-downwash building 

23 situations here, our low -- lowest ratio was point 

24 nine seven (.97), which is probably going to be 

25 acceptable here, and then Roger and his set of 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 81 

 2 sources, six hundred seventy-two sources, his 

 3 minimum value was point nine six (.96), and then 

 4 Bob Paine in complex terrain was one point 0 eight 

 5 (1.08). 

 6 So those are very, very good results and it 

 7 has taken a lot of work to get those numbers to be 

 8 in that range. 

 9 Now that helps us to appreciate the low-end 

10 values, so to speak, but if AERSCREEN really 

11 over predicts AERMOD that's also another concern, so 

12 we're looking at the maximum ratios here, how high 

13 are those values; in Jim's testing here he's -- his 

14 AERSCREEN results were five times higher than 

15 AERMOD. 

16 It's fairly acceptable, probably, for a 

17 screening model. 

18 Karen in her testing these stacks that we have 

19 basically from the consequence analysis, her 

20 highest ratios are about, somewhere between two and 

21 two-and-a-half, which is an outstanding result for 

22 a screening model. 

23 Roger Brode, in his stack was twenty-two (22) 

24 -- 

25 FROM THE AUDIENCE: High number! 
 1 AERSCREEN/Warren Peters for Jim Haywood Vol. 1, p. 82 

 2 WARREN PETERS: That's a high number, yes, -- 

 3 ( Laughter.) 

 4 WARREN PETERS: -- and Bob Paine was at around seven or eight 

 5 which is probably reasonable for a screen tool. 

 6 So there's still a bit of work to do with 

 7 AERSCREEN to make sure that these numbers come out 

 8 in reasonable ranges, but you can see overall, 

 9 based on this, this is going to be seven hundred 

10 (700), -- that's going to be close to eight hundred 

11 (800) sources being tested that AERSCREEN is doing 

12 a very, very nice job at this point. 

13 Those are the one-hour results. 

14 Now on the annual results, which is basically 

15 a reflection of the way that we have done our 

16 scaling, again, we looked at the minimum ratios. 

17 Jim's data set was a little over one, Karen 

18 had an example of about point seven five (.75), so 

19 we're still focusing in on that. 

20 The other non-downwash situations was around 

21 one. 

22 And, again, Bob Paine was around four. 

23 And then the max ratio, which is, again, the 

24 other extreme, so to speak, we went from thirteen, 

25 three, six and seven -- I'm sorry, no, seventy-one 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 83 

 2 (71) -- whew!, forgot about that one, Bob. That 

 3 would clearly need some more work. 

 4 But, again, we are seeing that our minimum 

 5 ratios are looking quite good in here. There still 

 6 needs to be more work done in support, and that's 

 7 why we want to release this model Beta test when it 

 8 becomes available and the documentation is ready. 

 9 Okay. 

10 So that concludes the presentation on 

11 AERSCREEN. 

12 The next portion that we want to introduce you 

13 to is the AERSURFACE, and I'd like to introduce to 

14 you Karen Wesson from our group who will now help 

15 us appreciate and understand some of the features 

16 of this new tool called AERSURFACE. 

17 Karen. 

18 KAREN WESSON: Okay, so I'm going to talk a little bit about 

 

19 the tool for AERMOD called AERSURFACE. 

20 And just what is AERSURFACE? Okay, so 

21 AERSURFACE is a tool and it produces the surface 

22 characteristics data that will go into AERMET which 

23 will spin into AERMOD. 

24 And these data include the albedo, the Bowen 

25 ratio, and the surface roughness. 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 84 

 2 This tool was originally developed by Chris 

 3 Arrington of West Virginia DEP and Larry Simmons of 

 4 Energy and Environmental Management, Incorporated. 

 5 AERSURFACE is actually a Fortran program, and 

 6 the way that was originally set up, it reads USGS 

 7 land use data from the 1970s-80s data. 

 8 And from this data, it returns back on back 

 9 surface characteristics values. These include the 

10 surface roughness, the albedo, and the Bowen 

11 ratio. 

12 And it does this for the -- for twelve sectors 

13 at thirty degrees (30o

). 

14 So AERSURFACE allows you to specify the center 

15 of the location that you are interested in, and the 

16 radius of the study area that you're -- that you 

17 want to average over. 

18 And then a circle is formed, and parsed into 

19 twelve sectors, and each of these sectors is a 

20 thirty (30) degree. 

21 Here you can take a picture of just what 

22 AERSURFACE does. So you specify the center of the 

23 location, and then you specify your radius. 

24 And here you can see a diagram for radiuses of 

25 one kilometer, three kilometers and five 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 85 

 2 kilometers. 

 3 And so it parses -- it draws a circle and 

 4 parses it into twelve (12) sectors and then 

 5 averages over each of these twelve (12) sectors. 

 6 The AERSURFACE help has developed, so you can 

 7 see for each of the twelve (12) sectors output, an 

 8 albedo, a Bowen ratio, and a surface roughness. 

 9 It also outputs for the entire -- for the 

10 entire area of the circle, the mean albedo and 

11 Bowen ratio and surface roughness. 

12 AERSURFACE, also, when it outputs this data, 

13 outputs it in a format that can be copied and 

14 pasted directly into AERMET. 

15 And this is what it would look like 

16 (projecting slide). 

17 So before we did any modifications to 

18 AERSURFACE, we felt that it was important to first 

19 understand just how AERMOD is responding to changes 

20 in surface characteristics. 

21 So we did a sensitivity study, and we divided 

22 it into two parts. 

23 The first part is, what we're doing is we 

24 varied the albedo, the Bowen ratio, the surface 

25 roughness, and we varied them systematically. 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 86 

 2 And we did this for two sets of met data. 

 3 In the second part of the study, we wanted to 

 4 be able to vary them, not systematically, but 

 5 together, and for seasonal variations. 

 6 And we did this for combinations of the land 

 7 surface value, so it would be bound in eight 

 8 surface -- excuse me, eight surface types. 

 9 So -- okay, so part one, the requirements were 

10 for two met data; one was Oklahoma City and one was 

11 Pittsburgh. And we varied the surface 

12 characteristics. 

13 For the albedo, we ranged the values from 

14 point one (.1) to zero point six (0.6), and we did 

15 this, we held the Bowen ratio and the surface 

16 roughness constant with values of one point zero 

17 (1.0) and zero point one (0.1). 

18 For the Bowen ratio, we varied from zero point 

19 one (0.1) to ten (10), again holding two constants, 

20 the albedo at zero point two (0.2) and the surface 

21 roughness at zero point one (0.1). 

22 And then for the surface roughness it ranged 

23 over a very large range here, from point zero zero 

24 one (.001) to one point three (1.3), holding the 

25 albedo and the Bowen ratio constant at point two 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 87 

 2 (.2) and one point zero (1.0). 

 3 So we did this for several stack heights. We 

 4 held eleven stack heights with no buoyancy, 

 5 between five and two hundred (200) meters, and you 

 6 can see here (indicating on slide) the eleven (11) 

 7 different stack heights that we used. 

 8 We held -- we did a -- three stack heights, a 

 9 hundred (100), a hundred fifty (150) and two 

10 hundred (200) meters, and how their stacks have to 

11 be buoyant. 

12 And we did this combination of these fourteen 

13 stack heights for both Oklahoma City and for the 

14 Pittsburgh met data. 

15 For the Oklahoma City data, we also added two 

16 other stack heights. That's thirty-five meter 

17 buoyant stack and a thirty-five meter very buoyant 

18 stack. 

19 Okay, so here's some of the results. 

20 For the albedo, again it's going from point 

21 one (.1) to zero point six (0.6) on the Bowen ratio 

22 constant and the surface roughness concept. 

23 Okay, so the results I'll show are going to be 

24 twenty-four-hour averages and are going to be the 

25 first high concentrations. 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 88 

 2 Here we see concentration plots, how the 

 3 albedo ranges across the X axis here; it's ranging 

 4 from point one (.1) to zero point six (0. 6), and 

 5 the concentration is plotted on along the scale. 

 6 We see some variation but not -- not a lot of 

 7 variation here. And this is for the sixteen (16) 

 8 stack heights for Oklahoma City, and we have run 

 9 AERMOD with a study of source characteristics. . 

10 So to give you some numerical idea of what 

11 that graph was trying to say, I've plotted here 

12 some stacks with percent difference, and this is 

13 for stack heights, we selected four, five meters, 

14 thirty (30) meters, a hundred (100) meters and two 

15 hundred (200) meters very buoyant. 

16 And principal differences we're showing are 

17 going from an albedo of point one (.1) to two times 

18 that value of zero point two (0.2), three times 

19 that value of zero point three (0.3), four point 

20 five (4.5) times the value or zero point four five 

21 (0.45) and six times that value at zero point six 

22 (0.6). 

23 So -- and here you can see the stats, the 

24 percent difference for the albedo, for the role 

25 setting for Oklahoma City. We see that the highest 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 89 

 2 variability in the concentration seems to be with 

 3 the higher stack. There is some variability for 

 4 the lower stacks, but the higher stack seems to 

 5 have -- be the most sensitive to the concen-concentration values -

- to 

 6 the albedo value. 

 7 (Projecting slide.) 

 8 And then we ran, also, for Oklahoma City, but 

 9 had AERMOD, in the urban setting. Again, you see the 

10 concentration values for variations in the albedo 

11 of the sixteen (16) stack heights; not a huge 

12 amount of variability that we can see on the log 

13 scale. 

14 So numerically here we have the stats for 

15 that, again, similar. We see that the most 

16 sensitive concentrations are at the taller stack, 

17 the two-hundred (200) meter, very buoyant. The 

18 five-meter stack is showing little or no 

19 sensitivity, but as we go to the higher stacks, 

20 we're seeing more sensitivity to the changes in 

21 the albedo. 

22 (Projecting slide.) 

23 Okay, so we also ran, for the role setting for 

24 Pittsburgh, we have fourteen (14) stack heights 

25 here. 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 90 

 2 You can see that for the low stacks, it seems 

 3 to be pretty flat, and then for some of the 

 4 intermediate stacks, we feel a little more 

 5 variation. 

 6 And numerically looking at this, again we see 

 7 the short stacks of five (5) meters, very little 

 8 sensitivity to the albedo change. However, as 

 9 we're going up in the stack height, more and more 

10 sensitive to the changes in the -- in the albedo 

11 value. 

12 (Projecting slide.) 

13 We also did this for Pittsburgh with the urban 

14 setting, again, for the fourteen (14) stack 

15 heights. 

16 We see a little bit of sensitivity 

17 numerically, see the -- the percent differences 

18 here again; five-meter stack, nice showing. Huge 

19 amount of sensitivity to the changes in the albedo. 

20 The other stacks are showing some sensitivity, 

21 the highest being in the taller stacks, the two 

22 hundred (200) meter very buoyant stacks. 

23 Okay, now -- and now for the Bowen ratio. 

24 The Bowen ratio is going to vary between point 

25 one (.1) and ten (10), so a little more variability 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 91 

 2 here. Holding albedo constant at the zero point 

 3 two (0.2) and surface roughness constant at zero 

 4 point one (0.1). 

 5 Again, twenty-four-hour average concentration, 

 6 first time. 

 7 (Projecting slide.) 

 8 So for the sixteen (16) stacks, for the rural 

 9 setting for Oklahoma City, we see a little bit of 

10 variability; here again concentration is plotted on 

11 the log scale. 

12 X factors of time has the Bowen ratio, Bowen 

13 ratio varying between zero point one (0.1) and ten 

14 (10). 

15 So, numerically looking at this, it seems that 

16 the shorter stack, the five-meter stack not showing 

17 a lot of sensitivity to the changes in the Bowen 

18 ratio. 

19 As we go up in the stacks, we see a higher 

20 concentration. Here the Bowen ratio -- we started 

21 -- we compared it against the Bowen ratio, with the 

22 -- at the zero point one (0.1) the concentration at 

23 that point, and then increasing the Bowen ratio to 

24 three times at zero point three (0.3), ten (10) 

25 times at one (1), forty (40) times at -- that Bowen 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 92 

 2 equals four and then a hundred times the Bowen 

 3 ratio equals a hundred (100). 

 4 So here again the taller stack seems to be the 

 5 most sensitive. 

 6 Okay, now, again for Oklahoma City, the same 

 7 sixteen (16) stack heights. 

 8 Now we're running with the urban setting, and 

 9 for the Bowen ratio, numerically we look at these, 

10 and again shorter stacks not showing that much 

11 sensitivity, but the taller stacks, again, more 

12 sensitivity -- sensitive there to the choice in the 

13 Bowen ratio line. 

14 All right, now for the Pittsburgh met at -- in 

15 the rural setting, the fourteen stack heights and 

16 the Bowen ratio value going from zero point one 

17 (0.1) to ten (10). 

18 Numerically, here we see the same thing, 

19 seeing a little bit more sensitivity with the 

20 highest stack, but again, the five-meter stack 

21 showing little sensitivity and as you go up in the 

22 stack height, you see more, some of the 

23 intermediate stack heights look like they are 

24 varying, also, in this example. 

25 Because now we've run Pittsburgh with the 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 93 

 2 urban setting, and again, it's the same fourteen 

 3 stack heights. 

 4 The concentration changes down here, at the -- 

 5 at the early stages of changing the Bowen ratio. 

 6 And statistically, again, the smaller stack 

 7 heights not showing a lot of variability, larger 

 8 stacks showing quite a bit of variability. 

 9 Now, sensitivity results, surface roughness is 

10 varying between point zero zero one (.001) and one 

11 point three (1.3), quite a large range. 

12 Albedo is held constant at the zero point two 

13 (0.2); Bowen ratio held constant at one point zero 

14 (1.0), 

15 Again, twenty-four-hour average, first high 

16 concentration. 

17 (Projecting slide.) 

18 Okay, here's the -- we're starting to see a 

19 lot of variability, and we're starting to see it in 

20 the -- in the low stack. As you know, the -- as 

21 the stack is -- is increased, the concentration 

22 decreases, and here again we're seeing that 

23 pattern, and we're seeing the lower sector having a 

24 lot more sensitivity to changes in the surface 

25 roughness. 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 94 

 2 Okay, now you look at that statistically, and 

 3 with the -- you know -- it's the five-meter stack 

 4 here is having a lot of variability, and the 

 5 Zee-naught is going from, you know, our case here is 

 6 where you seem to compare them, And the Zee-naught is 

 7 point zero zero one (.001), and we're comparing 

 8 that at five times the value of point zero zero 

 9 five (.005), fifty (50) times the value from point 

10 zero zero five (.005), five hundred times the value 

11 of point zero five (.05), five thousand times the 

12 value at point five (.5), and thirteen hundred 

13 (1300) times the value of one point three (1.3). 

14 So, again, we're ranging the Zee-naught at a -- 

15 quite over -- quite a large variability here. 

16 And that's not a lot of variability, 

17 especially in -- in the lower stacks, but there is 

18 still sensitivity in the -- in the taller stacks. 

19 So we also did this for the urban setting, 

20 again, in Oklahoma City, same fifteen (15) stack 

21 heights, and seeing the same pattern here. 

22 Again, the stats show something very sim- -- 

23 very similar, large sensitivity on the lower stack, 

24 the higher the stack goes, seems to be not quite as 

25 sensitive. 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 95 

 2 For the Pittsburgh met data, rural setting, 

 3 again, fourteen stack heights, and the surface 

 4 roughness on the X axis, a lot -- lot of 

 5 sensitivity here again, smaller stack. 

 6 Going to specifically looking at the larger 

 7 stack -- I mean the shorter stack, the five-meter, 

 8 showing sensitivity cliff to a hundred percent 

 9 (100%) rel- -- relative per- -- a hundred percent 

10 (100%) difference here, and -- but still the taller 

11 stacks are showing sensitivity. 

12 (Projecting slide.) 

13 Pittsburgh now in the urban setting, same 

14 fourteen (14) stack heights, again similar 

15 patterns, just to show you something similar, it's 

16 very sensitive to surface roughness, but the 

17 smaller stacks are showing the greater 

18 sensitivity. 

19 So from this side of the street, what have you 

20 learned? Well, it seems that the concentrations in 

21 AERMOD are pretty sensitive to the choice venue 

22 surface roughness. There is some sensitivity in 

23 albedo and the Bowen ratio, but we definitely see a 

24 source height dependency here. 

25 The shorter stack seems to be more sensitive 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 96 

 2 to the surface roughness value, and the taller 

 3 stacks are more sensitive to the albedo and Bowen 

 4 ratio values. 

 5 For the second part of the sensitivity study, 

 6 now we want to vary these values, not 

 7 systematically but together. We want to do it 

 8 seasonally, and we want to do this where the values 

 9 would actually be seen in nature for -- and we 

10 chose eight land types. And these eight land types 

11 are out of the AERMET user's guide. 

12 That's where we took the surface roughness and 

13 albedo and Bowen ratio values. 

14 The Bowen ratio values were selected for 

15 normal conditions, not wet, not dry, but normal 

16 conditions. 

17 The eight land types that we chose; water, 

18 grass, cultivated land, swamps, desert, deciduous 

19 forest, urban and conifer forest. 

20 (Projecting slide.) 

21 Okay, so here I've plotted, again, the 

22 concentration on the Y axis, and on the X axis we 

23 planted the different land use types, and here 

24 they're organized so that we go from the smallest 

25 surface roughness, point zero zero zero one (.0001) 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 97 

 2 to a larger surface roughness, one point three 

 3 (1.3). 

 4 We have done this -- this is Oklahoma City and 

 5 the rural setting for AERMOD and for the sixteen 

 6 (16) stack heights. 

 7 Again, we see -- it seems to be the pattern 

 8 where it -- the stacks -- the shorter stacks are 

 9 seeing more sensitivity to the surface roughness 

10 that seems to be having the larger impact here, 

11 and we did this also for the urban setting for 

12 AERMOD, again, for the Oklahoma City met data. 

13 And the sixteen (16) stack heights we're 

14 seeing very simply pattern here also for -- for 

15 these cases. 

16 And we did this for the Pittsburgh met set, 

17 and with the rural setting, and here we have the 

18 fourteen stack heights. Again, we're seeing 

19 sensitivity on these lower stacks and the same 

20 pattern here as with the -- with the Oklahoma City 

21 data. 

22 So, okay, now, we ran it for the urban setting 

23 for Pittsburgh, again with the same fourteen (14) 

24 stack heights, and we're seeing the same pattern 

25 again. 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 98 

 2 So what did we learn from part two of the 

 3 sensitivity study? 

 4 Well, we've learned that surface roughness 

 5 definitely dominates an influence on the 

 6 concentration that -- that AERMOD output. The 

 7 influence is still there from the albedo and the 

 8 Bowen ratio. 

 9 So we will put these -- these results out in a 

10 report, but we know that we need to take these into 

11 account with any modifications that we make to 

12 AERSURFACE. 

13 So, future plans for AERSURFACE. 

14 It currently uses USGS land use data from the 

15 70s and 80s. 

16 We hope to update this so that it can use USGS 

17 NLCD 92 data. This data has a thirty-meter spatial 

18 resolution with -- it was performed by USGS in 

19 '92-'93, that's when the data were collected, and 

20 it has a twenty-one category land cover 

21 classification scheme. 

22 We'd like to modify AERSURFACE, so that it 

23 will take into account seasonal variations for the 

24 surface characteristics. 

25 We have definitely seen that that's important 
 1 AERSURFACE/Karen Wesson Vol. 1, p. 99 

 2 in our sensitivity study. We'd also like to do -- 

 3 we'd like to put some default values in, so we'd 

 4 like to give the user some options. 

 5 We'd like to allow the user to specify the 

 6 number of sectors that the circle will be parsed 

 7 into. 

 8 We'd like them to determine what radius they 

 9 would like to use in the circle over which the land 

10 data would be -- land use data would be averaged. 

11 For example, if you had a taller stack height, 

12 you would have a larger footprint, you might want a 

13 larger radius. 

14 A shorter stack height, smaller footprint, 

15 maybe you wouldn't want such a large radius. 

16 We'd also like to output data on a monthly, 

17 seasonal, and annual, and we'd also like to allow 

18 the user to determine whether the conditions were 

19 wet, dry or normal. 

20 This would have an influence on the Bowen 

21 ratio value that would be chosen. 

22 We've seen the distance importance. We'd like 

23 to give the user some choices here. 

24 And, of course, any other user option we 

25 welcome advice from the user community. 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 100 

 2 And that's it. 

 3 Thank you. 

 4 WARREN PETERS: Thank you, Karen. 

 5 So that concludes the AERMOD -- I'm sorry, no, 

 6 we have one more. 

 7 (Laughter.) 

 8 ALAN CIMORELLI: You're right; you're right. Excuse me, I'll 

 

 9 be back. 

10 (Laughter.) 

11 WARREN PETERS: I'd like to introduce you to my former 

12 friend, Al Cimorelli. 

13 (Laughter.) 

14 Now Al would like to talk to us about the 

15 AERMOD Implementation group and the exciting things 

16 that they're doing to us at this point. 

17 Let me invite Al to the podium. 

18 ALAN CIMORELLI: Let me first say, now that you have heard 

19 how well this model does, and we have spent a lot 

20 of quality time doing this, and the model actually 

21 is in very good shape, and we've seen, again, how 

22 well it performs, that we are in a position that we 

23 are just about ready to get this thing promulgated. 

24 And as a result of that, I was put under a 

25 tremendous amount of pressure which I resisted to 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 101 

 2 come up here with slide rule in hand, adorned with 

 3 my pocket protector and declare victory, (laughter) 

 4 but I resisted that. I truly did resist that, even 

 5 though we did adopt an old Government approach 

 6 which is called shock and awe. I think most of 

 7 you probably remember that, (laughter) and I think 

 8 we've been quite successful. 

 9 The community is, I think, pretty well shocked 

10 that it took fourteen (14) years for us to get this 

11 far, and I am very much awed that seven people who, 

12 the majority of which are profoundly ADHD, could 

13 focus for that long, (laughter) but in any event, I 

14 resisted that. I will not declare victory, because 

15 it's not enough to win the war; we need to win the 

16 peace. 

17 And I think winning the peace -- I think 

18 winning the peace is what I'm about to talk about. 

19 Once we have this model in place, and we will, 

20 okay, have this model in place, the next part of 

21 this is going to be to implement it. 

22 Well, you think developing it took long. This 

23 model is fundamentally different than ISC, and what 

24 my hope is is that we can convince all of you, all 

25 of the ISC insurgency that's out there that we can 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 102 

 2 bring you into our group. 

 3 So we have thought about implementation. 

 4 Implementation is -- obviously really what this is 

 5 -- a lot of this is about. We have to worry about 

 6 taking this model, using this model in a way that 

 7 is scientifically appropriate and that is 

 8 consistent, which in many ways, in many situations, 

 9 is almost counter-intuitive. 

10 I mean, there was -- there is a quote that I 

11 think most of you realize when we were back in, I 

12 guess, in 1978 when the first guidelines came out, 

13 they were opining arguments; one side sat there and 

14 said, you know, you realize that consistency is the 

15 hot knobs in the small minds. 

16 Well, without consistency, implementation 

17 would be nothing more than chaos. So we do have to 

18 find a balance between those things. And if you 

19 think about it, we have been lulled, I think, and 

20 permitted, over the years into thinking over the 

21 last, maybe ten (10) years, into thinking that it's 

22 all been solved. 

23 But let me take you back before I get into 

24 this, thank God, everybody finished early, because 

25 I take forever, but let me just take you back to 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 103 

 2 the time when Complex I, when -- when valid, when 

 3 ISC, when CTDMPLUS, when -- which was actually 

 4 -- CTDM when we had AQDM. This goes way, way back, 

 5 you know, take you back to the time when the 

 6 guidelines were developed at that point. 

 7 Well, there hasn't been a whole lot of 

 8 activity in issues, and the -- and the question is, 

 9 is why has that stopped? It's not stopped, because 

10 there is no activity out there. It's that I think 

11 our processes have worked. We have taken models, 

12 we have taken them out, people have applied them, 

13 we've developed issues. There was all kinds of 

14 activities going along. 

15 We had the communications inside the 

16 community, and we solved them and we solved them 

17 primarily through a function like the model 

18 clearing house. 

19 So as you get through that period, those of 

20 you who were there during the 80s, when we were 

21 arguing and arguing about standardizing random 

22 numbers and things of that nature, (laughter) sets 

23 of random numbers, though, which I thought was 

24 pretty interesting! 

25 You know, we got to the point where we solved 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 104 

 2 most of those issues, but don't sit back and think 

 3 that's because we have advanced to the point where 

 4 we have no implementation issues. 

 5 That was a function of the fact that we have 

 6 optimized ISC. We are now going to be embarking on 

 7 a brand new model. This model, it is fundamentally 

 8 different than ISC. It looks like ISC, but the 

 9 issues, the implementation issues are going to be 

10 very different. 

11 We've thought about that. We are not leaving 

12 the community out there hanging. In fact, we put 

13 together a work group, a work group that compos- -- 

14 that's composed of folks from EPA, and state and 

15 local agencies, who have spent a fair amount of 

16 time trying to think through how we were going to 

17 go about implementing this process. 

18 And if I can go to the first slide here. 

19 (Projecting slide.) 

20 What I'd like to do is to give you sort of an 

21 overview of a number of things. 

22 First, I want to talk about the approach that 

23 we're going to take to implementation, the concept 

24 of guidance development, and I'm going to 

25 differentiate between guidance development, and the 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 105 

 2 third one you see there which is the implementation 

 3 guide, and that's -- and there's an important 

 4 distinction there. 

 5 And then model improvements, and then finally 

 6 we'll talk about summaries. 

 7 (Projecting slide.) 

 8 Okay, AERMOD implementation process. Why do 

 9 we need it? 

10 The reason we need it is pretty 

11 straightforward. It's that as we implement this 

12 process, issues are going to arise, make no mistake 

13 about it, we are going to have a fair amount of 

14 issues, and so therefore we need some process by 

15 which to deal with these issues. 

16 Number one; ISC and AERMOD, and I think this 

17 is a fairly wise decision we have made sometime 

18 back that during the first year of promulgation, 

19 the community is going to be free to use either ISC 

20 or AERMOD to do their permitting. Okay? The 

21 agency -- local agencies and so on will accept a 

22 permit for a SIP that uses ISC or AERMOD. 

23 And I think of that really as a shakedown 

24 period, a period for us to start looking at some of 

25 what are the most difficult problems are, and see 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 106 

 2 if we can get our arms around it. 

 3 At the end of that year, ISC is going to go 

 4 away, and it's going to be AERMOD and AERMOD only. 

 5 So those of you who are familiar, I think you 

 6 should take Warren's advice and start 

 7 reading the documentation. You will fall asleep 

 8 after the first page, I'm sure, but, you know, you 

 9 may need some -- (laughter) -- with some advanced 

10 medication so you can get through to the third 

11 paragraph. 

12 Okay. Second, is that we are going to provide 

13 an implementation guide with the promulgation. 

14 There are issues that we were able to think of, we 

15 don't have a lot of experience with implementing 

16 AERMOD, but we have been able to think through a 

17 variety of issues that we are almost certain will 

18 be -- will be arising as -- as people start 

19 implementing this, and so we thought that it was 

20 prudent to put together a guide, which is not 

21 guidance, but is sort of our advice on how one 

22 should probably approach this, how one should deal 

23 with this. 

24 And I will go through and I'll tell you what 

25 topics that covers. 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 107 

 2 This guide his not dead; it should be a living 

 3 guide, as we gain information and experience that we 

 4 think is good advice to communicate and transfer to 

 5 people, we will -- we will improve that. 

 6 But, when -- when it's promulgated we will 

 7 have the guide. In fact the guide is now ready. 

 8 It is just a matter of getting it up on SCRAM. 

 9 So, you need to start applying this model to 

10 the issues that we can anticipate now are going to 

11 arise. And they will arise during the permitting 

12 process, so there will be enormous pressure on 

13 getting the answers quickly. 

14 So it's really incumbent upon us to have a 

15 process that will try to resolve those issues in a 

16 timely fashion. 

17 And the process that's been tried and true is 

18 the model in the clearing house. 

19 As Tyler has mentioned, Warren has mentioned, 

20 we are reinvigorating that process, recognizing 

21 that it wasn't needed since about '95 when we, 

22 quote, solved all the problems with ISC, but we are 

23 going to need it now. 

24 And just to refresh people's memory, that 

25 process is set up as a relatively formal process, 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 108 

 2 and that is that we have state contacts, local -- 

 3 local people, that is the -- the reviewing 

 4 authorities, an issue arises, they contact the 

 5 region, the region writes a memorandum to the 

 6 clearing house, the clearing house then that's sent 

 7 through whoever they have to; we're going to 

 8 construct an ad hoc work group to help support that 

 9 with -- with AERMOD experts. 

10 And hopefully, this will work pretty quickly 

11 so that we can then get an answer back to the 

12 reviewing authority and to the people who are 

13 trying to get that permit through. 

14 And we -- it won't end there. We are going to 

15 archive those memoranda as we have in the past; 

16 hopefully there will be annual reports. 

17 As we gain experience in running this model, I 

18 think it's then when the precedents get developed 

19 and consensus gets built in the community that we 

20 start building guidance, differentiated from "the 

21 guidance". 

22 Boy, that sounds like bureaucratic speech, but 

23 nonetheless. 

24 And then, finally, of course, we need to 

25 improve the model. 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 109 

 2 We are going to find issues that are not going 

 3 to be enough for a bunch of people who sit around a 

 4 room and say, oh, yeah, let's just do this. 

 5 There is going to be -- there is going to be 

 6 the need to do some type of model development. 

 7 And in fact, it really falls into two 

 8 categories; number one is that we've already, as we 

 9 went through the development process, put a list 

10 together, sort of a wish list of a variety of 

11 things that we need to do, and I'll go through a 

12 couple of those in a minute. 

13 But, as we start implementing, there are going 

14 to be others, and so we need to have in place the 

15 ability to improve the model, and that is far more 

16 than just sitting around the room writing policy 

17 memoranda. 

18 (Projecting slide.) 

19 The guidance development process, not needing 

20 advice and guide. What is the purpose? 

21 The purpose of all of this is really to 

22 facilitate the scientifically appropriate and 

23 consistent regulatory application of AERMOD. 

24 That's what Section 320 of the Clean Air Act 

25 demands. That's what -- that's what prompted the 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 110 

 2 PSD or the new source review; regulations demand 

 3 that we do; that's why we're here. 

 4 And so that guidance will take the form of a 

 5 variety of things. But before I talk about that, 

 6 let me talk about what I think are the important 

 7 tenets that I think should appear in that guidance. 

 8 Things that we have learned through the years, 

 9 and I think number one is is that it's really 

10 important that we keep this guidance principle 

11 based, so we can avoid prescriptive guidance 

12 wherever possible. 

13 It's real nice to have bright lines, but with 

14 a model like AERMOD, I think that that would be a 

15 recipe for disaster. 

16 We need to have principles that we understand, 

17 and that we have to then be able to -- to allow 

18 some flexibility for those unique cases. We also 

19 have to recognize that the first decisions that are 

20 made are going to set substantial precedence, so we 

21 want to be able to -- to try to avoid precedents 

22 that are established, that are done specifically to 

23 get a particular permit through, without thinking 

24 through what the long-term -- the long-term 

25 consequences of that are. 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 111 

 2 So I think it's real important for the Agency 

 3 to be able to say, as we initially start 

 4 implementing this model, we need to think long term 

 5 as to what these precedents might mean. 

 6 Because precedents probably have more standing 

 7 in Court than just about anything else. 

 8 Types of guidance, and so finally the thing to 

 9 do is, as I say, the last bullet under basic tenets 

10 here is that once we have a concept of what that 

11 guidance ought to be, we need to zip that through 

12 the appropriate community, and that includes all 

13 the stakeholders. 

14 We need to document it, and we need to rule 

15 make where that's appropriate. We don't want to 

16 rule make everything, because you see how long it 

17 takes to rule make things, but we want to rule make 

18 certain things that are going to be necessary. 

19 We have all of those available to us. 

20 How does that guidance take form? It takes 

21 form as Appendix W which is the most formal of all 

22 guidance, where we absolutely rule make. 

23 That's the -- that's the guidance where AERMOD 

24 is going to go to communities -- where we're going 

25 to go out in the Federal Register and say, "thou 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 112 

 2 shalt use AERMOD". 

 3 There are EPA reports. There are OAQPS policy 

 4 memoranda. There are clearing house memoranda. 

 5 And finally there are the individual 

 6 precedents that the lawyers in the group will go -- 

 7 run around to different regions in different states 

 8 and say, how did you do this, how did you do that, 

 9 how did you do the other, and then bring that to 

10 the table with the others. 

11 So we have to keep all that together. 

12 Okay, so that's sort of the guidance approach. 

13 The implementation guide. Let me talk a 

14 little specifically about the types of -- or 

15 problems that we have anticipated, because of the 

16 type of model that AERMOD is. 

17 Now you've heard from a number of the previous 

18 speakers that AERMOD is quite different from the 

19 point of view of how it deals with the planetary 

20 layer. 

21 It is most different from -- well, not most, 

22 but it's -- it's, I think, it parts company with 

23 ISC in a fundamental way in the -- from the 

24 perspective that it utilizes profiles of wind 

25 speed, temperature and turbulence. It actually 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 113 

 2 uses those profiles. 

 3 In order to get those profiles, you need to 

 4 get -- you need to have certain surface 

 5 characteristics, like Bowen ratio, albedo and 

 6 Z zero (Z0). 

 7 You heard Karen tell you -- show you what kind 

 8 of -- how the sensitivities exist out there. 

 9 That is going to present a fundamental change 

10 as to how we have to view representativeness. 

11 If you think about it, in the past, and I'm 

12 going -- I'm going to really simplify this, and if 

13 Rob Wilson were in the audience, he'd probably 

14 shoot me, but in the past when you thought of -- if 

15 you're in flat terrain and there's a national 

16 weather service station, it's representative. 

17 Cool. Let's run it. 

18 If you're in complex terrain, there is no such 

19 thing as a representative anything. You've got to 

20 collect on-site data. 

21 Well, that was kind of easy. It's not so easy 

22 anymore. 

23 In flat terrain, now, if you've got an 

24 application site where the surrounding area 

25 surfaces look very different than where the 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 114 

 2 meteorological towers are, you might have a problem 

 3 with representativeness, because it's -- the 

 4 surface characteristics, which are going to 

 5 describe how you partition energy between 

 6 turbulence and mean flow, about how you build these 

 7 profiles, so it's going to be fairly significant. 

 8 We need to now start thinking about 

 9 representativeness from the point of view of, is 

10 this data which we're collecting over here going to 

11 be able to produce realistic profiles where the 

12 sources are. 

13 So that's something, therefore, that we 

14 address that concept in the guidance. 

15 And then finally we have to think about how 

16 we're going to match meteorological data with -- 

17 with source location. 

18 As Karen has shown, I think very, very 

19 eloquently, that we've got three parameters, one of 

20 which is very low, the figure of zero, I have to 

21 think of these zeros as a partitioning function 

22 between turbulence and mean flow when you think of 

23 the energy coming in. 

24 And if you get that -- if it's different at 

25 the application site as opposed to where the 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 115 

 2 meteorology is being collected, then you are going 

 3 to -- the winds that you are going to get from that 

 4 site are going to be very different from what is 

 5 really happening at the -- at the meteorological 

 6 site is going to be very different from what's 

 7 happening at the actual application site. 

 8 So Z zero (Zo0) is very low, so you're going to 

 9 have to think hard about that. 

10 I you have low level application, Z zero (Zo) 

11 is going to be important, and you might -- you 

12 might have a national weather service site whose 

13 surrounding area is very different in terms of 

14 Z zero (Zo), and therefore you may need to collect 

15 on-site data possibly. 

16 With the Bowen ratio and with the albedo, it's 

17 really only for the upper level source -- sources 

18 that are highly buoyant or elevated. It's a much 

19 more regional type parameter. I think what the 

20 guide does is it addresses the fact that -- that 

21 there is a difference between these parameters and 

22 gives some advice about how to think about 

23 representativeness. 

24 Okay. The next is, this model, unlike ISC, 

25 when you're running in an urban mode, it requires 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 116 

 2 that you put a population in. Population is 

 3 nothing more than a -- actually a surrogate for the 

 4 energy that's generated in the heat of the day. 

 5 So, there are going to be issues like, well, 

 6 how much of the population? How big is the urban 

 7 area? What -- how do we deal with this? 

 8 Okay, so in that case we have also put in some 

 9 advice on how to go -- get around that. 

10 I think there is something that we will talk 

11 about later in this -- in this conference, a very 

12 important, I think, issue, and that's the issue of 

13 how do we use gridded data. 

14 I've had an experience where I've actually 

15 taken an output from WRF and ran AERMOD with it for 

16 an application. And all of a sudden I found that 

17 there was this enormous high concentrations for 

18 certain surface sources, and that's because WRF was 

19 producing extraordinarily low wind speeds, okay, 

20 and I was using an area source and, as I'll get to 

21 in a second, AERMOD for reasons of economy we were 

22 unable to put the meander function into area 

23 sources, so we got these huge concentrations that 

24 -- that came out of it. 

25 What I did realize, however, in looking at the 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 117 

 2 WRF output is that at nighttime you're actually 

 3 getting positive heat fluxes, and this is an urban 

 4 application, you were getting positive W stars and 

 5 so the question becomes, maybe we can just use an 

 6 urban version of them and apply it with WRF or 

 7 something and actually be able to characterize 

 8 the urban boundary layer and not have to utilize 

 9 something like population as a surrogate for it. 

10 That, to me, is a very exciting process. The 

11 AERMIC committee, when it was building this model, 

12 realized that that was going -- that the urban 

13 formulation that we had in here although -- 

14 although, it was shown to perform well against the 

15 one database that we had, we all knew that there 

16 was going to be a need to rework this and possibly 

17 reformulate it. 

18 So there's some -- some -- perhaps some 

19 request for guidance in there with regards to that. 

20 There's a -- there was a very specific topic 

21 with regard to down-sloping terrain. The issue 

22 was, if you've got a source sitting here and you 

23 have a receptor that's down-sloped from it, AERMOD, 

24 and let's say there is -- there's some gravity flow 

25 at night so that -- so that terrain really isn't 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 118 

 2 there, if you just run it with the terrain in 

 3 there, you're going to pretty much underestimate 

 4 the concentrations. 

 5 So in this guidance, we suggest that you've 

 6 got your application, that you run the model in 

 7 flat terrain models. 

 8 Capping horizontal stacks became a fairly 

 9 substantial issue. I won't go into what we've 

10 done, but we -- we have some guidance in here as to 

11 how to deal with that for both downwash and 

12 non-downwash situations. 

13 I will say it's not trivial -- it wasn't as 

14 trivial as it was for ISC, because the plume rise 

15 algorithms in PRIME, if you're in downwash 

16 situation, are numerical -- it's a numerical plume 

17 rise formula which utilizes the conservation of the 

18 conservation mass equations, and if you do things 

19 like coming up with an effective diameter and 

20 putting it in a real time rural velocity -- you 

21 know -- you're violating the conservation and mass 

22 equations and then the plume rise has a problem. 

23 So we have -- we have some ideas as to how to 

24 get around that sort of a WRF parameters. 

25 In terms of AERMAP, as you heard Pete Eckhoff 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 119 

 2 talk about, there is this concept of this ten (10) 

 3 degree slope. 

 4 Purpose for that was is that we'd originally 

 5 said, well, we'll take a domain about this size and 

 6 so -- and then you get the terrain data for the 

 7 large domain. If you increased it, you've got to 

 8 change -- change the actual prediction of 

 9 concentration. 

10 Well, we really couldn't have that, so we put 

11 in this concept of a ten (10) degree slope. Then 

12 someone raised the issue, well, what if you have a 

13 huge mountain that's out there thirty (30) 

14 kilometers away; is that really going to affect 

15 what's going to happen. 

16 So we put in here some -- some guiding words 

17 that say, you know, the ten (10) degree slope is 

18 something we want, but on a case-by-case basis, if 

19 you can show that that's inappropriate, you might, 

20 you know, we should be able to -- to accept the 

21 -- or ignoring a piece of terrain like that, if one 

22 can -- if one can show that it's like giving you 

23 the right -- the right of -- the right kind of 

24 dynamics, okay. 

25 Then there is mutually -- manually entering 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 120 

 2 terrain. 

 3 As AER- -- as AERMAP presently exists, you 

 4 have to have a DEM file. You have to have a DEM 

 5 file of your data, you have to have that put in. 

 6 If you can't get a DEM file for your area, 

 7 then some people can't, I think, it doesn't cover 

 8 everywhere. 

 9 If you have an old one sitting on-site, we 

10 have come up with a procedure of exactly how to -- 

11 how to cut and paste the information so that you 

12 can enter that in. 

13 It is the hope, of course, that we will change 

14 AERMAP in the future and prove it, so that people 

15 can put their own terrain data in. 

16 And then finally the area source algorithm, 

17 there's some guidance in there which talks about 

18 the issue if you have very, very light winds for 

19 area sources, you might grossly over estimate 

20 concentrations. 

21 I think this is only an issue if you are below 

22 instrument threshold for most of the instruments, 

23 and the only time that's going to happen, really, 

24 is when -- is when you're using these numerical 

25 models, I think. 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 121 

 2 Okay, that's the implementation guide. 

 3 (Projecting slide.) 

 4 Model improvements, and I'll go through this 

 5 pretty quickly. 

 6 In the near term, and this I think was 

 7 important to a lot of people. I can -- I think I 

 8 can stand up here and say that at promulgation or 

 9 very soon thereafter, AERSCREEN will be available, 

10 and I think more importantly to some is the idea of 

11 having this Bulk Richardson number approach as a 

12 surrogate for cloud cover. 

13 Now, why is that important? 

14 That's real important if you need on-site 

15 data, because the last thing in the world you're 

16 going to do is get an observer on site to get your 

17 cloud cover data. 

18 So that was recognized a long time ago, and we 

19 came up with this approach which would be a 

20 surrogate for it. 

21 Roger is going through an extensive -- pretty 

22 extensive evaluation which shows that the scheme 

23 that's been placed in AER- -- in AERMET now is 

24 doing quite well. 

25 Okay, so those two were extremely important to 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 122 

 2 people in immediate need, and I think that we've 

 3 satisfied that. 

 4 I'm going to -- I have now and in the rest of 

 5 this slide really talks about examples of other 

 6 improvements that we have contemplated, written 

 7 down, it's on our action notice, and this is only a 

 8 couple of possibilities. 

 9 Selection of surface characteristics, 

10 AERSCREEN. 

11 We have heard from Karen that that that's 

12 pretty -- pretty -- just about ready to go out. 

13 Horizontal and capped stacks. 

14 It is our hope that we will come up with a far 

15 better objective approach to dealing with that. 

16 Reformulate air -- urban -- we've talked about 

17 that. 

18 Code authorization. As Warren talked about, 

19 this thing can run pretty long. And especially, I 

20 mean, I did it -- I was recently? Recently, well, 

21 over the last four years, I guess, I have been 

22 doing the Philadelphia toxic study, and at the 

23 beginning of it, I said, well, I should use AERMOD, 

24 and I realized that I was going to be modeling a 

25 hundred thousand (100,000) sources, and I can't run 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 123 

 2 AERMOD. We'll all be dead by the time the thing 

 3 finishes, (laughter) so optimization -- either that 

 4 or by the formaldehyde that's in Philadelphia; one 

 5 of the two is going to kill me. 

 6 And so code optimization is really important, 

 7 and I think Warren has already touched on that. 

 8 Use of gridded met data. I think we've 

 9 touched on that. Everything is in place right now. 

10 The money has been allocated to explore that, and I 

11 think we're going to be talking about that a little 

12 later. 

13 Meander for area sources, I talked about. 

14 PM two point five (PM2.5). You heard John 

15 Bachmann talk about PM. I mean, I feel -- you know 

16 -- I feel like a poor country cousin when I come to 

17 many of these meetings anymore when I hear 

18 everybody talking about regional scale models, 

19 regional scale models, regional scale models. 

20 And I'm sitting here thinking to myself, PM is 

21 what we looking for. They tell me Karen is taking 

22 care of all that stuff, so what's left?, and what's 

23 left is the urban excess and the urban excess is 

24 local. 

25 And you're not -- you're not going run -- 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 124 

 2 you're not going to run CMAQ to deal with those 

 3 type of -- of impacts. 

 4 So, whether they know it or, they're coming to 

 5 AERMOD. They're going to come to the local scale 

 6 modeling people, and so we're going to have to 

 7 worry about that. 

 8 And in that regard, right now, AERMOD does not 

 9 print out information or does not output 

10 information in the form of PM two point five (PM. 2.5) 

11 standard, and so that is something that -- excuse 

12 me, I think we'll be doing soon. You need the 

13 ninety-eight percentile concentration. 

14 There is this concept that when we went 

15 through the peer review process, years ago now, 

16 Gary Briggs raised an issue with regards to H sub c 

17 which is the terrain scaling height, which is used 

18 in AERMOD to -- to weight the two clones, that are 

19 being modeled, and Gary suggested that when, you 

20 know, depending on what the wind direction is, 

21 you're going to see a very different type of -- a 

22 very different type of terrain features. 

23 And he suggested that maybe we should have a 

24 wind dependent -- wind dependency for H sub c. So 

25 that's on our list, whether we ever do it, no one 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 125 

 2 knows, but it's there. 

 3 The other ones -- the other ones are 

 4 additional source types, like blind sources, 

 5 buoyant blind source. 

 6 I mean that's an issue that -- that has come 

 7 up three times already, and we haven't even started 

 8 implementing this. You know, people are looking 

 9 at, you know, long roof monitors that are buoyant, 

10 can we use AERMOD for that? And so those are 

11 there, and then, also, flares. 

12 And then finally, I just threw in this, I 

13 don't know how important this is anymore, given the 

14 sensitivity of Bowen ratio, and that is that, you 

15 know, we get Bowen ratio now into AERMOD purely by 

16 look-up tables or what-have-you, and we certainly 

17 can improve that if we treated soil moisture in 

18 some sense, where we could bring precipitation in. 

19 When was the last time we had precipitation 

20 and -- and tried to deal with the Bowen ratio that 

21 was more temporally varied. 

22 And in summary, let me simply say that 

23 implementation issues are expected. We should 

24 expect that there will be implementation issues. 

25 We need to implement in a manner that is going 
 1 AERMOD IMPLEMENTATION/Al Cimorelli Vol. 1, p. 126 

 2 to facilitate consistency in permitting and SIP 

 3 development. 

 4 We need to do that, and we all need to work 

 5 together to do that. 

 6 And the implementation process that we put in 

 7 place is one, ISC or AERMOD, can be used in the 

 8 first year as a shakedown, too. 

 9 We've been -- we were hopefully going to be 

10 providing advice for presently understood issues; 

11 that is, the implementation guide. 

12 We're going to try -- we put in place a system 

13 we hope that will deal with specific issues that 

14 come in -- come up within cases in a timely matter. 

15 We all recognize how important that is. 

16 We are going to communicate those issues 

17 through the clearing house memos. 

18 We'll develop formal guidance as experience is 

19 gained. 

20 You can't develop guidance, put it out there, 

21 until you've really had a sense of how good or bad, 

22 you know, what kind -- what kind of problems you're 

23 going to experience with this model. 

24 We definitely need to have flexibility. This 

25 model is too complex. It's not like -- it's not 
 1 Questions/Audience Vol. 1, p. 127 

 2 like ISC. 

 3 And finally, we're going to improve AERMOD, 

 4 but, of course, that's a function of dollars. And 

 5 I think we will get more dollars the sooner that 

 6 the establishment realizes that it just isn't a 

 7 regional scale gain. 

 8 And with that I'll leave. 

 9 WARREN PETERS: Thank you, Al. 

10 ALAN CIMORELLI: Unh-hunh. 

11 WARREN PETERS: As I said before, that concludes the AERMOD 

 

12 presentation (laughter). 

13 Now maybe we'll move on to economics. 

14 So at this point we have about another fifteen 

15 (15) minutes before noontime, which is when we're 

16 scheduled to break for lunch. I'd like to open it 

17 up to the audience for questions, but before we do 

18 that, I'd request -- we probably could make this a 

19 little bit easier for the stenographer -- I'd like 

20 to ask Desmond and Karen to sit at the table over 

21 here, and Peter. 

22 Sit in front of the mics. 

23 And what I'm going to ask you to do is, as you 

24 ask a question, if you would please identify 

25 yourself for the record, and then I'll ask the 
 1 Questions/Audience Vol. 1, p. 128 

 2 panel members, as you respond to questions, to 

 3 identify yourself, as well, and then make a 

 4 response. 

 5 And now, Al, I guess you and I can maybe share 

 6 the mic up front, please. 

 7 Are there any questions from the audience? 

 8 And Dennis here has a traveling mic. 

 9 Is that George? 

10 GEORGE SCHEWE: I would say there is thousands of questions 

11 out here. 

12 George Schewe, Alpine Geophysics. 

13 A few questions on AERSCREEN, Warren, so I 

14 guess you're up to bat first. 

15 Observation, still in DOS. 

16 Second question, scalable rates that you were 

17 talking about for taking ratios between one-hour, 

18 twenty-four-hour, annual. 

19 In the current system, I believe there's some 

20 rates or ratios that are applicable to flat 

21 terrain, complex terrain. 

22 You did not mention whether there's going to 

23 be any variability for those two different types of 

24 surfaces, or is there just going to be one set of 

25 those in there? 
 1 Questions/Audience Vol. 1, p. 129 

 2 WARREN PETERS: There will be two sets of scaling ratios for 

 3 complex versus simple terrain. 

 4 GEORGE SCHEWE: Okay. Okay. I'm trying to read my own 

 5 writing here. 

 6 I noticed a mixed set of units going into the 

 7 model as you were presenting your screen views, it 

 8 was all English on the first screen. The second 

 9 screen looked like it was all metric, and then at 

10 the end you had both. 

11 What -- what's the deal there? 

12 WARREN PETERS: Warren Peters, again. A mistake because of 

13 Jim Haywood's slides. What you do is, the first 

14 question as you may recall on that screen was, what 

15 units are you going to be dealing with? 

16 That's the first question, and you select 

17 either, you know, the American or the metric units. 

18 And then once you do that, then everything comes 

19 up, and you have to input the appropriate units 

20 emissions dates, so if -- if you pick metric from 

21 day one, you've got to go through and enter all the 

22 metric input data. 

23 GEORGE SCHEWE: Okay. And then the last question on 

24 receptors. I didn't see any receptor inputs except 

25 for that ambient boundary you were talking about. 
 1 Questions/Audience Vol. 1, p. 130 

 2 So, as a user, can I not generate a gradient 

 3 of concentrations, or do I get one value at the WRF 

 4 case, and then potentially one value in a so-called 

 5 fence line? 

 6 WARREN PETERS: Warren Peters, again. I believe right now, 

 7 the only AERSCREEN output is for one -- well, two 

 8 concentrations, the highest concentration, 

 9 regardless of the distance downwind; the second one 

10 was at the fence line, or the ambient boundary. 

11 But AERSCREEN does have other concentrations 

12 in there, and actually one point in an earlier 

13 version of the model, we actually had a table which 

14 listed concentrations at different distances, so 

15 maybe we could take this as a suggestion for an 

16 improvement to AERSCREEN is to have a user 

17 generated table for generating estimates for 

18 different directions or different distances 

19 downwind, and that would make it more useful, 

20 perhaps, for the user. 

21 I understand the point, and we'll have a 

22 record of that and we'll consider that. It should 

23 be relatively easy to do. 

24 GALE HOFFNAGLE: Gale Hoffnagle from TRC. 

25 Do you expect that the issue -- and this is 
 1 Questions/Audience Vol. 1, p. 131 

 2 basically directed at Al -- do you expect that the 

 3 issue of the representativeness of the location of 

 4 the source versus the location of the meteorology, 

 5 will force us, as a community, or you as EPA, to 

 6 require more meteorological data collection? 

 7 ALAN CIMORELLI: My opinion is, no, It will not. I do not 

 8 think that that will be the case, and I guess the 

 9 reason I say that is that at present, in the old 

10 system it was -- it was easy, you're in complex 

11 terrain, you're collecting on-site data; you in 

12 flat terrain you're not collecting on-site data. 

13 That will not be a distinction any longer. 

14 Now the distinction is going to be whether or not 

15 you can take the data that you have in the National 

16 Weather Service, and is it going to be able to 

17 produce, not just, not just rational or realistic 

18 profiles, but is your application going to be 

19 sensitive to the differences? 

20 So one of the things that's in the guide that 

21 we suggest is, you first look and ask is it 

22 representative? 

23 Are you getting the right profiles? 

24 The next question I think you need to ask is, 

25 even if you are not, even if you think that they're 
 1 Questions/Audience Vol. 1, p. 132 

 2 different, the question is is how significant is 

 3 it? 

 4 So you might want to do a sensitivity study. 

 5 If you've got an elevated source, that's, well, you 

 6 know, moderately elevated source, a fifty (50) 

 7 meter high source, and there -- you know there are 

 8 differences in Z zero (Zo), and you hear, oh, my 

 9 god, I've got a difference in Z zero (Zo) so 

10 therefore I've got to collect on-site data. 

11 The suggestion in the guide is to say, well, 

12 check it out, see if the difference in Z zero (Zo) 

13 that's occurring between two locations makes much 

14 of the difference in the design concentration for 

15 your particular application, and if it doesn't, 

16 then that may be adequately representative data 

17 for defining those things. My belief is that 

18 because the Bowen ratio and the -- and the 

19 albedo are really more regional type parameters, 

20 you're not going to really have to worry as much 

21 about that. 

22 What you're really going to have to worry far 

23 more is for the low-level sources. And if you've 

24 got low-level sources, and you've gotten your 

25 near-field impacts, and you want to use wind -- if 
 1 Questions/Audience Vol. 1, p. 133 

 2 you want to use National Weather Service data that 

 3 -- that is on the edge of Lake Michigan and you're 

 4 inside their cornfield, you shouldn't be using that 

 5 data. 

 6 And so under that circumstance, you really 

 7 should be collecting on-site data, and so I think 

 8 that -- I don't think that there are as many 

 9 applications where you're going to necessarily be 

10 forced to collect on-site data. 

11 That's point one. 

12 Point two is, I think we will be moving 

13 towards gridded met data, and when we do move 

14 towards gridded met data, we will be having fields 

15 of surface data. We have all the landscape 

16 information. 

17 We're using output from MM5 or WRF, or 

18 what-have-you. That will become a completely moot 

19 issue. So as we move towards utilizing that data, 

20 this becomes less important, and I think the -- I 

21 think because of the way AERMOD tries to construct 

22 an appropriate boundary layer, you are going to be 

23 -- I think the community is going to be asked to 

24 collect on-site data really where it's most 

25 important, where before there were situations where 
 1 Questions/Audience Vol. 1, p. 134 

 2 people we for- -- may be forced to collect it where 

 3 it was simply because of a black and white rule 

 4 that was set out there. 

 5 JOHN GIBBONS: John Gibbons with Bunge North 

 6 America. 

 7 Question is for Warren. 

 8 In your presentation, slides eleven (11), 

 9 twelve (12), and thirteen (13), I just wanted to 

10 clarify something. 

11 In a consequence analysis, it sounded like you 

12 said two different things; one was you were glad 

13 that there's an agreement between AERMOD and 

14 ISC-PRIME and ISC, that the ratios are near one. 

15 Then in another statement I heard you say that 

16 AERMOD we're glad is out performing ISC. 

17 And I wanted to know what's the difference and 

18 can you clarify that for me? 

19 WARREN PETERS: Okay, could you repeat that question again 

20 one more time for me? 

21 JOHN GIBBONS: You want me to repeat that question? 

22 WARREN PETERS: Yes, please. 

23 JOHN GIBBONS: I don't know if I can do that. 

24 WARREN PETERS: You had two issues; one was -- 

25 JOHN GIBBONS: (Interposing) Well, the question is between 
 1 Questions/Audience Vol. 1, p. 135 

 2 -- as far as the agreement between AERMOD and ISC, 

 3 I'm just trying to figure out -- you said the goal 

 4 was 

 5 WARREN PETERS: (Interposing) Oh, -- 

 6 JOHN GIBBONS: -- For there to be good agreement, but at the 

 7 same time, in a couple of cases, it's outperformed. 

 8 I just wanted to know, you know, what are we 

 9 striving for here? 

10 WARREN PETERS: Right. When we put PRIME into AERMOD, 

11 remember I made a comment that the goal was to have 

12 the performance, no, no, I'm sorry, the predicted 

13 concentrations from AERMOD PRIME versus ISC-PRIME 

14 behave the same in the cavity and in the downwash 

15 areas. 

16 That would be a successful implementation 

17 of PRIME into AERMOD, because it's almost 

18 independent of the other characteristics that 

19 AERMOD and ISC would have in the way it calculates 

20 dispersion. 

21 So that was our goal, to have those numbers 

22 match up. And they do match up quite well, but 

23 remember on this table here -- they don't match up 

24 exactly. 

25 There are still some slight differences, but 
 1 Questions/Audience Vol. 1, p. 136 

 2 when we went back to the evaluation performance, in 

 3 comparing AERMOD-PRIME to ISC-PRIME, AERMOD out- -- 

 4 slightly out performed ISC-PRIME, which was a 

 5 pleasant but unexpected event. 

 6 Does that clarify that? We expected it to be 

 7 about the same; they weren't exactly the same, they 

 8 were very close, so we were pleased about that, but 

 9 we actually experienced improvements in the 

10 evaluation as well, slight improvements. 

11 CAL ARZOLLI: Cal Arzolli from TRC. My question is related 

12 to the sensitivity analysis work done for the 

13 surface parameters. 

14 Was it obvious whether the variability in the 

15 parameters influenced a particular parameter in the 

16 model at wind speed, or was it not so obvious that 

17 any particular parameters would be in effect? 

18 KAREN WESSON: Yeah, we didn't analyze exactly what parameter 

19 was affected in the model itself. 

20 We just looked at the concentration output, 

21 but one thing I'd like to look at would be what 

22 time of day and whether or not -- when the 

23 concentration -- the high concentration picked up, 

24 I think that would tell us as far as what parameter 

25 would be affected, what cases we're seeing, where 
 1 Questions/Audience Vol. 1, p. 137 

 2 the high concentrations would be at the output? 

 3 WARREN PETERS: That was Karen Wesson. 

 4 Another question? 

 5 CAL ARZOLLI: So is it possible -- 

 6 WARREN PETERS: I'm sorry. Come to the mic, please. 

 7 CAL ARZOLLI: Cal Arzolli, again, TRC. 

 8 Is it possible then maybe surface roughness is 

 9 just affecting the wind speed, and that's what's 

10 causing the very variable results for the low -- 

11 low-level sources versus the high-level sources? 

12 KAREN WESSON: Yeah, that -- that -- I -- that would be my 

13 thought. The other thing is that even the surface 

14 roughness goes into AERMET. 

15 Surface roughness is also used in AERMOD to 

16 partition the wind speed. 

17 So you see -- it's directly used the model, 

18 AERMOD, so you -- you would expect to see a little 

19 bit more effects from it. 

20 WARREN PETERS: Next. 

21 BRUCE EGAN: I'm sorry. I'm Bruce Egan from Egan 

22 Environmental, Massachusetts. 

23 I have a question that relates to all the 

24 wonderful data you folks have produced on 

25 evaluation and performance of the models. 
 1 Questions/Audience Vol. 1, p. 138 

 2 And I think we're in a very different 

 3 situation with the AERMOD than we were in the early 

 4 days of ISC in terms of being able to extrapolate 

 5 that to what we might call uncertainty in our 

 6 predictions. 

 7 And I realize this is an old chestnut, or a 

 8 problem, for EPA to put air guards on the 

 9 predictions, but it is a real issue for litigation 

10 cases where we're dealing with hazardous was- -- 

11 hazardous substances and toxic releases and -- and 

12 so forth. 

13 Lawyers always are asking, well, you know, 

14 what's your error power, or put in some other terms 

15 of uncertainty or not. And I wonder if you have 

16 any intention of translating the evaluation data, 

17 seems like it's fairly simple to go, but it's 

18 complex because you've got many ways of showing it. 

19 You think of producing something in the realm 

20 of guidance for users like ourselves that would 

21 allow us to address uncertainty in our predictions. 

22 WARREN PETERS: All right, this is Warren Peters, again. 

23 Roger Brode and I were talking about that very 

24 issue, and I believe a number of those calculations 

25 and charts have actually been made, but they were 
 1 Questions/Audience Vol. 1, p. 139 

 2 not included in the model evaluation paper -- 

 3 report that we put together, due to space, pretty 

 4 much. 

 5 But that information could be made available 

 6 and the -- added to the -- either the evaluation 

 7 document or just something else that you would see 

 8 those results. 

 9 But I understand the issue of putting 

10 AER s together and actually doing a true 

11 statistical comparison between ISC and AERMOD and 

12 understanding the overlap of the uncertain range. 

13 CAL ARZOLLI: Thank you. 

14 TYLER FOX: This is Tyler Fox. 

15 The Air Quality Management report that came 

16 out that John Bachmann talked about actually 

17 exclusively mentioned the uncertainty in both 

18 emissions inventories and air quality modeling as 

19 something that we should look into. 

20 There is a study that was done in Houston that 

21 tried to look at emissions, meteorology and 

22 modeling from an uncertainty standpoint, and Joe 

23 Touma did that. We could -- you know -- make 

24 people aware of that, but that's a start in the 

25 beginning, you know, obviously, it is a complex 
 1 Questions/Audience Vol. 1, p. 140 

 2 system to -- to unwind in terms of uncertainty. 

 3 So we just need to be careful and thoughtful 

 4 in how we -- how we address that. 

 5 RICHARD SCHULZE: This is Dick Schulze for Trinity 

 6 Consultants. 

 7 This is for Karen over here. And I was 

 8 wondering, since most modeling is performed on the 

 9 Cartesian grade, is there any consideration to 

10 developing land use patterns on a Cartesian system, 

11 because it seems that you only have a polar system 

12 for that. 

13 KAREN WESSON: The polar system being used in the actual 

14 AERMOD model, is that --? 

15 RICHARD SCHULZE: Yes, in the AERSURFACE -- 

16 KAREN WESSON: Oh, I see. You're talking about because of 

17 the way that the circle is drawn rather than a 

18 polar coordinate, is that --? 

19 RICHARD SCHULZE: Yes, if land use -- if you -- if you were 

20 using circles and sectors, and that's, you know, a 

21 polar-type system -- 

22 KAREN WESSON: (Interposing) Okay, whereas, of course, land 

23 use data provided by USGS is provided in a 

24 Cartesian -- 

25 RICHARD SCHULZE: Right. 
 1 Questions/Audience Vol. 1, p. 141 

 2 KAREN WESSON: (Interposing) That's something to consider, I 

 3 suppose. 

 4 The model that was originally developed, the 

 5 AERSURFACE model -- the AERSURFACE model, did use a 

 6 circle rather than looking at it on a -- drawing a 

 7 square around your center of location. 

 8 But we haven't gotten into modifying that. 

 9 Maybe that's something that we should consider. 

10 RICHARD SCHULZE: All right, and the second question is for 

11 Al Cimorelli, and that is a comment, you know, some 

12 of the future issues that might, you know, you 

13 might consider, like the modeling of tank farms 

14 where you have emissions, and downwash, and a large 

15 number of tanks. 

16 And the other one would be the handling of 

17 aggregates and whether it's sand or gravel or 

18 cement industry or the lime industry or the mining 

19 industry, you know, trucks on haul roads, the dump 

20 stations, and screens and this sort of thing, and 

21 there is, you know, a sort of an absence of GOOD 

22 guidance as how to model these type of things. 

23 ALAN CIMORELLI: Okay. That's a good comment. 

24 JOHN IRWIN: John Irwin. I don't know what I represent, 

25 maybe, myself (laughter). 
 1 Questions/Audience Vol. 1, p. 142 

 2 To respond to Dick Schulze's question, I don't 

 3 think you want to go to a Cartesian co ordinate 

 4 system. 

 5 A plume model assumes that you have horizontal 

 6 homogeneity. That's the basic assumption. 

 7 So it's the trajectory of the winds coming 

 8 down towards the source that's set up the 

 9 meteorology, and the model, by its very basic 

10 assumptions that it's a plume model, doesn't have 

11 the ability to react to a checkerboard situation of 

12 changes in Z naught (Zo) and Bowen ratio. 

13 A puff model could do that, but it's 

14 philosophic -- be inappropriate to think about 

15 plume model being able to deal with a checkerboard. 

16 So, I don't think it would be a good idea to 

17 think in those terms for AERMOD. 

18 It would be a great idea to think of with 

19 CALPUFF. 

20 The other thing I was going to suggest to 

21 Karen, with regards to a sensitivity study, most of 

22 the people who are going to be doing a sensitivity 

23 study already have a pretty good idea of a ballpark 

24 value for the Bowen ratio, Z naught (Zo) and 

25 albedo. 
 1 Questions/Audience Vol. 1, p. 143 

 2 The question is not, am I going to -- am I 

 3 over water, or over- -- or am I in the urban 

 4 area? 

 5 I think the question is I think the roughness 

 6 length is around thirty (30) centimeters. Does it 

 7 really matter if it's sixty (60) or fifteen (15)? 

 8 So, we're already in the ballpark of value. I 

 9 would suggest that you rearrange your sensitivity 

10 study where you pick a central value, and then 

11 increase it or decrease it by some factor, and see 

12 how it changes the results. 

13 And then what you'll do is you will actually 

14 come up with a guidance for the user community as 

15 to how much of a ballpark, or how prescriptive they 

16 have to think about the problem in coming up with a 

17 value. 

18 And I think then what you'll see is that -- if 

19 you're anywhere close in your estimate of the Z 

20 naught (Zo) value, you're fine, probably within a 

21 factor of two. You're great, but you see in your 

22 results you buried it over a factor of ten (10) or 

23 more, so I think if you just get in the right 

24 ballpark you will find that changing Z naught (Zo) 

25 by a factor of two plus or minus, isn't going to 
 1 Questions/Audience Vol. 1, p. 144 

 2 make much difference in the results. 

 3 And I think that will also allay a lot of 

 4 fears in the user community as to how much effort 

 5 and work they have to do to put these values into 

 6 the model. 

 7 KAREN WESSON: And -- and I just want to -- I apologize; 

 8 actually that's exactly what we did do, and the 

 9 value that -- the research that we presented in New 

10 Orleans actually was presented along those bases of 

11 achieving a medium value and by going to the 

12 extreme. 

13 So, in the report, we'll try to angle it 

14 towards that. But they were actually large 

15 variations, even going from the medium level. 

16 JOHN IRWIN: Did you -- 

17 WARREN PETERS: (Interposing) I'm probably going to have 

18 time for one more question. 

19 As you can hear, we have the Mexican hat dance 

20 going on -- 

21 (Laughter and comments off record.) 

22 WARREN PETERS: It's a planned event that's going to go on 

23 from about noontime to one o'clock (1:00), and 

24 we're going to cooperate by breaking for lunch. 

25 But one more question, I guess, and then 
 1 Questions/Audience Vol. 1, p. 145 

 2 we'll break. 

 3 DENNIS McNALLY: Dennis McNally from Alpine Physics. 

 4 And I enjoyed your presentation, Karen. 

 5 I'm wondering if the sensitivity to Z naught 

 6 (Zo) isn't more of a suggestion of maybe a model 

 7 formulation issue than an implementation issue. 

 8 My concern with that is, if we -- if you think 

 9 about defining it as a radial, you're, of course, 

10 as you go through their wake, you're going by the 

11 square of the distance again. 

12 But we're finding that it's sensitive in the 

13 near-field, the low stacks. My concern is that 

14 when it comes time to -- you know -- do an 

15 application or review an application, what the user 

16 picked as that distance over which you're averaging 

17 is going to have a big impact and is going to end 

18 up being a, pardon the expression, will be a 

19 non-closed form solution. 

20 It will be sensitive to what that distance 

21 closed in. (Cough.) 

