UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

WASHINGTON D.C. 20460

OFFICE OF THE ADMINISTRATOR
SCIENCE ADVISORY BOARD February 12, 2010

EPA-CASAC-10-006

The Honorable Lisa P. Jackson

Administrator U.S. Environmental Protection Agency 1200 Pennsylvania Avenue, N.W. Washington, D.C. 20460

Subject: Review of Risk and Exposure Assessment to Support the Review of the Carbon Monoxide (CO) Primary National Ambient Air Quality Standards: First External Review Draft

Dear Administrator Jackson:

The Clean Air Scientific Advisory Comm ittee (CASAC) Carbon Monoxide (CO) Review Panel met on November 16-17, 2009 to review the Risk and Exposure Assessment (REA) to Support the Review of the Carbon Monoxide (C O) Primary National Ambient Air Quality Standards: First External Review Draft (October 2009). The Panel’s report was reviewed and approved by the chartered CASAC on a Decembe r 22, 2009 public teleconfer ence. This letter begins with CASAC’s overall co mments and evaluation. We highlig ht the most important issues

which need to be addressed as the first draft is revised. The Panel and CASAC membership is listed in Enclosure A. The Panel’s responses to EPA’s charge questions are presented in Enclosure B. Finally, Enclosure C is a co mpilation of comments from individual panel

members.

The Panel recognizes the time constraints under which this first draft REA was prepared. However, we found the document will need further development and refinement based on the strength of scientific evidence presented in the CO ISA, which was finalized January 2010.

Fundamental concerns with the current CO monito ring strategy and the limited amount of data at

realistic CO concentrations further constrain the an alyses that can be carried out in the REA. We

view this first draft REA as a reasonable exerci se in risk characteriza tion, but look forward to more fully-developed assessments and analyses in the second draft. Our major comments and suggestions to strengthen the document follow.

• We concur with the document’s conclusion that the available CO data is a limitation of the REA. However, CASAC finds that a mo re robust risk and exposure assessment could have been produced with bette r utilization of the existing da ta and modeling tools. Theexisting monitoring network is limited and mo st monitors do not have the sensitivity

needed to describe current ambient CO con centrations. These challenges are accentuated by decades of success in reducing ambient CO emissions and concentrations. The limited accuracy of measurements at lower concentrations has re ndered many of the current CO monitors obsolete. Moreover, in order to obtain adequate temporal and spatial information, a more extensive monitoring network is needed. These deficiencies reduce

our confidence in the nume rically simulated CO concentrations in the REA.

• The Agency needs to be more transparent in its selection of the urban centers for case studies and in its specification of exposure parameters for modeling, as well in addressing the implications of these choices. Nonethel ess, CASAC supports the aspects of the modeling that incorporate a public health pr otective strategy, such as modeling that

attempts to capture wors t-case exposure scenarios.

• EPA should improve the analysis of CO concen trations to better capture spatial- and temporal-variability and the ratio of in-v ehicle to ambient-air concentrations. Uncertainty in the model predictions of CO le vels translates into uncertainty in COHb estimates, further limiting the REA’s utilit y. The next draft REA should include a prioritization of the key sources of variability and discussion s of the degree of confidence with which they are characterized, as well as additional ambient concentration scenarios.

• EPA has selected adults with coronary arte ry disease (CAD) who experience myocardial ischemia to represent sensitive subpopulations in the REA. EPA should expand its consideration of susceptible populations to incl ude others who are at elevated risk of COinduced adverse effects. CASAC finds the br oader definition of cardiovascular disease (CVD) that includes populations with periphera l cardiovascular disease or stroke to be a more appropriate representation of suscep tible population. Other at-risk groups should also be accounted for in the REA, such as , pregnant women, fetuses, and people with anemias and sickle cell anemia, specifically.

• CASAC strongly recommends inclusion of a fi nal summary chapter in the next draft

REA.

• We are concerned with the last line in Chapter 6, “staff finds the utility of this assessment for the purpose of considering the adequacy of the current standards to be limited.”

Deficiencies in the current REA demonstrate th e critical need forr e nhanced utilization of the available data, models and approaches to improve the next draft REA. Strengthening the current assessment can only further improve future CO reviews, which we anticipate

will have better emissions data and air quality and exposure models.

2CASAC repeats its expectation that the revise d REA will be returned with a commentary pointing to key changes. This will enhance the efficiency of our subsequent review and will provide a transparent public record of the evolution of the document.

Sincerely,

/Signed/ /Signed/

Dr. Joseph D. Brain, Chair Dr. Jonathan M. Samet, Chair CASAC CO Review Panel Clean Air Scientific Advisory

Committee

Enclosures

3Enclosure 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 Pr ofessor of Environmental Physiology, Department of Environmental Health, Harvard School of Public Healt h, Harvard University, Boston, MA

MEMBERS

Dr. Paul Blanc , Professor and Chief, Department of Medicine, Endowed Chair, Occupational and Environmental Medicine, Division of Occupa tional and Environmental Medicine, University of California San Francisco, San Francisco, CA

Dr. Thomas Dahms , Professor and Director, Anesthesiol ogy 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 Civ il, Construction and Environmental Engineering, College of Engineering, No rth 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 Hi ll, Chapel Hill, NC

Dr. Joel Kaufman , Director, Occupational and Environmen tal 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 St ate University, Baton Rouge, LA

4Dr. Beate Ritz , Professor, Epidemiology, School of Public Health, University of California at Los Angeles, Los Angeles, CA

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

Dr. Armistead (Ted) Russell , Professor, Department of Civ il 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 H ealth 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 Pe nnsylvania Avenue, NW, Washington,

DC

5

### 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 Pr ofessor of Environmental Physiology, Department of Environmental Health, Harvard School of Public Healt h, Harvard University, Boston, MA

Dr. H. Christopher Frey , Professor, Department of Civ il, Construction and Environmental Engineering, College of Engineering, No rth Carolina State University, Raleigh, NC

Dr. Donna Kenski , Data Analysis Director, Lake Mi chigan Air Directors Consortium,
Rosemont, IL

Dr. Armistead (Ted) Russell , Professor, Department of Civ il 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 Institut e of Ecosystem Studies, Millbrook, NY

SCIENCE ADVISORY BOARD STAFF Dr. Holly Stallworth , Designated Federal Officer, Washington, DC

*Dr. Weathers did not participate in CASA C’s December 22, 2009 call to approve the draft

report.

6NOTICE

This report has been written as part of the activ ities 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.

7Enclosure B

CASAC’s Consensus Responses to EPA’s Charge Questions

Air Quality Considerations (Chapter 3)

1. Does the Panel find the considerations of current ambient carbon monoxide monitoring data and the discussion of the extent to which ne ar roadway concentrations are represented to be technically sound, clearly communica ted, and appropriately characterized?

The Panel found the discussions in Chapter 3 to be satisfactory. The REA makes it clear that many current monitors lack the sensitivity to provide accurate measurements of ambient concentrations (although page 3-3, line 8 should be “below 1 ppm” not “near 1 ppm”). Accurate measurements would be useful for estimating expo sure at high concentrations and showing longterm trends. The difficulties in estimating actual exposure from point monitors’ data that have been usually set up to demonstrate complia nce with the NAASQ are clearly and thoroughly presented. The added discussion of the NCore multi-pollutant monitoring network strengthens the document. The actual concentrations to which people are exposed will have to be estimated

with a combination of measuremen ts and models. There is one point made explicitly in the ISA but not in the REA: some published compar isons of emissions inventories and ambient measurements reveal substantial disagreements, potentially leading to major uncertainties in numerically simulated CO concentrations. Th e chapter needs a final statement regarding

uncertainties in emissions and/or measurements. The Panel notes that the quality and quantity of CO monitors must be improved in order to re duce uncertainties in e xposure, emissions, and

distributions in the future.

Although the REA discusses the monitoring network, there is an unresolved issue related to the

combined use of models and measurements to esti mate exposure. This point is addressed in the Panel’s response to charge questi ons related to Chapters 5 and 6, on the need for measurements and models to go hand in hand. They are co mplementary. Neither alone can provide the information needed to estimate concentrations accurately in each microenvironment, such as in vehicle and near roadways. The exposure modeling was judged to be oversimplified. Meteorological models like the Weather Resear ch and Forecasting model,WRF-URBAN, have progressed to realistically re present wind fields and therm odynamic variables on scales of

hundreds of m over an urban domain 1 . Without better estimates of exposure – from a combination of better models and measurements – the COHb estimates remain highly uncertain.

Selection and use of Health Endpoint, Target Population and Risk Metr ic (Chapters 2 and 4, Sections 5.3.7 and 6.2)

To characterize CO risks, the risk/exposure asse ssment estimates the dist ribution of COHb levels

1 D. L. Zhang, Y. X. Shou, and R. R. Dickerson, Upstream Urbanization Ex acerbates Urban Heat Island Effects, Geophys. Res. Lett. , in press, 2009.

8in the adult population with co ronary heart disease that are exposed to ambient CO. 1. Does the Panel find the description and sele ction of health endpoint, target population and risk metric (Chapters 2 and 4) to be technically sound, clearly communicated, and appropriately characterized?

Health Endpoints: The selection of health endpoints for effects of COHb in patients with ischemic heart disease (IHD, CAD) is justifie d. The Panel members agree that the controlled exposure studies in subjects with CAD currently provides the results with the highest degree of exposure and outcome certainty in the scientific data base. In addition, the IHD endpoint is coherent with a significant number of epidemio logic publications that need to viewed as supportive of this endpoint. However, the discus sion of levels relevantto current NAAQS (e.g. page 2-3 line 19 and page 2-5, li nes 10-11) creates confusion. By stating that COHb levels of 3- 6% produced most of the results in patients with CAD, the document uni ntentionally implies that

the levels of interest should be 3-6%. Yet the projections of numbers at risk are based on the lower numbers. Clarification needs to be provide d regarding this issue throughout the document. This strategy is appropriate and consistent with an apparent lack of a threshold for CO effect but this is not stated explicitly.

Target Population: A target population including individu als with coronary artery disease (CAD) is appropriate for the reasons noted in the ISA regarding the nature of their disease. Their diminished ability to compen sate for the loss of oxygen bein g carried in the blood due to increased carboxyhemoglobin makes them highly likel y to be at risk when exposed to CO. The epidemiological studies show increased hospita l admissions in this population. This provides support for this target population but indicates that the CAD target categorization is likely to be

too restrictive relative to a br oader group of cardiovascular dise ase. The populations of other likely targeted individuals ar e indicated by the epidemiology studies and include: congestive heart failure, ischemic heart disease and general ca rdiovascular disease (for example, with risk of stoke) (Summary Section 5.2.3).

