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### TABLE OF CONTENTS

SECTION PAGE

1.0 EXECUTIVE SUMMARY ............................................................................................. 1-1

2.0 INTRODUCTION/BACKGROUND .............................................................................. 2-1

3.0 PLANT DESCRIPTION .................................................................................................. 3-1

4.0 EMISSIONS DATA ........................................................................................................ 4-1

5.0 CALPUFF MODELING SY STEM OVERVIEW........................................................... 5-1

6.0 GEOPHYSICAL AND METEO ROLOGICAL DATA .................................................. 6-1 6.1 Modeling Domain ......................................................................................................... 6-1 6.2 Terrain ....................................................................................................................... .... 6-1 6.3 Land Use ...................................................................................................................... . 6-2 6.4 Meteorological Data Base ............................................................................................. 6-2

7.0 AIR QUALITY MODELING METHODOLOGY ......................................................... 7-1 7.1 Model Selection ............................................................................................................. 7 -1 7.2 Meteorological Modeling Options ................................................................................ 7-1 7.3 CALPUFF Computational Doma in and Receptors ....................................................... 7-2 7.4 Dispersion Modeling Options ....................................................................................... 7-2 7.5 Air Quality Monitoring Data ......................................................................................... 7-3 7.6 Regional Haze ............................................................................................................... 7 -4 7.7 Regional Haze Impact Calc ulation Methodology ......................................................... 7-4 7.8 Background Concentrations and Relative Humidity Adjustment Factors .................... 7-5

8.0 BART PROTOCOL MOD ELING RESULTS ................................................................ 8-1

9.0 SUMMARY ..................................................................................................................... 9 -1

### TABLE OF CONTENTS (Continued)

TABLES

Table ES-1: Modeled Vi sibility 20% B est Days*................................................................................ .... 1-4 Table 3-1 Colstrip Plant Stack Parameters ............................................................................... ........... 3-4 Table 4-1: Colstrip Clean Air Markets Summary – Maximum Daily Data .......................................... 4-3 Table 4-2: Colstrip Particulate Ma tter Emission Factors from Stack Testing ...................................... 4-3 Table 4-3: Summary of Colstrip Unit 3 September 1999 Coal Analysis .............................................. 4-4 Table 4-4: Colstrip Units 1 a nd 2 Annual Average Emissions Data ..................................................... 4-4 Table 4-5: Colstrip Unit Cases, English Units ............................................................................ .......... 4-5 Table 4-6: Colstrip Unit Cases, Metric Units.............................................................................. .......... 4-8 Table 4-7: Colstrip - Modeling Scenarios ................................................................................. .......... 4-11 Table 6-3. Meteorological Data Sources a nd Parameters Available ................................................... 6-7 Table 6-4. NWS Upper Air Stations ................................................................................................... 6-7 Table 6-5. NWS Hourly Surface Stations ........................................................................................... 6-8 Table 6-6. NWS Precipitation Stations ............................................................................................... 6-9 Table 7-5. Ozone Stations ................................................................................................................ ... 7-7 Table 7-6. Summary of Background Natural Visibility Conditions .................................................... 7-9 Table 7-7. Monthly f(RH) values based on Represen tative IMPROVE Site Locations...................... 7-9 Table 8-1 Class I Impacts (Deciviews) Method 8 (8 th 

### Highest Annual Average)* ............................ 8-1 Table 8-2 Class I Impacts (Deciviews) Method 8 20% Best Days Condition .................................... 8-2



### FIGURES
ES-1 Colstrip Location and Class I Areas Evaluated ............................................................................ 1-3 3-1 Colstrip Powe r Plant Location ............................................................................................. ......... 3-2 3-2 Plot Plan of the Colstrip Facility Showi ng the Relative Locations of Units 1-4. ......................... 3-3 6-1 Terrain Contours .............................................................................................................. ............. 6-4 6-2 Dominant Land U se Categories .................................................................................................. .. 6-5 6-3 Surface Stations .............................................................................................................. .............. 6-6 7-1 Locations of Receptors ........................................................................................................ ......... 7-6 7-4 Locations of Ozone Monitoring Stations used in the CALPUFF Modeling ................................. 7-7

### 1-1 

### 1.0 EXECUTIVE SUMMARY Atmospheric dispersion and chemistry mo deling was used to predict the possible visibility impacts of emissions from the Colstrip generating plant in Cols trip, MT at Prevention of Significant Deterioration (PSD) Class I areas. The Class I areas within 300 kilometers (km) of Colstrip are the UL Bend Na tional Wildlife Refuge (200 km to the northwest), the North Absaroka Wilderness Area (254 km to the west), the Theodore Roosevelt National Park (260 km to the northeast), the Washakie Wilderness Area (278 km to the southwest) and Yellowstone National Park (281 km to the west). These Cla ss I areas are shown in re lation to the Colstrip plant in Figure ES-1. The CALPUFF model was used to evaluate the visibility impacts of both historical and present emissions from Colstrip as well as a vari ety of emission control alternatives. The model setup and input meteorological data were obta ined from Environmental Protection Agency (EPA)/Western Regional Air Part nership (WRAP) files. Colstrip Units 1&2 are rated at 333gross megawatts (MW) each and Units 3&4 are rated at 805 gross MW each. Emissions data were from various sources representing histor ical worst-case actual emissions (2001-2003, the baseline Best Available Retrofit Technology (“ BART”) modeling period), current worst-case actual emissions (reference modeling period) and se veral potential control strategies to identify the “best system of continuous emission reducti on” applicable to the plant for filterable particulate, sulf ur dioxide (SO 2 

### ) and nitrogen oxides (NO x 

### ) control. These units already have relatively low emissions due to th e use of wet scrubbers that rem ove both particulate and sulfur dioxide, low sulfur Powder River Basin co al and good combustion control using low NO x 

### burners (LNB). A range of de monstrated control al ternatives for sub-b ituminous coal-fired
boilers was modeled:

 Baseline case controls – those controls in-p lace in the baseline period (2001-2003). These are wet scrubbers and LNB

.

 Reference case controls – those cont rols in-place as of November 2011.

 For Units 1 and 2, the reference case controls are wet sc rubbers, upgraded LNB, and digital boiler controls.

 For Units 3 and 4, the reference case controls are wet sc rubbers, upgraded LNB, Separated Over-Fire Air (SOFA) , and digital boiler controls.

 Potential add-on controls

 SOFA for Units 1 and 2 (includi ng further upgrades to the LNB).

 Selective Non-Catalytic Reduction (SNCR) for all units.

### 1-2 

###  Selective Catalytic Reduction (SCR) for all units.

 Enhanced SO 2 

### controls with lime injection for Units 1 & 2.

 Enhanced particulate matter controls for Units 1 & 2.

The modeling was conducted by TRC and a summ ary of the visibili ty modeling results for the 20 percent best natural b ackground visibility days is provi ded in ES-1. The results are presented as the 98 th 

### percentile predicted de lta-deciview impacts from natural background conditions where 1.0 delta-deciview is genera lly considered the av erage limit of human perception. Incremental changes of less than 1.0 be tween cases will not be generally perceptible.
Use of the 98 th 

### percentile predicted visibility impact is conservative because predicted visibility impacts of this magnitude or gr eater only occur eight days per year, but th ese predicted impacts are compared against all natural visibility conditions . Moreover, as elaborated herein, several additional conservative assumptions are built into the modeling protocol, so the actual visibility impacts should be regarded as less than the predicted values pr esented in Table ES-1.

### 1-3 

### Figure ES-1: Colstrip Location and Class I Areas Evaluated1-4Table ES-1: Modeled Visibility 20% Best Days**Scenario visibility predictions include application of indicated controls on all Units listed in the sub-headings (i.e. Units1&2, Units3&4).

### 2-1 

### 2.0 INTRODUCTION/BACKGROUND The owners of the Colstrip power plant, PPL Montana, Puget Sound Energy Inc., Portland General Electric Company, Avista Cor poration, PacifiCorp and NorthWestern Energy, are working with the U.S. Environmental Pr otection Agency (EPA) Region 8 to assess the efficacy of emission control options vis-à-vis th e facility’s predicted visibility impacts at Prevention of Significant Deterioration (PSD) Class I areas. Regional haze is caused by naturally occurring atmospheric particles and humidity as well as by anthropogenic emissions of primary particulate matter and of secondary emi ssions resulting from atmos pheric gas to particle conversions of sulfur dioxide (SO 2 

### ) and nitrogen oxides (NO x 

### ). The Regional Haze Regulations are intended to improve visibili ty in PSD Class I Areas. The Colstrip plant is located in Colstrip, Mont ana. Units 1 and 2 be gan operating in 1975 and 1976, and Units 3 and 4 began operation in 1984 and 1986. Colstrip Units 1&2 each have a gross generating capacity of 333 megawatts (MW), a nd have low emissions due to the use of low sulfur coal and venturi scrubbers. Colstrip Un its 3&4 each have a gross generating capacity of
805 MW and likewise use low sulfur co al and scrubbers as well as SOFA. Previous reports, Best Available Retrofit Technology (BART) Assess ment of Colstrip Generating Station, August 2007 and, respondi ng to EPA’s comments, Addendum to PPL Montana’s Colstrip BART Report, June 2008, ha ve been prepared and submitted relative to control strategies and predicted visibility im pacts for Units 1&2 under the BART rules. The
more recent, NO x 

### Control Update to PPL Montana’s Cols trip Generating Station BART Report, September 2011, updated cost estimates, but did not contain any new visibility modeling. 

### This February 2012 report addresses modeled visibili ty impacts of various control strategies for Units 1 through 4. This report describes the facility emissi ons for a “baseline case” as existed in 2001-2003 (used for the BART modeling), the emissions fo r a “reference case” as exists for current operations, and for various poten tial emission control options. The inputs to the CALPUFF model, used to predict the visibility impacts, ar e described and the predictions are presented.

