OSHA: Proposed Standard For Indoor Air Quality: ETS Hearings, September 26, 1994

OSHA: Proposed Standard For Indoor Air Quality: ETS Hearings, September 26, 1994



UNITED STATES DEPARTMENT OF LABOR

OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION

PUBLIC HEARING

PROPOSED STANDARD FOR INDOOR AIR QUALITY

Monday

September 26, 1994

Interstate Commerce Commission

Washington, D.C.

The above-entitled matter came on for hearing, pursuant to notice, at 9:46 a.m.

BEFORE: HONORABLE JOHN VITTONE

Administrative Law Judge

AGENDA

PAGE

Neal L. Benowitz 1194

Questions:

Ted Grossman 1245
John Rupp 1311
Jim Dinegar 1340
Debra Janes 1345
Ms. Sherman 1346

Wayne Ott, Ph.D. 1351

Questions:

John Rupp 1376
Ms. Sherman 1434

Peggy Jenkins, M.S. 1442

EXHIBITS

EXHIBIT NO. IDENTIFIED RECEIVED

29 1244 1244

30 1311 1311

31 1316 1316

32 1376 1376

33 1443 1443

P R O C E E D I N G S
(9:46 p.m.)

JUDGE VITTONE: Good morning. I hope everybody had a good weekend. We are going to resume this morning. We have three witnesses scheduled for today. Dr. Neal Benowitz, Mr. Wayne Ott, and Ms. Peggy Jenkins.

My understanding is that the OSHA team will lead off with Dr. Benowitz. Is Dr. Benowitz going to be using a slide or some kind of presentation?

DR. BENOWITZ: Slide projection.

JUDGE VITTONE: Slide projecting. Okay.

Dr. Benowitz, do you want to come forward over to this area here. This is where the witnesses will be, right there.

Dr. Benowitz, would you state your name for the record, your affiliation, and who you're representing today, if anyone?
NEAL L. BENOWITZ

DR. BENOWITZ: I'm Neal Benowitz. My affiliation if University of California San Francisco, and I'm here representing OSHA.

JUDGE VITTONE: Okay. You supplied a statement for the record on August the 18th, 1994?

DR. BENOWITZ: Yes.

JUDGE VITTONE: All right, sir. If you're prepared to go forward with your presentation, you may do so now.

DR. BENOWITZ: Yes, I would.

I would like to start out and just give a little bit of my background. I'm currently professor of medicine at University of California, San Francisco, and Chief of Clinical Pharmacology and Experimental Therapeutics, which is part of our Department of Medicine. I practice medicine at San Francisco General Hospital.

I have board certification in internal medicine, on clinical pharmacology and medical toxicology. The bulk of my research, through my academic career has been studying the effects and pharmacology in nicotine in humans. I've done work in that area for about 20 years.

That work has resulted in over 250 publications and 40 or 50 book chapters, the bulk of which have related to effects or pharmacology of nicotine in humans.

I was a scientific editor of the 1988 Surgeon General's report on nicotine addiction. I've been involved in other Surgeon General's reports on smokeless tobacco, environmental tobacco smoke, and ethnicity issues.

I've also served on the Scientific Advisory Board of EPA on their risk assessment of environmental tobacco smoke, and I recently served on the Institute of Medicine Committee that dealt with preventing tobacco or nicotine addiction in youth.

What I would like to talk about this morning is the issue of the validity of cotinine as a biomarker of human environmental tobacco smoke exposure.

This first slide is objectives. Cotinine is the main proximate metabolite of nicotine and has been widely used as a marker of environmental tobacco smoke exposure, both in smokers and in non-smokers.

The use of cotinine is a biomarker for environmental tobacco smoke exposure has been criticized, and what I would like to do is review the basis for the use of cotinine for that purpose and address various criticisms that have questioned its validity.

The objectives of my presentation are to establish that cotinine is a valid quantitative marker of the level of environmental tobacco smoke exposure; and, second, to establish that measurement of cotinine levels in human blood, saliva or urine is the most specific available marker of environmental tobacco smoke exposure.

Two: Nicotine is present in environmental tobacco smoke. Some of the background that's important before we talk about cotinine as a biomarker is some of the issues surrounding nicotine, it's parent, and its validity as a marker of environmental tobacco smoke.

It's known that the tobacco in a cigarette contains from 6 to 12 milligrams of nicotine. On average, a smoker absorbs systemically 1 milligram of nicotine, and that is almost irrespective of what the nominal smoking machine determined yield shows.

This is because individuals tend to adjust their smoking behaviors to take in a certain amount of nicotine that satisfies their nicotine addiction.

75 percent or more of nicotine in tobacco is emitted into the air as sidestream smoke, so that's 3 milligrams or more per cigarette.

It has been well shown that nicotine is present in the air in work places where there is smoking occurring, and concentrations of nicotine are much different in environments where people smoke or where people do not smoke.

Let me go on, next, to provide some of the basic parameters regarding nicotine in tobacco smoke.

Slide 3: sidestream tar to nicotine ratio is not substantially affected by a brand of cigarette.

One criticism has been that nicotine levels are not representative of levels of other tobacco toxins in ETS. It is known that ETS is present primarily in the vapor phase.

I say nicotine is present primarily in the vapor phase of ETS. There are other toxic components that are part of the vapor phase and still others that are part of the particulate phase, which has also been assessed as tar.

I think it's important to recognize that there are harmful chemicals in both phases and main culprits in causing cancer or heart disease or other injuries from environmental tobacco smoke are not known, so we really don't know which phase is the optimal.

I should also say nicotine is most likely not a major culprit in causing disease, and so nicotine is serving primarily as a marker for other potential toxins and environmental tobacco smoke.

One issue of concern is whether nicotine represents environmental tobacco smoke from different brands of cigarettes -- high yield cigarettes, low yield cigarettes, filter cigarettes, non-filter cigarettes, ventilator, non-ventilated cigarettes.

On this slide, I've summarized results of two studies that have looked at this question, where sidestream smoke was captured, and concentrations of tar and nicotine were measured in sidestream smoke.

What I have done is looked at the ratios of tar to nicotine in sidestream smoke.

I've expressed the ratio as a means. I've also shown the range for you on this slide, and the coefficient of variation.

The coefficient of variation is a term that means the standard deviation of a series of measurements divided by the mean, and this is a term that's widely used as a measure of variability. I'll be coming back to this.

In studies of Adams and Rickert, which looked at different kinds of cigarettes, the mean ratio of tar to nicotine was relatively constant, you can see the average was 5.2 in one case, 5.8 in the other case. The range is fairly narrow.

The Rickert study had one value at 8.1, but that's really an outlier. Most of the values were actually closer to the range of 5 to 6.

Most importantly, coefficient of variation is about 12 or 13 percent. This, when looking at biological measures, is quite a small coefficient of variation, and I think, by most standards, we would say that these studies indicate that sidestream smoke, tar to nicotine ratios, are comparable in different kinds of cigarettes.

In Rickert's study, he specifically looked at the correlation between tar to nicotine ratio in sidestream smoke and mainstream nicotine or tar yield, and they found no correlation.

He also looked at ventilated and non-ventilated cigarettes and found no correlation either.

So I would conclude from these data that nicotine is representative of environmental tobacco smoke generated from different brands and types of tobacco.

Next slide 4: Time-weighted nicotine exposure reflects exposure to other components of environmental tobacco smoke.

Another criticism is that the ratio of nicotine to other ETS components varies over time with the aging of smoke, and therefore nicotine is not an indicator of other components.

As I mentioned previously, nicotine in ETC exists primarily in the vapor or gaseous phase. There is evidence that nicotine and particulate concentrations decline at different rates, depending on surface material and other characteristics of the environment.

There is also a problem in that there are particulates that exist from other sources, besides environmental tobacco smoke, and that can bias ratios of nicotine to particulates, particularly at low ETS concentrations. This is something that Dr. Hammond is going to address in great detail later on.

So, in fact, if one measures at any particular point in time after single exposure, one can see changes in nicotine to tar ratio. However, people are exposed to ETS not at single points in time but over long periods, either in the work place, say over 8 hours, and what is most appropriate is to really look at time-weighted exposures which would deal with repeated generation of smoke and decline of nicotine and particulate concentrations over time.

When that is done, when time-weighted samples are used rather than point samples, there is fairly good consistency of nicotine to particulate ratios.

Slide 5: Nicotine and air sampled over time reflects exposure to other ETS components.

These are some data that were reviewed in a paper by Repace and Lowery. Again, some of these data Dr. Hammond will talk about later.

This slide shows results of three studies which looked at the relationship between respiratory suspended particles or RSP, to nicotine in the air of homes and workplaces.

The first paper by Hammond involved 47 home measurements; Meisner measured 21 workplaces, and Nagda 61, I believe, aircraft. When these air samples were taken over time, so we're looking at time-weighted averages and the relationship of RSP to nicotine is examined, there is relative consistency with a ratio that varies from 9 to 10.

Again, Dr. Hammond will talk about this later, but my conclusion, looking at this is, when the exposure to ETS is measured over time, as is relevant to human exposure, that the level of nicotine in air reasonably well represents the concentrations of other components of ETS, such as particulates.

This is Slide 5A, showing structures of nicotine and proximate metabolites.

Now that we have talked about the issue of nicotine in air as being a reasonable marker of ETS that's being present, I'd like to then go on to talk about assessing human exposure.

This slide shows the structure of nicotine in your upper left and shows the main proximate metabolic pathways. The one of concern today is cotinine. You can see that cotinine, basically, consists of having oxygen added to one of the -- to the five-member component or ring of nicotine. So that's the proximate pathway.

The other one is nicotine oxide, which is really a minor metabolite.

On average, about 70 or 80 percent of nicotine goes through cotinine, and then, as I'll show you in a second, cotinine is also further metabolized to other compounds, but it is important that, in the vast majority of people, most nicotine goes to cotinine. So it's usually between 70 to 80 percent.

This Slide 5B: These are some quantitatem metabolism data from work in my laboratory that address the fate of nicotine in a quantitative sense in humans.

The circles on the outside -- it starts with nicotine in a box in the middle, and then cotinine in the box in the middle, and then the circles on the outside are what is recovered on average in the urine, from a given dose of nicotine.

So you can see, again, about 80 percent of nicotine goes to cotinine. That is excreted, to some degree, in the urine, so about 13 percent of a nicotine dose is excreted as cotinine.

Cotinine is then converted to trans 3 prima hydroxy cotinine, which is then also excreted in the urine part and also conjugated. Cotinine is conjugated as metabolite, as is nicotine, to some degree, also.

Now, if one looks at what's in the urine, the 3 hydroxy cotinine, is the major metabolite that's found in the urine. However, there is considerable variability in the extent of metabolism of cotinine -- to 3 hydroxy cotinine -- so some people convert a lot and some people convert relatively little.

In that nicotine exposure, results of nicotine going into the bloodstream, and then liver metabolism, is most reasonable to consider the major proximate metabolic pathway as most likely being most representative of nicotine dose, so I believe that cotinine measured in the plasma is probably the best metabolic marker of nicotine intake, again, because, there's relatively a high percentage of nicotine converted to cotinine.

You will hear other speakers say that cotinine is not the major metabolite in the urine, and therefore cotinine is not worthwhile measuring. I think that that is not true. Again, I would restate that the proximate metabolite best reflects the parent and the real issue is the relationship of urinary cotinine, say, to plasma cotinine, and we'll talk about that in a minute.

Slide 6: Cotinine in various biological fluids.

Let me say, because I haven't explained this, nicotine is the main marker in environmental tobacco smoke that we're trying to measure. We don't measure nicotine as a biomarker because nicotine has got a relatively short half-life of 2 to 3 hours, such that with intermittent exposures, levels rise and fall, and so there's quite a bit of variation in the nicotine levels throughout the day.

Cotinine, as its proximate metabolite, has a half-life averaging of about 16 hours, so it is formed from nicotine and then tends to persist for a long period of time and basically gives an integrated value offer previous nicotine exposure.

That's the reason by cotinine has been widely used as a marker of tobacco exposure. Cotinine levels are relatively constant over time.

These are some representative data. There are many studies, and I have chosen this study of Jarvis in the U.K., where nicotine levels were measured by gas chromatography, which is a specific assay, and here are reported mean concentrations in nanograms per milliliter of cotinine and plasma, saliva, and urine.

He studied 94 smokers, 54 non-smokers with environmental tobacco smoke exposure, and 46 non-smokers without environmental tobacco smoke exposure.

If you look at your right-hand column, the values start with plasma. Smokers, more than 100 times that of non-smokers in general. So it's clear that cotinine can distinguish smokers by nonsmokers.

If you then compare nonsmokers with ETC exposure and without, there's also about a 2-fold difference here. So there are significant differences looking at mean values, between people with ETS exposure that's self-reported and without.

A number of studies have shown that plasma cotinine concentration is responsive or is increased in people who have a history of ETS exposure compared to those who don't.

Salivary concentrations are also shown here. Saliva is a widely-used marker because saliva is easier to get. It's not invasive.

A number of researchers have looked at the ratio of cotinine and saliva and plasma, and have shown that they're pretty well correlated with correlation co-efficients of .9 or greater, and salivary concentrations tend to be slightly higher than the plasma concentrations, but they are approximately the same.

It is assessed for two reasons.

One is that it is not invasive, and two is that the concentrations of cotinine are higher in the urine than in plasma, so it's easier to measure urinary concentrations.

In general urine concentrations are about five to six times greater than plasma concentrations. There is some degree of variability expected on the basis of urine flow rates, and perhaps urinary pH to a small degree, but again, in Jarvis' study where he looked at the correlation within individuals of plasma to urine concentrations, he found that there was an excellent correlation.

So you will see studies that report urine concentration, saliva concentration, or plasma concentration of cotinine as markers of environmental tobacco smoke exposure, and these are the general parameters that we'll be looking at.

What I would like to go on to now are some of the pharmacokinetic issues used in translating a cotinine level to a particular intake of nicotine from environmental tobacco smoke, and so I'd like to spend a little time talking about pharmacokinetics.

Slide 6A is a beaker model of human pharmacokinetics. What I'd like to do is to represent the human body, for simplicity sake, as a beaker that has a certain volume of fluid in it, and this volume can be thought of as the blood stream, or the blood stream and body tissues in which a drug is dissolved or binds.

On the top panel you can see that if you dose a certain amount of drug with that syringe, put it into this beaker, mix it up very well, and then take a sample from that beaker to measure the concentration, the concentration will be stable, because you put it in, and there's none leaving.

If you look at a concentration over time, you would get a curve, as shown on your upper right which basically shows a concentration is flat over time. So that would be a situation where there is no drug metabolism or clearance. Now the body does have mechanisms for getting rid of drugs.

The pharmacokinetic process of getting rid of drugs has been termed, "clearance," and clearance is, in effect, a spigot function. You can see on the bottom curve that there's a beaker that has a spigot, and a certain amount of fluid drops through that spigot, and if we assume that this is a recirculating spigot, so that all the fluid goes back into the volume so that the volume does not change, and if we also assume that whatever comes through that spigot is totally cleansed of drug, so that's the drug elimination pathway, then the flow rate through that spigot is the term that's called clearance.

In a sense, it's the volume of blood that's flowing per minute, say in milliliters per minute, of blood that's cleansed of a drug, and that's the term that we use to explain metabolic rates of drugs, we talk about clearance of a drug.

Now clearance is not the same thing as elimination rate; you'll see why that's important later on. If you wanted to know how many milligrams of drug is being eliminated from this beaker, what we would do is to measure the concentration of fluid in the beaker, then measure the spigot flow rate, and then multiply the two together, so that so many mils per minute of fluid or blood are being cleared, and each mil contains "X" number of nanograms or micrograms of drug, and therefore the total elimination rate would be micrograms or nanograms per minute.

The elimination rate is a product of this clearance times the concentration. I don't have a slide here to show this, unfortunately, but another critical concept is that of steady state.

Say instead of giving a single does into the beaker with the syringe, you constantly drip a certain amount of drug into the beaker over time, and you keep on dripping in so that levels in the beaker will rise and rise and rise, and at a certain point, they become constant.

They become constant when the rate of the drug going in is the same as the rate of the drug going out, which means that the dosing rate is equal to the elimination rate, which I said was equal to the product of the clearance times the concentration. That steady state, and I'll come back and emphasize this again, has three factors that are operative only.

It's really the dosing rate, the concentration, and the clearance rate. Any given concentration at steady state is determined only by the dosing in rate and the clearance rate out. It doesn't matter what the volume of this beaker is or any other characteristics. So that's an important steady state concept. And I'll explain more in a few minutes about why that's important.

Slide 6B shows the concept of half life, which I'll be talking about as well. If you go back to this beaker, and you give a certain dose of the drug, you allow clearance to occur, and you measure levels over time, you'll see as you see in the curving line that these levels will decline or fall over time.

If you were to plot it on a logarithmic scale, which is in your upper right-hand corner, you'll see that this line becomes straight. This straight line on a logarithmic scale means that a given percentage of the drug in the body is eliminated for any given fixed interval of time, which means, say we talk about half life.

Half life is the time it takes for half the drug in the body to be eliminated. So say if the half life for cotinine is 16 hours, that means that once you have a certain amount of cotinine in the body, it takes 16 hours for half of it to be gone, 16 hours for half of that to be gone, and 16 hours for half of what's left to be gone, etc.

So half life gives us some idea of how fast the body gets rid of a drug and also gives us some information of accumulation of a drug.

Slide 7: Pharmacokinetics of nicotine and cotinine are similar in smokers and nonsmokers. We know a lot about nicotine and cotinine kinetics and metabolism in smokers, and a concern has been raised about the comparability of nicotine and cotinine metabolism in smokers versus nonsmokers.

This is important if we're going to use some of our knowledge about smokers to apply to nonsmokers. Some early reports using small doses of radioactive nicotine suggested that there were different rates of metabolism, such that smokers metabolized nicotine faster than nonsmokers.

We have done quite a bit of work in this area, and our approach has been quite different from that used previously. We have wanted to study metabolism of nicotine and cotinine in smokers while they're smoking, as well as nonsmokers.

What we have done is to synthesize deuterium labeled nicotine and cotinine, so that's a non-radioactive stable isotope. We've shown in preliminary experiments that these labeled nicotine and labeled cotinine are metabolized in exactly the same way as natural nicotine, and I should say that our experiments with l-nicotine, which is natural nicotine, the sort that's found in tobacco.

I will also point out that some of the early studies with low doses of radioactive compounds used d&l-nicotine, racemic nicotine, so it has some of the unnatural nicotine.

We know from other substances, as well as from cotinine itself, that d&l-nicotine and cotinine may be metabolized at different rates, so I really don't think those studies are representative of humans.

In any case, in our experiment we looked at smokers and gave infusions of labeled nicotine, and we gave them infusions at two doses: We gave them a dose comparable to what they might get from smoking cigarettes, and then we gave them a very low dose, a dose would be the same as what we could give safely to nonsmokers, and then looked at a variety of pharmacokinetic parameters, as shown in this slide.

We looked at half life, volume of distribution, which is sort of the space or volume of the fluid and tissue inside the beaker, and total clearance.

We found that the half life of nicotine in smokers was 157 minutes, and 122 minutes in nonsmokers. The volumes were basically the same. The clearance was actually slightly faster in nonsmokers, at 1319 mils per minute versus 1085 mils per minute in smokers.

These values are pretty close, but most importantly, they're totally different from the earlier studies of Kyerematen, which suggested that smokers metabolized nicotine much faster, and I'll explain why I think it's different in a moment.

I would say that for practical purposes nicotine is metabolized and handled in a very similar rate in smokers and nonsmokers. I can't show you the same exact set of data for cotinine, but I can give you results of other data where we've infused cotinine to smokers and nonsmokers and basically found that half life is almost identical and that clearance is very similar.

I would say that two other investigators have looked at cotinine clearance rates in smokers and nonsmokers, and they all seem to be pretty much the same. So from my data and those of some of the other investigators of cotinine, I conclude that there are minor differences if any in the clearance and metabolism of nicotine and cotinine in cigarette smokers and nonsmokers.

Now the question is why would the early Kyerematen data have shown a much longer half life in nonsmokers? I can't say for sure, but one factor certainly is the fact that they were using unnatural nicotine, which is not appropriate for tobacco studies.

The second thing is that they used very low doses, and in nonsmokers, there may be dose-related binding of nicotine to certain body tissues which then gets slowly released, and so a long half life of nicotine might be due not to a difference in metabolism but slow release in body tissues. I believe that their data do not accurately reflect clearance and really are looking at probably distributional funny.

Another issue which I can't show you data on yet, but we'll have some data soon, is the pattern of metabolism of nicotine and cotinine in smokers versus nonsmokers.

As I've said before, 70 to 80 percent of nicotine is converted to cotinine. If there's concern about the use of cotinine in nonsmokers, it would be that cotinine is somehow overestimating the exposure. So the concern you would have in terms of metabolism is do nonsmokers make more cotinine from nicotine and therefore overestimate cotinine.

But when you're starting from 80 percent, the maximum you could go is from 80 percent to 100 percent, which is not likely, because other people have measured metabolites in nonsmokers and have shown that there are other metabolites, nicotine as well.

So the maximum error that could play a role if patterns of metabolism are different would be about 20 percent, which would not create any substantial error.

I think that the metabolism of nicotine and cotinine is likely to be quite similar in smokers and nonsmokers. The pharmacokinetics are similar, and therefore, we're justified in using data from smokers to do dose estimations in nonsmokers.

Slide aL: I just want to show you an example of some of the data from our study in smokers and nonsmokers that I've just described. These are blood levels of labeled nicotine that were given by intravenous infusion.

The solid circles are smokers, the open circles represent nonsmokers. If you look at the low dose where smokers and nonsmokers got exactly the same dose, those are the lower two lines, you can see that nicotine levels are virtually superimposable in smokers and nonsmokers. So there's no evidence whatsoever that they handle nicotine in a different way.

Slide 8: At steady state, the blood concentration is determined by exposure rate and clearance.

One of the assumptions that we'll be making in interpreting cotinine values is that cotinine levels represent relative steady state levels with steady state exposures.

Again, let me go back to this key concept. At steady state, as shown on the top line of this equation, the "d" which is the dosing rate is equal to the elimination rate.

That's the definition of steady state: what's going in is what's going out. We know that elimination rate is equal to the product of the clearance times the blood level at steady state.

If we rearrange this equation, which is shown on the bottom of this slide, you can see that a blood concentration at steady state is determined only by two factors: by the dosing rate, and by the clearance.

Slide 9: Prolonged half life after low-level exposure does not affect the validity of the use of cotinine in steady state exposure conditions.

Now, the reason why I've made such a big point about the steady state business deals with a criticism that the elimination rate of cotinine in nonsmokers after particular exposure to nicotine is longer, substantially longer, than that which is seen in smokers.

Therefore, the claim has been made that measuring cotinine in nonsmokers would overestimate nicotine exposure. Well, that is not true at steady state.

As I've said before, one explanation for this funny could be that with a single dose in a nonsmoker, there is avid binding to body tissues and very slow release, and that could produce a long half life, which is not elimination determined, but actually released from body tissues.

At steady state conditions, as would be the case with regular ETS exposure in the workplace, the relationship between exposure rate and blood concentration is determined only by clearance, not by tissue binding, and the data showing very long half lives after a single exposure in nonsmokers are totally irrelevant.

They do not reflect clearance, they do not reflect the dose-concentration relationship, and those data have no bearing on the assessment of steady state exposures.

Slide 10: Cotinine is a quantitative biomarker of daily nicotine intake. I would like now to consider the quantitative aspects of cotinine as a biomarker, and the question of inter-individual variability. Now the details behind the derivation of the equation, as I'm going to show you, are in my statement, so I won't bore you more than I have already with these pharmacokinetic issues by explaining them all, so I'm going to show you the first and last parts.

The basic assumption is that at steady state, the generation rate of cotinine, which is generally how much cotinine is being generated from nicotine in the body per time, is equal to the dosing rate of nicotine, how much nicotine is being taken in per time, times the percent of conversion of nicotine to cotinine.

In other words, you get a certain amount of nicotine in, a certain percent gets converted to cotinine, and if you know those two factors, you know how much cotinine is entering the body per unit of time. What we want to find out by the use of a biomarker is the intake rate of nicotine.

So we need to know two things for that:

The generation rate of cotinine and we need to know the percent conversion of nicotine to cotinine. In studies we've been doing in large populations, we've been giving labeled nicotine and cotinine simultaneously to two people, and by doing that, you can calculate the percent nicotine to cotinine. So we have that number in a lot of individuals.

We can figure out the clearance rate of cotinine by giving cotinine and measuring blood levels, and then we can measure the cotinine level in that individual, and then we can calculate the generation rate of cotinine. From these pharmacokinetic principles, we can then calculate the intake rate of nicotine.

Intakes, slide 5: If you go through a number of calculations, which are in my statement, the final equation which comes up, and these are based on studies of 20 smokers, you can come up with an equation which says,

"The daily dose of nicotine is equal to its conversion factor of 0.08 times the steady state blood cotinine concentration and nanograms per mil."

So this conversion factor .08 is the only pharmacokinetic factor you need to have to look at the relationship between nicotine intake and cotinine levels.

So you don't need to know anything about urinary metabolite ratios, as other people will talk about. You don't even have to know about separate out clearance versus fractional ingrosion nicotine ecodine because this factor contains it all. I'll talk about the variability in this factor in a minute.

But if you know this factor, and you know a steady state cotinine concentration, you've got your nicotine intake.

An example of the use of this factor in smokers: A typical smoker who is smoking about a pack of cigarettes a day would have a cotinine concentration of 300 nanograms per mil. Using this factor, it comes out to a daily dose of 24 mg or a little more than a milligram per cigarette, which is what we know from other studies is about right.

Say we take an ETS-exposed nonsmoker who has a plasma cotinine concentration of 1 nanogram per mil, we go through the same equation which gives us a daily dose of 80 micrograms per 24 hours.

I'll come back again, because I'm going to use this 80 micrograms as a general guideline for the amount of nicotine that an average ETS-exposed person will take into their body per day. So I'll come back to that 80 micrograms.

Slide 12: ETS exposure could be considered to be a steady state condition with regards to cotinine measurements. The question is how valid is the assumption that I've made that cotinine levels reasonably reflect steady state. Well, the factors are as follows.

ETS exposure in the workplace typically occurs for eight or nine hours per day, five days per week. The duration of ETS exposure at home may be of even longer duration.

As I mentioned before, nicotine levels in the body rise and fall after particular exposures owing to a relatively short half-life of nicotine. However, nicotine is converted to cotinine in the body, and cotinine levels persist for a long time, owing to its long half-life of about 16 hours.

Therefore, even intermittent daily exposures to nicotine will result in cotinine levels that are relatively stable and fluctuate by only 20 or 30 percent throughout the day. One can conclude that average cotinine levels reasonably represent a steady state exposure condition.

Let me show you some examples of what I'm talking about.

This is Slide 12A. These show plasma nicotine concentrations on the top panel with people smoking cigarettes, and you can see that with each cigarette there is a rise in nicotine levels and a fall in nicotine levels, and that they bounce up and down. So if you were to try to measure nicotine levels at any particular time, it would be hard to estimate the overall exposure because of that variability.

This is Slide 12B. These are data taken from some of our studies where people were allowed to smoke their own cigarettes throughout the day as they wished, and we measured cotinine levels at various times over 24 hours.

Now the scale here is not a scale from zero; it goes from 200 to 450 nanograms per mil. The solid line is the average cotinine measure at different times during the day. The dash line is 95 percent confidence intervals. You can see that even though nicotine levels are spiking up and down all day long, cotinine is sort of an integrated measure, and it only varies from 20 to 30 percent throughout the day.

I think it's reasonable to use something like cotinine as an integrated measure and to make an assumption, although it won't be perfect, that this represents a steady state exposure.

Slide 13, Variability and Biological Measurements: Another criticism that has been made, and Dr. Jeffrey Idle will be talking about this later and will be offering a criticism, that individual differences in rates and patterns of nicotine metabolisms severely compromise the utility of cotinine as quantitative biomarker. So let's talk about variability in general first.

As I said, a common measure of variability is what's called, "coefficient of variation," which is a standard deviation divided by the mean. What are some coefficient of variation that we typically encounter? Well, an excellent chemical assay may have a coefficient of variation of five percent.

An acceptable chemical assay may be ten percent. In pharmacokinetic parameters, the average is probably about 30 percent, with a range of eight percent to about 40 percent, in one study. If we look at pharmacodynamics, which are parameters that relate the concentration of a drug in the body to its effects, we see much more variability, with coefficient of variation of 70 percent.

Now the main factor that I was talking about, this conversion factor from cotinine levels to a dose of nicotine, was measured in about 20 subjects, and there's a coefficient of variation there of about 22 percent. So that gives you some perspective. Now I'd also like to make another point, which is relevant to variability in population studies; that is, any biological marker is going to have variability.

Even if the variability is considerable, when you do large population studies, the reason you do this is to average out the variability. So the mean of a large sample reflects pretty well the mean of the true population, assuming that you've sampled representatively. So even if there is variability in measures like this, the use of large samples balances out variability, and what you see as the final results provides a pretty good signal for population data.

So I think that even if one concludes that it's difficult for an individual to predict with certainty that nicotine intake based on their cotinine levels, if you look at a number of individuals, those estimates are pretty good.

Slide 14, Variability in Cotinine Conversion Factor Compared to Other Drug Kinetics: For our purposes, the only kinetic parameter of importance is this conversion factor, which incorporates both the rate of cotinine metabolism and the percent conversion of nicotine to cotinine. Its variability in 20 subjects was 21.9 percent.

I then listed the variability in clearance from a number of drugs from a recent paper by Levi, and you can see that the variability is quite wide; on average, it's about 30 percent, with a range of eight percent to 40 percent. So our cotinine conversion factor has pretty good limits of variability compared to most other pharmacokinetic parameters. And this is true for anything that you would use as a biomarker.

So the question is, if the concept of a biomarker can exist, then one has to accept the fact that there's going to be a certain amount of variability associated with assays and associated with kinetics, and I think that cotinine does about as good as you could expect any biological substance to do.

Slide 15, Air Levels of Nicotine from ETS and Predicted Cotinine Levels in Biological Fluids, Number 1: What I'd like to next is to use these pharmacokinetic parameters that I've developed to make predictions about cotinine levels in biological fluids after particular environmental exposures, and then we'll go on to talk about the relevance of sources of nicotine other than environmental tobacco smoke.

JUDGE VITTONE: Excuse me, Dr. Benowitz, how much longer?

DR. BENOWITZ: I would say 30 minutes.

JUDGE VITTONE: 30 minutes. Okay.

DR. BENOWITZ: So here what I'd like to do is to go through some calculations of going from an air level of nicotine to what to expect from cotinine in a biological fluid.

For the purposes of calculations, I'm going to start with a figure of a typical air workplace nicotine of 20 micrograms per cubic meter from Coultas. I realize that other data, and Dr. Hammond will present some of this, give the average exposures in offices of closer to about eight or ten, so we can certainly keep that factor of two in mind.

A typical ventilation rate for an adult during light activity is a cubic meter per hour. One can estimate the intake of nicotine by taking the product of air nicotine concentration and ventilation rates, that's basically how much a person is taking in, so that would be 20 micrograms per hour.

There is evidence that about 71 percent of nicotine that is inhaled is absorbed. If we assume an eight-hour workplace exposure, then the daily dose, and this is shown on the slide, comes out to about 112 micrograms per day. That would be what one would expect from eight-hour exposure.

Slide 16, Air Levels of Nicotine from ETS and Predicted Cotinine Levels in Biological Fluids, Number 2: If we start with this daily intake level of 112 micrograms, and then we use a conversion factor of 0.08, you can see that the blood concentration would be the dose divided by the conversion factor, or a blood level would be 1.4 nanograms per mil.

The urine concentration would be about six times that, so the urine concentration would be 8.6 nanograms per mil. The blood concentrations values are very similar to those that have been measured in people with ETS exposure, and the urine concentrations are very similar to those that have been measured in people with ETS exposure. So these parameters all fit in very nicely with the empiric data that is available.

Now, I'm going to talk about other potential sources of nicotine besides ETS, so I want to use a couple of parameters.

One parameter is that an average to moderate ETS exposure is 80 micrograms per 24 hours, and an urine level of about six, and a plasma level of about one. Let's look at what other sources of nicotine could do to those sorts of levels.

On Slide 17, Nicotine Content of Foods: It has been claimed that dietary nicotine exposure may confound measures of cotinine as a marker of ETS exposure. And it's well known that there are low levels of nicotine in certain foods. This slide is basically a summary of what's been published in four studies, giving concentrations and nanogram of nicotine, that is, a millionth of a gram of nicotine per gram of vegetable or substance.

You can see that it's present in cauliflower, eggplant, potatoes, tomatoes, and some teas. Taking these concentrations and then figuring out what intake, using the pharmacokinetic parameters that I've just provided, would be provided to give you say a urine level of one nanogram per mil, which might be a threshold for nonexposed or exposed persons, although it's actually about one-sixth of a level of a moderately person, so that's a lower limit which would be comparable to an intake of 13 micrograms.

So you would have to consume several pounds of cauliflower, 130 grams to an infinite amount of eggplant, several pounds of potatoes, a half a pound to several pounds of tomatoes to get this level of one-sixth of a moderate ETS exposure level.

So you can see that just taking from this slide that it's not very likely that adequate amounts of these amounts of these foods would be consumed to falsely indicate substantial ETS exposure.

Slide 18, Estimates of Dietary Nicotine as a Source of Urinary Cotinine from Davis et al.: One specific study has claimed that food may produce urine cotinine levels resembling that of ETS exposure.

So I'd like deal with this in detail, because you will hear about this from other people later on. On this slide are data of assumed daily intake, and these are from some dietary intake source, and so there are average consumption data for tomatoes, potatoes, cauliflower, and black tea, and then there are also maximum, the most that anyone would ever consume.

