### TABLE 2-5. NOMENCLATURE FOR 

### PMEMISSIONS SPECIATION ANALYSIS

Nomenclature Description

TSP Total suspendedpaticulate, filterable PM with an aerodynamic diameter < 30 pm PMIO Filterable particulate matter with an aerodynamic diameter < 10 pm PM6-10 Filterable particulate matter with an aerodynamic diameter > 6 and < 10 pm PM2.5-6 Filterable particulate matter with an aerodynamic diameter > 2.5 and < 6 p PM2.5 Filterable particulate matter with an aerodynanicdiameter < 2.5 pm PMl.?i.-2.5 Filterable particulate matter with an aerodynamic diameter > 1.25 and < 2.5 p PMI-1.25 Filterable particulate matter with an aerodynamic diameter > 1.0 and < I 25pn3 PMo.63-I Filterable particulate matter with an aerodynanicdiameter > 0.625 and < I .O p3 PMOS-0.625 Filterable particulate matter with an aerodynamic diameter > 0.5 and < 0.625pm CPM Condensableparticulate matter (organic and inorganic) POC Primary organic condensable enussions PIC Primary inorganic condensable enlissions TPMIo Filterable Ph410 

### + CPM TPM2.s FilterablePM2.,

### + CPM

These PM classifications are necessary in the Class 

### I visibility analysis because each type of PM has a different effect on visibility as defined by the extinction efficiency. The emission rates of each of these particulate phases and size categories are modeled in CALPUFF and grouped according to visibility-affecting characteristics as was illustrated in Figure 2-1. Elemental carbon (EC), if emitted, typically results from unburned carbonaceous he1and is distinguished from other PM types because of its light extinction characteristics. Coarse PM (PMC) comprises PM7.5-6 and PM6-10. Fine PM (PMF) comprises PM0.5-0.625, PM0.625-1, PM1-1.25, and PM1.15-2.5. CPM comprises both organic and inorganic species. The organic fraction of CPM is represented in CALPUFF primary organic condensable (POC) emissions, which are direct emissions but are sometimes referred to as secondary organic aerosols (SOA) by convention and due to the representation of their visibility-affecting characteristics in the light extinction equation. Primary emissions of inorganic CPM (PIC) may contain hygroscopic sulfates (SO4)and nitrates 

### (NO3),as well as other salts (e.g., carbonates) that lllay be hygroscopic to a lesser degree, and hence are considered in a manner similar to PMF (i.e., as soil) in terms of light e~tinction.~ Therefore, it can be important to distinguish inorganic CPM since hygroscopic species (i.e., sulfate) will have a greater extinction coefficient than non-hygroscopic (i.e., non-sulfate) species. Due to the low sulfur content of natural gas, BP estimates primary sulfate emissions as 5% of SO, emissions. Therefore, the remaining condensable, inorganic species from natural gas combustion are non-hygroscopic PIC species.

Table 

### 2-6 summarizes the grouping of PM species and extinction coefficient of each component. -4discussion of the PM speciation methodologies for each of the BART-eligible sources at the Decatur Works is presented in the following sections of this protocol.

The US.EPA's Guidarice for TrochingProgress under the Regional Haze Rule identifies carbonates, magnesium oxides, and sodium oxides as components of the soil mass concentration when analyzed to assess natural background visibiliw (Malm 1994).

BP Decatur Works BART Applicability Analysis 15 Trinity ConsultantsExtinction Modeled PM Output Coefficient categoryt Components categoryi (m2k)



### I PIC Non-hvmosco~jc. ~rimarv inorganic condensable (PIC) emissions Primary inorganic condensable emissions of sulfates SO4 ?flRH)

........................................................................................................................................................................................................................................... Primarv organic condensable emissions SOA 4 Unconlbusted carbonaceous fuel EC 10 

## I

+ Modeled PM Category denotes the input of emissions data into CALPUFF. 

### : Output Category denotes the assi-nment of modeled emissions in POSTUTIL for the visibility calculations in CALPOST.

BP operates one BART eligible fuel oil-firedboiler at the Decatur facility.' Boiler 

### #AB4302 is a 

### 281 MMBtuihr unit equipped with a low 

### NOx burner. PM emissions from this boiler are due to the combustion of residual fuel oilgandlor natural gas. Fuel oil speciated PM enlissions are presented in this section for the Boiler 4302 fuel oil combustion scenario. As noted previously, actual emissions are based on natural gas combustion,but BP provides results from both fuel oil and natural gas combustion.

To speciate the PM emissions from the residual oil fired boiler, data from the default speciation profile compiled by VISTAS were used to determinePh4 size fractions and CPM enlissions. Additional particle size information was obtained from Section 

### 1.3 of 

### US. EPA's AP42 emission factor databa~e.~ The percentage of elemental carbon in the PM emissions was also based on the default speciation profile compiled by VISTAS.]' Table 

### 2-7 sunlmarizesthe relevant data for this source.



## 'BP normally cornbusts natural gas in this boiler; however, fuel oil combustion results in the maximum emissions of visibility-affecting pollutants. 

# 'Sulfur content = 0.76%.

AP-42, Section 13, Fuel Oil Combustion, September 1998.

'O Battye and Boyer, Catalog qf Global EtnissionsInientories and Emission bn~ento~y Tools for Block Carbon, prepared for EPA DRAFT January 2002, Table 6.



### BP Decatur Works BART ApplicabilityAnalysis 

### 16 Trinity ConsultantsSpeciation Data

PM2.5 as a % of PMlo Filterable as a Oh of PhJlo Condensable as a % of PM,, EC as a % of PM,,, Organicportion of CPM Inorganicportion of CPM PM6-,, as a % ofPMlo PM2,5, as a % of PM, PM1 .25-2.5as a % of PMIo PMl-l,25 as a % of Ph4,, Ph40,62,.las a % ofPM,,

PMo.,o.62s as a % of PMlo Value Reference

VISTAS Default Speciation Profile (Uncontrolled Industrial Residual Oil Fired Boiler, S = 0.76%)

AP-42 Section 1.3, Table 1.3-5Industrial Boilers Firing Residual Oil (~ncontrolled)'

1. Values provided in AP-42 were expressed as a % of TSP and were converted to % as PMlO by dividing by the % ofTSP that is PM,,, (as shown in the AP-42 table). For example, PM,-,, is calculated as (PM,,% 

### - PM,oh/o)l(PM,n%) =PMh-IO as % of PM,,.

Using the information presented in Table 2-7, 

### BP first calculated 

### CPM emissionsby multiplying the maximum hourly 

### PMlo emission rate by 14.6%. Next, the POC emissions were determined by multiplying the calculated 

### CPM emissionsby the organic condensable percentage of 15%. POC was assumed to be evenly split between the two size categories, 0.625-1.0pm and 0.5-0.625 pm. 

### PIC emissionswere calculated using a similar methodology, using the inorganic condensable percentage of 

### 85%. Filterable

### PMlo emissionswere divided amongst six different size categoriesby multiplying filterable

### PMlo emissions by the percentage of 

### PMlo for each size category, yielding hourly emissionsof

PM6-10, PM2.5-6, PM1.25-2.5, PM1-1.2, PM0.625-1, and PM0.5-0.625.

Table 2-8 presents a summary of the speciated 

### PM emissions for the BART eligible fuel oil-fired boiler and Figure 2-2 depicts this speciation.



### TABLE 2-8. FUEL OILFIRED BOILER PR4 SPECIATED 

### E~~ISSIONS (LB/HR)



### BP Decatur Works BART Applicability Analysis 17 Trinity Consultants Emission Unit
Boiler $.4B 4302 P1C.non-sulfate (urn) 0.625 - 1.0 0.5 

### - 0 625 POC (urn) 0.625 

### - 1.0 0.5 - 0.625

0.1 6 0.16 SO4
1.76 PMC (urn) 6 

### - 10 2 5 - 6
1.27 2.96 PMF (urn) 1.25 - 2.5 1 0 - 1.25 0.625 - 1.0 0.5 - 0.625

2.39 0.42 0.84 3.64 

### !z!zud
0.5 - 0.625

0.58flPIC. sulfate (05-1.0 mrcrons)
PhiiC (6-10 rn~crons)

0 PMC' (1.5-6 mrcrons)
B PMF(1 "15-1.5 microns)
PMF (1.3-1'25 microns)
PMF (0625-1 0microns)

B i34F (0.5-0.625microns)
O EC (0.5-0.625rnicmns)



## ' AP-12, Sectron 1 4, h'aruiai Gas C'omhustron,July I998Global Emissions Im~entories and Emission Inventoly Tools for Black 

## arbo on." Table 2-9 summarizes the relevant data for these sources.



### TABLE 2-9. NATURAL GASCOMBUSTION SPECIATION 

### DATA

Speciation Data PM,,, as a % ofTPM,, Filterable as a % of TPMlo Condensable as a % of TPM,, EC as a % of PM?,~' Organic portion of ~~h4' Inorganic portion of CPM' PM,,, as a % of PM,, PM2.5-6 as a % of PM,, PM,.,,-,., as a % of Ph4,, PMl-,.25 as a % of PM,, PM0,625-1 as a % of PM,,~ PM0.5-0.625 as a % o~PM,,~ Value p~ Reference

AP-42 Section 1.4, Table I .4-2 Natural Gas ~ornbustion]

1. Table 1.4-2provides the ratio of filterable to condensable PM. Based on the assumptionin the footnotes of Table 1.4-2 that all PM is less than 1.0 microns, the size speciationwas developed. 2. Catalog of Global Emissions Inventories and Emission Invenrory Tools for Black Carbon,prepared for EP.4 DWT January 2002, Table 6. 3. Although AP-42 says, "PM in natural gas combustion are usually larger molecular weight hydrocarbons;"which s~uld lead one to believe that the majority of the CPM would be POC, some industry data suggests the opposite (C,orio & Sherwell,In-Stack Condensable Particulale Matter h4easurenrents and Issues, Table 5,Feb 1000). Therefore, CPM emissions were split equallybetween POC and PIC. I.As all PM emissions from natural gas combustion are assumed to be less than I micron in diameter, the size speciation was split equally between the two smallest size categories.

