BART FIVE FACTOR ANALYSIS

FLINT CREEK POWER PLANT 

GENTRY, ARKANSAS (AFIN 04-00107) 

Prepared By: 

TRINITY CONSULTANTS, INC.

120 East Sheridan, Suite 205 

Oklahoma City, Oklahoma 73104 

(405) 228-3292 

TRINITY CONSULTANTS, INC.

977 Ridge Drive, Suite 380 

Lenexa, Kansas 66219 

(913) 894-4500 

In conjunction with: 

AMERICAN ELECTRIC POWER SERVICE CORPORATION

PO Box 660164 

Dallas, Texas 72566 

(214) 777-1113 

for the 

SOUTHWESTERN ELECTRIC POWER COMPANY

FLINT CREEK POWER PLANT

21797 SWEPCO Plant Road 

Gentry, Arkansas 72734 

Trinity Project Nos. 113701.0022 & 123701.0038 

January 2013 

Version 2 
 

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BART Analysis – Flint Creek 

TABLE OF CONTENTS

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

2. INTRODUCTION AND BACKGROUND .................................................................... 2-1

3. MODELING METHODOLOGIES AND PROCEDURES ............................................. 3-1

3.1 CALMET AND CALPUFF ................................................................................... 3-1

3.2 CALPOST ............................................................................................................ 3-1

4. EXISTING EMISSIONS AND VISIBILITY IMPAIRMENT ......................................... 4-1

4.1 NOX, SO2, AND PM10 BASELINE EMISSION RATES ............................................... 4-1

4.2 BASELINE VISIBILITY IMPAIRMENT ....................................................................... 4-1

5. SO2 BART EVALUATION .................................................................................... 5-1

5.1 IDENTIFICATION OF AVAILABLE RETROFIT SO2 CONTROL TECHNOLOGIES .......... 5-1

5.2 ELIMINATE TECHNICALLY INFEASIBLE SO2 CONTROL TECHNOLOGIES ................ 5-1

5.2.1 DRY SORBENT INJECTION ................................................................................... 5-1

5.2.2 DRY SCRUBBER ................................................................................................... 5-2

5.2.3 WET SCRUBBER .................................................................................................. 5-2

5.2.4 CIRCULATING DRY SCRUBBER (CDS) ................................................................ 5-3

5.3 RANK OF TECHNICALLY FEASIBLE SO2 CONTROL OPTIONS BY EFFECTIVENESS .. 5-3

5.4 EVALUATION OF IMPACTS FOR FEASIBLE SO2 CONTROLS..................................... 5-3

5.4.1 COST OF COMPLIANCE ........................................................................................ 5-4

5.4.2 ENERGY IMPACTS AND NON-AIR QUALITY IMPACTS ......................................... 5-7

5.4.3 REMAINING USEFUL LIFE ................................................................................... 5-7

5.5 EVALUATION OF VISIBILITY IMPACT OF FEASIBLE SO2 CONTROLS ...................... 5-7

5.6 PROPOSED BART FOR SO2 ................................................................................... 5-10

5.6.1 COMPARATIVE SO2 BART DETERMINATIONS ................................................. 5-10

6. NOX BART EVALUATION ................................................................................... 6-1

6.1 CROSS-STATE AIR POLLUTION RULE, ................................................................... 6-1

CLEAN AIR INTERSTATE RULE, AND BART ...................................................................... 6-1

6.2 IDENTIFICATION OF AVAILABLE RETROFIT NOX CONTROL TECHNOLOGIES ......... 6-2

6.3 ELIMINATE TECHNICALLY INFEASIBLE NOX CONTROL TECHNOLOGIES ............... 6-2

6.3.1 COMBUSTION CONTROLS .................................................................................... 6-3

6.3.1.1 Flue Gas Recirculation (FGR) ............................................................. 6-3

6.3.1.2 Overfire Air (OFA) .............................................................................. 6-3

6.3.1.3 Low NOX Burners ................................................................................ 6-3

6.3.2 POST COM BUSTION CONTROLS .......................................................................... 6-4

6.3.2.1 Selective Catalytic Reduction .............................................................. 6-4

6.3.2.2 Selective Non-Catalytic Reduction ...................................................... 6-4

6.4 RANK OF TECHNICALLY FEASIBLE NOX CONTROL OPTIONS BY EFFECTIVENESS .. 6-5
 

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BART Analysis – Flint Creek 

6.5 EVALUATION OF IMPACTS FOR FEASIBLE NOX CONTROLS ................................... 6-5

6.5.1 COST OF COMPLIANCE ........................................................................................ 6-6

6.5.2 ENERGY IMPACTS & NON-AIR IMPACTS .......................................................... 6-10

6.5.3 REMAINING USEFUL LIFE ................................................................................. 6-10

6.6 EVALUATION OF VISIBILITY IMPACT OF FEASIBLE NOX CONTROLS ................... 6-10

6.7 PROPOSED BART FOR NOX .................................................................................... 6-1

7. PM10 BART EVALUATION .................................................................................. 7-1

APPENDIX A .................................................................................................................................

APPENDIX B .................................................................................................................................

APPENDIX C .................................................................................................................................
 

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BART Analysis – Flint Creek 

LIST OF TABLES

TABLE 1-1. EXISTING VISIBILITY IMPAIRMENT ATTRIBUTABLE TO SN-01 (2001-2003) ................... 1-1

TABLE 3-1. ANNUAL AVERAGE BACKGROUND CONCENTRATION ..................................................... 3-2

TABLE 3-2. FL(RH) LARGE RH ADJUSTMENT FACTORS ..................................................................... 3-3

TABLE 3-3. FS(RH) SMALL RH ADJUSTMENT FACTORS ..................................................................... 3-3

TABLE 3-4. FSS(RH) SEA SALT RH ADJUSTMENT FACTORS ............................................................... 3-3

TABLE 4-1. BASELINE MAXIMUM 24-HOUR SO2, NOX, AND PM10 EMISSION RATES (AS HOURLY 

EQUIVALENTS) ....................................................................................................................... 4-1

TABLE 4-2. BASELINE VISIBILITY IMPAIRMENT ATTRIBUTABLE TO SN-01 BOILER (2001-2003) ..... 4-2

TABLE 5-1. AVAILABLE SO2 CONTROL TECHNOLOGIES FOR SN-01 .................................................. 5-1

TABLE 5-2. CONTROL EFFECTIVENESS OF TECHNICALLY FEASIBLE SO2 CONTROL TECHNOLOGIES 5-3

TABLE 5-3. SUMMARY OF COST EFFECTIVENESS FOR SN-01 SO2 CONTROLS ................................... 5-5

TABLE 5-4. DOLLAR PER DECIVIEW COST EFFECTIVENESS FOR SN-01 SO2 CONTROLS OF WET 

SCRUBBING ............................................................................................................................. 5-6

TABLE 5-5. DOLLAR PER DECIVIEW COST EFFECTIVENESS FOR SN-01 SO2 CONTROLS OF NIDS .... 5-6

TABLE 5-6. SUMMARY OF EMISSION RATES MODELED TO REFLECT DRY SCRUBBER FOR SO2

CONTROL ................................................................................................................................ 5-8

TABLE 5-7. SUMMARY OF MODELED IMPACTS FROM SO2 CONTROL VISIBILITY IMPACT ANALYSIS 

FOR SN-01 (2001-2003) .......................................................................................................... 5-9

TABLE 6-1. AVAILABLE NOX CONTROL TECHNOLOGIES FOR SN-01 ................................................ 6-2

TABLE 6-2. CONTROL EFFECTIVENESS OF TECHNICALLY FEASIBLE NOX CONTROL TECHNOLOGIES6-5

TABLE 6-3. SUMMARY OF COST EFFECTIVENESS FOR SN-01 NOX CONTROLS ................................... 6-8

TABLE 6-4. DOLLAR PER DECIVIEW COST EFFECTIVENESS FOR SN-01 NOX CONTROL USING 

LNB/OFA ............................................................................................................................... 6-9

TABLE 6-5. DOLLAR PER DECIVIEW COST EFFECTIVENESS FOR SN-01 NOX CONTROL USING 

LNB/OFA PLUS SNCR .......................................................................................................... 6-9

TABLE 6-6. DOLLAR PER DECIVIEW COST EFFECTIVENESS FOR SN-01 NOX CONTROL USING SCR . 6-9
 

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BART Analysis – Flint Creek 

TABLE 6-7. SUMMARY OF EMISSION RATES MODELED TO REFLECT LNB/OFA FOR NOX CONTROL6-11

TABLE 6-8. SUMMARY OF EMISSION RATES MODELED TO REFLECT SCR FOR NOX CONTROL ....... 6-11

TABLE 6-9. SUMMARY OF EMISSION RATES MODELED TO REFLECT LNB/OFA + SNCR FOR NOX

CONTROL .............................................................................................................................. 6-11

TABLE 6-10. SUMMARY OF VISIBILITY IMPROVEMENT ASSOCIATED WITH NOX CONTROL SYSTEM ON 

SN-01 (2001-2003) ............................................................................................................... 6-12
 

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BART Analysis – Flint Creek 

1. EXECUTIVE SUMMARY

This report documents the determination of the Best Available Retrofit Technology (BART) for 

Southwestern Electric Power Company’s (SWEPCO’s)1 electric generating unit at the Flint Creek 

Power Plant (SN-01). SN-01 is a dry bottom wall-fired boiler with a nominal design maximum heat 

input of 6,324 million British thermal units per hour (MMBtu/hr) that burns primarily low sulfur 

western coal. The unit has a nominal generating capacity rating of 558 MW and commenced 

commercial operation in 1978. It is currently equipped with an electrostatic precipitator and low NOX

burners. 

Based on modeling performed for this analysis, cumulative emissions of nitrogen oxides (NOX), 

sulfur dioxide (SO2), and particulate matter with a mean diameter smaller than ten microns (PM10) 

from SN-01 are predicted to cause or contribute greater than 0.5 deciviews (∆dv) of visibility 

impairment in four Class I Areas: Caney Creek Wilderness (CACR), Upper Buffalo Wilderness 

(UPBU), Hercules Glades Wilderness (HERC), and Mingo Wilderness (MING). 

A summary of the existing visibility impairment attributable to SN-01 based on the default natural 

conditions is provided in Table 1-1. The visibility impairment summarized in Table 1-1 is based on 

modeling conducted by Trinity Consultants (Trinity) using actual emissions data based on a 

combination of stack testing and CEMS as further described in Section 4 of this report. 

TABLE 1-1. EXISTING VISIBILITY IMPAIRMENT ATTRIBUTABLE TO SN-01 (2001-2003) 

Caney Creek 

Wilderness 

Upper Buffalo 

Wilderness 

Hercules 

Glades 

Wilderness 

Mingo 

Wilderness 

 

98th 

% 

∆dv 

Days 

> 0.5 

∆dv 

98th 

% 

∆dv 

Days > 

0.5 

∆dv 

98th 

% 

∆dv 

Days 

> 0.5 

∆dv 

98th 

% 

∆dv 

Days 

> 0.5 

∆dv 

AEP Flint Creek SN-01 0.993 55 1.066 76 0.734 60 0.653 24 

Trinity used the EPA’s BART guidelines in 40 CFR Part 512 and other recent EPA guidance to 

determine BART for SN-01. Trinity conducted a five-step analysis to determine BART that included 

the following: 

1. Identifying all available retrofit control technologies; 

2. Eliminating technically infeasible control technologies; 

3. Evaluating the control effectiveness of remaining control technologies; 

4. Evaluating impacts and document the results; 

5. Evaluating visibility impacts. 

 1 Southwestern Electric Power Company (SWEPCO) is an owner and the operator of the Flint Creek Power Plant, 

and a subsidiary of American Electric Power Company, Inc. (AEP). American Electric Power Service Corporation is a 

subsidiary of AEP that provides legal, accounting, engineering, and other services to the utility operating companies in the 

AEP system, including SWEPCO. SWEPCO and the Service Corporation are referred to generically as AEP throughout this 

report. 

2 The BART guidelines were published as amendments to the EPA’s RHR in 40 CFR Part 51, Section 308 on July 

6, 2005. 
 

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BART Analysis – Flint Creek 

Based on the five-step analysis, the following were determined to be BART: 

▲ SO2 – The BART analysis concluded that the installation of a dry scrubber and baghouse 

(e.g., Novel Integrated Deacidification System [NIDS] technology) constitutes BART. The 

proposed BART emission rate for SO2 is 0.06 lb/MMBtu calculated as a 30-day rolling 

average over each boiler operating day. 

▲ NOX – EPA recently issued a final rule allowing states that are subject to the Cross-State Air 

Pollution Rule (CSAPR) trading program for seasonal NOx to rely on the reductions achieved 

through that trading program to satisfy the regional haze program requirements for units 

subject to BART.3 Subsequently, CSAPR was vacated, and the Clean Air Interstate Rule 

(CAIR) remains in effect until an acceptable replacement rule is promulgated.4 If CSAPR is 

upheld and implemented in Arkansas, SWEPCO will rely on CSAPR to satisfy its regional 

haze obligations at SN-01. If CSAPR is vacated and CAIR remains in effect, EPA’s prior 

determination that the reductions provided under CAIR’s seasonal NOX trading program 

provide greater visibility improvements than BART should allow SWEPCO to rely on the 

seasonal CAIR program to satisfy its NOX obligations under BART.5 

In the alternative, SWEPCO has evaluated the cost-effectiveness and visibility improvement 

of candidate BART controls at SN-01. The visibility improvements associated with the 

addition of NOX controls at SN-01 are minimal, and the cost-effectiveness values for all 

control options exceed the values previously determined to be reasonable in EPA’s 

presumptive BART analysis. However, visibility improvements consistent with the modeled 

values used in CENRAP’s analysis for the interstate transport portion of Arkansas’s Regional 

Haze SIP obligations can be achieved with the addition of LNB/OFA, and this control option 

is proposed as BART for SN-01. If ADEQ determines that SWEPCO cannot rely on CAIR 

or CSAPR as an alternative to BART, the proposed BART emission rate for NOX at SN-01 is 

0.23 lb/MMBtu calculated as a 30-day rolling average over each boiler operating day based 

on the application of LNB/OFA controls. 

▲ PM10 – A BART determination for PM10 at SN-01 was approved in EPA’s March 12, 2012 

final rule based on the existing ESP and a BART emission rate of 0.1 lb/MMBtu.6

 3 “Regional Haze: Revisions to Provisions Governing Alternatives to Source-Specific Best Available Technology 

(BART) Determinations, Limited SIP Disapprovals and Federal Implementation Plans” 77 Fed. Reg. 33651 (June 7, 2012). 

4 EME Homer City Generation, L.P., et al., v. United States Environmental Protection Agency, et al.,EPA. Case 

No. 11-1302 (and consolidated cases), Opinion (D.C. Cir Aug. 21, 2012). 

5 “Regional Haze Regulations and Best Available Retrofit Technology (BART) Guidelines, 70 Fed. Reg. 39104, 

39143 (July 6, 2005). 

6 “Approval and Promulgation of Implementation Plans; Arkansas; Regional Haze State Implementation Plan; 

Interstate Transport State Implementation Plan To Address Pollution Affecting Visibility and Regional Haze. Final Rule,” 

77 Fed. Reg. 14604 (March 12, 2012). 
 

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BART Analysis – Flint Creek 

2. INTRODUCTION AND BACKGROUND

In the 1977 amendments to the Clean Air Act (CAA), Congress set a national goal to restore 

national parks and wilderness areas to pristine conditions by preventing any future, and 

remedying any existing, man-made visibility impairment. On July 1, 1999, the U.S. EPA published 

the final Regional Haze Rule (RHR). The objective of the RHR is to restore visibility to pristine 

conditions in 156 specific areas across the United States known as Class I areas. The CAA defines 

Class I areas as certain national parks (over 6,000 acres), wilderness areas (over 5,000 acres), national 

memorial parks (over 5,000 acres), and international parks that were in existence on 

August 7, 1977. 

The RHR requires States to set goals that provide for reasonable progress towards achieving natural 

visibility conditions for each Class I area in their state. On July 6, 2005, the EPA published 

amendments to its 1999 RHR, often called the Best Available Retrofit Technology (BART) rule, 

which included guidance for making source-specific BART determinations. The BART rule defines 

BART-eligible sources as sources that meet the following criteria: 

(1) Have potential emissions of at least 250 tons per year of a visibility-impairing pollutant, 

(2) Began operation between August 7, 1962 and August 7, 1977, and 

(3) Are included as one of the 26 listed source categories in the guidance. 

A BART-eligible source is subject to BART if the source is “reasonably anticipated to cause or 

contribute to visibility impairment in any federal mandatory Class I area.” EPA has determined that a 

source is reasonably anticipated to cause or contribute to visibility impairment if the 98th percentile 

visibility impacts from the source are greater than 0.5 delta deciviews (∆dv) when compared against a 

natural background7. Air quality modeling is the tool that is used to determine a source’s visibility 

impacts. 

Once it is determined that a source is subject to BART, a BART determination must address air 

pollution control measures for the source. The visibility regulations define BART as follows: 

“...an emission limitation based on the degree of reduction achievable through the 

application of the best system of continuous emission reduction for each pollutant 

which is emitted by...[a BART-eligible source]. The emission limitation must be 

established on a case-by-case basis, taking into consideration the technology available, 

the cost of compliance, the energy and non air quality environmental impacts of 

compliance, any pollution control equipment in use or in existence at the source, the 

remaining useful life of the source, and the degree of improvement in visibility which 

may reasonably be anticipated to result from the use of such technology. 

Specifically, the BART rule states that a BART determination should address the following five 

statutory factors: 

1. Existing controls 

2. Cost of controls 

 7 Note this is a change from the ADEQ protocol with the 2006 CENRAP data, as the original analysis for 

Arkansas reviewed the “High First High” impacts rather than the 98th percentile impacts 
 

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BART Analysis – Flint Creek 

3. Energy and non-air quality environmental impacts 

4. Remaining useful life of the source 

5. Degree of visibility improvement as a result of controls 

Further, the BART rule indicates that the five basic steps in a BART analysis can be summarized as 

follows: 

1. Identify all available retrofit control technologies; 

2. Eliminate technically infeasible control technologies; 

3. Evaluate the control effectiveness of remaining control technologies; 

4. Evaluate impacts and document the results; 

5. Evaluate visibility impacts 

A BART determination should be made for each visibility affecting pollutant (VAP) by following the 

five steps listed above for each VAP. 

SN-01 meets the three BART-eligibility criteria described above, and the existing visibility 

impairment attributable to SN-01 is greater than 0.5 dv in at least one Class I area. Thus, SN-01 is 

subject to BART. The details of the SN-01 existing/baseline emissions and the contribution of the 

emissions to visibility impairment can be found in Section 4. The VAPs emitted by SN-01 include 

NOX, SO2, and PM10 of various forms (filterable coarse particulate matter [PMc], filterable fine 

particle matter [PMf], elemental carbon [EC], inorganic condensable particulate matter [IOR CPM] as 

sulfates [SO4], and organic condensable particulate matter [OR CPM] also referred to as secondary 

organic aerosols [SOA]). The BART determinations for SO2, NOx, and PM10 can be found in 

Sections 5, 6, and 7, respectively. 
 

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3. MODELING METHODOLOGIES AND PROCEDURES

This section summarizes the dispersion modeling methodologies and procedures applied in this 

BART analysis. All dispersion modeling has been conducted using the CALPUFF modeling system, 

consisting of the CALPUFF dispersion model, the CALMET meteorological data processor, and the 

CALPOST post-processing program. 

CALPUFF is a multi-layer, multi-species, non-steady-state puff dispersion model, which can simulate 

the effects of time and space varying meteorological conditions on pollutant transport, transformation, 

and removal. CALPUFF uses three-dimensional meteorological fields developed by the CALMET 

model. In addition to meteorological data, several other input files are used by the CALPUFF model 

to specify source and receptor parameters. The selection and control of CALPUFF options are 

determined by user-specific inputs contained in the control file. This file contains all of the necessary 

information to define a model run (e.g., starting date, run length, grid specifications, technical 

options, output options). CALPOST processes concentration, deposition, and visibility impacts based 

on pollutant specific concentrations predicted by CALPUFF. 

