Air Quality Modeling Protocol: Utah Regional Haze Federal 

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 MODELING...... 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 the Regional Haze Regulations and 

Guidelines and published the Guidelines for Best Available Retrofit Technology (BART) 

Determinations.1 Along with other requirements, the Guidelines address the methodology for 

determining which sources must apply BART and the evaluation of control options. In particular, 

the Guidelines state that the CALPUFF modeling system (or another appropriate dispersion 

model approved by EPA) should be used to predict the visibility improvement expected at a 

Class I area from potential BART control technologies 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 used 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. However, this protocol does not explain how 

the visibility results are factored into the BART determination process. Information related to the 

BART determination process appears in the Federal Register notice and elsewhere in the Docket. 

All EPA Region 8 modeling files used for this effort 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 determined 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. While the Utah modeling assessed the combined 

impacts of all of the BART and non-BART sources included in the BART Alternative – Carbon, 

Hunter, and Huntington, the EPA Region 8 modeling assesses the impacts of the individual 

BART sources. In addition, the EPA Region 8 modeling 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 and SOFA with Selective Non-Catalytic 

Reduction (SCR). Beyond assessing impacts from individual BART sources and evaluating all 

technologically feasible control options, the EPA Region 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 Region 8 are 

provided in the following sections. 

3.0 MODELING APPROACH 

This section describes the components and information required for the CALPUFF modeling. 

Each source that causes or contributes to visibility impairment in one or more Class I area must 

conduct a BART analysis to determine the best available retrofit technology applicable to that 

source and quantify the visibility improvement at the Class I areas associated with BART 

controls. This section covers the following elements: emission sources; Class I area 

identification; pollutants considered; natural background 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 includes Hunter Unit 3 even though this unit is 

not part of the Hunter BART source. This unit was modeled in order to account for the unit’s 

emission contributions when modeling the other units 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 were included in the State of Utah’s BART 

Alternatives modeling. These Class I areas are largely within a 300 mile radius of the BART 

sources. The federal Class I areas that were modeled 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 Modeling

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 National Park, 

Capitol Reef National Park, Flat Tops Wilderness Area, Grand 

Canyon National Park, Mesa Verde National Park, Zion 

National Park 

 

 

2 Air Quality Modeling Protocol: Utah Regional Haze State Implementation Plan, Utah Division of Air Quality, 

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 conducted for sulfur dioxide (SO2), NOx

and direct particulate matter (PM) emissions, including particles with a diameter of 10 

micrometers or less (PM10) and particles with a diameter smaller than 2.5 micrometers (PM2.5). 

The pollutants modeled for this analysis included SO2, Sulfate (SO4), NOx, Elemental Carbon 

(EC), Secondary Organic Aerosol (SOA), PM2.5, and PM10. However, the modeling will only 

evaluate the NOx 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 conditions 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 were used. This approach is consistent with the 

previous BART modeling conducted by the state and Pacificorp for these sources. The specific 

natural background values used in this protocol were drawn from the FLAG 2010 report. Class I 

area specific natural background assumptions are presented in Appendix A. 
4 

3.5 Visibility Calculation 

The methodology for performing visibility calculations with the CALPUFF modeling system is 

described in several documents, including: 

• Interagency Workgroup on Air Quality Modeling (IWAQM) Phase 2 Summary Report 

and Recommendations for Modeling Long Range Transport Impacts,3 

• Federal Land Manager’s Air Quality Related Values Workgroup (FLAG): Phase I 

Report,4

 and 

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

 

The CALPUFF modeling techniques presented in this protocol provide ground-level 

concentrations of visibility impairing pollutants. The concentration estimates from CALPUFF 

were used with the FLAG 2010 referenced IMPROVE equation6 to calculate the extinction 

coefficient (bext), as shown below. 

bext = 2.2 × fS(RH) × [Small Sulfate] + 4.8 × fL(RH) × [Large Sulfate] 

• 2.4 × fS(RH) × [Small Nitrate] + 5.1 × fL(RH) × [Large Nitrate] 

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

• 10 × [Elemental Carbon] 

• 1 × [Fine Soil] 

• 0.6 × [Coarse Mass] 

• 1.7 × fSS(RH) × [Sea Salt] 

• Rayleigh Scattering (Site Specific) 

• 0.33 × [NO2 (ppb)] {or as: 0.1755 × [NO2 (μg/m3

)]} 

Where: 

[ ] indicates concentrations in μg/m3

fS(RH) = Relative humidity adjustment factor for small sulfate and nitrate 

fL(RH) = Relative humidity adjustment factor for large sulfate and nitrate 

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

For Total Sulfate < 20 μg/m3: 

[Large Sulfate] = ([Total Sulfate] / 20 μg/m3

) × [Total Sulfate] 

For Total Sulfate ≥ 20 μg/m3: 

[Large Sulfate] = [Total Sulfate] 

And: 

[Small Sulfate] = [Total Sulfate] – [Large Sulfate]

To calculate large and small nitrate and organic mass, 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 visibility for the BART 

 

3

 Interagency Workgroup on Air Quality Modeling (IWAQM) Phase 2 Summary Report and Recommendations for 

Modeling Long Range Transport Impacts, Office of Air Quality Standards, EPA-454/R-98-019, December 1998.

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

5 Scire J.S., D.G. Strimaitis, R.J. Yamartino. “A User's Guide for the CALPUFF Dispersion Model.” Earth Tech, 

Concord, MA, January 2000. 

6 Federal Land Managers’ Air Quality Related Values Workgroup (FLAG) 2008. Phase I Report—Revised (2010). 
5 

analysis is the 98th percentile deciview change relative to the 20 percent best days natural 

background conditions7,8 The delta-deciview (∆dv) value is calculated from the source’s 

contribution to extinction, bext (source), and background extinction, bext(bkg), as follows: 

∆dv = 10 ln ( bext(bkg) + bext (source) ) / bext(bkg) )9

The assumptions or input values used in the equations above are included in Appendix A. 

