## BART F IVE 

## F ACTOR 

## A NALYSIS



## F LINT 

## C REEK 

## P OWER 

## P LANT



## G ENTRY



## , A RKANSAS 

## (AFIN 04

- 00107)

Prepared By:

T RINITY 

### C ONSULTANTS



### , I NC



### . 120 East Sheridan, Suite 205

Oklahoma City, Oklahoma 73104

(405) 228

- 3292

T RINITY 

### C ONSULTANTS



### , I NC



### . 977 Ridge Drive, Suite 380

Lenexa, Kansas 66219

(913) 894

- 4500

In conjunction with:

A MERICAN 

### E LECTRIC 

### P OWER 

### S ERVICE 

### C ORPORATION



### PO Box 660164

Dallas, Texas 72566

(214) 777

- 1113

for the

S OUTHWESTERN 

### E LECTRIC 

### P OWER 

### C OMPANY



### F LINT 

### C REEK 

### P OWER 

### P LANT



### 21797 SWEPCO Plant Road

Gentry, A rkansas 72734

Trinity Project No. 113701.0022

September 2012

Version 1

### Southwestern Electric Power Company i Trinity Consultants

BART Analysis

– Flint Creek 

## T ABLE OF 

## C ONTENTS



### 1. E XECUTIVE 

### S UMMARY



### ................................ ................................ ........................ 1

- 1

2. I NTRODUCTION AND 

### B ACKGROUND



### ................................ ................................ .... 2

- 1

3. M OD ELING 

### M ETHODOLOGIES AND 

### P ROCEDURES



### ................................ ............. 3

- 1

3.1 CALMET AND 

### CALPUFF

................................ ................................ ................... 3

- 1

3.2 CALPOST

................................ ................................ ................................ ............ 3

- 1

4. E XISTING 

### E MISSIONS AND 

### V ISIBILITY 

### I MPAIRMENT



### ................................ ......... 4

- 1

4. 1 NO X 

### , SO 2 

### , AND 

### PM 10 

### B ASELINE 

### E MISSION 

### R ATES



### ................................ ............... 4

- 1

4.2 B ASELINE 

### V ISIBILITY 

### I MPAIRMENT



### ................................ ................................ ....... 4

- 1

5. SO 2 

### BART E VALUATION



### ................................ ................................ .................... 5

- 1

5.1 I DENTIFICATION OF 

### A VAILABLE 

### R ETROFIT 

### SO 2 

### C ONTRO L 

### T ECHNOLOGIES



### .......... 5

- 1

5.2 E LIMINATE 

### T ECHNICALLY 

### I NFEASIBLE 

### SO 2 

### C ONTROL 

### T ECHNOLOGIES



### ................ 5

- 1

5.2.1 D RY 

### S ORBENT 

### I NJECTION



### ................................ ................................ ................... 5

- 1

5.2.2 S PRAY 

### D RY 

### A BSORBER



### ................................ ................................ ....................... 5

- 2

5.2.3 W ET 

### S CRUBBER



### ................................ ................................ ................................ .. 5

- 2

5.2.4 C IRCULATING 

### D RY 

### S CRUBBER 

### (CDS)

................................ ................................ 5

- 2



### 5.3 R ANK OF 

### T ECHNICALLY 

### F EASIBLE 

### SO 2 

### C ONTROL 

### O PTIONS BY 

### E FFECTIVENESS



### .. 5

- 3

5.4 E VALUATION OF 

### I MPACTS FOR 

### F EASIBLE 

### SO 2 

### C ONTROLS



### ................................ ..... 5

- 3

5.4.1 C OST OF 

### C OMPLIANCE



### ................................ ................................ ........................ 5

- 4

5.4.2 E NERGY 

### I MPACTS AND 

### N ON



### - A IR 

### Q UALITY 

### I MPACTS



### ................................ ......... 5

- 6

5.4.3 R EMAINING 

### U SEFUL 

### L IFE



### ................................ ................................ ................... 5

- 6



### 5.5 E VALUATION OF 

### V ISIBILITY 

### I MPACT OF 

### F EASIBLE 

### SO 2 

### C ONTROLS



### ...................... 5

- 6

5.6 P ROPOSED 

### B ART FOR 

### SO 2



### ................................ ................................ ..................... 5

- 9

5.6.1 C OMPARATIVE 

### SO 2 

### BART D ETERMINATIONS



### ................................ ................... 5

- 9



### 6. NO X 

### BA RT E VALUATION



### ................................ ................................ ................... 6

- 1

6.1 C ROSS



### - S TATE 

### A IR 

### P OLLUTION 

### R ULE



### , ................................ ................................ ... 6

- 1

C LEAN 

### A IR 

### I NTERSTATE 

### R ULE



### , AND 

### BART

................................ ................................ ...... 6

- 1

6.2 I DENTIFICATION OF 

### A VAILABLE 

### R ETROFIT 

### NO X 

### C ONTROL 

### T ECHNOLOGIES



### ......... 6

- 2

6.3 E LIMINATE 

### T ECHNICALLY 

### I NFEASIBLE 

### NO X 

### C ONTROL 

### T ECHNOLOGIES



### ............... 6

- 2

6.3.1 C OMBUSTION 

### C ONTROLS



### ................................ ................................ .................... 6

- 3

6.3.1.1 Flue Gas Recirculation (FGR)

................................ ............................. 6

- 3

6.3.1.2 Overfire Air (OFA)

................................ ................................ .............. 6

- 3

6.3.1.3 Low NO X 

### Burners

................................ ................................ ................ 6

- 3

6.3.2 P OST 

### C OM BUSTION 

### C ONTROLS



### ................................ ................................ .......... 6

- 4

6.3.2.1 Selective Catalytic Reduction

................................ .............................. 6

- 4

6.3.2.2 Selective Non

- Catalytic Reduction

................................ ...................... 6

- 4



### 6.4 R ANK OF 

### T ECHNICALLY FEASIBLE 

### NO X 

### C ONTROL 

### O PTIONS BY 

### E FFECTIVENESS



### .. 6

- 5

### Southwestern Electric Power Company ii Trinity Consultants

BART Analysis

– Flint Creek 

### 6.5 E VALUATION OF 

### I MPACTS FOR 

### F EASIBLE 

### NO X 

### C ONTROLS



### ................................ ... 6

- 5

6.5.1 C OST OF 

### C OMPLIANCE



### ................................ ................................ ........................ 6

- 6

6.5.2 E NERGY 

### I MPACTS 

### & N ON



### - A IR 

### I MPACTS



### ................................ .......................... 6

- 10

6.5.3 R EMAINING 

### U SEFUL 

### L IFE



### ................................ ................................ ................. 6

- 10



### 6.6 E VALUATION OF 

### V ISIBILITY 

### I MPACT OF 

### F EASIBL E 

### NO X 

### C ONTROLS



### ................... 6

- 10

6.7 P ROPOSED 

### B ART FOR 

### NO X



### ................................ ................................ .................. 6

- 1 3

7. PM 10 

### BART E VALUATION



### ................................ ................................ .................. 7

- 1

A PPENDIX 

### A

................................ ................................ ................................ ................................ .

A PPENDIX 

### B

................................ ................................ ................................ ................................ .

A PPENDIX 

### C

................................ ................................ ................................ ................................ .

### Southwestern Electric Power Company iii Trinity Consultants

BART Analysis

– Flint Creek 

## L IST OF 

## T ABLES

T ABLE 

### 1

- 1. E XISTING 

### V ISIBILITY 

### I MPAIRMENT 

### A TTRIBUTABLE TO 

### SN

- 01 (2001

- 2003)

................... 1

- 1

T ABLE 

### 3

- 1. A NNUAL 

### A VERAGE 

### B ACKGROUND 

### C ONCENTRATION



### ................................ ..................... 3

- 2

T ABLE 

### 3

- 2. F L 

### (RH) L ARGE 

### RH A DJUSTMENT 

### F ACTORS



### ................................ ................................ ..... 3

- 3

T ABLE 

### 3

- 3. F S 

### (RH) S MALL 

### RH A DJUSTMENT 

### F ACTORS



### ................................ ................................ ..... 3

- 3

T ABLE 

### 3

- 4. F SS 

### (RH) S EA 

### S ALT 

### RH A DJUSTMENT 

### F ACTORS



### ................................ ............................... 3

- 3

T ABLE 

### 4

- 1. B ASELINE 

### M AXIMUM 

### 24

- HOUR 

### SO 2 

### , NO X 

### , AND 

### PM 10 

### E MISSION RATES 

### ( AS 

### H OURLY



### E QUIVALENTS 

### )

................................ ................................ ................................ ....................... 4

- 1

T ABLE 

### 4

- 2. B ASELINE 

### V ISIBILITY 

### I MPAIRMENT 

### A TTRIBUTABLE TO 

### SN

- 01 B OILER 

### (2001

- 2003)

..... 4

- 2

TABLE 

### 5

- 1. A VAILABLE 

### SO 2 

### C ONTROL 

### T ECHNOLOGIES FOR 

### SN

- 01

................................ .................. 5

- 1

T ABLE 

### 5

- 2. C ONTROL 

### E FFECTIVENESS OF 

### T ECHNICALLY 

### F EASIBLE 

### SO 2 

### C ONTROL 

### T ECHNOLOGIES 

### 5

- 3

T ABLE 

### 5

- 3. S UMMARY OF 

### C OST 

### E FFECT IVENESS FOR 

### SN

- 01 SO 2 

### C ONTROLS OF 

### D RY 

### S CRUBBING



### (NID)

................................ ................................ ................................ ................................ ...... 5

- 5

T ABLE 

### 5

- 4. D OLLAR PER 

### D ECIVIEW 

### C OST 

### E FFECTIVENESS FOR 

### SN

- 01 SO 2 

### C ONTROLS OF 

### D RY



### S CRUBBING 

### (NID)

................................ ................................ ................................ .................. 5

- 5

T ABLE 

### 5

- 5. S UMMARY OF 

### E MISSION 

### R ATES 

### M ODELED TO 

### R EFLECT 

### D RY 

### S CRUBBER FOR 

### SO 2



### C ONTROL



### ................................ ................................ ................................ ................................ 5

- 7

T ABLE 

### 5

- 6. S UMMARY OF 

### M ODELED 

### I MPACTS FROM 

### SO 2 

### C ONTROL 

### V ISIBILITY 

### I MPACT 

### A NALYSIS

FOR 

### SN

- 0 1 (2001

- 2003)

................................ ................................ ................................ ......... 5

- 8

T ABLE 

### 6

- 1. A VAILABLE 

### NO X 

### C ONTROL 

### T ECHNOLOGIES FOR 

### SN

- 01

................................ ................ 6

- 2

T ABLE 

### 6

- 2. C ONTROL 

### E FFECTIVENESS OF 

### T ECHNICALLY 

### F EASIBLE 

### NO X 

### C ONTROL 

### T ECHNOLOGIES 

### 6

- 5

TABLE 

### 6

- 3. S UMMARY OF 

### C OST 

### E FFECTIVENESS FOR 

### SN

- 01 NO X 

### C ONTROLS



### ................................ ... 6

- 8

TABLE 

### 6

- 4. D OLLAR PER 

### D ECIVIEW 

### C OST 

### E FFECTIVENESS FOR 

### SN

- 01 NO

X 

### C ONTROL 

### U SING



### LNB/OFA

................................ ................................ ................................ ............................... 6

- 8

TABLE 

### 6

- 5. D OLLAR PER 

### D ECIVIEW 

### C OST 

### E FFECTIVENESS FOR 

### SN

- 01 NO

X 

### C ONTROL 

### U SING



### LNB/OFA P LUS 

### SNCR

................................ ................................ ................................ .......... 6

- 9

TABLE 

### 6

- 6. D OLLAR PER 

### D ECIVIEW 

### C OST 

### E FFECTIVENESS FOR 

### SN

- 01 NO

X 

### C ONTROL 

### U SING 

### SCR

.. 6

- 9

### Southwestern Electric Power Company iv Trinity Consultants

BART Analysis

– Flint Creek T ABLE 

### 6

- 7. S UMMARY OF 

### E MISSION 

### R ATES 

### M ODELED TO 

### R EFLECT 

### LNB/OFA FOR 

### NO X 

### C ONTROL 

### 6

- 11

T ABLE 

### 6

- 8. S UMM ARY OF 

### E MISSION 

### R ATES 

### M ODELED TO 

### R EFLECT 

### SCR FOR 

### NO X 

### C ONTROL



### ....... 6

- 11

T ABLE 

### 6

- 9. S UMMARY OF 

### E MISSION 

### R ATES 

### M ODELED TO 

### R EFLECT 

### LNB/OFA + SNCR FOR 

### NO X



### C ONTROL



### ................................ ................................ ................................ .............................. 6

- 11

T ABLE 

### 6

- 10. S UMMARY OF 

### V ISIBILITY 

### I MP ROVEMENT 

### A SSOCIATED WITH 

### NO

X 

### C ONTROL 

### S YSTEM ON



### SN

- 01 (2001

- 2003)

................................ ................................ ................................ ............... 6

- 12

### Southwestern Electric Power Company 1

- 1 Trinity Consultants

BART Analysis

– Flint Creek 

## 1. E XECUTIVE 

## S UMMARY

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

Southwestern Electric Power Company’s (SWE P CO ’s ) 1 

### electric generating unit at the Flint Creek

P ower P lant ( SN

- 01 )

. SN

- 01 is a dry bottom wall

- fired boiler with a nominal design maximum heat

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

western co al

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

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

burners.

Based on modeling performed for this analysis, c umulative emissi ons of nitrogen oxides (NO

x 

### ), sulfur

dioxide (SO 2 

### ), and particulate matter with a mean diameter smaller than ten microns (PM 10 

### ) from SN

01 are predicted to cause or contribute an increase of greater than 0.5 deciviews (∆dv) of visibility

impairment in f

our Class I Areas: Caney Creek Wilderness (CACR), Upper Buffalo Wilderness

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

A summary of the existing visibility impairment attri butable to SN

- 01 based on the default natural

conditio ns is provided in Table 1

- 1. T he visibility impairment summarize d in Table 1

- 1 is based on

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

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

T ABLE 

### 1

- 1. E XISTING 

### V ISIBILITY 

### I MPAIRMENT 

### A TTRIBUTABLE TO 

### SN

- 01 (2001

- 2003)

Caney Creek

Wilderness Upper Buffalo

Wilderness Hercules

Glades

Wilderness Mingo

Wilderness

98th

%

∆dv Days

> 0.5

∆dv 98th

%

∆dv Days >

0.5

∆dv 98th

%

∆dv Days

> 0.5

∆dv 98th

%

∆dv Days

> 0.5

∆dv

AEP Flint Creek SN

- 01 0.993 55 1.066 76 0.734 60 0.653 24



### Trinity used the EPA’s BART guidelines in 40 CFR Part 51 2 

### and other recent EPA guidance to

determine BART for SN

- 01

. Trinity conducted a five

- step analysis to determine BART that included

the following:

1. 

### Identif

ying all available retrofit control technologies;

2. 

### Eliminat ing technically infeasible control technologies;

3. 

### Evaluat ing the control effectiveness of remaining control technologies;

4. 

### Evaluating impacts and do cument the results ;

5. 

### Evaluating visibility impacts

.

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

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

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

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

report.

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

6 , 2005.

### Southwestern Electric Power Company 1

- 2 Trinity Consultants

BART Analysis

– Flint Creek Based on the five

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

▲ 

### SO 2 

### – The BART analysis concluded that the installation of a spray dry absorber and

baghouse (e.g. Novel Integrated Deacidifica tion System [ NIDS ] technology ) constitute s

BART. The proposed BART emission rate for SO 2 

### is 0.06 lb/MMBtu calculated as a 30

- day

rolling average over each boiler operating day.

▲ 

### NOx

– EPA recently issued a final rule allowing states that are subject to t he Cross

- State Air

Pollution Rule (CSAPR) trading program for seasonal NO

x 

### to rely on the reductions achieved

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

subject to BART. 3 

### Subsequently, CSAPR was vacated, and t he Clean Air Interstate Rule

(CAIR) remains in effect until an acceptable replacement rule is promulgated

. 4 

### If CSAPR is

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

haze obligations at SN

- 01. If CSAPR is vacated a nd CAIR remains in effect, EPA’s prior

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

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

seasonal CAIR program to satisfy its NOx obliga tions under BART

. 5



### In the alternative, SWEPCO has evaluated the cost

- effectiveness of candidate BART controls

at SN

- 01. The visibility improvements associated with the addition of NOx controls at SN

- 01

are minimal, and the cost

- effectiveness values for all control options exceed the values

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

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

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

with the addition of newer generation LNB/OFA systems, and are proposed as BART for SN

01. If ADEQ determines that SWEPCO cannot rely on CAIR or CSAPR as an alternative to

BART, the proposed BART emission r ate for NOx at SN

- 01 is 0.23 lb/ MM Btu calculated as

a 30

- day rolling average over each boiler operating day based on the application of

LNB/OFA controls.

▲ 

### PM 10 

### - A BART determination for PM 10 

### at SN

- 01 was approved in EPA’s March 12, 2012

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

3 “Regional Haze: Revisions to Provisions Governing Alternatives to Source

- Specific Best Available Technology

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

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

., EPA . Case

No. 11

- 1302 (and consolidated cases)

, Opinion ( D.C. Cir Aug. 21, 2012 ).

5 “Regional Haze Regulations and Best Available Retrofit Technology (BART) Guidelines, 70 Fed. Reg. 3 9104,

39143 (July 6, 2005).

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

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

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

### Southwestern Electric Power Company 2

- 1 Trinity Consultants

BART Analysis

– Flint Creek 

## 2. I NTRODUCTION AND 

## B ACKGROUND

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

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

remedying any existing

, man

- made visibility impairment. On July 1, 1999, the U.S. EPA published

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

conditions in 156 specific areas across th e U nited States known as Class I areas. The CAA 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.

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

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

amendments to its 1999 RHR, often called the Best Ava ilable 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 ye ar 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 anticipat ed 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 98 th 

### percentile

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

natural background 7 

### . 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 determinat ion 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 redu ction 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 environm ental 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 reasonabl

y be anticipated to result from the use of such techn ology.

