Appendix 9.5 

BART Analysis for KCP&L - La Cygne Units 1 and 2 
CALPUFF BART MODELING PROTOCOL  KANSAS CITY POWER 

& LIGHT

LA CYGNE GENERATING STATION

VERSION 0 

Prepared by: 

Kasi Dubbs  Senior Consultant 

Mary Pham  Consultant 

TRINITY CONSULTANTS

25055 West Valley Parkway 

Suite 101 

Olathe, Kansas 66061 

(913) 390-9700 

November 2006 

Project 061701.0125 
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TABLE OF CONTENTS

1. INTRODUCTION........................................................................................................5

1.1 BACKGROUND...........................................................................................................5 

1.2 LOCATION OF SOURCES AND RELEVANT CLASS I AREAS ..........................................5 

1.3 OBJECTIVE ................................................................................................................6 

2. CALPUFF MODEL SYSTEM ...................................................................................7

2.1 MODEL VERSIONS.....................................................................................................7

2.2 MODELING DOMAIN .................................................................................................8 

3. CALMET................................................................................................................9

3.1 GEOPHYSICAL DATA.................................................................................................9 

3.1.1 TERRAIN DATA ...................................................................................................... 9

3.1.2 LAND USE DATA.................................................................................................. 10

3.1.3 COMPILING TERRAIN AND LAND USE DATA........................................................ 11

3.2 METEOROLOGICAL DATA .......................................................................................11 

3.2.1 MESOSCALE MODEL METEOROLOGICAL DATA .................................................. 11

3.2.2 SURFACE METEOROLOGICAL DATA .................................................................... 12

3.2.3 PRECIPITATION METEOROLOGICAL DATA........................................................... 13

3.3 SUMMARY OF CALMET CONTROL PARAMETERS ..................................................14 

4. CALPUFF.............................................................................................................21

4.1 SOURCE EMISSIONS DATA ......................................................................................21 

4.1.1 SO2, NOX, AND PM10 EMISSIONS ......................................................................... 21

4.1.2 SPECIATED PM10 EMISSIONS................................................................................ 21

4.2 GEP STACK HEIGHT ...............................................................................................22 

4.3 CLASS I AREA RECEPTORS ......................................................................................24 

4.4 BACKGROUND OZONE ............................................................................................27 

4.5 BACKGROUND AMMONIA .......................................................................................28 

4.6 SUMMARY OF CALPUFF CONTROL PARAMETERS .................................................28

5. CALPOST.............................................................................................................43

5.1 LIGHT EXTINCTION ALGORITHM.............................................................................43 

5.2 CALPOST PROCESSING METHOD...........................................................................43 

5.3 NATURAL BACKGROUND ........................................................................................44 

5.4 SUMMARY OF CALPOST CONTROL PARAMETERS.................................................44

5.5 EVALUATING BART...............................................................................................49 

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

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

APPENDIX C.................................................................................................................................
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APPENDIX D.................................................................................................................................
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LIST OF TABLES

TABLE 1-1. DISTANCE TO CLASS I AREAS............................................................................................. 6

TABLE 2-1. CALPUFF MODELING SYSTEM VERSIONS ........................................................................ 7

TABLE 3-1. SUMMARY OF CALMET INPUTS ...................................................................................... 15

TABLE 4-1. SO2,NOX AND PM10 EMISSIONS ........................................................................................ 21

TABLE 4-2. HOURLY PM10SPECIATED EMISSIONS .............................................................................. 22

TABLE 4-3. SUMMARY OF STACK PARAMETERS ................................................................................. 23

TABLE 4-4. SUMMARY OF OZONE MONITORS ..................................................................................... 27

TABLE 4-5. SUMMARY OF CALPUFF INPUTS ..................................................................................... 28

TABLE 5-1. MONTHLY HUMIDITY FACTORS........................................................................................ 43

TABLE 5-2. DEFAULT AVERAGE ANNUAL NATURAL BACKGROUND LEVELS .................................... 44

TABLE 5-3. SUMMARY OF CALPOST INPUTS ..................................................................................... 44

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

TABLE A-2. TERRAIN DATA USED IN ANALYSIS................................................................................... 2

TABLE B-1. LIST OF SURFACE METEOROLOGCAL STATIONS................................................................. 1

TABLE B-2. LIST OF PRECIPITATION METEOROLOGICAL STATIONS...................................................... 2
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LIST OF FIGURES

FIGURE 1-1. LOCATION OF KCP&L LA CYGNE GENERATING STATION AND NEARBY CLASS I AREAS6

FIGURE 2-1. PROPOSED MODELING DOMAIN ........................................................................................ 8

FIGURE 3-1. PLOT OF LAND ELEVATION USING USGS TERRAIN DATA ............................................. 10

FIGURE 3-2. PLOT OF LAND USE USING USGS LULC DATA.............................................................. 11

FIGURE 3-3. PLOT OF SURFACE STATIONS........................................................................................... 13

FIGURE 3-4. PLOT OF PRECIPITATION METOROLOGICAL STATIONS .................................................... 14

FIGURE 4-1. LA CYGNE STACK AND BUILDING LOCATIONS ............................................................... 23

FIGURE 4-2. HERCULES-GLADES WILDERNESS RECEPTOR LOCATIONS ............................................. 24

FIGURE 4-3. WICHITA MOUNTAINS RECEPTOR LOCATIONS ............................................................... 25

FIGURE 4-4. UPPER BUFFALO RECEPTOR LOCATIONS ........................................................................ 26

FIGURE 4-5. CANEY CREEK RECEPTOR LOCATIONS............................................................................ 26

FIGURE 4-6. MINGO RECEPTOR LOCATIONS........................................................................................ 27

 
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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. 

1.2 LOCATION OF SOURCES AND RELEVANT CLASS I AREAS

Kansas City Power & Light (KCP&L) has identified the following sources that meet the three criteria 

for being BART-eligible sources: 

 La Cygne Generating Station – Boiler Unit 1 

 La Cygne Generating Station – Boiler Unit 2 

Table 1-1 provides a summary of the distances from the La Cygne Generating Station to nearby Class 

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

Distance to Class I Area (km) 

Source 

Wichita 

Mountains 

HerculesGlades Upper 

Buffalo 

Caney 

Creek Mingo 

La Cygne 533.4 233.6 291.5 437.8 416.4 

Figure 1-1 provides a plot of the location of the La Cygne Generating Station with respect to the 

listed Class I areas. 

FIGURE 1-1. LOCATION OF KCP&L LA CYGNE GENERATING STATION AND NEARBY 

CLASS I AREAS

1.3 OBJECTIVE

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

procedures that KCP&L will follow as we evaluate the visibility impacts attributable to La Cygne 

Unit 1 and La Cygne Unit 2 in the Class I areas listed in Table 1-1. Initially, KCP&L will use the 

methods in this protocol to determine the visibility impacts based on the existing emission rates and 

exhaust characteristics for the units (See Section 4). We will also use the methods in this protocol to 

evaluate BART control options. Since we are in the process of evaluating control options, no specific

emission rates or exhaust characteristics based on BART control options are provided in this protocol. 
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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 to model La Cygne Unit 

1 and Unit 2 are listed in Table 2-1. Table 2-1 also compares the program versions that will be used 

to model La Cygne Unit 1 and Unit 2 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 KCP&L will use alternate versions. 

TABLE 2-1. CALPUFF MODELING SYSTEM VERSIONS

CENRAP Suggested KCP&L Analyses Reason for Difference 

Program Version Level Version Level 

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 Modified code used by Alpine Geophysics 

CALMET 5.53a 040716 6.211 060414 Needed to process multiple CALMM5 files 

CALPUFF 5.711a 040716 6.112 060412 Needed to process CALMET output 

POSTUTIL 5.51 030709 6.131 060410 Needed to process CALPUFF output 

CALPOST 3.311 030709 3.311 030709 
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2.2 MODELING DOMAIN

The modeling domain for the La Cygne Generating Station is the same domain that has been 

calculated for other BART-eligible electric generating units in Kansas. The domain extends at least 

50 km in all directions beyond the La Cygne Generating Station and the five Class I areas of interest. 

The map projection for the modeling domain is Lambert Conformal Conic (LCC) and the coordinate 

system is World Geodetic System 1984 (WGS84), which is an LCC projection. The meteorological 

grid spacing is 2.5 km. 

The southwest corner of the modeling domain is Latitude 33.92oN, 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 39.77oN, Longitude 89.29oW. At a grid spacing of 2.5 km, the number of X 

grid cells will be 346 and the number of Y grid cells will be 261. 

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

0 200 400 600 800

East (km)

0

200

400

600

N

orth (km)

La Cygne Generating Station

Hercules Glades

Wichita Mountains

Upper Buffalo

Caney Creek

Mingo
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3. CALMET

KCP&L 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 KCP&L’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 A. 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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BART Modeling Protocol 

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

0 100 200 300 400 500 600 700 800

East (m)

0

100

200

300

400

500

600

North (k)

La Cygne Generating Station

Hercules Glades

Mingo NWR

Wichita Mountains

Upper Buffalo Wilderness Area

Caney Creek

-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 A. 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

0 100 200 300 400 500 600 700 800

East (km)

0

100

200

300

400

500

600

North (km)

La Cygne Generating Station

Hercules Glades

Mingo NWR

Wichita Mountains

Upper Buffalo Wilderness Area

Caney Creek

 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 and precipitation station observations 

to develop the meteorological field. 

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

meteorological data sets will be used: 

• 2001 MM5 data at 12 km resolution processed for EPA by Alpine Geophysics 

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

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

The MM5 data for the CENRAP region was extracted from the above MM5 data sets by 

Alpine Geophysics using the CALMM5 program. Trinity will use this extracted MM5 

data. 

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 B. 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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BART Modeling Protocol 

FIGURE 3-3. PLOT OF SURFACE STATIONS

0 200 400 600 800 1000

East (km)

-200

0

200

400

600

800

N

orth (km)

La Cygne Generating Station

KDFW

KICT

KCOU

KMCI

KSZL

KSHV

KACT

KABI

KFSM

KSPS

KOKC

KTUL

KPNC

KTXK

KCNK

KEMP

KSGF

KTOP

KTYR

KOCH

KPRX

KHOT

KFYV

KJLN

K1F0

KIRK

KSTJ

KCNU

KMHK

KSLN

KHBR KMLC

KUIN KSPI

KCPSKBLV

KJEF

KAIZ

KDMO

KVIH

KFAM KMDH

KCGI KPAH

KPOF

KARG KDYR

KBVX

KJBR KMKL

KMEM

KSGT

KPBF

KLIT

KLRF

KFLP

KDEC

KMVN

KSTL

Hercules Glades

Wichita Mountains

Upper Buffalo

Caney Creek

Mingo

3.2.3 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 B. The locations of the precipitation 

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 

5.31, Level: 030528 of EPA’s PMERGE program. 
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FIGURE 3-4. PLOT OF PRECIPITATION METOROLOGICAL STATIONS

0 200 400 600 800 1000

East (km)

-200

0

200

400

600

800

N

orth (km)

La Cygne Generating Station

ALUM

ANTOARKA

BLAK

BOON

BRIG

CAMD

CLAR

DE QDIER

FORE

FORT

HARR

LEWI MAGN

MENA

NIMR

NORF

PRES

TEXA

WALD

ARLI

CALD

CHAN

CONC

COUN

IONI

KIOW

MARY

MILF

SALI

TOPE

UNIO

WICH

MANS

MIND

NATC

SHRE RED 

APPL

BOLI

CASS

COLU

DORA

JOPL

KANS

KIRK

LEBA

MOUN

NEVA

SPRI

TABL

TRUM

ALTU

AMES

ARDM

BENG

CANE CART

CHAN

CHIC

CUST

DUNC

ELK 

FORT

GEAR

HENN

HOBA

KING

LAKE

LEHI

MACK

MARS

MCAL

MUSK OKAR

OKEM OKLA

PONC

ROFF

TULS

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

SPRI

JACK

PITT

CLAR GREECARL

MORR

CARL

SPAR

MURP

HANN

CLAR

LONG

MOBE

NEW FULT

CAP 

WASH ROSE

ROLL

VIEN

STEEPOTO

VIBU

SALE

ALLE CLEA

FARM

ADVA

WAPP

DORAWEST MALD

HORN

ARKA

CALH

CLAR

CLEV GREN

HICK

MOUN HOLL

SARE

UNIV

BOLI

BROW

GREE

JACK

MASO

MEMPMEMP

MUNF

SAMB UNIO

BATEALIC

BEEB

BRIN

CORN

DUMA

GREE

HARD

MONT

PINE

STUT

WYNN

Hercules Glades

Wichita Mountains

Upper Buffalo

Caney Creek

Mingo

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 KCP&L 

Will Use Notes 

NUSTA Number of upper air data 

sites 

0 0 Will not 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 33.9195N Appropriate for domain 

RLON0 Longitude (decimal 

degrees) of projection 

origin 

97W 99.3480W Appropriate for domain 

XLAT1 Latitude of 1st standard 

parallel 

33N 33N Appropriate for domain 

XLAT2 Latitude of 2nd standard 

parallel 

45N 40N Appropriate for domain 

DATUM Datum region for output 

coordinates 

WGS-G WGS-G Selected datum to match 

datum of land use data 

NX Number of X grid cells in 

meteorological grid 

300 346 Appropriate for domain 

NY Number of Y grid cells in 

meteorological grid 

192 261 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 KCP&L 

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 1 Will use surface 

observations only 

NSSTA Number of meteorological 

stations in SURF.DAT file 

0 45 Number of stations 
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BART Modeling Protocol 

CALMET 

Variable Description 

Value 

Included in 

CENRAP 

Protocol 

Value KCP&L 

Will Use Notes 

NPSTA Number of precipitation 

stations in PRECIP.DAT 

file 

0 206 Number of stations 

ICLOUD Gridded cloud fields (0 = 

no, 3 = Gridded cloud 

cover from prognostic 

relative humidity) 

3 0 

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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BART Modeling Protocol 

CALMET 

Variable Description 

Value 

Included in 

CENRAP 

Protocol 

Value KCP&L 

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) 

30 100 

RMAX2 Maximum radius of 

influence over land aloft 

(km) 

30 500 

RMAX3 Maximum radius of 

influence over water (km) 

50 100 

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 80 

R2 Weighting of first guess 

aloft field (km) 

1 200 

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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BART Modeling Protocol 

CALMET 

Variable Description 

Value 

Included in 

CENRAP 

Protocol 

Value KCP&L 

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 KCP&L 

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 1 Will use surface 

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

KCP&L 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

The BART rule indicates that if the PTE is greater than 250 tpy for any visibility-impairing pollutant, 

a source is required to include emissions of all visibility impairing pollutants in the BART analysis. 

La Cygne Unit 1 and Unit 2 emit three primary visibility-impairing pollutants: SO2, PM10, and NOX. 

Since the PTE for at least one of these pollutants is above 250 tpy, KCP&L will include emissions of 

all three pollutants in the BART modeling analysis. 