Using the infom~ation presented in Table 2-9, 

### BP calculated speciated 

### PM emissions in the

same manner as described in the previous section for the fuel oil-fired boiler. Table 2-10 presents a summary ofthe speciated 

### PM emissions for the eleven BART eligible natural gas-fired combustion units and Figure 2-3 depicts a representative speciation for Boiler 4302.

I' Battye and Boyer, Cafalogof Globol En~issions Inventories end Emission Inventory Tools for Black Carbon, prepared for EPA DRAFT January 2002, Table 6.



### BP Decatur Works BART Applicability Analysis 

### 19 Trinity ConsultantsEmission Unit
Boiler #.4B 4302 Catox Furnace EB-I 01 Process Heater EB-103 Process Heater EB-104 Process Heater Kh-101 Process Heater 0-1 02 Process Heater Kb-401 Process Heater Marine Dock Flare Kh-104 Process Heater PX Flare POC (urn) 0.625 - 1.O 0.5 - 0.621: PIC. non-sulfate (urn' 0.625

### - 1.O 0.5 - 0.62: PMC (urn) 6-10 2.5-6 PMF iurn) 1.25 - 2.5 1.0- 1.25 0.625 - 1.0 0.5 - 0.625

POC (0.5-1.0mlcrons) PIC, non-sulfate (0.5-1.0microns) PIC, sulfate (0.5-1.0 microns) PMF (0.625-1 .Omicrons) PMF (0.5-0.625 microns) EC (0.5-0.625 microns)



### 2.2.3 

### RIISCELLANEOUS PROCESS VENTS AND ~'~TERL~L HANDLING

### SOURCES
The primary visibility-affecting emission units at BP's Decatur Works are the combustion

sources. However, BP also operates a number of BART-eligible material handling, storage, and miscellaneous process vents that generate PM emissions. These sources are primarily associated with the drying, handling, and storage of purified terephthalic acid (PTA), which takes the form of 

### dry, free flowing crystals. BP is not aware of specific guidance for estimating speciated emissions from the miscellaneous process vents and material handling sources. Default speciation profiles compiled by VISTAS did not include specific source types operated at BP's Decatur Works. Therefore, for the miscellaneous sources that emit PM only, BP assumed that the particulate emissions from the scrubbers, bin vents, silos and baghouses associated with these miscellaneous process vents and material handling sources were all filterable PM emissions. BP operates one BART-eligible n~iscellaneous process vent, Crystallizer Scrubber Vent 

### (#3 PTA), that emits 

### VOC in addition to PM. It is likely that some portion of the PM emissions from this unit are condensable. However, the facility does not have specific data that indicate the fraction of 

### PM emissions that may be condensable. Therefore, BP conservatively assumed that all PM emissions from the Crystallizer Scrubber Vent were condensable organic PM

BP Decatur Works BART Applicability Analysis 20 Trinity Consultants(POC) emissions. BP also conservatively assumed that PM emissions fkom the Feed SlurryDrums,Dryer Vent Scrubbers, and Hold Tank were condensable.
As no default size speciation data were available,BP utilized general informationin AP-32 Appendix B.l 

### Particle Size Distribution Data and Sized Enzissioli Factors for Selected Sources and Appendix B.2 

### Generalized Particle Size Distributio~zs.Generic control efficienciesby size distribution are listed in Table B.2-3 of Appendix B. BP utilized the default control efficiencies of a high efficiency scrubber and high temperature fabric filter for the miscellaneous material handling and process vents. In addition, BP assumed the uncontrolledparticle size distribution was similar to that of a casting shakeout process at a steel foundry as listed in Appendix B. 1. Of the processes listed in Appendix B. 1,BP assumed that the crystallinenature of the PTA particulateemissions generated in these miscellaneous process vents most closely resembled the mold shakeout emissions. No data

were found to determine the percentage of elemental carbon in the PM en~issions; therefore, elemental carbon was assumed to be 0% of TSP for the nliscellaneousprocess vents. BP assumed that the condensable PM emissions were distributed equally between the two smallest size categories, 0.625-1.0pm and 0.5-0.625 pm. Table 2-1 1 summarizes the relevant data for these sources.

I. AP-42 Appendix B.2, Table B.2-3, AIRS Code 001 for scrubbers and AIRS Code 01 6 for fabric filters. 2. AP-42 Appendix B.1, Page B.1-88, Steel Foundries: Castings Shakeout (Uncontrolled). Control Description

Scrubber Fabric Filter

Using the information presented in Table 2-1 1,BP calculated speciated PM enlissions from the BART-eligible miscellaneous process vents. First, the size distribution data from Appendix B.l were used to calculate uncontrolled PM emissions in the various size categories. Next, the generic control efficiencies for a scrubber and fabric filter were applied to estimate controlled emissions for all six size categories. Table 2-12 presents a summary of the speciated PM emissions for the BART eligible miscellaneous process vents.

-- BP Decatur Works BART ApplicabilityAnalysis -- - Control Efficiency for Specific Size ~an~e] 0 

### - 2.5 pnl 2.5 

### - 6 pm 6 

### - 10pm
90 95 99 99 99.5 99.5

Trinity Consultants Cumulative Mass < Stated size' PMIO P"6 PMZS 82.0% 76.3% 72.2% 82.0% 76.3% 72.2%TABLE 2-12. MISCELLANEOUS PROCESS VENT P3lSPECLATED EMISSIONS (LB/HR)

PIC lum) 8.625 - 1.0 0.5 - 0 625 Emission Unit Stack Code Crystallizer ScrubberVent BPDOI Feed Slurry Dm BPD02 Dryer Vent Scrubber BPD03 PTA Silos Dust Collector System BPD04 Storage Silo Vent Scrubber BPDIO Storage Silo Baghouse BPD20 Crystallizer Scrubber JJent BPD2I Feed Slurry Drum BPD22 Dryer Vent Scrubber BPD23 Silos Storage BPD24 Ann Centrifuge Hold TadVent BPD25 Storage Silo Baghouse BPD3U Crystallizer Scrubber J'ent BPD46 Feed SluqDm BPD47 Dryer Vent Scrubber BPD4U Silos Storage BPD49 PMC (urn) 6-10 2.5 - 6 POC (urn) 0.625 - 1.0 0.5 - 0.625
1.64 1.64 0.0005 0 0005 0 40 0.40

045 045 0.0002 0.0002 0.25 0.25

0.02 0.02

0.45 0.45 0.0002 0.0002 0.25 0.25 PMF (urn) 1.25- 2.5 1.0- 1.25 0.625 - 1.0 0.5 

### - 0.625

0PMC (6-10microns)
E3 PMC (2.5-6nncrons)

1 I3 PMF (1.25-3.5 nncrons) PMF (I .O-1.35 microns)

E PMF (0.625-1.0 microns)

4.68

Actual stackparameters were input to the CALPUFF model to represent each point of visibilityaffecting pollutant emissions. The location of each point source was represented consistently in the Lambert Conformal Coordinate system used for the screening and refined meteorological data analysesprepared by VISTAS. Each exhaust discharges vertically without obstruction. Table 

### 2-13 summarizes the stack parameters. Table 

### 2-14 summarizes the modeled emission rates for BARTeligible emission units at BP's Decatur Works under the natural gas only combustion scenario and Table 

### 2-15 presents the same table assuming he1oil combustion en~issions for Boiler 

### 4302.

BP Decatur Works BART Applicability Analysis 

### 22 Trinity ConsultantsTABLE 2-13. STACK PARAMETERS FOR BART-ELIGIBLE E~~ISSION 

### UNITS

Emission unit' Source Codelstack ID Crystallizer Scrubber Vent Feed Sluny Drum Dryer Vent Scrubber PTA Silos Dust Collector System Catox Furnace Storage Silo Vent Scrubber Boiler #AB 4302 Storage Silo Baghouse Crystallizer Scrubber Vent Feed Sluny Drum Dryer Vent Scrubber Silos Storage Atm 'entrifuge Hold Tank Vent EB-I 01 Process Heater EB- 103 Process Heater EB- 104 Process Heater Storage Silo Baghouse Kb- lOl Process Heater Kb-102 Process Heater Kb-401 Process Heater Marine Dock Flare Kb- 104 7 MMBTUhReboiier PX Flare (KM-503) Crystallizer Scrubber Vent Feed Sluny Drum Dryer Vent Scrubber Silos Storage #3 PTNBPDO I #3 PTNBPDO2 #3 PTNBPD03 #3 PTNBPD04 #3 OxidationiBPDO9 #3 OxidationiBPD 10 BoilerBPD 12 #4 OxidationiBPDZO

#4 PTNBPD2I #4 PTNBPDX A4PTNBPD23 #4 PTNBPD24 #4 PTNBPD25 #I PWBPD27 #I PWBPD28 kl PXIBPD29 #5 OxidationBPD38 #2 PXBPD40 #2 PXBPD41 #2 PX!BPD42

PXIBPD43 #2 PX.BPD44

PWBPD45 #5 PTAJBPDI.6 #5 PTAiiBPD47 X5 PTNBPD48 k5 PTNBPD49 Stack Stack Exhaust Exhaust LCC East LCC North Height Diameter Temperature \'elocity

Otm) @m) (feet) (feet) ("F) (feetlsec)
6-00 212 15.92

1. Stackparameters for Stack ID'S BPDO4. BPD24. BPD49 are average values. which represent a group of similar emission sources. Emmionrates from these sources are equal to the total emission rate from all individual sources within the group.