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

statutory factors:

1. 

### Existing controls

2. 

### Cost of controls

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

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

### Southwestern Electric Power Company 2

- 2 Trinity Consultants

BART Analysis

– Flint Creek 3. 

### Energy and non

- air quality environmental impacts

4. 

### Remaining useful life of the source

5. 

### Degree of vis ibility improvement as a result of controls

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

follows:

1. 

### Identify all available retrofit control technologies;

2. 

### Eliminate technically infeasible control technolo gies;

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 step s listed above for each VAP.

SN

- 01 meet s the three BART

- eligibility criteria described above , and the existing visibility

impairment attributable to SN

- 01 is greater than 0.5 dv in at least one Class I area. Thu s, SN

- 01 is

subject to BART. The details o f the SN

- 01 existing/baseline emissions and the contribution of the

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

- 01 include

NO

x 

### , SO 2 

### , and PM 10 

### of various forms (filterable coarse particulate matter [PM

c 

### ], filterable fine

particle matter [PM f



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

sulfates [SO 4 

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

organic aerosols [SOA]). The BART determinations fo r SO 2 

### , NO

x 

### , and PM 10 

### can be found in

Sections 5

, 6 , and 7 , respectively.

### Southwestern Electric P ower Company 3

- 1 Trinity Consultants

BART Analysis

– Flint Creek 

## 3. M ODELING 

## M ETHODOLOGIES AND 

## P ROCEDURES

This section summari z es the dispersion modeling methodologies and procedures applied in this

BART analysis

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

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

CALPOST post

- processing program.

CALPUFF is a multi

- layer, multi

- species, non

- steady

- state puff dispersion model, which can simulate

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

and removal. CALPUFF uses three

- dimensional meteorological fields developed by the CALMET

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

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

determined by user

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

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

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

on pollutant specific concentrations predicted by CALPU FF.



## 3.1 CALMET AND 

## CALPUFF

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

the Central States Regional Air Planning Association (CENRAP)

. The CALMET data and

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

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

visibility impairment for several BART

- eligible sources located in Oklahoma as part of the BART

analyses for these source s

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

generated in accordance with the protocol in their BART analyses.



## 3.2 CALPOST

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

guidance from the Federal Land M anagers Air Quality Related Values Workgroup (FLA G)

. Th e

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

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

V isibility impairment is quantified using the light extinction coefficient ( b

ext 

### ), which is expressed in

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

T he i mpact of a source is determined by comparing the HI attributable to a source relative to

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

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

equation:

### Southwestern Electric P ower Company 3

- 2 Trinity Consultants

BART Analysis

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

equation for predicting light extinction as part of the 20 10 FLAG guidance ( often referred to as the

new IMPROVE equation ). The new IMPROVE equation i s as follows :

Visibility impairment predictions for SN

- 01 relied upon in this BART analysis used the equation

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

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

approach for addressing the growth of hygrosc opic particles due to moisture in the atmosphere

.

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

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

the old IM PROVE equation in the CENRAP BART modeling protocol.

CALPOST Method 8 , Mode 5 requires the following:

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

salt

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

 Rayleigh scattering parameter corrected for site

- specific elevation

Tables 3

- 1 to Table 3

- 4 below show the values for the data described above that were input to

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

guidance.

T ABLE 

### 3

- 1. A NNUAL 

### A VERAGE 

### B ACKGROUND 

### C ONCENTRATION

Class I Area (NH 4 ) 2 SO 4 NH 4 NO 3 OM EC Soil CM Sea Salt Rayleigh

(Mm - 1 )

Caney Creek Wilderness 0.23 0.1 1.8 0.02 0.5 3 0.03 11

Upper Buffalo Wilderness 0.23 0.1 1.8 0. 02 0.5 3 0.03 11

Hercules Glades Wilderness 0.23 0.1 1.8 0.02 0.5 3 0.02 11

Mingo Wilderness 0.23 0.1 1.83 0.02 0.51 3.05 0.04 12

### Southwestern Electric P ower Company 3

- 3 Trinity Consultants

BART Analysis

– Flint Creek

T ABLE 

### 3

- 2

. F L 

### (RH) L ARGE 

### RH A DJUSTMENT 

### F ACTORS

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

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

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

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

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



### T ABLE 

### 3

- 3

. F S 

### (RH) S MALL 

### RH A DJUSTMENT 

### F ACTORS

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

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

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

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

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



### T ABLE 

### 3

- 4

. F SS 

### (RH) S EA 

### S ALT 

### RH A DJUSTMENT 

### F ACTORS

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

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

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

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

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

### Southwestern Electric P ower Company 4

- 1 Trinity Consultants

BART Analysis

– Flint Creek 

## 4. E XISTING 

## E MISSIONS AND 

## V ISIBILITY 

## I MPAIRMENT

This section summarizes t he existing (i.e. baseline) visibility impairment attributable to SN

- 01 based

on air quality modeling conducted by Trinity.



## 4.1 NO X 

## , SO 2 

## , AND 

## PM 10 

## B ASELINE 

## E MISSION 

## R ATES

Table 4

- 1 summa ri zes the emission rates that were modeled for SO 2 

### , NO

x 

### , and PM 10 

### , inclu ding the

speciated PM 10 

### emissions. The SO 2 

### and NO

x 

### emission rates are the highest actual 24

- hour emission

rates based on 200 1

- 200 3 continuous emissions monitoring system (CEMS) data. The PM 10 

### emission

rate is based on the lb/MMBtu level for total PM 10 

### as dete rmined from the March 2006 stack test data

multiplied by the maximum 24

- hour rolling average heat input to the boiler from 2001

- 2003 (6,093

MMBtu/hr). The emission rates for the PM 10 

### species reflect the breakdown of the PM 10 

### determined

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

Pulverized Coal using only ESP 8 

### . More specifically, the NPS workbook shows the following

baseline distribution for the PM species:

▲ 

### Coarse PM (PM C 

### ) = 15.5 %

▲ 

### Fine soil (modeled as PM F 

### ) = 11.9 %

▲ 

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

▲ 

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

▲ 

### Inorganic condensable PM (modeled as SO 4 

### ) = 57.7 %

T ABLE 

### 4

- 1

. B ASELINE 

### M AXIMUM 

### 24

- HOUR 

### SO 2 

### , NO X 

### , AND 

### PM 10 

### E MISSION RATES 

### ( AS 

### H OURLY



### E QUIVALENTS 

### )

S O 2 9 

### NO

x 10 Total

PM 10 SO 4 PM

c PM f SOA EC

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

SN

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



## 4.2 B ASELINE 

## V ISIBILITY 

## I MPAIRMENT

Trinity conducted modeling to determine the visibility imp airment attributable to SN

- 01 in four Class

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

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

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

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

determination: total PM 10 emission rate of 192.5 lb/hr, heat value of 8,500 Btu/lb, sulfur content of 1%, ash content of

6.6%.

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

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

### Southwestern Electric P ower Company 4

- 2 Trinity Consultants

BART Analysis

– Flint Creek Table 4

- 2 provides a summary of the modeled visibility im pairment attributable to SN

- 01 at CACR,

UPBU, HERC, and MING based on the emission rates shown in Table 4

- 1

. Note that all of the

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

submitted with this document

.

T ABLE 

### 4

- 2

. B ASELINE 

### V ISIBILITY 

### I MP AIRMENT 

### A TTRIBUTABLE TO 

### SN

- 01 B OILER 

### (2001

- 2003)

Year Maximum

(Δdv) 98th Percentile

(Δdv) No. of Day with

Δdv ≥ 0.5 98th Percentile

% SO 4 98th Percentile

% NO 3 98th Percentile

% PM 10 98th

Percentile

% NO 2

Caney Creek Wilderness

2001 1.372 0.668 21 65.91 31.75 0.92 1.41

2002 1.247 0.734 14 84.92 14.45 0.63 0

2003 1.408 0.993 20 71.86 27.26 0.74 0.15

Upper Buffalo Wilderness

2001 1.914 1.034 27 56.82 41.44 1.05 0.69

2002 2.585 1.066 21 47.31 50. 9 0.87 0.93

2003 1.439 0.745 28 48.94 48.56 1.5 1.01

Hercules Glades Wilderness

2001 1.462 0.73 24 47.31 50.69 1.19 0.81

2002 1.439 0.734 19 86.99 7.39 2.06 3.56

2003 2.186 0.705 17 82.93 16.21 0.72 0.13

Mingo Wilderness

2001 1.37 0.653 13 91.3 8. 29 0.4 0.01

2002 0.883 0.444 7 59.98 38.83 0.94 0.24

2003 1.553 0.409 4 66.63 32.96 0.38 0.04

### Southwestern Electric P ower Company 5

- 1 Trinity Consultants

BART Analysis

– Flint Creek 

## 5. SO 2 

## BART E VALUATION



## 5.1 I DENTIFICATION OF 

## A VAILABLE 

## R ETROFIT 

## SO 2 

## C ONTROL



## T ECHNOLOGIES

Sulfur oxides, SO

x 

### , are generated during coal combustion from the oxidatio n of sulfur contained in

the fuel. SO

x 

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

generally not affected by boiler size or burner design. SO

x 

### emission s from conventional combustion

systems are predominantly in the fo rm of SO 2 

### . Since SO 2 

### is the predomina n t sulfu r compound emitted

from SN

- 01 , the BART a nalysis is specific to emissions of SO 2



### .

Step 1 of the top

- down control review is to identify available retrofit control options for SO 2 

### . The

available SO 2 

### retrofit con trol technologies for SN

- 01 are summarized in Table 5

- 1 . The retrofit

controls examined are limited to add

- on controls that eliminate SO 2 

### after it is formed

, as SN

- 01

currently uses a lower sulfur fuel and would not achieve significant additional reductio ns through

alternative fuel supplies.

TABLE 

### 5

- 1

. A VAILABLE 

### SO 2 

### C ONTROL 

### T ECHNOLOGIES FOR 

### SN

- 01

SO 2 Control Technologies

Wet Scrubber

Spray Dry Absorber (SDA or NID)

Circulating Dry Scrubber

Dry Sorbent Injection



## 5.2 E LIMINATE 

## T ECHNICALLY 

## I NFEASIBLE 

## SO 2 

## C ONTROL 

## T ECHNOLOGIES

Step 2 of the BART determination is to eliminate technically infeasible SO 2 

### control technologies that

were identified in Step 1.



### 5.2.1 D RY 

### S ORBENT 

### I NJECTION



### Dry sorbent injection involves the injection of a sorbent into the exhaust gas st ream where

SO 2 

### reacts with and becomes entrained in the sorbent

. The stream is then passed through a

particulate controls device to remove the sorbent and entrained SO 2



### . The process was

developed as a lower cost F lue G as D esulfurization (FGD) option beca use the mixing of

the SO 2 

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

Depending on the residence time

, gas stream temperature, and limitations of the particulate

control device, sorbent injection control efficiency c an range between 40 and 60 percent

. 11



### This control is a technically feasible option for the control of SO 2 

### from SN

- 01

.

11 "Assessment of Control Technology Options for BART

- Eligible Sources: Steam Electric Boilers, Industrial

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

March 2 005

.

### Southwestern Electric P ower Company 5

- 2 Trinity Consultants

BART Analysis

– Flint Creek 

### 5.2.2 S PRAY 

### D RY 

### A BSORBER



### S pray dry absorber system s (SDA) involve spray ing a fine mist of lime slurry into an

absorption tower where the SO 2 

### i s absorbed by the slurry drop lets. The absorption of the

SO 2 

### 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 dro plets reach the bottom of the tower. This leads to the formation of a dry

powder which is carried out with the gas and collected with a fabric filter.

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

absorber . Hydrat ed lime is added to recirculated dust in the mixer of the system. The

solids are sprayed with a thin layer of water in the mixer before being transported to the

reactor. The amount of water added is only a few percent which means that the dust

remains dr y. Compared to a traditional SDA system, the amount of water is the same but

the amount of solid compounds is larger. Hydrated lime react s with SO 2 

### in the NID

reactor such that SO 2 

### is bound to the hydrated lime. Then the flue gas toge ther with the

dry d ust material enters the fabric filter where dust is collected. After the fabric filter, the

cleaned flue gas leaves the NID system through the fabric filter plenus. Dust material

enters the trough through the hopper. Most of the solid material is recirc ulated to the mixer

by a rotary feeder with variable speed and is reused in the system. The system has a high

recirculation ratio of the dry dust material

Existing SDA control efficiencies range from 60 to 95 percent. 12 

### This is a technically

feasible option for the control of SO 2 

### from SN

- 01.



### 5.2.3 W ET 

### S CRUBBER



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

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

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

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

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

ab sorpti on, the SO 2 

### in the gas stream reacts with the lime or limestone slurry to form

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

- 95

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

- 01

. 13 

### This

contr ol is a technically feasible option for the control of SO 2 

### from SN

- 01.



### 5.2.4 C IRCULATING 

### D RY 

### S CRUBBER 

### (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 ex haust is mixed with water,

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

- solid mixing

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

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

13 Ibid.

### Southwestern Electric P ower Company 5

- 3 Trinity Consultants

BART Analysis

– Flint Creek

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

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

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

. A large

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

lime utilization. The control efficiency of a CDS is less than that of an SDA 14 

### . This

control is a technically feasible option for the control of SO 2 

### from SN

- 01.



## 5.3 R ANK OF 

## T ECHNICALLY 

## F EASIBLE 

## SO 2 

## C ONTROL 

## O PTIONS BY



## E FFECTIVENESS

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

effectiveness in reducing the VAP . Table 5

- 2 provides a ranking of the control levels for the controls

listed in the previous section for SN

- 01.

T ABLE 

### 5

- 2

. C ONTROL 

### E FFECTIVENESS OF 

### T ECHNICALLY 

### F EASIB LE 

### S O 2 

### C ONTROL



### T ECHNOLOGIES

Control Technology Estimated Control

Efficiency

Wet Scrubber 95%

SDA ( NID ) 95%

Circulating Dry Scrubber

(CDS) 75%

Dry Sorbent Injection 6 0%



## 5.4 E VALUATION OF 

## I MPACTS FOR 

## F EASIBLE 

## SO 2 

## C ONTROLS

A show n in Table 5

- 2 , w et scrubbing and SDA (NID) can both achieve 95% reduction in SO 2 

### on

lower sulfur coals, and t hese technologies are the most effective technologies at reducing SO 2



### . Step

four of the BART analysis procedure is the impact analysis. This ana lysis is typically conducted to

demonstrate that a control technology that is more effective than another technology does not

constitute BART. The BART determination guidelines list the four factors to be considered in the

impact analysis:

▲ 

### Cost of compli ance

▲ 

### Energy impacts

▲ 

### Non

- air quality impacts; and

▲ 

### The remaining useful life of the source

AEP is proposing th at the NID technology constitutes BART. The proposed BART emission rate

for the NIDS technology is 0.06 lb/MMBtu on a 30

- day rolling average

.

S ince AEP is proposing to use one of the two most effective control technologies for reducing

emissions of SO 2 

### as BART, it is not necessary to conduct an evaluation of impacts under Step s 4 and

5 of the BART evaluation. For informational purposes, AEP is p roviding Step 4 and Step 5

14 Babcock and Wilcox sales materials.

### Southwestern Electric P ower Company 5

- 4 Trinity Consultants

BART Analysis

– Flint Creek evaluation s specific to the NID technology

. Also, AEP is providing a discussion of energy and non

air quality impacts of wet scrubbing versus the NID technology.



### 5.4.1 C OST OF 

### C OMPLIANCE



### Control Costs

The capital and operating costs o f SDA used in the cost effectiveness calculations were

calculated based on vendor estimates and published calculations methods. The EPA Air

Pollution Control Cost Manual was followed to the extent possible and was supplemented

with vendor and site

- specifi c information where available. The capital costs were

annualized over a 15

- year period and then added to the annual operating costs to obtain the

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

in Appendix A o f this report.

Annual Tons Reduced

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

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

annual emission rate. The baseline annual em ission rate is the average rate from 2001

-

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

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

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

was determined from CAMD 2001

- 2003 average daily heat inputs at Flint Creek times an

estimated 7752 hours per year, the average number of operating hours from 2001

- 2003.

Cost Effectiveness

The cost effectiveness in dollars per ton of SO 2 

### reduced was determined by dividing the

annualized cost of control by the annual tons reduced. Table 5

- 3 indicates that the cost

effectiveness of the NID technology at a n S O 2 

### rate of 0. 06 lb/MMBtu is approximately

$ 4

, 288 per ton of S O 2 

### removed. The cost effectiveness in dollars per deciview of visibility

improvement attributable to the scrubber was also determined. The cost of the dry

scrubber averages over $21.5 million/dv across the Class I areas, as seen in Tabl e 5

- 4

.

### Southwestern Electric Power Company 5

- 5 Trinity Consultants

BART Analysis

– Flint Creek

T ABLE 

### 5

- 3

. S UMMARY OF 

### C OST 

### E FFECTIVENESS FOR 

### SN

- 01 SO 2 

### C ONTROLS OF 

### D RY 

### S CRUBBING 

### (NID)

T ABLE 

### 5

- 4

. D OLLAR PER 

### D ECIVIEW 

### C OST 

### E FFECTIVENESS FOR 

### SN

- 01 SO 2 

### C ONTROLS OF 

### D RY 

### S CRUBBING 

### ( NID)

### Southwestern Electric Power Company 5

- 6 Trinity Consult ants

BART Analysis

– Flint Creek 

### 5.4.2 E NERGY 

### I MPACTS AND 

### N ON



### - A IR 

### Q UALITY 

### I MPACTS



### Wet scrubbi ng is expected to achieve approximately the same level of control of SO 2 

### emissions as the proposed NID technology. However, t he negative non

- air quality

environmental impacts are greater with wet scrubbing systems . Such impacts includ e a

potential increa se in particulate and s ulfuric a cid m ist emissions . In addition, wet

scrubbers require increased water use and generate large volume s of wastewater and solid

waste/sludge that must be treated. This places additional burdens on the wastewater

treatment an d solid waste management capabilities

. Moreover, i f wet scrubbing produces

calcium sulfite sludge, the sludge will be water

- laden, and it must be stabilized be for e

landfilling. Wet scrubbing systems have increased power requirements and increased

reagent usage over dry scrubb ers

. Thus , from an overall environmental perspective, dry

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

.



