TABLE 2-5. NOMENCLATURE FOR PM EMISSIONS SPECIATION ANALYSIS 

Nomenclature Description 

TSP Total suspended paticulate, 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 aerodynanic diameter < 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 25 pn3 

PMo.63-I Filterable particulate matter with an aerodynanic diameter > 0.625 and < I .O p3 

PMOS-0.625 Filterable particulate matter with an aerodynamic diameter > 0.5 and < 0.625 pm 

CPM Condensable particulate matter (organic and inorganic) 

POC Primary organic condensable enussions 

PIC Primary inorganic condensable enlissions 

TPMIo Filterable Ph410 + CPM 

TPM2.s Filterable PM2., + 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 he1 and 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. 

-4 discussion 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 Troching Progress 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 Consultants 
Extinction 

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-fired boiler at the Decatur facility.' 

Boiler #AB 4302 is a 281 MMBtuihr unit equipped with a low NOx burner. PM emissions 

from this boiler are due to the combustion of residual fuel oilg andlor 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 determine Ph4 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 sunlmarizes the 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 1 3, Fuel Oil Combustion, September 1998. 

'O Battye and Boyer, Catalog qf Global Etnissions Inientories and Emission bn~ento~y Tools for Block Carbon, 

prepared for EPA DRAFT January 2002, Table 6. 

BP Decatur Works 

BART Applicability Analysis 

16 Trinity Consultants 
Speciation Data 

PM2.5 as a % of PMlo 

Filterable as a Oh of PhJlo 

Condensable as a % of PM,, 

EC as a % of PM,,, 

Organic portion of CPM 

Inorganic portion of CPM 

PM6-,, as a % of PMlo 

PM2,5, as a % of PM, 

PM1 .25-2.5 as a % of PMIo 

PMl-l,25 as a % of Ph4,, 

Ph40,62,.l as a % of PM,, 

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 1.3-5 Industrial 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 % of TSP 

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 emissions by 

multiplying the maximum hourly PMlo emission rate by 14.6%. Next, the POC emissions 

were determined by multiplying the calculated CPM emissions by the organic condensable 

percentage of 15%. POC was assumed to be evenly split between the two size categories, 

0.625- 1.0 pm and 0.5-0.625 pm. PIC emissions were calculated using a similar 

methodology, using the inorganic condensable percentage of 85%. Filterable PMlo 

emissions were divided amongst six different size categories by multiplying filterable PMlo 

emissions by the percentage of PMlo for each size category, yielding hourly emissions of 

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 OIL FIRED 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 

0.58 
fl PIC. sulfate (0 5-1.0 mrcrons) 

PhiiC (6-1 0 rn~crons) 

0 PMC' (1.5-6 mrcrons) 

B PMF (1 "15-1.5 microns) 

PMF (1.3-1 '25 microns) 

PMF (0 625-1 0 microns) 

B i34F (0.5-0.625 microns) 

O EC (0.5-0.625 rnicmns) 

' AP-12, Sectron 1 4, h'aruiai Gas C'omhustron, July I998 
Global 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 GAS COMBUSTION SPECIATION DATA 

Speciation Data 

PM,,, as a % of TPM,, 

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 asa % 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 1.4-2 provides the ratio of filterable to condensable PM. Based on the assumption in the footnotes of Table 

1.4-2 that all PM is less than 1.0 microns, the size speciation was 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 equally between 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 of the 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, Cafalog of 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 Consultants 
Emission 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 i urn) 

1.25 - 2.5 1.0 - 1.25 0.625 - 1.0 0.5 - 0.625 

POC (0.5-1.0 mlcrons) 

PIC, non-sulfate (0.5-1.0 microns) 

PIC, sulfate (0.5-1.0 microns) 

PMF (0.625-1 .O microns) 

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 

Slurry Drums, Dryer Vent Scrubbers, and Hold Tank were condensable. 

