## BART F IVE 

## F ACTOR 

## A NALYSIS



## A RKANSAS 

## E LECTRIC 

## C OOPERATIVE 

## C ORPORATION



## B AILEY AND 

## M C 

## C LELLAN 

## G ENERATING 

## S TATION S

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 RKANSAS E LECTRIC COOPERATIVE CORPORAT ION
PO Box 194208 Little Rock, Arkansas
( 501 ) 570

- 2420

Trinity Project No. 123701.0036

March 2014

Version 4Arkansas Electric Cooperative Corporation i Trinity Consultants BART Analysis

– Bailey and McClellan 

## T ABLE OF 

## C ONTENTS



### 1. E XECUTIVE 

### S UMMARY



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

- 1

2. I NTRODUCTION AND 

### B ACKGROUND



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

- 1

3. M ODELING 

### 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

- 2

5. SO 2 

### BART E VALUATION



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

- 1

5.1 I DENTIFICATION OF 

### A VAILABLE 

### R ETROFIT 

### SO 2 

### C ONTROL 

### T ECHNOLOGIES



### – F UEL


### O IL COMBUSTION



### ................................ ................................ ................................ .............. 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

, S PRAY D RYER A BSORPTION (SDA), W ET S CRUBBER

, C IRCULATING D RY S CRUBBER (CDS)

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

- 1

5.2.2 F UE L S WITCHING

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

- 2


### 5.3 R ANK OF 

### T ECHNICALLY 

### F EASIBLE 

### SO 2 

### C ONTROL 

### O PTIONS BY 

### E FFECTIVENESS



### .. 5

- 2

5.4 E VALUATION OF 

### I MPACTS FOR 

### F EASIBLE 

### SO 2 

### C ONTROLS



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

- 2

5.4.1 C OST OF C OMPLIANCE

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

- 3

5.4.2 E NERGY I MPACTS AND N ON

- A IR Q UALITY I MPACTS

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

- 10

5.4.3 R EMAINING U SEFUL L IFE

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

- 10


### 5.5 E VALUATION OF 

### V ISIBILITY 

### I MPACT OF 

### F EASIBLE 

### SO 2 

### C ONTROLS



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

- 10

5.6 P ROPOSED 

### B ART FOR 

### SO 2



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

- 14

6. NO X 

### BART E VALUATION



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

- 1

7. PM 10 

### BART E VALUATION



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

- 1

7.1 I DENTIFICATION OF 

### A VAILABLE 

### R ETROFIT 

### PM 10 

### C ONTROL 

### T ECHNOLOGIES



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

- 1

7.2 E LIMINATE 

### T ECHNICALLY 

### I NFEASIBLE 

### PM C ONTROL 

### T ECHNOLOGIES



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

- 1

7.2.1 D RY E LECTROSTATIC P RECIPITATORS (ESP)

................................ ..................... 7

- 1

7.2.2 W ET E LECTROSTATIC P RECIPITATORS (ESP)

................................ ..................... 7

- 1

7.2.3 M ECHANICAL C OLLECTORS (C YCLONES )

................................ .......................... 7

- 2

7.2.4 F ABRIC F ILTER

................................ ................................ ................................ .... 7

- 2

7.2.5 W ET S CRUBBER

................................ ................................ ................................ .. 7

- 2

7.2.6 F UEL S WITCHING

................................ ................................ ................................ 7

- 3


### 7.3 R ANK OF 

### T ECHNICALLY FEASIBLE 

### PM 10 

### C ONTROL 

### O PTIONS BY 

### E FFECTIVENESS



### . 7

- 3

7.4 E VALUATION OF 

### I MPACTS FOR 

### F EASIBLE 

### PM 10 

### C ONTROLS



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

- 4

7.4.1 C OST OF C OMPLIANCE

................................ ................................ ........................ 7

- 4

7.4.1.1 Energy Impacts and Non

- Air Quality Impacts

................................ .... 7

- 5Arkansas Electric Cooperative Corporation ii Trinity Consultants BART Analysis

– Bailey and McClellan 7.4.1.2 Remaining Useful Life

................................ ................................ ......... 7

- 5


### 7.5 E VALUATION OF 

### V ISIBILITY 

### I MPACT OF 

### F EASIBLE 

### PM 10 

### C ONTROLS



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

- 7

7.6 P ROPOSED 

### B ART FOR 

### PM 10



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

- 11

A PPENDIX 

### A

................................ ................................ ................................ ......................... 7

- 12

A PPENDIX 

### B

................................ ................................ ................................ ......................... 7

- 13Arkansas Electric Cooperative Corporation iii Trinity Consultants BART Analysis

– Bailey and McClellan 

## L IST OF 

## T ABLES

T A BLE 1

- 1. E XISTING V ISIBILITY I MPAIRMENT A TTRIBUTABLE TO B AILEY U NIT 1 AND M C C LELLAN

U NIT 1 (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 ACT ORS

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

- 2

T ABLE 4

- 2. B ASELINE V ISIBILITY I MPAIRMENT A TTRIBUTABLE TO B AILEY

, U NIT 1 (2001

- 2003)

– N ATURAL G AS

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

- 3

T ABLE 4

- 3. B ASELINE V ISIBILITY I MPAIRMENT A TTRIBUTABLE TO B AILEY

, U NIT 1 (2001

- 2003)

– F UEL O IL

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

- 3

T ABLE 4

- 4. B ASELINE V ISIBILITY I MPAIRMENT A TTRIBUTABLE TO M C C LELLAN

, U NIT 1 (2001

- 2003), N ATURAL G AS

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

- 4

T ABLE 4

- 5. B ASELINE V ISIBILITY I MPAIRMENT A TTRIBUTABLE TO M C C LELLAN

, U NIT 1 (2001

- 2003), F UEL O IL

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

- 4

TABLE 5

- 2. A VAILABLE SO 2 C ONTROL T ECHNOLOGIES FOR B AILEY U NIT 1 A ND M C C LELLAN U NIT 1 5

- 1

T ABLE 5

- 3. C ONTROL E FFECTIVENESS OF T ECHNICALLY F EASIBLE SO 2 C ONTROL T ECHNOLOGIES 5

- 2

T ABLE 5

- 7. A VERAGE S ULFUR C ONTENT OF F UEL S TORED AT B AILEY AND M C C LELLAN

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

- 4

T ABLE 5

- 4. S UMMARY OF F UTURE A NNUAL SO 2 E MISSIONS A SSOCIATED WITH C URRENT N O

. 6

F UEL O IL

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

- 5

T ABLE 5

- 5. S UMMARY OF F UTURE A NNUAL SO 2 E MISSIONS A SSOCIATED WITH 1% S ULFUR N O

. 6

F UEL O IL

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

- 5

T ABLE 5

- 6. S UMMARY OF F UTURE A NNUAL SO 2 E MISSIONS A SSOCIATED WITH 0.5% S ULFUR N O

. 6

F UEL O IL

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

- 6

T ABLE 5

- 7. S UMMARY OF F UTURE A NNUAL SO 2 E MISSIONS A SSOCIATED WITH D IESEL

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

- 6

T ABLE 5

- 8. S UMMARY OF F UTURE A NNUAL SO 2 E MISSIONS A SSOCIATED WITH N ATURAL G AS

..... 5

- 7Arkansas Electric Cooperative Corporation iv Trinity Consultants BART Analysis

– Bailey and McClellan FIGURE 5

- 1. S UMMARY OF F UTURE A NNUAL SO 2 E MISSIONS A SSOCIATED WITH N ATURAL G AS

.... 5

- 8

T ABLE 5

- 9. S UMMARY OF C OST E FFECTIVENESS FOR F UEL S WITCHING FOR CURRENT N O

. 6 F UEL

O IL AT B AILEY U NIT 1

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

- 9

T ABLE 5

- 10. S UMMARY OF C OST E FFECTIVENESS FOR F UEL S WITCHING FOR CURRENT N O

. 6 F UEL

O IL AT M C C LELLAN U NIT 1

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

- 9

T ABLE 5

- 11. S UMMARY OF E MISSION R ATES M ODELED TO R EFLECT F UEL S WITCHING FOR SO 2 C ONTROL A T B AILEY U NIT 1

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

- 11

T ABLE 5

- 12. S UMMARY OF E MISSION R ATES M ODELED TO R EFLECT F UEL S WITCHING FOR SO 2 C ONTROL A T M C C LELLAN U NIT 1

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

- 11

T ABLE 5

- 13. S UMMARY OF M ODELED I MPACTS FROM SO 2 C ONTROL V ISIBILITY I MPACT A NALYSIS

FOR B AILEY U NIT 1 (2001

- 2003)

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

- 12

T ABLE 5

- 14. S UMMARY OF M ODELED I MPACTS FROM SO 2 C ONTROL V ISIBILITY I MPACT A NALYSIS

FOR M C C LELLAN U NIT 1 (2001

- 2003)

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

- 13

T ABLE 7

- 1. A VAILAB LE PM C ONTROL T ECHNOLOGIES FOR B AILEY U NIT 1 AND M C C LELLAN U NIT 1 7

- 1

T ABLE 7

- 3. C ONTROL E FFECTIVENESS OF T ECHNICALLY F EASIBLE PM C ONTROL T ECHNOLOGIES 7

- 4

T ABLE 7

- 4. S UMMARY OF C OST E FFECTIVENESS FOR B AILEY U NIT 1 PM 10 C ONTROLS

.................... 7

- 6

T ABLE 7

- 5. S UMMARY OF C OST E FFECTIVENESS FOR M C C LELLAN U NIT 1 PM 10 C ONTROLS

........... 7

- 6

T ABLE 7

- 5. S UMMARY OF E MISSION R ATES M ODELED TO R EFLECT W ET ESP FOR PM 10 C ONTROL 7

- 7

T ABLE 7

- 6. S UMMARY OF E MISSION R ATES M ODELED TO R EFLECT W ET S CRUBBER FOR PM 10 C ONTROL

................................ ................................ ................................ ................................ 7

- 7

T ABLE 7

- 7. S UMMARY OF E MISSION R ATES M ODELED TO R EFLECT C YCLONE FOR PM 10 C ONTROL 7

- 7

T ABLE 7

- 8. S UMMARY OF M ODELED I MPACTS FROM PM 10 C ONTROL V ISIBILITY I MPACT A NALYSIS

FOR B AILEY U NIT 1 (2001

- 2003)

................................ ................................ ............................ 7

- 9

T ABLE 7

- 9. S UMMARY OF M ODELED I MPACTS FROM PM 10 C ONTROL V ISIBILITY I MPACT A NALYSIS

FOR M C C LELLAN U NIT 1 (2001

- 2003)

................................ ................................ ................. 7

- 10Arkansas Electric Cooperative Corporation 1

- 1 Trinity Consultants BART Analysis

– Bailey and McClellan 

## 1. E XECUTIVE 

## S UMMARY

This report documents the determination of the Best Available Retrofit Technology (BART) as proposed by Arkansas Electric Cooperative Corporation ( AECC ) for the Unit 1 Boiler at the Bailey Generating Station and the Unit 1 Boiler at the McClellan Generatin g Station

. Bailey Unit 1 is a

wall

- fired boiler with a maximum heat input of 1,350 million British thermal units per hour (MMBtu/hr) that burn s natural gas and No. 6 fuel oil

. McClellan Unit 1 is a wall

- fired boiler with a maximum heat input of 1,436 MMB tu/hr that burns natural gas and No. 6 fuel oil

. The ability to burn fuel oil at both Bailey and McClellan is important

– even if the fuel oil is more expensive to burn than natural gas. During natural gas curtailments, natural gas infrastructure mainten ance, and other emergencies, AECC relies on the fuel oil stored at the plants to maintain electrical reliability.