### 5.4.3 R EMAINING 

### U SEFUL 

### L IFE



### The remaining useful life of SN

- 01 does not impact the annualized capital costs becaus e

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

period, which is 15 years from EPA cost estimates

.



## 5.5 E VALUATION OF 

## V ISIBILITY 

## I MPACT OF 

## F EASIBLE 

## SO 2 

## C ONTROLS

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

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

BART emission rate

. Section 4 of this report documents the existing visibility impairment

attributable to SN

- 01. In order to assess the visibility improvement associated with NID , the

controlled SO 2 

### emission rate was modeled using CALPUFF. The SO 2 

### emission rate associated with

the NID for SN

- 01 is detailed as follows:

= 379.44 lb/hr

Wh ere:

P ( controlled emission level ) = 0. 06 lb/MMBtu

HI (hourly heat input) = 6

, 324 MMBtu/hr

Table 5

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

control at Flint Creek. The SO 2 

### rate was developed the control led rate of 0.06 lb/MMBtu and the

boiler heat input of 6

, 324 MMBtu/hr. The SO 4 

### emission rate was determined assuming the reduction

in SO 4 

### is proportional to the reduction in SO 2 

### from the baseline case to the controlled case. The NID

will have co

- effects on some of the acid gases. The control of H 2 

### SO 4 

### will result in fewer sulfates.

The NO

x 

### emission rate was modeled at the baseline rate. The NID involves the use of a baghouse.

The change from the current ESP to baghouse will result in changes in PM spec iation. All other rates

that changed from the baseline case were determined using the National Parks Services (NPS)

speciation spreadsheets for dry bottom boilers burning pulverized coal using only fabric filter for

emissions control.

### Southwestern Electric Power Company 5

- 7 Trinity Consult ants

BART Analysis

– Flint Creek T ABLE 

### 5

- 5

. S UMMAR Y OF 

### E MISSION 

### R ATES 

### M ODELED TO 

### R EFLECT 

### D RY 

### S CRUBBER FOR 

### SO 2



### C ONTROL

SO 2 (lb/hr) SO 4

(lb/hr) 

### NO

x

(lb/hr) PM C

(lb/hr) PM F

(lb/hr) SOA

(lb/hr) EC

(lb/hr) PM 10, total

(lb/hr)

SN

- 01 379.4 8.9 1,945.0 0.8 0.8 2.2 0.0 12.7



### Comparisons of the existing visibil ity impacts and the visibility impacts based on the NID , including

the maximum modeled visibility impact, 98 th 

### percentile modeled visibility impact, and the number of

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

5

- 6

. The visibility improvement associated with th e dry scrubber is also shown in th e table; this value

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

im pairment for the dry scrubber as measured by the 98 th 

### percentile modeled visibility impact

.

### Southwestern Electric Power Company 5

- 8 Trinity Consultants

BART Analysis

– Flint Creek T ABLE 

### 5

- 6

. S UMMARY OF 

### M ODELED 

### I MPACTS FROM 

### SO 2 

### C ONTROL 

### V ISIBILITY 

### I MPACT 

### A NALYSIS FOR 

### SN

- 0 1 (2001

- 2003)

Caney Creek Wilderness Upper Buffalo Wilderness Herc ules Glades

Wilderness Mingo NWR

Maxi mum Impact (Δdv) 98% Impact (Δdv) # Days > 0.5 Δdv Visibility Improvement* Maximum Impact (Δdv) 98% Impact (Δdv) # Days > 0.5 Δdv Visibility Improvement* Maximum Impact (Δdv) 98% Impact (Δdv) # Days > 0.5 Δdv Visibility Improvement* Maximum Impact (Δdv)

98 % Impact (Δdv) # Days > 0.5 Δdv Visibility Improvement*

Existing Emission Rate 1.408 0.993 55

- 1.553 1.066 76

- 2.585 0.734 60

- 2.186 0.653 24

-

Dry Scrubber 0.749 0.346 6 65.2 % 1.469 0.497 1 2 53.4 % 0.878 0.311 5 57.6 % 0. 630 0. 216 18 66.9 %

*Improv ement is based on the 98 th percentile impact (Δdv) for the control scenario compared to the 98 th percentile impact (Δdv) baseline impact (Δdv)

†The visibility improvement shown in the table has been calculated from 98 th percentile baseline and controlled i mpacts that include more decimal places than

what is shown in the table. Due to rounding of the baseline and controlled 98 th percentile impacts shown in the table, the visibility improvement calculated from

the baseline and controlled 98 th percentile impa cts shown in the table may be slightly different than the visibility improvement reflected in the table.

### Southwestern Electric Power Company 5

- 9 Trinity Consultants

BART Analysis

– Flint Creek As shown in Table 5

- 6

, based on visibility predictions from the CALPUFF modeling system, the

operation of a dry scrubber on SN

- 01 will result in up t o a 65 percent improvement (depending on the

Class I area) to the existing visibility impairment attributable to this unit.



## 5.6 P ROPOSED 

## B ART FOR 

## SO 2



### SWEPCO is proposing that the SO 2 

### BART emission rate for SN

- 01 be 0. 06 lb/MMBtu

, based on the

installati on and operation of the NID technology

. AEP is proposing to meet this limit calculated as a

30

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

from the existing continuous emissions monitoring systems (CEMS)

.



### 5.6.1 C OMPARATIVE 

### SO 2 

### BART D ETERMINATIONS



### The BART emission rate proposed for SN

- 01 is among the most stringent BART emission rates for

SO 2 

### approved for any coal

- fired generating unit over the last two years. I n Oklahoma 15 

### EPA agreed

with the BART determi nation of 0.06 lb/MMBtu achieved through use of dry scrubbers for similar

boilers

. I n Nebraska 16 

### at the Gerald Gentleman Station, BART for SO 2 

### was also determined to be

0.06 lb/MMBtu achieved through use of dry scrubbers. These similar units provide a goo d

comparison of emission levels achievable through similar control technology. Rates lower than 0.06

lb/MMBtu have been considered, but rejected based on lack of operating experience on retrofit units,

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

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

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

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

emission rate for SN

- 01.

Other BART determinations have resulted in higher emission limitations. For example, in Alabama 17



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

injection or comparable technologies. In Arizona 18 

### , SO 2 

### BART was determined to be in the range of

0.08

– 0.15 lb/MMBtu from existing w et scrubber s. An EGU in Colorado 19 

### has a proposed BART

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

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

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

In other determinations

, such as Illinois 20 

### , the control technology was not stated in the BART

determination but the SO 2 

### rate determined to be BART was in the range of 0.11

– 0.23 lb/MMBtu,

dependent upon boiler type and averaging considerations . SO 2 

### BART in Kansas 21 

### was achieved

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

scrubbing with an emission limitation of 0.15 lb/MMBtu for another . A n EGU in Montana 22 

### similar

to AEP’s SN

- 01 has a BART em ission rate of 0.08 lb/MMBtu.

15 77 Fed. Reg. 16168 (March 22, 2011).

16 77 F ed. Reg. 40150 (July 6, 2012).

17 77 Fed. Reg. 11937 (Feb. 28, 2012).

18 77 Fed. Reg. 42834 (July 20, 2012).

19 77 Fed. Reg. 18052 (March 26, 2012).

20 77 Fed. Reg. 3966 (Jan. 26, 2012).

21 77 Fed. Reg. 52604 (Aug. 23, 2011).

22 77 Fed. Reg. 23988 (April 20, 201 2).

### Southwestern Electric Power Company 5

- 10 Trinity Consultants

BART Analysis

– Flint Creek The proposed SO 2 

### BART emission rate is equivalent to the most stringent rates previously approved

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

visibility improvement in the affected Class I areas. The SO 2 

### emission rate of 0.06 lb/MMBtu should

be adopted as BART for SN

- 01.

### Southwestern Electric Power Company 6

- 1 Trinity Consultants

BART Analysis

– Flint Creek 

## 6. N O X 

## BART E VALUATION



## 6.1 C ROSS



## - S TATE 

## A IR 

## P OLLUTION 

## R ULE



## ,

C LEAN 

## A IR 

## I NTERSTATE 

## R ULE



## , AND 

## BART

On June 7 , 2012 EPA published a final rule allowing states p articipating in the Cross

- State Air

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

states with units subject to CSAPR that will participate in a NO

x 

### trading program during the ozone

season. EPA commented that “ NO

x 

### control in the five ozone season

- only states is achieved

predominantly by combustion controls .” 23 

### Due to the nature of combustion controls, plants typically

keep combustion controls in place and running year

- round, even if emission limitations are sea sonal.

Although Arkansas is an ozone season

- only state, combustion controls would run anytime the unit is

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

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

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

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

Court

. 24 

### If CSAPR is upheld and implemented in Arkansas, SWEPCO proposes rely on CSAPR to

satisfy its regional haze obligations at SN

- 01.

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

progress toward the national visibility goal than application of BART for NOx emissions at BART

eligible sources. 25 

### Since EPA has made the determination that CAIR reductions provide better

progress than BART, and Arkansas has adopted the CAIR requirements into the Arkansas SIP, 26



### SWEP CO should be entitled to rely upon CAIR to satisfy its obligations for NOx reductions at SN

01, if CSAPR is vacated in accordance with the D. C. Circuit’s opinion.

In the alternative, SWEPCO has evaluated the cost

- effectiveness of candidate BART control s at SN

01. The visibility improvements associated with the addition of NOx controls at SN

- 01 are minimal,

and the cost

- effectiveness values for all control options exceed the values previously determined to be

reasonable in EPA’s presumptive BART analysi s. However, visibility improvements consistent with

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

Regional Haze SIP obligations can be achieved with the addition of newer generation LNB/OFA

systems, and ar e proposed as BART for SN

- 01. If ADEQ determines that SWEPCO cannot rely on

CAIR or CSAPR as an alternative to BART, the proposed BART emission rate for NOx at SN

- 01 is

0.23 lb/mmBtu calculated as a 30

- day rolling average over each boiler operating day ba sed on the

application of LNB/OFA controls.

23 “Regional Haze: Revisions to Provisions Governing Alternatives to Source

- Specific Best Available Retrofit

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

(June 7, 2012).

24 EME Homer C ity v. EPA, Case No. 11

- 1302 and consolidated cases, Opinion , (D.C. Cir. Aug. 21, 2012)

. 25 70 Fed. Reg. 39104, 39136

- 37, and 39143 (July 6, 2005).

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

### Southwestern Electric Power Company 6

- 2 Trinity Consultants

BART Analysis

– Flint Creek 

## 6.2 I DENTIFICATION OF 

## A VAILABLE 

## R ETROFIT 

## NO X 

## C ONTROL



## T ECHNOLOGIES

Nitrogen oxides, NO

x 

### , are produced during fuel combustion when nitrogen contained in both the fuel

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

combustion air) has led to the use of the terms “thermal” NO

x 

### and “fuel” NO

x 

### when describing NO

x 

### emissions. Thermal NO

x 

### emissions are produced when elemental nitrogen in the combustion air is

exposed to a hi gh temperature zone and oxidized. Fuel NO

x 

### emissions are created during the rapid

oxidation of nitrogen compounds contained in the fuel.

Nitrogen oxide (NO) is typically the predominant form of NO

x 

### from fossil fuel combustion. Nitrogen

dioxide (NO

2 

### ) m akes up the remainder of the NO

x 

### . The formation of NO

x 

### compounds in utility boilers

is sensitive to the method of firing. In a wall

- fired boiler, such as SN

- 01, burners are mounted in the

boiler walls, producing discrete flames in the furnace. In tangent ially

- fired boilers, a single rotating

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

wall

- fired boilers. Tangentially fired boilers typically have lower uncontrolled NO

x 

### emissions than

wall

- fired boilers. Therefore baseline NO

x 

### emission rates can vary significantly from plant to plant

due to method of firing and also several other factors.

Step 1 of the BART determination is the identification of all available retrofit NO

x 

### control

technologies. The available retrofit NO

x 

### control technologies are summarized in Table 6

- 1 for

SN

- 01.

NO

x 

### emissions controls, as listed in Table 6

- 1 , can be categorized as combustion or post

- combustion

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

NO

x 

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

minimizes NO

x 

### formation. Post

- combustion controls, such as selective catalytic reduction (SCR) and

selective non

- catalytic reductio n (SNCR) convert NO

x 

### in the flue gas to molecular nitrogen and

water.

T ABLE 

### 6

- 1

. A VAILABLE 

### NO X 

### C ONTROL 

### T ECHNOLOGIES FOR 

### SN

- 01

NO

x Control Technologies

Combustion Controls Flue Gas Recirculation (FGR)

Overfire Air (OFA)

Low 

### NO

x Burners (LNB)

Post

- Combustion Controls Selective Catalytic Reduction (SCR)

Selective Non

- Catalytic Reduction (SNCR)



## 6.3 E LIMINATE 

## T ECHNICALLY 

## I NFEASIBLE 

## NO X 

## C ONTROL 

## T ECHNOLOGIES

Step 2 of the BART determination is to eliminate technically infeasible NO

x 

### control technologies that

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

ranges and efficiencies. Because many controlled emissions rates from literature values were higher

than the baseline NO

x 

### rate at SN

- 01, vendor estima tes were also used to assist in developing the

expected emission rates from the known relationships between the control options.

### Southwestern Electric Power Company 6

- 3 Trinity Consultants

BART Analysis

– Flint Creek 

### 6.3.1 C OMBUSTION 

### C ONTROLS



### 6.3.1.1 F LUE 

### G AS 

### R ECIRCULATION 

### (FGR)

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

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

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

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

flue gas) in the burner

. The lower oxygen level in the combustion zone reduces

flame temperatures; which in turn reduces thermal NO

x 

### formation

. When

operated without additional controls, the NO

x 

### control range for coal fired

boilers with FGR is approximately 5

- 25% for coal fire d boilers, or 0.23

- 0.29

lb/MMBtu from SN

- 01

. 27 

### This control is a technically feasible option for the

control of NO

x 

### from SN

- 01.



### 6.3.1.2 O VERFIRE 

### A IR 

### (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 NO

x 

### by lowering

combustion temperature and limiting the availability of oxygen in the

combustion zone where NO

x 

### is most likely to be formed. OFA as a single NO

x 

### control technique results in estimated NO

x 

### emissions for coal fired boilers of

approximately 10%, or 0.28

- 0

. 29 lb/MMBtu from SN

- 01

. 28 

### This control is a

technically f

easible option for the control of NO

x 

### from SN

- 01

.



### 6.3.1.3 L OW 

### NO X 

### B URNERS



### LNB technology utilizes advanced burner design to reduce NO

x 

### formation

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

reduced residence time. NO

x 

### creation rates ty pically peak at oxygen levels of

five to seven percent. 29 

### LNB is a staged combustion process that is designed to

split fuel combustion into two zones. In the primary zone, NO

x 

### formation is

limited by one of two methods. Under staged fuel

- rich condition s

, low oxygen

levels limit flame temperatures resulting in less NO

x 

### 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 NO

x 

### formation. In the secondary zone, combustion products formed in

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

decrease in NO

x 

### formation.

27 “Controlling Nitrogen Oxide s Under the Clean Air Act: A Menu of Options.” Utility Boiler section. July

1994.

28 Ibid.

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

.

### Southwestern Electric Power Company 6

- 4 Trinity Consultants

BART Analysis

– Flint Creek

The est imated NO

x 

### control range for LNBs on coal boilers is 0.20

- 0.26

lb/MMBtu. 30 

### When combined with OFA, the estimated NO

x 

### control range on is

0.18

- 0.24 lb/MMBtu

. 31 

### LNB systems are technically feasible for the control of

NO

x 

### from SN

- 01

.



### 6.3.2 P OST 

### C OM BUSTION 

### C ONTROLS



### 6.3.2.1 S ELECTIVE 

### C ATALYTIC 

### R EDUCTION



### SCR refers to the process in which NO

x 

### is reduced by ammonia over a

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

selective because the ammonia preferentially reacts with NO

x 

### rather than

oxygen, altho ugh the oxygen enhances the reaction and is a necessary

component of the process. The overall reactions are:

4NO + 4NH 3 + O 2  4N 2 + 6H 2 O

2NO 2 + 4NH 3 + O 2  3N 2 + 6H 2 O



### 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 NO

x 

### concentration, the exhaust temperature, the

ammonia injection rate, and the type of catalyst. The estimated NO

x 

### control for

SCR on coal fi red boilers is 80

- 90%, and is consistent with vendor estimates of

0.067 lb/MMBtu at SN

- 01. 32 

### This control is a technically feasible option for

the control of NO

x 

### from SN

- 01.



### 6.3.2.2 S ELECTIVE 

### N ON



### - C ATALYTIC 

### R EDUCTION



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

appropriate temperature window. The NO

x 

### and reagent (ammonia or urea)

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

storage, multi

- level reagent

- injection equipment, and associated control

instrumentation. The SNCR reagent storage and handling systems are similar

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

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

NO

x 

### reductions. The estimate d NO

x 

### control range for SNCR for coal fired

boilers is 0.18

- 0.27 lb/MMBtu. 33 

### This control is a technically feasible option

for the control of NO

x 

### from SN

- 01.

30 “Controlling Nitrogen Oxides Under the Clean Air Act: A Menu of Options.” Uti lity Boiler section. July

1994.

31 Ibid.

32 Ibid.

33 Ibid.

### Southwestern Electric Power Company 6

- 5 Trinity Consultants

BART Analysis

– Flint Creek 

## 6.4 R ANK OF 

## T ECHNICALLY FEASIBLE 

## NO X 

## C ONTROL 

## O PTIONS BY



## E FFECTIVENESS

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

effectiveness. Table 6

- 2 provides a ranking of the control levels for the controls listed in the

previous section for SN

- 01.