The subset of the susceptible population with CAD/ IHD that has been studied needs to be placed in the context of a larger population with varied cardiovascular diseases. Th is section should also acknowledge that many susceptible people have not been diagnosed. Reconc ile the descriptions in section 2.5, p.2-5 lin e 12 with section 4.1, p.4-2, lines 18-2 2. This becomes important in attempting to understand the numbers of susceptible persons in the population.

The Risk Metric: Limiting of the analysis to the be nchmarks of 1.5, 2.0, 2.5 and 3.0% COHb appears to be based on the assumption that no huma n clinical studies were carried out at levels below 2.0% COHb. Based on the information pres ented in the ISA (section 2.6.2. page 2-18 lines 32-34) and the body of epidemiologic data, the Panel recommends that 1.0 % COHb be added as a benchmark. The dose response curves cited in ISA section 2.6.2 include many data points

below 2.0% COHb. Should the staff choose to not consider the above -mentioned dose response information in the REA, justif ication needs to be provided.

2. Based on conclusions in the draft ISA re garding exacerbation of preexisting coronary heart disease in exercising individuals following CO ex posures, we have selected

9potential health effect benchmark valu es of 1.5, 2.0, 2.5 and 3.0 % COHb. To what extent does this range of benchmark values appropriately reflect the controlled human exposure studies health effects evidence related to CO exposures evaluated in the draft ISA?

Benchmarks: The Panel agrees with the document rega rding the strength of the evidence about

the effects of low levels of CO Hb on cardiovascular morbidity in the controlled human exposure studies. There is justification fo r continued use of these data as one of the primary health endpoints even though the evidence for thes e doses from environmental exposure and comparable cardiovascular events has not been made. Increasing epidemiological evidence on

CHD makes the case for the use of these data even stronger. The controlled human exposure studies provide sufficient data to demonstrate dose-response re lationships. Concern was voiced by the Panel that the draft document implies that the data from the controlled human studies do not support the development of a quantitative ri sk assessment that can characterize the doseresponse relationship within the rang e of interest. It is the view of the Panel reviewers that there is no convincing evidence supporting a threshold for key CO-mediate d health effects relevant to at risk populations. Therefore, CASAC has recommended adding a 1.0% COHb benchmark to provide a lower level of COHb in the risk assessment.

3. Does the Panel find the de rivation and presentation of COHb estimates (sections 5.3.7 and 6.2) to be technically sound, clea rly communicated, and appropriately
characterized?

The Agricultural Policy EXtender (APEX) model utilizes the non- linear form of the CoburnForster-Kane (CFK) equation to estimate COHb. Several improved predictive models of COHb were discussed in Chapter 4 of the ISA (Smith et al, 1994; Bruce and Br uce, 2008, Gosselin et al, 2009) that lack some of the limitations of CFK. For example, they are more responsive to transient changes in ambient CO concentrations. These approaches might be better suited for use in APEX for future analyses. In light of the improved models available, justification should be given for using the non-linear CFK. In addition, if no transient environmental data were used to coincide with activity patterns, this should be made clear.

The input variables for different susceptible popula tions need to be spelled out for APEX as well as for CFK. Perhaps this could be accomplishe d with an appendix that identified the major

variables for different at risk groups used in the modeling. If there were no substantive differences in the estimated outcomes among several models despite varying parameters, this needs to be stated and justified.

The exposure scenarios appear to be based on si ngle monitoring stations in LA and Denver. Given the non-uniformity of CO distribution descri bed in the ISA, these ’worst-case’ scenarios may not adequately describe representative e xposures. The manner in which data from the selected sites are adjusted for distance from the site and from local sources needs to be better explained. The selection of number s for the at risk population being exposed to the levels of CO close to the high reading monitors may not be re alistic. The extension of these monitoring sites to persons up to 20 km away is suspect.

10Characterization of Exposure (Chapters 5 and 6)

In recognition of key limita tions in available data with regard to spatial detail of ambient concentrations, this draft REA employs a simp lified approach to exposure assessment in the Denver and Los Angeles study areas. We are intere sted in eliciting the views of the Panel on the usefulness of this approach in informing our review the NAAQS for CO and we are also

interested in the Panel’s view on the relative mer its of alternatives or modifications to this approach, in light of the characteri zation of uncertainty as well as the limitations of the current

data and time constraints on this review.

1. Does the Panel find the summary of CO exposure and discussion of the relationship

between in-vehicle and ambient concentrat ions to be technically sound, clearly communicated, and appropriately characterized? 2. What are the views of the Panel on the approach taken?

There is limited data available characterizing the relationship between in-vehicle CO and corresponding levels measured at fixed site m onitors. From limited data, the REA chooses a single multiplier, 2, to relate in-vehicle CO levels to those observed at fixed site monitors. The

studies cited here a nd the work on the NO 2 REA show that this ratio is likely highly variable.

The NO 2 REA captured this variability in the modeli ng used in that document. The distribution

of in-vehicle to fixed site monitors should be presented and compared to what was found for

NO 2 , recognizing that there are di fferences in the sources and chemistry. This distribution should guide how the exposur e modeling is carried out.

3. Does the Panel view the results of th e exposure analyses to be technically sound, clearly communicated, and appropriately characterized?

While the assumptions made for the exposure m odeling are clear, the model used may be too simple. The Panel previously noted that th e CO monitoring network was limited and did not fully capture the range of ambient CO levels as might be desired for conducting an exposure analysis. But it presumed that instead of simp lifying the analysis further, the EPA would use tools to capture better the spat ial variability involved. There are a number of approaches that could have been employed to conduct the modeli ng that would have addressed greater spatial resolution. This includes using more monitors (as done in the prior assessment) with an approach to interpolating between monito rs. This might still miss many important microenvironments. Using results from a mi croscale dispersion model (as done in the NO 2 REA), land use regression or fusing larger scal e model results with observations should be considered. Though this might also miss hi gher levels in some of the important microenvironments. If possible, one of these more advanced approaches should be conducted. A range of in-vehicle vs. monitored levels could be utilized. Adding a third compartment, near road, should be explored. Given the presenta tion of the prior e xposure modeling, the REA should be more clear as to the relevant strengt hs and weaknesses betwee n the prior and current analyses and how the prior assessment is informative vis a vis the current one. There should be

an assessment of how the differences between the prior and current versio ns of APEX impact results, quantitatively, if possible. The REA should be more transparent as to the reasons behind

11the approaches chosen for how the exposure mo deling was conducted. It should also discuss

what needs to be done to make the anal ysis less limited for future use.

If the choice is made to consider COHb levels down to 1.5% or 1.0%, this has implications for the interpretation of the exposur e modeling results and how it was conducted. At 1%, the current analysis shows that 100% of the individuals would experience that level under the “just meeting” conditions assumption. Further, the prior result s suggest that the per cent of total population exceeding 1% increases by about 25% if indoor condi tions are simulated. This suggests that the indoor exposures are of increasing importance at the lower ambient levels. Like prior REAs, the fraction of exposure in the different microenvironments should be delineated.

4. What are the views of the Panel regarding th e adequacy of the assessment of uncertainty and variability? To what extent have s ources of uncertainty been iden tified and the implications for
the risk characterization been addressed? To what extent has variability adequately been taken into account? Does the Panel have any recommenda tions for sensitivity analyses that they feel would improve this assessment?

Variability : Table 6-24 is very useful. The key sources of variability have been wellcharacterized. However, there should be more discussion to help identify which sources of variability lead to more vari ation in adverse health eff ects compared to others.

EPA should, to the extent possible, provide information on additional susceptible populations beyond cardiovascular disease. CVD is overly na rrow in definition, and asthmatics and pregnant women need to be considered. At a minimum, EPA can quantify the exposures to such groups, if not health effect indicators such as percent C OHb in the blood. EPA should also comment more on the effect of incremental exposures to CO a nd their implications for those persons who may already have elevated levels of COHb because of exogenous sources of CO, such as use of leaf

blowers.

Uncertainty : The document has an extensive discussion of the qualitative assessment of uncertainty. The methodology for treatment of these topics is consistent with that in other ISAs, such as for PM. EPA has done a reasonable jo b of qualitatively identifying the key sources of uncertainty. Major sources of uncertainty are:

• Spatial and temporal variabil ity of CO concentrations

• In-vehicle CO concentrations

• Historical data used for the analys is of “just meeting” the standard

• Commuting data

• Activity pattern data

• Longitudinal profile data Including uncertainties in commu ting data, activity pattern data, and longitudinal profile data will be difficult given the limited time available for finalizing the REA. Furthermore, these sources of data are not specific to CO. Most are important for exposure assessment for many pollutants. However, there are opportunities to significantly improve the characterization of the first three and thereby to address the implications of their uncertainties more fully in the 2 nd draft

REA.

12We are concerned with the last line in Chapter 6, “staff finds the utility of this assessment for the purpose of considering the adequacy of the current standards to be limited.” This statement implies that the REA is not useful as an input to decision making regarding whether to retain or revise the NAAQS for CO. This raises the quest ion of what can be done to improve the quality

of the REA. How can it become a more useful basis for informing decision making? The Panel has identified several promisi ng opportunities for improvement, which are presented below.

With regard to spatial and te mporal variability in CO con centrations, there are several possibilities for improvement (listed in or der from simplest to more complex):

• Rather than base the analyses on only one mon itor per city, use all of the monitors in the city, and restrict the geographic domain to th at associated with the nearest monitor.

• Use a spatial interpolation technique to crea te a concentration field based on monitoring data, to enable use of multiple monitors as input to an exposure assessment.

• Use air quality model output, such as fr om the Community Multiscale Air Quality modeling system (CMAQ), to characterize spatial and temporal variability in CO concentration for each urban area, taking into account some model evaluations compared to the local monitoring data.

• Use CMAQ predicted CO concentrations comb ined with monitoring data, such as in Bayesian framework, to create a “fused” m odel-monitor based estimate of spatial and temporal variability in CO concentrations.

With regard to the ratio of in-vehicle to ambien t concentrations, this can be addressed via more extensive sensitivity analysis (i.e. vary this ratio over a plausible range). The central tendency of

this ratio should be based on a best estimate from the available data.

