Particulate Matter 

Urban-Focused Visibility Assessment

External Review Draft 

September 2009 
 

 

DISCLAIMER

This draft document has been prepared by staff from the Ambient Standards Group, 

Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency. Any 

opinions, findings, conclusions, or recommendations are those of the authors and do not 

necessarily reflect the views of the EPA. This document is being circulated to obtain review and 

comment from the Clean Air Scientific Advisory Committee (CASAC) and the general public. 

Comments on this draft document should be addressed to Vicki Sandiford, U.S. Environmental 

Protection Agency, Office of Air Quality Planning and Standards, C504-06, Research Triangle 

Park, North Carolina 27711 (email: sandiford.vicki@epa.gov). 

Elements of this report (see Acknowledgements below) have been provided to the U.S. 

Environmental Protection Agency (EPA) by Abt Associates Inc. and Stratus Consulting Inc. in 

partial fulfillment of Contract No. EP-D-08-100, Work Assignment 0-11. Any opinions, 

findings, conclusions, or recommendations are those of the authors and do not necessarily reflect 

the views of the EPA or its contractors. 

ACKNOWLEDGEMENTS

In addition to EPA staff, personnel from Abt Associates Inc. and Stratus Consulting Inc. 

contributed to the writing of this document. The specific chapter where Abt Associates Inc. and 

Stratus Consulting Inc. made contributions is chapter 2 (Urban Visibility Preference Studies). 
EPA 452/P-09-005 

September 2009 

Particulate Matter 

Urban-Focused Visibility Assessment 

External Review Draft 

U.S. Environmental Protection Agency 

Office of Air and Radiation 

Office of Air Quality Planning and Standards 

Health and Environmental Impacts Division 

Ambient Standards Group 

Research Triangle Park, North Carolina 27711 
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i 

TABLE OF CONTENTS 

LIST OF TABLES ...................................................................................................................................iii

LIST OF FIGURES ................................................................................................................................. iv

LIST OF ACRONYMS/ABBREVIATIONS......................................................................................... vi

1 INTRODUCTION...................................................................................................................... 1-1

1.1 PM NAAQS BACKGROUND.................................................................................................... 1-3 

1.2 SCOPE OF URBAN-FOCUSED VISIBILITY ASSESSMENT................................................ 1-5 

1.3 VISIBILITY EFFECTS SCIENCE OVERVIEW.......................................................................1-7 

1.4 GOALS AND APPROACH ........................................................................................................1-9 

1.5 ORGANIZATION OF DOCUMENT .......................................................................................1-11 

2 URBAN VISIBILITY PREFERENCE STUDIES.................................................................. 2-1

2.1 METHODS USED IN PREVIOUS STUDIES............................................................................ 2-1 

2.2 DENVER, COLORADO .............................................................................................................2-3 

2.3 VANCOUVER, BRITISH COLUMBIA, CANADA ................................................................. 2-7 

2.4 PHOENIX, ARIZONA..............................................................................................................2-12 

2.5 WASHINGTON, D.C................................................................................................................2-14 

2.5.1 Washington, D.C. 2001.................................................................................................. 2-15 

2.5.2 Washington, D.C., 2009................................................................................................. 2-17 

2.6 SUMMARY OF PREFERENCE STUDIES AND SELECTION OF CANDIDATE 

PROTECTION LEVELS...........................................................................................................2-23 

3 ESTIMATION OF CURRENT PM CONCENTRATIONS AND LIGHT EXTINCTION3-1

3.1 GENERAL CHARACTERIZATION .........................................................................................3-1 

3.1.1 PM2.5 and PM10-2.5 ............................................................................................................3-1 

3.1.2 Light extinction................................................................................................................3-4 

3.2 OVERVIEW OF APPROACH AND DATA SOURCES FOR URBAN STUDY ANALYSIS 3-9 

3.2.1 Study Period, Study Areas, Monitoring Sites, and Sources of Ambient PM Data........3-10 

3.2.2 Use of CMAQ Model Runs for 2004 to Augment Ambient Data .................................3-15 

3.2.3 Use of Original IMPROVE Algorithm to Estimate Light Extinction............................3-16 

3.3 DETAILED STEPS ...................................................................................................................3-18 

3.3.1 Hourly PM2.5 Component Concentrations .....................................................................3-18 

3.3.2 Hourly PM10-2.5 Concentrations......................................................................................3-24 

3.3.3 Hourly Relative Humidity Data.....................................................................................3-24 

3.3.4 Calculation of Hourly and Daily Maximum 1-Hour Total Light Extinction.................3-25 

3.4 SUMMARY OF RESULTS FOR CURRENT CONDITIONS................................................. 3-26 

3.4.1 Levels of Estimated PM2.5, PM2.5 Components, PM10-2.5, and Relative Humidity ........3-26 

3.4.2 Levels of Estimated Total Light Extinction...................................................................3-26 

3.4.3 Patterns of Relative Humidity and Relationship between Relative Humidity and Total 

Light Extinction ............................................................................................................. 3-33 
ii 

3.4.4 Extinction Budgets for High Total Light Extinction Conditions...................................3-36 

3.5 POLICY RELEVANT BACKGROUND..................................................................................3-37 

4 TOTAL LIGHT EXTINCTION UNDER “WHAT IF” CONDITIONS OF JUST 

MEETING SPECIFIC ALTERNATIVE SECONDARY NAAQS....................................... 4-1

4.1 ALTERNATIVE SECONDARY NAAQS BASED ON MEASURED TOTAL LIGHT 

EXTINCTION AS THE INDICATOR ....................................................................................... 4-1 

4.1.1 Indicator and Monitoring Method....................................................................................4-1 

4.1.2 Alternative Secondary NAAQS Scenarios based on Measured Total Light Extinction..4-1 

4.1.3 Monitoring Site Considerations for Alternative Secondary NAAQS Based on Measured 

Total Light Extinction......................................................................................................4-2 

4.1.4 Approach to Modeling “What If” Conditions for Alternative Secondary NAAQS based 

on Measured Total Light Extinction................................................................................4-2 

4.2 ALTERNATIVE SECONDARY PM2.5 NAAQS BASED ON ANNUAL AND 24-HOUR PM2.5

MASS...........................................................................................................................................4-5 

4.2.1 Secondary NAAQS Scenarios Based on Annual and 24-hour PM2.5 Mass ..................... 4-5 

4.2.2 Approach to Modeling Conditions If Secondary PM2.5 NAAQS Based on Annual and 24-

hour PM2.5 Mass Were Just Met.......................................................................................4-6 

4.3 RESULTS FOR “JUST MEETING” ALL ALTERNATIVE SECONDARY NAAQS 

SCENARIOS ...............................................................................................................................4-7 

5 REFERENCES...........................................................................................................................5-1

APPENDICES

APPENDIX A - PM2.5 MONITORING SITES AND MONITORS PROVIDING 2005-2007 DATA 

FOR THE ANALYSIS OF TOTAL LIGHT EXTINCTION IN THE 15 STUDY AREAS ..... A-1 

APPENDIX B - DISTRIBUTIONS OF ESTIMATED PM2.5 COMPONENTS.................................... B-1 

APPENDIX C - DEVELOPMENT OF PRB ESTIMATES OF PM2.5 COMPONENTS, PM10-2.5, AND 

TOTAL LIGHT EXTINCTION ................................................................................................. C-1 

APPENDIX D RELATIONSHIPS BETWEEN PM MASS CONCENTRATION AND TOTAL LIGHT 

EXTINCTION UNDER CURRENT CONDITIONS ................................................................ D-1 

APPENDIX E - DIFFERENCES IN DAILY PATTERNS OF RELATIVE HUMIDITY AND TOTAL 

LIGHT EXTINCTION BETWEEN AREAS AND SEASONS..................................................E-1 

APPENDIX F - DISTRIBUTIONS OF MAXIMUM DAILY DAYLIGHT TOTAL LIGHT 

EXTINCTION - UNDER “JUST MEET” CONDITIONS .........................................................F-1 
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LIST OF TABLES 

Table 2-1. VAQ of Denver photos substantively misclassified by majority of participants ......2-6 

Table 2-2. Summary of photographs used in British Columbia study......................................2-10 

Table 3-1. Annual Mean Reconstructed 24-hour Light Extinction Estimates............................. 3-7 

Table 3-2. Urban Visibility Assessment Study Areas ...............................................................3-10 

Table 3-3. PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Tacoma 

Study Area ......................................................................................................... 3-13 

Table 3-4. Number of days per quarter in each study area .......................................................3-14 

Table 3-5. Assumed daylight hours by season (Local Standard Time) ....................................3-25 

Table 3-6. Percentage of days in which daily maximum daylight 1-hour total light extinction 

exceeded three candidate protective levels across the 2005-2007 period,.........3-31 

Table 4-1. Alternative Secondary NAAQS Scenarios for Light Extinction...............................4-1 

Table 4-2. Current Conditions total light extinction design values for the study areas...............4-4 

Table 4-3. Percentage reductions in non-PRB light extinction required to “just meet” the 

NAAQS scenarios based on measured light extinction. ...................................... 4-5 

Table 4-4. Percentage reductions required in non-PRB PM2.5 mass to “just meet” NAAQS 

scenarios based on annual and 24-hour PM2.5 mass............................................. 4-7 

Table 4-5. Total light extinction design values for “just meeting” secondary NAAQS scenarios 

based on measured total light extinction............................................................ 4-10 

Table 4-6. Total light extinction design values for “just meeting” secondary NAAQS scenarios 

based on PM2.5 mass .......................................................................................... 4-10 

Table 4-7. Percentage of days across three years (two in the case of Phoenix and Houston) with 

maximum 1-hour daylight total light extinction above CPLs when “just meeting” 

the NAAQS scenarios........................................................................................ 4-11 
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LIST OF FIGURES 

Figure 1-1. Diagram showing the relationship steps between ambient PM and visibility 

impairment. ..........................................................................................................1-9 

Figure 2-1. Percent of Denver participants who consider VAQ in each photograph “acceptable.”

..............................................................................................................................2-5 

Figure 2-2. Photograph time of day information for the percent of participants who consider 

VAQ in each photograph “acceptable.”...............................................................2-7 

Figure 2-3. Denver photograph time of day results (9:00 a.m. photographs eliminated), with the 

broader range (17.7 dv and 24.6 dv) of the 50% acceptability criteria shown. ...2-7 

Figure 2-4. Composite Chilliwack, BC photograph showing VAQ of 14.1 dv and 34 dv......... 2-9 

Figure 2-5. Percent of BC participants who consider VAQ in each photograph “acceptable.” .. 2-

11 

Figure 2-6. Reproduction of the image with the best VAQ (15 dv) used in the Phoenix study. .. 2-

13 

Figure 2-7. Percent of Phoenix participants who consider VAQ in each image “acceptable.” 2-14 

Figure 2-8. Reproduction of the image with the best VAQ (8.8 dv) used in the Washington, D.C. 

study................................................................................................................... 2-16 

Figure 2-9. Percent of 2001 Washington participants who consider VAQ acceptable in each 

image..................................................................................................................2-17 

Figure 2-10. Percent of 2009 Test 1 study participants who consider VAQ acceptable in each 

image, showing the range of the lower and upper bound of 50% acceptability 

criteria. ............................................................................................................... 2-19 

Figure 2-11. Combined results of two Washington preference studies (showing 50% 

acceptability criteria from 2009, Test 1)............................................................2-20 

Figure 2-12. Comparison of results from Test 1 and Test 2 (Smith and Howell, 2009). ........2-20 

Figure 2-13. Comparison of results from the Washington, DC (2009) Test 1 and Test 3........2-22 

Figure 2-14. Summary of results of urban visibility studies in four North American cities, 

showing the identified range of the 50% acceptance criteria. ...........................2-24 

Figure 3-1. Annual average and 24-hour (98th percentile 24-hour concentrations) PM2.5 

concentrations in μg/m3, 2007. ............................................................................3-2 

Figure 3-2. Reconstructed 24-hour light extinction in U.S. urban areas in 2003 ........................3-6 

Figure 3-3. Isopleth map of annual total reconstructed particulate extinction based on IMPROVE 

data....................................................................................................................... 3-8 

Figure 3-4. January and August monthly average diurnal profiles of PM2.5 components derived 

from the 2004 CMAQ modeling platform, for the Detroit study area...............3-17 

Figure 3-5. Sequence of steps used to estimate hourly PM2.5 components and total light 

extinction............................................................................................................3-20 

Figure 3-6. Example from Detroit study area. ..........................................................................3-22 

Figure 3-7. Distribution of PM parameters and relative humidity across the 2005-2007 period, 

by study area ...................................................................................................... 3-28 

Figure 3-8. Distributions of estimated daylight 1-hour total light extinction and maximum daily 

daylight 1-hour total light extinction across the 2005-2007 period, by study area.

............................................................................................................................3-30 

Figure 3-9. Distributions of 1-hour total light extinction levels by daylight hour across the 2005-

2007 period, by study area................................................................................. 3-32 
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Figure 3-10. Distributions of 1-hour relative humidity levels by daylight hour across the 2005-

2007 period, by study area................................................................................. 3-34 

Figure 3-11. Scatter plot of daylight 1-hour relative humidity (percent) vs. reconstructed total 

light extinction (Mm-1) across the 2005-2007 period, by study area.................3-35 

Figure 3-12. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 1-

hour PM light Extinction for 2005-2007 (Tacoma and Fresno) ........................3-38 

Figure 3-13. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 1-

hour PM light Extinction for 2005-2007 (Los Angeles and Phoenix)...............3-39 

Figure 3-14. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 1-

hour PM light Extinction for 2005-2007 (Salt Lake City and Dallas)...............3-40 

Figure 3-15. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 1-

hour PM light Extinction for 2005-2007 (Houston and St. Louis)....................3-41 

Figure 3-16. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 1-

hour PM light Extinction for 2005-2007 (Birmingham and Atlanta)................3-42 

Figure 3-17. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 1-

hour PM light Extinction for 2005-2007 (Detroit and Baltimore).....................3-43 

Figure 3-18. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 1-

hour PM light Extinction for 2005-2007 (Pittsburgh and Philadelphia)............3-44 

Figure 3-19. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 1-

hour PM light Extinction for 2005-2007 (New York).......................................3-45 

Figure 4-1. Distributions of daily maximum daylight 1-hour total light extinction under two 

“just meeting” secondary NAAQS scenarios ......................................................4-9 
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LIST OF ACRONYMS/ABBREVIATIONS 

AQS EPA’s Air Quality System 

BAM Beta Attenuation Mass Monitor 

BC British Columbia 

CAA Clean Air Act 

CAIR Clean Air Interstate Rule 

CASAC Clean Air Scientific Advisory Committee 

CBSA Consolidated Business Statistical Area 

CCN Cloud Condensation Nuclei 

CDPHE Colorado Department of Public Health and Environment 

CMAQ Community Multiscale Air Quality 

CONUS CMAQ simulations covering continental US 

CPL Candidate Protection Level 

CRA Charles River Associates 

CSA Consolidated Statistical Area 

CSN Chemical Speciation Network 

CTM Chemical Transport Model 

CTS CMAQ model run 

DRE Direct Radiative Effects 

dv deciview 

EPA United States Environmental Protection Agency 

FEM Federal Equivalent Method 

FRM Federal Reference Method 

GEOS Global Scale Air Circulation Model 

IMPROVE Interagency Monitoring of Protected Visual Environment 

ISA Integrated Science Assessment 

Km Kilometer 

LCD Liquid Crystal Display 

LOESS Locally weighted Scatter Plot Smoothing 

Mm Megameter 

MSA Metropolitan Statistical Area 

N Nitrogen 

NAAQS National Ambient Air Quality Standards 

NARSTO North American Research Strategy for Tropospheric Ozone 
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NCEA National Center for Environmental Assessment 

NOAA National Oceanic and Atmospheric Administration 

NOx Nitrogen oxides 

NPS National Park Service 

NRC National Research Council 

NWS National Weather Service 

OAQPS Office of Air Quality Planning and Standards 

OAR Office of Air and Radiation 

OMB Office of Management and Budget 

ORD Office of Research and Development 

PA Policy Assessment 

PM Particulate Matter 

PM2.5 Particles with a 50% upper cut-point of 2.5 μm aerodynamic 

diameter and a penetration curve as specified in the Code of 

Federal Regulations. 

PM10 Particles with a 50% upper cut-point of 10± 0.5 μm aerodynamic 

diameter and a penetration curve as specified in the Code of 

Federal Regulations. 

PM10-2.5 Particles with a 50% upper cut-point of 10 μm aerodynamic 

diameter and a lower 50% cut-point of 2.5 μm aerodynamic 

diameter. 

PRB Policy Relevant Background 

REA Risk and Exposure Assessment 

RF Radiative Forcing 

RH Relative Humidity 

SANDWICH Sulfate, Adjusted Nitrate, Derived Water, Inferred Carbonaceous 

mass approach 

SEARCH Southeastern Aerosol Research and Characterization Study 

SMOKE Sparse Matrix Operator Kernal Emissions 

S Sulfur 

SO2 Sulfur Dioxide 

SOx Sulfur Oxides 

STP Standard Temperature and Pressure 

TEOM Tapered Element Oscillating Microbalance 

UBC University of British Columbia 

UFVA Urban-Focused Visibility Impact Assessment 

VAQ Visual Air Quality 
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1 1 INTRODUCTION 

2 The U.S. Environmental Protection Agency (EPA) is presently conducting a review of 

3 the national ambient air quality standards (NAAQS) for particulate matter (PM). Sections 108 

4 and 109 of the Clean Air Act (Act) govern the establishment and periodic review of the NAAQS. 

5 The NAAQS are to be based on air quality criteria, which are to accurately reflect the latest 

6 scientific knowledge useful in indicating the kind and extent of identifiable effects on public 

7 health or welfare that may be expected from the presence of the pollutant in ambient air. The 

8 EPA Administrator is to promulgate and periodically review, at no later than five-year intervals, 

9 “primary” (health-based) and “secondary” (welfare-based) NAAQS for such pollutants. Based 

10 on periodic reviews of the air quality criteria and standards, the Administrator is to make 

11 revisions in the air quality criteria and standards, and to promulgate any new standards, as may 

12 be appropriate. The Act also requires that an independent scientific review committee advise the 

13 Administrator as part of this NAAQS review process, a function performed by the Clean Air 

14 Scientific Advisory Committee (CASAC). 

15 The current NAAQS for PM include a suite of standards to provide protection from 

16 health and welfare effects related to fine and coarse particles, using PM2.5 and PM10 as 

17 indicators, respectively (71 FR 61144, October 17, 2006). With regard to the primary and 

18 secondary standards for fine particles, in 2006 EPA revised the level of the 24-hour PM2.5 

standard to 35 μg/m3 (calculated as a 3-year average of the 98th 19 percentile of 24-hour 

20 concentrations at each population-oriented monitor), retained the level of the annual PM2.5 annual 

standard at 15 μg/m3 21 (calculated as the 3-year average of the weighted annual mean PM2.5 

22 concentrations from single or multiple community-oriented monitors), and revised the form of 

the annual PM2.5 standard by narrowing the constraints on the optional use of spatial averaging1 23 . 

24 With regard to the primary and secondary standards for PM10, EPA retained the 24-hour PM10

standard at 150 μg/m3 25 (not to be exceeded more than once per year on average over 3 years) and 

26 revoked the annual standard because available evidence generally did not suggest a link between 

27 long-term exposure to current ambient levels of coarse particles and health or welfare effects. 

28 The 2006 primary standards were based primarily on a large body of epidemiological evidence 

29 relating ambient PM concentrations to various adverse health outcomes. The 2006 secondary 

30 standards for PM2.5 and PM10 were revised to be identical to the primary standards, on the basis 

31 that in the Administrator’s judgment these standards, in conjunction with the regional haze 

 1

 In the revisions to the PM NAAQS finalized in 2006, EPA tightened the constraints on the spatial averaging option 

limiting the conditions under which some areas may average measurements from multiple community-oriented 

monitors to determine compliance (see 71 FR 61165-61167, October 17, 2006). 
September 2009 1-2 DRAFT - Do Not Quote or Cite 

1 program , will provide appropriate protection to address PM-related welfare effects, including 

2 visibility impairment, effects on vegetation and ecosystems, materials damage and soiling, and 

3 effects on climate change. 

The next periodic review of the PM NAAQS is now underway.2 4 In the Integrated 

5 Review Plan for the National Ambient Air Quality Standards for Particulate Matter, March 2008 

6 (US EPA, 2008a), EPA outlined the science policy questions that will frame this review, outlined 

7 the process and schedule that the review will follow, and provided more complete descriptions of 

8 the purpose, contents, and approach for developing the key documents that will be developed in 

the review.3 9 EPA is currently completing the process of assessing the latest available policy10 relevant scientific information to inform the review of the PM standards. The latest draft of this 

11 assessment is contained in the second external review draft of the Integrated Science Assessment 

12 for Particulate Matter (ISA, US EPA, 2009a) which was released in July 2009 for review by 

13 CASAC and for public comments. The 2009 second draft PM ISA includes a summary of the 

14 scientific evidence for the relationship of PM to visibility effects, remote area and urban haze 

15 conditions, the PM components responsible for visibility impacts, and studies of public 

16 preference with respect to urban visibility conditions. 

17 Building upon the visibility effects evidence presented in the second draft PM ISA, as 

18 well as CASAC advice (Samet, 2009) and public comments on a planning document (US EPA, 

19 2009b), EPA’s Office of Air Quality Planning and Standards (OAQPS) has developed this draft 

20 Urban-Focused Visibility Assessment (UFVA) describing the quantitative assessments being 

21 conducted by the Agency to support the review of the secondary PM standards. This draft 

22 document is a concise presentation of the methods, key results, observations, and related 

23 uncertainties associated with the quantitative analyses performed. Revisions to this draft UFVA 

24 will draw upon the final ISA and will reflect consideration of CASAC and public comments on 

25 this draft UFVA. 

26 The final ISA and final UFVA will inform the policy assessment and rulemaking steps 

27 that will lead to final decisions on the secondary PM NAAQS. A Policy Assessment (PA) is 

28 now being prepared by OAQPS staff to provide a transparent staff analysis of the scientific basis 

29 for alternative policy options for consideration by senior EPA management prior to rulemaking. 

 2

 See http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_index.html for more information on the current and 

previous PM NAAQS reviews. 

3

 On November 30, 2007, EPA held a consultation with the Clean Air Scientific Advisory Committee (CASAC) on 

the draft IRP (Henderson, 2008). Public comments were also requested on the draft plan and presented at that 

CASAC teleconference. The final IRP incorporated comments received from CASAC and the general public on the 

draft plan as well as input from senior Agency managers. CASAC is an independent scientific advisory committee 

established to meet the requirements of section 109(d)(2) of the Clean Air Act. See 

http://yosemite.epa.gov/sab/sabpeople.nsf/WebCommittees/CASAC for more information, and, in particular, 

information on the CASAC PM Review Panel activities.
September 2009 1-3 DRAFT - Do Not Quote or Cite 

1 The PA is intended to help “bridge the gap” between the Agency’s scientific assessments, 

2 presented in the ISA and UFVA, and the judgments required of the Administrator in determining 

3 whether it is appropriate to retain or revise the secondary PM standards. The PA will integrate 

4 and interpret information from the ISA and the UFVA to frame policy options and to facilitate 

5 CASAC’s advice to the Agency and recommendations on any new standards or revisions to 

6 existing standards as may be appropriate, as provided for in the Clean Air Act. A very 

7 preliminary draft PA is planned for release in September 2009 to facilitate discussion on the 

8 overall structure, areas of focus, and level of detail to be included in an external review draft of 

9 the document, which EPA plans to release for CASAC review and public comment later this 

10 year. A discussion of the preliminary draft PA with CASAC will be held in conjunction with 

11 CASAC review and public comment of the second draft ISA, this draft UFVA, and a draft 

12 assessment document that will inform the review of the primary PM standards - Risk Assessment 

13 to Support the Review of the PM Primary National Ambient Air Quality Standards - External 

14 Review Draft (US EPA, 2009c). 

15 1.1 PM NAAQS BACKGROUND 

16 In the review of the secondary PM NAAQS completed in 2006, EPA took into account 

that the Regional Haze Program

4 17 , implemented under sections 169A and 169B of the CAA, was 

18 established to address all human-caused visibility impairment in Class I areas. Recognizing that 

19 efforts were underway under that program, EPA focused the 2006 PM NAAQS review on 

20 visibility impairment primarily in urban areas. The EPA evaluated the levels of visibility 

21 impairment occurring in urban areas and assessed available information on public preferences 

22 regarding acceptability of PM-related urban visibility impairment. At that time, EPA’s focus 

23 continued to remain on particle size and mass and EPA staff determined that PM2.5 size and 

24 particle mass, rather than particle composition, remained the most appropriate approach for 

25 addressing PM-related urban visibility effects. EPA recognized that PM composition and 

26 relative humidity are important factors in the relationship between light extinction (a measure of 

27 visibility) and PM mass concentration. The EPA’s assessment of PM and meteorological data 

28 from 161 cities showed that the least variation in the relationship of light extinction to PM2.5

29 mass concentration was for afternoon periods when low relative humidity conditions generally 

30 prevail (EPA, 2005). 

31 The EPA proposed to revise the secondary standards by making them identical to the 

32 suite of proposed primary standards for fine and coarse particles, providing protection against 

33 PM-related public welfare effects including visibility impairment, effects on vegetation and 

 4 See http://www.epa.gov/air/visibility/program.html for more information on EPA’s Regional Haze Program. 
September 2009 1-4 DRAFT - Do Not Quote or Cite 

1 ecosystems, and materials damage and soiling (71 FR 2620). The EPA also solicited comment on 

2 adding a new sub-daily PM2.5 secondary standard to address visibility impairment in urban areas. 

3 CASAC provided additional advice to EPA in a letter to the Administrator requesting 

4 reconsideration of CASAC’s recommendations for both the primary and secondary PM2.5

5 standards as well as standards for thoracic coarse particles (Henderson, 2006). With regard to 

6 the secondary standard, CASAC reaffirmed “... the recommendation of Agency staff regarding a 

7 separate secondary fine particle standard to protect visibility..... The CASAC wishes to 

8 emphasize that continuing to rely on primary standards to protect against all PM-related adverse 

9 environmental and welfare effects assures neglect, and will allow substantial continued 

10 degradation, of visual air quality over large areas of the country” (Henderson, 2006). 

11 On September 21, 2006, EPA announced its final decisions to revise the secondary 

12 NAAQS for PM to provide increased protection of public welfare by making them identical to 

13 the revised primary standards (71 FR 61144, October 17, 2006). This was designed to address 

14 both visibility and other non-visibility welfare related effects. Specifically, with regard to the 

15 secondary standards for fine particles, EPA revised the level of the 24-hour PM2.5 standard to 35 

μg/m3, retained the level of the annual PM2.5 annual standard at 15 μg/m3 16 , and revised the form 

17 of the annual PM2.5 standard by narrowing the constraints on the optional use of spatial 

18 averaging. With regard to the secondary standards for coarse particles, EPA retained PM10 as the 

19 indicator for purposes of regulating the coarse fraction of PM10 (referred to as thoracic coarse 

20 particles or coarse-fraction particles; generally including particles with a nominal mean 

21 aerodynamic diameter greater than 2.5 μm and less than or equal to 10 μm, or PM10-2.5). EPA 

retained the 24-hour PM10 standard at 150 μg/m3 22 and revoked the annual PM10 standard. 

23 Several parties filed petitions for review following promulgation of the revised PM 

24 NAAQS in 2006. These petitions addressed a number of issues, including the decision to set the 

25 secondary PM2.5 standards identical to the primary standards. On judicial review the court 

26 remanded the secondary PM2.5 NAAQS to EPA because the Agency failed to adequately explain 

27 why setting the standards equal to the primary PM2.5 standards provided the required protection 

28 from visibility impairment. In particular, the Agency failed to identify a target level of visibility 

29 impairment that would be requisite to protect the public welfare, and improperly relied on a 

30 comparison of the number of counties which would be in nonattainment for the revised primary 

31 NAAQS compared to various alternative secondary standards. Among other things, this 

32 equivalence analysis failed to address the issue of regional differences in humidity-related effects 

33 on visibility American Farm Bureau Federation v. EPA, 559 F. 3d 512 (D.C. Cir. 2009) 
September 2009 1-5 DRAFT - Do Not Quote or Cite 

1 1.2 SCOPE OF URBAN-FOCUSED VISIBILITY ASSESSMENT 

2 This chapter provides an overview of the scope and key design elements of the UFVA 

3 conducted for this review, including the process that has been followed to design the analyses. 

4 Following initiation of the current PM NAAQS review, we began the design of this assessment 

5 by reviewing the analyses completed during the previous PM NAAQS review (Abt Associates 

6 Inc., 2001; US EPA, 2005, chapter 6) with an emphasis on considering key limitations and 

7 sources of uncertainty recognized in that analysis. Furthermore, as an initial step in the overall 

8 PM NAAQS review, EPA invited a wide range of external experts as well as EPA staff, 

9 representing a variety of areas of expertise to participate in a workshop titled, “Workshop to 

10 Discuss Policy-Relevant Science to Inform EPA’s Integrated Plan for the Review of the 

11 Secondary PM NAAQS” (72 FR 34005, June 20, 2007). This workshop provided an opportunity 

12 for the participants to broadly discuss the key policy-relevant issues around which EPA would 

13 structure the PM NAAQS review and to discuss the most meaningful new science that would be 

14 available to inform our understanding of these issues. One session of this workshop was 

15 centered around issues related to visibility impacts associated with ambient PM. Specifically, 

16 the discussions focused on the extent to which new research and/or improved methodologies 

17 were available to inform how EPA evaluated visibility impairment in this review. 