As no default size speciation data were available, BP utilized general information in 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 

efficiencies by 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 

uncontrolled particle 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 crystalline nature of the PTA particulate emissions 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 nliscellaneous process 

vents. BP assumed that the condensable PM emissions were distributed equally between 

the two smallest size categories, 0.625-1.0 pm 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 Applicability Analysis 

-- - 

Control Efficiency for Specific Size ~an~e] 

0 - 2.5 pnl 2.5 - 6 pm 6 - 10 pm 

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 P3l SPECLATED EMISSIONS (LB/HR) 

PIC lum) 

Emission Unit Stack Code 8.625 - 1.0 0.5 - 0 625 

Crystallizer Scrubber Vent 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 Tad Vent BPD25 

Storage Silo Baghouse BPD3U 

Crystallizer Scrubber J'ent BPD46 

Feed Sluq Dm 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 

0 PMC (6-10 microns) 

E3 PMC (2.5-6 nncrons) 

1 I3 PMF (1.25-3.5 nncrons) 

PMF (I .O-1.35 microns) 

E PMF (0.625-1.0 microns) 

4.68 

Actual stack parameters 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 

analyses prepared 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 he1 oil combustion en~issions for Boiler 4302. 

BP Decatur Works 

BART Applicability Analysis 

2 2 Trinity Consultants 
TABLE 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- l Ol Process Heater 

Kb-102 Process Heater 

Kb-401 Process Heater 

Marine Dock Flare 

Kb- 104 7 MMBTUh Reboiier 

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 1 0 

BoilerBPD 12 

#4 OxidationiBPDZO 

#4 PTNBPD2 I 

#4 PTNBPDX 

A4 PTNBPD23 

#4 PTNBPD24 

#4 PTNBPD25 

#I PWBPD27 

#I PWBPD28 

kl PXIBPD29 

#5 OxidationBPD38 

#2 PXBPD40 

#2 PXBPD4 1 

#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. Stack parameters for Stack ID'S BPDO4. BPD24. BPD49 are average values. which represent a group of similar emission sources. Emmion rates from 

these sources are equal to the total emission rate from all individual sources within the group. 

BP Decatur Works 

BART Applicability Analysis 

Trinity Consultants 
TABLE 2-14. MODELED EMISSION RATES FOR BART-ELIGIBLE EMISSION UNITS 

Emission Unit Sotirce Codelstack ID 

3ystallizer Scrubber Vent [Feed Shy Drum 

Dryer Vent Scrubber 

PTA Silos Dust Collector System 

Catox Furnace Storage Silo Vent Scrubber 

Boiler #AD 4302 

Storage Silo Baghouse 

Crystallizer Scrubber Vent 

Peed Slur~y Drum 

D~yer Vellt Scrubber 

Silos Storage Atm Centrift~ge I lold Tank Vent 

EB-1 01 Process I leater 

EB- 103 Process I leater 

EB-I 04 Process I leater 

Storage Silo Baghouse 

Kb-l Ol Process Heater 

Kb- 102 Process Heater Kb-40 1 Process Heater Marine Dock Flare 

Kh-104 7 MMBTUIlir Reboiler 

PX Flare (KM-503) 

Crystallizer Scrubber Vent 

Feed Shy Drum 

Dryer Vent Scrubber 

Silos Storage 

POC (Iblhrl 

,625 - 1 .O 0.5 - 0.62! 

PIC, non-sulhte (Ibll~r) 

1.625 - 1 .0 0.5 - 0.625 

I'MC (Ibllir) 

5-10 2.5-6 

PMF 

1.25 - 2.5 1.0 - 1.25 

BP Decatur Works 

BART Applicability Analysis 

24 
Emission Unit Source Codelstack ID 

Crystallizer Scrubber Vent 

Feed Slurry Drllm 

Dryer Vent Scrubber 

I'TA Silos Dust Collector System 

Catox Furnace 

Storage Silo Vent Scruhber 

Boiler #AD 4302 

Storage Silo Bagliouse 

Crystallizer Scrubber Vent 

Feed Slurry Drum Dryer Vent Scrubber 

Silos Storage Atm Centrifi~ge I lold Tank Vent 

ED- I0 I I'rocess IHeater 

88-103 Process Heater 

EB- 104 Process Heater Storage Silo Bagliouse 

Kb- I0 I Process Heater 

Kb- 102 Process I-leater 

Kb-40 1 Process I-leater Marine Dock Flare 

Kb-104 7 MMBTUIhr Reboiler 

PX Flare (KM-503) 