Regarding the analysis of “just meeting” the st andard, there are several fairly straightforward improvements that could be made:

• Rather than focus on one scenario, try multiple scenarios.

• Rather than base the assessment on an older sc enario, also consider scaling from a more recent scenario. In this case, one might need to scale upward rather than downward to “just meet” the standard.

In the 2 nd draft REA, EPA should point out that they conducted a preliminary uncertainty

assessment in the 1 st draft REA, and used the results to target efforts to improve the REA as recommended above. Furthermore, the results of Table 6-25 shoul d be revised if/as appropriate. This will be a good example of an iterative approach to both un certainty analysis and model refinement, leading to an improved REA.

To support future exposure assessm ents that would quantify both inter-individual variability in exposure and uncertainty in exposure, EPA should continue to develop input data needed for microenvironmental population-ba sed stochastic simulation mode ls for exposure, as well as continue to develop and impr ove the models themselves.

5. To what extent does the simp lified approach taken in the docume nt help to characterize the public health implications of the current standard.

13The rationale for focusing on Denver and Los Angeles based on limited monitoring sites was cogently presented, as was the rationale for focusing upon health effects at low level

benchmarks.

A key aspect of the approach used was limiting the monitoring data input to the single most appropriate monitoring site in each city. The basis of selection for the sites whose data was used was their relevance to (but still underestimati ng) the microenvironment of prime interest – roadways. Simplifying the REA approach is justif ied when monitored or modeled exposure input data for the more complex model are unavailable. For example, it is reasonable when we lack spatially well-defined CO data, or when it can be shown that one of the key steps in the more complex APEX model is not likely to impact the overall results.

Also, current CO monitors – even the micro- scale ones – would not be able to represent exposures in a micro-environment of great concern, i.e., homes in close proximity to roadways. While the density of the current CO monitoring network and the sensitivity of instruments are not adequate to produce reliable, small scale exposur e surfaces for CO even in the cities with the largest numbers of monitors (such as LA), we nonetheless recommend exploring how exposure modeling based on traffic density and related factor s could be used to better inform the APEX

model in future risk assessments.

The simplified approach used can be justified for public health purposes. It is likely to be more public health protective than the ar ea-wide averaging techniques that have been used previously. But that still leaves much room for future improv ement. For example, it is very difficult to intuit how simply changing some of the input values (o r weights) for on-road and near-road exposureswould influence the modeled REA estimates. However, the 2.0 multiplication factor for invehicle exposures is not acceptable and should be changed to 2.4 based on the data provided; we also request a simulation based on the mean winter values derived from LA data and results from models with a probabilistic set of several values to better gage the influence of changing these parameters. Finally, these models should be a pplied down to 1.5 ppm or even 1.0 ppm, rather than cutting analyses off at 2.0 ppm, based on the absence of an apparent threshold for cardiovascular endpoints.

As mentioned earlier, the Pane l is concerned with using onl y narrowly-defined and poorlyestimated adult CAD as one of the simulated outco mes. This ignores concern for many different outcomes including impacts on fetuses and childr en or on the elderly and clear linkages for causal inferences. We recommend strongly that the cu rrent modeling of those at risk on the basis

of cardiac ischemia be extended to include a mo re broadly defined categ ory of cardiovascular disease (including congestive failur e and stroke) rather than narro wly restricting the modeling to coronary artery disease (based on NHIS 2007 checklist responses). Even with such changes, it is important to acknowledge that this REA exercise does not allow us to gauge in a quantitative or even qualitative manner how possibl e health effects from even low levels of CO exposure in large populations affect the growi ng number of elderly and very el derly individuals living in the

US or the more than 4 million children born in the US each year. Ther e are other susceptible subgroups (such as those with diabetes or non-CAD cardiovascular disease w ithin the brackets of youth and old age).

146. Does the Panel have any recommendations regarding how the approach might be modified to better characterize the public health implications of the current standards, in light of the uncertainty associated with the simplified approach, the current data and time constraints on

this review?

It would have been helpful if the evaluation of un certainties had not just been done qualitatively. We need to know how modeling sp ecifications would change the es timates. It would have been helpful to have at least some quantitative data for one or two of th e strongest and weakest factors. This would help calibra te our judgments, understand the ma gnitude of their impacts, and support the qualitative judgments presented.

Chapter 6 lacks a conclusion and leaves the read er to question what should be made of the difference in outcome between the current approach and the more thorough approach used in previous reviews. What are we to make of th is difference? What prac tical significance does it

have? Section 6.4.2 lacks sufficient direction and “punch.” Further, the Pa nel is not convinced that a simple score-card rati ng of low, medium, and high-im pact uncertainty factors was adequate. A more rigorous and focused descri ption of this should be achievable in the subsequent draft.

The Panel recommends EPA add a table similar to Table 6-24 that lists all capacities of the APEX model for all 7 steps in one column. The second column could list steps employed and assumptions made to help guide the reader. Th is would clarify why certain steps were omitted due to lack of detailed input data or because modeling was not productive.

Exposures for residents very close to roadways may be higher in winter during stagnant air

conditions. It is not clear whethe r and how this type of weather has been ta ken into account in the REA (for example, in Denver).

For the two monitoring site s selected, data was chosen from th e year 2006. In Denver, at the site in question, there was a marked upward tre nd from 2006 to 2007 and 2008 for the monitor in question for 1 hour (2nd highest) av erage and to a lesser degree for 8 hours (data Figure 3-1). Baring other issues, it would seem that greater pu blic health protection wo uld result with the use

of 2008 data or at a minimum to combine 2006- 2008 for Denver. Although Los Angeles overall was flat in these years, the monitor in question did fall during 2007-2008 (opposite to the Denver pattern). Nonetheless it is not clear why 3 years of data are not used (Figure 3-2).

15Enclosure C

Compendium of Revi ew Comments from CASAC Carbon Monoxide Review Panel on EPA’s Risk and Exposure Assessment to Support the Review of the CO Primary National Ambient Air Quality Standards: First External Review Draft (October 2009)

Comments received :

Dr. Paul Blanc ............................................................................................................................. 17

Dr. Thomas Dahms ..................................................................................................................... 19

Dr. Russell Dickerson .......................................................................................................... ....... 23

Dr. Laurence Fechter.................................................................................................................. 25 Dr. H. Christopher Frey............................................................................................................. 26

Dr. Milan Hazucha.............................................................................................................. ........ 30

Dr. Michael Kleinman ................................................................................................................ 32

Dr. Beate Ritz ................................................................................................................. ............. 35

Dr. Paul T. Roberts............................................................................................................ ......... 37 Dr. Armistead (Ted) Russell .................................................................................................... .. 43 Dr. Anne Sweeney ............................................................................................................... ........ 46 Dr. Stephen Thom....................................................................................................................... 47

16

### Dr. Paul Blanc

CO: EPA Review Risk and Exposure Assessment, Draft Comments

Characterization of Exposure (Chapters 5 and 6)

Question 5. To what extent does the simplifie d approach taken in the document help to characterize the public health imp lications of the current standard.

A key aspect of the approach used is to limit the monitoring data input to the single most appropriate monitoring site in each of 2 cities (D enver and Los Angeles). The basis of selection

for the sites whose data was used was their citing as relevant to (but still underestimating) the microenvironment of prime interest – roadways . Consistency and other sampling characteristics

were also taken into account in th is selection. In principa l, this “simplification” is logical and is indeed likely to be more public health protectiv e than the area-wide averaging techniques that have been used previously.

A second driver to the model was testing of a second exposure scenario taking into account commuting time with higher exposure, calculated a 2 x the monitoring site value. Once again this approach of a commuter higher expo sure scenario is reasonable.

The third assumption of the model is that the key outcome to be modeled is acute-exposure

related adverse cardiovasc ular events. Once again, in principa l this is a reas onable endpoint to choose as being the most sensitive, based on the revised ISA.

Question 6. Does the Panel have any recommenda tions regarding how the approach might be modified....

For the two monitoring sites data was chosen fr om the year 2006. In Denver, at the site in question, there was marked upward trend from 2006 to 2007 and 2008 for the monitor in question for 1 hour (2 nd highest) average and to a lesser de gree for 8 hours data Figure 3-1). Baring other issues it would seem more public health protection to us e 2008 data or at a

minimum to combine 2006-2008 for Denver.

Although Los Angeles overall was flat in these years, the monitor in question did fall 2007-2008 (opposite to the Denver pattern) - nonetheless it is not clear why 3 years of data are not used.(Figure 3-2)

The Los Angeles site seems less optimal for th e microenvironment but this does not seem to have been taken into account with an upward adjustment. This may need to be considered.

The factor used to go from best -as-possible fixed site to road ways was 2x as noted above, but based on table 5-3 this values is actually 2.4. The text may simply not be clear and 2.4 was used but if not it should be. Moreover, the winter ratio (based on LA data; Table 5-3) was actually 2.7.

Given the more extreme winter conditions in Denver, should a higher ratio be used?

17The population at risk for the risk calculations is estimated overly narrowly by defining this as persons with coronary artery disease (based on NHIS 2007). This may reflect the omission in Chapter 4 (Health Effects Benchmark) of any of th e epidemiological data in the draft ISA, and in particular, the 2009 pivotal Bell study . That study, for example, makes clear that the risk is for

cumulative cardiovascular disease endpoints, not all of which reflect baseline known coronary artery disease as would be defined in the NHIS. A clear example of this is the risk of CVA (stroke) in that analysis.

The modeling output cuts off at CO concentra tions of 3 before going down to zero. Modeling person days at 2 PPM and 1 PPM would also appear to be relevant (e.g., based on Bell)

18

### Dr. Thomas Dahms

Selection and use of Health Endpoint, Target Population and Risk Metr ic (Chapters 2 and 4, Sections 5.3.7 and 6.2)

To characterize CO risks, the risk/exposure assess ment estimates the distribution of COHb levels in the adult population with co ronary heart disease that are exposure to ambient CO.

Questions: 1. Does the panel find the description and sele ction of health endpoint, target population and risk metric (Chapters 2 and 4) to be technically so und, clearly communicated, and appropriately characterized ?