Below the average is the estimated nicotine intake in micrograms, and then the estimated urinary cotinine concentration.

Now the urinary cotinine concentration is problematic in terms of the calculations, and I won't talk about that, but let me just point out a few salient points.

For the average consumption, the intake of 8.8 micrograms of nicotine per day would assume intake of all of these things every day to provide a steady state level of cotinine that would be comparable to an intake of 8.8 micrograms per day. Very few people eat tomatoes, potatoes, cauliflower, and black tea in these quantities every single day.

A second thing is that even if they did, these nicotine levels are less than one-tenth of that seen with moderate ETS exposure, so even if someone consumed this stuff every day, their intake would be less than one-tenth of what they'd get from moderate ETS exposure in the workplace.

Now the maximum consumption is phenomenal: Two pounds of tomatoes, three pounds of potatoes, two pounds of cauliflower, and four quarts, a gallon of tea a day. Now is that likely? Not very likely. Look at their levels. Certainly a level of 99.9 micrograms of nicotine would be consistent with ETS, and I have no problem with that. The urine concentration figure is somewhat curious.

This urine concentration is based on urine output of one liter per day, which is the standard urine output of a human. But how many of people can drink four quarts of tea and put out one liter of urine? Not very likely; you're likely to put out closer to four liters, which means that this urinary cotinine concentration would be a quarter of what it is here, which would again bring it well below that from ETS.

I conclude that yes, there is some nicotine in food, and this undoubtedly explains very low levels of cotinine that are found in people without ETS exposures; however, the nicotine in food with any reasonable estimates of food consumption are not likely to confound ETS exposures; they're just too small. So this is a trivial contribution, and I don't think it's relevant to our considerations.

MR. GOODMAN: Pardon me, could you please give us the number of that chart?

DR. BENOWITZ: This is Chart 18. Sorry. Some examples or some other data to amplify this is contained in Slide 19, Median Serum Cotinine Levels According to Tea Consumption.

This is from a Scottish study published in 1991 by Pedoe who looked at over 3,000 people, not nonsmokers, and looked at tea consumption. This slide shows very clearly if you look at daily cups of tea and look at serum cotinine concentration, there was no relationship.

It's been argued that these people didn't drink the right kind of tea. Well, that's possible; I guess there may be some particular kind of tea, but in general, 3,000 people drinking lots of tea in England, there was no relationship between cotinine levels.

Slide 20, Median Serum Cotinine Levels According to ETS Exposure: The same study. When you look at ETS exposure, there is a robust relationship between serum cotinine and ETS exposure.

So the same study which showed no relationship between tea exposure showed a very robust relationship between cotinine levels and ETS exposure, again indicating that ETS is a far greater signal than dietary factors are likely to be.

Slide 21, Nicotine Emissions from the Environment Are Trivial as a Source of Human Exposure to Nicotine: Another criticism has been that exposure to nicotine vapor in the absence of other ETS components can occur, and this may confound estimates of ETS exposure.

There is evidence that nicotine from earlier environmental tobacco smoke presence may emit from room surfaces or be present in house dust. Nicotine may emit from the clothing of smokers.

It has been suggested, therefore, that nicotine exposure by nonsmokers may reflect such emissions rather than direct ETS exposure. Let me say that it's been very difficult for me to find data on this.

The only data that I could find that seemed relevant to this consideration was one figure by Dr. Nelson by R.J. Reynolds who showed basically that room concentrations of nicotine in the air after a given exposure and from one to five days after the exposure, the levels in the air range from 0.7 to 0.2 micrograms per cubic meter of air.

If you go through the same calculations we've previously done with workplace air nicotine levels, you would estimate a daily intake of nicotine of about one to four micrograms as compared to 80 from ETS, and a urinary concentration of 0.1 to 0.3 nanograms per mil.

These levels again are very trivial compared to that which would be expected to be derived from workplace ETS exposure.

My conclusions from the food studies and from these studies are that neither food nor emissions from rooms are significant sources of nicotine, compared to environmental tobacco smoke, and most cotinine in biological fluids in those people who have had ETS exposure derives from that exposure.

JUDGE VITTONE: Dr. Benowitz, you've been talking for one hour now. Would you like to take a short break before you conclude?

DR. BENOWITZ: Well, I'm almost finished, so I'd just as soon finish, if that's okay.

JUDGE VITTONE: Okay, let's go ahead. That would be good.

DR. BENOWITZ: On Slide 22, Analytical Chemistry Issues in Measuring Cotinine After ETS Exposure:

It has been argued and will be argued later, I'm sure, that there are no standard measures for determining nicotine and cotinine levels in biological fluids and therefore the reported values are invalid. Well, it is true that cotinine levels in ETS-exposed individuals are low and that measurement is technically demanding.

Two general types of analytical techniques have been used:

There's chromatography, there's gas chromatography, HPLC, and GC mass spectrotrometry, so those are one type of technique which are very specific and very sensitive.

Then there's been nonspecific technique of radioimmune assay, which using an antibody. One thing which does seem to be clear that for many radioimmune assays, the values tend to be higher than those measured by gas chromatography and GC mass spec, and this is most likely because the RIA is detecting metabolites.

In one comparative study that we have recently done, however, we had the same samples of passive smoke exposures in urine and compared GC mass spec done in our lab and RIA done in a second lab, and the curves were basically parallel, with the RIA shifted upward, meaning the RIA is probably picking up other metabolites, but it still is a pretty good relative signal.

If one looks at various publications, one can see that regardless of the technique, most researchers find increasing cotinine levels with increasing ETS exposure, and therefore, relatively speaking, ranking or categorization is valid if you're using RIA and comparing subjects by that measure, or using chromatography and comparing subjects by that measure.

Slide 23, Physiologic Models Are Not Necessary for Estimation of Daily Nicotine Intake from Cotinine Level:

This would actually be Slide 22A. Some researchers have developed physiological pharmacokinetic models to examine the kinetics of nicotine and cotinine and argue that such models are necessary to quantitate exposure, and I would argue that that is not true.

Let me spend a moment to show you that this is a sample or a picture or a cartoon of what a physiological model means. So physiological model basically divides the body up into different compartments which have a certain mass.

Say you have a brain compartment that weighs so many grams and a heart compartment and a muscle compartment, etc. Then it gives each compartment a blood flow, which you can know from ordinary data from human physiology studies, and then it gives a sort of a tissue uptake partition coefficient number.

One can solve a number of simultaneous mathematical equations and generate curves of the predicted levels of different drugs in each organ over time, so that's a physiological model. These are data from our simulations of nicotine physiological models, which is, by the way, Slide 22B.

You can see that we modeled 1.5 milligrams of nicotine given into the lung over ten minutes, which would be like smoking a cigarette, and you can see concentrations in the lung rise and fall and brain levels fall and arterial levels and venous levels and muscle levels.

You can see changes in concentration over time. This sort of model is particularly useful if you are measuring something that has toxicity in a particular organ, and you want to know what that organ exposure is like over time. This would be relevant if we were saying that nicotine was the cause of lung cancer, or that nicotine was the main cause of heart disease from ETS. However, we don't know that.

What we know is that nicotine intake reflects exposure to other components to ETS. So we don't need to know what the nicotine levels are in various body tissues. These are not necessary for estimation of daily nicotine intake from cotinine levels. So to recap, the use of physiological models will generate levels of nicotine and cotinine in the various body organs over time after a given exposure.

However, at steady state, which is the condition we're most concerned about, levels of nicotine or cotinine are totally independent of levels in particular organs and their change over time.

If you're interested only in intake, then you don't need to know what the levels are in various body tissues. All you need to know is what the clearance rate is for that drug, and what the concentration is at steady state, which will give you the dose.

In terms of dose estimation, there is no benefit whatsoever to physiological modeling. The only importance of physiological modeling is if you're trying to relate the concentrations in some particular organ over time.

Finally, the proposition that cotinine is a valid, quantitative marker of ETS exposure would be supported by finding significant relationships between health effects that are suspected to be related to ETS and cotinine levels and biological fluids. I would like to present three studies quickly that deal with that issue.

Slide 23B: These are data from a study on Matsunga and co-workers, and I was involved in it because we measured cotinine levels. This study looked at a series of nonsmokers and looked for a biological effect that's known to be affected by cigarette smoking.

So what was looked at was the metabolism or the clearance rate of theophylline, which is an asthma medicine that is related in structure to caffeine.

It is known that smokers metabolize theophylline faster than nonsmokers, so what we did is looked at nonsmokers and measured cotinine levels and measured their theophylline clearance.

In these studies, the diet was controlled, so there were no other factors we could identified that would be influencing theophylline metabolism. We found as shown here that if you look at plasma cotinine concentration versus theophylline clearance, there was a good correlation, and we found the same thing with urine cotinine concentration.

So here it did seem that there was a relationship between a cotinine level and a biological effect.

Slide 24, Risk of Middle-Ear Effusion in Seven-Year Old Children As Related to Saliva Cotinine Concentrations: These are data of Strachan et al. from England looking at 736 seven-year old children and the prevalence of middle-ear effusion and measuring salivary cotinine concentrations, which are expressed in this slide by quintal or by fifths.

You can see with the higher cotinine concentrations, there is a higher risk of middle-ear effusions, which is one of the known risks in children with ETS exposure. It does seem that cotinine is giving some quantitative relationship showing increased risk of a biological effect with higher concentration.

Slide 25, FEF-75 in Seven-Year Old Children As Reduced in Relation to Salivary Cotinine Concentrations: By the same author in a population of 770 children who had pulmonary function tests, this lung function test which is a certain marker of airway function was reduced in proportion or was more reduced in children who had higher cotinine levels, again indicating that a higher cotinine predicts a higher biological effect from ETS.

Slide 26, Potential Biomarkers of ETS Exposure: Thus far we have focused on nicotine and cotinine as biomarkers of ETS exposure and have concluded that in general cotinine functions well in this way.

One other question is that is this the best available biomarker?

This slide gives a number of potential biomarkers of ETS exposure. I will not go through all of these, but let me just point out a couple:

Carbon monoxide, for example, is well known to be present in tobacco smoke. CO levels are higher in smokers compared to nonsmokers, but there are other sources of CO in the environment, as well as the body's own metabolism, and therefore, CO is not specific and is relatively insensitive to low-level exposures. Fiacyoniate is a breakdown product of cyanide in the body and has the same problems on nonspecificity and insensitivity.

Aducts are various toxic compounds to body proteins and DNA and have been shown to be increased in smokers.

They are insensitive in terms of passive smoking; in fact, all of the measures on this list, although they may be able to differentiate smokers and nonsmokers, are not sensitive enough to look at environmental tobacco smoke exposure.

The last one is of some interest. Salanasol is a component of the particulate fraction, and it has been suggested to perhaps be the best marker for particulate exposure. The problem is, so far as we know, salanasol is rapidly and extensively metabolized and really cannot be measured, at least so far, in human biological fluids. Despite its limitation, cotanine is by far the best available biomarker of ETS exposure.

I'd like to wrap up now.

Slide 27 is National Research Council Criteria for Valid Markers of ETS Exposure. In its report on ETS which was, I think, in 1986, the National Research Council proposed four criteria for valid markers of ETS exposures. Let me go through these and comment on cotanine.

The first one is that it should be unique for ETS, so that other sources are minor in comparison. Certainly, there is nicotine in food, we talked about that, and there may be a certain amount of nicotine in room emissions, we talked about that. However, these sources are clearly minor in comparison to ETS, and so cotanine as a marker does satisfy that first criterion.

The second one is that it should be easily detectable. With current analytical technology, this is true. There have some problems in the past, but I think this has been resolved.

The third criteria is that it should be emitted at similar rates for a variety of tobacco products. I've shown you some data early on from a variety of types of cigarettes, and it seems that nicotine is emitted at a comparable rate.

The fourth criteria is that it should have a fairly constant ratio to other ETS components of interest under a range of environmental conditions encountered, and I think that when we sample over time that nicotine does meet that criteria.

Slide 28: Conclusions - I: Nicotine in the air is derived only from tobacco smoke. Low levels of nicotine may be present in the room deriving from emissions from room surfaces or house dust due to previous smoking or clothes of smokers; however, these levels are trivial compared those levels derived from ETS.

Conclusions - II: Human exposure to environmental tobacco smoke results in the intake of nicotine into the body of nonsmokers where its approximate metabolyte cotanine can be measured in plasma, saliva, or urine.

Conclusions - III: The environmental tobacco smoke generated by different brands of cigarettes generates similar levels of nicotine when normalized for generation of particulates or tar.

Slide 29, Conclusions IV: There are small amounts of nicotine in certain foods, but within typical consumption limits, food is an insignificant source of nicotine compared with environmental tobacco smoke exposure.

Conclusions - V: Nicotine is extensively converted within the body to cotanine.

Conclusions - VI: Cotanine can be measured in blood, saliva, and urine. Some variability in various assays for low levels of nicotine has been reported; however, most studies have reported consistent differences between people with and and without ETS exposure and an increase in cotanine levels with the increasing levels of exposure.

Slide 30, Conclusion 3, Number VII: Cotanine levels are a valid quantatitive marker of intake of nicotine from environmental tobacco smoke as demonstrated by positive relationships between self-reported exposure dose versus cotanine levels and correlations between air concentrations of nicotine in ETS and measures of cotanine in urine of nonsmokers.

Conclusion Number VIII: Although proportions to other compounds in ETS vary over time and may influenced by the environment, cotanine levels provide the best currently available quantatitive measure of average ETS exposure over time.

Conclusion Number IX: Cotanine levels in nonsmokers have been correlated to the risks of environmental tobacco smoke-related health complications in children, supporting the idea that cotanine levels quantitatively predict ETS exposure. That's all for my comments, thank you.

JUDGE VITTONE: Thank you, Dr. Benowitz. Let me ask the reporter...his statement should be Number 29, is that right? Okay. Dr. Benowitz' testimony will be Exhibit 29 plus the slides. Do you have copies of the slides available for the reporter?

DR. BENOWITZ: Most of them, I do, a few, the pictorial slides, I'll have to send you in a few days, but I've got all the text slides.

JUDGE VITTONE: Okay, if you could do that, the ones that aren't there, if you could provide them within the week, we would appreciate it.

DR. BENOWITZ: Yes I will.

JUDGE VITTONE: Okay.

MS. SHERMAN: Dr. Benowitz, when you send the slides, could you please mark them with the number that you gave them in the lecture?

DR. BENOWITZ: Yes I will.

JUDGE VITTONE: It is now 11:00. Let me ask for an indication of who has questions for Dr. Benowitz. Could you please stand, first of all. Okay, you're a new person to me, sir, what's your name?

VOICE: (Inaudible)

JUDGE VITTONE: And how long do you think you're going to be? And Mr. Rupp? An hour and a half? Wow. Anybody else? I see nobody else standing. Okay, let's take a short recess, and we'll come right back.

(Exhibit No. 29 was marked for identification and received into evidence.)

JUDGE VITTONE: On the record please. We will resume with the examination of Dr. Benowitz. Mr. Grossman, I guess you're going to go first, and then followed by Mr. Rupp, and then Wooscheck will be third. If we can proceed then.

MR. GROSSMAN: Thank you very much, Your Honor. Dr. Benowitz, my name is Ted Grossman, it's very nice to meet you. ETS is not a simple component; it's made up of a number of components, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: It's a complex mixture.

DR. BENOWITZ: Yes.

MR. GROSSMAN: Nicotine is only one component of that mixture.

DR. BENOWITZ: Yes.

MR. GROSSMAN: And as you said, nicotine is not the principal culprit believed to be responsible by some researchers for reported levels of disease from exposure to tobacco smoke, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Now, cotanine is a metabolite of nicotine?

DR. BENOWITZ: Yes.

MR. GROSSMAN: The only reason for measuring cotanine is that it's related to nicotine as it's metabolized?

DR. BENOWITZ: Yes.

MR. GROSSMAN: The only reason that you have for measuring nicotine as a marker is as a marker for total ETS exposure.

DR. BENOWITZ: Yes.

MR. GROSSMAN: You're not measuring cotanine simply to determine the level of nicotine, but you're measuring cotanine in order to determine as you see it the entire level of ETS exposure.

DR. BENOWITZ: Yes.

MR. GROSSMAN: Now, if the ratio between nicotine and the other many particles and components of ETS were not constant, the relationship between cotanine and ETS exposure would not be constant, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: All right. In fact, the relationship between nicotine and other ETS components is not stable, isn't that correct?

DR. BENOWITZ: Well, I tried to explain this. It depends what you mean by stable. If you mean is it exactly the same at every point in time, the answer is no, it's not. Is it generally stable if you measure exposure over long periods of time? I would say it is relatively stable. So it depends how you're looking at the issue.

MR. GROSSMAN: Well, let's break this down. For one thing, you put up a slide early on about sidestream smoke, and it compared the relationship between RSP and nicotine in sidestream smoke in various cigarettes, do you recall that?

DR. BENOWITZ: Yes, it was actually looking at particulate mass, just basically tar.

MR. GROSSMAN: Sidestream smoke and ETS are not identical, is that correct?

DR. BENOWITZ: That's correct.

MR. GROSSMAN: And that is because the various components of sidestream smoke and exhaled mainstream smoke break down at different decay rates?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Now, the relationship between RSP or other components of ETS and nicotine depends upon, among other things, ventilation, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: It also depends upon surface characteristics, isn't that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: The relationship between RSP and nicotine will tend to be different in a home than in the workplace, is that correct?

DR. BENOWITZ: Well, it may, depending on the characteristics of the sites.

MR. GROSSMAN: Ventilation characteristics of a typical workplace are significantly different than ventilation characteristics of a typical home, isn't that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: So the relationship between RSP and nicotine in the home and the workplace will tend to be different, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Now, it's fair to say, Doctor, that although you are an expert in a number of fields, you are not an expert in defining the relationship between RSP and nicotine in ETS, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: You have not made any independent studies on that, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: You have placed a couple of studies on the board through your slides. You have not reported, either in your prepared testimony or in your oral testimony today, on all of the peer-reviewed field reports on the relationship between nicotine and RSP in ETS, is that correct?

DR. BENOWITZ: That's correct.

MR. GROSSMAN: You're familiar, Doctor, with a study by Mourmatsu comparing the relationship between nicotine and RSP in ETS?

DR. BENOWITZ: Well, it's difficult for me to recall specific studies without seeing them, so I really can't comment. There's such a huge literature of material involved, that I really cannot keep track of all of them by name.

MR. GROSSMAN: Are you familiar with the research of Mourmatsu?

DR. BENOWITZ: Well, I think so, again, I would recognize the paper if I saw it, but it's hard for me to know for sure.

MR. GROSSMAN: I believe you referred in your testimony to a study by Miesner?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Now, in your chart, you showed the average RSP to nicotine ratio, as reported by Miesner, do you recall that?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Do you recall the range of variation that Miesner reported on?

DR. BENOWITZ: I don't, but I would just say that Dr. Hammond is going to be talking in great detail about this area, and I think that she'll provide you with much more detail than I. The purpose of my comments was really to be an overview of the issue, sort of a preface to looking at cotanine. But Dr. Hammond will talk about this in great detail.

MR. GROSSMAN: That's fine, Doctor, but you did testify to it, and in addition it's obviously a limiting characteristic to the extent to which cotanine is a valid marker for ETS presence, so to the extent that you can, I would just like to go through these few questions. The Miesner study reported a variation in the ratio between RSP and nicotine, ranging from eight to one to 55 to one. That's a wide variation, is it not?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Are you familiar with the Baylin-Black study?

DR. BENOWITZ: Not by name, I'd have to see it.

MR. GROSSMAN: That showed a variation from 5.7 to one to 260 to one, a very wide variation, is that correct?

DR. BENOWITZ: Yes. Let me just say that I don't know these studies, but there is an issue which again Dr. Hammond will bring up, which when ETS levels get very low, then the particulates from other sources, sources other than ETS which persist, they don't decline because they're coming from other sources, tend to increase the RSP/nicotine ratio, and so it's been well shown. Again, Dr. Hammond will show this, that if you look at the total ETS levels, when you get to low levels, this ratio really explodes.

MR. GROSSMAN: You're saying that you believe someone else will testify about these things on the peer-reviewed literature. Several layers removed from the original research, I just want to explore the degree of your testimony and the extent to which it can be relied on in this area for purposes of the rule making. I gather what you're saying is that you're not an expert in this field and do not feel comfortable suggesting what the RSP to nicotine ratio is or what the range of that ratio might be.

DR. BENOWITZ: Well, what I'm saying is you've asked me about specific numbers. Without having the papers in front of me, I cannot comment about those specific ratios. However, I know well from having read Dr. Hammond's work and her papers, as well as other people, that the ratio explodes at low ETS levels. And so if you just give me a random number and say isn't this really high my response would be, well, most likely that's because the ETS level is very low. That's as far as I can go without having the paper in front of me.

MR. GROSSMAN: Have you attempted to determine a coefficient of variation?

DR. BENOWITZ: No. I will. I need to get the raw data from these different studies to do that and I intend to try to do that in the future. I have not had those available to me.

MR. GROSSMAN: By the way, you are aware of testing done by RJR Laboratories in this field, are you not?

DR. BENOWITZ: Yes, I am aware that testing has been done.

MR. GROSSMAN: And you have worked with RJR Laboratories in raw data testing, is that correct? Not coming to conclusions but in raw data testing?

DR. BENOWITZ: I don't know what--

MR. GROSSMAN: You have had your laboratory itself perform raw data tests for Reynolds.

DR. BENOWITZ: We have done assays with people from RJR and I have shared data with Dr. Debathesie but I'm not sure what you mean by raw-- whatever the term was that you stated. It's not a term I understand.

MR. GROSSMAN: It's probably not a term of science. I'm referring to the actual numbers derived from the tests not the conclusions that you might derive therefrom.

DR. BENOWITZ: We've done assays for R.J. Reynolds, some of the studies, and I have given some data to R.J. Reynolds but that's the extent of it. I'm not sure what you mean beyond that.

MR. GROSSMAN: In your work with R.J. Reynolds, you have had no reason at any point to believe that the numbers that their laboratories have generated have been anything other than accurate, have you?

DR. BENOWITZ: No.

MR. GROSSMAN: Now, Doctor, given the reported ranges of nicotine to RSP ratios, all you can really say is that in any given workplace or in any given report the total RSP to nicotine ratio of ETS is likely to be within the reported ranges within the peer reviewed literature, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: You can't say that it's going to be the average of the ranges in the peer reviewed literature.

DR. BENOWITZ: Well, I'm not sure exactly what that question means.

MR. GROSSMAN: Well, where there is wide variation, as you have testified there is, depending upon workplace and other circumstances, in the RSP to nicotine ratio, you cannot assume that any study has an RSP to nicotine ratio that is the average of all the studies conducted.

DR. BENOWITZ: Well, obviously there's going to be issues of which workplaces were sampled, what environments were sampled and there are also some good studies and some not very good studies, so there are lots of issues involved. It's not a simple question to answer.

MR. GROSSMAN: That's fine. You simply cannot assume that the ratio will be nine to one or ten to one or anything else because there is a wide variation of ratios that have in fact been found.

DR. BENOWITZ: Well, there have been but I think some of the better studies with a larger number of samples, I don't know the RJR study, I have not seen its publication, but other studies with large samples seem to be pretty consistent in finding ratios of about nine or ten to one.

MR. GROSSMAN: Well, the Meisner study that you yourself relied on as a workplace study found ratios up to 55 to one.

DR. BENOWITZ: Well, again, I dealt with that question before. On the outlyers, one needs to look specifically at what the level is that they are assessing because in any measurement, when you get to low ETS levels, that ratio is going to rise and so you need to be very cautious in going down to low ETS levels for that ratio.

MR. GROSSMAN: In any event, the only way to find out the RSP to nicotine ratio in any workplace, the only way to accurately assess that is that is to monitor the air, is that correct?

DR. BENOWITZ: Well, that's the best way, sure.

MR. GROSSMAN: Yes. And the best evidence of the RSP to nicotine ratio is monitoring.

DR. BENOWITZ: Yes.

MR. GROSSMAN: Similarly, you referred to attempts to demonstrate the-- well, let me start that again. The best way to find out the precise level of ETS in the atmosphere in general is to monitor, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: All right. Let me come to the board and just put that down as a first point.

JUDGE VITTONE: Mr. Grossman, if you're going to do any talking, please make sure that it's recorded.

MR. GROSSMAN: I have this turned on. Excuse me.

JUDGE VITTONE: Ms. Sherman, can you see that?

MS. SHERMAN: Yes, I can. Sort of.

MR. GROSSMAN: All right, Doctor.

The best evidence of ETS level is monitoring. Now, you are referring now to the use of markers as something other than the best evidence. Is that correct?

Or, to rephrase the question, your testimony relates to attempts other than through monitoring to find or to estimate levels of ETS exposure. Is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Now, you went at some length into the reasons why you have suggested that cotinine may be the best marker. But it's clear you're looking for the best marker and not the best evidence, correct? The best evidence being monitoring itself.

DR. BENOWITZ: Well, it depends what question you're asking.

MR. GROSSMAN: Well, let me break it down to this.

Doctor, you referred to CO, to carbon monoxide, as one possible marker.

DR. BENOWITZ: Yes.

MR. GROSSMAN: The reasons that you've rejected carbon monoxide are that it's not specific to cigarettes, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And there is a very low level of carbon monoxide in ETS?

DR. BENOWITZ: Well, more importantly, there is a low level of carbon monoxide in people exposed to ETS.

MR. GROSSMAN: There's a low level of carbon monoxide in people exposed to ETS?

DR. BENOWITZ: Yes.

MR. GROSSMAN: There is carbon monoxide present in the environment from sources other than cigarettes?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Carbon monoxide is created by the body itself?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Now, regardless of the source of carbon monoxide, it has the same effect on the body, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And as far as environmental carbon monoxide is concerned, the best way to control for it would be ventilation, is that correct?

DR. BENOWITZ: From what source?

MR. GROSSMAN: From any source.

DR. BENOWITZ: Well, you know, some cases, if you have a faulty heater, you know, you have an engine that's not exhausted properly, there are things you can do about the source as well.

MR. GROSSMAN: But one way to control for carbon monoxide generally in the workplace is through better ventilation, is that correct?

DR. BENOWITZ: Yes, that is an obvious way to do it.

MR. GROSSMAN: Now, RSP is also present in the atmosphere from sources other than cigarettes, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: So it, too, is not specific?

DR. BENOWITZ: Correct.

MR. GROSSMAN: And regardless of the source, again, ventilation helps to control for RSP, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: You noted that there are other possible markers that have been suggested, including benzo(a) pyrene but you said that while those markers are capable of noting who is a smoker and who is not, they are not sensitive enough to determine the difference between non-smokers who are exposed to ETS and those who are not exposed to ETS?

DR. BENOWITZ: Correct.

MR. GROSSMAN: And that's because there's a massive difference in the chemical levels of those who are direct smokers and those who are non-smokers, regardless of whether they are exposed to ETS or not.

DR. BENOWITZ: Yes.

MR. GROSSMAN: The difference between smoking and not smoking is many, many times greater than the difference between living in an ETS-free environment and living in an environment with ETS.

DR. BENOWITZ: Yes.

MR. GROSSMAN: Now, let me come to the board again for a moment.

The best evidence, we said, was monitoring markers. And turning specifically to cotinine as a marker for ETS exposure, Doctor, the first limitation on this you've already testified to and that is that there is a variation in the RSP to nicotine ratio. Is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Now, the reported literature represents variances of sometimes 10 times, 100 times. What do you take as a typical variance level?

DR. BENOWITZ: What do you mean by variance level?

MR. GROSSMAN: Well, where a ratio may be five to one or 50 to one, that represents a 10 times difference in ratios, isn't that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: What would you take to be a typical range of ratios? A factor of how much?

DR. BENOWITZ: Three.

MR. GROSSMAN: We recognize that the reported literature shows a range of far higher than that but I'll put down your range of differences as 300 percent.

DR. BENOWITZ: Well, you know, it depends on what you-- you know, again, I think we need to go back and address this business about low level ETS and the impact of particulates from sources other than ETS because that's really going to throw this out. I think if you look at higher levels of exposure, say, with an average of about 10, then the range, I'm not talking about typical values, would be more likely to stay between five and 15.

MR. GROSSMAN: Okay. That would represent a 300percent variation, correct? A three to one variation.

DR. BENOWITZ: But that's the outlyers.

MR. GROSSMAN: The outlyers in studies go far beyond that, isn't that correct?

DR. BENOWITZ: Well, excluding the outlyers that are due to easily explained factors such as background particulates.

MR. GROSSMAN: You have already testified that you are not an expert in this field but you are reporting on this on the basis of your review of peer reviewed literature.

DR. BENOWITZ: Yes.

MR. GROSSMAN: All right. Accepting that you find a typical range excluding the outlyers of 300 percent, let's move on to the next point.

In addition to a limitation on accuracy in the RSP to nicotine ratio, you also noted that not all nicotine comes from ETS, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Now, you provided a chart, a couple of charts, 17, 18 and 19, I believe, and 20, in which you listed a number of foods and other substances that provide nicotine to individuals. Do you recall that?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And your cotinine measurements cannot separate out the cotinine that came into-- the nicotine that came into the body from cigarette smoke or from other sources, is that correct?

DR. BENOWITZ: That's correct.

MR. GROSSMAN: The tests are not specific to tobacco nicotine.

DR. BENOWITZ: Correct.

MR. GROSSMAN: Now, in your chart, you gave a value for the, at some point, not in the first chart but later, you gave a value for the amount of nicotine in tea. Do you recall that?

DR. BENOWITZ: Yes.

MR. GROSSMAN: In fact, there is extraordinary variance in the amount of nicotine in tea. Hasn't that been reported in the literature?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And instant tea has many times the nicotine value, typically, of brewed tea. Is that correct?

DR. BENOWITZ: That's been reported. That's correct.

MR. GROSSMAN: And they don't use instant tea in Scotland, do they?

DR. BENOWITZ: I don't know how much instant tea they use in Scotland.

MR. GROSSMAN: And the Scottish study that you referred to had no controls, did it?

DR. BENOWITZ: Controls for what?

MR. GROSSMAN: ETS exposure, for example. In the Scottish study that you presented, it attempted to draw a parallel between cotinine in people who drank tea and people who were exposed to ETS but it didn't cross-control for either, did it?

DR. BENOWITZ: Well, you know, I don't recall exactly what controls were used but even if they didn't, when you have a large sample like that, if you find no correlation between tea consumption and cotinine and you do find a correlation between ETS consumption and cotinine, the only way you could explain it is by very strong inverse confounding, which is not very improbable with a population of 3000 people.

MR. GROSSMAN: Perhaps you could first answer the question. You do know if that study controlled?

DR. BENOWITZ: I would have to look at it again. I don't recall.

MR. GROSSMAN: Okay. To get back to the variance in the nicotine levels reported in teas, some teas have been found to have no nicotine level, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Other instant teas have been reported to have nicotine levels as high as 250 nanograms per gram of net weight, is that correct?

DR. BENOWITZ: I believe so. I don't have the exact number. I could check it but I'll take your word for that.

MR. GROSSMAN: Well, if one consumed, say, iced tea, instant iced tea, at a rate of a quarter per day and if the nicotine content of the iced tea were 250 nanograms per gram net weight of the tea, how much nicotine would be consumed just from that iced tea?

DR. BENOWITZ: I would have to take some time and go through those calculations. I can't tell you that.

MR. GROSSMAN: It would be a substantial amount.

DR. BENOWITZ: I would have to go through the calculations.

MR. GROSSMAN: Now, Doctor, you referred to the supposed values of nicotine in various other foods using a short-- using numbers that you said were derived from a study by Davis?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Davis found a low amount, a high amount and an average amount in the reported vegetables and other foods that he studied, is that correct?

DR. BENOWITZ: I don't recall exactly how he put together his table. I'd have to look at the paper to answer that specifically.

MR. GROSSMAN: You in fact used the lower bound of his study rather than the average value in his study in compiling your numbers, isn't that correct?

DR. BENOWITZ: I used the table numbers that he used to make his argument for exposure so I basically lifted directly from his table estimating exposure in humans and so he thought that was most relevant to use and therefore that's what I used.

MR. GROSSMAN: Doctor, at low levels of exposure to environmental nicotine, dietary nicotine becomes a more important factor in total nicotine intake, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: The lower the level of environmental or smoking exposure, the greater the effect the diet plays in total nicotine intake?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And so with low level ETS exposure, dietary intake is apt to be a significant confounder.

DR. BENOWITZ: Well, it depends what you mean by confounder. If you're talking about the presence of cotinine, then you may well have cotinine in everyone's urine if you measure it sensitively enough but that's not going to be confounded with ETS exposure.

MR. GROSSMAN: It is going to be a confounder to the extent of cotinine that can be attributed to ETS exposure.

DR. BENOWITZ: Yes. But you won't get enough to falsely have the impression that someone has substantial ETS exposure from the diet.

MR. GROSSMAN: All right. Doctor, it's fair to say to that the second limitation on the use of cotinine as a marker is nicotine arises from other sources, is that correct?

DR. BENOWITZ: It's quite a minor limitation but, yes. I would call it a consideration because I don't think quantitatively it is a limitation.

MR. GROSSMAN: You say it's a consideration rather than a limitation?

DR. BENOWITZ: Because it's a quantitative issue.

MR. GROSSMAN: It's capable ultimately of measurement but an adequate measurement of the extent to which dietary nicotine has accounted for cotinine in various studies that you have relied on has not been taken, is that correct?

DR. BENOWITZ: That's correct.

MR. GROSSMAN: Okay. There's also nicotine in marijuana, is that correct?

DR. BENOWITZ: I have never seen specific measurements about it. I have heard that but I don't know any data.

MR. GROSSMAN: But that, too, would be a confounder, is that correct?

