Regional Haze Plan

for

Florida Class I Areas

Prepared by

Florida Department of Environment Protection

Division of Air Resource Management

March 17, 2010 

(Amended August 31, 2010)

(Amended September 17, 2012)

(Amended March 10, 2015)

i
Preface: This document contains summaries of the technical analyses used by Florida’s 

Department of Environmental Protection (DEP), Division of Air Resource Management, to 

support Florida’s regional haze state implementation plan pursuant to §§107(d)(3)(D) and (E) of 

the Clean Air Act, as amended.

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TABLE OF CONTENTS

EXECUTIVE SUMMARY .......................................................................................................... vii

1.0 INTRODUCTION .................................................................................................................... 1

1.1 What is regional haze?.......................................................................................................... 1

1.2 What are the requirements under the Clean Air Act for addressing regional haze?............. 1

1.3 General overview of regional haze SIP requirements .......................................................... 2

1.4 Class I areas in and near Florida........................................................................................... 4

1.5 State and Federal Land Manager (FLM) coordination ......................................................... 5

2.0 ASSESSMENT OF BASELINE AND CURRENT CONDITIONS AND ESTIMATE OF 

NATURAL BACKGROUND CONDITIONS IN CLASS I AREAS ................................... 9

2.1 Estimating Natural Conditions for Florida Class I Areas................................................... 10

2.2 Estimating Baseline Conditions for Florida Class I Areas................................................. 10

2.3 Summary of Natural Background and Baseline Conditions for Florida Class I Areas ...... 11

2.4 Pollutant Contributions to Visibility Impairment (2000-2004 Baseline Data)................... 12

3.0 GLIDEPATHS TO NATURAL CONDITIONS IN 2064...................................................... 17

3.1 Glidepaths for Class I Areas in Florida and Nearby States ................................................ 17

4.0 NATURE OF THE PROBLEM: CHIEF CAUSES OF VISIBILITY IMPAIRMENT IN 

FLORIDA CLASS I AREAS............................................................................................... 24

4.1 Baseline Emissions Inventory............................................................................................. 24

4.1.1 Stationary Point Sources ............................................................................................ 25

4.1.2 Stationary Area Sources............................................................................................. 26

4.1.3 Off-Road Mobile Sources .......................................................................................... 26

4.1.4 Highway Mobile Sources........................................................................................... 27

4.1.5 Biogenic Emission Sources........................................................................................ 27

4.1.6 Summary 2002 Base G2 (February 2007 version) Baseline Emissions Inventory for 

FL..................................................................................................................................... 27

4.1.7 Model Performance Improvements through Emissions Inventory Improvements .... 28

4.2 Assessment of Relative Contributions from Specific Pollutants and Sources Categories . 29

5.0 REGIONAL HAZE MODELING METHODS AND INPUTS ............................................. 30

5.1 Analysis Method ................................................................................................................. 30

5.2 Model Selection .................................................................................................................. 31

5.2.1 Selection of Photochemical Grid Model .................................................................... 31

5.2.2 Selection of Meteorological Model............................................................................ 32

5.2.3 Selection of Emissions Processing System ................................................................ 33

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5.3 Selection of the Modeling Year.......................................................................................... 34

5.4 Modeling Domains ............................................................................................................. 36

5.4.1 Horizontal Modeling Domain .................................................................................... 36

5.4.2 Vertical Modeling Domain......................................................................................... 38

6.0 MODEL PERFORMANCE EVALUATION......................................................................... 39

6.1 Modeling Performance Goals, and Criteria ........................................................................ 40

6.2 VISTAS Domain-Wide Performance ................................................................................. 41

6.3 Florida Class 1 Areas Performance .................................................................................... 44

7.0 LONG-TERM STRATEGY FOR FLORIDA CLASS I AREAS.......................................... 50

7.1 Overview of the Long-Term Strategy Development Process............................................. 50

a.Assuming implementation of existing federal and state air regulatory requirements in 

Florida and the VISTAS region, how much visibility improvement, compared to the 

glidepath, would we expect to see at Class I areas in or near Florida between now and 

2018? ................................................................................................................................ 50

b.If additional emission reductions were needed, from what pollutants and source 

categories would the greatest visibility benefits be realized between the baseline and 

2018? ................................................................................................................................ 50

d.What is the process for identifying additional emission controls or reductions that 

represent reasonable progress for those specific sources? ............................................... 50

f. Given the additional emission reductions expected from BART and reasonable progress 

improvements, how much additional visibility improvement, compared to the glidepath, 

will we expect to see at Class I areas in Florida between the baseline and 2018?........... 50

7.2 Expected Visibility Results in 2018 for Florida Class I Areas under existing and planned 

emissions controls (G2 and, Best and Final Inventory (G4))........................................... 51

7.2.1 Federal and State Control Requirements.................................................................... 51

7.2.2 Additional State programs to reduce emissions......................................................... 53

7.2.3 Projected 2009 and 2018 G2 and Best and Final (G4) Emissions Inventories.......... 54

7.2.4 Model Results for the 2018 Base Best and Final (G4) Inventory Compared to the 

Uniform Rate of Progress Glidepaths for FL Class I Areas............................................. 56

7.3 Relative Contribution from International Emissions to Visibility Impairment in 2018 at 

VISTAS Class I areas....................................................................................................... 75

7.4 Relative Contributions to Visibility Impairment: Pollutants, Source Categories, and 

Geographic Areas............................................................................................................. 77

7.5 Relative Contributions to Visibility Impairment: Geographic Areas of Influence for 

Florida Class I Areas........................................................................................................ 81

7.5.1 Back Trajectory Analyses .......................................................................................... 81

7.5.2 Residence Time Plots................................................................................................. 82

7.5.3 SO2 Areas of Influence............................................................................................... 83

7.5.4 Emissions Sources within SO2 Areas of Influence .................................................. 84

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7.5.5 Specific Source Types in the Areas of Influence for Florida and Nearby Class I 

Areas ................................................................................................................................ 89

7.6 Reasonable Progress Requirement...................................................................................... 93

7.7 Florida’s Reasonable Progress Analysis............................................................................. 94

7.8 Best Available Retrofit Technology (BART) for Individual Sources.............................. 111

7.8.1 BART-Eligible Sources in Florida......................................................................... 112

7.8.2 Florida’s BART Rule ............................................................................................... 114

7.8.3 Determination of Sources Subject to BART in Florida ........................................... 115

7.8.4 Determination of BART Requirements for Subject-to-BART Sources................... 117

8.0 REASONABLE PROGRESS GOALS ................................................................................ 174

9.0 MONITORING STRATEGY............................................................................................... 175

10.0 INTERSTATE CONSULTATION .................................................................................... 178

11.0 COMPREHENSIVE PERIODIC IMPLEMENTATION PLAN REVISIONS ................. 178

12.0 DETERMINATION OF ADEQUACY OF THE EXISTING PLAN ................................ 180

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LIST OF EXHIBITS

Exhibit 1: Rules Adopted by the State

Exhibit 2: BART Determinations and Permits, Permits Necessary for BART Exemption, 

Reasonable Progress Determinations and Permits, and Verification of Shutdowns

Exhibit 3: Consultation Materials

LIST OF APPENDICES

Appendix A: VISTAS Memorandum of Understanding and Bylaws

Appendix B: Conceptual Description

Appendix C: Modeling Analysis Protocol and Quality Assurance Project Plan

Appendix D: Emissions Inventory Documentation

Appendix E: Air Quality and Meteorological Preparations and Results

Appendix F1: Technical Support Document – Emissions and Air Quality Modeling

Appendix F2: Meteorological Modeling Documentation

Appendix G: Global Modeling Documentation

Appendix H: Air Quality Modeling Sensitivity Analysis and Source Apportionment

Appendix I: Data Access

Appendix J: Analysis of Consent Decree and Voluntary Reductions

Appendix K: Recommended Improvements

Appendix L: Best Available Retrofit Technology (BART) Supporting Materials

Appendix M: Supporting Materials for Rule Development

Appendix N: Florida Smoke Management Plan

vi
EXECUTIVE SUMMARY

Pursuant to the Clean Air Act requirements contained in sections 169A and 169B, and the 

subsequent implementing regulations contained in 40 CFR 51.308, the State of Florida, 

Department of Environmental Protection (DEP), has developed a proposed State Implementation 

Plan (SIP) revision for regional haze. The SIP revision represents commitments and actions 

taken by the state affecting reasonable progress during the ten-year period from 2008 to 2018

towards the goal of attaining natural visibility conditions by 2064. It also provides for the 

implementation of Best Available Retrofit Technology (BART).

To develop this proposed SIP revision, the state has relied heavily on the work of the Southeast 

regional planning group VISTAS (Visibility Improvement States and Tribal Association of the 

Southeast). VISTAS is directed by the state air directors of 10 southeastern states, including all 

of the eight U.S. Environmental Protection Agency (EPA), Region 4 states plus Virginia and 

West Virginia. One staff person is directly connected to VISTAS – the technical coordinator. 

All other personnel resources are within the state programs. Funding for VISTAS has been 

through grants from EPA. 

The data and analysis necessary to meet the requirements of the federal regional haze regulations 

are considerable. The 10 states, through VISTAS, completed most of the technical requirements 

using contracted resources, managed by the technical coordinator. To help direct the technical 

work, the state directors created three workgroups. To effect an open and inclusive direction of 

work, the workgroups consisted of federal, state, and private stakeholder representatives. The 

federal representatives included EPA Regions 3 and 4, and federal land managers (or their 

representatives) from the National Park Service, the Fish and Wildlife Service, and the Forest 

Service. Private stakeholders included industry representatives with sources within the 10-state 

planning region. These workgroups discussed and reviewed the work completed by the 

contractors used by VISTAS. These data and analyses produced by VISTAS form the technical 

basis for Florida’s proposed SIP revision. 

Florida’s proposed regional haze SIP consists of a set of rules, commitments, permit conditions, 

and plans addressing the requirements of the federal regulations, as well as supporting

administrative and technical documentation. Specifically, the materials proposed to be 

incorporated into the SIP include this document, Florida’s Regional Haze Plan for Class I 

Areas, Exhibit 1, Exhibit 2 (excluding those elements of the permits not specifically related to 

the BART or reasonable progress emission limits), and Exhibit 3. This document and portions of 

the exhibits have been amended twice (August 2010 and September 2012) since their original 

submittal to EPA in March 2010.

The 2012 amendments were prompted by the court-ordered termination of EPA’s Clean Air 

Interstate Rule (CAIR) and EPA’s December 2011 proposal to disapprove those portions of 

Florida’s August 2010 proposed SIP revision that explicitly relied on CAIR. At the time of 

EPA’s proposed December 2011 limited disapproval, EPA anticipated that CAIR would be 

replaced by a successor rule, the Cross State Air Pollution Rule (CSAPR). But, CSAPR was 

subsequently stayed and then vacated by the D.C. Circuit Court on August 21, 2012. The Court 

further ordered EPA to continue implementing CAIR until such time as a valid replacement was 

vii
promulgated. As a result, CAIR remains in effect as of September 2012 and emission reductions 

from CAIR continue to occur. However, those portions of Florida’s August 2010 proposed SIP 

revision that had explicitly relied on CAIR or its replacement are removed in the September 

2012 amendments.

The primary elements of the Florida regional haze SIP are the following:

1. Rules 62-296.340, Florida Administrative Code (F.A.C.) (new), and 62-204.800, F.A.C. 

(amended) – These state rules implement the Best Available Retrofit Technology (BART) 

requirements. Rule 62-204.800, F.A.C., adopts the federal rule by reference, and Rule 62-

296.340 adds specific state-determined criteria as needed or required by the federal rule. For 

example, the state BART rule is implemented through the state’s air construction permit 

program, and the rule includes required application submission dates and BART compliance 

dates. The rule also makes certain decisions required of the federal regulations such as excluding 

ammonia and volatile organic compounds from BART review. At the time of rule adoption, 

EPA regulations allowed the state to presume that CAIR equals BART for sulfur dioxide (SO2) 

and nitrogen oxides (NOx) from electric generating units. Given the court-ordered termination 

of CAIR, Florida is not requesting EPA approval of Rule 62-296.340, F.A.C., to the extent it 

allows sources to rely on CAIR to comply with BART.

Outside of these rules, and in response to the uncertainty over CAIR’s eventual replacement,

DEP has completed source-specific BART determinations for the electric generating sources that 

had previously relied on CAIR. 

DEP has evaluated 46 facilities having units that meet the BART applicability requirements. Of 

these, 33 meet the exemption criteria in the rule, 7 have been shut down, and 6 have completed 

BART determinations.

2. Reasonable Progress Requirements – The state is required to consider four factors (cost, time 

to comply, energy and non-air impacts, and remaining useful life) in determining whether further 

reductions in visibility-impairing pollutants would be reasonable for any sources in the state. To 

limit the scope of this requirement, and based on a VISTAS analysis, DEP has focused its 

response to reasonable progress on sulfur dioxide (SO2) emissions from large energy generating 

and industrial sources. Based on criteria to identify, from among these sources, those that are 

most affecting visibility in Class I areas, 32 emissions units from 15 major facilities were 

targeted for four-factor review. 

Of the 32 units subject to reasonable progress review, nine have been shut down, and three units

have taken federally enforceable permit conditions that limit SO2 emissions such that they are no 

longer applicable to reasonable progress review. For the remaining 20 units, DEP has completed 

a four-factor reasonable progress determination.

3. Reasonable Progress Goals – The state is required to set reasonable progress goals in units of 

deciviews applicable for 2018. These goals represent the progress (visibility improvement) 

expected as a result of implementation of the long-range plan presented in this regional haze SIP. 

Two goals are set for each Class I area, one for the 20 percent worst days and one for the 20 

percent best days.

viii
 

Visibility (dv) Baseline (00-04) Natural Conditions 2018 Reasonable Progress 

Goals

Class I Area Best 

20%

Worst 

20%

Best 

20%

Worst 

20%

Best 20% Worst 20%

Chassahowitzka 15.51 25.75 5.91 11.03 13.91 22.27

Everglades 11.69 22.30 5.21 12.09 11.46 19.80

Saint Marks 14.37 26.31 5.39 11.67 12.80 22.92

These goals are based upon predicted visibility response to the expected emissions reductions of 

visibility-impairing pollutants using air quality models. As a result, a fair amount of uncertainty 

surrounds each of these goals, but they represent the state’s best estimate at this time. 

4. Rate of Progress Needed to Attain Natural Visibility Conditions by 2064 – Using the current 

estimate of natural conditions for the worst days, the uniform and predicted rates of progress for 

each of the Florida Class I areas is:

Worst 20 Percent Days

Class I Area Uniform Rate 

of Progress 

(dv/yr)

2018 Uniform 

Rate of 

Progress (dv)

2018 Predicted 

Rate of 

Progress (dv/yr)

2018 Predicted 

Visibility (dv)

Chassahowitzka 0.25 22.31 0.25 22.27

Everglades 0.17 19.92 0.18 19.80

Saint Marks 0.24 22.89 0.24 22.92

The regulatory requirement for the best 20 percent visibility days is that these days not get 

worse.

Best 20 Percent Days

Class I Area Uniform Rate 

of Progress 

(dv/yr)

2018 Uniform 

Rate of 

Progress (dv)

2018 Predicted 

Rate of 

Progress (dv/yr)

2018 Predicted 

Visibility (dv)

Chassahowitzka 0.00 15.51 0.11 13.91

Everglades 0.00 11.69 0.02 11.46

Saint Marks 0.00 14.37 0.11 12.80

Each of the three Florida Class I areas are predicted to progress at approximately the nominal 

uniform rate of progress for the initial planning period. Rates of progress needed to meet the 

natural visibility goal for subsequent planning periods will be dependent on the actual progress 

made in the previous planning periods. 

5. Long-Term Strategy for Regional Haze – The state has developed a long-term strategy that 

largely relies on rules and programs that will result, or have resulted, in significant improvement 

of visibility in Class I areas. The most significant of these rules is CAIR, which in conjunction 

with other existing rules results in visibility improvement in all the Class I areas equal to the 

nominal uniform rate of progress toward the national goal of natural conditions. The annual 

sulfur dioxide and nitrogen oxides emission reductions from CAIR that the state considered for 

the initial planning period have been fully realized as of 2010. These CAIR-based emission 

ix
reductions will continue to be realized for the foreseeable future, while EPA determines its next 

steps in response to the vacatur of CSAPR. . The long-term strategy also includes new 

reductions of visibility precursor emissions resulting from the BART and reasonable progress

requirements of the regional haze rule and the proposed new federal rule for Industrial, 

Commercial, and Institutional Boilers and Process Heaters (Boiler MACT rule). Initial 

compliance with these rules will occur at various times throughout the planning period. 

Through VISTAS, state-of-the-art air quality modeling was completed to analyze the regional, 

national, and global contributions to visibility in each Class I area. Emissions of visibilityimpairing pollutants were included from all known source sectors and locations, including 

boundary conditions derived from a global model. Current visibility conditions were evaluated 

using data from public and private monitoring networks, and these and other associated data 

were used to validate model performance. Projected emissions were developed for 2018, 

considering growth and known or estimated emissions changes due to existing regulations. 

Substantial analysis was completed to determine visibility sensitivity to specific pollutant 

reductions, and to parse-out the source-sector contributions.

The reasonable progress goals set forth in this plan, as amended in 2012, are largely based on 

continued implementation of the CAIR-driven emission reductions, along with other existing 

requirements. Regardless of CAIR’s current status, significant emission reductions forced by 

CAIR have occurred as of 2010. Thus, the reasonable progress goals expressed above remain 

valid for Florida. Moreover, as of September 2012, CAIR remains in effect and its associated 

emission reductions continue to occur. The following chart shows the actual Florida SO2

emissions compared to the original VISTAS projections used to determine Florida’s reasonable

progress goals. Actual SO2 emissions by 2010 (the most recent year of available data) are 

already less than the projected 2018 emissions. SO2 is the dominant visibility-impairing 

pollutant.

 

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

2000200120022003200420052006200720082009201020112012201320142015201620172018

tons

Florida SO2 Annual Emissions

Compared with Regional Haze SIP Projections

Actual

RH SIP

x
Importantly, the actual visibility measurements through 2010 at the three Florida Class I areas 

have responded consistent with the VISTAS predictions. The following charts show the 

observed vs. predicted visibility improvement for the 20 percent worst days for each Class I area.

xi
xii
The conclusion of this analysis is that the long-term strategy for attaining the 2064 visibility goal 

can rely on recent CAIR-driven emission reductions as well as existing and proposed new 

regulations to provide reasonable progress toward this goal during the first ten-year planning 

period ending in 2018. 

6. Commitments – The state is committing to complete a mid-point review of the long-range 

plan as required in the regional haze rule (40 CFR 51.308(g)). The time of the review will be 

coordinated with the other VISTAS states to take advantage of common analyses, but will be no

later than five years after submission of the initial implementation plan. DEP will review the 

progress of the projected emissions changes to judge the necessity of making any revisions to the 

plan. The state is also committing to complete comprehensive periodic revisions of the 

implementation plan for regional haze. The first revision is due to EPA by July 31, 2018, and 

every ten years thereafter.

xiii
1.0 INTRODUCTION

1.1 What is regional haze?

Regional haze is pollution from disparate sources that impairs visibility over a large region, 

including national parks, forests, and wilderness areas (federal “Class I” areas). Regional haze is 

caused by sources and activities emitting fine particles and their precursors. Those emissions are 

often transported over large regions. 

Particles affect visibility through the scattering and absorption of light, and fine particles –

particles similar in size to the wavelength of light – are most efficient, per unit of mass, at 

reducing visibility. Fine particles may either be emitted directly or formed from emissions of 

precursors, the most important of which are sulfur dioxides (SO2) and nitrogen oxides (NOx). 

Reducing fine particles in the atmosphere is generally considered to be an effective method of 

reducing regional haze, and thus improving visibility. Fine particles also adversely impact 

human health, especially respiratory and cardiovascular systems. The United States 

Environmental Protection Agency (EPA) has set national ambient air quality standards for daily 

and annual levels of fine particles with diameter smaller than 2.5 μm (PM2.5). The most 

important sources of PM2.5 and its precursors are coal-fired power plants, industrial boilers and 

other combustion sources. Other significant contributors to PM2.5 and visibility impairment 

include mobile source emissions, area sources, fires, and windblown dust.

1.2 What are the requirements under the Clean Air Act for addressing regional haze?

In Section 169A of the 1977 Amendments to the Clean Air Act (CAA), Congress set forth a 

program for protecting visibility in Federal Class I areas which calls for the “prevention of any 

future, and the remedying of any existing, impairment of visibility in mandatory Class I Federal 

areas which impairment results from manmade air pollution.” Congress adopted the visibility 

provisions to protect visibility in 156 national parks and wilderness areas. On December 2, 

1980, EPA promulgated regulations to address visibility impairment (45 FR 80084). The 1980 

regulations were developed to address visibility impairment that is “reasonably attributable” to a 

single source or small group of sources. These regulations represented the first phase in 

addressing visibility impairment and deferred action on regional haze that emanates from a 

variety of sources until monitoring, modeling and scientific knowledge about the relationships 

between pollutants and visibility impairment improved. 

