# Air Quality Modeling Protocol: Utah Regional Haze F ederal Implementation Plan

November 2015

U.S. Environmental Protection Agency

Region 8 Denver, CO 80202

### i 

## Table of Contents

1.0 INTRODUCTION...................................

................................................... ........... 1

2.0 BACKGROUND.....................................

................................................... ........... 1

3.0 MODELING APPROACH............................................................ ... 2

3.1 Emission Sources.................................................................. 2

3.2 Class I Areas........................................................................ 2

3.3 Pollutants to Consider............................................................. . 3
3.4 Natural Background............................................................... 3
3.5 Visibility Calculation............................................................... 4

4.0 EMISSIONS DATA FOR MODELING................... ............................................. 5
4.1 Baseline Modeling.............................

................................................... ....... 5
4.2 Post-Control Modeling.........................

................................................... .... 6
4.3 Post-Processing of Model Scenarios..................................... ........ 6

5.0 MODELING SYSTEM.........

................................................... ........................... 6

5.1 CALMET........................................

................................................... ......... 7

5.2 CALPUFF...... ...................................................................... 11
5.2.1 Background Ozone Concentrations..................................... 11
5.2.2 Background Ammonia Concentrations.............................. ... 11
5.2.3 Receptor Locations........................................................ 11

5.3 POST-PROCESSING............................................................. 11

5.3.1 POSTUTIL................................................................. 12

5.3.2 CALPOST.................................................................. 13

6.0 PRESENTATION OF RESULTS AND REPORTING........................... 14

APPENDIX A – BACKGROUND CONDITIONS ASSUMED FOR MODE LING...... 15

APPENDIX B – EMISSION ASSUMPTIONS FOR MODELING............... ........... 17

APPENDIX C – CALMET CONTROL FILE INPUTS.................................... .... 20

APPENDIX D – CALPUFF CONTROL FILE INPUTS................................. ...... 21

APPENDIX E – CLASS I RECEPTOR DOMAINS.......................................... .. 22

APPENDIX F – CALPOST CONTROL FILE INPUTS.................................

...... 26

APPENDIX G – POSTUTIL CONTROL FILE INPUTS.............................. ......... 27

APPENDIX H – VISIBILITY IMPACT RESULTS....................................... ..... 28

### 1



### 1.0 INTRODUCTION

In 2005, the U.S. EPA issued final amendments to th e Regional Haze Regulations and Guidelines and published the Guidelines for Best Av ailable Retrofit Technology (BART)

Determinations. 1 

### Along with other requirements, the Guidelines addre ss the methodology for determining which sources must apply BART and the e valuation of control options. In particular, the Guidelines state that the CALPUFF modeling syst em (or another appropriate dispersion model approved by EPA) should be used to predict the visibility improvement expec ted at a Class I area from potential BART control technologi es applied to a single source. The Guidelines also recommend developing a modeling protocol that outlines the approach for modeling visibility improvement.

In accordance with EPA Guidelines, EPA Region 8 use d the CALPUFF model to predict the visibility impacts from Utah’s electric generating units (EGUs) that are subject-to-BART and to evaluate various control options. This air quality modeling protocol documents the methodology used to conduct the air quality dispersion modeling and the approach to determine the improvement in visibility to be achieved by BART. H owever, this protocol does not explain how the visibility results are factored into the BART d etermination process. Information related to the BART determination process appears in the Federal R egister notice and elsewhere in the Docket. All EPA Region 8 modeling files used for this effor t are available upon request. Contact Rebecca Matichuk at matichuk.rebecca@epa.gov.

This document is organized as follows:

• Section 2.0 – Background

• Section 3.0 – Modeling Approach

• Section 4.0 – Emissions Data for Modeling

• Section 5.0 – Modeling System

• Section 6.0 – Presentation of Results and Reporting

2.0 BACKGROUND

In evaluating the Utah’s State Implementation Plan (SIP) revisions and the supporting information submitted by the State, EPA Region 8 de termined that the analysis conducted for the BART Alternatives could not support the analysis of control options for individual BART sources under a five factor analysis. As a result, EPA developed separate CALPUFF modeling, as discussed in this protocol, for this purpose. W hile the Utah modeling assessed the combined impacts of all of the BART and non-BART sources inc luded in the BART Alternative – Carbon, Hunter, and Huntington, the EPA Region 8 modeling a ssesses the impacts of the individual BART sources. In addition, the EPA Region 8 modeli ng assesses the visibility impacts of all of the nitrogen oxide (NOx) BART control technologies found to be technologically feasible, including Low NOx Burners (LNB) with Separated Over -Fire Air (OFA), LNB and SOFA with Selective Non-Catalytic Reduction (SNCR), and LNB a nd SOFA with Selective Non-Catalytic Reduction (SCR). Beyond assessing impacts from ind ividual BART sources and evaluating all technologically feasible control options, the EPA R egion 8 modeling methodology is very

1 70 FR 39104 (July 6, 2005). BART Guidelines, 40 CFR Part 51, Appendix Y.

### 2



### similar to that employed by Utah. 2 

### The details of the modeling conducted by EPA Regio n 8 are provided in the following sections.

3.0 MODELING APPROACH

This section describes the components and informati on required for the CALPUFF modeling.

Each source that causes or contributes to visibilit y impairment in one or more Class I area must conduct a BART analysis to determine the best avail able retrofit technology applicable to that source and quantify the visibility improvement at t he Class I areas associated with BART controls. This section covers the following element s: emission sources; Class I area identification; pollutants considered; natural back ground conditions; and visibility calculations.

3.1 Emission Sources

The sources that EPA Region 8 modeled are listed in Table 1. These include the BART units Hunter 1 and 2 and Huntington 1 and 2. It also incl udes Hunter Unit 3 even though this unit is not part of the Hunter BART source. This unit was m odeled in order to account for the unit’s emission contributions when modeling the other unit s for this source. However, the individual model results or predicted impacts for Hunter Unit 3 were not evaluated for this modeling.

Table 1. Emissions Sources Modeled by EPA
Company Name Plant Name Units PacifiCorp Hunter Plant Boilers #1,2,3 PacifiCorp Huntington Plant Boilers #1,2



### 3.2 Class I Areas

EPA Region 8 modeled the same Class I areas that we re included in the State of Utah’s BART Alternatives modeling. These Class I areas are larg ely within a 300 mile radius of the BART

sources. The federal Class I areas that were modele d are listed in Table 2. Figure 1 is a map that presents the location of the modeled Class I areas in relation to the Utah BART sources. Visibility improvement at these Class I areas will provide the best measure of the effectiveness

of BART.

Table 2. Federal Class I Areas Selected for Modelin g
Source Class I Areas to be Evaluated

PacifiCorp Hunter and Huntington Plants Arches National Park, Black Canyon of the Gunnison National Park, Bryce National Park, Canyonlands Nat ional Park, Capitol Reef National Park, Flat Tops Wilderness Ar ea, Grand Canyon National Park, Mesa Verde National Park, Zio n National Park

2 Air Quality Modeling Protocol: Utah Regional Haze S tate Implementation Plan, Utah Division of Air Qual ity, February 13, 2015.

### 3



### Figure 1. Source Locations in Proximity to Class I Areas

3.3 Pollutants to Consider

The BART Guidelines state that modeling should be c onducted for sulfur dioxide (SO 2 

### ), NO
x 

### and direct particulate matter (PM) emissions, inclu ding particles with a diameter of 10 micrometers or less (PM 10 

### ) and particles with a diameter smaller than 2.5 mi crometers (PM 2.5 

### ). The pollutants modeled for this analysis included S O 2 

### , Sulfate (SO 4 

### ), NO
x 

### , Elemental Carbon (EC), Secondary Organic Aerosol (SOA), PM 2.5 

### , and PM 10 

### . However, the modeling will only

evaluate the NO
x 

### control scenarios for BART sources. The emissions data and emissions assumptions are discussed in more detail in Section 4.0 below.

3.4 Natural Background

The FLAG 2010 report lists two sets of natural cond itions corresponding to the annual average and the 20 percent best natural conditions days. To represent natural visibility background in the Class I areas, the 20 percent best natural days wer e used. This approach is consistent with the previous BART modeling conducted by the state and P acificorp for these sources. The specific natural background values used in this protocol wer e drawn from the FLAG 2010 report. Class I area specific natural background assumptions are pr esented in Appendix A.

### 4



### 3.5 Visibility Calculation

The methodology for performing visibility calculati ons with the CALPUFF modeling system is described in several documents, including:

• Interagency Workgroup on Air Quality Modeling (IWAQ M) Phase 2 Summary Report and Recommendations for Modeling Long Range Transpo rt Impacts, 3



### • Federal Land Manager’s Air Quality Related Values W orkgroup (FLAG): Phase I Report, 4 

### and

• A User's Guide for the CALPUFF Dispersion Model. 5



### The CALPUFF modeling techniques presented in this p rotocol provide ground-level concentrations of visibility impairing pollutants. The concentration estimates from CALPUFF were used with the FLAG 2010 referenced IMPROVE equ ation 6 

### to calculate the extinction coefficient ( b ext 

### ) , as shown below.

b ext 

### = 2.2 × f S 

### (RH) × [Small Sulfate] + 4.8 × f L 

### (RH) × [Large Sulfate]

• 2.4 × f

S 

### (RH) × [Small Nitrate] + 5.1 × f L 

### (RH) × [Large Nitrate]

• 2.8 × [Small Organic Mass] + 6.1 × [Large Organic M ass]

• 10 × [Elemental Carbon]

• 1 × [Fine Soil]

• 0.6 × [Coarse Mass]

• 1.7 × f

SS 

### (RH) × [Sea Salt]

• Rayleigh Scattering (Site Specific)

• 0.33 × [NO 2 

### (ppb)] {or as: 0.1755 × [NO 2 

### ( μ g/m 3 

### )]}

Where: [ ] indicates concentrations in μ g/m 3



### f S 

### (RH) = Relative humidity adjustment factor for sma ll sulfate and nitrate

f L 

### (RH) = Relative humidity adjustment factor for lar ge sulfate and nitrate

f SS 

### (RH) = Relative humidity adjustment factor for sea salt

For Total Sulfate < 20 μ g/m 3 

### : [Large Sulfate] = ([Total Sulfate] / 20 μ g/m 3 

### ) × [Total Sulfate]

For Total Sulfate ≥ 20 μ g/m 3 

### : [Large Sulfate] = [Total Sulfate]

And: [Small Sulfate] = [Total Sulfate] – [Large Sulfate] To calculate large and small nitrate and organic ma ss, substitute ({Large, Small, Total} {Nitrate, Organic Mass}) for Sulfate.