4.1.1 SO2, NOX, AND PM10 EMISSIONS 

The BART rule indicates that KCP&L should model the highest actual 24-hour emission rate for each 

visibility impairing pollutant that occurred during a baseline period. Thus, the SO2, NOx, and PM10

emissions that will be modeled to determine the current visibility impacts attributable to La Cygne 

Unit 1 and Unit 2 are the maximum of the 2002-2004 24-hour highest actual emissions rates. The 

SO2 and NOx emission rates will be based on CEMS data. The PM10 emission rates will be based on 

actual fuel data from 2002-2004 and AP-42 emission factors. The PM10 emission rates will include 

both the filterable and condensable fractions. Detailed calculations for the PM10 emission rates can be 

found in Appendix C. The SO2, NOx, and PM10 emissions are summarized in Table 4-1. 

TABLE 4-1. SO2,NOX AND PM10 EMISSIONS

 SO2 NOX PM10

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

La Cygne - Unit 1 6,151.15 11,589.52 53.79 

La Cygne - Unit 2 8,316.15 3,543.47 94.92 

4.1.2 SPECIATED PM10 EMISSIONS

The PM10 emissions will be speciated to include the following: 

• Coarse particulate matter (PMC) 

• Fine particulate matter (PMf) 

• Sulfates (SO4) 

• Nitrates (NO3) 

• Secondary organic aerosols (SOA) 

• Elemental carbon (EC) 

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

Federal Land Managers (FLM) for a Cyclone Furnace with Flue Gas Desulfurization (FGD) and ESP 
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BART Modeling Protocol 

(La Cygne Unit 1) and a dry bottom PC boiler with ESP (La Cygne Unit 2). It should be noted that 

Unit 1 is a cyclone furnace with wet FGD only; however, there is not an FLM PM10 speciation for this 

type of cyclone boiler. Therefore, the FLM PM10 speciation for a Cyclone Furnace with FGD and 

ESP was used. Since the wet FGD controls PM, this speciation is appropriate for Unit 1. Table 4-2 

provides a summary of the speciated emissions. 

TABLE 4-2. HOURLY PM10SPECIATED EMISSIONS

 Total 

PM10 

SO4 PMc PMf SOA EC 

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

La Cygne - Unit 1 53.79 34.37 4.92 5.68 8.59 0.22 

La Cygne - Unit 2 94.92 28.12 33.20 25.58 7.03 0.98 

4.2 GEP STACK HEIGHT

Section 6.2.2 of the Guideline on Air Quality Models

1 states the following: 

"The use of stack height credit in excess of Good Engineering Practice (GEP) stack 

height or credit resulting from any other dispersion technique is prohibited in the 

development of emission limitations by 40 CFR 51.118 and 40 CFR 51.164." 

Since this modeling is being used to determine if emissions limitations are needed, stack heights in 

excess of GEP stack heights should not be used in the modeling. KCP&L has calculated the GEP 

stack heights of La Cygne Unit 1 and Unit 2 and determined that the actual heights are in excess of 

GEP stack height. 

The EPA provides guidance for determining whether building downwash will occur in Guideline for 

Determination of Good Engineering Practice Stack Height.2 The minimum stack height not subject 

to the effects of downwash (called the Good Engineering Practice or GEP stack height) is defined by 

the following formula: 

GEP = H + 1.5L 

 Where: GEP = the minimum GEP stack height 

 H = the height of the structure 

 L = the lesser dimension of the structure (height or projected 

width) 

Stacks located more than 5L from any building are not subject to the effects of building downwash. 

 

1 40 CFR 51, Appendix W 

2EPA, Office of Air Quality Planning and Standards. Guideline for Determination of Good Engineering Practice 

Stack Height (Technical Support Document for the Stack Height Regulations) (Revised). Research Triangle Park, North 

Carolina. EPA 450/4-80-023R. June, 1985. 
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BART Modeling Protocol 

Calculations for determining the direction-specific downwash parameters and GEP stack height were 

performed using BREEZETM WAKE/BPIP software, which uses EPA’s Building Profile Input 

Program (BPIP) downwash algorithm. Figure 4.1 shows the stacks and buildings that were included 

in the BPIP analysis. Since the GEP stack heights are less than the actual stack heights, the stacks 

will be modeled at GEP stack heights rather than the actual stack heights. A summary of the stack 

parameters, including GEP and actual stack heights, can be found in Table 4-3. These parameters are 

only specific to the existing operations; as KCP&L evaluates BART control options, the parameters 

may be modified for each control option. 

FIGURE 4-1. LA CYGNE STACK AND BUILDING LOCATIONS

407.45 407.50 407.55 407.60 407.65 407.70 407.75

East (km)

487.55

487.60

487.65

487.70

487.75

487.80

North (km)

Boiler 1 Stack

Height: 700 ft

GEP: 591.2 ft

Boiler 2 Stack

Height: 700 ft

GEP: 597.8 ft

TABLE 4-3. SUMMARY OF STACK PARAMETERS

 La Cygne 1 La Cygne 2 

Latitude (degrees) 38.3486 38.3476 

Longitude (degrees) -94.6456 -94.6456 

Actual Stack height (ft) 700 700 

GEP Stack height (ft) 591.2 597.8 

Stack Diameter (ft) 23 24 

Exhaust Velocity (ft/s) 92.7 100.8 

Exhaust Temperature (F) 127 281 
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BART Modeling Protocol 

4.3 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 all 

Class I areas will be downloaded from the NPS website, converted into the LCC WGS84 projection, 

and incorporated into the CALPUFF model. The receptor locations for the Class I areas are shown in 

Figures 4-2 through 4-6. 

FIGURE 4-2. HERCULES-GLADES WILDERNESS RECEPTOR LOCATIONS
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FIGURE 4-3. WICHITA MOUNTAINS RECEPTOR LOCATIONS
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FIGURE 4-4. UPPER BUFFALO RECEPTOR LOCATIONS

FIGURE 4-5. CANEY CREEK RECEPTOR LOCATIONS
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FIGURE 4-6. MINGO RECEPTOR LOCATIONS

4.4 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. KCP&L is proposing to 

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

monitors are listed in Table 4-4. 

TABLE 4-4. 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 
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BART Modeling Protocol 

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

containing data from the above referenced stations. KCP&L is proposing to incorporate these files 

into the CALPUFF model. 

4.5 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, KCP&L 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. 

4.6 SUMMARY OF CALPUFF CONTROL PARAMETERS

Table 4-5 provides a listing of the CALPUFF parameters that KCP&L 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 4-5. SUMMARY OF CALPUFF INPUTS

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L 

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 9 

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) 
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BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L 

Will Use Notes 

ITEST Program is 

executed after 

SETUP phase 

2 2 

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 KCP&L 

Will Use Notes 

MTURBVW Use both σv and 

σw from 

PROFILE.DAT to 

compute σy and σz

(n/a) 

3 3 

MDISP2 PG dispersion 

coefficients 

3 3 

MROUGH PG σy and σz

 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 KCP&L 

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 

 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 KCP&L 

Will Use Notes 

NX Number of X grid 

cells in 

meteorological 

grid 

66 346 Appropriate for 

domain and grid 

spacing 

NY Number of Y grid 

cells in 

meteorological 

grid 

66 261 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 

66 346 Appropriate for 

domain 

JECOMP Y index of upper 

right corner of the 

computational grid 

66 261 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 

66 346 Appropriate for 

domain 
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BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L 

Will Use Notes 

JESAMP Y index of upper 

right corner of 

sampling grid 

66 261 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 
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BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L 

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 KCP&L 

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 (μm) 

0.48 0.48 

NO3- Geometric mass 

mean diameter of 

NO3- (μm) 

0.48 0.48 

PMC Geometric mass 

mean diameter of 

PMC (μm) 

6 6 

PMF Geometric mass 

mean diameter of 

PMF (μm) 

0.48 0.48 

EC Geometric mass 

mean diameter of 

EC (μm) 

0.48 0.48 

SOA Geometric mass 

mean diameter of 

SOA (μm) 

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 KCP&L 

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-04 1.0E-04 
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BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L 

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 

(μg/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 
Kansas City Power & Light 37 Trinity Consultants 

BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L 

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 

* * 
Kansas City Power & Light 38 Trinity Consultants 

BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L 

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 
Kansas City Power & Light 39 Trinity Consultants 

BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L 

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 σy/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 19 Should be by hour of 

day – 1900 is hour 19 

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 
Kansas City Power & Light 40 Trinity Consultants 

BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L 

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 

- - 
Kansas City Power & Light 41 Trinity Consultants 

BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L 

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 

- - 
Kansas City Power & Light 42 Trinity Consultants 

BART Modeling Protocol 

CALPUFF 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L 

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 338 
Kansas City Power & Light 43 Trinity Consultants 

BART Modeling Protocol 

5. CALPOST

KCP&L will conduct a three-year CALPOST analysis to determine the change in light extinction 

caused by La Cygne Unit 1 and Unit 2 when compared to a natural background. The CALPOST 

model requires the input of concentration data output by CALPUFF. 

5.1 LIGHT EXTINCTION ALGORITHM 

KCP&L 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 La Cygne Unit 1 and

Unit 2 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

 +















5.2 CALPOST PROCESSING METHOD

KCP&L will use CALPOST Method 6, which calculates hourly light extinction impacts for the 

source and background using monthly average relative humidity adjustment factors. KCP&L 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 the Class I areas in this analysis 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 

Upper Buffalo 3.3 3.0 2.7 2.8 3.4 3.4 3.4 3.4 3.6 3.3 3.2 3.3 

Caney Creek 3.4 3.1 2.9 3.0 3.6 3.6 3.4 3.4 3.6 3.5 3.4 3.5 

Mingo 3.3 3.0 2.8 2.6 3.0 3.2 3.3 3.5 3.5 3.1 3.4 3.3 
Kansas City Power & Light 44 Trinity Consultants 

BART Modeling Protocol 

5.3 NATURAL BACKGROUND

KCP&L 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 for Wichita Mountains. KCP&L will use EPA’s default average annual 

aerosol concentrations for the eastern 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 for Upper 

Buffalo, Caney Creek, Hercules Glades and Mingo. The annual average concentrations are provided 

in Table 5-2. 

TABLE 5-2. DEFAULT AVERAGE ANNUAL NATURAL BACKGROUND LEVELS

Component 

Average Annual 

Natural Background – 

Western 

 (μg/m3) 

Average Annual 

Natural Background – 

Eastern 

 (μg/m3) 

Ammonium Sulfate 0.12 0.23 

Ammonium Nitrate 0.1 0.1 

Organic Carbon Mass 0.47 1.4 

Elemental Carbon 0.02 0.02 

Soil 0.5 0.5 

Coarse Mass 3 3 

5.4 SUMMARY OF CALPOST CONTROL PARAMETERS

Table 5-3 provides a listing of the CALPOST parameters that KCP&L 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 KCP&L 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 

NREP Process every hour 

of data? 1 = yes 

1 1 

ASPEC Process species for 

visibility 

VISIB VISIB 
Kansas City Power & Light 45 Trinity Consultants 

BART Modeling Protocol 

CALPOST 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L Will 

Use Notes 

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 

LVNO3 Compute light 

extinction for 

nitrate? 

T T 

LVOC Compute light 

extinction for 

organic carbon? 

T T 
Kansas City Power & Light 46 Trinity Consultants 

BART Modeling Protocol 

CALPOST 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L Will 

Use Notes 

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 

RHFRAC % of particles 

affected by RH 

10 Not Used Not necessary since 

MVISBK=6 
Kansas City Power & Light 47 Trinity Consultants 

BART Modeling Protocol 

CALPOST 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L Will 

Use Notes 

RHFAC Extinction 

coefficients for 

modeled and 

background 

hygroscopic species 

computed using 

EPA (2003) 

monthly RH 

adjustment factors 

Depends on Class I 

Area 

See Table 5-1 As appropriate for 

Class I area 

BKSO4 Background sulfate 

extinction coeff - 

west 

0.12 0.12 Used for Wichita 

Mountains 

BKNO3 Background nitrate 

extinction coeff – 

west 

0.10 0.10 Used for Wichita 

Mountains 

BKPMC Background coarse 

part. extinction 

coeff – west 

3.00 3.00 Used for Wichita 

Mountains 

BKSOC Background 

organic carbon 

extinction coeff – 

west 

0.47 0.47 Used for Wichita 

Mountains 

BKSOIL Background soil 

extinction coeff – 

west 

0.50 0.50 Used for Wichita 

Mountains 

BKSEC Background 

elemental carbon 

extinction coeff – 

west 

0.02 0.02 Used for Wichita 

Mountains 

BKSO4 Background sulfate 

extinction coeff – 

east 

0.23 0.23 Used for Upper 

Buffalo, Caney 

Creek, Hercules 

Glades and Mingo 

BKNO3 Background nitrate 

extinction coeff – 

east 

0.10 0.10 Used for Upper 

Buffalo, Caney 

Creek, Hercules 

Glades and Mingo 

BKPMC Background sulfate 

extinction coeff – 

west 

3.00 3.00 Used for Upper 

Buffalo, Caney 

Creek, Hercules 

Glades and Mingo 

BKSOC Background 

organic carbon 

extinction coeff – 

east 

1.40 1.40 Used for Upper 

Buffalo, Caney 

Creek, Hercules 

Glades and Mingo 

BKSSOIL Background soil 

extinction coeff – 

east 

0.50 0.50 Used for Upper 

Buffalo, Caney 

Creek, Hercules 

Glades and Mingo 

BKSEC Background 

elemental carbon 

extinction coeff – 

east 

0.02 0.02 Used for Upper 

Buffalo, Caney 

Creek, Hercules 

Glades and Mingo 
Kansas City Power & Light 48 Trinity Consultants 

BART Modeling Protocol 

CALPOST 

Variable Description 

Value Included in 

CENRAP Protocol 

Value KCP&L 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 
Kansas City Power & Light 49 Trinity Consultants 

BART Modeling Protocol 

5.5 EVALUATING BART 

KCP&L will perform modeling as outlined in this protocol to determine the visibility impacts based 

on the existing emission rates and exhaust characteristics for La Cygne Unit 1 and Unit 2. The 

modeling methods outlined in this protocol will also be used in the evaluation of BART control 

options. Since we are in the process of evaluating BART control options, specific data related to the

control options are not provided in this protocol. KCP&L will provide data specific to the control 

options as part of the controls analysis. 

