Appendix 9.6 

BART Analysis for Westar Energy - Gordon Evans Unit 2 

and Jeffrey Units 1 and 2 (including May 2009 addendum 

for GEEC) 
CALPUFF BART MODELING PROTOCOL  WESTAR ENERGY

HUTCHINSON, GORDON EVANS, JEFFREY, & LAWRENCE ENERGY CENTERS

VERSION 0 

Prepared by: 

Kasi Dubbs  Senior Consultant 

Kelli Johnson  Senior Consultant 

TRINITY CONSULTANTS

25055 West Valley Parkway 

Suite 101 

Olathe, Kansas 66061 

(913) 390-9700 

May 2006 

Project 051701.0153 
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BART Modeling Protocol 

TABLE OF CONTENTS

1. INTRODUCTION....................................................................................................1

1.1 BACKGROUND ......................................................................................................1 

1.2 OBJECTIVE............................................................................................................1 

1.3 LOCATION OF SOURCES AND RELEVANT CLASS I AREAS ........................................2 

2. CALPUFF MODEL SYSTEM................................................................................4

2.1 MODEL VERSIONS.................................................................................................4 

2.2 MODELING DOMAIN..............................................................................................5 

3. CALMET............................................................................................................6

3.1 GEOPHYSICAL DATA.............................................................................................6 

3.1.1 TERRAIN DATA .................................................................................................. 6

3.1.2 LAND USE DATA................................................................................................ 7

3.1.3 COMPILING TERRAIN AND LAND USE DATA ....................................................... 8

3.2 METEOROLOGICAL DATA......................................................................................8 

3.2.1 MESOSCALE MODEL METEOROLOGICAL DATA .................................................. 9

3.2.2 SURFACE METEOROLOGICAL DATA ................................................................... 9

3.2.3 UPPER AIR METEOROLOGICAL DATA............................................................... 10

3.2.4 PRECIPITATION METEOROLOGICAL DATA ........................................................ 12

3.3 SUMMARY OF CALMET CONTROL PARAMETERS ................................................13 

4. CALPUFF ........................................................................................................20

4.1 SOURCE EMISSIONS DATA...................................................................................20 

4.1.1 SO2 AND NOX EMISSIONS ................................................................................. 20

4.1.2 TOTAL PM10 EMISSIONS ................................................................................... 20

4.1.3 SPECIATED PM10 EMISSIONS ............................................................................ 23

4.1.4 STACK PARAMETERS........................................................................................ 29

4.2 CLASS I AREA RECEPTORS ..................................................................................31 

4.3 BACKGROUND OZONE.........................................................................................32 

4.4 BACKGROUND AMMONIA....................................................................................33 

4.5 SUMMARY OF CALPUFF CONTROL PARAMETERS...............................................33 

5. CALPOST ........................................................................................................48

5.1 LIGHT EXTINCTION ALGORITHM .........................................................................48 

5.2 CALPOST PROCESSING METHOD........................................................................48 

5.3 NATURAL BACKGROUND ....................................................................................49 

5.4 EVALUATING BART-EXEMPTION........................................................................49 

5.5 SUMMARY OF CALPOST CONTROL PARAMETERS...............................................49 

APPENDIX A..........................................................................................................................1

APPENDIX B ..........................................................................................................................1
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APPENDIX C..........................................................................................................................1

APPENDIX D..........................................................................................................................1
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LIST OF TABLES

TABLE 1-1. DISTANCE TO CLASS I AREAS ......................................................................................... 2

TABLE 2-1. CALPUFF MODELING SYSTEM VERSIONS...................................................................... 4

TABLE 3-1. SUMMARY OF CALMET INPUTS................................................................................... 14

TABLE 4-1. WESTAR BART-ELIGIBLE SOURCES NOX AND SO2 MAXIMUM ACTUAL 24-HOUR 

EMISSION RATES ................................................................................................................ 20

TABLE 4-2. ANNUAL TOTAL PM10 EMISSION ESTIMATES ............................................................... 22

TABLE 4-3. SUMMARY OF SPECIATED PM10 EMISSION ESTIMATES .................................................. 23

TABLE 4-4. HEC UNIT 4 NORTH STACK PM SPECIATION ANALYSIS (SAME FOR SOUTH STACK) ..... 24

TABLE 4-5. GEEC UNIT 2 A STACK PM SPECIATION ANALYSIS (SAME FOR B STACK).................... 24

TABLE 4-5. GEEC UNIT 2 A STACK PM SPECIATION ANALYSIS (SAME FOR B STACK).................... 25

TABLE 4-6. JEC UNIT 1 PM SPECIATION ANALYSIS ........................................................................ 26

TABLE 4-7. JEC UNIT 2 PM SPECIATION ANALYSIS ........................................................................ 27

TABLE 4-8. LEC UNIT 5 PM SPECIATION ANALYSIS ....................................................................... 27

TABLE 4-8. LEC UNIT 5 PM SPECIATION ANALYSIS ....................................................................... 28

TABLE 4-9. SUMMARY OF SPECIATED PM10 EMISSION ESTIMATES .................................................. 30

TABLE 4-10. SUMMARY OF OZONE MONITORS................................................................................ 32

TABLE 4-11. SUMMARY OF CALPUFF INPUTS................................................................................ 33

TABLE 5-1. MONTHLY HUMIDITY FACTORS.................................................................................... 48

TABLE 5-2. DEFAULT WEST AVERAGE ANNUAL NATURAL BACKGROUND LEVELS......................... 49

TABLE 5-3. SUMMARY OF CALPOST INPUTS ................................................................................. 49

TABLE A-1. DETERMINATION OF MODELING DOMAIN ...................................................................... 2

TABLE C-1. LAND USE DATA USED IN ANALYSIS ............................................................................. 2

TABLE C-2. TERRAIN DATA USED IN ANALYSIS................................................................................ 3

TABLE D-1. LIST OF SURFACE METEOROLOGCAL STATIONS.............................................................. 1
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TABLE D-2. LIST OF UPPER AIR METEOROLOGICAL STATIONS .......................................................... 2

TABLE D-3. LIST OF PRECIPITATION METEOROLOGICAL STATIONS ................................................... 2
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LIST OF FIGURES

FIGURE 1-1. LOCATION OF WESTAR FACILITIES WITH BART-ELIGIBLE SOURCES AND NEARBY 

CLASS I AREAS ..................................................................................................................... 3

FIGURE 2-1. PROPOSED MODELING DOMAIN..................................................................................... 5

FIGURE 3-1. PLOT OF LAND ELEVATION USING USGS TERRAIN DATA ............................................. 7

FIGURE 3-2. PLOT OF LAND USE USING USGS LULC DATA ............................................................. 8

FIGURE 3-3. PLOT OF SURFACE STATIONS....................................................................................... 10

FIGURE 3-4. PLOT OF UPPER AIR STATIONS .................................................................................... 11

FIGURE 3-5. PLOT OF PRECIPITATION METOROLOGICAL STATIONS.................................................. 13

FIGURE 4-1. HERCULES-GLADES WILDERNESS RECEPTOR LOCATIONS ........................................... 31

FIGURE 4-2. WICHITA MOUNTAINS RECEPTOR LOCATIONS............................................................. 32

FIGURE B-1. EXAMPLE CALMM5 INPUT FILE .................................................................................. 2

 
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1. INTRODUCTION

1.1 BACKGROUND

On July 1, 1999, the U.S. Environmental Protection Agency (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 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 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 

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. 

To promote consistency between states in the development of BART modeling protocols and to 

harmonize the approaches between adjacent RPOs, CENRAP developed BART Modeling Guidelines

(December 15, 2005). The intent of the guidelines is to assist CENRAP states and source operators in 

the development of statewide and source-specific modeling protocols. 

1.2 OBJECTIVE

The objective of this document is to provide a protocol summarizing the modeling methods and 

procedures that Westar Energy (Westar) will follow as we evaluate whether BART applies to any of 

our BART-eligible sources. Westar will use the modeling methods and procedures to determine if 

our BART-eligible sources can reasonably be anticipated to cause or contribute to visibility 

impairment in a Class I area, and are thus subject to BART. We are proposing to consider a source 
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BART Modeling Protocol 

subject to BART if the 98th percentile of the visibility impacts predicted by the model are above 

EPA’s recommended visibility contribution threshold of 0.5 'dv. 

1.3 LOCATION OF SOURCES AND RELEVANT CLASS I AREAS

Westar has identified the following sources that meet the three criteria for being BART-eligible 

sources: 

Ÿ Hutchinson Energy Center (HEC) – Boiler Unit 4 

Ÿ Gordon Evans Energy Center (GEEC)– Boiler Unit 2 

Ÿ Jeffrey Energy Center (JEC) – Boiler Units 1 and 2 

Ÿ Lawrence Energy Center (LEC) – Boiler Unit 5 

Table 1-1 provides a summary of the distances from each of our facilities with BART-eligible sources 

to nearby Class I areas. 

TABLE 1-1. DISTANCE TO CLASS I AREAS

Distance to Class I Area (km) 

Energy Center 

Badlands 

National Park 

Wind Cave 

National Park 

Hercules-Glades 

Wilderness 

Wichita 

Mountains 

GEEC 781.48 812.69 423.51 360.36 

HEC 737.12 767.48 463.08 384.36 

JEC 723.64 775.72 403.08 560.08 

LEC 797.14 851.57 331.64 569.00 

In order to determine whether the BART eligible sources listed above are subject to BART, the 

visibility impacts in the two Class I areas that are within 600 km of the sources will be determined. 

The Class I areas within 600 km include Hercules-Glades Wilderness and Wichita Mountains. Figure 

1-1 provides a plot of the location of the facilities listed above with respect to the Hercules Glades

Wilderness and Wichita Mountains. 

 
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FIGURE 1-1. LOCATION OF WESTAR FACILITIES WITH BART-ELIGIBLE SOURCES AND 

NEARBY CLASS I AREAS
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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, and CALPOST computes visibility impacts 

from a source based on the visibility affecting pollutant concentrations that were produced by 

CALPUFF. 

2.1 MODEL VERSIONS

Earth Tech, Inc. is the primary developer of the CALPUFF modeling system and all related programs. 

The versions of the CALPUFF modeling system programs that will be used for our modeling are 

listed in Table 2-1. Table 2-1 also compares the program versions that will be used to model 

Westar’s sources with the program versions recommended by CENRAP. Note that some of the 

program versions are not the same as the program versions recommended by CENRAP. The program 

versions are different due to the fact that several of the program versions recommended by CENRAP 

are incompatible with each other as published. Specifically, the MM5 data extraction program 

(CALMM5) Version 2.4 is not compatible with CALMET Version 5.53a. CALMM5 Version 2.4 is 

compatible with a newer version of CALMET, Version 5.551. Note that meteorological data that is 

generated with CALMET Version 5.551 is not compatible with CALPUFF Version 5.711a. 

CALMET Version 5.551 is compatible with CALPUFF Version 5.727. In short, alternate program 

versions are required in order to accommodate the MM5 data extraction program version, so Westar 

will use alternate versions. 

TABLE 2-1. CALPUFF MODELING SYSTEM VERSIONS

CENRAP Suggested Westar Analyses 

Program Version Level Version Level Reason for Difference 

TERREL 3.311 030709 3.311 030709 

CTGCOMP 2.42 030709 2.22 030528 Version recommended is not 

available 

CTGPROC 2.42 030709 2.42 030709 

MAKEGEO 2.22 030709 2.22 030709 

CALMM5 2.4 050413 2.4 050413 

CALMET 5.53a 040716 5.551 050310 CALMM5 v2.4 is not compatible 

with CALMET v5.53a 

CALPUFF 5.711a 040716 5.727 050309 Use version compatible with 

CALMET v5.551 

POSTUTIL 1.4 040818 1.4 040818 

CALPOST 5.51 030709 5.636 050218 Use version compatible with 

CALPUFF v5.636 
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2.2 MODELING DOMAIN

The modeling domain will extend 50 km in all directions beyond Westar’s BART-eligible sources 

and the two Class I areas of interest (HWG and WM). The map projection for the modeling domain 

will be Lambert Conformal Conic (LCC) and the coordinate system will be North American Datum 

1927 (NAD27), which is an LCC projection. The meteorological grid spacing will be 2.5 km. 

The southwest corner of the modeling domain is Latitude 34.08oN, Longitude 99.35oW which will be 

assigned as the 0, 0 reference point for the domain. The northeast corner of the modeling domain is 

approximately Latitude 39.78oN, Longitude 92.05 oW. At a grid spacing of 2.5 km, the number of X 

grid cells will be 251 and the number of Y grid cells will be 246. 

Calculations showing the determination of these domain parameters are included in Appendix A. 

Further, Figure 2-1 provides a plot of the modeling domain with respect to the sources and Class I 

areas. 

FIGURE 2-1. PROPOSED MODELING DOMAIN

-100 0 100 200 300 400 500 600 700

East (km)

-100

0

100

200

300

400

500

600

700

North (km)

Gordon Evans

Hutchinson

Jeffrey

Lawrence

Hercules Glades

Wichita Mountains
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BART Modeling Protocol 

3. CALMET

Westar will conduct a three-year CALMET analysis that incorporates both mesoscale model and 

observation meteorological data. The CALMET analysis will generate three years of data that will be 

input to CALPUFF. The CALMET model requires the input of geophysical data, meteorological 

data, and model parameter settings. The CALMET modeling procedures that will be used will 

generally follow the recommendations in CENRAP’s protocol. However, some of CENRAP’s 

recommendations only apply to CALMET analyses that incorporate mesoscale model meteorological 

data (and no observation data). Since the CALMET analysis for Westar’s modeling will be a hybrid 

analysis (mesoscale model data plus observation data), it is expected that some parameters will be 

different. 

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 from the United States Geological Survey (USGS) in 1-degree (1:250,000 

scale or approximately 90 meter resolution) digital format will be used. A list of the 

USGS terrain files is provided in Appendix C. A plot of the land elevation for the 

modeling domain based on the referenced files is provided in Figure 3-1. 
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FIGURE 3-1. PLOT OF LAND ELEVATION USING USGS TERRAIN DATA

0 100 200 300 400 500 600

East (m)

0

100

200

300

400

500

600

North (k)

Gordon Evans

Hutchinson

Jeffrey

Lawrence

Hercules Glades

Wichita Mountains -50

0

50

100

150

200

250

300

350

400

450

500

550

600

650

700

750

Meters from MSL

The USGS terrain data will be input into the TERREL program to generate grid-cell 

elevation averages across the modeling domain. 

3.1.2 LAND USE DATA

USGS Composite Theme Grid (CTG) format Land Use and Land Cover (LULC) data files 

at 1:250,000 resolution will be used, where available. Where 1:250,000 land use data is 

not available, USGS data at 1:100,000 resolution will be used. A list of the USGS land 

use files is provided in Appendix C. A plot of the land use for the modeling domain based 

on the referenced files is provided in Figure 3-2. 
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FIGURE 3-2. PLOT OF LAND USE USING USGS LULC DATA

0 100 200 300 400 500 600

East (km)

0

100

200

300

400

500

600

North (km)

Gordon Evans

Hutchinson

Jeffrey

Lawrence

Hercules Glades

Wichita Mountains

 10 to 17

 20 to 24

 30 to 33

 40 to 43

 50 to 55

Urban

Agricultural

Rangeland

Forestland

Water

The LULC data will be input into the CTGPROC program to generate land use for each 

grid cell across the modeling domain. The USGS CTG format LULC data files must be 

compressed prior to use in the CTGPROC utility processor; therefore the files will be 

compressed using the program CTGCOMP. 

3.1.3 COMPILING TERRAIN AND LAND USE DATA

The terrain data files output by the TERELL program and the LULC files output by 

CTGPROC program will be input to the program MAKEGEO to create a geophysical data 

file that will be input to 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, and 

precipitation station observations to develop the meteorological field. 
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3.2.1 MESOSCALE MODEL METEOROLOGICAL DATA

Hourly mesoscale data will be used to supplement the hourly surface, upper air, and 

precipitation observation data. The mesoscale data will be used to define the initial guess 

field for the CALMET simulations. The following 5th generation mesoscale model (MM5) 

meteorological data sets will be used: 

x 2001 MM5 data at 36 km resolution processed for EPA by Alpine Geophysics 

x 2002 MM5 data at 36 km resolution processed by Iowa DNR 

x 2003 MM5 data set at 36 km resolution processed by the Midwest RPO 

The MM5 data for the modeling domain will be extracted from the above MM5 data sets 

using the CALMM5 program. The MM5 data extraction will follow CENRAP’s 

recommendations, meaning that all vertical layers will be extracted and vertical velocity, 

relative humidity, cloud/rain fields, and ice/snow fields will be included. An example 

CALMM5 input file is provided in Appendix B. 

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. The surface stations from which data will be extracted are listed in 

Appendix D. The locations of the surface stations with respect to the modeling domain are 

shown in Figure 3-3. 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 Version 5.55, Level: 050311 of EPA’s SMERGE 

program. 
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FIGURE 3-3. PLOT OF SURFACE STATIONS

0 100 200 300 400 500 600

East (km)

-200

-100

0

100

200

300

400

500

600

700

N

orth (km)

GEEC

HEC

JEC

LEC

KABI KTYR

KACT

KCNK

KCNU

KCOU

KDFW

KEMP

KFSM

KFYV

KHBR

KHOT

KICT

KIRK

KJLN

KMCI

KMHK

KMLC

KOCH

KOKC

KPNC

KPRX

KSGF

KSHV

KSLN

KSPS

KSTJ

KSZL

KTOP

KTUL

KTXK

K1F0

Hercules Glades

Wichita Mountains

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 Kansas) and 

1200 GMT (6 o’clock AM in Kansas). Sensors observe pressure, wind speed and 

direction, and temperature (among other parameters) as the balloon rises through the 
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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 from data will be extracted are listed 

in Appendix D. 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 Version 5.52a, Level: 040716 of 

EPA’s READ62 program. 

FIGURE 3-4. PLOT OF UPPER AIR STATIONS

0 100 200 300 400 500 600

East (km)

-200

-100

0

100

200

300

400

500

600

700

N

orth (km)

GEEC

HEC

JEC

LEC

KOUN

KLZK

KFWD

KSHV

KSGF

KTOP

Hercules Glades

Wichita Mountains
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3.2.4 PRECIPITATION METEOROLOGICAL DATA

The effects of chemical transformations 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 from 

which data will be extracted are listed in Appendix D. 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 Version 

5.31, Level: 030528 of EPA’s PMERGE program. 
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FIGURE 3-5. PLOT OF PRECIPITATION METOROLOGICAL STATIONS

0 100 200 300 400 500 600

East (km)

-200

-100

0

100

200

300

400

500

600

700

N

orth (km)

GEEC

HEC

JEC

LEC

ALUM

ANTO

ARKA

BLAK

BOON

BRIG

CAMD

CLAR

DE QDIER

FORE

FORT

LEWIMAGN

MENA

NIMR

PRES

TEXA

WALD

MANS

MIND

NATC

SHRE RED 

ALTU

ARDM

BENG

CANE CART

CHAN

CHIC

CUST

DUNC

ELK 

FORT

GEAR

HENN

HOBA

KING

LAKE

LEHI

MACK

MARS

MCAL

MUSK

OKAR

OKEM OKLA

ROFF WICH TUSK

WIST

WOLF

ABIL

BONI

BURL

CHIL

CLAR

COMM

CRAN

CRES

CROS

DALL DALL

DENT

EAST

FERR

FORT

GAIN

GILM

GORD

GROE

HICO

HONE

JACK

KOPP

LAKE

MABA LONG

MINE

MOLI

MOUN

NACO

NAVA

NEW 

NEW 

PALE

PAT 

PITT

PROC

RED 

RENO

SANT

STAM

STEP

SULP

SWAN

TRUS

WACO

WEAT

WELL

WHIT

WICH

WINC

WOOD

WRIG

HARR NORF

ARLI

CALD

CHAN

CONC

COUN

IONI

KIOW

MARY

MILF

SALI

TOPE

UNIO

WICH

APPL

BOLI

CASS

COLU

DORA

JOPL

KANS

KIRK

LEBA

MOUN

NEVA

SPRI

TABL

TRUM

AMES

PONC

TULS

3.3 SUMMARY OF CALMET CONTROL PARAMETERS

Table 3-1 provides a listing of the CALMET parameters will be used in the modeling analysis. In 

addition to the parameters that will be used for the modeling, the table also lists CENRAP’s 

recommended parameters for comparison. In cases where a parameter to be used is different than 

what CENRAP recommended, a short explanation as to the difference is proved. Note that most of 

the differences from CENRAP’s recommended parameters are due to the inclusion of observation 

data into the modeling analysis, since CENRAP’s parameters are based on a no-observation analysis. 
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TABLE 3-1. SUMMARY OF CALMET INPUTS

CALMET 

Variable Description 

Value 

Included in 

CENRAP 

Protocol 

Value Westar 

Will Use Notes 

NUSTA Number of upper air data 

sites 

0 6 Will use observations 

NOWSTA Number of overwater data 

sites 

0 0 

IBYR Starting year 2001 Appropriate 

met year 

Years 2001, 2002, 2003 

IBMO Starting month 1 Appropriate 

month 

Due to file size, analysis 

will be completed by 

month 

IBHR Starting hour 1 1 

IBTZ Base time zone 6 6 

IRLG Length of run 6 Varies with 

month 

Due to file size, analysis 

will be completed by 

month 

IRTYPE Run type (1 for 

CALPUFF) 

1 1 

LCALGRD Compute CALFRID data 

fields (T = run CALGRID) 

F F 

ITEST Stop run after SETUP to 

do input QA (2 = run) 

2 2 

PMAP Map projection LCC LCC 

RLAT0 Latitude (decimal degrees) 

of projection origin 

40N 34.0825N Appropriate for domain 

RLON0 Longitude (decimal 

degrees) of projection 

origin 

97W 99.3476W Appropriate for domain 

XLAT1 Latitude of 1st standard 

parallel 

33N 34N Appropriate for domain 

XLAT2 Latitude of 2nd standard 

parallel 

45N 40N Appropriate for domain 

DATUM Datum region for output 

coordinates 

WGS-G NAS-C Selected datum to match 

datum of land use data 

NX Number of X grid cells in 

meteorological grid 

300 251 Appropriate for domain 

NY Number of Y grid cells in 

meteorological grid 

192 246 Appropriate for domain 

DGRIDKM Grid spacing (km) 6.0 2.5 Refined grid spacing 

XORIGKM Ref. coordinate of SW 

corner of grid cell 

-1008 0 Appropriate for domain 

YORIGKM Ref. coordinate of SW 

corner of grid cell 

0.0 0 Appropriate for domain 

NZ Number of vertical layers 10 10 

ZFACE Vertical cell face heights 

(NZ + 1 values) 

0, 20, 40, 80, 

160, 320, 640, 

1200, 2000, 

3000, 4000 

0, 20, 40, 80, 

160, 320, 640, 

1200, 2000, 

3000, 4000 
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CALMET 

Variable Description 

Value 

Included in 

CENRAP 

Protocol 

Value Westar 

Will Use Notes 

LSAVE Save met. data fields in an 

unformatted file? 

T T 

IFORMO Type of unformatted 

output file (1 for 

CALPUFF) 

1 1 

LPRINT Print met. fields F F 

IPRINF Print intervals 1 1 

IUVOUT(NZ) Specify layers of u,v wind 

components to print 

NZ*0 NZ*0 

IWOUT(NZ) Specify layers of w wind 

component to print 

NZ*0 NZ*0 

ITOUT(NZ) Specify layers of 3D 

temperature field to print 

NZ*0 NZ*0 

LDB Print met data and 

variables 

F F 

NN1 First time step for debug 

data to be printed 

1 1 

NN2 Last time step for debug 

data to be printed 

1 2 Will generate debug data 

for a total of 2 time steps 

IOUTD Control variable for 

writing test/debug wind 

fields 

0 0 

NZPRN2 Number of levels starting 

at surface to print 

0 1 Default 

IPRO Print interpolated wind 

components 

0 0 

IPR1 Print terrain adjusted 

surface wind components 

0 0 

IPR2 Print initial divergence 

fields 

0 0 

IPR3 Print final wind speed and 

direction 

0 0 

IPR4 Print final divergence 

fields 

0 0 

IPR5 Print winds after kinematic 

effects 

0 0 

IPR6 Print winds after Froude 

number adjustment 

0 0 

IPR7 Print winds after slope 

flows are added 

0 0 

IPR8 Print final wind field 

components 

0 0 

NOOBS No observation mode (2 = 

No surface, overwater, or 

upper air observations; use 

MM5 for surface, 

overwater, and upper air 

data) 

2 0 Will use observations 

NSSTA Number of meteorological 

stations in SURF.DAT file 

0 32 Number of stations 
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CALMET 

Variable Description 

Value 

Included in 

CENRAP 

Protocol 

Value Westar 

Will Use Notes 

NPSTA Number of precipitation 

stations in PRECIP.DAT 

file 

0 138 Number of stations 

ICLOUD Gridded cloud fields (0 = 

no, 3 = Gridded cloud 

cover from prognostic 

relative humidity) 

3 3 

IFORMS Format of surface data (2 

= formatted) 

2 2 

IFORMP Format of precipitation 

data (2 = formatted) 

2 2 

IFORMC Format of cloud data (2 = 

formatted) 

2 1 N/A - No cloud data 

used in model 

IWFCOD Generate winds by 

diagnostic wind module? 