T ABLE 

### 6

- 2

. C ONTROL 

### E FFECTIVENESS OF 

### T ECHNICALLY 

### F EASIBLE 

### NO X 

### C ONTRO L



### T ECHNOLOGIES

Control Technology Estimated Controlled

Level for SN

- 01

(lb/MMBtu) 34

SCR 0.067

LNB/OFA + SNCR 0.18

- 0.23 35

LNB / OFA 0.18

- 0.24

S NCR 0.18

- 0.27

FGR 0.23

- 0.29

LNB 0.20

- 0.26

OFA 0.28

- 0 .29



### With the exception of the control level for SCR, the control levels in Table 6

- 2 are presented as

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

- 01 based on

the application of the controls listed in Table 6

- 2 is unknown. Based on several discussions between

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

as LNB in combination with OFA will achieve a NO

x 

### level of approxi mately 0.23 lb/MMBtu for SN

01. EPA established presumptive SO 2 

### and NO

x 

### controls for coal

- fired EGUs in the BART rule. For

dry

- bottom wall

- fired EGUs, the presumptive NO

x 

### limit is 0.23 lb/MMBtu

. 36 

### The presumptive

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

presumptive lim it for a unit like SN

- 01, the presumptive limit was not automatically assumed the

floor for combustion control on SN

- 01. Rather, experience with similar boilers and vendor

discussions have led the selection of this emission level. Current NO

x 

### emissions f rom SN

- 01 are

approximately 0.31 lb/MMBtu. Further, it is believed that SCR will achieve a NO

x 

### level of

approximately 0.067 lb/MMBtu and LNB/OFA + SNCR will achieve a level of 0.21 lb/MMBtu or

10

- 20% better control than from LNB/OFA alone

.



## 6.5 E VALUATION OF 

## I MPACTS FOR 

## F EASIBLE 

## NO X 

## C ONTROLS

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

factors to be considered in the impact analysis:

▲ 

### Cost of compliance

▲ 

### Energy impacts

34 Ibid.

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

January 2001.

36 Ibid.

### Southwestern Electric Power Company 6

- 6 Trinity Consultants

BART Analysis

– Flint Creek ▲ 

### Non

- air quality impacts; and

▲ 

### The rem aining useful life of the source



### 6.5.1 C OST OF 

### C OMPLIANCE



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

and SCR were estimated for the cost analysis.

Control Costs

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

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

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

supplemented with vendor and site

- specifi c information where available. The capital

costs were annualized over a 30

- year period and then added to the annual operating costs to

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

provided in Appendix B of this report.

Annual Tons Reduced

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

determined by subtracting the estimated con trolled annual emission rate from the baseline

annual emission rate.

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

- 2003

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

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

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

- 2003

average daily heat input for SN

- 01 as determined from the EPA’s Clean Air Markets

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

the average number of operating hours from 2001

- 2003.

Cost Effectiveness

The cost effectiveness in dollars per ton of N O

x 

### reduced was determined by dividing the

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

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

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

analysis is sum marized in Table 6

- 3.

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

boilers, combustion control technology is generally more cost

- effective than post

combustion controls. EPA estimates that approximately 75 per cent of the BART units

(non

- cyclone) could meet the presumptive NO

x 

### limits at a cost of $100 to $1,000 per ton of

NO

x 

### removed based on the use of combustion control technology. 37 

### For the units that

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

37 “Regional Haze Regulations and Guidelines for Best Availa ble Retrofit Technology (BART Determinations;

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

- 39135.

### Southwestern Electric Power Company 6

- 7 Trinity Consultants

BART Analysis

– Flint Creek

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

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

than $1,500 per ton of NO

x 

### removed. 38



### Table 6

- 3 indi cates that the cost effectiveness of LNB/OFA at a NO

x 

### rate of 0.23

lb/MMBtu is approximately $2, 129 per ton of NO

x 

### removed. Table 6

- 3 also indicates that

the costs for LNB/OFA/SNCR for SN

- 01 is nearly $3, 400 /ton of NO

x 

### removed and SCR

for SN

- 01 is greater than $3

, 380 per ton of NO

x 

### removed. Additionally, the incremental

cost of the LNB/OFA/SNCR over the LNB/OFA system is greater than $ 5,6 00 per ton of

NO

x 

### removed for SN

- 01. The incremental cost of SCR over the LNB/OFA system is

greater than $ 4 ,300/ton of NO

x 

### removed for SN

- 01.

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

each NO

x 

### control technology was also determined. Additional details on the visibility

improvement analysis are provided below. The cos t of LNB/OFA ranges from

approximately $33

- $160 million/dv across the Class I areas, as seen in Table 6

- 4. The cost

of LNB/OFA plus SNCR ranges from approximately $55

- 268 million/dv across the Class I

areas, as seen in Table 6

- 5. Table 6

- 6 shows that con trol of NO

x 

### from SCR results in a cost

range of approximately $88

- 442 million/dv across the Class I areas.

38 Ibid.

### Southwestern Electric Power Company 6

- 8 Trinity Consultants

BART Analysis

– Flint Creek TABLE 

### 6

- 3

. S UMMARY OF 

### C OST 

### E FFECTIVENESS FOR 

### SN

- 01 NO X 

### C ONTROLS

TABLE 

### 6

- 4

. D OLLAR PER 

### D ECIVIEW 

### C OST 

### E FFECTIVENESS FOR 

### SN

- 01 N O

X 

### C ONTROL 

### U SING 

### LN B/OFA

### Southwestern Electric Power Company 6

- 9 Trinity Consultants

BART Analysis

– Flint Creek

TABLE 

### 6

- 5

. D OLLAR PER 

### D ECIVIEW 

### C OST 

### E FFECTIVENESS FOR 

### SN

- 01 N O

X 

### C ONTROL 

### U SING 

### LNB/OFA P LUS 

### SNCR

TABLE 

### 6

- 6

. D OLLAR PER 

### D ECIVIEW 

### C OST 

### E FFECTIVENESS FOR 

### SN

- 01 N O

X 

### C ONTROL 

### U SING 

### SCR

### Southwestern Electric Power Company 6

- 10 Trinity Consul tants

BART Analysis

– Flint Creek 

### 6.5.2 E NERGY 

### I MPACTS 

### & N ON



### - A IR 

### I MPACTS



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

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

does not exist.

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

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

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

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

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

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

either from ammonia injection at temperatures too low for effective reaction wi th NO

x 

### , 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 th e

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

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



### 6.5.3 R EMAINING 

### U SEFUL 

### L IFE



### The remaining useful life of SN

- 01 does not impact the annualized capital cos ts of

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

the capital cost recovery period, which is 15 years.



## 6.6 E VALUATION OF 

## V ISIBILITY 

## I MPACT OF 

## F EASIBLE 

## NO X 

## C ONTROLS

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

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

. Section 4 of this report documented the existing visibility impairment attributable to SN

- 01. In orde r

to assess the visibility improvement associated with LNB/OFA, SCR and SNCR systems, t he NO

x 

### emission rate s associated with both LNB and SCR systems were modeled using CALPUFF. The

controlled emission level associated with SCR systems is 0.067 lb/MMBtu f or SN

- 01. The controlled

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

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

emission rates used in the modeling.

Tables 6

- 7 through 6

- 9 summarize the NO

x 

### emission rates that were modeled to reflect the LNB/OFA

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

in Tables 6

- 7 through 6

- 9 are the same as in the baseline model ing.

### Southwestern Electric Power Company 6

- 11 Trinity Consul tants

BART Analysis

– Flint Creek T ABLE 

### 6

- 7

. S UMMARY OF 

### E MISSION 

### R ATES 

### M ODELED TO 

### R EFLECT 

### LNB/OFA FOR 

### NO X



### C ONTROL

SO 2 (lb/hr) SO 4

(lb/hr) 

### NO

x

(lb/hr) PM C

(lb/hr) PM F

(lb/hr) SOA

(lb/hr) EC

(lb/hr) PM 10, total

(lb/hr)

SN

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



### T ABLE 

### 6

- 8

. S UMMARY OF 

### E MISSION 

### R ATES 

### M ODELED TO 

### R EFLECT 

### SCR FOR 

### NO X 

### C ONTROL

SO 2 (lb/hr) SO 4

(lb/hr) 

### NO

x

(lb/hr) PM C

(lb/hr) PM F

(lb/hr) SOA

(lb/hr) EC

(lb/hr) PM 10, total

(lb/hr)

SN

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



### T ABLE 

### 6

- 9

. S UMMARY OF 

### E MIS SION 

### R ATES 

### M ODELED TO 

### R EFLECT 

### LNB/OFA + SNCR FOR 

### NO X



### C ONTROL

SO 2 (lb/hr) SO 4

(lb/hr) 

### NO

x

(lb/hr) PM C

(lb/hr) PM F

(lb/hr) SOA

(lb/hr) EC

(lb/hr) PM 10, total

(lb/hr)

SN

- 01 4,728.4 111.2 1,777.74 29.8 22.9 27.8 0.9 192.5



### Table 6

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

associated with the addition of NO

x 

### controls on SN

- 01 in all affected Class I areas , including the

maximum modeled visibility impact, 98 th 

### percentile modeled visibility impact, and the num ber of

days with a modeled visibility impact greater than 0.5 Δdv. T h e visibility improvement shown in the

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

impairment associated with a retrofitted system with the specific control as measured by the 98 th



### percentile.

### Southwestern Electric Power Company 6

- 12 Trinity Consultants

BART Analysis

– Flint Creek

T ABLE 

### 6

- 10

. S UMMARY OF 

### V ISIBILITY 

### I MPROVEMENT 

### A SSOCIATED WITH 

### NO

X 

### C ONTROL 

### S YSTEM ON 

### SN

- 01 (2001

- 2003)

Caney Creek Wilderness Upper Buffalo Wilderness Hercules Glades

Wilderness Ming o NWR Maximum Impact (Δdv) 98% Impact (Δdv) # Days > 0.5 Δdv Visibility Improvement* Maximum Impact (Δdv) 98% Impact (Δdv) # Days > 0.5 Δdv Visibility Improvement* Maximum Impact (Δdv) 98% Impact (Δdv) # Days > 0.5 Δdv Visibility Improvement* Maximum Impact (Δdv ) 98% Impact (Δdv) # Days > 0.5 Δdv Visibility Improvement*

Baseline Emission Rate 1.408 0.993 55

- 2.585 1.066 76

- 2.186 0.734 60

- 1.553 0.653 24

-

LNB/OFA 1.286 0.924 46 6.9 % 2.294 1.030 68 3.4 % 2.023 0.683 51 6.9 % 1.427 0.639 21 2.1 %

SCR 1.105 0.784 33 21.0 % 1.816 1.011 55 28.2% 1.676 0.627 43 14.6 % 1.167 0.611 16 6.4 %

LNB/OFA + SNCR 1.255 0.900 45 9.4 % 2.188 1.028 67 3.6 % 1.964 0.676 50 7.9 % 1.382 0.634 20 2.9 %

*Improvement is based on the 98 th percentile impact (Δdv) compared to the baseline impact (Δdv)

†The visibility improvement shown in the table has been calculated from 98 th percentile baseline and controlled impacts that include more decimal places than

what is shown in the table. Due to rounding of the baseline and controlled 98 th per centile impacts shown in the table, the visibility improvement calculated from

the baseline and controlled 98 th percentile impacts shown in the table may be slightly different than the visibility improvement reflected in the table.

### Southwestern Electric Power Company 6

- 1 3 Trinity Consultants

BART Analysis

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

percent) of the 98 th 

### percentile visibility impairm ent attributable to SN

- 01 at the modeled Class I areas.

Further, the operation of SCR systems results in an estimated 0.0 4 to 0.21 Δdv improvement ( 6 to 28

pe rcent) of the 98 th 

### percentile visibility impairment attributable SN

- 01 at the modeled Class I areas,

while LNB/OFA + SNCR results in an estimated 0.02 to 0.09 Δdv improvement ( 3 to 9 percent) of

the 98 th 

### percentile

.



## 6.7 P ROPOSED 

## B ART FOR 

## NO X



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

regional haze obligations at SN

- 01. If CSAPR is vacated, SWEPCO should be entitled to rely on

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

obligations by continuing to comply with CAIR.

If a full evaluation of BART is required, the cost

- effectiveness of the control options and the limited

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

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

- day

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

improvement attributable to SN

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

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

approximately $2, 129 per ton of NO

x 

### removed. Although LNB/OFA plus SNCR adds a slight

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

cost of over $5

, 600 per ton of NO

x 

### removed. The incremental cost for SCR at SN

- 01 is nearly $ 4

, 355

per ton of NO

x 

### removed, and is an excessive cost to be considered BART. In addition, the adverse

e nvironmental impacts from the use of SCR, including an increased demand for electricity and the

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

improvements in visibility associated with its use at SN

- 01

.

### Southwester n Electric Power Company 7

- 1 Trinity Consultants

BART Analysis

– Flint Creek 

## 7. PM 10 

## BART E VALUATION

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

that the currently installed ESP is BART for PM 10 

### for SN

- 01 . As such, no further PM 10 

### analysis has

been conducted

.

### Southwestern Electric Power Company Trinity Consultants

BART Analysis

– Flint Creek 

## A PPENDIX 

## A

S O 2 

### C ONTROL 

### C OST 

### C ALCUL A TIONSCapital Costs

Technology

NID (SDA)

Material Capital Costs (including installation cost s) 1

Dry Flue Gas Desulfurization

(DFGD) $312,200,000

Total Capital Investment (TCI) $312,200,000

Annual Costs

Total Variable O&M 1 $/year $6,623,600

Total Fixed O&M 2 $/year $4,212,600

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

interest rate, a = equipment life 0.11

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

Annualized Capital Cost = Equipment CRF x TCI $34,277,882

Total Annual Costs ($/yr) $45,114,082

Operating Labor Cost $884,000

Maintenance Material $1,997,500

Maintenance Labor $1,331,100 Capital recovery factor Spary Dry Absorber (e.g. NID) Capital and O&M Cost Estimate

1 AEP regulatory filing in response to "Request for Declaratory Judgement" with the Arkansas Public

Service Commission on 2/8/2012.

1,2 Total Fixed O&M Costs ($/year) from AEP regulatory filing in response to "Request for Declaratory

Judgement" with the Arkansas Public Service Commiss ion on 2/8/2012 include:

### Southwestern Electric Power Company Trinity Consultants

BART Analysis

– Flint Creek 

## A PPENDIX 

## B

NO

X 

### C ONTROL 

### C OST 

### C ALCULATIONSCapital Costs Total Direct Capital

Technology

LNB-OFA

Material Capital Costs 1

Total Capital Cost Plus Installation $17,000,000

Annual Costs 2

Parameters/Costs Equation Unit 1

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

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

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

equipment life 0.08

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

Direct Annual Operating Costs $/yr

Variable O&M Costs =(0.027 mills/kW-hr/1000) x (1 kW-hr/10,000 Btu) x H x C x

10^6 Btu/mmBtu $132,364

Indirect Annual Costs, $/yr

1. Fixed O&M Costs (1.5% of capital cost) = 0.015 x TCI $255,000

2. Annualized capital cost = Equipment CRF x TCI $1,369,969

Total Annual Costs ($/yr) $1,757,333 LNB/OFA Capital and O&M Cost Estimate

1 Material capital costs are from Budgetary Proposal P006876 to AEP SWEPCO for Flint Creek Unit 1 Low N Ox combustion system from the Babcock

and Wilcox Company, October 7, 2011

Note - Capital cost does not include the following items and is therefore conservative in the sense th at the total capital cost of the LNB/OFA system

would actually be higher :

-Demolition of existing equipment

-Installation of the new equipment

-Insulation and lagging materials or installation

-Design, supply and installation of existing contro l system I/O hardware additions

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

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

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

Technology

SCR

Installed Capital Cost 1 $121,000,000

Annual Costs

Variable

Urea 1 $2,200,000

Catalyst replacement (per

year) 1 $1,500,000

Total Variable O&M 1 $3,700,000

Fixed

Operating Labor Cost 2 $530,000

Maintenance Labor 3 $530,000

Maintenance Material 1 $500,000

Total Fixed O&M 1 $1,560,000

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

= interest rate, a = equipment life 0.08

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

interest

Annualized capital cost = Equipment CRF x TCI $9,750,955

Total Annual Costs ($/yr) $15,010,955

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

3 Annual estimates provided by AEP based on 1 person per shift for 5 shifts. SCR Capital and O&M Cost Estimate

Capital recovery factor

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

estimates were informed by AEP's experience with SC R installations at other plants owned by AEPCapital Costs

Technology

SNCR

Parameters/Costs Equation Unit 1

Boiler design capacity, mmBtu/hr (Q

B ) Q B 6324

Total operating time (t

op , hrs/yr) t

op = CF total × 8760 hrs/yr 7752

Total Capacity Factor (CF total ) CF total = CF plant × CF SNCR 0.92

Plant Capacity Factor (CF plant ) 2 0.92

SNCR Capacity Factor (CF SCNR ) 3 CF SNCR = t SNCR /365 1

Assumed NOx removal efficiency ( η NOx ) 4 35%

Uncontrolled NOx rate (NOx in, lb/MMBtu) 5 0.33

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

Water Cost (Cost

water , $/gal) 7 $0.00362

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

Coal HHV (Btu/lb) 9 9,000

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

Capital recovery factor (CRF) CRF = [ I x (1+i)^a]/[(1+i)^a - 1], where I = inter est rate, a = equipment life 0.11

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

Cost Index 10

a. 2011 Cost Index 585

b. 1998 Cost Index 389.5

Capital Costs

Direct Capital Cost (A) DC ($) = ($950/MMBtu) × Q

B × ((2375 MMBtu/hr/Q

B )^0.577) × (0.66 + 0.85 η NOx ) × (CI 2011 /CI 1998 ) $5,007,199

Indirect Installation Costs ($)

General Facilities 0.05 × A $250,360

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

Process Contingency 0.05 × A $250,360

Total Indirect Installation Costs (B) = General Faci lities Cost + Engineering and Home Office Fees + Pr ocess Contingency $1,001,440

Other Installation Costs ($)

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

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

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

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

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

Inventory Capital (H) 11 H = Vol reagent (gal) × Cost reagent ($/gal) $76,102

Cost

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

Volume of Reagent Tank (Vol reagent (gal)) Vol reagent (gal) = q sol x days of reagent supply × 24 hr/day 49,417

Urea solution volumetric flow rate (q sol , gal/hr) 13 q sol = (m sol x 7.481 gal/ft 3 )/ ρ reagent 147.07