3.1 CALMET AND CALPUFF 

The CALPUFF data and parameters are based on the 2005 BART modeling guidelines prepared for 

the Central States Regional Air Planning Association (CENRAP). The CALMET data and 

parameters are based on the protocol included in Appendix C. Note that the protocol included in 

Appendix C summarizes modeling methods and procedures that were followed to predict visibility 

impairment for several BART-eligible sources located in Oklahoma as part of the BART analyses for 

these sources. In addition, several sources in Texas used the CALMET data that was generated in 

accordance with the protocol in their BART analyses. 

3.2 CALPOST

The CALPOST visibility processing completed for this BART analysis is based on the October 2010 

guidance from the Federal Land Managers Air Quality Related Values Workgroup (FLAG). The 

2010 FLAG guidance, which was issued in draft form on July 8, 2008 and published as final guidance 

in December 2010, makes technical revisions to the previous guidance issued in December 2000. 

Visibility impairment is quantified using the light extinction coefficient (bext), which is expressed in 

terms of the haze index expressed in deciviews (dv). The haze index (HI) is calculated as follows: 





 



  10 (dv) 10 ln ext b HI

The impact of a source is determined by comparing the HI attributable to a source relative to 

estimated natural background conditions. The change in the haze index, in deciviews, also referred to 

as “delta dv,” or ∆dv, based on the source and background light extinction is based on the following 

equation: 
 

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BART Analysis – Flint Creek 

 dv = 10*ln

b b

b

ext, background ext, source

ext, background

 















The Interagency Monitoring of Protected Visual Environments (IMPROVE) workgroup adopted an 

equation for predicting light extinction as part of the 2010 FLAG guidance (often referred to as the 

new IMPROVE equation). The new IMPROVE equation is as follows: 

bext 

         

     

        

    Site specificRayleigh Scattering 2

Small Large

4 3 Small 4 3 Large

4 4 2 Small 4 4 2 Large

1.4 Sea Salt 0.33 NO

2.8 OC 6.1 OC 10 EC 1 PMF 0.6 PMC

2.4 NH NO 5.1 NH NO

2.2 NH SO 4.8 NH SO

 

    

 

 

 f RH b

f RH f RH

f RH f RH

SS

S L

S L

Visibility impairment predictions for SN-01 relied upon in this BART analysis used the equation 

shown above. The use of this equation is referred to as “Method 8” in the CALPOST control file. 

The use of Method 8 requires that one of five different “modes” be selected. The modes specify the 

approach for addressing the growth of hygroscopic particles due to moisture in the atmosphere. 

“Mode 5” has been used in this BART analysis. Mode 5 addresses moisture in the atmosphere in a 

similar way as to “Method 6”, where “Method 6” is specified as the preferred approach for use with 

the old IMPROVE equation in the CENRAP BART modeling protocol. 

CALPOST Method 8, Mode 5 requires the following: 

 Annual average concentrations reflecting natural background for various particles and for sea 

salt 

 Monthly RH factors for large and small ammonium sulfates and nitrates and for sea salts 

 Rayleigh scattering parameter corrected for site-specific elevation 

Tables 3-1 to Table 3-4 below show the values for the data described above that were input to 

CALPOST for use with Method 8, Mode 5. The values were obtained from the 2010 FLAG 

guidance. 

TABLE 3-1. ANNUAL AVERAGE BACKGROUND CONCENTRATION 

Class I Area (NH4)2SO4 NH4NO3 OM EC Soil CM Sea Salt 

Rayleigh 

(Mm-1) 

Caney Creek Wilderness 0.23 0.1 1.8 0.02 0.5 3 0.03 11 

Upper Buffalo Wilderness 0.23 0.1 1.8 0.02 0.5 3 0.03 11 

Hercules Glades Wilderness 0.23 0.1 1.8 0.02 0.5 3 0.02 11 

Mingo Wilderness 0.23 0.1 1.83 0.02 0.51 3.05 0.04 12 
 

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TABLE 3-2. FL(RH) LARGE RH ADJUSTMENT FACTORS

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 

Caney Creek Wilderness 2.77 2.53 2.37 2.43 2.68 2.71 2.59 2.6 2.71 2.69 2.67 2.79 

Upper Buffalo Wilderness 2.71 2.48 2.31 2.33 2.61 2.64 2.57 2.59 2.71 2.58 2.59 2.72 

Hercules Glades Wilderness 2.7 2.48 2.3 2.3 2.57 2.59 2.56 2.6 2.69 2.54 2.57 2.72 

Mingo Wilderness 2.73 2.52 2.34 2.28 2.53 2.6 2.64 2.67 2.71 2.56 2.56 2.73 

TABLE 3-3. FS(RH) SMALL RH ADJUSTMENT FACTORS 

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 

Caney Creek Wilderness 3.85 3.44 3.14 3.24 3.66 3.71 3.49 3.51 3.73 3.72 3.68 3.88 

Upper Buffalo Wilderness 3.73 3.33 3.03 3.07 3.54 3.57 3.43 3.5 3.71 3.51 3.52 3.74 

Hercules Glades Wilderness 3.7 3.33 3.01 3.01 3.47 3.48 3.41 3.51 3.67 3.43 3.46 3.73 

Mingo Wilderness 3.74 3.38 3.07 2.97 3.39 3.52 3.57 3.64 3.72 3.47 3.43 3.74 

TABLE 3-4. FSS(RH) SEA SALT RH ADJUSTMENT FACTORS 

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 

Caney Creek Wilderness 3.9 3.52 3.31 3.41 3.83 3.88 3.69 3.68 3.82 3.76 3.77 3.93 

Upper Buffalo Wilderness 3.85 3.47 3.23 3.27 3.72 3.78 3.69 3.7 3.84 3.64 3.67 3.86 

Hercules Glades Wilderness 3.86 3.51 3.23 3.22 3.66 3.72 3.69 3.73 3.81 3.57 3.65 3.88 

Mingo Wilderness 3.92 3.58 3.3 3.19 3.58 3.72 3.8 3.82 3.85 3.61 3.66 3.9 
 

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4. EXISTING EMISSIONS AND VISIBILITY IMPAIRMENT

This section summarizes the existing (i.e. baseline) visibility impairment attributable to SN-01 based 

on air quality modeling conducted by Trinity. 

4.1 NOX, SO2, AND PM10 BASELINE EMISSION RATES

Table 4-1 summarizes the emission rates that were modeled for SO2, NOX, and PM10, including the 

speciated PM10 emissions. The SO2 and NOX emission rates are the highest actual 24-hour emission 

rates based on 2001-2003 continuous emissions monitoring system (CEMS) data. The PM10 emission 

rate is based on the lb/MMBtu level for total PM10 as determined from the March 2006 stack test data 

multiplied by the maximum 24-hour rolling average heat input to the boiler from 2001-2003 (6,093 

MMBtu/hr). The emission rates for the PM10 species reflect the breakdown of the PM10 determined 

from the National Park Service (NPS) “speciation spreadsheet” for Dry Bottom Boiler Burning 

Pulverized Coal using only ESP8. More specifically, the NPS workbook shows the following 

baseline distribution for the PM species: 

▲ Coarse PM (PMC) = 15.5% 

▲ Fine soil (modeled as PMF) = 11.9% 

▲ Fine elemental carbon (modeled as EC) = 0.5 % 

▲ Organic condensable PM (modeled as SOA) = 14.4% 

▲ Inorganic condensable PM (modeled as SO4) = 57.7% 

TABLE 4-1. BASELINE MAXIMUM 24-HOUR SO2, NOX, AND PM10 EMISSION RATES (AS HOURLY 

EQUIVALENTS) 

SO29 NOX10

Total 

PM10 SO4 PMc PMf SOA EC 

Source (lb/hr) (lb/hr) (lb/hr) (lb/hr) (lb/hr) (lb/hr) (lb/hr) (lb/hr) 

SN-01 4,728.4 1,945.0 192.5 111.2 29.8 22.9 27.8 0.9 

4.2 BASELINE VISIBILITY IMPAIRMENT

Trinity conducted modeling to determine the visibility impairment attributable to SN-01 in four Class 

I Areas: Caney Creek Wilderness (CACR), Upper Buffalo Wilderness (UPBU), Hercules Glades 

Wilderness (HERC), and Mingo Wilderness (MING) using the CALPUFF dispersion model. 

 8 The NPS Workbook, "PC Dry Bottom ESP Example.xls" updated 03/2006, was obtained from the NPS website: 

http://www.nature.nps.gov/air/Permits/ect/index.cfm. The following parameters were input into the workbook for speciation 

determination: total PM10 emission rate of 192.5 lb/hr, heat value of 8,500 Btu/lb, sulfur content of 1%, ash content of 

6.6%. 

9 Hourly rate was derived from EPA’s Clean Air Market Database (CAMD) daily rates of 113,482 lb/day. 

10 Hourly rate was derived from EPA’s Clean Air Market Database (CAMD) daily rates of 46,680 lb/day. 
 

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BART Analysis – Flint Creek 

Table 4-2 provides a summary of the modeled visibility impairment attributable to SN-01 at CACR, 

UPBU, HERC, and MING based on the emission rates shown in Table 4-1. Note that all of the 

CALMET, CALPUFF, and CALPOST modeling files are included as part of the electronic files 

submitted with this document. 

TABLE 4-2. BASELINE VISIBILITY IMPAIRMENT ATTRIBUTABLE TO SN-01 BOILER (2001-2003) 

Year 

Maximum 

(Δdv) 

98th Percentile 

(Δdv) 

No. of Day with 

Δdv ≥ 0.5 

98th Percentile 

% SO4

98th Percentile 

% NO3

98th Percentile 

% PM10

98th 

Percentile 

% NO2

 Caney Creek Wilderness 

2001 1.372 0.668 21 65.91 31.75 0.92 1.41 

2002 1.247 0.734 14 84.92 14.45 0.63 0 

2003 1.408 0.993 20 71.86 27.26 0.74 0.15 

 Upper Buffalo Wilderness 

2001 1.914 1.034 27 56.82 41.44 1.05 0.69 

2002 2.585 1.066 21 47.31 50.9 0.87 0.93 

2003 1.439 0.745 28 48.94 48.56 1.5 1.01 

 Hercules Glades Wilderness 

2001 1.462 0.730 24 47.31 50.69 1.19 0.81 

2002 1.439 0.734 19 86.99 7.39 2.06 3.56 

2003 2.186 0.705 17 82.93 16.21 0.72 0.13 

 Mingo Wilderness 

2001 1.37 0.653 13 91.3 8.29 0.4 0.01 

2002 0.883 0.444 7 59.98 38.83 0.94 0.24 

2003 1.553 0.409 4 66.63 32.96 0.38 0.04 
 

Southwestern Electric Power Company 5-1 Trinity Consultants 

BART Analysis – Flint Creek 

5. SO2 BART EVALUATION

5.1 IDENTIFICATION OF AVAILABLE RETROFIT SO2 CONTROL 

TECHNOLOGIES

Sulfur oxides, SOX, are generated during coal combustion from the oxidation of sulfur contained in 

the fuel. SOX emissions are almost entirely dependent on the sulfur content of the fuel and are 

generally not affected by boiler size or burner design. SOX emissions from conventional combustion 

systems are predominantly in the form of SO2. Since SO2 is the predominant sulfur compound emitted 

from SN-01, the BART analysis is specific to emissions of SO2. 

Step 1 of the top-down control review is to identify available retrofit control options for SO2. The 

available SO2 retrofit control technologies for SN-01 are summarized in Table 5-1. The retrofit 

controls examined are limited to add-on controls that eliminate SO2 after it is formed, as SN-01 

currently uses a low sulfur fuel and would not achieve significant additional reductions through 

alternative coal supplies. 

TABLE 5-1. AVAILABLE SO2 CONTROL TECHNOLOGIES FOR SN-01 

SO2 Control Technologies 

Wet Scrubber 

Dry Scrubber or Novel Integrated Deacidification (NID) 

Circulating Dry Scrubber 

Dry Sorbent Injection 

5.2 ELIMINATE TECHNICALLY INFEASIBLE SO2 CONTROL TECHNOLOGIES

Step 2 of the BART determination is to eliminate technically infeasible SO2 control technologies that 

were identified in Step 1. 

5.2.1 DRY SORBENT INJECTION

Dry sorbent injection involves the injection of a sorbent into the exhaust gas stream where 

SO2 reacts with and becomes entrained in the sorbent. The stream is then passed through a 

particulate control device to remove the sorbent and entrained SO2. The process was 

developed as a lower cost Flue Gas Desulfurization (FGD) option because the mixing of 

the SO2 and lime occurs directly in the exhaust gas stream instead of in a separate tower. 

Depending on the residence time, gas stream temperature, and limitations of the particulate 

control device, sorbent injection control efficiency can range between 40 and 60 percent.11 

This control is a technically feasible option for the control of SO2 from SN-01. 

 11 "Assessment of Control Technology Options for BART-Eligible Sources: Steam Electric Boilers, Industrial 

Boilers, Cement Plants and Paper and Pulp Facilities" Northeast States for Coordinated Air Use Management (NESCAUM), 

March 2005. 
 

Southwestern Electric Power Company 5-2 Trinity Consultants 

BART Analysis – Flint Creek 

5.2.2 DRY SCRUBBER

In a dry scrubber, an alkaline reagent (usually lime), in the form of a slurry, is atomized 

into the flue gas stream, where it reacts with and collects the SO2.

12 The liquid-to-gas ratio 

is such that the heat from the exhaust gas causes the water to evaporate before the droplets 

reach the bottom of the tower. This leads to the formation of a dry powder which is carried 

out with the gas and collected with a fabric filter. 

Novel Integrated Deacidification (NID) technology is a particular type of dry scrubber. 

Hydrated lime is added to recirculated dust in the mixer of the system. The solids are 

sprayed with a thin layer of water in the mixer before being transported to the reactor. The 

amount of water added is only a few percent which means that the dust remains dry. 

Hydrated lime reacts with SO2 in the NID-reactor such that SO2 is bound to the hydrated 

lime. The flue gas entrained with dry dust material enters the fabric filter where filter traps 

the dust material and clean air is released to atmosphere. Most of the solid material is 

reused in the system. The system has a high recirculation ratio of the dry dust material. 

Discussions with vendors have indicated that an outlet emission rate of 0.06 lb/MMBtu at 

Flint Creek will be achievable with the NID technology evaluated. A rate of 0.06 

lb/MMBtu represents a 92% control from the baseline 30-day average rate of 0.75 

lb/MMBtu. The controlled rates was quoted as an outlet rate rather than a straight percent 

control. 

Existing dry scrubber control efficiencies range from 60 to 95 percent.13 This is a 

technically feasible option for the control of SO2 from SN-01. 

5.2.3 WET SCRUBBER

Wet scrubbing involves scrubbing the exhaust gas stream with a slurry comprised of lime 

or limestone in suspension. The process takes place in a wet scrubbing tower located 

downstream of a PM control device such as a fabric filter or an electrostatic precipitator 

(ESP) to prevent the plugging of spray nozzles and other problems caused by the presence 

of particulates in the scrubber. Similarly to the chemistry illustrated above for dry 

scrubbing, the SO2 in the gas stream reacts with the lime or limestone slurry to form 

calcium sulfite and calcium sulfate. Wet lime scrubbing is capable of achieving 80-95 

percent control when used with lower sulfur coals like those burned at SN-01.14 This 

control is a technically feasible option for the control of SO2 from SN-01. 

 12 U.S. EPA. Air Pollution Control Technology Fact Sheet: Flue Gas Desulfurization (FGD) - Wet, Spray Dry, 

and Dry Scrubbers. (EPA-452/F-03-034). 

13 EPA Basic Concepts in Environmental Sciences, Module 6: Air Pollutants and Control Techniques 

http://www.epa.gov/eogapti1/module6/sulfur/control/control.htm 

14 Ibid. 
 

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BART Analysis – Flint Creek 

5.2.4 CIRCULATING DRY SCRUBBER (CDS) 

In the circulating dry scrubbing process, the flue gas is introduced into the bottom of a 

reactor vessel at high velocity through a venturi nozzle; the exhaust is mixed with water, 

hydrated lime, recycled flyash and CDS reaction products. The intensive gas-solid mixing 

that occurs in the reactor promotes the reaction of sulfur oxides in the flue gas with the dry 

lime particles. The mixture of reaction products (calcium sulfite/sulfate), unreacted lime, 

and fly ash is carried out with the exhaust and collected in an ESP or fabric filter. A large 

portion of the collected particles is recycled to the reactor to sustain the bed and improve 

lime utilization. The control efficiency of a CDS is less than that of a dry scrubber.15 This 

control is a technically feasible option for the control of SO2 from SN-01. 

5.3 RANK OF TECHNICALLY FEASIBLE SO2 CONTROL OPTIONS BY 

EFFECTIVENESS

The third step in the BART analysis is to rank the technically feasible options according to their 

effectiveness in reducing the visibility affecting pollutants (VAP). Table 5-2 provides a ranking of 

the control levels for the controls listed in the previous section for SN-01. 

TABLE 5-2. CONTROL EFFECTIVENESS OF TECHNICALLY FEASIBLE SO2 CONTROL 

TECHNOLOGIES

Control Technology 

Controlled Emission 

Rate 

(lb/MMBtu) 

Estimated Control 

Efficiency 

Wet Scrubber 0.04 95% 

Dry Scrubber or NID 0.06 92% 

Circulating Dry Scrubber 0.19 75% 

Dry Sorbent Injection 0.30 60% 

5.4 EVALUATION OF IMPACTS FOR FEASIBLE SO2 CONTROLS 

A shown in Table 5-2, wet scrubbing can achieve a 95% reduction in SO2 while dry scrubbing or NID 

can achieve a 92% reduction in SO2, and these technologies are the most effective technologies at 

reducing SO2. Step four of the BART analysis procedure is the impact analysis. The BART 

determination guidelines list the four factors to be considered in the impact analysis: 

▲ Cost of compliance 

▲ Energy impacts 

▲ Non-air quality impacts; and 

▲ The remaining useful life of the source 

 15 Babcock and Wilcox sales materials. 
 

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BART Analysis – Flint Creek 

AEP is providing Step 4 and Step 5 evaluations specific to the NID technology as well as WFGD. 

Also, AEP is providing a discussion of energy and non-air quality impacts of wet scrubbing versus 

the NID technology. 

5.4.1 COST OF COMPLIANCE

Control Costs 

The capital and operating costs of WFGD and NID used in the cost effectiveness 

calculations were calculated based on vendor estimates and published calculations 

methods. The EPA Air Pollution Control Cost Manual was followed to the extent possible 

and was supplemented with vendor and site-specific information where available. The 

capital costs were annualized over a 30-year period and then added to the annual operating 

costs to obtain the total annualized costs. The details of the capital and operating cost 

estimates are provided in Appendix A of this report. 

Annual Tons Reduced 

The annual tons reduced that were used in the cost effectiveness calculations were 

determined by subtracting the estimated controlled annual emission rate from the baseline 

annual emission rate. The baseline annual emission rate is the average rate from 2001-

2003, as reported by AEP in their air emission inventories. The controlled annual emission 

rates were based on lb/MMBtu levels believed to be achievable for the control technology 

multiplied by the baseline heat input in MMBtu/yr to the boiler. The baseline heat input is 

based on the 2001-2003 average daily heat input for SN-01 as determined from the EPA’s 

Clean Air Markets Database (CAMD), divided by 24 hours in a day times an estimated 

7,752 hours per year, the average number of operating hours from 2001-2003. 

 

Cost Effectiveness 

The cost effectiveness in dollars per ton of SO2 reduced was determined by dividing the 

annualized cost of control by the annual tons reduced. Table 5-3 indicates that the cost 

effectiveness of the wet scrubber at an SO2 rate of 0.04 lb/MMBtu is approximately $5,600 

per ton of SO2 removed. The cost effectiveness in dollars per deciview of visibility is over 

$508.9 million/dv across the Class I areas, as seen in Table 5-4. 

By comparison, Table 5-3 shows the cost effectiveness of a NIDS at an SO2 rate of 0.06 

lb/MMBtu is approximately $4,700 per ton of SO2 removed. The cost effectiveness in 

dollars per deciview is approximately $395 million/dv across the Class I areas, as seen in 

Table 5-5. Table 5-3 shows that the wet scrubber is $30,477/ton incrementally more 

expensive than the dry scrubber. 
Southwestern Electric Power Company 5-5 

BART Analysis – Flint Creek 

TABLE 5-3.