 
Kansas City Power & Light A - 1 Trinity Consultants

BART Modeling Protocol 

APPENDIX A 

GEOPHYSICAL DATA
Kansas City Power & Light A - 2 Trinity Consultants

BART Modeling Protocol 

TABLE A-1. LAND USE DATA USED IN ANALYSIS 

1:250,000 Scale Data

Abilene 

Ardmore 

Belleville 

Beloit 

Blytheville 

Clinton 

Dallas 

Decatur 

Dyersburg 

El Dorado 

Enid 

Fort Smith 

Great Bend 

Greenwood 

Harrison 

Helena 

Hutchinson 

Jackson 

Jefferson City 

Joplin 

Kansas City 

Lawrence 

Lawton 

Little Rock 

Manhattan 

Memphis 

Meridian 

Moberly 

Oklahoma City 

Paducah 

Poplar Bluff 

Pratt 

Quincy 

Rolla 

Sherman 

Shreveport 

Springfield 

St. Louis 

Texarkana 

Tulsa 

Tupelo 

Tyler 

West Point 

Wichita 

Wichita Falls 

Woodward 

1:100,000 Scale Data

Antlers 

Conway 

DeQueen 

Fly Gap Mountains 

McAlester 

Mena 

Mountainview 

Russellville
Kansas City Power & Light A - 2 Trinity Consultants

BART Modeling Protocol 

TABLE A-2. TERRAIN DATA USED IN ANALYSIS

1:250,000 Scale Data

Abilene-E 

Abilene-W 

Ardmore-E 

Ardmore-W 

Belleville-E 

Belleville-W 

Beloit-E 

Beloit-W 

Blytheville-E 

Blytheville-W 

Clinton-E 

Clinton-W 

Dallas-E 

Dallas-W 

Decatur-E 

Decatur-W 

Dyersburg-E 

Dyersburg-W 

El Dorado-E 

El Dorado-W 

Enid-E 

Enid-W 

Fort Smith-E 

Fort Smith-W 

Great Bend-E 

Great Bend-W 

Greenwood-E 

Greenwood-W 

Harrison-E 

Harrison-W 

Helena-E 

Helena-W 

Hutchinson-E 

Hutchinson-W 

Jackson-E 

Jackson-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 

Little Rock-E 

Little Rock-W 

Manhattan-E 

Manhattan-W 

McAlester-E 

McAlester-W 

Memphis-E 

Memphis-W 

Meridian-E 

Meridian-W 

Moberly-E 

Moberly-W 

Oklahoma City-E 

Oklahoma City-W 

Paducah-E 

Paducah-W 

Poplar Bluff-E 

Poplar Bluff-W 

Pratt-E 

Pratt-W 

Quincy-E 

Quincy-W 

Rolla-E 

Rolla-W 

Russellville-E 

Russellville-W 

Sherman-E 

Sherman-W 

Shreveport-E 

Shreveport-W 

Springfield-E 

Springfield-W 

Saint Louis-E 

Saint Louis-W 

Texarkana-E 

Texarkana-W 

Tulsa-E 

Tulsa-W 

Tupelo-E 

Tupelo-W 

Tyler-E 

Tyler-W 

West Point-E 

West Point-W 

Wichita Falls-E 

Wichita Falls-W 

Wichita-E 

Wichita-W 

Woodward-E 

Woodward-W 
Kansas City Power & Light B - 1 Trinity Consultants

BART Modeling Protocol 

APPENDIX B 

TABLE B-1. LIST OF SURFACE METEOROLOGCAL STATIONS

Station 

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

3927 DALLAS-FORT WORTH INTL AP KDFW 32.900 -97.017 217.594 -110.664 

3928 WICHITA MID-CONTINENT AP KICT 37.650 -97.433 168.277 415.757 

3945 COLUMBIA REGIONAL AIRPORT KCOU 38.817 -92.217 616.499 566.49 

3947 KANSAS CITY INT'L ARPT KMCI 39.300 -94.717 397.998 606.872 

13930 WHITEMAN AFB KSZL 38.717 -93.550 502.081 547.665 

13957 SHREVEPORT REGIONAL ARPT KSHV 32.450 -93.817 518.947 -148.434 

13959 WACO REGIONAL AP KACT 31.617 -97.233 200.571 -253.861 

13962 ABILENE REGIONAL AP KABI 32.417 -99.683 -31.46 -166.963 

13964 FORT SMITH REGIONAL AP KFSM 35.333 -94.367 450.826 168.614 

13966 WICHITA FALLS MUNICIPAL ARPT KSPS 33.983 -98.500 78.106 7.4 

13967 OKLAHOMA CITY WILL ROGERS WOR KOKC 35.383 -97.600 158.172 163.934 

13968 TULSA INTERNATIONAL AIRPORT KTUL 36.200 -95.883 310.224 258.752 

13969 PONCA CITY MUNICIPAL AP KPNC 36.733 -97.100 199.91 314.65 

13977 TEXARKANA WEBB FIELD KTXK 33.450 -94.000 495.621 -38.391 

13984 CONCORDIA BLOSSER MUNI AP KCNK 39.550 -97.650 145.489 626.359 

13989 EMPORIA MUNICIPAL AP KEMP 38.333 -96.183 275.593 494.432 

13995 SPRINGFIELD REGIONAL ARPT KSGF 37.233 -93.383 526.725 384.127 

13996 TOPEKA MUNICIPAL AP KTOP 39.067 -95.633 320.318 577.594 

72244 TYLER/POUNDS FLD KTYR 32.350 -95.400 370.978 -166.863 

72249 NACOGDOCHES (AWOS) KOCH 31.583 -94.717 439.217 -249.285 

72258 COX FLD KPRX 33.633 -95.450 360.508 -24.527 

72341 MEMORIAL FLD KHOT 34.467 -93.100 571.592 79.365 

72344 FAYETTEVILLE DRAKE FIELD KFYV 36.000 -94.167 464.929 243.488 

72349 JOPLIN MUNICIPAL AP KJLN 37.150 -94.500 428.648 369.387 

72352 ARDMORE K1F0 34.150 -97.117 205.042 27.981 

72445 KIRKSVILLE REGIONAL AP KIRK 40.100 -92.550 577.7 706.619 

72449 ST JOSEPH ROSECRANS MEMORIAL KSTJ 39.767 -94.900 379.885 657.971 

72450 CHANUTE MARTIN JOHNSON AP KCNU 37.667 -95.483 339.483 422.786 

72455 MANHATTAN RGNL KMHK 39.133 -96.667 230.987 581.961 

72458 SALINA MUNICIPAL AP KSLN 38.817 -97.667 145.454 544.915 

93950 MCALESTER MUNICIPAL AP KMLC 34.900 -95.783 324.515 114.893 

93986 HOBART MUNICIPAL AP KHBR 35.000 -99.050 27.099 120.026 

72439 QUINCY MUNICIPAL BALDWIN FLD KUIN 39.900 -91.200 694.052 693.367 

72439 SPRINGFIELD CAPITOL AP KSPI 39.800 -89.600 831.037 694.973 

72433 BELLEVILLE SCOTT AFB KBLV 38.500 -89.800 828.344 549.557 
Kansas City Power & Light B - 2 Trinity Consultants

BART Modeling Protocol 

Station 

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

72531 KAHOKIA/ST. LOUIS KCPS 38.500 -90.100 802.399 547.016 

72445 JEFFERSON CITY MEM KJEF 38.500 -92.100 629.243 532.143 

72445 KAISER MEM KAIZ 38.100 -92.500 597.734 485.303 

72445 SEDALIA MEM KDMO 38.700 -93.100 541.118 548.219 

72445 VICHY ROLLA NATL APT KVIH 38.100 -91.700 667.423 490.56 

72445 FARMINGTON APT KFAM 37.700 -90.400 784.689 456.128 

72433 CARBONDALE KMDH 37.700 -89.200 889.555 466.564 

72348 CAPE GIRARDEAU MUNICIPAL APT KCGI 37.200 -89.500 869.018 408.63 

72435 PADUCAH BARKLEY REG AP KPAH 37.000 -88.700 941.785 394.085 

72330 POPLAR BLUFF KPOF 36.700 -90.400 794.99 345.628 

72334 DYERSBURG MUN AP KDYR 36.000 -89.400 891.548 277.081 

72340 WALNUT RIDGE KARG 36.100 -90.900 756.52 275.288 

72344 BATESVILLE KBVX 35.700 -91.600 697.546 225.767 

72340 JONESBORO MUNICIPAL APT KJBR 35.800 -90.600 786.334 244.532 

72334 JACKSON MCKELLAR-SIPES REGL KMKL 35.600 -88.900 940.995 237.698 

72334 MEMPHIS INTL APT KMEM 35.000 -89.900 857.761 162.112 

72341 STUTTGART KSGT 34.600 -91.500 716.472 104.798

72341 PINE BLUFF/GRIDER KPBF 34.100 -91.900 684.322 46.538 

72340 LITTLE ROCK ADAMS FIELD KLIT 34.700 -92.200 651.867 110.892 

72340 LITTLE ROCK AFB KLRF 34.900 -92.100 659.299 133.715 

72344 FLIPPIN KFLP 36.300 -92.400 620.853 286.681 

72531 DECATUR KDEC 39.800 -88.800 898.976 702.162 

72433 MOUNT VERNON KMVN 38.300 -88.800 917.197 536.538 

72434 ST. LOUIS LAMBERT INTL APT KSTL 38.700 -90.300 783.013 567.477 

TABLE B-2. LIST OF PRECIPITATION METEOROLOGICAL STATIONS

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

30130 ALUM FORK ALUM 34.800 -92.850 591.935 117.768

30178 ANTOINE ANTO 34.033 -93.417 545.626 29.461 

30220 ARKADELPHIA 2 N ARKA 34.150 -93.050 578.461 44.534 

30764 BLAKELY MOUNTAIN DAM BLAK 34.567 -93.200 561.75 89.82 

30832 BOONEVILLE 3 SSE BOON 35.100 -93.917 493.003 144.997 

30900 BRIGGSVILLE BRIG 34.933 -93.500 531.902 128.745 

31152 CAMDEN 1 CAMD 33.600 -92.817 604.003 -14.996 

31457 CLARKSVILLE 6 NE CLAR 35.533 -93.400 536.873 195.774 

31952 DE QUEEN DAM DE Q 34.100 -94.367 457.937 31.902 

32020 DIERKS DAM DIER 34.150 -94.083 483.655 38.834

32544 FOREMAN FORE 33.717 -94.383 458.602 -10.703 

32574 FORT SMITH MU, OK FORT 35.333 -94.367 450.855 168.653 

33165 HARRISON BOONE CNTY AP HARR 36.267 -93.157 553.576 278.374 

34185 LEWISVILLE LEWI 33.367 -93.567 536.29 -45.314
Kansas City Power & Light B - 3 Trinity Consultants

BART Modeling Protocol 

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

34548 MAGNOLIA 3 N MAGN 33.333 -93.250 565.86 -47.199 

34756 MENA MENA 34.567 -94.267 464.388 84.135 

35200 NIMROD DAM NIMR 34.950 -93.167 562.061 132.486 

35228 NORFORK DAM NORF 36.249 -92.256 634.101 282.023 

35908 PRESCOTT PRES 33.800 -93.383 550.293 3.781 

37048 TEXARKANA TEXA 33.450 -94.000 495.621 -38.391

37488 WALDRON WALD 34.900 -94.100 477.588 121.905 

140326 ARLINGTON ARLI 37.900 -98.267 94.684 442.364

141233 CALDWELL CALD 37.034 -97.616 153.468 347.056

141427 CHANUTE FAA AIRPORT CHAN 37.670 -95.484 339.366 423.145 

141767 CONCORDIA BLOSSER MUNI CONC 39.551 -97.651 145.415 626.512 

141867 COUNCIL GROVE LAKE COUN 38.675 -96.526 244.636 531.493 

143997 IONIA IONI 39.661 -98.348 85.529 637.868 

144341 KIOWA KIOW 37.017 -98.485 76.494 344.138 

145063 MARYSVILLE MARY 39.833 -96.633 231.722 659.797 

145306 MILFORD LAKE MILF 39.075 -96.898 211.249 574.959 

147160 SALINA AP SALI 38.817 -97.667 145.454 544.915 

148167 TOPEKA BILLARD MUNI AP TOPE 39.069 -95.639 319.802 577.785 

148293 UNIONTOWN UNIO 37.848 -94.978 382.945 444.73

148830 WICHITA WICH 37.650 -97.433 168.277 415.757 

165874 MANSFIELD MANS 32.033 -93.700 532.631 -194.082

166244 MINDEN MIND 32.600 -93.300 566.346 -128.864

166582 NATCHITOCHES NATC 31.767 -93.100 591.063 -220.21 

167738 RED RIVER RSRCH STN RED 32.417 -93.633 536.38 -151.129

168440 SHREVEPORT, LA SHRE 32.467 -94.317 472.014 -149.154

230204 APPLETON CITY APPL 38.184 -94.026 464.144 486.148 

230789 BOLIVAR 1 NE BOLI 37.617 -93.391 523.377 426.582 

231383 CASSVILLE RANGER STN CASS 36.673 -93.858 488.393 319.564 

231791 COLUMBIA REGIONAL AP COLU 38.817 -92.218 616.384 566.475 

232302 DORA DORA 36.780 -92.233 631.838 340.862 

234315 JOPLIN REGIONAL AP JOPL 37.147 -94.502 428.471 369.008 

234358 KANSAS CITY AP KANS 39.300 -94.717 397.998 606.872 

234544 KIRKSVILLE KIRK 40.200 -92.567 575.475 717.609 

234825 LEBANON 2 W LEBA 37.685 -92.694 584.043 438.162 

235834 MOUNTAIN GROVE 2 N MOUN 37.153 -92.264 626.06 381.947 

235987 NEVADA WATER PLANT NEVA 37.839 -94.373 435.885 446.376 

237976 SPRINGFIELD REG AP SPRI 37.240 -93.390 526.086 384.835 

238252 TABLE ROCK DAM TABL 36.597 -93.308 537.808 314.127 

238466 TRUMAN DAM & RESERVIOR TRUM 38.258 -93.399 518.297 497.601 

340179 ALTUS IRIG RES STN ALTU 34.583 -99.333 1.342 73.726 

340215 AMES AMES 36.250 -98.183 104.257 259.348 

340292 ARDMORE ARDM 34.167 -97.133 203.499 29.797 
Kansas City Power & Light B - 4 Trinity Consultants

BART Modeling Protocol 

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

340670 BENGAL BENG 34.850 -95.083 388.412 111.938 

341437 CANEY CANE 34.233 -96.217 287.462 39.536 

341544 CARTER TOWER CART 34.267 -94.783 418.786 48.493 

341684 CHANDLER 1 CHAN 35.700 -96.883 222.108 200.524 

341750 CHICKASHA EXP STN CHIC 35.050 -97.917 130.07 126.502 

342334 CUSTER CITY CUST 35.650 -98.833 46.415 192.255 

342654 DUNCAN AIRPORT DUNC 34.483 -97.967 126.429 63.529 

342849 ELK CITY ELK 35.383 -99.400 -4.705 162.536 

343281 FORT COBB FORT 35.100 -98.433 83.068 131.48 

343497 GEARY GEAR 35.633 -98.317 93.029 190.78 

344052 HENNEPIN 5 N HENN 34.567 -97.350 182.671 73.771 

344202 HOBART HOBA 35.033 -99.083 24.058 123.718 

344865 KINGSTON KING 34.000 -96.733 240.748 12.214 

344975 LAKE EUFAULA LAKE 35.283 -95.433 354.598 158.646 

345108 LEHIGH LEHI 34.467 -96.217 286.619 65.434 

345463 MACKIE 4 NNW MACK 35.750 -99.833 -43.712 203.34 

