UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

 WASHINGTON D.C. 20460 

OFFICE OF THE ADMINISTRATOR 

SCIENCE ADVISORY BOARD 

May 19, 2010 

EPA-CASAC-10-012 

The Honorable Lisa P. Jackson 

Administrator 

U.S. Environmental Protection Agency 

1200 Pennsylvania Avenue, N.W. 

Washington, D.C. 20460 

Subject: Review of the Risk and Exposure Assessment for the Review of the Carbon 

Monoxide Primary National Ambient Air Quality Standards (NAAQS): Second 

External Review Draft 

Dear Administrator Jackson: 

The Clean Air Scientific Advisory Committee (CASAC or Committee) Carbon 

Monoxide (CO) NAAQS Review Panel met on March 22-23, 2010 to review EPA’s Risk and 

Exposure Assessment for the Review of the Carbon Monoxide Primary National Ambient Air 

Quality Standards (NAAQS): Second External Review Draft. The Chartered CASAC held a 

public teleconference on April 19, 2010, to review and approve the report. This letter provides 

CASAC’s overall comments and evaluation. We highlight the most important issues which need 

to be addressed as the second draft Risk and Exposure Assessment (REA) is finalized. 

The Panel expressed appreciation to EPA staff for the major improvements made in the 

second draft of the REA. The changes are responsive to the suggestions and concerns expressed 

by the Panel in its review of the first draft. Nonetheless, CASAC offers several suggestions and 

concerns to be considered as the second draft undergoes final revisions. 

The Panel encourages a clearer distinction between the levels set for the CO NAAQS and 

the concentrations at which exposures are currently experienced throughout the country. Current 

levels of CO are far lower than historic levels and the risk for health effects associated with these 

current levels may be minimal or difficult to quantify with certainty. However, the degree of 

protection afforded to susceptible populations by the current NAAQS still needs to be considered 

by EPA. A greater degree of protection may be warranted. 

As mentioned in its review of the first draft, the Panel felt strongly that the focus of the 

REA, and the associated Policy Assessment document, should be broader than cardiac ischemia 

(coronary artery disease or CAD). The Panel recognizes that compelling evidence comes from 

clinical studies demonstrating a relationship between elevated levels of carboxyhemoglobin 

1
(COHb) and a reduced time to the onset of angina. These studies have been at the center of the 

evidence used to set the NAAQS for CO. However, there is increasing evidence that CO 

increases the frequency and severity of congestive heart failure and enhances susceptibility to 

arrhythmias. Consequently, we recommend that a broad set of health outcomes be considered, 

beyond cardiac ischemia. The susceptible populations might also include those with pulmonary 

disease and the fetus. The Allred et al. (1989) study should be more completely presented. 

While a reduction in time to onset of angina is an important and easily interpretable clinical 

outcome, this response is subjective. In contrast, the outcome of ST segment depression, as 

assessed by a blinded cardiologist, is an objective measure of myocardial ischemia and should 

receive greater consideration. Moreover, ST segment depression has been validated, both as an 

outcome of inadequate delivery of oxygen to the myocardium and as a risk factor for more 

frequent arrhythmias. 

The Panel recommends greater clarity regarding the major contributors to COHb: 

ambient outdoor exposures, endogenous production of CO within the body, and finally indoor 

sources of CO from home cooking, heating, and passive smoking. The relative importance of 

these contributors to COHb must be more clearly delineated. The REA should address how 

these multiple sources are used in modeling and contribute to variability and uncertainty in 

model results. 

We are concerned about two aspects of the adequacy of the current CO monitoring 

network. First, more sensitive and precise monitors need to be deployed to measure levels that 

are less than or equal to 1 ppm. Such monitors are needed to validate CO exposure models. 

Second, the approach for siting monitors needs greater consideration. More extensive coverage 

may be warranted for areas where concentrations may be more elevated, such as near roadway 

locations. The Panel found that in some instances current networks underestimated carbon 

monoxide levels near roadways. Such underestimation is a critical issue since populations with 

low social economic status (SES) are often overrepresented in those areas. People with SES are 

more likely to smoke, a substantial source of CO. In addition, African Americans have a higher 

incidence of sickle cell disease, which affects oxygen transport. 

In regard to the quantitative risk assessment, the Panel recommends greater clarity in 

describing the model that was used, along with information available about its validity. The 

profile of COHb in time with varying CO exposures is complex since loading (increased COHb 

levels) is much more rapid than unloading of COHb levels as ambient CO levels drop. In an 

analysis that acknowledges multiple sources, it is essential to emphasize the increment which is 

attributable to ambient CO. 

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The CASAC and Panel membership are listed in Enclosure A. The Panel’s responses to 

EPA’s charge questions are presented in Enclosure B. Finally, Enclosure C is a compilation of 

individual panel member comments. We look forward to the Agency’s response and the 

successful completion of the CO NAAQS review. 

Sincerely, 

 /Signed/ /Signed/ 

Dr. Joseph D. Brain, Chair Dr. Jonathan M. Samet, Chair 

CASAC CO Review Panel Clean Air Scientific Advisory Committee 

 

Enclosures 

3
NOTICE 

This report has been written as part of the activities of the EPA’s Clean Air Scientific Advisory 

Committee (CASAC), a federal advisory committee independently chartered to provide extramural 

scientific information and advice to the Administrator and other officials of the EPA. CASAC 

provides balanced, expert assessment of scientific matters related to issues and problems facing the 

Agency. This report has not been reviewed for approval by the Agency and, hence, the contents of 

this report do not necessarily represent the views and policies of the EPA, nor of other agencies 

within the Executive Branch of the federal government. In addition, any mention of trade names of 

commercial products does not constitute a recommendation for use. CASAC reports are posted on 

the EPA website at http://www.epa.gov/CASAC.

4
Enclosure A 

Rosters of the CASAC CO Panel and CASAC 

U.S. Environmental Protection Agency 

Clean Air Scientific Advisory Committee 

Carbon Monoxide Review Panel 

CHAIR 

Dr. Joseph Brain, Cecil K. and Philip Drinker Professor of Environmental Physiology, 

Department of Environmental Health, Harvard School of Public Health, Harvard University, 

Boston, MA 

MEMBERS 

Dr. Paul Blanc, Professor and Chief, Department of Medicine, Endowed Chair, Occupational 

and Environmental Medicine, Division of Occupational and Environmental Medicine, University 

of California San Francisco, San Francisco, CA 

Dr. Thomas Dahms, Professor and Director, Anesthesiology Research, School of Medicine, St. 

Louis University, St. Louis, MO 

Dr. Russell R. Dickerson, Professor and Chair, Department of Meteorology, University of 

Maryland, College Park, MD 

Dr. Laurence Fechter, Senior Career Research Scientist, Department of Veterans Affairs, Loma 

Linda VA Medical Center, Loma Linda , CA 

Dr. H. Christopher Frey, Professor, Department of Civil, Construction and Environmental 

Engineering, College of Engineering, North Carolina State University, Raleigh, NC 

Dr. Milan Hazucha, Professor, Department of Medicine, Center for Environmental Medicine, 

Asthma and Lung Biology, University of North Carolina - Chapel Hill, Chapel Hill, NC 

Dr. Joel Kaufman, Director, Occupational and Environmental Medicine Program, University of 

Washington, Seattle, WA 

Dr. Michael T. Kleinman, Professor, Department of Medicine, Division of Occupational and 

Environmental Medicine, University of California, Irvine, Irvine, CA 

Dr. Francine Laden, Professor, Channing Laboratory, Harvard University, Boston, MA 

Dr. Arthur Penn, Professor LSU School of Veterinary Medicine, Department of Comparative 

Biomedical Sciences, Louisiana State University, Baton Rouge, LA 

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Dr. Beate Ritz, Professor, Epidemiology, School of Public Health, University of California at 

Los Angeles, Los Angeles, CA 

Dr. Paul Roberts, Executive Vice President, Sonoma Technology, Inc., Petaluma, CA 

Dr. Armistead (Ted) Russell, Professor, Department of Civil and Environmental Engineering, 

Georgia Institute of Technology, Atlanta, GA 

Dr. Anne Sweeney, Professor of Epidemiology, Department of Epidemiology and Biostatistics, 

