Technical Guidance on Tracking Visibility Progress 

for the Second Implementation Period of the 

Regional Haze Program

EPA-454/R-18-010 

December 2018

Technical Guidance on Tracking Visibility Progress for the Second Implementation Period 

of the Regional Haze Program

U.S. Environmental Protection Agency

Office of Air Quality Planning and Standards

Air Quality Assessment Division

Research Triangle Park, North Carolina
Table of Contents

1.0 Purpose of this guidance ......................................................................................................... 1

1.1 Regional Haze Background............................................................................................... 2

1.2 Statutory Provisions and Regulatory Requirements........................................................ 2

2.0 Ambient Data Analysis............................................................................................................. 4

2.1 Recommendations for estimating daily natural and anthropogenic visibility fractions 

and light extinction budgets and calculating the 20% most impaired and 20% clearest 

days.................................................................................................................................. 5

2.2 Calculating the baseline, current, and natural visibility conditions............................... 14

3.0 Adjustment of the Uniform Rate of Progress for Impacts from International Anthropogenic 

Emissions............................................................................................................................... 17

3.1 URP Adjustment in the Regional Haze Rule................................................................... 17

3.2 Year Selection for Estimating International Contribution ............................................. 18

3.3 Estimating the Anthropogenic International Visibility Impacts..................................... 20

3.4 EPA Review of an International URP Adjustment.......................................................... 22

References .................................................................................................................................... 24

APPENDIX A................................................................................................................................... 26

APPENDIX B................................................................................................................................... 28
1 

1.0 Purpose of this guidance

The purpose of this guidance document is to support states in the development of regional 

haze state implementation plans (SIPs) to protect visibility in certain national parks and 

wilderness areas, known as mandatory Class I Federal areas,1 in particular the SIPs that are due 

to be submitted to the Environmental Protection Agency (EPA) by July 31, 2021, for the second 

implementation period. The required content of these SIPs is specified in 40 CFR 51.308(f), 

which was revised in 2017.2 As called for in the agency’s “Regional Haze Reform Roadmap” 

(September 11, 2018), this guidance document describes EPA’s recommended methods on two 

aspects of the regional haze program: 

1) Visibility Tracking Metrics: The 2017 Regional Haze Rule revisions require a revised 

approach to tracking visibility improvements over time within the Uniform Rate of 

Progress (URP) framework.

3 Under these 2017 Regional Haze Rule revisions, in the 

second and future implementation periods, states must select the “20 percent most 

impaired days” each year at each Class I area based on daily anthropogenic 

impairment.4 This guidance document describes a recommended methodology to 

develop the baseline and current visibility conditions, and natural conditions on the 

most impaired and clearest days.

2) International Emissions: The 2017 Regional Haze Rule includes a provision that allows 

states to propose an adjustment to the URP to account for impacts from anthropogenic 

sources outside the United States, if the adjustment has been developed through 

scientifically valid data and methods. This guidance document describes recommended 

tools and methods to develop optional adjustments to the URP endpoint to account for 

international anthropogenic emissions impacts.

This document provides recommendations on these two aspects of SIP development under the 

Regional Haze Rule and is for use by states in developing SIP submissions and for EPA Regional 

offices in acting on them. This document does not substitute for provisions or requirements of 

the Clean Air Act (CAA), nor is it a rule itself. Thus, it does not impose binding, enforceable 

requirements on any party. States retain the discretion to develop regional haze SIP revisions 

that differ from this guidance so long as they are consistent with the CAA and the implementing 

regulations – a core principle of cooperative federalism.

 

1

For brevity, mandatory Class I Federal areas will often be referred to as “Class I areas” in the remainder of this 

document.

2

Final Rule: Protection of Visibility: Amendments to Requirements for State Plans, 82 FR 3078, January 10, 2017.

3

“URP framework” refers to the interrelated Regional Haze Rule requirements regarding the quantification of 

historical and projected visibility conditions using specific metrics, the quantification of natural conditions, the 

quantification of the uniform progress that would achieve natural visibility conditions for the 20 percent most 

anthropogenically impaired days in 2064, the URP glidepath, the setting of reasonable progress goals (RPGs) for 

the end of the implementation period, and the comparison of the RPG for the 20 percent most anthropogenically 

impaired days to the URP glidepath.

4

Previously, states and EPA tracked visibility progress on the 20 percent worst visibility days.
2 

EPA generally expects that SIPs which follow this guidance are likely to meet the related 

applicable statutory and regulatory requirements. Final decisions by EPA to approve a particular 

SIP revision can only be made based on the requirements of the statute and the Regional Haze 

Rule, and on whether the SIP submission is the product of reasoned decision making. In 

addition, final EPA decisions can only be made following a state’s final submission of the SIP 

revision to EPA in accordance with all applicable requirements, including appropriate notice and 

opportunity for public review and comment. Only final actions taken to approve or disapprove 

SIP submissions would be final actions for purposes of CAA section 307(b). Therefore, this 

guidance is not judicially reviewable. This guidance does not change or substitute for any law, 

regulation, or other legally binding requirement and is not legally enforceable. Due to casespecific circumstances, following the recommendations in this document does not ensure that 

the related aspects of a SIP will be approvable in all instances, as this guidance may not apply to 

the facts and circumstances underlying a particular SIP.

We encourage states to discuss with their EPA Regional office early in their SIP development 

the approach they anticipate taking and how the interpretations and recommendations in this 

guidance may relate to their SIPs. 

1.1 Regional Haze Background

Consistent with the CAA, “regional haze” is defined at 40 CFR 51.300 as “visibility impairment 

that is caused by the emission of air pollutants from numerous anthropogenic sources located 

over a wide geographic area. Such sources include, but are not limited to, major and minor 

stationary sources, mobile sources, and area sources.” This visibility impairment is a result of 

anthropogenic particles and gases in the atmosphere that scatter and absorb (i.e., extinguish) 

light, thus acting to reduce overall visibility. The primary cause of regional haze is light 

extinction by particulate matter (PM). For purposes of the Regional Haze Rule, light extinction is 

estimated from measurements of PM and its chemical components (sulfate, nitrate, organic 

mass by carbon (OMC), light absorbing carbon (LAC), fine soil (FS), sea salt, and coarse material 

(CM)), assumptions about relative humidity at the monitoring site, and the use of a commonly 

accepted algorithm (Pitchford, et al., 2007). These estimates of light extinction are 

logarithmically transformed to deciview units. The Regional Haze Rule established the deciview 

haze index as the principal metric for expressing visibility on any particular day. The deciview 

haze index is calculated from light extinction values and expresses uniform changes in the 

degree of haze in terms of common increments across the entire range of visibility conditions, 

from pristine to extremely hazy.

The PM measurements used in the regional haze program are collected by the IMPROVE 

(Interagency Monitoring for PROtected Visual Environments) monitoring network. The Regional 

Haze Rule requires states to submit a series of SIPs to protect visibility in Class I areas. 

1.2 Statutory Provisions and Regulatory Requirements

In section 169A of the 1977 Amendments to the CAA, Congress established a program for 

protecting and restoring visibility in certain national parks, wilderness areas, and other Class I 
3 

areas due to their “great scenic importance.”5 This section of the CAA establishes as a national 

goal the “prevention of any future, and the remedying of any existing, impairment of visibility in 

Class I areas which impairment results from manmade air pollution.” This section also required 

EPA to issue regulations requiring states to adopt implementation plans containing emission 

limits as may be necessary to make reasonable progress towards meeting this goal. 

In 2017, EPA issued a final rule revising portions of the visibility protection rule promulgated in 

1980 and the Regional Haze Rule promulgated in 1999.6 The revised rule covers EPA’s review of 

periodic SIPs developed for the second and subsequent implementation periods, among other 

requirements. 

The Regional Haze Rule established the concept of state-set reasonable progress goals (RPG) for 

the 20 percent most anthropogenically impaired days as a regulatory construct promulgated to 

implement the statutory requirements for visibility protection. These RPGs reflect the visibility 

conditions that are projected to be achieved by the end of the applicable implementation 

period as a result of its own and other states’ long-term strategies, as well as the 

implementation of other requirements of the CAA.

The 2017 Regional Haze Rule requires states to determine the baseline (2000-2004) visibility 

condition for the 20 percent most impaired days and requires that the long-term strategy and 

RPG must provide for improvement in visibility for the most impaired days, relative to the 

baseline period. Specifically, states must determine the rate of improvement in visibility that 

would need to be maintained during each implementation period in order to reach natural 

conditions by 2064 for the 20 percent most impaired days, given the starting point of the 2000-

2004 baseline visibility condition.

7 The “glidepath,” or URP, is the amount of visibility 

improvement that would be needed to stay on a linear path from the baseline period to natural 

conditions. 