(1 = yes) 

1 1 

IFRADJ Adjust winds using Froude 

number effects? (1 = yes) 

1 1 

IKINE Adjust winds using 

kinematic effects? (0 = no) 

0 1 Will compute kinematic 

effects in this analysis 

IOBR Use O’Brien procedure for 

vertical winds? (0 = no) 

0 0 

ISLOPE Compute slope flows? (1 = 

yes) 

1 1 

IEXTRP Extrapolate surface winds 

to upper layers (-1 = no 

extrapolation and ignore 

layer 1 of upper air station 

data) 

-1 -4 -4 = Since observations 

are included in model, 

will use similarity theory 

and ignore layer 1 of 

upper air station data 

(FLAG default) 

ICALM Extrapolate surface winds 

even if calm? (0 = no) 

0 0 

BIAS Layer dependent biases 

weighting aloft 

measurements 

0, 0, 0, 0, 0, 0, 

0, 0, 0, 0 

0, 0, 0, 0, 0, 0, 

0, 0, 0, 0 

RMIN2 Minimum vertical 

extrapolation distance 

Distance (km) around an 

upper air site where 

vertical extrapolation is 

excluded (set to –1 if 

IEXTRP = ± 4) 

-1 -1 

IPROG Using prognostic or MMFDDA data? (14 = Use 

winds from MM5.DAT as 

initial guess wind field) 

14 14 

ISTEPPG Timestep (hours) of the 

MM5 data 

1 1 
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CALMET 

Variable Description 

Value 

Included in 

CENRAP 

Protocol 

Value Westar 

Will Use Notes 

LVARY Use varying radius of 

influence to develop 

surface winds? 

T F Use FLAG default 

RMAX1 Maximum radius of 

influence over land in 

surface layer (km) 

30 36 Same as MM5 data 

spacing 

RMAX2 Maximum radius of 

influence over land aloft 

(km) 

30 36 Same as MM5 data 

spacing 

RMAX3 Maximum radius of 

influence over water (km) 

50 36 Same as MM5 data 

spacing 

RMIN Minimum radius of 

influence used anywhere 

(km) 

0.1 0.1 

TERRAD Radius of influence of 

terrain features (km) 

12 12 

R1 Weighting of first guess 

surface field (km) 

1 1 

R2 Weighting of first guess 

aloft field (km) 

1 1 

RPROG MM5 windfield weighting 

parameter (km) 

0 0 

DIVLIM Maximum acceptable 

divergence 

5.E-6 5.E-6 

NITER Max number of passes in 

divergence minimization 

50 50 

NSMTH Number of passes through 

smoothing filter in each 

layer of CALMET (NZ 

values) 

2, 4, 4, 4, 4, 4, 

4 

2, 4, 4, 4, 4, 4, 

4, 4, 4, 4 

NITR2 Max number of stations 

used in each layer for the 

interpolation of data to a 

grid point (NZ values) 

5, 5, 5, 5, 5, 5, 

5, 5, 5, 5 

5, 5, 5, 5, 5, 5, 

5, 5, 5, 5 

CRITFM Critical Froude number 1.0 1.0 

ALPHA Kinematic effects 

parameter 

0.1 0.1 

FEXTR2 Scaling factor for 

extrapolating surface 

winds aloft 

NZ*0.0 NZ*0.0 

NBAR Number of terrain barriers 0 0 

IDIOTP1 Compute temperature 

from observations (0 = 

true) 

0 0 

ISURFT Surface station to use for 

surface temperature 

(between 1 and NSSTA) 

4 4 

IDIOPT2 Domain-averaged wind 

component switch 

0 0 
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CALMET 

Variable Description 

Value 

Included in 

CENRAP 

Protocol 

Value Westar 

Will Use Notes 

IUPT Station for lapse rates 

(between 1 and NUSTA) 

2 2 

ZUPT Depth through which lapse 

rate is calculated 

200 200 

IDIOPT3 Domain averaged wind 

component switch 

0 0 

IUPWND Upper air station for 

domain winds 

-1 -1 

ZUPWND Bottom and top of layer 

through which the domain 

scale winds are computed 

1., 1000. 1., 1000. 

IDIOPT4 Observed surface wind 

component switch 

0 0 

IDIOPT5 Observed aloft wind 

component switch 

0 0 

LLBREZE Use lake breeze module? F F 

NBOX Number of lake breeze 

regions 

0 0 

NLB Number of stations in the 

region 

0 0 

METBXID(NLB) Station IDs in the region 0 0 

CONSTB Neutral stability mixing 

height coefficient 

1.41 1.41 

CONSTE Convective stability 

mixing height coefficient 

0.15 0.15 

CONSTN Stable stability mixing 

height coefficient 

2400 2400 

CONSTW Overwater mixing height 

coefficient 

0.16 0.16 

FCORIOL Absolute value of Coriolis 

parameter 

1.E-4 1.E-4 

IAVEZI Conduct spatial 

averaging? (1 = yes) 

1 1 

MNMDAV Max search radius in 

averaging process (number 

of grid cells) 

10 10 

HAFANG Half-angle of upwind 

looking cone for averaging 

(degrees) 

30 30 

ILEVZI Layers of wind use in 

upwind averaging 

(between 1 and NZ) 

1 1 

DPTMIN Minimum potential 

temperature lapse rate in 

the stable layer above the 

current convective mixing 

height 

0.001 0.001 
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BART Modeling Protocol 

CALMET 

Variable Description 

Value 

Included in 

CENRAP 

Protocol 

Value Westar 

Will Use Notes 

DZZI Depth of layer above 

current convective mixing 

height through which lapse 

rate is computed (m) 

200 200 

ZIMIN Minimum overland mixing 

height (m) 

50 50 

ZIMAX Maximum overland 

mixing height (m) 

3000 3000 

ZIMINW Minimum overwater 

mixing height (m) 

50 50 

ZIMAXW Maximum overwater 

missing height (m) 

3000 3000 

ITPROG 3D temperature from 

observations or from 

MM5? 

2 0 Will use surface and 

upper air observations 

IRAD Type of interpolation (1 = 

1/r) 

1 1 

TRADKM Temperature interpolation 

radius of influence (km) 

36 36 

NUMTS Max number of stations 

for temperature 

interpolations 

5 5 

IAVET Spatially average 

temperature? (1 = yes) 

1 1 

TGDEFB Temperature gradient 

below the mixing height 

over water (K/m) 

-.0098 -0.0098 

TGDEFA Temperature gradient 

above the mixing height 

over water (K/m) 

-.0045 -0.0045 

JWAT1 Beginning land use 

categories over water 

55 55 

JWAT2 Ending land use categories 

for water 

55 55 

NFLAGP Precipitation interpolation 

flag (2 = 1/r2) 

2 2 

SIGMAP Radius of influence for 

precipitation interpolation 

(km) 

50 50 

CUTP Minimum precipitation 

rate cut off (mm/hr) 

0.01 0.01 
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4. CALPUFF

Westar will conduct a three-year CALPUFF analysis. The CALPUFF model requires the input of 

meteorological data output by CALMET, source emissions data, receptor data, ozone and ammonia 

data, and model parameter settings. 

4.1 SOURCE EMISSIONS DATA

Westar will include emissions of SO2, NOx, and PM10 in the model. 

4.1.1 SO2 AND NOX EMISSIONS 

The SO2 and NOx emissions that will be included in the model are the 98th percentile of the 2002-

2004 24-hour highest actual emissions rates, excluding periods of startup, shutdown, and malfunction. 

Table 4-1 provides a summary of these emission rates. Note that these are the same emission rates 

that Westar has previously provided to the KDHE as part of KDHE’s request for information related 

to BART modeling. 

TABLE 4-1. WESTAR BART-ELIGIBLE SOURCES NOX AND SO2 MAXIMUM ACTUAL 24-HOUR 

EMISSION RATES

SO2

(tons/24-hour) 

NOx

(tons/24-hour)

SO2

(lbs/hour) 

NOx

(lbs/hour)

LEC Unit 5 22.9 13.2 1908.3 1100.0 

JEC Unit 1 78.2 41.2 6516.7 3433.3 

JEC Unit 2 81.5 41.3 6791.7 3441.7 

HEC Unit 4 (North Stack) 14.7 2.35 1225.0 195.8 

HEC Unit 4 (South Stack) 14.7 2.35 1225.0 195.8 

GEEC Evans Unit 2 (A Stack) 25.5 12.1 2125.0 1004.2 

GEEC Evans Unit 2 (B Stack) 25.5 12.1 2125.0 1004.2 

4.1.2 TOTAL PM10 EMISSIONS

The PM10 emissions that will be included in the model are based on an estimate as to the 98th

percentile of the 2002-2004 24-hour highest actual emissions rates. The method for estimating the 

98th percentile of the 2002-2004 24-hour highest actual PM10 emissions rates is described below. 

The 2002-2004 total annual calendar year PM10 emission rates were calculated by multiplying the 

annual fuel throughputs by the specific filterable and condensable AP-42 emission factors. Once the 

total annual PM10 emissions were determined based on AP-42, the annual emissions were divided by 

365 days to determine the average actual 24-hour emission rate. Next, the average actual 24-hour 
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BART Modeling Protocol 

PM10 emission rates for each calendar year were averaged to determine the 2002-2004 actual average 

24-hour emission rate. The maximum actual 24-hour emission rate was derived from the actual 

average 24-hour emission rate by multiplying the actual average 24-hour emission rate by a scaling 

factor. The scaling factor was derived as described below. 

First, the 2002-2004 calendar year average actual 24-hour SO2 emission rates (estimated as the actual 

annual emissions divided by 365 days per year) were determined. Next, the average 24-hour SO2

emission rates for each calendar year were averaged to determine the 2002-2004 actual average 24-

hour emission rate. Then, the 2002-2004 maximum actual 24-hour SO2 emission rates that were 

listed in Table 4-1 were divided by the 2002-2004 actual average 24-hour emission rates. This value 

is the SO2 scaling factor. The same procedure was followed to determine the NOx scaling factor. The 

average of the SO2 and NOx scaling factors was selected as the multiplier to convert the maximum 

actual average 24-hour PM10 emission rates to the maximum actual 24-hour PM10 emission rates. 

Table 4-2 provides a summary of the total PM10 emissions estimates using the methodology described 

above. 
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TABLE 4-2.

ANNUAL 

TOTAL 

P

M10

EMISSION 

ESTIMATES
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BART Modeling Protocol 

4.1.3 SPECIATED PM10 EMISSIONS

The PM10 emissions will be speciated according to FLM guidance to include the following: 

x Coarse particulate matter (PMC) 

x Fine particulate matter (PMf) 

x Sulfates (SO4) 

x Secondary organic aerosols (SOA) 

x Elemental carbon (EC) 

The PM10 emissions will be speciated according to the default speciation profiles prepared by the 

FLM’s. Table 4-3 provides a summary of the proposed speciated emission rates that will be included 

in the model. Tables 4-4 through 4-8 provide the speciation methodology using the FLM speciation 

guidelines. Note that there currently is no guidance for speciation of PM from a coal boiler with a 

wet scrubber (LEC Unit 5). Thus, Westar will speciate PM from LEC Unit 5 using the speciation 

profile for PC boilers with ESPs. 

TABLE 4-3. SUMMARY OF SPECIATED PM10 EMISSION ESTIMATES

SO4 

(tons/ 

24-hour) 

PMc 

(tons/ 

24-hour) 

PMf 

(tons/ 

24-hour) 

SOA 

(tons/ 

24-hour) 

EC 

(tons/ 

24-hour) 

Total PM10

(tons/ 

24-hour) 

LEC Unit 5 1.152 0.551 0.425 0.288 0.016 2.43 

JEC Unit 1 1.939 0.593 0.457 0.485 0.018 3.49 

JEC Unit 2 1.849 0.565 0.436 0.462 0.017 3.33 

HEC Unit 4 (North Stack) 0.070 0.206 0.513 0.012 0.041 0.84 

HEC Unit 4 (South Stack) 0.070 0.206 0.513 0.012 0.041 0.84 

GEEC Evans Unit 2 (A Stack) 0.125 0.338 0.842 0.022 0.067 1.39 

GEEC Evans Unit 2 (B Stack) 0.125 0.338 0.842 0.022 0.067 1.39 

SO4 

(lbs/hr) 

PMc 

(lbs/hr) 

PMf 

(lbs/hr) 

SOA 

(lbs/hr) 

EC 

(lbs/hr) 

Total PM10

(lbs/hr) 

LEC Unit 5 96.0 45.9 35.4 24.0 1.4 202.6 

JEC Unit 1 161.6 49.4 38.1 40.4 1.5 290.9 

JEC Unit 2 154.1 47.1 36.3 38.5 1.4 277.4 

HEC Unit 4 (North Stack) 5.8 17.2 42.7 1.0 3.4 70.2 

HEC Unit 4 (South Stack) 5.8 17.2 42.7 1.0 3.4 70.2 

GEEC Evans Unit 2 (A Stack) 10.4 28.2 70.1 1.8 5.6 116.2 

GEEC Evans Unit 2 (B Stack) 10.4 28.2 70.1 1.8 5.6 116.2 
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TABLE 4-4. HEC UNIT 4 NORTH STACK PM SPECIATION ANALYSIS (SAME FOR SOUTH STACK) 

Controlled PM10 Speciation from AP-42 Tables 1.3-2 & 1.3-4Uncontrolled Utility Residual Oil Boiler assumes firing of # 6 oil with a sulfur content of 1.77 %S; therefore, A = 2.356133333 Assume heating value of 156,270 Btu/Gal f(RH) = 1

Uncontrolled PM10 Emissions (Bold Values from Tables 1.3-2 and 1.3-4.)

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle CPM OR

Type (lb/mGal) (lb/mGal) (lb/mGal) Coef. (lb/mGal) (lb/mGal) Coef. (lb/mGal) Coef. (lb/mGal) (lb/mGal) Type Ext.Coef. (lb/mGal)

Utility 15.40 13.90 3.77 0.6 10.13 9.38 1 0.75 10 1.5 1.28 SO4 3*f(RH) 0.23

Uncontrolled PM10 Emissions

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle CPM OR

Type (% of Total) (% of Total) (% of Total) Coef. (% of Total) (% of Total) Coef. (% of Total) Coef. (% of Total) (% of Total) Type Ext.Coef. (% of Total)

Utility 100% 90.3% 24.5% 0.6 65.8% 60.9% 1 4.9% 10 9.7% 8.3% SO4 3*f(RH) 1.5%

Uncontrolled PM10 Emissions 

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle CPM OR

Type (lb/mmBtu) (lb/mmBtu) (lb/mmBtu) Coef. (lb/mmBtu) (lb/ton) Coef. (lb/mmBtu) Coef. (lb/mmBtu) (lb/mmBtu) Type Ext.Coef. (lb/mmBtu)

Utility 0.10 0.09 0.02 0.6 0.06 0.06 1 0.005 10 0.01 0.01 SO4 3*f(RH) 0.001

If you are given Total PM10 emissions in lb/hr:

Uncontrolled PM10 Emissions (Bold Value is Input by user.)

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle CPM OR

Type (lb/hr) (lb/hr) (lb/hr) Coef. (lb/hr) (lb/hr) Coef. (lb/hr) Coef. (lb/hr) (lb/hr) Type Ext.Coef. (lb/hr)

Utility 70.2 63.3 17.2 0.6 46.2 42.7 1 3.4 10 6.8 5.8 SO4 3 1.0

Weighted Extinction 10.3 42.7 34.2 17.4

Coarse 24.5% Coarse 17.2Fine Soil 60.9% Fine Soil 42.7Fine EC 4.9% Fine EC 3.4CPM IOR 8.3% CPM IOR 5.8CPM OR 1.5% CPM OR 1.0

100.0% 70.2
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TABLE 4-5. GEEC UNIT 2 A STACK PM SPECIATION ANALYSIS (SAME FOR B STACK) 

Controlled PM10 Speciation from AP-42 Tables 1.3-2 & 1.3-4

Uncontrolled Utility Residual Oil Boiler 

assumes firing of # 6 oil with a sulfur content of 1.59 %S; therefore, A = 2.154533333 Assume heating value of 156,052 Btu/Gal f(RH) = 1

Uncontrolled PM10 Emissions (Bold Values from Tables 1.3-2 and 1.3-4.)

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle 

Type (lb/mGal) (lb/mGal) (lb/mGal) Coef. (lb/mGal) (lb/mGal) Coef. (lb/mGal) Coef. (lb/mGal) (lb/mGal) Type Ext.Coef.

Utility 14.21 12.71 3.45 0.6 9.26 8.58 1 0.69 10 1.5 1.28 SO4 3*f(RH)

Uncontrolled PM10 Emissions

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle 

Type (% of Total) (% of Total) (% of Total) Coef. (% of Total) (% of Total) Coef. (% of Total) Coef. (% of Total) (% of Total) Type Ext.Coef.

Utility 100% 89.4% 24.3% 0.6 65.2% 60.4% 1 4.8% 10 10.6% 9.0% SO4 3*f(RH)

Uncontrolled PM10 Emissions 

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle 

Type (lb/mmBtu) (lb/mmBtu) (lb/mmBtu) Coef. (lb/mmBtu) (lb/ton) Coef. (lb/mmBtu) Coef. (lb/mmBtu) (lb/mmBtu) Type Ext.Coef.

Utility 0.09 0.08 0.02 0.6 0.06 0.05 1 0.004 10 0.01 0.01 SO4 3*f(RH)

If you are given Total PM10 emissions in lb/hr:

Uncontrolled PM10 Emissions (Bold Value is Input by user.)

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle 

Type (lb/hr) (lb/hr) (lb/hr) Coef. (lb/hr) (lb/hr) Coef. (lb/hr) Coef. (lb/hr) (lb/hr) Type Ext.Coef.

Utility 116.2 103.9 28.2 0.6 75.7 70.1 1 5.6 10 12.3 10.4 SO4 3

Weighted Extinction 16.9 70.1 56.0 31.3

Coarse 24.3% Coarse 28.2

Fine Soil 60.4% Fine Soil 70.1

Fine EC 4.8% Fine EC 5.6

CPM IOR 9.0% CPM IOR 10.4

CPM OR 1.6% CPM OR 1.8

100.0% 116.2
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TABLE 4-6. JEC UNIT 1 PM SPECIATION ANALYSIS

Controlled PM10 Speciation from AP-42 Tables 1.1-5 & 1.1-6

Dry Bottom Boiler burning Pulverized Coal using only ESP for Emissions control

assumes heating value of 12071.5 Btu/lb and a sulfur content of 0.55 % and an ash content of 4.82 % and f(RH) = 1

Controlled PM10 Emissions (Bold values from Table 1.1-5.)

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle 

Type (lb/mmBtu) (lb/mmBtu) (lb/mmBtu) Coef. (lb/mmBtu) (lb/ton) Coef. (lb/mmBtu) Coef. (lb/mmBtu) (lb/mmBtu) Type Ext.Coef.

PC-DB 0.0353 0.0108 0.0060 0.6 0.0048 0.0046 1 0.00018 10 0.025 0.020 SO4 3*f(RH)

Controlled PM10 Emissions (Bold Values from Table 1.1-6.)

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle 

Type (lb/ton) (lb/ton) (lb/ton) Coef. (lb/ton) (lb/ton) Coef. (lb/ton) Coef. (lb/ton) (lb/ton) Type Ext.Coef.

PC-DB 0.852 0.260 0.145 0.6 0.116 0.111 1 0.0043 10 0.592 0.473 SO4 3*f(RH)

Controlled PM10 Emissions

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle 

Type (% of Total) (% of Total) (% of Total) Coef. (% of Total) (% of Total) Coef. (% of Total) Coef. (% of Total) (% of Total) Type Ext.Coef.

PC-DB 100% 30.6% 17.0% 0.6 13.6% 13.1% 1 0.5% 10 69.4% 55.5% SO4 3*f(RH)

If you are given Total PM10 emissions in lb/hr:

Controlled PM10 Emissions (Bold Value is Input by user.)

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle 

Type (lb/hr) (lb/hr) (lb/hr) Coef. (lb/hr) (lb/hr) Coef. (lb/hr) Coef. (lb/hr) (lb/hr) Type Ext.Coef.

PC-DB 290.9 88.9 49.4 0.6 39.5 38.1 1 1.5 10 202.0 161.6 SO4 3

Weighted Extinction 29.6 38.1 14.6 484.7

Coarse 17.0% Coarse 49.4

Fine Soil 13.1% Fine Soil 38.1

Fine EC 0.5% Fine EC 1.5

CPM IOR 55.5% CPM IOR 161.6

CPM OR 13.9% CPM OR 40.4

100.0% 290.9
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TABLE 4-7. JEC UNIT 2 PM SPECIATION ANALYSIS

Controlled PM10 Speciation from AP-42 Tables 1.1-5 & 1.1-6

Dry Bottom Boiler burning Pulverized Coal using only ESP for Emissions control

assumes heating value of 12071.5 Btu/lb and a sulfur content of 0.55 % and an ash content of 4.82 % and f(RH) = 1

Controlled PM10 Emissions (Bold values from Table 1.1-5.)

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle 

Type (lb/mmBtu) (lb/mmBtu) (lb/mmBtu) Coef. (lb/mmBtu) (lb/ton) Coef. (lb/mmBtu) Coef. (lb/mmBtu) (lb/mmBtu) Type Ext.Coef.

PC-DB 0.0353 0.0108 0.0060 0.6 0.0048 0.0046 1 0.00018 10 0.025 0.020 SO4 3*f(RH)

Controlled PM10 Emissions (Bold Values from Table 1.1-6.)

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle 

Type (lb/ton) (lb/ton) (lb/ton) Coef. (lb/ton) (lb/ton) Coef. (lb/ton) Coef. (lb/ton) (lb/ton) Type Ext.Coef.

PC-DB 0.852 0.260 0.145 0.6 0.116 0.111 1 0.0043 10 0.592 0.473 SO4 3*f(RH)

Controlled PM10 Emissions

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle 

Type (% of Total) (% of Total) (% of Total) Coef. (% of Total) (% of Total) Coef. (% of Total) Coef. (% of Total) (% of Total) Type Ext.Coef.

PC-DB 100% 30.6% 17.0% 0.6 13.6% 13.1% 1 0.5% 10 69.4% 55.5% SO4 3*f(RH)

If you are given Total PM10 emissions in lb/hr:

Controlled PM10 Emissions (Bold Value is Input by user.)

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle 

Type (lb/hr) (lb/hr) (lb/hr) Coef. (lb/hr) (lb/hr) Coef. (lb/hr) Coef. (lb/hr) (lb/hr) Type Ext.Coef.

PC-DB 277.4 84.8 47.1 0.6 37.7 36.3 1 1.4 10 192.6 154.1 SO4 3

Weighted Extinction 28.3 36.3 13.9 462.2

Coarse 17.0% Coarse 47.1

Fine Soil 13.1% Fine Soil 36.3

Fine EC 0.5% Fine EC 1.4

CPM IOR 55.5% CPM IOR 154.1

CPM OR 13.9% CPM OR 38.5

100.0% 277.4
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BART Modeling Protocol 

TABLE 4-8. LEC UNIT 5 PM SPECIATION ANALYSIS

Controlled PM10 Speciation from AP-42 Tables 1.1-5 & 1.1-6

Dry Bottom Boiler burning Pulverized Coal using only ESP for Emissions control

assumes heating value of 12040 Btu/lb and a sulfur content of 0.49 % and an ash content of 5.84 % and f(RH) = 1

Controlled PM10 Emissions (Bold values from Table 1.1-5.)

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle CPM OR

Type (lb/mmBtu) (lb/mmBtu) (lb/mmBtu) Coef. (lb/mmBtu) (lb/ton) Coef. (lb/mmBtu) Coef. (lb/mmBtu) (lb/mmBtu) Type Ext.Coef. (lb/mmBtu)

PC-DB 0.0321 0.0131 0.0073 0.6 0.0058 0.0056 1 0.00022 10 0.019 0.015 SO4 3*f(RH) 0.004

Controlled PM10 Emissions (Bold Values from Table 1.1-6.)

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle CPM OR

Type (lb/ton) (lb/ton) (lb/ton) Coef. (lb/ton) (lb/ton) Coef. (lb/ton) Coef. (lb/ton) (lb/ton) Type Ext.Coef. (lb/ton)

PC-DB 0.773 0.315 0.175 0.6 0.140 0.135 1 0.0052 10 0.458 0.366 SO4 3*f(RH) 0.092

Controlled PM10 Emissions

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle CPM OR

Type (% of Total) (% of Total) (% of Total) Coef. (% of Total) (% of Total) Coef. (% of Total) Coef. (% of Total) (% of Total) Type Ext.Coef. (% of Total)

PC-DB 100% 40.8% 22.7% 0.6 18.1% 17.5% 1 0.7% 10 59.2% 47.4% SO4 3*f(RH) 11.8%

If you are given Total PM10 emissions in lb/hr:

Controlled PM10 Emissions (Bold Value is Input by user.)

