BART Determination Report: 

Georgia Power Company 

Plant Bowen 

Prepared by: 

Southern Company Services and RMB Consulting and Research 

for Georgia Power Company 

February 2007
i

Contents 

1.0 Executive Summary............................................................................................................1-1 

2.0 Introduction ........................................................................................................................2-1 

3.0 BART Exemption Modeling Results..................................................................................3-1 

4.0 BART Determination Analysis for PM..............................................................................4-1 

4.1 Overview of PM Species............................................................................................4-1 

4.2 Potentially Available PM Controls.............................................................................4-4 

4.3 Feasibility Analysis of Potential Controls................................................................4-11 

4.4 Control Effectiveness of Feasible Options ...............................................................4-13 

4.5 Impact Analysis for Feasible Options ......................................................................4-16 

4.6 Visibility Impacts Modeling for Feasible Options ...................................................4-32 

5.0 Proposed PM BART for the Plant Bowen EGUs...............................................................5-1 

Appendix A Buoyancy of Moist Plumes: Equivalent Dry Effluent Temperature ..................A-1 

Appendix B Exemption Modeling 

Delta-Deciview Values for the Top 20 Days - for Each Year/Each 

Class I Area and for the Top 25 Days - Over Three Years .................................B-1 

Appendix C Agglomerator Cost Estimate from Indigo Industries, Inc. ..................................C-1 

Appendix D BART Determination Modeling Protocol: Georgia Power Company 

 Plant Bowen.........................................................................................................D-1 

Appendix E Determination Modeling 

Delta-Deciview Values for the Top 20 Days - for Each Year/Each 

Class I Area and for the Top 25 Days - Over Three Years ................................. E-1 
ii

List of Tables 

Table 1-1 Summary of Bowen BART Determination Results .............................................1-2 

Table 3-1 Summary of Results - Plant Bowen Refined BART Exemption Modeling .........3-2 

Table 4-1 Technically Feasible Upgrade Options for Plant Bowen ...................................4-13 

Table 4-2 Total Capital Cost Estimates, Units 1 / 2 ...........................................................4-20 

Table 4-3 Total Capital Cost Estimates, Units 3 / 4 ...........................................................4-20 

Table 4-4 Annualized Upgrade Cost Summary (2006 Dollars), Units 1 / 2.......................4-21 

Table 4-5 Annualized Upgrade Cost Summary (2006 Dollars), Units 3 / 4.......................4-21 

Table 4-6 2003-2005 Historical Emissions, Unit 1 ............................................................4-22 

Table 4-7 2003-2005 Historical Emissions, Unit 2 ............................................................4-23 

Table 4-8 2003-2005 Historical Emissions, Unit 3 ............................................................4-23 

Table 4-9 2003-2005 Historical Emissions, Unit 4 ............................................................4-23 

Table 4-10 Baseline Emissions [tons per year], Units 1-4....................................................4-24 

Table 4-11 Estimated Post-Retrofit Emissions [tons per year], Unit 1.................................4-24 

Table 4-12 Estimated Post-Retrofit Emissions [tons per year], Unit 2.................................4-24 

Table 4-13 Estimated Post-Retrofit Emissions [tons per year], Unit 3.................................4-25 

Table 4-14 Estimated Post-Retrofit Emissions [tons per year], Unit 4.................................4-25 

Table 4-15 Average Cost Effectiveness of Upgrade Options, Unit 1...................................4-26 

Table 4-16 Average Cost Effectiveness of Upgrade Options, Unit 2...................................4-26 

Table 4-17 Average Cost Effectiveness of Upgrade Options, Unit 3...................................4-26 

Table 4-18 Average Cost Effectiveness of Upgrade Options, Unit 4...................................4-26 

Table 4-19 Incremental Cost Effectiveness, Unit 1 ..............................................................4-31 

Table 4-20 Incremental Cost Effectiveness, Unit 2 ..............................................................4-31 

Table 4-21 Incremental Cost Effectiveness, Unit 3 ..............................................................4-31 

Table 4-22 Incremental Cost Effectiveness, Unit 4 ..............................................................4-31 

Table 4-23 Summary of Results – Plant Bowen BART Determination 

Modeling for Cohutta .........................................................................................4-33 

Table 4-24 Summary of Results – Incremental Change from Baseline 

Plant Bowen BART Determination Modeling for Cohutta................................4-35 

Table 5-1 Summary of Bowen BART Determination Results .............................................5-2 
iii

List of Figures 

Figure 4-1 Least Cost Envelope, Unit 1...............................................................................4-29 

Figure 4-2 Least Cost Envelope, Unit 2...............................................................................4-29 

Figure 4-3 Least Cost Envelope, Unit 3...............................................................................4-30 

Figure 4-4 Least Cost Envelope, Unit 4...............................................................................4-30 
1-1 

1.0 Executive Summary 

Under the regional haze regulations, determinations of best available retrofit technology (BART) 

for sources that are BART-eligible and subject to BART must be submitted by the states to EPA no 

later than December 17, 2007. Coal-fired electric generating units 1, 2, 3, and 4 at Plant Bowen, 

owned and operated by Georgia Power Company (GPC), are BART-eligible units that are subject 

to BART. The Georgia Environmental Protection Division (GEPD) is responsible for determining 

BART for each of the electric generating units (EGUs) at Plant Bowen. With respect to sulfur 

dioxide (SO2) and nitrogen oxides (NOx), GEPD has indicated that it plans to adopt EPA’s regional 

haze rule that allows the cap-and-trade program of the Clean Air Interstate Rule (CAIR) to satisfy 

BART for SO2 and NOx at EGUs. Thus, no BART determination is required for SO2 and NOx

emissions from Plant Bowen’s EGUs. For particulate matter (PM) emissions from Plant Bowen’s 

EGUs, GEPD has requested that GPC provide a proposed BART determination. 

The PM emissions from Plant Bowen’s EGUs are currently controlled by electrostatic precipitators 

(ESPs). Wet flue gas desulfurization (WFGD) scrubbers for SO2 control, which also further reduce 

PM emissions, have been permitted for Plant Bowen’s EGUs and are under construction. 

Therefore, the PM BART determination analysis for Plant Bowen’s EGUs begins with the 

assumption that each EGU’s PM emissions are controlled with both an ESP and a scrubber. 

GPC, with the assistance of Southern Company Services (SCS) and RMB Consulting and 

Research, Inc. (RMB), has identified an additional six feasible PM control options for Units 1 and 

2, and five feasible PM control options for Units 3 and 4. The cost of each option, the option’s 

potential for further reducing PM emissions, the resulting dollar-per-ton removed costeffectiveness, and the energy and non-air environmental impacts of each option have also been 

analyzed. Using the least-cost-envelope curve approach recommended by EPA, GPC narrowed 

down the possible BART options for each of the units to the following four: (1) high voltage 

power conditioners (Juice Cans), (2) a particle agglomerator, (3) the combination of Juice Cans and 

an agglomerator, and (4) a wet electrostatic precipitator (WESP). To assess visibility 

improvement, two of those options (WESP and the Juice Can/agglomerator combination) have 

been modeled using CALPUFF. Table 1-1 contains a summary of the cost, expected PM emissions 

reduction, cost-effectiveness (average dollars-per-ton removed), and modeled visibility 

improvement (delta-delta-deciviews), for the control options at each of the Bowen EGUs. 

Based on this information, GPC proposes that PM BART for the Plant Bowen EGUs be no 

additional controls. Each unit at Plant Bowen is already extremely well controlled for PM 

emissions. With regard to the WESP control option, although the modeling predicts a small 

improvement in visibility at the Cohutta Class I area associated with use of that option, the costeffectiveness of that option is well above any threshold for cost-effectiveness that could be 

considered reasonable for BART. In addition, the WESP would consume additional energy and 

would create adverse non-air quality environmental impacts. 
1-2 

Table 1-1 Summary of Bowen BART Determination Results1 

Upgrade Option 

Annualized Cost 

[$/yr] 

PM10

Reduction 

[tpy] 

Average Cost 

[$/ton] 

Visibility 

Improvement 

from Baseline2

[delta-delta-dv] 

Bowen Unit 1 Results

Juice Can $76,860 11.3 $6,815 - 

Agglomerator $1,163,529 62.0 $18,759 - 

Agglomerator/Juice Cans $1,240,389 73.1 $16,921 -0.01 

Wet ESP $12,474,580 261.0 $47,804 -0.14 

Bowen Unit 2 Results

Juice Can $76,860 15.6 $4,923 - 

Agglomerator $1,163,529 85.9 $13,550 - 

Agglomerator/Juice Cans $1,240,389 101.5 $12,222 -0.01 

Wet ESP $12,474,580 336.2 $37,107 -0.14 

Bowen Unit 3 Results 

Juice Can $98,820 21.1 $4,677 - 

Agglomerator $1,495,965 51.6 $28,965 - 

Agglomerator/Juice Can $1,594,785 72.8 $21,914 -0.01 

Wet ESP $16,038,745 334.8 $47,909 -0.15 

Bowen Unit 4 Results

Juice Can $98,820 24.0 $4,110 - 

Agglomerator $1,495,965 58.8 $25,452 - 

Agglomerator/Juice Cans $1,594,785 82.8 $19,256 -0.01 

Wet ESP $16,038,745 360.5 $44,492 -0.16 

 Notes: 

1. Visibility improvement results represent new IMPROVE equation and virtual stack temperature. 

2. Incremental change is the “Highest of 8th Highest delta-delta-dv for the 3-years.” 

With regard to the agglomerator option and the Juice Can/agglomerator combination, the costeffectiveness values exceed levels that have been considered reasonable even in the context of New 

Source Review (NSR) “Best Available Control Technology” (BACT) assessments and the BARTlike determination conducted by Tampa Electric Company for evaluation of ESP-upgrade options 

at Big Bend Station. (The exception is for Unit 2, where the cost-effectiveness of these options 

falls within the upper range of values that could be considered reasonable for BACT.) Moreover, 

the CALPUFF modeling predicts virtually no visibility improvement would occur with use of those 

options. 

Finally, although the Juice Can option could be deemed by GEPD to have a relatively moderate 

dollar-per-ton removed cost-effectiveness, that option reduces only a few tons of PM and is not 

expected to improve visibility at all. 

For these reasons, GPC proposes that PM BART for Units 1-4 at Plant Bowen be no additional 

controls. 
2-1 

2.0 Introduction 

The regional haze regulations require a BART determination for each BART-eligible source that 

emits any air pollutant which may reasonably be anticipated to cause or contribute to any 

impairment of visibility in a mandatory Federal Class I area.1 The determination of BART for 

fossil-fuel fired power plants having a total generating capacity greater than 750 megawatts must 

be made pursuant to EPA’s “BART Guidelines” found in Appendix Y to 40 C.F.R. Part 51.2 

GPC owns and operates coal-fired EGUs 1, 2, 3, and 4 at Plant Bowen, near Cartersville, Georgia. 

To be BART-eligible, a source must fall within one of the 26 BART-eligible source categories 

identified in the Clean Air Act (for example, “fossil-fuel fired steam electric plants of more than 

250 million Btu per hour heat input”), the source must have been in existence on August 7, 1977 

and have begun operation after August 7, 1962, and the source must have potential emissions of a 

visibility-impairing pollutant of 250 tons per year or more. All four EGUs at Plant Bowen satisfy 

these criteria and thus are BART-eligible. The visibility-impairing pollutants emitted by Plant 

Bowen’s EGUs are SO2, NOx, and PM. GEPD has determined that volatile organic compounds 

(VOCs) and, except in limited cases not applicable here, ammonia will not be considered visibilityimpairing pollutants in Georgia. 

GEPD has announced its intention to participate in the CAIR cap-and-trade program and to use that 

program to satisfy BART for SO2 and NOx at BART-eligible EGUs, pursuant to 40 C.F.R. Section 

51.308(e)(4). Based on guidance from EPA, if a state opts to allow CAIR to satisfy SO2 and NOx

BART for an EGU, then a modeling analysis may be conducted to determine whether PM 

emissions from that EGU, by themselves, cause or contribute to visibility impairment in a Class I 

area (i.e., are subject to BART). As a result, GPC undertook CALPUFF modeling to assess 

whether the PM emissions from Plant Bowen’s EGUs are subject to BART. 

The Plant Bowen CALPUFF modeling was conducted pursuant to a modeling protocol submitted 

by GPC to GEPD in May 2006, see “BART Modeling Protocol: Plant Bowen” (May 2006), with 

revisions to the procedures based on later discussions with GEPD. 3 The results of that modeling 

indicate that the PM emissions from Plant Bowen’s EGUs are subject to BART. Specifically, 

using GEPD’s 0.5 delta-deciview threshold (8th highest impact each year; 22nd highest impact over 

three years) for assessing whether a source contributes to visibility impairment in a Class I area, the 

visibility impact from Plant Bowen’s PM emissions exceed that threshold in one Class I area, the 

Cohutta wilderness area in North Georgia. Table 3-1, as presented later in Section 3.0 of this 

BART Determination Report, shows the results of the CALPUFF exemption modeling performed 

for Plant Bowen. Therefore, pursuant to EPA’s BART Guidelines, a BART determination is 

required for PM emissions from each Plant Bowen EGU.4

 

1

 40 C.F.R. Section 51.308(e) 

2

 40 C.F.R. Section 51.308(e)(1)(ii)(B); BART Guidelines, Section I.F.1 

3

 The revised procedures are reflected in the “BART Determination Modeling Protocol” (December 2006) that was 

submitted to GEPD. See Section 4.6 of this report. 

4

 BART Guidelines, Section IV.B 
2-2 

BART is defined in the regional haze regulations as an emission limitation based on the degree of 

reduction achievable through the application of the best system of continuous emission reduction 

for a pollutant emitted by a BART-eligible source. A BART emission limitation must be 

established on a case-by-case basis taking into consideration the technology available, the costs of 

compliance, the energy and non-air quality environmental impacts of compliance, any pollution 

control equipment in use or in existence at the source, the remaining useful life of the source, and 

the degree of improvement in visibility which may reasonably be anticipated to result from the use 

of such technology.5

 

This document contains the analysis of these factors for determining BART for PM emitted from 

each of Plant Bowen’s EGUs. Section 3.0 summarizes the exemption modeling performed using 

the baseline conditions. Section 4.0 identifies and provides an analysis of the feasible PM control 

technology options, as well as a discussion of the considerations that must be examined for 

determining BART. Section 5.0 discusses GPC’s proposal that PM BART for Plant Bowen’s 

EGUs be no additional controls. 

 

5

 BART Guidelines, Section IV.A 
3-1 

3.0 BART Exemption Modeling Results 

One factor in evaluating whether a source is subject to BART and which control options should be 

evaluated as BART is consideration of any existing pollution control technology in use at the 

source. Currently, PM emissions from Plant Bowen’s EGUs are controlled with ESPs. However, 

SO2 scrubbers, which also remove additional PM emissions, have been permitted and are under 

construction for Plant Bowen’s EGUs. Because the scrubbers will be in operation well before the 

expected implementation date for any additional BART PM control option that may be required, 

GPC has used the PM emissions from the scrubbed EGUs as the baseline for the PM BART 

modeling. The baseline condition also includes the stack parameters associated with the new 

stacks that will be constructed for the new scrubbers. (“Good engineering practice” (GEP) stack 

height assumptions have been used for the modeling.) 

The procedures contained in the “BART Modeling Protocol: Plant Bowen,” submitted to EPD on 

May 1, 2006, were used to conduct the BART exemption modeling. Based on discussions with 

EPD, it was agreed that the exemption modeling would be done for the units as scrubbed (the May 

2006 Protocol as submitted discusses only unscrubbed emissions), and the results would be 

presented using both the new and old IMPROVE equations.6 

One issue that was not addressed in the modeling protocols was the stack temperature to use in the 

modeling. In the May 2006 and December 2006 Protocols (Tables 2-1 and 2-2, respectively), the 

stack temperature is reported as 327 K. This is the actual temperature. However, the virtual 

temperature of 349 K should have been reported and was, in fact, used in the modeling. The plume 

rise equations in the existing EPA-approved air quality models describe the behavior of dry 

plumes. Since a scrubber plume is saturated and thus has greater buoyancy than dry flue gas, the 

virtual temperature of the stack gas is appropriate for modeling of scrubbed plumes. Virtual 

temperature is the temperature that a dry plume would need to have to provide the same buoyancy 

as the wet gas. Research engineers at Southern Company’s Research and Environmental Affairs 

Department created a calculation tool which determines the virtual temperature of a moist plume 

based on fuel, operational, ambient and physical stack parameter inputs. This tool was used to 

calculate the virtual temperature at the stack exit of both of the new scrubber stacks. A description 

of the calculation tool is provided in Appendix A. Since the temperature does have a small effect 

on the results, the results using both the virtual and actual temperatures are presented below. 

However, the results representing the use of virtual temperature and the new IMPROVE equation 

are considered the primary basis for the BART exemption (Section 3.0) analysis. 

The exemption modeling results are provided in Table 3-1, and Appendix B lists delta-deciview 

results for the top 20 days for each year modeled and the top 25 days for the overall three years at 

each Class I area for the primary results (i.e., the virtual temperature, new IMPROVE equation 

case). The table indicates that both the 8th highest day’s impacts for each year and the 22nd highest 

day’s impacts over all three years are below 0.5 delta-dv for four of the five Class I areas within 

300 km. However, the impacts are greater than 0.5 delta-dv at Cohutta. These results demonstrate 

 

6

 Revisions to the modeling procedures (including estimates of PM emission reductions due to the scrubbers) are 

reflected in the “BART Determination Modeling Protocol” (December 2006), which is discussed in section 4.6 of this 

report. 
3-2 

Table 3-1 Summary of Results – Plant Bowen Refined BART Exemption Modeling 

2001 2002 2003 

Class I area 

Distance from 

source to 

Class I area 

boundary 

# of days and 

receptors beyond 

98th percentile 

with impact > 0.5 

delta-dv 

8th

Highest 

delta-dv 

# of days and 

receptors beyond 

98th percentile 

with impact > 0.5 

delta-dv 

8th

Highest 

delta-dv 

# of days and 

receptors beyond 

98th percentile 

with impact > 0.5 

delta-dv 

8th

Highest 

delta-dv 

Highest of 

8th Highest 

delta-dv 

for the 3-

years 

22nd

Highest 

delta-dv 

over 3-

year 

period 

km Days Rec delta-dv Days Rec delta-dv Days Rec delta-dv delta-dv delta-dv 

Cohutta 

New Improve 

Virtual Temp 84.8 6 5 0.74 12 6 0.94 6 4 0.59 0.94 0.74 

New Improve 

Actual Temp 84.8 10 6 0.78 15 7 1.05 13 5 0.73 1.05 0.82 

Old Improve 

Virtual Temp 84.8 13 8 0.91 20 6 1.15 16 7 0.73 1.15 0.91 

Old Improve 

Actual Temp 84.8 16 8 0.97 22 7 1.28 23 6 0.90 1.28 1.00 

Great Smoky Mountains 

New Improve 

Virtual Temp 175.9 0 0 0.28 0 0 0.23 0 0 0.23 0.28 0.24 

New Improve 

Actual Temp 175.9 0 0 0.27 0 0 0.28 0 0 0.26 0.28 0.27 

Old Improve 

Virtual Temp 175.9 0 0 0.35 0 0 0.29 0 0 0.28 0.35 0.30 

Old Improve 

Actual Temp 175.9 0 0 0.33 0 0 0.34 0 0 0.34 0.34 0.34 

Joyce Kilmer 

New Improve 

Virtual Temp 162.3 0 0 0.27 0 0 0.31 0 0 0.25 0.31 0.27 

New Improve 

Actual Temp 162.3 0 0 0.28 0 0 0.34 0 0 0.29 0.34 0.30 

Old Improve 

Virtual Temp 162.3 0 0 0.34 0 0 0.39 0 0 0.31 0.39 0.34 

Old Improve 

Actual Temp 162.3 0 0 0.35 0 0 0.43 0 0 0.37 0.43 0.38 

Shining Rock 

New Improve 

Virtual Temp 228.0 0 0 0.17 0 0 0.12 0 0 0.18 0.18 0.16 

New Improve 

Actual Temp 228.0 0 0 0.17 0 0 0.14 0 0 0.19 0.19 0.18 

Old Improve 

Virtual Temp 228.0 0 0 0.21 0 0 0.14 0 0 0.22 0.22 0.20 

Old Improve 

Actual Temp 228.0 0 0 0.20 0 0 0.16 0 0 0.24 0.24 0.22 

Sipsey 

New Improve 

Virtual Temp 223.5 0 0 0.08 0 0 0.12 0 0 0.11 0.12 0.11 

New Improve 

Actual Temp 223.5 0 0 0.08 0 0 0.12 0 0 0.12 0.12 0.11 

Old Improve 

Virtual Temp 223.5 0 0 0.10 0 0 0.15 0 0 0.14 0.15 0.14 

Old Improve 

Actual Temp 223.5 0 0 0.11 0 0 0.16 0 0 0.15 0.16 0.15 
3-3 

that Plant Bowen’s PM10 emissions contribute to visibility impairment at Cohutta and Plant 

Bowen’s EGUs are therefore subject to PM BART and a PM BART determination analysis for 

Cohutta is required. 

An external hard drive is being provided separately that contains all of the electronic data related to 

this application (i.e., the virtual temperature, new IMPROVE equation case). This drive contains 

all of the input and output files used in the modeling. A readme.txt file is also included on the hard 

drive that lists all of the files on the drive.
4-1 

4.0 BART Determination Analysis for PM

4.1 Overview of PM Species 

The size of particulate resulting from coal-fired combustion will vary depending on coal type, 

boiler design, and mill grind. At the boiler exit, particles may range up to 200 microns7 for a 

typical pulverized coal boiler.8 Particle size distribution of flue gas particulate may be altered by 

control device type and operation, as certain types of PM controls (such as ESPs) have different 

size-specific collection efficiencies. For an ESP-equipped boiler, PM sizes in the stack may range 

up to 100 microns, although 50-80% of the total mass is represented by particles less than 10 um.9

There are two distinct particle size ranges that are currently regulated by EPA. These are particles 

less than 10 microns in diameter (PM10) and particles less than 2.5 microns in diameter (PM2.5). 

EPA classifies PM between 10 and 2.5 microns as coarse PM and PM at or below 2.5 microns as 

fine PM. 

PM emissions from fossil fuel fired boilers are generally characterized as ‘filterable’ and 

‘condensable’ particulate. PM10 coarse is essentially all filterable and PM2.5 includes both filterable 

and condensable species. 

Filterable PM Species

Filterable particulate refers to particulate that is measured using standard filter-based measurement 

techniques.10 The particulate is captured from the flue gas on a filter and weighed for a direct mass 

measurement. Filterable PM is usually solid-phase material consisting of unburned carbon, ash, 

and other inorganic material.11 Filterable PM measurement techniques do not catch vapors or some 

particles less than 0.3 microns.12

Condensable PM Species

Condensable PM refers to particulate that forms either by condensation of vapor-phase species or 

by chemical reaction between gases. Primary condensable particulate forms either in the stack or 

shortly after discharge from the stack, as hot flue gases are cooled by ambient air. Secondary 

particulate is formed in the atmosphere through chemical reaction between ambient constituents. 

 

7

 A ‘micron’ is one millionth of a meter: 1 μm = 1x10-6 m 

8

 Applied Electrostatic Precipitation, Parker, K.R., 1997. 

9

 RMB analysis of SRI impactor data for a variety of coals and boiler types. 

10 EPA Reference Method (RM) 5 (out of stack sampling) and RM-17 (in stack sampling) 

11 While technically considered “condensable”, filterable measurements may occasionally include suspended droplets 

and aerosols, such as scrubber carryover and condensed sulfuric acid, which are large enough to be captured on the 

filter. 

12 AP-42 
4-2 

Virtually all condensable particulate is less than one micron, and therefore may constitute a 

significant fraction of PM2.5. 

Primary Condensable Species 

Primary condensable PM includes organic13 compounds, sometimes referred to as primary organic 

aerosols (POA), and inorganic compounds. For coal-fired applications, most primary condensable 

PM species is inorganic, representing roughly 80% of the total condensable PM10.

14 

The primary organic components include a broad range of compounds known as polycyclic organic 

matter (POM). The most commonly tested and reported subset of POM are polycyclic aromatic 

hydrocarbons (PAH), which are compounds containing only carbon and hydrogen. 

POM are products of incomplete combustion that are most often associated with complex fuels that 

have a high carbon to hydrogen content and staged combustion, such as coal.15 POM compounds 

exist in the solid phase under ambient conditions and may be emitted from the stack in either vapor 

form or solid form, depending on flue gas temperature. At typical flue gas temperatures (> 300°F), 

most POM is emitted in the vapor phase. However, for scrubbed stacks where temperatures are 

often below the melting point of most POM (~ 200°F), POM compounds readily condense onto 

existing particulate. In this case, only a small portion of POM is emitted from the stack in vaporphase. 

Primary inorganic compounds are typically condensed acids. For coal-fired applications, sulfuric 

acid (H2SO4) and the sulfuric acid precursor SO3 are most significant. During the combustion of 

fossil fuels, fuel-bound sulfur is oxidized to form SO2. A small fraction of SO2 (< 1%) is further 

oxidized to form SO3 in the convective regions of the furnace, depending on coal sulfur content 

and excess air level. Additional SO2 is oxidized in the economizer region of the boiler in a 

catalytic reaction that depends on SO2 concentration, ash and boiler tube compositions, excess air 

level, and gas/tube surface temperature and surface area. This additional oxidation may range up 

to 2%.16 Upstream of the air pre-heater, SO3 exists in the flue gas in the gaseous phase. However, 

as the gas passes through the air heater and cools, the hygroscopic SO3 combines with flue gas 

moisture to form vapor-phase sulfuric acid (H2SO4). 

Units equipped with SCR for NOx control, particularly those firing high-sulfur coals, have a higher 

susceptibility to acid gas formation, as SCR catalysts are known to cause additional oxidation of 

flue gas SO2. The SCR catalyst reduces NOx (predominately NO) to molecular nitrogen, which 

provides additional oxygen for further SO2 to SO3 conversion. Test data have shown that this 

additional conversion may be as high as 3% depending on the operating parameters, system design 

 

13 Carbon containing 

14 AP-42 

15 U.S. Environmental Protection Agency. Locating and Estimating Air Emissions from Sources of Polycyclic Organic 

Matter. EPA-454/R-98-014. Office of Air Quality Planning and Standards, Research Triangle Park, NC. 1998. 

16 Emissions of Sulfur Trioxide from Coal-Fired Power Plants, Srivastava, R.K., Miller, C.A., Erickson, C., Jambhekar, 

R. 
4-3 

and catalyst formulation. This increase can effectively double the existing SO3 flue gas 

concentration.17 

Measurement of primary condensable PM has become a more recent regulatory issue. The current 

version of the EPA reference method18 for measuring condensable PM is known to have a 

measurement bias for flue gas containing SO2, NOx, or soluble semi-volatile organic compounds. 

A portion of these gases dissolve in the impinger solutions and oxidize to form artifacts that 

artificially inflate measured particulate. EPA is presently considering modification of RM-202 to 

reduce artifact formation. 

Secondary Condensable Species

Secondary condensable PM also includes both organic (“secondary organic aerosols”, SOA) and 

inorganic components. SOA are formed when the oxidation products of certain volatile organic 

compounds19 (VOCs) condense on pre-existing aerosols (usually POA). The atmospheric behavior 

of SOA is currently not well understood and ambient SOA concentration is difficult to measure. 

The most notable secondary inorganic particulates associated with visibility impairment are 

ammonium sulfate, ammonium bisulfate, and ammonium nitrate, each formed in the atmosphere 

through photochemical reactions. Unlike SOA, the mechanisms of sulfate and nitrate formation 

and their contribution to atmospheric fine particles are well documented.20 

Applicable PM Species for BART

Only direct PM emissions, including filterable and primary condensable PM species, are 

considered in the BART evaluation. Secondary inorganic species are not considered PM emissions 

under the Clean Air Act, and thus are not considered for the purposes of the BART PM evaluation. 

These species are analyzed separately as part of BART evaluations for SO2 and NOx, which Plant 

Bowen is not required to undertake because SO2 and NOx BART are being satisfied through the 

State of Georgia’s implementation of the Clean Air Interstate Rule (CAIR). Secondary organic 

species (SOA), although considered PM in ambient air, is also not subject to this analysis since it is 

not considered to be direct PM emissions from a stack and is not included in the current VISTAS 

modeling protocol.21 

 

17 Current Work on the Impacts of SO3 Emissions from Selective Catalytic Reduction Systems, Erickson, C, Jambhekar, 

R. 

18 EPA RM-202, Determination of Condensable Particulate Emissions from Stationary Sources

19 Organic species include volatile, semi-volatile, and (primary) condensable organic compounds. VOCs refers to 

those volatile and semi-volatile components that are emitted to the atmosphere in a gaseous phase. 

20 EPA, ibid. 

21 CALPUFF provides SOA modeling capability. However, the model was adapted from SOA formation from 

biogenic organic emissions, and, therefore, is not suited for modeling combustion-related SOA formation. The 

VISTAS protocol acknowledges that the application for combustion-related SOA formation requires additional 

investigation. Note that the organic carbon model input parameter refers to POA, not SOA. 
4-4 

Filterable Species 

The initial selection of BART options for filterable PM emissions is independent of particle size. 

Separate evaluations are not required for PM10 and PM2.5. However, as part of the BART 

evaluation, the impact analysis requires a source to evaluate the visibility improvement of 

competing BART alternatives. Since fine particles have a greater effect on visibility, this suggests 

that any changes in the “baseline” particle size distribution should be considered when comparing 

BART alternatives. 

Condensable Species 

The BART evaluation for primary condensable PM species will be based on sulfuric acid 

emissions. Plant Bowen Units 1-4 are currently equipped with SCRs and Units 3 and 4 have flue 

gas conditioning. Also, all four units have permits for wet scrubbers and these scrubbers are 

currently under construction. Therefore, stack conditions may be favorable for relatively high 

concentrations of condensed sulfuric acid. 

POA (POM) will not be considered in the selection of BART alternatives. SCS is unaware of any 

post-combustion controls that are specifically designed for POA reduction for coal-fired 

applications. Furthermore, for those control scenarios where some theoretical reduction in POA 

may be possible (i.e. WESP, wet scrubber), SCS was unable to locate any additional information 

on removal efficiency. Given the relatively low concentrations of POA in the flue gas, if any such 

data were available, it would likely be meaningless because of measurement uncertainty. 

4.2 Potentially Available PM Controls 

The first step in the BART evaluation is to identify all available retrofit control technologies. 

“Available” refers to technologies “with a practical potential for application to the emissions unit 

and the regulated pollutant under evaluation.”22 This limits the potential retrofit options to only 

those technologies that are field-proven and commercially available. 

Based on the preceding discussion, this effort is limited to the control technologies for filterable 

PM and sulfuric acid gas emissions. Many of the control technologies available for filterable PM 

removal have little or no removal of sulfuric acid emissions and vice-versa. In fact, while some 

controls may improve collection of one species, they may increase emissions of the other (e.g. 

sorbent injection removes sulfuric acid gas but increases filterable PM).23 Therefore, in selecting 

the appropriate BART option, which could include one or more retrofit technologies, consideration 

will be given to the overall net PM removal and the net effects on visibility. 

The following section includes a general discussion of the various potentially available control 

options for filterable PM and sulfuric acid emissions. Some of these options may not be applicable 

to certain affected units. A case-by-case analysis is discussed in Section 4.3 as part of the BART 

evaluation to eliminate technically infeasible options for each unit. 

 

22 BART Guidelines, Section IV.D.1.1. 

23 The “appropriate” BART determination may include a combination of one or more PM control devices/upgrades 

(e.g. ESP upgrade and sorbent injection). Note that the appropriate BART determination could also be a single control 

technology that does not provide removal capability of both PM species. 
4-5 

Filterable PM Controls

For coal-fired applications, all conventional PM controls are designed to remove primary, filterable 

particulate. In determining the initial list of appropriate control technologies, SCS considered all 

field-proven, commercially available upgrade options listed in the EPRI ESP upgrade guidelines 

manual.24 These technologies have been applied at multiple coal-fired plants and the suppliers 

provide performance guarantees. Two additional technologies are included, because they have 

reached some degree of maturity in the period of time since the original guidelines documents were 

prepared: the Indigo Technologies’ particle agglomerator and the BHA “Juice Can” filter. 

Wet ESP 

Wet ESPs (“WESPs”) use the same basic operating principles as conventional, cold-side or hotside ESPs. However, instead of a plate rapping system, a flowing sheet of water covering each 

collecting plate is used to remove the collected ash. Collected material flows down the plate with 

the water film and is collected in a drain system. WESPs virtually eliminate reentrainment and 

back corona problems found in conventional precipitators. 

A WESP system can be installed either as a separate unit downstream of the existing ESP or, as a 

retrofit, in the outlet field of the existing ESP casing. WESPs can be constructed in either a tubular 

or plate (similar to conventional ESPs) configuration. Tubular WESPs are suitable for vertical 

flow applications only. This design is slightly more compact, but more complicated to build than a 

flat plate design. 

One of the critical design issues is the material used in the collection system. WESP internals must 

be made of a conductive material that will resist corrosion due to the acid mist that might be 

present in the gas. Common materials include conductive fiberglass, carbon steel, stainless steels, 

and various high-end alloys. For most multi-pollutant applications, an acid-gas scrubber is used to 

pre-treat the gas entering the WESP. 

WESP technology has received particular interest as a multi-pollutant emissions control device 

capable of reducing emissions of acid fumes, fine particulate, mercury, and other metals. WESPs 

have also been considered a performance enhancement option for installations with either high ash 

resistivity or excessive reentrainment. 

Although WESPs have been used successfully in some smaller-scale industrial applications and 

widely used in the sulfuric acid industry to control SO3 mist, historically, they have not been used 

in utility applications because of the high costs associated with the corrosion-resistant metals used 

in their manufacture. Disposal of wastewater is also an issue. 

Pulse Energization 

A conventional power supply for an ESP consists of a high voltage step up transformer to provide 

either a full wave or, in some older installations, half wave rectified electrical power input to the 

corona-generating electrode system. The complete system includes a control system with an 

appropriate operating control algorithm. The conventional power supply provides input to the ESP 

system with a sinusoidal shaped varying voltage to transfer energy to the ESP. Electrical energy 

 

24 Guidelines for Upgrading Electrostatic Precipitators: Volume 2, EPRI Report Number TR-113582. 
4-6 

flows to the collector when the applied voltage from the power supply exceeds the residual voltage 

on the ESP electrode system. This conventional power supply is appropriate for most ESP 

installations. 

Pulse energization is a technology that is useful for increasing the ESP collection efficiency for 

high resistivity fly ash particles. The advantage of pulse energization is that the voltage applied to 

the corona electrode is increased at such a fast rate that the process of individual tuft formation 

does not have time to develop before the entire corona electrode is brought into corona. It takes 

several microseconds of time for the individual tufts to form so the entire corona electrode is 

generating corona before the shielding of individual tufts can occur. This pulse corona process 

leads to the entire surface of the corona electrode supplying carrier ions and a much more nearly 

uniform current distribution over the surface of the dust layer. 

In order to implement pulsed energization, it is necessary to purchase and install the new power 

supplies. In some cases, portions of the existing power supplies can be reused, but in most cases, 

they are scrapped or installed on another unit. If the ESP is operating with heavy back corona, the 

emissions can be significantly reduced with the addition of pulsers. 

COHPAC 

COHPAC, an acronym for Compact Hybrid Particulate Collector, is a technology that includes a 

small pulse jet fabric filter downstream of the existing ESP. There are two methods of installing 

COHPAC. The first method (“COHPAC I”) places the fabric filter downstream of the ESP in a 

new casing. The second method (“COHPAC II”) requires the last mechanical field of the ESP to 

be replaced with the fabric filter.25 The pulse jet collector can be designed with a much higher gas 

to cloth ratio than a conventional collector because of two factors. First, the fly ash loading into 

the filter is much less than in a stand-alone filter because the ESP has removed more than 90% of 

the ash. Second, the ash suspended in the gas stream is electrically charged by the ESP and will 

form a much more porous dust cake than uncharged ash. PM removal efficiency (PM2.5 and total 

PM) for COHPAC is consistent with the typical efficiency of pulse jet fabric filter installations 

(~99% of existing emissions levels). 

Particle Agglomerator 

The collection efficiency of an ESP varies as a function of the particle size of the material to be 

collected. This is because of a combination of factors related to the electrical charging mechanisms 

and the ease with which particles of different sizes are able to move through the molecules in the 

gas stream. The collection efficiency for an ESP is high for large particles, decreases to a 

minimum for particles in the half micron diameter range, and then increases somewhat for the even 

smaller particles. The minimum collecting efficiency just coincides with the wavelength of light 

that causes the greatest opacity of particles in the atmosphere. 

The particle agglomerator is a technology that causes the smaller particles to contact and adhere to 

the larger particles so that they will be removed with the large particles that are collected more 

 

25 COHPAC II is not commercially available, and, therefore, does not meet the selection criteria as a viable retrofit 

technology. 
4-7 

efficiently than they would have been if remaining as individual particles. The principles used for 

particle coagulation are a combination of electrical and turbulent gas flow mechanisms that bring 

the oppositely charged particles into close proximity and allow them to adhere together. 

The system consists of a number of individual corona discharge systems operating in parallel, with 

one channel operated with negative corona and the next with positive corona. This provides a gas 

stream with approximately half of the particles charged positively, with the remainder negative. 

When these gas streams are mixed, the oppositely charged particles are attracted together, then, 

upon contact, they adhere to each other and behave as one larger particle. 

This device is installed in the ductwork leading to the ESP inlet plenum, where the gas velocity is 

relatively high – on the order of 20 to 40 feet per second. This region is designed to be highly 

turbulent to cause these gas streams to mix and bring the oppositely charged particles together. 

The gas stream is next brought into a conventional ESP for particle collection. 

The specific agglomerator considered in this study is the Indigo Technologies system. There have 

been other types of agglomerators evaluated in the past; acoustic, electrical and sonic. The Indigo 

unit, using a combination of oppositely charged particles together with a highly turbulent mixing 

region, has provided the best performance in operating systems. 

Vendor guarantees suggest a 50% reduction in particles less than five microns. The resulting 

improvement in ESP collection efficiency will depend on the existing particle size distribution 

upstream of the agglomerator. 

Gas Flow Optimization 

The gas velocity distribution in an ESP influences the overall removal efficiency in two ways. 

First, the ESP is an exponential type of collector; from collection considerations alone, the more 

nearly uniform the gas velocity distribution, the higher the primary collection efficiency. The 

removal process for a dry collector, however, consists of the primary removal coupled with the 

removal of the collected dust layer and deposition of this material into the ash hopper collection 

system. The optimization process depends on optimizing the combination of collection and 

removal to the hopper. 

When the ash deposit is removed from the collecting electrodes, the ash falls into the hopper by 

gravity. As the material falls, the layer will break up to some degree, with some of the material 

carried away by the gas stream while the remainder falls into the hopper. When this material falls 

into the hopper, the ash tends to break up and re-entrain into the gas stream. This reentrainment is 

referred to as hopper “boil up.” 

The amount of previously collected ash that is reentrained into the gas stream is a function of the 

gas velocity where reentrainment occurs. The material collected on the top of the collecting 

electrode falls a greater distance in traveling to the hoppers than that collected on the bottom. 

Hopper boil up occurs in the region just above the collecting electrode. Therefore, there is a trend 

for more reentrainment to occur near the lower portion of the ESP than from the top. These 

considerations favor a gas velocity distribution with higher velocities in the top, minimizing the 

amount of material that must fall through the gas stream with lower gas velocities near the bottom, 

where higher collecting and lower reentrainment should occur. These considerations suggest that 
4-8 

the gas velocity distribution for optimized collection will not necessarily be one that is uniform, but 

one that is somewhat skewed towards higher velocities in the top of the ESP. 

To optimize the gas flow in an ESP, the existing gas flow distribution must be measured and 

analyzed. The analysis is usually accomplished with a smaller scale model of the ESP system. 

When the desired gas velocity distribution is produced in the model study, the gas flow distribution 

baffles, turning vanes, etc. are designed and installed in the full scale unit. Of course, the resultant 

gas velocity distribution must be verified in the full scale ESP installation. The estimated 

improvement in ESP performance will depend on the quality of the existing flow distribution and 

the existing amount of hopper reentrainment. 

Juice Can 

Modern ESP power supply controls are programmed to maintain the electrical energization as high 

as possible to the point where some characteristic of the ESP- particle combination limits the 

applied voltage or current. The two primary limitations on the ESP operating level are the 

mechanical spacing of the ESP components and the electrical characteristics of the ash being 

collected. The applied voltage can increase until one of the following occurs: (1) spark-over 

between the electrodes, (2) the current or voltage limit is reached on the power supplies, or (3) 

electrical breakdown occurs in the collected dust layer. 

In conventional industrial negative corona ESPs, spark-over is initiated at the positive or collecting 

electrode. If the applied voltage is raised, corona begins to flow at an applied voltage of about 20 

kilovolts and increases somewhat exponentially until spark-over occurs or either the voltage or 

current reaches the power supply limits. If the collecting electrodes are clean, spark-over will 

occur when the local value of the electric field adjacent to some location on the collecting electrode 

system reaches a value on the order of 10 kilovolts per centimeter, where sparking is initiated. 

Sparking that is initiated by geometrical constraints is limited by the instantaneous value of the 

applied voltage. The formation of the flare on the electrically positive surface occurs in a few 

microseconds. Therefore, any modification to the ESP system that can maintain the peak value of 

the applied voltage just below sparking voltage while increasing the average value of the voltage 

will increase the collecting efficiency of the ESP. This condition applies whenever the ESP is 

collecting low resistivity particles. This is the condition where the “Juice Can” is an appropriate 

technology.26

The “Juice Can” consists of a capacitor connected in parallel with the distributed capacitance of the 

ESP electrode system. The normal ESP electrode system has an equivalent electrical circuit of a 

parallel resistor-capacitor combination with a time constant on the order of 15 milliseconds. Since 

capacitances in parallel add, the addition of the Juice Can increases the electrode system 

capacitance, while the equivalent resistance remains nearly constant. This causes the electrical 

time constant of the electrode system to increase. If the Juice Can capacitance is equal to that of 

the ESP electrode system, the time constant is approximately doubled. Since the charging current 

flows from the power supply every 8.33 milliseconds, while the time constant of the ESP-Juice 

Can combination is doubled to 30 milliseconds, the ESP voltage will decay less, perhaps leading to 

 

26 The Juice Can may actually be detrimental to the performance of an ESP collecting high resistivity fly ash (unless 

the ash is conditioned). 
4-9 

a peak to average voltage ratio of only 1.15. This would raise the average operating voltage to 

87% of the peak value. This simple change will increase the migration velocity for individual 

particles by perhaps 15%. It increases the average operating current density as well. The estimated 

performance improvement of Juice Can technology is unit-specific and depends on existing ash 

resistivity and field power levels. 

Add Extra Collecting Field 

Adding an extra field merely increases the size of the ESP and, thus, increases the overall 

collecting efficiency. This option can be considered for any ESP provided adequate space exists. 

The estimated performance improvement varies depending on the performance of the existing ESP, 

the size of the additional field, and gas velocity through the ESP. 

 

Moisture Injection 

It is well known that cooling a gas stream in a cold side ESP results in a reduction of gas volume 

and the electrical resistivity of the ash, which improves the overall performance of the ESP. While 

moisture conditioning is based on sound theory, the drawback is the difficulty with which the water 

must be injected into the flue gas without forming heavy deposits in the ductwork. Field 

experience with moisture conditioning systems has shown that the problems with the routine 

operation of these systems far outweigh the advantages. 

Moisture conditioning was not seriously considered for use as a retrofit. It is only included in the 

discussion of potential retrofit technologies because it is usually mentioned as a low cost option. 

Sulfuric Acid Gas Controls

Several methods are used to control emissions of condensed sulfuric acid and SO3, a sulfuric acid 

precursor. These methods are described briefly as follows: 

Sorbent Injection 

Acid gas formation can be controlled by the use of sorbent materials that are either injected directly 

into the boiler during the combustion process or into the flue gas stream upstream of the air heater. 

These sorbent materials are alkaline (basic) in nature and combine with the acid gas as particulate 

that is removed by the ESP or baghouse. 