### 3-1 

### 3.0 PLANT DESCRIPTION The Colstrip power plant has four coal-fir ed generating units. Units 1 and 2 began operation in 1975 and 1976 respectively, and Units 3 and 4 began operati ons in 1984 and 1986, respectively. Units 1 and 2 are rated at 333 megawatts of gross generating capacity each and
Units 3 and 4 are rated at 805 me gawatts of gross generating capac ity each. The facility burns
low sulfur Powder River Basin sub-bituminous co al. A map of the plant location is shown in Figure 3-1. The air pollution control devices for Units 1 and 2, include wet scrubbers installed as original equipment, upgraded low NOx burners installed on both units by 2006, and digital boiler controls installed on both units by 2007. Units 3 a nd 4 have wet scrubbers installed as original equipment, as well as upgraded low NOx burners , Separated Over-Fire Air (SOFA) and digital
boiler controls installed on Unit 3 in 2007, and on Unit 4 in 2009. Fi gure 3-2 presents a plot plan of the facility showing the west to east arrangements of Units 1 through 4. Each of the four units is serviced by its ow n, single flue stack. Table 3-1 presents the stack parameter data used for modeli ng input for all modeling scenarios.

### 3-2 

### Figure 3-1 Colstrip Power Plant Location3-3Figure 3-2 Plot Plan of the Colstrip FacilityShowing the Relative Locations of Units 1-4.

### 3-4 

### Table 3-1 Colstrip Plant Stack Parameters

Stack ID # Lambert Conformal Coordinates 1 

### Stack Height Base Elevation Diameter Gas Exit Velocity

LCC East LCC North

km km M m m m/sec
Unit 1 823.887 185.596 152.4 988 5.03 29.7
Unit 2 823.930 185.598 152.4 988 5.03 28.44
Unit 3 824.044 185.514 210.9 988 7.32 33.5
Unit 4 824.142 185.516 210.9 988 7.32 33.5

1 

### The LCC projection is based on sta ndard parallels at 45.0 and 49.0 North, and origin at 44.25 North and 109.5 West, false easting of 600 km and NAD83.

### 4-1 4.0 EMISSIONS DATA The maximum actual one-day (midnight to midnight) pollutant emission rates were compiled for modeling input. SO 2 

### , NOx and Particulate Matter (PM) emission rates were assembled. The maximum actual one-day emissions fo r each pollutant were not restricted to be concurrent, and thus the modele d emissions do not represent a re al emission day, but assume the worst-case emissions for each pollutant occur on all days of the modeling period. This is an unrealistic, conservative assumption based upo n EPA’s BART modeling protocol since the maximum emission rates of each pollutant do not, in fact, occur simultaneously and the actual daily emissions over the modeling period are lowe r than the maximum actual daily emissions. The U.S. Environmental Protection Agency (EPA) Clean Air Markets (CAM) web site 1


### contains the raw Continuous Emissions Monitori ng Systems (CEMS) data from the Electronic Data Reports (EDRs) submitted by power plants pursuant to Federal Acid Rain program and other market-based regulatory programs. Pre-packaged data sets 2 

### for January 2001 through December 2003 (the “baseline” period used for BART analysis) and January 2008 through June 2011 (the “reference” period for current emissions) were downloaded from the CAM web site. The maximum one-day SO 2 

### emission rate (pound per hour, lb/hr), NO x 

### emission rate (lb/hr), and heat input rate (million British Thermal Units per hour, MMBtu/hr) in each period are
summarized in Table 4-1. Note that “substitute data” are not included in Table 4-1, and were not used for the visibility evaluations, and that th e maximum one-day emissions for the pollutants are not concurrent. The use of CAM data, even absent substituted data, adds another layer of
conservativeness to the model results. The monitori ng protocols are designed to ensure that if a bias is present in the data, the emissions bias will always be positive ( i.e. , the bias will result only in overestimated emissions and impacts). Furthermore experience in measuring heat input at Colstrip indicates that the data re ported in CAM contains positive bias. PM consists of Filterable PM (FPM) and Condensable PM (CPM). FPM and CPM emission factors were calculated from testing of Units 1 and 3 in April 2011 and June 2010, respectively. These test results are summari zed in 4-2. CPM and FPM emissions employed for modeling are simply the emission factor multiplied by the maximum one-day heat input rate for the period of interest. PM speciation was performed using the method in the workbook provided by the National Park Service (NPS) for dry-bottom pulverized-coal boilers with wet scrubbing 3 

### . The

1 http://camddataandmaps.epa.gov/gdm/index.cfm?fuseaction=emissions.wizard , accessed October 11, 2011. 2 Each prepackaged data set covers one calendar quarter. 3 http://www.nature.nps.gov/air/per mits/ect/ectCoalFiredBoiler.cfm , accessed October 12, 2011.

### 4-2 NPS spreadsheet speciates CPM in to organic and inorganic fracti ons, and FPM into coarse soil, fine soil, and elemental carbon fractions. The NPS speciation is based on PM with an aerodynamic diameter of 10 microns or less (PM 10 

### ). All CPM is PM 10 

### . The stack tests, however, measure total FPM. Therefore, the to tal FPM emission factors from stack tests are multiplied by 0.71 (obtained from AP-42 4 

### ) to obtain FPM with an aerodynamic diameter of 10 microns or less (FPM 10 

### ). The coal properties (summarized in 4-3) input to the NPS workbook were obtained from a 1999 stack test report 5 

### for Unit 3. The control technologies consid ered include the following:

 Baseline case controls – those controls in-place as of 2003. These are wet scrubbers and LNB.

 Reference case controls – those cont rols in-place as of November 2011.

 For Units 1 and 2, the reference case cont rols are wet scrubb ers, upgraded LNB, and digital boiler controls.

 For Units 3 and 4, the reference case cont rols are wet scrubb ers, upgraded LNB, SOFA and digital controls. For each of these units, the maximum NO x 

### emission rate after the installation date is used as the SOFA emission rate. Substitute CAM data are excluded.

 Potential add-on controls

 SOFA for Units 1 and 2 (including upgrad ed LNB). The assumed NOx emissions rate of 0.266 lb/MMBtu (24 hour emission rate) is based on the average NOx emissions rate from Units 1 and 2 during the period from 2006 through 2010 (refer to 4-4), and the expect ed emission rate improvement.

 Selective Non-Catalytic Reduction (SNCR) for all units. A 10 percent reduction in emissions relative to the cases with LNB plus SOFA.

 Selective Catalytic Reduction (SCR) for all units. The assumed NOx emissions rate of 0.084 lb/MMBtu (24-hour average).

 Enhanced SO 2 

### controls with lime injection f or Units 1&2. Cases with 0.38 lb/MMBtu emissions (24 hour average) - approximately a 50% further reduction in emission (equivalent to an 88 percent reduction from the uncontrolled emission on a 30 day average).

 Enhanced particulate matter controls, with PM 10 

### emission rate of 0.015 lb/MMBtu for Units 1 & 2 Table 4-5 presents the emission control cases for each of the four Colstrip Units in English units. Table 4-6 presents these cases in metric units, which are used by the air dispersion model. Table 4-7 presents the modeling scenarios, which are combinations of the units’ cases in
Table 4-6.

4AP-42, Fifth Edition, Compilation of Air Pollutant Emissi on FactorsVolume I, Stationary Point and Area Sources,

Table 1.1-6. 5Source Emissions Survey of Montana Power Company Colstrip Pr oject Division Unit Number 3- 6 Scrubber Inlet Duct and Unit Number 3 Stack Colstrip, Montana, September 1999, 36404 File Number 99-166 http://www.epa.gov/ttnatw01/comb ust/utiltox/mercury/colstrpr.pdf , accessed October 12, 2011.

### 4-3 Table 4-2: Colstrip Particulate Matter Emission Factors from Stack Testing
Colstrip

Units Filterable Particulate

Matter (FPM) (lb/MMBtu) Condensable Particulate

Matter (CPM) (lb/MMBtu) Comments

Units 1&2 0.0155 0.0214 From April 2011 test of Unit 1. Average of 3 runs. Units 3&4 0.0226 0.0049 From June 2010 test of Unit 3. Average of 3 runs. 

### Table 4-1: Colstrip Clean Air Mark ets Summary – Maximum Daily Data

Year Unit Max Heat Input2 (MMBtu) Date On Which Max Heat Input Occurred Max SO 2 Emissio ns2 (lb/hr) Date On Which Max SO 2 Emissions Occurred Max NO x Emissio ns3 (lb/MMBtu) Max NO x Emission s2 (lb/hr) Date On Which Max NO x Emissions Occurred 20111 1 3,692 01/04/2011 2,367 01/04/2011 0.38 1,388 05/04/2011 20111 2 3,507 01/01/2011 1,649 01/08/2011 0.37 1,297 02/24/2011 20111 3 7,990 03/29/2011 790 03/18/2011 0.17 1,397 03/30/2011 20111 4 8,120 01/11/2011 814 01/03/2011 0.17 1,398 02/01/2011 2010 1 3,732 04/14/2010 2,645 12/22/2010 0.41 1,529 04/28/2010 2010 2 3,708 03/02/2010 2,250 03/30/2010 0.46 1,710 02/24/2010 2010 3 8,616 02/14/2010 785 04/06/2010 0.17 1,479 02/05/2010 2010 4 8,980 03/02/2010 830 07/09/2010 0.16 1,443 01/04/2010 2009 1 3,758 11/15/2009 2,652 11/15/2009 0.40 1,503 12/15/2009 2009 2 3,647 12/08/2009 2,453 10/21/2009 0.41 1,508 02/09/2009 2009 3 8,686 12/15/2009 820 01/29/2009 0.17 1,491 12/15/2009 2009 4 8,656 12/15/2009 782 12/20/2009 0.27 2,324 11/30/2009 2008 1 3,844 03/22/2008 2,342 01/21/2008 0.43 1,662 02/05/2008 2008 2 3,991 01/30/2008 2,368 01/21/2008 0.37 1,487 04/22/2008 2008 3 8,336 08/05/2008 799 09/19/2008 0.18 1,501 08/15/2008 2008 4 8,795 01/04/2008 1,054 09/19/2008 0.40 3,559 02/14/2008 2001- 2003 1 4,012 10/01/2003 2,812 01/03/2002 0.49 1,971 10/25/2003

2001- 2003 2 3,903 08/01/2002 2,909 04/06/2002 0.54 2,125 02/20/2001

2001- 2003 3 8,777 01/03/2002 969 10/29/2003 0.46 4,029 03/15/2002

2001- 2003 4 9,462 05/12/2001 914 10/05/2003 0.43 4,082 02/17/2001


### 1. January through June 2. Data are the 24 hour average of the maximum day (midnight to midnight), substitute data excluded, as reported by EPA Clean Air Markets website 3. Approximate