Several metrics are used to evaluate the change in visibility for the BART analysis, including the number of days with impacts greater than 0.5 delta- deciview ( ∆ dv), the number of days with impacts greater than 1.0 ∆ dv, and the change in visibility. The change in vis ibility for the BART

3 Interagency Workgroup on Air Quality Modeling (IWA QM) Phase 2 Summary Report and Recommendations for Modeling Long Range Transport Impacts, Office of Ai r Quality Standards, EPA-454/R-98-019, December 199 8.

4 Federal Land Managers’ Air Quality Related Values W orkgroup (FLAG) 2008. Phase I Report—Revised (2010)

. 5 Scire J.S., D.G. Strimaitis, R.J. Yamartino. “A Use r's Guide for the CALPUFF Dispersion Model.” Earth Tech, Concord, MA, January 2000.

6 Federal Land Managers’ Air Quality Related Values W orkgroup (FLAG) 2008. Phase I Report—Revised (2010)

.

### 5



### analysis is the 98 th 

### percentile deciview change relative to the 20 perc ent best days natural background conditions 7,8 

### The delta-deciview ( ∆ dv) value is calculated from the source’s contribution to extinction, b ext (source) 

### , and background extinction, b ext(bkg) 

### , as follows:

∆ dv = 10 ln ( b ext(bkg) 

### + b ext (source) 

### ) / b ext(bkg) 

### ) 9



### The assumptions or input values used in the equatio ns above are included in Appendix A.

4.0 EMISSIONS DATA FOR MODELING

CALPUFF model inputs require source parameters, inc luding pollutant emission rates and stack data (location, height, diameter, exit gas temperat ure, and exit gas velocity). In accordance with BART Guidelines, the baseline (pre-control) emissio n rates represent the 24-hour average actual emission rate from the highest emitting day of the meteorological period modeled. 10 

### The postcontrol emission rates were calculated as a percent age of pre-control emission rates. This approach is in accordance with the BART Guidelines. The details of the emissions data used in the modeling are discussed below and presented in A ppendix B.

4.1 Baseline Model Scenario

EPA modeled one baseline scenario (referenced as Ba seline) for each source and unit listed in Table 1 and Appendix B. The Baseline scenario refle cts the baseline emission rates. For the Baseline model scenario, the emission rates and sta ck data for the sources listed in Table 1 and Appendix B were based on the information developed by UDAQ for the time period of 2001 to 2003. The highest daily emission rates were derived from emissions information taken from EPA’s Clean Air Markets Division Air Markets Progra m Data (AMPD). This information

formed the basis of the baseline scenarios for all units modeled.

To determine the baseline hourly emission rate, the BART guidelines recommend the use of the 24-hour average actual emission rate from the highe st emitting day occurring during that same period. The daily values from this period were sort ed to identify the maximum emission rate (and date of occurrence). To convert this maximum daily (ton/day) value into the correct lb/hour value required by CALPUFF, the result was divided b y 24 hours/day and multiplied by 2000

lb/ton.

One non-BART source, specifically Hunter Unit 3, wa s included in this modeling. The Baseline for Hunter, Unit 3 was developed using a combinatio n of EPA’s AMPD and information contained within Utah DAQ’s emission inventory data base. The same emission time period of

2001-2003 was used for this case.

Note that the emission rates varied for each source and each unit, but remained constant across each year modeled. Appendix B presents the emission s assumptions for each of the sources that were used in the modeling.

7 70 FR 39119, 39121, 39170.

8 Guidance for Estimating Natural Visibility Conditio ns Under the Regional Haze Rule, Office of Air Qual ity Planning and Standards, Emissions, Monitoring and A nalysis Division, Air Quality Trends Analysis Group , EPA454/B-03-005, September 2003.

9 Federal Land Managers’ Air Quality Related Values W orkgroup (FLAG) 2008. Phase I Report—Revised (2010)

. 10 70 FR 39170.

### 6



### 4.2 Post-Control Model Scenarios

EPA modeled three control scenarios for each source and unit listed in Table 1 and Appendix B. The control scenarios consisted of LNB with SOFA, L NB and SOFA SNCR, and LNB and SOFA with SCR conditions to isolate the impact of d ifferent NO
x 

### control technologies. Similar to the baseline modeling, the emission rates and st ack data for the control scenarios were based on the information developed by UDAQ for the time p eriod of 2001 to 2003. Briefly, the postcontrol emissions for NO
x 

### were determined by multiplying the baseline emissi ons by the percent

reduction associated with the BART control. 11 

### Note that the only differences in the control scenarios are (1) the emission rates for NOx

, 

### and (2) the total sulfate emission rates in the SC R

scenario. For the SCR scenario total sulfate rates were increased to account for the additional production that results from the SCR controls. As s een in the tables presented in Appendix B, the

NO
x 

### emission rates were varied across the different co ntrol scenarios, while the other input parameters were held constant.

Appendix B presents the emissions assumptions for e ach of the sources and each of the scenarios that were used in the modeling.

4.3 Post-Processing of Model Scenarios

Unlike the UDAQ modeling for the BART Alternatives, EPA Region 8 modeled each unit and scenario separately in CALPUFF to isolate the impac t of different NO
x 

### control technologies for individual BART sources under a five factor analysi s. The model results for each unit and scenario were then combined using POSTUTIL to accou nt for the effects of multiple units in

ammonia-limited conditions. Section 5.3 and Table 5 explains the methodology for combining

the CALPUFF results for each unit and scenario.

5.0 MODELING SYSTEM

The visibility impact modeling used the CALPUFF sui te of programs and followed the procedures and recommendations outlined in applicab le documents. For the most part, the regulatory default options were utilized for the CA LPUFF modeling. Details are provided below for the non-default options selected for this model ing. The requirements and recommendations

outlined in the documents listed below were also fo llowed:

• EPA’s Guidance for Estimating Natural Visibility Co nditions under the Regional Haze Rule, 12



### • Appendix W of 40 CFR Part 51, Guideline on Air Qual ity Models, 13



### • Interagency Workgroup on Air Quality Modeling Phase 2 report, 14

11 Refer to Cost of NOx BART Controls on Utah EGUs , from Andover Technology Partners, to EC/R, Inc., October 22, 2015.

12 Guidance for Estimating Natural Visibility Conditio ns Under the Regional Haze Rule, Office of Air Qual ity Planning and Standards, Emissions, Monitoring and A nalysis Division, Air Quality Trends Analysis Group , EPA454/B-03-005, September 2003.

13 Appendix W, 40 CFR Part 51: Revision to the Guideli ne on Air Quality Models: Adoption of a Preferred G eneral Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions; Final Rule, Vol. 70, No. 216, 68218- 68261, November 9, 2005.

14 Interagency Workgroup on Air Quality Modeling (IWAQ M) Phase 2 Summary Report and Recommendations for Modeling Long Range Transport Impacts, Office of Ai r Quality Standards, EPA-454/R-98-019, December 199 8.

### 7



### • Federal Land Managers’ Air Quality Related Values W orkgroup – Phase I Report, 15



### • User's Guide for the CALPUFF Dispersion Model, 16 

### and

• State of Utah BART Modeling Protocol. 17



### Tables listing the specific modeling parameters for each CALPUFF module are located in the Appendices.

The individual CALPUFF modules of the CALPUFF model ing system and the version numbers used in the modeling are presented in Table 3. All modules of the CALPUFF modeling system, with the exception of the CALMET model, were re-run with the updated model scenarios and regulatory default options. The meteorological data provided by the State of Utah were used in the updated modeling. 18



### Table 3. CALPUFF Modeling System
Program Version Level

CALMET 5.8.4 130731

CALPUFF 5.8.4 130731

CALPOST 6.221 080724

POSTUTIL 1.56 070627



### 5.1 CALMET

CALMET is a diagnostic wind model that develops hou rly wind and temperature fields in a three-dimensional, gridded modeling domain. Meteoro logical inputs to CALMET can include surface and upper-air observations from multiple me teorological monitoring stations. The CALMET model can also utilize gridded analysis fiel ds from various mesoscale models, such as

the Fifth-Generation Penn State/NCAR Mesoscale Mode l (MM5), to better represent regional wind flows and complex terrain circulations.

The MM5/CALMET meteorological fields were provided by the State of Utah for 2001, 2002,

and 2003. 19 

### Figure 2 and Figure 3 show the CALMET model domain and the locations of the meteorological observations that were input to CALM ET, including surface, upper-air, and precipitation stations. The model domain is centere d in east-central Utah, and extends to the west covering five Class I areas in Utah, one Class I ar ea in Arizona, and three Class I areas in western Colorado. For most of the technical options , default settings were used in the CALMET input files. Table 5 lists the key user-defined CAL MET settings that were selected, and Appendix C presents the CALMET Control File inputs.

15 Federal Land Managers’ Air Quality Related Values W orkgroup (FLAG) 2008. Phase I Report—Revised (2010)

. 16 Scire J.S., D.G. Strimaitis, R.J. Yamartino. “A Use r's Guide for the CALPUFF Dispersion Model.” Earth Tech, Concord, MA, January 2000.

