### i

### ii

### TABLE OF CONTENTS

SECTION PAGE
EXECUTIVE SUMMARY ...................................................................................................... ES-1 1.0 INTRODUCTION/BACKGROUND..............................................................................1-1
2.0 PLANT DESCRIPTIONS – BART AFFECTED UNITS ...............................................2-1
2.1 Boiler Type .......................................................................................................... 2-1 2.2 Emissions ............................................................................................................. 2-1 2.3 Potentially Impacted Class I Areas ...................................................................... 2-4
3.0 BART METHODOLOGY OVERVIEW ........................................................................3-1
4.0 BART ANALYSES .........................................................................................................4-1
4.1 Approach .............................................................................................................. 4-1 4.1.1 Particulate Matter ...........................................................................................4-3 4.1.2 Sulfur Dioxide ................................................................................................4-5 4.1.3 Nitrogen Oxides .............................................................................................4-6 4.2 Evaluated Retrofit Technologies for Colstrip Units 1 &2 ...................................4-8 4.2.1 Particulate Controls ........................................................................................4-8 4.2.1.1 Particulate Control Technologies .......................................................4-9 4.2.1.2 Costs of Controls .............................................................................4-11 4.2.1.3 Energy ..............................................................................................4-13 4.2.1.4 Non-Air Quality Environmental Impacts .........................................4-14 4.2.1.5 Remaining Useful Life .....................................................................4-14 4.2.1.6 Visibility Modeling ..........................................................................4-14 4.2.2 Sulfur Dioxide Controls ...............................................................................4-15 4.2.2.1 Control Technologies .......................................................................4-15 4.2.2.2 Cost of SO 2 

### Controls ........................................................................4-16 4.2.2.3 Energy ..............................................................................................4-16 4.2.2.4 Non-Air Quality Environmental Impacts .........................................4-17 4.2.2.5 Remaining Useful Life .....................................................................4-17 4.2.2.6 Visibility Modeling ..........................................................................4-17 4.2.3 NO x 

### Controls ................................................................................................4-18 4.2.3.1 Control Technologies .......................................................................4-19 4.2.3.2 Cost of NO x 

### Controls .......................................................................4-19 4.2.3.3 Energy ..............................................................................................4-20 4.2.3.4 Non-Air Quality Environmental Impacts .........................................4-20 4.2.3.5 Remaining Useful Life .....................................................................4-20 4.2.3.6 Visibility Modeling ..........................................................................4-20 4.3 Visibility Modeling Pr ocedures and Results ...................................................... 4-21 4.3.1 General Modeling Procedures ......................................................................4-21 4.3.2 Summary of Modeling Results ....................................................................4-22
5.0 SUMMARY AND CONCLUSIONS ..............................................................................5-1
6.0 REFERENCES ................................................................................................................6-4

i

### TABLE OF CONTENTS (Continued)

LIST OF TABLES Table ES-1: Current / NSPS / Control Options Cost Summary ............................................... ES-5 Table ES-2: Modeled Visibility and Visibility Improvements ................................................ ES-6 Table 2-1: Colstrip Particul ate Matter Type and Size Speciation ............................................. 2-2 Table 2-2: Present (Base Case) SO 2 

### and NO x 

### Emissions ......................................................... 2-3
Table 4-1: Allowable / Current / NSPS / Presumptive Emission Limits ..................................4-2
Table 4-2: Particulate Emi ssions Summary for Colstrip 1&2 .................................................. 4-8
Table 4-3: PPL BA RT Particulate Control Cost Summary (Each Unit) ................................4-12 Table 4-4: Representative Control Equipment Pressure Drops .............................................. 4-14 Table 4-5: Summary of M odeling Results for Particulate ...................................................... 4-15
Table 4-6: PPL BART SO 2 

### Control Cost Summary (Each Unit) ........................................... 4-17 Table 4-7: Summary of Modeling Results for SO 2 

### ................................................................. 4-18
Table 4-8: PPL BART NO x 

### Control Cost Summary (Each Unit) .......................................... 4-19 Table 4-9: Summary of Modeling Results for NO x 

### ................................................................ 4-21 Table 4-10: Summary of Modeling Results .............................................................................. 4-23
Table 5-1: Current / NSPS / Control Options Cost Summary .................................................. 5-3
Table 5-2: Modeled Visibil ity and Visibility Improvements .................................................... 5-3

LIST OF FIGURES
FIGURE 4-1: COST ANALYSIS OF ESP CONTROL ...........................................................4-12

APPENDICES
APPENDIX A: DETAILED COST CALCULATIONS
APPENDIX B CALPUFF APPLICATION FO R BART ASSESSMENTS AT PPL COLSTRIP UNITS 1&2

ii

### EXECUTIVE SUMMARY

The Best Available Retrofit Technology (B ART) program was established under the federal Regional Haze Rule to evaluate possi ble retrofit emissions control technology for visibility impairing pollutants emitted from cer tain combustion units constructed between 1962 and 1977 that could potentially cause or contribute to a degradation of visibility at Prevention of Significant Deterioration (PSD) mandatory Class I Areas. Coal fired Units 1&2 at the Colstrip generati ng plant located in Colstrip, Montana, jointly owned by Puget Sound Energy and PPL Montana, LLC and operated by PPL Montana, LLC were determined to be BART-eligible under the Federal Regional Haze Rule by the U.S. Environmental Protection Agency Region 8. The Cla ss I areas within 300 km of Colstrip are the UL Bend National Wildlife Refuge (200 km to the northwest), the North Absaroka Wilderness Area (254 km to the west), the Theodore Rooseve lt National Park (260 km to the northeast), the Washakie Wilderness Area (278 km to the southwes t) and Yellowstone National Park (281 km to the west). These Class I areas are shown in relation to the Colstrip plant in Figure ES-1.
The CALPUFF model was used to evaluate th e visibility impacts of present emissions from the Colstrip Units 1&2 and BART contro l alternatives. The model setup and input meteorological and emissions data were obtai ned from EPA/WRAP files. The modeling conducted by TRC for PPL used those data file s with a few modifications. The particulate
emissions were revised based on PPL stack test data and a few adjustments to the modeling as described in Appendix B. The highest modeled annual 98 th 

### percentile daily visibility impact of emissions from Units 1&2 at present maximum actua l emissions as predicted to occur in the UL Bend National Wildlife Refuge (NWR) Class I ar ea is 2.233 deciviews. A summary of the visibility modeling results is provided in Table ES-2. The U.S. Environmental Protection Agency’s (EPA’s) BART Guideline approach has been applied to Colstrip Units 1&2 to iden tify the “best system of continuous emission reduction” applicable to the plant for filterable particulate, sulfur dioxide (SO 2 

### ) and nitrogen oxides (NO x 

### ) control in order to comply with Regi on 8’s BART program. These units already have relatively low emissions due to the use of wet scrubbers th at remove both particulate and sulfur dioxide, low sulfur Powder River Basi n coal and good combustion control using low NO x 

### burners. A range of demonstrated control alternatives for sub-b ituminous coal-fired boilers was

ES-1

### Figure ES-1: Colstrip Location and Class I Areas Evaluated

ES-2

### evaluated considering costs, ener gy and environmental impacts, rema ining useful life of the units and modeled visibility improvements. A summary of the results of the eval uations is provided in
Table ES-1. For filterable particulate matter, electrostatic precipitators (ESP), fabric filters (baghouses), mechanical collector s and wet scrubbers were considered. Cost analyses were
conducted for fabric filters and ESPs. Mechanical collectors were not further evaluated because these are used as pre-filters and do not perform well as a retrofit option. The Colstrip Units 1&2 already have venturi wet scrubbers that control both partic ulate matter and SO 2 

### emissions and therefore either an upgrade to the current techno logy, or the addition of fabric filter/ESP controls would be necessary to attain an emission rate equivalent to th e best demonstrated technology (BDT) filterable particulate em ission rate of 0.015 lbs/MMBtu. An upgrade to the existing scrubber technology was not evaluated as the existi ng particulate emissions level is already so
low that there is little room fo r further improvement of the scrubbe r. For installation of an ESP or fabric filter, this would cost appr oximately $30,000 to $40,000 per ton of particulate emissions controlled and result in only a 0.04 2 deciview reduction which is not a visibly discernable improvement. Consequently, implem entation of additional pa rticulate control at Colstrip is not warranted. The cost effectiveness analysis for SO 2 

### and NO x 

### was based on emission rates typical of 30-day average emissions. These rates for the pr esent (base case) emissions are 0.40 lb/MMBtu
for SO 2 

### and 0.35 lb/MMBtu for NO x 

### . However, consistent with the modeling guidance, the visibility modeling analysis wa s conducted at maximum daily emi ssion rates. For the present (base case) emissions these maximum rates during the modeling years for SO 2 

### are 0.72
lb/MMBtu for Unit 1 and 0.80 lb/MMBtu for Unit 2 and for NO x 

### they are 0.45 lb/MMBtu and 0.53 lb/MMBtu respectively. This di stinction was also made for the control alternatives as well as for the base case. For filterable particulat e, continuous emissions data (CEM data) are not
available and a distinction between maximum a nd typical emission rates was not made. The present filterable particulate emission rates based on stack te st data are 0.047 lb/MMBtu and 0.058 lb/MMBtu for Units 1&2, respectively and the condensable particulate emission rates
based on AP-42 emission factors are 0.038 lb/MMBtu for both units. Upgrades to the current venturi scrubbers were considered as a way to improve SO 2 

### removal efficiency. The low sulfur Powder Rive r Basin (PRB) coal is alkaline by nature and there is an estimated 75 percent control of SO 2 

### by virtue of flyash alkalinity acting with

ES-3

### scrubbing liquor alone. Enhancements to this re moval have been evaluated that include the addition of lime to the scrubbers presently in operation to enhance removal. The addition of lime is projected to increase SO 2 

### removal efficiency from the present 75 percent level to approximately 88 percent with little adverse operational impact at a cost effectiveness (CE) of an estimated $218/ton of additional SO 2 

### removed. It is projected that even higher increase in SO 2 

### removal efficiency to 91 percent, which corresponds to the EPA presumptive BART SO 2 

### rate of
0.15 lb/MMBtu can be achieved with even more lime addition, however, at additional costs. This presumptive rate applies to some coal-fired boilers, but it does not apply to the Colstrip boilers because they already achie ve over a 50 percent control effici ency. Nevertheless, this rate
was evaluated. The increased addition of lime to attain the 91 percent removal will incur scaling of the scrubber with significant downtime to des cale the scrubbing vessel at an estimated cost of $499/ton of SO 2 

### removed. To eliminate the downtime fo r descaling, a spare scrubber vessel
could be installed to eliminate downtime at a CE of $1,292/ton. Incremental CE of the high lime injection, and the backup scr ubber module options are $1,621 and $5,590/ton respectively. Cost
estimates are based on EPA Control Cost Manual information and techniques and PPL operating experience. All costs are indicated in 2007 dollars . Only a 0.422 deciview reduction is predicted with lime addition to improve SO 2 

### removal to 88 percent. This improvement is below the level considered discernable to the human eye. The incremental improvement to go beyond 88 percent reduction is only 0.146 deciviews or less. 

### Consequently, implementation of these controls
is not warranted.
NO x 

### controls at Colstrip include the tangential firing design of the boilers and existing
low-NO x 

### burners with close-coupled overfire air. Th e present typical annual emission rates are 0.35 lb/MMBtu for each unit. By the additi on of separated over-f ire air (SOFA) and
redistribution of combustion air to the mu ltiple injection ports for the current NO x 

### controls, it is likely that emissions can be reduced to an aver age of 0.18 lb/MMBtu at a cost effectiveness of $451/ton. Selective non-catalytic reduction (SNCR) by injection of urea into the same zone within the unit is projected to have only a slight additional effect on th e 0.18 lb/MMBtu SOFA controlled rate resulting in a projected rate of 0.16 lb/MMBtu. The cost of SNCR technology has been estimated at $977/ton of NO x 

### controlled, however, its tendency to form secondary particulate emissions from combin ation with sulfur oxides, and it s creation of ammonia slip in the exhaust, makes this technique undesirable. A hot-side selective ca talytic reduction system (SCR) was also reviewed to attain emissions to the presumptive BART NO x 

### rate of 0.15

ES-4

### lb/MMBtu, however its incremental cost over the addition of SNCR ma kes SCR economically unacceptable at an es timated $2,286/ton of NO x 

### , and an incremental cost effectiveness of $30,786/ton. On a visibility basis, only a 0.573 deciview improvement results from implementation of SOFA. This improvement is unlikely to be visibly discernable. The incremental improvements from controls beyond SOFA are 0.163 deciviews or less. Consequently, implementation of controls is not warranted. A summary of the results of the cost evaluations based on typical emissions representative of a 30-day average is provide d in Table ES-1, both re lative to the present emissions and incrementally from one level of c ontrol to the next. A summary of the modeled visibility impacts of the present emissions and the control alternatives based on maximum emissions is provided in Table ES-2, both relative to the pres ent emissions and incrementally.

