### 1 Attribution of Haze Workgroup’s Technical Recommendations on Monitoring Metrics for Regional Haze Planning

9/22/06 DRAFT

Executive Summary

The Attribution of Haze Workgroup recommends the fo llowing forms of monitoring metrics be used by states and tribes for assessing all visibility-protected Class I Federal areas of the WRAP region in the December 2007 regional haze implementation plans:



### • The revised IMPROVE light extinction equati on as developed and approved in 2005 by the IMPROVE Steering Committee to convert from mass c oncentration measurements to light extinction for visibility analysis and regional haze planning;



### • The 2000-04 baseline period IMPROVE visibility m onitoring data reported using the revised IMPROVE equation, as available on the Technical Support System;



### • The alternative 2064 natural visibility conditions es timates of total light extinction and individual light extinction species using the revised IMPROVE equation, as developed and recommended by the Inter-RPO Monitoring & Data Analysis Discussion Group; and



### • The 2018 planning milestone projected visibility va lue (using the Relative Reduction Factor or RRF), as calculated using a scaling factor from 2000-04 b aseline period monitoring data (WRAP method) applied to a ratio of historic and projected regi onal gridded air quality m odeling results to assess the amount of visibility improvement expected from emissions reductions acr oss all sources by 2018.

Using the revised IMPROVE light extinction equati on, applying these metrics for all WRAP region Class I areas allows a regionally consistent approach betw een the individual regional haze implementation plans based on the analysis of the impact of individual light extinction species (SO4, NO3, organic carbon, elemental carbon, fine soil, and coarse material) and the sources contributing to their formation. These metrics also allow the most up-to-date scientific analys is of the total visibility impact in units of light extinction or the haze index (the deciview) required in the Regional Haze Rule.

The 2000-04 baseline period monitoring data have b een reviewed by the AoH WG and found to be adequate as the basis of regional haze plans. Specifi c monitoring sites (5) with limited data from this 5- year period have additional site-specific recommendati ons for their limited data record. The alternative natural conditions estimates also incorporate the re vised IMPROVE equation so that progress in reducing emissions and increasing visibility across the nominal 60-year period defined in the Regional Haze Rule

to achieve natural conditions in Class I areas can be better assessed in terms of natural and anthropogenic sources, as well as the degree of controllability.

Finally, the WRAP RRF projection method for future visibility conditions incorporates the default EPA method modified with a standard approach to select monitoring data for projecting regional modeling results. This allows for a better, accounting of bot h source strength and temporal variation to produce a consistent estimate of future visibility cond itions based on modeling comprehensive emissions inventories. The revised IMPROVE equation and alternative Natural Conditions Estimates are not endorsed for individual state air program evaluation of BART modeling results for technical and process reasons discussed in the Monitoring Metrics document since these have not been incorporated into the EPA or Federal Land Managers' Air Qua lity Related Values Work Group (FLAG).

### 2 Technical Recommendations for Haze Planning in the WRAP region

1) Apply the revised IMPROVE light extinction equation as developed and approved in 2005 by the IMPROVE Steering Committee to conv ert from mass concentration measurements to light extinction for visibility analysis and regional haze planning at each WRAP region

Class I area.

2) Use the 2000-04 Best and Worst Days’ metrics as calculated and reported by VIEWS and

TSS. Individual states should review the data completeness and any data substitutions for

their CIAs.

3) Use the alterative Natural Conditions Estimate s in combination with the 2000-04 Best and Worst Days’ metrics as calculated and repor ted by VIEWS and TSS, utilizing the revised IMPROVE equation, for visibility analysis a nd regional haze planning at each WRAP region Class I area.

4) Use the alternative WRAP RRF Projection Method for projecting 2018 visibility conditions

in combination with the 2000-04 Best and Wo rst Days’ metrics as calculated and reported by VIEWS and TSS, utilizing the revised IMPROVE equation and alternative Natural Conditions Estimates, for visibility analysis and regional haze planning at each WRAP region Class I area. Study the effect of th is method for Fine Soil and Coarse Material visibility modeling results before applying it to those IMPROVE light extinction species.

### 3 Attribution of Haze Workgroup’s Technical Recommendations on Monitoring Metrics for Regional Haze Planning

9/22/06 DRAFT Background

This document summarizes the recommended monitoring metrics for application by states and tribes for regional haze planning, for the December 2007 plans’ due date. The intent of this document is to identify the currently available best technical monitoring metrics and reasons for using them. The motivation behind this consensus product from the Attributio n of Haze Workgroup is to lay out a regionally consistent approach for applying the following monitoring metrics at each WRAP region Class I area:



### • The light extinction equation to convert from mass concentrati on measurements to visibility;



### • The 2000-04 baseline period visibility monitoring data;



### • Natural visibility conditions estimates – the 2064 goa l to be defined in the 2007 haze plans; and



### • The 2018 planning milestone projected visibility va lue (using the Relative Reduction Factor or RRF), a scaling factor from monitoring data to be applied to regional gridded air quality modeling results to assess the amount of visibility improvement expected from emissions reductions across all sources by

2018.

This document provides a protocol for applying the monitoring metrics, and can serve as a reference document for individual haze implementation plans.



### Use of Monitoring Data in Support of Regional Haze Planning

The need for a consistent regional methodology for evaluating the WRAP region results from studying the nature and causes of light extinction and fundament al requirement to apply the best metrics to the regional haze planning process. Conceptual ly this process is shown in Figure 1.



### Figure 1. Conceptual Diagram of Monitoring Metrics for Planning under the Regional Haze Rule



### Monitoring Metrics for Haze Planning

IMPROVE Equation used to determine light

extinction and associated

deciview values

Natural

Conditions Estimates (species) 2000-04 Baseline Monitoring

Period Data

(species) Future Year Projections of Modeling Results scaled

against 2000-04 species monitoring data

Measured & modeled

values used in Glide Path Analysis for each

Class I area (dv, species)

### 4 The Interagency M onitoring of PRO tected V isual E nvironments (IMPROVE) national monitoring program has been designated by EPA to collect vi sibility impairment data representing the 156 Class I Federal areas (CIAs) with visibility protection unde r the Clean Air Act. More information about the IMPROVE monitoring program, the 110 monitoring s ites across the nation selected to represent the 156 CIAs, and the Steering Committee managing the monito ring program in support of regional haze plans required of all 50 states under the EPA Regi onal Haze Rule (RHR) can be found at: http://vista.cira.colostate.edu /improve/Overview/Overview.htm . EPA has also published a broader guidance document on Visibility Monitoring, see: http://www.epa.gov/ttn/amtic/files/ambient/visible/r99-003.pdf

.