22 I'm wondering if a better solution might be to 

23 go to a gridded field. Now, I understand, as John 

24 pointed out, the homogeneity, except it can then be 

25 homogeneous between the source -- to the apt 
 1 Questions/Audience Vol. 1, p. 146 

 2 receptor, and from that source to another receptor, 

 3 it's still -- it's just averaged over the factor; 

 4 or to at least have in the radials have distances 

 5 over which you make that assumption. 

 6 Because my concern is that when it comes time 

 7 to do a -- do the studies, what's ending up 

 8 happening is you're going to have to find out where 

 9 your -- your maximum impact is and then do an 

10 application with that sort of a distance. 

11 And then another receptor with a different 

12 distance, and it's going to become intractable 

13 pretty quick. 

14 WARREN PETERS: All right. Thank you for that comment. 

15 A couple of other procedural matters; we will 

16 put up these presentations just as fast as we can 

17 on our SCRAM web pages, so you can go back and 

18 download these things; don't have to worry about 

19 carrying all this material back with you. 

20 So that will be a help. 

21 Also, there is a thirty-day comment period as 

22 you may recall from the Federal Register Notice 

23 that goes beyond the meeting today. 

24 So, if you have further thoughts or ideas 

25 after you leave the conference, there still will be 
 1 Questions/Audience Vol. 1, p. 147 

 2 time for you to submit something to us in writing. 

 3 We have a formal docket. It will all be 

 4 entered into the docket, and we'll try and put some 

 5 of that information, comments and so forth, up on 

 6 the web pages, as well, especially significant 

 7 ideas. 

 8 So we have a couple of tools in there to help 

 9 you stay informed on what we're planning to do as 

10 reaction to this meeting. 

11 _______________________________ 

12 (ANNOUNCEMENTS.) 

13 _______________________________ 

14 (LUNCH RECESS,12:07 - 1:03 P.M.) 

15 _______________________________ 

16 WARREN PETERS: We'd like to open up the afternoon session. 

17 This morning we covered CALPUFF -- CALPUFF, right!, 

18 AERMOD. We had a full set OF AERMOD 

19 presentations. 

20 This afternoon, we're going to be looking at 

21 CALPUFF, and we have a number of topics; basically, 

22 for an overall presentation. 

23 I'd like to introduce to you Mark Evangelista 

24 who is the branch chief for the NOAA part that 

25 supports us in the Air Quality Modeling Group. 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 148 

 2 Mark will be the session chairman for the 

 3 first part of our CALPUFF presentations this 

 4 afternoon. 

 5 So, Mark, please lead us in the discussions we 

 6 have for our favorite model. 

 7 (Chuckles.) 

 8 MARK EVANGELISTA: Hi! How are y'all doing here? 

 

 9 I hope you can all hear me back there, and as 

10 Warren said I'm the Chief the NOAA quality modeling 

11 branch, formerly known as the Air Policy Support 

12 Branch, now quality modeling from the NOAA Air 

13 Resources Laboratory, and I am here as part of 

14 EPA's Emissions Monitoring Analysis Division to -- 

15 to talk with you today, at least for the first part 

16 of the afternoon about CALPUFF. 

17 But before we go into that, I just want to let 

18 you know that there's probably not a single, 

19 solitary new thing you're going to find out about 

20 CALPUFF coming from me to you. 

21 We are by no means the repository of the 

22 expertise on this model at this point in time. 

23 That lies out here in this room somewhere, or 

24 perhaps in folks who couldn't -- couldn't be with 

25 us today. 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 149 

 2 And what we are trying to do now is gather 

 3 that expertise, gather the experience, and fold 

 4 together and come up with the state of where this 

 5 model is, the state of where our experiences with 

 6 it are, and the state of what our next couple of 

 7 applications are going to look like down the road. 

 8 For those of you who have been involved with 

 9 BART, you know fairly well by now that we're kind 

10 of right on the edge of our comfort zone with -- 

11 with our expertise and our previous experiences 

12 with CALPUFF, and we're going on to new territory, 

13 at least for some. 

14 I would like to make one acknowledgement 

15 before I go on further, and that is when I say that 

16 we have, we are no longer the repository of great 

17 CALPUFF expertise that's because we had a 

18 retirement last year of one John Irwin over there 

19 to my right and to your left and with him went most 

20 of our CALPUFF expertise and a lot of the 

21 experiences and the general curiosity to go look 

22 and find out what's going on here, and what's going 

23 on there and learning just what this model is all 

24 about and what are applications and how they can 

25 benefit from them. 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 150 

 2 So what I want to do this morn- -- or this 

 3 afternoon is start off with a little backup and 

 4 look at where the last real footed foundation was 

 5 that we had with regard to CALPUFF, and that would 

 6 be the second IWAQM, the IWAQM phase two (IWAQM 

 7 II), recommendations that went out, and since then 

 8 we sort of built on this foundation here or there, 

 9 but not really gone back and rooted, once again, 

10 and firmed up the foundation as to how we're going 

11 to handle the technical recommendations for the use 

12 of this model. 

13 At any time during this, if you find I have 

14 something up here or something I say that is not as 

15 you perceive it to be, or not as it really is, in 

16 CALPUFF world, by all means, set the record 

17 straight right then and there. 

18 I am, by no way, an expert in this model. I 

19 am more of a coordinator, and gatherer of the key 

20 players. 

21 So, I don't want to perpetuate anything for 

22 five seconds that is not -- not exactly as is. 

23 So let's take a look at what we've got here, 

24 first of all. 

25 (Projecting slide.) 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 151 

 2 CALPUFF. 

 3 I'll move a little bit to the side here, if 

 4 you don't mind. 

 5 CALPUFF, the updates, applications, 

 6 recommendations, you'll see that there's one word 

 7 missing there, and that is guidance and we're not 

 8 going to talk about it in those terms. I wanted to 

 9 talk about it more in terms of recommendations and 

10 experiences at this point, and just see what we've 

11 got in terms of where the model is compared to 

12 where it was when IWAQM was finalized being the 

13 second one, and where we are headed from here on 

14 out. 

15 Right now we've convened a loose work group, 

16 we're going to call it CALPUFF work group, and it 

17 is some of the folks who had experience before, in 

18 the original IWAQM work group, folks who clearly 

19 are stakeholders, shall we say, or affected 

20 parties in what may come out of any recommendations 

21 for CALPUFF, and hopefully, some of the more 

22 experienced and knowledgeable folks with regard to 

23 CALPUFF. 

24 This is by no means an all-inclusive list. We 

25 will be reaching out to other individuals, 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 152 

 2 hopefully, some of you will rise up out of this 

 3 meeting today, and ask to be part of this -- this 

 4 activity. 

 5 The focus of this group is to take a good hard 

 6 look at where we are, technically, what's 

 7 available, what should be evaluated, what should be 

 8 tested, what should be recommended, and -- and get 

 9 the entire state of CALPUFF applications and just 

10 get our footing back once more. 

11 The tasks more specifically laid out are 

12 identifying the key technical issues. 

13 Now, you'll see in parentheses there a very 

14 preliminary schedule for trying to accomplish these 

15 things. 

16 When we're all finished, we'll put this 

17 schedule back up again and see if it -- if it makes 

18 sense, or if certain things need to be expanded. 

19 But identifying the technical issues, the 

20 first step, has a fairly short time line, and 

21 that's what we've been doing with this group in our 

22 first conference call communications is just going 

23 out and probing to say what are the things out 

24 there that we should be taking a look at? 

25 Are they recommendations for a setting, a 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 153 

 2 parameter, or are they parts of the model that 

 3 should be looked at once again? 

 4 Are they components, are they processors or 

 5 are they just application decisions? 

 6 The recommendations, if we can, and I say set 

 7 recommendations if possible. 

 8 If something is a parameter, it might be very 

 9 easy for us to evalu- -- or examine where those 

10 parameter settings lie and then what changes there 

11 might be available, and then recommend it. If not, 

12 we would have to set up investigations and look 

13 into model runs, sensitivities, evaluations, 

14 studies. 

15 We need to find out a priority list of what we 

16 want to examine and how we would have to go about 

17 examining some of these. And as I said, some may 

18 be fairly easy to achieve, and some may require an 

19 awful lot of work. 

20 And again we've set up December of this 

21 calendar year as a target date. And then finally 

22 we would conduct coordinating and reviewing of -- 

23 of whatever results and possible recommendations 

24 would come out, and that would be the first step 

25 towards solidifying this series of recommendations 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 154 

 2 into whether it be a new report, an extension of 

 3 the IWAQM report, we just don't know just yet how 

 4 we would go about putting this together. 

 5 We do know we would like to get another 

 6 gathering such as this in a workshop specifically 

 7 aimed at getting the final recommendations out. We 

 8 don't want to do this completely as a paper 

 9 exercise. 

10 We want to do it as a participatory exercise, 

11 doing as much as we can ahead of time in terms of 

12 identifying issues, getting work going, but near -- 

13 not so far near the end that you can't make a 

14 change but near enough to the end that we can all 

15 make educated and informed decisions and 

16 recommendations, we would get together and have a 

17 workshop for all interested parties to get 

18 together, and -- and put the finishing touches on 

19 -- on this activity, finalize the recommendation 

20 report, and as I said before, we just don't know 

21 what it would be at this time; what form this 

22 report would take, how stringently it would be 

23 published or produced; that is in play as well as 

24 everything else with regard to our activity here. 

25 The IWAQM originally -- the Interagency Work 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 155 

 2 Group on Air Quality Modeling, and I guess I should 

 3 read it out just once before I call it IWAQM; they 

 4 came together in the very beginning to coordinate 

 5 between, of course, EPA and the Federal land 

 6 managers, on long-range transport from air quality 

 7 related values. 

 8 And there were a number of interested parties. 

 9 At the time NOAA -- well, most of the NOAA 

10 representation was through the EPA conduit, but 

11 nonetheless NOAA did provide technical expertise, 

12 and once again, mostly in the form of the gentleman 

13 to my right, John Irwin. 

14 There were a number of other rep- -- number of 

15 individuals, EPA, Forest Service, Park Service and 

16 Fish and Wildlife Service involved at that time. 

17 And I probably neglected to mention those, as 

18 well. 

19 The first IWAQM, for those of you who are not 

20 familiar with how the history lays out, I'll give 

21 you a very brief rundown on it. And, again, I was 

22 not part of that activity, so it's -- you know -- 

23 all I know is what I read in the newspapers, so to 

24 speak. 

25 Many of you were a part of that activity, and 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 156 

 2 so this is primarily for those of you who weren't, 

 3 and for those of you who were, I apologize if some 

 4 of these facts aren't exactly as they should be. 

 5 The first IWAQM was essentially an interim 

 6 solution that involved a lot of off-the-shelf 

 7 activities for getting towards long-range 

 8 transport, and the phrase, perhaps we take a little 

 9 license, but better than nothing, there was -- 

10 there was for sometime the idea that you just 

11 treated some of these things as zeros, for 

12 secondary formations, things of that nature. 

13 Well, the first IWAQM said, let's at least put 

14 some of the -- some of the off-the-shelf tools 

15 together and give them a look. 

16 The second one came together to recommend the 

17 best modeling techniques, or my favorite part of 

18 this, combinations of techniques; that it is just 

19 not picking one setup, it's not just picking one 

20 model even, there could be combinations of 

21 approaches. 

22 This is a resonant theme that I found in my 

23 examination of the report, that there are possibly 

24 more than one combination of more than one viable 

25 solution, and you'll find in a little while that 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 157 

 2 the phrase "expert judgment" shows up time and time 

 3 and time again in selecting those. 

 4 These recommendations, over time, have become 

 5 default settings that are quickly and -- and very, 

 6 very casually referred to in immediate terms as, 

 7 you know, we want you to do this modeling in 

 8 accordance with the IWAQM II report, done deal. 

 9 And so over time, even though these were 

10 recommendations for combinations of techniques or 

11 the recommendations that came out explicitly have 

12 gathered an -- a -- sort of a concreteness to them, 

13 and they have become the default. 

14 There also are, in many cases, the actual 

15 defaults in the run scripts to run the CALPUFF 

16 model. 

17 Now, conveniently so, they were placed in that 

18 way, so the first option is the IWAQM 

19 recommendations. 

20 I'm not sure that exists in all cases today. 

21 We'll talk about that shortly. 

22 We are in the eighth modeling conference; I 

23 take you all the way back to the sixth modeling 

24 conference when this was presented the first time, 

25 and in -- as -- as the IWAQM report, phase two, was 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 158 

 2 -- was presented at the sixth modeling conference, 

 3 there were some of the -- the highlighted details, 

 4 CALPUFF formally introduced, mesoscale modeling 

 5 with data assimulation, something near and dear to 

 6 the NOAA hearts, and we will talk about that in a 

 7 later session this afternoon when we talk about our 

 8 gridded meteorology efforts. 

 9 And finally recommending these private/public 

10 committees, conclaves of people to come out and 

11 manage the technical issues, some less formally 

12 than we have here today, but still nonetheless, 

13 community gatherings of the affected parties and -- 

14 and the influential parties to make these things 

15 happen. 

16 The first recommendation that I noticed when I 

17 was reading this out was the screening techniques 

18 for CALPUFF -- I'll talk about that shortly in a 

19 little more detail. 

20 CALPUFF also was included at this point, if it

21 was recommended to be included in the guideline, of 

22 course, in April 2003. 

23 It was promulgated for certain applications, 

24 and the long-range transport was mentioned, 

25 visibility in the air quality and and related 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 159 

 2 values, and once again this community effort, the 

 3 regional committees to come up with some of these 

 4 technical decisions. 

 5 CALPUFF screening was -- it's interesting in 

 6 that it had a relatively recent application that I 

 7 was personally involved in. 

 8 First of all, for those of you, you know, 

 9 everyone is probably familiar with screening 

10 applications and that they're typically, slightly 

11 more conservative, but they also are more 

12 generalized in the screening. 

13 The application here is the maximum 

14 concentration at any receptor for a given distance 

15 in the old concentric ring model, and the BART, 

16 Best Available Retrofit Technology, proposal we 

17 used the CALPUFF screen runs to come up with a 

18 look-up table. 

19 That was one of the proposed methods for first 

20 pass at a -- at a screening application. 

21 So it was, while you don't see screening done 

22 as often as -- as you did maybe sometime ago, it's 

23 still interesting to see that it has been a applied 

24 here and there, and I think, this is just 

25 observations of applications that we've done in my 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 160 

 2 eight years here, that as computational efficiency 

 3 gets better, we seem to be more inclined to go to a 

 4 more refined application right out of the gate, and 

 5 I'm not sure that screening was ever brought about 

 6 because of computational requirements. 

 7 However, it seems that computational 

 8 requirements have, or computational efficiencies, 

 9 have allowed some folks to go straight towards 

10 doing more fine modeling right out of the gate. 

11 In our first call that we had with the players 

12 in the beginning that I had mentioned, one of the 

13 individuals here with us today, read a little bit 

14 from the report, and he wanted to put everyone on a 

15 sound footing as to what we are really trying to 

16 achieve when we talk about these new 

17 recommendations. 

18 And what he was trying to get at, and 

19 successfully so, was the spirit of the original 

20 IWAQM group and how they wanted their 

21 recommendations to be viewed and used in the 

22 future. 

23 And at the great risk of just reading verbatim 

24 off the slide, I'd like to just point out a few of 

25 -- of the popular -- the or actually the more 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 161 

 2 pressing phrases here, and that is that it requires 

 3 expert understanding of mesoscale, and microscale 

 4 meteorology and finesse. 

 5 It requires finesse to adjust the controls. 

 6 Now, they're talking about CALMET here, but this 

 7 really does generally apply to the entire suite of 

 8 applications that IWAQM addressed in phase two. 

 9 It does not -- and the last sentence really 

10 shows it accurately there, "IWAQM does not 

11 anticipate a lessening in the required 

12 expertise...". 

13 In other words, this is not designed to ever 

14 become a very simple checklist that anybody can go 

15 ahead and just punch a few buttons and walk away 

16 and they get the same answer that some learned 

17 educated person who has to actually look at this 

18 stuff and -- and figure out what each of the 

19 switches are doing, would get on their run. 

20 Moving on a little further in the document, it 

21 says, the report refers to Appendix A, of course, 

22 which is listing of the specific recommendations, 

23 and it says, you know, that the -- it provides a 

24 listing of the default settings recommended, and 

25 some of those settings require testing, and that's 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 162 

 2 one of the questions we have asked now as -- of the 

 3 new settings, but then the very last sentence says, 

 4 "The information provided in Appendix A should not 

 5 be interpreted as a cookbook approach to be 

 6 applied, regardless of the results that you 

 7 obtain." 

 8 It was never intended to be a cookbook. It 

 9 was never intended to be absolutely prescriptive. 

10 And as I said before, over time it has sort of 

11 defaulted in some applications to that, and we need 

12 to just take a step back and get this whole new 

13 crew of CALPUFF modelers that are out there and 

14 establish that, no, these are not hard and fast, 

15 you must use these settings if you're going to do 

16 this. 

17 That is not what they were ever intended to 

18 be, and that is definitely the spirit we want to 

19 continue our investigation in now. 

20 In meteorology, out of that report again, they 

21 say once again, expertise is required. It won't 

22 ever be as easy as ISC, and that was probably the 

23 best way to get the point home, at that time. 

24 Mesoscale and microscale meteorology expertise 

25 is needed, maybe not absolutely expressly required, 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 163 

 2 but it is certainly beneficial, and I would go so 

 3 far as to say "needed". 

 4 Some met processors in their report needed a 

 5 little work yet, and I think mostly they were 

 6 talking about some of the gridded meteorology field 

 7 converters that would feed into CALMET at that 

 8 time. 

 9 And in particular, formatting. Formatting 

10 always being an issue now as we're getting more and 

11 more different models, more and more different 

12 sources for our data. Formatting was addressed 

13 back then as where it was particular. 

14 And once again the recommendations are not 

15 cookbook. If I could have put that down between 

16 the two logos on these slides, I would have just 

17 left it there each and every time. 

18 (Chuckles for audience.) 

19 (Projecting slide.) 

20 One of the examples that jumped out at me was 

21 the data gap for upper-air data. It says there, if 

22 the data is greater than twelve (12) hours, it has 

23 to be filled by hand. 

24 There comes your expert judgment. I mean that 

25 clearly, just spatially upper-air fields are so far 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 164 

 2 apart that it's hard to just do a straight 

 3 interpolation, and as we started to -- and as I 

 4 started to see when I was looking into this 

 5 document, the meas- -- the mentioning of FDDA for, 

 6 in this case, MM4 or MM5 and the data blending, 

 7 were ahead of their time, almost, as we start to 

 8 really move in those directions now with -- with, 

 9 as you will find out later on this afternoon, 

10 trying to put MM5 into AERMET, or into AERMOD, I 

11 should say. 

12 IWAQM had addressed this way back then as a 

13 need to somehow supplant or augment the expert 

14 judgment that it cannot do without. 

15 But it's not just meteorology; it's emissions. 

16 It's geophysical characteristics, and again 

17 computational. We're getting into the age of 

18 parallel processing, where we might be running 

19 these models many, many, many different 

20 simulations, you might be running different 

21 scenarios simultaneously on parallel processors, on 

22 clusters. 

23 This could be run on the very laptop I'm 

24 standing in front of, or it could be run on a 

25 series of twenty-eight (28) Linux boxes located all 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 165 

 2 over the country, and computational expertise is 

 3 almost every bit as valuable in these applications 

 4 anymore as are meteorology, emissions, air quality 

 5 or even receptor locator. 

 6 And with geophysical data, I know I'm 

 7 hammering this a little hard, but I really, really 

 8 want to make sure that you understand the flavor in 

 9 which we're going to be reaching out and asking 

10 questions here. 

11 Again, it is about the judgment and the 

12 subjectivity, so to speak, and the sta- -- just the 

13 pure scientific intuition that one would need to 

14 perform some of these applications, is what we are 

15 trying to tap into. 

16 It mentions here, for instance, that the 

17 uncertainties with long-range transport are every 

18 bit as driven by mixing depth as by the winds 

19 themselves, and of course, land use is very 

20 significant in developing mixing depths and 

21 therefore land use is quite significant in coming 

22 up with the uncertainties, or at least in -- in 

23 contributing to those uncertainties. 

24 And something that -- that some folks may 

25 actually view as somewhat trivial in land use, pull 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 166 

 2 it from a -- from a file on the web, stick it in 

 3 and run away, it is not nearly as trivial as one 

 4 might think. 

 5 And each and every parameter that we'll list 

 6 later, each and every one of these settings, could 

 7 be the most important one in a particular 

 8 application, and we want to make sure that 

 9 they're all given their due examination and put 

10 in an order that's meaningful when we start 

11 chipping away at which ones we need to take a look 

12 at. 

13 Once again now, IWAQM requires outright expert 

14 judgment, but also site specific, case specific, if 

15 you will, decisions. Each and every one of these 

16 applications is going to require some sort of 

17 unique examination of the task at hand and how we 

18 attempt to address it. 

19 And in those cases, we are going to have to 

20 provide expert judgment and -- and to have 

21 something to fall back on that is not cookbook, that 

22 is not a list, will be very beneficial to, 

23 especially, those folks who are going at this for 

24 maybe the first or second or third time, but then 

25 again, if you're doing the unique modeling 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 167 

 2 situation, it practically is the first time each 

 3 and every time that you're doing these. 

 4 Strong interaction, coordination with the 

 5 applicable reviewing authorities. I've seen that 

 6 phrase a few times in the document, and again, that 

 7 -- that's still out there. 

 8 Now we see that with the protocols for those 

 9 of you who're involved with with BART. You'll see 

10 that in a number of requests for protocols with 

11 many regulatory actions, and it is not just to 

12 have a protocol stamped or approved, it is to get 

13 a discussion and a collaboration going between 

14 the folks who are proposing it, the folks who 

15 are reviewing it and everyone gains from that 

16 process. 

17 And finally consideration once again of 

18 computational expenses. When this was originally 

19 put out, this document, data sizes and data access 

20 were an issue. 

21 It was a very big issue, especially when you 

22 look at, say, getting MM4 data into a CALPUFF 

23 simulation as opposed to using observational data, 

24 just getting the data, just figuring out how to 

25 ship it from point A to point B was an issue, let 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 168 

 2 alone how much data you had to move around. 

 3 And in fact earlier, there was a conversation, 

 4 I was talking with someone about getting in MM5 

 5 data, and we've somehow managed to just expand the 

 6 amount of information to fill the vessel that we 

 7 have. The more hard drive space you buy, the more 

 8 space we fill up. So we're going to need a rented 

 9 truck no matter which way we look at it, but it -- 

10 it -- this was an issue way back when, it remains 

11 an issue now, only we're talking terabytes instead 

12 of megabytes. 

13 The example that I pulled from the document 

14 with visibility, you'll see it says, consult with 

15 experts, run the air quality model, obtain 

16 visibility, obtain relative humidity, determine the 

17 extinction, and finally you come out with a 

18 delta-deciview value. 

19 Three of those six items require 

20 collaboration, require some decision making, dare 

21 I say, subjectivity. They require something other 

22 than going and pulling a number off the chart. 

23 When you get the background numbers, that's 

24 been contentious and not just contentious on say 

25 legal or policy grounds, those numbers are -- are 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 169 

 2 in free play on technical grounds, as are the 

 3 relative humidity adjustment factors, as are some 

 4 of the other settings that we have. 

 5 Very, very rarely do we -- does the whole 

 6 world agree that this is the number that ought to 

 7 be stuck in all these models and we just go with 

 8 it. 

 9 And I'm not talking about these things in 

10 policy terms, I'm not talking about them in 

11 regulatory terms, just plain old technical 

12 scientific agreement on what's the best value, or 

13 -- or an acceptable value. 

14 Okay, so history lesson is gone; it's behind 

15 us. Now we start talking about where do we go from 

16 here. 

17 This group that I put -- that I put up on the 

18 slide earlier that may be enlarged to some of you 

19 or some other folks. 

20 What is this group going to do other than meet 

21 those little parenthetical deadlines. What we were 

22 going to do, hopefully, is come up with the issues 

23 that we -- that we think we need to address, and 

24 they -- they break down into several topics. 

25 Are there things out there that are in 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 170 

 2 existence that just flat out need to be evaluated, 

 3 once and for all, need to be set out as to whether 

 4 they pass muster or not. 

 5 Are there updates and/or improvements that are 

 6 needed to fix a gap, to fix a void -- to fill a 

 7 void or to address a lacking that might be 

 8 identified in one of those evaluations. 

 9 What mechanism are we going to use for 

10 adopting the new versions of the model? You will 

11 hear a little bit more about that, in fact, I think 

12 you may have heard it -- no, you will hear about it 

13 later on actually, you just had AERMOD this morning 

14 -- on how we would be talking about bringing new 

15 versions of CALPUFFs, specifically CALPUFF in this 

16 instance to the regulatory versioning. 

17 Re-examining the recommendation, the 

18 process I'm discussing with you now, and finally 

19 the mechanism for establishing new 

20 recommendations. 

21 How do we do this in the future, after -- do 

22 we want to wait eleven (11) years, again, to do 

23 this or do we want to move a little faster and/or 

24 make it an ongoing living process. 

25 We'll start off with some evaluations and 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 171 

 2 updates, and to do this, as I said before, I'm not 

 3 a terribly experienced person in running this 

 4 model, and many of the folks on my staff have about 

 5 the same level I've got, perhaps a little more. 

 6 There are folks out in the community, the regional 

 7 modelers, the state modelers, and there are folks 

 8 in the academic community that I probably don't 

 9 even know exist who are well versed in this model. 

10 And I tried reaching in all these places, finding 

11 publications, finding just about everywhere we can 

12 find where something has been brought to floor as 

13 an issue that needs to be addressed with regard, 

14 specifically, to the CALPUFF model. 

15 And I'd like to share with you some of them 

16 now that have just risen up, there -- and there's 

17 quite a few of them that you only see once and 

18 perhaps it's not quite germane, but the ones that 

19 I'm going to be putting forward in these subsequent 

20 slides I think have come up time and time again to 

21 the point where you probably all know about them 

22 anyway, and -- and many of you will be sitting 

23 there nodding approval, yeah, I know that one, I 

24 know that one, and I want to just bring these out 

25 here, and if there are any that are not here, find 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 172 

 2 out about them right away. 

 3 The Air Quality Modeling Group has, of course, 

 4 been using this model for quite sometime, and in 

 5 all those applications there have been issues that 

 6 have arisen in one way or another that I have tried 

 7 to get my finger on, and -- and they seem to be 

 8 able -- they seem to be capturable under the 

 9 heading of secondary formations, at least one group 

10 of them. 

11 In some of the modeling exercises that we've 

12 done, and those of you familiar with how the 

13 Federal Land Managers work with the flag document 

14 as opposed to what is expressly laid out for 

15 CALPUFF in the Appendix W, you know, there is quite 

16 a chasm in there in applications, and it centers 

17 around, in some cases, the secondary formation 

18 issue. 

19 It has been voiced that SO2 to sulfate are 

20 okay. Nit- -- the NOx -- the gaseous reactions are 

21 doing all right, however, the aqueous sulfate was 

22 defined in one spot as not adequate and 

23 thematically it was repeated in a few other places. 

24 Nitrate deposition was thought to be also a 

25 little problematic. Could that just be setting an 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 173 

 2 ammonia background value? Could this be one of the 

 3 instances where it's just a value that needs to be 

 4 readjusted as opposed to going in and doing a model 

 5 fix or something like that. 

 6 And then once again, for AQRVs, the IWAQM 

 7 report said, yes, we recognize a lot of these. We 

 8 know they're there, but right now for lack of a 

 9 better phrase it's better than nothing to go ahead 

10 and at least look at these things and start 

11 modeling them and seeing what the numbers give us. 

12 And those were the secondary issues, and you'll see 

13 those come up again. 

14 Downwind distance was the other big one, at 

15 least in going through the -- the AQMG experiences. 

16 Puff coherency; what happens can a -- when a 

17 puff gets so big that it just goes -- goes beyond 

18 its realm and -- and splitting it. Do we 

19 understand the -- I believe it was CAPTEXT where 

20 puff splitting became an issue. 

21 The underestimation of dispersion and for the 

22 over prediction of the concentrations at particular 

23 receptors because of the lack of splittings, and 

24 once again the vertical height -- well, vertical 

25 splitting changed in the mixing height. 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 174 

 2 The reason I bring this up is simply as a 

 3 carryover kind of, to tease us as we get towards 

 4 the -- the discussions of moving in and applying 

 5 them to other dispersion models. We find mixing 

 6 height to be a very, very big issue, and the fact 

 7 that the mixing height actually affects this 

 8 downwind distance argument, which is one of the 

 9 more prevalent issues that's -- that's out there 

10 with -- with regard to CALPUFF, it strikes that 

11 when we look towards the MM5, or the gridded 

12 meteorology, mixing height comes into play at that 

13 point, and it is still very much still up in the 

14 air. 

15 So something this sensitive to model, we need 

16 to take a good long look at how we change things, 

17 by changing our met inputs. 

18 Some of the other ones, and -- and I should 

19 point out at this point that there is an effort 

20 ongoing in this -- this air quality modeling group, 

21 to have someone take a look -- we do have a -- an 

22 effort out, there is a request for proposal out to 

23 look at some of these issues find out what can be 

24 evaluated and what can been done and in the 

25 statement of work not only do we have the 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 175 

 2 secondary formation mentioned, we have the downwind 

 3 distance issue mentioned, and we have these. 

 4 And as I said before, some of these may be, 

 5 again, very familiar as, yes, that is a -- that is 

 6 something I really wish they'd take a look at. 

 7 You may be looking at this saying, you know, 

 8 there's A, B, or C, that they didn't mention, 

 9 which are clearly more important to me than any of 

10 these. 

11 I would like to find out that sort of priority 

12 order from as many folks as I can. Of course, 

13 there is no bottomless pit of resources so we want 

14 to make really sure that we prioritize these 

15 things, and additionally, if there's anyone out 

16 there investigating some of these issues, it would 

17 be nice to make sure that are we're not having 

18 seven -- seven groups or seven people doing the 

19 same thing and just get as -- as overall process 

20 efficient as we can, as hopefully all of us try to 

21 move forward in this. 

22 There is also another document, the CALPUFF 

23 Reviewers Guide, with my apologies, if I 

24 misrepresent the name here, but it was prepared by 

25 Air Resource Specialists. It was prepared for the 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 176 

 2 Forest Service and the Park Service. 

 3 It is a draft document, and it does have a 

 4 straight narrow focus on AQRV's base, of course, on 

 5 -- on whom it was prepared for. 

 6 This is a draft document that does a very fine 

 7 job, in my opinion, of highlighting a lot of the 

 8 CALPUFF technical issues that are out there that 

 9 depart, or that came to be, after IWAQM II was put 

10 out. 

11 So there is a number of things that we're 

12 going to be showing you on the next couple of 

13 slides that discuss some of the things discovered 

14 by this report and contained in this report, that 

15 are not problems with CALPUFF or things that need 

16 to be changed or things that need to be reviewed. 

17 It's just -- this came out since IWAQM. IWAQM 

18 never had a chance to address this, so we like to 

19 put it out there and give it the same sort of 

20 robust treatment that the other CALPUFF issues had 

21 from the IWAQM group. 

22 Specifically looking at CALMET, there are some 

23 things, and the first one is No Obs which was, of 

24 course, more recent than IWAQM. 

25 That is something we'll talk about in a little 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 177 

 2 greater detail. In fact, I'll have -- hopefully 

 3 hear from some of you. We will hear from Bret 

 4 Anderson later, I hope, on -- on this very topic. 

 5 Gridded clouds -- the icon- -- I know in fact 

 6 kinematic effects was put forward as a setting just 

 7 by, most recently in applicant who was doing some 

 8 modeling said, I would like to use this -- the 

 9 kinematic effects here, however, it's not addressed 

10 anywhere. 

11 And I'd like to know, does anybody have any 

12 experience in the kind output or results one would 

13 get, and just exactly what's going on? 

14 So that was one little research activity that 

15 I did see show up. 

16 The bias parameter, the wind calculation, 

17 where and when and how much emphasis is given to a 

18 prognostic model when it goes into the wind 

19 calculations, the I-PROG variable. 

20 And I noticed in this report the mention that 

21 the National Weather Service 3240 data is so easily 

22 and readily available, you should use this, you 

23 should gather this data for every application. 

24 It's just there and there is no difficulty in 

25 obtaining it, and the report was fairly -- fairly 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 178 

 2 clear in saying, you really ought to use this 

 3 stuff. 

 4 Well, if you do, now the radius of influence 

 5 issues come to -- come up with regard to how much 

 6 you're going to blend and interact with your 

 7 gridded meteorological data, if you are applying 

 8 that as well as this. 

 9 So -- so these are the kinds of issues that 

10 are popping up now that were not nearly as 

11 prominent when IWAQM II was -- was done -- where 

12 most of the modeling was still done with either MM4 

13 or mostly with observational data being processed 

14 through CALMET. 

15 Finally, a lake-breeze module was also 

16 mentioned in there -- in this report as not being 

17 utilized very often, but it started to describe 

18 some of the results one might get if you did use 

19 it, and that could be an issue for further 

20 exploration. 

21 In CALPUFF itself, one tip of the hat to the 

22 computational issues is that the whole restart 

23 issue again, once we start using these things in 

24 clusters, and we're running simultaneously, and 

25 we're using very, very large data sets, we need to 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 179 

 2 do more like what happens in the grid modeling 

 3 world where we have to have smaller chunks 

 4 restarted, and so that was something that sort of 

 5 acknowledges the fact that computationally, we're 

 6 in a different world than we were before, not 

 7 always just in science. 

 8 Plume height calculations, again, puff 

 9 splitting shows up, and now we're more to, when we 

10 get to dispersion coefficients, we're more into the 

11 actual settings themselves. 

12 Again, not so much is it an issue with the 

13 model, is it an issue with the way the model is 

14 applied, it's within the scientific or technical 

15 values we give to the inputs. And some of these 

16 inputs need to be looked at and -- and given a good 

17 examination and perhaps a new recommendation. 

18 For the dispersion coefficient, the one that's 

19 very timely here, is if you use the 

20 Pascal-Gifford, you set it to number three, and 

21 DISP would equal three. 

22 And it says in this report that when AERMOD is 

23 promulgated, (pause), I'll just stop there for 

24 calming effect for a moment, but when AERMOD is 

25 promulgated, we will go to the AERMOD 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 180 

 2 micrometeorological method, and then suddenly the 

 3 probability density function for convection is now 

 4 required once you do that. 

 5 There is -- there is something that we should 

 6 take a good look at, because now, very shortly, 

 7 very shortly, we're going to have this as an 

 8 available option, because AERMOD is very, very 

 9 ready. 

10 I'm sure they discussed that this morning as 

11 to how close we are to getting it done. 

12 The regulatory default override which is -- 

13 (Mr. Fox speaks to Mr. Evangelista.) 

14 MARK EVANGELISTA: It's done? 

15 The regulatory default override -- what -- 

16 what you set back to, give me all the regulatory 

17 sevens and let's just go. 

18 How applicable is that now that we -- we 

19 realize a lot of these settings need to be 

20 re-examined. 

21 And, again, there's some other things like 

22 subgrid scale, complex terrain, in quotes, which 

23 are characteristically not used, and -- and it 

24 would be nice to find out if those had even been 

25 applied and -- and tested or evaluated. 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 181 

 2 Also, there's again parameter settings that 

 3 have shown up. 

 4 Background concentrations. This was something 

 5 during the BART modeling that became an issue. We 

 6 had to take a good long look at how we were going 

 7 come up with some of those backgrounds. 

 8 And also when you look at ammonium -- in some 

 9 instances you don't want to pick a number off the 

10 chart, but numbers off the chart aren't so bad. 

11 You just have to realize or calculate the -- the 

12 ratio, the weighted averages. You may be able to 

13 get very, very good land use data that is far more 

14 highly resolved than previous stuff, and rather 

15 than just taking one value or another arbitrarily, 

16 or based on a point in space, but actually coming 

17 up with -- with a, in this case, a weighted 

18 average, which would be for that application 

19 unique. 

20 Therefore, we're back to this site specific, 

21 case specific, unique applications that really are 

22 combinations of parameters. 

23 Again, we go all the way back to that previous 

24 segment, combinations of recommended parameters, so 

25 they just, in their application, create a new one. 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 182 

 2 Light extinction, coefficients, F of RH was an 

 3 issue, and of course, natural background, more in 

 4 the policy world, but it's still very much an issue 

 5 in doing this modeling and very much fair game for 

 6 this kind of activity that we're talking about 

 7 here. 

 8 Now, I want to go to some other places where I 

 9 found some CALPUFF discussions, and this was in the 

10 comments that we got back from the proposed rule 

11 for -- for BART, for the BART Notice of the 

12 proposed rulemaking, we got a number of comments 

13 back about how CALPUFF should be applied, how it 

14 was applied in the populating -- the look-up table 

15 that we did, and we found quite a few comments from 

16 quite a few individuals, and -- and groups that 

17 could be again boiled down into several key 

18 categories. 

19 In this case the discussion of mesopuff 

20 chemistries, that -- there was just quite a few 

21 comments about CALPUFF chemistry, itself, and that 

22 it has to be taken -- another look must be taken at 

23 this chemistry. 

24 There's questions as to how recent and timely 

25 it is, is it outdated? These are more questions 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 183 

 2 that lead towards the model itself. Is an update 

 3 necessary, and if so, what type of update we'll be 

 4 looking at. 

 5 Aqueous chemistry was called into question, 

 6 overestimating near sources, the phrase uncertain, 

 7 not really over- or underestimating, but uncertain 

 8 downwind, and then finally a lot of discussion on 

 9 the general over-prediction, over two hundred (200) 

10 kilometers, once again, so we go back to Appendix 

11 W. 

12 CALPUFF is recommended to two hundred 

13 kilometers (200k), and then beyond that you need to 

14 apply expert judgment and submit protocols. 

15 Also, where some of the nitrate and sulfate 

16 formation rates called into question; the 

17 comments, nitrate in the summer, sulfate in the 

18 winter, that's a common thing, as well, in the 

19 grid modeling world. The model is highly 

20 sensitive to the temperature effects which thereby 

21 brought up question about what temperatures were 

22 assumed during the development of some of the 

23 chemistry. 

24 And again these -- these are more literature 

25 search type issues that come up, and they may have 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 184 

 2 been resolved by now. They may have the results 

 3 before these comments were even submitted. It's -- 

 4 it's these kinds of things that we want to find 

 5 out. 

 6 And then finally another one was the 

 7 accounting for the NOx limiting on photochemistry. 

 8 And also consultation with other modelers, not 

 9 just submitting comments or finding it written 

10 down. Just in our experiences, and again as I say, 

11 we are not the most experienced crew in the world, 

12 when it comes to CALPUFF applications. 

13 There are many of you out there that have done 

14 more and more of those, and it's been in our 

15 interactions with the modeling world that we've 

16 come up with some other things that need to be 

17 looked at. 

18 And they boil down, not so much into 

19 specifics, as into places where we would consider 

20 areas for evaluation, and this kind of goes back 

21 again, to what we said in the beginning, there are 

22 places that we just need evaluation. There's 

23 places where we may need action to be taken; new 

24 code, new algorithms, what-have-you, and there may 

25 be places where we just need to recommend a new 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 185 

 2 value for a setting. 

 3 In this case, there is areas of evaluation to 

 4 find out all those things. There is also 

 5 recommendations that are needed, in other words, 

 6 this is more of a policy thing, but the modelers 

 7 have said, this works, this setting works, that 

 8 setting works, which one do we use? 

 9 We need some sort of authoritarian decision on 

10 which one of those equally viable options is 

11 useable, and let's just go with one. 

12 Future enhancements; there is a long list of 

13 things that would be nice to have as we move 

14 forward, now, not every dime has to always be spent 

15 on fixing bugs, on going back and holding workshops 

16 and re-evaluating things. 

17 There's also things that are achievable and 

18 obtainable in future enhancements that would really 

19 push what we do to the next level, and those type 

20 of enhancements start with, you know what we ought 

21 to do, and that's what we want to find out, too. 

22 Get those on the list and get them thought 

23 about, or at least on paper, and start putting 

24 plans together. 

25 And it is a growing, growing list. And, of 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 186 

 2 course, it's going to be a list that's too big for 

 3 the -- for the ability to see everything achieved, 

 4 but I would much rather see the list grow 

 5 enormously than have a very small list and say, 

 6 wow, look, we got ninety-five percent (95%) done of 

 7 everything that was out there. 

 8 I would much rather see, as would my 

 9 colleagues here in this effort, we would much 

10 rather find out what that list is all the way 

11 across the board of how we can take this system 

12 forward and we'd all learn together as we moved 

13 along. 

14 Now, in terms of determining current areas of 

15 evaluation of some of those things, I'm just going 

16 to step aside at this moment. 

17 This begins more specific layouts of some of 

18 those things I just described: current areas for 

19 evaluation, enhancements needed, and as I said 

20 before, this comes under the overall title of 

21 consultation with other modelers. 

22 What I've got here was one of the regional 

23 modelers out here, Bret Anderson was kind enough to 

24 actually put these together for me as a slide. 

25 Now, this is not in any way the sum total of 
 1 CALPUFF/Bret Anderson Vol. 1, p. 187 

 2 what the regional modelers have told me. 

 3 This is one regional modeler's description of 

 4 what we ought to do, that I hope is a template by 

 5 which we get dozens, if not scores, of similar 

 6 ideas from other modelers out there. 

 7 This is but one example, this is by no means 

 8 the sum total. 

 9 If you would be so kind, Bret, I would like 

10 you to describe some of these if you will, and the 

11 slides you sent me are carried along right through 

12 here. 

13 And we'll have some, after Bret is finished, 

14 I'll speak with you very shortly after that and 

15 hopefully hear from you, as well. 

16 BRET ANDERSON: Thanks, Mark. 

 

17 I'm Bret Anderson, US EPA Region Seven out of 

18 Kansas City, and there is a group of the regional 

19 modelers that've -- that have been facing a number 

20 of issues that are, as Mark described, kind of the 

21 evolution of CALPUFF, and we are starting to see 

22 these in the BART applications of modeling here, 

23 and so there's a lot of areas that are covered 

24 under Appendix W and in the IWAQM Phase II 

25 recommendations which are not readily spoken, or 
 1 CALPUFF/Bret Anderson Vol. 1, p. 188 

 2 have not been readily evaluated, which we are 

 3 starting to see be proposed for use in CALPUFF 

 4 applications with BART. 

 5 And so, what I've done here is prepared a list 

 6 of some of the applications in consultation with 

 7 some of the other EPA regions and with the Federal 

 8 Land Managers. 

 9 Some of the issues that we have seen come up 

10 as far as what has been proposed in some of the 

11 BART modeling protocols, and you can see the one of 

12 the most important ones is the use of the No Obs, 

13 and that one typically -- most of it, and I'll 

14 defer to John Vimont out here, you know, since 

15 they're the ones that deal mostly with the Class 1 

16 visibility applications, and so they -- they see 

17 these probably proposed more so than what the EPA 

18 regional offices do. 

19 But in the BART world, almost all the 

20 protocols that we have seen put forward to date 

21 have proposed the use of No Obs, versus, you know, 

22 the traditional recommended way in Appendix W which 

23 is use -- the use of prognostic meteorological data 

24 in conjunction with the available National Weather 

25 Service data. And so these are -- this is one of 
 1 CALPUFF/Bret Anderson Vol. 1, p. 189 

 2 those primary areas where it has not been evaluated 

 3 yet, and it -- you know -- it's facing the 

 4 regulatory community here. 

 5 The next one is, and this is a discussion, is 

 6 the IWAQM phase II recommendations for the use of 

 7 the PGs stability curve -- the gradient -- the PG 

 8 stability classes. 

 9 The discussions that we had with the Federal 

10 Land Manages was that upon promulgation of AERMOD 

11 that they will begin accepting the use of the 

12 turbulence-based dispersion coefficients, but 

13 that's one of those areas that most of the problems 

14 -- most of the evaluations have been done. Most of 

15 them have been done on the basis of using the PG 

16 curves. 

17 Next one, and this is an issue that we face, 

18 especially out in the central part of the United 

19 States, and the BART applications, is the issue of 

20 the effective range of CALPUFF, because the -- the 

21 guideline on air quality -- you know -- recommends 

22 somewhere in the range of two to three hundred 

23 kilometers (200-300km) as being the maximum 

24 effective range for this. 

25 And since that time, the model has evolved 
 1 CALPUFF/Bret Anderson Vol. 1, p. 190 

 2 somewhat in the application for -- you know -- with 

 3 using puff splitting to maybe -- you know -- make 

 4 the effective range longer. 

 5 But for states like Iowa, Nebraska and Kansas, 

 6 which do not have their own Class 1 areas, but are 

 7 under a requirement to do some sort of a 

 8 demonstration for their BART eligible sources, the 

 9 effective distance from these particular BART 

10 eligible sources to the nearest Class 1 area is 

11 well in excess of what the Appendix A 

12 recommendation is for this use, and so this is 

13 another one of those questions that we put out for 

14 evaluation is with the -- with the advent of both 

15 horizontal and vertical puff splitting, is that 

16 recommendation two to three hundred kilometers 

17 (200-300km), can we extend the range further? 

18 The next one is, this is the -- this is the 

19 kind of the ongoing one and the right extinction 

20 methodologies, as you're aware, the -- the BART 

21 guidance recommended using method six, which, I 

22 think, uses the monthly F of RH values, and there 

23 are another -- there are a series of a variance out 

24 there, the method seven, the method seven-PRIME, 

25 which have been proposed for use -- you know -- in 
 1 CALPUFF/Bret Anderson Vol. 1, p. 191 

 2 either, you know, the PSE visibility analyses or, 

 3 you know, as a further recommendation for BART. 

 4 Other areas for evaluation which may not be 

 5 necessarily limited to BART, but other areas where 

 6 we have seen may be potential proposals for the use 

 7 of this is one incident of the ammonia limiting 

 8 method. 

 9 Another one is the use of boundary conditions 

10 for CALPUFF, updates the aqueous space chemistry. 

11 Secondary organic, aerosols, and then this one is 

12 more in particular the -- the interest in the Blue 

13 Sky community, the people that are doing smoke 

14 modeling has deemed the numerical plume rise 

15 algorithm that this uses is how -- how effectively 

16 has this been evaluated. 

17 (Projecting slide.) 

18 As far as the recommendations that are needed, 

19 this is one of those areas where the, if you take a 

20 read of the current state of the guidance, you 

21 know, the Appendix W, what you find is is that 

22 there is some potential, I wouldn't call them 

23 discrepancies, but there is some clarifications 

24 that are needed in terms of what the guidance 

25 state. 
 1 CALPUFF/Bret Anderson Vol. 1, p. 192 

 2 In particular, for those that aren't familiar, 

 3 the No Obs is essentially when you're -- you have 

 4 essentially three different typ- -- or more types 

 5 of applications. 

 6 You can run CALMET, or you can drive 

 7 CALMET completely with just prognostic 

 8 meteorological data, or you can use a hybrid 

 9 approach. 

10 Essentially we're using a combination of 

11 either surface or upper-air data, or you can use 

12 surface data for your observations, and then you 

13 could use No Obs where you're using the prognostic 

14 data, to, you know, use -- essentially it's to 

15 replace the upper-air soundings, and so -- but 

16 basically when you read section nine three one two 

17 D (Section 9.3.12d) of the Guideline on Air Quality Models, it 

states that mesoscale meteorological 

19 fields should be used in conjunction with available 

20 standard National Weather Service data or 

21 comparable meteorological observations within and 

22 near the area that you're modeling, and so, you 

23 know, the keyword becomes, "should" but as we all 

24 know, the guideline oftentimes takes on a more 

25 concrete nature to it, and so this is one of those 
 1 CALPUFF/Bret Anderson Vol. 1, p. 193 

 2 areas where the existing guidance should 

 3 potentially be clarified to discuss the issue of No 

 4 Obs. 

 5 Secondly, is the use of the prognostic 

 6 meteorological data in the evaluation methods. 

 7 Statistical method -- metrics and 

 8 methodologies for determining the acceptability of 

 9 prognostic data sets. 

10 If you were to refer to Section nine three C 

11 (Section 9.3c) of the Guideline on Air Quality Models, what you 

find is, you find it states 

13 acceptance for the use of the output of prognostic 

14 mesoscale meteorological models is contingent upon 

15 the occurrence by the appropriate reviewing 

16 authorities that the data are of acceptable 

17 quality, which can be demonstrated through 

18 statistical comparisons with observations of winds 

19 aloft and at the surface at several appropriate 

20 locations. 

21 And there is no further guidance on what these 

22 metrics are and so what we find is that as data 

23 sets are being proposed, one set of these would be 

24 -- I would go back to experience like with the 

25 regional planning organizations, they have 
 1 CALPUFF/Bret Anderson Vol. 1, p. 194 

 2 developed multiple years of MM5 meteorological data 

 3 that have been extensively evaluated, but we have 

 4 seen other meteorological data sets proposed for 

 5 which a very minimal set of evaluation has been 

 6 conducted, and so, as such, what we are talking 

 7 about is clarifying the guidance to come up with a 

 8 consistent set of metrics and methodologies that 

 9 can been used so that the reviewing authorities, 

10 being the state and the regional offices, can turn 

11 to when they are facing -- or when they are 

12 reviewing a new meteorological data set that's 

13 being proposed for use. 

14 Because, essentially, what we're running into 

15 here is, are we're now running into the blending of 

16 the two (2) worlds. 

17 We have -- we have a group of people that are 

18 the regional, you know, meteorological and 

19 photochemical modelers that are very used to these 

20 evaluation techniques, and we have the near-field 

21 people, which are primarily composing this 

22 audience, that do -- may -- may also have the 

23 responsibility of conducting the CALPUFF 

24 applications. 

25 And so now we're in a situation where the 
 1 CALPUFF/Bret Anderson Vol. 1, p. 195 

 2 near-field people, who have very limited exposure 

 3 to the use of prognostic meteorological data and 

 4 the running of the models, are now being asked to 

 5 make the decision on the acceptability of the use 

 6 of these data sets. 

 7 And so we've -- this is another one of those 

 8 areas where we feel that additional guidance may be 

 9 necessary or additional clarification, within 

10 Appendix W, would be helpful as we move forward in 

11 the use of these meteorological data sets. 

12 (Projecting slide.) 

13 Okay. Here was a -- like I said, or like Mark 

14 said, this was one person's view of potential 

15 possible enhancements, you know, based upon some of 

16 the comments that we had from the other regional 

17 offices and the Federal Land Managers. 

18 One of the most common ones is the -- you know 

19 -- the comment is the -- common comment was that, 

20 you know, that the -- the datedness of the existing 

21 chemistry modules for RideOut and MESOPUFF II, and 

22 one suggestion was to examine the use of putting in 

23 a chemical module similar to what SKCICHEM has, and 

24 they realized that there's a technical formulation 

25 differences between the two of them. 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 196 

 2 But that was one suggestion that was put 

 3 forward. 

 4 Another one was additional enhancements to the 

 5 eight-voice based chemistry. 

 6 Another suggestion that was forward was 

 7 developing an MSIP style preprocessor for CALPUFF, 

 8 and for those who not familiar, MSIP is a processor 

 9 for the CMAQ modeling system, which essentially it 

10 takes MM5 data and it creates -- prepares the 

11 meteorolog- -- the gridded meteorological data for 

12 input into the photochemical model, but it also 

13 does some limited additional diagnosis of 

14 additional variables and things -- and things along 

15 that line. 

16 So the goal here would be to bypass the CALMET 

17 processing and rediagnosis of certain prognostic 

18 variables such as, you know, the planetary boundary 

19 layer computations and things along that line, and 

20 then also allow for the direct use of the 

21 prognostic meteorological data in CALPUFF rather 

22 than there being certain adjust- -- additional 

23 adjustments to it. 

24 Thank you. 

25 MARK EVANGELISTA: That is one person's five-minute 

 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 197 

 2 description of -- of where we ought to take our 

 3 look at -- at guidance, recommendations, where we 

 4 ought to look with regard to some of the 

 5 enhancements, and then also some of the current 

 6 options that have been employed, should be 

 7 employed, may be employed, what those options do, 

 8 and any sensitivities or evaluations of those 

 9 things, and then finally, some other set of 

10 recommendations. 

11 (Projecting slide.) 

12 I go to this slide, now, which is the final 

13 one that I have here, and this time I -- I ask you, 

14 given what we are trying to accomplish, just in 

15 listing those issues, given what you feel may be in 

16 your mind some of the more pressing issues and what 

17 it might take to get those resolved, how realistic 

18 are those parentheses, suddenly? 

19 Now keep in mind that there are applications, 

20 there are BART protocols that are moving forward 

21 regardless, there are -- there is a workshop I 

22 believe in April, an AWMA workshop, where it would 

23 be marvelous to roll something like this out. 

24 There are other events, applications, 

25 regulatory deadlines, that are coming no matter 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 198 

 2 what. 

 3 So to be relevant to as many of those as 

 4 possible, in addition to giving these types of 

 5 activities we want performed their just due, we 

 6 have to come up with some kind of a balance, and -- 

 7 and maybe modify some of those dates, maybe modify 

 8 some of our activities, maybe get a dose of 

 9 reality, we don't know yet. 

10 We're still looking into this, we're still 

11 trying to amass step one; getting the technical 

12 issues fleshed out. That group I gave you in the 

13 very beginning of -- of folks who are taking part, 

14 sure, we could all pole ourselves and -- and come 

15 up with a list and then just run with it, but that 

16 doesn't really tap into the full wealth of ideas 

17 that are out there of where we ought to be, or at 

18 least what the -- even the current state is in 

19 terms of applications. 

20 So I'm not looking for answers right now. 

21 What I'm looking for at this point in time is for 

22 you to think about how much this means to you and 

23 how much you would want to be staked out in 

24 participating, and whether it's just e-mailing me, 

25 evangelista.mark@epa.gov, whether it's just 
 1 CALPUFF/Mark Evangelista Vol. 1, p. 199 

 2 e-mailing me what you -- what you think ought to 

 3 happen, parts of the model you want to look into, 

 4 or whether it's wanting to be an active participant 

 5 or conducting an evaluation or doing anything, we 

 6 would certainly, certainly, welcome any -- any type 

 7 of contribution. 

 8 I believe that ends this, yes, it does, and 

 9 with that, I would like to, unless there are other 

10 preferences from my friends in the front row here, 

11 turn the microphone around and ask a few questions 

12 here as to what you've seen, more on, well, no, let 

13 me rephrase that. 

14 Everything's fair. The process itself, the 

15 technical issues, I'd -- I'd like to hear from -- 

16 from this group which clearly is more learned in 

17 this model than am I at this point, and I'd like to 

18 see the knowledge direction change for a few 

19 moments. 

20 And if there is something you want to put to 

21 someone, it doesn't necessarily have to be me. I 

22 would think John, and I don't mean to speak for you 

23 right now, but I -- I think you would be willing to 

24 entertain a question or two about this sort of 

25 stuff as well as perhaps Bret and some -- some 
 1 QUESTIONS/Audience Vol. 1, p. 200 

 2 others. 

 3 ALAN CIMORELLI: This is Al Cimorelli. One of the things 

 

 4 that came out in the most recent guidelines was with regard 

 5 to complex winds. 

 6 And most of the presentation that I've heard 

 7 now had to do more with BART, more with long-range 

 8 transport, or with -- you know -- RDs and so on. 

 9 Just recently people have been asking 

10 questions about toxics and doing risk assessments, 

11 and whether we should be using AERMOD or whether we 

12 should be using CALPUFF, and the whole question of 

13 a non-uniform wind field and whether you should be 

14 using one model or another in the near-field is 

15 something that I think is going to be an important 

16 aspect to this, and I would suggest that we start 

17 thinking about that as well. 

18 And I -- and in that regard, I remember along 

19 a while back, one of the studies that was done was 

20 to try to configure CALPUFF in a way that you -- 

21 that you could -- you could reproduce ISC, and I 

22 think that was done sometime back, and we 

23 demonstrated to ourselves pretty convincingly that 

24 if you put in a uniform wind field, then allow it 

25 to change spatially or temporally that you can 
 1 QUESTIONS/Audience Vol. 1, p. 201 

 2 get exactly the same answers as you could get with 

 3 ISC. 

 4 Now that we are moving to AERMOD, I think that 

 5 a study like that would be really quite important. 

 6 So I would recommend that we do that. And that's 

 7 -- and that's -- that doesn't require going out and 

 8 collecting a whole lot of data. That's simply a 

 9 computational experiment that I think you should be 

10 doing, and I think we should do that sooner rather 

11 than later. 

12 WARREN PETERS: Thank you, Al. 

13 PIETRO CATIZONE: This is Pete Catizone, TRC. Maybe it's 

14 more of a comment than a question. 

15 When you were speaking, you were talking about 

16 how CALPUFF's system was intended to be not the 

17 cookbook type of application model. 

18 When we hear Mark speak, he wants to make it a 

19 cookbook for particular applications. 

20 Should he maybe -- or specifying specific 

21 recommendations for applications. Should there be 

22 maybe a difference between whether we apply the 

23 model for a particular type of program versus 

24 generically putting some of those recommendations 

25 -- specific recommendations in the guideline? 
 1 QUESTIONS/Audience Vol. 1, p. 202 

 2 MARK EVANGELISTA: As far as the guideline end of things, I 

 3 would defer to Tyler Fox, the group leader, but I 

 4 would offer you this; I don't think those two are 

 5 mutually exclusive. 

 6 I think the IWAQM intent of not being cookbook 

 7 is not so much for CALPUFF per se as for the 

 8 recommendations they put forward. 

 9 You can have the non-cookbook recommendations, 

10 and the judgment that's required, and for a 

11 particular specific application that I believe Bret 

12 was referring to, you can have a more established 

13 protocol, template. 

14 They seem that they could -- they could 

15 co-exist. That's my impression. I -- would you 

16 like to add anything to that? 

17 BRET ANDERSON: No, I think they have it. 

18 RICHARD SCHULZE: I'm Dick Schulze, Trinity Consultants, and 

19 I noticed your committee was composed of employees 

20 of the Federal Government. There is a large number 

21 of consultants that have a great deal of experience 

22 in this. 

23 Is there any attempt to engage them in 

24 conversation with the -- your committee? 

25 MARK EVANGELISTA: There wasn't prior to this gathering, 
 1 QUESTIONS/Audience Vol. 1, p. 203 

 2 because it was hoped that we could use this 

 3 gathering as an outreach to everyone outside of 

 4 that. 

 5 The -- you -- you did notice they were all 

 6 Federal -- Federal as was what the original IWAQM 

 7 interagency work group, and that was the stepping 

 8 off point for this version. 

 9 By no means do we want to restrict it, and 

10 that's why we threw that group -- or we put that 

11 group together and had our first couple of 

12 discussions about the technical issues, always 

13 knowing that we were going to reach out to the 

14 entire modeling community very early in this 

15 process. 

16 And it was just fortuitous that this gathering 

17 was -- was on the schedule and -- and it lined up, 

18 so this -- this discussion we're having now was 

19 planned as part of the process, but before that we 

20 had not reached out to anyone outside the Federal 

21 Government, but we'd always intended to use this as 

22 a way to do that. 

23 So, there may be a perceived misinclusion at 

24 that point, but it was really a part of the overall 

25 logistics, I guess, of trying to get this group 
 1 QUESTIONS/Audience Vol. 1, p. 204 

 2 together. 

 3 So, yeah, as of now, we're -- we're taking 

 4 allcomers, so to speak in all the -- all the 

 5 technical aspects of this model and -- and how it 

 6 should be applied. 

 7 GALE HOFFNAGLE: Gale Hoffnagle, TRC, AWMA 

 8 actually. 

 9 Please come to Denver in April, and I will 

10 give you space on the program to make your 

11 presentations. 

12 MARK EVANGELISTA: Thank you, be happy to. 

13 JOHN IRWIN: John Irwin. 

14 One of the things that I was very happy to see 

15 was that we had at some point created a frequently 

16 asked questions section and Roger Brode and Joe 

17 Scire worked very hard to try and create the 

18 initial frequently asked questions, which was 

19 available off the web. 

20 And I was up there the other day, looking at 

21 it, and I noticed it is actually getting expanded. 

22 But some of the issues that you raise could 

23 probably be well addressed in that manner. 

24 There -- there probably won't be absolute 

25 answers, but if we could lay out, for this 
 1 QUESTIONS/Audience Vol. 1, p. 205 

 2 parameter you should think about changing it this 

 3 direction if you are in this situation or this 

 4 direction. If you are in another situation and lay 

 5 that out in the frequently asked questions as the 

 6 lessons are learned, then I think it will help 

 7 people make the technical judgment of where they 

 8 are and what selection, how they want to set that 

 9 parameter. 

10 Now that might be a way of -- you asked how 

11 could we get information out rapidly. 

12 Technical information, you can get out rapidly 

13 in this way, policy decision, it's inappropriate to 

14 do it that way, but technical information, you 

15 could get out very quickly this way, and you do 

16 have something there, I mean it is an existing 

17 item, just a matter of getting it updated and 

18 making that easier to do. 

19 And also getting the user community to submit 

20 ideas, you know, lessons that they have learned, 

21 submit them to somebody who can bet them, make sure 

22 that this is guidance or technical information that 

23 could be used in a more general sense and then make 

24 the steps necessary to update the frequently asked 

25 questions. 
 1 QUESTIONS/Audience Vol. 1, p. 206 

 2 TYLER FOX: As you mention that, John, I'm -- I call to mind 

 3 what goes on right now in the photochemical grid 

 4 modeling, and CMAQ has a frequently asked 

 5 questions, and a list search to air technical 

 6 issues. 

 7 And the other advantage, or the other thing 

 8 that comes to mind when you I mention that is I 

 9 mentioned in one of the earlier slides we would 

10 like to not have these step function, technical 

11 conclaves where we establish everything technically 

12 and then wait about four years 'til we bring it up 

13 again. 

14 That would allow this to be a continual 

15 living, breathing process, and technologically, 

16 it's practically foolish not to engage in something 

17 like that because the communications is right 

18 there. 

19 We're sharing notes up here, but I agree with 

20 you, John. I see that as the same thing as the 

21 AERMOD implementation guide; something that's a 

22 living, breathing document, you know, that can take 

23 in information, can -- can, you know, respond in a 

24 timely fashion, and at the proper point serve as a 

25 stepping stone to changes in the guidance. 
 1 QUESTIONS/Audience Vol. 1, p. 207 

 2 So I think we might to change that frequently 

 3 asked questions into something similar to like the 

 4 CALPUFF implementation guide, to be able to be more 

 5 responsive along those lines. 

 6 So, in some ways, I think we have a mechanism 

 7 and example to do that, so --. 

 8 ROBERT PAINE: Robert Paine, ENSR. 

 9 The management of this model by EPA is maybe 

10 the first of a series of inviting the private 

11 community to provide models to EPA. 

12 I guess I'd like to get a clarification, how 

13 -- what is the actual relationship between the EPA 

14 and the model developer in this case? 

15 It's sort of -- it's not really written down 

16 anywhere that I can see. 

17 MARK EVANGELISTA: Boy, I'd love to answer that, but being a 

18 NOAA guy -- 

19 (Laughter). 

20 TYLER FOX: You will hear, I believe, tomorrow morning our 

21 approach in updating the EPA approved version of 

22 this model, which makes the process and the 

23 implications transparent to everybody. 

24 It -- we're going to have discussions tomorrow 

25 about model development issues. 
 1 QUESTIONS/Audience Vol. 1, p. 208 

 2 We have an example here of -- of two different 

 3 models that are both embraced in the regulatory 

 4 sense, and both born from two different ways or 

 5 approaches. 

 6 I think we have to be respectful and open to 

 7 multiple ways of developing these models. I 

 8 certainly don't prescribe to the "only from these 

 9 hands shall you use a model", so in coming from a 

10 lot of experiences in the photochemical world, you 

11 know, you've got a number of folks building very 

12 nice, scientifically sound, and fairly transparent 

13 open-type community style models that -- that serve 

14 a good purpose from the policy and from the 

15 research technical side. 

16 Mark mentioned CMAQ as -- as the, you know, 

17 as the party that releases the CMAQ model, and that 

18 community style approach is one that, as you saw on 

19 the vision statement, I think is something that we 

20 may want to look further to, but address the issues 

21 of proprietary models and -- and the like in the 

22 future. 

23 RICHARD PERRY: Dick Perry, Bee-Line Software. 

24 I think that this comment sort of falls in the -- 

25 fits in with the old song, the difference between 
 1 QUESTIONS/Audience Vol. 1, p. 209 

 2 theory and practice, where you are encouraging 

 3 people to -- to coordinate ahead of time, i.e., do 

 4 a protocol. 

 5 Well, it appears pretty obvious that, you 

 6 know, our community has gotten to enjoy the ability 

 7 to get guidance from the EPA through a protocol 

 8 prior to committing to too much work, but it seems 

 9 equally obvious that the people you have to submit 

10 to in this case, the Federal Land Managers, are 

11 either uncomfortable, or they just don't do 

12 business that way, because invariably the answer 

13 that comes back when they try to go through that 

14 process of submitting a protocol is; submit it and 

15 we will evaluate it. 

16 And that -- that leaves everybody really cold. 

17 And it's probably just the difference between the 

18 way they do business and the way we have been doing 

19 business in this community for years, but it is 

20 something that is probably one of the biggest 

21 irritants I have of new people approaching doing a 

22 CALPUFF project. 

23 STAN VASA: Stan Vasa from Southern Company. 

24 You mentioned about two enhancements to the 

25 model, the chemistry module, -- 
 1 QUESTIONS/Audience Vol. 1, p. 210 

 2 (Audio level is adjusted in conference room.) 

 3 STAN VASA: Thank you. -- as well as -- I can hear myself 

 4 talking -- as well as the -- the chemistry and what 

 5 was the second comment -- two modules that you 

 6 wanted to upgrade. 

 7 Do you have any target at this time as to when 

 8 you want it completed? 

 9 If so, is there any plan as to who is going do 

10 it, in the sense that is EPA going to fund that 

11 kind of upgrade, or is it going to be done by the 

12 model developer? 

13 MARK EVANGELISTA: Before anything about funding or even 

14 schedule, we're taking a very, very fundamental 

15 step back and finding out, is that something we 

16 want to focus on at this point? 

17 Are there -- in the full scope, are there -- 

18 are there settings, are there background values, 

19 are there components, chemistry modules, everything 

20 out there should be fair game at this point, and -- 

21 and looked upon as what is most valuable for 

22 whatever we plan to use this model for in the 

23 future. 

24 I -- I don't have at this stage, from a purely 

25 technical standpoint, any obvious priority to one 
 1 QUESTIONS/Audience Vol. 1, p. 211 

 2 thing or another. So we haven't gotten to the 

 3 priority point, therefore, the other issues such as 

 4 funding and time lines and who would do it, have 

 5 not -- have not been flushed out. 

 6 Now maybe some of these things will have 

 7 already been proposed in one shape or another where 

 8 someone has said, I find this particular module to 

 9 be weak, it needs to be fixed. This is what it 

10 will cost, this is who can do it, here's how fast 

11 they can turn it around. 

12 But in that context, it would be the only 

13 time those -- the deadlines and costs would have 

14 been addressed. 

15 We're still looking fundamentally at what 

16 aspects of this -- of this system do we want to 

17 start focusing our attention on, and in terms of 

18 who does it, I'm more concerned right now with who 

19 contributes in this group and the community 

20 at-large to identify those issues. 

21 So those questions will be answered in time, 

22 but we're still answering upstream questions at 

23 this point, or actually we're still asking upstream 

24 questions at this point. 

25 TYLER FOX: And you should know, I mean, we really are trying 
 1 QUESTIONS/Audience Vol. 1, p. 212 

 2 to get a lay of the land here, and what the 

 3 landscape is, and what the appropriate steps 

 4 forward are. 

