1

From: Lydia Wegman/RTP/USEPA/US

To: nfrey@omb.eop.gov

Cc: Richard Wayland/RTP/USEPA/US@EPA, James Hemby/RTP/USEPA/US@EPA, James 

Kelly/RTP/USEPA/US@EPA, Beth Hassett-Sipple/RTP/USEPA/US@EPA, Joseph-J 

Dougherty/DC/USEPA/US@EPA, Stephanie Hogan/DC/USEPA/US@EPA, 

martin.karen@epa.gov, hannon.john@epa.gov

Date: 06/12/2012 12:13 PM

Subject: Memo on technical analyses to support surrogacy demonstrations related to the proposed PM 

secondary standard

Nathan, 

Attached is the technical surrogacy memo that we have discussed in the context of the secondary 

standard. It is referenced in the proposed rule as the Wayland memorandum. We are providing this for 

the information of the reviewers who have requested to see it but we are not seeking comments on it. 

Please let me know if you have any questions. 

Lydia
2

 

 UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

 Research Triangle Park, NC 27711

 

June XX, 2012

MEMORANDUM

TO: EPA Docket # EPA-HQ-OAR-2012-XXXX

FROM: James Kelly, Mark Schmidt, Neil Frank, Brian Timin, Douglas Solomon, and 

Venkatesh Rao

THROUGH: Richard Wayland, Director, Air Quality Assessment Division

RE: Technical Analyses to Support Surrogacy Policy for Proposed Secondary PM2.5

NAAQS under NSR/PSD Program

I. Overview

The Prevention of Significant Deterioration (PSD) program requires individual new or modified stationary 

sources to carry out an air quality analysis to demonstrate that their proposed emissions increases will not cause or 

contribute to a violation of any of the National Ambient Air Quality Standards (NAAQS). Such a demonstration for 

the proposed secondary PM2.5 visibility index NAAQS could require each PSD applicant to predict, via air quality 

modeling, the increase in visibility impairment that would result from the proposed source’s emissions in 

conjunction with an assessment of existing air quality (visibility impairment) conditions. If this demonstration were 

to be attempted using the six-step procedure that the EPA is proposing to use for calculating PM2.5 visibility index 

design values from monitored air concentrations of PM2.5 components, significant technical issues with the modeling 

procedures could arise. 

Recognizing these difficult technical issues, the EPA believes that there is an essential need to provide 

alternative approaches to enable prospective PSD sources to demonstrate that they will not cause or contribute to a 

OFFICE OF

AIR QUALITY PLANNING

AND STANDARDS
3

violation of the secondary PM2.5 visibility index NAAQS, if finalized as proposed. To meet this need, this 

memorandum documents the technical analyses conducted to provide the basis for a surrogacy approach that could 

be used by prospective PSD sources to facilitate the transition to a workable PSD permitting approach under the 

proposed secondary PM2.5 visibility index NAAQS. As described here, the EPA conducted a two-pronged technical 

analysis of the relationships between the proposed PM2.5 visibility index standard and the 24-hour PM2.5 standard. 

Based on this technical analysis, the EPA currently believes that there is sufficient evidence that a demonstration 

that a source does not cause or contribute to a violation of the mass-based 24-hour PM2.5 NAAQS serves as a 

suitable surrogate for demonstrating that a source does not cause or contribute to a violation of the proposed 

secondary 24-hour PM2.5 visibility index NAAQS under the PSD program. As such, many or all sources undergoing 

PSD review for PM2.5 could rely upon their analysis for demonstrating that they do not cause or contribute to a 

violation of the mass-based 24-hour PM2.5 NAAQS to also show that they do not cause or contribute to a violation 

of with the proposed secondary PM2.5 visibility index NAAQS, if finalized.

II. Policy Background

PSD applicants are currently required to demonstrate compliance with the existing annual and 24-hour 

PM2.5 NAAQS. To assist sources and permitting authorities in carrying out the required air quality analysis for PM2.5

under the existing standards, the EPA issued, on March 23, 2010, a guidance memorandum that recommends certain 

interim procedures to address the fact that compliance with the 24-hour PM2.5 NAAQS is based on a particular 

statistical form and that there are technical complications associated with the ability of existing models to estimate 

the impacts of secondarily formed PM2.5 resulting from emissions of PM2.5 precursors1. To provide more detail and 

to address potential issues associated with the modeling of direct and precursor emissions of PM2.5, the EPA is now 

developing additional permit modeling guidance that will recommend appropriate technical approaches for 

conducting a PM2.5 NAAQS compliance demonstration for the existing PM2.5 NAAQS, which includes a more 

adequate accounting for contributions from secondary formation of ambient PM2.5 resulting from a proposed new or 

modified source’s precursor emissions. To this end, the EPA discussed this draft guidance in March 2012 at the 

EPA’s 10th Modeling Conference.2 Based on its review of public comments received and further technical analyses, 

 

1 U.S. EPA (2010) Modeling procedures for demonstrating compliance with PM2.5 NAAQS. Stephen D. Page 

Memorandum, dated March 23, 2010. U.S. Environmental Protection Agency, Research Triangle Park, NC.

2

The presentation on this draft guidance is posted on the EPA website at: 

http://www.epa.gov/ttn/scram/10thmodconf.htm.
4

the EPA intends to issue final guidance by the end of calendar year 2012.