17 Air Quality Modeling Protocol: Utah Regional Haze S tate Implementation Plan, Utah Division of Air Qual ity, February 13, 2015.

18 While the CALMET configuration did not utilize all of the regulatory default options, EPA Region 8 di d not update the CALMET modeling platform due to the leve l of resources needed to regenerate the meteorologi cal data, and because EPA Region 8 does not have evidence tha t the use of the non-default options incorporated i nto the UDAQ CALMET modeling would substantially affect the model results.

19 The CALMET input/output data are in the docket ava ilable upon request.

### 8



### Figure 2. Modeling Domain and Class I Areas

Briefly, UDAQ used the cell face heights (ZFACE) es tablished by the WRAP in the August 15, 2006 WRAP BART modeling protocol 20 

### that was widely used for western BART analyses. T he cell face heights used in CALMET allow for a more d etailed vertical resolution in the model at the elevations near the plume center-line from the Hunter and Huntington Power Plants. In addition, because the plume is expected to be well mixed at the downwind locations of the Class I areas, the modeled concentrations are not expecte d to be sensitive to cell face heights.

UDAQ also used TERRAD, R1, and R2 settings establis hed by PacifiCorp in their 2012 modeling protocol that included CALMET settings pre viously approved for use under the PSD

program. 21 

### The TERRAD, R1/R2 values had been determined to b e appropriate after reviewing

the distance from the surface stations to the neare st terrain features (TERRAD) and each other (R1/R2). After CALMET was run, PacifiCorp determine d that the windfields were consistent

20 CALMET/CALPUFF Protocol for BART Exemption Screenin g Analysis for Class I Areas in the Western United States, Western Regional Air Partnership Air Qualit y Modeling Forum, August 15, 2006.

21 Air Quality Modeling Protocol: Utah Regional Haze S tate Implementation Plan, Utah Division of Air Qual ity, February 13, 2015. 

### Huntington Plant

Hunt er Plant Flat Tops

Wilderness

Black Canyon of

the Gunnison

Wilderness Arches NP

Canyonlands NP Capitol

Reef NP

Bryce

Canyon NP Zion NP

Grand Canyon NP Mesa Verde NP

### 9



### and there were not any major conflicts between CALM ET and the prognostic MM5 data set or the observations. Therefore, these values were reta ined in the Utah BART Alternative modeling. The surface stations in the modeled area are very s parse in the area between PacifiCorp’s plants and the Class I areas and would therefore have very little influence on surface winds, and even less impact on upper level winds that would transpo rt emissions from the plants to the Class I

areas.

EPA Region 8 did not regenerate the meteorological data using the regulatory default options in CALMET. Instead, EPA Region 8 continued to use the meteorological data provided by the State of Utah for years 2001 to 2003. EPA Region 8 relied on the meteorological data generated by the

State of Utah because of the level of resources nee ded to regenerate the data and there is no evidence that the non-regulatory options would have substantially affected the model results.

Figure 3. Observations Input for CALMET Modeling (O range markers are surface data, light blue markers are precipitation data, and blue diamond markers are upper air data).

### 10



### Table 4. Key User-Defined CALMET Settings

Variable Description Value

PMAP Map Projection LCC (Lambert Conformal Conic) DGRIDKM Grid Spacing (km) 4 NZ Number of Layers 11

ZFACE Cell Face Heights (m) 0, 20, 100, 200, 250, 500, 750, 1000, 2000, 3000, 4000, 5000 RMIN2 Minimum Distance for Extrapolation 1 IPROG Use Gridded Prognostic Model Output 14 (MM5 D ata) RMAX 1 Maximum Radius of Influence (surface layer, km) 10 RMAX 2 Maximum Radius of Influence (layers aloft, k m) 100 TERRAD Radius of Influence for Terrain (km) 20

R1 Relative Weighting of First Guess Wind Field and

Observations (km) 5

R2 Relative Weighting Aloft (km) 50



### 5.2 CALPUFF

The CALPUFF model was used with each of the three y ears of meteorological data to calculate pollutant concentrations at receptors in multiple C lass I areas for all units and control scenarios. In general, the application of CALPUFF uses the reg ulatory default options and follows the procedures and recommendations outlined in applicab le documents. Details of the parameter settings in CALPUFF are provided in Appendix D. How ever, the major features are outlined

below.

• Building downwash effects were included.

• Puff splitting was not used, following the recommen dations outlined in the IWAQM Phase 2 report. 22



### • Hourly ozone files were used to define background o zone concentration. 23 

### Data from Canyonlands were used for the entire domain.

• The background ozone concentration shown in Appendi x D (BCKO3 = 60 ppb) was used only when hourly data were missing.

• The background ammonia concentrations were based on the IWAQM guidance, which for this area is a constant 1 ppb for all months an d sources.

• MESOPUFF II chemical transformation rates were used

.

• The species emitted were the seven identified in CA LPUFF: SO 2 

### , SO 4 

### , NO
x 

### , EC, SOA,

PM 2.5 

### , and PM 10



### .

• The species modeled were the nine identified in CAL PUFF: SO 2 

### , SO 4 

### , NO
x 

### , EC, SOA,

HNO 3 

### , NO 3 

### , PM 2.5 

### , and PM 10



### .

• Pasquill-Gifford Dispersion Coefficients for rural areas were used because the area in the modeling domains is rural.

• All units of each source were modeled separately fo r each model scenario or control scenario and meteorological year.

22 Interagency Workgroup on Air Quality Modeling (IWAQ M) Phase 2 Summary Report and Recommendations for Modeling Long Range Transport Impacts, Office of Ai r Quality Standards, EPA-454/R-98-019, December 199 8.

23 Data were provided by the State of Utah. This data is in the docket and can be made available upon re quest.

### 11



### 5.2.1 Background Ozone Concentrations

The background ozone concentrations are based on th e information developed by UDAQ for the time period of 2001 to 2003. Briefly, data from Can yonlands was used for the entire domain and is representative of regional ozone concentrations for the modeling domain. A background ozone value of 60 ppb was assumed when hourly data were m issing. UDAQ did not use the default value of 80 ppb ozone because this level is not oft en reached in the area.

5.2.2 Background Ammonia Concentrations

The CALPUFF model requires input data to specify re presentative monthly background

ammonia concentrations for use in the transformatio n of gaseous nitric acid to particulate ammonium nitrate and for the formation of particula te ammonium sulfate.

EPA Region 8 relied on the background ammonia conce ntrations used by UDAQ. UDAQ relied on the IWAQM default ammonia value for arid areas, which for this area is a constant 1 ppb for

all months and sources.

5.2.3 Receptor Locations

Predicted visibility impacts were computed at a set of gridded receptor locations for the Class I areas within the area considered for this modeling (see Figure 2). These data are in Appendix E,

and were downloaded from the National Park Service website. 24



### 5.3 POST-PROCESSING

Visibility impacts were calculated from the CALPUFF concentration results using POSTUTIL and CALPOST. POSTUTIL was used to repartition total nitrate by accounting for ammonialimiting conditions. The output from CALPOST provid es the highest deciview impacts on each day from all receptors within each Class I area mod eled and the number of days with impacts greater than 0.5 and 1.0 ∆ dv. Details of the parameter settings in CALPOST an d POSTUTIL are provided in Appendix F and G, respectively, with so me of the major features summarized below:

• For the visibility calculation, Method 8, Mode 5 (M VISBK=8, M8_MODE=5) was employed. This method uses monthly average relative humidity and f(RH) values for each Class I area, which are based on data from FLA G 2010.

• Particulate species for the visibility analysis inc luded SO 4 

### , NO 3 

### , EC, SOA, PM 2.5 

### , and

PM 10



### .

• Natural background extinction calculations used the 20 percent best natural days for each Class I area considered for this modeling. The valu es assumed for the 20 percent best natural days are included in Appendix A.

• Tables providing the monthly relative humidity adju stment factors [f(RH)] and 20 percent best days coefficients are provided in Appe ndix A, and are based on data from

FLAG 2010.

24 National Park Service website with Class I area rec eptor information. http://www2.nature.nps.gov/air/Maps/Receptors/index .cfm. This data is in the docket and can be made av ailable

upon request.

### 12



### • POSTUTIL was used to combine units from sources wit h multiple units and to perform

HNO 3 

### /NO 3 

### repartitioning. However, each unit was processed s eparately by POSTUTIL for each source, scenario, and meteorological year.

• Each unit was processed separately by CALPOST for e ach source, scenario, and meteorological year.

5.3.1 POSTUTIL

The ammonia-limiting correction in the POSTUTIL pos tprocessor was used in all the model simulations to repartition the CALPUFF-predicted ni trate concentrations. This correction in POSTUTIL repartitions the particulate nitrate and g aseous nitric acid concentrations based on

nitrate and sulfate concentrations from all of the units modeled at a given receptor, the available background ammonia, and gridded temperature and hum idity data. The CALPUFF model simulates individual units (or sources) that may ha ve multiple parcels of air originating at each of the units. CALPUFF also assumes that the background ammonia concentration is fully available to react with emissions from each unit, regardless of the number of units or overlapping air parcels. However, in reality, the total emissions f rom the combined units compete for the available ammonia and there is a possibility that d ifferent air parcels can overlap at a Class I area. The ammonia-limiting correction in POSTUTIL i s designed to repartition the available

ammonia to react with emissions from all of the uni ts and overlapping air parcels, thereby avoiding double counting of the background ammonia. EPA Region 8 used the same approach in the modeling for Montana BART sources. 25 

### This approach is a standard configuration in the CALPUFF modeling system.

To apply the ammonia-limiting correction in POSTUTI L, the MNITRATE=1 setting was used,

the CALPUFF data were not scaled to alter the emiss ion rate of all units modeled, and the background ammonia concentrations were assumed to b e a constant 1.0 ppb. To correct for ammonia-limiting conditions in the baseline scenari os, all units from a single source were

combined with the use of POSTUTIL and the MNITRATE setting. For example, the baseline

CALPUFF data files for the three units of the Hunte r Plant were combined in POSTUTIL, and used the MNITRATE=1 setting and the constant 1.0 pp b background ammonia concentration. For the control scenarios, the CALPUFF data file fr om the unit of interest was combined with the baseline CALPUFF data files of the remaining un its by POSTUTIL, along with the MNITRATE=1 setting and the associated background am monia concentration. For example, the

control CALPUFF data file for unit 1 of the Hunter Plant was combined with the baseline

CALPUFF data file for Hunter unit 2 and unit 3. Thi s approach was used to correct for ammonialimiting conditions and isolate the degree of visib ility improvement from the control technology.

