UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

WASHINGTON D.C. 20460 

 

OFFICE OF THE ADMINISTRATOR 

 SCIENCE ADVISORY BOARD 

April 20, 2010 

EPA-CASAC-10-009 

The Honorable Lisa P. Jackson 

Administrator 

U.S. Environmental Protection Agency 

1200 Pennsylvania Avenue, N.W. 

Washington, D.C. 20460 

Subject: CASAC Review of Particulate Matter Urban-Focused Visibility 

Assessment – Second External Review Draft (January 2010) 

Dear Administrator Jackson, 

The Clean Air Scientific Advisory Committee (CASAC) Particulate Matter (PM) 

Review Panel met on March 10–11, 2010 to review the Quantitative Health Risk 

Assessment for Particulate Matter – Second External Review Draft (February 2010) and 

Particulate Matter Urban-Focused Visibility Assessment – Second External Review Draft

(January 2010). In this letter, CASAC offers general comments on the Particulate 

Matter Urban-Focused Visibility Assessment, followed by our consensus responses to the 

Agency’s charge questions. Comments from individual panelists are also enclosed. 

CASAC was favorably impressed with the quality and clarity of the second draft 

Particulate Matter Urban-Focused Visibility Assessment (UFVA). As we indicated in our 

letter of November 24, 2009 regarding the first draft of the UFVA, CASAC strongly 

supports the introduction of a new PM light extinction indicator for a secondary standard 

to protect against adverse effects on visibility. We concur with an hourly averaging time 

as the most appropriate to represent the nearly instantaneous nature of human perception 

of impaired visibility. We also agree with the 20 to 30 deciview (dv) range of light 

extinction levels as a reasonable representation of the levels of visibility impairment 

considered acceptable based on currently available studies. 

The UFVA presents logical and persuasive arguments for use of a PM light 

extinction indicator, with a 1-hour (daylight) averaging time as a sound basis for a 

secondary PM standard to protect urban visibility. The UFVA also presents and evaluates 

reasonable ranges for the level (20 to 30 deciviews) and form (90th to 98th percentile) 

that such a standard might take, and clearly illustrates the differences among the many 

resulting optional combinations of levels and forms in terms of protectiveness and/or 

stringency across the 15 diverse urban study areas selected for this analysis. The 

approaches employed here, the ranges of options considered, and the estimates of visual 

1
 

air quality resulting from the various combinations of options considered should provide 

a sound basis for more detailed consideration in the Policy Assessment. 

In addition, if the Agency is also considering options of using a PM2.5 light 

extinction indicator or a PM2.5 mass indicator as the basis for secondary PM standard, it 

would be important to see a more detailed comparison of the affected PM2.5

concentrations, species compositions and levels of visibility protection that would result 

from the use of alternative PM10 light extinction, PM2.5 light extinction or PM2.5 mass 

indicators. 

In its second draft UFVA, EPA staff were responsive to previous CASAC 

recommendations, adding a detailed logit analysis to better understand similarities and 

differences in results of the urban visibility preference studies, recalculating estimated 

extinction levels using a 90% relative humidity (RH) screen, and considering (90th, 95th 

and 98th) percentiles based on all available daylight hours as well as on the single worst 

daylight hour in each day. 

CASAC recommends the addition of an integrative summary chapter to the 

UFVA. At present, it lacks a summary that brings main findings and their implications 

together. This chapter might be included as an executive summary or as new chapter at 

its conclusion. CASAC has also identified needs for the next review cycle in terms of 

further research on a number of topics related to urban visibility; these needs should be 

assembled, highlighted and prioritized. In particular, there is a need for the Agency to 

conduct additional urban visibility preference studies over a broad range of urban areas 

and viewing conditions, to further evaluate and refine the range of visibility levels 

considered to be acceptable in the current assessment. 

We thank the Agency for the opportunity to provide advice on the UFVA, and 

look forward to continued discussions with the Agency as we review the first draft Policy 

Assessment for the Review of the Particulate Matter National Ambient Air Quality 

Standards (March 2010). 

Sincerely, 

 /Signed/ 

Dr. Jonathan M. Samet 

Chair 

Clean Air Scientific Advisory Committee 

Enclosures A: CASAC Particulate Matter Review Panel Roster 

 B: CASAC Responses to Charge Questions 

 C: Individual Panelists’ Responses to Charge Questions 

2
 

Enclosure A

Clean Air Scientific Advisory Committee 

Particulate Matter Review Panel 

CHAIR 

Dr. Jonathan M. Samet, Professor and Chair, Department of Preventive Medicine, 

University of Southern California, Los Angeles, CA 

CASAC MEMBERS 

Dr. Joseph Brain, Philip Drinker Professor of Environmental Physiology, Department of 

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

MA 

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

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

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

Rosemont, IL 

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

Engineering, Georgia Institute of Technology, Atlanta, GA 

Dr. Helen Suh, Associate Professor, Harvard School of Public Health, Harvard 

University, Boston, MA 

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

NY 

CONSULTANTS 

Dr. Lowell Ashbaugh, Associate Research Ecologist, Crocker Nuclear Lab, University of 

California, Davis, Davis, CA 

Prof. Ed Avol, Professor, Preventive Medicine, Keck School of Medicine, University of 

Southern California, Los Angeles, CA 

Dr. Wayne Cascio, Professor, Medicine, Cardiology, Brody School of Medicine at East 

Carolina University, Greenville, NC 

Dr. David Grantz, Director, Botany and Plant Sciences and Air Pollution Research 

Center, Riverside Campus and Kearney Agricultural Center, University of California, 

Parlier, CA 

3
 

Dr. Joseph Helble, Dean and Professor, Thayer School of Engineering, Dartmouth 

College, Hanover, NH 

Dr. Rogene Henderson, Senior Scientist Emeritus, Lovelace Respiratory Research 

Institute, Albuquerque, NM 

Dr. Philip Hopke, Bayard D. Clarkson Distinguished Professor, Department of Chemical 

Engineering, Clarkson University, Potsdam, NY 

Dr. Morton Lippmann, Professor, Nelson Institute of Environmental Medicine, New 

York University School of Medicine, Tuxedo, NY 

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

Health, Harvard University, Boston, MA 

Dr. William Malm, Research Physicist, National Park Service Air Resources Division, 

Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort 

Collins, CO 

Mr. Charles Thomas (Tom) Moore, Jr., Air Quality Program Manager, Western 

Governors' Association, Cooperative Institute for Research in the Atmosphere, Colorado 

State University, Fort Collins, CO 

Dr. Robert F. Phalen, Professor, Department of Community & Environmental Medicine; 

Director, Air Pollution Health Effects Laboratory; Professor of Occupational & 

Environmental Health, Center for Occupation & Environment Health, College of 

Medicine, University of California Irvine, Irvine, CA 

Dr. Kent Pinkerton, Professor, Regents of the University of California, Center for Health 

and the Environment, University of California, Davis, CA 

Mr. Richard L. Poirot, Environmental Analyst, Air Pollution Control Division, 

Department of Environmental Conservation, Vermont Agency of Natural Resources, 

Waterbury, VT 

Dr. Frank Speizer, Edward Kass Professor of Medicine, Channing Laboratory, Harvard 

Medical School, Boston, MA 

Dr. Sverre Vedal, Professor, Department of Environmental and Occupational Health 

Sciences, School of Public Health and Community Medicine, University of Washington, 

Seattle, WA 

SCIENCE ADVISORY BOARD STAFF 

Dr. Holly Stallworth, Designated Federal Officer, EPA Science Advisory Board Staff 

Office 

4
 

NOTICE 

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

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

provide extramural scientific information and advice to the Administrator and other 

officials of the EPA. CASAC provides balanced, expert assessment of scientific matters 

related to issues and problems facing the Agency. This report has not been reviewed for 

approval by the Agency and, hence, the contents of this report do not necessarily 

represent the views and policies of the EPA, nor of other agencies within the Executive 

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

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

posted on the EPA Web site at: http://www.epa.gov/casac. 

5
 

Enclosure B 

CASAC Responses to Charge Questions 

1) In general, what are the Panel’s views on the level of detail provided in the body 

of the report and associated appendices? Does the Panel agree that all of this 

information is useful to retain or is there material that the Panel would recommend 

deleting? Does the Panel have any suggestions regarding the organization and 

distribution of information throughout the document and in the appendices? 

While a substantial level of detail has been provided in the UFVA, many of the 

calculations included therein are complex, and a wide range of optional combinations of 

levels and forms is presented and compared. The report is long, but its completeness and 

detail are useful, particularly given that we are looking, for the first time, at a very 

different indicator for this secondary standard. The discussion is clear, and the associated 

appendices are valuable for examining questions raised by the main text. The CASAC 

would not recommend deleting any of the material. With the few exceptions noted below, 

the organization is good as it stands, both in the main body of the report and in the 

appendices. 

Chapter 2 may contain more information than is required with respect to the individual 

cities. Much of this material could be moved to the appendices. The memo of 2/3/2010 

on the statistical analysis of the preference studies should also be placed in the 

appendices, and consolidated with related material from Chapter 2 to avoid redundancy. 

Similarly, much of the material in sections 4.1.3 and 4.1.4 might be better suited to an 

appendix. In any case, the transition into future monitoring site characteristics (middle of 

page 4-2) is rather abrupt, and might be more appropriate for inclusion in the Policy 

Assessment, where it could be expanded based on recent feedback from the CASAC 

Ambient Air Monitoring and Methods Subcommittee. 

The SANDWICH method described in Chapter 3 does not include sea salt, which can be 

an important contributor to PM at coastal sites. The sea salt component of PM may be a 

source of uncertainty in the light extinction calculation at these sites. The SANDWICH 

approach has other sources of uncertainty that should be mentioned. Relying on mass 

closure to determine the hourly organic carbon assumes that all other species are 

accurately determined. This is problematic for nitrate, as well as for sea salt. These 

factors should be mentioned as areas of uncertainty that are associated with this method. 

2) In the Panel’s view, to what extent does the logit analysis presented in Chapter 2 

of the second draft Visibility Assessment, and further expanded and described in the 

supplemental memorandum, add value to the urban visibility preference study 

analysis and provide additional support for combining and comparing the results 

from the four cities, as shown in Figure 2-16? What are the Panel’s views on the 

clarity and adequacy of the descriptions associated with such a combined 

assessment and on the conclusions that can be drawn from the assessments? Please 

6
 

provide comments on any additional insights that might be drawn from these 

analyses or on any additional caveats that should be considered. 

The analysis presented in Section 2.6 and summarized in Figure 2-16 is quite reasonable. 

The characteristics of the studies that produced the data are discussed. The modeling 

approach is clearly presented and explained, with an appropriate level of detail, given that 

this approach has not been previously described in EPA visibility documents. Figure 2-16 

is very useful for comparing the four realizations of the model in comparison to the study 

data. Table 2-3 provides valuable information regarding the statistical significance of 

each model coefficient. The results in Table 2-3 are appropriately explained. The model 

is appropriately critiqued in terms of goodness-of-fit, statistical significance of the 

coefficients, and the interpretation of the coefficients. The limitations of the model with 

respect to limitations of the underlying data are appropriately discussed. 

The text does a good job of identifying limitations associated with the sample population 

in the UBC study (all participants were university students and therefore had advanced 

educational background), and discusses the broader socioeconomic distribution of the 

population participating in the Phoenix study. Absent is a comparable discussion of the 

demographic distribution in the second Washington DC study, other than noting the 

relatively small size of the sample population, and limitation that all participants were 

employees of the research firm conducting the study. It is therefore likely that all 

participants were well educated, and may have understood the methods and goals of the 

study better than the populations participating in the other studies. Since this is a 

preference study, this point is worth acknowledging in the text. 

The additional information presented in the supporting memo by Stratus Consulting is 

very helpful and should be retained as an attachment or in an appendix. The memo 

evaluates several alternative specifications of a logit model, of which the one presented in 

the assessment is Model 2. Confidence intervals on the predicted mean were estimated 

using a numerical method, and verified with another numerical method. Models 1 and 2 

are generally found to provide similar results. Thus, the results of the assessment are not 

substantially sensitive to the choice in functional form between these two models. 

Overall, the use of the logit model is reasonable, since the output is a binary variable. 