Boiler Total PM10 Filterable Coarse Ext. Fine Fine Soil Ext. Fine EC Ext. Condensible CPM IOR Particle CPM OR

Type (lb/hr) (lb/hr) (lb/hr) Coef. (lb/hr) (lb/hr) Coef. (lb/hr) Coef. (lb/hr) (lb/hr) Type Ext.Coef. (lb/hr)

PC-DB 202.6 82.7 45.9 0.6 36.7 35.4 1 1.4 10 120.0 96.0 SO4 3 24.0

Weighted Extinction 27.6 35.4 13.6 287.9

Coarse 22.7% Coarse 45.9

Fine Soil 17.5% Fine Soil 35.4

Fine EC 0.7% Fine EC 1.4

CPM IOR 47.4% CPM IOR 96.0

CPM OR 11.8% CPM OR 24.0

100.0% 202.6
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BART Modeling Protocol 

4.1.4 STACK PARAMETERS

Table 4-9 provides a summary of the exhaust characteristics that will be modeled, including a 

summary of the emission rates presented elsewhere in this protocol for the BART-eligible sources. 
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BART Modeling Protocol 

TABLE 4-9. SUMMARY OF SPECIATED PM10 EMISSION ESTIMATES

 LEC Unit 5 JEC Unit 1 JEC Unit 2 

HEC Unit 4 

(South Stack) 

HEC Unit 4 

(North Stack) 

GEEC Unit 2 

(A Stack) 

GEEC Unit 2 

(B Stack) 

Latitude (degrees) 39.007 39.287 39.287 38.092 38.092 37.793 37.793 Longitude (degrees) 95.275 96.116 96.116 97.873 97.873 97.518 97.518 Stack height (ft) 355 600 600 149 149 197 197 Stack Diameter (ft) 18.5 26.0 26.0 8.0 8.0 13.0 13.0 Exhaust Velocity (ft/s) 80.0 91.3 91.3 56.0 56.0 69.0 69.0 Exhaust Temperature (F) 166 300 300 313 313 290 290NOx (lb/hr) 1100.0 3433.3 3441.7 195.8 195.8 1004.2 1004.2 SO2 (lb/hr) 1908.3 6516.7 6791.7 1225.0 1225.0 2125.0 2125.0 SO4 (lb/hr) 96.0 161.6 154.1 5.8 5.8 10.4 10.4 PMc (lb/hr) 45.9 49.4 47.1 17.2 17.2 28.2 28.2 PMf (lb/hr) 35.4 38.1 36.3 42.7 42.7 70.1 70.1 SOA (lb/hr) 24.0 40.4 38.5 1.0 1.0 1.8 1.8 EC (lb/hr) 1.4 1.5 1.4 3.4 3.4 5.6 5.6 
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BART Modeling Protocol 

4.2 CLASS I AREA RECEPTORS 

The National Park Service (NPS) has electronic files for each Class I area available on their website 

containing the locations and elevations of discrete Class I area receptors. The receptor files for 

Hercules-Glades Wilderness and the Wichita Mountains will be downloaded from the NPS website, 

converted into the LCC NAD27 projection, and incorporated into the CALPUFF model. The receptor 

locations for the Hercules-Glades Wilderness are show in Figure 4-1, and the locations for Wichita 

Mountains are shown in Figure 4-2. 

FIGURE 4-1. HERCULES-GLADES WILDERNESS RECEPTOR LOCATIONS
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BART Modeling Protocol 

FIGURE 4-2. WICHITA MOUNTAINS RECEPTOR LOCATIONS

4.3 BACKGROUND OZONE

Background ozone concentrations are required in order to model the photochemical conversion of 

SO2 and NOx to sulfates (SO4

) and nitrates (NO3). CALPUFF can use either a single background 

value representative of an area or hourly ozone data from one or more ozone monitoring stations. 

CENRAP recommends either developing background ozone estimates from ambient monitors located 

within the particular domain being modeled or developing background ammonia estimates from 

CENRAP’s most recent CMAQ or CAMx simulation for the 2002 base year. Westar is proposing to 

incorporate hourly ozone data from three rural ozone monitors across the state of Kansas. The three 

monitors are listed in Table 4-10. 

TABLE 4-10. SUMMARY OF OZONE MONITORS

Monitor ID County Latitude Longitude 

201910002 (Peck) Sumner 37.477 97.366 

201950001 (Cedar Bluff) Trego 38.770 99.764 

20107002 (Mine Creek) Linn 38.135 94.732 

Andy Hawkins of KDHE has made available processed ozone data files for 2001 through 2003 

containing data from the above referenced stations. Westar is proposing to incorporate these files into 

the CALPUFF model. 
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BART Modeling Protocol 

4.4 BACKGROUND AMMONIA

Background ammonia concentrations are required to model the formation of ammonium sulfates and 

ammonium nitrates. CENRAP recommends developing background ammonia estimates from 

CENRAP’s most recent CMAQ or CAMx simulation for the 2002 base year. Since CMAQ/CAMx 

modeled and observed monthly averaged ammonia concentrations exhibit wide spatial variability, 

CENRAP recommends obtaining separate monthly-averaged ammonia concentrations from CMAQ 

or CAMx for the CENRAP north, central and south modeling domains, respectively. These would 

then be used as input to CALPUFF. Since the data from CENRAP’s CMAQ and CAMx simulations 

are not readily available, Westar is proposing to use a conservative monthly background 

concentration of 3 ppb. This background concentration is the value included in CENRAP’s protocol 

as a default background value for the CENRAP region. 

4.5 SUMMARY OF CALPUFF CONTROL PARAMETERS

Table 4-11 provides a listing of the CALPUFF parameters that Westar proposes to use in the 

modeling analysis. In addition to the parameters that will be used, the table also lists CENRAP’s 

recommended parameters for comparison. In cases where a parameter to be used is different than 

what CENRAP recommended, a short explanation as to the difference is proved. 

TABLE 4-11. SUMMARY OF CALPUFF INPUTS

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

METRUN All model periods 

in met files will be 

run 

0 0 

IBYR Starting year 2001 Appropriate met year Years 2001, 2002, 

2003 

IBMO Starting month 1 1 

IBDY Starting day 1 1 

IBHR Starting hour 1 1 

XBTZ Base time zone (6 

= CST) 

6 6 

IRLG Length of run 8760 8760 

NSPEC Number of 

MESOPUFF II 

chemical species 

10 10 

NSE Number of 

chemical species 

to be emitted 

8 7 Appears to be an 

error in CENRAP’s 

count of the emitted 

species (only 7 listed 

in Table B-4 of 

protocol) 

ITEST Program is 

executed after 

SETUP phase 

2 2 
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BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

MRESTART Do not read or 

write a restart file 

during run 

0 0 

NRESPD File written only at 

last period 

0 0 

METFM CALMET binary 

file 

(CALMET.MET) 

1 1 

AVET Averaging time in 

minutes 

60 60 

PGTIME PG Averaging 

time in minutes 

60 60 

MGAUSS Gaussian 

distribution used 

in near field 

1 1 

MCTADJ Partial plume path 

terrain adjustment 

3 3 

MCTSG Sub-grid-scale 

complex terrain 

not modeled 

0 0 

MSLUG Near-field puffs 

not modeled as 

elongated 

0 0 

MTRANS Transitional plume 

rise modeled 

1 1 

MTIP Stack tip 

downwash used 

1 1 

MSHEAR (0, 1) Vertical 

wind shear (not 

modeled, 

modeled) 

0 0 

MSPLIT Puffs are not split 0 1 Included puff 

splitting due to 

significant distance 

between sources and 

Class I areas 

MCHEM MESOPUFF II 

chemical 

parameterization 

scheme 

1 1 

MAQCHEM Aqueous phase 

transformation not 

modeled 

0 0 

MWET Wet removal 

modeled 

1 1 

MDRY Dry deposition 

modeled 

1 1 

MDISP PG dispersion 

coefficients 

3 3 
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BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

MTURBVW Use both Vv and 

Vw from 

PROFILE.DAT to 

compute Vy and Vz

(n/a) 

3 3 

MDISP2 PG dispersion 

coefficients 

3 3 

MROUGH PG Vy and Vz

 not 

adjusted for 

roughness 

0 0 

MPARTL No partial plume 

penetration of 

elevated inversion 

1 1 

MTINV Strength of 

temperature 

inversion 

computed from 

default gradients 

0 0 

MPDF PDF not used for 

dispersion under 

convective 

conditions 

0 0 

MSGTIBL Sub-grid TIBL 

module not used 

for shoreline 

0 0 

MBCON Boundary 

concentration 

conditions not 

modeled 

0 0 

MFOG Do not configure 

for FOG model 

output 

0 0 

MREG Technical options 

must conform to 

USEPA Long 

Range Transport 

(LRT) guidance 

1 1 

CSPEC CENRAP Westar 

Output 

Group 

Species Modeled Emitted 

Dry 

Deposition 

Output 

Group 

Species Modeled Emitted 

Dry 

Deposition 

SO2 1 1 1 SO2 1 1 1 

 SO4 1 0 2 SO4 1 1 2 

NOX 1 1 1 NOX 1 1 1 

 HNO3 1 0 1 HNO3 1 0 1 

 NO3 1 0 2 NO3 1 0 2 

 NH3 1 1 1 NH3 1 0 1 

 PMC 1 1 2 PMC 1 1 2 

 PMF 1 1 2 PMF 1 1 2 

 EC 1 1 2 EC 1 1 2 

 SOA 1 1 2 SOA 1 1 2 

PMAP Map projection UTM LCC 
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BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

NX Number of X grid 

cells in 

meteorological 

grid 

66 251 Appropriate for 

domain and grid 

spacing 

NY Number of Y grid 

cells in 

meteorological 

grid 

66 246 Appropriate for 

domain and grid 

spacing 

NZ Number of vertical 

layers in 

meteorological 

grid 

10 10 

DGRIDKM Grid spacing (km) 6 2.5 Refined grid size 

ZFACE Cell face heights 

in meteorological 

grid (m) 

0, 20, 40, 80, 160, 

320, 640, 1200, 2000, 

3000, 4000 

0, 20, 40, 80, 160, 

320, 640, 1200, 

2000, 3000, 4000 

XORIGKM Reference X 

coordinate for SW 

corner of grid cell 

of meteorological 

grid (km) 

5 0 Appropriate for 

domain 

YORIGKM Reference Y 

coordinate for SW 

corner of grid cell 

of meteorological 

grid (km) 

3327 0 Appropriate for 

domain 

IUTMZN UTM zone of 

coordinates 

(NAD83) 

12 14 Appropriate for 

domain 

IBCOMP X index of lower 

left corner of the 

computational grid 

1 1 

JBCOMP Y index of lower 

left corner of the 

computational 

grids 

1 1 

IECOMP X index of upper 

right corner of the 

computational grid 

66 251 Appropriate for 

domain 

JECOMP Y index of upper 

right corner of the 

computational grid 

66 246 Appropriate for 

domain 

LSAMP Sampling grid is 

not used 

F F 

IBSAMP X index of lower 

left corner of 

sampling grid 

1 1 

JBSAMP Y index of lower 

left corner of 

sampling grid 

1 1 

IESAMP X index of upper 

right corner of 

sampling grid 

66 251 Appropriate for 

domain 
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BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

JESAMP Y index of upper 

right corner of 

sampling grid 

66 246 Appropriate for 

domain 

MESHDN Nesting factor of 

sampling grid 

1 1 

ICON Output file 

CONC.DAT 

containing 

concentrations is 

created 

1 1 

IDRY Output file 

DFLX.DAT 

containing dry 

fluxes is created 

1 1 

IWET Output file 

WFLX.DAT 

containing wet 

fluxes is created 

1 1 

IVIS Output file 

containing relative 

humidity data is 

created 

1 1 

LCOMPRS Perform data 

compression in 

output file 

T T 

IMFLX Do not calculate 

mass fluzes across 

specific 

boundaries 

0 0 

IMBAL Mass balances for 

each species not 

reported hourly 

0 0 

ICPRT Print concentration 

fields to output list 

file 

1 1 

IDPRT Do not print dry 

flux fields to 

output list file 

0 0 

IWPRT Do not print wet 

flux fields to 

output list file 

0 0 

ICFRQ Concentration 

fields are printed 

to output list file 

every hour 

1 1 

IDFRQ Dry flux fields are 

printed to output 

list file every 1 

hour 

1 1 

IWFRQ Wet flux fields are 

printed to output 

list file every 1 

hour 

1 1 
Westar Energy, Inc. 38 Trinity Consultants 

BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

IPTRU Units for line 

printer output are 

in g/m3

 for 

concentration and 

g/m2

/s for 

deposition 

3 3 

IMESG Messages tracking 

the progress of run 

written to screen 

2 2 

LDEBUG Logical value for 

debug output 

F F 

IPFDEB First puff to track 1 1 

NPFDEB Number of puffs 

to track 

1 1 

NN1 Meteorological 

period to start 

output 

1 1 

NN2 Meteorological 

period to end 

output 

10 10 

NHILL Number of terrain 

features 

0 0 

NCTREC Number of special 

complex terrain 

receptors 

0 0 

MHILL Input terrain and 

receptor data for 

CTSG hills input 

in CTDM format 

2 2 

XHILL2M Conversion factor 

for changing 

horizontal 

dimensions to 

meters 

1 1 

ZHILL2M Conversion factor 

for changing 

vertical 

dimensions to 

meters 

1 1 

XCTDMKM X origin of CTDM 

system relative to 

CALPUFF 

coordinate system 

(km) 

0 0 

YCTDMKM Y origin of CTDM 

system relative to 

CALPUFF 

coordinate system 

(km) 

0 0 

SO2 Diffusivity 0.1509 0.1509 

 Alpha star 1000 1000 

 Reactivity 8 8 
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BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

 Mesophyll 

resistance 

0 0 

 Henry’s Law 

coefficient 

0.04 0.04 

NOX Diffusivity 0.1656 0.1656 

 Alpha star 1 1 

 Reactivity 8 8 

 Mesophyll 

resistance 

5 5 

 Henry’s Law 

coefficient 

3.5 3.5 

HNO3 Diffusivity 0.1628 0.1628 

 Alpha star 1 1 

 Reactivity 18 18 

 Mesophyll 

resistance 

0 0 

 Henry’s Law 

coefficient 

8.e-8 8.e-8 

SO4-2 Geomatric mass 

mean diameter of 

SO4-2 (Pm) 

0.48 0.48 

NO3- Geometric mass 

mean diameter of 

NO3- (Pm) 

0.48 0.48 

PMC Geometric mass 

mean diameter of 

PMC (Pm) 

6 6 

PMF Geometric mass 

mean diameter of 

PMF (Pm) 

0.48 0.48 

EC Geometric mass 

mean diameter of 

EC (Pm) 

0.48 0.48 

SOA Geometric mass 

mean diameter of 

SOA (Pm) 

0.48 0.48 

RCUTR Reference cuticle 

resistance (s/cm) 

30 30 

RGR Reference ground 

resistance (s/cm) 

10 10 

REACTR Reference 

pollutant reactivity 

8 8 

NINT Number of particle 

size intervals for 

effective particle 

deposition velocity 

9 9 

IVEG Vegetation in nonirrigated areas is 

active and 

unstressed 

1 1 
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BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

SO2 Scavenging 

coefficient for 

liquid precipitation 

(s-1) 

3.21E-05 3.E-05 

 Scavenging 

coefficient for 

frozen 

precipitation (s-1) 

0 0 

SO4-2 Scavenging 

coefficient for 

liquid precipitation 

(s-1) 

1.0E-04 1.0E-04 

 Scavenging 

coefficient for 

frozen 

precipitation (s-1) 

3.0E-05 3.0E-05 

HNO3 Scavenging 

coefficient for 

liquid precipitation 

(s-1) 

6.0E-05 6.0E-05 

 Scavenging 

coefficient for 

frozen 

precipitation (s-1) 

0 0 

NO3- Scavenging 

coefficient for 

liquid precipitation 

(s-1) 

1.0E-04 1.0E-04 

 Scavenging 

coefficient for 

frozen 

precipitation (s-1) 

3.0E-05 3.0E-05 

NH3 Scavenging 

coefficient for 

liquid precipitation 

(s-1) 

8.0E-05 NA 

 Scavenging 

coefficient for 

frozen 

precipitation (s-1) 

0 NA 

PMC Scavenging 

coefficient for 

liquid precipitation 

(s-1) 

1.0E-4 1.0E-4 

 Scavenging 

coefficient for 

frozen 

precipitation (s-1) 

3.0E-05 3.0E-05 

PMF Scavenging 

coefficient for 

liquid precipitation 

(s-1) 

1.0E-05 1.0E-05 
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BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

 Scavenging 

coefficient for 

frozen 

precipitation (s-1) 

3.0E-05 3.0E-05 

EC Scavenging 

coefficient for 

liquid precipitation 

(s-1) 

1.0E-04 1.0E-04 

 Scavenging 

coefficient for 

frozen 

precipitation (s-1) 

3.0E-05 3.0E-05 

OC Scavenging 

coefficient for 

liquid precipitation 

(s-1) 

1.0E-04 1.0E-04 

 Scavenging 

coefficient for 

frozen 

precipitation (s-1) 

3.0E-05 3.0E-05 

MOZ Read ozone 

background 

concentrations 

from ozone.dat file 

(measured values) 

1 1 

BCKO3 Background ozone 

concentration 

(ppb) 

12*40 NA Used ozone data file 

BCKNH3 Background 

ammonia 

concentration 

(ppb) 

12*3 12*3 

RNITE1 Nighttime NO2 

loss rate is %/hour 

0.2 0.2 

RNITE2 Nighttime NOX

loss rate is %/hour 

2 2 

RNITE3 Nighttime HNO3 

loss rate is %/hour 

2 2 

MH2O2 Background H2O2 

concentrations 

1 0 Need to choose 0 in 

order to use monthly 

background value 

BCKH2O2 Background 

monthly H2O2 

concentrations 

1 12*1 

BCKPMF Fine particulate 

concentration for 

SOA option 

(Pg/m3) 

1 1 

OFRAC Organic fraction of 

fine particulate for 

SOA option 

.2 0.15,0.15,0.2,0.2,0.2,

0.2,0.2,0.2,0.2,0.2, 

0.2,0.15 

Irrelevant, since 

MCHEM not equal to 

4 
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BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

VCNX VOC/NOX ratio 

for SOA option 

50 50 

SYDEP Horizontal size of 

a puff in meters 

beyond which the 

time dependant 

dispersion 

equation of Heffter 

is used 

550 550 

MHFTSZ Do not use Heffter 

formulas for sigma 

z 

0 0 

JSUP Stability class used 

to determine 

dispersion rates for 

puffs above 

boundary layer 

5 5 

CONK1 Vertical dispersion 

constant for stable 

conditions 

0.01 0.01 

CONK2 Vertical dispersion 

constant for 

neutral/stable 

conditions 

0.1 0.1 

TBD Use ISC transition 

point for 

determining the 

transition point 

between the 

Schulman-Scire to 

Huber-Snyder 

Building 

Downwash 

scheme 

0.5 0.5 

IURB1 Lower range of 

land use categories 

for which urban 

dispersion is 

assumed 

10 10 

IURB2 Upper range of 

land use categories 

for which urban 

dispersion is 

assumed 

19 19 

ILANDUIN Land use category 

for modeling 

domain 

* * 

XLAIIN Leaf area index for 

modeling domain 

* * 

ZOIN Roughness length 

in meters for 

modeling domain 

* * 
Westar Energy, Inc. 43 Trinity Consultants 

BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

ELEVIN Elevation above 

sea level 

* * 

XLATIN North latitude of 

station in degrees 

- - 

XLONIN South latitude of 

station in degrees 

- - 

ANEMHT Anemometer 

height in meters 

10 10 

ISIGMAV Sigma-v is read 

for lateral 

turbulence data 

1 1 

IMIXCTDM Predicted mixing 

heights are used 

0 0 

XMXLEN Maximum length 

of emitted slug in 

meteorological 

grid units 

1 1 

XSAMLEN Maximum travel 

distance of slug or 

puff in 

meteorological 

grid units during 

one sampling unit 

10 10 

MXNEW Maximum number 

of puffs or slugs 

released from one 

source during one 

time step 

60 60 

MXSAM Maximum number 

of sampling steps 

during one time 

step for a puff or 

slug 

60 60 

NCOUNT Number of 

iterations used 

when computing 

the transport wind 

for a sampling step 

that includes 

transitional plume 

rise 

2 2 

SYMIN Minimum sigma y 

in meters for a 

new puff or slug 

1 1 

SZMIN Minimum sigma z 

in meters for a 

new puff or slug 

1 1 

SVMIN Minimum lateral 

turbulence 

velocities (m/s) 

0.5 0.5 

SWMIN Minimum vertical 

turbulence 

velocities (m/s) 

0.20, 0.12, 0.08, 0.06, 

0.03, 0.016 

0.20, 0.12, 0.08, 

0.06, 0.03, 0.016 
Westar Energy, Inc. 44 Trinity Consultants 

BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

WSCALM Minimum noncalm wind speeds 

(m/s) 

0.5 0.5 

XMAXZI Maximum mixing 

height (m) 

3000 3000 

XMINZI Minimum mixing 

height (m) 

20 20 

SL2PF Maximum Vy/puff 

length 

10 10 

PLXO Wind speed 

power-law 

exponents 

0.07, 0.07, 0.10, 0.15, 

0.35, 0.55 

0.07, 0.07, 0.10, 

0.15, 0.35, 0.55 

WSCAT Upper bounds of 

1

st 5 wind speed 

classes 

1.54, 3.09, 5.14, 8.23, 

10.80 

1.54, 3.09, 5.14, 

8.23, 10.80 

PGGO Potential temp 

gradients PG E & 

F (deg/km) 

0.020, 0.035 0.020, 0.035 

CDIV Divergence 

criterion for dw/dz 

(1/s) 

0.01 0.01 

PPC Plume path 

coefficients (only 

if MCTADJ = 3) 

0.5, 0.5, 0.5, 0.5, 

0.35, 0.35 

0.5, 0.5, 0.5, 0.5, 

0.35, 0.35 

NSPLIT Number of puffs 

when split 

3 3 

IRESPLIT Hours when puff 

is eligible to split 

1900 Hour 17 Should be by hour of 

day – 1900 is hour 17 

ZISPLIT Previous hours 

minimum mixing 

height, m 

100 100 

ROLDMAX Previous max 

mixing 

height/current 

height ratio, must 

be less than this 

value to allow puff 

to split 

0.25 0.25 

NSPLITH Number of puffs 

resulting from a 

split 

5 5 

SYSPLITH Minimum sigma-y 

of puff before it 

may split 

1.0 1.0 

SHSPLITH Minimum puff 

elongation rate 

from wind shear 

before puff may 

split 

2.0 2.0 
Westar Energy, Inc. 45 Trinity Consultants 

BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

CNSPLITH Minimum species 

concentration 

before a puff may 

split 

1.0E-07 1.0E-07 

EPSSLUG Criterion for 

SLUG sampling 

1.0E-04 1.0E-04 

EPSAREA Criterion for area 

source integration 

1.0E-06 1.0E-06 

DSRISE Trajectory step 

length for 

numerical site 

algorithm 

1.0 1.0 

NPT1 Number of point 

sources with 

constant stack 

parameters or 

variable emission 

rate scale factors 

Varies by scenario Varies by scenario 

IPTU Units for point 

source emission 

rates are g/s 

1 3 Used different units 

(3 = lb/hr) 

NSPT1 Number of sourcespecies 

combinations with 

variable emissions 

scaling factors 

- - 

NPT2 Number of point 

sources with 

variable emission 

parameters 

provided in 

external file 

- - 

MISC Other point source 

inputs include 

stack height, stack 

diameter, exit 

temperature, exit 

velocity, 

downwash flag 

and emissions by 

species 

- - 

NAR1 Number of 

polygon area 

sources 

Varies by scenario 0 None modeled 

IARU Units for area 

source emission 

rates are g/m2

/s 

1 1 

NSAR1 Number of source 

species 

combinations with 

variable emissions 

scaling factors 

- - 
Westar Energy, Inc. 46 Trinity Consultants 

BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

NAR2 Number of 

buoyant polygon 

area sources with 

variable location 

and emission 

parameters 

- - 

NLN2 Number of 

buoyant line 

sources with 

variable location 

and emission 

parameters 

- 0 None modeled 

NLINES Number of 

buoyant line 

sources 

- - 

ILNU Units for line 

source emission 

rates in g/s 

- - 

NSLN1 Number of sourcespecies 

combinations with 

variable emissions 

scaling factors 

- - 

MXNSEG Maximum number 

of segments used 

to model each line 

- - 

NLRISE Number of 

distance at which 

transitional rise is 

computed 

- - 

XL Average line 

source length (m) 

- - 

HBL Average height of 

line source height 

(m) 

- - 

WBL Average building 

width (m) 

- - 

WML Average line 

source width (m) 

- - 

DXL Average 

separation 

between buildings 

(m) 

- - 

FPRIMEL Average buoyancy 

parameter (m4/s3) 

- - 

NVL1 Number of volume 

sources 

- 0 None modeled 

IVLU Units for volume 

source emission 

rates in 

grams/second 

- - 
Westar Energy, Inc. 47 Trinity Consultants 

BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar 

Will Use Notes 

NSVL1 Number of sourcespecies 

combinations with 

variable emissions 

scaling factors 

- - 

IGRDVL Gridded volume 

source data is not 

used 

- - 

VEFFHT Effective height of 

emissions (m) 

- - 

VSIGYI Initial sigma-y 

value 

- - 

VSIGZI Initial sigma-z 

value 

- - 

NREC Number of nongridded receptors 5630 139 Receptor data 

provided in 

Appendix 
Westar Energy, Inc. 48 Trinity Consultants 

BART Modeling Protocol 

5. CALPOST

Westar will conduct a three-year CALPOST analysis to determine the change in light extinction 

caused by our BART-eligible sources when compared to a natural background. The CALPOST 

model requires the input of concentration data output by CALPUFF. 