The POSTUTIL modeling combinations are outlined in Table 5. Details of the parameter settings in POSTUTIL are provided in Appendix G.

25 Modeling Protocol: Montana Regional Haze Federal I mplementation Plan (FIP) Support, prepared for EPA Region 8 by Alpine Geophysics, LLC, November 21, 20 11.

### 13



### Table 5. POSTUTIL Modeling Combinations

EPA Scenario POSTUITL Combination

Baseline

Hunter – Unit 1 Hunter – Unit 1: Baseline Source Assumptions Hunter – Unit 2: Baseline Source Assumptions Hunter – Unit 3: Baseline Source Assumptions

Baseline

Hunter – Unit 2 Hunter – Unit 1: Baseline Source Assumptions Hunter – Unit 2: Baseline Source Assumptions Hunter – Unit 3: Baseline Source Assumptions

Baseline Huntington – Unit 1 Huntington – Unit 1: Baseline Source Assumptions Huntington – Unit 2: Baseline Source Assumptions

Baseline Huntington – Unit 2 Huntington – Unit 1: Baseline Source Assumptions Huntington – Unit 2: Baseline Source Assumptions

LNB/OFA

Hunter – Unit 1 Hunter – Unit 1: LNB/OFA Source Assumptions Hunter – Unit 2: Baseline Source Assumptions Hunter – Unit 3: Baseline Source Assumptions

LNB/OFA

Hunter – Unit 2 Hunter – Unit 1: Baseline Source Assumptions Hunter – Unit 2: LNB/OFA Source Assumptions Hunter – Unit 3: Baseline Source Assumptions

LNB/OFA Huntington – Unit 1 Huntington – Unit 1: LNB/OFA Source Assumptions Huntington – Unit 2: Baseline Source Assumptions

LNB/OFA Huntington – Unit 2 Huntington – Unit 1: Baseline Source Assumptions Huntington – Unit 2: LNB/OFA Source Assumptions

LNB/OFA and SNCR

Hunter – Unit 1 Hunter – Unit 1: LNB/OFA and SNCR Source Assumption s Hunter – Unit 2: Baseline Source Assumptions Hunter – Unit 3: Baseline Source Assumptions

LNB/OFA and SNCR

Hunter – Unit 2 Hunter – Unit 1: Baseline Source Assumptions Hunter – Unit 2: LNB/OFA and SNCR Source Assumption s Hunter – Unit 3: Baseline Source Assumptions

LNB/OFA and SNCR Huntington – Unit 1 Huntington – Unit 1: LNB/OFA and SNCR Source Assump tions Huntington – Unit 2: Baseline Source Assumptions

LNB/OFA and SNCR Huntington – Unit 2 Huntington – Unit 1: Baseline Source Assumptions Huntington – Unit 2: LNB/OFA and SNCR Source Assump tions

LNB/OFA and SCR

Hunter – Unit 1 Hunter – Unit 1: LNB/OFA and SCR Source Assumptions Hunter – Unit 2: Baseline Source Assumptions Hunter – Unit 3: Baseline Source Assumptions

LNB/OFA and SCR

Hunter – Unit 2 Hunter – Unit 1: Baseline Source Assumptions Hunter – Unit 2: LNB/OFA and SCR Source Assumptions Hunter – Unit 3: Baseline Source Assumptions

LNB/OFA and SCR Huntington – Unit 1 Huntington – Unit 1: LNB/OFA and SCR Source Assumpt ions Huntington – Unit 2: Baseline Source Assumptions

LNB/OFA and SCR Huntington – Unit 2 Huntington – Unit 1: Baseline Source Assumptions Huntington – Unit 2: LNB/OFA and SCR Source Assumpt ions



### 5.3.2 CALPOST

The CALPOST postprocessor was used to calculate the visibility impacts from the individual sources at a given receptor for each meteorological year modeled. The visibility impacts were determined by comparing the impacts of sulfate, nit rate, nitrogen dioxide, course particulate matter (PM 10 

### ), and fine particulate matter (PM 2.5 

### ) from the sources to the 20 percent best days natural background conditions at each Class I area (i.e., delta-deciview [ ∆ dv]). The ∆ dv calculations followed the FLAG 2010 guidance. In pa rticular, Method 8 was used to assess the visibility impacts of the individual BART sources. Method 8 uses an improved algorithm to estimate the light scattering and visibility impair ment caused by air pollutants. To ensure compliance with the FLAG 2010 guidance, the CALPOST setting MVISCHECK was set to 1. All settings that comply with MVISCHECK, include:

### 14



### • MVISBK = 8 to invoke the latest FLAG guidance (late st IMPROVE equation); and

• M8_MODE = 5 to use species specific relative humidi ty factors.

The species concentrations of the 20 percent best d ays natural background conditions at each Class I area are defined in Appendix A, Table A-1. The species-specific relative humidity adjustment factors for each Class I area are define d in Appendix A, Table A-2 to Table A-4.

6.0 PRESENTATION OF RESULTS AND REPORTING

The change in visibility impairment (i.e., delta-de ciview [ ∆ dv]) for the visibility modeling is

based on the increase in the haze index from a sour ce relative to natural background, defined as the 20 percent best natural visibility days for eac h Class I area. EPA has recognized that the CALPUFF model can be conservative in estimating vis ibility impairment, and therefore, consistent with the BART Guidelines, the change in visibility impairment will be based on the

98 th 

### percentile model results instead of the maximum mo deled visibility impairment to address the possibility of model over predictions. 26 

### The FLAG 2010 guidance also recognizes that the visibility impairment is based on the 98 th 

### ∆ dv percentile value (or 8 th 

### highest value).

Visibility impacts were tabulated using the output from CALPOST. As noted above, CALPOST provides the ranked deciview impacts on each day fr om all receptors within each Class I area modeled and the number of days with impacts greater than 0.5 and 1.0 ∆ dv. The analysis of the

results are summarized below:

• The 98 th 

### percentile value was reported to three decimal pla ces because of the level of precision reported by CALPOST. This value was based on the 8 th 

### highest day for each year. The results are reported for each source unit , model scenario, Class I area, and model year. (see Appendix H, Tables H-1 to H-4)

• The change in visibility based on the 98 th 

### percentile deciview change relative to the 20 percent best days natural background conditions. Th is is based on the difference between the baseline and control scenario for the same year . The results are reported for each source unit, model scenario, Class I area, and mode l year. (see Appendix H, Tables H-1 to H-4)

• The maximum change in visibility based on the 98 th 

### percentile deciview change relative to the 20 percent best days natural background cond itions for each source unit, model scenario, and Class I area. This is based on the ma ximum improvement among the

difference between the baseline and control scenari o for the same model year at each Class I area. (see Appendix H, Tables H-5 to H-8).

• The number of days with impacts greater than 0.5 an d 1.0 ∆ dv. The results are reported for each source unit, model scenario, Class I area, and model year. (see Appendix H, Tables H-9 to H-12).

• The total number of days between 2001 and 2003 with impacts greater than 0.5 and 1.0

∆ dv. The results are reported for each source unit, model scenario, and Class I area. (see Appendix H, Tables H-13 to H-16).

The visibility impacts for all modeled scenarios ar e reported in Appendix H. This includes the impacts for each BART unit at all modeled Class I a reas and meteorological years.

26 40 CFR 51 Appendix Y.IV.D. and 70 FR 39121.

### 15



### APPENDIX A – BACKGROUND CONDITIONS ASSUMED FOR MODE LING

Table A-1. 20 Percent Best Natural Background Condi tions by Aerosol Component and Class I Area [ μ g/m 3 

### ]

Class I Area Ammonium

Sulfate Ammonium

Nitrate Organic

Carbon Elemental

Carbon SOIL Coarse

Matter Sea Salt Rayleigh [Mm -1 ]

Arches NP 0.07 0.06 0.23 0.01 0.14 0.89 0.01 9 Bryce Canyon NP 0.04 0.05 0.18 0.01 0.10 0.60 0.00 9 Canyonlands NP 0.07 0.06 0.23 0.01 0.14 0.89 0.01 9 Capitol Reef NP 0.06 0.07 0.26 0.01 0.15 0.79 0.01 9

Zion NP 0.05 0.06 0.28 0.01 0.10 0.60 0.01 Black Canyon of

the Gunnison NP 0.06 0.04 0.24 0.01 0.13 0.88 0.00 9

Mesa Verde NP 0.06 0.05 0.24 0.01 0.17 0.67 0.00 9 Grand Canyon NP 0.04 0.03 0.12 0.01 0.10 0.59 0.00 9 Flat Tops

Wilderness 0.04 0.03 0.14 0.01 0.08 0.36 0.00 8



### Values gathered from Table 5 of the Federal Land Ma nagers’ Air Quality Related Values Workgroup (FLAG) 2008. Phase I Report—Revised (2010).



