APPENDIX B 

Refined Best Available Retrofit Technology (BART) Modeling 

Report: 

OG&E Sooner Generating Station, OG&E Muskogee 

Generating Station, and AEP/PSO Northeastern Generating 

Station 

Prepared by: 

Erik Snyder 

Michael Feldman 
B-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 SO2 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 values used for “Method 6” ........................................... 7

Table 2-2. Monthly Humidity Factors 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 Sulfuric Acid Emission Calculations (EPRI 

method) ............................................................................................................................. 13

Table 4-1. Average of 98th percentile of daily maximum dv for 2001, 2002, and 2003, 

Method 6 ........................................................................................................................... 18

Table 4-2. Average of 98th percentile of daily maximum dv for 2001, 2002, and 2003, 

Method 8 ........................................................................................................................... 19

Table 4-3. Maximum of 98th percentile of daily maximum dv for 2001, 2002, and 2003, 

Method 6 ........................................................................................................................... 20

Table 4-4. Maximum of 98th percentile of daily maximum dv for 2001, 2002, and 2003, 

Method 8 ........................................................................................................................... 21
B-iii 
B-1 

Chapter 1: Introduction 

Units 4 and 5 of the Oklahoma Gas and Electric (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) Northeastern plant have been determined to 

be subject-to-BART. These units are tangentially 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 SO2, respectively. The AEP/PSO units have 

the same controls, with the addition of 1st generation low NOx burners with over fire air. 

After review of modeling and analysis performed by the Oklahoma Department of 

Environmental Quality (ODEQ), EPA agrees 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 scrubbers”) as BART controls for control of SO2 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 these three facilities’ (6 BART units) SO2 BART 

determination, ODEQ concluded that neither dry flue gas desulfurization with spray dryer 

absorbers (“dry scrubbers”) nor wet flue gas desulfurization (“wet scrubbers”) were cost 

effective for these units. ODEQ came to this decision based on their analysis of cost 

effectiveness and modeled visibility improvement at the nearest Class I areas. ODEQ 

determined that SO2 BART for these units was no control and specified an SO2 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 (PRB) of Wyoming, and already have historical 

annual emission rates significantly below this limit. Therefore, it is possible the OG&E 

units would be able to actually increase their emissions approximately 10-20%, and still 

be in compliance with ODEQ’s SO2 BART assessment. The AEP/PSO units have 

historical annual emission rates that have been steadily decreasing to a point where the 

imposition of ODEQ’s proposed BART SO2 emission rate of 0.65 lbs/MMBtu would 

result in very little in SO2 emission reduction. 

EPA reviewed the modeling and cost analysis that was the basis for these 

determinations. EPA disagrees with ODEQ’s SO2 BART determination for these units, 

and is proposing to promulgate a FIP to remedy 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 impacts 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 document 

 
B-2 

Chapter 2: BART Guidelines and Modeling Protocols 

2.1 BACKGROUND AND INTRODUCTION

 The BART analysis includes engineering 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 final factor to consider under EPA's BART Guidelines is 

the degree of visibility improvement from the BART control options1

. The BART 

guidelines recommend use of the CALPUFF air quality dispersion model to estimate the 

visibility improvements at each Class I area, typically within roughly a 300 km (186 

mile) or larger radius of the source, of alternative control technologies, and to compare 

these to each other and to the impact of the baseline, or current, source configuration.2

 

The four Class I Areas within approximately 300 km of the facilities were included in the 

modeling analysis. These 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) from 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 impacts 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 Sources and Class I Areas 

Trinity Consultants conducted the visibility modeling for Sooner, Muskogee, and 

Northeastern Generating Stations and this modeling was reviewed by ODEQ as part of 

their BART determination3. Although EPA generally regards the visibility modeling 

analyses performed by ODEQ to be of high quality, some issues were noted. EPA 

remodeled the visibility impacts 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. ODEQ and EPA modeling 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 the visibility improvement to be used in 

comparisons between various control scenarios is the 98th percentile of impacts expressed 

as 24-hour averages of delta deciviews relative 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 Stations BART determinations. 