SUMMARY OF 

COST 

EFFECTIVENESS FOR SN-01 SO2 CONTROLS 

Baseline 

Emission 

Rate

Controlled 

Emission 

Level1

Annual Heat 

Input3

Controlled 

Emission 

Rate

SO2 

Reduced Capital Cost

Annual 

Capital Cost

Annual 

Fixed O&M

Annual 

Variable 

O&M

Total 

Annual 

Cost

(tpy) (lb/MMBtu) (MMBtu/yr) (tpy) (ton/yr) ($) ($/yr) ($/yr) ($/yr) ($/yr) 

NIDS 2 11,641.00 0.06 37,344,776 1,120.34 10,520.66 430,449,714 34,688,394 4,210,000 10,806,080 49,704,474 

Wet Scrubber2 11,641.00 0.04 37,344,776 746.90 10,894.10 533,249,627 42,972,670 4,730,000 13,383,320 61,085,990 

2 NIDS and Wet Scrubber cost information from vendor communciation/estimates1 EPA Basic Concepts in Environmental Sciences, Module 6: Air Pollutants and Control Techniques 

http://www.epa.gov/eogapti1/module6/sulfur/control/control.htmIn conjunction with vendor estimates

3 Baseline heat input was determined from CAMD, 2001-2003, average daily heat inputs times the average number of operating hours from 2001-2003.
Southwestern Electric Power Company 5-6 

BART Analysis – Flint Creek 

TABLE 5-4.

DOLLAR PER 

DECIVIEW 

COST 

EFFECTIVENESS FOR SN-01 SO2 CONTROLS OF 

WET 

SCRU

Caney Creek 0.993 0.353 0.640 61,085,990 

$ 

Hercules-Glades 0.734 0.348 0.386 61,085,990 

$ 

Mingo 0.653 0.225 0.428 61,085,990 

$ 

Upper Buffalo 1.066 0.523 0.543 61,085,990 

$ 

Class I Area 

Baseline 98th 

Percentile 

∆dv

WFGD Controlled 98th 

Percentile 

∆dv

Improvement in 98th 

Percentile 

∆dv

Total Annual WFGD 

Cost

TABLE 5-5.

DOLLAR PER 

DECIVIEW 

COST 

EFFECTIVENESS FOR SN-01 SO2 CONTROLS OF NID

Caney Creek 0.993 0.346 0.647 49,704,474 Hercules-Glades 0.734 0.311 0.423 49,704,474 Mingo 0.653 0.216 0.437 49,704,474 Upper Buffalo 1.066 0.497 0.569 49,704,474 

Class I Area 

Baseline 98th 

Percentile 

∆dv

NID Controlled 98th Percentile 

∆dv

Total Annual NID 

Cost

Improvement in 98th 

Percentile 

∆dv
 

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BART Analysis – Flint Creek 

5.4.2 ENERGY IMPACTS AND NON-AIR QUALITY IMPACTS

Wet scrubbing is expected to achieve a slightly higher level of control of SO2 emissions 

compared to the proposed NID technology. However, the negative non-air quality 

environmental impacts are greater with wet scrubbing systems. Wet scrubbers require 

increased water use and generate large volumes of wastewater and solid waste/sludge that 

must be treated. This places additional burdens on the wastewater treatment and solid 

waste management capabilities. Moreover, if wet scrubbing produces calcium sulfite 

sludge, the sludge will be water-laden, and it must be stabilized before landfilling. Wet 

scrubbing systems have increased power requirements and increased reagent usage over 

dry scrubbers. Wet scrubber-controlled systems also have the potential for increased 

particulate and sulfuric acid mist releases. Thus, from an overall environmental 

perspective, dry scrubbing (i.e., NID technology) is superior to wet scrubbing. 

5.4.3 REMAINING USEFUL LIFE

The remaining useful life of SN-01 does not impact the annualized capital costs because 

the useful life of the unit is anticipated to be at least as long as the capital cost recovery 

period, which is 30 years based on EPA cost estimates. 

5.5 EVALUATION OF VISIBILITY IMPACT OF FEASIBLE SO2 CONTROLS 

A final impact analysis was conducted to assess the visibility improvement achieved by comparing 

the impacts associated with the baseline emission rates to the impacts associated with the controlled 

emission rates. Section 4 of this report documents the existing visibility impairment attributable to 

SN-01. In order to assess the visibility improvement associated with the considered control options, 

the controlled SO2 emission rates were modeled using CALPUFF. 

The SO2 emission rate associated with the NID for SN-01 is detailed as follows: 

P * HI = 379.44 lb/hr 

Where: 

P (controlled emission level) = 0.06 lb/MMBtu 

HI (hourly heat input) = 6,324 MMBtu/hr 

Table 5-6 summarizes the lb/hr emission rates that were modeled to reflect the addition of NIDS as a 

control at Flint Creek. The SO2 rate was developed from the controlled rate of 0.06 lb/MMBtu and 

the boiler heat input of 6,324 MMBtu/hr. The SO4 emission rate was determined assuming the 

reduction in SO4 from the baseline case is proportional to the reduction in SO2 from the baseline case 

to the controlled case (92%). The NIDS will have co-effects on some of the acid gases. The control 

of H2SO4 will result in fewer sulfates. The NOx emission rate was modeled at the baseline rate. The 

NIDS involves the use of a baghouse. The change from the current ESP to baghouse will result in 

changes in PM speciation. All other rates that changed from the baseline case were determined using 

the National Parks Services (NPS) speciation spreadsheets for dry bottom boilers burning pulverized 

coal using only fabric filter for emissions control. 
 

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BART Analysis – Flint Creek 

Table 5-6 also summarizes the emission rates that were modeled to reflect the addition of a wet 

scrubber on SN-01, at an outlet emission rate of 0.04 lb/MMBtu. The SO2 rate was developed by 

multiplying the controlled level of 0.04 lb/MMBtu by the boiler heat input of 6,324 MMBtu/hr. 

Sulfur trioxide (SO3), which condenses to sulfuric acid aerosols in an FGD system, is removed 

efficiently (greater than 90%) with a dry FGD/baghouse equipment combination. Wet scrubbers have 

less affinity for acid mist and typically capture between 25-50% of sulfuric acid aerosols, according 

to FGD suppliers. In order to conservatively estimate the maximum effects of wet scrubbing, the 

modeling analysis assumes a 50% reduction of SO3 and thus a 50% reduction in SO4 from the 

baseline case. The NOX emission rates were modeled at the baseline rates. The PM rates that 

changed from the baseline case were determined using the NPS speciation spreadsheets for dry 

bottom boilers burning pulverized coal using only fabric filter for emissions control. 

TABLE 5-6. SUMMARY OF EMISSION RATES MODELED TO REFLECT DRY SCRUBBER FOR SO2

CONTROL

 

SO2

(lb/hr) 

SO4 

(lb/hr) 

NOx

(lb/hr) 

PMC 

(lb/hr) 

PMF 

(lb/hr) 

SOA 

(lb/hr) 

EC 

(lb/hr) 

PM10, total 

(lb/hr) 

SN-01: NIDS 379.4 8.9 1,945.0 0.8 0.8 2.2 0.0 12.7 

SN-01: Wet 

Scrubbing 253.0 55.6 1,945.0 5.0 4.8 13.9 0.2 79.4 

Comparisons of the existing visibility impacts and the visibility impacts based on the NIDS, including 

the maximum modeled visibility impact, 98th percentile modeled visibility impact, and the number of 

days with a modeled visibility impact greater than 0.5 Δdv, for each Class I area are provided in Table 

5-7. 
Southwestern Electric Power Company 5-9 

BART Analysis – Flint Creek 

TABLE 5-7.

SUMMARY OF 

MODELED IMPACTS FROM SO2 CONTROL 

VISIBILITY IMPACT 

ANALYSIS FOR SN-0

Caney Creek Wilderness Upper Buffalo Wilderness Hercules Glades Wilderness 

Maximum Impact 

(Δdv) 

98% Impact (Δdv) 

 # Days > 0.5 Δdv 

Maximum Impact 

(Δdv) 

98% Impact (Δdv) 

 # Days > 0.5 Δdv 

Maximum Impact 

(Δdv) 

98% Impact (Δdv) 

 # Days > 0.5 Δdv 

Existing Emission Rate 

1.408 0.993 55 2.585 1.066 76 2.186 0.734 60 1

NIDS 0.749 0.346 6 1.469 0.497 12 0.878 0.311 5 0

Post Control Improvement 

0.659 0.647 49 1.116 0.569 64 1.308 0.423 55 0

Wet Scrubber 0.808 0.353 6 1.523 0.523 13 0.885 0.348 5 0

Post Control Improvement over NIDS 

-0.059 -0.007 0 -0.054 -0.026 -1 -0.007 -0.037 0 -0

Note: The visibility improvement shown in the table has been calculated from baseline and controlled impacts that include more decimshown in the table. Due to rounding of the baseline and controlled impacts shown in the table, the visibility improvement calculated fro

controlled impacts shown in the table may be slightly different than the visibility improvement reflected in the table. 
 

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BART Analysis – Flint Creek 

As shown in Table 5-7, based on visibility predictions from the CALPUFF modeling system, the 

operation of a dry scrubber will result in up to a 0.647 Δdv improvement (98th percentile basis) 

(depending on the Class I area) to the existing visibility impairment attributable to SN-01. By 

comparison, wet scrubbing does not add additional visibility improvement for SN-01 over dry 

scrubbing. The reason wet scrubbing, despite the lower SO2 emission rate, does not produce greater 

visibility improvement is because it results in other visibility impairing emissions.16 

5.6 PROPOSED BART FOR SO2

SWEPCO is proposing that the SO2 BART emission rate for SN-01 be 0.06 lb/MMBtu, based on the 

installation and operation of the NID technology. AEP is proposing to meet this limit calculated as a 

30-day rolling average over each boiler operating day. Compliance will be demonstrated using data 

from the existing continuous emissions monitoring systems (CEMS). 

The visibility improvement attributable to SN-01 through the use of the NIDS ranges from 53.4% to 

66.9% across the affected Class I areas (98th percentile basis). This level of improvement is 

achievable at a cost effectiveness of approximately $4,700 per ton of SO2 removed. By comparison, 

wet scrubbing is incrementally more expensive and offers less visibility improvement overall. In 

addition, the adverse environmental impacts from the use of wet scrubbing, including an increase in 

particulate and sulfuric acid mist emissions as well as increased water and energy usage and 

wastewater to be treated, make dry scrubbing a more appealing option. 

5.6.1 COMPARATIVE SO2 BART DETERMINATIONS 

The BART emission level proposed for SN-01 is among the most stringent BART emission levels 

approved for any coal-fired generating unit over the last two years. In Oklahoma, for similar boilers, 

EPA determined BART to be 0.06 lb/MMBtu achieved through use of dry scrubbers.17 In 

Nebraska18 at the Gerald Gentleman Station, BART for SO2 was also determined to be 0.06 

lb/MMBtu achieved through use of dry scrubbers. These similar units provide a good comparison of 

emission levels achievable through similar control technology. Levels lower than 0.06 lb/MMBtu 

have been considered, but rejected based on lack of operating experience on retrofit units, the 

incremental cost of additional reductions, and the limited incremental visibility improvement 

associated with those costs. AEP has no data to suggest that lower emission levels are sustainably 

achievable with the NID technology in a retrofit application, and has not been guaranteed any better 

performance by equipment vendors. All of these reasons support rejecting any lower emission level 

for SN-01. 

Other BART determinations have resulted in higher emission limitations. For example, in Alabama19

a smaller EGU was allowed an emission limitation of 0.47 lb/MMBtu through use of flue sorbent 

injection or comparable technologies. In Arizona20, SO2 BART was determined to be in the range of 

 16 Wet scrubbers have less affinity for acid mist than dry scrubbers; thus, sulfate particles that form from sulfuric 

acid in the stack will be lower for dry scrubbers than wet scrubbers. AEP’s best understanding of the reason wet scrubbing 

does not produce greater visibility improvement that drying scrubbing, despite the lower SO2 rate, is that the SO4 rate 

associated with wet scrubbing is higher. 

17 77 Fed. Reg. 16168 (March 22, 2011). 

18 77 Fed. Reg. 40150 (July 6, 2012). 

19 77 Fed. Reg. 11937 (Feb. 28, 2012). 

20 77 Fed. Reg. 42834 (July 20, 2012). 
 

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BART Analysis – Flint Creek 

0.08 – 0.15 lb/MMBtu from existing wet scrubbers. An EGU in Colorado21 has a proposed BART 

emission rate of 0.13 lb/MMBtu through use of dry scrubbing. It is interesting to note that a lower 

emission rate of 0.09 lb/MMBtu was evaluated and determined not reasonable due to the little 

visibility improvement as compared to the higher costs between scrubbing at these two rates. 

In other determinations, such as Illinois22, the control technology was not stated in the BART 

determination but the SO2 rate determined to be BART was in the range of 0.11 – 0.23 lb/MMBtu, 

dependent upon boiler type and averaging considerations. SO2 BART in Kansas23 was achieved 

through “scrubbing” with an emission limitation of 0.10 lb/MMBtu for one boiler and through wet 

scrubbing with an emission limitation of 0.15 lb/MMBtu for another. An EGU in Montana24 similar 

to AEP’s SN-01 has a BART emission rate of 0.08 lb/MMBtu. 

The proposed SO2 BART emission rate is equivalent to the most stringent rates previously approved 

by EPA, is consistent with the design specifications for this equipment, and results in significant 

visibility improvement in the affected Class I areas. The SO2 emission rate of 0.06 lb/MMBtu should 

be adopted as BART for SN-01. 

 21 77 Fed. Reg. 18052 (March 26, 2012). 

22 77 Fed. Reg. 3966 (Jan. 26, 2012). 

23 77 Fed. Reg. 52604 (Aug. 23, 2011). 

24 77 Fed. Reg. 23988 (April 20, 2012). 
 

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BART Analysis – Flint Creek 

6. NOX BART EVALUATION

6.1 CROSS-STATE AIR POLLUTION RULE, 

CLEAN AIR INTERSTATE RULE, AND BART 

On June 7, 2012 EPA published a final rule allowing states participating in the Cross-State Air 

Pollution Rule (CSAPR) trading program to use CSAPR to satisfy BART. Arkansas is one of the 

states with units subject to CSAPR that will participate in a NOX trading program during the ozone 

season. EPA commented that “NOX control in the five ozone season-only states is achieved 

predominantly by combustion controls.”25 Due to the nature of combustion controls, plants typically 

keep combustion controls in place and running year-round, even if emission limitations are seasonal. 

Although Arkansas is an ozone season-only state, combustion controls would run anytime the unit is 

in operation. However, on August 21, 2012, the D. C. Circuit Court of Appeal issued a decision 

vacating CSAPR and ordering EPA to continue to implement the Clean Air Interstate Rule (CAIR) 

until a new rule is adopted to replace it. The Court’s decision will not be effective until the time for 

filing rehearing petitions has passed, or any filed petitions for rehearing have been considered by the 

Court.26 If CSAPR is upheld and implemented in Arkansas, SWEPCO proposes rely on CSAPR to 

satisfy its regional haze obligations at SN-01. 

Prior to adopting CSAPR, EPA issued a rule confirming that CAIR provides greater reasonable 

progress toward the national visibility goal than application of BART for NOX emissions at BARTeligible sources.27 Since EPA has made the determination that CAIR reductions provide better 

progress than BART, and Arkansas has adopted the CAIR requirements into the Arkansas SIP,28

SWEPCO should be entitled to rely upon CAIR to satisfy its obligations for NOX reductions at SN01, if CSAPR is vacated in accordance with the D. C. Circuit’s opinion. 

In the alternative, SWEPCO has evaluated the cost-effectiveness and visibility improvement of 

candidate BART controls at SN-01. The visibility improvements associated with the addition of NOX

controls at SN-01 are minimal, and the cost-effectiveness values for all control options exceed the 

values previously determined to be reasonable in EPA’s presumptive BART analysis. However, 

visibility improvements consistent with the modeled values used in CENRAP’s analysis for the 

interstate transport portion of Arkansas’s Regional Haze SIP obligations can be achieved with the 

addition of newer generation LNB/OFA systems, and are proposed as BART for SN-01. If ADEQ 

determines that SWEPCO cannot rely on CAIR or CSAPR as an alternative to BART, the proposed 

BART emission rate for NOX at SN-01 is 0.23 lb/MMBtu calculated as a 30-day rolling average over 

each boiler operating day based on the application of LNB/OFA controls. 

 25 “Regional Haze: Revisions to Provisions Governing Alternatives to Source-Specific Best Available Retrofit 

Technology (BART) Determination, Limited SIP Disapprovals, and Federal Implementation Plans,” 77 Fed. Reg. 33651 

(June 7, 2012). 

26 EME Homer City v. EPA, Case No. 11-1302 and consolidated cases, Opinion, (D.C. Cir. Aug. 21, 2012). 

27 70 Fed. Reg. 39104, 39136-37, and 39143 (July 6, 2005). 

28 APC&EC Reg. 19.1401 et seq.; approved at 72 Fed. Reg. 54556 (Sept. 26, 2007). 
 

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BART Analysis – Flint Creek 

6.2 IDENTIFICATION OF AVAILABLE RETROFIT NOX CONTROL 

TECHNOLOGIES

Nitrogen oxides, NOX, are produced during fuel combustion when nitrogen contained in both the fuel 

and the combustion air is exposed to high temperatures. The origin of the nitrogen (i.e. fuel vs. 

combustion air) has led to the use of the terms “thermal” NOX and “fuel” NOX when describing NOX

emissions. Thermal NOX emissions are produced when elemental nitrogen in the combustion air is 

exposed to a high temperature zone and oxidized. Fuel NOX emissions are created during the rapid 

oxidation of nitrogen compounds contained in the fuel. 

Nitrogen oxide (NO) is typically the predominant form of NOX from fossil fuel combustion. Nitrogen 

dioxide (NO2) makes up the remainder of the NOX. The formation of NOX compounds in utility 

boilers is sensitive to the method of firing. In a wall-fired boiler, such as SN-01, burners are mounted 

in the boiler walls, producing discrete flames in the furnace. In tangentially-fired boilers, a single 

rotating flame is created in the center of the furnace, rather than the discrete flames produced by 

burners in the wall-fired boilers. Tangentially fired boilers typically have lower uncontrolled NOX

emissions than wall-fired boilers. Therefore baseline NOX emission rates can vary significantly from 

plant to plant due to method of firing and also several other factors. 

Step 1 of the BART determination is the identification of all available retrofit NOX control 

technologies. The available retrofit NOX control technologies are summarized in Table 6-1 for 

SN-01. 

NOX emissions controls, as listed in Table 6-1, can be categorized as combustion or post-combustion 

controls. Combustion controls, including flue gas recirculation (FGR), overfire air (OFA), and Low 

NOX Burners (LNB), reduce the peak flame temperature and excess air in the furnace which 

minimizes NOX formation. Post-combustion controls, such as selective catalytic reduction (SCR) and 

selective non-catalytic reduction (SNCR) convert NOX in the flue gas to molecular nitrogen and 

water. 

TABLE 6-1. AVAILABLE NOX CONTROL TECHNOLOGIES FOR SN-01 

NOX Control Technologies 

Combustion Controls 

Flue Gas Recirculation (FGR) 

Overfire Air (OFA) 

Low NOX Burners (LNB) 

Post-Combustion Controls Selective Catalytic Reduction (SCR) 

Selective Non-Catalytic Reduction (SNCR) 

6.3 ELIMINATE TECHNICALLY INFEASIBLE NOX CONTROL TECHNOLOGIES

Step 2 of the BART determination is to eliminate technically infeasible NOX control technologies that 

were identified in Step 1. Control ranges were developed using a combination of literature control 

ranges and efficiencies. Because many controlled emission levels from literature were higher than the 

baseline NOX rate at SN-01, vendor estimates were also used to assist in developing the expected 

emission rates from the known relationships between the control options. 
 