Light extinction theory

Based on aerosol research, the technical method to determin e visibility impairment is to calculate the light extinction coefficient (bext). This is defined as th e loss of image-forming light per unit distance due to scattering and absorption by particles and gases in the at mosphere. The light extinction coefficient is the sum of the scattering coefficient (bscat) and absorption coefficient (babs), which are similarly defined as the loss of light per unit distance by scattering and absorption mechanisms re spectively. The light extinction coefficient can be represented mathematically as:

; where s, a, g, and p refer to scattering and ab sorption by gases and particles, respectively.

Speciated Monitoring Data

To determine visibility impairment under the RHR, filter sampling data from IMPROVE aerosol monitors are collected and analyzed following Standard Operating Procedures, see: ( http://vista.cira.colostate.edu/improve/Publi cations/SOPs/UCDavis_SOPs/IMPROVE_SOPs.htm ). These resulting mass concentration data are then convert ed to light extinction using an algorithm referred to as the IMPROVE equation; this equation has been re viewed and changed during the last 2 years, (see: http://vista.cira.colostate.edu/improve/Publicati ons/GrayLit/019_RevisedIMPROVEeq/RevisedIMPROV EAlgorithm3.doc ), creating a ripple effect for the monitoring metrics required for use in regional haze planning.

Haze Index- The Deciview (dv)

The RHR also requires that the light extinction da ta from the IMPROVE equation be analyzed and presented in terms of a “haze index” value called the d eciview (dv); the dv index is related to total light extinction, described at: http://vista.cira.colostate.edu/improve /Publications/NewsLetters/apr_93.pdf . As such, light extinction for regional haze planning could be analyzed in terms of its component contributors to light extinction as defined in the old and re vised IMPROVE equations, and/or as the associated

deciview values.



### IMPROVE Light Extinction Equa tion – Original vs. Revised

The original IMPROVE light extinction equation w as adopted by the Steering Committee and used in their principle publications (see: http://vista.cira.colostate.edu/impr ove/Publications/Principle_pubs.htm ) since the early 1990s. The equation has also been wi dely evaluated and used in peer-reviewed journal articles as well as urban visibility studies. For those reasons, the EPA adopted this equation in their 2003

### 5 guidance document on Tracking Progress Under the Regional Haze Rule. See: http://www.epa.gov/ttn/oarpg/t1/memoranda/rh_tpurhr_gd.pdf

.

The equation uses additive extinction by chemical species as measured by the IMPROVE aerosol monitor, combined with the effect of Relative Humid ity (RH), to estimate the scattering of light by fine and coarse particles. The original IMPROVE equation, as adopted by EPA in their guidance document, is used to estimate total light extinction fo r the purposes of planning under the RHR:

The brackets in this equation indicate the species concen tration. The factors 3, 4, 1, and 0.6 are the m 2 /g dry specific scattering efficiency for each of the respec tive species. . Thus, a sulfate particle is three times more effective in scattering light than a particle of soil.

To account and control for relative humidity effects in th e light extinction data to be used in regional haze planning, EPA sponsored a project to examine meas ured hourly relative humidity data over a 10-year period (1988-1997) within the United States to deri ve month-specific climatological mean humidity correction factors designed to represent each CIA. The hourly RH measurements from each site were

converted to f(RH) values using a nonlinear weighting factor cu rve. Values above 95% RH were set equal

to the f(RH) corresponding to 95% RH.

Appendix A of: http://www.epa.gov/ttn/oarpg/t1/memoranda/rh_tpurhr_gd.pdf presents these values. Determination of the humidity factors is described in section 3.6 of that document. Using over 370 humidity monitoring locations across the country, monthly f(RH) values were calculated. In most regions there is a seasonal cycle of relative humidity, wh ich is accounted for by generating the appropriate monthly f (RH) values, as in Appendix A. The 12 monthly averaged f (RH) values are listed for each IMPROVE or IMPROVE protocol site and their corr esponding Class I areas. The site specific values are

listed for each CIA and are recommended to be used for all visibility and tracking progress calculations for that CIA. These values are provided in Table A-2. A table of 12 monthly-averaged f(RH) values for each CIA is also provided in Table A-3 for informational purposes.

Overview of revised IMPROVE equation

The IMPROVE light extinction equation was analyzed , revised, and approved by the Steering Committee during 2005. A detailed discussion of the revised equa tion and the reasons for changing it can be found

at: http://vista.cira.colostate.edu/improve/Pub lications/NewsLetters/IMPNews4thQtr2005.pdf . A summary of the differences between the or iginal and revised equations follows.

The original IMPROVE equation produces reasonable est imates of light scattering over a broad range of conditions. However, it tends to underestimate the highest extinction values and overestimate the lowest extinction values. Since EPA adopted the equation for use in RHR planning, the original IMPROVE equation has been scrutinized caref ully to assess deficiencies that could bias the implementation of the RHR. With those concerns identified, the IMPROV E Steering Committee initiated an internal review resulting in recommendations for revisions of the light extinction equation. The review team of scientists from the National Park Service and the Cooperative Ins titute for Research in the Atmosphere developed a revised algorithm that reduces biases in light extinction estimates and is as consistent as possible with the

### 6 current scientific literature. Review of the original equation and suggested revisions are presented at: http://vista.cira.colostate.edu/improve/P ublications/NewsLette rs/IMPNews2ndQtr2005.pdf

.

In July 2005, the equation review results and pr oposed revisions were presented to the IMPROVE Steering Committee. A subcommittee was formed to further investigate the proposed equation. The

subcommittee included scientists who worked on the initial review, as well as scientists who have been critical of the original IMPROVE equation. Their wo rk resulted in the final version of the equation, which was again presented to the Steering Committee. In December 2005, the IMPROVE Steering Committee voted to adopt this revised equation for use by IMPROVE as an alternative to the current approach.

