## Appendix B. Technical Support Document for Arkansas Regional Haze Best Available Retrofit Technology

(BART) Modeling Protocol Review

Prepared by:

Michael Feldman

March 201 5B

- ii 

## Table of Contents

Table of Contents

................................ ................................ ................................ ................ ii Chapter 1: Introduction

................................ ................................ ................................ ....... 3 Chapter 2: BART Guidelines and Modeling Protocols

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

2.1 Background and Introduction

................................ ................................ ................... 5 2.2 Calculation of Visibility Impact

................................ ................................ ................ 7 2.2.1. IMPROVE Equation

................................ ................................ ......................... 8 2.2.2 Revised IMPROVE Equation

................................ ................................ ............ 8 2.2.3 Deciview Impact C alculation

................................ ................................ ........... 10 2.3. CALMET/CALPUFF modeling protocol

................................ .............................. 11

2.4. EPA Conclusion

................................ ................................ ................................ ..... 14B

- 3 

## Chapter 1: Introd

u c tion

Arkansas submitted a Regional Haze ( RH ) State Implementation Plan ( SIP ) to
address the first regional haze implementation period on September 23, 2008, and August 3, 2010, and submitted supplemental information on September 27, 2011. On March 12, 2012, the EPA partially approv ed and partially disapproved the RH SIP submitted by Arkansas (77 FR 14604). This included a disapproval of some of the Best Available Retrofit Technology ( BART ) determinations made by Arkansas. See the Technical Support Document ( TSD ) that accompanied tha t action for our review of the visibility modeling submitted by Arkansas Department of Environmental Quality ( ADEQ ) to support the original BART determinations. Following EPA’s partial disapproval action, the ADEQ worked closely with the BART facilities an d with EPA Region 6 to revise the RH SIP. Trinity Consultants, on behalf of each BART facility, performed five

- factor analyses to correct the State’s BART decisions that were disapproved by the EPA. As part of our proposed Federal Implementation Plan ( FIP ) , w e have reviewed the final version of each BART analysis performed by Trinity Consultants that has been provided

to us

. ADEQ developed a visibility modeling protocol in support of their 2008 submitted

RH SIP. 1 ADEQ worked with EPA and Trinity to update this modeling protocol in

2012. 2 In general, the revisions to the modeling protocol were made to utilize an existing meteorological database that incorporated monitored surface and aloft measurements, and the use of the revised IMPROVE equation to calcula te extinction. Th is visibility modeling protocol was followed in the technical work performed by Trinity Consultants 3
for each facility and is described in detail in this document. Modeled emission rates and results of visibility modeling for specific BART sources are discussed under the full five

factor BART analysis in the main T echnical Support Document for th is proposed rulemaking

.

AECC Bailey Unit 1 and McClellan Unit 1

, American Electric Power (AEP ) Flint

Cree k Unit 1

, Entergy White Bluff Power Plant Units 1 and 2

, Entergy Lake Catherine

Unit 4 , and Domtar Ashdown Paper Mill No. 1 and No. 2 power boilers have been determined to be subject

- to

- BART. See 77 FR 14604. Revised BART modeling was performed by Trinit y for all the BART facilities following the same general modeling protocol and using the same meteorological data inputs as discussed in the following chapter.

1

. Draft Best Available Retrofit Technology (BART) Modeling P rotocol June 7, 2006. Available as Appendix 9.2A of the 2010 Arkansas Regional Haze SIP revision and in the docket for this proposed rulemaking.

2 July 26, 2012 ADEQ Best Available Retrofit Technology (BART) Modeling Protocol Addendum and April 26 , 2012 letter from Guy Donaldson, Chief of Air Planning Section at EPA Region 6 , to Anthony

Davis , ADEQ. A copy of this BART Modeling Protocol Addendum and letter can be found in the docket for this proposed rulemaking

. 3 A copy of the final version of each BART analysi s performed by Trinity Consultants on behalf of the BART sources, upon which our analysis is largely based, can be found in the docket for this proposed rulemaking.B

