iii 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...................................................................... 2-3
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 4.1.4 Pollutant Emissions from Corette .................................................................. 4-8 4.2 Evaluated Retrofit Technologies for J.E. Corette ................................................ 4-9 4.2.1 Particulate Matter Controls.......................................................................... 4-10 4.2.1.1 Summary of PM Control Tec hnology Analyses for Corette ........... 4-10 4.2.1.2 Costs of Controls ............................................................................. 4-10 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.......................................................................... 4-15 4.2.2 Sulfur Dioxide Controls............................................................................... 4-15 4.2.2.1 Controls and Emission Rates Evaluated .......................................... 4-15 4.2.2.2 Cost of SO 2 Controls........................................................................ 4-17 4.2.2.3 Energy Impacts of SO 2 Controls...................................................... 4-18 4.2.2.4 Non-Air Quality Impacts of SO 2 Controls....................................... 4-18 4.2.2.5 Remaining Useful Life..................................................................... 4-18 4.2.2.6 Visibility Modeling.......................................................................... 4-19 4.2.3 NO x Controls................................................................................................ 4-19 4.2.3.1 NO x Controls and Emission Rates Evaluated .................................. 4-19 4.2.3.2 Cost of NO x Controls....................................................................... 4-21 4.2.3.3 Energy Impacts of NO x Controls ..................................................... 4-22 4.2.3.4 Non-Air Quality Environmental Impacts of NO x Controls ............ 4-22 4.2.3.5 Remaining Useful Life..................................................................... 4-22 4.2.3.6 Visibility Modeling.......................................................................... 4-22 4.3 Visibility Modeling............................................................................................ 4-23 4.3.1 General Modeling Procedures...................................................................... 4-23 4.3.2 Summary of Modeling Results .................................................................... 4-24
5.0 SUMMARY AND CONCLUSIONS .............................................................................. 5-1
6.0 REFERENCES ................................................................................................................ 6-1ii TABLE OF CONTENTS (Continued)

LIST OF TABLES
Table ES-1: Allowable / Current / NSPS / Emi ssion Limits Control Equipment Cost Summary.............................................................................................................. ES- 6 Table ES-2: Modeled Visibility and Visibility Improvements................................................ ES- 6
Table 2-1: Corette: Part icle Speciation – Base Case ............................................................... 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: Corette Emissions Summary ................................................................................... 4-8
Table 4-3: PM Contro l Alternatives Evaluated ...................................................................... 4-11
Table 4-4: Particulat e Cost Analysis Summary...................................................................... 4-12 Table 4-5: Representative Control Equipment Pressure Drops .............................................. 4-14 Table 4-6: Summary of M odeling Results for Particulate...................................................... 4-15
Table 4-7: SO 2 Control Alternatives Evaluated ...................................................................... 4-16
Table 4-8: SO 2 Control Cost Summary .................................................................................. 4-18 Table 4-9: Summary of Modeling Results for SO 2 ................................................................. 4-19
Table 4-10: NO x Control Alternatives Evaluated ..................................................................... 4-20
Table 4-11: NO x Costing Analysis Summary........................................................................... 4-21 Table 4-12: Summary of Modeling Results for NO x ................................................................ 4-23 Table 4-13: Summary of Modeling Results.............................................................................. 4-25
Table 5-1: Summar y of Cost Evaluation Results Based on Emissions .................................... 5-3
Table 5-2: Modeled Visibil ity and Visibility Improvements.................................................... 5-3

LIST OF FIGURES

FIGURE ES-1: CORETTE LOCATION AN D CLASS I AREAS EVALUATED................ ES- 2
FIGURE 4-1: COST ANALYSIS OF ESP CONTROL......................................................... 4-12

APPENDICES
APPENDIX A: COST ANALYSIS TABLES
APPENDIX B: CALPUFF APPLICATION FOR BART ASSESSMENTS AT PPL CORETTEES-1 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 degradation of visibi lity at Prevention of Significant Deterioration (PSD) mandatory Class I Areas. The coal fired generating unit at the PPL M ontana, LLC J.E. Corette generating station (Corette) was determined to be BART-eligible u nder the Federal Regional Haze Rule by the U.S. Environmental Protection Agency Region 8. The Cl ass I areas within 300 km of Corette are the North Absaroka Wilderness Area (137 km to the southwest), Yellowstone National Park (145 km to the southwest), the Washakie Wilderness Ar ea (171 km to the southwest), the UL Bend National Wildlife Refuge (192 km to the north), the Teton Wilderness Area (199 km to the southwest), the Gates of the Mountains Wilder ness Area (276 km to the west) and Red Rock Lakes (277 km to the southwest) . These Class I areas are shown in relation to the Corette plant in Figure ES-1.
The CALPUFF model was used to evaluate th e visibility impacts of present emissions
from the Corette boiler and BART control 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 were made to the modeling as described in Appendix B. The highest modeled annual 98 th percentile daily visibility impact of emissions from the unit at present maximum actual emi ssions is predicted to
occur in the UL Bend National W ildlife Refuge (NWR) Class I ar ea and is 0.645 deciviews, only slightly above the BART threshold of 0.5 decivi ews. EPA notes that 0.5 deciview corresponds to “a just noticeable change” in most landscapes and was therefore selected by EPA as the
recommended threshold for inclusion of a source in the BART program. Note that the maximum
modeled 98 th percentile visibility impact from Corette is well below the 1.0 deciview value EPA employs as a metric to indicate that a source causes a visibility impact. A summary of the visibility modeling results appears in Table ES-2. The U.S. Environmental Protection Agency’s (EPA’s) BART Guideline approach has been applied to Corette to identify the “best sy stem of continuous emission reduction” applicable to the plant for filterable particulate, sulfur dioxide (SO 2 ) and nitrogen oxides (NO x ) control inES-2 Figure ES-1: Corette Location and Class I Areas EvaluatedES-3 order to comply with Region 8’ s BART program. Corette alr eady has relatively low emissions
due to the use of an electrosta tic precipitator, low sulfur Powder River Basin coal and good combustion control. A range of demonstrated co ntrol alternatives for su b-bituminous coal-fired boilers was evaluated considering costs, energy a nd environmental impacts, remaining useful life of the units and modeled visibility improvements. For filterable particulate matter, electrostatic precipitators (ESP), fabric filters (baghouses), mechanical collector s and wet scrubbers were considered. However, mechanical
collectors were not further evaluated because th ese are used as pre-filters and do not perform well as a retrofit option. All cost estimates are based on EPA Control Cost Manual information and techniques whenever possible, and all cost estimates are scaled to 2007 dollars. The Corette boiler already has E SP controls and therefore eith er an upgrade of the current technology, or the addition of fabric filter controls, would be necessary to attain an emission rate equivalent to the best demonstrated tec hnology (BDT) filterable emission rate of 0.015 lbs/MMBtu. For installation of a fabric filter, this would cost approximately $16,300 per ton of particulate emissions controlled. Although upgra des to the current ES P controls would only
make sense if one of the availa ble dry scrubbing techniques for SO 2 were chosen, a cost estimate for installation of a new modern ESP was performe d. This showed that a cost of approximately $21,000 per ton of additional control would be necessary to attain the 0.015 lb/MMBtu BDT
emission rate. The retrofit installation of a wet scrubber (venturi scrubbe r) to attain the same filterable particulate matter emission reduction a nd visibility improvement would also only be considered in conjunction with SO 2 control upgrades and are discusse d below in that context. From a visibility improvement basis with respect to filterable particulate matter, only a 0.03 deciview improvement, which is not visually di scernable, would result from installation of
either ESPs or fabric filters. Consequently, implementation of a dditional filterable particulate
control at Corette is not warranted.
For SO 2 and NO x , the cost effectiveness analysis wa s based on emission rates typical of 30-day average emissions. These rates for the pres ent, cost effectiveness (base case) emissions
are 0.46 lb/MMBtu for SO 2 and 0.26 lb/MMBtu for NO x . However, consistent with the modeling guidance, the modeling analysis was conducted at maximum actual daily emission rates. For modeling the present (base case) emi ssions the maximum actual daily rates during the modeling years are 0.6 lb/MMBtu for SO 2 and 0.31 lb/MMBtu for NO x based on Part 60 CEM
data. This distinction was also made for the eval uation of control alternatives for which the costES-4 analysis was based on expected typical emission rates and the modeling was based on expected maximum actual daily emission rates. For filt erable particulate, continuous emissions data (CEM data) are not available and a distincti on between maximum actual and typical emission
rates was not made.
For SO 2 , the available control tech nologies include the use of low sulfur fuels, dry gas scrubbing techniques and wet scrubbing (flue gas desulfuriza tion, FGD) techniques. Based on experience at other PPL facilities and EPA da ta that summarize the effectiveness of SO 2 removal technologies, PPL evaluated the co st effectiveness of lime or limes tone injection at Corette using the current ESP equipment. Corette already burns low-sulfur (approximately 0.3 weight percent) Powder River Basin (PRB) coal with uncontrolled daily SO 2 emissions during the modeling years that were a maximum of 0.6 lb/MMBtu and typically averaged clos er to 0.46 lb/MMBtu. The cost effectiveness of dry injection of lime or limestone to attain a 25% emissions reduction is $8,138/ton of SO 2 controlled. Emission reductions we re also evaluated to meet the presumptive BART level of 0.015 lb/MMBtu. This presumptive BART level does not apply to the Corette boiler which is below the size threshold for which this presumptive level is intended. Nevertheless, the cost of achieving this level wa s evaluated. To attain the 0.015 lb/MMBtu level by dry injection, the combined cost of the more reactive sorbents and an upgraded ESP would be an estimated $37,429/ton of SO 2 . Conversion of the Corette boiler to a wet scrubbing control technique is a technically feasible alternative which PPL has considered. PPL has substantial experience with this technology as it is used to control SO 2 at the Colstrip facility operated by PPL. The cost effectiveness of installing this alternate technology at Corette is estimated to be $25,480/ton of
SO 2 based on EPA costing factors. A wet sc rubbing FGD system has penalties for plume reheating which would require a reduction in generation output fr om 154 MW to approximately
124 MW. The loss in electrical en ergy generation from plume rehea ting is included in the cost of adding a wet scrubber. Modeling shows only a 0.08 deciview visibili ty improvement with lime/limestone addition used to achieve a 25 percent SO 2 emissions reduction. The incremental visibility improvements by reducing emissions to a 0.15 lb/MMBtu emissi on rate through either dry injection or wet scrubbing ar e 0.15 deciviews or less. Such improvements are not visually discernable and implementation of these contro l technologies is, theref ore, not warranted.
NO x controls in-place at Corette include the tangential firing design of the boilers and existing low-NO x burners with close coupled over fire air. The pr esent maximum actual dailyES-5 emission rate modeled is 0.31 lb/MMBtu and the typi cal emissions rate used for the cost analysis is 0.26 lb/MMBtu. By adding sepa rated over-fire air (SOFA) a nd redistribution of combustion air to the multiple injection ports to the current NO x controls, it is likely that emissions can be
reduced to 0.18 lb/MMBtu. Sele ctive non-catalytic reduc tion (SNCR) by inje ction of urea into
the same zone within the boiler could reduce em issions to 0.16 lb/MMBtu. The cost of SNCR technology has been estimated, however, its tenden cy to form secondary particulate emissions
from combination with sulfur oxide s, and its creation of ammonia sl ip in the exhaust, makes this technique undesirable. A hot-side selective cata lytic reduction system (SCR) to further reduce emissions to 0.15 lb/MMBtu was also reviewed, however its incremental cost over the addition of SOFA makes SCR economically unacceptable. This level (0.15 lb/MMB tu) was evaluated as a minimum emissions level because it is the pr esumptive BART emissions level, although the Corette boiler is below the size threshold for which this presumptive level is intended. Only a 0.04 deciview modeled visibility improvement re sults from implementati on of SOFA, which is not discernable, and the incremental visibili ty improvements of further controls are 0.06 deciviews or less. Implementation of these cont rol technologies is, ther efore, 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-2, 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 present emissions and incrementally. The indicated visibility improvements in Table ES-2 are based on the differences between the
maximum 98 th percentile predicted daily visibility impact s at each Class I Area for each level of control, regardless of the meteorological year modeled for each prediction. Because Corette’s highest 98 th percentile visibility impact s are only slightly above th e 0.5 deciview threshold for inclusion in the BART program and the predicted reductions of visibility impacts are small (Table ES-2), implementation of retrofit pollu tion controls at Corette is not justified.ES-6 Table ES-1: Allowable / Current / NSPS / Emission Li mits Control Equipment Cost Summary