### 4-4 Table 4-3: Summary of Colstrip Un it 3 September 1999 Coal Analysis
Coal Analysis Parameter Test 1 Test 2 Test 3 Average Sulfur (% dry) 0.72 0.74 0.76 0.74 Ash (% dry) 16.8 18 17.3 17.4 HHV (Btu/lb, as fired) 9,550 9,300 9,470 9,440



### Table 4-4: Colstrip Units 1 and 2 Annual Average Emissions Data
From EPA Clean Air Markets
Unit ID Year Operating Time Avg. NO x Rate (lb/MMBtu) NO x Tons Heat Input (MMBtu)

1 1997 7,406 0.390 4,702 24,119,389 1 1998 7,828 0.393 5,273 26,858,555 1 1999 7,278 0.407 5,305 26,069,267 1 2000 8,270 0.342 4,390 25,642,024 1 2001 7,620 0.399 5,370 26,939,103 1 2002 8,346 0.401 5,811 28,955,991 1 2003 7,460 0.378 4,983 26,328,944 1 2004 8,474 0.346 5,321 30,770,151 1 2005 8,428 0.348 5,145 29,574,218 1 2006 7,259 0.310 3,726 24,003,758 1 2007 8,353 0.306 4,428 28,950,693 1 2008 8,198 0.319 4,317 27,066,347 1 2009 7,519 0.304 3,854 25,314,407 1 2010 8,160 0.303 4,138 27,353,513 2 1997 7,517 0.417 5,933 28,484,395 2 1998 8,204 0.435 5,452 25,057,443 2 1999 8,085 0.381 5,517 28,933,076 2 2000 7,667 0.424 5,359 25,302,330 2 2001 8,563 0.430 6,339 29,450,519 2 2002 7,124 0.406 4,967 24,447,383 2 2003 8,228 0.402 5,773 28,747,739 2 2004 8,335 0.405 5,848 28,891,409 2 2005 7,418 0.366 4,678 25,570,756 2 2006 8,335 0.281 4,020 28,630,015 2 2007 8,154 0.302 4,363 28,936,718 2 2008 7,109 0.311 3,744 24,082,853 2 2009 8,590 0.297 4,117 27,731,018 2 2010 7,964 0.320 4,224 26,425,2084-5Table 4-5: Colstrip Unit Cases, English UnitsCaseIDCaseDescriptionSO2(lb/hr)NOx(lb/MMBtu)NOx(lb/hr)Particulate Matter (lb/hr)Stack Parameters§Filterable Condensable Height(ft)InnerDiameter(ft)Temp(F)ExitVelocity(ft/s)CoarseSoilFineSoilElementalCarbonInorganic(SOx)Organic1X Unit 1BaselineCase2,812@ 0.491@ 1,971@12.6∆30.4∆1.2∆68.7∆17.2∆500 16.5 200 971R Unit 1ReferenceCase(DigitalControls)2,652* 0.432* 1,662* 12.1! 29.1! 1.1! 65.8! 16.5! 500 16.5 200 971A Unit 1SOFA2,652* 0.266^ 1,022^ 12.1! 29.1! 1.1! 65.8! 16.5! 500 16.5 200 971B Unit 1 88%SO2Control1,461‡ 0.432* 1,662* 12.1! 29.1! 1.1! 65.8! 16.5! 500 16.5 200 971C Unit 1SOFA w/88% SO2Control1,461‡ 0.266^ 1,022^ 12.1! 29.1! 1.1! 65.8! 16.5! 500 16.5 200 971D Unit 1SOFA +SCR2,652* 0.084^ 323^ 12.1! 29.1! 1.1! 65.8! 16.5! 500 16.5 200 971E Unit 1 PM10= 0.015lb/MMBtu2,652* 0.432* 1,662* 5.6† 13.5† 0.5† 30.5† 7.6† 500 16.5 200 972X Unit 2BaselineCase2,909@ 0.544@ 2,125@ 12.3∆29.5∆1.1∆66.8∆16.7∆500 16.5 201 932R Unit 2ReferenceCase(DigitalControls)2,453* 0.461* 1,710* 12.5! 30.2! 1.2! 68.3! 17.1! 500 16.5 201 932A Unit 2SOFA2,453* 0.266^ 1,062^ 12.5! 30.2! 1.2! 68.3! 17.1! 500 16.5 201 932B Unit 2 88%SO2Control1,517‡ 0.461* 1,710* 12.5! 30.2! 1.2! 68.3! 17.1! 500 16.5 201 934-6Table 4-5: Colstrip Unit Cases, English UnitsCaseIDCaseDescriptionSO2(lb/hr)NOx(lb/MMBtu)NOx(lb/hr)Particulate Matter (lb/hr)Stack Parameters§Filterable Condensable Height(ft)InnerDiameter(ft)Temp(F)ExitVelocity(ft/s)CoarseSoilFineSoilElementalCarbonInorganic(SOx)Organic2C Unit 2SOFA w/88% SO2Control1,517‡ 0.266^ 1,062^ 12.5! 30.2! 1.2! 68.3! 17.1! 500 16.5 201 932D Unit 2SOFA +SCR2,453* 0.084^ 335^ 12.5! 30.2! 1.2! 68.3! 17.1! 500 16.5 201 932E Unit 2 PM10= 0.015lb/MMBtu2,453* 0.461* 1,710* 5.8† 14.0† 0.5† 31.6† 7.9† 500 16.5 201 933X Unit 3BaselineCase969@ 0.459@ 4,029@ 40.2$ 96.9$ 3.7$ 34.4$ 8.6$ 692 24.0 190 1103R Unit 3ReferenceCase(SOFA)820© 0.180© 1,501© 39.8# 95.9# 3.7# 34.0# 8.5# 692 24.0 190 1103A Unit 3SOFA +SNCR820© 0.162& 1,351& 39.8# 95.9# 3.7# 34.0# 8.5# 692 24.0 190 1103B Unit 3SOFA +SCR820© 0.084¶ 730¶ 39.8# 95.9# 3.7# 34.0# 8.5# 692 24.0 190 1104X Unit 4BaselineCase914@ 0.431@ 4082@ 43.4$ 104.4$ 4.0$ 37.1$ 9.3$ 692 24.0 190 1104R Unit 4ReferenceCase(SOFA)830© 0.172© 1,443© 41.2# 99.1# 3.8# 35.2# 8.8# 692 24.0 190 1104A Unit 4SOFA +SNCR830© 0.155& 1,299& 41.2# 99.1# 3.8# 35.2# 8.8# 692 24.0 190 1104-7Table 4-5: Colstrip Unit Cases, English UnitsCaseIDCaseDescriptionSO2(lb/hr)NOx(lb/MMBtu)NOx(lb/hr)Particulate Matter (lb/hr)Stack Parameters§Filterable Condensable Height(ft)InnerDiameter(ft)Temp(F)ExitVelocity(ft/s)CoarseSoilFineSoilElementalCarbonInorganic(SOx)Organic4B Unit 4SOFA +SCR830© 0.084¶ 754¶ 41.2# 99.1# 3.8# 35.2# 8.8# 692 24.0 190 110§ From August 2007 BART Report, Tables 2-1 & 2-2@ Data are based on maximum 24-hour average data from U.S. EPA Clean Air Markets, 2001 - 2003. Substitute data are not included.∆Data are based on maximum 24-hour average heat input data from U.S. EPA Clean Air Markets, 2001 - 2003 and emissions factors from the April 2011 testof Unit 1. Speciation per NPS guidance and coal data from PPL.! Data are based on maximum 24-hour average heat input data from U.S. EPA Clean Air Markets, 2008 - 2011 and emissions factorsfrom the April 2011 test ofUnit 1. Speciation per NPS guidance and coal data from PPL.* Data are based on maximum 24-hour averagedata from U.S. EPA Clean Air Markets, 2008 - 2011. Substitute data are not included.^ Data are based on maximum 24-hour average heat input data from U.S. EPA Clean Air Markets, 2008 - 2011, and an emissions factor based on the expectedreduction from the average of NOxemission reported for Units 1and 2 from 2006 through 2010 inEPA Clean Air Markets.& Data are based on 10% reduction relative to the SOFA case.‡ Percent SO2control is relative to uncontrolled operation.† Data are based on maximum 24-hour average heat input data from U.S. EPA Clean Air Markets, 2008 - 2011 and emissions factorsfrom the April 2011 testof Unit 1. Speciation per NPS guidance and coal data from PPL.© Data are based on maximum 24-hour average data from U.S. EPA Clean Air Markets. Only CAM data after 1/1/08 and 1/19/10 for Units 3 and 4,respectively were used.# Based on maximum 24-hour average heat input data from U.S. EPA Clean Air Markets and emissions factors from the June 2010 test of Unit 3. The SOFAinstallation dates are 1/1/08 and 1/19/10 for Units 3 and 4, respectively. Only CAM data after these dates were used. Speciation per NPS guidance.$ Data are based on maximum 24-hour average heat input data from U.S. EPA Clean Air Markets, 2001 - 2003 and emissions factorsfrom the April 2010 testof Unit 3. Speciation per NPS guidance and coal data from PPL.¶ Data are based on maximum 24-hour average heat input data fromU.S. EPA Clean Air Markets, 2008 - 2011, and an emissions factor based on the expectedreduction from the average of NOxemission reported for Units 3and 4 from 2006 through 2010 inEPA Clean Air Markets.4-8Table 4-6: Colstrip Unit Cases, Metric UnitsCaseIDCaseDescriptionSO2(g/s)NOx(g/s)Particulate Matter (g/s)Stack Parameters§Filterable Condensable Height(m)InnerDiameter(m)Temp(K)ExitVelocity(m/s)CoarseSoilFineSoilElementalCarbonInorganic(SOx)Organic1X Unit 1BaselineCase354@ 248@ 1.59∆3.83∆0.15∆8.66∆2.16∆152 5.03 366 29.71R Unit 1ReferenceCase(DigitalControls)334* 209* 1.52! 3.67! 0.14! 8.29! 2.07! 152 5.03 366 29.71A Unit 1SOFA334* 129^ 1.52! 3.67! 0.14! 8.29! 2.07! 152 5.03 366 29.71B Unit 1 88%SO2Control184‡ 209* 1.52! 3.67! 0.14! 8.29! 2.07! 152 5.03 366 29.71C Unit 1SOFA w/88% SO2Control184‡ 129^ 1.52! 3.67! 0.14! 8.29! 2.07! 152 5.03 366 29.71D Unit 1SOFA +SCR334* 41^ 1.52! 3.67! 0.14! 8.29! 2.07! 152 5.03 366 29.71E Unit 1PM10=0.015lb/MMBtu334* 209* 0.705† 1.697† 0.065† 3.838† 0.96† 152 5.03 366 29.72X Unit 2BaselineCase367@ 268@ 1.55∆3.72∆0.14∆8.42∆2.10∆152 5.03 367 28.42R Unit 2ReferenceCase(DigitalControls)309* 215* 1.58! 3.81! 0.15! 8.61! 2.15! 152 5.03 367 28.42A Unit 2SOFA309* 134^ 1.58! 3.81! 0.15! 8.61! 2.15! 152 5.03 367 28.44-9Table 4-6: Colstrip Unit Cases, Metric UnitsCaseIDCaseDescriptionSO2(g/s)NOx(g/s)Particulate Matter (g/s)Stack Parameters§Filterable Condensable Height(m)InnerDiameter(m)Temp(K)ExitVelocity(m/s)CoarseSoilFineSoilElementalCarbonInorganic(SOx)Organic2B Unit 2 88%SO2Control191‡ 215* 1.58! 3.81! 0.15! 8.61! 2.15! 152 5.03 367 28.42C Unit 2SOFA w/88% SO2Control191‡ 134^ 1.58! 3.81! 0.15! 8.61! 2.15! 152 5.03 367 28.42D Unit 2SOFA +SCR309* 42^ 1.58! 3.81! 0.15! 8.61! 2.15! 152 5.03 367 28.42E Unit 2 PM10= 0.015lb/MMBtu309* 215* 0.732† 1.762† 0.068† 3.985† 1.00† 152 5.03 367 28.43X Unit 3BaselineCase122@ 508@ 5.07$ 12.21$ 0.469$ 4.33$ 1.084$ 211 7.32 361 33.53R Unit 3ReferenceCase(SOFA)103© 189© 5.02# 12.08# 0.464# 4.29# 1.072# 211 7.32 361 33.53A Unit 3SOFA +SNCR103© 170& 5.02# 12.08# 0.464# 4.29# 1.072# 211 7.32 361 33.53B Unit 3SOFA +SCR103© 92¶ 5.02# 12.08# 0.464# 4.29# 1.072# 211 7.32 361 33.54X Unit 4BaselineCase115@ 514@ 5.47$ 13.16$ 0.506$ 4.67$ 1.168$ 211 7.32 361 33.54R Unit 4ReferenceCase(SOFA)105© 182© 5.19# 12.49# 0.480# 4.44# 1.109# 211 7.32 361 33.54A Unit 4SOFA +SNCR105© 164& 5.19# 12.49# 0.480# 4.44# 1.109# 211 7.32 361 33.54-10Table 4-6: Colstrip Unit Cases, Metric UnitsCaseIDCaseDescriptionSO2(g/s)NOx(g/s)Particulate Matter (g/s)Stack Parameters§Filterable Condensable Height(m)InnerDiameter(m)Temp(K)ExitVelocity(m/s)CoarseSoilFineSoilElementalCarbonInorganic(SOx)Organic4B Unit 4SOFA +SCR105© 95¶ 5.19# 12.49# 0.480# 4.44# 1.109# 211 7.32 361 33.5§ From August 2007 BART Report, Tables 2-1 & 2-2@ Data are based on maximum 24-hour average data from U.S. EPA Clean Air Markets, 2001 - 2003. Substitute data are not included.∆Data are based on maximum 24-hour average heat input data from U.S. EPA Clean Air Markets, 2001 - 2003 and emissions factors from the April 2011 testof Unit 1. Speciation per NPS guidance and coal data from PPL.! Data are based on maximum 24-hour average heat input data from U.S. EPA Clean Air Markets, 2008 - 2011 and emissions factorsfrom the April 2011 test ofUnit 1. Speciation per NPS guidance and coal data from PPL.* Data are based on maximum 24-hour averagedata from U.S. EPA Clean Air Markets, 2008 - 2011. Substitute data are not included.^ Data are based on maximum 24-hour average heat input data from U.S. EPA Clean Air Markets, 2008 - 2011, and an emissions factor based on the expectedreduction from the average of NOxemission reported for Units 1and 2 from 2006 through 2010 inEPA Clean Air Markets.& Data are based on 10% reduction relative to the SOFA case.‡ Percent SO2control is relative to uncontrolled operation.† Data are based on maximum 24-hour average heat input data from U.S. EPA Clean Air Markets, 2008 - 2011 and emissions factorsfrom the April 2011 testof Unit 1. Speciation per NPS guidance and coal data from PPL.© Data are based on maximum 24-hour average data from U.S. EPA Clean Air Markets. Only CAM data after 1/1/08 and 1/19/10 for Units 3 and 4,respectively were used.# Based on maximum 24-hour average heat input data from U.S. EPA Clean Air Markets and emissions factors from the June 2010 test of Unit 3. The SOFAinstallation dates are 1/1/08 and 1/19/10 for Units 3 and 4, respectively. Only CAM data after these dates were used. Speciation per NPS guidance.$ Data are based on maximum 24-hour average heat input data from U.S. EPA Clean Air Markets, 2001 - 2003 and emissions factorsfrom the April 2010 testof Unit 3. Speciation per NPS guidance and coal data from PPL.¶ Data are based on maximum 24-hour average heat input data fromU.S. EPA Clean Air Markets, 2008 - 2011, and an emissions factor based on the expectedreduction from the average of NOxemission reported for Units 3and 4 from 2006 through 2010 inEPA Clean Air Markets.