DR. BENOWITZ: If it's present. Like I said, I've not seen the data on it.

MR. GROSSMAN: All right. Doctor, OSHA is involved in regulating only the workplace, as you know.

DR. BENOWITZ: Yes.

MR. GROSSMAN: And not all nicotine that non-smokers breathe is from the workplace, is that correct?

DR. BENOWITZ: Correct.

MR. GROSSMAN: And so a third limitation on using cotinine as a marker for ETS exposure in the workplace is that not all nicotine is breathed in the workplace.

DR. BENOWITZ: Yes.

MR. GROSSMAN: Now, Doctor, the work day is half of the waking day? Roughly?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Five out of seven days a week?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And some people live with smokers, some don't?

DR. BENOWITZ: Yes.

MR. GROSSMAN: People go to movies, restaurants, bowling alleys, bars, other places where there may be ETS in the environment?

DR. BENOWITZ: Yes.

MR. GROSSMAN: There is no way to estimate, is there, what percentage of the average worker's cotinine is derived from workplace as opposed to non-workplace exposures, is that correct?

DR. BENOWITZ: For a particular worker, that's correct.

MR. GROSSMAN: Could we estimate half of the day means probably half of the cotinine?

DR. BENOWITZ: Well, it depends on issues like what is the level of nicotine in the home versus the work. Factors like that which you can address in population based studies but it's very difficult to address it for every individual.

MR. GROSSMAN: What percentage on average of a worker's cotinine would you anticipate comes from ETS in the workplace?

DR. BENOWITZ: It depends entirely on whether someone is smoking at home and what the ventilation is like at home versus work, so I don't have a figure. I can't give you a number.

MR. GROSSMAN: Would it be fair to say that individual variability could go from almost no exposure outside of the workplace to 70 percent of the total outside of the workplace?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Doctor, there's also a large individual variation in the rate at which people metabolize nicotine, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: That variation is more than 200 percent?

DR. BENOWITZ: Yes.

MR. GROSSMAN: In fact, Doctor, any given plasma level of nicotine could result from more than a two-fold different level of nicotine intake in different individuals.

DR. BENOWITZ: Yes.

MR. GROSSMAN: Okay. So point number four is individual metabolism differences count for 200 percent.

Two hundred percent or more.

And, Doctor, there is also a reported difference from test to test in the typical metabolism rates and average metabolism rates, isn't that correct, and nicotine?

DR. BENOWITZ: I don't understand the question. What do you mean, from test to test?

MR. GROSSMAN: Well, you have conducted various studies yourself on the average extent to which nicotine is converted to cotinine in the body, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And your studies have resulted in somewhat different average results, is that correct?

DR. BENOWITZ: You mean averages for the group studied at different times?

MR. GROSSMAN: Yes.

DR. BENOWITZ: Yes.

MR. GROSSMAN: And those averages have varied by as much as a third, is that correct?

DR. BENOWITZ: I don't recall exactly but they might. It depends on the sample selected.

MR. GROSSMAN: Well, do you recall that you wrote a paper revised June 6, 1994 with Paton Jacob entitled "Metabolism of Nicotine to Cotinine, A Study by Dual Stable Isotope Method"?

DR. BENOWITZ: Yes.

MR. GROSSMAN: At page 11 of that, you wrote, "Our data on cotinine kinetics differs somewhat from our earlier study with the infusion of natural cotinine in smokers. In the present study, the average occurrence and volume of distribution are about one-third lower."

DR. BENOWITZ: Yes.

MR. GROSSMAN: And so from two different studies involving exactly the same researchers, the difference was one-third. Is that correct?

DR. BENOWITZ: Yes. The techniques were somewhat different but your statement is correct. Those numbers were one-third different.

MR. GROSSMAN: So there is intra-observer variability, is that correct?

DR. BENOWITZ: Yes. I guess some degree.

MR. GROSSMAN: And there is also inter-observer variability, is that correct?

DR. BENOWITZ: Yes. One-third or more.

Now, another point that you spent a good deal of time on in your testimony was the derivation of steady state numbers. Do you recall that?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And your conclusions are premised on an assumption that there is a steady state of cotinine in the level of people tested, is that correct?

DR. BENOWITZ: Well, the calculations assume that and my statement was that that's probably reasonably accurate, assuming that someone is exposed over eight hours throughout the day.

MR. GROSSMAN: Well, Doctor, even in smokers there is a 30 percent variability in cotinine levels during the day, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And smokers smoke, as you understand it, smoke continuously during their 16 waking hours.

DR. BENOWITZ: More or less.

MR. GROSSMAN: People exposed in the workplace are exposed to ETS eight hours a day, five days a week. Is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: The level on Monday would not be the same as the level on Friday, is that correct?

DR. BENOWITZ: With no exposure over the weekend, that's correct.

MR. GROSSMAN: The level at different hours of the day would be different as well, too, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Now, you referred to variability that you said was moderated by averaging. Do you recall that?

DR. BENOWITZ: Yes.

MR. GROSSMAN: But in fact, in the studies taken of cotinine levels of workers, the workers' urine is not examined on a daily basis or hourly basis for a long period of time, is that correct?

DR. BENOWITZ: Well, if that's what you mean by averaging, that's not what my comment referred to. That's true but what my comment referred to and I think it's very relevant to this whole line of argument is that when you look at any individual there is a considerable potential for variability in using cotinine as a marker but when you look at a population, say, if you look at an English study of 700 children, then the values that you have, I think, are pretty representative of an exposure level.

MR. GROSSMAN: How would values taken on Monday morning of workers be representative of average cotinine levels of all workers?

DR. BENOWITZ: Well, there would be some noise and I think if every worker was sampled on Monday morning, then you would underestimate exposure. If every worker were sampled at some other time, you might overestimate it.

MR. GROSSMAN: If they were sampled, say, Thursday evening at seven o'clock, it would overestimate exposure, is that correct?

DR. BENOWITZ: It depends on the exact kinetics of it. But my point is when you sample large numbers of people, and this is done in a number of different types of studies, you end up with a population estimate which is pretty accurate.

MR. GROSSMAN: Well, you've already said that there is a 30 percent variation in the cotinine levels of regular smokers.

DR. BENOWITZ: Yes.

MR. GROSSMAN: Even excluding the question of the weekend and holidays, the variation in the cotinine level of non-smokers exposed to ETS in the workplace would be greater, isn't that correct?

DR. BENOWITZ: You mean throughout the day?

MR. GROSSMAN: Yes.

DR. BENOWITZ: Probably.

MR. GROSSMAN: All right. And taking into account the weekend and other times when they were not exposed at work at least, the variation level would be significantly higher still.

DR. BENOWITZ: Yes.

MR. GROSSMAN: So another limitation is that there is not in fact a steady state of cotinine in workers exposed only in the workplace, correct?

DR. BENOWITZ: Yes. I might just add that if anything that would end up in current measurements underestimating real exposure because in general you would be underestimating the extent of exposure at work by casual level and so that would underestimate the real exposure. Our current data would underestimate the real exposure.

MR. GROSSMAN: Depending on the time of the sampling, it could overestimate or underestimate, that is your testimony, correct?

DR. BENOWITZ: Well, not really. It takes four or five days to reach steady state. So the value that you get on Friday night or Friday afternoon would probably be the most representative, if you wanted to figure out daily exposure during the week. Any other value would tend to underestimate it because you have a certain period of time when you're not being exposed, say, the weekend. So the best steady state measure would actually be on Friday afternoon.

MR. GROSSMAN: Are you suggesting that the best steady state measure of a regular smoker would be at the top of the curve?

DR. BENOWITZ: Well, you know, if-- it depends on what the question is. If the question is what's the average exposure for seven days a week, then my answer to your question is no. If the question is what's the average exposure of these five workdays, then what you want to know is what point in time does a person reach steady state from exposure and that steady state is achieved at the end of the workweek and so that number, if you took the best number throughout the day, if you put Friday aside, say we're going to take Friday, we could take the average level of cotinine on Friday, that would be the best marker of average intake of nicotine during a work day.

MR. GROSSMAN: Well, you've testified that the average metabolism of cotinine is 18 hours with wide variations, correct?

DR. BENOWITZ: The half-life. I said 16 hours but 18 is close.

MR. GROSSMAN: Sixteen. In some places you've written 16, in others 18.

DR. BENOWITZ: Yes.

MR. GROSSMAN: And that would mean that in 32 hours, 75 percent is dissipated?

DR. BENOWITZ: About right, yes.

MR. GROSSMAN: So certainly within three days, the level Wednesday, Thursday and Friday would not be significantly different, is that correct?

DR. BENOWITZ: Well, it takes about three or four half-lives to reach a steady state so if you start your exposure on Monday, then by Thursday or Friday, you would be at steady state. So that would actually be the best time to measure steady state for the workplace.

MR. GROSSMAN: To reach a steady state, you say it takes three or four half-lives?

DR. BENOWITZ: Yes.

MR. GROSSMAN: If the half-life is 16 hours, three times 16 is 48 hours?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Okay. So if you begin the day at nine o'clock on Monday, 48 hours later is nine o'clock a.m. on Wednesday, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Now, Doctor, if one were at any time thereafter to take the cotinine measurement at the end of the work day, immediately after the exposure, it would represent not only what you refer to as the steady state but also the immediate exposure that had not yet had an opportunity to metabolize, is that correct?

DR. BENOWITZ: Yes. There is about a four or five-hour lag between, say, the last nicotine exposure and peak cotinine from that so you would-- that's where this 20 to 30 percent fluctuation comes from. So I would say if you could sample all day long and take the average value, that would be pretty good. We can't do that so we just take values at various times of the day and my point is just that that tends to balance out, if we're only talking about a 30 percent difference from peak to trough.

MR. GROSSMAN: And, of course, this concept of steady state assumes that there is a constant level of exposure, correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: But, of course, people who report ETS exposure at work do not necessarily report a constant level of exposure, is that correct?

DR. BENOWITZ: That's true but it's a reasonable approximation.

MR. GROSSMAN: They report it only in the cafeteria or only going to the copy room or only at intermittent moments, is that correct?

DR. BENOWITZ: Yes. But even so, looking at a cotinine concentration would still give you a quantitative approach, even if it wasn't absolutely a steady state you still would have some sort of ballpark estimate of consumption. Or if anything you might underestimate it.

MR. GROSSMAN: Dr. Benowitz, let me represent to you that OSHA's own proposed rulemaking states that of workers who identify exposure to ETS in the workplace, approximately 51 percent identify it as occurring in restaurants in lunch hours, another 35 or 36 percent report their exposure to be during breaks and only about 25 percent during actual working time. That indicates an intermittent rather than a steady level of exposure, does it not?

DR. BENOWITZ: Yes.

MR. GROSSMAN: All right. Now, in addition to the lack of a true steady state of cotinine in workers exposed to ETS, a variation significantly greater than 30 percent, Doctor?

DR. BENOWITZ: Well, it could be more than that. That 30 percent is based on people smoking throughout the day. If they're only exposed for eight hours, I haven't calculated what that variation would be but it could be greater than 30 percent.

MR. GROSSMAN: Now, yet another area of potential limitation concerns the method by which the cotinine is measured, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Cotinine has been measured in urine samples, in blood plasma and in saliva, as you reported. Is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And you believe that the medium, the test medium, should vary with the type of results you're looking for?

DR. BENOWITZ: I don't understand that question.

MR. GROSSMAN: Well, doctor, you have reported that the type of body fluid in which to measure cotinine depends upon the epidemiological question being asked?

DR. BENOWITZ: If I said that, that's out of context because I don't understand exactly what you mean by that.

MR. GROSSMAN: Okay. I'll tell you where you said it. Do you recall participating in an article in the American Journal of Public Health, June 1988, entitled "Cotinine in the Serum Saliva and Urine of Non-Smokers, Passive Smokers and Active Smokers"?

DR. BENOWITZ: By Wall?

MR. GROSSMAN: Wall, Johnson, Jacob and yourself.

DR. BENOWITZ: Yes. Let me just say something about that before we get into that. That was the first study we ever did looking at levels of nicotine from ETS and our assay was not set up for that. We were basically running an assay that we used for smokers. Subsequently, we have a GC mass spec assay which is just specifically standardized for very low concentrations. And so those data, although they're published, are not with an assay that we would use today.

MR. GROSSMAN: Well, in that assay where you were looking at cotinine concentrations in smokers-- let me take a step back. One nice thing about measuring body fluids of smokers is that you know the precise dose involved, is that correct?

DR. BENOWITZ: Dose of what?

MR. GROSSMAN: Dose of cigarettes. The smoker can tell you how many cigarettes per day he smoked.

DR. BENOWITZ: I don't follow your question.

MR. GROSSMAN: Well, if you don't have air sampling in ETS, it's my understanding that you were referring to using cotinine as a measurement to provide a back door way of trying to determine the level of ETS in the workplace. Is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: With cigarette consumption, one doesn't have to resort to air sampling to have the best evidence of the amount of the various compounds in the atmosphere breathed by the smoker. One has the actual consumption of cigarettes, isn't that correct?

DR. BENOWITZ: Well, what you get from measuring cotinine is an estimate of nicotine consumption, not cigarette consumption.

MR. GROSSMAN: You found only a very slight correlation between the number of cigarettes smoked per day and urine cotinine in the study that we were just referring to. Is that correct?

DR. BENOWITZ: I forget what the exact correlation was but it was--

MR. GROSSMAN: R squared equalled .06.

DR. BENOWITZ: I would have to look at the specific paper but it's true that in our work we found that urine cotinine versus nicotine intake was not as robust as some of the other cotinine measures. There was more variability in urine.

MR. GROSSMAN: And you also found in that study that you could not fully discern the difference between non-smokers who reported exposure to ETS and those who did not report exposure to ETS. Is that correct?

DR. BENOWITZ: Are you talking about the Wall study?

MR. GROSSMAN: Yes.

DR. BENOWITZ: Well, let me restate. We have done other studies since then where we can almost 100 percent distinguish. That study was done with a suboptimal assay and I would not rely on that study as a major source of quantitative data on ETS.

MR. GROSSMAN: Well, let's turn for a moment to testimony that you gave a little while ago in which you said that urine samples, sampling for cotinine, is dependent on flow, pH and other factors.

DR. BENOWITZ: Yes.

MR. GROSSMAN: That is correct, is it not?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And it therefore has elements of confounding that would not be present in blood plasma, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: So blood plasma provides a more accurate assessment of cotinine, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: All right. Let me just write this down.

MR. GROSSMAN: What is the degree of variation of blood samples for cotanine and urine samples for cotanine?

DR. BENOWITZ: We haven't measured that. The only data that I know of were the data published by Jarvis, and he basically generated what is called a correlation coefficient, and I think the correlation coefficient was close to .9. I don't remember the exact number, but it was surprisingly close, I thought.

MR. GROSSMAN: That would mean that there's a likelihood that the urine samples will be off by an average of 10 percent?

DR. BENOWITZ: No. No.

MR. GROSSMAN: What does that mean?

DR. BENOWITZ: Well, I can't answer the question the way you posed it. The correlation coefficient just says if you have hairs of measurements from a lot of different people, how close is one measurement to the other measurement, and in our value of .9 means that about 80 percent of the variability in one measure can be accounted for by the other measure. Now, I can't translate that to the question you're asking without looking at the data in a different way. But I just can't answer that question.

MR. GROSSMAN: All right. Doctor, let's turn briefly from the question of cotanine measurement to the question of questionnaires as a basis for setting a level of exposure in the workplace. You've reviewed literature on that as well, have you not?

DR. BENOWITZ: Yes. Not recently, but I have read literature about that.

MR. GROSSMAN: You refer to it somewhat in your written testimony.

DR. BENOWITZ: Yes.

MR. GROSSMAN: It's accurate to say, is it not, Doctor, that the purity of the studies that have been conducted suggest that questionnaires have some degree of reliability in assessing whether there was ETS exposure in the workplace, but they had almost no reliability in determining the level of ETS exposure.

DR. BENOWITZ: Well, the first part I would agree with. The second part, I think, depends on studies and I'd have to go back and review those to look at sort of the questionnaire dose response. On some studies I've found none, and I think other studies have found, or as a person reports exposure to ETS the greater the cotanine level. But I'd have to go back and look at the specific studies to give you more information about that.

MR. GROSSMAN: As you were saying, some studies have reported no correlation whatsoever between the amount of ETS exposure suggested by the respondent to the questionnaire and the amount of ETS exposure that that's not an accurate...

DR. BENOWITZ: I believe so. Although, again, I have to go back and look at details, both in terms of the quality of the questionnaire and the quality of the assays that were used.

MR. GROSSMAN: Now, as between using cotanine as a measurement for determining levels of ETS in the atmosphere and using questionnaires, what would you think was superior?

DR. BENOWITZ: Well, the problem with questionnaires is one doesn't know what the level of the exposure is. The cotanine gives you some quantitative marker of level of exposure, so I would trust the cotanine level more.

MR. GROSSMAN: Let me just note here, point B, questionnaires sometimes reported to be completely unreliable in assessing ETS exposure level. And now, doctor...

JUDGE VITTONE: Excuse me a second, please. Is that a question?

MR. GROSSMAN: I was just noting what the doctor reported. I was just saying that I was putting down as point B, questionnaires are unreliable in assessing ETS exposure level. I'm just summarizing.

JUDGE VITTONE: Do you agree with that, Doctor?

DR. BENOWITZ: Well, some studies.

JUDGE VITTONE: I'm not sure that I understood that there was that kind of a...

DR. BENOWITZ: No, I think there... Some people have said that. Some researchers have said that. I think there probably is some validity to it, because other studies have shown quantitative relationships between how much ETS exposure a person has and what their cotanine levels are, so I wouldn't say they are totally unreliable. I think that they've got limitations and I would trust cotanine more. I don't think those are totally unreliable.

MR. GROSSMAN: So would you say they're unreliable in assessing ETS exposure level according to some peer review literature?

DR. BENOWITZ: Yes. You can say that.

MR. GROSSMAN: And unquestionably limited?

DR. BENOWITZ: Yeah, I think it's limited. No measure is perfect. You know, it's got limitations, like everything else. But I think it's useful. I think the questionnaire data are quite useful.

MR. GROSSMAN: All right, Doctor. I'd like to put these points together, if we can.

The questionnaire is unreliable in assessing ETS exposure level according to some peer review literature and unquestionably limited. And as long as we're going to make this, why don't we say questionnaires are completely unreliable according to some peer review literature, which was your testimony.

MS. SHERMAN: Excuse me. Well, now, what you are saying is, if I understand you, this is not implying that Dr. Benowitz believes this. What you're saying is, this is what the literature says.

MR. GROSSMAN: You've done no studies of questionnaires' accuracy yourself, is that correct?

DR. BENOWITZ: That's correct.

MR. GROSSMAN: And so you can report only upon what the peer review literature says. Is that correct?

DR. BENOWITZ: That's correct.

MR. GROSSMAN: And the peer review literature says in many cases that questionnaires are completely unreliable in assessing the level of ETS exposure. Is that correct?

DR. BENOWITZ: I don't know many cases. I know that I've seen papers to that effect. I don't remember how many. I can't give you that. But it has been reported.

MR. GROSSMAN: Okay. According to some peer review literature. Is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And there's no question that there's a limitation on the utility of questionnaires in assessing precise levels of ETS exposure generally.

DR. BENOWITZ: Yes.

MR. GROSSMAN: All right. Now, Doctor, let's put all of this together.

The question is of assessing levels of ETS exposure in the workplace. You said the best evidence of ETS exposure and precise levels is monitoring.

DR. BENOWITZ: Yes.

MR. GROSSMAN: In the absence of monitoring, you look at cotanine as a marker for ETS exposure. And its limitations include the variable nicotine to RSP ratio, which has a typical range of 3 -- 300 percent.

The nicotine arising from other sources and the precise level of that has not been quantified. Not all nicotine absorbed by people is from the workplace. Individual variations are 0 to 70 percent, in addition to this 300 percent. Individual metabolism variations of 200 percent or more in addition to the variations that we already referred to. Intra and inter-observer variability from one test to another of one-third or more.

There isn't in fact a steady state which is an assumption of the cotanine level tests. Better than 30 percent variation with regard to ETS. And urine samples are less accurate than measuring cotanine in the blood.

Now Doctor, for purposes of determining the level of the ETS that arises from the workplace in a worker, if one uses cotanine as a marker, one must combine cotanine as a marker with questionnaires indicating the level of ETS exposure outside of the workplace. Is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And so in setting workplace ETS exposure, without monitoring, one must combine the limitations of cotanine measurement and the limitations of questionnaires. Is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Okay. That's the final point I want to put on the board.

(Brief pause)

MR. GROSSMAN: I know you have testified in a number of smoking and health and related...

DR. BENOWITZ: Can I?

MR. GROSSMAN: Yes.

DR. BENOWITZ: There is one critical point that I think has to be made with respect to the meaning of these ranges, and I wonder if I could use the...

MR. GROSSMAN: Well, I believe, Doctor, that you'll have an opportunity to submit an additional statement.

DR. BENOWITZ: No. But I think what you've said is misleading for the record, and I could explain it or I could draw it. But the issue is, what does a range mean when you have a distribution of values. You know, we're talking about the 300 percent range, or what have you. In fact, if you sample on a large number of values what you tend to get is what's called a normal distribution, or a bell-shaped curve.

Most of the values are toward the mean. Now there are ranges, and the range of say, 200 percent, 300 percent, are basically the extremes.

MR. GROSSMAN: Doctor...

DR. BENOWITZ: Just a minute. I'm not finished yet.

JUDGE VITTONE: Let him clarify that further.

DR. BENOWITZ: When you use the extremes to make your argument for the imprecision of a measure, it's misleading. Because what you really want to do is, say, if you sample any individual, what is the likelihood of variability for that individual. The likelihood is not that you're going to be at the extremes. The likelihood is it's going to be much closer to the mean. So these...

MR. GROSSMAN: Doctor...

DR. BENOWITZ: These numbers, I think, are misleading, and although I agree with them in fact, I don't agree with your interpretation that this variability renders the measure not very useful.

MR. GROSSMAN: All right, Doctor. For the first point. Different tests result in different bell-shaped curves. Is that correct?

DR. BENOWITZ: Well, that's such a general question.

MR. GROSSMAN: Sometimes most of the values are approximate to the mean and sometimes many of the values are spread over a wide range. Is that correct?

DR. BENOWITZ: Well, there are different ways to describe a bell-shaped curve, but many biological measures are described by bell-shaped curves.

MR. GROSSMAN: Well, sir, if you average 8, 9, 10, 11 and 12, you'll produce an average of 10. Correct?

DR. BENOWITZ: Without going through the calculation, I'll take your word for it.

MR. GROSSMAN: And if you average 2, 4, 10, 16 and 18, you'll also have an average of 10. Is that correct?

DR. BENOWITZ: Right.

MR. GROSSMAN: But as you referred to it, the values will be spread out over a very different range and the ability to presume that a study represents the mean will be different in the first case than the second. Is that correct?

DR. BENOWITZ: Right. And that's exactly why I spent a lot of time talking about coefficient and variation, because the standard deviation and the coefficient variation really gives you much more information about what's the likely variability if you just sample someone.

MR. GROSSMAN: And we went through a number of levels, and there were many levels as to which you could not state the coefficient and the variation. Is that correct?

DR. BENOWITZ: That's right.

MR. GROSSMAN: All right, Doctor, and just to sum up on that, you are not suggesting that setting ETS exposure levels without monitoring requires both cotanine measurements and questionnaires and involves the limitations of both of those processes.

DR. BENOWITZ: I don't follow the question.

MR. GROSSMAN: Setting ETS exposure levels if you don't have monitoring requires both cotanine measurement as a marker and the questionnaire to cover the time outside the workplace, and compounds the problems of both of those. The limitations of both of those.

DR. BENOWITZ: Well, I think for an individual that's certainly true. You could also approach it by population data, you know, and say that these are the average cotanine levels of these workers and if we sampled a population, this is the expected exposure at work versus the expected exposure outside of work. So I think you could extrapolate from population data. If you're going to use individuals, I think you're right. You need to get both those bits of information.

MR. GROSSMAN: And if you're going to use population data, they have to be adequately matched to the same individuals in terms of their leisure time activities. Is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: All right. Now, Doctor, you have

JUDGE VITTONE: Mr. Grossman, let me ask you a question. You've been at this an hour and five minutes here. How much longer is this going to take?

MR. GROSSMAN: About 25 minutes, but this would be a good break point if Your Honor wants to take lunch.

JUDGE VITTONE: Let's take five minutes.

AFTERNOON SESSION
1:13 p.m.

JUDGE VITTONE: Dr. Benowitz, welcome back.

Mr. Grossman, if you would proceed again.

MR. GROSSMAN: Thank you, Your Honor.

Dr. Benowitz, hi.

You've testified in a number of proceedings involving cigarettes in the past, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: You testified in a case called Cottler v. American Tobacco?

DR. BENOWITZ: What was the first name?

MR. GROSSMAN: Cottler?

DR. BENOWITZ: Yes.

MR. GROSSMAN: That was a case brought by the relatives of a smoker who alleged injury as a result of smoking?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And you testified on the area of addiction?

DR. BENOWITZ: Yes.

MR. GROSSMAN: You also testified in Canada on behalf of the Crown in a proceeding challenging a Canadian ad ban restriction?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And you've testified in other matters as well?

DR. BENOWITZ: Not in court, but in deposition.

MR. GROSSMAN: Yes. Those were smoking and health cases?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And they were in the area of addiction?

DR. BENOWITZ: Yes.

MR. GROSSMAN: The literature indicates, doctor, does it not, that nicotine aids performance in individuals in a certain number of ways, is that correct?

DR. BENOWITZ: Well, it has affects on performance tests. Many smokers perceive that it's aiding their performance. Whether it is actually aiding their performance in a significant functional way is not clear, as opposed to, for example, reversing a decrement of performance that occurs when they don't have the cigarettes.

MR. GROSSMAN: There are two parts to that. One relates to the performance enhancing characteristics of nicotine, and the other relates, as I understand it, to your view that the people who regularly smoke have a decline in performance when they're not able to smoke.

DR. BENOWITZ: Correct. So when they smoke, that's reversed back to normal.

MR. GROSSMAN: Let's cover both of those as separate bases. You're familiar with David Warbergen?

DR. BENOWITZ: Yes.

MR. GROSSMAN: He and others have written extensively on the effect of nicotine on learning and memory even in those who don't regularly smoke?

DR. BENOWITZ: Yes.

MS. SHERMAN: How are Mr. Grossman's questions on direct smoking relevant to this proceeding?

MR. GROSSMAN: OSHA, in its proposed rulemaking, had an extensive section on performance in the workplace and on productivity. These questions relate to productivity.

MS. SHERMAN: However, your questions involve direct smoking. OSHA's proposal has to do with passive smoking.

MR. GROSSMAN: OSHA's proposal eliminates direct smoking in the workplace.

MS. SHERMAN: I would take issue with that, but...

MR. GROSSMAN: These questions are all around the area of productivity addressed in OSHA's proposed regulation.

MS. SHERMAN: OSHA...

MR. GROSSMAN: I can take out the proposed rulemaking and cite it to you and read it to you if you like.

JUDGE VITTONE: It seems to be in the area of the Proposed Rule, so as long as we're not going to be dragging this out...

MR. GROSSMAN: It will not. I don't anticipate that this entire examination will last more than another 20 minutes, Your Honor.

JUDGE VITTONE: Okay.

MR. GROSSMAN: Dr. Benowitz, David Warbergen and others have written on the affect that nicotine has on learning and memory of even those who are not regular smokers, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And it's the belief of them and other researchers based upon their tests, that nicotine is an enhancement for learning and also for memory, is that correct?

DR. BENOWITZ: Within certain limits. They have been looking at specific types of tests and types of performance and types of memory, and for those tests that they use, that's their conclusion.

MR. GROSSMAN: What types of tests and performance of memory are they referring to?

DR. BENOWITZ: David Warbergen has studied primarily a vigilance task with a repetitive like word matching or like a number matching.

I forget what the exact task is, but it might be something like if you get two numbers flashed at you you have to indicate whether they're both odd or both even or one's odd and one's even, and they're flashed at you at a fast rate, and you have to make responses over a long period of time.

What he's shown is that normally there's a decrement as someone fatigues in their concentration, and if you give nicotine there may be less of a decrement. So it sort of maintains performance in a fatigue situation. That's been his basic type of research paradigm.

MR. GROSSMAN: You have also written that cotanine which is the metabolite of nicotine, is known to relax vascular smooth muscle and dilate blood vessels in vitro, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: That's true in regular smokers or non-smokers?

DR. BENOWITZ: We don't know that that's true in smokers or not. We speculate that it may be, but there still is not definitive evidence that levels seen in humans are having biological effects. They may, and we're looking at that question, but I would not say that they do for sure.

MR. GROSSMAN: In your statement that you have filed in this hearing, you say that smokers smoke for three reasons. One is a compelling need for nicotine; second is direct psychological effects; and the third is relief of nicotine withdrawal syndrome. Is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Let me just break that down.

How soon after a cigarette may a smoker experience a compelling need for nicotine?

DR. BENOWITZ: It's very hard to generalize. I think people smoke in different ways, and there is clearly an interaction between the environment and how compelling the need is for a cigarette.

For example, if someone is stressed and they normally smoke under stress, they might smoke cigarettes at very frequent intervals. Someone who's not stressed may be able to go longer between cigarettes. What's clear is that regular cigarette smokers do have, have for some period of time, a very strong urge or compulsion to smoke again.

MR. GROSSMAN: Just to break that down. Regular smokers include people who may smoke ten cigarettes a day, and they also include people that may smoke 50 cigarettes a day?

DR. BENOWITZ: Yes.

MR. GROSSMAN: There's individual variability in how soon they feel a need for a cigarette?

DR. BENOWITZ: Yes.

MR. GROSSMAN: That varies with mood and with environmental factors?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Including stress on the job?

DR. BENOWITZ: Yes, it could.

MR. GROSSMAN: And some may feel a need for a cigarette only 15 minutes after the last one?

DR. BENOWITZ: Some.

MR. GROSSMAN: And more may feel a need for a cigarette an hour after the last one?

DR. BENOWITZ: I would say yes.

MR. GROSSMAN: That's fairly common?

DR. BENOWITZ: Yes.

MR. GROSSMAN: You also said, apart from a compelling need for nicotine, that smokers receive direct psychological effects from smoking?

DR. BENOWITZ: Yes.

MR. GROSSMAN: What are you referring to in that?

DR. BENOWITZ: There is some question about sort of enhanced reaction time and enhancement in terms of concentration, especially with repetitive tasks as we've talked about before.

There's some evidence that some people use nicotine to modulate mood. If they feel depressed, for example, sometimes nicotine brightens people. So there is some evidence that some people smoke cigarettes to sort of optimize their mood.

MR. GROSSMAN: For those people who smoke cigarettes to optimize their mood, there might be other mental health effects if such people were not allowed to smoke, is that correct?

DR. BENOWITZ: That's been speculated about. It's very hard to show if you look at people who were never smokers versus people who were smokers and then quit smoking, that there's any fundamental difference. But that's been speculated about.

MR. GROSSMAN: That is that some people who suffer from depression use cigarettes to self-medicate their depression?

DR. BENOWITZ: That's a current hypothesis, that's correct.

MR. GROSSMAN: There is some evidence that's being tested to determine whether in fact that is the case?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And if that were, in fact, the case, then if people, if depressed people were not able to self medicate with cigarettes, there would be mental health problems in society that would have to be taken care of by other means.

DR. BENOWITZ: Well, that's a big leap. We don't know that. The issue is what other avenues are there for managing depression, and what does a population do who never started smoking? There's no evidence, if you look at populations where people smoke a lot of cigarettes and those who don't, that there's a fundamental difference in depression rates or whatever. So we don't know enough about that. But I think that issue has been raised.

MR. GROSSMAN: Doctor, you also refer in your testimony to smokers smoking to relieve them of nicotine withdrawal symptoms.

DR. BENOWITZ: Yes.

MR. GROSSMAN: What symptoms are you referring to?

DR. BENOWITZ: The most common ones are anxiety, irritability, restlessness, sometimes problems concentrating.

MR. GROSSMAN: Also depression and hunger?

DR. BENOWITZ: Yes, depression and hunger. Those are certainly longer term withdrawal symptoms.

MR. GROSSMAN: The literature in this area reports a great deal of individual variability, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: There's a debate among psychiatrists and people in the pharmacological fields and otherwise, whether these withdrawal symptoms, as you refer to them, are related directly to the nicotine in cigarettes or to other psychological affects.

DR. BENOWITZ: Well, I think there's no question that there's some relation to nicotine because these effects are relieved if you give nicotine in some other form.

There may be other factors involved but they certainly are, in large part, relieved by nicotine. I've also seen people, say, who use chewing tobacco and stop their use, or even people who use nicotine gum for a long period of time and stop their use. You can reproduce them.

So I think there's no question that the withdrawal symptoms are related to nicotine at some level. Whether there's other things involved as well is still, I guess, of some question.

MR. GROSSMAN: There's reason to believe that workers who are not allowed to work and smoke at the same time would have difficulty coping with anxiety that they previously coped with, with the aide of cigarettes?

DR. BENOWITZ: I think that concern has been raised. To my knowledge there's not been much evidence that that is in fact a problem in the workplace. I've never seen studies dealing with that issue.

In fact, the studies that I know about mostly have talked about the fact that smoking tends to impair productivity and the expectation that when people stop smoking their productivity will increase.

MR. GROSSMAN: I'm not referring to people stopping smoking on a permanent basis. If people are regular smokers but deprived of the opportunity to smoke while at work, that can increase their anxiety, lead to restlessness, reduce their concentration, increase their irritability, and otherwise undermine their productivity, can it not?