Table ES-1: Current / NSPS / Control Options Cost Summary

ES-5

### Table ES-2: Modeled Visibility and Visibility Improvements

Modeled Modeled Modeled Rate (1)(2) Prediction (3) from Rate (1)(2) Prediction from Rate (1)(2 ) Prediction from Option (lb/MMBtu) (deciviews) Present Inc (6) Option (lb/MMBtu) (deciviews) Present Inc (6) Option (lb/MMBtu ) (deciviews) Present Inc (6) Present 0.047/0.058 2.233 n/a n/a Present 0.72/0.80 2.233 n/a n/a Present 0.45/0.53 2.233 n/a n/a New ESP 0.015 2.213 0.042 0.042 WS-FGD(4) 0.36/0.40 2.000 0.422 0.422 SOFA 0.23/0.27 1.781 0.573 0.573 Added FF 0.015 2.213 0.042 0.042 WS-FGD(5) 0.27/0.30 1.954 0.505 0.091 SNCR 0.21/0.24 1.713 0.638 0.068 WS-FGD(6) 0.15 1.832 0.651 0.146 SCR 0.15 1.584 0.801 0.163

Notes: (1) The modeled emission rate is the rate corresponding to the maximum daily emissions during the modeling years (200 1-2003). (2) If Unit 1 and Unit 2 emission rates are different, they are indicated as Unit 1/Unit 2 rates. (3) Prediction is from all three pollutants at present emissions except the one being controlled (4) See corresponding footnote in Table ES-1. (5) See corresponding footnote in Table ES-1. (6) See corresponding footnote in Table ES-1. (7) Maximum improvements shown may occur at differeent Class I areas that the maximum prediction among all Class I areas. Improvement (7) Improvement (7) Improvement (7) Filterable Particulate Sulfur Dioxide Nitrogen Oxides



### ES-6

### 1.0 INTRODUCTION/BACKGROUND The U.S. Environmental Protection Agency (EPA) Region 8 identified Colstrip generating station Units 1&2 as Be st Available Retrofit Technology (BART) eligible units. This determination was made under the federal Regional Haze Rule (FR , Vol. 64, No. 126) which requires the States to submit State Implementation Pl ans to address haze and visibility issues in mandatory Prevention of Significa nt Deterioration (PSD ) Class I Areas. On June 19, 2006 the State of Montana withdrew its effort to adopt th e provisions of the Region al Haze Rule. Region 8 has assumed responsibility for the Rule and in tends to prepare a Fede ral Implementation Plan (FIP) for Montana sources. Regional haze is cau sed by naturally occurrin g atmospheric particles and humidity as well as by anthropogenic emi ssions of primary particulate matter and of secondary emissions resulting from atmospheric ga s to particle conversions of sulfur dioxide (SO 2 

### ) and nitrogen oxides (NO x 

### ). The BART regulations identify large stationary source emission units put into operation between 1962 a nd 1977, such as Colstrip Units 1&2, as BARTeligible. The pollutants subject to BART requirements are SO 2 

### , NO x 

### , particulate matter and volatile organic compounds (VOC). To address th e visibility impacts of these facilities, EPA issued the “Regional Haze Regulations and Guid elines for Best Availa ble Retrofit Technology (BART) Determinations” including “Appendix Y to Part 51 - Guidelines for BART Determinations Under the Regional Haze Rule” (FR , Vol. 70, No. 128). BART is an emission source specific re gulatory program under the Regional Haze Regulations designed to improve visibility in PSD Class I Areas through control of SO 2 

### , NO x 

### , particulate matter and VOC emissions. Colstrip Units 1&2 each have a generating capacity of 307 megawatts (MW), and have low SO 2 

### emissions due to the use of low sulfur coal and venturi scrubbers. Because Units 1&2 already have post-combustion SO 2 

### scrubbers achieving greater than 50 percent SO 2 

### removal, BART presumptive SO 2 

### rates applicable to power plants with over 750 MW capacity do not apply to Colstrip. The BART presumptive NO x 

### rates, however, do need to be considered. There are no BART pres umptive particulate rates. Units 1&2 have been
evaluated for SO 2 

### , NO x 

### , and particulate matter controls. The BART guideline spells out an approach to use dispersion modeling to identify potentially subject emissions sources that may contribute to regional haze impacts in Class I areas, to evaluate case-by-case emission limitati ons based on the “best system of continuous emission reduction of each pollutant ,” and to predict the degree of visibility improvement that

1-1

### 1-2 results from the proposed emissions limit. The best system of conti nuous emission reduction is
identified based on:

• The available retrofit control options

• Pollution control equipment already in use or planned to be in use

• The cost of the systems

• The remaining use-life of the facility

• The energy and non-air quality enviro nmental impacts of the systems

• The visibility impact analysis.
This report details these steps for Colstrip Units 1&2.

### 2-1 2.0 PLANT DESCRIPTIONS – BART AFFECTED UNITS
2.1 Boiler Type The Colstrip Power Plant consists of a total of four electric utility steam generating units, however only Units 1&2 are subject to BART since Units 3&4 were not operational during the BART eligibility period. Units 1&2 are subject to BART and have a nominal net capacity of 307 megawatts each. The boilers which bega n commercial operation in 1975 and 1976 are tangentially fired pulverized coal boilers that burn sub-bituminous coal as their exclusive fuel. PPL Montana LLC operates the Colstrip Plant under Air Quality Operating Permit OP0513-02.

2.2 Emissions Present (base case) particulate matter emissi ons for Colstrip Units 1&2 are summarized in Table 2-1. The heat input rates (and a ssociated emissions) for each boiler (3,981.8 MMBtu/hr and 3,897.2 MMBtu/hr) used to deri ve the particulate matter emi ssions are the highest daily average heat input rates duri ng the modeling period (2001-2003). The particulate emissions corresponding to these heat input rates were used for modeling the base case. The total filterable particulate emission ra tes are based on stack tests conducted during the modeling years. For each uni t, the highest of the single stac k test conducted during each of the modeling years (2001-2003) was used. This is 0.047 lb/MMBtu for Unit 1 and 0.058 lb/MMBtu for Unit 2. The speciati on of the total filtera ble particulate into elemental carbon, fine
soil and coarse soil and size fractions were based on guidance provided by the National Park Service (NPS). Stack test data for condensable particulates are not available for Units 1&2 during the modeling years. The total condensab le emissions are based on the AP-42 emission factor using a coal sulfur content of 0.68 percent, which is the highest annu al average as received sulfur content during the modeling years. Th is gives a condensables emission rate of 0.038 lb/MMBtu for each unit, which was speciated in to organic and inorganic particulate based on guidance provided by the NPS (20% organic and 80% inorganic). The particulate emissions used for the visibility modeling and the cost analyses were based on these filterable and condensable emission rates and the maximum daily average heat input during the modeling years (3,981.8 MMBtu/hr and 3,897.2 MMBtu/hr). These particulate emissions used for PPL's BA RT modeling are different than those used by EPA in the preliminary BART modeling provided to PPL. PPL believes that the total2-2Table 2-1: Colstrip Particulate Matter Type and Size SpeciationColstrip: Particle Speciation – Base CaseStack ID #Particle speciationCondensableFilterableorganiccondensable (OC)H2SO4COARSESoilElementalCarbon (EC)filterable PM10condensable PM10M1=0.48, SD1=2.0 μmM1=0.48, SD1=2.0 μm%%lb/hrlb/hrlb/hrlb/hrlb/hrUnit155.344.730.26121.0553.47128.734.95Unit260.439.629.62118.4764.58155.485.971M and SD stand for Geometric Mass Mean Diameter and Geometric Standard Deviation. These are the parameters used to calculate the particle size distribution in CALPUFF.

### 2-3 filterable values used here are more accurate because they are based on stack test data. They are higher than the values that EPA used. In terms of mass emissi ons, the modeling presented here
used total filterable particulate emissions of 187.2 lb/hr for Unit 1 and 226.0 lb/hr for Unit 2 versus values used in the EPA modeling of 30.8 lb/hr and 37.2 lb/hr. The total condensables emission rates provided by PPL and used for modeli ng are similar the emission rates used in the EPA modeling. In terms of mass emissions, the m odeling presented here used total condensables for Units 1&2 of 151.1 lb/hr and 148.1 lb/hr respec tively, versus values used in the EPA modeling of 123.0 lb/hr and 148.7 lb/hr.
The SO 2 

### and NO x 

### present (base case) emissions used for modeling are the same as those used in EPA's BART modeling th at was provided to PPL. These are the highest 24-hour average emissions over the modeling years as determined from Part 60 Continuous Emission Monitoring Systems (CEMS) data. For the cost analyses, SO 2 

### and NO x 

### present emission rates were based on typical emission rates representative of a 30-day rolling average actual emission rate for the units. The maximum daily emission rates for modeling and typical/average emission rates for the control technology analyses have been used in accordance with BART guidance in the Final Rule. For PM, for which continuous CEM data are not av ailable, a distinction between maximum and typical emission rates was not made. The particulate matter present (base case) emissions are summarized in Tables 2-1 and
the SO 2 

### and NO x 

### present emissions are summarized in Table 2-2.
Table 2-2: Present (Base Case) SO 2 

### and NO x 

### Emissions Pollutant Emissions Unit Typical/Average Emission Rate (1) (lb/MMBtu) Maximum Emission Rate(2) (lb/MMBtu) Maximum Mass Emissions(2) (lb/hr)

Unit 1 0.40 0.72 2612.0 SO 2


### Unit 2 0.40 0.80 2828.0

Unit1 0.35 0.45 1798.0 NO x



### Unit2 0.35 0.53 1955.0

NOTES: (1) Typical/average emission rates were used for the control technology and cost analyses. (2) Maximum emission rates are the highest daily average emissions during the modeling years (2001-2003). These emissions were used for the modeling analyses.

### 2-4 2.3 Potentially Impacted Class I Areas The Class I areas within 300 km of Colstrip are the UL Bend National Wildlife Refuge (200 km to the to the northwest), the North Ab saroka Wilderness (254 km to the west), the Theodore Roosevelt National Park (260 km to th e northeast), the Washakie Wilderness (278 km to the southwest) and Yellowstone National Park (281 km to the west) . These Class I areas are shown in Figure ES-1.

### 3-1 3.0 BART METHODOLOGY OVERVIEW EPA Region 8 identified the BA RT-eligible sources in Montan a as being in one of the Clean Air Act “26 named source categories” wh ich include steam electric plants, having potential SO 2 

### , NO x 

### , VOC or particulate matter emissions of 250 tons per year (tpy) or more, and having construction dates between 1962 and 1977. Th ese eligibility criter ia include Colstrip Units 1&2 as BART-eligible units. As recommended by EPA, the CALPUFF model was used to predict visibility impacts for normal operating conditions of the units during the modeling period (2001-2003) and for each emission reduction percentage eval uated for the retrofit control options. Potentially applicable retrofit filterable PM, SO 2 

### , and NO x 

### control technologies which represent a range of demonstrated alternatives for large coal-fir ed boilers were identified from
the technical literature. The identified control options were reviewed to determine whether or not they are technically feasible for use with the emission units (i.e., the control technologies have been successfully installe d and operated on similar sources or the technology could be applied to the source). Those control options were then compared to determine their relative performance levels using consistent metrics. In addition to determining the performance metric, other aspects of each technically
feasible retrofit control technol ogy were evaluated based on th e technical literature and plant specific information. These aspects included:

• The capital and operating cost

• The energy impacts

• The environmental impacts

• The remaining use-life of the emission units

• The visibility impacts
Based on the information compiled for each of the steps above, evaluations were conducted regarding retrofit controls applicable to the units.

Capital and Operating Cost To estimate the capital and operating cost of control technologies, information from the U.S. Environmental Protection Agency, Control Cost Manual (“EPA Air Pollution Control Cost Manual”, Sixth ed., EPA-452-02-001, January 2002) was utilized where such data were
available. The BART Final Rule states:

### 3-2 “In order to maintain and improve consistenc y, cost estimates s hould be based on the OAQPS Control Cost Manual where possible. The Control Cost Manual addresses most control technologies in sufficien t detail for a BART analysis.”

Other EPA information to supplement the Cont rol Cost Manual included a fact sheet on
SO 2 

### scrubbing using wet and dry te chnologies that was not availa ble for inclusion in the OAQPS
Manual in 2002. This and other sources of info rmation for the BART costing are cited where appropriate in the text. The application of EPA recommended factors to the capital cost to itemize direct and indirect installation costs is also used in the analyses. In the capitalization of the to tal capital cost of a techno logy, PPL uses 11 years as its standard depreciation schedule, cons istent with the tax code applicab le to the facility. Therefore this capitalization period with an interest rate of 7 percen t per annum was used throughout. Costs were corrected to 2007 dollars using the U.S. Department of Co mmerce, Implicit Price
Deflator cost index.

Energy Impacts The inherent energy consumption to operate air pollution control equipment is appropriate for inclusion in the a nnual operating cost analysis.

Environmental Impacts In some technology applications, a new waste stream is generated or an existing waste stream increases. As examples of this, an enhanced removal of particulate matter accordingly
increases the solids collected. The additi on of scrubbing solids to react with SO 2 

### may change the
character of the ash residue and alter its salability. In the case of some NO x 

### reduction technologies, ammonia used in the catalytic reduction equipment is an additional pollutant that can increase particulate matter formation.

Remaining Useful Life The lives of the Colstrip boilers are expect ed to exceed the study period and projected to have no effect on the costing an alyses for this facility. Visibility Impacts

### 3-3 The modeled results for visibility impact, in units of deciviews, of application of the selected BART options were dete rmined as a result of this study.

### 4-1 4.0 BART ANALYSES
4.1 Approach A technology is considered as a BART opti on if it is considered an “available” and “applicable” technology. A technol ogy is considered available if it has reached the licensing and commercial demonstration phase. EPA feels that this may change during the BART review process up to and includi ng the public comment phase. In addition to a control technology being availabl e, it must also be applicable. Generally, a technology that has been applied to the sour ce type under considerat ion indicates that the control technology is applicab le. This is not always true, and s ite specific factor s could preclude the technology from being applied at a particular source due to space c onstraints, reliability factors, or adverse effects on the rest of the facility. For the BART analyses, Colstrip Units 1&2 we re evaluated with respect to particulate emissions (particulate-filterable portion only), sulfur dioxide (SO 2 

### ) and nitrogen oxides (NO x 

### ). The analysis included review of the technologies listed in:

• EPA’s Clean Air Technology Center (t he RACT/BACT/LAER Clearinghouse)

• State and Local Best Available Control Technology Guidelines

• Control Technology Vendors

• Federal/State/Local permits and associat ed inspection/performance test reports

• EPA’s NSR Bulletin Board

• Department of Energy’s Clean Co al Program Technical Reports
The first step in the five step case-by-cas e BART analysis was identification of “all” retrofit options. These include those with a potential for application to the BART eligible emissions units and pollutants und er consideration for Colstrip. The Colstrip boilers fire sub-bituminous coal having a sulfur content typically under 1 percent by weight. The permit limit for SO 2 

### emissions is specified as no more than 1.2 lb/MMBtu of heat input. Boile rs 1&2 are controlled by vent uri scrubbers for simultaneous particulate and SO 2 

### control, and close coupled overfire air to reduce NO x 

### . In accordance with the Final Rule BART Guidelines (FR, Vol. 70, No. 128), a case-by-case BART analysis must identify the most stringent contro l option and a reasonable set of op tions for analyses that reflect a comprehensive list of available t echnologies for each pollutant. Th e list is considered complete
if the list includes the maximum level of contro l that each technology is capable of achieving. The New Source Performance Standards (N SPS) for Electric Utility Steam Generating Units (EUSGUs) are based on EPA's recent review of the state-of-the-art controls for particulate,

### SO 2 

### , and NO x 

### for electric utility boilers. The first su ch standards (Subpart D), which applied to fossil fuel-fired steam electric generators, we re promulgated on December 23, 1971. Standards specific to EUSGUs (Subpart Da) were prom ulgated on June 11, 1979. On February 27, 2006 (see FR , Vol. 71, No. 38) the particulate, SO 2 

### , and NO x 

### Subpart Da standards were revised to reflect improvements in emissions control si nce the promulgation of the previous NSPS standards. The discussions provided in proposing the rule indicated that revisions to emissions standards of Subpart Da are appropriate in light of the control technology developments since the previous version of the standards in 1979 a nd recent technological improvements in control technology. Although the new emissi on standards apply to units c onstructed after February 27, 2005, they represent the most stringent level of emissions control for new EUSGUs. A summary of the Colstrip allowable emission ra tes (as listed in the Title V permit for the facility), actual emission rates, the presumptive BART levels a nd the 2006 NSPS for particulate,
SO 2 