In the 1990 Amendments to the CAA, Congress added section 169B and called on EPA to issue 

regional haze rules. The Regional Haze rule (RHR) that EPA promulgated on July 1, 1999 (64 

FR 35713), revised the existing visibility regulations in order to integrate provisions addressing 

regional haze impairment and establish a comprehensive visibility protection program for Class I 

Federal areas. States are required to submit state implementation plans (SIPs) to EPA that set 

out each state’s plan for complying with the regional haze rule, including consultation and 

coordination with other states and with federal land managers. The timing of the SIP submittal is 

tied to EPA’s promulgation of designations for the National Ambient Air Quality Standard 

(NAAQS) for fine particulate matter (PM2.5) at 40 CFR Part 81. States must submit a regional 

1
haze implementation plan to EPA within three years after the date of designation. Because EPA

promulgated designation dates on December 17, 2004, regional haze SIPs must be submitted by 

December 17, 2007, which is specified at 40 CFR 51.308(b).

The regional haze rule addressed the combined visibility effects of various pollution sources over 

a wide geographic region. This wide reaching pollution net meant that many states – even those 

without Class I Areas – would be required to participate in haze reduction efforts. EPA

designated five Regional Planning Organizations (RPO) to assist with the coordination and 

cooperation needed to address the visibility issue. Those states that make up the southeastern 

portion of the contiguous United States are known as VISTAS (Visibility Improvement – State 

and Tribal Association of the Southeast), and include the following states: Alabama, Florida, 

Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee, Virginia, and West 

Virginia.

 Figure 1.2-1. Geographical Areas of Regional Planning Organizations

1.3 General overview of regional haze SIP requirements

The regional haze rule (RHR) at 40 CFR 51.308(d) requires states to demonstrate reasonable 

progress toward meeting the national goal of a return to natural visibility conditions by 2064. As 

a guide for reasonable progress, the RHR directs states to graphically show what would be a 

“uniform rate of progress” toward natural conditions for each mandatory Class I Federal area 

within the state and/or for each mandatory Class I Federal area located outside the state, which 

may be affected by emissions from sources within the state. States are to establish baseline 

visibility conditions for 2000-2004, natural background visibility conditions in 2064, and the rate 

2
of uniform progress between baseline and background conditions. The uniform rate of progress 

is also known as the “glidepath.” 

The RHR then requires states to establish reasonable progress goals (RPGs), expressed in 

deciviews, for visibility improvement at each affected Class I area covering each 

(approximately) 10-year period until 2064. The goals must provide for reasonable progress 

towards achieving natural visibility conditions, provide for improvement in visibility for the 

most impaired days over the period of the implementation plan, and ensure no degradation in 

visibility for the least impaired days over the same period (40 CFR 51.308(d)(1)). 

In order to ensure that visibility goals are properly met and set, state implementation plans must 

include determinations, for each Class I area, of the baseline visibility conditions (expressed in 

deciviews) for the most impaired and least impaired days. SIPs must also contain supporting 

documentation for all required analyses used to calculate the degree of visibility impairment 

under natural visibility conditions for the most impaired and least impaired days (40 CFR 

51.308(d)(2)). In addition, states must include a monitoring strategy for measuring, 

characterizing, and reporting of regional haze visibility impairment that is representative of all 

mandatory Class I Federal areas within the state (40 CFR 51.308(d)(4)).

This first set of reasonable progress goals must be met through measures contained in the state’s 

long-term strategy covering the period from the present until 2018. The long-term strategy 

includes enforceable emissions limitations, compliance schedules, and other measures as 

necessary to achieve the reasonable progress goals, including all controls required or expected 

under all federal and state regulations by 2009 and by 2018. During development of the longterm strategy, states are also required to consider specific factors such as the abovementioned 

ongoing control programs, measures to mitigate construction activities, source retirement and 

replacement schedules, smoke management programs for agriculture and forestry, and 

enforceability of specific measures (40 CFR 51.308(d)(3)).

In addition, a specific component of each state’s first long-term strategy is dictated by the 

specific best available retrofit technology (BART) requirements in 40 CFR 51.308(e) of the 

RHR. The RHR at 40 CFR 51.308(e) requires states to include a determination of BART for 

each BART-eligible source in the state 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. Clean Air Act section 169A(b) defines BART-eligible sources as sources in 26 

specific source categories, in operation within a 15-year period prior to enactment of the 1977 

Clean Air Act Amendments. States must determine BART according to five factors set out in 

section 169A(g)(7) of the Clean Air Act. Emission limitations representing BART and schedules 

for compliance with BART for each source subject to BART must be included in the long-term 

strategy.

State Implementation Plans for the first review period are due December 17, 2007. These plans 

will cover long-term strategies for visibility improvement between baseline conditions in 2000-

2004 and 2018. States are required to evaluate progress toward reasonable progress goals every 

5 years to assure that installed emissions controls are on track with emissions reduction forecasts 

in each SIP. The first interim review would be due to EPA in December 2012. If emissions 

3
controls are not on track to meet SIP forecasts, then states would need to take action to assure 

emissions controls by 2018 will be consistent with the SIP or to revise the SIP to be consistent 

with the revised emissions forecast. 

1.4 Class I areas in and near Florida

Florida has four Class I areas within its borders: Everglades National Park, Chassahowitzka 

Wilderness Area, St. Marks Wilderness Area, and Bradwell Bay Wilderness Area. Bradwell Bay 

is one of only two Class I areas in the country for which visibility is not considered an important 

value. As such, the RHR does not apply to Bradwell Bay. Florida air pollution sources are 

within 300 kilometers of three other Class I areas located in other states, for which consideration 

of visibility impact on these out-of-state Class I areas must be addressed in the SIP. These are 

Okefenokee Wilderness Area (Georgia), Wolf Island Wilderness Area (Georgia), and Breton 

Wilderness Area (Louisiana). The Florida Division of Air Resource Management (DARM) in 

the Florida Department of Environmental Protection (DEP) is responsible for developing the 

Regional Haze SIP. This SIP establishes reasonable progress goals for visibility improvement at 

each of the Florida Class I areas, and a long-term strategy that will achieve those reasonable 

progress goals within the first regional haze planning period. 

Figure 1.4-1. Florida and Nearby Class I areas

4
In developing this SIP, we have also considered that emission sources outside of Florida may 

affect visibility at these Florida Class I areas, and that emission sources within Florida may affect 

visibility at the Class I areas in neighboring states. Through VISTAS, the southeastern states 

have worked together to assess state-by-state contributions to visibility impairment in specific 

class I areas, including those in Florida and those affected by emissions from Florida. This 

technical work is discussed further in chapters 5, 6, and 7 below. Consultations to date between 

Florida and other states are summarized in chapter 10; consultations are ongoing. 

1.5 State and Federal Land Manager (FLM) coordination

As required by 40 CFR 51.308(i), the regional haze SIP must include procedures for continuing 

consultation between the states and Federal Land Managers on the implementation of the 

visibility protection program, including development and review of implementation plan 

revisions and 5-year progress reports, and on the implementation of other programs having the 

potential to contribute to impairment of visibility in any mandatory Class I Federal area within 

the state. DEP commits to ongoing consultation with the FLMs throughout the implementation 

process, including annual discussion of the implementation process and the most recent 

IMPROVE monitoring data and VIEWS data.

Successful implementation of a regional haze program will involve long-term regional 

coordination among states. VISTAS was formed in 2001 to address regional haze and visibility 

problems in the southeastern United States. Jurisdictions represented by VISTAS members 

include the Eastern Band of Cherokee Indians; the States of Alabama, Florida, Georgia, 

Kentucky, Mississippi, North Carolina, South Carolina, Tennessee, Virginia, and West Virginia; 

and the local air pollution control programs located in these states. A copy of the VISTAS 

Memorandum of Agreement and Bylaws is enclosed as Appendix A.

The objectives of the VISTAS project are to establish natural background visibility conditions 

across the mandatory Class I Federal areas, identify current visibility impairment levels, analyze 

emission control levels that will achieve interim visibility goals, and provide adequate 

documentation to member agencies so that they can develop their regional haze State/Tribal 

Implementation Plans (SIP/TIP). Figure 1.5-1 shows the 18 mandatory Class I Federal areas in 

the VISTAS Region, where visibility is an important value. Figure 1.5-2 lists these Class I areas.

5
Figure 1.5-1. Class I Areas in the VISTAS Region

6
Mandatory Class I Federal Areas in the VISTAS Region

Where Visibility is an Important Value 

State Area Name Acreage Federal 

Land 

Manager

40 CFR §81.401 Alabama Sipsey Wilderness 12,646 USDA-FS

40 CFR §81.407 Florida Chassahowitzka Wilderness 23,360 USDIFWS

Everglades National Park 1,397,429 USDI-NPS

St. Marks Wilderness 17,745 USDIFWS

40 CFR §81.408 Georgia Cohotta Wilderness 33,776 USDA-FS

Okefenokee Wilderness 343,850 USDIFWS

Wolf Island Wilderness 5,126 USDIFWS

40 CFR §81.411 Kentucky Mammoth Cave National Park 51,303 USDI-NPS

40 CFR §81.422 North 

Carolina

Great Smoky Mountains National 

Park

273,551 USDI-NPS

Joyce Kilmer-Slickrock Wilderness 10,201 USDA-FS

Linville Gorge Wilderness 7,575 USDA-FS

Shining Rock Wilderness 13,350 USDA-FS

Swanquarter Wilderness 9,000 USDIFWS

40 CFR §81.426 South 

Carolina

Cape Romain Wilderness 28,000 USDIFWS

40 CFR §81.428 Tennessee Great Smoky Mountains National 

Park

241,207 USDI-NPS

Joyce Kilmer-Slickrock Wilderness 3,832 USDA-FS

40 CFR §81.433 Virginia James River Face Wilderness 8,703 USDA-FS

Shenandoah National Park 190,535 USDI-NPS

40 CFR §81.435 West 

Virginia

Dolly Sods Wilderness 10,215 USDA-FS

Otter Creek Wilderness 20,000 USDA-FS

Figure 1.5-2. Mandatory Class I Federal Areas in the VISTAS Region Where Visibility is 

an Important Value

A technical support document for the regional haze state implementation plans has been prepared 

cooperatively by VISTAS staff and states to characterize regional haze in the southeastern 

United States. The report includes a review of the science and situation, calculation of initial 

7
baseline visibility, review of monitoring data/data gaps, and recommendations for additional 

monitoring, initial emission inventory characterization and projections, and compliance with 

existing control programs. Source contributions to VISTAS mandatory Class I Federal areas are 

also assessed. This document is included as Appendix F1.

8
2.0 ASSESSMENT OF BASELINE AND CURRENT CONDITIONS AND 

ESTIMATE OF NATURAL BACKGROUND CONDITIONS IN CLASS I 

AREAS

The goal of the Regional Haze Rule is to restore natural visibility conditions to the 156 Class I 

areas identified in the 1977 Clean Air Act Amendments. Section 40 CFR 51.301(q) defines 

natural conditions: “Natural conditions include naturally occurring phenomena that reduce 

visibility as measured in terms of light extinction, visual range, contrast, or coloration.” The 

Regional Haze SIPs must contain measures that make “reasonable progress” toward this goal by 

reducing anthropogenic emissions that cause haze. 

An easily understood measure of visibility to most people is visual range. Visual range is the 

greatest distance, in kilometers or miles, at which a dark object can be viewed against the sky. 

For evaluating the relative contributions of pollutants to visibility impairment, however, the most 

useful measure of visibility impairment is light extinction, which is usually expressed in units of 

inverse megameters (Mm-1). Light extinction affects the clarity and color of objects being 

viewed.

The measure used by the regional haze rule is the deciview (dv). Deciviews are calculated 

directly from light extinction using a logarithmic scale. The deciview is a useful measure for 

tracking progress in improving visibility, because each deciview change is an equal incremental 

change in visibility perceived by the human eye. Most people can detect a change in visibility at 

one deciview.

For each Class I area, there are three metrics of visibility that are part of the determination of 

reasonable progress:

1) natural conditions, 

2) baseline conditions, and 

3) current conditions. 

Each of the three metrics includes the concentration data of the visibility pollutants as different 

terms in the light extinction algorithm, with respective extinction coefficients and relative 

humidity factors. Total light extinction when converted to deciviews (dv) is calculated for the 

average of the 20 percent best and 20 percent worst visibility days. 

“Natural” visibility is determined by estimating the natural concentrations of visibility pollutants 

and then calculating total light extinction. “Baseline” visibility is the starting point for the 

improvement of visibility conditions. It is the average of the Interagency Monitoring of 

Protected Visual Environments (IMPROVE) monitoring data for 2000 through 2004 and is 

equivalent to “current” visibility conditions for this initial review period. The comparison of 

initial baseline conditions to natural visibility conditions indicates the amount of improvement 

necessary to attain natural visibility by 2064. Each state must estimate natural visibility levels 

for Class I areas within its borders in consultation with Federal Land Managers and other states 

9
(51.308(d)(2)). “Current conditions” are assessed every five years as part of the SIP review 

where actual progress in reducing visibility impairment is compared to the reductions committed 

to in the SIP.

2.1 Estimating Natural Conditions for Florida Class I Areas

Natural background visibility, as defined in 2003 EPA guidance, is based on annual average 

concentrations of fine particle components. The same annual average natural background 

visibility is assumed for all Class I areas in the eastern United States (separate values are 

estimated for the western United States). Natural background visibility for the 20 percent worst 

days is estimated by assuming that fine particle concentrations for natural background are 

normally distributed and the 90th percentile of the annual distribution represents natural 

background visibility on the 20 percent worst days.

In the 2003 guidance, EPA also provided that states may use a “refined approach” to estimate the 

values that characterize the natural visibility conditions of the Class I areas. The purpose of such 

a refinement would be to provide more accurate estimates with changes to the extinction 

algorithm that may include the concentration values, factors to calculate extinction from a 

measured particular species and particle size, the extinction coefficients for certain compounds, 

geographical variation (by altitude) of a fixed value, and the addition of visibility pollutants. 

In 2005 the IMPROVE Steering Committee made recommendations for a refined equation that 

modifies the terms of the original equation to account for the most recent data. The choice 

between use of the old or the new equation for calculating the visibility metrics for each Class I 

area is made by the state in which the Class I area is located.

The new IMPROVE equation accounts for the effect of particle size distribution on light 

extinction efficiency of sulfate, nitrate, and organic carbon. The mass multiplier for organic 

carbon (particulate organic matter) is increased from 1.4 to 1.8. New terms are added to the 

equation to account for light extinction by sea salt and light absorption by gaseous nitrogen 

dioxide. Site-specific values are used for Rayleigh scattering to account for the site-specific 

effects of elevation and temperature. Separate relative humidity enhancement factors are used 

for small and large size distributions of ammonium sulfate and ammonium nitrate and for sea 

salt. The elemental carbon (light-absorbing carbon), fine soil, and coarse mass terms do not 

change between the original and new IMPROVE equation.

The VISTAS states chose to use the new IMPROVE equation as the basis for the conceptual 

description because it takes into account the most recent review of the science and because it is 

recommended by the IMPROVE Steering Committee. For more detailed discussion of the two 

IMPROVE equations, see Appendices B and L.

2.2 Estimating Baseline Conditions for Florida Class I Areas

Baseline visibility conditions at each Florida Class I area are estimated using sampling data 

collected at IMPROVE monitoring sites at the three Class I areas in Florida. A five year average 

10
(2000 to 2004) was calculated for each of the 20 percent worst and 20 percent best visibility days 

in accordance with 40 CFR 51.308(d)(2) and the EPA Guidance for Tracking Progress Under 

the Regional Haze Rule. When less than five years of data had been collected, an acceptable 

average was calculated if at least three complete years were available. When less than three 

years of data were available data substitution methods, as descibed in Appendix B, were used to 

provide sufficient data. IMPROVE data records for the Everglades had four years of complete 

data and no substitution of data was made. However, Chassahowitzka and St. Marks both 

required data substitution to make their records complete. The light extinction and deciview 

visibility values for the 20 percent worst and 20 percent best visibility days at the Class I areas 

are based on data and calculations included in Appendix B of this SIP. 

2.3 Summary of Natural Background and Baseline Conditions for Florida Class I Areas

Table 2.3-1 presents estimated natural background and baseline visibility metrics for Florida

Class I areas. Note that Florida is not considering international emissions to be a component of 

natural background. Baseline visibility on the 20 percent worst days is significantly better at 

Everglades (22.3 dv) than Chassahowitzka (25.7 dv) or St. Marks (26.3). On the other hand, 

natural background visibility is slightly worse for Everglades (12.1 dv) than either 

Chassahowitzka (11.0 dv) or St. Marks (11.7 dv). Visibility in the northern Florida Class I areas 

is generally better than the other Southeastern Class I areas, but the Everglades is significantly 

better than any of the Southeastern areas. 

11
Table 2.3-1 Natural Background and Baseline Conditions for Florida Class I Areas

Natural Background Conditions

Class 1 area Average for 

20 percent 

Worst Days

(deciviews)

Average for 

20 percent 

Best Days

(deciviews)

Average for 

20 percent 

Worst Days

Bext (Mm-1)

Average for 

20 percent 

Best Days

Bext (Mm-1)

Everglades N.P. 12.1 5.2 42.7 16.9

Chassahowitzka W.A. 11.0 5.9 30.5 18.1

St. Marks W.A. 11.7 5.4 33.1 17.2

Baseline Visibility Conditions 2000-2004

Class 1 area Average for 

20 percent 

Worst Days

(deciviews)

Average for 

20 percent 

Best Days

(deciviews)

Bext (Mm-1) 

Average for 

20 percent 

Worst Days

Bext (Mm-1) 

Average for 

20 percent 

Best Days

Everglades N.P. 22.3 11.7 116.4 32.3

Chassahowitzka W.A. 25.7 15.5 135.0 47.7

St. Marks W.A. 26.3 14.4 142.1 42.7

2.4 Pollutant Contributions to Visibility Impairment (2000-2004 Baseline Data)

The 20 percent best and worst visibility days at the Florida sites occur throughout the year. The 

worst days are associated with high sulfate levels, with many of the extremely bad visibility days

often associated with high organic carbon levels due to fires. 

Ammonium sulfate, (NH4)2SO4, is the most important contributor to visibility impairment and 

fine particle mass on the 20 percent worst and 20 percent best visibility days at all the Florida

Class I areas. Sulfate levels on the 20 percent worst days at Chassahowitzka and St. Marks

accounts for 60-70 percent of the visibility impairment. At the Everglades, sulfates account for 

30-60 percent of the impairment. Across the VISTAS region, sulfate levels are higher at the 

Southern Appalachian sites than at the coastal sites of which Florida is grouped (Figure 2.4-1). 

And the sulfate levels in the Everglades are significantly lower than even Chassahowitzka or St. 

Marks. On the 20 percent clearest days, sulfate levels are a little more uniform across the region 

(Figure 2.4-2), however, it still remains a relatively large fraction of the total visibility 

impairment. 