### 4-11 Table 4-7: Colstrip - Modeling Scenarios

Scenario ID Scenario Description Unit Case IDs Meteorology

1.0 Units 1 & 2 combined with a baseline of 2001 ( 2001 emissions and met data 2001-2003) 1X 2X 2001 - 2003

1.1 Units 1 & 2 combined refere nce case 2008 (using 2008- 2011 emissions and met data 2001-2003) 1R 2R 2001 - 2003

1.2 SOFA 1 & 2 with the 2008-201 1 reference case emissions held constant 1A 2A 2001 - 2003

1.3 Lime addition 88% control with reference case emissions held constant 1B 2B 2001 - 2003

1.4 Units 1 & 2 Lime addition 88% and SOFA with reference case emissions held constant 1C 2C 2001 - 2003

1.5 SCR on top of SOFA with reference case emissions held constant 1D 2D 2001 - 2003

1.6 New PM controls to 0.015 lb/mmBtu control level and reference case emissions 1E 2E 2001 - 2003

2.0 Units 3 & 4 combined baseline of 2001 (2001 emissions and met data 2001-2003) 3X 4X 2001 - 2003

2.1 Units 3 & 4 combined refere nce case 2008 (using 2008- 2011 emissions data and met 2001-2003) Units 3&4 data reflect reduction in NO x and PM from operation of SOFA 3R 4R 2001 - 2003

2.2 Units 3 & 4 with SCNR and reference case emissions 3A 4A 2001 - 2003 2.3 Units 3 & 4 with SCR and reference case emissions 3B 4B 2001 - 2003

### 5-1 5.0 CALPUFF MODELING SYSTEM OVERVIEW To determine the long range transport of pol lutants emitted from a source, the U.S. EPA Guideline on Air Quality Models (Revised) (U.S. EPA, 2005) 6 

### , the IWAQM Phase 2 Report (U.S. EPA, 1998) 7 

### and the FLAG Phase I Report – Revised (2010) (FLAG, 2010) 8 

### recommend the CALPUFF dispersion modeling system. CALPUFF is a multi-layer, multi-species, non-steady-state, puff dispersion model. It can simulate the effects of time- and space-varying meteorological conditions on pollutant transport, transformation, and removal. It also 

### contains algorithms for near-source effects, such as building downwash, transitional plume rise, partial plume pene tration, sub-grid scale terrain interactions, and longer range effects, such as pollutant removal (wet scavenging and dry deposition), chemical transformation, vertical wind shear, and overwater transport. Running CALPUFF requires extensive preparation of data for input to the preprocessing programs of the 

### modeling system. The following steps are c onsidered necessary to determine the potential impacts in the Class I ar eas due to the proposed project:



###  Determine an appropriate modeling domain, which encompasses the Project site and the Class I areas with sufficient buffer for recirculation effects;

 Obtain three years of the appropriate Mesoscale Model (MM5) datasets, hourly surface meteorological data, hourly precipita tion data, and twice-daily sounding data;

 Process the meteorological da ta for input to the CALPU FF preprocessing programs;

 Develop an appropriate land use classifi cation for each grid cell of the modeling domain;

 Develop the terrain profile for the modeling domain;

 Locate receptors within the Class I area;

 Execute all the preprocessing programs of the CALPUFF dispersion modeling system, including CALMET (as discussed further below); and

 Execute the post-processing programs of the CALPUFF dispersion modeling system, namely CALPOST, for each of the desired pollutants, analyses (i.e., concentration, visibility, and deposition) and Class I areas as appropriate.
The steps presented above for BART visibility modeling 

### are based on the guidance provided by the FLAG Phase I Report – Revised (2010) (FLAG, 2010) and IWAQM Phase 2 Report (U.S. EPA, 1998) for a refined Class I analysis. The CALPUFF dispersion 

### modeling system consists of three main programs: CALMET, CALPUFF, and CALPOST. CALMET is used to process the land use, terrain, and meteorological data for use in the CALPUFF program. CALPUFF uses th e output from CALMET, along with the source data (i.e., exhaust characteristics and emission rates) to calculate hourly concentration and deposition values

6 http://www.epa.gov/scram001 /guidance/guide/appw_05.pdf
7 http://www.epa.gov/scram001 /7thconf/calpuff/phase2.pdf
8 http://www.nature.nps.gov/air /pubs/pdf/flag/FLAG_2010.pdf