The URP is calculated according to the following formula:

URP = [(2000-2004 visibility)20% most impaired - (natural visibility)20% most impaired]/60 (Eqn. 1)

An example diagram of the URP (in this case for GRSM1 in Great Smoky Mountains National 

Park) for the entire 2000-2064 period is shown in Figure 1. In this diagram, the URP (orange 

line) connects the 2000-2004 baseline period with the 2064 endpoint at the estimate of natural 

visibility conditions. 

 

5

H.R. Rep. No. 294, 95th Cong. 1st Sess. at 205 (1977).

6

45 FR 80084 (December 2, 1980) and 64 FR 35714 (July 1, 1999) 7

See 40 CFR 51.308(f)(1).
4 

Figure 1. Example diagram showing the important parameters used to calculate the visibility 

metrics for the Regional Haze Rule

The 2017 Regional Haze Rule also requires states to determine the baseline (2000-2004) 

visibility condition for the 20 percent clearest days and requires that the long-term strategy and 

RPG ensure no degradation in visibility for the clearest days since the baseline period.

2.0 Ambient Data Analysis

Among the requirements described in 40 CFR 51.308(f)(1)(i)-(vi), states must calculate the 

following tracking metrics using available ambient monitoring data (states typically use data 

collected by the IMPROVE monitoring program):

• Baseline, current, and natural visibility conditions for the 20 percent most 

anthropogenically impaired and 20 percent clearest days. These six conditions must 

be quantified in deciviews.

• The URP between the baseline visibility condition for the most impaired days and 

the natural visibility condition for the most impaired days. The URP must be 

quantified as the visibility improvement (in deciviews per year) that would need to 

be maintained during each implementation period in order to attain natural visibility 

conditions by 2064. The rule also allows states to propose an optional adjustment to 

the URP to account for impacts from anthropogenic sources outside the U.S. and 

from certain wildland prescribed fires.

The 1999 rule text defined “most impaired days” and “least impaired days” by referring to 

highest and lowest levels of “visibility impairment” caused by manmade air pollution. The 1999 

final rule preamble stated that the least and most impaired days were to be selected as the 

monitored days with the lowest and highest actual deciview levels, respectively, without 
5 

distinguishing between the natural and anthropogenic contributions to reduced visibility.8 In 

2003, EPA issued guidance describing in detail the steps for selecting and calculating light 

extinction on the “worst” and “best” visibility days (EPA, 2003a). Consistent with the 1999 final 

rule preamble, the 2003 guidance recommended that states determine the most and least 

impaired days based on which days had the highest and lowest overall deciview values, rather 

than determining and selecting the days with the highest and lowest anthropogenic 

impairment. However, because natural haze due to wildfires or dust storms can be larger than 

anthropogenic impairment for some Class I areas (particularly in the western U.S.), this 

approach resulted in some days with large natural sources of haze being included in the 20 

percent most impaired days metric.

The 2017 Regional Haze Rule defines visibility impairment or anthropogenic visibility 

impairment as “any humanly perceptible difference due to air pollution from anthropogenic 

sources between actual visibility and natural visibility on one or more days. Because natural 

visibility can only be estimated or inferred, visibility impairment also is estimated or inferred 

rather than directly measured.”9 In this definition, the Regional Haze Rule’s definition of 

visibility impairment is synonymous with anthropogenic impairment. A metric that reflects both 

the fraction of the actual light extinction that is above natural levels (in Mm-1) as well as the 

logarithmic relationship between light extinction and perceived visibility is, thus, a logical basis 

for selecting the 20 percent most anthropogenically impaired days. One such metric is the 

difference (the “delta deciviews”) between the total deciview value that exists (or is projected 

to exist) and the deciview value that would have existed if there were only natural sources 

causing reduced visibility. This is the metric that EPA recommends be used. We recommend 

that states use Equation 2 to calculate anthropogenic visibility impairment:

∆ dvanthropogenic visibility impairment = dvtotal-dvnatural (Eqn. 2)

where dvtotal is the overall deciview value for a day, and dvnatural is the natural portion of the 

deciview value for a day The Regional Haze Rule does not specify how dvtotal and dvnatural are to 

be determined; that is the subject of some of EPA’s recommendations in this document.

2.1 Recommendations for estimating daily natural and anthropogenic visibility fractions 

and light extinction budgets and calculating the 20% most impaired and 20% 

clearest days

The first step in determining dvnatural is to split the daily light extinction into natural and 

anthropogenic fractions. Because these are not directly measured, a statistical or 

computational method must be used to estimate these fractions. This guidance document 

presents EPA’s current recommendation for estimating these fractions; data for this 

recommended approach, as well as the results of applying the recommended approach,

10 will 

 

8

See 64 FR 35728. 9

See 40 CFR 51.301. 10A state that wishes to follow the EPA-recommended approach may download these completed results and will 

not have to itself execute the 7 steps discussed in this section. These completed results are available at 

http://vista.cira.colostate.edu/Improve/rhr-summary-data. 
6 

be provided by the IMPROVE program to states for their use on an annual basis. EPA may 

provide refinements to this method or additional recommended methods through additional 

guidance as such methods become available.

In general, the recommended approach to splitting daily light extinction into natural and 

anthropogenic fractions is to estimate the natural contribution to daily light extinction and then 

attribute the remaining light extinction to anthropogenic sources. The natural contributions are 

grouped into two types – “episodic” and “routine.” Episodic natural contributions are those 

that occur relatively infrequently. These may differ in number and size from year to year and 

likely result from extreme events. Routine natural contributions are those that occur on all or 

most days in a year or season and are more consistent from year to year. Large wildfires and 

strong dust storms are examples of episodic natural contributions from extreme events, while 

biogenic secondary aerosol is an example of a routine natural contribution.11 It is useful to 

make this distinction because the values used by most states in the first implementation period 

to represent natural visibility conditions, the “NC-II” estimates,12 are generally recognized as 

representing long-term averages influenced by routine natural sources but not episodic natural 

sources (EPA, 2003b). As explained below, the annual average NC-II estimates are used in the 

recommended method described in this section, but in a manner that is consistent with the 

premise that they represent only the influences of routine natural sources.

The recommended steps (1 through 7) to estimate natural and anthropogenic light extinction 

and the 20 percent most impaired days for the year are detailed below, using an example for 

Mesa Verde National Park (MEVE1). Note that the values throughout this example are unique 

to MEVE1 and have been included for illustrative purposes only. Each Class I area is treated 

individually, and these values do not apply to any site other than MEVE1. A flow chart 

summarizing these steps is shown in Figure 2.

 

11The EPA recognizes that natural emissions can also include volcanic emissions. The approach described in this 

guidance document does not attempt to account for haze formed from natural volcanic emissions. We encourage 

states with Class I areas affected by volcanic emissions to work with their EPA Regional office to determine an 

appropriate approach for determining which days are the 20 percent most anthropogenically impaired days.

12“NC-II” refers to a set of estimates of natural conditions for each Class I area contained in Regional Haze Rule 

Natural Level Estimates Using the Revised IMPROVE Aerosol Reconstructed Light Extinction Algorithm, available at 

http://vista.cira.colostate.edu/improve/publications/graylit/032_NaturalCondIIpaper/Copeland_etal_NaturalCondi

tionsII_Description.pdf. As called for in the agency’s “Regional Haze Reform Roadmap” (September 11, 2018, the 

agency may be updating the natural visibility conditions estimates in spring 2019, as necessary.
7 

Figure 2. Flow chart of the 7 steps involved in calculating the 20% most impaired days.

Step 1: Establish light extinction thresholds to identify extreme events

Analysis from the first implementation period showed that smoke from wildfires (mainly 

composed of OMC and LAC) and dust storms (mainly composed of CM and FS) are major 

contributors to light extinction at many Class I areas (Tombach, 2008). For each Class I area, 

using data from the IMPROVE monitor associated with the area, identify for each year the 95th

percentile 24-hour carbon (OMC + LAC) light extinction (Spracklen, et al., 2007) (Jaffe, et al., 

2008). Choose the year between 2000 and 2014 with the lowest such value. This year 

represents the “low wildfire” year of this period. Also, choose the year with the lowest 95th

percentile 24-hour dust (CM + FS) light extinction. This year represents the “low dust storm” 

year of this period. The 95th percentile carbon and dust values for these years will serve as the 

threshold values used to identify impacts on carbon and dust light extinction from extreme 

episodic events in that year and other years. At Class I areas where episodic influences vary 

significantly from year to year, it will not be unusual for more than five percent of the 

monitored days to be affected by extreme episodic events in years other than the “low 

wildfire” and “low dust storm” years. Thus, this approach allows a different number of high 

carbon days or high dust days in different years to be identified as ones with extreme episodic 

impacts, but all the days that are identified will have carbon or dust concentrations at least as 

high as the respective threshold. EPA believes this method for calculating threshold values for 

identifying episodic light extinction is reasonable and practical to apply to the large set of 

IMPROVE data, and our investigations have indicated that the results (i.e., the days selected as 

the 20 percent most impaired) would not be substantially different if slightly different 

percentile values were used for this purpose. However, some areas with a high frequency of 

episodic wildfire smoke or dust impacts even in the “low wildfire” or “low dust storm year” 

could use a lower percentile value. At other sites, the year representing the lowest wildfire or 

dust storm thresholds may have no episodic impacts and such sites could use a higher 
8 

percentile value. States may use other reasonable thresholds for determining impacts from 

extreme natural events if they explain why another method is appropriate for their individual 

Class I areas.