School of Rural Public Health, Texas A&M Health Science Center, College Station, TX 

Dr. Stephen R. Thom, Professor, Institute for Environmental Medicine, University of 

Pennsylvania, Philadelphia, PA 

SCIENCE ADVISORY BOARD STAFF 

Ms. Kyndall Barry, Designated Federal Officer, 1200 Pennsylvania Avenue, NW, Washington, 

DC

6
U.S. Environmental Protection Agency 

Clean Air Scientific Advisory Committee 

CHAIR 

Dr. Jonathan M. Samet, Professor and Flora L. Thornton Chair, Department of Preventive 

Medicine, University of Southern California, Los Angeles, CA 

MEMBERS 

Dr. Joseph Brain, Cecil K. and Philip Drinker Professor of Environmental Physiology, 

Department of Environmental Health, Harvard School of Public Health, Harvard University, 

Boston, MA 

Dr. H. Christopher Frey, Professor, Department of Civil, Construction and Environmental 

Engineering, College of Engineering, North Carolina State University, Raleigh, NC 

Dr. Donna Kenski, Data Analysis Director, Lake Michigan Air Directors Consortium, 

Rosemont, IL 

Dr. Armistead (Ted) Russell, Professor, Department of Civil and Environmental Engineering, 

Georgia Institute of Technology, Atlanta, GA 

Dr. Helen Suh, Associate Professor, Department of Environmental Health, School of Public 

Health, Harvard University, Boston, MA 

Dr. Kathleen Weathers, Senior Scientist, Cary Institute of Ecosystem Studies, Millbrook, NY 

SCIENCE ADVISORY BOARD STAFF 

Dr. Holly Stallworth, Designated Federal Officer, Washington, DC 

7
Enclosure B 

CASAC’s Consensus Responses to EPA’s Charge Questions

1. Does the Panel find the summary of CO exposure and discussion of ambient CO sources, 

exposures, dose, health effects and risk characterization approach to be technically sound, 

clearly communicated, and appropriately characterized? 

In general, the Panel found Chapter 2 to be well organized, technically sound and a good 

conceptual overview of the REA. The chapter provides a sound rationale for the decision to use 

COHb level as the internal dose metric for assessing exposure to ambient levels of CO and for 

characterizing the potential for health risks in the population of persons with coronary artery 

disease (CAD). While some Panel members supported a cautious approach to using 

epidemiological data in the risk assessment, overall there were concerns that the current 

presentation under-emphasized the epidemiologic findings. Even if the epidemiological data are 

not used in the risk assessment, it is important to incorporate them into the discussion of risk. 

The epidemiological evidence provides information on non-hypoxia relevant mechanisms and 

chronic outcomes that cannot be addressed by relying on COHb levels alone. 

The Panel continued to be concerned with EPA’s designation of the at-risk population. The 

choice of modeling risk for the CAD population needs to be further justified and/or expanded to 

include other susceptible populations. Again, the findings of epidemiological studies suggest 

several groups to be considered, especially the broader category of cardiovascular disease 

(CVD). Since this chapter serves as the introduction to the REA, it should be edited as the 

Panel’s recommendations are incorporated into subsequent chapters. 

2. Does the Panel find the considerations of current ambient carbon monoxide monitoring 

data, including specifically the data for the monitors included in this draft of the assessment, 

and the discussion of the extent to which near roadway concentrations are represented to be 

technically sound, clearly communicated, and appropriately characterized? 

The discussion is technically sound, clearly communicated, and appropriately characterized. The 

treatment of the CO monitoring data, the description of the extent that these monitors represent 

near-roadway concentrations, and the data used in this iteration of the assessment are improved 

over the first external draft REA. The current monitoring network does not represent nearroadway concentrations very accurately, which is now well-documented in the REA. The 

increased discussion of NCore and measurement characteristics is useful and appropriately 

placed. 

Should there be additional monitoring for indoor and in-vehicle exposures? Representative 

monitoring to evaluate emissions inventories or models may be different from monitoring to 

assess exposure. 

3. In recognition of CASAC comments of first draft REA, this draft REA is expanded from the 

previous assessment in a number of ways (summarized in section 1.3 of the draft document). 

The assessment study areas are in the Denver and Los Angeles study areas. We are 

8
interested in eliciting the views of the Panel on the usefulness of this approach in informing 

our review the NAAQS for CO. What are the Panel members’ views on the following aspects 

in which the assessment has been expanded from the previous draft? 

a. An important change of this assessment from the first draft is the expansion of each of the 

modeling domains to include a greater number of ambient monitors used as input to 

APEX. Additionally, this draft assessment employs an algorithm that adjusts for temporal 

and spatial heterogeneity in ambient concentrations across each study areas. 

An important improvement in this assessment from the first draft is the expansion of each 

modeling domain to include a greater number of ambient monitors for input to APEX. 

Additionally, this draft assessment employs an algorithm that adjusts for temporal and spatial 

heterogeneity in ambient concentrations across each study area. While use of a larger number of 

ambient air monitors may have improved exposure assessment, we are not convinced that spatial 

heterogeneity driven by proximity to sources can be adequately captured by the current ambient 

monitoring network. In fact, exposures outdoor, in homes and in workplaces near roadways 

might be underestimated. 

It would be helpful to describe with greater clarity how data from overlapping districts, zones 

and areas were treated for input into the APEX model. What approach was used to avoid 

duplication of input data from overlapping zones? For Los Angeles, was one of the areas 

designated as a dominant source or was each area considered separately in the assessment? 

These are all questions that should be addressed in future analyses. 

In generating simulated individuals, demographic variables should include socioeconomic status 

(SES) and race if possible. These variables will impact other APEX modules, particularly 

COHb. If not, future data collection efforts should provide sufficient coverage. 

We find the tables of exposure values vs. estimated number and percentage of CHD persons 

affected at specific CO concentrations to be very instructive. Tables showing estimated COHb 

levels vs. number of people with CHD and persons/days are similarly instructive. Additional 

calculations and tabulation of endogenous COHb level using APEX and additional plots 

reflecting contribution of endogenous COHb to total COHb are illustrative. 

 

b. The current draft assessment also include an increase in the number of 

microenvironments modeled over that in the first draft (from two to eight) and improved 

the representation of variability in estimated microenvironmental concentrations, 

including in-vehicles. 

The Panel has no major issues with this approach. 

c. This draft assessment has implemented the mass-balance model for estimating 

concentrations in indoor microenvironments. 

We consider the selection of the mass-balance model for indoor air to be appropriate. 

9
4. Does the Panel view the results of the draft exposure analyses to be technically 

sound,clearly communicated, and appropriately characterized? 

The Panel questions EPA’s assumption that it has captured spatial heterogeneity in homes and 

workplaces near busy roadways. We agree with the summary of findings (p. A-5) that the 

current physiology file data is obsolete and may even be incorrect for some variables. While 

some variables were already updated, others such as race, SES, total hemoglobin (THb) and 

DLco should be either added or replaced in the input module. With these qualifications, the 

Panel answers affirmatively to question 4. 

5. Does the Panel find the derivation and presentation of the modeling approach as a whole 

(chapters 4 and 5) to be technically sound, clearly communicated, and appropriately 

characterized? 

The data added to the ambient source inputs for the exposure modeling reflect commendable 

responsiveness to the feedback we provided in the previous review of the initial REA draft. The 

modeling appears to be technically sound. 

The subject matter is complex and highly challenging to communicate clearly, particularly the 

material in Chapter 4. The presentation of this material seems to be aimed at the exposure 

modeling community, which makes it difficult for others to readily grasp. Nonetheless, the 

detailed description of the APEX model provides a helpful snapshot of the extensive nature of 

the model. The derivation and presentation of the modeling approach as a whole are well 

presented. Moreover, the application of the “CHAD” database in modeling the physiological 

changes of simulated residents during their daily lives appears to be appropriately handled. This 

approach has been applied and vetted for other regulated air pollutants. Nonetheless, the 

coupling of the non-linear CFK with the CHAD in the APEX model would be more convincing 

if this approach had been validated with actual field study measurements of delivered dose. We 

understand, however, that such validation is not possible on practical grounds. Moreover, 

previous approaches are less sophisticated from a modeling point of view and also lack field 

validation for the same reasons of feasibility. 