18 Based in part on these workshop discussions, EPA developed a draft IRP outlining the 

19 schedule, the process, and the key policy-relevant science issues that would guide the evaluation 

20 of the air quality criteria for PM and the review of the primary and secondary PM NAAQS 

21 including initial thoughts for conducting quantitative assessments (US EPA, 2007, chapter 6). 

22 On November 30, 2007, CASAC held a teleconference with EPA to provide its comments on the 

23 draft IRP (72 FR 63177, November 8, 2007). Public comments were also presented at that 

24 teleconference. A final IRP incorporating comments received from CASAC and the general 

25 public on the draft plan was issued in March 2008 (US EPA, 2008a). 

26 On October 6-8, 2008 the EPA sponsored an urban visibility workshop in Denver, 

27 Colorado to identify and discuss methods and materials that could be used in “next step” projects 

28 to develop additional information about people’s preferences for reducing existing impairment of 

29 urban visibility, and about the value of improving urban visibility. Invited individuals came from 

30 a broad array of relevant technical and policy backgrounds, including visual air quality (VAQ) 

31 science, sociology, psychology, survey research methods, economics, and EPA’s process of 

32 setting NAAQS. The 23 people who attended the workshop (including one via teleconference 
September 2009 1-6 DRAFT - Do Not Quote or Cite 

1 line) came from EPA, the National Oceanic and Atmospheric Administration (NOAA), NPS, 

academia, regional and state air pollution planning agencies, and consulting firms.5 2 

3 As a next step in the design of the quantitative assessments, EPA developed a planning 

4 document outlining the initial design for the PM NAAQS visibility assessment - Particulate 

5 Matter National Ambient Air Quality Standards: Scope and Methods Plan for Urban Visibility 

6 Impact Assessment, henceforth Scope and Methods Plan (US EPA, 2009b). This planning 

7 document was released for CASAC consultation and public review in February 2009. Based on 

8 consideration of CASAC and public comments on that Scope and Methods Plan, along with 

9 ongoing review of the latest PM-related literature, we made modifications to the scope and 

10 design of the visibility assessment and completed our initial analyses. These modifications, as 

11 well as the current scope of the UFVA and the rationale supporting it, are described in this 

12 section below. 

13 The EPA staff continues to believe that a focus on urban area visibility is appropriate. In 

14 articulating a rationale for this conclusion, we have reviewed the information contained in the 

15 second draft ISA and find the following information compelling: 1) PM levels in urban areas are 

16 often in excess of those of the surrounding region since urban haze typically includes both 

17 regional and local contributions (US EPA, 2009a; sections 9.2.3.3 and 9.2.3.4), suggesting the 

18 potential for higher levels of PM-induced visibility impairment in urban areas; 2) the existence of 

19 numerous urban visibility protection programs and goals demonstrates that urban VAQ is noticed 

20 and an important value to urban residents (US EPA, 2009a; section 9.2.4), and 3) the existence of 

21 large urban populations suggests that potentially more people are routinely affected by poor 

22 VAQ than in rural areas. One aspect of the urban visibility conditions assessment, as depicted in 

23 Figure 1-1 of section 1.3 of the Scope and Methods document (US EPA, 2009b), has been 

24 modified. Taking into account the nature of urban versus more remote area PM composition, 

25 and input received at the April 2, 2009 CASAC meeting, EPA staff has concluded that it is 

26 unnecessary to develop a new urban-optimized algorithm at this time and that it remains 

27 appropriate in the context of this assessment to use the original IMPROVE algorithm to relate 

28 urban PM to local haze (PM light extinction). 

29 With regard to the urban visual air quality preference assessment described in the Scope 

30 and Methods document (US EPA, 2009b, section 1.3), more significant modifications have 

31 occurred. EPA staff has decided to conduct a reanalysis of the urban visibility preference studies 

32 available at the time of the 2006 PM NAAQS review, rather than conduct new public preference 

33 studies, as it has become apparent that the results of these studies would be unlikely to be 

34 completed in time to inform this review. Recognition that the initial plans described in the Scope 

 5

 To view the complete report from the October 2008 urban visibility workshop, see: 

http://vista.cira.colostate.edu/improve/Publications/GrayLit/gray_literature.h tm
September 2009 1-7 DRAFT - Do Not Quote or Cite 

1 and Methods document were possibly overly ambitious was also shared by members of CASAC 

2 (see individual member comments; Samet, 2009). This analysis, therefore, relies on existing, 

3 rather than new, urban visibility preference studies and is designed to explore the similarities and 

4 differences (comparability) between these studies and assess what information can be drawn 

5 from these results to inform the selection of VAQ candidate protection levels (CPLs) to be used 

6 in subsequent impact assessments. Further, information presented during the public comment 

7 phase of the April 2, 2009 CASAC meeting and later provided to EPA staff, led to the inclusion 

8 of a recent study by Smith and Howell (2009) for Washington, D.C. in the reanalysis. 

9 As described in the Scope and Methods document (US EPA, 2009b), EPA staff is 

10 continuing to focus assessments in this document in terms of an alternative indicator for PM 

11 visibility impairment, i.e. PM light extinction, instead of the traditional PM2.5 mass 

12 concentration. The 2005 Staff Paper discussed the use of a four-hour afternoon PM2.5 standard, 

13 where the underlying rational was that the generally lower afternoon relative humidity tended to 

14 produce a more uniform relationship between light extinction and PM2.5 mass concentration 

15 throughout the country, therefore providing a more uniform level of visibility protection 

16 nationwide. However, this more uniform level of visibility protection was limited to the 

17 afternoon hours of the day when relative humidity and visibility impairment are typically the 

18 lowest. However, visibility conditions can be the poorest when relative humidity levels are the 

19 highest. Thus, from a public welfare perspective, greater protection from visibility impairment is 

20 needed during the times when humidity is high. In that regard, morning relative humidity 

21 conditions, which are often generally higher in the Eastern US and coastal areas than in the West, 

22 causes the same PM concentrations to produce much higher PM-related visibility impairment in 

23 those regions than in areas with lower morning relative humidity resulting in unequal visibility 

24 impairment at the national scale. Unlike PM mass concentration, which is determined by 

25 removing the liquid water from the PM prior to measuring it, PM light extinction can be 

26 measured at ambient humidity conditions so that it includes the enhanced light extinction 

27 resulting from the liquid water that is associated with the hygroscopic PM components in the 

28 atmosphere. PM light extinction, like PM mass concentration, is a measurable physical 

29 characteristic of ambient PM. Thus, EPA believes that use of PM light extinction as the indictor 

30 for a secondary PM NAAQS is a more appropriate target and more directly related to the welfare 

31 effect of interest. 

32 1.3 VISIBILITY EFFECTS SCIENCE OVERVIEW 

33 Light extinction is the optical characteristic of the atmosphere that best determines the 

34 impact potential of PM on perceived visibility. Light extinction is the loss of light per unit of 

35 distance and occurs when light is either scattered or absorbed. Particulate matter and gases can 
September 2009 1-8 DRAFT - Do Not Quote or Cite 

1 both scatter and absorb light. Light scattering by gases (e.g., nitrogen, oxygen, etc.) that 

2 comprise the atmosphere (also known as Rayleigh or clean-air scattering) is related to the density 

3 of the air, which is sufficiently constant with elevation that it can be considered a known 

4 constant value for any location. NO2 is the only atmospheric pollutant gas that absorbs light 

5 appreciably and its effects are generally small (i.e. less than 5%) compared to PM light 

6 extinction, so its contribution to ambient visibility impacts is often ignored (as is done here). By 

7 this assumption, light extinction is approximated as the sum of PM light extinction (including 

8 both scattering and absorption) plus Rayleigh scattering, where the former characterizes the PM 

9 contribution to visibility impacts, and the latter is taken to be a time invariant constant depending 

10 only on elevation above sea level. In the same way PM light extinction is a good measure of the 

11 degree of visibility impairment. 

12 Visual air quality is defined as the visibility effect caused solely by air quality conditions 

13 and excluding those associated with meteorological conditions like fog and precipitation. It is 

commonly measured as either light extinction (in terms of inverse megameters, Mm-1 14 ) or the 

15 deciview (dv) metric (Pitchford and Malm, 1993), which is a logarithmic function of extinction. 

16 Extinction and deciviews are physical measures of the amount of visibility impairment (e.g., the 

17 amount of “haze”), with both extinction and deciview increasing as the amount of haze increases. 

18 A haziness index measured in deciview units was developed for use in visibility perception 

19 studies because it has a more linear relationship to perceived changes in haze compared with 

20 light extinction. The haziness index in deciviews (dv) is defined as ten times the natural 

logarithmic of one tenth of the light extinction in inverse megameter units (Mm-1 21 ) (Pitchford and 

22 Malm, 1993). 

23 There is no simple one-to-one correspondence between PM concentration and PM light 

24 extinction. However, as shown in Figure 1-1, the PM light extinction can be estimated from PM 

25 composition and relative humidity data, using an algorithm with assumed light extinction 

26 efficiencies for each of the major PM species and water growth factors for the hygroscopic 

27 species. Though PM light extinction can be accurately determined by direct measurements, there 

28 is only limited existing urban PM light extinction data. As a result, the assessment below will 

29 principally use monitored and modeled PM mass, species estimates, and relative humidity 

30 measurements. 

31 The extent to which any amount of light extinction affects a person’s ability to view a 

32 scene depends on both scene and light characteristics. For example the appearance of a nearby 

33 object (i.e. a building) is generally less sensitive to a change in light extinction than the 

34 appearance of a similar object at a greater distance. For a scene with known characteristics, the 

35 amount of degradation in the scene associated with a change in light extinction can be 
September 2009 1-9 DRAFT - Do Not Quote or Cite 

1 determined and the change in appearance can be realistically displayed on a digital photograph of 

2 the scene using the WinHaze system. 

3 Survey studies have used sets of photographs depicting a range of visibility conditions on 

4 urban scenes to assess the public’s opinion on the acceptability of conditions. For the specific 

5 scenes used in such studies there is a known/predetermined one-to-one correspondence between 

6 the percieved haze in the photographs and the amount of PM light extinction. For visibility 

7 preference studies, visibility levels are generally characterized using the haze index in units of 

8 deciview (similar to the decibel scale for sound). 

9 

10 Figure 1-1. Diagram showing the relationship steps between ambient PM and visibility 

11 impairment. 

12 1.4 GOALS AND APPROACH 

13 The principal goal of the current UFVA is to characterize current levels of visibility 

14 impairment, with a focus on urban areas, both in terms of the current secondary PM standards, as 
September 2009 1-10 DRAFT - Do Not Quote or Cite 

1 well as in terms of alternative standards, including indicators and forms that may better reflect 

2 the relationship between PM and visibility impairment. In particular, this UFVA focuses on the 

3 effectiveness of a light extinction-based indicator for a possible secondary PM NAAQS (see 

4 Figure 1-1). This is done by comparing estimates of hourly light extinction in 15 major U.S. 

5 urban areas over the three-year period 2005-2007 to the CPLs, which are a range of light 

6 extinction values beyond which half of the participants in assessed urban visibility preference 

7 studies indicated the haze conditions were unacceptable (see discussion in chapter 2 below and 

8 Stratus Consulting Inc., 2009). In addition, the UFVA will include additional characterizations of 

9 the effectiveness of a sub-daily PM2.5 mass concentration indicator, which was explored in the 

10 2005 PM staff paper and which was considered a viable option by EPA staff and CASAC in the 

11 2006 review. These latter assessments will be summarized in Appendix A. 

12 The previous PM NAAQS review used the results of visibility preference survey studies 

13 conducted in Denver (1990), Phoenix (2003), and British Columbia (1993) as the basis for 

14 suggesting that a standard set to protect visibility conditions to a level within a visual range from 

between about 40 km to about 60 km (corresponding to light extinction from ~100 Mm-1 15 to ~67 

Mm-1 16 ) could represent an appropriate degree of welfare protection from PM. With the exception 

17 of a small pilot study conducted in Washington, D.C. in 2001 (9 participants; Abt Associates 

18 Inc., 2001), and a replicate study also conducted for Washington, D.C. in 2009 (26 participants; 

19 Smith and Howell, 2009), there have been no additional visibility preference survey studies upon 

20 which to base the selection of CPLs. The EPA staff, with contractor support, has conducted a 

21 more detailed, in-depth assessment of the results from these studies, including the two recent 

22 Washington, D.C. studies. This assessment includes an analysis that combines data from across 

23 all studies to examine the consistency of the results between the surveys (Stratus Consulting Inc., 

24 2009). Based on the results of this analysis, we have been able to refine the range of visibility 

25 conditions that could represent an appropriate degree of public welfare visibility protection that 

26 was put forth in the 2006 review, and to determine a central tendency value for the CPLs. These 

27 analyses and results are described below in chapter 2. 

28 In the previous PM NAAQS review, the characterization of urban visibility conditions 

29 were based on IMPROVE algorithm estimates using the 2001 to 2003 PM2.5 mass and speciation 

30 data by assuming a constant composition for every hour of the day equal to the 24-hour 

31 measured composition and by using either actual or monthly average (10-year mean) hour of the 

32 day relative humidity for 161 urban area. Statistical relationships between hourly light extinction 

33 estimates and concurrent hourly PM2.5 mass concentrations were used to show that daytime and 

34 especially afternoon relationships are relatively strong with a similar linear relationship for both 

eastern and western urban areas (i.e. R2

>0.6, slope ~6 m2 35 /g). Relationships that included the 
September 2009 1-11 DRAFT - Do Not Quote or Cite 

1 non-daylight hours were not as strong and differed more between eastern and western urban 

2 areas. 

3 The current assessment of urban visibility conditions (as described in chapter 3) is similar 

4 in its development of an algorithm to estimate hourly light extinction using PM2.5 mass and 

5 speciation data with measured relative humidity. However, it differs in that instead of assuming 

6 constant composition for PM2.5, composition is made to vary during the day using urban-specific 

7 monthly mean diurnal variations of species concentrations determined from regional air quality 

8 model results, while constraining the means of the hourly species concentration for each day to 

9 closely match the 24-hour duration measured species concentrations. The current assessment 

10 examines 15 urban areas using 2005 to 2007 data sets (i.e. the same cities as used in the current 

11 assessment for the primary standard). 

12 1.5 ORGANIZATION OF DOCUMENT 

13 The remainder of this document is organized as follows: Chapter 2 includes an analysis 

14 of the urban visibility preference studies with a discussion of similarities and differences 

15 regarding the approaches and methods used and results obtained for each study. This chapter 

16 also includes a summary discussion of the results of a composite assessment of the combined 

17 four city results and use of these results in the selection of the alternative levels evaluated in the 

18 remainder of the assessment. Chapter 3 describes the analytical approach, methods, and data 

19 used in conducting the assessment of recent urban visibility conditions, both in terms of PM2.5

20 and light extinction indicators for the set of urban case studies included in this analysis. Selected 

21 results are presented in chapter 3, with additional results found in the Appendices. Chapter 4 

22 presents estimates of PM2.5 and light extinction conditions generated for the urban case studies 

23 for six alternative PM2.5 and light extinction scenarios. Additional information regarding 

24 approaches and results for both chapters 3 and 4 are presented in Appendices A-F). 
September 2009 2-1 DRAFT - Do Not Quote or Cite 

1 2 URBAN VISIBILITY PREFERENCE STUDIES 

2 The purpose of this chapter is to present the reanalysis of the methods and results of 

3 existing studies of preferences for urban visibility that EPA staff conducted (with contractor 

4 support) in order to provide information useful in selecting a range of CPLs in terms of light 

5 extinction values for subsequent use in the UFVA assessments of current and alternative VAQ 

6 conditions. To date, available urban visibility preference studies have examined individuals’ 

7 desire for good VAQ by investigating the basic question, “What level of visibility degradation is 

8 acceptable?” Preference studies have used a similar group interview type of survey to investigate 

9 the level of visibility impairment that participants described as “acceptable.” The specific 

10 definition of acceptable is largely left to each individual survey participant, allowing each to 

11 identify their own preferences. 

12 The reanalysis effort included three completed urban visibility preference survey studies 

13 plus a pair of smaller focus studies designed to explore and further develop urban visibility 

14 survey instruments. The first urban visibility study conducted was in Denver, Colorado (Ely et 

15 al., 1991), which developed the basic survey method used in all the subsequent studies. The two 

16 other western studies included one in the lower Fraser River valley near Vancouver, British 

17 Columbia (BC), Canada (Pryor, 1996), and one in Phoenix, Arizona (BBC Research & 

18 Consulting, 2003). A pilot focus group study was also conducted for Washington, DC (Abt 

19 Associates Inc., 2001). In response to an EPA request for public comment on the Scope and 

20 Methods Plan (74 FR 11580, March 18, 200), Dr. Anne Smith provided comments (Smith, 2009) 

21 about the results of a new Washington, D.C., focus group study that had been conducted using 

22 methods and approaches similar to the method and approach employed in the EPA pilot study 

23 (Smith and Howell, 2009). In total, 852 individuals participated in these studies in four cities, 

24 with each individual responding to a series of questions answered while viewing a set of images 

25 of various urban VAQ conditions. 

26 2.1 METHODS USED IN PREVIOUS STUDIES 

27 One direct physical measure of VAQ used in many visibility analyses is light extinction. 

28 Light extinction is the loss of light per unit of distance, and measures the ability of particles and 

29 gases in the atmosphere to scatter and absorb light traveling between an object and a person (or 

30 camera). Extinction and haziness are physical measures of the amount of visibility impairment 

31 (e.g., the amount of “haze”), with both extinction and haziness increasing as the amount of haze 

32 increases. 
September 2009 2-2 DRAFT - Do Not Quote or Cite 

In all but one6 1 of the visibility preference studies reviewed in this paper, participants 

2 were shown a series of different VAQ conditions projected on a large screen using a slide 

3 projector. In the earliest two studies (the Denver and lower Frazer River Valley studies) a range 

4 of VAQ conditions were presented by projecting photographs (slides) of actual VAQ conditions. 

5 The photographs were taken on different days from the same location, and presented the same 

6 scene. Photographs were selected to avoid depicting significant weather events (e.g., rain, snow, 

7 or fog), and where measured extinction data were available from the time the photograph was 

8 taken. 

9 The Phoenix study, as well as the subsequent Washington, D.C. survey instrument, 

10 development projects, used photographic-quality images generated by a computer to present 

11 different VAQ conditions. The images were developed from an original photograph using the 

12 WinHaze software program, which is based on a technique described in Molenar et al. (1994). 

13 The Phoenix study and the 2001 Washington, DC project projected slides of digital images 

14 prepared by WinHaze. The 2009 Washington, DC project presented images directly from the 

15 desktop version of WinHaze using either a liquid crystal display (LCD) projector or a computer 

16 monitor. 

17 WinHaze analysis synthetically superimposes a uniform haze on a digitized, near-pristine 

18 actual photograph. The WinHaze computer algorithm calculates how a given extinction level 

19 would impair the appearance of each individual portion of the photograph. A major advantage of 

20 presenting WinHaze-generated images is that they provide viewers depictions of alternative 

21 VAQ levels, with each image containing exactly the same scene, with identical light angle, time 

22 of day properties, weather conditions, and specific scene content details (e.g., the amount of 

23 traffic in a intersection). Additional details about WinHaze, and a discussion of the applicability 

24 of WinHaze images for regulatory purposes, is in the 2004 PM Criteria Document (U.S. EPA, 

25 2004). The desktop version of WinHaze is available online (Air Resources Specialists, 2008). 

26 The first urban visibility preference study was conducted in Denver, Colorado (Ely et al., 

27 1991), and developed the basic survey method used in all the subsequent studies. Although there 

28 are variations in specific details in each study, all the studies use a similar overall approach (key 

29 variations are discussed in the section on each study later in this paper). 

30 Visibility preference studies consist of a series of group interview sessions, where the 

31 participants are shown a set of photographs or images of alternative VAQ conditions and asked a 

32 series of questions. The group interview sessions are conducted multiple times with different 

 6

 Smith and Howell (2009) used digital projection technology not available at the time of the other studies to present 

the series of VAQ conditions. Some of the participants in the Smith and Howell study were shown images using a 

LCD projector connected to a laptop computer. In other sessions, participants in the Smith and Howell study were 

shown images on a computer monitor connected to the computer.
September 2009 2-3 DRAFT - Do Not Quote or Cite 

1 participants. Ideally the participants will be a representative sample of the residents of the 

2 metropolitan area. While all studies agree that this is the preferred approach, due to the high cost 

3 of organizing and conducting a series of in-person group interviews with a large, statistically 

4 representative sample, only the Phoenix study was able to fully meet this objective. 

5 During a group interview session, the participants were instructed to consider whether the 

6 VAQ in each photograph or image would meet an urban visibility standard, according to their 

7 own preferences and considering three factors: 

8 

9 1. The standard would be for their own urban area, not a pristine national park area 

10 where the standards might be more strict 

11 2. The level of an urban visibility standard violation should be set at a VAQ level 

12 considered to be unreasonable, objectionable, and unacceptable visually 

13 3. Judgments of standards violations should be based on visibility only, not on 

14 health effects. 

15 The photographs (images) are not shown in order of ascending or descending VAQ 

16 conditions; the VAQ conditions are shown in a randomized order (with the same order used in 

17 each group interview session). In order to check on the consistency of each individual’s 

18 answers, the full set of photographs (images) shown during the group interview included 

19 duplicates with the identical VAQ conditions. 

20 The participants were initially given a set of “warm up” exercises to familiarize them 

21 with how the scene in the photographs or image appears under different VAQ conditions. The 

22 participants next were shown 25 randomly ordered photographs (images), and asked to rate each 

23 one based on a scale of 1 (poor) to 7 (excellent). They were then shown the same photographs or 

24 images again (in the same order), and asked to judge whether each of the photographs (images) 

25 would violate what they would consider to be an appropriate urban visibility standard (i.e., 

26 whether the level of impairment was “acceptable” or “unacceptable”). 

27 2.2 DENVER, COLORADO 

28 The Denver urban visibility preference study (Ely et al., 1991) was conducted on behalf

29 of the Colorado Department of Public Health and Environment (CDPHE). The study consisted 

30 of a series of focus group sessions conducted in 1989 with participants from 16 civic 

associations, community groups, and employees of state and local government organizations.7 31 

 7

 No preference data were collected at a 17th focus group session due to a slide projector malfunction. 
September 2009 2-4 DRAFT - Do Not Quote or Cite 

1 The participants were not selected to be a fully representative sample of the Denver metropolitan 

2 population but were instead selected to take advantage of previously scheduled meetings. 

3 During the 16 focus group sessions, a total of 214 individuals were asked to rate 

4 photographs of varying visibility conditions in Denver. The photographs were taken November 

5 1987 through January 1988 by a camera in Thornton, Colorado. Thornton is suburb of Denver, 

6 located approximately six miles north of downtown Denver. The photographs were taken as part 

7 of a CDPHE study of Denver’s air quality. The scene in the photographs was toward the south 

8 from Thornton and included a broad view of downtown Denver and the mountains to the south. 

9 Each group was shown one of two sets of 20 randomly ordered unique photographs (13 of the 

10 sessions included 5 duplicate slides, for a total of 25 photographs, to evaluate consistency of 

11 responses). The two sets of different slides were used to investigate whether the responses 

12 between the two sets of photographs were different (no differences were found). Approximately 

13 100 participants viewed each photograph. Projected color slides were used to present the 

14 photographs to focus group participants, and were projected on a large screen 

15 The VAQ conditions in each Denver photograph were recorded when the photograph was 

16 taken and measured by a transmissometer yielding hourly average light extinction, bext. The 

17 transmissometer was located in downtown Denver, approximately eight miles from the camera 

18 and in the middle of the camera’s view path. Ely et al. (1991) provide the time of day and 

19 measured extinction level for each photograph. The extinction levels presented in the Denver 

photographs ranged from 30 to 596 Mm-1 20 . This corresponds to 11dv to 41dv, approximating the 

10th to 90th 21 percentile of wintertime visibility conditions in Denver in the late 1980s. 

22 The participants first rated the VAQ in each photograph on a 1 to 7 scale, and 

23 subsequently were asked if each photograph would violate an urban visibility standard. The 

24 individual’s rating on the 1 to 7 scale and whether the photograph violated a visibility standard 

25 were highly correlated (Pearson correlation coefficient greater than 80%). 

26 The percent of participants who found a photograph acceptable to them (i.e., would meet 

27 an appropriate urban visibility standard) was calculated for each photograph. Figure 2-1 shows 

28 the results of the Denver participants’ responses, with VAQ measured in deciviews. 

29 Ely et al. (1991) introduce a “50% acceptability” criteria analysis of the Denver 

30 preference study results. The 50% acceptability criteria is designed to identify the VAQ level 

31 that best divides the photographs into two groups: those with a VAQ rated as acceptable by the 

32 majority of the participants, and those rated not acceptable by the majority of participants. While 

33 no single VAQ level creates a perfect separation between the two groups, the CDPHE identified 

34 a VAQ of 20.3 dv as the point that best separates the Denver study responses into “acceptable” 

35 and “not acceptable” groups. Based in part on the findings of the Denver visibility preference 

study, the CDPHE established a Denver visibility standard at bext = 76 Mm-1 36 (dv = 20.3). 
September 2009 2-5 DRAFT - Do Not Quote or Cite 

1 Figure 2-1. Percent of Denver participants who consider VAQ in each photograph 

2 “acceptable.” 

0%

50%

100%

10 15 20 25 30 35 40 45

Deciview

% participants rating 

"acceptable"

% acceptable Denver standard

3 

4 Using 20.3 dv as a 50% acceptability criteria led to six photographs being inconsistently 

5 rated by the majority of the viewers. A photograph was inconsistently rated for two possible 

6 reasons; either the photograph’s VAQ was at least 1 dv better than the Denver standard (i.e., dv < 

7 19.3) but was judged to be “unacceptable” by a majority of the participants rating that 

8 photograph, or the VAQ was at least 1 dv worse than the standard (> 21.3 dv) but found to be 

9 acceptable by the majority of the participants. This definition of inconsistent rating helps 

10 evaluate the robustness of the study results to support the selection of the Denver urban visibility 

standard at 76 Mm-1 11 (20.3 dv) by identifying photographs with VAQ a minimum of 1 dv above 

12 or below the standard and ignoring “near misses” involving photographs within 1 dv of the 

13 standard. A change of 1 or 2 dv in uniform haze under many viewing conditions will be seen as a 

14 small but noticeable change in the appearance of a scene, regardless of the initial haze condition 

15 (U.S. EPA, 2004). 

16 Table 2-1 presents information about the six photographs that were inconsistently rated. 

17 All six of the inconsistently rated photographs were taken at 9:00 a.m. The five inconsistently 

18 rated photographs with a VAQ better than the Denver standard have a VAQ at least 2 dv below 

19 the standard. The VAQ in the only inconsistently rated photograph with air quality worse than 

20 the standard (Photograph #6) is 1.1 dv above the standard. The study used 18 photographs from 

21 9:00 a.m., so a third of the 9:00 a.m. photographs were inconsistently rated. Conversely, none of 

22 the 32 photographs taken at noon or 3:00 p.m. were inconsistently rated. 

 23 

 24 
September 2009 2-6 DRAFT - Do Not Quote or Cite 

1 Table 2-1. VAQ of Denver photos substantively misclassified by majority of participants 

2 

Photograph # 

VAQ in photograph 

in extinction 

(Mm-1) 

VAQ in 

photograph (dv)

% of participants 

who rated the photo 

“acceptable” 

Time of day of 

photograph 

14 44 13.8 43% 9:00 a.m. 

18 54 16.9 43% 9:00 a.m. 

19 54 16.9 31% 9:00 a.m. 

20 55 17.0 42% 9:00 a.m. 

24 60 17.9 13% 9:00 a.m. 

36 85 21.4 72% 9:00 a.m. 

3 

4 Figure 2-2 shows the same data results about percent of participants who rated each 

5 photograph acceptable as in Figure 2-1, but with the time of day of each photograph indicated by 

6 different colors. The time of day colors clearly indicate how inconsistently participants rated 

7 some of the 9:00 a.m. photographs. 

8 Eliminating the 9:00 a.m. photographs creates a “hole” in the range of remaining 

9 photographs; there are no photographs with a VAQ between 17.7 dv and 20.3 dv. As seen in 

10 Figure 2-2, this is a critical range in evaluating the responses. All of the photographs with a VAQ 

11 equal to or better (i.e., a lower dv value) than 17.7 dv are rated acceptable by the majority of the 

12 participants, and all photographs with a VAQ at or above 20.3 dv are rated not acceptable. After 

13 eliminating the 9:00 a.m. photographs, any VAQ level between 17.7dv and 20.3 dv would 

14 completely divide the photographs into two groups with no inconsistent ratings. 