### BP Decatur 

### Works BART Applicability Analysis 

### Trinity ConsultantsTABLE2-14.MODELEDEMISSIONRATESFORBART-ELIGIBLEEMISSIONUNITSEmission UnitSotirceCodelstackID3ystallizerScrubberVent[FeedShyDrumDryer VentScrubberPTASilosDust Collector SystemCatoxFurnaceStorageSiloVentScrubberBoiler#AD4302StorageSiloBaghouseCrystallizerScrubberVentPeedSlur~yDrumD~yerVelltScrubberSilos StorageAtmCentrift~geIloldTankVentEB-101ProcessIleaterEB-103ProcessIleaterEB-I04 ProcessIleaterStorageSiloBaghouseKb-lOlProcessHeaterKb- 102Process HeaterKb-401ProcessHeaterMarineDockFlareKh-1047MMBTUIlirReboilerPXFlare(KM-503)CrystallizerScrubberVentFeedShyDrumDryerVentScrubberSilosStoragePOC(Iblhrl,625-1.O0.5-0.62!PIC,non-sulhte(Ibll~r)1.625-1.00.5-0.625I'MC(Ibllir)5-102.5-6PMF(IWhr)1.25-2.51.0-1.250.625-1.00.5-0.62:BPDecaturWorksBART Applicability Analysis24TrinityConsultantsEmission UnitSourceCodelstackIDCrystallizerScrubberVentFeedSlurryDrllmDryerVentScrubberI'TASilosDustCollector SystemCatoxFurnaceStorageSiloVentScruhberBoiler#AD4302StorageSiloBagliouseCrystallizerScrubberVentFeedSlurryDrumDryer VentScrubberSilosStorageAtmCentrifi~geIloldTankVentED-I0II'rocessIHeater88-103ProcessHeaterEB-104Process HeaterStorageSiloBagliouseKb-I0IProcess HeaterKb-102ProcessI-leaterKb-401ProcessI-leaterMarine Dock FlareKb-1047MMBTUIhrReboilerPXFlare(KM-503)CrystallizerScrubberVentFeedSlurryDrumDryer VentScrubberSilosStoragePIC, non-sulfate(Iblhr)0.625-1.00.5-0.625PMF(Ibhr)1.25-2.5 1.0-1.250.625-100.5-0.622BPDecaturWorksBARTApplicability Analysis25TrinityConsultantsSection 3 ofthis BART Applicability Analysis Report for BP's Decatur Works describes the modeling methods, data resources, and technical options used to conduct screening and refined analyses to assess visibility impacts. Air quality modeling was conducted generally following the methods described in the 

### VISTASBARTJ4odeling Protocol as revised, with exceptions as described in this section.

CALPUFF is a multi-layer, multi-species, non-steady-state Lagrangian puff model, which can simulate the effects oftime- and space-varying meteorological conditions on pollutant transport, transfornlation, and removal. The modeling system is designed to handle the complexities posed by the conlplex terrain, the large source-receptor distances, chemical transformation and deposition, and other issues related to Class 

### I visibility impacts. A complete description of the model formulation and capabilities is provided in the 

### User's Guides for the CALPUFF modeling system and the 

### VISTAS BARTA4odeliiig Protocol.

The CALPUFF modeling system has been adopted by the US.EPA as a recommended regulatory guideline model for source-receptor distances greater than 50 

### km, and for use on a case-by-case basis in complex flow situations for shorter distances. CALPUFF is recommended for Class 

### I area impact assessments by the Interagency Workgroup on Air Quality Models (IWAQM). The U.S. EPA's BART guidance recommends CALPUFF as "the best modeling application available for predicting a single source's contribution to visibility impairment."

As a result of these recommendations, the 

### J/ISTAS BARTModeling Protocol was based on the use of CALPUFF and was used by BP for the source-specific analysis of visibility impacts attributable to the Decatur Works. Specifically, CALh4ETVersion 5.7241060414, CALPUFF Version 5.7541060202, POSTUTIL Version 1.52/0604 12, and CALPOST Version 5.63931060202 were designated as the "VISTAS Recommended Version for BART Modeling" by the VISTAS Technical Contractor and were used in the CALPUFF BART Applicability Analyses for BP's Decatur ~orks.'~

The 

### VISTASBARTA4odeling Protocol distinguishes between screening and refined applications of the CALPUFF model for the purposes of BART Applicability Analyses. As the names of these techniques imply, screening analyses are intended to provide a conservative estimate of visibility impacts using computationally efficient techniques. The refined analyses utilize less conservative and more representative data and modeling methods to compute visibility impacts following US.EPA's BART guidelines. Screening analyses may be used to determine that a facility is not subject to

l3 httn:lls~c.cod~~eriddow~loaddoaaload.h#VISTAS VERSION


### BP Decatur Works BART Applicability Analysis 2

### 6 Trinity ConsultantsBART using a conservative assessment, or to focus the scope of refined analyses by demonstrating that visibility impairment is not likely to occur at more distant Class I areas.
Although certain elements of the modeling analyses are identical regardless of which approach is used (eg,representation of emissions sources, chemical transformation algorithms, Class 

### I area receptors), the 

### VISTASBARTA40deling Protocol makes sellera1 important distinctionsbetween screening and refined analyses.

The U.S. EPA BART guidelines prescribe that the 9gth percentile, 24-hour average visibility impact conlputed in a modeling analysis that evaluates three years of meteorological data should be compared to the contribution threshold of 

### 0.5 dv to assess BART applicability. However, VISTAS prescribes that the 

### maxiriiunz computed visibility impact be used as the basis for comparison in the screening analysis to ensure that the modeled result is a conservative representation of visibility impaimlent. The 

### VISTAS BARTAlodeling Protocol describes the impact threshold for refined analyses as "the 9gth percentile (gth highest annual) 24-hour averagepredicted impact at the Class I

area.. .the predicted impact at the Class I area on any day is taken to be the highest 24-hr average impact at any receptor in the Class I area on that day. (Note that the receptor where the highest impact occurs can change from day to day.)" The default CALPOST processing of modeled visibility impacts outputs a summary table of this result, ranking the highest 24-hour average impacts for the year at each Class 

### I area, from which the gth highest impact can be readily discerned. The VISTAS refined approach may also consider the ~2"~-highest 24-how average visibility impact over the three years modeled if this result is more conservative.

The VISTAS interpretation of the visibility impact is a conservative estimate of the 9gth percentile impact since the spatial and temporal variability of impacts at each receptor is ignored, as the protocol notes by recognizing that the receptor where the highest impact

occurs can change from day to day. BP utilized the default conservative 9gth percentile calculations to quantify visibility impacts in refined modeling analyses to illustrate the distribution (i.e., frequency, duration, and magnitude) of peak visibility impainnent episodes attributable to the Decatur Works for comparison against the 0.5 dv contribution threshold.



### 3.2.2 

### METEOROLOGICAL AND 

### COMPUTATIONAL GRIDS

The 

### VISTASBART Modeling Protocol prescribes that screening analyses be conducted on
a 12-km meteorological and computational grid and that refined analyses be conducted on
a 4-km meteorological and computational grid. The resolution of the computational analysis dictates the extent to which geophysical (i.e., terrain and land use) and meteorological conditions are represented in the CALMET meteorological model, hence the advection, dispersion, and chemical transformation of visibility-affecting pollutants in the 

### CALPUFF lneteorological model. The VISTAS Technical Contractor conducted meteorological modeling using both screening 12-knl and refined 4-knl grids to provide

BP Decatur Works BART Applicability Analysis 2

### 7 Trinity Consultantscommon data resources to eligible sources conducting BART Applicability Analyses, which were used by BP to assess visibility impacts attributable to the Decatur Works. The following section of this report describes the CALMET meteorologxal modeling in greater detail.

The IWAQM

### Phase 

### 2 Report prescribes recommended default model processing options to be used in CALPUFF analyses, which are in most cases considered regulatory default options under U.S. EPA's 

### Guideline on Air QualityA4odels. IWAQM default model options as described in the following section of this report were prescribed for use in both screening and refined analyses. The 

### VISTASBARTA4odeling Protocol and BP's sourcespecific modeling protocol envisioned the possible use of puff-splitting algorithms to represent wind shear effects and differential rates of transport of well-mixed puffs that grow beyond the size of a grid cell. Puff splitting algorithms are computationally demanding and for some applications may require changes to the default parameter settings in POSTUTIL to allow more than the default number of split puffs. Puff splitting was evaluated and found not to significantly change modeled impacts in this application due to the relatively short distance between Decatur Works and the nearest Class 

### I area, Sipsey at approximately 

### 43 

### krn distant. Therefore, the default model option to disable puff splitting

was used in both screening and refined analyses.



### Inthe postprocessing of CALPUFF-computed concentrations of visibility-affecting pollutants, the POSTUTIL postprocessing utility can be used to apply the anmonia limiting method by re-partitioning the distribution of HN03and NO3concentrations at each Class 

### I area as a function of the temperature and relative humidity during each hour. 

### ALM processing is not run by default, and therefore was not used in the screening analyses. 

### ALM re-partitioning using the default ammonia background le\7el of 0.5 ppb was conducted in refined analyses as described by the 

### T/ISTASBARTModeling Protocol.

CALMET is the meteorological preprocessor that compiles three-dimensional meteorological fields from mesoscale model 

### (MM) output, raw observations of surface and upper air conditions, precipitation measurements, and geophysical parameters into a single hourly, gridded data set for input to CALPUFF. The 

### CALA4ET User's Guide and 

### VETASBARTA40deling Protocol provide 

### a detailed description of the model's formulation and capabilities.

The federal 

### Guideline for CALPUFF processing provides the following recommendations for the meteorological data period at Section 9.3.1.2:



### Less thaizfifive,but at least three, years ofmeteoro1ogical data (need not be coizsecutive) may be used ifn~esoscale n~eteorologicalJields are available, as discussed iizparagraph 9.3(c). lliese ~izesoscale iiieteoro1ogicalJields should be used in conjunction ~ith available standard [National WeatherSen:ice] MS or coriiparablemeteo~~ological obsei-vatioizs ~ithii? and iiear the modelir~g doiizain.

BP Decatur Works BART Applicability Analysis Trinity ConsultantsCell Face Height Vertical Grid Cell (meters)

Refined 4-km analyses were also conducted using this vertical grid structure. Sub-regonal Domain 4, which BP utilized for its refined analyses, contains all of Alabama, Georgia, Tennessee, southern Kentucky, and western North Carolina in which the BART-eligible

source and potentially affected Class I areas are located.