### , and NO x 

### is provided in Table 4-1. The NSPS app lies to new or modified sources and may be more stringent than a best available retrof it technology emission level. The development of the new emission standards for particulate, SO 2 

### , and NO x 

### by EPA are discussed in the following
sections.
Table 4-1: Allowable / Current / NSPS / Presumptive Emission Limits FOR THE PPL MONTANA, LLC, COLSTRIP UNITS 1&2 Particulate Matter Sulfur Dioxide Nitrogen Oxides Rate Units Rate Units Rate Units Permitted Allowable (1) 0.1 lb/MMBt u 1.2 lb/MMBtu 0.45 lb/MMBtu Emission Rate
Current Typical Emission rate 0.050 lb/MMBtu 0.4 lb/MMBtu 0.35 lb/MMBtu Colstrip Units 1&2

BDT (3) fro m 2006 NSPS 0.015 lb/MMBtu 1.4 lbs SO 2 /MW out 1.0 lb/MW out New Sources (0.15 lb/MM Btu in) (0.11 lb/MMBtu in)

Presumptive (4)
BART for Not Applicable 0.15 lb SO 2 /MMBtu (5) 0.15 lb/MMBtu (6) Large EUSGUs 95 % control (tang fired sub-bituminous) Notes 1) From current Title V Operating Permit - NOx short term limit is 0.7 lb/MMBtu; The allowable NOx limit is 0.45 lb/M MBtu on an annual average basis 2) EPA Reference Method 5 for PM and from coal analysis for SO 2 3) BDT = "Best Demonstrated Technology" - From FR Vol. 71, No. 38, Monday, From FR Vol. 71, No. 38, Monday February 27, 2007, Final Rule (NSPS for EUSGUs) February 27, 2006, Final Rule (NSPS for EUSGUs) - the 2006 revised standards were revised to a gross MW output basis (equivalent in lb/MMBtu input values listed in paren) 4) Applicable to EGU's > 200 MW at plants with output > 750 MW in size and without post-combustion pollutant-specific controls 5) Not applicable to Colstrip under the BART Guidelines 6) Applicable to Colstrip under BART Guidelines



### 4-2

### 4-3 EPA’s Regulatory Appro ach to the NSPS Revisions The publication of the Proposed Rule in 2005 in which new standards were proposed for EUSGUs included the following statement:

“We have reviewed emissions data and contro l technology inform ation applicable to criteria pollutants and have conc luded that regulation of NO x 

### , PM, and SO 2 

### emissions from these sources under the NSPS is approp riate. The proposed amendments to the NSPS reflect the BDT [Best Demonstrated Technology] for these sources based on the performance and cost of the emissi on technologies discussed above.”

In the BART Final Rule, EPA does not limit BART analysis to NSPS standards (see FR Vol. 70, No. 128/Wednesday, July 6, 2005, p. 39164, bottom center) where EPA notes:

“In EPA’s 1980 BART Guidelines for reasonably a ttributable visibility impairment, we concluded that NSPS standards generally, at th at time, represented the best level sources could install as BART. In the 20-year period since this guidance was developed, there have been advances in SO 2 

### control technologies, as well as technologies for the control of other pollutants, confirmed by a number of recent retrofits at Western power plants. Accordingly, EPA no longer concludes that th e NSPS level of controls automatically represents “the best these sources can instal l”. Analysis of the BART factors could result in the selection of an NSPS level of contro l, but you should reach this conclusion only after considering the full range of control options.”

Certainly to use the origin al Subpart Da NSPS emission standards (circa 1979) as proposed BART controls would fall under this BART Final Rule admonition. However, the very recently updated NSPS lim its for particulate, SO 2 

### , and NO x 

### in the 2006 Final Rule, which EPA
determined to be the best demonstrated technolo gy for new sources, could be concluded to be as stringent or more stringent th an BART for Colstrip Units 1&2. The present NSPS levels for particulate and SO 2 

### were considered as well as the SO 2 

### and NO x 

### presumptive BART levels and
other control levels in the BART evaluation. The presump tive BART levels were used as the
lowest level evaluated. The new NO x 

### NSPS level is below the presumptive BART level and was
not evaluated.

4.1.1 Particulate Matter In the proposed rule, EPA discussed the follo wing available particulate matter control technologies:

### 4-4 • Electrostatic Precipitators

• Fabric Filters (Baghouses)

• Mechanical Collectors

• Wet Scrubbers
Electrostatic Precipitators Electrostatic precipitators, commonly known as ESPs, utilize an electric field to ionize fine particulate matter in a flow ing gas using high voltage electrode s. The ionized particles are then attracted to an oppositely charged tube or plate upon which layers of particles build over time. The ESP is typically composed of a larg e box-type structure with several sections of electrified parallel plates or tubes and rappers to periodically remove accumulated particulate. The collected material falls into a hopper and is disposed properly. ESP technology is capable of high removal efficiencies of 99 pe rcent or higher even on very fi ne particulate. Wet ESPs are sometimes used where the plates are cleaned with water sprays, however, they can emit visible plumes.

Fabric Filters (Baghouses) Fabric filter baghouses contain numerous woven cylindrical bags with particle laden gases passing through the cloth material where th e solid particles deposit on the bag surface. With time, the filter cake that develops mu st be removed by one of three common methods which include blasts of reverse flow air injected into the bag, a mechanical shaking system, or a blast of sonic energy. Fabric filte rs are highly efficien t on very small particles and are capable of achieving high efficiencies of 99 percen t or higher similar to ESP technology.

Mechanical Collectors Mechanical collectors use inertial energy to separate particles by physical means only. The devices are cylindrical with a tangential gas inlet that induces a spinning motion to a particle laden gas stream with particles driven to the side s of the cylinder and gas with a reduced particle concentration exiting the top of the cyclone. For large gas flows, numerous parallel cyclones are typical and are called multiple cyclones. These de vices are mostly used as pre-filtration devices to remove the largest particles and can remove up to 80 percent of only the largest particles.

### 4-5 Wet Scrubbers If water is injected into a cyclone, imp action of particles on water droplets enhances removal and effectively scrubs the gas. The most common type of scrubber is a venturi scrubber where water is injected into the exhaust at th e throat of a converging section of duct. The converging section of duct increase s particle velocity and decreases water dr oplet size such that high removal efficiencies can be attained. Scr ubbers have the advantage of being capable of reacting with SO 2 

### under conditions that allow reaction of this pollutant to form water soluble sulfite and sulfate compounds.

4.1.2 Sulfur Dioxide
In their discussion of the available SO 2 

### control technologies in the Proposed Rule that led
to revision of the NSPS for SO 2 

### in February 2006, EPA lists the following available control technologies:

• Coal Pre-Treatment

• Alkali Wet Scrubbing

• Limestone Scrubbing with Forced Oxidation

• Spray Dryer Absorption

• Dry Injection

• Fluidized-bed Combusti on with Limestone

Coal Pre-Treatment There are two basic coal pre-treatments that can reduce SO 2 

### emissions: physical coal cleaning and gasification. Physical cleaning can re move 20 to 90 percent of pyritic sulfur in coal but cannot remove organic sulfur . Gasification processing can reduce sulfur content by over 99 percent.

Alkali Wet Scrubbing Wet scrubbing using a solution of water and lime or limestone, ot herwise known as fluegas desulfurization (FGD) creates intimate contact of flue-gas with the reactive solution in a contact device. Each applicati on of FGD scrubbing is dependent on the fuel sulfur content, and the scrubber design parameters, howev er, up to 98 percent removal of SO 2 

### has been
demonstrated.

### 4-6 Limestone Scrubbing with Forced Oxidation (LSFO)
This is a variation on alkali wet scrubbi ng where compressed air is used to oxidize sulfites in the absorption solution of sulfates . Oxidation creates gypsum which is a salable byproduct for wallboard manufacturers. Oxidati on makes the solids easier to remove from solution and facilitates waste disposal.

Spray Dryer Absorption An alkali containing slurry is used in spray form to contact the SO 2 

### laden flue gas prior to the particulate collection device. Removal of SO 2 

### depends on the stoichiometric ratio of reactant to sulfur and the degree of sa turation attained in the spray-dryer vessel. Solids from the particulate collection device may be recycled to the absorber to attain optimal absorption and utilization of the reactant. Such systems gene rally attain greater than 90 percent control.

Dry Injection Dry solid absorbent is injected directly into the ductwork upstream of the particulate
collection device. SO 2 

### removal occurs by adsorption of the po llutant on the particle surface and collection of the resulting solids with the fly ash in the particulate cont rol device. Lime or limestone based dry injection systems typically do not perform as well as FGD systems and attain 40 to 60 percent removal but up to 90 percent removal if a nother sorbent such as sodium
bicarbonate is used.

4.1.3 Nitrogen Oxides There are both primary and secondary categories of NO x 

### controls in EUSGUs.

• Primary NO x 

### Combustion Controls

o Low-NO x 

### Burners (LNBs)

o Over-Fire Air (OFA) also known as air staging

o LNBs with OFA

o Rotating Opposed Fire Air (ROFA)

o Combustion Improvement Techniques

• Secondary Control Techniques

o Reburning

o Selective Catalytic Reduction (SCR)

o Selective Non-Catalytic Reduction (SNCR)

### 4-7 Low-NO x 

### Burners (LNBs) This technique requires control of the combus tion stoichiometric air/fuel ratio and the boiler temperature profile. NO x 

### formation is dependent on peak flame temperature and the availability of excess air in and around the co mbustion zone. Reduction of the oxygen content in the primary reaction zone and the attendant reduction in peak flame temperature limit NO x 

### formation. Also, limitation in peak flame temperature residence time also will lower NO x 

### emissions. By introducing combustion air in stages, and thoroughly mixing gases in the combustion chamber to reduce hot zones, signif icant reductions of 35 to 55 percent can be realized (Srivastava, Ravi K., et al., Nitrogen oxides Emission Control Options for Coal-Fired Electric Utility Boilers, Journal of the Air a nd Waste Management Association, volume 55, September 2005).
LNBs can have undesirable side-effects that include an increase in the amount of unburned carbon (UBC). This can resu lt in an increas e in UBC of up to 2 pe rcent, however, the largest impacts are on small un its where UBC is already high. In Powder River Basin (PRB) coal-fired boilers it is possible to limit th e increase in UBC to less than 0.5 percent.

Over-Fire Air (OFA)/Air St aging and LNBs with OFA In air staging, 5 to 20 percent of the combustion air is not in jected into the main burner
and is instead introduced above the main burner location. A dding OFA to LNB technology can
reduce LNB NO x 

### levels by an additional 10 to 25 percent. Particularly significant NO x 

### reductions can result from the application of these techniques to tange ntially-fired boilers resulting in a 50 percent decrease in NO x 

### reductions with only a 25 to 35 percent increase in UBC. Increases in CO emissions can be limited to 50 ppm @ 3% O 2 

### .

Rotating Opposed Fire Air (ROFA) or Separated Overfire Air (SOFA) The addition of a combustion air fan to inject high velocity air that breaks up the fireball within the firebox smoothes out temperature prof iles and oxygen levels and typically does not
result in increases in UBC or CO emissions. An improvement in boiler heat rate may actually

occur.

### 4-8 Combustion Improvement Techniques Site and boiler specific controls that mon itor the fuel and air flow to each burner are available. Through computati onal fluid dynamic modeling, boiler operation can be fine-tuned with optimization of the locations of OFA in jection locations to obt ain optimum results.

Selective Catalytic Reduction (SCR) The SCR process utilizes a honeycomb bed of active metal catalyst impregnated with
zeolite to reduce NO x 

### to molecular nitrogen. Ammonia or an ammonia-like substance such as urea is injected upstream of the catalyst bed and by using the proper inj ection ratio of ammonia
to NO x 

### , the “reduction” of NO x 

### to N 2 

### and H 2 

### 0 occurs. The process is temperature dependent and coal-fired boilers typically loca te the catalyst bed in the boiler between the economizer outlet and the air preheater where the necessary reaction temperature of 450 to 750 degrees F is found. This technology is capable of 90 percent or greater NO x 

### control.

Selective Non-Catalytic Reduction (SNCR) In this control technique, ammonia or an ammonia-like reagent is injected into the combustion chamber where the flue gas is in the range of 1,600 to 2,000 degrees F. The same
reactions that reduce NO x 

### to nitrogen and water occur with SNCR, but without the catalyst bed. The technique only attains 30 to 50 percent NO x 

### control.

4.2 Evaluated Retrofit Technologies for Colstrip Units 1 &2 The following sections evaluate retrofit control technologies for Colstrip Units 1&2 for particulate matter, SO 2 

### and NO x 

### .

4.2.1 Particulate Controls The following table provides the present part iculate emission rates from Colstrip Units 1&2, as described in Section 2.2.
Table 4-2: Particulate Emi ssions Summary for Colstrip 1&2

Fuel Control Heat Input Unit Filterable Condensable Total Filterable Condensable Total Equip MMBtu/hr lbs/hr lbs/hr lbs/hr lb/MMBtu lb/MMBtu lb/MMBtu

Coal Venturi 3981.8 Unit 1 187.1 151.3 338.4 0.047 0.038 0.085 Coal Venturi 3897.2 Unit 2 226.0 148.1 374.1 0.058 0.038 0.096

### 4-9 The heat input rates shown above are the highest daily average heat i nput rates during the modeling years (2001-2003). The total particulate em ission rate applied to these heat input rates is 0.085 lb/MMBtu and 0.096 lb/MMBtu respectively for Units 1&2 based on stack test data. The speciation of the particulate emissions is desc ribed in Section 2.2. The above data show that emission rates from Units 1&2 are already low due to the good combustion techniques and application of wet scrubbing being used in these boilers. The filterable pa rticulate emission rates are typical for wet scrubbing using venturi scrubbing technology in coal-fir ed utility boilers. It is necessary, as part of the BART analysis , to identify the best demonstrated emission rate that a technology can deliver. Step 1 in the BART analysis pro cess is considered complete if the BDT rate, the New Source Performance Standards (NSPS) emission rate, and emission rate from current New Source Review permits are incl uded. The following list of potential filterable particulate control technologies has b een evaluated for Colstrip Units 1&2:

4.2.1.1 Particulate Control Technologies Electrostatic Precipitators and Fabric Filters (ESP/FF) In the Proposed Rule, EPA discussed these technologies as interchangeable. Both are capable of the control of fine particulate matter by 99+ percent for coal fired boilers. The Colstrip boilers are equipped with wet scrubbi ng technology that performs a dual function of particulate and SO 2 

### control. It is possible however, to use add-on control devices to attain the BDT emission rate of 0.015 lb/MMBtu for Colstrip Units 1&2. Either ESP or FF technology could be applie d to Colstrip Units 1&2. The additional removal of fine filterable part iculate would be limited, however, it is assumed that either could
attain the NSPS BDT limit of 0.015 lb/MMBtu. Ordinarily, FF tec hnology would be eliminated
from consideration because of the saturated exha ust from the venturi scr ubbers. In the case of the Colstrip units, however, the exhaust is reheated to above the dew point by steam condensation reheat exchangers and therefor e add-on devices could be feasible. Both technologies have therefore been analyzed as available and applicable add-on particulate
controls.