Appendix C contains some helpful illustrations of the variability in time spent for a given 

individual in locations/activities throughout the year. It might be helpful, additionally, to have 

similar illustrations of: 

1. Estimated %COHb levels for an individual during a day with exposures that were near 

current criteria (maximum allowable) levels of atmospheric CO, and 

2. An illustration of the potential variability in peak levels of %COHb throughout the year. 

Indeed, inclusion of such illustrative scenarios in the text, rather than in the Appendix, should be 

considered. This material could assist the reader in understanding the variability in the modeled 

levels of CO exposure. 

6. Does the Panel find the derivation and presentation of the COHb estimates (Chapters 5 

and 6) to be technically sound, clearly communicated, and appropriately characterized? 

10
The derivation and presentation of the %COHb estimates are clearly communicated and 

characterized. However, the final %COHb estimates, as presented in the REA, are potentially 

problematic. This is related, in part, to their derivation and the basic assumptions made in 

arriving at these values, not the computational operations of the APEX system. Modeling 

%COHb, as a biological marker of ambient CO exposure, presents particular challenges 

stemming from the various sources of exposure, each of which can potentially contribute to the 

final %COHb estimate. These sources include: endogenous production; ambient air pollution; 

and indoor air sources not accounted for by ambient pollution tracking indoors (e.g., combustion 

byproducts from home heating or cooking and secondhand smoking-associated CO). Extensive 

modeling in the REA appropriately deals with scenarios of ambient CO contributions to the 

indoor exposure environments. It was only well into Chapter 6 that modeling including “Internal 

Sources” of COHb was introduced. The Panel further takes issue with the confusing word 

choice since this does not mean internal in the sense of endogenous metabolism. As shown in 

Tables 6-15 and 6-16, excluding these indoor sources, modeled %COHb values (i.e., from 

ambient exposures levels) are similar between the 2000 model that also provides the indoor 

(“internal”) estimates and the current APEX model. Key is that inclusion of the indoor sources 

of exposure drives up exposure such that five percent of the population hits a 3% COHb level 

and roughly two percent of the population reaches a 4.0% COHb level. 

The Panel appreciated the additional attention given to endogenous CO production (again, not 

the “Internal” metric above). There was concern that this discussion could lead to confusion, 

because the modeled levels of endogenous %COHb are quite a bit lower than population means 

for non-smokers. This is because the actual data for the non-smoking population reflect the sum 

of ambient exposure, indoor exposure, and endogenous CO production. It might be useful to 

clarify these distinctions explicitly. Beyond issues of presentation, the modeled distribution of 

endogenous %COHb values seems too narrow. It appears to be based on “normal” healthy 

population estimates of endogenous production (albeit with a variety of activity levels). 

Literature demonstrating elevated endogenous %COHb values in certain subpopulations (for 

example, in persons with sickle cell disease) may be difficult to account for in these models, but 

an attempt to address them is warranted. At a minimum, the REA should directly acknowledge 

this limitation of the model estimates. 

Further confusion may be introduced through the random subset estimations, given that the 

central tendency (mean) of this random sub-sample seems to differ from the larger modeling 

estimate (apparently a chance observation). The narrower distribution is produced by the limited 

intra-person variation since most of the data points are derived from multiple runs on a relatively 

small subset – (this should not explain the shift in the mean). It may even be relevant to 

acknowledge that certain groups at risk for higher endogenous production systematically may be 

more likely to have higher ambient scenarios (e.g., persons with sickle cell disease, low SES, and 

those living/working near a major roadway). The lack of transparency in the endogenous 

production model as applied may also contribute to confusion. The description of what 

endogenous rates were used in the model is unclear and the information in Table B-3 on page B20 is poorly labeled. Despite these limitations, the material on endogenous production of CO 

and its contribution to the overall %COHb in combination with ambient levels of CO is very 

informative and indeed necessary. In summary, the Panel is concerned that there is no modeling 

11
of %COHb that covers indoor non- ambient sources and endogenous CO production, as well as 

ambient exposure. 

The staff’s presentation at the meeting included additional analyses of the contribution of 

ambient CO to the COHb% levels. The Panel found the analyses presented during the meeting 

represented an improvement of the discussions in the REA itself. Although the data were 

apparently computationally intensive to develop, some Panel members believe that the additional 

analyses could be an extremely useful avenue for further development of the standard. The 

specific increase in %COHb over the subjects’ pre-exposure or filtered air exposure was the 

focus of the influential Allred et al. papers and not on the magnitude of the final %COHb. It 

may well be that the ambient-attributable increment in %COHb is the most directly analogous 

dose for consideration in a risk assessment. Using incremental %COHb as the metric for 

ambient-attributable dose could simplify the risk assessment because the issue of “overlap” with 

the endogenous range of final COHb% (let alone indoor non ambient contributions) would be 

parsed-out. This treatment could still delineate the other sources of exposure as above-noted and 

would address the Panel’s concerns with regard to the continuity of the CO exposure-response in 

experimental studies. The presentation of incremental exposure data and estimated %COHb 

combined and separately would allow policy makers to consider ambient exposure alone, as well 

as in the context of other sources of exposure. 

7. In the Panel’s view, to what extent does the modified assessment approach employed in 

this second draft assessment provide results that meaningfully inform the EPA’s 

consideration of the public health implications of the current standards. 

The modified assessment approach has two key components: estimated exposure and estimated 

at-risk (susceptible) population. In terms of exposure, it should also be noted that the additional 

information included in the current modification does not relieve uncertainties from the use of a 

relatively limited data set (i.e., two case studies in Denver and Los Angeles), even with the 

additional monitoring data. The REA could be improved by showing the impact, or lack of 

impact, on dose variability that resulted from the inclusion of data from more monitoring sites. 

Data resolution from the two case studies and inclusion of data from more monitoring sites will 

be particularly relevant for national extrapolations. The Panel has provided additional 

suggestions to strengthen the exposure component in response to other charge questions. Such 

improvements could serve to better inform the EPA’s consideration of the public health 

implications of the current CO standard. 

There are serious potential data uncertainties in the estimates of the “at risk” population, many of 

which might lead to a systematic underestimation of the public health impact of CO exposure. 

The REA continues to rely singularly on the National Health Interview Survey (NHIS) data to 

provide a population estimate of persons at risk. The “at risk” population has been narrowly 

defined as self-reported coronary artery disease, which was the Panel’s primary point of 

contention and critique of the first draft REA. The revision now includes an estimate of 

“undiagnosed” disease that represents approximately 40% in addition to the base population. 

This is an important acknowledgment of one aspect of systematic underestimation, although the 

American Heart Association source of the mathematical value used is far from convincing. It is 

12
recommended that EPA incorporate a female>male differential to address the probable sex-based 

gap in CAD diagnosis. 

Data from NHANES and the Behavioral Risk Survey are easily accessible and will generally 

support the NHIS-based, restricted subset of susceptible persons based on a CAD definition. 

However, the narrowly-defined CAD prevalence estimate, to the exclusion of all others with 

cardiac disease, misinterprets the ISA (particularly Tables 4-9, 5-10, 5-11 and Figures 5-5 though 

5-7). Revisiting the NHIS, the prevalence rates for “all heart disease” are considerably greater 

than those of narrowly defined CAD. It is very likely that most, if not all, of these persons are at 

increased risk for adverse cardiovascular effects from ambient CO in ways that cannot be 

distinguished epidemiologically from the CAD subset. It is certainly appropriate for the REA to 

present estimates, as indeed it did, using a narrow CAD definition of “at risk” to inform an EPA 

public health assessment. However, this approach alone is not sufficient. Much effort is spent 

on multiple scenarios of exposure, while falling short in the critical area of defining alternate 

measures of the vulnerable population. As a consequence of the approach suggested above, a 

population more broadly defined with cardiovascular disease is likely to overlap to a meaningful 

extent with adults with chronic obstructive lung disease (through shared risk factors), which may 

be another at risk group for adverse CO exposure effects. This is not a determining factor, 

however, in the rationale for applying a more broadly-defined cardiac disease definition in 

modeling the at-risk population. 