- 4

Table 1

- 1. Subject

- to

- BART sources

FACILITY NAME UNIT ID

American Electric Power

– Flint

Creek Plant SN

- 01

- Boiler

AR Electric Cooperative

– Bailey Generating Station SN

- 01

– Boiler

AR Electric Cooperative

– John L. McClellan Generating Station SN

- 01

- Boiler

Entergy

– Lake Catherine SN

- 02

– Unit 4 Boiler

Entergy

– White Bluff SN

- 01

– Unit 1

SN

- 02

– Unit 2

SN

- 05

– Auxiliar y Boiler

Domtar

– Ashdown SN

- 03

– #1 Power Boiler

SN

- 05

- #2 Power BoilerB

- 5



## Chapter 2: BART Guidelines and Modeling Protocols

2.1 Background and Introduction

The BART analysis includes engineering and modeling methods and procedures

used to determin e the appropriate controls for the subject

- to

- BART units to reduce the source’s contribution to pollutant concentrations that result in visibility impairment in the surrounding Class I areas. The final factor to consider under EPA ’ s BART Guidelines is

the degree of visibility improvement from the BART control options 4

. The BART guidelines recommend use of the CALPUFF air quality dispersion model to estimate the visibility improvements at each Class I area, typically within roughly a 300 km (186 mile) radi us of the source, of alternative control technologies, and to compare these to each other and to the impact of the baseline, or current , source configuration. The four

Class I Areas within approximately 300 km of the facili ties were included in the

modeli ng analys e s. These Class I areas are listed in Table 2

- 1 . The location o f the

facilities and Class I areas are shown in the map in Figure 2

- 1. We note that, as shown in

F igure 2

- 1, Sipsey Wilderness is more than 300 km from any of the evaluated sources

and was not included in the revised visibility impact modeling evaluations.

Table 2

- 1

. Class I Areas

Class I Area State Agency IMPROVE

monitor
Caney Creek Wilderness Area AR USFS CACR

Hercules G l a des Wilderness Area MO USFS HEGL Upper Buffalo Wilderness Area AR USFS UPBU Mingo Wilderne ss Area MO FWS MING

4 59 FR 39104, 39170 (July 6, 2005).B

- 6

Figure 2

- 1. Location of Sources and Class I Areas

Trinity Consultants conducted the updated visibility modeling for all the subject

to

- BART sources and this modeling was reviewed by EPA as part of our BART

determination

. The revised modeling performed by Trinity Consultants and described in this document utilized an updated modeling protocol developed by ADEQ and Trinity

after discussions with EPA. 5 The modeling protocol is discussed here. See the TSD and

the Federal Re gister notice for this proposed rulemaking for discussion of modeled

emissions and visibility modeling resul ts.

Under the BART guidelines 6 , the measure of the visibility improvement to be used in comparisons between various control scenarios is the 98 th percentile of impact s expressed as 24

- hour averages of delta deciviews relative to natural background, as estimated using the CALPUFF air quality modeling system. The meaning of this is

5 July 26, 2012 ADEQ Best Available Retrofit Technolo gy (BART) Modeling Protocol Addendum and April 26, 2012 letter from Guy Donaldson, Chief of Air Planning Section at EPA Region 6, to Anthony Davis, ADEQ. A copy of this BART Modeling Protocol Addendum and letter can be found in the docket for this proposed rulemaking.

6 Appendix Y to 40 CFR 51.B

- 7

described next, followed by particulars of the application of CALPUFF to the individual

B ART determinations.

Table 2

- 2

. CALPUFF system modeling components utilized by Trinity

Processor Version Level

TERREL 3.3 030402

CTGCOMP 2.21 030402

CTGPROC 2.63 050128

MAKEGEO 2.2 030402

CALMET 5.53a 040716

CALPUFF 5.8 070623

POSTUTIL 1.3 030402

C ALPOST 6.221 080724



### 2.2 Calculation of Visibility Impact

Under the RHR, visibility is measured in deciviews. Visibility is traditionally described in terms of visual range in kilometers or miles. However, the visual range scale does not correspond t o how people perceive visibility: a given increase in visual range is perceived differently depending on how good the original visibility was (that is, it is not on a linear scale). The deciview scale is designed to address this problem. It is

linear wit h respect to perceived visual changes over its entire range, analogous to the decibel scale for sound: a given change in deciviews will be perceived as the same amount of visibility change, whatever the original visibility was. The defining equation

is:

deciviews = 10*ln(b ext / 10) (1)

where ln is the natural logarithm, and extinction b ext is the fraction of light scattered out of a viewing path. Extinction increases with the amount of pollution (b ext is in units of