Arkansas Department of Environmental Quality (ADEQ) has determined based on results of previous air dispersion modeling that cumulative emissions of nitrogen oxides (NO

x ), sulfur dioxide (SO 2 ), and particulate matter with a mass mean diameter smaller than ten microns (PM 10 ) from Bailey Unit 1 and

McClellan Unit 1 each cause or contribute greater than 0.5 delta deciviews (∆dv) to visibility impairment in f our Class I Areas: Caney Creek Wilderness (CACR), Upper Buffalo Wilderness (UPBU), Hercules Glades Wilderness (HERC), and Mingo Wilderness (MING). Since both Bailey

Unit 1 and McClellan Unit 1 meet the three criteria that make a source BA RT

- eligible, the fact that Bailey Unit 1 and McClellan Unit 1 contribute to visibility impairment in a Class I area greater than

0.5 ∆dv means that the boiler s are subject to BART.

A summary of the existing visibility impairment attri butable to each boiler based on the default

natural conditions is provided in Table 1

- 1. Note that the visibility impairment summarize d in Table

1

- 1 is based on recent modeling conducted by Trinity Consultants (Trinity) using emissions data

based on a combination of stac k testing

, Continuous Emission Monitoring System ( CEMS ) data and

AP

- 42 emission factors as further described in Section 4 of this report. AECC recognizes that the recent modeling shows impacts for Bailey Unit 1 that are less than 0.5 ∆dv , the threshold tha t ADEQ used to classify a source as subject to BART. Nevertheless, AECC is continuing with the BART analysis.

T ABLE 1

- 1. E XISTING V ISIBILITY I MPAIRMENT A TTRIBUTABLE TO B AILEY U NIT 1 AND
M C C LELLAN U NIT 1 (2001

- 2003)

CACR UPBU HERC MING

Unit / Fuel Scenario 98th

%

∆dv Days

> 0.5

∆dv 98th

%

∆dv Days

> 0.5

∆dv 98th

%

∆dv Days

> 0.5

∆dv 98th

%

∆dv Days

> 0.5

∆dv
Bailey, Unit 1

– Natural Gas 0. 083 0 0.072 0 0.073 0 0.102 0

Bailey, Unit 1

– Fuel Oil 0.330 8 0. 348 7 0.36 8 6 0.37 9 12

McClellan, Unit 1

– Natural Gas 0.125 3 0.052 0 0.040 0 0.058 0

McClellan, Unit 1

– Fuel Oil 0. 622 24 0.266 5 0.23 1 2 0.22 8 2Arkansas Electric Cooperative Corporation 1

- 2 Trinity Consultants BART Analysis

– Bailey and McClellan Trinity used the EPA’s BART guidelines in 40 CFR Part 51 1 to determine BART for Bailey Unit 1

and McClellan Unit 1 . Specifically, Trinity conducted a five

- step analysis to determine BART for

SO 2 , NO

x , and PM 10 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 document the results ;

5. Evaluating visibility impacts

.

Based on the five

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

▲ SO 2 – AECC has determined that BART for both Bailey Unit 1 and McClellan Unit 1 is using fuels with 0.5% sulfur or less (including natural gas)

.

▲ NO

x – AECC has determined that the requirements of the Cross State Air Pollution Rule ( CSAPR ) satisfy BART for NO X from Bailey Unit 1and McClellan Unit 1

. 2

▲ PM 10 – AECC has determined that no controls constitute BART. Neither a fuel change beyond that proposed for SO 2 nor add

- on controls are cost effective or result in an improvement to the visibility impairment attri butable to the AECC boilers of greater than 0 .011 Δdv , an insignificant improvement , as documented in Section 7

.

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

6 , 2005.

2 This determination was originally submitted on July 24, 2012. In response to CSAPR being vacated on August
21, 2012, AECC submitted a five

- factor analysis for NOx to ADEQ in September 2012 as an addendum to this analysis

.Arkansas Electric Cooperative Corporation 2

- 1 Trinity Consultants BART Analysis

– Bailey and McClellan 

## 2. I NT RODUCTION 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 preventing any future, and remedying any existing

, man

- made visibility impairment. On July 1, 1999, the U.S. EPA published the final Regional Haze Rule (RHR). The objective of the RHR is to restore visibility to pristine conditions in 156 specific areas across the U nited States known as Class I areas. The CAA defines Class I areas as certain national parks ( larger than 6

, 000 acres), wilderness areas ( larger than 5

, 000 acres), national memorial parks ( larger than 5

, 000 acres), and international parks that were in existence on August 7, 1977.

The RHR requires States to set goals that provide for reasonable progress towards achieving natural visibility conditions for each Class I area in their state. On July 6, 2005, the EPA published amendments to its 1999 RHR, often called the Best Available Retrofit Technology (BART) rule, which included guidance for making source

- specific BART determinations. The BART rule defines

BART

- eligible sources as sources that meet the following criteria:

(1) Have potential emissions of at least 250 tons per year of a visibility

- impairing pollutant, (2) Began operation between August 7, 1962 and August 7, 1977, and (3) Are included as one of the 26 listed source categories in the guidance.

A BART

- eligible source is subject to BART if the source is “reasonably anticipated to c ause 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 gr eater than 0.5 delta deciviews (∆dv) when compared against a natural background

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

Once it is determined that a source is subject to BART, a BART determination mus t address air pollution control measures for the source. The visibility regulations define BART as follows:

“...an emission limitation based on the degree of reduction achievable through the application of the best system of continuous emission reduction f or each pollutant which is emitted by...[a BART

- eligible source]. The emission limitation must be

established on a case

- by

- case basis, taking into consideration the technology available, the cost of compliance, the energy and non air quality environmental i mpacts of compliance, any pollution control equipment in use or in existence at the source, the remaining useful life of the source, and the degree of improvement in visibility which may reasonable be anticipated to result from the use of such technology.

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

3 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 impactsArkansas Electric Cooperative Corporation 2

- 2 Trinity Consultants BART Analysis

– Bailey and McClellan 1. Existing controls

2. Cost of controls

3. Energy and non

- air quality environmental impacts

4. Remaining useful life of the source

5. Degree of visibility improvement as a result of controls

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

follows:

1. Identify all available retrofit control technologies;

2. Eliminate technically infeasible control technologies;

3. Evaluate the control effectiveness of remaining control technologies;

4. Evaluate impacts and document the results ;

5. Evaluate visibility impacts

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

f ive steps listed above for each VAP.

Bailey Unit 1 and McClellan Unit 1 meet the three BART

- eligibility criteria described above

. Further, the existing visibility impairment attributable to each Bailey Unit 1 and McClellan Unit 1 is greater than 0.5 dv i n at least one Class I area. Thu s, both Bailey Unit 1 and McClellan Unit 1 are subject to BART. The details of the Bailey Unit 1 and McClellan Unit 1 existing/baseline emissions and the contribution of the emissions to visibility impairment can be found in Section 4 . The VAPs emitted by Bailey Unit 1 and McClellan Unit 1 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 m atter [IOR CPM] as sulfates [SO 4 ], and organic condensable particulate matter [OR CPM] also referred to as secondary organic aerosols [SOA]). The

BART determinations for SO 2 , NO

x , and PM 10 can be found in Sections 5

, 6 , and 7 , respectively.

O n June 7, 2012 EPA published a final rule allowing states participating in the Cross

- State Air Pollution Rule (CSAPR) trading program to use CSAPR to satisfy BART . Thus , AECC is proposing to satisfy

BART for NO

x by complying with CSAPR at Bailey Unit 1 and McClellan Unit 1. 4

4 This proposal was originally submitted on July 24, 2012. In response to CSAPR being vacated on August 21,
2012, AECC submitted a five

- factor analysis for NOx to ADEQ in September 2012 as an addendum to this analysis

.Arkansas Electric Cooperative Corporation 3

- 1 Trinity Consultants BART Analysis

– Bailey and McClellan 

## 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

- st eady

- 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. I n addition to meteorological data, several other input files are used by the CALPUFF model to specify source and receptor parameters. The selection and control of CALPUFF options are determined by user

- specific inputs contained in the control file. This file contains all of the necessary information to define a model run (e.g., starting date, run length, grid specifications, technical options, output options). CALPOST processes concentration, deposition, and visibility impacts based on pollutant specific concentrations predicted by CALPUFF.



## 3.1 CALMET AND 

## CALPUFF

The CALPUFF data and parameters are based on the 2005 BART modeling guidelines prepared for the Central States Regional Air Planning Association (CENRAP)

. The CALMET data and parameters are based on the modeling protocol included in Appendix B . Note that the protocol included in Appendix B summarizes modeling methods and procedures that were followed to predict visibility impairment for several BART

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

. In addition, several sources in Texas used the CALMET data that was generated in accordance with the protocol in their BART analyses.



## 3.2 CALPOST

The CALPOST visibility processing completed for this BART analysis is based on the October 2010 guidance from the Federal Land 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:

     

= 10 ln 10 (dv) ext b HI

T he impact of a source is determined by comparing the HI attributable to a source relative to estimated natural background conditions. The change in the haze index, in deciviews, also referred to
as “delta dv,” or ∆dv, b ased on the source and background light extinction is based on the following equation:Arkansas Electric Cooperative Corporation 3

- 2 Trinity Consultants BART Analysis

– Bailey and McClellan 

### ∆ dv = 10 * ln b b

b ext, backgroun d ext, source

ext, backgroun d 

### + 

   

  

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 :



### = ext 

### b 

## ( ) ( ) 

## [ ] ( ) ( ) 

## [ ]
( ) 

## [ ] ( ) 

## [ ] [ ] [ ] [ ] [ ] [ ] ( ) 

## [ ] [ ]

2 Scattering Rayleigh specific Site Large Small Large 3 4 Small 3 4 Large 2 4 4 Small 2 4 4



### NO 33

. 0 Salt Sea 4

. 1 PMC 6

. 0 PMF 1 EC 10 OC 1

. 6 OC 8

. 2 NO NH 1

. 5 NO NH 4

. 2 SO NH 8

. 4 SO NH 2

. 2

+ + + + + + + + + +

+

− 

### b RH f RH f RH f RH f RH f

SS L S L S

Visibility impairment predictions for Bailey Unit 1 and McClellan Unit 1 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 appro ach for addressing the growth of hygroscopic particles due to moisture in the atmosphere

. “ Mode 5 ” has been used in this BART analysis. Mode 5 addresses moisture in the atmosphere in a similar way as to “Method 6”, where “Method 6” is specified as the pr eferred approach for use with the old IMPROVE equation in the CENRAP BART modeling protocol.