 

3

 Throughout this document, any reference to “ODEQ modeling” refers to modeling performed or reviewed 

by ODEQ. 
B-4 

2.2 CALCULATION OF VISIBILITY IMPACT

 Under the RHR, visibility is measured in deciviews. Visibility is traditionally 

described in terms of visual range in kilometers or miles. However, the visual range 

scale does not correspond to how people perceive 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 perceived visual changes over its entire range, analogous to the 

decibel scale for sound: a given change in deciviews will be perceived as the same 

amount of visibility change, whatever the original visibility was. The defining equation 

is: 

deciviews = 10*ln(bext / 10) (1) 

where ln is the natural logarithm, and extinction bext is the fraction of light scattered out 

of a viewing path. Extinction increases with the amount of pollution (bext is in units of 

1/Mm, “inverse megameters”). Lower deciview values represent better visibility, more 

pristine atmospheres, and greater visual range, while increasing deciview values represent 

increasingly poor visibility. An increase of 1 deciview corresponds to about a 10% 

increase in extinction. (Deciviews are related 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, deciviews 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 following visibility-impairing pollutants: SO2, SO4, 

NOx, secondary organic aerosol (SOA), fine particulate matter (PMF), coarse particulate 

matter (PMC), and elemental carbon (EC). CALPUFF incorporates a semi-empirical 

chemical module that simulates the conversion of SO2 to particulate sulfate and NOx to 

particulate nitrate, at a rate dependent on meteorological conditions and background 

ozone concentration. These concentrations are converted to deciviews by the CALPOST 

post-processor in two steps. 

2.2.1 IMPROVE Equation 

 Under the original IMPROVE4

 equation, extinction (bext) is estimated from the 

predicted concentrations of various pollutants: 

bext = 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), ranging from 1 at low humidity to 18 at 98% 

humidity. 

2.2.2 Revised IMPROVE Equation 

EPA used the “revised” IMPROVE equation5

 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: 

bext = 2.2 * fs(RH) * [small sulfate] + 4.8 * fL(RH) * [large sulfate] 

+ 2.4 * fs(RH) * [small nitrate] + 5.1 * fL(RH) * [large nitrate] 

+ 2.8 * [small organic mass] + 6.1 * [large organic mass] 

+ 10 * [elemental carbon] 

+ 1 * [fine soil] 

+ 1.7 * fss(RH) * [sea salt] 

+ 0.6 * [coarse mass] 

+ Rayleigh scattering (site-specific) 

+ 0.33 * [NO2(ppb)] 

Sulfate is assumed to be all “large sulfate” if total sulfate is over 20 μg/m3

, 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 measured by IMPROVE monitors, an increase over 

the old 1.4. Sea salt is estimated as 1.8 * [chloride] (or chlorine if chloride not available) 

The fs, fL, fss are water growth factors for small (“S”) and large (“L”) fractions of sulfate 

and nitrate, and for sea salt (“SS”). Their 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 IMPROVE equation after a scientific 

assessment of its implications for regional haze planning to reduce biases in light 

extinction estimates compared to the old algorithm6

. In particular, when compared to 

nephelometer direct measurements of visibility extinction, the original IMPROVE 

equation over-predicts for low extinction conditions and under-predicts for high 

extinction. These biases have direct relevance for estimates for the worst 20% visibility 

days that are used to assess visibility impact. The new equation shows broader scatter 

overall, but less bias in matching 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 has less bias, is more refined, accounts for 

more pollutants and pollutant sizes, incorporates more recent data, and is based on 

considerations of relevance for the calculations needed for assessing progress under the 

Regional Haze Rule. 

EPA 2007 guidance7 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 extinction is converted to deciviews, using the 

defining equation (equation 1) for deciviews. The delta deciviews (Δdv) represents the 

impact on visibility in deciviews of the source 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 deciviews is the difference between deciviews 

including the impact of the source and natural background, and deciviews of the natural 

background alone. Each modeled day and location 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 percentile, roughly equivalent to the 8th 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. The 98th percentile is 

recommended rather than the maximum value 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 IMPROVE Equation for Estimating Ambient Light Extinction 

Coefficients – Final Report 

(http://vista.cira.colostate.edu/improve/Publications/GrayLit/016_IMPROVEEeqReview/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 impacts of sources be estimated in deciviews 

relative to natural background. ODEQ used background concentrations (Table 2-1) from 

Table 2-1 and monthly area-specific relative humidity factors (Table 2-2) from Table A-3 

of “Guidance for Estimating Natural Visibility Conditions Under the Regional Haze 

Rule”8

. The factors listed in Table 2-2 and used by ODEQ are not the recommended 

values and are given in the guidance document as supplemental information. Table 2-3 

shows the recommended values from Table A-2 of the guidance and used by EPA for 

visibility calculations 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 Creek9 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 Factors 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 Managers’ Air Quality Related Values Work 

Group (FLAG) Phase I Report10 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 Estimating Natural Visibility Conditions Under the Regional 

Haze Rule places Caney Creek in the East. 