The model is appropriately evaluated and reasonably represents the data to which it was 

fit. The limitations of the underlying data are discussed qualitatively. The overall 

findings are reasonably supported by the data, model, and appropriately take into account 

limitations of the data. The associated discussion presents a number of reasonable 

hypotheses that could account for the significant differences in the acceptability response 

curves among the different cities, and could explain why some of the study results have 

greater variability than others. 

While it is appropriate to move forward on the basis of available data, CASAC believes 

the data suggest some heterogeneity that needs to be explored with further research, 

especially to evaluate potential differences among regions or among cities that have 

different inherent scenic characteristics. The need for additional urban visibility 

preference studies, using consistent and robust survey methods, over a broader range of 

7
 

urban areas and viewing conditions, should be emphasized as a research priority. The 

results from these studies could help refine a secondary PM light extinction standard in 

future NAAQS review cycles. 

 

3) What are the Panel’s views on the extent to which the analysis of the frequency of 

co-occurrences of hourly relative humidity values below and above 90 percent with 

other meteorological events such as rain or fog (Chapter 3, section 3.3.5; Table 3-6) 

provides scientific support for consideration of how to address relative humidity in 

defining the form of a standard based on a PM light extinction indicator? 

An informative, new analysis was presented in section 3.3.5 (as revised by the 3/4/10 

memo from Philip Lorang and Mark Schmidt to the PM NAAQS Review Docket) 

comparing hourly daytime relative humidity (RH) and the incidence of natural weather 

visibility-impairing conditions (fog, rain, snow, etc.). CASAC concurred that this 

presentation provided a persuasive argument for the use of a 90% RH screen as an 

effective and efficient way to discard most of the hours potentially affected by natural 

weather conditions while removing only a small fraction of total daylight hours from 

consideration. 

CASAC also found that a 90% RH screen was not only a logical revision for use in the 

UFVA assessment, but would also be an appropriate component of a new secondary 

NAAQS based on PM light extinction. It would be an effective way to remove periods 

when weather influences might be the dominant cause of visibility impairment from the 

regulatory metric, and would also have other benefits relating to PM light extinction 

measurements, such as accommodating spatial variability in RH and weather influences, 

minimizing effects of RH measurement errors at high humidity, and allowing for 

measurement modifications (such as a “smart heater” on a nephelometer) that could 

substantially reduce instrument maintenance needs and improve data quality. 

4) In response to CASAC recommendations, descriptions of current conditions and 

results of just meeting NAAQS scenarios that considered all daylight hours were 

added to those based on maximum daily 1-hour indicators. The 98th percentile form 

was also included along with the 90th and 95th percentiles. Tile plots of hourly PM 

light extinction (Figure 3-12) and composition bar graphs of the top 10% of days for 

maximum daily 1-hour and aggregated individual daylight hours (Figure 3-13) were 

shown in part to help illuminate the similarities and differences between these 

various indicators with respect to current conditions. Similarly, additional figures 

and table entries were generated to illustrate the characteristics of various PM light 

extinction NAAQS scenario forms (Tables 4-2, 4-3, 4-5, and 4-7; Figures 4-1 through 

4-3). 

What are the Panel’s views regarding EPA staff interpretations of these displays 

included in the text? Are there supplemental or alternative interpretations the Panel 

would suggest? Are there additional approaches the Panel would suggest regarding 

ways to summarize, display, or assess the results of these analyses, including 

similarities and differences between the various scenarios? 

8
 

9

The revisions to accommodate the 90% RH screen, the inclusion of a higher (98th) 

percentile form, and consideration of an alternative way of calculating percentiles – based 

on all daylight hours, rather than just the worst hour in a day – were valuable additions to 

the UFVA. When these are combined with other options including 90th and 95th 

percentiles and different levels (64, 112, 191 Mm-1) of PM light extinction, the many 

resulting options are complex and difficult to communicate and compare. The various 

new graphical displays are quite helpful in communicating this complex new information 

clearly and illustrating the differences and similarities among the many options. 

CASAC found that the tile plots were especially informative and greatly helped to show 

the seasonal and diurnal patterns and similarities and differences across the different 

study areas. The stacked bar charts of maximum hourly extinction on top 10% days vs. 

compositions on top percentiles considering all daylight hours are useful for seeing 

differences between cities, and the accompanying interpretation and discussion are 

reasonable and informative. The plots also illustrate interesting differences in hourly 

compositions within individual cities for the (relatively few) hours which represent the 

single worst hours in a day. However, these comparisons do not really allow for a direct 

“apples vs. apples” comparison of the effect of calculating percentiles based on the single 

worst daylight hour each day, vs. using all daylight hours to calculate the percentiles. 

It seems likely that the two optional approaches may tend to focus on different kinds of 

visibility impairing PM species, sources, meteorological conditions, times of day, and/or 

seasons. It would be useful to have a clearer picture of what their similarities and 

differences really are before recommending one approach over the other. Additional 

suggestions on approaches for this are included in comment from individual panelists. 

Several panelists also expressed concerns that some of the occasionally very high coarse 

particle contributions in a few of the cities (St. Louis and Los Angeles) appeared 

questionable, and might benefit from closer scrutiny or warrant some cautionary language 

in the UFVA. 
 

Enclosure C 

Compendium of Individual Preliminary Panelists Comments 

Urban-Focused Visibility Assessment for Particulate Matter (January 2010) 

Comments from Dr. Lowell Ashbaugh....................................................................................... 2

Comments from Dr. David Grantz.............................................................................................. 8

Comments from Dr. Philip Hopke ............................................................................................ 10

Comments from Mr. Rich Poirot .............................................................................................. 12

1
 

Comments from Dr. Lowell Ashbaugh 

January 2010 2nd External Review Draft Particulate Matter Urban-Focused Visibility 

Assessment, 

Charge question 1

1) In general, what are the Panel’s views on the level of detail provided in the body

of the report and associated appendices? Does the Panel agree that all of this

information is useful to retain or is there material that the Panel would

recommend deleting? Does the Panel have any suggestions regarding the

organization and distribution of information throughout the document and in the

appendices?  

The report contains a lot of detail, but it is presented well. The discussion is clear and the 

associated appendices are valuable for examining questions raised by the main text. I 

would not recommend deleting any of the material. The organization is good, both in the 

main body of the report and in the appendices. I have some comments on the presentation 

of material that I’ll put later in this review. 