 5 And by all means to the extent we find 

 6 something that we need to do, it's not going to be 

 7 a process of handing over a bunch of money to 

 8 somebody and let them do what they want with the 

 9 model. 

10 We are going to be actively engaged in the 

11 process of implementation and evaluation, and the 

12 like. 

13 We have to. That's our responsibility. So 

14 anything and everything that we do will be very 

15 transparent and will be vented, you know, through 

16 the workshop Mark showed, the workshop early next 

17 year, you know, you've got the other thing going on 

18 in Denver. I think there is going to be ample 

19 opportunity for us to walk through these things as 

20 we learn more and present what we see and what we 

21 feel are high priority and get input, and then at 

22 some point at the appropriate time, figure out, you 

23 know, how we should actually implement some of 

24 these things. 

25 But it's, I think, too soon right now to jump 
 1 QUESTIONS/Audience Vol. 1, p. 213 

 2 on any one of those aspects. 

 3 The only thing that I think is moving forward 

 4 fairly quickly is the thing on met data, and that's 

 5 what we're going to be talking about this 

 6 afternoon, because that's more broad than just 

 7 CALPUFF. That's -- that's AERMOD and the like. 

 8 So --. 

 9 MARK GARRISON: I'm Mark Garrison with ERM. 

10 One thing I -- I didn't see on the list of 

11 issues and things that the workers were going to 

12 address, and forgive me if I -- if I missed 

13 something, but the whole question of how does 

14 CALPUFF perform when you compare its predictions to 

15 measurements, how well does it do for some things, 

16 how well does it do for nitrates et cetera, et 

17 cetera. 

18 Can you provide some comment about that? 

19 MARK EVANGELISTA: Inasmuch as we would look at a particular 

20 mechanism, those evaluations would certainly take 

21 place. In the holistic performance evaluation of 

22 CALPUFF, no, we haven't talked about that. 

23 In fact, it would be quite surprising to me 

24 that something like that hasn't already occurred in 

25 numerous instances when someone has tried to apply 
 1 QUESTIONS/Audience Vol. 1, p. 214 

 2 this model in one way, shape, or another. 

 3 But the particular module, a particular 

 4 setting of ammonia -- background ammonia, 

 5 background ozone, those kinds of value settings and 

 6 sensitivities, I can't see how else we would 

 7 evaluate whether or not those apply or are 

 8 reasonable without doing what you described. 

 9 So microcosmically, we would conduct those 

10 things, so -- but I'm not so sure a holistic 

11 evaluation would take place until we've laid out an 

12 awful lot of the recommendations and put them in a 

13 lump and said, these look good, and let's see what 

14 they look like together, and -- and do it at that 

15 point. 

16 So -- so more of a -- intermittent steps to 

17 the end. 

18 MARK BENNETT: Mark Bennett, CH2M HILL. 

19 Just another comment, or I guess, 

20 recommendation here. 

21 As we know, CALPUFF has been promulgated prior 

22 to the imminent promulgation here of the AERMOD, 

23 and during the AERMOD discussions we talked about 

24 getting information out, both technical information 

25 and policy statements, by what I would consider 
 1 QUESTIONS/Audience Vol. 1, p. 215 

 2 reactivating the model clearing house. 

 3 So I think that CALPUFF having been out, that 

 4 we would need to -- or I'd recommend that we 

 5 reactivate the model clearing house for those types 

 6 of policy statements for CALPUFF as well. 

 7 TYLER FOX: Yeah, and it -- it should be clear to everybody 

 8 that the model clearing house is not particular to 

 9 AERMOD. It's broad, and all and in fact we're 

10 actually urging folks in the context of CALPUFF 

11 that these protocols or issues that come up with 

12 respect to these protocols be vented through the 

13 model clearing house process. 

14 One thing to remember, these -- these are 

15 technical memos for the model clearing house. 

16 Policy issues will -- will have to be addressed 

17 maybe coming in through the clearing house, but it 

18 will have to be addressed through separate policy 

19 memos. 

20 Again, we're focusing on the modeling and the 

21 technical aspects. Of course, there is -- it's 

22 hard to separate those technical policy issues, but 

23 I did want to make that -- that one clarification. 

24 MARK BENNETT: We should probably -- go ahead. 

25 STEVE LUND: Hello, my name is Steve Lund, and I'm with URS 
 1 QUESTIONS/Audience Vol. 1, p. 216 

 2 Corporation. 

 3 And I've been -- I've been running CALPUFF and 

 4 CALMET and doing a lot of processing over these 

 5 years, and recently had the opportunity to take a 

 6 harder look at how visibility calculations were 

 7 being made in the model. 

 8 And this is just my observation, one person's 

 9 observation, but it -- your methodology you 

10 incorporated is that right now you can take a one 

11 point and basically turn around, like maximum 

12 concentration is, and then you use that in order to 

13 determine that you change an extinction and you 

14 change a deciview. 

15 Looking at the definition of a deciview, and how 

16 extinction was developed, you have a concept of a 

17 distance involved. 

18 Right now, I've played with CALPUFF enough 

19 where I'd put in a string of receptors and 

20 basically integrated -- came up with a' integrated 

21 change in deciview over that line of sight, and it 

22 seems to work pretty good in reducing 

23 concentrations quite a bit. 

24 I'd like to see a potential method which would 

25 have somebody take a harder look at that and come 
 1 QUESTIONS/Audience Vol. 1, p. 217 

 2 up with a methodology that would better represent 

 3 how extinction happens in the real world and put it 

 4 into the model. 

 5 Now, like I said, this is more of a comment. 

 6 Give me some rebuttal. 

 7 I will continue to look at this and work on 

 8 it, but I think it's an important issue. 

 9 Thank you. 

10 TYLER FOX: And if you have any information to share, I mean 

11 I -- we gave your an e-mail address, so forward it, 

12 please. 

13 MARK EVANGELISTA: I have something to say. 

14 That's a great example of a technical issue 

15 that we haven't thought of, but not only has 

16 someone thought of it, but you've done a 

17 considerable amount of work on it already. I'd 

18 love to see what you've done. 

19 WARREN PETERS: John, were you raising your hand? 

20 JOHN VIMONT: John Vimont with the National Park Service. 

21 With regard to that last statement, the only 

22 thing to remember is is visibility. Visibility is 

23 an instantaneous phenomenon. The experience 

24 visibility is continuously. 

25 The way the analysis has been set up 
 1 QUESTIONS/Audience Vol. 1, p. 218 

 2 originally with IWAQM, and it's has been carried 

 3 through in the flag document, is we're looking at a 

 4 twenty-four hour average. 

 5 A lot of the integration, while not spatial, 

 6 is being done temporally, so there's an offset 

 7 there. 

 8 When we go to an integrated over receptors, it 

 9 forces us into a minimum of an hour concentration. 

10 So the effects will change dramatically, when 

11 you look at one-hour concentration predicted by 

12 CALPUFF versus a twenty-four-hour average. 

13 MARK EVANGELISTA: Thanks, John. 

14 I'd also like to acknowledge all the help John 

15 has provided in -- in getting this started. 

16 You were one of the IWAQM originals, I 

17 believe, and providing me with some -- some 

18 perspective and history, and also a good deal of 

19 technical know-how. 

20 I appreciate that very much. 

21 Anyone else? 

22 (No response.) 

23 MARK EVANGELISTA: Well, thank you so much, and I'll speak 

24 with you in a short while. 

25 WARREN PETERS: Thank you Mark and Bret. That will conclude 
 1 GRIDDED MET DATA/Panel Vol. 1, p. 219 

 2 our CALPUFF discussion, for the first part of our 

 3 program today. 

 4 Why don't we take a -- I'll say a 

 5 fifteen-minute break. We're a little bit ahead of 

 6 schedule and meet back here, and we'll have the 

 7 panel discussion on the gridded met data. 

 8 _______________________________ 

 9 (BREAK, 2:26 - 2:52 P.M.) 

10 _______________________________ 

11 WARREN PETERS: The last series of presentations this 

 

12 afternoon will address the gridded met data, 

13 gridded meteorological data for air dispersion 

14 models. 

15 We actually have planned two presentations by 

16 Dennis Atkinson, and then Mark Evangelista, and 

17 then we'll have a panel discussion where Dennis 

18 Atkinson will be leading that discussion with his 

19 esteemed colleagues. 

20 Meteorological data used in air dispersion 

21 modeling has expanded to include meteorological 

22 model outputs from the National Center of the 

23 Environmental Prediction; that's the NCEP, as well 

24 as other sources of met data. 

25 These data are used routinely in regional 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 220 

 2 scale modeling. For local scale modeling, these 

 3 model outputs can provide spatial coverage with 

 4 additional parameters for locations which are not 

 5 well served by National Standard Weather Service 

 6 output. 

 7 This session is designed to explore the state 

 8 of science, so these are simulated data output, and 

 9 engage in a discussion on the topic. 

10 So, that will set the tone this afternoon. 

11 And the first part of the presentation will be 

12 from Dennis Atkinson, from our group, who works 

13 with NOAA and Mark Evangelista, and he'll be 

14 talking to us about the overall plan, the 

15 advantages, and the issues in using the NWS 

16 product, so, Dennis. 

17 DENNIS ATKINSON: Thank you. 

18 I'm going to be leading the discussion today 

 

19 on the gridded met portion, and this was a 

20 presentation that was also presented basically at 

21 the regional modelers workshop this year in New 

22 Orleans, and there has been a lot of -- a lot of 

23 work lately that's been done to talk about gridded 

24 met data and incorporating it into local scale 

25 modeling. 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 221 

 2 In the past, there has been a lot of work done 

 3 in the regional scale arena, using gridded met 

 4 data, but we're now looking to using that in the 

 5 local scale modeling. Of course, CALPUFF now uses 

 6 a gridded met data, but we are also looking to 

 7 using it in AERMOD and more contemporary NWS-type 

 8 models. 

 9 Just as an outline, I'm going to provide a 

10 background of what I'm going to talk about 

11 here. 

12 I'll also lay the groundwork for what type of 

13 work we're doing here at EPA as far as getting 

14 gridded met data into AERMOD and CALPUFF; also 

15 report out on a gridded met data that work group 

16 that was formed earlier this year, and some good 

17 discussions came out of that, and also some new 

18 developments at NOAA that I discovered when I went 

19 on a trip over to NCDC. 

20 First of all, as a background, back in 1998, 

21 John Irwin initiated some requests internally, that 

22 was when John was actually at EPA, to incorporate 

23 to -- or to actually ask for some seed money for -- 

24 in EPA's budget to incorporate gridded met data 

25 into local dispersion models. 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 222 

 2 At that point, AERMOD was very much underway; 

 3 it was what was going on, and there was a lot of 

 4 effort going toward AERMOD, and so -- and there was 

 5 other items going on as well, so the money just 

 6 really wasn't there. 

 7 There was a lot of interest, but the money 

 8 wasn't there. 

 9 Fast forward to 2000, the Seventh Modeling 

10 Conference, there was a panel discussion, and some 

11 presentations made on gridded met data, as well. 

12 And, of course, last year, there was some 

13 renewed interest in "Irwin's World" just because of 

14 CALPUFF being used more extensively, the gridded 

15 met data in CALPUFF being more visible, there was 

16 just a lot more visibility of the gridded met data, 

17 and so that renewed some interest in the gridded 

18 met information. 

19 And last year we initiated in September the 

20 gridded met data project which I will go over that 

21 with you and let you know what's going on with 

22 that, and what we plan to do here at EPA. 

23 First of all, you might want to ask, well, why 

24 do we want to use gridded met data? 

25 Well, first of all National Weather Service 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 223 

 2 surface and upper air sites are typically not 

 3 collocated. 

 4 And that sets the -- the case there for 

 5 discontinuity between your surface data and your 

 6 upper-air data. And there is a lot of 

 7 permutations that causes and a lot of problems from 

 8 the get-go. 

 9 Also, this gridded met data, because it's more 

10 spatially representative, it can also be more 

11 representative than the distant NWS sites that are 

12 often anywhere from fifty (50) to a hundred (100) 

13 miles from your modeling site. 

14 Also, the gridded data has many more 

15 parameters that are calculated, and they provide a 

16 lot more information about the atmosphere. 

17 They provide a lot of surface characteristics, 

18 a lot of physics parameters that are needed to 

19 upgrade our models, to incorporate. 

20 Like I was saying, state of the science 

21 product, it -- gridded met data incorporates a lot 

22 of cloud physics, land-air-sea moisture exchanges. 

23 Spatial density, of course, is typically higher 

24 than you would get for National Weather Service 

25 data information,. 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 224 

 2 Also, the data is typically NOAA approved as 

 3 NCEP typically runs the models that generate this 

 4 data. And currently MM5 is the kind of model of 

 5 choice, and that data is typically accepted pretty 

 6 generally throughout the modeling community. 

 7 Other reasons that we would probably want to 

 8 consider gridded met data, it's an advancement of 

 9 the science, and as was pointed out this morning in 

10 the introductions, the EPA has been tasked to 

11 become more science oriented and advance the 

12 science. 

13 One committee called the Clean Air Act 

14 Advisory Committee actually made recommendations to 

15 EPA to incorporate more advanced air quality 

16 modeling tools into our air dispersion models, and 

17 in doing this, would also pair National and 

18 regional scale modeling more with local scale 

19 modeling, which is something that we're really 

20 trying to do is bring all the atmospheres together, 

21 the regional and the local scale, and that way we 

22 can use the same meteorology to drive both types of 

23 models. 

24 We typically want to separate those two types 

25 of models and those two regimes, but they're really 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 225 

 2 coming together fast. 

 3 Also, the National Academy of Science has also 

 4 suggested that models in a four dimensional 

 5 simulation mode would provide superior air quality 

 6 forecasts, and as you know, AIRNOW employs air 

 7 quality forecast information in its air quality 

 8 forecasts. 

 9 And these are the URLs that you can go to 

10 reference this information. 

11 Which gridded met data product should be used? 

12 There is a whole host of products that are 

13 available from NCEP. Here's a few of them. 

14 GFS, used primarily for aviation. It's 

15 calculated or produced four times a day at zero, 

16 six, twelve and eighteen Z, has a very coarse grid. 

17 The ETA model, it's a regional mesoscale 

18 model. It's produced four times a day at a twelve 

19 kilometer (12km) grid. 

20 The NARR model is produced every three hours 

21 with a thirty-two kilometer (32km) grid. 

22 The RUC (rapid update cycle) was produced 

23 every three hours and recently was -- went to a 

24 twenty kilometer (20km) grid spacing. 

25 And, also, MM5 is available at a very mini- -- 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 226 

 2 large host of a grid sizes; typically thirty-six 

 3 (36), some are twelve four (12/4) and even at one 

 4 kilometer domains. 

 5 And the beauty of the MM5 data, as most of you 

 6 probably know, is it comes hourly. And that is 

 7 what we need to drive our local air dispersion 

 8 models at this point. 

 9 Another product that's going to become 

10 available is the WRF model. It's basically in 

11 development. It's the weather and research 

12 forecasting model, and it's being developed by a 

13 host of Government and nongovernment entities, 

14 and it's slated to replace MM5 sometime in the 

15 future. Currently NCEP runs at eight kilometers, 

16 and has high resolution window forecasts with 

17 that. 

18 Also, just to explain a little bit more 

19 what's going on in the modeling world, the 

20 regional long - -- long-range models are currently 

21 using MM5 to drive CMAQ, CALPUFF, those types of 

22 models, of course, CALPUFF is a medium range 

23 transport model. 

24 The local scale models use NWS or on-site. 

25 That would include AERMOD, and the on-the-way-out 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 227 

 2 ISC model. 

 3 But what we would like to do is use some 

 4 gridded met product. 

 5 It doesn't have to be MM5, but this is just 

 6 for illustration purposes, to drive both sets of 

 7 models. And at that point we can study the 

 8 interactions of the long-range and the local scale 

 9 models a lot better and not have the discontinuity 

10 of meteorology to be in the way. There is enough 

11 problems to be solved without having differences of 

12 meteorology. 

13 And what we are doing here at EPA, back in the 

14 spring OAQPS, Office of Air Quality Planning and 

15 Standards, offered up an opportunity for some 

16 innovative projects to compete for some dollars, 

17 and we put forward this initiative to explore the 

18 input of gridded met data into local dispersion 

19 models. 

20 And out of about twenty-five (25) entries, we 

21 were one of, I think, two or three winners. So we 

22 were proud of that. And we got fifty K ($50K), 

23 and so we will shortly begin embarking on a project 

24 to explore this possibility in very technical 

25 terms. 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 228 

 2 Just to go into some details about the gridded 

 3 met project, its goal is to incorporate and assess 

 4 gridded met data into the dispersion modeling 

 5 world. The steps basically, one, we just need to 

 6 review MM5 into CALPUFF. Currently, MM5 is 

 7 accepted in the CALPUFF via CALMM5, and soon CALRUC 

 8 and CALETA will also be able to be used pretty 

 9 readily by CALPUFF. 

10 We need to educate and learn how MM5 is 

11 processed through CALPUFF to apply similar 

12 procedures to AERMOD. 

13 Our goal really is to get gridded data into 

14 AERMOD. 

15 So in doing that, you can run MM5 both at 

16 thirty-six (36) and twelve (12) kilometers, and the 

17 NWS data through CALMET and analyze the results, 

18 which I know a lot of that's been done, but this is 

19 a learning process as well. 

20 And also, once you've run the met data of MM5 

21 and NWS through CALMET, you want to use that, and 

22 then put it in process through CALPUFF. 

23 And next our primary goal of the project is to 

24 incorporate MM5 into AERMOD, and basically there is 

25 two parts to this. 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 229 

 2 And part one is the, of course, the first part 

 3 that we are concerned with, and it's to use current 

 4 variables that are needed by AERMET from MM5 to 

 5 drive AERMOD. 

 6 That sounds like a fairly simple task, but 

 7 whenever you start trying to pair up variables 

 8 one-to-one, that's really not as simple as it 

 9 sounds. 

10 You've got a lot of different ways the 

11 variables are measured, how they are characterized, 

12 and that kind of thing, parameterized. 

13 So that's taken a little bit more than we 

14 anticipated. And, also, the second part of 

15 incorporating the MM5 data or gridded met data into 

16 AERMOD, is to utilize additional variables that are 

17 available, courtesy of MM5 to improve the actual 

18 physics within AERMOD. 

19 Of course, we all know that AERMOD is an 

20 improvement over ISC, but if we can drive AERMOD 

21 with more sophisticated inputs, we can improve the 

22 model that way as well. 

23 The way we plan to do this is to process MM5 

24 for a single grid cell, and also for NWS data and 

25 input that into AERMOD and for part one, AERMOD 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 230 

 2 will not be modified to accept more than one grid 

 3 -- grid data of information. 

 4 If we did that, it would become sort of a 

 5 pseudo-CALPUFF, which is not what we want to do 

 6 initially. 

 7 We want to leave AERMOD intact and so the way 

 8 we want to do that is to run AERMET using MM5 and 

 9 NWS data and analyze the results, and this would be 

10 for collocated data. 

11 We would get a web, excuse me, we would get 

12 information at a point that contains NWS data and 

13 also the grid data that was run through MM5 and run 

14 both of those through AERMET, and compare the 

15 results. 

16 And once we run the information through 

17 AERMET, then we are going to run it through AERMOD 

18 and get the output there and analyze the results 

19 using both sets of data. 

20 Looking at Part two, this is where we would 

21 want to modify possibly AERMOD and utilize new 

22 variables that are available to us from the MM5 

23 data set to enhance the physics and other features 

24 of AERMOD, you know, possibly replace modules. I 

25 mean, this would be a pretty extensive undertaking, 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 231 

 2 but, you know, we want to see what we can do to 

 3 utilize gridded met data to the fullest. 

 4 So we would run the -- the -- possibly the 

 5 modified AERMET using MM5 and NWS and analyze those 

 6 results and then run AERMOD with the modifications 

 7 and compare it with the MM5 output versus NWS 

 8 output. 

 9 Thirdly, if we get to it, we also want to look 

10 at some of the forecast models, RUC, ETA and WRF, 

11 and also try to incorporate those into CALPUFF and 

12 AERMOD and see exactly what kind of changes we get 

13 from MM5 type data versus forecast type data. And 

14 we would do the same type of analysis that we would 

15 in the other part one, and so -- and also we want 

16 to look at WRF, because it's going to be coming 

17 down the line, and that's at the point where we 

18 would take a look at WRF, and by the time we get to 

19 this stage, I'm sure WRF will be more well 

20 developed and that type of thing. 

21 So our end product for the N- -- for the 

22 gridded met data project would be an IT tool 

23 basically that would accept multiple grid met 

24 inputs, given MM5, RUC, whatever we want to, you 

25 know, allow it to accept. 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 232 

 2 And to process this data and make it 

 3 compatible with the models that they're going to be 

 4 used for, and -- which would be AERMOD, CALPUFF and 

 5 any others that we, you know, so choose. 

 6 And I also compute the fields from the gridded 

 7 met data that are needed by the recipient model. 

 8 That could be land use, I mean it could be a whole 

 9 host of surface parameters, whatever fields need to 

10 be computed, that tool would also -- we would like 

11 for that to also do those functions. 

12 Just to change gears a little bit, I put 

13 together earlier in the year a gridded met data 

14 work group, and this was just kind of as a 

15 precursor to this project to see what kind of 

16 issues there are out there in dealing with MM5 

17 data. And, of course, there are many, and there 

18 will be others that will pop up as we get into it. 

19 We had representation from a couple of 

20 regional EPA offices, Fisheries and Wildlife 

21 Service, many of the states participated, and we 

22 also had a Canadian participant. 

23 It formed in February. We had four calls. 

24 Our primary focus was seven issues that were 

25 related to gridded method data, and also at the 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 233 

 2 end, I took a survey of those states participating 

 3 just to see what their experiences were in using 

 4 gridded met data. 

 5 The first issue we looked at was identifying 

 6 additional met parameters available from gridded 

 7 output. That was a useful from AERMOD. And these 

 8 are just a very few, but these are some that came 

 9 up and were discussed and there was pretty well 

10 consensus that these things really need to be taken 

11 a look at, and TKE, currently AERMOD uses 

12 similarity theory for the protected boundary layer, 

13 but we might want to look at using TKE for some of 

14 that dispersion. 

15 Vertical velocity could potentially replace 

16 convective velocity scale. That's readily 

17 available in MM5 output. 

18 There is actually a PBL height in MM5 output. 

19 I'm not sure how reliable and what it uses to 

20 generate the PBL, but that's something else that 

21 could possibly be used in -- in order to calculate 

22 planetary boundary layers. 

23 Surface sensible heat flux and latent heat 

24 flux is currently used in AERMOD, and that could be 

25 a parameter that we would directly feed out of MM5. 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 234 

 2 Terrain elevations, of course they're very 

 3 important, and I believe that's in MM5 as well. 

 4 And that -- that would be used to determine the 

 5 dividing streamline, and, of course, which is very 

 6 important for the complex terrain situations. 

 7 Land use category, that is also in MM5, but we 

 8 have to use caution when -- when looking at that, 

 9 because MM5 is, of course, gridded information and 

10 the land use is averaged over the grid cell, so 

11 you're going to kind of wash out some of the more 

12 distinct features that you may want to capture. 

13 So that's something that would need to be 

14 looked at. 

15 The second issue was dealing with multi-grid 

16 source fields. 

17 How would a single met source model handle met 

18 data from multiple grid cells. 

19 That basically entails sources that encompass 

20 several grid cells, over a multi-grid area, and you 

21 know, do you pick the center of the -- center cell 

22 that represents the source; I mean, do you do it 

23 spatially, do you do some sort of weighted average, 

24 just how to you handle that? 

25 Here I've shown that you could make multiple 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 235 

 2 runs with each grid cell, and then, you know, do 

 3 some sort of adding together in space and time, but 

 4 that's -- that's not a very good solution. 

 5 Here, you, like I said before, you could 

 6 possibly use a center grid cell for the source 

 7 group, but you may want to use a weighted average 

 8 include the other source areas; or possibly use 

 9 some sort of interpolation scheme of all the grid 

10 cells. 

11 Of course, you would probably want to do some 

12 sort of weighting average for each grid. 

13 Another issue we looked at was, is on-site 

14 data necessary for grid cell data to be used -- 

15 excuse me. 

16 Is on-site data necessary if grid cell data is 

17 used? 

18 This came up quite a bit. On-site data has 

19 been relied upon quite a bit. It takes many 

20 dollars, thousands of dollars to -- to get 

21 on-site met data for sources. And it's heavily 

22 relied on in certain areas, certainly in complex 

23 terrain situations and situations where the met 

24 data isn't captured by National Weather Service 

25 data. 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 236 

 2 So, at what point do you determine that 

 3 on-site data is still valid and you don't want to 

 4 use gridded met data? There is a lot of issues 

 5 that need to be looked at and resolved in that 

 6 vein. 

 7 Gridded data has also been nudged to create a 

 8 flowing regime which I mentioned earlier, and 

 9 that's another reason why you may or may not want 

10 to use your on-site met data. 

11 As -- as the grid resolution gets smaller and 

12 smaller, the issue of on-site met data may become 

13 -- it may be more blurred, or it may become more 

14 clear. It's not always easy to -- to make that 

15 determination. 

16 But for now, it looks like on-site met data is 

17 useful. 

18 As was mentioned earlier, there's always data 

19 representativeness issues. Of course, AERMOD has 

20 those, and any time you're dealing with 

21 meteorological data, data representativeness is at 

22 the core. 

23 If you are using local, excuse me, if you are 

24 trying to capture local effects, it may be 

25 necessary to incorporate some local data. 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 237 

 2 Depending on your grid scale that you are 

 3 using, you may need to capture that by on-site or 

 4 NWS type data. 

 5 One of our work group members had had 

 6 extensive work in MM5, and exactly what you can 

 7 capture with the number of grid cells, and his 

 8 study showed that the spatial resolution of MM5 was 

 9 basically three to five times the grid spacing. 

10 So, if you have, say, a mountain feature 

11 that's only two grid spaces, you probably won't 

12 capture that in MM5. It may just kind of get 

13 washed out. It may be a little bit of a blip, but 

14 you're -- you really won't capture, you know, the 

15 detail that you will need. 

16 In looking at WRF, he said that he had done 

17 some preliminary work with WRF, and it basically 

18 has a bit of a tighter resolution, and it kind of 

19 comes down to about three times the grid 

20 spacings. 

21 Sensitivity tests, of course, are necessary to 

22 compare the gridded met data with the traditional 

23 National Weather Service data. It's not done to 

24 prove which is better, but to explain the 

25 differences. 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 238 

 2 This is something that our work group was very 

 3 clear on. 

 4 I don't think we're going to try to prove or 

 5 disprove one data set is better than the other. 

 6 They definitely will be different, because 

 7 they are calculated. One is calculated; one is 

 8 actual measured parameters, but we want to note 

 9 what the differences are, and then try to explain 

10 those in a rational way, and in a way that we 

11 understand and can accept. 

12 Also, there is an issue on the number of years 

13 to be used. Currently three years have been used, 

14 basically due to data availability for 

15 applications. Of course, in the Appendix W, it 

16 clearly states that five (5) years of met data 

17 should be used when available. 

18 The grid spacing requirement, of course, the 

19 lower grid resolution captures more of the local 

20 effects which I had mentioned, and that, of course, 

21 would just be common sense, but it's very important 

22 whenever you're trying to capture local effects to 

23 get a smaller grid, to get land, sea interactions, 

24 upscale/downscale flow in valleys. 

25 There is a lot of local effects that you can't 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 239 

 2 capture if your grid spacing is just too far 

 3 apart. 

 4 And this next part, the thirty-six kilometer 

 5 (36km) resolves met features from about a hundred 

 6 eight kilometers (108km) to a hundred and eighty 

 7 (180km), so certainly that's a very coarse grid, 

 8 most people agree. The twelve kilometers is 

 9 actually getting to a more useful stage, although a 

10 lot of situations, especially toward complex 

11 terrain, that's still fairly coarse, and there are 

12 runs from MM5 that are made at the fourth kilometer 

13 grid spacing level, and that, of course, captures 

14 much more information. 

15 Complex terrain, as I mentioned earlier, 

16 certainly the western states would need higher 

17 resolution, particularly in the Rockies and the 

18 close vicinities of it. Of course, you've got 

19 other land features in the west, you've got bluffs, 

20 gorges, upscale and downscale slopes, all kinds of 

21 complex terrain-related situations that would 

22 require very fine grid resolution. 

23 And, of course, when we're talking about local 

24 scale modeling, the fence line is of paramount 

25 importance, and so, you know, should we use NWS 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 240 

 2 data, on-site or gridded, and that's what we'll be 

 3 taking a look at in our study here. 

 4 And what grid resolution would capture 

 5 sufficient detail to use for the MAQ/PSD 

 6 applications, toxics, urban situations, and other 

 7 light types of modeling? 

 8 Those are questions that we will need to 

 9 address and need to look at in detail. 

10 Also, there was some known shortcomings of 

11 gridded met data, maybe they're not shortcomings, 

12 but artifacts of the data itself. There was some 

13 group members that brought up some precip 

14 inconsistencies, lack of calms, and I think that 

15 there were some others, but these are the two that 

16 are highlighted. 

17 For precip., this should be cross-checked, 

18 probably with actual observations when you use it 

19 for wet deposition. I'm not sure, you know, how 

20 much discrepancy there is, but at this point that 

21 should probably be something that people should 

22 cross-check. 

23 MM5, I keep saying MM5, this could be mean any 

24 gridded met data model. Typically has fewer calms, 

25 and this would result that steady state models 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 241 

 2 would use more of the hours to calculate the 

 3 concentration estimates, which is not a bad thing, 

 4 but this could lead to a higher design 

 5 concentrations, because as you get -- as you 

 6 incorporate lower wind speeds, of course, your 

 7 concentrations that you get out of the model would 

 8 typically be higher. 

 9 Another issue we looked at was, if given the 

10 choice, where would we want the gridded met data to 

11 reside? 

12 Basically, this is a logistical question, and 

13 because there is MM5 type data sets all over the 

14 country, a lot of the RPOs are creating their own 

15 data sets, and so, you know, should we go to 

16 different people for the data sets? 

17 Should they all be in one place? These are 

18 also issues that, you know, we should look at. 

19 Other logistical itsu- -- issues, excuse me, 

20 such as computer resources, acquisition of data, 

21 file sizes, these are not -- are not issues that 

22 cannot be overcome. These are just more logistics, 

23 and kind of implementation type issues. 

24 Another thing, the data that's used in their 

25 dispersion modeling typically, or should be public 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 242 

 2 domain data and not proprietary so that everyone 

 3 can access this data, replicate any model runs that 

 4 -- that need to be done to verify, and -- and 

 5 that's been an issue as of late with some data. 

 6 Data portability, of course, is important. 

 7 Gridded met data is typically very large in size, 

 8 so it needs to be in a format so that it can be 

 9 easy transported from place to place. 

10 And another aspect is that since we're trying 

11 to merge the -- the met data that's used for 

12 gridded and local scale models, we are becoming 

13 more of a, you know, one atmosphere environment, 

14 and that's -- that's the way the modeling world is 

15 just tending to divert -- or excuse me, converge, 

16 to. 

17 Just to take a look real quickly at the 

18 gridded met survey that I did, only twenty of the 

19 fifty (50) states reported, so, we asked for three 

20 pieces of information; how much -- how much 

21 experience do you have in gridded met data? 

22 What is the source of the data if you do use 

23 it, and any other relevant information. 

24 Basically, twelve (12) out of twenty (20) had 

25 some experience with gridded data, and it was 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 243 

 2 basically in relation to CALPUFF. 

 3 Eight of them said they had no experience, and 

 4 those that didn't respond, I presume that they had 

 5 no experience. 

 6 Some other issues that are very important that 

 7 we saw coming out of the gridded met data work 

 8 group, was education for the local modeling 

 9 community, gridded met data is not something that 

10 we're that familiar with, and I include myself in 

11 that group. 

12 So we have to educate ourselves and educate 

13 each other on this new type of data. 

14 And we will probably hear an EPA rule assist 

15 in that. And, also, we would like to partner and 

16 have an ongoing dialogue from EPA to the regions 

17 and states which we've already initiated in order 

18 to facilitate this, maybe conversion, if you will, 

19 from National Weather Service to gridded data. 

20 We will certainly welcome and want to work 

21 with all of you, and any -- any studies that you 

22 have done, you're certainly welcome, and we would 

23 like to share that information. 

24 Back in May I was fortunate enough to go to a 

25 workshop in Asheville on NOAA data, sponsored by 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 244 

 2 the National Climatic Data Center, and just a 

 3 little bit of information of note that I thought 

 4 would be good to pass along; so availability of the 

 5 NCEP products. Of course, the NCDC archives 

 6 gridded met data started in 2002. 

 7 They also had a web area called NOMADS, NOAA 

 8 Operational Model Archives and Distribution System, 

 9 and it's basically a collection of portals to 

10 gridded met data, and this is the URL. 

11 And if you go to that URL, this is what you 

12 see. There is a whole host of gridded products 

13 there at you finger tips. 

14 As I mentioned earlier; RUC actually went from 

15 twenty (20) to thirteen kilometers (13km) earlier 

16 in the summer, and according to some sources at 

17 NCDC, WRF will be stored by NCDC around April of 

18 next year. 

19 Also, there is another web area, called CLASS, 

20 Comprehensive Large Array data Storage System. 

21 This is an IT tool, as well, very similar to 

22 NOMADS, and it basically archives geo-stationary 

23 data, a data that comes from satellites and the 

24 like, a remote sensing type products. 

25 And according to the workshop I went to, it's 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 245 

 2 kind of exploding, and there is a lot of Government 

 3 agencies getting on board, and in the next ten (10) 

 4 years they expect the volume of information to go 

 5 to a hundred 

 petabytes. That's quite a bit of 

 6 data. 

 7 And, also, they also said that they would 

 8 probably store MM5 data at sometime in the future, 

 9 and I'm trying to keep my finger on that pulse. 

10 This is just a -- the portal out to the CLASS 

11 web site. You -- like I said, you can get a whole 

12 host of data just by that pop-down menu, and that's 

13 all I have. 

14 WARREN PETERS: Any questions? 

15 DENNIS ATKINSON: Anyone have any questions, remarks? 

16 (Microphone is being passed to audience.) 

17 JOSEPH SCLERY: I am Joe Scire from Earth Tech, and I had a 

18 couple of comments and questions. 

19 One is about the use of MM5 data and other 

20 sources of data. 

21 One option you might want to consider is using 

22 CALMET as the processor to get from the prognostic 

23 fields into the -- M- -- into the MM5-model -- or 

24 CAL- -- CALPUFF -- or CALMET near-fields, because 

25 it does do a lot of that translation of variables 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 246 

 2 and calculations of evaluated parameters and other 

 3 things. 

 4 There are currently four programs available, 

 5 CAL MM5 and then a database is CAL-ETA, CAL-RUC and 

 6 CAL- RAMS which will do that translation for you. 

 7 So, it's a lot of what you would need to -- to 

 8 have done is done. 

 9 The other point about this is, using CALMET 

10 offers another feature which is that it will take 

11 the grid resolution of the CALMET simulation and in 

12 reducing the grid spacing or whatever the 

13 prognostic grid spacing is, maybe there's six or 

14 twelve or four kilometers down to a scale that 

15 might really better reflect a local effects. 

16 You can run CALMET at, say, two hundred meter 

17 resolution very much more efficiently than you 

18 could run a prognostic model of that resolution. 

19 And then, one other point is that there is a 

20 version of -- a program that will take CALMET 

21 output and put it into the MR format, so all of the 

22 steps really have gone to MM5 processing it into 

23 CALMET ready for viewers, and then processing the 

24 CALMET output into AERMOD fields at -- all of those 

25 steps have been done. 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 247 

 2 The other -- the other comment is about the -- 

 3 the use of MM5 or other prognostic filing 

 4 parameters. 

 5 It should be tested carefully because there 

 6 have been many comments that the prognostic models 

 7 might in fact do not as well as, say, AERMET and 

 8 CALMET on certain bundling parameters. 

 9 So although they're -- it's certainly 

10 sophisticated models, they're not necessarily 

11 better in -- in developing the bundling parameters 

12 for this version. 

13 DENNIS ATKINSON: Exactly, and that's -- that's another 

14 reason, Joe, that we want to test these and really 

15 rigorously look at the results. 

16 ALAN CIMORELLI: Al Cimorelli. I'm -- I was -- I had exactly 

17 the same comment about CALMET. 

18 I think it's -- in fact, there was a study 

19 that we had done trying to figure out how we could 

20 get the finer resolution for driving CMAQ and we 

21 -- we had tried to take a -- a non-turbulent 

22 resolve MM5 run and see if we could diagnose down 

23 to -- with CALMET and use it drive CMAQ, and that 

24 actually worked out pretty well. 

25 And a comment regarding the multiple source 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 248 

 2 situation where you were talking about figuring out 

 3 doing weighted averages or what-have-you. 

 4 It occurred to me that maybe a way of looking 

 5 at this and certainly would have to be tested, is 

 6 to deresolve your MM5 run or your WRF run and look 

 7 at, if you have a -- if you have a thirty kilometer 

 8 (30km) domain or a forty kilometer (40km) domain 

 9 for your -- for your model -- for your modeling and 

10 run, and you get multiple sources of it within 

11 there, why not deresolve and only have a forty 

12 kilometer (40km) grid, because you're going to need 

13 to pick one -- one particular grid resolution. 

14 So I think one of the things that these 

15 numerical models do give you is the ability to vary 

16 your resolution depending on the kind of -- on the 

17 kind of problem that you have, and since -- since 

18 the model you're trying to use is a steady state 

19 model, you're only going to be able to put one 

20 particular, you know, parameter in there. 

21 I think the real advantage of this is that you 

22 do get profiles of wind, okay. 

23 Next, I'm not sure I understand why you would 

24 want to go through AERMET. 

25 If you are going to be running MM5 and you're 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 249 

 2 generating this stuff, you know, it seems to me 

 3 that the -- that the end game might be to replace 

 4 AERMET, except that -- except that you may, as Joe 

 5 pointed out, you know, AERMET may be able to do a 

 6 better job of generating new U star and W star and 

 7 things of that nature. 

 8 The other thing is TKE. When -- when I saw 

 9 that TKE up there, we -- we had tried to run -- we 

10 ran WRF and they constructed a WRF profile for 

11 AERMOD and ran it through there and couldn't figure 

12 out what to do with the TKEs, probably because they 

13 don't know how to do it, but you have to partition 

14 that energy between the lateral and vertical in 

15 order to the CBCMW, so I'm not sure how to do that. 

16 Maybe there are people in the room who do know how 

17 to do that, but I don't. 

18 You're going to have to think about that. 

19 And finally, I think this, for me, is probably 

20 the most significant. I -- I would love to see 

21 some work done where you would take one of these 

22 MM5 runs and to take a -- a grid cell inside an 

23 urban area, and look at an adjacent rural area and 

24 see if these -- if this model is characterizing the 

25 urban boundary layer, relative to the adjacent 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 250 

 2 rural boundary layers, if you are getting -- if 

 3 you're getting, for example, at night with a -- and 

 4 the time coincident where you're getting a negative 

 5 heat flux in the ur- -- in the rural area and a -- 

 6 and a positive heat flux in the urban area, that 

 7 may be a way, as I pointed out this morning, for us 

 8 to really reformulate the urban part of the AERMOD 

 9 model. 

10 Now, in the -- in the jubilee, there was -- at 

11 -- in the last two days, there was some discussions 

12 about the urban version, there is an urban version 

13 of MM5 and an urban version of WRF, and so one may 

14 want to look at that, as well, because obviously 

15 you need to look at the urban canopy and so on, 

16 a reasonable representation of the urban boundary 

17 layer, because I can -- and I saw that the one WRF 

18 front that I looked at, there were four days in a 

19 row where you -- where you never had a negative 

20 heat flux. 

21 You had a positive W-STAR all through the 

22 night. 

23 You know, I'm saying to myself, what am I 

24 going to do with this information, you know, assume 

25 that as soon as you go to night, you're not going 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 251 

 2 to have any convection and so on and so forth. 

 3 So that would be the part of the study that I 

 4 think would be really important. 

 5 (Microphone is passed to another member of the 

 6 audience.) 

 7 RYAN GESSER: I'm Ryan Gesser from Trinity Consultants. 

 8 I have two questions. They're probably 

 9 dangerously general in nature, but I'll ask them 

10 anyway. 

11 The first one really follows on Al's comment 

12 and I'd just -- to be more specific, there was a 

13 guidance document, I believe it was in the '98 time 

14 frame, called Minimum Meteorological Requirements 

15 for AERMOD. And I know many of the authors are in 

16 the room. 

17 That had several important conclusions and one 

18 of which, I think, was relevant here to what Al was 

19 talking about, is the point being that AERMOD, 

20 there was a step-up from ISC was still simplified 

21 enough that it wouldn't necessarily benefit from so 

22 much more refinement, so had -- had you considered 

23 that in this context, and -- you know -- basically 

24 the same question that Al asked, is why not direct 

25 efforts instead into improving AERMOD, rather just 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 252 

 2 into another model? 

 3 The second question was more to whether -- or 

 4 to what extent EPA is sharing resources 

 5 internally? 

 6 About ten years ago, when I was in graduate 

 7 School, I shared an office with a woman who is now 

 8 mid to, I think, to an upper level managing in -- 

 9 at EPA working with CMAQ, and in CMAQs, and I don't 

10 believe I see her here in the room, which is kind 

11 of an indication that, you know, that they use MM5 

12 data routinely for their level of modeling, but, 

13 you know, I have a feeling if you ask her, or 

14 someone else in that unit, they might say, oh, 

15 well, we've got some definite ideas, I can see how 

16 that would be done or how we could get folks to do 

17 that. 

18 So I was wondering just, if you could comment 

19 on that level of -- of collaboration, and even 

20 beyond the EPA campus here, in addition to the 

21 private sector and the different permitting 

22 components of EPA, also into the University 

23 communities that do -- tend to do a lot of this 

24 modeling for research purposes, but which are 

25 ultimately used by EPA. 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 253 

 2 DENNIS ATKINSON: On your first question about, you know, why 

 3 -- why do we want to explore this with AERMOD, we 

 4 are looking down the road, and it does appear that 

 5 the near-field modeling is going to converge as 

 6 well, as well as the regional and the local scale. 

 7 We kind of see AERMOD and probably CALPUFF 

 8 somehow coming together at some point. 

 9 We don't know exactly how that's going to play 

10 out, but right now, you know, AERMOD is being 

11 promulgated, and ISC had a pretty long shelf life. 

12 We are expecting AERMOD do have a fairly long shelf 

13 life. 

14 So, we are addressing this for AERMOD, 

15 because we expect it to be around a while. 

16 But I do -- I do take your comment well, 

17 because it does appear that the CALPUFF-type model 

18 is going to be the model of the future. 

19 We've had some of those discussions. 

20 JOHN IRWIN: Dennis? 

21 DENNIS ATKINSON: Yes. 

22 JOHN IRWIN: This is John Irwin, for the stenographer, again. 

23 What I was going to suggest goes along with 

24 what Al and others have said here, and if we're 

25 thinking down the line, and we're thinking that 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 254 

 2 things are going to harmonize between CALPUFF and 

 3 AERMOD, and there was a direct, should we say 

 4 suggestion, that we look to see how CALPUFF is in 

 5 harmony right now with the steady state AERMOD. 

 6 You have a perfect opportunity here. If you 

 7 run National Weather Service data, or gridded data, 

 8 through CALMET and look at the fluxes and the 

 9 things that come out as it now sits, and then run 

10 National Weather Service data through AERMET, you 

11 can now compare the Monin-Obukhov, friction 

12 velocities and mixing heights that come out, then 

13 you can look back into CALMET and see whether it 

14 could be improvements made to CALMET so that they 

15 are in closer accord. 

16 We were talking about what things needed to be 

17 updated in CALMET. This would be a perfect way of 

18 exploring. Maybe there is some improved 

19 parameterizations that are now currently in AERMET 

20 that could be incorporated into CALMET, and they 

21 the -- the two processors would start to generate 

22 very similar mixing heights, very similar friction 

23 velocities, and by that means you are upgrading 

24 CALMET for the future, and at the same time you 

25 aren't creating a discontinuity with AERMOD. 
 1 GRIDDED MET DATA/Dennis Atkinson Vol. 1, p. 255 

 2 DENNIS ATKINSON: Yes, that's -- that's basically what we 

 3 would like to do, and that's part of what this 

 4 tool is about is to have one -- one processor for 

 5 the met data. Up to now, we've had ISC 

 6 processors, AERMOD processors, and there's CALPUFF 

 7 processors. 

 8 And this is kind of a union of all of that, 

 9 and we're -- we've already thought about that, but 

10 your point is well taken on how to do that. 

11 MARK EVANGELISTA: Let me interrupt you for one second. 

12 Some of the questions, I think, that I have 

13 heard so far, would be more appropriate to be 

14 addressed after -- once we get to the panel. 

15 I don't mean to discourage anybody from asking 

16 these questions at all, but some of the things that 

17 I'm going to talk about in a short time, I think 

18 would address some of your concerns, and I'd like 

19 the feel -- to get the full -- the full taste here, 

20 and also maybe even have the opening addresses from 

21 -- from our panel before we get into this kind of 

22 stuff, and just purely in the name of meeting 

23 efficiency, not -- not in the content that we want 

24 to get around. 

25 If there is any objections, I'd been glad to 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 256 

 2 stay here with Dennis and answer your questions, 

 3 but some of the things that I have heard come up, I 

 4 think would be a little more clearly laid out in -- 

 5 in the coming moments after we finish the second 

 6 presentation and hear from our panelists in the 

 7 beginning. 

 8 WARREN PETERS: Mark, why don't you go ahead -- and Dennis -- 

 9 and make the second presentation at this time, and 

10 we'll get that started. 

11 MARK EVANGELISTA: Thanks for your indulgence on that. 

12 When I was a very young, brand new forecaster 

 

13 in the weather service, and actually in the Air 

14 Force before that, I, like everyone else, took my 

15 little education in meteorology, and back then the 

16 NGM model, and some of the other outputs, and MOSS 

17 data, FOUS data and my immense knowledge of the 

18 atmosphere, and created forecasts. 

19 And then we would go out and get the 

20 observations and verify them, and I was always 

21 shocked at how frequently the observations were 

22 wrong. 

23 (Laughter.) 

24 And there's just one of two ways you can deal 

25 with this; one is, you can call up every observer 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 257 

 2 and implore them to go out and take another look, 

 3 because they might just not have gotten the right 

 4 thing characterized. 

 5 And the other one is to adjust your forecast 

 6 to the way you think about how you might be 

 7 predicting what's happening. 

 8 Well, after several months of trying the first 

 9 one, I realized that wasn't going to work and -- 

10 and then as I got older and wiser, I started to 

11 learn that the observations are actually reality, 

12 and all this other stuff is an attempt somehow 

13 through the magic of physics and computations and 

14 mathematics and everything else, to get a grip on 

15 that reality. 

16 So, when -- and trust me -- and observations 

17 themselves -- we are an observing system, we all 

18 know how -- how uncertain they are and how the 

19 problems could arise. 

20 I have personally been involved in improving 

21 the visibility in many runways just by clearing 

22 the spider webs out of the sensor and watching the 

23 runway visual range go up, you know, hundreds of 

24 meters instantly, and so I know that the observing 

25 system has -- has its difficulties and its 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 258 

 2 uncertainties. 

 3 Certainly the predicting system has it, but 

 4 somewhere out there, there is truth and that is in 

 5 the observed data, and it's -- it's when we begin 

 6 to spatially allocate that truth that we start 

 7 getting in there and messing with it. 

 8 So when we compare MM5 to what AERMET does, 

 9 we're really trying to draw comparisons between one 

10 system for trying to estimate truth, which by the 

11 way begins with some observations, some are, and 

12 another system that tries to spatially allocate 

13 truth, but in both cases there are manipulations, 

14 and we're trying to take two separate, virtually 

15 independent manipulations and -- and compare them 

16 based on some modicum of truth that way, way 

17 upstream was ingested into both of these. 

18 So it's a perspective that -- that we really 

19 tried to keep rooted in as we went through, laying 

20 out this program and more importantly determining 

21 whether or not we're -- we are on the right track, 

22 as we move along. 

23 And what I want to talk about is basically 

24 taking what Dennis laid out as the plan, to some of 

25 the issues that were brought up by the folks in the 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 259 

 2 work group, and some of the first steps we've taken 

 3 to, maybe not even answer the questions, but at 

 4 least find out if we're asking the right ones. 

 5 And so that's -- that's what we'll talk about 

 6 here. 

 7 As Dennis mentioned to you before, the current 

 8 approach is clearly to take NWS observation data 

 9 and -- and stick it into AERMET. 

10 Let's just use the AERMOD paradigm for now, 

11 and get an upper air sounding, and if there's 

12 on-site data, by all means use on-site data. 

13 That's -- that's as close as you're going to get to 

14 the truth at that time. 

15 And, of course, we have profiles if there is 

16 not an appropriate upper-air sounding to be had, or 

17 it's missing or something like that. So we -- 

18 we've got these catches and safety valves, and we 

19 stick all these observational data, and if we need 

20 a safety valve, we'll use that, and we put it in 

21 AERMET and we come out with a solution for now. 

22 And many times, as you know, the upper air sounding 

23 is not collocated, where it's the nearest one, it's 

24 is not collocated with the surface, and anyone 

25 who's ever let a balloon go, knows that, you know, 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 260 

 2 by the time you get to three hundred (300) 

 3 millibars, it's telling you what's happening a 

 4 couple of hundred kilometers (200km) downwind, not 

 5 really off the top. So there's all sorts of 

 6 inherent uncertainties in the system, even when you 

 7 use that truth observation. 

 8 But to go to using a meteorological input 

 9 that takes -- well, let's just stay with the MM5 

10 paradigm for now, is -- is to reach into a 

11 different realm, and it's -- sure, we're talking 

12 about scientific, more scientifically sound, I 

13 think was the phrase Dennis used, but we're also 

14 talking about pragmatic terms here, as well. 

15 And -- and to use met model data that's 

16 currently available and that has been cur- -- that 

17 has been employed for another regulatory 

18 application, the consistency between those two 

19 regulatory applications, the SIP model run that was 

20 done with CMAQ, or the regional haze run that was 

21 done using CMAQ for regional planning 

22 organizations, to take that met input and use that 

23 very same met input to drive a near-field permit 

24 application or something, is to put, manufactured 

25 or otherwise, to put some level of consistency that 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 261 

 2 we don't believe occurs when we use the NWS 

 3 observational data, and that regional modeling has 

 4 used this model data, that -- that we feel the 

 5 perception exists that there is more consistency if 

 6 that same MM5 field is used in both instances. 

 7 And -- and, also, that it's already there. 

 8 It's already processed in to some extent. 

 9 The -- the two large bullets here, utilizing 

10 met model data currently available, and -- and 

11 preprocessed for pragmatic questions that we're 

12 still wrestling with right now -- and it speaks to 

13 the tool that Dennis talked about. 

14 The first one would be that we would just 

15 somewhere post -- here's the MM5 data for 2002 that 

16 was used for this particular CMAQ application for 

17 this particular set, or for this particular 

18 National rule. 

19 Here it is!, and that you were then to run a 

20 near-field application would then download a tool, 

21 download that data and create what you wanted for 

22 your met inputs. 

23 You would do the -- you would do the 

24 application meteorologically, for the 

25 transformation, whether it be CALMET, whether it be 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 262 

 2 some other tool, you would apply that. And then 

 3 you would be free to have -- to have some setting 

 4 up adjusting, or we could just take an entire 

 5 national run at a particular resolution, and ram it 

 6 through the same processor and create a National 

 7 database that is model ready, so to speak, sitting 

 8 up there and that everybody who uses it has this 

 9 perceived consistency, or maybe even more 

10 perceived, maybe actual consistency going for them, 

11 but the flexibility of maybe turning a few dials to 

12 -- to do what we saw earlier today with CALPUFF, 

13 the site specific things, the site specific 

14 judgment, you would have traded that for a more 

15 national consistency. 

16 So those are two pragmatic questions, or one 

17 pragmatic question; two pragmatic offers of a 

18 solution that we're -- we're dealing with now, but 

19 really, we can push forward with our projects and 

20 not answer this question just yet. 

21 And there's also other -- other issues, 

22 constants, and things like that that get -- that 

23 get in there, too. 

24 But these are considerations we wanted to at 

25 least throw out there in case they do modify the 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 263 

 2 type of solutions we want to come up with. 

 3 And our goal, shall we say, our long-term 

 4 goal, wishful thinking goal, however you want to 

 5 describe it, and I'm talking to you as a 

 6 meteorologist who's looking at how meteorology goes 

 7 into play in regulatory activities, in air quality 

 8 modeling activities for regulatory met. 

 9 That's what I'm talking here. I'm not talking 

10 about regulatory programs or policy ends of things, 

11 just how we can best use the environmental data 

12 that we have that out there. 

13 We could, if this consistency holds, we could 

14 start coming up with subregional and subgrid 

15 dispersion model applications that, maybe compu- -- 

16 if computational efficiency gets good enough, when 

17 you run a -- a national run, you just fire off. 

18 For certain types of sources, major points, 

19 whatever they get fired off instantly in the same 

20 time, and then you have this near-field. 

21 And perhaps that could be used to create 

22 subgrid variabilities, or actually subgrid 

23 densities, or -- or even maybe pure spatial 

24 allocations inside these model grids, and -- and 

25 I'm not saying that there is a regulatory appetite 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 264 

 2 for this, but it's a possibility if we can -- can 

 3 do this meteorologically to go in. 

 4 But more importantly, if we can feed some of 

 5 these models with time zero, prognostic model 

 6 output, why can't we feed it with time twelve (12), 

 7 and twenty-four (24), and forty-eight (48), and 

 8 then suddenly you're into a forecasting -- possibly 

 9 real-time forecasting realm that -- that may have 

10 some applicability, and, oh, I don't know, just 

11 planning for the public, I mean, forget for a 

12 moment that a regulatory implication, or even I'm 

13 -- I'm sure Homeland Security conferences going on 

14 at this very moment when someone is standing up in 

15 front of a room say, on a daily basis we can tell 

16 you where such a release of something would go here 

17 or there in a forecast model. So there's -- there 

18 could be applications for this; it's just feasible 

19 if we can get the meteorological inputs ironed out 

20 and fed into this system. 

21 One of the things that would come from this, 

22 though, is it's not just taking the met input here 

23 and -- and manipulating it to fit into the air 

24 quality model, there will be some air quality 

25 manipulations to match up. 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 265 

 2 We want to make sure that that matching is as 

 3 seamless and good as possible, and sometimes the 

 4 receiver has to be tweaked a little -- I don't want 

 5 to say "tweaked", has to be manipulated or 

 6 reanalyzed or recomputed or the algorithm 

 7 reestablished in order to make that -- that 

 8 association possible. 

 9 Dennis touched on some of the advantages to -- 

10 to model met data. There is perceived advantages, 

11 better geographical representation, sure, there are 

12 places when that is a great density of 

13 observational data, there's not a lot of terrain in 

14 the way, there's a lot of urban/rural interfaces 

15 that really can gum up spatial allocation schemes, 

16 and you can get a very good depiction in real time 

17 of the spatial texture, rather than going to a 

18 model. 

19 One of the things, though, that you will get 

20 in a model is, if you take that very same texture 

21 and just raise it up a couple of hundred kil- -- -- 

22 a couple of thousand feet, suddenly you're in the 

23 upper-air and that is where you really get the 

24 benefit of the model data, because we have much 

25 more vertical column resolution than you would in 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 266 

 2 just trying to look at upper-air soundings and 

 3 create a picture from that. 

 4 And if you've been in the business for, well, 

 5 I don't know, twenty -- twenty-two years, you 

 6 remember what it was like trying to plot those 

 7 little upper-air soundings, and you had four points 

 8 on the whole eastern U.S., and had to come up with 

 9 

 streamlines [?] -- I see some people nodding, the up 

10 and down. 

11 That's way back in the past, but that really 

12 drives home the idea of just how sparse the data is 

13 in the upper-airs before satellites and lidars and 

14 sonars and everything else came in to -- and 

15 profilers to give us more information. 

16 More scientifically sound, let's just all 

17 agree that that one is okay for now, and step by. 

18 But it does have more in it. It's -- it's 

19 more physics that goes into this stuff. But don't 

20 forget, this is an estimate of what's happening. 

21 We're using all this physics to try to create what 

22 an observation gives you in the first place, which 

23 is reality. 

24 So to say that MM5 has all these algorithms 

25 and AERMOD doesn't, is -- is like to say we can 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 267 

 2 manufacture a blueberry with -- with all these 

 3 chemicals, and almost get one as good as you pulled 

 4 off the blueberry bush, and that is just -- they're 

 5 two different things. One is a representation of 

 6 it, and one is it. 

 7 But pragmatically it's accepted for other 

 8 modeling, like I say, MM5 here; we've used MM5 

 9 in regional scale modeling, and we have evaluated 

10 it. 

11 And we have documented it, and it has gone up 

12 for review, and it has gone through notice and 

13 comment and it has passed all the trials it needs 

14 to pass, to take advantage of that data that has 

15 already gone through scrutiny and come through the 

16 other end favorably, to take advantage of that is 

17 -- is just a no brainer. 

18 We should at least try to -- to get this stuff 

19 formatted, insert it and use it and see what 

20 consistent numbers we can get up. 

21 Additionally, Dennis alluded to this, too. 

22 You get the whole throw weight of, in this case, NCAR, 

23 UCAR for making WRF, Penn State and NCAR and UCAR 

24 for making MM5, and if we do move towards a model 

25 put out by the Weather Service, you've got all 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 268 

 2 that. 

 3 Rather than Desmond Bailey and a -- and a 

 4 handful of others creating AERMET, we have the NWS, 

 5 and all of their abilities and all of their 

 6 experience creating another met model. 

 7 Again, we should try, at least try, to take 

 8 advantage of it and see -- see what comes out of 

 9 it. 

10 Again, the consistency with the regional 

11 modeling applications, now, I'm trying to stay away 

12 from the regulatory legal ends of those kinds of 

13 things, which I'm sure would be benefited by using 

14 the same input, and it's just one less moving port 

15 to have to use in the way of evidence or 

16 what-have-you. But I'm really trying to talk about 

17 this more in terms of just the pure meteorological 

18 and technical ends of things. 

19 But no matter which way you talk about it, 

20 regulatory, meteorologically, whatever, the second 

21 bullet does come into play for everybody, and that 

22 is if this stuff is already done and it's already 

23 run, it doesn't cost as much as going out and 

24 running your own; running your own model, digging 

25 up your own data and creating something, this MM5 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 269 

 2 data that we're using right now, it's there and 

 3 reviewed and evaluated and all, and it's just 

 4 sitting there waiting for someone to use it. There 

 5 are certain tops- -- advantages to trying at least 

 6 trying it once again. 

 7 The transition, as I said before, you go from 

 8 time zero to time twelve. That is not that big a 

 9 league, if you've got the formatting and everything 

10 else handled, you just are making the jump from -- 

11 from a prognostic initialization to a forecast, and 

12 all the inherent troubles that come with that, but 

13 you're not making any format differences, or 

14 anything. 

15 Once you've learned to get this model data 

16 into the air quality model, whatever time it values 

17 at, doesn't -- doesn't -- doesn't make a difference 

18 in the computation. And it should, keyword, 

19 "should" be easier to use, once we get this all 

20 done. 

21 It should be, and if we go back to the slide, 

22 a few -- a few slides ago, about having a national 

23 database run, then it would be valid, perhaps even 

24 web accessible, where you would -- you would just 

25 pull it down and it would go right in. 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 270 

 2 And there are some front-ends for some of our 

 3 dispersion models now that do that sort of thing, 

 4 and this, perhaps, could fit into that -- into that 

 5 kind of a paradigm. 

 6 The general steps that Dennis touched on these 

 7 earlier was, right now MM5 being fed into a 

 8 dispersion model is the -- is a general goal here, 

 9 and we choose MM5 because that's what ha- -- that's 

10 what's being used right now; the regional scale 

11 model. 

12 There's NCEP product data being used in 

13 dispersions modeling right now. That's the ETA 

14 model that's going into an air quality forecast run 

15 by CMAQ, and that's produced everyday. You can go 

16 on the National Weather Service site and you can 

17 see it, and that's ETA data going into CMAQ. 

18 So we have NCEP data which is the National 

19 Weather service Model Center, National Center for 

20 environmental prediction. We have their data going 

21 into an air quality model, be it a regional scale 

22 grid model, but we have it going into and being 

23 utilized right now. 

24 And we would want to go with MM5, because it 

25 is what we are most familiar with, and it's what's 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 271 

 2 been used in the regulatory world as of now. Go 

 3 with that into a dispersion model, and then there 

 4 is that leap. There is A -- if A equals B, and B 

 5 equals C, then A equals C, why we could make that 

 6 leap then and try to go from an NCEP field and feed 

 7 that into AERmuff -- AERMOD. 

 8 Starting with initialized fields, as I've said 

 9 before, and then -- then go into forecast fields. 

10 And I cannot emphasize that last bullet enough. 

11 We've got to pick this stuff apart and 

12 evaluate it at its very pieces, and see what's 

13 going on. And Dennis said not to say which is 

14 better, because we know they are two different 

15 animals, but just to illustrate and highlight the 

16 differences, so everybody walks into this 

17 knowledgeable and informed as we move forward. 

18 So what we were able to do, and the stuff I'm 

19 about to show you is very, very recent. We were 

20 able to take advantage of a project that -- that 

21 had been done for air toxics in Philadelphia, and 

22 do some conversions fairly quickly and -- and test 

23 out some of the things we wanted to do. It was not 

24 the project we had envisioned. 

25 It involved, oh, I don't know, something like 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 272 

 2 -- you may help me on this -- fifty-one thousand 

 3 (51,000) sources -- 

 4 FROM THE AUDIENCE: At least. 

 5 MARK EVANGELISTA: -- And fourteen thousand (14,000) 

 6 receptors, and that's about fifty thousand nine 

 7 hundred sources more than we had hoped to do in 

 8 some of our test runs (laughter), but it was there, 

 9 it was available, and -- and it was something that 

10 we could seize and take advantage of. 

11 So while it wasn't ideally what we had in 

12 mind, it was something that gave us a lot of good 

13 information. 

14 The -- the goal we had with -- with doing this 

15 project, or converting it to meet some of our ends, 

16 was to conduct, basically, an air quality model 

17 simulation using the input from MM5 as a 

18 replacement for the NWS observations. 

19 Now, Dennis gave you a very methodical mental 

20 list of what we wanted to do. 

21 First, we wanted to pull the observation out 

22 of AERMET and stick in MM5 in AERMET and rerun 

23 AERMET and see how that worked. Then we wanted to 

24 just maybe skip AERMET altogether and go straight 

25 to -- to AERMOD with the MM5 data, and do this in 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 273 

 2 methodical steps. 

 3 Well, when an opportunity like this lays in 

 4 front of you, you take what you can get from it -- 

 5 we knew we were not going to run twenty different 

 6 steps of fifty-one thousand (51,000) sources, so we 

 7 -- we were able to sit down and -- and plan out how 

 8 we would make some of these leaps, two or three at 

 9 a time. 

10 That doesn't mean we're not going to go back 

11 on a smaller scale and do the methodical stuff, we 

12 still plan to do that. But we wanted to take 

13 advantage of -- of this opportunity. 

14 We got well characterized emissions, very well 

15 characterized emissions, reasonable results that 

16 the IC results with the fifty-one thousand 

17 (51,000) sources and one monitor, I believe, worked 

18 -- there were two monitors, twice as many monitors 

19 as I thought, but it came out fairly well, and then 

20 the AERMOD compared to the ISC looked -- didn't 

21 look too bad, so we felt we could get some 

22 meaningful results out of this, and then, of 

23 course, the corresponding MM5 output for the 

24 observations were there, it was existing, it was on 

25 the shelf. 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 274 

 2 Everything was already hanging on the tree, we 

 3 just had to figure it altogether and -- and cork it 

 4 together. 

 5 Our domain was thirty-six kilometers (36km), 

 6 the red dot you see right there is the Philadelphia 

 7 Airport, the site of the NWS observation. 

 8 Right below it, I believe, is Veteran Stadium, 

 9 site of many heartbreaks of my youth, and that box 

10 there is the domain from which -- that is grid cell 

11 from which we extracted the met variables to 

12 replace this. 

13 So essentially, we took -- we took the UNB 

14 winds which are the on the corners of the grid 

15 cells, and then we took all the other data from the 

16 center of the cell, to represent that dot. 

17 And as Dennis pointed out before, he had some 

18 deal where there was a bunch of sources all around 

19 and he also had to actually think about 

20 deresolving, I believe, was the term you used? You 

21 can see where, in this instance, you might see, 

22 there -- there's nine grid cells here, so you might 

23 have -- well, in this case it would be a eight, but 

24 if you can envision this as a twelve (12), you 

25 could see the point they were trying to get to as 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 275 

 2 to how you would be able to deresolve them and back 

 3 out. 

 4 The color is -- don't mean a thing. It was 

 5 just -- we pulled off one parameter and just boxed 

 6 it just to give you an idea of the borders of the 

 7 grid cell, but that's -- that's the thirty-six 

 8 kilometer (36km) we used. It was just a straight 

 9 out one to one, pull it out and stick the other one 

10 in. 

11 Had we had a number of sources all over the 

12 place, I mean, if we're retaining the steady 

13 stateness of this thing, and computers are getting 

14 to where they're getting, why -- why could you not 

15 use all the sources in this box, use this data and 

16 all the sources in this box use this data; once we 

17 have done what you've done -- what you suggested, 

18 which is compare the values in adjacent cells. 

19 That's another thing we would need to look at, 

20 because we can't treat these things as completely 

21 independent things going on. There is some 

22 interplay back and forth, and we want to look at 

23 that. 

24 So the idea was to run MRN with ISC the good 

25 old fashioned way, and use the observations and get 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 276 

 2 that as a baseline, and stir that as the original. 

 3 Then AERMET and AERMOD using the observation data 

 4 once again, back comparing it to ISC. Then we 

 5 extracted the data from MM5 that we would need for 

 6 that grid cell to replace the observational data. 

 7 Any parameters that we could translate from MM5 to 

 8 AERMET output, in other words, bypass AERMET, we 

 9 seized on. 

10 If there was an MM5 output explicitly, if MM5 

11 output a parameter that AERMET output, we just 

12 jumped over AERMET and used the MM5 parameter. 

13 That was the goal, and the idea was to stop 

14 there. 

15 And what we did not want to do was calculate 

16 or recreate an outdoor processor coming from MM5 to 

17 go into AERMET, or to go into AERMOD. 

18 We wanted to allow AERMET to do its thing, but 

19 as we looked more and more at it, there were very, 

20 very few places where that was required, and we 

21 were able to bypass AERMET altogether. 

22 So at the end, this number five, which is what 

23 we were hoping to do, which is what we thought we 

24 would have to do, we didn't have to do. We didn't 

25 have do let AERMET take some -- some of the values. 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 277 

 2 So we just took AERMOD, any -- any calculated 

 3 AERMOD value that AERMOD calculated, -- not AERMET; 

 4 if AERMOD calculated something that MM5 provided, 

 5 we said, well, what the heck, we're always jumping 

 6 over AERMET, we have to jump over the AERMOD 

 7 processor and we don't hurt anything, let's take 

 8 that opportunity. 

 9 There weren't too many of those, but we were, 

10 you know, getting full of ourselves, and we had so 

11 much success with the first thing jumping over 

12 AERMET, that we thought we would take fullest 

13 advantage of what we had from MM5. 

14 So, as I said before, some of these steps we 

15 wanted to do quite methodically, we ended up 

16 jumping and leapfrogging, but we will go back and 

17 redo those. 