15 A modestly broader range of VAQ conditions provides an even more unambiguous 

16 interpretation of the Denver study results. Every photograph with a VAQ of 17.7 dv or lower was 

17 rated acceptable by 89% or more of the participants, and every photograph with a VAQ of 24.6 

18 or higher was rated not acceptable by 84% or more of the participants. The 17.7 dv to 24.6 dv 

19 range separating the results is shown in Figure 2-3, which also eliminates the 9:00 a.m. results. 
September 2009 2-7 DRAFT - Do Not Quote or Cite 

1 Figure 2-2. Photograph time of day information for the percent of participants who 

2 consider VAQ in each photograph “acceptable.” 

0%

50%

100%

10 15 20 25 30 35 40 45

Deciview

% participants rating 

"acceptable"

9:00 AM 12:00 PM 3:00 PM Denver standard

3 

4 Figure 2-3. Denver photograph time of day results (9:00 a.m. photographs eliminated), 

5 with the broader range (17.7 dv and 24.6 dv) of the 50% acceptability criteria shown. 

0%

50%

100%

10 15 20 25 30 35 40 45

Deciview

% Participants Rating 

"Acceptable"

12:00 PM 3:00 PM Denver Standard Lower Bound Upper Bound

6 2.3 VANCOUVER, BRITISH COLUMBIA, CANADA 

7 The BC urban visibility preference study (Pryor, 1996) was conducted on behalf of the 

8 BC Ministry of Environment following the methods used in the Denver study. Participants were 

9 students at the University of British Columbia, who were in one of four focus group sessions 

10 with between 7 and 95 participants. A total of 180 participants completed the surveys (29 did not 

11 complete the survey). 
September 2009 2-8 DRAFT - Do Not Quote or Cite 

1 The BC study used photographs (projected as slides) depicting various VAQ conditions 

2 in two cities (Chilliwack and Abbotsford) in the lower Fraser River valley in southwestern BC. 

3 Abbotsford is located approximately 75 miles east of Vancouver, BC, and had a 2006 population 

4 of 159,000 (Statistics Canada, 2009a). Abbotsford has a diverse and successful economy, with 

5 approximately 25% of the labor force working in the Vancouver metropolitan area. Chilliwack is 

6 adjacent to Abbotsford to the east. Both cities have experienced rapid population growth, 

7 growing faster than the Vancouver metropolitan area, and are considered suburbs (or exurbs) of 

8 Vancouver. 

9 The survey was conducted at the University of British Columbia (UBC) in 1994. The 

10 participants were 206 undergraduate and graduate students enrolled in classes in UBC’s 

11 Department of Geography. Information about student demographics and where they lived prior 

12 to enrolling at UBC (which potentially influences their knowledge of, and preferences for, 

13 Vancouver area visibility) is not available. 

14 The BC survey showed 20 unique photographs to the participants in random order. Ten 

15 photographs were from Chilliwack, and 10 were from Abbotsford. The Chilliwack photographs 

16 were taken at the Chilliwack Hospital, and the scene includes a complex foreground with 

17 downtown buildings, with mountains in the background up to 40 miles away. Figure 2-4 is a 

18 composite of two of the Chilliwack photographs used in the preference study, showing the scene 

19 with a good visibility day (14.1 dv) in the middle and a significantly impaired day (34 dv) around 

20 the border (Jacques Whitford AXYS, 2007). The Abbotsford photographs were taken at the 

21 Abbotsford Airport. The Abbotsford scene includes fewer man-made objects in the foreground 

22 and is primarily a more rural scene with the mountains in the background up to 36 miles away. 

23 The photographs were taken in July and August 1993 as part of a VAQ and fine 

24 particulate monitoring project sponsored by the BC Ministry of Environment, Lands and Parks 

25 (REVEAL, the Regional Visibility Experimental Assessment in the Lower Fraser Valley). All of 

26 the photographs were taken at either 12:00 p.m. or 3:00 p.m. VAQ data were available for each 

27 photograph from visibility monitors near the location of each camera. The types of VAQ 

28 measurement data available from the two locations were not identical. The Chilliwack location 

29 used both an open-chamber nephelometer and a long path transmissometer and collected hourly 

30 average data on both aerosol light scattering (bsp) and total extinction (bext), respectively. The 

31 visibility monitoring at the Abbotsford location had only a nephelometer and collected only bsp

32 data. 
September 2009 2-9 DRAFT - Do Not Quote or Cite 

1 Figure 2-4. Composite Chilliwack, BC photograph showing VAQ of 14.1 dv and 34 dv. 

2 

3 

4 Total light extinction is the sum of scattering by gases (bsg) and particles (bsp) plus light 

5 absorption by gases (bag) and particles (bap). In order to present the preference results from the 

6 BC study in comparable terms, bext for the Abbotsford photographs is estimated by assuming that 

7 the average of the ratios of PM light extinction (i.e., bap + bsp) to PM light scattering (bsp) for all 

8 ten of the Chilliwack photographs can be multiplied by the Abbotsford nephelometer determined 

9 bsp values corresponding to each of its photographs to estimate its PM light extinction value. By 

10 assuming that absorption by gases (bag) is zero, total light extinction is equal to the PM light 

11 extinction (i.e., bap + bsp) plus particle scattering by gases (i.e., bsg that is approximately equal to 

10Mm-1 12 ). Table 2-2 presents the data from the photographs used in the BC study, including the 

13 estimated bext for the Abbotsford photographs. 

14 There are two caveats to be noted about the extinction data for the photographs reported 

15 in Pryor, 1996. First, in Table 2 of the original article, two of the Abbotsford photographs are 

16 listed with the same date and time (12:00 p.m., 7/26/1993). There is no information provided for 

17 a 3:00 p.m., 7/26/1993 Abbotsford photograph, although there is a Chilliwack photograph from 

18 that time. The preference and VAQ data are presumed to be correct for both photographs and 

19 one of the two identical date/time labels is assumed to be a typographic error. The second caveat 

20 is that bsp levels from the same date and time can differ substantially between Abbotsford and 

21 Chilliwack, and the relative levels can change rapidly, even though the two cities are only 25 

22 miles apart . For example, at 12:00 p.m. on 8/19/1993, the bsp level in Chilliwack was about one- 
September 2009 2-10 DRAFT - Do Not Quote or Cite 

1 Table 2-2. Summary of photographs used in British Columbia study 

2 

Date Time bsp bext

Ratio 

(bext-bsg)/bsp

Estimated 

bext Deciview 

Chilliwack 

7/26/93 12:00 p.m. 86 128 1.372 NA 25.49 

7/26/93 3:00 p.m. 67 112 1.522 NA 24.16 

7/27/93 12:00 p.m. 63 105 1.508 NA 23.51 

7/27/93 3:00 p.m. 119 185 1.471 NA 29.18 

8/2/93 12:00 p.m. 18 37 1.5 NA 13.08 

8/2/93 3:00 p.m. 20 36 1.3 NA 12.81 

8/5/93 12:00 p.m. 45 70 1.333 NA 19.46 

8/5/93 3:00 p.m. 51 96 1.686 NA 22.62 

8/19/93 12:00 p.m. 46 81 1.543 NA 20.92 

8/19/93 3:00 p.m. 105 170 1.524 NA 28.33 

Average 62 102 1.476 21.96 

Abbotsford 

7/26/93 12:00 p.m. 39 NA NA 68 19.17 

7/26/93 12:00 p.m. 82 NA NA 131 25.73 

7/27/93 12:00 p.m. 104 NA NA 205 30.20 

7/27/93 3:00 p.m. 132 NA NA 164 27.97 

8/2/93 12:00 p.m. 24 NA NA 45 15.04 

8/2/93 3:00 p.m. 25 NA NA 47 15.48 

8/5/93 12:00 p.m. 62 NA NA 121 24.93 

8/5/93 3:00 p.m. 75 NA NA 102 23.22 

8/19/93 12:00 p.m. 67 NA NA 224 31.09 

8/19/93 3:00 p.m. 145 NA NA 109 23.89 

Average 76 122 23.67 

3 
September 2009 2-11 DRAFT - Do Not Quote or Cite 

1 Figure 2-5. Percent of BC participants who consider VAQ in each photograph 

2 “acceptable.” 

0%

50%

100%

10 15 20 25 30 35 40 45

% Participants Rating "Acceptable"

Deciview

Results of British Columbia Visiblity Study

Chilliwack Abbotsford

3 

4 

5 third of the Abbotsford bsp level. By 3:00 p.m. the situation was reversed, with the Chilliwack 

6 bsp level 50% higher than Abbotsford. In those three hours the Chilliwack bsp level had over 

doubled (from 46 Mm-1 to 105 Mm-1 7 ), and the Abbotsford level had fallen by over half (from 

145 Mm-1 to 67 Mm-1 8 ). Such substantial changes in measured bsp levels occurring across a 

9 relatively short period of time and short distance, may reflect an inherent uncertainty introduced 

10 by using a single measure of light extinction from a portion of visual scene (where the 

11 nephelometer or transmissometer was operating) to assess visibility conditions throughout an 

12 actual photographs of a complex scene. Spatial and temporal non-uniformity of visibility 

13 conditions within a scene are an atmospheric condition known to occur on some days, and may 

14 contribute to the variability in participant responses in preference studies utilizing actual 

15 photographs. 

16 Figure 2-5 presents the results of the BC study. The division corresponding to the 

17 Denver “50% acceptable” criteria occurs between 22.6 dv and 23.2 dv. All of the photographs 

18 with a VAQ better than 22.6 dv were rated acceptable by the majority of the participants with 

19 one exception (47% of the participants judged the 19.2 dv photograph to be acceptable). All 

20 photographs with a VAQ better than 19.2 dv were rated acceptable by over 90% of the 

21 participants. All photographs with a VAQ worse than 22.6 dv were rated not acceptable by the 
September 2009 2-12 DRAFT - Do Not Quote or Cite 

1 majority of the participants, and all photographs with a VAQ worse than 28.3 dv were rated not 

2 acceptable by over 90% of the participants. 

3 Figure 2-5 also suggests that there may be some difference between the preferences 

4 expressed for the Chilliwack scene and those for the Abbotsford scene. All photographs were 

5 rated by the same individuals (students at UBC), but the summary of the responses indicate that 

6 the participants may have rated as acceptable a worse level of impaired VAQ impairment (e.g., 

7 higher dv levels) in photographs showing more of a downtown area (Chilliwack) than in less 

8 congested scenes (Abbotsford). The strongest evidence for this hypothesis, however, is the 

9 preference for a single photograph (the 19.0 dv photograph from Abbotsford, rated as acceptable 

10 by 47%), previously identified as an outlier observation. 

11 The BC Ministry of the Environment is considering the BC urban visibility preference 

12 study as part of establishing urban and wilderness visibility goals in BC. 

13 2.4 PHOENIX, ARIZONA 

14 The Phoenix urban visibility preference study (BBC Research & Consulting, 2002), 

15 which was conducted on behalf of the Arizona Department of Environmental Quality, used 

16 group interviews based on the methods used in the Denver study, with two major exceptions: (1) 

17 the focus group participants were selected as a representative sample of the Phoenix area 

18 population, and (2) the pictures presented in the focus groups were computer-generated images 

19 to depict specific uniform haze conditions. 

20 The Phoenix study included 385 participants in 27 separate focus group sessions. 

21 Participants were recruited using random digit dialing to obtain a sample group designed to be 

22 demographically representative of the larger Phoenix population. During July 2002, group 

23 interview sessions took place at six neighborhood locations throughout the metropolitan area to 

24 improve the participation rate. Participants received $50 as an inducement to participate. 

25 Three sessions were held in Spanish in one region of the city with a large Hispanic 

26 population (25%), although the final overall participation of native Spanish speakers (18%) in 

27 the study was below the targeted level. The age distribution of the participants corresponded 

28 reasonably well to the overall age distribution in the 2000 U.S. Census for the Phoenix area 

29 (BBC Research & Consulting, 2002). Participants slightly over-represented the middle-income 

30 range ($50,000 to $74,999), compared with 2000 Census data, and slightly under-represented 

31 very low-income ranges (under $24,999). The distribution of participant education levels was 

32 fairly consistent with the education distribution in the 2000 Census. 

33 Photographic-quality slides of the images were developed using the WinHaze software 

34 (Molenar et al., 1994). The scene used in the Phoenix study images was taken at a water 

35 treatment plant. The view is toward the southwest, including downtown Phoenix, with the Sierra 
September 2009 2-13 DRAFT - Do Not Quote or Cite 

1 Estrella Mountains in the background at a distance of 25 miles. Figure 2-6 shows the image with 

2 the best VAQ (15 dv). 

3 

4 Figure 2-6. Reproduction of the image with the best VAQ (15 dv) used in the Phoenix 

5 study. 

6 

7 

8 The study used a total of 21 unique WinHaze images. Four of the 21 unique images were 

9 randomly selected and used twice to evaluate consistency; participants viewed a total of 

10 25 images. The 25 images were randomly ordered, with all participants viewing the images in 

11 the same order. The WinHaze images used in the Phoenix study do not include layered haze, a 

12 frequent and widely recognized form of visibility impairment in the Phoenix area. 

13 The VAQ levels in the 21 unique images ranged from 15 dv to 35 dv (the extinction 

coefficient bext ranged from 45 Mm-1 to 330 Mm-1 14 ). As in the Denver study, participants first 

15 individually rated the randomly shown slides on a VAQ scale of 1 (unacceptable) to 7 

16 (excellent). Participants were instructed to rate the photographs solely on visibility and to not 

17 base their decisions on either health concerns or what it would cost to have better visibility. Next, 

18 the participants individually rated the randomly ordered slides as “acceptable” or “not 

19 acceptable,” defined as whether the visibility in the slide is unreasonable or objectionable. 

20 Figure 2-7 presents the percent acceptability results from the Phoenix study. The 

21 combination of the use of WinHaze images and the larger number of participants than in the 

22 Denver study may account for the “smoother” backwards S-shaped pattern of preferences. 
September 2009 2-14 DRAFT - Do Not Quote or Cite 

1 Figure 2-7. Percent of Phoenix participants who consider VAQ in each image 

2 “acceptable.” 

0%

50%

100%

10 15 20 25 30 35 40 45

Deciview

% participants rating "acceptable"

 3 

4 90% or more of the participants rated a VAQ of 20 dv or better as acceptable, and 70% rated a 

5 VAQ of 22 dv or better as acceptable. The “50% acceptable criteria” was met at approximately 

6 24.3 dv (with 51.3% of the participants rating that image as acceptable). The percent 

7 acceptability declines rapidly as VAQ worsens; only 27% of the participants rated a 26 DV 

8 image as acceptable, and fewer than 10% rated a 29 dv image as acceptable. 

9 The Phoenix urban visibility study formed the basis of the decision of the Phoenix 

10 Visibility Index Oversight Committee for a visibility index for the Phoenix metropolitan area 

11 (Arizona Department of Environmental Quality, 2003). The Phoenix Visibility Index establishes 

12 an indexed system with 5 categories of visibility conditions, ranging from “Excellent” (14 dv or 

13 less, which was a better VAQ than any of the images used in the Phoenix study) to “Very Poor” 

14 (29 dv or greater, which less than 10% of the study participants rated as acceptable). The “Good” 

15 range is 15 dv to 20 dv (more than 90% of the participants rated images in this VAQ range as 

16 acceptable). The environmental goal of the Phoenix urban visibility program is to achieve 

17 continued progress through 2018 by moving the number of days in poorer quality categories into 

18 better quality categories. 

19 2.5 WASHINGTON, D.C. 

20 One of the Washington, D.C. urban visibility pilot studies was conducted on behalf of 

21 EPA (Abt Associates Inc., 2001). It was designed to be a pilot focus group study, an initial 

22 developmental trial run of a larger study. The intent of the pilot study was to refine both focus 

23 group method design and potential survey questions. Due to funding limitations, only a single 
September 2009 2-15 DRAFT - Do Not Quote or Cite 

1 focus group session took place, consisting of one extended session with nine participants. No 

2 further urban visibility focus group sessions were held in Washington, DC, on behalf of EPA. 

3 In March 2009, Dr. Anne Smith conducted a separate study of Washington urban 

4 visibility, using the same photographs and similar approach as the 2001 study (Smith and 

5 Howell, 2009). On behalf of the Utility Air Regulatory Group, Dr. Smith presented comments 

6 (Smith, 2009) to the CASAC at a public meeting held on April 2, 2009 to review EPA’s plan 

7 (US EPA, 2009b) for conducting further urban visibility studies in support of PM NAAQS 

8 reviews. Dr. Smith submitted the Smith and Howell (2009) report to the CASAC as part of the 

9 public comment process. The Smith and Howell study conducted three study variations of a 

10 Washington, DC, preference study, including one experiment involving 26 participants designed 

11 to replicate the EPA 2001 preference study. 

12 Both the Abt Associates Inc. (2001) study results and the results of the Smith and Howell 

13 (2009) study are discussed below. 

14 2.5.1 Washington, D.C. 2001 

15 The EPA’s Washington, D.C. study (Abt Associates Inc., 2001) adopted the general 

16 study methods used in the Denver, BC, and Phoenix studies, modifying them appropriately to be 

17 applicable in an eastern urban setting. Washington’s (and the entire East’s) current visibility 

18 conditions are typically substantially worse than western cities and have different characteristics. 

19 Washington’s visibility impairment is primarily a uniform whitish haze dominated by sulfates, 

20 and the relative humidity levels are higher compared with the western study areas. In addition, 

the relatively low-lying terrain8 21 in Washington, D.C., provides substantially shorter maximum 

22 sight distances. Many residents are not well informed that anthropogenic emissions impair 

23 visibility on hazy days. 

24 The Washington, D.C. focus group session included questions on valuation, as well as on 

25 preferences. The focus group content dealing with preferences for an urban visibility standard 

26 was similar to the focus group sessions in the Denver, BC, and Phoenix studies. 

27 A single scene of a panoramic photograph taken from Arlington National Cemetery in 

28 Virginia was used, and included an iconic view of the Potomac River, the National Mall, and 

29 downtown Washington, D.C. All of the distinct buildings in the scene are less than four miles 

30 from the camera, and the higher elevations in the background are less than 10 miles from the 

31 camera. Figure 2-8 presents the photograph used in the study. 

 8

The maximum elevation in Washington, DC is 409 feet. 
September 2009 2-16 DRAFT - Do Not Quote or Cite 

1 Figure 2-8. Reproduction of the image with the best VAQ (8.8 dv) used in the Washington, 

2 D.C. study. 

3 

4 The Washington, D.C. study used 20 unique images generated by WinHaze, each 

5 prepared from the same original photograph. Humidity and gaseous light scattering was held 

6 constant in preparing the WinHaze images, as was the relative chemical mix of aerosol 

7 particulates in the photos (i.e., only the aerosol concentrations were increased to create the 

8 images with worse VAQ). Five of the images were repeated as a consistency check, so 

9 participants viewed a total of 25 slides. The range of VAQ in the images ranged from 8.8 to 38.3 

dv, which is approximately the 10th to the 90th 10 percentile of the annual distribution of hourly 

11 VAQ conditions in Washington. 

12 Figure 2-9 presents the percent acceptability results from the 2001 Washington study. 

13 Because only nine participants were involved in the study, the possible values of “percent 

14 acceptable” are limited to multiples of 1/9. Figure 2-9 also shows an anomalous result involving 

15 one of the five repeated images. Three of the repeat images had the same ranking each time they 

16 were presented (i.e., all nine participants rated them acceptable or not acceptable both times they 

17 rated that slide). One of the images (the image with 8.8 dv, the best VAQ image used in the 

18 study) was rated acceptable by all nine participants the first time it was used, but the repeat of 

19 that slide was rated not acceptable by one participant. Another image, however, had a 

20 substantially different result. The 30.9 dv image was rated acceptable by five of the nine 

21 participants the first time it was presented, but the repeat of the slide was only rated acceptable 

22 by one of the nine participants. The responses for all five pairs of repeated images are shown in 
September 2009 2-17 DRAFT - Do Not Quote or Cite 

1 red on Figure 2-9, including the images which were identically rated both times they were 

2 presented. 

3 Figure 2-9. Percent of 2001 Washington participants who consider VAQ acceptable in each 

4 image. 

Results of 2001 Washington DC Preference Study

0%

50%

100%

5 10 15 20 25 30 35 40 45

Deciview

% Participants Rating 

"Acceptable"

Unique Images 5 Repeated Images

5 

6 In the 2001 Washington, D.C. study, all images with a VAQ below 25.9 dv were rated 

7 acceptable by the majority of the participants, and all images with a VAQ below 29.2 dv were 

8 rated acceptable by at least four of the nine (44%) participants. All images with a VAQ above 

9 30.9 dv were rated not acceptable. The “50% acceptability criteria” division occurs in the range 

10 of 25.9 dv to 30.9 dv, with the anomalous result of the inconsistent responses to the repeated 

11 image with 30.9 dv effectively broadening this range and adding uncertainty to identifying a 

12 clear division. 

13 2.5.2 Washington, D.C., 2009 

14 The Smith and Howell (2009) study conducted additional focus group sessions based on 

15 the methods and materials used in the 2001 Washington, D.C. study. Smith and Howell 

16 recreated the WinHaze images used in the 2001 Washington, D.C. urban visibility preference 

17 study, using the description in the report on the 2001 study (Abt Associates Inc., 2001), and 

18 created images using currently available desktop computer version of WinHaze (Version 2.9.0). 

19 Smith and Howell used a shortened version of the same question protocol as the 2001 study. The 

20 WinHaze images were presented to a total of 64 participants who were all employees of Charles 

21 River Associates (CRA International, Inc). (Smith and Howell also are CRA International 
September 2009 2-18 DRAFT - Do Not Quote or Cite 

1 employees). The CRA employees were based at the firm’s Washington, D.C. and Houston, 

2 Texas offices (44 and 20 participants, respectively). The Houston participants were included to 

3 explore whether familiarity with Washington, D.C. VAQ conditions developed from currently 

4 living in the Washington region noticeably influenced the responses. As noted by Smith and 

5 Howell, the participants were not a representative sample of either metropolitan area’s 

6 population; all participants were employed, and the participant group included a higher 

7 proportion of college educated individuals and higher household incomes than the general 

8 population. 

9 Eight of the Washington-based participants and all of the Houston participants viewed the 

10 WinHaze images on a desktop computer monitor. The remaining Washington participants 

11 viewed the images projected on a screen. 

12 The stated purpose of the Smith and Howell study was to explore the robustness of the 

13 2001 results. To investigate this issue, Smith and Howell conducted three different tests 

14 concerning urban visibility preferences. Each participant was involved with only one test. The 

15 three tests were: 

16  Test 1 - replicated the Abt Associates Inc. (2001) study 

17 

18  Test 2 - reduced the upper end of the range of VAQ by eliminating the 11 images 

19 used in Test 1 with a VAQ above 27.1 dv 

 20 

21  Test 3 - increased the upper end of the range of VAQ by including two new images 

22 of worse VAQ; the two new images had a VAQ of 42 dv and 45 dv 

 23 

24 Sixteen employees from the Washington, D.C. office and 10 participants from the 

25 Houston office took Test 1 (a total of 26 participants). All the participants viewed the same 

26 unique 20 Washington, DC WinHaze images as the 2001 study (plus repeated images for a total 

27 of 25 images shown to participants). Images were presented in the same random order as in the 

28 2001 study. Figure 2-10 presents the results of Test 1. The results for the 16 Washington 

29 participants are indicated in blue and results for the 10 Houston participants in red. Although all 

30 images used in the study were of Washington, D.C., the results suggest that there is not a 

31 significant difference in the preferences of participants based in the two offices. The scene in the 

32 images is an immediately recognizable iconic view of the National Mall and downtown 

33 Washington, D.C., which may influence the similarity of responses by residents of the two cities. 

34 Using the combined Test 1 results from the two CRA offices (26 total participants), the 

35 majority of participants in the 2009 study rated all VAQ images with 25.9 dv or less as 

36 acceptable and all VAQ images with 29.2 dv or greater as not acceptable. The image of 27.1 dv 

37 was rated as acceptable by 50% of the total participants (56% of the Washington-based and 40% 
September 2009 2-19 DRAFT - Do Not Quote or Cite 

1 of the Houston-based participants). All images with a VAQ less than 22.9 dv were rated 

2 acceptable by at least 90% of the participants, and all images with a VAQ greater than 32.3 dv 

3 were rated not acceptable by 88% of the participants. 

4 

5 Figure 2-10. Percent of 2009 Test 1 study participants who consider VAQ acceptable in 

6 each image, showing the range of the lower and upper bound of 50% acceptability criteria. 

7 

0%

50%

100%

5 10 15 20 25 30 35 40

Deciview

% Participants Rating "Acceptable"

Washington Houston Lower Bound Upper Bound

8 

9 Figure 2-11 presents the 2001 and 2009 study (Test 1) results on a single graph, 

10 representing the results of 35 total participants of preferences for urban visibility in Washington, 

11 DC. The results from the 2009 study on Figure 2-11 combine the Test 1 responses from the two 

12 CRA offices. Figure 2-11 also shows the 50% acceptability criteria range (22.9 dv to 32.3 dv) 

13 from the 2009 study, Test 1. In comparison, the 2001 study 50% acceptability range was 25.9 dv 

14 to 30.9 dv. Inspection of the points in Figure 2-11 indicate that the results from the 2009 study 

15 (Test 1) are not appreciably different than the results of the 2001 Washington study. 

16 In Test 2, Smith and Howell reduced the range of VAQ images presented to 26 

17 participants to images with a VAQ of 27.1 dv or less. The 26 participants were different people 

18 than the Test 1 participants. Test 2 presented only the nine unique clearest WinHaze images 

19 from the full Test 1 set of 20 images. This constricted the VAQ levels presented to the range that 

20 the majority of participants in the 2001 study rated as acceptable and reduced the upper end of 

21 
September 2009 2-20 DRAFT - Do Not Quote or Cite 

1 Figure 2-11. Combined results of two Washington preference studies (showing 50% 

2 acceptability criteria from 2009, Test 1). 

3 

0%

50%

100%

5 10 15 20 25 30 35 40

% Participants Rating "Acceptable"

Deciview

2001 Study 2009, Test 1 Lower Bound Upper Bound

 4 

5 Figure 2-12. Comparison of results from Test 1 and Test 2 (Smith and Howell, 2009). 

6 

Results of Smith and Howell Test 1 and Test 2

0%

50%

100%

5 10 15 20 25 30 35 40

Deciview

% Participants Rating "Acceptable"

Test 2 Test 1
September 2009 2-21 DRAFT - Do Not Quote or Cite 

1 the VAQ range by 11.2 dv. Nine unique WinHaze images were used in Test 2, with three 

2 duplicates included, so Test 2 participants were shown 12 images. Figure 2-12 presents the Test 

3 1 and Test 2 results. Test 2 found a substantial shift in the responses about which VAQ level is 

4 considered acceptable. The smaller number of images used in Test 2 makes identifying the range 

5 of the 50% acceptability criteria more difficult than in Test 1. The lower bound of the range 

6 occurs between 15.6 and 18.7 dv, and the upper bound occurs between 24.5 and 27.1 dv. Smith 

7 and Howell conclude that the shift in the acceptability responses between Test 1 and Test 2 

8 suggests that the acceptable responses in an urban visibility preference study conducted using the 

9 general approach used in the all the studies may be susceptible to the range of VAQ images 

10 presented. 

11 One hypothesis (not raised by Smith and Howell) suggested by the Test 2 results is that 

12 the 50% acceptability criteria occurs near the middle of the range of images shown to 

13 participants. This might be the result of the participants consciously or subconsciously 

14 identifying approximately the middle of the VAQ range presented to them. Participants (in all 

15 the studies reviewed in this paper) were shown all the images as part of “warm up” exercises and 

16 a separate initial rating exercise (ranking the VAQ in each image on a scale of 1 to 7). These 

17 initial reviews of the images allow participants to become familiar with the range of VAQ and 

18 may consciously or subconsciously calibrate their subsequent responses to the VAQ range they 

19 were presented. 

20 In Test 3, Smith and Howell expanded the VAQ range of WinHaze images shown to the 

21 participants, including two new images with a worse VAQ. The new images had a VAQ of 42 

22 dv and 45 dv, raising the upper end of the VAQ range by 6.7 dv. Test 3 reduced the total number 

23 of images shown to participants to 19 images by eliminating the use of the five repeat images in 

24 Test 1, and also eliminated three additional images in order to reduce the participants’ time 

25 burden. The three deleted images had a VAQ of 11.1, 15.6, and 24.5 dv. The best VAQ image 

26 shown to Test 3 participants was 8.8 dv (same as the best VAQ image in Tests 1 and 2). 

27 However, in Test 3 there were no images with VAQ between 8.8 dv and 18.7 dv, creating a 

28 significant “hole” in the distribution of VAQ conditions presented to the Test 3 participants. 

29 Test 3 was conducted with 12 participants from the CRA Washington office (none of whom 

30 participated in Test 1 or Test 2). No Houston participants were involved with Test 3. The results 

31 of Test 3 are shown in Figure 2-13, along with the results of Test 1. 