A. Section 2.3, page 2-3, line 19. I be lieve that the characterizati on of the level of COHb at which angina and ST-segment changes occur is improperly characterized as being 3-6% COHb. The levels emphasized by placement in text in this document are those levels produced by CO-oximeter readings. The presen tation of findings using CO-ox data needs to be justified in light of the informa tion in the 2000 CO NAQC (Section 2.6.1) based on Vreman’s findings that co-oximeters that are not designed to provide accurate information in this range of COHb. The e ffect of emphasizing the 3-6% COHb findings is problematic when numbers of at risk pati ents is determined for 1.5, 2.0 etc levels of

COHb.

The presentation of CO-Ox data with the implica tion that it is equivalent to data collected by many other methods is not justifiable. Seve ral other more sensitive methods have been shown to be accurate for measuring COHb levels near baseline and these data need to be

denoted somehow so the reader is not mislea d. The sensitivity of different methods for measuring COHb has been known for at least 30 years and the misinfor mation should not be promulgated in this document.(see Tabl e 5.2 on page 5-36 in the 1979 AQC for CO published by the EPA).

B. Section 2.3, page 2-3, lines 20-22. The studies using controlled human exposures mostly used one level of CO exposure resulting in a limited range of COHb levels (effective dose). Review of this information apparently leads to assessment of effects of CO pertaining to the mean COHb levels. Howeve r as noted in the ISA in section 2.6.2. page 2-18 lines 32-34, the 63 subjects reported by A llred et al demonstr ated a dose-response curve for COHb and angina and for ST-segment changes in subjects with CAD. There is a suggestion the the Allred et al (1991) publ ication that there was no obvious threshold of

effects of COHb. This is information conflic ts with the statement in this section and needs to clarified, discussed or changed.

C. Section 2.5, page 2-5, lines 10-11. There is on ly uncertainty about the COHb levels measured with the CO-oximeters (see item A above). All of the studies cited on page 4-2 line 8 either used the same exposure conditi ons or obtained simila r increases in COHb.

19The levels of COHb of interest should be c oncordant with the values used in the uptake

models in the document.

D. Section 2.5, page 2-5, line 12. The statemen t “that these studies did not include

individuals with more severe CHD” is too va gue. It is in conflict with the comments in Section 4.1, page 4-2 lines 18-22 which implies that the subjects studied had CHD that

was more severe than most with CHD. Neither statement allows the reader to determine what percentage of the populat ion with CHD is at risk base d upon the studies that have

been carried out.

E. Section 4.3. lines 23-27. How can this observatio n be reconciled with information in the ISA regarding a dose-response effect noted in sections 2.6.2 and 5.2.4 of the ISA?

F. Given all of the supportive information obtai ned from the epidemiology studies, why is there no quantitative weight given to all of these studi es? How can this mass of information not be accounted for in this phase of the process?

2. Based on conclusions in the draft ISA regar ding exacerbation of preexisting coronary heart disease in exercising individuals followin g CO exposures, we have selected potential health effect benchmark values of 1.5, 2.0, 2.5 a nd 3.0% COHb. To what extent does this range of benchmark values appropriately ref lect the controlled human exposure studies (in) the health effects evidence related to CO exposures evaluated in the draft ISA?

The range is fine if one does not consider the dos e-response curve of Allred et al to be valid.

3. Does the Panel find the derivation and pres entation of COHb estimates (sections 5.3.7 and 6.2) to be technically sound, clearly comm unicated, and appropriately characterized?

A. It is not clear how APEX determined expos ures and the non-linear CFK deals with the transient exposures that the model of Bruce and Bruce seemed to handle more convincingly. It seems too crude to use only 1 hour averages for exposure to determine

dose of CO for the 1 hour standard.

B. Page 5-12 line 24-25, and page 5-13 line 20. What is the evidence that “accurate results

for lower levels of COHb” were obtained from this model?

C. Section 6.1.3. Is the resulting number of persons at risk over estimated because of the

concerns raised in sections 2.5 and 4.1?

D. Tables 6-8 and 6-9 should include the current 1 hour standard in their CO concentrations. The foot notes should be changed accordingly. Tables 6-8, 6-10 and 6-12 should have the numbers of person days spelled out in thous ands rather than using the exponential notation. This would make the visual comparison between these tables and the following

tables easier to read.

E. The assumptions regarding activity patterns of patients with CHD relative to the general population need to be reiterated so that using a percentage of the entire population to generate the numbers at risk is justified. Or do I not unders tand how these numbers were generated?

20F. Does any of the epidemiologic data support any of these estimates assuming that the benchmark levels of COHb would trigger card iovascular events that would result in contact with the healthcare system?

21Editorial comments

1. Section 2.3 and beyond. This section (line 22) introduces the terms susceptibility and vulnerability yet after the firs t paragraph switches to at ri sk without explaining the link. For a person to be at risk needs to be clearly defined.

2. Section 2.3, page 2-3 line 26. Use of non-specifi c terms like IHD or CHD can lead to an overestimation of numbers of people at ri sk when exposed to CO. The distinction between the use of terms in the epidem iology literature and the controlled human exposure experiments needs to be made.

In reviewing the ICD-9 codes the diseases included under IHD includes a variety of conditions not studied in any of the controlled human exposure studies. CAD is a subset of conditions under IHD and (CHD is no longer iden tifiable). Therefore it is suggested that these terms be clearly identified in the REA since they ha ve been used as being synonymous in previous documents. The ISA is fairly clea r in its limiting its di scussion in section 5.8 Summary to use of the more limiting term CAD. The reference on line 5 to section 5.8 of the ISA is not clear. Perhaps the terminology adopt ed in sections 5.7.8 and 5.8 of the ISA should be followed especially if the focus is on the controlled human subject studies.

3. Section 2.4, page 2-4 line 10. suggested editor ial change for clarity: ...CO levels of concern is tissue hypoxia due to reduced O2 delivery resulting from increased COHb....

4. Section 2.5, page 2-4 line 26. how do these unde fined ‘short term ambient CO exposures’ relate to the standards or to the exposure models that were used to assess risk?

5. Section 4.1. page 4-1, line 13. ‘reduced iron’ should read iron. CO will competitively compete with oxygen for hemoglobin regardle ss of the oxygenation status of hemoglobin. Both will compete for iron in the plus 2 state of oxygenation, so to refer to the valence of the iron is only confusing

6. Section 4.2. p4-3. lines 8-17. As mentioned thro ughout the ISA (but not summarized in this way) all but one of the controlled hu man studies used nearly the same exposure conditions so one would expect the same CO dos e in all these subjects. Yet the variability is in the blood analysis by CO -Ox. It would be helpful if this information was presented as it would help the reader to understand the consistency in th e cardiovascular effects and the inconsistency in the COHb levels reported.

7. Section 4.2, p. 4-3 Lines 20-23. The conclusi on of the staff regarding dose-response relationships is clearly not supported by the opinion of the panel. If there is a benchmark for establishing whether or not a dose response exists for regulatory purposes it needs to be stated here. Otherwise it appear s to be an arbitrary decision.

8. Section 5.5.2 p.5-24 lines 23-26. If such an approach was acceptable for ozone there needs to be more detailed justification for the position of the CASAC_CO panel as summarized by Samet and Brain in this document. Or is this just a difference of opinion?

9. Tables 6-8 through 6-11 should have the one hour CO concentration values shown (35 ppm).

22

### Dr. Russell Dickerson

Air Quality Considerations (Chapter 3)

Considerations of current ambien t CO monitoring data and the disc ussion of the extent to which near roadway concentrations are technically sound, clearly communicat ed and appropriately

characterized?

The REA makes it clear that many current monito rs lack the sensitivit y to provide accurate measurements of ambient concentrations (although page 3-3, line 8 should be “below 1 ppm” not “near 1 ppm”), but these observati ons are useful for estimating e xposure at high concentrations and showing long-term trends. The REA further discusses thoroughly and cl early difficulties in extrapolating from point monito rs (usually set up to demonstrate compliance with the NAASQ) to actual exposure. The added discussion of NCORE strengthens the document. The actual concentrations to which people are exposed will have to be estimated with a combination of measurements and models. There is one point made explicitly in the ISA but not in the REA. Some published comparisons of emissions inve ntories and ambient measurements reveal substantial disagreements potential ly leading to major uncertainties in numerically simulated CO

concentrations.

Response to CQ1: Does the Panel find the cons iderations of current ambient carbon monoxide monitoring data and the discussion of the extent to which near roadway concentrations are represented to be technically sound, clearly communicated, and appropriately characterized?

Many of the comments made in regard to the ISA apply to the REA as well. It is good to see a discussion of the NCORE network. The chapter n eeds a final statement regarding uncertainties in emissions and/or measurements. The quality and quantity of CO m onitors need to be improved in order to reduce uncertainties in expo sure, emissions, and distributions, and the REA reflects these data limitations, so the answ er to Charge Question 1 is “yes”.

As far as monitoring goes, the REA does a good job – there is an issue related to the combined use of models and measurements to estimate exposu re. This point is addr essed in an answer to questions related to Chapters 5 & 6, on the n eed for measurements and models to go hand in hand. They are complementary and neither alone can provide the informati on needed to estimate accurately concentrations in each microenvironment such as in vehicle and near roadways. The exposure modeling was judged to be oversimplified. Meteorological models such as WRFURBAN have progressed to rea listically represent wind fields and thermodynamic variables on scales of 100’s of m over an urban domain (e.g., Zh ang et al., 2009). Without better estimates of exposure – from a combination of better models and measurements – the HbCO estimates remain highly uncertain.

D. L. Zhang, Y. X. Shou, and R. R. Dickers on, Upstream Urbanization Exacerbates Urban Heat Island Effects, Geophys. Res. Lett. , in press, 2009.

2324

### Dr. Laurence Fechter

Comments on Risk and Exposure Assessment document for CO

I found the 1 st draft of this document to be a reasonabl y strong and effective presentation of the new approach to modeling human exposure to carbon monoxide. The rationale for focusing on Denver and Los Angeles was cogently presente d as was the rationale for focusing upon the

health effect benchmarks between 1.5-3% C OHb and specific monitoring sites. Given the enormous detail that is provide d in chapters 5 and 6 of this document I confess to feeling seriously let down by the lack of co nclusions. It is very interesti ng that the current approach and the previous one produce significa nt differences in outcome, but what am I to make of this difference? What practi cal significance does it have? I found section 6.4.2 to lack sufficient direction and “punch”. I kept wondering where we were headed here. Additionally, I was not convinced that a simple score card of low, medium, and high-impact uncertainty factors was adequate. I am certain that a more rigorous and focused description can be achieved in the subsequent draft.