The 95th percentile value will be the 0.95×n measured value sorted from lowest to highest. If 

0.95×n is not an integer value, the 95th percentile value is the monitored value such that it and 

all lower values are more than 95 percent of the sample. For MEVE1 in 2003, there were 105 

complete values for carbon. For MEVE1 in 2003, 0.95×105 is 99.75, so the 95th percentile value 

would be the 100th value counting up from the lowest value, out of 105 (the sixth value 

counting down from the highest value). In 2003, the 100th highest carbon value is 25.36 Mm-1. 

Repeat this process to get a 95th percentile value for each year from 2000 to 2014 for carbon 

and dust. The results for each of these years for MEVE1 are shown in Table 1. 

Table 1. 95th percentile values for carbon and dust light extinction (in units of Mm-1) from 

2000-2014 at MEVE1.

Year Annual 95th percentile carbon 

light extinction 

Annual 95th percentile dust 

light extinction

2000 12.68 7.732

2001 7.002 6.686

2002 16.14 19.60

2003 25.36 16.45

2004 5.937 5.498

2005 9.640 5.658

2006 7.813 5.326 (lowest)

2007 11.72 5.685

2008 7.545 9.257

2009 10.55 10.35

2010 7.109 13.30

2011 5.289 9.726

2012 10.66 8.930

2013 5.396 8.223

2014 5.054 (lowest) 9.281

The years 2014 and 2006 have the lowest carbon and dust 95th percentile values for MEVE1, 

respectively. The year 2014 was in this sense the “low wildfire” year at MEVE1, such that the 

95th percentile value for carbon in 2014 becomes the threshold for identifying extreme wildfireaffected days in any year, with the same concept applying to dust from natural sources and the 

year 2006. The 95th percentile value of carbon in 2014 was 5.054 Mm-1, and the 95th percentile 

value of dust in 2006 was 5.326 Mm-1. National maps of the light extinction thresholds to 

identify extreme carbon and dust events are shown in Figures 3 and 4. 
9 

Figure 3. Site-specific extinction thresholds of carbon from extreme episodic events

Figure 4. Site-specific extinction thresholds of dust from extreme episodic events
10 

Step 2: Assign the portions of daily carbon and dust light extinction that are in excess of these 

thresholds to “natural (episodic)”

The IMPROVE light extinction data for a specific day (May 12, 2003) at MEVE1 are shown in 

Table 2. The light extinction from carbon (25.36 Mm-1) on this day is greater than the threshold 

of 5.054 Mm-1. Therefore, 25.36 minus 5.054 or 20.31 Mm-1 is assigned to natural (episodic).

Carbon light extinction in the amount of 5.054 Mm-1 remains to be split between natural 

(routine) and anthropogenic in Step 4 below, after the combined value of carbon is reallocated 

to OMC and LAC (Step 3). The dust-related light extinction of 2.699 Mm-1 is less than the 

threshold value of 5.326 Mm-1, therefore no dust-related light extinction is assigned to natural 

(episodic). However, the 2.699 Mm-1 value for dust-related light extinction does need to be split 

between natural (routine) and anthropogenic in Step 4 below, after the combined value of dust 

is reallocated to FS and CM (Step 3). A summary of the episodic thresholds and the light 

extinction assigned to natural (episodic) is shown in Table 2.

Step 3: Reallocate the daily combined carbon and dust light extinction remaining after 

assigning values over the threshold values to “natural (episodic)” into OMC, LAC, FS, and CM. 

Separate the combined carbon back into OMC and LAC and separate the combined dust back 

into FS and CM based on the original percentages of the individual PM species to the grouped 

light extinction. For example, at MEVE1 on May 12, 2003, the total carbon light extinction was 

25.36 Mm-1, with OMC light extinction of 21.78 and LAC Mm-1 light extinction of 3.576 Mm-1. 

The total dust light extinction was 2.699 Mm-1 with 1.141 Mm-1 from FS and 1.558 Mm-1 from 

CM. Therefore, on May 12, 2003, carbon light extinction was 85.88 percent from OMC and 

14.10 percent from LAC; dust light extinction was 42.27 percent from FS and 57.72 percent 

from CM. Separate the estimates of natural (episodic) and the remaining light extinction from 

carbon back into OMC and LAC and the remaining light extinction from dust back into FS and 

CM, using these percentages. Table 2 shows the results of these calculations for this example 

day at MEVE1. For example, of the 20.31 Mm-1 of carbon assigned to natural (episodic), 17.44 

Mm-1 (or 85.88 percent) is reallocated to OMC and 2.864 Mm-1 (14.10 percent) is reallocated to 

LAC. States may use other approaches than the one recommended here.
11 

Table 2. Total and speciated light extinction (in units of Mm-1) for an example day (May 12, 

2003) at MEVE1

PM Species Total Light 

Extinction 

Threshold Light extinction 

associated with 

natural (episodic)

Light extinction 

remaining after 

episodic treatment

Sulfate 2.963 NA 0 2.963

Nitrate 0.8055 NA 0 0.8055

Carbon 

(OMC + LAC)

25.36

(21.78 + 3.576)

5.054 20.31

(17.44 + 2.864)

5.054

(4.340 + 0.7126)

Dust 

(FS + CM)

2.699

(1.141 +1.558)

5.326 0 2.699

(1.141 +1.558)

Sea salt 0.001469 NA 0 0.001469

Rayleigh 9.0 NA 0 9.0

TOTAL 40.83 NA 20.31 20.52

Step 4: Split the remaining components of light extinction into natural (routine) and 

anthropogenic based in part on the NC-II estimates (Copeland, et al., 2008). 

In order to split the remaining components of light extinction into natural (routine) and 

anthropogenic components, we recommend allowing the natural (routine) to vary daily based 

on the NC-II estimates weighted by the ratio of the light extinction remaining after removing 

episodic contributions to the non-episodic annual average extinction. At most Class I areas, the 

use of this ratio results in higher natural (routine) values in the summer and lower values in the 

winter.

Starting with the daily results from Step 3 for all days with complete data in a year, calculate 

the annual average light extinction values for each PM species, excluding light extinction 

already attributed to episodic events. The non-episodic annual averages for 2003 at MEVE1 are

shown in Table 3. 

For all PM species except sea salt (which is treated as entirely natural (routine)), use the 

existing NC-II annual average natural light extinction values (which are distinct from the “p90” 

values), the daily light extinction values, and the annual averages for the site (for both, 

excluding the light extinction already attributed to episodic events) to calculate a daily estimate 

of natural (routine). These three input values appear in Table 3 for the May 12, 2003, MEVE1 

example. (Table 3 is not intended to show a calculation using these values. The way these input 

values are used to complete the calculation of anthropogenic versus natural light extinction for 

a given day is described below the table.)
12 

Table 3. The remaining light extinction at MEVE1 on May 12, 2003 (in units of Mm-1), after 

applying thresholds to allocate some light extinction to natural (episodic). The NC-II average 

light extinction estimates and the 2003 annual average light extinction excluding the episodic 

light extinction are also shown.

PM 

species

Light extinction 

remaining after 

episodic 

treatment (Step 3)

NC-II 

average 

natural light 

extinction

2003 annual 

average nonepisodic light 

extinction

Natural 

(routine) light 

extinction 

(Step 4)

Anthropogenic

light extinction 

(Step 5) 

Sulfate 2.963 0.5741 4.103 0.4146 2.548

Nitrate 0.8055 0.5829 1.599 0.2936 0.5119

OMC 4.340 1.831 3.194 2.489 1.851

LAC 0.7126 0.2 0.8624 0.1653 0.5467

FS 1.141 0.5 0.8793 0.6490 0.492

CM 1.558 1.726 2.351 1.144 0.4140

Sea salt 0.001469 0.01822 0.02806 0.001469 0

Rayleigh 9.000 9.000 9.000 9.000 0

TOTAL NA NA NA 14.16 6.36

The calculation formula in Step 4 using daily and annual average inputs like those shown in 

Table 3 depends on whether, for a given PM species, the annual average light extinction value 

(excluding episodic events) for the particular year is greater than or less than the NC-II estimate 

of annual average natural light extinction. For a site and PM species with an annual average 

light extinction value (excluding episodic events) less than the NC-II estimate, all of the daily 

light extinction is assigned to natural (routine). This results in the natural (routine) light 

extinction being different each day, with the annual average being less than the NC-II estimate. 