18 Then we ran AERMOD, using the reformatted 

19 data, I'll call it a hybrid, because it was a 

20 couple of steps added together, and then we looked 

21 at the met outputs as well as the output of -- of 

22 AERMOD itself. 

23 An example of -- of the jumpover would be 

24 something like relative humidity and cloud. And 

25 MM5 doesn't release -- I should point this out, 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 278 

 2 we were using an existing MM5 run that had 

 3 already been performed for a different 

 4 requirement. 

 5 There may have been output variables, that 

 6 were not required by that particular application, 

 7 that disappeared, that were just not saved that we 

 8 could have used. So we were at the mercy of what 

 9 was available. 

10 There may be other times now, where we can 

11 feed back into the process and say, hey, you know 

12 what, from now on when you do a CMAQ run, you need 

13 to say, these are the three variables. You may not 

14 need them, but we will, in this instance, hang onto 

15 them for consistency's sake. 

16 We didn't have that luxury this time, and so 

17 we did not have any kind of cloud-out, but not that 

18 MM5 really does an explicitly output something like 

19 that in the first place. 

20 We could take RH, and we could find a way to 

21 create a cloud output, which would then go into 

22 AERMOD. 

23 But the question is, well, what's AERMOD's 

24 using this for, if it's breaking it back down into 

25 a moisture profile, why don't we stick the whole 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 279 

 2 cloud thing together and go straight to moisture? 

 3 But if it's using it for insolation 

 4 characteristics, then maybe we need that, the idea 

 5 being is that if we're converting something, and 

 6 then converting it back to something else, maybe we 

 7 can skip that first something altogether. 

 8 And these are the kind of questions we need to 

 9 look at, and I believe you've answered quite a few 

10 of those with CALMET, already, because I -- I don't 

11 believe there's a lot of redundancy or convert to 

12 one thing and then back convert to something else 

13 going on there. 

14 We -- I've played with the CAL- -- MM5-CALMET 

15 thing a few times, and not insomuch as using it as 

16 a parallel for this process, but there's a lot we 

17 can learn from it, because I don't believe it does 

18 that -- that sort of thing where it converts to one 

19 thing and then back to something else. 

20 And then, of course, once again, examine the 

21 met processor and the dispersion model output, and 

22 this is where we end up. 

23 I'm telling you this stuff is still warm from 

24 the oven. We haven't had a chance to pore over it 

25 too much, but I thought I would throw these things 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 280 

 2 out here, being that we have a panel talking later, 

 3 perhaps we can answer a few questions as to why 

 4 this may -- some of things we're about to see, we 

 5 actually see. 

 6 Well, the first one we got back was wind speed. 

 7 We all declared victory at this point and didn't 

 8 look at any other data and just laughed, (laughter) 

 9 -- 

10 FROM THE AUDIENCE: Shame on you. 

11 MARK EVANGELISTA: -- but wind speed is not too bad. It 

12 matched up fairly well, and -- and if we do a 

13 paired plot, the factor of two lines kind of go -- 

14 I'm left-handed, let me, do the right way here. It 

15 kind of goes that way, so we're sort of within the 

16 factor of two lines in -- in pairing up the 

17 wind speed. 

18 And -- and that's -- that's not too shabby. 

19 Direction, well, this is the climatological 

20 breakdown for me forty ninety-two (40/92) for 

21 Philadelphia, and I'm going to test something out 

22 here. Okay, great! 

23 This is climate; this is the NWS statement, 

24 and I'll kind of cycle back and forth a little bit 

25 there, and you can -- you can sort of see that the 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 281 

 2 southwest is handled decently. The climatology has 

 3 a little southwest max, and then a little minor -- 

 4 secondary one in the northwest. Whoops! And the 

 5 NWS data, at least directionally, fairly 

 6 consistent. 

 7 When we go into MM5 though, we -- we give up 

 8 some of the southwest max here in exchange for 

 9 northwest, so the secondary becomes the primary in 

10 the MM5 section. I'll compare that -- that 

11 climatology, you can see it's quite different. 

12 And, also we don't catch too much in this -- 

13 in the eastern quadrants and you see that in the 

14 MM5, so perhaps -- let me back it up one -- the NWS 

15 data that -- that was -- that's the NWS and here's 

16 MM5. 

17 I don't want to get your eyes all swimming, 

18 but that's -- that's a little more directionally 

19 consistent with the AERMET treatment of the -- of 

20 the NWS data. 

21 If you pair them up, the hourly values, you 

22 can see that the -- the southwestern components, 

23 which are up here, just have an awful lot more 

24 values to look at, actually. Down here and up here 

25 is just the swing from three sixty (360o) to zero 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 282 

 2 (0); zero one zero (010), but there is just an 

 3 awful lot more in southwest node. 

 4 One of the things that I would like to do, and 

 5 we've talked about it is to take a number of other 

 6 locations; could there be some terrain problem, 

 7 could there be fall in the Delaware River, there is 

 8 -- there is, we've got to just pick a lot of spots 

 9 that represent different types of influences, and 

10 see how they pair up as well. 

11 And this is a fairly easy to do. It's not 

12 that difficult to take some spots and run them 

13 through AEDMed -- AERMET and compare them to what's 

14 going on in -- in MM5 for the same location. So 

15 we'd like to do that and just have more data 

16 locations to look at. 

17 But that's what we've got for Philadelphia. 

18 The two meter temperature, the well-known, 

19 well discussed, much maligned, and cold bias in MM5 

20 somewhat shows itself. 

21 I want to point something out here, as we talk 

22 about hourly averages. 

23 Some of the stuff we did here, the modeling 

24 was done in the toxics rollover. We're looking at 

25 annual averages, and we grab hourly averages as 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 283 

 2 once again, it was what was available to us. 

 3 We do plan to look at our pairs and things 

 4 like that and dig deeper into this data, and I'd 

 5 like to hear from you later on today, about what 

 6 else we can look at, but this is just our first 

 7 pass. 

 8 The hourly averages are for the NWS through 

 9 AERMET calculations done only for non-missing times. 

10 So we're not -- we're not averaging out any of the 

11 zeros. 

12 But as you can see, MM5, the triangles, it 

13 tracks pretty well, but it stays about two degrees 

14 colder the whole time. 

15 Surface pressure. MM5 being the triangle -- I 

16 think there's a triangle strata on the entire 

17 discussion here, so you can see the surface 

18 pressure from MM5 significantly lower than what we 

19 have in the NWS data run through AERMET. 

20 This is one of the places where we've got to 

21 realize what MM5 is doing versus what AERMET is 

22 doing, and I'm not professing to be an expert in 

23 what AERMET is doing, but fortunately, someone who 

24 does know what AERMET is doing is sitting right in 

25 front of me, so if we do want to discuss that, we 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 284 

 2 can. 

 3 But MM5 is talking about layer one surface 

 4 pressure. This is thirty-eight (38) meters off the 

 5 ground. That is thirty-eight (38) meters high, 

 6 it's not at the surface, so this is a very, very 

 7 elementary example if we've got to know what we're 

 8 looking at, we've got to know what this thing is 

 9 telling us before we just yank it out and stick it 

10 into -- to a model. 

11 Also, average or not, you've got synoptic 

12 scale events going on that are raising, lowering, 

13 the pressure. This isn't just the diurnal 

14 fluctuation we're talking about here. 

15 So you are going to see some that are 

16 reflective a little more in the observational data 

17 which is, you know, quicker responding than you're 

18 going to see in the model data which has gone 

19 through several smoothing operations. 

20 WARREN PETERS: It's about a quarter to four. 

21 How many more slides do you have? 

22 MARK EVANGELISTA: A few more. 

23 Let's adjust the -- let's adjust the pressure, 

24 say about ten millibars or one millibar for every 

25 ten (10) meters, and then somewhat as a 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 285 

 2 standardized version, and it kind of tracks a 

 3 little bit better. 

 4 Early average rainfall. This -- what we see 

 5 right here is roughly around twenty-two (22); 

 6 that's about when I have my tea time, that's when 

 7 it rained so much out there. 

 8 Those of you who use MM5 in a large production 

 9 type mode know what this is. This is about 

10 thirteen (13) Z. If you run a twelve (12) hour 

11 spin on it, on MM5, and throw the first twelve 

12 hours out; typical modeling run, you run a spin-up 

13 and you get rid of the beginning of it, so the 

14 boundary conditions and the initial conditions have 

15 had a chance to flush out. 

16 MM5 does not give you an hourly breakdown of 

17 precipitation, it gives you a cumulative 

18 precipitation. 

19 So this value here is reflecting the the 

20 previous twelve-hour spin-up that we threw out, 

21 plus that hour. That's why it's so much higher. 

22 It's a very easy thing to remove. In the CMAQ 

23 world they have been doing it for years. 

24 We left this in here just to illustrate -- 

25 that's sort of an illustrative example of why we 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 286 

 2 have to keep our eyes peeled on just what this 

 3 model is doing and not just look for a direct 

 4 translation across the way. 

 5 Relative humidity. Not too bad for the two of 

 6 them, so we should be able to convert the MM5 

 7 relative humidity to clouds, and have a pretty good 

 8 breakdown of what the clouds look like, so we do 

 9 it. 

10 The algorithm we use was -- was fairly 

11 exhaustive to -- to try and calculate it over. But 

12 let's face it, we're not taking -- in this case our 

13 algorithm did not bring every vertical layer, it 

14 just brought in the eight hundred fifty (850) 

15 millibars or thereabouts. 

16 The observation data, even though it's an ASOS 

17 shooting a radar beam straight overhead, it's still 

18 going through the column and coming back with what 

19 it gets at any of those vertical levels. If it 

20 gets a bounce back, it's got a cloud cover. 

21 So we're averaging right -- a little less than 

22 three and as you can see the cloud cover, and I'll 

23 give you a better slide of it here, (projecting 

24 slide) the cloud cover classes are much more 

25 broadly defined in the MM- -- for the National 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 287 

 2 Weather Service data going through AERMOD. 

 3 You can see over here, eight, nines, ten, 

 4 nonexistent, nonexistent in MM5, but -- so, it's 

 5 never overcast in MM5. So if you really want to 

 6 know whether you should have a picnic or something, 

 7 always look at -- look at MM5 (chuckles from 

 8 audience), and way, way more lower -- lower cloud 

 9 values across there. And this is stuff we have to 

10 just take a good look at. 

11 Sensible heat flux. And I want to thank 

12 Desmond Bailey for giving me the following couple 

13 of rundowns here; sensible heat flux in MM5, higher 

14 peaks, but not nearly as low on either side, as you 

15 can see the AERMOD data down much lower in the 

16 evening hours. When we convert that to W star for 

17 -- the heat flux has to be greater than zero for MM5 

18 to compute a W star so that we can see that when we 

19 look at the convective velocity scaling in MM5, 

20 it's higher all the way across, because it's 

21 dropping out all those non zeros. 

22 And there's the missings and dropouts in both 

23 MM5 and NWS, dropping out a ton of zeroes , as 

24 again you can see, it's a much smoother drop-off in 

25 the black bars, and MM5 and then the NWS AERMET 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 288 

 2 comes down much quicker and drops them out, more in 

 3 the end of the day issues. 

 4 Mechanical mixing height, we kind of cut the 

 5 face right but much lower on the scaling. 

 6 Convective mixing height. Two things at play 

 7 here; first of all, AERMET does collapse fairly 

 8 quickly by design, I believe, correct me if I'm 

 9 wrong, but secondly there were only fifty-five (55) 

10 values used here, a lot of non- outlier values were 

11 out. There are one, perhaps two, really nasty 

12 outliers that threw that average way up. 

13 So it's just -- there's a statistical anomaly 

14 in their head, as well as some of the differences 

15 in the way MM5 and AERMET are -- are wired to do 

16 their job. 

17 There is an awful lot more dropped out data in 

18 NWS, and of course, MM5 much higher over here in 

19 the very, very low classes, less values in that 

20 population. 

21 So maybe we could take it a little step 

22 further and look at the MM5 values and run the MM5 

23 raw values through AERMET's algorithm and see if we 

24 did what we originally wanted to do, which is 

25 instead of replace AERMET output with MM5, is 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 289 

 2 replace AERMET input with MM5, put the MM5 met data 

 3 into AERMET, and then crank it through that AERMET 

 4 algorithm and see what we get for the mixing 

 5 height. 

 6 When we get a little bit closer on the 

 7 convection as you can see, we kind of capture that 

 8 shift in the vassalbase, and we certainly capture the 

 9 drop faster than we do with this smooth value 

10 coming out of MM5. 

11 So, leads us to think maybe there has to be 

12 some mid process, sure it's adding another moving 

13 part which you're kind of reluctant to do, but it 

14 may be necessary. 

15 Mechanical mixing heights; we run into the 

16 same kind of thing, and then when we calculate 

17 again, the mechanical mixing height by shoving the 

18 MM5 data into AERMET's algorithm, we get this 

19 dotted area here, but now the phasing is not quite 

20 as good, and we also have an amplitude problem, so 

21 -- and like I say, we just looked at this stuff a 

22 little while ago, so that's not exactly what we had 

23 in mind, so now we have to go back and find out 

24 what's going on there. 

25 And if you -- on the mixing heights, if any of 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 290 

 2 you have any ideas, I'd love to hear them. We'd 

 3 all love to hear them, because we reallly haven't 

 4 had a chance to dig into this stuff just yet. 

 5 There's the classes of the mechanical mixing 

 6 heights; that's again some mixings over here, and 

 7 you can see it's much higher and then drops off 

 8 much quicker in the MM5 world for those -- for 

 9 those classes. 

10 All right, Mark, would you shut up about the 

11 meteorology and give us some concentration values 

12 coming out the backwind. 

13 If you promise not to tell anyone, we'll -- 

14 here's -- here's what we got for all sources. This 

15 is all sources here, and it's just for benzene; the 

16 AERMET outputs and the MM5 outputs, and we've got 

17 the max value, the min value and the twentieth 

18 through eightieth percentiles. 

19 You got about a factor of five going on here 

20 with MM5 rolling in higher, and everywhere else 

21 it's give or take a factor of three. 

22 Now we're so preliminary in this deal we don't 

23 know what the makeup is at this point, but we 

24 wanted to point this out. 

25 Again, annual averages. This is our benzene 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 291 

 2 annual average concentration map for using the NWS 

 3 meteorology with AERMET. This scale, I know you 

 4 can't read it, but it is identical for MM5 and for 

 5 AERMET when we move along. 

 6 Down here, you've got blue and you've got 

 7 orange and red and you see a little orange there, 

 8 and then when we move to MM5, we're considerably 

 9 blue, but in the same sort of pattern the highs are 

10 just higher, the lows are a little higher; we 

11 haven't seen any new spots develop. We 

12 predominantly have this big alignment here along 

13 the river, and then we have these two down here, 

14 and as you move to MM5 it's the same deal, only the 

15 amplitudes have changed a bit. 

16 And there's a difference plot, and as you can 

17 see, we're -- the higher concentrations do show the 

18 high increases. 

19 And finally, we have a concentration plot 

20 here, too, and what we noticed here is that there 

21 is this -- this inflection, it's very quick ramping 

22 up of the factor by which MM5 exceeds the AERMET 

23 output, but then -- then we get a significant 

24 tailing off, so -- it starts right about here, and 

25 then rolls up pretty quickly for the high 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 292 

 2 concentrations and then naturally, we tail off a 

 3 little bit because there is really only so much you 

 4 can put in the air. 

 5 This is the twenty-fifth percentile (25%) of 

 6 every data point -- I'm sorry, this is the 

 7 twenty-fifth highest value of every data point, 

 8 and we see the same general factor of three, give 

 9 or take, actually a little less in this case. 

10 And as I said, the concentration values we 

11 have barely looked at, I mean, I practically pulled 

12 these off the printer and brought them down here. 

13 It's the met values we are more interested in 

14 working out right now, as to how they affect 

15 concentration output, that is really not something 

16 we've dived into just yet, we're still -- we've got 

17 enough met discrepancies to work out. 

18 And the next steps, like I said, we're going 

19 to try and use different stations to look at the -- 

20 the met data, different data sets if we can do it, 

21 not the toxic stuff where we're dealing with 

22 averages and a very scanty monitoring of the 

23 models. 

24 We're going to try to go beyond this thing by 

25 employing grid cell, but that really frankly is 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 293 

 2 down the road. 

 3 We want to get some of these other things done 

 4 in a single cell, steady state being what it is, we 

 5 can -- we can do that. 

 6 We want to expand our evaluations into 

 7 components analyses and then continue to evaluate. 

 8 Joe beat us to the punch there talking about 

 9 CALPUFF applications, but we do know that there are 

10 processors out there that are doing this already, 

11 and we want to see the parallels. 

12 And then finally the NCEP model, as we get 

13 there, hopefully we have a lot of this stuff worked 

14 out. 

15 If a lot of this is in -- is idiosyncratic to 

16 MM5, well, give or take WRF as MM6, so some of the 

17 leaps from MM5 to WRF which is where we're going to 

18 go. WRF is going to be on line in March or April 

19 of next year, RUC, ETA, probably never going to be 

20 seen used operationally for feeding AERMOD, so we 

21 are going to transition MM5 to WRF. 

22 There's a lot of consistency between those two 

23 models that we're going to be able to take 

24 advantage of as we go that way, and collaborate 

25 with that work group that Dennis talked about, and 
 1 AERMOD/MM5/Mark Evangelista Vol. 1, p. 294 

 2 I'm sure he would say the same thing that I said 

 3 about the CALPUFF group, if you're not on that work 

 4 group and you have something you want to contribute 

 5 to us, or you want -- you want to say something to 

 6 our panel, whatever, we are all ears, absolutely. 

 7 I appreciate your indulgence, thank you for 

 8 your time, and I believe we are going to set up a 

 9 panel discussion. 

10 DENNIS ATKINSON: Thanks, Mark. 

11 If I could have the gridded met panel members 

12 come forward, or do we want to take a break? 

13 I guess we want to continue on. 

14 And if you would look at your -- your 

15 schedule, your agenda, there is -- well, I'll just 

16 say, there are about seven or eight questions that 

17 I'd like for you to kind of consider. 

18 And I'm going to ask each of the panel members 

19 to introduce themselves and try to give a little 

20 background of what their relationship is to gridded 

21 data, their experiences and as they relate to these 

22 questions. 

23 Panel members are, from left to right, John 

24 Vimont from the National Park Service, Dennis 

25 McNally from Alpine Geophysics, Dick Schulze from 
 1 PANEL DISCUSSION Vol. 1, p. 295 

 2 Trinity Consultants, and Bret Anderson from EPA, 

 3 Region Seven. 

 4 John, if you would like to start. 

 5 JOHN VIMONT: Okay. Background; I'm currently the Chief of 

 

 6 the Research and Monitoring Branch of the National 

 7 Park Service, Air Resources Division. 

 8 Prior to that, I was one of the air quality 

 9 modelers in the Division for EPA in states prior to 

10 that. As far as the overall use of the model, 

11 mostly we model use -- meteorological model output 

12 users, feeding into CALPUFF primarily, also into 

13 some of our regional modeling efforts that we are 

14 doing now. 

15 The -- I was one of the members of IWAQM where 

16 we tried to pioneer the use of mesoscaling 

17 meteorological model -- modeling output as inputs 

18 to the various regional scaling models, the puff 

19 policy we were trying to use, the CALPUFF came out 

20 of that effort. 

21 As far as the -- the questions you have here, 

22 I guess from my standpoint, I've got a couple of 

23 various -- to discuss; one is the purpose of why 

24 the model was run. 

25 And as Mark just alluded to, he took some 
 1 PANEL DISCUSSION Vol. 1, p. 296 

 2 modeling output that he had available to him and 

 3 ran -- and used it in the tests. It may not have 

 4 been ideal data. 

 5 One of the issues I think we have with using 

 6 NCEP data, which is MM5, is what was the purpose of 

 7 the model that was run in the first place? 

 8 The forecast data, they're interested in a -- 

 9 I'll call the extreme level of events in terms of 

10 the severity of the choice. They want to know if 

11 it is going to rain, they want to know if the wind 

12 is going to blow really hard; so they're really 

13 interested in what's going on as far as scale 

14 evaluator. 

15 And that's -- there -- you know -- the reason 

16 why those models are run. The historic use of MM5 

17 has been from -- in our community at least, has 

18 been to try to get it to work better for the air 

19 quality models which has been afloat for sometime 

20 in the air parameterizations. 

21 And the fact that the right ones -- 

22 improvements in regard to that, may even 

23 specifically, algorithms here and there that were 

24 developed specifically trying to run air quality 

25 models. 
 1 PANEL DISCUSSION Vol. 1, p. 297 

 2 So when you're picking one of these models, 

 3 you have to think that there are -- realize the 

 4 limitations -- you know -- even though it's stamped 

 5 and blessed by the -- by NOAA, and the data is 

 6 perfectly good, but it was developed for a 

 7 different reason than we may have had. 

 8 So keep that in mind as we go through this 

 9 process. 

10 Some of the other things we talk about using, 

11 say, as input to AERMOD, we said, as an example, 

12 it's some pretty severe differences in some of the 

13 results. 

14 Any model that's out there is built -- the 

15 builders of the model, I think, are -- in the back 

16 of their mind, are thinking what data is going into 

17 the scale of data that you have from a anemometer, 

18 temperature sensors, you know, even any temperature 

19 profiles that you are measuring is different than 

20 what you're getting out of something like MM5. You 

21 may have a -- he referenced thirty-eight kilometer 

22 (38km) surface layer. 

23 That's going to give you a very different 

24 result probably than what a measurement of a couple 

25 of years is going to give you. 
 1 PANEL DISCUSSION Vol. 1, p. 298 

 2 So if the model is built for a specific set of 

 3 measurements, you have to keep that in mind as 

 4 you're going through this. And I think the -- and 

 5 if there are going to be differences, and it may or 

 6 may not be appropriate to run those things through 

 7 your -- your evolving model, and the effort we're 

 8 willing to pursue that. 

 9 And it's attractive if you've got a lot of the 

10 parameters you want being spin out of the mesoscale 

11 model, but not, you know, it kind of sets the scale 

12 with your -- the other -- the air quality model was 

13 built for. 

14 And then there is the issue of the resolution, 

15 the horizontal resolution. We recently have been 

16 engaged in some experiments, actually, Tim Allen, 

17 out of the Fish and Wildlife Service did model runs 

18 where we were looking at flowing the four corners 

19 region of the southwestern United States. 

20 The -- over the years, the National Park 

21 Service has done a number of air quality studies 

22 around the Grand Canyon. We're fairly familiar 

23 with the flow regimes around there. 

24 And what we're seeing is in some model 

25 applications that the coarse scale mesoscale models 
 1 PANEL DISCUSSION Vol. 1, p. 299 

 2 were not capturing the WRF case kind of flows that 

 3 we get to take things from the four corners region 

 4 and transport them to the west into the, of course, 

 5 the Grand Canyon. 

 6 What we found by doing some experiments was it 

 7 really didn't matter which -- whether it was the 

 8 NCEP models, RUC output kinds of things, or whether 

 9 it was running MM5 at a thirty-six to forty 

10 kilometer (36-40km) resolution, the flow was being 

11 taken basically up, you know -- the south/southwest 

12 flow was being developed. When the model was 

13 nested down and run in a -- well, it went from 

14 twelve (12) to four from that thirty-six kilometer 

15 (36) run, both twelve (12) and four managed to 

16 actually pick up these easterly flows that take 

17 things in that direction. 

18 Now one of the comments was that, well, we can 

19 just take the coarse mesoscale meteorological 

20 output and run it through CALMET. CALMET didn't 

21 change the flow, and when you -- when you're 

22 forcing the flow in your general fields, CALMET 

23 isn't -- it's taking the wrong direction, I mean a 

24 dramatically wrong direction. 

25 CALMET just doesn't overcome that, and there 
 1 PANEL DISCUSSION Vol. 1, p. 300 

 2 may be some other ways to do some diagnostic 

 3 techniques to do that, but be aware of that, too. 

 4 We were actually kind of surprised and pleased that 

 5 the mesoscale model was able to pick up those kinds 

 6 of features, primarily from the higher resolution 

 7 of the terrain, and deal with that. 

 8 (Projecting slide.) 

 9 Alright, at thirty-six kilometers (36km) you 

10 see a little dip where the Grand Canyon is, and for 

11 twelve (12) you get a bigger deficit, or you get a 

12 bigger one. You know, you've got five thousand 

13 (5,000) feet of rock to try to resolve there, it's 

14 -- it gets important how the flow gets treated. 

15 DENNIS McNALLY: Okay. 

16 I'm Dennis McNally, Alpine Geophysics. 

17 And -- I've been a MM5 user since about -- 

18 WARREN PETERS: (Interposing) Dennis, is that mic on? 

19 DENNIS McNALLY: -- in both the production of the fields and 

20 also as a data user, primarily for local scale and 

21 regional scale modeling applications, CMAQ. 

22 WARREN PETERS: Dennis, please pull that microphone closer. 

23 DENNIS McNALLY: (Interposing) Oh, I'm sorry. Is it 

24 better? 

25 The -- I think that this is an appro- -- you 
 1 PANEL DISCUSSION Vol. 1, p. 301 

 2 know -- very good discussion that we've been 

 3 having, and I think that in all of the, you know, 

 4 users of the MM5 data that we are talking about, I 

 5 think it's really important that we do a balance of 

 6 the cost of the -- of the users that we are -- of 

 7 decisions that we're making with these data versus 

 8 the cost of how well we can do with the data. 

 9 I agree that it is really neat that there is 

10 some real time MM5 or real time RUC or real time 

11 fully available, pull 'em off-the-shelf and use 'em 

12 data sets around. It's sure tempting to use those, 

13 but we need to remember that the data sets that 

14 we've been using, that I know that certainly I've 

15 grown to understand and like, often have had data 

16 simulation in them. 

17 I've had the luxury of going back three or 

18 four years. I already know the answer. All I had 

19 to do was get to the answer. It looks like a 

20 forecaster's dream. They already have tomorrow's 

21 paper. So I think that that report -- and we 

22 aren't going to lose that. 

23 The other thing is, as rea- -- really as 

24 strongly is the scale problem that John came up to 

25 mention. 
 1 PANEL DISCUSSION Vol. 1, p. 302 

 2 For instance, the en- -- a thirty-six 

 3 kilometer (36km) in a bi-simulation, there is an 

 4 indication of the land see breeze and in some cases 

 5 it will kind of develop and you kind of have to -- 

 6 you know -- close one eye and tilt your head a 

 7 little bit to see it; that's not going to be 

 8 overcome unless you're hitting it real hard with an 

 9 observation, and observations are rarely dense 

10 enough to get a land/sea breeze to develop. 

11 So once you go to four -- twelve K (12k), you 

12 have pretty much there, you get a four K (4k) 

13 simulation, it's there, you know it's there. 

14 Maybe the extent isn't quite right, so I think 

15 that that's important. 

16 The other thing is, along the scale is, you 

17 need to be careful of the -- these prognostic 

18 fields. 

19 For instance, there is a comment of using the 

20 W fields, the vertical velocities. But vertical 

21 velocities are very, very scale dependent. In 

22 fact, they're so scale dependent in MM5 that as you 

23 get to these high, horizontal resolutions, one 

24 point three kilometers (1.3km), one kilometer, 

25 actually your time step gets determined by vertical 
 1 PANEL DISCUSSION Vol. 1, p. 303 

 2 motion, because we are so shallow. 

 3 That's the sort of a thing that any form of 

 4 downscale or any of the work with CALMET just isn't 

 5 going to capture. It's a fundamental of -- of the 

 6 MM5 field. 

 7 I think that the -- that the use of the MM- or 

 8 CAL, say, in the five resolutions of prognostic fields 

 9 is very encouraging, but I don't think that there 

10 -- they're not always the right hammer for the job. 

11 And if -- a prognostic model field is a regional 

12 field that I think can do as good a job, or better, 

13 than observations in doing regional field 

14 transports. But it's not for the fence line or 

15 on-site, that's -- that's way more appropriate. 

16 So, I guess that's my comment. 

17 RICHARD SCHULZE: I'm Dick Schulze, and I'm the fellow who 

18 started Trinity Consultants thirty-one (31) years 

19 ago, and we have a company of about two hundred 

20 (200) staff specializing in air quality, and I have 

21 quite a few comments, but they're really a 

22 distillation of a lot of the talented staff that we 

23 have within Trinity. 

24 And -- so, I don't know whether I should just 

25 go through these, or -- because these people have 
 1 PANEL DISCUSSION Vol. 1, p. 304 

 2 been fairly concessive, and they could be, I guess, 

 3 the same sort of questions that I have, but no use 

 4 of going on about that (chuckles from audience). 

 5 But I have about four pages here. 

 6 WARREN PETERS: Dick, could you pull the microphone up a 

 7 little bit closer to you? 

 8 RICHARD SCHULZE: Yeah. So let's go ahead, let's go ahead 

 9 and start here. I think the first point is, 

10 although assimilated data may provide more 

11 representative meteorological data in a large 

12 modeling domain, a regional area, how much will the 

13 use of this data change modeling results in the 

14 near-field domain, typically within fifty 

15 kilometers (50km) of the source, and how 

16 representative is the assimilated data of the local 

17 meteorological conditions? 

18 If the results differ by an inconsequential 

19 amount, this calls into question the value of using 

20 costly assimilated data as opposed to historical 

21 practices. 

22 And some sensitivity analyses might be 

23 necessary to document the improvement in modeling 

24 accuracy associated with the use of assimilated 

25 data. 
 1 PANEL DISCUSSION Vol. 1, p. 305 

 2 Our experience with the use of MM5 data shows 

 3 that the data quality at a specific location, or 

 4 even throughout the modeling domain may not 

 5 necessarily be superior to observations made in 

 6 that domain. 

 7 Now in one specific example, significant 

 8 variations existed between the MM5 data for 

 9 wind speed and direction compared to locally 

10 observed data. This was the Dallas-Fort Worth 

11 metropolitan area. 

12 Some other constraints; assimilated data is 

13 available chronologically, while modelers need data 

14 for the modeling domain. Each hour of MAPS-RUC 

15 data, this is the MAPS-RUC thirteen kilometer 

16 (13km) spacing, produces about a hundred and twenty 

17 megabytes (120mb) of data each hour. 

18 And if you store this for a year, that's one 

19 terabyte. 

20 Typically, data for only a few of the 

21 approximately hundred fifty thousand (150,000) 

22 locations in that domain are needed, and you have 

23 to extract these. 

24 The assimilated data is, I believe, only 

25 stored for about twelve (12) hours by NWS. One 
 1 PANEL DISCUSSION Vol. 1, p. 306 

 2 needs a robust, redundant, system to ensure capture 

 3 all the data. 

 4 And I think you mentioned NCDC, Dennis, just 

 5 now? 

 6 (Dennis Atkinson nods affirmatively.) 

 7 RICHARD SCHULZE: Okay. And the third thing, use of 

 8 assimilated data makes it more complicated for a 

 9 reviewing agency to assure that the proper data has 

10 been used. And you mentioned earlier the training 

11 requirement at the local agency, or even the 

12 regions within EPA. And this is going to be 

13 particularly troublesome. There are probably a 

14 hundred twenty (120) agencies within the United 

15 States that would have to be brought up to speed, 

16 and some of them may only process and crunch that 

17 data maybe every three years or whatever -- five 

18 years. This is a real chore for me to get up to 

19 speed. 

20 WARREN PETERS: Would you put that mic in front of you there? 

21 RICHARD SCHULZE: A little more? Okay, I can talk louder. 

22 Let's go to the next thing here; on specific 

23 technical issues, the planetary boundary layer 

24 heights of MM5. PBL is computed for the 

25 fundamental relationships in MM5 while AERMOD uses 
 1 PANEL DISCUSSION Vol. 1, p. 307 

 2 a somewhat more empirical approach. 

 3 MM5 generates several PBL options and you have 

 4 greater resolution as possible than with the AERMOD 

 5 scheme. Depending on how the scenario of a clear 

 6 sky transition from night to morning is handled, an 

 7 hourly PBL of modest dimension can create a very 

 8 high one-hour concentration. 

 9 That's been addressed in AERMOD to some 

10 extent. Some states have the one-hour, or a 

11 fraction of the hour, air quality regulations, and 

12 EPA has a one-hour CO standard. 

13 So, this gets fairly important for those kinds 

14 of situations. 

15 But computing compliance with these type of 

16 standards could be affected by this artifact. 

17 In general, however, PBL is important only 

18 when there are stacks of significant plume rise, 

19 typically large steam-electric power plants. 

20 But for most modeling on industrial and 

21 manufacturing sites: oil refineries, chemical 

22 plants, cement plants, some smelters and pulp and 

23 paper facilities, plumes tend to have sort of a 

24 limited interaction with the PBL particularly under 

25 convective turbulence conditions. 
 1 PANEL DISCUSSION Vol. 1, p. 308 

 2 Except for, again, fugitive emissions in these 

 3 facilities for the clear-sky hour after sunrise 

 4 situation. 

 5 As -- specific to AERMOD, how -- very near 

 6 calms are to be handled; well, EPA's made a policy 

 7 decision in ISC, as to how to handle these. 

 8 There's also been a decision made with SARA title 

 9 three (III) and RMP and PSM that's a little 

10 different policy decision. 

11 The first of all here -- issue here is 

12 modeling near ground level sources, such as waste 

13 treatment lagoons, fugitive emissions, cattle feed 

14 lots, accidental releases. Sensitivity analyses 

15 might be necessary to assess the various ways of 

16 treating calms with respect to permitting issues of 

17 mines and quarries. The max standards that are 

18 risk-based and permitting issues associated with 

19 fugitive sources. Such analysis should attempt to 

20 bring consistency to EPA's general approach, under 

21 SARA title three (III), RMP, PSM, and modeling for 

22 permits. 

23 It could be useful to confer with the NRC 

24 since they have a typical WRF case similar 

25 situation. 
 1 PANEL DISCUSSION Vol. 1, p. 309 

 2 Some states have developed policies on 

 3 modeling for the odors associated with waste water 

 4 facilities and animal feed lots, and these two (2) 

 5 can be considered. 

 6 But I think generally we're talking about -- 

 7 you know -- a policy issue here, but we should look 

 8 at it in a more holistic way with various people 

 9 that have interest in that subject. 

10 Deriving cloud coverage and cloud heights from 

11 MM5 moisture input. 

12 The issue here primarily is the missing data 

13 from ASOS. Again, it's probably a policy issue on 

14 whether to use MM5 moisture all the time, or only 

15 when cloud cover and cloud height are missing. 

16 One alternative would be to use the lesser of 

17 two values when both are computed, but this would 

18 lead to step function inconsistencies that are best 

19 avoided. 

20 Now the predicted cloud cover in MM5 is very 

21 sensitive to how a modeler chooses to simulate the 

22 cloud and precipitation generation processes. 

23 Hence a policy is necessary to describe how 

24 these processes should be modeled in MM5 for 

25 producing air quality related meteorological data 
 1 PANEL DISCUSSION Vol. 1, p. 310 

 2 sets. 

 3 The need for a policy in this would be 

 4 obviated if solar radiation and delta T at two and 

 5 ten (10) meters were added to the observed 

 6 parameters throughout the ASOS network. And this 

 7 is a -- something for NOAA to consider. 

 8 On-site local versus assimilated 

 9 meteorological data. 

10 Traditionally, the on-site data is best for 

11 modeling on-site sources, but it does not perform 

12 as well when sources away from the site are 

13 modeled. 

14 The purity of on-site data becomes tarnished 

15 as one computes concentrations five (5), ten (10), 

16 twenty (20) kilometers or more away from the 

17 source. 

18 Local, meaning nearby airport, or ASOS data, 

19 are presently allowed, but it becomes, by 

20 definition, less representative the further the 

21 sources and receptors are away. 

22 I'm just thinking of the Philadelphia example 

23 we just looked at. I don't know how AERMOD was set 

24 up to do all of the modeling, but I mean you ran 

25 from surface roughnesses over Delaware River or 
 1 PANEL DISCUSSION Vol. 1, p. 311 

 2 Delaware Bay that were point 0 0 one (.001) to 

 3 center City Philadelphia where the roughness was 

 4 maybe three or four meters; I don't know what was 

 5 used for center City. 

 6 Local or on-site data have an advantage in 

 7 Public Hearings because of the ease with which they 

 8 could be explained. Assimilated data, particularly 

 9 if it is interpolated, tends to add both -- shaves 

10 both the peaks and the valleys. 

11 This is the do-a- . You lose the -- the 

12 detail when you go to assimilated data, and this is 

13 a "Pablum" version of real data. 

14 Of course, one of our primary issues is 

15 whether the use of different data sets makes more 

16 than a consequential difference in computing 

17 concentrations and yet satisfying the regulatory 

18 need to err on the side of over estimation or maybe 

19 slight over estimation. 

20 Then the next one is a -- and that is it. 

21 Diagnostic and prognostic models. 

22 CALMET is a diagnostic model that provides a 

23 series of meteorological parameters for a series of 

24 grid cells based on analyzing meteorological data 

25 and the underlying terrain and land and sea 
 1 PANEL DISCUSSION Vol. 1, p. 312 

 2 interfaces. 

 3 MM5, although a prognostic model, is often 

 4 employed as a diagnostic model for modeling large 

 5 areas such as complete metropolitan areas or 

 6 portions of large states. 

 7 It generally lacks the detail both in terrain 

 8 and wind data for appropriate grid cells available 

 9 in the CALMET output. 

10 CALMET is useful because it applies its own 

11 set of physics on a smaller scale to capture 

12 relevant parameters for modeling on a meso- and 

13 micro-scale in a reduced data set that is more 

14 manageable than the MM5 output. 

15 The large volume of data from MM5 means that 

16 it is suited as an input for such regional models 

17 as CMAQ and CAMx. There is undoubtedly an 

18 opportunity to reconcile meteorological differences 

19 between the two models and others to achieve 

20 greater consistency. 

21 And this was alluded to again in this meeting. 

22 Next up. (Slide is projected.) 

23 The current version of AERMOD treats the 

24 entire modeling domain as a single grid cell. I 

25 suppose that one could make an argument that the 
 1 PANEL DISCUSSION Vol. 1, p. 313 

 2 assimilated data should be representative of a 

 3 point midway, perhaps even a third of the way, 

 4 from a source to a receptor. 

 5 There's not much data on that -- not at the 

 6 source, but somewhere between the source and the 

 7 receptor. 

 8 This would mean using assimilated data on a 

 9 thirteen kilometer (13km) grid or using present 

10 data and computing a met set for many intermediate 

11 locations. This seems pretty tortuous, I might 

12 add. 

13 Straight line plume models, such as AERMOD, 

14 work quite well in flat terrain, but when one gets 

15 to complex terrain or has land/sea interfaces, such 

16 plume models are much less effective. 

17 I'm not sure a Gaussian model can be naturally 

18 fitted into a grid assimilated data set. I see the 

19 most critical consideration to be how we can 

20 utilize the representative meteorological 

21 conditions at different grid cells in determining 

22 the plume dispersion and movement. 

23 Ideally, the plume should be allowed to 

24 respond to local conditions in the course of 

25 traveling, both at the surface and aloft. Can we 
 1 PANEL DISCUSSION Vol. 1, p. 314 

 2 really do this in a Gaussian model? 

 3 I think, Dennis, you said -- 

 4 DENNIS ATKINSON: (Shakes head negatively.) 

 5 RICHARD SCHULZE: No? 

 6 DENNIS ATKINSON: Probably not easily. 

 7 Probably not with AERMOD because to do that 

 8 would be to create a CALPUFF version of AERMOD, and 

 9 that's really not what we are going to be doing. 

10 Next one. 

11 (Slide is projected.) 

12 Grid spacing. AERMOD is simple. It has just 

13 one grid cell. For complex terrain, it may be 

14 useful to define a grid cell that has less than, 

15 say, point 0 0 five L (.005L) terrain variation 

16 where the L is the grid length size. But, you 

17 know, one would have to have special rules for 

18 land/sea interfaces, and the ratio of terrain to 

19 grid length size would also require some 

20 consideration of the elevation of the source. 

21 It's one thing to try to model a power plant which 

22 has a extraordinarily buoyant plume, but another to 

23 try to model a cattle feed lot or a quarry haul 

24 road. 

25 In addition, there could be significant 
 1 PANEL DISCUSSION Vol. 1, p. 315 

 2 differences based on surface roughness and albedo. 

 3 From a regulatory point of view, it may be 

 4 best to specify a rather small grid size and leave 

 5 it to the applicant to show that increasing the 

 6 grid size does not impair the result 

 7 consequentially. 

 8 And it would be helpful if CALPUFF or SCIPUFF

 9 could handle grid sizes of varying dimensions in a 

10 single run. 

11 It may be a challenge for the developers. 

12 And next one. 

13 (Slide is projected.) 

14 Storing assimilated data. 

15 The price of a terabyte of storage is now down 

16 to a thousand to two thousand dollars 

17 ($1,000-2,000), and I -- all I'm saying is, I 

18 guess, is what is already taking place with the use 

19 of NCDC or a similar body to archive the data. I 

20 guess they're doing it at the present time. 

21 Process data for U.S. sites produced from the 

22 archive by Government entities, or by the private 

23 sector, I think could be made -- you know -- 

24 available to others. The work done by the private 

25 sector generally is submitted with an analysis or 
 1 PANEL DISCUSSION Vol. 1, p. 316 

 2 an application for a regular, you know, for a 

 3 permit to a regulatory body. 

 4 And it would be useful if a modeling clearing 

 5 house had a directory of processed data sets, let's 

 6 say, that are less than five years old and from 

 7 where they might be obtained; that is, from which 

 8 regulatory body presumably has this, you know, data 

 9 set. That would be useful to have something like 

10 this data set available. 

11 And in final comments, there is a tendency to 

12 -- all us to think that newer is better. As a 

13 result, there is the risk that we will assume that 

14 processed assimilated data is likely to produce 

15 more representative results than traditional met 

16 sets. 

17 On the other hand, the computed -- if the 

18 computed concentrations are a small portion of a 

19 standard or increment, why should an applicant be 

20 required to spend the money to use the latest 

21 tools? It may make sense to authorize the use of 

22 traditional tools for preliminary analyses with the 

23 option for a regulatory body to request an analysis 

24 with assimilated data should the computed 

25 concentrations with existing data sets be too large 
 1 PANEL DISCUSSION Vol. 1, p. 317 

 2 a fraction of a standard or increment. 

 3 If assimilated data is used, then some 

 4 direction should be provided on whether data for 

 5 the nearest site should be used, or whether an 

 6 interpolation should be made of nine or sixteen 

 7 (16) sites -- you saw nine sets suggested in the 

 8 Philadelphia case -- that are nearest to the 

 9 applicant's main emissions. 

10 In our zeal to use better meteorology, it's 

11 important to understand the cost implications and 

12 whether there will be a significant enough 

13 differences in the results to justify the added 

14 cost. 

15 Thank you. 

16 BRET ANDERSON: I guess I'm last so I will make sure that I 

17 am brief, very brief here, because we are getting 

18 close to five o'clock (5:00). 

19 My name is Bret Anderson, and I'm an 

20 environmental scientist with the US EPA Region in 

21 Seven. And to give you a little bit on my 

22 background, I'm -- I'm kind of a translator between 

23 both worlds here. I spent the first eight years of 

24 my career as a near-field modeler, and then after 

25 the -- the tragedy of OTAG transitioned out of 
 1 PANEL DISCUSSION Vol. 1, p. 318 

 2 regional -- or near-field modeling into regional 

 3 modeling. 

 4 And like Dennis, I had a lot of experience in 

 5 dealing with -- you know -- the applications of 

 6 regional scale models, and particularly the use -- 

 7 in the use of MM5. 

 8 The -- I'm going to spare you a lot of the 

 9 philosophical discussion here on things, but I did 

10 want to reiterate one thing that Dennis had 

11 mentioned, which was, the differences between what 

12 it is that you're proposing to do here in terms of 

13 in -- the modeling that -- that we do in 

14 meteorological modeling for regional haze and ozone 

15 and PM two point five (2.5) SIPS, we're taking 

16 advantage of the fact that we were able to use the 

17 prognostic models in a retrospective sense, using 

18 the data assimilation. 

19 Additionally, we are also taking advantage of 

20 the fact that we are, to a great extent, we go 

21 through the various physics options that the models 

22 that we use that they have and we test them, and we 

23 find the options which work best for the particular 

24 application, or the particular air quality problem 

25 that we're in that we're dealing with. The reverse 
 1 PANEL DISCUSSION Vol. 1, p. 319 

 2 is oftentimes the case when you're applying a model 

 3 in a prognostic sense. 

 4 Oftentimes, the decisions that were made were 

 5 made in terms of physics options and things like 

 6 this, are tuned for performance in terms of being 

 7 able to generate for -- to generate a forecast in 

 8 the most computational efficient manner possible. 

 9 And so in some cases, what you find is is that 

10 there are models such as we'll go up to like the 

11 Pacific Northwest where the University of 

12 Washington is running the MM5 on a forecast mode, 

13 at a very fine resolution. 

14 But they are -- they have selected physics 

15 options which are the most computationally 

16 efficient, but from an air quality perspective they 

17 may not be the best particular selections, because 

18 they do not work the best in terms of, for example, 

19 producing accurate PBL estimates and things along 

20 that line. 

21 So those are things that we have to keep in 

22 mind, as we're using -- as we transition away from 

23 using -- you know -- the little philosophy of using 

24 mesoscale meteorological data assimilation towards 

25 forecast products in these things. 
 1 PANEL DISCUSSION Vol. 1, p. 320 

 2 To just, you know, summarize my philosophy on 

 3 this is, is I was asked to give a presentation for 

 4 the, you know, for the regional modelers in New 

 5 Orleans back in May, and it was on -- the topic of 

 6 the discussion was the use of alternative 

 7 meteorological products in models such as CALMET. 

 8 We, you know, in recent years, we have seen -- 

 9 the data products have transitioned beyond MM5, and 

10 have within -- we are starting to see RUC as a 

11 model that is being, you know, put forward to be 

12 used inside of CALMET. 

13 And I -- as I struggled -- you know -- going 

14 through my presentation, I kept going back to some 

15 of the discussions that some of the regional 

16 modelers have had, and they kept saying, well, RUC 

17 isn't MM5, and so therefore, it -- we shouldn't use 

18 it, because it's not MM5. 

19 And I kept trying to remind people that I can 

20 take the RUC data, and I can use it as my 

21 initialization data for MM5 and make the output 

22 from MM5 look very, very similar, if not identical 

23 to what the RUC data is. 

24 Conversely, I can take NCEP re-analysis data 

25 and run it, which a two and a half degree by two 
 1 PANEL DISCUSSION Vol. 1, p. 321 

 2 and a half degree resolution and take it and nest 

 3 MM5 down over the four corners region to a one 

 4 kilometer resolution and get a really bad solution, 

 5 but it's an MM5 solution. 

 6 So I kept asking myself what is -- what is the 

 7 message that we're trying to get across here in the 

 8 use of the prognostic data sets? And as I thumbed 

 9 through the guideline on air quality models, I came 

10 back to one particular statement that was in there, 

11 and this was on air quality models themselves, 

12 which says that, you know, these models that EPA 

13 puts forward in Appendix A are generally expected 

14 to be reliable; they are expected to be able to 

15 replicate a design concentration somewhere, 

16 sometime in the area of interest to where you're 

17 modeling. 

18 And so that philosophy led me to believe that, 

19 you know, the goal is not perfection in the use of 

20 the prognostic data sets here, we're not looking 

21 for perfection. What we're looking for is 

22 chronological consistency; where is the -- are the 

23 meteorological data products that are being put 

24 forward? 

25 Are they climatologically consistent in the 
 1 PANEL DISCUSSION Vol. 1, p. 322 

 2 sense of when you do a performance evaluation, you 

 3 compare them against historical observations that 

 4 they are, you know, that they are, you know, that 

 5 they are within bounds of reasons. 

 6 And, also, are the meteorological data sets, 

 7 are they sufficient resolution that they capture 

 8 the meteorological features of interest which are 

 9 important to the generation of those design 

10 concentrations. 

11 Since we are applying them -- this is more or 

12 less a probabilistic exercise. I realize that the 

13 determ- -- that the standards are deterministic, 

14 but we're still looking at in this terms of, we're 

15 looking at -- you know -- when we model five years, 

16 why are we modeling five years? 

17 And so the idea is to be able to capture the 

18 range of conditions which give rise to the design 

19 concentration here. So I -- I'll spare you the 

20 specific comments on that. But I think that's the 

21 one thing that we have to keep in mind here is that 

22 the applications of the air quality or the 

23 prognostic models, when we do them for SIP 

24 exercises is essentially, it is a fundamentally 

25 different exercise here, because we are only 
 1 PANEL DISCUSSION Vol. 1, p. 323 

 2 modeling limited data sets for limited time 

 3 periods, and so that perfection is one of those 

 4 things that we do strive for. 

 5 But in the realm of using, you know, gridded 

 6 products for AERMOD, or permit applications and 

 7 things along that line, I think it's more going 

 8 back to what the fundamental philosophy of what it 

 9 -- you know -- of why we're applying these air 

10 quality models to begin with. 

11 So, if these prognostic data sets are of 

12 sufficient quality, they meet whatever performance 

13 criteria are necessary and are appropriate for that 

14 particular application or the scale, that's -- 

15 that, I think is where this philosophy needs to 

16 focus itself for this discussion -- on this 

17 philosophy needs to focus itself. 

18 DENNIS ATKINSON: Thank you. 

19 Right now, I think, since it's getting late, 

20 I'm going to turn the floor over to anyone that 

21 wants to ask questions, and I'll take the mic and 

22 travel to whoever needs it. 

23 WARREN PETERS: I'll get the mic. 

24 DENNIS ATKINSON: (At the podium.) 

25 Does anyone have any questions, comments, for 
 1 QUESTIONS/Audience Vol. 1, p. 324 

 2 the panel? 

 3 Anything that you heard that you want to get 

 4 clarified. 

 5 ROBERT PAINE: Robert Paine. ENSR. 

 

 6 Couple of things. The issue of your comments 

 7 I think is an important issue and may have 

 8 something to do with the Philadelphia phenomenon; 

 9 found a thirty [ ] dealing with low-level 

10 sources, and if you have low or mechanical mixing 

11 heights with MM5, you will have a trapping 

12 situation that may be the cause of your 

13 discrepancies between the two approaches. 

14 And I've -- I've found that with another MM5 

15 database that was supplied from CALMET and -- and 

16 in a terrain situation without probably adequate 

17 fine grid, I -- I was getting lots of calm winds 

18 from that, but when we actually put a 

19 meteorological tower at the site, we had much 

20 higher winds. 

21 So I think it's very important to compare 

22 these meteorological gridded fields with real live 

23 data, and there's probably lots of those databases 

24 around, and we either -- need to collect them, 

25 especially with the -- in the year after 2000, 
 1 QUESTIONS/Audience Vol. 1, p. 325 

 2 because after 2000, with the next RAD radar getting 

 3 involved in the NCEP products, I think that's 

 4 greatly improved the wind speeds in those products. 

 5 The other thing I'd like to say, I don't know 

 6 if anyone that has ever gone to the NOAA ready web 

 7 site, but you can run a high speed model in real 

 8 time. It's linked to the NCEP forecast products, 

 9 and why can't we put CALPUFF and AERMOD into that 

10 sort of semi-realm where we can link the model to 

11 the readily available NCEP forecast winds, put in 

12 -- and right now you can put in the site, anywhere 

13 in the world, I think, or the northern hemisphere, 

14 at least, put in your emission parameters, and it 

15 will actually run them out for you and give you 

16 back graphics. 

17 It's very nuts, and if you haven't done it, 

18 you should go there and become a user. It's very 

19 informative, very useful. 

20 I think NOAA should look into that -- EPA and 

21 NOAA should look into a collaborative with Roland 

22 Draxler, beginning to get our up-to-date models 

23 linked to that -- that system. 

24 RICHARD SCHULZE: What was that web site, Bob? 

25 ROBERT PAINE: Well, it's NOAA -- put it in Google. NOAA and 
 1 QUESTIONS/Audience Vol. 1, p. 326 

 2 "ready", and you'll get it. 

 3 ALAN CIMORELLI: I think one comment I would have is that as 

 4 we go through this process, I think what we really 

 5 need to ask ourselves is, how well does -- how 

 6 well, does AERMOD -- and I'm just going to speak of 

 7 AERMOD for now, so how well does AERMOD perform 

 8 with this data? 

 9 We've got seventeen (17) databases sitting out 

10 there that we need to take, and some -- in some 

11 cases on-site -- most -- most cases is on-site 

12 meteorological data. 

13 We've gone through data -- a met data 

14 degradation, so we ask the question, if we got rid 

15 of the on-site data and went to National Weather 

16 Service data, how well, did the model do, and -- 

17 you know -- because one of the design criteria was 

18 -- criterias for AERMOD was that if it's going to 

19 be a replacement for ISC, we didn't want to put too 

20 much of a burden on the applications community -- 

21 you know -- that's -- so that readily available 

22 data could be used. 

23 And so all that data is sitting out there. I 

24 mean, I know -- I know Roger has it all organized 

25 very, very well, and I think the real -- the real 
 1 QUESTIONS/Audience Vol. 1, p. 327 

 2 test here is to take this -- to take gridded data, 

 3 however you want to construct it, and take some of 

 4 these databases and see how well the model performs 

 5 with that type of data. 

 6 And that gets to the point that Bret made, and 

 7 I could not agree with him more, we need to ask 

 8 ourselves the question, what question are we trying 

 9 to answer with these models? 

10 And if you are running -- if you are doing an 

11 ozone SIP, it's a very different question. You're 

12 doing relative reduction factors. You're looking 

13 at particulate monitors. It's very different than 

14 if you're doing a risk assessment. It's very 

15 different if you're doing a permit. 

16 You know, you have to ask the question, what 

17 are we going to be doing with this information, and 

18 I -- and to me the proof is in the -- as -- you 

19 know, it's in the pudding, and I think you do have, 

20 you know, you have to look at the components of it 

21 and ask how well all these things are going, but 

22 what I really think the question is is how 

23 sensitive is the concentrations going to be to 

24 this? 

25 Let's see, there was one other thing I wanted 
 1 QUESTIONS/Audience Vol. 1, p. 328 

 2 to say; the near calms, about Philly. Well, first 

 3 off, I think one of the reasons they were near calm 

 4 issues in AERMOD is that a lot of the sources in 

 5 Philadelphia were area sources. And as I had 

 6 mentioned earlier, we don't have the meander 

 7 working for air resources in AERMOD yet, that we 

 8 want to do. 

 9 If you get very, very light winds, all of 

10 that's going to be -- I mean, you're going -- 

11 you're going to have everything as a coherent 

12 plume, you're -- you're going to get some very high 

13 concentrations, and so like I said, in this AERMOD 

14 implementation guide, we've written up a bit of a 

15 work-around for that. 

16 But the hope is is that we will, at some 

17 point, get our treatment of meander in- -- into 

18 that. 

19 And the last thing I'll say is that, the 

20 question between how well -- how -- how well would 

21 you compare, say, the ISC predictions to MM5 

22 AERMOD. 

23 Well, I made a pre- -- I made a comparison 

24 between the ISC predictions in Philadelphia and 

25 CMAQ with MM5. Took the CMAQ predictions, and 
 1 QUESTIONS/Audience Vol. 1, p. 329 

 2 looked at the -- it was a four-kilometer grid 

 3 squares that we were going to use for CMAQ to get 

 4 secondaries. 

 5 Well, I took the primary production that was 

 6 in CMAQ, took the spatial average, compared it with 

 7 what was -- with what ISC showed, and I got 

 8 extraordinarily good comparisons, which was pretty 

 9 astounding to look at. 

10 I mean, so I -- I convinced myself that if 

11 that MM5 was constructing -- I thought it was 

12 constructing the wind field well enough to 

13 transport all this -- all of this -- all of these 

14 chemicals, in a way that I was getting the same -- 

15 very similar answers when I was taking one NWS 

16 measurement and running all these sources through 

17 ISC. 

18 So I thought that was -- that was actually 

19 pretty encouraging, so, --. 

20 I'm Al Cimorelli. (Mr. Cimorelli introduced 

21 himself after the fact.) 

22 DICK PERRY: Dick Perry, Bee-Line. I hadn't planned on it but 

23 one comment about the near calms, since people 

24 keep bringing it up, that I noticed just recently 

25 that may be showing up in the AERMOD processing 
 1 QUESTIONS/Audience Vol. 1, p. 330 

 2 that wasn't showing up before and that was the 

 3 decision that was taken in AERMET to treat variable 

 4 winds as calm. 

 5 And I -- that, I think, has the impact of 

 6 dramatically increasing the number of calms to 

 7 probably no reason, because there is a strict 

 8 definition from NCDC or -- or from the web -- in 

 9 the capturing of the variable wind as to what that 

10 variability is, and it's a non-zero wind speed and 

11 so a -- a random-type process that applies that -- 

12 to that factor, could eliminate a large number of 

13 those calms. 

14 Just as an aside. 

15 The other point that I -- as you were talking 

16 about having different studies, one I might suggest 

17 is that I might look to see if you already have 

18 what your trying to get to by doing this gridded 

19 met data, and do an evaluation that says, if I 

20 redefined the definition of near-field and applied 

21 steady state models only out to a distance where it 

22 -- where it really wasn't appropriate application, 

23 I mean, you didn't have that choice in the 1970s 

24 when you -- when you made that definition, but it 

25 looks like you do now, potentially. 
 1 QUESTIONS/Audience Vol. 1, p. 331 

 2 I mean, it's something that needs to be 

 3 evaluated, and if you redefine that near-field and 

 4 then applied -- looked at the appropriatability 

 5 (sic) of a CALPUFF to a mid-field if you will, that 

 6 you may have already what you're looking to try to 

 7 develop, and if you -- and if that would be -- 

 8 would play out by verification, then you -- your -- 

 9 you're building in for the future, because while 

10 John pointed out the -- it didn't resolve the -- 

11 the Grand Canyon if you fed it thirty-six (36) 

12 kilometer MM5 data I'll bet that CALMET would have 

13 a very good performance, if you fed it that four 

14 kilometer MM5 data, and it might be superior to 

15 what you saw from just the MM5 data set. 

16 And as that improves, there is no difficulty 

17 at all in bringing those, conceptually, in bringing 

18 those data sets, improved MM data sets into the 

19 CALMET regime and taking advantage of that. 

20 That's just a thought that I haven't heard 

21 tossed out and so -- I mean. 

22 MARK EVANGELISTA: If I may point one thing out to what John 

23 said earlier about what the NWS products were 

24 intended for, and it goes to what Al and Bret had 

25 alked talked about as well. 
 1 QUESTIONS/Audience Vol. 1, p. 332 

 2 It's -- it's -- we all know that the National 

 3 Weather Service, their mission is to protect lives 

 4 and property from severe weather, based on 

 5 precipitation for flash flooding, and they also 

 6 have an aviation component in their forecast 

 7 products that come out of NCEP. 

 8 But there is WRF coming down the line. There 

 9 is a WRF chem, and in the NOAA mission, air quality 

10 assessments are growing every day as part of their 

11 mission. 

12 There is a feedback mechanism for us to go to 

13 NCEP and not just between now and when WRF comes 

14 out, but as an ongoing process, and work with them 

15 to make sure that if there are treatments or 

16 parameters or anything that would benefit air 

17 quality, then it is in NOAA's interest, it is in 

18 NOAA's mission, to somehow consider that as they 

19 move those models forward. 

20 Granted, Bret's ha- -- hits it right on the 

21 head where computational efficiency is probably job 

22 one, but when it comes to scientific and just 

23 outright meteorological inputs, we may have a voice 

24 here that we probably had before but didn't know we 

25 had. 
 1 QUESTIONS/Audience Vol. 1, p. 333 

 2 But we may have a voice now, that we should at 

 3 least take advantage of. And, of course, it has to 

 4 be a knowledgeable voice. We have a lot more work 

 5 to do before we start asking for particular things, 

 6 but we could work with them as well, and tap into 

 7 their experiences and maybe get some of -- some of 

 8 these things that are -- that we're lacking now, 

 9 although we won't get FDDA. I mean, we're dealing 

10 in real time or -- or in the future. We're 

11 naturally not going to have the benefit of folding 

12 in some high quality hindsight. 

13 LARRRY SIMMONS: Larry Simmons with Energy and Environmental 

14 Management. 

15 I have more of a comment, I think, and it 

16 addresses something that John Vimont brought up. 

17 We've been doing class one modeling studies 

18 for some years now, and it was always some years 

19 ago, difficulty in getting protocols approved, 

20 because we just didn't have the databases 

21 available. 

22 We were using the National Weather Service 

23 information and arguing back and forth on 

24 protocols, told to use MM5, couldn't get the data, 

25 and one thing the National Park Service did, which 
 1 QUESTIONS/Audience Vol. 1, p. 334 

 2 I applaud them for, is that they provided that 

 3 information to the user community with the 1990, 

 4 1992 and 1996 data sets. All you had to do send 

 5 them a -- your hard drive, and they would download 

 6 that data, give it back to you, and they also 

 7 provided some very nice extraction utilities so you 

 8 could create the data sets that you needed, so they 

 9 went from complaining basically to helping us as a 

10 user community, and I wanted to say I appreciate 

11 that as a user. 

12 GEORGE SCHEWE: George Schewe, former EPA employee 

13 (laughter). 

14 I'm very pleased to be in the company of so 

15 many fine modelers. 

16 What my question is, and I'll throw this out 

17 from the perspective of the gridded meteorology 

18 that we're contemplating using, but also throwing 

19 this out to everyone here, but especially you guys, 

20 since this is your show. 

21 What consideration is being made for educating 

22 our regulatory agency folks? There is a few 

23 scattered people here, that are modelers, Chris 

24 Arrington, Ken MacBee, oh, they're gone, and -- 

25 (Laughter.) 
 1 QUESTIONS/Audience Vol. 1, p. 335 

 2 GEORGE SCHEWE: -- and the modeling capabilities of some of 

 3 these agencies is not very good. A recent Court 

 4 case where I was in a litigious type process, I had 

 5 used several different screening tools, did he go 

 __________ 

 6 cants and some other things, thank you, Dick, and 

 _____ 

 7 -- but some of those tools that they were comparing 

 8 to were screen three, they're still using screen 

 9 three and the level of expertise in some of the 

10 regulatory agencies, even at the state agency, is 

11 very low, and if they have a particular person who 

12 is pretty good, they have "a" particular person who 

13 is pretty good, (chuckles from audience), and then 

14 they have a lot of permit engineers that they just 

15 hired out of school. 

16 So what consideration is being made by the 

17 agency, by the guideline, by whoever, for 

18 accommodating the education of those folks so that 

19 when we go to them and say this is a better tool, 

20 they are going to say, we don't understand it. We 

21 can't re- -- even review your protocol; what do we 

22 do? 

23 (Laughter.) 

24 MARK EVANGELISTA: Well, Dennis had mentioned education there 

25 in his presentation, and, you know, as far as the 
 1 QUESTIONS/Audience Vol. 1, p. 336 

 2 out and out facts of how MM5 is working all we can 

 3 do is piece those things, taking it, as far as -- 

 4 ALAN CIMORELLI: (Interposing) Okay. 

 5 MARK EVANGELISTA: -- we can teach people how MM5 works. We 

 6 can teach people how PBLs are calculated. That's 

 7 -- that's what we are. We are meteorologists. We 

 8 can figure that stuff out. 

 9 It's -- I think your question is more along 

10 the terms of the delivery system of -- or any kind 

11 of setup as to -- as actual program to do that sort 

12 of stuff. 

13 ALAN CIMORELLI: I can speak for -- 

14 WARREN PETERS: Al, -- 

15 ALAN CIMORELLI: Al Cimorelli. I -- 

16 BRET ANDERSON: Bret Anderson, Region Seven (VII). 

17 ALAN CIMORELLI: Not Al Cimorelli. 

18 BRET ANDERSON: Yeah, not Al Cimorelli, for the record. 

19 (Laughter.) 

20 BRET ANDERSON: I want to make that clear. 

21 (Laughter.) 

22 BRET ANDERSON: The -- I give -- I'll give you the experience 

23 that we have in Region Seven; we have endeavored to 

24 provide training to our states. 

25 It is unusual to find where you -- you were 
 1 QUESTIONS/Audience Vol. 1, p. 337 

 2 either a state or a regional office actually might 

 3 have the cape- -- have the actual hands-on 

 4 capability of running the model. 

 5 But one of the things, I think there is two 

 6 different aspects of what we are talking about 

 7 here. 

 8 One is a general knowledge on how the modeling 

 9 gets done, but I think what's more important for a 

10 reg- -- you know -- for the general regulatory 

11 community is the, what I had mentioned earlier, as 

12 the acceptance criteria, is, you know, why -- what 

13 constitutes an acceptable data set, because you're 

14 not -- you as near-field modelers probably -- in 

15 your career probably, if you have the fortune of 

16 actually running one of these, you will find that 

17 it's -- you know -- it really realistically is 

18 probably no more labor intensive than running 

19 CALMET in many respects. 

20 But the analysis of the data, as it comes out, 

21 can be, you know, in trying to interpret the output 

22 of it, that's the -- you know -- that's the art 

23 form in all of this. 

24 But, the, you know, as I see it what we have 

25 done with our states is we have actually taken an 
 1 QUESTIONS/Audience Vol. 1, p. 338 

 2 MM5 modeling class on the road where we have went 

 3 out to the states and we have actually trained them 

 4 on how to run the model, how to process the data, 

 5 but actually the more important aspect of it, how 

 6 do we evaluate the data, I mean, what constitutes a 

 7 decent data set for use, you know, what are the, 

 8 you know --? 

 9 There are in the -- in the met community that 

10 does, you know, these are quality simulations for 

11 SIP purposes, you know, Dennis McNally, you know, 

12 is probably one of the best experts that there are 

13 in this. 

14 He's wrote a wonderful program called MAPS 

15 that does exactly what we are talking about; 

16 performance evaluation. 

17 Environ has another one called Met Stat that 

18 we do these things, and I think one of the things 

19 that, I think as we move forward, one of the things 

20 that I wanted to work with, you know, the air 

21 quality modeling group on, was taking those 

22 experiences that we have in the SIP realm and 

23 seeing if we can't find some common bridge and take 

24 that out to the regulatory community, so that the 

25 -- so that the regional and the local modelers can 
 1 QUESTIONS/Audience Vol. 1, p. 339 

 2 utilize the experience and maybe even some of the 

 3 tools; teach them how to do that, or at least here 

 4 is the acceptance criteria that we normally would 

 5 use for these things to determine whether or not 

 6 these are acceptable data sets, and that way, if 

 7 somebody comes in with a -- well, we'll just say a 

 8 nonstandard data set, that at least if you put the 

 9 burden on the applicant or the person proposing the 

10 use of that data set to demonstrate that it has 

11 this -- that it meets certain acceptance criteria, 

12 you at least know what you're looking for at that 

13 point. 

14 And I think that's where -- I think that's 

15 where we have been in Region Seven (VII), and where 

16 I'd like to -- you know -- take the commun- -- you 

17 know -- the regional and the state modelers as a 

18 whole as we move forward in the gridded met 

19 discussion to that level, because I think that's 

20 the more important aspect of it. 

21 DENNIS McNALLY: I think, Bret, to go along with that, I 

22 would strongly encourage that -- I guess I have 

23 this vision that some day there would be this data 

24 -- a web site where you would point and click on 

25 your domain, and it would grab your -- you know -- 
 1 QUESTIONS/Audience Vol. 1, p. 340 

 2 your MM5 data for you. 

 3 But in that pipe dream, I was really 

 4 encouraged that when your met data comes down, also 

 5 have the evaluation products of that same data 

 6 there. 

 7 I know I had a call from a consulting firm the 

 8 day before I left, moaning about how hard it was to 

 9 see this data. Well, it is, you know, I think all 

10 of us have developed tools over the years to look 

11 at data. 

12 When we start looking at the gridded fields, 

13 well, gee, all our tools are broke now. Well, we 

14 need to either redevelop those tools or at least 

15 make the -- easy to understand. I mean, people can 

16 understand a time series clock. That's not a 

17 mystery. That takes the mystery of a gridded model 

18 away. 