EPA is proposing a distinct secondary NAAQS for PM2.5 that will provide protection against visibility 

impairment, measured in terms of a visibility index using a calculated PM2.5 light extinction indicator. The PM2.5

visibility index values are determined using a six-step procedure involving 24-hour speciated PM2.5 concentration 

data together with climatological relative humidity factors. The EPA plans to calculate design values for the 

proposed secondary PM2.5 visibility index NAAQS using these procedures with ambient PM2.5 speciation 

measurement data available through the CSN and IMPROVE networks and climatological relative humidity data.

As noted in the overview section, certain technical issues currently prevent model-based determinations of 

the visibility impairment that would result from a new or modified source. These technical difficulties include the 

current limitations on speciated source-specific emissions data for model input; the lack of an EPA-approved air 

quality model with the capability to address the atmospheric chemistry associated with secondary formation of 

PM2.5; and the lack of PSD screening tools for streamlining the air quality analysis process. In addition, due to the 

limited monitoring network for speciated PM2.5, some sources may not be able to rely on existing speciated 

monitoring data to adequately represent the background air quality and thereby satisfy preconstruction monitoring 

requirements. Consequently, those prospective PSD sources could be required to collect new data in order to 

determine the representative background concentrations of PM2.5 species (i.e., those required for calculating the 

PM2.5 visibility index values).

Recognizing these difficult technical issues, the EPA believes that there is an essential need to provide 

alternative approaches to enable prospective PSD sources to demonstrate that they will not cause or contribute to a 

violation of the secondary PM2.5 visibility index NAAQS, if finalized as proposed. To meet this need, the EPA 

believes that it is reasonable to allow the use of a surrogacy approach for at least the interim period while technical 

issues are being resolved, but which could potentially be continued beyond such time if shown to be appropriate. 

The EPA believes that following this approach will facilitate the transition to a workable PSD permitting approach 

under the proposed secondary PM2.5 visibility index NAAQS.

To support consideration of alternative approaches that could be used by prospective PSD sources, the EPA 

conducted a two-pronged technical analysis of the relationships between the proposed PM2.5 visibility index 

NAAQS and the 24-hour PM2.5 NAAQS. The first prong of the analysis addressed aspects of a PSD significant 

impact analysis by evaluating whether an individual source’s impact resulting in a small increase in PM2.5

concentration would produce a comparably small increase in visibility impairment. This analysis included estimates 
5

of PM2.5 speciation profiles based on direct PM2.5 emission profiles for a broad range of source categories and for 

theoretical upper and lower bound scenarios. The analysis indicated that small increases in PM2.5 concentrations 

caused by individual sources produce similarly small changes in visibility impairment for ambient conditions near 

the proposed standard level of either 30 or 28 deciviews (dv). This result indicates that a significant impact level 

(SIL) defined in the context of the 24-hour PM2.5 NAAQS would also be suitable for use as a SIL in the context of 

the proposed secondary PM2.5 visibility index NAAQS. The second prong of the analysis addressed aspects of a 

PSD cumulative impact analysis by exploring the relationship between the three-year design values for the existing

24-hour PM2.5 NAAQS and coincident design values for the proposed PM2.5 visibility index NAAQS based on 

recent air quality data. This analysis indicated that increases in 24-hour PM2.5 design values generally correspond to 

increases in visibility index design values, and vice-versa. The analysis further explored the appropriateness of 

using a demonstration that a source does not cause or contribute to a violation of the 24-hour PM2.5 NAAQS as a 

surrogate for a demonstration that a source does not cause or contribute to a violation of the proposed secondary 

PM2.5 visibility index NAAQS. This analysis is based on 2008 to 2010 air quality data and on the proposed retention 

of the 24-hour PM2.5 NAAQS with a level of 35 μg/m3in conjunction with a 98th percentile form and the proposed 

secondary PM2.5 visibility index standard with a level of 28 or 30 dv in conjunction with 24-hour averaging time and 

a 90th percentile form. This analysis indicated that all (for the 30 dv level) or nearly all (for the 28 dv level) areas in 

attainment of the 24-hour PM2.5 standard would also be in attainment of the proposed secondary PM2.5 visibility 

index standard. 

Note that the surrogacy approach is not intended to replace or otherwise undermine the validity of the 

analytical techniques employed for air quality related value assessments (AQRVs), including visibility, required 

under 40 CFR Part 51.166 (p) and 40 CFR Part 52.21 (p). The Federal Land Managers (FLM) and the Federal 

official with direct responsibility for management of Federal Class I parks and wilderness areas have an affirmative 

responsibility to protect the AQRVs of such lands and to provide the appropriate procedures and analysis techniques 

for assessing AQRVs (Appendix W to 40 CFR Part 51, Sections 6.1(b) and 6.2.3(a)). The FLMs have developed 

specific modeling approaches for AQRV assessments that are not specifically governed under the requirements set 

forth in 40 CFR Part 51.166 (l) (1) and 40 CFR Part 52.21 (l) (1). Thus the surrogacy approach is not applicable to 

the AQRV assessments under the PSD program.
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III. Technical Background

The IMPROVE equation used here for calculating the light extinction coefficient, bext

3

, from speciated 

PM2.5 concentration is as follows:

bext = 3 × f(RH) [Sulfate] +

3 × f(RH) [Nitrate] +

4 × [Organic Mass] + (1)

10 × [Elemental Carbon] +

1 × [Fine Soil],

where [Sulfate] is the mass of ammonium sulfate under the assumption of fully-neutralized sulfate ion (i.e., [Sulfate] 