345589 MARSHALL MARS 36.150 -97.617 155.133 249.015

345664 MCALESTER MUNI AP MCAL 34.883 -95.783 324.554 113.043 

346130 MUSKOGEE MUSK 35.767 -95.333 361.415 212.616

346620 OKARCHE OKAR 35.717 -97.983 122.963 200.402 

346638 OKEMAH OKEM 35.433 -96.300 275.597 172.448 

346661 OKLAHOMA CITY, OK OKLA 35.383 -97.600 158.171 163.971 

347196 PONCA CITY PONC 36.717 -97.100 199.951 312.875 

347705 ROFF 2 WNW ROFF 34.633 -96.883 225.139 82.16

348992 TULSA INTL AIRPORT TULS 36.198 -95.888 309.803 258.552 

349023 TUSKAHOMA TUSK 34.633 -95.283 371.223 87.116

349629 WICHITA MTN WL REF WICH 34.733 -98.717 57.604 90.569 

349724 WISTER WIST 34.950 -94.700 422.763 124.642 

349748 WOLF 4 N WOLF 35.133 -96.667 243.38 138.175 

410016 ABILENE MUN, TX ABIL 32.417 -99.683 -31.492 -167 

410926 BONITA 4 NW BONI 33.833 -97.633 158.221 -8.161 

411246 BURLESON BURL 32.550 -97.317 190.447 -150.213

411698 CHILDRESS MUNI AP CHIL 34.433 -100.283 -85.662 57.486 

411773 CLARKSVILLE 1 W CLAR 33.617 -95.017 400.641 -24.627 

411921 COMMERCE COMM 33.200 -95.933 317.534 -74.315

412086 CRANFILLS GAP CRAN 31.767 -97.833 143.384 -238.27 

412096 CRESSON CRES 32.533 -97.617 162.357 -152.616

412131 CROSS PLAINS 2 CROS 32.133 -99.167 17.09 -198.565

412242 DALLAS-FORT WORTH/FORT. TX. DALL 32.900 -97.017 217.625 -110.663

412244 DALLAS LOVE FIELD DALL 32.850 -96.850 233.324 -115.831

412404 DENTON 2 SE DENT 33.200 -97.100 209.069 -77.506 

412715 EASTLAND EAST 32.400 -98.817 49.911 -168.771
Kansas City Power & Light B - 5 Trinity Consultants

BART Modeling Protocol 

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

413133 FERRIS FERR 32.517 -96.667 251.477 -152.428

413285 FORT WORTH WSFO FORT 32.833 -97.300 191.339 -118.676

413415 GAINESVILLE GAIN 33.633 -97.133 204.862 -29.433 

413546 GILMER 2 W GILM 32.733 -94.983 408.173 -122.577

413642 GORDONVILLE GORD 33.800 -96.850 230.585 -10.281 

413771 GROESBECK 2 GROE 31.533 -96.533 267.178 -261.477

414137 HICO HICO 31.983 -98.033 124.123 -214.429

414257 HONEY GROVE HONE 33.583 -95.900 319.106 -31.63 

414520 JACKSBORO 1 NNE JACK 33.233 -98.150 111.378 -75.549 

414866 KOPPERL KOPP 32.133 -97.483 175.721 -196.88 

414972 LAKE BRIDGEPORT DAM LAKE 33.217 -97.833 140.846 -76.986 

415348 LONGVIEW TX. LONG 32.350 -94.650 441.401 -163.699

415463 MABANK 4 SW MABA 32.350 -96.117 303.664 -169.375

415957 MINERAL WELLS 1 SSW MINE 32.783 -98.117 115.117 -125.535

415996 MOLINE MOLI 31.400 -98.317 98.07 -279.711

416108 MOUNT PLEASANT MOUN 33.167 -95.000 404.44 -74.517 

416177 NACOGDOCHES NACO 31.617 -94.650 445.383 -245.232

416210 NAVARRO MILLS DAM NAVA 31.950 -96.700 250.085 -215.548

416270 NEW BOSTON NEW 33.450 -94.417 457.042 -40.453 

416335 NEW SUMMERFIELD 2 W NEW 31.983 -95.133 397.806 -206.567

416757 PALESTINE 2 NE PALE 31.783 -95.600 354.65 -230.638

416834 PAT MAYSE DAM PAT 33.867 -95.517 353.313 1.165 

417066 PITTSBURG 5 S PITT 32.933 -94.933 411.826 -100.148

417300 PROCTOR RESERVOIR PROC 31.967 -98.500 80.081 -216.779

417499 RED SPRINGS 2 ESE RED 33.600 -99.383 -3.269 -35.493 

417556 RENO RENO 32.950 -97.567 166.188 -106.202

418047 SANTA ANNA SANT 31.750 -99.333 1.39 -241.254

418583 STAMFORD 1 STAM 32.933 -99.800 -42.179 -109.493

418623 STEPHENVILLE 1 N STEP 32.250 -98.200 108.034 -184.954

418743 SULPHUR SPRINGS SULP 33.150 -95.633 345.632 -78.835 

418778 SWAN SWAN 32.450 -95.417 368.959 -155.811

419163 TRUSCOTT TRUS 33.750 -99.867 -47.911 -18.699

419419 WACOMADISON-COOPER TX. WACO 31.617 -97.233 200.54 -253.899

419532 WEATHERFORD WEAT 32.750 -97.767 147.896 -128.764

419565 WELLINGTON WELL 34.833 -100.217 -79.156 101.839 

419715 WHITNEY DAM WHIT 31.850 -97.367 187.363 -228.192

419729 WICHITA FALLS/SHEPS AFB TX WICH 33.983 -98.500 78.106 7.437 

419817 WINCHELL WINC 31.467 -99.167 17.23 -272.793

419893 WOODSON WOOD 33.017 -99.050 27.781 -100.284

419916 WRIGHT PATMAN WRIG 33.300 -94.167 481.088 -55.882 

118179 SPRINGFIELD SPRI 39.850 -89.680 823.683 699.815 

114442 JACKSONVILLE JACK 39.730 -90.200 780.783 682.207 
Kansas City Power & Light B - 6 Trinity Consultants

BART Modeling Protocol 

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

116837 PITTSFIELD PITT 39.610 -90.800 730.895 664.216 

231640 CLARKSVILLE L&D CLAR 39.360 -90.900 724.802 635.788 

113666 GREENFIELD GREE 39.350 -90.210 783.935 640.088 

111284 CARLINVILLE CARL 39.280 -89.880 812.919 635.084 

115841 MORRISONVILLE MORR 39.410 -89.460 847.375 653.077 

111290 CARLYLE RESERVOIR CARL 38.630 -89.360 864.887 567.788 

118147 SPARTA SPAR 38.110 -89.710 840.454 507.252 

115983 MURPHYSBORO MURP 37.760 -89.360 874.891 471.721 

233601 HANNIBAL WATER WORKS HANN 39.710 -91.360 682.205 671.178 

231600 CLARENCE CANNON DAM CLAR 39.530 -91.630 660.799 649.357 

235050 LONG BRANCH RESERVOIR LONG 39.750 -92.510 583.855 668.049 

235671 MOBERLY MOBE 39.400 -92.430 593.467 629.742 

236012 NEW FRANKLIN NEW 39.010 -92.750 569.027 584.59 

233079 FULTON FULT 38.850 -91.930 640.981 572.019 

231283 CAP AU GRIS CAP 39.000 -90.680 747.223 597.635 

238746 WASHINGTON WASH 38.550 -90.980 725.766 545.56 

237300 ROSEBUD ROSE 38.450 -91.380 692.073 531.55 

237263 ROLLA UNIV OF MO ROLL 37.950 -91.780 661.764 473.409 

238620 VIENNA VIEN 38.200 -91.980 642.188 499.724 

238043 STEELVILLE STEE 38.000 -91.360 697.947 481.907 

236826 POTOSI POTO 37.960 -90.760 750.633 481.998 

238609 VIBURNUM VIBU 37.710 -91.130 720.74 451.526 

237506 SALEM SALE 37.550 -91.880 656.478 428.461 

230088 ALLEY SPRINGS ALLE 37.150 -91.450 697.833 387.234 

231674 CLEARWATER DAM CLEA 37.130 -90.760 758.841 390.244 

232809 FARMINGTON FARM 37.800 -90.410 782.785 467.099 

230022 ADVANCE ADVA 37.100 -89.900 834.924 394.048 

238700 WAPPAPELLO DAM WAPP 36.930 -90.280 803.219 372.036 

238880 WEST PLAINS WEST 36.750 -91.830 667.791 340.292 

232302 DORA DORA 36.780 -92.230 632.081 340.911 

235207 MALDEN MUNICIPAL MALD 36.610 -89.980 833.16 339.238 

233999 HORNERSVILLE HORN 36.050 -90.110 827.589 276.263 

220237 ARKABUTLA DAM, MS ARKA 34.450 -90.080 847.34 99.742 

221314 CALHOUN CITY 2 NW CALH 33.520 -89.210 937.459 5.027 

221707 CLARKSDALE CLAR 34.120 -90.340 827.064 60.998 

221743 CLEVELAND 3 N CLEV 33.480 -90.430 825.402 -10.568 

223650 GRENADA DAM GREN 33.480 -89.460 914.88 -1.8 

224001 HICKORY FLAT HICK 34.370 -89.110 936.648 99.892 

224173 HOLLY SPRINGS 4 N HOLL 34.490 -89.260 921.582 111.695 

226084 MOUNT PLEASANT 4 SW MOUN 34.540 -89.330 914.634 116.549 

227820 SAREPTA 1 NNE SARE 34.070 -89.180 933.781 66.081 

229079 UNIVERSITY, MS UNIV 34.230 -89.320 919.123 82.406 
Kansas City Power & Light B - 7 Trinity Consultants

BART Modeling Protocol 

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

400876 BOLIVAR WATERWORKS, TN BOLI 35.160 -88.590 974.247 192.241 

401150 BROWNSVILLE SEWAGE P BROW 35.350 -89.160 920.598 207.596 

403697 GREENFIELD GREE 36.100 -88.470 973.304 297.122 

404556 JACKSON MCKELLAR-SIP JACK 35.360 -88.550 975.369 214.706 

404561 JACKSON EXP STA JACK 35.370 -88.500 979.742 216.317 

405720 MASON MASO 35.240 -89.320 907.463 193.934 

405954 MEMPHIS INTL ARPT MEMP 35.030 -90.000 848.388 164.54 

405956 MEMPHIS WSFO MEMP 35.080 -89.480 894.852 174.771 

406358 MUNFORD MUNF 35.270 -89.490 891.793 195.658 

406750 OAK RIDGE OAK 36.000 -84.150 1358.823 338.461 

408065 SAMBURG WILDLIFE REF SAMB 36.270 -89.190 907.143 308.843 

409219 UNION CITY, TN UNIO 36.240 -89.020 922.623 307.148 

30064 ALICIA, AR ALIC 35.540 -91.050 748.472 212.202 

30458 BATESVILLE LIVESTOCK BATE 35.500 -91.460 711.939 204.668 

30530 BEEBE BEEB 35.040 -91.540 708.871 153.189 

30936 BRINKLEY BRIN 34.530 -91.110 752.656 100.029 

31632 CORNING CORN 36.260 -90.350 803.976 297.429 

32148 DUMAS DUMA 33.530 -91.290 745.537 -12.05 

32978 GREERS FERRY DAM GREE 35.310 -92.000 664.907 179.784 

33132 HARDY HARD 36.170 -91.280 721.923 280.109 

34900 MONTICELLO 3 SW MONT 33.360 -91.480 729.54 -32.333 

35754 PINE BLUFF PINE 34.140 -92.010 673.896 50.191

36920 STUTTGART 9 ESE STUT 34.280 -91.250 742.228 71.28 

38052 WYNNE, AR WYNN 35.150 -90.480 803.727 173.682
Kansas City Power & Light C - 1 Trinity Consultants

BART Modeling Protocol 

APPENDIX C

DETAILED EMISSION CALCULATIONS
Table C-1. Model Inputs Summary

 Source Name Base Elevation Latitude NAD83 Longitude NAD83 Stack Ht. GEP Stack Height Stack Diameter Exit Velocity Gas Temperatur e

ft dec. deg. dec. deg. ft ft ft ft/sec °F

La Cygne - Unit 1 850 38.349 -94.646 700 591.2 23.0 92.7 127La Cygne - Unit 2 850 38.348 -94.646 700 597.8 24.0 100.8 281

BART-Eligible Source Name

SO2 NOX PM10 SO2 NOX PM10 SO4 PMC PMf SOA EC

La Cygne - Unit 1 73.81 139.07 0.65 6,151.15 11,589.52 53.79 34.37 4.92 5.68 8.59 0.22

La Cygne - Unit 2 99.79 42.52 1.14 8,316.15 3,543.47 94.92 28.12 33.20 25.58 7.03 0.98

¶The Highest 24-hr Actual Mass Emission Rates of SO2 and NOX are determined from actual monitored data from 2002-2004. The Highest 24-hr Actual Mass Emission Rate of PM10 is calculated based on actual fuelusage data (the maximum daily heat input from 2002-2004, the minimum annual average fuel heat content from 2002-2004, the maximum annual average ash content from 2002 to 2004, and the maximum annual averagesulfur content from 2002-2004) and AP-42 emission factors (see Table C-2).

Highest 24 hr Actual 

Emission Rate¶ 2002-2004 

ton/24 hr

Input to CALPUFF 

 Hourly Mass Emission Rate 

lb/hr
Table C-2.

PM10 Emissions

24-Hr Fuel Usage

Maximum 24-Hr 

Coal Usage

Maximum 24-Hr 

Heat Input

(ton/24hr) (MMBtu/24hr)

La Cygne 1 12,806 223,488

La Cygne 2 11,739 198,911

The maximum daily coal usage is calculated by dividing the maximum daily heat input from 2002-2004 by the minimum of the annual average heat contents from 2002-2004.

The maximum daily heat input is the maximum daily heat input from the years 2002-2004.

PM10 Filterable and Condensable Emission Factors 

PM10 Filterable 

Emission Factor*

Emission Factor 

Units

Emission Factor 

Source

PM10 Condensible 

Emission Factor** Units Source

Sulfur 

Content§

(%)

Ash Content¥

(%)

Control 

Efficiency 

Filterable

Control 

Efficiency 

Condensable

La Cygne 1 2.17 lb/ton AP-42 Table 1.1-4 0.02 lb/MMBtu AP-42 Table 1.1-5 1.21 8.35 96% 96%

La Cygne 2 12.63 lb/ton AP-42 Table 1.1-4 0.004 lb/MMBtu AP-42 Table 1.1-5 0.34 5.49 99% 0%

*PM10 filterable emission factors are for "Cyclone furnace" boiler (La Cygne 1) and "PC-fired, dry bottom, wall-fired" boiler" (La Cygne 2).**PM10 condensable emission factor for La Cygne 1 is for PC boiler with FGD control; the factor for La Cygne 2 is for PC boiler without FGD control. §The coal sulfur content is the maximum of the annual average sulfur contents from 2002-2004.¥The coal ash content is the maximum of the annual average ash contents from 2002-2004.