CONTROL EQUIPMENT COST SUMMARY FOR THE PPL MONTANA, LLC, J.E. CORETTE POWER PLANT
Particulate Matter Sulfur Dioxide Nitrogen Oxides Evaluated

Rate Units Evaluated Rate Units Evaluated Rate Units Current Emission rate 0.082 lb/MMBtu 0.46 lb/MMBtu 0.26 lb/MMBtu (CEMS) (2001 to 2005 average)

BDT (1) from 2006 NSPS for 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 $/ton Option Evaluated CE Inc CE Option Evaluated $/ton (5) Inc CE Rate Rate Rate lb/MMBtu lb/MMBtu $/ton $/ton lb/MMBtu $/ton Control New ESP (2) 0.015 $21,149 Present 0.46 $0 Present (4) 0.26 $0 Options Added FF 0.015 $16,339 DGS (2) 0.35 $8,138 Tuning 0.23 $147 DGS (2) 0.15 $37,429 $53,538 SOFA 0.18 $914 $1,375 WS-FGD (3) 0.15 $25,480 $35,017 SNCR 0.16 $1,723 $4,966 SCR 0.15 $4,354 $30,518
Notes 1) 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/MMBtu input values listed in paren) 2) Adding lime or limestone injection makes flyash unsalable - Includes added waste disposal cost (two options of 23% and 67% control may be possible - precip upgrade required for 67%) The CE for the ESP is the cost of a new technology ESP to reduce PM from 0.082 to 0.015 lb/MMBtu 3) If a wet scrubber is added, the low sulfur PRB coal could be replaced with higher sulfur coal. (30 MW penalty for plume reheating) Includes lost revenue from ash sales. 4) It is assumed that boiler tuning and proper operation can improve the current 0.26 lb/MMBtu to 0.23 lb/MMBtu at minimal cost 5) Each technique applied individually; incremental cost effectiveness is that from previous option cost

Table ES-2: Modeled Visibility and Visibility Improvements

Modeled Modeled Modeled Rate (1) Prediction (3) from Rate Prediction from Rate Prediction from Option (lb/MMBtu) (deciviews) Present Inc (6) Option (lb/MMBtu) (deciviews) Present Inc (6) Option (lb/MMBtu ) (deciviews) Present Inc (6) Present 0.082 0.645 n/a n/a Present 0.6 0.645 n/a n/a Present 0.31 0.645 n/a n/a New ESP 0.015 0.633 0.032(5) 0.032(5) DGS(2) 0.46 0.568 0.077 0.077 Tuning(4 ) 0.27 0.616 0.043 0.043 Added FF 0.015 0.633 0.032(5) 0.032(5) EDGS(2) 0.2 0.446 0.199 0.147 SOFA 0.21 0.573 0.098 0.055 WS-FGD 0.15 0.407 0.238 0.049 SNCR 0.17 0.544 0.125 0.055 SCR 0.15 0.53 0.138 0.054

Notes: (1) The modeled emission rate is the rate corresponding to the maximum daily emissions during the modeling years (200 1-2003). (2) See corresponding footnote in Table ES-1 (3) Prediction is from all three pollutants at present emissions except the one being controlled (4) See corresponding footnote in Table ES-1. (5) The maximum improvement occurs at a different Class I area than the maximum prediction. (6) Inc = Incremental improvement from the immediately prec eeding control alternative in terms of level of emissions reduct ion attained. Improvement Improvement Improvement Filterable PM10 Sulfur Dioxide Nitrogen Oxides1-1 1.0 INTRODUCTION/BACKGROUND The U.S. Environmental Protection Agency (EPA) Region 8 identified PPL Montana’s (PPL) J.E. Corette station coal-fired boiler as a Best Available Retrofit Technology (BART) eligible unit. This determ ination was made under the federal Regional Haze Rule (FR , Vol. 64, No. 126) that requires the States to submit St ate Implementation Plans to address haze and visibility issues in mandatory Prevention of Si gnificant Deterioration (PSD) Class I Areas. On June 19, 2006 the State of Montana withdrew its e ffort to adopt the provisions of the Regional Haze Rule. Region 8 has assumed responsibility fo r the Rule and intends to prepare a Federal Implementation Plan (FIP) for Montana sources. Regional haze is caused by naturally occurring atmospheric particles and humidity as well as by anthropogenic emissions of primary particulate matter (PM) and of secondary emi ssions resulting from atmospheri c gas 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 and 1977, such as Corette, as BART-eligible. The pollutants subj ect to BART requirements are SO 2 , NO x , PM and volatile organic compounds (VOC). To address the visibili ty impacts of these fac ilities, EPA issued the “Regional Haze Regulations and Guidelines fo r Best Available Retr ofit 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 , PM and VOC emissions. Corette has a nominal net generating capacity of 154 megawatts (MW), and has an electrostatic precipit ator for PM emission control, low SO 2 emissions due to
the use of low sulfur coal and a low NO x emission burner system. A BART analysis has been
conducted for SO 2 , NO x and particulate. Although Corette is below the 750 MW size cutoff for which BART presumptive SO 2 and NO x limits of 0.15 lb/MMBtu are intended, this emissions
level was used as the minimum SO 2 and NO x control level evaluated. The BART guideline spells out an approach to use dispersion mo deling to identify potentially subject emissions sources that may contribute to regional haze impact s in Class I areas, to evaluate case-by-case emission limitations based on the “best system of continuous emission reduction of each pollutant,” and to predict the degree of visibi lity improvement that results from the proposed emissions limit. The best system of con tinuous emission reduction is identified based on:1-2 • The available retrof it 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 Corette.2-1 2.0 PLANT DESCRIPTIONS – BART AFFECTED UNITS
2.1 Boiler Type The PPL Montana J.E. Corette Power Plant (Cor ette) operates one electric utility steam generating unit with a nominal net capacity of about 154 megawa tts. The single boiler is a tangentially fired pulverized coal boiler that burns sub-bitumi nous (Powder River Basin (PRB)) coal as its exclusive fuel. The unit began commercial operation in 1968. PPL Montana LLC operates the Corette Plant under Air Quality Operating Permit OP2953-02.

2.2 Emissions The present (base case) particulate matter emi ssions for Corette are summarized in Table
2-1. Emissions in these tables are based on PRB sub-bituminous coal combustion. The heat input rate (and associated emissions) for the Corette boiler, 1941.1 MMBtu/hr, is the highest daily average heat input rate during the modeli ng period (2001-2003). The particulate emissions used for base case modeling corre spond to this heat input rate. The particulate matter emission rates (total filterable and condensable fractions) are based on stack tests conducted during the modeling years. The two stack tests conducted per year were averaged and the highest filterable and condensab le emission rates from among the average for each of the three years were selected. These va lues are 0.082 lb/MMBtu fo r filterable particulate and 0.014 lb/MMBtu for condensable particulate. The particulate mass emissions used for modeling the present base case were based on these emission rates and the maximum daily average heat input during the modeling year s (1941.1 MMBtu/hr). The speciation of the filterable particulate into elemental carbon, fine soil and coarse soil and size fractions were based on guidance provided by the Na tional Park Service (NPS). Similarly, the speciation of condensable particulate into or ganic and inorganic particulat e was based on guidance provided by the NPS (20% organic and 80% inorganic). 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 values we are using are more accurate because they are ba sed on stack test data. The most significant
difference is the condensables emission rate. The 0.014 lb/MMBtu condensables emission rate
used here is similar to the EPA's AP-42 level of 0.01 lb/MMBtu presented for pulverized coalfired boilers burning coal with a su lfur content less than 0.4 percent. In terms of mass emissions,2-2Table 2-1: Corette: Particle Speciation – Base CaseStack ID #Particle speciationCondensableFilterableOrganiccondensable (OC)H2SO4CoarseSoilElementalCarbon (EC)FilterablePM10CondensablePM10M1=0.48, SD1=2.0 μmM1=0.48, SD1=2.0 μm% % lb/hrlb/hr lb/hrlb/hrlb/hrUnit 1 85.4 14.6 5.44 21.74 88.43 68.12 2.621M 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 the modeling presented here used filterable an d condensable emissions of 159.2 lb/hr and 27.2 lb/hr respectively, compared to values used by EPA of 29.0 lb/hr and 111 .2 lb/hr respectively.
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 analysis, 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 Corette boiler. 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) em issions are summarized in Table 2-1 and the
SO 2 and NO x present emissions are summarized in Table 2-2.