= 1.375 × SO4

2-

concentration), [Nitrate] is the mass of ammonium nitrate under the assumption of fully-neutralized 

nitrate ion (i.e., [Nitrate] = 1.29 × NO3

-

concentration), [Organic Mass] is calculated as 1.4 × the organic carbon

concentration, [Elemental Carbon] is elemental carbon concentration, [Fine Soil] is a sum of the fine soil-derived 

elements (Al, Si, K, Ca, Ti, Fe) along with their normal oxides (Al2O3, SiO2, CaO, K2O, FeO, Fe2O3, TiO2), and 

f(RH) is a relative humidity adjustment factor that accounts for enhanced light extinction due to water uptake by 

hygroscopic particle components. For a given PM2.5 composition and RH, increases in bext are linear with respect to 

increases in PM2.5 concentration. The visibility index (VI) is a logarithmic transformation of the light extinction 

coefficient and is calculated as follows:

10

10 10 bext VI ln

,

(2)

where units are in deciviews. Increases in VI are logarithmic with respect to increases in bext such that changes in VI

are approximately linear with respect to perceived visibility changes. Equation 2 ensures that increases or decreases 

in light extinction coefficient always produce, respectively, increases or decreases in visibility index. 

While Equations 1 and 2 provide clear relationships between speciated PM2.5 concentrations and visibility

impairment, the impact of variable particle composition and RH on the relationships under ambient conditions is not 

obvious from the expressions. To explore the relationships for ambient conditions, calculated light extinction (bext) 

 

3

bext is the attenuation of light per unit distance due to scattering and absorption by gases and particles in the 

atmosphere; expressed in Mm-1units
7

and visibility index (VI) are plotted as functions of 24-hour PM2.5 concentration for PM2.5 measurements from 2008 

to 2010 at 199 locations in Figure 1. Following the trend expected from Equation 1, calculated light extinction 

increases roughly linearly with PM2.5 concentration (Figure 1a) with correlation coefficients for U.S. regions defined 

in Figure 2 ranging from 0.81 to 0.95 and equaling 0.92 over all sites (Table 1). The scatter in results in Figure 1a is 

due to differences in RH and PM2.5 composition for the different measurements. Results in Figure 1b indicate that 

calculated visibility index tends to increase logarithmically with increasing PM2.5 concentration for the ambient 

PM2.5 data as expected based on Equation 2. Similar to the light extinction case, the scatter in results for visibility 

index is due to differences in PM2.5 composition and RH for the different measurements. The strong relationship 

between 24-hour PM2.5 concentration and visibility impairment for the ambient data in Figure 1 provides the 

foundation for the analysis described below that focuses on demonstrating surrogacy in the context of the NSR/PSD 

program.

Figure 1. Daily calculated (a) light extinction coefficient and (b) visibility index as a function of measured daily 

average PM2.5 concentration

(a) (b)
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Figure 2. Definition of U.S. regions4considered in this analysis.

Table 1. Correlation of daily calculated light extinction and 24-hour PM2.5 concentration for U.S. observational sites. 

Note: values correspond to results shown in Figure 1a; regions are defined in Figure 2.

IV. Technical Analyses

This section examines use of the 24-hour PM2.5 NAAQS as a surrogate for the proposed secondary PM2.5

visibility index NAAQS in the context of two aspects of the NSR/PSD program. First, the topic of whether a SIL

defined for the 24-hour PM2.5 NAAQS would correspond to a comparably small value in terms of visibility 

impairment is examined. The NSR/PSD significant impact analysis uses a SIL in determining whether a source’s 

adverse impact on air quality is considered significant. If a source’s impact exceeds the SIL, then a cumulative 

impact analysis is required for that source to determine if its emissions cause or contribute to potential NAAQS

violations. The second component of the analysis explores the suitability of using a surrogate approach in a 

cumulative impact analysis by considering whether violation status based on recent air quality data would be similar 

under the proposed secondary PM2.5 visibility index NAAQS and under the 24-hour PM2.5 NAAQS.

A Small Increase in PM2.5 Concentration Produces a Comparably Small Increase in Visibility Impairment

For a SIL developed in the context of the 24-hour PM2.5 NAAQS to be suitable for the proposed secondary 

visibility index NAAQS, a small increase in PM2.5 concentration relative to the 24-hour PM2.5 NAAQS should 

produce a comparably small increase in visibility index relative to the secondary visibility index NAAQS. In this 

analysis, the changes in visibility index associated with increases in PM2.5 concentration of around 1 g m-3are 

evaluated. The PM2.5 speciation profiles listed in Table 2 are used with Equation 1 in examining the relationship 

between increases in PM2.5 concentration and visibility index for ambient conditions near the proposed standard 

levels of 28 or 30 dv under low- and high-RH conditions. The profiles in Table 2 are based on direct-PM2.5

 

4 U.S. EPA (1996) Air Quality Criteria for Particulate Matter. Volume I of III. EPA/600/P-95/001aF 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=2832

Region

n daily 

values n sites

Correlation of daily 

calculated light extinction, 

bext (in Mm-1) vs. daily mass 

concentration (in μg/m3)

Northeast 7,204 35 0.93

Southeast 7,039 41 0.88

Ind. Midwest 9,770 66 0.93

Upper Midwest 2,258 11 0.93

Southwest 967 7 0.81

Northwest 4,859 31 0.93

So. California 1,917 8 0.95

U.S. 34,014 199 0.92
9

emission source profiles as described in Appendix A. Cases where PM2.5 is assumed to be composed of a single 

component are also considered to provide theoretical upper- and lower-bound values. For instance, the upper-bound 

change in visibility index occurs under high-RH conditions when PM2.5 is composed entirely of a hygroscopic 

component such as sulfate. 