### MM data are used as "observed" or "first-guess" fields in CALMET due to its highresolution representation of meteorological conditions on a uniform three-dimensional *d. The followingthree years of MM5 meteorological data were assembledby VISTAS for use in the regional CALPUFF modeling effort:

A 2001 

### MM5 dataset at 12 

### knl and 36 

### km pd (developed for EPA)

A 2002 

### MM5 dataset at 12 

### km and 36 km grid (developedby VISTAS)

A 2003 MM5 dataset at 36 

### krn grid (developed by the Midwest Regional Planning Organization).

These data sets were provided to the VISTAS Technical Contractor, which produced threedimensional,CALMET-ready meteorological files for the VISTAS domain, which were subsequently used to run CALMET for the 12-knl screening and 4-knl sub-regional refined analyses.

According to the VISTAS BART ModelingProtocol, terrain elevations within the modeling domain were processed from SRTM-GTOP030 digital terrain data format with 30-arcsec resolution. SRTM30 is a digital elevation data set that spans the globe from 60' north latitude to 56' south latitude, approximately from the southern tip of Greenland to below the southenltip of South America. It has a horizontal grid spacing of 30 arc-seconds (approximately 1 lulometer). GTOP030 is a global digital elevation model with a horizontal grid spacing of 30 arc-seconds (approximately 1 kilometer) that was derived from several raster and vector sources of topographic information that include

### US.

- BP Decatur Works BART Applicability Analysis 

### 30 Trinity ConsultantsGeological Survey (USGS) digital elevation models. The VISTAS Technical Contractor used data preprocessors to format and assimilate these data into a single geophysical data file for processing by CALMET to generate the 12-km screening data set. According to the VISTAS BARTModelingProtocol, higher resolution 

### 3 arc-second DEM data were used
to simulate terrain elevations in the 4-km refined data set.

Land use and land cover (LULC) within the modeling domain was assimilated by the VISTAS technical contractor into a single geophysical data file for processing by CALMET using Composite Theme Grid (CTG) data archived by the 

### USGS at a resolution of 200 meters. CALMETwas used to calculate the fractional land use types within each cell of the CALMET grid. LULC in each grid cell was used by CALMET to compute the micrometeorological parameters (i.e., surface roughness, Bowen ratio, albedo, soil heat flux) that affect turbulent dispersion in the boundary layer. According to the VISTAS BARTA4odeling Protocol, 200-meter CTG LULC data were utilized for both 12-km screening and 4-km refined analyses.

The development of the regional screening CALMET meteorological fields from 

### MM5 data were conducted in No-Observations ("No-Obs") mode since the 

### MM5 data already reflect assimilation of observational data and are likely to adequately characterize regional wind patterns that are consistent with the 12-krn grid scale.

When the 12-km

### MM5 (2001 and 2002) data are used, the diagnostic CALMET terrain adjustments were turned off since the grid resolution of the 

### MM5 data is the same as the CALMET grid and the terrain adjustments on the 12-km grid scale will already be reflected in the 

### MM5 dataset. 

### In this case, the 

### MM5 winds were interpolated by CALMET
to the CALMET layers and CALhET's boundary layer modules computed mixing heights, turbulence parameters, and other meteorological parameters that are required by CALPUFF. For 2003, the 

### 36-km 

### MM5 data were used as CALMET's initial guess field and then the CALMET diagnostic terrain adjustments (see Section 3.1.1 of the P7STAS BARTAdodeling Protocol) were applied to reflect terrain on the scale of the CALMET grid (i.e., 12 km).



### 3.3.5 

### 4-MI

### REFINED GRID 

### CALMETPROCESSING

The finer grid (4 km) CALMET simulations were run by the VISTAS Technical Contractor in hybrid mode, using 

### MM5 data to define the initial guess fields, diagnostic terrain adjustments to create the Step 1 wind fields, and NTYS meteorological observational data in the Step 2 snloothing calculations. 

### In this manner, actual observations of threedimensional meteorological conditions were used in the model to sn~ooth the coarse 

### MM5 resolution to better represent areas in which terrain features and coastlines may have an important effect on meteorological conditions, but not be well resolved in the mesoscale model. Surface, upper air, precipitation, and offshore buoy observation points are readily available for use in CALMET. The following generally describes the use of NWS observations in Step 

### 2 of the CALMET analyses.

BP Decatur Works BART Applicability Analysis 

### 3 1 Trinity ConsultantsParameters affecting turbulent dispersionthat are observed hourly at surface stations include wind speed and direction, temperature, cloud cover and ceiling, relative humidity, and precipitation type. Surfacedata were selected from the available data inventory to optimize spatial coverage and representation of the domain. Raw observations were obtained from the National Climatic Data Center (NCDC), quality assured, and merged using the SMERGE pre-processor to create a single assimilated data file of surface observations for each year analyzed.

Observationsof meteorological conditionsin the upper atmosphere provide a profile of turbulence from the surface through the depth ofthe boundary layer in which dispersion

occurs. 

### In general, twice-dailyupper air data are collectedby balloons launched simultaneouslyacross the observation network at 0000 Greenwich Mean Time (GMT) and 1200GMT, which correspond to 6:OOpm and 6:00am, respectivelyin the Central Time Zone, includingAlabama. In CALMET analyses,the VISTAS Technical Contractor used Eastern Standard Time Zone (GMT-5) as the base time zone for all analyses, in which twice daily upper observations correspond to 7:OOpm and 7:00am, respectively.'4 BP presumes the meteorological data provided by VISTAS were prepared using appropriate representationsof meteorological observations from different time zones within the modeling domains. Sensors observe pressure, wind speed and direction, and temperature (among other parameters) as the balloon rises through the atmosphere. The upper air observation network is less dense than surface observation points since upper air conditionsvary less and are generallynot as affected by local effects (e.g., terrain or coastlines). Upper air data were extracted from the NCDC's available data inventory to optimize spatial coverage and representation of the domain, and utilization from year to year may vary due to availability and data quality.

The effects of wet deposition processes on ambient pollutant concentrationsare an important part of the 

### BART Applicability Analysis. Therefore,it was necessary to include observations ofprecipitation in the CALMET analysis. Precipitationdata were collected from selected surface meteorological data stations included in the analysis,plus Cooperative Observation Network (COOP) stations nearer to or within the domain. Precipitationdata were extracted from anlong the NCDC's available data inventory to optimize spatial coverage and representation of the domain. Raw observationsfrom these stationswere quality assured and merged using the PMERGE pre-processor to create a single assimilated data file of precipitation observations.

BP's BART Applicability Analyses were conducted using 

### 12-km screening and 

### 4-km refined CALMET data prepared by the VISTAS Technical Contractor. The 

### VISTAS BART ModelingProtocol describes quality assurance techniques used by the contractorto validate the model's performance.

l4 http:/lsrc.comiverioIdo\mload/FilesldomWmet2001 -don14-01a.inp.

BP Decatur Works 

### 32 Trinity Consultants BART ApplicabilityAnalysis

### 3.4 

## CALPUFF MODEL PROCESSING
CALPUFF analyses to assess the visibility impacts attributable to BP's Decatur Works were conducted generally in accordance with the recommendations of IWAQM

### Phase 

### 2 Sunznza~y Report and Reconzlnendations for Modeling Long Range Transpoi?Impacts, Appendix 

### B of which provides recommended default CALPCFFparameters. Appendix A of this BART ApplicabilityAnalysis Report contains sample 12-km screening and I-km refmed CALPUFF input files that can be compared to the IWAQM recommendationsto demonstrate that default options were used, including the following important model options.

Section 

### 2 of this 

### BART Applicability Analysis Report described the BART-eligible emission units operated at BP's Decatur Works and the visibility-affectingpollutants considered in the CALPUFF analysis. Emission rates were calculated following U.S. EPA and ADEM BART guidance for primary emissions of SO?,H2S04,NOXand PMlo.PM was further speciated into size categories of less than 0.625 pm, 0.625-1.0 pm, 1.O-1.25 pm, 1.25-2.5 pm, 2.5-6.0 prn and 6-10 pm aerodynamic diameters. hdustryspecific emission factors were utilized to analyze the phase, size, and character of PM emissions as described in Section 2 of this report. In addition to species emitted directly from the Decatur Works, secondary formation of HN03,NO3,and SO4was simulated using the MESOPUFF-II chemical transformation algorithms, which are considered the default for regulatory CALPUFF modeling. Background levels of ozone and ammonia, which drive the simulated chenlical transformation of emitted pollutants into visibility affecting species, were input to the model as described in subsequent sections of this report.

BP operates 

### 27 BART-eligible emission units at the Decatur Works evaluated in this BART Applicability Analysis, as described in Section 2 of this report as each having distinct emission release points and characteristics. Sample model processing files provided by the VISTAS Technical Contractor demonstrate modeling of a single point source using CALPUFF, POSTUTIL, and CALPOST to assess visibility change.'' The sanlple approach sinmlates actual emissions of each of three gaseouspollutants (SO?, SO4, and NOx) and unit emissions (e.g., 1 g/s) of each of six generic particle categories distinguished and designatedby size: PM800, PMI25, PM187, PM112, PM081, and PM056, to represent PM6.10, PM? j-6, 

### PMI?j-2 5, PMI-I 25, PMo 62j-I,and PMo 5-0 625, respectively. The size distributionis the only distinguishing feature ofthese particle categories. Table 3-2 summarizes the relevant model input parameters for each size category.

IS http://www.src.comiveriddoa?lloadi~ample~files.h~~#E~PLE~B~T

BP Decatur Works 

### 3 3 Trinity Consultants 

### BART Applicability Analysis

### TABLE 3-2. REPRESENTATION F PA4 SIZE CATEGORIES LN 

### CALPUFF

Computed Geometric Mass Geometric Standard Precipitation Scavenging Coefficient Deposition Mean Diameter Deviation Liquid Frozen Model Species Mode (microns) (microns)* (s") @‘I)
PMSOO Particle 8.00 0 1.O% 1 

## o-~ 3.0 % 10" Ph.1425 Particle 4.25 0 1.0 % lo4 3.0 % 10" PM187 Particle 1.87 0 1.0 % lo-4 3.0 % 10" PMll2 Particle 1.12 0 1.0 % 10‘~ 3.0 % 10" PMO8 1 Particle 0.81 0 1.O% 1

## o-~ 3.0 % 10" Ph.1056 Particle 0.56 0 1.0 % 3.0 % 10."
* Zero geometric standard deviation indicates that CALPUFF utilizes the deposition velocity associated with the geometric mass mean diameter.