DR. BENOWITZ: That is a theoretical concern. I've not seen data showing that that impairs productivity, but certainly that would be of concern. I think what happens usually is that breaks are set up so that people can smoke periodically.

MR. GROSSMAN: We'll get to the question of breaks in a moment, but these questions presume an absence of breaks for a moment.

You have testified, as you said, in a number of smoking and health cases, and in many smoking and health cases, plaintiffs report irritability, restlessness, mood disorders, anxiety, even an hour after they had their last cigarette. You're familiar with that are you not?

DR. BENOWITZ: Yes, that can happen.

MR. GROSSMAN: You're saying you do not disagree with those self reports?

DR. BENOWITZ: I think some people do experience that.

MR. GROSSMAN: And people who do experience that would be less productive on the job, if they could not take a break to take a cigarette, is that correct?

DR. BENOWITZ: That's a concern. Again, I've not seen any data from work places where that has really been established. I guess the issue is whether, in fact, people do work out ways to smoke cigarettes at appropriate intervals to feel comfortable. I think what you're saying is a concern, if smoking were not allowed then they could not smoke or get nicotine any other way, but I'm not aware that's been looked at empirically.

MR. GROSSMAN: So you're aware of no tests regarding that empirically.

DR. BENOWITZ: In the workplace, that's correct.

MR. GROSSMAN: Are you familiar with tests regarding that empirically outside of the workplace?

DR. BENOWITZ: It's been tested using batteries of performance tests, for example. Doing reaction times or doing number matching or a variety of other sorts of behavioral tests. Those have been probed after someone stopped smoking, and you can see impairments occurring.

MR. GROSSMAN: And you can see impairments occur within a matter of hours, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: If those impairments as demonstrated in the performance tests were mimicked in the workplace there would be reduced productivity of the workers involved, is that correct?

DR. BENOWITZ: It would be very specific for the tasks. I guess I could conceive of some types of work performances which would be relevant to those tasks. Again, I haven't seen it looked at with respect to work performance directly.

MR. GROSSMAN: Doctor, you referred earlier to workers stepping out to take breaks. Not all workers can step out to take breaks to smoke, isn't that correct?

DR. BENOWITZ: Most can at some time intervals. I guess the question is how frequently.

MR. GROSSMAN: If workers were allowed to leave their workstation in order to smoke elsewhere, and not allowed to take their work with them to the smoking area, that alone would diminish their productivity, would it not?

DR. BENOWITZ: It could.

MR. GROSSMAN: Unless you increased the total number of hours in their work day.

DR. BENOWITZ: It could.

MR. GROSSMAN: There are some workers who cannot leave their work station, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: For example, I assume you know that under the FCC rules, the passenger cabins of airplanes are smoke free, no one can smoke in them, but the flight cabin allows smoking. Are you familiar with that?

DR. BENOWITZ: Yes.

MR. GROSSMAN: A pilot on an eight hour trip has nowhere to step out of the flight cabin, is that correct?

DR. BENOWITZ: Correct.

MR. GROSSMAN: And he has the kind of high stress job, as an example, where he might rely upon cigarettes to relieve his anxiety, is that correct?

DR. BENOWITZ: I wouldn't go so far as to say that. I'd say if someone happened to be a smoker, and I think there are relatively few smokers nowadays among pilots. But if you happen to be a lifelong smoker, then you may well smoke when you're stressed.

MR. GROSSMAN: And there's reason to believe that a pilot in a six or eight hour flight who was a regular smoker and was deprived of the opportunity to smoke while working, may have increased anxiety, restlessness, and reduced concentration, is that correct?

DR. BENOWITZ: Yes.

MR. GROSSMAN: The same would be true of people in other occupations, is that correct?

DR. BENOWITZ: Yes. Of course it's very task specific in terms of how much impairment there would be.

MR. GROSSMAN: You've testified that the dose that a smoker receives from cigarettes, is constant regardless of the nominal value of the cigarette as measured by FTC?

DR. BENOWITZ: I didn't say constant. I said it averages about a milligram, and that there is a relatively poor correlation for an individual between how much they take in and the nominal yield. So it's not to say that everyone takes in one milligram.

Some people take in half a milligram, some people take in two milligrams, but what they take in is not related to the nominal yield.

MR. GROSSMAN: The amount of nicotine that smokers take in is not related to the nominal yield of the cigarette as measured by FTC methods, but rather is related to the way that they smoke the cigarettes?

DR. BENOWITZ: Yes, more or less. There is a poor correlation with yield, but it's very shallow and it's not a very good predictor.

MR. GROSSMAN: And the amount of nicotine that a smoker takes in is unrelated to the question of whether the cigarette is made of burlee tobacco or flue cured tobacco?

DR. BENOWITZ: I haven't seen specific data on that. My guess would be it probably is independent of that, but I've never seen a study designed looking at those parameters explicitly.

MR. GROSSMAN: It's generally independent of brand?

DR. BENOWITZ: Yes.

MR. GROSSMAN: And so it's your testimony that if, well let me take it one step back.

Your testimony earlier was that the principle agents in cigarettes, that it is hypothesized account for the increased risk of disease from cigarettes, are primarily things other than nicotine?

DR. BENOWITZ: Yes.

MR. GROSSMAN: Overall then, if smokers self regulate to take the same amount of nicotine from cigarettes regardless of the nicotine yield of the cigarette, it would be better to have a high nicotine, low tar cigarette rather than a high tar, low nicotine cigarette? From a public health standpoint?

DR. BENOWITZ: It depends on your time perspective. For example, if you're looking in the short term, and this is an approach that has been addressed in the UK, a person would probably consume less of other toxic components if you had a high nicotine cigarette.

The issue of the long term, there is some evidence that when you decrease nicotine, and especially the person that's trying to cut back on their smoking, but in the long term there may be some regulation of nicotine intake and some evidence that over the long run you may be able to decrease total exposure if you reduce nicotine levels in cigarettes.

And in fact I proposed that if one did that to a certain point in time, one could eventually have a cigarette that's not addicting which would give smokers much more freedom of choice as to whether they wanted to smoke or not because they wouldn't be compelled by nicotine addiction.

So there are sort of two issues. The short term issue, in which case I would agree with you; and then there's long term issue. I think there's evidence that you could lower exposures over a long period of time by gradually reducing nicotine.

MR. GROSSMAN: What do you hypothesize is the threshold level of nicotine per cigarette that would lead to a non-addictive cigarette in your estimation?

DR. BENOWITZ: The estimation is based on a daily intake of about five milligrams, and so it depends on how many cigarettes. But if you allow that people may smoke as many as 20 cigarettes a day, it ends up with a total nicotine intake of less than .25 milligrams per cigarette.

Which would require cigarettes with tobacco that contain less than half a milligram of cigarette per tobacco rod. So many maximum smoking efficiency.

MR. GROSSMAN: There are cigarettes available...

MS. SHERMAN: Excuse me.

The line of questioning, I fail to see how it's relevant to this proceeding and this proposal.

MR. GROSSMAN: I'm almost done with this, Your Honor. I've got only about two more minutes.

JUDGE VITTONE: Let's wrap it up then.

MR. GROSSMAN: Okay.

Doctor, if nicotine were added to current levels of cigarettes, it would not have an affect on smoking conduct as you understand it?

DR. BENOWITZ: What was the question?

MR. GROSSMAN: If nicotine were added to cigarettes that are in the marketplace now, would it have an affect upon smoking conduct as you understand it?

DR. BENOWITZ: It might. It's hard to tell for sure, but that's certainly been the proposition say in the UK analysis, that people might smoke less if they got more nicotine per cigarette.

MR. GROSSMAN: If there were higher nicotine cigarettes available on the marketplace, people might smoke fewer cigarettes?

DR. BENOWITZ: Either smoke fewer cigarettes or puff less intensely from each cigarette.

MR. GROSSMAN: I have no further questions.

Thank you very much, doctor.

JUDGE VITTONE: Thank you, Mr. Grossman.

MS. SHERMAN: Can you add that chart that you were making in front of the room to the record so that we will be able to decipher the transcript testimony?

MR. GROSSMAN: Yes, I'd be happy to.

MS. SHERMAN: That should be Exhibit No. 30.

(The document referred to was marked for identification as Exhibit No. 30 and received into evidence.)

MR. GROSSMAN: It is a three-page chart. Should I tear it off?

JUDGE VITTONE: Ms. Sherman, are you sure you want this in the record?

MS. SHERMAN: Yes, we may want to reduce it in size if that is possible, but I think it will make the transcript easier to understand.

JUDGE VITTONE: Okay. That's fine.

Mr. Rupp?

MR. RUPP: Thank, you, Your Honor.

Dr. Benowitz, my name is John Rupp. You've been very patient. I'll try to be as quick as I can with my questions this afternoon.

I note that you cite two health effects studies in your testimony, and I think you mentioned them this morning in your oral presentation as well. Strecker 1989 and Strecker 1990 to support the proposition that several different biological effects of ETS have been shown to be quantitatively related to cotanine levels, supporting the idea that cotanine levels do reflect ETS exposure and effects, is that correct?

DR. BENOWITZ: Yes.

MR. RUPP: I wonder whether the citations in your statement should not be instead of to Strecker to Strachan,
S-T-R-A instead of E, is that correct?

DR. BENOWITZ: Yes.

MR. RUPP: The first Strachan article appeared in the British Medical Journal in 1989 beginning at page 1549, a British Medical Journal article in any event.

DR. BENOWITZ: Yes.

MR. RUPP: And the second Strachan article that you've cited appeared in the Journal of Laryngology and Ontology in 1990?

DR. BENOWITZ: I don't have those with me, but it may well be. I'd have to check.

MR. RUPP: Do you want to take just a second to do that?

(Pause)

DR. BENOWITZ: The second one was from, I have the American Review of Respiratory Disease, Volume 142, page 147, 1990.

MR. RUPP: Okay, yes, starting on 147. There is, then, a third article, and I'm wondering whether you have reviewed that, in the Journal of Laryngology and Ontology in 1990. Have you reviewed that article in the same cohort of
children?

DR. BENOWITZ: I probably have it, but I don't recall the specifics of the article.

MR. RUPP: Let me focus on the other two first. Your understanding, I take it, is that the first Strachan article reported a statistically significant association between salivary cotanine level and the incidence of middle ear effusion in children seven years of age?

DR. BENOWITZ: Yes.

MR. RUPP: And that effusion was as indicated by the application of tympanograms?

DR. BENOWITZ: I believe so.

MR. RUPP: Can you explain to us very briefly how the tympanogram measures work? How does one take a tympanogram?

DR. BENOWITZ: I've not done that. I'm not a pediatrician. But it basically looks at the distensibility of the eardrum, I believe. So if there's fluid it becomes...

MR. RUPP: It uses waves, does it not, and tries to measure the smoothness or the amplitude of waves hitting the eardrum through the eustachian tube?

DR. BENOWITZ: Again, I don't use that, so I really can't go beyond what I've said.

MR. RUPP: All right. What you have said in your testimony is that with a doubling of salivary cotanine over baseline, the odds ratio for type B tympanograms was 1.14 with a 95 percent confidence interval of 1.03 to 1.27, is that correct? That's in the first article, as I recall.

DR. BENOWITZ: That's not what I said in my testimony. What I basically did is show a figure in my testimony.

MR. RUPP: Do you have the article there?

DR. BENOWITZ: I don't have the article with me.

MR. RUPP: Which figure are you referring to on which page?

DR. BENOWITZ: I made my own figure from their data.

MR. RUPP: Let's use the data themselves, because I think it's easier to talk about the numbers than it is to talk about figures which, of course, can be affected by scaling.

DR. BENOWITZ: I can't talk about the numbers, because I don't have a copy of the paper.

MR. RUPP: I think I can help you out there.

DR. BENOWITZ: Great.

(Pause)

DR. BENOWITZ: Thank you.

(Pause)

MR. RUPP: Your Honor, since we're going to use these for our discussion, perhaps I should ask them to be marked as an exhibit at this point.

JUDGE VITTONE: Okay. This will be Exhibit No. 31.

JUDGE VITTONE: Is this already in the record, though, Ms. Sherman?

MS. SHERMAN: I'm not sure. The article's by Strachan, Jarvis, and Firebend, and it's entitled "Passive Smoking Salivary Cotanine Concentrations and Middle Ear Effusion in Seven Year Old Children."

MR. RUPP: Actually, Your Honor, there are three articles attached. The three Strachan articles that Dr. Benowitz and I have been discussing are all in that set.

JUDGE VITTONE: These are the articles referred to in his testimony, right?

MR. RUPP: He has referred to two of the three, Your Honor, so this is the set of all three studies that have been reported. All three reports, thus far, on the same cohort of children looking at respiratory disease and middle ear effusion.

MS. SHERMAN: Have you another copy of that?

MR. RUPP: Yes, I do.

JUDGE VITTONE: For the clarity of the record,
let's make this Exhibit No. 31.

(The document referred to was marked for identification as Exhibit No. 31 and received into evidence.)

MR. RUPP: Dr. Benowitz, as I read the first of those articles, the odds ratio that was reported for the Type B tympanograms which is the pertinent measure, was 1.14 with a 95 percent confidence interval of 1.03 to 1.27, is that correct?

Do you see those numbers in the first article? I'm talking now about the British Medical Journal article, the 1989 publication.

As a matter of fact, if you look in the abstract of that article you'll see those numbers reprinted.

DR. BENOWITZ: What that's saying, the odds ratio for a doubling of the cotanine concentration.

MR. RUPP: Right. What these investigators did, did they not, was they arrayed the group of the cohort of children that they were studying into five groups, quintiles, if you will, with increasing levels of cotanine measured.

DR. BENOWITZ: Right.

MR. RUPP: And the odds ratio for the highest two levels of salivary cotanine over baseline for Type B tympanogram was 1.14 with a 95 percent confidence interval of 1.03 to 1.27, do you see that?

DR. BENOWITZ: No. Not for the highest group. I see that's the odds ratio for a doubling of concentration. So that is if you go from a concentration of one to two, you see a relative risk of 1.14.

But if you look at Table 2, and you look at the fourth column which is Type B abnormal tympanogram, and then you look at the prevalence of abnormality in the population on the last five lines by quintile, you will see that the prevalence basically doubles as you go from the lowest quintile to the highest quintile.

MR. RUPP: Right. But the odds ratio that we're talking about, the overall increase in incidents from one to the other, is as reported in the abstract, and also reported in the body of the paper, is 1.14, with an appropriate odds ratio attached.

DR. BENOWITZ: The odds ratio has to specify what you're comparing.

MR. RUPP: Right. And as the authors have said, with a doubling of, there was a trend toward more abnormal tympanogram, metric findings with increasing cotanine concentrations. The odds ratio for doubling of the cotanine concentrations being 1.14 (95 percent confidence interval, 1.03 to 1.27.)

DR. BENOWITZ: That is for doubling. That's not the same thing as comparing the lowest group with the highest group.

MR. RUPP: Let's focus on this to begin with, shall we?

DR. BENOWITZ: Yes.

MR. RUPP: Are you aware that when adjusted for the child's gender and housing tenure, and for no other potential confounders for middle ear effusion, the significance of that increase from a doubling of salivary cotanine levels, disappeared. So that the odds ratio at the 95 percent confidence interval encompassed one.

DR. BENOWITZ: Yes.

MR. RUPP: Let's focus for a moment on the second Strachan article that you mentioned. That article reported on that same cohort of children, did it not?

DR. BENOWITZ: Probably. I wasn't sure if it was exactly the same...

MR. RUPP: If you compare the numbers, I think you'll find that the numbers match.

DR. BENOWITZ: It's about the same number, but whether they're exactly the same kids or how it was dealt with, I assume they were the same, but...

MR. RUPP: Okay. And that article reported a crude association between, an unadjusted, let me say, association between number of smokers in the household and Type B tympanograms in the children, correct?

DR. BENOWITZ: Yes, although this was not a paper that I cited.

MR. RUPP: Have you had a chance to review that quickly?

DR. BENOWITZ: I just took a quick look at it. It's hard for me to comment in detail.

MR. RUPP: Do you find, Dr. Benowitz, the passages of that paper that also report that after adjustment for housing tenure, domestic crowding, gas cooking, and damp walls, and for no other confounders of middle ear effusion, the association between number of smokers in the house and Type B tympanograms disappeared.

DR. BENOWITZ: I'd have to take your word for it because I haven't had time to read this paper to...

MR. RUPP: Why don't you look at the table and the discussion, and I think you can find this perhaps most easily in the discussion portion. The odds ratio for one smoker after adjustment for the factors that I've mentioned was 1.04 with a 95 percent confidence interval of .056 to 1.78; and for two or more smokers the odds ratio was 1.8 with a 95 percent confidence interval of 0.96 to 3.40.

So again, both were not statistically significant, or rather I should say neither was statistically significant at the 95 percent confidence interval.

DR. BENOWITZ: Yes, I see that, that that's stated.

MR. RUPP: Let's take a look at the third Strachan publication, and this is the second of the two that you have cited in your testimony today so perhaps you'll be more familiar with that. Again, on the same cohort. Correct?

DR. BENOWITZ: Yes.

MR. RUPP: That article reported a weak association between salivary cotanine levels and number of smokers in the home. The article also reported, however, that three quarters of the children from non-smoking households had detectable salivary cotanine, and that ten percent of the children from non-smoking households had high cotanine levels which were in the upper two of the five quintiles. Is that your recollection as well?

DR. BENOWITZ: I haven't found that here specifically, but I don't doubt that.

MR. RUPP: I think you explored with Mr. Grossman some of the problems that bedevil the use without more of questionnaires to try to get a handle on exposure to ETS. I take it that these data do tend to confirm the problems that questionnaires can involve, their imprecision, if you will.

DR. BENOWITZ: There are a lot of issues with questionnaires that are quite complex, including the nature of the questionnaire, the amount of details in it...

MR. RUPP: The method of their administration.

DR. BENOWITZ: So it's hard for me to generalize about that. What I told Mr. Grossman is that there are studies that say there is no relationship between a particular questionnaire and cotanine levels, but I think going beyond that you really have to consider what questionnaires are being used, how they're administered, what the questions are, etcetera.

MR. RUPP: But here what you have is a cohort of children, ten percent of which, essentially 70 out of the 700, were not living with a smoker but yet had salivary cotanine levels of in the top ten percent of those included in the study. So that those studies that rely on parental status as a smoker, and that alone, have some problems, do they not?

DR. BENOWITZ: Well, it's not perfect in terms of predicting in the home, but the other question is, was there exposure outside the home? Caregivers, etcetera.

MR. RUPP: And presumably, this suggests that there may well have been. Or there may have been dietary sources, a whole host of things could have been going on here.

DR. BENOWITZ: Yes. Some other source other than smokers in the home. That's correct.

MR. RUPP: The cotanine data, particularly in the report that we're now discussing, also suggests, do they not, that some of the children in the Strachan cohort, were active smokers? That is, for several of the children, cotanine values exceeded 36.1 nannograms per milliliter?

DR. BENOWITZ: Yes.

MR. RUPP: Is that not above the cutoff one would typically think of between smoking and non-smoking?

DR. BENOWITZ: Yes, it is.

MR. RUPP: Strachan and colleagues also reported in their third article, data on salivary cotanine and the incidence of respiratory symptoms and pulmonary function levels, do you recall that? Indeed, I think you've talked about that in your testimony.

DR. BENOWITZ: Yes.

MR. RUPP: While a statistically significant, although weak association was reported between chest
colds -- that's the phrase used in the article -- and cotanine levels, no association was reported, if I have read the article correctly, for the following. Runny nose, night cough, day time cough, wheeze, sore throat, ear trouble, or hay fever. Is that correct?

DR. BENOWITZ: Well, you really have to know exactly how they define "ear trouble", and I think without having that information, that's hard to --

MR. RUPP: Let's assume, for purposes of our current discussion, the definition is the same and the only thing that is changed is a bit of time is passed between Report No. 1 and Report No. 3, if that is correct, and of the article will tell us whether that is correct, hopefully.

We have an unadjusted association that one adjusted went to insignificance with a doubling of cotinine levels and then disappeared entirely by the time of the second report, do we not? Would we not on those assumptions?

DR. BENOWITZ: Yes.

MR. RUPP: All right. Now, wouldn't it also be fair to say that focusing now again on the third article, which I think you have before you, that there was no overall and certainly no consistent association between cotinine levels and childhood respiratory health, as determined by the incidence of adverse respiratory symptomatology?

DR. BENOWITZ: Yes.

MR. RUPP: Indeed, the authors report precisely that, do they not?

DR. BENOWITZ: Yes.

MR. RUPP: With regard to pulmonary function parameters, the third article reports no association between cotinine and most baseline parameters. I'm referring here to FVC, FEV-1, FEV-0.5, FEF 25-75, FEV 1/FVC; FEF 25/75/FVC, and FEF 75-85/FVC. Is that correct?

DR. BENOWITZ: Yes.

MR. RUPP: That author has also found no association between cotinine and exercised-induced bronchospasm in normal spasm or children with a history of wheeze. Isn't that also correct?

DR. BENOWITZ: Yes.

MR. RUPP: Now, indeed, the only significant association reported in the third article was between cotinine and FEF 75 and FEF 75-85. Isn't that right, between the pulmonary function parameters?

DR. BENOWITZ: Yes. Although I should point out that all of the other measures had a tendency to worsening with higher cotinine levels, just those
two --

MR. RUPP: I'm sorry. I didn't catch that.

DR. BENOWITZ: All of the other measures had a tendency to worsen with higher cotinine levels, but only those two reached statistical significance.

MR. RUPP: Right. But they weren't statistically significant.

DR. BENOWITZ: Right.

MR. RUPP: Right.

DR. BENOWITZ: But 8 or 10 measures all going in the same direction, even though 2 are significant, is certainly suggestive that even though a lot of them --

MR. RUPP: All right. Well, let's just make clear on the record, at this point, that the other parameters were not statistically significant. The only two that were the ones I've mentioned.

DR. BENOWITZ: Okay.

MR. RUPP: Right? Now, let's go to some of the points that are included in your explanation. Let me read to you a passage from the OSHA Preamble in this proceeding and ask you whether you would agree with it.

I understand this is not your area of practice. Is that a correct understanding?

DR. BENOWITZ: That's correct.

MR. RUPP: Let me see, nonetheless, whether this is something that seems right to you. Quote -- and I'm quoting now from the Preamble.

"There is no clear consensus in the medical literature as to the routine clinical use of the FEF 25-75 or FEF 75-85, or their diagnostic in and independently detecting small airway disease."

Does that some right to you?

DR. BENOWITZ: Yes.

MR. RUPP: All right. Now, what are some of the problems, particularly when we're talking about children, so far as the use of functional parameters of the sort we've been discussing or concern.

If one problem that they rely upon effort on the part of the child, which, if it's going to be reliable and valid, has got to be consistent over the various times the test has taken?

DR. BENOWITZ: Yes.

MR. RUPP: And that's a greater problem to stimulate that in children than it is in adults?

DR. BENOWITZ: Yes. It's a greater problem with younger children. I think age 7, you might be able to get most of them to do a pretty good job.

MR. RUPP: All right. But even with adults, as the OSHA Preamble indicates, there is very substantial doubt, amply documented in the literature from both clinicians and others, raising questions about the validity of small changes in pulmonary function as evidenced by these tests, is there not?

DR. BENOWITZ: Well, not exactly the way you phrased it. The question is how they relate to clinical disease, I think.

MR. RUPP: That's not the issue I'm getting to, although I want to ask you about that as well.

DR. BENOWITZ: But, you know, if you say validity, if it's measured accurately and you have a big enough population, then you can see a valid effect, that there is an effect associated with a higher cotinine level.

Now, what that effect means is a different question.

MR. RUPP: All right.

DR. BENOWITZ: Whether you have a valid observation, I think you do have a valid observation.

MR. RUPP: Well, again, let's take it in two parts. The first question, I take it, is whether one of these tests -- two of these tests that may differ slightly -- let's use that word for the present, despite it's imprecision -- whether those differences are meaningful. That's the first question one must ask, correct? That is a range of error of the instrumentation?

DR. BENOWITZ: Yes.

MR. RUPP: All right. These are instruments that are known to have a substantial range of error, are they not?

DR. BENOWITZ: Yes. But this is a statistical issue. When you do a study in 700 people, you can deal with that variability because you population is large enough.

If it comes out statistically significant, it means that, in spite of the variability, you see still an effect.

MR. RUPP: But for most of the functional parameters we've been discussing, there was not statistical significance?

DR. BENOWITZ: Correct.

MR. RUPP: We also have, then, of including whether children 7 years of age or younger can be expected to, with the use of this equipment yield reproducible results, is there not?

DR. BENOWITZ: Yes. But, again, that's dealt with in the measures of variability that are considered in doing statistics. That basically brings in random noise of the measurement, which means it's harder to show significant effect, but if you have a big enough population and you show an effect, it means you've considered that variability, you considered that noise, and there's still an effect.

MR. RUPP: Is it your understanding that the typical statistical test used in circumstances of this sort accounts not only for sampling errors, but also for or sampling disparities of problems, but also for margins of error that may be built into the equipment being used?

DR. BENOWITZ: It accounts for any random error, which means, as long as there is not an error that is somehow related to the factors you're tryin to predict and your predictors, it was a random error, and statistics account for it.

MR. RUPP: I take it you would agree that there are a variety of factors that have been associated or identified as risk factors for middle ear effusion in children?

DR. BENOWITZ: Yes.

MR. RUPP: Those would include dampness of the housing?

DR. BENOWITZ: Mostly things like allergies, are the strong ones.

MR. RUPP: Allergies. Crowding?

DR. BENOWITZ: I don't know about dampness and crowding. The main one I know about is allergy.

MR. RUPP: Strachan and colleagues corrected for dampness in housing here, and their statistically significant result is here. Is that correct?

DR. BENOWITZ: I would have to go over it, but if you tell me that's what it says, I don't question you.

MR. RUPP: Right. Prior history of respiratory problems -- familial respiratory problems.

DR. BENOWITZ: Yes.

MR. RUPP: Incidents of coughs and colds in the parents and other siblings?

DR. BENOWITZ: Well, that's a little bit -- oh, in other family members?

MR. RUPP: In other family members.

DR. BENOWITZ: Yes. That's a little tricky, because that's a potential confounder with the issues of, say, environmental tobacco smoke. Why are they all coughing.

MR. RUPP: Right.

DR. BENOWITZ: So that's not a random factor. That's a fact.

MR. RUPP: But it's a complication that one needs to take into account?

DR. BENOWITZ: That's a sophisticated statistical question. Whether you should control for something that you think is linked, causally, with your predictor.

MR. RUPP: What about other aspects of socioeconomic status, which might include family income, prenatal and, in this case, perhaps more significantly, postnatal care of the degree and frequency of medical care or attendance at day care.

Would those be factors that one would take into account and looking at the respiratory health of children?

DR. BENOWITZ: If possible, yes.

MR. RUPP: There are a variety of other confounders that also have been identified in the literature on childhood respiratory health and also have been identified as important potential confounders and circumstances of this sort, are there not?

DR. BENOWITZ: Probably. I don't know specifically which ones you have in mind.

MR. RUPP: Do you know how many potential confounders in any of the three reports that we've been discussing, or all three together, Strachan and co-workers took into action, or collected data on that would permit them to take into account?

DR. BENOWITZ: I would have to re-review the papers to answer that question.

MR. RUPP: Let me read to you an observation that has been made concerning the three Strachan articles and ask whether, in view of the discussion we've been having, you would agree generally.

"The Strachan data illustrate the dangers of relying upon unsubstantiated reports of ETS exposure, gathered using questionnaires, and relying upon crude measures, such as, number of smokers in the household."

DR. BENOWITZ: What is the context of that statement?

MR. RUPP: Do you agree with that statement, or is that a statement with which you would have problems? I take it that's one of the reasons you where looking at salivary cotinine?

DR. BENOWITZ: Yes. I'd like to know the context of that sentence, but I do think that salivary cotinine is a better marker than some problem. You know, it's always hard for me to evaluate a sentence like that, just out of context.

JUDGE VITTONE: Is that from a particular article, Mr. Rupp?

MR. RUPP: No. I have no citation to give.

Let me shift gears slightly, if I may.

Dr. Benowitz, the anatomy of the ear in adults and children is quite different, is it not?

JUDGE VITTONE: Certainly the size of the passages changes.

MR. RUPP: Indeed, even the slope of the Eustachian tube is different, is it not?

DR. BENOWITZ: I'm not an expert in that are, but I would certainly expect that to be the case.

MR. RUPP: Have you reviewed in anything like a comprehensive fashion, epidemiologic literature relating to environmental tobacco smoke in the incidence of cardiovascular disease among nonsmokers?

DR. BENOWITZ: Not in a detailed, critical way. I certainly have read a number of articles and reviews in the area, but not enough that I could discuss the details of them.

MR. RUPP: Not enough to discuss the details of individual studies?

DR. BENOWITZ: Correct.

MR. RUPP: Is it also possible that you've missed a fair amount of the pertinent literature in that area or have you tried to look to collect it all, at least comprehensively?

DR. BENOWITZ: You know, try to collect the major papers. I don't have all of them, but I have several papers that I've looked at. I certainly have looked at the article that Dr. Glantz wrote and Steenland, I think -- Dr. Steenland.

MR. RUPP: Kyle Steenland. Those were reviews?

DR. BENOWITZ: Right. Those were reviews.

MR. RUPP: Rather than basic studies?

DR. BENOWITZ: you know, I've looked at a few of the primary papers, but I have not looked at them in critical light.

MR. RUPP: You, I take it then, would not feel comfortable testifying of your own personal knowledge and after your own analysis about the various issues that have been raised with respect to ETS and cardiovascular disease, epidemiology?

DR. BENOWITZ: At this time, that's correct.

MR. RUPP: In a paper that you published in Trends in Cardiovascular Medicine, entitled, "Cotinine and Coronary Heart Disease," in I think 1991, you stated as follows --

DR. BENOWITZ: Let me just correct that. Nicotine and coronary heart disease.

MR. RUPP: Nicotine. What did I say?

DR. BENOWITZ: Cotinine.

MR. RUPP: And we know that they're not the same, at this point, don't we?

DR. BENOWITZ: Yes.

MR. RUPP: Cotinine and coronary heart disease, 1991. Do you recall that paper?

DR. BENOWITZ: Yes.

MR. RUPP: There was a statement in that paper. Actually, there are many statements of interest, but the one statement I'd like to ask you to elaborate on for a benefit, if you will, is the following:

There are no good models for cigarette smoking or nicotine induced arterioslcerosis in animals, and then you refer to some of the problems with the use of high dose and the difficulties of extrapolating results and the animal species that have been used from the animals themselves to humans.

I would appreciate your elaborating on that point a bit, if you will. What are some of the problems that you see in this extrapolation issue? I take it it has at least two parts. One is consideration of dosimetry and also differences in the animals as opposed to when compared with humans.

DR. BENOWITZ: Yes. There have been some animal studies that have just used phenomenally high doses, and I think it's difficult to make extrapolations of the pharmacology or toxicology of high doses in animals to those seen in humans.

The problem with animal models of atherosclerosis is, in general, animals are pretty resistent, unless you give them some other factor.

So, for example, most studies in non-human primates put the animals on an atherogenic diet, like a high cholesterol diet or high-fat diet, to increase their baseline rates of atherosclerosis, and then they look at different stressors and see if those different stressors can accelerate the atherosclerosis on top of that sort of stimulus.

I think that's a very common model that's used nowadays for atherosclerosis, although I have to say, there are some exciting findings of genetically engineered animals that will develop spontaneous atherosclerosis, quite interesting study. Those are new models.

MR. RUPP: Right. I'm aware of those.

There are also some species, are there not, that, quite to the contrary of the situation you have described, cockerels, for example, that develop arteriosclerotic plaque spontaneously --

DR. BENOWITZ: Yes.

MR. RUPP: -- at a much more rapid rate than humans do as well.

DR. BENOWITZ: Yes.

MR. RUPP: So there is a kind of converse series of problems that get in the way of our trying to extrapolate those results to humans as well?

DR. BENOWITZ: Yes.

MR. RUPP: I take it you would agree that, in the area of heart disease, and perhaps you would say the same about others, but focusing now only on heart disease, that questions of dosimetry are critical if we're going to discuss an issue of that sort in an intelligent way?

DR. BENOWITZ: Yes.

MR. RUPP: Thank you, Your Honor.

JUDGE VITTONE: Thank you, Mr. Rupp.

MR. RUPP: Thank you, Dr. Benowitz.

DR. BENOWITZ: You're welcome.

JUDGE VITTONE: The gentleman from -- I'm sorry.

DR. WEINBERG: Yes, Your Honor. I'm (inaudible). The questions that I have are generally covered by (inaudible).

JUDGE VITTONE: Thank you, sir.

Mr. Dinegar. Five minutes.

JUDGE VITTONE: Five minutes. Fine.

MR. DINEGAR: I'm Jim Dinegar with Building Owners and Managers Association, Hearing Docket 1.

I read through your estimate, Doctor: Cotinine is a valid maker of environmental tobacco smoke exposure. I kind of thought that said it all until I heard a number of the questions, so I want to go through a couple of others, to get back on the record where we started with this testimony.

As I understand it, nicotine is converted by the human body into cotinine. Is that correct?

DR. BENOWITZ: Yes.

MR. DINEGAR: It is your assertion that the measurement of cotinine is a marker for ETS exposure?

DR. BENOWITZ: Yes.

MR. DINEGAR: In your estimation, are there more specific available markers?

DR. BENOWITZ: Well, there's nothing that is sensitive enough in humans at this point in time, besides cotinine or nicotine. Those are the only -- other markers, while they may be specific, we just can't measure them in passive smoking.

MR. DINEGAR: You go on to assert that cotinine is a valid quantitative marker of environmental tobacco smoke exposure. Not being a scientist, does that mean that you can accurately identify levels of exposure of nonsmokers to secondhand smoke?