CALPOST Method 8 , Mode 5 requires the following:

▲ Annual average concentrations reflecting natural background for various particles and for sea salt

▲ Monthly RH f actors for large and small ammonium sulfates and nitrates and for sea salts

▲ Rayleigh scattering parameter corrected for site

- specific elevation

Tables 3

- 1 to Table 3

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

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

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 )

CACR 0.23 0.1 1.8 0.02 0.5 3 0.03 11

UPBU 0.23 0.1 1.8 0.02 0.5 3 0.03 11

HERC 0.23 0.1 1.8 0.02 0.5 3 0.02 11

MING 0.23 0.1 1.83 0.02 0.51 3.05 0.04 12Arkansas Electric Cooperative Corporation 3

- 3 Trinity Consultants BART Analysis

– Bailey and McClellan 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

CACR 2.77 2.53 2.37 2.43 2.68 2.71 2.59 2.6 2.71 2.69 2.67 2.79

UPBU 2.71 2.48 2.31 2.33 2.61 2.64 2.57 2.59 2.71 2.58 2.59 2.72

HERC 2.7 2.48 2.3 2.3 2.57 2.59 2.56 2.6 2.69 2.54 2.57 2.72

MING 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

CACR 3.85 3.44 3.14 3.24 3.66 3.71 3.49 3.51 3.73 3.72 3.68 3.88

UPBU 3.73 3.33 3.03 3.07 3.54 3.57 3.43 3.5 3.71 3.51 3.52 3.74

HERC 3.7 3.33 3.01 3.01 3.47 3.48 3.41 3.51 3.67 3.43 3.46 3.73

MING 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

CACR 3.9 3.52 3.31 3.41 3.83 3.88 3.69 3.68 3.82 3.76 3.77 3.93

UPBU 3.85 3.47 3.23 3.27 3.72 3.78 3.69 3.7 3.84 3.64 3.67 3.86

HERC 3.86 3.51 3.23 3.22 3.66 3.72 3.69 3.73 3.81 3.57 3.65 3.88

MING 3.92 3.58 3.3 3.19 3.58 3.72 3.8 3.82 3.85 3.61 3.66 3.9Arkansas Electric Cooperative Corporation 4

- 1 Trinity Consultants BART Analysis

– Bailey and McClellan 

## 4. E XISTING 

## E MISSIONS AND 

## V ISIBILITY 

## I MPAIRMENT

This section summarizes the existing (i.e. baseline) visibility impairment attributable to Bailey Unit 1

and McClellan Unit 1 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 summarizes the emission rates that were modeled for SO 2 , NO

x , and PM 10 , including 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

– broken out to distinguish SO 2 and NO

x from burning No. 6 fuel oil and natural gas individually.

The PM 10 emission rate s for natural gas combustion are based on the emission factor for total PM 10 in

Table 1.4

- 2 of AP

- 42, which is 7.6 lbs/MMscf , and the maximum heat inputs for the units. T he

emission rates for the PM 10 species shown in Table 4

- 1 reflect the breakdown of th e filterable and

condensable PM 10 determined from AP

- 42 Table 1.4

- 2 Combustion of Natural Gas

. All filterable PM was assumed to be elemental carbon, as this is the assumption that the NPS uses for filterable PM 10 from natural gas fired combustion turbines . All of the condensable PM was assumed to be SOA, except for a small fraction of the condensable PM that was estimated to be SO 4 . One

- third of the

estimated SO 2 emissions were separated and adjusted for differences in molecular weight to represent

SO 4 e missions. This double counts some of the fuel sulfur based emissions as SO 2 but also as SO 4

. Since pipeline natural gas contains very little sulfur, both the SO 2 and SO 4 emission rates are very

low.

The PM 10 rates for fuel oil combustion are based on stack testing of both filterable and condensable

PM 10 conducted on Unit 1 at the McClellan plant on May 29, 2013. The total PM 10 emission rate determined during the testing was 59.4 lb/hr. Thus, a total PM 10 emission rate of 59.4 lb/hr was

modeled for M cCllellan. Stack testing was not conducted at Bailey in 2013, however, the total PM 10 emission rate for Unit 1 at Bailey was scaled by the ratio of the heat input for Bailey vs McClellan
(1436/1350) to get a total PM 10 emission rate of 55.8 lb/hr. T he emi ssion rates for the PM 10 species

shown in Table 4

- 1 reflect the breakdown of the PM 10 determined from the National Park Service (NPS) “speciation spreadsheet” for Uncontrolled Utility Residual Oil Boilers

. 5 More specifically, the

NPS workbook shows the fo llowing baseline distribution s for the PM species from No. 6 fuel oil at Bailey and McClellan, respectively :

▲ Coarse PM (PM C ) = 24.5%, 23.9 %

▲ Fine soil (modeled as PM F ) = 61.0 % , 64.3%

▲ Fine elemental carbon (modeled as EC) = 4.9 % , 4.8%

▲ Organic condensable PM (modeled as SOA) = 1 .4 % , 1.8%

▲ Inorganic condensable PM (modeled as SO 4 ) = 8.2 % , 10.0%

5 The NPS Workboo k, " Uncontrolled Utility Residual Oil Boiler .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 for Bailey: #6 oil with a sulfur content of 1.81%, and a heat input of 1,350 MMBtu/hr and for McClellan: #6 oil with a sulfur content of 1.38%, and a heat input of 1,436 MMBtu/hr.Arkansas Electric Cooperative Corporation 4

- 2 Trinity Consultants BART Analysis

– Bailey and McClellan

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 )

Unit / Fuel SO 2 6 NO

x 7 Total

PM 10 SO 4 PM

c PM f SOA EC

Scenario (lb/hr) (lb/hr) (lb/hr) (lb/hr) (lb/hr) (lb/hr) (lb/hr) (lb/hr) Bailey, Unit 1

– Natural Gas 0.5 443.8 10.2 0.3 0.0 0.0 7.4 2.6 Bailey, Unit 1

– Fuel Oil 2,375.8 408.8 55.8 4.6 13.7 34.1 0.8 2.7

McClellan, Unit 1

– Natural Gas 0.6 423.9 10.9 0.3 0.0 0.0 7.9 2.7
McClellan, Unit 1

– Fuel Oil 2,747.5 579.8 59.4 5.9 14.2 35.4 1.0 2.8



## 4.2 B ASELINE 

## V ISIBILITY 

## I MPAIRMENT

Trinity conducted modeling to determine the visibility impairment attributable to Ba iley Unit 1 and

McClellan Unit 1 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.

Table 4

- 2 through Table 4

- 5 provide a summary of the modeled visibility i m pairment attributable to Bailey Unit 1 and McClellan Unit 1 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 submit ted with this document

.

6 Hourly rates were derived from EPA’s Clean Air Market Database (CAMD) daily rates of 12 lb/day and 14

lb/day from natural gas at Bailey and McClellan, respectively, and 57,018 lb/day and 65,940 lb/day from No. 6 fuel oil at

Bailey and McClellan, respectively.

7 Hourly rates were derived from EPA’s Clean Air Market Database (CAMD) daily rates of 10,650 lb/day and

10,174 lb/day from natural gas at Bailey and McClellan, respectively , and 9,812 lb/day and 13,914 lb/day from No. 6 fuel

oil at Bailey and McClellan, res pectively.Arkansas Electric Cooperative Corporation 4

- 3 Trinity Consultants BART Analysis

– Bailey and McClellan T ABLE 4

- 2

. B ASELINE V ISIBILITY I MP AIRMENT A TTRIBUTABLE TO B AILEY , U NIT 1 (2001

- 2003)

– N ATURAL G AS

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 0.137 0.083 0 0.28 96.36 3.35 0.00

2002 0.219 0.075 0 0.31 95.93 3.22 0.54

2003 0.147 0.067 0 0.40 91.98 5.51 2.10

Upper Buffalo Wilderness

2001 0.089 0.04 0 0.23 95.01 3.05 1.72

2002 0.160 0.031 0 0.30 86.44 5.48 7.77

2003 0.170 0.072 0 0.29 95.02 3.43 1.26

Hercules Glades Wilderness

2001 0.238 0.056 0 0.23 96.39 3.08 0.31

2002 0.067 0.039 0 0.88 87.67 10.78 0.67

2003 0.175 0.073 0 0.22 92.76 3.67 3.3 5

Mingo Wilderness

2001 0.154 0.07 0 0 0.29 90.58 5.41 3.72

2002 0.443 0.084 0 0.43 83.07 7.92 8.58

2003 0.201 0.102 0 0.45 83.34 8.10 8.11

T ABLE 4

- 3

. B ASELINE V ISIBILITY I MPAIRMENT A TTRIBUTABLE TO B AILEY , U NIT 1 (2001

- 2003)

– F UEL O IL

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 0.684 0.307 2 75.66 22.47 1.44 0.44

2002 0.745 0.330 3 87.19 12.11 0.57 0.14

2003 0.970 0.327 3 98.80 0.81 0.40 0

Upper Buffalo Wilderness

2001 0.578 0.282 3 94.29 4.99 0.73 0.00

2002 0.668 0.305 1 73.65 21.28 3.43 1.64

2003 0.696 0.348 3 90.73 8.42 0.83 0.02

Hercules Glades Wilderness

2001 0.687 0.327 3 98.40 1.07 0.52 0

2002 0.635 0.249 2 80.38 18.62 0.87 0.12

2003 0.648 0.368 1 82.74 14.39 2.08 0.79
Mingo Wilderness

2001 0.524 0.355 1 89.57 8.35 1.67 0.41

2002 1.592 0.379 7 93.95 4.68 1.26 0.11

2003 0.689 0.300 4 66.17 29.13 2.83 1.87Arkansas Electric Cooperative Corporation 4

- 4 Trinity Consultants BART Analysis

– Bailey and McClellan T ABLE 4

- 4

. B ASELINE V ISIBILITY I MPAIRMENT A TTRIBUTABLE TO M C C LELLAN , U NIT 1 (2001

- 2003)

, N ATURAL G AS

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 0.670 0.116 1 0.31 93.69 4.43 1.57

2002 0.175 0.092 0 0.55 82.94 8.35 8.15

2003 0.538 0.125 2 0.39 87.09 6.63 5.89

Upper Buffalo Wilderness

2001 0.096 0.048 0 0.38 92.78 5.43 1.41

2002 0.258 0.031 0 0.32 94.54 4.04 1.10

2003 0.112 0.052 0 0.34 91.78 4.82 3.05

Hercules Glades Wilderness

2001 0.064 0.034 0 0.29 93.50 4.42 1.79

2002 0.082 0.022 0 0.74 88.76 10.09 0.41

2003 0.092 0.04 0 0.74 86.01 10.18 3.07

Mingo Wilderness

2001 0.091 0.032 0 0.30 92.13 3.91 3.67

2002 0.132 0.058 0 0.33 91.96 5.13 2.58

2003 0.107 0.034 0 0.37 90.42 5.85 3.35

T ABLE 4

- 5. B ASELINE V ISIBILITY I MPAIRMENT A TTRIBUTABLE TO M C C LELLAN , U NIT 1 (2001

- 2003), F UEL O IL

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 1.685 0.622 10 89.86 9.62 0.53 0.00

2002 1.021 0.389 4 86.29 11.26 1.72 0.74

2003 3.007 0.616 9 82.89 15.76 0.36 0.62

Upper Buffalo Wilderness

2001 0.604 0.258 2 84.02 14.98 0.99 0.01

2002 1.323 0.184 1 77.31 20.96 1.43 0.30

2003 0.599 0.266 2 98.47 0.95 0.58 0.00

Hercules Glades Wilderness

2001 0.512 0.231 1 78.67 20.16 1.17 0.01

2002 0.463 0.168 0 59.28 37.65 2.31 0.75

2003 0.662 0.211 1 76.18 20.22 2.51 1.08
Mingo Wilderness

2001 0.417 0.228 0 80.90 17.89 1.20 0.01

2002 0.547 0.213 2 59.42 36.88 2.32 1.38

2003 0.471 0.203 0 87.39 11.23 1.29 0.09Arkansas Electric Cooperative Corporation 5

- 1 Trinity Consultants BART Analysis

– Bailey and McClellan 

## 5. SO 2 

## BART E VALUATION



## 5.1 I DENTIFICATION OF 

## A VAILABLE 

## R ETROFIT 

## SO 2 

## C ONTROL 

## T ECHNOLOGIES



## – F UEL 

## O IL COMBUSTION

Bailey Unit 1 and McClellan Unit 1 currently combust No. 6 fuel oil and natural gas. Because the

SO 2 emissions profile from natural gas is so small, no additional controls will be considered for

combustion of na tural gas. This section concerns controlling SO 2 emissions from the combustion of

No. 6 fuel oil.