10 Federal Land Managers’ Air Quality Related Values 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 subject 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 were 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 identified in these versions15 therefore Trinity Consultants reverted to an 

existing CALMET data set that utilized CALMET v5.53a which is an earlier regulatory 

version and compatible with the regulatory version of CALPUFF (v5.8).16 

 

11 Calpuff Modeling Report BART Determination, Oklahoma 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 Determination, 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) Determination, 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/permitting/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/RulesAndPlanning/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/regionalstatelocalmodelingworkshop/archive/2007/presentations/Wednesday

%20-%20May%2016%202007/CALPUFF_status_update.pdf) 

16 Letter to Lee Warden (ODEQ) from Trinity Consultants, January 23, 2008 RE: Oklahoma Gas and 

Electric – Multiple Sites, Best Available Retrofit Technology (BART) Determination, CALMET Data 

Processing Protocol 
B-9 

Table 2-5 shows selected CALMET settings used by Trinity for modeling visibility 

impacts from the three facilities. R1MAX and R2MAX represent the radius of influence 

of surface and upper air observations, 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 required to redo the analyses. EPA concluded 

that these deviations were acceptable in this case due to time and work resources 

available. EPA elected to utilize the 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 modeling, refined source-specific modeling used a 

constant value of 3 ppb background concentration of ammonia for the domain during the 

modeling period. Hourly ozone observational data provided by ODEQ over the 2001-

2003 timeframe were used to define background ozone concentrations. 

 

17 Memorandum from Tyler Fox (EPA OAQPS) “Clarification on EPA-FLM Recommended Settings for 

CALMET,” August 31, 2009 
B-10 

Table 2-5. Selected CALMET Settings Used 

Option Description EPA default Trinity Consultants18

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 Consultants for use in CALPUFF simulations 
B-11 

Chapter 3: Emission Calculation Methodology 

This chapter discusses the differences in approaches to calculating emissions used by 

Trinity Consultants and EPA for the three facilities being evaluated. 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 SPECIATION

3.1.1 Trinity Consultants Approach 

For modeling scenarios that included only PM10 emissions, PM coarse, PM fine, soil, 

elemental carbon and SOA emissions were input 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 speciation 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 ash content. Trinity 

Consultants calculated PM speciation for Sooner and Muskogee 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 present 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 control scenarios, and again the proper coal 

properties were not used in the calculation. 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 and 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 scenarios19

PM speciation used for 

Muskogee Units for all 

control scenarios19

PM speciation used for 

Northeastern Units for 

all control scenarios20

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 boilers and the emission control equipment 

present in each modeling scenario. Coal properties 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., PM8.0, PM4.25, PM1.88, PM1.25, PM0.813, and PM0.625). After CALPUFF 

modeling, these modeled species are then grouped in POSTUTIL as to represent the 

appropriate visibility pollutants (e.g., PMcourse = PM8.0 + PM4.25 and PMfine = PM1.88 + 

PM1.25 + PM0.813 + PM0.625). Elemental carbon (EC) and secondary organic aerosols 

(SOA) are based on the PM1.88 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 Baseline emission rates and controlled emission 

rates also see Attachment A of this report. 

3.2 SULFURIC ACID EMISSIONS CALCULATIONS

3.2.1 Trinity Consultants Approach 

Sulfuric acid emissions were calculated in two ways by Trinity Consultants. For 

modeling scenarios that included only SO2/SO4 emissions, sulfuric acid emissions from 

the Sooner and Muskogee units were estimated based on an assumed 1% SO2 to SO3 

conversion rate across the boiler. A sulfuric acid control efficiency of 40% was assumed 

for the wet FGD and 90% for the dry FGD. Emissions from the Northeastern units were 

 

19PC Wet Bottom ESP PM Speciation worksheet from NPS 

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

http://www.nature.nps.gov/air/permits/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, 12/28/09 
B-13 

calculated based on an assumed 3ppm sulfur content conversion in the flue gas. In 

modeling scenarios including only PM emissions, all inorganic condensable PM were 

assumed to be sulfates by Trinity Consultants. As detailed above, errors were discovered 

in the PM speciation calculations which include the calculation of the emission rate of the 

inorganic condensable fraction. 