For furnace-injection technologies, alkaline sorbents are injected directly into the boiler. Known 

sorbent materials for this methodology include limestone and calcium or magnesium-based 

slurries. For units with SCR, furnace injection technologies offer the potential benefit of allowing 

lower load operation and reduced SCR inlet temperatures. However, preliminary data suggest that 

furnace-injected sorbents do not provide significant control of SCR generated SO3. 

For post-furnace sorbent injection, alkaline sorbents can be injected upstream or downstream of the 

SCR, if so equipped, or upstream or downstream of the air heater. Pre-air heater injection offers 

the potential benefit of reducing the SO3 generated by the SCR and lowering the acid dewpoint 

temperature, which allows for lower air heater outlet temperatures and the potential of increased 

plant efficiency. Known sorbents used for pre-air heater injection include ammonia, hydrated lime, 

limestone, magnesium oxide powder, and various sodium compounds. 
4-10 

Relatively high removal efficiencies (+80%) of SO3 have been reported using sorbent-based 

control techniques. However, the injection of sorbent material can cause a reduction in ESP 

performance and in some cases may be the limiting factor in SO3 reduction. This has been 

confirmed, to some extent, by existing field studies by EPRI, DOE, and others. The potential 

effects on ESP inlet flue gas characteristics include increased mass loading at the ESP inlet, a 

reduction in particle size distribution, increased particulate resistivity, and changes in particulate 

adhesion and cohesion properties. The combined effect of these issues suggests decreased ESP 

performance and an increase in outlet emissions. In addition, the collection of sorbent-containing 

ash may adversely affect the quality of salable flyash. 

Flue Gas Humidification 

Another method of sulfuric acid emissions control is to cool the flue gas below the acid dew point 

temperature by injecting water into the ductwork upstream of a cold-side ESP. The theory is to 

intentionally condense the sulfuric acid from the flue gas. 

Again, moisture conditioning was not seriously considered for use as a retrofit option. It is only 

included in the discussion of potential retrofit technologies because it is usually mentioned as a low 

cost option. While testing conducted by DOE has shown some incremental improvement in 

sulfuric acid removal, there is insufficient data to assess the long-term feasibility of this option. 

Previous studies using humidification for improving ESP performance have shown sludge buildup 

in flue gas ductwork to be a significant problem. For sulfuric acid control, corrosion of internal 

ESP components is another significant concern. 

SCR Catalyst Replacement 

Units equipped with SCR for NOx control, particularly those firing high-sulfur coals, have a higher 

susceptibility to acid gas formation, as SCR catalysts are known to cause additional oxidation of 

flue gas SO2. The SCR catalyst reduces NOx (predominately NO) to molecular nitrogen, which 

provides additional oxygen for further SO2 to SO3 conversion. Test data have shown that this 

additional conversion may be as high as 3% depending on the operating parameters, system design 

and catalyst formulation. This increase can effectively double the existing SO3 flue gas 

concentration.27

SO3 formation can also be controlled by reducing the additional SO2 conversion that takes place 

across the SCR. Catalysts are currently available from manufacturers that produce lower levels of 

SCR-formed SO3, in some cases, less than 0.5%. 

Wet ESP 

WESPs are widely used in the sulfuric acid industry to control SO3 mist. WESPs capture sulfuric 

acid by passing the flue gas through an electrostatic precipitator after it has been cooled to 

saturation. By combining the electrostatic forces with low temperature and water saturation, 

sulfuric acid can be captured at relatively high efficiencies (80+%). 

 

27 Current Work on the Impacts of SO3 Emissions from Selective Catalytic Reduction Systems, Erickson, C, Jambhekar, 

R. 
4-11 

4.3 Feasibility Analysis of Potential Controls 

GPC may eliminate potential upgrade options from the BART determination analysis if such 

options are considered technically infeasible.28 Technical feasibility depends on whether each 

technology is commercially available and whether the technology can be applied to the affected 

source. Site-specific issues, such as space limitations and flue gas properties, may preclude the 

application of certain commercially available technologies. Upgrade options that are eliminated 

due to technical feasibility are exempt from subsequent analysis in the BART determination. The 

following is a summary of the feasibility of the various potential upgrade options included in the 

previous section. 

Wet ESP

WESP is considered a technically feasible option for all four Bowen units. Each boiler could be 

retrofitted with a WESP to reduce filterable particulate matter as well as condensable particulate 

matter. Depending on the available space, the WESP would need to be integrated within the 

WFGD scrubber vessel or downstream of the WFGD as a grade-mounted installation. Additional 

analysis would be required to determine the available space, although a preliminary investigation 

suggests that an integrated design may be applicable to Units 3 and 4 due to the confined layout. 

Pulse Energization

Pulse energization is a technology that is useful for increasing the ESP collection efficiency for 

high resistivity fly ash particles. However, this is not an issue on any of the Bowen units because 

each unit is equipped with a flue gas conditioning system which controls fly ash resistivity. As a 

result, pulse energization is not considered a technically feasible option for any of the Bowen units. 

COHPAC

COHPAC is available in two configurations: COHPAC I and COHPAC II. COHPAC I requires 

the installation of a fabric filter in a separate casing downstream of the existing ESP. COHPAC II 

is a retrofit of the outlet field of an existing ESP with a fabric filter. Of the two configurations, 

only COHPAC I is commercially available and therefore COHPAC II is not considered as part of 

this analysis. 

COHPAC I retrofit would be very difficult if not impossible due to the limited space existing 

between the ESPs and ID fans, especially on Units 3 and 4. Therefore, this option is considered 

technically infeasible. 

Particle Agglomerator

The particle agglomerator is a technically feasible option for all four of the Bowen units. The 

addition of an agglomerator should improve the performance of the existing ESPs. Units 3 and 4 

should benefit the most from this technology due to the relatively smaller size of the ESPs. Some 

 

28 BART Guidelines, Section IV.D.2. 
4-12 

caution should be taken with this option due to the lack of experience in installing agglomerators 

on boilers of this size. 

Gas Flow Optimization

Gas flow optimization is considered a technical feasible option on all of the Bowen units. 

However, since GPC has already conducted gas flow improvements, it is uncertain how much 

additional improvement can be made on these units. The excellent performance of the existing 

ESPs brings to question the overall benefit possible with this option. 

Juice Can

Juice Can technology is considered a technically feasible option on all of the Bowen units. Juice 

Cans have already been installed on some transformer/rectifier sets on Units 3 and 4 and have 

shown to improve the performance of the ESPs. Installation on Units 1 and 2 may show similar 

levels of performance improvement. However, further improvement on Units 3 and 4 is uncertain 

due to the existing performance of these units. 

Add Extra Collecting Field

Adding collection surface to any ESP will improve performance. This option was evaluated for 

Plant Bowen for Units 3 and 4 but was determined to be technically infeasible due to inadequate 

space. Space is available for Units 1 and 2, and, therefore, addition of an extra collecting field is 

considered technically feasible for these two units. 

Moisture Injection (for PM and/or SO3 control)

Field experience with moisture conditioning/flue gas humidification has shown this to be an 

infeasible technology due to the associated maintenance problems. Moisture injection has 

repeatedly been shown to cause heavy deposits of sludge in the ductwork. On the Bowen units, 

moisture injection would also cause additional sulfuric acid condensation, which would create 

corrosion problems in the ESP ductwork and casing. 

Sorbent Injection

Sorbent injection for SO3 control is considered a technically feasible option for all of the Bowen 

units. However, while sorbent injection can provide a significant reduction in flue gas SO3

concentration, it produces collateral PM emissions due to the added particulate. In addition, since 

sorbent is typically injected upstream of the ESP, it can create a reduction in ESP performance due 

to the increased loading and adverse changes in flue gas properties. Because of these issues, SCS 

has assumed the sorbent would be injected downstream of the ESP between the ESP and the 

WFGD. SCS has also assumed that lime would be used as the sorbent material. 

SCR Catalyst Replacement

Catalyst replacement may be considered a feasible option for units with a high SO3 conversion 

across the SCR. However, the SO3 conversion across the SCRs on the Bowen units is already 

relatively low (~1%). Switching to an ultra-low conversion catalyst (~0.5%) is not considered 
4-13 

technically feasible at this time because such catalysts are not well demonstrated in the field. 

Furthermore, since SO3 conversion is related to mercury oxidation, SCS is evaluating the potential 

co-benefit of the additional mercury oxidation across the SCR (and subsequent removal in the 

WFGD) as part of the long-term compliance strategy for CAMR. 

Summary of Feasible Upgrade Options

Table 4-1 summarizes the feasible upgrade options for all four units. All other options are 

considered technically infeasible and have been excluded from the remainder of the BART 

determination analysis. 

Table 4-1 Technically Feasible Upgrade Options for Plant Bowen 

Upgrade Option Applicable Unit 

WESP Units 1-4 

Particle Agglomerator Units 1-4 

Gas Flow Optimization Units 1-4 

Juice Can Units 1-4 

New Collection Field Units 1 and 2 

Sorbent (Lime) Injection Units 1-4 

Combinations of Feasible Upgrade Options

The EPA BART Guidelines suggest that combinations of upgrade options should be considered as 

part of the feasibility analysis. EPA allows affected sources to determine the extent to which 

upgrade combinations are included but does not expect every possible control combination to be 

investigated. The selection of control combinations should be based on a reasonable consideration 

of estimated emissions reductions, the cost of the various alternatives, and other plant impacts. 

For Plant Bowen, any combination of the feasible upgrade options listed in Table 4-1 is technically 

possible since the effects on particulate removal are independent of each other. As EPA suggests, 

analysis of all possible control combinations is unreasonable. As part of the cost impact analysis, 

GPC will evaluate one or more combinations of the lower cost control technologies and/or control 

technologies that provide lower levels of emissions reduction. 

4.4 Control Effectiveness of Feasible Options 

The evaluation of the various upgrade options requires a comparison of total PM10 (filterable and 

condensable) reduction of each option. The estimated total PM10 reduction is determined by using 

an assumption of the incremental speciated removal efficiencies of filterable PM10, filterable PM2.5, 

and sulfuric acid for each upgrade option. For WESP and lime injection, speciated removal 

efficiencies reflect typical removal efficiencies that have been demonstrated in practice. For ESP 

upgrade options, speciated removal efficiencies are based on ESP computer model results. Once 

the incremental removal efficiencies were determined, they were then applied to the baseline 

emissions data to determine the overall emissions reduction, expressed in terms of ‘tons per year’, 

for each upgrade option. 
4-14 

The following section summarizes the assumptions used to determine the control effectiveness and 

the expected emissions reduction of each feasible option: 

Wet ESP

WESPs are capable of removing both filterable and condensable PM (sulfuric acid) species, 

although they are primarily considered for sulfuric acid removal on units equipped with SCR and 

WFGD. Like conventional ESPs, WESP removal efficiency depends on a number of factors 

including size, gas velocity, and various flue gas properties. WESPs may be designed to achieve a 

specific emissions limit and/or they may be used to achieve the same emissions level as pre-SCR 

conditions. Since this analysis does not require a target emissions rate for sulfuric acid or filterable 

PM emissions, SCS has assumed that the WESP would be used to limit sulfuric acid emissions to 

pre-SCR level. The estimated collection efficiency for this target emission rate is 80% removal of 

sulfuric acid at the WESP inlet. This removal rate also represents the maximum, sustained removal 

efficiency, accounting for normal unit downtime, that can be expected using WESP technology. 

SCS has assumed the corresponding filterable PM10 and filterable PM2.5 collection efficiency to be 

90%. 

Lime Injection

Lime injection has shown to be an effective method of reducing flue gas SO3. However, the 

injection of lime causes an increase in filterable particulate emissions because the added particulate 

is not completely removed in the downstream PM control device. Since the assumed injection 

point is upstream of the WFGD, the WFGD represents the downstream PM control device. 

Emissions of total PM10 (filterable and condensables) may increase or decrease depending on the 

speciation of the flue gas prior to the lime addition, injection rate, and the filterable PM removal 

efficiency of the downstream control device. As with WESP design, lime injection rate can be 

adjusted to achieve a specific target SO3 emission limit or to maintain SO3 emissions to pre-SCR 

levels. 

SCS calculated lime injection rates for each unit based on achieving pre-SCR levels of SO3. These 

injection rates translate to an estimated combined sulfuric acid collection efficiency of both the 

WFGD scrubber and lime injection of 75%.29 SCS assumed that the added particulate was 

collected in the WFGD with a collection efficiency of 90% for both filterable PM10 and filterable 

PM2.5. This removal efficiency is slightly higher than the removal efficiency of 80% used in the 

baseline scrubber emissions estimates due to the larger particle size distribution of the lime and the 

higher collection efficiency of the larger particulate in the scrubber. 

ESP Upgrade Options

ESP upgrade options include those options that result in an improvement in ESP performance - 

Juice Can, new collection field, gas flow optimization, particle agglomerator. Since ESPs remove 

filterable PM species, estimated performance effects are considered only for filterable PM for these 

options. Generalized emissions reduction factors are not appropriate for analysis of these options 

 

29 Based on testing conducted at Plant Yates in 2006. 
4-15 

because the effects of the various upgrade options on ESP removal efficiency are unit-specific and 

depend on a number of factors, including ESP size and configuration, inlet loading, particle size 

distribution, gas flow rate, and other flue gas properties. 

In order to improve the accuracy of the estimated emissions reduction, SCS conducted computer 

modeling30 of each upgrade option for each ESP design. ESP computer models calculate 

performance from first principles and, therefore, have the capability to account for variations in 

flue gas properties. The output of the computer model was used to determine an estimated percent 

emissions reduction for each option. Given the similarity in ESP design and flue gas 

characteristics between Units 1 and 2 (identical units) and Units 3 and 4 (identical units), modeling 

was conducted on a representative model for each set of units and the results were applied to the 

baseline emissions data for each unit. Certain upgrade options may affect particle-size specific 

collection efficiency more than others. Therefore, results were generated for both filterable PM10

and filterable PM2.5 species. 

Particle Agglomerator 

The particle agglomerator improves overall filterable PM removal by exploiting the site-specific 

collection efficiency of the ESP. It is well known that fine PM collection efficiency in an ESP is 

lower than the overall PM collection efficiency. The particle agglomerator combines some of the 

fine particulate into larger particulate, which is more readily collected in the ESP. This increases 

overall collection efficiency and reduces fine particle concentration at the ESP exit. 

Vendor guarantees suggest a 50% reduction in PM5 at the ESP inlets due to the particle 

agglomeration. This roughly translates to a 20% increase in the particle size distribution mass 

mean diameter at the ESP inlet on each unit. SCS adjusted the inlet particle size distributions 

accordingly in each baseline model. For Units 1 and 2, the modeling results suggest a 33% 

reduction in filterable PM10 and a 34% reduction in filterable PM2.5. For Units 3 and 4, the results 

suggest a 22% reduction in filterable PM10 and a 34% reduction in filterable PM2.5. 

Gas Flow Optimization 

One of the primary benefits of gas flow optimization is a reduction in rapping and steady 

reeentrainment losses from ESP hoppers. The degree of improvement is directly related to the 

existing flow profile within each ESP. Since SCS has already conducted previous flow studies on 

the Bowen units, it is not expected that this option will provide a significant performance 

improvement. As a conservative estimate, SCS assumed that gas flow optimization would produce 

a 15% reduction in reentrainment losses from the ESP. 

For Units 1 and 2, the modeling results suggest a 3% reduction in filterable PM10 and a 1% 

reduction in filterable PM2.5 at the ESP outlet. For Units 3 and 4, the results suggest a 6% 

reduction in filterable PM10 and a 2% reduction in filterable PM2.5. 

 

30 All modeling was conducted using EPRI’s ESPM Version 3 software using baseline models that were calibrated 

using measured emissions test data. 
4-16 

Juice Can 

The addition of Juice Can technology to the existing transformer-rectifier sets will increase the 

average operating voltages and currents within the ESP. EPRI research suggests an increase in the 

average voltage to ~90% of the peak operating voltage and an increase in the operating current 

density of approximately 10%.31 SCS adjusted the operating voltages of each calibrated model 

accordingly. For Units 1 and 2, operating currents were increased by 10%. For Units 3 and 4, 

operating currents were only increased by 5%, as a more conservative assumption, given the 

relatively high existing current levels.32

For Units 1 and 2, modeling results suggest a 6% reduction in both filterable PM10 and PM2.5. For 

Units 3 and 4, the results suggest a 9% reduction in both filterable PM10 and PM2.5. 

New Collection Field 

Units 1 and 2 are each equipped with two ESPs arranged in a parallel configuration. Box ‘A’ is 

equipped with four fields in the direction of gas flow and Box ‘B’ is equipped with six fields in the 

direction of gas flow. For the purpose of this analysis, SCS has assumed that the additional field 

would be added in a separate casing to the outlet of Box ‘A’ because it would provide a greater 

performance improvement over the addition to the outlet of Box ‘B’. SCS has also assumed that 

the mechanical and electrical characteristics of the new field would be identical to those in the 

immediate upstream field in Box ‘A’. 

For Units 1 and 2, modeling results suggest a 35% reduction in filterable PM10 and a 32% 

reduction in filterable PM2.5. Modeling was not conducted for Units 3 and 4 because the addition 

of a new field was considered technically infeasible on these units. 

4.5 Impacts Analysis for Feasible Options 

A BART determination requires consideration of certain statutory factors for each feasible control 

option. Among these are the costs of compliance and the energy and non-air quality environmental 

impacts of compliance. The following discussion analyzes these factors for the previouslyidentified feasible options. 

4.5.1 Energy Impacts 

Energy impacts may occur due to increased station service requirements and/or forced or extended 

unit outages that may be required to install a particular upgrade technology. Energy impacts are 

considered to be negligible for all feasible upgrade options, except the WESP, provided the 

upgrades can be conducted during a scheduled outage. Upgrades such as installation of the Juice 

Cans and gas flow optimization may be conducted during a one to two week outage. Installation of 

the particle agglomerator, lime injection, and the addition of a new ESP field may require four to 

six weeks, which could be coordinated with the plant’s major outage schedule. 

 

31 Nichols, G. (1999), Guidelines for Upgrading Electrostatic Precipitator Performance: Volume 2: Electrostatic 

Precipitator Upgrade Guidelines, Electric Power Research Institute.

32 Some of the existing T/R sets are already equipped with Juice Can technology. 
4-17 

WESP Energy Impacts 

WESP systems require additional station service to power the electrical fields and the various 

pumps associated with the water recycle and water treatment systems. Station service requirements 

are estimated at 0.5% of the gross turbine generating capacity (MW).33 

WESP installations may require an extended unit outage depending on the WESP configuration. 

Grade-mounted installations minimize unit downtime. Virtually all construction can be conducted 

with the unit online and the WESP may be tied-into the flue gas ductwork during a scheduled 

outage. The WESP tie-in could take four to six weeks, depending on complexity of the additional 

ductwork. Retrofit installations where the WESP is integrated into the WFGD vessel are more 

complicated than grade-mounted installations because additional custom field work (less 

modularization) is required. In addition, the integrated design may require reinforcement of the 

scrubber foundation as the WFGD may not support the additional weight of the WESP. Integrated 

retrofits require the unit to be offline for the duration of the installation, which can result in 

extended unit outages. A more detailed evaluation would be necessary to determine the potential 

unit downtime, but it is likely that such an installation would extend beyond the four weeks of a 

typical major outage at Bowen.34 A preliminary analysis suggests that an integrated design may be 

needed on the Bowen units due to the available space. 

4.5.2 Non-Air Quality Environmental Impacts 

Non-air quality related environmental impacts are considered to be negligible for all upgrade 

options except the WESP. WESP operation is a water intensive process that requires an adequate 

supply of make-up water and disposal and/or treatment of ash-laden byproducts. 

WESP water systems are site-specific and may vary considerably in complexity. The basic 

configuration may be either a once-through or closed-loop design. In a once-through design, fresh 

makeup water supplies 100% of the water used in the WESP. Make-up water may come from a 

nearby lake or stream or from other plant processes such as the condenser cooling water. While 

once-through systems typically provide better performance and cleaning than closed-loop systems, 

water requirements are much higher. Water consumption on a once-though system is estimated at 

10 gpm/MW for adequate plate washing.35

Make-up water requirements can be minimized by using a closed-loop design, which recycles most 

of the water in the WESP. This may be suited for plants with a limited supply of fresh makeup 

water. Some makeup water is still required in order to replace water lost through evaporation, 

leakage, and blow-down of recycled effluent. Make-up water requirements in closed-loop systems 

depend largely on flue gas ash concentration and recycle water chemistry. Water consumption in a 

 

33 L. Monroe (SCS). Estimate is supported by DOE estimates of 0.5% (Economic Comparison of SO3 Control Options 

for Coal-Fired Power Plants, presented at Air Quality IV Conference, Arlington, VA September 23, 2003). 

34 Major scheduled outages occur 18-24 months and are typically 30 days in duration. 

35 Harrison, W, et al. (1999), Field Pilot Test Results for a Utility Wet Electrostatic Precipitator: Water Treatment and 

Performance, Electric Power Research Institute. 
4-18 

closed-loop system may range from 1 to 2 gpm/MW for a typical bituminous coal application with 

WFGD.36

 

WESP ash disposal may represent a more significant environmental concern for many plants. 

WESP effluent may either be sluiced to the plant’s existing ash pond or filtered and shipped for 

landfill disposal. Unlike dry ESP flyash, where the ash can be sold for various commercial 

applications, the market for recycled WESP ash is likely to be limited because of the various 

substances in the ash. 

4.5.3 Cost Impacts 

SCS determined the cost effectiveness of each competing upgrade alternative. The cost 

components used in this analysis are consistent with those found in the EPA Air Pollution Control 

Cost Manual. For the purpose of this analysis, SCS has assumed a baseline generation rate of 700 

MW for Units 1 and 2 and 900 MW for Units 3 and 4. Baseline emissions and unit capacity factors 

are based on historical data for the period 2003-2005. Baseline emissions data have been adjusted 

to account for future WFGD operation. 

Total Capital Costs

The following section discusses the total capital costs associated with each of the upgrade options, 

including direct and indirect capital costs. Direct capital costs consist of basic equipment and 

installation costs, ductwork modifications (if applicable), various infrastructure costs incurred to 

accommodate the new equipment, design and engineering costs, and typical vendor contingencies. 

Indirect capital costs include the loss of investment interest incurred during the construction period. 

Direct Capital Costs 

The direct capital cost information provided represents the latest cost information available from 

industry sources. Direct capital cost estimates for retrofits are highly site-specific. The generalized 

estimates used in this analysis, expressed in terms of dollars per kilowatt ($/kW) of net generation 

capacity, are assumed to be accurate within 25% - 50%.37 Considerable effort would be required to 

develop more accurate cost estimates. However, this level of accuracy should be sufficient to 

evaluate the cost-effectiveness of various upgrade options since the cost uncertainties affect all of 

the proposed upgrade options. 

WESP. Capital costs for a WESP installation depend on a number of factors, including the 

configuration and size of the unit (based on required efficiency and gas flow rate), the cost of 

corrosion resistant materials used in construction, the required level of water treatment, and market 

conditions. These factors may result in as much as an order of magnitude variation in capital costs. 

In addition, capital costs for retrofit applications may be significantly higher, depending on the 

difficulty of the retrofit. For this analysis, SCS has assumed that an integrated retrofit 

configuration would be required for all units. Capital cost for the WESP has been estimated at 

 

36 Harrison, W., Ibid. 

37 Nichols, G., Ibid. 
4-19 

$115/kW.38 It should be noted that material costs can vary significantly depending on market 

conditions. As demand for new power plant construction and pollution control devices increases, 

particularly for new WFGD systems, market prices for materials and construction will also 

increase. 

Lime Injection. Lime injection requires the installation of an injection manifold, ductwork 

modifications, various storage tanks, silos, blowers, and piping. SCS has assumed a capital cost of 

$10/kW for the addition of lime injection.39 

ESP Upgrade Options. Capital costs for gas flow optimization and Juice Cans were assumed to be 

$1.5/kW and $1.0/kW, respectively.40 Capital costs for the installation of a new collection field 

were assumed to be $40/kW. Capital costs for the particle agglomerator were assumed to be 

$13.3/kW.41 

Indirect Capital Costs 

Indirect capital costs include the loss of investment interest incurred during the construction period 

of the upgrade option. While indirect capital costs can be a significant cost component for some 

construction projects, SCS has excluded them from this cost analysis. Almost all of the upgrade 

options can be completed within a four to six week timeframe and, therefore, the indirect capital 

costs associated with these upgrade options are considered minor. For the WESP option, while the 

installation may likely take longer than six weeks, SCS can not provide a reasonable estimate of 

the construction timeframe for the purpose of estimating indirect capital costs. Therefore, in order 

to provide a conservative cost estimate, SCS has excluded this cost component from the analysis. 

Capital Cost Summary 

The total capital investment (TCI) normally includes both the direct and indirect capital costs 

associated with upgrade option. Since indirect capital costs have been excluded from this analysis, 

TCI is based solely on direct capital costs. The TCI for each applicable upgrade option is 

summarized in Tables 4-2 and 4-3 for each unit. 

 

38 Estimate is consistent with EPA data for WESP of $40/kW to $400/kW (EPA Air Pollution Technology Fact Sheet 

EPA-452/F-03-029). Higher cost estimate is justified due to complexity of integrated retrofit. 

39 Data is consistent with DOE estimates for lime injection (upstream of A/H) of $9/kWh (Blythe, G. (2004). Furnace 

Injection of Alkaline Sorbents for Sulfuric Acid Removal, DOE Report). 

40 Nichols, G., Ibid. Estimates are based on a model 300MW boiler equipped with 200 SCA (cold-side) ESP. 

41 Based on vendor estimates provided by Indigo Technologies, Inc. for a 235 MW boiler equipped with a 110 SCA 

(cold-side) ESP (Appendix C). SCS has included an additional 20% cost adjustment to reflect in house facilities and 

engineering costs. 
4-20 

Table 4-2 Total Capital Cost Estimates, Units 1/2 

Upgrade Option TCI 

Agglomerator $9,310,000 

Optimize Gas Flow $1,068,065 

Juice Cans $700,000 

Add New Collection Field $28,000,000 

WESP $80,500,000 

Lime Injection $7,000,000 

Table 4-3 Total Capital Cost Estimates, Units 3/4 

Upgrade Option TCI 

Agglomerator $11,970,000 

Optimize Gas Flow $1,373,226 

Juice Cans $900,000 

WESP $103,500,000 

Lime Injection $9,000,000 

Annualized Costs

The cost impact analysis requires the determination of the annualized cost of each upgrade option. 

Annualized costs include operating and maintenance (O&M) costs, annualized TCI costs and 

station service penalties associated with certain upgrade options. Annualized costs are based on 

average capacity factor for the 2003 – 2005 historical baseline timeframe (see discussion below). 

The following section discusses the annualized costs associated with each upgrade option. 

Operation and Maintenance Costs 

O&M costs include the additional man-power and other resources (i.e. water requirements, sorbent 

materials, etc.) required to operate and maintain the equipment.42 O&M costs for most of the 

upgrades are considered negligible except for the WESP and lime injection options. O&M costs 

for the WESP have been estimated at $0.47/MWh43. O&M costs for the lime injection system 

consist primarily of the added sorbent cost. SCS has assumed the O&M costs for lime injection to 

be $0.40/MWh. 

Annualized TCI Costs 

Total capital costs (TCI) for major utility construction projects are typically referred to as “capital 

recovery costs” and are expressed on an annualized basis. Annual capital recovery costs are 

equivalent to an annual payment that is sufficient to finance the investment over the expected life 

of the equipment. Capital recovery costs are determined by applying a capital recovery factor to 

the TCI cost. The capital recovery factor used in this analysis (0.1098) is derived from a simple 

interest formula assuming a “real”44 interest rate of 7% and an equipment life of 15 years. The 

 

42 Station service requirements for WESP and lime injection are not included in O&M cost estimates. These costs are 

accounted for separately as station service penalties. 

43 Estimate is below EPA data for WESP O&M costs of $1.6/MWh to $2.6/MWh (EPA Air Pollution Technology Fact 

Sheet EPA-452/F-03-029). 

44 A “real” interest rate does not take into account the effects of inflation. 
4-21 

capital recovery cost approach does not include all revenues necessary to support an investment 

item such as administrative costs, property taxes, and insurance expenses. 

Capacity and Energy Penalties 

This analysis also includes the calculation of indirect capacity and energy penalties associated with 

the increased station service requirements of certain upgrade options. Station service requirements 

for Units 1/2 were assumed to be 350 kW for both the agglomerator retrofit and the addition of a 

new collection field and 3,500 kW for the WESP. Station service requirements for Units 3/4 were 

assumed to be 450 kW for the agglomerator retrofit and 4,500 kW for the WESP. Station service 

requirements for all other upgrade were assumed to be negligible. 

 

SCS assumed that the incremental capacity reduction would be made up by additional capacity 

constructed to offset the reduction. It is estimated that the cost of this capacity would be about 

$600/kW and that this capital would be recovered under the same financial assumptions as the 

control technologies being evaluated. In addition, the analysis includes an additional cost penalty 

associated with the energy production capability lost from the capacity reduction. It is reasonable 

to assume that this energy will be made up by purchasing makeup power at an average cost of 

$0.05/kWh. 

Annualized Cost Summary 

A breakdown of the total, annualized costs (in 2006 dollars) associated with each upgrade option is 

provided in Tables 4-4 and 4-5 for each unit. 

Table 4-4 Annualized Upgrade Cost Summary (2006 Dollars), Units 1/2 

Capacity and Energy Penalties 

Upgrade Option 

O&M 

Costs 

TCI Capital 

Recovery 

Capital Cost 

of Additional 

Capacity 

Capital Recovery 

of Additional 

Capacity 

Cost of 

Makeup 

Energy 

Annualized 

Cost 

Agglomerator $1,022,238 $210,000 $23,058 $118,233 $1,163,529 

Optimize Gas Flow $117,273 $117,273 

Juice Cans $76,860 $76,860 

Add New Collection 

Field 

 $3,074,400 $210,000 $23,058 $118,233 $3,215,691 

WESP $2,222,773 $8,838,900 $2,100,000 $230,580 $1,182,326 $12,474,580 

Lime Injection $1,891,722 $768,600 $2,660,322 

Table 4-5 Annualized Upgrade Cost Summary (2006 Dollars), Units 3/4 

Capacity and Energy Penalties 

Upgrade Option 

O&M 

Costs 

TCI Capital 

Recovery 

Capital Cost 

of Additional 

Capacity 

Capital Recovery 

of Additional 

Capacity 

Cost of 

Makeup 

Energy 

Annualized 

Cost 

Agglomerator $1,314,306 $270,000 $29,646 $152,013 $1,495,965 

Optimize Gas Flow $150,780 $150,780 

Juice Cans $98,820 $98,820 

WESP $2,857,851 $11,364,300 $2,700,000 $296,460 $1,520,134 $16,038,745 

Lime Injection $2,432,214 $988,200 $3,420,414 
4-22 

Other Cost Factors

There are a number of important factors that were not specifically included in the economic 

analysis. The most important of these relates to the reduced reliability that results from the add-on 

of sulfuric acid control options. Reduced reliability means these generating units would potentially 

be available for power generation less often. To make up for this unavailability, additional 

capacity would have to be installed or energy purchases made in order to adequately serve the 

customer demand for electricity. 

Cost Analysis

SCS performed the cost analysis of the various upgrade options in accordance with EPA’s BART 

Guidelines and the EPA Air Pollution Control Cost Manual. The objective of the cost analysis is 

to eliminate upgrade options from further evaluation that are not considered cost effective. This 

analysis considers both average and incremental cost effectiveness using the annualized installed 

capital, operating, and other indirect annualized costs and the estimated total PM10 emissions 

reduction of each upgrade option. Estimated emissions reduction for each option are determined 

using baseline emissions with scrubber operation and the incremental improvement in collection 

efficiency identified in the previous section. 

Baseline Emissions 

Baseline emissions for the cost analysis are derived from historical emissions for the three-year 

period 2003 through 2005 and have been adjusted to account for future scrubber operation. First, 

total filterable PM emissions were calculated using emissions test results for total, filterable PM 

from 2002 and 200445 and actual heat input data as reported in the Acid Rain Program quarterly 

EDR files. The resulting estimate for total, filterable PM emissions, in tons per year, along with 

corresponding NOx and SO2 emissions, is summarized in Tables 4-6 through 4-9 for the baseline 

historical period. 

Table 4-6 2003 – 2005 Historical Emissions, Unit 1 

Year 

Capacity 

Factor 

Boiler Heat 

Input 

PM Test 

Results 

Total, Filterable 

PM Emissions 

SO2

Emissions 

NOx

Emissions 

2003 70.9% 42,878,960 0.029 622 34,644 4,695 

2004 71.5% 43,260,104 0.081 1,752 34,447 5,129 

2005 74.8% 45,277,146 0.081 1,834 39.451 5,344 

Average 72.4% 43,805,403 0.064 1,403 36,181 5,056 

 

45 SCS conducts biannual PM compliance testing for total, filterable PM. Emissions test results, expressed in terms of 

‘lb/mmBtu’ from 2002 were applied to historical heat input data for 2003 to determine total, filterable PM emissions 

for 2003 in terms of ‘tons per year’. Emissions test results from 2004 were applied to historical heat input data for 

2004 – 2005 to determine total, filterable PM emissions for 2004 – 2005. 
4-23 

Table 4-7 2003 – 2005 Historical Emissions, Unit 2 

Year 

Capacity 

Factor 

Boiler Heat 

Input 

PM Test 

Results 

Total, Filterable 

PM Emissions 

SO2

Emissions 

NOx

Emissions 

2003 70.6% 42,723,636 0.071 1,517 34,063 4,760 

2004 76.9% 46,546,493 0.084 1,955 38,494 5,364 

2005 92.6% 56,039,764 0.084 2,354 48,000 7,153 

Average 80.1% 48,436,631 0.080 1,942 40,186 5,759 

Table 4-8 2003 – 2005 Historical Emissions, Unit 3 

Year 

Capacity 

Factor 

Boiler Heat 

Input 

PM Test 

Results 

Total, Filterable 

PM Emissions 

SO2

Emissions 

NOx

Emissions 

2003 81.8% 59,294,767 0.086 2,550 46,724 7,308 

2004 85.8% 62,211,838 0.046 1,431 50,603 7,979 

2005 76.5% 55,427,706 0.046 1,275 48,714 6,597 

Average 81.4% 58,978,104 0.059 1,752 48,680 7,295 

Table 4-9 2003 – 2005 Historical Emissions, Unit 4 

Year 

Capacity 

Factor 

Boiler Heat 

Input 

PM Test 

Results 

Total, Filterable 

PM Emissions 

SO2

Emissions 

NOx

Emissions 

2003 85.9% 63,231,404 0.099 3,130 49,453 8,197 

2004 71.5% 52,604,828 0.051 1,342 42,370 6,298 

2005 80.4% 59,201,659 0.051 1,510 50,306 7,151 

Average 79.3% 58,345,964 0.067 1,994 47,376 7,216 

The average total, historical filterable PM estimate for the baseline historical period was combined 

with AP-42 emissions factors to calculate estimated historical emissions for the various PM 

species, including filterable PM10, fine PM, and organic carbon.46 Baseline sulfuric acid emissions 

were calculated using the baseline SO2 emissions (unadjusted for WFGD operation) and the 

assumption of 0.8% conversion of flue gas SO2 to SO3 in the boiler, a 51% reduction in boilergenerated SO3 across both the air pre-heater and ESP, and an additional 0.99% oxidation of flue 

gas SO2 to SO3 across the SCR.47 Finally, the speciated PM emissions data were adjusted to 

account for future WFGD operation.48 The resulting baseline emissions for each unit are 

summarized in Table 4-10. 

 

46 The emissions factor used in the analysis for filterable PM10 (0.67) was applied to the baseline estimate of total, 

filterable PM emissions. The emissions factor for filterable, fine PM (0.444) was applied to the calculated estimate of 

filterable PM10 emissions. The emissions factor for organic carbon (0.0032) was applied to the baseline SO2 emissions 

(unadjusted for WFGD operation). 

47 The estimate of SCR-formed SO3 has been adjusted to account for reaction with ammonia, assuming an ammonia 

slip of 0.75 ppm at 6% O2. 

48 Baseline emissions estimates with WFGD operation assume an additional 80% removal of PM10 and an additional 

40% removal of sulfuric acid emissions across the scrubber. 
4-24 

Table 4-10 Baseline Emissions [tons per year], Units 1–4 

Filterable Species Condensable Species 

Unit 

Total 

PM10 

Tot Filt 

PM10 

Coarse 

PM Fine PM 

Tot Cond 

PM10 

Sulfuric 

Acid OC 

1 418.5 188.0 104.5 83.5 230.5 114.7 115.8 

2 516.3 260.2 144.7 115.5 256.1 127.5 128.6 

3 544.9 234.8 130.6 104.2 310.1 154.4 155.8 

4 568.8 267.2 148.6 118.6 301.6 150.0 151.6 

Estimated Post-Retrofit Emissions 

The estimated PM10 emissions for each upgrade option were calculated by applying the 

incremental removal efficiencies for filterable PM10, filterable fine PM, and sulfuric acid emissions 

(see Control Effectiveness of Feasible Options) to the baseline emissions for each unit. Tables 4-

11 through 4-14 summarize the estimated emissions for the various PM species for each unit. 

Table 4-11 Estimated Post-Retrofit Emissions [tons per year], Unit 1 

Filterable Species Condensable Species 

Upgrade Option 

Total 

PM10 

Tot Filt 

PM10 

Coarse 

PM Fine PM 

Tot Cond 

PM10 

Sulfuric 

Acid OC 

Agglomerator Retrofit 356.4 125.9 70.8 55.1 230.5 114.7 115.8 

Optimize Gas Flow 412.8 182.3 99.7 82.6 230.5 114.7 115.8 

Juice Can Retrofit 407.2 176.7 98.3 78.4 230.5 114.7 115.8 

Add New Collection 

Field 

352.7 122.2 65.5 56.7 230.5 114.7 115.8 

WESP 157.5 18.8 10.5 8.3 138.7 22.9 115.8 

Lime Injection 385.4 221.8 123.3 98.5 163.6 47.8 115.8 

Table 4-12 Estimated Post-Retrofit Emissions [tons per year], Unit 2 

Filterable Species Condensable Species 

Upgrade Option 

Total 

PM10 

Tot Filt 

PM10 

Coarse 

PM Fine PM 

Tot Cond 

PM10 

Sulfuric 

Acid OC 

Agglomerator Retrofit 430.4 174.3 76.2 98.1 256.1 127.5 128.6 

Optimize Gas Flow 508.5 252.4 114.4 138.0 256.1 127.5 128.6 

Juice Can Retrofit 500.7 244.6 108.6 136.0 256.1 127.5 128.6 

Add New Collection 

Field 

425.2 169.1 78.5 90.6 256.1 127.5 128.6 

WESP 180.1 26.0 11.5 14.5 154.1 25.5 128.6 

Lime Injection 478.2 296.5 131.6 164.9 181.7 53.1 128.6 
4-25 

Table 4-13 Estimated Post-Retrofit Emissions [tons per year], Unit 3 

Filterable Species Condensable Species 

Upgrade Option 

Total 

PM10 

Tot Filt 

PM10 

Coarse 

PM Fine PM 

Tot Cond 

PM10 

Sulfuric 

Acid OC 

Agglomerator Retrofit 493.3 183.1 114.3 68.8 310.1 154.4 155.8 

Optimize Gas Flow 530.8 220.7 118.6 102.1 310.1 154.4 155.8 

Juice Can Retrofit 523.8 213.6 118.7 94.9 310.1 154.4 155.8 

WESP 210.1 23.5 13.1 10.4 186.7 30.9 155.8 

Lime Injection 500.3 280.2 155.8 124.4 220.1 64.3 155.8 

Table 4-14 Estimated Post-Retrofit Emissions [tons per year], Unit 4 

Filterable Species Condensable Species 

Upgrade Option 

Total 

PM10 

Tot Filt 

PM10 

Coarse 

PM Fine PM 

Tot Cond 

PM10 

Sulfuric 

Acid OC 

Agglomerator Retrofit 510.0 208.4 130.1 78.3 301.6 150.0 151.6 

Optimize Gas Flow 552.8 251.1 134.8 116.3 301.6 150.0 151.6 

Juice Can Retrofit 544.8 243.1 135.2 107.9 301.6 150.0 151.6 

WESP 208.3 26.7 14.8 11.9 181.6 30.0 151.6 

Lime Injection 525.6 311.5 173.2 138.3 214.1 62.5 151.6 

Average Cost Effectiveness 

Average cost effectiveness refers to the total annualized costs of a control upgrade option, in 

dollars per year, divided by the estimated annual emissions reduction associated with the upgrade 

option, in tons per year. Average cost effectiveness is expressed in terms of (annualized) dollars 

per ton of pollutant removed ($/ton). 

In addition to the initial list of technically feasible upgrade options, SCS evaluated the cost 

effectiveness of combining multiple options.49 In evaluating which upgrade options to combine, 

SCS considered the combination of the two options that would provide the maximum expected 

visibility improvement (WESP and lime injection) and the combination of the two most cost 

effective options on an individual basis (agglomerator retrofit and Juice Cans). 

Tables 4-15 through 4-18 summarize the average cost effectiveness of each upgrade option and 

upgrade combination. The results show that the most cost effective control option for all four units 

is the addition of Juice Cans. The average cost for this option ranges from $4,100/ton to 

$6,800/ton. The results also show that the least cost effective control option for all four units is the 

addition of lime injection. The average cost for the addition of lime injection ranges from 

$70,000/ton to $80,000/ton. 

 

49 EPA’s BART Guidelines allow (Section IV.D.2) discretion in selecting the number of control combinations and the 

methodology used to determine these combinations. 
4-26 

Table 4-15 Average Cost Effectiveness of Upgrade Options, Unit 1 

Upgrade Option 

Annualized 

Cost [$/yr] 

PM10 Reduction 

[tpy] 

Average Cost 

[$/ton] 

Agglomerator $1,163,529 62.0 $18,759 

Optimize Gas Flow $117,273 5.6 $20,798 

Juice Cans $76,860 11.3 $6,815 

Add New Collection Field $3,215,691 65.8 $48,881 

WESP $12,474,580 261.0 $47,804 

Lime Injection $2,660,322 33.1 $80,377 

Agglomerator/Juice Cans $1,240,389 73.1 $16,921 

WESP/Lime Injection $15,134,902 271.0 $55,857 

Table 4-16 Average Cost Effectiveness of Upgrade Options, Unit 2 

Upgrade Option 

Annualized 

Cost [$/yr] 

PM10 Reduction 

[tpy] 

Average Cost 

[$/ton] 

Agglomerator $1,163,529 85.9 $13,550 

Optimize Gas Flow $117,273 7.8 $15,023 

Juice Cans $76,860 15.6 $4,923 

Add New Collection Field $3,215,691 91.1 $35,308 

WESP $12,474,580 336.2 $37,107 

Lime Injection $2,660,322 38.1 $69,889 

Agglomerator/Juice Cans $1,240,389 101.5 $12,222 

WESP/Lime Injection $15,134,902 347.4 $43,563 

Table 4-17 Average Cost Effectiveness of Upgrade Options, Unit 3 

Upgrade Option 

Annualized 

Cost [$/yr] 

PM10 Reduction 

[tpy] 

Average Cost 

[$/ton] 

Agglomerator Retrofit $1,495,965 51.6 $28,965 

Optimize Gas Flow $150,780 14.1 $10,705 

Juice Can Retrofit $98,820 21.1 $4,677 

WESP $16,038,745 334.8 $47,909 

Lime Injection $3,420,414 44.6 $76,652 

Agglomerator/Juice Can $1,594,785 72.8 $21,914 

WESP/Lime Injection $19,459,159 348.2 $55,878 

Table 4-18 Average Cost Effectiveness of Upgrade Options, Unit 4 

Upgrade Option 

Annualized 

Cost [$/yr] 

PM10 Reduction 

[tpy] 

Average Cost 

[$/ton] 

Agglomerator $1,495,965 58.8 $25,452 

Optimize Gas Flow $150,780 16.0 $9,406 

Juice Cans $98,820 24.0 $4,110 

WESP $16,038,745 360.5 $44,492 

Lime Injection $3,420,414 43.2 $79,225 

Agglomerator/Juice Cans $1,594,785 82.8 $19,256 

WESP/Lime Injection $19,459,159 373.6 $52,092 
4-27 

EPA does not provide a “bright line” in determining acceptable control costs for BART. The 

average cost effectiveness should be compared to the cost effectiveness of other similar BART 

determinations. However, such information is currently unavailable. SCS relies instead on the 

cost effectiveness of another “BART-like” determination in EPA Region 4 for this comparison. 