### 5-2 for each receptor. CALPOST uses the hourly output from CALPUFF and calculates the pollutant-specific and averaging period-specific concentration, change in light extinction, and deposition rates. In addition to these main programs, the CALPUFF dispersion modeling system requires the use of many other preprocessing programs. The following sections pr esent the model inputs and how each was developed for input to the programs of the CALPUFF dispersion modeling system. It is noted that the CALPOST program was updated to include the latest methods recommended by the Interagency Monitoring of Protected Visual Environments (IMPROVE) Steering Committee (IMPROVE 2005) 9 

### on calculating light extinction. It differs from the previous algorithm used in the previous guidance for regional haze analyses in six areas:



### 1. Extinction efficiencies of sulfates, nitrates , and organics vary with concentration, as there are distinct efficiencies for "small" and "large" particles and the ratio of smallto-large particle fraction decr eases as the concentration increases. Furthermore, the extinction efficiency for sulfates no longer equals th at for nitrates. 2. A separate hygroscopic humidity enhancemen t factor curve is prescribed for "small" and "large" particles, fS(RH) and fL(RH) . These curves apply to sulfates and nitrates. 3. Light extinction due to scat tering by sea salt (with its own hygroscopic humidity enhancement factor fSS(RH)) is included (not expected to be a si gnificant particulate component in Montana). 4. Light absorption by nitrogen dioxide (NO 2 

### ) gas is included in the extinction. 5. Background particulate organic matter c oncentration is taken to be 1.8 times measured organic carbon concentrations, instead of 1.4. 6. Rayleigh scattering extinction varies with site elevati on and mean temperature.
The new IMPROVE algorithm was developed in an effort to mitigate some of the technical criticism of the original equation. The FLAG, 2010 guidance recognizes the many enhancements of the IMPROVE group and recommends the use of Method 8, sub-mode 5 as the default method to calculate regional haze impacts. The new guidance has been coded in CALPOST (Version 6.221) and is available
as a Beta version of the model that has been review ed and accepted by the FLMs. This method was used for all visibility modeling analyses. The model was run in its regulatory default m ode, in accordance with the approved modeling protocol and the “EPA Model Clearinghouse Memorandum Clar ification On EPA-FLM Recommended Settings For CALMET” , of August 31 ST 

### , 2009 and “Federal Land Managers’ Air Quality Related Values Work Group (FLAG) Phase I Report—Revised (2010)” of October, 2010.
These documents are available at: ( http://www.epa.gov/ttn/scram/CALMET%20CLARIFICATION.pdf ) and ( http://www.nature.nps.gov/air/pubs/pdf/flag/FLAG_2010.pdf ) respectively.

9 http://vista.cira.colostate.edu/IMP ROVE/Publications/GrayLit/019_Revis edIMPROVEeq/RevisedIMPROVEAlgorith m3.doc

### 6-1 6.0 GEOPHYSICAL AND METEOROLOGICAL DATA
6.1 Modeling Domain The CALMET computational domain was designe d to cover an area of 780 km by 570 km (Figure 6-1). It includes Colstrip, all Class I areas within 300 km from it. and extends beyond the Class I areas by at least 50 km as recomm ended by the IWAQM Phase 2 Report (U.S. EPA, 1998). These Class I areas are: North Absaro ka WA, Theodore Roosevelt NP, UL Bend WA,
Washakie WA and Yellowstone NP.
Consistent with the “EPA Model Clearinghouse Memo randum Clarification On EPAFLM Recommended Settings For CALMET” , of August 31, 2009, a horizontal grid resolution of 4 km was used to represent the variations of the terrain elevations and land use within the
domain. Also consistent with th at guidance, the modeli ng domain has 10 vertical layers, with the top of the layers defined as (in meters): 0, 20, 40, 80, 160, 320, 640, 1200, 2000, 3000, and
4000. The resulting domain is capture d by the 196 x 143 gr id cells, a workable number of cells. The CALPUFF computational domain is the same as the CALMET domain. The domain extends beyond the Class I areas in order to provide an adequa te buffer zone at the boundaries, and to allow the effects of flow curvature and possibl e small-scale recircula tion to be evaluated. Lambert conformal coordinates (based on a Lambert Conformal Coni c Projection) were used to define the modeling domain. The projection origin of the modeling domain is 44.25 degrees North Latitude and 109.5 degrees West Long itude with two standard parallels set to 45.0 degrees and 49.0 degrees North Latitude. A False Easting of 600 kilometers at the projection origin was used. The datum is set to WGS-84.

6.2 Terrain Gridded terrain elevations for the modeling domain are derived from 3-sec Shuttle Radar Topo Mission files, or SRTM3 di gital elevation files, produced by the United States Geological Survey (USGS). Data are provided in files covering 3 arc seconds by 3 arc seconds of latitude and longitude. SRTM3 DEM data elevations are in meters relative to mean sea level, and the spacing of the elevations along each pr ofile is 3 arc-seconds, which corresponds to a spacing of approximately 90 meters. Figure 6-1 shows contours of the terrain aver aged to 2 km. The USGS elevation records located within each grid cell in the computa tional domain were averaged to produce a mean

### 6-2 elevation at each grid point. This figure also shows locations of Colstr ip and a circle with 300- km radius around the facility. North Absaroka , Theodore Roosevelt, UL Bend, Washakie and
Yellowstone Class I areas are with in the 300 km from the Colstrip.

6.3 Land Use A standard USGS dataset was used to assign a land use classification for each grid cell: the 30-m resolution U.S. Geological Survey (U SGS) 1992 National Land Cover Data (NLCD).
This dataset was downloaded from the USGS website in GeoTIFF format. A total of 6 files, covering the states of Idaho, Montana, Nebr aska, North Dakota, Sout h Dakota, and Wyoming
were used. These files were then processed using the CTGPROC preprocessing program that is part of the CALPUFF version 5.8 dispersion modeling system.
The land use classifications and associated geophysical pa rameters such as albedo, surface roughness, etc. are assigned to each gr id cell using the MAKEGEO program, which is also a part of the CALPUFF version 5.8 disper sion modeling system. The final output from
MAKEGEO is the GEO.DAT file Figure 6-2 shows the dominant land us e categories used in the modeling.

6.4 Meteorological Data Base The CALMET model requires meteorological in formation from the surface and upper air as well as geophysical informati on about the land use and terrai n heights. Specifically, CALMET requires surface observations of wind speed, wind direction, temperature, cloud cover, ceiling height, surface pressure, relativ e humidity, and precipitation type (e.g., snow, rain, etc.). These variables are routinely measured at the Nationa l Weather Service (NWS) surface stations. The upper air data include twice-daily observations of vertical profiles of wind speed, wind direction, temperature, and pressure. Three-dimensional gridded data from the prognostic numerical model MM5 provided by
WRAP were also included with a resolu tion of 36-km for 2001 through 2003. Hourly precipitation data, which are required for wet de position calculations in CALPUFF, were derived
from the MM5 data. The NWS collects twice-daily upper air data ver tical profiles of the atmosphere taken at 00 Greenwich Mean Time (GMT) and 12 GMT at each station. Seven stations are available within the modeling domain, or in close proximity. These stat ions are Aberdeen, SD; Bismark,

### 6-3 ND; Boise, ID; Glasgow, MT; Riverton, WY; Great Falls, MT; and Rapid City, SD (6-4). The upper air data were acquired from the Natio nal Oceanic and Atmospheric Administration (”NOAA”) (http://raob.fsl.noaa.gov/) and pr ocessed using the READ62 program. A total of 60 surface meteorological stations for the year 2001, and 57 stations for the years 2002 and 2003 were used in the refined runs (Figure 6-3 an d 6-5). The hourly surface meteorological data was obtained from the National Climatic Data Center (NCDC) in Integrated Surface Hourly (ISH) format, and were processe d by the SMERGE program for the creation of
the SURF.DAT file A total of 94 precipitation sta tions were used for all three y ears of the analyses. Hourly precipitation data for the precipitation stations included in the modeling analyses, were obtained
in TD-3240 format from the NCDC. This data was processed using two programs from the CALPUFF dispersion modeling syst em: PXTRACT and PMERGE.

### 6-4 Figure 6-1. Terrain Contours

Figure 6-1. Terrain contours (m MSL) at 2 km resolution for the 780 km by 570 km CALMET and CALPUFF computationa l domains. The Class I areas and the Colstrip facility are also shown. 350 400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100 LCCx (km), WGS-84 -100 -50

0 50 100 150 200 250 300 350 400 450LCCy (km),WGS-84

Yellowstone

Washakie UL Bend Theodore Roosevelt - N

Theodore Roosevelt - C

Theodore Roosevelt - S

Teton Red Rock Lakes North Absaroka Gates of the Mountains

Colstrip

Map projection: LCC, WGS-84 Feast = 600 km, Fnorth = 0 km LATo = 44.25N, LANo = 109.5W LAT1 = 45 N, LAT2 = 49 N ID MT ND

SD

WY

PPL, Montana Terrain (meters)

-1 100 300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500 2700 2900 3100 3300 3500 3700 3900 4500 300 km circle around facility

### 6-5 Figure 6-2. Dominant Land Use Categories

Figure 6-2. Dominant land use categories at 2 km resolution on the CALMET and CALPUFF modeling domains. Class I areas and the lo cation of Colstrip PPL are also shown. 350 400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100 LCCx (km), WGS-84 -100 -50

0 50 100 150 200 250 300 350 400 450LCCy (km), WGS-84

Yellowstone

Washakie UL Bend Theodore Roosevelt - N

Theodore Roosevelt - C

Theodore Roosevelt - S

Teton Red Rock Lakes North Absaroka Gates of the Mountains

Colstrip

Map projection: LCC, WGS-84 Feast = 600 km, Fnorth = 0 km LATo = 44.25N, LANo = 109.5W LAT1 = 45 N, LAT2 = 49 N ID MT ND

SD

WY

PPL, Montana 300 km circle around facility

10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 Snow/Ice

Tundra

Barren

Wetland

Water

Forest

Range

Agriculture

Urban/Built-Up

### 6-6 Figure 6-3. Surface Stations

Figure 6-3. Surface stations. The stations incl uded in the SURF.DAT files are plotted in purple 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 LCCx (km), WGS-84 -200 -150 -100 -50