The new equation splits ammonium sulfate, a mmonium nitrate, and organic carbon compound concentrations into two size fractions: small and larg e. The equation for estimating the light extinction

for the RHR is:

b ext ≈ 2.2 x f

s (RH) x [small sulfate] + 4.8 x f L (RH) x [large sulfate]

+ 2.4 x f

s (RH) x [small nitrate] + 5.1 x f L (RH) x [large nitrate] + 2.8 x [small organic mass] + 6.1 x [large organic mass] + 10 x [ elemental carbon ] + 1 x [ fine soil ]

+ 1.7 x f

ss (RH) x [sea salt] + 0.6 x [ coarse mass ] + Rayleigh scattering (site-specific) + 0.33 x [NO 2 (ppb)]

Though not explicitly shown, the organic mass conc entration used is 1.8 times the organic carbon mass concentration, (changed from 1.4 times carbon mass th e original equation uses). New terms have also been added for sea salt and for absorption by NO 2 . The apportionment of the total concentration of sulfate compounds into the concentrations of small and large size fractions is accomplished using the following equations:
[ large sulfate ] = [total sulfate] x [total su lfate], for [total sulfate] < 20 μg/m 3 [ large sulfate ] = [ total sulfate ], for [ total sulfate ] ≥ 20 μg/m 3 [ small sulfate ] = [ total sulfate ] - [ large sulfate ]

The same equations are used to apportion total nitr ate and total organic mass into small and large size fractions. Sea salt is calculated as 1.8 x [ chloride ], or 1.8 x [ chlorine ] if the chloride measurement is below detection limits, missing, or invalid. The new e quation contains three distinct water growth terms, designated f S , f L , and f SS for the small and large sulfate and nitrat e fractions, and for sea salt, respectively.

Technical justification for revisions

The new IMPROVE equation for estimating light extinc tion for the RHR contains five major revisions from the original equation:

1) A sea salt term has been added. Sea salt is a par ticular concern for coastal locations where the sum of the major components of light ex tinction and mass has been deficient. 2) The assumed organic mass to organic carbon ratio has been changed from 1.4 to 1.8, to reflect more recent peer-reviewed literature on the subject. 3) The Rayleigh scattering factor has been changed fro m a network-wide constant to a site-specific

value. This factor is based on the elevati on and annual average temperature of individual monitoring sites. 4) A split component extinction efficiency model for sulfate, nitrate, and organic carbon components has been developed. The model includes new water growth terms for sulfate and nitrate to better estimate light extinction at the high and low extremes of the range of extinction.

### 7 5) An NO 2 light absorption term has been added. This te rm can only be used at sites with available

NO 2 concentration data.

Comparison of original versus revised equation

One of the most compelling reasons for developing a revised equation was to reduce the biases in light scattering estimates at the extremes, when compar ed to nephelometer measurements a direct measure particle scattering. To assess the performance of th e new equation, the fractional bias for each sample period was calculated as the difference in estimated aerosol light scattering divided by the measured light scattering using collocated nephelometers. These biases we re then averaged into quintiles to indicate the bias in each of those five subsets of data. Analysis shows that the revised equation has lower fractional bias than the original equation, in all but the haziest conditions.

Scatter plots (Figures 2 and 3) of light scattering esti mates from the original and revised equations versus nephelometer data for all available data at 21 monitoring sites were used to view the overall performance differences. These figures show bias at the extrem es is reduced using the revised, compared to the original, equation (i.e., the points tend to be better centered on the one-to-one line). However, they also show the somewhat reduced precision of the revised e quation compared to the original (i.e., points are more broadly scattered).

Figure 2. Scatter plot of the original IMPROVE equation-estimated particle light scattering versus measured particle light scattering.

Figure 3. Scatter plot of the revised IMPROVE equation-estimated particle light scattering versus measured particle light scattering.

### 8 Directly measured light scattering data from collo cated Optec NGN-2 nephelometers were used to evaluating the performance of the original IM PROVE equation, as well as for development and performance evaluation of several possible versions of the revised equation, leading to the final revised equation approved by the IMPROVE Steering Committ ee. The 21 nephelometer sites used in the

evaluation were:

Acadia National Park, Maine Lye Brook Wilderness, Vermont Big Bend National Park, Texas Mammoth Cave National Park, Kentucky Boundary Waters Canoe Area Wilderness, Minnesota Mount Rainier National Park, Washington Columbia River Gorge National Scenic Area, Oregon Mount Zirkel Wilderness, Colorado Dolly Sods Wilderness, West Virginia Okefenokee National Wildlife Refuge, Georgia Gila Wilderness, New Mexi co Shenandoah National Park, Virginia Grand Canyon National Park, Arizona Shining Rock Wilderness, North Carolina Great Gulf Wilderness, New Hampshire Snoqualmie Pass, Washington Great Smoky Mountains National Pa rk, Tennessee/North Carolina Thre e Sisters Wilderness, Oregon Jarbidge Wilderness, Nevada Upper Buffalo Wilderness, Arkansas Lone Peak Wilderness, Utah

The revised IMPROVE equation reduces the biases co mpared to measurements at the high and low extremes, and is most apparent for the hazier easter n sites. The composition of “best and worst days” is very similar by the original and new equations. Most of the reduction of bias associated with the revised equation is attributed to the use of the split component extinction efficiency method for sulfate, nitrate, and organic components that permitted variable ex tinction efficiency depending on the component mass concentration. The revised equation also contains sp ecific changes incorpora ting a better understanding of the atmosphere based on recent scientific literature . It reflects a more complete accounting for contributors to haze (e.g., sea salt and NO 2 terms), and uses site-specific Rayleigh scattering terms to reduce elevation-related bias. EPA has prepared monthly average f(RH) terms for all IMPROVE monitoring sites for the revised equation. The revi sed equation has been added to the suite of data analysis tools on the Visibility Information Exchange (VIEWS - http://vista.cira.colostate.edu/views/ ) and the WRAP Technical Support System (TSS - http://vista.cira.colostate.e du/tss/Results/Monitoring.aspx ) web sites. A complete discussion and repor t is available on the IMPROVE Web site at http://vista.cira.colostate.edu/IMPROVE /Publications/GrayLit/Gray_literature.htm

.

Effects on Regional Haze Planning in the W RAP Region: Original vs. Revised IMPROVE Equation

The effects of the revised IMPROVE equation on the data used for regional haze planning under the RHR have been evaluated by the AoH Workgroup on a December 9, 2005 call and in more detail at a Workgroup Meeting on January 24-25, 2006. The detailed presentation at: http://wrapair.org/forums/aoh/meetings/0601 24m/Review_of_New_IMP ROVE_Equ_012406_ARS.pdf

, was the basis for the following obser vations from the AoH Workgroup. Analysis of the nature and causes of visibility impairment at the more than 100 CIAs in the WRAP region strongly suggests that control strategies for regional haze planning be evaluated us ing the revised IMPROVE equation, and that results be presented in units of both b ext and dv.