Crystallizer Scrubber Vent 

Feed Slurry Drum 

Dryer Vent Scrubber Silos Storage 

PIC, non-sulfate (Iblhr) 

0.625 - 1.0 0.5 - 0.625 

PMF 

1.25 - 2.5 1.0 - 1.2

BP Decatur Works BART Applicability Analysis 

2 5 

Section 3 of this 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 VISTAS BARTJ4odeling 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 of time- 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 

BART A4odeliiig 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, CALh4ET Version 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 VISTAS BARTA4odeling 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 Consultants 
BART 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 VISTAS BARTA40deling Protocol makes sellera1 important distinctions between 

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 average predicted 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 VISTAS BART 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 Consultants 
common 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 Quality A4odels. IWAQM default model 

options as described in the following section of this report were prescribed for use in both 

screening and refined analyses. The VISTAS BARTA4odeling 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. 

In the 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 HN03 and NO3 concentrations 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/ISTAS BART Modeling 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 VETAS BARTA40deling 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 iiz paragraph 9.3(c). lliese ~izesoscale iiieteoro1ogicalJields should be used 

in conjunction ~ith available standard [National Weather Sen:ice] MS or 

coriiparable meteo~~ological obsei-vatioizs ~ithii? and iiear the modelir~g doiizain. 

BP Decatur Works 

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Cell 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 following three years of MM5 meteorological data were assembled by 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 (developed by 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 Modeling Protocol, 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 southenl tip 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 

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Geological 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 BART Modeling Protocol, 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. CALMET was 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 

BART Adodeling Protocol) were applied to reflect terrain on the scale of the CALMET grid 

(i.e., 12 km). 

3.3.5 4-MI REFINED GRID CALMET PROCESSING 

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. 

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Parameters affecting turbulent dispersion that are observed hourly at surface stations 

include wind speed and direction, temperature, cloud cover and ceiling, relative humidity, 

and precipitation type. Surface data 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. 

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

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

occurs. In general, twice-daily upper air data are collected by balloons launched 

simultaneously across the observation network at 0000 Greenwich Mean Time (GMT) and 

1200 GMT, which correspond to 6:OOpm and 6:00am, respectively in the Central Time 

Zone, including Alabama. 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 

representations of 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 

conditions vary less and are generally not 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 concentrations are an 

important part of the BART Applicability Analysis. Therefore, it was necessary to include 

observations of precipitation in the CALMET analysis. Precipitation data were collected 

from selected surface meteorological data stations included in the analysis, plus 

Cooperative Observation Network (COOP) stations nearer to or within the domain. 

Precipitation data were extracted from anlong the NCDC's available data inventory to 

optimize spatial coverage and representation of the domain. Raw observations from these 

stations were 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 

Modeling Protocol describes quality assurance techniques used by the contractor to 

validate the model's performance. 

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

BP Decatur Works 32 Trinity Consultants 

BART Applicability Analysis 
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 CALPCFF parameters. Appendix A of this BART Applicability Analysis 

Report contains sample 12-km screening and I-km refmed CALPUFF input files that can be 

compared to the IWAQM recommendations to 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-affecting pollutants 

considered in the CALPUFF analysis. Emission rates were calculated following U.S. EPA 

and ADEM BART guidance for primary emissions of SO?, H2S04, NOX and 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 SO4 was 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 gaseous pollutants (SO?, SO4, 

and NOx) and unit emissions (e.g., 1 g/s) of each of six generic particle categories 

distinguished and designated by 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 distribution is the only distinguishing feature of these 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. REPRESENTATIONF 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. 

The preceding 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 

emissions profiles of speciated PM, the use of unit 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 14 particle 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. 

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I Modeled 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-I and 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 (PMI 25.2.5, PMI-I 25, PMo 645.1, PMo 5.0 625) 

ECO56 

So that explicit modeling of the 14 particle 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 CALPUFF utilizes the deposition velocity associated with the geometric mass mean 

diameter. 

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BART Applicability Analysis 

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To post-process the CALPUFF output concentrations that 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 emission rate. Table 3-5 summarizes the POSTUTIL 

grouping of modeled PM species into light extinction groups, and the light extinction 

coefficient subsequently used in CALPOST to compute light extinction due to the multiple 

emission points at the source. 