12
Figure 2.4-1. Average light extinction for the 20 percent Haziest Days in 2000-2004 at 

VISTAS and neighboring Class I areas using New IMPROVE equation 

Figure 2.4-2. Average light extinction for the 20 percent Clearest Days in 2000-2004 at 

VISTAS and neighboring Class I areas using New IMPROVE equation

VISTAS coastal VISTAS inland Neighboring non-VISTAS

0

50

100

150

200

250

300

Swanquarter, NC

Cae Romain, SC

Okefenokee, GA

Everglades, FL

Chassahowitzka, FL

St. Marks, FL

Dolly Sods, WV

Shenandoah, VA

James River Face, VA

Linville Gorge, NC

Shining Rock, NC

Great Smoky Mtns., TN

Cohutta, GA

Sipsey, AL

Mammoth Cave, KY

Brigantine, NJ

Breton, LAMingo, MO

Hercules Glade, MO

Upper Buffalo, AR

Caney Creek, AR

Extinction (Mm -1)

Sea Salt

Coarse

Soil

EC

POM

NH4NO3

(NH4)2SO4

Rayleigh

VISTAS coastal VISTAS inland Neighboring non-VISTAS

0

50

100

150

200

250

300

Swanquarter, NC

Cae Romain, SC

Okefenokee, GA

Everglades, FL

Chassahowitzka, FL

St. Marks, FL

Dolly Sods, WV

Shenandoah, VA

James River Face, VA

Linville Gorge, NC

Shining Rock, NC

Great Smoky Mtns., TN

Cohutta, GA

Sipsey, AL

Mammoth Cave, KY

Brigantine, NJ

Breton, LAMingo, MO

Hercules Glade, MO

Upper Buffalo, AR

Caney Creek, AR

Extinction (Mm -1)

Sea Salt

Coarse

Soil

EC

POM

NH4NO3

(NH4)2SO4

Rayleigh

0

10

20

30

40

50

60

Extinction (Mm-1)

Sea Salt

CM

Soil

EC

POM

NH4NO3

(NH4)2SO4

Rayleigh

VISTAS coastal VISTAS inland Neighboring non-VISTAS

Swanquarter, NC

Cae Romain, SC

Okefenokee, GA

Everglades, FL

Chassahowitzka, FL

St. Marks, FL

Dolly Sods, WV

Shenandoah, VA

James River Face, VA

Linville Gorge, NC

Shining Rock, NC

Great Smoky Mtns., TN

Cohutta, GA

Sipsey, AL

Mammoth Cave, KY

Brigantine, NJ

Breton, LAMingo, MO

Hercules Glade, MO

Upper Buffalo, AR

Caney Creek, AR

0

10

20

30

40

50

60

Extinction (Mm-1)

Sea Salt

CM

Soil

EC

POM

NH4NO3

(NH4)2SO4

Rayleigh

VISTAS coastal VISTAS inland Neighboring non-VISTAS

Swanquarter, NC

Cae Romain, SC

Okefenokee, GA

Everglades, FL

Chassahowitzka, FL

St. Marks, FL

Dolly Sods, WV

Shenandoah, VA

James River Face, VA

Linville Gorge, NC

Shining Rock, NC

Great Smoky Mtns., TN

Cohutta, GA

Sipsey, AL

Mammoth Cave, KY

Brigantine, NJ

Breton, LAMingo, MO

Hercules Glade, MO

Upper Buffalo, AR

Caney Creek, AR

13
Sulfate particles are formed in the atmosphere from sulfur dioxide emissions. Sulfate particles 

occur as hydrogen sulfate, H2(SO4), ammonium bisulfate HNH4SO4, and ammonium sulfate, 

(NH4)2SO4, depending on the availability of ammonia, NH3, in the atmosphere. 

Particulate Organic Matter (POM) is the second most important contributor to fine particle mass 

and light extinction on the 20 percent haziest and the 20 percent clearest days at the Florida Class 

I areas. Elevated levels of POM and Elemental Carbon, EC, indicate impact from wildfires or 

prescribed fire. Significant fire impacts are frequent enough to affect the Class I areas in Florida. 

Fires tend to be episodic and associated with dry conditions so year to year impacts can vary 

considerably. VISTAS collected additional samples of carbon at five sites, including Great 

Smoky Mountains and Millbrook, (Raleigh, NC), to better understand sources contributing to 

carbon in rural and urban areas. At Great Smoky Mountains and other mountain Class I areas 

the majority of carbon is from either biogenic emissions from vegetation or from wood burning. 

Wood burning is more important in the fall, winter, and early spring months. Biogenic 

emissions, chiefly emissions of volatile organics (VOC) from vegetation, peak in spring and 

summer. Biogenic carbon emissions at Cape Romain, SC, a coastal site similar to Swanquarter, 

were lower than emissions at the forested mountain sites. Carbon from gasoline and diesel 

engines is a relatively small contribution at the rural sites. At Millbrook, carbon from fossil fuel 

combustion is a larger percentage contribution than at the rural sites, but still less than 50 percent 

of total carbon measured. These results suggest that controlling anthropogenic sources of carbon 

will have little benefit in improving visibility in Class I areas. Controlling anthropogenic sources 

of carbon will likely be more effective to reduce levels of PM2.5 in urban areas. 

Ammonium nitrate, NH4NO3, is formed in the atmosphere by reaction of ammonia and nitrogen 

oxides. In the VISTAS region, nitrate formation is limited by availability of ammonia and by 

temperature. Ammonia preferentially reacts with sulfur dioxide and sulfate before reacting with 

nitrogen oxides. Particle nitrate is formed at lower temperatures; at elevated temperatures nitric 

acid remains in gaseous form. For this reason, particle nitrate levels are very low in the summer 

and a minor contributor to visibility impairment. Particle nitrate concentrations are higher on 

winter days and are more important for the coastal sites where 20 percent worst days can occur 

on winter days. Nitrogen oxides are emitted by fossil fuel combustion by point, area, on road, 

and non road sources. Modeling data (see section 7) indicate that in the VISTAS region 

ammonium nitrate formation is limited by ammonia concentrations and suggest that for winter 

days, controls of ammonia sources would be more effective in reducing ammonium nitrate levels 

than controls of nitrogen oxides. 

Elemental Carbon, EC, is a comparatively minor contributor to visibility impairment. Sources 

include agriculture, prescribed, wildland, and wild fires and incomplete combustion of fossil 

fuels. EC levels are higher at urban monitors than at the Class I areas and suggest controls of 

fossil fuel combustion sources would be more effective to reduce PM2.5 in urban areas than to 

improve visibility in Class I areas. 

Soil fine particles are minor contributors to visibility impairment at most sites on most days. 

Occasional episodes of elevated fine soil can be attributed to Saharan dust episodes, particularly 

at Everglades. No control strategies are indicated for fine soil. 

14
Sea salt, NaCl, is observed at the coastal sites. Sea salt contributions to visibility impairment are 

most important on the 20 percent clearest days when sulfate and POM levels are low. Sea salt 

levels do not contribute significantly to visibility on the 20 percent worst visibility days. The 

new IMPROVE equation uses Chloride ion, Cl-

, from routine IMPROVE measurements to 

calculate sea salt levels. Cl- may react with nitrate and volatize off the filter, so that Cl- may 

underestimate sea salt levels. VISTAS funded sodium ion, Na+, analyses of the IMPROVE 

filters from Oct 2003 to Dec 2004 for nine sites. Sodium ion measures may overestimate sea salt 

levels because sodium nitrate is an additional source of sodium ion that cannot be distinguished 

from sodium chloride. Our best understanding to date suggests that using Cl- may underestimate 

sea salt levels by as much as a factor of two. This uncertainty has greatest implications for 

calculating sea salt levels under natural visibility conditions. 

Coarse particle mass (particles with diameters between 2.5 and 10 microns) has a relatively 

small contribution to visibility impairment because the light extinction efficiency of coarse mass 

is very low compared to the extinction efficiency for sulfate, nitrate, and carbon. 

An unidentified component is reported by IMPROVE as the difference between the total PM2.5 

mass measured on the filter and the sum of the measured components. This unidentified mass 

may be positive or negative and is attributable to water and/or the factors used to calculate 

molecular weights of the other components. 

 

The New IMPROVE equation generally results in higher calculated light extinction on days with 

higher mass and lower light extinction on days with lower mass. This tends to increase 

calculated light extinction for current conditions and to decrease calculated light extinction for 

natural visibility conditions. Adding sea salt to the new IMPROVE equation increases light 

extinction for both current and natural visibility conditions. Increasing the mass multiplier for 

particulate organic matter in the new IMPROVE equation increases light extinction for current 

conditions more than for natural conditions. The new algorithm does not change the conclusion 

that in the VISTAS region and in Florida, the most effective means to improve visibility is to 

reduce sulfate concentrations.

PM2.5 trends in urban and Class I areas: IMPROVE data were compared to monitoring data 

from the Speciated Trends Network (STN) in nearby urban areas to understand the similarities 

and differences in composition of fine particle mass. Several PM2.5 nonattainment areas are in 

close proximity to the Class I areas in the southeastern US, including Atlanta, GA; Birmingham, 

AL; Charleston, WV; Chattanooga, TN; Louisville, KY; and Knoxville, TN. Ammonium 

sulfate concentrations are comparable between urban and nearby Class I areas, while organic 

carbon, elemental carbon, and nitrate concentration are generally higher in urban areas than the 

Class I areas. These results suggest that sulfate is widely distributed regionally while urban areas 

see an additional incremental pollutant loading from local emissions sources. 

Role of meteorology in determining visibility conditions: Classification and Regression Tree 

Analyses were used to characterize the relationship between meteorological conditions and 

visibility conditions at the Class I areas. Days were assigned to one of five visibility classes 

ranging from poor to good visibility. Days were then assigned to bins based on meteorological 

15
conditions. For the central and northern Florida Class I areas poor visibility days were most 

likely to occur on days with high temperatures, high relative humidity, low wind speeds, where 

previous days were also with poorer visibility. That is poor visibility is usually a multi-day event 

with building pollution levels. Precipitation was not a good predictor of visibility condition. In 

South Florida (Everglades), poor visibility is not differentiated by high temperatures and relative 

humidity and is more related to precipitation and number of rain events. Weights were assigned 

to days based on frequency of occurrence of days with similar meteorological conditions. 

The above analyses are further discussed in Appendix B. Also, the pollutant-specific extinction 

for each of the best and worst 20 percent days are provided graphically in Appendix E, subAppendix E.3. 

16
3.0 GLIDEPATHS TO NATURAL CONDITIONS IN 2064

As stated in section 1.3 above, the RHR directs states to graphically show what would be a 

“uniform rate of progress” toward natural conditions for each mandatory Class I Federal area 

within the state as well as for each mandatory Class I Federal area located outside the state, 

which may be affected by emissions from sources within the state. The uniform rate of progress 

is also known as the “glidepath.” The glidepath is simply a straight graphical line drawn from 

the baseline level of visibility impairment for 2000-2004 to the level representing no manmade 

impairment in 2064.

Each state must set goals for each Class I area that provide for reasonable progress towards 

achieving natural visibility conditions by 2064. Section 51.308(d)(1) of the regional haze rule 

requires that reasonable progress goals must both: 

(1) provide for improvement in visibility for the most impaired days over the period of the 

implementation plan; and

(2) ensure no degradation in visibility for the least impaired days over the same period. 

Uniform rate of progress graphs (glidepaths), were developed for each Class I area in the 

VISTAS region. The glidepaths were developed in accordance with EPA guidance and used 

data collected from the IMPROVE monitoring sites as described in section 2 above. The 

glidepath is one of the indicators used in setting reasonable progress goals. 

3.1 Glidepaths for Class I Areas in Florida and Nearby States

The following are glidepaths for the 20 percent most impaired days for Everglades National 

Park, Chassahowitzka National Wilderness Area, St. Marks National Wilderness Area, 

Okefenokee National Wilderness Area, and Breton National Wilderness Area, assuming uniform 

rate of progress toward regional haze goals. Wolf Island National Wilderness Area does not 

have an IMPROVE monitor and the Okefenokee site acts as its surrogate. Natural background 

visibility at all five sites is calculated to be about 11 to 12 dv. In general, these five Class I areas 

have better visibility conditions than in other areas of the Southeast. Of these five areas, 

Okefenokee has the worst current visibility and has greatest improvement to make to achieve 

natural visibility conditions (Table 3.1.1). The Everglades has the best current visibility 

conditions in the entire Southeast, and has the least amount of needed improvement to achieve 

natural conditions.

17
Table 3.1.1 – Rank Order of Current Visibility for Southeastern Class I Areas

Class I Area State

Baseline -

Avg. of 20% 

Worst Days 

(2000-2004) 

(dv)

Natural 

Background 

Goal (dv)

Necessary 

Improvement in 

Visibility to Attain 

Goal (dv)

Everglades FL 22.30 12.09 10.21

Swanquarter NC 24.71 11.55 13.17

Chassahowitzka FL 25.75 11.03 14.71

Breton LA 26.00 11.93 14.07

Upper Buffalo AR 26.27 11.49 14.78

Saint Marks FL 26.31 11.67 14.64

Caney Creek AR 26.36 11.57 14.79

Cape Romain SC 26.48 12.10 14.38

Hercules - Glade MO 26.75 11.24 15.50

Okefenokee GA 27.13 11.21 15.93

Mingo MO 28.05 11.62 16.43

Shining Rock NC 28.66 11.47 17.18

Linville Gorge NC 28.77 11.19 17.59

Brigantine NJ 29.01 12.06 16.95

Sipsey AL 29.03 10.90 18.12

Dolly Sods WV 29.04 10.36 18.68

James River Face VA 29.12 11.09 18.02

Shenandoah VA 29.31 11.37 17.94

Cadiz KY 29.39 10.82 18.58

Cohutta GA 30.25 10.78 19.48

Great Smoky Mountains TN 30.28 11.05 19.22

Mammoth Cave KY 31.37 11.08 20.29

18
Figure 3.1-1. Uniform Rate of Progress Glidepath for 20 percent worst days at Everglades

National Park. 

Uniform Rate of Progress Glide Path

Everglades - W20% Data Days

22.30 21.45

19.92

18.22

16.52

14.82

13.11 12.09

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation

19
Figure 3.1-2. Uniform Rate of Progress Glidepath for 20 percent worst days 

Chassahowitzka National Wilderness Area. 

Uniform Rate of Progress Glide Path

Chassahowitzka - W20% Data Days

25.75

24.52

22.31

19.86

17.41

14.96

12.50

11.03

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation

20
Figure 3.1-3. Uniform Rate of Progress Glidepath for 20 percent worst days at St. Marks 

National Wilderness Area.

Uniform Rate of Progress Glide Path

Saint Marks - W20% Data Days

26.31

25.09

22.89

20.45

18.01

15.57

13.13

11.67

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation

21
Figure 3.1-4. Uniform Rate of Progress Glidepath for 20 percent worst days at Okefenokee 

National Wilderness Area. 

Uniform Rate of Progress Glide Path

Okefenokee - W20% Data Days

27.13

25.81

23.42

20.76

18.11

15.45

12.80

11.21

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation

22
Figure 3.1-5. Uniform Rate of Progress Glidepath for 20 percent worst days at Breton 

National Wilderness Area.

Uniform Rate of Progress Glide Path

Breton - W20% Data Days

26.00

24.82

22.71

20.37

18.02

15.68

13.34

11.93

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation

23
4.0 NATURE OF THE PROBLEM: CHIEF CAUSES OF VISIBILITY 

IMPAIRMENT IN FLORIDA CLASS I AREAS

4.1 Baseline Emissions Inventory

The Regional Haze Rule at 40 CFR 51.308(d) (4) (v) requires a statewide emissions inventory of 

pollutants that are reasonably anticipated to cause or contribute to visibility impairment in any 

mandatory Class I area. An inventory was developed for the baseline year 2002 and projected to 

2009 and 2018. The pollutants inventoried include volatile organic compounds, nitrogen oxides, 

fine particulate (PM2.5), coarse particulate (PM10), ammonia and sulfur dioxide. The baseline 

emissions inventory for 2002 was developed for Florida and the other VISTAS states following 

the methods described in Appendix D. 

There are five different emission inventory source classifications: stationary point and area 

sources, off-road and on-road mobile sources, and biogenic sources. Stationary point sources are 

those sources that emit greater than a specified tonnage per year, with data provided at the 

facility level. Electric generating utilities and industrial sources are the major categories for 

stationary point sources. Stationary area sources are those sources whose individual emissions 

are relatively small, but due to the large number of these sources, the collective emissions from 

the source category could be significant (i.e., dry cleaners, service stations, agricultural sources, 

fire emissions, etc.). These types of emissions are estimated on a countywide level. Non-road 

(or off-road) mobile sources are equipment that can move but do not use the roadways, i.e., lawn 

mowers, construction equipment, railroad locomotives, aircraft, etc. The emissions from these 

sources, like stationary area sources, are estimated on a countywide level. On-road mobile 

sources are automobiles, trucks, and motorcycles that use the roadway system. The emissions 

from these sources are estimated by vehicle type and road type and are summed to the 

countywide level. Biogenic sources are the natural sources like trees, crops, grasses and natural 

decay of plants. The emissions from these sources are estimated on a countywide level.

In addition to the various source classifications, there are also various types of emission 

inventories. The first is the actual base year inventory. This inventory is the base year emissions 

that correspond to the meteorological data used, which for this modeling effort is data from 

2002. These emissions are used for evaluating the air quality model performance. 

The second type of inventory is the typical base year inventory. This inventory is similar to the 

actual base year inventory, except that for sources whose emissions change signficantly from 

year to year, a more typical emission value is used. In this modeling effort, typical emissions 

were developed for the electric generating units (EGUs) and the wildland fire emissions. The air 

quality modeling runs using the typical base year inventory provide results which are then used 

to calculate relative reduction factors for future years. These relative reduction factors for future 

years are then used to demonstrate reasonable progress toward visibility goals. 

Below is an overview of the inventories used for each source classification. More detailed 

discussion of the emissions inventory development is contained in Appendix D. 

24
4.1.1 Stationary Point Sources

Point source emissions are emissions from individual sources having a fixed location. Generally, 

these sources must have permits to operate, and their emissions are inventoried on a regular 

schedule. Large sources emitting at least 100 tons per year (tpy) of a criteria pollutant, 10 tpy of 

a single hazardous air pollutant (HAP), or 25 tpy total HAP are inventoried annually. Smaller 

sources have been inventoried less frequently. The point source emissions data can be grouped 

as EGU sources and other industrial point sources, also called non-EGUs.

Electric Generating Units

The actual base year inventory for the EGU sources used 2002 continuous emissions monitoring 

(CEM) data reported to the EPA’s Acid Rain program or 2002 hourly emissions data provided 

by stakeholders. These data provide hourly emissions profiles for SO2 and NOx that can be used 

in air quality modeling. Emissions profiles are used to estimate emissions of other pollutants 

(volatile organic compounds, carbon monoxide, ammonia, fine particles, soil) based on measured 

emissions of SO2 and NOx. 

Emissions from EGU vary daily and seasonally as a function of variability in energy demand and 

utilization and outage schedules. To avoid anomalies in future year emissions created by relying 

on 2002 operations to represent future operations, a typical base year emissions inventory was 

developed for EGUs. This approach is consistent with the EPA’s modeling guidance. To 

develop a typical year 2002 emissions inventory for EGU sources, each unit’s average CEM heat 

input for 2000 through 2004 was divided by the 2002 actual heat input to generate a unit specific 

normalizing factor. This normalizing factor was then multiplied by the 2002 actual emissions. 

The heat inputs for the period 2000 through 2004 were used because the modeling current design 

values use monitored data from this same 5-year period. If a unit was shut down for an entire 

year during the 2000 through 2004 period, the average of the years the unit was operational was 

used. If a unit was shut down in 2002, but not permanently shutdown, the emissions and heat 

inputs from 2001 (or 2000) were used in the normalizing calculations. 

As part of the VISTAS air quality modeling, VISTAS, in cooperation with the other eastern 

RPOs, contracted with ICF Resources, L.L.C., to generate future year emission inventories for 

the electric generating sector of the contiguous United States using the Integrated Planning 

Model (IPM). IPM is a dynamic linear optimization model that can be used to examine air 

pollution control policies for various pollutants throughout the contiguous United States for the 

entire electric power system. The dynamic nature of IPM enables projection of the behavior of 

the power system over a specified future period. Optimization logic in IPM determines the leastcost means of meeting electric generation and capacity requirements while complying with 

specified constraints including air pollution regulations, transmission bottlenecks, and plantspecific operational constraints. The versatility of IPM allows users to specify which constraints 

to exercise, and to populate IPM with their own datasets. 

Other Industrial Point Sources

For the non-EGU sources, the same inventory is used for both the actual and typical base year 

emissions inventories. The non-EGU category uses annual emissions as reported under the 

25
Consolidated Emissions Reporting Rule (CERR) for the year 2002. These emissions are 

temporally allocated to month, day, and hour using source category code (SCC)-based allocation 

factors. 

The general approach for assembling future year data was to use recently updated growth and 

control data consistent with EPA’s CAIR analyses. This data was supplemented with statespecific growth factors and stakeholder input on growth assumptions.

4.1.2 Stationary Area Sources

Stationary area sources are sources whose individual emissions are relatively small, but due to 

the large number of these sources, the collective emissions could be significant (i.e., combustion 

of fuels for heating, structure fires, service stations, etc.). Emissions are estimated by 

multiplying an emission factor by some known indicator of collective activity, such as fuel 

usage, number of households, or population. Stationary area source emissions are estimated at 

the countywide level.

The actual base year inventory will serve as the typical base year inventory for all area source 

categories except for wildland fires. For wildland fires, a typical year inventory was used to 

avoid anomalies in wildfire activity in 2002 compared to longer term averages. Development of 

a typical year fire inventory provided the capability of using a comparable data set for both the 

base year and future years. Thus, fire emissions remain the same for air quality modeling in both 

the base and any future years. The VISTAS Fire Special Interest Work Group used state records 

to ratio the number of acres burned over a longer term period (three or more years, as available 

from state records) to 2002. Based on these ratios, the 2002 acreage was then scaled up or down 

to develop a typical year inventory. 