32 Increasing the upper end of the VAQ range in Test 3 resulted in an overall increase in the 

33 percent of respondents rating as acceptable the VAQ images used in both tests. In Test 3 all 

34 images with a VAQ below 22.9 dv were rated acceptable by 100% of the participants (similar to 

35 the Test 1 results), implying there was no general change in the acceptability of the images with 

36 good VAQ. However, for all VAQ images (that were used in both studies) between 25.9 dv and 
September 2009 2-22 DRAFT - Do Not Quote or Cite 

1 Figure 2-13. Comparison of results from the Smith and Howell (2009) Test 1 and Test 3. 

2 

0%

50%

100%

5 10 15 20 25 30 35 40 45

Deciview

% Participants Rating "Acceptable"

Test 3 Test 1

3 

4 33.6 dv, a noticeably larger percentage of the participants in Test 3 rated the image as acceptable 

5 than in Test 1. At VAQ levels worse than 33.6 dv, the majority of the participants found the 

6 VAQ level not acceptable in both tests. 

7 While not as dramatic as the impact in Test 2 (which substantially reduced the VAQ 

8 range), the impact on the Test 3 results of increasing the VAQ range is consistent with Smith and 

9 Howell’s conclusion that changing the range of VAQ presented to the participants affects the 

10 responses about whether a particular VAQ is acceptable. The results of Test 3 also are consistent 

11 with the hypothesis that the “dividing line” for the 50% criteria occurs near the middle of the 

12 range of VAQ presented, and that changing the range of VAQ images changes the 50% criteria 

13 “dividing line,” with the “dividing line” remaining in roughly the middle of the VAQ range. 

14 The VAQ ranges that Smith and Howell used in Tests 2 and 3 did not span the range of 

15 actual VAQ conditions that occur in Washington, DC, and Smith and Howell provided no 

16 information about the range of actual conditions in Washington in any of their tests. The images 

17 used in the 2001 Washington, DC study (and Test 1) were deliberately selected to present the 

18 range of VAQ conditions in Washington, DC. In the 2001 study, participants were shown an 

19 image of annual average VAQ in Washington at the time, as well as an image of conditions on a 

20 hazy day (the 20th percentile day in the annual distribution). The Denver, Phoenix, and BC 

21 studies also provided participants with information that the range of VAQ conditions they would 

22 be seeing included the actual annual range of VAQ conditions in their city. It is not known 

23 whether the participants in the Smith and Howell Tests 2 and 3 recognized (based on their own 
September 2009 2-23 DRAFT - Do Not Quote or Cite 

1 knowledge and experience) that the range of VAQ images presented did not represent the actual 

2 annual range, or if they believed the range did depict the annual distribution. 

3 2.6 SUMMARY OF PREFERENCE STUDIES AND SELECTION OF 

4 CANDIDATE PROTECTION LEVELS 

5 Each of the studies reviewed in this assessment investigates the common question, “What 

6 level of visibility degradation is acceptable?” The approaches used in the four studies are similar 

7 and are all derived from the method first developed for the Denver urban visibility study. The 

8 specific materials and methods used in each study vary, however, making direct comparison of 

9 the study results challenging. Key differences between the studies include: 

10 

11  use of WinHaze (a significant technical advance in the method of presenting VAQ 

12 conditions), 

13 

14  number of participants in each study, 

15 

16  representativeness of participants for the general population of the relevant 

17 metropolitan area, and 

18 

19  specific wording used to frame the questions used in the group interview process. 

20 

21 Although the differences between the methods used in the urban visibility preference 

22 studies are significant, it is possible to examine the results of the studies to identify overall trends 

23 in the study findings. Figure 2-14 present a graphical summary of the results of the studies in the 

24 four cities. Figure 2-14 draws on results previously presented in Figures 2-3, 2-5, 2-7 and 2-11. 

25 For clarity in Figure 2-14, the Denver results omit the 9:00 a.m. photograph results, the 

26 Chilliwack and Abbotsford photographs appear as a single set of data for the BC study, and the 

27 results from 2001 and 2009 (Test 1) studies of VAQ preferences in Washington, D.C. are 

28 presented as a single combined set of data. The results from the 2009 Washington, D.C. study 

29 Tests 2 and 3 are not included on Figure 2-14; those tests are not comparable studies because 

30 they did not present the actual range of VAQ conditions in the study city. 

31 Figure 2-14 also contains lines at 20dv and 30 dv that effectively and pragmatically 

32 identifies a range where the 50% acceptance criteria occurs across all four of the urban 

33 preference studies. Out of the 114 data points shown in Figure 2-14, only one photograph (or 

34 image) with a VAQ below 20 dv was rated as acceptable by less than 50% of the participants 
September 2009 2-24 DRAFT - Do Not Quote or Cite 

who rated that photograph.9 1 Similarly, only one image with a VAQ above 30 dv was rated 

acceptable by more than 50% of the participants who viewed it.10 2 

3 

4 Figure 2-14. Summary of results of urban visibility studies in four North American cities, 

5 showing the identified range of the 50% acceptance criteria. 

6 

0%

50%

100%

5 10 15 20 25 30 35 40 45

Deciview

% Participants Rating Acceptable

Denver Phoenix BC

Washington Upper Upper

7 

8 Figure 2-14 shows that while there is a high degree of similarity between the preferences 

9 found in each study, there may be important differences in VAQ preferences in the four cities as 

10 well. For example, the Denver study identified preferences for a relatively good level of VAQ; 

11 the 50% criteria occur between 17.7 dv and 20.3 dv. In Washington, D.C., however, the 50% 

12 criteria separation occurs at a substantially worse level of VAQ, between 27 dv and 31 dv. 

13 There are several major hypotheses that may explain why the results of these studies may 

14 be indicating potentially important differences between the preferences for VAQ in different 

15 cities. As mentioned, the use of photographs versus WinHaze-generated images may play a 

16 significant role in preference studies, perhaps introducing bias (such as suggested by the 

 9

 Only 47% of the BC participants rated a 19.2 dv photograph as acceptable. 10 In the 2001 Washington, D.C. study, a 30.9 dv image was used as a repeated slide. The first time it was shown 

56% of the participants rated it as acceptable, and 11% rated it as acceptable the second time it was shown. The 

same VAQ level was rated as acceptable by 42% of the participants in the 2009 study (Test 1). 
September 2009 2-25 DRAFT - Do Not Quote or Cite 

1 responses to the 9:00 a.m. Denver photographs) as well as variability. Use of photographs from 

2 different days and times of day that rely on associated ambient measurements of light extinction 

3 to characterize their VAQ level introduces two types of uncertainty. The intrinsic appearance of 

4 the scene can change due to the changing shadow pattern and cloud conditions, and spatial 

5 variations in air quality can result in ambient light extinction measurements not being 

6 representative of the sight-path-averaged light extinction. WinHaze has neither of these sources 

7 of uncertainty because the same base photograph is used (i.e. no intrinsic change in scene 

8 appearance) and the modeled haze that is displayed in the photograph is determined based on 

9 uniform light extinction throughout the scene. 

10 Second, variation in the degree of representativeness of the participants and the sizes of 

11 the participant samples involved may also be important factors. The small sample size and fairly 

12 uniform population of respondents is a plausible explanation for the noisiness of the combined 

13 Washington, D.C. results (35 participants, including 26 from a single consulting firm and 10 of 

14 those from a different city) compared with the larger and more representative population of 

15 responders from Phoenix (385 participants, carefully selected to be representative of the Phoenix 

16 population). 

17 A third hypothesis explored by Smith and Howell (2009) is that the range of VAQ 

18 images presented in the survey may influence the results. Though this hypothesis appears to be 

19 borne out by Smith and Howell’s results for Washington, D.C., it seems an unlikely explanation 

20 for the differences in results between the four urban preference studies. For example the Denver 

21 study included photographs with the haziest conditions among the four studies, but resulted in 

the lowest haze condition for the 50th 22 percentile preference ratings among the four, not the 

23 highest as might be expected if the range of haze levels were a significant factor influencing the 

24 results of preference studies. 

25 A fourth major hypothesis is that urban visibility preferences may differ by location, and 

26 the differences may arise from inherent differences in the cityscape scene used in each city. The 

27 key evidence to suggest this hypothesis is that the apparent differences between the Denver 

28 results (which found the 50% acceptance criteria occurred in the best VAQ levels among the four 

29 cities) and the Washington, D.C. results (which found the 50% acceptance criteria occurred at 

30 the worst VAQ levels among the four cities). This hypothesis suggests that these results may 

31 occur because the cityscape of Denver includes clearly visible snow-covered mountains in the 

32 distance, while the prominent features of the Washington, D.C. cityscape are buildings relatively 

33 nearby with only modest changes in elevation. 

34 Finally, perhaps of significant importance is that the perceived sensitivity of individual 

35 scenes to changes in light extinction can be quite different. As in the fourth hypothesis, this may 

36 in part explain why the Denver study scene, with its long distance to the mountain backdrop, 
September 2009 2-26 DRAFT - Do Not Quote or Cite 

1 resulted a preference for the best VAQ level with a 50% criteria value between 17.7 and 20.3 dv, 

2 while in Washington, D.C., the 50% criteria separation occurs at a substantially worse level of 

3 VAQ, between 27 and 31 dv from Abt Associates Inc. (2001) and Smith and Howell (2009) Test 

4 1. The distinction between the last two hypotheses are that the earlier one speaks to the 

5 desirability of seeing distant mountains versus this hypothesis where its ability to perceive haze 

6 at lower light extinction levels. Additional studies, including directly comparable studies using 

7 similar methods in diverse cities, are necessary to gain further understanding of preferences for 

8 urban visibility. 

Based on the composite results and the effective range of 50th 9 percentile acceptability 

10 across the four urban preference studies shown in Figure 2-14, CPLs have been selected in a 

range from 20 dv to 30 dv (74 Mm-1 to 201 Mm-1 11 ) for the purpose of comparing to current and 

12 projected conditions in the assessment in chapters 3 and 4 of this document. A midpoint of 25 

dv (122 Mm-1 13 ) was also selected for use in the assessment. These three values provide a low, 

14 middle, and high set of light extinction conditions that are used in subsequent sections of the 

15 UFVA to provisionally define daylight hours with urban haze conditions that have been judged 

16 unacceptable by the participants of these preference studies. 

17 Though not directly supported by preference or other studies, it is necessary to also 

18 identify an averaging time and form to apply along with the CPLs in the assessments described 

19 in chapters 3 and 4. For this assessment only daylight hour visibility is being considered. VAQ 

20 impacts are instantaneously perceived, suggesting that a short averaging time (e.g. an hour) may 

21 be more appropriate than longer time periods (e.g. multiple hours). This is also consistent with 

22 the belief that most individuals experience urban VAQ as relatively short-term incidental and 

23 intermittent opportunities to be outdoors (e.g. during commutes to work, school, shopping, etc.). 

24 Given that some fraction of the public may experience poor VAQ during a relatively small time 

25 period and not have the opportunity to see it improve later during the same day, it seems 

26 appropriate by EPA staff to consider assessing the current and projected conditions in chapters 3 

27 and 4 by comparing the 1-hour daily maximum light extinction to each of the three CPLs 

28 supported by the preference studies. Another characteristic that needs to be set for the 

29 assessment is the frequency of conditions that should be at or below the CPLs to be considered 

30 acceptable. Again, none of the preference studies provided insight into this aspect of 

31 acceptability. Because the nature of the public welfare effect is one of aesthetics and/or on 

32 feelings of wellbeing and not directly related to a physical health outcome, EPA staff believes 

33 that it is not necessary to eliminate all such exposures and that some number of hours/days with 

34 poor VAQ can reasonably be tolerated. EPA staff is therefore considering the 90th and 95th 

35 percentiles per year averaged over a three year period as a reasonable range of frequencies for 

36 meeting the range of PM light extinction CPLs and has incorporated them in this assessment. 
September 2009 3-1 DRAFT - Do Not Quote or Cite 

1 3 ESTIMATION OF CURRENT PM CONCENTRATIONS AND 

2 LIGHT EXTINCTION 

3 The goals of the “current conditions” portion of this urban-focused visibility impact 

4 assessment are to characterize hourly light extinction conditions in a set of urban study areas in 

5 2005-2007, in order (1) to improve understanding of the levels, patterns, and causes of daylight 

6 hours light extinction given that essentially no direct measurements are available to inform that 

7 understanding, (2) to provide the starting point for projections of light extinction levels under 

8 “what if” scenarios in each of which it is assumed that each study area complies with a certain 

9 secondary NAAQS based either on a measurement-based light extinction indicator or on annual 

10 and 24-hour average PM2.5, and (3) to examine the correlation between light extinction and 

11 potential alternative indicator(s) based on PM2.5 concentration. This chapter addresses the first 

12 goal. Chapter 4 addresses the second goal regarding “what if” scenarios. Appendix D addresses 

13 the third goal. 

14 3.1 GENERAL CHARACTERIZATION 

15 3.1.1 PM2.5 and PM10-2.5

16 Chapter 2 of the 2005 Staff Paper from the previous review and chapters 3 (especially 

17 section 3.5) and 9 (especially section 9.2.3) and Annex A of the second draft ISA (US EPA, 

18 2009a) from the current review present extensive characterizations of the levels, composition, 

19 and temporal and spatial patterns of PM2.5 in U.S. urban areas. Both documents present data 

20 summaries based on the approximately 1000 PM2.5 monitoring sites in the U.S. The 

21 characterizations in the 2005 Staff Paper were based on 2001-2003 data. The characterizations 

22 in the ISA are based on 2005-2007 data, which is the same time period used in this visibility 

23 assessment. While there generally have been reductions in the concentrations of PM2.5 in many 

24 areas as a result of emission reductions of PM2.5 and its precursors, the general patterns, and the 

25 diversity of patterns across areas, noted in the 2005 Staff Paper still prevailed in the 2005-2007 

26 period. 

In 2005-2007, 38 urban areas violated the annual PM2.5 NAAQS of 15 μg/m3 27 , adopted in 

28 1997 and retained in the last review completed in 2006. Seventy-six areas violated the revised 

24-hour NAAQS of 35 μg/m3 29 . There is considerable but not complete overlap in the areas not 

30 meeting the two NAAQS. It should be noted that in many parts of the U.S., PM2.5 concentrations 

31 in 2005 were high relative to the next three years. Figure 3-1 illustrates PM2.5 air quality in 2007 

32 by representing each monitor by a symbol whose color reflects the annual mean of the 

concentration at that site or the 98th 33 percentile 24-hour concentration, in both cases in that one 

34 year. 
September 2009 3-2 DRAFT - Do Not Quote or Cite 

Figure 3-1. Annual average and 24-hour (98th 1 percentile 24-hour concentrations) PM2.5 

concentrations in μg/m3 2 , 2007. 

3 

4 

5 

6 
September 2009 3-3 DRAFT - Do Not Quote or Cite 

1 Each urban area exhibits its own detailed patterns of observed concentration levels, 

2 temporal and spatial variation, and composition. These differences are due to differences in local 

3 and transported emissions and in meteorology. Because of differences in the placement of PM2.5

4 monitoring sites in each urban area, the actual levels and spatial pattern of PM2.5 and PM2.5

5 species concentrations may not be consistently discernable in all areas. This variability and 

6 limited monitoring network make it difficult to offer concise generalizations, although some 

7 broad similarities can be drawn among areas. 

8 Midwestern, southeastern, and eastern urban areas have much higher sulfate levels than 

9 do more western areas, attributable to the much higher emissions of SO2 in and upwind of them. 

10 Upper midwestern areas and to a lesser extent upper eastern areas have notable nitrate 

11 concentrations in winter but not in summer, while southeastern areas generally lack notable 

12 nitrate even in winter. Many western urban areas have notable nitrate year round. In all areas, 

13 carbonaceous material is an important component of PM2.5 and is attributable to many emission 

14 sources of organic material in PM form and of organic PM precursor gases; in some areas with 

15 high local use of wood for residential heating carbonaceous material is dominant during the 

16 heating season. PM2.5 derived from crustal sources is generally a small faction of total mass, 

17 except during local high wind events or due to brief periods of intercontinental transport of dust 

18 from Africa or Asia. 

19 Comparison of PM2.5 species concentrations within and outside urban areas leads to the 

20 conclusion that, in the eastern areas with high sulfate concentrations, the large majority of the 

21 sulfate affecting any given urban area originates outside that area. Inward transport and local 

22 generation of nitrate and carbonaceous material are more evenly balanced in eastern areas, with 

23 some differences among areas. In western areas, local sources dominate for carbonaceous 

24 material and nitrate, with the origins of the small sulfate component being more balanced. See 

25 Figure 9-24 of the second draft ISA (US EPA, 2009a). 

26 Southeastern areas have their highest PM2.5 concentrations in the summer, when 

27 conditions are most conducive to sulfate formation. More northern areas, being affected by a 

28 more balanced mix of contributors, tend not to have such a strongly seasonal pattern. The 

29 seasonal patterns in western areas are individual and varied, related to differences in local 

30 sources and formation and dispersion conditions. In all areas, inversion conditions with low 

31 wind speeds are conducive to high concentrations due to the trapping of emissions from local 

32 sources. Some western areas, especially those with valley or bowl-like topography, are 

33 especially affected. 

34 There is at present no systematic monitoring network in place for PM10-2.5, as states have 

35 until January 1, 2011, to implement required monitoring sites for PM10-2.5. Consequently, 

36 estimates of PM10-2.5 must be developed using data from PM2.5 and PM10 monitoring sites and 
September 2009 3-4 DRAFT - Do Not Quote or Cite 

1 equipment, which are not always collocated and consistent. The 2005 Staff Paper presented such 

2 estimates in section 2.4.3. The second draft ISA presents such estimates in Figure 3-10 and 

3 Table 3-9 of section 3.5.1.1. The 2005 Staff Paper used a data-inclusive approach in which the 

4 best available data on PM2.5 and PM10 concentrations – in some cases not very robust data – 

5 were used to estimate 2001-2003 PM10-2.5 concentrations for 351 metropolitan area counties. For 

6 these counties, the annual mean PM10-2.5 concentrations were generally estimated to be below 40 

μg/m3, with one maximum value as high as 64 μg/m3 and a median of about 10-11 μg/m3 7 . The 

8 second draft ISA used a much more data-restrictive approach based only on paired (collocated) 

9 low-volume filter-based samplers for both PM10 and PM2.5, the most accurate method of 

10 measuring PM10-2.5. The second draft ISA reports that only 40 counties have such paired 

11 samplers. Using these available co-located PM measurements from 2005-2007, the mean 24-hr 

PM10-2.5 concentration in these 40 counties was 13 μg/m3 12 . This urban visibility assessment has 

13 used a data-inclusive approach to estimating PM10-2.5 concentrations, similar to that used for the 

14 2005 Staff Paper, where needed to obtain hourly PM10-2.5 estimates for 15 study areas, which are 

15 reported below in section 3.3.2. 

16 Additional detail on PM2.5, PM10, and PM10-2.5 concentrations, composition, and patterns 

17 appears in section 3.5.1.1 of the second draft ISA. Also, chapter 6 of the 2004 PM Assessment 

18 by NARSTO contains more detailed characterizations of PM in different parts of the U.S. 

19 3.1.2 Light extinction 

20 While light extinction is directly measurable, there are very few regularly operating 

21 monitoring sites measuring light extinction in urban areas, and generally those that do operate do 

not submit data to AQS.11 22 Consequently, any characterization of light extinction conditions 

23 based on actual measurements is necessarily less comprehensive than for PM2.5 and PM10-2.5. 

24 Many monitoring sites that employ nephelometers, which do measure light scattering, operate 

25 that equipment in a heated mode for purposes of tracking “dry” PM2.5 mass concentrations, and 

26 actual ambient light extinction is not reportable. There are many more filter-based 

27 Aethalometers® and similar instruments for measuring light absorption in operation and 

28 reporting to AQS, but light absorption is typically a small fraction of total light extinction, so 

29 these data alone are not a good indicator of light extinction in urban areas. Also, there are 

30 unresolved issues of data corrections and comparability for the light absorption data from these 

31 instruments now residing in AQS. 

 11 There is a large network of “visual range” monitors in operation at U.S. airports, aimed at providing information 

to determine landing and takeoff safety. Due to their locations and to the lack of data resolution (values of visual 

range above the level needed for unlimited airport operations are not individually reported) the data from these 

monitors are not suitable for use in this assessment. The second draft ISA discusses these monitors in section 

9.2.2.3. 
September 2009 3-5 DRAFT - Do Not Quote or Cite 

1 Light extinction can be “reconstructed” from measurements of PM2.5 mass components 

2 and PM10-2.5 concentrations, along with relative humidity, using the formula known as the 

3 IMPROVE algorithm. (Section 9.2.2.2 of the second draft ISA gives an overview of the 

4 algorithm and its basis.) PM2.5 component measurements are generally available only on a 24-

5 hour average basis, so it generally is possible to estimate only 24-hour average light extinction, 

unless additional information on hourly patterns is brought to bear.12 6 Because EPA’s Regional 

7 Haze Rule (RHR) currently requires states to address visibility problems in Class I visibility 

8 protection areas, which are nearly all rural and remote, there is a large body of literature 

9 characterizing light extinction in remote rural areas, based on data from the IMPROVE 

10 network’s 24-hour samplers and on special studies. Sections 9.2.3.2 and 9.2.3.4 of the second 

11 draft ISA summarizes this literature. Section 9.2.3.3 of the ISA contrasts concentrations of PM 

12 and PM components between rural and urban areas using data from the rural IMPROVE network 

13 and the urban Chemical Speciation Network (CSN), but does not present estimates of light 

14 extinction in urban areas. 

15 The CSN network provides 24-hour PM2.5 species measurements at about 200 urban 

16 sites, from which mass components can be derived. These sites have a mix of daily, one day in 

17 three, and one day in six sampling schedules. The 2005 Staff Paper (and its references) may be 

18 the only readily available prior assessment to use these urban PM2.5 speciation monitoring data, 

19 along with estimates of PM10-2.5 concentrations and data on relative humidity, to reconstruct daily 

20 24-hour average light extinction in urban areas, for the year 2003. One presentation of the 

21 results was in the form of a scatter plot of daily 24-hour reconstructed light extinction versus 24-

22 hour PM2.5 concentration. This graphic appears here as Figure 3-2. (For the immediate purpose 

23 of this section, it is the distribution of the data points along the y-axis that is of interest, not the 

24 relationship between light extinction and PM2.5 concentrations; the latter subject is addressed in 

Appendix D.) Generally, most days have light extinction below 200 inverse megameters (Mm-1 25 ), 

but a small percentage of values were as high as about 750 Mm-1.

13 26 

27 In addition to this scatter plot, a table developed for the previous PM NAAQS review 

28 presented the annual average of estimates of 24-hour reconstructed light extinction values, 

29 averaged across 161 urban areas grouped into seven regions (Schmidt, et al., 2005). Table 3-1 

30 reproduces these estimates. For regions excluding Southern California, annual average 24-hour 

31 light extinction 

 12 When the IMPROVE algorithm is used to estimate 24-hour light extinction from 24-hour PM2.5 species and 

PM10-2.5 concentrations, an assumption is made that every hour has the same PM concentrations but its own relative 

humidity value. Hourly estimates of light extinction, including the strongly non-linear effect of relative humidity, 

are then averaged to get the 24-hour light extinction estimate. 

13 Unfortunately, the file of paired data used to create this scatter plot is no longer available, so the actual 

distribution of light extinction values cannot be described more specifically.
September 2009 3-6 DRAFT - Do Not Quote or Cite 

1 Figure 3-2. Reconstructed 24-hour light extinction in U.S. urban areas in 2003 

2 Source: Schmidt et al., 2005 

3 

ranged from 73 to 118 Mm-1 4 . The estimate of the annual average 24-hour light extinction for 

Southern California was 168 Mm-1 5 . These estimates were based on 10-year average 1-hour 

6 relative humidity values and 2003 PM monitoring data. 

7 
September 2009 3-7 DRAFT - Do Not Quote or Cite 

1 Table 3-1. Annual Mean Reconstructed 24-hour Light Extinction Estimates 

by Region (Mm-1 2 ) 

3 

Region Reconstructed 24-hour Light 

Extinction in 2003 

Northeast 108 

Southeast 98 

Industrial Midwest 118 

Upper Midwest 80 

Southwest 73 

Northwest 76 

Southern California 168 

4 Source: Output D.3, Schmidt et al., 2005. We note these regions were used to summarize PM2.5 patterns for the PM 

5 NAAQS review 1997 (US EPA, 1996). 

6 

7 Figure 3-3 is a contour map of annual average reconstructed 24-hour light extinction 

8 based on IMPROVE monitoring sites in 2000-2004, nearly all of which are remote and rural (the 

9 three urban sites in Phoenix, AZ, Washington, D.C., and Puget Sound, WA are indicated by 

10 square symbols). Comparing the mean urban light extinction levels by region listed in Table 3-1, 

11 estimated based on CSN data, with this map of rural light extinction based on IMPROVE data 

12 indicates that remote rural light extinction levels are notably lower than in urban areas in most 

13 parts of the U.S., with the northeast and the southeast regions having the most similarity between 

14 rural and urban light extinction levels. This is consistent with observations of an “urban excess” 
September 2009 3-8 DRAFT - Do Not Quote or Cite 

1 Figure 3-3. Isopleth map of annual total reconstructed particulate extinction based on 

2 IMPROVE data. 

3 

4 

5 (Source: Spatial and Seasonal Patterns and Temporal Variability of Haze and its Constituents in the 

6 United States Report IV, November 2006.)

 7 

8 of PM2.5 and PM10-2.5 and with the known high regional concentrations of sulfate in these eastern 

9 areas. 

10 One-hour light extinction values of course vary above and below the 24-hour average, 

11 due to diurnal variations in PM2.5 component concentrations, PM10-2.5 concentrations, and 

12 relative humidity. Because low wind speeds, inversion conditions, and lower temperatures are 

13 more prevalent in the night and early morning hours, light extinction generally is higher at those 

14 times, with morning daylight hours being when poor visibility will most often be most 

15 observable. Although light extinction was formally reconstructed on an hourly basis in the 2005 

16 Staff Paper analysis for the last review cited above, the actual full strength of the diurnal pattern 

17 could not be discerned in that analysis because component mix was assumed not to vary from 

18 hour to hour. Under the unverified assumption of constant component mix and using actual 

19 hourly relative humidity data, the daily maximum daylight 1-hour light extinction values were 
September 2009 3-9 DRAFT - Do Not Quote or Cite 

roughly 50 percent higher than the 24-hour average light extinction values.14 1 The new analysis 

2 presented in this document includes a closer look at diurnal patterns, for 15 study areas. 

3 3.2 OVERVIEW OF APPROACH AND DATA SOURCES FOR URBAN STUDY 

4 ANALYSIS 

5 As explained above, there are limited data from direct measurements of light extinction in 

6 urban areas. Consequently, this assessment has reconstructed hourly light extinction levels from 

7 values of hourly PM2.5 components, PM10-2.5, and relative humidity. Hourly monitoring data for 

8 these parameters are also lacking, so the estimates of these parameters necessarily in turn have 

9 been developed from a combination of other available ambient monitoring data and air quality 

10 modeling results from a chemical transport model (CTM) run. Specifically, the ambient 

11 monitoring data starting points are 24-hour PM2.5 mass measured by filter-based Federal 

Reference Method (FRM) or Federal Equivalent Method (FEM) monitors15 12 , 24-hour PM2.5

13 components measured by the filter-based monitors of the Chemical Speciation Network, and 

14 hourly PM2.5 mass measured by continuous instruments (Tapered Element Oscillating 

15 Microbalance (TEOM), beta attenuation monitors (BAMs), and nephelometers were used at 

16 different sites). The CTS-based diurnal profiles for individual components, in conjunction with 

17 hourly PM2.5 measurements, are used to adjust and allocate the 24-hour PM2.5 components 

18 measurements to individual hours of each day, as described in detail below. In addition, levels 

19 of hourly PM10-2.5 mass are calculated from separate measurements of hourly PM10 and hourly 

20 PM2.5 if both are available and by applying PM10-2.5 to PM2.5 ratios to hourly PM2.5 data if both 

21 types of hourly measurements are not available. The ambient data are from 2005-2007 and were 

22 all obtained from AQS in the first half of 2009. 

23 The CTM run was the “actual emissions” run of the 2004 CMAQ modeling platform with 

boundary conditions provided by GEOS-Chem global scale CTM.16 24 The primary use of the CTM 

25 modeling is to provide realistic diurnal variations for each of the major PM2.5 components used 

26 to estimate light extinction, anchored to site-specific, day-specific measurements of 24-hour 

27 concentrations. That is, monthly averaged diurnal profiles for the five major components were 

28 generated using the CTM results which were then used to generate realistic hourly concentration 

29 variations for each of the 24-hour CSN sample days during the 2005-2007 period. 

 14 These observations on diurnal patterns come from examination of “Output D.3 (Relationship RE & PM2.5; Diurnal 

RE; Timeframe) 8 of 30” and “Output D.3 (Relationship RE & PM2.5; Diurnal RE; Timeframe) 17 of 30”, Analyses 

of Particulate Matter (PM) Data for the PM NAAQS Review, Schmidt et al., 2005. 

15 Filter-based Federal Reference Method samplers and filter-based Federal Equivalent Method samplers will both 

be referred to as FRM samplers in the remainder of this document. 