19 And, also, to let you know, maybe the model is 

20 really broke there. 

21 But -- so if you could have those products 

22 available, I think that would be a big win. 

23 ALAN CIMORELLI: This is Al Cimorelli, again. 

24 I couldn't agree with you more. I think that 

25 that is probably one of the most important issues 
 1 QUESTIONS/Audience Vol. 1, p. 341 

 2 that people need to realize. 

 3 We've got two different worlds here. We've 

 4 got a regional scale world, which is actually 

 5 pretty small compared to the -- to the local scale 

 6 world. 

 7 I mean, most of the modeling in this country 

 8 is not done by regional scale modelers; it's done 

 9 by permit modelers. I mean it's being done all the 

10 time, and you have -- in many regards, you have 

11 engineers who have come out of school, who have 

12 never had a fluid dynamics class and never heard of 

13 meteorology, and they are handed a program to run. 

14 And, they're going to be running that program. 

15 When we first started our design for AERMOD, 

16 we were -- we were, I think, steadfast in saying 

17 we've got to transition this over to a community 

18 that thinks that the atmosphere has a couple of 

19 discrete turbulence classes, you know. 

20 I mean, you've got a wind speed, you've got a 

21 wind direction, you've got a temperature, and 

22 you've got A, B, C, D, E, or F, and that's it, and 

23 everybody understands it. And that's what they 

24 think the atmosphere is. 

25 You've got to bring in the Monin-Obukov links 
 1 QUESTIONS/Audience Vol. 1, p. 342 

 2 and friction velocities and -- and probability 

 3 density functions, and I mean, and they're going to 

 4 go nuts. 

 5 So you have -- and I think you have to know 

 6 the audience. I mean, that's what Microsoft does. 

 7 I mean they would've sold a damn thing if they 

 8 didn't put most of their money into education. 

 9 Well, we tried to do that with AERMOD. That's 

10 why we documented it the way we did. That's why we 

11 rolled it out the way we did, and we tried to -- we 

12 tried to educate the community as we went along as 

13 a transition from the PG world to the PBL world, 

14 and I would -- you know -- I would say that I don't 

15 know how successful we've been. Only time will 

16 tell, but we certainly brought that into the very 

17 beginnings of the design of what we were doing, and 

18 I think -- I think your point is -- is right on 

19 mark, that unless we do that and until we do that, 

20 we can just -- we'll talk among ourselves, and it 

21 won't mean a hill of beans. It won't matter at 

22 all. 

23 RICHARD SCHULZE: Al, I'd like just to -- you know -- a 

24 follow-up on your comment. 

25 I'm thinking back to the people that have 
 1 QUESTIONS/Audience Vol. 1, p. 343 

 2 attended the classes that I have taught over the 

 3 years on the fundamentals of dispersion modeling, 

 4 and they appeal -- about sixty percent (60%), 

 5 seventy percent (70%), that attend are from 

 6 industry; about ten percent (10%) from regulatory 

 7 agencies, and about twenty percent (20%) are from 

 8 consulting firms. 

 9 And if I were to break down the educational 

10 background of those people that want to learn about 

11 dispersion modeling, I would say that, well, the -- 

12 probably ten percent (10%) are meteorologists, 

13 probably about half are chemical and mechanical 

14 engineers that have had a lot of exposure to fluid 

15 dynamics, and about forty percent (40%) are civil 

16 engineers or science majors, you know, chemistry, 

17 biology, mathematics, maybe geology, that are 

18 trying to learn this thing with just a basic 

19 science background. 

20 So that's the audience out there that is 

21 interested in learning about dispersion modeling. 

22 That's roughly the audience that will be using 

23 AERMOD, and who have used ISC. 

24 And I think that's important to recognize. 

25 WARREN PETERS: It's almost five thirty (5:30). I see a lot 
 1 QUESTIONS/Audience Vol. 1, p. 344 

 2 of tired faces out in the audience, and I know I'm 

 3 tired. 

 4 I would say that our meeting is closed 

 5 officially for the day, if you want to cut the 

 6 record. 

 7 _______________________________ 

 8 (DISCUSSION OFF RECORD.) 

 9 _______________________________ 

10 _____________________________________________________________ 

11 (WHEREUPON, THE CONFERENCE WAS ADJOURNED AT 5:27 P.M.) 

12 _____________________________________________________________ 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 
 Vol. 1, p. 345 

 C E R T I F I C A T E 

 _____________________ 

 

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 Public in and for the State of North Carolina, duly 

 commissioned, qualified and authorized to take and 

 certify conferences, do hereby certify that on Thursday, 

 September 22, 2005, I stenographically reported the 

 foregoing conference at the time and place aforesaid, 

 and that same was reduced to typewritten form under my 

 direct supervision; that the transcript contained 

 herein, pages 1-345 inclusive, is a true and correct 

 transcription of said proceedings to the best of my 

 ability and understanding; that I am not related to any 

 of the parties to this action; that I am not of counsel; 

 and that I am not interested in the event of this cause. 

 IN WITNESS WHEREOF, I have hereunto set my hand 

 and affixed my official Notarial seal, this the 4th day 

 of April, 2005. 

 _______________________________ 

 NOTARY PUBLIC 

 

 My Commission expires: 7-16-06 

 

 

 

 

 

 

 

 

 

 

 Manie P. Currin and Associates 

 Court Reporters 

 203 East Industry Drive - Suite C 

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 Telephone: (919) 693-6954 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 346 

 2 KEYWORD INDEX 

 _____________ 

 3 

 4 1. AERMAP 21. cell 

 5 2. AERMET 22. cells 

 6 3. AERMOD 23. clearing house 

 7 4. AERMOD-PRIME 24. complex 

 8 5. AERSCREEN 25. concentration 

 9 6. AERSURFACE 26. concentrations 

10 7. air 27. data 

11 8. albedo 28. database 

12 9. algorithm 29. databases 

13 10. algorithms 30. datum 

14 11. appendix 31. default 

15 12. ASOS 32. DEM 

16 13. atmosphere 33. dispersion 

17 14. BART 34. domain 

18 15. boundary 35. downwash 

19 16. Bowen 36. downwind 

20 17. calm 37. EPA 

21 18. CALMET 38. ETA 

22 19. calms 39. Federal 

23 20. CALPUFF 40. fence line 

24 

25 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 347 

 2 KEYWORD INDEX 

 _____________ 

 3 

 4 41. file 61. MAKEMET 

 5 42. files 62. mesoscale 

 6 43. forecast 63. met 

 7 44. forecasts 64. meteorological 

 8 45. grade 65. meteorologically 

 9 46. gridded 66. mixing 

10 47. group 67. MM5 

11 48. groups 68. model 

12 49. guidance 69. Model Clearing House 

13 50. guide 70. model evaluation 

14 51. guideline 71. modeler 

15 52. guidelines 72. modelers 

16 53. implement 73. modeling 

17 54. implementation 74. Monin-Obukov 

18 55. implementing 75. monitor 

19 56. ISC 76. monitors 

20 57. ISC-PRIME 77. NCDC 

21 58. IWAQM 78. near-field 

22 59. layer 79. No Obs 

23 60. layers 80. NOAA 

24 

25 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 348 

 2 KEYWORD INDEX 

 _____________ 

 3 

 4 81. NWS 101. PSD 

 5 82. OAQPS 102. puff 

 6 83. observation 103. ratio 

 7 84. observations 104. ratios 

 8 85. observed 105. receptor 

 9 86. ozone 106. regime 

10 87. parameter 107. regimes 

11 88. parameters 108. regulatory 

12 89. PBL 109. RUC 

13 90. PBLs 110. rule 

14 91. plume 111. run 

15 92. precedents 112. rural 

16 93. PRIME 113. scale 

17 94. processor 114. scaling 

18 95. processors 115. SCRAM 

19 96. profile 116. screening 

20 97. promulgated 117. sensitivity 

21 98. promulgation 118. service 

22 99. protocol 119. site 

23 100. protocols 120. slope 

24 

25 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 349 

 2 KEYWORD INDEX 

 _____________ 

 3 

 4 121. source 141. work group 

 5 122. speed 142. 

 6 123. stack 143. 

 7 124. stacks 144. 

 8 125. statistical 145. 

 9 126. steady state 146. 

10 127. surface 147. 

11 128. surrogate 148. 

12 129. temperature 149. 

13 130. terrain 150. 

14 131. toxic 151. 

15 132. toxics 152. 

16 133. turbulence 153. 

17 134. urban 154. 

18 135. variability 155. 

19 136. weather 156. 

20 137. wind 157. 

21 138. wind speed 158. 

22 139. wind speeds 159. 

23 140. winds 160. 

24 

25 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 350 

 2 

 3 Page Ref No. Keyword = "AERMAP" 

 4 ____ _______ __________________ 

 5 

 6 38 5 have AERMAP the terrain data preprocessor, and then 

 7 60 15 AERMAP, and Peter Eckhoff is involved in setting up 

 8 60 20 appreciate AERMAP, Peter. 

 9 60 23 EPA, and I've been assigned to improve AERMAP. 

10 60 24 And -- well, the purpose of AERMAP is to 

11 61 3 AERMAP uses a number of digital elevation 

12 61 14 same point on the earth, and AERMAP --we were asked 

13 61 15 in AERMAP to adjust the formula so that they were 

14 61 21 This is an example of an AERMAP output file, 

15 61 24 directly into AERMAP -- AERMOD. 

16 62 2 modifications that were made to AERMAP. 

17 62 7 format for including into AERMAP, since the cost 

18 62 20 AERMAP. 

19 64 12 and we also include it as part of the AERMAP 

20 64 14 the AERMAP package and that automatically -- well, 

21 64 21 use of AERMAP were two different DEMs, and we've 

22 65 25 And these codes are in the AERMAP manual. 

23 66 9 checking. We did add some error checks to AERMAP, 

24 66 11 people about AERMAP not processing their data sets 

25 67 5 copy of that Blue Book format is in the AERMAP 

26 67 13 data on into AERMAP run, and we should function 

27 67 16 meters that have caused AERMAP to crash. 

28 67 23 And status of AERMAP; I'm working on 

29 68 13 AERMET and AERMAP. 

30 118 25 In terms of AERMAP, as you heard Pete Eckhoff 

31 120 3 As AER- -- as AERMAP presently exists, you 

32 120 14 AERMAP in the future and prove it, so that people 

33 

34 Page Ref No. Keyword = "AERMET" 

35 ____ _______ __________________ 

36 

37 38 4 The AERMET meteorological preprocessor, we 

38 51 7 WARREN PETERS: And next on the AERMET presentation, I'd 

39 51 10 He's been directly responsible for the AERMET 

40 51 16 you to help us understand AERMET. 

41 51 25 into -- has gone into AERMET, and then get a -- get 

42 52 3 AERMET. But basically most of it's going to be the 

43 52 12 So the science in AERMET really was sort of 

44 52 14 AERMET is essentially a boundary layer model, 

45 53 8 The AERMET is designed to look at, or to 

46 53 11 What the dispersion -- the science in AERMET 

47 53 19 The algorithms in AERMET are -- are based on 

48 54 23 The boundary of the AERMET algorithms for the 

49 55 18 And in the AERMET, we use a Bowen ratio, it's the 

50 57 3 alternative method which we also use in AERMET is 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 351 

 2 

 3 Page Ref No. Keyword = "aermet" 

 4 ____ _______ __________________ 

 5 

 6 57 17 release of AERMET in 2002. 

 7 58 4 better which is in the current version of AERMET. 

 8 58 5 In terms of running AERMET basic, you know, I 

 9 58 23 by AERMET, the oldest is the CD one forty-four 

10 59 9 it through -- through AERMET. 

11 59 17 AERMET with gridded met data, taking what's good 

12 59 19 capabilities of AERMET to tailor these -- to tailor 

13 59 22 by AERMET, the Forecast Systems Laboratory, FSL 

14 60 12 helped us understand AERMET and its power this 

15 68 13 AERMET and AERMAP. 

16 76 14 based on the tables in AERMET, and you can select 

17 83 22 characteristics data that will go into AERMET which 

18 85 14 pasted directly into AERMET. 

19 96 11 are out of the AERMET user's guide. 

20 121 23 that's been placed in AER- -- in AERMET now is 

21 137 14 roughness goes into AERMET. 

22 164 10 trying to put MM5 into AERMET, or into AERMOD, I 

23 229 4 variables that are needed by AERMET from MM5 to 

24 230 8 we want to do that is to run AERMET using MM5 and 

25 230 14 both of those through AERMET, and compare the 

26 230 17 AERMET, then we are going to run it through AERMOD 

27 231 5 modified AERMET using MM5 and NWS and analyze those 

28 247 7 might in fact do not as well as, say, AERMET and 

29 248 24 want to go through AERMET. 

30 249 4 AERMET, except that -- except that you may, as Joe 

31 249 5 pointed out, you know, AERMET may be able to do a 

32 254 10 National Weather Service data through AERMET, you 

33 254 19 parameterizations that are now currently in AERMET 

34 258 8 So when we compare MM5 to what AERMET does, 

35 259 9 and -- and stick it into AERMET. 

36 259 21 AERMET and we come out with a solution for now. 

37 268 4 handful of others creating AERMET, we have the NWS, 

38 272 22 of AERMET and stick in MM5 in AERMET and rerun 

39 272 23 AERMET and see how that worked. Then we wanted to 

40 272 24 just maybe skip AERMET altogether and go straight 

41 276 3 Then AERMET and AERMOD using the observation data 

42 276 8 AERMET output, in other words, bypass AERMET, we 

43 276 11 output a parameter that AERMET output, we just 

44 276 12 jumped over AERMET and used the MM5 parameter. 

45 276 17 go into AERMET, or to go into AERMOD. 

46 276 18 We wanted to allow AERMET to do its thing, but 

47 276 21 were able to bypass AERMET altogether. 

48 276 25 have do let AERMET take some -- some of the values. 

49 277 3 AERMOD value that AERMOD calculated, -- not AERMET; 

50 277 6 over AERMET, we have to jump over the AERMOD 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 352 

 2 

 3 Page Ref No. Keyword = "aermet" 

 4 ____ _______ __________________ 

 5 

 6 277 12 AERMET, that we thought we would take fullest 

 7 281 19 consistent with the AERMET treatment of the -- of 

 8 282 13 through AEDMed -- AERMET and compare them to what's 

 9 283 9 AERMET calculations done only for non-missing times. 

10 283 19 have in the NWS data run through AERMET. 

11 283 21 realize what MM5 is doing versus what AERMET is 

12 283 23 what AERMET is doing, but fortunately, someone who 

13 283 24 does know what AERMET is doing is sitting right in 

14 287 25 the black bars, and MM5 and then the NWS AERMET 

15 288 7 here; first of all, AERMET does collapse fairly 

16 288 15 in the way MM5 and AERMET are -- are wired to do 

17 288 23 raw values through AERMET's algorithm and see if we 

18 288 25 instead of replace AERMET output with MM5, is 

19 289 2 replace AERMET input with MM5, put the MM5 met data 

20 289 3 into AERMET, and then crank it through that AERMET 

21 289 18 MM5 data into AERMET's algorithm, we get this 

22 290 16 AERMET outputs and the MM5 outputs, and we've got 

23 291 3 meteorology with AERMET. This scale, I know you 

24 291 5 AERMET when we move along. 

25 291 22 up of the factor by which MM5 exceeds the AERMET 

26 330 3 decision that was taken in AERMET to treat variable 

27 

28 Page Ref No. Keyword = "AERMOD" 

29 ____ _______ __________________ 

30 

31 25 8 AERMOD. 

32 25 19 (laughter) AERMOD, oh, AERMOD, where for art thou? 

33 25 24 assurances that AERMOD is as close to being 

34 27 9 AERMOD, and for next two days, let's just kind of 

35 27 12 the new era that we'll have with AERMOD, the issues 

36 28 20 AERMOD, we'll also touch on CALPUFF. 

37 33 10 TYLER FOX: I believe the -- our first session is on AERMOD 

38 33 12 of presentations about the AERMOD modeling system 

39 34 3 be on the AERMOD modeling system. 

40 34 5 addressing AERMOD issues, and all the team members 

41 34 10 AERMOD modeling system, and that will be the first 

42 34 14 in AERMOD. It's called the AERMIC Committee and it 

43 35 8 Just a brief regulatory history on AERMOD. 

44 35 11 AERMOD was proposed in April of 2000. There 

45 35 12 was a Seventh modeling Conference where the AERMOD 

46 35 17 of the significant changes we made to AERMOD, we 

47 35 20 consequence analysis that some of the AERMOD 

48 36 7 AERMOD has been updated since the proposal 

49 36 10 about putting PRIME into AERMOD. At the proposal 

50 36 11 we talked having ISC-PRIME and AERMOD separate 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 353 

 2 

 3 Page Ref No. Keyword = "aermod" 

 4 ____ _______ __________________ 

 5 

 6 36 15 AERMOD. And it actually is -- the conclusion of 

 7 36 17 looking even better in AERMOD, PRIME and ISC PRIME, 

 8 36 24 domains and did other things to the AERMOD 

 9 37 24 That is the background information on AERMOD. 

10 38 2 It's a modeling system. AERMOD really has 

11 38 6 AERMOD itself, which is the dispersion model. As 

12 38 7 you can see, because the AERMOD is little bit more 

13 38 12 data into AERMOD properly. 

14 38 21 which is now an important feature to the AERMOD. 

15 39 5 to be true moving from ISC to AERMOD. It's a more 

16 39 8 of data that go into AERMOD. 

17 39 12 a full-blown AERMOD run to get estimates, or 

18 39 17 The documentation, I believe that AERMOD is 

19 40 8 that are going into AERMOD. Al Cimorelli and Steve 

20 40 14 showing how AERMOD does perform much better than 

21 40 19 using AERMOD, and there are changes in AERMOD. 

22 40 22 Basically we see better science in AERMOD, and 

23 40 24 boundary layer concepts all now built into AERMOD, 

24 41 6 so AERMOD has much more power that way. 

25 41 12 from the surface of the earth. And AERMOD 

26 41 20 ISC to AERMOD. And it's a fairly thorough list of 

27 41 24 Now we've worked real hard in the AERMOD 

28 42 3 control across country with an AERMOD is just 

29 42 7 you to get up and get basic AERMOD up and going, 

30 42 13 transition to the AERMOD model. 

31 42 15 have better science in here. Now, AERMOD will 

32 43 21 ratios. This is the AERMOD concentration to the 

33 43 23 So a value of one at AERMOD and ISC basically 

34 43 25 sets at AERMOD was twice as high. A value of point 

35 44 2 five (.5) meant that AERMOD was half as high as 

36 44 6 (48) cases that AERMOD and ISC were pretty much the 

37 44 20 basically, you see that there AERMOD and ISC 

38 44 25 ratio for the mod- -- AERMOD and ISC is about as 

39 45 12 move into the AERMOD world. 

40 45 24 We compared AERMOD to ISC3 and we compared 

41 45 25 AERMOD to ISC-PRIME. They both were a part of the 

42 46 3 this case, notice when we compared AERMOD to ISC, 

43 46 6 the AERMOD was presenting concentrations a little 

44 46 13 brought PRIME into AERMOD, the goal was to make it, 

45 46 16 into the AERMOD it would produce other kinds of 

46 46 19 And here, we want AERMOD and ISC-PRIME to 

47 47 5 performance between AERMOD and ISC-PRIME. 

48 47 9 I believe the AERMOD presentation is -- is a 

49 47 17 AERMOD, of course, is doing much more of a 

50 47 19 expecting AERMOD to be quite a bit lower than 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 354 

 2 

 3 Page Ref No. Keyword = "aermod" 

 4 ____ _______ __________________ 

 5 

 6 47 20 AERMOD -- I'm sorry, than ISC, and indeed we find 

 7 47 23 that AERMOD was about a quarter as high 

 8 48 7 cases AERMOD in complex terrain, produced 

 9 48 14 because AERMOD performed better. 

10 48 17 different data bases in evaluating AERMOD. It was 

11 48 20 When we had the case of no downwash, AERMOD 

12 48 24 With the downwash scenarios, AERMOD out 

13 49 7 We compared AERMOD to ISC-PRIME, and that's 

14 49 14 So what we're saying is, AERMOD outperformed 

15 49 19 That is pretty much a summary of -- of AERMOD 

16 49 21 activities with AERMOD that I'd like to present to 

17 50 3 version of AERMOD that will run in parallel. 

18 50 10 Roger Brode, minor upgrades such as running AERMOD 

19 50 14 AERMOD run. 

20 50 18 modification to AERMOD in one run. 

21 50 24 AERMOD package now in BETA test mode. 

22 51 5 So that's the overview of AERMOD and its 

23 52 6 it's taking a long time to promulgate the AERMOD 

24 52 9 in the model formulation document for AERMOD, you 

25 58 12 actually creates the files that are used by AERMOD. 

26 58 15 AERMOD uses to develop profiles of turbulence 

27 58 18 when AERMOD goes to calculate a concentration and 

28 59 10 We talked about AERMOD as -- is a local scale 

29 60 6 end of the whole series of AERMOD presentations, so 

30 60 11 preprocessors in the AERMOD package. Desmond has 

31 61 2 are processed by AERMOD. 

32 61 20 input into AERMOD. 

33 61 24 directly into AERMAP -- AERMOD. 

34 68 4 our AERMOD presentations. 

35 68 12 been an overview of AERMOD and the two preprocessors, called 

36 69 5 called AERSCREEN is a screening model for AERMOD. And 

37 69 10 AERMOD in a refined mode but do it in relatively 

38 72 23 be at least as high as AERMOD. 

39 73 4 what AERMOD and ISC does, and that is, "store and 

40 73 20 refined mode with AERMOD. And actually, AERMOD is 

41 73 23 So you've got yourself an AERMOD control file, 

42 74 14 results, actual full-blown AERMOD runs where we 

43 76 12 parameter in the AERMOD. 

44 80 4 AERSCREEN results to AERMOD. 

45 80 7 high as AERMOD, and we had a number of people that 

46 80 11 This is, again, a ratio of AERSCREEN to AERMOD 

47 81 11 over predicts AERMOD that's also another concern, so 

48 81 15 AERMOD. 

49 83 19 the tool for AERMOD called AERSURFACE. 

50 83 23 will spin into AERMOD. 
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 6 85 19 understand just how AERMOD is responding to changes 

 7 88 9 AERMOD with a study of source characteristics. . 

 8 89 9 had AERMOD, in the urban setting. Again, you see the 

 9 95 21 AERMOD are pretty sensitive to the choice venue 

10 97 5 the rural setting for AERMOD and for the sixteen 

11 97 12 AERMOD, again, for the Oklahoma City met data. 

12 98 6 concentration that -- that AERMOD output. The 

13 100 5 So that concludes the AERMOD -- I'm sorry, no, 

14 100 15 AERMOD Implementation group and the exciting things 

15 105 8 Okay, AERMOD implementation process. Why do 

16 105 16 Number one; ISC and AERMOD, and I think this 

17 105 20 or AERMOD to do their permitting. Okay? The 

18 105 22 permit for a SIP that uses ISC or AERMOD. 

19 106 4 away, and it's going to be AERMOD and AERMOD only. 

20 106 16 AERMOD, but we have been able to think through a 

21 108 9 with -- with AERMOD experts. 

22 109 23 consistent regulatory application of AERMOD. 

23 110 14 a model like AERMOD, I think that that would be a 

24 111 23 That's the -- that's the guidance where AERMOD 

25 112 2 shalt use AERMOD". 

26 112 16 type of model that AERMOD is. 

27 112 18 speakers that AERMOD is quite different from the 

28 116 15 taken an output from WRF and ran AERMOD with it for 

29 116 21 in a second, AERMOD for reasons of economy we were 

30 117 23 have a receptor that's down-sloped from it, AERMOD, 

31 122 23 beginning of it, I said, well, I should use AERMOD, 

32 123 2 AERMOD. We'll all be dead by the time the thing 

33 124 5 AERMOD. They're going to come to the local scale 

34 124 8 And in that regard, right now, AERMOD does not 

35 124 18 in AERMOD to -- to weight the two clones, that are 

36 125 10 can we use AERMOD for that? And so those are 

37 125 15 know, we get Bowen ratio now into AERMOD purely by 

38 126 7 place is one, ISC or AERMOD, can be used in the 

39 127 3 And finally, we're going to improve AERMOD, 

40 127 11 WARREN PETERS: As I said before, that concludes the AERMOD 

41 133 21 think because of the way AERMOD tries to construct 

42 134 13 that there's an agreement between AERMOD and 

43 134 16 AERMOD we're glad is out performing ISC. 

44 135 2 -- as far as the agreement between AERMOD and ISC, 

45 135 10 WARREN PETERS: Right. When we put PRIME into AERMOD, 

46 135 13 concentrations from AERMOD PRIME versus ISC-PRIME 

47 135 17 of PRIME into AERMOD, because it's almost 

48 135 19 AERMOD and ISC would have in the way it calculates 

49 136 3 comparing AERMOD-PRIME to ISC-PRIME, AERMOD out- -- 

50 137 15 Surface roughness is also used in AERMOD to 
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 6 137 18 AERMOD, so you -- you would expect to see a little 

 7 138 3 situation with the AERMOD than we were in the early 

 8 139 11 statistical comparison between ISC and AERMOD and 

 9 140 14 AERMOD model, is that --? 

10 142 17 think in those terms for AERMOD. 

11 147 18 AERMOD. We had a full set OF AERMOD 

12 164 10 trying to put MM5 into AERMET, or into AERMOD, I 

13 170 13 later on actually, you just had AERMOD this morning 

14 179 22 And it says in this report that when AERMOD is 

15 179 24 calming effect for a moment, but when AERMOD is 

16 179 25 promulgated, we will go to the AERMOD 

17 180 8 available option, because AERMOD is very, very 

18 189 10 Land Manages was that upon promulgation of AERMOD 

19 200 11 and whether we should be using AERMOD or whether we 

20 201 4 Now that we are moving to AERMOD, I think that 

21 206 21 AERMOD implementation guide; something that's a 

22 213 7 CALPUFF. That's -- that's AERMOD and the like. 

23 214 22 to the imminent promulgation here of the AERMOD, 

24 214 23 and during the AERMOD discussions we talked about 

25 215 9 AERMOD. It's broad, and all and in fact we're 

26 221 7 using it in AERMOD and more contemporary NWS-type 

27 221 14 gridded met data into AERMOD and CALPUFF; also 

28 222 2 At that point, AERMOD was very much underway; 

29 222 4 effort going toward AERMOD, and so -- and there was 

30 226 25 That would include AERMOD, and the on-the-way-out 

31 228 12 procedures to AERMOD. 

32 228 14 AERMOD. 

33 228 24 incorporate MM5 into AERMOD, and basically there is 

34 229 5 drive AERMOD. 

35 229 16 AERMOD, is to utilize additional variables that are 

36 229 18 physics within AERMOD. 

37 229 19 Of course, we all know that AERMOD is an 

38 229 20 improvement over ISC, but if we can drive AERMOD 

39 229 25 input that into AERMOD and for part one, AERMOD 

40 230 7 We want to leave AERMOD intact and so the way 

41 230 17 AERMET, then we are going to run it through AERMOD 

42 230 21 want to modify possibly AERMOD and utilize new 

43 230 24 of AERMOD, you know, possibly replace modules. I 

44 231 6 results and then run AERMOD with the modifications 

45 231 12 AERMOD and see exactly what kind of changes we get 

46 232 4 used for, and -- which would be AERMOD, CALPUFF and 

47 233 7 output. That was a useful from AERMOD. And these 

48 233 11 a look at, and TKE, currently AERMOD uses 

49 233 24 flux is currently used in AERMOD, and that could be 

50 236 19 representativeness issues. Of course, AERMOD has 
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 6 246 24 CALMET output into AERMOD fields at -- all of those 

 7 249 11 AERMOD and ran it through there and couldn't figure 

 8 250 8 to really reformulate the urban part of the AERMOD 

 9 251 15 for AERMOD. And I know many of the authors are in 

10 251 19 talking about, is the point being that AERMOD, 

11 251 25 efforts instead into improving AERMOD, rather just 

12 253 3 -- why do we want to explore this with AERMOD, we 

13 253 7 We kind of see AERMOD and probably CALPUFF 

14 253 10 out, but right now, you know, AERMOD is being 

15 253 12 We are expecting AERMOD do have a fairly long shelf 

16 253 14 So, we are addressing this for AERMOD, 

17 254 3 AERMOD, and there was a direct, should we say 

18 254 5 harmony right now with the steady state AERMOD. 

19 254 25 aren't creating a discontinuity with AERMOD. 

20 255 6 processors, AERMOD processors, and there's CALPUFF 

21 259 10 Let's just use the AERMOD paradigm for now, 

22 266 25 and AERMOD doesn't, is -- is like to say we can 

23 271 7 that into AERmuff -- AERMOD. 

24 272 25 to -- to AERMOD with the MM5 data, and do this in 

25 273 20 the AERMOD compared to the ISC looked -- didn't 

26 276 3 Then AERMET and AERMOD using the observation data 

27 276 17 go into AERMET, or to go into AERMOD. 

28 277 2 So we just took AERMOD, any -- any calculated 

29 277 3 AERMOD value that AERMOD calculated, -- not AERMET; 

30 277 4 if AERMOD calculated something that MM5 provided, 

31 277 6 over AERMET, we have to jump over the AERMOD 

32 277 18 Then we ran AERMOD, using the reformatted 

33 277 22 AERMOD itself. 

34 278 22 AERMOD. 

35 278 23 But the question is, well, what's AERMOD's 

36 287 2 Weather Service data going through AERMOD. 

37 287 15 can see the AERMOD data down much lower in the 

38 293 20 seen used operationally for feeding AERMOD, so we 

39 297 11 say, as input to AERMOD, we said, as an example, 

40 306 25 fundamental relationships in MM5 while AERMOD uses 

41 307 4 greater resolution as possible than with the AERMOD 

42 307 9 That's been addressed in AERMOD to some 

43 308 5 As -- specific to AERMOD, how -- very near 

44 310 23 we just looked at. I don't know how AERMOD was set 

45 312 23 The current version of AERMOD treats the 

46 313 13 Straight line plume models, such as AERMOD, 

47 314 7 Probably not with AERMOD because to do that 

48 314 8 would be to create a CALPUFF version of AERMOD, and 

49 314 12 Grid spacing. AERMOD is simple. It has just 

50 323 6 products for AERMOD, or permit applications and 
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 6 325 9 and why can't we put CALPUFF and AERMOD into that 

 7 326 6 well, does AERMOD -- and I'm just going to speak of 

 8 326 7 AERMOD for now, so how well does AERMOD perform 

 9 326 18 -- criterias for AERMOD was that if it's going to 

10 328 4 issues in AERMOD is that a lot of the sources in 

11 328 7 working for air resources in AERMOD yet, that we 

12 328 13 concentrations, and so like I said, in this AERMOD 

13 328 22 AERMOD. 

14 329 25 that may be showing up in the AERMOD processing 

15 341 15 When we first started our design for AERMOD, 

16 342 9 Well, we tried to do that with AERMOD. That's 

17 343 23 AERMOD, and who have used ISC. 

18 

19 Page Ref No. Keyword = "AERMOD-PRIME" 

20 ____ _______ ________________________ 

21 

22 136 3 comparing AERMOD-PRIME to ISC-PRIME, AERMOD out- -- 

23 

24 Page Ref No. Keyword = "AERSCREEN" 

25 ____ _______ _____________________ 

26 

27 39 10 kinds of information, and also, AERSCREEN now 

28 68 24 about this morning is called AERSCREEN. 

29 69 5 called AERSCREEN is a screening model for AERMOD. And 

30 70 13 AERSCREEN options that we had to develop the 

31 70 23 This setup for AERSCREEN is a real simple 

32 72 7 available as a part of AERSCREEN. 

33 72 25 kind of a nice feature to the side with AERSCREEN; 

34 73 7 AERSCREEN run, rather than them going through the 

35 73 16 the AERSCREEN may not do everything you want to do, 

36 74 5 AERSCREEN goes through and develops the maximum 

37 74 18 produce conservative estimates for all AERSCREEN 

38 75 4 you're going through an AERSCREEN run. This is the 

39 77 12 calculated value here that comes out of AERSCREEN 

40 77 16 sixty-seven (129.967) from AERSCREEN. 

41 78 6 AERSCREEN will go through and calculate the 

42 78 14 AERSCREEN, and AERSCREEN starts calculations based 

43 79 4 restart file. Once you have made the AERSCREEN 

44 79 11 appropriate and then rerun AERSCREEN. 

45 80 2 compared the AERSCREEN numbers to the IS -- I'm 

46 80 4 AERSCREEN results to AERMOD. 

47 80 6 that AERSCREEN produced concentrations at least as 

48 80 11 This is, again, a ratio of AERSCREEN to AERMOD 

49 81 10 values, so to speak, but if AERSCREEN really 

50 81 14 AERSCREEN results were five times higher than 
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 6 82 7 AERSCREEN to make sure that these numbers come out 

 7 82 11 (800) sources being tested that AERSCREEN is doing 

 8 83 11 AERSCREEN. 

 9 121 9 very soon thereafter, AERSCREEN will be available, 

10 122 10 AERSCREEN. 

11 128 13 A few questions on AERSCREEN, Warren, so I 

12 130 7 the only AERSCREEN output is for one -- well, two 

13 130 11 But AERSCREEN does have other concentrations 

14 130 16 improvement to AERSCREEN is to have a user 

15 

16 Page Ref No. Keyword = "AERSURFACE" 

17 ____ _______ ______________________ 

18 

19 38 19 One is called the AERSURFACE, and this is a 

20 39 9 So AERSURFACE will help us in evaluating those 

21 83 13 to is the AERSURFACE, and I'd like to introduce to 

22 83 16 of this new tool called AERSURFACE. 

23 83 19 the tool for AERMOD called AERSURFACE. 

24 83 20 And just what is AERSURFACE? Okay, so 

25 83 21 AERSURFACE is a tool and it produces the surface 

26 84 5 AERSURFACE is actually a Fortran program, and 

27 84 14 So AERSURFACE allows you to specify the center 

28 84 22 AERSURFACE does. So you specify the center of the 

29 85 6 The AERSURFACE help has developed, so you can 

30 85 12 AERSURFACE, also, when it outputs this data, 

31 85 18 AERSURFACE, we felt that it was important to first 

32 98 12 AERSURFACE. 

33 98 13 So, future plans for AERSURFACE. 

34 98 22 We'd like to modify AERSURFACE, so that it 

35 140 15 RICHARD SCHULZE: Yes, in the AERSURFACE -- 

36 141 5 AERSURFACE model -- the AERSURFACE model, did use a 

37 

38 Page Ref No. Keyword = "air" 

39 ____ _______ _______________ 

40 

41 6 24 with: health sciences, air quality modeling, 

42 8 6 standards for particulate matter as we look at air 

43 8 23 we have for air quality management in the United 

44 9 20 I think the air program does this better than 

45 10 5 This is all separate, and air toxics is 

46 11 3 everyone's memory, this is the air quality 

47 11 8 Traditionally, National Ambient Air Quality 

48 12 2 So that's the air quality management system, 

49 12 4 program for air quality improvement, although 

50 13 8 hazardous air pollutants -- you know -- and moving 
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 6 14 14 worried by international scales and maintaining air 

 7 14 20 control it, because that's not air quality 

 8 14 21 management, but air quality managers need to 

 9 14 25 more difficult, at least in some cases, for air 

10 15 17 important traditional air quality problem. Why, 

11 16 4 concentrate, for example, Chapel Hill air and dose 

12 19 8 PM but air toxics. 

13 20 12 indirect strategies for managing air quality. 

14 20 17 they had air conditioning, all the buildings were 

15 20 24 will make air quality better. Well, modelers also 

16 21 7 But one of the key air policies -- policy 

17 21 9 more trees reduces air pollution. What are we 

18 21 25 International transport of air pollution is 

19 22 17 to forecast air quality, not just by empirical 

20 23 2 the air quality index is -- is one that is on the 

21 23 6 that, you know, we've always addressed air quality 

22 24 7 there in emission inventory and air quality, 

23 24 14 to -- to do better air quality management against 

24 24 23 leader for the air quality monitoring group for 

25 26 12 it cleared through the office of Air and Radiation. 

26 27 19 terms of air quality management; broadly, the 

27 29 4 near-field modeling, air quality modeling, to 

28 29 6 Again, lead, we're the air quality modeling 

29 30 2 Air Quality Modeling Group leadership role and 

30 54 17 to the free air aloft. 

31 60 22 work for the Air Quality Modeling Group here at 

32 109 24 That's what Section 320 of the Clean Air Act 

33 122 16 Reformulate air -- urban -- we've talked about 

34 138 8 problem, for EPA to put air guards on the 

35 139 15 The Air Quality Management report that came 

36 139 18 emissions inventories and air quality modeling as 

37 147 25 supports us in the Air Quality Modeling Group. 

38 148 11 branch, formerly known as the Air Policy Support 

39 148 12 Branch, now quality modeling from the NOAA Air 

40 155 2 Group on Air Quality Modeling, and I guess I should 

41 155 6 managers, on long-range transport from air quality 

42 158 25 visibility in the air quality and and related 

43 165 4 anymore as are meteorology, emissions, air quality 

44 168 15 experts, run the air quality model, obtain 

45 172 3 The Air Quality Modeling Group has, of course, 

46 174 14 air. 

47 174 20 ongoing in this -- this air quality modeling group, 

48 175 25 Air Resource Specialists. It was prepared for the 

49 189 21 guideline on air quality -- you know -- recommends 

50 192 17 D (Section 9.3.12d) of the Guideline on Air Quality Models, it 

states that mesoscale meteorological 
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 6 193 11 (Section 9.3c) of the Guideline on Air Quality Models, what you 

find is, you find it states 

 7 206 5 questions, and a list search to air technical 

 8 219 13 gridded meteorological data for air dispersion 

 9 219 20 Meteorological data used in air dispersion 

10 223 2 surface and upper air sites are typically not 

11 224 13 One committee called the Clean Air Act 

12 224 15 EPA to incorporate more advanced air quality 

13 224 16 modeling tools into our air dispersion models, and 

14 225 5 simulation mode would provide superior air quality 

15 225 6 forecasts, and as you know, AIRNOW employs air 

16 225 7 quality forecast information in its air quality 

17 226 7 what we need to drive our local air dispersion 

18 227 14 spring OAQPS, Office of Air Quality Planning and 

19 256 13 in the weather service, and actually in the Air 

20 259 11 and get an upper air sounding, and if there's 

21 259 22 And many times, as you know, the upper air sounding 

22 263 7 into play in regulatory activities, in air quality 

23 264 23 and -- and manipulating it to fit into the air 

24 264 24 quality model, there will be some air quality 

25 269 16 into the air quality model, whatever time it values 

26 270 14 model that's going into an air quality forecast run 

27 270 21 into an air quality model, be it a regional scale 

28 271 21 had been done for air toxics in Philadelphia, and 

29 272 16 was to conduct, basically, an air quality model 

30 274 7 Airport, the site of the NWS observation. 

31 292 4 can put in the air. 

32 295 7 Park Service, Air Resources Division. 

33 295 8 Prior to that, I was one of the air quality 

34 296 18 been to try to get it to work better for the air 

35 296 20 in the air parameterizations. 

36 296 24 developed specifically trying to run air quality 

37 298 12 with your -- the other -- the air quality model was 

38 298 21 Service has done a number of air quality studies 

39 303 20 (200) staff specializing in air quality, and I have 

40 307 11 fraction of the hour, air quality regulations, and 

41 309 25 producing air quality related meteorological data 

42 310 18 Local, meaning nearby airport, or ASOS data, 

43 318 24 application, or the particular air quality problem 

44 319 16 efficient, but from an air quality perspective they 

45 321 9 through the guideline on air quality models, I came 

46 321 11 and this was on air quality models themselves, 

47 322 22 the applications of the air quality or the 

48 323 9 -- you know -- of why we're applying these air 

49 328 7 working for air resources in AERMOD yet, that we 

50 332 9 is a WRF chem, and in the NOAA mission, air quality 
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 6 332 16 parameters or anything that would benefit air 

 7 338 20 that I wanted to work with, you know, the air 

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 9 Page Ref No. Keyword = "albedo" 

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12 42 17 surface characteristics, the albedo, the Bowen 

13 55 7 reflected, this is where the albedo comes into 

14 55 8 play, and Karen will be talking about the albedo, 

15 83 24 And these data include the albedo, the Bowen 

16 84 10 surface roughness, the albedo, and the Bowen 

17 85 8 albedo, a Bowen ratio, and a surface roughness. 

18 85 10 entire area of the circle, the mean albedo and 

19 85 24 varied the albedo, the Bowen ratio, the surface 

20 86 13 For the albedo, we ranged the values from 

21 86 20 the albedo at zero point two (0.2) and the surface 

22 86 25 albedo and the Bowen ratio constant at point two 

23 87 20 For the albedo, again it's going from point 

24 88 3 albedo ranges across the X axis here; it's ranging 

25 88 17 going from an albedo of point one (.1) to two times 

26 88 24 percent difference for the albedo, for the role 

27 89 6 the albedo value. 

28 89 10 concentration values for variations in the albedo 

29 89 21 the albedo. 

30 90 8 sensitivity to the albedo change. However, as 

31 90 10 sensitive to the changes in the -- in the albedo 

32 90 19 amount of sensitivity to the changes in the albedo. 

33 91 2 here. Holding albedo constant at the zero point 

34 93 12 Albedo is held constant at the zero point two 

35 95 23 albedo and the Bowen ratio, but we definitely see a 

36 96 3 stacks are more sensitive to the albedo and Bowen 

37 96 13 albedo and Bowen ratio values. 

38 98 7 influence is still there from the albedo and the 

39 113 5 characteristics, like Bowen ratio, albedo and 

40 115 16 With the Bowen ratio and with the albedo, it's 

41 132 19 albedo are really more regional type parameters, 

42 142 25 albedo. 

43 315 2 differences based on surface roughness and albedo. 

44 

45 Page Ref No. Keyword = "algorithm" 

46 ____ _______ _____________________ 

47 

48 56 23 extend the -- the algorithm that's used in the 

49 57 16 the algorithm for certain limits in -- in the first 

50 58 2 Vancouver, 2003, and a revised algorithm was 
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 6 62 18 algorithm in there. 

 7 63 8 algorithm now, instead of -- okay, let me say this, 

 8 66 19 write an algorithm to read all those -- or all with 

 9 120 16 And then finally the area source algorithm, 

10 191 15 algorithm that this uses is how -- how effectively 

11 265 6 reanalyzed or recomputed or the algorithm 

12 286 10 The algorithm we use was -- was fairly 

13 286 13 algorithm did not bring every vertical layer, it 

14 288 23 raw values through AERMET's algorithm and see if we 

15 289 4 algorithm and see what we get for the mixing 

16 289 18 MM5 data into AERMET's algorithm, we get this 

17 

18 Page Ref No. Keyword = "algorithms" 

19 ____ _______ ______________________ 

20 

21 36 22 algorithms in there, too. We had public comments 

22 37 19 plume rise in the PRIME algorithms, and we found 

23 41 8 algorithms in here through the PRIME model. 

24 42 22 The PRIME building downwash algorithms require 

25 53 19 The algorithms in AERMET are -- are based on 

26 54 23 The boundary of the AERMET algorithms for the 

27 62 10 algorithms to use with mixed DEM, or datums, and 

28 118 15 algorithms in PRIME, if you're in downwash 

29 184 24 code, new algorithms, what-have-you, and there may 

30 266 24 So to say that MM5 has all these algorithms 

31 296 23 specifically, algorithms here and there that were 

32 

33 Page Ref No. Keyword = "appendix" 

34 ____ _______ ____________________ 

35 

36 111 21 form as Appendix W which is the most formal of all 

37 161 21 says, the report refers to Appendix A, of course, 

38 162 4 "The information provided in Appendix A should not 

39 172 15 CALPUFF in the Appendix W, you know, there is quite 

40 183 10 kilometers, once again, so we go back to Appendix 

41 187 24 under Appendix W and in the IWAQM Phase II 

42 188 22 the traditional recommended way in Appendix W which 

43 190 11 well in excess of what the Appendix A 

44 191 21 know, the Appendix W, what you find is is that 

45 195 10 Appendix W, would be helpful as we move forward in 

46 238 15 applications. Of course, in the Appendix W, it 

47 321 13 puts forward in Appendix A are generally expected 
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 6 286 16 The observation data, even though it's an ASOS 

 7 309 13 from ASOS. Again, it's probably a policy issue on 

 8 310 6 parameters throughout the ASOS network. And this 

 9 310 18 Local, meaning nearby airport, or ASOS data, 

10 

11 Page Ref No. Keyword = "atmosphere" 

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14 41 10 the atmosphere. We understand how the various wind 

15 72 18 realistic worst case scenarios for the atmosphere, 

16 223 16 lot more information about the atmosphere. 

17 242 13 more of a, you know, one atmosphere environment, 

18 256 18 atmosphere, and created forecasts. 

19 341 18 that thinks that the atmosphere has a couple of 

20 341 24 think the atmosphere is. 

21 

22 Page Ref No. Keyword = "BART" 

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25 26 8 BART rule, the confirmation of our administrator 

26 149 9 BART, you know fairly well by now that we're kind 

27 159 15 in the old concentric ring model, and the BART, 

28 167 9 of you who're involved with with BART. You'll see 

29 181 5 during the BART modeling that became an issue. We 

30 182 11 for -- for BART, for the BART Notice of the 

31 187 22 these in the BART applications of modeling here, 

32 188 4 applications with BART. 

33 188 11 BART modeling protocols, and you can see the one of 

34 188 19 But in the BART world, almost all the 

35 189 19 States, and the BART applications, is the issue of 

36 190 8 demonstration for their BART eligible sources, the 

37 190 9 effective distance from these particular BART 

38 190 20 methodologies, as you're aware, the -- the BART 

39 191 3 you know, as a further recommendation for BART. 

40 191 5 necessarily limited to BART, but other areas where 

41 197 20 there are BART protocols that are moving forward 

42 200 7 now had to do more with BART, more with long-range 

43 

44 Page Ref No. Keyword = "boundary" 

45 ____ _______ ____________________ 

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47 40 24 boundary layer concepts all now built into AERMOD, 

48 52 14 AERMET is essentially a boundary layer model, 

49 52 16 idealization with the boundary layer. 

50 52 18 everything occurs in the boundary layer. It's the 
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 6 52 21 we look at what we call the convective boundary 

 7 52 22 layer during the day, and the stable boundary layer 

 8 52 24 The convective boundary layer is driven by 

 9 53 3 Stable boundary layer is less well understood. 

10 54 8 The convective boundary layer in its simplest 

11 54 18 And in the convective boundary layer, both 

12 54 23 The boundary of the AERMET algorithms for the 

13 54 24 boundary layer, we employ a heat budget approach to 

14 55 2 a surface -- the -- what drives the boundary layer 

15 55 3 -- the convective boundary layer is the heating 

16 55 22 the boundary layer. 

17 56 4 turbulence in convective boundary layers. 

18 56 6 convective boundary layer is -- is determined by an 

19 56 8 day, so, the boundary layer grows most rapidly 

20 56 12 The characteristics of the stable boundary 

21 56 17 compared to the convective boundary layer, it's 

22 56 22 in my lane(?) the convective boundary layer we kind of 

23 56 24 convective boundary layer, and we have, also, this 

24 57 7 boundary layers, it doesn't require -- it doesn't 

25 58 6 have been talking about the boundary layer model, 

26 59 12 it's a boundary layer model. It's not clear that 

27 63 10 and four. And this is a domain boundary that was 

28 63 23 boundary to include that particular critical 

29 78 5 boundary. 

30 78 9 have an ambient boundary or a boundary actually 

31 78 12 a boundary or a fence line that goes out to a 

32 78 18 concentrations or boundary concentrations. So you 

33 78 23 information about where ambient boundary is. It 

34 117 8 the urban boundary layer and not have to utilize 

35 129 25 for that ambient boundary you were talking about. 

36 130 10 was at the fence line, or the ambient boundary. 

37 133 22 an appropriate boundary layer, you are going to be 

38 191 9 Another one is the use of boundary conditions 

39 196 18 variables such as, you know, the planetary boundary 

40 233 12 similarity theory for the protected boundary layer, 

41 233 22 planetary boundary layers. 

42 249 25 urban boundary layer, relative to the adjacent 

43 250 2 rural boundary layers, if you are getting -- if 

44 250 16 a reasonable representation of the urban boundary 

45 285 14 boundary conditions and the initial conditions have 

46 306 23 technical issues, the planetary boundary layer 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 366 

 2 

 3 Page Ref No. Keyword = "Bowen" 

 4 ____ _______ _________________ 

 5 

 6 42 17 surface characteristics, the albedo, the Bowen 

 7 55 18 And in the AERMET, we use a Bowen ratio, it's the 

 8 83 24 And these data include the albedo, the Bowen 

 9 84 10 surface roughness, the albedo, and the Bowen 

10 85 8 albedo, a Bowen ratio, and a surface roughness. 

11 85 11 Bowen ratio and surface roughness. 

12 85 24 varied the albedo, the Bowen ratio, the surface 

13 86 15 this, we held the Bowen ratio and the surface 

14 86 18 For the Bowen ratio, we varied from zero point 

15 86 25 albedo and the Bowen ratio constant at point two 

16 87 21 one (.1) to zero point six (0.6) on the Bowen ratio 

17 90 23 Okay, now -- and now for the Bowen ratio. 

18 90 24 The Bowen ratio is going to vary between point 

19 91 12 X factors of time has the Bowen ratio, Bowen 

20 91 17 a lot of sensitivity to the changes in the Bowen 

21 91 20 concentration. Here the Bowen ratio -- we started 

22 91 21 -- we compared it against the Bowen ratio, with the 

23 91 23 that point, and then increasing the Bowen ratio to 

24 91 25 times at one (1), forty (40) times at -- that Bowen 

25 92 2 equals four and then a hundred times the Bowen 

26 92 9 for the Bowen ratio, numerically we look at these, 

27 92 13 Bowen ratio line. 

28 92 16 the Bowen ratio value going from zero point one 

29 93 5 at the early stages of changing the Bowen ratio. 

30 93 13 (0.2); Bowen ratio held constant at one point zero 

31 95 23 albedo and the Bowen ratio, but we definitely see a 

32 96 3 stacks are more sensitive to the albedo and Bowen 

33 96 13 albedo and Bowen ratio values. 

34 96 14 The Bowen ratio values were selected for 

35 98 8 Bowen ratio. 

36 99 20 This would have an influence on the Bowen 

37 113 5 characteristics, like Bowen ratio, albedo and 

38 115 16 With the Bowen ratio and with the albedo, it's 

39 125 14 sensitivity of Bowen ratio, and that is that, you 

40 125 15 know, we get Bowen ratio now into AERMOD purely by 

41 125 20 and -- and tried to deal with the Bowen ratio that 

42 132 18 because the Bowen ratio and the -- and the 

43 142 12 changes in Z naught (Zo) and Bowen ratio. 

44 142 24 value for the Bowen ratio, Z naught (Zo) and 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 367 

 2 

 3 Page Ref No. Keyword = "calm" 

 4 ____ _______ ________________ 

 5 

 6 161 6 Now, they're talking about CALMET here, but this 

 7 163 7 converters that would feed into CALMET at that 

 8 176 22 Specifically looking at CALMET, there are some 

 9 178 14 through CALMET. 

10 179 24 calming effect for a moment, but when AERMOD is 

11 192 6 You can run CALMET, or you can drive 

12 192 7 CALMET completely with just prognostic 

13 196 16 So the goal here would be to bypass the CALMET 

14 216 4 CALMET and doing a lot of processing over these 

15 228 7 accepted in the CALPUFF via CALMM5, and soon CALRUC 

16 228 17 NWS data through CALMET and analyze the results, 

17 228 21 and NWS through CALMET, you want to use that, and 

18 245 22 CALMET as the processor to get from the prognostic 

19 245 24 CAL- -- CALPUFF -- or CALMET near-fields, because 

20 246 9 The other point about this is, using CALMET 

21 246 11 the grid resolution of the CALMET simulation and in 

22 246 16 You can run CALMET at, say, two hundred meter 

23 246 20 version of -- a program that will take CALMET 

24 246 23 CALMET ready for viewers, and then processing the 

25 246 24 CALMET output into AERMOD fields at -- all of those 

26 247 8 CALMET on certain bundling parameters. 

27 247 17 the same comment about CALMET. 

28 247 23 to -- with CALMET and use it drive CMAQ, and that 

29 254 8 through CALMET and look at the fluxes and the 

30 254 13 you can look back into CALMET and see whether it 

31 254 14 could be improvements made to CALMET so that they 

32 254 17 updated in CALMET. This would be a perfect way of 

33 254 20 that could be incorporated into CALMET, and they 

34 254 24 CALMET for the future, and at the same time you 

35 261 25 transformation, whether it be CALMET, whether it be 

36 279 10 of those with CALMET, already, because I -- I don't 

37 299 20 output and run it through CALMET. CALMET didn't 

38 299 22 forcing the flow in your general fields, CALMET 

39 299 25 CALMET just doesn't overcome that, and there 

40 303 4 downscale or any of the work with CALMET just isn't 

41 311 22 CALMET is a diagnostic model that provides a 

42 312 9 in the CALMET output. 

43 312 10 CALMET is useful because it applies its own 

44 320 7 meteorological products in models such as CALMET. 

45 320 12 used inside of CALMET. 

46 324 15 database that was supplied from CALMET and -- and 

47 324 17 fine grid, I -- I was getting lots of calm winds 

48 328 3 off, I think one of the reasons they were near calm 

49 330 4 winds as calm. 

50 331 12 kilometer MM5 data I'll bet that CALMET would have 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 368 

 2 

 3 Page Ref No. Keyword = "calm" 

 4 ____ _______ ________________ 

 5 

 6 331 19 CALMET regime and taking advantage of that. 

 7 337 19 CALMET in many respects. 

 8 

 9 Page Ref No. Keyword = "CALMET" 

10 ____ _______ __________________ 

11 

12 161 6 Now, they're talking about CALMET here, but this 

13 163 7 converters that would feed into CALMET at that 

14 176 22 Specifically looking at CALMET, there are some 

15 178 14 through CALMET. 

16 192 6 You can run CALMET, or you can drive 

17 192 7 CALMET completely with just prognostic 

18 196 16 So the goal here would be to bypass the CALMET 

19 216 4 CALMET and doing a lot of processing over these 

20 228 17 NWS data through CALMET and analyze the results, 

21 228 21 and NWS through CALMET, you want to use that, and 

22 245 22 CALMET as the processor to get from the prognostic 

23 245 24 CAL- -- CALPUFF -- or CALMET near-fields, because 

24 246 9 The other point about this is, using CALMET 

25 246 11 the grid resolution of the CALMET simulation and in 

26 246 16 You can run CALMET at, say, two hundred meter 

27 246 20 version of -- a program that will take CALMET 

28 246 23 CALMET ready for viewers, and then processing the 

29 246 24 CALMET output into AERMOD fields at -- all of those 

30 247 8 CALMET on certain bundling parameters. 

31 247 17 the same comment about CALMET. 

32 247 23 to -- with CALMET and use it drive CMAQ, and that 

33 254 8 through CALMET and look at the fluxes and the 

34 254 13 you can look back into CALMET and see whether it 

35 254 14 could be improvements made to CALMET so that they 

36 254 17 updated in CALMET. This would be a perfect way of 

37 254 20 that could be incorporated into CALMET, and they 

38 254 24 CALMET for the future, and at the same time you 

39 261 25 transformation, whether it be CALMET, whether it be 

40 279 10 of those with CALMET, already, because I -- I don't 

41 299 20 output and run it through CALMET. CALMET didn't 

42 299 22 forcing the flow in your general fields, CALMET 

43 299 25 CALMET just doesn't overcome that, and there 

44 303 4 downscale or any of the work with CALMET just isn't 

45 311 22 CALMET is a diagnostic model that provides a 

46 312 9 in the CALMET output. 

47 312 10 CALMET is useful because it applies its own 

48 320 7 meteorological products in models such as CALMET. 

49 320 12 used inside of CALMET. 

50 324 15 database that was supplied from CALMET and -- and 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 369 

 2 

 3 Page Ref No. Keyword = "calmet" 

 4 ____ _______ __________________ 

 5 

 6 331 12 kilometer MM5 data I'll bet that CALMET would have 

 7 331 19 CALMET regime and taking advantage of that. 

 8 337 19 CALMET in many respects. 

 9 

10 Page Ref No. Keyword = "calms" 

11 ____ _______ _________________ 

12 

13 240 14 inconsistencies, lack of calms, and I think that 

14 240 24 gridded met data model. Typically has fewer calms, 

15 308 6 calms are to be handled; well, EPA's made a policy 

16 308 16 treating calms with respect to permitting issues of 

17 328 2 to say; the near calms, about Philly. Well, first 

18 329 23 one comment about the near calms, since people 

19 330 6 dramatically increasing the number of calms to 

20 330 13 those calms. 

21 

22 Page Ref No. Keyword = "CALPUFF" 

23 ____ _______ ___________________ 

24 

25 28 20 AERMOD, we'll also touch on CALPUFF. 

26 142 19 CALPUFF. 

27 147 17 This morning we covered CALPUFF -- CALPUFF, right!, 

28 147 21 CALPUFF, and we have a number of topics; basically, 

29 148 3 first part of our CALPUFF presentations this 

30 148 16 of the afternoon about CALPUFF. 

31 148 20 CALPUFF coming from me to you. 

32 149 12 with CALPUFF, and we're going on to new territory, 

33 149 17 CALPUFF expertise that's because we had a 

34 149 20 of our CALPUFF expertise and a lot of the 

35 150 5 that we had with regard to CALPUFF, and that would 

36 150 16 CALPUFF world, by all means, set the record 

37 151 2 CALPUFF. 

38 151 5 CALPUFF, the updates, applications, 

39 151 16 we're going to call it CALPUFF work group, and it 

40 151 21 for CALPUFF, and hopefully, some of the more 

41 151 23 CALPUFF. 

42 152 9 the entire state of CALPUFF applications and just 

43 157 15 defaults in the run scripts to run the CALPUFF 

44 158 4 CALPUFF formally introduced, mesoscale modeling 

45 158 18 for CALPUFF -- I'll talk about that shortly in a 

46 158 20 CALPUFF also was included at this point, if it 

47 159 5 CALPUFF screening was -- it's interesting in 

48 159 17 used the CALPUFF screen runs to come up with a 

49 162 13 crew of CALPUFF modelers that are out there and 

50 167 22 look at, say, getting MM4 data into a CALPUFF 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 370 

 2 

 3 Page Ref No. Keyword = "calpuff" 

 4 ____ _______ ___________________ 

 5 

 6 171 14 specifically, to the CALPUFF model. 

 7 172 15 CALPUFF in the Appendix W, you know, there is quite 

 8 174 10 with -- with regard to CALPUFF, it strikes that 

 9 175 22 There is also another document, the CALPUFF 

10 176 8 CALPUFF technical issues that are out there that 

11 176 15 are not problems with CALPUFF or things that need 

12 176 20 robust treatment that the other CALPUFF issues had 

13 178 21 In CALPUFF itself, one tip of the hat to the 

14 182 9 found some CALPUFF discussions, and this was in the 

15 182 13 back about how CALPUFF should be applied, how it 

16 182 21 comments about CALPUFF chemistry, itself, and that 

17 183 12 CALPUFF is recommended to two hundred 

18 184 12 when it comes to CALPUFF applications. 

19 187 21 evolution of CALPUFF, and we are starting to see 

20 188 3 starting to see be proposed for use in CALPUFF 

21 189 20 the effective range of CALPUFF, because the -- the 

22 191 10 for CALPUFF, updates the aqueous space chemistry. 

23 194 23 responsibility of conducting the CALPUFF 

24 196 7 developing an MSIP style preprocessor for CALPUFF, 

25 196 21 prognostic meteorological data in CALPUFF rather 

26 200 12 should be using CALPUFF, and the whole question of 

27 200 20 to try to configure CALPUFF in a way that you -- 

28 201 16 how CALPUFF's system was intended to be not the 

29 202 7 is not so much for CALPUFF per se as for the 

30 207 4 CALPUFF implementation guide, to be able to be more 

31 209 22 CALPUFF project. 

32 213 7 CALPUFF. That's -- that's AERMOD and the like. 

33 213 14 CALPUFF perform when you compare its predictions to 

34 213 22 CALPUFF, no, we haven't talked about that. 

35 214 21 As we know, CALPUFF has been promulgated prior 

36 215 3 So I think that CALPUFF having been out, that 

37 215 6 of policy statements for CALPUFF as well. 

38 215 10 actually urging folks in the context of CALPUFF 

39 216 3 And I've been -- I've been running CALPUFF and 

40 216 18 Right now, I've played with CALPUFF enough 

41 218 12 CALPUFF versus a twenty-four-hour average. 

42 219 2 our CALPUFF discussion, for the first part of our 

43 221 5 local scale modeling. Of course, CALPUFF now uses 

44 221 14 gridded met data into AERMOD and CALPUFF; also 

45 222 14 CALPUFF being used more extensively, the gridded 

46 222 15 met data in CALPUFF being more visible, there was 

47 226 21 using MM5 to drive CMAQ, CALPUFF, those types of 

48 226 22 models, of course, CALPUFF is a medium range 

49 228 6 review MM5 into CALPUFF. Currently, MM5 is 

50 228 7 accepted in the CALPUFF via CALMM5, and soon CALRUC 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 371 

 2 

 3 Page Ref No. Keyword = "calpuff" 

 4 ____ _______ ___________________ 

 5 

 6 228 9 readily by CALPUFF. 

 7 228 11 processed through CALPUFF to apply similar 

 8 228 22 then put it in process through CALPUFF. 

 9 231 11 and also try to incorporate those into CALPUFF and 

10 232 4 used for, and -- which would be AERMOD, CALPUFF and 

11 243 2 basically in relation to CALPUFF. 

12 245 24 CAL- -- CALPUFF -- or CALMET near-fields, because 

13 253 7 We kind of see AERMOD and probably CALPUFF 

14 253 17 because it does appear that the CALPUFF-type model 

15 254 2 things are going to harmonize between CALPUFF and 

16 254 4 suggestion, that we look to see how CALPUFF is in 

17 255 6 processors, AERMOD processors, and there's CALPUFF 

18 262 12 -- to do what we saw earlier today with CALPUFF, 

19 293 9 CALPUFF applications, but we do know that there are 

20 294 3 about the CALPUFF group, if you're not on that work 

21 295 12 users, feeding into CALPUFF primarily, also into 

22 295 19 policy we were trying to use, the CALPUFF came out 

23 314 8 would be to create a CALPUFF version of AERMOD, and 

24 315 8 And it would be helpful if CALPUFF or SCIPUFF 

25 325 9 and why can't we put CALPUFF and AERMOD into that 

26 331 5 (sic) of a CALPUFF to a mid-field if you will, that 

27 

28 Page Ref No. Keyword = "cell" 

29 ____ _______ ________________ 

30 

31 229 24 for a single grid cell, and also for NWS data and 

32 234 10 the land use is averaged over the grid cell, so 

33 234 21 know, do you pick the center of the -- center cell 

34 235 2 runs with each grid cell, and then, you know, do 

35 235 6 possibly use a center grid cell for the source 

36 235 14 data necessary for grid cell data to be used -- 

37 235 16 Is on-site data necessary if grid cell data is 

38 249 22 MM5 runs and to take a -- a grid cell inside an 

39 274 10 there is the domain from which -- that is grid cell 

40 274 16 center of the cell, to represent that dot. 

41 275 7 grid cell, but that's -- that's the thirty-six 

42 276 6 that grid cell to replace the observational data. 

43 292 25 employing grid cell, but that really frankly is 

44 293 4 in a single cell, steady state being what it is, we 

45 312 24 entire modeling domain as a single grid cell. I 

46 314 13 one grid cell. For complex terrain, it may be 

47 314 14 useful to define a grid cell that has less than, 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 372 

 2 

 3 Page Ref No. Keyword = "cells" 

 4 ____ _______ _________________ 

 5 

 6 234 18 data from multiple grid cells. 

 7 234 20 several grid cells, over a multi-grid area, and you 

 8 235 10 cells. 

 9 237 7 capture with the number of grid cells, and his 

10 274 15 cells, and then we took all the other data from the 

11 274 22 there -- there's nine grid cells here, so you might 

12 275 18 which is compare the values in adjacent cells. 

13 311 24 grid cells based on analyzing meteorological data 

14 312 8 and wind data for appropriate grid cells available 

15 313 21 conditions at different grid cells in determining 

16 

17 Page Ref No. Keyword = "clearing house" 

18 ____ _______ __________________________ 

19 

20 30 10 naming Warren as the Model Clearing House Director, 

21 103 18 clearing house. 

22 107 18 the model in the clearing house. 

23 108 6 clearing house, the clearing house then that's sent 

24 112 4 memoranda. There are clearing house memoranda. 

25 126 17 through the clearing house memos. 

26 215 2 reactivating the model clearing house. 

27 215 5 reactivate the model clearing house for those types 

28 215 8 that the model clearing house is not particular to 

29 215 13 model clearing house process. 

30 215 15 technical memos for the model clearing house. 

31 215 17 maybe coming in through the clearing house, but it 

32 

33 Page Ref No. Keyword = "complex" 

34 ____ _______ ___________________ 

35 

36 36 21 Also, we modified the complex terrain 

37 37 2 complex terrain analysis. 

38 47 13 In a complex terrain, now here's one of the 

39 47 15 actually had Complex I, the screening model in 

40 47 16 there for complex terrain. 

41 47 18 science approach to the complex terrain, and we're 

42 48 7 cases AERMOD in complex terrain, produced 

43 71 15 At this point, we can accommodate complex 

44 71 22 in rel- -- rather complex terrain, I guess, very 

45 71 23 complex terrain. 

46 73 17 or you have a really complex source scenario that 

47 81 4 Bob Paine in complex terrain was one point 0 eight 

48 103 2 the time when Complex I, when -- when valid, when 

49 113 18 If you're in complex terrain, there is no such 

50 126 25 model is too complex. It's not like -- it's not 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 373 

 2 

 3 Page Ref No. Keyword = "complex" 

 4 ____ _______ ___________________ 

 5 

 6 128 21 terrain, complex terrain. 

 7 129 3 complex versus simple terrain. 

 8 131 10 system it was -- it was easy, you're in complex 

 9 138 18 complex because you've got many ways of showing it. 

10 139 25 beginning, you know, obviously, it is a complex 

11 180 22 subgrid scale, complex terrain, in quotes, which 

12 200 5 to complex winds. 

13 234 6 important for the complex terrain situations. 

14 235 22 relied on in certain areas, certainly in complex 

15 239 10 lot of situations, especially toward complex 

16 239 15 Complex terrain, as I mentioned earlier, 

17 239 21 complex terrain-related situations that would 

18 313 15 to complex terrain or has land/sea interfaces, such 

19 314 13 one grid cell. For complex terrain, it may be 

20 

21 Page Ref No. Keyword = "concentration" 

22 ____ _______ _________________________ 

23 

24 40 17 helps to appreciate how much these concentration 

25 43 21 ratios. This is the AERMOD concentration to the 

26 43 22 ISC concentration. 

27 43 24 produce the same concentration. A value of two 

28 58 18 when AERMOD goes to calculate a concentration and 

29 72 19 so that when you do the downwind concentration 

30 74 6 one-hour concentration. From that one-hour 

31 74 7 concentration we try to add just correction 

32 74 9 concentration to estimate three-hour, 

33 77 13 would be the maximum one-hour concentration, this 

34 77 24 location is for the high concentration. 

35 78 7 maximum concentration, I believe, starting at some 

36 78 20 Again, the one-hour concentration is 

37 88 2 Here we see concentration plots, how the 

38 88 5 the concentration is plotted on along the scale. 

