## APPENDIX B

Refined Best Available Retrof it Technology (BART) Modeling Report: OG&E Sooner Generating St ation, OG&E Muskogee Generating Station, and AEP/ PSO Northeastern Generating Station

Prepared by:

Erik Snyder Michael FeldmanB-ii 

## Table of Contents

Table of Contents ............................................................................................................. ... ii List of Tables ................................................................................................................ ...... ii Chapter 1: Introduction ................................................................................................... 1 Chapter 2: BART Guidelines and Modeling Protocols .................................................. 2 2.1 Background and Introduction ............................................................................... 2 2.2 Calculation of Visibility Impact ........................................................................... 4 2.2.1 IMPROVE Equation ..................................................................................... 4 2.2.2 Revised IMPROVE Equation ....................................................................... 5 2.2.3 Deciview Impact Calculation ........................................................................ 6 2.3 CALMET/CALPUFF modeling protocol ............................................................ 8 Chapter 3: Emission Calculation Methodology ............................................................ 11 3.1 PM Speciation .................................................................................................... 11 3.1.1 Trinity Consultants Approach ..................................................................... 11 3.1.2 EPA Approach ............................................................................................ 12 3.2 Sulfuric Acid Emissions Calculations ................................................................ 12 3.2.1 Trinity Consultants Approach ..................................................................... 12 3.2.2 EPA Approach ............................................................................................ 13 3.3 NOx Emissions ................................................................................................... 13 3.4 SO 2 Emissions .................................................................................................... 14 Chapter 4: EPA Visibility Modeling ............................................................................ 15 4.1 EPA Modeling Scenarios ................................................................................... 15 4.1.1 EPA Visibility Results ................................................................................ 16 Attachment A .................................................................................................................. .. 22



## List of Tables Table 1-1. Distance (km) from source to Class I Area ...................................................... 2 Table 1-2. Class I Areas ...................................................................................................... 2 Table 2-1. Natural Background va lues used for “Method 6” ........................................... 7 Table 2-2. Monthly Humidity Factor s used by Trinity Consultants .................................. 7 Table 2-3. Monthly Humidity Factors used by EPA ......................................................... 7 Table 2-4. Natural Background Concentrations used by EPA for “Method 8” ................. 8 Table 2-5. Selected CALMET Settings Used ................................................................... 10 Table 3-1. PM Speciation values used by Trinity Consultants ........................................ 12 Table 3-2. Parameters used by EPA in Su lfuric Acid Emission Calculations (EPRI method) ....................................................................................................................... ...... 13 Table 4-1. Average of 98 th percentile of daily maximum dv for 2001, 2002, and 2003, Method 6 ...................................................................................................................... ..... 18 Table 4-2. Average of 98 th percentile of daily maximum dv for 2001, 2002, and 2003, Method 8 ...................................................................................................................... ..... 19 Table 4-3. Maximum of 98 th percentile of daily maximum dv for 2001, 2002, and 2003, Method 6 ...................................................................................................................... ..... 20 Table 4-4. Maximum of 98 th percentile of daily maximum dv for 2001, 2002, and 2003, Method 8 ...................................................................................................................... ..... 21B-iiiB-1 

### Chapter 1: Introduction

Units 4 and 5 of the Oklahoma Gas and Elect ric (OG&E) Muskogee plant, Units 1 and 2 of the OG&E Sooner plant, and Units 3 and 4 of the American Electric Power/Public Service Company of Oklahoma (AEP/PSO) North eastern plant have been determined to be subject-to-BART. These units are tange ntially fired, dry-bottom boilers. The OG&E units currently depend on combustion controls, electrostatic precipitator, and low-sulfur coal to control emissions of NOx, PM, and SO 2 , respectively. The AEP/PSO units have the same controls, with the addition of 1 st generation low NOx burners with over fire air. After review of modeling and analysis pe rformed by the Oklahoma Department of Environmental Quality (ODEQ), EPA ag rees with the NOx and PM BART determinations made by ODEQ for these units.

ODEQ originally proposed as part of their Regional Haze SIP dry flue gas desulfurization (“dry sc rubbers”) as BART controls for control of SO 2 at the OG&E Sooner and Muskogee BART units and also on the AEP/PSO Northeastern plant BART units. In their final RH SIP for thes e three facilities’ (6 BART units) SO 2 BART determination, ODEQ concluded that neither dry flue gas desulfurization with spray dryer absorbers (“dry scrubbers”) nor wet flue gas desulfurization (“wet sc rubbers”) were cost effective for these units. ODEQ came to this decision based on their analysis of cost effectiveness and modeled visibility improve ment at the nearest Class I areas. ODEQ determined that SO 2 BART for these units was no control and specified an SO 2 limit of 0.65 lbs/MMBtu on a 30 day rolling average. The OG&E units currently burn a low sulfur coal from the Powder River Basin (P RB) of Wyoming, and alr eady have historical annual emission rates significantly below this li mit. Therefore, it is possible the OG&E units would be able to actually increase th eir emissions approximately 10-20%, and still be in compliance with ODEQ’s SO 2 BART assessment. The AEP/PSO units have historical annual emission rate s that have been steadily decreasing to a point where the imposition of ODEQ’s proposed BART SO 2 emission rate of 0.65 lbs/MMBtu would result in very little in SO 2 emission reduction.

EPA reviewed the modeling and cost an alysis that was the basis for these determinations. EPA disagrees with ODEQ’s SO 2 BART determination for these units, and is proposing to promulgate a FIP to reme dy this defect in the Oklahoma RH SIP. Although EPA generally regards the visibility modeling analyses performed by ODEQ in support of BART determinations to be of high quality, some deviations from EPA guidance and errors in emission calculations were noted for analyses of these 6 BART units. EPA remodeled the visibility impact s of the Sooner, Muskogee and Northeastern Generating Stations to rectify these issues and to address consistency with modeling guidance EPA has provided to the states. This visibility modeling effort is described in detail in this documentB-2 

### Chapter 2: BART Guidelines and Modeling Protocols 2.1 B ACKGROUND AND I NTRODUCTION

The BART analysis includes engineeri ng and modeling methods and procedures used to determine the appropriate controls for the subject-to-BART units to reduce the source’s contribution to pollutant concentrations that result in visibility impairment in the surrounding Class I areas. The fi nal factor to consider under EPA's BART Guidelines is the degree of visibility improveme nt from the BART control options 1 . The BART guidelines recommend use of the CALPUFF ai r quality dispersion model to estimate the visibility improvements at each Class I ar ea, typically within roughly a 300 km (186 mile) or larger radius of the source, of a lternative control technologies, and to compare these to each other and to the impact of th e baseline, or current , source configuration. 2 The four Class I Areas within approximately 300 km of the facilities were included in the modeling analysis. Thes e facilities and Class I areas are listed in Table 1-1 and 1-2 and shown in area map in Figure 1-1.

Table 1-1. Distance (km) fr om source to Class I Area Caney Creek Hercules - Glades Upper Buffalo Wichita Mountains

Northeastern 263 244 211 323 Sooner 345 363 327 234 Muskogee 180 230 164 324

Table 1-2. Class I Areas

Class I Area State Agency IMPROVE monitor Caney Creek Wilderness Area AR USFS CACR Hercules Glades Wilderness Area MO USFS HEGL Upper Buffalo Wilderness Area AR USFS UPBU Wichita Mountains Wilderness Area OK FWS WIMO

1 59 FR 39104, 39170 (July 6, 2005).