16 GEOS-Chem is the NASA Goddard Earth Observing System-CHEMistry (global 3-D CTM for atmospheric 

composition). This modeling platform, with an appropriately different emissions scenario, is also the basis for the 

estimates of policy relevant background concentrations of PM2.5 presented in section 3.6 of the second draft ISA (US 

EPA, 2009a). 
September 2009 3-10 DRAFT - Do Not Quote or Cite 

1 3.2.1 Study Period, Study Areas, Monitoring Sites, and Sources of Ambient PM 

2 Data 

3 As of the time this assessment began, the ambient monitoring data from 2005-2007, but 

4 not from 2008, had been certified as accurate and complete by the state/local monitoring 

5 agencies that collected them, and the data had been extensively summarized and presented in the 

6 first draft ISA. The EPA staff aimed to develop estimates of daylight hours light extinction for a 

7 reasonably representative number of days in each year of 2005-2007, to allow the application of 

8 statistical forms based on three years of data. However, as explained in more detail below, in 

9 several study areas the limited availability of starting data for these estimates resulted in estimate 

10 sets that do not cover all three years. Also, even in areas with some data in all three years, the 

11 number of days with valid estimates differs by year and is in some cases not large by typical 

12 standards of monitoring data completeness. 

13 For efficiency in the analysis, this visibility assessment uses the same 15 urban study 

14 areas selected for the health risk assessment. These areas are listed in Table 3-2, along with the 

15 area-wide FRM-based 2005-2007 annual and 24-hour PM2.5 design values for each study area. 

16 (See below for an explanation of the “site-specific” columns in Table 3-2.) 

17 

18 Table 3-2. Urban Visibility Assessment Study Areas 

Study Area 

Area-wide 

2005-2007 

Annual 

Design Value

Area-wide 

2005-2007 

 

24-hour 

Design Value

Sitespecific 

 2005-2007 

Annual 

Design Value 

Sitespecific 

2005-2007 

24-hour 

Design Value 

Region 

Tacoma 10.2 43 Same Same Northwest 

Fresno 17.4 63 Same Same Southern 

California 

Los Angeles-South 

Coast Air Basin 

19.6 55 Same Same Southern 

California 

Phoenix 12.6 32 7.9 15 Southwest 

Salt Lake City 11.6 55 10.7 48 Northwest 

Dallas 12.8 26 11.5 25 Southeast 

Houston 15.8 31 13.1 25 Southeast 

St. Louis 16.5 39 14.5 34 Midwest 

Birmingham 18.7 44 Same Same Southeast 

Atlanta 16.2 35 15.7 33 Southeast 

Detroit-Ann Arbor 17.2 43 Same Same Midwest 

Pittsburgh 16.5 43 15.0 40 Industrial 

Midwest 

Baltimore 15.6 37 14.5 35 Northeast 

PhiladelphiaWilmington 

15.0 38 14.7 37 Northeast 

New York-N. New 

Jersey-Long Island 

15.9 42 14.4 42 Northeast 

19 
September 2009 3-11 DRAFT - Do Not Quote or Cite 

1 For time reasons and because it was anticipated that some study areas would not contain 

2 more than one suitable study site, EPA staff sought to identify the single best study site in each 

3 area. In identifying the single best study site in each study area consideration was given to the 

4 availability of collocated 24-hour data on PM2.5 and its components, because the contribution of 

5 PM2.5 components to total light extinction will typically dominate the contribution from PM10-2.5. 

6 Ideally, within each study area the three types of PM2.5 data (FRM PM2.5, CSN PM2.5

7 components, continuous PM2.5) would be available at a common site, and that site would be 

8 located in a manner consistent with reliance on it to characterize visibility as it would be 

9 perceived by a large number of area residents and visitors. Shown in Table 3-2 for convenient 

10 comparison are the site-specific FRM-based design values for the monitoring site in each study 

11 area from which FRM PM2.5 data were taken for the purposes of this assessment, where not the 

same as the site providing the area-wide design values.17 12 As can be seen in Table 3-2, in most of 

13 the study areas the site providing FRM data for this assessment is not the area-wide design value 

14 site, because the area-wide design value site did not have collocated CSN and/or continuous 

15 PM2.5 data. 

16 Appendix A provides details on the site(s) identified and used in each study area, 

17 including information on the type of monitoring that provided the data and other information that 

18 may help interpret the results of the analysis. A portion of this table for a single site – Tacoma – 

19 is presented here as Table 3-3 as an example. When viewing this document electronically, the 

20 site IDs in these tables are active links and can be used to view the location of the site via 

GoogleMaps.18 21 

 17 2005-2007 PM2.5 design values were taken from the information posted at 

http://www.epa.gov/airtrends/values.html, and are consistent with the design values used in the health risk 

assessment to “roll back” current concentrations to represent achievement of alternative annual and 24-hour PM2.5 

NAAQS. Except in Dallas and Fresno, the area-wide design values are the highest design values of any monitoring 

site in the designated (1997 NAAQS) nonattainment area that has sufficiently complete data to allow the calculation 

of a design value according to the provisions of 40 CFR 50 appendix N. For Dallas, the design values come from a 

site with nearly complete data, and are somewhat higher than the highest values from a site with complete data (see 

the draft PM Risk Assessment, US EPA, 2009c, section 3.2.3) For Fresno, the area-wide design value is for the 

Fresno-Madera CSA, which is only a portion of the San Joaquin Valley nonattainment area. Also, note that there 

are three cases in which the nonattainment area does not include certain areas sometimes thought of as being part of 

the area named in Table 2; monitors in these non-included areas were not considered in this assessment. (1) The 

design value shown for Pittsburgh is for the Pittsburgh-Beaver nonattainment area; the Liberty-Clairton 

nonattainment area is within the Pittsburgh CBSA but is distinct for regulatory purposes, and was not considered in 

this assessment. (2) Baltimore was treated separately, although part of a CSA with Washington DC. (3) Berks Co., 

PA is part of the Philadelphia-Camden-Vineland CSA, but not part of the Philadelphia-Wilmington nonattainment 

area. 

18 Additional meta data on each monitoring site, and access to daily and annual data listings, can be conveniently 

obtained using GoogleEarth and the PM2.5, PM10, and CSN monitoring network KML files that can be downloaded 

from http://www.epa.gov/airexplorer/monitor_kml.htm. 
September 2009 3-12 DRAFT - Do Not Quote or Cite 

1 In 11 of the study areas, the three types of PM2.5 data were available at a common site. In 

2 the remaining four areas, Phoenix, AZ, Pittsburgh, PA, Baltimore, MD, and St. Louis, MO-IL, 

3 two types of data were available at one site, but the remaining type of data had to be taken from 

4 another site and treated as being representative of the former site. 

5 The monitoring agencies described all but one of these sites as neighborhood or urban 

6 scale, indicating those agencies’ opinion that the sites represent concentrations in an area at least 

7 0.5 to 4 km across. An aerial view of the remaining site (in Phoenix) suggests that it may be 

8 middle or neighborhood scale. Selected sites are not necessarily the locations of the maximum 

9 measured annual or 24-hour PM2.5 levels in their urban area. 

10 Hourly PM10-2.5 presented more varied challenges. In four areas (Birmingham, Detroit, 

11 Baltimore, and Philadelphia) the site that provides the continuous PM2.5 data also hosts a 

12 continuous FEM PM10 monitor, and hourly PM10-2.5 could be calculated by difference for most 

13 hours. In other areas, this was not the case, and either (1) instruments at two different sites were 

14 used in this subtraction (Tacoma, Los Angeles-South Coast Air Basin, Phoenix, St. Louis, 

15 Atlanta, and New York-N. New Jersey) or (2) a single regionally applicable PM10-2.5 to PM2.5

16 ratio calculated as part of the last review based on 2001-2003 24-hour FRM/FEM PM10 and 

17 PM2.5 samples was applied to 2005-2007 hourly PM2.5 data to estimate hourly PM10-2.5 (Fresno, 

18 Salt Lake City, Dallas, Houston, and Pittsburgh). In the case of Los Angeles-South Coast Air 

19 Basin, the continuous PM10 and PM2.5 sites were quite distant and separated by a range of hills, 

20 so the estimates of PM10-2.5 and its contribution to total light extinction are more uncertain than if 

21 the monitors were clearly within the same air mass. Obviously, for those study areas for which 

22 1-hour PM10-2.5 was estimated by application of ratios, PM10-2.5 estimates can only represent 

23 broad trends, not hour-specific conditions at the particular site. More description of the methods 

24 used for estimating hourly PM10-2.5 appears in section 3.3.2.

25 The sampling schedule for CSN PM2.5 speciation monitoring was one-in-six days for 

26 Tacoma, Phoenix, Houston, Detroit, and Philadelphia, and one-in-three days for the other study 

27 areas. Not every scheduled CSN site day in 2005-2007 had data for all three types of PM2.5 data, 

28 due to missed or invalid samples. Also, for continuous PM2.5, values for a small number of hours 

29 of an otherwise data-sufficient day were sometimes missing, due to equipment failure or 

30 servicing. EPA staff retained only those days in which 75 percent or more of daylight hours had 

31 measurements of PM2.5 (see section 3.3. for more details). If for isolated hours at a site (or site 

32 pair) with collocated measurements, PM10-2.5 concentrations could not be estimated because of 

33 gaps in the same-hour continuous PM10 and/or PM2.5 data, EPA staff used the regional ratio 

34 approach described above to estimate PM10-2.5 for those specific hours. Table 3-4 provides more 

35 detailed information on the quarterly distribution of the successfully matched and sufficiently 

36 complete data available for use. As described later, for some parts of this assessment EPA staff 
September 2009 3-13 DRAFT - Do Not Quote or Cite 

1 Table 3-3. PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Tacoma St2 

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site 

(if applicable) 

PM10 data source for PM

Tacoma 

AQS ID 530530029

State: Washington City: Tacoma MSA: Tacoma, WA Local Site Name: TACOMA - L STREET Address: 7802 SOUTH L STREET, TACOMA 0.5 miles east of I-5 2005-2007 annual DV = 10.2 2005-2007 24-hr DV = 43 This is the highest 24-hour PM2.5 DV site in the Seattle-Tacoma-Olympia, WA annual PM2.5 nonattainment area Neighborhood Scale Parameters taken from this site: 

 24-hour FRM PM2.5 mass (AQS 

parameter 88101; one-in-three sampling schedule) 

 PM2.5 speciation (one-in-six sampling 

schedule) 

 1-hour PM2.5 mass (AQS parameter 

88502, Acceptable PM2.5 AQI & 

Speciation Mass) Correlated Radiance 

Research M903 Nephelometry 

No continuous PM10 monitoring at this site, 

see right hand column. 

N/A 

AQS ID 530530031

State: Washington City: Tacoma MSA: Tacoma, WA Local Site Name: TACOMA - ALAddress: 2301 ALEXANDER AV6.4 miles NNE of PM2.5 site 

Neighborhood Scale Parameters taken from this site: 

 1-hour PM10 STP mass (AQS  Sample Collection Method: I

SA246B-INLET 

 Sample Analysis Method: TE7% of PM10-2.5 values were determ

PM10-2.5:PM2.5 ratios from 2005 St

Additional Explanation 

 In this Table, the 1-hour concentration parameter “88502, Acceptable PM2.5 AQI & Speciation Mass” is the same as the ISA refers to as “FRM-like” PM2.5 m

Raw Data” indicates that the monitoring agency makes no representation as to the degree of correlation with FRM PM2.5 mass. The latter type of continuous P

the former were unavailable.

 Where PM10 was reported in STP, it was converted to LC before PM10-2.5 was calculated.

 For convenient, continuous PM2.5 data was obtained through the AirNow website rather than from AQS, as an initial exploration indicated that not all the desi

submitted to AQS.
September 2009 3-14 DRAFT - Do Not Quote or Cite 

1 Table 3-4. Number of days per quarter in each study area 2 

2005 2006 

Study Area 

Total Number of Days Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 

Tacoma 110 0 0 0 0 13 15 15 14 13 Fresno 324 19 24 27 27 30 29 29 27 26 Los AngelesSouth Coast Air Basin 

302 28 28 22 28 26 26 27 22 21 

Phoenix 

86 0 13 11 14 12 13 11 12 0 

Salt Lake City 306 27 28 30 26 20 28 31 20 23 Dallas 274 22 24 26 22 23 23 24 24 18 Houston 149 21 20 10 14 14 12 8 12 15 St. Louis 294 27 27 24 27 28 19 27 29 29 Birmingham 350 30 30 29 30 29 29 30 30 30 Atlanta 295 22 25 25 24 28 27 26 27 25 Detroit-Ann Arbor 

141 12 12 10 11 12 13 11 15 11 

Pittsburgh 284 26 23 25 23 22 25 24 26 22 Baltimore 187 19 17 15 11 15 16 19 18 12 PhiladelphiaWilmington 145 15 11 13 10 9 13 10 13 13 New YorkN.New JerseyLong Island 

228 22 23 13 15 23 19 18 21 19 

3 Note: Only days with matched and sufficiently complete data were retained in the assessment.
September 2009 3-15 DRAFT - Do Not Quote or Cite 

1 substituted data for the single missing quarters of data in Phoenix and Houston, to achieve 

2 seasonal balance. 

3 3.2.2 Use of CMAQ Model Runs for 2004 to Augment Ambient Data 

4 Because systematic monitoring data are not available on hourly PM2.5 component 

5 concentrations, EPA staff extracted and applied certain information from the modeling platform 

6 for calendar year 2004 described in section 3.7.1.2 of the second draft ISA, in which the global7 scale circulation model GEOS-Chem was paired with the regional scale air quality model 

CMAQ.19 8 The main use of this platform in the ISA is to estimate policy-relevant background 

9 concentrations of PM2.5. For the urban-focused visibility assessment described here, however, we 

10 used results from the validation run of the platform, in which emissions for all emission source 

11 types and countries are included, to develop realistic diurnal variations of the major PM2.5

12 components. 

13 The EPA staff identified the 36 km-by-36 km CMAQ grid cell corresponding to the 

14 location of the CSN monitoring site used in each study area. We then extracted from the detailed 

15 model output for this grid cell the day/hour-specific concentrations of sulfate, nitrate, elemental 

16 carbon, organic carbon, and “crustal/unspeciated” PM2.5 during 2004, and then we averaged 

across days within the month for each individual hour of the day.20 17 Thus, for each species, EPA 

18 staff obtained 24 values for a month, for each of the 12 calendar months. We then averaged the 

19 24 hourly values in each monthly set for each component to obtain the 24-hour average 

20 concentration for the month. We then divided each hourly value by the 24-hour value, to obtain 

21 a normalized diurnal profile for the pollutant, which was taken to represent all days in that month 

22 for 2005, 2006, and 2007. In total, this resulted in 5 (components) x 12 (months) x 15 (study 

23 areas) = 900 profiles. Visual examination of a number of these showed them to be reasonably 

24 smooth and generally to show morning (and sometimes also late afternoon/evening) peaks which 

25 are the anticipated effect of higher vehicle traffic and lower mixing heights. The peaks were 

26 generally moderate, as would be expected in light of the large grid cells and generally moderate 

27 diurnal profiles for SMOKE pre-processing of emissions in the CMAQ modeling platform. 

28 Sulfate, as would be expected for a regionally transported pollutant, generally had a flatter 

29 diurnal profile than for other components. Hourly nitrate concentrations were low when 

30 expected: during warmer months and in warmer areas. Figure 3-4 shows example diurnal profiles 

 19 Similar modeling was not available for 2005, 2006, or 2007. 

20 For several of the listed components that are not direct CMAQ outputs, concentrations were estimated by postprocessing to aggregate the appropriate CMAQ outputs. The “crustal/unspeciated” CMAQ output results from nonreactive dispersion of that portion of the PM2.5 emission inputs not assigned during SMOKE processing to a more 

specific CMAQ species, and is considered in most EPA analyses to represent the same material as the “soil” 

component reported for IMPROVE sampling.
September 2009 3-16 DRAFT - Do Not Quote or Cite 

1 for the five PM2.5 components, for the Detroit study area for the months of January and August. 

2 Diurnal profiles like these were applied to 24-hour CSN measurements of component 

3 concentrations, as explained in detail below. 

4 3.2.3 Use of Original IMPROVE Algorithm to Estimate Light Extinction 

5 The EPA staff used the original IMPROVE light extinction algorithm, rather than the 

6 more recent revised version, because the original version is considered more representative of 

7 urban situations, when emissions are still fresh rather than aged as at remote IMPROVE sites. 

8 To maintain consistency with the form of the candidate protective levels (CPLs) identified in 

chapter 2, we staff included a value of 10 Mm-1 9 to represent clear air Rayleigh scattering, and we 

use the term “total light extinction” to indicate this.21 10 No presumption is intended regarding 

11 whether a possible secondary NAAQS using measured light extinction as the indicator should 

12 include or exclude light extinction due to gases. The formula for total light extinction using the 

13 traditional IMPROVE algorithm is shown below. 

14 

15 

Total light extinction (bext) is in units of Mm-1 16 , the mass concentrations of the 

17 components indicated in brackets are in μg/m3, and f(RH) is the unitless water growth term that 

18 depends on relative humidity. We refer to the first five terms in this algorithm as the five PM2.5

19 components. In this algorithm, the sulfate and nitrate components are to be expressed as fully 

20 neutralized, without associated water since the water absorption effect is reflected in the f(RH) 

21 term. The organic mass component is to include the mass of associated elements other than 

22 carbon. As described below, we included steps in our development of estimates of hourly 

23 component concentration to ensure consistency with these aspects of the IMPROVE algorithm.

 21 We did not include a term for light absorption by NO2 or other gases. 
September 2009 3-17 DRAFT - Do Not Quote or Cite 

1 Figure 3-4. January and August monthly average diurnal profiles of PM2.5 components 

2 derived from the 2004 CMAQ modeling platform, for the Detroit study area.

Normalized Diurnal Profile for PM2.5 Components

 (January, Detroit)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM

soil

ec

no3

so4

ocm

3 

Normalized Diurnal Profile for PM2.5 Components

 (August, Detroit)

0

0.5

1

1.5

2

2.5

3

12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM12:00:00 AM

soil

ec

no3

so4

ocm

4 
September 2009 3-18 DRAFT - Do Not Quote or Cite 

1 3.3 DETAILED STEPS 

2 3.3.1 Hourly PM2.5 Component Concentrations 

3 The task of estimating hourly PM2.5 component concentrations is in a sense over4 determined, given the four types of available information: 24-hour PM2.5 mass by filter-based 

5 FRM, 24-hour component concentrations by CSN, hourly PM2.5 mass by continuous instrument, 

6 and diurnal profiles of components from the 2004 CMAQ run. There are multiple ways in which 

7 two or three of these four data sources could be used to estimate hourly PM2.5 component 

8 concentrations, and the result generally can be expected to be at least somewhat inconsistent with 

9 the information in the remaining data sources. For example, each 24-hour PM2.5 component 

10 mass from CSN sampling can be apportioned to hours based on the diurnal profile developed 

11 from the 2004 CMAQ run, but then in general the hourly values of PM2.5 mass determined by 

12 summing the components in an hour would not exactly match the data from the continuous PM2.5

13 instrument. EPA staff therefore used a sequence of steps which achieves a prioritized 

14 compromise among the data sources. In this sequence, we have given greater weight to the 24-

15 hour FRM, CSN, and continuous PM2.5 mass data because these are instrument-based and 

16 location- and day-specific, than to the CMAQ-based profiles which are CTM-based, averaged to 

17 the month, and extrapolated from 2004 to each of 2005, 2006, and 2007. 

18 Because of differences in filter materials, laboratory analysis, and data reporting, there 

19 are differences between the contribution of some PM components to PM2.5 mass as, reported by 

20 filter-based 24-hour FRM sampler or by continuous instruments, and the mass of the same 

21 component as reported by CSN (or IMPROVE) sampling. The following summary of these 

22 differences may be helpful in understanding the steps used to develop estimates of hourly PM2.5

23 components in this analysis. In the IMPROVE algorithm for reconstructing total light extinction, 

24 the light extinction contribution multipliers per unit of mass concentration of components are 

25 different for each of the five principle components. Consequently, care is required to estimate 

26 these components as consistently as possible with the IMPROVE sampling and analytical 

27 methods. 

28  Nitrate: CSN (and IMPROVE) sampling uses a Nylon filter for purposes of nitrate 

29 quantification, while FRM sampling uses a Teflon filter for PM2.5 as a whole. The 

30 Nylon filter limits the loss of nitrate in the form of nitric acid vapor, compared to the 

31 Teflon filter. Hence, the nitrate mass reported by CSN (and IMPROVE) sampling 

32 typically will be higher than the nitrate contribution to FRM PM2.5 mass, particularly 

33 under warm ambient conditions. In addition, the IMPROVE program does not measure 

34 ammonium ion and hence must make an assumption that nitrate ion is fully neutralized 

35 by ammonium ion. In contrast, in FRM sampling ammonium ion is measured and it is 

36 possible for nitrate to be found not to be fully neutralized. These two factors tend to 

37 make nitrate mass as reported for a CSN or IMPROVE site higher than the nitrate 
September 2009 3-19 DRAFT - Do Not Quote or Cite 

1 contribution to PM2.5 mass reported for a FRM site. On the other hand, FRM sampling 

2 results in some water that is associated with nitrate being included in the reported PM2.5

3 mass, while the nitrate mass reported by CSN (or IMPROVE) sampling excludes all 

4 water. Continuous PM2.5 samplers employ a variety of methods for measuring PM2.5

5 mass, with correspondingly different behavior regarding retention/loss of nitrate. 

6 However, it is generally accepted that the continuous PM2.5 sampling methods used at the 

7 study sites have less nitrate retention than a CSN sampler, and are more like the FRM 

8 method in that regard. 

9  Sulfate: Unlike nitrate, sulfate is not subject to loss once collected by a filter, but like 

10 nitrate the issues of neutralization and water retention apply. Also, as for nitrate, as a first 

11 order approximation, continuous PM2.5 instruments can be assumed to be more like FRM 

12 samplers in reporting the mass effect of sulfate than like CSN samplers. 

13  Elemental and Organic Carbon: Only the mass of carbon atoms is included in the 

14 reported elemental carbon and organic carbon for a CSN (or IMPROVE) sampler. In 

15 addition, the distinction between elemental and organic carbon atoms is dependent on the 

16 specifics of the two different thermo-optical analytical methods used in the CSN vs. the 

IMPROVE network.22 17 Also, the quartz filter used to quantify carbonaceous material in 

18 CSN and IMPROVE sampling both absorbs and loses organic vapors during sampling, 

19 while the Teflon filter in a FRM sampler does not absorb organic vapors (although PM 

20 on the filter may do so). Therefore, some method other than direct measurement must be 

21 used to estimate the total mass concentration of organic carbonaceous material in ambient 

22 air. The IMPROVE program adjusts for absorption of vapors by subtracting a monthly 

23 average backup filter value, and then applies a standard adjustment factor (1.4 in the 

24 “old” IMPROVE method) to the remaining organic carbon measurement to estimate 

25 organic carbonaceous material. In contrast, the standard reports from CSN sampling 

26 submitted to AQS do not include these two adjustments, but it is routine for EPA staff to 

27 apply similar adjustments for the same purpose, after reporting of CSN data to AQS. For 

28 this assessment the SANDWICH approach to such adjustments (Frank, 2006) is used to 

29 estimate the organic mass through a mass balance of component measured on the CSN 

30 and FRM samplers. 

31  Hourly PM2.5: The continuous instruments used for measuring hourly PM2.5 mass were 

32 different among sites (as listed in Appendix A), and none of the instrument types that 

33 provided data for this assessment perfectly measures “true” ambient concentrations. 

34 None of them, when averaged over 24 hours, exactly matches either the measurements of 

35 PM2.5 mass from a FRM sampler or the sum-of-components reportable from CSN 

36 sampling. Differences can arise because of differences in water capture and retention, 

37 inconsistent absorption and loss of organic vapors and nitric acid vapor, etc. In 2006, 

38 EPA developed and promulgated criteria for approval of continuous PM2.5 samplers as 

39 “federal equivalent methods”. These criteria assure a minimum level of correlation 

40 between approved continuous instruments and the FRM method, when data from both are 

 22 While CSN carbon sampling and analysis methods have recently been harmonized with IMPROVE methods at 

many CSN sites, it was not until mid-2007 that the first 57 sites were using the harmonized methods. Consequently, 

most of the elemental and organic carbon data used in this assessment were obtained with the original CSN methods. 
September 2009 3-20 DRAFT - Do Not Quote or Cite 

1 expressed as 24-hour average concentrations. However, in 2005-2007 no commercially 

2 available instruments were yet approved under those criteria. Consequently, the 

3 continuous instruments providing data to this assessment can be assumed to have a range 

4 of correlation performance versus the FRM. In light of these consistency issues, the 

5 hourly data from the continuous instruments were taken to be most indicative of the 

6 relative concentrations of PM2.5 from hour-to-hour, with less reliance on the absolute 

7 accuracy of the continuous instruments. 

8 Taking into consideration the above information, EPA staff combined the four types of 

9 available PM2.5 data in each study area using the following steps. Figure 3-5 provides a flow 

10 chart that may assist in understanding these steps. 

11 

12 Figure 3-5. Sequence of steps used to estimate hourly PM2.5 components and total light 

13 extinction 
September 2009 3-21 DRAFT - Do Not Quote or Cite 

1 1. The SANDWICH method (Frank, 2006) was used to subdivide the 24-hour PM2.5 mass 

2 reported by the FRM for each day and site into sulfate (including associated ammonium 

3 and residual water during filter weighing), nitrate (including associated ammonium and 

4 residual water during filter weighing), elemental carbon, organic carbonaceous mass, and 

5 fine soil/crustal mass. This is done using information from the CSN measurements, 

6 physical models, and day-specific temperatures. Significantly, in the SANDWICH 

7 method, the component referred to as organic carbonaceous mass is actually a residual 

8 whose value is determined as the difference between the PM2.5 mass determined from 

9 weighing the FRM filter and the sum of the estimated masses of the other four mass 

10 components as listed above. 

 11 

12 2. The CMAQ-derived monthly diurnal profiles for sulfate, nitrate, elemental carbon, 

13 organic carbon and fine soil/crustal, like the examples for Detroit in Figure 3-4, were 

14 multiplied by the day-specific SANDWICH-based estimates of the 24-hour average 

15 concentrations of these five PM2.5 components, to get day-specific hourly estimates of 

16 these five components (including ammonium and water associated with sulfate and 

17 nitrate ion). 

18 3. The hourly concentrations of these five components (including ammonium and water 

19 associated with sulfate and nitrate ion when the filter is weighed) were added together, to 

20 get a sum-of-components estimate of hourly PM2.5 mass for the day of the FRM 

21 sampling. 

22 4. The hourly data from the continuous PM2.5 instrument on the day of the FRM sampling 

23 were normalized by their 24-hour average, to get a diurnal profile. (Recall that days were 

24 not used in this assessment if hourly PM2.5 mass data were missing for more than 25 

25 percent of daylight hours.) This profile was applied to the 24-hour PM2.5 mass reported 

26 by the FRM sampler, to get a second, FRM-consistent estimate of hourly PM2.5 mass for 

27 the day of the FRM sampling. This is straightforward when all 24 values of 1-hour PM2.5

28 mass were available for the day. However, for some (but not many) days, some values 

29 for continuously measured hourly PM2.5 mass were missing. In such cases, EPA staff 

30 used only the hours with valid 1-hour PM2.5 mass values to develop the diurnal profile 

31 and then applied the profile to the FRM value as just described. This keeps the average 

32 of the valid 1-hour PM2.5 values equal to the 24-hour value from the FRM sampler. 

33 5. The two estimates of hourly PM2.5 mass from steps 3 and 4 were compared, hour-by34 hour. By virtue of the way they were derived, the averages of these estimates across all 

35 24 hours of the day will necessarily be the same (and will be equal to the 24-hour FRM 

36 measurement). However, while the diurnal pattern of these two estimates of the same 

37 physical parameter should also be generally similar, it can be expected (and it is 

38 observed) that the hourly measurements from the continuous PM2.5 instruments (after 

39 adjustment to be consistent with the FRM data) have more hour-to-hour variability. 

40 Figure 3-6 gives an example of this comparison, for one day for the Detroit study area. 

 41 

 42 
September 2009 3-22 DRAFT - Do Not Quote or Cite 

1 Figure 3-6. Example from Detroit study area. 

0

5

10

15

20

25

30

35

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Concentration, ug/m3

FRM adjusted Hourly PM2.5

Sum of diurnalized SANDWICHED species data using CMAQ profiles

Example comparison from the Detroit study area of hourly PM2.5 mass on March 24, 2006 as 

estimated by applying CMAQ-based diurnal profiles to SANDWICH estimates of 24-hour 

component concentrations versus applying a diurnal profile derived from continuous PM2.5

measurements to FRM PM2.5 mass. 

2 

3 6. Given that the continuous instrument is reacting to hour-specific local conditions that can 

4 vary from hour-to-hour due to real variations in local emissions and dispersion/transport 

5 conditions, while the CMAQ-based estimates contain much less specific information, the 

6 diurnal pattern of PM2.5 mass observed by the continuous instrument (adjusted to be 

7 consistent with the FRM value for 24-hour average PM2.5) was taken as more reliable. 