DR. BENOWITZ: Yes, within reasonable limits. I would restate that for an individual -- for a single person -- it's difficult to say exactly what that exposure has been, but certainly if you have a population that you're sampling, you can get a pretty good idea from measuring cotinine levels of what that population's exposure was to environmental tobacco smoke.

MR. DINEGAR: Have you done studies in that vein to maybe some up with estimates of exposure from nonsmokers, exposure to environmental tobacco smoke?

DR. BENOWITZ: My involvement, I've worked with other people in terms of assaying cotinine levels. I have worked on the pharmacokinetic basis for converting levels in plasma or urine or saliva to exposure.

What I would say is that the data that are available in total, if you look at the levels that are seen in most workplaces, when that's been studied where there's smoking, and the levels that are seen in the urine of people with exposure to ETS, and the pharmacokinetic calculations, they all fit together.

They all give the same general answers, and therefore I'm confident that the overall assessments of exposure are reliable.

MR. DINEGAR: Are you aware that the EPA has classified secondhand tobacco smoke as a Group A carcinogen?

DR. BENOWITZ: Yes.

MR. DINEGAR: Is that caused because of the nicotine exposure --

DR. BENOWITZ: No.

MR. DINEGAR: -- of environmental tobacco smoke? What health effects, or adverse health effects, if any, are associated with involuntary exposure to nicotine?

DR. BENOWITZ: It's not known which, if any. I personally do not think nicotine is a very important toxin for environmental tobacco smoke. I think other things are much more important, and nicotine is primarily a marker.

MR. DINEGAR: Flip it around then.

Earlier we heard that nicotine also provides a stimulant to the human system. There are benefits associated with the ingestion of nicotine. Is that so?

DR. BENOWITZ: Well, that's a complicated question. Benefits --

MR. DINEGAR: Increase productivity, increased energy, increased --

DR. BENOWITZ: That's never been shown. What has been clearly shown is that when smokers do no have cigarettes their impairment is decreased and when they're allowed to smoke again, their performance is normalized.

Those are the soundest data. No one has ever looked at productivity or tried to translate that. Certainly, no one has ever shown that a person is more productive because they're a smoker or because they're using nicotine than they would have been had they not been a smoker.

MR. DINEGAR: So you're not aware of any data that would show that?

DR. BENOWITZ: No. In fact, the opposite is true. When you look at smokers, their productivity in the workplace is substantially less because their sick more often, they have more severe illnesses when they do get sick. They have more absteneeism. They have more accidents.

They lose a lot of time just manipulating smoking materials. It's been estimated that a substantial loss of productivity is related to smokers.

MR. DINEGAR: I'm aware of those estimates, but there is no scientific evidence right now that points to an increase in productivity or a decrease in productivity, now, based on exposure to nicotine or exposure to environmental tobacco smoke?

DR. BENOWITZ: Not that I'm aware of.

MR. DINEGAR: You may be aware that in countries like Japan, exposure to peppermint in the airwaves are used to increase productivity, or at least they're argued to increase productivity. Aroma therapy is the name they're given.

Are you aware of any benefits associated in productivity now, with exposure to environmental tobacco smoke, whether it's by the odor or by the nicotine or by any of the other byproducts associated with environmental tobacco smoke?

DR. BENOWITZ: No. no, I'm not.

MR. DINEGAR: Thank you. Thank you, Your Honor.

JUDGE VITTONE: Thank you, Mr. Dinegar.

I think that takes care of everybody in the audience.

Ms. Sherman.

MS. SHERMAN: Just a minute, Your Honor.

MS. JANES: Dr. Benowitz, are you aware, what are some of the effects of smoking restrictions and can you cite any studies?

DR. BENOWITZ: On effects of working restrictions?

MS. JANES: Workplace smoking restrictions.

DR. BENOWITZ: Well, people smoke fewer cigarettes. Those people who continue to smoke do smoke fewer cigarettes throughout the day. I don't know if there's been any translation yet in terms of less adverse health effects. There's also evidence that about 25 percent of people quit smoking when smoking is banned in the workplace, which I think has long-term benefits for those people. Those are the only studies I'm aware of.

MS. JANES: Okay.

MS. SHERMAN: Dr. Benowitz, do you consider yourself a ventilation expert?

DR. BENOWITZ: No.

MS. SHERMAN: Have you done any studies of ventilation as it relates to home exposure to ETS as opposed to workplace exposure to ETS?

DR. BENOWITZ: You mean, my own research studies? No.

MS. SHERMAN: You made a statement to
Mr. Grossman, and I believe it was something along the order that individual metabolism differences may account for a 200 percent differential in metabolizing cotinine. DR. BENOWITZ: Yes.

MS. SHERMAN: Does that mean that any relationship between ETS exposure and cotinine levels in the blood or saliva, would be off by 200 percent?

DR. BENOWITZ: Well, what it means is, if you were to pick 2 individuals and you happened to pick individuals at the 2 extremes, that for a given cotinine level, there could be a 2-fold difference in intake.

However, usually, you're sampling more than two people and, by chance, when you're sampling, you usually are sampling people that much closer to the mean values, so the chances of actually choosing those two extremes are very small.

Most samples, where you have reasonably large groups, will represent fairly well the mean relationship or the mean clearance, and the average values that you get will be representative of the exposure.

I think, for individual cases, cotinine is a problem in being sure what the exposure is, but when studying groups, I think it's a very good marker.

MS. SHERMAN: Do you consider yourself an expert on the reliability of questionnaires?

DR. BENOWITZ: No.

MS. SHERMAN: But you testified that you have read articles about the reliability of questionnaires?

DR. BENOWITZ: I've read articles that relate questionnaires to cotinine exposure, et cetera, because I've been interested in cotinine exposure, but I've done that, from the point of view of my general knowledge of cotinine, I've never critically looked at the issue of how questionnaires are put together, what makes for a valid questionnaire and a not valid questionnaire,
et cetera.

So I've not done research on the technology of questionnaires.

MS. SHERMAN: Would you say, perhaps, that people who are expert have a divided opinion at to the reliability of questionnaires in this area?

DR. BENOWITZ: Probably.

MS. SHERMAN: Would your reading in the area affirm this?

DR. BENOWITZ: Yes. Although since I'm not in the area, it's really hard for me to say what the current state of understanding is. For example, it may be that the earlier studies were not very useful because the questionnaires were, technically, not very good questionnaires, whereas modern studies are much better because people have learned more about developing questionnaires.

I would really have to defer that sort of a discussion to someone who really has investigated questionnaire technology.

MS. SHERMAN: Do all the variables or limitations that you discussed with Mr. Grossman, also apply to the use of other markers?

DR. BENOWITZ: Yes. They virtually apply to virtually any biological marker, is going to have variability in measurement; it's going to have laboratory to laboratory variability in measurement; it's going to have environmental levels and intake per person.

It's going to have variability on rate and extent of metabolism within the body. That's just intrinsic in any biological substance.

I think when we look at the variability of other biological substances, cotinine of ETS does fairly well.

MS. SHERMAN: Getting back to your discussion with Mr. Grossman, I believe at the beginning of
Mr. Grossman's easel portrayal of various factors to consider, which I believe is Exhibit 30, he asked you what the best evidence of ETS exposure was.

I guess I would like to revisit that with you. Do you believe that the best evidence of ETS exposure is concentration or do you believe it is dose?

DR. BENOWITZ: It's the integrated exposure over time, which is basically the product of a concentration in the air over time, considering the person's ventilation right.

As I talked about in my presentation this morning, all three of those factors play a role, and so you have to know all three of them. What all three of them give you the dose, and the dose is what we're trying to estimate with our cotinine levels.

I think if you had data on the air concentrations and the ventilation rate and the time of exposure and you sampled that multiple times, that would probably be a very good marker, but we never have that.

MS. SHERMAN: Thank you.

JUDGE VITTONE: Thank you, Ms. Sherman.

Dr. Benowitz, thank you. I think you're going to make that plane.

DR. BENOWITZ: Yes. Thank you very much.

JUDGE VITTONE: Before we take a short break here, let me make sure, if I haven't done it, Exhibit 29, plus the slides, 30 and 31 will be received in the record of this proceeding.

Mr. Ott and Ms. Jenkins coming up next.

MS. SHERMAN: I believe Dr. Ott is first.

JUDGE VITTONE: Mr. Ott, you can put your materials here. We're going to take a short break here, and be back, please, in 10 minutes.

[Recess]

JUDGE VITTONE: Dr. Ott, I see you're sitting at the witness table. Would you state your full name for the record, please, your affiliation, and who you're representing here today, please.

DR. OTT: Is the microphone on?

JUDGE VITTONE: I don't think so. His microphone is not working. Try it now.

DR. OTT: Hello.

JUDGE VITTONE: There we go.
WAYNE OTT, PH.D.
U.S. ENVIRONMENTAL PROTECTION AGENCY

DR. OTT: My name is Wayne Ott. I received my Ph.D. in Environmental Engineering from Stanford University in 1971. Since 1966, I have been a U.S. Public Health Service Commissioned Officer, assigned to the U.S. Environmental Protection Agency.

I am currently assigned to EPA's Office of Research of Development's Atmospheric Research and Exposure Research Laboratory, AREAL, located at Research Triangle Park, North Carolina.

I am currently conducting my research activities at Stanford University.

My primary area of research for the EPA is the development and validation of mathematical human exposure models.

These models assist EPA in the assessment of personal exposures to various indoor and outdoor pollutants, from a great variety of sources.

I have published one book, 11 research reports, and 29 articles in the peer-reviewed scientific journals on environmental statistics and data analysis, mathematical modeling of human exposures to environmental pollutants, field studies, indoor air quality, and quality assurance of environmental measurements.

My testimony will provide:

(1) An overview of the historical development of mathematical models designed to predict concentrations of pollutants from smoking activities in indoor settings; and,

(2) My recent research illustrating the performance of a specific model for predicting environmental tobacco smoke concentrations in a chamber and a moving automobile.

The primary topic of my testimony is modelling exposure to environmental tobacco smoke in indoor settings.

Over the last three decades, considerable progress has been made in developing mathematical models to predict the concentrations present in indoor settings due to smoking activities. These mathematical models use the mass balance equation, which is based on the physical principal of conservation of matter. That means that matter cannot to be created or destroyed.

In a simple, conceptual framework, the models assume that the quality of pollutant generated is the source in an indoor setting, is equal to the quantity of pollutant leaving, plus the quantity absorbed on surfaces, plus the quantity remaining inside the indoor setting, usually contained in the air. Thus, all the matter is accounted for.

I am not going to bore you with the derivation of the mass balance equation, because it is described in greater detail in the paper that I will be discussing today.

Models based on the mass balance equation can calculate the concentrations in indoor settings from a knowledge of the source strength, that is, the quantity emitted by the source per unit time; the volume of the indoor setting, usually expressed in cubic meters;

The air exchange rate; that is, the quantity of replacement outdoor air per unit time expressed usually as air changes per hour;

Any scents such as walls or surfaces that absorb the pollutant, and

The mixing factor, is a dimensionless factor representing how well the air is mixed in the indoor setting.

First, I will present a brief historical background of the development of indoor air quality models that have been applied to tobacco smoke. Using the mass balance approach, a number of efforts have been undertaken to model mathematically the pollutant concentrations from tobacco smoke in indoor locations.

For example, in 1960, Brief proposed a simple graph to determine transient concentrations for pollutants in indoor settings that is based on an exponential decay as a function of time.

In 1963, Turk proposed a general equation for calculating the concentrations in a chamber that includes both exterior and interior sources, as well the removal effect of pollutants by air treatment systems.

Bridge and Corn, in 1972, reported that a solution to the equations proposed by Turk, adequately predicts tobacco smoke in occupied settings.

In 1974, Jones and Fagan used Turk's equation to calculate carbon monoxide concentrations versus time from cigarette smoke in an office building and a single family dwelling.

Ishizu in 1980, examined experimentally the inclusion of a mixing factor in the models, and Repace and Lowrey, in 1980, developed a modification of the Turk equation incorporating a mixing factor.

Repace, in 1987, published a literature reviewer that summarizes many of the indoor cigarette smoking models. The concentrations of pollutants from environmental tobacco smoke, or ETS, in a large mixing volume, such as a room, have been observed to increase exponentially, once a cigarette is ignited. They actually increase as 1 minus E to the P -- P is the air exchange rate, so it's not a straight exponential, it's an exponential subtracting from a constant on the upswing.

Similarly, the pollutant concentrations have been observed to decay exponentially once the cigarette is extinguished. These findings are described in brief, 1960, Ishuzi, 1980; Repace and Lowery, 1980; and 1982, Lederer, 1984, and Repace in 1987.

These papers are listed in the bibliography and list of citations attached to my written testimony.

These exponential functions are solutions to the mass balance equation, with the case of a source that emits at a fixed rate when it is on and at zero rate when it is off, with a fixed air exchange rate.

This source can be viewed mathematically as a quote, "rectangular", end quote, input time series. By time series, I mean concentration as a function of time, an input to the mass balance equation.

Next, I will describe the sequential cigarette exposure model, which we have called SCEM, that that have developed.

Smokers ordinarily engage in a sequential smoking, quote, activity pattern, over time. One cigarette is smoked after another with a recovery period between each cigarette. A person in a room with a
smoker -- for example, an office, an automobile, a smoking lounge, a restaurant -- is exposed to a time series of concentrations resulting from a succession of cigarettes reflecting the smoking activity pattern of the smoker or smokers.

In our recent research, the basic mass balance equation was adapted to the case of a sequence of cigarettes smoked one after another.

It's effectiveness in predicting pollutant concentrations as a function of time, that is, the time series of concentrations, was tested using a real time monitoring instrument, actually, a set of instruments, and it is described in our paper entitled, a time series model for cigarette smoking activity patterns, model validation for carbon monoxide and respirable particles in a chamber and an automobile by Ott, Langan and Switzer, in the Journal of which we have called SCEM, that we have developed.

Smokers ordinarily engage in a sequential smoking "activity pattern" over time. One cigarette is smoked after another with a recovery period between each cigarette. A person in a room with a smoker, for example an office, an automobile, a smoking lounge, a restaurant, is exposed to a timed series of concentrations resulting from a succession of cigarettes reflecting the smoking activity pattern of the smoker or smokers.

In our recent research, the basis mass-balance equation was adapted to the case of a sequence of cigarettes smoked one after the other. Its effectiveness in predicting pollutant concentrations as a function of time -- that is, the time series of concentrations -- was tested using a real time monitoring instrument. Actually, a set of instruments. And it is described in our paper entitled "A Time Series Model for Cigarette Smoking Activity Patterns - Model Validation for Carbon Monoxide and Respirable Particles In A Chamber, In An Automobile," by Ott, Langan and Switzer, published in 1992 in the Journal of Exposure Analysis and Environmental Epidemiology, Volume 2, Supplement 2, pages 175 to 200. Much of my testimony today will refer to that paper. Our work has developed this model because of the need to describe with high time resolution the concentrations in various locations instead of just the average concentration over a long time period, which may be viewed as a special case of our model. Our research also has derived theoretical equations for predicting the minimum, the maximum and the mean pollutant concentrations in a well mixed micro-environment for any cigarette smoking activity pattern. General solutions also have been derived for the case of the habitual smoker -- that is, one who smokes with a uniform cigarette duration and the same time between cigarettes -- and for the case of multiple habitual smokers. And these results appear in the equations presented in our 1992 paper.

I am not presenting all of these equations in the testimony. The reader can find them in our paper. The equations used to derive the SCEM are general and are consistent with earlier ETS air quality models that were derived for special cases. For example, the model by Repace and Lowrey in 1980.

In a 1987 paper, Repace described a person with a uniform smoking activity that is a constant rate of smoking per unit time as an habitual smoker. He considered the special case in which the habitual smoker smokes two cigarettes per hour, which is based on a national averaged smoking rate. The SCEM considers the general case in which each habitual smoker can have any smoker rate and concentration is measured in real time. That is, on a continuous basis.

When the parameter values used in Repace's habitual smoker model are substituted into our general model, described in our 1992 paper by Ott, Lowrey and Switzer, the two models agree. Thus, our recent modeling research confirms mathematically that the earlier model for predicting concentrations indoors can be derived theoretically from the basic principals of conservation of mass.

Solutions to the mass-balance equation provide a theoretical basis for calculating all parameters of the model. The air exchange rate, the source strength and the sink removal terms in a single experiment. Because of the SCEM's fine time resolution, experiments to validate our model require monitoring instruments that operate with fine time resolution also -- minutes or seconds.

The air exchange rate is determined from the exponential decay of concentration in the micro-environment in the manner described in our 1992 paper.

The source strength is determined from the equilibrium concentration with continuous smoking.

The sink removal term for pollutants that adhere to surfaces, such as particles, is determined by subtracting the particle decay rate from the decay rate for a pollutant that has no surface sinks, such as CO. And by sink removal term, I mean the particles tend to be absorbed or played out on surfaces such as carpets, walls and other things in a room.

In most cases, an "effective" air exchange rate is measured, which includes the effect of the mixing factor. In the micro-environment considered in the recent research I will be describing today based on the 1992 paper which covers a chamber and an automobile, the pollutant appears to be reasonably well mixed and the model gives good agreement with measured concentration of time series.

Now I will discuss the application of our model to compute average concentrations rather than time varying concentrations. Although the SCEM is designed for predicting concentrations with very fine time resolution -- minutes or seconds -- all of the existing models in the literature reduced to the same basic equation for computing the average concentration from a source in a well mixed location, although the model ordinarily is written as a mathematical expression obtained by integrating the mass-balance equation. See, for example, our 1992 paper and also another 1992 paper which is listed on our list of references, and that one is entitled "Derivation of an Indoor Air Averaging Time Model from the Mass-Balance Equation for the Case of Independent Source Inputs and Fixed Air Exchange Rates." And that's published in the Journal of Exposure Analysis and Environmental Epidemiology, Volume 2, Supplement 2, pages 113 to 135 in 1992.

The basic computation of the average can be stated in words. The average concentration in a well mixed indoor setting is given by the source strength divided by the product of the volume of the setting and the air exchange rate of the setting. And this slide shows that equation.

One can see basically the average, and by average I'm talking about a ten minute average, an hour average, an eight hour average, a twelve hour average, is equal to a source strength, typically expressed in, say, grams per minute or something like that, which has to be weighted, of course, if it's a source strength that turns on and off by the time it's on and off in order to get an average.

JUDGE VITTONE: Dr. Ott. Excuse me. I'm sorry. I don't want to interrupt you too much here. That's Slide 1. If you could identify the slides by numbers as you go through them.

DR. OTT: Okay. That's Slide 1 there. I have just three slides.

In any case, we see S in the numerator and in the denominator we see C, which is the air exchange rate, times the volume of the setting, and this, as I say, is the equation that our more general model reduces to. And I'll show you in one of the slides, the last slide I'll show you, some of the ideas that are contained in the more general model where you're looking at things that vary with high time resolution.

These mathematical concepts -- that is, computing the average -- can be illustrated by a simple example. Assume that the average smoking account -- that is, the average number of cigarettes being actively smoked -- is one cigarette. And by that I'm assuming this is a continuous function, counts of cigarettes, but we're now talking about its average so one cigarette could be the same as one cigarette smoked for an hour or it could be the same as two cigarettes smoked for a half hour, and then no cigarettes. That would give you this average of one cigarette. It's actually something in the work we are doing now we coin as the average smoking count, to make it very clear what kind of a variable this is.

Assume that it's one cigarette in a well mixed location that has a volume of 483 cubic meters and an air exchange rate of four air changes per hour. The air exchange rates in indoor settings typically range between .5 and 7 air changes per hour and the volume of 483 cubic meters used in this example might be, oh, maybe a tavern that could hold 100 people or more.

Assume a cigarette source strength of 1.6 milligrams per minute of respirable suspended particles, which is typical of the lowest range of values described in our paper. Then the average RSP concentration resulting from the one smoking, one cigarette count, would be one cigarette times 1.6 milligrams per minute times 1,000 micrograms per milligram (it's just a conversion of units) times 60 minutes per hour (another conversion of units), divided by four air changes per hour times the 483 cubic meters, and that would come up with a number, an average, of 50 micrograms per cubic meter.

This is example is included only to illustrate the modeling approach and not to describe any real indoor setting.

But now I will discuss our experiment to validate the sequential cigarette exposure model. If the SCEM can adequately predict the actual concentration time series with fine time resolution, then it follows that the model also will be able to predict the averages of these time series quite accurately. So that's why it's important to now get into this discussion and show you this very fine time resolution, because when you have a general model that's predicting for a very fine time resolution, like minutes or seconds, then it will always predict the averages accurately if it predicts the minute by minute readings. It also follows, kind of, from intuitive common sense.

To evaluate the validity of the basic SCEM, it was tested by experiment in a 3.41 cubic meter chamber with a sequence of cigarettes smoked by a smoking machine and also in a moving automobile with a smoker present as described in our 1992 paper. This same chamber in which these experiments were done was at the University of California in San Francisco and was used by Zhu, et. al. in 1993 to test the effect of ETC in increasing atherosclerosis in cholesterol-fed rabbits.

The test vehicle part of our experiment used a 1986 four-door sedan equipped with a continuous CO and continuous RSP monitoring instruments in both the front and back seats. A volunteer sat in the front passenger seat and smoked a single cigarette every 15 minutes. When the smoking took place, the vehicle was driven at 20 miles an hour on ordinary residential side streets free of traffic with the windows closed and the air conditioning system operating. And this slide, this overhead, shows really...

JUDGE VITTONE: Excuse me just a minute, that slide, that's Number 3.

DR. OTT: That is number 2, though, the example 2 is on there. I'm sorry.

JUDGE VITTONE: Would you identify just for the...

DR. OTT: This is the second one. This is Number 3.

JUDGE VITTONE: No. I know that. But identify the second one just to make sure it's clear in the record.

DR. OTT: Sure. Anyway, I'm sorry that's not as clear because the lines just aren't dark. There's a lot of information on that slide. I think it would be better if I stood up and tried to explain the slide.

This is simply one segment of a trip, and you're not seeing the other parts of the trip. We have extensive information in this neighborhood which I'm not showing on the slide because it would clutter it up too much, of driving in this neighborhood at different speeds for another study we were doing to kind of measure what we called for another study, a highway exposure study, background levels. And typically the carbon monoxide levels in this neighborhood on the dates and times we do these types of studies is about a half part per million, which would be -- this is one here, so the background would be somewhere down there.

Similarly, the RSP levels in this area, if you drive around on these streets because there's no traffic at all and California in the daytime has pretty clean air, you can expect about a half part from the CO background, which is about what we have on this particular day, and you can expect about 20 micrograms per cubic meter of respirable suspended particles.

And to illustrate the graph, to give you an overview of what this graph is showing, these three lines on the top are carbon monoxide and they're explainable along this axis simply as parts per million, and this little lower set of curves is respirable suspended particles, and you have to do a conversion of the units here. If this is two, it's two milligrams per cubic meter, so basically for this curve the two is 2,000 micrograms per cubic meter of RSP.

Now, also plotted on this picture are some cigarettes, and what we have here in this experiment is, the driver is told to drive, and he just drives, and the passenger is told to smoke the cigarettes, and she was told to start a cigarette every 15 minutes and smoke it until it ended. So if you look carefully at the time along the bottom here, this is like 4:20 p.m., you'll see cigarette one started there -- the levels were very, very low, almost 0 here. Zero in effect, but it's a half parts per million for CO and 20 micrograms per cubic meter, which, since this is 2,000, is way down there. So she lit up this cigarette and was told to smoke -- they were Marlboro filter cigarettes -- to smoke it until it ended. And it ended about there, some seven minutes later. The paper has the exact times of each cigarette.

As she smoked the cigarette, these jagged lines represent the concentrations -- these jagged ones here -- measured in the front and back seats for carbon monoxide. You can see during the time that she is smoking that cigarette, then, the levels rise from a half parts per million CO in the vehicle, both in the front and back seat, up to something like 17 parts per million. The cigarette ends, and then they begin to decay.

Now. The dash line is the SCEM model. And actually it's following the equation -- I'm not sure everyone would be interested in all these details, but it's following an equation of an aspotophic value (that's the value way up there which is coming from calculating the aspotoph from the source strength of the cigarette) times one minus E to the minus-VT (and P is the air exchange rate and T is time).

So that's this part of the model, here, with an offset of a half parts per million. And it gets up to the there, the cigarette stops, and then here we have the decay and then at that part of the model it changes.

This is what is called a piece-wise discreet model. It changes and it becomes, this part just becomes that concentration times E to the minus-VT until it gets to there. And then another cigarette starts.

So we see the model telling us that the concentrations in this vehicle ought to go up like this, and here's what they really do. They follow the curve reasonably well, with the only exception, which, really, we haven't explained. There is some speculation in the paper about it. But for the second and the third cigarettes the model tends to overpredict a little bit. And one hypothesis is that the people are absorbing the CO. That's a hypothesis.

But, in any case, you can see generally good agreement, both in the shape, the magnitude, the character of the predicted concentrations in the vehicle -- the dotted line here -- and then the observed concentrations in both the front and back seat.

And you may wonder what all this is over here. Although we were on streets barren of traffic, they were selected for that reason. They were very small residential streets in a neighborhood that has virtually no traffic -- an old neighborhood -- so we could get rid of the vehicle effect.

And this vehicle had been tested quite thoroughly for CO intrusion, so that's not an issue. But after it then went out on El Camino Real, and that's this part, and that's the typical CO levels that you would get from a highway, that's just a little piece on that. However, we do have extensive data -- 88 trips -- on El Camino Real over a 14 year period of two sets of data and we kind of know what the levels are on CO on a highway, and basically you can see that this is not too far...

Actually, this is a little high for a highway. El Camino Real, on the 80 -- I think there were actually 131 trips done more recently, and this is published in the Journal of the Air and Waste Management Association, August of this year. The concentrations there are about four and a half parts per million. And they're a little higher here. There are about six. So we just had a little high day.

So the cigarette has elevated the interior concentration of the motor vehicle up to around 18 parts per million whereas the average on that highway would read about four and half. This is just to give you a sense of the numbers.

And down here in the particle data we see that this is the, again, the same kind of thing. This is the SCEM's prediction for respirable suspended particles in the vehicle. And you can see it again follows this equation that I mentioned earlier. The V is a little different because particles have a plating characteristic, and the aspotoph's different because the numbers are different, but this really moves up.

The prediction says it should move up to above 2,000 micrograms per cubic meter in the vehicle, and the observed concentration doesn't quite follow as well, but it follows it reasonably well, such that if you took the average over the two, which again, is my point -- that one of the relevances of this particular model to all the other models is that this is very fine time resolution -- so if you took the two averages you'd get very, very good agreement between the predicted concentration, based on this mass-balance concept in this vehicle and observed concentrations in the vehicle.

And I also must say this is also for the case of 20 miles an hour, windows closed, air conditioning operating. That was just an arbitrary case that was chosen and we found also there are other cases that are both worse and better. It turns out vehicles are somewhat complicated. But our job was not to characterize vehicles. It was simply to test the model for kind of one important case.

So that's basically a summary of the experimental results if taking this model in a vehicle, and I'm not showing you but they are in the paper, I'm not showing you the results from the chamber. There's a figure in the paper. The one I'm referring to in this testimony, where you can see more details and more experiments done with this same model. In general, the model gave good agreement with what was predicted on a minute by minute basis.

Also, in the automobile experiment, just as an additional piece of information that's in the paper, that's in the testimony also here, the blood carboxyhemoglobin levels of both the active and passive smoker, as measured using the breath technique of Jones, et. al., 1958, increased after smoking occurred. The overall results of the experiment show the combination of a small mixing volume and restricted air infiltration make the automobile a micro-environment in which very high concentrations may occur from smoking.

It is not uncommon to find air conditioned vehicles being driven on U.S. highways in summer with active smoking and closed windows. If the surrounding traffic is congested and slow, the concentrations contributed by the other vehicles may add to the high concentrations already present from cigarette smoking inside the vehicle.

Finally, as an overview of all the findings that are in the paper, the specific findings in this 1992 paper can be summarized as follows.

First, a sequential cigarette exposure model, called the SCEM, has developed for predicting the time variation of the cigarette pollutant concentration in any well mixed indoor micro-environment for any cigarette smoking activity pattern.

Second, the model has performed successfully in a chamber experiment with a smoking machine and several different smoking activity patterns. Also, from experiments, it is possible to determine all the parameters of the SCEM, including the source emission rate of the cigarette.

In addition, if both CO and particles are measured, as we've done in these experiments, it is possible to estimate the value of the particle sink rate using the difference between the "effective" air exchange rate observed for particles and the actual ventilation air exchange rate of the chamber observed for CO, since CO doesn't stick.

Another finding is that for the "habitual smoker" -- that is, this person with this idealized smoking activity of a uniform smoking pattern and fixed cigarette duration in a well mixed environment, the mean pollutant concentration is given by a simple equation. The product of the concentration contributed by a continuously emitting cigarette, cigarette source rate, divided by the air flow times the proportion of time the smoking occurred. And the air flow is that thing I showed you before in the equation, the denominator, of Exhibit 1, I think, which was V times V.

It is important to point out that the equations for the mean concentrations generated by the habitual smoker agree structurally with the equations proposed by Repace in 1987 for the special case of two cigarettes per hour. Another finding is that modeling the exposures in the chamber, where the variables can be controlled, gives considerable insight into the physical processes involved.

In our experiments, the model also performed successfully in an automobile with a passenger smoking a sequence of three cigarettes. An important finding is that the concentrations observed experimentally in a motor vehicle with a single smoker and the windows closed were relatively high, approaching 18 to 20 parts per million CO above the background levels, and 2,000 micrograms per cubic meter of RSP, when the smoking rate was four cigarettes per hour. Also, comparison of the concentrations in the front and rear seats of a moving automobile suggests that the motor vehicle is a reasonably well mixed micro-environment.
Another finding is that driving a motor vehicle at 20 miles an hour with the windows closed and the air conditioning operating, during such trips the measured CO level of the driver and smoker increased from 2 parts per million -- this is breath CO -- to 9.2 parts per million of CO after one passenger, the smoker, had smoked the three cigarettes, using the method of Jones, et. al., 1958.

Similarly, during the same motor vehicle trip at 20 miles an hour with the windows closed and the air conditioning operating, the measured breath CO level of the passenger, a smoker, increased from 15.2 ppm to 30.8 ppm after the passenger had smoked three cigarettes.

To not confuse things here, with all these characters, the passenger -- it's a very simple experiment. The driver is the non-smoker. The passenger is the smoker. And the equipment is all running by remote control. So there's no other person needed at that point.

One other finding is that from a knowledge of the volume of the passenger compartment the air exchange rate, the sink term and the pollutant emission rate, it should be possible to predict the mean concentration of other ETS pollutants in a motor vehicle for any smoking activity pattern. Also, we considered in our paper several other cases using the exchange rate that we actually measured in an earlier study of another set of motor vehicles that calculated mean CO concentration inside a vehicle for four cigarettes smoked per hour, each lasting seven minutes, ranged in our calculations -- again, using this SCEM model, which in a way has been validated for the 20 miles an hour case -- range from .8 parts per million (that was for the windows open with 20 miles an hour) to 7.22 ppm (windows closed 20 miles an hour) to 66.3 ppm (windows closed, vehicle parked). And there's a table in the paper showing the air exchange rates used to make those calculations.

Also, from our earlier experiments, there is evidence that passengers in small micro-environments such as the automobile can absorb enough ETS pollutants to alter the interior concentrations, but this topic needs further research.

An important finding is that the SCEM appears suitable for predicting the pollutant concentration time series in well mixed indoor micro-environments when a smoker is present.

In conclusion, the above research suggests, one, mathematical models for predicting pollutants from ETS in indoor settings have a long history of development, with derivations that are based on the underlying physical theory of the process involved: conservation of matter. And with experiment, evaluating the validity of predictions of these models. And, two, the predicted concentrations of the models often agree well with measured values, both on a minute by minute basis, which I've called a sequential time series, and also for longer term averages, which I've also shown you.

The SCEM model, for example, provides both a theoretical basis for the short and long term equations and shows that the predicted concentrations agree well with the observed concentrations in a controlled chamber and in an automobile with an active smoker. The SCEM model is consistent in its structure and behavior with the other published literature. See, for example, my attached list of references and bibliography.

Finally, I want to point out that additional studies are being conducted to collect data for testing and validating the SCEM under other typical indoor micro-environments, to include airport smoking lounges, taverns, restaurants, bingo games, residences and others. These data and the corresponding reports will be made publicly available upon the completion of EPA's normal peer review.

JUDGE VITTONE: Thank you, Dr. Ott. Dr. Ott's previously submitted statement has been identified as Exhibit No. 32. In addition there are three slides that he used during his oral presentation. They will be received into the record of this proceeding.

(The document referred to was marked for identification as Exhibit No. 32.)

JUDGE VITTONE: Dr. Ott, do you have copies of those slides for the Court Reporter?

DR. OTT: Yes.

JUDGE VITTONE: Okay. Let me ask for a demonstration of who has questions for Dr. Ott. Mr. Rupp? Let me see Mr. Rupp standing. Very good. Let's proceed, Mr. Rupp.

(Brief pause)

MR. RUPP: Dr. Ott, good afternoon. My name is John Rupp. I'm going to ask you a series of questions, if I may, to try to see if I can understand what application or what significance your model might have, if any, to the issues that are presented in this proceeding. Let me start by asking you a couple of general questions.

My understanding is that exposure models of the sort you've described... This is an exposure model. Is that correct?

DR. OTT: Yes.

MR. RUPP: It's not a model of dosimetry in any way?

DR. OTT: No. It's an exposure model.

MR. RUPP: Okay. That such models typically have two purposes. First, their development and use can be of value in prompting investigators to think in a logical and systematic way about the complex interrelationships that can affect the extent of exposure to a substance. So it's a disciplining measure, if you will.