Future year emissions

The VISTAS contractor generated future year emissions inventories for 2009 and 2018 for the 

regional haze modeling. Growth factors, supplied either by states or taken from the CAIR 

emission projections, were applied to project the controlled emissions to 2018. If no growth 

factor was available from either a state or the CAIR growth factor files, then the EPA’s 

Economic Growth and Analysis System Version 5 growth factors were used.

4.1.3 Off-Road Mobile Sources

Off-road (or non-road) mobile sources are equipment that can move but do not use the roadways, 

such as construction equipment, aircraft, railroad locomotives, lawn and garden equipment, etc. 

For the majority of the non-road mobile sources, the emissions for 2002 were estimated using the 

EPA’s NONROAD2005c model. For the three source categories not included in the 

NONROAD model, i.e., aircraft engines, railroad locomotives and commercial marine, more 

traditional methods of estimating the emissions were used. The same inventory is used for both 

the actual and typical base year emissions inventories. 

For the source categories estimated using the EPA’s NONROAD model, the model growth 

assumptions were used to create the 2009 and 2018 future year inventories. The NONROAD 

26
model takes into consideration regulations affecting emissions from these source categories. For 

the four largest airports in North Carolina, the Federal Aviation Adminstration’s Terminal Area 

Forecast was used to project growth in aircraft emissions. For the commercial marine, railroad 

locomotives and the remaining airport emissions, the VISTAS contractor calculated the future 

growth in emissions using detailed inventory data (both before and after controls) for 1996 and 

2010, obtained from the CAIR Technical Support Document. When available, state-specific 

growth factors were used. 

4.1.4 Highway Mobile Sources

For onroad vehicles, the newest version of the MOBILE model, MOBILE6.2, was used. Key 

inputs for MOBILE include information on the age of vehicles on the roads, the average speeds 

on the roads, the mix of vehicles on the roads, any programs in place in an area to reduce 

emissions for motor vehicles (e.g., emissions inspection programs), and temperature.

The MOBILE model takes into consideration regulations that affect emissions from this source 

sector. The same MOBILE run is used to represent the actual and typical year emissions for 

onroad vehicles using input data reflective of 2002. The MOBILE model then is run for 2018 

inventory using input data reflective of that year. The 2002 vehicle miles traveled (VMT), 

speeds, vehicle age and vehicle mix data were obtained from the Florida Department of 

Transportation (FLDOT). For urban areas in Florida that run travel demand models (TDMs), 

VMT and speed data from TDMs were used.

4.1.5 Biogenic Emission Sources

Biogenic emissions were prepared with the SMOKE-BEIS3 (Biogenic Emission Inventory 

System 3 version 0.9) preprocessor. SMOKE-BEIS3 is a modified version of the Urban Airshed 

Model (UAM)-BEIS3 model. Modifications include use of MM5 data, gridded land use data, 

and improved emissions characterization. The emission factors that are used in SMOKE-BEIS3 

are the same as the emission factors as in UAM-BEIS3. The basis for the gridded land use data 

used by BEIS3 is the county land use data in the Biogenic Emissions Landcover Database 

version 3 (BELD3) provided by the EPA. A separate land classification scheme, based upon 

satellite (AVHRR, 1 km spatial resolution) and census information, aided in defining the forest, 

agriculture and urban portions of each county. 

4.1.6 Summary 2002 Base G2 (February 2007 version) Baseline Emissions Inventory for FL

Table 4.1 is a summary of the 2002 baseline emission inventory for Florida. The complete 

inventory and discussion of the methodology is contained in Appendix D. The emissions 

summaries for other VISTAS states can also be found in Appendix D.

27
Table 4.1. 2002 Emissions Inventory Summary for FL in tons per year.

CO NH3 NOx PM10 PM2.5 SO2 VOC

EGU 57,113 234 257,677 21,387 15,643 453,631 2,524

NON-EGU 81,933 1,423 45,156 35,857 30,504 65,090 38,471

ONROAD 4,493,820 17,922 460,503 11,148 7,779 20,687 520,757

NON-ROAD 1,920,729 134 180,627 18,281 17,415 20,614 272,072

AREA 71,079 37,446 28,872 443,346 58,878 40,491 404,302

FIRES 790,620 3,102 15,942 85,263 75,717 4,057 42,724

BIOGENICS 0 0 36,320 0 0 0 1,522,031

TOTAL 7,415,293 60,261 1,025,098 615,281 205,936 604,570 2,802,880

4.1.7 Model Performance Improvements through Emissions Inventory Improvements 

Since the initial model performance evaluation, VISTAS has made several improvements to the 

emissions inventory, which in turn improve model performance. These inventory improvements 

are detailed in the VISTAS emissions inventory report and Appendix D, and are summarized 

here: 

• For electric generating utilities, the Integrated Planning Model (IPM) was used to provide 

estimates of future year utility production and emissions. Continuous Emissions 

Monitoring data was used to define seasonal variability in production and emissions. For 

Base G2 emissions, states updated IPM model projections from 2005 with control data 

provided by utility companies in 2006 through winter 2007. 

• For on-road vehicle emissions, states and local agencies provided updated MOBILE 

model input and vehicle-miles-traveled data.

• For ammonia emissions from agricultural sources, the Carnegie Mellon University 

ammonia model was used to improve annual and monthly estimates.

• For fires, the VISTAS states provided fire activity data for 2002 for wildfires, prescribed 

fire, land clearing and agricultural burning and MACTEC developed a 2002 fire 

inventory. Where data allowed, Alpine Geophysics modeled fire events as point sources. 

In 2006, United States Forest Service and Fish and Wildlife Service provided projections 

of increased prescribed burning in 2009 and 2018; these data were incorporated in the 

Base G inventory for all states except Florida.

• For non-road engines, the updated EPA NONROAD2005 emissions model was used in 

Base G.

• For commercial marine emissions in shipping lanes in the Gulf of Mexico and Atlantic 

Oceans, ENVIRON created gridded emissions for the VISTAS modeling domain using 

inventory data newly developed for EPA by Corbett at University of Delaware. These 

emissions were incorporated in the Base G modeling. 

• Updated inventories from the neighboring RPOs, Mexico, and Canada were incorporated 

as available.

28
4.2 Assessment of Relative Contributions from Specific Pollutants and Sources Categories 

Ammonium sulfate is the largest contributor to visibility impairment at Florida Class I areas, and 

reduction of SO2 emissions would be the most effective means of reducing ammonium sulfate. 

With the lower SO2 emissions in South Florida, and its greater distance from the large 

continental emissions of SO2, the Everglades National Park is occasionally dominated by carbon. 

As illustrated in Figure 4.2-1, 96 percent of SO2 emissions in the VISTAS states are attributable 

to electric generating facilities and industrial point sources. As shown in Table 4.1, 92 percent of 

SO2 emissions in Florida are attributable to electric generating facilities and industrial point 

sources (electric generating facilities, non-electric generating facilities, and area sources).

Figure 4.2-1. SO2 emissions in 2002 in the VISTAS States.

VISTAS States SO2 Emissions - 2002 

Utilities

Industrial

On road

Non road

Other

Industrial: 20% Utilities: 76%

4.8 Million tons

VISTAS States SO2 Emissions - 2002 

Utilities

Industrial

On road

Non road

Other

Industrial: 20% Utilities: 76%

4.8 Million tons

29
5.0 REGIONAL HAZE MODELING METHODS AND INPUTS

Modeling for regional haze was performed by VISTAS for the ten southeastern states, including 

Florida. The sections below outline the methods and inputs used by VISTAS for the regional 

modeling. Additional details are provided in Appendices C.

5.1 Analysis Method

The modeling analysis is a complex technical evaluation that begins by selection of the modeling 

system. VISTAS decided to use the following modeling system:

• Meteorological Model: The Pennsylvania State University/National Center for 

Atmospheric Research (PSU/NCAR) Mesoscale Meteorological Model (MM5) is a 

nonhydrostatic, prognostic meteorological model routinely used for urban- and regionalscale photochemical, fine particulate matter, and regional haze regulatory modeling 

studies.

• Emissions Model: The Sparse Matrix Operator Kernel Emissions (SMOKE) modeling 

system is an emissions modeling system that generates hourly gridded speciated emission 

inputs of mobile, nonroad mobile, area, point, fire and biogenic emission sources for 

photochemical grid models.

• Air Quality Model: EPA’s Models-3/ Community Multiscale Air Quality (CMAQ) 

modeling system is an ‘One-Atmosphere’ photochemical grid model capable of

addressing ozone, particulate matter (PM), visibility and acid deposition at regional scale 

for periods up to one year.

The EPA Modeling Guidance recommends modeling an entire year or at a minimum several 

days in each quarter of a year to adequately represent the range of meteorological conditions that 

contribute to elevated levels of fine particulate matter. The year 2002 was selected by VISTAS 

as the modeling year for this demonstration. Meteorological inputs were developed for 2002 

using the meteorological model. Emission inventories were also developed for 2002 and 

processed through the emissions model. These inputs were used in the air quality model to 

predict fine particle mass and visibility. The model results for 2002 were compared with 

observed meteorological and air quality data to evaluate model performance. Several 

configurations of the meteorological and air quality model were evaluated to select a 

configuration that gave the best overall performance for the VISTAS region. 

Once model performance was deemed adequate, the current and future year emissions were 

processed through the emissions model. The air quality modeling results are used to determine a 

relative reduction in future visibility impairment, which is used to determine reasonable progress.

The complete modeling protocol used for this analysis can be found in Appendix C.

30
5.2 Model Selection

To ensure that a modeling study is defensible, care must be taken in the selection of the models 

to be used. The models selected must be scientifically appropriate for the intended application 

and be freely accessible to all stakeholders. “Scientifically appropriate” means that the models 

address important physical and chemical phenomena in sufficient detail, using peer-reviewed 

methods. “Freely accessible” means that model formulations and coding are freely available for 

review and that the models are available to stakeholders, and their consultants, for execution and 

verification at no or low cost.

The following sections outline the criteria for selecting a modeling system that is both defensible 

and capable of meeting the study's goals. These criteria were used in selecting the modeling 

system used for this modeling demonstration.

5.2.1 Selection of Photochemical Grid Model

Criteria

For a photochemical grid model to qualify as a candidate for use in a regional haze SIP, a state 

needs to show that it meets the same several general criteria as a model for an attainment 

demonstration for a national ambient air quality standard (NAAQS): 

The model has received a scientific peer review

The model can be demonstrated applicable to the problem on a theoretical basis

Data bases needed to perform the analysis are available and adequate

Available past appropriate performance evaluations have shown the model is not biased 

toward underestimates or overestimates

A protocol on methods and procedures to be followed has been established

The developer of the model must be willing to make the source code available to users for 

free or for a reasonable cost, and the model cannot otherwise be proprietary.

Overview of CMAQ

The photochemical model selected for this study was CMAQ version 4.5. For more than a 

decade, the EPA has been developing the Models-3 CMAQ modeling system with the 

overarching aim of producing a ‘One-Atmosphere’ air quality modeling system capable of 

addressing ozone, fine particulate matter, visibility and acid deposition within a common 

platform. The original justification for the Models-3 development emerged from the challenges 

posed by the 1990 CAAA and the EPA’s desire to develop an advanced modeling framework for 

‘holistic’ environmental modeling utilizing state-of-science representations of atmospheric 

processes in a high performance computing environment. The EPA completed the initial stage 

of development with Models-3 and released the CMAQ model in mid-1999 as the initial 

operating science model under the Models-3 framework. The most recent rendition is CMAQ 

version 4.5, which was released in September 2005. 

31
An advantage of choosing CMAQ as the atmospheric model is the ability to do one-atmospheric 

modeling. The same model configuration is being applied for the ozone and PM2.5 attainment 

demonstrations SIPs, as well as the regional haze SIP. A number of features in CMAQ’s 

theoretical formulation and technical implementation make the model well suited for annual PM 

modeling.

The configuration used for this modeling demonstration, as well as a more detailed description of 

the CMAQ model, can be found in the Modeling Protocol (Appendix C). 

5.2.2 Selection of Meteorological Model 

Criteria

Meteorological models, either through objective, diagnostic, or prognostic analysis, extend 

available information about the state of the atmosphere to the grid upon which photochemical 

grid modeling is to be carried out. The criteria for selecting a meteorological model are based on 

both the models ability to accurately replicate important meteorological phenomena in the region 

of study, and the model's ability to interface with the rest of the modeling systems -- particularly 

the photochemical grid model. With these issues in mind, the following criteria were established 

for the meteorological model to be used in this study:

Non-Hydrostatic Formulation

Reasonably current, peer reviewed formulation

Simulates Cloud Physics

Publicly available on no or low cost

Output available in I/O API format 

Supports Four Dimensional Data Assimilation (FDDA)

Enhanced treatment of Planetary Boundary Layer heights for AQ modeling

Overview of MM5

The non-hydrostatic MM5 model is a three-dimensional, limited-area, primitive equation, 

prognostic model that has been used widely in regional air quality model applications. The basic 

model has been under continuous development, improvement, testing and open peer-review for 

more than 20 years and has been used worldwide by hundreds of scientists for a variety of 

mesoscale studies. 

MM5 uses a terrain-following non-dimensionalized pressure, or "sigma", vertical coordinate 

similar to that used in many operational and research models. In the non-hydrostatic MM5, the 

sigma levels are defined according to the initial hydrostatically-balanced reference state so that 

the sigma levels are also time-invariant. The gridded meteorological fields produced by MM5 

are directly compatible with the input requirements of ‘one atmosphere’ air-quality models using 

32
this coordinate. MM5 fields can be easily used in other regional air quality models with different 

coordinate systems by performing a vertical interpolation, followed by a mass-conservation readjustment. 

Distinct planetary boundary layer (PBL) parameterizations are available for air-quality 

applications, both of which represent sub-grid-scale turbulent fluxes of heat, moisture and 

momentum. One scheme uses a first-order eddy diffusivity formulation for stable and neutral 

environments and a modified first-order scheme for unstable regimes. The other scheme uses a 

prognostic equation for the second-order turbulent kinetic energy, while diagnosing the other key 

boundary layer terms. 

Initial and lateral boundary conditions are specified for real-data cases from mesoscale threedimensional analyses performed at 12-hour intervals on the outermost grid mesh selected by the 

user. Surface fields are analyzed at three-hour intervals. A Cressman-based technique is used to 

analyze standard surface and radiosonde observations, using the National Meteorological 

Center's spectral analysis, as a first guess. The lateral boundary data are introduced using a 

relaxation technique applied in the outermost five rows and columns of the coarsest grid domain.

MM5 modeling system in regulatory air quality application studies have been widely reported in 

the literature (e.g., Emery et al., 1999; Tesche et al., 2000, 2003) and many have involved 

comparisons with other prognostic models such as the Regional Atmospheric Modeling System 

(RAMS) and the Systems Application International Mesoscale Model. The MM5 enjoys a far 

richer application history in regulatory modeling studies compared with RAMS or other models. 

Furthermore, in evaluations of these models in over 60 recent regional scale air quality 

application studies since 1995, it has generally been found that the MM5 model tends to produce 

somewhat better photochemical model inputs than alternative models. 

The configuration used for this modeling demonstration, as well as a more detailed description of 

the MM5 model, can be found in the meteorological modeling protocol (Appendicies E and F2).

5.2.3 Selection of Emissions Processing System 

Criteria

The principal criterion for an emissions processing system is that it accurately prepares 

emissions files in a format suitable for the photochemical grid model being used. The following 

list includes clarification of this criterion and additional desirable criteria for effective use of the 

system.

File System Compatibility with the I/O API

File Portability

Ability to grid emissions on a Lambert Conformal projection

Report Capability

Graphical Analysis Capability

33
MOBILE6 Mobile Source Emissions

Biogenic Emissions Inventory System version 3 (BEIS-3)

Ability to process emissions for the proposed domain in a reasonable amount of time.

Ability to process control strategies

No or low cost for acquisition and maintenance

Expandable to support other species and mechanisms

Overview of SMOKE

The SMOKE Emissions Processing System Prototype was originally developed at the Microcomputing Center of North Carolina. As with most ‘emissions models’, SMOKE is principally 

an emission processing system and not a true emissions modeling system in which emissions 

estimates are simulated from ‘first principles’. This means that, with the exception of mobile 

and biogenic sources, its purpose is to provide an efficient, modern tool for converting emissions 

inventory data into the formatted emission files required by an air quality simulation model. For 

mobile sources, SMOKE actually simulates emissions rates based on input mobile-source 

activity data, emission factors and outputs from transportation travel-demand models. 

SMOKE was originally designed to allow emissions data processing methods to utilize emergent 

high-performance-computing as applied to sparse-matrix algorithms. Indeed, SMOKE is the 

fastest emissions processing tool currently available to the air quality modeling community. The 

sparse matrix approach utilized throughout SMOKE permits both rapid and flexible processing 

of emissions data. The processing is rapid because SMOKE utilizes a series of matrix 

calculations instead of less efficient algorithms used in previous systems. The processing is 

flexible because the processing steps of temporal projection, controls, chemical speciation, 

temporal allocation, and spatial allocation have been separated into independent operations 

wherever possible. The results from these steps are merged together at a final stage of 

processing.

SMOKE contains a number of major features that make it an attractive component of the 

modeling system. The model supports a variety of input formats from other emissions 

processing systems and models. It supports both gridded and county total land use scheme for 

biogenic emissions modeling. SMOKE can accommodate emissions files from up to 10 

countries and any pollutant can be processed by the system.

For additional information about the SMOKE model please refer to Modeling Protocol 

(Appendix C).

5.3 Selection of the Modeling Year

A crucial step to SIP modeling is the selection of the period of time to model to represent current 

air quality conditions and to project changes in air quality in response to changes in emissions. 

The year 2002 was selected as the base year for several reasons. 

34
The EPA’s April 2007 Guidance on the use of Models and Other Analyses for Demonstrating 

Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze identifies specific goals 

to consider when selecting one or more episodes for use in demonstrating reasonable progress in 

attaining the regional haze air quality goals. The EPA recommends that episode selection derive 

from three principal criteria:

• Simulate a variety of meteorological conditions;

• Model time periods in which observed concentrations are close to the appropriate baseline 

design value or visibility impairment; 

• Model periods for which extensive air quality/meteorological data bases exist; and

• Model a sufficient number of days so that the modeled attainment test applied at each 

monitor violating the NAAQS is based on multiple days.

For regional haze modeling, the guidance goes further by suggesting that the preferred approach 

is to model a full, representative year. Moreover, the required RRF values should be based on 

model results averaged over the 20% worst and 20% best visibility days determined for each 

Class I are based on monitoring data from the 2000 – 2004 baseline period. 

The EPA also lists several other considerations to bear in mind when choosing potential regional 

haze episodes including: (a) choose periods which have already been modeled, (b) choose 

periods which are drawn from the years upon which the current design values are based, (c) 

include weekend days among those chosen, and (d) choose modeling periods that meet as many 

episode selection criteria as possible in the maximum number of nonattainment or Class I areas 

as possible. Finally, the EPA explicitly recommended in its 2007 guidance to use 2002 as the 

baseline inventory year.

VISTAS adopted a logical, stepwise approach in implementing the EPA guidance in order to 

identify the most preferable, representative year for regional haze modeling. 

These steps include the following:

Representativeness of Meteorological Conditions: The VISTAS meteorological 

contractor (BAMS) identified important meteorological characteristics and data sets in 

the VISTAS region directly relevant to the evaluation of candidate annual modeling 

episodes.

Initial Episode Typing: At the time of selection in 2003, meteorological and air quality 

data were available for 2002 for model inputs and model performance evaluation. 

VISTAS used Classification and Regression Tree Analyses to evaluate visibility 

conditions for 2000, 2001, and 2002, the candidate modeling years. The year 2002 was 

found to be representative of conditions in the other two years. Subsequently, these 

analyses were repeated with the meteorological and air quality monitoring data for 2000 

to 2004 to evaluate how well the 2002 modeling year represented the full 2000-2004 

baseline period. This analysis confirmed that visbility and PM2.5 mass in 2002 were 

representative of the five-year baseline period for the VISTAS Class I areas. This 

analysis is discussed in more detail in the project report in Appendix B.

35
Data Availability: In parallel with the CART analysis, episode characterization analyses, 

collaborative investigations by VISTAS states (e.g., NCDAQ, Georgia DNR, FL DEP) 

intensively studied the availability of PM2.5, meteorological, and emissions data and 

representativeness of alternative Baseline modeling periods from a regulatory standpoint. 

Additionally, 2002 was the year that EPA was requiring states to provide emissions 

inventory data for the Comprehensive Emissions Reporting Rule, it made sense to use 

2002 as the modeling year to take advantage of the 2002 inventory.

Years to be used by other RPOs: VISTAS also considered what years other RPO would 

be modeling, and several had already chosen calendar year 2002 as the modeling year.