The increases in visibility index associated with a 1 g m-3increase in PM2.5 concentration for low- and 

high-RH conditions are shown in Figure 3 as a function of the background ambient visibility index for PM2.5 with 

the concentration profiles in Table 2. Curves for the theoretical upper and lower bounds are based on calculations 

for 1 g m-3of single-component PM2.5 without hydration5. Although the upper-bound composition may not be 

realized in practice, it is included here as a reference to address the potential concern that the secondary component 

of PM2.5 concentration resulting from SO2 and NOx emissions is not directly considered in the concentration profiles 

in Table 2. In this discussion, “low-RH” conditions correspond to a relative humidity adjustment factor, f(RH), of 

1.51, and “high-RH” conditions correspond to f(RH)=4.16. These values occur at the lower and upper end of the 

climatological monthly average f(RH) distributions shown in Figure A.1 in Appendix A. In terms of relative 

humidity, the RH adjustment factors correspond to RHs of 55% and 90% based on the scale used in Regional Haze 

Rule guidance documents (see Appendix A). Visibility impairment by PM2.5 is greatest under high-RH conditions 

due to water uptake by hygroscopic particle components (i.e., sulfate and nitrate) with increasing RH. Therefore, 

results in Figure 3b for profiles with large sulfate fractions are an extreme test of the visibility impacts associated 

with a 1 g m-3increase in PM2.5 concentration.

For a background ambient visibility index of 27 dv, the addition of 1 g m-3of PM2.5 produces a median

increase in visibility impairment of 0.2 dv with a range of 0.09-0.44 dv under low-RH conditions based on the 

profiles in Table 2 (Figure 3a). Elemental carbon (EC) has the greatest light extinction per unit mass for low-RH 

conditions, and so the Natural Gas Combustion profile (43.9% EC) produces the greatest visibility impairment in 

Figure 3a. The theoretical upper-bound of 0.65 dv is given in this case by single-component EC PM2.5, and the 

theoretical lower bound of 0.07 dv is given by single-component fine soil PM2.5. Under high-RH conditions (Figure 

3b), the median increase in visibility index for the profiles for an increase of 1 g m-3of PM2.5 concentration is 0.36

dv and the range is 0.11-0.78 dv at a background ambient visibility index of 27 dv. [Sulfate] and [Nitrate] have the 

greatest light extinction per unit mass for high-RH conditions, and so the Residential Oil Combustion profile (95.2% 

 

5

For instance, the upper-bound dashed curve in Figure 3b is based on calculations with Equation 1 using a value of 1 

g m-3for [Sulfate].
10

[Sulfate]) produces the greatest visibility impairment of the source profiles in Figure 3b. The theoretical upperbound of 0.81 dv is given in this case by single-component [Sulfate] PM2.5, and the theoretical lower bound of 0.07 

dv is given by single-component fine soil PM2.5. Considering that median changes in visibility index for the profiles 

is less than 0.5 dv and the theoretical maximum change is less than 1 dv even under conditions of high RH, results in 

Figure 3 indicate increases in visibility index are comparably small to a 1 g m-3increase in PM2.5 concentration for 

ambient conditions near the proposed levels of 28 or 30 dv.

The increase in visibility impairment with an increase in PM2.5 concentration for ambient conditions with a 

background visibility index of 27 dv is shown as a function of PM2.5 concentration increase (0.8 to 1.2 g m-3) in 

Figure 4 for low- and high-RH conditions. For the highest PM2.5 concentration increase considered, the median

increase in visibility impairment under low-RH conditions is 0.24 dv with a range of 0.11-0.53 dv (Figure 4a) for the 

profiles in Table 2, with theoretical upper- and lower-bound values of 0.78 dv and 0.08 dv, respectively. The 

median increase in visibility impairment under high-RH conditions for the source profiles is 0.43 dv with a range of 

0.13-0.93 dv (Figure 4b), and the theoretical upper- and lower-bound values are 0.96 dv and 0.08 dv, respectively. 

Results in Figure 4 indicate that visibility index changes associated with an increase of PM2.5 concentration of up to 

1.2 g m-3are comparably small for ambient conditions near the proposed levels of 28 or 30 dv.

For readers so interested, the increases in light extinction coefficient associated with increases in PM2.5

concentration (0.8 to 1.2 g m-3) are shown in Figure 5 for low- and high-RH conditions. Note that changes in the 

light extinction coefficient associated with changes in PM2.5 concentration do not depend on the background amount 

of light extinction as do changes in the visibility index. Under low-RH conditions, a 1 g m-3increase in PM2.5

concentration produces a median increase in light extinction of 3.06 Mm-1 with a range of 1.31-6.72 Mm-1for the 

source profiles in Table 2 (Figure 5a). The median increase in light extinction coefficient in this case is 1.9% of the 

total light extinction coefficient at 28 dv (i.e., bext+10=164.4 Mm-1; Equation 2) and 1.5% of the value at 30 dv (i.e., 

200.9 Mm-1; Equation 2). The theoretical upper-bound of 10 Mm-1for a 1 g m-3increase in PM2.5 concentration is 

given in this case by single-component EC PM2.5, and the theoretical lower bound of 1 Mm-1is given by singlecomponent soil PM2.5. Under high-RH conditions, a 1 g m-3

increase in PM2.5 concentration produces a median

increase in light extinction coefficient for the source profiles of 5.43 Mm-1 with a range of 1.6-12.13 Mm-1(Figure 

5b). The median increase in light extinction coefficient in this case is 3.3% of the total light extinction coefficient at 

28 dv and 2.7% of the value at 30 dv. Under high-RH conditions, single-component [Sulfate] PM2.5 gives a 
11

theoretical upper-bound change in light extinction coefficient of 12.48 Mm-1for a 1 g m-3increase in PM2.5

concentration, and soil PM2.5 gives a theoretical lower bound of 1 Mm-1. Results in Figure 5 indicate that changes in 

light extinction associated with a small increase in PM2.5 concentration would be comparably small relative to total 

light extinction at 28 or 30 dv.