Mechanical Collectors Mechanical collectors, sometim es known as inertial separa tors, use the momentum of particulate matter to concentrate and remove pa rticles from a gas stream. Devices such as cyclones and settling chambers are in this group of controls. Multiple pa rallel cyclones are often

### 4-10 used in particulate control to obt ain relatively high removal efficienci es of even fine particulate. One reference states that a multiple cyclone can c ontrol high percentages of particulate generated by coal-fired units, but cannot attain the very low regulatory allowable emission rates of the NSPS or most state agencies. Mechanical collectors, almost exclusively multiple cyclones, have been used on coal fired boilers as pre-filters to reduce particul ate emissions to the primary control device. However, it is not possible to retrofit mechanic al collection equipment to the Colstrip boilers
since it must be installed before the main collector and in association with the design of the main collector. Furthermore, the existing wet scr ubbers are already achieving an efficiency higher than would be achieved by mechanical collectors. Mechanical collectors were, therefore, given
no consideration as an availa ble retrofit technology.

Wet Scrubbers Scrubbing equipment adds the effect of wate r washing to the inertial separation of
mechanical collectors. The common venturi scr ubber is a device where a converging section of duct is injected with water. The water, normall y injected at the narrowest point in the venturi throat, expands downstream into micron and submicron sized droplet s. High pressure drops are typically utilized to create the minute water dr oplets that are capable of absorbing the fine particulate. Particulate laden gases entering the throat of the venturi are captured by impaction and absorption in the downstream section of the ve nturi scrubber. The particle laden liquid can be filtered, recycled, and reused in most cas es. As noted previously, particulate removal efficiencies of these types of devices, while not as high as baghouses and fabric filters, are potentially as high as 99 percent even for fine particulate generated from coal firing. Wet scrubbers are currently operating to control particulate and SO 2 

### emissions on Colstrip Units 1&2. While enhancements to pa rticulate collection effi ciency are potentially possible, the filterable emission rates of 0.047 and 0.058 lb/MMBtu, as determined from stack testing, are already very low and indicative of excellent control efficiency for this technology. Furthermore, enhancement of the wet scrubbers would not be expected to result in additional particulate removal. Accordingly, ESP and FF cont rols were the applicable and available control technologies to enhance the alread y 98% particulate cont rol efficiency of the Colstrip Units 1&2
boilers.

### 4-11 Other Impacts of Technically Feasible Control Options
Other criteria are relevant in th e BART selection process. Th e costs of retrofit controls, the energy consumption of these controls, and th e non-air quality environm ental impacts of the controls are included in the BART selection pro cess. This section discusses these additional
factors.

4.2.1.2 Costs of Controls The costs of ESP and FF filterable particulate controls for application to the Colstrip
Units 1&2 boilers were evaluated. The cost of control makes the assumption that adequate land acreage is available to locate the devices and that the controls will be installed after the ID fan and plume reheat exchangers. The cost effectiveness (CE) is assu med to be an incremental value
determined as that to reduce th e current particulate emissions of 0.058 lb/MMBtu (Unit 2) to the
BDT emission rate of 0.015 lb/MMBtu. Unit 2 was analyzed as an example because it has the higher filterable particulate emission rate which would give the lower of the two CE values.
The cost of ESP control is based on a base cost in 1986 dollars of $60/kW as shown in Figure 4-1 from AWMA for 99 percent control. Table 4-3 shows the ESP costing calculations for a 68 percent reduction from present emissions levels, which would reduce filterable particulate emissions to 0.015 lb/MMBtu, see Appendix A, Tables A4-3(a) and A4-3(b) for complete details. The electrification of the fields and rapper costs are based on the specific collection area estimated for one PPL Colstrip boiler in accordance with EPA recommendations.
The annualized cost is an incremental cost to reduce the current particulate emissions from one boiler. Equipment maintenance, administrative annual costs, and all calculat ions use the standardized OAQPS control costin g methods. It is speculative wh ether this control efficiency could be attained for a unit with a present filterable particulate emissions level of 0.05
lb/MMBtu. At a CE of about $30,000 to $40,000/ton of additional cont rol, this is not considered economically justifiable. The analysis of the cost of ESP and FF control summarized in Table 4-3 was prepared using the standard cost estimation techniques from EPA (EPA 2002). The approach uses percentage factors applied to the purchased capital equipment cost to estimate a total installed capital cost for installation of an FF. EPA cost factors specif ically developed for FF technology were used. An annualized capital cost of the eq uipment was determined using a capital recovery

### Figure 4-1: Cost Analysis of ESP Control

Table 4-3: PPL BART Particul ate Control Cost Summary (Per Unit)

Option Description Total Annual Tons controlled Cost Cost ($) Effectiveness $/ton

Added ESP Control $21,754,115 562 $38,738 Added Fabric Filtration $16,622,318 562 $29,599



### 4-12

### 4-13 factor based on a depreciation schedule of 11 year s, and assumed that mone y is available at an annual interest rate of 7 percent. All equipment cost data are corrected to 2007 do llars. As in the case of ESP controls, the cost estimate has been prepared for Colstrip Un it 2 and would be higher for the other unit, asUnit 1 has a slightly lower filterable particulate emission rate. At a CE of approximately $30,000 to $40,000/ton of additional particulate controlled, a pplication of this opti on is not economically justifiable.

4.2.1.3 Energy Although full costing data were not develope d for each potential particulate control option, energy consumption, in terms of the fa n power to drive the exhaust gas through the control devices is a parameter that can be readil y estimated for ESP and venturi scrubber control. The energy cost of the control op tions is included in the cost effectiveness Table 4-3. This motive power is directly related to the pressure drop of the particular control option and the following equation is offered by EPA as being representative of the required fan power for control devices throughout its Control Cost Manual:

Power (kw-hrs/year) = 1.81 x 10 -4 

### x ACFM x Δ p x annual operating hours

Where : 1.81 x 10 -4 

### is a proportionality constant ACFM = the actual cubic feet per minute exhaust treated Δ p is the equipment pressure drop in inches of water column (w.c.)
The following Table 4-4 is presented to illust rate the power consumption requirements of the four common types of partic ulate control devices. Each technique has predictable energy consumption in terms of the pressure drop associ ated with the control option. For example, an ESP has numerous parallel flat plates with electr ode wires to charge the particulate passing into the collector. The pressure dr op within the device is very low. Fabric filter baghouses expectedly have a higher pressu re drop due to the fabric filter passages which are much smaller than the widely spaced plates in an ESP. The spinning motion of the multiple cyclone (MC) leads to the loss of considerable energy in a ty pical 4” w.c. drop, and the venturi scrubber (VS), attains its relatively high collec tion efficiency at the expense of up to a 100” pressure drop, required for fine particulate collection. The Colstrip scrubber pressure drop for Units 1&2 is on
the order of 35” of water.

### 4-14 Table 4-4: Representative Control Equipment Pressure Drops
Control Option Typical Δ p Reference Table or Page No. (inches w.c.)
ESP 0.09 to 0.38 EPA, 2002 Pg. 3-34 Section 6 FF 6 to 7 EPA, 2002 Pg. 1-47 Section 6 MC 4 Vendor Estimate VS < 100 AWMA Table 5.4-5

4.2.1.4 Non-Air Quality Environmental Impacts The ESP or FF particulate cont rols for Colstrip, would gene rate a new particulate waste stream. The current ash collected by the sc rubbers would remain, however, operation of particulate controls to collect an additional 70 percent of current particulate emissions, 562 tons per year from each unit. The cost for dis posal of this ash is estimated at $40/ton.

4.2.1.5 Remaining Useful Life The life of the Colstrip boilers is expected to exceed the st udy period and is projected to have no effect on the costing an alyses for this facility.

4.2.1.6 Visibility Modeling The predicted visibility impacts from the pr esent (base case) Colstrip particulate, SO 2 

### and
NO x 

### emissions and for the altern ative filterable particulate co ntrol level evaluated (0.015 lb/MMBtu) are summarized in Table 4-5. Shown in the table are the hi ghest of the annual 98th percentiles of daily modeled vi sibility impacts among the three years modeled (2001-2003) and
the five Class I areas modeled. The highest of those visibility impacts among the five Class I areas modeled are presented. For the modeled c ontrol alternative, the emissions of filterable particulate were at its contro lled level (0.015 lb/MMBtu) and the emissions of the other pollutants were at their base case levels. Also presented in the table are the largest differences between the 98th percentile valu es for the base case and the evaluated particulate control alternative at any of the Class I areas. This difference is shown relative to the base case. The visibility modeling result s are described and presented in more detail in Section 4.3 and Appendix B.

### 4-15 Table 4-5: Summary of Mo deling Results for Particulate

Emissions (1) Control Option lb/MMBtu lb/hr Max 98th Percentile Prediction (deciviews) Deciview Difference Relative to the

Base Case Base Case 0.047/0.058(f) 0.038 (c) 187.2/226.0 (f) 151.3/148.1 (c) 2.233 (2)
---

NSPS Case 0.015 (f) 0.038 (c) 59.7/58.5(f) 151.3/148.1 (c) 2.21 (2) 0.042 (3)

NOTES: (1) "f" refers to filterable and "c" refers to condensable particulate. (2) The maximum deci view impact occurred at the UL Bend Class I area. (3) The maximum deciview di fference occurred at the Theodore Roosevelt National Park.



### 4.2.2 Sulfur Dioxide Controls
The sub-bituminous coal fired boiler at Colstrip utilizes lo w-sulfur (<1 weight percent sulfur) Powder River Basin coal. With long term contracts for the use of such coal, the baseline emissions for the Colstrip boilers are al ready low at 0.72 to 0.80 lb/MMBtu of SO 2 

### , maximum 24-hr average, and are typically lower at 0.40 lb/MMBtu, which is representative of a typical 30- day average emission rate considering the actual sulfur content of the fuel and the removal efficiency of the wet scrubbers. The Cols trip boilers are equi pped with CEMS for SO 2 

### which were used to determine the baseline maximum 24-hr average SO 2 

### emission rates.

4.2.2.1 Control Technologies Coal cleaning to reduce SO 2 

### emissions in addition to that performed prior to delivery to Colstrip would have no effect on SO 2 

### emissions. PRB coal already has low sulfur levels and any further reduction in this fuel sulfur content by any mechanical means is not expected. The option to gasify the coal for sulfur removal is a complete change in the method of operation for Colstrip which was given no consideration. The controls evaluated to improve SO 2 

### control below the levels attained by using the low-sulfur content coal included dry scrubbing techniques and wet scrubbing (FGD) technology. With emissions already at very lo w levels, the dry techniques are limited in their ability to attain very high SO 2 

### removals without impacting the particulat e emissions with the existing scrubbers.
In view of the alkaline nature of PR B coal, the inherent reaction between SO 2 

### and flyash is what accounts for an average SO 2 

### emission rate (from CEMS data) of 0.40 lb/MMBtu. PPL estimates

### 4-16 that an increase in SO 2 

### removal can be attained by chemical addition using inje ction technologies (injection of lime). If this inj ection is limited to quantities that do not impact the operation of the current scrubbers, it is estimated that the curren t removal efficiency can be increased from 75% to about 88%, i.e., an additional 50% removal of SO 2 

### to a new emission ra te of 0.20 lb/MMBtu can be achieved before impacti ng the scrubber operation. As the amount of lime is increased, operation of the scrubbers will be affected. Scaling is projected to begin at levels of control exceeding 88 percent and become significant as removal efficiency increases and achieves an emission ra te of 0.15 lb/MMBtu. Th is will incur additional maintenance expenses and outages representing an additional cost of implementing this option. This could also require back-up scrubbers to reduce downtime for descaling. O&M time, however, will be greater despit e the additional scrubbers.

4.2.2.2 Cost of SO 2 

### Controls PPL used experience from operation of the we t scrubbers on Units 3&4 at Colstrip to estimate the costs of lime inject ion and O&M costs for Colstrip Units 1&2. Three options were evaluated that are summarized in Table 4-6, see Appendix A, Tables A4-6(a), A4-6(b) and A4- 6(c) for complete details. Control options incl ude the basic addition of lime injection equipment for Units 1&2, the cost of the lime, and minimal O&M costs. To attain the presumptive limit, the equipment cost doubles and there is additiona l expense for descaling and downtime. It is important to point out that the Cols trip boilers are currently equipped with wet scrubbers with a removal efficiency greater than 50% and thus the presumptive limit does not apply to Units 1&2. While the presumptive limit may be technically feasible, modifications to
the current scrubbers to increase SO 2 

### removal incurs excessive O&M costs and may require backup scrubber modules at excessive incremental costs.

4.2.2.3 Energy The pressure drop of each of the venturi scr ubbers is maintained in the range of 17 to 20
inches of water column. The addition of lime to attain the 25% increase in SO 2 

### removal will be accompanied by little to no increase in pressure drop, but a small increase in pump power consumption. This is included in the cost analysis as an annual cost of additional operations and maintenance (O&M) expenses of an estimated $125,000 per year.

### 4-17 Table 4-6: PPL BART SO 2 

### Control Cost Summary (Per Unit)

Option Description Total Annual Tons controlled Cost Incremental Cost ($) Effectiveness CE $/ton (CE) $/ton

Lime Addition (88%control) $700,035 3209 $218 Lime Addition (91%control) $2,000,071 4011 $499 $1,621 Added Scrubber Module $5,183,993 4011 $1,292 $5,590



### To achieve the higher removal of SO 2 

### of 70% over that currently attained, the additional sprays and pumps will increase O&M to an estimated $390,000. In summary, energy impacts of the addition of lime to the venturi scrubbers serving Units
1&2 will be minimal and have been included in the cost analysis based on experience from Colstrip Units 3&4.

4.2.2.4 Non-Air Quality Environmental Impacts The most significant impact of adding lime to the scrubbing equipment serving Units 1&2 will be the scaling that will occur at high lime addition rates. This will appear as lost revenue from downtime for scrubber descaling. The third option listed in Table 4-6 with the
added scrubber module will eliminate the dow ntime but not the O&M costs to descale one scrubber unit while other modules remain operational.

4.2.2.5 Remaining Useful Life The life of the Colstrip boilers is expected to exceed the st udy period and is projected to have no effect on the costing an alyses for this facility.