24-Hr Emissions

PM10 Filterable 24-

Hr Emissions 

(Uncontrolled)

PM10 Condensable 

24-Hr Emissions 

(Uncontrolled)

Total PM10 

(Uncontrolled)

PM10 Filterable 

Emissions 

(Controlled)

PM10 Condensable 

Emissions 

(Controlled)

Total PM10 

(Controlled)

(lb/24-hr) (lb/24-hr) (lb/24-hr) (lb/24-hr) (lb/24-hr) (lb/24-hr)

La Cygne 1 27,802 4,470 32,271 1,112 179 1,291

La Cygne 2 148,232 796 149,028 1,482 796 2,278

Hourly Emissions (Based on 24-hr emissions divided by 24hrs)

PM10 Filterable 24-

Hr Emissions 

(Uncontrolled)

PM10 Condensable 

24-Hr Emissions 

(Uncontrolled)

Total PM10 

(Uncontrolled)

PM10 Filterable 

Emissions 

(Controlled)

PM10 Condensable 

Emissions 

(Controlled)

Total PM10 

(Controlled)

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

La Cygne 1 1,158 186 1,345 46 7 54

La Cygne 2 6,176 33 6,209 62 33.15 95
Table C-3.

La Cygne Unit 1 PM10 Speciation

Controlled PM10 Speciation from AP-42 Tables 1.1-5 & 1.1-8Cyclone Furnace w FGD + ESP for Emissions controlassumes heating value of 8,794 Btu/lb and a sulfur content of 1.03 % and an ash content of 8.05 % and a heat inp 9,312 mmBtu/hr 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 Particle 

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) Type Ext.Coef.

Cyclone 0.0250 0.0050 0.0023 0.6 0.0027 0.00265 1 0.00010 10 0.020 0.016 SO4 3*f(RH) 0.004 SOA 4

Controlled PM10 Emissions (Bold Values from Table 1.1-8.)

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

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) Type Ext.Coef.

Cyclone 0.440 0.089 0.040 0.6 0.048 0.0465 1 0.0018 10 0.352 0.281 SO4 3*f(RH) 0.070 SOA 4

Controlled PM10 Emissions

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

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) Type Ext.Coef.

Cyclone 100% 20.1% 9.1% 0.6 11.0% 10.6% 1 0.4% 10 79.9% 63.9% SO4 3*f(RH) 16.0% SOA 4

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 Particle 

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) Type Ext.Coef.

Cyclone 53.8 10.82 4.92 0.6 5.90 5.68 1 0.22 10 43.0 34.4 SO4 3 8.6 SOA 4

Weighted Extinction 3.0 5.7 2.2 103.1 34.4 2.8

Coarse 9.1% Coarse 4.9Fine Soil 10.6% Fine Soil 5.7Fine EC 0.4% Fine EC 0.2

CPM IOR 63.9% CPM IOR 34.4CPM OR 16.0% CPM OR 8.6

100.0% 53.8
Table C-4.

La Cygne Unit 2 PM10 Speciation

Controlled PM10 Speciation from AP-42 Tables 1.1-5 & 1.1-6Dry Bottom Boiler burning Pulverized Coal using only ESP for Emissions controlassumes heating value of 8596 Btu/lb and a sulfur content of 0.33 % and an ash content of 5.41 % and a heat input o 8,288 mmBtu/hr 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 Particle 

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) Type Ext.Coef.

PC-DB 0.0270 0.0170 0.0094 0.6 0.0076 0.0073 1 0.0003 10 0.010 0.008 SO4 3*f(RH) 0.002 SOA 4

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 Particle 

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) Type Ext.Coef.

PC-DB 0.464 0.292 0.162 0.6 0.130 0.125 1 0.005 10 0.172 0.138 SO4 3*f(RH) 0.034 SOA 4

Controlled PM10 Emissions

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

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) Type Ext.Coef.

PC-DB 100% 63.0% 35.0% 0.6 28.0% 26.9% 1 1.0% 10 37.0% 29.6% SO4 3*f(RH) 7.4% SOA 4

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 Particle 

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) Type Ext.Coef.

PC-DB 94.9 59.8 33.2 0.6 26.6 25.6 1 1.0 10 35.2 28.1 SO4 3 7.0 SOA 4

Weighted Extinction 19.9 25.6 9.8 84.4 28.1 1.8

Coarse 35.0% Coarse 33.2Fine Soil 26.9% Fine Soil 25.6Fine EC 1.0% Fine EC 1.0

CPM IOR 29.6% CPM IOR 28.1CPM OR 7.4% CPM OR 7.0

100.0% 94.9
Kansas City Power & Light D - 1 Trinity Consultants

BART Modeling Protocol 

APPENDIX D 

RECEPTOR DATA

Receptor Latitude 

(deg) 

Longitude 

(deg) 

Elevation 

(m) 

1 36.654 -92.946 274

2 36.654 -92.938 299

3 36.654 -92.929 328

4 36.654 -92.921 365

5 36.663 -92.963 250

6 36.663 -92.954 278

7 36.663 -92.946 335

8 36.663 -92.938 307

9 36.663 -92.929 345

10 36.671 -92.971 261

11 36.671 -92.963 271

12 36.671 -92.954 274

13 36.671 -92.946 331

14 36.671 -92.938 327

15 36.671 -92.929 304

16 36.671 -92.921 335

17 36.671 -92.913 312

18 36.671 -92.904 340

19 36.671 -92.896 361

20 36.671 -92.888 382

21 36.679 -92.971 274

22 36.679 -92.963 274

23 36.679 -92.954 335

24 36.679 -92.946 294

25 36.679 -92.938 304

26 36.679 -92.929 279

27 36.679 -92.921 304

28 36.679 -92.913 318

29 36.679 -92.904 335

30 36.679 -92.896 347

31 36.679 -92.888 340

32 36.688 -92.954 247

33 36.688 -92.946 271

34 36.688 -92.938 275

35 36.688 -92.929 274

36 36.688 -92.921 277

37 36.688 -92.913 304

38 36.688 -92.904 330

39 36.688 -92.896 357

40 36.688 -92.888 384

41 36.688 -92.879 372

42 36.696 -92.979 274

43 36.696 -92.971 293

44 36.696 -92.963 272

45 36.696 -92.954 271

46 36.696 -92.946 274

47 36.696 -92.938 327
Kansas City Power & Light D - 2 Trinity Consultants

BART Modeling Protocol 

Receptor Latitude 

(deg) 

Longitude 

(deg) 

Elevation 

(m) 

48 36.696 -92.929 316

49 36.696 -92.921 304

50 36.696 -92.913 354

51 36.696 -92.904 346

52 36.696 -92.896 335

53 36.696 -92.888 344

54 36.696 -92.879 364

55 36.704 -92.971 243

56 36.704 -92.963 335

57 36.704 -92.954 324

58 36.704 -92.946 335

59 36.704 -92.938 341

60 36.704 -92.929 333

61 36.704 -92.921 306

62 36.704 -92.913 304

63 36.704 -92.904 365

64 36.704 -92.896 304

65 36.704 -92.888 309

66 36.704 -92.879 307

67 36.713 -92.971 270

68 36.713 -92.963 274

69 36.713 -92.954 301

70 36.713 -92.946 274

71 36.713 -92.938 274

72 36.713 -92.929 312

73 36.713 -92.921 274

74 36.713 -92.913 322

75 36.713 -92.904 304

76 36.713 -92.896 275

77 36.713 -92.888 304

78 36.713 -92.879 290

79 36.721 -92.913 249

80 36.721 -92.904 274

81 34.704 -98.754 454

82 34.704 -98.746 486

83 34.704 -98.738 487

84 34.704 -98.729 478

85 34.704 -98.721 518

86 34.704 -98.713 518

87 34.713 -98.771 510

88 34.713 -98.763 493

89 34.713 -98.754 488

90 34.713 -98.746 615

91 34.713 -98.738 522

92 34.713 -98.729 494

93 34.713 -98.721 609

94 34.713 -98.713 518

95 34.721 -98.779 487

96 34.721 -98.771 518

97 34.721 -98.763 609

98 34.721 -98.754 554

99 34.721 -98.746 578

100 34.721 -98.738 557

101 34.721 -98.729 571
Kansas City Power & Light D - 3 Trinity Consultants

BART Modeling Protocol 

Receptor Latitude 

(deg) 

Longitude 

(deg) 

Elevation 

(m) 

102 34.721 -98.721 670

103 34.721 -98.713 518

104 34.729 -98.763 518

105 34.729 -98.754 548

106 34.729 -98.746 548

107 34.729 -98.738 518

108 34.738 -98.763 517

109 34.738 -98.754 579

110 34.738 -98.746 613

111 34.738 -98.738 548

112 34.738 -98.729 523

113 34.746 -98.771 542

114 34.746 -98.763 545

115 34.746 -98.754 552

116 34.771 -98.679 579

117 34.779 -98.713 609

118 34.779 -98.704 654

119 34.779 -98.696 621

120 34.779 -98.688 629

121 34.779 -98.679 579

122 34.779 -98.671 560

123 34.788 -98.721 615

124 34.788 -98.713 641

125 34.788 -98.704 640

126 34.788 -98.696 662

127 34.788 -98.688 618

128 34.788 -98.679 630

129 34.788 -98.671 534

130 34.796 -98.721 606

131 34.796 -98.713 566

132 34.796 -98.704 633

133 34.796 -98.696 670

134 34.796 -98.688 609

135 34.796 -98.679 579

136 34.796 -98.671 535

137 34.804 -98.704 548

138 34.804 -98.696 518

139 34.804 -98.688 506

140 35.821 -93.454 555

141 35.821 -93.446 589

142 35.821 -93.421 563

143 35.829 -93.454 549

144 35.829 -93.446 487

145 35.829 -93.438 487

146 35.829 -93.429 490

147 35.838 -93.454 650

148 35.838 -93.446 563

149 35.838 -93.438 540

150 35.838 -93.429 502

151 35.838 -93.421 526

152 35.838 -93.404 534

153 35.838 -93.396 563

154 35.846 -93.454 548

155 35.846 -93.446 628
Kansas City Power & Light D - 4 Trinity Consultants

BART Modeling Protocol 

Receptor Latitude 

(deg) 

Longitude 

(deg) 

Elevation 

(m) 

156 35.846 -93.438 623

157 35.846 -93.429 579

158 35.846 -93.421 469

159 35.846 -93.413 457

160 35.846 -93.404 573

161 35.846 -93.396 605

162 35.846 -93.388 588

163 35.854 -93.454 608

164 35.854 -93.446 660

165 35.854 -93.438 598

166 35.854 -93.429 599

167 35.854 -93.421 639

168 35.854 -93.413 457

169 35.854 -93.404 568

170 35.863 -93.454 730

171 35.863 -93.446 681

172 35.863 -93.438 640

173 35.863 -93.429 625

174 35.863 -93.421 426

175 35.863 -93.413 555

176 35.863 -93.404 612

177 35.871 -93.463 667

178 35.871 -93.454 580

179 35.871 -93.446 656

180 35.871 -93.438 640

181 35.871 -93.429 487

182 35.871 -93.421 457

183 35.871 -93.413 654

184 35.871 -93.404 548

185 35.871 -93.396 622

186 35.871 -93.388 683

187 35.879 -93.463 579

188 35.879 -93.454 554

189 35.879 -93.446 609

190 35.879 -93.438 622

191 35.879 -93.429 427

192 35.879 -93.421 555

193 35.879 -93.413 502

194 35.879 -93.404 639

195 35.879 -93.396 580

196 35.879 -93.388 639

197 35.888 -93.446 548

198 35.888 -93.438 548

199 35.888 -93.429 438

200 35.888 -93.421 579

201 35.888 -93.404 620

202 35.896 -93.429 579

203 35.896 -93.421 426

204 35.896 -93.413 611

205 35.904 -93.446 604

206 35.904 -93.438 548

207 35.904 -93.429 488

208 35.904 -93.421 402

209 35.904 -93.413 579
Kansas City Power & Light D - 5 Trinity Consultants

BART Modeling Protocol 

Receptor Latitude 

(deg) 

Longitude 

(deg) 

Elevation 

(m) 

210 35.904 -93.404 573

211 35.904 -93.396 609

212 34.371 -94.054 365

213 34.371 -94.046 365

214 34.371 -94.038 368

215 34.379 -94.071 411

216 34.379 -94.063 462

217 34.379 -94.054 431

218 34.379 -94.046 518

219 34.379 -94.038 487

220 34.379 -94.029 396

221 34.388 -94.104 518

222 34.388 -94.096 523

223 34.388 -94.088 548

224 34.388 -94.079 579

225 34.388 -94.071 547

226 34.388 -94.063 538

227 34.388 -94.054 640

228 34.388 -94.046 608

229 34.396 -94.163 335

230 34.396 -94.154 431

231 34.396 -94.146 457

232 34.396 -94.138 414

233 34.396 -94.129 426

234 34.396 -94.121 426

235 34.396 -94.113 388

236 34.396 -94.104 388

237 34.396 -94.096 365

238 34.396 -94.088 386

239 34.396 -94.079 396

240 34.396 -94.071 426

241 34.396 -94.063 446

242 34.396 -94.054 441

243 34.396 -94.046 457

244 34.396 -94.038 465

245 34.396 -94.029 442

246 34.396 -94.021 426

247 34.404 -94.163 304

248 34.404 -94.154 304

249 34.404 -94.146 319

250 34.404 -94.138 334

251 34.404 -94.129 370

252 34.404 -94.121 405

253 34.404 -94.113 409

254 34.404 -94.104 450

255 34.404 -94.096 518

256 34.404 -94.088 609

257 34.404 -94.079 534

258 34.404 -94.071 517

259 34.404 -94.063 575

260 34.404 -94.054 600

261 34.404 -94.046 609

262 34.404 -94.038 609

263 34.404 -94.029 561
Kansas City Power & Light D - 6 Trinity Consultants

BART Modeling Protocol 

Receptor Latitude 

(deg) 

Longitude 

(deg) 

Elevation 

(m) 

264 34.413 -94.154 335

265 34.413 -94.146 432

266 34.413 -94.138 487

267 34.413 -94.129 499

268 34.413 -94.121 514

269 34.413 -94.113 442

270 34.413 -94.104 439

271 34.413 -94.096 395

272 34.413 -94.088 400

273 34.413 -94.079 426

274 34.413 -94.071 487

275 34.413 -94.063 548

276 34.413 -94.054 548

277 34.413 -94.046 548

278 34.413 -94.038 535

279 34.421 -94.146 304

280 34.421 -94.138 334

281 34.421 -94.129 396

282 34.421 -94.121 457

283 34.421 -94.113 457

284 34.421 -94.104 426

285 34.421 -94.096 411

286 34.421 -94.088 406

287 34.421 -94.079 396

288 34.421 -94.071 401

289 34.421 -94.063 397

290 34.429 -94.146 322

291 34.429 -94.138 334

292 36.946 -90.246 106

293 36.946 -90.229 102

294 36.954 -90.238 105

295 36.954 -90.229 102

296 36.954 -90.221 102

297 36.963 -90.238 114

298 36.963 -90.229 104

299 36.963 -90.221 102

300 36.963 -90.213 102

301 36.963 -90.204 102

302 36.963 -90.196 103

303 36.971 -90.229 108

304 36.971 -90.221 105

305 36.971 -90.213 102

306 36.971 -90.204 102

307 36.971 -90.196 102

308 36.971 -90.188 102

309 36.971 -90.179 102

310 36.971 -90.171 102

311 36.979 -90.221 121

312 36.979 -90.213 104

313 36.979 -90.204 102

314 36.979 -90.196 102

315 36.979 -90.188 102

316 36.979 -90.179 102

317 36.979 -90.171 102
Kansas City Power & Light D - 7 Trinity Consultants

BART Modeling Protocol 

Receptor Latitude 

(deg) 