Southwestern Electric Power Company 6-3 Trinity Consultants 

BART Analysis – Flint Creek 

6.3.1 COMBUSTION CONTROLS

6.3.1.1 FLUE GAS RECIRCULATION (FGR) 

FGR uses flue gas as an inert material to reduce flame temperatures. In a 

typical flue gas recirculation system, flue gas is collected from the combustion 

chamber or stack and returned to the burner via a duct and blower. The 

addition of flue gas reduces the oxygen content of the “combustion air” (air + 

flue gas) in the burner. The lower oxygen level in the combustion zone reduces 

flame temperatures; which in turn reduces thermal NOX formation. When 

operated without additional controls, the NOX control range for coal fired 

boilers with FGR is approximately 5-25% for coal fired boilers, or 0.23-0.29 

lb/MMBtu from SN-01.29 This control is a technically feasible option for the 

control of NOX from SN-01. 

6.3.1.2 OVERFIRE AIR (OFA) 

OFA diverts a portion of the total combustion air from the burners and injects it 

through separate air ports above the top level of burners. Staging of the 

combustion air creates an initial fuel-rich combustion zone with a lower peak 

flame temperature. This reduces the formation of thermal NOX by lowering 

combustion temperature and limiting the availability of oxygen in the 

combustion zone where NOX is most likely to be formed. OFA as a single NOX

control technique results in estimated NOX emissions for coal fired boilers of 

approximately 10%, or 0.28-0.29 lb/MMBtu from SN-01.30 This control is a 

technically feasible option for the control of NOX from SN-01. 

6.3.1.3 LOW NOX BURNERS

LNB technology utilizes advanced burner design to reduce NOX formation 

through the restriction of oxygen, lowering of flame temperature, and/or 

reduced residence time. NOX creation rates typically peak at oxygen levels of 

five to seven percent.31 LNB is a staged combustion process that is designed to 

split fuel combustion into two zones. In the primary zone, NOX formation is 

limited by one of two methods. Under staged fuel-rich conditions, low oxygen 

levels limit flame temperatures resulting in less NOX formation. The primary 

zone is then followed by a secondary zone in which the incomplete combustion 

products formed in the primary zone act as reducing agents. Alternatively, 

under staged fuel-lean conditions, excess air will reduce flame temperature to 

reduce NOx formation. In the secondary zone, combustion products formed in 

the primary zone act to lower the local oxygen concentration, resulting in a 

decrease in NOx formation. 

 29 “Controlling Nitrogen Oxides Under the Clean Air Act: A Menu of Options.” Utility Boiler section. July 

1994. 

30 Ibid. 

31 http://www.energysolutionscenter.org/boilerburner/Workshop/RCTCombustion.htm.
 

Southwestern Electric Power Company 6-4 Trinity Consultants 

BART Analysis – Flint Creek 

The estimated NOX control range for LNBs on coal boilers is 0.20-0.26 

lb/MMBtu.32 When combined with OFA, the estimated NOX control range on 

is 0.18-0.24 lb/MMBtu.33 LNB systems are technically feasible for the control 

of NOx from SN-01. 

6.3.2 POST COM BUSTION CONTROLS

6.3.2.1 SELECTIVE CATALYTIC REDUCTION

SCR refers to the process in which NOX is reduced by ammonia over a 

heterogeneous catalyst in the presence of oxygen. The process is termed 

selective because the ammonia preferentially reacts with NOX rather than 

oxygen, although the oxygen enhances the reaction and is a necessary 

component of the process. The overall reactions are: 

4NO + 4NH3 + O2  4N2 + 6H2O 

2NO2 + 4NH3 + O2  3N2 + 6H2O 

The SCR process requires a reactor, a catalyst, and an ammonia storage and 

injection system. The effectiveness of an SCR system is dependent on a variety 

of factors, including the inlet NOX concentration, the exhaust temperature, the 

ammonia injection rate, and the type of catalyst. The estimated NOX control for 

SCR on coal fired boilers is 80-90%, and is consistent with vendor estimates of 

0.067 lb/MMBtu at SN-01, resulting in an 80% control efficiency.34 Control 

efficiencies of 80-90% depend on the design of the boiler as well as the starting 

baseline emissions. The vendor was able to provide an estimate of control as 

an outlet emission level of 0.067 lb/MMBtu, a low emission level. A 90% 

percent reduction would result in an outlet emission rate of 0.03 lb/MMBtu and 

has not been guaranteed by a vendor. This control is a technically feasible 

option for the control of NOX from SN-01. 

6.3.2.2 SELECTIVE NON-CATALYTIC REDUCTION

In SNCR systems, a reagent is injected into the flue gas in the furnace within an 

appropriate temperature window. The NOX and reagent (ammonia or urea) 

react to form nitrogen and water. A typical SNCR system consists of reagent 

storage, multi-level reagent-injection equipment, and associated control 

instrumentation. The SNCR reagent storage and handling systems are similar 

to those for SCR systems. However, both ammonia and urea SNCR processes 

require three to four times as much reagent as SCR systems to achieve similar 

NOX reductions. The estimated NOX control range for SNCR for coal fired 

boilers is 0.18-0.27 lb/MMBtu.35 This control is a technically feasible option 

for the control of NOX from SN-01. 

 32 “Controlling Nitrogen Oxides Under the Clean Air Act: A Menu of Options.” Utility Boiler section. July 

1994. 

33 Ibid. 

34 Ibid. 

35 Ibid. 
 

Southwestern Electric Power Company 6-5 Trinity Consultants 

BART Analysis – Flint Creek 

6.4 RANK OF TECHNICALLY FEASIBLE NOX CONTROL OPTIONS BY 

EFFECTIVENESS

The third step in the BART analysis is to rank the technically feasible options according to 

effectiveness. Table 6-2 provides a ranking of the control levels for the controls listed in the 

previous section for SN-01. 

TABLE 6-2. CONTROL EFFECTIVENESS OF TECHNICALLY FEASIBLE NOX CONTROL 

TECHNOLOGIES

Control Technology 

Estimated Controlled 

Level for SN-01 

(lb/MMBtu) 36

SCR 0.067 

LNB/OFA + SNCR 0.18-0.23 37

LNB/OFA 0.18-0.24 

SNCR 0.18-0.27 

FGR 0.23-0.29 

LNB 0.20-0.26 

OFA 0.28-0.29 

With the exception of the control level for SCR, the control levels in Table 6-2 are presented as 

ranges. This is due to the fact that the specific level of control that is achievable for SN-01 based on 

the application of the controls listed in Table 6-2 is unknown. Based on several discussions between 

AEP Flint Creek and the Babcock and Wilcox Company, it is believed that combustion controls such 

as LNB in combination with OFA will achieve a NOX level of approximately 0.23 lb/MMBtu for SN01. EPA established presumptive SO2 and NOX controls for coal-fired EGUs in the BART rule. For 

dry-bottom wall-fired EGUs, the presumptive NOX limit is 0.23 lb/MMBtu.38 The presumptive 

BART emission rate was modeled for this source by CENRAP. Although 0.23 lb/MMBtu is the 

presumptive limit for a unit like SN-01, the presumptive limit was not automatically assumed the 

floor for combustion control on SN-01. Rather, experience with similar boilers and vendor 

discussions have led the selection of this emission level. Current NOX emissions from SN-01 are 

approximately 0.31 lb/MMBtu. Further, it is believed that SCR will achieve a NOX level of 

approximately 0.067 lb/MMBtu and LNB/OFA + SNCR will achieve a level of 0.201 lb/MMBtu or 

10-20% better control than from LNB/OFA alone. Vendor estimates for LNB/OFA + SNCR were 

not available at the time of this analysis, and obtaining vendor estimates would add significantly to 

the timing of this analysis submittal. 

6.5 EVALUATION OF IMPACTS FOR FEASIBLE NOX CONTROLS 

Step four for the BART analysis is the impact analysis. The BART determination guidelines list four 

factors to be considered in the impact analysis: 

 36 Ibid. 

37 “Preferred and Alternative Methods for Estimating Air Emissions from Boilers.” Volume II: Chapter 2. 

January 2001. 

38 Ibid. 
 

Southwestern Electric Power Company 6-6 Trinity Consultants 

BART Analysis – Flint Creek 

▲ Cost of compliance 

▲ Energy impacts 

▲ Non-air quality impacts; and 

▲ The remaining useful life of the source 

6.5.1 COST OF COMPLIANCE

The capital costs, operating costs, and cost effectiveness of LNB/OFA, LNB/OFA + SNCR 

and SCR were estimated for the cost analysis. 

Control Costs 

The capital and operating costs of the controls that were used in the cost effectiveness 

calculations were estimated based on vendor estimates and published calculation methods. 

The EPA Air Pollution Control Cost Manual was followed to the extent possible and was 

supplemented with vendor and site-specific information where available. The capital 

costs were annualized over a 15-year period for LNB/OFA and over a 20-year period for 

both SCR and SNCR, and then added to the annual operating costs to obtain the total 

annualized costs. The details of the capital and operating cost estimates are provided in 

Appendix B of this report. 

Annual Tons Reduced 

The annual tons reduced that were used in the cost effectiveness calculations were 

determined by subtracting the estimated controlled annual emission rate from the baseline 

annual emission rate. 

The baseline annual emission rate is the average rate as reported by AEP in the 2001-2003 

air emission inventories. The controlled annual emission rate is based on the lb/MMBtu 

level believed to be achievable from the control technology multiplied by the baseline heat 

input to the boiler in MMBtu/yr. The baseline heat input is based on the 2001-2003 

average daily heat input for SN-01 as determined from the EPA’s Clean Air Markets 

Database (CAMD), divided by 24 hours in a day times an estimated 7,752 hours per year, 

the average number of operating hours from 2001-2003. 

 

Cost Effectiveness 

The cost effectiveness in dollars per ton of NOX reduced was determined by dividing the 

annualized cost of control by the annual tons reduced. An incremental cost analyses was 

also performed to show the incremental increase in costs between SCR and an LNB/OFA 

system, as well as between LNB/OFA + SNCR and LNB/OFA. The costs effectiveness 

analysis is summarized in Table 6-3. 

In the BART guidelines, EPA calculated that for all types of boilers other than cyclone 

boilers, combustion control technology is generally more cost-effective than postcombustion controls. EPA estimates that approximately 75 percent of the BART units 

(non-cyclone) could meet the presumptive NOX limits at a cost of $100 to $1,000 per ton of 
 

Southwestern Electric Power Company 6-7 Trinity Consultants 

BART Analysis – Flint Creek 

NOX removed based on the use of combustion control technology.39 For the units that 

could not meet the presumptive limits using combustion control technology, EPA estimates 

that almost all of these sources could meet the presumptive limits using advanced 

combustion controls. The EPA estimates that the costs of such controls are usually less 

than $1,500 per ton of NOX removed.40 

Table 6-3 indicates that the cost effectiveness of LNB/OFA at a NOX rate of 0.23 

lb/MMBtu is $2,579 per ton of NOX removed. Table 6-3 also indicates that the costs for 

LNB/OFA/SNCR for SN-01 is approximately $3,600/ton of NOX removed and SCR for 

SN-01 is more than $4,300 per ton of NOX removed. Additionally, the incremental cost of 

the LNB/OFA/SNCR over the LNB/OFA system is greater than $5,200 per ton of NOX

removed for SN-01. The incremental cost of SCR over the LNB/OFA system is nearly 

$4,800/ton of NOX removed for SN-01. 

The cost effectiveness in dollars per deciview of visibility improvement attributable to the 

each NOX control technology was also determined. Additional details on the visibility 

improvement analysis are provided below. The cost of LNB/OFA is approximately $284 

million/dv across the Class I areas, as seen in Table 6-4. The cost of LNB/OFA plus 

SNCR is approximately $519 million/dv across the Class I areas, as seen in Table 6-5. 

Table 6-6 shows that control of NOX from SCR results in a cost of approximately $939 

million/dv across the Class I areas. So a review of cost effectiveness on a dollars per 

deciview basis reveals that both post-combustion control options are prohibitively 

expensive relative to the LNB/OFA control option.

 39 “Regional Haze Regulations and Guidelines for Best Available Retrofit Technology (BART Determinations; 

Final Rule.” CFR Vol. 77, No. 128. Wednesday, July 6, 2005, Rules and Regulations. Pages 39134-39135. 

40 Ibid. 
Southwestern Electric Power Company 6-8 

BART Analysis – Flint Creek 

TABLE 6-3.

SUMMARY OF 

COST 

EFFECTIVENESS FOR SN-01 NO

X

CONTROLS

Baseline Emission 

Rate

Controlled 

Emission 

Level

Annual Heat 

Input4

Controlled 

Emission 

Rate

NOx 

Reduced Capital Cost

Annual 

Capital Cost

Annual 

Fixed O&M

Annualized 

Variable 

O&M

Total 

Annual 

Cost

(tpy) (lb/MMBtu) (MMBtu/yr) (tpy) (ton/yr) ($) ($/yr) ($/yr) ($/yr) ($/yr) 

LNB/OFA1 5,120.27 0.23 37,344,776 4294.65 825.62 16,000,000 1,756,714 240,000 132,364 2,129,078 

LNB/OFA/SNCR2 5,120.27 0.20 37,344,776 3771.82 1348.44 23,124,235 2,429,191 240,000 2,183,048 4,852,239 SCR3 5,120.27 0.07 37,344,776 1251.05 3869.22 121,440,000 11,463,077 1,560,000 3,700,000 16,723,077 

3 SCR Cost information: Please refer to Appendix B.1 LNB Cost information: Please refer to Appendix B.2 SNCR Cost information: Please refer to Appendix B.4 Baseline heat input was determined from CAMD, 2001-2003, average daily heat inputs times the average number of operating hours from 2001-2003 divided by 24 hours 
Southwestern Electric Power Company 6-9 

BART Analysis – Flint Creek 

TABLE 6-4.

DOLLAR PER 

DECIVIEW 

COST 

EFFECTIVENESS FOR SN-01 NO

X

CONTROL 

USING LNB/

Caney Creek 0.993 0.924 0.069 2,129,078 Hercules-Glades 0.734 0.683 0.051 2,129,078 Mingo 0.653 0.639 0.014 2,129,078 Upper Buffalo 1.066 1.03 0.036 2,129,078 

Class I Area

LNB/OFA Controlled 98th 

Percentile 

∆dv 

Baseline 98th 

Percentile 

∆dv

Improvement in 98th 

Percentile 

∆dv

Total Annual 

LNB/OFA Cost

TABLE 6-5.

DOLLAR PER 

DECIVIEW 

COST 

EFFECTIVENESS FOR SN-01 NO

X

CONTROL 

USING LNB/OFA

P

Caney Creek 0.993 0.9 0.093 4,852,239 Hercules-Glades 0.734 0.676 0.058 4,852,239 Mingo 0.653 0.634 0.019 4,852,239 Upper Buffalo 1.066 1.028 0.038 4,852,239 

Class I Area

LNB/OFA/SNCR 98th 

Percentile 

∆dv 

Baseline 98th 

Percentile 

∆dv

Improvement in 98th 

Percentile 

∆dv

Total Annual 

LNB/OFA + SNCR 

Cost

TABLE 6-6.

DOLLAR PER 

DECIVIEW 

COST 

EFFECTIVENESS FOR SN-01 NO

X

CONTROL 

USING SC

Caney Creek 0.993 0.784 0.209 16,723,077 Hercules-Glades 0.734 0.627 0.107 16,723,077 Mingo 0.653 0.611 0.042 16,723,077 Upper Buffalo 1.066 1.011 0.055 16,723,077 

Class I Area

SCR Controlled 98th Percentile 

∆dv 

Baseline 98th 

Percentile 

∆dv

Improvement in 98th 

Percentile 

∆dv

Total Annual SCR 

Cost
 

Southwestern Electric Power Company 6-10 Trinity Consultants 

BART Analysis – Flint Creek 

6.5.2 ENERGY IMPACTS & NON-AIR IMPACTS

SCR systems require electricity to operate the ancillary equipment. The need for electricity 

to help power some of the ancillary equipment creates a demand for energy that currently 

does not exist. 

SCR and SNCR can potentially cause significant environmental impacts related to the 

storage of ammonia. The storage of aqueous ammonia above 10,000 lbs is regulated by a 

risk management program (RMP), since the accidental release of ammonia has the 

potential to cause serious injury and death to persons in the vicinity of the release. SCR 

and SNCR will likely also cause the release of unreacted ammonia to the atmosphere. 

This is referred to as ammonia slip. Ammonia slip from SCR and SNCR systems occurs 

either from ammonia injection at temperatures too low for effective reaction with NOx, 

leading to an excess of unreacted ammonia, or from over-injection of reagent leading to 

uneven distribution; which also leads to an excess of unreacted ammonia. Ammonia 

released from SCR and SNCR systems will react with sulfates and nitrates in the 

atmosphere to form ammonium sulfate and ammonium nitrate. Together, ammonium 

sulfate and ammonium nitrate are the predominant sources of regional haze. 

6.5.3 REMAINING USEFUL LIFE

The remaining useful life of SN-01 does not impact the annualized capital costs of 

potential controls because the useful life of the boiler is anticipated to be at least as long as 

the capital cost recovery period, which is 15 years for LNB/OFA and 20 years for SNCR 

and SCR. 

6.6 EVALUATION OF VISIBILITY IMPACT OF FEASIBLE NOX CONTROLS 

A final impact analysis was conducted to assess the visibility improvement for existing emission rates 

when compared to the emission rates associated with LNB/OFA, LNB/OFA/SNCR and SCR systems. 

Section 4 of this report documented the existing visibility impairment attributable to SN-01. In order 

to assess the visibility improvement associated with LNB/OFA, SCR and SNCR systems, the NOX

emission rates associated with both LNB and SCR systems were modeled using CALPUFF. The 

controlled emission level associated with SCR systems is 0.067 lb/MMBtu for SN-01. The controlled 

emission level associated with the LNB/OFA system is 0.23 lb/MMBtu, and for LNB/OFA/SNCR is 

0.21 lb/MMBtu. These levels were multiplied by the maximum heat input to derive hourly the hourly 

emission rates used in the modeling. 

Tables 6-7 through 6-9 summarize the NOX emission rates that were modeled to reflect the LNB/OFA 

SCR and LNB/OFA/SNCR systems, respectively. The emission rates for the other pollutants shown 

in Tables 6-7 through 6-9 are the same as in the baseline modeling. 
 

Southwestern Electric Power Company 6-11 Trinity Consultants 

BART Analysis – Flint Creek 

TABLE 6-7. SUMMARY OF EMISSION RATES MODELED TO REFLECT LNB/OFA FOR NOX

CONTROL

 

SO2

(lb/hr) 

SO4 

(lb/hr) 

NOX

(lb/hr) 

PMC 

(lb/hr) 

PMF 

(lb/hr) 

SOA 

(lb/hr) 

EC 

(lb/hr) 

PM10, total 

(lb/hr) 

SN-01 4,728.4 111.2 1,454.5 29.8 22.9 27.8 0.9 192.5 

TABLE 6-8. SUMMARY OF EMISSION RATES MODELED TO REFLECT SCR FOR NOX CONTROL

 

SO2

(lb/hr) 

SO4 

(lb/hr) 

NOX

(lb/hr) 

PMC 

(lb/hr) 

PMF 

(lb/hr) 

SOA 

(lb/hr) 

EC 

(lb/hr) 

PM10, total 

(lb/hr) 

SN-01 4,728.4 111.2 423.7 29.8 22.9 27.8 0.9 192.5 

TABLE 6-9. SUMMARY OF EMISSION RATES MODELED TO REFLECT LNB/OFA + SNCR FOR NOX

CONTROL

 

SO2

(lb/hr) 

SO4 

(lb/hr) 

NOX 

(lb/hr) 

PMC 

(lb/hr) 

PMF 

(lb/hr) 

SOA 

(lb/hr) 

EC 

(lb/hr) 

PM10, total 

(lb/hr) 

SN-01 4,728.4 111.2 1,277.74 29.8 22.9 27.8 0.9 192.5 

Table 6-10 provides a comparison of the existing visibility impairment and the visibility impairment 

associated with the addition of NOX controls on SN-01 in all affected Class I areas, including the 

maximum modeled visibility impact, 98th percentile modeled visibility impact, and the number of 

days with a modeled visibility impact greater than 0.5 Δdv. 
Southwestern Electric Power Company 6-12 

BART Analysis – Flint Creek 

TABLE 6-10.