TMLE 3-5. 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 changes to 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 14 PM types and sizes plus the SOz, SO4, NOx, 

HN03, and NO3 species results in a total of 19 modeled 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 SO4 and NO3) of particle species simulated in the model. 

This modified approach follows conceptually the steps outlined in the revised VISTAS 

BART h4odeling Protocol as evidenced between comparisons between the two methods. 

Results using the explicit method for multiple emission points and the sample method 

using a single point 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 

conlparative analysis are further described in Appendix B and included with the electronic 

media provided with this BART Applicability Analysis Report to demonstrate that explicit 

modeling of PM emissions results in equivalent calculations of visibility impacts. 

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3.4.2 CALPUFF DISPERSION ALGORITHMS 

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

the VIST4S BART Modeling Protocol, the use of Pasquill-Gifford (ISC-like) dispersion 

coefficients was 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 

of building downwash were not considered in the BART Applicability Analyses. 

3.4.4 CALPUFF MODELING DOMAINS AND CLASS IAREA 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-regional Domain 4. The size of each conlputational domain 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 of puffs 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-affecting pollutants 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 3-1 1.17 

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. 

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60m non-urban 
Monthly average ozone background values were computed based on daytime average 

ozone concentrations from the 0ZONE.DAT file (6am-6pm average ozone concentrations 

computed by month) of each year for substitution should all observations be missing for a 

particular hour of the dataset. Table 3-6 summarizes the monthly average ozone values 

computed for this substitution for screening and refined analyses, respectively. 

TABLE 3-6. MONTHLY AVERAGE 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 BART Modeling Protocol 

envisioned the use of modeled boundary conditions of anvnonia and sulfates in the refined 

analysis of chemical transformations involving these species and nitrates. However, 

VISTAS' Technical Analysis Workgroup has since concluded that modeled background 

and boundary conditions should not be utilized for BART modeling purposes because 

"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-partition the 

HN03 and NO3 equilibrium distributions using only a constant 0.5 ppb ammonia 

background level. 

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As recommended by the VISTAS BART Modeling Protocol, the default integrated puff 

sampling methodology was enabled for both screening and refined CALPUFF analyses. Ln 

the screening analyses, the default setting to disable puff splitting algorithms was retained. 

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. 

3.4.7 QUALITY ASSURWCE OF CALPUFF ANALYSES 

Sample CaPUFF input 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 of the CALPUFF model inputs 

indicates that default values, as prescribed by IWAQM (Appendix B) and in the VISTAS 

BART Modelirig Protocol, were used with the exception of the source-specific model 

options described in this report. Source parameters input for each BART-eligible 

emissions unit were verified with the information presented in Section 2 of this report. The 

location and elevations of 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 HAZE INDEX CALCULATIONS 

Using the concentrations of 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-affecting pollutant groups as originally shown as Table 3-5, reproduced here 

as Table 3-7. 

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TABLE 3-7. ASSIGNMENT OF MODELED PM SPECIES TO 

LIGHT EXTINCTION GROUPS LN POSTUTIL 

Modeled CALPOST Light Extinction Coefficient 

Components Extinction Group (m2/g) 

I PMC800 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 HN03 and NO3 concentrations 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 USTAS BART Modeli~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 Analysis 
conditions 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 

operations in 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 conditions as 

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 1 AREAS 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 1 1.44 

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 1 1.44 

* 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 scattering and scattering due to soils (i.e., fine particles) based on the 

annual average haze index, and is calculated using the following equations. 

where HI is 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. 

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7.55 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 = 10 exp - = 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 the Regional 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 1 Area 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 3 2 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,for Estiinating Natural T'isibilif~ Conditions under the Regional Haze Rule (2003). 