4.0 EMISSIONS DATA FOR MODELING 

CALPUFF model inputs require source parameters, including pollutant emission rates and stack 

data (location, height, diameter, exit gas temperature, and exit gas velocity). In accordance with 

BART Guidelines, the baseline (pre-control) emission 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 percentage 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 Appendix B. 

4.1 Baseline Model Scenario 

EPA modeled one baseline scenario (referenced as Baseline) for each source and unit listed in 

Table 1 and Appendix B. The Baseline scenario reflects the baseline emission rates. For the 

Baseline model scenario, the emission rates and stack 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 Program 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 highest emitting day occurring during that same 

period. The daily values from this period were sorted 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 by 24 hours/day and multiplied by 2000 

lb/ton. 

One non-BART source, specifically Hunter Unit 3, was included in this modeling. The Baseline 

for Hunter, Unit 3 was developed using a combination of EPA’s AMPD and information 

contained within Utah DAQ’s emission inventory database. 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 emissions assumptions for each of the sources that 

were used in the modeling. 

 

7 70 FR 39119, 39121, 39170. 

8 Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule, Office of Air Quality 

Planning and Standards, Emissions, Monitoring and Analysis Division, Air Quality Trends Analysis Group, EPA454/B-03-005, September 2003. 

9 Federal Land Managers’ Air Quality Related Values Workgroup (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, LNB and SOFA SNCR, and LNB and 

SOFA with SCR conditions to isolate the impact of different NOx control technologies. Similar 

to the baseline modeling, the emission rates and stack data for the control scenarios were based 

on the information developed by UDAQ for the time period of 2001 to 2003. Briefly, the postcontrol emissions for NOx were determined by multiplying the baseline emissions by the percent 

reduction associated with the BART control.11Note that the only differences in the control 

scenarios are (1) the emission rates for NOx, and (2) the total sulfate emission rates in the SCR 

scenario. For the SCR scenario total sulfate rates were increased to account for the additional 

production that results from the SCR controls. As seen in the tables presented in Appendix B, the 

NOx emission rates were varied across the different control scenarios, while the other input 

parameters were held constant. 

Appendix B presents the emissions assumptions for each 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 impact of different NOx control technologies for 

individual BART sources under a five factor analysis. The model results for each unit and 

scenario were then combined using POSTUTIL to account 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 suite of programs and followed the 

procedures and recommendations outlined in applicable documents. For the most part, the 

regulatory default options were utilized for the CALPUFF modeling. Details are provided below 

for the non-default options selected for this modeling. The requirements and recommendations 

outlined in the documents listed below were also followed:

• EPA’s Guidance for Estimating Natural Visibility Conditions under the Regional Haze 

Rule, 12 

• Appendix W of 40 CFR Part 51, Guideline on Air Quality 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 Conditions Under the Regional Haze Rule, Office of Air Quality 

Planning and Standards, Emissions, Monitoring and Analysis Division, Air Quality Trends Analysis Group, EPA454/B-03-005, September 2003. 

13 Appendix W, 40 CFR Part 51: Revision to the Guideline on Air Quality Models: Adoption of a Preferred General 

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 (IWAQM) Phase 2 Summary Report and Recommendations for 

Modeling Long Range Transport Impacts, Office of Air Quality Standards, EPA-454/R-98-019, December 1998.
7 

• Federal Land Managers’ Air Quality Related Values Workgroup – 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 modeling 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 hourly wind and temperature fields in a 

three-dimensional, gridded modeling domain. Meteorological inputs to CALMET can include 

surface and upper-air observations from multiple meteorological monitoring stations. The 

CALMET model can also utilize gridded analysis fields from various mesoscale models, such as 

the Fifth-Generation Penn State/NCAR Mesoscale Model (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 CALMET, including surface, upper-air, and 

precipitation stations. The model domain is centered in east-central Utah, and extends to the west 

covering five Class I areas in Utah, one Class I area 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 CALMET settings that were selected, and 

Appendix C presents the CALMET Control File inputs.

 

 

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

16 Scire J.S., D.G. Strimaitis, R.J. Yamartino. “A User's Guide for the CALPUFF Dispersion Model.” Earth Tech, 

Concord, MA, January 2000. 

17 Air Quality Modeling Protocol: Utah Regional Haze State Implementation Plan, Utah Division of Air Quality, 

February 13, 2015.

18 While the CALMET configuration did not utilize all of the regulatory default options, EPA Region 8 did not 

update the CALMET modeling platform due to the level of resources needed to regenerate the meteorological data, 

and because EPA Region 8 does not have evidence that the use of the non-default options incorporated into the 

UDAQ CALMET modeling would substantially affect the model results. 

19 The CALMET input/output data are in the docket available upon request. 
8 

Figure 2. Modeling Domain and Class I Areas 

Briefly, UDAQ used the cell face heights (ZFACE) established by the WRAP in the August 15, 

2006 WRAP BART modeling protocol20 that was widely used for western BART analyses. The 

cell face heights used in CALMET allow for a more detailed 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 expected to be sensitive to cell face heights. 

UDAQ also used TERRAD, R1, and R2 settings established by PacifiCorp in their 2012 

modeling protocol that included CALMET settings previously approved for use under the PSD 

program.21 The TERRAD, R1/R2 values had been determined to be appropriate after reviewing 

the distance from the surface stations to the nearest terrain features (TERRAD) and each other 

(R1/R2). After CALMET was run, PacifiCorp determined that the windfields were consistent 

 

20 CALMET/CALPUFF Protocol for BART Exemption Screening Analysis for Class I Areas in the Western United 

States, Western Regional Air Partnership Air Quality Modeling Forum, August 15, 2006. 