Sulfur oxides, SO

x , are generated during fuel oil combustion from the oxidation of sulfur contained in

the fuel. SO

x emissions are almost entirely depend ent on the sulfur content of the fuel and are not affected by boiler size or burner design. SO

x emission from conventional combustion systems are predominantly in the form of SO 2 . Since SO 2 is the predominant sulfur compound emitted from the AECC boilers, 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 control technologies for the AECC boilers are summarized in Table 5

- 2. The

retrofit controls include both add

- on controls that eliminate SO 2 after it is formed and switching to

lower sulfur fuels which reduces the formation of SO 2

.

TABLE 5

- 2

. A VAILABLE SO 2 C ONTROL T ECHNOLOGIES FOR B AILEY U NIT 1 A ND M C C LELLAN
U NIT 1

SO 2 Control Technologies

Dry Sorbent Injection

Spray Dry er Absorber (SDA) i.e., Semi

- Dry Scrubber

Wet Scrubber Circulating Dry Scrubber (CDS) Fuel Switching



## 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 

### , S PRAY 

### D RYER 

### A BSORPTION 

### (SDA), W ET 

### S CRUBBER 

### , C IRCULATING 

### D RY 

### S CRUBBER 

### (CDS)

These technologies are coll ectively known as flue gas desulfurization (FGD) systems. FGD applications have not been used historically for SO 2 control on oil

- fired units in the U.S. electric industry. As there are no known FGD applications for oil

- fired units, the performance of FG Ds on oil

- fired units is unknown. EPA took this into account when evaluating the presumptive SO 2 emission rate for oil

- fired units and determined that the presumptive emission rate should be based on the sulfur content of the fuel oil, rather thanArkansas Electric Cooperative Corporation 5

- 2 Trinity Consultants BART Analysis

– Bailey and McClellan on FGD rates

. 8 Since there are no applications of FGD on oil

- fired units in the U.S., FGDs are considered technically infeasible for the control of SO 2 from Bailey Unit 1 and

McClellan Unit 1 and are not considered further for BART.



### 5.2.2 F UEL 

### S WITCHING

The AECC boil ers currentl y burn some residual fuel oil

. The most recent fuel oil shipment for Bailey was in December of 2006, and the most recent fuel oil shipment for McClellan was in April of 2009. The fuel oil that has been stored at Bail ey since 2006 has an average sulfur content of 1.81 percent by weight

, and the fuel oil that has been stored at McClellan

since 2009 has an average sulfur content of 1.38 percent by weight

.

Switching to a fuel with lower sulfur content should reduce SO 2 emissions in propor tion to

the reduction in the sulfur content of the fuel , assuming similar heat contents of the fuels

. Fuels with lower sulfur content include lower sulfur No. 6 fuel oil, No. 2 fuel oil, or natural

gas.



## 5.3 R ANK OF 

## T ECHNICALLY 

## F EASIBLE 

## SO 2 

## C ONTROL 

## O PTIONS B Y 

## E FFECTIVENESS

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

effectiveness. Fuel switching is the only technically feasible control option. SO 2 emissions from fuel combustion are generally proportional to the sulfur content of the fuel. For example, combusting

diesel oil (0. 05 percent sulfur ) should result in approximately a 96

- 97 percent reduction in SO 2 emissions from the AECC boilers as compared to the combustion of the current No. 6 fuel oil ( 1.81 and 1.38 percent sulfur for Bailey and McClellan, respectively )

.

Table 5

- 3 provides a ranking of the control levels for switching fuels in the AECC boilers.

T ABLE 5

- 3. C ONTROL E FFECTIVENESS OF T ECHNICALLY F EASIBLE S O 2 C ONTROL
T ECHNOLOGIES

Fuel Switching t o: Estimated Control Efficiency (Bailey, McClellan)

1% sulfur No. 6 fuel oil 45%, 28%

0.5% sulfur No. 6 fuel oil 72%, 64%

0.05% sulfur diesel 97%, 96%
Natural gas 99.9%, 99.9%



## 5.4 E VALUATION OF 

## I MPACTS FOR 

## F EASIBLE 

## SO 2 

## C ONTROLS

Step four of the BART analysis procedure is the impact analysis. The BART determination guidelines list the four factors to be considered in the impact analysis:

8 Summary of Comments and Responses on the 2004 and 2001 Proposed Guidelines for Best Available Retrofit Technology (BART) Determinations Under the Regional Haze Regulations EPA Docket Number OAR

- 2002

- 0076.Arkansas Electric Cooperative Corporation 5

- 3 Trinity Consultants BART Analysis

– Bailey and McClellan ▲ Cost of compliance

▲ Energy impacts

▲ Non

- air quality impacts; and

▲ The remaining useful life of the source



### 5.4.1 C OST OF 

### C OMPLIANCE

Control Costs The cost of the fuel switching that w as used in the cost effectiveness calculations w as determined by calculating the annual cost of the current No. 6 fuel oil and determining the

increased cost of switching to the various lower sulfur fuels. Switching fuel to diesel will require changes to the burners and the fuel system. However, for this analysis

, capital expenses were not included.

As AE CC currently burns both No. 6 fuel oil and natural gas at Bailey and McClellan , the

costs for these fuels were based on historical pricing , as an average dollar per MMBtu from

2000 to 2011

. The s upplier of the existing fuels (i.e.

, No. 6 fuel oil and natural gas) provided cost e stimates for lower sulfur No. 6 fuel oil s and diesel in phone calls with

AECC staff

.

Annual Tons Reduced The annual tons reduced used in the cost effectiveness calculations were determined by subtracting the estimated controlled annual emission rates from the baseline annual

emission rates.

The baseline and controlled annual emission rates were estimated by conducting a mass

balance on the sulfur in the various fuels.

The sulfur content used for baseline was 1.81% for Bailey Unit 1 and 1.38% for McClellan

Unit 1. Table 5

- 4 below summarizes the annual average sulfur content of the No. 6 fuel oil historically used at Bailey and McClellan. The most recent fuel oil shipment for Bailey was in December of 2006, and the most recent fuel oil shipment fo r McClellan was in April of 2009. The fuel oil that has been stored at Bailey since 2006 has an average sulfur content of 1.81 percent by weight

, and the fuel oil that has been stored at McClellan since

2009 has an average sulfur content of 1.38 percent b y weight.Arkansas Electric Cooperative Corporation 5

- 4 Trinity Consultants BART Analysis

– Bailey and McClellan T ABLE 5

- 7

. A VERAGE S ULFUR C ONTENT OF F UEL S TORED AT B AILEY AND M C C LELLAN

Bailey McClellan

2000 1.59 1.84

2001 1.30 1.70

2002 1.69 2.21

2003 1.89 1.67

2004 1.07 1.60

2005 1.45 1.94

2006 1.33 2.08

2007 1.81 2.06

2008 1.81 2.18

2009 1.81 1.38

2010 1.81 1.38

2011 1.81 1.38

2001

- 2003 average 1.63 1.86

2009

- 2011 average 1.81 1.38

In the EPA’s 2005 R egional H aze R ule BART Guidelines, EPA described baseline

emissions as follows:

“The baseline emissions rate should represent a realistic depiction of anticipated annual emissions for the source

... In the absence of enforceable limitations, you calculate baseline emissions based upon continuation of past practice.”

Since EPA states that baseline emissions should be based on antic ipated annual emissions and a continuation of past practice, AECC used the sulfur content of the fuel oil currently stored at Bailey and McClellan to estimate baseline emissions for Bailey Unit 1 and

McClellan Unit 1.

The No. 2 fuel oil emission rate, fo r example, was determined by first using the No. 2 fuel oil heat content to determine the quantity of No. 2 fuel that wo uld be used per year:

Average annual heat input from 2007

- 2011 / No. 2 oil heat content

The tons per year of sulfur that is availabl e to form sulfur compounds (i.e. SO 2 and SO 4 )

was calculated:

No. 2 fuel use per year * No. 2 oil density * Sulfur content in No. 2 fuel

The mass of sulfur in the form of SO 4 was estimated and subtracted from the total sulfur to determine the quantity of sulfur that could form SO 2 . The SO 2 emission rate was estimated by multiplying the sulfur available to form SO 2 by the ratio of the molecular weight forArkansas Electric Cooperative Corporation 5

- 5 Trinity Consultants BART Analysis

– Bailey and McClellan SO 2 vs. sulfur. The m ass of sulfur in the form of SO 4 was estimated by reducing the

baseline SO 4 emission rate in proportion to the percent reduction in fuel sulfur and then multiplying the SO 4 rate by the ratio of the molecular weight of sulfur vs. SO 4

.

Tables 5

- 4 through an d 5

- 8 provide a summary of the mass balance data and calculations

for the future annual SO 2 emission rates.