Overall, results in Figures 3–5 suggest that a small increase in PM2.5 concentration relative to the 24-hour PM2.5

NAAQS produces a comparably small increase in visibility index and light extinction coefficient relative to the 

proposed secondary visibility index NAAQS, and thus the results provide support for using the 24-hour PM2.5

NAAQS as a surrogate for the proposed secondary visibility index NAAQS in the air quality analysis for NSR/PSD 

applications. Specifically, the results indicate that a SIL defined in the context of the 24-hour PM2.5 NAAQS would 

be suitable for use as a SIL in the context of the secondary PM2.5 visibility index NAAQS.

Table 2. Profiles of PM2.5 concentration used in visibility calculations with Equation 1 (see Appendix A for details

on the development of the profiles).

Category EC OM [Nitrate] [Sulfate] Soil

Aluminum Production 2.9% 6.9% 0.7% 7.7% 81.8%

Asphalt Manufacturing 7.9% 8.3% 0.2% 1.3% 82.4%

Asphalt Roofing 0.0% 98.9% 0.0% 0.1% 0.9%

Bituminous Combustion 2.9% 6.3% 0.5% 29.8% 60.5%

Cast Iron Cupola 0.9% 8.8% 0.6% 8.5% 81.1%

Catalytic Cracking 0.1% 0.0% 0.0% 44.0% 55.9%

Cement Production 2.9% 17.6% 6.0% 24.1% 49.4%

Construction Dust 0.0% 10.8% 0.1% 2.4% 86.7%

Distillate Oil Combustion 13.8% 48.4% 0.0% 36.1% 1.6%

Electric Arc Furnace 0.4% 4.8% 0.3% 3.3% 91.1%

Industrial Manufacturing - Avg 3.6% 41.0% 1.5% 53.9% 0.0%

Lignite Combustion 1.4% 38.8% 0.5% 10.1% 49.2%

Lime Kiln 2.1% 8.3% 0.6% 45.1% 43.9%

Natural Gas Combustion 43.9% 39.5% 3.1% 13.5% 0.0%

Open Hearth Furnace 0.0% 27.3% 0.7% 53.6% 18.5%

Petroleum Industry - Avg 0.0% 13.0% 0.9% 86.0% 0.0%

Process Gas Combustion 14.7% 42.5% 3.1% 22.9% 16.8%

Pulp & Paper Mills 0.1% 0.0% 0.0% 65.3% 34.6%

Residential Coal Combustion 24.0% 62.8% 0.4% 4.6% 8.2%

Residential Natural Gas Combustion 6.4% 65.1% 4.2% 16.5% 7.9%

Residual Oil Combustion 1.6% 2.2% 0.0% 95.2% 1.0%

Solid Waste Combustion 2.2% 17.1% 2.7% 13.5% 64.5%

Sub-Bituminous Combustion 6.5% 6.7% 0.1% 21.2% 65.5%

Wood Fired Boiler 3.6% 48.0% 0.0% 8.8% 39.6%
12

Figure 3. Change in visibility index in deciview units for a 1 g m-3increase in PM2.5 under (a) low-RH and (b) 

high-RH conditions. The order of emission sources in the legend matches that of the curves.
13

Figure 4. Change in visibility index in deciview units for an increase in PM2.5 concentration at ambient conditions 

of 27 dv under (a) low-RH and (b) high-RH conditions. The order of emission sources in the legend matches that of 

the curves.
14

Figure 5. Change in light extinction for an increase in PM2.5 concentration under (a) low-RH and (b) high-RH 

conditions. The order of emission sources in the legend matches that of the curves.
15

Areas that Attain the 24-hour PM2.5 NAAQS Generally Attain the Proposed Secondary Visibility Index NAAQS

In this section, the relationship between 24-hour PM2.5 design values and visibility index design values is 

examined along with violation status under the 24-hour PM2.5 NAAQS and the secondary visibility index NAAQS. 

While the relationship between PM2.5 concentration and visibility index has been described above, the relationship 

between design values for the 24-hour PM2.5 NAAQS and secondary visibility index NAAQS is not obvious a priori

because of differences in design value calculations for the standards. 

Design values for the 24-hour PM2.5 NAAQS and the secondary PM2.5 visibility index NAAQS based on

PM2.5 measurements from 2008 to 2010 are shown in Figure 6. The 102 sites represented in Figure 6 are those with 

data that meet the current and/or proposed data completeness criteria of 40 CFR Part 50, Appendix N, for the 24-

hour PM2.5 NAAQS and a possible visibility index NAAQS level of 28 dv. Data markers are color-coded according 

to the U.S. regions defined in Figure 2 and are shape-coded according to location in the eastern or western U.S. The

data suggest that increases or decreases in 24-hour PM2.5 design values correspond, respectively, to increases or 

decreases in visibility index design values. Although some curvature is indicated by the data for the relationship 

between 24-hour PM2.5 design values and visibility index design values, linear correlations were calculated and

range from 0.65 to 0.98 for the U.S. regions and equal 0.75 over all U.S. sites (Figure 6). The curvature in the data 

arises from the logarithmic relationship between PM2.5 concentration and visibility index (i.e., Equation 2) that 

persists to some degree through the design value calculation6. 