SUMMARY OF 

VISIBILITY IMPROVEMENT 

ASSOCIATED WITH NO

X

CONTROL 

SYSTEM ON SN-0

Caney Creek Wilderness Upper Buffalo Wilderness Hercules Glades Wilderness 

Maximum Impact (Δdv) 

98% Impact (Δdv) 

 # Days > 0.5 Δdv 

Maximum Impact (Δdv) 

98% Impact (Δdv) 

 # Days > 0.5 Δdv 

Maximum Impact (Δdv) 

98% Impact (Δdv) 

 # Days > 0.5 Δdv 

Existing Emission Rate 

1.408 0.993 55 2.585 1.066 76 2.186 0.734 60 

LNB/OFA 1.286 0.924 46 2.294 1.030 68 2.023 0.683 51 

Post Control Improvement 

0.122 0.069 9 0.291 0.036 8 0.163 0.051 9 

SCR 1.105 0.784 33 1.816 1.011 55 1.676 0.627 43 

Improvement over LNB/OFA 

0.181 0.140 13 0.478 0.019 13 0.347 0.056 8 

LNB/OFA+ SNCR 1.255 0.900 45 2.188 1.028 67 1.964 0.676 50 

Improvement over LNB/OFA 

0.031 0.024 1 0.106 0.002 1 0.059 0.007 1 

Note: The visibility improvement shown in the table has been calculated from baseline and controlled impacts that include more decimal places than w

Due to rounding of the baseline and controlled impacts shown in the table, the visibility improvement calculated from the baseline and controlled impabe slightly different than the visibility improvement reflected in the table.
 

Southwestern Electric Power Company 6-13 Trinity Consultants 

BART Analysis – Flint Creek 

The operation of an LNB/OFA system results in an estimated 0.01 to 0.07 Δdv improvement (2 to 7 

percent) (98th percentile basis) of visibility impairment attributable to SN-01 at the modeled Class I 

areas. Further, the operation of SCR systems results in an estimated 0.02 to 0.14 Δdv incremental 

improvement over LNB/OFA alone, while LNB/OFA + SNCR results in an estimated 0.002 to 0.02 

Δdv incremental improvement over LNB/OFA alone. 

6.7 PROPOSED BART FOR NOX 

If CSAPR is upheld and implemented in Arkansas, SWEPCO will rely on CSAPR to satisfy its 

regional haze obligations at SN-01. If CSAPR is vacated, SWEPCO should be entitled to rely on 

EPA’s prior determination that CAIR provides greater reductions than BART, and satisfy its 

obligations by continuing to comply with CAIR. 

If a full evaluation of BART is required, the cost-effectiveness of the control options and the limited 

incremental improvement in visibility in the affected Class I areas do not justify the installation of 

SCR or SNCR. SWEPCO proposes a BART emission rate of 0.23 lb/MMBtu calculated as a 30-day 

rolling average for each boiler operating day, achievable through use of LNB/OFA. The visibility 

improvement attributable to SN-01 through the use of LNB/OFA ranges from 2.1% to 6.9% across 

the affected Class I areas. This level of improvement is achievable at a cost effectiveness of 

approximately $2,730 per ton of NOX removed. Although LNB/OFA plus SNCR adds a slight 

visibility improvement over LNB/OFA alone, the small improvement does not justify the incremental 

cost of over $5,209 per ton of NOX removed. The incremental cost for SCR at SN-01 is nearly 

$4,740 per ton of NOX removed, and is an excessive cost to be considered BART. In addition, the 

adverse environmental impacts from the use of SCR, including an increased demand for electricity 

and the potential for ammonia slip, which could create haze, outweigh the limited, imperceptible 

improvements in visibility associated with its use at SN-01. 
 

Southwestern Electric Power Company 7-1 Trinity Consultants 

BART Analysis – Flint Creek 

7. PM10 BART EVALUATION

EPA’s Approval and Promulgation of Implementation Plans published March 12, 2012, determined 

that the currently installed ESP is BART for PM10 for SN-01. As such, no further PM10 analysis has 

been conducted. 
 

Southwestern Electric Power Company Trinity Consultants 

BART Analysis – Flint Creek 

APPENDIX A 

 SO2CONTROL COST CALCULATIONS
Capital Costs1

NID FGD + FF 243,881,264 $ 

NID By-Product Handling 38,792,582 $ 

Balance of Plant (BOP) Construction Total 59,656,085 $ 

Contingency & Allocations 88,119,783 $ 

Total Capital Investment (TCI) 430,449,714 $ 

Annual Costs

Variable O&M2 $/year $6,620,000

Auxiliary Power2 $/year $4,186,080

Total Fixed O&M2 $/year $4,210,000

 = [ I x (1+i)^a]/[(1+i)^a - 1], where I = 

interest rate, a = equipment life 0.08

a. Equipment CRF, 30-yr life, 7% interest

Annualized Capital Cost = Equipment CRF x TCI $34,688,394

Total Annual Costs ($/yr) $49,704,474

2 Total O&M Costs ($/year) from AEP based on information gathered from a detailed estimate developed 

for the simailar study at another AEP facility (Big Sandy FGD Project), scaled to account for the slightly 

smaller unit size at Flint Creek.

NIDS Capital and O&M Cost Estimate

Capital recovery factor

1

 From "FC DFGD & FF Budgetary Cost Estimate Breakdown (Class 4)."
Capital Costs1

WFGD + FF 444,439,524 $ 

Waste Water Treatment 22,685,874 $ 

Boiler Modifications 3,816,274 $ 

Balance of Plant (BOP) Construction Total 15,708,422 $ 

Contingency & Allocations 46,599,533 $ 

Total Capital Investment (TCI) 533,249,627 $ 

Annual Costs

Variable O&M2 $/year $5,360,000

Auxiliary Power2 $/year $8,023,320

Total Fixed O&M2 $/year $4,730,000

 = [ I x (1+i)^a]/[(1+i)^a - 1], where I = 

interest rate, a = equipment life 0.08

a. Equipment CRF, 30-yr life, 7% interest

Annualized Capital Cost = Equipment CRF x TCI $42,972,670

Total Annual Costs ($/yr) $61,085,990

2 Total O&M Costs ($/year) from AEP based on information gathering from a detailed estimate developed 

for the simailar study at another AEP facility (Big Sandy FGD Project), scaled to account for the slightly 

smaller unit size at Flink Creek.

Wet Flue Gas Desulfurization (WFGD) Capital and O&M Cost Estimate

Capital recovery factor

1

 From "Budgetary Cost Estimate Breakdown for FC WFGD & FF."
 

Southwestern Electric Power Company Trinity Consultants 

BART Analysis – Flint Creek 

APPENDIX B 

NOX CONTROL COST CALCULATIONS
Capital Costs Total Direct Capital

Technology

LNB-OFA

Material Capital Costs1

Total Capital Cost Plus Installation $16,000,000

Annual Costs2

Parameters/Costs Equation Unit 1

Boiler design capacity, mmBtu/hr (C) C 6324

Annual operating hours, hr/yr (H) H = average from 2001-2003 7752

Capital recovery factor

= [ I x (1+i)^a]/[(1+i)^a - 1], where I = interest rate, a = 

equipment life 0.11

a. Equipment CRF, 15-yr life, 7% interest

Direct Annual Operating Costs $/yr

Variable O&M Costs

=(0.027 mills/kW-hr/1000) x (1 kW-hr/10,000 Btu) x H x C x 

10^6 Btu/mmBtu $132,364

Indirect Annual Costs, $/yr

1. Fixed O&M Costs (1.5% of capital cost) = 0.015 x TCI $240,000

2. Annualized capital cost = Equipment CRF x TCI $1,756,714

Total Annual Costs ($/yr) $2,129,078

LNB/OFA Capital and O&M Cost Estimate

1

 Public Service Commission Docket 12-008-U.

2

 Annual cost calculation methods for variable costs and fixed costs from Eastern Research Group "Analysis of Combustion Controls for Reducing NOx 

Emissions from Coal-fired EGUs in the WRAP Region" September 6, 2005. Section 4.3.1 and Appendix D. 

Note: The variable rate used for variable O&M costs was 0.027 mills/kW-hr. This is the rate listed in Appendix D
Capital Costs Total Direct Capital

Technology

SCR

Installed Capital Cost1 $121,440,000

Annual Costs

Variable

Urea1 $2,200,000

Catalyst replacement (per 

year)1 $1,500,000

Total Variable O&M1 $3,700,000

Fixed

Operating Labor Cost2 $530,000

Maintenance Labor3 $530,000

Maintenance Material1 $500,000

Total Fixed O&M1 $1,560,000

= [ I x (1+i)^a]/[(1+i)^a - 1], where I 

= interest rate, a = equipment life 0.09

a. Equipment CRF, 20-yr life, 7% 

interest

Annualized capital cost = Equipment CRF x TCI $11,463,077

Total Annual Costs ($/yr) $16,723,077

2

 Annual estimates provided by AEP based on 1 person per shift for 5 shifts.

3

 Annual estimates provided by AEP based on 1 person per shift for 5 shifts.

Capital recovery factor

SCR Capital and O&M Cost Estimate

1

 All capital and O&M cost estimates provided by AEP are based on engineering estimates. The engineering 

estimates were informed by AEP's experience with SCR installations at other plants owned by AEP
Capital Costs

Technology

SNCR

Parameters/Costs Equation Unit 1

Boiler design capacity, mmBtu/hr (QB) QB 6324

Total operating time (top, hrs/yr) top = CFtotal × 8760 hrs/yr 7752

Total Capacity Factor (CFtotal) CFtotal = CFplant × CFSNCR 0.92

Plant Capacity Factor (CFplant

)

2 0.92

SNCR Capacity Factor (CFSCNR)

3 CFSNCR = tSNCR/365 1

Assumed NOx removal efficiency (ηNOx)

4 35%

Uncontrolled NOx rate (NOxin,

 lb/MMBtu)5 0.33

Electricity Cost (Costelect, $/kwh)6 $0.05

Water Cost (Costwater, $/gal)7 $0.00362

Coal Cost (Costcoal, $/MMBtu)8 $2.50

Coal HHV (Btu/lb)9 9,000

Cost of Ash Disposal (Cash, $/ton)10 $9.0

Capital recovery factor (CRF) CRF = [ I x (1+i)^a]/[(1+i)^a - 1], where I = interest rate, a = equipment life 0.09

a. Equipment CRF, 20-yr life, 7% interest

Cost Index10

a. 2011 Cost Index 585

b. 1998 Cost Index 389.5

Capital Costs 

Direct Capital Cost (A) DC ($) = ($950/MMBtu) × QB × ((2375 MMBtu/hr/QB)^0.577) × (0.66 + 0.85 ηNOx) × (CI2011/CI1998) $5,007,199

Indirect Installation Costs ($)

General Facilities 0.05 × A $250,360

Engineering and Home Office Fees 0.10 × A $500,720

Process Contingency 0.05 × A $250,360

Total Indirect Installation Costs (B) = General Facilities Cost + Engineering and Home Office Fees + Process Contingency $1,001,440

Other Installation Costs ($)

Project Contingency (C) C = 0.15 × (A + B) $901,296

Total Plant Cost (D) D = A + B + C $6,909,934

Allowance for Funds During Construction (E) E = 0 (Assumed for SNCR) $0

Royalty Allowance (F) F = 0 (Assumed for SNCR) $0

Preproduction Cost (G) G = 0.02 × (D + E) $138,199

Inventory Capital (H)11 H = Volreagent

 (gal) × Costreagent ($/gal) $76,102

Costreag, 50% Urea solution ($/gal)12 1.54

Volume of Reagent Tank (Volreagent

 (gal)) Volreagent (gal) = qsol x days of reagent supply × 24 hr/day 49,417

Urea solution volumetric flow rate (qsol

, gal/hr)13 qsol = (msol x 7.481 gal/ft3)/ρreagent 147.07

Mass flow rate of urea solution (msol

, lb/hr)14 msol = mreagent/Cureasol 1,395.84

Mass flow rate of reagent (mreagent

, lb/hr)15 mreagent = (NOxin x QB x ηNOx × NSR x Mreagent)/(MNOx x SRT) 697.92

Normalized Stoichiometric Ratio (NSR) NSR = ([2 × NOxin + 0.7] × ηNOx)/NOxin 1.43

Initial Catalyst and Chemicals (I) I = 0 (Assumed for SNCR due to no catalyst) $0

Total Capital Investment (TCI) (Capital Cost) TCI = D + E + F + G + H + I $7,124,235

Annual Costs ($)

Annual Maintenance Cost (J) J = 0.015 × TCI $106,864

Annual Reagent Cost (K) K = qsol

 × Costreag × top $1,755,781

Annual Electricity Cost (L) L = P × Costelect × top $58,064

Power (P, kW) P = (0.47 × NOxin × NSR × QB)/9.5 149.80

Annual Water Cost (M) M = qwater × Costwater × top $18,775

Water flowrate for SNCR system (qwater, gal/hr)16 qwater = (msol

/ρwater) × [(Cureasolstored/Cureasolinj) - 1] 669.06

Annual ΔCoal Cost (N) N = ΔCoal × Costcoal × top $109,558

Additional coal required (ΔCoal, MMBtu/hr)17 ΔCoal = (Hv × mreagent

 × [(1/Cureasolinj) - 1])/106 Btu/MMBtu 5.65

Annual ΔAsh Cost (O) O = (ΔAsh × Costash × top)/2000 lb/ton $1,643

Additional ash generated (ΔAsh , lb/hr)18 ΔAsh = (ΔCoal × ashproduct × 106

 Btu/MMBtu)/HHV 47.11

Direct Annual Costs (DAC)/Variable O&M DAC = J + K + L + M + N + O $2,050,684

Indirect Annual Costs (IDAC)/Annualized Capital Cost IDAC = CFR × TCI $672,477

Total Annualized Costs (TAC) TAC = DAC + IDAC $2,723,162

Selective Non-Catalytic Reduction Capital and O&M Cost Estimate 1
1

 All SNCR costing equations from EPA Air Pollution Control Cost Manual (APCCM), 6th Edition (January 2002)

2 Plant capacity factor from plant data

3

 tSCNR assumed to be 365 days

4

 ηNOx (NOx removal efficiency) assumed to be 33% for SNCR alone

5 24-hr NOx rate 46,680 lbs/day - from Clean Air Markets Database, with a heat input of 6324 MMBtu/hr

6

 Electricity cost form Arkansas Industrial Energy Clearinghouse, http://www.arkansasiec.org/newsmanager/templates/?a=71&z=1

7

 Water cost estimate from Bentonville, AR commercial rate of $0.00362/gal, http://www.bentonvillear.com/utbc_rates.html

8 Cost of coal from Lazard's 2009 Levelized Cost of Energy Analysis (LCOE)

10 Cost of ash disposal from BART Analysis for NCS Unit 1, Appendix A

11 From Chemical Engineering Plant Cost Index (CEPCI) 

12 Cost for urea stored on site, i.e., the first fill of the reagent tanks. 

14 ρreagent

 = 71.0 lb/ft3

15 Cureasol

 = urea solution concentration = 50%

18 Approximate heat of vaporization of water at 310°F, Hv = 900 Btu/lb From EPA APCCM, 2002

19 Ashproduct is the fraction of ash produced as a byproduct of burning a given type of coal. Assumed ashproduct = 0.075 from EPA APCCM, 2002 for subbituminous 

coal.

9

 Coal used at AEP Flint Creek originates from Powder River Basin near Gillette, WY and is considered to be subbituminous (source: 

http://www.aecc.com/about/generation-facilities/)

HHV for subbituminous coal ranges from 8,000 - 10,000 Btu/lb (EPA APCCM, 2002). 

Using HHV of 9,000 Btu/lb

13 Five-yr average urea cost = $356.11/metric ton, from http://www.indexmundi.com/commodities/?commodity=urea&months=180

Density of 50% urea solution = 9.5 lb/gal (50% urea solution) based on EPA APCCM, 2002

Equates to $1.54/gal

16 Mreagent = 60.6 g/mol (molecular weight of urea)

 MNOx = 46.01 g/mol (molecular weight of NO2)

 SRT = 2 (ratio of equivalent moles NH3 per mole of urea)

17 Concentration of stored urea, Cureasolstored = 50%

 Concentration of urea injected into SNCR system, Cureasolinj = 10%

 From EPA APCCM, 2002
 

Southwestern Electric Power Company Trinity Consultants 

BART Analysis – Flint Creek 

APPENDIX C 

CALMET PROTOCOL

The meteorological data used in the analyses presented in this report was originally developed in 

2007 and was first used in a BART determination for Oklahoma Gas & Electric. Because the 

development of a set of CALMET/CALPUFF meteorological data is so intensive, this same dataset 

has been used numerous times since 2007 for various other BART projects in EPA Region 6. The 

protocol that accompanied the original development has followed the dataset in each case and is 

doing so here again. 
CALMET DATA PROCESSING PROTOCOL  BART DETERMINATION

OKLAHOMA GAS & ELECTRIC

MUSKOGEE GENERATING STATION

SEMINOLE GENERATING STATION

SOONER GENERATING STATION

Prepared by:

Vern Choquette  Principal Consultant

Eugene Chen, PE  Senior Consultant

Jeremy Townley  Consultant

TRINITY CONSULTANTS

120 East Sheridan

Suite 205

Oklahoma City, OK 73104

(405) 228-3292

January 23, 2008

Project 083701.0004
OG&E i Trinity Consultants

CALMET Processing Protocol 083701.0004

TABLE OF CONTENTS

1. INTRODUCTION.................................................................................................... 1-1

1.1 BEST AVAILABLE RETROFIT TECHNOLOGY RULE BACKGROUND ......................... 1-1

1.2 OBJECTIVE ............................................................................................................ 1-2

1.3 LOCATION OF SOURCES AND RELEVANT CLASS I AREAS...................................... 1-2

2. CALPUFF MODEL SYSTEM ............................................................................... 2-1

2.1 MODEL VERSIONS................................................................................................. 2-1

2.2 MODELING DOMAIN ............................................................................................. 2-1

3. CALMET............................................................................................................ 3-1

3.1 GEOPHYSICAL DATA............................................................................................. 3-1

3.1.1 TERRAIN DATA ...................................................................................................3-1

3.1.2 LAND USE DATA.................................................................................................3-2

3.1.3 COMPILING TERRAIN AND LAND USE DATA.......................................................3-3

3.2 METEOROLOGICAL DATA ..................................................................................... 3-3

3.2.1 MESOSCALE MODEL METEOROLOGICAL DATA .................................................3-3

3.2.2 SURFACE METEOROLOGICAL DATA ...................................................................3-4

3.2.3 UPPER AIR METEOROLOGICAL DATA.................................................................3-5

3.2.4 PRECIPITATION METEOROLOGICAL DATA..........................................................3-6

3.2.5 BUOY METEOROLOGICAL DATA.........................................................................3-7

3.3 CALMET CONTROL PARAMETERS....................................................................... 3-8

3.3.1 VERTICAL METEOROLOGICAL PROFILE..............................................................3-8

3.3.2 INFLUENCES OF OBSERVATIONS .........................................................................3-9

APPENDIX A- METEOROLOGICAL STATIONS

APPENDIX B – SAMPLE CALMET CONTROL FILE (CALPUFF VERSION 5.8)

APPENDIX C – SAMPLE CALMET CONTROL FILE (CALPUFF VERSION 6)
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CALMET Processing Protocol 083701.0004

LIST OF TABLES

TABLE 1-1. BART-ELIGIBLE SOURCES ...............................................................................................1-2

TABLE 1-2. DISTANCE FROM STATION TO SURROUNDING CLASS I AREAS .......................................1-2

TABLE 2-1. CALPUFF MODELING SYSTEM VERSIONS .....................................................................2-1

TABLE 3-1. VERTICAL LAYERS OF THE CALMET METEOROLOGICAL DOMAIN................................3-9

TABLE A-1. LIST OF SURFACE METEOROLOGICAL STATIONS ...........................................................A-1

TABLE A-2. LIST OF UPPER AIR METEOROLOGICAL STATIONS.........................................................A-5

TABLE A-3. LIST OF PRECIPITATION METEOROLOGICAL STATIONS..................................................A-6

TABLE A-4. LIST OF OVER WATER METEOROLOGICAL STATIONS..................................................A-14
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CALMET Processing Protocol 083701.0004

LIST OF FIGURES

FIGURE 1-1. PLOT OF SOURCES AND NEAREST CLASS I AREAS .........................................................1-3

FIGURE 2-1. REFINED METEOROLOGICAL MODELING DOMAIN.........................................................2-2

FIGURE 3-1. PLOT OF LAND ELEVATION USING USGS TERRAIN DATA ............................................3-2

FIGURE 3-2. PLOT OF LAND USE USING USGS LULC DATA.............................................................3-3

FIGURE 3-3. PLOT OF SURFACE STATION LOCATIONS........................................................................3-5

FIGURE 3-4. PLOT OF UPPER AIR STATIONS LOCATIONS ...................................................................3-6

FIGURE 3-5. PLOT OF PRECIPITATION METEOROLOGICAL STATIONS .................................................3-7

FIGURE 3-6. PLOT OF BUOY METEOROLOGICAL STATIONS ................................................................3-8
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CALMET Processing Protocol 083701.0004

1. INTRODUCTION

Oklahoma Gas & Electric (OG&E) owns and operates three electric generating stations near

Muskogee, Oklahoma (Muskogee Generating Station), Seminole, Oklahoma (Seminole Generating 

Station), and Stillwater, Oklahoma (Sooner Generating Station). These generating stations are

considered eligible to be regulated under the U.S. Environmental Protection Agency’s (EPA) Best 

Available Retrofit Technology (BART) provisions of the Regional Haze Rule. This protocol 

describes the proposed methodology for conducting the CALMET data processing for the refined 

CALPUFF BART modeling analysis for OG&E’s Muskogee, Seminole, and Sooner Generating 

Stations. A detailed CALPUFF BART modeling protocol will be submitted in the near future and 

will include a discussion of the CALPUFF parameters as well as the post processing methodologies 

to be used in the refined modeling analysis for each station.