Longitude 

(deg) 

Elevation 

(m) 

318 36.988 -90.213 121

319 36.988 -90.204 105

320 36.988 -90.196 102

321 36.988 -90.188 102

322 36.988 -90.179 102

323 36.988 -90.171 101

324 36.996 -90.204 117

325 36.996 -90.196 101

326 36.996 -90.188 101

327 36.996 -90.179 102

328 36.996 -90.171 101

329 37.004 -90.196 106

330 37.004 -90.188 102

331 37.004 -90.179 102

332 37.004 -90.171 102

333 37.013 -90.188 103

334 37.013 -90.179 102

335 37.013 -90.171 102

336 37.021 -90.179 103

337 37.021 -90.171 102

338 37.029 -90.171 103
 

BART FIVE FACTOR ANALYSIS  KANSAS CITY POWER & LIGHT

LA CYGNE GENERATING STATION

VERSION 0 

Prepared by: 

Kasi Dubbs  Managing Consultant 

Mary Pham  Consultant 

TRINITY CONSULTANTS

9777 Ridge Drive 

Suite 380 

Lenexa, Kansas 66219 

(913) 894-4500 

August 2007 

Project 061701.0125 
Kansas City Power & Light i Trinity Consultants 

BART Analysis 

TABLE OF CONTENTS

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

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

2.1 PRESUMPTIVE LIMITS............................................................................................ 2-2 

2.2 EXISTING CONTROLS ............................................................................................ 2-3 

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

4. 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 ...................................................................................4-2

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.........................................4-4

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 ..................................................................................... 4-5 

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

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

5.2 ELIMINATE TECHNICALLY INFEASIBLE NOX CONTROL TECHNOLOGIES ............... 5-2 

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 FEASIBLE NOX CONTROLS IMPACT ON VISIBILITY..................... 5-9 

5.6 PROPOSED BART FOR NOX.................................................................................. 5-10 
Kansas City Power & Light ii Trinity Consultants 

BART Analysis 

6. PM BART EVALUATION..................................................................................... 6-1

7. PROPOSED BART LIMITS COMPLIANCE SUMMARY .......................................... 7-1

7.1 SO2 BART COMPLIANCE SUMMARY .................................................................... 7-1 

7.2 NOX BART COMPLIANCE SUMMARY................................................................... 7-2 

7.3 PM10 BART COMPLIANCE SUMMARY .................................................................. 7-3 
Kansas City Power & Light iii Trinity Consultants 

BART Analysis 

LIST OF TABLES

TABLE 1-1. VISIBILITY IMPAIRMENT ATTRIBUTABLE TO LA CYGNE GENERATING STATION ............1-1

TABLE 1-2. VISIBILITY IMPAIRMENT IMPROVEMENT..........................................................................1-2

TABLE 3-1. HIGHEST ACTUAL 24-HOUR SO2 AND NOX EMISSIONS AND CALCULATED HIGHEST PM10

EMISSIONS (AS AN HOURLY EQUIVALENT) ...........................................................................3-1

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

TABLE 3-3. SUMMARY OF 98TH PERCENTILE VISIBILITY IMPACTS AND NUMBER OF DAYS WITH 

VISIBILITY IMPACT GREATER THAN 0.5 DV.........................................................................3-2

TABLE 3-4. BREAKDOWN OF POLLUTANT SPECIFIC CONTRIBUTIONS TO VISIBILITY........................3-2

TABLE 4-1. EXISTING MAXIMUM 24-HOUR SO2 EMISSION RATES ....................................................4-1

TABLE 4-2. AVAILABLE SO2 CONTROL TECHNOLOGIES.....................................................................4-1

TABLE 4-3. CONTROL EFFECTIVENESS OF TECHNICALLY FEASIBLE SO2 CONTROL TECHNOLOGIES4-3

TABLE 4-4. EXISTING AND PRESUMPTIVE BART EMISSION RATES...............................................4-5

TABLE 4-5.MODELED IMPACTS BASED ON EXISTING AND PRESUMPTIVE BART EMISSION RATES ..4-5

TABLE 5-1. EXISTING MAXIMUM 24-HOUR NOX EMISSION RATE.....................................................5-1

TABLE 5-2. AVAILABLE NOX CONTROL TECHNOLOGIES...................................................................5-1

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

TABLE 5-4. NOX CONTROL TECHNOLOGY COST FACTORS* ...............................................................5-6

TABLE 5-5. NOX CONTROL TECHNOLOGY COST SUMMARY (IN 2005 DOLLARS) FOR LA CYGNE UNIT 

2..............................................................................................................................................5-8

TABLE 5-6. EXISTING AND PRESUMPTIVE BART EMISSION RATES...................................................5-9

TABLE 5-7.MODELED IMPACTS BASED ON EXISTING AND PRESUMPTIVE BART EMISSION RATES 5-10

TABLE 6-1. HISTORICAL MAXIMUM 24-HOUR PM10 EMISSION RATE................................................6-1

TABLE 6-2. VISIBILITY IMPAIRMENT CONTRIBUTIONS .......................................................................6-1
 

Kansas City Power & Light 1-1 Trinity Consultants 

BART Analysis 

1. EXECUTIVE SUMMARY

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

proposed by Kansas City Power & Light (KCP&L) for the La Cygne Generating Station located in La 

Cygne, Kansas. There are two boilers at La Cygne. Unit 1 is an 840 MW supercritical cyclone coal 

boiler that was manufactured in 1973 by Babcock and Wilcox with a scrubber for sulfur dioxide 

(SO2) and particulate matter (PM) control and overfire air that minimizes the formation of thermal 

nitrogen oxides (NOX). Unit 2 is a 710 MW radiant opposed-fired pulverized coal (PC) boiler that 

was manufactured in 1976 by Babcock and Wilcox with an electrostatic precipitator (ESP) for PM 

control. Unit 1 burns a blend of Powder River Basin (PRB) coal and local coal. Unit 2 burns 100 

percent PRB coal. 

KCP&L has determined that the two boilers at the La Cygne Generating Station contribute greater 

than 0.5 deciviews (dv) to visibility impairment in a federally protected Class I area when compared 

to a natural background. Therefore, these two sources are subject to BART. A summary of the 

visibility impairment attributable to the boilers is provided in Table 1-1. 

TABLE 1-1. VISIBILITY IMPAIRMENT ATTRIBUTABLE TO LA CYGNE GENERATING STATION 

 Visibility Impairment 

Class I Area

98th % 

dv

Days > 0.5 

dv

Wichita Mountains Wilderness 1.02 57 

Hercules Glades Wilderness 1.74 138 

Caney Creek Wilderness 1.14 63 

Upper Buffalo Wilderness 1.92 125 

Mingo Wilderness 0.92 62 

KCP&L used the guidelines in 40 CFR Part 511 to determine BART for the boilers. Specifically, 

KCP&L conducted a five-step 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, KCP&L proposes the following as BART: 

• NOX – KCP&L proposes to meet the U.S. Environmental Protection Agency’s (EPA’s) 

presumptive BART limits of 0.10 lb/MMBtu and 0.23 lb/MMBtu for Unit 1 and Unit 2, 

respectively, by complying with a combined Unit 1 and Unit 2 weighted average limit. This 

 

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

Determinations 
 

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BART Analysis 

will be achieved by operating the currently permitted SCR on Unit 1 and by installing NOX

controls on Unit 2. 

• SO2 – KCP&L proposes to meet the U.S. EPA’s presumptive BART limit of 0.15 lb/MMBtu 

for Unit 1 and Unit 2 by complying with a combined Unit 1 and Unit 2 weighted average 

limit by installing either wet scrubbers or spray dryer absorbers (SDA) on both units. 

• PM – KCP&L proposes that no additional PM controls are required for BART compliance 

because the PM controls would provide little visibility improvement while requiring 

significant capital expenditures. Although not required for BART compliance, KCP&L plans 

to install baghouses on Unit 1 and Unit 2 for compliance with other environmental 

regulations. 

The proposed presumptive BART emission rates will result in reductions of the visibility impacts 

attributable to La Cygne Unit 1 and Unit 2. A summary of the visibility improvement based on the 

existing emission rates and presumptive BART emission rates is provided in Table 1-2. 

TABLE 1-2. VISIBILITY IMPAIRMENT IMPROVEMENT

 

Caney Creek 

Wilderness 

Hercules Glades 

Wilderness 

Mingo Wilderness Upper Buffalo 

Wilderness 

Wichita Mountains 

Wilderness 

 

Existing 

BART 

Improvement 

Existing 

BART 

Improvement 

Existing 

BART 

Improvement 

Existing 

BART 

Improvement 

Existing 

BART 

Improvement 

Max Impact 

(dv) 5.16 1.278 75% 4.479 0.998 78% 3.82 0.868 77% 6.359 1.563 75% 8.404 2.117 75%

98% Impact 

(dv) 1.138 0.227 80% 1.738 0.357 79% 0.915 0.177 81% 1.923 0.415 78% 1.017 0.205 80%

Days > 0.5 63 5 92% 138 6 96% 62 3 95% 125 14 89% 57 7 88%
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2. INTRODUCTION AND 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 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 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. 

KCP&L performed a BART applicability analysis for La Cygne Unit 1 and Unit 2 and determined the 

units are subject to BART. The details of the applicability determination can be found in Section 3. 

Subsequently, KCP&L performed an analysis to determine BART for each VAP for Unit 1 and Unit 

2. The VAPs emitted by La Cygne Unit 1 and 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 CMP] as sulfates [SO4], and organic condensable particulate matter [OR 

CMP] 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. 

2.1 PRESUMPTIVE LIMITS

EPA established presumptive limits in the BART guidelines for 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 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. The SO2 presumptive limit for both Unit 1 and Unit 2 is 0.15 

lb/MMBtu. 

Similarly for NOX, the guidelines state: 

“For coal-fired EGUs greater than 200 MW located at greater than 750 MW power 

plants and operating without post-combustion controls (i.e. selective catalytic 

reduction or selective non-catalytic reduction), we have provided presumptive NOX

limits differentiated by boiler design and type of coal burned.” 

The guidelines go on to state for cyclone boilers: 

“Because of the relatively high NOX emission rates of cyclone units, SCR is more 

cost-effective than the use of current combustion control technology for these units. 

The use of SCRs at cyclone units burning bituminous coal, sub-bituminous coal, and 

lignite should enable the units to cost-effectively meet NOX rates of 0.10 lbs/MMBtu. 
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BART Analysis 

As a result, we are establishing a presumptive NOX limit of 0.10 lb/MMBtu based on 

the use of SCR for coal-fired cyclone units greater than 200 MW located at 750 MW 

power plants. 

Therefore, for units greater than 200 MW located at power plants greater than 750 MW, the 

presumptive limits are also a floor for NOX. Since La Cygne Unit 1 is a cyclone boiler, the 

presumptive limit is 0.10 lb/MMBtu. For La Cygne Unit 2, which is a dry-bottom wall-fired boiler 

combusting sub-bituminous coal, the NOX presumptive limit is 0.23 lb/MMBtu. 

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

2.2 EXISTING CONTROLS

La Cygne Unit 1 and Unit 2 have existing emission controls. Unit 1 is currently equipped with a 

scrubber for SO2 and particulate control and overfire air that minimizes the formation of thermal 

NOX. KCPL is in the process of voluntarily constructing an SCR system for Unit 1 which will further 

reduce NOX emissions. The SCR project is scheduled to be operational by May 2007. Unit 2 is 

equipped with an electrostatic precipitator (ESP) for particulate control. 
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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 deciviews 

(dv) when compared against a natural background. KCP&L conducted air quality modeling to predict 

the existing visibility impairment attributable to La Cygne Unit 1 and Unit 2 in the following Class I

areas: 

Wichita Mountains Wilderness (Fish and Wildlife Service [FWS]) 

Hercules Glades Wilderness (Forest Service [FS]) 

Upper Buffalo Wilderness (FS) 

Caney Creek Wilderness (FS) 

Mingo Wilderness (FWS) 

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

of Health and Environment (KDHE) in a November 2006 modeling protocol. In response to 

comments provided to KCP&L by KDHE regarding the modeling protocol, the only change made to 

the modeling methods and procedures documented in the protocol was to correct a typographical 

error for the November monthly humidity factor for Mingo from 3.4 to the correct value of 3.1. 

Since this change did not warrant a new version of the protocol, the documentation of this change is 

provided in this report. 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. HIGHEST ACTUAL 24-HOUR SO2 AND NOX EMISSIONS AND CALCULATED HIGHEST 

PM10 EMISSIONS (AS AN HOURLY EQUIVALENT) 

 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) 

La Cygne - Unit 1 6,151.15 11,589.52 53.79 34.37 4.92 5.68 8.59 0.22 

La Cygne - Unit 2 8,316.15 3,543.47 94.92 28.12 33.20 25.58 7.03 0.98 

Table 3-2 summarizes the stack parameters that were used to model La Cygne Unit 1 and Unit 2. It 

should be noted that the good engineering practice (GEP) stack heights were modeled instead of the 

actual stack heights since the GEP stack heights are less than the actual stack heights. 
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TABLE 3-2. SUMMARY OF STACK PARAMETERS

 La Cygne Unit 1 La Cygne Unit 2 

Latitude (degrees) 38.3486 38.3476 

Longitude (degrees) -94.6456 -94.6456 

Actual Stack height (ft) 700 700 

GEP Stack height (ft) 591.2 597.8 

Stack Diameter (ft) 23 24 

Exhaust Velocity (ft/s) 92.7 100.8 

Exhaust Temperature (F) 127 281 

The results of the modeling indicate that the 98th percentile of the visibility impacts attributable to 

La Cygne Unit 1 and Unit 2 are greater than 0.5 dv when compared against a natural background. 

Since the visibility impacts are greater than 0.5 dv, La Cygne Unit 1 and Unit 2 are subject to 

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

TABLE 3-3. SUMMARY OF 98TH PERCENTILE VISIBILITY IMPACTS AND NUMBER OF DAYS WITH 

VISIBILITY IMPACT GREATER THAN 0.5 DV

 Visibility Impairment 

Class I Area 

98th % 

dv

Days > 0.5 

dv

Wichita Mountains Wilderness 1.02 57 

Hercules Glades Wilderness 1.74 138 

Caney Creek Wilderness 1.14 63 

Upper Buffalo Wilderness 1.92 125 

Mingo Wilderness 0.92 62 

Table 3-4 provides a breakdown of the visibility impacts listed in Table 3-3 by each VAP. 