The introductory material is excellent. It’s short, but it’s complete and it lays the 

foundation for review of the NAAQS. The overview of the science of visibility and PM 

might be too brief for readers new to the field, but the references are sufficient to fill in 

the details. 

 Charge question 2

2) In the Panel’s view, to what extent does the logit analysis presented in Chapter 2

of the second draft Visibility Assessment and further expanded and described in

the supplemental memorandum add value to the urban visibility preference study

analysis and provide additional support for combining and comparing the results

from the four cities, as shown in Figure 2‐16? What are the Panel’s views on the

clarity and adequacy of the descriptions associated with such a combined

assessment and on the conclusions that can be drawn from the assessments?

Please provide comments on any additional insights that might be drawn from

these analyses or on any additional caveats that should be considered.  

The logit analysis is important to this assessment. It provides a common basis to analyze 

the results from the four studies in different cities and it sets forth a quantitative method 

to establish boundaries on the CPL levels. The discussion of the hypotheses that might 

explain the different VAQ acceptability responses is clear. There may be other factors 

involved in the differences between cities, but it would take more research to confirm or 

refute them. For example, one hypothesis that was not discussed is the possible 

differences in population that inhabits the different cities that makes them more or less 

sensitive to VAQ. Denver and BC are known for their outdoors activities; people who 

live there may be more attuned to the visual environment and more sensitive to poor 

VAQ. People living in Washington, DC may be less attuned to the outdoor environment 

and therefore less sensitive to poor VAQ. 

Page 2-31 suggests that additional studies would be useful to gain further understanding. 

Are there plans for such studies? Is there an outline or more comprehensive listing of the 

2
 

studies that would be useful? Such a list or discussion would be very useful if funding 

becomes available at some time in the future. 

Charge question 3

3) What are the Panel’s views on the extent to which the analysis of the frequency of

co‐ occurrences of hourly relative humidity values below and above 90 percent

with other meteorological events such as rain or fog (Chapter 3, section 3.3.5;

Table 3‐6) provides scientific support for consideration of how to address relative

humidity in defining the form of a standard based on a PM light extinction

indicator?

The analysis of the frequency of co-occurrences of rain and/or fog with relative 

humidity above or below 90 percent has a flaw in it. I don’t believe it would 

change the conclusions, but on page 3-29, lines 11-12, is the statement “Based on 

this assessment, the 90% relative humidity cutoff criteria is effective in that on 

average less than 6% of the hours are removed from consideration...” This is not 

correct. It’s correct that (except for Tacoma) less than 6% of the hours with 

RN≤90% co-occur with rain or fog. The number of daylight hours with relative 

humidity >90% and their percentage of all daylight hours is shown below (data 

extracted from Table 3-6). On average, about 10% of all hours in all study areas 

would be removed with the RH>90% criterion. This percentage varies from city 

to city, with a low of 1% at Phoenix and a high of 30% at Tacoma. Birmingham, 

Atlanta, Pittsburgh, Baltimore, and Philadelphia are also above 6%. 

Study area 

Number of 

Daylight 

hours with 

RH<=90% 

Number of 

Daylight 

hours with 

RH>90% 

Percent of 

Daylight 

Hours with 

RH>90% 

Tacoma 18293 7987 30% 

Fresno 24245 1615 6% 

Los Angeles 

Phoenix 26045 235 1% 

Salt Lake City 24989 1291 5% 

Dallas 25519 761 3% 

Houston 

St. Louis 

Birmingham 23826 2454 9% 

Atlanta 23696 2584 10% 

Detroit 

Pittsburgh 22254 4026 15% 

Baltimore 22867 3413 13% 

Philadelphia 24302 1978 8% 

New York 24963 1314 5% 

Overall total 260999 27658 10% 

I can’t reconcile the data in this table with Table G-1 in Appendix G, but the 

statement on page 3-29 is also not consistent with Table G-1. Whatever the cause 

3
 

of the inconsistency, it should be rectified so that the statements and tables are 

consistent. If I’ve misunderstood the presentation, it should be clarified. 

It’s difficult to see the contrast in the distributions shown in Figure G-2. It’s 

probably not important to see the difference (i.e. the distribution of extinction in 

the excluded hours), so I recommend the text be revised to bring the reader’s 

attention to the important aspects of the plot. In particular, it appears that the 

horizontal bar on the display for each city shows the 90th percentile extinction 

design value, but it isn’t mentioned in the text or in the table. It would be useful to 

highlight how the design value drops with the excluded hours. 

Charge question 4

4) In response to CASAC recommendations, descriptions of current conditions and

results of just meeting NAAQS scenarios that considered all daylight hours were

added to those based on maximum daily 1‐hour indicators. The 98th percentile

form was also included along with the 90th and 95th percentiles. Tile plots of

hourly PM light extinction (Figure 3‐12) and composition bar graphs of the top

10% of days for maximum daily 1‐hour and aggregated individual daylight hours

(Figure 3‐13) were shown in part to help illuminate the similarities and differences

between these various indicators with respect to current conditions. Similarly,

additional figures and table entries were generated to illustrate the

characteristics of various PM light extinction NAAQS scenario forms (Tables 4‐2, 4‐

3, 4‐ 5, and 4‐7; Figures 4‐1 through 4‐3).

What are the Panel’s views regarding EPA staff interpretations of these displays

included in the text? Are there supplemental or alternative interpretations the

Panel would suggest? Are there additional approaches the Panel would suggest

regarding ways to summarize, display, or assess the results of these analyses,

including similarities and differences between the various scenarios?

The tile plots in Figure 3-12 are an excellent way to show the hourly light 

extinction. I would like to see all plots scaled so the time periods directly 

correspond across the years. In particular, the 9-month plots for Houston and 

Phoenix should be scaled such that the 9 months shown correspond to the same 

period as in the 12-month plots, i.e. not stretched out to fill the space. All the 12-

month plots are currently scaled slightly differently so that the same time period is 

not directly opposite for different years. 

The staff interpretation of the plots is good, but the conditions at each city could 

be more fully explained. Section 3.4.5 has highlights of the extinction budgets for 

individual urban areas. I would like to see something similar for Section 3.4.4. 