### Table A-2. Monthly f L 

### (RH) – Large (NH 4 

### ) 2 

### SO 4 

### and NH 4 

### NO 3 

### Relative Humidity Adjustment Factors by Month and Class I Area

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Arches NP 2.28 2.12 1.73 1.57 1.5 1.28 1.34 1.47 1. 51 1.56 1.9 2.13 Bryce Canyon

NP 2.15 2.05 1.83 1.75 1.74 1.51 1.59 1.78 1.8 1.68 1. 96 2.06

Canyonlands NP 2.31 2.16 1.82 1.56 1.47 1.26 1.3 1. 46 1.46 1.55 1.87 2.15 Capitol Reef NP 2.32 2.16 1.78 1.58 1.51 1.28 1.36 1.53 1.55 1.58 1.93 2.17

Zion NP 2.36 2.22 1.84 1.63 1.54 1.31 1.36 1.52 1.5 5 1.61 1.95 2.22 Black Canyon of

the Gunnison NP 2.45 2.25 1.98 1.57 1.61 1.31 1.62 1.87 1.75 1.66 2 .01 2.3

Mesa Verde NP 2.32 2.18 1.83 1.56 1.45 1.26 1.24 1. 38 1.4 1.51 1.84 2.14 Grand Canyon

NP 2.13 2.01 1.74 1.46 1.36 1.19 1.29 1.49 1.47 1.5 1. 75 1.98

Flat Tops

Wilderness 2.09 2.04 1.87 1.84 1.86 1.62 1.59 1.7 1.79 1.72 1. 97 2.03



### Values gathered from Table 7 of the Federal Land Ma nagers’ Air Quality Related Values Workgroup (FLAG) 2008. Phase I Report—Revised (2010).



### Table A-3. Monthly f S 

### (RH) – Small (NH 4 

### ) 2 

### SO 4 

### and NH 4 

### NO 3 

### Relative Humidity Adjustment Factors by Month and Class I Area

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Arches NP 2.96 2.7 2.09 1.84 1.75 1.4 1.49 1.69 1.7 6 1.83 2.33 2.69 Bryce Canyon

NP 2.71 2.56 2.23 2.12 2.12 1.75 1.87 2.17 2.21 2 2.42 2.57

Canyonlands NP 3.02 2.77 2.23 1.84 1.7 1.38 1.42 1. 67 1.67 1.81 2.3 2.75 Capitol Reef NP 3.03 2.77 2.17 1.86 1.76 1.4 1.52 1 .78 1.81 1.87 2.38 2.77

Zion NP 3.1 2.86 2.27 1.94 1.81 1.45 1.52 1.77 1.81 1.91 2.43 2.86 Black Canyon of

the Gunnison NP 3.32 2.96 2.55 1.88 1.96 1.46 1.94 2.35 2.13 2.04 2 .57 3.06

Mesa Verde NP 3.05 2.81 2.26 1.84 1.67 1.37 1.33 1. 54 1.58 1.75 2.25 2.72 Grand Canyon

NP 2.73 2.53 2.12 1.69 1.52 1.27 1.42 1.72 1.69 1.74 2 .11 2.49

Flat Tops

Wilderness 2.61 2.53 2.28 2.26 2.31 1.91 1.86 2.04 2.19 2.06 2 .42 2.51

### 16

Values gathered from Table 8 of the Federal Land Ma nagers’ Air Quality Related Values Workgroup (FLAG) 2008. Phase I Report—Revised (2010).



### Table A-4. Monthly f SS 

### (RH) – Sea Salt Relative Humidity Adjustment Factor s by Month

and Class I Area

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Arches NP 3.25 2.99 2.26 1.97 1.86 1.48 1.59 1.82 1 .88 1.96 2.6 3.02 Bryce Canyon

NP 3.24 3 2.4 1.96 1.8 1.45 1.52 1.8 1.78 1.93 2.52 2. 99

Canyonlands NP 3.3 3.04 2.33 1.99 1.87 1.48 1.63 1. 9 1.94 2 2.64 3.07 Capitol Reef NP 3.35 3.11 2.45 2.08 1.93 1.54 1.62 1.9 1.94 2.05 2.68 3.13

Zion NP 3.26 3.03 2.44 1.96 1.78 1.44 1.41 1.66 1.6 7 1.88 2.48 2.98 Black Canyon of

the Gunnison NP 3.05 2.89 2.47 2.31 2.28 1.89 2.04 2.36 2.37 2.18 2 .71 2.92

Mesa Verde NP 3.4 3.1 2.61 1.95 2 1.53 2.04 2.45 2. 28 2.05 2.69 3.15 Grand Canyon

NP 2.93 2.73 2.26 1.78 1.61 1.32 1.5 1.85 1.79 1.84 2. 29 2.7

Flat Tops

Wilderness 2.99 2.88 2.54 2.47 2.47 2.07 2.03 2.23 2.35 2.25 2 .75 2.89



### Values gathered from Table 9 of the Federal Land Ma nagers’ Air Quality Related Values Workgroup (FLAG) 2008. Phase I Report—Revised (2010).

### 17



### APPENDIX B – EMISSION ASSUMPTIONS FOR MODELING

Table B.1 – Modeling Assumptions for PacifiCorp - H unter Unit 1
CALPUFF Inputs Baseline LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR

SO 2 

### (lb/hr) 570 570 570 570

Total Sulfate (SO 4 

### )(lb/hr) 0.11 0.11 0.11 1.64

NOx (lb/hr) 2388 1202 944.772 298

HNO 3 

### 0 0 0 0

NO 3 

### 0 0 0 0

EC 0.219 0.219 0.219 0.219

SOA 4.75 4.75 4.75 4.75

PM 2.5 

### (lb/hr) 29.329 29.329 29.329 29.329

PM 10-2.5 

### (coarse PM)(lb/hr) 1.33 1.33 1.33 1.33

Stack Height (meters) 183 183 183 183

Base Elevation (meters) 1720 1720 1720 1720

Stack Diameter (meters) 7.3 7.3 7.3 7.3
Exit Velocity (meters/second) 17.3 17.3 17.3 17.3

Exit Temperature (Kelvin) 317 317 317 317

Table B.2 – Modeling Assumptions for PacifiCorp - H unter Unit 2
CALPUFF Inputs Baseline LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR

SO 2 

### (lb/hr) 570 570 570 570

Total Sulfate (SO 4 

### )(lb/hr) 0.10 0.10 0.10 1.53

NOx (lb/hr) 1975 1044 822.672 259

HNO 3 

### 0 0 0 0

NO 3 

### 0 0 0 0

EC 0.229 0.229 0.229 0.229

SOA 4.96 4.96 4.96 4.96

PM 2.5 

### (lb/hr) 30.61 30.61 30.61 30.61

PM 10-2.5 

### (coarse PM)(lb/hr) 1.4 1.4 1.4 1.4

Stack Height (meters) 183 183 183 183

Base Elevation (meters) 1720 1720 1720 1720

Stack Diameter (meters) 7.3 7.3 7.3 7.3
Exit Velocity (meters/second) 17.3 17.3 17.3 17.3

Exit Temperature (Kelvin) 317 317 317 317

Table B.3 – Modeling Assumptions for PacifiCorp - H unter Unit 3
CALPUFF Inputs Baseline LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR

SO 2 

### (lb/hr) 269.8 269.8 269.8 269.8

Total Sulfate (SO 4 

### )(lb/hr) 0.37 0.37 0.37 0.37

### 18

NOx (lb/hr) 1240.3 1240.3 1240.3 1240.3

HNO 3 

### 0 0 0 0

NO 3 

### 0 0 0 0

EC 0.275 0.275 0.275 0.275

SOA 5.945 5.945 5.945 5.945

PM 2.5 

### (lb/hr) 19.478 19.478 19.478 19.478

PM 10-2.5 

### (coarse PM)(lb/hr) 18.9 18.9 18.9 18.9

Stack Height (meters) 182.88 182.88 182.88 182.88

Base Elevation (meters) 1736.61 1736.61 1736.61 173 6.61

Stack Diameter (meters) 7.3 7.3 7.3 7.3
Exit Velocity (meters/second) 13.4 13.4 13.4 13.4

Exit Temperature (Kelvin) 322 322 322 322

Table B.4 – Modeling Assumptions for PacifiCorp - H untington Unit 1
CALPUFF Inputs Baseline LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR

SO 2 

### (lb/hr) 595 595 595 595

Total Sulfate (SO 4 

### )(lb/hr) 0.10 0.10 0.10 1.55

NOx (lb/hr) 2260 1338 1047.654 301

HNO 3 

### 0 0 0 0

NO 3 

### 0 0 0 0

EC 0.229 0.229 0.229 0.229

SOA 4.96 4.96 4.96 4.96

PM 2.5 

### (lb/hr) 30.610 30.610 30.610 30.610

PM 10-2.5 

### (coarse PM)(lb/hr) 1.4 1.4 1.4 1.4

Stack Height (meters) 183 183 183 183

Base Elevation (meters) 1964 1964 1964 1964

Stack Diameter (meters) 7.3 7.3 7.3 7.3
Exit Velocity (meters/second) 19.6 19.6 19.6 19.6

Exit Temperature (Kelvin) 317 317 317 317

Table B.5 – Modeling Assumptions for PacifiCorp – H untington Unit 2
CALPUFF Inputs Baseline LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR

SO 2 

### (lb/hr) 595.5 595.5 595.5 595.5

Total Sulfate (SO 4 

### )(lb/hr) 0.11 0.11 0.11 1.61

NOx (lb/hr) 2014 1166 915.31 261

HNO 3 

### 0 0 0 0

NO 3 

### 0 0 0 0

EC 0.220 0.220 0.220 0.220

SOA 4.76 4.76 4.76 4.76

### 19

PM 2.5 

### (lb/hr) 29.319 29.319 29.319 29.319

PM 10-2.5 

### (coarse PM)(lb/hr) 1.4 1.4 1.4 1.4

Stack Height (meters) 183 183 183 183

Base Elevation (meters) 1964 1964 1964 1964

Stack Diameter (meters) 7.3 7.3 7.3 7.3
Exit Velocity (meters/second) 19.6 19.6 19.6 19.6