21 Air Quality Modeling Protocol: Utah Regional Haze State Implementation Plan, Utah Division of Air Quality, 

February 13, 2015.

Huntington Plant

Hunter 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 CALMET and the prognostic MM5 data set or 

the observations. Therefore, these values were retained in the Utah BART Alternative modeling. 

The surface stations in the modeled area are very sparse 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 transport 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 needed 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 (Orange 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 Data) 

RMAX 1 Maximum Radius of Influence (surface layer, km) 10 

RMAX 2 Maximum Radius of Influence (layers aloft, km) 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 years of meteorological data to calculate 

pollutant concentrations at receptors in multiple Class I areas for all units and control scenarios. 

In general, the application of CALPUFF uses the regulatory default options and follows the 

procedures and recommendations outlined in applicable documents. Details of the parameter 

settings in CALPUFF are provided in Appendix D. However, the major features are outlined 

below. 

• Building downwash effects were included. 

• Puff splitting was not used, following the recommendations outlined in the IWAQM 

Phase 2 report.22 

• Hourly ozone files were used to define background ozone concentration.23 Data from 

Canyonlands were used for the entire domain. 

• The background ozone concentration shown in Appendix 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 and sources. 

• MESOPUFF II chemical transformation rates were used. 

• The species emitted were the seven identified in CALPUFF: SO2, SO4, NOx, EC, SOA, 

PM2.5, and PM10. 

• The species modeled were the nine identified in CALPUFF: SO2, SO4, NOx, EC, SOA, 

HNO3, NO3, PM2.5, and PM10. 

• 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 for each model scenario or control 

scenario and meteorological year. 

 

 

22 Interagency Workgroup on Air Quality Modeling (IWAQM) Phase 2 Summary Report and Recommendations for 

Modeling Long Range Transport Impacts, Office of Air Quality Standards, EPA-454/R-98-019, December 1998.

23 Data were provided by the State of Utah. This data is in the docket and can be made available upon request. 
11 

5.2.1 Background Ozone Concentrations 

The background ozone concentrations are based on the information developed by UDAQ for the 

time period of 2001 to 2003. Briefly, data from Canyonlands 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 missing. UDAQ did not use the default 

value of 80 ppb ozone because this level is not often reached in the area. 

5.2.2 Background Ammonia Concentrations 

The CALPUFF model requires input data to specify representative monthly background 

ammonia concentrations for use in the transformation of gaseous nitric acid to particulate 

ammonium nitrate and for the formation of particulate ammonium sulfate. 

EPA Region 8 relied on the background ammonia concentrations 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 provides the highest deciview impacts on each 

day from all receptors within each Class I area modeled and the number of days with impacts 

greater than 0.5 and 1.0 ∆dv. Details of the parameter settings in CALPOST and POSTUTIL are 

provided in Appendix F and G, respectively, with some of the major features summarized below: 

• For the visibility calculation, Method 8, Mode 5 (MVISBK=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 FLAG 2010. 

• Particulate species for the visibility analysis included SO4, NO3, EC, SOA, PM2.5, and 

PM10. 

• Natural background extinction calculations used the 20 percent best natural days for each 

Class I area considered for this modeling. The values assumed for the 20 percent best 

natural days are included in Appendix A. 

• Tables providing the monthly relative humidity adjustment factors [f(RH)] and 20 

percent best days coefficients are provided in Appendix A, and are based on data from 

FLAG 2010. 

 

24 National Park Service website with Class I area receptor information. 

http://www2.nature.nps.gov/air/Maps/Receptors/index.cfm. This data is in the docket and can be made available 

upon request. 
12 

• POSTUTIL was used to combine units from sources with multiple units and to perform 

HNO3/NO3 repartitioning. However, each unit was processed separately by POSTUTIL 

for each source, scenario, and meteorological year. 

• Each unit was processed separately by CALPOST for each source, scenario, and 

meteorological year. 

5.3.1 POSTUTIL 

The ammonia-limiting correction in the POSTUTIL postprocessor was used in all the model 

simulations to repartition the CALPUFF-predicted nitrate concentrations. This correction in 

POSTUTIL repartitions the particulate nitrate and gaseous 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 humidity data. The CALPUFF model 

simulates individual units (or sources) that may have 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 from the combined units compete for the 

available ammonia and there is a possibility that different air parcels can overlap at a Class I 

area. The ammonia-limiting correction in POSTUTIL is designed to repartition the available 

ammonia to react with emissions from all of the units 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 POSTUTIL, the MNITRATE=1 setting was used, 

the CALPUFF data were not scaled to alter the emission rate of all units modeled, and the 

background ammonia concentrations were assumed to be a constant 1.0 ppb. To correct for 

ammonia-limiting conditions in the baseline scenarios, 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 Hunter Plant were combined in POSTUTIL, and 

used the MNITRATE=1 setting and the constant 1.0 ppb background ammonia concentration. 

For the control scenarios, the CALPUFF data file from the unit of interest was combined with 

the baseline CALPUFF data files of the remaining units by POSTUTIL, along with the 

MNITRATE=1 setting and the associated background ammonia 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. This approach was used to correct for ammonialimiting conditions and isolate the degree of visibility 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 Implementation Plan (FIP) Support, prepared for EPA 

Region 8 by Alpine Geophysics, LLC, November 21, 2011. 
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 Assumptions 

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 Assumptions 

Hunter – Unit 3: Baseline Source Assumptions 

LNB/OFA and SNCR 

Huntington – Unit 1 

Huntington – Unit 1: LNB/OFA and SNCR Source Assumptions 

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 Assumptions 

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 Assumptions 

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 Assumptions 

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, nitrate, nitrogen dioxide, course particulate 

matter (PM10), and fine particulate matter (PM2.5) 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 particular, 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 impairment 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 (latest IMPROVE equation); and 

• M8_MODE = 5 to use species specific relative humidity factors. 