25

### Dr. H. Christopher Frey

Review of Carbon Monoxide First Dr aft of Risk and Exposure Assessment

Chapters 5 and 6

Charge Question 1 : Does the Panel find the summary of CO exposure and discussion of the relationship between in-vehicle and ambient c oncentrations to be technically sound, clearly communicated, and appropriately characterized?

Response to Charge Question 1 : From a qualitative perspective, the REA reasonably

characterizes the relatio nship between in-vehicle concentr ation, concentration outside the vehicle, near-roadway concentra tion, and area-wide concentration. It is clear that the CO concentration on the roadway is typically higher than at fixed site monitors (FSMs). It is also appropriate that the CO concentration in the ve hicle is very similar to the CO concentration immediately outside the vehicle. Hence, it is appropriate to estimate that the in-vehicle CO concentration is a multiplier greater than the FSM data.

The REA could better describe the “microscale” aspects of vehicle activity and emissions that could lead to substantial variability in exposur e. For example, on a portion of roadway with positive road grade, for which a significant port ion of vehicles might be operating in fuel enrichment mode, the localized tailpipe emissions of CO can be much higher than elsewhere on the transportation network. Such episodes might last only a few seconds, however, and thus are of an averaging time that may not be commensurat e with the available health effects data and

models.

Even for longer term averages, ther e is likely to be subs tantial variability in in-vehicle exposure depending on factors such as wind speed, atmospheri c stability class, vehicle traffic volume, and vehicle tailpipe emission rates.

Charge Question 2 : What are the views of the Panel on the approach taken?

Response to Charge Question 2 : The use of a multiplier such as 2 might be a reasonable average, but is not likely to ta ke into account variabil ity in onroad conditions that might lead to much higher exposures. Rather than use one num ber for the multiplier, a range of numbers can be used either as a sensitivity analysis or as a probabilistic analys is using a distribution.

The distribution of windspeed and direction for each FSM used in the REA should be evaluated to determine whether the monitor is upwind or downwind of the nearest major roadways. An assessment should be made as to whether the multiplier for in-vehicle to ambient proximity should be adjusted to take into account these me teorological conditions. This decision could be informed by sensitivity analysis with an air quality model such as CALINE4.

Charge Question 3 : Does the Panel view th e results of the exposure an alyses to be technically sound, clearly communicated, and appropriately characterized?

26Response to Charge Question 3 : The exposure analysis does not appear to be technically sound. Consider that the last line in Chapter 6 is “staff finds the utility of this assessment for the purpose of considering theadequacy of the current standards to be limited.” This statement implies that the REA is not useful as an input to decision making regarding whether to retain or revise the NAAQS for CO. This begs the question of what can be done to improve the quality of the REA so that it is a useful basis for informing decision making.

In Section 6.4.2, the key sources of un certainty are identified to include:

• In-vehicle CO concentration

• Commuting

• Spatial and temporal variab ility of CO concentration

• Historical data used for the analys is of just meeting the standard

• Activity pattern data

• Longitudinal profile data

For some of these, such as activity pattern and longitudinal profile data, and perhaps the methodology used for estimating commuting-related exposures, there is not likely to be any improvement in the next few months.

However, there is the potential for significant im provement in the characterization of spatial and temporal variability in CO concentration. There are several possibi lities for improvement:

• Rather than base the analyses on only one mon itor per city, use all of the monitors in the city, and restrict the geographic domain to th at associated with the nearest monitor.

• Use a spatial interpolation technique to crea te a concentration field based on monitoring data, to enable use of multiple monito rs as input to an exposure assessment

• Use air quality model output, such as from CMAQ, to characterize spatial and temporal variability in CO concentration for each urban area, taking into account some model evaluations compared to the local monitoring data

• Use CMAQ predicted CO concentrations comb ined with monitoring data, such as in Bayesian framework, to create a “fused” m odel-monitor based estimate of spatial and temporal variability in CO concentration.

The latter would be the technica lly most attractive approach. This would iteratively address what EPA has identified as one of the key sources of uncertainty in the analysis.

Although there may be little prospect of obtaini ng more measurements of in-vehicle CO

concentration relative to con centration at the vehicle exte rior, the use of a better CO concentration field as an input to estimating in-vehicle concen tration, still us ing a reasonably justifiable proximity factor such as two, would nonetheless lead to some improvement in the invehicle concentration estimate.

The use of land-use regression models should be c onsidered if it could improve the prediction of concentration gradients in the pr oximity of roadways and thus better inform estimates of invehicle concentration.

27Regarding the analysis of just meeting the stan dard, there are several fairly straightforward improvements that could be made:

• Rather than focus on one scenario, try multiple scenarios

• Rather than base the assessment on an older sc enario, also consider scaling from a more recent scenario (in which case one might need to scale upward rather than downward to “just meet” the standard).

Charge Question 4 : What are the views of the Panel re garding 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 addressed? To what extent has variability adequately been taken into account? Does the Panel have any recommendations for sensitivity analyses that they feel w ould improve this assessment?

Response to Charge Question 4 : Variability : Table 6-24 is very useful. However, ther e should be more discussion that helps to identify which sources of variability lead to more variation in adverse health effects compared to others. For example, does variability in activit y patterns because of temperature lead to more variability in adverse eff ects than the population data?

Uncertainty : The document has reasonable content regarding a qualitative assessment of uncertainty. The methodology for treatment of these topics is consistent with that in other ISAs,

such as for PM.

p. 6-37, line 13. The assessment endpoint is rela ted to exposure or effect, not air quality. Lines 16-28. Are these categories of uncertainty based on some absolu te scale or relative to each

other?

Table 6-25:

• knowledge base uncertainty for adjustment of air quality to simulate just meeting the standard -- it seems not very compelling that it is “largely unknown” as to how emissions level per vehicle, etc. compare between the earlier period of time and the hypothetical condition. For example, emission factors are av ailable for vehicle tec hnologies typical of the time period, such as in the Mobile5b emission factor model.

• Population data base – the population data are for 2000. The air quality data are from 2006. While this is not a problem per se, a reader might misinterpr et that the effects estimates are based on a 2006 population. If population has increased from 2000 to 2006, then the number of incidences would app ear to be underestimat e relative to a 2006 population. Thus, it is important to clearly characterize th at results are based on 2000 population when reporting result s in tables and figures.

28• Algorithm and Input Data for All other microenvironmental CO concentrations – consideration of the lag effect associated with air excha nges might delay and lower the peak indoor concentration relative to the peak outdoor concentration, but also will

increase the minimum indoor CO concentrati on relative to the am bient concentration.

• CHD prevalence: The Coronary Heart Dise ase (CHD) prevalence is estimated based on gender-specific ratios applied to all age groups. Hence, there may be some uncertainty as to the accuracy of the prevalence estim ates for specific age and gender groups.

The summary of uncertainty is in terms of focu sing on the “direction” of uncertainty first and then considering the magnitude of uncertainty.

Page 6-41, line 12/13 (in between thes e) it is stated that there is “relatively less uncertainty” but intended meaning seems to be relatively ‘more’

Other comments:

Where is EPA going with this? Given that the on ly analyses are at the level of the current standard and “as is” air quality for two cities, doe s this imply that EPA is merely considering to continue the current standard? What regul atory alternatives are to be considered?

To what extent can/should there be an assessment of welfare effects relate d to climate change?

29

### Dr. Milan Hazucha

Updated Comments on the First External Review Draft of the REA for Carbon Monoxide

Chapter 2:

Individuals with cardiovas cular disease identified as the primary target population indeed appear to be the most susceptible to CO-induced h ealth effects. However, there are other large populations such as people with anemias that are also more susceptible to adverse effects from CO exposure. These “secondary” populations do not s eem to be considered in either dose or risk

metrics assessment.

Page 2-4, l. 13 and Page 5-12, l.7-8: Chapter 4 of ISA has revi ewed numerous empirical, mechanistic, and mathematical COHb predictive models that are more accurate in variable ambient CO and physiologic conditions than CFKE which contains numerous assumptions with potentially inaccurate COHb values. W hy not to use more accurate model?

Page 2-5, l. 13-14 : Although the statement is correct I sugge st clarifying it by adding that COHb levels below 2% were measured post-target (2% and 4%) exposure and at the end of exercise

which further reduced COHb concentration. This will prevent quite frequent misunderstanding by even CO panel members that the “exposur es” were to concentrations below 2%.

Page 2-5, l.14-16 : The proposed range of benchmarks ( 1.5, 2.0, 2.5, and 3% COHb) is adequate for CO risk characterization. Reducing the benchm arks below 1.5 % would be problematic since, (1) recent data (Hart et al., 2006) report an av erage resting blood COHb level of 1.59 % in 2448 never smokers, (2) Figure 4-12 of ISA shows that the baseline COHb level is ≥ 1% for diseases/conditions listed, and (3) many diseases discussed in the ISA section 4.5, and listed in Fig.4-13 such as asthma, metabolic diseases and other inflammatory conditions result in

increased blood COHb levels above 1% as well. So there is a huge population with blood COHb

level ≥ 1% not due to ambient CO exposure but disease conditions. Consequently, any risk assessment below 1.5% would be highly questionable.

Chapter 4:

Page 4-2, l. 5-6: Be more specific. They are all standard protocol depending on intended test goals. Modified Naughton exercise protocol was used in the study.

Chapter 5:

The Apex model employs CFK equation for es timation of COHb (Appendix C). Though CFK is a robust model, a review of various predictive m odels of COHb in Chapter 4 of ISA shows that there are more sophisticated models (Smith et al, 1994; Bruce and Bru ce, 2008, Gosselin et al, 2009) that do not have the limitations of CFK an d are more responsive to transient changes in ambient CO concentration and thus might be be tter suited for APEX. The suitability of more comprehensive models in COHb module of APEX should be explored.

30Another concern is the selection criteria used to characterize simu lated individuals for the APEX

data set. The individuals are defi ned by age, gender and body weight (section 5.3.2, page 6-35

and C-7 ). This info is subsequently used to develop a “personal profile” which includes physiologic variables. The derived values are th en used in CFK model. However, the profile does not have build in any “health status” variab le which could modify the input of physiologic variables of CFK equation. Do I understand it correctly?