3.2.2 EPA Approach 

Sulfuric acid emissions from power plants are calculated by EPA by estimating the 

amount of H2SO4 produced and the amount of H2SO4 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 SO2, the 

amount of SO2 oxidized to SO3, and the amount of H2SO4 lost to (or mitigated by) the air 

pre-heater and applicable control equipment, such as baghouses, and FGDs. Baseline and 

post-control estimates of H2SO4 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 emission rates and controlled emission rates, see 

Attachment A of this report. 

Table 3-2. Parameters used by EPA in Sulfuric Acid Emission Calculations (EPRI 

method) 

EPRI method parameter Value 

% Sulfur23 0.48% 

% Ash13 7.5% 

Heating value13 8000 Btu/lb 

Sulfer conversion to SO2

24 0.875 

F125 (Fuel Impact Factor, 

subbituminous/PRB all boilers) 0.0019 

F225 (Technology Impact factors): 

Control Scenario BaseA BaseB_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 NOX EMISSIONS

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 Northeastern 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 visibility 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 inclusion of our proposed SO2 reductions, the analysis indicates 

small visibility improvements would be achieved with also requiring SCR, therefore we 

are determining that the visibility improvements 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 below 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 facility (including all visibility impairing 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 Attachment A of this report. 

3.4 SO2 EMISSIONS

As discussed in the Main TSD and other Appendices to the Main TSD, EPA concluded 

that installation of DFGD could achieve a 0.06 lb/mmBtu SO2 emission limit or the 

installation of WFGD could achieve a 0.04 lb/mmBtu SO2 emission limit at all six BART 

units. We modeled a Baseline emission rate for comparison using emission rates that are 

documented in Attachment A to this report. Baseline SO2 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 conjunction 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 estimates used in the modeling analysis to 

determine visibility impairment impacts should reflect steady-state operating conditions 

during periods of high capacity utilization. These baseline emission rates are 

representative of the highest 24-hour block emissions reported during the baseline period 

(the RHR defines the baseline period as 2000-2004) and are consistent with the baseline 

emissions used in each facility’s BART analysis. We note, these units currently burn a 

low sulfur coal from the Powder River Basin (PRB) of Wyoming, and currently have 

emission rates below this baseline rate. However, without a BART determination, there 

are no federally enforceable permits that prohibit these units from returning to a higher 

sulfur coal and emission rates similar to those seen during the baseline modeling period. 

For further information about the Baseline emission 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 modeling for each pollutant was carried out 

separately so that only NOx emissions or only SO2/H2SO4 emissions or only PM10 

emissions were included in a modeling scenario. Due to the nonlinear nature and 

complexity of atmospheric chemistry and chemical transformation among pollutants, 

CALPUFF modeling on a pollutant-specific basis is not recommended.26 Furthermore, 

this approach does not allow for predictions of total visibility impairment for different 

control scenarios at Class I area receptors and the determination of the 98th percentile day 

for visibility impairment. To model the visibility 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 MODELING SCENARIOS

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. SO2 controls evaluated were dry flue gas 

desulfurization (DFGD) and wet flue gas desulfurization (WFGD). We did not explicitly 

model the SO2 emissions if a unit was converted to combusting natural gas instead of 

coal, but the visibility impairment improvements 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 emission rates for NOx, SO2, and PM10 are 

from Appendix E, of each facilities’ Best Available Retrofit Technology 

Evaluation report27,28,29. SO4 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 

27Calpuff Modeling Report BART Determination, Oklahoma 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 Determination, 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 above. PM speciation was calculated 

using the correct NPS PM speciation worksheet and coal properties. 

2. LNB – Emission rates for NOx are at the LNB/OFA controlled value of 

0.15 lb/mmBTU consistent with the controlled rate assumed by the 

facilities. All other emissions are unchanged 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. SO4 emissions were calculated for each unit based on the 

EPRI method discussed above. PM speciation was calculated using the 

correct NPS PM speciation worksheet and 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 NOx are at the LNB/OFA controlled 

value of 0.15 lb/mmBTU. SO2 emissions are controlled to 0.04 

lb/mmBTU. SO4 emissions were calculated for each unit based on the 

EPRI method discussed above. PM speciation was calculated using the 

correct NPS PM speciation worksheet and coal properties. 

The SO2 emission rates suggested by the facilities 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 the application of control 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 provide 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 assessed more or less intuitively, weighing the 

various area impacts and the number of affected Class I areas. 