Mass flow rate of urea solution (m sol , lb/hr) 14

m sol = m reagent /C ureasol 1,395.84

Mass flow rate of reagent (m reagent , lb/hr) 15

m reagent = (NOx in x Q B x η NOx × NSR x M reagent )/(M NOx x SR T ) 697.92

Normalized Stoichiometric Ratio (NSR) NSR = ([2 × NOx in + 0.7] × η NOx )/NOx in 1.43

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

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

Annual Costs ($)

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

Annual Reagent Cost (K) K = q sol × Cost

reag × t

op $1,755,781

Annual Electricity Cost (L) L = P × Cost elect × t

op $58,064

Power (P, kW) P = (0.47 × NOx in × NSR × Q B )/9.5 149.80

Annual Water Cost (M) M = q

water × Cost

water

× t

op $18,775

Water flowrate for SNCR system (q

water , gal/hr) 16 q water = (m sol / ρ water ) × [(C ureasolstored /C ureasolinj ) - 1] 669.06

Annual ∆ Coal Cost (N) N = ∆ Coal × Cost coal × t

op $109,558

Additional coal required ( ∆ Coal, MMBtu/hr) 17 ∆ Coal = (Hv × m reagent × [(1/C ureasolinj ) - 1])/10 6 Btu/MMBtu 5.65

Annual ∆ Ash Cost (O) O = ( ∆ Ash × Cost ash × t

op )/2000 lb/ton $1,643

Additional ash generated ( ∆ Ash , lb/hr) 18 ∆ Ash = ( ∆ Coal × ashproduct × 10 6 Btu/MMBtu)/HHV 47.11

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

Indirect Annual Costs (IDAC)/Annualized Capital Cos t IDAC = CFR × TCI $782,203

Total Annualized Costs (TAC) TAC = DAC + IDAC $2,832,887 Selective Non-Catalytic Reduction Capital and O&M C ost Estimate 11 All SNCR costing equations from EPA Air Pollution Control Cost Manual (APCCM), 6th Edition (January 2 002)

2 Plant capacity factor from plant data

3 t SCNR assumed to be 365 days

4 η NOx (NOx removal efficiency) assumed to be 35% for SNCR alone

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

6 Electricity cost form Arkansas Industrial Energy C learinghouse, http://www.arkansasiec.org/newsmanage r/templates/?a=71&z=1

7 Water cost estimate from Bentonville, AR commercia l rate of $0.00362/gal, http://www.bentonvillear.co m/utbc_rates.html

8 Cost of coal from Lazard's 2009 Levelized Cost of E nergy Analysis (LCOE)

10 Cost of ash disposal from BART Analysis for NCS Un it 1, Appendix A

11 From Chemical Engineering Plant Cost Index (CEPCI)

12 Cost for urea stored on site, i.e., the first fill of the reagent tanks.

14 ρ reagent = 71.0 lb/ft 3

15 C ureasol = urea solution concentration = 50%

18 Approximate heat of vaporization of water at 310°F , Hv = 900 Btu/lb From EPA APCCM, 2002

19 Ashproduct is the fraction of ash produced as a byp roduct of burning a given type of coal. Assumed as hproduct = 0.075 from EPA APCCM, 2002 for subbitumi nous

coal. 9 Coal used at AEP Flint Creek originates from Powde r River Basin near Gillette, WY and is considered t o be subbituminous (source:

http://www.aecc.com/about/generation-facilities/)

HHV for subbituminous coal ranges from 8,000 - 10,0 00 Btu/lb (EPA APCCM, 2002).

Using HHV of 9,000 Btu/lb

13 Five-yr average urea cost = $356.11/metric ton, fro m http://www.indexmundi.com/commodities/?commodity= urea&months=180

Density of 50% urea solution = 9.5 lb/gal (50% urea solution) based on EPA APCCM, 2002

Equates to $1.54/gal

16 M reagent = 60.6 g/mol (molecular weight of urea)

M NOx = 46.01 g/mol (molecular weight of NO 2 )

SRT = 2 (ratio of equivalent moles NH 3 per mole of urea)

17 Concentration of stored urea, C ureasolstored = 50%

Concentration of urea injected into SNCR system , C ureasolinj = 10%

From EPA APCCM, 2002

### Southwestern Electric Power Company Trinity Consultants

BART Analysis

– Flint Creek 

## A PPENDIX 

## C

M ODELING 

### P ROTOCOL

# CALMET D ATA 

# P ROCESSING 

# P ROTOCOL  

# BART D ETERMINATION



# O KLAHOMA 

# G AS 

# & E LECTRIC

M USKOGEE 

### G ENERATING 

### S TATION



### S EMINOLE 

### G ENERATING 

### S TATION



### S OONER 

### G ENERATING 

### S TATION



### Prepared by:

Vern Choquette  

### Principal Consultant

Eugene Chen, PE  

### Senior Consultant

Jerem y Townley  

### Consultant

T RINITY 

### C ONSULTANTS



### 120 East Sheridan

Suite 205

Oklahoma City, OK 73104

(405) 228

- 3292

January 2 3 , 2008

Project 0 83701 .00 04

### OG&E i Trinity Consultants

CALMET Processing Protocol 083701.0004 

## T ABLE OF 

## C ONTENTS



### 1. I NTRODUCTION



### ................................ ................................ ................................ .... 1

- 1

1.1 B EST 

### A VAILABLE 

### R ETROFIT 

### T ECHNOLOGY 

### R ULE 

### B ACKGROUND



### ......................... 1

- 1

1.2 O BJECTIVE



### ................................ ................................ ................................ ............ 1

- 2

1.3 L OCATION OF 

### S OURCES AND 

### R ELEVANT 

### C LASS 

### I A REAS



### ................................ ...... 1

- 2

2. CALPUFF M ODEL 

### S YSTEM



### ................................ ................................ ............... 2

- 1

2.1 M ODEL 

### V ERSIONS



### ................................ ................................ ................................ . 2

- 1

2.2 M ODELING 

### D OMAIN



### ................................ ................................ ............................. 2

- 1

3. CALMET

................................ ................................ ................................ ............ 3

- 1

3.1 G EOPHYSICAL 

### D ATA



### ................................ ................................ ............................. 3

- 1

3.1.1 T ERRAIN 

### D ATA



### ................................ ................................ ................................ ... 3

- 1

3.1.2 L AND 

### U SE 

### D ATA



### ................................ ................................ ................................ . 3

- 2

3.1.3 C OMPILING 

### T ERRAIN AND LAND 

### U SE 

### D ATA



### ................................ ....................... 3

- 3



### 3.2 M ETEOROLOGICAL 

### D ATA



### ................................ ................................ ..................... 3

- 3

3.2.1 M ESOSCALE 

### M ODEL 

### M ETEOROLOGICAL 

### D ATA



### ................................ ................. 3

- 3

3.2.2 S URFACE 

### M ETEOROLOGICAL 

### D ATA



### ................................ ................................ ... 3

- 4

3.2.3 U PPER 

### A IR 

### M ETEOROLOGICAL 

### D ATA



### ................................ ................................ . 3

- 5

3.2.4 P RECIPITATION 

### M ETEOROLOGICAL 

### D ATA



### ................................ .......................... 3

- 6

3.2. 5 B UOY 

### M ETEOROLOGICAL 

### D ATA



### ................................ ................................ ......... 3

- 7



### 3.3 CALMET C ONTROL 

### P ARAMETERS



### ................................ ................................ ....... 3

- 8

3.3.1 V ERTICAL 

### M ETEOROLOGICAL 

### P ROFILE



### ................................ .............................. 3

- 8

3.3.2 I NFLUENCES OF 

### O BSERVATIONS



### ................................ ................................ ......... 3

- 9



### A PPENDIX 

### A

- M ETEOROLOGICAL 

### S TATIONS



### A PPENDIX 

### B

– S AMPLE 

### CALMET C ONTROL 

### F ILE 

### (CALPUFF V ERSION 

### 5.8)

A PPENDIX 

### C

– S AMPLE 

### CALMET C ONTROL 

### F ILE 

### (CALPUFF V ERSION 

### 6)

### OG&E ii Trinity Consultants

CALMET Processing Protocol 083701.0004 

## L IST OF 

## T ABLES

T ABLE 

### 1

- 1. BART

- E LIGIBLE 

### S OURCES



### ................................ ................................ ............................... 1

- 2

T ABLE 

### 1

- 2. D ISTANCE 

### F ROM 

### S TATION TO 

### S URROUNDING 

### C LASS 

### I A REAS



### ................................ ....... 1

- 2

T ABLE 

### 2

- 1. CALPUFF M ODELING 

### S YSTEM 

### V ERSIONS



### ................................ ................................ ..... 2

- 1

T ABLE 

### 3

- 1. V ERTICAL 

### L AYERS OF THE 

### CALMET M ETEOROLOGICAL 

### D O MAIN



### ................................ 3

- 9

T ABLE 

### A

- 1. L IST OF 

### S URFACE METEOROLOGICA L 

### S TATIONS



### ................................ ........................... A

- 1

T ABLE 

### A

- 2. L IST OF 

### U PPER 

### A IR METEOROLOGICAL 

### S TATIONS



### ................................ ......................... A

- 5

T ABLE 

### A

- 3. L IST OF 

### P RECIPITATION METEORO LO GICAL 

### S TATIONS



### ................................ .................. A

- 6

T ABLE 

### A

- 4. L IST OF 

### O VER 

### W ATER METEOROLOGICAL 

### S TATIONS



### ................................ .................. A

- 14

### OG&E iii Trinity Consultants

CALMET Processing Protocol 083701.0004 

## L IST OF 

## F IGURES

F IGURE 

### 1

- 1. P LOT OF 

### S OURCES AND 

### N EAREST 

### C LASS 

### I A REAS



### ................................ ......................... 1

- 3

F IGURE 

### 2

- 1. R EFINED 

### M ETEOROLOGICAL 

### M ODELING 

### D OMAIN



### ................................ ......................... 2

- 2

F IGURE 

### 3

- 1. P LOT OF 

### L AND 

### E LEVATION 

### U SING 

### USGS T ERRAIN 

### D ATA



### ................................ ............ 3

- 2

F IGURE 

### 3

- 2. P LOT OF 

### L AND 

### U SE 

### U SING 

### USGS LULC D ATA



### ................................ ............................. 3

- 3

F IGURE 

### 3

- 3. P LOT OF 

### S URFACE 

### S TATION 

### L OCATIONS



### ................................ ................................ ........ 3

- 5

F IGURE 

### 3

- 4. P LOT OF 

### U PPER 

### A IR 

### S TATIONS 

### L OCATIONS



### ................................ ................................ ... 3

- 6

F IGURE 

### 3

- 5. P LOT OF 

### P RECIPITATION METEORO LOGICAL 

### S TATIONS



### ................................ ................. 3

- 7

F IGURE 

### 3

- 6. P LOT OF 

### B UOY 

### M ETEOROLOGICAL 

### S TATIONS



### ................................ ................................ 3

- 8

### OG&E 1

- 1 Trinity Consultants

CALMET Processing Protocol 083701.0004 

## 1. I NTRODUCTION

Oklahoma Gas & Electric ( OG&E ) owns and operates three electric generating stations near

Muskogee, Oklahoma (M uskogee Generat ing Station ) , Seminole, Oklahoma (Seminole Generating

Station), and Stillwater, Oklahoma (Sooner Generating Station)

. The se generating stations are

considered eligible to be regulated under the U.S. Environmental Protection Agency’s (EPA) Best

Available R etrofit Technology (BART) provisions of the Regional Haze Rule. This protocol

describes the proposed methodology for conducting the CALMET data processing for the r efined

CALPUF F BART modeling analysis for OG&E’s Muskogee, Seminole, and Sooner Generating

Stations

. A detailed CALPUFF BART modeling protocol will be submitted in the near future and

will include a discussion of the CALPUFF parameters as well as the post processing methodologies

to be used in the refined modeling analysis for each station.



## 1.1 B ES T 

## A VAILABLE 

## R ETROFIT 

## T ECHNOLOGY 

## R ULE 

## B ACKGROUND

On July 1, 1999, the U.S. Environmental EPA published the final Regional Haze Rule (RHR). The

objective of the RHR is to improve visibility in 156 specific areas across with United States, known

as Class I a reas. 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, t he EPA published amendments to its 1999 RHR, often called the BART rule, which

included guidance for making source

- specific Best Available Retrofit Technology (BART)

determinations. The BART rule defines BART

- eligible sources as sources that meet the foll owing

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

- eligi ble 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 det ermine a source’s visibility impacts. States have the

authority to exempt certain BART

- eligible sources from installing BART controls if the results of the

dispersion modeling demonstrate that the source cannot reasonably be anticipated to cause or

contri bute 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.

### OG&E 1

- 2 Trinity Consultants

CALMET Processing Protocol 083701.0004 

## 1.2 O BJECTIVE

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

procedures that will be followed to conduct the CALMET data processing necessary to complete a

refined CALPUFF modeling analysis for the OG&E generating stations discussed above . The

modeling methods and procedures conta ined in this protocol and the CALPUFF protocol yet to be

submitted will be used to determine appropriate controls for OG&E’s BART

- eligible sources that can

reasonably be anticipated to reduce the sources’ effects on or contribution to visibility impairment in

the surrounding Class I area s

. It is OG&E ’s intent to determine a combination of emissions controls

that will reduce the impact of each generating station to a degree that the 98 th 

### percentile of the

visibility impact predicted by the model due to all the BART eligible sources at each station

collectively is below EPA’s recommended visibility contribution threshold of 0.5  dv.



## 1.3 L OCATION OF 

## S OURCES AND 

## R ELEVANT 

## C LASS 

## I A REAS

The sources listed in Table 1

- 1 are the sources that have been identified by OG&E as sources that

meet the three criteria for BART

- eligible sources.

T ABLE 

### 1

- 1

. BART

- E LIGIBLE 

### S OURCE S

EPN Description

Muskogee Sources

Unit 4 5,480 MMBtu/hr Coal Fired Boiler

Unit 5 5,480 MMBtu/hr Coal Fired Boiler

Seminole Sources

SM1 5,480 MMBtu/hr N atural Gas Fired Boiler

SM2 5,480 MMBtu/hr Natural Gas Fired Boiler

SM3 5,496 MMBtu/hr Natural Gas Fired Boiler

Sooner Sources

Unit 1 5,116 MMBtu/hr Coal Fired Boiler

Unit 2 5,116 MMBtu/hr Coal Fired Boiler



### As required in CENRAP’s BART Modeling Guid elines, Class I areas within 300 km of each station

will be included in each analysis. The following table summarize s the distances of the four closest

Class I areas to each station. As seen from this summary, some Class I areas are more than 300 km

from the certain station s . However, in order to demonstrate that each station will not have an adverse

effect on the visibility at any of the four nearest Class I areas, OG&E has opted to include those Class

I areas more than 300 km away in this analysis. No t e that the distances listed in the table below are

the distances between the stations and the closest border of the Class I areas.

T ABLE 

### 1

- 2

. D ISTANCE 

### F ROM 

### S TATION TO 

### S URROUNDING 

### C LASS 

### I A REAS

CACR HEGL UPBU WIMO

Muskogee 180 230 164 324

Seminole 2 42 386 310 178

Sooner 345 363 327 234

### OG&E 1

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CALMET Processing Protocol 083701.0004 A plot of the Class I areas with respect to the each station is provided in Figure 1

- 1.



### F IGURE 

### 1

- 1. P LOT OF 

### S OURCES AND 

### N EAREST 

### C LASS 

### I A REAS

### OG&E 2

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CALMET Processing Protocol 083701.0004 

## 2. CALPUFF M ODEL 

## S YSTEM

The main components of the CALPUFF modeling sy stem 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 transformatio n of air pollutants emitted from a source in “puffs”. CALPUFF calculates

hourly concentrations of visibility affecting pollutants at each specified receptor in a modeling

domain. CALPOST is the post

- processor for CALPUFF that computes visibility impacts from a

source based on the visibility affecting pollutant concentrations that were output by CALPUFF.



## 2.1 M ODEL 

## V ERSIONS

The versions of the CALPUFF modeling system programs that are propos ed for conducting OG&E ’s

BART modeling are listed in Table 2

- 1. A deta iled refined CALPUFF BART modeling protocol will

be submitted in the near future.

T ABLE 

### 2

- 1. CALPUFF M ODELING 

### S YSTEM 

### V ERSIONS



### Processor Version Level

TERREL 3.3 030 402

CTGCOMP 2.21 030402

CTGPROC 2.63 050128

MAKEGEO 2.2 030402

CALMET 5.53a 040716

CA LPUFF 5.8 070623

POSTUTIL 1.3 030402

CALPOST 5.51 030709



## 2.2 M ODELING 

## D OMAIN

The CALPUFF modeling system utilizes three modeling grids: the meteorological grid, the

computational grid, and the sampling grid. The meteorological grid is the system of grid p oints at

which meteorological fields are developed with CALMET. The computational grid determines the

computational area for a CALPUFF run. Puffs are advected and tracked only while within the

computational grid. The meteorological grid is defined so th at it covers the areas of concern and

gives enough marginal buffer area for puff transport and dispersion. A plot of the proposed

meteorological modeling domain with respect to the Class I areas being modeled is also provided in

### OG&E 2

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CALMET Processing Protocol 083701.0004 Figure 2

- 1 . The computati onal domain will be set to extend at least 50 km in all directions beyond

the Muskogee, Seminole, and Sooner Generating Stations and the Class I areas of interest. Note that

t he map projection for the modeling domain will be Lambert Conformal Conic (LCC) and the datum

will be the World Geodetic System 84 (WGS

- 84). The reference point for the modeling domain is

Latitude 40oN, Longitude 97oW. The southwest corner will be set to

- 951.547 km LCC,

- 1646.637

km LCC corresponding to Latitude 24.813 oN and Longi tude 87.778 oW

. The meteorological grid

spacing will be 4 km, resulting i n 462 grid p oints in the X direction and 376 grid points in the Y

direction.