The species concentrations of the 20 percent best days 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 defined 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-deciview [∆dv]) for the visibility modeling is 

based on the increase in the haze index from a source relative to natural background, defined as 

the 20 percent best natural visibility days for each Class I area. EPA has recognized that the 

CALPUFF model can be conservative in estimating visibility impairment, and therefore, 

consistent with the BART Guidelines, the change in visibility impairment will be based on the 

98th percentile model results instead of the maximum modeled 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 98th ∆dv percentile value (or 8th highest value). 

Visibility impacts were tabulated using the output from CALPOST. As noted above, CALPOST 

provides the ranked deciview impacts on each day from 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 98th percentile value was reported to three decimal places because of the level of 

precision reported by CALPOST. This value was based on the 8th 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 98th percentile deciview change relative to the 20 

percent best days natural background conditions. This 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 model year. (see Appendix H, Tables H-1 

to H-4)

• The maximum change in visibility based on the 98th percentile deciview change relative 

to the 20 percent best days natural background conditions for each source unit, model 

scenario, and Class I area. This is based on the maximum improvement among the 

difference between the baseline and control scenario 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 and 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 are reported in Appendix H. This includes the 

impacts for each BART unit at all modeled Class I areas and meteorological years.

 

26 40 CFR 51 Appendix Y.IV.D. and 70 FR 39121. 
15 

APPENDIX A – BACKGROUND CONDITIONS ASSUMED FOR MODELING 

Table A-1. 20 Percent Best Natural Background Conditions by Aerosol Component and 

Class I Area [μg/m3] 

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 Managers’ Air Quality Related Values Workgroup 

(FLAG) 2008. Phase I Report—Revised (2010).

Table A-2. Monthly fL(RH) – Large (NH4)2SO4 and NH4NO3 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 1.55 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 Managers’ Air Quality Related Values Workgroup 

(FLAG) 2008. Phase I Report—Revised (2010).

Table A-3. Monthly fS(RH) – Small (NH4)2SO4 and NH4NO3 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 1.76 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 Managers’ Air Quality Related Values Workgroup 

(FLAG) 2008. Phase I Report—Revised (2010).

Table A-4. Monthly fSS(RH) – Sea Salt 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 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 1.67 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 Managers’ 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 - Hunter Unit 1 

CALPUFF Inputs Baseline LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR

SO2 (lb/hr) 570 570 570 570 

Total Sulfate (SO4)(lb/hr) 0.11 0.11 0.11 1.64 

NOx (lb/hr) 2388 1202 944.772 298 

HNO3 0 0 0 0 

NO3 0 0 0 0 

EC 0.219 0.219 0.219 0.219 

SOA 4.75 4.75 4.75 4.75 

PM2.5 (lb/hr) 29.329 29.329 29.329 29.329 

PM10-2.5 

(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 - Hunter Unit 2 

CALPUFF Inputs Baseline LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR

SO2 (lb/hr) 570 570 570 570 

Total Sulfate (SO4)(lb/hr) 0.10 0.10 0.10 1.53 

NOx (lb/hr) 1975 1044 822.672 259 

HNO3 0 0 0 0 

NO3 0 0 0 0 

EC 0.229 0.229 0.229 0.229 

SOA 4.96 4.96 4.96 4.96 

PM2.5 (lb/hr) 30.61 30.61 30.61 30.61 

PM10-2.5 

(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 - Hunter Unit 3 

CALPUFF Inputs Baseline LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR

SO2 (lb/hr) 269.8 269.8 269.8 269.8 

Total Sulfate (SO4)(lb/hr) 0.37 0.37 0.37 0.37 
18 

NOx (lb/hr) 1240.3 1240.3 1240.3 1240.3 

HNO3 0 0 0 0 

NO3 0 0 0 0 

EC 0.275 0.275 0.275 0.275 

SOA 5.945 5.945 5.945 5.945 

PM2.5 (lb/hr) 19.478 19.478 19.478 19.478 

PM10-2.5 

(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 1736.61 

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 - Huntington Unit 1 

CALPUFF Inputs Baseline LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR 

SO2 (lb/hr) 595 595 595 595 

Total Sulfate 

(SO4)(lb/hr) 0.10 0.10 0.10 1.55 

NOx (lb/hr) 2260 1338 1047.654 301 

HNO3 0 0 0 0 

NO3 0 0 0 0 

EC 0.229 0.229 0.229 0.229 

SOA 4.96 4.96 4.96 4.96 

PM2.5 (lb/hr) 30.610 30.610 30.610 30.610 

PM10-2.5 

(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 – Huntington Unit 2 

CALPUFF Inputs Baseline LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR 

SO2 (lb/hr) 595.5 595.5 595.5 595.5 

Total Sulfate 

(SO4)(lb/hr) 0.11 0.11 0.11 1.61 

NOx (lb/hr) 2014 1166 915.31 261 

HNO3 0 0 0 0 

NO3 0 0 0 0 

EC 0.220 0.220 0.220 0.220 

SOA 4.76 4.76 4.76 4.76 
19 

PM2.5 (lb/hr) 29.319 29.319 29.319 29.319 

PM10-2.5 

(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) 0,20,100,200,350,500,750,1000,2000,3000,4000,5000 

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 Data) 

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 SO4, NO3, PM2.5, PM10 

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 Modeling 

Figure E.3 – Bryce Canyon National Park Receptors for Modeling 

 
23 

Figure E.4 – Canyonlands National Park Receptors for Modeling 

Figure E.5 – Capitol Reef National Park Receptors for Modeling 

 
24 

Figure E.6 – Flat Tops Wilderness Area Receptors for Modeling 

Figure E.7 – Grand Canyon National Park Receptors for Modeling 

 
25 

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

Figure E.9 – Zion National Park Receptors for Modeling 
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 Coarse PM 0.6 

EESO4 Extinction efficiencies for Ammonium Sulfate 3.0 

EENO3 Extinction efficiencies for Ammonium Nitrate 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 Table 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 Carbon 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 Small Table A-3 

RHFLG Relative Humidity Adjustment Factors for Large Table A-2 

RHFSEA Relative Humidity Adjustment Factors for Sea Salt Table A-4 

BEXTRAY Extinction due to Rayleigh scattering Table 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 scaled 0 

MNITRATE Recompute the HNO3/NO3 partition for concentrations? 1 

NH3TYP What is the input source of Ammonia? 3 

BCKNH3 Background ammonia concentration (ppb) used for HNO3/NO3 partition 1.0 

 
28 

APPENDIX H – VISIBILITY IMPACT RESULTS 

Table H.1 – Predicted Visibility Impacts for Pacificorp – Hunter Unit 1. 