5.1 LIGHT EXTINCTION ALGORITHM 

Westar will utilize EPA’s currently approved algorithm for reconstructing light extinction (as 

opposed to the new equation for reconstructing light extinction recommended by the IMPROVE 

Steering Committee). The light extinction equation is provided below. 

b = 3*f(RH) *[(NH SO + 3* f(RH) *[NH NO3 + 4*[OC] + 1*[PM

 + 0.6*[PM ] + 10*[EC] + b

ext 4 4 4 f

c Ray

) ] ] ] 2

The algorithm will be used to calculate the daily light extinction attributable to Westar’s BARTeligible sources and light extinction attributable to a natural background. The change in deciviews 

based on the source and background light extinctions will be evaluated using the equation below. 

' dv = 10*ln

b b

b

ext, background ext, source

ext, background

a 

¬

«

«

o

1⁄4

»

»

5.2 CALPOST PROCESSING METHOD

Westar will use CALPOST Method 6, which calculates hourly light extinction impacts for the source 

and background using monthly average relative humidity adjustment factors. Westar will use 

monthly Class I area-specific relative humidity adjustment factors based on the centroid of the Class I 

areas as included in Table A-3 of EPA’s Guidance for Estimating Natural Visibility Conditions 

Under the Regional Haze Program. The factors for Hercules Glades Wilderness and Wichita 

Mountains are provided in Table 5-1. 

TABLE 5-1. MONTHLY HUMIDITY FACTORS

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

Hercules-Glades 3.2 2.9 2.7 2.7 3.3 3.3 3.3 3.3 3.4 3.1 3.1 3.3 

Wichita Mountains 2.7 2.6 2.4 2.4 3.0 2.7 2.3 2.5 2.9 2.6 2.7 2.8 
Westar Energy, Inc. 49 Trinity Consultants 

BART Modeling Protocol 

5.3 NATURAL BACKGROUND

Westar will use EPA’s default average annual aerosol concentrations for the western half of the U.S. 

that are included in Table 2-1 of EPA’s Guidance for Estimating Natural Visibility Conditions Under 

the Regional Haze Program. The annual average concentrations are provided in Table 5-2. 

TABLE 5-2. DEFAULT WEST AVERAGE ANNUAL NATURAL BACKGROUND LEVELS

Component 

Average Annual 

Natural Background 

(Pg/m3

) 

Ammonium Sulfate 0.12 

Ammonium Nitrate 0.1 

Organic Carbon Mass 0.47 

Elemental Carbon 0.02 

Soil 0.5 

Coarse Mass 3 

5.4 EVALUATING BART-EXEMPTION

Westar will compare the 98th percentile of the 2001 through 2003 daily 'dv values output by 

CALPOST (22nd highest daily value) to a contribution threshold of 0.5 'dv. If the 98th percentile 

daily 'dv values output by CALPOST is less 0.5 'dv, then it will be concluded that the source is 

exempt from BART and that no further analysis is necessary. If the 98th percentile of the daily 'dv 

values output by CALPOST is greater than 0.5 'dv, then it will be concluded that further analysis is 

necessary. 

5.5 SUMMARY OF CALPOST CONTROL PARAMETERS

Table 5-3 provides a listing of the CALPOST parameters that Westar proposes to use in the modeling 

analysis. In addition to the parameters that will be used for the modeling, the table also lists 

CENRAP’s recommended parameters for comparison. In cases where a parameter to be used is 

different than what CENRAP recommended, a short explanation as to the difference is proved. 

TABLE 5-3. SUMMARY OF CALPOST INPUTS

CALPOST 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar Will 

Use Notes 

ISYR Starting year 2001 Appropriate met 

year 

Years 2001, 2002, 

2003 

ISMO Starting month 1 1 

ISDY Starting day 1 1 

ISHR Starting hour 0 1 All CALPUFF 

periods will be 

included 

NPER Number of periods 

to process 

8760 8760 
Westar Energy, Inc. 50 Trinity Consultants 

BART Modeling Protocol 

CALPOST 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar Will 

Use Notes 

NREP Process every hour 

of data? 1 = yes 

1 1 

ASPEC Process species for 

visibility 

VISIB VISIB 

ILAYER Layer/deposition 

code; 1 for 

CALPUFF 

concentrations 

1 1 

A Scaling factor, 

slope 

0 0 

B Scaling factor, 

intercept 

0 0 

LBACK Add hourly 

background 

concentrations of 

fluxes? 

F F 

LG Process gridded 

receptors? 

F F 

LD Process discrete 

receptors? 

T T 

LCT Process complex 

terrain receptors? 

F F 

LDRING Report receptor ring 

results? 

F F 

NDRECP Select all discrete 

receptors 

-1 Varies As appropriate for 

Class I area being 

analyzed 

IBGRID X index of LL 

corner of receptor 

grid 

-1 -1 

JBGRID Y index of LL 

corner of receptor 

grid 

-1 -1 

IEGRID X index of UR 

corner of receptor 

grid 

-1 -1 

JEGRID Y index of UR 

corner of receptor 

grid 

-1 -1 

NGONOFF Number of gridded 

receptor rows 

0 0 

NGXRECP Exclude specific 

gridded receptors, 

Yes = 0 

0 0 

RHMAX Maximum RH% 

used in particle 

growth curve 

95 95 

LVSO4 Compute light 

extinction for 

sulfate? 

T T 
Westar Energy, Inc. 51 Trinity Consultants 

BART Modeling Protocol 

CALPOST 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar Will 

Use Notes 

LVNO3 Compute light 

extinction for 

nitrate? 

T T 

LVOC Compute light 

extinction for 

organic carbon? 

T T 

LVMPC Compute light 

extinction for 

coarse particles? 

T T 

LVMPF Compute light 

extinction for fine 

particles? 

T T 

LVEC Compute light 

extinction for 

elemental carbon? 

T T 

LVBK Include background 

in extinction 

calculation? 

T T 

SPECPMC Coarse particulate 

species 

PMC PMC 

SPECPMF Fine particulate 

species 

PM10 PMF Notation difference 

EEPMC Extinction 

efficiency for 

coarse particulates 

0.6 0.6 

EEPMF Extinction 

efficiency for fine 

particles? 

1.0 1.0 

EEPMCBCK Extinction 

efficiency for 

coarse part. 

Background 

0.6 0.6 

EESO4 Extinction 

efficiency for 

ammonium sulfate 

3.0 3.0 

EENO3 Extinction 

efficiency for 

ammonium nitrate 

3.0 3.0 

EEOC Extinction 

efficiency for 

organic carbon 

4.0 4.0 

EESOIL Extinction 

efficiency for soil 

1.0 1.0 

EEEC Extinction 

efficiency for 

elemental carbon 

10.0 10.0 

MVISBK Method 6 for 

background light 

extinction 

6 6 

BEXTBTBK Background 

extinction for 

MVISBK=1 

12 Not Used Not necessary since 

MVISBK=6 
Westar Energy, Inc. 52 Trinity Consultants 

BART Modeling Protocol 

CALPOST 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar Will 

Use Notes 

RHFRAC % of particles 

affected by RH 

10 Not Used Not necessary since 

MVISBK=6 

RHFAC Extinction 

coefficients for 

modeled and 

background 

hygroscopic species 

computed using 

EPA (2003) 

monthly RH 

adjustment factors 

Depends on Class I 

Area 

For HerculesGlades: 

3.2, 2.9, 2.7, 2.7, 

3.3, 3.3, 3.3, 3.3, 

3.4, 3.1, 3.1, 3.3 

For Wichita Mtns: 

2.7, 2.6, 2.4, 2.4, 

3.0, 2.7, 2.3, 2.5, 

2.9, 2.6, 2.7, 2.8 

As appropriate for 

Class I area 

BKSO4 Background sulfate 

extinction coeff - 

west 

0.12 0.12 

BKNO3 Background nitrate 

extinction coeff – 

west 

0.10 0.10 

BKPMC Background coarse 

part. extinction 

coeff – west 

3.00 3.00 

BKSOC Background 

organic carbon 

extinction coeff – 

west 

0.47 0.47 

BKSOIL Background soil 

extinction coeff – 

west 

0.50 0.50 

BKSEC Background 

elemental carbon 

extinction coeff – 

west 

0.02 0.02 

BKSO4 Background sulfate 

extinction coeff – 

east 

0.23 Not Used West analysis only 

BKNO3 Background nitrate 

extinction coeff – 

east 

0.10 Not Used West analysis only 

BKPMC Background sulfate 

extinction coeff – 

west 

3.00 Not Used West analysis only 

BKSOC Background 

organic carbon 

extinction coeff – 

east 

1.40 Not Used West analysis only 

BKSSOIL Background soil 

extinction coeff – 

east 

0.50 Not Used West analysis only 

BKSEC Background 

elemental carbon 

extinction coeff – 

east 

0.02 Not Used West analysis only 
Westar Energy, Inc. 53 Trinity Consultants 

BART Modeling Protocol 

CALPOST 

Variable Description 

Value Included in 

CENRAP Protocol 

Value Westar Will 

Use Notes 

BEXTRAY Extinction due to 

Rayleigh scattering 

(1/Mm) 

10.0 10.0 

LDOC Print documentation image? F F 

IPTRU Print output units 

for concentrations 

and for deposition 

3 1 Units preference 

L1HR Report 1 hr 

averaging times 

F F 

L3HR Report 3 hr 

averaging times 

F F 

L24HR Report 24 hr 

averaging times 

T T 

LRUNL Report run-length 

averaging times 

F F 

LT50 Top 50 table F F 

LTOPN Top N table F F 

NTOP Number of Top-N 

values at each 

receptor 

4 4 

ITOP Ranks of Top-N 

values at each 

receptor 

1,2,3,4 1,2,3,4 

LEXCD Threshold 

exceedances counts 

F F 

THRESH1 Averaging time 

threshold for 1 hr 

averages 

-1 -1 

THRESH3 Averaging time 

threshold for 3 hr 

averages 

-1 -1 

THRESH24 Averaging time 

threshold for 24 hr 

averages 

-1 -0.2 Lower threshold – 

no effect on results 

THRESHN Averaging time 

threshold for 

NAVG-hr averages 

-1 -1 

NDAY Accumulation 

period, days 

0 0 

NCOUNT Number of 

exceedances 

allowed 

1 1 

LECHO Echo option F F 

LTIME Time series option F F 

LPLT Plot file option F F 

LGRD Use grid format 

instead of DATA 

format 

F F 

LDEBUG Output information 

for debugging? 

F F 
Westar Energy, Inc. A - 1 Trinity Consultants 

BART Modeling Protocol 

APPENDIX A 

MODELING DOMAIN
Westar Energy, Inc. A - 2 Trinity Consultants 

BART Modeling Protocol 

TABLE A-1. DETERMINATION OF MODELING DOMAIN

X Y Lat NAD27 Lon NAD27

Gordon Evans NAD 27, Zone 14 630.457 4183.633 37.793 97.518

Hutchinson NAD 27, Zone 14 598.828 4216.416 38.092 97.873

Jeffrey NAD 27, Zone 14 748.746 4352.838 39.287 96.116

Lawrence NAD 27, Zone 14 822.578 4323.950 39.007 95.275

Hercules-Glades Wilderness Area

UTM = NAD 27, Zone 14 Lat NAD27 Lon NAD27

SouthWest 1038.441 4073.213 36.654 92.979

NorthEast 1046.917 4081.226 36.721 92.879

SouthEast 1047.394 4073.782 36.654 92.879

NorthWest 1037.973 4080.657 36.721 92.979

Wichita Mountains Area

UTM = NAD 27, Zone 14 Lat NAD27 Lon NAD27

SouthWest 530.176 3840.082 34.7041 98.6705

NorthEast 520.233 3851.144 34.8041 98.7788

SouthEast 520.258 3840.055 34.7041 98.7788

NorthWest 530.140 3851.171 34.8041 98.6705

50 distance from facility

50 distance from Hercules-Glades WA

UTM = NAD 27, Zone 14 Lat NAD27 Lon NAD27

POINT UTM (KM) E UTM(KM) N Latitude (Decimal) Longitude (Decimal)

A 470.233 3790.055 34.25 99.32

B 1097.394 3790.055 34.08 92.53

C 1097.394 4402.838 39.57 92.05

D 470.233 4402.838 39.78 99.35

2.5 km grid spacing

MAX HORIZONTAL DIST (KM)

627.16 251 NX

MAX VERTICAL DIST (KM)

612.78 246 NY

Modeling Domain

D 39.78 C

99.35 92.05

A B

34.08
Westar Energy, Inc. B - 1 Trinity Consultants 

BART Modeling Protocol 

APPENDIX B 

EXAMPLE OF CALMM5 INPUT FILE
Westar Energy, Inc. B - 2 Trinity Consultants 

BART Modeling Protocol 

FIGURE B-1. EXAMPLE CALMM5 INPUT FILE

CALMM5 VER3 Output Sample Input File

33 ! Number of MM5 Output files (0 for auto)

i:\mm5\MMOUT_DOMAIN1_01_2000123112-2001010600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_02_2000123112-2001010600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_03_2000123112-2001010600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_04_2000123112-2001010600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_05_2000123112-2001010600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_01_2001010512-2001011100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_02_2001010512-2001011100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_03_2001010512-2001011100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_04_2001010512-2001011100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_05_2001010512-2001011100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_01_2001011012-2001011600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_02_2001011012-2001011600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_03_2001011012-2001011600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_04_2001011012-2001011600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_05_2001011012-2001011600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_01_2001011512-2001012100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_02_2001011512-2001012100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_03_2001011512-2001012100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_04_2001011512-2001012100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_05_2001011512-2001012100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_01_2001012012-2001012600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_02_2001012012-2001012600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_03_2001012012-2001012600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_04_2001012012-2001012600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_05_2001012012-2001012600 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_01_2001012512-2001013100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_02_2001012512-2001013100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_03_2001012512-2001013100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_04_2001012512-2001013100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_05_2001012512-2001013100 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_01_2001013012-2001020500 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_02_2001013012-2001020500 ! MM5 input file name (no space before or within filename)

i:\mm5\MMOUT_DOMAIN1_03_2001013012-2001020500 ! MM5 input file name (no space before or within filename)

R:\WestarBART\CALMM5\2001Outputs\Jan.m3d ! CALMM5 output file name (no space before or within filename)

R:\WestarBART\CALMM5\2001Outputs\Jan.lst ! CALMM5 list file name (no space before or within filename) 

1 ! Options for selecting a region (1: use lat/long; 2: use J/I)

34.08 ! Southernmost latitude (in decimal, positive for NH), or J1/Y1

39.78 ! Northermost latitude (in decimal, positive for NH), or J2/Y2

-99.35 ! Westernmost longitude (in decimal, negative for WH), or I1/X1

-92.05 ! Easternmost longitude (in decimal, negative for WH), or I2/X2

2001010107 ! Starting date (year-month-day-UTC hour)(yymmddhh)

2001020106 ! Ending date

1 ! Output format (1,2,3,4,5, 6 - see readme.cm5 for details)

Keep this line - The following lines vary depending on the output format selected

1 1 1 1 0 ! Output W, RH, cloud and rain, ice and snow, graupel

0 ! Flag for 2-D variables output (1/0: output/not)

1 ! Lowest extraction level in MM5 

34 ! Highest extraction level in MM5
Westar Energy, Inc. C - 1 Trinity Consultants 

BART Modeling Protocol 

APPENDIX C 

GEOPHYSICAL DATA
Westar Energy, Inc. C - 2 Trinity Consultants 

BART Modeling Protocol 

TABLE C-1. LAND USE DATA USED IN ANALYSIS 

1:250,000 scale data 1:100,000 scale data

Ardmore Antlers

Beloit Conway

Clinton Dequeen

Enid Fly Gap Mountain

Fort Smith McAlester

Great Bend Mena

Harrison Mountain View

Helena Russellville

Hutchinson

Jefferson City

Joplin

Kansas City

Lawrence

Lawton

Little Rock

Manhattan

Memphis

Moberly

Oklahoma City

Poplar Bluff

Pratt

Quincy

Rolla

Springfield

St. Louis

Tulsa

Wichita

Woodward
Westar Energy, Inc. C - 3 Trinity Consultants 

BART Modeling Protocol 

TABLE C-2. TERRAIN DATA USED IN ANALYSIS

Ardmore-E

Ardmore-W

Beloit-E

Beloit-W

Clinton-E

Clinton-W

Enid-E

Enid-W

FortSmith-E

FortSmith-W

GreatBend-E

GreatBend-W

Harrison-E

Harrison-W

Helena-W

Hutchinson-E

Hutchinson-W

Jefferson_City-E

Jefferson_City-W

Joplin-E

Joplin-W

Kansas_City-E

Kansas_City-W

Lawrence-E

Lawrence-W

Lawton-E

Lawton-W

LittleRock-E

LittleRock-W

Manhattan-E

Manhattan-W

Mcalester-E

Mcalester-W

Memphis-W

Moberly-E

Moberly-W

OklahomaCity-E

OklahomaCity-W

Poplar_Bluff-W

Pratt-E

Pratt-W

Quincy-W

Rolla-W

Russellville-E

Russellville-W

Saint_Louis-W

Springfield-E

Springfield-W

Tulsa-E

Tulsa-W

Wichita-E

Wichita-W

Woodward-E

Woodward-W
Westar Energy, Inc. D - 1 Trinity Consultants 

BART Modeling Protocol 

APPENDIX D 

TABLE D-1. LIST OF SURFACE METEOROLOGCAL STATIONS

Station 

ID Name ID Latitude Longitude X (km) Y (km) 

72244 TYLER/POUNDS FLD KTYR 32.35 -95.4 371.587 -184.785 

13962 ABILENE REGIONAL AP KABI 32.417 -99.683 -31.309 -184.980 

13959 WACO REGIONAL AP KACT 31.617 -97.233 201.010 -271.953 

13984 CONCORDIA BLOSSER MUNI AP KCNK 39.55 -97.65 145.670 608.842 

72450 CHANUTE MARTIN JOHNSON AP KCNU 37.667 -95.483 339.779 405.295 

3945 COLUMBIA REGIONAL AIRPORT KCOU 38.817 -92.217 616.771 549.227 

3927 DALLAS-FORT WORTH INTL AP KDFW 32.9 -97.017 218.011 -128.585 

13989 EMPORIA MUNICIPAL AP KEMP 38.333 -96.183 275.837 476.935 

13964 FORT SMITH REGIONAL AP KFSM 35.333 -94.367 451.322 151.049 

72344 FAYETTEVILLE DRAKE FIELD KFYV 36 -94.167 465.386 225.981 

93986 HOBART MUNICIPAL AP KHBR 35 -99.05 27.301 102.282 

72341 MEMORIAL FLD KHOT 34.467 -93.1 572.243 61.814 

3928 WICHITA MID-CONTINENT AP KICT 37.65 -97.433 168.512 398.200 

72445 KIRKSVILLE REGIONAL AP KIRK 40.1 -92.55 577.848 689.334 

72349 JOPLIN MUNICIPAL AP KJLN 37.15 -94.5 429.008 351.924 

3947 KANSAS CITY INT'L ARPT KMCI 39.3 -94.717 398.209 589.456 

72455 MANHATTAN RGNL KMHK 39.133 -96.667 231.189 564.465 

93950 MCALESTER MUNICIPAL AP KMLC 34.9 -95.783 324.946 97.220 

72249 NACOGDOCHES (AWOS) KOCH 31.583 -94.717 439.952 -267.268 

13967 OKLAHOMA CITY WILL ROGERS WOR KOKC 35.383 -97.6 158.463 146.240 

13969 PONCA CITY MUNICIPAL AP KPNC 36.733 -97.1 200.187 297.058 

72258 COX FLD KPRX 33.633 -95.45 361.036 -42.304 

13995 SPRINGFIELD REGIONAL ARPT KSGF 37.233 -93.383 527.118 366.736 

13957 SHREVEPORT REGIONAL ARPT KSHV 32.45 -93.817 519.713 -166.247 

72458 SALINA MUNICIPAL AP KSLN 38.817 -97.667 145.653 527.389 

13966 WICHITA FALLS MUNICIPAL ARPT KSPS 33.983 -98.5 78.361 -10.434 

72449 ST JOSEPH ROSECRANS MEMORIAL KSTJ 39.767 -94.9 380.065 640.548 

13930 WHITEMAN AFB KSZL 38.717 -93.55 502.346 530.306 

13996 TOPEKA MUNICIPAL AP KTOP 39.067 -95.633 320.534 560.134 

13968 TULSA INTERNATIONAL AIRPORT KTUL 36.2 -95.883 310.581 241.170 

13977 TEXARKANA WEBB FIELD KTXK 33.45 -94 496.288 -56.103 

72352 ARDMORE K1F0 34.15 -97.117 205.406 10.192 
Westar Energy, Inc. D - 2 Trinity Consultants 

BART Modeling Protocol 

TABLE D-2. LIST OF UPPER AIR METEOROLOGICAL STATIONS

Station ID Name ID Latitude Longitude X (km) Y (km) 

3948 NORMAN, OK KOUN 35.233 -97.47 170.562 129.807

3952 LITTLE ROCK, AR KLZK 34.83 -92.27 645.107 107.361

3990 FT. WORTH, TX KFWD 32.8 -97.3 191.81 -140.322

13957 SHREVEPORT, LA KSHV 32.45 -93.817 519.713 -166.247

13995 SPRINGFIELD, MO KSGF 37.233 -93.383 527.118 366.736

13996 TOPEKA, KS KTOP 39.067 -95.633 320.534 560.134

TABLE D-3. LIST OF PRECIPITATION METEOROLOGICAL STATIONS

Station ID Name ID Latitude Longitude X (km) Y (km) 

30130 ALUM FORK ALUM 34.800 -92.850 592.573 100.264

30178 ANTOINE ANTO 34.033 -93.417 546.292 11.848 

30220 ARKADELPHIA 2 N ARKA 34.150 -93.050 579.146 26.959 

30764 BLAKELY MOUNTAIN DAM BLAK 34.567 -93.200 562.385 72.271 

30832 BOONEVILLE 3 SSE BOON 35.100 -93.917 493.544 127.441 

30900 BRIGGSVILLE BRIG 34.933 -93.500 532.484 111.205 

31152 CAMDEN 1 CAMD 33.600 -92.817 604.758 -32.605 

31457 CLARKSVILLE 6 NE CLAR 35.533 -93.400 537.41 178.286 

31952 DE QUEEN DAM DE Q 34.100 -94.367 458.524 14.232 

32020 DIERKS DAM DIER 34.150 -94.083 484.26 21.186 

32544 FOREMAN FORE 33.717 -94.383 459.215 -28.412 

32574 FORT SMITH MU, OK FORT 35.333 -94.367 451.35 151.087 

34185 LEWISVILLE LEWI 33.367 -93.567 537.001 -63.005 

34548 MAGNOLIA 3 N MAGN 33.333 -93.250 566.603 -64.87 

34756 MENA MENA 34.567 -94.267 464.947 66.513 

35200 NIMROD DAM NIMR 34.950 -93.167 562.663 114.971 

35908 PRESCOTT PRES 33.800 -93.383 550.983 -13.852 

37048 TEXARKANA TEXA 33.450 -94.000 496.288 -56.103

37488 WALDRON WALD 34.900 -94.100 478.133 104.322 

165874 MANSFIELD MANS 32.033 -93.700 533.444 -211.938 

166244 MINDEN MIND 32.600 -93.300 567.151 -146.621 

166582 NATCHITOCHES NATC 31.767 -93.100 591.967 -238.055 

167738 RED RIVER RSRCH STN RED 32.417 -93.633 537.167 -168.933 

168440 SHREVEPORT, LA SHRE 32.467 -94.317 472.727 -166.999 

340179 ALTUS IRIG RES STN ALTU 34.583 -99.333 1.525 55.944 

340292 ARDMORE ARDM 34.167 -97.133 203.861 12.009 

340670 BENGAL BENG 34.850 -95.083 388.894 94.294 

341437 CANEY CANE 34.233 -96.217 287.894 21.785 

341544 CARTER TOWER CART 34.267 -94.783 419.327 30.813 

341684 CHANDLER 1 CHAN 35.700 -96.883 222.432 182.873 

341750 CHICKASHA EXP STN CHIC 35.050 -97.917 130.348 108.775 
Westar Energy, Inc. D - 3 Trinity Consultants 

BART Modeling Protocol 

Station ID Name ID Latitude Longitude X (km) Y (km) 