39 89 2 variability in the concentration seems to be with 

40 89 10 concentration values for variations in the albedo 

41 91 5 Again, twenty-four-hour average concentration, 

42 91 10 variability; here again concentration is plotted on 

43 91 20 concentration. Here the Bowen ratio -- we started 

44 91 22 -- at the zero point one (0.1) the concentration at 

45 93 4 The concentration changes down here, at the -- 

46 93 16 concentration. 

47 93 21 the stack is -- is increased, the concentration 

48 96 22 concentration on the Y axis, and on the X axis we 

49 98 6 concentration that -- that AERMOD output. The 

50 119 9 concentration. 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 374 

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 3 Page Ref No. Keyword = "concentration" 

 4 ____ _______ _________________________ 

 5 

 6 124 13 ninety-eight percentile concentration. 

 7 132 14 of the difference in the design concentration for 

 8 136 20 We just looked at the concentration output, 

 9 136 23 concentration -- the high concentration picked up, 

10 159 14 concentration at any receptor for a given distance 

11 216 12 concentration is, and then you use that in order to 

12 218 9 forces us into a minimum of an hour concentration. 

13 218 11 you look at one-hour concentration predicted by 

14 241 3 concentration estimates, which is not a bad thing, 

15 290 11 meteorology and give us some concentration values 

16 291 2 annual average concentration map for using the NWS 

17 291 19 And finally, we have a concentration plot 

18 292 10 And as I said, the concentration values we 

19 292 15 concentration output, that is really not something 

20 307 8 high one-hour concentration. 

21 321 15 replicate a design concentration somewhere, 

22 322 19 concentration here. So I -- I'll spare you the 

23 

24 Page Ref No. Keyword = "concentrations" 

25 ____ _______ __________________________ 

26 

27 20 9 concentrations to try to take that next bite, and 

28 35 21 concentrations had changed from what was proposed 

29 39 14 concentrations. 

30 44 17 concentrations, so this actually was good news for 

31 46 6 the AERMOD was presenting concentrations a little 

32 46 24 relative concentrations were one point one seven 

33 47 24 concentrations as what we've just seen from the 

34 48 8 concentrations much lower than ISC. 

35 48 11 concentrations, but is that seen by, or is it 

36 69 8 will provide concentrations that are as 

37 72 22 that get reasonably good concentrations, that would 

38 77 10 The concentrations here are set up on a very 

39 78 18 concentrations or boundary concentrations. So you 

40 80 6 that AERSCREEN produced concentrations at least as 

41 87 25 first high concentrations. 

42 89 16 sensitive concentrations are at the taller stack, 

43 95 20 learned? Well, it seems that the concentrations in 

44 116 17 there was this enormous high concentrations for 

45 116 23 sources, so we got these huge concentrations that 

46 118 4 the concentrations. 

47 120 20 concentrations. 

48 130 3 of concentrations, or do I get one value at the WRF 

49 130 8 concentrations, the highest concentration, 

50 130 11 But AERSCREEN does have other concentrations 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 375 

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 3 Page Ref No. Keyword = "concentrations" 

 4 ____ _______ __________________________ 

 5 

 6 130 14 listed concentrations at different distances, so 

 7 135 13 concentrations from AERMOD PRIME versus ISC-PRIME 

 8 137 2 the high concentrations would be at the output? 

 9 173 22 over prediction of the concentrations at particular 

10 181 4 Background concentrations. This was something 

11 216 23 concentrations quite a bit. 

12 241 5 concentrations, because as you get -- as you 

13 241 7 concentrations that you get out of the model would 

14 291 17 see, we're -- the higher concentrations do show the 

15 292 2 concentrations and then naturally, we tail off a 

16 310 15 as one computes concentrations five (5), ten (10), 

17 311 17 concentrations and yet satisfying the regulatory 

18 316 18 computed concentrations are a small portion of a 

19 316 25 concentrations with existing data sets be too large 

20 322 10 concentrations. 

21 327 23 sensitive is the concentrations going to be to 

22 328 13 concentrations, and so like I said, in this AERMOD 

23 

24 Page Ref No. Keyword = "data" 

25 ____ _______ ________________ 

26 

27 17 4 Ozone itself, we now have more data that's 

28 28 23 data, and then tomorrow, there will be some focus 

29 31 6 gridded meteorological data, including state-of-the 

30 32 20 and data, and timely models acceptance for use in 

31 38 5 have AERMAP the terrain data preprocessor, and then 

32 38 11 bringing in the terrain data and the meteorological 

33 38 12 data into AERMOD properly. 

34 38 20 tool that processes surface characteristic data, 

35 39 8 of data that go into AERMOD. 

36 48 17 different data bases in evaluating AERMOD. It was 

37 57 22 using field data from Prairie Grass, Kansas, and 

38 58 8 that, which involves extracting raw data from -- 

39 58 22 The types of surface data that are supported 

40 59 3 Integrated Surface Hourly Data, and it is probably 

41 59 7 of gridded met data and certainly a need to add to 

42 59 8 this ability to take gridded met data and process 

43 59 14 job than some of the gridded met data they have on 

44 59 17 AERMET with gridded met data, taking what's good 

45 59 18 out of the gridded met data but using the 

46 59 21 The upper-air data formats that are supported 

47 61 9 earth, such as the North American data of 1927, and 

48 61 11 data of 1983. 

49 62 14 also to use XYZ terrain data inside the model, and 

50 64 5 to read the SDTS data formats, which stands for 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 376 

 2 

 3 Page Ref No. Keyword = "data" 

 4 ____ _______ ________________ 

 5 

 6 64 6 Spatial Data Transfer Standard, and it's available 

 7 64 15 that manually processes the data, and you have to 

 8 64 23 five (7.5) minute data, and that's represented by 

 9 66 11 people about AERMAP not processing their data sets 

10 66 25 data processing capabilities, and what we decided 

11 67 13 data on into AERMAP run, and we should function 

12 67 19 point five (7.5) or one degree data, to just 

13 70 14 meteorological database. 

14 71 17 a web site, download one degree DEM data and make 

15 71 21 degree data probably isn't sufficient when you're 

16 72 5 there is such a term. And the one degree data file 

17 72 17 meteorological database that should cover all 

18 76 21 Now once the data are entered, you hit the go 

19 76 22 button, so to speak, it comes back with a data 

20 77 3 proper data at this last second check before you 

21 79 5 run, you've entered in your data on an interactive 

22 82 17 Jim's data set was a little over one, Karen 

23 83 22 characteristics data that will go into AERMET which 

24 83 24 And these data include the albedo, the Bowen 

25 84 7 land use data from the 1970s-80s data. 

26 84 8 And from this data, it returns back on back 

27 85 12 AERSURFACE, also, when it outputs this data, 

28 86 2 And we did this for two sets of met data. 

29 86 10 for two met data; one was Oklahoma City and one was 

30 87 14 Pittsburgh met data. 

31 87 15 For the Oklahoma City data, we also added two 

32 95 2 For the Pittsburgh met data, rural setting, 

33 97 12 AERMOD, again, for the Oklahoma City met data. 

34 97 21 data. 

35 98 14 It currently uses USGS land use data from the 

36 98 17 NLCD 92 data. This data has a thirty-meter spatial 

37 98 19 '92-'93, that's when the data were collected, and 

38 99 10 data would be -- land use data would be averaged. 

39 99 16 We'd also like to output data on a monthly, 

40 113 20 collect on-site data. 

41 114 10 this data which we're collecting over here going to 

42 114 16 we're going to match meteorological data with -- 

43 115 15 on-site data possibly. 

44 116 13 how do we use gridded data. 

45 117 15 one database that we had, we all knew that there 

46 119 6 so -- and then you get the terrain data for the 

47 120 5 file of your data, you have to have that put in. 

48 120 15 can put their own terrain data in. 

49 121 15 data, because the last thing in the world you're 

50 121 17 cloud cover data. 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 377 

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 3 Page Ref No. Keyword = "data" 

 4 ____ _______ ________________ 

 5 

 6 123 8 Use of gridded met data. I think we've 

 7 129 22 metric input data. 

 8 131 6 require more meteorological data collection? 

 9 131 11 terrain, you're collecting on-site data; you in 

10 131 12 flat terrain you're not collecting on-site data. 

11 131 15 you can take the data that you have in the National 

12 132 10 therefore I've got to collect on-site data. 

13 132 16 then that may be adequately representative data 

14 133 2 you want to use National Weather Service data that 

15 133 5 data. 

16 133 7 should be collecting on-site data, and so I think 

17 133 10 forced to collect on-site data. 

18 133 13 towards gridded met data, and when we do move 

19 133 14 towards gridded met data, we will be having fields 

20 133 15 of surface data. We have all the landscape 

21 133 19 issue. So as we move towards utilizing that data, 

22 133 24 collect on-site data really where it's most 

23 137 24 wonderful data you folks have produced on 

24 138 16 any intention of translating the evaluation data, 

25 140 23 use data provided by USGS is provided in a 

26 158 5 with data assimulation, something near and dear to 

27 163 12 sources for our data. Formatting was addressed 

28 163 21 the data gap for upper-air data. It says there, if 

29 163 22 the data is greater than twelve (12) hours, it has 

30 164 6 in this case, MM4 or MM5 and the data blending, 

31 165 6 And with geophysical data, I know I'm 

32 167 19 put out, this document, data sizes and data access 

33 167 22 look at, say, getting MM4 data into a CALPUFF 

34 167 23 simulation as opposed to using observational data, 

35 167 24 just getting the data, just figuring out how to 

36 168 2 alone how much data you had to move around. 

37 168 5 data, and we've somehow managed to just expand the 

38 177 21 the National Weather Service 3240 data is so easily 

39 177 23 should gather this data for every application. 

40 178 7 gridded meteorological data, if you are applying 

41 178 13 or mostly with observational data being processed 

42 178 25 we're using very, very large data sets, we need to 

43 181 13 get very, very good land use data that is far more 

44 188 23 is use -- the use of prognostic meteorological data 

45 188 25 Service data. And so these are -- this is one of 

46 192 8 meteorological data, or you can use a hybrid 

47 192 11 either surface or upper-air data, or you can use 

48 192 12 surface data for your observations, and then you 

49 192 14 data, to, you know, use -- essentially it's to 

50 192 20 standard National Weather Service data or 
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 6 193 6 meteorological data in the evaluation methods. 

 7 193 9 prognostic data sets. 

 8 193 16 authorities that the data are of acceptable 

 9 193 22 metrics are and so what we find is that as data 

10 194 2 developed multiple years of MM5 meteorological data 

11 194 4 seen other meteorological data sets proposed for 

12 194 12 reviewing a new meteorological data set that's 

13 195 3 to the use of prognostic meteorological data and 

14 195 6 of these data sets. 

15 195 11 the use of these meteorological data sets. 

16 196 10 takes MM5 data and it creates -- prepares the 

17 196 11 meteorolog- -- the gridded meteorological data for 

18 196 21 prognostic meteorological data in CALPUFF rather 

19 201 8 collecting a whole lot of data. That's simply a 

20 213 4 fairly quickly is the thing on met data, and that's 

21 219 7 panel discussion on the gridded met data. 

22 219 12 afternoon will address the gridded met data, 

23 219 13 gridded meteorological data for air dispersion 

24 219 20 Meteorological data used in air dispersion 

25 219 24 as other sources of met data. 

26 219 25 These data are used routinely in regional 

27 220 8 of science, so these are simulated data output, and 

28 220 24 met data and incorporating it into local scale 

29 221 4 data, but we're now looking to using that in the 

30 221 6 a gridded met data, but we are also looking to 

31 221 14 gridded met data into AERMOD and CALPUFF; also 

32 221 15 report out on a gridded met data that work group 

33 221 24 in EPA's budget to incorporate gridded met data 

34 222 11 presentations made on gridded met data, as well. 

35 222 15 met data in CALPUFF being more visible, there was 

36 222 16 just a lot more visibility of the gridded met data, 

37 222 20 gridded met data project which I will go over that 

38 222 24 do we want to use gridded met data? 

39 223 5 discontinuity between your surface data and your 

40 223 6 upper-air data. And there is a lot of 

41 223 9 Also, this gridded met data, because it's more 

42 223 14 Also, the gridded data has many more 

43 223 21 product, it -- gridded met data incorporates a lot 

44 223 25 data information,. 

45 224 2 Also, the data is typically NOAA approved as 

46 224 4 data. And currently MM5 is the kind of model of 

47 224 5 choice, and that data is typically accepted pretty 

48 224 8 consider gridded met data, it's an advancement of 

49 225 11 Which gridded met data product should be used? 

50 226 5 And the beauty of the MM5 data, as most of you 
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 6 227 18 input of gridded met data into local dispersion 

 7 228 4 gridded met data into the dispersion modeling 

 8 228 13 Our goal really is to get gridded data into 

 9 228 17 NWS data through CALMET and analyze the results, 

10 228 20 And also, once you've run the met data of MM5 

11 229 15 incorporating the MM5 data or gridded met data into 

12 229 24 for a single grid cell, and also for NWS data and 

13 230 3 -- grid data of information. 

14 230 9 NWS data and analyze the results, and this would be 

15 230 10 for collocated data. 

16 230 12 information at a point that contains NWS data and 

17 230 13 also the grid data that was run through MM5 and run 

18 230 19 using both sets of data. 

19 230 23 data set to enhance the physics and other features 

20 231 3 utilize gridded met data to the fullest. 

21 231 13 from MM5 type data versus forecast type data. And 

22 231 22 gridded met data project would be an IT tool 

23 232 2 And to process this data and make it 

24 232 7 met data that are needed by the recipient model. 

25 232 13 together earlier in the year a gridded met data 

26 232 17 data. And, of course, there are many, and there 

27 232 25 related to gridded method data, and also at the 

28 233 4 gridded met data. 

29 234 18 data from multiple grid cells. 

30 235 14 data necessary for grid cell data to be used -- 

31 235 16 Is on-site data necessary if grid cell data is 

32 235 18 This came up quite a bit. On-site data has 

33 235 21 on-site met data for sources. And it's heavily 

34 235 24 data isn't captured by National Weather Service 

35 235 25 data. 

36 236 3 on-site data is still valid and you don't want to 

37 236 4 use gridded met data? There is a lot of issues 

38 236 7 Gridded data has also been nudged to create a 

39 236 10 to use your on-site met data. 

40 236 12 smaller, the issue of on-site met data may become 

41 236 16 But for now, it looks like on-site met data is 

42 236 18 As was mentioned earlier, there's always data 

43 236 21 meteorological data, data representativeness is at 

44 236 25 necessary to incorporate some local data. 

45 237 4 NWS type data. 

46 237 22 compare the gridded met data with the traditional 

47 237 23 National Weather Service data. It's not done to 

48 238 5 disprove one data set is better than the other. 

49 238 14 basically due to data availability for 

50 238 16 clearly states that five (5) years of met data 
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 6 240 2 data, on-site or gridded, and that's what we'll be 

 7 240 11 gridded met data, maybe they're not shortcomings, 

 8 240 12 but artifacts of the data itself. There was some 

 9 240 24 gridded met data model. Typically has fewer calms, 

10 241 10 choice, where would we want the gridded met data to 

11 241 13 because there is MM5 type data sets all over the 

12 241 15 data sets, and so, you know, should we go to 

13 241 16 different people for the data sets? 

14 241 20 such as computer resources, acquisition of data, 

15 241 24 Another thing, the data that's used in their 

16 242 2 domain data and not proprietary so that everyone 

17 242 3 can access this data, replicate any model runs that 

18 242 5 that's been an issue as of late with some data. 

19 242 6 Data portability, of course, is important. 

20 242 7 Gridded met data is typically very large in size, 

21 242 11 to merge the -- the met data that's used for 

22 242 21 experience do you have in gridded met data? 

23 242 22 What is the source of the data if you do use 

24 242 25 some experience with gridded data, and it was 

25 243 7 we saw coming out of the gridded met data work 

26 243 9 community, gridded met data is not something that 

27 243 13 each other on this new type of data. 

28 243 19 from National Weather Service to gridded data. 

29 243 25 workshop in Asheville on NOAA data, sponsored by 

30 244 2 the National Climatic Data Center, and just a 

31 244 6 gridded met data started in 2002. 

32 244 10 gridded met data, and this is the URL. 

33 244 20 Comprehensive Large Array data Storage System. 

34 244 23 data, a data that comes from satellites and the 

35 245 6 data. 

36 245 8 probably store MM5 data at sometime in the future, 

37 245 12 host of data just by that pop-down menu, and that's 

38 245 19 One is about the use of MM5 data and other 

39 245 20 sources of data. 

40 246 5 CAL MM5 and then a database is CAL-ETA, CAL-RUC and 

41 252 12 data routinely for their level of modeling, but, 

42 254 7 run National Weather Service data, or gridded data, 

43 254 10 National Weather Service data through AERMET, you 

44 255 5 the met data. Up to now, we've had ISC 

45 256 17 data, FOUS data and my immense knowledge of the 

46 258 5 the observed data, and it's -- it's when we begin 

47 259 8 approach is clearly to take NWS observation data 

48 259 12 on-site data, by all means use on-site data. 

49 259 19 stick all these observational data, and if we need 

50 260 15 And -- and to use met model data that's 
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 6 261 3 observational data, and that regional modeling has 

 7 261 4 used this model data, that -- that we feel the 

 8 261 10 met model data currently available, and -- and 

 9 261 15 somewhere post -- here's the MM5 data for 2002 that 

10 261 21 download that data and create what you wanted for 

11 262 7 database that is model ready, so to speak, sitting 

12 263 11 just how we can best use the environmental data 

13 265 10 to model met data. There is perceived advantages, 

14 265 13 observational data, there's not a lot of terrain in 

15 265 24 benefit of the model data, because we have much 

16 266 12 drives home the idea of just how sparse the data is 

17 267 14 to pass, to take advantage of that data that has 

18 268 25 up your own data and creating something, this MM5 

19 269 2 data that we're using right now, it's there and 

20 269 15 Once you've learned to get this model data 

21 269 23 database run, then it would be valid, perhaps even 

22 270 12 There's NCEP product data being used in 

23 270 17 see it, and that's ETA data going into CMAQ. 

24 270 18 So we have NCEP data which is the National 

25 270 20 environmental prediction. We have their data going 

26 272 25 to -- to AERMOD with the MM5 data, and do this in 

27 274 15 cells, and then we took all the other data from the 

28 275 15 use all the sources in this box, use this data and 

29 275 16 all the sources in this box use this data; once we 

30 276 3 Then AERMET and AERMOD using the observation data 

31 276 5 extracted the data from MM5 that we would need for 

32 276 6 that grid cell to replace the observational data. 

33 277 19 data, I'll call it a hybrid, because it was a 

34 280 8 look at any other data and just laughed, (laughter) 

35 281 5 NWS data, at least directionally, fairly 

36 281 15 data that -- that was -- that's the NWS and here's 

37 281 20 the NWS data. 

38 282 15 we'd like to do that and just have more data 

39 283 4 like that and dig deeper into this data, and I'd 

40 283 19 have in the NWS data run through AERMET. 

41 284 16 reflective a little more in the observational data 

42 284 18 going to see in the model data which has gone 

43 286 16 The observation data, even though it's an ASOS 

44 287 2 Weather Service data going through AERMOD. 

45 287 15 can see the AERMOD data down much lower in the 

46 288 17 There is an awful lot more dropped out data in 

47 289 2 replace AERMET input with MM5, put the MM5 met data 

48 289 18 MM5 data into AERMET's algorithm, we get this 

49 292 6 every data point -- I'm sorry, this is the 

50 292 7 twenty-fifth highest value of every data point, 
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 6 292 20 the met data, different data sets if we can do it, 

 7 294 21 data, their experiences and as they relate to these 

 8 296 4 been ideal data. 

 9 296 6 NCEP data, which is MM5, is what was the purpose of 

10 296 8 The forecast data, they're interested in a -- 

11 297 5 and blessed by the -- by NOAA, and the data is 

12 297 16 of their mind, are thinking what data is going into 

13 297 17 the scale of data that you have from a anemometer, 

14 300 20 also as a data user, primarily for local scale and 

15 301 4 users of the MM5 data that we are talking about, I 

16 301 7 decisions that we're making with these data versus 

17 301 8 the cost of how well we can do with the data. 

18 301 12 data sets around. It's sure tempting to use those, 

19 301 13 but we need to remember that the data sets that 

20 301 15 grown to understand and like, often have had data 

21 304 10 although assimilated data may provide more 

22 304 11 representative meteorological data in a large 

23 304 13 use of this data change modeling results in the 

24 304 16 representative is the assimilated data of the local 

25 304 20 costly assimilated data as opposed to historical 

26 304 25 data. 

27 305 2 Our experience with the use of MM5 data shows 

28 305 3 that the data quality at a specific location, or 

29 305 8 variations existed between the MM5 data for 

30 305 10 observed data. This was the Dallas-Fort Worth 

31 305 12 Some other constraints; assimilated data is 

32 305 13 available chronologically, while modelers need data 

33 305 15 data, this is the MAPS-RUC thirteen kilometer 

34 305 17 megabytes (120mb) of data each hour. 

35 305 20 Typically, data for only a few of the 

36 305 24 The assimilated data is, I believe, only 

37 306 3 all the data. 

38 306 8 assimilated data makes it more complicated for a 

39 306 9 reviewing agency to assure that the proper data has 

40 306 17 data maybe every three years or whatever -- five 

41 309 12 The issue here primarily is the missing data 

42 309 25 producing air quality related meteorological data 

43 310 9 meteorological data. 

44 310 10 Traditionally, the on-site data is best for 

45 310 14 The purity of on-site data becomes tarnished 

46 310 18 Local, meaning nearby airport, or ASOS data, 

47 311 6 Local or on-site data have an advantage in 

48 311 8 could be explained. Assimilated data, particularly 

49 311 12 detail when you go to assimilated data, and this is 

50 311 13 a "Pablum" version of real data. 
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 6 311 15 whether the use of different data sets makes more 

 7 311 24 grid cells based on analyzing meteorological data 

 8 312 8 and wind data for appropriate grid cells available 

 9 312 13 micro-scale in a reduced data set that is more 

10 312 15 The large volume of data from MM5 means that 

11 313 2 assimilated data should be representative of a 

12 313 5 There's not much data on that -- not at the 

13 313 8 This would mean using assimilated data on a 

14 313 10 data and computing a met set for many intermediate 

15 313 18 fitted into a grid assimilated data set. I see the 

16 315 14 Storing assimilated data. 

17 315 19 of NCDC or a similar body to archive the data. I 

18 315 21 Process data for U.S. sites produced from the 

19 316 5 house had a directory of processed data sets, let's 

20 316 8 regulatory body presumably has this, you know, data 

21 316 10 this data set available. 

22 316 14 processed assimilated data is likely to produce 

23 316 24 with assimilated data should the computed 

24 316 25 concentrations with existing data sets be too large 

25 317 3 If assimilated data is used, then some 

26 317 4 direction should be provided on whether data for 

27 318 18 the data assimilation. 

28 319 24 mesoscale meteorological data assimilation towards 

29 320 9 the data products have transitioned beyond MM5, and 

30 320 20 take the RUC data, and I can use it as my 

31 320 21 initialization data for MM5 and make the output 

32 320 23 to what the RUC data is. 

33 320 24 Conversely, I can take NCEP re-analysis data 

34 321 8 use of the prognostic data sets? And as I thumbed 

35 321 20 the prognostic data sets here, we're not looking 

36 321 23 meteorological data products that are being put 

37 322 6 And, also, are the meteorological data sets, 

38 323 2 modeling limited data sets for limited time 

39 323 11 So, if these prognostic data sets are of 

40 324 15 database that was supplied from CALMET and -- and 

41 324 23 data, and there's probably lots of those databases 

42 326 8 with this data? 

43 326 9 We've got seventeen (17) databases sitting out 

44 326 12 meteorological data. 

45 326 13 We've gone through data -- a met data 

46 326 15 of the on-site data and went to National Weather 

47 326 16 Service data, how well, did the model do, and -- 

48 326 22 data could be used. 

49 326 23 And so all that data is sitting out there. I 

50 327 2 test here is to take this -- to take gridded data, 
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 6 327 4 these databases and see how well the model performs 

 7 327 5 with that type of data. 

 8 330 19 met data, and do an evaluation that says, if I 

 9 331 12 kilometer MM5 data I'll bet that CALMET would have 

10 331 14 kilometer MM5 data, and it might be superior to 

11 331 15 what you saw from just the MM5 data set. 

12 331 18 those data sets, improved MM data sets into the 

13 333 20 because we just didn't have the databases 

14 333 24 protocols, told to use MM5, couldn't get the data, 

15 334 4 1992 and 1996 data sets. All you had to do send 

16 334 6 that data, give it back to you, and they also 

17 334 8 could create the data sets that you needed, so they 

18 337 13 constitutes an acceptable data set, because you're 

19 337 20 But the analysis of the data, as it comes out, 

20 338 4 on how to run the model, how to process the data, 

21 338 6 do we evaluate the data, I mean, what constitutes a 

22 338 7 decent data set for use, you know, what are the, 

23 339 6 these are acceptable data sets, and that way, if 

24 339 8 nonstandard data set, that at least if you put the 

25 339 10 use of that data set to demonstrate that it has 

26 339 23 this vision that some day there would be this data 

27 340 2 your MM5 data for you. 

28 340 4 encouraged that when your met data comes down, also 

29 340 5 have the evaluation products of that same data 

30 340 9 see this data. Well, it is, you know, I think all 

31 340 11 at data. 

32 

33 Page Ref No. Keyword = "database" 

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35 

36 70 14 meteorological database. 

37 72 17 meteorological database that should cover all 

38 117 15 one database that we had, we all knew that there 

39 246 5 CAL MM5 and then a database is CAL-ETA, CAL-RUC and 

40 262 7 database that is model ready, so to speak, sitting 

41 269 23 database run, then it would be valid, perhaps even 

42 324 15 database that was supplied from CALMET and -- and 

43 

44 Page Ref No. Keyword = "databases" 

45 ____ _______ _____________________ 

46 

47 324 23 data, and there's probably lots of those databases 

48 326 9 We've got seventeen (17) databases sitting out 

49 327 4 these databases and see how well the model performs 

50 333 20 because we just didn't have the databases 
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 6 61 16 all under one datum, and there are formulations for 

 7 64 10 datum DEM format using the SDTS2DEM program. 

 8 64 24 the North American Datum of 1927, and also 1983; 

 9 64 25 and the Old Hawaiian Datum and the Puerto Rican and 

10 65 2 the Virgin Island Datum. 

11 65 4 allows us to take any one of these datum and 

12 65 5 convert it into the North American Datum of 1983, 

13 65 7 Also, we have one degree datum scales, and 

14 65 12 system of 1984 and the North American Datum of 1983 

15 65 16 to add the datum code at the end of the anchor 

16 65 17 keyword, and this is to identify the datum on which 

17 65 20 American Datum map of 1927, the report is code for 

18 65 21 that datum. 

19 

20 Page Ref No. Keyword = "default" 

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23 76 19 other user default mode, and the sock will -- will 

24 99 3 we'd like to put some default values in, so we'd 

25 157 5 default settings that are quickly and -- and very, 

26 157 13 and they have become the default. 

27 161 24 listing of the default settings recommended, and 

28 162 11 defaulted in some applications to that, and we need 

29 180 12 The regulatory default override which is -- 

30 180 15 The regulatory default override -- what -- 

31 

32 Page Ref No. Keyword = "DEM" 

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35 62 10 algorithms to use with mixed DEM, or datums, and 

36 62 15 also the nodes spacing on the DEM files has 

37 63 9 that this is the DEM file one, DEM file two, three, 

38 63 11 superimposed over four of these DEM files, and we 

39 63 15 And the mandatory inclusion of the DEM terrain 

40 64 10 datum DEM format using the SDTS2DEM program. 

41 66 14 the DEM files that were sent in and apparently they 

42 67 2 to do was have the users take an old DEM file and 

43 67 21 the DEM files. 

44 71 17 a web site, download one degree DEM data and make 

45 109 25 demands. That's what -- that's what prompted the 

46 110 2 PSD or the new source review; regulations demand 

47 120 4 have to have a DEM file. You have to have a DEM 

48 120 6 If you can't get a DEM file for your area, 

49 190 8 demonstration for their BART eligible sources, the 

50 193 17 quality, which can be demonstrated through 
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 6 200 23 demonstrated to ourselves pretty convincingly that 

 7 339 10 use of that data set to demonstrate that it has 

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 9 Page Ref No. Keyword = "dispersion" 

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12 21 4 increases dispersion by doing this. 

13 37 5 the urban dispersion mechanism for low-level 

14 37 7 heights to make sure we calculate the dispersion 

15 38 6 AERMOD itself, which is the dispersion model. As 

16 52 17 All the dispersion that we're dealing with, 

17 52 19 focus of our dispersion models. 

18 53 10 vertical and lateral dispersion models. 

19 53 11 What the dispersion -- the science in AERMET 

20 53 15 translates the turbulence into dispersion, vertical 

21 53 16 and lateral dispersion. 

22 58 21 dispersion coefficients. 

23 135 20 dispersion. 

24 173 21 The underestimation of dispersion and for the 

25 174 5 them to other dispersion models. We find mixing 

26 179 10 get to dispersion coefficients, we're more into the 

27 179 18 For the dispersion coefficient, the one that's 

28 189 12 turbulence-based dispersion coefficients, but 

29 219 13 gridded meteorological data for air dispersion 

30 219 20 Meteorological data used in air dispersion 

31 221 25 into local dispersion models. 

32 224 16 modeling tools into our air dispersion models, and 

33 226 7 what we need to drive our local air dispersion 

34 227 18 input of gridded met data into local dispersion 

35 228 4 gridded met data into the dispersion modeling 

36 233 14 that dispersion. 

37 241 25 dispersion modeling typically, or should be public 

38 263 15 dispersion model applications that, maybe compu- -- 

39 270 3 dispersion models now that do that sort of thing, 

40 270 8 dispersion model is the -- is a general goal here, 

41 271 3 with that into a dispersion model, and then there 

42 279 21 met processor and the dispersion model output, and 

43 313 22 the plume dispersion and movement. 

44 343 3 years on the fundamentals of dispersion modeling, 

45 343 11 dispersion modeling, I would say that, well, the -- 

46 343 21 interested in learning about dispersion modeling. 
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 6 36 25 evaluation domain, it changed the results of the 

 7 50 13 of the overall domain and still put that in one 

 8 50 16 close by, and you wanted to run just one domain 

 9 62 5 change the domain size, the results changed. 

10 62 22 heights could vary based on the domain zones which 

11 63 10 and four. And this is a domain boundary that was 

12 63 20 inside the domain, but we have one that is outside 

13 63 21 the domain. And in order -- since this is the 

14 63 22 highest one, we would need to increase the domain 

15 119 5 said, well, we'll take a domain about this size and 

16 119 7 large domain. If you increased it, you've got to 

17 242 2 domain data and not proprietary so that everyone 

18 248 8 (30km) domain or a forty kilometer (40km) domain 

19 274 5 Our domain was thirty-six kilometers (36km), 

20 274 10 there is the domain from which -- that is grid cell 

21 304 12 modeling domain, a regional area, how much will the 

22 304 14 near-field domain, typically within fifty 

23 305 4 even throughout the modeling domain may not 

24 305 6 that domain. 

25 305 14 for the modeling domain. Each hour of MAPS-RUC 

26 305 22 locations in that domain are needed, and you have 

27 312 24 entire modeling domain as a single grid cell. I 

28 339 25 your domain, and it would grab your -- you know -- 

29 

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33 41 7 We have a more advanced building downwash 

34 42 22 The PRIME building downwash algorithms require 

35 45 17 Now, moving to the building downwash, those 

36 45 20 significant building downwash; that is, there was 

37 48 18 seven with the building downwash scenarios. We had 

38 48 20 When we had the case of no downwash, AERMOD 

39 48 24 With the downwash scenarios, AERMOD out 

40 72 8 We have in there the PRIME building downwash 

41 75 24 building downwash. Your building height, length, 

42 80 19 downwash, we had one case in here, I believe, that 

43 118 11 how to deal with that for both downwash and 

44 118 15 algorithms in PRIME, if you're in downwash 

45 135 14 behave the same in the cavity and in the downwash 

46 141 14 where you have emissions, and downwash, and a large 
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 6 39 13 conservative estimates, to the downwind 

 7 72 19 so that when you do the downwind concentration 

 8 130 9 regardless of the distance downwind; the second one 

 9 130 19 downwind, and that would make it more useful, 

10 173 14 Downwind distance was the other big one, at 

11 174 8 downwind distance argument, which is one of the 

12 175 2 secondary formation mentioned, we have the downwind 

13 183 8 downwind, and then finally a lot of discussion on 

14 260 4 couple of hundred kilometers (200km) downwind, not 

15 

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19 8 19 at EPA's NOAA conferences, but some of this is from 

20 15 14 EPA's look at what the NRC said. 

21 29 20 in terms of EPA and in our working relationships. 

22 29 23 expertise and working relationships across EPA, 

23 30 14 the EPA regions, we're pursuing and engaging in 

24 30 15 technical work groups across, not just across EPA, 

25 35 5 from EPA and from consulting. So, we are pleased 

26 60 23 EPA, and I've been assigned to improve AERMAP. 

27 70 11 Herman Wong, from EPA Region Ten (10), has 

28 104 14 that's composed of folks from EPA, and state and 

29 112 3 There are EPA reports. There are OAQPS policy 

30 131 5 will force us, as a community, or you as EPA, to 

31 138 8 problem, for EPA to put air guards on the 

32 148 14 EPA's Emissions Monitoring Analysis Division to -- 

33 155 5 between, of course, EPA and the Federal land 

34 155 10 representation was through the EPA conduit, but 

35 155 15 individuals, EPA, Forest Service, Park Service and 

36 187 17 I'm Bret Anderson, US EPA Region Seven out of 

37 188 7 some of the other EPA regions and with the Federal 

38 188 17 these probably proposed more so than what the EPA 

39 207 9 The management of this model by EPA is maybe 

40 207 11 community to provide models to EPA. 

41 207 13 -- what is the actual relationship between the EPA 

42 207 21 approach in updating the EPA approved version of 

43 209 7 to get guidance from the EPA through a protocol 

44 210 10 it, in the sense that is EPA going to fund that 

45 221 13 work we're doing here at EPA as far as getting 

46 221 22 was when John was actually at EPA, to incorporate 

47 221 24 in EPA's budget to incorporate gridded met data 

48 222 22 that, and what we plan to do here at EPA. 

49 224 10 the introductions, the EPA has been tasked to 

50 224 15 EPA to incorporate more advanced air quality 
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 6 227 13 And what we are doing here at EPA, back in the 

 7 232 20 regional EPA offices, Fisheries and Wildlife 

 8 243 14 And we will probably hear an EPA rule assist 

 9 243 16 have an ongoing dialogue from EPA to the regions 

10 252 4 to what extent EPA is sharing resources 

11 252 9 at EPA working with CMAQ, and in CMAQs, and I don't 

12 252 20 beyond the EPA campus here, in addition to the 

13 252 22 components of EPA, also into the University 

14 252 25 ultimately used by EPA. 

15 295 2 Trinity Consultants, and Bret Anderson from EPA, 

16 295 9 modelers in the Division for EPA in states prior to 

17 306 12 regions within EPA. And this is going to be 

18 307 12 EPA has a one-hour CO standard. 

19 308 6 calms are to be handled; well, EPA's made a policy 

20 308 20 bring consistency to EPA's general approach, under 

21 317 20 environmental scientist with the US EPA Region in 

22 321 12 which says that, you know, these models that EPA 

23 325 20 I think NOAA should look into that -- EPA and 

24 334 12 GEORGE SCHEWE: George Schewe, former EPA employee 

25 

26 Page Ref No. Keyword = "ETA" 

27 ____ _______ _______________ 

28 

29 225 17 The ETA model, it's a regional mesoscale 

30 231 10 at some of the forecast models, RUC, ETA and WRF, 

31 270 13 dispersions modeling right now. That's the ETA 

32 270 17 see it, and that's ETA data going into CMAQ. 

33 293 19 of next year, RUC, ETA, probably never going to be 

34 

35 Page Ref No. Keyword = "Federal" 

36 ____ _______ ___________________ 

37 

38 29 24 other Federal agencies, and the scientific 

39 35 22 and as seen by the Federal Register, and that 

40 111 25 to go out in the Federal Register and say, "thou 

41 146 22 you may recall from the Federal Register Notice 

42 155 5 between, of course, EPA and the Federal land 

43 172 13 Federal Land Managers work with the flag document 

44 188 7 some of the other EPA regions and with the Federal 

45 189 9 The discussions that we had with the Federal 

46 195 17 offices and the Federal Land Managers. 

47 202 20 of the Federal Government. There is a large number 

48 203 6 Federal -- Federal as was what the original IWAQM 

49 203 20 had not reached out to anyone outside the Federal 

50 209 10 to in this case, the Federal Land Managers, are 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 390 

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 3 Page Ref No. Keyword = "fence line" 

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 5 

 6 78 12 a boundary or a fence line that goes out to a 

 7 78 15 on the distance to the fence line. 

 8 78 17 about right here. These are fence line 

 9 130 5 fence line? 

10 130 10 was at the fence line, or the ambient boundary. 

11 239 24 scale modeling, the fence line is of paramount 

12 303 14 transports. But it's not for the fence line or 

13 

14 Page Ref No. Keyword = "file" 

15 ____ _______ ________________ 

16 

17 58 14 file, which contains the scaling parameters that 

18 61 21 This is an example of an AERMAP output file, 

19 62 6 We were asked to also process the SDTS file 

20 63 9 that this is the DEM file one, DEM file two, three, 

21 64 18 to interact with the patch file in order to run it 

22 66 18 variable file lengths, and I was able to go and 

23 67 2 to do was have the users take an old DEM file and 

24 72 5 there is such a term. And the one degree data file 

25 73 3 develops a basic control file; something similar to 

26 73 9 this control file and just modify the parameter or 

27 73 23 So you've got yourself an AERMOD control file, 

28 79 4 restart file. Once you have made the AERSCREEN 

29 79 9 into this file called "restart file", and you can 

30 79 16 So this is an example of the restart file, and 

31 120 4 have to have a DEM file. You have to have a DEM 

32 120 5 file of your data, you have to have that put in. 

33 120 6 If you can't get a DEM file for your area, 

34 166 2 it from a -- from a file on the web, stick it in 

35 241 21 file sizes, these are not -- are not issues that 

36 

37 Page Ref No. Keyword = "files" 

38 ____ _______ _________________ 

39 

40 58 9 from meteorological files, created -- or that were 

41 58 12 actually creates the files that are used by AERMOD. 

42 58 13 There are two (2) files; one is a surface 

43 61 4 model computer files that contain elevations that 

44 62 8 for those files were free over the internet. 

45 62 15 also the nodes spacing on the DEM files has 

46 63 11 superimposed over four of these DEM files, and we 

47 64 13 package. It's a batch files system included with 

48 66 14 the DEM files that were sent in and apparently they 

49 67 15 USGS SDTS files have node spacings of ten (10) 

50 67 21 the DEM files. 
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 3 Page Ref No. Keyword = "forecast" 

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 5 

 6 9 12 We use models a lot to forecast what things 

 7 18 9 And as we look at the forecast residual 

 8 21 15 Our forecast models go out for ten (10) and 

 9 22 17 to forecast air quality, not just by empirical 

10 23 17 of forecast. 

11 59 22 by AERMET, the Forecast Systems Laboratory, FSL 

12 225 7 quality forecast information in its air quality 

13 226 12 forecasting model, and it's being developed by a 

14 231 10 at some of the forecast models, RUC, ETA and WRF, 

15 231 13 from MM5 type data versus forecast type data. And 

16 256 12 When I was a very young, brand new forecaster 

17 257 5 And the other one is to adjust your forecast 

18 264 8 then suddenly you're into a forecasting -- possibly 

19 264 9 real-time forecasting realm that -- that may have 

20 264 17 or there in a forecast model. So there's -- there 

21 269 11 from a prognostic initialization to a forecast, and 

22 270 14 model that's going into an air quality forecast run 

23 271 9 before, and then -- then go into forecast fields. 

24 296 8 The forecast data, they're interested in a -- 

25 301 20 forecaster's dream. They already have tomorrow's 

26 319 7 able to generate for -- to generate a forecast in 

27 319 12 Washington is running the MM5 on a forecast mode, 

28 319 25 forecast products in these things. 

29 325 8 time. It's linked to the NCEP forecast products, 

30 325 11 the readily available NCEP forecast winds, put in 

31 332 6 have an aviation component in their forecast 

32 

33 Page Ref No. Keyword = "forecasts" 

34 ____ _______ _____________________ 

35 

36 225 6 forecasts, and as you know, AIRNOW employs air 

37 225 8 forecasts. 

38 226 16 and has high resolution window forecasts with 

39 256 18 atmosphere, and created forecasts. 

40 

41 Page Ref No. Keyword = "grade" 

42 ____ _______ _________________ 

43 

44 140 9 Cartesian grade, is there any consideration to 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 392 

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 3 Page Ref No. Keyword = "gridded" 

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 5 

 6 28 22 of the future elements in terms of gridded met 

 7 31 6 gridded meteorological data, including state-of-the 

 8 59 7 of gridded met data and certainly a need to add to 

 9 59 8 this ability to take gridded met data and process 

10 59 14 job than some of the gridded met data they have on 

11 59 17 AERMET with gridded met data, taking what's good 

12 59 18 out of the gridded met data but using the 

13 61 22 and in this case it's for a gridded polar, and you 

14 116 13 how do we use gridded data. 

15 123 8 Use of gridded met data. I think we've 

16 133 13 towards gridded met data, and when we do move 

17 133 14 towards gridded met data, we will be having fields 

18 145 23 go to a gridded field. Now, I understand, as John 

19 158 8 gridded meteorology efforts. 

20 163 6 talking about some of the gridded meteorology field 

21 174 11 when we look towards the MM5, or the gridded 

22 177 5 Gridded clouds -- the icon- -- I know in fact 

23 178 7 gridded meteorological data, if you are applying 

24 196 11 meteorolog- -- the gridded meteorological data for 

25 219 7 panel discussion on the gridded met data. 

26 219 12 afternoon will address the gridded met data, 

27 219 13 gridded meteorological data for air dispersion 

28 220 19 on the gridded met portion, and this was a 

29 220 23 work lately that's been done to talk about gridded 

30 221 3 in the regional scale arena, using gridded met 

31 221 6 a gridded met data, but we are also looking to 

32 221 14 gridded met data into AERMOD and CALPUFF; also 

33 221 15 report out on a gridded met data that work group 

34 221 24 in EPA's budget to incorporate gridded met data 

35 222 11 presentations made on gridded met data, as well. 

36 222 14 CALPUFF being used more extensively, the gridded 

37 222 16 just a lot more visibility of the gridded met data, 

38 222 17 and so that renewed some interest in the gridded 

39 222 20 gridded met data project which I will go over that 

40 222 24 do we want to use gridded met data? 

41 223 9 Also, this gridded met data, because it's more 

42 223 14 Also, the gridded data has many more 

43 223 21 product, it -- gridded met data incorporates a lot 

44 224 8 consider gridded met data, it's an advancement of 

45 225 11 Which gridded met data product should be used? 

46 227 4 gridded met product. 

47 227 18 input of gridded met data into local dispersion 

48 228 2 Just to go into some details about the gridded 

49 228 4 gridded met data into the dispersion modeling 

50 228 13 Our goal really is to get gridded data into 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 393 

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 3 Page Ref No. Keyword = "gridded" 

 4 ____ _______ ___________________ 

 5 

 6 229 15 incorporating the MM5 data or gridded met data into 

 7 231 3 utilize gridded met data to the fullest. 

 8 231 22 gridded met data project would be an IT tool 

 9 232 6 And I also compute the fields from the gridded 

10 232 13 together earlier in the year a gridded met data 

11 232 25 related to gridded method data, and also at the 

12 233 4 gridded met data. 

13 233 6 additional met parameters available from gridded 

14 234 9 because MM5 is, of course, gridded information and 

15 236 4 use gridded met data? There is a lot of issues 

16 236 7 Gridded data has also been nudged to create a 

17 237 22 compare the gridded met data with the traditional 

18 240 2 data, on-site or gridded, and that's what we'll be 

19 240 11 gridded met data, maybe they're not shortcomings, 

20 240 24 gridded met data model. Typically has fewer calms, 

21 241 10 choice, where would we want the gridded met data to 

22 242 7 Gridded met data is typically very large in size, 

23 242 12 gridded and local scale models, we are becoming 

24 242 18 gridded met survey that I did, only twenty of the 

25 242 21 experience do you have in gridded met data? 

26 242 25 some experience with gridded data, and it was 

27 243 7 we saw coming out of the gridded met data work 

28 243 9 community, gridded met data is not something that 

29 243 19 from National Weather Service to gridded data. 

30 244 6 gridded met data started in 2002. 

31 244 10 gridded met data, and this is the URL. 

32 244 12 see. There is a whole host of gridded products 

33 254 7 run National Weather Service data, or gridded data, 

34 294 11 If I could have the gridded met panel members 

35 294 20 background of what their relationship is to gridded 

36 323 5 But in the realm of using, you know, gridded 

37 324 22 these meteorological gridded fields with real live 

38 327 2 test here is to take this -- to take gridded data, 

39 330 18 what your trying to get to by doing this gridded 

40 334 17 from the perspective of the gridded meteorology 

41 339 18 whole as we move forward in the gridded met 

42 340 12 When we start looking at the gridded fields, 

43 340 17 mystery. That takes the mystery of a gridded model 

44 

45 Page Ref No. Keyword = "group" 

46 ____ _______ _________________ 

47 

48 24 22 retired, and my name is Tyler Fox. I've been group 

49 24 23 leader for the air quality monitoring group for 

50 28 2 folks in the group to really think about how we had 
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 3 Page Ref No. Keyword = "group" 

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 6 29 7 group, Joe is not here anymore, we lost a number of 

 7 30 2 Air Quality Modeling Group leadership role and 

 8 34 4 We actually have a team within our group 

 9 51 9 group. 

10 60 22 work for the Air Quality Modeling Group here at 

11 70 7 work group. As I mentioned, Jim Haywood from the 

12 70 15 I'm on the work group here. 

13 70 16 Karen Wesson, a new employee at our group, has 

14 83 14 you Karen Wesson from our group who will now help 

15 100 15 AERMOD Implementation group and the exciting things 

16 102 2 bring you into our group. 

17 104 13 together a work group, a work group that compos- -- 

18 108 8 construct an ad hoc work group to help support that 

19 112 6 precedents that the lawyers in the group will go -- 

20 147 25 supports us in the Air Quality Modeling Group. 

21 151 15 Right now we've convened a loose work group, 

22 151 16 we're going to call it CALPUFF work group, and it 

23 151 18 the original IWAQM work group, folks who clearly 

24 152 5 The focus of this group is to take a good hard 

25 152 21 that's what we've been doing with this group in our 

26 155 2 Group on Air Quality Modeling, and I guess I should 

27 160 20 IWAQM group and how they wanted their 

28 169 17 This group that I put -- that I put up on the 

29 169 20 What is this group going to do other than meet 

30 172 3 The Air Quality Modeling Group has, of course, 

31 172 9 heading of secondary formations, at least one group 

32 174 20 ongoing in this -- this air quality modeling group, 

33 176 21 from the IWAQM group. 

34 187 18 Kansas City, and there is a group of the regional 

35 194 17 We have -- we have a group of people that are 

36 198 12 issues fleshed out. That group I gave you in the 

37 199 16 from this group which clearly is more learned in 

38 202 3 would defer to Tyler Fox, the group leader, but I 

39 203 7 interagency work group, and that was the stepping 

40 203 10 that's why we threw that group -- or we put that 

41 203 11 group together and had our first couple of 

42 203 25 logistics, I guess, of trying to get this group 

43 211 19 contributes in this group and the community 

44 220 12 from Dennis Atkinson, from our group, who works 

45 221 15 report out on a gridded met data that work group 

46 232 14 work group, and this was just kind of as a 

47 235 7 group, but you may want to use a weighted average 

48 237 5 One of our work group members had had 

49 238 2 This is something that our work group was very 

50 240 13 group members that brought up some precip 
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 3 Page Ref No. Keyword = "group" 

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 6 243 8 group, was education for the local modeling 

 7 243 11 that group. 

 8 259 2 work group, and some of the first steps we've taken 

 9 293 25 with that work group that Dennis talked about, and 

10 294 3 about the CALPUFF group, if you're not on that work 

11 294 4 group and you have something you want to contribute 

12 338 21 quality modeling group on, was taking those 

13 

14 Page Ref No. Keyword = "groups" 

15 ____ _______ __________________ 

16 

17 30 15 technical work groups across, not just across EPA, 

18 30 19 work groups, and we -- we really see that given the 

19 175 18 seven -- seven groups or seven people doing the 

20 182 16 quite a few individuals, and -- and groups that 

21 

22 Page Ref No. Keyword = "guidance" 

23 ____ _______ ____________________ 

24 

25 104 24 of guidance development, and I'm going to 

26 104 25 differentiate between guidance development, and the 

27 106 21 guidance, but is sort of our advice on how one 

28 108 20 start building guidance, differentiated from "the 

29 108 21 guidance". 

30 109 19 The guidance development process, not needing 

31 110 4 And so that guidance will take the form of a 

32 110 7 tenets that I think should appear in that guidance. 

33 110 10 important that we keep this guidance principle 

34 110 11 based, so we can avoid prescriptive guidance 

35 111 8 Types of guidance, and so finally the thing to 

36 111 11 guidance ought to be, we need to zip that through 

37 111 20 How does that guidance take form? It takes 

38 111 22 guidance, where we absolutely rule make. 

39 111 23 That's the -- that's the guidance where AERMOD 

40 112 12 Okay, so that's sort of the guidance approach. 

41 114 14 address that concept in the guidance. 

42 117 19 request for guidance in there with regards to that. 

43 118 5 So in this guidance, we suggest that you've 

44 118 10 done, but we -- we have some guidance in here as to 

45 120 17 there's some guidance in there which talks about 

46 126 18 We'll develop formal guidance as experience is 

47 126 20 You can't develop guidance, put it out there, 

48 138 20 of guidance for users like ourselves that would 

49 141 22 guidance as how to model these type of things. 

50 143 14 come up with a guidance for the user community as 
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 3 Page Ref No. Keyword = "guidance" 

 4 ____ _______ ____________________ 

 5 

 6 151 7 missing there, and that is guidance and we're not 

 7 190 21 guidance recommended using method six, which, I 

 8 191 20 read of the current state of the guidance, you 

 9 191 24 that are needed in terms of what the guidance 

10 193 2 areas where the existing guidance should 

11 193 21 And there is no further guidance on what these 

12 194 7 about is clarifying the guidance to come up with a 

13 195 8 areas where we feel that additional guidance may be 

14 197 3 look at -- at guidance, recommendations, where we 

15 205 22 that this is guidance or technical information that 

16 206 25 stepping stone to changes in the guidance. 

17 209 7 to get guidance from the EPA through a protocol 

18 251 13 guidance document, I believe it was in the '98 time 

19 

20 Page Ref No. Keyword = "guide" 

21 ____ _______ _________________ 

22 

23 67 6 user's guide. 

24 67 7 And there is a draft XYZ terrain user's guide 

25 96 11 are out of the AERMET user's guide. 

26 102 12 guess, in 1978 when the first guidelines came out, 

27 103 6 guidelines were developed at that point. 

28 105 3 guide, and that's -- and there's an important 

29 106 13 an implementation guide with the promulgation. 

30 106 20 prudent to put together a guide, which is not 

31 107 2 This guide his not dead; it should be a living 

32 107 3 guide, as we gain information and experience that we 

33 107 7 have the guide. In fact the guide is now ready. 

34 109 20 advice and guide. What is the purpose? 

35 112 13 The implementation guide. Let me talk a 

36 115 20 guide does is it addresses the fact that -- that 

37 121 2 Okay, that's the implementation guide. 

38 126 11 that is, the implementation guide. 

39 131 20 So one of the things that's in the guide that 

40 132 11 The suggestion in the guide is to say, well, 

41 158 21 was recommended to be included in the guideline, of 

42 175 23 Reviewers Guide, with my apologies, if I 

43 189 21 guideline on air quality -- you know -- recommends 

44 192 17 D (Section 9.3.12d) of the Guideline on Air Quality Models, it 

states that mesoscale meteorological 

45 192 24 know, the guideline oftentimes takes on a more 

46 193 11 (Section 9.3c) of the Guideline on Air Quality Models, what you 

find is, you find it states 

47 200 4 that came out in the most recent guidelines was with regard 

48 201 25 -- specific recommendations in the guideline? 

49 202 2 MARK EVANGELISTA: As far as the guideline end of things, I 

50 206 21 AERMOD implementation guide; something that's a 
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 3 Page Ref No. Keyword = "guide" 

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 6 207 4 CALPUFF implementation guide, to be able to be more 

 7 321 9 through the guideline on air quality models, I came 

 8 328 14 implementation guide, we've written up a bit of a 

 9 335 17 agency, by the guideline, by whoever, for 

10 

11 Page Ref No. Keyword = "guideline" 

12 ____ _______ _____________________ 

13 

14 158 21 was recommended to be included in the guideline, of 

15 189 21 guideline on air quality -- you know -- recommends 

16 192 17 D (Section 9.3.12d) of the Guideline on Air Quality Models, it 

states that mesoscale meteorological 

17 192 24 know, the guideline oftentimes takes on a more 

18 193 11 (Section 9.3c) of the Guideline on Air Quality Models, what you 

find is, you find it states 

19 201 25 -- specific recommendations in the guideline? 

20 202 2 MARK EVANGELISTA: As far as the guideline end of things, I 

21 321 9 through the guideline on air quality models, I came 

22 335 17 agency, by the guideline, by whoever, for 

23 

24 Page Ref No. Keyword = "guidelines" 

25 ____ _______ ______________________ 

26 

27 102 12 guess, in 1978 when the first guidelines came out, 

28 103 6 guidelines were developed at that point. 

29 200 4 that came out in the most recent guidelines was with regard 

30 

31 Page Ref No. Keyword = "implement" 

32 ____ _______ _____________________ 

33 

34 8 8 sources, and in particular, as we implement 

35 11 22 strategies. We implement the strategies, we check 

36 13 7 Designing and implementing controls for 

37 27 13 on implementing it and using it, developing it and 

38 57 14 There were problems in the implementation of 

39 58 3 implemented which seems to -- which works much 

40 100 15 AERMOD Implementation group and the exciting things 

41 101 21 this is going to be to implement it. 

42 102 3 So we have thought about implementation. 

43 102 4 Implementation is -- obviously really what this is 

44 102 16 Well, without consistency, implementation 

45 104 4 we have no implementation issues. 

46 104 9 issues, the implementation issues are going to be 

47 104 17 go about implementing this process. 

48 104 23 we're going to take to implementation, the concept 

49 105 2 third one you see there which is the implementation 

50 105 8 Okay, AERMOD implementation process. Why do 
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 3 Page Ref No. Keyword = "implement" 

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 6 105 11 straightforward. It's that as we implement this 

 7 106 13 an implementation guide with the promulgation. 

 8 106 15 don't have a lot of experience with implementing 

 9 106 19 implementing this, and so we thought that it was 

10 109 13 But, as we start implementing, there are going 

11 111 4 implementing this model, we need to think long term 

12 112 13 The implementation guide. Let me talk a 

13 121 2 Okay, that's the implementation guide. 

14 125 8 implementing this. You know, people are looking 

15 125 23 implementation issues are expected. We should 

16 125 24 expect that there will be implementation issues. 

17 125 25 We need to implement in a manner that is going 

18 126 6 And the implementation process that we put in 

19 126 11 that is, the implementation guide. 

20 135 16 That would be a successful implementation 

21 145 7 formulation issue than an implementation issue. 

22 206 21 AERMOD implementation guide; something that's a 

23 207 4 CALPUFF implementation guide, to be able to be more 

24 212 11 process of implementation and evaluation, and the 

25 212 23 know, how we should actually implement some of 

26 241 23 and kind of implementation type issues. 

27 328 14 implementation guide, we've written up a bit of a 

28 

29 Page Ref No. Keyword = "implementation" 

30 ____ _______ __________________________ 

31 

32 57 14 There were problems in the implementation of 

33 100 15 AERMOD Implementation group and the exciting things 

34 102 3 So we have thought about implementation. 

35 102 4 Implementation is -- obviously really what this is 

36 102 16 Well, without consistency, implementation 

37 104 4 we have no implementation issues. 

38 104 9 issues, the implementation issues are going to be 

39 104 23 we're going to take to implementation, the concept 

40 105 2 third one you see there which is the implementation 

41 105 8 Okay, AERMOD implementation process. Why do 

42 106 13 an implementation guide with the promulgation. 

43 112 13 The implementation guide. Let me talk a 

44 121 2 Okay, that's the implementation guide. 

45 125 23 implementation issues are expected. We should 

46 125 24 expect that there will be implementation issues. 

47 126 6 And the implementation process that we put in 

48 126 11 that is, the implementation guide. 

49 135 16 That would be a successful implementation 

50 145 7 formulation issue than an implementation issue. 
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 6 206 21 AERMOD implementation guide; something that's a 

 7 207 4 CALPUFF implementation guide, to be able to be more 

 8 212 11 process of implementation and evaluation, and the 

 9 241 23 and kind of implementation type issues. 

10 328 14 implementation guide, we've written up a bit of a 

11 

12 Page Ref No. Keyword = "implementing" 

13 ____ _______ ________________________ 

14 

15 13 7 Designing and implementing controls for 

16 27 13 on implementing it and using it, developing it and 

17 104 17 go about implementing this process. 

18 106 15 don't have a lot of experience with implementing 

19 106 19 implementing this, and so we thought that it was 

20 109 13 But, as we start implementing, there are going 

21 111 4 implementing this model, we need to think long term 

22 125 8 implementing this. You know, people are looking 

23 

24 Page Ref No. Keyword = "ISC" 

25 ____ _______ _______________ 

26 

27 36 11 we talked having ISC-PRIME and AERMOD separate 

28 36 17 looking even better in AERMOD, PRIME and ISC PRIME, 

29 39 5 to be true moving from ISC to AERMOD. It's a more 

30 40 15 ISC. 

31 40 18 estimates are going to change, from using ISC to 

32 41 3 You remember with ISC we had classifications, 

33 41 20 ISC to AERMOD. And it's a fairly thorough list of 

34 41 25 development to make it as similar to ISC as 

35 42 4 exactly the same as what we had with ISC. 

36 42 5 So if you've been running ISC for a number of 

37 42 11 options are there as we what we have in ISC. So 

38 42 25 we had in ISC-PRIME, but still it's different from 

39 43 2 what we had in ISC. 

40 43 7 remember, from the ISC runs. 

41 43 22 ISC concentration. 

42 43 23 So a value of one at AERMOD and ISC basically 

43 44 3 ISC. 

44 44 6 (48) cases that AERMOD and ISC were pretty much the 

45 44 16 that ISC tended to underestimate long-term 

46 44 20 basically, you see that there AERMOD and ISC 

47 44 25 ratio for the mod- -- AERMOD and ISC is about as 

48 45 3 (.32) which is about a third of ISC. 

49 45 24 We compared AERMOD to ISC3 and we compared 

50 45 25 AERMOD to ISC-PRIME. They both were a part of the 
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 6 46 3 this case, notice when we compared AERMOD to ISC, 

 7 46 7 bit lower than what we might expect from ISC in the 

 8 46 15 ISC-PRIME models. We knew when we brought PRIME 

 9 46 19 And here, we want AERMOD and ISC-PRIME to 

10 46 20 perform very, very similarly to ISC-PRIME. If you 

11 47 5 performance between AERMOD and ISC-PRIME. 

12 47 14 most dramatic results. May we call it ISC, we 

13 47 20 AERMOD -- I'm sorry, than ISC, and indeed we find 

14 47 25 ISC3 model. 

15 48 8 concentrations much lower than ISC. 

16 48 21 out performed ISC in nine out of the ten 

17 48 25 performed ISC-PRIME in two evaluations, had about 

18 49 5 here, or made the conclusion, is that ISC -- oh, 

19 49 7 We compared AERMOD to ISC-PRIME, and that's 

20 49 10 too, that in evaluating ISC-PRIME, and comparing 

21 49 11 ISC-PRIME to ISC, which is probably the logic or 

22 49 12 the reasoning here, ISC-PRIME slightly outperformed 

23 49 13 ISC. 

24 49 15 ISC-PRIME; ISC-PRIME slightly outperformed ISC3. 

25 49 20 in its comparison to ISC. We do have some ongoing 

26 73 4 what AERMOD and ISC does, and that is, "store and 

27 80 3 sorry, ISC -- (chuckling) when we've compared 

28 101 23 model is fundamentally different than ISC, and what 

29 101 25 of the ISC insurgency that's out there that we can 

30 103 3 ISC, when CTDMPLUS, when -- which was actually 

31 104 6 optimized ISC. We are now going to be embarking on 

32 104 8 different than ISC. It looks like ISC, but the 

33 105 16 Number one; ISC and AERMOD, and I think this 

34 105 19 the community is going to be free to use either ISC 

35 105 22 permit for a SIP that uses ISC or AERMOD. 

36 106 3 At the end of that year, ISC is going to go 

37 107 22 quote, solved all the problems with ISC, but we are 

38 112 23 ISC in a fundamental way in the -- from the 

39 115 24 Okay. The next is, this model, unlike ISC, 

40 118 14 trivial as it was for ISC, because the plume rise 

41 126 7 place is one, ISC or AERMOD, can be used in the 

42 127 2 like ISC. 

43 134 14 ISC-PRIME and ISC, that the ratios are near one. 

44 134 16 AERMOD we're glad is out performing ISC. 

45 135 2 -- as far as the agreement between AERMOD and ISC, 

46 135 13 concentrations from AERMOD PRIME versus ISC-PRIME 

47 135 19 AERMOD and ISC would have in the way it calculates 

48 136 3 comparing AERMOD-PRIME to ISC-PRIME, AERMOD out- -- 

49 136 4 slightly out performed ISC-PRIME, which was a 

50 138 4 days of ISC in terms of being able to extrapolate 
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 4 ____ _______ _______________ 

 5 

 6 139 11 statistical comparison between ISC and AERMOD and 

 7 162 22 ever be as easy as ISC, and that was probably the 

 8 200 21 that you could -- you could reproduce ISC, and I 

 9 201 3 ISC. 

10 227 2 ISC model. 

11 229 20 improvement over ISC, but if we can drive AERMOD 

12 251 20 there was a step-up from ISC was still simplified 

13 253 11 promulgated, and ISC had a pretty long shelf life. 

14 255 5 the met data. Up to now, we've had ISC 

15 273 20 the AERMOD compared to the ISC looked -- didn't 

16 275 24 So the idea was to run MRN with ISC the good 

17 276 4 once again, back comparing it to ISC. Then we 

18 308 7 decision in ISC, as to how to handle these. 

19 326 19 be a replacement for ISC, we didn't want to put too 

20 328 21 you compare, say, the ISC predictions to MM5 

21 328 24 between the ISC predictions in Philadelphia and 

22 329 7 what was -- with what ISC showed, and I got 

23 329 17 ISC. 

24 343 23 AERMOD, and who have used ISC. 

25 

26 Page Ref No. Keyword = "ISC-PRIME" 

27 ____ _______ _____________________ 

28 

29 36 11 we talked having ISC-PRIME and AERMOD separate 

30 42 25 we had in ISC-PRIME, but still it's different from 

31 45 25 AERMOD to ISC-PRIME. They both were a part of the 

32 46 15 ISC-PRIME models. We knew when we brought PRIME 

33 46 19 And here, we want AERMOD and ISC-PRIME to 

34 46 20 perform very, very similarly to ISC-PRIME. If you 

35 47 5 performance between AERMOD and ISC-PRIME. 

36 48 25 performed ISC-PRIME in two evaluations, had about 

37 49 7 We compared AERMOD to ISC-PRIME, and that's 

38 49 10 too, that in evaluating ISC-PRIME, and comparing 

39 49 11 ISC-PRIME to ISC, which is probably the logic or 

40 49 12 the reasoning here, ISC-PRIME slightly outperformed 

41 49 15 ISC-PRIME; ISC-PRIME slightly outperformed ISC3. 

42 134 14 ISC-PRIME and ISC, that the ratios are near one. 

43 135 13 concentrations from AERMOD PRIME versus ISC-PRIME 

44 136 3 comparing AERMOD-PRIME to ISC-PRIME, AERMOD out- -- 

45 136 4 slightly out performed ISC-PRIME, which was a 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 402 

 2 

 3 Page Ref No. Keyword = "IWAQM" 

 4 ____ _______ _________________ 

 5 

 6 150 6 be the second IWAQM, the IWAQM phase two (IWAQM 

 7 151 12 where it was when IWAQM was finalized being the 

 8 151 18 the original IWAQM work group, folks who clearly 

 9 154 3 the IWAQM report, we just don't know just yet how 

10 154 25 The IWAQM originally -- the Interagency Work 

11 155 3 read it out just once before I call it IWAQM; they 

12 155 19 The first IWAQM, for those of you who are not 

13 156 5 The first IWAQM was essentially an interim 

14 156 13 Well, the first IWAQM said, let's at least put 

15 157 8 accordance with the IWAQM II report, done deal. 

16 157 18 way, so the first option is the IWAQM 

17 157 25 and in -- as -- as the IWAQM report, phase two, was 

18 160 20 IWAQM group and how they wanted their 

19 161 8 applications that IWAQM addressed in phase two. 

20 164 12 IWAQM had addressed this way back then as a 

21 166 13 Once again now, IWAQM requires outright expert 

22 173 6 And then once again, for AQRVs, the IWAQM 

23 176 9 depart, or that came to be, after IWAQM II was put 

24 176 17 It's just -- this came out since IWAQM. IWAQM 

25 176 21 from the IWAQM group. 

26 176 24 course, more recent than IWAQM. 

27 178 11 prominent when IWAQM II was -- was done -- where 

28 187 24 under Appendix W and in the IWAQM Phase II 

29 189 6 the IWAQM phase II recommendations for the use of 

30 202 6 I think the IWAQM intent of not being cookbook 

31 203 6 Federal -- Federal as was what the original IWAQM 

32 218 2 originally with IWAQM, and it's has been carried 

33 218 16 You were one of the IWAQM originals, I 

34 295 15 The -- I was one of the members of IWAQM where 

35 

36 Page Ref No. Keyword = "layer" 

37 ____ _______ _________________ 

38 

39 40 24 boundary layer concepts all now built into AERMOD, 

40 52 14 AERMET is essentially a boundary layer model, 

41 52 16 idealization with the boundary layer. 

42 52 18 everything occurs in the boundary layer. It's the 

43 52 22 layer during the day, and the stable boundary layer 

44 52 24 The convective boundary layer is driven by 

45 53 3 Stable boundary layer is less well understood. 

46 53 21 the surface layer which extends up to approximately 

47 53 23 layer we're able to -- by applying similarity 

48 54 8 The convective boundary layer in its simplest 

49 54 9 form has two regimes. It's a surface layer, as I 

50 54 13 It's overlain by a mixed layer and capped -- 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 403 

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 3 Page Ref No. Keyword = "layer" 

 4 ____ _______ _________________ 

 5 

 6 54 14 the mixed layer is capped by a stable layer. 

 7 54 15 There is also a -- an entrainment layer above 

 8 54 16 the mixed layer which sort of provides a transition 

 9 54 18 And in the convective boundary layer, both 

10 54 24 boundary layer, we employ a heat budget approach to 

11 55 2 a surface -- the -- what drives the boundary layer 

12 55 3 -- the convective boundary layer is the heating 

13 55 22 the boundary layer. 

14 56 6 convective boundary layer is -- is determined by an 

15 56 8 day, so, the boundary layer grows most rapidly 

16 56 13 layer, that again, develops when the -- develops, 

17 56 17 compared to the convective boundary layer, it's 

18 56 22 in my lane(?) the convective boundary layer we kind of 

19 56 24 convective boundary layer, and we have, also, this 

20 57 12 surface layer and a wind speed at one -- at one 

21 58 6 have been talking about the boundary layer model, 

22 59 12 it's a boundary layer model. It's not clear that 

23 112 20 layer. 