The four quadrants demarcated by solid grey lines in Figure 6 identify zones of exceedance for the 24-hour 

PM2.5 NAAQS and the proposed secondary visibility index NAAQS level of 28 dv. Note that these quadrants are 

based on design values of 35.5 g m-3and 28.5 dv (rather than 35 g m-3and 28 dv) in the Figure 6 to reflect 

rounding conventions. Similarly, the dashed horizontal line at 30.5 dv corresponds to the proposed secondary 

NAAQS level of 30 dv. The majority of the design values in Figure 6 fall into the lower-left quadrant where neither 

the 24-hour nor the secondary NAAQS level is exceeded. For design values in the upper-right quadrant, where both 

NAAQS levels are exceeded, a question arises on whether the visibility index levels of 28 or 30 dv would be 

attained if the 24-hour PM2.5 design values were reduced to the level of 35 g m-3through emission controls. Based 

on trends in the figure, the secondary standard level of 30 dv would likely be attained at sites that violate both the 

24-hour level and the secondary visibility index 30 dv level if PM2.5 concentrations were reduced such that the 24-

 

6 The relationship between annual PM2.5 design values and visibility index design values (Figure A.2 in Appendix 

A) is similar to that for the 24-hour PM2.5 design values but with generally higher linear correlations (i.e., 0.72 to 

0.96 for U.S. regions and 0.87 over all U.S. sites).
16

hour level was attained. For the Southern California (red circles) and Northwest (blue circles) design values that 

exceed the 24-hr NAAQS and the secondary 28 dv level, a roughly 2-3 dv decrease in visibility index design value 

with a roughly 13-27 g m-3decrease in 24-hour PM2.5 design value would provide for attainment of both standards. 

Such behavior is consistent with the overall trend of design values for the Southern California and Northwest 

regions in Figure 6. No design value for these regions occurs in the upper-left quadrant, where the proposed 

visibility index NAAQS is exceeded and the 24-hour PM2.5 NAAQS is attained. For the Industrial Midwest marker 

(grey star) in the upper-right quadrant, a roughly 3 dv decrease in visibility index design value with a roughly 13 g 

m

-3

decrease in 24-hour PM2.5 design value would provide for attainment of both the 24-hour level and secondary

level of 28 dv. For this case, attainment of the 24-hour PM2.5 NAAQS may lead to attainment of the proposed 

secondary level of 28 dv, although behavior for Industrial Midwest sites is more complicated because four values for 

this region occur in the upper-left quadrant.

Design values in the upper-left and lower-right quadrants of Figure 6 correspond to cases where either the 

24-hour PM2.5 NAAQS or the secondary visibility index NAAQS is exceeded (but not both). Of the design values 

in these quadrants, values for sites in Southern California and the Northwest occur in the lower-right quadrant where 

both secondary visibility index NAAQS levels are attained despite exceedance of the 24-hour PM2.5 NAAQS level, 

while values for sites in the Industrial Midwest occur in the upper-left quadrant where the secondary visibility index 

NAAQS level of 28 dv is exceeded despite attainment of the 24-hour PM2.5 NAAQS level. No design value exists 

where the secondary NAAQS level of 30 dv is exceeded but the 24-hour PM2.5 NAAQS level is attained. However, 

the design values for Industrial Midwest sites that exceed the secondary visibility index NAAQS level of 28 dv but 

attain the 24-hour PM2.5 NAAQS level indicate that attainment of the 24-hour PM2.5 NAAQS does not guarantee 

attainment of the proposed visibility index NAAQS level of 28 dv. 

A map of exceedance counties for the 24-hour PM2.5 NAAQS and secondary visibility index NAAQS level 

of 28 dv based on 24-hour average PM2.5 measurements from 2008 to 2010 is shown in Figure 7. Note that 132

counties are represented in Figure 7 while only 102 sites are represented in Figure 6 due to data completeness 

considerations. For instance, a county is represented in Figure 7 if complete data exists for calculating a 24-hour 

design value and a secondary standard design value for the county from a combination of monitors in the county,

whereas a site is represented in Figure 6 if complete data exists for calculating both the 24-hour and secondary 

standard design values at the individual monitoring site. The Industrial Midwest counties in Indiana (i.e., Elkhart 

and Clark) and Ohio (i.e., Cuyahoga and Jefferson) shown in red in Figure 7 exceed the secondary NAAQS level of 
17

28 dv but do not exceed the 24-hour PM2.5 NAAQS. The Industrial Midwest is characterized by PM2.5 with

relatively high nitrate and sulfate fractions (Figure 8a) as well as instances of high RH (Figure 8b) that can combine 

to produce relatively high visibility impairment per unit mass of PM2.5. This region also tends to experience a 

relatively large number of days with moderate PM2.5 levels such that the 90th percentile PM2.5 concentration

(relevant to visibility index design value calculations) is relatively close to the 98th percentile PM2.5 concentration

(relevant to 24-hour PM2.5 design value calculations). This behavior is evident in the comparison of the ratios of 

90th-to-98th percentiles of PM2.5 concentration distributions in Figure 8c. The combination of high nitrate and sulfate 

fractions, substantial RH adjustment factors, and PM2.5 distribution characteristics leads to relatively high visibility 

index design values for a given 24-hour PM2.5 design value for counties in the Industrial Midwest. Regional 

reductions in sulfate PM2.5 due to emission controls planned as part of national rules as well as emission reductions 

associated with potential annual standard violations7are expected to improve visibility in this region.