Exit Temperature (Kelvin) 317 317 317 317

### 20



### APPENDIX C – CALMET CONTROL FILE INPUTS

Variable Description Value

INPUT GROUP 1

IBYR Year 2001, 2002, 2003

IBTZ Base Time Zone 7 IRTYPE Run Type 1 LCALGRD Compute Data Fields for CALGRD T

INPUT GROUP 2 PMAP Map Projection LCC (Lambert Conformal Conic) DGRIDKM Grid Spacing (km) 4 NZ Number of Layers 11 ZFACE Cell Face Heights (m) 0,20,100,200,350,500,75 0,1000,2000,3000,4000,5000

INPUT GROUP 4

NOOBS No Observation Mode 0

INPUT GROUP 5

IWFCOD Model selection variable 1 IFRADJ Froude number adjustment 1

IKINE Kinematic effects 0 IOBR Use O’Brien procedure 0 ISLOPE Slope flow effects 1 IEXTRP Extrapolate surface wind observations 1 ICALM Extrapolate calm surface winds 0

BIAS Biases for weights of surface/upper air

stations All 0

RMIN2 Minimum Distance for Extrapolation 1 IPROG Use Gridded Prognostic Model Output 14 (MM5 D ata) ISTEPPG Time Step (hours) 1 LVARY Use varying radius of influence F RMAX 1 Max Radius Influence (surface layer/km) 10 RMAX 2 Max Radius Influence (layers aloft, km) 100 RMIN Minimum radius of influence (km) 0.1 TERRAD Radius of Influence for Terrain (km) 20

R1 Relative Weighting of First Guess Wind

Field and Observations (km) 5

R2 Relative Weighting Aloft (km) 50 IDIOPT 1 Surface temperature 0 IDIOPT 2 Upper air lapse rate 0 ZUPT Lapse rate depth (m) 200 IDIOPT 3 Average wind components 0 IUPWND Upper air station 1
ZUPWND (1) ZUPWND (2) Bottom and top of layer for domain scale

winds (m) 1, 1000 1, 1000 IDIOPT4 Surface wind components 0 IDIOPT5 Upper air wind components 0

INPUT GROUP 6 IAVEZI Spatial averaging 1

MNMDAV Max search radius 1 HAFANG Half angle for averaging (deg) 30 ILEVZI Layer of winds in averaging 1 ZIMAX Maximum overland mixing height (m) 4000 ITPROG 3D temperature source 1 IRAD Interpolation type 1 TRADKM Radius of influence – temperature (km) 500

NUMTS Maximum number of Stations 12 IAVET Spatial averaging of temperatures 1 NFLAGP Precipitation interpolation 2

### 21



### APPENDIX D – CALPUFF CONTROL FILE INPUTS

Variable Description Value

INPUT GROUP 1

METRUN Control parameter for running all periods in met file 0

IBYR Starting year 2001, 2002, 2003

XBTZ Base time zone 7 NSPEC Number of chemical species modeled 9 NSE Number of species emitted 7 METFM Meteorological data format 1

INPUT GROUP 2

MGAUSS Vertical distribution in near field 1 MCTADJ Terrain adjustment method 3 MCTSG Subgrid scale complex terrain 0 MSLUG Elongated puffs 0 MTRANS Transitional plume rise 1 MTIP Stack tip downwash 1

MSHEAR Vertical wind shear 0 MSPLIT Puff splitting allowed? 0

MCHEM Chemical mechanism 1 MAQCHEM Aqueous phase transformation 0

MWET Wet removal 1 MDRY Dry deposition 1 MTILT Gravitational Settling 0 MDISP Dispersion Coefficients 3 MROUGH Adjust sigma for roughness 0 MPARTL Partial plume penetration of inversions 1 MTINV Strength of Temperature Inversion 0

MPDF PDF for convective conditions 0

MSGTIBL Sub-Grid module used for shore line 0 MBCON Boundary Conditions Modeled 0

INPUT GROUP 4 PMAP Map projection LCC DGRIDKM Grid spacing 4

ZFACE Cell face heights (m) 0,20,100,200,350,500,750,1000,2000,3000 ,4000,5000

INPUT GROUP 6

NHILL Number of terrain features 0

INPUT GROUP 7

Dry Gas Deposition Chemical parameters for dry gas deposition Defaults

INPUT GROUP 8

Dry Particle Deposition Size parameters for dry particle deposition SO 4 , NO 3 , PM 2.5 , PM 10 Geometric Mass Mean Diameter [μm]

0.48 Geometric Standard Deviation [μm]

2.00

INPUT GROUP 11 MOZ Ozone Input option 1 BCK03 Background ozone – all months (ppb) 60.0 BCKNH3 Background ammonia (ppb) 1.0

INPUT GROUP 12 XMAXZI Maximum mixing height (m) 3000 XMINZI Minimum mixing height (m) 50

### 22



### APPENDIX E – CLASS I RECEPTOR DOMAINS

Figure E.1 – Arches National Park Receptors for Mod eling

Figure E.3 – Bryce Canyon National Park Receptors f or Modeling

### 23

Figure E.4 – Canyonlands National Park Receptors fo r Modeling

Figure E.5 – Capitol Reef National Park Receptors f or Modeling

### 24

Figure E.6 – Flat Tops Wilderness Area Receptors fo r Modeling

Figure E.7 – Grand Canyon National Park Receptors f or Modeling

### 25

Figure E.8 – Mesa Verde National Park Receptors for Modeling

Figure E.9 – Zion National Park Receptors for Model ing

### 26



### APPENDIX F – CALPOST CONTROL FILE INPUTS

Variable Description Value

INPUT GROUP 1 ASPEC Species to Process VISIB ILAYER Layer/deposition code 1 A,B Scaling factors 0,0 LBACK Add background concentrations? F

BTZONE Base time zone 7

INPUT GROUP 2 MVISCHECK Test Visibility Options for Conformity to FLAG 2008 T RHMAX Maximum Relative Humidity 95

LVSO4 Sulfate included in extinction T

LVNO3 Nitrate included in extinction T LVOC Organic Carbon included in extinction T

LVPMC Coarse Particles included in extinction T

LVPMF Fine Particles included in extinction T

LVEC Elemental Carbon included in extinction T LVNO2 NO2 Absorption T LVBK Include background? T

EEPMC Extinction efficiencies for Coarse PM 0.6

EEPMF Extinction efficiencies for Fine PM 1.0 EEPMCBK Extinction efficiencies for Background Co arse PM 0.6

EESO4 Extinction efficiencies for Ammonium Sulfat e 3.0

EENO3 Extinction efficiencies for Ammonium Nitrat e 3.0 EEOC Extinction efficiencies for Organic Carbon 4 .0

EESOIL Extinction efficiencies for Soil 1.0

EEEC Extinction efficiencies for Elemental Carbon 10.0

EENO2 Extinction efficiencies for NO2 Gas 0.1755 MVISBK Visibility calculation method 8 BKSO4 Background concentrations for SO4 Table A-1 BKNO3 Background concentrations for NO3 Table A-1 BKPMC Background concentrations for Coarse PM Tabl e A-1 BK OC Background concentrations for Organic Carbon Table A-1 BKSOIL Background concentrations for Soil Table A- 1 BKEC Background concentrations for Elemental Carbo n Table A-1 M8_Mode Relative Humidity Adjustment Factors 5 BKSALT Background concentrations for Sea Salt Table A-1 RHFSML Relative Humidity Adjustment Factors for Sma ll Table A-3 RHFLG Relative Humidity Adjustment Factors for Larg e Table A-2 RHFSEA Relative Humidity Adjustment Factors for Sea Salt Table A-4 BEXTRAY Extinction due to Rayleigh scattering Tab le A-1

### 27



### APPENDIX G – POSTUTIL CONTROL FILE INPUTS

Variable Description Value

INPUT GROUP 1 NSPECINP Number of species to process from CALPUFF runs 9 NSPECOUT Number of species to write to output file 9