Because unit emission rates were modeled from the single point source in the sample approach, actual emission rates were used in the POSTUTIL postprocessing step to combine PM types and sizes into light scattering groups by scaling the modeled concentrations up or down by the nlultiplicative factor of the actual emission rate of each PM size category, which includes multiple types of PM (e.g., coarse filterable 

### PM, fine filterable PM, organic condensable PM, inorganic condensable PM, and elemental carbon). The output concentration file from POSTUTIL was then input to CALPOST to calculate visibility change attributable to emissions from the point source in the sample analysis.

Thepreceding approach is reasonable for modeling a single point source; however, for facilities with multiple emission point sources, the preceding approach is not appropriate. Specifically, for sources with nlultiple emission points that have different exhaust characteristics (e.g., stack height, diameter, velocity, and temperature) and/or different emissionsprofiles of speciated PM, the use ofunit emission rates from each source is not appropriate since the CALPUFF output concentrations at particular receptors will not distinguish which source(s) contribute to the PM concentrations. Therefore, the POSTUTIL source profile technique cannot be applied. One alternative to this approach for sources with multiple emission points is to model each emission point individually in multiple CALPUFF runs using unit emission rates, then run POSTUTlL to combine the PM concentrations at each receptor for each modeled emission point, finally running the CALSUM postprocessing utility (or a second application of POSTUTIL) to combine the impacts of all sources. This approach, though conceptually appropriate, is undesirable due to substantial additional computer runtime required to model and post-process each emission point individually.

As a computationally efficient alternative to the preceding approaches, the 

### BART Applicability Analyses for BP's Decatur Works were conducted by explicitly modeling in CALPUFF the actual emission rate fioin each point source each of 14particle species defined as described in Table 

### 3-3. The nomenclature used in Table 

### 3-3 is analogous to that used to describe the emissions from BP's BART-eligible emission units in Section 

### 2 of this report.



### BP Decatur Works BART Applicability Analysis 34 Trinity Consultants

# IModeled PRI Category Components 

# I

Ph4C800 Filterable coarse particles divided between two size categories PMC425 (pM6-1o~ PM2.5-6)



### .......................................................................................................................................................................................................... Ph.IFl87 PMFI 12 Filterable fine particles divided among four size categories Ph.IFO8 1 (PhI1.25-2.5, Ph11l-l.2j, PMo.62-I, PhIo.5-0.63) Ph4F056



### .......................................................................................................................................................................................................... POCO8 1 Primary condensable organic emissions divided between two size categories POCO56 (PMo.625-Iand pM0.5-0.63)



### .......................................................................................................................................................................................................... PIC08 1 Primary condensable inorganic emissions divided between two size categories PIC056 (Ph40.62-I and pM0.5-0.625)



### .......................................................................................................................................................................................................... ECl87 ECll2 Primary elemental carbon enlissions divided among four size categories ECO8 1 (PMI25.2.5, PMI-I 25, PMo645.1, PMo5.0 625) ECO56

So that explicit modeling of the 14particle species and sizes could be conducted equivalently to the unit emissions approach, identical model processing options for each Phil size category were enabled as summarized in Table 3-4.

Computed Geometric Mass Geometric Standard Precipitation Scavenging Coefficient Deposition Mean Diameter Deviation Liquid Frozen Model Species Mode (microns) (microns)"

Ph4CSOO 3.0 % 10"

.............. ................................. . ............. PMC325 3.0 % lo-'

-
. ........................... ............................... PMFl87

EC187 3.0 % 10.'

-. ........... ......................... ........................... ............................................... ...................................................................... PMF112 Particle 1.12 0 3.0 % 10'~

EC112

Particle

Particle
PIC056 * Zero geometric standard deviation indicates that CALPUFFutilizes the deposition velocity associated with the geometric mass mean diameter.

BP Decatur Works BART Applicability Analysis -- Trinity ConsultantsTo post-process the CALPUFF output concentrationsthat result from explicitly modeled multiple emission points, POSTUTIL was used only to group modeled PM into light extinction groups. Unit scaling factors were used in POSTUTIL and there was no adjustment to the explicitly modeled emissionrate. Table 

### 3-5 summarizes the POSTUTIL grouping of modeled PM species into light extinction groups, and the light extinction coefficient subsequentlyused in CALPOST to compute light extinction due to the multiple emission points at the source.



### TMLE3-5. ASSIGNMENT OF 

### MODELED PM 

### SPECIES TO

### LIGHT EXTINCTION GROUPS 

# I Modeled CALPOST Light Extinction Coefficient Components Extinction Group (m2k)

PMC8OO Ph4C425 PMC 0.6

.................................................................................................................................................... PMFl87

SOIL 1



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

# I POCO8 1

POCO56 SOA 4

Implementation of the explicit modeling approach required minor changesto the parameter declaration file and re-compilation of the CALPUFF model executable file. Kote that this approach does not require changes to the FORTRAN model code, only the parameter declaration limits. Explicit modeling of the 14PM types and sizes plus the SOz,SO4,NOx, HN03,and NO3 species results in a total of 19modeled species,which is within the default parameter limit of 20 species modeled (MXSPEC). However, the parameter for particle species deposited 

### (MXPDEP) was increased from 9 to 20 to accommodate the greater number (16, including SO4and NO3)of particle species simulated in the model.

This modified approach follows conceptually the steps outlined in the revised VISTAS BART h4odelingProtocol as evidenced between comparisonsbetween the two methods. Results using the explicit method for multiple emission points and the samplemethod using a singlepoint source with PM speciation 

### (PMF, PMC, SOA, 

### EC) applied during the POSTUTIL step provides equivalent results. The model input and output files of a sample conlparativeanalysis are further described in Appendix 

### B and included with the electronic media provided with this BART Applicability Analysis Report to demonstratethat explicit modeling of PM emissions results in equivalent calculations of visibility impacts.

BP Decatur Works BART Applicability Analysis 

### 36 Trinity Consultants

### 3.4.2 

### CALPUFF

### DISPERSION ALGORITHMS
As specified in a March 16,2006U.S. EPA rnemorand~m]~ and the most recent revision to the 

### VIST4S 

### BARTModeling Protocol, the use of Pasquill-Gifford (ISC-like) dispersion coefficientswas enabled as the default option in screening and refined CALPUFF analyses.

Because the Decatur Works is located more than 30 km from any Class 

### I area, the effects ofbuilding downwash were not consideredin the BART Applicability Analyses.



### 3.4.4 CALPUFF MODELING DOMAINS AND 

### CLASS 

### I AREA 

### RECEPTORS

CALPUFF modeling for 12-km screening and 4-km refined analyses was performed on computational domains that are subsets of the VISTAS Regional Domain 0 and Sub-regionalDomain 4. The size of each conlputationaldomain was selected to encompass the Decatur Works and the Class 

### I areas being analyzed, and to extend at least 50 km beyond in all directions. The size of the domain allows for the possible recirculation ofpuffs beyond the facility and areas being evaluated. Computational domains use the same vertical grid structure as described in the CALMET model formulation in Section 3.3 of this report. Figures 3-2 through 3-7 illustrate the locations of, and terrain elevations and land use within, the 12-km screening and 4-km computational domains used in BP's BART Applicability Analyses.

The ground level receptors at which concentrations of visibility-affectingpollutants and visibility impacts were calculated at the five Class 

### I areas within 300 

### lan were obtained from the National Park Service as depicted in Figures 3-8 through 3-11.17

l6 U.S. EPA Memorandum "Dispersion CoeEcients for Regulatory Air Quality h4odeling in CALPUFF*'from Mr. Dennis Atkinson and Mr. Tyler Fox (Air Quality Modeling Group) to Ms. Kay Prince (Regulatory Planning Branch) dated March 16,2006.

BP Decatur Works BART ApplicabilityAnalysis 

### 37 Trinity Consultants

### 60mnon-urbanMonthly average ozone background values were computed based on daytime average
ozone concentrationsfrom the 0ZONE.DAT file (6am-6pm average ozone concentrations computed by month) of each year for substitution should all observations be missing for a particularhour of the dataset. Table 

### 3-6 summarizesthe monthly average ozone values computed for this substitution for screeningand refined analyses, respectively.



### TABLE 3-6. MONTHLYAVERAGE SUBSTITUTE 

### OZONE VALUES 

### FOR 12-KM SCREENING ANALYSIS

2001 Substitute 2002 Substitute 2003 Substitute Month Ozone Values (ppb) Ozone Values (ppb) Ozone Values (ppb) January February March April May June July August September October November December



### In both the screening and refined analyses, a constant ammonia background value of 

### 0.5 ppb was input to the CALPUFF model. The initial 

### VISTAS BARTModeling Protocol envisioned the use of modeled boundary conditions of anvnonia and sulfates in the refined analysis of chemical transformations involvingthese species and nitrates. However, VISTAS' Technical Analysis Workgroup has since concluded that modeled background and boundary conditions should not be utilized for BART modeling purposesbecause "EPA and FLM recommend that ALM approach using CMAQ concentration data (SOx, NOx, total NH3)be reviewed by EPA Modeling Clearinghouse before being used in a regulatory application." Accordingly, such background data were not utilized in BP's BART applicability modeling analyses. As described in the following section of this report, only refined analyses utilized the POSTUTIL postprocessing tool to re-partitionthe 

### HN03and NO3equilibrium distributionsusing only a constant 0.5 ppb ammonia background level.

BP Decatur Works BART Applicability Analysis 

### 44 Trinity ConsultantsAs recommended by the 

### VISTAS BARTModelingProtocol, the default integrated puff samplingmethodology was enabled for both screening and refined CALPUFF analyses. 