8. What are the views of the Panel regarding the adequacy of the assessment of uncertainty 

and variability? To what extent have sources of uncertainty been identified and the 

implications for the risk characterization been characterized? To what extent has 

variability adequately described and represented? 

In general, the incorporation of more monitors in each area, more microenvironments, and 

variability in various variables within APEX better addresses variability and thus general 

uncertainty in exposure and dose. However, the use of the power 0.621 in equations 4-11 and 4-

22, reduces the CO concentration at an outdoor location, relative to the nearest central monitor, 

and thus possibly reduces the number of occurrences of the highest CO concentrations. 

In addition, all three contributors to COHb (ambient, endogenous production, and indoor 

sources, excluding smoking) should be considered in modeling and as contributing to variability 

and uncertainty in model results. 

13
Enclosure C 

Review Comments from the CASAC CO Panel on the Second Draft Risk and 

Exposure Assessment to Support the Review of the Carbon Monoxide Primary 

NAAQS

Comments received: 

Dr. Paul Blanc............................................................................................................................... 15 

Dr. Thomas Dahms ....................................................................................................................... 18 

Dr. Russell Dickerson ................................................................................................................... 21 

Dr. Milan Hazucha........................................................................................................................ 23 

Dr. Francine Laden ....................................................................................................................... 29 

Dr. Arthur Penn............................................................................................................................. 30 

Dr. Beate Ritz................................................................................................................................ 31 

Dr. Paul T. Roberts....................................................................................................................... 32 

Dr. Anne Sweeney ........................................................................................................................ 34 

Dr. Stephen Thom......................................................................................................................... 35 

14
Dr. Paul Blanc 

5. Does the Panel find the derivation and presentation of the modeling approach as a whole 

(Chapters 4 and 5) to be technically sound, clearly communicated, and appropriately 

characterized? 

Insofar as the increase inputs to the ambient source inputs to the models, this revision was quite 

responsive to the input that it received in review of its initial draft and is to be commended. This 

aspect of the approach appears to be technically sounds. This subject matter is complex and 

highly challenging to communicate clearly, in particular the material in Chapter 4. . 

6. Does the Panel find the derivation and presentation of the COHb estimates (Chapters 5 

and 6) to be technically sound, clearly communicated, and appropriately characterized? 

The final COHb estimates in 6 are problem-ridden. This is related in part to the derivation 

(including under this the basic assumptions made, not simply the mathematical operations of the 

APEX system). The presentation magnifies certain issues by potentially obscuring points 

presumed to be manifest but that may be to be more explicit. 

Modeling COHb, as a biological marker of ambient air pollution exposure, presents a particular 

challenge because there are 4 principal domains of exposure, each which can potentially 

contribute to the end concentration measured. These 4 domains are: endogenous production; 

ambient air pollution; active cigarette smoking; and supplemental sources of carbon monoxide 

beyond these three. This fourth domain, for most persons, is drive by indoor air exposure to CO 

from combustion byproducts from home heating or cooking and secondhand smoking-associated 

CO [although other sources of exposure within this domain may be important for population 

subsets, e.g., occupationally-related CO exposure]. 

Chapter 5, in relation to CO exposure modeling leading to COHb is focused entirely on the 

domain of ambient CO, although extensive modeling deals with scenarios of contributions of 

ambient CO to indoor exposure environments. This can be a bit confusing because internal 

combustion engine contributions to exposure in certain indoor scenarios are essentially point 

sources (service station and auto repair GM 2.97 [PPMs although not labeled]). Of note, another 

indoor facility group includes (Manufacturing facility) and is rather low – GM 0.089. One 

assumes fork lifts or truck deliveries not considered. The salient point however is: these 

scenarios exclude other likely concomitant sources of exposure. 

It is not until well into Chapter 6 that modeling that includes the domain of “Internal Sources” of 

COHb is introduced. The term Internal as used here is unfortunate, since it actually is intended to 

mean “indoor – not from ambient sources” i.e., what I refer to as the 4th domain above. If this 

also includes endogenous production it is by no means clear. As shown in Tables 6-15 and 6-16, 

excluding these indoor sources these estimated exposures levels are similar between a 2000 

model and the current APEX model – but inclusion of this critical source of exposure drives up 

exposure such that 5% of the population hits a 3% COHb level and roughly 2% a 4.0% COHb 

15
level. Remarkably there is no simulation or other estimation combining current indoor sources 

with the ambient estimates. 

Despite the short-shrift give the indoor exposure issue, a great deal of attention is then given to 

endogenous CO production. This, of course, is not “Internal” as used above, but rather refers to 

“normal” metabolic production of CO. This section is likely to lead to some confusion because, 

quite appropriately, the modeled levels of COHb% (population mean 0.255%) are quite a bit 

lower than population means for non-smokers. The reason of course if that observed nonsmoking population data reflect the sum of domains 1,2,and 4, no simply endogenous production 

(thus the baseline samples in the Allred study, etc). This is a point of blurred presentation, not 

modeling. The modeling itself, however, could benefit from more transparency. The reader is 

told that a certain number of studies informed the metabolic parameters as detailed in B but in 

fact it is hard to tease-out which references there are the ones in question. These seem to be fairly 

dated (Coburn’s work from the 1960s) and this may be the best there is. Nonetheless, more 

recent literature exploring moderately elevated COHb in certain conditions (for example, sickle 

cell disease) suggests that the model specifications and simulations yielding a maximum 

endogenous value of 1.54 is not likely to be reflective of population variability. This may be 

driven by simulating 59 individuals only, albeit with 8,760 hours of modeled observation. To 

capture endogenous variability, within person hour to hour activity inputs is not nearly as 

important as between person variability. Moreover, it is likely that certain at risk groups may be 

more likely to have ambient scenarios (and indoor scenarios) of higher exposure: eg. a low 

income resident of south-central LA dwelling near a freeway with sickle cell disease (and 

heating the home with a gas stove in the winter). 

Integrating the comments above, there is no apparent modeling of COHb that includes variable 

indoor not ambient sources (exclusive of direct cigarette smoking) + endogenous CO production 

(anticipation a possible bimodal distribution, with certain disease states contributing a sub-group 

of outliers) and ambient exposure. 

7. In the Panel’s view, to what extent does the modified assessment approach employed in 

this second draft assessment provide results that meaningfully inform the EPA’s 

consideration of the public health implications of the current standards. 

The modified assessment approach has two key components: estimated exposure and the 

estimated at risk (susceptible) population. All of the comments above (charge questions 5 and 6) 

relate to the exposure assessment. To the extent that the exposure issues raised above can be 

addressed, this would serve to better inform the EPA’s consideration of the public health 

implications of the current CO standard. Even as is, this portion of the Risk and Exposure 

Assessment is not fundamentally flawed. 

Insofar as the at risk population estimates are concerned, the document as currently constituted is 

prone to several sources of data uncertainties, all of which would tend to systematically 

underestimate the public health impact of exposure. The document continues to rely on National 

Health Interview Survey (NHIS) to provide a population estimate of persons at risk, narrowly 

defined as self reported coronary artery disease. This was a matter of focused critique of the first 

draft document. The revision now includes an estimate of “undiagnosed” disease (approximately 

16
40% in addition to the base population). Conceptually this is an important acknowledgment of 

the one aspect of systematic underestimation, although the American Heart Association source of 

the mathematical value used is far from convincing (and whatever value is used should 

incorporate a female>male differential given the clear sex-based gap in diagnosis. In addition, in 

terms of the restricted subset of susceptible persons based on CAD, supportive prevalence data 

based on NHANES and the Behavioral Risk Survey are easily accessible and will generally 

support the NHIS-based values. More fundamentally, the narrowly defined CAD prevalence 

estimate, to the exclusion of all others with cardiac disease misreads and misinterprets the ISA 

particularly Tables 4-9, 5-10, 5-11 and Figures 5-5 though 5-7. Revisiting the NHIS, the 

prevalence rates for “all heart disease” are considerably more than for narrowly defined CAD. It 

is very likely that most if not all of these are at risk as from adverse cardiac effects from ambient 

CO in ways that cannot be distinguished epidemiologically from the CAD subset (this includes 

in term of RR). It is certainly appropriate for the REA to present estimates, as it did, using a 

narrow definition of “at risk”; to inform an EPA public health assessment, this approach alone is 

unacceptable. It is ironic that so much effort is spent on multiple scenarios of exposure, while 

falling short in the critical area of the key vulnerable population. 