2 CENRAP, ODEQ, and the facilities all modeled imp acts at these four Class I areas. EPA and FLM representative guidance is that using CALPUFF beyond 300 km is appropriate for large emission sources.B-3 Figure 1-1. Location of S ources and Class I Areas

Trinity Consultants conducted the visibi lity modeling for Sooner, Muskogee, and Northeastern Generating Stations and this modeling was reviewed by ODEQ as part of their BART determination 3 . Although EPA generally rega rds the visibility modeling analyses performed by ODEQ to be of high quality, some issues were noted. EPA remodeled the visibility impacts of the S ooner, Muskogee and Northeastern Generating Stations to rectify these issues and to a ddress consistency with modeling guidance EPA has provided to the states. ODEQ and EPA mode ling protocols are discussed later in this chapter, followed by detailed discussion of model inputs and results in the following chapters.

Under the BART guidelines, the measure of th e visibility improvement to be used in comparisons between various control scenarios is the 98 th percentile of impacts expressed as 24-hour averages of delta deciviews relati ve to natural background, as estimated using the CALPUFF air quality modeling system. The meaning of this is described next, followed by particulars of the application of CALPUFF to the Sooner, Muskogee, and Northeastern Generating Sta tions BART determinations.

3 Throughout this document, any reference to “ODEQ modeling” refers to modeling performed or reviewed by ODEQ.B-4 2.2 C ALCULATION OF V ISIBILITY I MPACT

Under the RHR, visibility is measured in deciviews. Visibility is traditionally described in terms of visual range in kilome ters or miles. However, the visual range scale does not correspond to how people percei ve visibility: a given increase in visual range is perceived differently depending on how good the original visibility was (that is, it is not on a linear scale). The deciview scale is designed to address this problem. It is linear with respect to perceive d visual changes over its en tire range, analogous to the decibel scale for sound: a given change in deciviews will be perceived as the same amount of visibility change, wh atever the original visibility was. The defining equation is:

deciviews = 10*ln(b ext / 10) (1)

where ln is the natural logarithm, and extinction b ext is the fraction of light scattered out of a viewing path. Extinction incr eases with the amount of pollution (b ext is in units of 1/Mm, “inverse megameters”). Lower deciview values represent better visibility, more pristine atmospheres, and greater visual rang e, while increasing deciview values represent increasingly poor visibility. An increase of 1 deciview corresponds to about a 10% increase in extinction. (Deciviews are rela ted to the more traditional visual range according to dv = 10*ln(391 / visual range)). An eligible BART source with a predicted impact of 0.5 dv or more of impairment in a Class I area “contributes” to visibility impairment and is subject to BART. 70 FR 39104, 39121 (July 6, 2005).

Under the BART guidelines, deciview s are estimated using the CALPUFF air quality model. CALPUFF predicts 24-hour average pollutant concentrations based on source emissions and how they disperse in the atmosphere. The CALPUFF modeling includes source emissions of the followi ng visibility-impairing pollutants: SO 2 , SO 4 , NO x , secondary organic aerosol (S OA), fine particulate matter (PMF), coarse particulate matter (PMC), and elemental carbon (EC). CALPUFF incorporates a semi-empirical chemical module that simu lates the conversion of SO 2 to particulate sulfate and NO x to particulate nitrate, at a rate dependent on meteorological c onditions and background ozone concentration. These concentrations are converted to deci views by the CALPOST post-processor in two steps.

2.2.1 IMPROVE Equation

Under the original IMPROVE 4 equation, extinction (b ext ) is estimated from the predicted concentrations of various pollutants:

b ext = 3 * f(RH) * [sulfate]

4 Interagency Monitoring of Protected Visual Environments (IMPROVE) is a network of monitors in various Class I Areas, established to assess visibility impairment and its causes. The IMPROVE equation is used to converted monitored concentrations into extinction, a measure of visibility. See: http://vista.cira.colostate.edu/improve/B-5 + 3 * f(RH) * [nitrate] + 4 * [organic mass] + 10 * [elemental carbon] + 1 * [fine soil] + 0.6 * [coarse mass] + 10

The 10 is for Rayleigh scattering, which is due to the interaction of light with molecules of air itself with no pollutants. The f(RH) is a water growth factor for sulfate and nitrate; its value depends on relative humidity (RH), ra nging from 1 at low humidity to 18 at 98% humidity.

2.2.2 Revised IMPROVE Equation

EPA used the “revised” IMPROVE equation 5 to calculate light extinction. Sometimes the revised IMPROVE equation is called the “New” Improve equation. The revised IMPROVE equation is used to convert measured or modeled concentrations into extinction for each pollutant chemical species , and then total them up, accounting for the effect of relative humidity.

Revised IMPROVE equation: b ext = 2.2 * f s (RH) * [small sulfate] + 4.8 * f L (RH) * [large sulfate] + 2.4 * f s (RH) * [small nitrate] + 5.1 * f L (RH) * [large nitrate] + 2.8 * [small organic mass] + 6.1 * [large organic mass] + 10 * [elemental carbon] + 1 * [fine soil] + 1.7 * f ss (RH) * [sea salt] + 0.6 * [coarse mass] + Rayleigh scatteri ng (site-specific) + 0.33 * [NO 2 (ppb)]

Sulfate is assumed to be all “large sulfate” if total sulfate is over 20 μ g/m 3 , otherwise its fraction of the total is assumed to increase uniformly between 0 and 1 when the total is in the range between 0 and 20 (i.e . large sulfate = (total sulfate/20)*total). A similar definition applies for nitrate and for organic mass. The organic mass is assumed to be 1.8 times the organic carbon mass that is meas ured by IMPROVE monitors, an increase over the old 1.4. Sea salt is estimated as 1.8 * [chlor ide] (or chlorine if chloride not available) The f s , f L , f ss are water growth factors for small (“S” ) and large (“L”) fractions of sulfate and nitrate, and for sea salt (“SS”). Thei r values depend on relative humidity, ranging from 1 at low humidity to over 5 at 95% humidity. Rayleigh scattering is due to the interaction of light with molecules of air itself with no pollutants.

5 Pitchford, M. L., W. C. Malm, B. A. Schichtel, N. Kumar, D. Lowenthal and J. L. Hand, Revised algorithm for estimating light extinction from IMPROVE particle speciation data, Journal of the Air & Waste Management Association, 57 , 1326-1336, 2007.B-6 The IMPROVE program revised the IM PROVE equation afte r a scientific assessment of its implications for regiona l haze planning to reduce biases in light extinction estimates compared to the old algorithm 6 . In particular, when compared to nephelometer direct measurements of visi bility extinction, th e original IMPROVE equation over-predicts for low extincti on conditions and under-predicts for high extinction. These biases have direct relevance for estimate s for the worst 20% visibility days that are used to asse ss visibility impact. The new equation shows broader scatter overall, but less bias in matc hing visibility measurements under high and low visibility conditions. The split between small and large particles was the main factor in reducing the biases. The revised IMPROVE equation ha s less bias, is more refined, accounts for more pollutants and pollutant sizes, incor porates more recent data, and is based on considerations of relevance for the calcul ations needed for assessing progress under the Regional Haze Rule.