For example, the description at Tacoma could read: The hours excluded at 

Tacoma are primarily in the late fall and winter, and are generally in the 

morning. Occasional periods last all day. Few hours are excluded due to high RH 

in spring, summer, and early fall. High light extinction periods also occur more 

often in late fall and winter, and with few exceptions occur mostly in the early 

daylight hours in other seasons. Fresno could be described as: The hours excluded 

in Fresno due to high RH are exclusively in the late fall and winter. This is the fog 

season in California’s Central Valley, and periods of high humidity can last for 

4
 

days at a time. The highest light extinction occurs during this period, also. 

Episodes of high light extinction also occur in spring and summer, sometimes 

lasting for many days. Many of these episodes last well into the afternoon. For 

Los Angeles, the following description could apply: Most hours excluded due to 

high RH at Los Angeles occur during the morning, and are primarily in the 

spring, summer, and early fall. High light extinction periods occur at all times of 

the year, but are more frequent in the spring and summer. These periods 

generally last all day. Each city has some characteristics that could be described 

more fully; this would more completely establish the conditions of high RH and 

light extinction in different urban areas of the country. 

The extinction budgets shown in Figure 3-13 are very helpful in explaining the 

causes of poor VAQ in the different cities. I particularly like the separate displays 

of the top 10% of days and the top 10% of individual daylight hours. The staff 

interpretation of these plots is very good. 

I question the high contribution to light extinction at Los Angeles from coarse PM 

during two of the top 10% of days. Having done considerable data validation of 

IMPROVE data, I can attest to the possibility of invalid values entering the 

database. I also know that hourly concentrations can be quite high under the right 

conditions, but such extreme values warrant further investigation of their validity. 

The explanation that the coarse PM is determined in part from measurements at 

Victorville could well explain the high values, and would make these values 

suspect for use at Los Angeles. There is no doubt that coarse PM measured at 

Victorville would be unrepresentative of coarse PM at Rubidoux, and especially 

in the wider South Coast Air Basin. 

I have a few comments relating to particular sections of the assessment, and a few 

editorial comments that I’ll list separately. First, the comments: 

Page Line Comment 

3-16 No suggestions – just a comment that this is an excellent description. 

3-21 36-27 Sea salt is an important contributor at coastal sites. This may be a source 

of uncertainty in the light extinction calculation at these sites. 

3-25 31-36 The approach described here has other sources of uncertainty that should 

be mentioned. Relying on mass closure to determine the hourly organic 

carbon assumes that all other species are accurately determined. This is 

problematic for nitrate, as pointed out just a few paragraphs earlier, and 

it leaves out sea salt that is an important contributor to mass at coastal 

sites. These factors should be mentioned as areas of uncertainty that are 

introduced by this method. 

3-26 14-15 Setting negative values to zero introduces a bias in the results. There is 

inherent uncertainty in both PM10 and PM2.5 measurements. During 

periods of very low coarse mass, the PM10 and PM2.5 measurements are 

very close, and their uncertainties may cause the PM2.5 measurement to 

be higher than the PM10 measurement. It’s important to retain negative 

5
 

values as a measure of the uncertainty during low coarse mass periods. 

3-32, 

3-33 

I have grave doubts about the outlier concentrations in these plots, 

particularly for Los Angeles and St. Louis. I have seen many cases of 

invalid high mass measurements of filter while performing data 

validation of IMPROVE samples. I have no doubt that there are high 

hourly PM concentrations for short periods, but the extreme values 

shown, coupled with the caveats mentioned, cast doubt on their validity. 

I have the following suggestions for editorial changes in the document. 

The Table of Contents is hard to read with the mix of all caps and mixed case font 

that is currently used. I suggest making Level 1 all caps, Level 2 small caps or 

mixed case, and Level 3 mixed case. This would more effectively set off the 

major and minor sections of the document in the Table of Contents. The 

appendices are good as they are. 

In the list of acronyms/abbreviations, the description for IMPROVE should have 

an “s” at the end, i.e. “Interagency Monitoring of Protected Visual 

Environments”. The description of NARSTO is out of date. It was originally the 

North American Research Strategy for Tropospheric Ozone, but is now just 

NARSTO. This could be noted in the description. For SMOKE, “Kernel” is 

misspelled. 

Other editorial suggestions: 

Page Line Suggestion 

1-1 5 Change to “...which are to reflect accurately...” 

2-11 15 “Visibility” in the graph heading is misspelled 

2-20 8 I suggest using different colors or symbols in Figure 2-11. These are the 

same as are used in Figure 2-10, but they have different meanings. It 

would be a good idea to review all graphics with this in mind, in 

particular those that are adjacent to each other. 

2-28 15 Do you mean to say “insignificant” as written, or “significant”? It looks 

to me as if this term is significant. 

2-30 13 Change “it” to “is” 

3-19 1 For some reason this line that ends a sentence appears as a heading in 

the Table of Contents. Please correct this. 

3-32 12-13 Do you mean to say section 3.3.1? I can’t find the referenced step in 

section 3.4.1. 

3-33 Figure 3-7 might be better using a logarithmic scale on the y-axis. The 

linear scale compresses the bulk of the data to the point that differences 

between the cities are not distinguishable. A logarithmic scale would 

show the outliers and still allow the lower values to be observable. 

6
 

Page Line Suggestion 

3-35 16-17 It looks like the references to Figures 3-8b and 3-8a are reversed. 

3-36 3 Fresno is listed as a city without a preference for morning high PM light 

extinction. The figures in Appendix E indicate otherwise. There are 

other cities that show such a preference that aren’t listed here. 

3-37 There is no units label on Figure 3-8. I assume it should be Mm-1, but it 

should be on the graph. 

3-44 31 Remove the first “a” 

3-44 32 Change “than” to “that” 

3-62 31 Change the comma to a semicolon 

3-63 10 

and 

23 

Remove “of” after “as high as” 

3-63 25 End the sentence with a period 

4-7 44 Change to “...in one or more...” 

4-10 3 Figure 4-2 should be a square plot so the units have equivalent length on 

the x- and y-axes. 

4-11 15 Table 4-4 says Dallas meets the 15/35 NAAQS, not Salt Lake City. 

4-11 30 Table 4-5 should be the next one in sequence. 

4-15, 

4-16 

The scale on Figures 4-3(a) and (b) is very high. Why? It compresses the 

bulk of the data and makes it difficult to see the differences between the 

cities. 