For the purposes of regional haze planning, the revised IMPROVE equation has benefits, as it:



### • incorporates new terms to more completely account for haze;



### • uses updated research information;



### • was developed by comparing to directly-measured op tical light scattering data at collocated sites; and



### • reduces known biases.

For regional haze planning purposes, using the revised IMPROVE equation has some tradeoffs, as it:

### 9 • is a national data analysis and addresses data dist ribution for the whole country, with the associated large sulfate impact dominating Eastern US visibility, and does not as directly address the mix of light extinction causes at Western Class I area monitoring sites;



### • requires that in using the revised equation to the 2000-04 baseline monitoring period would also require that it be applied to as we ll to natural conditions estimates, to insure a consistent calculation of the glide path for each Class I area;



### • has a somewhat greater uncertainty that causes it to mis-select the 20 % worst visibility days for the RHR a little more frequently, altho ugh little difference was observed w ith respect to the composition on those 20 % worst visibility days;



### • chooses a “better fit” for all data across the distribu tion at the sites tested over the better precision of the original IMPROVE equation for individual data points in the middle of the distribution; and



### • has little consequence for SO 4 and NO 3 in the WRAP region in terms of the “ split component extinction efficiency method”, as Figures 4 and 5 be low show – Figure 6 shows that this new method for Organic Mass would have a more profound imp act in the WRAP region, as expected from the episodic impacts of wildland fire emi ssions, as shown on the following page.

While the consistent use of the revised IMPROVE equation is recommended for regional haze planning in the WRAP region as the most useful and robust technical method to support reasonable progress analysis, the revised IMPROVE equation is not endorsed for u se in evaluation of BART modeling results. The interpretation of BART modeling results for screening and subsequent determina tion of BART controls involves consideration of a range of various modeled values, and is a st ate-by-state regulatory decision; a number of WRAP region states have used the original equation in their BART determinations and are quite far along in regulatory rulemaki ng to determine BART controls at this time. As the BART analyses and determinations are not a comprehensive analysis of all sources contributing to or controllable for reasonable progress, and the BART re gulatory findings of individual st ates are based on multiple factors, no recommendation or endorsement of a particul ar light extinction equation is needed.



### Recommendation:

Apply the revised IMPROVE light extinction equa tion as developed and approved in 2005 by the IMPROVE Steering Committee to convert from mass concentration measurements to light extinction for visibility analysis and regional ha ze planning at each WRAP region Class I area.

### 10 Figures 4, 5, 6. Histograms of Sulfate, Nitrate, and Organic Mass concentration data from all IMPROVE sites for 2000-04 in the WRAP (same data in paired charts, lower charts in logarithmic scale).

### 11 2000-04 Baseline Visibility Period Monitoring Data

The RHR requires that data from the IMPROVE mo nitoring sites representing CIAs for the 2000-04 baseline monitoring period is to be used to:



### • Determine the current level of visibility impairment under the RHR;



### • Quantify sources and pollutant species contributing to impairment;



### • Assist in classifying natural and anthropoge nic sources’ contributions to impairment; and



### • Develop regional haze implementation plans dem onstrating reasonable progress across a 60-year timeline toward the Clean Air Act goal of no manmade visibility impairment in CIAs.

A short overview of the IMPROVE monitoring program operations is presented earlier in this document;

additional information is at: http://vista.cira.colostate.edu/improve/

.

Quality Assurance of IMPROVE Monitoring Data

The IMPROVE monitoring program has a Qua lity Assurance Project Plan (QAPP), see: http://vista.cira.colostate.edu/improve/P ublications/QA_QC/IMPROVE_QAPP_R0.pdf , and a Quality Management Plan (QMP), see: http://vista.cira.colostate.edu/improve/Publi cations/QA_QC/IMPROVEAerosolQMP_May2002.PDF ; both were published in 2002. The QMP and QAPP were prepared and the QA activities identified in that QMP and QAPP are executed by the laboratory and fi eld operations contractor team for the IMPROVE aerosol sampler network, institutional members of the contractor team and locations are:



### • Crocker Nuclear Laboratory – University of California, Davis, NC;



### • Research Triangle Institute – Research Triangle Park, NC;



### • Desert Research Institute – Reno, NV; and



### • Environmental Protection Agency – coordinate d by OAQPS, Research Triangle Park, NC.

Staff of the National Park Service, the U.S. Forest Service, and the Cooperative Institute for Research in the Atmosphere (CIRA) at Colorado State University all provide additional quality assurance checks for, and analyses of, the IMPROVE data from the contract or team. The continuity of contractor team members over time, the centralized QA efforts of the contractor team, as well as the additional QA and analytical efforts coordinated by CIRA all combine to provide a very high level of confidence in the IMPROVE data for regulatory planning purposes.

Quality Assurance of the 2000-04 Baseline Monito ring Period WRAP Region IMPROVE Data

Batches of IMPROVE aerosol sampler data ar e published through the VIEWS website, see: http://vista.cira.colostate.edu/views/ . The publication goal for these data is quarterly, sometimes the data are published twice-yearly or an annual update is made depending when updated data are provided by Crocker Nuclear Laboratory. In October 2005, an update specific to the 2000-04 data was made, see: http://vista.cira.colostate.edu/improve/Publicati ons/GrayLit/018_IMPROVEDataResubmission/DataRede liverySummary2005.pdf

.

Crocker Nuclear Laboratory resubmitted all of th e IMPROVE aerosol data to VIEWS for the 2000-04 monitoring period in October 2005. Th e data were resubmitted to correct several errors and discrepancies

### 12 in the data in order to provide the RHR analysts w ith the best available data set. There were four systematic changes that affected large blocks of data:



### • New flow rate validation flags were assigned;



### • Flow rates were recalculated to correct an error in the calculation that existed prior to January 2004;



### • Spectral corrections were applied to sulfur and al uminum data collected beginning in December 2001, when Crocker changed the elemental analysis technique; and



### • Carbon analysis data were resubmitte d to correct a bias in the data.

In addition to these systematic changes, a number of site-specific data problems were resolved and the

data were resubmitted as well. Ex amples included inadvertently swappe d samples, backdated flow rate calibrations, samples requiring reanalysis, and equipmen t problems that were resolved after the original

data had been submitted.