342334 CUSTER CITY CUST 35.650 -98.833 46.626 174.563 

342654 DUNCAN AIRPORT DUNC 34.483 -97.967 126.717 45.752 

342849 ELK CITY ELK 35.383 -99.400 -4.528 144.821 

343281 FORT COBB FORT 35.100 -98.433 83.311 113.749

343497 GEARY GEAR 35.633 -98.317 93.27 173.092 

344052 HENNEPIN 5 N HENN 34.567 -97.350 183.003 56.015 

344202 HOBART HOBA 35.033 -99.083 24.257 105.976 

344865 KINGSTON KING 34.000 -96.733 241.149 -5.578 

344975 LAKE EUFAULA LAKE 35.283 -95.433 355.031 141.02 

345108 LEHIGH LEHI 34.467 -96.217 287.04 47.705 

345463 MACKIE 4 NNW MACK 35.750 -99.833 -43.561 185.653 

345589 MARSHALL MARS 36.150 -97.617 155.403 231.376

345664 MCALESTER MUNI AP MCAL 34.883 -95.783 324.985 95.368 

346130 MUSKOGEE MUSK 35.767 -95.333 361.825 195.03 

346620 OKARCHE OKAR 35.717 -97.983 123.223 182.725 

346638 OKEMAH OKEM 35.433 -96.300 275.968 154.796 

346661 OKLAHOMA CITY, OK OKLA 35.383 -97.600 158.462 146.277 

347705 ROFF 2 WNW ROFF 34.633 -96.883 225.503 64.423 

349023 TUSKAHOMA TUSK 34.633 -95.283 371.705 69.443

349629 WICHITA MTN WL REF WICH 34.733 -98.717 57.832 72.804 

349724 WISTER WIST 34.950 -94.700 423.264 107.027 

349748 WOLF 4 N WOLF 35.133 -96.667 243.74 120.487 

410016 ABILENE MUN, TX ABIL 32.417 -99.683 -31.34 -185.017 

410926 BONITA 4 NW BONI 33.833 -97.633 158.551 -25.995 

411246 BURLESON BURL 32.550 -97.317 190.846 -168.184 

411698 CHILDRESS MUNI AP CHIL 34.433 -100.283 -85.552 39.694 

411773 CLARKSVILLE 1 W CLAR 33.617 -95.017 401.207 -42.383 

411921 COMMERCE COMM 33.200 -95.933 318.041 -92.161

412086 CRANFILLS GAP CRAN 31.767 -97.833 143.748 -256.356 

412096 CRESSON CRES 32.533 -97.617 162.725 -170.597

412131 CROSS PLAINS 2 CROS 32.133 -99.167 17.298 -216.619 

412242 DALLAS-FORT WORTH/FORT. TX. DALL 32.900 -97.017 218.043 -128.584 

412244 DALLAS LOVE FIELD DALL 32.850 -96.850 233.76 -133.752 

412404 DENTON 2 SE DENT 33.200 -97.100 209.467 -95.394 

412715 EASTLAND EAST 32.400 -98.817 50.155 -186.788

413133 FERRIS FERR 32.517 -96.667 251.944 -170.383 

413285 FORT WORTH WSFO FORT 32.833 -97.300 191.73 -136.613 

413415 GAINESVILLE GAIN 33.633 -97.133 205.242 -47.275

413546 GILMER 2 W GILM 32.733 -94.983 408.8 -140.429 

413642 GORDONVILLE GORD 33.800 -96.850 230.983 -28.097 

413771 GROESBECK 2 GROE 31.533 -96.533 267.703 -279.557 

414137 HICO HICO 31.983 -98.033 124.459 -232.49 
Westar Energy, Inc. D - 4 Trinity Consultants 

BART Modeling Protocol 

Station ID Name ID Latitude Longitude X (km) Y (km) 

414257 HONEY GROVE HONE 33.583 -95.900 319.597 -49.433 

414520 JACKSBORO 1 NNE JACK 33.233 -98.150 111.677 -93.458 

414866 KOPPERL KOPP 32.133 -97.483 176.115 -214.908

414972 LAKE BRIDGEPORT DAM LAKE 33.217 -97.833 141.174 -94.891 

415348 LONGVIEW TX. LONG 32.350 -94.650 442.089 -181.578 

415463 MABANK 4 SW MABA 32.350 -96.117 304.197 -187.329 

415957 MINERAL WELLS 1 SSW MINE 32.783 -98.117 115.428 -143.496 

415996 MOLINE MOLI 31.400 -98.317 98.384 -297.856 

416108 MOUNT PLEASANT MOUN 33.167 -95.000 405.037 -92.321 

416177 NACOGDOCHES NACO 31.617 -94.650 446.124 -263.206 

416210 NAVARRO MILLS DAM NAVA 31.950 -96.700 250.573 -233.576 

416270 NEW BOSTON NEW 33.450 -94.417 457.673 -58.192 

416335 NEW SUMMERFIELD 2 W NEW 31.983 -95.133 398.467 -224.521 

416757 PALESTINE 2 NE PALE 31.783 -95.600 355.27 -248.642 

416834 PAT MAYSE DAM PAT 33.867 -95.517 353.821 -16.591 

417066 PITTSBURG 5 S PITT 32.933 -94.933 412.444 -117.974 

417300 PROCTOR RESERVOIR PROC 31.967 -98.500 80.365 -234.849 

417499 RED SPRINGS 2 ESE RED 33.600 -99.383 -3.088 -53.373 

417556 RENO RENO 32.950 -97.567 166.549 -124.131 

418047 SANTA ANNA SANT 31.750 -99.333 1.58 -259.359

418583 STAMFORD 1 STAM 32.933 -99.800 -42.038 -127.448 

418623 STEPHENVILLE 1 N STEP 32.250 -98.200 108.347 -202.983 

418743 SULPHUR SPRINGS SULP 33.150 -95.633 346.171 -96.673 

418778 SWAN SWAN 32.450 -95.417 369.56 -173.721 

419163 TRUSCOTT TRUS 33.750 -99.867 -47.772 -36.562

419419 WACOMADISON-COOPER TX. WACO 31.617 -97.233 200.979 -271.99 

419532 WEATHERFORD WEAT 32.750 -97.767 148.243 -146.722 

419565 WELLINGTON WELL 34.833 -100.217 -79.036 84.082 

419715 WHITNEY DAM WHIT 31.850 -97.367 187.779 -246.255 

419729 WICHITA FALLS/SHEPS AFB TX WICH 33.983 -98.500 78.36 -10.397 

419817 WINCHELL WINC 31.467 -99.167 17.441 -290.937 

419893 WOODSON WOOD 33.017 -99.050 27.996 -118.228 

419916 WRIGHT PATMAN WRIG 33.300 -94.167 481.752 -73.621 

33165 HARRISON BOONE CNTY AP HARR 36.267 -93.157 554.062 260.951 

35228 NORFORK DAM NORF 36.249 -92.256 634.629 264.668 

140326 ARLINGTON ARLI 37.900 -98.267 94.889 424.802 

141233 CALDWELL CALD 37.034 -97.616 153.714 329.468

141427 CHANUTE FAA AIRPORT CHAN 37.670 -95.484 339.661 405.655 

141767 CONCORDIA BLOSSER MUNI CONC 39.551 -97.651 145.595 608.996 

141867 COUNCIL GROVE LAKE COUN 38.675 -96.526 244.858 513.992 

143997 IONIA IONI 39.661 -98.348 85.704 620.341 

144341 KIOWA KIOW 37.017 -98.485 76.705 326.534 
Westar Energy, Inc. D - 5 Trinity Consultants 

BART Modeling Protocol 

Station ID Name ID Latitude Longitude X (km) Y (km) 

145063 MARYSVILLE MARY 39.833 -96.633 231.897 642.307 

145306 MILFORD LAKE MILF 39.075 -96.898 211.451 557.455 

147160 SALINA AP SALI 38.817 -97.667 145.653 527.389

148167 TOPEKA BILLARD MUNI AP TOPE 39.069 -95.639 320.018 560.323 

148293 UNIONTOWN UNIO 37.848 -94.978 383.243 427.269 

148830 WICHITA WICH 37.650 -97.433 168.512 398.2 

230204 APPLETON CITY APPL 38.184 -94.026 464.443 468.749 

230789 BOLIVAR 1 NE BOLI 37.617 -93.391 523.736 409.205 

231383 CASSVILLE RANGER STN CASS 36.673 -93.858 488.813 302.115 

231791 COLUMBIA REGIONAL AP COLU 38.817 -92.218 616.657 549.212 

232302 DORA DORA 36.780 -92.233 632.313 323.535 

234315 JOPLIN REGIONAL AP JOPL 37.147 -94.502 428.83 351.544 

234358 KANSAS CITY AP KANS 39.300 -94.717 398.209 589.456 

234544 KIRKSVILLE KIRK 40.200 -92.567 575.614 700.322 

234825 LEBANON 2 W LEBA 37.685 -92.694 584.416 420.837 

235834 MOUNTAIN GROVE 2 N MOUN 37.153 -92.264 626.498 364.635 

235987 NEVADA WATER PLANT NEVA 37.839 -94.373 436.201 428.946 

237976 SPRINGFIELD REG AP SPRI 37.240 -93.390 526.478 367.443 

238252 TABLE ROCK DAM TABL 36.597 -93.308 538.258 296.711 

238466 TRUMAN DAM & RESERVIOR TRUM 38.258 -93.399 518.603 480.243 

340215 AMES AMES 36.250 -98.183 104.495 241.705 

347196 PONCA CITY PONC 36.717 -97.100 200.229 295.282 

348992 TULSA INTL AIRPORT TULS 36.198 -95.888 310.16 240.97 
 

BART FIVE FACTOR ANALYSIS § WESTAR ENERGY

JEFFREY ENERGY CENTER AND GORDON EVANS ENERGY CENTER

VERSION 0 

Prepared by: 

TRINITY CONSULTANTS

9777 Ridge Drive 

Suite 380 

Lenexa, Kansas 66219 

(913) 894-4500 

August 2007 

Project 051701.0153 
Westar Energy i Trinity Consultants 

BART Analysis 

TABLE OF CONTENTS

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

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

3. BART APPLICABILITY DETERMINATION.......................................................... 3-1

4. JEC SO2 BART EVALUATION......................................................................... 4-1

4.1 IDENTIFICATION OF AVAILABLE RETROFIT SO2 CONTROL TECHNOLOGIES ......... 4-1 

4.2 ELIMINATE TECHNICALLY INFEASIBLE SO2 CONTROL TECHNOLOGIES ............... 4-1 

4.2.1 DRY SORBENT INJECTION................................................................................4-1

4.2.2 SPRAY DRYER ABSORPTION (SDA).................................................................4-2

4.2.3 WET SCRUBBER.............................................................................................. 4-2

4.2.4 CIRCULATING DRY SCRUBBER (CDS) ............................................................. 4-2

4.3 RANK OF TECHNICALLY FEASIBLE SO2 CONTROL OPTIONS BY EFFECTIVENESS .. 4-3 

4.4 EVALUATION OF IMPACTS FOR FEASIBLE SO2 CONTROLS................................... 4-3 

4.4.1 COST OF COMPLIANCE .................................................................................... 4-3

4.4.2 ENERGY IMPACTS AND NON-AIR QUALITY IMPACTS.......................................4-3

4.4.3 REMAINING USEFUL LIFE................................................................................4-4

4.5 EVALUATION OF VISIBILITY IMPACT OF FEASIBLE SO2 CONTROLS ..................... 4-4 

4.6 PROPOSED BART FOR SO2 ................................................................................. 4-7 

5. JEC NOX BART EVALUATION ....................................................................... 5-1

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

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

5.2.1 COMBUSTION CONTROLS ................................................................................5-2

5.2.1.1 Flue Gas Recirculation (FGR) .......................................................... 5-2

5.2.1.2 Overfire Air (OFA) ..........................................................................5-2

5.2.1.3 Low and Ultra Low NOX Burners..................................................... 5-2

5.2.2 POST COMBUSTION CONTROLS .......................................................................5-3

5.2.2.1 Selective Catalytic Reduction........................................................... 5-3

5.2.2.2 Selective Non-Catalytic Reduction ................................................... 5-4

5.3 RANK OF TECHNICALLY FEASIBLE NOX CONTROL OPTIONS BY EFFECTIVENESS . 5-4 

5.4 EVALUATION OF IMPACTS FOR FEASIBLE NOX CONTROLS.................................. 5-5 

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

5.4.2 ENERGY IMPACTS & NON-AIR IMPACTS.......................................................... 5-9

5.4.3 REMAINING USEFUL LIFE................................................................................5-9

5.5 EVALUATION OF VISIBILITY IMPACT OF FEASIBLE NOX CONTROLS .................... 5-9 

5.6 PROPOSED BART FOR NOX ...............................................................................5-13 

6. GEEC SO2 BART EVALUATION..................................................................... 6-1

6.1 IDENTIFICATION OF AVAILABLE RETROFIT SO2 CONTROL TECHNOLOGIES ......... 6-1 
Westar Energy ii Trinity Consultants 

BART Analysis 

6.2 ELIMINATE TECHNICALLY INFEASIBLE SO2 CONTROL TECHNOLOGIES ............... 6-1 

6.2.1 DRY SORBENT INJECTION, SPRAY DRYER ABSORPTION (SDA), WET SCRUBBER,

CIRCULATING DRY SCRUBBER (CDS)..........................................................................6-1

6.2.2 FUEL SWITCHING TO ONE PERCENT SULFUR FUEL OIL....................................6-2

6.3 RANK OF TECHNICALLY FEASIBLE SO2 CONTROL OPTIONS BY EFFECTIVENESS .. 6-2 

6.4 EVALUATION OF IMPACTS FOR FEASIBLE SO2 CONTROLS................................... 6-2 

6.4.1 COST OF COMPLIANCE .................................................................................... 6-2

6.4.1.1 Energy Impacts and Non-Air Quality Impacts ..................................6-5

6.4.1.2 Remaining Useful Life .....................................................................6-5

6.5 EVALUATION OF VISIBILITY IMPACT OF FEASIBLE SO2 CONTROLS ..................... 6-5 

6.6 PROPOSED BART FOR SO2 ................................................................................. 6-8 

7. GEEC NOX BART EVALUATION.................................................................... 7-1

7.1 IDENTIFICATION OF AVAILABLE RETROFIT NOX CONTROL TECHNOLOGIES ........ 7-1 

7.2 ELIMINATE TECHNICALLY INFEASIBLE NOX CONTROL TECHNOLOGIES .............. 7-1 

7.2.1 COMBUSTION CONTROLS ................................................................................7-2

7.2.1.1 Flue Gas Recirculation (FGR) .......................................................... 7-2

7.2.1.2 Overfire Air (OFA) ..........................................................................7-2

7.2.1.3 Low and Ultra Low NOX Burners..................................................... 7-2

7.2.2 POST COMBUSTION CONTROLS .......................................................................7-3

7.2.2.1 Selective Catalytic Reduction........................................................... 7-3

7.2.2.2 Selective Non-Catalytic Reduction ................................................... 7-4

7.3 RANK OF TECHNICALLY FEASIBLE NOX CONTROL OPTIONS BY EFFECTIVENESS . 7-4 

7.4 EVALUATION OF IMPACTS FOR FEASIBLE NOX CONTROLS.................................. 7-5 

7.4.1 COST OF COMPLIANCE .................................................................................... 7-5

7.4.2 ENERGY IMPACTS & NON-AIR IMPACTS.......................................................... 7-8

7.4.3 REMAINING USEFUL LIFE................................................................................7-8

7.5 EVALUATION OF VISIBILITY IMPACT OF FEASIBLE NOX CONTROLS .................... 7-8 

7.6 PROPOSED BART FOR NOX ...............................................................................7-11 

8. PM10 BART EVALUATION .............................................................................. 8-1

9. PROPOSED GEEC BART ALTERNATIVE......................................................... 9-1

9.1.1.1 Compliance with Alternative BART Control Strategy....................... 9-1

9.1.2 COMPARISON OF VISIBILITY IMPACTS FOR BART AND PROPOSED ALTERNATIVE 

BART CONTROL STRATEGIES ..................................................................................... 9-1
Westar Energy iii Trinity Consultants 

BART Analysis 

LIST OF TABLES

TABLE 1-1. EXISTING VISIBILITY IMPAIRMENT ATTRIBUTABLE TO JEC UNIT 1 AND UNIT 2 AND 

GEEC UNIT 2 (2001-2003).................................................................................................1-1

TABLE 1-2. VISIBILITY IMPAIRMENT IMPROVEMENT FROM JEC UNIT 1 AND UNIT 2 (2001-2003)....1-2

TABLE 1-3. VISIBILITY IMPAIRMENT IMPROVEMENT FROM GEEC UNIT 2 (2001-2003)................... 1-3

TABLE 3-1. EXISTING MAXIMUM 24-HOUR SO2,NOX, AND PM10 EMISSIONS (AS HOURLY 

EQUIVALENTS) ..................................................................................................................3-1

TABLE 3-2. SUMMARY OF EXISTING STACK PARAMETERS ............................................................. 3-2

TABLE 3-3. EXISTING VISIBILITY IMPAIRMENT ATTRIBUTABLE TO JEC UNIT 1 AND UNIT 2 AND 

GEEC UNIT 2 (2001-2003).................................................................................................3-2

TABLE 3-4. BREAKDOWN OF POLLUTANT SPECIFIC CONTRIBUTIONS TO EXISTING VISIBILITY 

IMPAIRMENT FOR JEC UNIT 1 AND UNIT 2 (2001-2003)..................................................... 3-2

TABLE 3-5. BREAKDOWN OF POLLUTANT SPECIFIC CONTRIBUTIONS TO EXISTING VISIBILITY 

IMPAIRMENT FOR GEEC UNIT 2 (2001-2003) ....................................................................3-3

TABLE 4-1. EXISTING MAXIMUM 24-HOUR SO2 EMISSION RATES FOR JEC UNIT 1 AND UNIT 2 .....4-1

TABLE 4-2. AVAILABLE SO2 CONTROL TECHNOLOGIES FOR JEC UNIT 1 AND UNIT 2 ..................... 4-1

TABLE 4-3. CONTROL EFFECTIVENESS OF TECHNICALLY FEASIBLE SO2 CONTROL TECHNOLOGIES 

FOR JEC UNIT 1 AND UNIT 2 .............................................................................................. 4-3

TABLE 4-4. SUMMARY OF EMISSION RATES MODELED IN SO2 CONTROL VISIBILITY IMPACT 

ANALYSIS FOR JEC UNIT 1 AND UNIT 2 .............................................................................4-4

TABLE 4-5. SUMMARY OF MODELED IMPACTS FROM SO2 CONTROL VISIBILITY IMPACT ANALYSIS 

FOR JEC UNIT 1 (2001-2003) ............................................................................................. 4-5

TABLE 4-6. SUMMARY OF MODELED IMPACTS FROM SO2 CONTROL VISIBILITY IMPACT ANALYSIS 

FOR JEC UNIT 2 (2001-2003) ............................................................................................. 4-6

TABLE 5-1. EXISTING MAXIMUM 24-HOUR NOX EMISSION RATE FOR JEC UNIT 1 AND UNIT 2 ......5-1

TABLE 5-2. AVAILABLE NOX CONTROL TECHNOLOGIES FOR JEC UNIT 1 AND UNIT 2.................... 5-1

TABLE 5-3. CONTROL EFFECTIVENESS OF TECHNICALLY FEASIBLE NOX CONTROL TECHNOLOGIES5-5

TABLE 5-4. SUMMARY OF COST EFFECTIVENESS FOR JEC UNIT 1 NOX CONTROLS.......................... 5-8
Westar Energy iv Trinity Consultants 

BART Analysis 

TABLE 5-5. SUMMARY OF COST EFFECTIVENESS FOR JEC UNIT 2 NOX CONTROLS.......................... 5-8

TABLE 5-6. SUMMARY OF EMISSION RATES MODELED IN NOX CONTROL VISIBILITY IMPACT 

ANALYSIS FOR JEC UNIT 1 AND JEC UNIT 2 .................................................................... 5-10

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

FOR JEC UNIT 1 (2001-2003) ........................................................................................... 5-11

TABLE 5-8. SUMMARY OF MODELED IMPACTS FROM NOX CONTROL VISIBILITY IMPACT ANALYSIS 

FOR JEC UNIT 2 (2001-2003) ........................................................................................... 5-12

TABLE 6-1. EXISTING MAXIMUM 24-HOUR SO2 EMISSION RATES..................................................6-1

TABLE 6-2. AVAILABLE SO2 CONTROL TECHNOLOGIES FOR GEEC UNIT 2.....................................6-1

TABLE 6-3. SUMMARY OF COST EFFECTIVENESS FOR SWITCHING FROM NO. 6 OIL TO 1% SULFUR 

FUEL OIL ........................................................................................................................... 6-4

TABLE 6-4. SUMMARY OF EMISSION RATES MODELED IN SO2 CONTROL VISIBILITY IMPACT 

ANALYSIS.......................................................................................................................... 6-5

TABLE 6-5. SUMMARY OF MODELED IMPACTS FROM SO2 CONTROL VISIBILITY IMPACT ANALYSIS 

FOR GEEC UNIT 2 (2001-2003).......................................................................................... 6-7

TABLE 7-1. EXISTING MAXIMUM 24-HOUR NOX EMISSION RATE ..................................................7-1

TABLE 7-2. AVAILABLE NOX CONTROL TECHNOLOGIES FOR GEEC UNIT 2...................................7-1

TABLE 7-3. CONTROL EFFECTIVENESS OF TECHNICALLY FEASIBLE NOX CONTROL TECHNOLOGIES7-5

TABLE 7-4. SUMMARY OF COST EFFECTIVENESS FOR GEEC UNIT 2 NOX CONTROLS ...................... 7-7

TABLE 7-5. SUMMARY OF EMISSION RATES MODELED IN NOX CONTROL VISIBILITY IMPACT 

ANALYSIS.......................................................................................................................... 7-9

TABLE 7-6. SUMMARY OF MODELED IMPACTS FROM NOX CONTROL VISIBILITY IMPACT ANALYSIS 

FOR GEEC UNIT 2 (2001-2003)........................................................................................ 7-10

TABLE 8-1. EXISTING MAXIMUM 24-HOUR PM10 EMISSION RATE..................................................8-1

TABLE 8-2. VAP VISIBILITY IMPAIRMENT CONTRIBUTIONS FROM JEC UNIT 1 AND UNIT 2 (2001-

2003).................................................................................................................................8-1

TABLE 8-3. VISIBILITY IMPAIRMENT CONTRIBUTIONS FROM GEEC UNIT 2(2001-2003) .................8-2

TABLE 9-1. MODELED IMPACTS BASED ON PRESUMPTIVE BART EMISSION RATES AND 

ALTERNATIVE BART AT GEEC UNIT 2 (2001-2003).......................................................... 9-2
Westar Energy v Trinity Consultants 

BART Analysis 
Westar Energy 1-1 Trinity Consultants 

BART Analysis 

1. EXECUTIVE SUMMARY

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

proposed by Westar Energy (Westar) for the Jeffrey Energy Center (JEC) located in St. Mary’s, 

Kansas and the Gordon Evans Energy Center (GEEC) located in Colwich, Kansas. There are two 

units at JEC and one unit at GEEC that are subject to BART. JEC Unit 1 and Unit 2 are each coalfired boilers with heat input ratings of 8,110 million British thermal units per hour (MMBtu/hr). 

GEEC Unit 2 is an oil-fired boiler with a heat input rating of 4,110 MMBtu/hr. 

Westar has determined that JEC Unit 1 and Unit 2 and GEEC Unit 2 contribute greater than 0.5 delta 

deciviews (∆dv) to visibility impairment in a federally protected Class I area when compared to a 

natural background. Therefore, these three units are subject to BART. A summary of the visibility 

impairment attributable to the JEC Unit 1 and Unit 2 and GEEC Unit 2 is provided in Table 1-1. 

TABLE 1-1. EXISTING VISIBILITY IMPAIRMENT ATTRIBUTABLE TO JEC UNIT 1 AND UNIT 2 AND 

GEEC UNIT 2 (2001-2003) 

Wichita 

Mountains 

Hercules 

Glades 

Wilderness 

Caney Creek 

Wilderness Mingo NWR Upper Buffalo 

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

98th

 

% 

∆dv

Days 

> 0.5 

∆dv

JEC Unit 1 and Unit 2 0.99 59 0.90 63 0.73 37 0.49 21 0.85 53 

GEEC Unit 2 1.08 85 0.40 16 0.38 14 0.17 4 0.42 16 

Westar used the U.S. Environmental Protection Agency’s (EPA’s) guidelines1 in 40 CFR Part 51 to 

determine BART for JEC Unit 1 and Unit 2 and GEEC Unit 2. Specifically, Westar conducted a fivestep analysis to determine BART for SO2, NOX, and PM10 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 

Based on the five-step analysis, Westar proposes the following as BART: 

JEC Unit 1: 

• PM10 – Westar proposes upgrades to the existing electrostatic precipitator (ESP). 

• NOX – Westar proposes to meet a BART limit of 0.15 lb/MMBtu by installing a low-NOX

burner (LNB) system. 