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

 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

Class I Area (%) (%) (%) (%) (%) (%) (dv) 

Wichita Mountains Wilderness 82.89 17.02 0.05 0.01 0.01 0.03 1.017 

Hercules Glades Wilderness 19.63 79.99 0.20 0.04 0.04 0.10 1.738 

Caney Creek Wilderness 24.32 75.46 0.12 0.02 0.02 0.06 1.138 

Upper Buffalo Wilderness 20.20 79.53 0.15 0.03 0.02 0.07 1.923 

Mingo Wilderness 42.26 57.61 0.07 0.01 0.00 0.03 0.915 

As shown in Table 3-4, 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 Unit 1 and 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 Unit 
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BART Analysis 

1 and 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 much smaller (<1%) 

than the contribution from SO2 and NOX. 
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BART Analysis 

4. SO2 BART EVALUATION

SO2 emissions at coal-fired EGUs are the result of the oxidation of the sulfur compounds in the coal 

during the combustion process. 

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

 Maximum 24-

Hour Heat 

Input 

SO2

Emission 

Rate 

SO2

Emission 

Rate 

 (MMBtu/24hr) (lb/hr) (lb/MMBtu)

La Cygne - Unit 1 223,488 6,151.15 0.66 

La Cygne - Unit 2 198,911 8,316.15 1.00 

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 BART analyses, 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. 

TABLE 4-2. AVAILABLE SO2 CONTROL TECHNOLOGIES

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 also 

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. 
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BART Analysis 

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 

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 La Cygne 

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 La Cygne 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.3 This 

control is a technically feasible option for the control of SO2 from La Cygne 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 

 

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 Module 6: Air Pollutants and Control Techniques 
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BART Analysis 

control is a technically feasible option for the control of SO2 from La Cygne Unit 1 and 

Unit 2. 

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. 

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

TECHNOLOGIES

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% 

As seen in Table 4-3, dry sorbent injection has the lowest estimated control efficiency and will 

therefore no longer be considered for BART. 

It should be noted that Unit 1 has an existing scrubber for SO2 control; however, the current control 

efficiency of the scrubber is below the efficiencies for the FGD controls listed in Table 4-3. 

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 cost of compliance was evaluated for the two technologies with the highest SO2

control efficiencies: wet scrubbers and SDA systems. The typical annual cost effectiveness 

for both wet scrubbers and SDA systems is $200 to $500 per ton of SO2 removed at the 

highest removal efficiencies. The cost effectiveness was estimated from a published cost 

in a technical paper.4 This cost estimate is considered to be study grade, which is +/- 30 

percent accuracy. 

 

4 "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. 
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BART Analysis 

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. Based on EPA’s guidelines as to 

what is considered cost effective for SO2 removal and the annual cost effectiveness of $200 

to $500 published in the technical paper, wet scrubbers and SDA systems are cost 

effective. 

4.4.2 ENERGY IMPACTS AND NON-AIR QUALITY IMPACTS

FGD systems require electricity to operate the blowers and pumps needed for the operation 

of the scrubbers. The generation of the electricity will most likely involve fuel 

combustion, which will cause emissions. While the required electricity will result in 

emissions, the emissions should be small compared to the reduction in SO2 that would be 

gained by operating an FGD system. 

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. 

Disposal of material from dry FGD systems is also required and will result in landfill 

impacts. 

4.4.3 REMAINING USEFUL LIFE

The remaining useful life of Unit 1 and Unit 2 do 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 

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

rates when compared to the presumptive BART emission rates. The existing and presumptive BART 

emission rates were modeled using CALPUFF. The existing emission rates are the same rates that 

were modeled for the BART applicability analysis. The BART rates are the presumptive limits (in 

lb/MMBtu) multiplied by the historical maximum daily heat inputs. A sample calculation of the SO2

presumptive BART hourly equivalent emission rate for Unit 1 is provided as follows: 

hr

day P HI

24

* * = 1,396.8 lb/hr 

Where: 

P (Presumptive BART Emission Rate) = 0.15 lb/MMBtu 

HI (2002-2004 maximum daily heat input) = 223,488 MMBtu/day 
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The existing and presumptive BART emission rates are summarized in Table 4-4. 

TABLE 4-4. EXISTING AND PRESUMPTIVE BART EMISSION RATES

 Existing Emission Rate Presumptive BART Emission Rate 

 SO2 NOX PM10 SO2 NOX PM10

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

La Cygne - Unit 1 6,151.15 11,589.52 53.79 1,396.80 931.20 53.79 

La Cygne - Unit 2 8,316.15 3,543.47 94.92 1,243.19 1,906.23 94.92 

The visibility improvement due to the presumptive BART limits was calculated as the difference 

between the existing visibility impairment and the visibility impairment for the presumptive rates. A

comparison of the existing visibility impacts and the visibility impacts based on the presumptive 

BART emission rates, 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 dv, for 

each Class I area is provided in Table 4-5. It should be noted that the visibility impacts presented in 

Table 4-5 are based on the application of the presumptive BART limits for both SO2 and NOx. The 

analysis included the presumptive BART limits from both SO2 and NOX in order to determine the 

overall visibility improvement that would be gained from applying BART to both pollutants. The 

presumptive BART limits for NOX are discussed in Section 5. 

TABLE 4-5.MODELED IMPACTS BASED ON EXISTING AND PRESUMPTIVE BART EMISSION RATES

 

Caney Creek 

Wilderness 

Hercules Glades 

Wilderness 

Mingo Wilderness Upper Buffalo 

Wilderness 

Wichita Mountains 

Wilderness 

 

Existing 

BART 

Improvement 

Existing 

BART 

Improvement 

Existing 

BART 

Improvement 

Existing 

BART 

Improvement 

Existing 

BART 

Improvement 

Max Impact 

(dv) 5.16 1.28 75% 4.48 1.00 78% 3.82 0.87 77% 6.36 1.56 75% 8.40 2.12 75%

98% Impact 

(dv) 1.14 0.23 80% 1.74 0.36 79% 0.92 0.18 81% 1.92 0.42 78% 1.02 0.21 80%

Days > 0.5 63 5 92% 138 6 96% 62 3 95% 125 14 89% 57 7 88%

As seen in Table 4-5, the visibility impacts (the maximum visibility impact, 98th percentile visibility 

impact, and the number of days with a visibility impact greater than 0.5 dv) for each Class I area are 

lower for the presumptive BART emission rates than for the existing emission rates. 

4.6 PROPOSED BART FOR SO2

KCP&L has determined that the SO2 BART emission rate for Unit 1 and Unit 2 is the presumptive 

emission rate of 0.15 lb/MMBtu. KCP&L is proposing to meet the presumptive BART SO2 emission 

rate of 0.15 lb/MMBtu for each unit by complying with a combined Unit 1 and Unit 2 weighted 

average limit. KCP&L will meet this limit by installing scrubbing technology (i.e., either wet 

scrubber or SDA). Wet scrubbers and SDA systems achieve the highest levels of SO2 control. In 

addition, the costs of compliance associated with both controls are similar, so no cost effectiveness is 
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BART Analysis 

gained by choosing one control over the other. KCP&L will select one of these control options at a 

later date pending several factors, including anticipated performance, availability, and market 

conditions. Performance, availability, and market conditions at the time of the BART implementation 

may drive the selection of the control option. At that time, a more detailed study may determine that

one control is more favorable than the other. 
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BART Analysis 

5. NOX BART EVALUATION

NOx from coal-fired EGUs is formed by three fundamentally different mechanisms. The principle 

NOx formation mechanism, thermal NOx, arises from the thermal dissociation and subsequent 

reaction of nitrogen (N2) and oxygen (O2) molecules in the combustion air. Most thermal NOx forms 

in the highest temperature regions of the combustion chamber (i.e., the air/fuel interface). The second 

NOx formation mechanism, prompt NOx, arises from early reactions of nitrogen intermediaries and 

hydrocarbon radicals in the fuel. The final NOx formation mechanism, fuel NOx, arises from the 

evolution and reaction of fuel bound nitrogen compounds with oxygen. 

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

 

Maximum 24-

Hour Heat 

Input 

NOX

Emission 

Rate 

NOX

Emission 

Rate 

 (MMBtu/24hr) (lb/hr) (lb/MMBtu)

La Cygne - Unit 1 223,488 11,589.52 1.24 

La Cygne - Unit 2 198,911 3,543.47 0.43 

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

The available retrofit NOX control technologies are summarized in Table 5-2. 

TABLE 5-2. AVAILABLE NOX CONTROL TECHNOLOGIES 

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 
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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. 

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 La Cygne 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 KCP&L currently uses OFA on La Cygne Unit 1, and this is a 

technically feasible option for the control of NOX from La Cygne 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 

 

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 
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BART Analysis 

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. 

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. 

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 

LNBs and ULNBs 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 Since La Cygne Unit 1 is a cyclone boiler, LNBs and ULNBs are not 

technically feasible for the control of NOx from this boiler. LNBs and ULNBs 

are technically feasible for the control of NOx from La Cygne Unit 2. 

5.2.2 POST COMBUSTION CONTROLS

NOX can be reduced to molecular nitrogen (N2) in add-on systems located downstream of 

the furnace. The two main post-combustion control techniques in commercial service are 

SCR and SNCR. 

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
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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 4N2 + 6H2O 

2NO2 + 4NH3 + O2 3N2 + 6H2O 

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

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

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

ammonia injection rate, and the type of catalyst. The 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 La Cygne 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 La Cygne 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. 

 

10 Ibid. 

11 Interim White Paper “Source Category: Electric Generating Units” Midwest RPO Candidate Control Measures, 

December 9, 2005. 
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TABLE 5-3. CONTROL EFFECTIVENESS OF TECHNICALLY FEASIBLE NOX CONTROL 

TECHNOLOGIES

Control Technology 

Estimated Control 

Efficiency 

(%) 

SCR ~70-90 

OFA/LNB* ~30-60 

LNB* ~25-50 

FGR ~30-50 

SNCR ~25-50 

OFA ~25-55 

*LNBs are technically feasible for La Cygne Unit 

2 only, they are not technically feasible for La 

Cygne Unit 1. 

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

Control Costs

The capital costs, operating costs, and cost effectiveness for combustion controls and SCR 

were estimated for La Cygne Unit 2 using an EPA cost estimate method outlined in the 

document Nitrogen Oxides (NOX), Why and How They Are Controlled.

12 These control 

options were selected because they provide the highest levels of control and are commonly 

used for NOX control in large utility boilers. For the purposes of this analysis, LNB with 

OFA was used to represent a combustion controls system capable of achieving a NOX

emission rate of 0.23 lb/MMBtu. 

The EPA cost method relies on cost factors for capital costs, annual fixed operating and 

maintenance costs, and annual variable operating and maintenance costs for each of the 

control technologies. A summary of the cost factors is provided in Table 5-4. 

 

12 Nitrogen Oxides (NOX), Why and How They Are Controlled. EPA 456/F-99-006R, November 1999. 
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TABLE 5-4. NOX CONTROL TECHNOLOGY COST FACTORS* 

Control Technology 

Capacity 

(MW) 

Capital 

Cost 

($/kW) 

Fixed 

O&M 

($/kW/yr) 

Variable 

O&M 

(mils/kWh) 

Capital Cost 

($) 

Annualized 

Capital 

Cost** 

 ($/yr) 

Annual Fixed 

O&M Cost 

($/yr) 

Annual 

Variable 

O&M Cost 

($/yr) 

Total 

Annual 

Cost 

($/yr) 

Combustion Controls System§ 750 22.8 0.35 0.07 17,100,000 2,008,566 262,500 459,900 2,730,966 SCR 750 69.7 6.12 0.24 52,275,000 6,140,222 4,590,000 1,576,800 12,307,022

*These cost factors are in 1997 dollars. Table 5-5 shows the capital costs, annual fixed O&M costs, and annual variable O&M costs in 2005 dollars. 

**The annualized cost is based on a recovery period of 20 years, assuming 10% interest. The capital recovery factor (CRF) of 0.11746 was obtained from EPA's Air Pollution Control Cost Manual, 

Sixth Edition. EPA 452/B-02-001, January 2002. 

§For the purposes of this analysis, the cost of a combustion control system is represented by a LNB w/OFA system capable of achieving a NOX emission rate of 0.23 lb/MMBtu. As KCP&L is 

proposing not to commit to specific combustion controls at this time, KCP&L is using LNB w/ OFA to represent combustion control equipment that can achieve a NOX rate of 0.23 lb/MMBtu. 
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These cost estimates are considered to be study grade, which is +/- 30 percent accuracy. It 

is likely that these costs are low, since the costs may not reflect the current high market 

price for steel and other increased costs associated with high demand. 

KCP&L is in the process of constructing an SCR system on La Cygne Unit 1. Since SCR 

provides the highest level of control there is no need to evaluate the cost for other controls. 

Construction on the SCR system is scheduled to be operational in May 2007. 

Annual Tons Reduced

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

controls on La Cygne Unit 2 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 the controlled NOX emission 

rates for each control method in lb/MMBtu. These emission rates were multiplied by the 

maximum 365-day rolling heat input as determined from CEMS data from 2002-2004. 

A sample of the controlled annual emission rate is provided below for combustion controls 

with a controlled emission rate of 0.23 lb/MMBtu: 

.0 23lb / MMBtu × 63,507,314MMBtu / yr ÷ ,2 000lb / ton =7,303 tpy 

Cost Effectiveness

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. The cost 

effectiveness for a combustion controls system (represented by LNB with OFA) and SCR 

were determined by dividing the total annualized cost by the annual tons reduced. The 

control technology costs are summarized for Unit 2 in Table 5-5. 

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. 

Table 5-5 indicates that the cost effectiveness of a combustion controls system (represented 

by LNB with OFA) for La Cygne Unit 2 is less than $1,500 per ton of NOX removed; 

however, the cost for SCR is over $1500 per ton of NOX removed, which is greater than 

EPA’s cost estimate for advanced combustion controls. 
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TABLE 5-5. NOX CONTROL TECHNOLOGY COST SUMMARY (IN 2005 DOLLARS) FOR LA CYGNE UNIT 2 

Current 

Annual 

Emission 

Rate 

Estimated Controlled 

Emission Rate 

Annual 

Emissions 

Reduced 

Capital 

Cost 

Annualized 

Fixed 

O&M 

Annualized 

Variable 

O&M 

Total 

Annualized 

Cost* 

Cost 

Effectiveness

 (tpy) (lb/MMBtu) (tpy) (ton/yr) ($) ($/yr) ($/yr) ($/yr) ($/ton) Combustion Controls System** 10,669 0.23 7,303 3,365 20,714,670 317,988 557,116 3,308,249 983 SCR 10,669 0.10 3,175 7,493 63,325,110 5,560,254 1,910,111 14,908,532 1,990 

*The costs are annualized in 2005 dollars. ** For the purposes of this analysis, the cost of a combustion control system is represented by a LNB w/OFA system capable of achieving a NOX emission rate of 0.23 lb/MMBtu. 
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5.4.2 ENERGY IMPACTS & NON-AIR IMPACTS

SCR systems require electricity to operate the blowers and pumps needed to operate the 

systems. The generation of the electricity will most likely involve fuel combustion, which 

will cause emissions. While the required electricity will result in the emissions, the 

emissions should be small compared to the reduction in NOx that would be gained by 

operating an SCR system 

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 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 FEASIBLE NOX CONTROLS IMPACT ON VISIBILITY 

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

rates when compared to the presumptive BART emission rates. The existing and presumptive BART 

emission levels were modeled using CALPUFF. The existing emission rates are the same rates that 

were modeled for the BART applicability analysis. The BART rates are the presumptive limits (in 

lb/MMBtu) multiplied by the historical maximum daily heat inputs. The existing and BART 

emission rates are summarized in Table 5-6. 