Attribution of Haze Workgroup Review of 2000-04 Baseline Period Monitoring Data

Data completeness was reviewed at the AoH Wo rkgroup meeting of November 16-17, 2005, see: http://wrapair.org/forums/aoh/ meetings/051116m/Summary_of_Reg ional_Haze_Baseline_Data_111605_ ARS.pdf . This was a preliminary assessment, and the IMPROVE data have been updated since that time.

The RHR Tracking Progress guidance document published by EPA in 2003, see: http://www.epa.gov/ttn/oarpg/t1/memoranda/rh_tpurhr_gd.pdf , prescribes the method for calculating the Worst 20% and Best 20% Visibility Days’ metrics to determine the baseline peri od values to be used in regional haze planning. The following steps to calcu late these metrics are already complete in VIEWS and the TSS, using both the original and revised IM PROVE light extinction equations; specific steps are:

• Assemble daily speciated data and monthly f(RH) values from each IMPROVE site for each CIA;

• Perform allowed data substitutions as prescribed in Tracking Progress guidance, if warranted;

• Sites must have at least 3 of 5 years of “complete” data;

• Calculate daily extinction, convert to Haze Index (deciviews);

• Determine the average Haze Index of the 20% worst and best visibility days for each complete year, average these annual values for baseline period statistic; and

• Determine Glide Path by comparing the 2000- 04 baseline value with natural conditions.

Five (5) WRAP region IMPROVE sites did not meet 2000-04 baseline monitoring period data completeness criteria of at least 3 years of data:

• Arizona - (BALD) Mount Baldy

• California - (KAIS) Kaiser and (RAFA) San Rafael

• Utah: - (CAPI) Capitol Reef

• Washington - (NOCA) North Cascades

A site-specific Baseline period value will be calculated for these ClAs on VIEWS and TSS, in consultation with the appropriate state. Methods may include data prior to 2000, data from nearby, representative sites, et cetera.

Recommendation:

Use the 2000-04 Best and Worst Days’ metrics as calculated and reported by VIEWS and TSS. Individual states should review the data complete ness and any data substitutions for their CIAs.

### 13 2064 Natural Visibility Conditions Estimates

Default natural visibility conditions estimates and the associated methodology were published by EPA in

2003 at: http://www.epa.gov/ttn/oarpg/t1/memoranda/rh_envcurhr_gd.pdf . This Estimating Natural Visibility Conditions Under the Regi onal Haze Rule guidance document w as prepared prior to the review of the IMPROVE light extinction equation during 20 05 and provided estimates of natural conditions in haze index units (deciviews) only. Numerous cr iticisms of these estimates have been noted, see the

collection of documents at: http://www.wrapair.org/forums/aamrf/projects/NCB/index.html . These estimates are in terms of the original IMPROVE light extinction equation, and are not comparable to baseline period monitoring metrics calculated with the revised IMPROVE equation.

Regional haze planning in the WRAP region should separately assess reasonable progress toward the national visibility goal by IMPROVE light extinction species, due to the mixture of sulfate, nitrate, carbonaceous aerosols, and soil materials causing West ern visibility impairment, along with the large

amount of natural fire and dust emissions contribu ting to visibility impairment. For those reasons, Alternative Natural Conditions Estimates, in term of deciviews, total light extinction, and IMPROVE species light extinction have been developed, review ed, and proposed for use in regional haze planning;

see: http://vista.cira.colostate.edu/improve/Pub lications/NewsLetters/IMPNews2ndQtr2006.pdf

.

Alternative Natural Visibility Conditions

EPA 2003 RHR guidance 2003 for tracking progress and est imating natural conditions were based on the original IMPROVE equation, providing a consistent set of instructions. see: http://vista.cira.colostate.edu/improve/Pub lications/GuidanceDocs/guidancedocs.htm . As noted earlier, a revised IMPROVE equation was devel oped and approved that mitigated some of the technical criticism of the original IMPROVE equation, especially as it a pplied to implementing the RHR through the regional haze implementation plans due in December 2007. Many of the regional planning organizations (RPOs) and states indicated their preference to use the revi sed equation, but to do so they need natural haze

condition estimates for their CIAs determined in a consistent manner (i.e., by the new IMPROVE equation). The revised IMPROVE equation is described earlier in this document.

Estimates of natural haze levels using either e quation involve applying the equation to estimates of natural species concentrations. The natural species concentration estimates used for this purpose come from the 1990 NAPAP State of Science Report 24 by John Trijonis, see: http://vista.cira.colostate.edu/improve/Publicati ons/Principle/NAPAP_SOS/High%20Res/napap_(high).ht

m

and are typical values for the eastern and western U.S. Some methodology is needed to adjust these typical values to estimate the 20% best and 20% worst values. A goal in developing the new values is to avoid problems identified in the EPA default appr oach. The Natural Haze Levels II Committee was established by the Inter-RPO Monitoring & Data An alysis Workgroup in Spring 2006 to review and refine, as appropriate, a methodolog y developed by Roger Ames (CIRA) for applying the new IMPROVE equation for estimating light extinction from aeroso l concentrations to natural species concentration estimates. Ultimately this would provide natural h aze estimates for the 20% best and 20% worst day for each of the CIAs covered by the RHR. The comm ittee was composed of Marc Pitchford, NOAA; Bill Malm, NPS; Bruce Polkowsky, NPS; Pat Brew er, VISTAS; Tom Moore, WRAP; Ivar Tombach, consultant; John Vimont, NPS; Rich Poirot, Verm ont; Roger Ames, CIRA; and Naresh Kumar, EPRI.

The committee work has b een summarized in an annotated pr esentation that is available at: http://vista.cira.colostate.edu/datawarehou se/improve/docs/naturalhazelevelsIIreport.ppt . This information was presented July 27, 2006 at th e Attribution of Haze Workgroup meeting, see: http://wrapair.org/forums/aoh/ meetings/060726den/index.html and on August 14 at the RPO

### 14 Monitoring/Data Analysis Workgroup conference cal l. Comments received by August 25, 2006 were used to generate an approved appr oach that was forwarded to the indi vidual RPOs for their consideration

and use.

The alternative natural conditions estimates offer a nu mber of advantages for regional haze planning, over the default estimates in EPA guidance. The altern ative conditions are divided into the 6 measured IMPROVE light extinction species, and can still be totale d to estimate total visibility in light extinction or deciviews, using the revised IMPROVE equation. The alternative estimates are based on analyzing and estimating the natural fraction of the 2000-04 baseline period monitoring data at each IMPROVE monitoring site. At more than a dozen sites, the na tural fractions estimated by the alternative method for the 2000-04 data were compared to the period of reco rd (>15 years) data for the same sites, and the alternative method for the 2000-04 period is quite similar to the long period of record since the late 1980s.