For a site and PM species with an annual average light extinction value (excluding episodic 

events) greater than the NC-II estimate, the daily estimates of natural (routine) light extinction 

are calculated by multiplying the total daily light extinction for each species by the ratio of the 

NC-II annual average estimates and the annual average non-episodic light extinction. This 

results in the natural (routine) light extinction being different each day and the annual average 

of the daily estimates of natural (routine) light extinction equaling the NC-II annual average

value. The daily contributions to natural (routine) are calculated according to Equation 3: 

natural(routine)= daily extinction × NC-II estimate

non-episodic annual average (Eqn. 3) 

An example for the OMC light extinction on May 12, 2003, at MEVE1, using extinction values 

from Table 3, is shown below.

natural(routine)OMC= 4.340 × 1.831

3.194

= 2.489 Mm-1

Repeat this calculation for LAC, FS, CM, sulfate, and nitrate light extinction (not shown here).

States may use other reasonable methods for estimating routine natural and anthropogenic 

fractions if they explain why another method is appropriate for their individual Class I areas.
13 

Step 5: Consider the remaining light extinction from sulfate, nitrate, OMC, LAC, FS, and CM as

“anthropogenic.”

Starting with the daily total light extinction measured on each day, subtract the daily natural 

(episodic) and daily natural (routine) to find the daily anthropogenic light extinction attributable 

to each PM species and overall, i.e., the light extinction budget. For the May 12, 2003, MEVE1 

example, the daily total light extinction was 40.83 Mm-1, daily natural light extinction was 34.46

Mm-1 (20.31 episodic + 14.16 routine), and daily anthropogenic light extinction was 6.36 Mm-1

(see Tables 2 and 3). 

Step 6: Calculate anthropogenic impairment for each day using the daily estimates of natural 

and anthropogenic light extinction, according to Equation 2. 

For each day at the Class I area of interest, convert the daily total and natural light extinction to 

deciviews and calculate anthropogenic impairment according to Equation 2. At MEVE1, for May 

12, 2003, the anthropogenic impairment is calculated as:

∆ dvanthropogenic visibility impairment = 10 × ln

40.83

10 - 10 × ln

34.46

10

= 1.695 dv

Step 7: Sort each year’s days with complete data by the anthropogenic impairment value and 

choose the 20 percent most impaired days based on this value.

Perform these calculations for each day at the Class I area of interest, then rank the days within 

each year from high to low by anthropogenic impairment where a rank of 1 is the most 

impaired day (i.e., the day with the highest anthropogenic impairment value). At MEVE1, this 

day, May 12, 2003, with an anthropogenic impairment value of 1.695 deciviews, is a relatively 

low impairment day and was ranked 99 out of 105 total days with complete observations. 

Therefore, based on anthropogenic impairment, this day is not one of the 20 percent most 

impaired days for 2003.13 Average the deciviews of total haze on the 20 percent most impaired 

days for each year to obtain a single value for the associated visibility condition for each year 

(for MEVE1 in 2003, which had 105 complete observations, 21 days will be in the 20 percent 

most impaired).

States may choose alternative approaches for estimating natural and anthropogenic 

contributions to light extinction, but the Regional Haze Rule requires states to choose the 20 

percent most impaired days based on anthropogenic impairment. In other words, while Steps 1 

through 6 described above are EPA recommendations and states are not precluded from using 

other approaches to determine the anthropogenic impairment on each day, the Regional Haze 

Rule requires states to follow Step 7 as it is described here.

The 2017 Regional Haze Rule revisions introduced a new term for describing the days with the 

lowest light extinction and deciview values: clearest days. These days are not to be selected 

 

13In contrast, if ranking this day based on either total light extinction or overall visibility conditions (the ranking 

would be the same with these two metrics), as the EPA’s guidance for the first implementation period 

recommended, this day would be ranked 14 out of 105 days with complete observations and would be one of the 

20 percent of days with the haziest visibility conditions. 
14 

based on the lowest anthropogenic impairment (as referring to them as the 20 percent least 

impaired days as in the 1999 Regional Haze Rule would suggest). These will be the days with the 

lowest values of the deciview index. It is unnecessary to split the data into “natural” and 

“anthropogenic” fractions. Rather, the days are to be sorted for each year by total deciviews, 

and the 20 percent of days with the lowest deciviews are the 20 percent clearest days. When 

0.2 multiplied by the number of monitored days in a year with complete data is not an integer, 

an “extra” day should not be included in the set of clearest days, which means that the 

percentage of days in this set may be a value somewhat below 20 percent.

2.2 Calculating the baseline, current, and natural visibility conditions

The 2017 Regional Haze Rule continues to define the period for establishing baseline visibility 

conditions as 2000 to 2004 for the second and future implementation periods.14 Visibility 

conditions averaged over these 5 baseline years are the starting point for calculating the URP 

and drawing the URP line for all implementation periods of the Regional Haze Rule. It is 

important to note that in the 2017 Regional Haze Rule, the term “most impaired days” has a 

different meaning than EPA and states gave to that term in the first implementation period. The 

“baseline visibility condition (in deciviews) for the 20 percent most impaired days” in a state’s 

SIP submission for the second implementation period will likely have a different value than the 

baseline values used in SIPs for the first implementation period, even if there have been no 

revisions to the IMPROVE data for the 2000-2004 period. The differences will be largest at Class 

I areas impacted by fire and dust events in the baseline period. If a state chooses an alternative 

approach for estimating natural and anthropogenic contributions to light extinction, it is likely 

that the baseline visibility condition will have a different value than with the recommended 

approach.

The period for calculating current visibility conditions in the 2017 Regional Haze Rule is the 5-

year period ending with the most recently available data. Due to the laboratory, data analysis, 

and quality assurance procedures of the IMPROVE program, there is some delay between the 

date of the filter collection and the date the data are ready for use in analyses. Current visibility 

conditions must be calculated based on the annual average level of visibility impairment for the 

20 percent most impaired and the 20 percent clearest days. The current visibility condition for 

each set of days is the average of the valid annual values from the 5-year period ending with 

the most recently available data set as expressed in deciviews. Five years are averaged to 

account for variability in meteorology and emissions. Data completeness requirements for valid 

years are described in the 2003 Regional Haze Rule visibility tracking guidance (EPA, 2003a). 

Incomplete or missing data from some IMPROVE sites may require the combination or 

substitution of data from multiple IMPROVE sites for the ongoing visibility tracking of the 

Regional Haze Rule. The appropriate EPA Regional office should be consulted when data 

completeness issues arise. 

 

14It is recommended that the data for the 2000-2004 baseline period be refreshed prior to analysis due to periodic 

revisions in the methods for calculating ambient concentrations from measurements made on filters and for filling 

in missing or invalidated data.
15 

The URP framework requires states to determine a single value for the “natural visibility 

condition” for the 20 percent most impaired days. Given the inherent day-to-day variability of 

natural processes (e.g., windblown dust, fire, volcanic activity, biogenic emissions, etc.), it 

follows that even if there were no anthropogenic sources, visibility would not be constant and 

would vary day-to-day. Also, visibility due only to natural sources has never occurred in modern 

times and, therefore, has never been directly measured nor could it be directly measured. It 

must be estimated. Even if past natural conditions could be known with certainty, future 

natural conditions may be different. The steps for estimating natural and anthropogenic 

fractions of light extinction recommended in this guidance are based on estimates of natural 

visibility conditions for each monitored day in the past, with a given past day having the 

potential for both routine and episodic contributions to natural conditions. An additional step is 

needed to get the single value for the “natural visibility condition.” Under the Regional Haze 

Rule, the single value of the natural visibility condition for the 20 percent most impaired days is 

used in several ways:

1. The value of the natural visibility condition is to be compared to the “current 

visibility condition,” i.e., the most recent 5-year average of actual visibility for the 20 

percent most impaired days. (51.308(f)(1)(v)).

2. The URP can be calculated as the difference between the 2000-2004 baseline 

visibility condition and the natural visibility condition for the 20 percent most 

impaired days, divided by 60 years. In other words, the “glidepath” can end at the 

natural visibility condition in 2064. (51.308(f)(1)(vi)).15

3. The future year (2028 for the second implementation period) RPG for the 20 percent 

most impaired days is compared to its value on the URP line, which can use the 

natural visibility condition estimate as its endpoint. (51.308(f)(1)(vi)).