### F IGURE 

### 2

- 1. R EFINED 

### M ETEOROLOGICAL 

### M ODELING 

### D OMAIN

- 800

- 600

- 400

- 200 0 200 400 600 800

LCC Easting (km) - 1600 - 1400 - 1200 - 1000 - 800 - 600 - 400 - 200

L C C N o r t h i n g ( k m ) Seminole Station Muskogee Station Sooner Station

WIMO

C ACR UPBU HEGL

Class I Areas Meteorological Modeling Domain

Computational Modeling Domain 1

### OG&E 3

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CALMET Processing Protocol 083701.0004 

## 3. CALMET

T he EPA Approv ed Version of the CALMET meteorological processor will be used to generate the

meteorological data for CALPUFF. CALMET is the meteorological processor that compiles

meteorological data from raw observations of surface and upper air conditions, precipitati on

measurements, mesoscale model output, and geophysical parameters into a single hourly, gridded

data set for input in to CALPUFF. CALMET will be used to assimilate data for 2001

- 2003 using

National Weather Service (NWS) surface station observations, upp er air station observations,

precipitation station observations , buoy station observations (for overwater areas) , and mesoscale

model output to develop the meteorological field.



## 3.1 G EOPHYSICAL 

## D ATA

CALMET requires geophysical data to characterize the terrai n 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 characteris tics such as surface roughness, albedo, Bowen ratio, and leaf

- area index that also

effect turbulence and dispersion.



### 3.1.1 T ERRAIN 

### D ATA



### Terrain data will be obtained from the United States Geological Survey (USGS) in

1

- degree (1:250,000 scale or approximately 90 mete r resolution) digital format. The

USGS terrain data will then be processed by the TERREL program to generate grid

- cell

elevation averages across the modeling domain. A plot of the land elevation s based on the

USGS data for the modeling domain is provided in Figure 3

- 1.

### OG&E 3

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CALMET Processing Protocol 083701.0004



### F IGURE 

### 3

- 1. P LOT OF 

### L AND 

### E LEVATION 

### U SING 

### USGS T ERRAIN 

### D ATA



### 3.1.2 L AND 

### U SE 

### D ATA



### The land use land cover (LULC) data from the USGS North American land cover

characteristics data base in the Lambert Azimuthal eq ual area map projection will be used

in order to determine the land use within the modeling domain

. The LULC data will be

processed by the CTGPROC program which will generate land use for each grid cell

across the modeling domain. A plot of the land use based on the USGS data for the

modeling domain is provided in Figure 3

- 2. - 800

- 600

- 400

- 200 0 200 400 600 800

LCC Easting(km) - 1600 - 140 0 - 1200 - 1000 - 800 - 600 - 400 - 200

L C C N o r t h i n g ( k m ) Seminole Station Muskogee Station Sooner Station

0 982 1960 2950 3930

Terrain

Elevation (m)

### OG&E 3

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CALMET Processing Protocol 083701.0004



### F IGURE 

### 3

- 2. P LOT OF 

### L AND 

### U SE 

### U SING 

### USGS LULC D ATA



### 3.1.3 C OMPILING 

### T ERRAIN AND LAND 

### U SE 

### D ATA



### The terrain data files output by the TERELL program and the LULC f iles output by the

CTGPROC program will be uploaded into the MAKEGEO program to create a

geophysical data file that will be input in to CALMET.



## 3.2 M ETEOROLOGICAL 

## D ATA

CALMET will be used to assimilate data for 2001, 2002, and 2003 using mesoscale model outp ut and

National Weather Service (NWS) surface station observations, upp er air station observations,

precipitation station observations , and National Oceanic and Atmosphere Administrations (NOAA)

buoy station observations to develop the meteorological field

.



### 3.2.1 M ESOSCALE 

### M ODEL 

### M ETEOROLOGICAL 

### D ATA



### Hourly mesoscale data will also be used as the initial guess field in developing the

CALMET meteorological data

. It is OG&E ’s intent to use the following 5 th 

### generation

mesoscale model meteorological data sets (or M M5 data) in the analysis :

 2001 MM5 data at 12 km resolution generated by the U.S. EPA

 2002 MM5 data at 36 km resolution generated by the Iowa DNR

- 800

- 600

- 400

- 200 0 200 400 600 8 00

LCC Easting (km) - 1600 - 1400 - 1200 - 1000 - 800 - 600 - 400 - 200

L C C N o r t h i n g ( k m )

10 27.5 45 62.5 80

Land Use Sooner Station

Muskogee Station

Seminole Station

### OG&E 3

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CALMET Processing Protocol 083701.0004

 2003 MM5 data set at 36 km resolution generated by the Midwest RPO

The specific MM5 data that will be use d are subsets of the data listed above. As the

contractor to CENRAP for developing the meteorological data sets for the BART

modeling

, Alpine Geophysics extracted three subsets of MM5 data for each year from

2001 to 2003 from the data sets listed above usin g the CALMM5 extraction program. The

three subsets covered the northern, central, and southern portions of CENRAP

. TXI is

proposing to use the southern set of the extracted MM5 data

.

The 2001 southern subset of the extracted MM5 data includes 30 fil es that are broken into

10 to 11 day incre ments (3 files per month). The 2002 and 2003 southern subsets of

extracted MM5 data include 12 files each of which are broken into 30 to 31 day increment

file s (1 file per month)

. Note that the 2001 to 2003 MM5 d ata extracted by Alpine

Geophysics will not be able to be used directly in the modeling analysis. To run the Alpine

Geophysics extracted MM data in the EPA approved CALMET program, each of the MM5

files will need to be adjusted by appending an additional six (6) hours, at a minimum, to

the end of each file to account for the shift in time zones from the Greenwich Mean Time

(GMT) prepared Alpine Geophysics data to Time Zone 6 for this analysis. No change to

the data will occur.

The time periods covered by the data in each of the MM5 files extracted by Alpine

Geophysics include a specific number of calendar days, where the data starts at Hou r 0 in

GMT for the first calendar day and ends at Hour 23 in GMT on the last calendar day. In

order to run CALMET i n the local standard time (LST), which is necessary since the

surface meteorological observations are recorded in LST, there must be hours of MM5 data

referenced in a CALMET run that match the LST observation hours. Since the LST hours

in Central Standard Time (CST) are 6 hours behind GMT, it is necessary to adjust the data

in each MM5 file so that the time period s covered in the files match CST.

Based on the above discussion, t he Alpine Geophysics MM5 data will not be used directly

. Instead the data fi les will be modified to add 8 additional hours of data to the end of each

file from the beginning of the subsequent file

. CALMET will then be run using the

appended MM5 data to generate a contiguous set of CALMET output files

. The converted

MM5 data file s occupy approximately 1.2 terabytes (TB) of hard drive space.



### 3.2.2 S URFACE 

### M ETEOROLOGICAL 

### D ATA



### Parameters affecting turbulent dispersion that are observed hourly at surface stations

include wind speed and direction, temperature, cloud cover and ceiling, relati ve humidity,

and precipitation type. It is OG&E ’s intent to use the surface stations listed in T able A

- 1

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

are shown in Figure 3

- 3. The stations were selected from th e available data inventory to

optimize spatial coverage and representation of the domain. Data from the stations will be

processed for use in CALMET using EPA’s SMERGE program.

### OG&E 3

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CALMET Processing Protocol 083701.0004



### F IGURE 

### 3

- 3. P LOT OF 

### S URFACE 

### S TATION 

### L OCATION S



### 3.2.3 U P PER 

### A IR 

### M ETEOROLOGICAL 

### D ATA



### Observations of meteorological conditions in the upper atmosphere provide a profile of

turbulence from the surface through the depth of the boundary layer in which dispersion

occurs. Upper air data are collected by balloons lau nched simultaneously across the

observation network at 0000 Greenwich Mean Time (GMT) (6 o’clock PM in Oklahoma )

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

direction, and temperature (among other parameters) as the b alloon rises through the

atmosphere. The upper air observation network is less dense than surface observation

points since upper air conditions vary less and are generally not as affected by local effects

(e.g., terrain or water bodies). The upper air st ations that are proposed for this analysis are

listed in Table A

- 2 of Appendix A

. The locations of the upper air stations with respect to

the modeling domain are shown in Figure 3

- 4. These stations were selected from the

available data inventory to optim ize spatial coverage and representation of the domain.

Data from the stations will be processed for use in CALMET using EPA’s READ62

program. - 800

- 600

- 400

- 200 0 200 400 600 800

LCC Easting (km) - 1600 - 1400 - 1200 - 1000 - 80 0 - 600 - 400 - 200

L C C N o r t h i n g ( k m ) Seminole Station Muskogee Station Sooner Station

WIMO

CACR UPBU HEGL

Class I Areas

Surface Stations

### OG&E 3

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CALMET Processing Protocol 083701.0004



### F IGURE 

### 3

- 4. P LOT OF 

### U PPER 

### A IR 

### S TATIONS 

### L OCATIONS



### 3.2.4 P RECIPITATION 

### M ETEOROLOGICAL 

### D ATA



### The effects of chemical tra nsformation and deposition processes on ambient pollutant

concentrations will be considered in this analysis. Therefore, it is necessary to include

observations of precipitation in the CALMET analysis. The precipitation stations that are

proposed for thi s analysis are listed in Table A

- 3 of Appendix A . The locations of the

precipitation stations with respect to the modeling domain are shown in Figure 3

- 5. These

stations were selected from the available data inventory to optimize spatial coverage and

rep resentation of the domain. Data from the stations will be processed for use in

CALMET using EPA’s PMERGE program.

### OG&E 3

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CALMET Processing Protocol 083701.0004



### F IGURE 

### 3

- 5. P LOT OF 

### P RECIPITATION MET E OROLOGICAL 

### S TATIONS



### 3.2.5 B UOY 

### M ETEOROLOGICAL 

### D ATA



### The effects of land/sea breeze on ambient pollutant concentrations will be considered in

this analysis. Therefore, it is necessary to include observations of buoy stations in the

CALMET analysis. The buoy stations that are proposed for this analysis are listed in Table

A

- 4 of Appendix A

. The locations of the buoy stations with respect to the modeling

domain are shown in Figure 3

- 6. These stations were selected from the available data

inventory to optimize spatial coverage and representation of the domain along the

coastline . Data from the stations will be pr epared by filling missing hour records with the

CALMET missing parameter value (9999). No adjustments to the data will occur.

### OG&E 3

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CALMET Processing Protocol 083701.0004



### F IGURE 

### 3

- 6. P LOT OF 

### B UOY 

### M ETEOROLOGICAL 

### S TATIONS



## 3.3 CALMET C ONTROL 

## P ARAMETERS

Appendix B provides a sample CALMET input fil e use d in OG&E ’s modeling analysis. A few

details of the CALMET model setup for sensitive parameters are also discussed below.



### 3.3.1 V ERTICAL 

### M ETEOROLOGICAL 

### P ROFILE



### The height of the top vertical layer will be set to 3

, 500 meters . This height corresponds to

t he top sounding pressure level for which upper air observation data will be relied upon.

T he vertical dimension of the domain will be divided into 12 layers with the maximum

elevations for each layer shown in Table 3

- 1. The vertical dimensions are weigh ted

towards the surface to resolve the mixing layer while using a somewhat coarser resolution

for the layers aloft.

### OG&E 3

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CALMET Processing Protocol 083701.0004 T ABLE 

### 3

- 1. V ERTICAL 

### L AYERS OF THE 

### CALMET M ETEOROLOGICAL 

### D OMAIN

Layer Elevation (m)

1 20

2 40

3 60

4 80

5 100

6 150

7 200

8 250

9 500

10 1000

11 2000

12 3500



### CALMET allows for a bias value to be applied to each of the vertical layers. The bias

settings for each vertical layer determine the relative weight given to the vertically

extrapolated surface and upper air wind and tem perature observations. The initial guess

fields are computed with an inverse distance weighting (1/ r 2 

### ) of the surface and upper air

data. The initial guess fields may be modified by a layer dependent bias factor. V alue s for

the bias factor may range fro m

- 1 to +1. A bias of

- 1 eliminate s upper

- air observations in

the 1/r 2 

### interpolations used to initialize the vertical wind fields

. Conversely

, a bias of +1

eliminate s the surface observations in the interpolations for this layer. Normally, bias is set

t o zero (0) for each vertical layer, such that the upper air and surface observations are given

equal weight in the 1/r 2 

### interpolations. T he biases for each layer of the proposed modeling

domain will be set to zero.

CALMET allows for vertical extrapolatio n of surface wind observations to layers aloft to

be skipped if the surface station is close to the upper air station. Alternatively, CALMET

allows data from all surface stations to be extrapolated. The CALMET parameter that

con trols this setting is IEXT RP. Setting IEXTRP to a value less than zero (0) means that

layer 1 data from upper air soundings is ignored in any vertical extrapolations. IEXTRP

will be set to

- 4 for this analysis (i.e., t he similarity theory is used to extrapolate the surface

winds into the layers aloft, which provides more information on observed local effects to

the upper layers )

.



### 3.3.2 I NFLUENCES OF 

### O BSERVATIONS



### Step 1 wind fields will be based on an initial guess using MM5 data and refined to reflect

terrain affects. Step 2 wind field s will adjust the Step 1 wind field by incorporating the

influence of local observations. An inverse distance method is used to determine the

influence of observations to the Step 1 wind field. R M AX1 and RMAX2 define the radius

of influence for data from surface stations to land in the surface layer and data from upper

air stations to land in the layers aloft. In general, RMAX1 and RMAX2 are used to

exclude observations from being inappropriately included in the development of the Step 2

### OG&E 3

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CALMET Processing Protocol 083701.0004

wind field if th e distance from an observation station to a grid point exceeds the maximum

radius of influence.

If the distance from an observation station to a grid point is less than the value set for

RMAX, the observation data will be used in the development of the Step 2 wind field. R1

represents the distance from a surface observation station at which the surface observation

and the Step 1 wind field are weighted equally. R2 represents the comparable distance for

winds aloft. R1 and R2 are used to weight the obs ervation data with respect to the MM 5

data that was used to generate the Step 1 wind field. Large values for R1 and R2 give

more weight to the observations, where as small values give more weight to the MM 5 data.

In this BART modeling analysis, RMAX 1 will be set to 20 km, and R1 will be set to 10

km. This will limit the influence of the surface observation data from all surface stations to

20 km from each station, and will equally weight the MM5 and observation data at 10 km.

RMAX2 will be set to 50 km, and R2 will be set to 25 km. This will limit the influence of

the upper air observation data from all surface stations to 50 km from each station, and will

equally weight the MM5 and observation data at 25 km. These settings of radius of

influence wi ll allow for adequate weighting of the MM5 data and the observation data

across the modeling domain due to the vast domain to be modeled

. RAMX 3 will be set to

500 km.

### OG&E A

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CALMET Processing Protocol 083701.0004 

## A PPENDIX 

## A

- M ETEOROLOGICAL 

## S TATIONS

T ABLE 

### A

- 1. L IST OF 

### S URFACE METEOROLOG I CAL 

### S TAT IONS

Number Station

Acronym Station

ID LCC

East

(km) LCC North

(km) Long Lat

1 KDYS 69019

- 267.672

- 834.095 96.9968 39.9925

2 KNPA 72222 932.565

- 1020.909 97.0110 39.9908

3 KBFM 72223 857.471

- 996.829 97.0101 39.9910

4 KGZH 72227 946.767

- 899.515 97. 0112 39.9919

5 KTCL 72228 870.843

- 706.104 97.0103 39.9936

6 KNEW 53917 674.172

- 1078.342 97.0080 39.9903

7 KNBG 12958 677.719

- 1104.227 97.0080 39.9900

8 BVE 12884 741.996

- 1153.463 97.0088 39.9896

9 KPTN 72232 550.88

- 1124.295 97.0065 39.9898

10 KM EI 13865 774.911

- 814.225 97.0092 39.9926

11 KPIB 72234 728.416

- 915.165 97.0086 39.9917

12 KGLH 72235 557.072

- 703.097 97.0066 39.9936

13 KHEZ 11111 540.777

- 912.22 97.0064 39.9918

14 KMCB 11112 622.755

- 949.618 97.0074 39.9914

15 KGWO 11113 640.102

- 695.286 97.0076 39.9937

16 KASD 72236 692.381

- 1043.261 97.0082 39.9906

17 KPOE 72239 363.294

- 984.839 97.0043 39.9911

18 KBAZ 72241

- 102.133

- 1140.886 96.9988 39.9897

19 KGLS 72242 215.108

- 1185.604 97.0025 39.9893

20 KDWH 11114 140.413

- 1101.174 97 .0017 39.9900

21 KIAH 12960 158.266

- 1108.37 97.0019 39.9900

22 KHOU 72243 167.147

- 1147.402 97.0020 39.9896

23 KEFD 12906 178.551

- 1152.782 97.0021 39.9896

24 KCXO 72244 152.739

- 1069.309 97.0018 39.9903

25 KCLL 11115 60.898

- 1044.381 97.0007 39.9906

26 KLFK 93987 214.643

- 969.355 97.0025 39.9912

27 KUTS 11116 136.056

- 1026.773 97.0016 39.9907

28 KTYR 11117 150.451

- 846.207 97.0018 39.9924

29 KCRS 72246 56.655

- 882.642 97.0007 39.9920

30 KGGG 72247 214.572

- 841.163 97.0025 39.9924

31 KGKY 11118

- 9.365

- 812.25 96.9999 39.9927

32 KDTN 72248 304.827

- 821.713 97.0036 39.9926

33 KBAD 11119 312.743

- 825.101 97.0037 39.9925

34 KMLU 11120 465.834

- 816.211 97.0055 39.9926

35 KTVR 11121 561.446

- 840.225 97.0066 39.9924

36 KTRL 11122 68.599

- 806.417 97 .0008 39.9927

37 KOCH 72249 216.81

- 930.252 97.0026 39.9916

38 KBRO 12919

- 44.167

- 1571.387 96.9995 39.9858

### OG&E A

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CALMET Processing Protocol 083701.0004