Class I Area Year 

Baseline LNB/SOFA LNB/SOFA/SNCR 

98th Percentile 

Impact (∆dv) 

98th Percentile 

Impact (∆dv) 

Visibility 

Improvement (∆dv) 

98th Percentile 

Impact (∆dv) 

Visibility 

Improvement (∆dv) 

98th 

Im

Arches NP 

2001 4.601 3.864 0.737 3.695 0.906 

2002 4.362 3.689 0.673 3.532 0.830 2003 3.575 2.967 0.608 2.835 0.740 

Black Canyon NP 

2001 0.855 0.696 0.159 0.662 0.193 2002 1.097 0.899 0.198 0.856 0.241 2003 0.954 0.781 0.173 0.743 0.211 

Bryce Canyon NP 

2001 0.869 0.699 0.170 0.662 0.207 

2002 1.833 1.527 0.306 1.461 0.372 2003 0.477 0.394 0.083 0.373 0.104 

Canyonlands NP 

2001 5.356 4.510 0.846 4.315 1.041 2002 5.259 4.490 0.769 4.311 0.948 2003 5.642 4.962 0.680 4.769 0.873 

Capitol Reef NP 

2001 3.645 3.092 0.553 3.001 0.644 

2002 4.606 3.967 0.639 3.856 0.750 2003 3.931 3.319 0.612 3.181 0.750 

Flat Tops Wilderness 

2001 0.907 0.732 0.175 0.694 0.213 2002 1.281 1.050 0.231 1.001 0.280 2003 1.241 1.015 0.226 0.967 0.274 

Grand Canyon NP 

2001 1.090 0.892 0.198 0.852 0.238 

2002 1.891 1.542 0.349 1.465 0.426 2003 0.854 0.693 0.161 0.660 0.194 

Mesa Verde NP 

2001 1.208 0.989 0.219 0.942 0.266 2002 1.080 0.888 0.192 0.847 0.233 2003 1.327 1.092 0.235 1.041 0.286 

Zion NP 

2001 0.963 0.779 0.184 0.739 0.224 

2002 0.957 0.783 0.174 0.745 0.212 2003 0.223 0.192 0.031 0.192 0.031 
29 

Table H.2 – Predicted Visibility Impacts for Pacificorp – Hunter Unit 2. 

Class I Area Year 

Baseline LNB/SOFA LNB/SOFA/SNCR 

98th Percentile 

Impact (∆dv) 

98th Percentile 

Impact (∆dv) 

Visibility 

Improvement (∆dv) 

98th Percentile 

Impact (∆dv) 

Visibility 

Improvement (∆dv) 

98t

Im

Arches NP 

2001 4.601 4.032 0.569 3.890 0.711 

2002 4.362 3.842 0.520 3.713 0.649 2003 3.575 3.106 0.469 2.995 0.580 

Black Canyon NP 

2001 0.855 0.735 0.120 0.707 0.148 2002 1.097 0.944 0.153 0.908 0.189 2003 0.954 0.819 0.135 0.788 0.166 

Bryce Canyon NP 

2001 0.869 0.736 0.133 0.705 0.164 

2002 1.833 1.599 0.234 1.542 0.291 2003 0.477 0.416 0.061 0.398 0.079 

Canyonlands NP 

2001 5.356 4.698 0.658 4.534 0.822 2002 5.259 4.663 0.596 4.513 0.746 2003 5.642 5.080 0.562 5.002 0.640 

Capitol Reef NP 

2001 3.645 3.179 0.466 3.107 0.538 

2002 4.606 4.115 0.491 3.983 0.623 2003 3.931 3.462 0.469 3.347 0.584 

Flat Tops Wilderness 

2001 0.907 0.773 0.134 0.741 0.166 2002 1.281 1.101 0.180 1.058 0.223 2003 1.241 1.065 0.176 1.024 0.217 

Grand Canyon NP 

2001 1.090 0.935 0.155 0.901 0.189 

2002 1.891 1.616 0.275 1.551 0.340 2003 0.854 0.724 0.130 0.695 0.159 

Mesa Verde NP 

2001 1.208 1.037 0.171 0.997 0.211 2002 1.080 0.932 0.148 0.896 0.184 2003 1.327 1.145 0.182 1.102 0.225 

Zion NP 

2001 0.963 0.819 0.144 0.785 0.178 

2002 0.957 0.821 0.136 0.788 0.169 2003 0.223 0.193 0.030 0.192 0.031 
30 

Table H.3 – Predicted Visibility Impacts for Pacificorp – Huntington Unit 1. 