 29 Best Available Retrofit Technology (BART) Determination, 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/permitting/applications/96-288-TV_M-3/index.htm) 
B-17 

Tables 4-1 and 4-2 present the average value of the 98th percentile of the daily maximum 

impact for the three modeled years (2001-2003) using “Method 6” and “Method 8,” 

respectively. SO2 controls in addition 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 between the results of the WFGD and DFGD in 

the 98th percentile values. At the low sulfur emission levels of these controls, nitrates are 

responsible for the majority of visibility impairment so no benefit is seen in decreasing 

SO2 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 98th 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 the 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 scientifically robust “Method 8” version. 
B-18 

Table 4-1. Average of 98th 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 2.98 
B-19 

Table 4-2. Average of 98th 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 2.47 
B-20 

Table 4-3. Maximum of 98th 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 3.64 
B-21 

Table 4-4. Maximum of 98th 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 3.02 
B-22 

Attachment A
B-23 

SOONER UNIT 1 Control systems NOx SO2 PM10 

5116 mmBTU/hr NOx SO2 lb/mmBTU lb/hr lb/mmBTU lb/hr lb/mmBTU lb/hr 

Baseline A base base 0.601 3074.716 0.860 4399.760 0.038 193.896 

Base B LNB LNB/OFA base 0.150 767.400 0.860 4399.760 0.038 193.896 

LNB DFGD LNB/OFA DFGD 0.150 767.400 0.060 306.960 0.012 61.392 

LNB WFGD LNB/OFA WFGD 0.150 767.400 0.040 204.640 0.038 193.896 

SOONER UNIT 1 Control systems PM Coarse (lb/hr) PM Fine (lb/hr) EC (lb/

NOx SO2 PM 8 PM 4.25 PM 1.88 PM 1.25 PM 0.813 PM 0.625 

Baseline A base base 49.20 60.77 34.73 8.68 5.79 34.73 3.20 

Base B LNB LNB/OFA base 49.20 60.77 34.73 8.68 5.79 34.73 3.20 

LNB DFGD LNB/OFA DFGD 10.01 16.02 14.68 4.00 7.34 9.34 1.10 

LNB WFGD LNB/OFA WFGD 24.58 30.04 43.69 10.92 30.04 54.62 5.10 

SOONER UNIT 2 Control systems NOx SO2 PM10 

5116 mmBTU/hr NOx SO2 lb/mmBTU lb/hr lb/mmBTU lb/hr lb/mmBTU lb/hr 

Baseline A base base 0.584 2987.744 0.860 4399.760 0.039 200.036 

Base B LNB LNB/OFA base 0.150 767.400 0.860 4399.760 0.039 200.036 

LNB DFGD LNB/OFA DFGD 0.150 767.400 0.060 306.960 0.012 61.392 

LNB WFGD LNB/OFA WFGD 0.150 767.400 0.040 204.640 0.039 200.036 

SOONER UNIT 2 Control systems PM Coarse (lb/hr) PM Fine (lb/hr) EC (lb/

NOx SO2 PM 8 PM 4.25 PM 1.88 PM 1.25 PM 0.813 PM 0.625 

Baseline A base base 50.63 62.54 35.74 8.93 5.96 35.74 3.30 

Base B LNB LNB/OFA base 50.63 62.54 35.74 8.93 5.96 35.74 3.30 

LNB DFGD LNB/OFA DFGD 10.01 16.02 14.68 4.00 7.34 9.34 1.10 

LNB WFGD LNB/OFA WFGD 25.36 30.99 45.08 11.27 30.99 56.35 5.30 
B-24 

MUSKOGEE 

UNIT 4 Control systems NOx SO2 PM10 

5480 mmBTU/hr NOx SO2 lb/mmBTU lb/hr lb/mmBTU lb/hr lb/mmBTU lb/hr 