T ABLE 5

- 4. S UMMARY OF F UTURE A NNUAL SO 2 E MISSIONS A SSOCIATED WITH C URRENT
N O

. 6 F UEL O IL

Parameter Bailey McClellan

No. 6 Oil Heat Content ( MMBtu/Mgal) 155 155

Fuel Use (gal/yr) 252,855 1,882,146

No. 6 Oil Density (lb/gal) 8.26 8.26

Average Sulfur in No. 6 Oil (%) 1.81 1.38

Average Sulfur in No. 6 Oil (tpy) 18.90 107.27

SO4 (lb/hr) 4.55 5.92

SO4 (tpy) 2.31 15.35

SO4 as Sulfur in Fuel [Assume 1 mol S for each mol SO4] (tpy) 0.39 2.56

% S as SO4 2.04 2.39

Sulfur Available for SO2 Formation [backing out Sulfur for SO4] 18.52 104.71

% S as SO2 97.96 97.61

SO2 (tpy) 37.03 209.43

T ABLE 5

- 5. S UMMARY OF F UTURE A NNUAL SO 2 E MISSIONS A SSOCIATED WITH 1% S ULFUR
N O

. 6 F UEL O IL

Parameter Bailey McClellan

No. 6 Oil Heat Content (MMBtu/Mgal) 155 155

Fuel Use (gal/yr) 252,855 1,882,146

No. 6 Oil Density (lb/gal) 8.26 8.26

Sulfur in No. 6 Oil (%) 1 1

Sulfur in No. 6 Oil (tpy) 10.44 77.73

SO4 (lb/hr) 1.26 2.14

SO4 (tpy) 0.64 5.56

SO4 as Sulfur in Fuel [Assume 1 mol S for each mol SO4] (tpy) 0.11 0.93

% S as SO4 1.02 1.19

Sulfur Available for SO2 Formation [backing out Sulfur for SO4] 10.34 76.81

% S as SO2 98.98 98.81

SO2 (tpy) 20.67 153.61Arkansas Electric Cooperative Corporation 5

- 6 Trinity Consultants BART Analysis

– Bailey and McClellan

T ABLE 5

- 6. S UMMARY OF F UTURE A NNUAL SO 2 E MISSIONS A SSOCIATED WITH 0.5% S ULFUR
N O

. 6 F UEL O IL

Parameter Bailey McClellan

No. 6 Oil Heat Content (MMBtu/Mgal) 155 155

Fuel Use (gal/yr) 252,855 1,882,146

No. 6 Oil Density (lb/gal) 8.26 8.26

Sulfur in No. 6 Oil (%) 0.5 0.5

Sulfur in No. 6 Oil (tpy) 5.22 38.87

SO4 (lb/hr) 1.26 2.14

SO4 (tpy) 0.64 5.56

SO4 as Sulfur in Fuel [Assume 1 mol S for each mol SO4] (tpy) 0.11 0.93

% S as SO4 2.04 2.39

Sulfur Available for SO2 Formation [backing out Sulfur for SO4] 5.12 37.94

% S as SO2 97.96 97.61

SO2 (tpy) 10.23 75.88

T ABLE 5

- 7. S UMMARY OF F UTURE A NNUAL SO 2 E MISSIONS A SSOCIATED WITH D IESEL

Parameter Bailey McClellan

No. 2 Oil Heat Content (MMBtu/Mgal) 136.15 136.15

Fuel Use (gal/yr) 287,863 2,142,730

No. 2 Oil Density (lb/gal) 7.0 7.0

Sulfur in No. 2 Oil (%) 0.05 0.05

Sulfur in No. 2 Oil (tpy) 0.50 3.75

SO4 (lb/hr) 0.13 0.21

SO4 (tpy) 0.06 0.56

SO4 as Sulfur in Fuel [Assume 1 mol S for each mol SO4] (tpy) 0.01 0.09

% S as SO4 2.11 2.47

Sulfur Available for SO2 Formation [backing out Sulfur for SO4] 0.49 3.66

% S as SO2 0.98 0.98

SO2 (tpy) 0.99 7.31Arkansas Electric Cooperative Corporation 5

- 7 Trinity Consultants BART Analysis

– Bailey and McClellan

T ABLE 5

- 8. S UMMARY OF F UTURE A NNUAL SO 2 E MISSIONS A SSOCIATED WITH N ATURAL G AS

Parameter Bailey McClellan

Natural Gas Heat Content (MMBtu/Mscf) 1,011.00 1,011.00

Fuel Use (scf/yr) 38,766 288,558

Natural Gas Density (lb/scf) 0.5825 0.5798

Sulfur in N.G (%) 0.0437 0.0435

Sulfur in N.G. (tpy) 0.00 0.04

% S as SO4 1.22% 1.33%

Sulfur Available for SO2 Formation [backing out Sulfur for SO4] 0.00 0.04

% S as SO2 98.78% 98.67%

SO2 (tpy) 0.01 0.07

Cost Effectiveness

Table 5

- 9 presents a summary of the cost effectiveness of switching from the current No. 6

fuel oil to the lower sulfur fuels . The cost effectiveness was determined by dividing the annual cost increase of fuel switching by the annual tons of SO 2 re duced. Table s 5

- 9 and

5

- 10 indicate that the cost of switching to lower sulfur No. 6 fuel oil is over 1, 000 /ton of

SO 2 reduced for Bailey Unit 1 and over $2,000/ton for McClellan Unit 1 ; switching to diesel is greater than $ 7 ,000/ton for Bailey Unit 1 and over $ 10 ,000/ton for McClellan Unit

1

, and switching to natural gas would save AECC money

. 9 Because fuel is a traded commodity, the price for fuel can vary greatly dependent upon factors such as supply, demand, as well as environmental and regulatory influences. The estimates provided by current fuel suppliers for lower sulfur fuel oils, while higher than the estimates provided in

2001

- 2003, are representative of today’s market available at Bailey and McClellan. 10

AECC believes for fuel switching analyses, it may not be prudent to compare pricing between natural gas and fuel oil due to the fuel price variability. I t i s important to note that

with fuel price variability the cost effectiveness values summarized above will vary from year to year. For instance, over the past ten years , there were periods of time when fuel oil

was less expensive than natural gas. During t hose times, the cost effectiveness numbers would yield different results

– with the natural gas cost effectiveness numbers being greater than the fuel oil cost effectiveness numbers.

This is demonstrated in Figure 5

- 1, below

, which is a historical graph o f costs of natural gas and fuel oil from years 2003 through 2012. In four out of the last ten years, natural gas prices have been higher than fuel oil prices.

9 Although AECC would save money under this scenario, the option to burn fuel oil must be maintained for electricity reliability purposes in case natural gas is not available (such as during a natural gas curtailment).

10 Current vendor estimates (not quote s) for fuel oil with varying levels of sulfur include: 0.5% sulfur

- $18/MMBtu, 1.0%

- $16.90/MMBtu, $1.5%

- $16.50/MMBtu, 2.0% $16.00/MMbtuArkansas Electric Cooperative Corporation 5

- 8 Trinity Consultants BART Analysis

– Bailey and McClellan

FIGURE 5

- 1. S UMMARY OF F UTURE A NNUAL SO 2 E MISSIONS A SSOCIATED WITH N ATURAL G AS$/MMBTU

Year Fuel Price Variability 2003

- 2012

Natural Gas

Fuel OilArkansas Electric Cooperative Corporation 5

- 9 Trinity Consultants BART Analysis

– Bailey and McClellan

T ABLE 5

- 9

. S UMMARY OF C OST E FFECTIVENESS FOR F UEL S WITCHING FOR CURRENT N O

. 6 F UEL O IL AT B AILEY U NIT 1

T ABLE 5

- 10

. S UMMARY OF C OST E FFECTIVENESS FOR F UEL S WITCHING FOR CURRENT N O

. 6 F UEL O IL AT M C C LELLAN U NIT 1 Average

Sulfur

Content A Baseline

SO 2
Emission

Rate B Controlled

SO 2
Emission

Rate G SO 2
Reduced Baseline

PM10

Emission

Rate B Controlled

PM10

Emission

Rate F PM10

Reduced Annual Heat Input Fuel Heating
Value (HHV) C Annual Fuel Usage Fuel Cost Differential

Cost of Fuel Switching SO 2 Cost

Effectiveness E PM10 Cost

Effectiveness E

(%) (tpy) (tpy) (tpy) (tpy) (tpy) (tpy) (MMBtu/yr) (MMBtu/Mgal)

or (MMBtu/Mscf) (Mgal/yr) ($/MMBtu) ($/yr) ($/ton) ($/ton)

Base Case A 1.81 37.03

- - 25.63

- - 39,193 155.00 252.86 16.00

- - - No. 6 - 1% 1.00

- 20.67 16.36

- 8.80 16.83 39,193 155.00 252.86 16.50 19,596 $ 1,198 1,165

No. 6 - 0.5% 0.50

- 10.23 26.80

- 2.75 22.88 39,193 155.00 252.86 17.75 68,587 $ 2,559 2,998

Diesel A 0.05

- 0.99 36.05

- 0.13 25.50 39,193 136.15 287.86 20.95 194,003 $ 5,382 7,608

Natural Gas

- - 0.01 37.02

- 0.26 25.37 39,193 1,011.00 38.77 6.19 (384,550) $ -10,387 -15,158

Average

Sulfur

Content A Baseline

SO 2
Emission

Rate B Controlled

SO 2
Emission

Rate SO 2
Reduced Baseline

PM10

Emission

Rate B Controlled

PM10

Emission

Rate F PM10

Reduced Annual Heat Input Fuel Heating
Value (HHV) C Annual Fuel Usage Fuel Cost Differential

Cost of Fuel Switching SO 2 Cost

Effectiveness PM10 Cost

Effectiveness

(%) (tpy) (tpy) (tpy) (tpy) (tpy) (tpy) (MMBtu/yr) (MMBtu/Mgal)

or (MMBtu/Mscf) (Mgal/yr) ($/MMBtu) ($/yr) ($/ton) ($/ton)

Base Case 1.38 209.43

- - 136.08

- - 291,733 155.00 1882.15 16.00

- - - No. 6 - 1% 1.00

- 153.61 55.81

- 76.70 59.38 291,733 155.00 1882.15 16.50 145,866 2,613 2,457

No. 6 - 0.5% 0.50

- 75.88 133.55

- 23.94 112.14 291,733 155.00 1882.15 17.75 510,532 3,823 4,553

Diesel A 0.05

- 7.31 202.11

- 1.10 134.98 291,733 136.15 2142.73 20.95 1,444,077 7,145 10,698

Natural Gas 0.04

- 0.07 209.35

- 1.36 134.72 291,733 1,011.00 288.56 5.97 -2,926,874 -13,980 -21,726

F Reductions in PM Species are based on default NPS profile. A Sulfur content of base case No. 6 fuel oil based on average of fuel burned in 2009- 2011. Sulfur content of diesel based on average sulfur in diesel burned at AECC Fitzhugh plant during the same timeframe since diesel is not burned at Bailey or McClellan.

C Higher heating value of residual oil based on data from supplier. Higher heating value of diesel is the average from Fitzhugh plant. Higher heating value of natural gas from 6.23.11 Bailey gas analysis and 7.12.11 gas analysis. B The baseline SO2 emission rates were calcauted using the average fuel usage from 2007 to 2011, the average heat content of the No. 6 fuel oil during that same time, and the average sulfur content of the fuel during that time. The baseline PM10 emission rates are the sum of the filterable PM species as predicted by the NPS workbook (based on total PM10 rates input to the workbook).Arkansas Electric Cooperative Corporation 5

- 10 Trinity Consultants

BART Analysis

– Bailey and McClellan 

### 5.4.2 E NERGY 

### I MPACTS AND 

### N ON



### - A IR 

### Q UALITY 

### I MPACTS

There are no energy or non

- air quality impacts associated with fuel switching to 1% sulfur
No. 6 fuel oil, 0.5% sulfur No. 6 fuel oil, or diesel. Switching to natural gas may have an impact during periods of natural gas curtailments. However, temporary permitted use of fuel oil would provide for electric grid reliability

. The ability to burn fuel oil at both Bailey and McClellan is important

– even if fuel oil is more expensive and difficult to burn than natural gas. During natural gas curtailments, natural gas infrastructure maintenance, and other emergencies, AECC rel ies on the fuel oil stored at the plants to maintain electrical reliability.



### 5.4.3 R EMAINING 

### U SEFUL 

### L IFE

The remaining useful li ves of Bailey Unit 1 and McClellan Unit 1 do not impact the annualized capital costs since it is assumed that fuel switching will no t require any significant capital costs , and thus for the purpose of this analysis there is nothing to capitalize that would require a review of the life of the equipment

.



## 5.5 E VALUATION OF 

## V ISIBILITY 

## I MPACT OF 

## F EASIBLE 

## SO 2 

## C ONTROLS

A final impact analysis was conducted to assess the visibility improvement associated with switching

fuels

. Table s 5

- 11 and 5

- 12 summarize the lb/hr emission rates that were modeled to reflect fuel switching as a control at Bailey and McClellan, respectivel y

. The SO 2 emission rate in lb/MMBtu associated with the combustion of a particular fuel was calculated by scaling the existing rolling 30

- day average emission rate from 2001 to 2003 by the ratio of the sulfur content of the new fuel and the

current maxim um annual average sulfur content from 2009 to 2011

.