### Ln the screening analyses,the default settingto disablepuff splittingalgorithms was retained. Puff splittingwas evaluated and found not to significantlychange modeled impacts in this application due to the relatively short distancebetween Decatur Works and the nearest Class 

### I area, Sipsey, at approximately 43 krn distant. Therefore,the default model option to disable puff splitting was used in both screeningand refined analyses.



### 3.4.7 QUALITY ASSURWCE OF 

### CALPUFFANALYSES
Sample CaPUFFinput files for the screening and refined analyses are presented in Appendix A of this report and copies of all input and output files are included on the electronic media enclosed with this report. Comparison ofthe CALPUFF model inputs indicates that default values, as prescribed by IWAQM (Appendix 

### B) and in the 

### VISTAS BARTModelirigProtocol, were used with the exception of the source-specific model options described in this report. Source parameters input for each BART-eligible emissionsunit were verified with the information presented in Section 2 of this report. The location and elevationsof Class 

### I area receptors as illustrated in Figures 3-8 and 3-9 of this report were verified by comparison to NPS maps.



## 3.5 

## CALPOST POSTPROCESSING A~'D 

## NAT~TRAL BACKGROUND CORDITIONS FOR 

## LIGHT EXTINCTION AND 

## HAZEINDEX 

## CALCULATIONS
Using the concentrationsof visibility-affecting pollutants computed by CALPUFF, two postprocessors,POSTUTIL and CALPOST, were used to compute light extinction attributable to BP's Decatur Works and the relevant metrics for the BART Applicability Analysis determination. The computation of light extinction attributable to the natural background and source was generally described in Section 1.1.2 of this report.



### 3.5.1 

### POSTUTIL PROCESSING

The first postprocessing step involves running POSTUTIL to calculate the concentrations of visibility-affecting species S04, N03, SOA, EC, PMF, and PMC, as described in Section 3.4.1 of this report. Specifically,POSTUTIL is used to group modeled species into visibility-affectingpollutant groups as originally shown as Table 3-5, reproduced here

as Table 3-7.

BP Decatur Works BART Applicability Analysis 45 Trinity Consultants

### TABLE 3-7. ASSIGNMENT OF MODELED PM SPECIES TO LIGHT EXTINCTION GROUPS LN POSTUTIL

Modeled CALPOST Light Extinction Coefficient Components Extinction Group (m2/g) 

# IPMC800 PMC 0.6

PMC425

. . .

. . . 

### . . 

### . . . . . 

### . . . . .

. . . . . .

. . .. .

. . . . .

.. .

. . .

. . .

. . . . . . . . . . 

### . . 

### . . . 

### . . . 

### . . . .

. 

### . . .

. . . . . . . . . . .

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

### . . 

### . . 

### . . .

. . .



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

. . .

. . . . . . . . . . . . . . . . PMFl87 PMFI 12 PhIFO8 1 PhIF056 PIC081 SOIL I

In screening analyses, POSTUTIL is only run once to achieve this pollutant grouping. 

### In refined analyses, POSTUTIL is run a second time to apply the anmonia limiting method (fih4)to re-partition the distribution of HN03and NO3concentrations at each Class I area
as a function of the temperature, relative humidity, and free ammonia during each hour. 

### ALh4 processing is not run by default, and therefore was not used in the screening analyses. 

### ALM re-partitioning using the default ammonia background level of 0.5 ppb was conducted in refined analyses.

The visibility goal of the Clean Air Act is both the remedying of existing visibility inlpainnent and prevention of future visibility impairment. In its B,4RTI~7zpIementatio~1 Guidance, U.S. EPA affirms that it interprets the goal to mean return atmospheric conditions to "natural visibility conditions." For the purposes of BART analyses, the U.S. EPA has determined that it "did not intend to limit States to the use of the 20% best visibility days...States may use 20% best visibility days or annual average" to assess BART applicability.'8 The Aupst 

### 3

### 1, 2006 revision to the USTASBARTModeli~lg Protocol indicates that three options are available at the discretion of the state including Option (1) a single annual average natural background condition for each Class 

### I area; Option 

## (3, a single value representing the average haze index on the 20% estimated best visibility days at each Class 

### I area; or, Option 

### (3) monthly average natural background



## '' U.S. EPA Memorandum from Mr. Joseph Paisie to Ms. Kay Prince, as Attachment A to a proposed settlement agreement between the Utility Air Regulatory Group and U.S. EPA, published at 71 Federal Register No. 84, pp. 25,838- 25,840, May 2, 7006.



### BP Decatur Works 

### 46 Trinity Consultants BART Applicability Analysisconditions computed from estimated components of visibility-affecting pollutants and monthly average relative humidity values specific to each Class 

### I area. The Option (1) annual average natural background condition appears to be the preferred approach since analyses conducted by the VISTAS Technical Contractor for certain sources in the region used this method exclusively (for example, screening analyses of BART-eligible operationsin Alabama).

For the five Class 

### I areas withn 300 

### krn of the Decatur Works and potentially affected by BP's operations, Table 3-8 summarizes the default natural background conditionsas tabulated in Appendix 

### B of U.S. EPA's 

### Guidavlce for Esfimatirqg Natural Visibility Conditions under the Regional Haze Rule that were used to calculate natural background conditions for the preceding three approaches.



### TABLE 3-8. 

### NATURAL BACKGROUND CONCENTRATIONS FOR CLASS 1AREAS

### POTENTIALLY AFFECTED BY THE DECATUR \vORKS 

# I
Class I Area Annual Average Best Days Haze Worst Days Haze bed (~m-') Haze Index (dv) Index (dv) Index (dv) 

# I

Sipsey 21.28 7.55 3.71 1 1.39

Cohutta 21.39 7.60 3.76 11.44
Mammoth Cave 21.58 7.69 3.85 11.53 

# I Joyce Kilmer/Slickrock 21.40 7.61 3.77 11.45 

# 1

reat Smoky Mountains 11.39 7.60 3.76 11.44 * As tabulated in Appendix B of U.S. EPA's Guidance,for Estimating Natural l'isibilihl Conditions under the Regional Haze Rule (2003).
To represent natural conditions in the absence of anthropogenic sources of sulfates and nitrates using Option (I),the monthly background extinction coefficient is expressed in
terms of Rayleigh scatteringand scattering due to soils (i.e., fine particles)based on the annual average haze index, and is calculated using the following equations.

where HIis Haze Index expressed in units of deciviews (dv). Therefore,total bback for the best days at the seven Class 

### I areas within 300 

### km of the Decatur Works, including the default Rayleigh scattering coefficient is calculated as shown in the following equations.



### BP Decatur Works BART Applicability Analysis 

### 47 Trinity Consultants7.55 b,, =10e~~(~) =21.28Mm-I =b

### .,, +b 

## , -1OMrn-I +b ,,o,, 3 b,, = 11.28Mm' forsipsey

b,,,, =10exp 

### - = 21.58 ~m-' =b,,, 

## +b,, = lO~m-' 

## +b,?,, b

### ,, = 11.58 ~m-' for Mammothcave 

# (7;609)

bhsCf =10exp 

### - =21.40 h4n-' =b,, 

## +bsoi1 =10 Mn-' 

## +b,,,, b,,, =1 1.40 h4rr-I for Joyce Kilmer/Slickrock 

# (

# 713

b,,, =10exp - =21.38Mm-' =by +b,,, =10h4n-'+b,,, =bs,, =11.38~m-I forGSMNP 

# [

# 7i3

The Option (3) approach of calculating the default natural background conditions using average natural concentrations of sulfate, nitrate, and particulate species for areas in the Eastern U.S. as tabulated in Table 2-1 of U.S. EPA's 

### Guidance for Estimating Natural Visibility Conditions under theRegional Haze Rule was reviewed but not used in this analysis because the natural background conditions are essentially equivalent to the VISTAS annual average background approach such that the alternative analysis was not warranted.

The effects of relative humidity to amplify the visibility impairment of hygroscopic sulfates and nitrates were characterized using CALPOST "Method 6," which computes Ab,, using a 

### nzontlzly average relative humidity adjustment particular to each Class I area applied to background and modeled sulfate and nitrate. Table 

### 3-9 summarizes the monthly average humidity values that were applied for the seven Class 

### I areas considered in this analysis, as tabulated in Table A-3 of U.S. EPA's 

### Guidarvce for Estimatir7g Natural Visibility Conditions wider the Regional Haze Rule.

TABLE 

### 3-9. MONTHLY AVERAGEARH) FOR 

### SELECTED CLASS 1



### AREAS

Class 1Area January February March April May June July August September October November December 

# I Sipsey 3.4 3.1 2.9 2.8 3.3 3.7 3.9 3.9 3.9 3.6 3.3 3.4 

# I I Cohutta 3.3 3.1 3.0 2.8 3.4 3.8 4.0 4.2 4.2 3.8 3.4

h4ammoth Cave 3.4 3.1 2.9 2.6 32 3.5 3.7 3.9 3.9 3.4 3.2 3.5
Joyce Kilmeri 3.3 3.1 2.9 2.7 3.3 3.8 4.0 4.2 1.2 3.8 3.3 3.5 Slickrock 

# I Great Smoky

Mountains I I * As tabulated in Table A-3 of U.S. EPA's Guidance,forEstiinatingNatural T'isibilif~ Conditions under the Regional Haze Rule (2003).

BP Decatur Works 

### BART ApplicabilityAnalysis 

### 48 Trinity ConsultantsNatural background conditions for each Class 1 area were calculated using the data summarized in Tables 3-7, 3-8, and 3-9, and the revised IMPROVE light extinction formula, which is summarized in the following equation.