We are recommending that states set the single value of the natural visibility condition for the 

20 percent most impaired days to be equal to the average of the new estimates of daily natural 

visibility conditions estimated for the particular days that have been identified as the 20 

percent most impaired days from 2000-2014. This method takes advantage of the already 

calculated daily “natural (episodic)” and “natural (routine)” estimates of light extinction 

produced in steps 1 through 3. These revised natural visibility conditions are consistently lower 

in magnitude than the “p90” NC-II haze estimates (representing the average conditions for days 

between the 80th percentile and the 100th percentile) and generally more similar in magnitude 

to the annual average NC-II haze estimates. (Gantt, et al., 2018) describes in greater detail the 

methodology, seasonality, composition, and trends in the natural visibility conditions, and a 

summary of the natural visibility condition estimates for each IMPROVE site can be found in 

Appendix A. 

When following the recommended approach to select the 20 percent most impaired days 

based on anthropogenic impairment, days with large impacts from extreme, episodic natural 

events such as fires and dust storms are no longer selected. Therefore, these extreme impacts 

 

15If an adjustment is made to the URP for impacts from international anthropogenic emissions or wildland 

prescribed fires, the glidepath would not end at the natural visibility condition.
16 

generally will not be included in estimates of natural visibility conditions that will be compared 

with the most impaired days. This addresses past feedback from the first implementation 

period that the natural and current visibility conditions were inconsistent because 1) the “p90” 

NC-II Natural Haze estimates developed by the Natural Haze Levels II Committee in 2007 failed

to include effects from large episodic natural events (Tombach, 2008) and 2) the 20 percent of 

days with the worst overall visibility included these extreme episodic natural influences. In 

addition to avoiding selecting historical days dominated by extreme natural events when 

calculating the single value of the natural visibility condition that will be used in calculating the 

URP, it is important to recognize that the 20 percent most impaired days will be distributed 

across seasons of the year differently than the 20 percent haziest days used for the first 

implementation period (Gantt, et al., 2018). Because the revised national visibility condition 

value is calculated from estimates of daily natural contributions on the most impaired days, this 

recommended natural visibility condition value is more consistent within the framework.

At most Class I areas, these updates to the baseline and natural visibility conditions in 

recommended approach result in a time series that is less influenced by natural events and 

reflects the substantial visibility improvements that have occurred in many areas of the United 

States between 2000 and 2016 (see Figure 5).

Figure 5. National map of current visibility conditions relative to the URP in 2012-2016 based 

on the 20 percent most impaired days (recommended approach).
17 

3.0 Adjustment of the Uniform Rate of Progress for Impacts from

International Anthropogenic Emissions

Visibility at Class I areas is impacted not only by natural and anthropogenic emissions from 

within the U.S., but also by natural and anthropogenic international emissions. Due to the fact 

that international anthropogenic emissions are beyond the control of states preparing regional 

haze SIPs, the Regional Haze Rule allows states to propose an adjustment of the 2064 URP to 

account for international anthropogenic impacts, if the adjustment has been developed using

scientifically valid data and methods. The URP can be adjusted by adding an estimate of the 

visibility impact of international anthropogenic sources to the value of natural visibility 

condition to get an adjusted 2064 endpoint.16

The optional adjustment to the URP for international anthropogenic emissions is in addition to 

another optional adjustment relating to certain prescribed fires. Specifically, the rule also 

allows states to include an adjustment of the URP to account for impacts from certain wildland 

prescribed fires. The information and procedures for prescribed fire adjustments are expected 

in practice to be similar to the recommended international anthropogenic adjustment 

procedure provided in this guidance. Therefore, this section of the guidance document may be 

useful in either case. Note that preliminary EPA regional haze modeling (based on 2011 fire 

emissions) (EPA, 2017) indicates that prescribed fire impacts on the 20 percent most impaired 

days at most Class I areas are likely to be small and, thus, any adjustment to the URP would also 

be small. This section focuses on anthropogenic international emissions and their impacts.

3.1 URP Adjustment in the Regional Haze Rule 

The relevant international anthropogenic URP adjustment language in the Regional Haze Rule is 

at 40 CFR 51.308(f)(1)(vi): 

(B) As part of its implementation plan submission, the State may propose (1) an 

adjustment to the uniform rate of progress for a mandatory Class I Federal area to 

account for impacts from anthropogenic sources outside the United States and/or (2) an 

adjustment to the uniform rate of progress for the mandatory Class I Federal area to 

account for impacts from wildland prescribed fires that were conducted with the 

objective to establish, restore, and/or maintain sustainable and resilient wildland 

ecosystems, to reduce the risk of catastrophic wildfires, and/or to preserve endangered 

or threatened species during which appropriate basic smoke management practices 

were applied. To calculate the proposed adjustment(s), the State must add the 

estimated impact(s) to the natural visibility condition and compare the baseline visibility 

 

16The EPA expects that the revised approach of selecting the most anthropogenically impaired days for purposes of 

defining RPGs and tracking progress, which focuses progress tracking on days not affected by large episodic natural 

events such as dust storms and wildfires, will also largely resolve any concerns stemming from the same types of 

natural emission sources in other countries. Because the recommended method for identifying the most 

anthropogenically impaired days is based entirely on information from IMPROVE monitoring sites, it can be 

executed without detailed information on the emissions from natural sources outside the U.S.
18 

condition for the most impaired days to the resulting sum. If the Administrator 

determines that the State has estimated the impact(s) from anthropogenic sources 

outside the United States and/or wildland prescribed fires using scientifically valid data 

and methods, the Administrator may approve the proposed adjustment(s) to the 

uniform rate of progress.

The URP is based on 1) PM species measurements that do not distinguish between PM due to

natural, U.S. anthropogenic, and international anthropogenic emissions, and 2) the “natural 

visibility condition” endpoint that should not include any anthropogenic contribution (see 

Figure 1). The natural visibility condition endpoint, therefore, assumes no anthropogenic 

international contribution in 2064 and the default URP slope reflects a hypothetical uniform 

decrease in both U.S. and international anthropogenic haze contributions. The rule provision 

that allows states to include an international adjustment allows for the modification of the URP 

slope to account for international anthropogenic contributions that states cannot control. 

The Regional Haze Rule allows for an adjusted URP but does not prescribe a particular

adjustment methodology. To inform this adjustment to the URP, EPA recommends the use of 

chemical transport models (CTMs) as the most broadly applicable method for attributing 

pollutant concentrations to emissions sources. Two key issues with using CTMs for this purpose 

are addressed below: what year should be used to estimate international anthropogenic 

impacts, and how to apply the models to quantify international anthropogenic impacts.

3.2 Year Selection for Estimating International Contribution

Estimating international anthropogenic visibility impact is a function of transport patterns and 

emissions. Both meteorology and emissions are year-specific, so the first choice in 

photochemical modeling is determining what year to simulate. For example, the estimation 

could be based on a current or recent year, the implementation period end year (e.g., 2028, 

2038, etc.), or the URP endpoint (2064). 

To illustrate the potential impacts of international emissions, Figure 6 shows hypothetical 

effects of adjusting the 2064 endpoint to account for international emissions at a hypothetical 

Class I area. The URP lines in Figure 6 illustrate how the URP slope is impacted by different

estimates of international impacts. The URP represented by the orange line shows an 

unadjusted URP that assumes both U.S. and international anthropogenic impacts will decrease 

uniformly to zero in 2064. The black URP line represents an adjusted URP, assuming constant 

international anthropogenic impacts over time. In both URP series, the U.S. anthropogenic 

contribution is uniformly decreasing in each period.17 

 

17In the example figure, the U.S. visibility impairment improvement is calculated as a fixed percentage in each 

implementation period. However, consistent with the Regional Haze Rule, there is no regulatory requirement to 

achieve “uniform progress.” The actual improvement in visibility impairment during each implementation period 

may vary. 
19 

Figure 6. URP lines based on alternate international projections. For each year except 2004, 

there are two bars representing two different possibilities (1st: decreasing international (INT); 

2nd: constant international). Note that both realizations have the same decreasing U.S. 

anthropogenic (USA) contribution and same constant natural conditions (NAT). 

Projecting international emissions to 2064 may be speculative and somewhat uncertain. EPA 

therefore believes that recent year estimates of visibility impacts are most appropriate to use in 

estimating international adjustments. There are existing recent estimates of global PM and PM 

precursor emissions that have been used in various modeling studies (Galmarini, et al., 2016; 

Janssens-Maenhout, et al., 2015; Li, et al., 2015; Hoesly, et al., 2018). Therefore, for the second

implementation period, EPA recommends estimating international impacts in a recent year, 

with more recent years being best able to reflect current international emissions and trends. In 

choosing the analysis year, additional practical considerations, such as the availability of 

emission information or modeling results may constrain a state’s options. For example, it may 

only be practical to use 2011, 2014, or 2016 base year international emissions to calculate the 

adjustment because only that information is readily available. 