DR. OTT: Yes.

MR. RUPP: And, secondly, they can provide varying degrees of insight into expected exposures across the range of circumstances considered in the particular model. Would that be fair?

DR. OTT: What did you say providing, exactly?

MR. RUPP: They can provide varying degrees of insight into expected exposure across a range of circumstances considered in the particular model.

DR. OTT: Yes.

MR. RUPP: Okay. That's a fair general characterization of the objectives of modeling exercises.

DR. OTT: Well, there are other objectives, but that's a fair characterization.

MR. RUPP: Okay. And would you also agree that the product of any model -- the answer or the answers that any model provides -- typically requires a number of assumptions to be made relating both to the data that's fed into the model and the interrelationships the model attempts to take into account.

DR. OTT: Well, if you're speaking about my model or models in general, they vary in the amount of assumptions that are needed and their complexity.

MR. RUPP: Right. But typically, there are some assumptions which one seeks to verify eventually, but assumptions of one sort or another.

DR. OTT: Right. Well, I've tried to be very explicit, because my assumptions are fairly few.

MR. RUPP: Okay. And then you have to do some thinking about and an incorporation of interrelationships that may be occurring, depending on the nature of the model, of course.

DR. OTT: Well, I don't have too many interrelationships, but in a purely theoretical or speculative sense you're probably correct.

MR. RUPP: All right. Well, we'll pursue that. The ultimate that I take it, what anyone using a model should insist upon as verification. That is, what you want to do eventually is look for empirical evidence that either tends to validate the model and the model output or experimental data that shows that in some respect the model is going awry.

DR. OTT: Correct.

MR. RUPP: Now. Would you also agree with me that the best measure of exposure would be a direct measurement. That is, if we had unlimited resources, what one would want to do to find out, to get a clear sense of, a pretty complete profile of the environmental tobacco smoke exposure, what would do measurements in the field. And probably a fairly substantial series of measurements.

DR. OTT: You're actually now mixing objectives up. I don't know if you know you are, but model validation is a different science than characterizing populations or something like that.

MR. RUPP: Sure. Sure. But if OSHA were to put before itself the task of trying to decide how much ETS individuals are exposed to in particular environments, again, if resources were unlimited, the first thing, the best evidence, certainly would be to go out into the field and do samples in those areas, in those circumstances, and use those direct measures of exposure.

DR. OTT: Well, I don't really think I'm equipped to say what's the best for OSHA to do. If you can narrow what we are talking about to the statistical question that one might investigate, like do we wish to validate a model to see...

MR. RUPP: That's not what I'm asking. That's not what I'm asking.

DR. OTT: Then I don't understand your question.

MR. RUPP: All right. Let me try it again.

The question with which OSHA must grapple here, among others, is how much ETS people are exposed to in a variety of micro-environments. A rather heterogeneous group of micro-environments. Whether you're a modeler or have some other area of expertise, isn't it clear that the best measure of exposure are going to be direct measures of exposure?

DR. OTT: Well, for characterizing distributions across populations, I don't think there's any question that the best measure is direct measurement. The best way to do that, that's quite a different thing than, in answer to your question, than trying to understand and predict exposures in particular settings. Which you might want to do because you might have a plan to change something. You might pass a regulation or something and want to know what, how will things change. It's very difficult to do that without the model. It's just a different kind of thing.

MR. RUPP: But ultimately, after you've used the model in the circumstance that you've hypothesized, again, both to verify the model, that the model is working properly...

DR. OTT: Right.

MR. RUPP: ...and to determine what impact your regulatory measure has had, one would probably want to, if the resources are available, get into the field and actually take some direct measures of exposure in the environments affected by the regulation, right?

DR. OTT: Well, as a general rule I favor the more measurements the better.

MR. RUPP: Sure. Okay. That's all I'm trying to get at. Nothing more mysterious than that.

Now. Would you also agree that the extent of an individual's exposure to ETS is likely to be affected by a range of factors?

DR. OTT: Of what?

MR. RUPP: A range of factors.

DR. OTT: A range of factors?

MR. RUPP: Right.

DR. OTT: Yes. We could be a little more specific.

MR. RUPP: All right. Well, let's be more specific. Those factors would include, would it not, the amount of smoking that's occurring over some pertinent unit of time? And that's one of the factors you've taken into account in your model.

DR. OTT: Yeah. I'm not sure. We can be a little more specific in answering your question.

MR. RUPP: Okay. Let's focus on that element first.

DR. OTT: The way you would like to do that, if I follow your logic, is something along the lines we've done in another model, the THEM model, which also is an EPA project and was presented in Cincinnati at the Air and Waste Management meeting in June, and that simply is a model that takes activity patterns -- and I haven't heard you mention that -- and that's really very, well, that tells where people were minute by minute during the day, and then it takes micro-environmental concentrations and it puts them together, so it kind of does what you'd want. And, in fact, there's a paper you can get and see it there.

MR. RUPP: That is useful. But here is what I want to do here, to proceed in a kind of systematic way here.

I'm going to name a number of factors that occurred to me as likely or inevitably affecting the extent of an individual's exposure. And when we're done with that list, if I've missed some, I'd like you to help me figure out what I've missed, okay? But follow along with me and se if I've got some of the major elements.

The first one that occurred to me is the amount of smoking that's occurring over some pertinent unit of time in the particular place we're interested in.

You might not need that because you might use something like the THEM model which samples from distributions based on real data which represent locations like bars, so you may not need to have the count.

DR. OTT: Well, look. Let's make it quite specific. Let's make it quite specific because I think we're going to kind of fly off into the air here.

MR. RUPP: Let's just talk about this room. Could I talk about this room?

DR. OTT: I think this is --

MR. RUPP: Let's talk about --

JUDGE VITTONE: Gentlemen, Mr. Rupp, pity the poor reporter. She's trying to get both of you talking at the same time, so let's make it one at a time, okay?

And let's wait until he finishes his question and then you can begin your answer, please.

MR. RUPP: All right. Let's take this room as our point of departure, shall we? Okay?

DR. OTT: Sure.

MR. RUPP: All right. Now, I'm going to ask myself how much ETS I might be exposed to in this room. Is one thing I would ask myself how many cigarettes were smoked in this room during the period I was in it?

DR. OTT: If you wish to calculate the --

MR. RUPP: I don't wish to calculate. I'm trying to figure out what factors might affect my exposure. What factors might affect my exposure.

DR. OTT: I'm going to answer that.

MR. RUPP: Please.

DR. OTT: If you wish to find that out, in this room, you would need the air exchange rate, you would need the smoking count, which is what you just said.

MR. RUPP: We're going one factor at a time, okay?

DR. OTT: Okay.

MR. RUPP: Let's try it one more time. If we don't get off the starting blocks here, this race will never end. All right?

One of the first factors I would take into account is how much smoking was occurring while I was in the room. Is that not patently obvious?

DR. OTT: That is correct.

MR. RUPP: Great. All right. That would include the number of cigarettes smoked, perhaps the type of cigarettes, and perhaps even the manner of smoking.

DR. OTT: I don't know what you mean by manner of smoking.

MR. RUPP: For example, whether the person was inhaling deeply and retaining materials in the lung or whether the smoking was occurring quite shallowly, whether the person was really taking any puffs or simply holding it aloft.

DR. OTT: I don't know that any study has shown that to be pertinent. That's a speculation.

MR. RUPP: That's a speculation.

DR. OTT: On your part.

MR. RUPP: Well, maybe it is. Would it not be intuitive that the amount of materials I might retain in my lung as I smoke would diminish correspondingly the amount of materials to which you might be exposed?

DR. OTT: I don't have any knowledge that that would happen.

MR. RUPP: Okay. So if I retain materials in my lung, you think that at least theoretically you could be exposed to it at the same time?

DR. OTT: I think it's a time bearing thing. Your lung is going to inhale and exhale and it's not evident to me that we would need, as I think you are postulating, the individual characteristics of the people's breathing to find out what the levels are in the room.

MR. RUPP: I think this is a small point but I'm going to pursue it nonetheless.

DR. OTT: Go ahead.

MR. RUPP: Do you know anything about lung clearance rates for particles that are deposited in the lung?

DR. OTT: No. That's not my area of expertise.

MR. RUPP: All right. Is it your assumption that any materials that I take into my lungs when I'm smoking are re-emitted immediately or are inevitably going to be re-emitted while you are in the room?

DR. OTT: I really don't know. I'm just saying --
MR. RUPP: Okay. So if I were to hypothesize a situation or to suggest that it's a reasonable situation, the following, that is, one can safely assume that material that I have inhaled into my lungs and is deposited there is material that is not available for your exposure, would you have any basis for challenging the reasonable of that assumption?

DR. OTT: I would have no basis.

MR. RUPP: All right. We would also have to take into account the nature of the location in which the smoking was occurring, would we not, and let's take that in several steps. For example, I have suggested that one hypothetical place smoking might occur is this room. We might have quite a different situation if the smoking I was talking about, number of cigarettes smoked over some unit of time, were occurring outdoors. Isn't that right?

DR. OTT: Yes.

MR. RUPP: All right. Now, if inside, would we not want to know how large the room is and its volume?

DR. OTT: Yes. It's in the equation.

MR. RUPP: Right. And the manner in which the air in the room is moving, whether the air is being mixed, whether there is a horizontal or vertical air flow, the extent of mixing the air flow and the air exchange rate.

DR. OTT: You would want to know the air exchange rate.

MR. RUPP: Certainly.

DR. OTT: There are some papers questioning how important it is to know some of the other factors you've listed.

MR. RUPP: That is, how important it is to know whether the air is rising or moving laterally?

DR. OTT: Yes. Simply because -- in fact, there is a paper going to be given tomorrow in this town on how important it is to deal with the ideal or non-ideal mixing in a room and there are experiment suggesting with convective mixing, which is normal in places where people are occupying, that the mixing is very rapid and very fast.

MR. RUPP: Is this room characterized today by convective mixing?

DR. OTT: Yes.

MR. RUPP: That's your view.

DR. OTT: Yes. That's my view.

MR. RUPP: All right. And so horizontal air flows are not something you would be particularly -- horizontal or vertical air flows are not something that would be particularly interesting to you because you believe that complete mixing occurs quite instantaneously or very quickly.

DR. OTT: I think the data support that. There is a study on that subject.

MR. RUPP: And which study are you referring to?

DR. OTT: A study by Nazaroff, by Baughman and by Gadgil and Nazaroff. It's published in Indoor Air.

MR. RUPP: And what expertise do you have concerning ventilation? Have you studied ventilation?

DR. OTT: I have not studied ventilation as a ventilation engineer. No, I have not.

MR. RUPP: All right. Would we want to know something about the nature of the items in the particular room that might act as absorbent sinks for substances being released into the air?

DR. OTT: The basic point of my testimony was that you really don't need that. You need to characterize that as a sink term which you can then measure.

MR. RUPP: And the potency of that sink could well depend upon the nature of the substances in the particular room, would they not? That is, if we had a stainless steel room, it would have one sink factor --

DR. OTT: It is --

MR. RUPP: Let me finish my question, please.

DR. OTT: Sure.

MR. RUPP: And if we had another room composed of, oh, let's say green plants, it was basically a forest of green plants, that would have another sink factor, would it not?

DR. OTT: I have no data base to answer that question. I think it's a very legitimate area for future research. The studies I've seen don't show me data on green plants or those particular cases. They do show me that the sink term can be measured for a particular pollutant.

MR. RUPP: Regardless of room, it's a single sink term?

DR. OTT: Well, I just don't have any basis to speculate on how big an effect this is. It may be a trivial effect, it may be a 10 percent effect, it may be a 1 percent effect. I have no way to speculate.

MR. RUPP: Could it be 80 percent? You just haven't measured it.

DR. OTT: It could be 80 percent. My general judgment as a professional who has done work in indoor air quality is that it is remarkable how easy it is to characterize these sink terms and I don't see great variation.

Now, obviously, to answer your question, the room with all the plants, I don't think anyone has studied it. Maybe there might be a different sink term.

MR. RUPP: You're aware of no research by NASA?

DR. OTT: Who?

MR. RUPP: NASA. NASA.

DR. OTT: NASA?

MR. RUPP: Right. On the effects of plants --

DR. OTT: Yes, I am aware.

MR. RUPP: And did that show that plants were having an effect on --

DR. OTT: That research -- that research has been question.

MR. RUPP: That's not what I asked you to start with. Did that research report that plants did have an effect on air constituents and the level of air constituents?

DR. OTT: Yes. I don't know the details of the report but the general report was that plants were a cure for indoor air. I don't know any more detail about that report.

MR. RUPP: I think that may be a little extreme in the characterization of it but it showed it had an effect.

DR. OTT: Well, that's all I know, so I'm giving you my characterization of it.

MR. RUPP: Okay. All right. But you haven't looked at all of the literature on the effects of various sinks on the levels of indoor air pollution?

DR. OTT: Is there a lot of literature? Do you have any evidence?

MR. RUPP: Well, do you know of any?

DR. OTT: I don't know of any.

MR. RUPP: Have you looked for any?

DR. OTT: Yes.

MR. RUPP: You've done a comprehensive search and have found none?

DR. OTT: I have looked at all the indoor literature that I could find that's relevant to the pieces that go into this model and I have found none.

MR. RUPP: All right. Whether it's relevant to the model or not, let me ask you again the question, have you done a comprehensive search for materials relating to the sink factor including the absorptive qualities and re-emitting qualities of various substances found in the indoor environment and found little or none? Is that what your testimony is?

DR. OTT: No. My testimony is not that I have done an extensive and exhaustive literature review of that subject unto itself. I did not do that. Basically, I'm here to testify about the model that I did the work on and I characterized the sink term very experimentally from that model and found successful results with these sink terms that I used.

MR. RUPP: In the two circumstances that you described.

DR. OTT: Exactly.

MR. RUPP: And one was a chamber and one was an automobile.

DR. OTT: Correct.

MR. RUPP: All right. Now, your selection of a sink factor, as we've been calling it which is probably not a particularly elegant phrase but one that at least you and I know what we're talking about --

DR. OTT: Right.

MR. RUPP: That was an arbitrary numeric value that was factored in?

DR. OTT: It was measured. It was measured. Did you want me to elaborate?

MR. RUPP: Yes, please.

DR. OTT: Okay. It's measured simply by -- from the mathematical concept, you're putting in what is a delta function. You're elevating the concentration and then you're watching it decay. And, as I tried to indicate in the testimony, one of the pollutants I'm using can be used as a target indicator pollutant, that's carbon monoxide. It's inert, it doesn't stick to any surfaces so it has no sink. The other pollutant I'm looking at is respirable suspended particles and it has a sink which are those things you described and I also mentioned in my testimony, the carpet, the wall and so on. The difference between those is the effect of the carpets, the walls and so on in absorbing the particles and I don't have the numbers right on the tip of my tongue but I think the number we got for the inert tracer pollutant was something like 5.7 air changes per hour and then for the particles it was something like 7.5. That's the incremental effect of all those characteristics you're describing, the absorption by the carpets and the surfaces of the furniture and the wall in the experiment that we're talking about. So that's how --

MR. RUPP: Right. But when we're talking about materials that are not inert, and the RSP component of ETS is one of those sets of materials --

DR. OTT: Right. Correct.

MR. RUPP: We do have to take the sink factor into account, do we not?

DR. OTT: Correct.

MR. RUPP: All right. And the potency of the sink effect in any particular location is going to be a function of the materials, the geometry and so forth of the individual location. There may be an average of it but it's going to be affected by a variety of factors in each location. Is that not clear?

DR. OTT: In theory, it should be.

MR. RUPP: All right. Now, again, in trying to get some insight into the rather generalized question I asked when we started of how much ETS I might be exposed to, and we touched on this already but let me pursue it, would I not want to know or should it be of any significance to me how close I am to the person who is smoking?

DR. OTT: That is actually a complicated topic and I don't know if you want to get into it and also a subject of a paper given in this town tomorrow which I am a co-author of --

MR. RUPP: Which paper is that?

DR. OTT: It's an EPA cleared paper. What's the exact title? It's -- basically it's a study of how ideal mixing, how much you might deviate from ideal mixing in a room or a chamber.

MR. RUPP: And who are the authors of that paper?

DR. OTT: Myself and David Major are the authors.

MR. RUPP: And is that a paper that was generated following experiment in a chamber?

DR. OTT: Yes. Well, not our experiment. It's more a pulling together -- because it is an important issue, a very important issue. It's pulling together all the literature we could find on -- and I mentioned it in my testimony, this variable called M which we weren't very comfortable about because people had put M in their equations and we couldn't find a physical basis for M and so we simply reviewed all the literature, including recent chamber experiments at Berkeley, recent chamber experiments at EPA by Ed Furtow in Las Vegas, and reviewed what they all said about this exact question you're asking and we found that by looking at the mathematics, the non-mixed portion, after a cigarette is smoked, looking at all the other where the non-mixed portion of time, the poorly mixed portion was fairly small compared to the well mixed portion, again, pulling together all experiments and data bases that bear on this, and consequently if you averaged over a long period, you really had no effect or a very negligible effect. It comes down to less than 5 percent.

MR. RUPP: All right. Let's see if I understand what you're saying. If I were to sit next to you for half an hour and smoke several cigarettes, is it your testimony that you are likely to be exposed to about the same amount of ETS within 5 percent to which you would be exposed if you were sitting in the far end of this room and I were smoking the same number of cigarettes diagonally across this very large and commodious room from you?

DR. OTT: Well, from the limited data, and we reached a data limitation, to answer your question, and I like to speak from data or from studies that I publish, we can't be quite certain. It is -- the data point to the rather remarkable thing, that large rooms, they mix rather rapidly and again our common sense verifies this if we'll just look at the fact that if someone opened a can of very odorous in one corner of the room, the other corner would be only a few minutes later, you would smell it.

MR. RUPP: Do particles transport through the air precisely the same as odors?

DR. OTT: It's a similar mechanism, yes. But the basic difference we see in the particles is simply the sink term.

MR. RUPP: Well, I take it, then, that if this room were 20 times the size your answer would be the same?

DR. OTT: I'm saying that there we run into, and it's also professional judgment, we just run into a lack of data on this subject.

MR. RUPP: So you really don't have any way of knowing from your model or from your experiments or from your review of the pertinent literature or intuitively common sense whether if you were sitting in that end of the room and I were sitting diagonally across the room, in this room, given its size which is substantial --

DR. OTT: Right.

MR. RUPP:  -- whether you would be exposed to the same amount of materials as you would be exposed to were I sitting right next to you smoking the same number of cigarettes?

DR. OTT: Well, to answer your question from a physical science point of view, during the time that the source is on, which we call the alpha period in our paper, if you want to get into the specifics of it, and since a cigarette has a very small alpha period, maybe seven minutes, during that time, there is a great disparity in the concentration. As soon as the cigarette goes out, there is a transition period which we call the beta period and that's very small. And then finally we get to the gamma period and that's what we describe at the point at which there is less than a coefficient of variation of less than 10 percent which again uses some of the ideas that Nazaroff came up with in his 40-point chamber, which is a large chamber, I believe.

MR. RUPP: All right. Now, so now your testimony is that initially there would be a difference but not necessarily over a longer period of time.

DR. OTT: Right.

MR. RUPP: During the beta and gamma periods there may be none.

DR. OTT: Correct. Right.

MR. RUPP: Or only 10 percent.

DR. OTT: Yes.

MR. RUPP: All right. Now let's add another assumption. What if the air exhaust for this room is over my head and I'm sitting at the one end of the room and smoking my cigarette and you're sitting diagonally across from me and the air intake for the room is located near you. Irrelevant?

DR. OTT: I don't know. I can only speculate on that. I don't have data to see what effect that is.

MR. RUPP: Have you looked for any data that would give us insight into the movement of air in a room when all air intakes are located on one wall and all air exhausts are located on another, which way the air in that room would be moving?

DR. OTT: Yes, I did review the literature on that subject. A large number of papers by Sherman and others and they are cited in -- and I can give you a response and put that in the record, if you would like.

MR. RUPP: Which way would the air in that hypothetical room move?

DR. OTT: Well, it doesn't apply to that particular room. You asked me if --

MR. RUPP: Well, I'm asking about this room.

DR. OTT: I can't answer that question.

MR. RUPP: Well, let's try it again and maybe I can ask you to think not for the moment quite so much about data and just use what I think might be common sense.

If those two doors are open and they become the exhaust for this room and all the air is entering over here to my left, which way would the air in this room be moving?

DR. OTT: My first comment is that's a hypothetical and I don't know what point it has. It's very irrelevant as far as I see to real settings.

MR. RUPP: Well, why don't we let the judge --

DR. OTT: I mean, we could construct a wind tunnel --

MR. RUPP: Why don't we let the judge and OSHA decide what's relevant? Can you answer the question?

DR. OTT: No.

MR. RUPP: You have no idea --

DR. OTT: I can't answer it. No.

MR. RUPP: You have no idea which way the air in that room would be moving.

DR. OTT: No. No idea at all.

MR. RUPP: I apologize for talking over him. I don't quite know when he's going to stop.

You don't have any idea which way the air in that room would be moving?

DR. OTT: I don't know. May I comment?

MR. RUPP: Sure.

DR. OTT: When I reviewed the literature, a number of papers by Sherman and I don't remember all the other authors which are cited in our paper that we will be happy to submit to the record, the papers were very theoretical and that bothered me. The people had done all their mathematical number crunching but there was very little of what you and I both talked about earlier, validation to see if this was really right. So I'm very uncomfortable with these theoretical, elegant papers. And I can't answer your question when I look at the papers because they're so obtuse.

MR. RUPP: Yes. Well, there is a great deal of uncertainty about air flow in rooms, that's for sure. Let's take the converse situation of the one I posited a few minutes ago. Again, the doors are open and they are the only exhaust from the room. The only entry point for air is at my right. Is there any chance at all that the predominant air flow in this room will be to my right in those circumstances?

DR. OTT: The mean flow certainly would be that way.

MR. RUPP: Would be to the right? Toward the air intake?

DR. OTT: I mean, it's again a hypothetical that it would be that way. But there would be also much, much complex mixing at that point. You've also presented to me a situation on which I have no data, no firsthand experience.

MR. RUPP: Okay. Now, what if the air intakes are located near the floor and the air coming through the intakes is warmer than the ambient air that preceded it into the room? What typically does physics tell us about what direction that air would move after it had lost its lateral momentum?

DR. OTT: I really don't want to speculate on the mechanical engineering aspects of air flow.

MR. RUPP: Does relatively warm air tend to rise?

DR. OTT: I really don't want to speculate on this topic. It's --

MR. RUPP: In the ocean, does warmer water tend to rise and colder water sink?

DR. OTT: I don't see how this is relevant to the testimony.

MR. RUPP: That's not the question. The question is do you know whether warm water rises, the warmest water rises in the ocean.

DR. OTT: One can speculate that it does but I can imagine situations when it wouldn't.

MR. RUPP: When the warmer water, absent any lateral --

DR. OTT: But I'm not an expert -- I have no expertise in water --

MR. RUPP: Your Honor, may I have an instruction that he stop speaking mid-sentence?

JUDGE VITTONE: Gentlemen --

Dr. Ott, this is not a trial.

DR. OTT: I know.

JUDGE VITTONE: But we do have to proceed in an orderly manner so that we can get the question clearly on the record and your response clearly on the record. And when you both talk at the same time, that doesn't happen.

DR. OTT: Let me slow down and try to answer.

JUDGE VITTONE: Yes. Don't anticipate. Wait until he stops and then give your answer.

Can we get out of the ocean and get back to the air, I guess?

MR. RUPP: Again, we're still pursuing this exposure question for my benefit.

DR. OTT: Sure.

MR. RUPP: Would I care to know at all about the nature of any air cleaning devices or filtration devices that might be in the room and between me and the person smoking?

DR. OTT: For what purpose?

MR. RUPP: To know something about the extent of my likely exposure.

DR. OTT: The answer is no. If you do the kind of work we're describing here because we are taking into account the sink and that would turn up as a particle sink, that air cleaner.

MR. RUPP: All right. I could include that in the model as a sink.

DR. OTT: Right.

MR. RUPP: Have you included air filters as part of the sink? Did you take that into account?

DR. OTT: Nothing we have studied used a filter like that but we would.

MR. RUPP: Okay. All right. No. I'm asking a somewhat different question. I'm asking you to put your model to the side for a moment and let me come to that in a moment.

DR. OTT: Sure.

MR. RUPP: If I'm asking myself how much ETS I might be exposed to in this room, would I want to know something about the extent of the filtration in the room if there is any filtration in the room, including any air cleaners that might be operating? Isn't that a pertinent question?

DR. OTT: Yes.

MR. RUPP: Yes? All right. In addition, we would want to know something about the decay rates for the individual chemicals that might be found in ETS, how they behave at different temperatures, how they interact, their absorbent qualities, the extent to which they can be or are removed either by filtration, ventilation or any number of other different types of air cleaning? Again, leave your model to the side for a moment.

DR. OTT: Yes. No, I think if I understood your question, you mentioned the decay rates of various chemicals? Did you --

MR. RUPP: Of all of the chemicals that may be hypothesized to be in ETS.

DR. OTT: Right. To answer your question, you would want to know this and you can know it.

MR. RUPP: Fair enough. I'm just asking whether it's a factor and you've said that it is.

DR. OTT: Sure.

MR. RUPP: All right. Then we can move on.

Now, let's talk for a few moments about the techniques that are available to measure exposure directly. Would you agree that so far as ETS components are concerned and the quantity levels we're talking about that the techniques for measurement and the analytic procedures that are available to us today are far superior to the equipment and the analytic procedures that were available to us ten years ago?

DR. OTT: Yes.

MR. RUPP: Indeed, not many people would use today, would they not, a piezo electric balance to measure particles.

DR. OTT: Why not?

MR. RUPP: You would use that?

DR. OTT: Certainly.

MR. RUPP: Okay. What kind of precautions would you take before you used the piezo electric balance? Would you be quite sure, for example, that the piezo electric balance was properly calibrated?

DR. OTT: Certainly.

MR. RUPP: And what would you use for that purpose? Arizona road dust or would you use if you were looking at ETS a room of ETS?

DR. OTT: Again, this is somewhat of a speculative question. I think it would depend on my precision I want and how I'm going to apply this.

MR. RUPP: Well, say you want to do a pretty good job.

DR. OTT: Yes. My experience --

MR. RUPP: And I'm asking you how you would calibrate your piezo electric balance.

DR. OTT:  -- with that particular instrument is it's precision is around 10 micrograms per meter cubed or less and that's very good precision.

MR. RUPP: Calibration is very important to the piezo electric balance, though, isn't it?

DR. OTT: It's important for every instrument. And it also depends, again, on the precision you desire.

MR. RUPP: Well, I take it additionally, Dr. Ott, that no scientist or at least no scientist worth his salt, given what we know today, would assume that all of the RSP in a room is traceable to ETS.

DR. OTT: That's true.

MR. RUPP: We know now, do we not, that there are many contributors to room air concentrations of respirable suspended particulates of which smoking is only one?

DR. OTT: There are a few. Yes. I'm not sure many but there are a few.

MR. RUPP: Are you aware that several techniques have been developed over the past several years seeking to apportion the amount of RSP found in any room to ETS and other combustion sources on the one hand and other RSP sources on the other?

DR. OTT: I'm not intimately familiar with what studies you seem to be alluding to.

MR. RUPP: Have you used or are you aware of the techniques for measuring the UVPM sensitive component of RSP?

DR. OTT: No, I'm not.

MR. RUPP: Do you know what UVPM or fluorescence methods are?

DR. OTT: No. I'm not familiar with those methods.

MR. RUPP: Have you done any indoor air monitoring yourself?

DR. OTT: Extensively.

MR. RUPP: With respirable suspended particulates being part of the target compounds?

DR. OTT: Yes.

MR. RUPP: Would you agree that the best way to determine personal exposures is to use whenever they are available personal exposure monitors for the chemicals we have an interest in?

DR. OTT: I think they're very good methods.

MR. RUPP: Better than area monitoring equipment?

DR. OTT: Well, it depends on your purpose.

MR. RUPP: Well, let's assume that there is movement in the room of people so that they are not chained to their desk or otherwise stationary throughout the day. Then would a personal monitor tend to be superior to an area monitor if our interest is the exposure of the particular individuals to the constituents of interest?

DR. OTT: Yes.

MR. RUPP: All right. Now, let's turn back to your model which you've been aching to return to, I know, and I'm going to let you do that now. Your model is designed, is it not, to provide some insights into expected exposure to the RSP and CO contributions of smoking in rooms in which smoking is occurring, is that right? The RSP and CO components.

DR. OTT: Yes. Or general. I mean, I'd go further than that. If we have a source. Yes.

MR. RUPP: All right. The model does not necessarily tell us anything, does it, about smoking's expected contribution to the room air levels of other chemicals.

DR. OTT: Well, no model really does that. Your measurements you described do that.

MR. RUPP: Yes. The direct measurements. But not your model, at least to the point that you've elaborated it thus far.

DR. OTT: Right.

MR. RUPP: All right. Your model assumes complete and perfect mixing, does it not?

DR. OTT: Correct.

MR. RUPP: And do I understand your testimony to be that while you believe that that is not an unreasonable assumption in many circumstances you have not yet done the research that would be required to know precisely in a variety of heterogenous circumstances that exist in the world, how applicable that assumption would be in individual locations.

DR. OTT: Yes, that's true.

MR. RUPP: And I could also say the same thing about surface absorptions. At this point, my understanding is that what you have done is choose a sink factor that you believe to be reasonable given the environments in which your model -- you've sought thus far to validate your model, that's worked out reasonably well, but other sink factors may be required depending upon the circumstances of the locations in which the model is applied.

DR. OTT: You're partly right. Just to clarify that, I've measured that sink term in these settings. That's the main point. I'm showing you a way to get that number by doing these two pollutants.

MR. RUPP: But if we wanted to take sinks into account in a really comprehensive way, we'd have to do a fair amount more work than the model thus far incorporates, would we not?

DR. OTT: If you wanted to do what? I'm sorry.

MR. RUPP: Take the sinks in this room into account, we would have to refine that model a fair amount more than it has been refined if we're trying to get answers for this room.

DR. OTT: To answer your question as completely as I can, what we are doing here with this particular model is starting with small micro-environments like the chamber and the automobile and moving up to larger ones.

MR. RUPP: Right. And the larger we get, the more complicated the geometry of the room, the greater the number of sinks, the more complicated the human activity patterns, the greater the number of sources, the more complicated the model has to be if it's going to represent in a set of mathematical equations exposures in the particular environment. Isn't that quite clear?

DR. OTT: Well, I think what you're going to do is you're going to say we have this single compartment model, that's the one I described --

MR. RUPP: Right.

DR. OTT: And you're going to apply it to a compartment and at some point the compartment is going to get so complex you're going to say, well, now, it's going to have to be a multiple compartment model.

MR. RUPP: Right. And then we're probably -- at some point, we're going to tell ourselves that it's better to go out and actually measure directly, it's going to give us more reliable answers anyway rather than trying to add yet another set of factors in an already complicated equation.

DR. OTT: Sure. I'm not sure where your question is leading, so that's why I'm trying to answer --

MR. RUPP: Well, I'm not sure I'm leading anywhere.

DR. OTT: Okay. Well, to answer, where I think we're both going is that I think the direct approach where you sample lots of people is a very important complement to this kind of approach. In fact, people have called the two one the direct approach and the indirect approach and what I am describing is the indirect approach.

MR. RUPP: Sure.

DR. OTT: And they complement each other.

MR. RUPP: Sure. Now, what does your model tell us, if anything, about the following circumstance. Let's assume that this is my office, a rather large and rather grand place, and I'm smoking in my office and you are seated down the hall. And the question is I say to myself let's run this model and see how much ETS Dr. Ott is exposed to from my smoking, albeit he's located down the hall. The model doesn't tell us anything, does it?

DR. OTT: No.

MR. RUPP: Okay. Indeed, if you are located in the room next door, the model really at this point of its evolution doesn't apply to that circumstance, it doesn't tell us anything there, because we know there's not going to be complete mixing in that circumstance, isn't that correct?

DR. OTT: You had two compartments there, as I understand?

MR. RUPP: Correct. I have two compartments.

DR. OTT: No. It's not going to --

MR. RUPP: Any time we have a two-compartment area, the model really at this stage of its development doesn't tell us anything, is that correct?

DR. OTT: Correct.

MR. RUPP: Okay. What if the door to my office, one of those doors to the rear of you, is left a crack open during the day? Again, I take it we still have predominantly a two-compartment situation there and your model is not yet directly applicable to that situation.

DR. OTT: No. To comment or answer, the door setting is going to be something which is going to move us from a double compartment to a single compartment when we open it wide enough. But my model, or the one I presented, is simply one compartment and you simply put its output into this same model again and you get the other compartment, so it's the same model, just kind of replicated,

MR. RUPP: All right. Let's talk for a moment then about the field experiments you've discussed, both in your printed statement and in your testimony.

JUDGE VITTONE: Mr. Rupp, excuse me a second. Would this be an appropriate time to take a short recess?

MR. RUPP: Yes, it would, Your Honor.

JUDGE VITTONE: Okay. Thank you.

JUDGE VITTONE: Let's go back on the record and resume with Dr. Ott and Mr. Rupp.

You may proceed.

MR. RUPP: Thank you very much, Your Honor.

Your Honor, I wonder if I shouldn't just to make sure that the record is reasonably clear about what we've been talking about in some of the examples I've given.

I have paced off this room during the break and my estimate would be that it's about 80 feet long, 40 feet wide and 30 feet tall.

That may be off a little bit but does that seem about right to you, Dr. Ott?

DR. OTT: I'm sure it's reasonable.

MR. RUPP: Okay. And I think that will help people reading the transcript some time in the future to understand what we've been talking about.