The PM BACT determination conducted by Tampa Electric Company (TECO) for ESP upgrades at 

Big Bend Station50 showed an average cost effectiveness for upgrade options ranging from 

$2,800/ton to $5,100/ton51. The only upgrade option with similar cost effectiveness for Bowen is 

the installation of Juice Can technology. The data suggests that all other upgrade options are not 

cost effective. 

Incremental Cost Effectiveness 

Incremental cost effectiveness (ICE) is used to compare the cost and performance of a particular 

upgrade option to the next most stringent upgrade option. Incremental cost effectiveness is 

calculated according to the following formula: 

( )

( )

Option NextMostStringentOption

Option NextMostStringentOption

Emissions Emissions

Cost Cost ICE −− =

EPA recommends that both incremental and average cost effectiveness be used in combination 

when considering whether to eliminate potential upgrade options. The incremental cost 

effectiveness may be used to justify the elimination of a more stringent alternative that may have 

comparable average cost effectiveness to the next most stringent option, but the incremental cost of 

the additional emissions reduction is excessive. 

EPA recommends evaluating incremental cost effectiveness based on dominant control 

alternatives. 52 A dominant control alternative is a control option that has an average cost 

effectiveness that is consistent with the general relationship between cost and emissions reduction 

for all competing control options. Dominant control alternatives can be identified by graphing the 

average cost effectiveness of each upgrade option. Dominant alternatives will form a smooth, nonlinear curve known as the “least-cost envelope”. Control options that lie inside of the least-cost 

envelope are considered inferior options because the cost per ton of particulate removed is 

inconsistent with other competing alternatives. 

SCS determined the least-cost envelope for the technically feasible upgrade options by creating a 

graphical plot of the total annualized cost and total PM10 emissions reductions for each upgrade 

option. An iterative procedure was then used to select the dominant options by including various 

combinations of upgrade options to achieve a least-cost envelope with the best curve fit. 

 

50 TECO’s PM BACT analysis was conducted as a requirement of a consent decree that was issued in 2000. TECO 

applied BACT procedures to evaluate potential upgrade technologies for their existing ESPs on Units 1 - 3. 

51 The BACT determination for all three units was a combination of upgrades including the installation of PC-based 

controls, improvements in ESP flow and temperature distribution, and upgrades to the ash handling system. 

52 BART Guidelines, Section IV.D.4.e.2. 
4-28 

As shown in Figures 1 through 4, the dominant control choices for all four units include WESP, the 

addition of Juice Can technology on existing transformer/rectifier (T/R) sets, the particle 

agglomerator, and the combination of Juice Can/particle agglomerator. Gas flow optimization, 

lime injection, the addition of a new electrical field (on Units 1 and 2), and the combination of 

WESP/lime injection have been eliminated because they fall inside of the least-cost envelope. 

These options are considered inferior based on cost and emissions reduction and, therefore, have 

been eliminated from further analysis. 

SCS calculated the incremental cost effectiveness of the dominant control options, as shown in 

Tables 4-19 thru 4-22, sorted in ascending order by annualized cost. The results suggest that the 

WESP has both high average costs ($37,000/ton - $48,000/ton and high incremental costs 

($47,000/ton - $60,000/ton) and should be eliminated due to the excessive cost. The results 

suggest that, while the incremental cost of the agglomerator/Juice Can combination is moderate 

($4,100/ton - $6,800/ton), the average cost of this option in also relatively high ($12,000/ton - 

$22,000/ton) and should be eliminated. Comparing the lowest cost option (Juice Cans) with the 

next most stringent option (agglomerator retrofit) shows incremental costs ranging from 

$15,000/ton to $46,000/ton. These incremental costs are also excessive – the incremental cost is 

approximately three to ten times higher than the average cost of the Juice Cans. 

Cost Analysis Summary 

The cost analysis suggests that the gas flow optimization, the addition of a new collection field 

(Units 1 and 2), lime injection, and the combination of WESP and lime injection should be 

eliminated from further consideration. These options were identified as inferior because they fall 

inside the least-cost envelope for each unit. Of the dominant upgrade options (Juice Cans, 

agglomerator retrofit, WESP, combination of Juice Cans/agglomerator), the Juice Can retrofit is 

the most cost-effective for all four units at Bowen. Average costs for this option range from 

$4,100/ton to $6,800/ton, which is somewhat higher but comparable to the average costs shown in 

TECO’s BACT evaluation. Average and incremental costs for the remaining dominant alternatives 

appear to be excessive. 
4-29 

y = 156.21x2 + 7050.1x - 3815.2

R2

 = 0.9997

$-

$2,000,000

$4,000,000

$6,000,000

$8,000,000

$10,000,000

$12,000,000

$14,000,000

$16,000,000

$18,000,000

0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0

Incremental Total PM Reduction [tpy]

Annualized Cost [$/yr]

WESP

Agglomerator

Gas Flow Opt

Lime

New Field

WESP/Lime

Agg/JuiceCan

JuiceCan

Figure 4-1. Least Cost Envelope, Unit 1 

y = 101.63x2 + 2853.4x + 27626

R2

 = 0.9997

$-

$2,000,000

$4,000,000

$6,000,000

$8,000,000

$10,000,000

$12,000,000

$14,000,000

$16,000,000

$18,000,000

0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0 400.0

Incremental Total PM Reduction [tpy]

Annualized Cost [$/yr]

WESP

Agglomerator

Gas Flow Opt

Lime

New Field

WESP/Lime

Agg/JuiceCan

JuiceCan

Figure 4-2. Least Cost Envelope, Unit 2
4-30 

y = 74.426x2 + 23891x - 303588

R2

 = 0.9988

$-

$2,000,000

$4,000,000

$6,000,000

$8,000,000

$10,000,000

$12,000,000

$14,000,000

$16,000,000

$18,000,000

$20,000,000

$22,000,000

$24,000,000

0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0 400.0

Incremental Total PM Reduction [tpy]

Annualized Cost [$/yr]

WESP

Agglomerator

Gas Flow Opt

Lime

WESP/Lime

Agg/JuiceCan

JuiceCan

Figure 4-3. Least Cost Envelope, Unit 3 

y = 71.151x2 + 19601x - 276282

R2

 = 0.9987

$-

$2,000,000

$4,000,000

$6,000,000

$8,000,000

$10,000,000

$12,000,000

$14,000,000

$16,000,000

$18,000,000

$20,000,000

$22,000,000

$24,000,000

0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0 400.0 450.0

Incremental Total PM Reduction [tpy]

Annualized Cost [$/yr]

WESP

Agglomerator

Gas Flow Opt

Lime

WESP/Lime

Agg/JuiceCan

JuiceCan

Figure 4-4. Least Cost Envelope, Unit 4
4-31 

Table 4-19 Incremental Cost Effectiveness, Unit 1 

Upgrade Option 

Annualized 

Cost [$/yr] 

Total PM10

Reduction [tpy] 

Average Cost 

[$/ton] 

Incremental Cost 

[$/ton] 

Juice Cans $76,860 11.3 $6,815 NA 

Agglomerator $1,163,529 62.0 $18,759 $21,413 

Agglomerator/Juice Cans $1,240,389 73.3 $16,921 $6,815 

WESP $12,474,580 261.0 $47,804 $59,868 

Table 4-20 Incremental Cost Effectiveness, Unit 2 

Upgrade Option 

Annualized 

Cost [$/yr] 

Total PM10

Reduction [tpy] 

Average Cost 

[$/ton] 

Incremental Cost 

[$/ton] 

Juice Cans $76,860 15.6 $4,923 NA 

Agglomerator $1,163,529 85.9 $13,550 $15,467 

Agglomerator/Juice Cans $1,240,389 101.5 $12,222 $4,923 

WESP $12,474,580 336.2 $37,107 $47,867 

Table 4-21 Incremental Cost Effectiveness, Unit 3 

Upgrade Option 

Annualized 

Cost [$/yr] 

Total PM10

Reduction [tpy] 

Average Cost 

[$/ton] 

Incremental Cost 

[$/ton] 

Juice Cans $98,820 21.1 $4,677 NA 

Agglomerator $1,495,965 51.6 $28,965 $45,780 

Agglomerator/Juice Cans $1,594,785 72.8 $21,914 $4,677 

WESP $16,038,745 334.8 $47,909 $55,129 

Table 4-22 Incremental Cost Effectiveness, Unit 4 

Upgrade Option 

Annualized 

Cost [$/yr] 

Total PM10

Reduction [tpy] 

Average Cost 

[$/ton] 

Incremental Cost 

[$/ton] 

Juice Cans $98,820 24.0 $4,110 NA 

Agglomerator $1,495,965 58.8 $25,452 $40,227 

Agglomerator/Juice Cans $1,594,785 82.8 $19,256 $4,110 

WESP $16,038,745 360.5 $44,492 $52,020 
4-32 

4.5.4 Remaining Useful Life 

One of the factors that is considered in determining BART is the remaining useful life of the 

emissions unit.53 In situations in which the unit will retire before BART compliance is required, 

the “remaining useful life” factor would allow a state to determine that no control of that unit is 

required as BART. Similarly, in situations in which the unit will retire before conclusion of the 

assumed 15-year equipment life used for the capital recovery factor in annualizing the cost of the 

control options, the state would consider the “remaining useful life” factor in determining the costeffectiveness of the control options being evaluated. 

For each of the EGUs at Plant Bowen, neither situation exists. None of the units will be retired 

before BART compliance would be required, and none of the units will be retired before 

conclusion of the 15-year equipment life for annualizing the cost of control options. Thus, there is 

no basis for considering the “remaining useful life” factor in determining PM BART for any of 

Plant Bowen’s EGUs. 

4.6 Visibility Impacts Modeling for Feasible Options 

In determining BART, states must consider the visibility improvement that would result from the 

potential control options under evaluation. 54 The visibility improvement modeling for Plant 

Bowen’s EGUs was conducted pursuant to the “BART Determination Modeling Protocol” 

submitted to EPD on December 4, 2006 (Appendix D). (As was the case for the exemption 

modeling discussed in section 3.0 above, the stack temperature used in the determination modeling 

has been adjusted from actual to virtual temperature.) Although each possible control option could 

be modeled and that option’s visibility improvement could then be compared to the baseline 

visibility impact, the previous discussion suggests that the visibility improvement analysis for the 

Plant Bowen PM BART determination could be simplified by limiting the required modeling to a 

subset of the dominant control options for each unit. Specifically, modeling was conducted for the 

following two upgrade options for each unit: (1) the combination of the particle agglomerator and 

Juice Cans, which has the highest PM removal rate of the set of relatively lower cost controls; and 

(2) the WESP, the option with the highest total PM10 removal. The December 2006 Modeling 

Protocol further explains this approach. As discussed below, this approach provides adequate 

information to evaluate the visibility improvement associated with each of the feasible control 

options. 

Tables 4-23 and 4-24 summarize the results of the visibility improvement modeling. For the 

agglomerator/Juice Can combination, the results show that there is virtually no visibility 

improvement associated with that option. For each of the units, the delta-delta-deciview 

improvement compared to the baseline is -0.01 dv (out to two decimal places, using the new 

IMPROVE equation and virtual temperature, 8th highest high). Given these results, it is clear that, 

 

53 BART Guidelines, Section IV.D.4.k 

54 BART Guidelines, Section IV.D.5. 
4-33 

Table 4-23 

Summary of Results - Plant Bowen BART Determination Modeling for Cohutta 

2001 2002 2003 

8th

Highest 

delta-dv 

8th

Highest 

delta-dv 

8th

Highest 

delta-dv 

Highest of 

8th Highest 

delta-dv 

for the 3-

years 

22nd

Highest 

delta-dv 

over 3-

year 

period 

Baseline - Scrubbed 

Bowen 1-4 Result

New Improve 

Virtual Temp 0.74 0.94 0.59 0.94 0.74 

New Improve 

Actual Temp 0.78 1.05 0.73 1.05 0.82 

Old Improve 

Virtual Temp 0.91 1.15 0.73 1.15 0.91 

Old Improve 

Actual Temp 0.97 1.28 0.90 1.28 1.00 

Agglomerator/Juice Can 

Bowen 1-4 Results - Unit 1 Controlled

New Improve 

Virtual Temp 0.73 0.94 0.58 0.94 0.73 

New Improve 

Actual Temp 0.78 1.04 0.72 1.04 0.81 

Old Improve 

Virtual Temp 0.91 1.14 0.73 1.14 0.91 

Old Improve 

Actual Temp 0.96 1.27 0.89 1.27 0.99 

Bowen 1-4 Results - Unit 2 Controlled

New Improve 

Virtual Temp 0.73 0.94 0.58 0.94 0.73 

New Improve 

Actual Temp 0.78 1.04 0.72 1.04 0.81 

Old Improve 

Virtual Temp 0.91 1.14 0.73 1.14 0.91 

Old Improve 

Actual Temp 0.96 1.27 0.89 1.27 0.99 

Bowen 1-4 Results - Unit 3 Controlled

New Improve 

Virtual Temp 0.73 0.94 0.59 0.94 0.73 

New Improve 

Actual Temp 0.78 1.05 0.72 1.05 0.81 

Old Improve 

Virtual Temp 0.91 1.15 0.73 1.15 0.91 

Old Improve 

Actual Temp 0.96 1.28 0.90 1.28 1.00 

Bowen 1-4 Results - Unit 4 Controlled

New Improve 

Virtual Temp 0.73 0.94 0.59 0.94 0.73 

New Improve 

Actual Temp 0.78 1.05 0.72 1.05 0.81 

Old Improve 

Virtual Temp 0.91 1.15 0.73 1.15 0.91 

Old Improve 

Actual Temp 0.96 1.28 0.90 1.28 1.00 
4-34 

Table 4-23 (Continued) 

Summary of Results - Plant Bowen BART Determination Modeling for Cohutta 

2001 2002 2003 

8th

Highest 

delta-dv 

8th

Highest 

delta-dv 

8th

Highest 

delta-dv 

Highest of 

8th Highest 

delta-dv 

for the 3-

years 

22nd

Highest 

delta-dv 

over 3-

year 

period 

Wet ESP 

Bowen 1-4 Results - Unit 1 Controlled

New Improve 

Virtual Temp 0.64 0.80 0.50 0.80 0.64 

New Improve 

Actual Temp 0.67 0.89 0.61 0.89 0.70 

Old Improve 

Virtual Temp 0.78 0.98 0.62 0.98 0.78 

Old Improve 

Actual Temp 0.83 1.09 0.76 1.09 0.85 

Bowen 1-4 Results - Unit 2 Controlled

New Improve 

Virtual Temp 0.63 0.80 0.50 0.80 0.63 

New Improve 

Actual Temp 0.67 0.89 0.61 0.89 0.69 

Old Improve 

Virtual Temp 0.77 0.98 0.62 0.98 0.77 

Old Improve 

Actual Temp 0.83 1.08 0.75 1.08 0.85 

Bowen 1-4 Results - Unit 3 Controlled

New Improve 

Virtual Temp 0.63 0.79 0.50 0.79 0.63 

New Improve 

Actual Temp 0.65 0.88 0.61 0.88 0.68 

Old Improve 

Virtual Temp 0.78 0.96 0.61 0.96 0.78 

Old Improve 

Actual Temp 0.81 1.08 0.77 1.08 0.84 

Bowen 1-4 Results - Unit 4 Controlled

New Improve 

Virtual Temp 0.62 0.78 0.49 0.78 0.62 

New Improve 

Actual Temp 0.65 0.87 0.61 0.87 0.67 

Old Improve 

Virtual Temp 0.78 0.95 0.61 0.95 0.77 

Old Improve 

Actual Temp 0.78 1.06 0.76 1.06 0.83 
4-35 

Table 4-24 

Summary of Results – Visibility Improvement from Baseline 

Plant Bowen BART Determination Modeling for Cohutta 

2001 2002 2003 

8th

Highest 

delta-dv 

8th

Highest 

delta-dv 

8th

Highest 

delta-dv 

Highest of 

8th Highest 

delta-dv 

for the 3-

years 

22nd

Highest 

delta-dv 

over 3-

year 

period 

deltadelta-dv deltadelta-dv deltadelta-dv delta-deltadv delta-deltadv 

Agglomerator/Juice Can 

Bowen 1-4 Results - Unit 1 Controlled

New Improve 

Virtual Temp -0.01 0.00 -0.01 -0.01 -0.01 

New Improve 

Actual Temp 0.00 -0.01 -0.01 -0.01 -0.01 

Old Improve 

Virtual Temp 0.00 -0.01 0.00 -0.01 0.00 

Old Improve 

Actual Temp -0.01 -0.01 -0.01 -0.01 -0.01 

Bowen 1-4 Results - Unit 2 Controlled

New Improve 

Virtual Temp -0.01 0.00 -0.01 -0.01 -0.01 

New Improve 

Actual Temp 0.00 -0.01 -0.01 -0.01 -0.01 

Old Improve 

Virtual Temp 0.00 -0.01 0.00 -0.01 0.00 

Old Improve 

Actual Temp -0.01 -0.01 -0.01 -0.01 -0.01 

Bowen 1-4 Results - Unit 3 Controlled

New Improve 

Virtual Temp -0.01 0.00 0.00 -0.01 -0.01 

New Improve 

Actual Temp 0.00 0.00 -0.01 -0.01 -0.01 

Old Improve 

Virtual Temp 0.00 0.00 0.00 0.00 0.00 

Old Improve 

Actual Temp -0.01 0.00 0.00 -0.01 0.00 

Bowen 1-4 Results - Unit 4 Controlled

New Improve 

Virtual Temp -0.01 0.00 0.00 -0.01 -0.01 

New Improve 

Actual Temp 0.00 0.00 -0.01 -0.01 -0.01 

Old Improve 

Virtual Temp 0.00 0.00 0.00 0.00 0.00 

Old Improve 

Actual Temp -0.01 0.00 0.00 -0.01 0.00 
4-36 

Table 4-24 (Continued) 

Summary of Results – Visibility Improvement from Baseline 

Plant Bowen BART Determination Modeling for Cohutta 

2001 2002 2003 

8th

Highest 

delta-dv 

8th

Highest 

delta-dv 

8th

Highest 

delta-dv 

Highest of 

8th Highest 

delta-dv 

for the 3-

years 

22nd

Highest 

delta-dv 

over 3-

year 

period 

deltadelta-dv deltadelta-dv deltadelta-dv delta-deltadv delta-deltadv 

Wet ESP 

Bowen 1-4 Results - Unit 1 Controlled

New Improve 

Virtual Temp -0.10 -0.14 -0.09 -0.14 -0.10 

New Improve 

Actual Temp -0.11 -0.16 -0.12 -0.16 -0.12 

Old Improve 

Virtual Temp -0.13 -0.17 -0.11 -0.17 -0.13 

Old Improve 

Actual Temp -0.14 -0.19 -0.14 -0.19 -0.15 

Bowen 1-4 Results - Unit 2 Controlled

New Improve 

Virtual Temp -0.11 -0.14 -0.09 -0.14 -0.11 

New Improve 

Actual Temp -0.11 -0.16 -0.12 -0.16 -0.13 

Old Improve 

Virtual Temp -0.14 -0.17 -0.11 -0.17 -0.14 

Old Improve 

Actual Temp -0.14 -0.20 -0.15 -0.20 -0.15 

Bowen 1-4 Results - Unit 3 Controlled

New Improve 

Virtual Temp -0.11 -0.15 -0.09 -0.15 -0.11 

New Improve 

Actual Temp -0.13 -0.17 -0.12 -0.17 -0.14 

Old Improve 

Virtual Temp -0.13 -0.19 -0.12 -0.19 -0.13 

Old Improve 

Actual Temp -0.16 -0.20 -0.13 -0.20 -0.16 

Bowen 1-4 Results - Unit 4 Controlled

New Improve 

Virtual Temp -0.12 -0.16 -0.10 -0.16 -0.12 

New Improve 

Actual Temp -0.13 -0.18 -0.12 -0.18 -0.15 

Old Improve 

Virtual Temp -0.13 -0.20 -0.12 -0.20 -0.14 

Old Improve 

Actual Temp -0.19 -0.22 -0.14 -0.22 -0.17 
4-37 

for each of the control options that provide fewer tons removed than does the agglomerator/Juice 

Can combination (i.e., the agglomerator alone and the Juice Cans alone), there also will be no 

visibility improvement from those options. 

For the WESP, the results show a small visibility improvement as compared to baseline visibility 

impacts. For Units 1 & 2 with a WESP, the model predicts a -0.14 delta-delta-deciview 

improvement compared to the baseline (8th highest high, new IMPROVE equation and virtual 

temperature). For Unit 3, the model predicts a -0.15 delta-delta-deciview improvement. Finally, 

for Unit 4, the model predicts a -0.16 delta-delta-deciview improvement. 

Appendix E lists delta-deciview results for the top 20 days for each year modeled and the top 25 

days for the overall three years at Cohutta for the primary results (i.e., the virtual temperature, new 

IMPROVE equation case). 

An external hard drive is being provided separately that contains all of the electronic data related to 

this application (i.e., the virtual temperature, new IMPROVE equation case). This drive contains 

all of the input and output files used in the modeling. A readme.txt file is also included on the hard 

drive that lists all of the files on the drive. 
5-1 

5.0 Proposed PM BART for the Plant Bowen EGUs 

EPA’s BART Guidelines contain little guidance regarding how to select BART from among the 

control options under consideration.55 The Guidelines simply indicate that, for each option, the 

emissions reduction, costs, energy and non-air quality environmental impacts, and modeled 

visibility improvement must be considered. 

Section 4.0 of this document explains that PM emissions from Plant Bowen’s EGUs are already 

very well controlled. Moreover, the available control options for PM BART span a wide range of 

costs but provide relatively small additional PM emissions reductions. From a regional haze 

standpoint, none of the available control options would produce a significant improvement in 

visibility in the most impacted Class I area, Cohutta. This is not surprising given VISTAS’ 

conclusion that SO2 emissions, not PM emissions, are primarily responsible for visibility 

impairment in the VISTAS’ Class I areas. 

Table 5-1 summarizes the information that is relevant for assessing whether any of the feasible PM 

control options should be considered BART. The following discussion analyzes this information. 

The cost of compliance is one of the considerations that must be taken into account in selecting 

BART. Because neither EPA nor GEPD has announced any cost threshold for selecting BART and 

cost information from other PM BART determinations is unavailable, GPC has evaluated the 

BART options based on its general knowledge of previous NSR BACT cost thresholds that have 

been applied by regulators. It should be noted that GPC believes that NSR BACT cost evaluations 

are not directly relevant, and are conservative, for a BART analysis, given that NSR BACT applies 

to new sources and is part of a nationwide health-and-welfare based air quality program, while 

BART is focused on retrofits to existing sources and is relevant to a single-component (i.e., 

visibility), welfare-based air quality program for only Federal Class I areas. Thus, if the costeffectiveness for a BART option exceeds the cost-effectiveness range that has been deemed 

reasonable in BACT determinations, then GPC believes that there is no reasonable basis for 

requiring those technologies under the regional haze program. Under NSR BACT determinations, 

regulators typically have not required installation of technologies that cost more than about 

$10,000/ton of pollutant removed. 

As discussed previously, GPC has considered the cost information from the BART-like ESP 

upgrade analysis conducted by TECO for Big Bend Station as part of the consent decree issued in 

2000. This is perhaps the most relevant cost information, since the objective of the TECO analysis 

was to evaluate the cost-effectiveness of various PM control device upgrade technologies, which is 

very similar to BART. The TECO determination showed upgrade costs ranging from $2,800/ton to 

$5,100/ton. 

 

The analysis described in section 4.0 above reveals that the average cost-effectiveness of the 

WESP option ranges from about $37,000/ton (for Unit 2) to about $48,000/ton (for Units 1 and 3). 

In GPC’s view, such cost-effectiveness values cannot be considered reasonable for BART. In 

addition, the WESP uses additional energy and has negative non-air environmental impacts 

 

55 BART Guidelines, Section IV.E. 
5-2 

associated with wastewater disposal. Finally, the WESP is estimated to produce less than a -0.2 

delta-delta-deciview improvement in visibility in the closest Class I area, Cohutta, for any of the 

units. This level of improvement is well below the level that EPA considers to be detectable 

Table 5-1 Summary of Bowen BART Determination Results1

Upgrade Option 

Annualized Cost 

[$/yr] 

PM10

Reduction 

[tpy] 

Average Cost 

[$/ton] 

Visibility 

Improvement 

from Baseline2

[delta-delta-dv] 

Bowen Unit 1 Results

Juice Can $76,860 11.3 $6,815 - 

Agglomerator $1,163,529 62.0 $18,759 - 

Agglomerator/Juice Cans $1,240,389 73.1 $16,921 -0.01 

Wet ESP $12,474,580 261.0 $47,804 -0.14 

Bowen Unit 2 Results

Juice Can $76,860 15.6 $4,923 - 

Agglomerator $1,163,529 85.9 $13,550 - 

Agglomerator/Juice Cans $1,240,389 101.5 $12,222 -0.01 

Wet ESP $12,474,580 336.2 $37,107 -0.14 

Bowen Unit 3 Results 

Juice Can $98,820 21.1 $4,677 - 

Agglomerator $1,495,965 51.6 $28,965 - 

Agglomerator/Juice Can $1,594,785 72.8 $21,914 -0.01 

Wet ESP $16,038,745 334.8 $47,909 -0.15 

Bowen Unit 4 Results

Juice Can $98,820 24.0 $4,110 - 

Agglomerator $1,495,965 58.8 $25,452 - 

Agglomerator/Juice Cans $1,594,785 82.8 $19,256 -0.01 

Wet ESP $16,038,745 360.5 $44,492 -0.16 

 Notes: 

1. Visibility improvement results represent new IMPROVE equation and virtual stack temperature. 

2. Incremental change is the “Highest of 8th Highest delta-delta-dv for the 3-years.” 

(approximately one deciview), and is also below the level (0.5 deciview) that EPA has 

recommended be used for visibility contribution analyses in the “subject-to-BART” step. In 

addition, because VISTAS’ modeling shows that the Cohutta Class I area is achieving, by a wide 

margin, the uniform rate of progress (glide slope goal) in 2018, the small additional fraction of 

visibility improvement that would be associated with use of the WESP would, in GPC’s view, not 

be worth the significant additional cost. 

The agglomerator and the Juice Can/agglomerator combination both have average costeffectiveness values that exceed (Units 1, 3, & 4) or lie at the upper limit (Unit 2) of costeffectiveness values considered to be reasonable for BACT and other BART-like determinations. 

As a result, GPC believes that these technologies are not cost-effective for BART. Moreover, these 
5-3 

technologies are estimated to produce virtually no visibility improvement in the Cohutta Class I 

area. Therefore, these options should also be rejected as BART. 

Finally, the Juice Can option has an average cost-effectiveness ($4,110 - $6,815) that a regulator 

might consider reasonable for BACT, and which is close to the upper range for the TECO 

determination. However, even if this cost range were to be considered reasonable under the BART 

program, this option reduces PM emissions by only 11 to 24 tons (depending on the unit), and the 

CALPUFF modeling of control options that reduce even more PM reveals that this option is not 

expected to improve visibility in the Cohutta Class I area. The fact that the Juice Can option does 

not improve visibility in Cohutta should eliminate the option from consideration, regardless of 

whether GEPD would or would not find the cost-effectiveness values to be reasonable. 

Based on the foregoing discussion, GPC believes that none of the PM control options should be 

selected by EPD as BART for any of Plant Bowen’s EGUs. 
Appendix A 

Description of Virtual Temperature Calculation Tool 
Appendix A 

Buoyancy of Moist Plumes: Equivalent Dry Effluent Temperature 

Russell Noble, P.E.; Charles Boohaker, P.E. 

Southern Company Services, September 2003 

Background 

Power plant stack effluent is typically treated in dispersion models as a ‘dry’ plume and moisture 

impacts are ignored. In high moisture plumes, such as those exiting a wet scrubber, the added 

buoyancy of water vapor compared to dry air or combustion product gases should be considered. 

One method of accounting for added buoyancy of high moisture plumes is to calculate an 

equivalent dry plume temperature. Simply put, a virtual temperature (Tv) can be defined and 

calculated1 such that a moist plume of temperature T has the same density as a dry plume with 

temperature Tv. This paper will describe a calculation tool created to determine Tv of a moist 

plume based on fuel, operational, ambient and physical stack parameter inputs. 

Input Data 

In order to calculate actual plume constituents and concentrations, a fuel ultimate analysis (user 

input or provided selections) is needed along with expected excess combustion air. Local ambient 

dry bulb temperature and humidity ratio are required in addition to site base elevation, stack height 

and stack exit diameter. A flue gas temperature must be supplied and specified whether the 

temperature corresponds to the scrubber inlet or outlet (already saturated) location. The program is 

equipped with a ‘saturator’ module to calculate scrubber outlet conditions if unknown. Stack exit 

velocity will be calculated if a total flue gas flow is supplied. It is assumed that the given gas flow 

corresponds to the chosen scrubber inlet/outlet location. Required input summary: 

 Fuel ultimate analysis % by weight of constituents 

 Flue gas temperature oF 

 Temperature location Scrubber inlet or outlet (drop down box) 

 Excess air % 

 Flue gas flow lb/hr 

 Ambient temperature oF 

 Ambient humidity ratio lbwater vapor / lbdry air

 Site base elevation ft above sea level 

 Stack height ft above site base elevation 

 Stack exit diameter ft 

 

1

 Rolland B. Stull, Meteorology for Scientists and Engineers, 2nd Ed. (Pacific Grove, CA: Brooks/Cole, 2000), p. 8. 
Optional Data 

There is a provision for indirect reheat of the flue gas. In this case, the number of degrees of reheat 

(over saturation) is required. Note that reheat is indirect - no moisture or hot gas is added and no 

supplemental fuel is fired. A reheat limit of 40oF over saturation is incorporated into the tool. 

 

Output Data 

For a scrubber ‘inlet’ specified input parameter set, the tool will saturate the flue gas and provide 

the actual stack exit (saturated) gas temperature, stack exit virtual temperature, and average stack 

exit gas velocity. Given a scrubber ‘outlet’ parameter set, the tool will return stack exit virtual 

temperature and average stack exit gas velocity (actual saturated stack exit temperature provided in 

parameter set). 

Methodology 

Calculation of Tv can be broken down into four distinct areas or calculation modules: 

determination of (1) fuel/air specific combustion products, (2) moisture saturation temperature of 

the combustion gas, (3) moisture properties and absolute pressure at various elevations, and (4) 

final calculation of virtual temperature. 

Data from the provided fuel analysis, along with excess air levels, are used to calculate the wet 

products of combustion. Complete combustion is assumed and combustion air moisture is 

incorporated. Flue gas composition is now fully defined and can be expressed on a wet or dry 

basis. 

If gas temperature is specified as scrubber ‘inlet’, the moisture saturation temperature of the gas 

will be calculated (otherwise, it is given). Saturation temperature is determined by assuming an 

adiabatic cooling process with a correction2

 for actual flue gas specific heat as a function of CO2

content. Added moisture from the ‘saturator’ is incorporated into the flue gas composition. 

Saturator calculations are performed at the site elevation pressure. No drop in saturated gas 

temperature occurs as the gas travels to the stack exit elevation. This assumption is based on 

vendor modeling of heat transfer from the gas to atmosphere for a fiberglass stack liner inside a 

concrete shell design3. For other stack configurations, this assumption should be reviewed. 

Local barometric pressure will affect volumetric flow (exit gas velocity) and moisture properties. 

Absolute pressure at site and stack exit elevation was calculated from U.S. standard atmosphere 

lapse rate. Properties of moist air, along with lapse rate information were taken from ASHRAE 

tables4 or formulae. 

Final calculation of virtual temperature is straightforward and is a function of absolute temperature 

of the gas and mixture humidity ratio (sometimes known as mixing ratio or specific humidity, 

 

2

 Sirozi Hatta, “New Humidity Chart Simplifies Combustion Gas Problems,” Chemical & Metallurgical Engineering, 

(March 1930), p. 165. 

3

 Hamon Custodis model of 500 ft, 130F stack system with 10F ambient indicated <0.3F temperature drop. 

4

 American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc., 1997 ASHRAE Handbook: 

Fundamentals, Inch Pound Edition, (1997), pp. 6.1-6.6. 
depending on the reference source). Humidity ratio is defined as the ratio of mass of water vapor 

to mass of dry gas. Tv is calculated as: 

= TTv × + ×ω)609.01(

Where: T = absolute gas temperature, o K 

ω = gas humidity ratio, lbwater vapor / lbdry gas
Appendix B 

Exemption Modeling 

Delta-Deciview Values for the Top 20 Days – for Each Year/Each 

Class I Area and for the Top 25 Days – Over Three Years 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 20 Days Each Year) 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.31 7.94 1.37 3.8 2.9 4.3 73.1 0.0 19.9 1.3 2.4 3.3 1 

2001 113 1 8.60 7.60 0.99 2.8 2.3 3.6 67.2 0.0 24.2 1.6 3.0 4.0 2 

2001 225 3 9.27 8.33 0.94 4.9 3.5 5.1 77.9 0.0 16.3 1.1 2.0 2.7 3 

2001 297 3 8.97 8.10 0.87 4.2 3.2 4.6 75.4 0.0 18.2 1.2 2.1 3.1 4 

2001 114 4 8.43 7.60 0.82 2.8 2.3 3.6 67.5 0.0 24.3 1.6 2.6 4.0 5 

2001 279 1 8.87 8.10 0.77 4.2 3.2 4.6 75.4 0.0 18.3 1.1 2.2 3.0 6 

2001 220 54 9.10 8.33 0.76 4.9 3.5 5.1 77.9 0.0 16.3 1.1 1.9 2.8 7 

2001 111 16 8.34 7.60 0.74 2.8 2.3 3.6 67.5 0.0 24.2 1.6 2.7 4.0 8 

2001 294 1 8.79 8.10 0.69 4.2 3.2 4.6 75.2 0.0 18.2 1.2 2.3 3.1 9 

2001 51 8 8.39 7.72 0.67 3.2 2.5 3.8 69.7 0.0 22.6 1.4 2.5 3.7 10 

2001 102 9 8.20 7.60 0.60 2.8 2.3 3.6 67.4 0.0 24.2 1.6 2.7 4.1 11 

2001 229 16 8.88 8.33 0.55 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.5 2.7 12 

2001 110 3 8.12 7.60 0.52 2.8 2.3 3.6 67.3 0.0 24.2 1.6 2.7 4.1 13 

2001 142 3 8.34 7.87 0.47 3.6 2.8 4.1 72.5 0.0 20.7 1.4 1.9 3.6 14 

2001 112 35 8.08 7.60 0.47 2.8 2.3 3.6 67.5 0.0 24.2 1.6 2.6 4.1 15 

2001 343 97 8.40 7.94 0.46 3.8 2.9 4.3 73.0 0.0 19.9 1.4 2.4 3.4 16 

2001 158 25 8.56 8.10 0.46 4.2 3.2 4.6 75.4 0.0 18.3 1.2 2.2 2.9 17 

2001 126 3 8.31 7.87 0.44 3.6 2.8 4.1 72.2 0.0 20.6 1.3 2.3 3.5 18 

2001 236 25 8.77 8.33 0.43 4.9 3.5 5.1 77.8 0.0 16.3 1.1 2.1 2.7 19 

2001 198 9 8.62 8.21 0.42 4.5 3.3 4.9 76.7 0.0 17.3 1.2 1.9 3.0 20 

 

2002 224 3 9.67 8.33 1.33 4.9 3.5 5.1 77.9 0.0 16.3 1.1 2.0 2.7 1 

2002 15 16 9.07 7.82 1.26 3.4 2.7 4.0 71.4 0.0 21.4 1.3 2.4 3.5 2 

2002 227 8 9.52 8.33 1.19 4.9 3.5 5.1 78.0 0.0 16.3 1.1 1.9 2.7 3 

2002 365 16 9.08 7.94 1.15 3.8 2.9 4.3 73.0 0.0 19.9 1.3 2.4 3.4 4 

2002 67 3 8.72 7.67 1.05 3.0 2.5 3.7 68.7 0.0 23.2 1.5 2.7 3.9 5 

2002 228 97 9.33 8.33 1.00 4.9 3.5 5.1 78.0 0.0 16.3 1.1 1.9 2.7 6 

2002 230 3 9.31 8.33 0.98 4.9 3.5 5.1 77.8 0.0 16.3 1.1 2.0 2.8 7 

2002 226 97 9.28 8.33 0.94 4.9 3.5 5.1 77.9 0.0 16.3 1.1 2.0 2.7 8 

2002 314 2 8.76 7.87 0.89 3.6 2.8 4.1 72.1 0.0 20.6 1.3 2.6 3.5 9 

2002 35 9 8.57 7.72 0.85 3.2 2.5 3.8 69.6 0.0 22.6 1.4 2.8 3.6 10 

2002 222 16 9.12 8.33 0.79 4.9 3.5 5.1 78.2 0.0 16.4 1.1 1.6 2.7 11 

2002 28 3 8.59 7.82 0.77 3.4 2.7 4.0 71.3 0.0 21.3 1.3 2.5 3.6 12 

2002 107 97 8.32 7.60 0.72 2.8 2.3 3.6 67.3 0.0 24.2 1.5 2.9 4.1 13 

2002 207 9 8.90 8.21 0.69 4.5 3.3 4.9 76.8 0.0 17.4 1.1 1.7 3.0 14 

2002 85 97 8.24 7.67 0.57 3.0 2.5 3.7 68.7 0.0 23.2 1.5 2.7 3.9 15 

2002 323 3 8.43 7.87 0.55 3.6 2.8 4.1 72.1 0.0 20.6 1.3 2.5 3.4 16 

2002 105 8 8.13 7.60 0.53 2.8 2.3 3.6 67.6 0.0 24.3 1.5 2.7 3.9 17 

2002 191 16 8.72 8.21 0.51 4.5 3.3 4.9 77.1 0.0 17.4 1.1 1.5 2.9 18 

2002 128 3 8.37 7.87 0.50 3.6 2.8 4.1 72.0 0.0 20.6 1.4 2.5 3.5 19 

2002 106 8 8.08 7.60 0.48 2.8 2.3 3.6 67.2 0.0 24.2 1.6 3.0 4.1 20 

 

2003 271 3 9.29 8.33 0.96 4.9 3.5 5.1 78.0 0.0 16.3 1.1 1.8 2.7 1 

2003 270 1 9.28 8.33 0.95 4.9 3.5 5.1 78.0 0.0 16.3 1.1 1.9 2.8 2 

2003 178 3 8.79 8.10 0.69 4.2 3.2 4.6 75.2 0.0 18.2 1.2 2.4 3.1 3 

2003 356 16 8.61 7.94 0.67 3.8 2.9 4.3 73.2 0.0 19.9 1.3 2.4 3.3 4 

2003 68 3 8.33 7.67 0.66 3.0 2.5 3.7 68.4 0.0 23.1 1.5 3.0 4.0 5 

2003 246 3 8.98 8.33 0.65 4.9 3.5 5.1 78.0 0.0 16.3 1.1 1.7 2.9 6 

2003 107 1 8.23 7.60 0.63 2.8 2.3 3.6 67.4 0.0 24.3 1.6 2.7 4.1 7 

2003 163 3 8.69 8.10 0.59 4.2 3.2 4.6 75.5 0.0 18.2 1.2 2.0 3.1 8 

2003 164 97 8.69 8.10 0.58 4.2 3.2 4.6 75.4 0.0 18.3 1.2 2.0 3.1 9 

2003 187 3 8.79 8.21 0.58 4.5 3.3 4.9 76.4 0.0 17.3 1.1 2.2 2.9 10 

2003 35 10 8.25 7.72 0.53 3.2 2.5 3.8 69.6 0.0 22.6 1.5 2.5 3.8 11 

2003 242 16 8.84 8.33 0.51 4.9 3.5 5.1 78.2 0.0 16.3 1.0 1.7 2.7 12 

2003 160 3 8.60 8.10 0.50 4.2 3.2 4.6 75.0 0.0 18.1 1.3 2.4 3.1 13 

2003 326 1 8.36 7.87 0.49 3.6 2.8 4.1 71.9 0.0 20.6 1.3 2.7 3.5 14 

2003 247 97 8.81 8.33 0.48 4.9 3.5 5.1 78.3 0.0 16.4 1.1 1.4 2.8 15 

2003 304 1 8.56 8.10 0.46 4.2 3.2 4.6 75.4 0.0 18.3 1.2 2.2 3.0 16 

2003 108 3 8.06 7.60 0.45 2.8 2.3 3.6 67.3 0.0 24.2 1.6 2.8 4.1 17 

2003 259 3 8.78 8.33 0.45 4.9 3.5 5.1 77.7 0.0 16.3 1.1 2.1 2.8 18 

2003 197 9 8.65 8.21 0.44 4.5 3.3 4.9 76.6 0.0 17.4 1.1 2.2 2.8 19 

2003 166 46 8.54 8.10 0.44 4.2 3.2 4.6 75.3 0.0 18.2 1.2 2.1 3.1 20 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 25 Days Over 3 Years) 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.31 7.94 1.37 3.8 2.9 4.3 73.1 0.0 19.9 1.3 2.4 3.3 1 

2002 224 3 9.67 8.33 1.33 4.9 3.5 5.1 77.9 0.0 16.3 1.1 2.0 2.7 2 

2002 15 16 9.07 7.82 1.26 3.4 2.7 4.0 71.4 0.0 21.4 1.3 2.4 3.5 3 

2002 227 8 9.52 8.33 1.19 4.9 3.5 5.1 78.0 0.0 16.3 1.1 1.9 2.7 4 

2002 365 16 9.08 7.94 1.15 3.8 2.9 4.3 73.0 0.0 19.9 1.3 2.4 3.4 5 

2002 67 3 8.72 7.67 1.05 3.0 2.5 3.7 68.7 0.0 23.2 1.5 2.7 3.9 6 

2002 228 97 9.33 8.33 1.00 4.9 3.5 5.1 78.0 0.0 16.3 1.1 1.9 2.7 7 

2001 113 1 8.60 7.60 0.99 2.8 2.3 3.6 67.2 0.0 24.2 1.6 3.0 4.0 8 

2002 230 3 9.31 8.33 0.98 4.9 3.5 5.1 77.8 0.0 16.3 1.1 2.0 2.8 9 

2003 271 3 9.29 8.33 0.96 4.9 3.5 5.1 78.0 0.0 16.3 1.1 1.8 2.7 10 

2003 270 1 9.28 8.33 0.95 4.9 3.5 5.1 78.0 0.0 16.3 1.1 1.9 2.8 11 

2002 226 97 9.28 8.33 0.94 4.9 3.5 5.1 77.9 0.0 16.3 1.1 2.0 2.7 12 

2001 225 3 9.27 8.33 0.94 4.9 3.5 5.1 77.9 0.0 16.3 1.1 2.0 2.7 13 

2002 314 2 8.76 7.87 0.89 3.6 2.8 4.1 72.1 0.0 20.6 1.3 2.6 3.5 14 

2001 297 3 8.97 8.10 0.87 4.2 3.2 4.6 75.4 0.0 18.2 1.2 2.1 3.1 15 

2002 35 9 8.57 7.72 0.85 3.2 2.5 3.8 69.6 0.0 22.6 1.4 2.8 3.6 16 

2001 114 4 8.43 7.60 0.82 2.8 2.3 3.6 67.5 0.0 24.3 1.6 2.6 4.0 17 

2002 222 16 9.12 8.33 0.79 4.9 3.5 5.1 78.2 0.0 16.4 1.1 1.6 2.7 18 

2002 28 3 8.59 7.82 0.77 3.4 2.7 4.0 71.3 0.0 21.3 1.3 2.5 3.6 19 

2001 279 1 8.87 8.10 0.77 4.2 3.2 4.6 75.4 0.0 18.3 1.1 2.2 3.0 20 

2001 220 54 9.10 8.33 0.76 4.9 3.5 5.1 77.9 0.0 16.3 1.1 1.9 2.8 21 

2001 111 16 8.34 7.60 0.74 2.8 2.3 3.6 67.5 0.0 24.2 1.6 2.7 4.0 22 

2002 107 97 8.32 7.60 0.72 2.8 2.3 3.6 67.3 0.0 24.2 1.5 2.9 4.1 23 

2003 178 3 8.79 8.10 0.69 4.2 3.2 4.6 75.2 0.0 18.2 1.2 2.4 3.1 24 

2002 207 9 8.90 8.21 0.69 4.5 3.3 4.9 76.8 0.0 17.4 1.1 1.7 3.0 25 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for GSM (Top 20 Days Each Year) 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 112 396 7.97 7.57 0.40 2.8 2.3 3.5 67.3 0.0 25.0 1.7 1.9 4.2 1 