17
Dr. Thomas Dahms 

5. Does the Panel find the derivation and presentation of the modeling approach as a whole 

(Chapters 4 and 5) to be technically sound, clearly communicated, and appropriately 

characterized? 

The detailed description of the apex model provides a helpful snapshot of the extensive nature of 

the model. The application of the CHAD database in modeling the physiological changes of 

simulated residents during their daily lives seems to be appropriately handled. This approach has 

been applied and vetted for other regulated air pollutants. The presentation of the material seems 

to be aimed at the exposure modeling community which makes it difficult to assess for someone 

not in the modeling community. 

Appendix C contains some helpful illustrations of the variability in time spent for an individual 

in locations/activities during a year. It would be helpful to have a similar illustration of 

estimated %COHb levels of %COHb in an individual during a day with near criteria levels of 

atmospheric CO and also an illustration of the variability in peak levels of %COHb thoughout 

the year. Additions of these illustrations to the text rather than in the Appendix should be 

considered. It would assist the reader in understanding the variability in the modeled levels of 

dose of CO. 

The coupling of the non-linear CFK with the CHAD in the APEX model would be more 

convincing if there were references to validation of this model in studies where measurements of 

dose were made. Without documentation of such validation, the reader is expected to accept this 

model based on years of improvements over other models. 

Since the controlled human exposure data is a major factor in setting policy, it would be helpful 

to see how well the exposure model predicts the measured CO dose in these experiments. 

Although these exposures are for only 1 hour with subjects at rest, it would provide a means of 

validation of the exposure/dose modeling used for the general population. It might also provide a 

means of comparison of the various controlled human exposures. 

6. Does the Panel find the derivation and presentation of the COHb estimates (chapters 5 

and 6) to be technically sound, clearly communicated, and appropriately characterized? 

The presentation of how the model arrives at estimates of %COHb in the population of Denver 

and Los Angeles is clear in that it follows a natural progression in this field over the past 40 

years. It is clearly communicated and the improvements in the modeling over the years is clearly 

presented and is very rational. There are concerns with the output of the model that leads to a 

level of uncertainty that could be somewhat reduced as described below. 

The primary goal of this section would be to determine whether or not the estimated levels of 

%COHb (from the model) using the current as is data are lower or higher than those estimated 

levels of %COHb using the current standards. It is presumed that the exposure to the current 

standards for CO results in a small but acceptable number of at risk persons for a given %COHb 

18
benchmark. If the current as is data results in a smaller number of persons at that benchmark, 

there would be little pressure to change the standards. Therefore the issue that needs to be 

discussed/defined is : what is a small but acceptable number of persons who can be exposed at 

an acceptable benchmark. This discussion is absent. 

It is not clear what background in modeling minutia the reader is expected to have to clearly 

understand and analyze the details of the material presented. The crux of the matter is that for 

carbon monoxide there is an agreed upon dose metric, %COHb, that can be used to evaluate 

exposure. This is not quite the case for the other regulated pollutants. There is no mention of any 

attempt to validate the model being used under any circumstances. No matter how sophisticated 

the model, without validation it is just a model with all of the attendant uncertainties. 

The presentation of the information in section 6.4 on the influence of endogenous rates of CO 

production on dose estimates is potentially a problem. The description of what endogenous rates 

were used in the model is unclear and the information on Table B-3 on page B-20 is very poorly 

labeled. The values used in this portion of the model need to be clearly documented and justified. 

This becomes and issue because this modeling data is used to justify not including 1.0 %COHb 

in the Policy Assessment document. The modeling of all of the parameters that impact baseline 

%COHb into ‘endogenous rates of CO production’ as the primary determinate of baseline (no 

CO exposure) %COHb. This comes to light in Table 6-17 on page 6-18 which shows the APEX 

model to result in a median value of %COHB somewhere between 0.25 and 0.50% COHb and 

the non-parametric distribution of values is considerable. The modelers claim that this data can 

not be compared to any studies in the literature because of the time frame over which the data is 

modeled. Unfortunately there will always be skepticism of any model that can not be validated 

practically with actual measurements. The study by Allred et al observed 63 subjects in 3 cities 

on 4 experimental days (repeated measurements on an individual occurred within 6 weeks) and 

all of the subjects were observed over less than a 2 year period ( 270 measurements of baseline 

levels of %COHb). The mean %COHb levels did not vary over this period of time. These values 

ranged between 0.62 and 0.64 %COHb with a standard deviation of 0.16% COHb. The model 

results does not fit these results on the population most at risk in this assessment. 

The search for a alternative formats for setting standards maybe statistically enticing but would 

present too many problems for implementation of public health measures when the standards 

have been exceeded. News readers have a difficult time with the current standards provided in 

PPM so I can only imagine how they would attempt to explain any of the proposed alternative 

methods. 

There is also no attempt made to employ the model in the studies dealing with controlled 

exposures in subjects with CAD. I know that using APEX to model a 1 hour exposure to CO is 

akin to killing a slug with a sledge hammer, but what other data base is as relevant to validation 

of the model being so widely used? 

7. In the Panel’s view, to what extent does the modified assessment approach employed in 

this second draft assessment provide results that meaningfully inform EPA’s consideration of 

the public health implications of the current standards? 

19
The additional information included in the current modification does not relieve the anxiety from 

the use of so little monitoring data to provide guidance for setting standards. Perhaps it is in the 

way in which the information is presented: there is no data presented or referred to that shows 

that including more data adds nothing to the analysis. As a result of what has currently been 

presented, I am still uneasy with the use of so little of the available monitoring data for this risk 

assessment. Does the use of data from a few monitoring cites imply that we need fewer monitors 

in our cities because we can accurately predict what exists in the entire metro area based upon a 

few monitors? How is the reader to interpret the use of data from so few sites. To state the above 

concern in another way, the document could be improved by showing the impact, or lack of 

impact, on the dose variability by including data from more monitoring sites. This could be 

previously published information and need not involve re-running of the models with data from 

these additional sites. 

There is also mention of the lack of data resolution of the LA monitors vs the Denver monitors 

but the impact of the low resolution monitors in LA is not discussed. If it has no impact why was 

the issue raised? 

It is my impression that the estimates of risk due to exposure to CO are to apply to entire country 

and not just to Denver and Los Angeles. It is clear that the detail presented for these two cities 

can not be also presented for all of the major metropolitan areas of the country. However it is 

incumbent upon the authors to address how these risk assessments for Denver and LA are to be 

applied to the entire population of the United States. After all the document goes to great lengths 

to describe how many people are in the at risk group in the country and then applies some metric 

to determine how many of these individuals are in Denver and in LA. 

20
Dr. Russell Dickerson 

2. Does the Panel find the considerations of current ambient carbon monoxide monitoring 

data, including specifically the data for the monitors included in this draft of the assessment, 

and the discussion of the extent to which near roadway concentrations are represented to be 

technically sound, clearly communicated, and appropriately characterized? 

The revised draft is much improved, and generally meets expectations. EPA is faced with the 

situation that ambient measurements are more accurate than emissions. This makes 

measurement/model comparisons difficult. Although Chemical Transport Models (CTM’s) are 

not used in Chapter 3 or the REA, that chapter should point out that such tools should be used 

and continued evaluations and improvements (if necessary) in emissions are needed. 

The increased discussion of NCore and Analytical Sensitivity are useful and appropriately placed 

near the front. 

Key Observations (page 3-18 and 3-19) are appropriate, except I could not find much on the 

uncertainties in emissions (see also comments on ISA) and their impact on model output. 

Chapter 5 appears to reflect the state of knowledge. 

Preliminary Comments on the ISA (relevant to REA)

In one last reading of the ISA, Chapter 2 does a thorough job of providing an overview of our 

technical understanding of CO. 

A few comments: 

1. Page 2-3 might mention HCHF’s are removed by OH 

2. The caption to Figure 3-1 might include the word DIRECT so people don’t go looking for 

isoprene. 