• SO2 – Westar proposes to meet a BART limit of 0.15 lb/MMBtu by rebuilding the existing 

wet scrubber. 

 

1 40 CFR 51, Regional Haze Regulations and Guidelines for Best Available Retrofit Technology (BART) 

Determinations 
Westar Energy 1-2 Trinity Consultants 

BART Analysis 

JEC Unit 2: 

• PM10 – Westar proposes upgrades to the existing ESP. 

• NOX – Westar proposes to meet a BART limit of 0.15 lb/MMBtu by installing a LNB 

system. 

• SO2 – Westar proposes to meet a BART limit of 0.15 lb/MMBtu by rebuilding the existing 

wet scrubber. 

GEEC Unit 2: 

• PM10 – Westar proposes that no additional PM10 controls, other than the fuel switching from 

No.6 fuel oil to natural gas proposed as a BART alternative, are required for PM10 BART 

compliance. Additional PM controls for a gas-fired unit would provide little visibility 

improvement and require significant capital expenditures. 

• NOX and SO2 – Westar proposes to meet the BART control requirement by switching from 

combusting No. 6 fuel oil to combusting natural gas, exclusively, except as discussed in 

Section 9 of this document. 

 

The proposed BART control strategies will result in reductions of the visibility impacts attributable to 

JEC Unit 1 and Unit 2 and GEEC Unit 2. A summary of the visibility improvement based on the 

existing emission rates and proposed BART emission rates for JEC Unit 1 and Unit 2 is provided in 

Table 1-2. A summary of the visibility improvement based on the existing emission rates for GEEC 

Unit 2 and the BART control strategy for GEEC Unit 2 is provided in Table 1-3. 

TABLE 1-2. VISIBILITY IMPAIRMENT IMPROVEMENT FROM JEC UNIT 1 AND UNIT 2 (2001-2003) 

 

Caney Creek 

Wilderness 

Hercules Glades 

Wilderness Mingo NWR 

Upper Buffalo 

Wilderness Wichita Mountains 

 

Existing BART Improvement Existing BART Improvement Existing BART Improvement Existing BART Improvement Existing BART Improvement 

Max 

Impact 

(Δdv) 2.74 0.85 69% 2.70 0.75 72% 1.44 0.44 69% 2.73 0.84 69% 3.51 1.19 66% 

98% 

Impact 

(Δdv) 0.73 0.23 70% 0.90 0.30 67% 0.49 0.16 69% 0.85 0.25 71% 0.99 0.32 68% 

Days 

> 0.5 37 4 89% 63 4 94% 21 0 100% 53 3 94% 59 11 81% 
Westar Energy 1-3 Trinity Consultants 

BART Analysis 

TABLE 1-3. VISIBILITY IMPAIRMENT IMPROVEMENT FROM GEEC UNIT 2 (2001-2003) 

 

Caney Creek 

Wilderness 

Hercules Glades 

Wilderness Mingo NWR 

Upper Buffalo 

Wilderness Wichita Mountains 

 

Existing BART* Improvement Existing BART* Improvement Existing BART* Improvement Existing BART* Improvement Existing BART* Improvement 

Max 

Impact 

(Δdv) 1.07 0.49 54% 1.31 0.93 29% 0.71 0.49 31% 2.22 1.62 27% 2.16 1.66 23% 

98% 

Impact 

(Δdv) 0.38 0.25 34% 0.4 0.21 48% 0.17 0.08 55% 0.42 0.28 33% 1.08 0.69 36% 

Days 

> 0.5 14 0 100% 16 4 75% 4 0 100% 16 11 31% 85 44 48% 

* Based on the BART alternative presented in Section 9
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BART Analysis 

2. INTRODUCTION AND BACKGROUND

On July 1, 1999, the U.S. 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 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 background. 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 reasonable 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 

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: 
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BART Analysis 

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. 

Westar performed a BART applicability analysis for JEC Unit 1 and Unit 2 and GEEC Unit 2 and 

determined the units are subject to BART. The details of the applicability determination can be found

in Section 3. Subsequently, Westar performed an analysis to determine BART for each VAP for JEC 

Unit 1 and Unit 2 and GEEC Unit 2. The VAPs emitted by JEC Unit 1 and Unit 2 and GEEC Unit 2 

include NOx, SO2, and particulate matter with a mass mean diameter smaller than ten microns (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 4, 5, and 6, 

respectively. 

EPA established presumptive limits in the BART guidelines for coal-fired electric generating units 

(EGUs). The presumptive limits were established by reviewing BART-eligible units and determining 

a level of emissions reductions that would be cost effective. The EPA’s BART guidelines state the 

following with regard to presumptive BART for coal-fired EGU units for SO2 : 

“You must require 750 MW power plants to meet specific control levels for SO2 of 

either 95 percent control or 0.15 lb/MMBtu... For coal fired EGUs with an existing 

post combustion SO2 controls achieving less than 50 percent removal efficiencies, we 

recommend that you evaluate construction a new FGD system to meet the same 

emission limit as above (95 percent removal or 0.15 lb/MMBtu)” 

For power plants greater than 750 MW, EPA requires that state agencies apply the presumptive 

BART limit as a floor for SO2. Thus, the SO2 presumptive limit for both JEC Unit 1 and Unit 2 is 

0.15 lb/MMBtu. 

Similarly, the guidelines provide presumptive NOX limits for coal-fired EGUs. JEC Unit 1 

and Unit 2 are tangential-fired units burning sub-bituminous coal; the guidelines state that the 

NOX presumptive limit is 0.15 lb/MMBtu for this type of EGU. 

The BART guidelines state the following with regard to presumptive BART controls for oilfired boilers: 

“For oil-fired and gas-fired EGUs larger than 200 MW, we believe that installation of 

current combustion control technology to control NOX is generally highly cost-effective and 

should be considered in your determination of BART for these sources.” 

EPA also established presumptive SO2 controls for oil-fired EGUs. For oil-fired units, the guidelines 

state that sources of all sizes should evaluate limiting the sulfur content of the fuel oil to 1 percent or 
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BART Analysis 

less by weight as BART. Thus, the SO2 presumptive limit for GEEC Unit 2 is fuel oil sulfur content 

of 1 percent. 

The BART guidelines do not specify presumptive BART limits for PM10 emissions. 
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BART Analysis 

3. BART APPLICABILITY DETERMINATION

As stated in Section 2, 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 of the visibility impacts from the source is greater than 0.5 ∆dv when 

compared against a natural background. Westar conducted air quality modeling to predict the 

existing visibility impairment attributable to JEC Unit 1 and Unit 2 and GEEC Unit 2 in the following 

Class I areas: 

▲ Wichita Mountains 

▲ Hercules Glades Wilderness 

▲ Upper Buffalo Wilderness 

▲ Caney Creek Wilderness 

▲ Mingo National Wildlife Refuge (NWR) 

The modeling methods and procedures that were followed were provided to the Kansas Department 

of Health and Environment (KDHE) in a modeling protocol in September 2006. Table 3-1 

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 2002-2004 continuous emissions monitoring system (CEMS) data. The PM10 emission rates are 

the calculated highest emission rates based on fuel data from 2002-2004 and AP-42 emission factors. 

The total PM10 emission rates include both the filterable and condensable fractions and are speciated 

into the following: 

▲ Coarse particulate matter (PMC) 

▲ Fine particulate matter (PMf) 

▲ Sulfates (SO4) 

▲ Secondary organic aerosols (SOA) 

▲ Elemental carbon (EC) 

TABLE 3-1. EXISTING MAXIMUM 24-HOUR SO2,NOX, AND PM10 EMISSIONS (AS HOURLY 

EQUIVALENTS) 

SO2 NOX

Total 

PM10 SO4 PMc PMf SOA EC 

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

JEC Unit 1 6,938.9 3,972.3 327.4 181.9 55.6 42.8 45.5 1.6 

JEC Unit 2 7,128.2 3,924.0 303.9 168.8 51.6 39.8 42.2 1.5 

GEEC Unit 2 5,766.7 4,818.3 431.5 38.7 104.7 260.5 6.8 20.8 

Table 3-2 summarizes the stack parameters that were used to model JEC Unit 1 and Unit 2 and GEEC 

Unit 2 (two stacks). It should be noted that the good engineering practice (GEP) stack heights were 

modeled instead of the actual stack heights for JEC Unit 1 and Unit 2 since the GEP stack heights are 

less than the actual stack heights. 
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BART Analysis 

TABLE 3-2. SUMMARY OF EXISTING STACK PARAMETERS

 JEC Unit 1 JEC Unit 2 

GEEC Unit 2 

(Stack 2A) 

GEEC Unit 2 

(Stack 2B) 

Latitude (degrees) 39.287 39.287 37.793 37.793 

Longitude (degrees) 96.116 96.116 97.518 97.518 

Actual Stack height (ft) 600 600 197 197 

GEP Stack height (ft) 574 574 381 381 

Stack Diameter (ft) 26 26 13 13 

Exhaust Velocity (ft/s) 91.3 91.3 69 69 

Exhaust Temperature (F) 300 300 290 290 

The results of the modeling are summarized in Table 3-3. The results of the modeling indicate that 

the 98th percentile of the visibility impacts attributable to JEC Unit 1 and Unit 2 and GEEC Unit 2 are 

greater than 0.5 Δdv when compared against a natural background. Since the visibility impacts are 

greater than 0.5 Δdv, JEC Unit 1 and Unit 2 and GEEC Unit 2 are subject to BART. 

TABLE 3-3. EXISTING VISIBILITY IMPAIRMENT ATTRIBUTABLE TO JEC UNIT 1 AND UNIT 2 AND 

GEEC UNIT 2 (2001-2003) 

Class I Area

Wichita 

Mountains 

Hercules 

Glades 

Wilderness 

Caney Creek 

Wilderness Mingo NWR 

Upper Buffalo 

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

98th 

% 

∆dv

Days 

> 0.5 

∆dv

JEC Unit 1 and Unit 2 0.99 59 0.90 63 0.73 37 0.49 21 0.85 53 

GEEC Unit 2 1.08 85 0.40 16 0.38 14 0.17 4 0.42 16 

Tables 3-4 and 3-5 provide a breakdown of the visibility impacts listed in Table 3-3 by each VAP for 

JEC and GEEC, respectively. 

TABLE 3-4. BREAKDOWN OF POLLUTANT SPECIFIC CONTRIBUTIONS TO EXISTING VISIBILITY 

IMPAIRMENT FOR JEC UNIT 1 AND UNIT 2 (2001-2003) 

Visibility 

Impairment 

Attributable 

to SO4

Visibility 

Impairment 

Attributable 

to NO3

Visibility 

Impairment 

Attributable 

to SOA 

Visibility 

Impairment 

Attributable 

to EC 

Visibility 

Impairment 

Attributable 

to PMc

Visibility 

Impairment 

Attributable 

to PMf

Total 

Visibility 

Impairment 

98% 

Class I Area (%) (%) (%) (%) (%) (%) (Δdv) 

Wichita Mountains Wilderness 51.13 48.28 0.44 0.04 0.01 0.1 0.99 

Hercules Glades Wilderness 38.21 60.92 0.63 0.06 0.03 0.15 0.90 

Caney Creek Wilderness 40.79 57.87 0.98 0.09 0.05 0.23 0.73 

Mingo Wildlife 43.81 55.53 0.49 0.04 0.01 0.11 0.49 

Upper Buffalo Wilderness 39.6 59.22 0.85 0.08 0.05 0.2 0.85 
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BART Analysis 

TABLE 3-5. BREAKDOWN OF POLLUTANT SPECIFIC CONTRIBUTIONS TO EXISTING VISIBILITY 

IMPAIRMENT FOR GEEC UNIT 2 (2001-2003) 

Visibility 

Impairment 

Attributable 

to SO4

Visibility 

Impairment 

Attributable 

to NO3

Visibility 

Impairment 

Attributable 

to SOA 

Visibility 

Impairment 

Attributable 

to EC 

Visibility 

Impairment 

Attributable 

to PMc

Visibility 

Impairment 

Attributable 

to PMf

Total 

Visibility 

Impairment 

98% 

Class I Area (%) (%) (%) (%) (%) (%) (Δdv) 

Wichita Mountains Wilderness 29.29 67.54 0.16 1.25 0.19 1.57 1.08 

Hercules Glades Wilderness 41.15 57.14 0.09 0.7 0.04 0.88 0.40 

Caney Creek Wilderness 26.11 71.72 0.12 0.89 0.04 1.11 0.38 

Mingo Wildlife 63.14 34.96 0.1 0.78 0.03 0.98 0.17 

Upper Buffalo Wilderness 35.67 62.6 0.09 0.71 0.02 0.89 0.42 

As shown in Tables 3-4 and 3-5, the most significant contributors to the visibility impairment are 

sulfates (SO4) and nitrates (NO3). The SO4 contribution is primarily from the chemical conversion of 

SO2 emitted by JEC Unit 1 and Unit 2 and GEEC Unit 2 to SO4; a very small fraction is from SO4

emitted as condensable particulate. The NO3 contribution is entirely from the chemical conversion of 

NOX emitted from JEC Unit 1 and Unit 2 and GEEC Unit 2. The contribution of PM10 to the total 

visibility impairment can be estimated as the sum of the contributions from SOA, EC, PMc, and PMf. 

The PM10 contribution is less than the contribution from SO2 and NOX. 
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BART Analysis 

4. JEC SO2 BART EVALUATION

The existing maximum 24-hour SO2 emission rates that were modeled for the BART applicability 

determination are summarized in Table 4-1. 

TABLE 4-1. EXISTING MAXIMUM 24-HOUR SO2 EMISSION RATES FOR JEC UNIT 1 AND UNIT 2 

Heat Input 

SO2 24-Hour 

Emission Rate 

SO2 Hourly 

Emission Rate 

SO2 Emission 

Rate 

 (MMBtu/hr) (ton/24-hr) (lb/hr) (lb/MMBtu) 

JEC Unit 1 8,110 83.3 6,938.9 0.86 

JEC Unit 2 8,110 85.5 7,128.2 0.88 

4.1 IDENTIFICATION OF AVAILABLE RETROFIT SO2 CONTROL 

TECHNOLOGIES

Step 1 of the BART determination is the identification of all available retrofit SO2 control 

technologies. A list of control technologies was obtained by reviewing the U.S. EPA’s Clean Air 

Technology Center, control equipment vendor information, publicly-available air permits, 

applications, and technical literature published by the U.S. EPA and Regional Planning Organizations 

(RPOs). 

The available retrofit SO2 control technologies are summarized in Table 4-2 for JEC Unit 1 and 2. 

TABLE 4-2. AVAILABLE SO2 CONTROL TECHNOLOGIES FOR JEC UNIT 1 AND UNIT 2 

SO2 Control Technologies 

Dry Sorbent Injection 

Spray Dryer Absorber (SDA) i.e., Semi-Dry Scrubber 

Wet Scrubber 

Circulating Dry Scrubber (CDS) 

All of the technologies listed in Table 4-2 involve removing the SO2 in the exhaust gas, which is 

known as flue gas desulfurization (FGD). 

4.2 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. 

4.2.1 DRY SORBENT INJECTION

Dry sorbent injection involves the injection of a lime or limestone powder into the exhaust 

gas stream where SO2 becomes entrained in the lime. The stream is then passed through a 

fabric filter to remove the sorbent and entrained SO2. The process was developed as a 

lower cost FGD option because the mixing of the SO2 and lime occurs directly in the 
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BART Analysis 

exhaust gas stream instead of in a separate tower. Depending on the residence time and 

gas stream temperature, sorbent injection control efficiency is typically between 40 and 60 

percent.2 This control is a technically feasible option for the control of SO2 from JEC Unit 

1 and Unit 2. 

4.2.2 SPRAY DRYER ABSORPTION (SDA) 

Spray dryer absorption is a semi-dry scrubbing system that sprays a fine mist of lime slurry 

into an absorption tower where the SO2 is absorbed by the slurry droplets. The absorption 

of the SO2 leads to the formation of calcium sulfite and calcium sulfate within the droplets. 

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. Existing 

spray dryer absorption control efficiencies range from 60 to 95 percent.3 This control is a 

technically feasible option for the control of SO2 from JEC Unit 1 and Unit 2. 

4.2.3 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 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 spray dryer absorption, 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.4 This 

control is a technically feasible option for the control of SO2 from JEC Unit 1 and Unit 2. 

4.2.4 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. CDS absorbers have been installed with both fabric filters and ESPs for 

particulate control. The control efficiency of a CDS is similar to that of an SDA. This 

control is a technically feasible option for the control of SO2 from JEC Unit 1 and Unit 2. 

 

2 "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. 

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

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

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

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

4.3 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 

effectiveness. Table 4-3 provides a ranking of the control efficiencies for the controls listed in the 

previous section for JEC Unit 1 and 2. 

TABLE 4-3. CONTROL EFFECTIVENESS OF TECHNICALLY FEASIBLE SO2 CONTROL 

TECHNOLOGIES FOR JEC UNIT 1 AND UNIT 2 

Control Technology 

Estimated Control 

Efficiency 

Wet Scrubber ~80-95% 

Spray Dryer Absorber (SDA) ~60-95% 

Circulating Dry Scrubber (CDS) ~60-95% 

Dry Sorbent Injection ~40-60% 

Since dry sorbent injection has the lowest control level of the controls listed in Table 4-3, this control 

will no longer be evaluated. 

4.4 EVALUATION OF IMPACTS FOR FEASIBLE SO2 CONTROLS 

Step four for 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 

4.4.1 COST OF COMPLIANCE

The three remaining SO2 control options (wet scrubbers, SDA, CDS) for JEC Unit 1 and 

Unit 2 are FGD systems capable of achieving similar maximum levels of SO2 reductions. 

Westar will only evaluate wet scrubbers for BART. Since this control option achieves an 

equally high level of control as the other control options, cost analyses are not necessary. 

4.4.2 ENERGY IMPACTS AND NON-AIR QUALITY IMPACTS

FGD systems require electricity to operate the ancillary equipment. Additionally, wet 

FGD systems generate wastewater and sludge that must be treated. This places additional 

burdens on the wastewater treatment and solid waste management capabilities. If wet 

scrubbing produces calcium sulfite sludge, the sludge will be water-laden, and it must be 

stabilized for landfilling. If wet scrubbing produces calcium sulfate sludge, it is stable and 

easy to dewater. However, control costs will be higher because additional equipment is 

required. 
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BART Analysis 

4.4.3 REMAINING USEFUL LIFE

The remaining useful life of JEC Unit 1 and Unit 2 does not impact the annualized capital 

costs because the useful lives of the units are anticipated to be at least as long as the capital 

cost recovery period, which is 20 years. 

4.5 EVALUATION OF VISIBILITY IMPACT OF FEASIBLE SO2 CONTROLS 

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

when compared to the emission rates of associated with a wet scrubber. The existing emission rates 

and emission rates associated with a wet scrubber were modeled using CALPUFF. The existing 

emission rates are the same rates that were modeled for the BART applicability analysis. The 

emission rate associated with the wet scrubber is 0.15 lb/MMBtu multiplied by the maximum hourly 

heat inputs for JEC Unit 1 and Unit 2. A sample calculation of the SO2 emission rate associated with 

a wet scrubber for JEC Unit 1 is provided as follows: 

P* HI = 1,216.5 lb/hr 

Where: 

P (emission rate of wet scrubber) = 0.15 lb/MMBtu 

HI (hourly heat input) = 8,110 MMBtu/hr 

The existing hourly equivalent of the maximum 24-hour emission rates and the hourly equivalent of 

the 24-hour emission rates associated with the wet scrubber that were utilized in the visibility impact 

modeling are summarized in Table 4-4. 

TABLE 4-4. SUMMARY OF EMISSION RATES MODELED IN SO2 CONTROL VISIBILITY IMPACT 

ANALYSIS FOR JEC UNIT 1 AND UNIT 2 

Unit Emission Rate Scenario Emission Rate 

 SO2 NOX PM10*

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

JEC Unit 1 Existing Emission Rate 6,938.9 3,972.3 327.4 

 Wet Scrubber 1,216.5 3,972.3 327.4 

JEC Unit 2 Existing Emission Rate 7,128.2 3,924.0 303.9 

 Wet Scrubber 1,216.5 3,924.0 303.9 

*PM10 emissions are calculated based on AP-42 emission factors. 

Comparisons of the existing visibility impacts and the visibility impacts based on the wet scrubber, 

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 Tables 4-5 and 4-6 for JEC Unit 1 and JEC Unit 2, respectfully. The visibility 

improvement associated with the wet scrubber is also shown in Tables 4-5 and 4-6; this value was 

calculated as the difference between the existing visibility impairment and the visibility impairment 

for the wet scrubber as measured by the 98th percentile modeled visibility impact. 
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BART Analysis 

TABLE 4-5. SUMMARY OF MODELED IMPACTS FROM SO2 CONTROL VISIBILITY IMPACT ANALYSIS FOR JEC UNIT 1 (2001-2003) 

Wichita Mountains 

Hercules Glades 

Wilderness 

Caney Creek 

Wilderness Mingo NWR 

Upper Buffalo 

Wilderness 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

v) 98% Impact (Δd

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Existing Emission Rate 1.91 0.51 24 - 1.44 0.47 19 - 1.46 0.37 11 - 0.75 0.25 5 - 1.45 0.43 17 - Wet Scrubber 1.22 0.34 10 33% 0.78 0.30 6 36% 0.95 0.22 5 42% 0.48 0.16 0 34% 0.88 0.27 6 39% 

*Improvement is based on the 98th percentile visibility impact (Δdv) of the wet scrubber over the existing emission rate. 
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BART Analysis 

TABLE 4-6. SUMMARY OF MODELED IMPACTS FROM SO2 CONTROL VISIBILITY IMPACT ANALYSIS FOR JEC UNIT 2 (2001-2003) 

Wichita Mountains 

Hercules Glades 

Wilderness 

Caney Creek 

Wilderness Mingo NWR 

Upper Buffalo 

Wilderness 

 

M a x i m u m I m p a c t ( Δ d v )9 8 % I m p a c t ( Δ d v )

# D a y s > 0 . 5 Δ d vV i s i b i l i t y I m p r o v e m e n t * M a x i m u m I m p a c t ( Δ d v )9 8 % I m p a c t ( Δ d v )# D a y s > 0 . 5 Δ d vV i s i b i l i t y I m p r o v e m e n t * M a x i m u m I m p a c t ( Δ d v )9 8 % I m p a c t ( Δ d v )# D a y s > 0 . 5 Δ d vV i s i b i l i t y I m p r o v e m e n t * M a x i m u m I m p a c t ( Δ d v )9 8 % I m p a c t ( Δ d v )# D a y s > 0 . 5 Δ d v

V i s i b i l i t y I m p r o v e m e n t * M a x i m u m I m p a c t ( Δ d v )9 8 % I m p a c t ( Δ d v )# D a y s > 0 . 5 Δ d vV i s i b i l i t y I m p r o v e m e n t * 

Existing Emission Rate 1.91 0.51 24 - 1.45 0.46 20 - 1.47 0.37 11 - 0.75 0.25 5 - 1.47 0.43 17 - 

Wet Scrubber 1.20 0.33 10 34% 0.77 0.30 4 36% 0.93 0.21 5 43% 0.47 0.16 0 36% 0.87 0.26 6 40% 

*Improvement is based on the 98th percentile visibility impact (Δdv) of a wet scrubber over the existing emission rate. 
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BART Analysis 

As shown in Table 4-5, the operation of a wet scrubber on JEC Unit 1 results in a 33 to 42 percent 

improvement (depending on the Class I area) to the existing visibility impairment attributable to this

unit. Similarly, as shown in Table 4-6, the operation of wet scrubbers on JEC Unit 2 results in a 34 to 

43 percent improvement (depending on the Class I area) to the existing visibility impairment 

attributable to this unit. 

4.6 PROPOSED BART FOR SO2

Westar has determined that the SO2 BART emission rate for JEC Unit 1 and Unit 2 is 0.15 lb/MMBtu 

based on the operation of wet scrubbers. Westar is proposing to meet this limit for each unit on a 30-

day rolling average, excluding periods of startup, shutdown and malfunction. Compliance will be 

demonstrated using data from the existing continuous emissions monitoring systems (CEMS). 
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BART Analysis 

5. JEC NOX BART EVALUATION

The existing maximum daily NOX emission rates that were modeled for the BART applicability 

determination are summarized in Table 5-1. 

TABLE 5-1. EXISTING MAXIMUM 24-HOUR NOX EMISSION RATE FOR JEC UNIT 1 AND UNIT 2 

Heat Input 

NOX 24-Hour 

Emission Rate 

NOX Hourly 

Emission Rate 

NOX Emission 

Rate 

 (MMBtu/hr) (ton/24-hr) (lb/hr) (lb/MMBtu) 

JEC Unit 1 8,110 47.7 3,972.3 0.49 

JEC Unit 2 8,110 47.1 3,924.0 0.48 

5.1 IDENTIFICATION OF AVAILABLE RETROFIT NOX CONTROL 

TECHNOLOGIES

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

technologies. A list of control technologies was obtained by reviewing the U.S. EPA’s Clean Air 

Technology Center, control equipment vendor information, publicly-available air permits, 

applications, and technical literature published by the U.S. EPA and the RPOs. 