App. F The comments for Figure 4-3 also apply to the figures in Appendix F. 

G-1 Para. 

3 

In the second line, change to “...prior to the their exclusion.” 

I-1 Para. 

3 

I believe the references to “top of figure” and “bottom of figure” should 

be interchanged. 

7
 

Comments from Dr. David Grantz 

3-16-10 

Urban-Focused Visibility Assessment, Second External Review Draft

Charge Question 1) Level of detail provided in the body of the report and 

appendices and suggestions regarding organization of the document. 

This review draft of the UFVA appears to be of appropriate length and complexity, with 

very few exceptions. Staff is to be commended for preparing an excellent document. 

Chapter 2 may contain more information than is required with respect to the individual 

cities. Much of this material could be moved to the Appendices. The memo of 2/3/2010 

on the statistical analysis of the preference studies could also be placed in the 

Appendices, and consolidated with related material from Chapter 2 to avoid redundancy. 

Similarly, much of the material in sections 4.1.3 and 4.1.4 might be better suited to an 

Appendix. In any case, the transition into future monitoring site characteristics (middle of 

page 4 – 2) is rather abrupt. 

Charge Question 2) Contribution of the logit analysis. 

I remain concerned that despite the abundant statistical analysis of visual preference data 

performed since the first external review draft, the amount of data is simply insufficient 

to determine what level of air quality/visibility may be acceptable nationwide. The most 

important conclusions from these preliminary studies are the closely related concepts that 

(1) the range of haziness views presented to panelists is important, as suggested by Smith 

and Howell, and (2) that there may be true regional differences in expected air quality, 

due to the range of visibility to which residents have become accustomed. This is 

considered explicitly at the bottom of page 2 – 30, although it may be premature to 

attempt to identify the reasons for these differences. This has significant policy 

implications. While the agency has every reason to move forward on this, these results 

should be flagged throughout as tentative and subject to further research. 

Charge Question 4) All daylight versus maximum daily 1-hour indicators. 

The distinction between all daylight hours and maximum daily 1 hour indicators is not 

made completely clear in the document. This could be defined more definitively 

somewhere early in the text. In general, the abundant consideration of various indicators 

and end points is useful and probably unavoidable. 

Other editorial points. 

The definition of haziness in deciview units and light extinction in inverse mega meters 

on page 1 -- 6 is useful and well presented. However, visual range is used later in the 

document (first appearing on page 1 – 10) but is not defined here. Explanation of the 

utility of each parameter would help the narrative. While visual range may be most 

intuitive to many readers, it is dropped on page 1 – 15, in favor of explicit definition of 

CPLs in terms of light extinction. For general readability, explicit interconversion 

between the different measures could be carried through the document. 

Page 1 – 13, lines 4 - 8: The relationship between organic compounds, carbon mass, and 

air mass aging needs to be better explained here. 

Page 1 – 14, line 35: “indictor” or should be “indicator” 

Page 3 – 44, line 32. “such than average” should be changed to “such that average”. 

8
 

Figures

Maps, Page 3 – 2. It is disconcerting to find Alaska, Hawaii, and Puerto Rico lumped 

into the Gulf of Mexico. There may be room off the Pacific and Atlantic coasts, 

respectively, if the legend were placed in the Gulf. 

Figure 3 – 9, Page 3 – 40. The X axis labels are unclear. 

9
 

Comments from Dr. Philip Hopke 

1) In general, what are the Panel’s views on the level of detail provided in the body of the 

report and associated appendices? Does the Panel agree that all of this information is 

useful to retain or is there material that the Panel would recommend deleting? Does the 

Panel have any suggestions regarding the organization and distribution of information 

throughout the document and in the appendices? 

Yes, it is long and somewhat dry, but its completeness and detail are useful particularly given 

that we are looking at a very different indicator for this secondary standard. It is not obvious 

to me that alternative organization or distribution of the information would be more 

informative to the reader. 

2) In the Panel’s view, to what extent does the logit analysis presented in Chapter 2 of the 

second draft Visibility Assessment and further expanded and described in the 

supplemental memorandum add value to the urban visibility preference study analysis 

and provide additional support for combining and comparing the results from the four 

cities, as shown in Figure 2-16? What are the Panel’s views on the clarity and adequacy 

of the descriptions associated with such a combined assessment and on the conclusions 

that can be drawn from the assessments? Please provide comments on any additional 

insights that might be drawn from these analyses or on any additional caveats that should 

be considered. 

The logit analysis is useful in exploring these data. One point that is not adequately made 

regarding the Washington studies is that the DC photo is significantly different from the 

others in the lack of significant scenic features at a distance. There is a brief mention of this 

on the top of page 2-31 and only in comparison to Denver. However, all of the other studies 

have mountains some tens of miles from the point of view. I suspect that the lack of a distant 

object has significantly biased the acceptable level values upward. In fact the distance to the 

background features might well be a key factor in the acceptability ratings. Has there been an 

effort to look at the relationship between the 50% acceptability level and the maximum 

distance to visible objects in the pictures? That might be informative. 

3) What are the Panel’s views on the extent to which the analysis of the frequency of cooccurrences of hourly relative humidity values below and above 90 percent with other 

meteorological events such as rain or fog (Chapter 3, section 3.3.5; Table 3-6) provides 

scientific support for consideration of how to address relative humidity in defining the 

form of a standard based on a PM light extinction indicator? 

This section seemed adequate. 

4) In response to CASAC recommendations, descriptions of current conditions and results 

of just meeting NAAQS scenarios that considered all daylight hours were added to those 

based on maximum daily 1-hour indicators. The 98th percentile form was also included 

10
 

along with the 90th and 95th percentiles. Tile plots of hourly PM light extinction (Figure 3-

12) and composition bar graphs of the top 10% of days for maximum daily 1-hour and 

aggregated individual daylight hours (Figure 3-13) were shown in part to help illuminate 

the similarities and differences between these various indicators with respect to current 

conditions. Similarly, additional figures and table entries were generated to illustrate the 

characteristics of various PM light extinction NAAQS scenario forms (Tables 4-2, 4-3, 4-

5, and 4-7; Figures 4-1 through 4-3). 

What are the Panel’s views regarding EPA staff interpretations of these displays included 

in the text? Are there supplemental or alternative interpretations the Panel would suggest? 