NSCALED Number of CALPUFF data files that will be s caled 0 MNITRATE Recompute the HNO 3 /NO 3 partition for concentrations? 1 NH3TYP What is the input source of Ammonia? 3 BCKNH3 Background ammonia concentration (ppb) used for HNO 3 /NO 3 partition 1.028APPENDIX H – VISIBILITY IMPACT RESULTSTable H.1 – Predicted Visibility Impacts for Pacificorp – Hunter Unit 1.Class I AreaYearBaselineLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCR98th PercentileImpact (∆dv)98th PercentileImpact (∆dv)VisibilityImprovement (∆dv)98th PercentileImpact (∆dv)VisibilityImprovement (∆dv)98th PercentileImpact (∆dv)VisibilityImprovement (∆dv)Arches NP2001 4.601 3.864 0.737 3.695 0.906 3.259 1.3422002 4.362 3.689 0.673 3.532 0.830 3.127 1.2352003 3.575 2.967 0.608 2.835 0.740 2.513 1.062Black Canyon NP20010.8550.6960.1590.6620.1930.5740.28120021.0970.8990.1980.8560.2410.7520.34520030.9540.7810.1730.7430.2110.6520.302Bryce Canyon NP2001 0.869 0.699 0.170 0.662 0.207 0.570 0.2992002 1.833 1.527 0.306 1.461 0.372 1.299 0.5342003 0.477 0.394 0.083 0.373 0.104 0.323 0.154Canyonlands NP20015.3564.5100.8464.3151.0413.8111.54520025.2594.4900.7694.3110.9483.8441.41520035.6424.9620.6804.7690.8734.2801.362Capitol Reef NP2001 3.645 3.092 0.553 3.001 0.644 2.747 0.8982002 4.606 3.967 0.639 3.856 0.750 3.493 1.1132003 3.931 3.319 0.612 3.181 0.750 2.832 1.099Flat Tops Wilderness20010.9070.7320.1750.6940.2130.6030.30420021.2811.0500.2311.0010.2800.8770.40420031.2411.0150.2260.9670.2740.8460.395Grand Canyon NP2001 1.090 0.892 0.198 0.852 0.238 0.754 0.3362002 1.891 1.542 0.349 1.465 0.426 1.273 0.6182003 0.854 0.693 0.161 0.660 0.194 0.581 0.273Mesa Verde NP20011.2080.9890.2190.9420.2660.8260.38220021.0800.8880.1920.8470.2330.7450.33520031.3271.0920.2351.0410.2860.9010.426Zion NP2001 0.963 0.779 0.184 0.739 0.224 0.640 0.3232002 0.957 0.783 0.174 0.745 0.212 0.650 0.3072003 0.223 0.192 0.031 0.192 0.031 0.185 0.03829Table H.2 – Predicted Visibility Impacts for Pacificorp – Hunter Unit 2.Class I AreaYearBaselineLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCR98th PercentileImpact (∆dv)98th PercentileImpact (∆dv)VisibilityImprovement (∆dv)98th PercentileImpact (∆dv)VisibilityImprovement (∆dv)98th PercentileImpact (∆dv)VisibilityImprovement (∆dv)Arches NP20014.601 4.032 0.569 3.890 0.711 3.521 1.08020024.362 3.842 0.520 3.713 0.649 3.372 0.99020033.575 3.106 0.469 2.995 0.580 2.721 0.854Black Canyon NP20010.8550.7350.1200.7070.1480.6260.22920021.0970.9440.1530.9080.1890.8180.27920030.9540.8190.1350.7880.1660.7090.245Bryce Canyon NP20010.869 0.736 0.133 0.705 0.164 0.626 0.24320021.833 1.599 0.234 1.542 0.291 1.404 0.42920030.477 0.416 0.061 0.398 0.079 0.356 0.121Canyonlands NP20015.3564.6980.6584.5340.8224.1061.25020025.2594.6630.5964.5130.7464.1201.13920035.6425.0800.5625.0020.6404.6001.042Capitol Reef NP20013.645 3.179 0.466 3.107 0.538 2.910 0.73520024.606 4.115 0.491 3.983 0.623 3.734 0.87220033.931 3.462 0.469 3.347 0.584 3.052 0.879Flat Tops Wilderness20010.9070.7730.1340.7410.1660.6630.24420021.2811.1010.1801.0580.2230.9530.32820031.2411.0650.1761.0240.2170.9200.321Grand Canyon NP20011.090 0.935 0.155 0.901 0.189 0.816 0.27420021.891 1.616 0.275 1.551 0.340 1.385 0.50620030.854 0.724 0.130 0.695 0.159 0.624 0.230Mesa Verde NP20011.2081.0370.1710.9970.2110.8960.31220021.0800.9320.1480.8960.1840.8090.27120031.3271.1450.1821.1020.2250.9830.344Zion NP20010.963 0.819 0.144 0.785 0.178 0.701 0.26220020.957 0.821 0.136 0.788 0.169 0.705 0.25220030.223 0.193 0.030 0.192 0.031 0.192 0.03130Table H.3 – Predicted Visibility Impacts for Pacificorp – Huntington Unit 1.Class I AreaYearBaselineLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCR98th PercentileImpact (∆dv)98th PercentileImpact (∆dv)VisibilityImprovement (∆dv)98th PercentileImpact (∆dv)VisibilityImprovement (∆dv)98th PercentileImpact (∆dv)VisibilityImprovement (∆dv)Arches NP20013.887 3.203 0.684 2.980 0.907 2.399 1.48820022.734 2.319 0.415 2.205 0.529 1.911 0.82320033.579 2.962 0.617 2.767 0.812 2.275 1.304Black Canyon NP20010.6190.4950.1240.4560.1630.3550.26420020.8480.6940.1540.6450.2030.5330.31520030.7730.6170.1560.5680.2050.4450.328Bryce Canyon NP20010.799 0.651 0.148 0.603 0.196 0.473 0.32620021.221 0.999 0.222 0.929 0.292 0.748 0.47320030.513 0.411 0.102 0.379 0.134 0.300 0.213Canyonlands NP20013.7813.2720.5093.0920.6892.6061.17520025.1304.2790.8513.9971.1333.2491.88120034.2393.6460.5933.4210.8182.8371.402Capitol Reef NP20012.561 2.092 0.469 1.941 0.620 1.552 1.00920023.389 2.926 0.463 2.761 0.628 2.281 1.10820032.680 2.187 0.493 2.029 0.651 1.627 1.053Flat Tops Wilderness20010.6920.5770.1150.5400.1520.4510.24120020.9350.7540.1810.6960.2390.5520.38320030.9260.7480.1780.6920.2340.5460.380Grand Canyon NP20010.996 0.796 0.200 0.734 0.262 0.577 0.41920021.107 0.920 0.187 0.863 0.244 0.722 0.38520030.767 0.626 0.141 0.583 0.184 0.472 0.295Mesa Verde NP20010.8290.6710.1580.6210.2080.4920.33720021.1100.8980.2120.8320.2780.6630.44720031.1150.9000.2150.8310.2840.6530.462Zion NP20010.614 0.494 0.120 0.457 0.157 0.361 0.25320020.820 0.670 0.150 0.622 0.198 0.500 0.32020030.241 0.197 0.044 0.183 0.058 0.149 0.09231Table H.4 – Predicted Visibility Impacts for Pacificorp – Huntington Unit 2.Class I AreaYearBaselineLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCR98th PercentileImpact (∆dv)98th PercentileImpact (∆dv)VisibilityImprovement (∆dv)98th PercentileImpact (∆dv)VisibilityImprovement (∆dv)98th PercentileImpact (∆dv)VisibilityImprovement (∆dv)Arches NP20013.887 3.262 0.625 3.071 0.816 2.571 1.31620022.734 2.349 0.385 2.253 0.481 2.001 0.73320033.579 3.021 0.558 2.856 0.723 2.435 1.144Black Canyon NP20010.6190.5050.1140.4710.1480.3820.23720020.8480.7070.1410.6650.1830.5590.28920030.7730.6300.1430.5890.1840.4810.292Bryce Canyon NP20010.799 0.663 0.136 0.622 0.177 0.511 0.28820021.221 1.016 0.205 0.955 0.266 0.797 0.42420030.513 0.420 0.093 0.393 0.120 0.324 0.189Canyonlands NP20013.7813.3170.4643.1670.6142.7561.02520025.1304.3540.7764.1141.0163.4731.65720034.2393.7090.5303.5190.7203.0211.218Capitol Reef NP20012.561 2.132 0.429 2.003 0.558 1.666 0.89520023.389 2.969 0.420 2.832 0.557 2.434 0.95520032.680 2.231 0.449 2.096 0.584 1.751 0.929Flat Tops Wilderness20010.6920.5870.1050.5560.1360.4780.21420020.9350.7670.1680.7180.2170.5920.34320030.9260.7620.1640.7130.2130.5860.340Grand Canyon NP20010.996 0.813 0.183 0.760 0.236 0.625 0.37120021.107 0.936 0.171 0.888 0.219 0.768 0.33920030.767 0.638 0.129 0.600 0.167 0.504 0.263Mesa Verde NP20010.8290.6870.1420.6440.1850.5340.29520021.1100.9140.1960.8570.2530.7080.40220031.1150.9160.1990.8570.2580.7010.414Zion NP20010.614 0.504 0.110 0.472 0.142 0.388 0.22620020.820 0.684 0.136 0.644 0.176 0.539 0.28120030.241 0.201 0.040 0.188 0.053 0.158 0.08332Table H.5 – Predicted Maximum Visibility Improvements for Pacificorp – Hunter Unit 1.Class I AreaLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCRLNB/SOFA/SCR vs.LNB/SOFALNB/SOFA/SCR vs.LNB/SOFA/SNCRVisibilityImprovement (∆dv)Visibility Improvement (∆dv)Visibility Improvement (∆dv)Visibility Improvement (∆dv)Visibility Improvement (∆dv)Arches NP0.737 0.906 1.342 0.605 0.436Black Canyon NP0.198 0.241 0.345 0.147 0.104Bryce Canyon NP0.306 0.372 0.534 0.228 0.162Canyonlands NP0.846 1.041 1.545 0.699 0.504Capitol Reef NP0.639 0.750 1.113 0.474 0.363Flat Tops Wilderness0.231 0.280 0.404 0.173 0.124Grand Canyon NP0.349 0.426 0.618 0.269 0.192Mesa Verde NP0.235 0.286 0.426 0.191 0.140Zion NP0.184 0.224 0.323 0.139 0.099Table H.6 – Predicted Maximum Visibility Improvements for Pacificorp – Hunter Unit 2.Class I AreaLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCRLNB/SOFA/SCR vs.LNB/SOFALNB/SOFA/SCR vs.LNB/SOFA/SNCRVisibilityImprovement (∆dv)Visibility Improvement (∆dv)Visibility Improvement (∆dv)Visibility Improvement (∆dv)Visibility Improvement (∆dv)Arches NP0.569 0.711 1.080 0.511 0.369Black Canyon NP0.153 0.189 0.279 0.126 0.090Bryce Canyon NP0.234 0.291 0.429 0.195 0.138Canyonlands NP0.658 0.822 1.250 0.592 0.428Capitol Reef NP0.491 0.623 0.879 0.388 0.256Flat Tops