The controlled 30

- day lb/MMBtu was converted to lb/hr by multiplying by the boiler design heat input. The calculation of the SO 2 emission rate for the one percent sulfur fuel oil for Bailey Unit 1 is provided for an example:



### Sulfur Sulfur MMBtu lb % 81

. 1 %) 1 % 81

. 1 (
* / 592

. 1 − = 0.880 lb/MMBtu



### hr MMBtu MMBtu lb / 350

, 1 * / 880

. 0 = 1,187.62 lb/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. Once the SO4 emission rate was determined, this rate was assumed to be IOR CPM and the emission rate was divided by the percentage of the total

PM that NPS workbook in dicates is IOR CPM to get the total PM rate. The total PM rate was then entered into the NPS workbook to get the emission rates for all of the PM species. The NO

x emission

rate was modeled at the baseline rate.Arkansas Electric Cooperative Corporation 5

- 11 Trinity Consultants

BART Analysis

– Bailey and McClellan T ABLE 5

- 11

. S UMMARY OF E MISSION R ATES M ODELED TO R EFLECT F UEL S WITCHING FOR SO 2 C ONTROL A T B AILEY U NIT 1

Bailey Unit 1 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)

1% sulfur fuel oil

No. 6 1,187.6 2.5 408.8 4.7 11.7 0.4 0.9 20.3

0.5 % sulfur fuel

oil No. 6 593.8 1.3 408.8 1.5 3.7 0.2 0.3 6.9

Diesel 59.4 0.1 408.8 0.1 0.2 0.0 0.0 0.4
Natural gas 0.5 0.3 443.8 0.0 0.0 7.4 2.6 10.3

T ABLE 5

- 12

. S UMMARY OF E MISSION R ATES M ODELED TO R EFLECT F UEL S WITCHING FOR SO 2 C ONTROL A T M C C LELLAN U NIT 1

McClellan Unit 1 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)

1% sulfur fuel oil

No. 6 2,317.1 4.3 579.8 8.0 19.9 0.8 1.6 34.6

0.5% sulfur fuel

oil No. 6 1,158.5 2.1 579.8 2.5 6.2 0.4 0.5 11.7

Diesel 115.9 0.2 579.8 0.1 0.3 0.0 0.0 0.7
Natural gas 0.6 0.3 423.9 0.0 0.0 7.9 2.7 10.9

Visibility improvement was evaluated by comparing the visibility impairment from the baseline scenario to the impairment for a control scenario. The baseline rate used to establish the baseline visibility impairment reflects a peak 24

- hour emission rate. Thus, it would make sense that the emission rates used in control scenarios would represent the peak emission rates associated with th e controls. That being said, control effectiveness is typically not evaluated on a 24

- hour basis. Typically, control effectiveness for EGUs for NO X /SO X is based on a longer term performance, with

30

- day being standard. While using rolling 30

- day average emissions rates gives a lower emission rate than using peak rates, this methodology of comparing the peak to average is consistent with other accepted BART methodologies.

Comparisons of the existing visibility impacts and the visibility impacts based on fuel switching

, 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 s 5

- 13 and 5

- 14 . The visibility improvement associated with fuel switching was calculated as the difference between the existing visibility impairment a nd the visibility impairment

for the various fuels as measured by the 98 th percentile modeled visibility impact

.Arkansas Electric Cooperative Corporation 5

- 12 Trinity Consultants BART Analysis

– Bailey and McClellan T ABLE 5

- 13

. S UMMARY OF M ODELED I MPACTS FROM SO 2 C ONTROL V ISIBILITY I MPACT A NALYSIS FOR B AILEY U NIT 1 (2001

- 2003)

Caney Creek Wilderness Upper Buffalo Wilderness Hercules Glades Wilderness Mingo NWRMaximum Impact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*Maximum Impact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*Maximum Impact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*Maximum Impact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*

B aseline Emission Rate

– (fuel oil) 0.970 0.330 8

- 0.696 0.348 7

- 0.687 0.368 6

- 1.592 0.379 12

-
1% sulfur fuel oil No. 6 0.544 0.193 1 41.52% 0.377 0.194 0 44.25% 0.408 0.206 0 44.02% 1.008 0.206 2 45.65%

0.5% sulfur fuel oil No. 6 0.333 0.142 0 56.97% 0.227 0.127 0 63.51% 0.279 0.135 0 63.32% 0.706 0.170 1 55.15%

Diesel 0.208 0.084 0 74.55% 0.156 0.069 0 80.17% 0.215 0.069 0 81.25% 0.429 0.095 0 74.93%

Natural gas 0.219 0.083 0 74.85% 0.170 0.072 0 79.31% 0.238 0.073 0 80.16% 0.443 0.102 0 73.09%

*Improvement 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 impacts 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 impacts shown in the table may be slightly different than the visibility improvement reflected in the table.Arkansas Electric Cooperative Corporation 5

- 13 Trinity Consultants BART Analysis

– Bailey and McClellan

T ABLE 5

- 14. S UMMARY OF M ODELED I MPACT S FROM SO 2 C ONTROL V ISIBILITY I MPACT A NALYSIS FOR M C C LELLAN U NIT 1 (2001

- 2003)

Caney Creek Wilderness Upper Buffalo Wilderness Hercules Glades Wilderness Mingo NWRMaximum Impact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*MaximumImpact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*Maximum Impact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*Maximum Impact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*

Baseline Emission Rate 3.015 0.622 24

- 1.323 0.266 5

- 0.662 0.231 2

- 0.547 0.228 2

-
1% sulfur fuel oil No. 6 2.671 0.537 18 13.67% 1.170 0.231 4 13.16% 0.562 0.202 1 12.55% 0.478 0.193 0 15.35%

0.5% sulfur fuel oil No. 6 1.722 0.322 8 48.23% 0.761 0.146 1 45.11% 0.294 0.115 0 50.22% 0.324 0.136 0 40.35%

Diesel 0.909 0.174 4 72.03% 0.382 0.073 0 72.56% 0.136 0.062 0 73.16% 0.190 0.080 0 64.91%

Natural gas 0.670 0.125 3 79.90% 0.258 0.052 0 80.45% 0.092 0.040 0 82.68% 0.132 0.058 0 74.56%

*Improvement 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 v isibility 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 percentile impacts show n 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.Arkansas Electric Cooperative Corporation 5

- 14 Trinity Consultants BART Analysis

– Bailey and McClellan As shown in Table 5

- 13

, based on visibility predictions from the CALPUFF modeling system

, fuel switching at Bailey Unit 1 will result in up to a 45.65

, 63.51

, 81.25 or 80. 1 6 percent improvement (depending on the Class I area ) to the existing visibility impairment attributable to this unit for fuel switching to 1% sulfur fuel oil, 0.5% sulfur fuel oil, diesel and natural gas, respectively

. Please note that despite th e varying levels of percent visibility improvement, the number of days of visibility impairment > Δ 0.5 dv is 0 in many of the control cases. For example, at Hercules Glades Wilderness there are 0 days of visibility impairment greater than > Δ 0.5 dv for the 1% sulfur fuel oil and also for the natural gas control although the visibility improvement varies from 44.02 % to 81.25 %.

As shown in Table 5

- 14, based on visibility predictions from the CALPUFF modeling system , fuel switching at McClellan Unit 1 will res ult in up to a 15.35

, 50.22

, 73.16 , or 82. 6 8 percent improvement (depending on the Class I area) to the existing visibility impairment attributable to this unit for fuel switching to 1% sulfur fuel oil, 0.5% sulfur fuel oil, diesel and natural gas, respect ively.



## 5.6 P ROPOSED 

## B ART FOR 

## SO 2

AE CC has determined that BART for Bailey Unit 1 and McClellan Unit 1 is fuel switching to using fuels with 0.5% sulfur or less (including natural gas)

. As mentioned in the Section 5.5 of this report,

fuel with a sulfur content of 0.5% or less will have visibility improvements in Class I areas of up to

63.51 % for Bailey and 50.22 % for McClellan.

When the BART limits become effective, Bailey and McClellan would burn the existing supply of

No. 6 fuel oil as the normal course of business dictates and in accordance with any operating restrictions enforced by ADEQ

. Future fuel purchases will be fuels of 0.5% sulfur content or less

.

While EPA might have some hesitation comparing the visibility impairment from the baseline scenario on a peak 24

- hour basis to visibility impairment due to control effectiveness on a 30

- day rolling average basis, the increased visibility improvement did no t have a significant bearing on AECC selecting to burn 0.5% sulfur fuel oil going forward. Because burning fuel oil is necessary in addition to using natural gas from a grid reliability perspective, AECC had to select a lower sulfur

fuel oil than currentl y received fuel oil. And because the cost/ton of the 0.5% sulfur is lower than for 1% sulfur, 0.5% sulfur is the appropriate option.Arkansas Electric Cooperative Corporation 6

- 1 Trinity Consultants BART Analysis

– Bailey and McClellan 

## 6. NO X 

## BART E VALUATION

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

- State Air Pollution Rule (CSAPR) trading program to use CSAPR to satisfy BART. Arkansas is one of the states with units subject to CSA PR 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 .” 11 Due to the nature of combustion controls, plants typically keep combustion controls in place and running year

- round, even if emission limitations are seasonal. Although Arkansas is an ozone season

- only state, units with combustion controls would run anyti me the unit is in operation.

An email dated June 28, 2012 from ADEQ stated, “ADEQ agrees CSAPR is better than BART and the subject

- to

- BART sources do not need to include NOx in their five

- factor analysis.” 12 Therefore, AECC is not including NOx analyses in the Bailey and McClellan five

- factor analyses.

On July 6, 201 2 EPA published a final rule of the Nebraska Regional Haze Federal Implementation Plan (FIP). 13 Nebraska is subject to CSAPR for annual SO 2 and NO

x . The FIP reviewed the Nebraska suggest BA RT for NO

x , but ultimately stated that because CSAPR satisfies BART, CSAPR controls will equate with BART in the state. 14

AECC is proposing to satisfy BART for NO

x by complying with CSAPR at Bailey Unit 1 and

McClellan Unit 1

. 15

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

- Specific Best Available Retrofit

Tech nology (BART) Determination, Limited SIP Disapprovals, and Federal Implementation Plans.” CFR Vol. 77, No. 110. Thursday, June 7, 2012, Rules and Regulations. Page 33651.

12 Email from Mary Pettyjohn of ADEQ to subject

- to

- BART unit operators dated June 28, 2012.

13 “Approval, Disapproval and Promulgation of Implementation Plans; State of Nebraska; Regional Haze State Implementation Plan; Federal Implementation Plan for Best Available Retrofit Technol ogy Determination.” CFR Vol. 77, No. 130. Friday, July 6, 2012. Page 40150.

14 Ibid, 40151.

15 This proposal was originally submitted on July 24, 2012. In response to CSAPR being vacated on August 21,
2012, AECC submitted a five

- factor analysis for NOx to ADEQ in September 2012 as an addendum to this analysis

.Arkansas Electric Cooperative Corporation 7

- 1 Trinity Consultants BART Analysis

– Bailey and McClellan 

## 7. PM 10 

## BART E VALUATION



## 7.1 I DENTIFICATION OF 

## A VAILABLE 

## R ETROFIT 

## PM 10 

## C ONTROL 

## T ECHNOLOGIES

PM 10 emissions are either “filterable” or “condensable”. Filterable PM 10 is generally considered to be particles less than or equal to 10 microns in diameter that are trapped by a filter during testing of exhaust gas . Condensable PM is material that is emitt ed in the vapor state but that condenses in the atmosphere to form particles. Filterable PM 10 emissions from fuel oil combustion depend predominantly on the grade of fuel oil fired. Combustion of lighter distillate oils results in significantly lower PM 10 formation than does combustion of heavier residual oils. Among residual oils, firing of No. 4 or No. 5 oil usually produces less PM 10 than does the firing of heavier residual oil. This is due to the higher ash and sulfur contents of residual oil compared to lighter oils.