The design value trends in Figure 6 for U.S. regions suggest that the 24-hour PM2.5 NAAQS level of 35 g m-3

would generally be controlling of violation status compared with the secondary visibility index levels of 28 or 30 dv. 

For instance, moving from left to right in the figure, the red and blue circles pass from the quadrant of attaining both 

standards to the quadrant of exceeding the 24-hour PM2.5 NAAQS before entering the quadrant where the secondary 

visibility index NAAQS level of 28 dv is exceeded. Such a trend indicates that a source would trigger a violation of 

the 24-hour PM2.5 NAAQS before triggering a violation of the secondary visibility index NAAQS if it caused a 24-

hour PM2.5 concentration increase above the SIL in an area attaining both standards. Emissions from a single source 

would be unlikely to alter the trends apparent in Figure 6, particularly for background PM2.5 conditions near the 

levels of the standards. Therefore trends in Figure 6 generally support the use of the surrogacy approach in a 

NSR/PSD cumulative impact analysis. For Industrial Midwest counties, the trend of design values in Figure 6 

indicates that the secondary visibility index level of 28 dv may be controlling compared with the 24-hour PM2.5 level 

in some cases. However, the main driver of the behavior in the Industrial Midwest (i.e., large amounts of sulfate 

PM2.5) is projected to be substantially reduced in coming years due to emissions controls associated with planned 

national rules. 

Overall, design values based on 2008-2010 data suggest that counties that attain the 24-hour PM2.5 NAAQS 

would attain the proposed secondary PM2.5 visibility index NAAQS level of 30 dv and generally attain the level of 

 

7

For instance, annual PM2.5 design values for Cuyahoga, Jefferson, and Clark counties exceed the annual level of 12 

g m-3and Elkhart has an annual design value equal to 12 g m-3
18

28 dv. The Industrial Midwest counties where this behavior does not hold at the lower secondary standard level of 

28 dv will experience visibility improvements due to regional emission controls planned as part of national rules and 

due to potential annual PM2.5 NAAQS violations. Therefore the comparison of design values for the 24-hour and 

proposed secondary PM2.5 NAAQS provides support for using the 24-hour PM2.5 NAAQS as a surrogate for the 

proposed secondary visibility index NAAQS in NSR/PSD applications. Specifically, the results indicate that a 

cumulative impact analysis that demonstrated that a source does not cause or contribute to a violation of the 24-hour

PM2.5 NAAQS would generally be suitable for demonstrating that a source does not cause or contribute to a 

violation of the secondary visibility index NAAQS under current conditions.

Figure 6. Design values for 24-hour PM2.5 NAAQS and secondary visibility index NAAQS based on 24-hour 

average PM2.5 measurements from 2008 to 2010 for sites that meet the current and/or proposed data completeness 

criteria of 40 CFR Part 50, Appendix N, for the 24-hour PM2.5 NAAQS and the 28-dv visibility index NAAQS.

8

 

8 Quadrants in the figure are based on design values of 35.5 g m-3

, 28.5 dv, and 30.5 dv (rather than 35 g m-3, 28

dv, and 30 dv, respectively) to reflect rounding conventions. 
19

Figure 7. Map of exceedance counties for the 24-hour PM2.5 NAAQS and secondary visibility index NAAQS level 

of 28 dv based on 24-hour average PM2.5 measurements from 2008 to 2010.

Figure 8. Distributions of the (a) fraction of PM2.5 composition that is nitrate and sulfate, (b) RH adjustment factor,

and (c) 90th-to-98th percentile mass ratios for U.S. regions defined in Figure 2 (NE=Northeast, SE=Southeast, 

IM=Industrial Midwest, UM=Upper Midwest, SW=Southwest, NW=Northwest, SC=Southern California, U.S.=all 

U.S. regions).
20

Appendix A. Development of PM2.5 Concentration Profiles from Emission Source Profiles, Distributions of 

RH adjustment factors, and Annual Design Values.

To estimate PM2.5 concentration profiles that could potentially correspond to direct-PM2.5 emissions, PM2.5

emission source profiles developed by Reff et al. (2009)9 were used. Stationary sources relevant to PSD regulations 

include coal fired boilers, coal fired EGUs, refineries, pulp and paper operations, biomass boilers, and other 

potentially large emission sources. Median profiles for these and other sources that emit significant amounts of 

PM2.5 and primary sulfates were selected from Reff et al. (2009) to represent a wide range of possible direct-PM2.5

emissions. Emission source profiles for the 24 categories considered are given in Table A.1. Note that controlled 

and uncontrolled EGUs/boilers are not distinguished because the compositing process used by Reff et al. (2009) 

tends to lump this information together in arriving at a median value. 

In Table A.1, organic mass (OM) is 1.4 times the organic carbon (OC) proportion of the PM2.5 source 

profile. “Crustal” represents the sum of all non-sulfur elements plus the estimated oxides of the metals (Reff et al., 

2009). “Other” represents unmeasured components and/or measurement uncertainty and includes water and 

ammonium. The “other” category is a significant percentage of the total PM2.5 for many of the source categories in 

Table A.1. Primary emissions of elemental carbon, sulfate, and nitrate are represented by labels “pec”, “pso4”, and 

“pno3”, respectively.