Are there additional approaches the Panel would suggest regarding ways to summarize, 

display, or assess the results of these analyses, including similarities and differences 

between the various scenarios? 

I would suggest there be more exploration of what if any potential problems would arise 

if there would be for a PM2.5 visibility standard only. There are substantial advantages 

to establishing monitoring systems for fine particle scattering (nephelometers) that would 

avoid the difficulties of the predominately forward scattering by coarse particles. In most 

locations, it is likely that a PM10-2.5 primary standard could reduce the effect of this 

fraction on extinction to the point where it is not a significant part of the visibility 

problem. Such an approach would be easier to implement on both a monitoring and 

implementation basis. 

11
 

Comments from Mr. Rich Poirot 

Review Comments on 2nd Draft January 2010 PM UFVA, R. Poirot, 2/4/10 

I thought the first draft UFVA was well done, especially considering the limited time 

schedule and complexity of the required calculations. In the second draft, EPA staff has 

been very responsive to CASAC recommendations, adding a detailed logit analysis to 

better understand similarities and differences in the urban visibility preference studies, 

recalculating estimated extinction levels using a 90% RH screen, and considering (90th, 

95th and 98th) percentiles based on all available daylight hours as well as based on the 

single worst daylight hour in each day. These additions represent a substantial body of 

new work, again conducted in a very limited time period, and as before the additional 

calculations and results are explained, compared and illustrated in clear detail. 

The UFVA presents logical and persuasive arguments for use of a PM light extinction 

indicator with a 1-hour (daylight) averaging time as a sound basis for a secondary PM 

standard to protect visibility. The UFVA also presents reasonable ranges for the level 

(20 to 30 deciviews) and form (90th to 98th percentile) that such a standard might take, 

and clearly illustrates the differences among the many resulting optional combinations in 

terms of the protectiveness and/or stringency across the 15 diverse urban areas selected 

for this analysis. 

I don’t believe that any major revisions are required in this second draft, and that the 

methods employed here – if not some of the specific calculations – would make a sound 

basis for recommending and comparing optional ranges of a secondary PM light 

extinction standard in the upcoming Policy Assessment document. 

1) In general, what are the Panel’s views on the level of detail provided in the body of 

the report and associated appendices? Does the Panel agree that all of this 

information is useful to retain or is there material that the Panel would recommend 

deleting? Does the Panel have any suggestions regarding the organization and 

distribution of information throughout the document and in the appendices? 

While a substantial level of detail has been provided in the UFVA, many of the calculations 

included here are very complex, and a fairly wide range of optional combinations of levels 

and forms are presented and compared. I think the level of detail provided is appropriate in 

relation to the level of complexity and the range of options considered, allowing the 

“interested reader” to understand just exactly how the many calculations have been made, 

and often providing several different views for “seeing” the results in several different 

contexts. For the “disinterested reader” there are several summary tables toward the end 

which condense most of the varied results to a single page or two. I don’t believe the 

document could be better organized or more succinctly written. 

2) In the Panel’s view, to what extent does the logit analysis presented in Chapter 2 of 

the second draft Visibility Assessment and further expanded and described in the 

supplemental memorandum add value to the urban visibility preference study 

analysis and provide additional support for combining and comparing the results 

12
 

from the four cities, as shown in Figure 2-16? What are the Panel’s views on the 

clarity and adequacy of the descriptions associated with such a combined 

assessment and on the conclusions that can be drawn from the assessments? Please 

provide comments on any additional insights that might be drawn from these 

analyses or on any additional caveats that should be considered. 

The logit analysis presented in chapter 2 helps in more clearly quantifying and understanding 

the similarities and differences among results from the 4 urban visibility preference studies. 

The associated discussion of the logit results and consideration of alternative hypotheses for 

the differences and similarities across the different study areas (and different study 

approaches) are also helpful. While the resulting 20 to 30 deciview range of visual air 

quality levels meeting a 50% acceptability criteria, remains rather broad, I doubt that much 

more can be learned or that this range could be substantially reduced by additional analyses 

of these limited results, and think that selecting a level or levels from within this 20 to 30 dv 

range is well justified for the initial establishment of a secondary PM standard. Additional 

studies using consistent methods and conducted over a range of different kinds of urban areas 

and different views will help refine this range in the future. 

3) What are the Panel’s views on the extent to which the analysis of the frequency of 

co-occurrences of hourly relative humidity values below and above 90 percent with 

other meteorological events such as rain or fog (Chapter 3, section 3.3.5; Table 3-6) 

provides scientific support for consideration of how to address relative humidity in 

defining the form of a standard based on a PM light extinction indicator? 

Eliminating hours when RH exceeds 90% is a good idea - for conducting this assessment as 

well as for specifying conditions for and determining compliance with a secondary PM light 

extinction standard. The analysis presented in the 2nd draft UFVA provides a compelling 

demonstration that a 90% RH screen can efficiently eliminate periods when “natural” 

visibility-impairing weather events are occurring, and when PM light extinction is not likely 

to be the predominant cause of impaired visibility. The spatial (& temporal) variability of 

RH and weather (& PM species) are important related issues, in that there may be natural 

weather event impairing visibility along the sight path but not observed at the location of the 

RH (or PM or PM light extinction observation). I don’t think its warranted here, but it might 

be possible to explore this possibility a bit by considering the RH and weather observations at 

a range of stations within say a 30 mile radius and looking for co-occurrences of RH above or 

below 90% and weather events across all the sites. 

In addition to screening out weather events, there are other benefits of employing this RH 

screen. It will help avoid any public perception, however faulty, that the regulatory metric is 

influenced by uncontrollable weather events. RH can be difficult to measure, especially at 

high levels, such that an indicated RH of 90% may actually be significantly higher (or lower) 

than that. The hygroscopic growth curve gets very steep at high humidity such that a small 

error in the RH or (sulfate or nitrate) PM species measurement or in its spatial or temporal 

representativeness of the actual (or in the case of this assessment, estimated) extinction 

throughout the site path could result in a large error in estimated extinction, or in the 

visibility relevance of extinction measured at a single location. An RH screen might also 

allow for measurement options such as adding a “smart heater” to a nephelometer that would 

only kick in at high RH but would prevent larger water droplets from entering and soiling the 

13
 

measurement chamber, reducing instrumental maintenance costs, and promoting better data 

quality and capture efficiency. 