2.3 Potentially Impacted Class I Areas The federal mandatory Class I Areas within 300 km of Corette are the North Absaroka Wilderness (137 km to the southwest), Yellowstone National Park (145 km to the southwest), the Washakie Wilderness (171 km to the southwest) , the UL Bend National Wildlife Refuge (192 km to the north), the Teton Wilderness (199 km to the southwest), the Gates of the Mountains Wilderness Area (276 km to the west) and Red Rock Lakes (277 km to the southwest). These Class I areas are shown in Figure ES-1. Table 2-2: Present (Base Case) SO 2 and NO x Emissions

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

SO 2 0.46 0.60 1135.0

NO x 0.26 0.31 604.0

NOTES: (1) Typical/average emission rate s were used for the control technology and cost analyses. (2) Maximum emission rates are the highest daily average emissions during the modeling year s (2001-2003). These emissions were used for the modeling analyses.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 PM emissions of 250 tons pe r year (tpy) or more, and having construction dates between 1962 and 1977. These elig ibility criteria include Corette as a BARTeligible source. As recommended by EPA, the CALPUFF model was used to predict visibility impacts for maximum daily actual operating conditions during the modeling period (2001-2003) and for
each emission reduction alterna tive evaluated for the retrof it control options. For SO 2 and NO x , the cost effectiveness analysis was based on emi ssion rates typical of 30-day average emissions. For filterable particulate, CEM data are not available and a distinction between maximum actual and typical emission rates was not made. Potentially applicable retrofit filterable PM, SO 2 , and NO x control technologies which represent the full range of demonstrated alternativ es for large coal-fired 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 Corette boiler.3-2 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: “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 referenced 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. For the capitalization of the to tal cost of a technology, PPL uses 11 years as its standard depreciation schedule, consistent with the tax code applicable to the facility. Therefore this capitalization period with an in terest rate of 7 percent per a nnum was used throughout. Costs
were corrected to 2007 dollars us ing 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 annual operating cost analysis. The cost of energy consumption for plume reheating was included as a potential implementation cost for the wet scrubbing control option based on PPL's expe rience at the Colstrip plant wh ere wet scrubbing technology is
used.

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 PM accordingly increases the
solids collected. The addition 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, ammonia3-3 used in the catalytic reduction equipment is an additional pollutant that can increase PM
formation.

Remaining Useful Life The life of the Corette boiler is expected to exceed the study period and is projected to have no effect on the costing an alyses for this facility.

Visibility Impacts 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 For this BART analysis retrofit emission cont rol technologies applicab le to Corette were evaluated with respect to partic ulate emissions (PM-filterable por tion only), sulfur dioxide (SO 2 ) and nitrogen oxides (NO x ). The analysis included review of the technologi es 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 emissions unit and pollutant under consideration for the nominal gr oss capacity of about 162 megawatt (MW) steam electric plant boiler emissions unit located at Corette.
The Corette boiler fires sub-bituminous coal having a sulfur conten t typically under 1 percent by weight. The single boiler has an el ectrostatic precipitator for PM control, no SO 2 controls, and low-NO x burners 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 control option and a reas onable set of options for analys is that reflects a comprehensive list of available technologies for each pollutant. The list is considered complete if the list
includes the maximum level of control 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 PM, SO 2 , and NO x for electric utility boilers. The first such standards (Subpart D), which applied to fossil fuel-fired steam electric generators, were 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 PM, SO 2 , and NO x Subpart Da standards were revised to reflect improvements in emissions control since the promul gation of the previous NSPS standards. The discussions provided in proposing the rule indicated that revisi ons to emissions standards of Subpart Da are appropriate in li ght of the control technology de velopments since the previous
version of the standards in 1979 and recent tec hnological improvements in control technology. Although the new emission standard s apply to units constructed after February 27, 2005, they4-2 represent the most stringent level of emissions control for new EUSGUs. These present NSPS standards are presented in Table 4-1. A summary of the Corette allowable emission ra tes (as listed in the Title V permit for the facility), actual emission ra tes, the presumptive BART levels and the NSPS for PM, SO 2 , and
NO x is provided in Table 4-1 The NSPS applies to new or modified sources and may be more stringent than a best available retrofit technol ogy emission level. The development of the new emission standards for PM, 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, 162 Gross MW J.E. Corette Power Plant

Filterable Particulate Matter Sulfur Dioxide Nitrogen Oxides Limit Units Limit Units Limit Units Permitted Allowable (1) 0.26 lb/MMBtu 1 lb/MMBtu 0.4 lb/MMBtu Emission Rate (as S)

Typical Current 0.082 lb/MMBtu 0.46 lb/MMBtu 0.26 lb/MMBtu Emission rate (2001 to 2005 average) (from CEMS)) (from CEMS))

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)
Presumptive (4)
BART for 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 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 Febr uary 27, 2007, Final Rule (NSPS for EUSGUs) February 27, 2006, Final Rule (NSPS for EUSGUs) - the 2006 standards were revised to a gross MW output basis (equ ivalent 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 pre-existing pollutant-specific controls 5) Not applicable to either Colstrip or Corette under the BART Guidelines 6) Not applicable to Corette under BART Guidelines4-3 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 EPAs 1980 BART Guidelines for reasonably attributable visibility impairment, we concluded that NSPS standards generally, at th at time, represented th e best level sources could install as BART. In the 20-year pe riod 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 insta ll”. 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 original Subpart Da NSPS emission standa rds (circa (1979) as proposed BART controls would fall under this BART Final Rule admonition. However, the very recently updated NSPS limits for PM, 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 than BART for the PPL Corette coal fired boiler. The present NSPS
levels for PM 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 presumptiv e BART levels were used as the lowest level evaluated although they actual ly do not apply to Corette because Corette is below the size cutoff of the presumptive levels. 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 electri c 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 withseveral 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 w ith 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

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 PM collection device may be recycled to the absorber to attain optimal absorption and utilization of the reactant. Such systems generally a ttain greater than 90 percent control.

Dry Injection Dry solid absorbent is injected directly into the ductwork upstream of the PM collection
device. SO 2 removal occurs by adsorption of the pollutant on the particle surface and collection of the resulting solids with the fly ash in the PM control device. Lime or limestone based dry injection systems typically do not perform as we ll as FGD systems and attain 40 to 60 percent removal, but may achieve up to 90 percent re moval if another 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

• Low-NO x Burners (LNBs)

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

• LNBs with OFA

• Rotating Opposed Fire Air (ROFA)

• Combustion Improvement Techniques
Secondary Control Techniques

• Reburning

• Selective Catalytic Reduction (SCR)

• 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, Journa l of the Air and 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 be an increase in UBC of up to 2 percent, 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) or Air Staging 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 injection to obtain optimum results.

Selective Catalytic Reduction (SCR) The SCR process utilizes a honeycomb bed of active metal catalyst impregnated zeolite
to reduce NO x to its molecular nitrogen starting form. Ammonia or an ammonia-like substance such as urea is injected upstream of the catalys t bed and by using the proper injection 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 locate the catalyst bed in the boiler between the economizer outlet and the air preheater where th e 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.

4.1.4 Pollutant Emissions from Corette
The Gross 162 MW coal fired unit at the J. E. Corette power plant shows the following maximum daily actual PM, SO 2 and NO x emission rates in Table 4-2:

Table 4-2: Corette Emissions Summary
Fuel Control Heat Input Po llutant Filt Cond Total Filterable Condensable Total

Equip MMBtu/hr lbs/hr lbs/hr lbs/hr lb/MMBtu lb/MMBtu lb/MMBtu

Coal ESP 1941.1 PM 159.17 27.18 186.4 0. 082 0.014 0.096 Coal None 1894.5 SO2 N/ A N/A 1135 N/A N/A 0.60

Coal LNB 1930.4 NOx N/ A N/A 604 N/A N/A 0.314-9 The heat input rate shown a bove for PM is the highest da ily average heat input rate during the modeling years (2001-2003). The total PM emission rate applied to this heat input
rate is 0.096 lb/MMB tu based on stack test data. For SO 2 and NO x , the heat input rate shown is the daily average rate for the day of highest daily SO 2 and NO x emissions during the modeling years. The speciation of the PM emissions is de scribed in Section 2.3. Th e above data show that emission rates from Corette are already low due to the ESP control technology for PM, low sulfur coal (0.3 wt % S), and low-NO x burners. The 0.082 lbs/MMBtu filterable PM emission
rate and 0.014 lb/MMBtu condensables emissi on rate are based on stack emission tests conducted during the modeling year s. The current ESP technology is an old design and new designs are capable of meeting the BDT limit from the revised NSPS.

4.2 Evaluated Retrofit Technologies for J.E. Corette It is necessary, as part of th e BART analysis, to identify the most stringent control option and a reasonable set of options for each pollu tant. The following list of potential control technologies has been evaluated for J.E. Corette:

Filterable Particulat e Matter (Section 4.2.1)

• PM Control Alternatives Summary (Table 4-3)

• Electrostatic Precipitators (Table A4-4(a))

• Fabric Filters (Baghouses) (Table A4-4(b))

• Mechanical Collectors

• Wet Scrubbers
Sulfur Dioxide (Section 4.2.2)

• SO 2 Control Alternatives Evaluated (Table 4-7)

• Clean Fuel

• Dry Gas Scrubbing (Tables A4-7 and A4-8)

• Flue Gas Desulfurization (Wet Scrubbing) (Table A4-9)
Nitrogen Oxides (Section 4.2.3)

• NO x Control Alternatives Evaluated (Table 4-10)

• Upgrade of Low NO x Burners (Baseline) (Table A4-11)

• LNBs with SOFA (Table A4-12)

• Selective Non-Catalytic Reduc tion (SNCR) (Table A4-13)

• Selective Catalytic Reduction (SCR) (Table A4-14)
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 and4-10 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.

4.2.1 Particulate Matter Controls
4.2.1.1 Summary of PM Control Tec hnology Analyses for Corette Table 4-3 shows a comparison of the maximu m 24-hr emission rate used as a modeling
baseline and the control alternative emission rate modeled. The “NSPS case” of 0.015 lb/MMBtu is attained by either fabric filtra tion (FF) or electrosta tic precipitator technology (ESP) as described in this section. Mechanical collectors are not capable of attaining the high efficiencies of removal required and were ruled out from consider ation. Wet scrubbers, in use at the PPL Colstrip facility, are an available control option, however , this alternate technology was evaluated as primarily an SO 2 removal control option and is discussed in Section 4.2.2. Table 4-3 is presented to show the technol ogy cases evaluated for the BART analysis. While the modeled emission rates must represen t the maximum 24-hr emission rate during the study period, BART guidance requires use of anticipated actual emission rates for the cost analysis. In the case of the pol lutant PM, both FF and ESP control are assumed to be capable of attaining the BDT emission rate of 0.015 lb /MMBtu and were evaluated accordingly. In summary, only ESP and fabric filtration were further evaluated as filterable particulate control technologies for th e sub-bituminous coal-fir ed boiler at Corette.