8 Within each hour, the estimates of all five components from step 2 were increased or 

9 decreased by a common percentage (referred to below as Ai where the subscript i 

10 indicates the hour) so that the sum of the five components after this adjustment was equal 

11 to the estimate of the hourly PM2.5 mass from step 4. The adjustment percentage varied 

12 from hour-to-hour. Necessarily, in some hours the adjustment is an increase in the 

13 concentrations of all components, and in other hours it is a decrease. While this 

14 adjustment preserves the consistency between the 24 values of hourly PM2.5 mass and the 

15 24-hour FRM mass, it can disturb the consistency between the hourly estimates of PM2.5

16 components and the SANDWICH-based estimates of 24-hour average component 

17 concentrations. This disturbance was generally small, because the adjustments 

18 necessarily go in one direction for some hours and the other direction for other hours. For 

19 example, for the particular day in Detroit used for illustration purposes in Figure 6, the 

20 effect of this step was to cause a discrepancy of 3 percent between the SANDWICH21 based values of 24-hour sulfate concentration and the average of the 24 estimates of 1-
September 2009 3-23 DRAFT - Do Not Quote or Cite 

1 hour sulfate concentrations (the positive percent indicates a higher concentration in the 

2 result of this step than the SANDWICH-based value). The discrepancies were 1, 1, 2, 

3 and 2 percent for nitrate, elemental carbon, organic carbon, and fine soil/crustal, 

4 respectively.

5 7. Each hourly estimate of sulfate concentration from step 6 (which includes estimates of 

6 associated ammonium and particle bound water) was adjusted so that it excludes water 

7 and reflects full neutralization and therefore is consistent with the reporting practices of 

8 the IMPROVE program and the IMPROVE algorithm. This was done via these sub9 steps: 

10 a. The 24-hour CSN value for the dry mass of sulfate ion (not SANDWICHed, no 

11 ammonium) was multiplied by 1.375 to reflect an assumption of full 

12 neutralization. 

13 b. The ratio of this fully neutralized 24-hour sulfate mass to the SANDWICH-based 

14 24-hour sulfate value was calculated. 

15 c. This ratio was applied to each individual hour’s sulfate concentration from step 6. 

16 As in Step 6, it is possible for the 24 final hourly sulfate estimates to no longer be 

17 exactly consistent with the 24-hour CSN sulfate measurement. 

18 

19 8. A similar adjustment as in step 7 (for sulfate) was made to each hour’s nitrate 

20 concentration from step 6, so that the estimate of hourly nitrate would reflect actual 

21 atmospheric conditions and be consistent with the IMPROVE algorithm. However, the 

22 ratio approach used in step 7(b) for sulfate could not be applied for nitrate, so this 

23 adjustment had to be more complicated. Because in warm weather the FRM Teflon filter 

24 does not retain nitrate, the initial FRM-consistent nitrate estimate derived by applying the 

25 SANDWICH method to the FRM and CSN data can be zero. Such a zero value makes it 

26 impossible to use the ratio approach in 7(b). Instead, the adjustment was made as 

27 follows: 

28 a. The 24-hour CSN value for nitrate ion (not SANDWICHed, no ammonium) was 

29 multiplied by 1.29 to reflect an assumption of full neutralization. 

30 b. This 24-hour value was then diurnalized using the CMAQ-based profile, similar 

31 to step 2. 

32 c. Each resulting hourly value of nitrate was further multiplied by the Ai factor from 

33 step 6. 

34 d. This new estimate of hourly nitrate was used to replace the initial nitrate value 

35 that had resulted from step 6. 

36 For cooler areas and days in which the 24-hour SANDWICH results include some nitrate, 

37 the effect of these steps for nitrate are exactly the same as the effects of step 7 for sulfate (except 

38 for the 1.29 vs. 1.37 neutralization factor). For warmer areas and days in which the 24-hour 
September 2009 3-24 DRAFT - Do Not Quote or Cite 

1 SANDWICH results did not include any nitrate even though nitrate was measured on the CSN 

2 Nylon filter, the effect of these steps is to assign the CSN nitrate to each hour using a 

3 combination of the information in the CMAQ-based profiles and the information provided by the 

4 continuous PM2.5 sampler. As in Step 6, it is possible for the 24 final hourly nitrate estimates to 

5 no longer be exactly consistent with the 24-hour CSN nitrate measurement. 

6 3.3.2 Hourly PM10-2.5 Concentrations 

7 Three different paths were used to estimate hourly PM10-2.5 concentrations, in the 

8 following order of preference: 

 9 

10 1. When hourly data from a collocated PM10 instruments were available at the continuous 

11 PM2.5 site in a study area, PM2.5 was subtracted hour-by-hour from PM10. Negative values 

12 were reset to zero. 

 13 

14 2. When collocated continuous PM10 data were not available at the continuous PM2.5 site in 

15 a study area, but continuous PM10 data were available at another site in the same study 

16 area, PM10-2.5 was estimated by subtraction, implicitly assuming that the latter site was 

17 also representative of PM10 at the former site. 

 18 

19 3. If neither of the first two methods was possible, a regional average ratio of PM10-2.5 to 

20 PM2.5 determined from an analysis of 24-hour data for the 2005 Staff Paper was applied 

21 to hourly PM2.5 from the continuous instrument associated with the study area. 

 22 

23 The estimation of PM10-2.5 was further complicated because some types of data were 

24 missing for isolated hours in the 2005-2007 period. As result, even for a single study area more 

25 than one method sometimes had to be used to estimate hourly PM10-2.5. Appendix A gives more 

26 specifics about the estimation of hourly PM10-2.5 in each study area. 

27 The three-path approach described here is similar to that used for the visibility analysis 

28 reported in the 2005 Staff Paper. While the second and third paths involve the use of data and 

29 assumptions that are not robust compared to the use of paired, collocated, same-method 

30 continuous instruments or to the use of paired low-volume filter-based samplers, in most areas 

31 and periods the contribution to total light extinction from the resulting PM10-2.5 concentrations 

32 was not large compared to the light extinction due to PM2.5 components. 

33 3.3.3 Hourly Relative Humidity Data 

34 Hourly relative humidity (RH) data for each study area’s primary monitoring site were 

35 obtained hour-by-hour from the closest available non-missing relative humidity measurement, as 

36 reported by either an air monitoring station reporting such data to AQS or a National Weather 

37 Service (NWS) station. For the AQS RH data, parameter 62201 values were utilized. RH data 

38 from both sources are expressed as percentages. 
September 2009 3-25 DRAFT - Do Not Quote or Cite 

1 3.3.4 Calculation of Hourly and Daily Maximum 1-Hour Total Light Extinction 

2 The original IMPROVE algorithm was applied hour-by-hour to estimate total light 

3 extinction in each study area. 

4 Because the interest in this analysis is on visibility during daylight hours, EPA staff 

5 applied an hour-of-day filter to identify those hours that were daylight hours. The actual times of 

6 local sunset and sunrise for each day and area were taken from tables of sunrise and sunset 

7 available from the US Naval Observatory for each of the 15 urban areas. Daylight hours were 

8 defined as any hour (e.g., 8:00 AM to 8:59 AM) containing no minutes before sunrise or after 

9 sunset. For simplicity, these were generalized, so that all the days within each “season” in all 

study areas were considered to have the same daylight hours.23 10 Table 3-5 shows the resulting 

11 definition of daylight hours for the study areas. Unless otherwise stated, all subsequent 

12 discussion of the results refers only to the values of parameters during these daylight hours. 

13 

14 Table 3-5. Assumed daylight hours by season (Local Standard Time) 

15 

NovemberJanuary February-April May-July August-October 

First hour that is 

entirely daylight 

8:00-9:00 AM 7:00-8:00 AM 5:00-6:00 AM 6:00-7:00 AM 

Last hour that is 

entirely daylight 

3:00-4:00 PM 5:00-6:00 PM 6:00-7:00 PM 5:00-6:00 PM 

Number of 

daylight hours 

8 11 14 12 

16 

17 Daily maximum 1-hour total light extinction is the statistic of most interest in this 

18 assessment, as briefly discussed in section 2.6. Days were set aside and not used to determine 

19 this statistic if the hourly PM2.5 mass value was missing (or reported to be less than zero) for 

20 more than 25 percent of daylight hours. Two or three missing daylight hours were allowed, 

21 depending on season. 

22 In this assessment, we capped the value of the humidity adjustment factor in the 

23 IMPROVE algorithm (“f(RH)”) at the value it has for a relative humidity of 95 percent. The 

24 effect of measurement errors in relative humidity at values above 95 percent on the value of 

25 f(RH) and thus on reconstructed total light extinction is considerable because of the highly 

26 nonlinear form of the function in that range. This creates uncertainty as to the representativeness 

27 of the extinction values calculated with high values of relative humidity. In addition, very high 

28 values of relative humidity may be due to ongoing or very recent precipitation or fog. Persons 

 

23 This simplification may be eliminated for the final version of this assessment. 
September 2009 3-26 DRAFT - Do Not Quote or Cite 

1 may not expect or value clear visibility during such conditions. Later, consideration will be 

2 given to the interpretation of these results and the appropriate treatment of days with very high 

3 relative humidity in the statistical form of possible secondary PM NAAQS aimed at protection of 

4 visibility in urban areas. 

5 3.4 SUMMARY OF RESULTS FOR CURRENT CONDITIONS 

6 3.4.1 Levels of Estimated PM2.5, PM2.5 Components, PM10-2.5, and Relative Humidity 

7 Figure 3-7 presents box-and-whisker plots to illustrate the distributions in each study area 

8 of the estimates of 1-hour PM2.5 (the diurnalized FRM value, resulting from step 4 in section 

9 3.4.1), PM10-2.5, and relative humidity over the entire 2005-2007 study period. In the plot for 

10 each parameter, areas are ordered by longitude, to make it easier to see east-versus-west regional 

11 differences. For these three parameters, the distributions are given for all the daylight 1-hour 

12 estimates. Similar plots of the daily maximum daylight 1-hour values of PM2.5, PM10-2.5, and 

13 relative humidity concentration are available in Appendix B, as are plots of all daylight 1-hour 

14 values for each of the PM2.5 component species. 

15 From these plots we see that the distributions of PM2.5 generally trend toward higher 

16 concentrations from west to east except for the two California urban locations which have PM2.5 

17 concentrations more typical of eastern areas. The lowest median PM2.5 concentrations are in 

18 Tacoma, WA, and Phoenix, AZ. Median PM10-2.5 concentrations are highest in St. Louis, MO, 

19 and Phoenix, AZ, and lower elsewhere. The highest outlier PM10-2.5 concentrations are in St. 

20 Louis, MO, and Los Angeles, CA. Relative humidity is lowest for the western urban areas 

21 except for Tacoma, WA, which is similar to the northeastern urban locations with respect to 

22 humidity. These hourly daylight PM concentration and relative humidity box and whisker plots 

23 are consistent with our expectations based on regional 24-hour PM concentration values and 

24 humidity climatology. 

25 3.4.2 Levels of Estimated Total Light Extinction 

26 Figure 3-8 presents box-and-whisker plots to illustrate the distributions of the estimates 

27 of daylight 1-hour reconstructed total light extinction levels in each area in each year. The 

28 distribution of the individual 1-hour values (8a) and the daily maximum 1-hour values (8b) are 

29 both shown. The horizontal dashed lines in the plots represent the low, middle, and high 

30 candidate protective levels (CPL) as discussed in section 2.6. These benchmarks for total light 

extinction are 74, 122, and 201 Mm-1 31 , corresponding to the benchmark VAQ values of 20 dv, 25 

32 dv and 30 dv. Table 3-6 provides the percentages of days (across all of 2005-2007, unweighted) 

33 in which the daily maximum daylight 1-hour total light extinction level was greater than each of 

34 the three candidate protective levels.
September 2009 3-27 DRAFT - Do Not Quote or Cite 

1 As was also seen in the comparable PM2.5 box and whisker plots in Figure 3-7, the hourly 

2 total light extinction values in Figure 3-8 tend to be higher in the eastern urban areas and lower 

3 in the non-California western urban areas. The distributions of maximum daily total light 

4 extinction values are higher (Figure 3-8b), as expected, than for all hours (Figure 3-8a). Both 

5 Figure 3-8 and Table 3-6 indicate that all 15 urban areas have daily maximum hourly total light 

6 extinctions that exceed even the highest of the CPL some of the time. Again, the non-California 

7 western urban locations have the lowest frequency of maximum hourly total light extinction with 

8 values in excess of the high CPL less than 10% of the time. Except for the two Texas and the 

9 non-California western urban areas, all of the other urban areas exceed that high CPL about one10 quarter to one-half the time. Based on these estimated maximum hourly total light extinction 

11 estimates, all 15 of the urban areas exceed the low CPL for about 60% to 100% of the days. As 

12 noted in section 3.2.1, in most of the study areas the study site used in this assessment is not the 

13 site in the study area with the highest concentrations of PM2.5. 

14 In the last review of the secondary PM NAAQS, the pattern of light extinction during the 

15 day was of particular interest. To illustrate the distributions of 1-hour total light extinction levels 

16 in specific daylight hours, Figure 3-9 shows the distributions of 1-hour total light extinction 

17 across the entire three-year study period, individually for the study areas. (Appendix E provides 

18 additional graphics related to temporal/spatial patterns of light extinction.) These plots show that 

19 high total light extinction can occur during any of the daylight hours, though for most of these 

20 urban areas the early morning hours have the highest total light extinction. Urban areas without 

21 a prominent preference for early morning high total light extinction include Phoenix, AZ; Salt 

22 Lake City, UT; Tacoma, WA; Fresno, CA; and Philadelphia, PA.
September 2009 3-28 DRAFT - Do Not Quote or Cite 

1 Figure 3-7. Distribution of PM parameters and relative humidity across the 2005-2007 

2 period, by study area 

3 

4 (a) Estimates of 1-hour PM2.5 mass, based on applying continuous instrument-based 

5 diurnal profiles to 24-hour FRM PM2.5 mass 

6 

7 

8 (b) Estimates of 1-hour PM10-2.5

9 
September 2009 3-29 DRAFT - Do Not Quote or Cite 

1 Figure 3-7. (cont.). Distribution of PM parameters and relative humidity across the 2005-

2 2007 period, by study area 

3 

4 (c) 1-hour relative humidity 

5 
September 2009 3-30 DRAFT - Do Not Quote or Cite 

1 Figure 3-8. Distributions of estimated daylight 1-hour total light extinction and maximum 

2 daily daylight 1-hour total light extinction across the 2005-2007 period, by study area. 

3 

4 (a) Individual 1-hour values 

5 

6 (b) Maximum daily values 

7 
September 2009 3-31 DRAFT - Do Not Quote or Cite 

1 Table 3-6. Percentage of days in which daily maximum daylight 1-hour total light 

2 extinction exceeded three candidate protective levels across the 2005-2007 period, 

3 by study area 

4 

Candidate Protective Level 

74 Mm-1 122 Mm-1 201 Mm-1

Study Area 

Number of Days with 

Estimates Percentage of days 

Tacoma 110 68 36 9 

Fresno 324 80 51 24 

Los Angeles-South 

Coast Air Basin 302 92 80 49 

Phoenix 86 59 13 3 

Salt Lake City 306 61 24 9 

Dallas 274 86 53 14 

Houston 149 89 58 21 

St. Louis 294 100 86 55 

Birmingham 350 96 80 52 

Atlanta 295 95 80 34 

Detroit-Ann Arbor 141 91 79 57 

Pittsburgh 284 93 70 43 

Baltimore 187 88 65 38 

PhiladelphiaWilmington 145 95 76 46 

New YorkN. New Jersey-Long 

Island 

228 91 70 46 

Average 232 86 61 33 
September 2009 3-32 DRAFT - Do Not Quote or Cite 

1 Figure 3-9. Distributions of 1-hour total light extinction levels by daylight hour across the 2005-2007 pe2 3 
September 2009 3-33 DRAFT - Do Not Quote or Cite 

1 3.4.3 Patterns of Relative Humidity and Relationship between Relative Humidity 

2 and Total Light Extinction 

3 Figure 3-10 shows the distribution of relative humidity values at each daylight hour, for 

4 each study area across 2005-2007 (Seasonal patterns are shown in Appendix E). As expected, in 

5 every area relative humidity is lowest in the early afternoon, typically the warmest part of the 

6 day. Relative humidity is most similar across areas in this time period, as observed in the 2005 

7 Staff Paper. However, even in this period there are notable differences among areas. This 

8 variation was not as evident in the information presented in the 2005 Staff Paper because only 

9 regionally averaged information was presented. In all areas, there is considerable variation in 

10 hour-specific relative humidity during the three-year period. 

11 To allow closer inspection of estimated total light extinction values that have been 

12 calculated using high relative humidity values, Figure 3-11 is a scatter plot of actual (uncapped) 

13 1-hour relative humidity and 1-hour reconstructed total light extinction. Horizontal lines are 

14 included in each of the individual plots corresponding to the three benchmarks for total light 

15 extinction and a vertical line in each for 90 percent relative humidity. As stated above, f(RH) was 

16 capped at its value when relative humidity is 95 percent. While some of the highest values of 

17 total light extinction occur when relative humidity is above 90 percent, the majority of the 

18 instances with total light extinction greater than the candidate protective levels occur when 

19 relative humidity is 90 percent or lower. Notice that in Figure 3-11 there are plenty of high 

20 humidity conditions for each urban area that correspond to low total light extinction values. This 

21 is because humid air does not by itself contribute to light extinction. Particles composed of 

22 material that absorbs water in high relative humidity conditions (e.g., sulfate and nitrate PM) 

23 swell to larger solution droplets that scatter more light than their smaller dry particle counterparts 

24 in a less humid environment. The magnitude of the relative humidity effect on light extinction 

25 depends directly on the concentration of these hygroscopic PM components. (Figure 3-11 

26 reveals skips in reported relative humidity values for some but not all the study areas. This is a 

27 result of calculations of relative humidity from dry and wet bulb temperatures reported to the 

28 nearest whole Celsius degree.) 
September 2009 3-34 DRAFT - Do Not Quote or Cite 

1 Figure 3-10. Distributions of 1-hour relative humidity levels by daylight hour across the 2005-2007 per2 

3 
September 2009 3-35 DRAFT - Do Not Quote or Cite 

Figure 3-11. Scatter plot of daylight 1-hour relative humidity (percent) vs. reconstructed total light extin

1 2 the 2005-2007 period, by study area 3 
September 2009 3-36 DRAFT - Do Not Quote or Cite 

1 3.4.4 Extinction Budgets for High Total Light Extinction Conditions 

2 An extinction budget for a single period shows the contribution that each PM component 

3 makes to total light extinction via the additive terms of the IMPROVE algorithm. It can be 

4 expected that the pattern in the extinction budgets will vary by time of year and by study area. 

5 Examination of extinction budgets allows initial insights into what emission reduction approach 

6 may be most effective in reducing total light extinction. 

7 Figures 3-12 through 3-19 present day-specific maximum daylight 1-hour light extinction 

8 budgets for the 10% of the days in each study area that have the highest daily maximum 1-hour 

9 light extinction levels. (These figures show PM light extinction, not total light extinction. The 

Rayleigh scattering term of 10 Mm-1 10 is not shown in Figures 3-12 through 3-19.) The pattern of 

11 results shown in Figures 3-12 through 3-19 is generally as expected in light of emissions and 

12 climate differences among study areas. Except for the PM2.5 soil component, each of the 

13 components of total light extinction is a major contributor to extreme light extinction events at 

14 some time and location. In the West, carbonaceous PM2.5 (i.e., organic mass and elemental 

15 carbon), nitrate, and/or coarse mass (especially in Phoenix) tend to be most responsible for these 

16 high haze hours. In the East it tends to be sulfate, nitrate, and the carbonaceous PM2.5 

17 components that are the large contributors to total light extinction. From the sample period dates 

18 we can determine the seasonal variations in major components. Nitrate and carbonaceous PM2.5

19 contribute more to the extreme light extinction periods during winter, while sulfate contributes 

20 more in the summer. In many of the more northerly eastern urban areas, a combination of sulfate 

21 and nitrate contributes to high light extinction year-round. 

22 Looking at individual urban areas, Tacoma has its highest light extinction hours in the 

23 colder months and primarily due to carbonaceous PM2.5 components. Extreme haze hours in the 

24 two California urban areas are primarily caused by high nitrate PM2.5, though Los Angeles has 

25 several extreme hours associated with coarse PM. Phoenix is unique among the 15 urban areas 

26 in having most of its extreme light extinction caused by coarse PM, though there are a few top27 10-percent days where the maximum hourly haze is dominated by carbonaceous, sulfate, and 

28 nitrate PM2.5. Salt Lake City has extreme haze hours caused mostly by nitrate in the winter with 

29 some periods with carbonaceous PM2.5 being the major contributor. Dallas and Houston have 

30 high contributions to total light extinction by sulfate PM2.5, but Dallas includes winter nitrate and 

31 carbonaceous-caused extreme hours in the winter while Houston seems to have less contribution 

32 by nitrate. Sulfate in the summer and nitrate in the fall and winter are responsible for most of the 

33 extreme light extinction at St. Louis, though there are several maximum hourly periods where 

34 coarse PM is a major component. Birmingham and Atlanta are similar in having sulfate year35 round and winter carbonaceous PM2.5 as major contributors to their extreme light extinction 

36 periods. Detroit has frequent large light extinction contributions from nitrate PM2.5, mostly in 
September 2009 3-37 DRAFT - Do Not Quote or Cite 

1 the winter, as well as some contributions from sulfate PM2.5 year-round and one winter period 

2 with high contributions from carbonaceous PM2.5. The remaining four urban locations (i.e., 

3 Pittsburgh, Baltimore, Philadelphia, and New York) are similar in that most of their extreme 

4 light extinction is from year-round combinations of sulfate and nitrate. New York also has some 

5 winter carbonaceous contributions to its extreme light extinction. 

6 3.5 POLICY RELEVANT BACKGROUND 

7 Policy relevant background levels of total light extinction have been estimated for this 

8 assessment by relying on outputs for the 2004 CMAQ run in which anthropogenic emissions in 

9 the U.S., Canada, and Mexico were omitted, as described in the second draft ISA. Estimates of 

10 PRB for total light extinction were calculated from modeled concentrations of PM2.5 components 

11 using the IMPROVE algorithm. The necessary component concentrations were extracted from 

12 the CMAQ output files, as they were not summarized in the second draft ISA. More detail is 

13 provided in Appendix C. 

14 It is also necessary to have estimates of PRB for PM10-2.5, as input to the IMPROVE 

15 algorithm. The second draft ISA for this review does not present any new information on this 

16 subject. The approach used in the two previous reviews was to present the historical range of 

17 annual means of PM10-2.5 concentrations from IMPROVE monitoring sites selected as being least 

18 influenced by anthropogenic emissions (US EPA, 2004, Table 3E-1). For this assessment, EPA 

19 staff estimated PRB for PM10-2.5 using a contour map based on average 2000-2004 PM10-2.5 

20 concentrations from all IMPROVE monitoring sites, found in a recent report from the 

21 IMPROVE program (DeBell, 2006). 
September 2009 3-38 DRAFT - Do Not Quote or Cite 

1 Figure 3-12. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 

2 1-hour PM light Extinction for 2005-2007 (Tacoma and Fresno) 

3 

4 

5 
September 2009 3-39 DRAFT - Do Not Quote or Cite 

1 Figure 3-13. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 

2 1-hour PM light Extinction for 2005-2007 (Los Angeles and Phoenix) 

3 

4 

5 
September 2009 3-40 DRAFT - Do Not Quote or Cite 

1 Figure 3-14. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 

2 1-hour PM light Extinction for 2005-2007 (Salt Lake City and Dallas) 

3 

4 
September 2009 3-41 DRAFT - Do Not Quote or Cite 

1 Figure 3-15. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 

2 1-hour PM light Extinction for 2005-2007 (Houston and St. Louis) 

3 

4 

5 
September 2009 3-42 DRAFT - Do Not Quote or Cite 

1 Figure 3-16. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 

2 1-hour PM light Extinction for 2005-2007 (Birmingham and Atlanta) 

3 

4 
September 2009 3-43 DRAFT - Do Not Quote or Cite 

1 Figure 3-17. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 

2 1-hour PM light Extinction for 2005-2007 (Detroit and Baltimore) 

3 

4 
September 2009 3-44 DRAFT - Do Not Quote or Cite 

1 Figure 3-18. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 

2 1-hour PM light Extinction for 2005-2007 (Pittsburgh and Philadelphia) 

3 

4 
September 2009 3-45 DRAFT - Do Not Quote or Cite 

1 Figure 3-19. Light Extinction Budgets for the Top 10 Percent of Days for Maximum Daily 

2 1-hour PM light Extinction for 2005-2007 (New York) 

3 
September 2009 4-1 DRAFT – Do Note Quote or Cite 

1 4 TOTAL LIGHT EXTINCTION UNDER “WHAT IF” 

2 CONDITIONS OF JUST MEETING SPECIFIC ALTERNATIVE 

3 SECONDARY NAAQS 

4 4.1 ALTERNATIVE SECONDARY NAAQS BASED ON MEASURED TOTAL 

5 LIGHT EXTINCTION AS THE INDICATOR 

6 4.1.1 Indicator and Monitoring Method 

7 As proposed in the Scope and Methods plan, the indicator considered in this section is 

8 total light extinction, assumed to be measured by a continuous instrument, or instrument pair, 

9 capable of reporting both light scattering and light absorption. For example, the measurement 

10 method could be an Aethalometer® or similar instrument for measuring light absorption paired 

11 with a nephelometer, with both instruments using a PM10 inlet so that total light extinction due to 

12 PM2.5 and PM10-2.5 combined (and gases) would be measured. The measurement would include 

13 the effect of Rayleigh scattering by gases, while the alternative NAAQS would be intended to 

14 provide protection from the loss in visual air quality due to PM. Therefore, it would be 

15 necessary to account for the contribution to measured total light extinction from Rayleigh 

scattering either when setting the level of the NAAQS (by adding an increment of about 10 Mm-1 16 

17 to the intended permitted level of light extinction caused by PM) or in the data interpretation rule 

for comparing instrument readings to the NAAQS (by subtracting about 10 Mm-1 18 before 

19 comparison to the level of the NAAQS). 

20 4.1.2 Alternative Secondary NAAQS Scenarios based on Measured Total Light 

21 Extinction 

22 Six alternative NAAQS scenarios presented in Table 4-1 are analyzed in this section, 

23 each based on daily maximum daylight 1-hour total light extinction. The scenarios are ordered 

24 from least to most stringent. 

25 

26 Table 4-1. Alternative Secondary NAAQS Scenarios for Light Extinction 

Level (including Rayleigh 

scattering) 

Annual 

Percentile Form 

201 Mm-1 90 3-year average of percentile value 

201 Mm-1 95 3-year average of percentile value 

122 Mm-1 90 3-year average of percentile value 

122 Mm-1 95 3-year average of percentile value 

74 Mm-1 90 3-year average of percentile value 

74 Mm-1 95 3-year average of percentile value 

27 
September 2009 4-2 DRAFT – Do Note Quote or Cite 

1 It is useful to think ahead to monitor siting aspects of NAAQS implementation, so that 

2 the suitability of the monitoring sites used in this assessment for the purpose of this section can 

3 be considered. 

4 4.1.3 Monitoring Site Considerations for Alternative Secondary NAAQS Based on 

5 Measured Total Light Extinction 

6 It is most likely that instruments that would be used to implement a secondary NAAQS 

7 with a measured light extinction indicator will be “closed path” instruments that react only to air 

8 quality in their immediate vicinity. However, light paths that matter to perceived visual air 

9 quality are likely to be several kilometers long. Therefore, a monitoring site should be at least 

10 neighborhood in scale, i.e., its relationship to emission sources and transport should be such that 

11 measurements made at the site reasonably reflect concentrations in an area surrounding the site 

12 of at least about 0.5 to 4 kilometers in diameter. 

13 It would be logical to require that in any urban area for which light extinction monitoring 

14 is deemed a necessary requirement, at least one monitoring site would be placed in an area 

15 expected to have the maximum total light extinction conditions, subject to the above scale of 

16 representation consideration and possibly also subject to the condition that the site be in an area 

17 (or reasonably represent such an area) where scenic vistas are able to be perceived by people. 

18 i.e., that the site is “population oriented.” Given that site paths of concern will typically be 

19 several kilometers long, it is difficult to imagine a neighborhood scale monitoring location within 

20 the census-defined urbanized area of an urban area which would not be “population oriented” for 

21 purposes of visual air quality, as “neighborhood” size land areas typically would have residents, 

22 workers, etc. somewhere within them during daylight hours. 

23 With regard to the monitoring sites used in this assessment, all are reported to be, or 

24 appear to be, neighborhood or larger scale, and all are in areas where people are present during 

25 daylight hours. The sites in Detroit (Dearborn) and New York-N.New Jersey are, however, rather 

26 close to an industrial source and a major interstate highway interchange/turnpike exit, 

27 respectively. Significantly, most of the study sites are not the highest PM2.5 concentration site 

28 in their urban area, so a “what if” scenario that manipulates the “current conditions” at these sites 

29 to “just meet” an alternative secondary NAAQS might implicitly leave other parts of their urban 

30 areas with total light extinction above the NAAQS. 