Step 1 of the BART determination is the identification of all available retrofit PM 10 control technologies. The available retrofit PM 10 control technologies are summarized in Table 6

- 2 for Bailey Unit 1 and McClellan Unit 1.

T ABLE 7

- 1

. A VAILABLE PM C ONTROL T ECHNOLOGIES FOR B AILEY U NIT 1 AND M C C LELLAN
U NIT 1

PM 10 Control Technologies

Dry Electrostatic Precipitator (ESP) Wet Electrostatic Precipitator (ESP)

Fabric Filter

Wet Scrubber Cyclone Fuel Switching



## 7.2 E LIMINATE 

## T ECHNICALLY 

## I NFEASIBLE 

## PM C ONTROL 

## T ECHNOLOGIES

Step 2 of the BART determination is to eliminate technically infeasible PM control technologies that were identified in Step 1.



### 7.2.1 D RY 

### E LECTROSTATIC 

### P RECIPITATORS 

### (ESP)

A dry ESP operates by first placing a charge on the p articles through a series of electrodes, and then capturing the charged particles on collection plates. Particles from oil

- fired boilers tend to be sticky and small. Because of these properties and a general lack of existence in practice, a dry ESP is no t a good technological match for either Bailey Unit 1

or McClellan Unit 1

.



### 7.2.2 W ET 

### E LECTROSTATIC 

### P RECIPITATORS 

### (ESP)

A wet ESP operates similarly to a dry ESP but is a better technological match for oil

- fired

boilers because it is not sensitive to small and sticky particulates. A wet ESP utilizes water to collect and remove the particles, and will produce a waste

- water product. Flue gasArkansas Electric Cooperative Corporation 7

- 2 Trinity Consultants BART Analysis

– Bailey and McClellan leaving wet ESPs will be saturated and may result in a visual steam plume exiting the

stack. The estimated PM control eff iciency is up to 90% for a wet ESP

. 16 Wet ESP is a technically feasible option for control of PM 10 for Bailey Unit 1 and McClellan Unit 1.



### 7.2.3 M ECHANICAL 

### C OLLECTORS 

### (C YCLONES 

### )

Mechanical collectors, or cyclones, control particulates generated during soot blowi ng, during upset conditions, or when a heavy oil is fired. For these situations, high

- efficiency cyclonic collectors can achieve up to 85% control of particulate

. 17 This control is designed for the larger PM size fractions, and thus, when firing residual oi l, the control will not be as effective at controlling the smaller particles that are the primary source of visibility impairment. Further, when a clean oil is combusted, cyclonic collectors are not nearly so effective because of the high percentage of sm all particles (less than 3 micrometers in
diameter) emitted.



### 7.2.4 F ABRIC 

### F ILTER

Fabric filters work by filtering the PM in flue gas through filter bags. The collected particles are periodically removed from the bag through a pulse jet or reverse flow

mechani sm. Due to the sticky nature of particles from oil

- fired boilers and the associated hazard from flammability of their use, fabric filters are not used to control PM from boilers firing residual oil. Thus, fabric filters are not technically feasible for B ailey Unit 1 and

McClellan Unit 1

.



### 7.2.5 W ET 

### S CRUBBER

Wet scrubbers remove PM from flue gas by contacting it with a scrubbing liquid using one
of several approaches: spraying the gas stream with the liquid, forcing the gas stream through a pool of liquid, or by some other contact method. PM in the gas stream is captured in the scrubbing liquid. The PM

- laden scrubbing liquid is separated from the gas stream, and the resultant scrubbing liquid is treated prior to discharge or reuse in the plant.

Problems associa ted with scrubbers include corrosion issues, high power requirements, and

water

- disposal challenges. However, the use of wet scrubbers for Bailey Unit 1 and

McClellan Unit 1 is considered a technically feasible option. The estimated PM 10 removal

efficien cy for a wet scrubber is 50

- 60%. 18

While wet scrubbers are considered technically feasible, it is worth noting the wet scrubbers are not very efficient at controlling submicron size particles. When drops of water are suspended in a stream of air containing particles, such as they are in wet scrubbers, the air must go around the drops to pass through the scrubber. This creates streamlines of higher velocity air near each drop. For particles to be captured, they must push through these streamlines to the surface of the drop. Particles that are smaller than 1 micron are hardest to control because they follow the streamlines and avoid contact with

16 Ibid.

17 AP

- 42, Fifth Edition, Volume I, Chapter 1, Section 1.3.4.1

18 AP

- 42, Fifth Edition, Volume I, Chapter 1, Section 1.3.4.1Arkansas Electric Cooperative Corporation 7

- 3 Trinity Consultants BART Analysis

– Bailey and McClellan the drop. As particle size decreases, more energy is needed to force contact with the drops. This makes conventional scrubbers ineffective for particles smaller than a few microns. 19
While the majority of the PM emissions for Bailey Unit 1 and McClellan Unit 1 are not less than a few microns, particles of this size have the highest ability to impair visibility; thus, a wet scrubber may not be effective at controlling the particles that have the greatest ability to impair visibility.



### 7.2.6 F UEL 

### S WITCHING

Residual oil has inherent ash that contributes to the emis sions of filterable PM. Lower grades of fuel oil have less ash and ultimately lower filterable PM emissions. Filterable

PM emissions could be reduced by switching to a lower grade fuel oil or natural gas.

Section 5 discussed the option of fuel switching with respect to reducing SO 2 emissions.

D istillate fuel oil has only trace amounts of ash

. 20 It is estimated that filterable PM 10 emissions would be reduced in proportion to the reduction in ash content . B ased on the

reduction in ash content

, reductio ns of filterable PM 10 would be expected to be greater than

99%. Reductions in filterable PM 10 in No. 6 fuel oil are directly related to the sulfur
content of the fuel, as seen in AP

- 42, 1.3

- 1. The p ercent reduction in filterable PM 10 from fuel switching to natural gas is estimated from the reduced ash content in natural gas (trace
amount) as compared to current No. 6 fuel, 0.035% ash content

, for 99 % control efficiency.



## 7.3 R ANK OF 

## T ECHNICALLY FEASIBLE 

## PM 10 

## C ONTROL 

## O PTIONS BY 

## E FFECTIVENESS

Step 3 of the to p

- down control review is to rank the technically feasible options according to

effectiveness. Table 7

- 3 provides a ranking of the control levels for the controls listed in the previous section.

19 http://www.tri

- mer.com/q&a/comparing

- electrostatic

- precipitator.htm

20 Combustion

- Fossil Power Systems, J.G. Singer published by Combustion Engineer, Inc

. 21 AP

- 42, Fifth Edition, Volume I, Chapter 1, Section 1.3.4.1 , 9.19(S)+3.22. For Bailey, the average sulfur content of fuel delivered in

2009

- 2011 was 1.81%, and the avera ge fuel usage was 252,855 gal. For McClellan these values were 1.38% sulfur and 1,882,146 gal. Bailey: (9.19*(1.81)+3.22)*(252,855*10 3 /200) = 2.51 tpy. McClellan: (9.19*(1.38)+3.22)*(1,882,146*10 3 /200) = 14.97 tpyArkansas Electric Cooperative Corporation 7

- 4 Trinity Consultants BART Analysis

– Bailey and McClellan T ABLE 7

- 3. C ONTROL E FFECTIVENESS OF T ECHNICALLY F EASIBLE PM C ONTROL
T ECHNOLOGIES

Control Technology Control Efficiency 21

(%)

Fuel Switching ≤ 99%

Wet ESP ≤90
Cyclone 85%

Wet Scrubber 55%



## 7.4 E VALUATION OF 

## I MPACTS FOR 

## F EASIBLE 

## PM 10 

## C ONTROLS

Step four for the BART analysis procedure is the impact analysis. The BART determination guidelines list the four factors to be considered in the impact analysis:

▲ Cost of compliance

▲ Energy impacts

▲ Non

- air quality impacts; and

▲ The remaining useful life of the source



### 7.4.1 C OST OF 

### C OMPLIANCE

T he capital costs, operat ing costs, and cost effectiveness of wet ESPs, cyclones and wet

scrubbers have been estimated for Bailey Unit 1 and McClellan Unit 1 . The cost

effectiveness of fuel switching to 1% sulfur fuel oil, 0.5% sulfur fuel oil, diesel and natural

gas has also bee n estimated.

Control Costs The capital and operating costs of the wet ESP and wet scrubber were prepared by AECC using Electric Power Research Institute ’s (EPRI) IECCOST Software, and cyclone

estimates were derived from EPA estimates. 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 B of this report

.

Annual Tons Reduced

The a nnual tons reduced that were used in the cost effectiveness calculations were determined by subtracting the estimated controlled annual emission rates from the baseline
annual emission rates, as calculated from AP

- 42: 1.3

- 1. The controlled annual emissi on rates were estimated by reducing the existing annual emission rate by the control percentages shown in Table 7

- 3

.

21 AP

- 42, Fifth Edition, Volume I, Chapter 1, Section 1.3.4.1 , 9.19(S)+3.22. For Bailey, the average sulfur

content of fuel delivered in 2009

- 2011 was 1.81%, and the avera ge fuel usage was 252,855 gal. For McClellan these values were 1.38% sulfur and 1,882,146 gal. Bailey: (9.19*(1.81)+3.22)*(252,855*10 3 /200) = 2.51 tpy. McClellan: (9.19*(1.38)+3.22)*(1,882,146*10 3 /200) = 14.97 tpyArkansas Electric Cooperative Corporation 7

- 5 Trinity Consultants BART Analysis

– Bailey and McClellan Cost Effectiveness The cost effectiveness was determined by dividing the annualized cost by the annual tons

reduced. The costs effective ness analysis is summarized in Table s 7

- 4 and 7

- 5

.

Table 7

- 4 indicates that the cost effectiveness of switching to natural gas is over $ 5,000 /ton
for each boiler. Further, Table s 7

- 4 and 7

- 5 indicate that the cost effectiveness for all other controls is excessively expensive at $300,217/ton for fuel switching to diesel at McClellan

Unit 1 to $36,326,871/ton for a wet scrubber at Bailey Unit 1

.



### 7.4.1.1 E NERGY 

### I MPACTS AND 

### N ON



### - A IR 

### Q UALITY 

### I MPACTS

There are no energy or non

- air quality impacts associated with fuel switching, but there are impacts associated with wet ESPs and wet scrubbers. ESPs by design apply energy to the particles they are collecting. This energy usage can be significant, especially if the wet ESP is designed to control sub micron size particles where more energy is applied to collect more of the particles. Wet scrubbers also require a substantial amount of energy to force exhaust gases through the scrubber.

Both wet ESPs and wet scrubber generate wastewater streams that must either

be treated on

- site or sent to a waste water treatment plant. Further, the wastewater treatment process will generate a filter cake that would likely require land

- filling.