EPA 2007 guidance 7 states that the use of either the IMPROVE or the revised IMPROVE equation is acceptable provided that the same algorithm is utilized for both the base and future extinction calculations. EPA believes it is appropriate to use the revised IMPROVE equation and that this is the preferred method. EPA provides alternative calculations using the original IMPROVE equation for comparison with these visibility calculation results.

2.2.3 Deciview Impact Calculation

In the second CALPOST step this extincti on is converted to deciviews, using the defining equation (equation 1) for d eciviews. The delta deciviews ( Δ dv) represents the impact on visibility in deciviews of the s ource being evaluated, and is also provided by CALPUFF. It is the change, or “delta”, between deciviews with and without the source. Under the BART guidelines, delta decivi ews is the difference between deciviews including the impact of the source and natural background, a nd deciviews of the natural background alone. Each modeled day and lo cation in the Class I area will have an associated delta deciview. For each day, the model finds the maximum visibility impact of all locations (receptors) in the Class I area. From among these daily values, the BART guidelines recommend use of the 98th pe rcentile, roughly equivalent to the 8 th highest day, visibility impacts expressed as 24-hour averages of delta deciviews relative to natural background, as estimated using the CALPUFF air quality modeling system for comparing the base case and the effects of various controls. Th e 98th percentile is recommended rather than the maximum va lue to avoid undue influence from unusual

6 Revised IMPROVE algorithm for Esimating Light Extinction from Particle Speciation Data , IMPROVE, January 2006 ( http://vista.cira.colostate.edu/improve /Publications/GrayLit/gray_literature.htm ) ; Hand, J.L., Douglas, S.G., 2006, Review of the IMPROV E Equation for Estimating Ambient Light Extinction Coefficients – Final Report ( http://vista.cira.colostate.edu/improve/Publicati ons/GrayLit/016_IMPROVEEe qReview/IMPROVEeqRevi ew.htm )

7 Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze , EPA-454/B-07-002, April 2007, EPA OAQPS; ( http://www.epa.gov/ttn/scram/guidance/guide/final-03-pm-rh-guidance.pdf )B-7 meteorological conditions when CALPUFF is executed according to EPA’s guideline on Air Quality Models (40 CFR Part 51 Appendix W).

The BART guidelines recommend that impact s of sources be estimated in deciviews relative to natural background. ODEQ used b ackground concentrations (Table 2-1) from Table 2-1 and monthly area-specif ic relative humidity factors (Table 2-2) from Table A-3 of “Guidance for Estimating Natural Visi bility Conditions Under the Regional Haze Rule” 8 . The factors listed in Table 2-2 a nd used by ODEQ are not the recommended values and are given in the guidance documen t as supplemental information. Table 2-3 shows the recommended values from Table A-2 of the guidance and used by EPA for visibility calculati ons using “Method 6.”

Table 2-1. Natural Background values used for “Method 6” Class I Area Region SO4 NO3 OC EC Soil Coarse Mass Caney Creek 9 East 0.23 0.1 1.4 0.02 0.5 3.00 Hercules-Glades East 0.23 0.1 1.4 0.02 0.5 3.00

Upper Buffalo East 0.23 0.1 1.4 0.02 0.5 3.00 Wichita Mountains West 0.12 0.1 0.47 0.02 0.5 3.00

Table 2-2. Monthly Humidity Fact ors used by Trinity Consultants Class I Area Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec Caney Creek 3.4 3.1 2.9 3.0 3.6 3.6 3.4 3.4 3.6 3.5 3.4 3.5 Hercules-Glades 3.2 2.9 2.7 2.7 3.3 3.3 3.3 3.3 3.4 3.1 3.1 3.3

Upper Buffalo 3.3 3.0 2.7 2.8 3.4 3.4 3.4 3.4 3.6 3.3 3.2 3.3 Wichita Mountains 2.7 2.6 2.4 2.4 3.0 2.7 2.3 2.5 2.9 2.6 2.7 2.8

Table 2-3. Monthly Humidity Factors used by EPA Class I Area Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec Caney Creek 3.3 3.0 2.7 2.8 3.2 3.2 3.0 3.0 3.2 3.2 3.1 3.3 Hercules-Glades 3.2 2.9 2.6 2.6 3.0 3.0 3.0 3.0 3.2 2.9 3.0 3.2

Upper Buffalo 3.2 2.9 2.6 2.7 3.1 3.1 3.0 3.0 3.2 3.0 3.0 3.2 Wichita Mountains 2.8 2.6 2.4 2.4 2.7 2.5 2.2 2.4 2.7 2.5 2.6 2.8

EPA used average background concentrations (Table 2-4) and relative humidity adjustment factors from the Federal Land Ma nagers’ Air Quality Related Values Work Group (FLAG) Phase I Report 10 for use with the revised IMPROVE equation (“Method 8”).

8 U.S. Environmental Protection Agency, EPA-454/B-03-005, September 2003, on web page http://www.epa.gov/ttn/oarpg/t1/memoranda/rh_envcurhr_gd.pdf

9 Trinity Consultants used “West” values for Caney Creek visibility calculations when modeling Muskogee and Sooner Stations. The EPA Guidance for Estimat ing Natural Visibility Conditions Under the Regional Haze Rule places Caney Creek in the East.

10 Federal Land Managers’ Air Quality Related Valu es Work Group (FLAG) Phase I Report—Revised (2010) Natural Resource Report NPS/NRPC/NRR—2010/232 (http://www.nature.nps.gov/air/Pubs/pdf/flag/FLAG_2010.pdf)B-8 Table 2-4. Natural Background Concentrations used by EPA for “Method 8”

Class I Area BKSALT BKSO4 BKNO3 BKPMC BKOC BKSOIL BKEC

Salt Ammonium sulfate Ammonium nitrate Coarse particulates Organic carbon Soil Elemental carbon Caney Creek .03 0.23 0.10 3.0 1.8 0.5 0.02

HerculesGlades .02 0.23 0.10 3.0 1.8 0.5 0.02

Upper Buffalo .03 0.23 0.10 3.0 1.8 0.5 0.02

Wichita Mountains .03 0.12 0.10 3.0 0.6 0.5 0.02

2.3 CALMET/CALPUFF MODELING PROTOCOL

Trinity Consultants conducted modeling for each of the facilities of interest (Sooner, Muskogee and Northeastern) according to modeling protocols submitted and reviewed by ODEQ. 11,12,13 Rather than evaluate each unit s ubject to BART individually, OG&E and AEP elected to evaluate cost effectiveness and visibility on a facility basis. The selected control technology will be installed on each of the affected units at the facility being modeled. The modeling analysis generally followed the BART protocol developed by CENRAP. 14 Surface and upper air observations we re utilized (NO OBS = 0) for the source-specific modeling, consistent with EPA and FLM recommendations. Originally, modeling was performed with CALMET v6 for use with CALPUFF v6.211. Problems have been identifie d in these versions 15 therefore Trinity Consultants reverted to an existing CALMET data set that utilized CA LMET v5.53a which is an earlier regulatory version and compatible with the re gulatory version of CALPUFF (v5.8). 16