4.2.2.6 Visibility Modeling The predicted visibility impacts from the present (base case) Colstrip SO 2 

### , NOx and particulate emissions and for the alternative SO 2 

### control levels evaluated are summarized in Table 4-7. Shown in the table are the highest of the annual 98th percentiles of daily modeled visibility impacts among the th ree years modeled (2001-2003) and the five Class I areas
modeled. For the modeled control alternatives, the emissions of SO 2 

### were at its controlled level and the emissions of the other poll utants were at their base case levels. Also presented in the

### 4-18 table are the largest differences between the 98th percentile values for the base case and the evaluated control alternatives at any of the Class I areas. These differences are shown relative to the base case and also incrementally relative to the immediately preceding control alternative in
terms of the level of em issions reduction attained. The visibility modeling results are described and presented in more detail in Section 4.3 and Appendix B.

Table 4-7: Summary of Modeling Results for SO 2

Deciview Difference Emissions Control Option lb/MMBtu lb/hr Max 98th Percentile Prediction (deciviews) Relative to Base Case Increment

Base Case 0.72/0.80 2612.0/2828.0 2.233 --- --- Lime Injection (50% reduction from Present) 0.36/0.40 1433.4/1558.9 2.000 0.422 0.422
Lime Injection (63% Reduction from Present) 0.27/0.30 1075.1/1169.2 1.954 0.505 0.091

Add a Scrubber Vessel 0.15 597.3/584.6 1.832 0.651 0.146

NOTE: The maximum deciview impacts and di fferences occur at either the UL Bend, Theodore Ro osevelt or North Absaroka Class I areas.



### 4.2.3 NO x 

### Controls The Colstrip boilers are tangentially fired units equipped with low-NO x 

### burners. A
review of CEMS data reveal ed that the maximum 24-hr NO x 

### emission rates during the 2001 to 2003 evaluation period were 0.45 lb/MMBtu for Unit 1 and 0.53 lb /MMBtu for Unit 2. While these values were used for BART modeling, a ba seline value of 0.35 lb/MMBtu was used as a typical NO x 

### emission rate representative of a 30-day average for the BART cost analysis as applicable to either unit. This is maintain ed by operation of the current burners and closecoupled overfire air presently in operation at Colstrip.

### 4-19 4.2.3.1 Control Technologies PPL evaluated three control options for NO x 

### reduction at Colstrip that include SOFA, SNCR, and SCR add-on controls. Adding SOFA a nd readjustment of the entire air distribution to the firebox is predicted to reduce NO x 

### to 0.18 lb/MMBtu. The add ition of SNCR is predicted to produce little additional NO x 

### reduction (to 0.16 lb/MMBtu) over that obtained by SOFA at significant additional cost. A hot-side SCR to reduce NO x 

### to the presumptive level for tangentially fired sub-bitumi nous coal-fired boilers of 0.15 lb/MMBtu was analyzed. Reburning technology for application to Cols trip was not evaluated. This technology option is considered as the equi valent of SOFA. Bo th technologies produc e fuel-rich zones in
the combustion chamber which can reduce NO x 

### emissions by significant amounts. Therefore,
PPL limited the control evaluation to SOFA with an anticipated reduction to 0.18 lb/MMBtu.

4.2.3.2 Cost of NO x 

### Controls The costing analysis of the various control options for NO x 

### reduction are summarized in Tables 4-8, see Appendix A, Tables A4-8(a), A4-8 (b) and A4-8(c) for complete details. Table 4- 8 utilizes cost estimations for adding SOFA to the LNB technology, based on recent upgrades to
the burners in Units 3&4 at Cols trip. Reduction from an emission rate of 0.35 lb/MMBtu to 0.18
lb/MMBtu results in a CE of $451/ton (in 2007 dollars) of NO x 

### controlled.

Table 4-8: PPL BART NO x 

### Control Cost Summary (Per Unit)

Option Description Total Annual Tons controlled Cost Incremental Cost ($) Effectiveness CE $/ton $/ton

Separated Over-Fire Air $1,131,633 2509 $451 SNCR $2,979,427 3049 $977 $3,424 SCR $7,289,482 3209 $2,272 $26,938



### Cost for conventional SNCR and SCR t echnologies were estimated using the EPA Control Cost Manual (U.S. Environmental Prot ection Agency, EPA Air Pollution Control Cost Manual, 6 th 

### ed., EPA-452-02-001, January 2002). The cost analysis for application of SNCR is summarized in Table 4-8 which presents the CE calculations for reduction of boiler NO x 

### emission rate of 0.35lb/MMBtu to 0.18 lb/MMBtu using SOFA. With th e SNCR control option
estimated to result in an emission rate of 0.16 lb/MMBtu, the CE of $977/ton for SNCR is not

### 4-20 justifiable. Similarly, SCR controls, applied to a typical boiler emissi on rate of 0.35 lb/MMBtu shows a CE value (Table 4-8) of $2,272/ton of NO x 

### necessary to attain the presumptive limit of
0.15 lb/MMBtu.

4.2.3.3 Energy The NO x 

### control alternatives in Ta ble 4-8 each require additional energy. Each detailed cost calculation includes the electrical fan pow er consumption to run the SOFA fans, to pump urea solution, or to overcome SCR catalyst pressure drop. While these costs are a relatively small portion of the overall cost of control, they have been included in the analysis as part of the annualized cost for each option.

4.2.3.4 Non-Air Quality Environmental Impacts While SOFA may have impacts on particulat e matter emissions with a slight change in LOI, this is of little impact for Colstrip boilers which use scrubbing for control of particulate and
hence there is no salable ash. The addition of chem ical reagents in SNCR and SCR controls adds equipment for its storage and use. The additional costs of chemicals and catalysts in the case of SCR have been included in the cost analysis.

4.2.3.5 Remaining Useful Life The life of the Colstrip boilers is expected to exceed the st udy period and is projected to have no effect on the costing an alyses for this facility.

4.2.3.6 Visibility Modeling The predicted visibility impacts from the present (base case) Colstrip NO x 

### , SO 2 

### and particulate emissions and for the alternative NO x 

### control levels evaluated are summarized in Table 4-9. Shown in the table are the highest of the annual 98th percentiles of daily modeled visibility impacts among the th ree years modeled (2001-2003) and the five Class I areas
modeled. For the modeled control alternatives, the emissions of NO x 

### were at its controlled level and the emissions of the other poll utants were at their base case levels. Also presented in the table are the largest differences between the 98th percentile values for the base case and the evaluated control alternatives at any of the Class I areas. These differences are shown relative to the base case and also incrementally relative to the immediately preceding control alternative in
terms of the level of em issions reduction attained.

### 4-21 Table 4-9: Summary of Modeling Results for NO x

Deciview Difference Emissions Pollutant Control Option lb/MMBtu lb/hr Max 98th Percentile Prediction (deciviews) Relative to Base Case Increment

NOx Base Case 0.45/0.53 1798.0/1955.0 2.233 --- ---
SOFA 0.23/0.27 915.8/1052.2 1.781 0.573 0.573

SNCR 0.21/0.24 836.2/935.3 1.713 0.638 0.068

SCR 0.15 597.3/584.6 1.584 0.801 0.163
NOTES: The maximum deciview impacts and di fferences occur at either the UL Bend or the Theodore Roosevelt Class I areas.



### The visibility modeling results are described and presented in more detail in Section 4.3 and Appendix B.

4.3 Visibility Modeling Pr ocedures and Results Section 4.3.1 describes the general visibil ity modeling procedur es and Section 4.3.2 summarizes the results. The modeling procedures and results are described in more detail in Appendix B.

4.3.1 General Modeling Procedures
The CALPUFF model was used to assess the impact of emissions from Colstrip BART eligible Units 1&2 on visibility in the five fede ral mandatory Class I areas within 300 km of the units, as identified in Section 2.3 and shown in Figure ES-1. CA LPUFF (Scire et al., 2000) is EPA's guideline model for long range transpor t and their recommended model for BART analyses. Modeling was conducted with three year s of hourly meteorological data for the years 2001, 2002 and 2003. The CALPUFF and CALMET model setup and input meteorological and emissions data were obtained from the WRAP website ( http://pah.cert.ucr.e du/aqm/308/bart.shtml ) 

### provided by EPA Region 8 in a February 28, 2007 letter to PPL identifying Colstrip Units 1&2 as subject to BART and providing preliminary modeling results. The modeling conducted by TRC for PPL is
based on those data files w ith the following exceptions:

### 4-22 • Speciation of filterable and condensable pa rticulate emissions was revised by PPL based on stack test data available during the modeling years (2001-2003) and AP-42 factors.

• There were a few modifications to th e modeling as described in Appendix B.

The present (base case) SO 2 

### , NO x 

### and particulate emissions as modeled are presented in Tables 2-1 and Table 2-2. The particulate em issions presented include a breakdown of the particulate emissions by species and size fracti on. Table 4-10 presents the emissions (and a summary of the modeling results as described below) for each of the control scenarios evaluated.
These modeled SO 2 

### , NO x 

### and particulate emissions are based on the maximum actual daily operation of Units 1&2 during the three-year mo deling period as described in Section 2.2. The present base case visibility impact of Cols trip Units 1&2 in each Class I area in terms of the deciview haze index was determined by co mparing the combined visibility impact of the modeled units’ present emissions and the annual average background visibility level provided in the EPA/WRAP files against the background leve l alone. The similarly modeled visibility impacts of each of the control alternatives were then compared against the base case and each other to determine the degree of visibility improvement for each control alternative.

4.3.2 Summary of Modeling Results The highest of the annual 98th percentiles of daily modeled visibility impacts under the present base case particulate emissions and th e emissions control scenarios evaluated are presented and compared for each pollutant in Table 4-10. The 98th percentile comparison level, using the highest 98th percentile prediction from among the years modeled, is recommended by EPA as a visibility metric. The values presen ted are the highest of those visibility impacts among the five Class I areas evaluated. A summa ry of the results for each Class I area is presented in Appendix B. Under the present emissions case (base case), as presented in Table 4-10, the maximum of the annual 98th percentile Units 1&2 daily visi bility impacts is 2.233 d eciviews and occurs at the UL Bend Class I area. The deciview impact for each of the control alternatives are also provided in the table. For each control altern ative modeled, the emissions of the controlled

### 4-23 Table 4-10: Summary of Modeling Results

Deciview Difference Emissions (1) Pollutant Control Option lb/MMBtu lb/hr Max 98th Percentile Prediction (deciviews) Relative to Base Case Increment

SO 2 Base Case (2) 0.72/0.80 2612.0/2828.0 2.233 (3)
--- --- Lime Injection (50% reduction from Present) 0.36/0.40 1433.4/1558.9 2.000 0.422 0.422

Lime Injection (63% Reduction from Present) 0.27/0.30 1075.1/1169.2 1.954 0.505 0.091

Add a Scrubber

Vessel 0.15 597.3/584.6 1.832 0.651 0.146

NOx Base Case (2) 0.45/0.53 1798.0/1955.0 2.233 --- ---
SOFA 0.23/0.27 915.8/1052.2 1.781 0.573 0.573

SNCR 0.21/0.24 836.2/935.3 1.713 0.638 0.068

SCR 0.15 597.3/584.6 1.584 0.801 0.163

PM Base Case (2) 0.047/0.058(f) 0.038 (c) 187.2/226.0 (f) 151.3/148.1 (c) 2.233 --- ---

NSPS Case 0.015 (f)) 0.038 (c) 59.7/58.5 (f) 151.3/148.1 (c) 2.213 0.042 (2) 0.042

NOTES: (1) “f" refers to filterable and "c" refers to condensable particulate. (2) The base case is the same for all three pollutants. (3) The maximum deciview impact of the base case occurred at the UL Bend Class I area. For other cases shown, the maximum impact or difference occurred at either th e UL Bend or Theodore Roosevelt or North Absaroka Class I areas.

### pollutant were at its controlled level and the emissions of the non-contro lled pollutant s were at their base case levels. Also pr ovided in the table ar e the net changes in the highest annual 98th percentile deciview impacts from each pollutant fo r each control alternative. These are provided
relative to the base case and also incrementall y relative to the immedi ately preceding control alternative in terms of the level of emissions reduction attained. The net changes presented are highest net change in visibility at any of the Class I areas evaluated.

4-24

### 5.0 SUMMARY AND CONCLUSIONS The Best Available Retrofit Technology (B ART) program was established under the federal Regional Haze Rule to evaluate possi ble retrofit emissions control technology for visibility impairing pollutants emitted from cer tain combustion units constructed between 1962 and 1977 that could potentially cause or contribute to a degradation of visibility at Prevention of Significant Deterioration (PSD ) mandatory Class I Areas. Colstrip Units 1&2 were determined to be BART-eligible under the Federal Regional Haze Rule by the EPA Region 8. The Colstrip are already relatively low particulate emitting units due to efficient operation and good combustion control. EPA’s BART Guideline approach has been applied to Colstrip Units 1&2 to identify the “best system of continuous emissi on reduction” applicable to the units for f ilterable particulate control, SO 2 

### reduction and the control of NO x 

### . A range of demonstrated control alternatives for large tangentially-fired coal boilers was evalua ted considering costs, energy and environmental impacts, remaining useful life of the units and modeled visibility improvements. Electrostatic precipitators (ESP) and fabric filters (baghouses were evaluated for additional filterable particulate control. Mechanic al collection and enhanced wet scrubbers were considered for particulate control but not furt her evaluated. Mechanical colle ction was not further evaluated because that technology is used as a pre-filter and does not pe rform well as a retrofit option.
Enhancement to the wet scrubber was also not evaluated further as th e existing particulate emissions level is already so low that there is little room for further improvement of the scrubber. Modified wet scrubbing by the existing venturi scrubbers to include lime injection and the
addition of an additional scrubber vess el were evaluated for additional SO 2 

### control, and separated over-fire air, selective non-catalyt ic reduction and selective catalyt ic reduction were evaluated
for NO x 

### control.
The CALPUFF model was used to evaluate the visibility impacts of present emissions from Colstrip Units 1&2 and the BART control alternatives. The model setup and input meteorological and emissions data were obtaine d from EPA/WRAP files. The modeling was
based on those data files with a few modifications . The particulate emissions were revised based
on stack test data and there were a few modeli ng adjustments as described in Appendix B. Modeling was conducted to determine visibility impacts in the five mandatory Class I areas within 300 km of Colstrip. The cost analyses an d modeling were based on actual emissions. For the cost analyses typical emission rates representative of average 30-day emissions were used.