Class I Area Year 

Baseline LNB/SOFA LNB/SOFA/SNCR 

98th Percentile 

Impact (∆dv) 

98th Percentile 

Impact (∆dv) 

Visibility 

Improvement (∆dv) 

98th Percentile 

Impact (∆dv) 

Visibility 

Improvement (∆dv) 

98t

Im

Arches NP 

2001 3.887 3.203 0.684 2.980 0.907 

2002 2.734 2.319 0.415 2.205 0.529 2003 3.579 2.962 0.617 2.767 0.812 

Black Canyon NP 

2001 0.619 0.495 0.124 0.456 0.163 2002 0.848 0.694 0.154 0.645 0.203 2003 0.773 0.617 0.156 0.568 0.205 

Bryce Canyon NP 

2001 0.799 0.651 0.148 0.603 0.196 

2002 1.221 0.999 0.222 0.929 0.292 2003 0.513 0.411 0.102 0.379 0.134 

Canyonlands NP 

2001 3.781 3.272 0.509 3.092 0.689 2002 5.130 4.279 0.851 3.997 1.133 2003 4.239 3.646 0.593 3.421 0.818 

Capitol Reef NP 

2001 2.561 2.092 0.469 1.941 0.620 

2002 3.389 2.926 0.463 2.761 0.628 2003 2.680 2.187 0.493 2.029 0.651 

Flat Tops Wilderness 

2001 0.692 0.577 0.115 0.540 0.152 2002 0.935 0.754 0.181 0.696 0.239 2003 0.926 0.748 0.178 0.692 0.234 

Grand Canyon NP

2001 0.996 0.796 0.200 0.734 0.262 

2002 1.107 0.920 0.187 0.863 0.244 2003 0.767 0.626 0.141 0.583 0.184 

Mesa Verde NP 

2001 0.829 0.671 0.158 0.621 0.208 2002 1.110 0.898 0.212 0.832 0.278 2003 1.115 0.900 0.215 0.831 0.284 

Zion NP 

2001 0.614 0.494 0.120 0.457 0.157 

2002 0.820 0.670 0.150 0.622 0.198 2003 0.241 0.197 0.044 0.183 0.058 
31 

Table H.4 – Predicted Visibility Impacts for Pacificorp – Huntington Unit 2. 

Class I Area Year 

Baseline LNB/SOFA LNB/SOFA/SNCR 

98th Percentile 

Impact (∆dv) 

98th Percentile 

Impact (∆dv) 

Visibility 

Improvement (∆dv) 

98th Percentile 

Impact (∆dv) 

Visibility 

Improvement (∆dv) 

98t

Im

Arches NP

2001 3.887 3.262 0.625 3.071 0.816 

2002 2.734 2.349 0.385 2.253 0.481 2003 3.579 3.021 0.558 2.856 0.723 

Black Canyon NP 

2001 0.619 0.505 0.114 0.471 0.148 2002 0.848 0.707 0.141 0.665 0.183 2003 0.773 0.630 0.143 0.589 0.184 

Bryce Canyon NP 

2001 0.799 0.663 0.136 0.622 0.177 

2002 1.221 1.016 0.205 0.955 0.266 2003 0.513 0.420 0.093 0.393 0.120 

Canyonlands NP 

2001 3.781 3.317 0.464 3.167 0.614 2002 5.130 4.354 0.776 4.114 1.016 2003 4.239 3.709 0.530 3.519 0.720 

Capitol Reef NP 

2001 2.561 2.132 0.429 2.003 0.558 

2002 3.389 2.969 0.420 2.832 0.557 2003 2.680 2.231 0.449 2.096 0.584 

Flat Tops Wilderness 

2001 0.692 0.587 0.105 0.556 0.136 2002 0.935 0.767 0.168 0.718 0.217 2003 0.926 0.762 0.164 0.713 0.213 

Grand Canyon NP 

2001 0.996 0.813 0.183 0.760 0.236 

2002 1.107 0.936 0.171 0.888 0.219 2003 0.767 0.638 0.129 0.600 0.167 

Mesa Verde NP 

2001 0.829 0.687 0.142 0.644 0.185 2002 1.110 0.914 0.196 0.857 0.253 2003 1.115 0.916 0.199 0.857 0.258 

Zion NP 

2001 0.614 0.504 0.110 0.472 0.142 

2002 0.820 0.684 0.136 0.644 0.176 2003 0.241 0.201 0.040 0.188 0.053 
32 

Table H.5 – Predicted Maximum Visibility Improvements for Pacificorp – Hunter Unit 1. 

Class I Area 

LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR LNB/SOFA/SCR vs. LNB/SOFA 

Visibility 

Improvement (∆dv) Visibility Improvement (∆dv) Visibility Improvement (∆dv) Visibility Improvement (∆d

Arches NP 0.737 0.906 1.342 0.605 

Black Canyon NP 0.198 0.241 0.345 0.147 

Bryce Canyon NP 0.306 0.372 0.534 0.228 

Canyonlands NP 0.846 1.041 1.545 0.699 

Capitol Reef NP 0.639 0.750 1.113 0.474 

Flat Tops Wilderness 0.231 0.280 0.404 0.173 

Grand Canyon NP 0.349 0.426 0.618 0.269 

Mesa Verde NP 0.235 0.286 0.426 0.191 

Zion NP 0.184 0.224 0.323 0.139 

Table H.6 – Predicted Maximum Visibility Improvements for Pacificorp – Hunter Unit 2. 

Class I Area 

LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR LNB/SOFA/SCR vs. LNB/SOFA 

Visibility 

Improvement (∆dv) Visibility Improvement (∆dv) Visibility Improvement (∆dv) Visibility Improvement (∆d

Arches NP 0.569 0.711 1.080 0.511 

Black Canyon NP 0.153 0.189 0.279 0.126 

Bryce Canyon NP 0.234 0.291 0.429 0.195 

Canyonlands NP 0.658 0.822 1.250 0.592 

Capitol Reef NP 0.491 0.623 0.879 0.388 

Flat Tops Wilderness 0.180 0.223 0.328 0.148 

Grand Canyon NP 0.275 0.340 0.506 0.231 

Mesa Verde NP 0.182 0.225 0.344 0.162 

Zion NP 0.144 0.178 0.262 0.118 
33 

Table H.7 – Predicted Maximum Visibility Improvements for Pacificorp – Huntington Unit 1. 