After a lengthy process of integrated studies, the episode selection process culminated in the 

selection of calendar year 2002 (1 January through 31 December) as the most current, 

representative, and pragmatic choice for VISTAS regional haze modeling. All of the EPA

criteria for regional haze episode selection were directly considered in this process together with 

many other considerations (e.g., timing of new emissions or aerometric data deliveries by the 

EPA or the states to the modeling teams).

5.4 Modeling Domains

5.4.1 Horizontal Modeling Domain 

The EPA’s modeling guidance recommends a 12-km modeling grid resolution for PM2.5 

modeling while a 36-km grid is considered acceptable for regional haze. For the VISTAS 

modeling, a coarse 36-km grid resolution was used for modeling the entire United States and a 

finer 12-km grid was used to model the eastern United States. 

The CMAQ model was run in one-way nested grid mode. This allowed the larger outer domains 

to feed concentration data to the inner nested domain. One-way nesting is believed to be 

appropriate for the generally stagnant conditions experienced during North Carolina ozone 

episodes. Two-way nesting was not considered due to numerical and computational uncertainty 

associated with the technique.

The horizontal coarse grid modeling domain boundaries were determined through a national 

effort to develop a common grid projection and boundary. A smaller 12-km grid, modeling 

domain was selected in an attempt to balance location of areas of interest, such as ozone and fine 

particulate matter nonattainment areas, as well as Class 1 and wilderness areas for regional haze. 

Processing time was also a factor in choosing a smaller 12-km grid, modeling domain.

The coarse 36-km horizontal grid domain covers the continental United States. This domain was 

used as the outer grid domain for MM5 modeling with the CMAQ domain nested within the 

MM5 domain. Figure 5.4.1-1 shows the MM5 horizontal domain as the outer most, blue grid 

with the CMAQ 36-km domain nested in the MM5 domain. 

36
Figure 5.4.1-1. The MM5 horizontal domain is the outer most, blue grid, with the CMAQ 

36-km domain nested in the MM5 domain. 

To achieve finer spatial resolution in the VISTAS states, a one-way nested high resolution 

(12-km grid resolution) was used. Figure 5.4.1-2 shows the 12-km grid, modeling domain for 

the VISTAS region. This is the modeling domain for which the reasonable progress goals will 

be assessed.

Figure 5.4.1-2. A more detailed view of the 12-km grid over the VISTAS region.

37
5.4.2 Vertical Modeling Domain

The CMAQ vertical structure is primarily defined by the vertical grid used in the MM5 

modeling. The MM5 model employed a terrain following coordinate system defined by 

pressure, using 34 layers that extend from the surface to the 100 mb. A layer-averaging scheme 

was used to generate 19 vertical layers for CMAQ to reduce the computational cost of the 

CMAQ simulations. The effects of layer averaging were evaluated in conjunction with the 

VISTAS modeling effort and was found to have a relatively minor effect on the model 

performance metrics when both the 34 layer and a 19 layer CMAQ models were compared to 

ambient monitoring data.

38
6.0 MODEL PERFORMANCE EVALUATION

The initial modeling effort focused on evaluating previous regional air quality modeling 

applications and testing candidate model configurations for the SMOKE emissions and CMAQ 

model for the VISTAS 36-km and 12-km modeling domains. This effort resulted in a report 

recommending the model configuration for the annual emissions and air quality modeling, which 

is included as part of the VISTAS Emissions and Air Quality Modeling Protocol. The evaluation 

of the meteorological modeling configuration can be found in Appendix F.1, with a summary of 

the final meteorological and air quality modeling configuration in the modeling protocol 

contained in Appendix E and Appendix C, respectively.

Air quality model performance for the 2002 modeling year was initially tested in 2004 using an 

early version of the VISTAS emissions inventory. In keeping with the one-atmosphere objective 

of the CMAQ modeling platform, model performance was evaluated based on measured ozone, 

fine particles, and acid deposition in the Air Quality System (AQS), IMPROVE, Speciated 

Trends Network (STN), Southeastern Aerosol Research and Characterization (SEARCH), 

National Acid Deposition Program (NADP) and Clean Air Status and Trends Network 

(CASTNet) monitoring networks (Figure 6.0-1). 

Figure 6.0-1: Monitoring Networks used for VISTAS 2002 model performance evaluation 

and their location within the VISTAS 12km domain. 

39
6.1 Modeling Performance Goals, and Criteria

In 2004, VISTAS established model performance goals and criteria for components of fine 

particle mass (Table 6.1-1) based on previous model performance for ozone and fine particles. 

The EPA modeling guidance for fine particulate matter at the time noted that PM models might 

not be able to achieve the same level of performance as ozone models. VISTAS’ evaluation 

considered several statistical performance measures and displays. Fractional bias and mean 

fractional error were selected as the most appropriate metrics to summarize model performance; 

other metrics were also calculated and are included for IMPROVE monitors in the full model 

performance evaluation (Appendix F.2). 

Table 6.1-1: Established model performance goals and criteria for the component species of 

fine particle mass.

Fractional Bias Mean Fractional 

Error

Comment

<15 percent <35 percent Goal for PM model performance based on ozone 

model performance, considered excellent performance 

<30 percent <50 percent Goal for PM model performance, considered good 

performance 

<60 percent <75 percent Criteria for PM model performance, considered 

average performance. Exceeding this level of 

performance indicates fundamental concerns with the 

modeling system and triggers diagnostic evaluation.

Several graphic displays of model performance were prepared including: 

1. Scatter plots of predicted and observed concentrations and deposition by species, 

monitoring network, and month

2. Time series plots of predicted and observed concentrations and deposition by species, 

monitoring site, and month

3. Spatially average time series plots

4. Time series plots of monthly fractional bias and error for a species, region, and network 

5. Performance goal plots (“soccer plots”) that summarize model performance by species, 

region, season

6. Concentration performance plots (“bugle plots”) that display fractional bias or error as a 

function of concentration by species, region, monitoring network, and month

The “soccer plots” and “bugle plots” are relatively new tools in model performance evaluations, 

and have recently been included as model performance evaluation displays in the EPA’s 

modeling guidance for Ozone, PM2.5, and Regional Haze (2007). Both “soccer plots” and 

“bugle plots” allow for convenient way to examine model performance with respect to set goals 

and criteria. The bugle plots have the added benefit of adjusting the goals and criteria to 

consider the concentration of the species. Analysis of “bugle plots” generally suggests that 

greater emphasis should be placed on performance of those components with the greatest 

contribution to PM mass and visibility impairment (e.g. sulfate and organic carbon) and that 

greater bias and error could be accepted for components with smaller contributions to total PM 

mass (e.g. elemental carbon, nitrate, and soil). 

40
6.2 VISTAS Domain-Wide Performance

Further discussion of model performance in this document will focus on the comparison of 

observational data from the IMPROVE monitors and model output data from the 2002 VISTAS 

BaseG2-Actual annual air quality modeling. Focus is limited to the IMPROVE monitoring 

network as these sites are the locations used in projecting attainment visibility improvement 

goals in the Class I areas. 

The evaluation will primarily focus on the air quality model’s performance with respect to 

individual components of fine particulate matter (PM2.5), as good model performance of the 

component species will dictate good model performance of total or reconstituted fine particulate

matter. Model performance of the total fine particulate matter and the resulting total light 

extinction will also be provided as a means to discuss the overall model performance for this 

Implementation Plan. 

In our analyses, mean fractional bias (error) is used in lieu of mean bias (error), to prevent low 

observations and model predictions from skewing the metrics. A full list of model performance 

statistics is found in Appendix F.2. The soccer and bugle plots for the all of the VISTAS 

IMPROVE monitors are included here for summary purposes. Plots have been developed for the 

average monthly concentrations and the performance statistics for all of the most significant light 

scattering component species (Sulfate, Nitrate, and Organic Carbon) for the 20% best days and 

20% worst days. Plots for individual IMPROVE monitors associated with Florida Class I areas 

are included in Appendix F.2.

The soccer plots of monthly concentrations (Figures. 6.2-1 and 6.2-2) show that values for nitrate 

generally fall outside of criteria performance thresholds. Sulfates and organic carbon generally 

fall within goal thresholds, with a couple of months falling just outside the goal thresholds but 

well within the criteria thresholds. Figure 6.2-3 contains separate soccer plots for each season. 

The seasonal plots emphasize poorer nitrate performance in the summer (does not even appear 

on the plots provided because performance is off scale with other constituents), when observed 

nitrate is quite low and predicted nitrate is even lower. When concentration is factored into 

performance criteria, nitrate performance improves with respect to MFB and MFE (Figures 6.2-4 

and 6.2-5) 

Additionally, performance assed at the “one atmosphere” level was also deemed acceptable for 

ozone and particulate matter at various monitoring sites (STN, FRM, CASTNet, etc.). Overall, 

VISTAS found the Base G2 modeling results to be representative and acceptable for use in 

modeling projection for ozone, particulate matter, and regional haze. 

41
Figure 6.2-1: Soccer plot depicting both the mean fractional error and fractional bias for 

component concentration for all VISTAS sites based on Base G2 results. Each point 

represents a monthly value as compared to the model performance criteria (red box) and 

modeling performance goals (green box).

Figure 6.2-2: A zoomed view of the soccer plot depicting both the mean fractional error 

and fractional bias for component concentration for all VISTAS sites based on Base G2 

results. Each point represents a monthly value as compared to the model performance 

criteria (red box) and modeling performance goals (green box).

All Sites CMAQ 12km - 2002 Monthly

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0

Fractional Bias

Mean Fractional Error 

Sulfate

Nitrate

Organics

Criteria

Goal

All Sites CMAQ 12km - 2002 Monthly

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

-75.0 -25.0 25.0 75.0

Fractional Bias

Mean Fractional Error 

Sulfate

Nitrate

Organics

Criteria

Goal

42
Figure 6.2-3: Seasonal soccer plots based on Base G1 results for all VISTAS IMPROVE 

monitors. 

Figure 6.2-4: Bugle plot of the mean fraction bias for particulate matter and its component 

concentrations for all VISTAS sites based on Base G2 results. Each point represents a 

monthly mean fraction bias value as compared to the model performance criteria (red 

lines) and modeling performance goals (green lines). 

All Sites CMAQ 12km - 2002 Monthly

0.0

50.0

100.0

150.0

200.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0

Average Concentration (μg/m3)

Mean Fractional Error 

Sulfate

Nitrate

Organics

Criteria

Goal

43
Figure 6.2-5: Bugle plot of mean fraction error for particulate matter and its component 

species for all VISTAS sites based on Base G2 results. Each point represents a monthly 

mean fraction bias value as compared to the model performance criteria (red lines) and 

modeling performance goals (green lines). 

6.3 Florida Class 1 Areas Performance

The following section provides stack bar charts comparing observed fine particulate matter 

composition and modeled fine particulate matter composition. The charts have been split into 

two charts, with the first displaying the 20% best days followed by the chart for the 20% worst 

days. Stacked bar charts have been developed for each of the four IMPROVE monitoring sites 

located in Florida: Chassahowitzka Wilderness (CHAS), Everglades National Park (EVER), and 

St. Marks Wilderness (SAMA), as well as the adjacent Class I area in Georgia: Okefenokee 

(OKEF) (See Figure 6.3.1-6.3.4). 

The stacked bar chart allows a side by side comparison of each days observed and modeled 

compositional and total light extinction. Within each bar the color codes are:

• Yellow = light extinction due to sulfates (bextSO4)

• Red = light extinction due to nitrates (bextNO3)

• Green = light extinction due to organic carbon (bextOC)

• Black = light extinction due to elemental (bextEC)

• Brown = light extinction due to soil (bextSoil)

• Grey = light extinction due to coarse mass (bextCM)

The components are presented in the same order for both the observed (left hand bar) and 

modeled bar (right hand bar), so it easy to identify days when the prediction light extinction for 

the component differs from the observed. The total height of the bar provides the total 

reconstructed particulate matter light extinction value. 

All Sites CMAQ 12km - 2002 Monthly

-200.0

-150.0

-100.0

-50.0

0.0

50.0

100.0

150.0

200.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0

Average Concentration (μg/m3

)

Mean Fractional Bias 

Sulfate

Nitrate

Organics

(+) Criteria

(+) Goal

(-) Goal

(-) Criteria

44
A cursory view of the stacked bars charts reiterates that sulfates are a large contributor to light 

extinction in many of the Florida Class I areas and Okefenokee during most of the 20% best and 

20% worst days. The bar charts also suggest organic carbon and nitrates are other significant 

components in light extinction on the 20% best days. Concerning the 20% worst days, nitrates 

are not as significant and sulfates and organic carbon dominate the light extinction in both 

modeling and observations. Overall, modeling performance tends to under predict most species 

of PM on average at all four sites. Model performance is better during the 20% best days, where 

under prediction primarily takes place in the nitrates. During the 20% worst days, sulfates are a 

large source of the light extinction under prediction. Modeling performance is best at St. Marks 

and Chassahowitzka, with performance in the Everglades proportionally worse for the 20% best 

days. Okefenokee has a large amount of under prediction, primarily concerning sulfates, during 

the 20% worst days. There are several days at each Florida Class I area where a large over or 

under prediction occurs, particularly concerning sulfates (20% best days) and organic carbon 

(20% worst days). 

Nitrates tend to be under predicted at all sites during the 20% best and worst days, especially 

during the summer. The model performance evaluation prepared by Environ recognizes the 

consistent issues with nitrate under prediction and attribute it to several causes, including errors 

with convective rainfall in the meteorological model and uncertainty in sea salt and ammonia 

concentrations. The nitrate under prediction is exaggerated during extremely low levels of 

nitrates (< 1.0 μg/m3

) and at coastal sites, such as the Everglades National Park. In the stacked 

bar charts for the Everglades, nitrates are completely missing in the modeled contributions in 

both the 20% best and 20% worst days. 

Overall, DEP found model performance to fall within acceptable limits for model performance, 

although the performance for the Everglades falls within the lower levels of acceptability. Due 

to the poor modeling of nitrates in the Everglades, modifications to the relative reduction factor 

calculation were applied to correct the performance issues. This is discussed further in section 

7.2.4. DEP further asserts the one atmosphere modeling performed by the VISTAS contractors 

is representative of conditions in the southeastern states and is applicable for use in attainment 

demonstrations. 

45
6.3.1 Chassahowitzka, FL 

Figure 6.3-1: Stacked bar chart for CHAS1 on the 20% best days (top) and 20% worst 

days (bottom). Observed composition is presented in the left hand bar, with modeled 

composition from the 12km CMAQ represented by the right hand bar.

Best 20% Obs (left) vs 2002gt2a (right) at CHAS1

0

10

20

30

40

50

60

70

80

90

38 68 71 104 146 161 164 170 173 176 182 191 203 224 227 239 242 248 266 320 344 347 _ _ _ Avg

Julian Day in Best 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

Worst 20% Obs (left) vs 2002gt2a (right) at CHAS1

0

20

40

60

80

100

120

140

160

180

200

5 17 26 41 44 47 56 89 116 128 155 200 206 236 260 278 281 290 296 329 332 341 350 _ _ Avg

Julian Day in Worst 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

46
6.3.2 Everglades, FL

Figure 6.3.2: Stacked bar chart for EVER1 on the 20% best days (top) and 20% worst days 

(bottom). Observed composition is presented in the left hand bar, with modeled 

composition from the 12km CMAQ represented by the right hand bar.

Best 20% Obs (left) vs 2002gt2a (right) at EVER1

0

5

10

15

20

25

30

23 29 32 71 80 104 134 137 140 164 176 191 206 212 242 245 248 251 254 284 287 296 299 302 _ Avg

Julian Day in Best 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

Worst 20% Obs (left) vs 2002gt2a (right) at EVER1

0

20

40

60

80

100

120

140

160

180

200

5 35 44 56 62 74 95 98 113 125 128 152 158 218 236 257 281 290 305 311 332 341 350 362 _ Avg

Julian Day in Worst 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

47
6.3.3 Okefenokee, GA

Figure 6.3.3: Stacked bar chart for OKEF1 on the 20% best days (top) and 20% worst days 

(bottom). Observed composition is presented in the left hand bar, with modeled 

composition from the 12km CMAQ represented by the right hand bar.

Best 20% Obs (left) vs 2002gt2a (right) at OKEF1

0

10

20

30

40

50

60

11 20 38 59 62 104 170 173 176 179 191 239 242 257 266 275 284 335 344 347 356 359 _ _ _ Avg

Julian Day in Best 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

Worst 20% Obs (left) vs 2002gt2a (right) at OKEF1

0

50

100

150

200

250

300

350

17 23 44 56 89 95 122 128 155 188 197 200 218 236 254 260 263 281 296 308 338 341 350 _ _ Avg

Julian Day in Worst 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

48
6.3.4 Saint Marks, FL

Figure 6.3.4: Stacked bar chart for SAMA on the 20% best days (top) and 20% worst days 

(bottom). Observed composition is presented in the left hand bar, with modeled 

composition represented by the right hand bar.

Best 20% Obs (left) vs 2002gt2a (right) at SAMA1

0

10

20

30

40

50

60

70

80

90

100

11 14 20 32 38 68 80 158 161 173 176 179 194 206 209 218 224 239 266 302 344 356 _ _ _ Avg

Julian Day in Best 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

Worst 20% Obs (left) vs 2002gt2a (right) at SAMA1

0

50

100

150

200

250

300

35 44 47 56 89 95 98 107 116 122 125 128 131 155 185 188 197 200 260 290 293 296 341 _ _ Avg

Julian Day in Worst 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

49
7.0 LONG-TERM STRATEGY FOR FLORIDA CLASS I AREAS 

As stated in section 1.3 above, the regional haze rule requires states to establish reasonable 

progress goals, expressed in deciviews, for visibility improvement at each affected Class I area 

covering each (approximately) 10-year period until 2064. This first set of reasonable progress 

goals must be met through measures contained in the state’s long-term strategy covering the 

period from the baseline until 2018. This section discusses development of Florida’s long-term 

strategy. 

7.1 Overview of the Long-Term Strategy Development Process

The monitored data and modeling analyses cited in sections 2 and 5 above establish that for the 

VISTAS region, the key contributors to regional haze in the 2000-2004 baseline timeframe were 

large stationary sources of sulfur dioxide emissions. Keeping that key conclusion in mind, this 

section addresses the following questions: 

a. Assuming implementation of existing federal and state air regulatory requirements in 

Florida and the VISTAS region, how much visibility improvement, compared to the 

glidepath, would we expect to see at Class I areas in or near Florida between now and 

2018?

b. If additional emission reductions were needed, from what pollutants and source 

categories would the greatest visibility benefits be realized between the baseline and 

2018?

c. How do we select any additional sources that would provide potentially significant 

visibility benefits in making reasonable progress?

d. What is the process for identifying additional emission controls or reductions that

represent reasonable progress for those specific sources?

e. What additional emission controls represent BART in Florida?

f. Given the additional emission reductions expected from BART and reasonable 

progress improvements, how much additional visibility improvement, compared to 

the glidepath, will we expect to see at Class I areas in Florida between the baseline 

and 2018?

50
7.2 Expected Visibility Results in 2018 for Florida Class I Areas under existing and 

planned emissions controls (G2 and, Best and Final Inventory (G4)) 

There are significant control programs being implemented between the baseline period and 2018. 

These programs are described in more detail below.

7.2.1 Federal and State Control Requirements

Clean Air Interstate Rule (CAIR). Although there is uncertainty over CAIR’s eventual 

replacement as a result of the vacatur of CAIR’s intended successor, the Cross State Air 

Pollution Rule (CSAPR), significant emission reductions forced by CAIR have occurred as of 

2010 and are integral to Florida’s long-term strategy. Moreover, CAIR remains in effect as of 

September 2012 and its associated emission reductions continue to occur. 

NOx SIP Call. Phase I of the NOx SIP Call applies to certain EGUs and large non-EGUs, 

including large industrial boilers and turbines, and cement kilns. Those states affected by the 

NOx SIP call in the VISTAS region have developed rules for the control of NOx emissions that 

have been approved by the EPA. The NOx SIP Call has resulted in a 68 percent reduction in 

NOx emissions from large stationary combustion sources. For this analysis, we capped the 

emissions for NOx SIP Call-affected sources at 2007 levels, and carried forward the capped 

levels for the 2009 and 2018 future year inventories. 

North Carolina Clean Smokestacks Act (CSA). Under the act, enacted in 2002, coal-fired power 

plants in North Carolina must achieve a 77-percent cut in NOx emissions by 2009 and a 73-

percent cut in SO2 emissions by 2013. This legislation establishes annual caps on both SO2 and 

NOx emissions for the two primary utility companies in North Carolina, Duke Energy and 

Progress Energy. These reductions must be made in North Carolina, and allowances are not 

saleable.

Consent Agreements (TECO, VEPCO) and Gulf Power Crist 7 Voluntary Agreement.