5-1

### For the modeling analyses maximum daily em issions during the m odeling years (2001-2003)
were used. The results of the cost and modeling analyses are presented in Tables 5-1 and 5-2. The highest modeled annual 98 th 

### percentile daily visibility impact of emissions from Units 1&2 based on present (base case) maximum actual load is pr edicted to occur in the in the UL Bend National Wildlife Refuge (NWR) Class I area and is 2.233 deciviews. From a visibility improvement basis with respect to filterable particulate matter, only a 0.042 deciview reduction, which is not visually discernable, would result from installation of
either ESPs or fabric filters. Consequently, implementation of additional particulate control at Colstrip is not warranted. With respect to sulfur dioxide only a 0.4 22 deciview reduction is achieved with lime addition to improve SO 2 

### removal to 88 percent. This is below a level that is visually discernable. The incremental improve ment through installation of any of the other technologies considered is 0.146 de civiews or less, which is not visibly discerna ble. Based upon the level of visibility improvement implemen tation of these control technologies are not warranted. And with respect to nitrogen oxides only a 0.573 deciview improvement results from implementation of SOFA. This is likely belo w a level that is visu ally discernable. The incremental improvements from controls beyo nd SOFA are 0.163 deciviews or less. Again, implementation of the controls is not warranted based upon the level of visibility improvement.

5-2

### Table 5-1: Current / NSPS / Control Options Cost Summary FOR THE PPL MONTANA, LLC, COLSTRIP UNITS 1 AND 2 (EACH UNIT)

Particulate Matter Sulfur Dioxide Nitrogen Oxides Rate Units Rate Units Rate Units Control Current ( 1 ) Emission rate 0.050 lb/MMBtu 0.4 lb/MMBtu 0.35 lb/MMBtu COFA ( 2 )

BDT ( 3 ) from 2006 NSPS 0.015 lb/MMBtu 1.4 lbs SO 2 /MW out 1.0 lb/MW out New Sources (0.15 lb/MM Btu in) (0.11 lb/MM Btu in) Cost Effeciveness Calcs Cost Effeciveness Calcs Option Evaluated Option Evaluated CE ( 7 ) Inc CE Option Evaluated CE ( 8 ) Inc CE Rate Rate Rate lb/MMBtu $/ton lb/MMBtu $/ton $/ton lb/MMBtu $/ton $/ton Control Added ESP 0.015 $38,738 Present 0.4 $0 Present 0.35 Options Added FF 0.015 $29,599 WS-FGD ( 4 ) 0.2 $218 SOFA 0.18 $451 WS-FGD ( 5 ) 0.15 $499 $1,621 SNCR 0.16 $977 $3,424 WS-FGD ( 6 ) 0.15 $1,292 $5,590 SCR 0.15 $2,286 $30,786
Notes 1) Colstrip Unit 1 = 0.047, Unit 2 = 0.058 lb/MMBtu ; 0.05 lb/MMBtu used as representative of each unit 2) Low-NOx Burners with Close-Coupled Overfire Air 3) BDT = "Best Demonstrated Technology" - From FR Vol. 71, No. 38, Monday, February 27,2007 Final Rule (NSPS for EUSGUs) - the 2006 revised standards were revised to a gross megawatt output basis (equivalent in lb/M MBtu input values listed in paren) 4) Wet Scrubber-Flue Gas Desulfurization; actual emissions are 0.40 lbs/MMBtu (per CEMS); adding lime to the scrubber will reduce emissions by 50% 5) Similar to 3 but additional downtime due to scaling to attain a reduction to 0.15 lbs/MMBtu 6) Similar to (4), but more lime and an additional scrubber (per unit) necessary to reach the presumptive limit 7) Control options considered separately; incremental cost of scrubbing options compares the relative additional removal to the baseline lime injected scrubber option 8) Control options considered separately; incremental cost of SNCR and SCR reflect the relative cost of increased NOx removal



### Table 5-2: Modeled Visibili ty and Visibility Improvements

Modeled Modeled Modeled Rate (1)(2) Prediction (3) from Rate (1)(2) Prediction from Rate (1)(2 ) Prediction from Option (lb/MMBtu) (deciviews) Present Inc (6) Option (lb/MMBtu) (deciviews) Present Inc (6) Option (lb/MMBtu ) (deciviews) Present Inc (6) Present 0.047/0.058 2.233 n/a n/a Present 0.72/0.80 2.233 n/a n/a Present 0.45/0.53 2.233 n/a n/a New ESP 0.015 2.213 0.042 0.042 WS-FGD(4) 0.36/0.40 2.000 0.422 0.422 SOFA 0.23/0.27 1.781 0.573 0.573 Added FF 0.015 2.213 0.042 0.042 WS-FGD(5) 0.27/0.30 1.954 0.505 0.091 SNCR 0.21/0.24 1.713 0.638 0.068 WS-FGD(6) 0.15 1.832 0.651 0.146 SCR 0.15 1.584 0.801 0.163

Notes: (1) The modeled emission rate is the rate corresponding to the maximum daily emissions during the modeling years (200 1-2003). (2) If Unit 1 and Unit 2 emission rates are different, they are indicated as Unit 1/Unit 2 rates. (3) Prediction is from all three pollutants at present emissions except the one being controlled (4) See corresponding footnote in Table ES-1. (5) See corresponding footnote in Table ES-1. (6) See corresponding footnote in Table ES-1. (7) Maximum improvements shown may occur at differeent Class I areas that the maximum prediction among all Class I areas. Improvement (7) Improvement (7) Improvement (7) Filterable Particulate Sulfur Dioxide Nitrogen Oxides



### 5-3

### 6.0 REFERENCES

AWMA, Air Pollution Engineering Manual, Air & Waste Management Association, Anthony J. Buonicore and Wayne T. Davis, eds., Van Nostrand Reinhold, 1992.
EC/R, Stationary Source Contro l Techniques Document for Fi ne Particulate Matter, EPA Contract No. 68-D-98-026, Work Assignment No. 0-08, EC/R Incorporated, October 1998.
EPA 2002, Air Pollution Control Cost Manual , U.S. EPA, Volume 2, Sixth Ed., EPA-452-02- 001, January 2002.
EPA, 2003, Guidance for Estimating Natural Visi bility Conditions Under the Regional Haze Rule , http://www.epa.gov/ttn /oarpg/t1/memoranda/rh_envcurhr_gd.pdf
EPA 2004, Supplemental Air Quality Modeling T echnical Support Docume nt (TSD) for the Clean Air Interstate Rule, http://www.epa.gov/cair/pdfs/saqmtsd.pdf
Federal Register , Vol. 64, No. 126, July 1, 1999, pgs 35713-35774.
Federal Register , Vol. 70, No. 38, February 28, 2005, pgs 9706-9735.
Federal Register , Vol. 70, No. 128, July 6, 2005, pgs 39104-39172.
Federal Register , Vol. 71, No. 38, February 27, 2006, pgs 9866-9873.
NPS, http://www2.nature.nps.gov/air/permits /ect/ectOilFir edBoiler.cfm
Scire, J, et al. 2000, A User’s Guide for the CALPUFF Dispersion Model , Earth Tech, Inc. January 2000.

6-4

# APPENDIX A:
DETAILED COST CALCULATIONS

Table numbers in this appendix refer back to the summary tables in Section 4 of the report (e.g., Table A4-3(a ) in this appendix supports Table 4-3 in Section 4 of this report).

### Table A4-3(a): PPL BART Cost Analysis Electrostatic Precipitato r Particulate Control

### Table A4-3(a) continued

### Table A4-3(b): PPL BART Cost Analysis Pulse Jet - Fabric Filter for Additional Particulate Control

### Table A4-3(b) continued

### Table A4-6(a): PPL BART Cost Analysis Wet Scrubbing Sulfur Dioxide Control (Option 1)

### Table A4-6(b): PPL BART Cost Analysis Wet Scrubbing Sulfur Dioxide Control (Option 2)

### Table A4-6(c): PPL BART Cost Analysis Wet Scrubbi ng Sulfur Dioxide Control (Option 3)

### Table A4-8(a): PPL B ART Cost Analysis Low NO x 

### Burner Controls with SOFA

### Table A4-8(b): SNCR Cost Analysis for Colstrip Unit 1

### Table A4-8(c): SCR Cost Analysis for Colstrip Unit 1

### Table A4-8(c) continued

# APPENDIX B
CALPUFF APPLICATION FOR BART
ASSESSMENTS AT PPL COLSTRIP UNITS
1&2

# CALPUFF Application for BART Assessments at PPL Facility Colstrip Units 1&2 in Montana for the UL Bend, Theodore Roosevelt, Washakie, North Absaroka, and Yellowstone Class I Areas

Prepared For:
PPL Montana, LLC Billings, Montana

Submitted By : TRC Environmental Corporation 650 Suffolk Street, Wannalancit Mills Lowell, Massachusetts 01854 (978) 970-5600

August 2007

### TABLE OF CONTENTS

Page



### 1.0 INTRODUCTION .............................................................................................................. 1
2.0 SOURCE DESCRIPTION .................................................................................................. 3
3.0 GEOPHYSICAL AND M ETEOROLOGICAL DATA ..................................................... 7
3.1 Terrain ..................................................................................................................... 7 3.2 Land Use ................................................................................................................. 9 3.3 Meteorological Data Base....................................................................................... 9 3.4 Air Quality Monitoring Data ................................................................................ 14
4.0 AIR QUALITY MODELING METHODOLOGY .......................................................... 17
4.1 Model Selection .................................................................................................... 17 4.2 Modeling Domain Configuration .......................................................................... 17 4.3 Meteorological Modeling Options ........................................................................ 17 4.4 CALPUFF Computational Domain and Receptors ............................................... 18 4.5 Dispersion Modeling Options ............................................................................... 18 4.6 Visibility Calculations .......................................................................................... 20
5.0 RESULTS ......................................................................................................................... 23
6.0 REFERENCES ................................................................................................................. 26

i

### LIST OF FIGURES

Page


### Figure 2-1. Aerial photo of the PPL Colstrip facility 4 Figure 3-1. Terrain contours (m MSL) at 2 km resolution for the 780 km by 570 km CALMET and CALPUFF computational domains. The Class I areas and the Colstrip facility are also shown. 8 Figure 3-2. Dominant land use categories at 2 km resolution on the CALMET and CALPUFF modeling domains. Class I ar eas and the location of Colstrip PPL are also shown. 10 Figure 3-3. Surface stations. The stations included in the SURF.DAT files are plotted in purple. For reference in orange ar e shown the stations included in the original SURF.DAT files. As the figure shows better coverage of the domain is achieved by using the ISHWO data base. 13 Figure 3-4. Locations of ozone monitoring statio ns used in the CALPUFF modeling. 15 Figure 4-1. Locations of receptors at UL Bend, North Absaroka, Theodore Roosevelt, Washakie and Yellowstone Class I areas. 19

ii

### LIST OF TABLES

Page



### Table 2-1. Colstrip: Source Parameters and Emission Rates – Base Case 5 Table 2-2. Colstrip: Particle Speciation – Base Case 5 Table 2-3. Colstrip: Emissions for Base Case and Control Alternatives 6 Table 3-3. Meteorological Data Sources and Parameters Available 11 Table 3-4. NWS Hourly Surface Stations 12 Table 3-5. Ozone Stations 16 Table 4-1. Summary of Background Natural Visibility Conditions 22 Table 4-2. Monthly f(RH) values based on the Representative IMPROVE Site Location, for Visibility Method 6 applications 22 Table 5-1. Summary of Visibility Results for Base Case 24 Table 5-2. Summary of Visibility Results for Alternative 1 (SO 2 

### Control Efficiency Increased to 88%) 24 Table 5-3. Summary of Visibility Results for Alternative 2 (SO 2 

### Control Efficiency Increased to 91%) 24 Table 5-4. Summary of Visibility Results for Alternative 3 (SO 2 

### Reduced to 0.15 lb/MMBtu) 24 Table 5-5. Summary of Visibility Results for Alternative 4 (NO x 

### Reduced with SOFA) 25 Table 5-6. Summary of Visibility Results for Alternative 5 (NO x 

### Reduced with SNCR) 25 Table 5-7. Summary of Visibility Results for Alternative 6 (NO x 

### Reduced to 0.15 lb/MMBtu with SCR) 25 Table 5-8. Summary of Visibility Results for Alternative 7 (Filterable PM Reduced to 0.015 lb/MMBtu) 25

iii

### 1.0 INTRODUCTION TRC Environmental Corporation has conducted a Best Available Retrofit Technology (BART) analysis for Units 1&2 at PPL Montana, LLC's Cols trip power plant. This analysis followed the “Draft CALPUFF BART Modeling Protocol For Federal Mandatory Class I Areas” prepared by the Montana Department of Environmental Quality (MDEQ), dated September 2006, called ‘Montana Protocol’ hereafter. A few deviations from the Montana Protocol were made in the analysis and detailed in this report. Montan a Protocol, as well as the CALPUFF and CALMET model setup and input meteorological and emissions data described in the Montana Protocol were obtained from the WRAP website (http://pah.cert. ucr.edu/aqm/308/bart.shtml) provided by EPA Region 8 in a February 28, 2007 letter to PPL iden tifying the Colstrip units as subject to BART and providing preliminary modeling results. In this report, results are presented for Units 1&2 of the Colstrip PPL plant. Colstrip PPL plant is located east of Billings, Montana.

On July 6, 2005 the US Environment Protection Agency amended the Federal Register document, 40 CFR Part 51 in order to introduce new National Regional Haze Regulations for Best Available Retrofit Technology. The regional haze rule requires States to submit implementation plans (SIPs) to address regional haze visibility impairment in 156 Federally-protected parks and Wilderness Areas (WA), commonly referred to as “Class I Areas”. The final rule included a requirement for BART for certain large stationa ry sources that were put in place between 1962 and 1977. The regional haze rule uses the term “BART-eligible source” to describe those sources which have the potential to emit 250 tons or more of a visibility-impairing air pollutant, were put in place between August 7, 1962 and August 7, 1 977 and whose operations fall within one or more of 26 specifically listed source categories, of which fossil-fuel fired steam electric plants of more than 250 million British thermal un its (BTU) per hour heat input is one.

BART review is required when the source emits any air pollutant which may reasonably be anticipated to cause or contribute to any impa irment of visibility in any Class I area. In identifying a level of control of BART, States are required by section 169A(g) of the CAA to consider; (a) the costs of compliance, (b) the ener gy and non-air quality environmental impacts of compliance, (c) any existing pollution control techno logy in use at the source, (d) the remaining useful life of the source and (e) the degree of visibility improvement which may reasonably be anticipated from the use of BART.

The purpose of the modeling was to assess the visibility impacts of sulfur dioxide (SO 2 ), nitrogen oxides (NO x ) and primary particulate matter (PM) emis sions (including primary sulfuric acid, H 2 SO 4 , emissions), at those Class I areas that are locat ed within 300 km from the plant. A total of five Class I areas are located within this radius: North Absaroka WA, Theodore Roosevelt National Park (NP), UL Bend WA, W ashakie WA and Yellowstone NP.