2001 98 350 7.96 7.57 0.39 2.8 2.3 3.5 67.0 0.0 24.9 1.6 2.4 4.1 2 

2001 208 361 8.48 8.10 0.38 4.2 3.2 4.6 75.9 0.0 18.4 1.2 1.4 3.2 3 

2001 113 609 7.89 7.57 0.32 2.8 2.3 3.5 67.3 0.0 25.0 1.7 1.8 4.2 4 

2001 111 371 7.88 7.57 0.31 2.8 2.3 3.5 67.5 0.0 25.0 1.5 1.8 4.1 5 

2001 341 606 8.17 7.87 0.30 3.6 2.8 4.1 72.9 0.0 20.8 1.4 1.4 3.5 6 

2001 331 363 8.10 7.82 0.29 3.4 2.7 4.0 71.2 0.0 21.3 1.5 2.3 3.7 7 

2001 297 514 8.39 8.10 0.28 4.2 3.2 4.6 76.0 0.0 18.5 1.3 1.1 3.2 8 

2001 279 514 8.37 8.10 0.27 4.2 3.2 4.6 75.9 0.0 18.4 1.2 1.5 3.1 9 

2001 343 609 8.11 7.87 0.24 3.6 2.8 4.1 72.7 0.0 20.8 1.3 1.7 3.5 10 

2001 198 381 8.34 8.10 0.23 4.2 3.2 4.6 76.0 0.0 18.4 1.2 1.4 3.1 11 

2001 199 435 8.33 8.10 0.22 4.2 3.2 4.6 76.1 0.0 18.5 1.2 1.2 3.0 12 

2001 298 364 8.31 8.10 0.21 4.2 3.2 4.6 75.9 0.0 18.4 1.3 1.3 3.2 13 

2001 143 364 7.97 7.76 0.21 3.3 2.6 4.0 70.9 0.0 22.1 1.4 1.8 3.8 14 

2001 225 606 8.41 8.21 0.20 4.5 3.3 4.9 77.1 0.0 17.4 1.1 1.3 3.1 15 

2001 263 371 8.54 8.33 0.20 4.9 3.5 5.1 78.2 0.0 16.4 1.1 1.5 2.8 16 

2001 141 435 7.95 7.76 0.19 3.3 2.6 4.0 70.6 0.0 22.1 1.5 2.0 3.8 17 

2001 102 710 7.75 7.57 0.18 2.8 2.3 3.5 67.2 0.0 25.0 1.6 2.1 4.2 18 

2001 158 475 8.27 8.10 0.17 4.2 3.2 4.6 75.6 0.0 18.4 1.1 1.8 3.2 19 

2001 239 814 8.37 8.21 0.16 4.5 3.3 4.9 77.1 0.0 17.4 1.1 1.4 3.0 20 

 

2002 129 354 8.30 7.73 0.57 3.3 2.6 4.0 70.4 0.0 22.1 1.5 2.3 3.7 1 

2002 228 609 8.67 8.17 0.50 4.5 3.3 4.9 77.2 0.0 17.4 1.1 1.3 2.9 2 

2002 107 474 7.89 7.54 0.35 2.8 2.3 3.5 67.1 0.0 25.0 1.6 2.0 4.2 3 

2002 67 474 7.93 7.61 0.33 2.9 2.4 3.6 68.9 0.0 24.0 1.6 1.6 3.9 4 

2002 106 351 7.86 7.54 0.31 2.8 2.3 3.5 66.8 0.0 24.8 1.7 2.6 4.1 5 

2002 31 371 8.08 7.78 0.30 3.4 2.7 4.0 71.6 0.0 21.4 1.4 1.9 3.7 6 

2002 226 434 8.43 8.17 0.26 4.5 3.3 4.9 77.0 0.0 17.4 1.2 1.5 2.9 7 

2002 85 514 7.84 7.61 0.23 2.9 2.4 3.6 68.9 0.0 24.0 1.5 1.7 3.9 8 

2002 66 363 7.83 7.61 0.23 2.9 2.4 3.6 68.5 0.0 23.9 1.5 2.1 4.0 9 

2002 230 609 8.40 8.17 0.22 4.5 3.3 4.9 77.2 0.0 17.4 1.2 1.4 2.8 10 

2002 356 349 8.02 7.84 0.18 3.6 2.8 4.1 72.4 0.0 20.8 1.3 2.0 3.5 11 

2002 224 435 8.35 8.17 0.18 4.5 3.3 4.9 76.9 0.0 17.4 1.2 1.5 2.9 12 

2002 128 341 7.90 7.73 0.16 3.3 2.6 4.0 71.0 0.0 22.1 1.4 1.7 3.7 13 

2002 93 434 7.70 7.54 0.16 2.8 2.3 3.5 67.3 0.0 24.9 1.5 2.1 4.2 14 

2002 28 562 7.94 7.78 0.16 3.4 2.7 4.0 71.8 0.0 21.4 1.5 1.8 3.5 15 

2002 229 574 8.32 8.17 0.15 4.5 3.3 4.9 77.0 0.0 17.4 1.2 1.5 3.0 16 

2002 330 513 7.93 7.78 0.15 3.4 2.7 4.0 71.2 0.0 21.4 1.2 2.5 3.7 17 

2002 324 763 7.93 7.78 0.15 3.4 2.7 4.0 72.1 0.0 21.7 1.2 1.6 3.4 18 

2002 225 429 8.32 8.17 0.15 4.5 3.3 4.9 77.5 0.0 17.4 1.2 0.9 3.0 19 

2002 164 340 8.21 8.07 0.15 4.2 3.2 4.6 75.8 0.0 18.4 1.2 1.5 3.1 20 

 

2003 304 351 8.45 8.07 0.38 4.2 3.2 4.6 75.7 0.0 18.3 1.2 1.8 3.0 1 

2003 327 475 8.10 7.78 0.32 3.4 2.7 4.0 71.6 0.0 21.4 1.3 2.2 3.5 2 

2003 246 474 8.59 8.30 0.30 4.9 3.5 5.1 78.2 0.0 16.3 1.0 1.6 2.8 3 

2003 247 423 8.56 8.30 0.27 4.9 3.5 5.1 78.3 0.0 16.3 1.2 1.5 2.8 4 

2003 163 356 8.33 8.07 0.26 4.2 3.2 4.6 75.7 0.0 18.4 1.2 1.7 3.1 5 

2003 178 353 8.30 8.07 0.23 4.2 3.2 4.6 75.5 0.0 18.2 1.2 2.0 3.1 6 

2003 165 373 8.29 8.07 0.23 4.2 3.2 4.6 75.2 0.0 18.2 1.2 2.2 3.2 7 

2003 6 367 8.01 7.78 0.23 3.4 2.7 4.0 71.2 0.0 21.4 1.4 2.3 3.7 8 

2003 35 372 7.85 7.64 0.21 3.0 2.5 3.7 69.5 0.0 23.5 1.6 1.6 3.9 9 

2003 188 353 8.27 8.07 0.21 4.2 3.2 4.6 75.8 0.0 18.3 1.1 1.7 3.1 10 

2003 187 340 8.27 8.07 0.21 4.2 3.2 4.6 76.0 0.0 18.4 1.1 1.5 3.1 11 

2003 85 350 7.81 7.61 0.20 2.9 2.4 3.6 68.3 0.0 23.9 1.7 2.1 4.0 12 

2003 320 513 7.96 7.78 0.17 3.4 2.7 4.0 71.7 0.0 21.5 1.3 1.6 3.8 13 

2003 68 366 7.78 7.61 0.17 2.9 2.4 3.6 68.3 0.0 23.9 1.7 1.9 4.1 14 

2003 156 341 8.24 8.07 0.17 4.2 3.2 4.6 75.4 0.0 18.3 1.3 1.8 3.1 15 

2003 321 346 7.95 7.78 0.16 3.4 2.7 4.0 71.7 0.0 21.4 1.5 2.0 3.5 16 

2003 235 558 8.32 8.17 0.15 4.5 3.3 4.9 77.1 0.0 17.4 1.2 1.5 2.9 17 

2003 240 322 8.32 8.17 0.15 4.5 3.3 4.9 77.2 0.0 17.4 1.2 1.2 3.0 18 

2003 164 514 8.21 8.07 0.14 4.2 3.2 4.6 75.9 0.0 18.3 1.3 1.3 3.2 19 

2003 166 609 8.21 8.07 0.14 4.2 3.2 4.6 75.5 0.0 18.4 1.3 1.6 3.2 20 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for GSM (Top 25 Days Over 3 Years) 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2002 129 354 8.30 7.73 0.57 3.3 2.6 4.0 70.4 0.0 22.1 1.5 2.3 3.7 1 

2002 228 609 8.67 8.17 0.50 4.5 3.3 4.9 77.2 0.0 17.4 1.1 1.3 2.9 2 

2001 112 396 7.97 7.57 0.40 2.8 2.3 3.5 67.3 0.0 25.0 1.7 1.9 4.2 3 

2001 98 350 7.96 7.57 0.39 2.8 2.3 3.5 67.0 0.0 24.9 1.6 2.4 4.1 4 

2003 304 351 8.45 8.07 0.38 4.2 3.2 4.6 75.7 0.0 18.3 1.2 1.8 3.0 5 

2001 208 361 8.48 8.10 0.38 4.2 3.2 4.6 75.9 0.0 18.4 1.2 1.4 3.2 6 

2002 107 474 7.89 7.54 0.35 2.8 2.3 3.5 67.1 0.0 25.0 1.6 2.0 4.2 7 

2002 67 474 7.93 7.61 0.33 2.9 2.4 3.6 68.9 0.0 24.0 1.6 1.6 3.9 8 

2003 327 475 8.10 7.78 0.32 3.4 2.7 4.0 71.6 0.0 21.4 1.3 2.2 3.5 9 

2001 113 609 7.89 7.57 0.32 2.8 2.3 3.5 67.3 0.0 25.0 1.7 1.8 4.2 10 

2002 106 351 7.86 7.54 0.31 2.8 2.3 3.5 66.8 0.0 24.8 1.7 2.6 4.1 11 

2001 111 371 7.88 7.57 0.31 2.8 2.3 3.5 67.5 0.0 25.0 1.5 1.8 4.1 12 

2001 341 606 8.17 7.87 0.30 3.6 2.8 4.1 72.9 0.0 20.8 1.4 1.4 3.5 13 

2002 31 371 8.08 7.78 0.30 3.4 2.7 4.0 71.6 0.0 21.4 1.4 1.9 3.7 14 

2003 246 474 8.59 8.30 0.30 4.9 3.5 5.1 78.2 0.0 16.3 1.0 1.6 2.8 15 

2001 331 363 8.10 7.82 0.29 3.4 2.7 4.0 71.2 0.0 21.3 1.5 2.3 3.7 16 

2001 297 514 8.39 8.10 0.28 4.2 3.2 4.6 76.0 0.0 18.5 1.3 1.1 3.2 17 

2001 279 514 8.37 8.10 0.27 4.2 3.2 4.6 75.9 0.0 18.4 1.2 1.5 3.1 18 

2003 247 423 8.56 8.30 0.27 4.9 3.5 5.1 78.3 0.0 16.3 1.2 1.5 2.8 19 

2003 163 356 8.33 8.07 0.26 4.2 3.2 4.6 75.7 0.0 18.4 1.2 1.7 3.1 20 

2002 226 434 8.43 8.17 0.26 4.5 3.3 4.9 77.0 0.0 17.4 1.2 1.5 2.9 21 

2001 343 609 8.11 7.87 0.24 3.6 2.8 4.1 72.7 0.0 20.8 1.3 1.7 3.5 22 

2001 198 381 8.34 8.10 0.23 4.2 3.2 4.6 76.0 0.0 18.4 1.2 1.4 3.1 23 

2003 178 353 8.30 8.07 0.23 4.2 3.2 4.6 75.5 0.0 18.2 1.2 2.0 3.1 24 

2002 85 514 7.84 7.61 0.23 2.9 2.4 3.6 68.9 0.0 24.0 1.5 1.7 3.9 25 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Joyce-Kilmer (Top 20 Days Each Yr) 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 112 240 7.98 7.54 0.44 2.8 2.3 3.5 67.1 0.0 24.9 1.6 2.2 4.2 1 

2001 98 225 7.94 7.54 0.40 2.8 2.3 3.5 66.7 0.0 24.8 1.7 2.6 4.2 2 

2001 113 317 7.89 7.54 0.34 2.8 2.3 3.5 67.3 0.0 25.0 1.7 1.9 4.1 3 

2001 111 225 7.87 7.54 0.33 2.8 2.3 3.5 67.2 0.0 24.9 1.6 2.0 4.2 4 

2001 279 278 8.39 8.07 0.33 4.2 3.2 4.6 75.9 0.0 18.3 1.1 1.6 3.0 5 

2001 297 310 8.39 8.07 0.32 4.2 3.2 4.6 76.1 0.0 18.4 1.2 1.2 3.1 6 

2001 343 310 8.22 7.90 0.31 3.8 2.9 4.3 73.4 0.0 20.0 1.3 1.9 3.4 7 

2001 198 226 8.44 8.17 0.27 4.5 3.3 4.9 77.2 0.0 17.4 1.2 1.3 3.0 8 

2001 341 317 8.17 7.90 0.27 3.8 2.9 4.3 74.0 0.0 20.1 1.2 1.4 3.3 9 

2001 208 225 8.43 8.17 0.26 4.5 3.3 4.9 76.9 0.0 17.3 1.2 1.5 3.0 10 

2001 263 221 8.55 8.30 0.26 4.9 3.5 5.1 78.4 0.0 16.3 1.0 1.5 2.7 11 

2001 199 278 8.42 8.17 0.25 4.5 3.3 4.9 77.3 0.0 17.5 1.1 1.3 2.9 12 

2001 225 278 8.54 8.30 0.24 4.9 3.5 5.1 78.3 0.0 16.3 1.1 1.5 2.7 13 

2001 331 225 8.00 7.78 0.22 3.4 2.7 4.0 71.3 0.0 21.2 1.5 2.4 3.6 14 

2001 141 221 8.00 7.78 0.21 3.4 2.7 4.0 71.4 0.0 21.4 1.3 2.2 3.7 15 

2001 298 225 8.28 8.07 0.21 4.2 3.2 4.6 76.0 0.0 18.4 1.1 1.5 3.0 16 

2001 332 239 7.98 7.78 0.19 3.4 2.7 4.0 71.3 0.0 21.4 1.5 2.2 3.6 17 

2001 158 310 8.25 8.07 0.19 4.2 3.2 4.6 75.5 0.0 18.4 1.2 2.0 2.9 18 

2001 12 286 7.96 7.78 0.18 3.4 2.7 4.0 72.1 0.0 21.6 1.3 1.3 3.7 19 

2001 239 221 8.46 8.30 0.17 4.9 3.5 5.1 78.6 0.0 16.4 1.1 1.1 2.9 20 

 

2002 228 317 8.85 8.30 0.56 4.9 3.5 5.1 78.4 0.0 16.4 1.1 1.3 2.7 1 

2002 129 225 8.28 7.78 0.49 3.4 2.7 4.0 71.3 0.0 21.3 1.4 2.4 3.6 2 

2002 107 286 7.95 7.54 0.41 2.8 2.3 3.5 67.1 0.0 24.9 1.6 2.2 4.2 3 

2002 67 278 8.00 7.61 0.39 2.9 2.4 3.6 68.6 0.0 24.0 1.6 1.8 4.0 4 

2002 226 239 8.68 8.30 0.38 4.9 3.5 5.1 78.3 0.0 16.3 1.0 1.6 2.8 5 

2002 31 221 8.14 7.78 0.35 3.4 2.7 4.0 71.4 0.0 21.4 1.4 2.1 3.7 6 

2002 224 226 8.61 8.30 0.32 4.9 3.5 5.1 78.3 0.0 16.4 1.1 1.5 2.8 7 

2002 106 225 7.85 7.54 0.31 2.8 2.3 3.5 66.9 0.0 24.8 1.5 2.6 4.1 8 

2002 230 310 8.54 8.30 0.24 4.9 3.5 5.1 78.4 0.0 16.4 1.1 1.4 2.7 9 

2002 35 221 7.93 7.69 0.24 3.2 2.5 3.8 69.2 0.0 22.5 1.5 2.7 4.1 10 

2002 85 317 7.84 7.61 0.23 2.9 2.4 3.6 68.8 0.0 24.0 1.6 1.6 3.9 11 

2002 28 278 8.00 7.78 0.21 3.4 2.7 4.0 71.9 0.0 21.4 1.3 2.0 3.5 12 

2002 164 222 8.27 8.07 0.20 4.2 3.2 4.6 75.7 0.0 18.4 1.1 1.6 3.2 13 

2002 128 226 7.97 7.78 0.18 3.4 2.7 4.0 71.7 0.0 21.4 1.3 2.0 3.5 14 

2002 330 222 7.97 7.78 0.18 3.4 2.7 4.0 71.3 0.0 21.3 1.3 2.6 3.6 15 

2002 356 225 8.09 7.90 0.18 3.8 2.9 4.3 73.2 0.0 19.9 1.3 2.3 3.3 16 

2002 225 239 8.47 8.30 0.18 4.9 3.5 5.1 79.0 0.0 16.5 1.0 0.8 2.8 17 

2002 138 270 7.95 7.78 0.16 3.4 2.7 4.0 72.0 0.0 21.6 1.4 1.4 3.5 19 

2002 93 278 7.71 7.54 0.16 2.8 2.3 3.5 66.9 0.0 24.9 1.8 2.3 4.1 18 

2002 66 225 7.77 7.61 0.16 2.9 2.4 3.6 68.4 0.0 23.8 1.5 2.1 4.2 20 

 

2003 246 270 8.63 8.30 0.34 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.7 2.7 1 

2003 327 310 8.12 7.78 0.34 3.4 2.7 4.0 71.4 0.0 21.3 1.4 2.3 3.6 2 

2003 304 225 8.38 8.07 0.31 4.2 3.2 4.6 75.7 0.0 18.3 1.1 1.9 3.0 3 

2003 247 241 8.60 8.30 0.31 4.9 3.5 5.1 78.4 0.0 16.4 1.1 1.3 2.8 4 

2003 165 225 8.37 8.07 0.31 4.2 3.2 4.6 75.3 0.0 18.3 1.2 2.2 3.1 5 

2003 187 241 8.47 8.17 0.30 4.5 3.3 4.9 76.8 0.0 17.3 1.2 1.8 2.9 6 

2003 178 221 8.34 8.07 0.27 4.2 3.2 4.6 75.4 0.0 18.2 1.2 2.1 3.1 7 

2003 6 239 8.03 7.78 0.25 3.4 2.7 4.0 71.0 0.0 21.3 1.5 2.4 3.7 8 

2003 68 221 7.84 7.61 0.23 2.9 2.4 3.6 68.2 0.0 23.8 1.6 2.2 4.1 9 

2003 188 222 8.40 8.17 0.23 4.5 3.3 4.9 76.8 0.0 17.4 1.2 1.8 2.9 10 

2003 85 225 7.83 7.61 0.22 2.9 2.4 3.6 68.6 0.0 23.9 1.5 1.9 4.1 11 

2003 35 225 7.91 7.69 0.22 3.2 2.5 3.8 69.9 0.0 22.8 1.5 1.9 3.9 12 

2003 156 221 8.28 8.07 0.21 4.2 3.2 4.6 75.5 0.0 18.3 1.3 1.9 3.0 13 

2003 163 225 8.25 8.07 0.18 4.2 3.2 4.6 75.8 0.0 18.3 1.2 1.7 3.0 14 

2003 321 225 7.96 7.78 0.18 3.4 2.7 4.0 71.6 0.0 21.3 1.3 2.1 3.7 15 

2003 52 223 7.86 7.69 0.18 3.2 2.5 3.8 69.8 0.0 22.7 1.3 2.4 3.8 16 

2003 240 225 8.47 8.30 0.17 4.9 3.5 5.1 78.6 0.0 16.5 1.0 1.0 2.9 17 

2003 357 222 8.07 7.90 0.17 3.8 2.9 4.3 73.6 0.0 19.9 1.4 1.6 3.5 18 

2003 235 317 8.46 8.30 0.16 4.9 3.5 5.1 78.5 0.0 16.3 1.1 1.4 2.7 19 

2003 291 240 8.23 8.07 0.16 4.2 3.2 4.6 75.3 0.0 18.2 1.1 2.0 3.4 20 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Joyce-Kil (Top 25 Days Over 3 Yrs) 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2002 228 317 8.85 8.30 0.56 4.9 3.5 5.1 78.4 0.0 16.4 1.1 1.3 2.7 1 

2002 129 225 8.28 7.78 0.49 3.4 2.7 4.0 71.3 0.0 21.3 1.4 2.4 3.6 2 

2001 112 240 7.98 7.54 0.44 2.8 2.3 3.5 67.1 0.0 24.9 1.6 2.2 4.2 3 

2002 107 286 7.95 7.54 0.41 2.8 2.3 3.5 67.1 0.0 24.9 1.6 2.2 4.2 4 

2001 98 225 7.94 7.54 0.40 2.8 2.3 3.5 66.7 0.0 24.8 1.7 2.6 4.2 5 

2002 67 278 8.00 7.61 0.39 2.9 2.4 3.6 68.6 0.0 24.0 1.6 1.8 4.0 6 

2002 226 239 8.68 8.30 0.38 4.9 3.5 5.1 78.3 0.0 16.3 1.0 1.6 2.8 7 

2002 31 221 8.14 7.78 0.35 3.4 2.7 4.0 71.4 0.0 21.4 1.4 2.1 3.7 8 

2001 113 317 7.89 7.54 0.34 2.8 2.3 3.5 67.3 0.0 25.0 1.7 1.9 4.1 9 

2003 246 270 8.63 8.30 0.34 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.7 2.7 10 

2003 327 310 8.12 7.78 0.34 3.4 2.7 4.0 71.4 0.0 21.3 1.4 2.3 3.6 11 

2001 111 225 7.87 7.54 0.33 2.8 2.3 3.5 67.2 0.0 24.9 1.6 2.0 4.2 12 

2001 279 278 8.39 8.07 0.33 4.2 3.2 4.6 75.9 0.0 18.3 1.1 1.6 3.0 13 

2001 297 310 8.39 8.07 0.32 4.2 3.2 4.6 76.1 0.0 18.4 1.2 1.2 3.1 14 

2002 224 226 8.61 8.30 0.32 4.9 3.5 5.1 78.3 0.0 16.4 1.1 1.5 2.8 15 

2003 304 225 8.38 8.07 0.31 4.2 3.2 4.6 75.7 0.0 18.3 1.1 1.9 3.0 16 

2001 343 310 8.22 7.90 0.31 3.8 2.9 4.3 73.4 0.0 20.0 1.3 1.9 3.4 17 

2002 106 225 7.85 7.54 0.31 2.8 2.3 3.5 66.9 0.0 24.8 1.5 2.6 4.1 18 

2003 247 241 8.60 8.30 0.31 4.9 3.5 5.1 78.4 0.0 16.4 1.1 1.3 2.8 19 

2003 165 225 8.37 8.07 0.31 4.2 3.2 4.6 75.3 0.0 18.3 1.2 2.2 3.1 20 

2003 187 241 8.47 8.17 0.30 4.5 3.3 4.9 76.8 0.0 17.3 1.2 1.8 2.9 21 

2003 178 221 8.34 8.07 0.27 4.2 3.2 4.6 75.4 0.0 18.2 1.2 2.1 3.1 22 

2001 198 226 8.44 8.17 0.27 4.5 3.3 4.9 77.2 0.0 17.4 1.2 1.3 3.0 23 

2001 341 317 8.17 7.90 0.27 3.8 2.9 4.3 74.0 0.0 20.1 1.2 1.4 3.3 24 

2001 208 225 8.43 8.17 0.26 4.5 3.3 4.9 76.9 0.0 17.3 1.2 1.5 3.0 25 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Shining Rk (Top 20 Days Each Yr) 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 298 1265 7.89 7.65 0.24 4.2 3.2 4.6 76.0 0.0 18.4 1.2 1.3 3.1 1 

2001 331 1207 7.59 7.35 0.24 3.4 2.7 4.0 71.5 0.0 21.4 1.4 2.2 3.4 2 

2001 102 1265 7.32 7.09 0.23 2.8 2.3 3.5 67.1 0.0 25.0 1.5 2.2 4.1 3 

2001 279 1266 7.84 7.65 0.19 4.2 3.2 4.6 75.5 0.0 18.2 1.2 1.9 3.1 4 

2001 208 1313 7.94 7.76 0.19 4.5 3.3 4.9 77.7 0.0 17.5 1.0 0.7 3.0 5 

2001 342 1208 7.59 7.41 0.18 3.6 2.8 4.1 72.6 0.0 20.8 1.3 1.8 3.4 6 

2001 52 1210 7.37 7.20 0.17 3.0 2.5 3.7 69.3 0.0 23.3 1.4 2.0 4.0 7 

2001 330 1308 7.52 7.35 0.17 3.4 2.7 4.0 71.6 0.0 21.3 1.4 2.0 3.7 8 

2001 148 1210 7.57 7.41 0.17 3.6 2.8 4.1 72.6 0.0 20.8 1.4 1.7 3.5 9 

2001 199 1265 7.89 7.76 0.13 4.5 3.3 4.9 77.8 0.0 17.6 1.1 0.7 2.8 10 

2001 156 1265 7.77 7.65 0.12 4.2 3.2 4.6 75.9 0.0 18.4 1.1 1.5 3.1 11 

2001 209 1305 7.88 7.76 0.12 4.5 3.3 4.9 76.6 0.0 17.3 1.2 1.9 3.1 12 

2001 173 1216 7.76 7.65 0.12 4.2 3.2 4.6 76.2 0.0 18.5 1.2 0.8 3.3 13 

2001 149 1266 7.51 7.41 0.11 3.6 2.8 4.1 72.0 0.0 20.7 1.4 2.3 3.6 14 

2001 48 1313 7.30 7.20 0.10 3.0 2.5 3.7 69.6 0.0 23.7 1.5 1.5 3.9 15 

2001 98 1210 7.19 7.09 0.10 2.8 2.3 3.5 67.7 0.0 25.2 1.5 1.5 4.1 17 

2001 343 1302 7.50 7.41 0.10 3.6 2.8 4.1 72.0 0.0 20.5 1.5 2.5 3.5 18 

2001 224 1210 8.15 8.05 0.10 5.4 3.8 5.4 80.4 0.0 15.5 0.9 0.5 2.7 16 

2001 198 1265 7.85 7.76 0.09 4.5 3.3 4.9 77.4 0.0 17.6 1.0 1.0 3.0 19 

2001 210 1277 7.85 7.76 0.09 4.5 3.3 4.9 77.0 0.0 17.4 1.0 1.5 3.1 20 

 

2002 330 1228 7.61 7.35 0.26 3.4 2.7 4.0 71.4 0.0 21.3 1.5 2.2 3.7 1 

2002 29 1210 7.61 7.35 0.26 3.4 2.7 4.0 72.2 0.0 21.6 1.3 1.3 3.6 2 

2002 129 1313 7.57 7.41 0.16 3.6 2.8 4.1 73.0 0.0 20.8 1.5 1.2 3.5 3 

2002 147 1216 7.57 7.41 0.16 3.6 2.8 4.1 72.4 0.0 20.8 1.5 1.8 3.5 4 

2002 66 1302 7.32 7.16 0.16 2.9 2.4 3.6 68.2 0.0 23.8 1.5 2.5 4.0 5 

2002 31 1235 7.49 7.35 0.14 3.4 2.7 4.0 71.6 0.0 21.3 1.4 2.0 3.7 6 

2002 35 1206 7.34 7.20 0.14 3.0 2.5 3.7 69.3 0.0 23.4 1.4 2.1 3.9 7 

2002 84 1210 7.28 7.16 0.12 2.9 2.4 3.6 68.4 0.0 24.0 1.7 1.7 4.2 8 

2002 77 1210 7.27 7.16 0.11 2.9 2.4 3.6 68.6 0.0 24.1 1.4 1.8 4.1 9 

2002 75 1210 7.24 7.16 0.08 2.9 2.4 3.6 68.2 0.0 23.8 1.8 1.8 4.3 10 

2002 145 1210 7.49 7.41 0.08 3.6 2.8 4.1 72.5 0.0 20.9 1.2 1.8 3.6 11 

2002 165 1206 7.72 7.65 0.08 4.2 3.2 4.6 76.1 0.0 18.3 1.2 1.2 3.1 12 

2002 225 1265 8.12 8.05 0.07 5.4 3.8 5.4 80.3 0.0 15.5 1.2 0.6 2.4 13 

2002 178 1265 7.72 7.65 0.07 4.2 3.2 4.6 75.7 0.0 18.4 1.3 1.3 3.3 14 

2002 67 1308 7.23 7.16 0.07 2.9 2.4 3.6 68.9 0.0 23.8 1.5 2.2 3.7 15 

2002 164 1265 7.70 7.65 0.06 4.2 3.2 4.6 76.6 0.0 18.5 0.8 0.8 3.3 17 

2002 134 1210 7.46 7.41 0.06 3.6 2.8 4.1 73.0 0.0 21.2 1.7 0.8 3.3 16 

2002 192 1210 7.81 7.76 0.06 4.5 3.3 4.9 77.4 0.0 17.7 0.8 0.8 3.3 18 

2002 229 1300 8.10 8.05 0.05 5.4 3.8 5.4 80.3 0.0 15.4 0.9 0.9 2.6 19 

2002 226 1313 8.10 8.05 0.05 5.4 3.8 5.4 80.3 0.0 15.4 0.9 0.9 2.6 20 

 

2003 85 1212 7.42 7.16 0.26 2.9 2.4 3.6 68.3 0.0 23.8 1.6 2.3 4.1 1 

2003 343 1212 7.66 7.41 0.25 3.6 2.8 4.1 72.2 0.0 20.6 1.3 2.5 3.4 2 

2003 35 1211 7.45 7.20 0.25 3.0 2.5 3.7 69.2 0.0 23.4 1.6 1.9 3.9 3 

2003 357 1210 7.62 7.41 0.21 3.6 2.8 4.1 72.1 0.0 20.7 1.4 2.3 3.6 4 

2003 178 1251 7.85 7.65 0.20 4.2 3.2 4.6 76.4 0.0 18.5 1.2 0.9 3.0 5 

2003 247 1266 8.09 7.89 0.20 4.9 3.5 5.1 78.4 0.0 16.4 1.1 1.4 2.8 6 

2003 52 1206 7.38 7.20 0.19 3.0 2.5 3.7 68.9 0.0 23.3 1.6 2.1 4.0 7 

2003 356 1208 7.59 7.41 0.18 3.6 2.8 4.1 72.2 0.0 20.6 1.3 2.4 3.5 8 

2003 188 1206 7.93 7.76 0.18 4.5 3.3 4.9 77.3 0.0 17.5 1.0 1.3 2.9 9 

2003 327 1206 7.51 7.35 0.17 3.4 2.7 4.0 71.5 0.0 21.5 1.5 2.0 3.5 10 

2003 240 1211 8.21 8.05 0.16 5.4 3.8 5.4 80.3 0.0 15.3 1.1 0.8 2.5 11 

2003 320 1266 7.49 7.35 0.15 3.4 2.7 4.0 71.6 0.0 21.4 1.3 2.0 3.7 12 

2003 130 1210 7.54 7.41 0.13 3.6 2.8 4.1 72.2 0.0 20.6 1.5 2.2 3.6 13 

2003 316 1209 7.47 7.35 0.12 3.4 2.7 4.0 71.9 0.0 21.6 1.2 1.6 3.7 14 

2003 72 1208 7.28 7.16 0.12 2.9 2.4 3.6 68.1 0.0 23.9 1.7 2.5 3.8 15 

2003 166 1314 7.76 7.65 0.12 4.2 3.2 4.6 76.3 0.0 18.4 1.2 1.2 2.9 16 

2003 344 1312 7.52 7.41 0.11 3.6 2.8 4.1 73.0 0.0 20.7 1.3 1.7 3.4 17 

2003 160 1206 7.76 7.65 0.11 4.2 3.2 4.6 75.9 0.0 18.2 1.3 1.7 2.9 18 

2003 58 1252 7.30 7.20 0.10 3.0 2.5 3.7 69.0 0.0 23.3 1.4 2.4 3.8 19 

2003 291 1214 7.75 7.65 0.10 4.2 3.2 4.6 76.1 0.0 18.4 0.9 1.8 2.7 20 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change - Shining Rk (Top 25 Days Over 3 Yrs) 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2002 330 1228 7.61 7.35 0.26 3.4 2.7 4.0 71.4 0.0 21.3 1.5 2.2 3.7 1 

2002 29 1210 7.61 7.35 0.26 3.4 2.7 4.0 72.2 0.0 21.6 1.3 1.3 3.6 2 

2003 85 1212 7.42 7.16 0.26 2.9 2.4 3.6 68.3 0.0 23.8 1.6 2.3 4.1 3 

2003 343 1212 7.66 7.41 0.25 3.6 2.8 4.1 72.2 0.0 20.6 1.3 2.5 3.4 4 

2003 35 1211 7.45 7.20 0.25 3.0 2.5 3.7 69.2 0.0 23.4 1.6 1.9 3.9 5 

2001 298 1265 7.89 7.65 0.24 4.2 3.2 4.6 76.0 0.0 18.4 1.2 1.3 3.1 6 

2001 331 1207 7.59 7.35 0.24 3.4 2.7 4.0 71.5 0.0 21.4 1.4 2.2 3.4 7 

2001 102 1265 7.32 7.09 0.23 2.8 2.3 3.5 67.1 0.0 25.0 1.5 2.2 4.1 8 

2003 357 1210 7.62 7.41 0.21 3.6 2.8 4.1 72.1 0.0 20.7 1.4 2.3 3.6 9 

2003 178 1251 7.85 7.65 0.20 4.2 3.2 4.6 76.4 0.0 18.5 1.2 0.9 3.0 10 

2003 247 1266 8.09 7.89 0.20 4.9 3.5 5.1 78.4 0.0 16.4 1.1 1.4 2.8 11 

2001 279 1266 7.84 7.65 0.19 4.2 3.2 4.6 75.5 0.0 18.2 1.2 1.9 3.1 12 

2001 208 1313 7.94 7.76 0.19 4.5 3.3 4.9 77.7 0.0 17.5 1.0 0.7 3.0 13 

2003 52 1206 7.38 7.20 0.19 3.0 2.5 3.7 68.9 0.0 23.3 1.6 2.1 4.0 14 

2001 342 1208 7.59 7.41 0.18 3.6 2.8 4.1 72.6 0.0 20.8 1.3 1.8 3.4 15 

2003 356 1208 7.59 7.41 0.18 3.6 2.8 4.1 72.2 0.0 20.6 1.3 2.4 3.5 16 

2003 188 1206 7.93 7.76 0.18 4.5 3.3 4.9 77.3 0.0 17.5 1.0 1.3 2.9 17 

2001 52 1210 7.37 7.20 0.17 3.0 2.5 3.7 69.3 0.0 23.3 1.4 2.0 4.0 18 

2001 330 1308 7.52 7.35 0.17 3.4 2.7 4.0 71.6 0.0 21.3 1.4 2.0 3.7 19 

2001 148 1210 7.57 7.41 0.17 3.6 2.8 4.1 72.6 0.0 20.8 1.4 1.7 3.5 20 

2003 327 1206 7.51 7.35 0.17 3.4 2.7 4.0 71.5 0.0 21.5 1.5 2.0 3.5 21 

2003 240 1211 8.21 8.05 0.16 5.4 3.8 5.4 80.3 0.0 15.3 1.1 0.8 2.5 22 

2002 129 1313 7.57 7.41 0.16 3.6 2.8 4.1 73.0 0.0 20.8 1.5 1.2 3.5 23 

2002 147 1216 7.57 7.41 0.16 3.6 2.8 4.1 72.4 0.0 20.8 1.5 1.8 3.5 24 

2002 66 1302 7.32 7.16 0.16 2.9 2.4 3.6 68.2 0.0 23.8 1.5 2.5 4.0 25 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Sipsey (Top 20 Days Each Year) 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 259 1058 8.39 8.17 0.22 4.2 3.2 4.6 75.9 0.0 18.4 1.2 1.4 3.1 1 

2001 311 1165 8.01 7.88 0.13 3.4 2.7 4.0 71.6 0.0 21.3 1.4 2.1 3.6 2 

2001 164 1077 8.20 8.08 0.12 4.0 3.0 4.5 74.5 0.0 19.1 1.1 1.9 3.4 3 

2001 215 1205 8.28 8.17 0.11 4.2 3.2 4.6 76.2 0.0 18.5 1.2 0.8 3.2 4 

2001 273 1199 8.27 8.17 0.10 4.2 3.2 4.6 75.3 0.0 18.3 1.4 1.8 3.2 5 

2001 205 1058 8.27 8.17 0.10 4.2 3.2 4.6 75.6 0.0 18.3 1.4 1.4 3.3 6 

2001 216 1147 8.26 8.17 0.09 4.2 3.2 4.6 76.3 0.0 18.4 1.1 1.1 3.2 7 

2001 304 1129 8.16 8.08 0.08 4.0 3.0 4.5 75.0 0.0 19.2 1.2 1.2 3.5 8 

2001 170 1092 8.16 8.08 0.08 4.0 3.0 4.5 75.2 0.0 19.5 1.2 1.2 3.0 9 

2001 274 1201 8.24 8.17 0.07 4.2 3.2 4.6 75.3 0.0 18.3 1.3 1.9 3.2 10 

2001 120 1092 7.73 7.66 0.07 2.8 2.3 3.6 68.0 0.0 24.3 1.4 2.1 4.2 11 

2001 346 1205 8.00 7.94 0.06 3.6 2.8 4.1 72.3 0.0 20.4 1.5 2.2 3.7 12 

2001 213 1204 8.23 8.17 0.06 4.2 3.2 4.6 76.1 0.0 18.2 0.8 1.6 3.2 13 

2001 326 1129 7.93 7.88 0.05 3.4 2.7 4.0 71.5 0.0 21.2 1.8 1.8 3.7 14 

2001 43 1092 7.82 7.78 0.05 3.2 2.5 3.8 70.7 0.0 23.3 1.0 1.0 4.0 15 

2001 312 1092 7.92 7.88 0.04 3.4 2.7 4.0 72.5 0.0 21.7 1.2 1.2 3.5 16 

2001 320 1129 7.92 7.88 0.04 3.4 2.7 4.0 72.6 0.0 21.4 1.2 1.2 3.6 17 

2001 206 1147 8.21 8.17 0.04 4.2 3.2 4.6 76.0 0.0 18.1 1.2 1.2 3.5 18 

2001 89 1058 7.73 7.69 0.04 2.9 2.4 3.6 68.3 0.0 24.2 1.3 2.5 3.8 19 

2001 178 1204 8.12 8.08 0.04 4.0 3.0 4.5 74.9 0.0 19.0 1.2 1.2 3.7 20 

 

2002 3 1092 8.17 7.94 0.24 3.6 2.8 4.1 72.8 0.0 20.8 1.3 1.5 3.5 1 

2002 268 1092 8.39 8.17 0.22 4.2 3.2 4.6 75.7 0.0 18.3 1.2 1.6 3.1 2 

2002 241 1067 8.35 8.17 0.18 4.2 3.2 4.6 75.7 0.0 18.3 1.2 1.5 3.2 3 

2002 247 1147 8.32 8.17 0.15 4.2 3.2 4.6 76.0 0.0 18.5 1.2 1.2 3.1 4 

2002 220 1110 8.32 8.17 0.15 4.2 3.2 4.6 75.5 0.0 18.4 1.2 1.8 3.1 5 

2002 216 1065 8.31 8.17 0.13 4.2 3.2 4.6 75.7 0.0 18.3 1.3 1.7 3.0 6 

2002 245 1147 8.30 8.17 0.13 4.2 3.2 4.6 76.4 0.0 18.5 1.0 1.0 3.1 7 

2002 244 1147 8.29 8.17 0.12 4.2 3.2 4.6 76.1 0.0 18.5 1.2 1.2 3.1 8 

2002 170 1092 8.19 8.08 0.11 4.0 3.0 4.5 74.7 0.0 19.1 1.2 1.6 3.3 9 

2002 253 1065 8.28 8.17 0.11 4.2 3.2 4.6 76.3 0.0 18.3 1.2 1.2 2.9 10 

2002 242 1058 8.28 8.17 0.11 4.2 3.2 4.6 76.0 0.0 18.5 1.3 1.3 2.9 11 

2002 243 1092 8.27 8.17 0.10 4.2 3.2 4.6 75.9 0.0 18.4 1.3 1.3 3.1 12 

2002 240 1129 8.26 8.17 0.09 4.2 3.2 4.6 76.6 0.0 18.4 1.0 1.0 3.0 13 

2002 189 1147 8.23 8.17 0.06 4.2 3.2 4.6 75.2 0.0 18.3 1.4 2.1 2.9 14 

2002 273 1165 8.23 8.17 0.06 4.2 3.2 4.6 75.1 0.0 18.4 1.4 2.2 2.9 15 

2002 288 1093 8.14 8.08 0.05 4.0 3.0 4.5 74.4 0.0 19.4 0.9 1.8 3.6 16 

2002 344 1205 7.99 7.94 0.05 3.6 2.8 4.1 71.9 0.0 20.7 0.9 2.8 3.7 17 

2002 339 1205 7.98 7.94 0.04 3.6 2.8 4.1 73.1 0.0 20.8 1.0 2.1 3.1 18 

2002 234 1092 8.21 8.17 0.04 4.2 3.2 4.6 75.8 0.0 17.9 1.1 2.1 3.2 19 

2002 252 1065 8.21 8.17 0.04 4.2 3.2 4.6 76.2 0.0 18.4 1.1 1.1 3.2 20 

 

2003 251 1148 8.48 8.17 0.31 4.2 3.2 4.6 76.1 0.0 18.4 1.2 1.2 3.2 1 

2003 314 1058 8.11 7.88 0.23 3.4 2.7 4.0 71.8 0.0 21.6 1.4 1.6 3.6 3 

2003 282 1067 8.32 8.08 0.23 4.0 3.0 4.5 74.3 0.0 19.1 1.4 2.0 3.3 2 

2003 308 1147 8.07 7.88 0.19 3.4 2.7 4.0 71.9 0.0 21.5 1.5 1.5 3.7 4 

2003 250 1201 8.31 8.17 0.14 4.2 3.2 4.6 75.6 0.0 18.3 1.3 1.6 3.2 5 

2003 281 1092 8.22 8.08 0.14 4.0 3.0 4.5 74.9 0.0 19.1 1.3 1.3 3.3 6 

2003 286 1201 8.20 8.08 0.12 4.0 3.0 4.5 74.6 0.0 19.2 1.1 1.5 3.4 7 

2003 283 1201 8.19 8.08 0.11 4.0 3.0 4.5 74.4 0.0 19.0 1.2 2.1 3.3 8 

2003 261 1201 8.25 8.17 0.08 4.2 3.2 4.6 76.0 0.0 18.3 1.1 1.7 2.9 9 

2003 255 1147 8.25 8.17 0.08 4.2 3.2 4.6 76.9 0.0 18.5 1.2 0.6 2.9 10 

2003 285 1204 8.15 8.08 0.06 4.0 3.0 4.5 74.5 0.0 19.2 1.4 1.4 3.5 11 

2003 348 1201 7.99 7.94 0.06 3.6 2.8 4.1 72.2 0.0 20.6 1.6 2.4 3.2 12 

2003 284 1204 8.14 8.08 0.05 4.0 3.0 4.5 75.6 0.0 19.1 0.9 0.9 3.5 13 

2003 74 1147 7.74 7.69 0.05 2.9 2.4 3.6 69.0 0.0 23.8 2.1 1.0 4.1 14 

2003 77 1204 7.74 7.69 0.04 2.9 2.4 3.6 67.9 0.0 23.4 2.2 2.2 4.3 15 

2003 227 1147 8.21 8.17 0.04 4.2 3.2 4.6 76.0 0.0 18.6 1.1 1.1 3.3 16 

2003 262 1201 8.21 8.17 0.04 4.2 3.2 4.6 75.6 0.0 18.7 1.1 1.1 3.4 17 

2003 238 1147 8.21 8.17 0.03 4.2 3.2 4.6 76.8 0.0 18.0 1.3 1.3 2.6 18 

2003 254 1147 8.20 8.17 0.03 4.2 3.2 4.6 75.8 0.0 18.6 1.4 1.4 2.8 19 

2003 175 1205 8.12 8.08 0.03 4.0 3.0 4.5 74.0 0.0 18.9 1.4 2.9 2.9 20 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Sipsey (Top 25 Days Over 3 Years) 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2003 251 1148 8.48 8.17 0.31 4.2 3.2 4.6 76.1 0.0 18.4 1.2 1.2 3.2 1 

2002 3 1092 8.17 7.94 0.24 3.6 2.8 4.1 72.8 0.0 20.8 1.3 1.5 3.5 2 

2003 282 1067 8.32 8.08 0.23 4.0 3.0 4.5 74.3 0.0 19.1 1.4 2.0 3.3 3 

2003 314 1058 8.11 7.88 0.23 3.4 2.7 4.0 71.8 0.0 21.6 1.4 1.6 3.6 4 

2001 259 1058 8.39 8.17 0.22 4.2 3.2 4.6 75.9 0.0 18.4 1.2 1.4 3.1 5 

2002 268 1092 8.39 8.17 0.22 4.2 3.2 4.6 75.7 0.0 18.3 1.2 1.6 3.1 6 

2003 308 1147 8.07 7.88 0.19 3.4 2.7 4.0 71.9 0.0 21.5 1.5 1.5 3.7 7 

2002 241 1067 8.35 8.17 0.18 4.2 3.2 4.6 75.7 0.0 18.3 1.2 1.5 3.2 8 

2002 247 1147 8.32 8.17 0.15 4.2 3.2 4.6 76.0 0.0 18.5 1.2 1.2 3.1 9 

2002 220 1110 8.32 8.17 0.15 4.2 3.2 4.6 75.5 0.0 18.4 1.2 1.8 3.1 10 

2003 250 1201 8.31 8.17 0.14 4.2 3.2 4.6 75.6 0.0 18.3 1.3 1.6 3.2 11 

2003 281 1092 8.22 8.08 0.14 4.0 3.0 4.5 74.9 0.0 19.1 1.3 1.3 3.3 12 

2002 216 1065 8.31 8.17 0.13 4.2 3.2 4.6 75.7 0.0 18.3 1.3 1.7 3.0 13 

2001 311 1165 8.01 7.88 0.13 3.4 2.7 4.0 71.6 0.0 21.3 1.4 2.1 3.6 14 

2002 245 1147 8.30 8.17 0.13 4.2 3.2 4.6 76.4 0.0 18.5 1.0 1.0 3.1 15 

2001 164 1077 8.20 8.08 0.12 4.0 3.0 4.5 74.5 0.0 19.1 1.1 1.9 3.4 16 

2003 286 1201 8.20 8.08 0.12 4.0 3.0 4.5 74.6 0.0 19.2 1.1 1.5 3.4 17 

2002 244 1147 8.29 8.17 0.12 4.2 3.2 4.6 76.1 0.0 18.5 1.2 1.2 3.1 18 

2001 215 1205 8.28 8.17 0.11 4.2 3.2 4.6 76.2 0.0 18.5 1.2 0.8 3.2 19 

2002 170 1092 8.19 8.08 0.11 4.0 3.0 4.5 74.7 0.0 19.1 1.2 1.6 3.3 20 

2003 283 1201 8.19 8.08 0.11 4.0 3.0 4.5 74.4 0.0 19.0 1.2 2.1 3.3 21 

2002 253 1065 8.28 8.17 0.11 4.2 3.2 4.6 76.3 0.0 18.3 1.2 1.2 2.9 22 

2002 242 1058 8.28 8.17 0.11 4.2 3.2 4.6 76.0 0.0 18.5 1.3 1.3 2.9 23 

2002 243 1092 8.27 8.17 0.10 4.2 3.2 4.6 75.9 0.0 18.4 1.3 1.3 3.1 24 

2001 273 1199 8.27 8.17 0.10 4.2 3.2 4.6 75.3 0.0 18.3 1.4 1.8 3.2 25 
Appendix C 

Agglomerator Cost Estimate from Indigo Industries, Inc.