Number Station

Acronym Station

ID LCC

East

(km) LCC North

(km) Long Lat

39 KALI 72251

- 103.012

- 1363.74 96.9988 39.9877

40 KLRD 12920

- 246.548

- 1381.603 96.9971 39.9875

41 KSSF 72252

- 143.386

- 1183.35 96.9983 39.989 3

42 KRKP 11123

- 4.965

- 1324.914 96.9999 39.9880

43 KCOT 11124

- 219.097

- 1280.964 96.9974 39.9884

44 KLBX 11125 150.245

- 1207.466 97.0018 39.9891

45 KSAT 12921

- 143.024

- 1160.935 96.9983 39.9895

46 KHDO 12962

- 211.702

- 1178.172 96.9975 39.9894

47 KSK F 72253

- 154.625

- 1177.555 96.9982 39.9894

48 KHYI 11126

- 84.156

- 1122.487 96.9990 39.9899

49 KTKI 72254 38.788

- 754.791 97.0005 39.9932

50 KBMQ 11127

- 118.39

- 1027.031 96.9986 39.9907

51 KATT 11128

- 67.587

- 1075.97 96.9992 39.9903

52 KSGR 11129 131.4 78

- 1151.702 97.0016 39.9896

53 KGTU 11130

- 65.624

- 1033.173 96.9992 39.9907

54 KVCT 12912 6.587

- 1236.788 97.0001 39.9888

55 KPSX 72255 73.878

- 1253.33 97.0009 39.9887

56 KACT 13959

- 22.12

- 929.156 96.9997 39.9916

57 KPWG 72256

- 30.147

- 944.073 96.99 96 39.9915

58 KILE 72257

- 65.288

- 988.507 96.9992 39.9911

59 KGRK 11131

- 79.643

- 990.173 96.9991 39.9911

60 KTPL 11132

- 38.203

- 981.19 96.9996 39.9911

61 KPRX 13960 143.317

- 703.663 97.0017 39.9936

62 KDTO 72258

- 17.018

- 752.974 96.9998 39.9932

63 KA FW 11133

- 29.564

- 777.061 96.9997 39.9930

64 KFTW 72259

- 34.302

- 795.502 96.9996 39.9928

65 KMWL 11134

- 99.769

- 798.767 96.9988 39.9928

66 KRBD 11135 12.453

- 810.467 97.0002 39.9927

67 KDRT 11136

- 384.069

- 1170.59 96.9955 39.9894

68 KFST 22010

- 566.41 8

- 988.838 96.9933 39.9911

69 KGDP 72261

- 739.127

- 873.302 96.9913 39.9921

70 KSJT 72262

- 333.338

- 952.54 96.9961 39.9914

71 KMRF 23034

- 676.265

- 1042.616 96.9920 39.9906

72 KMAF 72264

- 489.668

- 878.107 96.9942 39.9921

73 KINK 23023

- 586.882

- 890.654 96.9931 39.9920

74 KABI 72265

- 252.044

- 836.353 96.9970 39.9924

75 KLBB 13962

- 445.006

- 689.313 96.9948 39.9938

76 KATS 11137

- 696.818

- 763.258 96.9918 39.9931

77 KCQC 11138

- 785.757

- 515.724 96.9907 39.9953

78 KROW 23009

- 698.822

- 712.898 96.9918 39. 9936

79 KSRR 72268

- 789.593

- 686.226 96.9907 39.9938

80 KCNM 11139

- 682.79

- 822.109 96.9919 39.9926

81 KALM 36870

- 838.056

- 752.338 96.9901 39.9932

82 KLRU 72269

- 931.527

- 804.112 96.9890 39.9927

83 KTCS 72271

- 952.353

- 695.469 96.9888 39.9937

### OG&E A

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CALMET Processing Protocol 083701.0004