Now, let's go back to the specific field experiments that you have undertaken in an effort to validate your model and let's focus first on the automobile experiment, okay?

DR. OTT: Yes.

MR. RUPP: Now, as I understand it, what we had there was a car being driven at 20 miles per hour on residential streets with a driver smoking a cigarette every 15 minutes with the windows rolled up but the air conditioner operating. Is that correct?

DR. OTT: The passenger was smoking the cigarette. All else is correct.

MR. RUPP: Okay. Passenger smoking, driver driving.

DR. OTT: Yes.

MR. RUPP: Okay. And in those circumstances, what you did was to measure CO and RSP.

DR. OTT: Correct.

MR. RUPP: All right. Do you know how often people who smoke in automobiles leave all four windows completely closed?

DR. OTT: No, I don't know that. You're talking about the frequency of occurrence.

MR. RUPP: Yes.

DR. OTT: I don't know that.

MR. RUPP: Do you know what impact the opening of one of the windows or the partial opening of one of the windows near the smoker would have had on the level of RSP and CO in the automobile?

DR. OTT: Yes. Because we studied that vehicle in another study under different regimes, windows open, windows closed, lots of different regimes, and we got from those regimes the air exchange rate which is one of the parameters that goes into the model so I can make a very good estimate.

MR. RUPP: Why don't you make an estimate so we'll have that on the record?

DR. OTT: For what?

MR. RUPP: For CO and RSP when the smoker is sitting next to an open window.

DR. OTT: Okay. It's in the paper I cited. It's part of the literature. It's a little table --

MR. RUPP: Do you recall that?

MS. SHERMAN: Dr. Ott, perhaps you could make it available again as a post-hearing comment.

DR. OTT: Okay. I'll make that available as a post-hearing comment.

MR. RUPP: All right. That will be fine. But do you have that paper with you? I see you were looking through it?

DR. OTT: Yes.

MR. RUPP: All right. Would you look through it and see what the impact was when you opened one window adjacent to the smoker on RSP and CO levels?

DR. OTT: We didn't have RSP calculated in the paper, we just had CO. I'd have to get the table.

MR. RUPP: What impact did it have on CO?

DR. OTT: Okay. I'm going to get the table. Okay. Actually, I presented it in my testimony, too. Three cases are in the paper. I think they address your comment. One case is the window is open -- let me give all three cases because it's simple. One is windows open, 20 miles an hour. The second one is windows closed, 20 miles an hour. And then windows closed zero miles an hour. Just three cases here. And then the air exchange rates for those three cases respectively: 121 air changes per hour, 13.2 air changes per hour and 1.4 air changes per hour and the answers you wanted, the numbers you were asking about, for those three cases are .8 parts per million for the windows open, that's one of the cases you mentioned.

MR. RUPP: This is CO.

DR. OTT: This is CO. Correct.

MR. RUPP: All right.

DR. OTT: 7.22 parts per million for the windows closed, 20 miles an hour. And 63.3 parts per million -- actually, there is an error, there is a typo in that paper. It's actually 66.25 parts per million with the windows closed. That's the worst case.

MR. RUPP: Okay. So the CO is varying by a factor of about 10 in the three scenarios.

DR. OTT: Probably --

MR. RUPP: Pretty close.

DR. OTT: Ten each one -- almost ten.

MR. RUPP: Yes. Exactly. Ten, ten and ten.

DR. OTT: That's correct.

MR. RUPP: All right. Now, do you know at what level the air conditioning was running in the automobile that was used in your experiment? Was it on high? Was it on low?

DR. OTT: Yes. It was on high.

MR. RUPP: Was that material being exhausted?

DR. OTT: It was a recirculation pattern with the air conditioner at the maximum it could go.

MR. RUPP: So the air was simply being cooled by the unit and recirculating in the interior passenger compartment.

DR. OTT: Right. For the case I described in the paper.

MR. RUPP: For that case right there, the one you have depicted by chart.

DR. OTT: Right.

MR. RUPP: That is a situation when we have recirculation of the air with two passengers, air conditioning on and that is the method of the recirculation and those depict CO and RSP levels in those circumstances.

DR. OTT: Correct.

MR. RUPP: Okay. Now, have you looked yet at the situation one would have if one used the air vents in the automobile so that you eliminated the recirculation or reduced the amount of recirculation and the air was actually being exhausted from the automobile without lowering the windows?

DR. OTT: No. That's just one of many other cases. To elaborate, and maybe this is relevant to what you just asked. We took the position that we also don't know about ventilation rates of all the other vehicles. Actually, we tried about two. But someone else needs to do a very exhaustive study of these air exchange rates as a function of all these things.

MR. RUPP: Right. But we do know, do we not, or at least we can assume fairly safely, can we not, that air exchange rates in different automobiles is going to be quite different depending upon factors such as these: whether the air conditioning is on or not and at what level it is on; whether the vents are on so that material is being taken from the car or whether we're talking about 100 percent recirculation; the size of the compartment; whether windows are open or down and which are open and down. There are several factorials there are as well.

DR. OTT: Do you want me to answer all that?

MR. RUPP: I'm just asking aren't those all factors affecting the degree of exposure.

DR. OTT: Well, I believe you've mixed in some bogus but not intentionally. The volume is not a parameter because the volume is -- the air exchange rate is measured as volume of the vehicle. And it is surprising, and if you really think about it it will agree kind of with common sense but the thing that really is a powerful factor in that list is opening and closing windows. I mean, the most extreme would be to go to a convertible, it's all open. And, again, this would agree with common sense. And these other things and there is some recent work the American Petroleum Institute has told me about where they are saying windows are everything in a car, it seems that those are the main -- which is another way to say that ventilation is quite important.

MR. RUPP: Yes. All right. Now, your statement indicates that blood carboxyhemoglobin levels were increased in both the smoker and passenger in your automobile experiment, as measured in breath using the method described by Jones and co-workers in 1958. I would be interested in knowing how much the elevation was in the non-smoker.

DR. OTT: In the non-smoker?

MR. RUPP: Yes.

DR. OTT: It went from -- and I presented the numbers, so I might be able to -- they're in the testimony.

MR. RUPP: I don't believe they are, actually, unless I've missed them.

DR. OTT: Maybe you're right. Did you say blood carboxyhemoglobin?

MR. RUPP: Correct. That's what I said.

DR. OTT: You're right. Excuse me. I did not convert these breath levels to blood carboxyhemoglobin. I didn't do that conversion. I simply presented them as PPM in breath as an indicator of the change in the carboxyhemoglobin.

MR. RUPP: So we don't know what the impact of any measures you've taken would be on blood carboxyhemoglobin.

DR. OTT: That's correct.

MR. RUPP: I take it you do understand that the Jones breath carboxyhemoglobin measure is not a measure that would be used in science today to measure blood carboxyhemoglobin.

DR. OTT: Well, it's -- there are questions about it but for this type of -- you know, what we're doing with it here, it is quite suitable. We're not doing a study on blood carboxyhemoglobin, we're simply looking -- you know, we're seeing if there's some kind of gross change.

MR. RUPP: But if your interest were blood carboxyhemoglobin, you would measure that directly, would you not?

DR. OTT: Oh, I think I might do something like Hank Freeman's approach, which is gas chromatography for blood carboxyhemoglobin.

MR. RUPP: All right. You also sought to validate your model using a chamber. And in that chamber, did you have perfect air mixing, no perceptible air flows and no sinks?

DR. OTT: That's three questions. In the chamber, we had a couple of little fans that were not very -- you know, enormous in their effect. There were a couple of little, tiny fan. What was your other question?

MR. RUPP: What were the dimensions of the chamber?

DR. OTT: I gave them in the paper. I didn't give the dimensions right, I gave the volume. The volume was 3.4 cubic meters but I don't have the dimensions handy here. They're probably in the original paper.

MR. RUPP: And the air was mixed in the chamber by a fan?

DR. OTT: A couple of little, tiny, two-inch diameter fans in the corners of the chamber that weren't terribly effective at the far corners because we did do about 16 measurements in the chamber as part of quality assurance before we did our study.

MR. RUPP: Was there an ventilation or exhaust from the chamber?

DR. OTT: It wasn't a chamber which had -- if that's what you're asking, it wasn't a chamber which had an attached venting system and attached supply system.

MR. RUPP: The air in the chamber was being recirculated, then, by the fans.

DR. OTT: Yes. That's right. And we started the experiment in the day with a very, very clean background. In the building, there was no -- this was in San Francisco.

MR. RUPP: Were there places in the chamber where the air might seep out, around the door, for example?

DR. OTT: Yes. Yes. And that was what we assumed was controlling our exchange rate, so we could fix it if we didn't like it. What we had on the chamber were large vinyl covers. This is a UCSF chamber in San Francisco and we could fasten those as tightly as we wanted to vary things.

MR. RUPP: All right. Let me ask one final question on the blood carboxyhemoglobin level. I'm going to read you a passage and ask you whether you would agree or disagree or have any basis for offering any comments.

DR. OTT: Okay.

MR. RUPP: All right. This passage is from the volume by Garin, Jenkins and Thompkins, "The Chemistry of Environmental Tobacco Smoke, Composition and Management" and the date of this volume is 1992. I am going to read to you, Dr. Ott, from page 183. It's a short passage, happily.

"Shevilbean and Riechter summarized several studies describing the ranges of carboxyhemoglobin in unexposed smokers both before and after exposure to ETS. Carboxyhemoglobin percentages for non-smokers range from 0.1 to 3.7 percent as shown in nine studies which used between 78 and 16,000 subjects."

Are you still with me?

DR. OTT: Go ahead.

MR. RUPP: "The percentages for non-smokers exposed to ETS ranged from 0.5 to 2.6 percent based on nine studies involving between 7 and 47 subjects. Hence, studies which quantified the percentage of carboxyhemoglobin in non-smokers show very little difference in non-smokers who were or were not exposed to ETS."

Do you have any basis for disputing the interpretation of the pertinent studies undertaken by Garin, Jenkins and Thompkins?

DR. OTT: I really have no opinion on it at all. I have no basis for supporting or rejecting it.

MR. RUPP: Okay. The model developed by Mr. Repace to which you also refer in your statement, that model also assumes, does it not, instantaneous perfect mixing of indoor air components and a single compartment?

DR. OTT: Yes.

MR. RUPP: Let me read to you again from a statement from Professor T. Yamamoto and co-workers presented at Indoor Air '90, the proceedings of the fifth international conference on indoor air quality and climate, at which they stated after referring to the models developed by Mr. Repace and others, "These models do not adequately account for various parameters such as supply return air duct location and source location. Especially the contaminant concentration in the occupants' breathing zone will be an important consideration for evaluating the indoor air quality and ventilation effectiveness."

Those comments are as valid today as when they were made in 1990, are they not? That is if we make certain assumptions or ignore certain complications, we can get one set of answers --

DR. OTT: I don't understand --

MR. RUPP:  -- or an interpretation --

DR. OTT: I'm sorry. I would not agree. I would immediately talk to that person as to where he did his reasoning. I think he needs some help. I'm not familiar with that and I would not agree with that.

MR. RUPP: I'm sorry?

DR. OTT: I would not agree with that statement.

MR. RUPP: You wouldn't agree with that. So you don't think the location of the supply or return air ducts, the location and their strength, would have any impact on the level of contaminants in an indoor space?

DR. OTT: Well, you've been through this before with me. I'm not sure why you want to go back to it again. I said I'm not a ventilation engineer and I have no data. We've looked at the literature very carefully as it concerns our model and I have no data showing where this deviation from uniform mixing is gong to make a big effect in average exposures in the places people really are in and they are not in long tubes that have laminar flow very often.

MR. RUPP: Okay. But if we have -- well, two questions are suggested by that. The first is to confirm again the application of your model is limited to the single compartment. That's point one.

DR. OTT: Correct.

MR. RUPP: All right. Point two is you have not done the work that would determine -- that would permit us to make a determination of the extent to which there is or is not laminar flow in the various indoor environments in which people find themselves, have you?

DR. OTT: No. But some work is underway on that.

MR. RUPP: That's not what I asked. You haven't done it.

DR. OTT: I don't think anybody's done it.

MR. RUPP: Okay. Fair enough. You also have cited a 1980 paper by Mr. Repace and Dr. Lowery. Since the data reported in that paper are now 15 years old, I take it that you would agree that those data do not necessarily tell us much about the extent of exposure in the American workplace today?

DR. OTT: I don't agree with that and I didn't cite any of the data. If you go through my testimony --

MR. RUPP: You cited the paper, is what I said.

DR. OTT: I simply cited the paper and the models, the structure of the model.

MR. RUPP: I'm now asking you about the data in the paper.

DR. OTT: Okay. I think -- what was your question about the data? I'm sorry.

MR. RUPP: Let me try it again. Let's assume that those data, that the 1980 Repace data were valid at the point at which the measurements were taken, to the extent they were based on measurements.

DR. OTT: Right.

MR. RUPP: Would you agree or do you have any insights that would cause you to agree or to doubt my statement were I to suggest that the situation in the American workplace in 1980 so far as exposure to ETS is concerned is not at all the situation that exists in 1994 on average?

DR. OTT: Well, I have a personal opinion.

MR. RUPP: And what is that opinion? You think ETS exposure has increased over that period of time? Has stayed constant or has been reduced over that period of time?

DR. OTT: Well, my personal opinion is that it has declined because smoking has declined.

MR. RUPP: Are you also aware that the RSP figures cited in the 1980 Repace-Lowery paper are approximately an order of magnitude higher than those reported by the overwhelming majority of other investors? Or have you looked at that aspect of the paper?

DR. OTT: I have not looked in detail with all the field measurements that have been done, the numbers, because I have been looking at the models.

MR. RUPP: Right.

DR. OTT: But I don't have any basis to see that order of magnitude you're describing.

MR. RUPP: But you haven't looked yet.

DR. OTT: Right. I haven't looked.

MR. RUPP: All right. Are you aware that it was assumed in the Repace-Lowery paper, the 1980 paper that you cited, that all RSP was derived from ETS?

DR. OTT: I'm not aware of the details of how they did their --

MR. RUPP: If they had made such an assumption, I take it you would agree that that assumption would not be correct.

DR. OTT: If they had made that assumption, correct.

MR. RUPP: In an article published in the January 1990 edition of "Seminars in Respiratory Medicine," Volume 11 beginning at page 87, Drs. Mehasian and Huber offered the following observation and, again, I would ask you to listen to this and tell me whether you agree or disagree with this observation.

"The enormously high levels of particulate matter reported by Repace and Lowery," referring to their 1990 paper, did not adequately control for other environmental particulate matter, half or more of which originates from non-tobacco sources. Other criticisms of this study include lack of control for humidity, inadequate calibration and use of obsolete and inaccurate equipment."

Do you have any basis for agreeing or disagreeing with those observations?

DR. OTT: A little bit. I have used the instrument that Repace -- well, you had a whole bunch of things listed there and so when you say agree, what am I agreeing to?

MR. RUPP: Let me make it easy. Are there any aspects of this with which you would disagree?

DR. OTT: Well, I kind of forgot them all, there were so many there.

MR. RUPP: We're talking about the assumption that all RSP in an indoor space originates from smoking and the other criticisms include lack of control for humidity, inadequate calibration and the use of obsolete and inaccurate equipment.

DR. OTT: Those latter two ones, I don't believe -- I believe the reviewer fabricated those.

MR. RUPP: You still like the equipment used in 1980 by Repace and Lowery?

DR. OTT: The equipment is excellent.

MR. RUPP: Okay. Now, finally, I would like to quote a passage that appears in the monograph written again by Garen and co-workers at Oakridge National Laboratory and ask you to respond to this particularly in connection with this mixing question which may be of some significance here.

DR. OTT: Sure.

MR. RUPP: Garen and Jenkins after having reviewed the literature stated as follows, "Even closely spaced area samples showed considerable differences. The authors," referring to nicotine and RSP, "concluded that this finding may suggest considerable atmospheric inhomogeneity of nicotine concentrations within indoor environments."

If we find in the pertinent literature significantly different readings being given by area samplers spaced within a large room such as this, would that be inconsistent with your notion of perfect and instantaneous mixing?

DR. OTT: Well, you haven't found that.

MR. RUPP: Let's assume we have. Would it be -- if the literature --

DR. OTT: There's many things in the literature.

MR. RUPP: Sir, if the literature showed that, would that be inconsistent with your notion of instantaneous and complete mixing of RSP and CO?

DR. OTT: If the literature showed what I know it doesn't show, yes, you're right.

MR. RUPP: And you know that there is no literature out there that shows that if you put area samplers in a room of this sort, you would not at various times, given a variety of factors including human activity patterns, smoking source location, different readings on that area monitoring equipment?

DR. OTT: Well, I have tried to answer that earlier so let me just repeat so there is no doubt. A study by Baughman, Gadgil and Nazaroff that's published recently in the peer reviewed literature studied 40 points in a large chamber to address that specific question, and this gets back to the alpha, gamma and beta periods and this is the relevant work and this is the only work of which I am aware that meets my sense of good science and it shows a different story than the one that you are citing. I don't know where you are getting these references at all.

MR. RUPP: All right. You have written a number of these papers, I take it, with Dr. Paul Switzer of Stanford?

DR. OTT: Yes.

MR. RUPP: Do you believe that Dr. Switzer agrees with you that in large open spaces of the sort that we are located in today that one can safely and productively assume instantaneous and complete mixing of the air without regard to the geometry of the room, the air flow within the room and so forth?

DR. OTT: I don't think Dr. Switzer has any opinion nor really do I about a speculative room. I think to answer your question as best I can, I think his approach to the science, as I followed it, is to go out and measure and see what's really happening. Or to look at the best, most recent peer reviewed, high quality science on that subject.

MR. RUPP: Let me read to you a sentence from Dr. Switzer. And I quote, "Considering the heterogeneity of workplaces and the lack of appropriate survey data, it would be impossible to characterize workplace pollutant concentrations over the population of workplaces using the proposed model." Do we just have a difference --

DR. OTT: Which proposed model?

MR. RUPP: Using the --

DR. OTT: I don't know what you're taking out of context there but I think that's even a statement that I would make in that we aren't -- we are very careful here to say that we aren't applying this model to the multi-compartment case which I could visualize a complicated building. I have not in any referred to any work or application or even suggested that be done, so I would support that comment.

MR. RUPP: So you agree with Dr. Switzer, then.

DR. OTT: In the conditions I believe he's speaking, which is what I just said. It's an office, a complicated office. But I also think for the sake of experiment, one can do work on offices just like we've done on chambers, vehicles and a lot of other work that EPA is doing but if you'll remember in my testimony I said we are doing other work in other settings, the same kind of careful work, three or four points in each setting, to look at exposures and to look at concentrations and to factor in all the things you have talked about.

MR. RUPP: And some day we will know whether the model does a good job or a bad job and what kind of refinements may or may not be needed in those variety of circumstances. Is that --

DR. OTT: Well, the way you've said that, I wouldn't agree with because it sounds like someday the model will work. The model is impressive for the validity and precision with which it predicts the cases we've described. You can see right up there. And in addition, another point in my testimony was the model uses this basic law from physics, which I've described, which is used by all the other models. So we don't have just one model, I mean, we don't have just a great variety of models that are all different, we really have one model. And you'd pretty darn surprised if they all came up with different models.

MR. RUPP: And the basic law of physics is that all matter has to be somewhere.

DR. OTT: Somewhere. Exactly. You've said it well.

MR. RUPP: That's all I have

JUDGE VITTONE: Thank you, Mr. Rupp.

Just for the record, what kind of car was involved in this experiment?

DR. OTT: It was a Mazda 626 sedan. It was my car and it smelled awful for at least a month after that experiment.

JUDGE VITTONE: All right.

I think I've got everybody. Only Mr. Rupp indicated he wanted to ask questions. Let me make sure there is nobody else in the audience. Okay.

Ms. Sherman, any clarification or redirect or whatever?

MS. SHERMAN: On page 4, the second paragraph, the third line from the bottom of that paragraph, you may have said 50 milligrams per cubic meter rather than 99 milligrams.

DR. OTT: Micrograms. Micrograms. Yes. Right.

MS. SHERMAN: Excuse me?

DR. OTT: Micrograms per cubic meter.

MS. SHERMAN: Yes. Micrograms per cubic meter. Did you mean 50 or did you mean 99?

DR. OTT: We changed the example just one little bit to make it simpler for everybody so we could put it on the overhead and we just had one cigarette and the testimony has two cigarettes so it got us up to twice the number, so it's all consistent.

MS. SHERMAN: So in other words, your written testimony was giving an example with two cigarettes and you came out with 99 micrograms per cubic meter, your oral testimony had one cigarette and it came out to be 50 micrograms per cubic meter. Is that correct?

DR. OTT: That's correct.

MS. SHERMAN: Thank you.

Just to recap, in your experiment with the car where the person was driving and another one was smoking, you had the air conditioner operating on recirculation, did you not?

DR. OTT: Yes.

MS. SHERMAN: Do you have any research underway to explore the validity of your assumption about even mixing that's included in your model?

DR. OTT: About what? I didn't hear. I just couldn't hear you. I'm sorry. About uniform mixing?

MS. SHERMAN: Yes.

DR. OTT: Yes.

MS. SHERMAN: Do you have any research underway to explore the validity of your assumption about uniform mixing?

DR. OTT: Yes. First of all, it's not just me. There are also other people who talk to each other around the country. There is research at EPA, in Las Vegas EPA, going on now and I won't go into the details. There is research at Berkeley going on and we talk. And then we have a plan to do a 16-point measurement in a large room, not quite this large, but with high precision, real time CO. To do some of the same experiments that I was asked about.

In a way, the funny thing is what we seem to be doing is trying to find out where does this uniform mixing break down because it does not seem to break down very much in real settings where people seem to be but it has to break down. I think if we make the setting complicated enough, because we know if we go to the multi-compartment case, we put a barrier between the two, it breaks down there. It's a complicated topic.

MS. SHERMAN: Do you have any estimate as to when this research would be completed?

DR. OTT: Well, I think, as I've tried to point out, the Baughman, Gadgil, Nazaroff work is relevant and just was completed and there's more probably going on there. I can't speak for the work going on in Las Vegas in their chamber, which by the way puts a point source in the chamber and then measures different distances from that point source. And in our case, I think it's really a matter of -- the equipment has not arrived. It's probably a matter of a year or two to do those experiments. And also to figure out what other experiments would be a good idea to do.

MS. SHERMAN: This is something that I would perhaps like you to do for the post-hearing comment, if you would. If you had a 483-cubic meter space and you had an average of one cigarette smoked at all times, so when one was finished another one would be lighted, what level of general ventilation would be required to reduce the office exposure to 10 milligrams per cubic meter of RSPs from ETS?

DR. OTT: Ten micrograms per cubic meter.

MS. SHERMAN: Micrograms. Excuse me. Milligrams is the wrong thing.

DR. OTT: Sure.

MS. SHERMAN: If you could do that computation --

DR. OTT: Certainly.

MS. SHERMAN: I wouldn't want you to do it up here on the stage but if you could supply that for us, I would appreciate it.

DR. OTT: Certainly.

MS. SHERMAN: I have no other questions.

MR. RUPP: Would you indulge me for another 90 seconds? There was one item that I wanted to pursue with him and I failed and I would be happy to have Ms. Sherman have another opportunity to ask questions but I think this is important enough to get into the record and I would like to do it now where the issue is here.

JUDGE VITTONE: How long will it take?

MR. RUPP: I think I can do it in 90 seconds.

JUDGE VITTONE: Ninety seconds?

MR. RUPP: Ninety seconds.

JUDGE VITTONE: Okay.

MR. RUPP: Thank you very much. I appreciate it.

I'd like to proceed with you one further step, this concept of perfect mixing. Are you familiar, Dr. Ott, with a work by Nagda and co-workers aboard commercial aircraft?

DR. OTT: I know the work went on but I'm not intimately familiar with the work.

MR. RUPP: All right. This is work that was conducted in the coach class cabin of the environment. Would that qualify as a single compartment for purposes of your model?

DR. OTT: I think -- well, some planes are complicated. I have to know what kind of plane it is.

MR. RUPP: Well, this was a plane which you'll find at United Airlines, any of the airlines, with no divisions between.

DR. OTT: Well, to save time, yes.

MR. RUPP: Okay. All right. Fair enough. Now, let me read you the results of that study as reported in 1990. "Ninety-two randomly selected flights averaged nicotine concentration in the smoking section was 13.5 micrograms per meter cubed dropping to 0.3 micrograms per meter cubed at the smoking/non-smoking boundary and reaching background concentration of 0.05 micrograms per meter cubed at the middle of the aircraft cabin. Respirable particulate matter concentration similarly dropped from 76 micrograms per meter cubed to 54 to a background concentration of 34. Other studies show less dramatic but clearly measurable spatial isolation of ETS constituents aboard aircraft."

I take it you would agree if the Oakridge researchers have properly characterized the Nagda results that your model would not accurately predict what's happening on an aircraft because this is not perfect mixing.

DR. OTT: If that's the date from the aircraft and those numbers, if I remember the last numbers, and, again, I'm not familiar with the work so I would want to look at that in great detail but I could certainly give you a speculative answer. If the numbers were kind of as you -- just remembering, 60 to 30, something in that range RSP, that wouldn't be too unreasonable for me to consider that to be a two-compartment model which would be very easy to handle with this kind of approach but the reason probably it's a two-compartment model is we're all in what we call the alpha period in that paper I referred to, the cigarettes are on and during that -- all these people are smoking, after all, and so the -- and for all I know, and, again, I don't know the study, there could be quite a bit of difference in the ventilation system purposely designed to separate those areas. I don't know. But it seems to me all of the results you have are reasonable and also consistent with good modeling that we could do a pretty good job on that aircraft.

MR. RUPP: So the quality of the ventilation does affect -- you are prepared to assume that it would affect the concentration in particular locations within a single otherwise uninterrupted space.

DR. OTT: Yes. I think you're getting, to my way of thinking, to a little close to your long tunnel and in the parts of the work that we've done for quality assurance purposes only, quality assurance where we've tested instruments, we have found if you had a restaurant that was long enough, it would have to be awfully long, you've got a smoking section and a non-smoking section in the restaurant that was like a hot dog, it was a block long, you could see some isolation. But it took a radical separation and distance because this well mixed assumption is a very powerful assumption operating in the kinds of micro-environments people --

MR. RUPP: It's a powerful assumption. The question is whether it is correct.

Thank you, Your Honor.

JUDGE VITTONE: All right. Thank you, Mr. Rupp.

MS. SHERMAN: I have another question.

JUDGE VITTONE: Sure.

MS. SHERMAN: Dr. Ott, would you be willing to look at the article cited by Mr. Rupp and as a post-hearing comment put in any other impressions as to how this would relate to your model?

DR. OTT: Sure. But the chances are it wouldn't go a lot beyond what I said unless -- and I'll just say at the beginning, unless those folks were trying to model it. If they're not trying to model it, you read it, they leave out all kinds of things you really want to know, so it's hard to --

MS. SHERMAN: Well, perhaps you could review it and see if you have any other thoughts on it.

DR. OTT: I'd be happy to. Sure.

JUDGE VITTONE: All right. Thank you, Dr. Ott. You may step down, sir.

JUDGE VITTONE: Ms. Jenkins?

We are off the record.

JUDGE VITTONE: Okay, let's go back on the record.
Our next witness is Ms. Peggy Jenkins.

Ms. Jenkins, would you identify yourself for the record, please, and who you're representing today?

PEGGY JENKINS

CALIFORNIA AIR RESOURCES BOARD

MS. JENKINS: Yes, I'm Peggy Jenkins, I'm the manager of the indoor exposure assessment section at the California Air Resources Board, and I'm here at the invitation of OSHA. However, I'm also here under approval from the State of California; so to be frank, I'm not sure who I represent. I think both, but my comments are from the State of California.

JUDGE VITTONE: Okay, and you previously submitted your comments on August the 12th, 1994?

MS. JENKINS: Yes, I did.

JUDGE VITTONE: Your comments that were submitted will be marked as Exhibit No. 33.

(Exhibit No. 33 was marked for identification.)

JUDGE VITTONE: You're also going to be using some slides, I guess?

MS. JENKINS: Yes, sir.

JUDGE VITTONE: Will you be able to provide a copy of those slides for the record?

MS. JENKINS: I will. I'm missing two hard copies, but I can send those as soon as I get back.

JUDGE VITTONE: If you could do that within a week after you get back.

MS. JENKINS: Okay.

JUDGE VITTONE: Could I ask you, as you go through your presentation and you use the slides, to please identify them by some process; slide number one, slide number two, something like that if you've got some kind of identification for them.

MS. JENKINS: Okay.

JUDGE VITTONE: Can you give me an idea how long you're going to take for your direct?

MS. JENKINS: The full presentation is about an hour and 15 minutes. I can try to go down to about an hour. I think as I mentioned earlier, there are some items that I wanted to clarify and also several areas in my written testimony where I did not yet have the final numerical values, so I do want to present those today.

JUDGE VITTONE: All right.

By the big clock up on the wall, that will probably take us to at least 6 o'clock. At that point I'm going to find out who has questions; I think some people have already indicated that they will have questions for Ms. Jenkins. And then I think we will break for the evening and come back with her first thing in the morning, and resume with her. But I'd like to get her direct in tonight.

Go ahead, Ms. Jenkins.

MS. JENKINS: Thank you. My name is Peggy Jenkins, I hold a master of science degree in ecology and a bachelor of science degree in zoology, both from the University of California at Davis. Since 1987, I've managed the California Air Resources Board's Indoor Air Quality and Personal Exposure Assessment Program.

As the manager, I do oversee the allocation expenditure of $500,000 a year in research funds. I have been responsible for developing the study designs for and funding a number of I think very unique and pioneering studies in the fields of indoor air quality and exposure assessment.

These include California's first state-wide radon study, the first representative activity pattern study directly related to estimating air pollution exposure; and of course that I'll be talking about today, and the first large scale studies to measure polycyclic aromatic hydrocarbons and other semivolatile pollutants in residences.

I serve on a number of advisory committees and task forces, including Cal-OSHA's Indoor Air Quality Advisory Committee -- that's California OSHA -- the Building Standards Construction and Management Task Force of the advisory committee to the California Senate Subcommittee on the Rights of the Disabled. The peer review panel for USCPA's national activity pattern survey, and the California Indoor Air Quality Interagency Working Group.

I also was an active member of the Human Health Committee for California's Comparative Risk Project, which was recently completed. I've also participated in a number of indoor air quality and exposure assessment conferences as a speaker, session chair, and reviewer.

Prior to my current position, I worked at the Air Resources Board in their health standards program, assessing the health risks for ambient air pollutants. Finally, I also have some expertise in survey research; I received training in survey research methods in grad school, conducted survey research as a grad student and subsequently, for one and a half years, worked for the Forest Service in survey research.

[Slides shown]

I appreciate the opportunity to present information today regarding our indoor air quality research. First I will discuss relevant analyses of data from our activity pattern study,l which I believe does provide important information, useful in OSHA's consideration of their proposed rule. The majority of my presentation will focus on our activity pattern study, following that, I will present limited information from field studies that have been conducted under ARB funding.

I will not be presenting information today on the last study mentioned in my written testimony; that's an environmental tobacco smoke chamber study conducted by Joan Dazey at Lawrence Berkeley Lab. That study has not been reviewed yet by ARB's research screening committee, and that is a prerequisite before we can present results to the outside world. So that committee should meet this Wednesday to consider that study.

The first slide was slide 1; this is slide 2. I'd like to acknowledge the investigators that conducted our adult activity pattern study; Dr. Jim Wiley of the Survey Research Center at UC-Berkeley, and Dr. John Robinson at the University of Maryland.

It was a state-wide survey of activity patterns of Californians over 11 years of age, and we did this primarily to obtain data needed for exposure modeling. This was not an ETS study per se. Therefore, we did not measure ETS or any other air pollutants. This was strictly conducted to fill major data gaps for exposure modeling.

Slide 3, I'd like to acknowledge also the advisory panel members that served to review and provide guidance on all aspects of this study including both the study design, the questionnaire development, review of the final report and so forth. And as you can see, a number of individuals from USEPA assisted us as did some individuals from the private sector and the academic sector.
I should also mention that the Air Resources Board's research screening committee did review and approve all aspects of our study as well. That committee is composed of individuals knowledgeable in air pollution, statistics, and really all aspects of air pollution risk assessment and risk management.

Slide 4, study objectives. The primary objective of this study, as I said, was to obtained detailed data on the time spent in various locations and activities for use in estimating exposure to air pollutants.

Additional study objectives including -- we wanted to obtain knowledge of California's use of and their proximity to pollutant sources; hence our question to the respondents regarding ETS. And household ventilation practices and other characteristics. We also wanted to examine demographic and socioeconomic differences in activity patterns to the extent feasible.

Slide 5, survey design. This was really not a computerized telephone survey, per se, but a computer-assisted telephone survey or CATI survey; which involved modified random digit dialing after the Waksberg method. It included only English-speaking households, primarily because of the cost.

In California, people tend to think that the only other language one needs to translate into is Spanish; however, these days, we have many Asian languages that we would also have to translate our survey into.

It involved a 24-hour recall diary. 24-hour recall diaries have been used and validated in previous time use studies, after Juster and Stafford, Szalai, Robinson and Holland, and others.

These studies have shown that 24 and even 48-hour recall is very good. Beyond that, there is a sharp in an individual's ability to recall the specifics of where they went and what they did several days ago.

We did, the sample was random except for one adjustment we made in the sampling rate for different regions, because we wanted to try to identify differences in activity patterns in different regions. We needed to do this, otherwise most of our sample would have consisted of people in Los Angeles, and there's a lot more to California than L.A.; so we did adjust the sampling rate.

The data are weighted in the analysis we've done to adjust back to the actual ratio in the state population. And we did conduct the study over four seasons, and all seven days of the week.