11 Calpuff Modeling Report BART Determination, Ok lahoma Gas & Electric, Sooner Generating Station, Trinity Consultants, March 17, 2008 (available at http://www.deq.state.ok.us/aqdnew/permitting/ applications/2003-274-TVR_M-2/index.htm , as attachment B of Sooner BART application submitted to ODEQ May 30, 2008)

12 Calpuff Modeling Report BART Determinati on, Oklahoma Gas & Electric, Muskogee Generating Station, Trinity Consultants, March 17, 2008 (available at http://www.deq.state.ok.us/aqdnew/permitting/ applications/2005-271-TVR_M-1/index.htm , as attachment B of Muskogee BART application submitted to ODEQ May 30, 2008)

13 Best Available Retrofit Technology (BART) Determ ination, American Electric Power, Northeastern Power Plant, N.N. Dharmarajan (AEP), Eugene Chen, Jeremy Townley (Trinity Consultants), May 30, 2008 (http://www.deq.state.ok.us/aqdnew/permi tting/applications/96-288-TV_M-3/index.htm)

14 CENRAP BART Modeling Guidelines, T. W. Tesche, D. E. McNally, and G. J. Schewe (Alpine Geophysics LLC), December 15, 2005 (http://www.deq.state.ok.us/aqdnew/RulesAndPlan ning/Regional_Haze/SIP/ Appendices/index.htm)

15 CALPUFF: Status and Update , Atkinson, Dennis, Presentation at Regional/State/Local Modelers Workshop, May 16, 2007. (http://www.cleanairinfo.com/regionalstatelocalmode lingworkshop/archive/2007/presentations/Wednesday %20-%20May%2016%202007/CALPUFF_status_update.pdf)

16 Letter to Lee Warden (ODEQ) from Trinity Cons ultants, January 23, 2008 RE: Oklahoma Gas and Electric – Multiple Sites, Best Available Retrofit Technology (BART) Determination, CALMET Data Processing ProtocolB-9 Table 2-5 shows selected CALMET settings used by Trinity for modeling visibility impacts from the three facilities. R1MAX a nd R2MAX represent the radius of influence of surface and upper air observati ons, respectively. R1 (R2) defines the distance from an observation at which the surface (upper air) observation and the initial wind field are equally weighted and is typically set to half the value of R1MAX(R2MAX). EPA and FLMs recommend the use of higher values for R1MAX (100 km) and R2MAX (200 km) based on tracer evaluations and testing. 17 EPA is aware of these deviations and weighed the potential differences that may occur due to these deviations with the additional work and computing resources that would be requi red to redo the analyses. EPA concluded that these deviations were acceptable in th is case due to time and work resources available. EPA elected to utilize th e CALMET v5.53a output generating by Trinity Consultants and described here for input into CALPUFF for visibility modeling to assess the benefit of emission controls on visibility.

For both Trinity Consultants and EPA modeli ng, refined source-specific modeling used a constant value of 3 ppb background concentrat ion of ammonia for the domain during the modeling period. Hourly ozone observationa l data provided by ODEQ over the 2001- 2003 timeframe were used to define background ozone concentrations.

17 Memorandum from Tyler Fox (EPA OAQPS) “C larification on EPA-FLM Recommended Settings for CALMET,” August 31, 2009B-10 Table 2-5. Selected CALMET Settings Used Option Description EPA default Trinity Consultants 18

version CALMET version 5.8, level 070623 5.53a, level 040716 NOOBS No Observation Mode 0 0 ICLOUD gridded cloud fields 0 0 IWFCOD diagnostic winds 1 1 IFRADJ Froude wind adj. 1 1 IKINE kinematic effects 0 0 IOBR O'Brien vertical wind adj. 0 0 ISLOPE slope flows 1 1 IEXTRP extrapolate wind to upper air -4 -4 ICALM extrapolate calm to upper air 0 0

BIAS layer biases sfc vs. UA NZ*0 NZ*0 IPROG gridded initial prognostic 0 14 RMAX1 max surface radius of influence NA 20 RMAX2 max aloft radius of influence NA 50 RMAX3 max over-water radius of influence. NA 100

RMIN min wind radius of influence. 0.1 0.1 RMIN2 min dist sfc winds extrap 4 4 TERRAD terrain radius of in influence NA 10 R1 weight surface Step 1 vs. obs NA 10 R2 weight aloft Step 1 vs. obs NA 25 ITPROG 3D T from obs or prognostic 0 0 TRADKM radius of influ. for T interp. 500 500

IAVET spatial T averaging 1 1 JWAT1 starting land use for T interp. over water 999 55 JWAT2 ending land use for T interp. over water 999 55

18 EPA utilized CALMET output from Trinity Co nsultants for use in CALPUFF simulationsB-11 

### Chapter 3: Emission Calculation Methodology

This chapter discusses the differences in a pproaches to calculating emissions used by Trinity Consultants and EPA for the three fa cilities being evalua ted. Errors were identified in the emission calculations performed by Trinity Consultants for PM10 speciation which impacted the emission estimates for species of particulate matter and sulfuric acid emissions.

3.1 PM S PECIATION

3.1.1 Trinity Consultants Approach

For modeling scenarios that included only PM 10 emissions, PM coarse, PM fine, soil, elemental carbon and SOA emissions were i nput into CALPUFF. The speciated PM emissions were calculated using the National Park Service (NPS) speciation worksheets. Review of these values (Table 3-1) revealed that the incorrect sp eciation worksheet was utilized and the proper coal properties were not input into the calculations. PM speciations in these worksheets are based on AP-42 Tables 1.1-5 and 1-1.6 (for drybottom boilers). Emission factors within these tables vary by the type of emission control equipment downstream and are functions of the coal’s sulfur and as h content. Trinity Consultants calculated PM sp eciation for Sooner and Musk ogee Station units for all control scenarios using emission factors for wet bottom boilers (AP-42 Table 1.1-7) with ESP and used the placeholder values presen t in the worksheets, rather than inputting specific data for the type of coal used. For the Northeastern units, the dry-bottom speciation worksheet was used for all contro l scenarios, and again the proper coal properties were not used in the calcul ation. All units considered here are dry bottom tangentially-fired pulverized coal boilers and the appropriate PM speciation worksheet should be used to utilize the proper emission factor from AP-42 Table 1.1-6 for the control scenario being considered (e.g. “PC Dry Bottom FGD a nd FF” NPS worksheet for control scenario with dry FGD and polishing filter).B-12 Table 3-1. PM Speciation values used by Trinity Consultants PM speciation used for

Sooner Units for all control scenarios 19 PM speciation used for Muskogee Units for all

control scenarios 19 PM speciation used for Northeastern Units for all control scenarios 20

Coarse 10.99% 10.99% 15.46% Fine Soil 11.64% 11.64% 11.91% Fine EC 0.45% 0.45% 0.46% CPM (inorganic

condensable) 61.54% 61.54% 57.73%
CPM OR (organic condensable) 15.38% 15.38% 14.43%
Heating Value (BTU/lb) 10000 10000 10000

% sulfur 1 1 1

% ash 10 10 10

3.1.2 EPA Approach

All particulate modeling was performed with the emission rates derived from the NPS spreadsheets corresponding to dry bottom bo ilers and the emission control equipment present in each modeling scenario. Coal pr operties of 8000 BTU/lb heating value, 0.48% sulfur and 7.5% ash content were used in these calculations. 21 Emission rates were entered in CALPUFF for the specific size ranges presented in the NPS speciation spreadsheets (i.e., PM 8.0 , PM 4.25 , PM 1.88 , PM 1.25 , PM 0.813 , and PM 0.625 ). After CALPUFF modeling, these modeled species are then gr ouped in POSTUTIL as to represent the appropriate visibility pollu tants (e.g., PMcourse = PM 8.0 + PM 4.25 and PMfine = PM 1.88 + PM 1.25 + PM 0.813 + PM 0.625 ). Elemental carbon (EC) and secondary organic aerosols (SOA) are based on the PM 1.88 species and scaled with the emission rates derived from the NPS spreadsheets. (These spreadsheets are available in the Docket for this proposed action) For further information about the Ba seline emission rates and controlled emission rates also see Attachment A of this report.