Baseline A base base 0.495 2712.600 0.800 4384.000 0.018 100.832 

Base B LNB LNB/OFA base 0.150 822.000 0.800 4384.000 0.018 100.832 

LNB_DFGD LNB/OFA DFGD 0.150 822.000 0.060 328.800 0.012 65.760 

LNB_WFGD LNB/OFA WFGD 0.150 822.000 0.040 219.200 0.018 100.832 

MUSKOGEE 

UNIT 4 Control systems PM Coarse (lb/hr) PM Fine (lb/hr) EC (lb/h

NOx SO2 PM 8 PM 4.25 PM 1.88 PM 1.25 PM 0.813 PM 0.625 

Baseline A base base 25.58 31.60 18.06 4.51 3.01 18.06 1.70 

Base B LNB LNB/OFA base 25.58 31.60 18.06 4.51 3.01 18.06 1.70 

LNB_DFGD LNB/OFA DFGD 10.72 17.15 15.73 4.29 7.86 10.01 1.20 

LNB_WFGD LNB/OFA WFGD 12.78 15.62 22.72 5.68 15.62 28.40 2.70 

MUSKOGEE 

UNIT 5 Control systems NOx SO2 PM10 

5480 mmBTU/hr NOx SO2 lb/mmBTU lb/hr lb/mmBTU lb/hr lb/mmBTU lb/hr 

Baseline A base base 0.522 2860.560 0.850 4658.000 0.024 133.712 

Base B LNB LNB/OFA base 0.150 822.000 0.850 4658.000 0.024 133.712 

LNB_DFGD LNB/OFA DFGD 0.150 822.000 0.060 328.800 0.012 65.760 

LNB_WFGD LNB/OFA WFGD 0.150 822.000 0.040 219.200 0.024 133.712 

MUSKOGEE 

UNIT 5 Control systems PM Coarse (lb/hr) PM Fine (lb/hr) EC (lb/h

NOx SO2 PM 8 PM 4.25 PM 1.88 PM 1.25 PM 0.813 PM 0.625 

Baseline A base base 33.93 41.91 23.95 5.99 3.99 23.95 2.20 

Base B LNB LNB/OFA base 33.93 41.91 23.95 5.99 3.99 23.95 2.20 

LNB_DFGD LNB/OFA DFGD 10.72 17.15 15.73 4.29 7.86 10.01 1.20 

LNB_WFGD LNB/OFA WFGD 16.95 20.72 30.13 7.53 20.72 37.67 3.50 
B-25 

NORTHEASTERN 

UNIT 3 Control systems NOx SO2 PM10 

5812 mmBTU/hr NOx SO2 lb/mmBTU lb/hr lb/mmBTU lb/hr lb/mmBTU lb/hr 

Baseline A base base 0.536 3115.232 0.900 5230.800 0.038 220.856 

Base B LNB LNB/OFA base 0.150 871.800 0.900 5230.800 0.038 220.856 

LNB_DFGD LNB/OFA DFGD 0.150 871.800 0.060 348.720 0.012 69.744 

LNB_WFGD LNB/OFA WFGD 0.150 871.800 0.040 232.480 0.038 220.856 

NORTHEASTERN 

UNIT 3 Control systems PM Coarse (lb/hr) PM Fine (lb/hr) EC (

NOx SO2 PM 8 PM 4.25 PM 1.88 PM 1.25 PM 0.813 PM 0.625 

Baseline A base base 56.04 69.22 39.56 9.89 6.59 39.56 3

Base B LNB LNB/OFA base 56.04 69.22 39.56 9.89 6.59 39.56 3

LNB_DFGD LNB/OFA DFGD 11.37 18.19 16.68 4.55 8.34 10.61 1

LNB_WFGD LNB/OFA WFGD 28.00 34.22 49.77 12.44 34.22 62.21 5

NORTHEASTERN 

UNIT 4 Control systems NOx SO2 PM10 

5594 mmBTU/hr NOx SO2 lb/mmBTU lb/hr lb/mmBTU lb/hr lb/mmBTU lb/hr 

Baseline A base base 0.491 2746.654 0.900 5034.600 0.059 342.908 

Base B LNB LNB/OFA base 0.150 839.100 0.900 5034.600 0.059 342.908 

LNB_DFGD LNB/OFA DFGD 0.150 839.100 0.060 335.640 0.012 69.744 

LNB_WFGD LNB/OFA WFGD 0.150 839.100 0.040 223.760 0.059 342.908 

NORTHEASTERN 

UNIT 4 Control systems PM Coarse (lb/hr) PM Fine (lb/hr) EC (

NOx SO2 PM 8 PM 4.25 PM 1.88 PM 1.25 PM 0.813 PM 0.625 

Baseline A base base 83.74 103.45 59.11 14.78 9.85 59.11 5

Base B LNB LNB/OFA base 83.74 103.45 59.11 14.78 9.85 59.11 5

LNB_DFGD LNB/OFA DFGD 10.94 17.51 16.05 4.38 8.03 10.22 1

LNB_WFGD LNB/OFA WFGD 41.84 51.13 74.38 18.59 51.13 92.97 8
B-26