Class I Area 

LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR LNB/SOFA/SCR vs. LNB/SOFA 

Visibility 

Improvement (∆dv) Visibility Improvement (∆dv) Visibility Improvement (∆dv) Visibility Improvement (∆d

Arches NP 0.684 0.907 1.488 0.804 

Black Canyon NP 0.156 0.205 0.328 0.172 

Bryce Canyon NP 0.222 0.292 0.473 0.251 

Canyonlands NP 0.851 1.133 1.881 1.030 

Capitol Reef NP 0.493 0.651 1.108 0.615 

Flat Tops Wilderness 0.181 0.239 0.383 0.202 

Grand Canyon NP 0.200 0.262 0.419 0.219 

Mesa Verde NP 0.215 0.284 0.462 0.247 

Zion NP 0.150 0.198 0.320 0.170 

Table H.8 – Predicted Maximum Visibility Improvements for Pacificorp – Huntington Unit 2. 

Class I Area 

LNB/SOFA LNB/SOFA/SNCR LNB/SOFA/SCR LNB/SOFA/SCR vs. LNB/SOFA 

Visibility 

Improvement (∆dv) Visibility Improvement (∆dv) Visibility Improvement (∆dv) Visibility Improvement (∆d

Arches NP 0.625 0.816 1.316 0.691 

Black Canyon NP 0.143 0.184 0.292 0.149 

Bryce Canyon NP 0.205 0.266 0.424 0.219 

Canyonlands NP 0.776 1.016 1.657 0.881 

Capitol Reef NP 0.449 0.584 0.955 0.506 

Flat Tops Wilderness 0.168 0.217 0.343 0.175 

Grand Canyon NP 0.183 0.236 0.371 0.188 

Mesa Verde NP 0.199 0.258 0.414 0.215 

Zion NP 0.136 0.176 0.281 0.145 
34 

Table H.9 – Predicted Number of Days Greater than 0.5 and 1.0 Δdv for Pacificorp – Hunter Unit 1. 

Class I Area Year 

Baseline LNB/SOFA LNB/SOFA/SNCR 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

Arches NP 

2001 84 48 74 42 72 42 

2002 117 67 102 55 105 55 2003 92 55 84 44 82 42 

Black Canyon NP 

2001 17 4 13 3 11 3 2002 30 11 24 5 24 4 2003 21 7 18 5 18 5 

Bryce Canyon NP 

2001 16 6 13 6 13 5 

2002 21 13 19 10 18 10 2003 5 3 5 3 5 3 

Canyonlands NP 

2001 103 70 93 65 90 59 2002 140 93 126 85 123 80 2003 116 77 111 68 109 63 

Capitol Reef NP 

2001 40 30 37 29 36 29 

2002 70 51 63 48 63 47 2003 65 37 60 33 57 33 

Flat Tops Wilderness 

2001 16 5 13 4 12 4 2002 26 13 20 8 18 8 2003 35 13 30 8 29 6 

Grand Canyon NP 

2001 16 10 14 7 14 7 

2002 22 15 20 11 19 10 2003 11 7 9 7 9 6 

Mesa Verde NP 

2001 23 9 18 7 18 7 2002 32 12 25 5 25 4 2003 27 11 23 8 20 8 

Zion NP 

2001 11 7 8 4 8 3 

2002 15 5 12 5 12 5 2003 3 2 3 0 3 0 
35 

Table H.10 – Predicted Number of Days Greater than 0.5 and 1.0 Δdv for Pacificorp – Hunter Unit 2. 

Class I Area Year 

Baseline LNB/SOFA LNB/SOFA/SNCR 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

Number of Days 

∆dv > 0.5 

Number of Day

∆dv > 1.0 

Arches NP 

2001 84 48 80 44 74 42 

2002 117 67 110 60 109 58 2003 92 55 86 47 85 45 

Black Canyon NP 

2001 17 4 13 4 13 3 2002 30 11 26 7 24 5 2003 21 7 18 5 18 5 

Bryce Canyon NP 

2001 16 6 14 6 13 6 

2002 21 13 20 12 19 10 2003 5 3 5 3 5 3 

Canyonlands NP 

2001 103 70 96 65 93 65 2002 140 93 128 86 126 85 2003 116 77 112 70 112 68 

Capitol Reef NP 

2001 40 30 38 29 37 29 

2002 70 51 64 49 63 48 2003 65 37 61 35 61 34 

Flat Tops Wilderness 

2001 16 5 13 4 13 4 2002 26 13 20 8 20 8 2003 35 13 31 8 30 8 

Grand Canyon NP 

2001 16 10 16 7 15 7 

2002 22 15 21 11 21 11 2003 11 7 9 7 9 7 

Mesa Verde NP 

2001 23 9 20 8 18 7 2002 32 12 28 5 25 5 2003 27 11 24 9 23 8 

Zion NP 

2001 11 7 9 5 8 4 

2002 15 5 12 5 12 5 2003 3 2 3 1 3 0 
36 

Table H.11 – Predicted Number of Days Greater than 0.5 and 1.0 Δdv for Pacificorp – Huntington Unit 1. 