The available retrofit NOX control technologies are summarized in Table 5-2 for JEC Unit 1 and 2. 

TABLE 5-2. AVAILABLE NOX CONTROL TECHNOLOGIES FOR JEC UNIT 1 AND UNIT 2

NOX Control Technologies 

Flue Gas Recirculation (FGR) 

Combustion Controls Overfire Air (OFA) 

Low NOX Burners (LNB) and Ultra Low NOX Burners (ULNB) 

Selective Catalytic Reduction (SCR) Post-Combustion Controls 

Selective Non-Catalytic Reduction (SNCR) 

NOX emissions controls, as listed in Table 5-2, 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. 

5.2 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. 
Westar Energy 5-2 Trinity Consultants 

BART Analysis 

5.2.1 COMBUSTION CONTROLS

5.2.1.1 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 heater 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 efficiency range for FGR is 30 

percent to 50 percent. When coupled with LNB the control efficiency increases 

to 50-72 percent.5 This control is a technically feasible option for the control of 

NOX from JEC Unit 1 and Unit 2. 

5.2.1.2 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 may reduce NOX emissions by 25 to 55 

percent. When combined with LNB, reductions of up to 60 percent may 

result.6 This control is a technically feasible option for the control of NOX from 

JEC Unit 1 and Unit 2. 

5.2.1.3 LOW AND ULTRA 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. 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 either 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 

 

5 "Midwest Regional Planning Organization Boiler Best Available Retrofit Technology (BART) Engineering 

Analysis" MACTEC, March 30, 2005. 

6 "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 
Westar Energy 5-3 Trinity Consultants 

BART Analysis 

products formed in the primary zone act to lower the local oxygen 

concentration, resulting in a decrease in NOX formation. The estimated NOX

control efficiency for LNBs in high temperature applications is 25 percent. 

However when coupled with FGR or SNCR these efficiencies increase to 50-72 

and 50-89 percent, respectively.7

ULNBs may incorporate a variety of techniques including induced FGR, steam 

injection, or a combination of techniques. These burners combine the benefits 

of flue gas recirculation and LNB control technologies. Rather than a system of 

fans and blowers (like FGR), the burner is designed to recirculate hot, oxygen 

depleted flue gas from the flame or firebox back into the combustion zone. 

This leads to a reduction in the average oxygen concentration in the flame 

without reducing the flame temperature below temperatures necessary for 

optimal combustion efficiency. 

LNBs may also be coupled with neural net systems to further optimize 

combustion. Neural net systems are computer automated systems that measure 

certain operational parameters associated with combustion. Based on these 

measured parameters, the neural net systems can either automatically adjust 

operational parameters to achieve optimal operation or provide 

recommendations to operators of changes to boiler control elements. By 

accepting the recommendations, NOX and unit heat rate can be optimized for 

best overall performance. 

The estimated NOX control efficiency for ULNBs in high temperature 

applications is 50 percent. Newer designs have yielded efficiencies of between 

75-85 percent. When coupled with SCR, efficiencies in the range of 85-97 

percent can be obtained.8 

LNB systems are technically feasible for tangential and wall-fired boilers of 

various sizes, but are not feasible for other boiler types such as cyclone or 

stoker. 9 LNB systems are technically feasible for the control of NOx from JEC 

Unit 1 and Unit 2. 

5.2.2 POST COMBUSTION CONTROLS

5.2.2.1 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 

 

7 "Midwest Regional Planning Organization Boiler Best Available Retrofit Technology (BART) Engineering 

Analysis" MACTEC, March 30, 2005. 

8 Interim White Paper “Source Category: Electric Generating Units” Midwest RPO Candidate Control Measures, 

December 9, 2005 

9 AP 42, Fifth Edition, Volume I Chapter 1 Section 1.1.4.3
Westar Energy 5-4 Trinity Consultants 

BART Analysis 

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 can be written: 

4NO + 4NH3 + O2 à 4N2 + 6H2O 

2NO2 + 4NH3 + O2 à 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 NOX control efficiency 

range for SCR is 70 to 90 percent.10 This control is a technically feasible 

option for the control of NOX from JEC Unit 1 and Unit 2. 

5.2.2.2 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, because of higher stoichiometric ratios, 

both ammonia and urea SNCR processes require three or four times as much 

reagent as SCR systems to achieve similar NOx reductions. The NOX control 

efficiency range for SNCR is 25 to 50 percent.11 This control is a technically 

feasible option for the control of NOX from JEC Unit 1 and Unit 2. 

5.3 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 5-3 provides a ranking of the NOx control efficiencies for JEC Unit 1 and JEC 

Unit 2. 

 

10 Ibid. 

11 Interim White Paper “Source Category: Electric Generating Units” Midwest RPO Candidate Control Measures, 

December 9, 2005. 
Westar Energy 5-5 Trinity Consultants 

BART Analysis 

TABLE 5-3. CONTROL EFFECTIVENESS OF TECHNICALLY FEASIBLE NOX CONTROL 

TECHNOLOGIES

Control Technology 

Estimated Control 

Efficiency 

(%) 

SCR ~70-90 

LNB Systems ~30-60 

FGR ~30-50 

OFA ~25-55 

LNB Only ~25-50 

SNCR ~25-50 

5.4 EVALUATION OF IMPACTS FOR FEASIBLE NOX CONTROLS 

Step four for the BART analysis procedure is the impact analysis. The BART determination 

guidelines list 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 

5.4.1 COST OF COMPLIANCE

The capital costs, operating costs, and cost effectiveness of LNB systems and SCR were 

estimated for the cost analysis. LNB systems refer to a control system which includes 

LNB and possibly OFA or neural net systems. These control options were included in the 

analysis because they provide the highest levels of control and are commonly used for NOX

control in large utility boilers. 

Control Costs

The capital cost of the LNB systems for JEC Unit 1 and Unit 2 was estimated based on 

Westar’s experience with the capital costs for a similar project on JEC Unit 3, and the 

operating costs were estimated using an EPA cost estimate method.12 Westar is still 

experiencing what type of operating costs to expect from a LNB system project, but project 

specific data from which to base the annual operating costs over the operating life of the 

system does not yet exist, so an EPA estimate was relied upon. 

The capital cost for the SCR was determined from recent SCR installation experience. The 

operating and maintenance costs for the SCR were estimated using an EPA cost method.13 

The EPA estimates for the operating and maintenance costs are considered to be study 

grade, which is +/- 30 percent accuracy. 

 

12 Nitrogen Oxides (NOX), Why and How They Are Controlled. EPA 456/F-99-006R, November 1999. 

13 Cost of Selective Catalytic Reduction (SCR) Application for NOx Control on Coal-fired Boiler. EPA 600/R01/087, October 2001. 
Westar Energy 5-6 Trinity Consultants 

BART Analysis 

The capital costs were annualized over a 20-year period and then added to the annual 

operating costs to obtain the total annualized costs for each technology. 

Annual Tons Reduced

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

estimated by subtracting the estimated controlled annual emission rates from the existing 

annual emission rates. The existing annual emission rates were the highest 365 day rolling 

totals as determined from CEMS data from 2002-2004. 

The controlled annual emission rates were estimated based on NOX emission rates of 0.15 

lb/MMBtu for LNB systems and 0.10 lb/MMBtu for SCR. These emission rates were 

multiplied by the maximum hourly heat input (8,110 MMBtu/hr) and then multiplied by 

the annual number of operating hours. The annual number of operating hours was 8,760. 

The annual operating hours were based on the maximum number of annual operating hours 

of JEC Unit 1and Unit 2 from 2002-2004. The maximum annual operating time was 

approximately 94 percent for JEC Unit 1 and 96 percent for JEC Unit 2; therefore, an 

estimated 100 percent factor was used for both units. A sample of the controlled annual 

emission rate is shown as follows for a LNB system for JEC Unit 1: 

*100%

,2 000

*

,8 760 .0 15 / * ,8110 / *

lb

ton

yr

hrs lb MMBtu MMBtu hr =5,220 tpy 

Cost Effectiveness

The cost effectiveness for the remaining two control options was determined by dividing 

the annual cost by the annual tons reduced. The incremental cost effectiveness was also 

calculated for the two control options. In this case, the incremental cost analysis was 

performed to show the incremental increase in costs between the SCR and the LNB 

system. The costs are summarized for JEC Unit 1 and JEC Unit 2 in Tables 5-4 and 5-5, 

respectively. 

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 

NOX removed based on the use of combustion control technology. 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 cost of such controls are usually less than $1,500 per 

ton removed. 

Tables 5-4 and 5-5 indicate that the cost effectiveness of LNB systems for JEC Unit 1 and 

Unit 2 is less than $1,500 per ton of NOX removed. Tables 5-4 and 5-5 also indicate that 

the costs for SCR for JEC Unit 1 and Unit 2 are over $1500 per ton of NOX removed (JEC 

Unit 1 SCR cost = $2,211/ton and JEC Unit 2 SCR cost = $1,738/ton). Additionally, the 
Westar Energy 5-7 Trinity Consultants 

BART Analysis 

incremental costs of the SCR over the LNB systems are greater than $6,600 per ton of NOX

removed for JEC Unit 1 and Unit 2. Westar believes that the incremental costs are 

excessive. 
Westar Energy 5-8 Trinity Consultants 

BART Analysis 

TABLE 5-4. SUMMARY OF COST EFFECTIVENESS FOR JEC UNIT 1 NOX CONTROLS

Current 

Annual 

Emission 

Rate 

Controlled 

Annual 

Emission 

Rate 

Annual 

Emissions 

Reduced 

Capital 

Cost 

Annualized 

Capital 

Cost* 

Annualized 

Fixed 

O&M* 

Annualized 

Variable 

O&M* 

Total 

Annualized 

Cost* 

Cost 

Effectiveness 

Incremental 

Cost 

 (tpy) (tpy) (ton/yr) ($) ($/yr) ($/yr) ($/yr) ($/yr) ($/ton) ($/ton) LNB System 9,524 5,220† 4,304 11,500,000 1,350,790 506,709 0 1,857,499 432 - SCR 9,524 3,480‡ 6,044 81,000,000 9,514,260 338,492 3,510,068 13,362,820 2,211 6,613 

*The costs are annualized in 2006 dollars. †The LNB system represents an emission rate of 0.15 lb/MMBtu. 

‡The SCR represents an emission rate of 0.1 lb/MMBtu. 

TABLE 5-5. SUMMARY OF COST EFFECTIVENESS FOR JEC UNIT 2 NOX CONTROLS

Current 

Annual 

Emission 

Rate 

Controlled 

Annual 

Emission 

Rate 

Reduced 

Emissions 

Capital 

Cost 

Annualized 

Capital 

Cost* 

Annualized 

Fixed 

O&M* 

Annualized 

Variable 

O&M* 

Total 

Annualized 

Cost* 

Cost 

Effectiveness 

Incremental 

Cost 

 (tpy) (tpy) (ton/yr) ($) ($/yr) ($/yr) ($/yr) ($/yr) ($/ton) ($/ton) LNB System** 11,115 5,156† 5,959 11,500,000 1,350,790 506,709 0 1,857,499 312 - SCR*** 11,115 3,437‡ 7,677 81,000,000 9,514,260 338,420 3,493,270 13,345,950 1,738 6,684 

*The costs are annualized in 2006 dollars. †The LNB w/ OFA emission rate represents an emission rate of 0.15 lb/MMBtu. 

‡ The SCR represents an emission rate of 0.1 lb/MMBtu. 
Westar Energy 5-9 Trinity Consultants 

BART Analysis 

5.4.2 ENERGY IMPACTS & NON-AIR IMPACTS

SCR systems require electricity to operate the ancillary equipment. Additionally, the SCR 

can potentially cause significant environmental impacts related to the usage and storage of 

ammonia. 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. Ammonia can also 

be emitted in the exhaust of boilers that operate with SCR or SNCR for NOX control due to 

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. 

Together, ammonium sulfate and ammonium nitrate are the predominant sources of 

regional haze. 

5.4.3 REMAINING USEFUL LIFE

The remaining useful life of JEC Unit 1 and Unit 2 do not impact the annualized capital 

costs of potential controls because the useful lives of the units are anticipated to be at least 

as long as the capital cost recovery period, which is 20 years. 

5.5 EVALUATION OF VISIBILITY IMPACT OF FEASIBLE NOX CONTROLS 

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

rates when compared to the emission rates associated with SCR and LNB systems. The existing 

emission rates and emission rates associated with SCR and LNB systems were modeled using 

CALPUFF. The existing emission rates are the same rates that were modeled for the BART 

applicability analysis. The emission rates associated with SCR and LNB systems for JEC Unit 1 and 

Unit 2 are the presumptive limit of 0.15 lb/MMBtu for LNB systems and 0.10 lb/MMBtu for SCR. 

These rates were multiplied by the maximum hourly heat inputs for JEC Unit 1 and Unit 2 to obtain 

the modeled hourly emission rate. A sample calculation of the NOX emission rate associated with a 

LNB system for JEC Unit 1 is provided as follows: 

E * HI = 1,216.5 lb/hr 

Where: 

E (emission rate of LNB system) = 0.15 lb/MMBtu 

HI (hourly heat input) = 8,110 MMBtu/hr 

 
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BART Analysis 

TABLE 5-6. SUMMARY OF EMISSION RATES MODELED IN NOX CONTROL VISIBILITY IMPACT 

ANALYSIS FOR JEC UNIT 1 AND JEC UNIT 2 

Unit Emission Rate Scenario Emission Rate 

 SO2 NOX PM10

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

JEC Unit 1 Existing Emission Rate 6,938.9 3,972.3 327.4 

 LNB System 6,938.9 1,216.5 327.4 

 SCR 6,938.9 811.0 327.4 

JEC Unit 2 Existing Emission Rate 7,128.2 3,924.0 303.9 

 LNB System 7,128.2 1,216.5 303.9 

 SCR 7,128.2 811.0 303.9 

Comparisons of the existing visibility impacts and the visibility impacts associated with SCR and 

LNB systems, 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 Tables 5-8 and 5-9 for JEC Unit 1 and JEC Unit 2, respectively. The visibility

improvement associated with SCR and LNB systems are also shown in Tables 5-7 and 5-8; this value 

was calculated as the difference between the existing visibility impairment and the visibility 

impairment associated with SCR and LNB systems as measured by the 98th percentile modeled 

visibility impact. 
Westar Energy 5-11 Trinity Consultants 

BART Analysis 

TABLE 5-7. SUMMARY OF MODELED IMPACTS FROM NOX CONTROL VISIBILITY IMPACT ANALYSIS FOR JEC UNIT 1 (2001-2003) 

Wichita Mountains 

Hercules Glades 

Wilderness 

Caney Creek 

Wilderness Mingo NWR 

Upper Buffalo 

Wilderness 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

) Maximum Impact (Δdv

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Existing Emission Rate 1.91 0.51 24 - 1.44 0.47 19 - 1.46 0.37 11 - 0.75 0.25 5 - 1.45 0.43 17 - LNB System 1.34 0.34 11 33% 1.08 0.35 4 26% 1.04 0.25 6 33% 0.50 0.18 0 27% 1.23 0.32 4 25% SCR 1.26 0.31 11 38% 1.03 0.32 4 31% 0.97 0.23 6 39% 0.46 0.18 0 30% 1.20 0.31 3 29% 

*Improvement is based on the 98th percentile impact visibility impact (Δdv) of an LNB system and SCR over the existing emission rate. 
Westar Energy 5-12 Trinity Consultants 

BART Analysis 

TABLE 5-8. SUMMARY OF MODELED IMPACTS FROM NOX CONTROL VISIBILITY IMPACT ANALYSIS FOR JEC UNIT 2 (2001-2003) 

 Wichita Mountains 

Hercules Glades 

Wilderness 

Caney Creek 

Wilderness Mingo NWR 

Upper Buffalo 

Wilderness 

 

M a x i m u m I m p a c t ( Δ d v )9 8 % I m p a c t ( Δ d v )# D a y s > 0 . 5 Δ d vV i s i b i l i t y I m p r o v e m e n t * M a x i m u m I m p a c t ( Δ d v )9 8 % I m p a c t ( Δ d v )# D a y s > 0 . 5 Δ d vV i s i b i l i t y I m p r o v e m e n t * M a x i m u m I m p a c t ( Δ d v )9 8 % I m p a c t ( Δ d v )# D a y s > 0 . 5 Δ d vV i s i b i l i t y I m p r o v e m e n t * M a x i m u m I m p a c t ( Δ d v ) 9 8 % I m p a c t ( Δ d v )# D a y s > 0 . 5 Δ d vV i s i b i l i t y I m p r o v e m e n t * M a x i m u m I m p a c t ( Δ d v )9 8 % I m p a c t ( Δ d v )# D a y s > 0 . 5 Δ d vV i s i b i l i t y I m p r o v e m e n t * 

Existing Emission Rate 1.91 0.51 24 - 1.45 0.46 20 - 1.47 0.37 11 - 0.75 0.25 5 - 1.47 0.43 17 - 

LNB System 1.36 0.34 11 32% 1.10 0.34 4 25% 1.05 0.25 6 32% 0.50 0.19 1 25% 1.24 0.33 4 23% 

SCR 1.27 0.32 11 37% 1.04 0.33 4 28% 0.99 0.23 6 38% 0.47 0.18 0 29% 1.21 0.31 3 28% 

*Improvement is based on the 98th percentile impact visibility impact (Δdv) of an LNB system and SCR over the existing emission rate. 
Westar Energy 5-13 Trinity Consultants 

BART Analysis 

As shown in Table 5-7, the installation of a LNB system on JEC Unit 1 results in a 25 to 33 percent 

improvement (depending on the Class I area) to the existing visibility impairment attributable to this

unit. The installation of SCR results in 29 to 39 percent visibility improvement. Similarly, as shown 

in Table 5-8, the installation of a LNB system on JEC Unit 2 results in a 23 to 32 percent 

improvement (depending on the Class I area) to the existing visibility impairment attributable to this

unit. The installation of SCR results in 28 to 38 percent visibility improvement. In short, the 

visibility improvement based on the installation of LNB systems for JEC Unit 1 and JEC Unit 2 is 

only slightly better than the visibility improvement based on the installation of SCR for the units. 

The slight increase in visibility improvement does not offset the large incremental cost of installing

SCR over LNB systems. 

5.6 PROPOSED BART FOR NOX 

Westar has determined that the NOX BART emission rate is 0.15 lb/MMBtu for both JEC Unit 1 and 

Unit 2. Westar proposes to meet this limit for both JEC Unit 1 and Unit 2 by installing LNB systems. 

Westar has eliminated SCR as BART due to the high incremental cost of SCR over LNB systems and 

the minimal increase in visibility improvement. 
Westar Energy 6-1 Trinity Consultants 

BART Analysis 

6. GEEC SO2 BART EVALUATION

The existing maximum 24-hour SO2 emission rates that were modeled for the BART applicability 

determination are summarized in Table 6-1. 

TABLE 6-1. EXISTING MAXIMUM 24-HOUR SO2 EMISSION RATES

Heat Input 

SO2 24-Hour 

Emission Rate 

SO2 Hourly 

Emission Rate 

SO2 Emission 

Rate 

 (MMBtu/hr) (ton/24-hr) (lb/hr) (lb/MMBtu) 

GEEC Unit 2 4,110 69.2 5,766.7 1.40 

6.1 IDENTIFICATION OF AVAILABLE RETROFIT SO2 CONTROL 

TECHNOLOGIES

Step 1 of the BART determination is the identification of all available retrofit SO2 control 

technologies. A list of control technologies was obtained by reviewing the U.S. EPA’s Clean Air 

Technology Center, control equipment vendor information, publicly-available air permits, 

applications, and technical literature published by the U.S. EPA and Regional Planning Organizations 

(RPOs). 

The available retrofit SO2 control technologies are summarized in Table 6-2 for GEEC Unit 2. 

TABLE 6-2. AVAILABLE SO2 CONTROL TECHNOLOGIES FOR GEEC UNIT 2 

SO2 Control Technologies 

Dry Sorbent Injection 

Spray Dryer Absorber (SDA) i.e., Semi-Dry Scrubber 

Wet Scrubber 

Circulating Dry Scrubber (CDS) 

Fuel Switching 

6.2 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. 

6.2.1 DRY SORBENT INJECTION, SPRAY DRYER ABSORPTION (SDA), WET SCRUBBER,

CIRCULATING DRY SCRUBBER (CDS) 

These technologies are collectively known as flue gas desulfurization (FGD) systems. 

FGD applications have not been used historically for SO2 control in the U.S. electric 

industry on oil-fired units. As there are no known FGD applications for oil-fired units, the 

performance of FGDs on oil-fired units is unknown. EPA took this into account when 
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BART Analysis 

evaluating the presumptive SO2 emission rate14 for oil-fired units and determined that the 

presumptive emission rate should be based on the sulfur content of the fuel oil, rather than 

on FGD. Therefore, FGDs are considered technically infeasible for the control of SO2

from GEEC Unit 2 and will no longer be considered for BART. 

6.2.2 FUEL SWITCHING TO ONE PERCENT SULFUR FUEL OIL

One percent sulfur fuel oil is listed by EPA as the presumptive BART limit for oil-fired 

units. The one percent sulfur oil is an alternative to the No. 6 fuel oil that is currently 

combusted by GEEC Unit 2. The lower sulfur content of the one percent sulfur fuel oil 

should result in approximately a 33 percent reduction in SO2 emissions from GEEC Unit 2 

as compared to the combustion of the current No. 6 fuel oil, which contains approximately 

1.5 percent sulfur. Fuel switching to 1 percent sulfur fuel oil is a technically feasible 

option for the control of SO2 from GEEC Unit 2. 

6.3 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 

effectiveness. Fuel switching is the only remaining technically feasible control option GEEC Unit 2. 

Westar has estimated that switching to one percent sulfur oil, consistent with the EPA’s presumptive 

BART determination for GEEC Unit 2, would result in approximately a 33% reduction in SO2

emissions from GEEC Unit 2. 

6.4 EVALUATION OF IMPACTS FOR FEASIBLE SO2 CONTROLS 

Step four for 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 

6.4.1 COST OF COMPLIANCE

The cost effectiveness of switching to one percent sulfur fuel oil has been evaluated. 

Control Cost

The cost of the fuel switching that was used in the cost effectiveness calculations was 

determined by calculating the cost of the current No. 6 fuel oil and determining the 

increased cost of switching to one percent sulfur fuel oil. It was assumed in this analysis 

that the fuel switch will not require any capital expenses. The fuel costs for 1 percent fuel 

oil was determined from the most recent fuel costs published by the Energy Information 

 

14 Summary of Comments and Responses on the 2004 and 2001 Proposed Guidelines for Best Available Retrofit

Technology (BART) Determinations Under the Regional Haze Regulations EPA Docket Number OAR-2002-0076. 
Westar Energy 6-3 Trinity Consultants 

BART Analysis 

Administration. The fuel cost for the No. 6 fuel oil is the market price on February 14, 

2007. 

Annual Tons Reduced

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

determined by subtracting the estimated controlled annual emission rates from the existing 

annual emission rates. The existing annual emission rates was the highest 365 day rolling 

totals as determined from CEMS data from 2002-2004. The controlled annual emission 

rate was estimated by reducing the existing annual emission rate by 33%. 

Cost Effectiveness

In the BART guidelines, EPA calculated that that the majority of BART-eligible units 

could meet the presumptive limits at a cost of $400 to $2,000 per ton of SO2 removed, 

based on the use of wet scrubbers and SDA systems. Table 6-3 indicates that the cost of 

switching to 1% sulfur fuel oil is well above this range. 
Westar Energy 6-4 Trinity Consultants 

BART Analysis 

TABLE 6-3. SUMMARY OF COST EFFECTIVENESS FOR SWITCHING FROM NO. 6 OIL TO 1% SULFUR FUEL OIL

Current/Uncontrolled 

Annual SO2

Emission Rate 

Controlled Annual 

SO2 Emission 

Rate 

Estimated Annual 

SO2 Tons Reduced 

Estimated 

SO2 Control 

(tpy) (tpy) (tpy) (%) 

4,303 2,869 1,434 33.33 

Estimated No. 6 

Oil Hourly Usage 

Rate* 

Estimated No. 

6 Oil Annual 

Fuel Usage† 

No. 6 Oil Fuel 

Cost 

Estimated Annual 

No. 6 Oil Fuel 

Cost 

Estimated 1% S 

Fuel Oil Hourly 

Usage Rate* 

Estimated 1% S 

Fuel Oil Annual 

Fuel Usage‡ 

1% S Fuel Oil 

Cost 

Estimated Annual 

1% S Fuel Oil 

Cost 

Mgal/hr Mgal/yr Cents/gal $/yr Mgal/hr Mgal/yr Cents/gal $/yr 

27.40* 108,011† 85 91,809,180 27.96‡ 110,215† 117.1 129,061,884 

*4110 MMBtu/hr/150 MMBtu/Mgal †Annual fuel usage is based on the hourly fuel usage rate and 3,942 annual operating hours (Assuming unit operates at an annual 45% capacity factor, 45% * 8,760 hours = 3,942 hours) 

‡4110 MMBtu/hr/147 MMBtu/Mgal 

Annual Cost of Fuel 

Switching 

SO2 Cost 

Effectiveness 

($/yr) ($/ton) 

37,252,704 25,969 
Westar Energy 6-5 Trinity Consultants 

BART Analysis 

6.4.1.1 ENERGY IMPACTS AND NON-AIR QUALITY IMPACTS

There are no energy or non-air quality impacts associated with fuel switching to 

one percent sulfur fuel oil. 