4.2.1.2 Costs of Controls The costs of modern ESP and fabric filter particulate controls for application to the
Corette boiler were evaluated. The cost of c ontrol makes the assumption that adequate land acreage is available to locate the new devices.4-11 Table 4-3: PM Contro l Alternatives Evaluated

Pollutant Control Option Typical/Average Emission Rate for Cost Analysis (lb/MMBtu) Maximum Emission Rate for Modeling (lb/MMBtu)

PM (1) Base Case 0.082 (f) 0.014 (c) 0.082 (f) 0.014 (c)

NSPS Case 0.015 (f) 0.014 (c) 0.015 (f) 0.014 (c)

Note: (1) "f" refers to filterable and "c " refers to condensable particulate.

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 (AWMA, Air Pollution Engineering Manual , Air & Waste Management Association, Anthony J. Buonicore and Wayne T. Davis, eds., Van Nostrand Reinhold, 1992) for 99 percent contro l. Table A4-4(a) shows the co sting calculations for an 82 percent reduction from present emissions leve ls, which would reduce filterable particulate emissions to 0.015 lb/MMBtu. The table presented illustrates the costs for an ESP designed to
control filterable PM to the NSPS level for ne w sources of 0.015 lbs/MMBtu from the current
level. This is a fair and reasonable calculatio n of cost effectiveness (C E) to attain the NSPS
level. The summary analysis of the cost of ESP control presented in Table 4-4 (see Appendix A, Table A4-4(a) for details) was prepared usi ng the standard cost es timation 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 ESP. EPA factors specifically developed for ESP technology were used. An annualized capital cost of the equipment was determined using a capital rec overy factor based on an equipment life of 11 years, and assumed that money is available at an annual interest ra te of 7 percent. All equipment cost data are corrected to 2007 dollars. The cost estimates have been prepared for the Corette boiler using an annual capac ity factor of 89%. The electrification of the fields and rapper costs are based on the specific co llection area estimated for the Corette boiler in4-12 Figure 4-1: Cost Analysis of ESP Control

Table 4-4: Particulat e Cost Analysis Summary

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

Added ESP Control $10,721,795 507 $21,149 Added Fabric Filtration $8,283,582 507 $16,339

accordance with EPA recommendations. The annualiz ed cost is an incremental cost to reduce the current PM emissions from the present 0.0 82 lb/MMBtu filterable emission rate to the present NSPS BDT level of 0.015 lb/MMBtu. E quipment maintenance, administrative annual costs, and all calculations use the sta ndardized OAQPS control costing methods.
The estimated cost calculated for a modern technology ESP to obtain the NSPS BDT for new sources of 0.015 lb/MMBtu is $21,149 per t on assuming that the unit operated at the4-13 average annual capacity factor from among the three modeling y ears (2003-2005). This cost per year assumes an annual capacity factor of 89 percent. These estimates are based on OAQPS cost factors and engineering judgment and incl ude a 1.4 multiplier on equipment cost as recommended by EPA in the Control Cost Manual.
The cost estimate of a fabric filter added to the existing PM control to reduce emissions
from 0.082 lb/MMBtu to the BDT level of 0.015 lb/MMBtu is presented in Appendix A, Table A4-4(b). A capital cost, adjust ed to 2007 dollars was estimated at $50/kW. After application of the OAQPS cost factors to this cap ital cost and adding the annual material and maintenance costs for fabric filters, a CE value of $16,339 was determ ined. This is for an add-on fabric filter in series with the existing ESP controls.
The cost of venturi sc rubber installation is presented in Section 4.2.2. The control of PM with wet scrubbing is evaluated in conjunction with flue gas desu lfurization (FGD) technology. A change to wet scrubbing controls would not be considered separately from the FGD aspect of
such a device and is ther efore discussed in the SO 2 technology section.

4.2.1.3 Energy In addition to the costing data developed for each potential PM control option, energy consumption, in terms of the fan power to drive the exhaust gas through th e control devices is a parameter that can be readily esti mated for ESP, fabric filter, a nd venturi scrubber control. The energy cost of the control options is included in the cost effectiveness Tables A4-4(a) and A4- 4(b) in Appendix A. This motive power is directly related to the pressure drop of the particular control option and the following equation is o ffered by EPA as being representative of the required fan power for control device s 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 4-5 is presented to illust rate the pressure dr op/power consumption requirements of the four common types of PM cont rol devices. Each technique has predictable energy consumption in te rms of the pressure dr op associated with th e control option. For example, an ESP has numerous parallel flat plates with electrode wires to charge the particulate4-14 Table 4-5: 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

passing into the collector. The pressure drop w ithin the device is very low. Fabric filter baghouses expectedly have a higher pressure drop due to the fabric filt er 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 typical 4” w. c. drop, and the venturi scrubber (VS), attains its relati vely high collection efficiency at the expense of up to a 100” pressure drop required for fine PM collection.

4.2.1.4 Non-Air Quality Environmental Impacts All PM controls for Corette, whether upgraded or new, generate a PM waste stream. The current ash collected by the ESP is sold as a product to the cem ent industry. Operation of PM controls to collect an additional 82 percent of current PM emissions at Corette would generate approximately 507 tons per year of additi onal fly ash waste based on 2003 to 2005 annual operation of the units. For the venturi scrubber control option, reh eating would be mandatory and would reduce the available electrical ge neration due to the energy required to heat the exhaust. Reheating would be required to satisfy plume buoyancy perm it requirements for the Corette plant. Based on the Colstrip boiler reheating experience, a 30 MW loss in power output from the plant would result to eliminate a highly visible steam plume.

4.2.1.5 Remaining Useful Life The PPL Corette boiler is expected to remain in operation for the foreseeable future and therefore an 11-year control equipment life, consistent with the financial approach of Corette amortization has been assumed for the control cost analyses.4-15 4.2.1.6 Visibility Modeling The predicted visibility impacts from the present (base case) Corette 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 4-6. Shown in the table are the hi ghest of the annual 98th percentiles of daily modeled vi sibility impacts among the thr ee years modeled (2001-2003) and the seven Class I areas modeled. The highest of those visibility impact s among the Class I areas modeled are presented. For the modeled cont rol 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.

Table 4-6: Summary of Mo deling Results for Particulate

Deciview Difference (2) Emissions (1) Control Option lb/MMBtu lb/hr Max 98th Percentile Prediction(2)

(deciviews) Relative to Base Case Incremental

Base Case 0.082 (f) 0.014 (c) 159.2 (f) 27.2 (c) 0.645 --- ---

NSPS Case 0.015 (f)) 0.014 (c) 29.11 (f) 27.2 (c) 0.633 0.032 (2) 0.032

NOTES: (1) "f" refers to filterable and "c" refers to condensable particulate. (2) The maximum (98th per centile) deciview impact occu rs at the UL Bend Class I area and the maximum difference of the 98th percentiles between the base case and control alternative evaluated occurs at the Washakie Class I area.

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

4.2.2 Sulfur Dioxide Controls
4.2.2.1 Controls and Emission Rates Evaluated Table 4-7 presents the modeled emission rates and the typical/averag e emission rates used in the costing analysis for the control alternativ es selected. For the PRB coal burned at Corette, the installation of controls is expected to result in 25 to 70 percent reduction4-16 Table 4-7: SO 2 Control Alternatives Evaluated

Pollutant Control Option Typical/Average Emission Rate for Cost Analysis (lb/MMBtu) Maximum Emission Rate for Modeling (lb/MMBtu)

SO 2 Base Case 0.46 0.60 Dry Injection (25% Reduction) 0.35 0.46

Dry Injection (70% Reduction) 0.15 0.20

Wet Scrubber 0.15 0.15

over current emission rates. Two dry gas scr ubbing emission rates and installation of a wet
scrubber were evaluated for the costs of control and other associated impacts.
The sub-bituminous coal fired boiler at Corett e utilizes low-sulfur (0.3 weight percent sulfur) Powder River Basin coal. With long term contracts for the use of such coal, the baseline
emissions for the Corette boiler are already low at 0.6 lb/MMBtu of SO 2 , corresponding to the maximum 24-hr average emissions during the mode ling years, and are ac tually lower with a typical emission rate of 0.46 lb/MMBtu when the actua l sulfur content of the fuel is considered. The Corette boiler is equipped with CEMS for SO 2 which were used to determine the maximum 24-hr average SO 2 emissions. Coal cleaning to reduce SO 2 emissions in addition to that performed prior to delivery to
Corette would have no substantial effect on SO 2 emissions. PRB coal already has maximum sulfur levels of 0.3 weight per cent, and any further reduction in this fuel sulfur content by any mechanical means is not expected. The option to ga sify the coal for sulfur removal is a complete change in the method of operation for Co rette which was given no consideration. The controls evaluated to improve SO 2 emission rates to 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 low le vels, the dry techniques are limited in their ability to attain very high SO 2 removals without impacting the PM emissions with the existing
ESP controls. In view of the alkaline nature of PRB coal, some inherent reaction between SO 2 and flyash likely accounts for a typical SO 2 emission rate (from CEMS data) of 0.46 lb/MMBtu. PPL estimates that about a 25 percent increase in SO 2 removal can be attained by chemical addition using dry injection technologies (injec tion of lime or limestone) before impacting the4-17 PM emission rate. If, however, a new ESP were to be installed, additional SO 2 removal could be attained without impacting PM compliance.
Installation of a wet scrubber (FGD) has been evaluated for Corette. As discussed above,
the alkaline nature of the PRB coal burned at Corette is conducive to SO 2 removal which is more evident with water scrubbing. Based on the PPL f acility at Colstrip, wet scrubbing using venturi scrubbers produces approximately 75 percent SO 2 removal without the addition of lime in Units 1 and 2 at Colstrip. Based on the PPL experience at Colstrip and EPA cost estimations for wet scrubbers, an analysis of wet scrubbing is includ ed herein. An emission rate of 0.15 lbs/MMBtu
was used as the control level. This level was us ed because it is the presumptive BART emissions level, although the Corette boiler is below the size threshold for which this presumptive level is
intended.