CALPOST is 

### run separately for each Class 

### I area to obtain the necessaryvisibility statistics for evaluating impacts compared to the BART visibility impairment thresholds. The inputs to CALPOST involve selection of the visibility method (i.e., Method 

### 6) and entry of Class 

### I area-specific data for computing background extinction and monthly relative humidity factors for hygroscopic aerosols as described in Section 3.5.2. CALPOST contains a receptor selection option that allow subsets of a receptor network modeled in CALPUFFto be selected for processing in a given CALPOST run. This selection specifies which receptors representing a single Class I area are selected for processing from a CALPUFF output file that may contain receptors from several Class 

### I areas.

For screening analyses, the peak 24-hour average visibility impact for each year and Class 

### I area was tabulated. The previously described Option (1) was used to quantify visibility impacts relative to annual average natural background conditions.

Refined analyses were analyzedby tabulatingthe 98" percentile 24-hour average visibility impact for each year and Class 

### I area. Option (1) was used to quantifyvisibility impacts relative to annual average natural background conditions. As described in Section 3.2.1, the default interpretation of the 98" percentile @-highest day regardless of variability at each receptor) was evaluated for each year.

To facilitate the use of the revised IMPROVE algorithm for assessing BART applicability, the VISTAS Technical Advisor developed and distributed a spreadsheetprocessing tool to implement the revised IMPROVE light extinction algorithm, designated as the CALPOSTIMPROVE Processor Version 2 (September 29,2006). This processor calculates the reconstructed light extinctionusing the revised IMPROVE algorithm and output from the current version of the CALPOST postprocessor. To inlplelnentthe CALPOST-IMPROVE Processor, three additional data points are required: background concentrationof gaseous NOz,Rayleigh scattering parameter corrected for site-specific elevation, and an estimate of the average background sea salt aerosol concentration. The following specific inputs to the tool were used:

BP Decatur Works BART Applicability Analysis 49 Trinity ConsultantsA Elevation-dependent Rayleigh scattering coefficient of 11 

### Mm-' as tabulated in the VISTAS spreadsheet

A Sea Salt background concentration of 0.05 pg/m3as tabulated in the VISTAS spreadsheet

A 24-hour average NO? concentration at each receptor attributable to BART-eligible

sources at BP's Decatur Works as calculated by an additional CALPOST analysis

Although other anthropogenic(stationary and mobile) sources contribute to background levels ofNO? at Class 

### I areas, for the purposes of this analysis, the background NO? concentration is assumed to be attributable only to BART-eligible sources at BP's Decatur Works. The Whour average NOz concentration for each day and receptor was calculated by separate CALPOST processing analyses, and converted from units of pg/m3(default model output) to parts per billion as required by the tool. The NO? concentration entered into the CALPOST-IMPROVEProcessor for each 24-hour average visibility impacts corresponds to the specificday and receptor at which the modeled visibility impact occurs. The N02/NOxratio was conservatively entered as 1.0in the CALPOST-IMPROVE Processor. Appendix A of this report contains printed output from the CALPOSTIMPROVE calculation worksheets and copies of each spreadsheet are included on the electronicmedia enclosed with this report.

Quality assurance of postprocessing analyses was conductedby verifying the sequence of postprocessing (i.e., POSTUTIL, including

### ALM for refined analyses,followed by CALPOST) and that appropriate data files are referenced throughout the calculation sequence. The CALPOST inputs that were checked include the following: Visibility technique (Method 6) Monthly Class I-specific relative humidity factors for Method 6 Background light extinction values calculated as appropriate using annual average natural background Option (1) Inclusion of all appropriate species from modeled sources (e.g., sulfate, nitrate, organics), coarse and fine particulate matter, and elemental carbon. Appropriate species names for coarse 

### PM used Extinction efficiencies for each species AppropriateRayleigh scatteringtenn for screening and refined analyses Screen to select appropriate Class 

### I receptors for each CALPOST simnulation.

BP Decatur Works BART Applicability Analysis 5 0 Trinity ConsultantsScreeninganalyses of visibility impacts attributableto BP' s Decatur Works were conducted to deternine whether the facility is subject to BART using a conservative assessment,and to focus the scope ofrefined analyses by demonstratingthat visibility impaimlent is not likely to occur at more distant Class 

### I areas. The screening analyses were conducted using the emissionsdata represented in Section 2 of this report, the screeningCALMET and CALPUFF methods described in Sections 3.2, 3.3, and 3.4 of this report, and the VISTAS default postprocessing methods. For each Class 

### I area, screening analysisresults are presented for both the natural gas and fuel oil emissions scenarios for Boiler 4302. All impacts are computed relative to annual average natural background conditions using Option 

### (1) described in Section 3.5 of this report.

Table 4-1 summarizes the modeled peak, 24-hour average visibility impacts at Sipsey WA attributable to BP's Decatur Works during exclusivenatural gas firing in Boiler 4302. Results are presented in terms of visibility impact and the total number of days exceeding the 1.0 dv causation and 0.5 dv contribution thresholds, respectively.

Natural Background 2001 2002 2003 Method Adv(>l.Odv,>0.5dv) Adv(>l.Odv,>0.5dv) Adv(>I.Odv,>0.5dv)
Annual Average 0.480 (0, 0) 0.390 (0, 0) 0.427 (0, 0)

Table 4-2 summarizes the modeled peak, 24-hour average visibility impacts at Sipsey WA attributable to BP's Decatur Works during fuel oil firing in Boiler 4302. Results are presented in
terms of visibility impact and the total number of days exceeding the 1.0dv causation and 0.5 dv contribution thresholds, respectively.



### TABLE 4-2. PEAK 24-HOUR AVERAGEVISIBILITY IMPACTS AT SIPSEY DURING 

### FUEL OILFIRING IN 

### BOILER 4302

Natural Background 2001 2002 2003 Method Adv (> 1.0 dv, > 0.5 dv) Adv (> 1.0 dv, > 0.5 dv) Adv (> 1.0 dv, > 0.5 dv)
Annual Average 0.699 (0, 3) 0.588 (0,4) 0.662 (0, 5)

The results presented in Tables4-1 and 4-2 indicate that refined analyses were necessary to evaluate visibility impacts at Sipsey since peak visibility impacts when fuel oil is burned in Boiler 4302 exceed the contribution threshold. During normal natural gas firing, BPYs BART-eligible source does not contribute to visibility impairment at Sipsey.

BP Decatur Works 

### BART Applicability Analysis 51 Trinity ConsultantsTable 4-3 summarizes the modeled peak, 24-hour average visibility impacts at Cohutta WA attributableto BP's Decatur Works during exclusive natural gas firing in Boiler 4302. Results are presented in terms of visibility impact and the total number of days exceeding the 1.0 dv causation and 0.5 dv contribution thresholds, respectively.



# INatural Background 2001 2002 2003

Method Adv(>l.Odv,>O.5dv) Adv(>l.Odv,>O.5dv) Adv(>l.Odv,>0.5dv) 

# I

Annual Average 0.021 (0,O) 0.033 (0,O) 0.049 (0, 0)

Table 4-4 summarizes the modeled peak, 24-hour average visibility impacts at Cohutta WA attributable to BP's Decatur Works during fuel oil firing in Boiler 4302. Results are presented in terms of visibility impact and the total number of days exceedingthe 1.0 dv causation and 0.5 dv contributionthresholds, respectively.



### TABLE 4-4. PEAK HOUR 

### AVERAGE VISIBILITY IMPACTS AT 

### COHUTTA DURLYG 

### FUEL OIL

### FIRING IN 

### BOILER 4302

Natural Background 2001 2002 2003 Method Adv(>l.Odv,>0.5dv) Adv(>l.Odv,>0.5dv) Adv(>l.Odv,>0.5dv)

Annual Average 0.071 (0,O) 0.084 (0, 0) 0.I08 (0,O)

The results presented in Tables 4-3 and 4-4 indicate that refined analyses were not necessary to evaluate visibility impacts at Cohutta sincepeak visibility impacts when natural gas or he1oil is burned in Boiler 4302 do not exceed the contribution threshold.

Table 4-5 summarizes the modeled peak, 24-hour average visibility impacts at Mammoth Cave NP attributable to BP's Decatur Works during exclusivenatural gas firing in Boiler 4302. Results are presented in terms of visibility impact and the total number of days exceeding the 1.0dv causation and 0.5 dv contribution thresholds, respectively.



### TABLE 4-5. PEAK 24-~0UR AVERAGE VISIBILITY IMPACTS AT M.4.MkIOTH 

### CAVE DURIRTG 

### NATURAL GAS FIRING IN 

### BOILER 4302 

# INatural Background 2001 2002 2003

Method Adv(>l.Odv,>0.5dv) Adv(>l.Odv,>0.5dv) Adv(>1.0dv,>0.5dv) 

# 1

Annual Average 0.023 (0,O) 0.041 (0'0) 0.036 (0,O)

BP Decatur Works BART Applicability Analysis 52 Trinity ConsultantsTable 4-6 summarizes the modeled peak, 24-hour average visibility impacts at Mammoth Cave

### Nl' attributableto BP's Decatur Works during fuel oil firing in Boiler 4302. Results are presented in
terms of visibility impact and the total number of days exceeding the 1.0 dv causation and 0.5 dv contribution thresholds, respectively.



### TABLE 4-6. PEAK 24-HOUR AVERAGE VISIBILITY IMPACTS AT MAMMOTH 

### CAVE DURING 

### FUEL OIL FIRING IN 

### BOILER 4302

Natural Background 2001 2002 2003 Method Adv(>l.Odv,>0.5dv) Adv(>l.Odv,>0.5dv) Adv(>l.Odv,>O.5dv)
Annual Average 0.092 (0,O) 0.106 (0, 0) 0.101 (0,O)

The results presented in Table 4-5 and 4-6 indicatethat refined analyses were necessary to evaluate visibility impacts at Mammoth Cave since peak visibility impacts when natural gas or fuel oil is burned in Boiler 4302 do not exceed the contribution threshold.

Table 4-7 summarizes the modeled peak, 24-hour average visibility impacts at Joyce Kilmerl SlickrockWA attributableto BP's Decatur Works during exclusivenatural gas firing in Boiler 4302. Results are presented in terms of visibility impact and the total number of days exceeding the 1 .O dv causation and 0.5 dv contribution thresholds, respectively.