6.4.1.2 REMAINING USEFUL LIFE

The remaining useful life of GEEC Unit 2 does not impact the annualized cost 

for this analysis, since it is assumed that fuel switching will not require any 

capital costs. 

6.5 EVALUATION OF VISIBILITY IMPACT OF FEASIBLE SO2 CONTROLS 

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

when compared to the emission rates associated with the combustion of one percent sulfur fuel oil. 

The existing emission rate and emission rate associated with the combustion of one percent sulfur fuel

oil were modeled using CALPUFF. The existing emission rates are the same rates that were modeled 

for the BART applicability analysis. 

The SO2 emission rate associated with the combustion of one percent sulfur fuel oil was calculated by 

scaling the hourly equivalent of the maximum 24-hour emission rate for GEEC Unit 2 by the ratio of 

the one percent sulfur fuel oil content and the current maximum sulfur content (1.5%). The 

calculation of the SO2 emission rate for the one percent sulfur fuel oil for GEEC Unit 2 is provided as 

follows: 

Sulfur

Sulfur lb hr

5.1 %

1%

,5 676 / * = 3,845 lb/hr 

The existing hourly equivalent of the maximum 24-hour emission rates and the hourly equivalent of 

the 24-hour emission rates associated with the remaining control option that was utilized in the 

visibility impact modeling are summarized in Table 6-4. 

TABLE 6-4. SUMMARY OF EMISSION RATES MODELED IN SO2 CONTROL VISIBILITY IMPACT 

ANALYSIS 

Unit Emission Rate Scenario Emission Rate 

 SO2 NOX PM10*

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

GEEC Unit 2 Existing Emission Rate 5,766.7 4,818.3 431.5 

 1 Percent Sulfur Fuel Oil 3,844.5 4,818.3 326.3 

*PM10 emissions are calculated based on AP-42 emission factors. 

Comparisons of the existing visibility impacts and the visibility impacts associated with the 

combustion of one percent sulfur fuel oil, 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 6-5 for GEEC Unit 2. The visibility 

improvement associated with the combustion of one percent sulfur fuel oil is also shown in Table 6-5; 
Westar Energy 6-6 Trinity Consultants 

BART Analysis 

this value was calculated as the difference between the existing visibility impairment and the 

visibility impairment for the remaining control option emission rates as measured by the 98th

percentile modeled visibility impact. 
Westar Energy 6-7 Trinity Consultants 

BART Analysis 

TABLE 6-5. SUMMARY OF MODELED IMPACTS FROM SO2 CONTROL VISIBILITY IMPACT ANALYSIS FOR GEEC UNIT 2 (2001-2003) 

Wichita Mountains 

Hercules Glades 

Wilderness 

Caney Creek 

Wilderness Mingo NWR 

Upper Buffalo 

Wilderness 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

) Maximum Impact (Δdv

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Existing Emission Rate 2.16 1.08 85 - 1.31 0.40 16 - 1.07 0.38 14 - 0.71 0.17 4 - 2.22 0.42 16 - One Percent Sulfur Fuel Oil 2.02 0.94 71 13% 1.19 0.34 10 13% 0.87 0.34 9 10% 0.65 0.14 2 16% 2.04 0.38 15 10% 

*Improvement is based on the 98th percentile impact visibility impact (Δdv) of one percent sulfur fuel oil over the existing emission rate. 
Westar Energy 6-8 Trinity Consultants 

BART Analysis 

As shown in Table 6-5, the combustion of 1 percent sulfur fuel oil results in a 10 to 16 percent 

improvement (depending on the Class I area) to the existing visibility impairment attributable to 

GEEC Unit 2. 

6.6 PROPOSED BART FOR SO2

Westar has determined that SO2 BART for GEEC Unit 2 is fuel switching to 1 percent sulfur fuel oil. 

However, Westar is proposing an alternative to BART for GEEC Unit 2. The alternative control for 

GEEC Unit 2 is natural gas combustion; the details of this alternative can be found in Section 9.
Westar Energy 7-1 Trinity Consultants 

BART Analysis 

7. GEEC NOX BART EVALUATION

The existing maximum daily NOX emission rates that were modeled for the BART applicability 

determination are summarized in Table 7-1. 

TABLE 7-1. EXISTING MAXIMUM 24-HOUR NOX EMISSION RATE

Heat Input 

NOX 24-Hour 

Emission Rate 

NOX Hourly 

Emission Rate 

NOX Emission 

Rate 

 (MMBtu/hr) (ton/24-hr) (lb/hr) (lb/MMBtu) 

GEEC Unit 2 4,110 57.8 4,818.3 1.17 

7.1 IDENTIFICATION OF AVAILABLE RETROFIT NOX CONTROL 

TECHNOLOGIES

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

technologies. A list of control technologies was obtained by reviewing the U.S. EPA’s Clean Air 

Technology Center, control equipment vendor information, publicly-available air permits, 

applications, and technical literature published by the U.S. EPA and the RPOs. 

The available retrofit NOX control technologies are summarized in Table 7-2 for GEEC Unit 2. 

TABLE 7-2. AVAILABLE NOX CONTROL TECHNOLOGIES FOR GEEC UNIT 2 

NOX Control Technologies 

Flue Gas Recirculation (FGR) 

Combustion Controls Overfire Air (OFA) 

Low NOX Burners (LNB) and Ultra Low NOX Burners (ULNB) 

Selective Catalytic Reduction (SCR) Post-Combustion Controls 

Selective Non-Catalytic Reduction (SNCR) 

NOX emissions controls, as listed in Table 5-2, 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. 

7.2 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. 
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BART Analysis 

7.2.1 COMBUSTION CONTROLS

7.2.1.1 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 heater 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 efficiency range for FGR is 30 

percent to 50 percent. When coupled with LNB the control efficiency increases 

to 50-72 percent.15 This control is a technically feasible option for the control 

of NOX from GEEC Unit 2. 

7.2.1.2 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 may reduce NOX emissions by 25 to 55 

percent. When combined with LNB, reductions of up to 60 percent may 

result.16 This control is a technically feasible option for the control of NOX

from GEEC Unit 2. 

7.2.1.3 LOW AND ULTRA 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. 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 either 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. The estimated NOX

control efficiency for LNBs in high temperature applications is 25 percent. 

 

15 "Midwest Regional Planning Organization Boiler Best Available Retrofit Technology (BART) Engineering 

Analysis" MACTEC, March 30, 2005. 

16 "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 
Westar Energy 7-3 Trinity Consultants 

BART Analysis 

However when coupled with FGR or SNCR these efficiencies increase to 50-72 

and 50-89 percent, respectively.17

ULNBs may incorporate a variety of techniques including induced FGR, steam 

injection, or a combination of techniques. These burners combine the benefits 

of flue gas recirculation and LNB control technologies. Rather than a system of 

fans and blowers (like FGR), the burner is designed to recirculate hot, oxygen 

depleted flue gas from the flame or firebox back into the combustion zone. 

This leads to a reduction in the average oxygen concentration in the flame 

without reducing the flame temperature below temperatures necessary for 

optimal combustion efficiency. 

LNBs may also be coupled with neural net systems to further optimize 

combustion. Neural net systems are computer automated systems that measure 

certain operational parameters associated with combustion. Based on these 

measured parameters, the neural net systems can either automatically adjust 

operational parameters to achieve optimal operation or provide 

recommendations to operators of changes to boiler control elements. By 

accepting the recommendations, NOX and unit heat rate can be optimized for 

best overall performance. 

The estimated NOX control efficiency for ULNBs in high temperature 

applications is 50 percent. Newer designs have yielded efficiencies of between 

75-85 percent. When coupled with SCR, efficiencies in the range of 85-97 

percent can be obtained.18 

LNB systems are technically feasible for tangential and wall-fired boilers of 

various sizes, but are not feasible for other boiler types such as cyclone or 

stoker. 19 LNB systems are technically feasible for the control of NOx from 

GEEC Unit 2. 

7.2.2 POST COMBUSTION CONTROLS

7.2.2.1 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 can be written: 

4NO + 4NH3 + O2 à 4N2 + 6H2O 

 

17 "Midwest Regional Planning Organization Boiler Best Available Retrofit Technology (BART) Engineering 

Analysis" MACTEC, March 30, 2005. 

18 Interim White Paper “Source Category: Electric Generating Units” Midwest RPO Candidate Control Measures, 

December 9, 2005 

19 AP 42, Fifth Edition, Volume I Chapter 1 Section 1.1.4.3
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BART Analysis 

2NO2 + 4NH3 + O2 à 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 NOX control efficiency 

range for SCR is 70 to 90 percent.20 This control is a technically feasible 

option for the control of NOX from GEEC Unit 2. 

7.2.2.2 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, because of higher stoichiometric ratios, 

both ammonia and urea SNCR processes require three or four times as much 

reagent as SCR systems to achieve similar NOx reductions. The NOX control 

efficiency range for SNCR is 25 to 50 percent.21 This control is a technically 

feasible option for the control of NOX from GEEC Unit 2. 

7.3 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 7-3 provides a ranking of the control efficiencies for the controls listed in the 

previous section for GEEC 2. 

 

20 Ibid. 

21 Interim White Paper “Source Category: Electric Generating Units” Midwest RPO Candidate Control Measures, 

December 9, 2005. 
Westar Energy 7-5 Trinity Consultants 

BART Analysis 

TABLE 7-3. CONTROL EFFECTIVENESS OF TECHNICALLY FEASIBLE NOX CONTROL 

TECHNOLOGIES

Control Technology 

Estimated Control 

Efficiency 

(%) 

SCR ~70-90 

LNB Systems ~30-60 

FGR ~30-50 

OFA ~25-55 

LNB Only ~25-50 

SNCR ~25-50 

7.4 EVALUATION OF IMPACTS FOR FEASIBLE NOX CONTROLS 

Step four for the BART analysis procedure is the impact analysis. The BART determination 

guidelines list 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 

7.4.1 COST OF COMPLIANCE

As mentioned in Section 2 of this report, EPA has concluded that “for oil-fired and gasfired EGUs larger than 200 MW, we believe that installation of current combustion control 

technology to control NOX is generally highly cost-effective and should be considered in 

your determination of BART for these sources”. Thus, Westar is proposing that BART for 

GEEC Unit 2 is the operation of LNB. 

For purposes of this 5 factor analysis, the capital costs, operating costs, and cost 

effectiveness of an SCR have been estimated. This control option is the only control 

option included in the analysis because it provides the highest level of NOx control and it is 

the only technology with control efficiency higher than that of LNB systems. Should the 

analysis conclude that SCR is not BART, the next best control to SCR is LNB, and this 

will be selected as BART. 

Control Costs

The capital cost and operating costs of SCR were estimated based on recent SCR 

installation experience. The capital costs were annualized over a 20-year period and then 

added to the annual operating costs to obtain the total annualized costs. 

Annual Tons Reduced

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

estimated by subtracting the estimated controlled annual emission rates from the existing 
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BART Analysis 

annual emission rates. The existing annual emission rates were the highest 365 day rolling 

totals as determined from CEMS data from 2002-2004. 

The controlled annual emission rates were estimated by multiplying an estimated control 

efficiency for the SCR (90 percent) by the existing annual emission rates. A sample of the 

controlled annual emission rate is shown as follows: 

,2 352tpy (* 100% − 90%)=235 tpy 

Cost Effectiveness

The cost effectiveness for the SCR was determined by dividing the annual cost by the 

annual tons reduced. The cost is summarized in Table 7-4. The cost of the SCR is greater 

than $5,300/ton of NOX removed. Westar believes this cost is excessive. 
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BART Analysis 

TABLE 7-4. SUMMARY OF COST EFFECTIVENESS FOR GEEC UNIT 2 NOX CONTROLS

Current 

Annual 

Emission 

Rate 

Controlled 

Annual 

Emission 

Rate* 

Estimated 

Reduced 

Emissions Capital Cost† 

Annualized 

Capital 

Cost‡

Annualized 

Fixed 

O&M‡

Annualized 

Variable 

O&M‡

Total 

Annualized 

Cost 

Cost 

Effectiveness

 (tpy) (tpy) (ton/yr) ($) ($/yr) ($/yr) ($/yr) ($/yr) ($/ton) SCR 2,352 235 2,117 81,000,000 9,514,260 218,932 1,627,628 11,360,820 5,367 

*The annual emission rate represents a control efficiency of 90%. †The SCR capital cost was determined from recent SCR installation experience ‡The costs are annualized in 2006 dollars. 
Westar Energy 7-8 Trinity Consultants 

BART Analysis 

7.4.2 ENERGY IMPACTS & NON-AIR IMPACTS

SCR systems require electricity to operate the ancillary equipment. Additionally, the SCR 

can potentially cause significant environmental impacts related to the usage and storage of 

ammonia. 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. Ammonia can also 

be emitted in the exhaust of boilers that operate with SCR or SNCR for NOX control due to 

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. 

Together, ammonium sulfate and ammonium nitrate are the predominant sources of 

regional haze. 

7.4.3 REMAINING USEFUL LIFE

The remaining useful life of GEEC Unit 2 does not impact the annualized capital costs of 

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

the capital cost recovery period, which is 20 years. 

7.5 EVALUATION OF VISIBILITY IMPACT OF FEASIBLE NOX CONTROLS 

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

rates when compared to the emission rates associated with SCR. The existing emission rates and 

emission rates associated with SCR were modeled using CALPUFF. The existing emission rates are 

the same rates that were modeled for the BART applicability analysis. 

The emission rate associated with the SCR for GEEC Unit 2 is 0.12 lb/MMBtu. The emission rate for 

SCR was determined by reducing the existing hourly equivalent of the maximum 24-hour emission 

rate by a control efficiency of 90 percent. 

The existing hourly equivalent of the maximum 24-hour emission rates and the hourly equivalent of 

the 24-hour emission rates associated with SCR are summarized in Table 7-5. 
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BART Analysis 

TABLE 7-5. SUMMARY OF EMISSION RATES MODELED IN NOX CONTROL VISIBILITY IMPACT 

ANALYSIS

Unit Emission Rate Scenario Emission Rate 

 SO2 NOX PM10

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

GEEC Unit 2 Existing Emission Rate 5,766.7 4,818.3 431.5 

 SCR 5,766.7 481.8 431.5 

Comparisons of the existing visibility impacts and the visibility impacts associated with SCR, 

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 7-6 for GEEC Unit 2. The visibility improvement associated with SCR is also 

shown in Table 7-6; this value was calculated as the difference between the existing visibility 

impairment and the visibility impairment for the remaining control options as measured by the 98th

percentile modeled visibility impact. 
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BART Analysis 

TABLE 7-6. SUMMARY OF MODELED IMPACTS FROM NOX CONTROL VISIBILITY IMPACT ANALYSIS FOR GEEC UNIT 2 (2001-2003) 

Wichita Mountains 

Hercules Glades 

Wilderness 

Caney Creek 

Wilderness Mingo NWR 

Upper Buffalo 

Wilderness 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

) Maximum Impact (Δdv

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Existing Emission Rate 2.16 1.08 85 - 1.31 0.40 16 - 1.07 0.38 14 - 0.71 0.17 4 - 2.22 0.42 16 - SCR 1.34 0.60 28 45% 1.09 0.20 5 51% 0.65 0.21 4 46% 0.34 0.09 0 48% 1.07 0.20 8 51% 

*Improvement is based on the 98th percentile impact visibility impact (Δdv) of SCR over the existing emission rate. 
Westar Energy 7-11 Trinity Consultants 

BART Analysis 

As shown in Table 7-6, the installation of SCR results in 45 to 51 percent visibility improvement 

(depending on the Class I area) to the existing visibility impairment attributable to GEEC Unit 2. 

However, as documented in Table 7-4, the cost of SCR for this unit is estimated at over $5,300/ton. 

This large cost does not offset the visibility improvement that would be obtained by controlling NOx

using an SCR. Further, the future visibility impairment attributable to GEEC Unit 2 will be 

significantly improved from the existing visibility impairment based on the switch from the 

combustion of No. 6 fuel oil to the combustion of natural gas, and the large corresponding reduction 

in SO2 emissions. 

7.6 PROPOSED BART FOR NOX 

Since SCR is not cost effective for GEEC Unit 2, Westar has determined that NOx BART for GEEC 

Unit 2 is a LNB. However, Westar is proposing an alternative to BART for GEEC Unit 2. The 

alternative control for GEEC Unit 2 is natural gas combustion; the details of this alternative can be 

found in Section 9.
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BART Analysis 

8. PM10 BART EVALUATION

The primary source of PM from JEC Unit 1 and Unit 2 is the fly ash in the flue gas. Other sources of 

PM include unburned carbon present in the flue gas, which is the result of incomplete combustion, 

and reactions of SO2 and NOX compounds to form fine PM in the form of nitrates, sulfur trioxide, and 

sulfates. PM emissions from JEC Unit 1 and Unit 2 are currently controlled by electrostatic 

precipitators (ESP). Similarly, PM emissions from GEEC Unit 2 are particles generated during the 

combustion of the No. 6 fuel oil. PM emissions from GEEC Unit 2 are currently uncontrolled. 

The maximum daily PM10 emission rates that were modeled for the BART applicability determination 

are summarized in Table 8-1. 

TABLE 8-1. EXISTING MAXIMUM 24-HOUR PM10 EMISSION RATE

Heat Input 

PM10 24-Hr 

Emission Rate 

PM10 Hourly 

Emission Rate 

PM10 Emission 

Rate 

 (MMBtu/hr) (ton/24-hr) (lb/hr) (lb/MMBtu) 

JEC Unit 1 8,110 3.93 327.4 0.04 

JEC Unit 2 8,110 3.65 303.9 0.04 

GEEC Unit 2 4,110 5.2 431.5 0.10 

From Table 8-1 it can be seen that the current PM10 emission rates for JEC Unit 1 and Unit 2 and 

GEEC Unit 2 are much less than the current emission rates of SO2 and NOX. The low PM10 emission 

rates correspond to low visibility impacts attributable to PM10 when compared to the impacts 

attributable to SO2 and NOX, from JEC Unit 1 and Unit 2 and GEEC Unit 2, as shown in Tables 8-2 

and 8-3. 

TABLE 8-2. VAP VISIBILITY IMPAIRMENT CONTRIBUTIONS FROM JEC UNIT 1 AND UNIT 2 (2001-

2003) 

 Visibility 

Impairment 

Attributable to 

SO4

1

Visibility 

Impairment 

Attributable to 

NO3

2

Visibility 

Impairment 

Attributable to 

PM10

2

 (%) (%) (%) 

Wichita Mountains 

Wilderness 51.13 48.28 0.59 

Hercules Glades Wilderness 38.21 60.92 0.87 

Caney Creek Wilderness 40.79 57.87 1.35 

Mingo Wildlife 43.81 55.53 0.65 

Upper Buffalo Wilderness 39.6 59.22 1.18 

1 The visibility impairment attributable to SO4 is primarily from SO2 emissions. A very small portion is 

from SO4 emitted as condensable particulate. 

2 The visibility impairment attributable to NO3 is entirely from NOX emissions. 

3 The visibility impairment attributable to PM10 is the sum of the visibility impairment attributable to all 

modeled primary PM species (PMc, PMf, EC, and SOA). 
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BART Analysis 

TABLE 8-3. VISIBILITY IMPAIRMENT CONTRIBUTIONS FROM GEEC UNIT 2(2001-2003) 

 Visibility 

Impairment 

Attributable to 

SO4

1

Visibility 

Impairment 

Attributable to 

NO3

2

Visibility 

Impairment 

Attributable to 

PM10

2

 (%) (%) (%) 

Wichita Mountains 

Wilderness 29.29 67.54 3.17 

Hercules Glades Wilderness 41.15 57.14 1.71 

Caney Creek Wilderness 26.11 71.72 2.16 

Mingo Wildlife 63.14 34.96 1.89 

Upper Buffalo Wilderness 35.67 62.6 1.71 

1 The visibility impairment attributable to SO4 is primarily from SO2 emissions. A very small portion is 

from SO4 emitted as condensable particulate. 

2 The visibility impairment attributable to NO3 is entirely from NOX emissions. 

3 The visibility impairment attributable to PM10 is the sum of the visibility impairment attributable to all 

modeled primary PM species (PMc, PMf, EC, and SOA). 

Westar proposes to upgrade the existing ESPs on JEC Unit 1 and Unit 2 in order to improve the PM 

control from these units. The upgrades to the existing ESPs will improve control of PM from JEC 

Unit 1 and Unit 2, thereby improving the visibility impacts from JEC Unit 1 and Unit 2. 

Westar proposes that no additional PM control technologies are required for GEEC Unit 2, which is 

currently uncontrolled. The fuel switching from fuel oil no. 6 to natural gas proposed as a BART 

alternative for SO2 (see Section 9) will significantly reduce the PM emissions from GEEC Unit 2. 

Given the small PM emission rates from natural gas combustion, Westar believes that the reduced PM 

emissions from the fuel switching combined with the cost of retrofitting GEEC Unit 2 with a new PM 

control technology would provide little visibility improvement and require significant capital 

expenditures.
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BART Analysis 

9. PROPOSED GEEC BART ALTERNATIVE 

Based on the GEEC SO2 and NOx BART analyses, Westar has determined that BART for SO2 for 

GEEC Unit 2 is the combustion of 1 percent sulfur fuel oil and BART for NOX is a LNB. Westar is 

proposing an alternative to the controls determined to meet BART for SO2 and NOX for GEEC Unit 

2. In order for control strategies to be acceptable as an alternative to what is determined to meet 

BART, the alternatives must show greater visibility improvement than what is determined to meet 

BART based on the following visibility metrics: 

▲ The maximum visibility impact 

▲ The 98th percentile visibility impact 

▲ The number of days where the visibility impacts are greater than 0.5 ∆dv 

In other words, the values for the metrics listed above for an alternative BART control strategy must 

be equal to or better than the values for the BART control strategy for each Class I area. 

As an alternative to combusting 1 percent fuel oil to reduce SO2 and LNB to reduce NOX for GEEC 

Unit 2, Westar is proposing to combust natural gas in GEEC Unit 2. The switch to natural gas will 

provide greater than 95 percent SO2 control from GEEC Unit 2. 

9.1.1.1 COMPLIANCE WITH ALTERNATIVE BART CONTROL STRATEGY

Westar is proposing to demonstrate compliance with the alternative BART control strategy for GEEC 

Unit 2 that includes switching from No. 6 fuel oil to natural gas by submitting annual certifications of 

compliance verifying that natural gas was the only fuel combusted in GEEC Unit 2 for the year, 

except as provided below. 

In order to assure electric system reliability, Westar requires the availability of an emergency fuel for 

backup, as well as the ability to burn a limited amount of the fuel periodically during nonemergencies to assure that the emergency system functions adequately. When the natural gas 

company implements an Operational Flow Order (OFO) or declares an emergency which could result 

in an impact to electric system reliability, Westar will combust No. 6 fuel oil for the time period of

the emergency. Westar will diminish the existing supply of No. 6 fuel oil, once diminished the 

emergency fuel will be replaced with a fuel oil containing 1% or less sulfur content. 

9.1.2 COMPARISON OF VISIBILITY IMPACTS FOR BART AND PROPOSED ALTERNATIVE 

BART CONTROL STRATEGIES

The modeled visibility impacts of the BART control strategy and the proposed alternative BART 

control strategy are summarized in Table 9-1. The visibility improvement associated with the BART 

and alternative BART control options are also shown in Table 9-1; this value was calculated as the 

difference between the existing visibility impairment and the visibility impairment for the BART and 

alternative BART control options as measured by the 98th percentile modeled visibility impact. The 

visibility impacts for each metric are lower in all five Class I areas for the alternate BART control 

strategy. 
T

Westar Energy 9-2 Trinity Consultants BART Analysis 

ABLE 9-1.

MODELED IMPACTS 

BASED ON 

PRESUMPTIVE BART

EMISSION 

RATES AND 

ALTERNATIVE BART AT GEEC

UNIT 

2 (2001-2003) 

Wichita Mountains 

Hercules Glades 

Wilderness 

Caney Creek 

Wilderness Mingo NWR 

Upper Buffalo 

Wilderness 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Maximum Impact (Δdv)

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

dv) Maximum Impact (Δ

98% Impact (Δdv)

# Days > 0.5 Δdv

Visibility Improvement* 

Existing 2.16 1.08 85 - 1.31 0.40 16 - 1.07 0.38 14 - 0.71 0.17 4 - 2.22 0.42 16 - BART - LNB + 1% sulfur fuel oil 2.02 0.94 71 13% 1.19 0.34 10 13% 0.87 0.34 9 10% 0.65 0.14 2 16% 2.04 0.38 15 10% Alternative - Natural gas 1.66 0.69 44 36% 0.93 0.21 4 48% 0.49 0.25 0 34% 0.49 0.08 0 55% 1.62 0.28 11 33%