Wilderness0.180 0.223 0.328 0.148 0.105Grand Canyon NP0.275 0.340 0.506 0.231 0.166Mesa Verde NP0.182 0.225 0.344 0.162 0.119Zion NP0.144 0.178 0.262 0.118 0.08433Table H.7 – Predicted Maximum Visibility Improvements for Pacificorp – Huntington Unit 1.Class I AreaLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCRLNB/SOFA/SCR vs.LNB/SOFALNB/SOFA/SCR vs.LNB/SOFA/SNCRVisibilityImprovement (∆dv)Visibility Improvement (∆dv)Visibility Improvement (∆dv)Visibility Improvement (∆dv)Visibility Improvement (∆dv)Arches NP0.684 0.907 1.488 0.804 0.581Black Canyon NP0.156 0.205 0.328 0.172 0.123Bryce Canyon NP0.222 0.292 0.473 0.251 0.181Canyonlands NP0.851 1.133 1.881 1.030 0.748Capitol Reef NP0.493 0.651 1.108 0.615 0.457Flat Tops Wilderness0.181 0.239 0.383 0.202 0.144Grand Canyon NP0.200 0.262 0.419 0.219 0.157Mesa Verde NP0.215 0.284 0.462 0.247 0.178Zion NP0.150 0.198 0.320 0.170 0.122Table H.8 – Predicted Maximum Visibility Improvements for Pacificorp – Huntington Unit 2.Class I AreaLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCRLNB/SOFA/SCR vs.LNB/SOFALNB/SOFA/SCR vs.LNB/SOFA/SNCRVisibilityImprovement (∆dv)Visibility Improvement (∆dv)Visibility Improvement (∆dv)Visibility Improvement (∆dv)Visibility Improvement (∆dv)Arches NP0.625 0.816 1.316 0.691 0.500Black Canyon NP0.143 0.184 0.292 0.149 0.108Bryce Canyon NP0.205 0.266 0.424 0.219 0.158Canyonlands NP0.776 1.016 1.657 0.881 0.641Capitol Reef NP0.449 0.584 0.955 0.506 0.371Flat Tops Wilderness0.168 0.217 0.343 0.175 0.126Grand Canyon NP0.183 0.236 0.371 0.188 0.135Mesa Verde NP0.199 0.258 0.414 0.215 0.156Zion NP0.136 0.176 0.281 0.145 0.10534Table H.9 – Predicted Number of Days Greater than 0.5 and 1.0Δdvfor Pacificorp – Hunter Unit 1.Class I AreaYearBaselineLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCRNumber of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv => 1.0Arches NP200184 48 74 42 72 42 68 372002117 67 102 55 105 55 94 48200392 55 84 44 82 42 73 37Black Canyon NP200117413311382200230112452442142003217185185123Bryce Canyon NP200116 6 13 6 13 5 8 4200221 13 19 10 18 10 16 920035 3 5 3 5 3 4 3Canyonlands NP200110370936590598757200214093126851238011973200311677111681096310558Capitol Reef NP200140 30 37 29 36 29 35 26200270 51 63 48 63 47 57 39200365 37 60 33 57 33 53 29Flat Tops Wilderness20011651341241122002261320818816520033513308296233Grand Canyon NP200116 10 14 7 14 7 12 6200222 15 20 11 19 10 16 9200311 7 9 7 9 6 9 3Mesa Verde NP20012391871871562002321225525421120032711238208196Zion NP200111 7 8 4 8 3 8 3200215 5 12 5 12 5 12 420033 2 3 0 3 0 2 035Table H.10 – Predicted Number of Days Greater than0.5 and 1.0Δdvfor Pacificorp – Hunter Unit 2.Class I AreaYearBaselineLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCRNumber of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Arches NP200184 48 80 44 74 42 69 412002117 67 110 60 109 58 100 49200392 55 86 47 85 45 76 41Black Canyon NP2001174134133102200230112672452442003217185185155Bryce Canyon NP200116 6 14 6 13 6 10 4200221 13 20 12 19 10 16 920035 3 5 3 5 3 4 3Canyonlands NP200110370966593658859200214093128861268512178200311677112701126810861Capitol Reef NP200140 30 38 29 37 29 35 28200270 51 64 49 63 48 62 46200365 37 61 35 61 34 55 31Flat Tops Wilderness20011651341341222002261320820816720033513318308295Grand Canyon NP200116 10 16 7 15 7 13 7200222 15 21 11 21 11 18 9200311 7 9 7 9 7 9 6Mesa Verde NP20012392081871672002321228525523120032711249238206Zion NP200111 7 9 5 8 4 8 3200215 5 12 5 12 5 12 520033 2 3 1 3 0 2 036Table H.11 – Predicted Number of Days Greater than0.5 and 1.0Δdvfor Pacificorp – Huntington Unit 1.Class I AreaYearBaselineLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCRNumber of Days∆dv => 0.5Number of Days∆dv => 1.0Number of Days∆dv => 0.5Number of Days∆dv => 1.0Number of Days∆dv => 0.5Number of Days∆dv => 1.0Number of Days∆dv => 0.5Number of Days∆dv => 1.0Arches NP200172 42 69 35 66 35 54 26200294 57 85 47 81 45 68 32200371 47 67 39 63 37 58 28Black Canyon NP2001115727261200220515314311120031461129261Bryce Canyon NP200113 5 8 4 8 2 5 1200215 11 14 7 13 7 11 420038 3 4 2 4 0 3 0Canyonlands NP200186537148694461352002109671046110256874720038255744473436235Capitol Reef NP200131 25 30 20 30 20 26 17200254 40 51 32 50 30 44 23200346 26 36 22 36 19 29 15Flat Tops Wilderness200114592826020022061141141022003306213182111Grand Canyon NP200110 7 10 5 10 5 8 5200219 9 17 7 16 6 13 3200311 3 8 1 8 1 6 1Mesa Verde NP2001155105947220022591931821212003238175144111Zion NP20018 6 7 3 7 3 6 2200210 5 8 5 8 3 8 220033 0 1 0 1 0 0 037Table H.12 – Predicted Number of Days Greater than0.5 and 1.0Δdvfor Pacificorp – Huntington Unit 2.Class I AreaYearBaselineLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCRNumber of Days∆dv => 0.5Number of Days∆dv => 1.0Number of Days∆dv => 0.5Number of Days∆dv => 1.0Number of Days∆dv => 0.5Number of Days∆dv => 1.0Number of Days∆dv => 0.5Number of Days∆dv => 1.0Arches NP200172 42 70 35 67 35 58 28200294 57 86 47 82 46 70 38200371 47 67 40 65 37 58 32Black Canyon NP20011159272612002205154153132200314611210271Bryce Canyon NP200113 5 8 5 8 4 8 1200215 11 14 8 14 7 12 520038 3 4 2 4 2 3 0Canyonlands NP200186537348694763372002109671066110258925020038255754473446539Capitol Reef NP200131 25 30 20 30 20 26 19200254 40 52 32 50 30 46 24200346 26 37 23 36 20 32 16Flat Tops Wilderness2001145112926020022061141141022003306223192152Grand Canyon NP200110 7 10 5 10 5 8 5200219 9 17 7 17 7 14 3200311 3 9 1 8 1 8 1Mesa Verde NP20011551151058420022591931831212003238185155111Zion NP20018 6 8 3 7 3 6 2200210 5 8 5 8 3 8 220033 0 1 0 1 0 1 038Table H.13 – Predicted Total Number of Days Greaterthan 0.5 and 1.0Δdvbetween 2001 and 2003 for Pacificorp – Hunter Unit1.Class I AreaBaselineLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCRNumber of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Arches NP293 170 260 141 259 139 235 122Black Canyon NP68 22 55 13 53 12 41 9Bryce Canyon NP42 22 37 19 36 18 28 16Canyonlands NP359 240 330 218 322 202 311 188Capitol Reef NP175 118 160 110 156 109 145 94Flat Tops Wilderness77 31 63 20 59 18 50 10Grand Canyon NP49 32 43 25 42 23 37 18Mesa Verde NP82 32 66 20 63 19 55 13Zion NP29 14 23 9 23 8 22 7Table H.14 – Predicted Total Number of Days Greaterthan 0.5 and 1.0Δdvbetween 2001 and 2003 for Pacificorp – Hunter Unit2.Class I AreaBaselineLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCRNumber of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Arches NP293 170 276 151 268 145 245 131Black Canyon NP68 22 57 16 55 13 49 11Bryce Canyon NP42 22 39 21 37 19 30 16Canyonlands NP359 240 336 221 331 218 317 198Capitol Reef NP175 118 163 113 161 111 152 105Flat Tops Wilderness77 31 64 20 63 20 57 14Grand Canyon NP49 32 46 25 45 25 40 22Mesa Verde NP82 32 72 22 66 20 59 14Zion NP29 14 24 11 23 9 22 839Table H.15 – Predicted Total Number of Days Greaterthan 0.5 and 1.0Δdvbetween 2001 and 2003 for Pacificorp – HuntingtonUnit 1.Class I AreaBaselineLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCRNumber of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Arches NP237 146 221 121 210 117 180 86Black Canyon NP45 16 33 7 30 7 23 3Bryce Canyon NP36 19 26 13 25 9 19 5Canyonlands NP277 175 249 153 244 143 210 117Capitol Reef NP131 91 117 74 116 69 99 55Flat Tops Wilderness64 17 41 9 37 8 27 3Grand Canyon NP40 19 35 13 34 12 27 9Mesa Verde NP63 22 46 13 41 10 30 4Zion NP21 11 16 8 16 6 14 4Table H.16 – Predicted Total Number of Days Greaterthan 0.5 and 1.0Δdvbetween 2001 and 2003 for Pacificorp – HuntingtonUnit 2.Class I AreaBaselineLNB/SOFALNB/SOFA/SNCRLNB/SOFA/SCRNumber of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Number of Days∆dv > 0.5Number of Days∆dv > 1.0Arches NP237 146 223 122 214 118 186 98Black Canyon NP45 16 35 8 32 7 26 4Bryce Canyon NP36 19 26 15 26 13 23 6Canyonlands NP277 175 254 153 244 149 220 126Capitol Reef NP131 91 119 75 116 70 104 59Flat Tops Wilderness64 17 44 9 39 8 31 4Grand Canyon NP40 19 36 13 35 13 30 9Mesa Verde NP63 22 48 13 43 13 31 6Zion NP21 11 17 8 16 6 15 4