• Under a settlement agreement, Tampa Electric has installed permanent emissions-control

equipment to meet stringent pollution limits.

• Virginia Electric and Power Co. (VEPCO) agreed to spend $1.2 billion by 2013 to 

eliminate 237,000 tons of SO2 and NOx emissions each year from eight coal-fired 

electricity generating plants in Virginia and West Virginia.

• Under a 2002 voluntary agreement, Gulf Power has upgraded its operation to 

significantly cut NOx emissions at its Crist generating plant.

One-hour ozone SIPs (Atlanta / Birmingham / Northern Kentucky). New SIPs have been 

submitted to the EPA to demonstrate attainment of the one-hour ozone National Ambient Air 

Quality Standard (NAAQS). These SIPs require NOx reductions from specific coal fired power 

plants and address transportation plans in these cities.

NOx RACT in 8-hour Nonattainment Area SIPs. The NCDAQ’s SIP for the Charlotte / Rock 

Hill / Gastonia nonattainment area includes Reasonable Achievable Control Technology (RACT) 

51
for NOx for two facilities located in the nonattainment area: Philip Morris USA and Norandal 

USA. These controls were also modeled in 2018. Additional RACT controls may be realized as 

other companies subject to RACT complete the determination, but RACT-level controls were 

assumed for just these two sources.

Heavy Duty Diesel (2007) Engine Standard (for onroad trucks and buses). EPA set a PM 

emissions standard for new heavy-duty engines of 0.01 grams per brake-horsepower-hour 

(g/bhp-hr), to take full effect for diesel engines in the 2007 model year. This rule also includes 

standards for NOx and non-methane hydrocarbons (NMHC) of 0.20 g/bhp-hr and 0.14 g/ bhp-hr, 

respectively. These NOx and NMHC standards were phased in together between 2007 and 2010, 

for diesel engines. Sulfur in diesel fuel must be lowered to enable modern pollution-control 

technology to be effective on these trucks and buses. EPA will require a 97 percent reduction in 

the sulfur content of highway diesel fuel from its current level of 500 parts per million (low 

sulfur diesel, or LSD) to 15 parts per million (ultra-low sulfur diesel, or ULSD).

Tier 2 Tailpipe (Onroad vehicles). EPA mobile rules include the Tier 2 fleet averaging program, 

modeled after the California LEV II standards. Manufacturers can produce vehicles with 

emissions ranging from relatively dirty to zero, but the mix of vehicles a manufacturer sells each 

year must have average NOx emissions below a specified value. Tier 2 standards became 

effective in the 2005 model year. 

Large Spark Ignition and Recreational Vehicle Rule. EPA has adopted new standards for 

emissions of oxides of nitrogen (NOx), hydrocarbons (HC), and carbon monoxide (CO) from 

several groups of previously unregulated nonroad engines. Included in these are large industrial 

spark-ignition engines and recreational vehicles. Nonroad spark-ignition engines are those 

powered by gasoline, liquid propane gas, or compressed natural gas rated over 19 kilowatts (kW) 

(25 horsepower). These engines are used in commercial and industrial applications, including 

forklifts, electric generators, airport baggage transport vehicles, and a variety of farm and 

construction applications. Nonroad recreational vehicles include snowmobiles, off-highway 

motorcycles, and all-terrain-vehicles. These rules were initially effective in 2004 and will be 

fully phased-in by 2012.

Nonroad Diesel Rule. This rule sets standards that will reduce emissions by more than 90 

percent from nonroad diesel equipment, and reduce sulfur levels by 99 percent from current 

levels in nonroad diesel fuel starting in 2007. This step will apply to most nonroad diesel fuel in 

2010 and to fuel used in locomotives and marine vessels in 2012. (http://www.epa.gov/nonroaddiesel/)

Industrial Boiler/Process Heater/RICE MACTs. The EPA originally issued final rules to 

substantially reduce emissions of toxic air pollutants from industrial, commercial and 

institutional boilers, process heaters and from stationary reciprocating internal combustion 

engines (RICE). These rules reduced emissions of a number of toxic air pollutants, including 

hydrogen chloride, manganese, lead, arsenic and mercury by 2009. These rules also reduced 

emissions of SO2 and PM in conjunction with the toxic air pollutant reductions. The applied 

Maximum Achievable Control Technology (MACT) control efficiencies were 4 percent for SO2 

and 40 percent for PM10 and PM2.5. While the EPA’s industrial boiler MACT rules were 

52
vacated on June 8, 2007, the VISTAS “best and final” modeling run includes these reductions. It 

was the consensus of the VISTAS states that these reductions would eventually be reinstated in 

some form well prior to 2018. The proposed Boiler MACT affects numerous relatively large 

boilers in Florida, including one coal-fired unit (Rock Tenn in Fernandina Beach) that has been 

identified as a unit to be addressed within the reasonable progress provisions for SO2 reductions. 

The acid gas emissions requirement of this proposed rule would have the significant co-benefit 

of further reducing SO2 emissions for many of the subject sources. 

Combustion Turbine MACT. The projection inventories do not include the NOx co-benefit 

effects of the MACT regulations for Gas Turbines or stationary Reciprocating Internal 

Combustion Engines, which EPA estimates to be small compared to the overall inventory.

VOC 2-, 4-, 7-, and 10-year MACT Standards. Various point source MACTs and associated 

emission reductions were implemented. We did not count reductions occurring before 2002.

7.2.2 Additional State programs to reduce emissions 

In addition to accounting for specific emission reductions due to ongoing air pollution programs 

as required under the RHR section 40 CFR 51.308 (d)(3)(v)(A), states are also required to 

consider the air quality benefits of measures to mitigate the impacts of construction activities 

[section 40 CFR 51.308(d)(3)(v)(B)] and agricultural and forestry smoke management [section 

40 CFR 51.308(d)(3)(v) (E)]. 

With regard to the impact of construction activities, Rule 62-296.320, F.A.C., General Pollution 

Emission Limiting Standards addresses construction related activities. In particular, section 

(4)(c) Unconfined Emissions of Particulate Matter provides that reasonable precautions be taken 

to prevent or eliminate emissions. For example, the rule addresses paving and maintenance of 

roads, parking areas, and yards and the application of water or chemicals to control emissions

during construction.

With regard to smoke management, Florida has a certified Smoke Management Plan (SMP)

meeting the intent of EPA’s Interim Air Quality Policy on Wildland and Prescribed Fires. The 

Environmental Protection Agency, Region 4, acknowledged receipt of this SMP and its 

certification in February 2002.

The SMP follows the requirements for such a plan contained in the Interim Air Quality Policy on 

Wildland and Prescribed Fires. The Florida Forest Service operates a burn authorization 

program that considers the potential for smoke from the burn impacting smoke sensitive 

receptors (e.g., airports, roads, hospitals, urban areas, etc.). The SMP provides alternatives for 

burning and is considerate of minimizing air pollutants. The SMP is located in Appendix N.

The Prevention of Significant Deterioration (PSD) new source review program also affects 

visibility in Class I area by assuring that major new or modified sources of visibility-affecting 

pollutants are installed with the best available control technology. The air quality review 

required for PSD sources includes an analysis of visibility impacts. The results of this analysis 

weighs-in on the determination of the allowed emissions and required controls for the sources.

53
7.2.3 Projected 2009 and 2018 G2 and Best and Final (G4) Emissions Inventories

The G2 and Best and Final (G4) inventory for 2018 account for post-2002 emission reductions 

from promulgated and proposed federal, state, local, and site-specific control programs as of July 

1, 2004. In general, the G2 emissions inventories were developed for 2009 and 2018 using 

current control information in Florida, and growing the 2002 inventory using EGAS6, 

MOBILE6, and IPM for electric generating units (EGUs). In addition, the Best and Final (G4)

inventory for 2018 includes any known BART and Reasonable Progress emissions changes, and 

changes to specific oil-fired EGUs in Florida to adjust for the IPM solution which assumed 

complete conversion to natural gas. It should be noted that very few of the BART and 

Reasonable Progress changes were available at the time of the last modeling run. For Florida, 

the only the Georgia Pacific Palatka BART changes were included. Many of the projections 

contained in this document are based on the G2 inventory, however, when available, some 

figures and results are based on the Best and Final inventory. The difference between the two 

inventories is limited to a relatively few stationary point source changes that were updated for 

the purpose of the final modeling run. These changes mostly affect sulfur dioxide emissions

(52,540 tons addition) with the Best and Final emissions having greater values, however on a 

state-wide basis, either inventory provides similar qualitative results.

For EGUs, IPM results were adjusted based on state and local (S/L) agency knowledge of 

planned emission controls at specific EGUs (including the changes to the oil-fired units in 

Florida mentioned in the previous paragraph). These updates for G4 are documented in the 

MACTEC emissions inventory report “Documentation of the 2002 Base Year and 2009 and 

2018 Projection Year Emission Inventories for VISTAS” dated July 2007. (Appendix D)

For non-EGUs, we used recently updated growth and control data consistent with the data used 

in EPA’s CAIR analyses supplemented by state and local agency data and updated forecasts 

from the Department of Energy (DOE).

Area source controls were estimated using known state level Stage I controls on gasoline 

dispensing facilities and open burning estimates, as well as controls used to project emissions for 

EPA’s Heavy Duty Diesel rulemaking and for the CAIR rulemaking.

Mobile source controls included local controls underlying the 2002 baseline inventory (vehicle 

emission inspection, Stage II vapor recovery, anti-tampering, etc.) with changes based on 

specific state input. Nonroad control data and projections for 1996, 2010, 2015, and 2020 were 

obtained from the EPA's CAIR Technical Support Document, and straight line projections were 

used to estimate 2009 and 2018 levels.

• The following bar charts show expected decreases in emissions of SO2 and NOx across 

the VISTAS states from 2002 through 2018. Note that for SO2 emissions in particular, 

which are the largest contributors to haze, emissions from electric generating facilities are 

expected to decrease dramatically (57 percent in Florida) between 2002 and 2018. 

However, even after implementation of CAIR, EGU emissions are projected to remain 

54
the largest contributor to haze, comprising more than half of remaining SO2 emissions in 

every state.

Figure 7.2.3-1. Base G2 Annual SO2 emissions for 2002, 2009, and 2018 in the VISTAS 

states.

West Virginia

Alabama

Florida

Kentucky

Georgia

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

West Virginia

Alabama

Florida

Kentucky

Georgia

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

Alabama

Florida

Kentucky

Georgia

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

0

100

200

300

400

500

600

700

800

900

1,000

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual NOx (Thousand Tons)

Miscellaneous

Nonroad Onroad

Industrial Other Fuel Combustion EGU

2002

2009

2018

0

100

200

300

400

500

600

700

800

900

1,000

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual NOx (Thousand Tons)

Miscellaneous

Nonroad Onroad

Industrial Other Fuel Combustion EGU

Miscellaneous

Nonroad Onroad

Industrial Other Fuel Combustion EGU

2002

2009

2018

55
Figure 7.2.3-2. Base G2 Annual NOx emissions in 2002, 2009, and 2018 in the VISTAS 

States.

Summary of Final Base Emissions Inventories for 2009 and 2018

Table 7.2.3-1 is a summary of the 2009 Base G2 emission inventory. The complete inventory 

and discussion of the methodology is contained in Appendix D.

Table 7.2.3-1. 2009 Emissions Inventory Summary for FL.

CO NH3 NOx PM10 PM2.5 SO2 VOC

EGU 35,928 1,631 86,165 9,007 5,910 186,055 1,910

NONEGU 87,037 1,544 46,020 39,872 33,946 65,511 36,880

ONROAD 3,308,863 21,549 312,321 9,801 6,104 2,584 336,707

NONROAD 2,104,920 148 163,794 15,613 14,866 8,967 209,543

AREA 57,011 38,616 28,187 503,230 64,589 36,699 420,172

FIRES 923,310 3,157 19,791 98,470 88,756 4,129 51,527

BIOGENICS 0 0 36,320 0 0 0 1,522,031

TOTAL 6,517,070 66,645 692,599 675,993 214,170 303,943 2,578,768

Table 7.2.3-2 is a summary of the 2018 G4 emission inventory. The complete inventory and 

discussion of the methodology is contained in Appendix D.

Table 7.2.3-2. 2018 Emissions Inventory Summary for FL.

CO NH3 NOx PM10 PM2.5 SO2 VOC

EGU 54,146 2,976 74,640 10,022 6,886 138,340 2,422

NONEGU 96,819 1,829 51,902 46,456 39,430 75,047 42,811

ONROAD 2,520,315 25,885 148,486 8,178 3,994 2,506 219,554

NONROAD 2,323,327 171 127,885 12,497 11,868 7,536 183,452

AREA 53,903 40,432 30,708 578,516 72,454 38,317 489,975

FIRES 923,310 3,157 19,791 98,470 88,756 4,129 51,527

BIOGENICS 0 0 36,320 0 0 0 1,522,031

TOTAL 5,971,821 74,450 489,733 754,139 223,388 265,875 2,511,772

7.2.4 Model Results for the 2018 Base Best and Final (G4) Inventory Compared to the 

Uniform Rate of Progress Glidepaths for FL Class I Areas 

Using 2000 - 2004 IMPROVE monitoring data, the deciview values for the 20 percent best days 

in each year are averaged together, producing a single average deciview value for the best days. 

Similarly, the deciview values for the 20 percent worst days in each year are averaged together, 

producing a single average deciview value for the worst days. 

56
Figures 7.2.4-1 through 7.2.4-10 illustrate the predicted visibility improvement by 2018 resulting 

from the Best and Final inventory that represents implementation of existing federal and state 

regulations, and limited BART and reasonable progress compared to the Uniform Rate of 

Progress glidepath for Everglades National Park (EVER), Chassahowitzka National Wilderness 

Area (CHAS), St. Marks National Wilderness Area (SAMA), Okefenokee National Wilderness 

Area (OKEF), and Breton Island National Wilderness Area (BRET). The green lines show the 

target natural condition in 2064 for the 20 percent worst days or 20 percent best days. The red 

line shows incremental deciview changes resulting from a uniform rate of progress (uniform 

glide slope) between current and natural conditions in 2064, for average 20 percent worst 

visibility days or 20 percent best visibility days in the 2000-2004 baseline period. The purple 

lines show the improvement expected from existing and planned emission controls during the 

period of the first long term strategy. The legend for the purple line refers to Method 1—this is 

the EPA method of averaging all 20% worst days in 2002 without consideration of model 

performance.

The “a” version of figures 7.2.4-1 to 7.2.4-5 represent the projected glidepaths based on the 

CMAQ 12 km results using the new IMPROVE equation without any corrections for model 

performance. The “b” version of figures 7.2.4-1 to 7.2.4-5 make corrections to the calculation of 

the relative reduction factors to account for poor model performance in replicating NO3 and SO4 

concentrations. It was found that NO3 levels were greatly under-predicted by the model 

compared to the actual measurements in some areas, with the Everglades being affected the 

most. Also, but to a lesser extent, there were some days in which SO4 model performance was 

poor. The consequence of this poor model performance is that the relative reduction factors 

developed from the model predictions would be adversely affected if these days are included in 

the calculation. It was our best judgment that the reliability of the relative reduction factor 

would be improved if the calculation took model performance into account. Thus, some limited 

corrections were made in developing the relative reduction factors to account for those days in 

which model performance did not meet certain expectations. The details of this correction are

developed in the Technical Support Document, section 5.3.3 (Appendix F1). 

57
Figure 7.2.4-1a. CMAQ 2018 Best and Final results compared to Uniform Rate of Progress 

at Everglades National Park. 

58
Figure 7.2.4-1b. CMAQ 2018 Best and Final results compared to Uniform Rate of Progress 

at Everglades National Park. (Corrected for NO3 and SO4 model performance)

59
Figure 7.2.4-2a. CMAQ 2018 Best and Final results compared to Uniform Rate of Progress 

at ChassahowitzkaWilderness Area.

60
Figure 7.2.4-2b. CMAQ 2018 Best and Final results compared to Uniform Rate of Progress 

at ChassahowitzkaWilderness Area. (Corrected for NO3 and SO4 model performance)

61
Figure 7.2.4-3a. CMAQ 2018 Best and Final results compared to Uniform Rate of Progress 

at St. Marks Wilderness Area.

62
Figure 7.2.4-3b. CMAQ 2018 Best and Final results compared to Uniform Rate of Progress 

at St. Marks Wilderness Area. (Corrected for NO3 and SO4 model performance)

63
Figure 7.2.4-4a. CMAQ 2018 Best and Final results compared to Uniform Rate of Progress 

at Okefenokee Wilderness Area.

64
Figure 7.2.4-4b. CMAQ 2018 Best and Final results compared to Uniform Rate of Progress 

at Okefenokee Wilderness Area. (Corrected for NO3 and SO4 model performance)

65
Figure 7.2.4-5a. CMAQ 2018 Best and Final results compared to Uniform Rate of Progress 

at Breton Island Wildlife Refuge.

66
Figure 7.2.4-5b. CMAQ 2018 Best and Final results compared to Uniform Rate of Progress 

at Breton Island Wildlife Refuge. (Corrected for NO3 and SO4 model performance)

67
Figure 7.2.4-6 CMAQ 2018 Best and Final results at Everglades National Park.

Reasonable Progress Assessment Base G2 inventory, 

new IMPROVE Algorithm

Everglades - Best 20% Days

11.69 11.69 11.69

11.35 11.46

5.21

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction

68
Figure 7.2.4-7 CMAQ 2018 Best and Final results at Chassahowitzka Wilderness Area.

Reasonable Progress Assessment Base G2 inventory, 

new IMPROVE Algorithm

Chassahowitzka - Best 20% Days

15.51 15.51 15.51

13.83 13.91

5.91

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction

69
Figure 7.2.4-8 CMAQ 2018 Best and Final results at St. Marks Wilderness Area.

Reasonable Progress Assessment Base G2 inventory, 

new IMPROVE Algorithm

Saint Marks - Best 20% Days

14.37 14.37 14.37

13.15 12.80

5.39

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction

70
Figure 7.2.4-9 CMAQ 2018 Best and Final results at Okefenokee Wilderness Area.

Reasonable Progress Assessment Base G2 inventory, 

new IMPROVE Algorithm

Okefenokee - Best 20% Days

15.23 15.23 15.23

14.25 13.92

5.31

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction

71
Figure 7.2.4-10 CMAQ 2018 Best and Final results at Breton Island Wildlife Refuge.

Tables 7.2.4-1 and 7.2.4-2 are provided to show the pollutant-specific extinction without and 

with the model performance correction, respectively. The data shows the unusually large 

percentage increase in NO3 extinction when the poor performance data is included.