It is still unclear to me how a simulated at-risk population is selected. From Section 5.3.2, table 6-24 and corresponding text it appe ars that the source data, i.e., for simulated individuals are derived from general population. Subsequently, based on the prevalence of specific health condition, e.g., CHD, a subset of at-risk simulate d individual is create d from the initial set without adjusting input variables for that (speci fic) health condition. Another possibility is that the generated sample includes simulated at-risk individuals at certain prevalence rate, but the physiologic variables are not adjusted accordingly either. For example, people with anemia or CAD have different Hb concentration, endogenous production of CO, etc., then healthy individuals ( ISA, 4-29 to 4-31 ). Consequently, if the input vari able values are not adjusted the

COHb estimates will be incorrect. How is this corrected for in the APEX?

Some of the methods and formulae for paramete r estimates are rather old (Allen et al, 1956; Salorinne, 1976; Galetti, 1959) . Over the last 50 years the population characteristics have changed dramatically and there are more recent predictive formulae available for input parameter estimates such as blood volume, DLCO and VA. Moreover, some of the physiologic variables in CFK must be adjusted for barometric pressu re. The VA is adjusted, but DLCO is not. The American Thoracic Society recommends that the va lue of DLCO is adjusted for altitude (ATS, 2005). This is important for Denver site exposure assessment by APEX.

Page 5-10, l.24-25: The statement is true, but only fo r sub-maximal exercise in healthy

individuals. Need to st ate that. Moreover, VA/VO 2 ratio is not so constant for patients with

cardiovascular disease.

Page 5-13, l. 31-32: Does this “reasonable sample” also in clude individuals who may be at-risk?

Page 5-20, table 5-2: The table data seem to be based on passenger cars only. Any data on pickups, vans, buses, trucks? Out of ~500 mil ve hicles only about 250 mil are passenger cars (US Bureau of Transit Statistics). Th e other one half of on road vehicl es is most likely polluting more than passenger cars do.

Page C-8, last paragraph : Do you run the model under instantaneous CO concentration or 1- hour averaging time? How is the averaging time selected?

31

### Dr. Michael Kleinman

Selection and use of Health Endpoint, Target Population and Risk Metr ic (Chapters 2 and 4, Sections 5.3.7 and 6.2)

1. Re: The description and selec tion of health endpoint, target population and risk metric.

a. The strongest evidence regarding CO health effects does relate to cardiovascular
morbidity and it appears that the evid ence is sufficient to indicate a causal
relationship is likely to exist. The cohe rence of epidemiological evidence with
the human controlled exposure study data supports this finding.

b. The controlled exposure studies provide both exposure-response relationships and
through use of COHb measurements as a exposure/dose biomarker there appears
reasonable data to provide dose-response relationships.

c. Having said that, Chapter 4 goes on to note the data from controlled human
studies ‘do not support the development of a quantitative ri sk assessment to
characterize the dose-response relationship w ithin the range of interest.’ This
conclusion is not sufficiently supported in the REA. While there are some

inconsistencies in the contro lled study time to angina endpoints, there seem to be
sufficient data and reasonable consistency in study methods and designs that a
‘meta-analysis’ or comprehensive da ta analysis could be performed.

2. Re: Benchmark values.

a. Extending the benchmark values below the level at which significant changes
were detected in controlled exposure studi es is appropriate an d consistent with
previous CASAC suggestions. The subj ects participating in the controlled
exposure studies were required to be able to perform aerobic exercise as part of
the protocol, hence were not as debilitate d as many individuals with CVD or IHD.

b. The coherence of the epidemiological study results with the results of the
controlled human studies also suggests that extension of consideration below 2%
COHb is warranted since the epidemio logy demonstrates morbidity at CO
exposure levels that would produce COHb we ll below 2%. If the baseline level of
the participants of the controlled studie s is representative of the COHb of the
general population of CVD and IHD patients, their average COHb is on the order

of 1% or less.

3. Re: Presentation and deriva tion of COHb estimates.

a. Section 5.3.7 provides a useful summary of the parameters incorporated into the

CFK model. On the other hand, the ISA goes to great lengths about the problems

of CFK for low levels of COHb and s hort-term exposures. Presumably APEX
generates 8hr and 24hr CO exposure estimat es. If those estimates are appropriate
for the CFK, it could be e xplicitly stated in 5.3.7.

32b. The methodology for generating the scenar ios is reasonable if one accepts the
premise that 1 monitoring station each in LA and Denver are sufficient to describe
exposures. This seemed like a major jum p, given everything prev iously stated in
the ISA and the REA about CO being non-uniformly distributed. Given the
conclusion in 6.5 ‘the utility of this assessment for the purpose of considering the
adequacy of the current standards to be limited’ suggests that the REA could be
improved.

i. Use a meta-analysis or other technique to better define the dose response

curve.

ii. Use a more comprehensive design for assessing exposures in both LA and

Denver that could take into acc ount the inhomogeneities of CO

distributions.

c. The finding that the REA utility is ‘limited’ needs to be better qualified as to what
those limitations are with respect to evaluating the current standards. At a

minimum it would seem that more information on what more would be needed to
consider the adequacy of the standards should be provided.

Additional REA Comments

Page Line Comment

4-3 22 The distinction between the quan titative risk assessment and the risk characterization should be made more clearly.

4-4 11-15 Lowering the range of consideration also may be relevant to other populations that might be at risk such as people with anemia, sickle cell disease, fetuses and perhaps severe COPD where O2 transport/delivery is impaired

5-7 16-17 The simplified approach also ignores other sources of indoor CO production such as cooking, smoking and emissions fro m poorly ventilated fossile-fueled appliances.

5-21 2 ...the ‘properly maintained automob ile engine and exhaust system’ does not

contribute....

5-21 12 ...converge to unity ‘as averaging times and durations of observations increased.’

5-23 25 Were the remaining monitors placed in a way that allowed one to draw conclusions about inhomogeneity?

5-24 27 Limiting the monitoring data to a single site in Denver and a single sit in LA needs to be more strongly justified.

6-1 12 It should be mentioned in this paragraph that compa ri son runs were made between the proposed simplified model and PNEM/CO that will be discussed later in Chapter 6.

6-10 22 The design value definition should be show n here rather than later in the chapter.

6-17 Use the exponential format for tables 6-8 through 6-12.

6-40 Should a row be added for the CFK algorithm which has several components that potentially contribute to biases.

6-43 15-19 The number of individuals living near road sides is an issue that is raised at several points in the REA. Can’t something be said of a more quantitative nature so that the magnitude of the problem can be assessed?

336-43 25-26 The statement that the utility of this assessment is limited needs to be followed up with a suggestion of what will be done next to consider the adequacy of the current

standards.

34

### Dr. Beate Ritz

CO: EPA Review Risk and Exposure Assessm ent, Draft Comments Characterization of Exposure (Chapters 5 and 6)

Question 5. To what extent does the simplifie d approach taken in the document help to characterize the public health imp lications of the current standard.

A simplified approach is certainly justified wh en the data needed for a complex model is unavailable (such as a lack of enough spatially well defined CO monitoring data – note however that I do not understand why there is a ‘lack of temporal vari ability in available ambient monitoring data as stated on page 5-24 line 24), or when modeling one of the seven steps in the conventional APEX models is not likely to impact the estimation overall; for example, since the reported ratio for indoor/outdoor CO levels is close to 1 without additional indoor sources, distinguishing between in-and out door activities in the population does not seem necessary. These model simplifications then are necessary and not just convenient. It would be helpful for the reader of the REA to see a table (similar to ta ble 6-24) that lists all capacities of the APEX model for all 7 steps in one column and in a s econd column lists which steps were employed and what the assumptions were when doing so or wh y certain steps were omitted due to lack of detailed input data or because modeling was not necessary (such as when a microenvironment does not contribute to exposure differences).

Similarly, it seems that a more complex approach of estimating spatial distributions of exposure across cities might not have been possible since the density of the monitoring network and the sensitivity of instruments (with relatively high detection limits around 0.5 ppm) is not adequate to produce reliable small scale exposure surfaces for CO even in the cities with larger numbers of

monitors such as LA. Moreover most monitors – even those at micro-scale levels, would not be likely to pick up the true levels for the micro- environment of greatest concern, i.e. the roadway. Thus, using one monitor that might represent prox imity to roadway exposure best in both LA and Denver seems justified.

Yet, for the in-road micro-environment, it has to be recognized that these monitors are still removed from roadways and do not represent exposures in roadways and it might be questionable whether a factor of 2 to estimate in-roadway or closest proximity to roadways exposures is correct. Also exposures for residents very close to ro adways maybe higher in winter during stagnant air conditions a nd it is not clear whether and ho w this type of meteorology has

been taken into account. In fact , I did not understand how the weathe r data was being used in the

APEX model. This s hould be clarified.

Thus overall, the simplified approach that does not model micro-environments and uses a larger

radius and the monitor most reflective of road way exposures seems justified. What seems less well justified, given the new wealth of epidemiol ogic data, is using only adult CVD as one of the

simulated outcomes. This limits what can be taken seen as possible health effects from even low levels of CO exposure in large populations to mos tly elderly individuals, wh en it is likely that

35fetal development is affect and more than 4 mill ion children born in the US might be a sensitive subpopulation for CO effects as well. It is not easily understandable how the large differences in end-of-hour COHb levels for

individuals above 2% for both e xposure scenarios are obtained in Denver and not LA, i.e. the

26% and 56% versus 2 and 7% in Denver and 3 and 8% in LA (page 6-26); it seems that these differences depend solely on the upp er percentiles of the exposure di stributions that are higher in Denver than LA. How well these upp er percentiles are reflecting the exposure distributions in each city ofr those in the most highly exposed micro-environments when using an ambient monitoring station to estimate personal exposur es is then a question, i.e. I would like to understand better how these large di fferences are generated since th ey seem to point towards a major uncertainty in these models.

Question 6. Does the Panel have any recommenda tions regarding how the approach might be modified to better characterize the public health implications of the current standards, in light of the uncertainty associated with the simplified approach, the current data and time constraints on

this review?

It would have been helpful if the evaluation of uncertainties had not just been done qualitatively but been accompanied by some data on how mode ling specifications would change be changing the estimates. Having at least some quantitative da ta for one or two of the strongest and weakest factors to calibrate our judgme nts against would have helped understand the magnitude of their impacts and consolidated the qua litative judgments presented.