Tables 1 through 4 below show example data summa ries for regional haze planning use in documenting

differences between EPA default and alternative met hods of estimating natural conditions at each CIA.

Both EPA default and alternative natural conditions estimates represen t 2064 target values for regional haze planning purposes; the true values are not known at this time, and more analysis is needed to refine these estimates for future regional haze planning cy cles, as anthropogenic emissions are reduced and natural visibility conditions are better measured.

The alternative natural conditions estimates are not u sed in evaluation of BART modeling results, as their use would require the use of the revised IMPROVE e quation, which has not been incorporated into EPA or the Federal Land Managers' Air Quality Rela ted Values Work Group (FLAG) guidance for the evaluating modeling results for impacts from, and control of, individual st ationary sources. The application of the original IMPROVE equation and sp ecified natural conditions in evaluation of BART modeling results is for a fundamentally different pur pose than regional haze planning, as defined in the

EPA BART rule.

While the consistent use of the revised IMPROVE equation is recommended for regional haze planning in the WRAP region as the most useful and robust technical method to support reasonable progress analysis, the revised IMPROVE equation is not endorsed for u se in evaluation of BART modeling results. The interpretation of BART modeling results for screening and subsequent determina tion of BART controls involves consideration of a range of various modeled values, and is a st ate-by-state regulatory decision; a number of WRAP region states have used the original equation in their BART determinations and are quite far along in regulatory rulemaki ng to determine BART controls at this time. As the BART analyses and determinations are not a comprehensive analysis of all sources contributing to or controllable for reasonable progress, and the BART re gulatory findings of individual st ates are based on multiple factors, no recommendation or endorsement of a particul ar light extinction equation is needed.

As the revised IMPROVE equation and alternative na tural conditions estimates recommended for analysis of reasonable progress in the WRAP region were de veloped specifically based on regional haze 2000-04 baseline period monitoring data, the equation and the associated alternative natural conditions estimates were designed to be consistently integrated and used in species and total visibility impact glide paths to natural conditions; allowing assessment of the amount of visibility impairment by species to be reduced from the 2000-04 baseline period through to 2064 for each Class I area. Use of the revised IMPROVE equation and alternative natural c onditions estimates in individual BART analyses process of each state is not necessary and may not be accurate, as BART cont rols are required for implementation by 2012, and the natural conditions already defined in the exis ting EPA or the Federal Land Managers' Air Quality Related Values Work Group (FLAG) guidance are su fficient for screening and evaluation purposes. Further, precise estimates of aerosol mass and size distributions at natural conditions is unknown for

### 15 short-term planning purposes, and will likely by differe nt than the alternative natural conditions current recommended, as over the next ~60 years, anthropoge nic aerosol loadings decrease, more and better aerosol data are collected, and implementation of regional haze control plans move forward.

Recommendation:

Use the alterative Natural Conditions Estimates in combination with the 2000-04 Best and Worst Days’ metrics as calculated and reported by VIEWS and TSS, utilizing the revised IMPROVE equation, for visibility analysis and regional haze planning at each WRAP region Class I area.16Table 1 – Comparison of Natural Visibility Conditions Estimatesusing EPA Default and New Alternative Methods, including the changein Regional Haze Rule Uniform Rate of Progress 2018 Target Values20% Best Days2064 NaturalConditions20% Worst Days2000-04 BaselinePeriod MonitoringData20% Worst Days2064 NaturalConditionsUniform Rate ofProgress: 2018 HazePlanning Milestonefor 20% Worst DaysUniform Rate ofProgress: 2018Visibility ImprovementIncrement for 20%Worst DaysMandatory FederalClass I AreaStateMonitoringSite CodeDefaultmethod(dv)Alt.method(dv)Defaultmethod(dv)Alt.method(dv)Defaultmethod(dv)Alt.method(dv)Defaultmethod(dv)Alt.method(dv)Defaultmethod(dv)Alt.method(dv)Agua TibiaWilderness AreaCA AGTI1Arches NP UT ARCH1Table 2 – Light Extinction Component s of 20% Worst VisibilityDays for 2064 Natural Visibility Conditions Estimates (revisedIMPROVE light extinction equation & alternative method for estimating Natural Visibility Conditions)Light Extinction Components of 20% Worst Days2064 Natural Visibility Conditions EstimatesMandatory FederalClass I AreaStateMonitoringSite Code20% WorstDays 2064NaturalConditionsEstimates (dv)(from Table 1)20% WorstDays 2064NaturalConditionsEstimates(1/Mm)Sulfate(1/Mm)Nitrate(1/Mm)OrganicMaterial(1/Mm)ElementalCarbon(1/Mm)Fine Soil(1/Mm)CoarseMaterial(1/Mm)Agua Tibia Wild. Area CA AGTI1Arches NP UT ARCH1Table 3 – Light Extinction Components of 20% Best Visibility Days for 2064 Natural Visibility Conditions Estimates(revised IMPROVE light extinction equation & alternative method for estimating Natural Visibility Conditions)Light Extinction Components of 20% Best Days2064 Natural Visibility Conditions EstimatesMandatory FederalClass I AreaStateMonitoringSite Code20% BestDays 2064NaturalConditionsEstimates (dv)(from Table 1)20% BestDays 2064NaturalConditionsEstimates(1/Mm)Sulfate(1/Mm)Nitrate(1/Mm)OrganicMaterial(1/Mm)ElementalCarbon(1/Mm)Fine Soil(1/Mm)CoarseMaterial(1/Mm)Agua Tibia Wild. Area CA AGTI1Arches NP UT ARCH117Table 4 - Uniform Rate of Progress: 2018 Haze Planning Milestone for 20% Worst Days and 2018 Visibility Improvement Increment for20% Worst Days, by light extinction component,using Alternative Natural Conditions EstimatesUniform Rate of Progress:2018 Haze Planning Milestone:Light Extinction Components on 20% Worst Days (1/Mm)Uniform Rate of Progress:2018 Visibility Improvement Increment:Light Extinction Components on 20% Worst Days (1/Mm)MandatoryFederal Class IAreaStateMonitoringSite CodeSulfate NitrateOrganicMaterialElementalCarbonFineSoilCoarseMaterialSulfate NitrateOrganicMaterialElementalCarbonFineSoilCoarseMaterialAgua TibiaWilderness AreaCA AGTI1Arches NP UT ARCH1

### 18 2018 Planning Milestone Visibility Projection Values

In order to prepare regional haze implementation pl ans for the initial RHR milestone date of 2018, air quality modeling results comparing the impacts of historic and projected emissions estimates using consistent meteorology have to be pr ojected in terms of monitored visi bility values, using monitoring data from the 2000-04 baseline period as a controlling term . The concept is that both historic and future modeling results contain errors, but by using the monito ring data to control the predictions of the model, the relative change in model results from 2000-04 to 2018 can be a reasonable assessment of likely air quality changes. Several questions about which m onitoring are representative a nd the best to use are discussed next. Information about th e air quality model is also reviewed.