4.2.2.2 Cost of SO 2 Controls PPL used EPA cost estimation techniques to ev aluate the cost implic ations of wet and dry technology applications for SO 2 to the Corette boiler (EPA-CIAC Fact Sheet, EPA-452/F-03- 034, Air Pollution Control Technology Fact Sheet, Flue Gas Desulfurization (FGD) – Wet, Spray dry, and Dry Scrubbers, 2003). The EPA fact sheet is a summary of the costs and capabilities of various FDG techniques to coal fired boilers. A large variation in the capital cost of such systems in units of $/MW is obser ved. While EPA lists a range of cost effectiveness (CE) values in $/ton of SO 2 controlled that ranges from $500 to $4,000, the low sulfur PRB coal makes the CE for Corette more expensive. The EPA data show a capital cost for spra y dry controls that ranges from 150 to 1500 $/KW and an operations and maintenance (O&M) cost of $10 to $300 per KW. Using the low end of the range for the nominal case of dry chemical addition to boiler exhaust a nd utilization of the existing ESP, Table 4-8 is a summary of the cost analysis of the SO 2 control options. Details of each analysis are presented in Appendix A, Tables A4-7 and A4-8. A change to wet scrubbing at Corette was ev aluated for CE by use of the average capital cost of such systems as indicated by EPA on th eir fact sheet. The es timated cost of a wet
scrubber to control emissions to 0.15 lb/MMBtu, presented in Ta ble A4-9 in Appendix A, is $25,480 including the loss in revenue due to plume reheating.4-18 Table 4-8: SO 2 Control Cost Summary

Option Description Total Annual Tons controlled Cost Incremental Cost ($) Effectiveness CE $/ton (CE) $/ton
Dry Gas Scrubber Option 1 $6,773,630 832.3 $8,138 Dry Gas Scrubber Option 2 $87,797,502 2345.7 $37,429 $53,538 Wet Scrubber (FGD) $59, 768,829 2345.7 $25,480 $35,017

4.2.2.3 Energy Impacts of SO 2 Controls The most significant impact of SO 2 controls at Corette would occur with a change to wet scrubbing controls for SO 2 . The operation of wet venturi scr ubbers has an energy cost in terms of additional fan power to overcome higher pressure drops (see Table 4-5). Additionally, based on experience at PPL Colstrip, reheating of th e plume to meet permit requirements for plume buoyancy would reduce the availa ble power output from Corett e by approximately 30 MW or 18.5 percent.

4.2.2.4 Non-Air Quality Impacts of SO 2 Controls Corette currently generates revenue from the sale of 30,000 tons of PM to the cement industry at $4/ton. Contamination of the PM as h with dry scrubbing wastes would render the solids unacceptable for use as a cem ent additive. This, coupled with the added PM due to sulfite and sulfate and excess scrubbing reagent, and th e waste disposal cost of $40/ton are strong disincentives for application of the additional SO 2 controls. The use of limestone contributes to gr eenhouse gas emissions by release of the CO 2 portion of the limestone reaction with SO 2 . Full implementation of dr y gas scrubbing at Corette
would release almost 1700 tons of CO 2 in the process from calcinations of limestone.

4.2.2.5 Remaining Useful Life The life of the Corette boiler is expected to exceed the study period and is projected to have no effect on the costing an alyses for this facility.4-19 4.2.2.6 Visibility Modeling The predicted visibility impacts fr om the present (base case) Corette SO 2 , NO x and particulate emissions and for the alternative SO 2 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 three years modeled (2001-2003) and the seven 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 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.

Table 4-9: 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 Incremental

Base Case(1) 0.60 1135.0 0.645 --- --- Dry Injection (25% Reduction) 0.46 892.9 0.568 0.077 0.077

Dry Injection (70% Reduction) 0.20 388.2 0.446 0.199 0.147

Wet Scrubber 0.15 291.2 0.407 0.238 0.049
NOTE: The maximum 98th percentile base case deciview impact of 0.645 deciviews occurs at the UL Bend Class I area. Maximums (98th percentiles) and maximum changes from them for the control a lternatives occur at the UL Bend, Washakie or North Absaroka Class I Areas.

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

4.2.3 NO x Controls
4.2.3.1 NO x Controls and Emission Rates Evaluated At Corette, four control options were ev aluated as presented in Table 4-10. The maximum and the typical/average emission rates are those determined from review of CEMS4-20 data and estimates of how the indicated controls will perform if applied at Corette. The Corette boiler is a tangentially fire d unit equipped with low-NO x burners. A review of CEMS data revealed that the maximum daily NO x emissions during the 2001 to 2003 evaluation period corresponded to a NO x emission rate of 0.31 lb/MMBtu. Wh ile this value was used for BART modeling, a baseline value of 0.26 lb/MMB tu was used as a typical average NO x emissions rate for the BART cost analysis. This is maintained by operation of the low-NO x burners and close coupled over-fire air presently in operation at Corette.
Table 4-10: NO x Control Alternatives Evaluated

Pollutant Control Option Typical/Average Emission Rate for Cost Analysis (lb/MMBtu) Maximum Emission Rate for Modeling (lb/MMBtu)
NO x Base Case 0.26 0.31

Boiler Tuning 0.23 0.27 SOFA 0.18 0.21 SNCR 0.16 0.17 SCR 0.15 0.15

PPL evaluated four control options for NO x reduction at Corette that included boiler tuning, SOFA, SNCR, and SCR add-on controls. Tuning or adjustment of the current configuration is predicte d to reduce emissions to 0.23 lbs/MMBt u with a small, one time cost of $250,000. Adding SOFA and readjustment of the entire air distribution to the firebox is predicted to reduce NO x to 0.18 lb/MMBtu. Th e addition of SNCR is predicted to produce
almost no additional NO x reduction (to 0.16 lb/MMBtu) ove r that obtained by SOFA at significant additional cost. A hot-side SCR to reduce NO x to the presumptive level for tangentially fired sub-bituminous coal-fired boilers of 0.15 lb/MMBtu was analyzed. This level (0.15 lb/MMBtu) was evalua ted as a minimum emissions level because it is the presumptive BART emissions level, although the Corette boiler is below the size threshold for which this presumptive level is intended. Reburning technology for application to Core tte was not evaluate d. 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.4-21 4.2.3.2 Cost of NO x Controls A summary of the costing analysis of the various control options for NO x are presented in
Table 4-11. The detailed costin g of the various options for NO x reduction is presented in Appendix A, Tables A4-11 through A4-14. Tabl e A4-11 presents the annualized cost of implementation of a one-time tuning of the pres ent LNB configuration. Table A4-11 utilizes information from a 2004 World Bank article (World Bank Low NO x Burner Costing, http://www.worldbank.org/html/fpd/em/power/EA/ mitigatn/aqnolow.stm, August 2004) on cost estimation for LNB technology and LNBs with over-f ire air injection. The cost estimate for adding SOFA to the LNB technology, see Table A4 -12, already present was estimated using the lower limit of the range of $10/kW because a base line LNB is already installed and operating at Corette. Reduction from the present emission ra te of 0.26 lb/MMBtu to 0.18 lb/MMBtu results in a CE of $914/ton (in 2007 dollars) of NO x controlled and an incremental cost of $1,375/ton over tuning alone.
Table 4-11: NO x Costing Analysis Summary

Option Description Total Annual Tons controlled Cost Incremental Cost ($) Effectiveness CE $/ton $/ton
Boiler Tuning $33,339 227.0 $147 Separated Over-Fire Air $553,554 605.4 $914 $1,375 SNCR $1,303,471 756.4 $1,723 $4,966 SCR $3,624,027 832.4 $4,354 $30,518

Conventional SNCR and SCR technologies were estimated using the EPA Control Cost Manual (U.S. Environmental Protection Agency, EPA Air Pollution Cont rol Cost Manual, 6 th ed., EPA-452-02-001, January 2002). The cost analysis for application of SNCR is presented in Table A4-13 and the cost analysis for applica tion of SCR is presented in Table A4-14. For SNCR, an emissions reduction from the pres ent level of 0.26 lb/MMBtu to 0.16 lb/MMBtu results in a CE of $1,723/t on (in 2007 dollars) of NO x controlled and an incremental cost of $4,966/ton over SOFA. For SCR, a reduction from the present level of 0.26 lb/MMBtu to 0.15 lb/MMBtu results in a CE of $4,354/ton (in 2007 dollars) of NO x controlled and an incremental cost of $30,518/ton over SNCR.4-22 4.2.3.3 Energy Impacts of NO x Controls Energy Impacts which accompany NO x controls are relatively few. The installation of SOFA can result in slight improvements in heat ra te. This potential benefit has not been taken into account in this costing an alysis. The power consumption of the fans and pumps and added pressure drop energy consumption of the add-on contro ls has been factored in to the cost analysis.

4.2.3.4 Non-Air Quality Environmental Impacts of NO x Controls In addition to the increase in ash accompanying dry gas control of SO 2 using the present or a new ESP, SO 2 and NO x controls would contribute to re ndering the current ash unsalable. While minimal as compared to the ash changes resulting from dry scrubbing techniques, some increase in carbon due to impacts to the combus tion process could render the ash unsalable if a
NO x option is implemented independent of an SO 2 control option.

4.2.3.5 Remaining Useful Life The life of the Corette boiler is expected to exceed the study 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 fr om the present (base case) Corette NO x , SO 2 and particulate emissions and for the alternative NO x control levels evaluated are summarized in
Table 4-12. Shown in the table ar e the highest of the annual 98t h percentiles of daily modeled visibility impacts among the three years modeled (2001-2003) and the seven 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 emissions reduction attaine d. The visibility modeling results are described and presented in more detail in Section 4.3 and Appendix B.4-23 Table 4-12: Summary of Modeling Results for NO x

Deciview Difference(2) Emissions Control Option lb/MMBtu lb/hr Max 98th Percentile Prediction(2)

(deciviews) Relative to Base Case Incremental

Base Case 0.31 604.0 0.645 --- --- Boiler Tuning 0.27 524.1 0.616 0.043 (2) 0.043

SOFA 0.21 407.6 0.573 0.098 0.055
SNCR (1) 0.17 330.0 0.544 0.125 0.055

SCR 0.15 291.2 0.530 0.138(2) 0.054
NOTES: (1) The deciview impacts for the SN CR case were interpolated between the SCR and SOFA modeling results. All other cases were modeled.
(2) The maximum 98th percentile base case deciview impact of 0.645 deciviews occurs at the UL Bend Class I area. Maximums (98th percentiles) and maximum changes from them for the control alternatives occur at the UL Bend, Washakie or North Absaroka Class I Areas.