### 7.4.1.2 R EMAINING 

### U SEFUL 

### L IFE

The remaining useful li v e s of Bailey Unit 1 and M cClellan Unit 1 d o not impact the annualized capital costs of the wet ESP

, wet scrubber , or cyclone

because the useful li fe of the boilers is anticipated to be at least as long as the capital cost recovery period, which is 15 years. Further, t he remaining useful

li ves of Bailey Unit 1 and McClellan Unit 1 do not impact the annualized fuel

cost , since it is assumed that fuel switching will not require any capital costs

, and thus there is nothing to capitalize that would require a review of the life of

the e quipment

.Arkansas Electric Cooperative Corporation 7

- 6 Trinity Consultants BART Analysis

– Bailey and McClellan T ABLE 7

- 4. S UMMARY OF C OST E FFECTIVENESS FOR B AILEY U NIT 1 PM 10 C ONTROLS

T ABLE 7

- 5. S UMMARY OF C OST E FFECTIVENESS FOR M C C LELLAN U NIT 1 PM 10 C ONTROLS

Baseline

Emission

Rate Control Efficiency Annual Heat
Input A Controlled

Emission Rate PM 10 Reduced Capital Cost Total Annual Cost Cost

Effectiveness

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

Wet ESP 25.63 90.00 39,193 2.56 23.06 105,141,431 22,638,340 981,583

Wet Scrubber 25.63 55.00 39,193 11.53 14.09 140,957,713 50,150,862 3,558,286 Cyclone 25.63 85.00 39,193 3.84 21.78 989,479 1,188,630 54,570

No. 6 Fuel Oil - 1% 25.63

- 39,193 8.80 16.83

- 463,185 27,528

No 6. Fuel Oil - 0.5% 25.63

- 39,193 2.75 22.88

- 512,175 22,386

Diesel 25.63

- 39,193 0.13 25.50

- 637,592 25,004

Natural Gas 25.63

- 39,193 0.26 25.37

- 59,038 2,327

A Annual Heat Input derived for 2007-2011 average fuel usage times the heat content of No. 6 fuel oil

Baseline

Emission

Rate Control Efficiency Annual Heat
Input A Controlled

Emission Rate PM 10 Reduced Capital Cost Total Annual Cost Cost

Effectiveness

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

Wet ESP 136.08 90.00 291,733 13.61 122.47 151,509,333 32,605,907 266,237

Wet Scrubber 136.08 55.00 291,733 61.23 74.84 146,303,011 52,056,542 695,549 Cyclone 136.08 85.00 291,733 20.41 115.67 1,432,971 1,721,384 14,882

No. 6 Fuel Oil - 1% 136.08

- 291,733 76.70 59.38

- 3,149,652 53,044

No 6. Fuel Oil - 0.5% 136.08

- 291,733 23.94 112.14

- 3,514,317 31,338

Diesel 136.08

- 291,733 1.10 134.98

- 4,447,862 32,952

Natural Gas 136.08

- 291,733 1.36 134.72

- 76,911 571

A Annual Heat Input derived for 2007-2011 average fuel usage times the heat content of No. 6 fuel oilArkansas Electric Cooperative Corporation 7

- 7 Trinity Consultants BART Analysis

– Bailey and McClellan 

## 7.5 E VALUATION OF 

## V ISIBILITY 

## I MPACT OF 

## F EASIBLE 

## PM 10 

## C ONTROLS

A final impact analysis was conducted to assess the visibility improvement associated with wet ESPs

, wet scrubbers , and cyclones

. Note that fuel switching has impacts on both SO 2 and PM, as shown in Section 5 of this report . Section 4 of this report documented the existing visibility impairment

attributable to Bailey Unit 1 and McClellan Unit 1

.

In order to assess the visibility improvement associated with wet ESPs

, scrubbers, and cyclones t he

maximum short

- term PM 10 emission rate s ass ociated with these controls were modeled using

CALPUFF. The maximum short

- term PM 10 emission rate s associated with wet ESPs, scrubbers, and cyclones were calculated by reducing the uncontrolled yearly PM 10 emission rates , in Table 7

- 4, by the control perc entages shown in Table 7

- 3

. Tables 7

- 5 through 7

- 7 summarize the emission rates

that were modeled to reflect the wet ESPs, wet scrubbers, and cyclones , respectively. The emission rates for the pollutants shown in Tables 7

- 5 through 7

- 7 for NO X and SO 2 that are not PM are the same as in the baseline modeling

.

T ABLE 7

- 5

. S UMMARY OF E MISSION R ATES M ODELED TO R EFLECT W ET ESP FOR
PM 10 C ONTROL

Unit 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)
Bailey Unit 1 2,375.8 0.4 408.8 1.2 3.0 0.1 0.2 4.9

McClellan Unit 1 2,747.5 0.5 579.8 1.2 2.9 0.1 0.2 4.8

T ABLE 7

- 6

. S UMMARY OF E MISSION R ATES M ODELED TO R EFLECT W ET S CRUBBER FOR
PM 10 C ONTROL

Unit 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)
Bailey Unit 1 2,375.8 1.8 408.8 5.5 13.6 0.3 1.1 22.2

McClellan Unit 1 2,747.5 2.2 579.8 5.2 12.9 0.4 1.0 21.7

T ABLE 7

- 7

. S UMMARY OF E MISSION R ATES M ODELED TO R EFLECT C YCLONE FOR
PM 10 C ONTROL

Unit 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)
Bailey Unit 1 2,375.8 4.0 408.8 1.8 4.5 0.7 0.4 7.4

McClellan Unit 1 2,747.5 4.8 579.8 1.7 4.3 0.8 0.3 7.2

Comparisons of the existing visibility impacts and the visibility impacts for PM

- specific controls, excluding fuels switching which are included in Section 5

, 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 s 7

- 8 and 7

- 9 . The visibility improvement associated with PM controls was calculated as the difference between the existingArkansas Electric Cooperative Corporation 7

- 8 Trinity Consultants BART Analysis

– Bailey and McClellan visibility impairment and the visibility impairment for the control as measured by the 98 th percentile modeled visibility impact

.Arkansas Electric Cooperative Corporation 7

- 9 Trinity Consultants BART Analysis

– Bailey and McClellan T ABLE 7

- 8. S UMMARY OF M ODELED I MPACTS F ROM PM 10 C ONTROL V ISIBILITY I MPACT A NALYSIS FOR B AILEY U NIT 1 (2001

- 2003)

Caney Creek Wilderness Upper Buffalo Wilderness Hercules Glades

Wilderness Mingo NWRMaximum Impact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*MaximumImpact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*Maximum Impact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*Maximum Impact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*

Baseline Emission Rate 0.969 0.330 8

- 0.695 0.347 7

- 0.686 0.367 6

- 1.589 0.378 12

- Wet ESP 0.961 0.327 8 0.91% 0.687 0.343 6 1.15% 0.677 0.356 5 3.00% 1.572 0.371 12 1.85%

Wet Scrubber 0.964 0. 328 8 0.61% 0.690 0.345 6 0.58 % 0.681 0.360 5 1.91% 1.579 0.374 12 1.06%
Cyclone 0.965 0.328 8 0.61% 0.691 0.345 7 0.58% 0.682 0.361 5 1.63% 1.580 0.374 12 1.06%

*Improvement 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 impacts that include more decimal places than
what is shown in the table. Due to rounding of the baseline and controlled 98 th percentile impacts sho wn 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.Arkansas Electric Cooperative Corporation 7

- 10 Trinity Consultants BART Analysis

– Bailey and McClellan

T ABLE 7

- 9. S UMMARY OF M ODELED I MPACTS F ROM PM 10 C ONTROL V ISIBILITY I MPACT A NALYSIS FOR M C C LELLAN U NIT 1 (2001

- 2003)

Caney Creek Wilderness Upper Buffalo Wilderness Hercules Glades

Wilderness Mingo NWRMaximum Impact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*MaximumImpact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*Maximum Impact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*Maximum Impact (Δdv)98% Impact (Δdv)# Days > 0.5 ΔdvVisibility Improvement*

Baseline Emission Rate 3.007 0.621 22

- 1.319 0.266 5

- 0.660 0.230 2

- 0.546 0.227 2

- Wet ESP 2.977 0.617 21 0.64% 1.305 0.263 5 1.13% 0.656 0.227 2 1.30% 0.540 0.223 2 1.76%

Wet Scrubber 2.989 0.619 21 0.32% 1.311 0.264 5 0.75% 0.657 0.228 2 0.87% 0.542 0.224 2 1.32%
Cyclone 2.993 0.619 21 0.32% 1.313 0.265 5 0.38% 0.658 0.229 2 0.43% 0.543 0.225 2 0.88%

*Improvement 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 visib ility 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 percentile 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.Arkansas Electric Cooperative Corporation Trinity Consultants BART Analysis

– Bailey and McClellan As shown in Table 7

- 8 , the operation of wet ESPs results in an estimated 0.0 03 to 0. 00 4 Δdv improvement ( 0 .64 to 1.76 percent) of the 98 th percentile visibility impairment attributable to Bailey Unit 1 at the applicable Class I areas . Further, as shown in Table 7

- 8, the operation of wet scrubbers

results in an estimated 0.0 02 to 0. 003 Δdv improvement ( 0

. 3 2 to 1.32 percent) of the 98 th perce ntile visibility impairment attributable to Bailey Unit 1, and the operation of cyclones results in an

estimated 0.0 01 to 0.0 02 Δdv improvement ( 0. 3 2 to 0.88 percent) of the 98 th percentile visibility impairment attributable to Bailey Unit 1.

As shown i n Table 7

- 9 , the operation of wet ESPs results in an estimated 0.0 03 to 0. 011 Δdv improvement (0 .91 to 3.00 percent) of the 98 th percentile visibility impairment attributable to McClellan Unit 1 at the applicable Class I areas . Further, as shown in Table 7

- 9 , the operation of wet

scrubbers results in an estimated 0.002 to 0.00 7 Δdv improvement ( 0

. 58 to 1. 91 percent) of the 98 th
percentile visibility impairment attributable to McClellan Unit 1, and the operation of cyclones results

in an estimated 0.00 2 to 0.00 6 Δdv improvement (0. 58 to 1.63 percent) of the 98 th percentile visibility impairment attributable to McClellan Unit 1.



## 7.6 P ROPOSED 

## B ART FOR 

## PM 10

The cost effectiveness of all the PM controls evaluated for both the boilers is greater than $ 5

, 0 00/ton,

and for most controls is much greater than $5,000/ton. Based on the low PM 10 emission from the boilers (less than 15 tpy for either Bailey Unit 1 or McClellan Unit 1 ) and the related low improvement to t he visibility impairment attributable to the boilers based on the application of the controls ( only up to 0.0 11 Δdv)

, none of the controls are determined to satisfy BART. Thus, there are no fuel changes or add

- on controls proposed as BART for PM 10 for Bailey Unit 1 or McClellan Unit

1

. 22

22 However, AECC is proposing fuel swi tching to 0.5% sulfur fuel oil as BART for SO 2

.Arkansas Electric Cooperative Corporation Trinity Consultants BART Analysis

– Bailey and McClellan 

## A PPEN DIX 

## A

PM 10 

### C ONTROL 

### C OST 

### C ALCULATIONSArkansas Electric Cooperative Corporation Trinity Consultants BART Analysis

– Bailey and McClellan 

## A PPENDIX 

## B

M ODELING 

### P ROTOCOL