TABLE 5-6. EXISTING AND PRESUMPTIVE BART EMISSION RATES

 Existing Emission Rate Presumptive BART Emission Rate 

 SO2 NOX PM10 SO2 NOX PM10

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

La Cygne - Unit 1 6,151.15 11,589.52 53.79 1,396.80 931.20 53.79 

La Cygne - Unit 2 8,316.15 3,543.47 94.92 1,243.19 1,906.23 94.92 
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The visibility improvement due to the presumptive BART limits was calculated as the difference 

between the existing visibility impairment and the visibility impairment for the presumptive rates. A

comparison of the existing visibility impacts and the visibility impacts based on the presumptive 

BART emission rates, including the maximum modeled visibility impact, 98th percentile modeled 

visibility impact, and the modeled number of days with a modeled visibility impact greater than 0.5 

dv, for each Class I area is provided in Table 5-7. It should be noted that the visibility impacts 

presented in Table 5-7 are based on the application of the presumptive BART limits for both SO2 and 

NOx. The analysis included the presumptive BART limits from both SO2 and NOX in order to 

determine the overall visibility improvement that would be gained from applying BART to both 

pollutants. The presumptive BART limits for SO2 are discussed in Section 4. 

TABLE 5-7.MODELED IMPACTS BASED ON EXISTING AND PRESUMPTIVE BART EMISSION RATES

Caney Creek 

Wilderness 

Hercules Glades 

Wilderness 

Mingo Wilderness Upper Buffalo 

Wilderness 

Wichita Mountains 

Wilderness 

 

Existing 

BART 

Improvement 

Existing 

BART 

Improvement 

Existing 

BART 

Improvement 

Existing 

BART 

Improvement 

Existing 

BART 

Improvement 

Max Impact 

(dv) 5.16 1.28 75% 4.48 1.00 78% 3.82 0.87 77% 6.36 1.56 75% 8.40 2.12 75%

98% Impact 

(dv) 1.14 0.23 80% 1.74 0.36 79% 0.92 0.18 81% 1.92 0.42 78% 1.02 0.21 80%

Days > 0.5 63 5 92% 138 6 96% 62 3 95% 125 14 89% 57 7 88%

As seen in Table 5-6, the visibility impacts (the maximum visibility impact, 98th percentile visibility 

impact, and the number of days with a visibility impact greater than 0.5 dv) for each Class I area are 

lower for the presumptive BART emission rates than for the existing emission rates. 

5.6 PROPOSED BART FOR NOX 

KCP&L has determined that the NOX BART emission rates are the presumptive emission rates of 

0.10 lb/MMBtu and 0.23 lb/MMBtu for Unit 1 and Unit 2, respectively. The presumptive NOX limit 

of 0.10 lb/MMBtu for cyclone units is based on the use of SCR and the NOX limit of 0.23 lb/MMBtu 

is based on combustion controls. Therefore, KCP&L proposes that the currently permitted SCR is 

equivalent to BART controls for Unit 1 and that combustion controls, such as LNB or LNB and OFA, 

or post-combustion controls, such as an SCR, are equivalent to BART controls for Unit 2. 

Although KCP&L proposes that combustion controls are equivalent to BART for Unit 2, KCP&L 

proposes to install an SCR for Unit 2 and further study the installation of combustion controls on Unit 

2. KCP&L will further study combustion control options at a later date pending several factors, 

including other regulatory requirements, availability, and market conditions. The concerns 

surrounding these factors are described below. 

La Cygne Generating Station is located just south of the Kansas City metropolitan area. Based on 

ozone monitoring data for the past several ozone seasons, KCP&L anticipates that the Kansas City 

metropolitan area may soon implement regulatory requirements to reduce volatile organic compound 

(VOC) and NOX emissions in the area in order to avoid designation as a nonattainment area for the 
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BART Analysis 

ozone National Ambient Air Quality Standard (NAAQS). Controls at La Cygne Generating Station 

have already been proposed as part of the Kansas City Ozone Maintenance Plan, which has been 

submitted and approved by EPA. This may require KCP&L to install NOX controls sooner than the 

BART deadline for controls implementation. The extent of NOX reductions and the exact timeline for 

implementation that would be required are unknown at this time. KCP&L would like to retain the 

flexibility to choose a control option based on upcoming ozone standard regulatory requirements that 

may require additional NOX controls prior to the BART deadline. 

Lastly, market conditions and vendor availability at the time of the BART implementation may drive 

the selection of combustion control options. At that time, a more detailed study analysis may 

determine that one combustion control is more favorable than the other. 

 

Additional details on the proposed compliance demonstration methods are provided in Section 7. 
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6. PM BART EVALUATION

The primary source of PM from 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, 

sulfates, and sulfuric acid mist. 

The maximum daily PM10 emission rates that were modeled for the BART applicability determination 

are summarized in Table 6-1. 

TABLE 6-1. HISTORICAL MAXIMUM 24-HOUR PM10 EMISSION RATE

 Maximum 24-

Hour Heat 

Input 

PM10

Emission 

Rate 

PM10

Emission 

Rate 

 (MMBtu/24hr) (lb/hr) (lb/MMBtu)

La Cygne - Unit 1 223,488 53.79 0.006 

La Cygne - Unit 2 198,911 94.92 0.011 

From Table 6-1 it can be seen that the current PM10 emission rates for Unit 1 and Unit 2 are much less

than the current emission rates of SO2 and NOX. The low PM10 emission rates correspond to very low 

visibility impacts attributable to PM10 when compared to the impacts attributable to SO2 and NOX, as 

shown in Table 6-2. 

TABLE 6-2. VISIBILITY IMPAIRMENT CONTRIBUTIONS

Year Visibility 

Impairment 

Attributable to 

SO4

1

Visibility 

Impairment 

Attributable to 

NO3

2

Visibility 

Impairment 

Attributable to 

PM10

2

 (%) (%) (%) 

Wichita Mountains 82.89 17.02 0.10 

Hercules Glades 19.63 79.99 0.38 

Caney Creek 24.32 75.46 0.22 

Upper Buffalo 20.20 79.53 0.27 

Mingo Wildlife 42.26 57.61 0.11 

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).

Given the small PM10 emission rates compared to SO2 and NOX and the small contribution of PM10 to 

the visibility impacts, any additional control technology would provide little visibility improvement 

and require significant capital expenditures. Therefore, additional control technologies would not be

cost effective, and are not required as PM control technologies for BART compliance. Although not 
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required for BART compliance, KCP&L plans to install a baghouse on Unit 1 and Unit 2 for 

compliance with other environmental regulations. 
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7. PROPOSED BART LIMITS COMPLIANCE SUMMARY

7.1 SO2 BART COMPLIANCE SUMMARY

Based on the SO2 BART analysis, KCP&L has determined that the BART limit for SO2 for Unit 1 and 

Unit 2 is the presumptive emission limit of 0.15 lb/MMBtu. Per the BART guidelines, states may 

allow sources to “average” emissions across any set of BART-eligible emission units within a 

fenceline, so long as the emission reductions from each pollutant being controlled for BART would 

be equal to those reductions that would be obtained by simply controlling each of the BART-eligible 

units that constitute a BART-eligible source. The weighted average of the BART limits for Unit 1 

and Unit 2 is 0.15 lbs/MMBtu. 

Even though the weighted average of the presumptive BART limits for Unit 1 and Unit 2 is 0.15 

lb/MMBtu, KCP&L proposes to demonstrate compliance with a limit that is more stringent than this 

limit. Specifically, KCP&L proposes a weighted average limit of 0.10 lb/MMBtu on a 30-day rolling 

average for Unit 1 and Unit 2. The proposed weighted average emission limit is below the 

presumptive BART emission rates which will result in reductions of the visibility impacts attributable

to La Cygne Unit 1 and Unit 2 in excess of those indicated in Sections 4 and 5. 

KCP&L proposes to demonstrate compliance with the Unit 1 and Unit 2 weighted average emission 

limit of 0.10 lbs/MMBtu using the existing CEMS with a new 30-day rolling average report. The 

CEMS software will be configured to generate a two unit weighted average. The daily average SO2

rate for each unit will be the average of the hourly SO2 rates for each hour of a particular boiler 

operating day, excluding periods of start-up and shut-down. A boiler operating day will be any day 

that the unit combusts fuel for any period of time, excluding periods of start-up and shut-down. 

The two-unit daily average will be calculated using the following equation: 

((SO2Day#1 x HIsum-day#1) + (SO2Day#2 x HIsum-day#2)) 

_____________________________________ 

(HIsum-day#1 + HIsum-day#2) 

 Where: 

 SO2day#1 = Daily average of hourly SO2 rates for Unit 1 

 SO2 day#2 = Daily average of hourly SO2 rates for Unit 2 

 HIsum-day#1 = Summation of hourly heat inputs for the day for Unit 1 

 HIsum-day#2 = Summation of hourly heat inputs for the day for Unit 2 

The 30-day rolling average will be the simple average of the last 30 days of two-unit daily averages 

and will be in compliance if it is less than 0.10 lbs/MMBtu, excluding periods of start-up and shutdown. 

Periods of start-up and shut-down for Unit 1 and Unit 2 will be based on good industry practice or the

manufacturer's recommendations. 
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7.2 NOX BART COMPLIANCE SUMMARY

Based on the NOX BART analysis, KCP&L has determined that the BART limits for NOX are the 

presumptive emission limits of 0.10 lb/MMBtu and 0.23 lb/MMBtu for Unit 1 and Unit 2, 

respectively. Per the BART guidelines, states may allow sources to “average” emissions across any 

set of BART-eligible emission units within a fenceline, so long as the emission reductions from each 

pollutant being controlled for BART would be equal to those reductions that would be obtained by 

simply controlling each of the BART-eligible units that constitute a BART-eligible source. The 

weighted average of the presumptive BART limits for Unit 1 and Unit 2 is 0.16 lbs/MMBtu. The 

Unit 1 + Unit 2 weighted average emission limit has been calculated as follows: 



=

×

2

2

1

i

im

i

ip im

HI

R HI

Where 

Rip = Presumptive BART emission rate for unit i (lb/MMBtu) 

HIim = Maximum daily heat input from 2002-2004 (MMBtu/day) for unit i 

The detailed calculation of the weighted presumptive emission limit is shown below. 

( ) ( )

( ) =

+

× + ×

m m

p m p m

HI HI

R HI R HI

1 2

1 1 2 2

0.16 lb/MMBtu 

Where: 

R1p = Presumptive BART emission rate for Unit 1 (lb/MMBtu) = 0.10 lb/MMBtu 

HI1m = Maximum daily heat input from 2002-2004 (MMBtu/day) for Unit 1 = 

223,488 MMBtu/day 

R2p = Presumptive BART emission rate for Unit 2 (lb/MMBtu) = 0.23 lb/MMBtu 

HI2m = Maximum daily heat input from 2002-2004 (MMBtu/day) for Unit 2 = 

198,911 MMBtu/day 

Even though the weighted average of the presumptive BART limits for Unit 1 and Unit 2 is 0.16 

lb/MMBtu, KCP&L proposes to demonstrate compliance with a limit that is more stringent than this 

limit. Specifically, KCP&L proposes a weighted average limit of 0.13 lb/MMBtu on a 30-day rolling 

average for Unit 1 and Unit 2. The proposed weighted average emission limit is below the 

presumptive BART emission rates which will result in reductions of the visibility impacts attributable

to La Cygne Unit 1 and Unit 2 in excess of those indicated in Sections 4 and 5. 

KCP&L proposes to demonstrate compliance with the Unit 1 and Unit 2 weighted average emission 

limit of 0.13 lbs/MMBtu using the existing CEMS with a new 30-day rolling average report. The 

CEMS software will be configured to generate a two unit weighted average. The daily average NOX

rate for each unit will be the average of the hourly NOX rates for each hour of a particular boiler 
Kansas City Power & Light 7-3 Trinity Consultants 

BART Analysis 

operating day, excluding periods of start-up and shut-down. A boiler operating day will be any day 

that the unit combusts fuel for any period of time, excluding periods of start-up and shut-down. 

The two-unit daily average will be calculated using the following equation: 

((NOXDay#1 x HIsum-day#1) + (NOXDay#2 x HIsum-day#2)) 

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(HIsum-day#1 + HIsum-day#2) 

 Where: 

 NOXday#1 = Daily average of hourly NOX rates for Unit 1 

 NOX day#2 = Daily average of hourly NOX rates for Unit 2 

 HIsum-day#1 = Summation of hourly heat inputs for the day for Unit 1 

 HIsum-day#2 = Summation of hourly heat inputs for the day for Unit 2 

The 30-day rolling average will be the simple average of the last 30 days of two-unit daily averages 

and will be in compliance if it is less than 0.13 lbs/MMBtu, excluding periods of start-up and shutdown. 

In the event of an extraordinary situation involving an extended outage of Unit 2 (duration in excess 

of 10 weeks) KCP&L will submit a plan to KDHE to achieve compliance with a La Cygne Unit 1 

NOX presumptive limit of 0.10 lbs/MMBtu on a 30-day rolling average excluding periods of start-up 

and shut-down. The 10-week period is intended to cover all anticipated scheduled outages so that 

this scenario would only come up in the case of a unit retirement or a catastrophic loss of one unit. 

Periods of start-up and shut-down for Unit 1 and Unit 2 will be based on good industry practice or the

manufacturer's recommendations. 

7.3 PM10 BART COMPLIANCE SUMMARY

KCP&L proposes that no additional PM controls are required for BART compliance. Although not 

required for BART compliance, KCP&L plans to install a baghouse on Unit 1 and Unit 2 for 

compliance with other environmental regulations. 

KCP&L proposes to demonstrate compliance with the La Cygne Unit 1 and Unit 2 average emission 

limit of 0.015 lbs/MMBtu for PM10 (filterable) and 0.024 lbs/MMBtu for PM10 (total) by conducting 

annual stack tests. Compliance is demonstrated if the weighted average stack test results of the two 

units combined meets the emission limits. Annual stack test results will be the average of three onehour stack tests for each unit.