1

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

Research Triangle Park, NC 27711

June 15, 2012

MEMORANDUM

TO: EPA Docket # EPA-HQ-OAR-2007-0492

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

II. Policy Background

PSD applicants are currently required to demonstrate that they do not cause or contribute to a violation of

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

precursors.

1 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

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.
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and further technical analyses, the EPA intends to issue final guidance by the end of calendar year 2012.

The 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 this procedure with ambient PM2.5 speciation measurement

data (available through the Chemical Speciation Network, CSN, and the Interagency Monitoring of Protected Visual

Environments, IMPROVE, network) and climatological relative humidity (RH) data.

As noted in the overview section, certain technical issues currently prevent modeled determinations of the

visibility impairment that would result from a new or modified source. The relevant 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, some prospective PSD sources could be required to collect new data in order to

determine the representative background concentrations of the PM2.5 species 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
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concentration would produce a comparably small increase in visibility impairment. This analysis included estimates

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 ambient 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 aspect of the 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 the

proposed level of 35 μg/m3for the 24-hour PM2.5 standard and for illustrative purposes an alternative standard level

of 12 g/m3for the annual PM2.5 standard together with the proposed levels of 28 or 30 dv for the secondary PM2.5

visibility index standard in conjunction with 24-hour averaging time and a 90th percentile form. The results indicate

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.

3

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 (FLMs)—the federal officials

with direct responsibility for management of Federal Class I parks and wilderness area—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

3 The relationships between design values as characterized here are dependent on the specific level and form of each

of the standards
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AQRV assessments under the PSD program.

III. Technical Background

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

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, 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 ext b

VI ln

,

(2)

where units are in dv. 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)

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

4

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

atmosphere and is expressed in Mm-1(inverse megameter) units.
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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. The results shown in Figure 1b

indicate that the 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 the

results for the 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

Figure 2. Definition of U.S. regions5considered in this analysis.

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

(a) (b)

6

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. The results shown in Figure 1b

indicate that the 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 the

results for the 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

Figure 2. Definition of U.S. regions5considered in this analysis.

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

(a) (b)

6

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. The results shown in Figure 1b

indicate that the 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 the

results for the 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

Figure 2. Definition of U.S. regions5considered in this analysis.

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

(a) (b)
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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 the 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 air quality impact analysis uses a SIL in determining whether a source’s

modeled impact on air quality for a particular pollutant is considered significant6. 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 corresponding increases in ambient PM2.5 concentration and visibility index values for ambient conditions

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

6 The EPA defined SILs for PM2.5 in a final rule issued on October 20, 2010. See, 75 FR 64864. SILs for other

pollutants are defined at 40 CFR 51.165(b)(2).

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
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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 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 values associated with a 1 g m-3increase in PM2.5 concentration for lowand 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 hydration7. 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

7

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

[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 the 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 the visibility index are comparably small to a 1 g m-3increase in PM2.5

concentration for ambient conditions near the proposed secondary standard 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
10

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

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 the proposed levels of either 28 or 30 dv8.

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. 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.

8

In the context of AQRV protection including Class I visibility relative to natural background conditions, similar

changes in light extinction could approach or exceed thresholds of concern to FLMs.
11

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 calculation9.

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-

9 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 violations10 are 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

10 For instance, PM2.5 design values for the annual standard for Cuyahoga, Jefferson, and Clark counties exceed the

alternative standard 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.

11

11 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.

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.

11

11 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.

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.

11

11 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).

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).

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)12 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.

13 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

12 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.

13 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%

Pe troleum 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 \& Pape r 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 Boile r 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.

14,15 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.

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

15 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.

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.

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.