Reasonable Progress Assessment Base G2 inventory, 

new IMPROVE Algorithm

Breton - Best 20% Days

14.04 14.04 14.04

13.75 13.50

5.33

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction

72
Table 7.2.4-1 

Class I Area Name State

IMPROVE 

Site

# 

Days 

in 

2002

2000-2004 

Baseline 

dV

Natural 

Background dV

2018 dV 

Reduction 

Target

Modeled 

2018 dV 

Reduction

Difference 

from dV 

Reduction 

Target

Chassahowitzka FL CHAS1 23 25.7 11.3 3.4 3.5 -0.1

Everglades FL EVER1 24 22.3 12.3 2.3 1.5 0.8

Saint Marks FL SAMA1 23 26.3 11.6 3.4 3.3 0.1

Okefenokee GA OKEF1 23 27.1 11.5 3.6 3.3 0.3

Breton LA BRET1 24 26.0 12.3 3.2 2.8 0.4

Percent Change in Average Extinction (Mm-1) for Worst 20% Days

bEXT

(w/ Ray) bSO4 bNO3 bOC bEC bSOIL bCM bSS

Chassahowitzka FL CHAS1 -30% -43% -2% -6% -29% 22% 28% 0%

Everglades FL EVER1 -12% -39% 131% -6% -22% 2% 7% 0%

Saint Marks FL SAMA1 -28% -42% 17% -4% -12% 12% 6% 0%

Okefenokee GA OKEF1 -28% -44% 37% -6% -14% 16% 8% 0%

Breton LA BRET1 -24% -41% 68% 4% -9% 14% 0% 0%

Absolute Change in Average Extinction (Mm-1) for Worst 20% Days

bEXT

(w/ Ray) bSO4 bNO3 bOC bEC bSOIL bCM bSS

Chassahowitzka FL CHAS1 -40.3 -37.9 -0.1 -1.3 -1.9 0.2 0.8 0.0

Everglades FL EVER1 -14.0 -16.5 6.3 -2.8 -1.3 0.0 0.2 0.0

Saint Marks FL SAMA1 -39.9 -39.3 0.8 -0.9 -0.7 0.1 0.1 0.0

Okefenokee GA OKEF1 -45.4 -45.0 1.8 -1.8 -0.9 0.1 0.2 0.0

Breton LA BRET1 -34.0 -39.9 5.8 0.4 -0.5 0.1 0.0 0.0

2000-2004 Baseline Average Extinction (Mm-1) for Worst 20% Days

bEXT

(w/ Ray) bSO4 bNO3 bOC bEC bSOIL bCM bSS

Chassahowitzka FL CHAS1 135.0 87.4 5.1 20.6 6.7 0.9 3.0 0.2

Everglades FL EVER1 116.4 42.5 4.8 47.1 5.9 0.9 3.0 1.2

Saint Marks FL SAMA1 142.1 93.1 4.5 24.2 5.6 0.8 2.6 0.2

Okefenokee GA OKEF1 159.4 102.9 4.9 30.3 6.2 0.8 3.1 0.2

Breton LA BRET1 139.0 97.0 8.5 11.7 5.2 1.0 3.8 0.7

73
Table 7.2.4-2

Class I Area Name State

IMPROVE 

Site

# 

Days 

in 

2002

2000-2004 

Baseline 

dV

Natural 

Background dV

2018 dV

Reduction 

Target

Modeled 

2018 dV 

Reduction

Difference 

from dV 

Reduction 

Target

Chassahowitzka FL CHAS1 23 25.7 11.3 3.4 3.5 -0.1

Everglades FL EVER1 24 22.3 12.3 2.3 2.5 -0.2

Saint Marks FL SAMA1 23 26.3 11.6 3.4 3.4 0.0

Okefenokee GA OKEF1 23 27.1 11.5 3.6 3.4 0.3

Breton LA BRET1 24 26.0 12.3 3.2 3.8 -0.6

Percent Change in Average Extinction (Mm-1) for Worst 20% Days

bEXT

(w/ Ray) bSO4 bNO3 bOC bEC bSOIL bCM bSS

Chassahowitzka FL CHAS1 -30% -43% -2% -6% -29% 22% 28% 0%

Everglades FL EVER1 -18% -40% 0% -6% -23% 2% 7% 0%

Saint Marks FL SAMA1 -29% -43% 17% -4% -12% 12% 7% 0%

Okefenokee GA OKEF1 -29% -44% 37% -6% -14% 16% 9% 0%

Breton LA BRET1 -32% -46% 0% 4% -11% 16% 0% 0%

Absolute Change in Average Extinction (Mm-1) for Worst 20% Days

bEXT

(w/ Ray) bSO4 bNO3 bOC bEC bSOIL bCM bSS

Chassahowitzka FL CHAS1 -40.3 -37.9 -0.1 -1.3 -1.9 0.2 0.8 0.0

Everglades FL EVER1 -21.1 -17.1 0.0 -2.9 -1.3 0.0 0.2 0.0

Saint Marks FL SAMA1 -40.8 -40.2 0.8 -0.9 -0.7 0.1 0.2 0.0

Okefenokee GA OKEF1 -46.1 -45.7 1.8 -1.8 -0.9 0.1 0.3 0.0

Breton LA BRET1 -44.3 -44.3 0.0 0.5 -0.6 0.2 0.0 0.0

Absolute Change in Average Extinction (Mm-1) for Worst 20% Days

bEXT

(w/ Ray) bSO4 bNO3 bOC bEC bSOIL bCM bSS

Chassahowitzka FL CHAS1 -40.3 -37.9 -0.1 -1.3 -1.9 0.2 0.8 0.0

Everglades FL EVER1 -21.1 -17.1 0.0 -2.9 -1.3 0.0 0.2 0.0

Saint Marks FL SAMA1 -40.8 -40.2 0.8 -0.9 -0.7 0.1 0.2 0.0

Okefenokee GA OKEF1 -46.1 -45.7 1.8 -1.8 -0.9 0.1 0.3 0.0

Breton LA BRET1 -44.3 -44.3 0.0 0.5 -0.6 0.2 0.0 0.0

In Class I areas in Florida, visibility improvements on the 20 percent worst days are expected to 

be slightly better than the uniform rate of progress glidepath by 2018 for Everglades and 

Chassahowitzka, and slightly less than the uniform rate of progress for St. Marks based on 

reductions from existing and planned emissions controls. Visibility improvement in nearby

Class I areas outside of Florida (Okefenokee and Breton), for which Florida sources may impact, 

74
are all slightly worse and slightly better, respectively, than the uniform rate of progress. In all 

cases, the rate of visibility improvement is hovering near the uniform rate of progress. 

Additional emissions reductions from application of BART or reasonable progress requirements, 

which have not been taken in to account in the final modeling run, would provide additional 

visibility improvement. 

In addition to improving visibility on the 20 percent worst visibility days, states are also required 

to assure that visibility on the 20 percent best days at the Class I areas does not degrade. Figures 

7.2.4-6 to 7.2.4-10 show that visibility on the best days improves. 

7.3 Relative Contribution from International Emissions to Visibility Impairment in 2018 at 

VISTAS Class I areas

Emissions from Mexico, Canada, Central America, Asia, and Africa contribute to PM2.5 

loadings and visibility impairment at Class I areas in the continental United States. To evaluate 

the relative contribution of international emissions to visibility at Class I areas in the 

southeastern United States, VISTAS used a combination of modeling results from the global 

three-dimensional chemical transport model (GEOS-Chem) and CMAQ. VISTAS used the 

GEOS-Chem global model to generate initial and boundary conditions for the CMAQ modeling 

domain. GEOS-Chem was run for the 2002 modeling year using a 4 x 5 degree horizontal grid 

resolution and a 3-hour temporal resolution. Because emissions were based on monthly 

averages, the model does not capture the episodic variability in emissions. The GEOS-Chem 

outputs were used to calculate initial and boundary conditions for the national CMAQ modeling 

domain. The national CMAQ domain included portions of Canada and Mexico, so emissions for 

these countries were included within the national CMAQ modeling domain or as part of the 

boundary conditions outside the national modeling domain, as appropriate.

Two complementary methods were used to calculate the impact of international emissions at 

Class I areas. Because all international fires are treated as natural emissions in these runs, both 

cases underestimate the contributions from international fires that are due to anthropogenic 

burning. 

1) International emissions are represented by the difference between two GEOS-Chem runs. 

In the first run United States anthropogenic emissions were removed, and in the second 

run both United States and international anthropogenic emissions were removed. The 

difference represents international anthropogenic emissions, in the absence of United 

States anthropogenic emissions (e.g. compared to 2064 levels). Harvard University 

provided GEOS-Chem results to VISTAS for 2002 international contribution on 4 x 5 

degree grid. Concurrently Harvard modeling for the Electric Power Research Institute 

(EPRI) provided GEOS-Chem results for 2001 international contribution on a 1 x 1 

degree grid scale. 

2) International emissions are represented by the difference between two CMAQ 36-km 

simulations, both using 2018 Base F emissions and boundary conditions from GEOS75
Chem. In the first CMAQ run, all global natural and anthropogenic emissions in 2018 

are active. In the second CMAQ run, only global (United States and international) 

natural emissions are active. Here the impacts of international emissions are compared 

against 2018 conditions rather than natural background conditions. 

Separate from VISTAS, the CENRAP RPO used PM Source Apportionment Technology 

(PSAT) in the CAMx regional air quality model to calculate the impact of Canadian and 

Mexican emissions and boundary conditions on visibility at Class I areas in 2002. 

As illustrated in Figure 7.3-1 for annual average contributions to sulfate at VISTAS and 

neighboring Class I areas, the estimated international contributions are higher at Class I areas 

near the Canadian and Mexican borders and along the eastern coast. The estimated 

international contribution is higher using CMAQ and PSAT than in the GEOS-Chem runs 

because the grid scale is finer (more accurate dispersion of emissions) and because the 

background atmosphere includes loadings from current United States anthropogenic 

emissions (greater photochemical activity). Similar charts for nitrate and organic carbon 

mass, for impacts on 20 percent worst visibility days, and for impacts of international 

emissions on calculated light extinction are included in Appendix H. 

Figure 7.3-1. Estimated international emissions contributions to sulfate at VISTAS and 

neighboring Class I areas. 

Transboundary Man-Made Impacts

0.0

0.2

0.4

0.6

0.8

1.0

1.2

BRIG

HEGL

CACR

MING

UPBU

BRETEVER

CHAS

SAMA

COHU

OKEF

ROMA

SIPS

SHRO

GRSM

LIGO

MACASWAN

JARI

DOSO

SHEN

(NH4)2SO4 Conc. (

μg/m3

)

GEOS_4x5 GEOS_1x1 PSAT CMAQ

76
7.4 Relative Contributions to Visibility Impairment: Pollutants, Source Categories, and 

Geographic Areas

An important step toward identifying further reasonable progress measures is to identify the key 

pollutants contributing to visibility impairment at each Class I area. To understand the relative 

benefit of further reducing emissions from different pollutants, source sectors, and geographic 

areas, VISTAS engaged the Georgia Institute of Technology to perform emission sensitivity 

model runs using CMAQ. Emissions sensitivities were initially performed for three episodes 

representing winter and summer conditions: Jan 2002, July 2001, and July 2002. These runs 

used the initial 2018 projections inventory and considered 30 percent reductions from specific 

pollutants, source categories, and geographic areas. Emissions sensitivities were repeated using 

the 2009 Base D projection inventory and two month-long episodes from 2002: Jun 1-Jul 10 and 

Nov 19 – Dec 19. Emissions in 2009 were reduced by 30 percent for each pollutant sensitivity 

run. The pollutant contributions that were evaluated were:

• SO2 from EGU sources in each VISTAS state, other RPOs in the VISTAS 12 km grid, 

and Boundary Conditions from outside the 12 km domain.

• SO2 from non-EGU point sources in each VISTAS state, other RPOs, and Boundary 

Conditions

• NOx from ground level (on-road plus non-road plus area) sources in each VISTAS state 

and other RPOs

• NOx from point (EGU plus non-EGU) sources in each VISTAS state and other RPOs

• NH3 from all sources in VISTAS and other RPOs

• Volatile Organic Compounds from anthropogenic and biogenic sources in the 12 km 

modeling domain

• Primary Carbon from all ground level sources in each VISTAS state and other RPOs

• Primary Carbon from all point sources in each VISTAS state and other RPOs

• Primary Carbon from all fires in each VISTAS state and other RPOs

Results are shown in Figures 7.4-1 through 7.4-4 below for the average of the 20 percent worst 

visibility days for each of three Florida Class I areas, plus Okefenokee. Responses for 20 percent 

worst days were calculated by averaging the responses of the 20 percent worst days that were 

modeled in the two episodes. For the Florida sites, responses on four to five of the 20 percent 

worst visibility days were included in these graphics.

77
Figure 7.4-1. CMAQ projections of visibility responses on 20 percent worst days at 

Everglades to 30 percent reductions from the 2009 Base D inventory for visibility-reducing 

pollutants in different source categories and geographic areas. 

Everglades, FL (Worst)

-4.50

-4.00

-3.50

-3.00

-2.50

-2.00

-1.50

-1.00

-0.50

0.00

0.50

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

∆

Bext (Mm-1)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

78
Figure 7.4-2. CMAQ projections of visibility responses on 20 percent worst days at 

Chassahowitzka to 30 percent reductions from the 2009 Base D inventory for 

visibility-reducing pollutants in different source categories and geographic areas.

Figure 7.4-3. CMAQ projections of visibility responses on 20 percent worst days at St. 

Marks to 30 percent reductions from the 2009 Base D inventory for visibility-reducing 

pollutants in different source categories and geographic areas. 

Chassahowitzka, FL (Worst)

-8.00

-7.00

-6.00

-5.00

-4.00

-3.00

-2.00

-1.00

0.00

1.00

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

∆

Bext (Mm-1)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

St._Marks, FL (Worst)

-16.00

-14.00

-12.00

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

2.00

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

∆

Bext (Mm-1)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

79
Figure 7.4-4. CMAQ projections of visibility responses on 20 percent worst days at 

Okefenokee to 30 percent reductions from the 2009 Base D inventory for visibility-reducing 

pollutants in different source categories and geographic areas.

As Figures 7.4-1 through 7.4-4 illustrate, the greatest visibility benefits on the 20 percent worst 

days for the Florida Class I areas and Okefenokee are projected to result from further reducing 

SO2 from EGUs. The Everglades is somewhat different than any of the other Class I areas with a 

greater relative influence from carbon (VOC) and boundary conditions. Contributions from 

other RPOs are comparatively small and the greatest benefits would likely be from further EGU 

reductions within Florida, Georgia, and Alabama. Additional benefits are projected from SO2

emission reductions from non-utility, industrial point sources. The pattern of relative SO2

contributions from non-EGUs among the various VISTAS states is similar to the pattern of 

relative SO2 contributions from EGUs.

Because ammonium nitrate is a relatively small contributor to PM2.5 mass and visibility 

impairment on the 20 percent worst days at all the Class I areas, the benefits of reducing NOx 

and NH3 emissions at these sites are small. For the 20 percent best days ammonium nitrate has 

a somewhat larger contribution to visibility impairment. Reducing ammonia emissions would be 

more beneficial for reducing ammonium nitrate contributions to visibility impairment than 

further reducing nitrogen oxide emissions from either ground or point sources. 

VOCs do contribute to visibility impairment, but as shown in the charts above, this contribution 

is largely from biogenic sources such as vegetative emissions. Controlling anthropogenic 

Okefenokee, GA (Worst)

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

2.00

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

∆

Bext (Mm-1)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

80
sources of VOC emissions has little if any visibility benefit at the Class I areas. Reducing 

primary carbon from point sources, ground level sources or fires have a relatively small visibility 

benefit on average, although fires can have a large impact on individual days. This is consistent 

with the monitoring data that shows that most of measured organic carbon is secondary in origin 

and primary carbon is only a small fraction of the total measured carbon (Appendix B). 

Note that these results from the emission sensitivity runs are consistent with the conclusions 

drawn from the 2000-2004 baseline monitoring data (see section 2.4 above). The results indicate 

that sulfate is the dominant contributor to visibility impairment on the 20 percent worst days at 

all sites, and that ammonium nitrate may be important for sites where the 20 percent worst days 

occur in the winter. We conclude that reducing SO2 emissions from EGU and non-EGU point 

sources in the VISTAS states would have the greatest visibility benefits for the Florida and 

nearby Class I areas. 

7.5 Relative Contributions to Visibility Impairment: Geographic Areas of Influence for 

Florida Class I Areas

Once it was determined that SO2 emission reductions from EGU and non-EGU point sources in 

the VISTAS states would be the most effective sources to control to improve visibility at the 

Florida and nearby Class I areas, the next step was to identify the specific geographic areas that 

most likely influence visibility in each Class I area, and then to identify the major SO2 point 

sources located in those geographic areas. An SO2 Area of Influence (AoI) was defined for each 

Class I area to represent the geographic area containing sources that would likely have the 

greatest impact on visibility at that Class I area. All SO2 point sources within these Areas of 

Influence were identified and ranked by their 2002 emissions. The following sections contain a 

broad overview of the steps in the Area of Influence analyses. See Appendix F1 for a more 

detailed discussion of these analyses and plots for additional Class I areas.

7.5.1 Back Trajectory Analyses

The first step was to generate meteorological back trajectories for IMPROVE monitoring sites in 

Florida and neighboring Class I areas for the 2000-2004 baseline period. Back trajectory 

analyses use interpolated measured or modeled meteorological fields to estimate the most likely 

central path of air masses that arrive at a receptor at a given time. The method essentially 

follows a parcel of air backward in hourly steps for a specified length of time. Figure 7.5.1 is an 

example of a back trajectory analysis for Everglades National Park for the 20 percent worst days 

in 2002. 

81
Trajectories were started at 100 meters and 500 meters above the surface and run backward from 

the site for 72-hours. These individual back trajectories for 20 percent worst days in 2002 were 

also useful in evaluating model performance for individual days at the Class I areas. 

7.5.2 Residence Time Plots

The next step was to plot residence time for each Class I area using five years of back trajectories 

for the 20 percent worst visibility days in 2000-2004. Residence time is the frequency that winds 

pass over a specific geographic area on the path to a Class I area. Separate residence time plots 

were generated using trajectories with 100m and 500m start heights. As illustrated in Figure 

7.5.2, winds influencing Everglades on the 20 percent worst days come from directions that 

move over either highly populated areas or areas where large point sources of emissions eminate.

82
Figure 7.5.2. Example residence time plot for 20 percent worst visibility days in 2000-2004 

for Everglades. Based on trajectories with 100m start height.

7.5.3 SO2 Areas of Influence

The next step was to develop sulfate extinction weighted residence time plots to define the 

geographic area with highest probability of influencing the receptor on the 20 percent worst days 

in 2000-2004 that were dominated by sulfate. Each back trajectory was weighted by sulfate 

extinction for that day. This allows us to focus on the 20 percent worst days that are influenced 

by sulfate and place less importance on days influenced by organic carbon from fires. Sulfateweighted back trajectories for the 20 percent worst days were combined for 5 years of data. The 

resulting sulfate extinction-weighted residence time plots were used to define the geographic 

Area of Influence for sources of SO2 emissions. In Figure 7.5.3 the area representing 10 percent 

or greater residence time is outlined in red and the area representing 5 percent or greater 

residence time is outlined in gray. The VISTAS states focused their analyses on the Area of 

Influence defined by 5 percent or greater sulfate extinction-weighted residence time. 

83
Figure 7.5.3. Example SO2 Area of Influence plot for sulfate extinction weighted residence 

time for 20 percent worst visibility days in 2000-2004 for Everglades. Based on trajectories 

with 100m start height.

7.5.4 Emissions Sources within SO2 Areas of Influence 

Residence time plots were then combined with geographically-gridded emission data based on 

the 2002 baseline and 2018 BaseG emissions inventories. Plots were generated for the Areas of 

Influence defined by trajectories with 100 m and 500 m start heights. As a way of incorporating 

the effects of transport, deposition, and chemical transformation of point source emissions along 

the path of the trajectories, these data were weighted by 1/d, where d was calculated as the 

distance, in kilometers, between the center of the grid cell in which a source is located and the 

center of the grid cell in which the IMPROVE monitor is located. The distance-weighted point 

84
source SO2 emissions are then combined with the gridded extinction-weighted back-trajectory 

residence times at a spatial resolution of 36-km. 

The final step was to combine the residence times and gridded emissions data in plots and data 

sets. The distance weighted (1/d) gridded point source SO2 emissions were multiplied by the 

total extinction-weighted back-trajectory residence times on a grid cell by grid cell basis. These 

results were then normalized by the domain-wide total and displayed as a percentage. The 

analysis was done using both the 2002 and 2018 base year inventories. 

Figures 7.5.4-1 illustrates 2002 and 2018 distance weighted gridded emissions * sulfate 

extinction weighted residence time plots for Everglades. These maps help visualize where the 

emissions reductions will be occurring between 2002 and 2018. The change in SO2 emissions 

between 2002 and 2018 can be seen by comparing emissions source strengths in the two plots. 

Note the emissions from each source are normalized by the total emissions in the domain. 

Sources that reduce SO2 emissions by 2018 will show a lower contribution to emissions in the 

domain. On the 2018 map the grid cells with these sources will show a lighter color gradient 

than on the 2002 map. 

Figure 7.5.4-1. Everglades 2002 and 2018 SO2 distance weighted emissions * SO4 

extinction-weighted residence time plots.

Comparison 2002 vs 2018 SO2 Emissions * Residence 

Time Using 100 m Start Height – Everglades, FL

2002 SO2 emissions 2018 SO2 emissions

Green circles indicate 100-km and 200-km radii from Class I area.

Red line perimeter indicate Area of Influence with Residence Time > 10%.

Orange line perimeter indicate Area of Influence with Residence Time > 5%.

Max Value = 37%

85
Figures 7.5.4-2 through 7.5.4.4 illustrate gridded SO2 distance weighted emissions * sulfate 

extinction weighted residence time plots for 2002 and 2018 emissions for Chassahowitzka, St. 

Marks, Okefenokee, and Breton. These plots illustrate the relative importance of Florida sources 

of SO2 compared to sources in neighboring states. 

These analyses are serving as the basis for consultation among the VISTAS states.

Figure 7.5.4-2. 2002-2018 SO2 distance weighted emissions * SO4 extinction-weighted 

residence time plot for Chassahowitzka.

Comparison 2002 vs 2018 SO2 Emissions * Residence 

Time Using 100 m Start Height – Chassahowitzka, FL

2002 SO2 emissions 2018 SO2 emissions

Green circles indicate 100-km and 200-km radii from Class I area.

Red line perimeter indicate Area of Influence with Residence Time > 10%.

Orange line perimeter indicate Area of Influence with Residence Time > 5%.

Max Value = 68%

86
Figure 7.5.4-3. 2002-2018 SO2 distance weighted emissions * SO4 extinction-weighted 

residence time plot for St. Marks.