0 50 100 150 200 250 300 350 400 450 500 550 600LCCy (km), WGS-84

Yellowstone

Washakie UL Bend Theodore Roosevelt - N

Theodore Roosevelt - C

Theodore Roosevelt - S

Teton Red Rock Lakes North Absaroka Gates of the Mountains

KPIH KIDA KSUN

KBYI KSMN KGDV

KBIL KLWT

KBHK

KBTM

KDLN KBZN KLVM KGGW

KJDN KOLF

KSDY

KHLN KMSO KGTF KHVR KFCA KCTB

KMLS

KHEI KDIK KISN KMIB KMOT

KN60 CYEN

KCUT KPHP

KIEN

KD07

KRAP KRCA

KDGW KCPR KLND

KRIW KJAC KGCC KBYG KSHR

P60

KWRL KGEY KCOD TH28

SP26

PE25

SA32 GL27

MO39 GA38 BA37 K2WX

KBPI KRXE MIN2

LAN3 SHE4

BIL5 LEW6

MIL7

CAS8 RAP9 GR11

HE12 KA13

MI14

PO15 GL17 WI18

BO19 BU20

CU21

DI22 HA23

LI24 PE25

SP26 GL27

TH28

YE29

RE31 SA32 DI33

RI34 ES35

BA37 GA38 MO39 Colstrip

Map projection: LCC, WGS-84 Feast = 600 km, Fnorth = 0 km LATo = 44.25N, LANo = 109.5W LAT1 = 45 N, LAT2 = 49 N

MM5 grid points
Surface met stations Facility BC AL SA

ID MT ND

SD

WY PPL, Montana

MODELING DOMAIN 300 km circles around facility

### 6-7 Table 6-3. Meteorological Data Sources and Parameters Available

Type of Dataset Frequency Source Parameters

Surface observations Hourly NWS Wind speed, wind direction, temperature, ceiling height, cloud cover, relative humidity, surface pressure, precipitation type

Precipitation Observations Hourly NWS Precipitation

Modeled Profiles MM5 for 2001, 2002 and 2003 Hourly WRAP Hourly, gridded fields of winds, temperature, pressure, and humidity and liquid water content on 36 km grid for 2003, 2004 and 2005.



### Table 6-4. NWS Upper Air Stations City Code ID X Cord. (km) Y Cord. (km) Time Zone

Aberdeen, SD ABR 14929 1463.662 194.558 6 

### Bismark, ND BIS 24011 1266.552 317.294 6 

### Boise, ID BOI 24131 57.175 -52.317 6 

### Glasgow, MT GGW 94008 813.956 442.858 7 

### Riverton, WY RIW 24061 684.046 -131.806 7 

### Great Falls, MT TFX 4102 458.315 357.276 7 

### Rapid City, SD UNR 94043 1103.706 0.223 7

### 6-8 Table 6-5. NWS Hourly Surface Stations

WMO WBAN Station Name State Latitude (deg.) Longitude (deg.) CALL ID LCCX 1 (km) LCCY 1 (km)
Colstrip region MT 46.90 -103.40 TH28 824.377 178.618 Border of WY & MT close to KSHR MT 45.10 -106.90 SP26 805.708 99.912 Colstrip region MT 45.80 -106.60 PE25 269.113 482.966 Border of ID & MT close to KSMN ID 45.10 -113.50 SA32 1064.318 312.121 Glacier WA area MT 48.50 -114.00 GL27 283.839 99.808 Colstrip region 2 MT 45.70 -106.50 MO39 828.340 159.976 Colstrip region 2 MT 45.60 -106.50 GA38 836.341 154.721 Colstrip region 2 MT 45.70 -106.60 BA37 831.370 162.314 718620 99999 ESTEVAN AIRPORT SA 49.22 -102.97 CYEN 1075.221 572.157 725686 99999 DOUGLAS WY 42.80 -105.38 KDGW 937. 563 -152.417 725690 24089 CASPER NATRONA CO INTL A WY 42.90 -106.47 KCPR 847.878 -145.371 725760 24021 LANDER HUNT FIELD WY 42.82 -108.73 KLND 663.094 -158.761 725765 99999 RIVERTON MUNICIPL AP WY 43.05 -108.45 KRIW 685.694 -132.898 725776 99999 JACKSON HOLE (AWOS) WY 43.60 -110.73 KJAC 500.578 -71.501 725780 24156 POCATELLO REGIONAL AP ID 42.92 -112.57 KPIH 348.939 -143.020 725785 24145 IDAHO FALLS FANNING FIEL ID 43.52 -112.07 KIDA 392.002 -77.767 725865 99999 HAILEY/FRIEDMAN MEM ID 43.50 -114.30 KSUN 211.558 -71.499 725867 24133 BURLEY MUNICIPAL ARPT ID 42.53 -113.77 KBYI 248.522 -181.773 726514 99999 CUSTER (RAMOS) SD 43.73 -103.62 KCUT 1073.773 -40.031 726516 99999 PHILIP ARPT SD 44.05 -101.60 KPHP 1232.468 9.686 726517 99999 PINE RIDGE SD 43.03 -102.52 KIEN 1169.119 -110.323 726539 99999 FAITH SD 45.03 -102.02 KD07 1188.561 114.823 726620 24090 RAPID CITY REGIONAL ARPT SD 44.05 -103.05 KRAP 1116.674 -0.951 726625 99999 ELLSWORTH AFB SD 44.15 -103.10 KRCA 1111.770 9.802 726627 99999 BUFFALO (AMOS) SD 45.57 -103.52 K2WX 1066.215 164.509 726650 99999 GILLETTE (AMOS) WY 44.35 -105.53 KGCC 916.548 19.141 726654 99999 JOHNSON CO ARPT WY 44.38 -106.72 KB YG 821.593 18.385 726660 24029 SHERIDAN COUNTY ARPT WY 44.77 -106.97 KSHR 800.273 61.038 726664 94173 YWLLOESTONE LAKE RAMOS WY 44.55 -110.42 P60 526.875 33.779 726665 24062 WORLAND MUNICIPAL WY 43.97 -107.95 KWRL 724.471 -29.901 726667 99999 SOUTH BIG HORN CO WY 44.52 -108.08 KGEY 712.923 31.039 726676 99999 GLENDIVE(AWOS) MT 47.13 -104.80 KGDV 956.165 330.710 726700 99999 CODY MUNI (AWOS) WY 44.52 -109.02 KC OD 638.174 30.132 726710 99999 BIG PINEY (AMOS) WY 42.57 -110.10 KBPI 550.622 -186.713 726770 24033 BILLINGS LOGAN INT'L ARP MT 45.80 -108.55 KBIL 673.824 172.705 726776 24036 LEWISTOWN MUNICIPAL ARPT MT 47.05 -109.45 KLWT 603.797 311.134 726777 99999 BAKER MUNI ARPT MT 46.33 -104.25 KBHK 1003.738 244.677 726785 24135 BUTTE BERT MOONEY ARPT MT 45.95 -112.50 KB TM 367.559 193.375 726796 99999 DILLON AIRPORT MT 45.25 -112.55 KDLN 360.659 115.807 726797 24132 BOZEMAN GALLATIN FIELD MT 45.80 -111.15 KBZN 471.785 173.608 726798 24150 LIVINGSTON MISSION FIELD MT 45.70 -110.45 KLVM 526.041 161.596 726818 99999 REXBURG ID 43.83 -111.80 KRXE 414.859 -43.982 726865 99999 SALMON/LEMHI (AWOS) ID 45.12 -113.88 KSMN 255.576 106.332 727584 99999 HETTINGER ND 46.02 -102.65 KHEI 1129.513 219.869 727645 24012 DICKINSON MUNICIPAL AP ND 46.80 -102.80 KDIK 1110.543 305.206 727670 94014 WILLISTON SLOULIN INTL A ND 48.20 -103.65 KISN 1034.294 455.151 727675 99999 MINOT AFB ND 48.42 -101.35 KMIB 1201.973 494.726 727676 24013 MINOT FAA AP ND 48.27 -101.28 KMOT 1208.871 478.684 727677 99999 GARRISON (AMOS) ND 47.65 -101.43 KN60 1204.887 408.989 727680 94008 GLASGOW INTL ARPT MT 48.22 -106.62 KGGW 813.875 445.081 727684 99999 JORDAN (RAMOS) MT 47. 33 -106.93 KJDN 794.107 345.428 727686 99999 WOLF POINT INTL MT 48.10 -105.58 KOLF 891.719 435.111 727687 99999 SIDNEY-RICHLAND MT 47.70 -104.20 KSDY 997.286 396.803 727720 24144 HELENA REGIONAL AIRPORT MT 46.60 -111.97 KHLN 410.886 264.119 727730 24153 MISSOULA INTERNATIONAL A MT 46.92 -114.10 KMSO 250.034 306.969 727750 24143 GREAT FALLS INTL ARPT MT 47.47 -111.38 KGTF 458.369 359.499 727770 94012 HAVRE CITY-COUNTY AP MT 48.55 -109.77 KHVR 580.071 477.866 727790 24146 KALISPELL GLACIER PKINT MT 48.32 -114.25 KFCA 248.065 462.938 727796 24137 CUT BANK MUNI AP MT 48.60 -112.37 KCTB 388.414 487.267 742300 24037 MILES CITY MUNICIPAL ARP MT 46.43 -105.88 KMLS 877.984 248.676

1 The Lambert Conformal Conic (LCC) projection is based on st andard parallels of 45.0 N and 49.0 N, an origin latitude and longitude of 44.25 N and 109.5 W, fa lse easting is 600 km, and datum WGS-84. 2 Available for year 2001 only