In some cases, additional data on emissions trends may be used to estimate future year 

international impacts, if future changes are well known. This is especially relevant for North 

American emissions sources (generally within the regional modeling domain), where future 

trends in some non-U.S. emissions sectors (e.g., on-road mobile sources and commercial ships) 

0

5

10

15

20

25

30

35

0

5

10

15

20

25

30

35

2004200920142019202420292034203920442049205420592064

Deciviews

NAT USA INT Unadjusted URP Adjusted URP
20 

may be relatively well characterized in existing inventories. Since 2028 is the end of the second

implementation period, it is the most likely future modeling analysis year. To the extent that 

high-quality international emissions projections are available, it may be appropriate to calculate 

international anthropogenic adjustments based on 2028 emissions. 

Since international anthropogenic visibility impacts are likely to change in the future, in 

subsequent planning periods, a new international adjustment can be made for each 

implementation period. In this way, an iterative process over time allows the glidepath to be 

periodically adjusted to reflect future trends in international anthropogenic emissions. 

Eventually, as we get closer in time to the URP endpoint, the international anthropogenic 

visibility impact will become less uncertain.

3.3 Estimating the Anthropogenic International Visibility Impacts

The methods to quantify international visibility impacts are largely independent of the chosen 

year. The Regional Haze Rule requires that a state’s approach be based on scientifically valid 

data and methods. Due to long-range transport and secondary PM components involved in 

international transport, photochemical chemical transport modeling (CTM) is the preferred 

approach for quantifying international contributions to visibility. Detailed guidance on 

performing CTM simulations is available in EPA’s photochemical modeling guidance for ozone, 

PM2.5, and regional haze (EPA, 2018). 

Using CTMs, there are several potential ways to quantify international anthropogenic impacts 

in Class I areas: 

1) The simplest approach is to perform brute force “zero-out” model runs, which involves 

at least two model runs: one “base case” run with all emissions, and one with 

anthropogenic emissions from outside of the U.S. removed from the original base case 

simulation. The difference between these simulations provides an estimate of the air 

quality impact due to the international anthropogenic emissions. 

2) An alternative approach to isolating international anthropogenic impacts in 

photochemical grid models is “photochemical source apportionment.” Some 

photochemical models have been developed with a photochemical source 

apportionment capability, which tracks emissions from specific sources or groups of 

sources and/or source regions through chemical transformation, transport, and 

deposition processes to estimate the apportionment of predicted PM2.5 species 

concentrations (Kwok, et al., 2013; Kwok, et al., 2015; Ramboll, 2018). Source 

apportionment can be used to track PM formed from international anthropogenic 

emissions sources.

From the CTM runs, whether based on brute-force or source apportionment (or a combination 

of both), PM species concentration increments due to international anthropogenic emissions 

can be calculated for each of the 20 percent most impaired days (for each Class I area). The PM 

concentration increments on the 20 percent most impaired days are then converted to 
21 

extinction and averaged. The “delta deciview” adjustment factor associated with the 

international anthropogenic impact can then be calculated as follows18: 

∆dv=10 ln�bextnatural conditions+bextinternational anthropogenic�/ bextnatural conditions (Eqn. 4)

The Class I area-specific adjustment factor (in deciviews) is added to the natural conditions 

value for each Class I area to get the adjusted URP.

19 In this process, the following issues should 

be given appropriate treatment:

The air quality model (or combination of models) that is used.

The modeling system typically includes a global/hemispheric modeling simulation and a 

regional photochemical modeling simulation. The global component is often used to supply 

“boundary” conditions to the regional simulation. To the extent practical, the modeling 

platforms with the two scales should be consistent using the same (or similar) meteorology, 

vertical resolution, emissions, and representation of chemical species. This is particularly true 

for the international emissions but is also true for gas-phase and aerosol modeling components. 

The consistency is particularly important when performing anthropogenic zero-out and/or 

source apportionment simulations that cross horizontal grid scales (going from a lower 

resolution global/hemispheric model to a higher resolution nested regional model).20 

The validity of the estimates of both international and U.S emissions.

Before estimating source contributions, the “basecase” simulation, both for global and regional 

models, should be able to reasonably reproduce historical PM measurements and calculated

visibility values. Thus, model performance evaluation and diagnostic evaluation should both 

play a role as described in the photochemical modeling guidance (EPA, 2018) (Simon, et al., 

2012). This will provide confidence that both U.S. and international emissions and visibility 

impacts are reasonably well represented.

After the basecase has been evaluated and shown capable of representing historical PM and 

visibility, then the models can be used to quantify international impacts. Quantifying the 

international sources, as previously stated, may be done using zero-out (sensitivity) or source 

apportionment model runs, or a combination of both.

21 Unless the international impacts are 

primarily from the portions of North America included in the smaller scale (regional) modeling 

simulation, the modeling will likely require coordinated efforts between a global/hemispheric 

and regional CTM simulation. When this is the case, it is especially important to understand the 

 

18There may be multiple ways this aggregation across days might be done, keeping in mind that the URP line is in 

units of deciviews, so the adjustment must also be in units of deciviews. 19Note that the Regional Haze Rule does not allow a state to subtract an estimate of the impacts of international 

anthropogenic sources when projecting the RPGs for the end of the implementation period, as an alternative to 

adding international anthropogenic impacts to the 2064 endpoint of the URP glidepath. 

20The boundary between the global and regional models should be sufficiently far removed from U.S. emissions 

sources and/or the Class I areas being considered. 21For example, zero-out modeling could be used in the global or hemispheric model to feed boundary conditions to 

the regional model. Then source apportionment technology could be used to track international anthropogenic 

emissions within the regional model. The available options depend on the source apportionment capability of the 

chosen global, hemispheric, and/or regional CTMs. 
22 

harmony of inventories at the different scales. Regardless of the technology used for 

quantification of source contributions (sensitivity or source apportionment), the most 

important aspect is appropriate selection of source sectors and domains over which they apply. 

Previous studies provide guidance on which inventories need to be considered in international 

contribution analysis. The majority of studies have focused on ozone because of its long-range 

transport capability (Zhang, et al., 2011; Emery, et al., 2012). Estimating international 

contribution continues to evolve and applications should review all emission sectors and 

consider the appropriate divisions between natural, international anthropogenic, and domestic 

anthropogenic sources.

When the emissions inventory coverages cross scales (global to regional), the emissions should 

be consistent between the two scales and the sensitivity (zero-out) or source apportionment 

should also be consistent between the two scales. Emissions that cross scales include aircraft 

and international shipping. These inventories require special consideration if they are used in 

estimating international contributions. The assignment of domestic versus foreign emissions 

depends on the jurisdiction of the waters and/or air space. Where the assignment is unclear, 

the appropriate EPA Regional office should be consulted. For brute force modeling, the 

“boundary conditions” for the regional perturbation simulation would be provided by a 

consistent perturbation in the global model.

Model contributions will vary, and a range of estimates should be considered and discussed to 

provide context. Particularly for sensitivity modeling, the sequential order of emission 

perturbations influences the result (zeroing the international source or the local source give 

different answers). Thus, two estimates of international source contribution can be developed 

and used to characterize a range of possible results. This is particularly important for haze that 

is strongly influenced by secondary organic aerosol and/or nitrate. For example, nitrate 

concentrations can increase when removing international sulfate due to chemical 

displacement. Estimates of all species should be characterized and the realism of the estimate 

considered before simply adding to natural conditions.

Because the adjustment factor will be added to the endpoint of the URP and ultimately used to 

calculate an adjusted URP for comparison with the RPG, it is important that the modeling be 

consistent across the URP framework (e.g., the same or similar model, domain, meteorology, 

and emissions should be used in both the RPG modeling and in the modeling used to adjust the 

endpoint).

3.4 EPA Review of an International URP Adjustment

EPA’s approval for a URP adjustment will be part of EPA’s review of the full SIP submission for 

the second implementation period, and not a separate action in advance of SIP submission. In 

this way, EPA’s decision to approve or not approve the adjustment will be made in the context 

of the complete SIP submission, with public notice and an opportunity to comment. States are 

encouraged to consult with their EPA Regional office during the development of any proposed 

adjustment approach. Any proposed adjustment must be adequately documented to allow 
23 

public comment and EPA review. An adequate explanation of the adjustment will necessarily 

show the unadjusted and adjusted values for the 2064 endpoint and for the URP.