1/Mm , “inverse megameters”). Lower deciview values represent better visibility, more pristine atmospheres, and greater visual range, while increasing deciview values represent increasingly poor visibility. An increase of 1 deciview corresponds to about a 10%

increase in extinction. (Deciviews are related to the more traditional visual range according to dv = 10*ln(391 / visual range)). An eligible BART source with a predicted impact of 0.5 dv or more of impairment in a Class I area “contributes” to visibility impairment and is subje ct to BART. 70 FR 39104, 39121 (July 6, 2005).

Under the BART guidelines, deciviews are estimated using the CALPUFF air quality model. CALPUFF predicts 24

- hour average pollutant concentrations based on source emissions and how they disperse in the atm osphere. The CALPUFF modeling includes source emissions of the following visibility

- impairing pollutants: SO 2 , SO 4 , NO
x , secondary organic aerosol (SOA), fine particulate matter (PMF), coarse particulate matter (PMC), and elemental carbon (EC). CALPUFF i ncorporates a semi

- empiricalB

- 8

chemical module that simulates the conversion of SO 2 to particulate sulfate and NO
x to particulate nitrate, at a rate dependent on meteorological conditions and background

ozone concentration. These concentrations are converte d to deciviews by the CALPOS T
post

- processor in two steps.



### 2.2.1 . IMPROVE Equation

Under the original IMPROVE 7 equation, extinction ( b ext ) is estimated from the predicted concentrations of various pollutants:

b ext = 3 * f(RH) * [sulfate] + 3 * f( RH) * [nitrate] + 4 * [organic mass] + 10 * [ elemental carbon ] + 1 * [ fine soil ] + 0.6 * [ coarse mass ]

+ 10

The 10 is for Rayleigh scattering

, which is due to the interaction of light with molecules of air itself with no pollutants

. The f(RH ) is a water growth factor for sulfate and nitrate ; i ts value depends on relative humidity (RH) , ranging from 1 at low humidity to 18 at 98% humidity.



### 2.2.2 Revised IMPROVE Equation

The Trinity revised modeling used the “revised” IMPROVE equation 8 to cal culate light extinction. Sometimes the revised IMPROVE equation is called the “New” Improve equation. The revised IMPROVE equation is used to convert measured or modeled concentrations into extinction for each pollutant chemical species, and then total

t hem up, accounting for the effect of relative humidity

.

Revised IMPROVE equation:

b ext = 2.2 * f

s (RH) * [small sulfate] + 4.8 * f L (R H) * [large sulfate] + 2.4 * f

s (RH) * [small nitrate] + 5.1 * f L (RH) * [large nitrate] + 2.8 * [small organic mass] + 6. 1 * [large organic mass] + 10 * [ elemental carbon ] + 1 * [ fine soil ]

7 Interagency Monitoring of Protected Visual Environments ( IMPROVE) is a network of monitors in various Class I Areas, established to assess visibility impairment and its causes. The IMPROVE equation

is used to c onverted monitored concentrations into extinction, a measure of visibility. See: http://vista.cira.colostate.edu/improve/

8 Pitchford, M. L., W. C. Malm, B. A. Schichtel, N. Kumar, D. Lowenthal and J. L. Hand, Revised algorithm for estimating light extin ction from IMPROVE particle speciation data, Journal of the Air & Waste Management Association, 57 , 1326

- 1336, 2007.B

- 9 + 1.7 * f

ss (RH) * [sea salt] + 0.6 * [ coarse mass ] + Rayleigh scattering (site

- specific) + 0.33 * [NO 2 (ppb)]

Sulfate is assumed to be all “large sulfate” if total sulfate is over 20 μg/m 3 , otherwise its fraction of the total is assumed to increase uniformly between 0 and 1 when the total i s in the range between 0 and 20 (i .e. large sulfate = (total sulfate/20)*total ) . A similar definition applies for nitrate and for organic mass. Th e organic mass is assumed to be 1.8 times the organic carbon mass that is measured by IMPROVE monitors, an increase over

the old 1.4. Sea salt is estimated as 1.8 * [chloride] (or chlorine if chloride not available)

. T he f
s , f L , f
ss are water growth facto rs for small (“S”) and large (“L”) fractions of sulfate and nitrate, and for sea salt (“SS”). Their values depend on relative humidity, ranging from 1 at low humidity to over 5 at 95% humidity. Rayleigh scattering is due to the interaction of light with molecules of air itself with no pollutants.