BP Decatur Works 

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48 Trinity Consultants 
Natural 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 necessary visibility 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 

CALPUFF to 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 analyzed by tabulating the 98" percentile 24-hour average visibility 

impact for each year and Class I area. Option (1) was used to quantify visibility 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 spreadsheet processing 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 extinction using the revised IMPROVE algorithm and output from the 

current version of the CALPOST postprocessor. To inlplelnent the CALPOST-IMPROVE 

Processor, three additional data points are required: background concentration of 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 

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49 Trinity Consultants 
A Elevation-dependent Rayleigh scattering coefficient of 11 Mm-' as tabulated in the 

VISTAS spreadsheet 

A Sea Salt background concentration of 0.05 pg/m3 as 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 of NO? 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-IMPROVE Processor for each 24-hour average visibility impacts 

corresponds to the specific day and receptor at which the modeled visibility impact occurs. 

The N02/NOx ratio was conservatively entered as 1.0 in 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 

electronic media enclosed with this report. 

Quality assurance of postprocessing analyses was conducted by 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 

Appropriate Rayleigh scattering tenn 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 Consultants 

Screening analyses of visibility impacts attributable to BP' s Decatur Works were conducted to 

deternine whether the facility is subject to BART using a conservative assessment, and to focus the 

scope of refined analyses by demonstrating that visibility impaimlent is not likely to occur at more 

distant Class I areas. The screening analyses were conducted using the emissions data represented in 

Section 2 of this report, the screening CALMET 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 analysis results 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 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. 

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 1.0 dv causation and 0.5 dv 

contribution thresholds, respectively. 

TABLE 4-2. PEAK 24-HOUR AVERAGE VISIBILITY IMPACTS AT SIPSEY 

DURING FUEL OIL FIRING 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 Tables 4-1 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 

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Table 4-3 summarizes the modeled peak, 24-hour average visibility impacts at Cohutta WA 

attributable to 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. 

I Natural Background 200 1 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 exceeding the 1.0 dv causation and 0.5 dv 

contribution thresholds, 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 since peak visibility impacts when natural gas or he1 oil 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 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. 

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

DURIRTG NATURAL GAS FIRING IN BOILER 4302 

I Natural 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 Consultants 
Table 4-6 summarizes the modeled peak, 24-hour average visibility impacts at Mammoth Cave Nl' 

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 1.0 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 indicate that 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 

Slickrock WA attributable to 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 .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) 0.01 6 (0, 0) 

Table 4-8 summarizes the modeled peak, 24-hour average visibility impacts at Joyce Kilmerl 

Slickrock 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 1.0 dv causation 

and 0.5 dv contribution thresholds, respectively. 

TABLE 4-8. PEAK 24-HOUR AVERAGE VISIBILITY IMPACTS AT JOYCE KILMEWSLICKROCK 

DURING FUEL OIL FIRING IN BOILER 4302 

I Natural 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 Applicability Analysis 

5 3 Trinity Consultants 
The results presented in Table 4-7 and 4-8 indicate that refined analyses were necessary to evaluate 

visibility impacts at Joyce Kilmer/Slickrock since 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 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. 

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 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 1.0 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 

I Natural 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 contribution threshold at 

any Class I area, suggesting that 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 indicated peak 24-hour average impacts above the 0.5 dv contribution threshold 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 Consultants 

Because the screening analysis results described in Section 4 of this report exceeded the 0.5 dv 

contribution threshold for impacts at Sipsey, refined analyses were conducted using 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 including the 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 conditions using 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 Sispey WA 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 contribution thresholds 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-HOUR AVERAGE 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 sunlmarizes the computed impacts in 

comparison to the 0.5 dv contribution tlnesl~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 

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5 6 Trinity Consultants 

Using 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) he1 oil firing in Boiler 1302, which is a pemitted 

operating scenario but 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 operations because the facility does not 

typically burn fuel oil in Boiler 4302. Nonetheless, fuel oil combustion was evaluated to demonstrate 

visibility impacts in a manner consistent with U.S. EPA guidance. 

Refined modeling and postprocessing analyses to quantify the 98" percentile, 24-hour average 

visibility change using the revised IMPROVE light extinction algorithm demonstrate that impacts 

attributable to BP's Decatur Works are less than the 0.5 dv contribution threshold relative to annual 

average natural background conditions. These results indicate that 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. 

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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 SCREENING ANALYSES 

BP Decatur Works 

BART Applicability Analysis 

A - 2 Trinity Consultants 
REM 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