Slide 6, because questions have been raised regarding our survey, I'd like to emphasize that there is extensive QA/QC, quality control/quality assurance. In particular, the interviewers were extensively trained, and this is absolutely critical in survey research because interviewers probably are the big factor in terms of avoiding bias in the estimate in terms of people's responses.

Most of the interviewers on the study had already been very experienced; those that weren't received extensive training in interviewing techniques. They were all trained on the CATI system, they had to review and discuss the detailed project training manual that was developed at UC-Berkeley Survey Center for this project. They went through extensive practice interviews, and their supervisors reviewed their interviews extensively.

I should note that nearly 50 percent of the actual interviews were monitored by supervisors in a blind fashion; in other words, the interviewers did not know that they were being monitored, and the supervisors were checking throughout for appropriate interaction between interviewers and their respondents, appropriate coding and recording of the data.

The CATI system itself involves extensive QC checks. For example, there's an automatic probe of any activities over two hours in length in which the interviewer must go back and ask the respondent if they have forgotten any activities that they were doing during that two hours, to assure that activities reported two hours or more really just consisted of that one activity in that one location.

Automatic branching and actual recording of the actual responses was also a feature of CATI; and also a number of pilot interviews were conducted, both with individuals at the Survey Center and individuals out in the public, in order to assure that the questions were clear and that any problems were identified and remedied immediately. That was Slide 7.

Next slide, 8. Our sample consisted of 1762 individuals, 12 years and older. Much of the time today I will be talking about individuals 18 years and older; the adults in our sample, the total in there is 1579. Interviewing was conducted from October of '87 to September of '88.

The response rate for the adults was 61 percent. This is at the low end of the normal range for this kind of survey. However, we've done a number of checks to determine how close our sample was to that of California's population at the time.

Slide 9, Figure 1.1. In comparing the age and gender groups of our sample to that of California, compared very well except for older individuals, those over 65, and in particular the males over 65 were undersampled in our survey. You can see the 6.1 and 4.1. And we did compare our data to the 1988 current population survey report from the California State Census Data Center. This is an annual effort, actually conducted by the U.S. Census Bureau every year to update the Census for individual states.

Slide 10, Figure 1.2, comparing employment in socioeconomic factors, the unemployment rate was comparable. The median household income technically speaking matched; however, as you can see in our sample population, we did not ask for the explicit income, but rather asked income by $10,000 increments.

In looking at the differences between our sample and the California population for education, you can see that our sample had a higher average education level than the California population. Therefore, we suspect that we slightly oversampled the higher socioeconomic groups relative to lower socioeconomic groups.

Slide 11, at the risk of offending some of you, this is not intended to imply that people here don't know what exposure equals, but I had an important point that I wanted to make. This is a very simple equation; the fancy scientific one just looks a little different.

But essentially, exposure is equal to the air concentration of a pollutant in a given microenvironment times the amount of time that the individual spends in that environment; and of course one sums up the exposures in different environments over the day to reach total exposure.

What's important here, and the point I want to make is, so often people tend to think of exposure as only being based on the concentration of a pollutant in a given environment. I want to point out that the duration of that exposure, that time is an equal partner here. Time is equally important in determining people's actual exposure.

And this may not be very visible with all the lights on, but this I think illustrates my point
well -- on the left-hand side there's an increasingly dense concentration of a pollutant in the air, and you can see the individual becoming ill because of the greater concentration.

On the right hand side of the slide, there's the same low concentration over time that the concentration is held constant, but as the individual remains in that environment over time, the amount of pollutant inhaled is doing harm.

And what this shows is that, particularly I think for carcinogens for which there is no known level of effects, no threshold of effects, where IARC and EPA and other groups have not been able to identify a safe level, there is concern over low levels of pollutants to which people are exposed over long periods of time.

That was Slide 12, this next one is Slide 13. One other point I'd like to make; when we consider what the inhaled dose is of individuals in a given microenvironment -- in this equation, microenvironment J.

That, of course, is equal to the air concentration times the time, which is essentially exposure times a breathing rate. And I would just note that this is essentially the concept, the reason we were obtaining the time duration data is that we had air concentration data for a number of environments. We funded a separate study to obtain the breathing information.

We do know both from our breathing study and other studies that the rate of inhalation of air is generally less in the home environment because people spend on average seven or eight hours a night sleeping, and the respiration rate goes down tremendously. People are out and about and at work, breathing rates tend to be higher.

Slide 14, the way that our 24-hour recall diary worked is that the interviewer starts with midnight the night before and attempts to take the individual through their day sequentially; for example, "what were you doing at midnight the night before?" Most people will answer "I was asleep." Okay, where were you?

They go through activity and location, activity and location. For each activity and location, the respondents were asked "Were you around anyone who was smoking a cigarette, cigar or pipe while you were in that location or doing that activity? Smokers, people who had previously identified or indicated that they had smoked on their diary day, were asked "were you around anyone else who was smoking a cigarette, cigar or pipe while you were doing that activity or in that location?" Thus, we feel that the responses to our question, what we feel is a good measure of reported ETS exposure.

Slide 15 is from our atmospheric environment paper, which has been -- was published in 1992 in Atmospheric Environment.

The data I'm going to present in about the next four slides has been published and peer reviewed. The remaining slides have not yet been peer reviewed or published.

We're working on a paper right now, we hope to have them published in the very near term.

They were presented, recently -- just last week I presented a number of the slides in here that are not yet published, presented them at a joint conference of the International Society of Exposure Analysis and the International Society of Environmental Epidemiology.

What we've done with our data, over time for different purposes, is to attempt to look at the reported ETS exposures from a variety of angles. Again this is really just to try to make the best use of the information we have. So the very first look at the reported ETS data that was taken was actually compiled by Dr. John Robinson. He initially had put together a draft of this table.

What he looked at and what we later refined was, to identify first the total number of activity episodes, meaning times people did different activities in different locations. This list -- this slide and the next slide do not constitute the full list of locations; it's just the ones that came out with the highest number of total activity episodes. They're in order of the number of episodes with smokers present.

I want to draw your attention to the last two columns, the percent of episodes with a smoker present and the average minutes per episode with a smoker present.

I don't know if this is going to be able to be seen by everybody in the back. First if you look at this column here, the higher percent numbers, you can see that in restaurants, 42 percent of visits to restaurants involved reported exposures to ETS, 22 percent of office visits, 37 percent of visits to the industrial plants, over here.

And the fourth column, if you look at the average minutes, the average duration per activity-episode reported with a smoker present, office buildings and industrial plants showed 153 and 173 average minutes duration exposure reported each.

And looking at this a little further, I'll just draw your attention to bars and nightclubs. Not unexpectedly, 78 percent of those visits involved reported exposures to ETS. Other public buildings, 25 percent of the episodes.

Over here, other public buildings had 35 average minutes per episode, and beauty parlors and barber shops also had long durations of reported exposure. That was Slide 16.

Slide 17, our view of what that means is that the locations with the greater likelihood of exposure, TTS included in order -- bars and nightclubs, restaurants, industrial plants, offices and public buildings, and one's own home. One's own home is that data for the home added up. You might have noticed, there are several categories for home; living rooms, kitchens, et cetera.

Slide 18, we also gathered from those tables at locations with the likelihood of longer exposures to ETS included industrial plants, offices in public buildings, one's own home and beauty parlors and barber shops.

Slide 19. Reported exposure to ETS by labor force status. After we completed our paper about maybe two years ago, we were asked by the state, California Office of Environmental Health Hazard Assessment, to do some further analyses of our data for their ETS risk assessment workshop; and this is one of the outcomes of that effort. Again, it's not published, but we hope it will be soon.

This shows, by categorizing our respondents by their status in labor force categories, meaning in and out of the labor force. In the labor force includes people who are actively working, a class of individuals who are currently unemployed, are laid off, but looking for work.

Students, retired individuals, and those keeping house. And as you can see from this slide, a greater percent of individuals in the labor force reported ETS exposure at some time during the day. This is not necessarily workplace exposure yet; this is just across the day.

The average minutes of reported exposure was greatest for those in the labor force compared to those in the other labor force categories.

This is also new. As a next step, one of the statisticians on my staff conducted a logistic regression exercise in which he started with 14 possible variables that we thought would likely be associated with reported ETS exposure.

These included some variables that had previously been reported as linked with or associated with active smoking; it also, the 14 variables chosen also stemmed from our inspection of our own descriptive statistics.

These five variables are the ones that came out with the I guess strongest evidence as predictors of reported exposure to ETS; however, certainly I would acknowledge they are not as strong as one sees, for example, in variables linked with active smoking. That's not too surprising, I don't think.

These are also the five whose P-values were less than .05, which gives one a reasonable amount of confidence.

There are also logical -- with logistic regression and any other regression, of course you need to assess whether the results make sense. And in our view, they did; these are all factors that we had seen from our data and other data;
appeared legitimate.

Just because most individuals are more familiar with linear regression than logistic regression including myself, I'd like to know that what the .739 means, even though it says logit coefficient; it's actually a log exponent, and the interpretation of that value would be that, being a smoker, that smokers have -- it's
about -- well, smokers are a little more than twice as likely to have reported being exposed to ETS in our study compared to nonsmokers.

For labor status, members of the labor force were a little less than twice as likely to have reported exposure to ETS compared to those not in the labor force.

The other findings are not terribly exciting, although they are positive and significant. I would note that both in this regression and also in some data that I will show later, it seems clear that males do tend to report greater exposures to ETS in the sense that both a higher percentage of males than females report exposure, and the frequency, the number of episodes was greater. Also the servicing clerical occupations do have a slight increased probably of reporting exposure and I think these two terms are important when we look at other studies whose samples undersample these categories.

Slide No. 20, that was. Slide No. 21, to sum up then in order -- our results showed that the predictors of probability of exposure, of reported exposure to ETS, were first smoking status, second labor force status, region of residence -- this being L.A.

We believe that just because L.A. has fewer smoking restrictions and smoking ordinances than the rest of the populated areas of Northern California, also just a higher density of population. And then gender, males, and occupation of servicing clericals.

Slide 22, the next few slides are in my written testimony, so I will go through these very quickly. This is the same as Table 1 in the written testimony. I'd just like to point out that here we're starting to narrow down the end.

The next few slides including this one will refer to nonsmokers who worked outside the home; and the N in that group, from our study, is 462 and the percent of those who reported exposure to ETS at work, one minute or more exposure, 47 percent of the males and 30 percent of the females, for an average of 40 percent.

Although I will be, of course, focused on what's going on with that 40 percent, I think it's important to know it and to acknowledge that 60 percent of the nonsmokers who work outside the home did not report exposure to ETS at work.

Slide 23, Table 3 -- no, I didn't skip Table 2, and I apologize; we'll get to Table 2. I realized in my written testimony things are really not in a logical order. This is still looking at nonsmokers who worked outside the home.

The data here are from Table 3C, the A columns in my written testimony, and I want to indicate that the numbers here replace the percentage data indicated in Table 3-8 of the Federal Register.

What this shows is that -- the workplace percentages are just what you saw in a previous slide; the other percentages show the percent of males, females and both combined, who reported exposure to ETS in the home and other indoor places other than the home and work, and in outdoor places.

Slide 24, Figure 3A1. This is from Table 3A in my written testimony; it's just showing the data for the males. I want to take a minute to explain this, because I have several pie charts just like this one. This is the proportion of reported ETS exposure duration in specific environments for male nonsmokers who worked outside the home.

What this is is for each individual respondent in this category, 248 of them, we added up the total minutes during which they had reported exposure to ETS, and then for each major microenvironment, the total minutes in that environment divided by the total across the date in order to determine sort of an insides, if you will, of where they were receiving or experiencing the greatest duration of exposure.

So this is a proportion of their total daily reported exposure. As you can see for this group, the males, 51 percent of their total exposure duration on average was experienced at work. I will note here in on just about every other slide, the numbers in parentheses, plus or minus, are standard deviations.

They're all generally very large, and this is not an anomaly, there's not something wrong with the data. Standard deviation is simply a way to tell you that indeed, the population is quite variable. We have people in this group with one or two or five minutes of reported exposure, and people with ten and twelve hours because they were on the job that long and said "Yes, I was exposed the whole time."

This is not a surprise to me simply because all of our other analyses of our activity data have also had large standard deviations, and it took us a while -- we studied and studied the data -- as I said earlier, the actual responses from the respondents were recorded on the computer before any coding was done, and what we discovered is contrary to all of our views of human beings in our society.

We're actually quite different, we just don't all do things the same way everyone else does. We all have a lot of variability in our lives, so while it may seem disturbing at first, I can assure you we've looked at the data extensively, an, in fact, people are variable.

It's quite plausible Californians are a little more variable than others, but I'll talk about that more (inaudible) minute.

Slide 25, Figure 3A-2. This is from Table 3-A in my written testimony, the data for females. As you can see, they do have a lower proportion of the reported ETS exposure duration reported for work.

The males, as you recall, was 51 was percent; females 38 percent of their total exposure duration occurring at work.

The other indoor is large. I guess because I don't go to beauty parlors too often, I was surprised when we looked at where these women were going, they go all over, beauty parlors had some very extensive -- reported smoking -- just about every visit to the beauty shop, and in fact some of the barber shops showed exposure.

There were a variety of other places -- shopping malls and places that women go to run errands that had smoking occurring.

Slide 26, Figure 3A.3; this is from Table 3A in my written testimony. Again, the combined data here for males and females, showing that, overall, 46 percent of the reported ETC exposure duration occurs in the workplace.

Slide 27, Figure 3B.1., this is from Table 3B in my written testimony, data for the males.

These are average minutes of reported exposure duration and different microenvironments for male nonsmokers who worked outside the home. I'd like to put out a few things.

The top number is the actual number of minutes. For example, 3.13 is the average minutes reported for exposure duration in the workplace.

There is a mislabeling on this and my other bar graph slides, right here. Those bars labeled "anyplace" really are not what they appear to be. They really should be over here, separately, but I guess I didn't communication clearly with the fellow who made the slides for me.

That bar -- all the ones labeled "anyplace" actually show the average for the entire group on that slide, so here, for example, the 219 is the average minutes of reported ETS exposure duration for all male nonsmokers who worked outside the home.

Slide 28, Figure 3B.2 -- this is from Table 3B in my written testimony. It shows the data for the females. Again, the reported exposure duration in the workplace is longer than that by far, in the other microenvironments, at home, outdoor, and other indoor.

Again, the "anyplace" is the average for all the females in this group. I would note that we have not actually completed the test for significance of difference between the workplace, bars, and the other places. We will be doing that, of course, for our paper.

Slide 29, Figure 3B.3, from Table 3B, the men and women combined; again, this just shows the group as a whole. The average of 324 minutes of reported exposure duration in the workplace.

Now we get to Table 2, as I promised. This is Table 2, in the written testimony. It does show the cumulative distribution of the reported exposure duration at work. This is for nonsmokers, who worked outside the home, who reported exposure at work, meaning everyone who reported one minute or more of exposure, therefore, the zero values, those who did not report exposure to work are excluded from this table.

The means at the bottom you've already seen. I would put that when you compare it to the median value, which is the 50th percentile, you can see that, as you might expect, the 50th percentile, the median, is quite a bit lower than the arithmetic mean. This tells us that the distribution is skewed to the right, to the high levels.

We've actually tried to look at some of the distributions. They're very interesting. We haven't entirely characterized them yet. They tend to be fairly long and low. They're not very peaked. There's a word for that, and I forget what it is.

Table 4; this is from Table 4.C., in my written testimony, from the A columns. These figures replace the percent values in the Federal Register, Table 3-9.

This is going down to a smaller end, total of 164, looking at further nonsmokers who worked outside the home and reported ETS exposure, the percent of them that reported exposure to ETS in specific locations. You can see that a very small percent of this particular group reported exposure in the home.

The 100, of course, is because we selected for that group for this table.

Slide 32, Figure 4A.1, this is from Table 4A, data for the males, in their written testimony. Again, going back the proportion of reported ETS exposure duration, in specific environments, for male nonsmokers, who worked outside the home, for this group -- this subgroup -- 77 percent of their reported exposure duration occurred in the workplace.

Slide 33, Figure 4A.2; Table 4A data for the females. Again, this shows that 85 percent of the the proportion of their reported ETS exposure duration occurred in the workplace.

Slide 34, Figure 4A.3, showing the 2 groups combined, resulting in 80 percent of their proportion of reported ETS exposure duration occurring in the workplace.

Slide 35, Figure 4B.1., this is from Table 4B in the written testimony; the males. Again, you can see the high average minutes at work. As I mentioned, "the anyplace" should be moved separately. It's the overall mean for this group.

Slide 36, Figure 4B.2., data for the females, from Table 4B, in my written testimony.

Figure 4B.3, Slide 37; this is for the two combined, showing the average of 324 minutes per day, reported in the workplace.

As I said before, the numbers in parenthesis are standard deviations and show a great amount of variability in this population.

MS. JENKINS: I would like to comment in writing and verbally on what I've read or heard over the past year or two, particularly in the last recent weeks, regarding these estimates, what constitute overestimates, underestimates, or reasonable estimates.

As you can tell from my slide, I believe there are reasonable estimates of exposure duration, but I recognize that not all of you would agree with this.

First of all, they could be overestimates because of the way --

JUDGE VITTONE: Excuse me, Ms. Jenkins.

MS. JENKINS: Yes.

JUDGE VITTONE: You've been talking for approximately 45 minutes. Would like to give your throat a rest for a few minutes?

MS. JENKINS: I'm sorry? What was that?

JUDGE VITTONE: I said, would you like to take a small break?

MS. JENKINS: I'm fine.

JUDGE VITTONE: You're fine?

MS. JENKINS: I'm fine.

JUDGE VITTONE: Okay.

MS. JENKINS: I have a lot of wind.

It is possible...

JUDGE VITTONE: Go ahead, Ms. Jenkins.

MS. JENKINS: It is possible that these data represent overestimates because of the way the data were coded. As each individual reported their duration of work active, their time at work, and they were asked this question, if they represented yes to the ETS question, that yes went with the entire work activity location period.

As I mentioned earlier, if the reported period -- for example, if they just said, I went to work, and I was there for 8 hours, they were then probed, well, you must have moved around, and taken a break; did you go to lunch.

They were probed, and if they said, I went to lunch, that was coded separately.

But it's possible, since some of those individuals may not have remembered taking a break or they may have gotten up and just not reported it. It's possible that there is an overestimation because of that coding technique.
However, I would respond to that that, first of all, in the literature there are a number of studies that are shown that ETS is not immediately or fully removed by air circulation. It can be circulated to other spaces via the HVAC systems, components of ETS do adhere to carpets and materials. They can be remitted later.

Cigarette smoke can often -- the smoke odor can often be smelled quite some time after smokers have left the room.

Therefore, my view is that if there is any overestimation going on here, I think it would be very minimal, because even if smoking only occurred during part of that reported period, the components of the smoke would linger, the exposure would continue, albeit it at a reduced level.

We don't know the level, the concentration of the smoke in the air.

Because of those reasons, I'm not convinced that there is any overestimation going on.

I would also note that for underestimates, some people have actually approached me and said, I think you underestimate reported your exposure duration. That is possible, because it appears that we do have a slight undersampling of the lower socioeconomic groups who appear to at least be more involved in active smoking. Also some investigators have found that about five percent of non-smokers under-report their exposure to ETS. They do not seem to be aware that they've been exposed. This is based on cotanine levels and their body fluids. I'm talking here about Cummings et al, Coltis et al, Haley et al, and Jarvis et al.

In my view,I think these are reasonable estimates, in part because 24 hour recall diaries have been shown to be better than general recollection diaries, much more accurate. Also, there's no known bioseason to sample. There's no reason that they would have wanted to answer the ETS question anyway, but to their best ability, to their best knowledge.

There are also a number of other studies. I guess Klause et al, Benner et al, Lufraff, Langan, Hammond, and recent work by Ito and Baughman. Separate studies. The Baughman et al. These studies have all shown some sort of lingering of ETS components. Some of the comments that I made earlier with regard to HVAC systems, adherence to materials and so on. There is one that Wayne Ott mentioned today with Bill Nazaroff, which I had forgotten about. So in my view, these could be overestimates, they could be underestimates. In my view they're very reasonable because I feel very confident about the data that we do have. I readily acknowledge these are reported ETS duration numbers.

You may think I'm bold for stating that the California activity data are representative of the nation. This is Slide 39. However, I do think that they're reasonably representative for several reasons, and therefore, I do think it is reasonable for OSHA to use our data in their efforts to examine this issue on a national basis.

First of all, the California smoking rate, prevalence rate in 1977 and 1978 was 21.8 percent based on a California Department of Health Services survey which actually is from briefs; the behavioral related factor survey sponsored by the Centers for Disease Control. It's an annual survey that 44 states and the District of Columbia participate in. So their estimate was 21.8 percent. Our response and our dataset for people saying that they had actively smoked on their diary day was 22.5 percent. The national smoking rate for 1990, and this was just the latest number we could get. We're trying to get data for '92, '93 based on the brief study, as reported in the California Department of Health Services summary from CDC was 22.6 percent. So our smoking rate in '87, '88 was comparable to that of the nation in 1990.

This is not really news to anybody that follows this information. California has a slightly lower, probably now a little more than a slightly lower smoking rate in the state because of all of our various smoking ordinances and so on. But in my view, because there are similar smoking rates between our data then and what I think has gone on at the national level at least a few years ago, that the similarity of smoking rates is probably equal to a similar probability of being their ETS when other conditions are equal.

Slide 40. Another reason that I feel that our data are reasonably useful for estimating national exposures is that in 1991 John Robinson and Jacob Thomas, Thomas of ETA Las Vegas, extensively used the California national activity data and compared it to the 1985, excuse me. They used our California data and compared it to the 1985 national activity study data. Because the national data had not attained the same detail with regard to location of activity, and they wanted to determine if the activities were sufficiently comparable, then they felt that they could use our location codes and results to further refine national location results This is just a quote from their report.

"The strong comparability of the figures on average time for the activity data do indicate that the California data could be used to generate a better set of location codings for the national data. In fact they went on and did that, and those data are now available from UNLV.
It also means that the CARBdata on specific exposure, e.g., passive cigarette smoke, gasoline, and service station visitations collected in California may have national implications.

The one difference I would note that I noted in the report that could affect this finding or their view is that, for whatever reason, Californians worked an average of nine minutes more per day. We spent nine minutes more per day at work than did people surveyed in the national study. And I don't really know what the current rate of time spent in the workplace is. We, of course, just told them we work very hard in California, but...

Slide 41. Finally, our data have been so heavily utilized at this point that I think I can fully attest to the legitimacy of the data as collected. They're being heavily used by just about everybody in exposure modeling. This is actually a somewhat dated slide, but for example, EPA Las Vegas, and in North Carolina, ORD are using our data for benzene models in their national exposure model. They've done some ETS analyses with it. It was also a basic study design incorporated into the national study.

STI is Sonoma Technology Inc. in California. They've used our data extensively in exposure models they've developed, first for South Coast Air Quality Management District in LA and now for the San Francisco Bay area district. California Department of Health Services has used our data. American Petroleum Institute has used our data in their exposure work. They've had Ted Johnson and some of their other contractors using our data extensively.

Fortunately, we've gotten a lot of good feedback. There were a few issues in the very early days. It turned out there were a few diaries that were not complete and we took those out, so the ends that you see are the final ends. They're complete diaries.

Leaving the activity data, moving on to a few of our other studies. I'll try to do this very quickly.

Our agency has conducted some large residential studies, two of which involve measurement of residential levels of polycyclic aromatic hydrocarbons. What I really want to do is the datasets are so robust, I want to show them and then go on to show the link between our results and the results available from public building studies.

I wanted to note here in particular, I hear a lot of discussion about ventilation. I believe ventilation is absolutely necessary to a good indoor environment. However, I do so also believe that, particularly for carcinogens, you simply cannot ventilate enough to remove all of the possible air pollutants that may cause adverse affects.

I wanted to point out in particular for PAH's, benzo(a)pyrene and benzo(a)anthracine are classified as Group 2A, probably human carcinogens by IARC, that's the International Agency for Research on Cancer. And by U.S. EPA as group B2 carcinogens, possible human carcinogens. Benzoflouranthenes are classified by both as possible human carcinogens. pH's are known or suspected to have other adverse affects as well. They're mutagenic in bacteria, they can cause genetic changes in a variety of materials. They're possible contributors to heart disease. I would comment that nitro pHs are known to be especially potent.

For these compounds, IARC, EPA, all of the noted scientific groups I have studied and examined the literature, have not yet found any threshold of effects for these compounds. In other words, they have not found a level below which one can be exposed to these compounds and still be safe.

Just a quick comment on particulate matter, slide 43. This slide was made for outdoor particles, morbidity and mortality. Without getting into a deep discussion of PM-10 standards, they are believed to have fairly significant effects on the population. I would add that indoor respondable particles have also been found to cause, for example, allergic reactions when you're talking about molds or house dust. Many of them carry lead, asbestos, and pH's absorbed to them, and some of the bacteria and viruses, of course, can cause infections.

Slide 44, this was the first of our large studies involving pH measurements in homes, and actually tomorrow Dr. Wallace will be talking a little bit more about the particle team study from the perspective of the particle findings. I'm just going to mention some of the pH results.

Basically in this study and in the next study I'll talk about the Northern California pH study. All of the pH's studied were found at higher levels in smoking versus non-smoking homes.

P Team involved 178 homes, measured PM-10, 2.5 metals, and I don't have nicotine on this slide and I should. It was conducted in Riverside in the fall of '90.

For the pH study, pH measurements were made in 125 homes. This is slide 46.

We looked at levels of 13 different polycyclic aromatic hydrocarbons. The method used was XAD-2, that's the exorbant plus quartz fiber filters, so both phases, pH's are semi-volatile, so we collected both the gaseous phase and particle phase.

In this study they obtained two 12-hour samples. I'd just like to note that the QC results were very good. Recovery for the method and fill controls was all over 70 percent recovery. Most were in the range of 90 to 104 percent. The accuracy was very good, 87 to 89 percent recovery of the spike samples, duplicate, the precision was very good, 7 to 16 percent relative mean, mean relative standard deviation. And the method quantifiable limit which is actually a detection limit. Ranged from .08 to 1.1 nanograms per cubic meter, except for phenanthrene which was at 2.8 nanogram per cubic meter.

Slide 47, picking out benzo(a)pyrene because this is probably the most commonly discussed and studied compound. It was recently classified as a toxic air contaminant by the State of California.

This shows the mean levels found in smoking versus non-smoking homes. You can see it's clearly higher.

Just very quickly, to look at the actual numbers, and these are included in my written testimony as an attachment. This shows I think about nine of the 12 pHs measured in this study showed higher levels in smoking versus non-smoking homes. Where the difference is in those two groups of homes were statistically significant and they were all significant at at least P=.05 level.

The other three pHs were higher in the smoking homes, but the difference was not statistically significant.

Our Northern California home, slide 49, our Northern California pH study was also conducted by RTI. Very recently completed, in fact we're still polishing the final draft.

Slide 50. This study involved measurements in 280 homes in Placerville and Roseville, California, indoor and outdoor samples. Twenty-four hour averages. This was a wintertime study, because we wanted to stratify the sample by what we thought were the major indoor sources based on prior research.

Slide 51 just shows very quickly the source categories for this study. The total number of homes where smoking occurred during the monitoring period is 64, the sum of those two. The remainder of the homes were non-smoking and had different sources present, i.e., the fire place was used, or the wood stove was used or they had gas heat or other things going on.

I should comment in this study, California has some rules against kerosene heater advertising for residential use, so we only had five kerosene heaters. They do tend to be high but they didn't really show up here because we don't have enough to talk about.

In this study, again, the accuracy and precision was very good. The accuracy percent recovery was 84 to 121 percent; precision, 5.6 to 13 percent mean relative standard deviation. Median relative standard deviation was four to ten percent. The method quantifiable in that was .04 to 2.5 nannograms per cubic meter.

All of the compounds on this slide are significantly higher in the smoking homes versus the no-source homes at the .01 significance level. I'm not showing you all the data in the attachment. There are some columns missing in the middle. The fireplace, the wood burning homes fell in between the smoking homes and essentially the no-source homes.

Slide 53, continuing the list of pHs. All but coronene on this list were significantly higher in the smoking versus no-source homes at the .01 level.

Now I need to show my one overhead, and I guess we lost whoever was going to help...

JUDGE VITTONE: What do you need, Mrs. Jenkins?

MS. JENKINS: I need one overhead.

JUDGE VITTONE: Okay.

(Pause)

MS. JENKINS: This will be Slide 54. I simply wanted to go now from our residential measurements to pointing to some of the measurements, both for pHs and respirable particles, and even other pollutants that have been made in public and commercial buildings. This list comes from Repace and Lawry 1980; Lufraff et al 1989; Turk et al 1987. I believe these are all cited in my testimony.

You can see that measurements have been made in a good number of environments. This is just something that frankly, I didn't think of when I was first preparing my testimony, but I think it's very important to note, and I will show you, that there is certainly some comparability between residential data and public building data, so even though the public building data may be a more limited body of information than our residential data, I think there's certainly some very reasonable evidence that one can extrapolate from one to the other.

Slide 55. Talking now briefly about the Turk et al study. This was conducted by Lawrence Berkley Laboratories' indoor environment program in the Pacific Northwest, primarily in Oregon and Washington state. They studied 38 buildings, examined the pH levels in 16 buildings. The work was done in '84, '85, reported in '86, '87. They studied mostly government and education buildings, and these were not problems. These were simply representative buildings of different sizes and types. But the main reason they ended up in government buildings is that a lot of the private companies did not really want them in their building with their monitors, so it's much easier to get a government building to cooperate. So all but four buildings were some sort of government or educational facility such as college administration offices and so on.
They monitored for ten working days and they defined smoking areas as smoking occurring within 30 feet of their sample location.

Turk et all found, Slide 56, that when they summed up the total of the seven pHs that they actually measured and got good measurements for, that in the indoor smoking areas, they averaged 9.36 nannograms per cubic meter. In the indoor non-smoking areas the average was 2.4 nannograms per cubic meter. So the smoking areas showed levels about four times higher than the non-smoking indoor areas.

For the indoor/outdoor ratios, looking at the smoking areas versus the simultaneously measured outdoor levels 2.95 and for the non-smoking areas, 1.20. So essentially, smoking areas here averaged about three times the outdoor level, which tells you that the levels measured indoors are not just due to infiltration from higher outdoor levels.

For B(a)P which we were particularly interested in at the time, the levels measured in indoor smoking areas were 1.07 nannograms per cubic meter, and the indoor non-smoking is .39. I want to take you back right here to show you what we found. The numbers are very comparable. Here's B(a)p. 1.2, 1.3. They got 1.07 in the indoor smoking. For non-smoking we had .24 and .34, and they had .39.

The reason I want to bring this up is I do hear very often, and it is correct for many conditions to say that public buildings have higher air exchange rates than homes. But in this case, the buildings did not have particularly significantly higher air exchange rates than in our homes. I think part of that is because many of the buildings in the Western states have undertaken rather extensive energy conservation measures in about the last ten years. At this point I'm not sure there's as great difference between residential and public/commercial buildings in their air exchange rates as might be true for other parts of the country. But I think the fact that the major levels here are similar is very important, and I think it does allow us to utilize our residential data in some interpolated manner for public buildings.

One other finding from the Turk et al study, this is Slide 57. I want to point out that they also studied, actually they studied many pollutants in this study, but in addition to pHs they wanted to show their results for respirable particles. As you can see here, the mean concentration was about 69.6 micrograms per cubic meter in the smoking areas; it was 18.9 micrograms per cubic meter in the non-smoking areas and outdoors. In this case, the non-smoking areas and the outdoor levels showed the same RSP levels.

Slide 58. Our findings are that the workplace is a major site of exposure to ETS for non-smokers who work outside the home. Exposure duration is greater in the workplace than in other major environments. Some carcinogens, especially pHs, are consistently found at higher levels in places where smoking occurs.

This is my conclusion. Our findings indicate that restrictions on workplace smoking would significantly reduce exposures of non-smoking employees to ETS and its carcinogenic components.

Thank you.

JUDGE VITTONE: Thank you, Ms. Jenkins.

You are going to be able to provide a copy of all those slides for the reporter?

MS. JENKINS: Yes.

JUDGE VITTONE: Who would like to ask Ms. Jenkins questions?

(Pause)

JUDGE VITTONE: Can I have an indication of who has questions for Ms. Jenkins?

Ms. Ward and... I'm sorry, I've forgotten your name, sir. Anyone else? Mr. Rupp. Okay.

It is approximately five minutes after 6:00. I suggest that we recess for the day and begin tomorrow morning at 9:30 with any questioning for Ms. Jenkins.

Is that okay with you, Ms. Jenkins?

MS. JENKINS: Sure. I just have to leave around 3:00 o'clock tomorrow afternoon. So as long as it doesn't go until then.

JUDGE VITTONE: Let's get an estimate of how much questioning people may have tomorrow.

Can you give me an estimate, Ms. Ward?

MS. WARD: About an hour.

JUDGE VITTONE: Sir?

VOICE: Thirty minutes.

JUDGE VITTONE: Anybody else?

(Pause)

Thank you very much for today, and we will resume tomorrow morning at...

Anything else before we break?

MS. WARD: I almost hate to say this, but we have got a full day tomorrow, and we might start at 9:00.

JUDGE VITTONE: I don't have any problem with that. Does anybody else care?

MS. SHERMAN: I have asked Dr. Wallace to not testify tomorrow, and to testify on Friday instead.

JUDGE VITTONE: Does that change your evaluation any or what?

MS. WARD: Yes, it does.

JUDGE VITTONE: Let me just ask, you originally had Kathy Hammond, Lance Wallace and Bill Turner, so I guess you still have Kathy Hammond and Bill Turner.

MS. SHERMAN: That's correct.

JUDGE VITTONE: Off the record.

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