3. Section 3.2.2 looks really good, as does Figure 3-8. This makes an important point that should 

appear in the PA. 

4. The sections on ambient measurements, detection limits and NCore are all much improved. 

5. Based on a quick read, Section 3.5 looks solid now. 

In poking around the literature I have found a few more papers that evaluate the emissions 

inventories of CO. Kuhns et al. (2004) and Yu et al. (2007; 2009) also found evidence of 

overestimates of CO emissions in Mobile6 or CMAQ. Marmur et al. (2009) in contrast seem to 

find that the CO emissions are underestimated. Zhang and Batterman (2010) find that Mobile 6 

matches plume dispersion models and a roadside monitor reasonably well. We are just about to 

submit a paper that evaluates Mobile6 CO emissions using about 100 altitude profiles and find 

that modeled emissions are high but not in gross error. If the paper is accepted soon enough I 

will send a preprint. 

21
Kuhns, H. D., et al. (2004), Remote sensing of PM, NO, CO and HC emission factors for onroad gasoline and diesel engine vehicles in Las Vegas, NV Science of the Total Environment, 

322, 123-137. 

Marmur, A., et al. (2009), Evaluation of model simulated atmospheric constituents with 

observations in the factor projected space: CMAQ simulations of SEARCH measurements, 

Atmospheric Environment, 43, 1839-1849. 

Yu, S.C., et al. (2007), A detailed evaluation of the Eta-CMAQ forecast model performance for 

O3, its related precursors, and meteorological parameters during the 2004 ICARTT study, 

Journal of Geophysical Research, 112, D12S14. 

Yu, S.C., et al. (2009), Eta-CMAQ air quality forecasts for O3 and related species using three 

different photochemical mechanisms (CB4, CB05, SAPRC-99): comparisons with 

measurements during the 2004 ICARTT study, Atmospheric Chemistry and Physics 

Discussions, 9, 22955-22992. 

Zhang, K., and S. Batterman, Near-road air pollutant concentrations of CO and PM2.5: A 

comparison of MOBILE6.2/CALINE4 and generalized additive models, Atmospheric 

Environment, doi:10.1016/j.atmosenv.2010.02.008, in press 2010. 

22
Dr. Milan Hazucha 

Background on assessing ambient CO exposure and risk (Chapter 2).

Charge Question 1: Does the Panel find the summary of CO exposure and discussion of 

ambient CO sources, exposures, dose, health effects and risk characterization approach to be 

technically sound, clearly communicated, and appropriately characterized? 

Qualified yes in all respects. 

In addition to already mentioned endogenous CO production and exogenous sources (p. 2-6, 

l. 11-13), additional source is metabolic production of CO due to inhalation of, e.g., 

dihalomethanes, other substances and certain medication. 

Do we really consider people using recreational drugs to be at-risk population and be 

considered in risk assessment (p. 2-8, l.19)? If so we will have to consider smokers to be atrisk population as well. 

Since Allred et al. studies provide the key evidence for CO health effects assessment it would 

be very helpful if the document, in addition to % changes of the critical endpoint, e.g., time 

to angina also reported the actual mean and CI (confidence interval) values in respective 

endpoint units (p.2-11, l.24-27 and p.2-12, l. 10-13). How clinically significant is shorter by 

22 seconds time to angina out of nearly 9 minutes? Besides reduced time to angina, was the 

duration and the intensity of angina affected as well? Did frequency of angina attacks 

increased because of CO exposure? If these endpoints were not reported by the investigators, 

it should be specifically stated so in REA. 

I support very cautious approach to some epidemiology studies reports of the effects of CO 

on respiratory system (p.2-10, 2-13, 2-18). I fully agree with EPA assessment that the 

interpretation of CO-induced lung-related outcomes “is affected by uncertainties including 

with regard to the biological mechanism that could explain CO-induced outcomes” (p. 2-13, 

l. 8-11). 

As far 1% COHb benchmark suggested by the Panel, the staff correctly pointed out that “this 

level overlaps with the upper part of the range of endogenous levels” and decided not to 

focus on dose estimates (p.2-16, l. 26-34). I support this approach since this complies with 

the EPA’s task “to establish standards that are neither more nor less stringent than necessary 

for these purposes”, .i.e. public health. 

23
Air Quality Considerations (Chapter 3 and 5)

Charge Question 2: Does the panel find the considerations of current ambient carbon 

monoxide monitoring data, including specifically the data for the monitors included in this draft 

of the assessment, and the discussion of the extent to which near roadway concentrations are 

represented to be technically sound, clearly communicated, and appropriately characterized? 

Yes in all respects. 

Characterization of Exposure, Dose and Potential Risk (Chapter 4-6)

Charge Question 3: In recognition of CASAC comments of first draft REA, this draft REA is 

expanded from the previous assessment in a number of ways (summarized in section 1.3 of the 

draft document). The assessment study areas are in the Denver and Los Angeles study areas. We 

are interested in eliciting the views of the Panel on the usefulness of this approach in informing 

our review the NAAQS for CO. What are the Panel members’ views on the following aspects in 

which the assessment has been expanded from the previous draft? 

The charge questions span across 3 chapters: Ch. 4 Overview of APEX modeling, Ch. 5 

Application of APEX, and Ch. 6 Simulated exposure and COHb dose results. 

However, it is difficult to comment on the chapters in general since the sub-questions are 

rather specific. 

A. An important change of this assessment from the first draft is the expansion of each of the 

modeling domains to include a greater number of ambient monitors used as input to 

APEX. Additionally, this draft assessment employs an algorithm that adjusts for temporal 

and spatial heterogeneity in ambient concentrations across each study areas. 

The bulleted list of modified/expanded sections is very helpful. Similarly, the flow 

chart showing input points and flow of data has been very helpful as well. 

How does the expansion of modeling domains in this REA compare to REA1? Were 

the estimates about the same or different and how they were different? 

Generally, larger number of monitors may improve exposure assessment. Figure 5.1 

(p.5-5) shows a considerable overlay of air districts, meteorological zones and for Los 

Angeles study areas as well. Although the overlapping districts, zones and areas were 

adjusted for as far as exposure goes, how were they treated in terms of input data into 

other modules of APEX? What approach was used to avoid duplication of input 

data? For L. A., was one of the areas designated as a dominant source or each area 

was considered separately in the assessment? 

In generation of simulated individuals, demographic variables should include socioeconomic status and race. These variables will impact other APEX modules, 

particularly the COHb one. 

Chapter 6: The tables tabulating exposure values vs estimated number and percentage 

of CHD persons affected at specific CO concentrations are very instructive and 

24
revelatory. Tables showing estimated COHb levels vs number of CHD persons and 

persons/days are similarly instructive. Generally, these table show that the current 

level of both standards is protective as required by the legislation, i.e., “standards that 

are neither more nor less stringent than necessary.” 

Additional calculations and tabulation of endogenous COHb level using APEX has 

been also very helpful. Table 6-18 (p.6-19) shows that the endogenous contribution to 

a total COHb is “less than 0.5%, though for a limited number of hours, the 

endogenous contribution could be over 1.0% COHb.” The additional plots reflect 

contribution of endogenous COHb to a total COHb level essentially following 

physiologic laws of Haldane. 

Section 6.5 Key Observations (p.6-24) summarizes the main observations presented 

in this chapter. One of the important conclusions is that more than 95% of simulated 

at-risk population of L.A. study areas will experience an annual daily maximum endof-hours COHb level below 1.5%. Moreover, when considering alternative standards 

“only 0.1% of the CHD population was estimated to experience a maximum end-of 

hour COHb at or above 2%. Similar values are provided for Denver. 

B. The current draft assessment also include an increase in the number of 

microenvironments modeled over that in the first draft (from two to eight) and improved 

the representation of variability in estimated microenvironmental concentrations, 

including in-vehicles. 

Chapter 4: Table 4-4 (p. 5-21) and 4-5 (p. 4-29) lists 15 microenvironments used in 

estimates in pNEM/CO model in 2000, and the same number and type in APEX4.3. 

However, the number for this draft is reduced to 8. Did this change in any way 

affected the estimates? 