3.2 S ULFURIC A CID E MISSIONS C ALCULATIONS

3.2.1 Trinity Consultants Approach

Sulfuric acid emissions were calculated in two ways by Trinity Consultants. For modeling scenarios that included only SO 2 /SO 4 emissions, sulfuric acid emissions from the Sooner and Muskogee units were estimat ed based on an assumed 1% SO2 to SO3 conversion rate across the boiler. A sulfuric acid control e fficiency of 40% was assumed for the wet FGD and 90% for the dry FGD. E missions from the Northeastern units were

19 PC Wet Bottom ESP PM Speci ation worksheet from NPS http://www.nature.nps.gov/air/perm its/ect/ectCoalFiredBoiler.cfm

20 PC Dry Bottom ESP PM Speciation worksheet from NPS http://www.nature.nps.gov/air/perm its/ect/ectCoalFiredBoiler.cfm

21 Worst Case Coal Properties from Table 2.1-1 Sooner Units 1 & 2, Muskogee Units 4 & 5 Dry FGD BART Analysis Follow-Up Report, Sargent & Lundy, 12/28/09B-13 calculated based on an assumed 3ppm sulfur c ontent conversion in the flue gas. In modeling scenarios including only PM emissi ons, all inorganic condensable PM were assumed to be sulfates by Trinity Consultants. As detailed above, e rrors were discovered in the PM speciation calculati ons which include the calculation of the emission rate of the inorganic condensable fraction.

3.2.2 EPA Approach

Sulfuric acid emissions from power plan ts are calculated by EPA by estimating the amount of H 2 SO 4 produced and the amount of H 2 SO 4 removed by control equipment using information from the Electric Power Research Institute (EPRI). 22 These calculations rely on assumed values for the amount of fuel sulfur converted to SO 2 , the amount of SO 2 oxidized to SO 3 , and the amount of H 2 SO 4 lost to (or mitigated by) the air pre-heater and applicable cont rol equipment, such as baghou ses, and FGDs. Baseline and post-control estimates of H 2 SO 4 from Sooner, Muskogee and Northeastern are based on the best current information available from EPRI and coal properties (Table 3-2). For further information about the Baseline emissi on rates and controlled emission rates, see Attachment A of this report.

Table 3-2. Parameters used by EPA in Su lfuric Acid Emission Calculations (EPRI method) EPRI method parameter Value % Sulfur 23 0.48%

% Ash 13 7.5% Heating value 13 8000 Btu/lb Sulfer conversion to SO 2 24 0.875 F1 25 (Fuel Impact Factor, subbituminous/PRB all boilers) 0.0019

F2 25 (Technology Impact factors): Control Scenario BaseA Base B_LNB LNB_WFGD LNB_DFGD Air Heater (PRB) 0.36 0.36 0.36 0.36 Cold-side ESP (PRB) 0.72 0.72 0.72 1 Wet spray tower (PRB) 1 1 0.4 1 Dry FGD and baghouse 1 1 1 0.01

3.3 NO X E MISSIONS EPA reviewed the modeling associated with the NOx BART determinations ODEQ made for Units 1 and 2 of the OG&E Sooner plant, Units 4 and 5 of the OG&E Muskogee

22 Estimating Total Sulfuric Acid Emissions from Stationary Power Plants : Version 2010a. EPRI, Palo Alto, CA: 2010. 1020636.

23 Worst Case Coal Properties from Table 2.1-1 Sooner Units 1 & 2, Muskogee Units 4 & 5 Dry FGD BART Analysis Follow-Up Report, Sargent & Lundy, 12/28/09

24 Implicit from EPA AP-42 (EPA, “Compilation of Air Pollutant Emission Factors AP-42, Fifth Edition, Volume I: Stationary Point and Area Sources.” http://www.epa.gov/ttnchie1/ap42pdf/c01s01.pdf.)

25 Estimating Total Sulfuric Acid Emissions from Stationary Power Plants : Version 2010a. EPRI, Palo Alto, CA: 2010. 1020636.B-14 plant, and Units 3 and 4 of AEP/PSO North eastern plant. ODEQ determined that the installation of LNB with OFA to achieve an emission limit of 0.15 lb/mmBTU is NOx BART for these units. EPA reviewed ODEQ’ s basis for these BART determinations, including the costs of compliance, the energy impacts, the non-air quality environmental impacts, the remaining useful life and visi bility modeling. EPA performed additional visibility modeling with CALPUFF that included our proposed SO2 limits in combination with ODEQ proposed limits for NOx and PM. This modeling suggests small visibility improvements can be expected from also requiring the installation of SCR on these units. With the incl usion of our proposed SO2 reduc tions, the analys is indicates small visibility improvements would be achie ved with also requiri ng SCR, therefore we are determining that the visibility improveme nts do not justify when weighed against the additional cost of SCR. As can be seen from the results of LNB with OFA and Dry Scrubbers in Tables 4-1 to 4-4 and in Attachment A of this document, the total visibility impact with these controls in place is be low 0.5 deciview. Evaluation of the BART modeling output files indicates a number of the highest days are now nitrate limited, but the overall impacts from the facil ity (including all visibility imp airing pollutants) is fairly small (less than 0.5 deciview on a Class I area). Therefore the nitrate portion of visibility impairment, which is just part of the total visibility impairment, is fairly small for each facility. For further information about the Baseline emission rates and controlled emission rates, see Attachme nt A of this report.

3.4 SO 2 E MISSIONS

As discussed in the Main TSD and other A ppendices to the Main TSD, EPA concluded that installation of DFGD c ould achieve a 0.06 lb/mmBtu SO 2 emission limit or the installation of WFGD could achieve a 0.04 lb/mmBtu SO 2 emission limit at all six BART units. We modeled a Baseline emission rate fo r comparison using emission rates that are documented in Attachment A to this report. Baseline SO 2 emission rates of 0.86 lb/mmBtu for the Sooner units, 0.80 lb/mmBtu and 0.85 lb/mmBtu for Muskogee units 4 & 5, and 0.90 lb/mmBtu for Northeastern units were used in conjunc tion with firing rate information to determine the lb/hr emission rate modeled. EPA guidelines in 40 CFR 51 Appendix Y Part III state that emission estim ates used in the m odeling analysis to determine visibility impairment impacts s hould reflect steady-stat e operating conditions during periods of high capacity utilizati on. These baseline emission rates are representative of the highest 24-hour block em issions reported duri ng the baseline period (the RHR defines the baseline period as 2000-200 4) and are consistent with the baseline emissions used in each facility’s BART analys is. We note, these units currently burn a low sulfur coal from the Powder River Ba sin (PRB) of Wyoming, and currently have emission rates below this baseline rate. Ho wever, without a BART determination, there are no federally enforceable permits that prohi bit these units from re turning to a higher sulfur coal and emission rates similar to thos e seen during the baseline modeling period. For further information about the Baseline em ission rates and controlled emission rates, see Attachment A of this report.B-15 