Appendix D 

BART Determination Modeling Protocol: 

Georgia Power Company 

Plant Bowen 
BART Determination Modeling Protocol: 

Georgia Power Company 

Plant Bowen 

Prepared by: 

Southern Company Services and ENSR Corporation 

for Georgia Power Company 

November 2006
Contents 

1.0 Introduction............................................................................................................................................... 1-1

1.1 Objectives ........................................................................................................................................ 1-1

1.2 Location of source vs. relevant Class I Areas ................................................................................ 1-1

1.3 Organization of protocol document................................................................................................. 1-1

2.0 Source description and emissions data ............................................................................................... 2-1

2.1 BART determination baseline ......................................................................................................... 2-1

2.2 PM emissions controls to be modeled............................................................................................ 2-1

2.3 Unit-specific source data................................................................................................................. 2-1

3.0 Input data to the CALPUFF model ......................................................................................................... 3-1

3.1 General modeling procedures: ....................................................................................................... 3-1

3.2 Air quality database (background ozone and ammonia) ............................................................... 3-1

3.3 Natural conditions and monthly f(RH) at Class I Areas ................................................................. 3-1

4.0 Air quality modeling procedures ........................................................................................................... 4-1

4.1 Model selection and features.......................................................................................................... 4-1

4.2 Modeling domain and receptors ..................................................................................................... 4-1

4.3 Technical options used in the modeling ......................................................................................... 4-1

4.4 Light extinction and haze impact calculations ................................................................................ 4-2

5.0 Presentation of modeling results........................................................................................................... 5-1

Appendix A Basis for Source-Specific Sulfuric Acid Emissions..........................................................A-1 

Appendix B Estimated Emissions of Primary Total Carbon and Primary Sulfate From 

 Coal-Fired Power Plants .......................................................................................................B-1 

i 113006 Bowen BART Determination Modeling Protocol.doc November 2006
List of Tables 

Table 2-1 Plant Bowen premiminary BART Cost Analysis Results ........................................................ 2-2

Table 2-2 Plant Bowen modeling emission parameters .......................................................................... 2-7

List of Figures 

Figure 1-1 Location of Class I Areas in Relation to Plant Bowen............................................................. 1-2

Figure 2-1 Plant Bowen Unit 1 - Annualized Cost versus PM Removed ................................................. 2-3

Figure 2-2 Plant Bowen Unit 2 - Annualized Cost versus PM Removed ................................................. 2-3

Figure 2-3 Plant Bowen Unit 3 - Annualized Cost versus PM Removed ................................................. 2-4

Figure 2-4 Plant Bowen Unit 4 - Annualized Cost versus PM Removed ................................................. 2-4

ii 113006 Bowen BART Determination Modeling Protocol.doc November 2006
1.0 Introduction 

1.1 Objectives 

The Regional Haze Rule requires Best Available Retrofit Technology (BART) for any BART-eligible source that 

‘‘emits any air pollutant which may reasonably be anticipated to cause or contribute to any impairment of 

visibility” in any mandatory Class I federal area. Pursuant to federal regulations, states have the option of 

exempting a BART-eligible source from the BART requirements based on dispersion modeling demonstrating 

that the source cannot reasonably be anticipated to cause or contribute to visibility impairment in a Class I 

area. In addition, the Environmental Protection Agency (EPA) has promulgated a rule allowing states subject 

to the Clean Air Interstate Rule (CAIR) to determine that CAIR satisfies the BART requirements for SO2 and 

NOx for electric generating units (EGUs). Preliminary feedback from the Georgia Environmental Protection 

Division indicates that they anticipate making the decision that CAIR satisfies BART for SO2 and NOx for 

EGUs. Therefore, this modeling protocol focuses on performing the BART modeling analysis for particulate 

matter (PM) only. 

Units 1, 2, 3, and 4 at Plant Bowen, located near Cartersville, which is owned and operated by Georgia Power 

Company, has been identified as a BART-eligible source. The purpose of this document is to summarize the 

procedures by which modeling analyses will be conducted for this source. Georgia Power has determined 

that Plant Bowen is subject to BART for PM. Therefore, the procedures below will be used to evaluate the 

visibility improvement factor in the BART determination step (determination modeling). The modeling 

procedures are consistent with those outlined in the updated final VISTAS common BART modeling protocol 

(dated December 22, 2005, revision 3.2 – August 31, 2006), available at http://www.vistassesarm.org/BART/BARTModelingProtocol_rev3.2_31Aug2006.pdf. This source-specific BART modeling 

protocol references relevant portions of the common VISTAS modeling protocol. 

1.2 Location of source vs. relevant Class I Areas 

The Georgia Environmental Protection Division, which is in charge of the state’s BART program, has 

determined that Units 1, 2, 3, and 4 at Plant Bowen are BART-eligible for PM. Figure 1-1 shows a plot of Plant 

Bowen relative to nearby Class I Areas. There are five Class I areas within 300 km of the plant: Cohutta (84.8 

km), Great Smoky Mountains (175.9 km), Joyce Kilmer (162.3 km), Shinning Rock (228.0 km), and Sipsey 

(223.5 km). Baseline modeling will be conducted for each of these Class I areas in accordance with the 

referenced VISTAS common BART modeling protocol and the procedures described in this source-specific 

BART modeling protocol. Visibility improvement modeling for the BART determination analysis will be 

performed for those Class I areas where the baseline modeling shows a greater than 0.5 deciview impact. 

1.3 Organization of protocol document 

Section 2 of this protocol describes the baseline to be used for the BART determination, identifies the PM 

emissions controls that will be modeled, and outlines the source emissions that will be used as input to the 

BART determination modeling. Section 3 describes the input data to be used for the modeling including the 

modeling domain, terrain and land use, and meteorological data. Section 4 describes the air quality modeling 

procedures and Section 5 discusses how the modeling results will be presented. Since all of the references 

cited are also included in the VISTAS common BART modeling protocol (Section 7.), no reference section is 

included in this document. Appendices A and B provide additional information on the baseline source 

emissions. 

113006 Bowen BART Determination Modeling Protocol.doc 1-1 November 2006
Figure 1-1 Location of Class I Areas in Relation to Plant Bowen 

113006 Bowen BART Determination Modeling Protocol.doc 1-2 November 2006
2.0 Source description and emissions data 

2.1 BART determination baseline 

SO2 scrubbers have been permitted and are under construction for all four units at Plant Bowen. The 

scrubbers will go on line in 2008 for Units 3 and 4, 2009 for Unit 2, and 2010 for Unit 1. So, these scrubbers 

will be “existing” controls for Bowen well ahead of the estimated implementation date for BART (~2014). It has 

been determined that impacts from Bowen 1-4 (the BART eligible source) will be greater than 0.5 deciview on 

at least one Class I area even with the PM emissions reductions that occur from scrubbers. In addition, using 

the scrubbers as baseline provides consistency that allows for straight forward (i.e., effect of emission 

reduction only) interpretation of results. That is, there will be consistency in stack parameters and emissions 

that might otherwise confound interpretation of modeling results. Finally, this approach is consistent with the 

BART statutory factor that requires consideration of "any existing pollution control technology in use at the 

source." For these reasons, scrubbers on the Bowen units will be the starting point (baseline) for the PM 

BART determination and visibility improvement modeling. 

2.2 PM emissions controls to be modeled 

Georgia Power has initiated the PM BART determination analysis for Bowen. Preliminary results include 

identification of technically feasible PM controls and performance of a removal cost analysis for these controls. 

This preliminary cost analysis considers the installed capital and operating cost (including sorbent cost, where 

appropriate), capacity and energy penalties associated with station service impacts, PM species specific 

removal efficiencies for each control, emissions derived based on 2003-2005 actuals adjusted by removal 

efficiencies, and financial assumptions consistent with the EPA Control Cost Manual and industry-accepted 

capital and operating cost estimates.. 

Table 2-1 summarizes preliminary cost analysis results for each technically feasible PM control. Due to space 

constraints, COHPAC (on all four units) and the addition of a new electrostatic precipitator (ESP) collection 

field in a new case (on Units 3 and 4) were not considered. A detailed description of potentially available PM 

controls and their feasibility for Bowen and a detailed discussion of the cost analysis will be provided in the 

final BART determination analysis report to be submitted later. Further refinements to the analysis are 

possible, but it is not anticipated that the conclusions will be significantly different. As described in the EPA 

BART guidance, the data in Table 2-1 was used to create a graphical plot of the total annualized cost for the 

total PM emissions reductions for all feasible control alternatives (Figures 2-1 thru 2-4). A curve was fit to the 

data in order to identify a “least-cost envelope” of dominant control choices. Control options that lie inside of 

the least-cost envelope are considered inferior options based on cost because the cost per ton of particulate 

removed is inconsistent with other competing alternatives. 

Figures 2-1 through 2-4 show that the dominant control choices for all four units include WESP, the addition of 

JuiceCan technology on existing transformer/rectifier (T/R) sets, the particle agglomerator, and the 

combination of JuiceCan/particle agglomerator. Gas flow optimization, lime injection, the addition of a new 

electrical field (on Units 1 and 2), and the combination of WESP/lime injection have been eliminated because 

they fall inside of the least-cost envelope. These options are considered inferior based on cost and, therefore, 

have been eliminated from further consideration. Rather than performing visibility improvement modeling for 

all of the remaining controls, modeling will be performed for two of the remaining options: (1) 

Agglomerator/Juice Can - the highest removal option of the set of relatively lower cost controls, and (2) Wet 

ESP - the remaining control with the overall highest total PM removal. This will bracket the overall visibility 

improvement results. 

2.3 Unit-specific source data 

The emissions data used to assess the visibility impacts at the Class I areas within 300 km of Plant Bowen are 

discussed in this section. As noted earlier, indications from the Georgia Environmental Protection Division are 

113006 Bowen BART Determination Modeling Protocol.doc 2-1 November 2006
that they will issue rules stating that CAIR will suffice for EGU BART for SO2 and NOx. Therefore, this protocol 

focuses only on PM10. Since various components of PM10 emissions have different visibility extinction 

efficiencies, the PM10 emissions are divided, or “speciated,” into several components (VISTAS common 

protocol Sections 4.3.3 and 4.4.2). The VISTAS protocol (Section 5.) allows for the use of source-specific 

emissions and speciation factors and/or default values from AP-42. The PM10 emissions and speciation 

Table 2-1 Plant Bowen Preliminary BART Cost Analysis Results

Total PM10 

Removed

Annualized 

Cost

Removal 

Cost

Total PM10 

Removed

Annualized 

Cost

Removal 

Cost

Control Option

Tons $/Yr $ per Ton Tons $/Yr $ per Ton

Optimize Gas Flow 5.6 $125,600 $22,274 7.8 $125,600 $16,089

Juice Can Retrofit 11.3 $82,317 $7,299 15.6 $82,317 $5,272

Lime Injection 33.1 $2,714,893 $82,026 38.1 $2,714,893 $71,323

Agglomerator Retrofit 62.0 $1,236,108 $19,929 85.9 $1,236,108 $14,395

Add field in new casing 65.8 $3,433,973 $52,199 91.1 $3,433,973 $37,705

Agglomerator/JuiceCan 73.3 $1,318,425 $17,986 101.5 $1,318,425 $12,991

WESP 261.0 $13,102,142 $50,209 336.2 $13,102,142 $38,973

WESP/Lime Injection 271.0 $15,817,034 $58,375 347.4 $15,817,034 $45,527

Control Option

Tons $/Yr $ per Ton Tons $/Yr $ per Ton

Optimize Gas Flow 14.1 $161,486 $11,465 16.0 $161,486 $10,074

Juice Can Retrofit 21.1 $105,836 $5,009 24.0 $105,836 $4,402

Lime Injection 44.6 $3,490,576 $78,224 43.2 $3,490,576 $80,850

Agglomerator Retrofit 51.6 $1,589,281 $30,772 58.8 $1,589,281 $27,039

Agglomerator/JuiceCan 72.8 $1,695,117 $23,292 82.8 $1,695,117 $20,467

WESP 334.8 $16,845,611 $50,319 360.5 $16,845,611 $46,731

WESP/Lime Injection 348.2 $20,336,187 $58,396 373.6 $20,336,187 $54,440

Add field in new casing n/a n/a n/a n/a n/a n/a

Bowen 3 Bowen 4

Bowen 1 Bowen 2

113006 Bowen BART Determination Modeling Protocol.doc 2-2 November 2006
Figure 2-1 Plant Bowen Unit 1 - Annualized Cost versus PM Removed 

y = 162.81x2 + 7738.6x - 6001.7

R2

 = 0.9997

$-

$2,000,000

$4,000,000

$6,000,000

$8,000,000

$10,000,000

$12,000,000

$14,000,000

$16,000,000

$18,000,000

0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0

Incremental Total PM Reduction [tpy]

Annualized Cost [$/yr]

Baseline: FGD

WESP

Agglomerator

Gas Flow Opt

Lime

New Field

WESP/Lime

Agg/JuiceCan

JuiceCan

Figure 2-2 Plant Bowen Unit 2 - Annualized Cost versus PM Removed 

y = 106.02x2 + 3245.8x + 26909

R2

 = 0.9997

$-

$2,000,000

$4,000,000

$6,000,000

$8,000,000

$10,000,000

$12,000,000

$14,000,000

$16,000,000

$18,000,000

0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0 400.0

Incremental Total PM Reduction [tpy]

Annualized Cost [$/yr]

Baseline: FGD

WESP

Agglomerator

Gas Flow Opt

Lime

New Field

WESP/Lime

Agg/JuiceCan

JuiceCan

113006 Bowen BART Determination Modeling Protocol.doc 2-3 November 2006
Figure 2-3 Plant Bowen Unit 3 - Annualized Cost versus PM Removed 

y = 76.74x2 + 25591x - 325653

R2

 = 0.9988

$-

$2,000,000

$4,000,000

$6,000,000

$8,000,000

$10,000,000

$12,000,000

$14,000,000

$16,000,000

$18,000,000

$20,000,000

$22,000,000

$24,000,000

0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0 400.0

Incremental Total PM Reduction [tpy]

Annualized Cost [$/yr]

Baseline: FGD

WESP

Agglomerator

Gas Flow Opt

Lime

WESP/Lime

Agg/JuiceCan

JuiceCan

Figure 2-4 Plant Bowen Unit 4 - Annualized Cost versus PM Removed

y = 73.543x2 + 21034x - 297166

R2

 = 0.9987

$-

$2,000,000

$4,000,000

$6,000,000

$8,000,000

$10,000,000

$12,000,000

$14,000,000

$16,000,000

$18,000,000

$20,000,000

$22,000,000

$24,000,000

0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0 400.0 450.0

Incremental Total PM Reduction [tpy]

Annualized Cost [$/yr]

Baseline: FGD

WESP

Agglomerator

Gas Flow Opt

Lime

WESP/Lime

Agg/JuiceCan

JuiceCan

113006 Bowen BART Determination Modeling Protocol.doc 2-4 November 2006
approach to be used for the modeling described in this protocol is indicated in the bullets below. Where 

default speciation values are used, the data represents a unit where current (baseline) emission controls 

include ESPs and selective catalytic reduction (SCR) systems, but no post-combustion SO2 control equipment 

exists. 

As indicated in Section 2.1, it has been determined that the baseline for the BART determination analysis and 

visibility improvement modeling will include scrubbers on all of the Bowen units. Therefore, the foundation for 

deriving the baseline and control option emissions for the BART determination modeling was to establish 

“maximum 24-hour average emission rates” based on the current configuration consistent with the VISTAS 

common protocol and then to apply the species specific control efficiencies as appropriate. To establish 

emission rates for the BART determination baseline modeling, scrubber control efficiencies were applied to the 

maximum 24-hour average rates. 

• Total PM10 is comprised of filterable and condensable emissions. 

• Filterable PM10 emissions are based on the highest stack test for the most recent 3-year period (2003-

2005). This stack test is combined with the highest 24 hour heat input value for this period from 

CEMS data to calculate the “maximum 24-hour average emission rate” as required by the VISTAS 

protocol. 

• Filterable PM10 will be subdivided by size category consistent with the default approach from AP-42 

Table 1-1.6, and as noted on pages 43 and 44 of the VISTAS common BART modeling protocol. The 

AP-42 Table 1-1.6 specifies for the emission controls indicated above that 55.6% of filterable PM10

emissions is coarse (greater than 2.5 microns in size) and 44.4% is fine. Of the fine portion, 3.7% is 

elemental carbon and the remainder is inorganic fine particulates (soil). 

• Condensable PM10 consists of inorganic and organic compounds. The inorganic portion is by default 

assumed to be H2SO4, although other non-sulfate inorganic condensables could be present. The 

organic portion is modeled as organic aerosols. 

• H2SO4 emissions are calculated consistent with the method used by Georgia Power to derive these 

emissions for TRI purposes. This approach assumes that the H2SO4 emissions released from the 

stack are proportional to SO2 emissions from combustion and are dependent on the fuel type and the 

removal of H2SO4 by downstream equipment (i.e., ESP and air heater). For eastern bituminous coal 

the fundamental H2SO4 release rate (without scrubbers or add-on PM controls) is in the range of 0.3 to 

0.8% of the SO2 emissions. Appendix A provides the basis for the site-specific values used. 

• Emissions of condensable organics (the remaining portion of condensable PM10) are derived based on 

the supporting field observational information in Appendix B and is estimated as 0.32% of SO2

emitted. 

• Coarse filterable particles (between 2.5 and 10 microns in size) will be modeled with a geometric mass 

mean diameter of 5 microns, while fine filterable and all condensable particles will be modeled with a 

geometric mass mean diameter of 0.48 microns, consistent with the CALPUFF default value for fine 

particles. The geometric standard deviation for both fine and coarse particles will be set to 2 microns, 

consistent with the CALPUFF default value. The 0.48 micron diameter value for fine particles comes 

from the default values in sample input files presented on the TRC web site. There is no default 

value presented for the coarse particles on the TRC web site. However, since 5 is the geometric 

mass mean diameter of 2.5 and 10 (the bounds of coarse particle sizes), it is a reasonable estimate 

for the geometric mass mean diameter for that class of particles. 

In practice, CALPUFF allows for the user to input certain components of PM10 as separate species and 

separate sizes, which will result in more accurate wet and dry deposition velocity results and also more 

accurate effects on light scattering. As noted above, the particle size distribution information is provided in 

AP-42 Table 1-1.6, and will be used for the BART determination modeling. 

113006 Bowen BART Determination Modeling Protocol.doc 2-5 November 2006
2-6 November 2006 113006 Bowen BART Determination Modeling Protocol.doc

Table 2-2 provides a summary of the modeling emission parameters to be used in the BART CALPUFF 

modeling, consistent with the source emissions data presented in Appendices A and B for the current 

configuration. The foundation for all of the emissions in Table 2-2 were derived from CEMS data for the 2003 

to 2005 period and represent the maximum 24-hour average lb/hr rates (excluding days where startup, 

shutdown, or malfunctions occurred). For NOx and SO2 the current configuration values are directly from 

CEMS. Filterable PM10 emissions were calculated using the highest stack test over the 2003 to 2005 period 

and multiplying these values times the maximum 24-hour average heat input derived from CEMS. These 

values were then adjusted using AP-42 factors from Table 1.1-6 that indicate that PM10 is 67% of total PM for a 

pulverized coal unit with an ESP. PM10 speciation was then performed as indicated above such that total 

Filterable PM10 is made up of Coarse Soil plus total Fine PM and total Fine PM is made up of Fine Soil plus 

Elemental Carbon (EC). Since these units include SCRs, a consistent set of seasonal emissions data was 

developed representing periods with and without SCR operation. For these, the maximum 24-hour average 

rates were extracted from the seasonal (May - September) and non-seasonal (October - April) CEMS data. 

For visibility improvement modeling, only the emissions representing SCR operation was used as the 

foundation for establishing the baseline (scrubbed) emission rates and the emission rates for PM controls 

under consideration. 
Table 2-2 Plant Bowen modeling emission parameters 

Location UTM 

(Zone 16 NAD-83) Emissions1 Part

Case Source / Unit 

UTM 

East 

UTM 

North 

Actual 

Stack Ht 

Base 

Elev. 

Flue 

Diameter 

Gas 

Exit 

Vel. 

Stack 

Gas 

Exit 

Temp. SO2 NOX PM10 Filt. PM10 Coarse Soil Fine PM F

m m m m m m/s deg K lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr 

FUNDAMENTAL EMISSIONS DATA 

Fundamental Data (Unit Basis) 

Current Config. Unit 1 691,893 3,778,033 304.8 219.8 7.6 20.8 403.0 15374.22 1565.42 510.21 378.07 210.20 167.86 Current Config. Unit 2 691,893 3,778,033 304.8 219.8 7.6 20.8 403.0 16059.38 1253.44 545.86 407.51 226.58 180.94 Current Config. Unit 3 691,893 3,778,033 304.8 219.8 7.6 27.1 409.7 18519.37 773.00 478.86 268.01 149.01 119.00 Current Config. Unit 4 691,893 3,778,033 304.8 219.8 7.6 27.1 409.7 19504.06 971.92 521.14 297.26 165.28 131.98 

BART DETERMINATION BASELINE EMISSIONS 

Scrubber Baseline Data (Unit Basis) 

Baseline Unit 1 691,893 3,778,033 207.5 219.5 7.6 12.5 327.0 768.71 1565.42 174.58 75.61 42.04 33.57 Baseline Unit 2 691,893 3,778,033 207.5 219.5 7.6 12.5 327.0 802.97 1253.44 185.07 81.50 45.32 36.19 Baseline Unit 3 691,893 3,778,033 207.5 219.5 7.6 15.8 327.0 925.97 773.00 173.03 53.60 29.80 23.80 Baseline Unit 4 691,893 3,778,033 207.5 219.5 7.6 15.8 327.0 975.20 971.92 185.10 59.45 33.06 26.40 

Scrubber Baseline Data (Stack Basis) 

Modeled 

Stk Ht3 Eq. Dia. 

m m m m m m/s deg K lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 1571.68 2818.85 359.64 157.12 87.36 69.76 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 1901.17 1744.92 358.13 113.05 62.86 50.20 

Stack Basis Emissions Converted to g/sec g/sec g/sec g/sec g/sec g/sec g/sec 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 198.03 355.18 45.32 19.80 11.01 8.79 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 239.55 219.86 45.12 14.24 7.92 6.32 

2-7 

113006 Bowen BART Determination Modeling Protocol.doc
Table 2-2 (Continued) Plant Bowen modeling emission parameters

Location UTM 

(Zone 16 NAD-83) Emissions1 Part

Case Source / Unit 

UTM 

East 

UTM 

North 

Actual 

Stack Ht 

Base 

Elev. 

Flue 

Diameter 

Gas 

Exit 

Vel. 

Stack 

Gas 

Exit 

Temp. SO2 NOX PM10 Filt. PM10 Coarse Soil Fine PM F

m m m m m m/s deg K lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr 

EMISSIONS for MODELED CONTROL OPTIONS 

Agglomerator/Juice Can Data (Unit Basis) 

Agglom/JC Unit 1 691,893 3,778,033 207.5 219.5 7.6 12.5 327.0 768.71 1565.42 145.09 46.12 25.98 20.14 Agglom/JC Unit 2 691,893 3,778,033 207.5 219.5 7.6 12.5 327.0 802.97 1253.44 153.28 49.72 28.00 21.71 Agglom/JC Unit 3 691,893 3,778,033 207.5 219.5 7.6 15.8 327.0 925.97 773.00 156.41 36.99 23.42 13.57 Agglom/JC Unit 4 691,893 3,778,033 207.5 219.5 7.6 15.8 327.0 975.20 971.92 166.67 41.02 25.98 15.05 

Agglomerator/Juice Can Data (Stack Basis) - Unit 1 Only Controlled 

Modeled 

Stk Ht3

Eq. 

Dia. 

m m m m m m/s deg K lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 1571.68 2818.85 330.16 127.63 71.30 56.33 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 1901.17 1744.92 358.13 113.05 62.86 50.20 

Stack Basis Emissions Converted to g/sec g/sec g/sec g/sec g/sec g/sec g/sec 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 198.03 355.18 41.60 16.08 8.98 7.10 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 239.55 219.86 45.12 14.24 7.92 6.32 

Agglomerator/Juice Can Data (Stack Basis) - Unit 2 Only Controlled 

Modeled 

Stk Ht3 Eq. Dia. 

m m m m m m/s deg K lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 1571.68 2818.85 327.86 125.33 70.05 55.28 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 1901.17 1744.92 358.13 113.05 62.86 50.20 

Stack Basis Emissions Converted to g/sec g/sec g/sec g/sec g/sec g/sec g/sec 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 198.03 355.18 41.31 15.79 8.83 6.97 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 239.55 219.86 45.12 14.24 7.92 6.32 

2-8 

113006 Bowen BART Determination Modeling Protocol.doc
Table 2-2 (Continued) Plant Bowen modeling emission parameters 

Location UTM 

(Zone 16 NAD-83) Emissions1 Part

Case Source / Unit 

UTM 

East 

UTM 

North 

Actual 

Stack Ht 

Base 

Elev. 

Flue 

Diameter 

Gas 

Exit 

Vel. 

Stack 

Gas 

Exit 

Temp. SO2 NOX PM10 Filt. PM10 Coarse Soil Fine PM F

Agglomerator/Juice Can Data (Stack Basis) - Unit 3 Only Controlled 

Modeled 

Stk Ht3 Eq. Dia. 

m m m m m m/s deg K lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 1571.68 2818.85 359.64 157.12 87.36 69.76 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 1901.17 1744.92 341.51 96.44 56.48 39.96 

Stack Basis Emissions Converted to g/sec g/sec g/sec g/sec g/sec g/sec g/sec 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 198.03 355.18 45.32 19.80 11.01 8.79 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 239.55 219.86 43.03 12.15 7.12 5.04 

Agglomerator/Juice Can Data (Stack Basis) - Unit 4 Only Controlled 

Modeled 

Stk Ht3

Eq. 

Dia. 

m m m m m m/s deg K lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 1571.68 2818.85 359.64 157.12 87.36 69.76 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 1901.17 1744.92 339.70 94.62 55.78 38.85 

Stack Basis Emissions Converted to g/sec g/sec g/sec g/sec g/sec g/sec g/sec 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 198.03 355.18 45.32 19.80 11.01 8.79 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 239.55 219.86 42.80 11.92 7.03 4.89 

2-9 

113006 Bowen BART Determination Modeling Protocol.doc
Table 2-2 (Continued) Plant Bowen modeling emission parameters 

Location UTM 

(Zone 16 NAD-83) Emissions1 Part

Case Source / Unit 

UTM 

East 

UTM 

North 

Actual 

Stack Ht 

Base 

Elev. 

Flue 

Diameter 

Gas 

Exit 

Vel. 

Stack 

Gas 

Exit 

Temp. SO2 NOX PM10 Filt. PM10 Coarse Soil Fine PM F

Wet ESP Data (Unit Basis) 

Wet ESP Unit 1 691,893 3,778,033 207.5 219.5 7.6 12.5 327.0 768.71 1565.42 66.71 7.56 4.20 3.36 Wet ESP Unit 2 691,893 3,778,033 207.5 219.5 7.6 12.5 327.0 802.97 1253.44 69.98 8.15 4.53 3.62 Wet ESP Unit 3 691,893 3,778,033 207.5 219.5 7.6 15.8 327.0 925.97 773.00 76.65 5.36 2.98 2.38 Wet ESP Unit 4 691,893 3,778,033 207.5 219.5 7.6 15.8 327.0 975.20 971.92 81.01 5.95 3.31 2.64 

Wet ESP Data (Stack Basis) - Unit 1 Only Controlled 

Modeled 

Stk Ht3 Eq. Dia. 

m m m m m m/s deg K lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 1571.68 2818.85 251.78 89.06 49.52 39.54 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 1901.17 1744.92 358.13 113.05 62.86 50.20 

Stack Basis Emissions Converted to g/sec g/sec g/sec g/sec g/sec g/sec g/sec 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 198.03 355.18 31.72 11.22 6.24 4.98 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 239.55 219.86 45.12 14.24 7.92 6.32 

Wet ESP Data (Stack Basis) - Unit 2 Only Controlled 

Modeled 

Stk Ht3 Eq. Dia. 

m m m m m m/s deg K lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 1571.68 2818.85 244.55 83.76 46.57 37.19 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 1901.17 1744.92 358.13 113.05 62.86 50.20 

Stack Basis Emissions Converted to g/sec g/sec g/sec g/sec g/sec g/sec g/sec 

Stack 1 1&2 691,893 3,778,033 304.8 219.5 14.2 12.5 327.0 198.03 355.18 30.81 10.55 5.87 4.69 Stack 2 3&4 691,893 3,778,033 304.8 219.5 14.2 15.8 327.0 239.55 219.86 45.12 14.24 7.92 6.32 

Wet ESP Data (Stack Basis) - Unit 3 Only Controlled 

Modeled 

Stk Ht3 Eq. Dia. 

m m m m m m/s deg K lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 1571.68 2818.85 359.64 157.12 87.36 69.76 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 1901.17 1744.92 261.76 64.81 36.04 28.78 

Stack Basis Emissions Converted to g/sec g/sec g/sec g/sec g/sec g/sec g/sec 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 198.03 355.18 45.32 19.80 11.01 8.79 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 239.55 219.86 32.98 8.17 4.54 3.63 

2-10 

113006 Bowen BART Determination Modeling Protocol.doc
113006 Bow

Location UTM 

(Zone 16 NAD-83) Emissions1 Part

Case Source / Unit 

UTM 

East 

UTM 

North 

Actual 

Stack Ht 

Base 

Elev. 

Flue 

Diameter 

Gas 

Exit 

Vel. 

Stack 

Gas 

Exit 

Temp. SO2 NOX PM10 Filt. PM10 Coarse Soil Fine PM F

Wet ESP Data (Stack Basis) - Unit 4 Only Controlled 

Modeled 

Stk Ht3 Eq. Dia. 

m m m m m m/s deg K lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr lbs/hr 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 1571.68 2818.85 359.64 157.12 87.36 69.76 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 1901.17 1744.92 254.03 59.55 33.11 26.44 

Stack Basis Emissions Converted to g/sec g/sec g/sec g/sec g/sec g/sec g/sec 

Stack 1 1&2 691,893 3,778,033 207.5 219.5 14.2 12.5 327.0 198.03 355.18 45.32 19.80 11.01 8.79 Stack 2 3&4 691,893 3,778,033 207.5 219.5 14.2 15.8 327.0 239.55 219.86 32.01 7.50 4.17 3.33 

2 Elemental carbon (EC) and Fine PM are a part of Filterable PM10 and H2SO4 and Organics are a part of Condensable PM10. Note that 

SO4. The molecular weights of H2SO4 and SO4 are 98 and 96 respectively; therefore the conversion factor from H2SO4 to SO4 is 96/98. 

1 SO2 and NOx emissions are not BART-applicable for EGU sources in CAIR states, if the state agency agrees with EPA’s interpretation 

emissions for SO2 and NOx are provided for information purposes, and for reference in the computation of certain particle species such 

2-11 

en BART Determination Modeling Protocol.doc

3 Stack credit is equal to actual stack height since this stack is grandfathered. 

Table 2-2 (Continued) Plant Bowen modeling emission parameters Notes: 
3.0 Input data to the CALPUFF model 

3.1 General modeling procedures: 

VISTAS has developed five sub-regional 4-km CALMET meteorological databases for three years (2001-

2003) (VISTAS common protocol Section 4.4.2). The sub-regional modeling domains are strategically 

designed to cover all potential BART eligible sources within VISTAS states and all PSD Class I areas within 

300 km of those sources (to the nearest edge). The extents of the 4-km sub-regional domains are shown in 

Figure 4-4 of the VISTAS common BART modeling protocol. The BART modeling for Plant Bowen will be 

done using the 4-km subdomain 4. 

USGS 90-meter Digital Elevation Model (DEM) files were used by VISTAS to generate the terrain data at 4-km 

resolution for input to the 4-km sub-regional CALMET run. Likewise, USGS 90-meter Composite Theme Grid 

(CTG) files were used by VISTAS to generate the land use data at 4-km resolution for input to the 4-km subregional CALMET run. 

Three years of MM5 data (2001-2003) were used by VISTAS to generate the 4-km sub-regional 

meteorological datasets. See Sections 4.3.2 and 4.4.2 in the VISTAS common BART modeling protocol for 

more detail on these issues. 

It is intended that all of the modeling for Plant Bowen will use the 4-km subdomain 4. However, if the results 

indicate that the modeling could be improved with a CALPUFF run using a finer grid, then refinements in the 

modeling procedures will be considered and the Georgia Environmental Protection Division will be asked to 

approve these refinements. 

In the event that a finer grid resolution is used, CALMET must be rerun. Other modifications to inputs of 

CALMET would include the extent of the modeling domain, the resolution of the terrain and land use data, and 

other relevant settings. The same MM5 data and observations as used for the 4-km sub-regional CALMET 

simulations would be used. The extent of the modeling domain may need to be changed because of disk 

space restrictions. The size of the CALMET output is directly proportional to the grid resolution of the run. The 

domain would be limited to the source and the exclusive Class I area(s) being assessed with a higher grid 

resolution, including a 50-km buffer in all directions. 

If CALMET needs to be run at even a finer grid resolution, then the appropriate model setting/files (specifically 

the GEO.DAT file) will be modified. A summary of these modifications would be provided to the Georgia 

Environmental Protection Division for review and approval. 

3.2 Air quality database (background ozone and ammonia) 

Hourly measurements of ozone from all non-urban monitors, as generated by VISTAS and available on the 

VISTAS CALPUFF page on the Earth Tech web site (http://www.src.com/verio/download/sample_files.htm), 

will be used as input to CALPUFF. For ammonia, a 0.5 ppb background value as recommended by VISTAS 

will be used. However, since only PM emissions are being modeled, ozone and ammonia data is not really 

needed given that this data has no effect on PM results in CALPUFF. 

3.3 Natural conditions and monthly f(RH) at Class I Areas 

For each of the applicable Class I areas, natural background conditions must be established in order to 

determine a change in natural conditions related to a source’s emissions. The modeling described by this 

protocol document intends to use annual average natural background light extinction (EPA 2003 values). 

113006 Bowen BART Determination Modeling Protocol.doc 3-1 November 2006
To determine the input to CALPUFF, it is first necessary to convert the deciviews to extinction using the 

equation: 

Extinction (Mm-1) = 10 exp(deciviews/10). 

For example, the EPA guidance document indicates for Great Smoky Mountains National Park that the 

deciview value for the average of the days is 7.60. This is equivalent to an extinction of 21.38 inverse 

megameters (Mm-1). 

This extinction includes the default 10 Mm-1 for Rayleigh scattering. The remaining extinction is due to 

naturally occurring particles, and should be held constant for the entire year’s simulation. Therefore, the data 

provided to CALPOST for Great Smoky Mountains would be the total natural background extinction minus 10 

(expressed in Mm-1), or 11.38. This is most easily input as fine soil concentrations (11.38 μg/m3

) in CALPOST, 

since the extinction efficiency of soil (PM-fine) is 1.0 and there is no f(RH) component. The concentration 

entries for all other particle constituents would be set to zero, and the fine soil concentration would be kept the 

same for each month of the year. The monthly values for f(RH) that CALPOST needs will be taken from 

"Guidance for Tracking Progress Under the Regional Haze Rule" (EPA, 2003) Appendix A, Table A-3. 

113006 Bowen BART Determination Modeling Protocol.doc 3-2 November 2006
4.0 Air quality modeling procedures 

This section provides a summary of the modeling procedures outlined in the VISTAS protocol that will be used 

for the refined CALPUFF analysis to be conducted for Plant Bowen. 

4.1 Model selection and features 

As noted in the VISTAS protocol (Summary, Recommendations Section II.), VISTAS will use CALPUFF 

Version 5.754 and CALMET Version 5.7, which can be obtained at 

http://www.src.com/verio/download/download.htm#VISTAS_VERSION. These versions contain 

enhancements funded by the Minerals Management Service (MMS) and VISTAS. They are maintained on 

TRC’s Atmospheric Studies Group CALPUFF website for public access. This release includes CALMET, 

CALPUFF, CALPOST, CALSUM, and POSTUTIL as well as CALVIEW. 

The major features of the CALPUFF modeling system, including those of CALMET and the post processors 

(CALPOST and POSTUTIL), are referenced in Section 3 of the VISTAS protocol. 

The baseline BART modeling will be conducted for Bowen Units 1 thru 4 (BART eligible units) for each Class I 

area within 300 km of the source. Unit 1 thru 4 will each be modeled separately for the visibility improvement 

modeling for the BART determination step for the Class I areas where baseline modeling shows a greater than 

0.5 deciview impact. 

4.2 Modeling domain and receptors 

The initial Plant Bowen BART runs will use the sub-domain 4, 4-km CALMET data supplied by VISTAS, as 

discussed above. This domain includes all Class I areas within 300 km of the source, plus a 50-km buffer. If 

there is the need for a refined analysis with a finer grid, a supplement to this modeling protocol will be provided 

describing the proposed procedures. 

The receptors used for each of the Class I areas are based on the NPS database of Class I receptors, as 

recommended by the VISTAS common protocol (Section 4.3.3). 

4.3 Technical options used in the modeling 

CALMET modeling for the VISTAS-provided 4-km subdomains will be performed per the procedures specified 

in the VISTAS common BART modeling protocol. If it is decided to conduct additional modeling with a finer 

grid than 4 km, this modeling protocol will be updated to specify the technical options to be used in the 

CALMET run, in order to allow for state agency review and approval. 

For CALPUFF model options, Plant Bowen will follow the VISTAS common BART modeling protocol (Section 

4.4.1), which states that we should use IWAQM (EPA, 1998) guidance. The VISTAS protocol (Section 4.3.3) 

also notes that building downwash effects are not required to be included unless the state directs the source to 

include these effects. Since Plant Bowen is more than 50 km from the nearest Class I area, building 

downwash effects will not be included in the CALPUFF modeling. 

The POSTUTIL utility program (VISTAS common protocol Section 4.4.2) will be used to repartition HNO3 and 

NO3 using VISTAS-provided ammonia concentrations derived from previous 2002 CMAQ modeling conducted 

by EPA or the alternate ammonia concentrations approach recommended by VISTAS, if the CMAQ data is 

unavailable. As indicated earlier, since only PM emissions are being modeled, the treatment of ammonia 

should not have an affect on PM results from CALPUFF. 

113006 Bowen BART Determination Modeling Protocol.doc 4-1 November 2006
4.4 Light extinction and haze impact calculations 

The CALPOST postprocessor will be used as prescribed in the VISTAS protocol for the calculation of the 

impact from the modeled source’s primary and secondary particulate matter concentrations on light extinction. 

The formula that is currently used in CALPOST is the existing (not the November 2005 revised) 

IMPROVE/EPA formula, which is applied to determine a change in light extinction due to increases in the 

particulate matter component concentrations. Using the notation of CALPOST, the formula is the following: 

bext = 3 f(RH) [(NH4)2SO4] + 3 f(RH) [NH4NO3] + 4[OC] + 1[Soil] + 0.6[Coarse Mass] + 10[EC] + bRay

The concentrations, in square brackets, are in ug/m3

 and bext is in units of Mm-1. The Rayleigh scattering term 

(bRay) has a default value of 10 Mm-1, as recommended in EPA guidance for tracking reasonable progress 

(EPA, 2003a). 

The extinction formula shown above is known to be inadequate in its representation of light extinction from sea 

salt and its usage of 1.4 as the organic mass to carbon mass ratio. Furthermore, guidance for this formula did 

not provide for site-specific Rayleigh scattering. In December of 2005, the IMPROVE Steering Committee 

adopted a new formula for determining light extinction that addresses these and other shortcomings. The new 

formula is shown below.. 

)]([33.0

( )

[6.0 ]

][)(7.1

][1

[10 ]

[8.2 [1.6] ]

[)(4.2 [)(1.5] ]

[)(2.2 [)(8.4] ]

2 ppbNO

Rayleigh Scattering SpecificSite

Course Mass

SaltSeaRHf

SoilFine

Elemental Carbon

Small Organic Mass OrganicrgeLa Mass

RHf Small Nitrate NitratergeLaRHf

b RHf Small Sulfate SulfatergeLaRHf

SS

S L

ext S L

×+

+

×+

××+

×+

×+

×+ ×+

××+ ××+

××≈ + × ×

The apportionment of the total concentration of sulfate compounds into the concentrations of the small and 

large size fractions is accomplished using the following equations. 