36

### Dr. Paul T. Roberts

Revised Comments on 1 st draft REA

Air Quality Considerations (Chapter 3), REA Ch arge Question 1: Does the Panel find the considerations of current ambient CO monitoring data and the discussi on of the extent to which near roadway concentrations are repre sented to be technically sound, clearly communicated, and approp riately characterized?

I think EPA did a very good job on the summary and presentation of the ambient CO data and the near-roadway data; however, I have some concerns about the classification of the ambient data from the sites in Denver and LA, and thus th e use of that data as ‘near-road’ in the model in Chapters 5 and 6. My comments on this follo w. In addition, I have a few minor comments and some suggested minor edit; these are included at the end.

I am still concerned about the characterization of the selected LA and Denver sites as ‘near road’, which then sets-up the base for the 2-mircroenvironmental model used in Chapters 5 and 6. The text on page 3-16 (correctly) states that current CO monitors are located near roads of moderate traffic (<100,000 AADT), but, in fact, the sites with the highest CO concentrations are really at the very low end of the moderate traffic range, at best; 10,000-17,200 AADT for Denver and 35,000 AADT for LA (see text at page 5-25, lines 11-20). In addition, the LA site is 350 m from the 35,000 AADT freeway, well outs ide the recommended range for micro-scale

CO monitors of 2-10 meters (EPA monitoring guidance, 40 CRF Part s 53 and 58; ref below) or for the proposed NO2 near-roadway mon itors of 50 meters (Proposed NO2 NAAQS Factsheet, ref below).

In addition, there are a couple more references to illustrate characte ristics of ‘near-road’ monitoring locations, including:

- http://www.fhwa.dot.gov/environmen t/airtoxicmsat/p rotocol.htm Detailed Monitoring protocol for the U.S. 95 Settlement Agreement, June 12, 2006 by Battelle for FHWA....should only consider lo cations with freeway traffi c of at least 150,000 AADT

- http://www.epa.gov/air/nitr ogenoxides/pdfs/20090722fs.pdfProposed NO2 nearroadway monitoring locations “...A sec ond monitor would be required near a major road in areas with either: (1) population gr eater than or equal to 2.5 million people, or (2) one or more road segment with an annual average daily traffic (AADT) count greater than or equal to 250,000 vehicles. .....EPA also is pro posing specific criteria for siting new NO 2 air quality monitors near major ro ads. These include identifying road segments ranked with the highest traffi c levels by AADT and identifying locations where the highest peak concentrations of NO 2 are expected to occur, and placing monitors no more than 50 meters (about 164 feet) away from the edge of the nearest

traffic lane.”

- EPA monitoring site guidance suggests th at microscale (stree t canyon or traffic corridor) sites be located 2-10 meters from th e edge of the nearest traffic lane (40 CFR Parts 53 and 58, October 17, 2006, page 504,

37http://www.epa.gov/ttn/amtic /files/ambient/pm25/092706sign.pdf Note that this is a link to the final, but not the published versio n; I can’t seem to find that version on the EPA/AMTIC web site)

Page 5-25, lines 20-23: This statement attributed to Rode s et al. (1998) is not supported by the text or tables in that report, especially due to the poor detection limit of the CO monitors used

both in the vehicles and for roadside and ambi ent CO measurements. See, for example the comments on page 146 of Rodes et al., 1998 rega rding in-vehicle CO (“The relatively low levels of CO currently found in commuti ng California vehicles posed a significant measurement problem for portable monitors with a MQL of 2 ppm”) and on page 140 for ambient and roadside monitors (“ The very lo w concentrations measured at both ambient and roadside sites were consistently below th e MDL of the study monitors. This makes it impossible to draw conclusions about the predicti ve relationships for CO.”). By the way, based on data for other pollutants for which they had be tter detection, they make the statement that “Roadside pollutant measurement provided signif icantly better indications of in-vehicle pollutant concentrations than did ambient sites, but were still low by factors of 2 or more [for] many commuting scenarios.” Rodes, et al., 1998, bottom of page 150. Given these qualifications in the published report, I am not su re that these data shou ld be relied on strongly for the conclusions using Table 5-2, for example.

Characterization of Exposure (Chapters 5 and 6): The following comments are in regard to the usefulness of the simpli fied approach to exposure asse ssment...and on the relative merits of alternatives or modifications to this approach, in light of uncertainties and

limitations of timefor this review.

38Overall, I am concerned about the decision to take the CASAC Panel comments regarding the inadequacy of the monitoring da ta to represent the spatial extent of human exposure (REA, page 1-5, lines 15-19, Brain and Samat, 2009) so seriously that EPA st aff did only a draft, screening-level analysis around one site in each of two cities. I thought that those comments would influence EPA to develop an adaptive appr oach using monitoring data and GIS, traffic count data, etc., or some other method, such as land-use regression, to estimate the spatial variability of exposures, similar to what is me ntioned on page 3-11, lines 15-17. Note that this more-detailed analysis is what is often done for the exposure analysis for many health studies (see, for example, publications from the Child ren’s Health Study such as Gauderman, Avol, Lurmann, Kuenzli, Filliland, Peters, and Mc Connell “Childhood Asth ma and Exposure to Traffic and Nitrogen Dioxide, Epidemiology 2005; 16, 737-743). I did not expect EPA to perform only a simple, two-microenvironment m odel for exposure with just one environment represented by monitoring data and one in-trans it microenvironment. It seems like this approach places all of the vari ability in exposure on the variou s parameters associated with individuals and none of the variability on the ac tual ambient concentrations to which those individuals might be exposed (as summarized in Table 6-24, plus the un certainties summarized in Table 6-25). So my question becomes: does the range of CO concentration represented by

the ambient and in-transit microenvironments and the assumed time of exposure in those microenvironments properly represen t the true exposures? I am not su re that this is the case. It seems to me that this draft, screening-level asse ssment is a good first step, but I would prefer to see a follow-on, more-detailed analysis to be confident in the results, or a convincing discussion that these properly represent the variabilities and uncertainties of the actual

exposure.

Based on the discussions during th e meeting, and the available time to complete this review, my comments and recommendations are as follows:

- I do not agree with the comments on page 6-13, lines 30-35 and continuing on page 6- 14, lines 1-2. As stated above, although th ese monitoring sites are the best available ones, they do not properly represent the exposure near busy roadways in LA or probably in Denver (I don’t have the data on traffic on other roadways in Denver, so can’t make as specific comments as I can about LA). See my comments above on the level of traffic on the roadways near these sites, which are way below busy roadways in LA (less than 10,000-35,000 versus the 150,000 plus on many other roadways in the LA area. Also, as mentioned above, these sites are actua lly not very close to the roadways; they should be 2-10 or maybe up to 50 meters from the edge of the roadway to properly represent near-roadway concentratio ns. Even given that the suspected zone of influence may be much larger during ni ghttime or low-wind conditions, monitoring

sites need to be close to represent the daytime period.

39- The simplest approach, given this late data and the time still available to finish this review, would be to run some cases as sensi tivity runs of the mode l with an additional microenvironment to better represent near -roadway exposures. For example, maybe use the measured ambient data to represent data beyond 300 meters, use the ambient data increased by a multiplier from the literature, and then use the in-vehicle multiplier, such as 2 used in the current draft REA, to increase the near-road value to represent the in-vehicle concentration. However, give n that the selected LA and Denver sites probably represent something closer than the 300 meter ‘urban background’ from papers such as Zhu et al., 2002, maybe the fact or should not be as la rge as the factor of 10 from the Zhu et al., 2002 paper (see disc ussion on page 3-10, lines 19-29). Staff could review the various LA papers (Zhu et al, 2002; Zhu et al., 2006; papers by the Sioutas group at USC, plus others) and select a ratio less than 10. I recognize that some of these papers do not have CO data, but they have data for other primary vehicle pollutants which can support the selection of a ratio. Also, there is not similar literature data for Denver, but I think the general drop- off in concentrations for LA can be used for Denver. Maybe this approach could be implemented as scenario C, in order to compare with the A and B scenarios. Us ing this approach would result in higher numbers of person-days at specific CO con centrations levels, compared with numbers

for scenarios A and B in the “As Is” columns of Tables 6-8 to 6-14, and thus illustrate the results for a full range of exposures with more-realistic near-road exposure

conditions.

The in-vehicle to near-road ratios suggested (2, for the model) are reasonable. However, there

is additional literature which could be added to Table 5-2, Page 5-20. For example, I am not sure why recent California ARB papers are no t included here? Papers such as those by Westerdahl (2005) and Frui n (2008) could be included.

My comments regarding the characterizations of uncertainty, as repres ented in Table 6-25 and surrounding text, for example, are as follows:

- Although I do agree that the CO exposures ar e over-estimated for MOST individuals, I believe that CO exposures are actually underestimated for the large fraction of individuals who live or work or go to school near roadways and spend significant time commuting. See my earlier comments on my reasons and potential ways to address

this.

- I think that the most significant uncertainties from this table could be better quantified by using sensitivity runs of the model. Sensitivity runs might include variations in the fractions of individuals living, etc. clos e enough to a major roadway to receive the higher, near-road concentration in scenario C, for example, and variations in transit time that would represent longer peri ods of exposure to the in-vehicle

microenvironment.

40Additional detailed comments:

Page 1-2, lines 3-6: Several places in the REA, a previ ous report is mentioned, such as this NRC report. It was really help the reader if a one or two sentence summary were also provided. Other places include page 1-4, lines 25-27, page 5-2, lines 18-19,

Page 3-3, lines 7-16: In this discussion, it is implied that the trace-le vel monitors are needed for exposure analysis at current CO concentrat ion levels, but it would be better to state it directly, possibly at the beginning of the list of reasons on lines 12-16.

Page 3-3, lines 19-29: The ISA text (page 3-20, for exam ple) used the term LOD while the REA uses MDL; please be consis tent or explain the difference. Also, Table A-1 in the ISA

listed MDL for the trace-level monitors as 0.02 (there are no 0.04 MDLs lis ted), so delete the

reference to 0.04 MDLs in lines 25 and 29. Also provide the reference in the ISA for all this.

Page 3-10, line 26: Modify to read “...greater than measurements taken at...” since they used

one set of monitors and moved them around to re present concentrations at all distances, not separate monitors at each distance from the roadway. Note that this means the measurements

at different distances ar e not at the same time.

Page 3-11, lines 13-17: Note that this more-detailed anal ysis is what is often done for the exposure analysis for many health studies; see, for example, publications from the Children’s Health Study such as Gauderman, Avol, Lurm ann, Kuenzli, Filliland, Peters, and McConnell “Childhood Asthma and Exposure to Traffic and Nitrogen Dioxide, Epidemiology 2005; 16,

737-743.