### 6-9 Table 6-6. NWS Precipitation Stations
Station # Code LCCX 1 

### (km) LCCY 1 

### (km)

1 102707 384.179 3.054 2 104456 414.496

‐ 97.83 3 104598 450.949 20.568 4 109065 457.016

‐ 42.187 5 240019 608.743 144.598 6 240165 1000.85 98.169 7 240330 851.652 154.443 8 240364 381.95 364.385 9 240807 674.436 173.49 10 241008 398.496 223.504 11 241047 471.102 159.731 12 241102 646.324 119.765 13 241127 919.923 140.95 14 241309 363.69 187.631 15 241318 367.545 195.043 16 241500 409.693 182.013 17 241737 398.556 400.264 18 241875 818.853 315.938 19 241984 745.578 415.841 20 241995 562.873 85.142 21 242414 355.318 100.002 22 242584 444.483 401.422 23 242689 984.011 194.513 24 243176 830.225 422.568 25 243489 355.513 377.545 26 243581 962.534 328.424 27 243751 458.225 359.835 28 243753 457.965 358.396 29 244038 454.666 70.289 30 244143 610.515 333.696 31 244241 409.064 307.639 32 244442 960.363 260.842 33 244820 416.337 41.508 34 244904 642.972 227.183 35 244983 604.404 311.356 36 245030 354.764 48.082 37 245040 359.981 305.525 38 245086 526.738 161.364 39 245106 767.83 120.773 40 245122 448.108 184.266 41 245387 535.71 250.371 42 245690 877.768 248.331 43 245706 458.006 309.604 44 245791 641.199 170.619 45 246008 503.089 310.922 46 246946 596.886 161.814 47 247258 483.489 424.972 48 247610 383.28 164.443 49 248101 349.712 440.303 50 248169 903.889 321.125 51 248329 462.783 235.703 52 248511 798.078 245.511 53 248866 473.254 47.536 54 248927 492.377 255.769 55 249044 686.942 306.878 56 249052 699.148 299.624 57 249240 722.38 119.254 58 249900 672.688 408.034 59 320995 1069.91 233.549 60 322183 1110.78 305.115 61 322188 1108.84 315.208 62 322365 1116.27 366.482 63 324180 1129.9 218.118 64 328812 1022.96 352.255

### 6-10 Station # Code LCCX 1 

### (km) LCCY 1 

### (km)

65 391114 1064.05 167.24 66 391294 1031.04 159.581 67 392557 1059.01

‐ 88.635 68 392565 1050.72

‐ 53.541 69 396304 1104.96

‐ 74.095 70 396427 1082.03

‐ 2.375 71 396937 1116.41

‐ 1.753 72 397882 1047.24 45.423 73 399347 1087.2

‐ 57.859 74 399537 1111.61 112.063 75 481000 708.358

‐ 93.048 76 481165 821.651 14.493 77 482715 589.641

‐ 79.28 78 482725 967.911

‐ 82.53 79 484910 498.026

‐ 84.364 80 485345 528.722 35.425 81 485371 994.597

‐ 22.508 82 486395 965.28 6.992 83 486440 512.452 43.09 84 486603 1027.28

‐ 81.928 85 486660 1025.02

‐ 29.239 86 486935 1007.7

‐ 17.014 87 487388 658.66 58.747 88 487545 898.839 61.78 89 488626 806.921 39.792 90 488852 769.79

‐ 18.384 91 488858 771.919

‐ 46.47 92 488875 704.667

‐ 66.076 93 488888 664.779

‐ 59.38 94 489770 722.855

‐ 25.372

### 7-1 7.0 AIR QUALITY MODELING METHODOLOGY
7.1 Model Selection
The CALPUFF modeling system (Scire et al ., 2000a,b) was used to predict visibility impacts at UL Bend, North Absaroka, Theodore R oosevelt, Washakie and Yellowstone Class I areas. The EPA-approved version of CALPUFF modeling system, Version 5.8 was used in the modeling.

7.2 Meteorological Modeling Options The CALMET model was run in its regulatory default mode, in accordance with the “EPA Model Clearinghouse Memorandum Clarificati on On EPA-FLM Recommended Settings For
CALMET” , of August 31 ST 

### , 2009 10 

### ; and “Federal Land Managers’ Air Quality Related Values Work Group (FLAG) Phase I Report—Revised (2010)” of October, 2010 11



### . Initial Guess Field 

### The MM5 gridded meteorological data were us ed to define the initial guess field for the
CALMET simulations. MM5 data were available for years 2001-2003 with a horizontal grid spacing of 36 km and 34 vertical levels. Step 1 Field: Terrain Effects 

### In developing the Step 1 wind field, CALMET adjusts the initial guess field to reflect kinematic effects of the terrain, slope flows and blocking effects. Slope flows are a function of the local slope and altitude of the nearest crest. The crest is define d as the highest peak within a radius TERRAD around each grid point. Fo r the domain used to perf orm the modeling, a value of
TERRAD of 15 km was used. This value has been recommended by MDEQ in the Montana Protocol and is considered appropriate for this modeling domain. The Step 1 field produces a flow
field consistent with the fine-scale CALMET terrain resolution (2 km). Step 2 Field: Objective Analysis 

### In Step 2, observations are incorporated into the Step 1 wind field to produce a final wind
field. Each observation site influenc es the final wind field within a radius of influence (parameters RMAX1 at the surface and RMAX2 aloft). Observati ons and Step 1 field ar e weighted by means of parameters R1 at the surface and R2 aloft: at a dist ance R1 from an observation site, the Step 1 wind

10 ( http://www.epa.gov/ttn/scram /CALMET%20CLARIFICATION.pdf
11 http://www.nature.nps.gov/air/pubs/pdf/flag/FLAG_2010.pdf

### 7-2 field and the surface observations are weighted equally. RMAX1 and RMAX2 were set to 100 km and 200 km, while R1 and R2 were set to 50 km and 100 km, respectively.

7.3 CALPUFF Computational Domain and Receptors The CALPUFF computational domain is the sa me as the CALMET computational domain. Receptor locations and terrain elevations within the Class I areas were obtained from the NPS website ( http://www2.nature.nps.gov/air/Maps/Receptors/index.htm ) for the this Class I Area analysis. Receptor locations and elevations were converted to the coordinate system of the modeling domain and input to the CALPUFF mode l to determine the maximum change in light extinction in each of the Class I areas as appropriat e. The distribution of the receptors within UL Bend, Theodore Roosevelt, Washakie, North Absaroka , and Yellowstone are shown in Figure 7-1.

7.4 Dispersion Modeling Options The CALMET, CALPUFF, and CALPOST progra ms of the CALPUFF dispersion modeling system require numerous inputs and the selection of different modeling options to develop the meteorological fields, calculate hourly concentrat ion and deposition values, and calculate averaging period and pollutant-specific conc entrations and deposition values, along with the change in light extinction due to a project. These model analyses for the BART protocol modeling were run in th e regulatory default mode, in accordance with the “EPA Model Clearinghouse Memorandum Clarification On EPAFLM Recommended Settings For CALMET” , of August 31ST, 2009 and “Federal Land Managers’ Air Quality Related Values Work Group (FLAG) Phase I Report—Revised (2010)” of October, 2010. If not addressed in the previously discusse d documents, default values provided by A User’s Guide for the CALMET Meteorological Model (V ersion 5) (Earth Tech, 2000a) and A User’s Guide for the CALPUFF Dispersion Model (Ver sion 5) (Earth Tech, 2000b) were used.
The CALPUFF simulations were conducte d using the following model options:

- Gaussian near-field distribution - Transitional plume rise - No building downwash - Pasquill-Gifford (PG) dispersion coeffi cients (rural areas) and McElroy-Pooler coefficients (urban areas) - Transition of σ y to time-dependent (Heffter) growth rates - Partial plume path adjustment for terrain - Wet deposition, dry deposition, and chemical transformation using the MESOPUFF II scheme.

### 7-3 - Regulatory option used
Two important computational parameters in CALPUFF are XMXLEN (maximum length of an emitted puff, in grid units) and XSAMLEN (maxim um travel distance of a puff, in grid units, during one time step). Both of these variables we re set to 1.0 in the CALPUFF simulations in order to allow the strong wind channeling effects to be accounted for in th e puff trajectory calculations. The first parameter ensures that the length of an emitted puff does not become so large so that it cannot respond to change s in the wind field on the scale of the meteorological grid. The model automatically increases the frequency of puff re leases to ensure the length of a single puff is not larger than the grid size. The second paramete r decreases the internal time step to ensure the travel distance during one time step does not exceed the grid size. The partial plume path adjustment option was used in CALPUFF for this analysis (MCTADJ=3). The CALMET wind field incorporates the effect of the terrain on the plume trajectories. The plume path coefficient is used to characterize the local effect on ground-level concentrations. The default plume path coefficients (PPC) used for this analysis are listed below:

Stability Class A B C D E F PPC 0.5 0.5 0.5 0.5 0.35 0.35



### Nine species were modeled with CALPUFF for this analysis: SO 2 

### , SO 4 

### , NO x 

### , NO 3 

### , HNO 3 

### , and four subcategories of PM 10 

### , (PMF, PMC, EC, and SOA). Of these nine species, seven are emitted by the Colstrip sources: SO 2 

### , SO 4 

### , NO x 

### and four subcategories of PM 10 

### . The chemical mechanism comput es transformation rates of SO 2 

### to SO 4 

### and NO x 

### to
NO 3 

### /HNO 3 

### . Hourly measured ozone concentrations are provided in an external OZONE.DAT file
for use with the chemical transformation module. Th e ozone concentrations are used as a surrogate for OH radical concentrations during the day when the gas phase free radical chemistry is active. To allow for flexibility, each of the four units were modeled individually and their source contributions were summed in postprocessing steps.

7.5 Air Quality Monitoring Data Ambient ozone monitoring data from the EPA AIRS and CASTNET networks were used to develop the hourly ozone monitoring data file (O ZONE.DAT). The ozone stations used in the modeling are plotted in Figure7-4. These statio ns and their locations are listed in 7-5. Monthly background ammonia concentrations we re calculated from hourly ammonia data
collected from 2001 to 2002 at a site near Be ulah, ND. The MDEQ believes these data are

### 7-4 representative of Montana b ackground ammonia concentrations and the EPA concurs. These ammonia background concentrations, shown in 4.3.2 of the Montana Protocol were used in the CALPUFF modeling.

7.6 Regional Haze Haze is a result of the suspension of small aerosols in the atmosphere, which individually are invisible, but collectively give the sky an opale scent appearance. Sources of aerosols are natural (e.g., sea spray, forest fires, dust storms) and an thropogenic (e.g., automobile and stack exhaust). Haze usually is associated with s ub-saturated air, whereas fog or mi st indicates saturated conditions. To measure the amount of haze, light extinction, i. e., the attenuation of light (defined as the reduction in luminance of a parallel beam of li ght as the light passes through a medium wherein absorption and scattering occur), is used. Howeve r, light extinction can also be caused by fog or mist and other naturally occurring atmospheric phenomena (e.g., precipitation). Therefore, the change in light extinction shoul d be based upon the change from the existing or background light
extinction to the potential light extinction cau sed by a proposed source. However, under the regulations promulgated for visibility protection (40 Code of Federal Regulations (CFR) Part 51.301(x)), visi bility impairment is defined as, “...any humanly perceptible change in visibility (visual range, contrast, colo ration) from that whic h would have existed under
natural conditions.” Thus, the change in light extinction du e to the plant is co mpared to the light
extinction under natural conditions (i.e., no man-made pollution). Calc ulations of the impact of the simulated plume particulate matter component concen trations on light extincti on were carried out in the CALPOST postprocessor.