4.3 Visibility Modeling Section 4.3.1 describes the general visibil ity modeling procedur es and Section 4.3.2 summarizes the results. The modeling procedures a nd results are is described in more detail in Appendix A.

4.3.1 General Modeling Procedures
The CALPUFF model was used to assess th e impact of emissions from Corette on visibility in the federal mandatory Class I areas within 300 km of the plant, as identified in Section 2.3 and shown in Figure ES-1. CALPUFF (Scire et al ., 2000) is EPA's guideline model for long range transport and their recommende d model for BART analyses. Modeling was conducted with three years of hourly meteor ological 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 the Corette boiler as subject to4-24 BART and providing preliminary modeling results. The modeling conducted by TRC for PPL is
based on those data files w ith the following exceptions:

• Speciation of filterable and condensable pa rticulate emissions was revised by PPL based on stack test data available dur ing the modeling years (2001-2003).

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

The present (base case) emissions modeled ar e presented in Table 2-1 and Table 2-2. The particulate emissions presen ted include a breakdown of the pa rticulate emissions by species and size fraction. Table 4-13 presents the emi ssions (and a summary of the modeling results as described below) for each of the control scen arios evaluated. These modeled emissions are based on the maximum actual daily operation of the Corette boiler during the three-year modeling period as described in Section 2.2. The present base case visibility impact of th e Corette boiler in each Class I area in terms of the deciview haze index was determined by co mparing the combined visibility impact of the boiler's present emissions and the annual average background visibility level provided in the WRAP files against the backgroun d level alone. The similarly modeled visibility impacts of
each of the control alternatives were then co mpared against the base case and each other to determine the degree of visibility improve ment 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 emissions and the emissions control scenarios evaluated are presented and compared for each pollutant in Table 4-13. The 98th percentile comparison level, using the highest 98th percentile prediction from among th e years modeled, is recommended by EPA as a visibility metric. The values presented are the highest of t hose visibility impacts among the seven Class I areas evaluated. A summary of th e results for each Class I area is presented in Appendix A. Under the present emissions case, the maximu m 98th percentile Corette visibility impact
as is 0.645 deciviews at the UL Bend Class I area . The deciview impact for each of the control alternatives is also provided in the table. For each control alte rnative modeled, the emissions of the controlled pollutant were at its controlled level and the emissions of the non-controlled pollutants were at their base case levels. Also provided in the table ar e the net changes in4-25 Table 4-13: Summary of Modeling Results

Deciview Difference (2) Emissions (4) Pollutant Control Option lb/MMBtu lb/hr Max 98th Percentile Prediction(2)

(deciviews) Relative to Base Case Incremental

SO 2 Base Case(1) 0.60 1135.0 0.645 --- --- Dry Injection (25% Reduction) 0.46 892.9 0.568 0.077 0.077

Dry Injection (70% Reduction) 0.20 388.2 0.446 0.199 0.147

Wet Scrubber 0.15 291.2 0.407 0.238 0.049

NO x Base Case(1) 0.31 604.0 0.645 --- --- Boiler Tuning 0.27 524.1 0.616 0.043 0.043

SOFA 0.21 407.6 0.573 0.098 0.055
SNCR (3) 0.17 330.0 0.544 0.125 0.055

SCR 0.15 291.2 0.530 0.138 0.054

PM Base Case(1) 0.082 (f) 0.014 (c) 159.2 (f) 27.2 (c) 0.645 --- ---

NSPS Case 0.015 (f)) 0.014 (c) 29.11 (f) 27.2 (c) 0.633 0.032 0.032

NOTES: (1) The base case is the same for all three pollutants. (2) The maximum 98th percentile base case deciview impact of 0.645 deciviews occurs at the UL Bend Class I area. Maximums (98th percentiles) and maximum changes from them for the control alternatives occur at the UL Bend, Washakie or North Absaroka Class I Areas. (3) The deciview impacts fo r the SNCR case were interpolat ed between the SCR and SOFA modeling results. All other cases were modeled. (4) "f" refers to f ilterable and "c" refers to condensable particulate.

deciview impacts from the plant for each control a lternative. These are pr ovided relative to the base case and also incrementally relative to the immediately pr eceding control al ternative in
terms of the level of emissions reduction attained. The net ch anges presented are the maximum changes of the 98 th percentile impacts at any of the Class I areas.5-1 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. Corette was determined to be BART-eligible under the Federal Regional Haze Rule by EPA Region 8. Region 8 further found that the Core tte boiler is subject to possible particulate matter, SO 2 , and NO x retrofit controls for BART analysis. EPA’s BART Guideline approach has been app lied to Corette to identify the “best system of continuous emission reduction” applicable to the plant for filterable particulate control, SO 2 reduction and the control of NO x . A range of demonstrated c ontrol alternatives for large tangentially-fired coal boilers was evaluated considering co sts, energy and environmental impacts, remaining useful life of the units and modeled visibility improvements. Electrostatic precipitators (ESP), fabric filt ers (baghouses), mechanical collectors and wet scrubbers were considered for PM. Dry and wet scr ubbing techniques were considered for SO 2 , 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 the Corette boiler and the BART contro l 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 PPL stack test data and a few adjustments were made to the modeling as described in Appendix B. Modeling was conducted to determ ine visibility impacts in the seven mandatory
Class I areas within 300 km of Corette. The cost analyses and modeling were based on actual emissions. For the cost analyses typical em ission rates representati ve of average 30-day emissions were used. For the modeling analys es maximum daily emissions during the modeling years (2001-2003) were used. A summary of the results of the cost evaluati ons is provided in Tabl e 5-1, both relative to the present emissions and incrementally from one le vel of control to the next. A summary of the modeled visibility impacts of the present emissi ons and the control alternatives is provided in Table 5-2, both relative to the present emission s and incrementally. The indicated visibility5-2 improvements in Table 5-2 are based on the differences between the maximum annual 98 th percentile daily predicted visibility impacts at each site for each le vel of control, regardless of the meteorological year modeled for each predictio n. The highest of these differences among the seven Class I areas modeled is presented. The highest modeled annual 98 th percentile daily visibility impact of emissions from the
Corette boiler at maximum actual load is predicted to occur in the UL Bend National Wildlife Refuge (NWR) Class I area and is 0.645 deciviews. This is only slightly above the 0.5 deciview level that EPA has proposed as a level at which a source may contribute to a visibility impact but
well below the 1.0 deciview leve l EPA employs as a level to indicate that a source causes a visibility impact. From a visibility improvement basis with respect to filterable particulate matter, only a 0.03 deciview improvement, which is not visually di scernable, would result from installation of
either ESPs or fabric filters. Consequently, implementation of additional particulate control at
Corette is not warranted. With respect to sulfur dioxide only a 0.08 deciview reduction is achieved with lime/limestone addition to either the boiler or fuel. The incremental improvements by reducing
emissions to a 0.15 lb/MMBtu em ission rate through either dry injection or wet scrubbing are 0.15 deciviews or less. Such improvements are not discernable to the human eye and implementation of these control technologi es are, therefore, not warranted. Finally, with respect to nitrogen oxides on ly a 0.04 deciview improvement results from implementation of SOFA, which is not discernable, and the incr emental improvements of further
controls are 0.06 deci views or less. As a result of the studies and analysis, we are proposing that the existing permit limits for particulate, SO 2 and NO x are BART.5-3 Table 5-1: Summary of Cost E valuation Results Based on Emissions
CONTROL EQUIPMENT COST SUMMARY FOR THE PPL MONTANA, LLC, J.E. CORETTE POWER PLANT
Particulate Matter Sulfur Dioxide Nitrogen Oxides Evaluated

Rate Units Evaluated Rate Units Evaluated Rate Units Current Emission rate 0.082 lb/MMBtu 0.46 lb/MMBtu 0.26 lb/MMBtu (CEMS) (2001 to 2005 average)

BDT (1) from 2006 NSPS for 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 $/ton Option Evaluated CE Inc CE Option Evaluated $/ton (5) Inc CE Rate Rate Rate lb/MMBtu lb/MMBtu $/to n $/ton lb/MMBtu $/ton Control New ESP (2) 0.015 $21,149 Present 0.46 $0 Present (4) 0.26 $0 Options Added FF 0.015 $16,339 DGS (2) 0.35 $8,138 Tuning 0.23 $147 DGS (2) 0.15 $37,429 $53,538 SOFA 0.18 $914 $1,375 WS-FGD (3) 0.15 $25,480 $35,017 SNCR 0.16 $1,723 $4,966 SCR 0.15 $4,354 $30,518
Notes 1) 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/MMBtu input values listed in paren) 2) Adding lime or limestone injection makes flyash unsalable - Includes added waste disposal cost (two options of 23% and 67% control may be possible - precip upgrade required for 67%) The CE for the ESP is the cost of a new technology ESP to reduce PM from 0.082 to 0.015 lb/MMBtu 3) If a wet scrubber is added, the low sulfur PRB coal could be replaced with higher sulfur coal. (30 MW penalty for plume reheating) Includes lost revenue from ash sales. 4) It is assumed that boiler tuning and proper operation can improve the current 0.26 lb/MMBtu to 0.23 lb/MMBtu at minimal cost 5) Each technique applied individually; incremental cost effectiveness is that from previous option cost

Table 5-2: Modeled Visibility and Visibility Improvements

Modeled Modeled Modeled Rate (1) Prediction (3) from Rate Prediction from Rate Prediction from Option (lb/MMBtu) (deciviews) Present Inc (6) Option (lb/MMBtu) (deciviews) Present Inc (6) Option (lb/MMBtu ) (deciviews) Present Inc (6) Present 0.082 0.645 n/a n/a Present 0.6 0.645 n/a n/a Present 0.31 0.645 n/a n/a New ESP 0.015 0.633 0.032(5) 0.032(5) DGS(2) 0.46 0.568 0.077 0.077 Tuning(4 ) 0.27 0.616 0.043 0.043 Added FF 0.015 0.633 0.032(5) 0.032(5) EDGS(2) 0.2 0.446 0.199 0.147 SOFA 0.21 0.573 0.098 0.055 WS-FGD 0.15 0.407 0.238 0.049 SNCR 0.17 0.544 0.125 0.055 SCR 0.15 0.53 0.138 0.054

Notes: (1) The modeled emission rate is the rate corresponding to the maximum daily emissions during the modeling years (200 1-2003). (2) See corresponding footnote in Table ES-1 (3) Prediction is from all three pollutants at present emissions except the one being controlled (4) See corresponding footnote in Table ES-1. (5) The maximum improvement occurs at a different Class I area than the maximum prediction. (6) Inc = Incremental improvement from the immediately prec eeding control alternative in terms of level of emissions reduct ion attained. Improvement Improvement Improvement Filterable PM10 Sulfur Dioxide Nitrogen Oxides6-1 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 U nder 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 Guid e for the CALPUFF Dispersion Model , Earth Tech, Inc. January 2000.