The IMPROVE program revised the IMPROVE equation after a scientific assessment of its implications for regional haze planning to reduce biases in light extinction estimates compared to the old algorithm 9

. In p articular, when compared to nephelometer direct measurements of visibility extinction, the original IMPROVE equation over

- predicts for low extinction conditions and under

- predicts for high

extinction. These biases have direct relevance for estimates for t he worst 20% visibility days that are used to assess visibility impact. The new equation shows broader scatter overall, but less bias in matching visibility measurements under high and low visibility conditions. The split between small and large particle s was the main factor in reducing

the biases. The revised IMPROVE equation has less bias, is more refined, accounts for more pollutants and pollutant sizes , incorporates more recent data, and is based on

considerations of relevance for the calculations nee ded for assessing progress under the

R egional H aze R ule

.

EPA 2007 guidance 10 states that the use of either the IMPROVE or the revised

IMPROVE equation is acceptable provided that the same algorithm is utilized for both

the base and future extinction calcul ations. EPA believes it is appropriate to use the revised IMPROVE equation and that this is the preferred method

.

9 Revised IMPROVE algorithm for Estimating Light Extinction from Particle Speciation Data , IMPROVE, January 2006 ( http://vista.cira.colostate.edu/improve/Publications/GrayLit/gray_literature.htm ) ; Hand, J.L., Douglas, S.G., 2006, Review of the IMPROVE Equation for Estimating Ambient Light Extinction

Coefficients

– Final Report ( http://vista.cira.colostate.edu/improve/Publications/GrayLit/016_IMPROVEEeqReview/IMPROVEeqRevi

ew.htm )

10 Guida nce on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze , EPA

- 454/B

- 07

- 002

, April 2007, EPA OAQPS; ( http://www.epa.gov/ttn/scram/guidance/guide/final

- 03

- pm

- rh

- guidance.pdf )B

- 10



### 2.2.3 Deciview Impact Calculation

In the second CALPOST step this extinction is converted to deciviews, using the defining equation (eq uation 1) for deciviews. The delta deciviews (Δdv) represents the impact on visibility in deciviews of the source being evaluated, and is also provided by CALPUFF. It is the change, or “delta”, between deciviews with and without the source.

Under the BA RT guidelines, delta deciviews is the difference between deciviews including the impact of the source and natural background, and deciviews of the natural background alone. Each modeled day and location in the Class I area will have an

associated delta de ciview. For each day, the model finds the maximum visibility impact of all locations (receptors) in the Class I area. From among these daily values, the BART guidelines recommend use of the 98th percentile, roughly equivalent to the 8 th highest day, visi bility impacts expressed as 24

- hour averages of delta deciviews relative to natural background, as estimated using the CALPUFF air quality modeling system for comparing the base case and the effects of various controls. The 98th percentile is

recommended rather than the maximum value to avoid undue influence from unu sual meteorological conditions when CALPUFF is executed according to EPA’s guideline on Air Quality Models (40 CFR Part 51 Appendix W)

. 11

T he BART guidelines recommend that impacts of sources b e estimated in deciviews relative to natural background. The Trinity evaluations used average background

concentrations (Table 2

- 3 ) and relative humidity adjustment factors (Table s 2

- 4, 2

- 5, and

2

- 6) from the Federal Land Manag ers’ Air Quality Related Values Work Group (FLAG)

Phase I Report 12 for use with the revised IMPROVE equation (“Method 8”)

.