Number Station

Acronym Station

ID LCC

East

(km) LCC North

(km) Long Lat

84 KSV C 93063

- 1042.03

- 752.033 96.9877 39.9932

85 KDMN 72272

- 1006.77

- 799.231 96.9881 39.9928

86 KMSL 72323 854.846

- 536.687 97.0101 39.9952

87 KPOF 72330 578.62

- 336.733 97.0068 39.9970

88 KGTR 11140 779.065

- 689.108 97.0092 39.9938

89 KTUP 93862 753.875

- 600.337 97.0089 39.9946

90 KMKL 72334 727.051

- 454.383 97.0086 39.9959

91 KLRF 72340 440.654

- 550.661 97.0052 39.9950

92 KHKA 11141 643.365

- 424.419 97.0076 39.9962

93 KHOT 72341 358.094

- 604.603 97.0042 39.9945

94 KTXK 11142 278.022

- 720.623 97.003 3 39.9935

95 KLLQ 72342 488.655

- 698.008 97.0058 39.9937

96 KMWT 72343 254.18

- 599.224 97.0030 39.9946

97 KFSM 13964 237.97

- 512.87 97.0028 39.9954

98 KSLG 72344 224.881

- 419.064 97.0027 39.9962

99 KVBT 11143 248.074

- 399.892 97.0029 39.9964

100 KHRO 11144 343.525

- 405.601 97.0041 39.9963

101 KFLP 11145 404.239

- 399.142 97.0048 39.9964

102 KBVX 11146 480.712

- 457.853 97.0057 39.9959

103 KROG 11147 258.44

- 397.685 97.0031 39.9964

104 KSPS 13966

- 138.053

- 664.886 96.9984 39.9940

105 KHBR 72352

- 186 .121

- 551.123 96.9978 39.9950

106 KCSM 11148

- 198.844

- 513.911 96.9977 39.9954

107 KFDR 11149

- 181.653

- 625.205 96.9979 39.9944

108 KGOK 72353

- 35.905

- 458.97 96.9996 39.9959

109 KTIK 72354

- 34.581

- 506.938 96.9996 39.9954

110 KPWA 11150

- 58.596

- 493. 951 96.9993 39.9955

111 KSWO 11151

- 7.42

- 425.828 96.9999 39.9962

112 KMKO 72355 146.972

- 479.879 97.0017 39.9957

113 KRVS 72356 91.059

- 438.276 97.0011 39.9960

114 KBVO 11152 87.136

- 357.069 97.0010 39.9968

115 KMLC 11153 110.647

- 563.566 97.0013 39. 9949

116 KOUN 72357

- 40.731

- 527.298 96.9995 39.9952

117 KLAW 11154

- 129.405

- 600.222 96.9985 39.9946

118 KCDS 72360

- 300.297

- 610.668 96.9965 39.9945

119 KGNT 72362

- 985.117

- 475.563 96.9884 39.9957

120 KGUP 11155

- 1059.48

- 427.151 96.9875 39.9961

1 21 KAMA 23047

- 425.319

- 518.171 96.9950 39.9953

122 KBGD 72363

- 395.603

- 466.083 96.9953 39.9958

123 KFMN 72365

- 993.449

- 297.944 96.9883 39.9973

124 KSKX 72366

- 770.464

- 355.855 96.9909 39.9968

125 KTCC 23048

- 597.271

- 511.241 96.9930 39.9954

126 KLV S 23054

- 732.565

- 448.329 96.9914 39.9960

127 KEHR 72423 812.573

- 199.695 97.0096 39.9982

128 KEVV 93817 822.929

- 172.715 97.0097 39.9984

### OG&E A

- 4 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number Station

Acronym Station

ID LCC

East

(km) LCC North

(km) Long Lat

129 KMVN 72433 704.666

- 154.54 97.0083 39.9986

130 KMDH 11156 676.745

- 218.041 97.0080 39.9980

131 KBLV 11157 617 .659

- 136.018 97.0073 39.9988

132 KSUS 3966 547.898

- 130.122 97.0065 39.9988

133 KPAH 3816 725.985

- 293.319 97.0086 39.9974

134 KJEF 72445 419.01

- 145.496 97.0050 39.9987

135 KAIZ 11158 387.096

- 200.609 97.0046 39.9982

136 KIXD 72447 182.322

- 126.913 97.0022 39.9989

137 KWLD 72450 0

- 298.57 97.0000 39.9973

138 KAAO 11159

- 18.976

- 248.773 96.9998 39.9978

139 KIAB 11160

- 23.392

- 263.471 96.9997 39.9976

140 KEWK 11161

- 24.645

- 215.58 96.9997 39.9981

141 KGBD 72451

- 161.892

- 180.781 96.9981 39.9984

1 42 KHYS 11162

- 195.191

- 124.723 96.9977 39.9989

143 KCFV 11163 126.442

- 319.698 97.0015 39.9971

144 KFOE 72456 114.618

- 115.26 97.0014 39.9990

145 KEHA 72460

- 432.761

- 320.089 96.9949 39.9971

146 KALS 72462

- 777.592

- 245.892 96.9908 39.9978

147 KDRO 1 1164

- 945.713

- 259.163 96.9888 39.9977

148 KLHX 72463

- 568.426

- 195.178 96.9933 39.9982

149 KSPD 2128

- 494.076

- 285.176 96.9942 39.9974

150 KCOS 93037

- 664.022

- 102.596 96.9922 39.9991

151 KGUC 72467

- 857.452

- 115.301 96.9899 39.9990

152 KMTJ 93013

- 9 40.981

- 109.358 96.9889 39.9990

153 KCEZ 72476

- 1020.87

- 233.14 96.9880 39.9979

154 KCPS 72531 591.652

- 136.14 97.0070 39.9988

155 KLWV 72534 808.939

- 94.46 97.0096 39.9992

156 KPPF 74543 130.433

- 293.855 97.0015 39.9973

157 KHOP 74671 841.751

- 324.56 9 97.0099 39.9971

158 KBIX 74768 778.252

- 1028.514 97.0092 39.9907

159 KPQL 11165 814.599

- 1019.583 97.0096 39.9908

160 MMPG 76243

- 348.007

- 1248.779 96.9959 39.9887

161 MMMV 76342

- 446.576

- 1449.334 96.9947 39.9869

162 MMMY 76394

- 316.664

- 1581.176 9 6.9963 39.9857

### OG&E A

- 5 Trinity Consultants

CALMET Processing Protocol 083701.0004

T ABLE 

### A

- 2. L IST OF 

### U PPER 

### A IR METEOROLOGICAL 

### S TATIONS

Number Station

Acronym Station

ID LCC

East

(km) LCC

North

(km) Long Lat

1 KABQ 23050

- 869.46

- 501.713 96.9897 39.9955

2 KAMA 23047

- 425.319

- 518.171 96.9950 39.9953

3 KBMX 53823 9 51.609

- 702.935 97.0112 39.9936

4 KBNA 13897 920.739

- 377.164 97.0109 39.9966

5 KBRO 12919

- 44.167

- 1571.39 96.9995 39.9858

6 KCRP 12924

- 51.535

- 1360.35 96.9994 39.9877

7 KDDC 13985

- 259.352

- 242.681 96.9969 39.9978

8 KDRT 22010

- 384.069

- 1170.59 96. 9955 39.9894

9 KEPZ 3020

- 914.558

- 852.552 96.9892 39.9923

10 KFWD 3990

- 28.034

- 793.745 96.9997 39.9928

11 KJAN 3940 650.105

- 826.452 97.0077 39.9925

12 KLCH 3937 364.461

- 1089.15 97.0043 39.9902

13 KLZK 3952 432.063

- 560.441 97.0051 39.9949

14 KMAF 23023

- 489.668

- 878.107 96.9942 39.9921

15 KOUN 3948

- 40.731

- 527.298 96.9995 39.9952

16 KSHV 13957 298.869

- 831.166 97.0035 39.9925

17 KSIL 53813 698.079

- 1054.03 97.0082 39.9905

### OG&E A

- 6 Trinity Consultants

CALMET Processing Protocol 083701.0004

T ABLE 

### A

- 3. L IST OF 

### P RECIPITATION METEORO LOGICAL 

### S TATIONS

Number Sta tion

Acronym Station

ID LCC

East

(km) LCC

North

(km) Long Lat

1 ADDI 10063 906.825

- 601.428 97.0107 39.9946

2 ALBE 10140 917.606

- 821.64 97.0108 39.9926

3 BERR 10748 892.454

- 683.388 97.0105 39.9938

4 HALE 13620 881.928

- 601.878 97.0104 39.9946

5 HA MT 13645 863.663

- 612.725 97.0102 39.9945

6 JACK 14193 898.014

- 915.623 97.0106 39.9917

7 MBLE 15478 851.953

- 1022.41 97.0101 39.9908

8 MUSC 15749 880.113

- 567.484 97.0104 39.9949

9 PETE 16370 935.558

- 908.259 97.0110 39.9918

10 THOM 18178 900.858

- 91 5.326 97.0106 39.9917

11 TUSC 18385 895.631

- 713.223 97.0106 39.9936

12 VERN 18517 825.585

- 685.773 97.0098 39.9938

13 BEEB 30530 462.394

- 532.485 97.0055 39.9952

14 BRIG 30900 318.015

- 554.857 97.0038 39.9950

15 CALI 31140 419.619

- 731.44 97.0050 39. 9934

16 CAMD 31152 386.546

- 699.659 97.0046 39.9937

17 DIER 32020 268.114

- 643.184 97.0032 39.9942

18 EURE 32356 286.738

- 390.862 97.0034 39.9965

19 GILB 32794 383.362

- 435.625 97.0045 39.9961

20 GREE 32978 450.594

- 483.201 97.0053 39.9956

21 STUT 36 920 509.943

- 596.328 97.0060 39.9946

22 TEXA 37048 278.022

- 720.623 97.0033 39.9935

23 ALAM 50130

- 749.044

- 267.856 96.9912 39.9976

24 ARAP 50304

- 441.903

- 152.324 96.9948 39.9986

25 COCH 51713

- 819.794

- 148.582 96.9903 39.9987

26 CRES 51959

- 828.107

- 119.911 96.9902 39.9989

27 GRAN 53477

- 451.781

- 203.82 96.9947 39.9982

28 GUNN 53662

- 829.573

- 141.995 96.9902 39.9987

29 HUGO 54172

- 539.364

- 81.948 96.9936 39.9993

30 JOHN 54388

- 483.95

- 201.915 96.9943 39.9982

31 KIM 54538

- 544.501

- 283.337 96.993 6 39.9974

32 MESA 55531

- 993.391

- 256.696 96.9883 39.9977

33 ORDW 56136

- 549.552

- 55.741 96.9935 39.9995

34 OURA 56203

- 904.197

- 168.246 96.9893 39.9985

35 PLEA 56591

- 1005.94

- 229.472 96.9881 39.9979

36 PUEB 56740

- 633.961

- 176.872 96.9925 39.9984

3 7 TYE 57320

- 662.095

- 242.254 96.9922 39.9978

38 SAGU 57337

- 790.269

- 176.061 96.9907 39.9984

### OG&E A

- 7 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number Sta tion

Acronym Station

ID LCC

East

(km) LCC

North

(km) Long Lat

39 SANL 57428

- 726.777

- 285.47 96.9914 39.9974

40 SHEP 57572

- 714.046

- 252.189 96.9916 39.9977

41 TELL 58204

- 920.205

- 215.382 96.9891 39.9981

42 TERC 58220

- 708.229

- 296.023 96.9916 39.9973

43 TRIN 58429

- 642.489

- 293.805 96.9924 39.9973

44 TRLK 58436

- 646.185

- 295.727 96.9924 39.9973

45 WALS 58781

- 654.989

- 262.821 96.9923 39.9976

46 WHIT 58997

- 619.615

- 250.12 96.9927 39.9977

47 ASHL 110281 684.787

- 16 9.285 97.0081 39.9985

48 CAIR 111166 697.177

- 301.436 97.0082 39.9973

49 CARM 111302 772.938

- 177.782 97.0091 39.9984

50 CISN 111664 758.146

- 151.446 97.0090 39.9986

51 FLOR 113109 751.801

- 139.837 97.0089 39.9987

52 HARR 113879 762.044

- 246.62 97.009 0 39.9978

53 KASK 114629 650.464

- 239.886 97.0077 39.9978

54 LAWR 114957 829.038

- 128.708 97.0098 39.9988

55 MTCA 115888 827.797

- 149.966 97.0098 39.9986

56 MURP 115983 682.261

- 251.649 97.0081 39.9977

57 NEWT 116159 766.098

- 72.902 97.0090 39.9993

5 8 REND 117187 731.633

- 185.058 97.0086 39.9983

59 SMIT 118020 770.027

- 283.638 97.0091 39.9974

60 SPAR 118147 658.275

- 185.973 97.0078 39.9983

61 VAND 118781 685.449

- 127.048 97.0081 39.9989

62 WEST 119193 778.655

- 147.215 97.0092 39.9987

63 EVAN 1227 38 842.476

- 172.871 97.0100 39.9984

64 NEWB 126151 855.854

- 223.713 97.0101 39.9980

65 PRIN 127125 836.901

- 153.449 97.0099 39.9986

66 STEN 128442 859.099

- 156.613 97.0101 39.9986

67 JTML 128967 788.703

- 239.572 97.0093 39.9978

68 ARLI 140326

- 101.734

- 271.373 96.9988 39.9976

69 BAZI 140620

- 210.423

- 201.758 96.9975 39.9982

70 BEAU 140637 59.762

- 288.39 97.0007 39.9974

71 BONN 140957 211.236

- 103.29 97.0025 39.9991

72 CALD 141233

- 32.689

- 330.586 96.9996 39.9970

73 CASS 141351 54.006

- 217.645 97.0 006 39.9980

74 CENT 141404 170.503

- 206.038 97.0020 39.9981

75 CHAN 141427 150.257

- 286.094 97.0018 39.9974

76 CLIN 141612 155.623

- 157.682 97.0018 39.9986

77 COLL 141730

- 265.465

- 156.95 96.9969 39.9986

78 COLU 141740 220.541

- 316.555 97.0026 39.9971

### OG&E A

- 8 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number Sta tion

Acronym Station

ID LCC

East

(km) LCC

North

(km) Long Lat

79 CONC 141867 58.918

- 175.589 97.0007 39.9984

80 DODG 142164

- 226.497

- 277.655 96.9973 39.9975

81 ELKH 142432

- 400.112

- 321.784 96.9953 39.9971

82 ENGL 142560

- 264.927

- 324.066 96.9969 39.9971

83 ERIE 142582 162.669

- 291.383 97.0019 39.9974

84 FALL 142686 83.491

- 288.177 97.0010 39.9974

85 GALA 142938

- 136.931

- 176.83 96.9984 39.9984

86 GARD 142980

- 304.059

- 215.308 96.9964 39.9981

87 GREN 143248 64.308

- 307.161 97.0008 39.9972

88 HAYS 143527

- 190.307

- 161.342 96.9978 39.9985

89 HEAL 143554

- 29 2.133

- 175.921 96.9966 39.9984

90 HILL 143686 214.018

- 174.006 97.0025 39.9984

91 INDE 143954 139.335

- 315.058 97.0016 39.9972

92 IOLA 143984 153.451

- 269.438 97.0018 39.9976

93 JOHR 144104 134.784

- 203.41 97.0016 39.9982

94 KANO 144178

- 50.289

- 181.1 77 96.9994 39.9984

95 KIOW 144341

- 113.967

- 329.843 96.9987 39.9970

96 MARI 145039

- 4.343

- 195.712 97.0000 39.9982

97 MELV 145210 137.104

- 186.781 97.0016 39.9983

98 MILF 145306 39.504

- 106.05 97.0005 39.9990

99 MOUD 145536 152.624

- 318.136 97.0018 39 .9971

100 OAKL 145888

- 306.378

- 96.814 96.9964 39.9991

101 OTTA 146128 158.639

- 178.635 97.0019 39.9984

102 POMO 146498 143.864

- 176.707 97.0017 39.9984

103 SALI 147160

- 29.426

- 166.908 96.9997 39.9985

104 SMOL 147551

- 34.639

- 171.31 96.9996 39.9985

105 STAN 147756 225.026

- 164.85 97.0027 39.9985

106 SUBL 147922

- 303.514

- 292.808 96.9964 39.9974

107 TOPE 148167 139.116

- 104.91 97.0016 39.9991

108 TRIB 148235

- 387.855

- 180.643 96.9954 39.9984

109 UNIO 148293 211.43

- 272.537 97.0025 39.9975

110 WAL L 148535

- 376.076

- 152.432 96.9956 39.9986

111 WICH 148830

- 23.729

- 288.579 96.9997 39.9974

112 WILS 148946

- 111.502

- 156.22 96.9987 39.9986

113 BENT 150611 781.608

- 348.109 97.0092 39.9969

114 CALH 151227 865.268

- 261.635 97.0102 39.9976

115 CLTN 151 631 749.287

- 365.634 97.0088 39.9967

116 HERN 153798 859.01

- 352.458 97.0101 39.9968

117 MADI 155067 854.116

- 265.064 97.0101 39.9976

118 PADU 156110 753.185

- 293.024 97.0089 39.9974

### OG&E A

- 9 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number Sta tion

Acronym Station

ID LCC

East

(km) LCC

North

(km) Long Lat

119 PCTN 156580 834.464

- 280.496 97.0099 39.9975

120 ALEX 160103 433 .824

- 959.253 97.0051 39.9913

121 BATN 160549 562.794

- 1032.4 97.0066 39.9907

122 CALH 161411 436.113

- 817.451 97.0052 39.9926

123 CLNT 161899 578.969

- 999.986 97.0068 39.9910

124 JENA 164696 455.225

- 912.366 97.0054 39.9918

125 LACM 165078 364.784

- 1 089.92 97.0043 39.9901

126 MIND 166244 346.708

- 812.651 97.0041 39.9927

127 MONR 166314 463.225

- 814.905 97.0055 39.9926

128 NATC 166582 369.451

- 905.316 97.0044 39.9918

129 SHRE 168440 299.526

- 831.143 97.0035 39.9925

130 WINN 169803 408.309

- 884.596 97.0048 39.9920

131 BROK 221094 621.827

- 914.236 97.0073 39.9917

132 CONE 221900 737.007

- 823.513 97.0087 39.9926

133 JAKS 224472 650.361

- 826.097 97.0077 39.9925

134 LEAK 224966 805.886

- 943.78 97.0095 39.9915

135 MERI 225776 774.942

- 814.558 97.009 2 39.9926

136 SARD 227815 658.33

- 593.661 97.0078 39.9946

137 SAUC 227840 763.399

- 1005.93 97.0090 39.9909

138 TUPE 229003 753.571

- 600.03 97.0089 39.9946

139 ADVA 230022 657.892

- 298.102 97.0078 39.9973

140 ALEY 230088 505.348

- 305.864 97.0060 39.997 2

141 BOLI 230789 331.651

- 291.689 97.0039 39.9974

142 CASV 231383 310.855

- 392.187 97.0037 39.9965

143 CLER 231674 575.868

- 302.209 97.0068 39.9973

144 CLTT 231711 307.465

- 190.83 97.0036 39.9983

145 COLU 231791 421.287

- 155.672 97.0050 39.9986

146 DREX 232331 228.23

- 185.776 97.0027 39.9983

147 ELM 232568 257.758

- 159.419 97.0030 39.9986

148 FULT 233079 470.408

- 150.668 97.0056 39.9986

149 HOME 233999 619.93

- 415.469 97.0073 39.9962

150 JEFF 234271 424.774

- 172.095 97.0050 39.9984

151 JOPL 234 315 238.245

- 318.262 97.0028 39.9971

152 LEBA 234825 402.239

- 276.263 97.0048 39.9975

153 LICK 234919 480.849

- 280.775 97.0057 39.9975

154 LOCK 235027 302.048

- 300.612 97.0036 39.9973

155 MALD 235207 659.982

- 377.876 97.0078 39.9966

156 MARS 235298 33 2.062

- 94.655 97.0039 39.9991

157 MAFD 235307 391.968

- 300.033 97.0046 39.9973

158 MCES 235415 471.737

- 143.942 97.0056 39.9987

### OG&E A

- 10 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number Sta tion

Acronym Station

ID LCC

East

(km) LCC

North

(km) Long Lat

159 MILL 235594 309.516

- 311.398 97.0037 39.9972

160 MTGV 235834 426.937

- 310.43 97.0050 39.9972

161 NVAD 235987 243.915

- 2 72.715 97.0029 39.9975

162 OZRK 236460 349.133

- 390.626 97.0041 39.9965

163 PDTD 236777 334.055

- 265.018 97.0039 39.9976

164 POTO 236826 572.215

- 251.455 97.0068 39.9977

165 ROLL 237263 484.503

- 253.958 97.0057 39.9977

166 ROSE 237300 500.59

- 175.393 97.0059 39.9984

167 SALE 237506 498.94

- 274.122 97.0059 39.9975

168 SENE 237656 233.959

- 383.703 97.0028 39.9965

169 SPRC 237967 238.112

- 373.616 97.0028 39.9966

170 SPVL 237976 332.385

- 309.374 97.0039 39.9972

171 STEE 238043 503.354

- 205.135 97.0059 39.9981

172 STOK 238082 310.911

- 279.239 97.0037 39.9975

173 SWSP 238223 324.053

- 150.325 97.0038 39.9986

174 TRKD 238252 340.418

- 395.428 97.0040 39.9964

175 TRUM 238466 326.883

- 197.796 97.0039 39.9982

176 UNIT 238524 238.567

- 154.494 97.0028 39.99 86

177 VIBU 238609 519.633

- 267.258 97.0061 39.9976

178 VIEN 238620 470.383

- 193.872 97.0056 39.9983

179 WAPP 238700 606.68

- 358.746 97.0072 39.9968

180 WASG 238746 556.425

- 164.993 97.0066 39.9985

181 WEST 238880 489.373

- 377.809 97.0058 39.9966

182 ALBU 290234

- 869.46

- 501.713 96.9897 39.9955

183 ARTE 290600

- 689.529

- 773.897 96.9919 39.9930

184 AUGU 290640

- 973.07

- 598.391 96.9885 39.9946

185 CARL 291469

- 680.335

- 811.474 96.9920 39.9927

186 CARR 291515

- 819.836

- 665.132 96.9903 39.9940

187 CL AY 291887

- 547.124

- 374.102 96.9935 39.9966

188 CLOV 291939

- 566.973

- 599.296 96.9933 39.9946

189 CUBA 292241

- 890.304

- 392.495 96.9895 39.9965

190 CUBE 292250

- 951.142

- 489.293 96.9888 39.9956

191 DEMI 292436

- 1007.99

- 799.087 96.9881 39.9928

192 DUR A 292665

- 767.148

- 577.618 96.9909 39.9948

193 EANT 292700

- 735.089

- 366.94 96.9913 39.9967

194 LAVG 294862

- 738.245

- 461.163 96.9913 39.9958

195 PROG 297094

- 811.39

- 578.971 96.9904 39.9948

196 RAMO 297254

- 733.737

- 615.175 96.9913 39.9944

197 ROSW 2 97610

- 698.544

- 712.921 96.9918 39.9936

198 ROY 297638

- 644.735

- 422.422 96.9924 39.9962

### OG&E A

- 11 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number Sta tion

Acronym Station

ID LCC

East

(km) LCC

North

(km) Long Lat

199 SANT 298085

- 807.375

- 445.708 96.9905 39.9960

200 SPRI 298501

- 676.681

- 374.272 96.9920 39.9966

201 STAY 298518

- 810.491

- 495.501 96.9904 39.9955

202 TNMN 29 9031

- 912.488

- 413.425 96.9892 39.9963

203 TUCU 299156

- 604.359

- 508.834 96.9929 39.9954

204 WAST 299569

- 638.605

- 820.288 96.9925 39.9926

205 WISD 299686

- 856.967

- 756.366 96.9899 39.9932

206 AIRS 340179

- 212.731

- 597.062 96.9975 39.9946

207 ARDM 340 292

- 12.242

- 645.633 96.9999 39.9942

208 BENG 340670 174.368

- 568.011 97.0021 39.9949

209 CANE 341437 71.857

- 637.935 97.0009 39.9942

210 CHRT 341544 203.233

- 632.067 97.0024 39.9943

211 CHAN 341684 10.494

- 475.655 97.0001 39.9957

212 CHIK 341750

- 83. 175

- 547.26 96.9990 39.9951

213 CCTY 342334

- 165

- 479.536 96.9981 39.9957

214 DUNC 342654

- 88.38

- 610.04 96.9990 39.9945

215 ELKC 342849

- 216.769

- 507.879 96.9974 39.9954

216 FORT 343281

- 129.964

- 541.113 96.9985 39.9951

217 GEAR 343497

- 118.53

- 482.1 87 96.9986 39.9956

218 HENN 344052

- 31.964

- 601.206 96.9996 39.9946

219 HOBA 344202

- 189.062

- 547.36 96.9978 39.9951

220 KING 344865 24.538

- 664.103 97.0003 39.9940

221 LKEU 344975 141.702

- 520.6 97.0017 39.9953

222 LEHI 345108 71.634

- 612.05 97.0009 39.9945

223 MACI 345463

- 254.63

- 466.154 96.9970 39.9958

224 MALL 345589

- 55.127

- 425.644 96.9994 39.9962

225 MAYF 345648

- 258.49

- 512.583 96.9970 39.9954

226 MUSK 346130 149.764

- 466.905 97.0018 39.9958

227 NOWA 346485 121.551

- 364.038 97.0014 39.996 7

228 OKAR 346620

- 88.424

- 473.338 96.9990 39.9957

229 OKEM 346638 63.188

- 504.958 97.0008 39.9954

230 OKLA 346661

- 54.198

- 510.562 96.9994 39.9954

231 PAOL 346859

- 23.665

- 573.142 96.9997 39.9948

232 PAWH 346935 57.704

- 369.174 97.0007 39.9967

233 P AWN 346944 16.927

- 398.139 97.0002 39.9964

234 PONC 347196

- 8.871

- 363.068 96.9999 39.9967

235 PRYO 347309 150.763

- 407.824 97.0018 39.9963

236 SHAT 348101

- 256.963

- 407.368 96.9970 39.9963

237 STIG 348497 171.02

- 523.736 97.0020 39.9953

238 TULS 3489 92 99.361

- 419.873 97.0012 39.9962

### OG&E A

- 12 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number Sta tion

Acronym Station

ID LCC

East

(km) LCC

North

(km) Long Lat

239 TUSK 349023 156.629

- 592.395 97.0019 39.9946

240 WMWR 349629

- 156.42

- 581.308 96.9982 39.9947

241 WOLF 349748 30.212

- 538.388 97.0004 39.9951

242 BOLI 400876 760.886

- 500.256 97.0090 39.9955

243 BROW 401150 710.0 48

- 480.346 97.0084 39.9957

244 CETR 401587 877.35

- 456.294 97.0104 39.9959

245 DICS 402489 872.14

- 391.132 97.0103 39.9965

246 DYER 402680 695.792

- 409.316 97.0082 39.9963

247 GRNF 403697 760.795

- 395.69 97.0090 39.9964

248 JSNN 404561 765.932

- 476.4 14 97.0090 39.9957

249 LWER 405089 885.291

- 487.757 97.0105 39.9956

250 LEXI 405210 790.003

- 471.897 97.0093 39.9957

251 MASO 405720 694.163

- 496.166 97.0082 39.9955

252 MEMP 405954 671.8

- 522.492 97.0079 39.9953

253 MWFO 405956 681.292

- 516.15 97.008 0 39.9953

254 MUNF 406358 678.65

- 495.241 97.0080 39.9955

255 SAMB 408065 697.077

- 382.536 97.0082 39.9965

256 SAVA 408108 800.788

- 498.682 97.0095 39.9955

257 UNCY 409219 711.595

- 384.605 97.0084 39.9965

258 ABIL 410016

- 251.753

- 836.027 96.9970 39.9 924

259 AMAR 410211

- 425.302

- 517.839 96.9950 39.9953

260 AUST 410428

- 67.587

- 1075.97 96.9992 39.9903

261 BRWN 411136

- 43.861

- 1571.39 96.9995 39.9858

262 COST 411889 60.611

- 1044.72 97.0007 39.9906

263 COCR 412015

- 51.832

- 1360.01 96.9994 39.9877

2 64 CROS 412131

- 204.599

- 868.469 96.9976 39.9922

265 DFWT 412242

- 1.867

- 786.341 97.0000 39.9929

266 EAST 412715

- 171.024

- 840.253 96.9980 39.9924

267 ELPA 412797

- 886.583

- 860.763 96.9895 39.9922

268 HICO 414137

- 97.323

- 888.181 96.9989 39.9920

269 H UST 414300 157.976

- 1108.38 97.0019 39.9900

270 KRES 414880

- 434.746

- 611.717 96.9949 39.9945

271 LKCK 414975 99.734

- 693.521 97.0012 39.9937

272 LNGV 415348 220.962

- 844.674 97.0026 39.9924

273 LUFK 415424 214.652

- 969.69 97.0025 39.9912

274 MATH 415 661

- 86.438

- 1330.47 96.9990 39.9880

275 MIDR 415890

- 489.385

- 878.123 96.9942 39.9921

276 MTLK 416104

- 672.024

- 1008.98 96.9921 39.9909

277 NACO 416177 223.065

- 925.966 97.0026 39.9916

278 NAVA 416210 28.358

- 892.028 97.0003 39.9919

### OG&E A

- 13 Trinity Consultants

CALMET Processing Protocol 083701.0004

Number Sta tion

Acronym Station

ID LCC

East

(km) LCC

North

(km) Long Lat

279 NEWB 416270 2 39.111

- 721.818 97.0028 39.9935

280 BPAT 417174 288.962

- 1110.65 97.0034 39.9900

281 RANK 417431

- 472.048

- 959.488 96.9944 39.9913

282 SAAG 417943

- 333.338

- 952.54 96.9961 39.9914

283 SAAT 417945

- 143.322

- 1161.27 96.9983 39.9895

284 SHEF 418252

- 463. 759

- 1019.19 96.9945 39.9908

285 STEP 418623

- 112.988

- 857.918 96.9987 39.9922

286 STER 418630

- 376.683

- 897.195 96.9956 39.9919

287 VALE 419270

- 720.749

- 1015.17 96.9915 39.9908

288 VICT 419364 6.882

- 1236.45 97.0001 39.9888

289 WACO 419419

- 21.834

- 928.823 96.9997 39.9916

290 WATR 419499

- 353.767

- 916.015 96.9958 39.9917

291 WHEE 419665 57.489

- 1008.99 97.0007 39.9909

292 WPDM 419916 262.792

- 737.786 97.0031 39.9933

293 DORA 232302 433.256

- 378.797 97.0051 39.9966

294 DIXN 112353 756.057

- 267.19 3 97.0089 39.9976

295 DAUP 12172 864.408

- 1050.41 97.0102 39.9905

296 FREV 123104 847.031

- 117.884 97.0100 39.9989

297 WARR 18673 890.447

- 788.703 97.0105 39.9929

298 MDTN 235562 493.264

- 87.222 97.0058 39.9992

### OG&E A

- 14 Trinity Consultants

CALMET Processing Protocol 083701.0004

T ABLE 

### A

- 4. L IST OF 

### O VER 

### W ATER METEOR OLOGICAL 

### S TATIONS

Number Station

ID Input file

Name LCC

East

(km) LCC North

(km) Long Lat

1 42001 42001 746.874

- 1541.35 89.67 25.9

2 42002 42002 265.486

- 1650.616 94.42 25.19

3 42007 42007 795.674

- 1063.667 88.77 30.09

4 42019 42019 163.178

- 1342.917 95.36 27.91

5 42020 42020 30.212

- 1453.738 96.7 26.94

6 42035 42035 254.465

- 1193.539 94.41 29.25

7 42040 42040 859.497

- 1160.066 88.21 29.18

8 BURL1 42045 743.116

- 1202.117 89.43 28.9

9 DPIA1 42046 861.385

- 1039.466 88.07 30.25

10 GDIL1 42047 687.9 84

- 1164.910 89.96 29.27

11 PTAT2 42048

- 4.980

- 1353.398 97.05 27.83

12 SRST2 42049 288.163

- 1175.682 94.05 29.67

### OG&E B

- 1 Trinity Consultants

CALMET Processing Protocol 083701.0004 

## A PPENDIX 

## B

– S AMPLE 

## CALMET C ONTROL 

## F ILE 

## (CALPUFF V ERSION 

## 5.8)

### OG&E C

- 1 Trinity Consultants

CALMET Processing Protocol 083701.0004 

## A PPENDIX 

## C

– S AMPLE 

## CALMET C ONTROL 

## F ILE 

## (CALPUFF V ERSION 

## 6 )