1.1 BEST AVAILABLE RETROFIT TECHNOLOGY RULE BACKGROUND

On July 1, 1999, the U.S. Environmental EPA published the final Regional Haze Rule (RHR). The 

objective of the RHR is to improve visibility in 156 specific areas across with United States, known 

as Class I areas. The Clean Air Act defines Class I areas as certain national parks (over 6000 acres), 

wilderness areas (over 5000 acres), national memorial parks (over 5000 acres), and international 

parks that were in existence on August 7, 1977.

On July 6, 2005, the EPA published amendments to its 1999 RHR, often called the BART rule, which 

included guidance for making source-specific Best Available Retrofit Technology (BART) 

determinations. The BART rule defines BART-eligible sources as sources that meet the following 

criteria: 

(1) Have potential emissions of at least 250 tons per year of a visibility-impairing pollutant,

(2) Began operation between August 7, 1962 and August 7, 1977, and

(3) Are listed as one of the 26 listed source categories in the guidance.

A BART-eligible source is not automatically subject to BART. Rather, BART-eligible sources are 

subject-to-BART if the sources are “reasonably anticipated to cause or contribute to visibility 

impairment in any federal mandatory Class I area.” EPA has determined that sources are reasonably 

anticipated to cause or contribute to visibility impairment if the visibility impacts from a source are 

greater than 0.5 deciviews (dv) when compared against a natural background.

Air quality modeling is the tool that is used to determine a source’s visibility impacts. States have the 

authority to exempt certain BART-eligible sources from installing BART controls if the results of the 

dispersion modeling demonstrate that the source cannot reasonably be anticipated to cause or 

contribute to visibility impairment in a Class I area. Further, states also have the authority to define 

the modeling procedures for conducting modeling related to making BART determinations. 
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CALMET Processing Protocol 083701.0004

1.2 OBJECTIVE

The objective of this document is to provide a protocol summarizing the modeling methods and 

procedures that will be followed to conduct the CALMET data processing necessary to complete a

refined CALPUFF modeling analysis for the OG&E generating stations discussed above. The 

modeling methods and procedures contained in this protocol and the CALPUFF protocol yet to be 

submitted will be used to determine appropriate controls for OG&E’s BART-eligible sources that can 

reasonably be anticipated to reduce the sources’ effects on or contribution to visibility impairment in 

the surrounding Class I areas. It is OG&E’s intent to determine a combination of emissions controls 

that will reduce the impact of each generating station to a degree that the 98th percentile of the 

visibility impact predicted by the model due to all the BART eligible sources at each station 

collectively is below EPA’s recommended visibility contribution threshold of 0.5 dv.

1.3 LOCATION OF SOURCES AND RELEVANT CLASS I AREAS

The sources listed in Table 1-1 are the sources that have been identified by OG&E as sources that 

meet the three criteria for BART-eligible sources.

TABLE 1-1. BART-ELIGIBLE SOURCES

EPN Description

Muskogee Sources

Unit 4 5,480 MMBtu/hr Coal Fired Boiler

Unit 5 5,480 MMBtu/hr Coal Fired Boiler

Seminole Sources

SM1 5,480 MMBtu/hr Natural Gas Fired Boiler

SM2 5,480 MMBtu/hr Natural Gas Fired Boiler

SM3 5,496 MMBtu/hr Natural Gas Fired Boiler

Sooner Sources

Unit 1 5,116 MMBtu/hr Coal Fired Boiler

Unit 2 5,116 MMBtu/hr Coal Fired Boiler

As required in CENRAP’s BART Modeling Guidelines, Class I areas within 300 km of each station 

will be included in each analysis. The following table summarizes the distances of the four closest 

Class I areas to each station. As seen from this summary, some Class I areas are more than 300 km 

from the certain stations. However, in order to demonstrate that each station will not have an adverse 

effect on the visibility at any of the four nearest Class I areas, OG&E has opted to include those Class 

I areas more than 300 km away in this analysis. Note that the distances listed in the table below are 

the distances between the stations and the closest border of the Class I areas. 

TABLE 1-2. DISTANCE FROM STATION TO SURROUNDING CLASS I AREAS

CACR HEGL UPBU WIMO

Muskogee 180 230 164 324

Seminole 242 386 310 178

Sooner 345 363 327 234
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CALMET Processing Protocol 083701.0004

A plot of the Class I areas with respect to the each station is provided in Figure 1-1.

 FIGURE 1-1. PLOT OF SOURCES AND NEAREST CLASS I AREAS

-800 -600 -400 -200 0 200 400 600 800

LCC Easting (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

LCC Northing (km)

Seminole Station

Muskogee Station

Sooner Station

WIMO

CACR

UPBU

HEGL

Class I Areas
OG&E 2-1 Trinity Consultants

CALMET Processing Protocol 083701.0004

2. CALPUFF MODEL SYSTEM

The main components of the CALPUFF modeling system are CALMET, CALPUFF, and CALPOST. 

CALMET is the meteorological model that generates hourly three-dimensional meteorological fields 

such as wind and temperature. CALPUFF simulates the non-steady state transport, dispersion, and 

chemical transformation of air pollutants emitted from a source in “puffs”. CALPUFF calculates 

hourly concentrations of visibility affecting pollutants at each specified receptor in a modeling 

domain. CALPOST is the post-processor for CALPUFF that computes visibility impacts from a 

source based on the visibility affecting pollutant concentrations that were output by CALPUFF.

2.1 MODEL VERSIONS

The versions of the CALPUFF modeling system programs that are proposed for conducting OG&E’s 

BART modeling are listed in Table 2-1. A detailed refined CALPUFF BART modeling protocol will 

be submitted in the near future.

TABLE 2-1. CALPUFF MODELING SYSTEM VERSIONS

Processor Version Level

TERREL 3.3 030402

CTGCOMP 2.21 030402

CTGPROC 2.63 050128

MAKEGEO 2.2 030402

CALMET 5.53a 040716

CALPUFF 5.8 070623

POSTUTIL 1.3 030402

CALPOST 5.51 030709

2.2 MODELING DOMAIN

The CALPUFF modeling system utilizes three modeling grids: the meteorological grid, the 

computational grid, and the sampling grid. The meteorological grid is the system of grid points at 

which meteorological fields are developed with CALMET. The computational grid determines the 

computational area for a CALPUFF run. Puffs are advected and tracked only while within the 

computational grid. The meteorological grid is defined so that it covers the areas of concern and 

gives enough marginal buffer area for puff transport and dispersion. A plot of the proposed 

meteorological modeling domain with respect to the Class I areas being modeled is also provided in 
OG&E 2-2 Trinity Consultants

CALMET Processing Protocol 083701.0004

Figure 2-1. The computational domain will be set to extend at least 50 km in all directions beyond 

the Muskogee, Seminole, and Sooner Generating Stations and the Class I areas of interest. Note that 

the map projection for the modeling domain will be Lambert Conformal Conic (LCC) and the datum 

will be the World Geodetic System 84 (WGS-84). The reference point for the modeling domain is

Latitude 40oN, Longitude 97oW. The southwest corner will be set to -951.547 km LCC, -1646.637 

km LCC corresponding to Latitude 24.813 oN and Longitude 87.778oW. The meteorological grid 

spacing will be 4 km, resulting in 462 grid points in the X direction and 376 grid points in the Y 

direction.

FIGURE 2-1. REFINED METEOROLOGICAL MODELING DOMAIN

-800 -600 -400 -200 0 200 400 600 800

LCC Easting (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

L

C

C

N

o

r

t

h

i

n

g

(

k

)m

Seminole Station

Muskogee Station

Sooner Station

WIMO

CACR

UPBU

HEGL

Class I Areas

Meteorological Modeling Domain

Computational Modeling Domain 1
OG&E 3-1 Trinity Consultants

CALMET Processing Protocol 083701.0004

3. CALMET

The EPA Approved Version of the CALMET meteorological processor will be used to generate the 

meteorological data for CALPUFF. CALMET is the meteorological processor that compiles 

meteorological data from raw observations of surface and upper air conditions, precipitation 

measurements, mesoscale model output, and geophysical parameters into a single hourly, gridded 

data set for input into CALPUFF. CALMET will be used to assimilate data for 2001- 2003 using 

National Weather Service (NWS) surface station observations, upper air station observations, 

precipitation station observations, buoy station observations (for overwater areas), and mesoscale 

model output to develop the meteorological field. 

3.1 GEOPHYSICAL DATA

CALMET requires geophysical data to characterize the terrain and land use parameters that 

potentially affect dispersion. Terrain features affect flows and create turbulence in the atmosphere 

and are potentially subjected to higher concentrations of elevated puffs. Different land uses exhibit 

variable characteristics such as surface roughness, albedo, Bowen ratio, and leaf-area index that also 

effect turbulence and dispersion. 

3.1.1 TERRAIN DATA

Terrain data will be obtained from the United States Geological Survey (USGS) in 

1-degree (1:250,000 scale or approximately 90 meter resolution) digital format. The

USGS terrain data will then be processed by the TERREL program to generate grid-cell 

elevation averages across the modeling domain. A plot of the land elevations based on the 

USGS data for the modeling domain is provided in Figure 3-1.
OG&E 3-2 Trinity Consultants

CALMET Processing Protocol 083701.0004

FIGURE 3-1. PLOT OF LAND ELEVATION USING USGS TERRAIN DATA

3.1.2 LAND USE DATA

The land use land cover (LULC) data from the USGS North American land cover 

characteristics data base in the Lambert Azimuthal equal area map projection will be used 

in order to determine the land use within the modeling domain. The LULC data will be 

processed by the CTGPROC program which will generate land use for each grid cell 

across the modeling domain. A plot of the land use based on the USGS data for the 

modeling domain is provided in Figure 3-2.

-800 -600 -400 -200 0 200 400 600 800

LCC Easting(km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

L

C

C

N

o

r

t

h

i

n

g

(

k

)m

Seminole Station

Muskogee Station

Sooner Station

0

982

1960

2950

3930

Terrain 

Elevation (m)
OG&E 3-3 Trinity Consultants

CALMET Processing Protocol 083701.0004

FIGURE 3-2. PLOT OF LAND USE USING USGS LULC DATA

3.1.3 COMPILING TERRAIN AND LAND USE DATA

The terrain data files output by the TERELL program and the LULC files output by the 

CTGPROC program will be uploaded into the MAKEGEO program to create a 

geophysical data file that will be input into CALMET. 

3.2 METEOROLOGICAL DATA 

CALMET will be used to assimilate data for 2001, 2002, and 2003 using mesoscale model output and 

National Weather Service (NWS) surface station observations, upper air station observations,

precipitation station observations, and National Oceanic and Atmosphere Administrations (NOAA) 

buoy station observations to develop the meteorological field. 

3.2.1 MESOSCALE MODEL METEOROLOGICAL DATA

Hourly mesoscale data will also be used as the initial guess field in developing the 

CALMET meteorological data. It is OG&E’s intent to use the following 5th generation 

mesoscale model meteorological data sets (or MM5 data) in the analysis:

 2001 MM5 data at 12 km resolution generated by the U.S. EPA 

 2002 MM5 data at 36 km resolution generated by the Iowa DNR

-800 -600 -400 -200 0 200 400 600 800

LCC Easting (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

L

C

C

N

o

r

t

h

i

n

g

(

k

)m

10

27.5

45

62.5

80

Land Use

Sooner Station

Muskogee Station

Seminole Station
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CALMET Processing Protocol 083701.0004

 2003 MM5 data set at 36 km resolution generated by the Midwest RPO

The specific MM5 data that will be used are subsets of the data listed above. As the 

contractor to CENRAP for developing the meteorological data sets for the BART 

modeling, Alpine Geophysics extracted three subsets of MM5 data for each year from 

2001 to 2003 from the data sets listed above using the CALMM5 extraction program. The 

three subsets covered the northern, central, and southern portions of CENRAP. TXI is 

proposing to use the southern set of the extracted MM5 data. 

The 2001 southern subset of the extracted MM5 data includes 30 files that are broken into 

10 to 11 day increments (3 files per month). The 2002 and 2003 southern subsets of 

extracted MM5 data include 12 files each of which are broken into 30 to 31 day increment

files (1 file per month). Note that the 2001 to 2003 MM5 data extracted by Alpine

Geophysics will not be able to be used directly in the modeling analysis. To run the Alpine 

Geophysics extracted MM data in the EPA approved CALMET program, each of the MM5 

files will need to be adjusted by appending an additional six (6) hours, at a minimum, to 

the end of each file to account for the shift in time zones from the Greenwich Mean Time 

(GMT) prepared Alpine Geophysics data to Time Zone 6 for this analysis. No change to 

the data will occur. 

The time periods covered by the data in each of the MM5 files extracted by Alpine 

Geophysics include a specific number of calendar days, where the data starts at Hour 0 in 

GMT for the first calendar day and ends at Hour 23 in GMT on the last calendar day. In 

order to run CALMET in the local standard time (LST), which is necessary since the 

surface meteorological observations are recorded in LST, there must be hours of MM5 data 

referenced in a CALMET run that match the LST observation hours. Since the LST hours 

in Central Standard Time (CST) are 6 hours behind GMT, it is necessary to adjust the data 

in each MM5 file so that the time periods covered in the files match CST. 

Based on the above discussion, the Alpine Geophysics MM5 data will not be used directly. 

Instead the data files will be modified to add 8 additional hours of data to the end of each

file from the beginning of the subsequent file. CALMET will then be run using the 

appended MM5 data to generate a contiguous set of CALMET output files. The converted 

MM5 data files occupy approximately 1.2 terabytes (TB) of hard drive space.

3.2.2 SURFACE METEOROLOGICAL DATA

Parameters affecting turbulent dispersion that are observed hourly at surface stations 

include wind speed and direction, temperature, cloud cover and ceiling, relative humidity, 

and precipitation type. It is OG&E’s intent to use the surface stations listed in Table A-1 

of Appendix A. The locations of the surface stations with respect to the modeling domain 

are shown in Figure 3-3. The stations were selected from the available data inventory to 

optimize spatial coverage and representation of the domain. Data from the stations will be 

processed for use in CALMET using EPA’s SMERGE program.
OG&E 3-5 Trinity Consultants

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FIGURE 3-3. PLOT OF SURFACE STATION LOCATIONS

3.2.3 UPPER AIR METEOROLOGICAL DATA

Observations of meteorological conditions in the upper atmosphere provide a profile of 

turbulence from the surface through the depth of the boundary layer in which dispersion 

occurs. Upper air data are collected by balloons launched simultaneously across the 

observation network at 0000 Greenwich Mean Time (GMT) (6 o’clock PM in Oklahoma) 

and 1200 GMT (6 o’clock AM in Oklahoma). Sensors observe pressure, wind speed and 

direction, and temperature (among other parameters) as the balloon rises through the 

atmosphere. The upper air observation network is less dense than surface observation 

points since upper air conditions vary less and are generally not as affected by local effects 

(e.g., terrain or water bodies). The upper air stations that are proposed for this analysis are 

listed in Table A-2 of Appendix A. The locations of the upper air stations with respect to 

the modeling domain are shown in Figure 3-4. These stations were selected from the 

available data inventory to optimize spatial coverage and representation of the domain. 

Data from the stations will be processed for use in CALMET using EPA’s READ62 

program.

-800 -600 -400 -200 0 200 400 600 800

LCC Easting (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

L

C

C

N

o

r

t

h

i

n

g

(

k

m)

Seminole Station

Muskogee Station

Sooner Station

WIMO

CACR

UPBU

HEGL

Class I Areas

Surface Stations
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FIGURE 3-4. PLOT OF UPPER AIR STATIONS LOCATIONS

-800 -600 -400 -200 0 200 400 600 800

LCC Easting (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

LCC Northing (km)

Seminole Station

Muskogee Station

Sooner Station

WIMO

CACR

UPBU

HEGL

Class I Areas

Upper Air Stations

3.2.4 PRECIPITATION METEOROLOGICAL DATA

The effects of chemical transformation and deposition processes on ambient pollutant 

concentrations will be considered in this analysis. Therefore, it is necessary to include 

observations of precipitation in the CALMET analysis. The precipitation stations that are 

proposed for this analysis are listed in Table A-3 of Appendix A. The locations of the 

precipitation stations with respect to the modeling domain are shown in Figure 3-5. These 

stations were selected from the available data inventory to optimize spatial coverage and 

representation of the domain. Data from the stations will be processed for use in 

CALMET using EPA’s PMERGE program.
OG&E 3-7 Trinity Consultants

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FIGURE 3-5. PLOT OF PRECIPITATION METEOROLOGICAL STATIONS

-800 -600 -400 -200 0 200 400 600 800

LCC Easting (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

LCC Northing (km)

Seminole Station

Muskogee Station

Sooner Station

WIMO

CACR

UPBU

HEGL

Class I Areas

Precipitation Stations

3.2.5 BUOY METEOROLOGICAL DATA

The effects of land/sea breeze on ambient pollutant concentrations will be considered in 

this analysis. Therefore, it is necessary to include observations of buoy stations in the 

CALMET analysis. The buoy stations that are proposed for this analysis are listed in Table 

A-4 of Appendix A. The locations of the buoy stations with respect to the modeling 

domain are shown in Figure 3-6. These stations were selected from the available data 

inventory to optimize spatial coverage and representation of the domain along the 

coastline. Data from the stations will be prepared by filling missing hour records with the 

CALMET missing parameter value (9999). No adjustments to the data will occur. 
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FIGURE 3-6. PLOT OF BUOY METEOROLOGICAL STATIONS

-800 -600 -400 -200 0 200 400 600 800

LCC Easting (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

LCC Northing (km)

Seminole Station

Muskogee Station

Sooner Station

WIMO

CACR

UPBU

HEGL

Class I Areas

Buoy Stations

3.3 CALMET CONTROL PARAMETERS

Appendix B provides a sample CALMET input file used in OG&E’s modeling analysis. A few 

details of the CALMET model setup for sensitive parameters are also discussed below. 

3.3.1 VERTICAL METEOROLOGICAL PROFILE

The height of the top vertical layer will be set to 3,500 meters. This height corresponds to 

the top sounding pressure level for which upper air observation data will be relied upon. 