Whether and what adjustment should be made to the URP to account for impacts from 

international anthropogenic emissions will be a new issue for the SIP for each implementation 

period. EPA’s approval of an adjustment approach included in the SIP revision due in 2021 does 

not mean that the same adjustment will be automatically approved if included in the SIP 

revision due in 2028, for example.
24 

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26 

APPENDIX A. 

Site

First Implementation Period Approach Recommended Approach e3 (Mm-1)

Baseline Visibility 

Condition for 

20% Haziest Days 

(2000-2004)

Current Visibility 

Condition for 

Most Impaired 

Days (2012-2016)

NC-II 

P90

(2064)

Baseline Visibility 

Condition for 20% 

Most Impaired 

Days (2000-2004)

Current Visibility 

Condition for 20% 

Most Impaired 

Days (2012-2016)

DerivedNC

(2064)

carbon dust

ACAD1 23.21 16.50 12.43 22.01 15.28 10.39 10.44 3.11

AGTI1 23.50 17.65 7.64 21.62 16.73 7.63 10.85 8.86

BADL1 17.14 14.71 8.06 14.98 12.56 6.09 9.17 7.49

BALD1 11.51 10.19 6.24 8.64 7.55 4.04 6.65 5.42

BAND1 12.23 10.71 6.26 9.70 8.88 4.59 5.60 4.36

BIBE1 17.30 15.29 7.16 15.57 14.25 5.33 7.60 8.59

BLIS1 12.63 12.64 6.05 10.06 9.39 4.91 11.14 2.84

BOAP1 13.80 14.06 6.73 11.61 10.98 5.36 9.38 7.83

BOWA1 19.99 16.51 11.61 18.94 14.58 9.11 11.11 3.16

BRCA1 11.65 9.29 6.80 8.42 6.88 4.08 6.13 4.26

BRID1 11.12 10.84 6.45 7.96 6.58 3.90 7.75 2.83

BRIG1 29.01 21.62 12.24 27.43 20.44 10.69 20.15 9.07

BRIS1a 21.29 11.93 19.67 9.28 18.10 9.12

CABI1 14.09 14.27 7.52 10.73 9.97 5.65 13.14 4.13

CACR1 26.36 20.68 11.58 23.99 19.22 9.47 16.84 7.80

CANY1 11.25 9.91 6.43 8.79 7.36 4.11 5.53 5.02

CAPI1 9.97 9.97 6.03 8.62 7.27 4.13 5.07 5.14

CHAS1 26.10 19.96 11.03 24.62 18.12 8.97 24.69 6.68

CHIR1 13.43 11.94 7.20 10.50 9.78 4.93 4.81 7.87

COHU1 30.30 20.15 10.78 28.83 18.59 9.52 18.17 4.44

CRLA1 13.74 12.96 7.62 9.36 8.64 5.22 8.67 2.37

CRMO1 14.00 14.08 7.53 11.91 9.28 4.97 7.26 4.72

DENA1 9.86 9.25 7.31 7.06 6.97 4.79 3.58 1.60

DOME1 19.43 17.95 7.46 17.20 15.42 6.18 14.13 11.58

DOSO1 29.05 19.96 10.39 28.29 18.88 8.92 13.57 3.40

EVER1 22.31 18.06 12.15 19.54 15.33 8.34 10.00 7.90

GAMO1 11.29 10.97 6.38 8.95 7.50 4.66 10.17 3.03

GICL1 13.11 11.11 6.66 8.93 8.02 4.22 5.73 4.40

GLAC1 20.47 16.91 9.18 16.19 13.69 6.99 22.24 7.50

GRCA2 11.66 9.56 7.04 7.94 6.95 4.18 5.97 4.74

GRGU1 22.82 15.20 11.99 21.93 13.92 9.78 12.07 3.23

GRSA1 12.78 10.63 6.66 9.66 8.28 4.45 8.01 6.69

GRSM1 30.28 19.66 11.24 29.16 18.42 10.05 16.09 4.48

GUMO1 17.19 14.93 6.65 14.60 12.86 4.83 6.25 12.95

HACR1b 13.33 9.16 7.43 12.67 8.37 4.78 1.24 2.01

HAVO1 18.86 19.01 7.17 18.66 18.82 5.64 1.65 1.93

HECA1 18.55 17.17 8.32 16.51 13.09 6.57 13.88 5.00

HEGL1 26.75 20.73 11.30 25.17 19.32 9.30 20.30 6.84

HOOV1 12.87 11.84 7.71 8.97 7.91 4.91 8.92 4.00

IKBA1 13.35 11.80 6.68 11.19 9.52 5.22 6.78 6.14

ISLE1 20.74 17.46 12.37 19.53 16.03 10.15 12.05 4.22

JARB1 12.07 12.85 7.87 8.73 7.82 5.23 7.45 8.00

JARI1 29.12 20.18 11.13 28.08 18.70 9.48 26.27 3.13

JOSH1 19.62 14.97 7.19 17.74 13.15 6.09 7.82 9.81

KAIS1 14.75 15.45 7.12 12.67 11.45 5.98 11.16 5.19

KALM1 15.51 14.40 9.44 13.35 12.12 7.80 12.46 2.43

KPBO1c 14.11 12.94 11.31 10.47 10.48 6.96 3.39 2.32

LABE1 15.05 15.03 7.85 11.29 9.92 6.16 10.38 3.81

LAVO1 14.15 12.69 7.31 11.50 9.97 6.14 12.36 2.59

LIGO1 28.77 19.15 11.22 28.05 17.36 9.70 18.22 2.83

LOST1 19.57 18.37 8.00 18.27 15.89 5.88 10.17 9.28

LYEB1d 24.45 17.11 11.73 23.57 16.07 10.23 11.44 2.75

MACA1 31.37 23.04 11.08 29.83 22.03 9.79 19.44 4.28

MELA1 17.72 17.75 7.89 16.63 15.50 5.95 9.14 9.09

MEVE1 13.03 9.88 6.81 9.22 7.03 4.20 5.05 5.33

MING1 29.54 22.34 11.62 26.65 20.70 9.28 28.55 10.81

MOHO1 14.86 13.14 8.43 12.10 9.74 6.60 7.75 2.74

MONT1 14.48 15.15 7.73 10.84 9.61 5.43 14.92 4.89

MOOS1 21.72 15.64 12.01 20.66 14.07 9.97 11.13 2.54
27 

Site

First Implementation Period Approach Recommended Approach e3 (Mm-1)

Baseline Visibility 

Condition for 

20% Haziest Days 

(2000-2004)

Current Visibility 

Condition for 

Most Impaired 

Days (2012-2016)

NC-II 

P90

(2064)

Baseline Visibility 

Condition for 20% 

Most Impaired 

Days (2000-2004)

Current Visibility 

Condition for 20% 

Most Impaired 

Days (2012-2016)

DerivedNC

(2064)