# APPENDIX A:
COST ANALYSIS TABLESA-1 Table A4-4(a): PPL BART Cost Analysis Electrostatic Precipitator Particulate ControlA-2 Table A4-4(a): PPL BART Cost Analysis continuedA-3 Table A4-4(b): PPL BART Cost Analysis Pulse Jet Fabric Filter for A dditional Particulate ControlA-4 Table A4-4(b): PPL BART Cost Analysis continuedA-5 Table A4-7: PPL BART Cost Analysis Dry Injection (with Low Sulfur Coal) Sul fur Dioxide Control (25% Reduction)A-6 Table A4-8: PPL BART Cost Analysis Dry Injection (with Low Sulfur Coal) Sul fur Dioxide Control (70% Reduction)A-7 Table A4-9: PPL BART Cost Analysis Wet Scrubbing (with Low Sulfur Coal) Sulfur Dioxide ControlA-8 Table A4-11: PPL BART Cost Analysis

Upgrade of Current LNB TechnologyA-9 Table A4-12: PPL BART Cost Analysis SOFA Addition to LNB TechnologyA-10 Table A4-13: SNCR Cost Analysis for CoretteA-11 Table A4-14: SCR Cost Analysis for Corette

# APPENDIX B:
CALPUFF APPLICATION FOR BART
ASSESSMENTS AT PPL CORETTE

# CALPUFF Application for BART Assessments at PPL Facility Corette in Montana for the North Absaroka, Yellowstone, Washakie, UL Bend, Teton, Gates of the Mountains and Red Rock Lakes 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 2007i TABLE OF CONTENTS

Page

1.0 INTRODUCTION .............................................................................................................. 1
2.0 SOURCE DESCRIPTION.................................................................................................. 3
3.0 GEOPHYSICAL AND METEOROLOGICAL 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 ................................................................................................................. 27ii LIST OF FIGURES

Page
Figure 2-1. Aerial photo of the PPL Corette facility 4 Figure 3-1. Terrain contours (m MSL) at 2 km resolution for the 782 km by 572 km CALMET and CALPUFF computational domains. The Class I areas and the Corette 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 areas and the location of Corette PPL are also shown. 10 Figure 3-3. Surface stations. The stations in cluded 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 stations used in th e CALPUFF modeling. 15 Figure 4-1. Locations of receptors at North Absaroka, Yellowstone, Washakie, Teton, Red Rock Lakes, Gates of the Mount ains and UL Bend Class I areas. 19iii LIST OF TABLES

Page

Table 2-1. Corette: Source Parameters and Emission Rates – Base Case 5 Table 2-2. Corette: Particle Speciation – Base Case 2-2 Table 2-3. Corette: Emissions for Ba se Case and Control Alternatives 6 Table 3-3. Meteorological Data So urces 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 base d on the Representative IMPROVE Site Location, for Visibility Method 6 applications 22 Table 5-1. Summary of Visibi lity Results for Base Case 24 Table 5-2. Summary of Visibility Results for Alternative 1 (SO 2 Reduced 25% by Limestone Injection) 24 Table 5-3. Summary of Visibility Results for Alternative 2 (SO 2 Reduced 70% with a Dry Scrubber) 24 Table 5-4. Summary of Visibility Results for Alternative 3 (SO 2 Reduced to 0.15 lb/MMBtu with a Wet Scrubber) 25 Table 5-5. Summary of Visibility Results for Alternative 4 (NO x Reduced through Boiler Tuning) 25 Table 5-6. Summary of Visibility Results for Alternative 5 (NO x Reduced with SOFA) 25 Table 5-7. Summary of Visibility Results for Alternative 6 (NO x Reduced to 0.15 lb/MMBtu with SCR) 26 Table 5-8. Summary of Visibility Results for Alternative 7 (Filterable PM Reduced to 0.015 lb/MMBtu) 261 Introduction 1.0 INTRODUCTION TRC Environmental Corporation has conducted a Best Available Retrofit Technology (BART) analysis for the coal-fired boiler at PPL Montana' s Corette 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. The Montana 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 webs ite (http://pah.cert.ucr.edu/aqm/308/bart.shtml) provided by EPA Region 8 in a February 28, 20 07 letter to PPL identifying the Corette unit as subject to BART and providing preliminary modeling results. The Corette PPL plant is located along the Yellowstone River on the outskirts 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 impair ment 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 “B ART-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 seven Class I areas are located within this radius: North Absaroka WA, Yellowstone National Park (NP), Washakie WA, UL Bend WA, Teton WA, Gates of the Mountains WA and Red Rock Lakes WA.2 Introduction 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 effects. 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 hour ly meteorological datasets developed from the fifth generation Penn State/NCAR (National Center For Atmosp heric 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, variab ility 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 the Montana Protocol, Table 3.0 lists the versions 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 ve rsion 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 5.3 Source Description 2.0 SOURCE DESCRIPTION
The Corette Power Plant is located near Billings, Montana. There is one coal-fired boiler at the plant that is a BART-eligible source. Figure 2-1 shows the aerial photo of the Corette 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 conde nsable portions, with the condensable portion further split into organics and inorganics and th e filterable portion split into fine particulate matter, elemental carbon and coarse particulate matte r parts based on available stack test data 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 emissions 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.4 Source Description Figure 2-1. Aerial photo of the PPL Corette facility5Source DescriptionTable 2-1...........................................Corette: Source Parametersand Emission Rates – Base CaseLambert ConformalCoordinates1StackID #LCC East LCC NorthStackHeightBaseElevationDiameterGas ExitVelocityStackGas ExitTemp.SO2EmissionsH2SO4Emissions2NOxEmissionsPM10Emissions3km km m m m m/s Klb/hr lb/hr lb/hrlb/hrUnit 1 678.999 170.084 106.7 947.3 3.5136.58 389.0 1135.0 21.74 604.0 186.351The 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).4PM10emission rate includes filterable and condensable emissions. The condensable component includes H2SO4emissions.Table 2-2........................................................................... Corette: Particle Speciation – Base CaseStack ID #Particle speciationCondensableFilterableOrganiccondensable (OC)H2SO4CoarseSoilElementalCarbon (EC)FilterablePM10CondensablePM10M1=0.48, SD1=2.0 μmM1=0.48, SD1=2.0 μm% % lb/hrlb/hr lb/hrlb/hrlb/hrUnit 1 85.4 14.6 5.44 21.74 88.43 68.12 2.621M 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.6Source DescriptionTable 2-3..............................................Corette: Emissions for Base Case and Control AlternativesStackID #CondensableFilterableSO2EmissionsNOxEmissionsPM10Emissions3Organiccondensable(OC)H2SO4CoarseSoilElementalCarbon(EC)lb/hrlb/hrlb/hrlb/hr lb/hr lb/hrlb/hrlb/hrUnit 1 Base Case 1135.0 604.0186.35 5.44 21.74 88.43 68.12 2.62Control Alt. 1 892.9 604.0186.35 5.44 21.74 88.43 68.12 2.62Control Alt. 2 388.2 604.0186.35 5.44 21.74 88.43 68.12 2.62Control Alt. 3 291.2 604.0186.35 5.44 21.74 88.43 68.12 2.62Control Alt. 4 1135.0 524.1186.35 5.44 21.74 88.43 68.12 2.62Control Alt. 5 1135.0 407.6186.35 5.44 21.74 88.43 68.12 2.62Control Alt. 6 1135.0 291.2186.35 5.44 21.74 88.43 68.12 2.62Control Alt. 7 1135.0 604.056.29 5.44 21.74 16.17 12.46 0.48NOTES: Control Alt 1 = SO2reduced 25% by limestone injection.Control Alt 2 = SO2reduced 70% with a dry scrubber.Control Alt 3 = SO2reduced to 0.15 lb/MMBtuwith a wet scrubber.Control Alt 4 = NOxreduced through boiler tuning.Control Alt 5 = NOxreduced with SOFA.Control Alt 6 = NOxreduced to 0.15 lb/MMBtu with SCR.Control Alt 7 = Filterable PM reduced to 0.015 lb/MMBtu.7 Geophysical and Meteorological Data 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 782 km by 572 km (Figure 3-1). It includes Corette and all Class I areas within 3 00 km from it. These Class I areas are: Gates of the Mountains WA, North Absaroka WA, Red Rock Lakes WA, Teton WA, UL Bend WA, Washakie WA and Yellowstone NP. The domain also includes th e other PPL Bart-eligible facility in Montana (Colstrip) and the Class I areas within 300 km of it. The domain includes an adequate buffer of more than 50 km in all directions from each of the tw o facilities and each of the Class I areas. A horizontal resolution of 2 km was used to capture the variations of the terrain elevations in the area. This modeling domain is different from the domain proposed in th e Montana Protocol for several reasons. In the 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 eligible 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 the Montana Protocol was 6 km. In the current analysis, the modeling domain was redesigned to in clude only two PPL facilities, Colstrip and Corette, and Class I areas within 300 km from these two facilities only. This resulted in a modeling domain much smaller in size than originally proposed. He nce, better horizontal resolution of 2 km was possible to achieve while still using the reasonable number of gr id cells. In addition, the domain was extended to the south to include the 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 recirculation to be evaluated. Figure 3-1 shows the location of8 Geophysical and Meteorological Data Figure 3-1. Terrain contours (m MSL) at 2 km resolution for the 782 km by 572 km CALMET and CALPUFF computational domains. The Class I areas and the Corette facil ity 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

Corette

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

SD

WY

PPL, Montana Terrain (meters)

-1 100 300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500 2700 2900 3100 3300 3500 3700 3900 4500 300 km circle around facility9 Geophysical and Meteorological Data Corette and a 300-km radius circle around the fac ility. North Absaroka, Yellowstone, Washakie, UL Bend, Teton, Gates of the Mountains and Red Rock La kes Class I areas are with in 300 km from Corette. These seven Class I areas were include d in the BART visibility analysis for the Corette 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 mean s that upper air were taken from MM5 and not from observations. Also, precipitation and relative hum idity 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 five from 2002 and 2003 from the original SURF.DAT file were not found in any of ISHWO or METAR databases. The records 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).10 Geophysical and Meteorological Data Figure 3-2. Dominant land use categories at 2 km resolution on the CALMET and CALPUFF modeling domains. Class I areas and the location of Corette 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