Natural Background 2001 2002 2003 Method Adv(>l.Odv,>0.5dv) Adv(>l.Odv,>0.5dv) Adv(>l.Odv,>0.5dv)
Annual Average 0.009 (0, 0) 0.020 (0,O) 0.016 (0, 0)

Table 

### 4-8 summarizes the modeled peak, 24-hour average visibility impacts at Joyce Kilmerl SlickrockWA attributableto BP's Decatur Works during fuel oil firing in Boiler 4302. Results are presented in terms of visibility impact and the total number of days exceeding the 1.0 dv causation and 0.5 dv contribution thresholds,respectively.



### TABLE 4-8. PEAK 24-HOURAVERAGE VISIBILITY IMPACTS AT 

### JOYCE KILMEWSLICKROCK DURING 

### FUEL OIL FIRING IN 

### BOILER 4302 

# INatural Background 2001 2002 2003

Method Adv(>l.Odv,>0.5dv) Adv(>l.Odv,>0.5dv) Adv(>l.Odv,>0.5dv) 

# I

Annual Average 0.042 (0, 0) 0.067 (0,O) 0.041 (0, 0) 

# I

BP Decatur Works BART ApplicabilityAnalysis 5 3 Trinity ConsultantsThe results presented in Table 4-7 and 4-8 indicate that refined analyses were necessary to evaluate visibility impacts at Joyce Kilmer/Slickrocksince peak visibility impacts when natural gas or fuel oil is burned in Boiler 4302 do not exceed the contribution threshold.

Table 4-9 summarizes the modeled peak, 24-hour average visibility impacts at Great Smoky Mountains

### NP attributable to BP's Decatur Works during exclusivenatural gas firing in Boiler 4302. Results are presented in terms of visibility impact and the total number of days exceeding the 1.0 dv causation and 0.5 dv contribution thresholds, respectively.



### TABLE 4-9. PEAK HO HOUR 

### AVERAGE VISIBILITY IMPACTS AT 

### GREAT SMOKY >$OUNTAINS DURLWG 

### NATUIL~L GAS FIRLWG IN 

### BOILER 4302

Natural Background 2001 2002 2003 Method Adv(>l.Odv,>OSdv) Adv(>l.Odv,>0.5dv) Adv(>l.Odv,>OSd~)

Annual Average 0.01 1 (0, 0) 0.027 (0, 0) 0.021 (0,O) 

# I

Table 4-10 summarizes the modeled peak, 24-hour average visibility impacts at Great Smoky Mountains 

### NP attributableto BP's Decatur Works during fuel oil firing in Boiler 4302. Results are presented in terms of visibility impact and the total number of days exceeding the 1.0 dv causation and 0.5 dv contribution thresholds, respectively.



### TABLE 4-10. PEAK 24-HOUR AVERAGE VISIBILITY IMPACTS AT 

### GREAT SMO107 MOUNTAINS DURING 

### FUEL OIL FIRING IN 

### BOILER 4302 

# INatural Background 2001 2002 2003

Method Adv(>l.Odv,>OSd~) Adv(>I.Odv,>0.5dv) Adv(>l.Odv,>OSdv) 

# I Annual Average 0.043 (0,O) 0.060 (0, 0) 0.062 (0,O)

The results presented in Table 4-9 and 4-10 indicate that refined analyses were necessary to evaluate visibility impacts at Great Smoky Mountains since peak visibility impacts when natural gas or fuel oil is burned in Boiler 4302 do not exceed the contribution threshold.

Screening analyses of visibility inlpacts attributable to BP's Decatur Works during natural gas firing in Boiler 4302 indicated no peak 24-hour average impacts above the 0.5 dv contributionthreshold at any Class 

### I area, suggestingthat no refined analyses are required for this operating scenario. Screening analyses of visibility impacts attributable to BP's Decatur Works during fuel oil firing in Boiler 4302 indicatedpeak 24-hour average impacts above the 0.5 dv contributionthreshold only at Sipsey. Therefore, refined modeling was required to evaluate BP's contributions using refined modeling methods for this operating scenario.



### BP Decatur Works 

### BART Applicability Analysis 54 Trinity ConsultantsBecause the screening analysis results described in Section 4 of this report exceededthe 0.5 dv contribution threshold for impacts at Sipsey, refined analyses were conductedusing the emissions data represented in Section 2 of this report, the refined CALMET and CALPUFF methods described in Sections 3.2, 3.3, and 3.4 of this report, and the postprocessing methods includingthe CALPOSTIMPROVE implementation of the revised light extinction algorithm described in Section 3.5. Refined analysis results are presented only for the fuel oil emissions scenario for Boiler 4302 since the screening analyses presented in Section 

### 4 indicated BP's Decatur Works does not contribute to visibility impairment under the natural gas operating scenario. All impacts are computed relative to annual average natural background conditionsusing Option (1) described in Section 3.5 of this report.

Table 5-1 summarizes the top eight modeled 24-hour average visibility impacts of each data analysis year at SispeyWA attributable to BP's Decatur Works during fuel oil firing in Boiler 4302 using refined modeling methods and the default CALPUFF option to disable puff splitting. The 98' percentile impact is represented as the 8'-high 24-hour average impact among the three years of analysis as computed using CALPOST output and the VISTAS CALPOST-IMPROVE Processor. The total number of days exceeding the 

### 1.O dv causation and 0.5 dv contributionthresholds are also summarized.

Natural Background Ranked Ranked Ranked Maximum 8th-~igh Adv Method 2001 Adv 2002 Adv 2003 Adv (Total Days > 1.0 dv, > 0.5 dv)

Annual Average

As an alternative representation of the 98" percentile, Table 5-2 summarizes a ranlung of the top 25 daily average impacts over the three-year period modeled to quantify the 2znd-high impact over three years.

BP Decatur Works BART Applicability Analysis 5 5 Trinity Consultants

### TABLE 5-2. 

### RANKED 24-HOURAVERAGE VISIBILITY IMPACTS AT SIPSEY OVER 2001 THROUGH 2003

### DATA ANALYSIS 

### PERIOD

Overall Rank Annual Rank Adv

Refined CALPUFF modeling analyses were conducted to compute 24-hour average visibility impacts at Sipsey for the operating scenario in which fuel oil is conlbusted in Boiler 4302. Default methods for calculating the 98th percentile were used with the VISTAS CALPOST-IMPROVE Processor to implement the revised light extinction calculation. Table 

### 5-3 sunlmarizesthe computed impacts 

### in comparison to the 0.5 dv contributiontlnesl~old.

Refined CALPUFF Maximum gth-~igh Adv 22nd-~igh Adv Processing of 3 Years over 3 Years

Fuel Oil Combustion 0.486 0.40 1

BP Decatur Works BART Applicability Analysis 

### 56 Trinity ConsultantsUsing analysis methods prescribed by the U.S. EPA, VISTAS, and ADEM, BP conducted BART Applicability Analyses of emissions of visibility-affecting pollutants from BART-eligible emission units at the Decatur Works. BP evaluated maximum actual 24-hour average emissions from two operating scenarios: 

### (1) exclusive natural gas firing in Boiler 4302, which is the normal operating scenario over the past three to five years; and, (2) he1oil firing in Boiler 1302,which is a pemitted operating scenariobut not a normal operating condition, since no fuel oil has been in fired in Boiler 4302 in the last three to five years. The natural gas combustion scenario provides a true indication of BP's visibility impact under normal steady-state operationsbecause the facility does not typically burn fuel oil in Boiler 4302. Nonetheless, fuel oil combustionwas evaluated to demonstrate visibility impacts in a manner consistentwith U.S. EPA guidance.

Refined modeling and postprocessing analyses to quantify the 

### 98" percentile, 24-hour average visibility changeusing the revised IMPROVE light extinction algorithm demonstratethat impacts attributableto BP's Decatur Works are less than the 0.5 dv contributionthreshold relative to annual average natural background conditions. These results indicatethat BP's Decatur Works is not subject to BART because the BART-eligible source does not contribute to visibility impairment at any Class 

### I areas.

BP Decatur Works BART Applicability Analysis 

### 57 Trinity Consultants

### SAMPLE CALPUFF, POSTUTIL, AND 

### CALPOST 

### LNPUT FILES

BP Decatur Works A- 1 Trinity Consultants BART Applicability Analysis

## CALPUFF BATCH PROCESSING FILE

12-KM 

## SCREENINGANALYSES

BP Decatur Works BART Applicability Analysis 

### A 

### - 2 Trinity ConsultantsREM BPDCTRAL REM BART APPLICABILITY ANALYSIS WITH UPDATED 12 KM CALMET REM FAH 8.23.06

REM RUN 2001 CALL CALPUFFL.EXE BPDCTRALO1.INP CALL POSTUTILL.EXE BPDCTRALUTO1.INP CALL CALPOSTL.EXE BPDCTRALVANSIO1.INP CALL CALPOSTL.EXE BPDCTRALVANMCO1.INP CALL CALPOSTL.EXE BPDCTRALVANJKO1.INP CALL CALPOSTL.EXE BPDCTRALVANGSO1.INP CALL CALPOSTL.EXE BPDCTRALVANC001.INP

REM RUN 2002 CALL CALPUFFL.EXE BPDCTRAL02.INP CALL POSTUTILL.EXE BPDCTRALUT02.INP CALL CALPOSTL.EXE BPDCTRASVANSIO2.INP CALL CALPOSTL.EXE BPDCTRALVANMC02.INP CALL CALPOSTL.EXE BPDCTRALVANJK02.INP CALL CALPOSTL.EXE BPDCTRALVANGS02.INP CALL CALPOSTL.EXE BPDCTRALVANCOO2.INP

REM RUN 2003 CALL CALPUFFL.EXE BPDCTRAL03.INP CALL POSTUTILL.EXE BPDCTRALUT03.INP CALL CALPOSTL.EXE BPDCTRALVANSI03.INP CALL CALPOSTL.EXE BPDCTRALVANMC03.INP CALL CALPOSTL.EXE BPDCTRALVANJK03.INP CALL CALPOSTL.EXE BPDCTRALVANGS03.INP CALL CALPOSTL.EXE BPDCTRALVANC003.INP

PAUSE