3

3 [ [], /20] /20

[ ] [ ] Total Sulfate Total Sulfate mg

mg

Total Sulfate SulfatergeLa μ

μ = × <

3 [ SulfatergeLa = [] Total Sulfate [], Total Sulfate ≥ μ /20] mg

[Small Sulfate = [] Total Sulfate −[] SulfatergeLa ]

This revised version of the IMPROVE Equation will be used to calculate visibility improvement results for the 

BART determination modeling. Dr. Ivar Tombach (VISTAS consultant) has produced a spreadsheet tool 

(September 29, 2006) to allow the new IMPROVE formula results to be derived from the basic CALPOST 

113006 Bowen BART Determination Modeling Protocol.doc 4-2 November 2006
outputs. Also, since the BART determination modeling is focused only on PM, NO2 will be set to zero in the 

new formula. For informational purposes only, results from the old equation will also be presented. 

The assessment of visibility impacts at the Class I areas will use CALPOST Method 6 (VISTAS common 

protocol Section 4.3.2). Each hour’s source-caused extinction is calculated by first using the hygroscopic 

components of the source-caused concentrations, due to ammonium sulfate and nitrate, and monthly Class I 

area-specific f(RH) values. The contribution to the total source-caused extinction from ammonium sulfate and 

nitrate is then added to the other, non-hygroscopic components of the particulate concentration (from coarse 

and fine soil, secondary organic aerosols, and from elemental carbon) to yield the total hourly source-caused 

extinction. 

The BART rule significance threshold for the contribution to visibility impairment is 0.5 deciviews. The VISTAS 

protocol (Section 4.3.2) indicates that with the use of the 4-km sub-regional CALMET database, a source does 

not cause or contribute to visibility impairment if the 98th percentile (or 8th highest) day’s change in extinction 

from natural conditions does not exceed 0.5 deciviews for any of the modeled years (an added check is: the 

22nd highest prediction over the three years modeled should also not exceed 0.5 deciviews for a source to be 

exempted from a BART determination). Both the 98th percentile (or 8th highest) day's change in extinction 

from natural conditions for any modeled year and the 22nd highest prediction over the three years modeled 

will be evaluated. 

Figure 4-1 of the VISTAS common BART modeling protocol presents a flow chart showing the components of 

that common protocol. The modeling for Plant Bowen will focus on Subregional Fine-Scale modeling as 

depicted in the lower half of the figure. 

The source will perform BART determination modeling for the baseline and each control option in the manner 

described in this document. 

113006 Bowen BART Determination Modeling Protocol.doc 4-3 November 2006
5.0 Presentation of modeling results 

The BART determination modeling results for Plant Bowen will be provided to the state agency in a manner as 

described in the VISTAS protocol (Section 4.5). The results will include the following elements (as suggested 

in the VISTAS protocol): 

1. A map of the source location and Class I areas within 300 km of the source. 

2. For the CALPUFF modeling domain, a table listing all Class I areas in the VISTAS domain and those 

in neighboring states and impacts from the BART 4-km grid baseline modeling at those Class I 

areas within 300 km of the source, as illustrated in Table 4-3 of the VISTAS protocol. 

3. Identify from the baseline modeling the number of Class I areas with visibility impairment due to 

source emissions for the 98th percentile days in each year (and the 98th percentile over all three 

years modeled) greater than 0.5 dv. 

4. For the Class I area with the maximum impact, identification of the number of days beyond those 

excluded (e.g., the 98th percentile for refined analyses) that the impact of the source exceeds 0.5 

dv, the number of receptors in the Class I area where the impact exceeds 0.5 dv, and the maximum 

impact. 

The BART determination modeling will be performed for those Class I areas shown in the baseline modeling to 

exceed 0.5 dv impact. The results presented will be a comparison of the 98th percentile value for the baseline 

and each control option and emissions unit derived as is outlined above for the baseline modeling. A 

summary of the relative results among all emission scenarios run would be produced. 

Additionally, the appropriate electronic files used to conduct the CALPUFF modeling will be submitted on CDROM or DVD media. 

113006 Bowen BART Determination Modeling Protocol.doc 5-1 November 2006
Appendix A 

Basis for Source-Specific Sulfuric Acid Emissions 

113006 Bowen BART Determination Modeling Protocol.doc A-1 November 2006
Appendix A 

Basis for Source-Specific Sulfuric Acid Emissions 

Sulfuric Acid (H2SO4) Emissions

During the combustion of sulfur-containing fuels, a percentage of the SO2 formed is further oxidized to SO3. 

As the flue gas cools across the air heater, this SO3 combines with flue gas moisture to form vapor-phase 

and/or condensed sulfuric acid (H2SO4). The H2SO4 emissions shown in Table 2-1 of this BART modeling 

protocol were calculated consistent with the method used by Southern Company to derive these emissions for 

Toxics Release Inventory (TRI) purposes. This method is documented in a report titled Estimating Total 

Sulfuric Acid Emissions from Stationary Power Plants: Revision 3 (2005) prepared by Keith Harrison and Dr. 

Larry Monroe (Southern Company Services) and Edward Cichanowicz (Consultant). The approach described 

in this report assumes that H2SO4 emissions released from the stack are proportional to SO2 emissions from 

combustion and are dependent on the fuel type and the removal of H2SO4 by downstream equipment (i.e., 

ESP and air heater) and add-on emissions control equipment (scrubber). 

Since this facility contains post-combustion NOx control (SCR), the baseline sulfuric acid emissions estimate 

accounts for the manufacture of H2SO4 through combustion and through further oxidation of SO2 in the SCR. 

Calculated sulfuric acid releases then account for loss or removal within the system. The equations below 

show how the manufacture and release calculations are made. Table A-1 shows the resulting H2SO4

emissions calculations . 

Sulfuric Acid Manufactured from Combustion (EMComb): 

EMComb = K x F1 x E2 

where, 

EMComb = total sulfuric acid manufactured from combustion, lbs/yr 

K = Molecular weight and units conversion constant = 98.07 / 64.04 * 2000 = 3,063 

(98.07 = Molecular weight of sulfuric acid; 64.04 = Molecular weight of SO2; Conversion from tons per 

year to pounds per year – multiply by 2000.) 

F1 = Fuel Impact Factor (from the emissions estimating report) 

E2 = Sulfur dioxide emissions, tons (from CEMS data). 

Sulfuric Acid Released from Combustion (ERComb) 

ERComb = EMComb x F2 (technology impact factors for air heater and ESP) 

ERComb = EMComb x (0.49) x (0.49) 

Sulfuric Acid Manufactured by SCR (EMSCR) 

EMSCR = K * S2 * fs * E2 

where, 

EMSCR = Total sulfuric acid manufactured from SCR, lbs per year 

K = Conversion factor = 3063 

S2 = SCR catalyst SO2 oxidation rate (specified as a decimal) 

fs = Operating factor of SCR system, fraction of coal burn when SCR operates 

E2 = SO2 produced, tons per year 

Sulfuric Acid Released from SCR (ERSCR) 

ERSCR = [EMSCR – (Ks * B * fs * SNH3)] * F2x 

where, 

ERSCR = Total sulfuric acid released from SCR, lbs per year 

EMSCR = Total sulfuric acid manufactured from SCR, lbs per year 

Ks = Conversion factor = 3799 

B = Coal burn in TBtu/hr 

113006 Bowen BART Determination Modeling Protocol.doc A-2 November 2006
A-3 November 2006 113006 Bowen BART Determination Modeling Protocol.doc

fs = Operating factor of SCR system, fraction of coal burn when SCR operates 

SNH3 = NH3 slip from SCR, ppmv at 3% O2 

F2x = Technology Impact Factors, all that apply 

Sulfuric Acid Manufactured from Flue Gas Conditioning (EMfgc): 

EMfgc = Ke x B x fe x Is 

where, 

EMfgc = total sulfuric acid manufactured from flue gas conditioning system, lbs/hr 

Ke = Conversion Factor = 3,799 

B = Coal burn in TBtu/hr 

fe = Operating factor of FGC system, fraction of coal burned when FGC operates 

Is =SO3 injection rate in ppmv at 6% O2, wet 

Sulfuric Acid Released from FGC (ERfgc) 

ERfgc = [EMfgc – (Ke * B * fe * INH3)] * F3 x F2 

where, 

ERfgc = Total sulfuric acid released from FGC, lbs per hour 

EMfgc = Total sulfuric acid manufactured from FGC, lbs per hour 

Ke = Conversion factor = 3799 

B = Coal burn in TBtu/hr 

fe = Operating factor of FGC system, fraction of coal burn when FGC operates 

INH3 = NH3 injection for dual flue gas conditioning system, ppmv at 6% O2, wet (= 0 if no NH3 used) 

F3 = Technology Impact Factors for FGC 

F2 = Technology Impact Factors for equipment after ESP only

 If no control after ESP, F2 = 1 

Total Sulfuric Acid Released (TSAR): 

TSAR = ERComb + ERSCR + ERfgc[Bowen 3 and 4 only] 
November 2006

A-4 006 Bowen BART Determination Modeling Protocol.doc

Table A-1 Plant Bowen sulfuric acid calculations 

Case Source / Unit SO2 

Conv. 

Factor 

Fuel 

Impact 

Factor 

Manuf 

from 

Combut. 

APH 

Factor 

ESP 

Factor 

Released 

From 

Combust. 

SCR 

Oxid. 

Rate 

SCR 

Op. 

Factor 

Manuf by 

SCR Coal Burn, B C

F

lbs/hr K F1 lbs/hr F2 F2 lbs/hr S2 fs lbs/hr TBtu/hr 

EC NS Unit 1 17069.4 3063 0.008 209.1 0.49 0.49 50.2 0.0075 0 0.0 0.00684 EC S Unit 1 15374.2 3063 0.008 188.4 0.49 0.49 45.2 0.0075 1 176.6 0.00684 

Baseline S Unit 1 15374.2 3063 0.008 188.4 0.49 0.49 45.2 0.0075 1 176.6 0.00684 

EC NS Unit 2 17247.6 3063 0.008 211.3 0.49 0.49 50.7 0.0075 0 0.0 0.00669 EC S Unit 2 16059.4 3063 0.008 196.8 0.49 0.49 47.2 0.0075 1 184.5 0.00669 

Baseline S Unit 2 16059.4 3063 0.008 196.8 0.49 0.49 47.2 0.0075 1 184.5 0.00669 

EC NS Unit 3 20652.4 3063 0.008 253.0 0.49 0.49 60.8 0.0075 0 0.0 0.00772 EC S Unit 3 18519.4 3063 0.008 226.9 0.49 0.49 54.5 0.0075 1 212.7 0.00772 

Baseline S Unit 3 18519.4 3063 0.008 226.9 0.49 0.49 54.5 0.0075 1 212.7 0.00772 

EC NS Unit 4 20097.2 3063 0.008 246.2 0.49 0.49 59.1 0.0075 0 0.0 0.00843 EC S Unit 4 19504.1 3063 0.008 239.0 0.49 0.49 57.4 0.0075 1 224.0 0.00843 

Baseline S Unit 4 19504.1 3063 0.008 239.0 0.49 0.49 57.4 0.0075 1 224.0 0.00843 

EC= Existing Configuration (i.e., no scrubber) Baseline=Scrubbed NS = No SCR Operation S= SCR Operation 

Case Source / Unit 

Conv. 

Factor 

FGC 

Op. 

Factor 

SO3 

Injection 

Rate 

Manuf 

by 

FGC 

Tech 

Impact 

Factor 

for 

FGC 

Tech 

Impact 

Factor for 

Equip 

after ESP 

NH3 

Injection 

Rate 

Released 

From FGC 

Total 

Released 

without 

Scrubber 

Removal 

Rate for 

Scrubber 

Ke fe Is lbs/hr F3 F2 INH3 lbs/hr lbs/hr % 

EC NS Unit 1 n/a n/a n/a n/a n/a n/a n/a n/a 50.2 EC S Unit 1 n/a n/a n/a n/a n/a n/a n/a n/a 83.0 

Baseline S Unit 1 n/a n/a n/a n/a n/a n/a n/a n/a 83.0 40 

EC NS Unit 2 n/a n/a n/a n/a n/a n/a n/a n/a 50.7 EC S Unit 2 n/a n/a n/a n/a n/a n/a n/a n/a 87.0 

Baseline S Unit 2 n/a n/a n/a n/a n/a n/a n/a n/a 87.0 40 

EC NS Unit 3 3799 1.0 7.0 205.2 0.25 1.0 0.0 51.3 112.1 EC S Unit 3 3799 1.0 7.0 205.5 0.25 1.0 0.0 51.3 151.6 

Baseline S Unit 3 n/a n/a n/a n/a n/a n/a n/a n/a 100.3 40 

EC NS Unit 4 3799 1.0 7.0 224.3 0.25 1.0 0.0 56.1 115.2 EC S Unit 4 3799 1.0 7.0 224.3 0.25 1.0 0.0 56.1 161.5 

Baseline S Unit 4 n/a n/a n/a n/a n/a n/a n/a n/a 105.4 40 

EC= Existing Configuration (i.e., no scrubber) Baseline=Scrubbed NS = No SCR Operation S= SCR Operation 

113
Appendix B 

Estimated Emissions of Primary Total Carbon and Primary Sulfate 

From Coal-Fired Power Plants

[The above titled paper is included as a separate document along with 

this site specific BART modeling protocol. This paper was prepared for 

Southern Company by Eric S. Edgerton of Atmospheric Research & 

Analysis, Inc.] 

113006 Bowen BART Determination Modeling Protocol.doc B-1 November 2006
Estimated Emissions of Condensable Carbon and Condensable SO3

 From Coal-Fired Power Plants 

Prepared for 

John J. Jansen 

Southern Company 

Birmingham, AL 

Prepared by 

Eric S. Edgerton 

Atmospheric Research & Analysis, Inc. 

Cary, NC 

June 11, 2006 
 

2

ABSTRACT 

Data from the SEARCH network were used to estimate condensable carbon and condensable 

SO3 emissions from coal-fired power plants (CFPPs). Continuous trace gas and PM2.5 

measurements were used to identify CFPP plumes and to quantify incremental fine particulate 

total carbon (TC) and fine particulate total sulfate (SO4) during the period October 2005-May 

2006. As measured in the field, incremental TC includes emitted particulate OC, particulate EC 

and condensable carbon as well as secondary organic aerosol (SOA). Incremental SO4 includes 

emitted particulate SO4, condensable SO3, and secondary SO4. As such, TC and SO4 provide 

upper bounds for CFPP emissions of condensable carbon and condensable SO3. Plume events 

were selected so as to avoid confounding of TC and SO4 signals by other sources, and to 

minimize in-plume production of secondary SO4 and SOA. Results are presented as ratios 

relative to SO2, for example, pounds TC per pound SO2 (lb TC/lb SO2,). Plume increments can 

be interpreted as emission ratios for TC and primary SO4. For TC, 14 plume events from 4 sites 

and 7 CFPPs exhibited sufficiently stable data for analysis. Of these, 11 events yielded an 

average TC/SO2 emission ratio of 3.2 x 10-3 lb/lb (range 1.1 x 10-3 to 6.6 x 10-3). In other words, 

TC emissions represented about 0.32 percent of SO2 emissions, on a mass basis. The 3 

remaining events yielded negative emission ratios using the default approach, and an average 

emission ratio of 1.5 x 10-3 using an alternate approach. For SO4, a total of 20 events from 4 

sites and 8 CFPPs were analyzed. Results showed an average SO4/SO2 emission ratio of 6.4 x 

10-3 lb/lb (range 2.1 x 10-3 to 15.0 x 10-3). On average, SO4 was found to represent about 0.64 

percent of SO2 emissions during the study period. Inferred emission ratios should be considered 

upper bound estimates because: 1) the measurements include, in addition to the condensable 
 

3

carbon and condensable SO3 emissions of interest, primary particulate carbon (EC and OC) and 

primary particulate sulfate emitted by the CFPP; 2) may include secondary carbon and 

secondary sulfate produced in the atmosphere; and 3) could be inflated due to preferential loss 

of SO2 from the plume (due to conversion and/or dry deposition) in transit from the CFPP to the 

research site. 

INTRODUCTION

The Southeastern Aerosol Research and Characterization Study (SEARCH) was designed to 

provide extensive, long-term data on the sources and chemical characteristics of PM2.5 and 

PMcoarse for the southeastern U. S. SEARCH is unique in that continuous PM2.5 measurements of 

all major components are made at urban/rural pairs of sites in and around four southeastern U. S. 

cities. In conjunction with co-measured meteorological and trace gas data, continuous PM2.5 

measurements provide opportunities for: (1) investigating sources and physico-chemical 

dynamics of PM2.5; (2) evaluating chemical transport and transformation models; (3) assessing 

the effectiveness of emissions reduction programs; and (4) examining relationships between PM 

mass and composition and various health end points. 

CFPPs emit three forms of primary particulate carbon to the atmosphere: filterable organic 

carbon (OC), filterable elemental carbon (EC) and condensable carbon. OC and EC are emitted 

as particles, while condensable carbon is emitted in the vapor phase and is presumed to condense 

rapidly onto pre-existing particles. These three forms of carbon, plus secondary organic aerosol 
 

4

(SOA), are measured collectively in the SEARCH network, as total carbon (TC), using 

continuous measurement techniques. CFPPs also emit two forms of primary particulate sulfate: 

filterable sulfate and condensable sulfur trioxide (SO3). In the atmosphere, condensable SO3

reacts more or less instantaneously with water vapor to produce particulate sulfate. These forms 

of sulfate, plus secondary sulfate from oxidation of SO2, are also measured in the SEARCH 

network using continuous techniques. 

This report uses SEARCH data to: (1) identify CFPP plumes observed at numerous sites during 

the fall of 2005 through spring of 2006; and, (2) calculate total carbon (TC) and total sulfate 

(SO4) associated with such plumes. Results are used to estimate CFPP emission ratios of TC and 

SO4, relative to SO2. Given that the measurement techniques do not discriminate between the 

various form of particulate carbon and particulate sulfate present in the plume, results can be 

used as upper bound estimates of emission ratios for condensable carbon and condensable SO3. 

EXPERIMENTAL 

Continuous measurements of trace gases fine particulate TC and fine particulate SO4 were made 

at the Southeastern Aerosol Research and Characterization (SEARCH) sites shown in Figure 1. 

Analyzable plume events were observed at 5 of the 8 SEARCH sites between early October 2005 

and early May 2006: Yorkville, GA; Jefferson Street, GA; Centreville, AL; OLF, FL; and 

Gulfport, MS. Brief descriptions for these 5 sites are provided below. 
 

5

Yorkville, GA - Yorkville (lat. 33.9283 N, long. 85.0456 W) is a rural/agricultural site 55 km 

WNW and 40 km SSW of Atlanta, GA and Rome, GA, respectively. The site is on a broad ridge 

(elev. 395 m) in a large (>150 ha) clearing devoted largely to pasture. CFPPs in the vicinity of 

Yorkville are shown in Figure 2. 

Centreville, AL – Centreville (lat. 32.9029 N, long. 87.2497 W) is located on private property in 

rural Bibb County, approximately 85 km SSW of Birmingham, AL. The surrounding area 

includes the Talladega National Forest and is heavily wooded with mixed deciduous (oakhickory) and loblolly pine. CFPPs in the vicinity of Centreville are shown in Figure 2. 

Jefferson Street (Atlanta), GA - Jefferson Street (lat. 33.7775 N, long. 84.4167 W) is an 

urban/industrial-residential site 4.5 kilometers NW of downtown Atlanta, GA. The site is 

located at 829 Jefferson Street NW, on Georgia Power Company property in a 70m by 125m 

grass-covered clearing on a knoll 15 meters above street level. CFPPs in the vicinity of Jefferson 

Street are shown in Figure 3. 

Outlying Landing Field #8 (OLF), FL - OLF (lat. 30.5496 N, long. 87.3734 W) is a suburban 

site 21 km NW of downtown Pensacola, FL and 20 km N of the Gulf of Mexico. The site is 

adjacent to a paved, lightly traveled (< 200 vehicles/day) road on the northern edge of a large 

(>500 ha) grass-covered field. CFPPs in the vicinity of OLF are shown in Figure 3. 
 

6

Gulfport, MS – Gulfport (lat. 30.3901 N, long. 89.0498 W) is located 1.5 km from the Gulf of 

Mexico on the premises of the Harrison County Youth Court at 47 Maples Ave. The area is 

covered with sparse forest and grass, with single family homes to the east, an elementary school 

to the north and athletic fields to the south. CFPPs in the vicinity of OLF are shown in Figure 3. 

Continuous Trace Gas and Particle Measurements 

SO2, NOy and CO are measured at each site and used to: 1) screen for periods of influence from 

point sources (specifically CFPPs) and non-point sources; 2) identify specific CFPPs based on 

SO2:NOy ratios; and 3) calculate TC/SO2 and SO4/SO2 ratios. Continuous (1-minute average) 

measurements were made at a reference height of 10 m above ground level. Sample air is pulled 

through a weather-proof inlet box and then into the equipment shelter via 1⁄4” o.d. heavy wall 

PFA Teflon tubing. The inlet box contains catalytic converters (for NOy), solenoids and 

plumbing for introduction of zero air and calibrant gases. Calibration gases (+/- 1% for CO and 

NO and +/- 2% for SO2) were supplied by Scott-Marrin, Inc. (Riverside, CA). 

SO2 is measured via pulsed UV fluorescence with a TEI Model 43ctl analyzer operated on a 0-

200 ppb scale. The instrument is calibrated every third day by gas replacement and zeroed 10 

out of every 90 minutes by diverting sample air through a sodium carbonate impregnated annular 

denuder (URG, Carrboro, NC). The analyzer is also subjected to weekly multipoint gas 

replacement calibrations (GRC). 
 

7

CO is measured via gas filter correlation with non-dispersive infrared detection using a TEI 

Model 48ctl analyzer operated on a 0-3000 ppb scale (0-10,000 ppb at JST). The analyzer is 

calibrated and zeroed on the same schedule as the SO2 analyzer. Zeroing is performed by 

diverting the sample stream through a heated (50-100C) trap containing approximately 200 

grams of 1% Pt on alumina (DeGussa, Seviersville, TN). 

NOy is measured via ozone-NO chemiluminescence following reduction to NO on a 350 oC Mo 

catalytic converter, using a dual-channel TEI Model ctl NO-NOx analyzer operated on a 0-200 

ppb scale. The analyzer is zeroed four times per day and calibrated every third day via gas 

replacement. Converter efficiency is checked once a week with n-propyl nitrate. 

SO4 is measured continuously using a variation of the Harvard School of Public Health (HSPH) 

approach. This method uses a 1000 °C inconel steel tube to reduce particulate SO4 to sulfur 

dioxide (SO2). The SO2 is then detected using a Thermo-Environmental Instruments (TEI, 

Franklin, MA) Model 43S or 43Ctl high sensitivity, pulsed ultra-violet fluorescence SO2

analyzer. Sample air is pulled through a 2.5 μm sharp-cut cyclone inlet (BGI, Atlanta, GA), then 

through two 30 mm o.d., 254 mm long sodium carbonate and citric acid coated annular denuders 

(URG, Carrboro, NC) followed by a 30 mm o.d., 100 mm long carbon honeycomb denuder 

(MAST Carbon Ltd., Surrey, UK). The denuders effectively remove a wide range of 

interferents, including SO2, reduced sulfur gases, nitrogen oxides and volatile organic 

compounds. Sample air then passes through a 300 mm section of inconel tubing heated to 1000 

°C in a Lindberg/Blue M horizontal tube furnace. Every 90 minutes, the system is zeroed for 10 
 

8

minutes by diverting sample air through an inline filter upstream of the converter. The SO2

analyzer is subjected to manual and automated gas replacement audits on a weekly schedule. 

Total carbon (TC) is measured continuously with a Sunset Laboratory Model RT-OCEC Aerosol 

Carbon Analyzer. This device operates on an hourly cycle, with 47 minutes devoted to sample 

collection and 13 minutes devoted to sample analysis. In sample mode, ambient air is pulled 

through an activated carbon monolith denuder (NovacarbTM, Mast Carbon Ltd., UK) at a flow 

rate of 8.5 lpm, then through dual quartz fiber filters. In analysis mode, the filters are heated 

through several temperature plateaus to a final temperature of 900 oC. CO2 produced during the 

heating cycle is quantified with a non-dispersive infra-red (NDIR) detector and TC is calculated 

based on CO2 produced and sample volume. The TC analyzer is automatically calibrated with 

5% methane in helium after every analysis cycle.

Trajectory Calculations 

Twenty-four hour back trajectories are generated using the interactive version of the NOAA 

HYSPLIT4 model on the NOAA-ARL web site (12). Back trajectories use EDAS 40 km 

meteorological data and default vertical motion, with starting heights of 1000 m, 500 m and 250 

m, for the time (hour) of peak SO2 concentration during each event. The 250 m trajectory is 

used to determine which CFPP affected the site, as well as time of emission at the CFPP. 
 

9

Event Selection and Data Reduction 

Event selection attempted to identify episodes with minimal contamination from non-CFPP 

sources. In general, this means that different episodes are used for TC and SO4 analyses. For 

TC, we look for clean, well-ventilated conditions during the middle of the day, with low and 

stable CO concentrations. This avoids rush hour emissions and near-surface sources that tend to 

accumulate under the nocturnal boundary layer. While some VOC to SOA conversion is 

possible, the effect should be small during fall and winter because of: 1) low biogenic precursor 

emissions; and 2) low temperatures; and 3) low solar insolation. For SO4, in contrast, we are less 

concerned with contamination from non-CFPP sources, but want to avoid strong sunlight and 

consequent photochemical production of secondary SO4 within the plume. Thus, the majority of 

SO4 events selected for this analysis occurred either at night or during the early morning hours. 

TC emission ratios are calculated using the “ratio of deltas” method, as shown below, 

ERTC = (TCPlume-TCBase)/(SO2Plume-SO2Base) = ΔTC/ΔSO2, (Eq. 1) 

where subscripts Plume and Base refer to concentrations measured during the plume event and 

before or after the event, respectively. The technique is illustrated in Figure 4, which shows an 

event that occurred at Yorkville on April 9, 2006. The upper panel shows SO2 and CO during 

the course of the day. Note that the regular gaps in the time series reflect zeroing cycles. SO2

concentrations were <5 ppb until about 1430 local standard time (LST), when they increased 

sharply and remained above 40 ppb until about 1630, then fell below 5 ppb for the remainder of 
 

10

the day. CO concentrations were between 80 and 100 ppb for the entire day, indicating no 

evidence of plumes from biomass burning, transportation and other activities. 

The lower panel shows time series for SO2 (red symbols) and TC (black bars), also for April 9, 

2006. In this case, SO2 concentrations have been averaged to coincide exactly with the 47-

minute Sunset collection period. The plume event is shown in the red box and the downward 

facing arrows indicate the two values used (i.e., averaged) to calculate Base concentration. The 

symbols and bars at 1500 LST and 1600 LST are averaged to calculate Plume concentration. 

Base and Plume concentrations are then used to calculate the ratio of deltas, as shown in 

Equation 1. Note that ΔTC during this event (0.22 μg/m3

) is quite small compared to the overall 

range of TC observed during the day, despite the fact that average SO2 concentrations exceeded 

75 ppb for the 47-minute period beginning at 1600 LST. This is typical of CFPP plume events 

and underscores the fact that CFPPs are minor sources of particulate carbon. In other words, 

large plumes are needed in order to even “see” an increase in TC. The small increment of TC 

associated with CFPP events places a high premium on stable TC measurements. 

For several CFPP events, ΔTC was negative, indicating that Base concentrations were slightly 

higher than the Plume concentrations. Based on Equation 1, this implies a physically unrealistic 

negative ER. For these events, we used the detection limit for the Sunset analyzer (0.1 μg/m3) in 

the numerator of Equation 1. 
 

11

SO4 emission ratios are calculated by linear least square regression of 1-minute SO4

concentrations versus 1-minute SO2 concentrations. The regression slope is equivalent to the 

primary SO4/SO2 emission ratio and the intercept is equivalent to the baseline SO4 concentration 

in absence of the plume. Figure 5 illustrates an example SO4 event which occurred at Yorkville 

on February 25, 2006. In the upper panel, SO2 concentration is < 5 ppb until approximately 

0400 (LST), increases to nearly 50 ppb just before 0600, then falls below 5 ppb by 0900. SO4

concentrations (right hand scale) are < 1 ppb (3.9 μg/m3

) the entire day, but show several minor 

excursions, some of which are associated with SO2 excursions and some of which are not. The 

lower panel shows the scattergram of SO4 versus SO2 and associated regression statistics. Data 

for the regression correspond to the red box in the upper panel. Results show a highly significant 

relationship between SO4 and SO2 (p<0.01) with a regression slope of 0.0042 on a ppb/ppb basis. 

Given that the molecular weight of SO4 is 1.5 times that of SO2, the emission ratio for this event 

is 0.0063 lb/lb or 0.63 %. 

It should be noted that both the ratio of deltas approach and the linear regression approach give 

upper bound estimates of TC and SO4. The principal reason for this is dry deposition, which 

removes gaseous SO2 from the plume much faster than particles. If we assume dry deposition to 

be a first order loss process, then the effect is to reduce ΔSO2 in the denominator of equation 1 

and thereby inflate the ratio ΔTC/ΔSO2. Another reason is photochemical or non-photochemical 

production of secondary SO4 and OC, which would increase SO4 and, at the same time, decrease 

SO2 in the plume. Although events have been carefully selected to minimize these effects, we 

cannot be certain they have been eliminated completely. 
 

12

RESULTS 

Table 1 summarizes results for 14 TC plume events observed at 4 sites. Data include the site 

which observed the CFPP plume, the likely source of the plume (based on trajectory analyses 

and SO2/NOy ratios) and concentration data for the ratio of deltas calculation. Mean ΔTC/ΔSO2

for 11 events is 0.0032 +/- 0.0014 with a range of 0.0011 to 0.0066. OLF and Yorkville both 

observed 5 events. At OLF, all 5 events were from the Crist CFPP and these gave an emission 

ratio of 0.0020 +/- 0.0012 lb/lb. At Yorkville, the plume events likely originated from 3 different 

CFPPs and these gave an average ratio of 0.0033 +/- 0.0021 lb/lb. These events clearly show 

that TC is a small and difficult to detect component of CFPP emissions.

Table 2 summarizes results for 20 SO4 plume events observed at 4 sites and likely originating 

from 8 different CFPPs. Data include the maximum observed 1-minute SO2 concentration, plus 

the regression slope and r-squared for SO4 vs. SO2. Calculated values for ΔSO4/ΔSO2 range 

from 0.0030 to 0.0180 lb/lb with an average of 0.0064 lb/lb. In most cases, the regression is 

highly significant; however, r-square tends to decrease as slope decreases because instrument 

noise starts to dominate the SO4 signal. These events clearly show that SO4 is a small and 

difficult to detect component of CFPP emissions.

CONCLUSIONS 

Continuous field measurements can be used to derive emission estimates for TC and SO4 from 

CFPPs which are upper bound estimates of condensable carbon and condensable SO3. Careful 

attention must be paid to plume event selection in order to avoid contamination from non-CFPP 
 

13

sources (TC) and photochemical activity in the CFPP plume (SO4). Optimal conditions for both 

TC and SO4 estimates appear to occur during the cooler months when photochemical activity is 

low and persistent winds advect relatively fresh CFPP plumes to the research sites. Plume 

analysis results show that primary TC emissions and primary SO4 emissions from CFPPs are 

well below 1% of SO2 on a mass basis. For primary TC, analysis of 14 events from 7 different 

CFPPs gave an overall average emission ratio of 0.0032 lb TC/lb SO2 (or 0.32% of SO2. For

primary SO4, analysis of 20 events from 8 different CFPPs gave an overall average emission 

ratio of 0.0064 lb SO4/lb SO2 (or 0.64% of SO2). 
Figure 1. The SEARCH Network 

35.0 

32.5 

30.0 

90.0 87.5 85.0 82.5 

 

14
Figure 2. CFPPs observed at YRK (top) and CTR (bottom). 
Figure 3. CFPPs observed at JST (top), OLF (middle) and GFP (bottom). 

 

16
Figure 4. CFPP plume event at YRK showing 1-minute SO2 and CO (top), 47-minute SO2 and TC (bottom). 

0

40

80

120

160

200

4/9/06 0:00 4/9/06 3:00 4/9/06 6:00 4/9/06 9:00 4/9/06 12:00 4/9/06 15:00 4/9/06 18:00 4/9/06 21:00

SO2 (ppb)

0

80

160

240

320

400

CO (ppb)

SO2 CO

0

10

20

30

40

50

60

70

80

4/9/06 0:00 4/9/06 3:00 4/9/06 6:00 4/9/06 9:00 4/9/06 12:00 4/9/06 15:00 4/9/06 18:00 4/9/06 21:00

SO2 (ug/m3)

0

1

2

3

4

TC (ug/m3)

Sunset TC SO2

 

17
Figure 5. CFPP plume event at YRK showing SO2 and SO4 (top) and SO4 vs. SO2 (bottom).

0

10

20

30

40

50

2/25/06 0:00 2/25/06 3:00 2/25/06 6:00 2/25/06 9:00 2/25/06 12:00 2/25/06 15:00 2/25/06 18:00 2/25/06 21:00

SO2 (ppb) .

0

1

2

3

4

5

SO4 (ppb) .

SO2 SO4 ZERO

SO4 = 0.0042*SO2 + 0.43

R2

 = 0.68

0.00

0.25

0.50

0.75

1.00

1.25

0 10 20 30 40 50 60

SO2 (ppb) .

SO4 (ppb) .

 

18
 

19

Table 1. Summary of Total Carbon Events.

Site Date 

Probable 

CFPP 

Base 

SO2

(ppb) 

Plume 

SO2

(ppb) 

Base TC 

(μg/m3) 

Plume 

TC 

(μg/m3) 

ΔTC/ΔSO2

(lb/lb) 

Alternate 

ΔTC/ΔSO2

(lb/lb) 

CTR 12/18/05 Gaston 15.6 51.2 2.96 3.30 3.7 x 10-3

CTR 12/20/05 Gorgas 15.1 23.1 1.30 1.38 3.8 x 10-3

CTR 02/23/06 Miller 5.1 20.6 1.71 1.49 < 0 2.5 x 10-3

JST 05/06/06 McDonough 3.5 64.5 3.35 3.6 1.6 x 10-3

OLF 11/25/05 Crist 11.9 38.9 2.22 2.38 2.3 x 10-3

OLF 02/07/06 Crist 4.2 34.6 2.22 2.38 2.0 x 10-3

OLF 02/24/06 Crist 11.1 35.0 1.48 1.70 3.5 x 10-3

OLF 04/28/06 Crist 4.3 41.2 3.53 3.48 < 0 1.2 x 10-3

OLF 05/06/06 Crist 3.3 85.3 3.31 3.55 1.1 x 10-3

YRK 10/31/05 McDonough 6.3 48.8 2.72 3.45 6.59 x 10-3

YRK 02/25/06 Bowen 4.7 39.5 2.24 2.52 3.08 x 10-3

YRK 03/04/06 Bowen 5.5 33.4 3.49 3.72 3.15 x 10-3

YRK 03/11/06 Wansley 1.8 52.2 4.06 3.87 < 0 7.6 x 10-4

YRK 04/09/06 Bowen 1.7 61.6 2.12 2.34 3.63 x 10-3

Mean 

(s.d.) 

3.2 x 10-3 

(1.4 x 10-3) 

1.5 x 10-3

(0.9 x 10-3) 

Note: Base and Peak concentrations based on 47-minute averages. 
Table 2. Summary of SO4 Events. 

Site Date 

Probable 

CFPP 

1-min Max. 

SO2

(ppb) 

SO4 vs. SO2

Slope 

SO4 vs. SO2

R2

ΔSO4/ΔSO2

(lb/lb) 

CTR 12/07/05 Gorgas 49.7 5.6 x 10-3 0.77 8.4 x 10-3

CTR 12/17/05 Gorgas 21.4 2.0 x 10-3 0.02 3.0 x 10-3

CTR 12/17/05 Miller 29.6 2.5 x 10-3 0.09 3.7 x 10-3

CTR 12/18/05 Gaston 55.3 4.4 x 10-3 0.70 6.6 x 10-3

CTR 12/19/05 Gorgas 30.1 3.6 x 10-3 0.13 5.4 x 10-3

CTR 12/20/05 Gorgas 43.3 5.9 x 10-3 0.81 8.9 x 10-3

CTR 01/27/06 Miller 20.2 5.1 x 10-3 0.20 7.7 x 10-3

GFP 01/26/06 Watson 137.1 3.8 x 10-3 0.95 5.7 x 10-3

GFP 02/19/06 Watson 49.9 3.6 x 10-3 0.34 5.4 x 10-3

OLF 11/19/05 Crist 42.8 2.5 x 10-3 0.08 3.7 x 10-3

OLF 02/07/06 Crist 52.1 1.4 x 10-3 0.02 2.1 x 10-3

OLF 02/24/06 Crist 59.1 4.3 x 10-3 0.29 6.5 x 10-3

OLF 4/13/06 Crist 186. 5.4 x 10-3 0.68 8.1 x 10-3

YRK 10/09/05 Bowen 33.8 1.2 x 10-3 0.10 1.8 x 10-3

YRK 10/31/05 McDonough 73.4 10.0 x 10-3 0.90 15.0 x 10-3

YRK 11/11/05 McDonough 48.3 3.3 x 10-3 0.43 4.9 x 10-3

YRK 12/18/05 Bowen 202.8 6.6 x 10-3 0.96 9.9 x 10-3

YRK 02/08/06 Hammond 31.2 7.6 x 10-3 0.64 11.4 x 10-3

YRK 02/25/06 Bowen 47.4 4.4 x 10-3 0.69 6.6 x 10-3

YRK 03/04/06 Bowen 60.9 2.4 x 10-3 0.09 3.6 x 10-3

Mean 

(s.d.) 