31 4.1.4 Approach to Modeling “What If” Conditions for Alternative Secondary 

32 NAAQS based on Measured Total Light Extinction 

33 Before modeling “what if” conditions, EPA staff augmented the data set described in 

34 Table 4 so that the sets of study days for Houston and Phoenix were seasonally balanced despite 

35 the lack of actual monitoring data for one quarter in each city. For the first quarter of 2005 in 
September 2009 4-3 DRAFT – Do Note Quote or Cite 

1 Phoenix, we substituted the available 12 days from the first quarter of 2006. For the fourth 

2 quarter of 2007 in Houston, we substituted 13 randomly drawn days from the fourth quarters of 

3 2005 and 2006. 

4 Also, Tacoma (originally) and Phoenix (after this augmentation) each have only two 

5 calendar years of suitable data, while the form of the alternative NAAQS scenarios requires the 

6 averaging of the 90th or 95th percentile values from three years. In Tacoma and Phoenix, for 

7 every step in the analysis at which a design value is used as an input or reported as an output, we 

8 averaged the percentile values from the only two available years. 

9 We modeled daily maximum daylight 1-hour total light extinction under each of the 

10 “what if” scenarios (in which each study area “just meets” one of the alternative secondary 

11 NAAQS listed in section 4.1.2) via the following steps. These steps are essentially the same as 

12 the “proportional rollback” steps that have been used in the health risk assessment modeling of 

13 “what if” conditions in several previous NAAQS reviews for PM and other criteria pollutants. 

14 

1. Identify the appropriate percentile (90th or 95th 15 ) daily light extinction value in each 

16 year, noting the day and hour each occurred, and average these values across years to 

17 calculate the light extinction design value for each site consistent with the percentile 

18 form of the NAAQS scenario. The two resulting design values for each area (for the 

90th and 95th 19 percentile forms) are shown in Table 4-2. (Note that in a few cases, 

20 which are identified by a footnote, the study area meets one or more of the NAAQS 

21 scenario under current conditions. In these cases, the “current conditions” total light 

22 extinction values are not adjusted, i.e., total light extinction values are never “rolled 

23 up.”) 

24 

25 2. Using the same days and hours, find the three (or two, in the case of Phoenix and 

26 Houston for which there were only two years of suitable data available) 

27 corresponding values of PRB total light extinction, and average these values across 

28 years to calculate the PRB portion of the design value. 

 29 

30 3. Subtract the value from step 2 from the value from step 1, to determine the non-PRB 

31 portion of the design value. 

 32 

33 4. Calculate the percentage reduction required in non-PRB total light extinction in order 

34 to reduce the design value to the total light extinction level that defines the NAAQS 

35 scenario, using the following equation: 

36 

37 Percent reduction required = 1 – (NAAQS level – PRB portion of the design value)/(non-PRB 

38 portion of the design value) 

39 

40 The percentage reductions determined in this step are shown in Table 4-3. 

1. 41 
September 2009 4-4 DRAFT – Do Note Quote or Cite 

1 5. Turning to the entire set of day/hour-specific actual and PRB daylight total light 

2 extinction values for the three (or two) year period, determine the non-PRB portion of 

3 total light extinction, reduce it by the percentage determined in step 4, and add back 

4 in the PRB total light extinction. The result is the “just meets” total light extinction 

5 value for that day and hour. 

6 

7 Note that in these steps, it is not necessary to make any explicit or implicit assumption 

8 about what PM components would be reduced to allow the area to meet the NAAQS scenario, as 

9 the NAAQS scenario’s target design value is itself in units of light extinction. 

10 

11 Table 4-2. Current Conditions total light extinction design values for the study areas. 

Study Area 

Design Value for 90th

Percentile Form (Mm-1) 

Design Value for 95th

Percentile Form (Mm-1) 

Tacoma 228 278 

Fresno 308 403 

Los Angeles-South Coast Air 

Basin 323 436 

Phoenix 117* 154* 

Salt Lake City 184 256 

Dallas 213* 262 

Houston 235 275 

St. Louis 420 512 

Birmingham 436 565 

Atlanta 269 291 

Detroit-Ann Arbor 444 636 

Pittsburgh 425 481 

Baltimore 441 484 

Philadelphia-Wilmington 409 436 

New York-N.New JerseyLong Island 449 538 

* This design value meets one or more of the NAAQS scenarios.

12 
September 2009 4-5 DRAFT – Do Note Quote or Cite 

1 Table 4-3. Percentage reductions in non-PRB light extinction required to “just meet” the 

2 NAAQS scenarios based on measured light extinction. 

NAAQS Scenarios Based on Maximum Daily 1-hour Daylight Total 

Light Extinction, Average of Percentile Value Over Three Years 

Total Light Extinction 

Level (Mm-1) 201 201 122 122 74 74 

Percentile Form 90th 95th 90th 95th 90th 95th

Area 

Percentage Reduction Required in 

Non-PRB Total Light Extinction 

Tacoma 13 29 51 59 74 77 

Fresno 38 53 65 73 82 86 

Los Angeles 40 56 66 75 82 87 

Phoenix 0 0 0 23 43 59 

Salt Lake City 0 23 36 56 65 76 

Dallas 7 26 49 59 75 79 

Houston 16 29 53 60 76 79 

St. Louis 55 64 75 80 87 90 

Birmingham 56 67 75 82 87 90 

Atlanta 28 33 60 63 79 80 

Detroit 58 71 77 84 88 91 

Pittsburgh 55 61 75 78 87 88 

Baltimore 58 61 76 79 88 89 

Philadelphia 54 57 74 76 86 88 

New York 59 65 77 80 88 90 

3 4.2 ALTERNATIVE SECONDARY PM2.5 NAAQS BASED ON ANNUAL AND 

4 24-HOUR PM2.5 MASS 

5 4.2.1 Secondary NAAQS Scenarios Based on Annual and 24-hour PM2.5 Mass 

6 In this draft version of the assessment, EPA staff have modeled two “what if” scenarios 

7 based on the same indicators and averaging periods as define the current secondary PM2.5 

8 NAAQS: 

 15 μg/m3

 weighted annual average PM2.5 concentration and 35 μg/m3 9 24-hour average 

PM2.5 concentration with a 98th 10 percentile form, both averaged over three years. These are 

11 the current secondary NAAQS for PM2.5.

 12 μg/m3

 weighted annual average PM2.5 concentration and 25 μg/m3 12 24-hour average 

PM2.5 concentration with a 98th 13 percentile form, both averaged over three years. 

14 These are the highest and lowest alternative NAAQS scenarios considered in the health 

15 risk assessment, and therefore encompass the full range of alternative primary PM2.5 NAAQS 

16 being analyzed by EPA staff. 
September 2009 4-6 DRAFT – Do Note Quote or Cite 

1 4.2.2 Approach to Modeling Conditions If Secondary PM2.5 NAAQS Based on 

2 Annual and 24-hour PM2.5 Mass Were Just Met 

3 Because these NAAQS scenarios are based on PM2.5 mass as the indicator, rather than 

4 light extinction, the steps needed to model “what if” conditions are somewhat different, and 

5 involve explicit consideration of changes in PM2.5 components. 

6 

7 1. Apply proportional rollback to all the PM2.5 monitoring sites in each study area, 

8 taking into account PRB PM2.5 mass, to “just meet” the NAAQS scenario for the area 

9 as a whole, not just at the visibility assessment study site. The health risk assessment 

10 document describes this procedure in detail. The degree of rollback is controlled by 

11 the highest annual or 24-hour design value, which in most study areas is from a site 

12 other than the site used in this visibility assessment. The relevant result from this 

13 analysis is the percentage reduction in non-PRB PM2.5 mass need to “just meet” the 

14 NAAQS scenario, for each study area. These percentage reductions are shown in 

15 Table 4-4. Note that Phoenix and Salt Lake City meet the 15/35 NAAQS scenario 

16 under current conditions, and require no reduction. PM2.5 levels in these two cities 

17 were not “rolled up.” 

 18 

19 2. For each day and hour for each PM2.5 component, subtract the PRB concentration 

20 from the current conditions concentration, to determine the non-PRB portion of the 

21 current conditions concentration. 

 22 

23 3. Apply the percentage reduction from step 1 to the non-PRB portion of each of the 

24 five PM2.5 components. Add back the PRB portion of the component. 

 25 

26 4. Re-apply the IMPROVE algorithm, using the reduced PM2.5 component 

27 concentrations, the current conditions PM10-2.5 concentration for the day and hour, and 

28 relative humidity for the day and hour. Include the term for Rayleigh scattering. 
September 2009 4-7 DRAFT – Do Note Quote or Cite 

1 Table 4-4. Percentage reductions required in non-PRB PM2.5 mass to “just meet” NAAQS 

2 scenarios based on annual and 24-hour PM2.5 mass 

Percentage Reduction Required 

Study Area Annual PM2.5 NAAQS = 15 μg/m3

24-hour PM2.5 NAAQS = 35 μg/m3

Annual PM2.5 NAAQS = 12 μg/m3

24-hour PM2.5 NAAQS = 25 μg/m3

Tacoma 19 43 

Fresno 45 61 

Los AngelesSouth Coast 

Air Basin 

37 55 

Phoenix 0* 22 

Salt Lake City 37 56 

Dallas 0* 7 

Houston 6 27 

St. Louis 10 37 

Birmingham 22 45 

Atlanta 8 30 

Detroit-Ann 

Arbor 

19 43 

Pittsburgh Being recalculated Being recalculated 

Baltimore 6 33 

PhiladelphiaWilmington 

8 35 

New YorkN.New JerseyLong Island 

17 41 

* These areas meet this NAAQS scenario under current conditions.

3 4.3 RESULTS FOR “JUST MEETING” ALL ALTERNATIVE SECONDARY 

4 NAAQS SCENARIOS 

5 The modeling described in sections 4.1 and 4.2 resulted in estimates of total light 

6 extinction for each day and hour in each study area. Four summaries of these conditions are 

7 presented here. 

8 Figure 4-1 shows two box-and-whisker plots of daily maximum daylight 1-hour total 

9 light extinction. The top panel (a) is for the single illustrative scenario of a NAAQS based on 

measured light extinction with a level of 122 Mm-1 and a 90th 10 percentile form, which was chosen 

11 for this illustration because it is approximately mid-way among the six such scenarios in terms of 

12 stringency. Plots for all six scenarios of NAAQS based on measured total light extinction are 

13 provided in Appendix F. The bottom panel (b) is for the scenario of meeting the current 

secondary PM2.5 NAAQS of 15 μg/m3

 for the annual average and 35 μg/m3 for the 98th 14 percentile 

15 24-hour average. A notable feature of this comparison is that in the top panel, all the study areas 
September 2009 4-8 DRAFT – Do Note Quote or Cite 

1 have a similar distribution of the daily maximum daylight 1-hour total light extinction, while in 

2 the bottom panel this is not the case. This is expected, since a NAAQS based on a measured 

3 total light extinction indicator will of course result in areas achieving similar total light extinction 

4 patterns once each area reaches a “just meets” condition; in areas with generally higher relative 

5 humidity conditions, concentrations of PM2.5 components and/or PM10-2.5 would need to be lower 

6 to achieve the “just meet” condition. In contrast, in the NAAQS scenario represented by the 

7 bottom panel, concentrations of PM2.5 mass will be similar across areas, but concentrations of 

8 PM2.5 components may not be, and levels of total light extinction will not be similar in areas with 

9 dissimilar levels of relative humidity. The specific differences among areas in the bottom panel 

10 are generally as expected, with the drier study areas having lower levels of total light extinction. 

11 Tables 4-5 and 4-6 summarize the “just meets” conditions in the eight NAAQS scenarios 

12 in terms of the total light extinction design value. Table 4-5 addresses the six scenarios of 

13 NAAQS based on measured total light extinction, and the form of the design value given in the 

14 Table corresponds to the assumed percentile form of the NAAQS. Table 4-6 addresses the two 

15 scenarios of NAAQS based on PM2.5 mass, and total light extinction design values in both 

16 percentile forms are shown. Note that the design values in Table 4-5 resulting from the rollback 

17 steps described in section 4.1.4, in some cases do not exactly equal the assumed level of the 

18 NAAQS, although all are quite close. This is a result of hours switching their ranking in the 

19 rollback process. This can happen because the level of PRB total light extinction varies with 

20 each hour, so a uniform percentage reduction in non-PRB light extinction (step 5) can result in 

21 non-uniform percentage reductions in actual total light extinction. In principle, rollback could be 

22 iterated to exactly achieve a design value equal to the level of the NAAQS for each scenario. 

23 However, the discrepancies indicated in Table 4-5 were judged too small to justify iterative 

24 rollback, given other uncertainties in the analysis. 

25 Finally, Table 4-7 summarizes all eight scenarios in terms of the percentage of days 

26 (across 2005 to 2007, but after rollback) in which the daily maximum daylight 1-hour total light 

27 extinction under “just meeting” conditions exceeds each of the CPLs. Also shown at the bottom 

28 of the table in each column representing a NAAQS scenario is the average of these percentages 

29 across the 15 study areas. Comparisons of these percentages allows a rough indication of how the 

30 two scenarios of a NAAQS based on PM2.5 mass compare to the other six scenario in terms of 

31 protecting visual air quality. Notice that even the most restrictive of the two NAAQS scenarios 

32 based on PM2.5 mass would permit projected 1-hour maximum daily light extinction above the 

least restrictive CPL (201Mm-1 33 ) more that 10% of the time for most of the Eastern urban areas 

34 (Dallas, Houston and Atlanta have values near 10%), while the percent of maximum hourly days 

35 for the Western urban areas are all less than 10%. 

36 
September 2009 4-9 DRAFT – Do Note Quote or Cite 

Figure 4-1. Distributions of daily maximum daylight 1-hour total light extinction under 

two “just meeting” secondary NAAQS scenarios 

(a) Secondary NAAQS based on measured total light extinction with a level of 122 Mm1

 and a 90th percentile form 

(b) Secondary NAAQS of 15 μg/m3

 for the annual average and 35 μg/m3 for the 98th

percentile 24-hour average 
September 2009 4-10 DRAFT – Do Note Quote or Cite 

Table 4-5. Total light extinction design values for “just meeting” secondary NAAQS 

scenarios based on measured total light extinction 

Secondary NAAQS Scenario

Level (Mm-1) 74 74 122 122 201 201 

Percentile Form 90th 95th 90th 95th 90th 95th

Total Light Extinction Design Value 

(based on same percentile form as the NAAQS scenario)

Tacoma, WA 74 90 122 126 201 201 

Fresno, CA 72 74 121 122 201 201 

Los Angeles, CA 74 74 122 122 201 201 

Phoenix, AZ 74 74 122 122 201 201 

Salt Lake City, UT 75 73 122 122 201 201 

Dallas, TX 71 73 120 122 201 201 

Houston, TX 78 80 124 124 201 201 

St. Louis, IL 75 74 123 122 202 201 

Birmingham, AL 77 76 123 122 201 201 

Atlanta, GA 73 80 121 127 200 203 

Detroit, MI 71 75 121 122 201 201 

Pittsburgh, PA 74 76 122 124 200 203 

Baltimore, MD 73 75 122 122 202 201 

Philadelphia, PA 74 76 122 122 201 201 

New York, NY 72 77 121 124 201 202 

Table 4-6. Total light extinction design values for “just meeting” secondary NAAQS 

scenarios based on PM2.5 mass 

Annual/1-hour PM2.5 

NAAQS 15μg/m3 / 35μg/m3 12μg/m3 / 25μg/m3

City Name 

90th %tile 

Design Value 

(Mm-1) 

95th %tile 

Design Value 

(Mm-1) 

90th %tile Design 

Value (Mm-1) 

95th %tile Design 

Value (Mm-1) 

Tacoma, WA 188 228 139 165 

Fresno, CA 183 238 139 179 

Los Angeles, CA 221 311 175 261 

Phoenix, AZ 117* 154* 107 145 

Salt Lake City, UT 126 174 98 133 

Dallas, TX 213* 262* 200 245 

Houston, TX 224 261 182 211 

St. Louis, IL 384 477 311 383 

Birmingham, AL 355 476 268 369 

Atlanta, GA 249 271 197 218 

Detroit, MI 364 520 264 376 

Pittsburgh, PA Recalculating Recalculating Recalculating Recalculating 

Baltimore, MD 419 459 308 335 

Philadelphia, PA 377 403 273 296 

New York, NY 377 450 274 325 

* Phoenix and Dallas meet 15 μg/m3/35 μg/m3 under current conditions, so these entries are the same as for current 

conditions. 
September 2009 4-11 DRAFT – Do Note Quote or Cite 

Table 4-7. Percentage of days across three years (two in the case of Phoenix and Houston) with maximu

total light extinction above CPLs when “just meeting” the NAAQS scenarios 

Days above 74 Mm-1 (Percent) Days above 122 Mm-1 (Percent) Days above 201 

Mm-1 

Level 201 201 122 122 74 74 201 201 122 122 74 74 201 201 122 122 7

Percentile 

Form 90 95 90 95 90 95 90 95 90 95 90 95 90 95 90 95 9

Annual/24-

hour 

15/ 

35 

12/

25 15/35 

12/

25 

Area Percentage of days Percentage of days Percenta

Tacoma 56 46 26 23 11 9 55 39 25 18 8 6 2 1 23 11 8 6 2 0 

Fresno 54 42 29 21 9 3 48 33 27 19 10 4 1 1 23 14 10 4 1 1 

Los Angeles 81 74 53 24 8 5 82 76 49 20 8 5 2 1 59 28 8 5 3 1 

Phoenix 88 66 50 30 9 5 46 42 46 27 9 5 2 1 7 6 9 5 3 2 

Salt Lake City 54 32 25 14 11 4 26 19 24 13 10 4 3 2 11 6 10 4 3 2 

Dallas 77 66 43 30 9 4 80 77 42 26 11 4 2 1 46 42 11 5 2 1 

Houston 75 68 45 32 14 9 81 69 40 30 11 7 1 1 48 31 11 6 1 1 

St. Louis 75 62 40 28 10 6 98 94 36 25 10 6 2 1 79 66 10 6 2 1 

Birmingham 67 56 42 26 13 6 90 82 36 22 11 5 2 1 66 52 11 5 2 1 

Atlanta 86 84 57 50 9 7 91 85 50 42 10 7 0 0 68 49 10 5 0 0 

Detroit 66 50 40 18 11 5 82 79 36 16 11 5 1 0 70 59 11 5 1 0 

Pittsburgh 55 52 30 25 10 6 * * 27 22 10 6 0 0 * * 10 5 0 0 

Baltimore 55 50 25 22 10 8 82 71 23 22 10 6 0 0 60 46 9 6 0 0 

Philadelphia 67 65 33 28 8 6 90 81 29 26 8 6 0 0 70 54 8 6 0 0 

New York 57 50 27 23 10 6 80 70 26 21 11 6 1 1 60 45 12 5 2 1 

Average 68 58 38 26 10 6 73 65 34 23 10 5 1 1 49 36 10 5 2 1 

* EPA is currently recalucating these values.
September 2009 5-1 DRAFT – Do Note Quote or Cite 

5 REFERENCES 

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Report. Prepared for EPA Office of Air Quality Planning and Standards; funded under EPA Contract No. 

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http://www.epa.gov/ttncaaa1/t1/reports/vis_rpt_final.pdf. Accessed 9/16/2008. 

Air Resource Specialists. 2003. 2003 WinHaze Air Quality Modeler, Version 2.9. Air Resource Specialists, Inc. 

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Arizona Department of Environmental Quality. 2003. Recommendation for a Phoenix Area Visibility Index. 

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Available: http://www.azdeq.gov/environ/air/download/vis_021903f.pdf. Accessed 9/16/2008. 

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http://www.azdeq.gov/environ/air/download/vis_021903f.pdf. Accessed 9/16/2008. 

DeBell L. (2006). Spatial and seasonal patterns and temporal variaibility of haze and its constituents in the United States: Report 

IV. 1Cooperative Institute for Research in the Atmosphere. Colorado State University Fort Collins, CO. 156388

Ely, D.W., J.T. Leary, T.R. Stewart, and D.M. Ross. 1991. The Establishment of the Denver Visibility Standard. 

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16-21. 

Frank NH. (2006). Retained nitrate, hydrated sulfates, and carbonaceous mass in federal reference method fine 

particulate matter for six eastern U.S. cities. J Air Waste Manag Assoc, 56: 500-11 

Henderson, R. (2006) Letter from Dr. Rogene Henderson, Chair, Clean Air Scientific Advisory Committee to the 

Honorable Stephen L. Johnson, Administrator, US EPA. Clean Air Scientific Advisory Committee 

Recommendations Concerning the Proposed National Ambient Air Quality Standards for Particulate 

Matter. March 21, 2006. Available: http://www.epa.gov/sab/pdf/casac-ltr-06-002.pdf

Henderson, R. (2008) Letter from Dr. Rogene Henderson, Chair, Clean Air Scientific Advisory Committee to the 

Honorable Stephen L. Johnson, Administrator, US EPA. Clean Air Scientific Advisory Committee 

Consultation on EPA’s Draft Integrated Review Plan for the National Ambient Air Quality Standards for 

Particulate Matter January 3, 2008. 

Jacques Whitford AXYS. 2007. The View Ahead; Identifying Options for a Visibility Management Framework for 

British Columbia. Report for the British Columbia Ministry of Environment. Available: 

http://www.env.gov.bc.ca/air/airquality/pdfs/view_ahead.pdf. Accessed 8/5/2009. 

Molenar, J.V., W.C. Malm, and C.E. Johnson. 1994. Visual air quality simulation techniques. Atmospheric 

Environment 28(5):1055-1063. 

NARSTO (2004) Particulate Matter Science for Policy Makers: A NARSTO Assessment. P. McMurry, M. 

Shepherd, and J. Vickery, eds. Cambridge University Press, Cambridge, England. ISBN 0 52 184287 5 

Pitchford, M. and W. Malm. 1993. Development and applications of a standard visual index. Atmospheric 

Environment 28(5):1049-1054. 

Pryor, S.C. 1996. Assessing public perception of visibility for standard setting exercises. Atmospheric Environment

30(15):2705-2716. 
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RWDI AIR. 2008. Final Report: Establishing a Visibility Goal for Wilderness and Urban areas in British Columbia 

and Canada. Report to the British Columbia Ministry of Environment. Available: 

http://www.env.gov.bc.ca/air/airquality/pdfs/visibility_goal_report_final.pdf. Accessed 8/5/2009. 

Samet, J. (2009) Letter from Dr. Jonathan M. Samet, Chair, Clean Air Scientific Advisory Committee (CASAC) to 

The Honorable Lisa P. Jackson, Administrator, U.S. EPA. Consultation on EPA’s Particulate Matter 

National Ambient Air Quality Standards: Scope and Methods Plan for Urban Visibility Impact Assessment. 

May 21, 2009. Available: http://yosemite.epa.gov/sab/sabpeople.nsf/WebCommittees/CASAC. 

Schmidt. M; Frank, N.; Mintz, D.; Rao, T.; McCluney, L. (2005). Analyses of particulate matter (PM) data for the 

PM NAAQS review. Memorandum to PM NAAQS review docket EPA-HQ-OAR-2001-0017. June 30, 

2005. Available: http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_cr_td.html 

Smith, A. 2009. Comments on the First External Review Draft of EPA’s “Integrated Science Assessment for 

Particulate Matter.” CRA International, Washington, DC. March 30. Prepared for the Utility Air 

Regulatory Group. Submitted as public comment to the public meeting EPA Clean Air Science Advisory 

Council. April 2. 

Smith, A.E. and S. Howell. 2009. An Assessment of the Robustness of Visual Air Quality Preference Study Results. 

CRA International, Washington, DC. March 30. Prepared for the Utility Air Regulatory Group. Submitted 

as supplemental material to presentation by Anne Smith to the public meeting of the EPA Clean Air 

Science Advisory Council. April 2. 

Statistics Canada. 2009a. Population and Dwelling Count Highlight Tables, 2006 Census. Available: 

http://www12.statcan.gc.ca/census-recensement/2006/dp-pd/hlt/97-550/Index.cfm?Page = INDX&LANG 

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of Scientific and Technical Information, OAQPS Staff Paper. Research Triangle Park, NC 27711: Office 

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Agency, Research Triangle Park, NC. EPA-452/P-09-001. February 2009. Available: 

http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_2007_pd.html. 
APPENDICES 

A. PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis of 

Total Light Extinction in the 15 Study Areas 

B. Distributions of Estimated PM2.5 Components under Current Conditions 

C. Development of PRB Estimates of PM2.5 components, PM10-2.5, and Total Light 

Extinction 

D. Relationships between PM Mass Concentration and PM Light Extinction under Current 

Conditions 

E. Differences in Daily Patterns of Relative Humidity and Light Extinction between Areas 

and Seasons 

F. Distributions of Maximum Daily Daylight Total Light Extinction under “Just Meets” 

Conditions 
September 2009 

DRAFT Do Not Quote or Cite 

A-1

APPENDIX A - PM2.5 MONITORING SITES AND MONITORS 

PROVIDING 2005-2007 DATA FOR THE ANALYSIS OF TOTAL 

LIGHT EXTINCTION IN THE 15 STUDY AREAS 
September 2009 

DRAFT Do Not Quote or Cite 

A-2

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

Tacoma AQS ID 530530029

State: Washington City: Tacoma MSA: Tacoma, WA Local Site Name: TACOMA - L STREET Address: 7802 SOUTH L STREET, TACOMA 0.5 miles east of I-5 2005-2007 annual DV = 10.2 2005-2007 24-hr DV = 43 This is the highest 24-hour PM2.5 DV site in 

the Seattle-Tacoma-Olympia, WA annual PM2.5 nonattainment area Neighborhood Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; one-in-three sampling schedule)  PM2.5 speciation (one-in-six sampling schedule)  1-hour PM2.5 mass (AQS parameter 88502, Acceptable PM2.5 AQI & Speciation Mass) Correlated Radiance Research M903 Nephelometry No continuous PM10 monitoring at this site, see right hand column..

NA AQS ID 530530031

State: Washington City: Tacoma MSA: Tacoma, WA Local Site Name: TACOMA - ALAddress: 2301 ALEXANDER AV6.4 miles NNE of PM2.5 site Neighborhood Scale Parameters taken from this site:  1-hour PM10 STP maso Sample CollINSTRUMENTAL-R&P SA246B-o Sample Ana

GRAVIMETRIC 

7% of PM10-2.5 values were regional average PM10-2.5:PStaff Paper 
September 2009 

DRAFT Do Not Quote or Cite 

A-3

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

Fresno AQS ID 060190008

State: California City: Fresno MSA: Fresno, CA Local Site Name: None given Address: 3425 N FIRST ST, FRESNO 2.5 miles west of the airport, 3 miles NNE of central Fresno 2005-2007 annual DV = 17.4 2005-2007 24-hr DV = 63 This is not the highest annual or 24-hr PM2.5 DV site in the San Joaquin nonattainment area. Neighborhood Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; every day sampling schedule)  PM2.5 speciation (one-in-three sampling schedule)  1-hour PM2.5 mass (AQS parameter 88501, PM2.5 Raw Data) MetOne BAM No continuous PM10 monitoring at this site, see right hand column..

NA PM10-2.5 values were determ

average PM10-2.5:PM2.5 ra
September 2009 

DRAFT Do Not Quote or Cite 

A-4

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

Los AngelesSouth Coast Air Basin 

AQS ID 060658001State: California City: Rubidoux (West Riverside) MSA: Riverside-San Bernardino, CA Local Site Name: None given Address: 5888 MISSION BLVD., RUBIDOUX Eastern SCAB, 0.4 miles from Pomona Freeway. 2005-2007 annual DV = 19.6 2005-2007 24-hr DV = 55 This site is not the highest DV site in the LA-South Coast nonattainment area. Neighborhood scale. Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; every day sampling schedule)  PM2.5 speciation (one-in-three sampling schedule)  1-hour PM2.5 (AQS parameter 88502, Acceptable PM2.5 AQI & Speciation Mass) [still investigating instrument type]No continuous PM10 monitoring at this site, see right hand column..

NA AQS ID 060710306

State: California City: Victorville MSA: Riverside-San Bernardino, Local Site Name: MOVED FROM Address: 14306 PARK AVE., VIC36 miles north of PM2.5 site, on hills. 0.4 miles from I-15 Measurement Scale not given in Neighborhood by aerial image. Parameters taken from this site:  1-hour PM10 STP maso Sample CollINSTRUMENTAL-R&P SA246B-o Sample Ana

GRAVIMETRIC

6% of PM10-2.5 values were regional average PM10-2.5:PStaff Paper 
September 2009 

DRAFT Do Not Quote or Cite 

A-5

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

Phoenix AQS ID 040137020 (FRM & CSN) 

State: Arizona City: Scottsdale MSA: Phoenix-Mesa, AZ Local Site Name: Address: 10844 EAST OSBORN ROAD SCOTTSDALE' AZ Reporting Agency: Salt River PimaMaricopa Indian Community of Salt River Reservation Eastern edge of the metro area, largely surrounded by agricultural fields. 2005-2007 annual DV = 7.9 2005-2007 24-hr DV = 15 This site is not the highest DV site in the Phoenix-Mesa CBSA. Neighborhood Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; one-in-six sampling schedule)  PM2.5 speciation (one-in-three sampling schedule) No continuous PM10 monitoring at this site, see right hand column. 