Table 2

- 3 . Natural Background Concentrations used for “Method 8”

Class I Area CALPOST control input parameters (μg/m 3 )

B KSO4 BKNO3 BKOC BKEC BKSOIL BKCM BKSALT

Ammonium

sulfate Ammoni um

nitrate Organic

carbon Elemental

carbon Soil Coarse

mass Sea salt

Caney Creek 0.23 0.10 1.80 0.02 0.50 3.00 0.03
Upper Buffalo 0.23 0.10 1.80 0.02 0.50 3.00 0.03

Hercules

Glades 0.23 0.10 1.80 0.02 0.50 3.00 0.02

Mingo 0.23 0.10 1.83 0.02 0.51 3.05 0.04

11 In our March 12, 2012, final action on the 2010 Arkansas RH SIP revision we noted that the original meteorological databases generated by CENRAP and used by Arkansas to cond uct its modeling analyses did not include observations as EPA guidance recommends. Thus, in its visibility modeling evaluation s Arkansas used the maximum value ( i.e. 1 st high value) of modeled visibility impacts instead of the 98 th percentile value ( i.e. 8 th high value). The use of the maximum modeled values was agreed to by EPA, representatives of the Federal Land Managers, and CENRAP stakeholders.

12 Federal Land Managers’ Air Quality Related Values Work Group (FLAG) Phase I Report

— Revised (2010) Natural R esource Report NPS/NRPC/NRR

— 2010/232 ( http://www.nature.nps.gov/air/Pubs/pdf/flag/FLAG_2010.pdf )B

- 11

Table 2

- 4

. f

L (RH) Large RH Adjustment Factors

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Caney Creek 2.77 2.53 2.37 2.43 2.68 2.71 2.59 2.6 2.71 2.69 2.67 2.79
Upper Buffalo 2.71 2.48 2.31 2.33 2.61 2.64 2.57 2.59 2.71 2.58 2.59 2.72

Hercules

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

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

Table 2

- 5 . f

S (RH) Small RH Adjustment Factors

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Caney Creek 3.85 3.44 3.14 3.24 3.66 3.71 3.49 3.51 3.73 3.72 3.68 3.88
Upper Buffalo 3.73 3.33 3.03 3.07 3.54 3.57 3.43 3.5 3.71 3.51 3.52 3.74

Hercules

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

Mingo 3.74 3.38 3.07 2.97 3.39 3. 52 3.57 3.64 3.72 3.47 3.43 3.74

Table 2

- 6 . f

SS (RH) Sea Salt RH Adjustment Factors

Class I Area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Caney Creek 3.9 3.52 3.31 3.41 3.83 3.88 3.69 3.68 3.82 3.76 3.77 3.93
Upper Buffalo 3.85 3.47 3.23 3.27 3. 72 3.78 3.69 3.7 3.84 3.64 3.67 3.86

Hercules

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

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



### 2.3 . CALMET

/CALPUFF modeling protocol

Trinity Consultants conducted model ing for each of the facilities of interest according to modeling protocols submitted and reviewed by EPA. 13 The modeling analys e s generally followed the BART protocol developed by CENRAP

. 14 However, unlike previous modeling conducted for these sources, s ur face and upper air observations were utilized (NO OBS = 0) for th e revised source

- specific modeling, consistent with EPA and FLM recommendations. Trinity Consultants used an existing CALMET data set that utilized CALMET v5.53a which is an earlier regulato ry version and compatible with the regulatory version of CALPUFF (v5.8)

. In discussions with ADEQ to develop a revised BART modeling protocol, EPA identified the availability of this existing

dataset. 15 This data set was generated by Trinity Consultants fo r use in BART analyses

13 A copy of the final version of each BART analysis performed by Trinity Consultants on behalf of the BART sources, upon which our analysis is largely based, c an be found in the docket for our proposed rulemaking.

14 CENRAP BART Modeling Guidelines, T. W. Tesche, D. E. McNally, and G. J. Schewe (Alpine Geophysics LLC), December 15, 2005 ( http://www.deq.state.ok.us/aqdnew/RulesAndPlanning/Regional_Haze/SIP/Appen dices/index.htm )

15 April 26, 2012 letter from Guy Donaldson, Chief of Air Planning Section at EPA Region 6, to Anthony Davis, ADEQ.B

- 12

of sources in Oklahoma. 16 The modeling protocol for this CALMET data set is available in the docket for this action and describes in full the modeling domain and input data utilized in developing the meteorological dataset. We note that because this CALMET data was prepared using both surface and upper air observations (NO OBS = 0), consistent with our guidance, we recommend the use of the 98 th percentile or 8 th highest value in analyzing the visibility benefits anticipated due to t he use of controls , rather than the maximum value utilized in the previous modeling analysis

.