7.7 Regional Haze Impact Calculation Methodology Two regional haze analyses specified by FLAG 2010 were conducted at the Class I areas. Using the background values discussed in the next se ction, the visibility imp acts were first assessed relative to the annual average background extinctions and the 98th percentile impact, and second
relative to the 20% best da ys (B20%) extinctions and th e 98th percentile impacts.
CALPOST version 6.221 level 080 724 was used for this asse ssment. CALPOST version
6.221 was run in conformance with FLAG 2010 defaul t settings (MVISCHECK=1). This is Method 8, sub-mode 5, which conforms to using mont hly RHFSML, RHFLRG, and RHFSEA with daily modeled and monthly background concentrations.

### 7-5 7.8 Background Concentrations and Relative Humidity Adjustment Factors To determine the change in visibility or light extinction in the Class I areas of interest, the natural background estimates for visi bility reference levels, or background concentrations, must be quantified. These consist of am monium sulfate, ammonium nitr ate, organic matter, elemental carbon, soil, coarse matter, and sea salt. These c oncentrations are input into CALPOST variables BKSO4, BKNO3, BKOC, BKEC, BKSOIL, BKPMC and BKSALT, respectively. Tables 5 and 6 of FLAG 2010 provide the natura l background concentrations for the Class I areas pertinent to this part of the analysis. Ba ckground concentrations used for these analyses are presented in 7-6. These estimates of background visibility assume no man-made pollution exists (i.e., relate to a time before humans) and were based on the na tural background aerosol concentrations provided by the National Acid Precipitation Assessment Progr am (NAPAP) and adjusted to account for the effect of relative humidity on particle fo rmation (namely sulfates and nitrates). The extinction due to Rayleigh scattering was set as listed in Tables 5 and 6 of FLAG 2010. The average monthly relative humidity adjustment factors from Tables 7 and 8 of FLAG 2010 (see 7-7), along with the preceding extin ction components, were used to determine the ex tinction change from the natural background visibility levels.

### 7-6 Figure 7-1. Locations of Receptors

480 500 520 540 560 580 600 620 640 LCCx (km), WGS-84 -60 -40 -20

0 20 40 60 80 100LCCy (km), WGS-84 Yellowstone

Washakie

Teton North Absaroka

Map projection: LCC, WGS-84 Feast = 600 km, Fnorth = 0 km LATo = 44.25N, LANo = 109.5W LAT1 = 45 N, LAT2 = 49 N

1030 1040 1050 1060 1070 1080 1090 LCCx (km), WGS-84 300 310 320 330 340 350 360 370 380 390 400LCCy (km),WGS-84 Theodore Roosevelt - N

Theodore Roosevelt - C

Theodore Roosevelt - S

705 710 715 720 725 730 LCCx (km), WGS-84 350 355 360 365 370 375 380 385 390LCCy (km), WGS-84

UL Bend

### 7-7 Figure 7-1. Locations of receptors at UL Bend, North Absaroka, Theodore Roosevelt, Washakie and Yellowstone Class I areas

Table 7-5. Ozone Stations

Station ID Latitude (deg.) Longitude (deg.) Land use Setting Site name 160230101 43.46 113.56 Blighted Areas Rural 300298001 48.51 114.00 Agricultural Rural Glacier National Park 380070002 46.89 103.37 Agricultural Rural Painted Canyon 380130004 48.64 102.40 Agricultural Rural LostwoodNwr 380250003 47.32 102.53 Agricultural Rural Dunn Center 380530002 47.60 103.26 Agricultural Rural Trnp-Nu 380570004 47.30 101.77 Agricultural Rural Beulah North 380650002 47.19 101.43 Agricultural Rural Hannover 460711001 43.75 101.94 Agricultural Rural 461030016 44.06 103.21 Residential Urban Near Robinsdale School 560050123 44.67 105.29 Desert Rural 560391011 44.57 110.40 Forest Rural Near the Water Tower of Hwy98 560358001 42.93 109.79 Forest Rural Freemont Lake South, WV



### Figure 7-4. Locations of Ozone Monitoring Stations used in the CALPUFF Modeling

### 7-8 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 LCCx (km), WGS-84 -200 -150 -100 -50

0 50 100 150 200 250 300 350 400 450 500 550LCCy (km),WGS-84

160230101 300298001

380070002 380130004

380250003 380530002

380570004 380650002

460711001 461030016 560050123

560391011 GLR468

THR422

WNC429

PND165 YEL408 Colstrip

Map projection: LCC, WGS-84 Feast = 600 km, Fnorth = 0 km LATo = 44.25N, LANo = 109.5W LAT1 = 45 N, LAT2 = 49 N CASTNET

AIRS ID MT

ND

SD

WY PPL, Montana

MODELING DOMAIN

### 7-9 Table 7-6. Summary of Background Natural Visibility Conditions

Class I area Average Natural Concentration West ( μ g/m 3 ) Dry Extinction Efficiency Coefficient ( m 3 /g )

Ammonium sulfate 0.12 3

Ammonium nitrate 0.10 3
Organic carbon mass 0.47 4

Elemental carbon 0.02 10

Soil 0.50 1

Coarse Mass 3.00 0.6

Source : Guidance for Estimating Natural Visibility Condi tions Under the Regional Haze Rule (2003), 2-1



### Table 7-7. Monthly f(RH) values based on Representative IMPROVE Site Locations
Class I area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

UL Bend WA 2.6 2.4 2.4 2.3 2.2 2.1 1.9 1.8 1.9 2.2 2.6 2.6

Theodore Roosevelt NP 2.9 2.8 2.8 2. 4 2.4 2.5 2.4 2.2 2.2 2.3 3.0 3.0

Washakie WA 2.4 2.2 2.2 2.1 2.1 1.9 1.6 1.5 1.8 2.0 2.3 2.4

North Absaroka WA 2.4 2.2 2.2 2.1 2.1 1.9 1.6 1.5 1.8 2.0 2.3 2.4

Yellowstone NP 2.5 2.3 2.2 2.1 2.1 1.9 1.7 1.6 1.8 2.1 2.4 2.5

Source: Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule (2003), Appendix A

### 8-1 8.0 BART PROTOCOL MODELING RESULTS The changes in light extin ction relative to the na tural background due to SO 2 

### , NO x 

### and
PM 10 

### from Colstrip Units 1&2, 3&4, and 1-4, were computed using the BART modeling protocol approach based on th e base case emissions level dur ing the years (2001-2003), the reference case emission levels during the year s (2009-2010), and the contro l options analyzed. The emissions levels for the base case, the re ference case, and the control alternatives are presented in Tables 4-5 and 4-6, Engl ish and metric uni ts, respectively. The CALPUFF modeling predicted the effects of emissions from the units on visibility at
the five Class I areas within 300 km of the facility. The FLAG 2010 methodology with
CALPOST Method 8 and 98 th 

### percentile day results were used to predict visibility impacts. The light extinction impacts are presen ted for each modeled year in units of change in deciview (dv) for each of the five Class I areas, consistent with the procedures outlined in the Montana Protocol. As previously noted, the use of non-co incident actual daily maximum emissions from EPA’s CAM database and applying the 98 th 

### percentile in order to predict visibility impacts to all background visibility conditions result in conservativ e predictions that overestimate the facility’s visibility impact.
Tables 8-1 and 8-2 summarize the delta in deci views (i.e., the change in visibility) for the base case, the reference case, and each of the c ontrol alternatives from natural annual average conditions and conditions on the 20 percent best vi sibility days.The coe fficients used in the IMPROVE equation for calculating li ght extinction as presented in the Federal Land Managers’ Air Quality Related Values Work Group (FLAG) Phase I Report – Revised (2010) 12 

### are presented to either one or two significant digits. Using the rule s of mathematical significance, the modeling results should only be presented to one significant digit precision; however, following EPA convention, the results presented he rein are reported to two decimal places. It
must be noted that the inclusion of a second significant digit in these results implies a level of model precision not warranted by the underlying equation. For e ach control alte rnative, the emissions were altered for only th e specific pollutant for which th e control alternative applied, with the other pollutants modeled at their base ca se emissions. Recall that changes of less than 1.0 deciview are considered imperceptible.

12 http://www.nature.nps.gov/air /pubs/pdf/flag/FLAG_2010.pdf8-1Table 8-1 Class I Impacts (Deciviews) Method 8 (8thHighest Annual Average)**Scenario visibility predictions include application of indicated controls on all Units listed in the sub-headings (i.e. Units1&2, Units 3&4).8-2Table 8-2 Class I Impacts (Deciviews) Method 8 20% Best Days Condition

### 9-1 9.0 SUMMARY
Conservative BART Protoc ol CALPUFF visibility modeling was conducted for emissions from the Colstrip generating station. The approach conservatively uses non-coincident maximum daily emissions from EPA’s CAM database for NOx, SO 2 

### and PM for all modeling days and assess the 98 th 

### percentile visibility impact. Modeling shows that the predic ted visibility impacts of the Colstrip facility have decreased since the BART baseline years (200 1-2003) due to implementation of additional controls and reduction of emissions. Colstrip bu rns low sulfur Powder River Basin Coal as its fuel and employs SO 2 

### scrubbers and LNB technology, as well as SOFA on Units 3 & 4, resulting
in low emission rates. A review of the model predicted visibility impacts of the vari ous control techniques considered (Tables 8-1 and 8-2) shows that implementing these controls will not, in most cases, lead to perceptible visibility improvements (i.e., changes greater than 1. 0 delta-deciview). Due to the conservative nature of the BART protoc ol predictions (unrealisti c emission scenario, use
of the 98 th 

### percentile prediction as the metric of pe rformance), it is likely that the predicted impacts are being over-predicted and that actual visibility impacts and modeled improvements
will be less than indicated on these tables.