### Chapter 4: EPA Visibility Modeling

EPA’s CALPUFF modeling approach differed from that used by ODEQ. In ODEQ’s modeling approach, CALPUFF visibility m odeling for each pollutant was carried out separately so that only NO x emissions or only SO 2 /H 2 SO 4 emissions or only PM10 emissions were included in a modeling scen ario. Due to the nonlinear nature and complexity of atmospheric chemistry and chemical transformation among pollutants, CALPUFF modeling on a pollutant-specific basi s is not recommended. 26 Furthermore, this approach does not allow for predictions of total visibility impairment for different control scenarios at Class I area rece ptors and the determination of the 98 th percentile day for visibility impairment. To model the vi sibility benefit of emission controls, all relevant pollutants should be modeled together to determine the total visibility impact at each Class I area receptor.

4.1 EPA M ODELING S CENARIOS

EPA performed visibility modeling to evaluate the visibility benefit of additional emission controls for each facility. For NOx control, operation of low NOx burners with Over-Fire Air (LNB/OFA) was examined. SO 2 controls evaluated were dry flue gas desulfurization (DFGD) and wet flue gas desulfurization (WF GD). We did not explicitly model the SO 2 emissions if a unit was converted to combusting natural gas instead of coal, but the visibility impairment improve ments would be more than the improvements from WFGD. EPA’s proposal indicates that a conversion from combusting coal to combusting natural gas would be acceptable as an alternative to installing either DFGD or WFGD.

These control scenarios are outlined below. Emission inputs for each scenario for each facility are included in Attachment A of this report.

Control Scenarios:

1. Baseline – Heat Input and emissi on rates for NOx, SO2, and PM10 are from Appendix E, of each facilities’ Best Available Retrofit Technology Evaluation report 27,28,29 . SO 4 emissions were calculated for each unit

26 Memo from Joseph Paisie (Geographic Strategies Group, OAQPS) to Kay Prince (Branch Chief EPA Region 4) on Regional Haze Regulations and Guidelines for Best Available Retrofit Technology (BART) Determinations, July 19, 2006

27 Calpuff Modeling Report BART Determination, Ok lahoma Gas & Electric, Sooner Generating Station, Trinity Consultants, March 17, 2008 (available as attachment B of Sooner BART application submitted to ODEQ May 30, 2008 at http://www.deq.state.ok.us /aqdnew/permitting/applications/2003-274-TVR_M2/index.htm)

28 Calpuff Modeling Report BART Determinati on, Oklahoma Gas & Electric, Muskogee Generating Station, Trinity Consultants, March 17, 2008 (available as attachment B of Muskogee BART application submitted to ODEQ May 30, 2008 at http://www.deq .state.ok.us/aqdnew/permitting/applications/2005- 271-TVR_M-1/index.htm)B-16 based on the EPRI method discussed a bove. PM speciation was calculated using the correct NPS PM speciatio n worksheet and coal properties.

2. LNB – Emission rates for NOx are at the LNB/OFA controlled value of 0.15 lb/mmBTU consistent with th e controlled rate assumed by the facilities. All other emissions are un changed from the Baseline scenario above.

3. LNB DFGD - Emission rates for NOx are at the LNB/OFA controlled value of 0.15 lb/mmBTU. SO2 emissions are controlled to 0.06 lb/mmBTU. SO 4 emissions were calculated for each unit based on the EPRI method discussed above. PM speciation was calculated using the correct NPS PM speciation worksheet a nd coal properties. Installation of a polishing filter is included in this scenario as it is required for operation of the DFGD.

4. LNB WFGD – Emission rates for NO x are at the LNB/OFA controlled value of 0.15 lb/mmBTU. SO2 emissions are controlled to 0.04 lb/mmBTU. SO 4 emissions were calculated for each unit based on the EPRI method discussed above. PM speciation was calculated using the correct NPS PM speciation work sheet and coal properties.

The SO 2 emission rates suggested by the facili ties were 0.10 for the DFGD and 0.08 for the WFGD. EPA’s review of factors and current state of what is being achieved at similar facilities informed EPA of the proposed levels that can be achieved with DFGD or WFGD. For further details see the main TSD and other appendices of the main TSD.

4.1.1 EPA Visibility Results

We present the visibility improvement from th e application of contro l technologies in two ways: (1) deciview improvement at each Class I area, and (2) the sum of the improvements at all areas.

Deciview improvement at each Class I area is the metric that is most commonly evaluated for BART impacts, but does not give the overall picture of improvement at all impacted Class I areas. The motivation for the second metric, which involves summing over Class I areas, is to provi de a single number for comparing control scenarios to each other. There are multiple Class I areas, with different visibility impacts for each, but there is no established metric for expressing visibility impact considering all areas together in a single number. The overall impact can be asse ssed more or less in tuitively, weighing the various area impacts and the number of affected Class I areas.

29 Best Available Retrofit Technology (BART) Determ ination, American Electric Power, Northeastern Power Plant, N.N. Dharmarajan (AEP), Eugene Chen, Jeremy Townley (Trinity Consultants), May 30, 2008 (http://www.deq.state.ok.us/aqdnew/permi tting/applications/96-288-TV_M-3/index.htm)B-17 Tables 4-1 and 4-2 present the average value of the 98 th percentile of the daily maximum impact for the three modeled years ( 2001-2003) using “Method 6” and “Method 8,” respectively. SO2 controls in additi on to LNB/OFA provide for significant improvements in visibility, lowering the impact each facility has on any one Class I area to below 0.5 dv. There is little difference be tween the result s of the WFGD and DFGD in the 98 th percentile values. At the low sulfur emission levels of these controls, nitrates are responsible for the majority of visibility impa irment so no benefit is seen in decreasing SO 2 emissions from the DFGD rate of 0.06 to the WFGD rate of 0.04 lb/mmBTU. Tables 4-3 and 4-4 present the maximum value of the 98 th percentile of the daily maximum impact for the three modeled years (2001-2003) using “Method 6” and “Method 8,” respectively. As discussed above we are including th e results from the original IMPROVE equation with “Method 6” results, and the revised IMPROVE equation with the “Method 8” results. EPA’ s analysis and conclusions are based on the results of the more scientifica lly robust “Method 8” version.B-18 Table 4-1. Average of 98 th percentile of daily maximum dv for 2001, 2002, and 2003, Method 6 Visibility Impact ( Δ dv) Visibility Improvement ( Δ dv)