Class I Area Year 

Baseline LNB/SOFA LNB/SOFA/SNCR 

Number of Days 

∆dv => 0.5 

Number of Days 

∆dv => 1.0 

Number of Days 

∆dv => 0.5 

Number of Days 

∆dv => 1.0 

Number of Days 

∆dv => 0.5 

Number of Days 

∆dv => 1.0 

Arches NP 

2001 72 42 69 35 66 35 

2002 94 57 85 47 81 45 2003 71 47 67 39 63 37 

Black Canyon NP 

2001 11 5 7 2 7 2 2002 20 5 15 3 14 3 2003 14 6 11 2 9 2 

Bryce Canyon NP 

2001 13 5 8 4 8 2 

2002 15 11 14 7 13 7 2003 8 3 4 2 4 0 

Canyonlands NP 

2001 86 53 71 48 69 44 2002 109 67 104 61 102 56 2003 82 55 74 44 73 43 

Capitol Reef NP 

2001 31 25 30 20 30 20 

2002 54 40 51 32 50 30 2003 46 26 36 22 36 19 

Flat Tops Wilderness 

2001 14 5 9 2 8 2 2002 20 6 11 4 11 4 2003 30 6 21 3 18 2 

Grand Canyon NP

2001 10 7 10 5 10 5 

2002 19 9 17 7 16 6 2003 11 3 8 1 8 1 

Mesa Verde NP 

2001 15 5 10 5 9 4 2002 25 9 19 3 18 2 2003 23 8 17 5 14 4 

Zion NP 

2001 8 6 7 3 7 3 

2002 10 5 8 5 8 3 2003 3 0 1 0 1 0 
37 

Table H.12 – Predicted Number of Days Greater than 0.5 and 1.0 Δdv for Pacificorp – Huntington Unit 2. 

Class I Area Year 

Baseline LNB/SOFA LNB/SOFA/SNCR 

Number of Days 

∆dv => 0.5 

Number of Days 

∆dv => 1.0 

Number of Days 

∆dv => 0.5 

Number of Days 

∆dv => 1.0 

Number of Days 

∆dv => 0.5 

Number of Days 

∆dv => 1.0 

Arches NP

2001 72 42 70 35 67 35 

2002 94 57 86 47 82 46 2003 71 47 67 40 65 37 

Black Canyon NP 

2001 11 5 9 2 7 2 2002 20 5 15 4 15 3 2003 14 6 11 2 10 2 

Bryce Canyon NP 

2001 13 5 8 5 8 4 

2002 15 11 14 8 14 7 2003 8 3 4 2 4 2 

Canyonlands NP 

2001 86 53 73 48 69 47 2002 109 67 106 61 102 58 2003 82 55 75 44 73 44 

Capitol Reef NP 

2001 31 25 30 20 30 20 

2002 54 40 52 32 50 30 2003 46 26 37 23 36 20 

Flat Tops Wilderness 

2001 14 5 11 2 9 2 2002 20 6 11 4 11 4 2003 30 6 22 3 19 2 

Grand Canyon NP 

2001 10 7 10 5 10 5 

2002 19 9 17 7 17 7 2003 11 3 9 1 8 1 

Mesa Verde NP 

2001 15 5 11 5 10 5 2002 25 9 19 3 18 3 2003 23 8 18 5 15 5 

Zion NP 

2001 8 6 8 3 7 3 

2002 10 5 8 5 8 3 2003 3 0 1 0 1 0 
38 

Table H.13 – Predicted Total Number of Days Greater than 0.5 and 1.0 Δdv between 2001 and 2003 for Pacificorp – Hunt

Class I Area 

Baseline LNB/SOFA LNB/SOFA/SNCR 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

N

Arches NP 293 170 260 141 259 139 

Black Canyon NP 68 22 55 13 53 12 

Bryce Canyon NP 42 22 37 19 36 18 

Canyonlands NP 359 240 330 218 322 202 

Capitol Reef NP 175 118 160 110 156 109 

Flat Tops Wilderness 77 31 63 20 59 18 

Grand Canyon NP 49 32 43 25 42 23 

Mesa Verde NP 82 32 66 20 63 19 

Zion NP 29 14 23 9 23 8 

Table H.14 – Predicted Total Number of Days Greater than 0.5 and 1.0 Δdv between 2001 and 2003 for Pacificorp – Hunt

Class I Area 

Baseline LNB/SOFA LNB/SOFA/SNCR 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

N

Arches NP 293 170 276 151 268 145 

Black Canyon NP 68 22 57 16 55 13 

Bryce Canyon NP 42 22 39 21 37 19 

Canyonlands NP 359 240 336 221 331 218 

Capitol Reef NP 175 118 163 113 161 111 

Flat Tops Wilderness 77 31 64 20 63 20 

Grand Canyon NP 49 32 46 25 45 25 

Mesa Verde NP 82 32 72 22 66 20 

Zion NP 29 14 24 11 23 9 
39 

Table H.15 – Predicted Total Number of Days Greater than 0.5 and 1.0 Δdv between 2001 and 2003 for Pacificorp – Hunt

Class I Area 

Baseline LNB/SOFA LNB/SOFA/SNCR 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

N

Arches NP 237 146 221 121 210 117 

Black Canyon NP 45 16 33 7 30 7 

Bryce Canyon NP 36 19 26 13 25 9 

Canyonlands NP 277 175 249 153 244 143 

Capitol Reef NP 131 91 117 74 116 69 

Flat Tops Wilderness 64 17 41 9 37 8 

Grand Canyon NP 40 19 35 13 34 12 

Mesa Verde NP 63 22 46 13 41 10 

Zion NP 21 11 16 8 16 6 

Table H.16 – Predicted Total Number of Days Greater than 0.5 and 1.0 Δdv between 2001 and 2003 for Pacificorp – Hunt

Class I Area 

Baseline LNB/SOFA LNB/SOFA/SNCR 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

Number of Days 

∆dv > 0.5 

Number of Days 

∆dv > 1.0 

N

Arches NP 237 146 223 122 214 118 

Black Canyon NP 45 16 35 8 32 7 

Bryce Canyon NP 36 19 26 15 26 13 

Canyonlands NP 277 175 254 153 244 149 

Capitol Reef NP 131 91 119 75 116 70 

Flat Tops Wilderness 64 17 44 9 39 8 

Grand Canyon NP 40 19 36 13 35 13 

Mesa Verde NP 63 22 48 13 43 13 

Zion NP 21 11 17 8 16 6