24 117 8 the urban boundary layer and not have to utilize 

25 133 22 an appropriate boundary layer, you are going to be 

26 196 19 layer computations and things along that line, and 

27 233 12 similarity theory for the protected boundary layer, 

28 249 25 urban boundary layer, relative to the adjacent 

29 250 17 layer, because I can -- and I saw that the one WRF 

30 284 3 But MM5 is talking about layer one surface 

31 286 13 algorithm did not bring every vertical layer, it 

32 297 22 (38km) surface layer. 

33 306 23 technical issues, the planetary boundary layer 

34 

35 Page Ref No. Keyword = "layers" 

36 ____ _______ __________________ 

37 

38 56 4 turbulence in convective boundary layers. 

39 57 7 boundary layers, it doesn't require -- it doesn't 

40 233 22 planetary boundary layers. 

41 250 2 rural boundary layers, if you are getting -- if 

42 

43 Page Ref No. Keyword = "MAKEMET" 

44 ____ _______ ___________________ 

45 

46 72 15 There is also a MAKEMET portion to this, where 

47 73 19 stand alone MAKEMET version that you can run in a 

48 73 22 understand, and MAKEMET will support that. 

49 73 24 and you can run MAKEMET with it. And it's a more 

50 76 4 Now here for -- to drive MAKEMET, you have to 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 404 

 2 

 3 Page Ref No. Keyword = "mesoscale" 

 4 ____ _______ _____________________ 

 5 

 6 158 4 CALPUFF formally introduced, mesoscale modeling 

 7 161 3 expert understanding of mesoscale, and microscale 

 8 162 24 Mesoscale and microscale meteorology expertise 

 9 192 17 D (Section 9.3.12d) of the Guideline on Air Quality Models, it 

states that mesoscale meteorological 

10 193 14 mesoscale meteorological models is contingent upon 

11 225 17 The ETA model, it's a regional mesoscale 

12 298 10 parameters you want being spin out of the mesoscale 

13 298 25 applications that the coarse scale mesoscale models 

14 299 19 just take the coarse mesoscale meteorological 

15 300 5 the mesoscale model was able to pick up those kinds 

16 319 24 mesoscale meteorological data assimilation towards 

17 

18 Page Ref No. Keyword = "met" 

19 ____ _______ _______________ 

20 

21 9 11 the goals are being met. 

22 22 4 -- for VOC, and I'm including methane here, and -- 

23 22 6 Turns out methane is the most important, 

24 22 18 methods, which is a really useful way to do it 

25 28 22 of the future elements in terms of gridded met 

26 30 4 applications and evaluation of those methods. 

27 31 6 gridded meteorological data, including state-of-the 

28 31 7 practice, NWS meteorological analyses to improve 

29 31 20 evaluation methods to identify areas of improvement 

30 31 23 the emissions and the meteorological inputs that go 

31 38 4 The AERMET meteorological preprocessor, we 

32 38 11 bringing in the terrain data and the meteorological 

33 47 3 So I think we met our goal and did a pretty 

34 50 22 PVMRM, the ozone limiting method and the plume 

35 50 23 volume molar racial method is also included in the 

36 53 22 fifty (50) meters at most, varies, and surface 

37 54 11 meters, and this is where the similarity theory 

38 57 3 alternative method which we also use in AERMET is 

39 57 21 alternative methods were looked at and tested, 

40 58 9 from meteorological files, created -- or that were 

41 59 7 of gridded met data and certainly a need to add to 

42 59 8 this ability to take gridded met data and process 

43 59 14 job than some of the gridded met data they have on 

44 59 17 AERMET with gridded met data, taking what's good 

45 59 18 out of the gridded met data but using the 

46 67 16 meters that have caused AERMAP to crash. 

47 70 14 meteorological database. 

48 72 17 meteorological database that should cover all 

49 75 6 and applying the English and metric units. 

50 76 25 comes out in both English and metric units, and you 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 405 

 2 

 3 Page Ref No. Keyword = "met" 

 4 ____ _______ _______________ 

 5 

 6 78 13 hundred meters, you want to enter that into 

 7 78 25 seventy-five (75) meters. 

 8 86 2 And we did this for two sets of met data. 

 9 86 10 for two met data; one was Oklahoma City and one was 

10 87 5 between five and two hundred (200) meters, and you 

11 87 10 hundred (200) meters, and how their stacks have to 

12 87 14 Pittsburgh met data. 

13 87 16 other stack heights. That's thirty-five meter 

14 87 17 buoyant stack and a thirty-five meter very buoyant 

15 88 13 for stack heights, we selected four, five meters, 

16 88 14 thirty (30) meters, a hundred (100) meters and two 

17 88 15 hundred (200) meters very buoyant. 

18 89 17 the two-hundred (200) meter, very buoyant. The 

19 90 7 the short stacks of five (5) meters, very little 

20 90 22 hundred (200) meter very buoyant stacks. 

21 92 14 All right, now for the Pittsburgh met at -- in 

22 95 2 For the Pittsburgh met data, rural setting, 

23 97 12 AERMOD, again, for the Oklahoma City met data. 

24 97 16 And we did this for the Pittsburgh met set, 

25 114 2 meteorological towers are, you might have a problem 

26 114 16 we're going to match meteorological data with -- 

27 115 2 meteorology is being collected, then you are going 

28 115 5 really happening at the -- at the meteorological 

29 123 8 Use of gridded met data. I think we've 

30 129 9 screen looked like it was all metric, and then at 

31 129 17 either, you know, the American or the metric units. 

32 129 20 emissions dates, so if -- if you pick metric from 

33 129 22 metric input data. 

34 131 4 the source versus the location of the meteorology, 

35 131 6 require more meteorological data collection? 

36 132 7 meter high source, and there -- you know there are 

37 133 13 towards gridded met data, and when we do move 

38 133 14 towards gridded met data, we will be having fields 

39 139 21 tried to look at emissions, meteorology and 

40 142 9 meteorology, and the model, by its very basic 

41 158 8 gridded meteorology efforts. 

42 159 19 That was one of the proposed methods for first 

43 161 4 meteorology and finesse. 

44 162 20 In meteorology, out of that report again, they 

45 162 24 Mesoscale and microscale meteorology expertise 

46 163 4 Some met processors in their report needed a 

47 163 6 talking about some of the gridded meteorology field 

48 164 15 But it's not just meteorology; it's emissions. 

49 165 4 anymore as are meteorology, emissions, air quality 

50 174 12 meteorology, mixing height comes into play at that 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 406 

 2 

 3 Page Ref No. Keyword = "met" 

 4 ____ _______ _______________ 

 5 

 6 174 17 by changing our met inputs. 

 7 178 7 gridded meteorological data, if you are applying 

 8 180 2 micrometeorological method, and then suddenly the 

 9 188 23 is use -- the use of prognostic meteorological data 

10 190 20 methodologies, as you're aware, the -- the BART 

11 190 21 guidance recommended using method six, which, I 

12 190 24 there, the method seven, the method seven-PRIME, 

13 191 8 method. 

14 192 8 meteorological data, or you can use a hybrid 

15 192 17 D (Section 9.3.12d) of the Guideline on Air Quality Models, it 

states that mesoscale meteorological 

16 192 21 comparable meteorological observations within and 

17 193 6 meteorological data in the evaluation methods. 

18 193 7 Statistical method -- metrics and 

19 193 8 methodologies for determining the acceptability of 

20 193 14 mesoscale meteorological models is contingent upon 

21 193 22 metrics are and so what we find is that as data 

22 194 2 developed multiple years of MM5 meteorological data 

23 194 4 seen other meteorological data sets proposed for 

24 194 8 consistent set of metrics and methodologies that 

25 194 12 reviewing a new meteorological data set that's 

26 194 18 the regional, you know, meteorological and 

27 195 3 to the use of prognostic meteorological data and 

28 195 11 the use of these meteorological data sets. 

29 196 11 meteorolog- -- the gridded meteorological data for 

30 196 21 prognostic meteorological data in CALPUFF rather 

31 213 4 fairly quickly is the thing on met data, and that's 

32 216 9 observation, but it -- your methodology you 

33 216 24 I'd like to see a potential method which would 

34 217 2 up with a methodology that would better represent 

35 219 7 panel discussion on the gridded met data. 

36 219 12 afternoon will address the gridded met data, 

37 219 13 gridded meteorological data for air dispersion 

38 219 20 Meteorological data used in air dispersion 

39 219 21 modeling has expanded to include meteorological 

40 219 24 as other sources of met data. 

41 220 19 on the gridded met portion, and this was a 

42 220 24 met data and incorporating it into local scale 

43 221 3 in the regional scale arena, using gridded met 

44 221 6 a gridded met data, but we are also looking to 

45 221 14 gridded met data into AERMOD and CALPUFF; also 

46 221 15 report out on a gridded met data that work group 

47 221 24 in EPA's budget to incorporate gridded met data 

48 222 11 presentations made on gridded met data, as well. 

49 222 15 met data in CALPUFF being more visible, there was 

50 222 16 just a lot more visibility of the gridded met data, 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 407 

 2 

 3 Page Ref No. Keyword = "met" 

 4 ____ _______ _______________ 

 5 

 6 222 18 met information. 

 7 222 20 gridded met data project which I will go over that 

 8 222 24 do we want to use gridded met data? 

 9 223 9 Also, this gridded met data, because it's more 

10 223 21 product, it -- gridded met data incorporates a lot 

11 224 8 consider gridded met data, it's an advancement of 

12 224 22 can use the same meteorology to drive both types of 

13 225 11 Which gridded met data product should be used? 

14 227 4 gridded met product. 

15 227 10 of meteorology to be in the way. There is enough 

16 227 12 meteorology. 

17 227 18 input of gridded met data into local dispersion 

18 228 3 met project, its goal is to incorporate and assess 

19 228 4 gridded met data into the dispersion modeling 

20 228 20 And also, once you've run the met data of MM5 

21 229 15 incorporating the MM5 data or gridded met data into 

22 231 3 utilize gridded met data to the fullest. 

23 231 22 gridded met data project would be an IT tool 

24 231 23 basically that would accept multiple grid met 

25 232 7 met data that are needed by the recipient model. 

26 232 13 together earlier in the year a gridded met data 

27 232 25 related to gridded method data, and also at the 

28 233 4 gridded met data. 

29 233 6 additional met parameters available from gridded 

30 234 17 How would a single met source model handle met 

31 235 21 on-site met data for sources. And it's heavily 

32 235 23 terrain situations and situations where the met 

33 236 4 use gridded met data? There is a lot of issues 

34 236 10 to use your on-site met data. 

35 236 12 smaller, the issue of on-site met data may become 

36 236 16 But for now, it looks like on-site met data is 

37 236 21 meteorological data, data representativeness is at 

38 237 22 compare the gridded met data with the traditional 

39 238 16 clearly states that five (5) years of met data 

40 239 5 (36km) resolves met features from about a hundred 

41 240 11 gridded met data, maybe they're not shortcomings, 

42 240 24 gridded met data model. Typically has fewer calms, 

43 241 10 choice, where would we want the gridded met data to 

44 242 7 Gridded met data is typically very large in size, 

45 242 11 to merge the -- the met data that's used for 

46 242 18 gridded met survey that I did, only twenty of the 

47 242 21 experience do you have in gridded met data? 

48 243 7 we saw coming out of the gridded met data work 

49 243 9 community, gridded met data is not something that 

50 244 6 gridded met data started in 2002. 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 408 

 2 

 3 Page Ref No. Keyword = "met" 

 4 ____ _______ _______________ 

 5 

 6 244 10 gridded met data, and this is the URL. 

 7 246 16 You can run CALMET at, say, two hundred meter 

 8 251 14 frame, called Minimum Meteorological Requirements 

 9 255 5 the met data. Up to now, we've had ISC 

10 256 15 little education in meteorology, and back then the 

11 257 24 meters instantly, and so I know that the observing 

12 260 8 But to go to using a meteorological input 

13 260 15 And -- and to use met model data that's 

14 260 22 organizations, to take that met input and use that 

15 260 23 very same met input to drive a near-field permit 

16 261 10 met model data currently available, and -- and 

17 261 22 your met inputs. 

18 261 24 application meteorologically, for the 

19 263 6 meteorologist who's looking at how meteorology goes 

20 263 8 modeling activities for regulatory met. 

21 264 3 do this meteorologically to go in. 

22 264 19 if we can get the meteorological inputs ironed out 

23 264 22 though, is it's not just taking the met input here 

24 265 10 to model met data. There is perceived advantages, 

25 268 6 experience creating another met model. 

26 268 17 this more in terms of just the pure meteorological 

27 268 20 regulatory, meteorologically, whatever, the second 

28 272 19 Now, Dennis gave you a very methodical mental 

29 273 2 methodical steps. 

30 273 11 on a smaller scale and do the methodical stuff, we 

31 274 11 from which we extracted the met variables to 

32 277 15 wanted to do quite methodically, we ended up 

33 277 21 at the met outputs as well as the output of -- of 

34 279 21 met processor and the dispersion model output, and 

35 282 18 The two meter temperature, the well-known, 

36 284 4 pressure. This is thirty-eight (38) meters off the 

37 284 5 ground. That is thirty-eight (38) meters high, 

38 284 25 ten (10) meters, and then somewhat as a 

39 289 2 replace AERMET input with MM5, put the MM5 met data 

40 290 11 meteorology and give us some concentration values 

41 291 3 meteorology with AERMET. This scale, I know you 

42 292 13 It's the met values we are more interested in 

43 292 17 enough met discrepancies to work out. 

44 292 20 the met data, different data sets if we can do it, 

45 294 11 If I could have the gridded met panel members 

46 295 11 mostly we model use -- meteorological model output 

47 295 17 meteorological model -- modeling output as inputs 

48 299 19 just take the coarse mesoscale meteorological 

49 304 11 representative meteorological data in a large 

50 304 17 meteorological conditions? 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 409 

 2 

 3 Page Ref No. Keyword = "met" 

 4 ____ _______ _______________ 

 5 

 6 305 11 metropolitan area. 

 7 309 25 producing air quality related meteorological data 

 8 310 5 ten (10) meters were added to the observed 

 9 310 9 meteorological data. 

10 311 4 maybe three or four meters; I don't know what was 

11 311 23 series of meteorological parameters for a series of 

12 311 24 grid cells based on analyzing meteorological data 

13 312 5 areas such as complete metropolitan areas or 

14 312 18 opportunity to reconcile meteorological differences 

15 313 10 data and computing a met set for many intermediate 

16 313 20 utilize the representative meteorological 

17 316 15 more representative results than traditional met 

18 317 10 In our zeal to use better meteorology, it's 

19 318 14 meteorological modeling for regional haze and ozone 

20 319 24 mesoscale meteorological data assimilation towards 

21 320 7 meteorological products in models such as CALMET. 

22 321 23 meteorological data products that are being put 

23 322 6 And, also, are the meteorological data sets, 

24 322 8 the meteorological features of interest which are 

25 324 19 meteorological tower at the site, we had much 

26 324 22 these meteorological gridded fields with real live 

27 326 12 meteorological data. 

28 326 13 We've gone through data -- a met data 

29 330 19 met data, and do an evaluation that says, if I 

30 332 23 outright meteorological inputs, we may have a voice 

31 334 17 from the perspective of the gridded meteorology 

32 336 7 -- that's what we are. We are meteorologists. We 

33 338 9 There are in the -- in the met community that 

34 338 17 Environ has another one called Met Stat that 

35 339 18 whole as we move forward in the gridded met 

36 340 4 encouraged that when your met data comes down, also 

37 341 13 meteorology, and they are handed a program to run. 

38 343 12 probably ten percent (10%) are meteorologists, 

39 

40 Page Ref No. Keyword = "meteorological" 

41 ____ _______ __________________________ 

42 

43 31 6 gridded meteorological data, including state-of-the 

44 31 7 practice, NWS meteorological analyses to improve 

45 31 23 the emissions and the meteorological inputs that go 

46 38 4 The AERMET meteorological preprocessor, we 

47 38 11 bringing in the terrain data and the meteorological 

48 58 9 from meteorological files, created -- or that were 

49 70 14 meteorological database. 

50 72 17 meteorological database that should cover all 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 410 

 2 

 3 Page Ref No. Keyword = "meteorological" 

 4 ____ _______ __________________________ 

 5 

 6 114 2 meteorological towers are, you might have a problem 

 7 114 16 we're going to match meteorological data with -- 

 8 115 5 really happening at the -- at the meteorological 

 9 131 6 require more meteorological data collection? 

10 178 7 gridded meteorological data, if you are applying 

11 188 23 is use -- the use of prognostic meteorological data 

12 192 8 meteorological data, or you can use a hybrid 

13 192 17 D (Section 9.3.12d) of the Guideline on Air Quality Models, it 

states that mesoscale meteorological 

14 192 21 comparable meteorological observations within and 

15 193 6 meteorological data in the evaluation methods. 

16 193 14 mesoscale meteorological models is contingent upon 

17 194 2 developed multiple years of MM5 meteorological data 

18 194 4 seen other meteorological data sets proposed for 

19 194 12 reviewing a new meteorological data set that's 

20 194 18 the regional, you know, meteorological and 

21 195 3 to the use of prognostic meteorological data and 

22 195 11 the use of these meteorological data sets. 

23 196 11 meteorolog- -- the gridded meteorological data for 

24 196 21 prognostic meteorological data in CALPUFF rather 

25 219 13 gridded meteorological data for air dispersion 

26 219 20 Meteorological data used in air dispersion 

27 219 21 modeling has expanded to include meteorological 

28 236 21 meteorological data, data representativeness is at 

29 251 14 frame, called Minimum Meteorological Requirements 

30 260 8 But to go to using a meteorological input 

31 261 24 application meteorologically, for the 

32 264 3 do this meteorologically to go in. 

33 264 19 if we can get the meteorological inputs ironed out 

34 268 17 this more in terms of just the pure meteorological 

35 268 20 regulatory, meteorologically, whatever, the second 

36 295 11 mostly we model use -- meteorological model output 

37 295 17 meteorological model -- modeling output as inputs 

38 299 19 just take the coarse mesoscale meteorological 

39 304 11 representative meteorological data in a large 

40 304 17 meteorological conditions? 

41 309 25 producing air quality related meteorological data 

42 310 9 meteorological data. 

43 311 23 series of meteorological parameters for a series of 

44 311 24 grid cells based on analyzing meteorological data 

45 312 18 opportunity to reconcile meteorological differences 

46 313 20 utilize the representative meteorological 

47 318 14 meteorological modeling for regional haze and ozone 

48 319 24 mesoscale meteorological data assimilation towards 

49 320 7 meteorological products in models such as CALMET. 

50 321 23 meteorological data products that are being put 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 411 

 2 

 3 Page Ref No. Keyword = "meteorological" 

 4 ____ _______ __________________________ 

 5 

 6 322 6 And, also, are the meteorological data sets, 

 7 322 8 the meteorological features of interest which are 

 8 324 19 meteorological tower at the site, we had much 

 9 324 22 these meteorological gridded fields with real live 

10 326 12 meteorological data. 

11 332 23 outright meteorological inputs, we may have a voice 

12 

13 Page Ref No. Keyword = "meteorologically" 

14 ____ _______ ____________________________ 

15 

16 261 24 application meteorologically, for the 

17 264 3 do this meteorologically to go in. 

18 268 20 regulatory, meteorologically, whatever, the second 

19 

20 Page Ref No. Keyword = "mixing" 

21 ____ _______ __________________ 

22 

23 37 6 sources, did some things with minimum mixing 

24 53 2 mixing, and as I say, it occurs during the day. 

25 53 5 vertical mixing. 

26 53 18 mixing. 

27 54 7 other important parameter is the mixing height. 

28 56 5 And the mixing height, the growth of the 

29 56 16 height and mixing becomes very weak and is, 

30 165 18 bit as driven by mixing depth as by the winds 

31 165 20 significant in developing mixing depths and 

32 173 25 splitting changed in the mixing height. 

33 174 5 them to other dispersion models. We find mixing 

34 174 7 that the mixing height actually affects this 

35 174 12 meteorology, mixing height comes into play at that 

36 254 12 velocities and mixing heights that come out, then 

37 254 22 very similar mixing heights, very similar friction 

38 288 4 Mechanical mixing height, we kind of cut the 

39 288 6 Convective mixing height. Two things at play 

40 289 4 algorithm and see what we get for the mixing 

41 289 15 Mechanical mixing heights; we run into the 

42 289 17 again, the mechanical mixing height by shoving the 

43 289 25 And if you -- on the mixing heights, if any of 

44 290 5 There's the classes of the mechanical mixing 

45 324 10 sources, and if you have low or mechanical mixing 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 412 

 2 

 3 Page Ref No. Keyword = "MM5" 

 4 ____ _______ _______________ 

 5 

 6 133 17 We're using output from MM5 or WRF, or 

 7 164 6 in this case, MM4 or MM5 and the data blending, 

 8 164 10 trying to put MM5 into AERMET, or into AERMOD, I 

 9 168 4 I was talking with someone about getting in MM5 

10 174 11 when we look towards the MM5, or the gridded 

11 194 2 developed multiple years of MM5 meteorological data 

12 196 10 takes MM5 data and it creates -- prepares the 

13 224 4 data. And currently MM5 is the kind of model of 

14 225 25 And, also, MM5 is available at a very mini- -- 

15 226 5 And the beauty of the MM5 data, as most of you 

16 226 14 and it's slated to replace MM5 sometime in the 

17 226 21 using MM5 to drive CMAQ, CALPUFF, those types of 

18 227 5 It doesn't have to be MM5, but this is just 

19 228 6 review MM5 into CALPUFF. Currently, MM5 is 

20 228 10 We need to educate and learn how MM5 is 

21 228 15 So in doing that, you can run MM5 both at 

22 228 20 And also, once you've run the met data of MM5 

23 228 24 incorporate MM5 into AERMOD, and basically there is 

24 229 4 variables that are needed by AERMET from MM5 to 

25 229 15 incorporating the MM5 data or gridded met data into 

26 229 17 available, courtesy of MM5 to improve the actual 

27 229 23 The way we plan to do this is to process MM5 

28 230 8 we want to do that is to run AERMET using MM5 and 

29 230 13 also the grid data that was run through MM5 and run 

30 230 22 variables that are available to us from the MM5 

31 231 5 modified AERMET using MM5 and NWS and analyze those 

32 231 7 and compare it with the MM5 output versus NWS 

33 231 13 from MM5 type data versus forecast type data. And 

34 231 24 inputs, given MM5, RUC, whatever we want to, you 

35 232 16 issues there are out there in dealing with MM5 

36 233 17 available in MM5 output. 

37 233 18 There is actually a PBL height in MM5 output. 

38 233 25 a parameter that we would directly feed out of MM5. 

39 234 3 important, and I believe that's in MM5 as well. 

40 234 7 Land use category, that is also in MM5, but we 

41 234 9 because MM5 is, of course, gridded information and 

42 237 6 extensive work in MM5, and exactly what you can 

43 237 8 study showed that the spatial resolution of MM5 was 

44 237 12 capture that in MM5. It may just kind of get 

45 239 12 runs from MM5 that are made at the fourth kilometer 

46 240 23 MM5, I keep saying MM5, this could be mean any 

47 241 13 because there is MM5 type data sets all over the 

48 245 8 probably store MM5 data at sometime in the future, 

49 245 19 One is about the use of MM5 data and other 

50 245 23 fields into the -- M- -- into the MM5-model -- or 
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 6 246 5 CAL MM5 and then a database is CAL-ETA, CAL-RUC and 

 7 246 22 steps really have gone to MM5 processing it into 

 8 247 3 the use of MM5 or other prognostic filing 

 9 247 22 resolve MM5 run and see if we could diagnose down 

10 248 6 to deresolve your MM5 run or your WRF run and look 

11 248 25 If you are going to be running MM5 and you're 

12 249 22 MM5 runs and to take a -- a grid cell inside an 

13 250 13 of MM5 and an urban version of WRF, and so one may 

14 252 11 of an indication that, you know, that they use MM5 

15 258 8 So when we compare MM5 to what AERMET does, 

16 260 9 that takes -- well, let's just stay with the MM5 

17 261 6 that same MM5 field is used in both instances. 

18 261 15 somewhere post -- here's the MM5 data for 2002 that 

19 266 24 So to say that MM5 has all these algorithms 

20 267 8 modeling, like I say, MM5 here; we've used MM5 

21 267 24 for making MM5, and if we do move towards a model 

22 268 25 up your own data and creating something, this MM5 

23 270 7 earlier was, right now MM5 being fed into a 

24 270 9 and we choose MM5 because that's what ha- -- that's 

25 270 24 And we would want to go with MM5, because it 

26 272 17 simulation using the input from MM5 as a 

27 272 22 of AERMET and stick in MM5 in AERMET and rerun 

28 272 25 to -- to AERMOD with the MM5 data, and do this in 

29 273 23 course, the corresponding MM5 output for the 

30 276 5 extracted the data from MM5 that we would need for 

31 276 7 Any parameters that we could translate from MM5 to 

32 276 10 If there was an MM5 output explicitly, if MM5 

33 276 12 jumped over AERMET and used the MM5 parameter. 

34 276 16 or recreate an outdoor processor coming from MM5 to 

35 277 4 if AERMOD calculated something that MM5 provided, 

36 277 13 advantage of what we had from MM5. 

37 277 25 MM5 doesn't release -- I should point this out, 

38 278 2 we were using an existing MM5 run that had 

39 278 18 MM5 really does an explicitly output something like 

40 279 14 We -- I've played with the CAL- -- MM5-CALMET 

41 281 7 When we go into MM5 though, we -- we give up 

42 281 10 the MM5 section. I'll compare that -- that 

43 281 14 MM5, so perhaps -- let me back it up one -- the NWS 

44 281 16 MM5. 

45 282 14 going on in -- in MM5 for the same location. So 

46 282 19 well discussed, much maligned, and cold bias in MM5 

47 283 12 But as you can see, MM5, the triangles, it 

48 283 15 Surface pressure. MM5 being the triangle -- I 

49 283 18 pressure from MM5 significantly lower than what we 

50 283 21 realize what MM5 is doing versus what AERMET is 
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 6 284 3 But MM5 is talking about layer one surface 

 7 285 8 Those of you who use MM5 in a large production 

 8 285 11 spin on it, on MM5, and throw the first twelve 

 9 285 16 MM5 does not give you an hourly breakdown of 

10 286 6 them, so we should be able to convert the MM5 

11 287 4 nonexistent, nonexistent in MM5, but -- so, it's 

12 287 5 never overcast in MM5. So if you really want to 

13 287 7 always look at -- look at MM5 (chuckles from 

14 287 13 of rundowns here; sensible heat flux in MM5, higher 

15 287 17 -- the heat flux has to be greater than zero for MM5 

16 287 19 look at the convective velocity scaling in MM5, 

17 287 23 MM5 and NWS, dropping out a ton of zeroes , as 

18 287 25 the black bars, and MM5 and then the NWS AERMET 

19 288 15 in the way MM5 and AERMET are -- are wired to do 

20 288 18 NWS, and of course, MM5 much higher over here in 

21 288 22 further and look at the MM5 values and run the MM5 

22 288 25 instead of replace AERMET output with MM5, is 

23 289 2 replace AERMET input with MM5, put the MM5 met data 

24 289 10 coming out of MM5. 

25 289 18 MM5 data into AERMET's algorithm, we get this 

26 290 8 much quicker in the MM5 world for those -- for 

27 290 16 AERMET outputs and the MM5 outputs, and we've got 

28 290 20 with MM5 rolling in higher, and everywhere else 

29 291 4 can't read it, but it is identical for MM5 and for 

30 291 8 and then when we move to MM5, we're considerably 

31 291 14 and as you move to MM5 it's the same deal, only the 

32 291 22 up of the factor by which MM5 exceeds the AERMET 

33 293 16 MM5, well, give or take WRF as MM6, so some of the 

34 293 17 leaps from MM5 to WRF which is where we're going to 

35 293 21 are going to transition MM5 to WRF. 

36 296 6 NCEP data, which is MM5, is what was the purpose of 

37 296 16 why those models are run. The historic use of MM5 

38 297 20 what you're getting out of something like MM5. You 

39 299 9 it was running MM5 at a thirty-six to forty 

40 300 17 And -- I've been a MM5 user since about -- 

41 301 4 users of the MM5 data that we are talking about, I 

42 301 10 some real time MM5 or real time RUC or real time 

43 302 22 fact, they're so scale dependent in MM5 that as you 

44 303 6 MM5 field. 

45 305 2 Our experience with the use of MM5 data shows 

46 305 8 variations existed between the MM5 data for 

47 306 24 heights of MM5. PBL is computed for the 

48 306 25 fundamental relationships in MM5 while AERMOD uses 

49 307 3 MM5 generates several PBL options and you have 

50 309 11 MM5 moisture input. 
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 6 309 14 whether to use MM5 moisture all the time, or only 

 7 309 20 Now the predicted cloud cover in MM5 is very 

 8 309 24 these processes should be modeled in MM5 for 

 9 312 3 MM5, although a prognostic model, is often 

10 312 14 manageable than the MM5 output. 

11 312 15 The large volume of data from MM5 means that 

12 318 7 in the use of MM5. 

13 319 12 Washington is running the MM5 on a forecast mode, 

14 320 9 the data products have transitioned beyond MM5, and 

15 320 17 isn't MM5, and so therefore, it -- we shouldn't use 

16 320 18 it, because it's not MM5. 

17 320 21 initialization data for MM5 and make the output 

18 320 22 from MM5 look very, very similar, if not identical 

19 321 3 MM5 down over the four corners region to a one 

20 321 5 but it's an MM5 solution. 

21 324 11 heights with MM5, you will have a trapping 

22 324 14 And I've -- I've found that with another MM5 

23 328 21 you compare, say, the ISC predictions to MM5 

24 328 25 CMAQ with MM5. Took the CMAQ predictions, and 

25 329 11 that MM5 was constructing -- I thought it was 

26 331 12 kilometer MM5 data I'll bet that CALMET would have 

27 331 14 kilometer MM5 data, and it might be superior to 

28 331 15 what you saw from just the MM5 data set. 

29 333 24 protocols, told to use MM5, couldn't get the data, 

30 336 2 out and out facts of how MM5 is working all we can 

31 336 5 MARK EVANGELISTA: -- we can teach people how MM5 works. We 

32 338 2 MM5 modeling class on the road where we have went 

33 340 2 your MM5 data for you. 

34 

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38 6 9 Eighth Modeling Conference. 

39 6 24 with: health sciences, air quality modeling, 

40 8 2 modeling today that are crucial to us, and one of 

41 10 3 model and measure CO and we'll do SO2 

42 10 16 are modeling how things move through soils and 

43 11 24 monitor, you know, not with a model. And if it's 

44 16 18 this is a big, big deal in doing PM modeling at all 

45 18 23 of cities and advances in local scale modeling are 

46 20 6 Another one I find a challenge for modelers is 

47 20 23 Well, modelers -- and everybody says, oh, that 

48 20 24 will make air quality better. Well, modelers also 

49 24 8 modeling applications, integrated multi-pollutant 

50 24 9 monitoring, obviously, and modeling, and developing 
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 6 24 25 believe, is the first modeling conference that Joe 

 7 27 23 Our near-field modeling experience and 

 8 28 10 work that we do, not just for permit modeling sake, 

 9 28 24 on some general questions about model evaluation 

10 29 4 near-field modeling, air quality modeling, to 

11 29 6 Again, lead, we're the air quality modeling 

12 30 2 Air Quality Modeling Group leadership role and 

13 30 3 promote the best use of both science in modeling 

14 30 6 business. We re-energized our model clearing 

15 30 10 naming Warren as the Model Clearing House Director, 

16 31 8 the modeling science and performance for near-field 

17 31 9 modeling applications. 

18 31 19 continual development of the appropriate model 

19 31 21 in our modeling system. 

20 31 22 That means not just the model itself, but also 

21 32 2 modeling community, scientific community, 

22 32 4 model performance in critical policy and science 

23 32 17 community approach to model development and 

24 32 19 supports continual improvement in modeling science 

25 33 12 of presentations about the AERMOD modeling system 

26 34 3 be on the AERMOD modeling system. 

27 34 10 AERMOD modeling system, and that will be the first 

28 34 15 stands for the AMS/EPA regulatory model improvement 

29 35 12 was a Seventh modeling Conference where the AERMOD 

30 35 25 from the changes we made to the model, in the 

31 38 2 It's a modeling system. AERMOD really has 

32 38 6 AERMOD itself, which is the dispersion model. As 

33 38 16 other states and local modelers, but we're 

34 39 18 the most documented model that the ADC has ever put 

35 40 5 We have the model formulation document that's 

36 40 13 We have the model evaluation report where it's 

37 41 8 algorithms in here through the PRIME model. 

38 42 13 transition to the AERMOD model. 

39 42 16 require more information to drive the model, but 

40 45 9 modeling the point source, try to find something 

41 47 15 actually had Complex I, the screening model in 

42 47 25 ISC3 model. 

43 49 17 Each version of the model became better and 

44 52 9 in the model formulation document for AERMOD, you 

45 52 14 AERMET is essentially a boundary layer model, 

46 58 6 have been talking about the boundary layer model, 

47 59 11 model, and the -- and it has -- as I say, it has -- 

48 59 12 it's a boundary layer model. It's not clear that 

49 60 16 and keeping this part of the model functional and 

50 60 22 work for the Air Quality Modeling Group here at 
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 6 61 4 model computer files that contain elevations that 

 7 62 14 also to use XYZ terrain data inside the model, and 

 8 68 23 The first model that I'm going to be talking 

 9 69 5 called AERSCREEN is a screening model for AERMOD. And 

10 70 24 model. It's set up for interactive mode in a DOS 

11 71 2 model -- and I'm going to try to present two 

12 71 11 the model. In fact, Jim's actually working on that 

13 73 14 the model. 

14 73 25 sophisticated screening model, if you will. 

15 74 13 applied off the relationships from the modeling 

16 76 3 to make this model run. 

17 78 19 have the option to put that into the model. 

18 81 17 screening model. 

19 81 22 a screening model. 

20 83 7 why we want to release this model Beta test when it 

21 100 19 how well this model does, and we have spent a lot 

22 100 20 of quality time doing this, and the model actually 

23 101 19 Once we have this model in place, and we will, 

24 101 20 okay, have this model in place, the next part of 

25 101 23 model is fundamentally different than ISC, and what 

26 102 6 taking this model, using this model in a way that 

27 103 17 primarily through a function like the model 

28 104 7 a brand new model. This model, it is fundamentally 

29 105 5 And then model improvements, and then finally 

30 107 9 So, you need to start applying this model to 

31 107 18 the model in the clearing house. 

32 108 17 As we gain experience in running this model, I 

33 108 25 improve the model. 

34 109 6 the need to do some type of model development. 

35 109 15 ability to improve the model, and that is far more 

36 110 14 a model like AERMOD, I think that that would be a 

37 111 4 implementing this model, we need to think long term 

38 112 16 type of model that AERMOD is. 

39 115 24 Okay. The next is, this model, unlike ISC, 

40 117 11 AERMIC committee, when it was building this model, 

41 118 6 got your application, that you run the model in 

42 121 4 Model improvements, and I'll go through this 

43 122 24 and I realized that I was going to be modeling a 

44 124 6 modeling people, and so we're going to have to 

45 124 19 being modeled, and Gary suggested that when, you 

46 126 23 going to experience with this model. 

47 126 25 model is too complex. It's not like -- it's not 

48 129 7 model as you were presenting your screen views, it 

49 130 13 version of the model, we actually had a table which 

50 136 16 model at wind speed, or was it not so obvious that 
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 6 136 19 was affected in the model itself. 

 7 137 17 So you see -- it's directly used the model, 

 8 139 2 not included in the model evaluation paper -- 

 9 139 18 emissions inventories and air quality modeling as 

10 139 22 modeling from an uncertainty standpoint, and Joe 

11 140 8 wondering, since most modeling is performed on the 

12 140 14 AERMOD model, is that --? 

13 141 4 The model that was originally developed, the 

14 141 5 AERSURFACE model -- the AERSURFACE model, did use a 

15 141 13 might consider, like the modeling of tank farms 

16 141 22 guidance as how to model these type of things. 

17 142 5 A plume model assumes that you have horizontal 

18 142 9 meteorology, and the model, by its very basic 

19 142 10 assumptions that it's a plume model, doesn't have 

20 142 13 A puff model could do that, but it's 

21 142 15 plume model being able to deal with a checkerboard. 

22 144 6 the model. 

23 145 6 (Zo) isn't more of a suggestion of maybe a model 

24 147 25 supports us in the Air Quality Modeling Group. 

25 148 6 have for our favorite model. 

26 148 10 Warren said I'm the Chief the NOAA quality modeling 

27 148 12 Branch, now quality modeling from the NOAA Air 

28 148 22 expertise on this model at this point in time. 

29 149 5 model is, the state of where our experiences with 

30 149 23 on there and learning just what this model is all 

31 150 12 of this model. 

32 150 18 I am, by no way, an expert in this model. I 

33 151 11 got in terms of where the model is compared to 

34 153 2 parameter, or are they parts of the model that 

35 153 13 into model runs, sensitivities, evaluations, 

36 155 2 Group on Air Quality Modeling, and I guess I should 

37 156 17 best modeling techniques, or my favorite part of 

38 156 20 model even, there could be combinations of 

39 157 7 you know, we want you to do this modeling in 

40 157 16 model. 

41 157 22 We are in the eighth modeling conference; I 

42 157 23 take you all the way back to the sixth modeling 

43 158 2 -- was presented at the sixth modeling conference, 

44 158 4 CALPUFF formally introduced, mesoscale modeling 

45 159 15 in the old concentric ring model, and the BART, 

46 160 10 doing more fine modeling right out of the gate. 

47 162 13 crew of CALPUFF modelers that are out there and 

48 166 25 again, if you're doing the unique modeling 

49 168 15 experts, run the air quality model, obtain 

50 170 10 adopting the new versions of the model? You will 
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 6 171 4 model, and many of the folks on my staff have about 

 7 171 7 modelers, the state modelers, and there are folks 

 8 171 9 even know exist who are well versed in this model. 

 9 171 14 specifically, to the CALPUFF model. 

10 172 3 The Air Quality Modeling Group has, of course, 

11 172 4 been using this model for quite sometime, and in 

12 172 11 In some of the modeling exercises that we've 

13 173 4 readjusted as opposed to going in and doing a model 

14 173 11 modeling them and seeing what the numbers give us. 

15 174 15 So something this sensitive to model, we need 

16 174 20 ongoing in this -- this air quality modeling group, 

17 177 8 modeling said, I would like to use this -- the 

18 177 18 prognostic model when it goes into the wind 

19 178 12 most of the modeling was still done with either MM4 

20 179 2 do more like what happens in the grid modeling 

21 179 13 model, is it an issue with the way the model is 

22 181 5 during the BART modeling that became an issue. We 

23 182 5 in doing this modeling and very much fair game for 

24 183 2 that lead towards the model itself. Is an update 

25 183 19 grid modeling world. The model is highly 

26 184 8 And also consultation with other modelers, not 

27 184 15 interactions with the modeling world that we've 

28 185 6 this is more of a policy thing, but the modelers 

29 186 21 consultation with other modelers. 

30 186 23 modelers out here, Bret Anderson was kind enough to 

31 187 2 what the regional modelers have told me. 

32 187 3 This is one regional modeler's description of 

33 187 6 ideas from other modelers out there. 

34 187 19 modelers that've -- that have been facing a number 

35 187 22 these in the BART applications of modeling here, 

36 188 11 BART modeling protocols, and you can see the one of 

37 189 25 And since that time, the model has evolved 

38 191 14 modeling has deemed the numerical plume rise 

39 192 22 near the area that you're modeling, and so, you 

40 194 19 photochemical modelers that are very used to these 

41 196 9 for the CMAQ modeling system, which essentially it 

42 196 12 input into the photochemical model, but it also 

43 199 3 happen, parts of the model you want to look into, 

44 199 17 this model than am I at this point, and I'd like to 

45 200 14 using one model or another in the near-field is 

46 201 17 cookbook type of application model. 

47 201 23 model for a particular type of program versus 

48 203 14 entire modeling community very early in this 

49 204 5 technical aspects of this model and -- and how it 

50 206 4 modeling, and CMAQ has a frequently asked 
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 6 207 9 The management of this model by EPA is maybe 

 7 207 14 and the model developer in this case? 

 8 207 22 this model, which makes the process and the 

 9 207 25 about model development issues. 

10 208 9 hands shall you use a model", so in coming from a 

11 208 17 as the party that releases the CMAQ model, and that 

12 209 25 model, the chemistry module, -- 

13 210 12 model developer? 

14 210 22 whatever we plan to use this model for in the 

15 212 9 model. 

16 214 2 this model in one way, shape, or another. 

17 215 2 reactivating the model clearing house. 

18 215 5 reactivate the model clearing house for those types 

19 215 8 that the model clearing house is not particular to 

20 215 13 model clearing house process. 

21 215 15 technical memos for the model clearing house. 

22 215 20 Again, we're focusing on the modeling and the 

23 216 7 being made in the model. 

24 217 4 into the model. 

25 219 21 modeling has expanded to include meteorological 

26 219 22 model outputs from the National Center of the 

27 220 2 scale modeling. For local scale modeling, these 

28 220 3 model outputs can provide spatial coverage with 

29 220 21 the regional modelers workshop this year in New 

30 220 25 modeling. 

31 221 5 local scale modeling. Of course, CALPUFF now uses 

32 222 9 Fast forward to 2000, the Seventh Modeling 

33 223 13 miles from your modeling site. 

34 224 4 data. And currently MM5 is the kind of model of 

35 224 6 generally throughout the modeling community. 

36 224 18 regional scale modeling more with local scale 

37 224 19 modeling, which is something that we're really 

38 225 17 The ETA model, it's a regional mesoscale 

39 225 18 model. It's produced four times a day at a twelve 

40 225 20 The NARR model is produced every three hours 

41 226 10 available is the WRF model. It's basically in 

42 226 12 forecasting model, and it's being developed by a 

43 226 19 what's going on in the modeling world, the 

44 226 23 transport model. 

45 227 2 ISC model. 

46 228 4 gridded met data into the dispersion modeling 

47 229 22 model that way as well. 

48 232 7 met data that are needed by the recipient model. 

49 234 17 How would a single met source model handle met 

50 239 24 scale modeling, the fence line is of paramount 
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 6 240 7 light types of modeling? 

 7 240 24 gridded met data model. Typically has fewer calms, 

 8 241 7 concentrations that you get out of the model would 

 9 241 25 dispersion modeling typically, or should be public 

10 242 3 can access this data, replicate any model runs that 

11 242 14 and that's -- that's the way the modeling world is 

12 243 8 group, was education for the local modeling 

13 244 8 Operational Model Archives and Distribution System, 

14 246 18 could run a prognostic model of that resolution. 

15 248 9 for your -- for your model -- for your modeling and 

16 248 18 the model you're trying to use is a steady state 

17 248 19 model, you're only going to be able to put one 

18 249 24 see if these -- if this model is characterizing the 

19 250 9 model. 

20 252 2 into another model? 

21 252 12 data routinely for their level of modeling, but, 

22 252 24 modeling for research purposes, but which are 

23 253 5 the near-field modeling is going to converge as 

24 253 17 because it does appear that the CALPUFF-type model 

25 253 18 is going to be the model of the future. 

26 256 16 NGM model, and some of the other outputs, and MOSS 

27 260 15 And -- and to use met model data that's 

28 260 19 regulatory applications, the SIP model run that was 

29 261 3 observational data, and that regional modeling has 

30 261 4 used this model data, that -- that we feel the 

31 261 10 met model data currently available, and -- and 

32 262 7 database that is model ready, so to speak, sitting 

33 263 8 modeling activities for regulatory met. 

34 263 15 dispersion model applications that, maybe compu- -- 

35 263 24 allocations inside these model grids, and -- and 

36 264 17 or there in a forecast model. So there's -- there 

37 264 24 quality model, there will be some air quality 

38 265 10 to model met data. There is perceived advantages, 

39 265 18 model. 

40 265 20 in a model is, if you take that very same texture 

41 265 24 benefit of the model data, because we have much 

42 267 8 modeling, like I say, MM5 here; we've used MM5 

43 267 9 in regional scale modeling, and we have evaluated 

44 267 24 for making MM5, and if we do move towards a model 

45 268 6 experience creating another met model. 

46 268 11 modeling applications, now, I'm trying to stay away 

47 268 24 running your own; running your own model, digging 

48 269 15 Once you've learned to get this model data 

49 269 16 into the air quality model, whatever time it values 

50 270 8 dispersion model is the -- is a general goal here, 
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 6 270 11 model. 

 7 270 13 dispersions modeling right now. That's the ETA 

 8 270 14 model that's going into an air quality forecast run 

 9 270 19 Weather service Model Center, National Center for 

10 270 21 into an air quality model, be it a regional scale 

11 270 22 grid model, but we have it going into and being 

12 271 3 with that into a dispersion model, and then there 

13 272 16 was to conduct, basically, an air quality model 

14 279 21 met processor and the dispersion model output, and 

15 282 23 Some of the stuff we did here, the modeling 

16 284 10 into -- to a model. 

17 284 18 going to see in the model data which has gone 

18 285 12 hours out; typical modeling run, you run a spin-up 

19 286 3 model is doing and not just look for a direct 

20 293 12 And then finally the NCEP model, as we get 

21 295 9 modelers in the Division for EPA in states prior to 

22 295 10 that. As far as the overall use of the model, 

23 295 11 mostly we model use -- meteorological model output 

24 295 13 some of our regional modeling efforts that we are 

25 295 17 meteorological model -- modeling output as inputs 

26 295 24 the model was run. 

27 296 2 modeling output that he had available to him and 

28 296 7 the model that was run in the first place? 

29 297 14 Any model that's out there is built -- the 

30 297 15 builders of the model, I think, are -- in the back 

31 298 2 So if the model is built for a specific set of 

32 298 7 your -- your evolving model, and the effort we're 

33 298 11 model, but not, you know, it kind of sets the scale 

34 298 12 with your -- the other -- the air quality model was 

35 298 17 out of the Fish and Wildlife Service did model runs 

36 298 24 And what we're seeing is in some model 

37 299 12 flow was being developed. When the model was 

38 300 5 the mesoscale model was able to pick up those kinds 

39 300 21 regional scale modeling applications, CMAQ. 

40 303 11 And if -- a prognostic model field is a regional 

41 304 12 modeling domain, a regional area, how much will the 

42 304 13 use of this data change modeling results in the 

43 304 23 necessary to document the improvement in modeling 

44 305 4 even throughout the modeling domain may not 

45 305 13 available chronologically, while modelers need data 

46 305 14 for the modeling domain. Each hour of MAPS-RUC 

47 307 20 But for most modeling on industrial and 

48 308 12 modeling near ground level sources, such as waste 

49 308 21 SARA title three (III), RMP, PSM, and modeling for 

50 309 3 modeling for the odors associated with waste water 
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 6 309 21 sensitive to how a modeler chooses to simulate the 

 7 309 24 these processes should be modeled in MM5 for 

 8 310 11 modeling on-site sources, but it does not perform 

 9 310 13 modeled. 

10 310 24 up to do all of the modeling, but I mean you ran 

11 311 22 CALMET is a diagnostic model that provides a 

12 312 3 MM5, although a prognostic model, is often 

13 312 4 employed as a diagnostic model for modeling large 

14 312 12 relevant parameters for modeling on a meso- and 

15 312 24 entire modeling domain as a single grid cell. I 

16 313 17 I'm not sure a Gaussian model can be naturally 

17 314 2 really do this in a Gaussian model? 

18 314 21 It's one thing to try to model a power plant which 

19 314 23 try to model a cattle feed lot or a quarry haul 

20 316 4 And it would be useful if a modeling clearing 

21 317 24 my career as a near-field modeler, and then after 

22 318 2 regional -- or near-field modeling into regional 

23 318 3 modeling. 

24 318 13 in -- the modeling that -- that we do in 

25 318 14 meteorological modeling for regional haze and ozone 

26 319 2 is oftentimes the case when you're applying a model 

27 320 4 the, you know, for the regional modelers in New 

28 320 11 model that is being, you know, put forward to be 

29 320 16 modelers have had, and they kept saying, well, RUC 

30 321 17 modeling. 

31 322 15 looking at -- you know -- when we model five years, 

32 322 16 why are we modeling five years? 

33 323 2 modeling limited data sets for limited time 

34 325 7 site, but you can run a high speed model in real 

35 325 10 sort of semi-realm where we can link the model to 

36 326 16 Service data, how well, did the model do, and -- 

37 327 4 these databases and see how well the model performs 

38 333 17 We've been doing class one modeling studies 

39 334 15 many fine modelers. 

40 334 23 scattered people here, that are modelers, Chris 

41 335 2 GEORGE SCHEWE: -- and the modeling capabilities of some of 

42 337 4 capability of running the model. 

43 337 8 One is a general knowledge on how the modeling 

44 337 14 not -- you as near-field modelers probably -- in 

45 338 2 MM5 modeling class on the road where we have went 

46 338 4 on how to run the model, how to process the data, 

47 338 21 quality modeling group on, was taking those 

48 338 25 -- so that the regional and the local modelers can 

49 339 17 know -- the regional and the state modelers as a 

50 340 17 mystery. That takes the mystery of a gridded model 
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 6 340 19 And, also, to let you know, maybe the model is 

 7 341 7 I mean, most of the modeling in this country 

 8 341 8 is not done by regional scale modelers; it's done 

 9 341 9 by permit modelers. I mean it's being done all the 

10 343 3 years on the fundamentals of dispersion modeling, 

11 343 11 dispersion modeling, I would say that, well, the -- 

12 343 21 interested in learning about dispersion modeling. 

13 

14 Page Ref No. Keyword = "Model Clearing House" 

15 ____ _______ ________________________________ 

16 

17 30 10 naming Warren as the Model Clearing House Director, 

18 215 2 reactivating the model clearing house. 

19 215 5 reactivate the model clearing house for those types 

20 215 8 that the model clearing house is not particular to 

21 215 13 model clearing house process. 

22 215 15 technical memos for the model clearing house. 

23 

24 Page Ref No. Keyword = "model evaluation" 

25 ____ _______ ____________________________ 

26 

27 28 24 on some general questions about model evaluation 

28 40 13 We have the model evaluation report where it's 

29 139 2 not included in the model evaluation paper -- 

30 

31 Page Ref No. Keyword = "modeler" 

32 ____ _______ ___________________ 

33 

34 187 3 This is one regional modeler's description of 

35 309 21 sensitive to how a modeler chooses to simulate the 

36 317 24 my career as a near-field modeler, and then after 

37 

38 Page Ref No. Keyword = "modelers" 

39 ____ _______ ____________________ 

40 

41 20 6 Another one I find a challenge for modelers is 

42 20 23 Well, modelers -- and everybody says, oh, that 

43 20 24 will make air quality better. Well, modelers also 

44 38 16 other states and local modelers, but we're 

45 162 13 crew of CALPUFF modelers that are out there and 

46 171 7 modelers, the state modelers, and there are folks 

47 184 8 And also consultation with other modelers, not 

48 185 6 this is more of a policy thing, but the modelers 

49 186 21 consultation with other modelers. 

50 186 23 modelers out here, Bret Anderson was kind enough to 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 425 

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 3 Page Ref No. Keyword = "modelers" 

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 5 

 6 187 2 what the regional modelers have told me. 

 7 187 6 ideas from other modelers out there. 

 8 187 19 modelers that've -- that have been facing a number 

 9 194 19 photochemical modelers that are very used to these 

10 220 21 the regional modelers workshop this year in New 

11 295 9 modelers in the Division for EPA in states prior to 

12 305 13 available chronologically, while modelers need data 

13 320 4 the, you know, for the regional modelers in New 

14 320 16 modelers have had, and they kept saying, well, RUC 

15 334 15 many fine modelers. 

16 334 23 scattered people here, that are modelers, Chris 

17 337 14 not -- you as near-field modelers probably -- in 

18 338 25 -- so that the regional and the local modelers can 

19 339 17 know -- the regional and the state modelers as a 

20 341 8 is not done by regional scale modelers; it's done 

21 341 9 by permit modelers. I mean it's being done all the 

22 

23 Page Ref No. Keyword = "modeling" 

24 ____ _______ ____________________ 

25 

26 6 9 Eighth Modeling Conference. 

27 6 24 with: health sciences, air quality modeling, 

28 8 2 modeling today that are crucial to us, and one of 

29 10 16 are modeling how things move through soils and 

30 16 18 this is a big, big deal in doing PM modeling at all 

31 18 23 of cities and advances in local scale modeling are 

32 24 8 modeling applications, integrated multi-pollutant 

33 24 9 monitoring, obviously, and modeling, and developing 

34 24 25 believe, is the first modeling conference that Joe 

35 27 23 Our near-field modeling experience and 

36 28 10 work that we do, not just for permit modeling sake, 

37 29 4 near-field modeling, air quality modeling, to 

38 29 6 Again, lead, we're the air quality modeling 

39 30 2 Air Quality Modeling Group leadership role and 

40 30 3 promote the best use of both science in modeling 

41 31 8 the modeling science and performance for near-field 

42 31 9 modeling applications. 

43 31 21 in our modeling system. 

44 32 2 modeling community, scientific community, 

45 32 19 supports continual improvement in modeling science 

46 33 12 of presentations about the AERMOD modeling system 

47 34 3 be on the AERMOD modeling system. 

48 34 10 AERMOD modeling system, and that will be the first 

49 35 12 was a Seventh modeling Conference where the AERMOD 

50 38 2 It's a modeling system. AERMOD really has 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 426 

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 3 Page Ref No. Keyword = "modeling" 

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 5 

 6 45 9 modeling the point source, try to find something 

 7 60 22 work for the Air Quality Modeling Group here at 

 8 74 13 applied off the relationships from the modeling 

 9 122 24 and I realized that I was going to be modeling a 

10 124 6 modeling people, and so we're going to have to 

11 139 18 emissions inventories and air quality modeling as 

12 139 22 modeling from an uncertainty standpoint, and Joe 

13 140 8 wondering, since most modeling is performed on the 

14 141 13 might consider, like the modeling of tank farms 

15 147 25 supports us in the Air Quality Modeling Group. 

16 148 10 Warren said I'm the Chief the NOAA quality modeling 

17 148 12 Branch, now quality modeling from the NOAA Air 

18 155 2 Group on Air Quality Modeling, and I guess I should 

19 156 17 best modeling techniques, or my favorite part of 

20 157 7 you know, we want you to do this modeling in 

21 157 22 We are in the eighth modeling conference; I 

22 157 23 take you all the way back to the sixth modeling 

23 158 2 -- was presented at the sixth modeling conference, 

24 158 4 CALPUFF formally introduced, mesoscale modeling 

25 160 10 doing more fine modeling right out of the gate. 

26 166 25 again, if you're doing the unique modeling 

27 172 3 The Air Quality Modeling Group has, of course, 

28 172 11 In some of the modeling exercises that we've 

29 173 11 modeling them and seeing what the numbers give us. 

30 174 20 ongoing in this -- this air quality modeling group, 

31 177 8 modeling said, I would like to use this -- the 

32 178 12 most of the modeling was still done with either MM4 

33 179 2 do more like what happens in the grid modeling 

34 181 5 during the BART modeling that became an issue. We 

35 182 5 in doing this modeling and very much fair game for 

36 183 19 grid modeling world. The model is highly 

37 184 15 interactions with the modeling world that we've 

38 187 22 these in the BART applications of modeling here, 

39 188 11 BART modeling protocols, and you can see the one of 

40 191 14 modeling has deemed the numerical plume rise 

41 192 22 near the area that you're modeling, and so, you 

42 196 9 for the CMAQ modeling system, which essentially it 

43 203 14 entire modeling community very early in this 

44 206 4 modeling, and CMAQ has a frequently asked 

45 215 20 Again, we're focusing on the modeling and the 

46 219 21 modeling has expanded to include meteorological 

47 220 2 scale modeling. For local scale modeling, these 

48 220 25 modeling. 

49 221 5 local scale modeling. Of course, CALPUFF now uses 

50 222 9 Fast forward to 2000, the Seventh Modeling 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 427 

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 3 Page Ref No. Keyword = "modeling" 

 4 ____ _______ ____________________ 

 5 

 6 223 13 miles from your modeling site. 

 7 224 6 generally throughout the modeling community. 

 8 224 16 modeling tools into our air dispersion models, and 

 9 224 18 regional scale modeling more with local scale 

10 224 19 modeling, which is something that we're really 

11 226 19 what's going on in the modeling world, the 

12 228 4 gridded met data into the dispersion modeling 

13 239 24 scale modeling, the fence line is of paramount 

14 240 7 light types of modeling? 

15 241 25 dispersion modeling typically, or should be public 

16 242 14 and that's -- that's the way the modeling world is 

17 243 8 group, was education for the local modeling 

18 248 9 for your -- for your model -- for your modeling and 

19 252 12 data routinely for their level of modeling, but, 

20 252 24 modeling for research purposes, but which are 

21 253 5 the near-field modeling is going to converge as 

22 261 3 observational data, and that regional modeling has 

23 263 8 modeling activities for regulatory met. 

24 267 8 modeling, like I say, MM5 here; we've used MM5 

25 267 9 in regional scale modeling, and we have evaluated 

26 268 11 modeling applications, now, I'm trying to stay away 

27 270 13 dispersions modeling right now. That's the ETA 

28 282 23 Some of the stuff we did here, the modeling 

29 285 12 hours out; typical modeling run, you run a spin-up 

30 295 13 some of our regional modeling efforts that we are 

31 295 17 meteorological model -- modeling output as inputs 

32 296 2 modeling output that he had available to him and 

33 300 21 regional scale modeling applications, CMAQ. 

34 304 12 modeling domain, a regional area, how much will the 

35 304 13 use of this data change modeling results in the 

36 304 23 necessary to document the improvement in modeling 

37 305 4 even throughout the modeling domain may not 

38 305 14 for the modeling domain. Each hour of MAPS-RUC 

39 307 20 But for most modeling on industrial and 

40 308 12 modeling near ground level sources, such as waste 

41 308 21 SARA title three (III), RMP, PSM, and modeling for 

42 309 3 modeling for the odors associated with waste water 

43 310 11 modeling on-site sources, but it does not perform 

44 310 24 up to do all of the modeling, but I mean you ran 

45 312 4 employed as a diagnostic model for modeling large 

46 312 12 relevant parameters for modeling on a meso- and 

47 312 24 entire modeling domain as a single grid cell. I 

48 316 4 And it would be useful if a modeling clearing 

49 318 2 regional -- or near-field modeling into regional 

50 318 3 modeling. 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 428 

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 3 Page Ref No. Keyword = "modeling" 

 4 ____ _______ ____________________ 

 5 

 6 318 13 in -- the modeling that -- that we do in 

 7 318 14 meteorological modeling for regional haze and ozone 

 8 321 17 modeling. 

 9 322 16 why are we modeling five years? 

10 323 2 modeling limited data sets for limited time 

11 333 17 We've been doing class one modeling studies 

12 335 2 GEORGE SCHEWE: -- and the modeling capabilities of some of 

13 337 8 One is a general knowledge on how the modeling 

14 338 2 MM5 modeling class on the road where we have went 

15 338 21 quality modeling group on, was taking those 

16 341 7 I mean, most of the modeling in this country 

17 343 3 years on the fundamentals of dispersion modeling, 

18 343 11 dispersion modeling, I would say that, well, the -- 

19 343 21 interested in learning about dispersion modeling. 

20 

21 Page Ref No. Keyword = "Monin-Obukov" 

22 ____ _______ ________________________ 

23 

24 341 25 You've got to bring in the Monin-Obukov links 

25 

26 Page Ref No. Keyword = "monitor" 

27 ____ _______ ___________________ 

28 

29 11 24 monitor, you know, not with a model. And if it's 

30 24 9 monitoring, obviously, and modeling, and developing 

31 24 23 leader for the air quality monitoring group for 

32 148 14 EPA's Emissions Monitoring Analysis Division to -- 

33 273 17 (51,000) sources and one monitor, I believe, worked 

34 292 22 averages and a very scanty monitoring of the 

35 295 6 the Research and Monitoring Branch of the National 

36 

37 Page Ref No. Keyword = "monitors" 

38 ____ _______ ____________________ 

39 

40 125 9 at, you know, long roof monitors that are buoyant, 

41 273 18 -- there were two monitors, twice as many monitors 

42 327 13 at particulate monitors. It's very different than 

43 

44 Page Ref No. Keyword = "NCDC" 

45 ____ _______ ________________ 

46 

47 58 10 once available from the NCDC. There is a QA and a 

48 221 19 on a trip over to NCDC. 

49 244 5 NCEP products. Of course, the NCDC archives 

50 244 17 NCDC, WRF will be stored by NCDC around April of 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 429 

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 3 Page Ref No. Keyword = "ncdc" 

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 5 

 6 306 4 And I think you mentioned NCDC, Dennis, just 

 7 315 19 of NCDC or a similar body to archive the data. I 

 8 330 8 definition from NCDC or -- or from the web -- in 

 9 

10 Page Ref No. Keyword = "near-field" 

11 ____ _______ ______________________ 

12 

13 27 23 Our near-field modeling experience and 

14 29 4 near-field modeling, air quality modeling, to 

15 31 8 the modeling science and performance for near-field 

16 132 25 near-field impacts, and you want to use wind -- if 

17 145 13 near-field, the low stacks. My concern is that 

18 194 20 evaluation techniques, and we have the near-field 

19 195 2 near-field people, who have very limited exposure 

20 200 14 using one model or another in the near-field is 

21 253 5 the near-field modeling is going to converge as 

22 260 23 very same met input to drive a near-field permit 

23 261 20 near-field application would then download a tool, 

24 263 20 time, and then you have this near-field. 

25 304 14 near-field domain, typically within fifty 

26 317 24 my career as a near-field modeler, and then after 

27 318 2 regional -- or near-field modeling into regional 

28 330 20 redefined the definition of near-field and applied 

29 331 3 evaluated, and if you redefine that near-field and 

30 337 14 not -- you as near-field modelers probably -- in 

31 

32 Page Ref No. Keyword = "No Obs" 

33 ____ _______ __________________ 

34 

35 176 23 things, and the first one is No Obs which was, of 

36 188 12 the most important ones is the use of the No Obs, 

37 188 21 have proposed the use of No Obs, versus, you know, 

38 192 3 the No Obs is essentially when you're -- you have 

39 192 13 could use No Obs where you're using the prognostic 

40 

41 Page Ref No. Keyword = "NOAA" 

42 ____ _______ ________________ 

43 

44 8 19 at EPA's NOAA conferences, but some of this is from 

45 22 16 and faster computational models working with NOAA, 

46 147 24 who is the branch chief for the NOAA part that 

47 148 10 Warren said I'm the Chief the NOAA quality modeling 

48 148 12 Branch, now quality modeling from the NOAA Air 

49 155 9 At the time NOAA -- well, most of the NOAA 

50 155 11 nonetheless NOAA did provide technical expertise, 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 430 

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 3 Page Ref No. Keyword = "noaa" 

 4 ____ _______ ________________ 

 5 

 6 158 6 the NOAA hearts, and we will talk about that in a 

 7 207 18 NOAA guy -- 

 8 220 13 with NOAA and Mark Evangelista, and he'll be 

 9 221 18 developments at NOAA that I discovered when I went 

10 224 2 Also, the data is typically NOAA approved as 

11 243 25 workshop in Asheville on NOAA data, sponsored by 

12 244 7 They also had a web area called NOMADS, NOAA 

13 297 5 and blessed by the -- by NOAA, and the data is 

14 310 7 is a -- something for NOAA to consider. 

15 325 6 if anyone that has ever gone to the NOAA ready web 

16 325 20 I think NOAA should look into that -- EPA and 

17 325 21 NOAA should look into a collaborative with Roland 

18 325 25 ROBERT PAINE: Well, it's NOAA -- put it in Google. NOAA and 

19 332 9 is a WRF chem, and in the NOAA mission, air quality 

20 332 17 quality, then it is in NOAA's interest, it is in 

21 332 18 NOAA's mission, to somehow consider that as they 

22 

23 Page Ref No. Keyword = "NWS" 

24 ____ _______ _______________ 

25 

26 31 7 practice, NWS meteorological analyses to improve 

27 220 15 advantages, and the issues in using the NWS 

28 221 7 using it in AERMOD and more contemporary NWS-type 

29 223 11 representative than the distant NWS sites that are 

30 226 24 The local scale models use NWS or on-site. 

31 228 17 NWS data through CALMET and analyze the results, 

32 228 21 and NWS through CALMET, you want to use that, and 

33 229 24 for a single grid cell, and also for NWS data and 

34 230 9 NWS data and analyze the results, and this would be 

35 230 12 information at a point that contains NWS data and 

36 231 5 modified AERMET using MM5 and NWS and analyze those 

37 231 7 and compare it with the MM5 output versus NWS 

38 237 4 NWS type data. 

39 239 25 importance, and so, you know, should we use NWS 

40 259 8 approach is clearly to take NWS observation data 

41 261 2 we don't believe occurs when we use the NWS 

42 268 4 handful of others creating AERMET, we have the NWS, 

43 272 18 replacement for the NWS observations. 

44 274 7 Airport, the site of the NWS observation. 

45 280 23 This is climate; this is the NWS statement, 

46 281 5 NWS data, at least directionally, fairly 

47 281 14 MM5, so perhaps -- let me back it up one -- the NWS 

48 281 15 data that -- that was -- that's the NWS and here's 

49 281 20 the NWS data. 

50 283 8 The hourly averages are for the NWS through 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 431 

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 3 Page Ref No. Keyword = "nws" 

 4 ____ _______ _______________ 

 5 

 6 283 19 have in the NWS data run through AERMET. 

 7 287 23 MM5 and NWS, dropping out a ton of zeroes , as 

 8 287 25 the black bars, and MM5 and then the NWS AERMET 

 9 288 18 NWS, and of course, MM5 much higher over here in 

10 291 2 annual average concentration map for using the NWS 

11 305 25 stored for about twelve (12) hours by NWS. One 

12 329 15 very similar answers when I was taking one NWS 

13 331 23 said earlier about what the NWS products were 

14 

15 Page Ref No. Keyword = "OAQPS" 

16 ____ _______ _________________ 

17 

18 6 17 We have John Bachmann who is the OAQPS 

19 26 6 cleared it through OAQPS, and it went up to DC. 

20 112 3 There are EPA reports. There are OAQPS policy 

21 227 14 spring OAQPS, Office of Air Quality Planning and 

22 

23 Page Ref No. Keyword = "observation" 

24 ____ _______ _______________________ 

25 

26 128 15 Observation, still in DOS. 

27 167 23 simulation as opposed to using observational data, 

28 178 13 or mostly with observational data being processed 

29 216 8 And this is just my observation, one person's 

30 216 9 observation, but it -- your methodology you 

31 259 8 approach is clearly to take NWS observation data 

32 259 19 stick all these observational data, and if we need 

33 260 7 use that truth observation. 

34 261 3 observational data, and that regional modeling has 

35 265 13 observational data, there's not a lot of terrain in 

36 266 22 an observation gives you in the first place, which 

37 272 21 First, we wanted to pull the observation out 

38 274 7 Airport, the site of the NWS observation. 

39 276 3 Then AERMET and AERMOD using the observation data 

40 276 6 that grid cell to replace the observational data. 

41 284 16 reflective a little more in the observational data 

42 286 16 The observation data, even though it's an ASOS 

43 

44 Page Ref No. Keyword = "observations" 

45 ____ _______ ________________________ 

46 

47 159 25 observations of applications that we've done in my 

48 192 12 surface data for your observations, and then you 

49 192 21 comparable meteorological observations within and 

50 193 18 statistical comparisons with observations of winds 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 432 

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 3 Page Ref No. Keyword = "observations" 

 4 ____ _______ ________________________ 

 5 

 6 240 18 probably with actual observations when you use it 

 7 256 20 observations and verify them, and I was always 

 8 256 21 shocked at how frequently the observations were 

 9 257 11 learn that the observations are actually reality, 

10 257 16 So, when -- and trust me -- and observations 

11 258 11 way begins with some observations, some are, and 

12 272 18 replacement for the NWS observations. 