To perform source-specific visibility calculations, characteristic direct-PM2.5 concentration profiles were

developed using the emission source profiles in Table A.1. First, the fractions of primary sulfate and nitrate

emissions were scaled by factors of 1.375 and 1.29, respectively, under the assumption that they are fully neutralized 

by ammonium. Next, the resulting component fractions for pec, OM, pso4, pno3, and Crustal were normalized by 

dividing by a total fraction, which was the sum of these component fractions. The component percentages resulting 

from this procedure are listed in Table 2. Note that hydration of the pso4 and pno3 components was not considered 

in developing the profiles in Table 2 even though PM2.5 would contain some adsorbed water in a PM2.5 Federal 

Reference Method measurement.

10

 Hydration was excluded for the sake of clarity, and this exclusion enhances the 

conservative nature of the visibility calculations. For instance, if hydration of pno3 and pso4 had been considered, 

the PM2.5 component percentages in Table 2 would sum to less than 100%, and visibility impairment for a given 

amount of PM2.5 would be reduced accordingly. Finally, note that the normalization procedure effectively allocates 

 

9 Reff A., Bhave P.V., Simon H., Pace T.G., Pouliot G.A., Mobley J.D., and Houyoux M. (2009) Emissions 

inventory of PM2.5 trace elements across the United States. Environmental Science & Technology 43, 5790-5796. 

10 Frank N. (2006) Retained nitrate, hydrated sulfates, and carbonaceous mass in Federal reference method PM2.5 for 

six eastern US cities. Journal of the Air and Waste Management Association 56, 500‐511.
21

unknown PM2.5 emissions proportionally among the five components: pec, OM, pso4, pno3, and Crustal. Therefore 

PM2.5 concentration profiles for categories with large “other” emissions (e.g., industrial manufacturing, petroleum 

industry, and residual oil combustion) tend to have large sulfate fractions and are large contributors to visibility 

impairment under high-RH conditions based on this approach.

Table A.1. Stationary source profiles of directly-emitted PM2.5.

Species pec OM pno3 pso4 Crustal PM2.5 other

Aluminum Production 2.3% 5.5% 0.4% 4.4% 64.4% 78.0% 22.0%

Asphalt Manufacturing 5.7% 6.1% 0.1% 0.7% 60.0% 72.9% 27.1%

Asphalt Roofing 0.0% 84.4% 0.0% 0.1% 0.8% 85.8% 14.2%

Bituminous Combustion 1.7% 3.7% 0.2% 12.7% 35.3% 56.4% 43.6%

Cast Iron Cupola 0.9% 8.9% 0.5% 6.3% 81.9% 100.0% 0.0%

Catalytic Cracking 0.1% 0.0% 0.0% 32.7% 57.0% 98.1% 1.9%

Cement Production 2.9% 17.7% 4.7% 17.7% 49.8% 100.0% 0.0%

Construction Dust 0.0% 6.5% 0.0% 1.1% 51.9% 59.8% 40.2%

Distillate Oil Combustion 10.0% 35.0% 0.0% 19.0% 1.2% 65.2% 34.9%

Electric Arc Furnace 0.4% 4.5% 0.2% 2.2% 85.1% 92.5% 7.5%

Industrial Manufacturing - 

Avg 0.9% 10.3% 0.3% 9.9% 0.0% 23.7% 76.3%

Lignite Combustion 1.4% 39.8% 0.4% 7.6% 50.4% 100.0% 0.0%

Lime Kiln 2.3% 9.3% 0.6% 37.0% 49.5% 98.7% 1.3%

Natural Gas Combustion 38.4% 34.6% 2.1% 8.6% 0.0% 83.7% 16.3%

Open Hearth Furnace 0.0% 28.0% 0.6% 40.0% 19.0% 87.5% 12.5%

Petroleum Industry - Avg 0.0% 4.9% 0.3% 23.5% 0.0% 34.3% 65.7%

Process Gas Combustion 14.6% 42.2% 2.4% 16.6% 16.7% 100.0% 0.0%

Pulp \& Paper Mills 0.1% 0.0% 0.0% 50.6% 36.8% 87.4% 12.6%

Residential Coal Combustion 24.0% 62.8% 0.3% 3.3% 8.2% 100.0% 0.0%

Residential Natural Gas 

Combustion 6.7% 68.6% 3.4% 12.6% 8.3% 100.0% 0.0%

Residual Oil Combustion 1.0% 1.4% 0.0% 44.0% 0.7% 47.1% 52.9%

Solid Waste Combustion 1.5% 11.8% 1.4% 6.8% 44.5% 74.3% 25.7%

Sub-Bituminous Combustion 4.3% 4.4% 0.1% 10.2% 43.2% 62.5% 37.5%

Wood Fired Boiler 3.7% 49.2% 0.0% 6.5% 40.6% 100.0% 0.0%

In visibility calculations with the “original” IMPROVE algorithm (Equation 1), relative humidity 

adjustment factors, f(RH), are used to convert dry extinction values for sulfate and nitrate to ambient extinction

values.

11,12 Distributions of monthly average climatological f(RH) are given in Figure A.1. In Figure A.2, a 

comparison of annual PM2.5 design values with secondary visibility index design values is provided.

 

11 http://vista.cira.colostate.edu/improve/Tools/humidity_correction.htm

12 http://vista.cira.colostate.edu/improve/Publications/GuidanceDocs/guidancedocs.htm
22

Figure A.1. Distributions of climatological monthly average RH adjustment factor, f(RH)

Figure A.2. Three-year design values for annual PM2.5 NAAQS and secondary visibility index NAAQS based on

PM2.5 measurements from 2008 to 2010 for sites that meet the current and/or proposed data completeness criteria of 

40 CFR Part 50, Appendix N, for the annual PM2.5 NAAQS and the 28-dv visibility index NAAQS.