It would have been helpful instead of making a general statement on how better 

APEX is, to actually list in 4.5 Key Observations section(p. 4-35) specific 

enhancements of APEX over pNEM/CO. 

The two important conclusions were that (1) the policy relevant background was 

negligible, and (2) the fixed site monitoring data could be adjusted. The tables 

provide sufficiently detailed data to evaluate all 5 scenarios. 

In the current draft the number of microenvironments was increased to 4 indoor, 3 

outdoor and 1 in-vehicle. Such expansion may improve strategies and enhance the 

validity as well as credibility of the assessment. More realistic scenarios provide 

stronger and more representative base for decision making. 

C. This draft assessment has implemented the mass-balance model for estimating 

concentrations in indoor microenvironments. 

I consider the selection of mass-balance model for indoor air appropriate. 

25
Charge Question 4. Does the Panel view the results of the draft exposure analyses to be 

technically sound, clearly communicated, and appropriately characterized? 

Qualified yes to all respects. 

The various modules of APEX model are regularly upgraded to improve the simulation 

process making it as realistic as possible. Yet the COHb module to estimate venous blood 

COHb level, the ultimate endpoint remains the same, i.e. based on CFKE (p.4-34, l.20-31). 

As already commented on this matter by several panel members including myself in the past 

why is EPA so adamant exploring more recent and more sophisticated CFK equations? 

Replacing original CFK with an enhanced, e.g. Bruce and Bruce module should be simple 

enough. If there are no substantial differences, then no change is necessary. However, if 

there are differences in COHb estimates, then we may search and evaluate the factors that 

may have affected the change. Such information may potentially useful in standard setting. 

Moreover, regardless of a mathematical model employed in COHb module, the COHb 

estimates can be improved by tuning some of the explicit input variables such as THb and 

DLco. 

Appendix A: I agree with the summary of findings (p. A-5) that the current physiology file 

data is obsolete and may even be incorrect for some variables. While some variables were 

already updated, others such as race, SES, THb and DLco should be either added to or 

replace the old data in the input module. 

Charge Question 5: Does the Panel find the derivation and presentation of the modeling 

approach as a whole (chapters 4 and 5) to be technically sound, clearly communicated, and 

appropriately characterized? 

Yes in all respects. The staff did an excellent job of presenting and discussing APEX model. 

I agree with well reasoned arguments and the conclusions. 

Any concerns about the effect of missing concentration values on their distribution were 

cleared by addition of descriptive statistics tables (5-7 through 5-10). The tables demonstrate 

that the missing values whether estimated and corrected for or not do not influence the 

distribution of hourly values either in Denver or Los Angeles. Similar approach to estimation 

of missing temperature values required by APEX likely resulted, as stated in the document, 

in negligible differences. 

Charge Question 6: Does the Panel find the derivation and presentation of the COHb estimates 

(chapters 5 and 6) to be technically sound, clearly communicated, and appropriately 

characterized? 

Qualified YES in all respects. 

Section 6.3.1 referenced in the document is likely section 6.4.1. 

26
The section 6.4 on endogenous production of CO and its contribution to overall COHb in 

combination with ambient levels of CO is very informative. Table 6-17 clearly shows that 

even at 0 ppm CO in ambient air several hundred individuals will reach COHb level as high 

as 1.8%. It would be instructive to identify groups of individuals (e.g. with anemia) who 

exceeded 1% COHb level due to endogenous production. 

Figure 6-2 shows, as expected, that endogenous CO will not influence COHB level if the 

ambient CO concentration exceed the one produced endogenously (this needs to be stated 

more clearly on p. 6-21, l. 6-8). Figure 6-4 indeed confirms the above statement. 

Appendix B. COHB module: 

p. B-3: The PIco , should be defined as a partial pressure. 

p. B-5 In eq. B-11 and B-14 Pco2 subscript should be correct to read not as CO2 (carbon 

dioxide) but as cO2 (capillary O2). 

Suggest to move the second paragraph on page B-8 as the first paragraph of the section, 

otherwise without the explanation, the statement is misleading. 

p. B-9- B-14. Section C4: The COHb module seems to be the weakest of the APEX modules. 

Primarily, it is because we do not have sufficient data over the physiologic range for many 

variables. However, though still limited some physiologic data are available for healthy and 

at-risk groups and they should be integrated into data base for COHb module. From the 

tables nor the text it does not look like that many critical variables such as Hb, DLco, 

endogenous CO and others were, besides age and gender, adjusted for other physical 

characteristics or disease conditions. For example, the amount of Hb will determine the rate 

of COHb formation and is a critical variable. There are substantial differences between blood 

concentration of Hb in whites and blacks. 

Charge Question 7: In the Panel’s view, to what extent does the modified assessment approach 

employed in this second draft assessment provide results that meaningfully inform EPA’s 

consideration of the public health implications of the current standard? 

I agree with the expanded approach and I believe that it will allow for more accurate 

assessment and risk-characterization. 

Characterization of Variability and Uncertainty (Chapter 7)

Charge Question 8: What are the views of the Panel regarding the adequacy of the assessment 

of uncertainty and variability? To what extent have sources of uncertainty been identified and the 

implications for risk characterization been characterized? To what extent has variability 

adequately described and represented? 

The staff adequately described uncertainty and variability. However, from table 7-1 it appears 

that CHD has been considered to be the only sources of variability and no other disease 

27
conditions were considered in the model. Why no other relevant diseases were considered? Was 

socio-economic status in any way considered in estimating uncertainty? 

Does APEX model has build in any internal consistency check between factors used in the 

calculations (p. 7-2)? For example, randomly selected oxygen uptake which may be high maybe 

assigned to an individual with CHD who is unable to achieve such uptake level. 

Activity patterns of persons 30 years ago used as APEX input are very much different for current 

activity patterns (p. 7-8). Can CHAD data be limited only to more recent activity patterns?? 

28
Dr. Francine Laden 

1. Does the Panel find the summary of CO exposure and discussion of ambient CO sources, 

exposures, dose, health effects and risk characterization approach to be technically sound, 

clearly communicated, and appropriately characterized? 

Chapter 2, background on assessing ambient CO exposure and risk, is well organized and 

technically sound. EPA appropriately characterized what they did do, as well as what they did 

not do. The discussion explaining the uncertainties associated with directly using studies of the 

association of cardiovascular morbidity with measurements of ambient CO is important for 

motivating the focus on COHb levels. It may not be immediately obvious to all readers why 

ambient CO exposures are not the exposure of interest. One concern is that most of the 

monitoring data and the laboratory data crucial to the assessment is quite old and could thus 

effect the determination of risk. Is EPA confident that current situations can be extrapolated 

appropriately from what was observed in the past? Perhaps some statement to this uncertainty 

would be valuable, as well as acknowledgement that there are not any appropriate-more recent 

studies available. For the most part the chapter is clearly communicated. However, the chapter 

overall would benefit from some careful editing. 

5. Does the Panel find the derivation and presentation of the modeling approach as a whole 

(chapters 4 and 5) to be technically sound, clearly communicated, and appropriately 

characterized? 

The derivation and presentation of the modeling approach as a whole is very well presented. I 

had one trivial question: Could the prevalence of undiagnosed CHD be greater for women than 

for men? The model assumes that the ratios of undiagnosed cases to diagnosed cases are 

identical for each gender and also that this ratio has not changed since 1990. The text should at 

least acknowledge that this might not be so. 

6. Does the Panel find the derivation and presentation of the COHb estimates (chapters 5 

and 6) to be technically sound, clearly communicated, and appropriately characterized? 

The derivation and presentation of the COHb estimates are technically sound, clearly 

communicated and appropriately characterized. 

7. In the Panel’s view, to what extent does the modified assessment approach employed in 

this second draft assessment provide results that meaningfully inform EPA’s consideration of 

the public health implications of the current standards? 

The draft assessment provides results that meaningfully inform EPA’s consideration of the 

public health implications of the current standards. Given that CO levels have decreased 

significantly over the years, that levels rarely approach the standards, and that elevated levels of 

COHb estimated by the risk assessment are quite low, the usefulness of the current standards 

may need to be reassessed. 