Table 2

- 7 shows selected CALMET settings used in the Trinity evaluation for modeling visibility impacts from these facilities. R1MAX and R2MAX represent the

r adius of influence of surface and upper air observations, respectively. R1 (R2) defines the distance from an observation at which the surface (upper air) observation and the initial wind field are equally weighted and is typically set to half the value of R1MAX (R2MAX). EPA and FLMs recommend the use of higher values for R1MAX (100 km) and R2MAX (200 km) based on tracer evaluations and testing

. 17 EPA is aware of these deviations and weighed the potential differences that may occur due to these deviations with the additional work and computing resources that would be required to redo the analyses. G iven the time and resource constraints, EPA concluded that these deviations were acceptable and offered to share this dataset with ADEQ and Trinity Consultants for the purpose of evaluating visibility benefits due to the use of controls as part of a full

five

- factor BART analysis for subject

- to

- BART sources in Arkansas.

16 The modeling protocol for this CALMET data set was included as an appendix to each BART analysis prepared by Trinity Consu ltants and can be found as: CALMET DATA Processing Protocol BART Determination Oklahoma Gas and Electric, Prepared by Trinity Consultants, January 23, 2008.

17 Memorandum from Tyler Fox (EPA OAQPS) “Clarification on EPA

- FLM Recommended Settings for CALMET,” August 31, 2009B

- 13

Table 2

- 7 . Selected CALMET Settings Used

Option Description EPA default Trinity Consultant s

version CALMET version 5.8 .4 , level 130731 5.53a, level 040716

NOOBS No Observation Mode 0 0

ICLOUD gridded cloud fields 0 0

IWFCOD diagnostic winds 1 1

IFRADJ Froude wind adj. 1 1

IKINE kinematic effects 0 0

IOBR O'Brien vertical wind adj. 0 0

I SLOPE slope flows 1 1

IEXTRP extrapolate wind to upper air

- 4

- 4

ICALM extrapolate calm to upper air 0 0

BIAS layer biases sfc vs. UA NZ*0 NZ*0

IPROG gridded initial prognostic 0 14

RMAX1 max surface radius of influence NA 20

RMAX2 max aloft radius o f influence NA 50

RMAX3 max over

- water radius of influence. NA 100

RMIN min wind radius of influence. 0.1 0.1

RMIN2 min dist sfc winds extrap 4 4

TERRAD terrain radius of in influence NA 10

R1 weight surface Step 1 vs. obs NA 10

R2 weight aloft Step 1 vs. obs NA 25

ITPROG 3D T from obs or prognostic 0 0

TRADKM radius of influ. for T interp. 500 500

IAVET spatial T averaging 1 1

JWAT1 starting land use for T interp. over water 999 55

JWAT2 ending land use for T interp. over water 999 55

The Trin ity evaluation used the regulatory version of CALPUFF (v5.8) 18 and CALPOST (v6.221). For visibility calculations, the pollution concentration predictions of CALPUFF are used in post

- processing. First, POSTUTIL considers ammonia background concentrations, temperature, and humidity to determine how much nitrate ends up as particulate ammonium nitrate; this is to reflect the competition between sulfate and nitrate for available ammonia and is referred to as “Nitrate Repartitioning.”

CALPOST then converts the predicted pollutant concentrations into extinction using the revised IMPROVE equation followed by converting the estimated total extinction into

deciviews.

The refined source

- specific modeling used a constant value of 3 ppb background

concentration of amm onia for the domain during the modeling period. Hourly ozone observational data provided by ADEQ to Trinity over the 2001

- 2003 timeframe were used to define background ozone concentrations.

18 CALPUFF v5.8 was the regulatory version at the time the modeling protocol was developed. On December 4, 2013, EPA approved an update to v5 .8.4 that contains bug fixes to the previous version. See December 3, 2013 CALPUFF Update Memo for a discussion of model changes.B

- 14



### 2.4. EPA C

onclusion

We find the modeling protocol to be consiste nt with EPA and FLM guidance and acceptable for the purposes of evaluating the anticipated visibility benefit due to the use of controls at the subject

- to

- BART facilities in Arkansas.