Corette

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

SD

WY

PPL, Montana 300 km circle around facility

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

Tundra

Barren

Wetland

Water

Forest

Range

Agriculture

Urban/Built-Up11 Geophysical and Meteorological Data Table 3-3...................................................Meteorological Data So urces and Parameters Available

Type of Dataset Frequency Source Parameters

Surface observations Hourly NWS Wind speed, wind direction, temperature, ceiling height, cloud cover, relative humidity, surface pressure, precipitation type 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 2005.12 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 only13 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 shows better coverage of the domain is achieved by using the ISHWO data base. 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100 1150 1200 1250 LCCx (km), WGS-84 -200 -150 -100 -50

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

Yellowstone

Washakie UL Bend Theodore Roosevelt - N

Theodore Roosevelt - C

Theodore Roosevelt - S

Teton Red Rock Lakes North Absaroka Gates of the Mountains

KPIH KIDA KSUN

KBYI KSMN KGDV

KBIL KLWT

KBHK

KBTM

KDLN KBZN KLVM KGGW

KJDN KOLF

KSDY

KHLN KMSO KGTF KHVR KFCA KCTB

KMLS

KHEI KDIK KISN KMIB KMOT

KN60 CYEN

KCUT KPHP

KIEN

KD07

KRAP KRCA

KDGW KCPR KLND

KRIW KJAC KGCC KBYG KSHR

P60

KWRL KGEY KCOD TH28

SP26

PE25

SA32 GL27

MO39 GA38 BA37 K2WX

KBPI KRXE MIN2

LAN3 SHE4

BIL5 LEW6

MIL7

CAS8 RAP9 GR11

HE12 KA13

MI14

PO15 GL17 WI18

BO19 BU20

CU21

DI22 HA23

LI24 PE25

SP26 GL27

TH28

YE29

RE31 SA32 DI33

RI34 ES35

BA37 GA38 MO39 Colstrip Corette

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

MM5 grid points
Surface met stations Facility BC AL SA

ID MT ND

SD

WY PPL, Montana

MODELING DOMAIN 300 km circles around facility14 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 CASTN ET 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.15 Geophysical and Meteorological Data Figure 3-4. Locations of ozone monitoring stations used in the CALPUFF modeling. 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-8 4 -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 Corette

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 DOMAIN16 Geophysical and Meteorological Data 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, WV17 Air Quality Modeling Methodology 4.0 AIR QUALITY MODELING METHODOLOGY

4.1 Model Selection
The CALPUFF modeling system (Scire et al., 2000a,b) w as used in the Corette BART analysis at North Absaroka, Yellowstone, Washakie, UL Bend, Teton, Gates of the Mountains and Red Rock Lakes Class I areas. The EPA-approved version of CALPUFF m odeling 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 Corette 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 the18 Air Quality Modeling Methodology surface and RMAX2 aloft). Observations and Step 1 fi eld are weighted by means of parameters R1 at the 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 North Absaroka, Yellowstone, Washakie, UL Bend, Teton, Gates of the Mountains and Red Rock Lakes are shown in Figure 4-1. In the screening modeling, the domain did not include the southernmost part of the Yellowstone NP, Teton WA 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) dispersi on 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.19 Air Quality Modeling Methodology Figure 4-1. Locations of receptors at North Absaroka, Yellowstone, Washakie, Teton, Red Rock Lakes, Gates of the Mountains and UL Bend Class I areas. 410 415 420 425 430 435 440 LCCx (km), WGS-84 280 285 290 295 300 305 310LCCy (km), WGS-84

Gates of the Mountains

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

UL Bend 400 420 440 460 480 500 520 540 560 580 600 620 640 LCCx (km), WGS-84 -60 -40 -20

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

Washakie

Teton Red Rock Lakes

North Absaroka

Map projection: LCC, WGS-84 Feast = 600 km, Fnorth = 0 km LATo = 44.25N, LANo = 109.5W LAT1 = 45 N, LAT2 = 49 N20 Air Quality Modeling Methodology The partial plume path adjustment option was used in CALPUFF for this analysis (MCTADJ=3). The CALMET wind field incorporates the effect of the terrain on the plume trajectories. The plume path coefficient is used to 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 Corette 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.

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 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 Guid ance 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 extinc tion coefficient via the following formula:
HI = 10 ln(b ext /10)
where 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

.21 Air Quality Modeling Methodology 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 co ncentration 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 ente red into the CALPOST input control file for all aerosols defining the background. The 20% best days fo r each of the seven Class I area were used for the natural background extinction calculations. The na tural 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.22 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

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

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

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

Teton WA 2.5 2.3 2.2 2.1 2.1 1.9 1.7 1.6 1.8 2.1 2.4 2.5

Gates of the Mountains WA 2.8 2.5 2. 4 2.3 2.3 2.2 2.0 1. 9 2.1 2.4 2.7 2.7

Red Rock Lakes WA 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 A23 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 Corette was computed based on th e base case emissions level during the modeling years (2001-2003), described in Section 2, and the emissions levels under the potential BART options being evaluated. The emissions levels for the base case and control alte rnatives are presented in Table 2-3. The CALPUFF modeling predicted the effects of emissions from the Corette unit on visibility at the seven 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 impact s. The light extinction impacts are presented for each modeled year in units of change in deciview (dv) for each of the seven 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) a nd 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.24 Air Quality Modeling Methodology Table 5-1....................................................................Summary of Visibi lity Results for Base Case

Class I Area Minimum Distance (km) 2001 2002 2003
98th percentile delta-deciview North Absaroka WA 137 0.372 0.489 0.500 Yellowstone NP 145 0.330 0.331 0.213 Washakie WA 171 0.508 0.548 0.436 UL Bend WA 192 0.645 0.365 0.572 Teton WA 199 0.354 0.263 0.157 Gates of the Mountains WA 276 0.126 0.246 0.098 Red Rock Lakes WA 277 0.069 0.125 0.031

Table 5-2.Summary of Visibility Results for Alternative 1 (SO 2 Reduced 25% by Limestone Injection)

Class I Area Minimum Distance (km) 2001 2002 2003
98th percentile delta-deciview North Absaroka WA 137 0.334 0.449 0.455 Yellowstone NP 145 0.294 0.291 0.195 Washakie WA 171 0.458 0.520 0.394 UL Bend WA 192 0.568 0.322 0.539 Teton WA 199 0.329 0.245 0.135 Gates of the Mountains WA 276 0.112 0.221 0.081 Red Rock Lakes WA 277 0.063 0.107 0.028

Table 5-3.Summary of Visibility Results for Alternative 2 (SO 2 Reduced 70% with a Dry Scrubber)

Class I Area Minimum Distance (km) 2001 2002 2003
98th percentile delta-deciview North Absaroka WA 137 0.286 0.350 0.387 Yellowstone NP 145 0.229 0.219 0.148 Washakie WA 171 0.372 0.373 0.318 UL Bend WA 192 0.427 0.235 0.446 Teton WA 199 0.269 0.176 0.097 Gates of the Mountains WA 276 0.085 0.172 0.054 Red Rock Lakes WA 277 0.053 0.074 0.02025 Air Quality Modeling Methodology Table 5-4. Summary of Visibility Results for Alternative 3 (SO 2 Reduced to 0.15 lb/MMBtu with a Wet Scrubber)

Class I Area Minimum Distance (km) 2001 2002 2003
98th percentile delta-deciview North Absaroka WA 137 0.280 0.338 0.276 Yellowstone NP 145 0.214 0.205 0.086 Washakie WA 171 0.355 0.347 0.188 UL Bend WA 192 0.407 0.219 0.248 Teton WA 199 0.252 0.160 0.054 Gates of the Mountains WA 276 0.079 0.163 0.041 Red Rock Lakes WA 277 0.050 0.067 0.014

Table 5-5.Summary of Visibility Results for Alternative 4 (NO x Reduced through Boiler Tuning)

Class I Area Minimum Distance (km) 2001 2002 2003
98th percentile delta-deciview North Absaroka WA 137 0.353 0.460 0.478 Yellowstone NP 145 0.308 0.313 0.197 Washakie WA 171 0.485 0.505 0.410 UL Bend WA 192 0.616 0.346 0.526 Teton WA 199 0.331 0.244 0.152 Gates of the Mountains WA 276 0.119 0.235 0.095 Red Rock Lakes WA 277 0.068 0.120 0.030

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

Class I Area Minimum Distance (km) 2001 2002 2003
98th percentile delta-deciview North Absaroka WA 137 0.325 0.418 0.444 Yellowstone NP 145 0.276 0.289 0.176 Washakie WA 171 0.443 0.450 0.371 UL Bend WA 192 0.573 0.313 0.463 Teton WA 199 0.297 0.219 0.144 Gates of the Mountains WA 276 0.112 0.214 0.089 Red Rock Lakes WA 277 0.065 0.107 0.02926 Air Quality Modeling Methodology Table 5-7.Summary of Visibility Results for Alternative 6 (NO x Reduced to 0.15 lb/MMBtu with SCR)

Class I Area Minimum Distance (km) 2001 2002 2003
98th percentile delta-deciview North Absaroka WA 137 0.298 0.381 0.390 Yellowstone NP 145 0.245 0.264 0.161 Washakie WA 171 0.401 0.410 0.332 UL Bend WA 192 0.530 0.290 0.443 Teton WA 199 0.263 0.200 0.136 Gates of the Mountains WA 276 0.103 0.188 0.084 Red Rock Lakes WA 277 0.061 0.095 0.029

Table 5-8..........Summary of Visibility Results fo r Alternative 7 (Filtera ble PM Reduced to 0.015 lb/MMBtu)

Class I Area Minimum Distance (km) 2001 2002 2003
98th percentile delta-deciview North Absaroka WA 137 0.353 0.467 0.482 Yellowstone NP 145 0.319 0.322 0.205 Washakie WA 171 0.495 0.516 0.423 UL Bend WA 192 0.633 0.356 0.549 Teton WA 199 0.339 0.251 0.151 Gates of the Mountains WA 276 0.121 0.241 0.093 Red Rock Lakes WA 277 0.067 0.123 0.03127 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.i