The EPA default guidance method is to use “2002 worst monitored days” to project future visibility conditions in “draft” 2001 EPA guidance, even t hough the RHR requires monitoring data from 2000-04 baseline period to be used as the basis of the regi onal haze implementation plans. This guidance also applies to interpreting the modeling results for PM 2.5 National Ambient Air Quality Standard (NAAQS) attainment demonstrations, and is also closely relat ed to attainment demonstrations required for the Ozone NAAQS. The EPA guidance is found at: http://www.epa.gov/scram001/ guidance/guide/draft_pm.pdf . The purpose of applying the EPA guidance was to develop a series of relative Reduction Factors (RRFs) using monitoring data to control and “fit” historic and projected model predictions, assuming th at the air quality model is better at predicting relative changes in concentration than absolute concentrations.

Basic steps for applying the EPA RRF guidance to project visibility conditions in 2018 at each CIA are:



### • Model species concentrations for 2002;



### • Model species concentrations for 2018 scenario;



### • Determine a species-specific RRF for the average of the 20% worst monitored days (selected from 2002 IMPROVE data), where, for example:



### 3⁄4 RRF sulfate = 2018 sulfate/2002 sulfate



### • Using the selected 20% worst days for 2002, apply the RRF values, such that: 

### 3⁄4 2018 concentration = Average [RRF x Baseline concentration]



### • Calculate projected 2018 visibility valu es for 20% worst days for each CIA.

The 20% best visibility days are pr ojected in the same manner, selec ting the 20% best monitored days from 2002 IMPROVE data. Several issues with this approach are evident when analyzing the regional haze monitoring data and model performance.

Figures 7 through 11, below show the monthly variat ion in the fractional occurrence of worst days at 5 randomly-selected IMPROVE monitoring sites. These figures clearly show a fair amount of inter-annual variation in the distribution of 20% worst monito red visibility days. As the EPA guidance requires the use of specific days only from 2002, these figures demons trate that 2002 is not similar to other years in the 2000-04 baseline period, likely due to variatio n in [mostly] fire and dust emissions, and differences in meteorology from year to year. For this reason, the use of only 2002 for projecting visibility in 2018 is not in keeping with the requirements of the RHR.

### 19 Figures 7, 8, 9, 10, 11. Time Series of Monthly Variation in the Fraction Variation of the 20% Worst Monitored Days at randomly-select ed WRAP region Class I areas.

Agua Tibia, CA (AGTI1) Distribution of 20% Worst Days by Year (IMPROVE data)

0 0.1 0.2 0.3 0.4

1 2 3 4 5 6 7 8 9 10 11 12

Mont h 2001

2002

2003

2004

Salt Creek, NM (SACR1) Distribution of 20% Worst Days by Year (IMPROVE data)

0 0.05 0.1 0.15 0.2 0.25 0.3

1 2 3 4 5 6 7 8 9 10 11 12

MonthFractionof Worst Days 2001

2002

2003

2004

Sawtooth, ID (SAWT1) Distribution of 20% Worst Days by Year (IMPROVE data)

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

1 2 3 4 5 6 7 8 9 10 11 12

MonthFractionof Worst Days 2001

2002

2003

2004

Badlands (BADL1) Distribution of 20% Worst Days by Year (IMPROVE data)

0 0.1 0.2 0.3 0.4 0.5

1 2 3 4 5 6 7 8 9 10 11 12

MonthFractionof Worst Days 2000

2001

2002

2003

2004

Mount Rainier (MORA1) Distribution of 20% Worst Days by Year (IMPROVE data)

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

1 2 3 4 5 6 7 8 9 10 11 12

MonthFractionof Worst Days 2000

2001

2002

2004

### 20 Air quality modeling in support of regional haze im plementation planning is conducted by the WRAP Regional Modeling Center (RMC), see: http://pah.cert.ucr.edu/aqm/308/ . The RMC uses state of the art, regional gridded photochemical models for aero sol modeling called CMAQ and CAMx. Extensive and numerous air quality modeling studies have been perfor med by the RMC over the past 6 years to support regional haze planning in the WRAP region.

Performance of the RMC models for 2002-specific em issions and meteorology is done by comparing air quality modeling results to 2002 monitored results from the IMPROVE and other monitoring networks’ by species; see: http://pah.cert.ucr.edu/aqm/308/reports /final/2002_MPE_report_main_body_FINAL.pdf

. Fire and dust air quality modeling results, and their projection using RRFs wa s considered at a WRAP workshop in May 2006, see: http://www.wrapair.org/foru ms/ioc/meetings/060523m/ . Aerosol sampling at IMPROVE sites is 24 hours in duration, mi dnight to midnight, conducted every-3rd-day, and the hourly modeling results are summed and matched in time . The RMC models provide hourly estimates of visibility and aerosol species concen trations. The modeled gaseous and aerosol species are "mapped" to the IMPROVE and other networks’ observational speci es, to calculate mass and aerosol light extinction in comparable terms. More information on RMC sp ecies mapping is shown in Tables 5 and 6 below.