carbon dust

MORA1 18.25 14.93 8.54 16.53 13.35 7.66 13.33 2.53

MOZI1 10.52 9.16 6.08 7.29 5.63 3.16 5.70 3.23

NOAB1 11.46 11.30 6.83 8.78 7.17 4.54 10.18 4.23

NOCA1 13.96 12.65 8.39 12.57 10.42 6.79 8.20 1.97

OKEF1 27.13 20.47 11.44 25.34 18.73 9.47 20.65 5.50

OLYM1 16.74 13.38 8.44 14.93 12.24 6.88 8.78 1.76

PASA1 15.23 13.94 8.25 10.41 9.17 5.97 9.42 2.58

PEFO1 13.21 10.73 6.49 9.82 8.49 4.21 6.75 7.84

PINN1 18.46 16.03 7.99 17.02 14.35 6.96 11.33 5.88

PORE1 22.81 19.98 15.77 19.38 15.94 9.75 6.78 8.23

RAFA1 18.86 16.08 7.57 17.00 14.14 6.85 7.65 8.20

REDW1 18.45 17.88 13.91 13.64 12.70 8.54 5.86 4.44

ROMA1 26.48 20.21 12.12 25.25 18.32 9.79 23.38 5.35

ROMO1 13.83 11.54 7.15 11.12 8.66 4.93 8.54 5.32

SACR1 18.03 17.33 6.81 16.54 15.36 5.50 9.01 14.44

SAGA1 19.94 14.83 6.99 17.89 13.63 6.12 8.49 7.11

SAGO1 22.17 15.98 7.30 20.43 14.80 6.19 11.94 7.77

SAGU1 14.83 12.69 6.46 12.64 10.96 5.16 6.15 9.62

SAMA1 26.03 20.64 11.67 24.30 18.17 9.19 21.26 5.22

SAPE1 10.17 9.13 5.72 7.66 6.66 3.36 5.66 4.53

SAWT1 13.78 17.12 6.42 9.62 8.52 4.67 12.35 2.57

SENE1 24.16 19.20 12.65 23.62 18.41 11.11 13.67 2.52

SEQU1 24.62 21.10 7.70 23.23 19.20 6.29 23.11 11.47

SHEN1 29.31 19.71 11.35 28.32 18.40 9.52 15.06 3.92

SHRO1 27.89 18.65 11.47 27.32 16.87 10.01 13.99 3.09

SIAN1 13.67 6.59 10.76 5.14 6.77 5.91

SIME1 18.56 16.97 15.60 13.67 13.69 8.49 3.42 4.63

SIPS1 29.03 20.95 10.99 27.71 19.77 9.55 21.66 4.79

SNPA1 17.84 15.54 8.43 15.37 13.07 7.25 12.33 1.79

STAR1 18.57 14.54 8.92 14.53 11.53 6.59 13.10 5.66

SULA1 13.41 15.55 7.43 10.06 8.53 5.48 11.78 3.22

SWAN1 25.49 19.06 11.55 24.40 17.44 9.79 16.47 5.01

SYCA2e 15.26 14.59 6.65 12.16 11.45 4.68 13.12 15.93

THRO1 17.74 15.97 7.80 16.35 13.70 5.96 9.87 8.71

THSI1 15.34 15.28 8.79 12.80 11.48 7.30 12.62 4.01

TONT1 13.94 12.47 6.54 11.34 10.63 5.06 7.14 8.76

TRCR1 11.61 10.03 8.40 9.16 8.85 6.38 5.11 2.38

TRIN1 16.32 16.02 7.90 11.97 10.45 6.24 10.36 3.61

ULBE1 15.14 14.31 8.16 12.76 10.79 5.87 9.82 6.17

UPBU1 26.27 20.57 11.57 24.25 18.85 9.43 17.22 7.72

VIIS1 17.02 18.49 10.68 14.29 15.60 8.53 2.60 21.54

VOYA2 19.27 17.08 12.06 17.75 15.04 9.38 11.48 4.14

WEMI1 10.33 9.17 6.21 7.81 6.74 3.98 6.51 3.93

WHIT1 13.70 13.21 6.80 11.31 10.41 4.89 7.16 7.13

WHPA1 12.76 12.02 8.35 10.48 8.51 6.15 6.89 2.41

WHPE1 10.41 9.11 6.08 7.35 7.02 3.53 5.13 3.50

WHRI1 9.61 7.93 6.06 6.30 5.18 3.02 4.92 3.56

WICA1 15.84 13.55 7.71 13.09 10.63 5.64 8.02 4.62

WIMO1 23.81 19.53 7.53 22.15 18.79 6.92 13.95 9.94

YELL2 11.76 12.26 6.44 8.30 7.65 3.98 10.08 3.06

YOSE1 17.63 15.84 7.64 13.52 11.89 6.29 13.14 5.19

ZICA1f 12.97 10.32 6.70 10.72 8.66 5.08 5.54 6.90

a

Site data combined with BRET1 starting 01-01-08 b

Site data combined with HALE1 starting 01-01-08 c

Site data combined with TUXE1 starting 01-01-15 d

Site data combined with LYBR1 starting 01-01-12 e

Site data combined with SYCA1 starting 01-01-16 f

Site data combined with ZION1 starting 01-01-04
28 

APPENDIX B 

For each of the following sites, the left column gives the total extinction budget for days classified as the 20 percent most impaired 

in 2015 (or 2013 when noted), middle column gives the time series from 2000-2016 of the annual average total extinction budget for 

days classified as the 20 percent most impaired , and right column shows the visibility conditions on the 20 percent most impaired 

days from 2000 to 2016. For all extinction budget figures, the following color scale applies: sulfate (yellow), nitrate (red), OMC (teal), 

LAC (black), FS (tan), CM (brown), and sea salt (blue). For all visibility conditions figures, the blue points are annual average values; 

red points are 5-year averages and the orange line is the glidepath between 2000-2004 and 2064.22

Acadia National Park, ME

 

22Updated site-specific graphics summarizing visibility status and trends following the Regional Haze Rule metrics can be found at 

http://views.cira.colostate.edu/fed/SiteBrowser/Default.aspx?appkey=SBCF_VisSum.
29 

Agua Tibia, CA

Badlands National Park, SD
30 

Mount Baldy, AZ

Bandelier National Monument, NM
31 

Big Bend National Park, TX

Bliss State Park, CA
32 

Bosque del Apache, NM

Boundary Waters Canoe Area, MN
33 

Breton Island, LA

Bryce Canyon National Park, UT
34 

Bridger Wilderness, WY

Brigantine National Wildlife Refuge, NJ
35 

Cabinet Mountains, MT

Caney Creek, AR
36 

Canyonlands National Park, UT

Capitol Reef National Park, UT
37 

Chassahowitzka National Wildlife Refuge, FL

Chiricahua National Monument, AZ
38 

Cohutta, GA

Crater Lake National Park, OR
39 

Craters of the Moon National Monument, ID

Denali National Park, AK
40 

Dome Lands Wilderness, CA

Dolly Sods Wilderness, WV
41 

Everglades National Park, FL

Gates of the Mountains, MT
42 

Gila Wilderness, NM

Glacier National Park, MT
43 

Grand Canyon National Park, AZ

Great Gulf Wilderness, NH
44 

Great Sand Dunes National Monument, CO

Great Smoky Mountains National Park, TN
45 

Guadalupe Mountains National Park, TX

Haleakala National Park, HI (combined HALE1 and HACR1 starting 01/01/2007)
46 

Hawaii Volcanoes National Park, HI

Hells Canyon, OR
47 

Hercules-Glades, MO

Hoover, CA
48 

Ike's Backbone, AZ

Isle Royale National Park, MI
49 

Jarbidge Wilderness, NV

James River Face Wilderness, VA
50 

Joshua Tree National Park, CA

Kaiser, CA
51 

Kalmiopsis, OR

Lava Beds National Monument, CA
52 

Lassen Volcanic National Park, CA

Linville Gorge, NC
53 

Lostwood, ND

Lye Brook Wilderness, VT (combined LYBR1 and LYEB1 starting 01/01/2012)
54 

Mammoth Cave National Park, KY

Medicine Lake, MT
55 

Mesa Verde National Park, CO

Mingo, MO
56 

Mount Hood, OR

Monture, MT
57 

Moosehorn National Wildlife Refuge, ME

Mount Rainier National Park, WA
58 

Mount Zirkel Wilderness, CO

North Absaroka, WY
59 

North Cascades National Park, WA

Okefenokee National Wildlife Refuge, GA
60 

Olympic National Park, WA

Pasayten, WA
61 

Petrified Forest National Park, AZ

Pinnacles National Monument, CA
62 

Point Reyes National Seashore, CA

San Rafael, CA
63 

Redwood National Park, CA

Cape Romain National Wildlife Refuge, SC
64 

Rocky Mountain National Park, CO

Salt Creek, NM
65 

San Gabriel, CA

San Gorgonio Wilderness, CA
66 

Saguaro National Monument, AZ

St. Marks, FL
67 

San Pedro Parks, NM

Sawtooth National Forest, ID
68 

Seney, MI

Sequoia National Park, CA
69 

Shenandoah National Park, VA

Shining Rock Wilderness, NC
70 

Sierra Ancha, AZ (2013 data shown on figures in left column)

Simeonof, AK
71 

Sipsey Wilderness, AL

Snoqualmie Pass, WA
72 

Starkey, OR

Sula Peak, MT (2013 data shown for figures in right column)
73 

Swanquarter, NC

Sycamore Canyon, AZ (2013 data shown for figures in right column)
74 

Theodore Roosevelt, ND

Three Sisters Wilderness, OR
75 

Tonto National Monument, AZ

Trinity, CA (2013 data shown for figures in right column)
76 

Trapper Creek, AK

Tuxedni, AK (2013 data shown for figures in right column)
77 

UL Bend, MT

Upper Buffalo Wilderness, AR
78 

Virgin Islands National Park, VI

Voyageurs National Park, MN
79 

Weminuche Wilderness, CO

White Mountain, NM
80 

White Pass, WA

Wheeler Peak, NM (2013 data shown for figures in right column)
81 

White River National Forest, CO

Wind Cave, SD
82 

Wichita Mountains, OK

Yellowstone National Park, WY
83 

Yosemite National Park, CA

Zion National Park, UT (combined ZION1 and ZICA1 starting 1/1/04)
84 
85 

United States

Environmental Protection

Agency

Office of Air Quality Planning and Standards

Air Quality Assessment Division

Research Triangle Park, NC

Publication No. EPA-454/R-18-010

December 2018