Page 4-3, lines 22-23 and 31-32: It seems like these two statemen ts are contrary to each other; please explain. How can the data be insufficien t for a dose-response relationship but one could confidently attribute a COHb dos e level to a CO exposure?

Chapter 5, sections 5.1-5.3 on the APEX model: This is a great discussion of the model’s capabilities; however, I would lik e to see an emphasis on those capabilities that are actually used in this analysis; maybe a s hort section with a list of what is used here would help. [ I see in a few places where the text says that this cu rrent aspect is not used, but a summary at the end would be much better and help the reader recognize what is used in one place].

Minor edits and typos in the 1 st draft REA:

- Page iii: The title for Figures 5-1, 5-2, and 5-3 are duplicated in the List of figures.

- Page 2-1, lines 4-6: this part of the introductory sentence is quite awkward.

- Page 2-2, line 14: us e “are also important”

- Page 2-2, line 19: delete “on”.

- Page 3-2, line 3: the details for footnote 2 are missing.

- Page 3-10, line 31: insert a comma after estimates.

- Page 3-11, line 12: Make end of line read “(draft ISA, Figure 3-17)”.

- Page 4-2, line 3: add the da tes for the reference (1989a, 1989b).

41- Page 4-2, line 29: it would r ead better if the word “decreas e” were inserted after “and”.

- Page 5-16, line 11: I think this reference should be draft ISA, page 3-98, Figure 3-43.

- Page 5-21, line 24 and 5-22, line 1: this should be Table 5-3.

- Table 6-25, page 6-38: please include the footnote regarding INF and KB on all 3 pages of the table.

Additional references:

Zhu Y, Kuhn T, Mayo P, Hinds WC. Comparis on of daytime and nighttime concentration profiles and size distributions of ultr afine particles near a major highway. Environmental Science & Technology 2006;40(8):2531-2536.

. Westerdahl, et al (2005). Mobile platform measurements of ultr afine particles and associated pollutant concentrations on freeways and reside ntial streets in Los Angeles, Atmospheric Environment ISSN 1352-2310, 2005, vol. 39, n o 20, pp. 3597-3610

Fruin, S.A., Westerdahl, D., Sax, T., Fine, P.M., Sioutas, C. Meas urements and predictors of in-vehicle ultrafine particle concentrations a nd associated pollutants on freeways and arterial roads in Los Angeles. Atmospheric Environment, 42(2):207-219, 2008.

42

### Dr. Armistead (Ted) Russell

In general, the CO Risk and Exposure Character ization was clear and informative, and is a good start on a more comprehensive REA. I think it begins to provide a foundation for the coming policy assessment to link potential primary standard s to potential health effects. On the other hand, it was a bit disappointing.

The major disappointment had to do with how the exposure modeling was done in that it appears to be a step backwards from what was done in th e last CO review, and th e current analysis is biased. I would prefer taking an approach that is unbiased (or at least less needlessly biased), and individuals can interpret the results and add their individual amount of conservatism later in the process. Specifically I refer to using the highest monitor in th e region, with a 20 mile impact radius, rather than a number of monitors each with a smaller area-of-influence. Using the highest monitor leads to the grea test modeled exposures, one that is likely biased high. Using multiple monitors reduces this bias. I was also disappointed by not using indoor sources in the modeling. Thus, the prior modeling was more co mprehensive and informative. It would be better to provide less biased estimates and an assessment of the uncertainties. I was glad to see both the prior and current results provided. A question that came to mind is whether APEX has changed in such a way as to significantly impact the model results. If not the prior results may be more informative. If so, the degree to wh ich model changes have impacted results should be

discussed.

One problem with presenting the results as COHb levels is that it was not easy to assess the severity of the exposures with likely health ou tcomes, and the document was weak on this issue as well. What are the likely hea lth ramifications of COHb levels of 1.5, 2, 3 or possibly higher? How does this interplay with COHb levels at thos e levels to a given frac tion of the population? The discussion on pages 6-42/43 need to be more informative on this issue. This is both a risk and exposure document, and there should be more on what are the likely risks. It would be

valuable to have a succinct discussion of the likely current risks from CO exposure nationally. That brings up an additional need is how the an alyses for LA and Denve r relate to risks and exposures nationally. The analysis done as part of the PM Risk Assessment was effective in this direction (Chapters 4 and 5 of the RA for PM... though that document would benefit from a Chapter 6 integrating them.)

I would also have appreciated ex amining other potential standards if changes are to be made. The current analysis suggests th at there are potential exposures of concern (using COHb cutoffs of 2.0% or so), but there is no information as to how the fraction of potential exposures will respond to lower ambient CO levels reflecting tighter standards.

I also note that, like NO 2 , the highest exposures to CO will like ly happen in-vehicle or near to the road. If a near-road network monitoring network is to be developed, the maximum ambient levels observed will likely increase, and the in -vehicle-ambient monitoring relationships will likely change, possibly dramaticall y. This should be explored here . The information available in making the policy assessment should provide the needed risk and exposure characterization to

43adequately inform the determination of a standa rd if a new network design were to be put in place.

In summary, this is a solid start. I am glad to see the exposure mode ling, though it should have been more realistic (use more monitors, larger area, similar to, or preferably beyond that done in 2000). Next, if a change in standards is envisi oned, this document should evaluate how a such a change might impact exposures. Without such, an important part of the foundation for future action is missing. Third, if there is going to be a change in the monitoring network,, the REA should assess the implications of such a change.

In response to the Charge Questions:

1. Air Quality Considerations

This discussion is fine.

2. Selection of Health Endpoints, etc.

2.1. Health endpoint... sound, clear and appropriate?

2.2. Does the range of benchmark reflect the ISA

2.3. Is the derivation of COHb levels sound, clean, appropriate.

3. Characterization of exposure

3.1. Relationship between in-vehicle and am bient ... sound, clear and appropriate? While the approach taken is clearly communicat ed and well characterized, it is somewhat over simplified. The in-vehicle and ambient concentra tion data relationship is variable, and it a more comprehensive treatment of this variability would be appropriate. Given the isse of using just the highest monitor for CO concentr ations, there is a potential for hidden bias in that the studies upon which the factor is based typica lly relate in-vehicle data to a central site monitor, not the highest central site monitor. As noted in the REA, there is also the issue of vehicles having much higher CO emissions at the time of the studies mentioned than are typically present today. The potential for being near a high emitting vehicl e was greater, leading to an excessively, and unrepresentatively for present conditions, high CO level in the vehicle. The biggest concern, here, however, is that the ratio of two is taken using three loca tions that do not represent the highest CO levels in the area.

3.2. Approach taken As might be evident from the above, there is li kely unexplored bias in the approach taken. I would prefer using methods w ithout such bias built in.

3.3. Exposure analysis ... sound, clear and appropriate? The exposure modeling is well laid out, clear, and given the assumptions made, using an appropriate approach. However, it is disappointing to see that th e prior REA was done in a way I think is better, with less built in bias, and able to better catch the distri bution of exposures.

3.4. Adequacy of the assessment of uncertaint y and variability? Sensitivity analysis? The first sensitivity analysis I would conduct is to use a variety of CO monitors in the analysis, e.g., similar to what was done in 2000 as part of the prior REA. Second, I would, if possible, do a head-to-head comparison of the models used in 2000 and this time. A third sensitivity

44analysis should assess how concentrations that would be measured near the road would be

reflected in a simulated in -vehicle concentration.

3.5. How does the simplified approach help?

3.6. Recommendations regarding how th e approach might be modified?

Additional Comments:

2-2/23 Make sure we use susceptibility and vu lnerability consistently between documents. (I personally like the distinction, but recognize so me do not because of the ambiguities.) 3-3: Define GFC (I did not im mediately see it defined, above) 3-3/29 Replace below with “better than”

3-4/21: The number of stations belongs further up, e.g., Page 2-1 or 2-2, as part of the network description.

3-12: How much does the PRB contribute to COHb? If it is straight forward to calculate, that might be of interest.

45

### Dr. Anne Sweeney

REA Charge Questions 5-6, Chapters 5 and 6

1. Page 5-14, lines 33-34. This may present a problem, as many people commute long
distances from their homes, and may experien ce a change in air quality over the route.

E.g., in a ranking of large cities (with populations of 250,000 or more), New York (38.3 minutes); Chicago (33.2 minutes ); Newark, N.J. (31.5 minutes); Riverside, Calif. (31.2 minutes); Philadelphia (29.4 minutes); and Los Angeles (29.0 minutes) had among the nation’s highest average commute times. Th e average two-way commute distance in Los Angeles is 29.8 mileshttp://www.census.gov/PressRelease/www/releases/archives/amer ican_community_survey_acs/004489.html (http://www.zevnet.org/car_sum mit/01%20Summit_Recker.pdfay)

2. The simulated population was assigned age and gender distributions to be representative
of the target population. However, there is no mention of active or second hand smoking
status, which would greatly influence the st udy results. Consideration of at minimum
second hand smoke exposure is recommended.

4647 

### Dr. Stephen Thom

RISK AND EXPOSURE ASSESSMENT – FIRST DRAFT:

Charge questions:

Air quality considerations (Chapter 3)

I found the discussion clear and appropriate.

Selection of health endpoints, etc (Chapters 2 and 4, Sections 5.3.7 and 6.2)

Rationale for selecting health effects benc hmark values of 1.5, 2.0, 2.5 and 3.0 %: Research supports - and the ISA states - that there is no threshold for CO mediat ed health effects. I recognize that benchmark values had to be chosen to satisfy pragmatic needs. The choices were arbitrary but logical given the rang e of exposures in controlled h ealth effects studies. Moreover,

use of these levels in the modeling charts (e.g. Tables 6- 12 and 6-13) was useful for demonstrating the small portion of the population at risk.

Characterization of Exposures (Chapters 5 and 6)

The history of the EPA’s human exposure and dose model (APEX) is clear. The additional discussion on microenvironments and especia lly the importance of indoor and in-vehicle exposure assessments was also logical but leads to a rather fundamental question. Does the emphasis/concern pertaining to microenvironments render APEX unusable or are there data for CO uptake and elimination patterns relevant to indoor and in-vehicle environments ( e.g. activity estimates which influence uptake, etc.)?