The vertical dimension of the domain will be divided into 12 layers with the maximum 

elevations for each layer shown in Table 3-1. The vertical dimensions are weighted 

towards the surface to resolve the mixing layer while using a somewhat coarser resolution 

for the layers aloft. 
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TABLE 3-1. VERTICAL LAYERS OF THE CALMET METEOROLOGICAL DOMAIN

Layer Elevation (m)

1 20 

2 40

3 60

4 80

5 100

6 150

7 200

8 250

9 500

10 1000

11 2000

12 3500

CALMET allows for a bias value to be applied to each of the vertical layers. The bias 

settings for each vertical layer determine the relative weight given to the vertically 

extrapolated surface and upper air wind and temperature observations. The initial guess 

fields are computed with an inverse distance weighting (1/r

2

) of the surface and upper air 

data. The initial guess fields may be modified by a layer dependent bias factor. Values for 

the bias factor may range from -1 to +1. A bias of -1 eliminates upper-air observations in

the 1/r2interpolations used to initialize the vertical wind fields. Conversely, a bias of +1 

eliminates the surface observations in the interpolations for this layer. Normally, bias is set 

to zero (0) for each vertical layer, such that the upper air and surface observations are given 

equal weight in the 1/r2interpolations. The biases for each layer of the proposed modeling 

domain will be set to zero.

CALMET allows for vertical extrapolation of surface wind observations to layers aloft to 

be skipped if the surface station is close to the upper air station. Alternatively, CALMET 

allows data from all surface stations to be extrapolated. The CALMET parameter that 

controls this setting is IEXTRP. Setting IEXTRP to a value less than zero (0) means that 

layer 1 data from upper air soundings is ignored in any vertical extrapolations. IEXTRP 

will be set to -4 for this analysis (i.e., the similarity theory is used to extrapolate the surface 

winds into the layers aloft, which provides more information on observed local effects to 

the upper layers).

3.3.2 INFLUENCES OF OBSERVATIONS

Step 1 wind fields will be based on an initial guess using MM5 data and refined to reflect 

terrain affects. Step 2 wind fields will adjust the Step 1 wind field by incorporating the 

influence of local observations. An inverse distance method is used to determine the 

influence of observations to the Step 1 wind field. RMAX1 and RMAX2 define the radius 

of influence for data from surface stations to land in the surface layer and data from upper 

air stations to land in the layers aloft. In general, RMAX1 and RMAX2 are used to 

exclude observations from being inappropriately included in the development of the Step 2
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wind field if the distance from an observation station to a grid point exceeds the maximum 

radius of influence. 

If the distance from an observation station to a grid point is less than the value set for 

RMAX, the observation data will be used in the development of the Step 2 wind field. R1 

represents the distance from a surface observation station at which the surface observation 

and the Step 1 wind field are weighted equally. R2 represents the comparable distance for 

winds aloft. R1 and R2 are used to weight the observation data with respect to the MM5 

data that was used to generate the Step 1 wind field. Large values for R1 and R2 give 

more weight to the observations, where as small values give more weight to the MM5 data. 

In this BART modeling analysis, RMAX 1 will be set to 20 km, and R1 will be set to 10 

km. This will limit the influence of the surface observation data from all surface stations to 

20 km from each station, and will equally weight the MM5 and observation data at 10 km. 

RMAX2 will be set to 50 km, and R2 will be set to 25 km. This will limit the influence of 

the upper air observation data from all surface stations to 50 km from each station, and will 

equally weight the MM5 and observation data at 25 km. These settings of radius of 

influence will allow for adequate weighting of the MM5 data and the observation data 

across the modeling domain due to the vast domain to be modeled. RAMX 3 will be set to 

500 km. 
OG&E A-1 Trinity Consultants

CALMET Processing Protocol 083701.0004

APPENDIX A- METEOROLOGICAL STATIONS

TABLE A-1. LIST OF SURFACE METEOROLOGICAL STATIONS

Number

Station 

Acronym

Station 

ID

LCC 

East 

(km)

LCC North

(km) Long Lat

1 KDYS 69019 -267.672 -834.095 96.9968 39.9925

2 KNPA 72222 932.565 -1020.909 97.0110 39.9908

3 KBFM 72223 857.471 -996.829 97.0101 39.9910

4 KGZH 72227 946.767 -899.515 97.0112 39.9919

5 KTCL 72228 870.843 -706.104 97.0103 39.9936

6 KNEW 53917 674.172 -1078.342 97.0080 39.9903

7 KNBG 12958 677.719 -1104.227 97.0080 39.9900

8 BVE 12884 741.996 -1153.463 97.0088 39.9896

9 KPTN 72232 550.88 -1124.295 97.0065 39.9898

10 KMEI 13865 774.911 -814.225 97.0092 39.9926

11 KPIB 72234 728.416 -915.165 97.0086 39.9917

12 KGLH 72235 557.072 -703.097 97.0066 39.9936

13 KHEZ 11111 540.777 -912.22 97.0064 39.9918

14 KMCB 11112 622.755 -949.618 97.0074 39.9914

15 KGWO 11113 640.102 -695.286 97.0076 39.9937

16 KASD 72236 692.381 -1043.261 97.0082 39.9906

17 KPOE 72239 363.294 -984.839 97.0043 39.9911

18 KBAZ 72241 -102.133 -1140.886 96.9988 39.9897

19 KGLS 72242 215.108 -1185.604 97.0025 39.9893

20 KDWH 11114 140.413 -1101.174 97.0017 39.9900

21 KIAH 12960 158.266 -1108.37 97.0019 39.9900

22 KHOU 72243 167.147 -1147.402 97.0020 39.9896

23 KEFD 12906 178.551 -1152.782 97.0021 39.9896

24 KCXO 72244 152.739 -1069.309 97.0018 39.9903

25 KCLL 11115 60.898 -1044.381 97.0007 39.9906

26 KLFK 93987 214.643 -969.355 97.0025 39.9912

27 KUTS 11116 136.056 -1026.773 97.0016 39.9907

28 KTYR 11117 150.451 -846.207 97.0018 39.9924

29 KCRS 72246 56.655 -882.642 97.0007 39.9920

30 KGGG 72247 214.572 -841.163 97.0025 39.9924

31 KGKY 11118 -9.365 -812.25 96.9999 39.9927

32 KDTN 72248 304.827 -821.713 97.0036 39.9926

33 KBAD 11119 312.743 -825.101 97.0037 39.9925

34 KMLU 11120 465.834 -816.211 97.0055 39.9926

35 KTVR 11121 561.446 -840.225 97.0066 39.9924

36 KTRL 11122 68.599 -806.417 97.0008 39.9927

37 KOCH 72249 216.81 -930.252 97.0026 39.9916

38 KBRO 12919 -44.167 -1571.387 96.9995 39.9858
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Number

Station 

Acronym

Station 

ID

LCC 

East 

(km)

LCC North

(km) Long Lat

39 KALI 72251 -103.012 -1363.74 96.9988 39.9877

40 KLRD 12920 -246.548 -1381.603 96.9971 39.9875

41 KSSF 72252 -143.386 -1183.35 96.9983 39.9893

42 KRKP 11123 -4.965 -1324.914 96.9999 39.9880

43 KCOT 11124 -219.097 -1280.964 96.9974 39.9884

44 KLBX 11125 150.245 -1207.466 97.0018 39.9891

45 KSAT 12921 -143.024 -1160.935 96.9983 39.9895

46 KHDO 12962 -211.702 -1178.172 96.9975 39.9894

47 KSKF 72253 -154.625 -1177.555 96.9982 39.9894

48 KHYI 11126 -84.156 -1122.487 96.9990 39.9899

49 KTKI 72254 38.788 -754.791 97.0005 39.9932

50 KBMQ 11127 -118.39 -1027.031 96.9986 39.9907

51 KATT 11128 -67.587 -1075.97 96.9992 39.9903

52 KSGR 11129 131.478 -1151.702 97.0016 39.9896

53 KGTU 11130 -65.624 -1033.173 96.9992 39.9907

54 KVCT 12912 6.587 -1236.788 97.0001 39.9888

55 KPSX 72255 73.878 -1253.33 97.0009 39.9887

56 KACT 13959 -22.12 -929.156 96.9997 39.9916

57 KPWG 72256 -30.147 -944.073 96.9996 39.9915

58 KILE 72257 -65.288 -988.507 96.9992 39.9911

59 KGRK 11131 -79.643 -990.173 96.9991 39.9911

60 KTPL 11132 -38.203 -981.19 96.9996 39.9911

61 KPRX 13960 143.317 -703.663 97.0017 39.9936

62 KDTO 72258 -17.018 -752.974 96.9998 39.9932

63 KAFW 11133 -29.564 -777.061 96.9997 39.9930

64 KFTW 72259 -34.302 -795.502 96.9996 39.9928

65 KMWL 11134 -99.769 -798.767 96.9988 39.9928

66 KRBD 11135 12.453 -810.467 97.0002 39.9927

67 KDRT 11136 -384.069 -1170.59 96.9955 39.9894

68 KFST 22010 -566.418 -988.838 96.9933 39.9911

69 KGDP 72261 -739.127 -873.302 96.9913 39.9921

70 KSJT 72262 -333.338 -952.54 96.9961 39.9914

71 KMRF 23034 -676.265 -1042.616 96.9920 39.9906

72 KMAF 72264 -489.668 -878.107 96.9942 39.9921

73 KINK 23023 -586.882 -890.654 96.9931 39.9920

74 KABI 72265 -252.044 -836.353 96.9970 39.9924

75 KLBB 13962 -445.006 -689.313 96.9948 39.9938

76 KATS 11137 -696.818 -763.258 96.9918 39.9931

77 KCQC 11138 -785.757 -515.724 96.9907 39.9953

78 KROW 23009 -698.822 -712.898 96.9918 39.9936

79 KSRR 72268 -789.593 -686.226 96.9907 39.9938

80 KCNM 11139 -682.79 -822.109 96.9919 39.9926

81 KALM 36870 -838.056 -752.338 96.9901 39.9932

82 KLRU 72269 -931.527 -804.112 96.9890 39.9927

83 KTCS 72271 -952.353 -695.469 96.9888 39.9937
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Number

Station 

Acronym

Station 

ID

LCC 

East 

(km)

LCC North

(km) Long Lat

84 KSVC 93063 -1042.03 -752.033 96.9877 39.9932

85 KDMN 72272 -1006.77 -799.231 96.9881 39.9928

86 KMSL 72323 854.846 -536.687 97.0101 39.9952

87 KPOF 72330 578.62 -336.733 97.0068 39.9970

88 KGTR 11140 779.065 -689.108 97.0092 39.9938

89 KTUP 93862 753.875 -600.337 97.0089 39.9946

90 KMKL 72334 727.051 -454.383 97.0086 39.9959

91 KLRF 72340 440.654 -550.661 97.0052 39.9950

92 KHKA 11141 643.365 -424.419 97.0076 39.9962

93 KHOT 72341 358.094 -604.603 97.0042 39.9945

94 KTXK 11142 278.022 -720.623 97.0033 39.9935

95 KLLQ 72342 488.655 -698.008 97.0058 39.9937

96 KMWT 72343 254.18 -599.224 97.0030 39.9946

97 KFSM 13964 237.97 -512.87 97.0028 39.9954

98 KSLG 72344 224.881 -419.064 97.0027 39.9962

99 KVBT 11143 248.074 -399.892 97.0029 39.9964

100 KHRO 11144 343.525 -405.601 97.0041 39.9963

101 KFLP 11145 404.239 -399.142 97.0048 39.9964

102 KBVX 11146 480.712 -457.853 97.0057 39.9959

103 KROG 11147 258.44 -397.685 97.0031 39.9964

104 KSPS 13966 -138.053 -664.886 96.9984 39.9940

105 KHBR 72352 -186.121 -551.123 96.9978 39.9950

106 KCSM 11148 -198.844 -513.911 96.9977 39.9954

107 KFDR 11149 -181.653 -625.205 96.9979 39.9944

108 KGOK 72353 -35.905 -458.97 96.9996 39.9959

109 KTIK 72354 -34.581 -506.938 96.9996 39.9954

110 KPWA 11150 -58.596 -493.951 96.9993 39.9955

111 KSWO 11151 -7.42 -425.828 96.9999 39.9962

112 KMKO 72355 146.972 -479.879 97.0017 39.9957

113 KRVS 72356 91.059 -438.276 97.0011 39.9960

114 KBVO 11152 87.136 -357.069 97.0010 39.9968

115 KMLC 11153 110.647 -563.566 97.0013 39.9949

116 KOUN 72357 -40.731 -527.298 96.9995 39.9952

117 KLAW 11154 -129.405 -600.222 96.9985 39.9946

118 KCDS 72360 -300.297 -610.668 96.9965 39.9945

119 KGNT 72362 -985.117 -475.563 96.9884 39.9957

120 KGUP 11155 -1059.48 -427.151 96.9875 39.9961

121 KAMA 23047 -425.319 -518.171 96.9950 39.9953

122 KBGD 72363 -395.603 -466.083 96.9953 39.9958

123 KFMN 72365 -993.449 -297.944 96.9883 39.9973

124 KSKX 72366 -770.464 -355.855 96.9909 39.9968

125 KTCC 23048 -597.271 -511.241 96.9930 39.9954

126 KLVS 23054 -732.565 -448.329 96.9914 39.9960

127 KEHR 72423 812.573 -199.695 97.0096 39.9982

128 KEVV 93817 822.929 -172.715 97.0097 39.9984
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Number

Station 

Acronym

Station 

ID

LCC 

East 

(km)

LCC North

(km) Long Lat

129 KMVN 72433 704.666 -154.54 97.0083 39.9986

130 KMDH 11156 676.745 -218.041 97.0080 39.9980

131 KBLV 11157 617.659 -136.018 97.0073 39.9988

132 KSUS 3966 547.898 -130.122 97.0065 39.9988

133 KPAH 3816 725.985 -293.319 97.0086 39.9974

134 KJEF 72445 419.01 -145.496 97.0050 39.9987

135 KAIZ 11158 387.096 -200.609 97.0046 39.9982

136 KIXD 72447 182.322 -126.913 97.0022 39.9989

137 KWLD 72450 0 -298.57 97.0000 39.9973

138 KAAO 11159 -18.976 -248.773 96.9998 39.9978

139 KIAB 11160 -23.392 -263.471 96.9997 39.9976

140 KEWK 11161 -24.645 -215.58 96.9997 39.9981

141 KGBD 72451 -161.892 -180.781 96.9981 39.9984

142 KHYS 11162 -195.191 -124.723 96.9977 39.9989

143 KCFV 11163 126.442 -319.698 97.0015 39.9971

144 KFOE 72456 114.618 -115.26 97.0014 39.9990

145 KEHA 72460 -432.761 -320.089 96.9949 39.9971

146 KALS 72462 -777.592 -245.892 96.9908 39.9978

147 KDRO 11164 -945.713 -259.163 96.9888 39.9977

148 KLHX 72463 -568.426 -195.178 96.9933 39.9982

149 KSPD 2128 -494.076 -285.176 96.9942 39.9974

150 KCOS 93037 -664.022 -102.596 96.9922 39.9991

151 KGUC 72467 -857.452 -115.301 96.9899 39.9990

152 KMTJ 93013 -940.981 -109.358 96.9889 39.9990

153 KCEZ 72476 -1020.87 -233.14 96.9880 39.9979

154 KCPS 72531 591.652 -136.14 97.0070 39.9988

155 KLWV 72534 808.939 -94.46 97.0096 39.9992

156 KPPF 74543 130.433 -293.855 97.0015 39.9973

157 KHOP 74671 841.751 -324.569 97.0099 39.9971

158 KBIX 74768 778.252 -1028.514 97.0092 39.9907

159 KPQL 11165 814.599 -1019.583 97.0096 39.9908

160 MMPG 76243 -348.007 -1248.779 96.9959 39.9887

161 MMMV 76342 -446.576 -1449.334 96.9947 39.9869

162 MMMY 76394 -316.664 -1581.176 96.9963 39.9857
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TABLE A-2. LIST OF UPPER AIR METEOROLOGICAL STATIONS

Number

Station 

Acronym

Station 

ID

LCC 

East 

(km)

LCC 

North

(km) Long Lat

1 KABQ 23050 -869.46 -501.713 96.9897 39.9955

2 KAMA 23047 -425.319 -518.171 96.9950 39.9953

3 KBMX 53823 951.609 -702.935 97.0112 39.9936

4 KBNA 13897 920.739 -377.164 97.0109 39.9966

5 KBRO 12919 -44.167 -1571.39 96.9995 39.9858

6 KCRP 12924 -51.535 -1360.35 96.9994 39.9877

7 KDDC 13985 -259.352 -242.681 96.9969 39.9978

8 KDRT 22010 -384.069 -1170.59 96.9955 39.9894

9 KEPZ 3020 -914.558 -852.552 96.9892 39.9923

10 KFWD 3990 -28.034 -793.745 96.9997 39.9928

11 KJAN 3940 650.105 -826.452 97.0077 39.9925

12 KLCH 3937 364.461 -1089.15 97.0043 39.9902

13 KLZK 3952 432.063 -560.441 97.0051 39.9949

14 KMAF 23023 -489.668 -878.107 96.9942 39.9921

15 KOUN 3948 -40.731 -527.298 96.9995 39.9952

16 KSHV 13957 298.869 -831.166 97.0035 39.9925

17 KSIL 53813 698.079 -1054.03 97.0082 39.9905
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TABLE A-3. LIST OF PRECIPITATION METEOROLOGICAL STATIONS

Number

Station 

Acronym

Station 

ID

LCC 

East 

(km)

LCC 

North

(km) Long Lat

1 ADDI 10063 906.825 -601.428 97.0107 39.9946

2 ALBE 10140 917.606 -821.64 97.0108 39.9926

3 BERR 10748 892.454 -683.388 97.0105 39.9938

4 HALE 13620 881.928 -601.878 97.0104 39.9946

5 HAMT 13645 863.663 -612.725 97.0102 39.9945

6 JACK 14193 898.014 -915.623 97.0106 39.9917

7 MBLE 15478 851.953 -1022.41 97.0101 39.9908

8 MUSC 15749 880.113 -567.484 97.0104 39.9949

9 PETE 16370 935.558 -908.259 97.0110 39.9918

10 THOM 18178 900.858 -915.326 97.0106 39.9917

11 TUSC 18385 895.631 -713.223 97.0106 39.9936

12 VERN 18517 825.585 -685.773 97.0098 39.9938

13 BEEB 30530 462.394 -532.485 97.0055 39.9952

14 BRIG 30900 318.015 -554.857 97.0038 39.9950

15 CALI 31140 419.619 -731.44 97.0050 39.9934

16 CAMD 31152 386.546 -699.659 97.0046 39.9937

17 DIER 32020 268.114 -643.184 97.0032 39.9942

18 EURE 32356 286.738 -390.862 97.0034 39.9965

19 GILB 32794 383.362 -435.625 97.0045 39.9961

20 GREE 32978 450.594 -483.201 97.0053 39.9956

21 STUT 36920 509.943 -596.328 97.0060 39.9946

22 TEXA 37048 278.022 -720.623 97.0033 39.9935

23 ALAM 50130 -749.044 -267.856 96.9912 39.9976

24 ARAP 50304 -441.903 -152.324 96.9948 39.9986

25 COCH 51713 -819.794 -148.582 96.9903 39.9987

26 CRES 51959 -828.107 -119.911 96.9902 39.9989

27 GRAN 53477 -451.781 -203.82 96.9947 39.9982

28 GUNN 53662 -829.573 -141.995 96.9902 39.9987

29 HUGO 54172 -539.364 -81.948 96.9936 39.9993

30 JOHN 54388 -483.95 -201.915 96.9943 39.9982

31 KIM 54538 -544.501 -283.337 96.9936 39.9974

32 MESA 55531 -993.391 -256.696 96.9883 39.9977

33 ORDW 56136 -549.552 -55.741 96.9935 39.9995

34 OURA 56203 -904.197 -168.246 96.9893 39.9985

35 PLEA 56591 -1005.94 -229.472 96.9881 39.9979

36 PUEB 56740 -633.961 -176.872 96.9925 39.9984

37 TYE 57320 -662.095 -242.254 96.9922 39.9978

38 SAGU 57337 -790.269 -176.061 96.9907 39.9984
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Number

Station 

Acronym

Station 

ID

LCC 

East 

(km)