6.4 x 10-3

(3.3 x 10-3) 
Appendix E 

Determination Modeling 

Delta-Deciview Values for the Top 20 Days – for Each Year/Each 

Class I Area and for the Top 25 Days – Over Three Years 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 20 Days Each Year) 

Bowen 1-4 Results - Unit 1 Controlled with Agglomerator/Juice Can 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.30 7.94 1.36 3.8 2.9 4.3 73.7 0.0 20.1 1.1 2.2 3.0 1 

2001 113 1 8.59 7.60 0.98 2.8 2.3 3.6 67.9 0.0 24.4 1.4 2.7 3.6 2 

2001 225 3 9.27 8.33 0.93 4.9 3.5 5.1 78.4 0.0 16.4 1.0 1.8 2.4 3 

2001 297 3 8.97 8.10 0.87 4.2 3.2 4.6 75.9 0.0 18.4 1.1 1.9 2.8 4 

2001 114 4 8.42 7.60 0.82 2.8 2.3 3.6 68.2 0.0 24.5 1.4 2.3 3.6 5 

2001 279 1 8.87 8.10 0.76 4.2 3.2 4.6 75.9 0.0 18.4 1.0 2.0 2.7 6 

2001 220 54 9.09 8.33 0.76 4.9 3.5 5.1 78.5 0.0 16.4 1.0 1.7 2.5 7 

2001 111 16 8.33 7.60 0.73 2.8 2.3 3.6 68.1 0.0 24.5 1.4 2.4 3.6 8 

2001 294 1 8.78 8.10 0.68 4.2 3.2 4.6 75.8 0.0 18.3 1.0 2.1 2.8 9 

2001 51 8 8.38 7.72 0.67 3.2 2.5 3.8 70.3 0.0 22.8 1.2 2.3 3.3 10 

2001 102 9 8.19 7.60 0.59 2.8 2.3 3.6 68.1 0.0 24.5 1.3 2.5 3.6 11 

2001 229 16 8.88 8.33 0.55 4.9 3.5 5.1 78.8 0.0 16.5 0.9 1.3 2.4 12 

2001 110 3 8.12 7.60 0.51 2.8 2.3 3.6 68.1 0.0 24.5 1.4 2.4 3.6 13 

2001 142 3 8.34 7.87 0.47 3.6 2.8 4.1 73.1 0.0 20.9 1.2 1.8 3.1 14 

2001 112 35 8.07 7.60 0.47 2.8 2.3 3.6 68.2 0.0 24.5 1.4 2.3 3.6 15 

2001 343 97 8.40 7.94 0.46 3.8 2.9 4.3 73.6 0.0 20.0 1.2 2.1 3.1 16 

2001 158 25 8.56 8.10 0.45 4.2 3.2 4.6 75.9 0.0 18.4 1.0 2.1 2.6 17 

2001 126 3 8.31 7.87 0.44 3.6 2.8 4.1 72.9 0.0 20.8 1.2 2.0 3.1 18 

2001 236 25 8.77 8.33 0.43 4.9 3.5 5.1 78.4 0.0 16.4 0.9 1.9 2.4 19 

2001 198 9 8.62 8.21 0.41 4.5 3.3 4.9 77.2 0.0 17.5 1.0 1.7 2.7 20 

 

2002 224 3 9.66 8.33 1.32 4.9 3.5 5.1 78.4 0.0 16.4 0.9 1.8 2.4 1 

2002 15 16 9.06 7.82 1.25 3.4 2.7 4.0 72.0 0.0 21.5 1.2 2.2 3.1 2 

2002 227 8 9.51 8.33 1.18 4.9 3.5 5.1 78.5 0.0 16.4 0.9 1.7 2.4 3 

2002 365 16 9.08 7.94 1.14 3.8 2.9 4.3 73.6 0.0 20.0 1.2 2.2 3.0 4 

2002 67 3 8.71 7.67 1.04 3.0 2.5 3.7 69.3 0.0 23.4 1.3 2.5 3.4 5 

2002 228 97 9.33 8.33 0.99 4.9 3.5 5.1 78.5 0.0 16.4 0.9 1.7 2.5 6 

2002 230 3 9.31 8.33 0.97 4.9 3.5 5.1 78.4 0.0 16.4 0.9 1.8 2.4 7 

2002 226 97 9.27 8.33 0.94 4.9 3.5 5.1 78.4 0.0 16.4 0.9 1.8 2.4 8 

2002 314 2 8.75 7.87 0.88 3.6 2.8 4.1 72.7 0.0 20.8 1.2 2.3 3.1 9 

2002 35 9 8.56 7.72 0.84 3.2 2.5 3.8 70.1 0.0 22.7 1.2 2.6 3.3 10 

2002 222 16 9.12 8.33 0.79 4.9 3.5 5.1 78.8 0.0 16.5 0.9 1.4 2.4 11 

2002 28 3 8.58 7.82 0.76 3.4 2.7 4.0 71.9 0.0 21.5 1.2 2.2 3.2 12 

2002 107 97 8.32 7.60 0.71 2.8 2.3 3.6 67.9 0.0 24.4 1.4 2.6 3.7 13 

2002 207 9 8.89 8.21 0.69 4.5 3.3 4.9 77.3 0.0 17.5 1.0 1.5 2.7 14 

2002 85 97 8.24 7.67 0.56 3.0 2.5 3.7 69.4 0.0 23.4 1.3 2.5 3.5 15 

2002 323 3 8.42 7.87 0.55 3.6 2.8 4.1 72.7 0.0 20.8 1.2 2.3 3.1 16 

2002 105 8 8.13 7.60 0.52 2.8 2.3 3.6 68.1 0.0 24.5 1.3 2.4 3.6 17 

2002 191 16 8.72 8.21 0.51 4.5 3.3 4.9 77.6 0.0 17.5 0.9 1.3 2.6 18 

2002 128 3 8.37 7.87 0.50 3.6 2.8 4.1 72.6 0.0 20.8 1.2 2.3 3.1 19 

2002 106 8 8.08 7.60 0.47 2.8 2.3 3.6 67.8 0.0 24.4 1.4 2.7 3.7 20 

 

2003 271 3 9.29 8.33 0.96 4.9 3.5 5.1 78.5 0.0 16.4 0.9 1.7 2.4 1 

2003 270 1 9.28 8.33 0.94 4.9 3.5 5.1 78.5 0.0 16.4 0.9 1.7 2.5 2 

2003 178 3 8.79 8.10 0.69 4.2 3.2 4.6 75.8 0.0 18.3 1.0 2.1 2.8 3 

2003 356 16 8.60 7.94 0.67 3.8 2.9 4.3 73.7 0.0 20.0 1.1 2.2 3.0 4 

2003 68 3 8.32 7.67 0.65 3.0 2.5 3.7 69.1 0.0 23.3 1.3 2.7 3.5 5 

2003 246 3 8.98 8.33 0.64 4.9 3.5 5.1 78.6 0.0 16.5 0.9 1.5 2.5 6 

2003 107 1 8.23 7.60 0.62 2.8 2.3 3.6 68.0 0.0 24.5 1.3 2.5 3.7 7 

2003 163 3 8.69 8.10 0.58 4.2 3.2 4.6 76.0 0.0 18.4 1.1 1.8 2.7 8 

2003 164 97 8.68 8.10 0.58 4.2 3.2 4.6 76.0 0.0 18.4 1.1 1.8 2.7 9 

2003 187 3 8.79 8.21 0.58 4.5 3.3 4.9 77.0 0.0 17.4 1.0 2.0 2.6 10 

2003 35 10 8.24 7.72 0.53 3.2 2.5 3.8 70.2 0.0 22.8 1.3 2.3 3.3 11 

2003 242 16 8.84 8.33 0.50 4.9 3.5 5.1 78.6 0.0 16.4 0.9 1.5 2.5 12 

2003 160 3 8.59 8.10 0.49 4.2 3.2 4.6 75.7 0.0 18.3 1.1 2.2 2.8 13 

2003 326 1 8.35 7.87 0.48 3.6 2.8 4.1 72.5 0.0 20.7 1.1 2.5 3.1 14 

2003 247 97 8.81 8.33 0.47 4.9 3.5 5.1 78.8 0.0 16.5 0.9 1.3 2.5 15 

2003 304 1 8.56 8.10 0.46 4.2 3.2 4.6 75.9 0.0 18.4 1.0 2.0 2.7 16 

2003 108 3 8.05 7.60 0.45 2.8 2.3 3.6 68.0 0.0 24.5 1.4 2.5 3.7 17 

2003 259 3 8.78 8.33 0.44 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.9 2.4 18 

2003 197 9 8.65 8.21 0.44 4.5 3.3 4.9 77.0 0.0 17.5 1.0 2.0 2.5 19 

2003 166 46 8.53 8.10 0.43 4.2 3.2 4.6 75.9 0.0 18.4 1.0 1.9 2.8 20 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 25 Days for 3 Years) 

Bowen 1-4 Results - Unit 1 Controlled with Agglomerator/Juice Can 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.30 7.94 1.36 3.8 2.9 4.3 73.7 0.0 20.1 1.1 2.2 3.0 1 

2002 224 3 9.66 8.33 1.32 4.9 3.5 5.1 78.4 0.0 16.4 0.9 1.8 2.4 2 

2002 15 16 9.06 7.82 1.25 3.4 2.7 4.0 72.0 0.0 21.5 1.2 2.2 3.1 3 

2002 227 8 9.51 8.33 1.18 4.9 3.5 5.1 78.5 0.0 16.4 0.9 1.7 2.4 4 

2002 365 16 9.08 7.94 1.14 3.8 2.9 4.3 73.6 0.0 20.0 1.2 2.2 3.0 5 

2002 67 3 8.71 7.67 1.04 3.0 2.5 3.7 69.3 0.0 23.4 1.3 2.5 3.4 6 

2002 228 97 9.33 8.33 0.99 4.9 3.5 5.1 78.5 0.0 16.4 0.9 1.7 2.5 7 

2001 113 1 8.59 7.60 0.98 2.8 2.3 3.6 67.9 0.0 24.4 1.4 2.7 3.6 8 

2002 230 3 9.31 8.33 0.97 4.9 3.5 5.1 78.4 0.0 16.4 0.9 1.8 2.4 9 

2003 271 3 9.29 8.33 0.96 4.9 3.5 5.1 78.5 0.0 16.4 0.9 1.7 2.4 10 

2003 270 1 9.28 8.33 0.94 4.9 3.5 5.1 78.5 0.0 16.4 0.9 1.7 2.5 11 

2002 226 97 9.27 8.33 0.94 4.9 3.5 5.1 78.4 0.0 16.4 0.9 1.8 2.4 12 

2001 225 3 9.27 8.33 0.93 4.9 3.5 5.1 78.4 0.0 16.4 1.0 1.8 2.4 13 

2002 314 2 8.75 7.87 0.88 3.6 2.8 4.1 72.7 0.0 20.8 1.2 2.3 3.1 14 

2001 297 3 8.97 8.10 0.87 4.2 3.2 4.6 75.9 0.0 18.4 1.1 1.9 2.8 15 

2002 35 9 8.56 7.72 0.84 3.2 2.5 3.8 70.1 0.0 22.7 1.2 2.6 3.3 16 

2001 114 4 8.42 7.60 0.82 2.8 2.3 3.6 68.2 0.0 24.5 1.4 2.3 3.6 17 

2002 222 16 9.12 8.33 0.79 4.9 3.5 5.1 78.8 0.0 16.5 0.9 1.4 2.4 18 

2002 28 3 8.58 7.82 0.76 3.4 2.7 4.0 71.9 0.0 21.5 1.2 2.2 3.2 19 

2001 279 1 8.87 8.10 0.76 4.2 3.2 4.6 75.9 0.0 18.4 1.0 2.0 2.7 20 

2001 220 54 9.09 8.33 0.76 4.9 3.5 5.1 78.5 0.0 16.4 1.0 1.7 2.5 21 

2001 111 16 8.33 7.60 0.73 2.8 2.3 3.6 68.1 0.0 24.5 1.4 2.4 3.6 22 

2002 107 97 8.32 7.60 0.71 2.8 2.3 3.6 67.9 0.0 24.4 1.4 2.6 3.7 23 

2003 178 3 8.79 8.10 0.69 4.2 3.2 4.6 75.8 0.0 18.3 1.0 2.1 2.8 24 

2002 207 9 8.89 8.21 0.69 4.5 3.3 4.9 77.3 0.0 17.5 1.0 1.5 2.7 25 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 20 Days Each Year)

Bowen 1-4 Results - Unit 2 Controlled with Agglomerator/Juice Can 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.30 7.94 1.36 3.8 2.9 4.3 73.7 0.0 20.1 1.1 2.2 3.0 1 

2001 113 1 8.59 7.60 0.98 2.8 2.3 3.6 67.9 0.0 24.4 1.4 2.7 3.6 2 

2001 225 3 9.27 8.33 0.93 4.9 3.5 5.1 78.4 0.0 16.4 1.0 1.8 2.4 3 

2001 297 3 8.97 8.10 0.87 4.2 3.2 4.6 76.0 0.0 18.4 1.1 1.9 2.7 4 

2001 114 4 8.42 7.60 0.82 2.8 2.3 3.6 68.2 0.0 24.5 1.4 2.3 3.6 5 

2001 279 1 8.87 8.10 0.76 4.2 3.2 4.6 75.9 0.0 18.4 1.0 2.0 2.7 6 

2001 220 54 9.09 8.33 0.76 4.9 3.5 5.1 78.5 0.0 16.4 1.0 1.6 2.5 7 

2001 111 16 8.33 7.60 0.73 2.8 2.3 3.6 68.1 0.0 24.5 1.4 2.4 3.6 8 

2001 294 1 8.78 8.10 0.68 4.2 3.2 4.6 75.9 0.0 18.3 1.0 2.0 2.8 9 

2001 51 8 8.38 7.72 0.67 3.2 2.5 3.8 70.3 0.0 22.8 1.2 2.3 3.3 10 

2001 102 9 8.19 7.60 0.59 2.8 2.3 3.6 68.1 0.0 24.5 1.3 2.5 3.6 11 

2001 229 16 8.88 8.33 0.55 4.9 3.5 5.1 78.8 0.0 16.5 0.9 1.3 2.4 12 

2001 110 3 8.12 7.60 0.51 2.8 2.3 3.6 68.1 0.0 24.5 1.4 2.4 3.6 13 

2001 142 3 8.34 7.87 0.47 3.6 2.8 4.1 73.2 0.0 20.9 1.2 1.7 3.1 14 

2001 112 35 8.07 7.60 0.47 2.8 2.3 3.6 68.2 0.0 24.5 1.4 2.3 3.6 15 

2001 343 97 8.39 7.94 0.46 3.8 2.9 4.3 73.7 0.0 20.1 1.2 2.1 3.0 16 

2001 158 25 8.56 8.10 0.45 4.2 3.2 4.6 75.9 0.0 18.4 1.0 2.1 2.6 17 

2001 126 3 8.31 7.87 0.44 3.6 2.8 4.1 72.9 0.0 20.8 1.2 2.0 3.1 18 

2001 236 25 8.77 8.33 0.43 4.9 3.5 5.1 78.4 0.0 16.4 0.9 1.9 2.4 19 

2001 198 9 8.62 8.21 0.41 4.5 3.3 4.9 77.3 0.0 17.5 1.0 1.7 2.6 20 

 

2002 224 3 9.66 8.33 1.32 4.9 3.5 5.1 78.5 0.0 16.4 0.9 1.7 2.4 1 

2002 15 16 9.06 7.82 1.25 3.4 2.7 4.0 72.0 0.0 21.5 1.2 2.1 3.1 2 

2002 227 8 9.51 8.33 1.18 4.9 3.5 5.1 78.5 0.0 16.5 0.9 1.7 2.4 3 

2002 365 16 9.08 7.94 1.14 3.8 2.9 4.3 73.7 0.0 20.1 1.2 2.2 3.0 4 

2002 67 3 8.71 7.67 1.04 3.0 2.5 3.7 69.4 0.0 23.4 1.3 2.4 3.5 5 

2002 228 97 9.33 8.33 0.99 4.9 3.5 5.1 78.6 0.0 16.4 0.9 1.7 2.4 6 

2002 230 3 9.31 8.33 0.97 4.9 3.5 5.1 78.4 0.0 16.4 0.9 1.8 2.4 7 

2002 226 97 9.27 8.33 0.94 4.9 3.5 5.1 78.4 0.0 16.4 0.9 1.8 2.4 8 

2002 314 2 8.75 7.87 0.88 3.6 2.8 4.1 72.7 0.0 20.8 1.2 2.3 3.0 9 

2002 35 9 8.56 7.72 0.84 3.2 2.5 3.8 70.2 0.0 22.8 1.2 2.5 3.3 10 

2002 222 16 9.12 8.33 0.79 4.9 3.5 5.1 78.8 0.0 16.5 0.9 1.4 2.4 11 

2002 28 3 8.58 7.82 0.76 3.4 2.7 4.0 71.9 0.0 21.5 1.2 2.2 3.1 12 

2002 107 97 8.32 7.60 0.71 2.8 2.3 3.6 68.0 0.0 24.5 1.4 2.6 3.6 13 

2002 207 9 8.89 8.21 0.69 4.5 3.3 4.9 77.3 0.0 17.5 1.0 1.5 2.6 14 

2002 85 97 8.24 7.67 0.56 3.0 2.5 3.7 69.4 0.0 23.4 1.3 2.5 3.5 15 

2002 323 3 8.42 7.87 0.55 3.6 2.8 4.1 72.8 0.0 20.8 1.2 2.2 3.1 16 

2002 105 8 8.13 7.60 0.52 2.8 2.3 3.6 68.2 0.0 24.6 1.3 2.4 3.5 17 

2002 191 16 8.72 8.21 0.51 4.5 3.3 4.9 77.6 0.0 17.5 0.9 1.3 2.6 18 

2002 128 3 8.37 7.87 0.50 3.6 2.8 4.1 72.6 0.0 20.8 1.2 2.3 3.1 19 

2002 313 8 8.34 7.87 0.47 3.6 2.8 4.1 72.9 0.0 20.9 1.2 2.1 3.0 20 

 

2003 271 3 9.29 8.33 0.96 4.9 3.5 5.1 78.5 0.0 16.5 0.9 1.6 2.4 1 

2003 270 1 9.28 8.33 0.94 4.9 3.5 5.1 78.5 0.0 16.4 0.9 1.7 2.4 2 

2003 178 3 8.79 8.10 0.69 4.2 3.2 4.6 75.8 0.0 18.4 1.0 2.1 2.7 3 

2003 356 16 8.60 7.94 0.67 3.8 2.9 4.3 73.7 0.0 20.1 1.1 2.2 2.9 4 

2003 68 3 8.32 7.67 0.65 3.0 2.5 3.7 69.2 0.0 23.3 1.4 2.6 3.5 5 

2003 246 3 8.98 8.33 0.64 4.9 3.5 5.1 78.6 0.0 16.5 0.9 1.5 2.5 6 

2003 107 1 8.23 7.60 0.62 2.8 2.3 3.6 68.1 0.0 24.5 1.3 2.5 3.6 7 

2003 163 3 8.69 8.10 0.58 4.2 3.2 4.6 76.0 0.0 18.4 1.1 1.8 2.7 8 

2003 164 97 8.68 8.10 0.58 4.2 3.2 4.6 76.0 0.0 18.4 1.1 1.8 2.7 9 

2003 187 3 8.79 8.21 0.58 4.5 3.3 4.9 77.0 0.0 17.4 1.0 2.0 2.6 10 

2003 35 10 8.24 7.72 0.53 3.2 2.5 3.8 70.2 0.0 22.8 1.3 2.3 3.3 11 

2003 242 16 8.84 8.33 0.50 4.9 3.5 5.1 78.7 0.0 16.4 0.9 1.5 2.4 12 

2003 160 3 8.59 8.10 0.49 4.2 3.2 4.6 75.8 0.0 18.3 1.1 2.1 2.7 13 

2003 326 1 8.35 7.87 0.48 3.6 2.8 4.1 72.7 0.0 20.8 1.1 2.4 3.0 14 

2003 247 97 8.81 8.33 0.47 4.9 3.5 5.1 78.8 0.0 16.5 0.9 1.3 2.5 15 

2003 304 1 8.56 8.10 0.46 4.2 3.2 4.6 76.0 0.0 18.4 1.0 2.0 2.6 16 

2003 108 3 8.05 7.60 0.45 2.8 2.3 3.6 68.1 0.0 24.5 1.4 2.5 3.6 17 

2003 259 3 8.78 8.33 0.44 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.9 2.4 18 

2003 197 9 8.65 8.21 0.44 4.5 3.3 4.9 77.0 0.0 17.5 1.0 2.0 2.5 19 

2003 166 46 8.53 8.10 0.43 4.2 3.2 4.6 76.0 0.0 18.4 1.0 1.9 2.7 20 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 25 Days for 3 Years) 

Bowen 1-4 Results - Unit 2 Controlled with Agglomerator/Juice Can

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.30 7.94 1.36 3.8 2.9 4.3 73.7 0.0 20.1 1.1 2.2 3.0 1 

2002 224 3 9.66 8.33 1.32 4.9 3.5 5.1 78.5 0.0 16.4 0.9 1.7 2.4 2 

2002 15 16 9.06 7.82 1.25 3.4 2.7 4.0 72.0 0.0 21.5 1.2 2.1 3.1 3 

2002 227 8 9.51 8.33 1.18 4.9 3.5 5.1 78.5 0.0 16.5 0.9 1.7 2.4 4 

2002 365 16 9.08 7.94 1.14 3.8 2.9 4.3 73.7 0.0 20.1 1.2 2.2 3.0 5 

2002 67 3 8.71 7.67 1.04 3.0 2.5 3.7 69.4 0.0 23.4 1.3 2.4 3.5 6 

2002 228 97 9.33 8.33 0.99 4.9 3.5 5.1 78.6 0.0 16.4 0.9 1.7 2.4 7 

2001 113 1 8.59 7.60 0.98 2.8 2.3 3.6 67.9 0.0 24.4 1.4 2.7 3.6 8 

2002 230 3 9.31 8.33 0.97 4.9 3.5 5.1 78.4 0.0 16.4 0.9 1.8 2.4 9 

2003 271 3 9.29 8.33 0.96 4.9 3.5 5.1 78.5 0.0 16.5 0.9 1.6 2.4 10 

2003 270 1 9.28 8.33 0.94 4.9 3.5 5.1 78.5 0.0 16.4 0.9 1.7 2.4 11 

2002 226 97 9.27 8.33 0.94 4.9 3.5 5.1 78.4 0.0 16.4 0.9 1.8 2.4 12 

2001 225 3 9.27 8.33 0.93 4.9 3.5 5.1 78.4 0.0 16.4 1.0 1.8 2.4 13 

2002 314 2 8.75 7.87 0.88 3.6 2.8 4.1 72.7 0.0 20.8 1.2 2.3 3.0 14 

2001 297 3 8.97 8.10 0.87 4.2 3.2 4.6 76.0 0.0 18.4 1.1 1.9 2.7 15 

2002 35 9 8.56 7.72 0.84 3.2 2.5 3.8 70.2 0.0 22.8 1.2 2.5 3.3 16 

2001 114 4 8.42 7.60 0.82 2.8 2.3 3.6 68.2 0.0 24.5 1.4 2.3 3.6 17 

2002 222 16 9.12 8.33 0.79 4.9 3.5 5.1 78.8 0.0 16.5 0.9 1.4 2.4 18 

2002 28 3 8.58 7.82 0.76 3.4 2.7 4.0 71.9 0.0 21.5 1.2 2.2 3.1 19 

2001 279 1 8.87 8.10 0.76 4.2 3.2 4.6 75.9 0.0 18.4 1.0 2.0 2.7 20 

2001 220 54 9.09 8.33 0.76 4.9 3.5 5.1 78.5 0.0 16.4 1.0 1.6 2.5 21 

2001 111 16 8.33 7.60 0.73 2.8 2.3 3.6 68.1 0.0 24.5 1.4 2.4 3.6 22 

2002 107 97 8.32 7.60 0.71 2.8 2.3 3.6 68.0 0.0 24.5 1.4 2.6 3.6 23 

2003 178 3 8.79 8.10 0.69 4.2 3.2 4.6 75.8 0.0 18.4 1.0 2.1 2.7 24 

2002 207 9 8.89 8.21 0.69 4.5 3.3 4.9 77.3 0.0 17.5 1.0 1.5 2.6 25 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 20 Days Each Year) 

Bowen 1-4 Results - Unit 3 Controlled with Agglomerator/Juice Can 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.30 7.94 1.37 3.8 2.9 4.3 73.4 0.0 20.0 1.2 2.3 3.1 1 

2001 113 1 8.59 7.60 0.99 2.8 2.3 3.6 67.6 0.0 24.3 1.4 2.9 3.7 2 

2001 225 3 9.27 8.33 0.94 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.9 2.5 3 

2001 297 3 8.97 8.10 0.87 4.2 3.2 4.6 75.7 0.0 18.3 1.1 2.0 2.9 4 

2001 114 4 8.42 7.60 0.82 2.8 2.3 3.6 67.9 0.0 24.4 1.5 2.5 3.7 5 

2001 279 1 8.87 8.10 0.77 4.2 3.2 4.6 75.7 0.0 18.3 1.1 2.1 2.7 6 

2001 220 54 9.10 8.33 0.76 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.8 2.6 7 

2001 111 16 8.34 7.60 0.73 2.8 2.3 3.6 67.8 0.0 24.4 1.5 2.6 3.7 8 

2001 294 1 8.79 8.10 0.69 4.2 3.2 4.6 75.5 0.0 18.3 1.2 2.2 2.9 9 

2001 51 8 8.39 7.72 0.67 3.2 2.5 3.8 70.1 0.0 22.8 1.3 2.4 3.4 10 

2001 102 9 8.20 7.60 0.59 2.8 2.3 3.6 67.8 0.0 24.4 1.5 2.6 3.8 11 

2001 229 16 8.88 8.33 0.55 4.9 3.5 5.1 78.6 0.0 16.5 1.0 1.4 2.5 12 

2001 110 3 8.12 7.60 0.52 2.8 2.3 3.6 67.8 0.0 24.4 1.5 2.5 3.8 13 

2001 142 3 8.34 7.87 0.47 3.6 2.8 4.1 72.8 0.0 20.8 1.3 1.8 3.3 14 

2001 112 35 8.07 7.60 0.47 2.8 2.3 3.6 67.8 0.0 24.4 1.5 2.5 3.8 15 

2001 343 97 8.40 7.94 0.46 3.8 2.9 4.3 73.3 0.0 20.0 1.3 2.3 3.2 16 

2001 158 25 8.56 8.10 0.46 4.2 3.2 4.6 75.8 0.0 18.4 1.1 2.1 2.6 17 

2001 126 3 8.31 7.87 0.44 3.6 2.8 4.1 72.6 0.0 20.7 1.2 2.2 3.2 18 

2001 236 25 8.77 8.33 0.43 4.9 3.5 5.1 78.2 0.0 16.3 1.0 2.0 2.5 19 

2001 198 9 8.62 8.21 0.42 4.5 3.3 4.9 76.9 0.0 17.4 1.1 1.9 2.8 20 

 

2002 224 3 9.66 8.33 1.33 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.9 2.5 1 

2002 15 16 9.07 7.82 1.25 3.4 2.7 4.0 71.8 0.0 21.5 1.3 2.3 3.2 2 

2002 227 8 9.52 8.33 1.18 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.8 2.5 3 

2002 365 16 9.08 7.94 1.14 3.8 2.9 4.3 73.4 0.0 20.0 1.2 2.3 3.1 4 

2002 67 3 8.71 7.67 1.04 3.0 2.5 3.7 69.1 0.0 23.3 1.4 2.7 3.6 5 

2002 228 97 9.33 8.33 1.00 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.8 2.5 6 

2002 230 3 9.31 8.33 0.98 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.9 2.5 7 

2002 226 97 9.27 8.33 0.94 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.9 2.5 8 

2002 314 2 8.76 7.87 0.88 3.6 2.8 4.1 72.4 0.0 20.7 1.3 2.5 3.2 9 

2002 35 9 8.56 7.72 0.84 3.2 2.5 3.8 70.0 0.0 22.7 1.3 2.7 3.3 10 

2002 222 16 9.12 8.33 0.79 4.9 3.5 5.1 78.5 0.0 16.4 1.0 1.5 2.5 11 

2002 28 3 8.58 7.82 0.77 3.4 2.7 4.0 71.7 0.0 21.5 1.3 2.4 3.2 12 

2002 107 97 8.32 7.60 0.72 2.8 2.3 3.6 67.6 0.0 24.3 1.5 2.8 3.8 13 

2002 207 9 8.89 8.21 0.69 4.5 3.3 4.9 77.1 0.0 17.4 1.1 1.6 2.8 14 

2002 85 97 8.24 7.67 0.57 3.0 2.5 3.7 69.1 0.0 23.3 1.4 2.6 3.6 15 

2002 323 3 8.42 7.87 0.55 3.6 2.8 4.1 72.4 0.0 20.7 1.2 2.5 3.2 16 

2002 105 8 8.13 7.60 0.52 2.8 2.3 3.6 68.1 0.0 24.5 1.3 2.6 3.5 17 

2002 191 16 8.72 8.21 0.51 4.5 3.3 4.9 77.4 0.0 17.5 1.0 1.4 2.7 18 

2002 128 3 8.37 7.87 0.50 3.6 2.8 4.1 72.4 0.0 20.7 1.3 2.5 3.2 19 

2002 106 8 8.08 7.60 0.47 2.8 2.3 3.6 67.5 0.0 24.3 1.5 2.9 3.8 20 

 

2003 271 3 9.29 8.33 0.96 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.8 2.5 1 

2003 270 1 9.28 8.33 0.94 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.8 2.6 2 

2003 178 3 8.79 8.10 0.69 4.2 3.2 4.6 75.5 0.0 18.3 1.1 2.3 2.8 3 

2003 356 16 8.60 7.94 0.67 3.8 2.9 4.3 73.6 0.0 20.0 1.1 2.3 3.0 4 

2003 68 3 8.33 7.67 0.65 3.0 2.5 3.7 68.8 0.0 23.2 1.4 2.9 3.7 5 

2003 246 3 8.98 8.33 0.65 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.7 2.7 6 

2003 107 1 8.23 7.60 0.63 2.8 2.3 3.6 67.7 0.0 24.4 1.5 2.7 3.8 7 

2003 163 3 8.69 8.10 0.59 4.2 3.2 4.6 75.7 0.0 18.3 1.1 2.0 2.9 8 

2003 164 97 8.68 8.10 0.58 4.2 3.2 4.6 75.7 0.0 18.3 1.1 2.0 2.9 9 

2003 187 3 8.79 8.21 0.58 4.5 3.3 4.9 76.7 0.0 17.4 1.1 2.2 2.7 10 

2003 35 10 8.24 7.72 0.53 3.2 2.5 3.8 70.0 0.0 22.8 1.3 2.5 3.4 11 

2003 242 16 8.84 8.33 0.50 4.9 3.5 5.1 78.4 0.0 16.4 1.0 1.6 2.6 12 

2003 160 3 8.60 8.10 0.49 4.2 3.2 4.6 75.4 0.0 18.2 1.2 2.3 2.9 13 

2003 326 1 8.35 7.87 0.48 3.6 2.8 4.1 72.3 0.0 20.7 1.2 2.6 3.2 14 

2003 247 97 8.81 8.33 0.48 4.9 3.5 5.1 78.5 0.0 16.5 1.0 1.4 2.6 15 

2003 304 1 8.56 8.10 0.46 4.2 3.2 4.6 75.7 0.0 18.4 1.1 2.1 2.7 16 

2003 108 3 8.05 7.60 0.45 2.8 2.3 3.6 67.7 0.0 24.4 1.5 2.7 3.8 17 

2003 259 3 8.78 8.33 0.45 4.9 3.5 5.1 78.1 0.0 16.3 1.0 2.0 2.5 18 

2003 197 9 8.65 8.21 0.44 4.5 3.3 4.9 77.0 0.0 17.4 1.0 2.1 2.5 19 

2003 166 46 8.54 8.10 0.43 4.2 3.2 4.6 75.6 0.0 18.3 1.1 2.1 2.9 20 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 25 Days for 3 Years) 

Bowen 1-4 Results - Unit 3 Controlled with Agglomerator/Juice Can

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.30 7.94 1.37 3.8 2.9 4.3 73.4 0.0 20.0 1.2 2.3 3.1 1 

2002 224 3 9.66 8.33 1.33 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.9 2.5 2 

2002 15 16 9.07 7.82 1.25 3.4 2.7 4.0 71.8 0.0 21.5 1.3 2.3 3.2 3 

2002 227 8 9.52 8.33 1.18 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.8 2.5 4 

2002 365 16 9.08 7.94 1.14 3.8 2.9 4.3 73.4 0.0 20.0 1.2 2.3 3.1 5 

2002 67 3 8.71 7.67 1.04 3.0 2.5 3.7 69.1 0.0 23.3 1.4 2.7 3.6 6 

2002 228 97 9.33 8.33 1.00 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.8 2.5 7 

2001 113 1 8.59 7.60 0.99 2.8 2.3 3.6 67.6 0.0 24.3 1.4 2.9 3.7 8 

2002 230 3 9.31 8.33 0.98 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.9 2.5 9 

2003 271 3 9.29 8.33 0.96 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.8 2.5 10 

2003 270 1 9.28 8.33 0.94 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.8 2.6 11 

2002 226 97 9.27 8.33 0.94 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.9 2.5 12 

2001 225 3 9.27 8.33 0.94 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.9 2.5 13 

2002 314 2 8.76 7.87 0.88 3.6 2.8 4.1 72.4 0.0 20.7 1.3 2.5 3.2 14 

2001 297 3 8.97 8.10 0.87 4.2 3.2 4.6 75.7 0.0 18.3 1.1 2.0 2.9 15 

2002 35 9 8.56 7.72 0.84 3.2 2.5 3.8 70.0 0.0 22.7 1.3 2.7 3.3 16 

2001 114 4 8.42 7.60 0.82 2.8 2.3 3.6 67.9 0.0 24.4 1.5 2.5 3.7 17 

2002 222 16 9.12 8.33 0.79 4.9 3.5 5.1 78.5 0.0 16.4 1.0 1.5 2.5 18 

2002 28 3 8.58 7.82 0.77 3.4 2.7 4.0 71.7 0.0 21.5 1.3 2.4 3.2 19 

2001 279 1 8.87 8.10 0.77 4.2 3.2 4.6 75.7 0.0 18.3 1.1 2.1 2.7 20 

2001 220 54 9.10 8.33 0.76 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.8 2.6 21 

2001 111 16 8.34 7.60 0.73 2.8 2.3 3.6 67.8 0.0 24.4 1.5 2.6 3.7 22 

2002 107 97 8.32 7.60 0.72 2.8 2.3 3.6 67.6 0.0 24.3 1.5 2.8 3.8 23 

2003 178 3 8.79 8.10 0.69 4.2 3.2 4.6 75.5 0.0 18.3 1.1 2.3 2.8 24 

2002 207 9 8.89 8.21 0.69 4.5 3.3 4.9 77.1 0.0 17.4 1.1 1.6 2.8 25 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 20 Days Each Year) 

 Bowen 1-4 Results - Unit 4 Controlled with Agglomerator/Juice Can 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.30 7.94 1.37 3.8 2.9 4.3 73.4 0.0 20.0 1.2 2.3 3.0 1 

2001 113 1 8.59 7.60 0.99 2.8 2.3 3.6 67.7 0.0 24.3 1.4 2.9 3.7 2 

2001 225 3 9.27 8.33 0.94 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.9 2.5 3 

2001 297 3 8.97 8.10 0.87 4.2 3.2 4.6 75.7 0.0 18.3 1.1 2.0 2.9 4 

2001 114 4 8.42 7.60 0.82 2.8 2.3 3.6 67.9 0.0 24.4 1.4 2.5 3.7 5 

2001 279 1 8.87 8.10 0.76 4.2 3.2 4.6 75.8 0.0 18.4 1.0 2.1 2.7 6 

2001 220 54 9.09 8.33 0.76 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.8 2.6 7 

2001 111 16 8.34 7.60 0.73 2.8 2.3 3.6 67.9 0.0 24.4 1.5 2.6 3.7 8 

2001 294 1 8.79 8.10 0.68 4.2 3.2 4.6 75.6 0.0 18.3 1.1 2.2 2.9 9 

2001 51 8 8.39 7.72 0.67 3.2 2.5 3.8 70.2 0.0 22.8 1.3 2.4 3.3 10 

2001 102 9 8.20 7.60 0.59 2.8 2.3 3.6 67.9 0.0 24.4 1.4 2.6 3.7 11 

2001 229 16 8.88 8.33 0.55 4.9 3.5 5.1 78.6 0.0 16.5 0.9 1.4 2.5 12 

2001 110 3 8.12 7.60 0.52 2.8 2.3 3.6 67.8 0.0 24.4 1.5 2.5 3.8 13 

2001 142 3 8.34 7.87 0.47 3.6 2.8 4.1 72.8 0.0 20.8 1.3 1.8 3.3 14 

2001 112 35 8.07 7.60 0.47 2.8 2.3 3.6 68.0 0.0 24.4 1.4 2.5 3.7 15 

2001 343 97 8.40 7.94 0.46 3.8 2.9 4.3 73.3 0.0 20.0 1.3 2.3 3.2 16 

2001 158 25 8.56 8.10 0.45 4.2 3.2 4.6 75.9 0.0 18.4 1.0 2.2 2.6 17 

2001 126 3 8.31 7.87 0.44 3.6 2.8 4.1 72.6 0.0 20.7 1.2 2.2 3.2 18 

2001 236 25 8.77 8.33 0.43 4.9 3.5 5.1 78.2 0.0 16.3 1.0 2.0 2.5 19 

2001 198 9 8.62 8.21 0.42 4.5 3.3 4.9 76.9 0.0 17.4 1.1 1.9 2.8 20 

 

2002 224 3 9.66 8.33 1.33 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.9 2.5 1 

2002 15 16 9.06 7.82 1.25 3.4 2.7 4.0 71.8 0.0 21.5 1.2 2.3 3.2 2 

2002 227 8 9.52 8.33 1.18 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.8 2.5 3 

2002 365 16 9.08 7.94 1.14 3.8 2.9 4.3 73.4 0.0 20.0 1.2 2.3 3.1 4 

2002 67 3 8.71 7.67 1.04 3.0 2.5 3.7 69.1 0.0 23.3 1.4 2.7 3.5 5 

2002 228 97 9.33 8.33 1.00 4.9 3.5 5.1 78.4 0.0 16.4 1.0 1.8 2.5 6 

2002 230 3 9.31 8.33 0.98 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.9 2.5 7 

2002 226 97 9.27 8.33 0.94 4.9 3.5 5.1 78.3 0.0 16.4 0.9 1.9 2.5 8 

2002 314 2 8.76 7.87 0.88 3.6 2.8 4.1 72.5 0.0 20.7 1.2 2.5 3.1 9 

2002 35 9 8.56 7.72 0.84 3.2 2.5 3.8 70.0 0.0 22.7 1.3 2.7 3.3 10 

2002 222 16 9.12 8.33 0.79 4.9 3.5 5.1 78.6 0.0 16.4 1.0 1.5 2.5 11 

2002 28 3 8.58 7.82 0.77 3.4 2.7 4.0 71.7 0.0 21.5 1.2 2.4 3.2 12 

2002 107 97 8.32 7.60 0.71 2.8 2.3 3.6 67.7 0.0 24.3 1.4 2.8 3.8 13 

2002 207 9 8.89 8.21 0.69 4.5 3.3 4.9 77.1 0.0 17.5 1.1 1.6 2.7 14 

2002 85 97 8.24 7.67 0.57 3.0 2.5 3.7 69.1 0.0 23.3 1.4 2.6 3.6 15 

2002 323 3 8.42 7.87 0.55 3.6 2.8 4.1 72.5 0.0 20.7 1.2 2.5 3.1 16 

2002 105 8 8.13 7.60 0.52 2.8 2.3 3.6 68.1 0.0 24.5 1.3 2.6 3.5 17 

2002 191 16 8.72 8.21 0.51 4.5 3.3 4.9 77.4 0.0 17.5 1.0 1.4 2.7 18 

2002 128 3 8.37 7.87 0.50 3.6 2.8 4.1 72.4 0.0 20.7 1.3 2.5 3.2 19 

2002 106 8 8.08 7.60 0.47 2.8 2.3 3.6 67.5 0.0 24.3 1.5 2.9 3.8 20 

 

2003 271 3 9.29 8.33 0.96 4.9 3.5 5.1 78.4 0.0 16.4 1.0 1.8 2.5 1 

2003 270 1 9.28 8.33 0.94 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.8 2.5 2 

2003 178 3 8.79 8.10 0.69 4.2 3.2 4.6 75.5 0.0 18.3 1.1 2.3 2.8 3 

2003 356 16 8.60 7.94 0.67 3.8 2.9 4.3 73.6 0.0 20.0 1.1 2.3 3.0 4 

2003 68 3 8.33 7.67 0.65 3.0 2.5 3.7 68.8 0.0 23.2 1.4 2.9 3.7 5 

2003 246 3 8.98 8.33 0.65 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.7 2.6 6 

2003 107 1 8.23 7.60 0.62 2.8 2.3 3.6 67.8 0.0 24.4 1.4 2.6 3.7 7 

2003 163 3 8.69 8.10 0.59 4.2 3.2 4.6 75.9 0.0 18.3 1.1 2.0 2.8 8 

2003 164 97 8.68 8.10 0.58 4.2 3.2 4.6 75.7 0.0 18.3 1.1 2.0 2.9 9 

2003 187 3 8.79 8.21 0.58 4.5 3.3 4.9 76.7 0.0 17.4 1.1 2.2 2.7 10 

2003 35 10 8.24 7.72 0.53 3.2 2.5 3.8 70.0 0.0 22.8 1.3 2.5 3.4 11 

2003 242 16 8.84 8.33 0.50 4.9 3.5 5.1 78.5 0.0 16.4 0.9 1.6 2.6 12 

2003 160 3 8.60 8.10 0.49 4.2 3.2 4.6 75.5 0.0 18.2 1.1 2.3 2.9 13 

2003 326 1 8.35 7.87 0.48 3.6 2.8 4.1 72.3 0.0 20.7 1.2 2.5 3.2 14 

2003 247 97 8.81 8.33 0.48 4.9 3.5 5.1 78.5 0.0 16.5 1.0 1.4 2.6 15 

2003 304 1 8.56 8.10 0.46 4.2 3.2 4.6 75.7 0.0 18.4 1.1 2.1 2.7 16 

2003 108 3 8.05 7.60 0.45 2.8 2.3 3.6 67.7 0.0 24.4 1.5 2.7 3.8 17 

2003 259 3 8.78 8.33 0.45 4.9 3.5 5.1 78.1 0.0 16.3 1.0 2.0 2.5 18 

2003 197 9 8.65 8.21 0.44 4.5 3.3 4.9 77.0 0.0 17.4 1.0 2.1 2.5 19 

2003 166 46 8.54 8.10 0.43 4.2 3.2 4.6 75.7 0.0 18.3 1.1 2.1 2.8 20 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 25 Days for 3 Years) 

Bowen 1-4 Results - Unit 4 Controlled with Agglomerator/Juice Can

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.30 7.94 1.37 3.8 2.9 4.3 73.4 0.0 20.0 1.2 2.3 3.0 1 

2002 224 3 9.66 8.33 1.33 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.9 2.5 2 

2002 15 16 9.06 7.82 1.25 3.4 2.7 4.0 71.8 0.0 21.5 1.2 2.3 3.2 3 

2002 227 8 9.52 8.33 1.18 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.8 2.5 4 

2002 365 16 9.08 7.94 1.14 3.8 2.9 4.3 73.4 0.0 20.0 1.2 2.3 3.1 5 

2002 67 3 8.71 7.67 1.04 3.0 2.5 3.7 69.1 0.0 23.3 1.4 2.7 3.5 6 

2002 228 97 9.33 8.33 1.00 4.9 3.5 5.1 78.4 0.0 16.4 1.0 1.8 2.5 7 

2001 113 1 8.59 7.60 0.99 2.8 2.3 3.6 67.7 0.0 24.3 1.4 2.9 3.7 8 

2002 230 3 9.31 8.33 0.98 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.9 2.5 9 

2003 271 3 9.29 8.33 0.96 4.9 3.5 5.1 78.4 0.0 16.4 1.0 1.8 2.5 10 

2003 270 1 9.28 8.33 0.94 4.9 3.5 5.1 78.3 0.0 16.4 1.0 1.8 2.5 11 

2002 226 97 9.27 8.33 0.94 4.9 3.5 5.1 78.3 0.0 16.4 0.9 1.9 2.5 12 

2001 225 3 9.27 8.33 0.94 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.9 2.5 13 

2002 314 2 8.76 7.87 0.88 3.6 2.8 4.1 72.5 0.0 20.7 1.2 2.5 3.1 14 

2001 297 3 8.97 8.10 0.87 4.2 3.2 4.6 75.7 0.0 18.3 1.1 2.0 2.9 15 

2002 35 9 8.56 7.72 0.84 3.2 2.5 3.8 70.0 0.0 22.7 1.3 2.7 3.3 16 

2001 114 4 8.42 7.60 0.82 2.8 2.3 3.6 67.9 0.0 24.4 1.4 2.5 3.7 17 

2002 222 16 9.12 8.33 0.79 4.9 3.5 5.1 78.6 0.0 16.4 1.0 1.5 2.5 18 

2002 28 3 8.58 7.82 0.77 3.4 2.7 4.0 71.7 0.0 21.5 1.2 2.4 3.2 19 

2001 279 1 8.87 8.10 0.76 4.2 3.2 4.6 75.8 0.0 18.4 1.0 2.1 2.7 20 

2001 220 54 9.09 8.33 0.76 4.9 3.5 5.1 78.2 0.0 16.4 1.0 1.8 2.6 21 

2001 111 16 8.34 7.60 0.73 2.8 2.3 3.6 67.9 0.0 24.4 1.5 2.6 3.7 22 

2002 107 97 8.32 7.60 0.71 2.8 2.3 3.6 67.7 0.0 24.3 1.4 2.8 3.8 23 

2003 178 3 8.79 8.10 0.69 4.2 3.2 4.6 75.5 0.0 18.3 1.1 2.3 2.8 24 

2002 207 9 8.89 8.21 0.69 4.5 3.3 4.9 77.1 0.0 17.5 1.1 1.6 2.7 25 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 20 Days Each Year) 

Bowen 1-4 Results - Unit 1 Controlled with WESP 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.12 7.94 1.18 3.8 2.9 4.3 70.4 0.0 23.5 1.1 2.1 2.9 1 

2001 113 1 8.46 7.60 0.86 2.8 2.3 3.6 64.3 0.0 28.2 1.3 2.6 3.5 2 

2001 225 3 9.13 8.33 0.80 4.9 3.5 5.1 75.5 0.0 19.4 0.9 1.8 2.4 3 

2001 297 3 8.84 8.10 0.74 4.2 3.2 4.6 72.6 0.0 21.8 1.0 1.8 2.7 4 

2001 114 4 8.31 7.60 0.71 2.8 2.3 3.6 64.6 0.0 28.4 1.3 2.2 3.5 5 

2001 279 1 8.77 8.10 0.67 4.2 3.2 4.6 73.2 0.0 21.2 1.0 1.9 2.6 6 

2001 111 16 8.24 7.60 0.64 2.8 2.3 3.6 64.5 0.0 28.3 1.3 2.4 3.5 7 

2001 220 54 8.97 8.33 0.64 4.9 3.5 5.1 75.2 0.0 19.7 0.9 1.7 2.4 8 

2001 51 8 8.31 7.72 0.59 3.2 2.5 3.8 67.3 0.0 26.0 1.3 2.3 3.2 9 

2001 294 1 8.68 8.10 0.58 4.2 3.2 4.6 72.4 0.0 21.9 1.0 2.0 2.8 10 

2001 102 9 8.12 7.60 0.51 2.8 2.3 3.6 64.4 0.0 28.3 1.4 2.4 3.6 11 

2001 229 16 8.80 8.33 0.47 4.9 3.5 5.1 76.0 0.0 19.4 0.9 1.3 2.4 12 

2001 110 3 8.05 7.60 0.45 2.8 2.3 3.6 64.2 0.0 28.5 1.4 2.3 3.6 13 

2001 112 35 8.01 7.60 0.41 2.8 2.3 3.6 64.6 0.0 28.4 1.3 2.2 3.5 14 

2001 142 3 8.27 7.87 0.40 3.6 2.8 4.1 69.4 0.0 24.6 1.1 1.7 3.1 15 

2001 158 25 8.50 8.10 0.40 4.2 3.2 4.6 73.4 0.0 20.9 1.0 2.0 2.7 16 

2001 343 97 8.32 7.94 0.39 3.8 2.9 4.3 69.8 0.0 23.9 1.2 2.1 3.0 17 

2001 126 3 8.24 7.87 0.37 3.6 2.8 4.1 69.3 0.0 24.5 1.1 2.0 3.1 18 

2001 236 25 8.70 8.33 0.37 4.9 3.5 5.1 75.6 0.0 19.2 0.9 1.9 2.4 19 

2001 198 9 8.56 8.21 0.35 4.5 3.3 4.9 74.0 0.0 20.7 1.0 1.8 2.5 20 

 