Baseline LNB LNB & DFGD LNB & WFGD LNB over Baseline DFGD over LNB WFGD over LNB

Sooner Units 1&2

Caney Creek 0.73 0.48 0.13 0.12 0.25 0.35 0.36

HerculesGlades 0.64 0.39 0.11 0.10 0.26 0.27 0.28

Upper Buffalo 0.69 0.46 0.11 0.10 0.23 0.35 0.36

Wichita Mountains 2.06 1.45 0.40 0.38 0.60 1.06 1.08

Sum 4.12 2.78 0.75 0.70 1.34 2.03 2.08

Muskogee Units 4&5

Caney Creek 1.52 1.10 0.35 0.39 0.42 0.75 0.71

HerculesGlades 1.15 0.96 0.19 0.17 0.19 0.77 0.79

Upper Buffalo 1.60 1.24 0.32 0.28 0.36 0.92 0.96

Wichita Mountains 1.45 1.18 0.25 0.25 0.26 0.93 0.94

Sum 5.72 4.48 1.11 1.09 1.24 3.37 3.39

Northeastern Units 3&4

Caney Creek 1.56 1.00 0.27 0.28 0.56 0.73 0.72

HerculesGlades 0.98 0.84 0.17 0.17 0.15 0.67 0.66

Upper Buffalo 1.20 0.86 0.20 0.20 0.34 0.66 0.66

Wichita Mountains 1.38 1.18 0.23 0.24 0.20 0.95 0.94

Sum 5.12 3.88 0.87 0.90 1.24 3.01 2.98B-19 Table 4-2. Average of 98 th percentile of daily maximum dv for 2001, 2002, and 2003, Method 8 Visibility Impact ( Δ dv) Visibility Improvement ( Δ dv)

Baseline LNB LNB & DFGD LNB & WFGD LNB over Baseline DFGD over LNB WFGD over LNB

Sooner Units 1&2

Caney Creek 0.64 0.43 0.12 0.11 0.21 0.31 0.31

HerculesGlades 0.57 0.33 0.10 0.09 0.24 0.23 0.24

Upper Buffalo 0.62 0.39 0.10 0.09 0.22 0.29 0.30

Wichita Mountains 1.78 1.21 0.35 0.33 0.57 0.86 0.87

Sum 3.60 2.36 0.67 0.63 1.25 1.69 1.72

Muskogee Units 4&5

Caney Creek 1.36 0.94 0.33 0.36 0.42 0.61 0.58

HerculesGlades 0.99 0.82 0.17 0.16 0.18 0.65 0.66

Upper Buffalo 1.41 1.09 0.29 0.25 0.32 0.80 0.83

Wichita Mountains 1.23 0.98 0.21 0.22 0.26 0.76 0.76

Sum 4.99 3.82 1.00 0.99 1.17 2.82 2.83

Northeastern Units 3&4

Caney Creek 1.43 0.89 0.25 0.26 0.54 0.64 0.63

HerculesGlades 0.85 0.71 0.15 0.16 0.14 0.56 0.55

Upper Buffalo 1.07 0.72 0.19 0.18 0.35 0.54 0.54

Wichita Mountains 1.17 0.98 0.20 0.22 0.19 0.78 0.76

Sum 4.51 3.29 0.78 0.82 1.22 2.52 2.47B-20 Table 4-3. Maximum of 98 th percentile of daily maximum dv for 2001, 2002, and 2003, Method 6 Visibility Impact ( Δ dv) Visibility Improvement ( Δ dv)

Baseline LNB LNB & DFGD LNB & WFGD LNB over Baseline DFGD over LNB WFGD over LNB

Sooner Units 1&2

Caney Creek 0.85 0.58 0.14 0.14 0.27 0.44 0.44

HerculesGlades 0.79 0.50 0.14 0.13 0.29 0.36 0.37

Upper Buffalo 0.87 0.57 0.14 0.13 0.30 0.43 0.44

Wichita Mountains 2.41 1.75 0.46 0.39 0.66 1.29 1.36

Sum 4.92 3.40 0.89 0.80 1.51 2.52 2.60

Muskogee Units 4&5

Caney Creek 1.72 1.39 0.47 0.56 0.33 0.91 0.83

HerculesGlades 1.25 1.09 0.20 0.20 0.16 0.89 0.88

Upper Buffalo 1.68 1.36 0.39 0.36 0.32 0.97 1.00

Wichita Mountains 1.52 1.25 0.34 0.38 0.27 0.91 0.87

Sum 6.17 5.09 1.40 1.51 1.08 3.69 3.58

Northeastern Units 3&4

Caney Creek 1.86 1.11 0.33 0.33 0.75 0.78 0.77

HerculesGlades 1.10 1.05 0.20 0.21 0.05 0.85 0.84

Upper Buffalo 1.67 1.01 0.30 0.30 0.66 0.71 0.72

Wichita Mountains 1.95 1.67 0.35 0.36 0.27 1.32 1.31

Sum 6.57 4.84 1.18 1.20 1.73 3.66 3.64B-21 Table 4-4. Maximum of 98 th percentile of daily maximum dv for 2001, 2002, and 2003, Method 8 Visibility Impact ( Δ dv) Visibility Improvement ( Δ dv)