The topography of the modeling domain includes areas of complex terrain. There is the potential for terrain effects, both on the meteorological fi elds and in terms of plume-terrain interaction

1 Introductioneffects. The CALMET and CALPUFF non-steady-state models (Scire et al., 2000a,b) were used for the modeling analysis. The U.S. Environmen tal Protection Agency (EPA) has recommended CALPUFF as the preferred model for BART analyses (U.S. EPA, 2005). The CALPUFF modeling system is the regulatory Guideline Model for Class I impact assessments and other long range transport applications and on a case-by-case basis for near-field applications involving complex flows (U.S. EPA, 2003a). CALPUFF is al so recommended by both the Federal Land Managers Air Quality Workgroup (FLAG, 2000) and the Interagency Workgroup on Air Quality Modeling (U.S. EPA, 1998).

CALMET is a diagnostic meteorological model that produces three-dimensional wind fields based on parameterized treatments of terrain effects such as slope flows, terrain blocking effects, and kinematic effects. Meteorological observations were used to determine the wind field in areas where the observations are representative. The hourly meteorological datasets developed from fifth generation Penn State/NCAR (National Center For Atmospheric Research, Boulder, CO) three-dimensional mesoscale weather predicti on model MM5 for 2001-2003 were used to help define the initial estimate of the wind fields. The horizontal resolution of data is 36 km for all three years.

CALPUFF is a non-steady-state puff dispersion mode l. It accounts for spatial changes in the CALMET-produced meteorological fields, variability in surface conditions (elevation, surface roughness, vegetation type, etc.), chemical transf ormation, wet removal due to rain and snow, dry deposition, and terrain influen ces on plume interaction with the surface. CALPUFF contains a module to compute visibility effects, based on a humidity-dependent relationship between particulate matter concentrations and light ex tinction, as well as wet and dry acid deposition fluxes. The refined meteorological and dispersi on modeling simulations ha ve been conducted for a three-year period (2001-2003). Visibility impacts have been predicted by the model at receptors in the Class I areas.

In Montana Protocol, Table 3.0 lists the ve rsions of the CALMET, CALPUFF, POSTUTIL and CALPOST codes to be used in the modeling. The Protocol also states that “if new and improved versions become available, the MDEQ will apply those versions and document the changes”. In June 2007, EPA has approved the new version of CALPUFF modeling system, Version 5.8. This new, EPA-approved version was used in the modeling.

This report outlines the techniques and data used in the BART analyses. Section 2 describes the study area and the source configuration. The site characteristics and the data bases (meteorological, geophysical, and aerometric) used in the analysis are provided in Section 3. Section 4 includes an overview of the CALM ET and CALPUFF models, and the importance of evaluating non-steady-state effects. The results of the modeling analysis are described in Section 5.

2 Introduction

### 2.0 SOURCE DESCRIPTION
The Colstrip Power Plant is located in Colstrip, Montana. The BART-eligible sources consist of two tangential coal-fired units, Units 1&2. Figure 2- 1 shows the aerial photo of the Colstrip plant.

The emissions for the conditions during the modeling years (2001 – 2003) from each BARTeligible unit were based on the maximum daily em issions recorded over the three-year modeling period.

PM 10 emissions were split into filterable and condensable portions, with the condensable portion further split into organics and inorganics and the filterable portion split into fine particulate matter, elemental carbon and coarse particulate matt er parts based on available stack test data, AP-42 emission factors and current guidance of the National Park Service. The particulate matter was modeled using the geometric mass mean diameter of 0.4 micrometers ( μ m) and geometric standard deviation of 2 μ m.
Stack parameters for modeling were based on full load operation. Table 2-1 summarizes the stack parameters and emissions, while Table 2-2 summarizes the particulate speciation for the present emission case.

Table 2-3 summarizes the emissions and particulat e speciation for the base case and seven control alternatives evaluated. Each control alternative is related to a single pollutant emission reduction.

3 Source DescriptionDescription 4 Source 

### Figure 2-1. Aerial photo of the PPL Colstrip facilityTable 2-1..........................................Colstrip: Source Parameters and Emission Rates – Base CaseLambert ConformalCoordinates1StackID #LCC EastLCC NorthStackHeightBaseElevationDiameterGas ExitVelocityStackGas ExitTemp.SO2EmissionsH2SO4Emissions2NOxEmissionsPM10Emissions3kmkmmmmm/sKlb/hrlb/hrlb/hrlb/hrUnit 1823.887185.596152.4988.05.029229.7366.32612.0121.051798.0338.45Unit 2823.930185.598152.4988.05.029228.44367.32828.0118.471955.0374.131The LCC projection is based on standard parallels of 45.0 N and49.0 N, an origin latitude and longitude of 44.25 N and 109.5W, false easting is600 km, and datum NAD83.2H2SO4emissions are entered in CALPUFF as SO4i.e., weighted by ratio of molecular weights (96/98).3PM10emission rate includes filterable and condensable emissions. The condensable component includes H2SO4emissions.Table 2-2.......................................................................... Colstrip: Particle Speciation – Base CaseStack ID #Particle speciationCondensableFilterableorganiccondensable (OC)H2SO4COARSESoilElementalCarbon (EC)filterable PM10condensable PM10M1=0.48, SD1=2.0 μmM1=0.48, SD1=2.0 μm%%lb/hrlb/hrlb/hrlb/hrlb/hrUnit155.344.730.26121.0553.47128.734.95Unit260.439.629.62118.4764.58155.485.971M and SD stand for Geometric Mass Mean Diameter and Geometric Standard Deviation. These are the parameters used to calculate the particle size distribution in CALPUFF.5Source Description6Source DescriptionTable 2-3.............................................Colstrip: Emissions for Base Case and Control AlternativesStackID #CondensableFilterableSO2EmissionsNOxEmissionsPM10Emissions3organiccondensable(OC)H2SO4COARSESoilElementalCarbon(EC)lb/hrlb/hrlb/hrlb/hrlb/hrlb/hrlb/hrlb/hrUnit 1Base Case2612.01798.0338.4530.26121.0553.47128.734.95Control Alt. 11433.41798.0338.4530.26121.0553.47128.734.95Control Alt. 21075.11798.0338.4530.26121.0553.47128.734.95Control Alt. 3597.31798.0338.4530.26121.0553.47128.734.95Control Alt. 42612.0915.8338.4530.26121.0553.47128.734.95Control Alt. 52612.0836.2338.4530.26121.0553.47128.734.95Control Alt. 62612.0597.3338.4530.26121.0553.47128.734.95Control Alt. 72612.01798.0211.0330.26121.0517.0641.081.58Unit 2Base Case2828.01955.0374.1329.62118.4764.58155.485.97Control Alt. 11558.91955.0374.1329.62118.4764.58155.485.97Control Alt. 21169.21955.0374.1329.62118.4764.58155.485.97Control Alt. 3584.61955.0374.1329.62118.4764.58155.485.97Control Alt. 42828.01052.2374.1329.62118.4764.58155.485.97Control Alt. 52828.0935.3374.1329.62118.4764.58155.485.97Control Alt. 62828.0584.6374.1329.62118.4764.58155.485.971.54Control Alt. 72828.01955.0206.5429.62118.4716.7040.21NOTES: Control Alt 1 = SO2control efficiency increased to 88% with lime injection.Control Alt 2 = SO2control efficiency increased to 91% with lime injection.Control Alt 3 = SO2reduced to 0.15 lb/MMBtu by adding an additional scrubber vessel.Control Alt 4 = NOx reduction with SOFA.Control Alt 5 = NOx reduction with SNCR.Control Alt 6 = NOx reduction to 0.15 lb/MMBtu with SCR.Control Alt 7 = Filterable PM reduced to 0.015 lb/MMBtu.

### 3.0 GEOPHYSICAL AND METEOROLOGICAL DATA

3.1 Terrain
Gridded terrain elevations for the modeling domain are derived from 3 arc-second digital elevation models (DEMs) produced by the United States Geological Survey (USGS). Data are provided in files covering 1 degree by 1 degree blocks of latitude a nd longitude. The 1-degree DEMs are produced by the Defense Mapping Agency using cartographic and photographic sources. USGS 1:250,000 scale topographic maps are the primary source of 1-degree DEMs.

One degree DEM data consists of an array of 1201 by 1201 elevations referenced on the geographic (latitude/longitude) coordinate system of the Worl d Geodetic System 1972 Datum. Elevations are in meters relative to mean sea level, and the spacing of the elevations along each profile is 3 arc-seconds, which corresponds to a spacing of approximately 90 meters.

The CALMET computational domain was designed to c over an area of 780 km by 570 km (Figure 3-1). It includes Colstrip and all Class I areas within 300 km from it. These Class I areas are: North Absaroka WA, Theodore Roosevelt NP, UL Bend WA, Washak ie WA and Yellowstone NP. The domain also includes the other PPL Bart-eligible facility in Mont ana (Corette) and the Class I areas within 300 km of it. The domain includes an adequate buffer of more th an 50 km in all directions from each of the two facilities and each of the Class I areas. A horizontal resolution of 2 km was used to represent the variations of the terrain elevations in the area. This modeling domain is different from the domain proposed in the Montana Protocol for several reasons . In Montana Protocol, a single, large domain was designed to cover the entire state of Montana and parts of five neighboring states, since that modeling domain was intended to be used for 10 BART eligib le Montana sources and all Class I areas within 300 km from those 10 facilities. Since the size of such domain was very large, proposed horizontal resolution in Montana Protocol was 6 km. In the current analysis, modeling domain was redesigned to include only two PPL facilities, Colstrip and Corette, and Class I areas within 300 km from these two facilities only. This resulted in the modeling domain mu ch smaller in size than the originally proposed. Hence, better horizontal resolution of 2 km was po ssible to achieve with still using the reasonable number of grid cells. In addition, domain was extended to the south to include complete set of receptors in Yellowstone, Washakie and Teton Class I areas.

Figure 3-1 shows contours of the terrain averaged to 2 km. The USGS elevation records located within each grid cell in the computational domain were av eraged to produce a mean elevation at each grid point. Adequate representation of the important terr ain features and valleys associated with the Class I areas and the surrounding area are captured by the 391 x 286 grid 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 adequate buffer zone at the boundaries, and to allow the effects of flow curvature and possible small-scale recirculati on to be evaluated. Figure 3-1 shows locations of Colstrip and a circle with 300-km radius around the facility. North Absaroka, Theodore Roosevelt,

7 Geophysical and Meteorological Data

### igure 3-1. Terrain contours (m MSL) at 2 km resolution for the 780 km by 570 km CALMET and 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 300 km circle around facility



### F CALPUFF computational domains. The Class I areas and the Colstrip facility are also shown. 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

8 Geophysical and Meteorological DataUL Bend, Washakie and Yellowstone Class I areas ar e within the 300 km from the Colstrip. These five Class I areas were included in the BART visib ility analysis for the Colstrip facility.



### 3.2 Land Use

The USGS Land Use data within the CALMET/CALPU FF computational domain have been used to produce a gridded field of dominant Land Use categories. The Land Use data for the analysis were obtained in Composite Theme Grid (CTG) format from the USGS, with a resolution of 200 m.

Land use data were processed to produce a 2 km resolution gridded field of fractional land use categories. The 37 USGS Land Use categories were then mapped into 14 CALMET land use categories. Surface properties such as albedo, Bowen ratio, roughness length, and leaf area index were computed proportionally to the fractional land use. The 14 CALMET land use categories are described in the Montana Protocol. Figure 3-2 shows the dominant land use categories used in the modeling.



### 3.3 Meteorological Data Base
The CALMET model requires meteorological information from the surface and upper air as well as geophysical information about the land use and te rrain heights. Specifically, CALMET requires surface observations of wind speed, wind direction, temper ature, cloud cover, ceiling height, surface pressure, relative humidity, and precipitation t ype (e.g., snow, rain, etc.). These variables are routinely measured at the National Weather Service (NWS) surface st ations. The upper air data include twice-daily observations of vertical profiles of wind speed , wind direction, temperature, and pressure.

The CALMET was run using NOOBS=1, which means that upper air were taken from MM5 and not from observations. Also, precipitation and relative humidity were also derived from the MM5 data. Table 3-3 lists the types of observational and modeled data available that are used in the modeling. A total of 60 surface meteorological stations for each y ear were used in the refined runs (Table 3-4). And three-dimensional gridded data from the prognostic numerical model MM5 provided by WRAP were also included with a resolution of 36-km for 2001 th rough 2003. Hourly precipitation data, which are required for wet deposition calculations in CALPUFF, were derived from the MM5 data.

SURF.DAT has been recreated using Integrated Su rface Hourly Weather Observations (ISHWO) data base. Eight stations in 2001 and 5 from 2002 and 2003 from the original SURF.DAT file were not found in any of ISHWO or METAR databases. The reco rds from theses stations were extracted from the original SURF.DAT files and added to the new ones (first eight stations listed in Table 3-4).

9 Geophysical and Meteorological Data

### igure 3-2. Dominant land use categories at 2 km resolution on the CALMET and CALPUFF odeling 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 300 km circle around facility



### F

m 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 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

10 Geophysical and Meteorological Data

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

Type of Dataset Frequency Source Parameters

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

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.

11 Geophysical and Meteorological Data

### Table 3-4........................................................................................... NWS Hourly Surface Stations

WMO WBAN Station Name State Latitude (deg.) Longitude (deg.) CALL ID LCC X 1 (km) LCC Y 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 KI DA 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 PK INT 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 standard parallels of 45.0 N and 49.0 N, an origin latitude and longitude of 44.25 N and 109.5 W, fals e easting is 600 km, and datum WGS-84. 2 Available for year 2001 only

12 Geophysical and Meteorological Data

### Figure 3-3. Surface stations. The stations included in the SURF.DAT files are plotted in purple. For reference in orange are shown the stations included in the original SURF.DAT files. As the figure 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 KFC CYEN



### shows better coverage of the domain is achieved by using the ISHWO data base. A KCTB

KMLS

KHEI KDIK KISN KMIB KMOT GL27

KN60

TH28

KCUT KPHP

KIEN

KD07

KRAP KRCA

KDGW KCPR KLN D

KRIW KJAC KGCC KBYG KSHR

P60

KWRL KGEY KCOD SP26 PE25

SA32 MO3 9 GA3 8 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

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

Colstrip BC AL SA

ID MT ND

SD

WY PPL, Montana

MODELING DOMAIN 300 km circles around facility

13 Geophysical and Meteorological Data

### 3.4 Air Quality Monitoring Data
CALPUFF uses hourly ozone concentration measurements in the chemical transformation calculations (SO 2 to SO 4 , NO x to HNO 3 /NO 3 ). The ambient ozone measurements were used in determining SO 2 loss rates due to chemical transformation to sulfate and in determining NO x loss rates to nitrate. Ambient ozone monitoring data from the EPA AIRS and CASTNET networks were used to develop the hourly ozone monitoring data file (OZONE.DAT). The or iginal OZONE.DAT files from the WRAP web site were not used her since they contained many stati ons that were very far from the modeling domain and in addition, a couple of these stations had wrong coor dinates. The ozone stations used in the modeling are plotted in Figure 3-4. These stations and their locations are listed in Table 3-5.