29
Dr. Arthur Penn 

1. Does the Panel find the summary of CO exposure and discussion of ambient CO sources, 

exposures, dose, health effects and risk characterization approach to be technically sound, 

clearly communicated, and appropriately characterized?

No major issues with this chapter. The summaries are well-done and the health effects and risk 

characterization approach are presented clearly and seem technically sound. 

30
Dr. Beate Ritz 

3. What are the Panel members’ views on the following aspects in which the assessment has 

been expanded from the previous draft? 

A. An important change of this assessment from the first draft is the expansion of each of the 

modeling domains to include a greater number of ambient monitors used as input to APEX. 

Additionally, this draft assessment employs an algorithm that adjusts for temporal and 

spatial heterogeneity in ambient concentrations across each study area. 

While the larger number of ambient air monitors may have improved exposure assessment, I am 

not convinced that this in fact gives more correct estimates of exposure near roadways - mainly 

in homes since only one singular distribution was used for all homes and this distribution may 

not adequately reflect near roadways exposures in homes i.e. I am not convinced that spatial 

heterogeneity driven by proximity to sources can be adequately captured by the ambient 

monitoring network. In fact, the exposure both in homes and in work places closer to roadways 

might be underestimated. 

B. The current draft assessment also includes an increase in the number of 

microenvironments modeled over that in the first draft (from two to eight) and improved the 

representation of variability in estimated microenvironmental concentrations, including invehicles. 

yes 

C. This draft assessment has implemented the mass-balance model for estimating 

concentrations in indoor microenvironments. 

yes 

4. Does the Panel view the results of the draft exposure analyses to be technically 

sound,clearly communicated, and appropriately characterized? 

Yes, except for the assumption about having captured spatial heterogeneity in homes and work 

places near busy roadways. 

31
Dr. Paul T. Roberts 

2. Does the Panel find the considerations of current ambient carbon monoxide monitoring 

data, including specifically the data for the monitors included in this draft of the 

assessment, and the discussion of the extent to which near roadway concentrations are 

represented to be technically sound, clearly communicated, and appropriately 

characterized? 

In general, the treatment of the CO monitoring data and the (admittedly poor) extent that these monitors 

represent near-roadway concentrations, including the data used for this version of the assessment, are 

improved over the 1st external draft REA, technically sound, clearly communicated, and appropriately 

characterized. In addition, the use of data from more monitors as input to the exposure modeling is a 

significant improvement. 

Characterization of Exposure (Chapters 4 and 5)

The following changes from the 1st external draft REA are significant improvements and help the results 

from this REA do a much better job of informing our review of the CO NAAQS. 

• Expansion of the modeling domain to include more monitors in both Denver and LA. 

• Adjusting for both spatial and temporal heterogeneity in ambient CO concentrations in each 

study area. 

• A significant increase in the modeled microenvironments. 

• The use of a mass-balance model for estimating CO concentrations in indoor environments 

(factors are reasonable estimates for the other microenvironments). 

However, I am concerned about the use of the power of .621 in equations 4-11 and 4-22, which 

reduces the CO concentration at an outdoor location, relative to the nearest central monitor. The 

main justification for this is given on lines 33 to 35 of page 4-27 as a way to get the pNEM/CO 

and APEX models to agree, but I do not understand the physical rationale for this. On page 5-

23, lines 8-10, it is suggested that the resulting “compression effect” is consistent with Wilson et 

al (1995). However, even if we agree that this might be occurring near most residences, as in the 

Wilson study, it does not occur at near-roadway or in-vehicle locations. In fact, the net result of 

using this as part of the factor calculation for estimated CO concentrations is that near-roadway 

and in-vehicle concentrations are a fair amount lower than was documented in the 1st REA, 

section 5.4.2 (in-vehicle concentrations) and in the ISA for near-roadway. Since these two 

microenvironments might be contributing a fair amount to total exposure, I think this is an 

important issue to resolve. In addition, the use of this factor for near-road and in-vehicle 

microenvironments has probably decreased the percent of people who experience the highest 

concentration exposures, for example in Chapter 6. 

Table 5-16 is a good summary of the various conditions in the 8 microenvironments, especially 

with the distributions. I did noticed, however, in Appendix that a couple of locations codes are 

probably mis-assigned, although these are probably small contributions: bicycle should be 5, as 

shown in Table 5-16, and all the boat categories should be 8, since boats are uncontrolled for CO 

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and produce significantly high CO concentrations (they should probably be much higher than 8, 

but again this is probably a small contributor). 

8. What are the views of the Panel regarding the adequacy of the assessment of uncertainty 

and variability? To what extent have sources of uncertainty been identified and the 

implications for the risk characterization been characterized? To what extent has 

variability adequately described and represented? 

In general, the incorporation of more monitors in each area, more microenvironments, and 

variability in various variables within APEX is an important method for addressing variability 

and thus general uncertainty in exposure and dose. 

Although I still think that the most significant uncertainties from this table could be better 

quantified by using sensitivity runs of the model, I understand the time constraints on the current 

NAAQS process. I believe that the significant improvements in representing near-roadway and 

in-vehicle exposures has reduced the uncertainties associated with that end of the exposued 

population, as represented in Table 7-2. 

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Dr. Anne Sweeney 

1. Does the Panel find the summary of CO exposure and discussion of ambient CO sources, 

exposures, dose, health effects and risk characterization approach to be technically sound, 

clearly communicated, and appropriately characterized? 

Overall, Chapter 2 is a very well-written comprehensive background that describes the issues and 

considerations that were confronted in the effort to assess ambient air CO exposure and human 

health risks. The contributions of the various sources of both ambient and indoor CO levels were 

clearly described and supported by numerous published studies. Exposure pathways and the 

importance of the microenvironment were also well-documented. 

The justification for the utilization of persons with CHD as the unit of analysis in the quantitative 

assessment is appropriate, given the lack of data on COHb levels in other potentially high risk 

groups. However, characteristics of this simulated population that should be included in the 

modeling include the population prevalence of income level (a surrogate for several important 

covariates, e.g., residence near congested traffic areas) and smoking (also related to income 

level). 

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Dr. Stephen Thom 

1. Does the Panel find the summary of CO exposure and discussion of ambient CO sources, 

exposures, dose, health effects and risk characterization approach to be technically sound, 

clearly communicated, and appropriately characterized? 

The summary is accurate and appropriate. 

2. Does the Panel find the considerations of current ambient carbon monoxide monitoring 

data, including specifically the data for the monitors included in this draft of the assessment, 

and the discussion of the extent to which near roadway concentrations are represented to be 

technically sound, clearly communicated, and appropriately characterized? 

The discussion on current air quality monitoring is accurate and appropriate. 

3. In recognition of CASAC comments on first draft REA, this draft REA is expanded from 

the previous assessment in a number of ways (summarized in section 1.3 of the draft 

document). The assessment study areas are in the Denver and Los Angeles study areas. 

We are interested in eliciting the views of the Panel on the usefulness of this approach in 

informing our review the NAAQS for CO. What are the Panel members’ views on the 

following aspects in which the assessment has been expanded from the previous draft? 

A. An important change of this assessment from the first draft is the expansion of each 

of the modeling domains to include a greater number of ambient monitors used as 

input to APEX. Additionally, this draft assessment employs an algorithm that adjusts 

for temporal and spatial heterogeneity in ambient concentrations across each study 

area. 

B. The current draft assessment also includes an increase in the number of 

microenvironments modeled over that in the first draft (from two to eight) and 

improved the representation of variability in estimated microenvironmental 

concentrations, including in-vehicles. 

C. This draft assessment has implemented the mass-balance model for estimating 

concentrations in indoor microenvironments. 

I found the document to be generally well written. My one question pertains to the APEX 

modeling, as raised in my review of the Policy Assessment document. The discussion in the 

REA document includes information that most fixed monitors have a 1 ppm CO lower detectable 

limit so the modelers added 0.5 ppm CO to all measured values to remove zeros and negative 

numbers thought to be related to monitor drift. It seems to me that this makes it exceedingly 

difficult to accept estimates of the at-risk population and threshold COHb levels. 

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4. Does the Panel view the results of the draft exposure analyses to be technically sound, 

clearly communicated, and appropriately characterized? 

I am unsure if the draft exposure analysis is technically sound (see comment #3).