2002 224 3 9.47 8.33 1.13 4.9 3.5 5.1 75.5 0.0 19.4 0.9 1.7 2.4 1 

2002 15 16 8.91 7.82 1.09 3.4 2.7 4.0 68.9 0.0 24.8 1.2 2.1 3.1 2 

2002 227 8 9.35 8.33 1.01 4.9 3.5 5.1 75.7 0.0 19.3 0.9 1.7 2.4 3 

2002 365 16 8.92 7.94 0.98 3.8 2.9 4.3 70.3 0.0 23.6 1.1 2.1 2.9 4 

2002 67 3 8.58 7.67 0.90 3.0 2.5 3.7 65.8 0.0 27.2 1.3 2.4 3.4 5 

2002 228 97 9.19 8.33 0.85 4.9 3.5 5.1 75.7 0.0 19.4 0.9 1.7 2.4 6 

2002 230 3 9.17 8.33 0.83 4.9 3.5 5.1 75.5 0.0 19.4 0.9 1.8 2.4 7 

2002 226 97 9.14 8.33 0.80 4.9 3.5 5.1 75.6 0.0 19.3 0.9 1.8 2.4 8 

2002 314 2 8.63 7.87 0.76 3.6 2.8 4.1 69.4 0.0 24.2 1.1 2.2 3.0 9 

2002 35 9 8.46 7.72 0.75 3.2 2.5 3.8 67.2 0.0 25.8 1.2 2.5 3.3 10 

2002 28 3 8.48 7.82 0.66 3.4 2.7 4.0 68.6 0.0 24.9 1.2 2.2 3.1 11 

2002 222 16 9.01 8.33 0.67 4.9 3.5 5.1 75.9 0.0 19.4 0.9 1.4 2.4 12 

2002 107 97 8.22 7.60 0.62 2.8 2.3 3.6 64.1 0.0 28.4 1.4 2.5 3.6 13 

2002 207 9 8.79 8.21 0.58 4.5 3.3 4.9 74.0 0.0 20.9 1.0 1.5 2.6 14 

2002 85 97 8.16 7.67 0.49 3.0 2.5 3.7 65.7 0.0 27.2 1.2 2.4 3.4 15 

2002 323 3 8.35 7.87 0.48 3.6 2.8 4.1 69.5 0.0 24.1 1.2 2.2 3.0 16 

2002 105 8 8.07 7.60 0.47 2.8 2.3 3.6 65.3 0.0 27.6 1.3 2.4 3.4 17 

2002 191 16 8.65 8.21 0.44 4.5 3.3 4.9 74.6 0.0 20.5 1.0 1.3 2.6 18 

2002 128 3 8.30 7.87 0.43 3.6 2.8 4.1 69.2 0.0 24.4 1.2 2.3 3.0 19 

2002 313 8 8.29 7.87 0.42 3.6 2.8 4.1 70.1 0.0 23.7 1.1 2.1 3.0 20 

 

2003 271 3 9.15 8.33 0.82 4.9 3.5 5.1 75.7 0.0 19.4 0.9 1.6 2.4 1 

2003 270 1 9.14 8.33 0.80 4.9 3.5 5.1 75.6 0.0 19.4 0.9 1.6 2.4 2 

2003 178 3 8.69 8.10 0.59 4.2 3.2 4.6 72.7 0.0 21.5 1.0 2.1 2.7 3 

2003 356 16 8.52 7.94 0.58 3.8 2.9 4.3 70.9 0.0 23.1 1.1 2.1 2.9 4 

2003 68 3 8.23 7.67 0.56 3.0 2.5 3.7 65.2 0.0 27.5 1.3 2.6 3.4 5 

2003 107 1 8.14 7.60 0.54 2.8 2.3 3.6 64.3 0.0 28.4 1.3 2.3 3.6 6 

2003 246 3 8.87 8.33 0.54 4.9 3.5 5.1 75.2 0.0 19.8 1.0 1.5 2.5 7 

2003 163 3 8.60 8.10 0.50 4.2 3.2 4.6 73.0 0.0 21.6 1.0 1.8 2.7 8 

2003 164 97 8.60 8.10 0.49 4.2 3.2 4.6 72.7 0.0 21.8 1.0 1.8 2.7 9 

2003 187 3 8.70 8.21 0.49 4.5 3.3 4.9 73.8 0.0 20.7 1.0 2.0 2.6 10 

2003 35 10 8.18 7.72 0.46 3.2 2.5 3.8 67.0 0.0 26.3 1.2 2.2 3.3 11 

2003 242 16 8.76 8.33 0.43 4.9 3.5 5.1 75.6 0.0 19.5 0.9 1.5 2.4 12 

2003 326 1 8.29 7.87 0.41 3.6 2.8 4.1 69.3 0.0 24.3 1.1 2.3 3.0 13 

2003 160 3 8.52 8.10 0.41 4.2 3.2 4.6 72.3 0.0 21.9 1.1 2.1 2.7 14 

2003 304 1 8.50 8.10 0.40 4.2 3.2 4.6 73.3 0.0 21.1 1.0 2.0 2.7 15 

2003 247 97 8.73 8.33 0.40 4.9 3.5 5.1 75.5 0.0 19.8 0.9 1.3 2.5 16 

2003 108 3 7.99 7.60 0.39 2.8 2.3 3.6 64.3 0.0 28.4 1.3 2.4 3.5 17 

2003 197 9 8.59 8.21 0.39 4.5 3.3 4.9 74.7 0.0 19.9 0.9 1.9 2.5 18 

2003 320 25 8.25 7.87 0.38 3.6 2.8 4.1 69.9 0.0 23.7 1.1 2.3 2.9 19 

2003 259 3 8.71 8.33 0.38 4.9 3.5 5.1 75.3 0.0 19.5 0.9 1.9 2.4 20 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 25 Days for 3 Years) 

Bowen 1-4 Results - Unit 1 Controlled with WESP 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.12 7.94 1.18 3.8 2.9 4.3 70.4 0.0 23.5 1.1 2.1 2.9 1 

2002 224 3 9.47 8.33 1.13 4.9 3.5 5.1 75.5 0.0 19.4 0.9 1.7 2.4 2 

2002 15 16 8.91 7.82 1.09 3.4 2.7 4.0 68.9 0.0 24.8 1.2 2.1 3.1 3 

2002 227 8 9.35 8.33 1.01 4.9 3.5 5.1 75.7 0.0 19.3 0.9 1.7 2.4 4 

2002 365 16 8.92 7.94 0.98 3.8 2.9 4.3 70.3 0.0 23.6 1.1 2.1 2.9 5 

2002 67 3 8.58 7.67 0.90 3.0 2.5 3.7 65.8 0.0 27.2 1.3 2.4 3.4 6 

2001 113 1 8.46 7.60 0.86 2.8 2.3 3.6 64.3 0.0 28.2 1.3 2.6 3.5 7 

2002 228 97 9.19 8.33 0.85 4.9 3.5 5.1 75.7 0.0 19.4 0.9 1.7 2.4 8 

2002 230 3 9.17 8.33 0.83 4.9 3.5 5.1 75.5 0.0 19.4 0.9 1.8 2.4 9 

2003 271 3 9.15 8.33 0.82 4.9 3.5 5.1 75.7 0.0 19.4 0.9 1.6 2.4 10 

2003 270 1 9.14 8.33 0.80 4.9 3.5 5.1 75.6 0.0 19.4 0.9 1.6 2.4 11 

2002 226 97 9.14 8.33 0.80 4.9 3.5 5.1 75.6 0.0 19.3 0.9 1.8 2.4 12 

2001 225 3 9.13 8.33 0.80 4.9 3.5 5.1 75.5 0.0 19.4 0.9 1.8 2.4 13 

2002 314 2 8.63 7.87 0.76 3.6 2.8 4.1 69.4 0.0 24.2 1.1 2.2 3.0 14 

2002 35 9 8.46 7.72 0.75 3.2 2.5 3.8 67.2 0.0 25.8 1.2 2.5 3.3 15 

2001 297 3 8.84 8.10 0.74 4.2 3.2 4.6 72.6 0.0 21.8 1.0 1.8 2.7 16 

2001 114 4 8.31 7.60 0.71 2.8 2.3 3.6 64.6 0.0 28.4 1.3 2.2 3.5 17 

2002 222 16 9.01 8.33 0.67 4.9 3.5 5.1 75.9 0.0 19.4 0.9 1.4 2.4 18 

2001 279 1 8.77 8.10 0.67 4.2 3.2 4.6 73.2 0.0 21.2 1.0 1.9 2.6 19 

2002 28 3 8.48 7.82 0.66 3.4 2.7 4.0 68.6 0.0 24.9 1.2 2.2 3.1 20 

2001 220 54 8.97 8.33 0.64 4.9 3.5 5.1 75.2 0.0 19.7 0.9 1.7 2.4 21 

2001 111 16 8.24 7.60 0.64 2.8 2.3 3.6 64.5 0.0 28.3 1.3 2.4 3.5 22 

2002 107 97 8.22 7.60 0.62 2.8 2.3 3.6 64.1 0.0 28.4 1.4 2.5 3.6 23 

2001 51 8 8.31 7.72 0.59 3.2 2.5 3.8 67.3 0.0 26.0 1.3 2.3 3.2 24 

2003 178 3 8.69 8.10 0.59 4.2 3.2 4.6 72.7 0.0 21.5 1.0 2.1 2.7 25 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 20 Days Each Year) 

Bowen 1-4 Results - Unit 2 Controlled with WESP 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.11 7.94 1.17 3.8 2.9 4.3 70.3 0.0 23.7 1.1 2.1 2.8 1 

2001 113 1 8.46 7.60 0.85 2.8 2.3 3.6 64.2 0.0 28.5 1.3 2.6 3.4 2 

2001 225 3 9.12 8.33 0.79 4.9 3.5 5.1 75.3 0.0 19.6 0.9 1.7 2.4 3 

2001 297 3 8.83 8.10 0.73 4.2 3.2 4.6 72.5 0.0 22.0 1.0 1.8 2.7 4 

2001 114 4 8.31 7.60 0.71 2.8 2.3 3.6 64.4 0.0 28.6 1.3 2.2 3.4 5 

2001 279 1 8.76 8.10 0.66 4.2 3.2 4.6 73.0 0.0 21.4 1.0 1.9 2.6 6 

2001 111 16 8.24 7.60 0.63 2.8 2.3 3.6 64.4 0.0 28.5 1.3 2.3 3.5 7 

2001 220 54 8.96 8.33 0.63 4.9 3.5 5.1 75.2 0.0 19.9 0.9 1.6 2.4 8 

2001 51 8 8.30 7.72 0.59 3.2 2.5 3.8 67.2 0.0 26.2 1.2 2.2 3.2 9 

2001 294 1 8.67 8.10 0.57 4.2 3.2 4.6 72.3 0.0 22.1 1.0 1.9 2.6 10 

2001 102 9 8.11 7.60 0.51 2.8 2.3 3.6 64.3 0.0 28.6 1.3 2.3 3.5 11 

2001 229 16 8.80 8.33 0.46 4.9 3.5 5.1 75.9 0.0 19.5 0.9 1.3 2.3 12 

2001 110 3 8.05 7.60 0.44 2.8 2.3 3.6 64.1 0.0 28.8 1.3 2.2 3.5 13 

2001 112 35 8.01 7.60 0.40 2.8 2.3 3.6 64.4 0.0 28.6 1.3 2.2 3.5 14 

2001 142 3 8.27 7.87 0.40 3.6 2.8 4.1 69.3 0.0 24.9 1.2 1.6 3.0 16 

2001 158 25 8.50 8.10 0.40 4.2 3.2 4.6 73.4 0.0 21.1 1.0 1.9 2.6 15 

2001 343 97 8.32 7.94 0.38 3.8 2.9 4.3 69.8 0.0 24.2 1.1 2.0 2.9 17 

2001 126 3 8.24 7.87 0.37 3.6 2.8 4.1 69.2 0.0 24.8 1.1 1.9 3.0 18 

2001 236 25 8.70 8.33 0.37 4.9 3.5 5.1 75.4 0.0 19.4 1.0 1.8 2.4 19 

2001 198 9 8.55 8.21 0.35 4.5 3.3 4.9 73.8 0.0 20.9 1.0 1.7 2.6 20 

 

2002 224 3 9.46 8.33 1.12 4.9 3.5 5.1 75.5 0.0 19.6 0.9 1.7 2.4 1 

2002 15 16 8.90 7.82 1.09 3.4 2.7 4.0 68.8 0.0 25.0 1.2 2.1 3.0 2 

2002 227 8 9.34 8.33 1.00 4.9 3.5 5.1 75.6 0.0 19.5 0.9 1.6 2.4 3 

2002 365 16 8.91 7.94 0.97 3.8 2.9 4.3 70.1 0.0 23.8 1.1 2.1 2.9 4 

2002 67 3 8.57 7.67 0.90 3.0 2.5 3.7 65.7 0.0 27.4 1.2 2.4 3.3 5 

2002 228 97 9.18 8.33 0.84 4.9 3.5 5.1 75.5 0.0 19.6 0.9 1.6 2.4 6 

2002 230 3 9.16 8.33 0.82 4.9 3.5 5.1 75.4 0.0 19.6 0.9 1.8 2.4 7 

2002 226 97 9.13 8.33 0.80 4.9 3.5 5.1 75.5 0.0 19.5 0.9 1.7 2.4 8 

2002 314 2 8.63 7.87 0.76 3.6 2.8 4.1 69.2 0.0 24.5 1.1 2.2 3.0 9 

2002 35 9 8.46 7.72 0.74 3.2 2.5 3.8 67.1 0.0 26.1 1.2 2.5 3.2 10 

2002 28 3 8.47 7.82 0.66 3.4 2.7 4.0 68.5 0.0 25.2 1.2 2.1 3.0 12 

2002 222 16 9.00 8.33 0.67 4.9 3.5 5.1 75.8 0.0 19.5 0.9 1.4 2.4 11 

2002 107 97 8.22 7.60 0.61 2.8 2.3 3.6 64.1 0.0 28.7 1.3 2.5 3.4 13 

2002 207 9 8.78 8.21 0.57 4.5 3.3 4.9 73.9 0.0 21.1 1.0 1.5 2.5 14 

2002 85 97 8.16 7.67 0.48 3.0 2.5 3.7 65.6 0.0 27.5 1.3 2.3 3.4 15 

2002 323 3 8.34 7.87 0.47 3.6 2.8 4.1 69.3 0.0 24.3 1.2 2.2 3.0 16 

2002 105 8 8.07 7.60 0.46 2.8 2.3 3.6 65.1 0.0 27.8 1.3 2.3 3.4 17 

2002 191 16 8.64 8.21 0.43 4.5 3.3 4.9 74.6 0.0 20.7 0.9 1.2 2.5 18 

2002 128 3 8.29 7.87 0.42 3.6 2.8 4.1 69.1 0.0 24.6 1.1 2.2 2.9 19 

2002 313 8 8.28 7.87 0.41 3.6 2.8 4.1 70.1 0.0 23.9 1.1 2.0 2.9 20 

 

2003 271 3 9.15 8.33 0.81 4.9 3.5 5.1 75.6 0.0 19.5 0.9 1.6 2.4 1 

2003 270 1 9.13 8.33 0.80 4.9 3.5 5.1 75.5 0.0 19.6 0.9 1.6 2.4 2 

2003 178 3 8.69 8.10 0.58 4.2 3.2 4.6 72.6 0.0 21.7 1.0 2.0 2.7 3 

2003 356 16 8.51 7.94 0.58 3.8 2.9 4.3 70.7 0.0 23.3 1.1 2.1 2.8 4 

2003 68 3 8.22 7.67 0.55 3.0 2.5 3.7 65.0 0.0 27.8 1.3 2.5 3.4 5 

2003 107 1 8.14 7.60 0.54 2.8 2.3 3.6 64.2 0.0 28.7 1.3 2.4 3.5 6 

2003 246 3 8.87 8.33 0.53 4.9 3.5 5.1 75.1 0.0 20.0 0.9 1.5 2.4 7 

2003 163 3 8.60 8.10 0.50 4.2 3.2 4.6 72.8 0.0 21.7 1.0 1.8 2.7 8 

2003 164 97 8.59 8.10 0.49 4.2 3.2 4.6 72.5 0.0 22.0 1.0 1.8 2.6 9 

2003 187 3 8.69 8.21 0.49 4.5 3.3 4.9 73.7 0.0 20.9 1.0 1.9 2.5 10 

2003 35 10 8.17 7.72 0.45 3.2 2.5 3.8 66.8 0.0 26.5 1.2 2.2 3.3 11 

2003 242 16 8.76 8.33 0.42 4.9 3.5 5.1 75.5 0.0 19.7 0.9 1.5 2.4 12 

2003 326 1 8.28 7.87 0.41 3.6 2.8 4.1 69.0 0.0 24.5 1.1 2.3 3.0 13 

2003 160 3 8.51 8.10 0.41 4.2 3.2 4.6 72.1 0.0 22.1 1.0 2.1 2.7 14 

2003 304 1 8.50 8.10 0.40 4.2 3.2 4.6 73.3 0.0 21.2 1.0 1.9 2.6 15 

2003 247 97 8.73 8.33 0.39 4.9 3.5 5.1 75.4 0.0 20.0 0.9 1.2 2.4 16 

2003 108 3 7.99 7.60 0.39 2.8 2.3 3.6 64.2 0.0 28.7 1.4 2.3 3.4 17 

2003 197 9 8.59 8.21 0.38 4.5 3.3 4.9 74.6 0.0 20.1 0.9 2.0 2.4 18 

2003 320 25 8.25 7.87 0.37 3.6 2.8 4.1 69.8 0.0 23.9 1.1 2.2 3.0 19 

2003 259 3 8.71 8.33 0.37 4.9 3.5 5.1 75.3 0.0 19.7 0.9 1.8 2.3 20 

 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 25 Days for 3 Years) 

Bowen 1-4 Results - Unit 2 Controlled with WESP 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 2 9.11 7.94 1.17 3.8 2.9 4.3 70.3 0.0 23.7 1.1 2.1 2.8 1 

2002 224 3 9.46 8.33 1.12 4.9 3.5 5.1 75.5 0.0 19.6 0.9 1.7 2.4 2 

2002 15 16 8.90 7.82 1.09 3.4 2.7 4.0 68.8 0.0 25.0 1.2 2.1 3.0 3 

2002 227 8 9.34 8.33 1.00 4.9 3.5 5.1 75.6 0.0 19.5 0.9 1.6 2.4 4 

2002 365 16 8.91 7.94 0.97 3.8 2.9 4.3 70.1 0.0 23.8 1.1 2.1 2.9 5 

2002 67 3 8.57 7.67 0.90 3.0 2.5 3.7 65.7 0.0 27.4 1.2 2.4 3.3 6 

2001 113 1 8.46 7.60 0.85 2.8 2.3 3.6 64.2 0.0 28.5 1.3 2.6 3.4 7 

2002 228 97 9.18 8.33 0.84 4.9 3.5 5.1 75.5 0.0 19.6 0.9 1.6 2.4 8 

2002 230 3 9.16 8.33 0.82 4.9 3.5 5.1 75.4 0.0 19.6 0.9 1.8 2.4 9 

2003 271 3 9.15 8.33 0.81 4.9 3.5 5.1 75.6 0.0 19.5 0.9 1.6 2.4 10 

2003 270 1 9.13 8.33 0.80 4.9 3.5 5.1 75.5 0.0 19.6 0.9 1.6 2.4 11 

2002 226 97 9.13 8.33 0.80 4.9 3.5 5.1 75.5 0.0 19.5 0.9 1.7 2.4 12 

2001 225 3 9.12 8.33 0.79 4.9 3.5 5.1 75.3 0.0 19.6 0.9 1.7 2.4 13 

2002 314 2 8.63 7.87 0.76 3.6 2.8 4.1 69.2 0.0 24.5 1.1 2.2 3.0 14 

2002 35 9 8.46 7.72 0.74 3.2 2.5 3.8 67.1 0.0 26.1 1.2 2.5 3.2 15 

2001 297 3 8.83 8.10 0.73 4.2 3.2 4.6 72.5 0.0 22.0 1.0 1.8 2.7 16 

2001 114 4 8.31 7.60 0.71 2.8 2.3 3.6 64.4 0.0 28.6 1.3 2.2 3.4 17 

2002 222 16 9.00 8.33 0.67 4.9 3.5 5.1 75.8 0.0 19.5 0.9 1.4 2.4 18 

2001 279 1 8.76 8.10 0.66 4.2 3.2 4.6 73.0 0.0 21.4 1.0 1.9 2.6 19 

2002 28 3 8.47 7.82 0.66 3.4 2.7 4.0 68.5 0.0 25.2 1.2 2.1 3.0 20 

2001 111 16 8.24 7.60 0.63 2.8 2.3 3.6 64.4 0.0 28.5 1.3 2.3 3.5 21 

2001 220 54 8.96 8.33 0.63 4.9 3.5 5.1 75.2 0.0 19.9 0.9 1.6 2.4 22 

2002 107 97 8.22 7.60 0.61 2.8 2.3 3.6 64.1 0.0 28.7 1.3 2.5 3.4 23 

2001 51 8 8.30 7.72 0.59 3.2 2.5 3.8 67.2 0.0 26.2 1.2 2.2 3.2 24 

2003 178 3 8.69 8.10 0.58 4.2 3.2 4.6 72.6 0.0 21.7 1.0 2.0 2.7 25 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 20 Days Each Year) 

Bowen 1-4 Results - Unit 3 Controlled with WESP 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 1 9.10 7.94 1.16 3.8 2.9 4.3 69.2 0.0 23.8 1.3 2.4 3.3 1 

2001 113 1 8.45 7.60 0.84 2.8 2.3 3.6 62.9 0.0 28.7 1.5 3.0 3.9 2 

2001 225 3 9.12 8.33 0.79 4.9 3.5 5.1 74.5 0.0 19.6 1.1 2.0 2.8 3 

2001 297 3 8.84 8.10 0.74 4.2 3.2 4.6 71.9 0.0 21.7 1.2 2.1 3.1 4 

2001 114 4 8.30 7.60 0.70 2.8 2.3 3.6 63.2 0.0 28.8 1.5 2.5 4.0 5 

2001 220 54 8.98 8.33 0.65 4.9 3.5 5.1 74.9 0.0 19.3 1.1 1.9 2.8 6 

2001 279 4 8.74 8.10 0.64 4.2 3.2 4.6 71.5 0.0 22.2 1.2 2.2 3.0 7 

2001 111 16 8.23 7.60 0.63 2.8 2.3 3.6 63.1 0.0 28.8 1.5 2.6 4.0 8 

2001 294 1 8.69 8.10 0.59 4.2 3.2 4.6 71.9 0.0 21.5 1.2 2.3 3.1 9 

2001 51 8 8.28 7.72 0.56 3.2 2.5 3.8 65.0 0.0 27.6 1.4 2.4 3.6 10 

2001 102 9 8.11 7.60 0.51 2.8 2.3 3.6 63.1 0.0 28.7 1.6 2.7 4.0 11 

2001 229 16 8.79 8.33 0.46 4.9 3.5 5.1 74.8 0.0 19.9 1.0 1.5 2.8 12 

2001 110 3 8.05 7.60 0.45 2.8 2.3 3.6 63.2 0.0 28.5 1.6 2.7 4.0 13 

2001 142 3 8.28 7.87 0.40 3.6 2.8 4.1 68.8 0.0 24.4 1.4 1.9 3.5 14 

2001 112 35 8.00 7.60 0.40 2.8 2.3 3.6 63.2 0.0 28.7 1.5 2.5 4.0 15 

2001 343 97 8.33 7.94 0.40 3.8 2.9 4.3 69.5 0.0 23.3 1.4 2.4 3.4 16 

2001 126 3 8.25 7.87 0.38 3.6 2.8 4.1 68.5 0.0 24.4 1.3 2.2 3.6 17 

2001 158 25 8.47 8.10 0.37 4.2 3.2 4.6 71.1 0.0 22.7 1.1 2.2 2.9 18 

2001 236 25 8.70 8.33 0.36 4.9 3.5 5.1 74.4 0.0 19.7 1.1 2.1 2.8 19 

2001 198 9 8.56 8.21 0.35 4.5 3.3 4.9 73.3 0.0 20.6 1.1 1.9 3.0 20 

 

2002 224 3 9.45 8.33 1.12 4.9 3.5 5.1 74.5 0.0 19.7 1.1 2.0 2.7 1 

2002 15 16 8.87 7.82 1.05 3.4 2.7 4.0 67.1 0.0 25.8 1.3 2.3 3.4 2 

2002 227 8 9.33 8.33 0.99 4.9 3.5 5.1 74.5 0.0 19.8 1.1 1.9 2.7 3 

2002 365 16 8.91 7.94 0.97 3.8 2.9 4.3 69.3 0.0 23.7 1.3 2.4 3.3 4 

2002 67 2 8.57 7.67 0.89 3.0 2.5 3.7 64.5 0.0 27.5 1.5 2.7 3.8 5 

2002 228 97 9.17 8.33 0.84 4.9 3.5 5.1 74.6 0.0 19.7 1.1 1.9 2.7 6 

2002 230 3 9.15 8.33 0.82 4.9 3.5 5.1 74.5 0.0 19.7 1.0 2.0 2.8 7 

2002 226 97 9.12 8.33 0.79 4.9 3.5 5.1 74.6 0.0 19.8 1.0 2.0 2.7 8 

2002 314 2 8.62 7.87 0.75 3.6 2.8 4.1 68.1 0.0 24.6 1.3 2.5 3.4 9 

2002 35 9 8.42 7.72 0.70 3.2 2.5 3.8 64.8 0.0 27.5 1.4 2.7 3.5 10 

2002 222 16 8.99 8.33 0.66 4.9 3.5 5.1 74.8 0.0 19.8 1.0 1.6 2.7 11 

2002 28 3 8.46 7.82 0.65 3.4 2.7 4.0 67.1 0.0 25.6 1.3 2.4 3.5 12 

2002 107 97 8.22 7.60 0.62 2.8 2.3 3.6 63.1 0.0 28.5 1.5 2.8 4.0 13 

2002 207 9 8.79 8.21 0.59 4.5 3.3 4.9 73.5 0.0 20.7 1.1 1.7 3.0 14 

2002 85 97 8.16 7.67 0.48 3.0 2.5 3.7 64.5 0.0 27.5 1.4 2.7 3.9 15 

2002 323 3 8.34 7.87 0.47 3.6 2.8 4.1 68.1 0.0 24.7 1.3 2.6 3.4 16 

2002 105 16 8.04 7.60 0.44 2.8 2.3 3.6 62.7 0.0 29.3 1.5 2.7 3.9 17 

2002 191 16 8.63 8.21 0.43 4.5 3.3 4.9 73.4 0.0 21.1 1.1 1.5 2.9 18 

2002 128 3 8.30 7.87 0.42 3.6 2.8 4.1 68.2 0.0 24.5 1.3 2.6 3.5 19 

2002 106 8 8.01 7.60 0.41 2.8 2.3 3.6 63.0 0.0 28.6 1.5 2.9 4.0 20 

 

2003 271 3 9.14 8.33 0.80 4.9 3.5 5.1 74.6 0.0 19.8 1.1 1.9 2.7 1 

2003 270 1 9.13 8.33 0.79 4.9 3.5 5.1 74.6 0.0 19.7 1.1 1.9 2.7 2 

2003 178 3 8.68 8.10 0.58 4.2 3.2 4.6 71.5 0.0 21.9 1.1 2.4 3.1 3 

2003 68 3 8.24 7.67 0.57 3.0 2.5 3.7 64.7 0.0 26.9 1.5 3.0 3.9 4 

2003 356 16 8.49 7.94 0.56 3.8 2.9 4.3 69.0 0.0 24.2 1.2 2.4 3.3 5 

2003 246 3 8.88 8.33 0.55 4.9 3.5 5.1 75.1 0.0 19.3 1.1 1.6 2.8 6 

2003 107 1 8.14 7.60 0.54 2.8 2.3 3.6 63.1 0.0 28.6 1.6 2.7 4.0 7 

2003 164 97 8.60 8.10 0.50 4.2 3.2 4.6 71.9 0.0 21.7 1.2 2.1 3.1 8 

2003 163 3 8.60 8.10 0.49 4.2 3.2 4.6 71.7 0.0 22.0 1.2 2.1 3.1 9 

2003 187 3 8.70 8.21 0.49 4.5 3.3 4.9 73.0 0.0 20.6 1.2 2.2 3.0 10 

2003 35 10 8.16 7.72 0.45 3.2 2.5 3.8 65.3 0.0 27.1 1.5 2.5 3.7 11 

2003 242 16 8.76 8.33 0.42 4.9 3.5 5.1 74.8 0.0 19.6 1.0 1.7 2.8 12 

2003 160 3 8.52 8.10 0.42 4.2 3.2 4.6 71.8 0.0 21.4 1.2 2.4 3.2 13 

2003 326 1 8.28 7.87 0.41 3.6 2.8 4.1 68.0 0.0 24.5 1.3 2.7 3.5 14 

2003 247 97 8.74 8.33 0.41 4.9 3.5 5.1 75.3 0.0 19.4 1.1 1.4 2.8 15 

2003 108 1 7.99 7.60 0.39 2.8 2.3 3.6 63.2 0.0 28.4 1.6 2.7 4.0 16 

2003 304 25 8.48 8.10 0.38 4.2 3.2 4.6 71.3 0.0 22.4 1.2 2.1 3.0 17 

2003 259 3 8.71 8.33 0.38 4.9 3.5 5.1 74.6 0.0 19.5 1.0 2.1 2.8 18 

2003 316 97 8.24 7.87 0.37 3.6 2.8 4.1 68.4 0.0 24.3 1.4 2.5 3.5 19 

2003 166 46 8.47 8.10 0.37 4.2 3.2 4.6 71.8 0.0 21.9 1.2 2.1 3.1 20 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 25 Days for 3 Years) 

Bowen 1-4 Results - Unit 3 Controlled with WESP 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 1 9.10 7.94 1.16 3.8 2.9 4.3 69.2 0.0 23.8 1.3 2.4 3.3 1 

2002 224 3 9.45 8.33 1.12 4.9 3.5 5.1 74.5 0.0 19.7 1.1 2.0 2.7 2 

2002 15 16 8.87 7.82 1.05 3.4 2.7 4.0 67.1 0.0 25.8 1.3 2.3 3.4 3 

2002 227 8 9.33 8.33 0.99 4.9 3.5 5.1 74.5 0.0 19.8 1.1 1.9 2.7 4 

2002 365 16 8.91 7.94 0.97 3.8 2.9 4.3 69.3 0.0 23.7 1.3 2.4 3.3 5 

2002 67 2 8.57 7.67 0.89 3.0 2.5 3.7 64.5 0.0 27.5 1.5 2.7 3.8 6 

2001 113 1 8.45 7.60 0.84 2.8 2.3 3.6 62.9 0.0 28.7 1.5 3.0 3.9 7 

2002 228 97 9.17 8.33 0.84 4.9 3.5 5.1 74.6 0.0 19.7 1.1 1.9 2.7 8 

2002 230 3 9.15 8.33 0.82 4.9 3.5 5.1 74.5 0.0 19.7 1.0 2.0 2.8 9 

2003 271 3 9.14 8.33 0.80 4.9 3.5 5.1 74.6 0.0 19.8 1.1 1.9 2.7 10 

2003 270 1 9.13 8.33 0.79 4.9 3.5 5.1 74.6 0.0 19.7 1.1 1.9 2.7 11 

2001 225 3 9.12 8.33 0.79 4.9 3.5 5.1 74.5 0.0 19.6 1.1 2.0 2.8 12 

2002 226 97 9.12 8.33 0.79 4.9 3.5 5.1 74.6 0.0 19.8 1.0 2.0 2.7 13 

2002 314 2 8.62 7.87 0.75 3.6 2.8 4.1 68.1 0.0 24.6 1.3 2.5 3.4 14 

2001 297 3 8.84 8.10 0.74 4.2 3.2 4.6 71.9 0.0 21.7 1.2 2.1 3.1 15 

2002 35 9 8.42 7.72 0.70 3.2 2.5 3.8 64.8 0.0 27.5 1.4 2.7 3.5 16 

2001 114 4 8.30 7.60 0.70 2.8 2.3 3.6 63.2 0.0 28.8 1.5 2.5 4.0 17 

2002 222 16 8.99 8.33 0.66 4.9 3.5 5.1 74.8 0.0 19.8 1.0 1.6 2.7 18 

2001 220 54 8.98 8.33 0.65 4.9 3.5 5.1 74.9 0.0 19.3 1.1 1.9 2.8 19 

2002 28 3 8.46 7.82 0.65 3.4 2.7 4.0 67.1 0.0 25.6 1.3 2.4 3.5 20 

2001 279 4 8.74 8.10 0.64 4.2 3.2 4.6 71.5 0.0 22.2 1.2 2.2 3.0 21 

2001 111 16 8.23 7.60 0.63 2.8 2.3 3.6 63.1 0.0 28.8 1.5 2.6 4.0 22 

2002 107 97 8.22 7.60 0.62 2.8 2.3 3.6 63.1 0.0 28.5 1.5 2.8 4.0 23 

2001 294 1 8.69 8.10 0.59 4.2 3.2 4.6 71.9 0.0 21.5 1.2 2.3 3.1 24 

2002 207 9 8.79 8.21 0.59 4.5 3.3 4.9 73.5 0.0 20.7 1.1 1.7 3.0 25 

 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 20 Days Each Year) 

Bowen 1-4 Results - Unit 4 Controlled with WESP 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 1 9.09 7.94 1.15 3.8 2.9 4.3 69.0 0.0 24.1 1.3 2.4 3.3 1 

2001 113 1 8.44 7.60 0.84 2.8 2.3 3.6 62.7 0.0 29.0 1.5 2.9 3.9 2 

2001 225 3 9.11 8.33 0.78 4.9 3.5 5.1 74.4 0.0 19.8 1.0 2.0 2.7 3 

2001 297 3 8.83 8.10 0.73 4.2 3.2 4.6 71.8 0.0 21.9 1.2 2.0 3.1 4 

2001 114 4 8.30 7.60 0.69 2.8 2.3 3.6 63.0 0.0 29.1 1.5 2.5 3.9 5 

2001 220 54 8.98 8.33 0.64 4.9 3.5 5.1 74.8 0.0 19.5 1.1 1.8 2.8 6 

2001 279 4 8.73 8.10 0.63 4.2 3.2 4.6 71.3 0.0 22.5 1.1 2.1 3.0 7 

2001 111 16 8.22 7.60 0.62 2.8 2.3 3.6 62.9 0.0 29.1 1.5 2.6 3.9 8 

2001 294 1 8.68 8.10 0.58 4.2 3.2 4.6 71.6 0.0 21.7 1.2 2.3 3.1 9 

2001 51 8 8.27 7.72 0.55 3.2 2.5 3.8 64.8 0.0 27.9 1.3 2.4 3.5 10 

2001 102 9 8.11 7.60 0.50 2.8 2.3 3.6 62.9 0.0 29.0 1.5 2.6 3.9 11 

2001 229 16 8.79 8.33 0.45 4.9 3.5 5.1 74.7 0.0 20.1 1.1 1.4 2.7 12 

2001 110 3 8.04 7.60 0.44 2.8 2.3 3.6 63.1 0.0 28.9 1.5 2.6 4.0 13 

2001 142 3 8.27 7.87 0.40 3.6 2.8 4.1 68.7 0.0 24.6 1.4 1.8 3.4 14 

2001 112 35 8.00 7.60 0.40 2.8 2.3 3.6 63.0 0.0 29.0 1.6 2.5 3.9 15 

2001 343 97 8.33 7.94 0.39 3.8 2.9 4.3 69.5 0.0 23.5 1.3 2.3 3.4 16 

2001 126 3 8.24 7.87 0.37 3.6 2.8 4.1 68.3 0.0 24.6 1.4 2.2 3.5 17 

2001 158 25 8.47 8.10 0.37 4.2 3.2 4.6 70.9 0.0 23.0 1.1 2.2 2.8 18 

2001 236 25 8.69 8.33 0.36 4.9 3.5 5.1 74.2 0.0 19.9 1.1 2.1 2.7 19 

2001 198 9 8.56 8.21 0.35 4.5 3.3 4.9 73.2 0.0 20.9 1.1 1.9 2.9 20 

 

2002 224 3 9.44 8.33 1.11 4.9 3.5 5.1 74.4 0.0 19.9 1.1 1.9 2.7 1 

2002 15 16 8.86 7.82 1.04 3.4 2.7 4.0 66.9 0.0 26.2 1.3 2.3 3.4 2 

2002 227 8 9.31 8.33 0.98 4.9 3.5 5.1 74.4 0.0 20.1 1.0 1.9 2.7 3 

2002 365 16 8.90 7.94 0.97 3.8 2.9 4.3 69.1 0.0 23.9 1.3 2.4 3.3 4 

2002 67 2 8.56 7.67 0.88 3.0 2.5 3.7 64.3 0.0 27.8 1.5 2.6 3.8 5 

2002 228 97 9.16 8.33 0.83 4.9 3.5 5.1 74.4 0.0 20.0 1.0 1.9 2.7 6 

2002 230 3 9.15 8.33 0.81 4.9 3.5 5.1 74.3 0.0 19.9 1.1 2.0 2.7 7 

2002 226 97 9.11 8.33 0.78 4.9 3.5 5.1 74.4 0.0 20.0 1.0 1.9 2.7 8 

2002 314 2 8.61 7.87 0.74 3.6 2.8 4.1 67.9 0.0 24.9 1.3 2.5 3.3 9 

2002 35 9 8.41 7.72 0.70 3.2 2.5 3.8 64.6 0.0 27.8 1.3 2.7 3.5 10 

2002 222 16 8.98 8.33 0.65 4.9 3.5 5.1 74.6 0.0 20.1 1.1 1.5 2.7 11 

2002 28 3 8.46 7.82 0.64 3.4 2.7 4.0 66.9 0.0 25.9 1.4 2.3 3.5 12 

2002 107 97 8.21 7.60 0.61 2.8 2.3 3.6 62.8 0.0 28.8 1.5 2.8 4.0 13 

2002 207 9 8.79 8.21 0.58 4.5 3.3 4.9 73.4 0.0 20.9 1.1 1.7 2.9 14 

2002 85 97 8.15 7.67 0.48 3.0 2.5 3.7 64.3 0.0 27.8 1.5 2.6 3.8 15 

2002 323 3 8.33 7.87 0.46 3.6 2.8 4.1 67.9 0.0 25.0 1.3 2.5 3.4 16 

2002 105 16 8.04 7.60 0.44 2.8 2.3 3.6 62.5 0.0 29.6 1.5 2.6 3.8 17 

2002 191 16 8.63 8.21 0.42 4.5 3.3 4.9 73.3 0.0 21.4 1.2 1.4 2.8 18 

2002 128 3 8.29 7.87 0.42 3.6 2.8 4.1 68.1 0.0 24.7 1.3 2.5 3.4 19 

2002 106 8 8.00 7.60 0.40 2.8 2.3 3.6 62.8 0.0 28.9 1.5 2.8 3.9 20 

 

2003 271 3 9.13 8.33 0.79 4.9 3.5 5.1 74.4 0.0 20.0 1.0 1.8 2.7 1 

2003 270 1 9.12 8.33 0.79 4.9 3.5 5.1 74.5 0.0 19.9 1.0 1.8 2.7 2 

2003 178 3 8.68 8.10 0.57 4.2 3.2 4.6 71.4 0.0 22.1 1.2 2.3 3.0 3 

2003 68 3 8.24 7.67 0.56 3.0 2.5 3.7 64.5 0.0 27.2 1.5 3.0 3.9 4 

2003 356 16 8.49 7.94 0.55 3.8 2.9 4.3 68.7 0.0 24.5 1.2 2.4 3.2 5 

2003 246 3 8.88 8.33 0.55 4.9 3.5 5.1 74.9 0.0 19.5 1.1 1.7 2.8 6 

2003 107 1 8.14 7.60 0.53 2.8 2.3 3.6 62.9 0.0 28.9 1.5 2.7 4.0 7 

2003 164 97 8.59 8.10 0.49 4.2 3.2 4.6 71.8 0.0 22.0 1.2 2.0 3.1 8 

2003 163 3 8.59 8.10 0.49 4.2 3.2 4.6 71.6 0.0 22.2 1.2 2.0 3.0 9 

2003 187 3 8.69 8.21 0.49 4.5 3.3 4.9 72.9 0.0 20.9 1.1 2.2 2.9 10 

2003 35 10 8.16 7.72 0.44 3.2 2.5 3.8 65.1 0.0 27.4 1.4 2.4 3.6 11 

2003 242 16 8.75 8.33 0.42 4.9 3.5 5.1 74.7 0.0 19.9 1.0 1.7 2.7 12 

2003 160 3 8.52 8.10 0.42 4.2 3.2 4.6 71.7 0.0 21.7 1.2 2.3 3.1 13 

2003 326 1 8.28 7.87 0.41 3.6 2.8 4.1 67.8 0.0 24.8 1.4 2.6 3.4 14 

2003 247 97 8.74 8.33 0.40 4.9 3.5 5.1 75.1 0.0 19.6 1.1 1.4 2.8 15 

2003 108 1 7.99 7.60 0.38 2.8 2.3 3.6 63.1 0.0 28.8 1.5 2.7 4.0 16 

2003 304 25 8.48 8.10 0.37 4.2 3.2 4.6 71.2 0.0 22.7 1.1 2.2 2.9 17 

2003 259 3 8.70 8.33 0.37 4.9 3.5 5.1 74.4 0.0 19.7 1.1 2.1 2.7 18 

2003 316 97 8.24 7.87 0.37 3.6 2.8 4.1 68.1 0.0 24.5 1.4 2.5 3.5 19 

2003 166 46 8.46 8.10 0.36 4.2 3.2 4.6 71.6 0.0 22.2 1.1 2.1 3.0 20 

 
New IMPROVE/Virtual Temp - Ranked Daily Visibility Change for Cohutta (Top 25 Days for 3 Years) 

Bowen 1-4 Results - Unit 4 Controlled with WESP 

 F(RH) % of Modeled Extinction by Species 

YEAR DAY REC DV(Total) DV(BKG) DELTA DV S L SS %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF Rank

2001 341 1 9.09 7.94 1.15 3.8 2.9 4.3 69.0 0.0 24.1 1.3 2.4 3.3 1 

2002 224 3 9.44 8.33 1.11 4.9 3.5 5.1 74.4 0.0 19.9 1.1 1.9 2.7 2 

2002 15 16 8.86 7.82 1.04 3.4 2.7 4.0 66.9 0.0 26.2 1.3 2.3 3.4 3 

2002 227 8 9.31 8.33 0.98 4.9 3.5 5.1 74.4 0.0 20.1 1.0 1.9 2.7 4 

2002 365 16 8.90 7.94 0.97 3.8 2.9 4.3 69.1 0.0 23.9 1.3 2.4 3.3 5 

2002 67 2 8.56 7.67 0.88 3.0 2.5 3.7 64.3 0.0 27.8 1.5 2.6 3.8 6 

2001 113 1 8.44 7.60 0.84 2.8 2.3 3.6 62.7 0.0 29.0 1.5 2.9 3.9 7 

2002 228 97 9.16 8.33 0.83 4.9 3.5 5.1 74.4 0.0 20.0 1.0 1.9 2.7 8 

2002 230 3 9.15 8.33 0.81 4.9 3.5 5.1 74.3 0.0 19.9 1.1 2.0 2.7 9 

2003 271 3 9.13 8.33 0.79 4.9 3.5 5.1 74.4 0.0 20.0 1.0 1.8 2.7 10 

2003 270 1 9.12 8.33 0.79 4.9 3.5 5.1 74.5 0.0 19.9 1.0 1.8 2.7 11 

2001 225 3 9.11 8.33 0.78 4.9 3.5 5.1 74.4 0.0 19.8 1.0 2.0 2.7 12 

2002 226 97 9.11 8.33 0.78 4.9 3.5 5.1 74.4 0.0 20.0 1.0 1.9 2.7 13 

2002 314 2 8.61 7.87 0.74 3.6 2.8 4.1 67.9 0.0 24.9 1.3 2.5 3.3 14 

2001 297 3 8.83 8.10 0.73 4.2 3.2 4.6 71.8 0.0 21.9 1.2 2.0 3.1 15 

2002 35 9 8.41 7.72 0.70 3.2 2.5 3.8 64.6 0.0 27.8 1.3 2.7 3.5 16 

2001 114 4 8.30 7.60 0.69 2.8 2.3 3.6 63.0 0.0 29.1 1.5 2.5 3.9 17 

2002 222 16 8.98 8.33 0.65 4.9 3.5 5.1 74.6 0.0 20.1 1.1 1.5 2.7 18 

2001 220 54 8.98 8.33 0.64 4.9 3.5 5.1 74.8 0.0 19.5 1.1 1.8 2.8 19 

2002 28 3 8.46 7.82 0.64 3.4 2.7 4.0 66.9 0.0 25.9 1.4 2.3 3.5 20 

2001 279 4 8.73 8.10 0.63 4.2 3.2 4.6 71.3 0.0 22.5 1.1 2.1 3.0 21 

2001 111 16 8.22 7.60 0.62 2.8 2.3 3.6 62.9 0.0 29.1 1.5 2.6 3.9 22 

2002 107 97 8.21 7.60 0.61 2.8 2.3 3.6 62.8 0.0 28.8 1.5 2.8 4.0 23 

2001 294 1 8.68 8.10 0.58 4.2 3.2 4.6 71.6 0.0 21.7 1.2 2.3 3.1 24 

2002 207 9 8.79 8.21 0.58 4.5 3.3 4.9 73.4 0.0 20.9 1.1 1.7 2.9 25