Monthly background ammonia concen trations were calculated from hourly ammonia data collected from 2001 to 2002 a site near Beulah, ND. The MDEQ believes this data is representative of Montana background ammonia concentrations and the EPA concurs. These ammonia background concentrations, shown in Table 4.3.2 of the Montana Prot ocol were used in the CALPUFF modeling.

14 Geophysical and Meteorological Data15 Geophysical and Meteorological Data 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



### Figure 3-4. Locations of ozone monitoring stations used in the CALPUFF modeling.

### Table 3-5................................................................................................................... Ozo ne 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 Lostwood Nwr 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

16 Geophysical and Meteorological Data

### 4.0 AIR QUALITY MODELING METHODOLOGY

4.1 Model Selection
The CALPUFF modeling system (Scire et al., 2000a,b) w as used in the Colstrip BART analysis at UL Bend, North Absaroka, Theodore Roosevelt, Wash akie and Yellowstone Class I areas. The EPAapproved version of CALPUFF modeling system, Version 5.8 was used in the modeling.



### 4.2 Modeling Domain Configuration
CALMET and CALPUFF use terrain-following coordinat es. The modeling domain consists of 391x286 grid cells, uniform in the horizontal with a spatial resolution of 2 km. This domain covers the Colstrip PPL facility in Montana and eight Class I areas in its vicinity, along with the appropriate buffer zones. In the vertical, a stretched grid was used with fine r resolution in the lower layers and somewhat coarser resolution aloft thus allowing adequa te representation of the mixed layer. The ten vertical levels are centered at: 10, 30, 60, 120, 230, 450, 800, 1250, 1850 and 2600 meters.



### 4.3 Meteorological Modeling Options
In CALMET, the regulatory option was used (MREG= 1), indicating the selection of the mixing height method (IMIXH=-1 using the Maul-Carson met hod over land and the OCD method over water; ICOARE=0 using the OCD method for turbulence a nd fluxes over water; and THRESHL=0.0 using a value of zero for the threshold sensible heat flux over land).

Initial Guess Field

The MM5 gridded meteorological data were used to define the initial guess field for the CALMET simulations. MM5 data were available for years 200 1-2003 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 adjust s 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 defined as the hi ghest peak within a radius TERRAD around each grid point. For the domain used to perform the modeling, a value of TERRAD of 15 km was used. This value has been recommended by MDEQ in the Montana Prot ocol and is considered appropriate for this modeling domain. The Step 1 field produces a flow fi eld consistent with the fine-scale CALMET terrain resolution (2 km).

Step 2 Field: Objective Analysis

In Step 2, observations are incorporated into the St ep 1 wind field to produce a final wind field. Each observation site influences the final wind field with in a radius of influence (parameters RMAX1 at the surface and RMAX2 aloft). Observations and Step 1 fi eld are weighted by means of parameters R1 at


### 17 Air Quality Modeling Methodologythe surface and R2 aloft: at a distance R1 from an observation site, the Step 1 wind field and the surface observations are weighted equally. As recommended in the Montana Protocol, RMAX1 and RMAX2 were set to 40 km and 100 km, while R1 and R2 were set to 20 km and 50 km, respectively.



### 4.4 CALPUFF Computational Domain and Receptors
The CALPUFF computational domain is the same as the CALMET computational domain. The modeling domain includes a buffer zone of at least 50 km from the source and beyond the borders of the Class I areas. This minimizes the edge effects and a llow pollutants involved in flow reversals to be brought back into the Class I areas. CALPUFF was run for three years, 2001, 2002 and 2003.

The receptor locations along with receptor elevati ons were available from the National Park Service (NPS). The distribution of the receptors within UL Bend, Theodore Roosevelt, Washakie, North Absaroka, and Yellowstone are shown in Figure 4-1. In the screening modeling, the domain did not include the southernmost part of the Yellowstone NP and Washakie WA. In this refined run, the complete set of receptors for these Class I areas was included.



### 4.5 Dispersion Modeling Options

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 coefficients (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. - Regulatory option used

Two important computational parameters in CALP UFF are XMXLEN (maximum length of an emitted puff, in grid units) and XSAMLEN (maximum travel distance of a puff, in grid units, during one time step). Both of these variables were 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 beco me so large so that it cannot respond to changes in the wind field on the scale of the meteorologi cal grid. The model automatically increases the frequency of puff releases to ensure the length of a single puff is not larger than the grid size. The second parameter decreases the internal time step to ensure the travel distance during one time step does not exceed the grid size.



### 18 Air Quality Modeling Methodology480 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 

### Fig

ure 4-1

. L

19 Air Quality Modeling MethodologyThe 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 characteriz e 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

Deposition was modeled using the default dry depo sition model and the scavenging coefficient wet removal module. Nine species were mode led 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 computes transformation rates of SO 2 to SO 4 and NO x to NO 3 /HNO 3 . Hourly measured ozone concentrations are provided in an extern al OZONE.DAT file for use with the chemical transformation module. The 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, the two units were modele d individually and their source contributions were summed in postprocessing steps.



### 4.6 Visibility Calculations
Calculations of the impact of the simulated plume particulate matter component concentrations on light extinction was carried out in the CALPOST pos tprocessor. The equation used is the usual IMPROVE/EPA equation which is applie d to determine the change in lig ht extinction due to changes in component concentrations. Using the notations of CALPOST, the formula is the following:



### B

B ext 

### = 3f(RH)[(NH 4 

### ) 2 

### SO 4 

### ] + 3f(RH)[NH 4 

### NO 3 

### ] + 4[OC] + 1[Soil] + 0.6[Coarse Mass] +10[EC] + b ray The concentrations, in square brackets, are in μ g/m 3 and b ext is in units of Mm -1 . The Rayleigh scattering term (b ray ) has a default value of 10 Mm -1 , as recommended in EPA Guidance for Estimating Natural Visibility Conditions Under the Re gional Haze Program (U.S. EPA, 2003b). Note that organic carbon (OC), which consists of condensable particulates, was modeled as SOA in CALPUFF runs. Soil is fine particulates which is defined as PMF in the CALPUFF runs, while Coarse Mass was labeled PMC. All particulate matter including EC, PMF, PMC and OC were modeled in CALPUFF with geometric mass mean diameter of 0.4 μ m and geometric standard deviation of 2 μ m.
The haze index (HI) is calculated from the extinction coefficient via the following formula:


### HI = 10 ln(b ext 

### /10)

20 Air Quality Modeling Methodologywhere HI is in units of deciviews (dv) and b ext is in Mm -1 . The impact of a source is determined by comparing HI for estimated natural background conditi ons with the impact of the source and without the impact of the source

. CALPOST Method 6 was used to compute the extincti on change in deciviews consistent with the procedures outlined in the Montana Protocol. A monthl y background concentration must be entered into the CALPOST input control file. This background concentration was entered only for SOIL. The way it is computed makes it suitable to represent background light extinction for all particulates (hygroscopic + non-hygroscopic) at the same time when multip lied by an extinction coefficient of one.

A monthly background concentration must be entered into the CALPOST input control file for all aerosols defining the background. The 20% best days fo r each of the five Class I area were used for the natural background extinction calculations. The natura l background values for the 20% best days as provided in the Guidance for Estimating Visibility Conditi ons Under the Regional Haze Program (U.S. EPA, 2003) and Montana Protocol are shown in Table 4-1. Table 4-2 provides the monthly f(RH) values based on the representative IMPROVE site location of the Class I areas as required for application of Method 6. The monthly f(RH) values for each month are extracted from Appendix A of Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule (2003)

. In the BART procedures, the 8 th highest (98 th percentile) predicted change in light extinction expressed in deciviews is used as a metric to compare emission scenarios.



### 21 Air Quality Modeling Methodology

### Table 4-1....................................................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 Conditi ons Under the Regional Haze Rule (2003), Table 2-1



### Table 4-2. Monthly f(RH) values based on the Repr esentative IMPROVE Site Location, for Visibility Method 6 applications

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



### 22 Air Quality Modeling Methodology

### 5.0 RESULTS
The change in light extinction relativ e to the natural background due to SO 2 , NO x and PM 10 from Colstrip Units 1&2 was computed based on the ba se case emissions level during the modeling years (2001-2003), described in Section 2, and the emissi ons levels under the potential BART options being evaluated. The emissions levels for the base case and control alternatives are presented in Table 2-3. The CALPUFF modeling predicted the effects of emis sions from the units on visibility at the five Class I areas within 300 km of the facility. The BART methodology with CALPOST Method 6 and 98 th percentile day results was used to determine visibility impacts. The light extinction impacts are presented 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.

Tables 5-1 through 5-8 summarize the eight highest (98 th percentile) predicted extinction changes for 2001-2003 for the present emission case (Base Case) and seven control alternatives. For each control alternative, the emissions were altered for only the specific pollutant for which the control alternative applied, with the other pollutants modeled at their base case emissions.



### 23 Air Quality Modeling Methodology

### Table 5-1....................................................................Summary of Visibi lity Results for Base Case

2001 2002 2003 Class I Area Minimum Distance (km) 98th percentile delta-deciview UL Bend 200 1.880 2.124 2.233 North Absaroka WA 254 0.649 1.569 0.981 Theodore Roosevelt NP 260 1.781 2.186 1.749 Washakie WA 278 1.202 1.152 0.642 Yellowstone NP 281 0.783 1.037 0.571



### Table 5-2.Summary of Visibility Results for Alternative 1 (SO 2 

### Control Efficiency Increased to 88%)

2001 2002 2003 Class I Area Minimum Distance (km) 98th percentile delta-deciview UL Bend 200 1.537 1.524 1.811 North Absaroka WA 254 0.480 1.263 0.795 Theodore Roosevelt NP 260 1.553 2.000 1.466 Washakie WA 278 1.025 0.932 0.632 Yellowstone NP 281 0.606 0.842 0.449



### Table 5-3.Summary of Visibility Results for Alternative 2 (SO 2 

### Control Efficiency Increased to 91%)

2001 2002 2003 Class I Area Minimum Distance (km) 98th percentile delta-deciview UL Bend 200 1.452 1.728 1.689 North Absaroka WA 254 0.434 1.172 0.736 Theodore Roosevelt NP 260 1.479 1.954 1.342 Washakie WA 278 0.945 0.874 0.580 Yellowstone NP 281 0.564 0.775 0.391



### Table 5-4........Summary of Visibility Results for Alternative 3 (SO 2 

### Reduced to 0.15 lb/MMBtu)

2001 2002 2003 Class I Area Minimum Distance (km) 98th percentile delta-deciview UL Bend 200 1.331 1.543 1.582 North Absaroka WA 254 0.364 1.041 0.653 Theodore Roosevelt NP 260 1.373 1.832 1.176 Washakie WA 278 0.830 0.765 0.505 Yellowstone NP 281 0.503 0.677 0.320



### 24 Air Quality Modeling Methodology

### Table 5-5.................. Summary of Visibility Results for Alternative 4 (NO x 

### Reduced with SOFA)

2001 2002 2003 Class I Area Minimum Distance (km) 98th percentile delta-deciview UL Bend 200 1.586 1.557 1.781 North Absaroka WA 254 0.534 1.280 0.805 Theodore Roosevelt NP 260 1.426 1.613 1.305 Washakie WA 278 0.972 0.929 0.560 Yellowstone NP 281 0.619 0.844 0.460



### Table 5-6..................Summary of Visibility Results for Alternative 5 (NO x 

### Reduced with SNCR)

2001 2002 2003 Class I Area Minimum Distance (km) 98th percentile delta-deciview UL Bend 200 1.554 1.492 1.713 North Absaroka WA 254 0.522 1.248 0.786 Theodore Roosevelt NP 260 1.388 1.548 1.272 Washakie WA 278 0.953 0.904 0.559 Yellowstone NP 281 0.605 0.823 0.449



### Table 5-7.Summary of Visibility Results for Alternative 6 (NO x 

### Reduced to 0.15 lb/MMBtu with SCR)

2001 2002 2003 Class I Area Minimum Distance (km) 98th percentile delta-deciview UL Bend 200 1.456 1.298 1.584 North Absaroka WA 254 0.484 1.151 0.729 Theodore Roosevelt NP 260 1.236 1.385 1.173 Washakie WA 278 0.895 0.829 0.555 Yellowstone NP 281 0.561 0.760 0.418



### Table 5-8.Summary of Visibility Results for Alte rnative 7 (Filterable PM Reduced to 0.015 lb/MMBtu)

2001 2002 2003 Class I Area Minimum Distance (km) 98th percentile delta-deciview UL Bend 200 1.856 2.090 2.213 North Absaroka WA 254 0.644 1.541 0.971 Theodore Roosevelt NP 260 1.762 2.144 1.728 Washakie WA 278 1.177 1.129 0.635 Yellowstone NP 281 0.776 1.023 0.566



### 25 Air Quality Modeling Methodology

### 6.0 REFERENCES

FLAG, 2000. Federal Land Manager' Air Qualit y Related Values Workgroup (FLAG). Phase I Report. U.S. Forest Service, National Park Service, U.S. Fish and Wildlife Service.
Scire, J.S., D.G. Strimaitis, and R.J. Yamartino, 2000a: A User’s Guide for the CALPUFF Dispersion Model (Version 5) . Earth Tech, Inc., Concord, MA
Scire, J.S., F.R. Robe, M.E. Fernau, and R.J. Yamartino, 2000b: A User’s Guide for the CALMET Meteorological Model (Version 5). Earth Tech, Inc., Concord, MA.
U.S. Environmental Protection Agency (EPA), 1998: Interagency Workgroup on Air Quality Modeling (IWAQM), Phase 2 Report: Su mmary Report and Recommendation for Modeling Long Range Transport and Imp acts on Regional Visibility. EPA-454/R-98- 019. U.S. Environmental Protection Agency (EPA), 2003a: Revision to the Guideline on Air Quality Models: Adoption of a Pref erred Long Range Transport Model and Other Revisions; Final Rule. 40 CRF 51. Federal Register , April 15, 2003, 68 

### , 72, pp 18440-18482. U.S., Environmental Protection Agency (EPA), 2003b: Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Program . EPA-454/B-03-005, September 2003.
U.S. Environmental Protection Agency (EPA), 2005: Regional Haze Regulations and Guidelines for Best Available Retrofit T echnology (BART) Determinations; Final Rule, 40 CFR 41. Federal Register , July 6, 2006, 70 

### , 128, pp 39104-39172.

26Colstrip BART Report.doc i Air Quality Modeling Methodology