AQS ID 040139998 (Continuous) 

State: Arizona City: Phoenix MSA: Phoenix-Mesa, AZ Local Site Name: Vehicle Emissions Laboratory Address: 600 N 40th St & Fillmore St 

Measurement Scale not available; 0.75 miles from intersection of two freeways, 1 mile from Phoenix airport. Parameters taken from this site:  1-hour PM2.5 mass. Nephelometer. 

AQS ID 040133002

State: Arizona City: Phoenix MSA: Phoenix-Mesa, AZ Local Site Name: CENTRAL PHAddress: 1645 E ROOSEVELT S1.8 miles NE of central Phoenix Neighborhood Scale Parameters taken from this site:  1-hour PM10 STP maso Sample CollINSTRUMENTAL-R&P SA246B-o Sample Ana

GRAVIMETRIC 

2% of PM10-2.5 values were PM10-2.5:PM2.5 ratios from 
September 2009 

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A-6

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

Salt Lake City AQS ID490353006 State: Utah 

City: Salt Lake City MSA: Salt Lake City-Ogden, UT Local Site Name: UTM COORDINATES = PROBE LOCATION Address: 1675 SOUTH 600 EAST, SALT LAKE CITY 2.5 miles SSE of central Salt Lake City 2005-2007 annual DV = 10.7 2005-2007 24-hr DV = 48 This is not the highest DV site in the Salt Lake City CSA. Neighborhood Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; every day sampling schedule)  PM2.5 speciation (one-in-three sampling schedule)  1-hour PM2.5 mass (AQS parameter 88501, PM2.5 Raw Data) FDMS-Gravimetric No continuous PM10 monitoring at this site, see right hand column.

NA PM10-2.5 values were deter

average PM10-2.5:PM2.5 ra
September 2009 

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A-7

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

Dallas AQS ID 481130069

State: Texas City: Dallas MSA: Dallas, TX Local Site Name: DALLAS HINTON Address: 1415 HINTON STREET 4.5 miles NE of central Dallas 2005-2007 annual DV = 11.5 2005-2007 24-hr DV = 25 This is not the highest DV site in the Dallas-Ft. Worth CSA. Neighborhood Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; every day sampling schedule)  PM2.5 speciation (one-in-three sampling schedule)  1-hour PM2.5 mass (AQS parameter 88502, Acceptable PM2.5 AQI & Speciation Mass) TEOM Gravimetric 50 deg C No continuous PM10 monitoring at this site, see right hand column..

NA PM10-2.5 values were deter

average PM10-2.5:PM2.5 ra
September 2009 

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A-8

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

Houston AQS ID 482010024

State: Texas City: Not in a city MSA: Houston, TX Local Site Name: HOUSTON ALDINE Address: 4510 1/2 ALDINE MAIL RD 10 miles NNE of central Houston 2005-2007 annual DV = 13.1 2005-2007 24-hr DV = 25 This is not the highest DV site in the 'Houston-Baytown-Huntsville, TX CSA. Neighborhood Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; one-in-six day sampling schedule)  PM2.5 speciation (one-in-six sampling schedule)  1-hour PM2.5 mass (AQS parameter 88502, Acceptable PM2.5 AQI & Speciation Mass) TEOM Gravimetric 50 deg C No continuous PM10 monitoring at this site, see right hand column.

NA PM10-2.5 values were deter

average PM10-2.5:PM2.5 ra
September 2009 

DRAFT Do Not Quote or Cite 

A-9

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

St. Louis AQS ID 295100085

State: Missouri City: St. Louis MSA: St, Louis, MO-IL Local Site Name: BLAIR STREET CATEGORY A CORE SLAM PM2.5. Address: BLAIR S 2 miles north of central St. Louis 2005-2007 annual DV = 14.5 2005-2007 24-hr DV = 34 This is not the highest DV site in the St. Louis nonattainment area. Neighborhood Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; every day sampling schedule)  PM2.5 speciation (one-in-three sampling schedule)  1-hour PM2.5 mass (AQS parameter 88502, Acceptable PM2.5 AQI & Speciation Mass) TEOM Gravimetric 30 deg C No continuous PM10 monitoring at this site, see right hand column.

NA AQS ID 295100092 (2005 

State: Missouri City: St. Louis MSA: St, Louis, MO-IL Local Site Name: Address: 3 NORTH MARKET 0.7 miles ESE of PM2.5 site, acreastern edge of what appears to works yard. Middle Scale Parameters taken from this site:  1-hour PM10 STP maso Sample CollINSTRUMENTAL-R&P SA246B-o Sample AnaGRAVIMETRIC Site was on the recycling/municipal works yard a295100093 (2007 data) State: Missouri City: St. Louis MSA: St, Louis, MO-IL Local Site Name: None given Address: Branch Street 0.6 miles ESE of PM2.5 site, acrwestern edge of what appears to works yard. Middle Scale Parameters taken from this site:  1-hour PM10 STP maso Sample CollINSTRUMENTAL-R&P SA246B-o Sample Ana

GRAVIMETRIC

4% of PM10-2.5 values were regional average PM10-2.5:PStaff Paper
September 2009 

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A-10

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

Birmingham AQS ID 010730023 State: Alabama 

City: Birmingham MSA: Birmingham, AL Local Site Name: Address: NO. B'HAM,SOU R.R., 3009 28TH ST. NO 2.3 miles north of central Birmingham 2005-2007 annual DV = 18.7 2005-2007 24-hr DV = 44 This is the highest DV site in the Birmingham nonattainment area Neighborhood Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; every day sampling schedule)  PM2.5 speciation (one-in-three sampling schedule)  1-hour PM2.5 mass (AQS parameter 88502, Acceptable PM2.5 AQI & Speciation Mass) TEOM Gravimetric 50 deg C  1-hour PM10 STP mass (AQS parameter 81102) o Sample Collection Method: INSTRUMENTAL-R&P SA246BINLET o Sample Analysis 

Method: TEOM-GRAVIMETRIC

NA Same as PM2.5 site. 

0.3% of PM10-2.5 values weregional average PM10-2.5:PStaff Paper 
September 2009 

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A-11

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

Atlanta AQS ID 130890002

State: Georgia City: Decatur MSA: Atlanta, GA Local Site Name: 2390-B WILDCAT ROAD, DECATUR, GA Address: SOUTH DEKALB About 7 miles SE of central Atlanta 2005-2007 annual DV = 15.7 2005-2007 24-hr DV = 33 This is not the highest DV site in the Atlanta nonattainment area. Neighborhood Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; every day sampling schedule)  PM2.5 speciation (one-in-three sampling schedule)  1-hour PM2.5 mass (AQS parameter 88502, Acceptable PM2.5 AQI & Speciation Mass) TEOM Gravimetric 30 deg C No continuous PM10 monitoring at this site, see right hand column.

NA AQS ID 131210048

State: Georgia City: Atlanta MSA: Atlanta, GA Local Site Name: Georgia Tech, and Technology Bldg, roof Address: GA. TECH., Ford ES&T Atlanta GA 8.6 miles NW of PM2.5 site Neighborhood Scale Parameters taken from this site:  1-hour PM10 STP mao Sample CollINSTRUMENT MET ONE 4 MODo Sample Ana

ATTENUATION 

8% of PM10-2.5 values were regional average PM10-2.5:PStaff Paper 
September 2009 

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A-12

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

Detroit-Ann Arbor 

AQS ID 261630033State: Michigan City: Dearborn MSA: Detroit, MI Local Site Name: PROPERTY OWNED BY DEARBORN PUBLIC SCHOOLS Address: 2842 WYOMING About 0.2 miles from Ford River Rouge auto plant 2005-2007 annual DV = 17.2 2005-2007 24-hr DV = 43 This is the highest annual and 24-hr DV site in the Detroit nonattainment area Neighborhood Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; every day sampling schedule)  PM2.5 speciation (one-in-six sampling schedule)  1-hour PM2.5 mass (AQS parameter 88501, PM2.5 Raw Data)TEOM Gravimetric 50 deg C  1-hour PM10 STP mass (AQS parameter 81102)o Sample Collection 

Method: INSTRUMENTAL-R&P SA246BINLET 

o Sample Analysis 

Method: TEOM-GRAVIMETRIC

NA Same as PM2.5 site. 

2% of PM10-2.5 values were regional average PM10-2.5:PStaff Paper 
September 2009 

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A-13

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

Pittsburgh AQS ID 420030008 State: Pennsylvania 

City: Pittsburgh MSA: Pittsburgh, PA Local Site Name: None given Address: BAPC 301 39TH STREET BLDG #7 3 miles NE of central Pittsburgh, 0.5 miles from Allegheny River 2005-2007 annual DV = 15.0 2005-2007 24-hr DV = 40 This site is not the highest DV site in the Pittsburgh nonattainment area. Urban Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; every day sampling schedule)  PM2.5 speciation (one-in-three sampling schedule)  1-hour PM2.5 mass (AQS parameter 88502, Acceptable PM2.5 AQI & Speciation Mass) TEOM Gravimetric 50 deg C No continuous PM10 monitoring at this site, see right hand column.

NA PM10-2.5 values were deter

average PM10-2.5:PM2.5 ra
September 2009 

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A-14

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

Baltimore AQS ID 240053001 (FRM & CSN) 

State: Maryland City: Essex MSA: Baltimore, MD Local Site Name: Essex Address: 600 Dorsey Avenue 7 miles east of central Baltimore 2005-2007 annual DV = 14.5 2005-2007 24-hr DV = 35 This is not the highest DV site in the Baltimore nonattainment area. Neighborhood Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; every day sampling schedule)  PM2.5 speciation (one-in-three sampling schedule)  1-hour PM10 LC mass (AQS parameter 85101 

AQS ID 245100040 (Continuous) 

State: Maryland City: Baltimore MSA: Baltimore, MD Local Site Name: Oldtown Address: Oldtown Fire Station, 1100 Hillen Street 1 mile NNE of Inner Harbor area Middle Scale Parameters taken from this site:  1-hour PM2.5 mass (AQS parameter 88502, Acceptable PM2.5 AQI & Speciation Mass) TEOM Gravimetric 50 deg C 

Same as PM2.5 site. 5% of PM10-2.5 values were regional average PM10-2.5:PStaff Paper
September 2009 

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A-15

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

PhiladelphiaWilmington AQS ID100032004 (DE) State: Delaware City: Wilmington 

MSA: Wilmington-Newark, DE-MD Local Site Name: CORNER OF MLK BLVD AND JUSTISON ST 2.5 miles NE of central Wilimington, 0.25 miles from the Delaware River, 22 miles SW from central Philadelphia 2005-2007 annual DV = 14.7 2005-2007 24-hr DV = 37 This is not the highest DV site in the Philadelphia nonattainment area Neighborhood Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; every day sampling schedule)  PM2.5 speciation (one-in-six sampling schedule)  1-hour PM2.5 mass (AQS parameter 88501, PM2.5 Raw Data) Beta Attenuation  1-hour PM10 STP mass (AQS parameter 81102) 

NA Same as PM2.5 site. 

3% of PM10-2.5 values were regional average PM10-2.5:PStaff Paper 
September 2009 

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A-16

PM2.5 Monitoring Sites and Monitors Providing 2005-2007 Data for the Analysis 

Extinction in the 15 Study Areas

Study Area First PM2.5 Monitoring Site Second PM2.5 Monitoring Site (if 

applicable) 

PM10 data sour

New YorkN.New JerseyLong Island AQS ID 340390004 (NJ) State: New Jersey City: Elizabeth MSA: Newark, NJ Local Site Name: ELIZABETH LAB 

Address: NEW JERSEY TURNPIKE INTERCHANGE 13 1.75 miles south of Elizabeth, at the I-95 interchange with I-278 2005-2007 annual DV = 14.4 2005-2007 24-hr DV = 42 This is not the highest DV site in the New York nonattainment area Neighborhood Scale Parameters taken from this site:  24-hour FRM PM2.5 mass (AQS parameter 88101; every day sampling schedule)  PM2.5 speciation (one-in-three sampling schedule)  1-hour PM2.5 mass (AQS parameter 88502, Acceptable PM2.5 AQI & Speciation Mass) TEOM Gravimetric 30 deg C No continuous PM10 monitoring at this site, see right hand column. 

NA AQS ID 360610125

State: New York City: New York MSA: New York, NY Local Site Name: PARK ROW Address: 1 PACE PLAZA Near the on-ramp to the BrooklyMeasurement scale not stated. Parameters taken from this site:  1-hour PM10 STP maso Sample CollINSTRUMENTAL-R&P SA246B-o Sample Ana

GRAVIMETRIC

2% of PM10-2.5 values were regional average PM10-2.5:PStaff Paper

Notes:  In this Table, the 1-hour concentration parameter “88502, Acceptable PM2.5 AQI & Speciation Mass” is the same as the ISA re

PM2.5 mass. An entry of “88501, PM2.5 Raw Data” indicates that the monitoring agency makes no representation as to the degr

FRM PM2.5 mass. The latter type of continuous PM2.5 data were used only when the former were unavailable. 

 Where PM10 was reported in STP, it was converted to LC before PM10-2.5 was calculated. 

 For convenience, continuous PM2.5 data were obtained through the AirNow website rather than from AQS, as an initial explor

the desired 1-hour data had been submitted to AQS.
September 2009 

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B-1

APPENDIX B - DISTRIBUTIONS OF ESTIMATED PM2.5 

COMPONENTS 
September 2009 

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B-2

Figure B-1 – Distribution of daily maximum PM2.5, PM10-2.5, and relative humidity across the 2005-2007 p

(a) Daily maximum daylight PM2.5
September 2009 

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B-3

(b) Daily maximum daylight PM10-2.5 
September 2009 

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B-4

(c) Daily maximum daylight relative humidity 
September 2009 

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B-5

Figure B-2 – Distribution of hourly PM2.5 components across the 2005-2007 period, by stud

(a) 1-hour daylight sulfate (dry, fully neutralized) 
September 2009 

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B-6

Figure B-2 – Distribution of PM2.5 components across the 2005-2007 period, by study area, co

 (b) 1-hour daylight nitrate (dry, fully neutralized, CSN method consistent) 
September 2009 

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B-7

Figure B-2 – Distribution of PM2.5 components across the 2005-2007 period, by study area, co

 (c) 1-hour daylight elemental carbon 
September 2009 

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B-8

Figure B-2 – Distribution of PM2.5 components across the 2005-2007 period, by study area, co

(d) 1-hour daylight organic carbonaceous material 
September 2009 

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B-9

Figure B-2 – Distribution of PM2.5 components across the 2005-2007 period, by study area, co

 (e) 1-hour daylight fine soil 
September 2009 

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C-1

APPENDIX C - DEVELOPMENT OF PRB ESTIMATES OF PM2.5 

COMPONENTS, PM10-2.5, AND TOTAL LIGHT EXTINCTION 

Policy relevant background levels of total light extinction have been estimated for this 

assessment by relying on outputs for the 2004 CMAQ run in which anthropogenic emission 

in the U.S., Canada, and Mexico were omitted, as described in the second draft ISA. 

Estimates of PRB for total light extinction were calculated from modeled concentrations of 

PM2.5 components using the IMPROVE algorithm. The necessary component concentrations 

were extracted from the CMAQ output files, as they were not summarized in the second draft 

ISA. 

More specifically, for each study area, EPA staff overlaid CMAQ grid cells over 

shapes representing the Census-defined urbanized area for each study area, and visually 

identified the CMAQ grid cells that had a substantial portion of their area coincident with the 

urbanized area. For each such grid cell, for each of the 12 months of the year, we obtained 

the 24 values of the hour-specific average concentrations of the five PM2.5 components. We 

then averaged these across the selected grid cells. Thus, a given hour of the day has the same 

PRB estimate for a component on all days within a month, but months and study areas differ. 

Table C-1 summarizes these PRB estimates for the PM2.5 components (including the specific 

form assumed for sulfate, nitrate, and organic carbon). The most notable observed feature of 

the PRB estimates is relatively high values for elemental and organic carbon PRB for the 

Tacoma study area. This area is often affected by wildfires for extended periods in the 

autumn months, and such fires were included in the 2004 emissions scenario for the PRB 

CMAQ run. A cursory review of information on fire events in 2005-2007 confirmed that the 

fire situation in this part of the country in 2004 was not an anomaly. 
September 2009 

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C-2

Table C-1. Summary of PRB estimates for the five PM2.5 components: average 1-hour 

values across 2005-2007 

Average 1-Hour PRB Concentration Across 2005-2007 (μg/m3) 

Study Area Sulfate 

 (dry, no 

ammonium) 

Nitrate 

(dry, no 

ammonium) 

Elemental Carbon Organic 

Carbonaceous 

Material 

Fine 

Soil/Crustal 

Tacoma 0.45 0.026 0.15 1.3 0.31 

Fresno 0.4 0.00062 0.08 0.74 0.19

Los Angeles-South 0.36 0.0037 0.028 0.3 0.036

Phoenix 0.31 0.000052 0.02 0.26 0.015

Salt Lake City 0.25 0.00028 0.025 0.26 0.034

Dallas 0.27 0.0022 0.055 0.59 0.092

Houston 0.3 0.0055 0.091 0.86 0.17

St. Louis 0.31 0.0027 0.047 0.53 0.07

Birmingham 0.29 0.007 0.099 1.1 0.19

Atlanta 0.3 0.016 0.1 1.1 0.19

Detroit-Ann Arbor 0.34 0.00062 0.024 0.32 0.018

Pittsburgh 0.3 0.00052 0.029 0.36 0.034

Baltimore 0.34 0.0016 0.039 0.44 0.054

Philadelphia- 0.34 0.00097 0.03 0.36 0.032

New York-N.New 

Jersey-Long Island 0.36 0.0038 0.026 0.31 0.022 
September 2009 

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C-3

It is also necessary to have estimates of PRB for PM10-2.5, to feed into the IMPROVE 

algorithm. The second draft ISA for this review does not present any new information on 

this subject. The approach used in the previous two Criteria Documents was to present the 

historical range of annual means of PM10-2.5 concentrations from IMPROVE monitoring sites 

selected as being least influenced by anthropogenic emissions. See Table 3E-1 of the 2004 

Criteria Document. For sites in the lower 48 states, these annual means range from a low of 

1.8 μg/m3

 to a high of 10.8 μg/m3. For this assessment, EPA staff estimated PRB for PM10-2.5 

using a contour map based on average 2000-2004 PM10-2.5 concentrations from all 

IMPROVE monitoring sites, found in a recent report from the IMPROVE program. (Spatial 

and Seasonal Patterns and Temporal Variability of Haze and its Constituents in the United 

States: Report IV, November 2006). We located each study area’s position on this map, and 

assigned it the mid-point of the range of concentrations indicated by the contour band for that 

location. The contour map is reproduced here as Figure C-1. Stars show locations of the 15 

study areas. In this reproduction, the midpoints of the contour ranges have been added to the 

legend. 

The results are shown in Table C-2. Lacking any other information, these PRB 

values are taken to apply to every hour of the year. While the contour map and thus these 

values are influenced by data from IMPROVE sites that were not considered in the 2004 

Criteria Document to be the sites most isolated from the influence of anthropogenic 

emissions, including three IMPROVE sites in urban areas, these values are generally within 

the range of values presented in the Criteria Document for such isolated sites. Further, these 

PRB values are low enough that their exact values will have little effect on the results of 

“what if” estimation of total light extinction levels under possible secondary PM NAAQS. 

Table C-3 presents the resulting 2005-2007 average PRB daylight total light 

extinction by study area, determined by using each daylight hour’s f(RH), the hour-specific 

PRB PM2.5 component estimates summarized as annual averages in Table C-1, the PRB 

PM10-2.5 estimates in Table C-2, and the IMPROVE algorithm. The sulfate and nitrate 

component values in Table C-1 are multiplied by 1.375 and 1.29 to reflect full neutralization, 

before being used in the IMPROVE algorithm. 
September 2009 

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C-4

Figure C-1. Selection of PRB values for PM10-2.5 based on contoured IMPROVE 

monitoring data 

9.5

8.5

7.5

6.5

5.5

4.5

3.5

2.5

1.5

0.5

9.5

8.5

7.5

6.5

5.5

4.5

3.5

2.5

1.5

0.5
September 2009 

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C-5

Table C-2. Policy Relevant Background Concentrations of PM10-2.5 Used in This 

Assessment, Based on Measurements at IMPROVE Sites 

Study Area PRB PM10-2.5 Mass (μg/m3) 

Tacoma 4.5 

Fresno 5.5 

Los Angeles-South Coast Air Basin 4.5 

Phoenix 5.5 

Salt Lake City 4.5 

Dallas 8.5 

Houston 5.5 

St. Louis 7.5 

Birmingham 5.5 

Atlanta 5.5 

Detroit-Ann Arbor 9.5 

Pittsburgh 3.5 

Baltimore 3.5 

Philadelphia-Wilmington 6.5 

New York-N.New Jersey-Long Island 3.5 

Table C-3. 2005-2007 Average Policy Relevant Background Daylight Total light 

Extinction 

Study Area 2005-2007 Average Policy Relevant 

Background Daylight Total Light Extinction, 

Mm-1

Tacoma 22 

Fresno 21 

Los Angeles-South Coast Air Basin 18 

Phoenix 18 

Salt Lake City 15 

Dallas 18 

Houston 20 

St. Louis 19 

Birmingham 19 

Atlanta 19 

Detroit-Ann Arbor 17 

Pittsburgh 17 

Baltimore 19 

Philadelphia-Wilmington 18 

New York-N.New Jersey-Long Island 18 
September 2009 

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D-1

APPENDIX D RELATIONSHIPS BETWEEN PM MASS 

CONCENTRATION AND TOTAL LIGHT EXTINCTION UNDER 

CURRENT CONDITIONS 

In the last review, the 2005 Staff Paper examined the correlation between total light 

extinction and PM2.5 mass concentrations, each defined for various consistent time periods. 

The 2005 Staff Paper analysis assumed that the percentage mix of PM2.5 components was the 

same in all 24 hours of each day, equal to that indicated by 24-hour CSN sampling. The 

modeling of 1-hour total light extinction in this new assessment allows these correlations to 

be re-examined, with the more realistic treatment in which the mix of PM2.5 components is 

modeled to vary during the day, based in part of diurnal profiles from CMAQ modeling (see 

section 3.2.4). 

Four figures are presented here, using different time periods for PM2.5 mass 

concentrations and total light extinction, not always matching. In each figure, the solid red 

line represents a LOESS fit (a form of locally weighted polynomial regression, see 

http://support.sas.com/rnd/app/papers/loesssugi.pdf) to the data. Table D-1 presents squared 

correlation coefficients between observed and LOESS model-predicted values for all four 

figures. 

Figure D-1 compares hourly PM2.5 mass (as actually measured by the continuous 

instruments) vs. same-hour daylight total light extinction. As the 2005 Staff Paper explained, 

the scatter is due to variations in the mix of PM2.5 components and in relative humidity across 

hours. In addition, continuous PM2.5 mass instruments do not register the mass of each 

component consistently with CSN samplers and analysis, which affects the scatter in this 

figure because the estimates of light extinction are ground truthed to the CSN measurements 

more strongly than to the continuous PM2.5 measurements. 

Figure D-2 compares 12-4 pm average PM2.5 mass vs. 12-4 pm average total light 

extinction. Because this time period is generally the time of lowest relative humidity, in most 

study areas and on average as indicated by the squared correlation coefficients, the scatter in 

Figure D-2 is less than in Figure D-1. 

Figure D-3 compares 12-4 pm average PM2.5 mass vs. daily maximum daylight 1-

hour total light extinction. The scatter in Figure D-3 is typically more than in Figure D-2, 

because daily maximum daylight 1-hour total light extinction often occurs earlier in the day 

than the 12-4 pm period used to average PM2.5 mass, when relative humidity is higher. 
September 2009 

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D-2

Figure D-4 compares 8 am-12 pm average PM2.5 mass vs. daily maximum daylight 1-

hour total light extinction. The scatter in Figure D-4 is typically less than in Figure D-3 and the 

squared correlation coefficients larger, because this earlier averaging period for PM2.5 mass more 

often encompasses the period of maximum total light extinction. 

Table D-1. Squared correlation coefficients between observed and LOESS 

model-predicted values of total light extinction 

Figure D-1 

1-hour PM2.5

mass vs. samehour total light 

extinction 

Figure D-2 

12-4 pm average 

PM2.5 mass vs. 

12-4 pm average 

total light 

extinction 

Figure D-3 

12-4 pm average 

PM2.5 mass vs. 

daily maximum 

daylight 1-hour 

total light 

extinction 

Figure D-4 

8 am-12pm 

average PM2.5

mass vs. daily 

maximum 

daylight 1-hour 

total light 

extinction 

Area 

Tacoma 0.82 0.80 0.36 0.73 

Fresno 0.79 0.89 0.60 0.69 

Los AngelesSouth Coast Air 

Basin 0.58 0.65 0.35 0.46 

Phoenix 

 0.63 0.66 0.16 0.17 

Salt Lake City 0.86 0.94 0.70 0.80 

Dallas 0.51 0.50 0.15 0.28 

Houston 0.52 0.57 0.20 0.31 

St. Louis 0.44 0.27 0.25 0.41 

Birmingham 0.63 0.60 0.25 0.33 

Atlanta 0.62 0.74 0.35 0.58 

Detroit-Ann 

Arbor 0.49 0.58 0.11 0.31 

Pittsburgh 0.47 0.51 0.39 0.41 

Baltimore 0.43 0.48 0.47 0.49 

PhiladelphiaWilmington 0.43 0.36 0.16 0.25 

New YorkN.New JerseyLong Island 0.68 0.82 0.49 0.52 

AVERAGE 0.59 0.62 0.33 0.45 
September 2009 

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D-3

Figure D-1. – Relationship between 1-hour PM2.5 mass vs. same-hour total light extincti
September 2009 

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D-4

Figure D-2. Relationship between 12-4 pm average PM2.5 mass vs. 12-4 pm average total light e
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D-5

Figure D-3. Relationship between 12-4 pm average PM2.5 mass vs. daily maximum daylight 1

extinction. 
September 2009 

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D-6

Figure D-4. Relationship between 8 am-12pm average PM2.5 mass vs. daily maximum daylight 1-hour to
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E-1

APPENDIX E - DIFFERENCES IN DAILY PATTERNS OF 

RELATIVE HUMIDITY AND TOTAL LIGHT EXTINCTION 

BETWEEN AREAS AND SEASONS 

In the last review of the secondary PM NAAQS, the pattern of total light extinction 

during the day was of particular interest. It was noted, using estimates of hourly total light 

extinction based on a simpler approach than described for this analysis, that both (1) mid-day 

total light extinction and (2) the slope of the relationship between total light extinction and 

PM2.5 concentration varied less among regions of the country that at other times of the day. 

This was attributed to greater homogeneity of relative humidity across regions in the mid-day 

period. This is in contrast to the situation in the morning and later afternoon hours, when 

more eastern areas typically experience higher relative humidity levels than the more arid 

western and southwestern areas. The current analysis allows these patterns to be reexamined. 

Figures E-1 through E-4 show the diurnal pattern of season-average, hour-specific 

total light extinction and relative humidity for the four “daylight seasons.” Light extinction 

and relative humidity for a given clock hour are averaged across the days in the season, 

across all three years. Daylight hours (per the simplified schedule of Table 3-5) are indicated 

by solid circles. Average 1-hour total light extinction generally is highest in the morning, 

corresponding to higher relatively humidity (mostly due to lower temperature), higher 

vehicle traffic, and less dispersive conditions than later in the day. As was observed in the 

last review, there is more variation in average 1-hour total light extinction among areas in the 

morning than at mid-day. 
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E-2

Figure E-1. Diurnal and seasonal patterns of relative humidity (percent) and total light extinction (Mm-1) 

(a) November-January 
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E-3

Figure E-2. Diurnal and seasonal patterns of relative humidity (percent) and total light extinction (Mm

continued 

(b) February-April 
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E-4

Figure E-3. Diurnal and seasonal patterns of relative humidity (percent) and total light extinction (Mm

continued 

(c) May-July 
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E-5

Figure E-4. Diurnal and seasonal patterns of relative humidity (percent) and total light extinction (Mm

continued 

(d) August-October 
September 2009 F-1

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1 APPENDIX F - DISTRIBUTIONS OF MAXIMUM DAILY 

2 DAYLIGHT TOTAL LIGHT EXTINCTION - UNDER “JUST 

3 MEET” CONDITIONS 

(a) 201 Mm-1, 90th 4 percentile 

5 

(b) 201 Mm-1, 95th 6 percentile 

7 
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(c) 122 Mm-1, 90th 1 percentile 

2 

(d) 122 Mm-1, 95th 3 percentile 

4 
September 2009 F-3

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(e) 74 Mm-1, 90th 1 percentile 

2 

(f) 74 Mm-1, 95th 3 percentile 

4 
September 2009 F-4

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(g) 15 μg/m3

 annual, 35 μg/m3 1 24-hour 

2 

(h) 12 μg/m3 annual, 35 μg/m3 3 24-hour 

4 

5 

6 


United States 

Environmental Protection Agency 

Office of Air Quality Planning and Standards 

Health and Environmental Impacts Division 

Research Triangle Park, NC 

Publication No.