LCC 

North

(km) Long Lat

39 SANL 57428 -726.777 -285.47 96.9914 39.9974

40 SHEP 57572 -714.046 -252.189 96.9916 39.9977

41 TELL 58204 -920.205 -215.382 96.9891 39.9981

42 TERC 58220 -708.229 -296.023 96.9916 39.9973

43 TRIN 58429 -642.489 -293.805 96.9924 39.9973

44 TRLK 58436 -646.185 -295.727 96.9924 39.9973

45 WALS 58781 -654.989 -262.821 96.9923 39.9976

46 WHIT 58997 -619.615 -250.12 96.9927 39.9977

47 ASHL 110281 684.787 -169.285 97.0081 39.9985

48 CAIR 111166 697.177 -301.436 97.0082 39.9973

49 CARM 111302 772.938 -177.782 97.0091 39.9984

50 CISN 111664 758.146 -151.446 97.0090 39.9986

51 FLOR 113109 751.801 -139.837 97.0089 39.9987

52 HARR 113879 762.044 -246.62 97.0090 39.9978

53 KASK 114629 650.464 -239.886 97.0077 39.9978

54 LAWR 114957 829.038 -128.708 97.0098 39.9988

55 MTCA 115888 827.797 -149.966 97.0098 39.9986

56 MURP 115983 682.261 -251.649 97.0081 39.9977

57 NEWT 116159 766.098 -72.902 97.0090 39.9993

58 REND 117187 731.633 -185.058 97.0086 39.9983

59 SMIT 118020 770.027 -283.638 97.0091 39.9974

60 SPAR 118147 658.275 -185.973 97.0078 39.9983

61 VAND 118781 685.449 -127.048 97.0081 39.9989

62 WEST 119193 778.655 -147.215 97.0092 39.9987

63 EVAN 122738 842.476 -172.871 97.0100 39.9984

64 NEWB 126151 855.854 -223.713 97.0101 39.9980

65 PRIN 127125 836.901 -153.449 97.0099 39.9986

66 STEN 128442 859.099 -156.613 97.0101 39.9986

67 JTML 128967 788.703 -239.572 97.0093 39.9978

68 ARLI 140326 -101.734 -271.373 96.9988 39.9976

69 BAZI 140620 -210.423 -201.758 96.9975 39.9982

70 BEAU 140637 59.762 -288.39 97.0007 39.9974

71 BONN 140957 211.236 -103.29 97.0025 39.9991

72 CALD 141233 -32.689 -330.586 96.9996 39.9970

73 CASS 141351 54.006 -217.645 97.0006 39.9980

74 CENT 141404 170.503 -206.038 97.0020 39.9981

75 CHAN 141427 150.257 -286.094 97.0018 39.9974

76 CLIN 141612 155.623 -157.682 97.0018 39.9986

77 COLL 141730 -265.465 -156.95 96.9969 39.9986

78 COLU 141740 220.541 -316.555 97.0026 39.9971
OG&E A-8 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number

Station 

Acronym

Station 

ID

LCC 

East 

(km)

LCC 

North

(km) Long Lat

79 CONC 141867 58.918 -175.589 97.0007 39.9984

80 DODG 142164 -226.497 -277.655 96.9973 39.9975

81 ELKH 142432 -400.112 -321.784 96.9953 39.9971

82 ENGL 142560 -264.927 -324.066 96.9969 39.9971

83 ERIE 142582 162.669 -291.383 97.0019 39.9974

84 FALL 142686 83.491 -288.177 97.0010 39.9974

85 GALA 142938 -136.931 -176.83 96.9984 39.9984

86 GARD 142980 -304.059 -215.308 96.9964 39.9981

87 GREN 143248 64.308 -307.161 97.0008 39.9972

88 HAYS 143527 -190.307 -161.342 96.9978 39.9985

89 HEAL 143554 -292.133 -175.921 96.9966 39.9984

90 HILL 143686 214.018 -174.006 97.0025 39.9984

91 INDE 143954 139.335 -315.058 97.0016 39.9972

92 IOLA 143984 153.451 -269.438 97.0018 39.9976

93 JOHR 144104 134.784 -203.41 97.0016 39.9982

94 KANO 144178 -50.289 -181.177 96.9994 39.9984

95 KIOW 144341 -113.967 -329.843 96.9987 39.9970

96 MARI 145039 -4.343 -195.712 97.0000 39.9982

97 MELV 145210 137.104 -186.781 97.0016 39.9983

98 MILF 145306 39.504 -106.05 97.0005 39.9990

99 MOUD 145536 152.624 -318.136 97.0018 39.9971

100 OAKL 145888 -306.378 -96.814 96.9964 39.9991

101 OTTA 146128 158.639 -178.635 97.0019 39.9984

102 POMO 146498 143.864 -176.707 97.0017 39.9984

103 SALI 147160 -29.426 -166.908 96.9997 39.9985

104 SMOL 147551 -34.639 -171.31 96.9996 39.9985

105 STAN 147756 225.026 -164.85 97.0027 39.9985

106 SUBL 147922 -303.514 -292.808 96.9964 39.9974

107 TOPE 148167 139.116 -104.91 97.0016 39.9991

108 TRIB 148235 -387.855 -180.643 96.9954 39.9984

109 UNIO 148293 211.43 -272.537 97.0025 39.9975

110 WALL 148535 -376.076 -152.432 96.9956 39.9986

111 WICH 148830 -23.729 -288.579 96.9997 39.9974

112 WILS 148946 -111.502 -156.22 96.9987 39.9986

113 BENT 150611 781.608 -348.109 97.0092 39.9969

114 CALH 151227 865.268 -261.635 97.0102 39.9976

115 CLTN 151631 749.287 -365.634 97.0088 39.9967

116 HERN 153798 859.01 -352.458 97.0101 39.9968

117 MADI 155067 854.116 -265.064 97.0101 39.9976

118 PADU 156110 753.185 -293.024 97.0089 39.9974
OG&E A-9 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number

Station 

Acronym

Station 

ID

LCC 

East 

(km)

LCC 

North

(km) Long Lat

119 PCTN 156580 834.464 -280.496 97.0099 39.9975

120 ALEX 160103 433.824 -959.253 97.0051 39.9913

121 BATN 160549 562.794 -1032.4 97.0066 39.9907

122 CALH 161411 436.113 -817.451 97.0052 39.9926

123 CLNT 161899 578.969 -999.986 97.0068 39.9910

124 JENA 164696 455.225 -912.366 97.0054 39.9918

125 LACM 165078 364.784 -1089.92 97.0043 39.9901

126 MIND 166244 346.708 -812.651 97.0041 39.9927

127 MONR 166314 463.225 -814.905 97.0055 39.9926

128 NATC 166582 369.451 -905.316 97.0044 39.9918

129 SHRE 168440 299.526 -831.143 97.0035 39.9925

130 WINN 169803 408.309 -884.596 97.0048 39.9920

131 BROK 221094 621.827 -914.236 97.0073 39.9917

132 CONE 221900 737.007 -823.513 97.0087 39.9926

133 JAKS 224472 650.361 -826.097 97.0077 39.9925

134 LEAK 224966 805.886 -943.78 97.0095 39.9915

135 MERI 225776 774.942 -814.558 97.0092 39.9926

136 SARD 227815 658.33 -593.661 97.0078 39.9946

137 SAUC 227840 763.399 -1005.93 97.0090 39.9909

138 TUPE 229003 753.571 -600.03 97.0089 39.9946

139 ADVA 230022 657.892 -298.102 97.0078 39.9973

140 ALEY 230088 505.348 -305.864 97.0060 39.9972

141 BOLI 230789 331.651 -291.689 97.0039 39.9974

142 CASV 231383 310.855 -392.187 97.0037 39.9965

143 CLER 231674 575.868 -302.209 97.0068 39.9973

144 CLTT 231711 307.465 -190.83 97.0036 39.9983

145 COLU 231791 421.287 -155.672 97.0050 39.9986

146 DREX 232331 228.23 -185.776 97.0027 39.9983

147 ELM 232568 257.758 -159.419 97.0030 39.9986

148 FULT 233079 470.408 -150.668 97.0056 39.9986

149 HOME 233999 619.93 -415.469 97.0073 39.9962

150 JEFF 234271 424.774 -172.095 97.0050 39.9984

151 JOPL 234315 238.245 -318.262 97.0028 39.9971

152 LEBA 234825 402.239 -276.263 97.0048 39.9975

153 LICK 234919 480.849 -280.775 97.0057 39.9975

154 LOCK 235027 302.048 -300.612 97.0036 39.9973

155 MALD 235207 659.982 -377.876 97.0078 39.9966

156 MARS 235298 332.062 -94.655 97.0039 39.9991

157 MAFD 235307 391.968 -300.033 97.0046 39.9973

158 MCES 235415 471.737 -143.942 97.0056 39.9987
OG&E A-10 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number

Station 

Acronym

Station 

ID

LCC 

East 

(km)

LCC 

North

(km) Long Lat

159 MILL 235594 309.516 -311.398 97.0037 39.9972

160 MTGV 235834 426.937 -310.43 97.0050 39.9972

161 NVAD 235987 243.915 -272.715 97.0029 39.9975

162 OZRK 236460 349.133 -390.626 97.0041 39.9965

163 PDTD 236777 334.055 -265.018 97.0039 39.9976

164 POTO 236826 572.215 -251.455 97.0068 39.9977

165 ROLL 237263 484.503 -253.958 97.0057 39.9977

166 ROSE 237300 500.59 -175.393 97.0059 39.9984

167 SALE 237506 498.94 -274.122 97.0059 39.9975

168 SENE 237656 233.959 -383.703 97.0028 39.9965

169 SPRC 237967 238.112 -373.616 97.0028 39.9966

170 SPVL 237976 332.385 -309.374 97.0039 39.9972

171 STEE 238043 503.354 -205.135 97.0059 39.9981

172 STOK 238082 310.911 -279.239 97.0037 39.9975

173 SWSP 238223 324.053 -150.325 97.0038 39.9986

174 TRKD 238252 340.418 -395.428 97.0040 39.9964

175 TRUM 238466 326.883 -197.796 97.0039 39.9982

176 UNIT 238524 238.567 -154.494 97.0028 39.9986

177 VIBU 238609 519.633 -267.258 97.0061 39.9976

178 VIEN 238620 470.383 -193.872 97.0056 39.9983

179 WAPP 238700 606.68 -358.746 97.0072 39.9968

180 WASG 238746 556.425 -164.993 97.0066 39.9985

181 WEST 238880 489.373 -377.809 97.0058 39.9966

182 ALBU 290234 -869.46 -501.713 96.9897 39.9955

183 ARTE 290600 -689.529 -773.897 96.9919 39.9930

184 AUGU 290640 -973.07 -598.391 96.9885 39.9946

185 CARL 291469 -680.335 -811.474 96.9920 39.9927

186 CARR 291515 -819.836 -665.132 96.9903 39.9940

187 CLAY 291887 -547.124 -374.102 96.9935 39.9966

188 CLOV 291939 -566.973 -599.296 96.9933 39.9946

189 CUBA 292241 -890.304 -392.495 96.9895 39.9965

190 CUBE 292250 -951.142 -489.293 96.9888 39.9956

191 DEMI 292436 -1007.99 -799.087 96.9881 39.9928

192 DURA 292665 -767.148 -577.618 96.9909 39.9948

193 EANT 292700 -735.089 -366.94 96.9913 39.9967

194 LAVG 294862 -738.245 -461.163 96.9913 39.9958

195 PROG 297094 -811.39 -578.971 96.9904 39.9948

196 RAMO 297254 -733.737 -615.175 96.9913 39.9944

197 ROSW 297610 -698.544 -712.921 96.9918 39.9936

198 ROY 297638 -644.735 -422.422 96.9924 39.9962
OG&E A-11 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number

Station 

Acronym

Station 

ID

LCC 

East 

(km)

LCC 

North

(km) Long Lat

199 SANT 298085 -807.375 -445.708 96.9905 39.9960

200 SPRI 298501 -676.681 -374.272 96.9920 39.9966

201 STAY 298518 -810.491 -495.501 96.9904 39.9955

202 TNMN 299031 -912.488 -413.425 96.9892 39.9963

203 TUCU 299156 -604.359 -508.834 96.9929 39.9954

204 WAST 299569 -638.605 -820.288 96.9925 39.9926

205 WISD 299686 -856.967 -756.366 96.9899 39.9932

206 AIRS 340179 -212.731 -597.062 96.9975 39.9946

207 ARDM 340292 -12.242 -645.633 96.9999 39.9942

208 BENG 340670 174.368 -568.011 97.0021 39.9949

209 CANE 341437 71.857 -637.935 97.0009 39.9942

210 CHRT 341544 203.233 -632.067 97.0024 39.9943

211 CHAN 341684 10.494 -475.655 97.0001 39.9957

212 CHIK 341750 -83.175 -547.26 96.9990 39.9951

213 CCTY 342334 -165 -479.536 96.9981 39.9957

214 DUNC 342654 -88.38 -610.04 96.9990 39.9945

215 ELKC 342849 -216.769 -507.879 96.9974 39.9954

216 FORT 343281 -129.964 -541.113 96.9985 39.9951

217 GEAR 343497 -118.53 -482.187 96.9986 39.9956

218 HENN 344052 -31.964 -601.206 96.9996 39.9946

219 HOBA 344202 -189.062 -547.36 96.9978 39.9951

220 KING 344865 24.538 -664.103 97.0003 39.9940

221 LKEU 344975 141.702 -520.6 97.0017 39.9953

222 LEHI 345108 71.634 -612.05 97.0009 39.9945

223 MACI 345463 -254.63 -466.154 96.9970 39.9958

224 MALL 345589 -55.127 -425.644 96.9994 39.9962

225 MAYF 345648 -258.49 -512.583 96.9970 39.9954

226 MUSK 346130 149.764 -466.905 97.0018 39.9958

227 NOWA 346485 121.551 -364.038 97.0014 39.9967

228 OKAR 346620 -88.424 -473.338 96.9990 39.9957

229 OKEM 346638 63.188 -504.958 97.0008 39.9954

230 OKLA 346661 -54.198 -510.562 96.9994 39.9954

231 PAOL 346859 -23.665 -573.142 96.9997 39.9948

232 PAWH 346935 57.704 -369.174 97.0007 39.9967

233 PAWN 346944 16.927 -398.139 97.0002 39.9964

234 PONC 347196 -8.871 -363.068 96.9999 39.9967

235 PRYO 347309 150.763 -407.824 97.0018 39.9963

236 SHAT 348101 -256.963 -407.368 96.9970 39.9963

237 STIG 348497 171.02 -523.736 97.0020 39.9953

238 TULS 348992 99.361 -419.873 97.0012 39.9962
OG&E A-12 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number

Station 

Acronym

Station 

ID

LCC 

East 

(km)

LCC 

North

(km) Long Lat

239 TUSK 349023 156.629 -592.395 97.0019 39.9946

240 WMWR 349629 -156.42 -581.308 96.9982 39.9947

241 WOLF 349748 30.212 -538.388 97.0004 39.9951

242 BOLI 400876 760.886 -500.256 97.0090 39.9955

243 BROW 401150 710.048 -480.346 97.0084 39.9957

244 CETR 401587 877.35 -456.294 97.0104 39.9959

245 DICS 402489 872.14 -391.132 97.0103 39.9965

246 DYER 402680 695.792 -409.316 97.0082 39.9963

247 GRNF 403697 760.795 -395.69 97.0090 39.9964

248 JSNN 404561 765.932 -476.414 97.0090 39.9957

249 LWER 405089 885.291 -487.757 97.0105 39.9956

250 LEXI 405210 790.003 -471.897 97.0093 39.9957

251 MASO 405720 694.163 -496.166 97.0082 39.9955

252 MEMP 405954 671.8 -522.492 97.0079 39.9953

253 MWFO 405956 681.292 -516.15 97.0080 39.9953

254 MUNF 406358 678.65 -495.241 97.0080 39.9955

255 SAMB 408065 697.077 -382.536 97.0082 39.9965

256 SAVA 408108 800.788 -498.682 97.0095 39.9955

257 UNCY 409219 711.595 -384.605 97.0084 39.9965

258 ABIL 410016 -251.753 -836.027 96.9970 39.9924

259 AMAR 410211 -425.302 -517.839 96.9950 39.9953

260 AUST 410428 -67.587 -1075.97 96.9992 39.9903

261 BRWN 411136 -43.861 -1571.39 96.9995 39.9858

262 COST 411889 60.611 -1044.72 97.0007 39.9906

263 COCR 412015 -51.832 -1360.01 96.9994 39.9877

264 CROS 412131 -204.599 -868.469 96.9976 39.9922

265 DFWT 412242 -1.867 -786.341 97.0000 39.9929

266 EAST 412715 -171.024 -840.253 96.9980 39.9924

267 ELPA 412797 -886.583 -860.763 96.9895 39.9922

268 HICO 414137 -97.323 -888.181 96.9989 39.9920

269 HUST 414300 157.976 -1108.38 97.0019 39.9900

270 KRES 414880 -434.746 -611.717 96.9949 39.9945

271 LKCK 414975 99.734 -693.521 97.0012 39.9937

272 LNGV 415348 220.962 -844.674 97.0026 39.9924

273 LUFK 415424 214.652 -969.69 97.0025 39.9912

274 MATH 415661 -86.438 -1330.47 96.9990 39.9880

275 MIDR 415890 -489.385 -878.123 96.9942 39.9921

276 MTLK 416104 -672.024 -1008.98 96.9921 39.9909

277 NACO 416177 223.065 -925.966 97.0026 39.9916

278 NAVA 416210 28.358 -892.028 97.0003 39.9919
OG&E A-13 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number

Station 

Acronym

Station 

ID

LCC 

East 

(km)

LCC 

North

(km) Long Lat

279 NEWB 416270 239.111 -721.818 97.0028 39.9935

280 BPAT 417174 288.962 -1110.65 97.0034 39.9900

281 RANK 417431 -472.048 -959.488 96.9944 39.9913

282 SAAG 417943 -333.338 -952.54 96.9961 39.9914

283 SAAT 417945 -143.322 -1161.27 96.9983 39.9895

284 SHEF 418252 -463.759 -1019.19 96.9945 39.9908

285 STEP 418623 -112.988 -857.918 96.9987 39.9922

286 STER 418630 -376.683 -897.195 96.9956 39.9919

287 VALE 419270 -720.749 -1015.17 96.9915 39.9908

288 VICT 419364 6.882 -1236.45 97.0001 39.9888

289 WACO 419419 -21.834 -928.823 96.9997 39.9916

290 WATR 419499 -353.767 -916.015 96.9958 39.9917

291 WHEE 419665 57.489 -1008.99 97.0007 39.9909

292 WPDM 419916 262.792 -737.786 97.0031 39.9933

293 DORA 232302 433.256 -378.797 97.0051 39.9966

294 DIXN 112353 756.057 -267.193 97.0089 39.9976

295 DAUP 12172 864.408 -1050.41 97.0102 39.9905

296 FREV 123104 847.031 -117.884 97.0100 39.9989

297 WARR 18673 890.447 -788.703 97.0105 39.9929

298 MDTN 235562 493.264 -87.222 97.0058 39.9992
OG&E A-14 Trinity Consultants

CALMET Processing Protocol 083701.0004

TABLE A-4. LIST OF OVER WATER METEOROLOGICAL STATIONS

Number

Station 

ID

Input file 

Name

LCC 

East 

(km)

LCC North

(km) Long Lat

1 42001 42001 746.874 -1541.35 89.67 25.9

2 42002 42002 265.486 -1650.616 94.42 25.19

3 42007 42007 795.674 -1063.667 88.77 30.09

4 42019 42019 163.178 -1342.917 95.36 27.91

5 42020 42020 30.212 -1453.738 96.7 26.94

6 42035 42035 254.465 -1193.539 94.41 29.25

7 42040 42040 859.497 -1160.066 88.21 29.18

8 BURL1 42045 743.116 -1202.117 89.43 28.9

9 DPIA1 42046 861.385 -1039.466 88.07 30.25

10 GDIL1 42047 687.984 -1164.910 89.96 29.27

11 PTAT2 42048 -4.980 -1353.398 97.05 27.83

12 SRST2 42049 288.163 -1175.682 94.05 29.67