Screening out the higher RH values will slightly “dry out” the regulatory metric, eliminate 

some of the highest (but most uncertain) periods of estimated and measured PM extinction, 

shift the distribution downward and reduce, somewhat, the differences between East and 

West. It would also limit the extent to which the influences of hygroscopic sulfate and nitrate 

species are enhanced relative to the other PM species. At 95% RH the extinction efficiencies 

of ammonium sulfate and ammonium nitrate would be more than 22 m2

/g, compared to 

efficiencies of 10 m2

/g for EC, 4 m2/g for organic matter, 1 m2/g for fine soil and 0.6 m2/g for 

coarse particles. At 90% RH the maximum extinction efficiencies of ammonium sulfate and 

ammonium nitrate would be limited to 12.5 m2

/g. This would be an “artificial” limit, and 

there will likely be hours of very poor visibility when natural weather is not the cause which 

will not be considered with this RH screen, but I think it’s use is well justified for the other 

reasons indicated above, and that there are other benefits associated with having a slightly 

dryer and more stable regulatory metric. 

4) In response to CASAC recommendations, descriptions of current conditions and 

results of just meeting NAAQS scenarios that considered all daylight hours were 

added to those based on maximum daily 1-hour indicators. The 98th percentile form 

was also included along with the 90th and 95th percentiles. Tile plots of hourly PM 

light extinction (Figure 3-12) and composition bar graphs of the top 10% of days for 

maximum daily 1-hour and aggregated individual daylight hours (Figure 3-13) were 

shown in part to help illuminate the similarities and differences between these 

various indicators with respect to current conditions. Similarly, additional figures 

and table entries were generated to illustrate the characteristics of various PM light 

extinction NAAQS scenario forms (Tables 4-2, 4-3, 4-5, and 4-7; Figures 4-1 through 

4-3). 

What are the Panel’s views regarding EPA staff interpretations of these displays 

included in the text? Are there supplemental or alternative interpretations the Panel 

would suggest? Are there additional approaches the Panel would suggest regarding 

ways to summarize, display, or assess the results of these analyses, including 

similarities and differences between the various scenarios? 

I think applying the 90% RH screen, including a higher (98th) percentile form and 

considering an alternative way of calculating percentiles – based on all daylight hours , 

rather than just the worst hour in a day – were valuable additions to the UFVA. When 

these are combined with other options including 90th and 95th percentiles, different levels 

(64, 112, 191 Mm-1) of a secondary standard and assuming attainment of different levels 

of a primary standard (15/35, 12/25 ug/m3

), the many resulting options are complex and 

difficult to communicate and compare. I think the UFVA does an excellent job of 

presenting this information as clearly as possible. 

I think the tile plots are very informative (not to mention beautiful!) and really help show 

the seasonal and diurnal patterns and similarities and differences across the different 

study areas. They also help show that the effect of the 90% RH screen tends to often be 

elimination of the first few early morning hours when fog is most likely and when its 

14
 

most difficult for human observers to discern the differences between natural and 

manmade effects, and provide added confidence that the use of this screen is appropriate. 

The plots of maximum hourly extinction on top 10% days vs. compositions on top 

percentiles considering all daylight hours are useful for seeing differences between cities, 

on different worst days (hours) and (to a lesser extent) for different high percentiles. I 

think the accompanying interpretation and discussion are reasonable and informative. I 

don’t these graphs necessarily make for an effective direct comparison or evaluation of 

whether percentiles calculated from the single worst hour of each day would be a better 

regulatory metric. Personally, I think I prefer using all daylight hours to only using the 

worst single hour each day, since I think a day that’s hazy all day long is more 

objectionable than one where its hazy for just one humid hour just after sunrise. I also 

don’t think there are many 1-hr control strategies, especially for SOx and NOx (and 

NHx) sources, which I think get additionally emphasized by the single worst hour 

approach, with a consequent relative de-emphasis of carbonaceous pollutants. I also 

imagine that using all daylight hours would produce a more stable and somewhat dryer 

metric, reducing, somewhat, the differences between East and West. I think this could be 

important if the Agency finds it necessary to employ a traditional fixed “threshold-based” 

approach for the secondary NAAQS, rather than the “progress-based” approach 

recommended by the PM panel as scientifically preferable, and a conceptual approach to 

consider during implementation – even though it may not currently be a practical option 

for the Agency. 

Possibly it would be informative to present side by side bar graphs showing an average of 

the compositions on the worst 10%, 5% and 2% hours calculated using the 2 different 

approaches. Are the compositions really much different? Would it be informative to 

know how many days would be involved using the 2 different approaches, or perhaps to 

consider the days or kinds of pollution events that tend to get considered in one approach 

but not the other? 

Certain aspects of the discussion seem directed toward supporting the original worst hour 

of day approach – for example a repeated observation that the 98th percentile using all 

daylight hours is not much different from the 98th percentile using worst daylight hours 

and expressing the results of both approaches in Table 4.7 in units of single worst hour of 

day. As indicated, I think I conceptually prefer the all-hours approach but think it would 

be useful to see more clearly what the differences are. I don’t think this is needed in the 

Risk Assessment, but maybe the Policy Assessment could explore these options in more 

detail.

15
 

16

Other Comments: 

As indicated in comments on the 1st draft UFVA, I am very suspicious of the results for 

St. Louis and especially the extremely high coarse mass concentrations there – which 

often dominate the reconstructed extinction estimates during the haziest hours. I note that 

the 2 estimated haziest hours at STL for which the estimated coarse mass is the major 

contributor to extinction are 7/10/06 at 11:00 (estimated extinction of about 600 Mm-1) 

and 5/17/06 at 15:00 (estimated extinction of about 800 Mm-1). However, the ASOS 

visibility data from the STL airport (15 miles from downtown) indicates visibility was 10 

miles or greater (Bext was 245 Mm-1 or less) during both of these time periods. I 

suggest discarding the STL estimates, or using other PM10 and PM2.5 data for making 

these estimates. Note that these Bext data were extracted from the Datafed.net system, in 

which a Koschmeider constant of 3000, rather than 3912 was used (incorrectly, I think) to 

convert the visual range data to extinction.