13 273 24 observations were there, it was existing, it was on 

14 275 25 old fashioned way, and use the observations and get 

15 302 9 observation, and observations are rarely dense 

16 303 13 than observations in doing regional field 

17 305 5 necessarily be superior to observations made in 

18 322 3 compare them against historical observations that 

19 

20 Page Ref No. Keyword = "observed" 

21 ____ _______ ____________________ 

22 

23 258 5 the observed data, and it's -- it's when we begin 

24 305 10 observed data. This was the Dallas-Fort Worth 

25 310 5 ten (10) meters were added to the observed 

26 

27 Page Ref No. Keyword = "ozone" 

28 ____ _______ _________________ 

29 

30 10 4 and we'll do PM and ozone. 

31 15 4 more VOC emissions and more ozone and maybe more 

32 17 4 Ozone itself, we now have more data that's 

33 17 6 published that ozone in fact also contributes to 

34 17 10 with ozone. 

35 17 11 So there is more growing evidence that ozone 

36 17 15 under the current ozone and (projecting map) PM 

37 17 18 either PM only or ozone only. 

38 18 2 plenty of places where -- with persistent ozone 

39 19 7 We're going to worry about not just ozone and 

40 19 18 for ozone and PM and to the fact that some of these 

41 22 10 international transport of ozone which is important 

42 22 11 for meeting the standard as the ozone standard has 

43 22 13 ozone happens to be a green house risk. 

44 50 22 PVMRM, the ozone limiting method and the plume 

45 214 5 background ozone, those kinds of value settings and 

46 318 14 meteorological modeling for regional haze and ozone 

47 327 11 ozone SIP, it's a very different question. You're 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 433 

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 3 Page Ref No. Keyword = "parameter" 

 4 ____ _______ _____________________ 

 5 

 6 54 7 other important parameter is the mixing height. 

 7 73 9 this control file and just modify the parameter or 

 8 76 12 parameter in the AERMOD. 

 9 115 19 more regional type parameter. I think what the 

10 136 18 KAREN WESSON: Yeah, we didn't analyze exactly what parameter 

11 136 24 I think that would tell us as far as what parameter 

12 153 2 parameter, or are they parts of the model that 

13 153 8 If something is a parameter, it might be very 

14 153 10 parameter settings lie and then what changes there 

15 166 5 And each and every parameter that we'll list 

16 177 16 The bias parameter, the wind calculation, 

17 181 2 Also, there's again parameter settings that 

18 205 2 parameter you should think about changing it this 

19 205 9 parameter. 

20 229 12 and that kind of thing, parameterized. 

21 233 25 a parameter that we would directly feed out of MM5. 

22 248 20 particular, you know, parameter in there. 

23 254 19 parameterizations that are now currently in AERMET 

24 275 5 just -- we pulled off one parameter and just boxed 

25 276 11 output a parameter that AERMET output, we just 

26 276 12 jumped over AERMET and used the MM5 parameter. 

27 296 20 in the air parameterizations. 

28 

29 Page Ref No. Keyword = "parameters" 

30 ____ _______ ______________________ 

31 

32 42 20 the impacts of those parameters as you do your 

33 53 24 theory, we can estimate scaling parameters that are 

34 54 2 parameters. Some of the scaling parameters, these 

35 56 3 parameters that are needed to characterize 

36 58 14 file, which contains the scaling parameters that 

37 58 16 parameters. 

38 75 22 Those will all be parameters that you would 

39 79 19 parameters in here. 

40 114 19 eloquently, that we've got three parameters, one of 

41 115 21 there is a difference between these parameters and 

42 118 24 get around that sort of a WRF parameters. 

43 132 19 albedo are really more regional type parameters, 

44 136 13 surface parameters. 

45 136 15 parameters influenced a particular parameter in the 

46 136 17 any particular parameters would be in effect? 

47 181 22 combinations of parameters. 

48 181 24 segment, combinations of recommended parameters, so 

49 220 4 additional parameters for locations which are not 

50 223 15 parameters that are calculated, and they provide a 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 434 

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 3 Page Ref No. Keyword = "parameters" 

 4 ____ _______ ______________________ 

 5 

 6 223 18 a lot of physics parameters that are needed to 

 7 232 9 host of surface parameters, whatever fields need to 

 8 233 6 additional met parameters available from gridded 

 9 238 8 actual measured parameters, but we want to note 

10 246 2 and calculations of evaluated parameters and other 

11 247 4 parameters. 

12 247 8 CALMET on certain bundling parameters. 

13 247 11 better in -- in developing the bundling parameters 

14 276 7 Any parameters that we could translate from MM5 to 

15 298 10 parameters you want being spin out of the mesoscale 

16 310 6 parameters throughout the ASOS network. And this 

17 311 23 series of meteorological parameters for a series of 

18 312 12 relevant parameters for modeling on a meso- and 

19 325 14 at least, put in your emission parameters, and it 

20 332 16 parameters or anything that would benefit air 

21 

22 Page Ref No. Keyword = "PBL" 

23 ____ _______ _______________ 

24 

25 233 18 There is actually a PBL height in MM5 output. 

26 233 20 generate the PBL, but that's something else that 

27 306 24 heights of MM5. PBL is computed for the 

28 307 3 MM5 generates several PBL options and you have 

29 307 7 hourly PBL of modest dimension can create a very 

30 307 17 In general, however, PBL is important only 

31 307 24 limited interaction with the PBL particularly under 

32 319 19 producing accurate PBL estimates and things along 

33 342 13 a transition from the PG world to the PBL world, 

34 

35 Page Ref No. Keyword = "PBLs" 

36 ____ _______ ________________ 

37 

38 336 6 can teach people how PBLs are calculated. That's 

39 

40 Page Ref No. Keyword = "plume" 

41 ____ _______ _________________ 

42 

43 37 19 plume rise in the PRIME algorithms, and we found 

44 50 22 PVMRM, the ozone limiting method and the plume 

45 58 19 determines the height of the plume and then it goes 

46 118 14 trivial as it was for ISC, because the plume rise 

47 118 16 situation, are numerical -- it's a numerical plume 

48 118 22 equations and then the plume rise has a problem. 

49 142 5 A plume model assumes that you have horizontal 

50 142 10 assumptions that it's a plume model, doesn't have 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 435 

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 3 Page Ref No. Keyword = "plume" 

 4 ____ _______ _________________ 

 5 

 6 142 15 plume model being able to deal with a checkerboard. 

 7 179 8 Plume height calculations, again, puff 

 8 191 14 modeling has deemed the numerical plume rise 

 9 307 18 when there are stacks of significant plume rise, 

10 313 13 Straight line plume models, such as AERMOD, 

11 313 16 plume models are much less effective. 

12 313 22 the plume dispersion and movement. 

13 313 23 Ideally, the plume should be allowed to 

14 314 22 has a extraordinarily buoyant plume, but another to 

15 328 12 plume, you're -- you're going to get some very high 

16 

17 Page Ref No. Keyword = "precedents" 

18 ____ _______ ______________________ 

19 

20 108 18 think it's then when the precedents get developed 

21 110 21 want to be able to -- to try to avoid precedents 

22 111 5 as to what these precedents might mean. 

23 111 6 Because precedents probably have more standing 

24 112 6 precedents that the lawyers in the group will go -- 

25 

26 Page Ref No. Keyword = "PRIME" 

27 ____ _______ _________________ 

28 

29 36 8 package, as we've mentioned. We've added PRIME. 

30 36 10 about putting PRIME into AERMOD. At the proposal 

31 36 14 And so we listened, we now have PRIME into 

32 36 16 PRIME, we actually have the performance evaluation 

33 36 17 looking even better in AERMOD, PRIME and ISC PRIME, 

34 37 19 plume rise in the PRIME algorithms, and we found 

35 41 8 algorithms in here through the PRIME model. 

36 42 22 The PRIME building downwash algorithms require 

37 46 13 brought PRIME into AERMOD, the goal was to make it, 

38 46 14 so that PRIME performs very similarly to the 

39 46 15 ISC-PRIME models. We knew when we brought PRIME 

40 72 8 We have in there the PRIME building downwash 

41 118 15 algorithms in PRIME, if you're in downwash 

42 135 10 WARREN PETERS: Right. When we put PRIME into AERMOD, 

43 135 13 concentrations from AERMOD PRIME versus ISC-PRIME 

44 135 17 of PRIME into AERMOD, because it's almost 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 436 

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 3 Page Ref No. Keyword = "processor" 

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 6 196 8 and for those who not familiar, MSIP is a processor 

 7 245 22 CALMET as the processor to get from the prognostic 

 8 255 4 tool is about is to have one -- one processor for 

 9 262 6 through the same processor and create a National 

10 276 16 or recreate an outdoor processor coming from MM5 to 

11 277 7 processor and we don't hurt anything, let's take 

12 279 21 met processor and the dispersion model output, and 

13 

14 Page Ref No. Keyword = "processors" 

15 ____ _______ ______________________ 

16 

17 153 4 Are they components, are they processors or 

18 163 4 Some met processors in their report needed a 

19 164 21 scenarios simultaneously on parallel processors, on 

20 254 21 the -- the two processors would start to generate 

21 255 6 processors, AERMOD processors, and there's CALPUFF 

22 255 7 processors. 

23 293 10 processors out there that are doing this already, 

24 

25 Page Ref No. Keyword = "profile" 

26 ____ _______ ___________________ 

27 

28 58 17 The profile -- there's a vertical profile, 

29 58 20 to the profile to get the lateral and vertical 

30 249 10 ran WRF and they constructed a WRF profile for 

31 266 15 profilers to give us more information. 

32 278 25 a moisture profile, why don't we stick the whole 

33 

34 Page Ref No. Keyword = "promulgated" 

35 ____ _______ _______________________ 

36 

37 25 25 promulgated as it ever has been. 

38 33 13 that will be soon promulgated. 

39 100 23 are just about ready to get this thing promulgated. 

40 107 6 But, when -- when it's promulgated we will 

41 158 23 It was promulgated for certain applications, 

42 179 23 promulgated, (pause), I'll just stop there for 

43 179 25 promulgated, we will go to the AERMOD 

44 214 21 As we know, CALPUFF has been promulgated prior 

45 253 11 promulgated, and ISC had a pretty long shelf life. 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 437 

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 3 Page Ref No. Keyword = "promulgation" 

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 5 

 6 36 5 now we'll have it the promulgation of Version 

 7 105 18 back that during the first year of promulgation, 

 8 106 13 an implementation guide with the promulgation. 

 9 121 8 can stand up here and say that at promulgation or 

10 189 10 Land Manages was that upon promulgation of AERMOD 

11 214 22 to the imminent promulgation here of the AERMOD, 

12 

13 Page Ref No. Keyword = "protocol" 

14 ____ _______ ____________________ 

15 

16 167 12 have a protocol stamped or approved, it is to get 

17 202 13 protocol, template. 

18 209 4 a protocol. 

19 209 7 to get guidance from the EPA through a protocol 

20 209 14 process of submitting a protocol is; submit it and 

21 335 21 can't re- -- even review your protocol; what do we 

22 

23 Page Ref No. Keyword = "protocols" 

24 ____ _______ _____________________ 

25 

26 167 8 Now we see that with the protocols for those 

27 167 10 that in a number of requests for protocols with 

28 183 14 apply expert judgment and submit protocols. 

29 188 11 BART modeling protocols, and you can see the one of 

30 188 20 protocols that we have seen put forward to date 

31 197 20 there are BART protocols that are moving forward 

32 215 11 that these protocols or issues that come up with 

33 215 12 respect to these protocols be vented through the 

34 333 19 ago, difficulty in getting protocols approved, 

35 333 24 protocols, told to use MM5, couldn't get the data, 

36 

37 Page Ref No. Keyword = "PSD" 

38 ____ _______ _______________ 

39 

40 110 2 PSD or the new source review; regulations demand 

41 

42 Page Ref No. Keyword = "puff" 

43 ____ _______ ________________ 

44 

45 142 13 A puff model could do that, but it's 

46 173 16 Puff coherency; what happens can a -- when a 

47 173 17 puff gets so big that it just goes -- goes beyond 

48 173 20 puff splitting became an issue. 

49 179 8 Plume height calculations, again, puff 

50 190 3 using puff splitting to maybe -- you know -- make 
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 6 190 15 horizontal and vertical puff splitting, is that 

 7 295 18 to the various regional scaling models, the puff 

 8 

 9 Page Ref No. Keyword = "ratio" 

10 ____ _______ _________________ 

11 

12 11 20 is rational, equitable, and cost effective. 

13 42 18 ratio when there's surface roughness. 

14 43 20 An average ratio -- now, this is a table of 

15 44 25 ratio for the mod- -- AERMOD and ISC is about as 

16 55 18 And in the AERMET, we use a Bowen ratio, it's the 

17 55 19 ratio relating to sensible heat flux to -- to get 

18 80 10 on is probably the minimum ratio. 

19 80 11 This is, again, a ratio of AERSCREEN to AERMOD 

20 80 16 had seven sources, his minimum ratio is one point 0 

21 80 23 situations here, our low -- lowest ratio was point 

22 82 23 And then the max ratio, which is, again, the 

23 83 25 ratio, and the surface roughness. 

24 84 11 ratio. 

25 85 8 albedo, a Bowen ratio, and a surface roughness. 

26 85 11 Bowen ratio and surface roughness. 

27 85 24 varied the albedo, the Bowen ratio, the surface 

28 86 15 this, we held the Bowen ratio and the surface 

29 86 18 For the Bowen ratio, we varied from zero point 

30 86 25 albedo and the Bowen ratio constant at point two 

31 87 21 one (.1) to zero point six (0.6) on the Bowen ratio 

32 90 23 Okay, now -- and now for the Bowen ratio. 

33 90 24 The Bowen ratio is going to vary between point 

34 91 12 X factors of time has the Bowen ratio, Bowen 

35 91 13 ratio varying between zero point one (0.1) and ten 

36 91 18 ratio. 

37 91 20 concentration. Here the Bowen ratio -- we started 

38 91 21 -- we compared it against the Bowen ratio, with the 

39 91 23 that point, and then increasing the Bowen ratio to 

40 92 3 ratio equals a hundred (100). 

41 92 9 for the Bowen ratio, numerically we look at these, 

42 92 13 Bowen ratio line. 

43 92 16 the Bowen ratio value going from zero point one 

44 93 5 at the early stages of changing the Bowen ratio. 

45 93 13 (0.2); Bowen ratio held constant at one point zero 

46 95 23 albedo and the Bowen ratio, but we definitely see a 

47 96 4 ratio values. 

48 96 13 albedo and Bowen ratio values. 

49 96 14 The Bowen ratio values were selected for 

50 98 8 Bowen ratio. 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 439 

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 3 Page Ref No. Keyword = "ratio" 

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 6 99 21 ratio value that would be chosen. 

 7 113 5 characteristics, like Bowen ratio, albedo and 

 8 115 16 With the Bowen ratio and with the albedo, it's 

 9 125 14 sensitivity of Bowen ratio, and that is that, you 

10 125 15 know, we get Bowen ratio now into AERMOD purely by 

11 125 20 and -- and tried to deal with the Bowen ratio that 

12 131 17 produce, not just, not just rational or realistic 

13 132 18 because the Bowen ratio and the -- and the 

14 142 12 changes in Z naught (Zo) and Bowen ratio. 

15 142 24 value for the Bowen ratio, Z naught (Zo) and 

16 181 12 ratio, the weighted averages. You may be able to 

17 238 10 those in a rational way, and in a way that we 

18 314 18 land/sea interfaces, and the ratio of terrain to 

19 

20 Page Ref No. Keyword = "ratios" 

21 ____ _______ __________________ 

22 

23 43 21 ratios. This is the AERMOD concentration to the 

24 44 12 So it slightly increased -- the ratios 

25 69 18 averaging time ratios. 

26 74 4 of time in doing the scaling ratios. Right now the 

27 81 12 we're looking at the maximum ratios here, how high 

28 81 20 highest ratios are about, somewhere between two and 

29 82 16 scaling, again, we looked at the minimum ratios. 

30 83 5 ratios are looking quite good in here. There still 

31 128 17 talking about for taking ratios between one-hour, 

32 128 20 rates or ratios that are applicable to flat 

33 129 2 WARREN PETERS: There will be two sets of scaling ratios for 

34 134 14 ISC-PRIME and ISC, that the ratios are near one. 

35 

36 Page Ref No. Keyword = "receptor" 

37 ____ _______ ____________________ 

38 

39 61 19 each receptor, and the output is formatted for 

40 62 4 receptor in the calculations, in that when you 

41 62 25 percent (10%) slope from a receptor. 

42 63 7 PETER ECKHOFF: Okay. Sorry. When you have a receptor, the 

43 63 12 have an example receptor, and we have various hills 

44 63 14 from that receptor. 

45 64 3 (10%) slope from your receptor. 

46 77 22 some distance in receptor height information, 

47 117 23 have a receptor that's down-sloped from it, AERMOD, 

48 146 2 receptor, and from that source to another receptor, 

49 146 11 And then another receptor with a different 

50 159 14 concentration at any receptor for a given distance 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 440 

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 6 165 5 or even receptor locator. 

 7 313 4 from a source to a receptor. 

 8 313 7 receptor. 

 9 

10 Page Ref No. Keyword = "regime" 

11 ____ _______ __________________ 

12 

13 236 8 flowing regime which I mentioned earlier, and 

14 331 19 CALMET regime and taking advantage of that. 

15 

16 Page Ref No. Keyword = "regimes" 

17 ____ _______ ___________________ 

18 

19 54 9 form has two regimes. It's a surface layer, as I 

20 224 25 of models and those two regimes, but they're really 

21 298 23 with the flow regimes around there. 

22 

23 Page Ref No. Keyword = "regulatory" 

24 ____ _______ ______________________ 

25 

26 32 21 regulatory arena. 

27 34 15 stands for the AMS/EPA regulatory model improvement 

28 35 8 Just a brief regulatory history on AERMOD. 

29 46 8 regulatory sense. 

30 109 23 consistent regulatory application of AERMOD. 

31 167 11 many regulatory actions, and it is not just to 

32 169 11 regulatory terms, just plain old technical 

33 170 16 instance to the regulatory versioning. 

34 180 12 The regulatory default override which is -- 

35 180 15 The regulatory default override -- what -- 

36 180 16 what you set back to, give me all the regulatory 

37 189 4 regulatory community here. 

38 197 25 regulatory deadlines, that are coming no matter 

39 208 3 models that are both embraced in the regulatory 

40 260 17 has been employed for another regulatory 

41 260 19 regulatory applications, the SIP model run that was 

42 263 7 into play in regulatory activities, in air quality 

43 263 8 modeling activities for regulatory met. 

44 263 10 about regulatory programs or policy ends of things, 

45 263 25 I'm not saying that there is a regulatory appetite 

46 264 12 moment that a regulatory implication, or even I'm 

47 268 12 from the regulatory legal ends of those kinds of 

48 268 20 regulatory, meteorologically, whatever, the second 

49 271 2 been used in the regulatory world as of now. Go 

50 311 17 concentrations and yet satisfying the regulatory 
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 6 315 3 From a regulatory point of view, it may be 

 7 316 3 permit to a regulatory body. 

 8 316 8 regulatory body presumably has this, you know, data 

 9 316 23 option for a regulatory body to request an analysis 

10 334 22 our regulatory agency folks? There is a few 

11 335 10 regulatory agencies, even at the state agency, is 

12 337 10 reg- -- you know -- for the general regulatory 

13 338 24 that out to the regulatory community, so that the 

14 343 6 industry; about ten percent (10%) from regulatory 

15 

16 Page Ref No. Keyword = "RUC" 

17 ____ _______ _______________ 

18 

19 225 22 The RUC (rapid update cycle) was produced 

20 231 10 at some of the forecast models, RUC, ETA and WRF, 

21 231 24 inputs, given MM5, RUC, whatever we want to, you 

22 244 14 As I mentioned earlier; RUC actually went from 

23 293 19 of next year, RUC, ETA, probably never going to be 

24 299 8 NCEP models, RUC output kinds of things, or whether 

25 301 10 some real time MM5 or real time RUC or real time 

26 320 10 have within -- we are starting to see RUC as a 

27 320 16 modelers have had, and they kept saying, well, RUC 

28 320 20 take the RUC data, and I can use it as my 

29 320 23 to what the RUC data is. 

30 

31 Page Ref No. Keyword = "rule" 

32 ____ _______ ________________ 

33 

34 26 8 BART rule, the confirmation of our administrator 

35 54 3 are sort of like rulers, are the friction velocity, 

36 101 2 come up here with slide rule in hand, adorned with 

37 111 14 We need to document it, and we need to rule 

38 111 16 rule make everything, because you see how long it 

39 111 17 takes to rule make things, but we want to rule make 

40 111 22 guidance, where we absolutely rule make. 

41 134 3 it was simply because of a black and white rule 

42 182 10 comments that we got back from the proposed rule 

43 182 12 proposed rulemaking, we got a number of comments 

44 243 14 And we will probably hear an EPA rule assist 

45 261 18 National rule. 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 442 

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 3 Page Ref No. Keyword = "run" 

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 6 22 19 today, but also by running models, we are -- we are 

 7 37 20 that if there was a bug in there, we'd run the 

 8 39 12 a full-blown AERMOD run to get estimates, or 

 9 42 5 So if you've been running ISC for a number of 

10 43 5 run times on the computer. So be expecting that. 

11 49 23 Because of some of the long run times on 

12 49 25 gobs of receptors, lots of sources, run times are 

13 50 3 version of AERMOD that will run in parallel. 

14 50 10 Roger Brode, minor upgrades such as running AERMOD 

15 50 14 AERMOD run. 

16 50 16 close by, and you wanted to run just one domain 

17 50 18 modification to AERMOD in one run. 

18 52 2 a little bit into the -- what's involved in running 

19 56 20 computationally -- computationally -- you can run 

20 57 2 computationally we run into some problems. An 

21 58 5 In terms of running AERMET basic, you know, I 

22 64 18 to interact with the patch file in order to run it 

23 67 13 data on into AERMAP run, and we should function 

24 69 11 quick run time. 

25 70 25 screen, and basically when you turn on and run the 

26 73 2 when you make the run it gip- -- I'm sorry, it 

27 73 7 AERSCREEN run, rather than them going through the 

28 73 11 the run. 

29 73 18 you want to try to run a screen on, there is a 

30 73 19 stand alone MAKEMET version that you can run in a 

31 73 24 and you can run MAKEMET with it. And it's a more 

32 75 4 you're going through an AERSCREEN run. This is the 

33 76 3 to make this model run. 

34 77 4 make your final run. 

35 79 5 run, you've entered in your data on an interactive 

36 79 15 depending on what options you're running. 

37 80 18 When Karen was running through the stack 

38 88 8 stack heights for Oklahoma City, and we have run 

39 92 8 Now we're running with the urban setting, and 

40 92 25 Because now we've run Pittsburgh with the 

41 108 17 As we gain experience in running this model, I 

42 112 7 run around to different regions in different states 

43 113 17 Cool. Let's run it. 

44 115 25 when you're running in an urban mode, it requires 

45 118 2 there, if you just run it with the terrain in 

46 118 6 got your application, that you run the model in 

47 122 19 this thing can run pretty long. And especially, I 

48 122 25 hundred thousand (100,000) sources, and I can't run 

49 123 25 And you're not -- you're not going run -- 

50 124 2 you're not going to run CMAQ to deal with those 
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 3 Page Ref No. Keyword = "run" 

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 6 155 21 you a very brief rundown on it. And, again, I was 

 7 157 15 defaults in the run scripts to run the CALPUFF 

 8 161 19 switches are doing, would get on their run. 

 9 164 18 parallel processing, where we might be running 

10 164 20 simulations, you might be running different 

11 164 23 This could be run on the very laptop I'm 

12 164 24 standing in front of, or it could be run on a 

13 166 3 and run away, it is not nearly as trivial as one 

14 168 15 experts, run the air quality model, obtain 

15 171 3 a terribly experienced person in running this 

16 178 24 clusters, and we're running simultaneously, and 

17 192 6 You can run CALMET, or you can drive 

18 194 14 Because, essentially, what we're running into 

19 194 15 here is, are we're now running into the blending of 

20 195 4 the running of the models, are now being asked to 

21 198 15 up with a list and then just run with it, but that 

22 216 3 And I've been -- I've been running CALPUFF and 

23 228 15 So in doing that, you can run MM5 both at 

24 228 20 And also, once you've run the met data of MM5 

25 230 8 we want to do that is to run AERMET using MM5 and 

26 230 13 also the grid data that was run through MM5 and run 

27 230 16 And once we run the information through 

28 230 17 AERMET, then we are going to run it through AERMOD 

29 231 4 So we would run the -- the -- possibly the 

30 231 6 results and then run AERMOD with the modifications 

31 246 16 You can run CALMET at, say, two hundred meter 

32 246 18 could run a prognostic model of that resolution. 

33 247 22 resolve MM5 run and see if we could diagnose down 

34 248 6 to deresolve your MM5 run or your WRF run and look 

35 248 10 run, and you get multiple sources of it within 

36 248 25 If you are going to be running MM5 and you're 

37 249 9 that TKE up there, we -- we had tried to run -- we 

38 254 7 run National Weather Service data, or gridded data, 

39 254 9 things that come out as it now sits, and then run 

40 257 21 the visibility in many runways just by clearing 

41 257 23 runway visual range go up, you know, hundreds of 

42 260 19 regulatory applications, the SIP model run that was 

43 260 20 done with CMAQ, or the regional haze run that was 

44 261 19 Here it is!, and that you were then to run a 

45 262 5 national run at a particular resolution, and ram it 

46 263 17 you run a -- a national run, you just fire off. 

47 268 23 run, it doesn't cost as much as going out and 

48 268 24 running your own; running your own model, digging 

49 269 23 database run, then it would be valid, perhaps even 

50 270 14 model that's going into an air quality forecast run 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 444 

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 6 273 5 we knew we were not going to run twenty different 

 7 275 24 So the idea was to run MRN with ISC the good 

 8 278 2 we were using an existing MM5 run that had 

 9 278 12 what, from now on when you do a CMAQ run, you need 

10 282 12 that difficult to take some spots and run them 

11 283 19 have in the NWS data run through AERMET. 

12 285 10 thirteen (13) Z. If you run a twelve (12) hour 

13 285 12 hours out; typical modeling run, you run a spin-up 

14 287 13 of rundowns here; sensible heat flux in MM5, higher 

15 288 22 further and look at the MM5 values and run the MM5 

16 289 15 Mechanical mixing heights; we run into the 

17 295 24 the model was run. 

18 296 7 the model that was run in the first place? 

19 296 16 why those models are run. The historic use of MM5 

20 296 24 developed specifically trying to run air quality 

21 298 6 may not be appropriate to run those things through 

22 299 9 it was running MM5 at a thirty-six to forty 

23 299 13 nested down and run in a -- well, it went from 

24 299 15 (36) run, both twelve (12) and four managed to 

25 299 20 output and run it through CALMET. CALMET didn't 

26 315 10 single run. 

27 319 12 Washington is running the MM5 on a forecast mode, 

28 320 25 and run it, which a two and a half degree by two 

29 325 7 site, but you can run a high speed model in real 

30 325 15 will actually run them out for you and give you 

31 327 10 And if you are running -- if you are doing an 

32 329 16 measurement and running all these sources through 

33 337 4 capability of running the model. 

34 337 16 actually running one of these, you will find that 

35 337 18 probably no more labor intensive than running 

36 338 4 on how to run the model, how to process the data, 

37 341 13 meteorology, and they are handed a program to run. 

38 341 14 And, they're going to be running that program. 

39 

40 Page Ref No. Keyword = "rural" 

41 ____ _______ _________________ 

42 

43 17 2 it's urban or rural; doing something about that is 

44 91 8 So for the sixteen (16) stacks, for the rural 

45 92 15 the rural setting, the fourteen stack heights and 

46 95 2 For the Pittsburgh met data, rural setting, 

47 97 5 the rural setting for AERMOD and for the sixteen 

48 97 17 and with the rural setting, and here we have the 

49 118 20 putting it in a real time rural velocity -- you 

50 249 23 urban area, and look at an adjacent rural area and 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 445 

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 3 Page Ref No. Keyword = "rural" 

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 6 250 2 rural boundary layers, if you are getting -- if 

 7 250 5 heat flux in the ur- -- in the rural area and a -- 

 8 

 9 Page Ref No. Keyword = "scale" 

10 ____ _______ _________________ 

11 

12 8 4 attention of late on regional scale transport 

13 8 7 toxics, to worry about -- about local scale 

14 8 14 personal scale exposure, that's very, very 

15 10 10 And you see, at least on the regional scale, 

16 14 13 on a smaller scale and regional scale, we're 

17 18 6 scale and secondary formation, and some of these 

18 18 7 operate on a more local scale, direct emissions or 

19 18 23 of cities and advances in local scale modeling are 

20 19 5 continental scale, and also personal, as I 

21 22 8 global scale, because there is so much of it, and 

22 54 4 a convective velocity scale, a Monin- -- what we 

23 54 5 call Monin-Obukhov length, which is a length scale. 

24 54 6 There is a temperature scale and then the 

25 59 10 We talked about AERMOD as -- is a local scale 

26 78 21 calculated. These values in here are scaled. 

27 88 5 the concentration is plotted on along the scale. 

28 89 13 scale. 

29 91 11 the log scale. 

30 123 18 everybody talking about regional scale models, 

31 123 19 regional scale models, regional scale models. 

32 124 5 AERMOD. They're going to come to the local scale 

33 127 7 regional scale gain. 

34 180 22 subgrid scale, complex terrain, in quotes, which 

35 220 2 scale modeling. For local scale modeling, these 

36 220 24 met data and incorporating it into local scale 

37 221 3 in the regional scale arena, using gridded met 

38 221 5 local scale modeling. Of course, CALPUFF now uses 

39 224 18 regional scale modeling more with local scale 

40 224 21 the regional and the local scale, and that way we 

41 226 24 The local scale models use NWS or on-site. 

42 227 8 interactions of the long-range and the local scale 

43 233 16 convective velocity scale. That's readily 

44 237 2 Depending on your grid scale that you are 

45 239 24 scale modeling, the fence line is of paramount 

46 242 12 gridded and local scale models, we are becoming 

47 246 14 twelve or four kilometers down to a scale that 

48 253 6 well, as well as the regional and the local scale. 

49 267 9 in regional scale modeling, and we have evaluated 

50 270 10 what's being used right now; the regional scale 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 446 

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 3 Page Ref No. Keyword = "scale" 

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 6 270 21 into an air quality model, be it a regional scale 

 7 273 11 on a smaller scale and do the methodical stuff, we 

 8 284 12 scale events going on that are raising, lowering, 

 9 291 3 meteorology with AERMET. This scale, I know you 

10 296 13 interested in what's going on as far as scale 

11 297 17 the scale of data that you have from a anemometer, 

12 298 11 model, but not, you know, it kind of sets the scale 

13 298 25 applications that the coarse scale mesoscale models 

14 300 20 also as a data user, primarily for local scale and 

15 300 21 regional scale modeling applications, CMAQ. 

16 301 24 strongly is the scale problem that John came up to 

17 302 16 The other thing is, along the scale is, you 

18 302 21 velocities are very, very scale dependent. In 

19 302 22 fact, they're so scale dependent in MM5 that as you 

20 312 11 set of physics on a smaller scale to capture 

21 318 6 regional scale models, and particularly the use -- 

22 323 14 particular application or the scale, that's -- 

23 341 4 got a regional scale world, which is actually 

24 341 5 pretty small compared to the -- to the local scale 

25 341 8 is not done by regional scale modelers; it's done 

26 

27 Page Ref No. Keyword = "scaling" 

28 ____ _______ ___________________ 

29 

30 53 24 theory, we can estimate scaling parameters that are 

31 54 2 parameters. Some of the scaling parameters, these 

32 56 2 and the Monin-Obukhov length which are the scaling 

33 58 14 file, which contains the scaling parameters that 

34 74 4 of time in doing the scaling ratios. Right now the 

35 74 17 us to produce a scaling factor that should work to 

36 74 25 And then the scaling factors are plotted on 

37 77 17 And from there, scaling factors are applied to 

38 77 20 calculations made other than the simple scaling. 

39 82 16 scaling, again, we looked at the minimum ratios. 

40 124 17 which is the terrain scaling height, which is used 

41 129 2 WARREN PETERS: There will be two sets of scaling ratios for 

42 287 19 look at the convective velocity scaling in MM5, 

43 288 5 face right but much lower on the scaling. 

44 295 18 to the various regional scaling models, the puff 
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 6 67 9 on SCRAM yet? 

 7 107 8 It is just a matter of getting it up on SCRAM. 

 8 146 17 on our SCRAM web pages, so you can go back and 

 9 

10 Page Ref No. Keyword = "screening" 

11 ____ _______ _____________________ 

12 

13 47 15 actually had Complex I, the screening model in 

14 69 5 called AERSCREEN is a screening model for AERMOD. And 

15 69 7 We wanted to develop some screening procedures that 

16 72 12 dimensions, so, still, even though it's a screening 

17 73 25 sophisticated screening model, if you will. 

18 81 17 screening model. 

19 81 22 a screening model. 

20 158 17 was reading this out was the screening techniques 

21 159 5 CALPUFF screening was -- it's interesting in 

22 159 9 everyone is probably familiar with screening 

23 159 12 generalized in the screening. 

24 159 20 pass at a -- at a screening application. 

25 159 21 So it was, while you don't see screening done 

26 160 5 I'm not sure that screening was ever brought about 

27 335 5 used several different screening tools, did he go 

28 

29 Page Ref No. Keyword = "sensitivity" 

30 ____ _______ _______________________ 

31 

32 85 21 So we did a sensitivity study, and we divided 

33 89 19 sensitivity, but as we go to the higher stacks, 

34 89 20 we're seeing more sensitivity to the changes in 

35 90 8 sensitivity to the albedo change. However, as 

36 90 16 We see a little bit of sensitivity 

37 90 19 amount of sensitivity to the changes in the albedo. 

38 90 20 The other stacks are showing some sensitivity, 

39 91 17 a lot of sensitivity to the changes in the Bowen 

40 92 11 sensitivity, but the taller stacks, again, more 

41 92 12 sensitivity -- sensitive there to the choice in the 

42 92 19 seeing a little bit more sensitivity with the 

43 92 21 showing little sensitivity and as you go up in the 

44 93 9 Now, sensitivity results, surface roughness is 

45 93 24 lot more sensitivity to changes in the surface 

46 94 18 still sensitivity in the -- in the taller stacks. 

47 94 23 very similar, large sensitivity on the lower stack, 

48 95 5 sensitivity here again, smaller stack. 

49 95 8 showing sensitivity cliff to a hundred percent 

50 95 11 stacks are showing sensitivity. 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 448 

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 6 95 18 sensitivity. 

 7 95 22 surface roughness. There is some sensitivity in 

 8 96 5 For the second part of the sensitivity study, 

 9 97 9 seeing more sensitivity to the surface roughness 

10 97 19 sensitivity on these lower stacks and the same 

11 98 3 sensitivity study? 

12 99 2 in our sensitivity study. We'd also like to do -- 

13 125 14 sensitivity of Bowen ratio, and that is that, you 

14 132 4 So you might want to do a sensitivity study. 

15 136 12 to the sensitivity analysis work done for the 

16 142 21 Karen, with regards to a sensitivity study, most of 

17 142 22 the people who are going to be doing a sensitivity 

18 143 9 would suggest that you rearrange your sensitivity 

19 145 5 I'm wondering if the sensitivity to Z naught 

20 237 21 Sensitivity tests, of course, are necessary to 

21 304 22 And some sensitivity analyses might be 

22 308 14 lots, accidental releases. Sensitivity analyses 

23 

24 Page Ref No. Keyword = "service" 

25 ____ _______ ___________________ 

26 

27 33 21 service, so it looks like it paid off. 

28 65 8 with that is the world geodetic center -- service 

29 113 16 weather service station, it's representative. 

30 115 12 might have a national weather service site whose 

31 131 16 Weather Service, and is it going to be able to 

32 133 2 you want to use National Weather Service data that 

33 155 15 individuals, EPA, Forest Service, Park Service and 

34 155 16 Fish and Wildlife Service involved at that time. 

35 176 2 Forest Service and the Park Service. 

36 177 21 the National Weather Service 3240 data is so easily 

37 188 25 Service data. And so these are -- this is one of 

38 192 20 standard National Weather Service data or 

39 217 20 JOHN VIMONT: John Vimont with the National Park Service. 

40 220 5 well served by National Standard Weather Service 

41 222 25 Well, first of all National Weather Service 

42 223 24 than you would get for National Weather Service 

43 232 21 Service, many of the states participated, and we 

44 235 24 data isn't captured by National Weather Service 

45 237 23 National Weather Service data. It's not done to 

46 243 19 from National Weather Service to gridded data. 

47 254 7 run National Weather Service data, or gridded data, 

48 254 10 National Weather Service data through AERMET, you 

49 256 13 in the weather service, and actually in the Air 

50 267 25 put out by the Weather Service, you've got all 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 449 

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 6 270 16 on the National Weather Service site and you can 

 7 270 19 Weather service Model Center, National Center for 

 8 287 2 Weather Service data going through AERMOD. 

 9 294 24 Vimont from the National Park Service, Dennis 

10 295 7 Park Service, Air Resources Division. 

11 298 17 out of the Fish and Wildlife Service did model runs 

12 298 21 Service has done a number of air quality studies 

13 326 16 Service data, how well, did the model do, and -- 

14 332 3 Weather Service, their mission is to protect lives 

15 333 22 We were using the National Weather Service 

16 333 25 and one thing the National Park Service did, which 

17 

18 Page Ref No. Keyword = "site" 

19 ____ _______ ________________ 

20 

21 71 17 a web site, download one degree DEM data and make 

22 113 24 application site where the surrounding area 

23 114 25 the application site as opposed to where the 

24 115 4 site are going to be very different from what is 

25 115 6 site is going to be very different from what's 

26 115 7 happening at the actual application site. 

27 115 12 might have a national weather service site whose 

28 121 16 going to do is get an observer on site to get your 

29 166 14 judgment, but also site specific, case specific, if 

30 181 20 Therefore, we're back to this site specific, 

31 223 13 miles from your modeling site. 

32 245 11 web site. You -- like I said, you can get a whole 

33 262 13 the site specific things, the site specific 

34 270 16 on the National Weather Service site and you can 

35 274 7 Airport, the site of the NWS observation. 

36 274 9 site of many heartbreaks of my youth, and that box 

37 310 12 as well when sources away from the site are 

38 317 5 the nearest site should be used, or whether an 

39 324 19 meteorological tower at the site, we had much 

40 325 7 site, but you can run a high speed model in real 

41 325 12 -- and right now you can put in the site, anywhere 

42 325 24 RICHARD SCHULZE: What was that web site, Bob? 

43 339 24 -- a web site where you would point and click on 

44 

45 Page Ref No. Keyword = "slope" 

46 ____ _______ _________________ 

47 

48 62 25 percent (10%) slope from a receptor. 

49 63 13 represented here, and a ten percent (10%) slope 

50 64 3 (10%) slope from your receptor. 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 450 

 2 

 3 Page Ref No. Keyword = "slope" 

 4 ____ _______ _________________ 

 5 

 6 119 3 degree slope. 

 7 119 11 in this concept of a ten (10) degree slope. Then 

 8 119 17 that say, you know, the ten (10) degree slope is 

 9 

10 Page Ref No. Keyword = "source" 

11 ____ _______ __________________ 

12 

13 29 5 improve source culpability assessments. 

14 31 15 of a particular source causing the problem and 

15 43 17 different source scenarios, okay? So forty-eight 

16 45 9 modeling the point source, try to find something 

17 49 24 larger source scenario evaluations, when you have 

18 69 16 doing the point source evaluations; that is, it has 

19 71 9 source. We had wanted to set it up for volume 

20 71 10 source which should be a relatively quick change to 

21 73 17 or you have a really complex source scenario that 

22 88 9 AERMOD with a study of source characteristics. . 

23 95 24 source height dependency here. 

24 110 2 PSD or the new source review; regulations demand 

25 114 17 with source location. 

26 116 20 and I was using an area source and, as I'll get to 

27 117 22 was, if you've got a source sitting here and you 

28 120 16 And then finally the area source algorithm, 

29 125 5 buoyant blind source. 

30 131 4 the source versus the location of the meteorology, 

31 132 5 If you've got an elevated source, that's, well, you 

32 132 6 know, moderately elevated source, a fifty (50) 

33 132 7 meter high source, and there -- you know there are 

34 142 8 down towards the source that's set up the 

35 145 25 homogeneous between the source -- to the apt 

36 146 2 receptor, and from that source to another receptor, 

37 234 16 source fields. 

38 234 17 How would a single met source model handle met 

39 234 22 that represents the source; I mean, do you do it 

40 235 6 possibly use a center grid cell for the source 

41 235 8 include the other source areas; or possibly use 

42 242 22 What is the source of the data if you do use 

43 247 25 And a comment regarding the multiple source 

44 304 15 kilometers (50km) of the source, and how 

45 310 17 source. 

46 313 4 from a source to a receptor. 

47 313 6 source, but somewhere between the source and the 

48 314 20 consideration of the elevation of the source. 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 451 

 2 

 3 Page Ref No. Keyword = "speed" 

 4 ____ _______ _________________ 

 5 

 6 57 12 surface layer and a wind speed at one -- at one 

 7 76 5 recall that we have to have a minimum wind speed in 

 8 76 8 the wind direction -- I mean for the wind speed, 

 9 112 25 speed, temperature and turbulence. It actually 

10 136 16 model at wind speed, or was it not so obvious that 

11 137 9 just affecting the wind speed, and that's what's 

12 137 16 partition the wind speed. 

13 280 6 Well, the first one we got back was wind speed. 

14 280 11 MARK EVANGELISTA: -- but wind speed is not too bad. It 

15 280 17 wind speed. 

16 305 9 wind speed and direction compared to locally 

17 306 15 States that would have to be brought up to speed, 

18 306 19 speed. 

19 325 7 site, but you can run a high speed model in real 

20 330 10 variability is, and it's a non-zero wind speed and 

21 341 20 I mean, you've got a wind speed, you've got a 

22 

23 Page Ref No. Keyword = "stack" 

24 ____ _______ _________________ 

25 

26 72 10 some details about where the stack is located in 

27 72 14 building and the stack locations. 

28 74 22 but the abscissa here is stack height. 

29 74 23 So you can see that there is a range of stack 

30 75 8 going on for the emissions rates, stack height, 

31 75 9 stack diameter, all the things you leach back, 

32 75 18 have to understand where the stack is in relation 

33 75 25 width, then the angle to the true north, and stack 

34 78 8 very, very close distance to the stack, but if you 

35 80 18 When Karen was running through the stack 

36 81 23 Roger Brode, in his stack was twenty-two (22) 

37 87 3 So we did this for several stack heights. We 

38 87 4 held eleven stack heights with no buoyancy, 

39 87 7 different stack heights that we used. 

40 87 8 We held -- we did a -- three stack heights, a 

41 87 13 stack heights for both Oklahoma City and for the 

42 87 16 other stack heights. That's thirty-five meter 

43 87 17 buoyant stack and a thirty-five meter very buoyant 

44 87 18 stack. 

45 88 8 stack heights for Oklahoma City, and we have run 

46 88 13 for stack heights, we selected four, five meters, 

47 89 3 the higher stack. There is some variability for 

48 89 11 of the sixteen (16) stack heights; not a huge 

49 89 16 sensitive concentrations are at the taller stack, 

50 89 18 five-meter stack is showing little or no 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 452 

 2 

 3 Page Ref No. Keyword = "stack" 

 4 ____ _______ _________________ 

 5 

 6 89 24 Pittsburgh, we have fourteen (14) stack heights 

 7 90 9 we're going up in the stack height, more and more 

 8 90 14 setting, again, for the fourteen (14) stack 

 9 90 18 here again; five-meter stack, nice showing. Huge 

10 91 16 the shorter stack, the five-meter stack not showing 

11 92 4 So here again the taller stack seems to be the 

12 92 7 sixteen (16) stack heights. 

13 92 15 the rural setting, the fourteen stack heights and 

14 92 20 highest stack, but again, the five-meter stack 

15 92 22 stack height, you see more, some of the 

16 92 23 intermediate stack heights look like they are 

17 93 3 stack heights. 

18 93 6 And statistically, again, the smaller stack 

19 93 20 the -- in the low stack. As you know, the -- as 

20 93 21 the stack is -- is increased, the concentration 

21 94 3 with the -- you know -- it's the five-meter stack 

22 94 20 again, in Oklahoma City, same fifteen (15) stack 

23 94 23 very similar, large sensitivity on the lower stack, 

24 94 24 the higher the stack goes, seems to be not quite as 

25 95 3 again, fourteen stack heights, and the surface 

26 95 5 sensitivity here again, smaller stack. 

27 95 7 stack -- I mean the shorter stack, the five-meter, 

28 95 14 fourteen (14) stack heights, again similar 

29 95 25 The shorter stack seems to be more sensitive 

30 97 6 (16) stack heights. 

31 97 13 And the sixteen (16) stack heights we're 

32 97 18 fourteen stack heights. Again, we're seeing 

33 97 24 stack heights, and we're seeing the same pattern 

34 99 11 For example, if you had a taller stack height, 

35 99 14 A shorter stack height, smaller footprint, 

36 

37 Page Ref No. Keyword = "stacks" 

38 ____ _______ __________________ 

39 

40 74 15 have buoyant and non-buoyant stacks, and these 

41 81 18 Karen in her testing these stacks that we have 

42 87 10 hundred (200) meters, and how their stacks have to 

43 88 12 some stacks with percent difference, and this is 

44 89 4 the lower stacks, but the higher stack seems to 

45 89 19 sensitivity, but as we go to the higher stacks, 

46 90 2 You can see that for the low stacks, it seems 

47 90 4 intermediate stacks, we feel a little more 

48 90 7 the short stacks of five (5) meters, very little 

49 90 20 The other stacks are showing some sensitivity, 

50 90 21 the highest being in the taller stacks, the two 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 453 

 2 

 3 Page Ref No. Keyword = "stacks" 

 4 ____ _______ __________________ 

 5 

 6 90 22 hundred (200) meter very buoyant stacks. 

 7 91 8 So for the sixteen (16) stacks, for the rural 

 8 91 19 As we go up in the stacks, we see a higher 

 9 92 10 and again shorter stacks not showing that much 

10 92 11 sensitivity, but the taller stacks, again, more 

11 93 8 stacks showing quite a bit of variability. 

12 94 17 especially in -- in the lower stacks, but there is 

13 94 18 still sensitivity in the -- in the taller stacks. 

14 95 11 stacks are showing sensitivity. 

15 95 17 smaller stacks are showing the greater 

16 96 3 stacks are more sensitive to the albedo and Bowen 

17 97 8 where it -- the stacks -- the shorter stacks are 

18 97 19 sensitivity on these lower stacks and the same 

19 118 8 Capping horizontal stacks became a fairly 

20 122 13 Horizontal and capped stacks. 

21 145 13 near-field, the low stacks. My concern is that 

22 307 18 when there are stacks of significant plume rise, 

23 

24 Page Ref No. Keyword = "statistical" 

25 ____ _______ _______________________ 

26 

27 93 6 And statistically, again, the smaller stack 

28 94 2 Okay, now you look at that statistically, and 

29 139 11 statistical comparison between ISC and AERMOD and 

30 193 7 Statistical method -- metrics and 

31 193 18 statistical comparisons with observations of winds 

32 288 13 So it's just -- there's a statistical anomaly 

33 

34 Page Ref No. Keyword = "steady state" 

35 ____ _______ ________________________ 

36 

37 240 25 and this would result that steady state models 

38 248 18 the model you're trying to use is a steady state 

39 254 5 harmony right now with the steady state AERMOD. 

40 293 4 in a single cell, steady state being what it is, we 

41 330 21 steady state models only out to a distance where it 

42 

43 Page Ref No. Keyword = "surface" 

44 ____ _______ ___________________ 

45 

46 37 8 very, very close down near the surface of the earth 

47 38 20 tool that processes surface characteristic data, 

48 41 12 from the surface of the earth. And AERMOD 

49 42 17 surface characteristics, the albedo, the Bowen 

50 42 18 ratio when there's surface roughness. 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 454 

 2 

 3 Page Ref No. Keyword = "surface" 

 4 ____ _______ ___________________ 

 5 

 6 52 25 surface heating. It's characterized by vertical 

 7 53 21 the surface layer which extends up to approximately 

 8 53 22 fifty (50) meters at most, varies, and surface 

 9 54 9 form has two regimes. It's a surface layer, as I 

10 54 21 closer to the surface, the more the shear forces 

11 54 25 estimate the surface heat flux, and basically it's 

12 55 2 a surface -- the -- what drives the boundary layer 

13 55 9 which is one of our surface characteristics. It's 

14 55 10 -- it's the reflection of the -- of the surface. 

15 55 15 heating the surface. 

16 56 14 you know, after sunset when the surface begins to 

17 57 12 surface layer and a wind speed at one -- at one 

18 58 13 There are two (2) files; one is a surface 

19 58 22 The types of surface data that are supported 

20 59 3 Integrated Surface Hourly Data, and it is probably 

21 61 8 formulated. Some were done over the surface of the 

22 76 10 Also, going back to the surface 

23 76 17 know what your surface characteristics are already, 

24 83 21 AERSURFACE is a tool and it produces the surface 

25 83 25 ratio, and the surface roughness. 

26 84 9 surface characteristics values. These include the 

27 84 10 surface roughness, the albedo, and the Bowen 

28 85 8 albedo, a Bowen ratio, and a surface roughness. 

29 85 11 Bowen ratio and surface roughness. 

30 85 20 in surface characteristics. 

31 85 24 varied the albedo, the Bowen ratio, the surface 

32 86 7 surface value, so it would be bound in eight 

33 86 8 surface -- excuse me, eight surface types. 

34 86 11 Pittsburgh. And we varied the surface 

35 86 15 this, we held the Bowen ratio and the surface 

36 86 20 the albedo at zero point two (0.2) and the surface 

37 86 22 And then for the surface roughness it ranged 

38 87 22 constant and the surface roughness concept. 

39 91 3 two (0.2) and surface roughness constant at zero 

40 93 9 Now, sensitivity results, surface roughness is 

41 93 24 lot more sensitivity to changes in the surface 

42 95 3 again, fourteen stack heights, and the surface 

43 95 16 very sensitive to surface roughness, but the 

44 95 22 surface roughness. There is some sensitivity in 

45 96 2 to the surface roughness value, and the taller 

46 96 12 That's where we took the surface roughness and 

47 96 25 surface roughness, point zero zero zero one (.0001) 

48 97 2 to a larger surface roughness, one point three 

49 97 9 seeing more sensitivity to the surface roughness 

50 98 4 Well, we've learned that surface roughness 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 455 

 2 

 3 Page Ref No. Keyword = "surface" 

 4 ____ _______ ___________________ 

 5 

 6 98 24 surface characteristics. 

 7 113 4 get -- you need to have certain surface 

 8 114 4 surface characteristics, which are going to 

 9 116 18 certain surface sources, and that's because WRF was 

10 122 9 Selection of surface characteristics, 

11 133 15 of surface data. We have all the landscape 

12 136 13 surface parameters. 

13 137 8 Is it possible then maybe surface roughness is 

14 137 13 thought. The other thing is that even the surface 

15 137 15 Surface roughness is also used in AERMOD to 

16 192 11 either surface or upper-air data, or you can use 

17 192 12 surface data for your observations, and then you 

18 193 19 aloft and at the surface at several appropriate 

19 223 2 surface and upper air sites are typically not 

20 223 5 discontinuity between your surface data and your 

21 223 17 They provide a lot of surface characteristics, 

22 232 9 host of surface parameters, whatever fields need to 

23 233 23 Surface sensible heat flux and latent heat 

24 259 24 is not collocated with the surface, and anyone 

25 283 15 Surface pressure. MM5 being the triangle -- I 

26 283 17 discussion here, so you can see the surface 

27 284 3 But MM5 is talking about layer one surface 

28 284 6 it's not at the surface, so this is a very, very 

29 297 22 (38km) surface layer. 

30 310 25 from surface roughnesses over Delaware River or 

31 313 25 traveling, both at the surface and aloft. Can we 

32 315 2 differences based on surface roughness and albedo. 

33 

34 Page Ref No. Keyword = "surrogate" 

35 ____ _______ _____________________ 

36 

37 116 3 nothing more than a -- actually a surrogate for the 

38 117 9 something like population as a surrogate for it. 

39 121 12 surrogate for cloud cover. 

40 121 20 surrogate for it. 

41 

42 Page Ref No. Keyword = "temperature" 

43 ____ _______ _______________________ 

44 

45 21 3 reducing temperature in the city, but maybe it also 

46 54 6 There is a temperature scale and then the 

47 57 11 number are a temperature difference of the inner 

48 112 25 speed, temperature and turbulence. It actually 

49 183 20 sensitive to the temperature effects which thereby 

50 282 18 The two meter temperature, the well-known, 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 456 

 2 

 3 Page Ref No. Keyword = "temperature" 

 4 ____ _______ _______________________ 

 5 

 6 297 18 temperature sensors, you know, even any temperature 

 7 341 21 wind direction, you've got a temperature, and 

 8 

 9 Page Ref No. Keyword = "terrain" 

10 ____ _______ ___________________ 

11 

12 36 21 Also, we modified the complex terrain 

13 37 2 complex terrain analysis. 

14 38 5 have AERMAP the terrain data preprocessor, and then 

15 38 11 bringing in the terrain data and the meteorological 

16 43 13 terrain scenarios. We had point, volume and area 

17 47 13 In a complex terrain, now here's one of the 

18 47 16 there for complex terrain. 

19 47 18 science approach to the complex terrain, and we're 

20 48 7 cases AERMOD in complex terrain, produced 

21 60 14 We also have a terrain preprocessor called 

22 62 14 also to use XYZ terrain data inside the model, and 

23 62 24 searched for the terrain that breaks through a ten 

24 63 15 And the mandatory inclusion of the DEM terrain 

25 66 24 There was -- we were asked to add XYZ terrain 

26 67 7 And there is a draft XYZ terrain user's guide 

27 69 17 a wake effect on the building, terrain features and 

28 71 16 terrain automatically. It will automatically go to 

29 71 22 in rel- -- rather complex terrain, I guess, very 

30 71 23 complex terrain. 

31 72 4 terrain, or simple/complex terrain, if you will, if 

32 81 4 Bob Paine in complex terrain was one point 0 eight 

33 113 15 you're in flat terrain and there's a national 

34 113 18 If you're in complex terrain, there is no such 

35 113 23 In flat terrain, now, if you've got an 

36 117 21 with regard to down-sloping terrain. The issue 

37 117 25 at night so that -- so that terrain really isn't 

38 118 2 there, if you just run it with the terrain in 

39 118 7 flat terrain models. 

40 119 6 so -- and then you get the terrain data for the 

41 119 21 -- or ignoring a piece of terrain like that, if one 

42 120 2 terrain. 

43 120 15 can put their own terrain data in. 

44 124 17 which is the terrain scaling height, which is used 

45 124 22 very different type of terrain features. 

46 128 21 terrain, complex terrain. 

47 129 3 complex versus simple terrain. 

48 131 11 terrain, you're collecting on-site data; you in 

49 131 12 flat terrain you're not collecting on-site data. 

50 180 22 subgrid scale, complex terrain, in quotes, which 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 457 

 2 

 3 Page Ref No. Keyword = "terrain" 

 4 ____ _______ ___________________ 

 5 

 6 234 2 Terrain elevations, of course they're very 

 7 234 6 important for the complex terrain situations. 

 8 235 23 terrain situations and situations where the met 

 9 239 11 terrain, that's still fairly coarse, and there are 

10 239 15 Complex terrain, as I mentioned earlier, 

11 239 21 complex terrain-related situations that would 

12 265 13 observational data, there's not a lot of terrain in 

13 282 6 locations; could there be some terrain problem, 

14 300 7 of the terrain, and deal with that. 

15 311 25 and the underlying terrain and land and sea 

16 312 7 It generally lacks the detail both in terrain 

17 313 14 work quite well in flat terrain, but when one gets 

18 313 15 to complex terrain or has land/sea interfaces, such 

19 314 13 one grid cell. For complex terrain, it may be 

20 314 15 say, point 0 0 five L (.005L) terrain variation 

21 314 18 land/sea interfaces, and the ratio of terrain to 

22 324 16 in a terrain situation without probably adequate 

23 

24 Page Ref No. Keyword = "toxic" 

25 ____ _______ _________________ 

26 

27 122 22 doing the Philadelphia toxic study, and at the 

28 138 11 hazardous substances and toxic releases and -- and 

29 292 21 not the toxic stuff where we're dealing with 

30 

31 Page Ref No. Keyword = "toxics" 

32 ____ _______ __________________ 

33 

34 8 7 toxics, to worry about -- about local scale 

35 10 5 This is all separate, and air toxics is 

36 11 6 toxics rules, or acid rain programs, or whatever, 

37 19 8 PM but air toxics. 

38 31 11 John saying this, as many of you know, for toxics 

39 200 10 questions about toxics and doing risk assessments, 

40 240 6 applications, toxics, urban situations, and other 

41 271 21 had been done for air toxics in Philadelphia, and 

42 282 24 was done in the toxics rollover. We're looking at 

43 

44 Page Ref No. Keyword = "turbulence" 

45 ____ _______ ______________________ 

46 

47 53 15 translates the turbulence into dispersion, vertical 

48 53 25 necessary to derive profiles of the turbulence 

49 54 19 shear and turbulence -- or both shear and blocking 

50 54 20 contribute to the generation of turbulence. The 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 458 

 2 

 3 Page Ref No. Keyword = "turbulence" 

 4 ____ _______ ______________________ 

 5 

 6 54 22 contribute to turbulence. 

 7 56 4 turbulence in convective boundary layers. 

 8 56 15 cool. Turbulence is shear driven, decays with 

 9 58 15 AERMOD uses to develop profiles of turbulence 

10 112 25 speed, temperature and turbulence. It actually 

11 114 6 turbulence and mean flow, about how you build these 

12 114 22 between turbulence and mean flow when you think of 

13 189 12 turbulence-based dispersion coefficients, but 

14 307 25 convective turbulence conditions. 

15 341 19 discrete turbulence classes, you know. 

16 

17 Page Ref No. Keyword = "urban" 

18 ____ _______ _________________ 

19 

20 13 13 ones that are -- that are exposing people in urban 

21 17 2 it's urban or rural; doing something about that is 

22 20 25 know that that also is going to reduce the urban -- 

23 37 5 the urban dispersion mechanism for low-level 

24 50 11 in multiple urban areas where you can specify an 

25 50 12 urban situation that is different from another part 

26 50 15 So if you had multiple urban areas that are 

27 75 12 go to the urban row, and you have to pick one of 

28 89 9 had AERMOD, in the urban setting. Again, you see the 

29 90 13 We also did this for Pittsburgh with the urban 

30 92 8 Now we're running with the urban setting, and 

31 93 2 urban setting, and again, it's the same fourteen 

32 94 19 So we also did this for the urban setting, 

33 95 13 Pittsburgh now in the urban setting, same 

34 96 19 forest, urban and conifer forest. 

35 97 11 and we did this also for the urban setting for 

36 97 22 So, okay, now, we ran it for the urban setting 

37 115 25 when you're running in an urban mode, it requires 

38 116 6 how much of the population? How big is the urban 

39 117 3 getting positive heat fluxes, and this is an urban 

40 117 6 urban version of them and apply it with WRF or 

41 117 8 the urban boundary layer and not have to utilize 

42 117 12 realized that that was going -- that the urban 

43 122 16 Reformulate air -- urban -- we've talked about 

44 123 23 left is the urban excess and the urban excess is 

45 143 3 over water, or over- -- or am I in the urban 

46 240 6 applications, toxics, urban situations, and other 

47 249 23 urban area, and look at an adjacent rural area and 

48 249 25 urban boundary layer, relative to the adjacent 

49 250 6 and a positive heat flux in the urban area, that 

50 250 8 to really reformulate the urban part of the AERMOD 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 459 

 2 

 3 Page Ref No. Keyword = "urban" 

 4 ____ _______ _________________ 

 5 

 6 250 12 about the urban version, there is an urban version 

 7 250 13 of MM5 and an urban version of WRF, and so one may 

 8 250 15 you need to look at the urban canopy and so on, 

 9 250 16 a reasonable representation of the urban boundary 

10 265 14 the way, there's a lot of urban/rural interfaces 

11 

12 Page Ref No. Keyword = "variability" 

13 ____ _______ _______________________ 

14 

15 16 6 heart rate variability. 

16 89 2 variability in the concentration seems to be with 

17 89 3 the higher stack. There is some variability for 

18 89 12 amount of variability that we can see on the log 

19 90 25 one (.1) and ten (10), so a little more variability 

20 91 10 variability; here again concentration is plotted on 

21 93 7 heights not showing a lot of variability, larger 

22 93 8 stacks showing quite a bit of variability. 

23 93 19 lot of variability, and we're starting to see it in 

24 94 4 here is having a lot of variability, and the 

25 94 15 quite over -- quite a large variability here. 

26 94 16 And that's not a lot of variability, 

27 128 23 be any variability for those two different types of 

28 136 14 Was it obvious whether the variability in the 

29 330 10 variability is, and it's a non-zero wind speed and 

30 

31 Page Ref No. Keyword = "weather" 

32 ____ _______ ___________________ 

33 

34 14 22 realize the probability is the climate, our weather 

35 113 16 weather service station, it's representative. 

36 115 12 might have a national weather service site whose 

37 131 16 Weather Service, and is it going to be able to 

38 133 2 you want to use National Weather Service data that 

39 177 21 the National Weather Service 3240 data is so easily 

40 188 24 in conjunction with the available National Weather 

41 192 20 standard National Weather Service data or 

42 220 5 well served by National Standard Weather Service 

43 222 25 Well, first of all National Weather Service 

44 223 24 than you would get for National Weather Service 

45 226 11 development. It's the weather and research 

46 235 24 data isn't captured by National Weather Service 

47 237 23 National Weather Service data. It's not done to 

48 243 19 from National Weather Service to gridded data. 

49 254 7 run National Weather Service data, or gridded data, 

50 254 10 National Weather Service data through AERMET, you 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 460 

 2 

 3 Page Ref No. Keyword = "weather" 

 4 ____ _______ ___________________ 

 5 

 6 256 13 in the weather service, and actually in the Air 

 7 267 25 put out by the Weather Service, you've got all 

 8 270 16 on the National Weather Service site and you can 

 9 270 19 Weather service Model Center, National Center for 

10 287 2 Weather Service data going through AERMOD. 

11 326 15 of the on-site data and went to National Weather 

12 332 3 Weather Service, their mission is to protect lives 

13 332 4 and property from severe weather, based on 

14 333 22 We were using the National Weather Service 

15 

16 Page Ref No. Keyword = "wind" 

17 ____ _______ ________________ 

18 

19 37 12 at low wind speeds for all stable and unstable 

20 41 10 the atmosphere. We understand how the various wind 

21 53 9 produce, profiles of wind/temperature in the 

22 57 12 surface layer and a wind speed at one -- at one 

23 76 5 recall that we have to have a minimum wind speed in 

24 76 8 the wind direction -- I mean for the wind speed, 

25 112 24 perspective that it utilizes profiles of wind 

26 116 19 producing extraordinarily low wind speeds, okay, 

27 124 20 know, depending on what the wind direction is, 

28 124 24 wind dependent -- wind dependency for H sub c. So 

29 132 25 near-field impacts, and you want to use wind -- if 

30 136 16 model at wind speed, or was it not so obvious that 

31 137 9 just affecting the wind speed, and that's what's 

32 137 16 partition the wind speed. 

33 177 16 The bias parameter, the wind calculation, 

34 177 18 prognostic model when it goes into the wind 

35 200 13 a non-uniform wind field and whether you should be 

36 200 24 if you put in a uniform wind field, then allow it 

37 226 16 and has high resolution window forecasts with 

38 241 6 incorporate lower wind speeds, of course, your 

39 248 22 do get profiles of wind, okay. 

40 280 6 Well, the first one we got back was wind speed. 

41 280 11 MARK EVANGELISTA: -- but wind speed is not too bad. It 

42 280 17 wind speed. 

43 296 11 it is going to rain, they want to know if the wind 

44 305 9 wind speed and direction compared to locally 

45 312 8 and wind data for appropriate grid cells available 

46 325 4 greatly improved the wind speeds in those products. 

47 329 12 constructing the wind field well enough to 

48 330 9 the capturing of the variable wind as to what that 

49 330 10 variability is, and it's a non-zero wind speed and 

50 341 20 I mean, you've got a wind speed, you've got a 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 461 

 2 

 3 Page Ref No. Keyword = "wind" 

 4 ____ _______ ________________ 

 5 

 6 341 21 wind direction, you've got a temperature, and 

 7 

 8 Page Ref No. Keyword = "wind speed" 

 9 ____ _______ ______________________ 

10 

11 57 12 surface layer and a wind speed at one -- at one 

12 76 5 recall that we have to have a minimum wind speed in 

13 76 8 the wind direction -- I mean for the wind speed, 

14 136 16 model at wind speed, or was it not so obvious that 

15 137 9 just affecting the wind speed, and that's what's 

16 137 16 partition the wind speed. 

17 280 6 Well, the first one we got back was wind speed. 

18 280 11 MARK EVANGELISTA: -- but wind speed is not too bad. It 

19 280 17 wind speed. 

20 305 9 wind speed and direction compared to locally 

21 330 10 variability is, and it's a non-zero wind speed and 

22 341 20 I mean, you've got a wind speed, you've got a 

23 

24 Page Ref No. Keyword = "wind speeds" 

25 ____ _______ _______________________ 

26 

27 37 12 at low wind speeds for all stable and unstable 

28 116 19 producing extraordinarily low wind speeds, okay, 

29 241 6 incorporate lower wind speeds, of course, your 

30 325 4 greatly improved the wind speeds in those products. 

31 

32 Page Ref No. Keyword = "winds" 

33 ____ _______ _________________ 

34 

35 115 3 to -- the winds that you are going to get from that 

36 120 18 the issue if you have very, very light winds for 

37 142 7 So it's the trajectory of the winds coming 

38 165 18 bit as driven by mixing depth as by the winds 

39 193 18 statistical comparisons with observations of winds 

40 200 5 to complex winds. 

41 274 14 winds which are the on the corners of the grid 

42 324 17 fine grid, I -- I was getting lots of calm winds 

43 324 20 higher winds. 

44 325 11 the readily available NCEP forecast winds, put in 

45 328 9 If you get very, very light winds, all of 

46 330 4 winds as calm. 
 1 Eighth Modeling Conference Keyword Index Vol. 1, p. 462 

 2 

 3 Page Ref No. Keyword = "work group" 

 4 ____ _______ ______________________ 

 5 

 6 70 7 work group. As I mentioned, Jim Haywood from the 

 7 70 15 I'm on the work group here. 

 8 104 13 together a work group, a work group that compos- -- 

 9 108 8 construct an ad hoc work group to help support that 

10 151 15 Right now we've convened a loose work group, 

11 151 16 we're going to call it CALPUFF work group, and it 

12 151 18 the original IWAQM work group, folks who clearly 

13 203 7 interagency work group, and that was the stepping 

14 221 15 report out on a gridded met data that work group 

15 232 14 work group, and this was just kind of as a 

16 237 5 One of our work group members had had 

17 238 2 This is something that our work group was very 

18 259 2 work group, and some of the first steps we've taken 

19 293 25 with that work group that Dennis talked about, and 

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