Table 5 – Mapping of Gaseous RMC Mode l Species to Gaseous Observational Species

### 21 Table 6 – Mapping of Particulate RMC Mode l Species to Particulat e Observational Species

Model results often do not precisely match monitoring data due to temporal, spatial, chemical, and physical limitations in the emissions estimates, the accuracy and precision of the meteorology data employed in the models, and/or the chemical and physics parameterizations in the CMAQ and CAMx models. This is especially true for Coarse Mat erial, and to a lesser degree, Fine Soil, see Figure 12 below. Most dust emissions contributing to mode led fine soil and coarse material have been held constant from 2002 to 2018 in RMC modeling, due to the lack of acceptable methods to project factors causing changes in dust emissions over time. In c ontrast, the RMC has applied average fire emissions of carbonaceous aerosols for the period 2000-04, and believe that those modeling simulations, called the “Plan02” series, provide reasonable mo deling approximations of visi bility impacts in the 2000-04 baseline monitoring period. Other emissions in the Plan02 modeling series are from 2002 and are thought to be representative of the 5-year baseline period. Only 2002 meteorology is used in the Plan02 series; for more information on the Plan02 series, see Plan02 references in Table 1 at: http://pah.cert.ucr.edu/aqm/308/cmaq.shtml

.

### 22 Figure 12. Example Model Performance “Bugle Plot” for 2002 RMC Model Results versus IMPROVE Monitoring Data for all WRAP region Class I areas in the RMC modeling domain.

### 23 WRAP RRF Projection Method

An alternative “WRAP RRF projection method” to use 2000-04 distribution of worst days at each IMPROVE site is proposed for use in lieu of the EPA default RRF method. Due to model performance issues discussed above, the fine soil and coarse material projection values will need to be subjected to additional analysis before using this approach. Fo r sulfate, nitrate, and carbonaceous aerosols, the basic steps for applying the WRAP RRF projection met hod for visibility conditions in 2018 at each CIA

are:



### • Determine daily modeled species concentrations for 2000-04 baseline period using Plan02c modeling results;



### • Determine daily modeled species concentrations for 2018 using Base18b [and subsequent scenarios] modeling results;



### • Determine the distribution and average monthly num ber of 20% worst monitored visibility days in deciviews for each CIA monitori ng site [examples shown in Figures 7-11 above, by converting the fraction of days by month to the nearest integer value for each month, to taling 24 values across 12 months] – this becomes the number of mode led days to select in the next step;



### • Starting with the highest modeled 20% worst days, choose values in order by month from Plan02c and Base18b model results for the associated 2000- 04 average monthly number of worst monitored days as shown above;



### • Apply the modeled ratio by to each IM PROVE light extinction species, for example: 

### 3⁄4 WRAP RRF January highest day modeled sulfate concentration = ( 2018 January modeled sulfate/2002 January modeled sulfate)



### • Report projected 2018 average 20% wors t visibility values for each CIA; and



### • For the appropriate number of worst modeled days by month, also report the deciview, total light extinction, and species extinction and species mass concentration values for each CIA.

The 20% best visibility days would also be projected for 2018 in the same manner, using modeled best days’ values for the Plan02c and Base18b modeli ng simulation results’, using the distribution and average monthly number of 20% best monitored visibility days.

The concept of selecting ratios of visibility modeling results to project future visibility conditions, fitted to the distribution of 20% worst and best monitored days by month for the 2000-04 baseline monitoring period better represents the "20% Wo rst and Best" visibility days for the RHR visibility metric than the EPA default guidance approach of selecting specific days in 2002. The worst and best days are not likely to happen on exactly the same days in 2018, and the fractional monthly variation over the 2000-04 time period is substantial. The WRAP RRF Projecti on Method works around data completeness issues:

• Missing data and/or incomplete data for worst and best days’ monitored distributions from 2002 – a number of WRAP region sites are affected;

• The systematic bias of the 1 in 3-day sampling fre quency of the monitored observations from the 1 in 1-day [actually hourly] frequency of the modeling results; and

• The episodic and substantial nature of dust and fire impacts on individual IMPROVE samplers and CIAs in a particular year.

The WRAP RRF Projection Method provides additio nal benefits for regional haze analysis:

• Determines a common monthly distribution of 20% Worst and Best visibility days to allow a standardized method to compare modeling and monitoring results.

### 24 • Allows regional haze planning to be based on the mo st complete estimates of historic and projected air quality conditions, with longer-term (5 years) of monitoring data used to ground the modeled

values.

• Allows consideration of the quality of emissions and meteorological inputs to the air quality model in conjunction and in balance with limitations of monitoring data for regional haze planning for complex air quality issues such as the impact of fire and dust emissions.

While the consistent use of the revised IMPROVE eq uation is recommended for regional haze planning in the WRAP region as the most useful and robus t technical method to support reasonable progress analysis, the revised IMPROVE equation is not endorsed for use in evaluation of BART modeling results. The interpretation of BART modeling results for screening and subsequent determination of BART controls involves consideration of a range of various modeled values, and is a state-by-state regulatory decision; a number of WRAP region states have used th e original equation in their BART determinations and are quite far along in regulatory rulemaking to de termine BART controls at this time. As the BART analyses and determinations are not a comprehensive analysis of all sources contributing to or controllable for reasonable progress, and the BART regulat ory findings of individual states are based on multiple factors, no recommendation or endorsement of a particular light extinction equation is needed.

As the revised IMPROVE equation and alternative natural conditions estim ates recommended for analysis of reasonable progress in the WRAP region w ere developed specifically based on regional haze 2000-04 baseline period monitoring data, the equation an d the associated alternative natural conditions estimates were designed to be consis tently integrated and used in sp ecies and total visibility impact glide paths to natural conditions; allowing assessment of th e amount of visibility impairment by species to be reduced from the 2000-04 baseline period through to 2064 for each Class I area. Use of the revised IMPROVE equation and alternative natural conditions estimates in individual BART analyses process of each state is not necessary and may not be accurate, as BART controls are required for implementation by 2012, and the natural conditions already defined in the existing EPA or the Federal Land Managers' Air Quality Related Values Work Group (FLAG) guid ance are sufficient for screening and evaluation purposes. Further, precise estimates of aerosol ma ss and size distributions at natural conditions is unknown for short-term planning purposes, and will li kely by different than the alternative natural conditions current recommended, as over the next ~60 years, anthropoge nic aerosol loadings decrease, more and better aerosol data are collected, and impl ementation of regional haze control plans move forward.

Recommendation:

Use the alternative WRAP RRF Projection Method for projecting 2018 visibility conditions in combination with the 2000-04 Best and Worst Days’ metrics as calculated and reported by VIEWS and TSS, utilizing the revised IMPROVE equation and a lternative Natural Conditions Estimates, for visibility analysis and regional haze planning at each WRAP region Class I area. Study the effect of this method for Fine Soil and Coarse Material vi sibility modeling results before applying it to those IMPROVE light extinction species.