Baseline LNB LNB & DFGD LNB & WFGD LNB over Baseline DFGD over LNB WFGD over LNB

Sooner Units 1&2

Caney Creek 0.73 0.50 0.13 0.13 0.23 0.37 0.38

HerculesGlades 0.71 0.43 0.13 0.12 0.28 0.30 0.31

Upper Buffalo 0.77 0.49 0.13 0.12 0.28 0.35 0.37

Wichita Mountains 2.08 1.46 0.41 0.35 0.62 1.05 1.11

Sum 4.28 2.88 0.80 0.71 1.41 2.08 2.16

Muskogee Units 4&5

Caney Creek 1.48 1.19 0.45 0.51 0.29 0.74 0.69

HerculesGlades 1.07 0.92 0.19 0.19 0.14 0.74 0.73

Upper Buffalo 1.52 1.20 0.37 0.33 0.31 0.84 0.87

Wichita Mountains 1.31 1.03 0.29 0.34 0.27 0.75 0.70

Sum 5.37 4.35 1.29 1.37 1.02 3.06 2.98

Northeastern Units 3&4

Caney Creek 1.70 0.99 0.29 0.30 0.71 0.70 0.69

HerculesGlades 0.92 0.88 0.18 0.20 0.04 0.70 0.68

Upper Buffalo 1.52 0.85 0.28 0.28 0.67 0.57 0.57

Wichita Mountains 1.66 1.39 0.30 0.31 0.27 1.09 1.08

Sum 5.80 4.11 1.05 1.09 1.69 3.06 3.02B-22 

## Attachment AB-23SOONER UNIT 1 Control systems NOx SO2 PM10 H2SO45116 mmBTU/hrNOx SO2 lb/mmBTU lb/hr lb/mmBTUlb/hr lb/mmBTU lb/hr lb/hrBaseline A base base 0.601 3074.7160.860 4399.760 0.038 193.896 4.05Base B LNB LNB/OFA base 0.150 767.400 0.860 4399.760 0.038 193.896 4.05LNB DFGD LNB/OFA DFGD 0.150 767.400 0.060 306.960 0.012 61.392 0.06LNB WFGD LNB/OFA WFGD 0.150 767.400 0.040 204.640 0.038 193.896 1.62SOONER UNIT 1 Control systems PMCoarse (lb/hr) PM Fine (lb/hr)EC (lb/hr) SOA (lb/hr)NOx SO2 PM 8 PM 4.25 PM 1.88PM 1.25 PM 0.813 PM 0.625Baseline A base base 49.20 60.77 34.738.68 5.79 34.73 3.20 27.60Base B LNB LNB/OFA base 49.20 60.7734.73 8.68 5.7934.73 3.20 27.60LNB DFGD LNB/OFA DFGD 10.01 16.0214.68 4.00 7.349.34 1.10 26.20LNB WFGD LNB/OFA WFGD 24.58 30.0443.69 10.92 30.0454.62 5.10 3.50SOONER UNIT 2 Control systems NOx SO2 PM10 H2SO45116 mmBTU/hrNOx SO2 lb/mmBTU lb/hr lb/mmBTUlb/hr lb/mmBTU lb/hr lb/hrBaseline A base base 0.584 2987.7440.860 4399.760 0.039 200.036 4.05Base B LNB LNB/OFA base 0.150 767.400 0.860 4399.760 0.039 200.036 4.05LNB DFGD LNB/OFA DFGD 0.150 767.400 0.060 306.960 0.012 61.392 0.06LNB WFGD LNB/OFA WFGD 0.150 767.400 0.040 204.640 0.039 200.036 1.62SOONER UNIT 2 Control systems PMCoarse (lb/hr) PM Fine (lb/hr)EC (lb/hr) SOA (lb/hr)NOx SO2 PM 8 PM 4.25 PM 1.88PM 1.25 PM 0.813 PM 0.625Baseline A base base 50.63 62.54 35.748.93 5.96 35.74 3.30 28.40Base B LNB LNB/OFA base 50.63 62.5435.74 8.93 5.9635.74 3.30 28.40LNB DFGD LNB/OFA DFGD 10.01 16.0214.68 4.00 7.349.34 1.10 26.20LNB WFGD LNB/OFA WFGD 25.36 30.9945.08 11.27 30.9956.35 5.30 3.70B-24MUSKOGEEUNIT 4Control systems NOx SO2 PM10 H2SO45480 mmBTU/hrNOx SO2 lb/mmBTU lb/hr lb/mmBTUlb/hr lb/mmBTU lb/hr lb/hrBaseline A base base0.495 2712.600 0.800 4384.000 0.018 100.832 4.34Base B LNB LNB/OFA base0.150 822.000 0.800 4384.000 0.018 100.832 4.34LNB_DFGD LNB/OFA DFGD0.150 822.000 0.060 328.800 0.012 65.760 0.06LNB_WFGD LNB/OFA WFGD0.150 822.000 0.040 219.200 0.018 100.832 1.74MUSKOGEEUNIT 4Control systems PM Coarse (lb/hr) PM Fine (lb/hr)EC (lb/hr) SOA (lb/hr)NOx SO2 PM 8 PM 4.25 PM 1.88PM 1.25 PM 0.813 PM 0.625Baseline A base base25.58 31.60 18.06 4.51 3.01 18.06 1.70 14.30Base B LNB LNB/OFA base25.58 31.60 18.06 4.51 3.01 18.06 1.70 14.30LNB_DFGD LNB/OFA DFGD10.72 17.15 15.73 4.29 7.86 10.01 1.20 28.10LNB_WFGD LNB/OFA WFGD12.78 15.62 22.72 5.68 15.62 28.40 2.70 1.80MUSKOGEEUNIT 5Control systems NOx SO2 PM10 H2SO45480 mmBTU/hrNOx SO2 lb/mmBTU lb/hr lb/mmBTUlb/hr lb/mmBTU lb/hr lb/hrBaseline A base base0.522 2860.560 0.850 4658.000 0.024 133.712 4.34Base B LNB LNB/OFA base0.150 822.000 0.850 4658.000 0.024 133.712 4.34LNB_DFGD LNB/OFA DFGD0.150 822.000 0.060 328.800 0.012 65.760 0.06LNB_WFGD LNB/OFA WFGD0.150 822.000 0.040 219.200 0.024 133.712 1.74MUSKOGEEUNIT 5Control systems PM Coarse (lb/hr) PM Fine (lb/hr)EC (lb/hr) SOA (lb/hr)NOx SO2 PM 8 PM 4.25 PM 1.88PM 1.25 PM 0.813 PM 0.625Baseline A base base33.93 41.91 23.95 5.99 3.99 23.95 2.20 19.00Base B LNB LNB/OFA base33.93 41.91 23.95 5.99 3.99 23.95 2.20 19.00LNB_DFGD LNB/OFA DFGD10.72 17.15 15.73 4.29 7.86 10.01 1.20 28.10LNB_WFGD LNB/OFA WFGD16.95 20.72 30.13 7.53 20.72 37.67 3.50 2.40B-25NORTHEASTERNUNIT 3Control systems NOx SO2 PM10 H2SO45812 mmBTU/hrNOx SO2 lb/mmBTU lb/hr lb/mmBTUlb/hr lb/mmBTU lb/hr lb/hrBaseline A base base0.536 3115.232 0.900 5230.800 0.038 220.856 4.6Base B LNB LNB/OFA base0.150 871.800 0.900 5230.800 0.038 220.856 4.6LNB_DFGD LNB/OFA DFGD0.150 871.800 0.060 348.720 0.012 69.744 0.06LNB_WFGD LNB/OFA WFGD0.150 871.800 0.040 232.480 0.038 220.856 1.84NORTHEASTERNUNIT 3Control systems PM Coarse (lb/hr) PM Fine (lb/hr)EC (lb/hr) SOA (lb/hr)NOx SO2 PM 8 PM 4.25 PM 1.88PM 1.25 PM 0.813 PM 0.625Baseline A base base56.04 69.22 39.56 9.89 6.59 39.56 3.60 31.40Base B LNB LNB/OFA base56.04 69.22 39.56 9.89 6.59 39.56 3.60 31.40LNB_DFGD LNB/OFA DFGD11.37 18.19 16.68 4.55 8.34 10.61 1.30 29.80LNB_WFGD LNB/OFA WFGD28.00 34.22 49.77 12.44 34.22 62.21 5.80 4.00NORTHEASTERNUNIT 4Control systems NOx SO2 PM10 H2SO45594 mmBTU/hrNOx SO2 lb/mmBTU lb/hr lb/mmBTUlb/hr lb/mmBTU lb/hr lb/hrBaseline A base base0.491 2746.654 0.900 5034.600 0.059 342.908 4.43Base B LNB LNB/OFA base0.150 839.100 0.900 5034.600 0.059 342.908 4.43LNB_DFGD LNB/OFA DFGD0.150 839.100 0.060 335.640 0.012 69.744 0.06LNB_WFGD LNB/OFA WFGD0.150 839.100 0.040 223.760 0.059 342.908 1.77NORTHEASTERNUNIT 4Control systems PM Coarse (lb/hr) PM Fine (lb/hr)EC (lb/hr) SOA (lb/hr)NOx SO2 PM 8 PM 4.25 PM 1.88PM 1.25 PM 0.813 PM 0.625Baseline A base base83.74 103.45 59.11 14.78 9.85 59.11 5.40 46.90Base B LNB LNB/OFA base83.74 103.45 59.11 14.78 9.85 59.11 5.40 46.90LNB_DFGD LNB/OFA DFGD10.94 17.51 16.05 4.38 8.03 10.22 1.20 28.60LNB_WFGD LNB/OFA WFGD41.84 51.13 74.38 18.59 51.13 92.97 8.70 6.00B-26