Comparison 2002 vs 2018 SO2 Emissions * Residence 

Time Using 100 m Start Height – St. Marks, FL

2002 SO2 emissions 2018 SO2 emissions

Green circles indicate 100-km and 200-km radii from Class I area.

Red line perimeter indicate Area of Influence with Residence Time > 10%.

Orange line perimeter indicate Area of Influence with Residence Time > 5%.

Max Value = 22%

87
Figure 7.5.4-4. 2002-2018 SO2 distance weighted emissions * SO4 extinction-weighted 

residence time plot for Okefenokee, GA.

2002 vs 2018 SO2 Emissions weighted by Residence Time

Okefenokee, GA 

2002 SO2 emissions 2018 SO2 emissions

Green circles indicate 100-km and 200-km radii from Class I area.

Red line perimeter indicate Area of Influence with Residence Time > 10%.

Orange line perimeter indicate Area of Influence with Residence Time > 5%.

Max Value = 25%

88
Figure 7.5.4-5. 2002-2018 SO2 distance weighted emissions * SO4 extinction-weighted 

residence time plot for Breton, LA.

7.5.5 Specific Source Types in the Areas of Influence for Florida and Nearby Class I Areas

As previously concluded in section 7.4, the greatest opportunity to affect visibility improvement 

is to reduce emissions of SO2 from stationary point sources. The following tables quantify the 

emissions from specific source categories that emit SO2 within the area of influence, defined as 

within the area having a residence time of 5% or greater surrounding each Class I area. The 

contributions from major source categories to the 2018 Base G2 inventory for the SO2 Areas of 

Influence for the Florida Class I areas are listed in Tables 7.5.5-1 through 7.5.5-5. 

2002 vs 2018 SO2 Emissions weighted by Residence Time

Breton, LA 

2002 SO2 emissions 2018 SO2 emissions

Green circles indicate 100-km and 200-km radii from Class I area.

Red line perimeter indicate Area of Influence with Residence Time > 10%.

Orange line perimeter indicate Area of Influence with Residence Time > 5%.

Max Value = 10%

89
Annual 2018 G2 Emissions - Everglades Area of Influence

Category VOC NOX CO SO2 PM-10 PM-2.5 NH3

Fuel Comb. Elec. Util. 0% 15% 1% 34% 3% 5% 6%

Fuel Comb. Industrial 1% 8% 2% 11% 4% 11% 0%

Fuel Comb. Other 1% 4% 0% 9% 2% 4% 0%

Chemical & Allied Product Mfg 0% 0% 0% 36% 0% 0% 3%

Metals Processing 0% 0% 0% 1% 0% 0% 0%

Petroleum & Related Industries 0% 0% 0% 0% 0% 0% 0%

Other Industrial Processes 3% 1% 0% 1% 2% 2% 0%

Solvent Utilization 40% 0% 0% 0% 0% 0% 0%

Storage & Transport 10% 0% 0% 0% 0% 1% 0%

Waste Disposal & Recycling 1% 0% 1% 0% 2% 5% 1%

Highway Vehicles 21% 34% 41% 1% 2% 3% 37%

Off-highway 20% 34% 45% 5% 3% 9% 0%

Miscellaneous 3% 3% 10% 2% 82% 60% 52%

Table 7.5.5-1. 2018 Emissions Contributions from Major Source Categories in the Area of Influence for 

Everglades.

Annual 2018 G2 Emissions - Chassahowitzka Area of Influence

Category VOC NOX CO SO2

PM10PM2.5 NH3

Fuel Comb. Elec. Util. 0% 19% 1% 48% 3% 5% 3%

Fuel Comb. Industrial 0% 13% 1% 17% 2% 5% 0%

Fuel Comb. Other 2% 4% 1% 7% 1% 3% 0%

Chemical & Allied Product Mfg 1% 1% 0% 12% 0% 1% 1%

Metals Processing 0% 0% 0% 4% 0% 0% 0%

Petroleum & Related Industries 0% 0% 0% 5% 0% 0% 0%

Other Industrial Processes 5% 4% 1% 4% 7% 11% 3%

Solvent Utilization 36% 0% 0% 0% 0% 0% 0%

Storage & Transport 9% 0% 0% 0% 0% 0% 0%

Waste Disposal & Recycling 4% 3% 7% 0% 9% 19% 0%

Highway Vehicles 19% 27% 37% 1% 1% 1% 18%

Off-highway 17% 25% 31% 2% 2% 4% 0%

Miscellaneous 6% 5% 20% 2% 73% 51% 75%

Table 7.5.5-2. 2018 Emissions Contributions from Major Source Categories in the Area of Influence for 

Chassahowitzka.

90
Annual 2018 G2 Emissions - St. Marks Area of Influence

Category VOC NOX CO SO2

PM10PM2.5 NH3

Fuel Comb. Elec. Util. 0% 20% 1% 46% 4% 7% 2%

Fuel Comb. Industrial 1% 17% 2% 20% 3% 5% 0%

Fuel Comb. Other 2% 4% 1% 8% 1% 3% 0%

Chemical & Allied Product Mfg 1% 1% 0% 7% 0% 1% 1%

Metals Processing 0% 0% 0% 4% 0% 0% 0%

Petroleum & Related Industries 2% 0% 0% 5% 0% 0% 0%

Other Industrial Processes 7% 7% 1% 8% 8% 11% 4%

Solvent Utilization 36% 0% 0% 0% 0% 0% 0%

Storage & Transport 8% 0% 0% 0% 1% 1% 0%

Waste Disposal & Recycling 4% 2% 7% 0% 8% 18% 0%

Highway Vehicles 18% 21% 36% 0% 1% 1% 18%

Off-highway 14% 24% 28% 2% 2% 4% 0%

Miscellaneous 7% 4% 23% 1% 71% 50% 75%

Table 7.5.5-3. 2018 Emissions Contributions from Major Source Categories in the Area of Influence for St. 

Marks. 

Annual 2018 G2 Emissions - Okefenokee Area of Influence

Category VOC NOX CO SO2

PM10PM2.5 NH3

Fuel Comb. Elec. Util. 0% 22% 1% 51% 7% 12% 1%

Fuel Comb. Industrial 1% 16% 2% 25% 3% 5% 0%

Fuel Comb. Other 3% 4% 1% 6% 2% 4% 0%

Chemical & Allied Product Mfg 1% 1% 0% 4% 0% 1% 0%

Metals Processing 0% 0% 0% 4% 0% 0% 0%

Petroleum & Related Industries 0% 0% 0% 0% 0% 0% 0%

Other Industrial Processes 7% 6% 1% 7% 8% 11% 2%

Solvent Utilization 39% 0% 0% 0% 0% 0% 0%

Storage & Transport 7% 0% 0% 0% 0% 0% 0%

Waste Disposal & Recycling 4% 3% 7% 0% 8% 16% 0%

Highway Vehicles 18% 25% 38% 1% 1% 1% 10%

Off-highway 14% 19% 29% 1% 2% 3% 0%

Miscellaneous 6% 4% 20% 1% 68% 46% 86%

Table 7.5.5-4. 2018 Emissions Contributions from Major Source Categories in the Area of Influence for 

Okefenokee, GA.

91
Annual 2018 G2 Emissions - Breton Area of Influence

Category VOC NOX CO SO2

PM10PM2.5 NH3

Fuel Comb. Elec. Util. 1% 19% 1% 33% 3% 6% 1%

Fuel Comb. Industrial 2% 31% 4% 18% 8% 14% 0%

Fuel Comb. Other 4% 3% 2% 5% 2% 4% 0%

Chemical & Allied Product Mfg 4% 4% 1% 24% 2% 3% 6%

Metals Processing 1% 1% 1% 4% 3% 5% 0%

Petroleum & Related Industries 4% 1% 1% 8% 1% 1% 0%

Other Industrial Processes 7% 5% 2% 5% 11% 13% 16%

Solvent Utilization 33% 0% 0% 0% 0% 0% 0%

Storage & Transport 8% 0% 0% 0% 1% 1% 0%

Waste Disposal & Recycling 3% 1% 5% 0% 5% 10% 1%

Highway Vehicles 12% 13% 33% 0% 1% 1% 7%

Off-highway 14% 20% 29% 2% 2% 4% 0%

Miscellaneous 6% 2% 21% 1% 62% 39% 69%

Table 7.5.5-5. 2018 Emissions Contributions from Major Source Categories in the Area of Influence for 

Breton, LA.

The next step in the analysis was to determine which particular sources to target for potential 

further reasonable progress emission reductions. Lists of SO2 point sources within the Areas of 

Influence for each Class I areas were developed using the most current (BaseG) VISTAS 2002 

base year and 2018 future year emissions. For this purpose the Area of Influence was defined as 

the counties with maximum sulfate extinction weighted residence time greater than 5. For SO2

sources within each Area of Influence, the following attributes were defined for each individual 

unit: 

• State, county, and source (plant), and industry identification codes

• SO2 emissions for 2002 and 2018

• 2018 control efficiency

• Distance to Class I areas (defined by centroid of the Class I area)

• Emissions divided by distance (Q/d), a metric that accounts for the dispersion of 

emissions over distance 

• Maximum sulfate extinction weighted residence time (RTmax)

Based on this information, we could establish an objective criteria for identifying the sources of 

SO2 having the greatest potential for visibility impairment in each Class I area. The metric that 

most states have used to best summarize the relative visibility impact is Q/d * RTmax, where Q 

represents the amount of emissions (the greater the emissions, the greater the chance of visibility 

impairment), d is the distance (the greater the distance the more disperse the emissions and the 

less impact on visibility), and RTmax – a measure of the probability that the local climatology 

will direct winds from the source to the Class I area (larger RTmax leads to greater visibility 

impairment). Based on this product, associated with each unit, most states paired-down the list 

of visibility-impairing sources to those having at least a 1% relative contribution to the total 

Q/d*RTmax for a given Class I area. Some states used a value of 0.5% relative contribution. In 

92
most cases, other states, in developing these data used the projected 2018 emissions, which for 

EGU’s was based on the IPM electric generation demand model. The IPM model produced what 

we believe to likely be inaccurate projections for oil-fired EGU’s in Florida. Namely, IPM 

projects that all of these units will convert to natural gas by 2018, thus producing essentially no 

SO2 emissions. Thus, for the purpose of identifying sources for potential reasonable progress 

review, we used the 2002 emissions. These data were used to develop the Florida-specific 

criteria to determine sources for reasonable progress four-factor review. 

7.6 Reasonable Progress Requirement

The Clean Air Act (Sec. 169A) requires that states provide for reasonable progress toward 

attaining the goal of preventing any future, and remedying any existing impairment of visibility 

in mandatory class I Federal areas. In determining reasonable progress, states shall consider the 

four factors listed below.

• the costs of compliance

• the time necessary for compliance

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

• the remaining useful life of any potentially affected sources.

Regulations implementing this requirement have been promulgated in 40 CFR Part 51, Subpart P 

– Protection of Visibility. Section 51.308 specifically addresses the regional haze program 

requirements. Guidance on implementing the reasonable progress requirements have been 

developed by the EPA, “Guidance for Setting Reasonable Progress Goals Under the Regional 

Haze Program” revised June 1, 2007.

It is the stated objective of the regional haze rule that states shall establish a reasonable progress 

goal that provides for “reasonable progress” to be made within the planning period for each 

Class I area toward the goal of natural visibility conditions by 2064. Further, in establishing 

whether reasonable progress is being made, states must consider the straight line path from 

baseline (2000-2004) to natural conditions in 2064 (i.e., the uniform rate of progress). In 

establishing the reasonable progress goal for a Class I area, states must consider the four factors

listed above. In judging the adequacy of visibility improvement, the state first considers all 

current regulations and programs, and then determines the amount of additional improvement 

that may be necessary to represent reasonable progress. As stated in EPA’s guidance, “Given the 

significant emissions reductions that we anticipate to result from BART, the CAIR, and the 

implementation of other CAA programs, including the ozone and PM2.5 NAAQS, for many 

States this [determining the visibility improvement from these reductions] will be an important 

step in determining your RPG, and it may be all that is necessary to achieve reasonable progress 

in the first planning period for some States.” In fact, the reasonable progress goals set forth in 

this plan, as amended in 2012, are largely based on continued implementation of the CAIRdriven emission reductions, along with other existing requirements. Although there is 

uncertainty over CAIR’s eventual replacement, CAIR remains in effect and its associated 

emission reductions continue to occur. Significant emission reductions forced by CAIR have 

occurred as of 2010. Thus, the reasonable progress goals as originally developed remain valid 

93
for Florida. The following chart shows the actual Florida SO2 emissions compared to the 

original VISTAS projections used to determine Florida’s reasonable progress goals. Actual SO2

emissions by 2010 (the most recent year of available data) are already less than the projected 

2018 emissions.

 

Because of the large amount of emissions reductions of SO2 and NOx in the Southeastern U.S. 

from existing rules and programs, Class I areas in VISTAS states are expected to make 

considerable visibility improvement during the first regional haze planning period. 

7.7 Florida’s Reasonable Progress Analysis

As stated earlier, Florida participated in regional planning through the Visibility Improvement 

State and Tribal Association of the Southeast (VISTAS) regional planning organization. 

VISTAS was established to complete common technical requirements of the regional haze SIP, 

such as air quality modeling and data analysis. Through this process, VISTAS provided states 

data and information related to the state’s determination of reasonable progress toward the longrange visibility goal. This information helped states decide which pollutants and which sources 

of these pollutants best provided for reasonable progress. Further, limited information was 

gathered to help states address the cost of potential pollutant reductions. While VISTAS 

provided a common dataset for states to use in their reasonable progress requirement, the states 

did not attempt to establish a common procedure that all states would use. Instead, each state 

developed its own analysis of these data, considering state-specific situations, to develop its 

reasonable progress requirements. 

Focus on Sulfur Dioxide

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

2000200120022003200420052006200720082009201020112012201320142015201620172018

tons

Florida SO2 Annual Emissions

Compared with Regional Haze SIP Projections

Actual

RH SIP

94
VISTAS, through its modeling contractors, completed a series of sensitivity runs that evaluated 

visibility improvements to pollutant reductions. These runs showed reduction of sulfur dioxide 

(SO2) provided the greatest benefit to visibility improvement throughout the VISTAS domain 

(See Figures 7.4.1 through 7.4.4). The VISTAS modeling contractors also evaluated the 

visibility improvement expected (projected) to occur as a result of the already implemented (onthe-books) regulations by 2018 for each of the Class I areas. Because of the large decreases in 

SO2, primarily from CAIR, most of the Class I areas easily show visibility improvement at a 

faster rate than that of a straight line path to meeting the national goal. Class I areas located 

along the coast show visibility improvement near the straight line path, sometimes marginally 

better or marginally worse. The Florida Class I areas are in this category (see Figures 7.2.4-1 

through 7.2.4-5). Because considerable progress (visibility improvement) was expected by 2018 

with on-the-books regulations, and because SO2 reductions provide the best opportunity for 

additional improvement, the VISTAS states (including Florida) concluded that it was appropriate 

to consider only SO2 reductions in any reasonable progress analysis.

An analysis of the source categories where SO2 emissions are emitted, show that electric 

generating units and other industrial boilers that burn coal and oil represent approximately 95 

percent of the emissions. As a result, VISTAS states, including Florida, decided to limit the 

reasonable progress analysis to these source categories.

Implementation of Reasonable Progress in Florida 

Beginning with the limitation to consider only SO2 from electric generation and other industrial 

sources, Florida considered how to best apply the reasonable progress requirements. Through 

VISTAS, a common analysis was completed to identify the area of influence (AOI) surrounding 

each Class I area (see section 7.5). This analysis considered three variables that each play a 

strong role in determining the impact any source may have on a particular Class I area. The first 

variable is the amount of SO2 emissions; the greater the emissions, the more likely a source may 

impact visibility. The second variable is distance to a Class I area; the farther you get from a 

source, the less the impact (acknowledging that chemistry builds in a delay). And the third 

variable is frequency of winds (residence time) in the direction of the Class I area from the 

source (trajectory analysis). This is a surrogate for the probability that winds will blow toward a 

Class I area. VISTAS contractors provided states a spreadsheet containing emissions, distance, 

and residence time values for each source-Class I area combination. The states then engaged in 

considerable discussion on how to best use this information to identify a list of sources that 

would be considered for a reasonable progress four-factor analysis.

The VISTAS states considered a number of different combinations of these variables as a 

surrogate for visibility impact. Using the notation that Q represents SO2 emissions in tons per 

year, d represents distance in kilometers, and RTmax represents the maximum residence time for 

a source-Class I area, states considered the following metrics, all of which logically relate to 

potential visibility impairment:

Q/d*RTmax, Q*RTmax, Q/d, Q/d**2* RTmax

95
There were very little data or modeling results to provide a definitive analysis identifying the 

best performing surrogate. Most VISTAS states made a judgment that Q/d*RTmax represented 

a reasonable surrogate for visibility impact. The purpose for formulating such a surrogate was to 

pair-down the list of all stationary sources of SO2 to a shorter list representing the sources of 

greatest potential impact to Class I areas. This list would limit the number of sources having to 

undergo a four-factor analysis, while providing the greatest potential benefit to visibility 

improvement. To limit the list, VISTAS considered a unit-specific threshold of 1 percent of the 

Q/d*RTmax relative contribution considering all sources within the area of influence of each 

Class I area to be appropriate for identifying the largest contributors of visibility impairment. 

For reasons of better public clarity and understanding, we chose to develop a reasonable progress 

source selection metric based on Q/d that would be essentially equivalent to the nominal 

VISTAS metric of Q/d*RTMax. The Q/d metric was, in fact, used previously by VISTAS states 

in providing a cutpoint for when the VISTAS contractors would perform CALPUFF BART 

exemption modeling for relatively small sources. The cutpoint used was Q/d = 10, a value that a 

limited amount of evaluation modeling showed a reasonable probability the visibility impacts 

would not be significant (i.e., < 0.5 dv). Since visibility in Class I areas in or near Florida is 

expected to improve at very near the nominal straight line path to the 2064 goal with current 

rules, we chose a cutpoint of Q/d = 50 (five times the nominal significance criteria). This assures 

us that many of the largest sources of SO2 nearest the Class I areas are required to address 

reasonable progress, while smaller sources (not expected to provide significant, cost-effective 

reductions) are excluded. Similarly, we provided some bounds for emissions (Q) and distance 

(d) to affect a reasonable process. First, we exclude small (< 250 tons per year) units, the 

rationale being that any reductions would be very small and likely not very cost effective. 

Second, we do not consider any sources outside of 300 kilometers from a Class I area. This 

limitation is consistent with the bounds used in the BART exemption analysis where only 

sources within this distance from a Class I area were considered. Third, we only consider 

sources which commenced construction or submitted a complete application prior to August 30, 

1999, a date after which permit review requires that visibility specifically be addressed (EPA’s 

Regional Haze Regulations, July 1, 1999). Finally, we use the 2002 emissions for Q, where 

VISTAS used the projected 2018 emissions. This is important in Florida for two reasons. First,

we question some of the IPM projections that convert all of our oil-fired boilers to natural gas. If 

we accepted this premise, emissions of SO2 are presumed to be zero in 2018 and these units 

would not be considered for reasonable progress review. Second, as a general strategy, we don’t 

want to base our selection of sources for four-factor review on IPM’s guess at how the CAIR 

market-based reductions will occur. We believe it is best to start with the known largest sources 

having the potential to impair visibility and make sure that these sources are addressed through 

the reasonable progress process.

The Florida criterion (Q/d>=50) captures for reasonable progress analysis the 1st through 9th, 

15th, 18th, 19th, 27th, and 30th largest SO2 sources (2002) in the state. Of all the SO2 sources 

considered in the VISTAS area of influence around each of the Class I areas, the Florida 

criterion subjects 67.6 percent of the emissions to reasonable progress review. In comparison, 

use of the criteria used by VISTAS (1% contribution using Q/d*RTmax) would select 70.5 

percent of the emissions.

96
TPY

Percent of 

Total

2002 Total Florida SO2 Emissions (within VISTAS 

AOI) 497,867

Selected w/1% criteria 351,167 70.5%

Selected w/ Q/d >50 criteria 336,595 67.6%

Consequently, we believe that the Florida criterion is consistent with the general approach taken 

by the VISTAS states. A complete comparison of the Florida selection criteria with the general 

VISTAS criteria is contained in the tables 7.7.1 – 7.7.4. The disposition of the selected sources 

is provided in table 7.7.5. 

97
98
99
100
Table 7.7.5 Reasonable Progress 

Sources

Plant ID Plant Name Point ID Type

2002 SO2 

EMISSION 

(TON/YR)

2010 SO2 

EMISSION 

(TON/YR)

Existing and 

Projected SO2 

Control 

Equipment Disposition

Currently Shutdown

570040 TECO GANNON 1 coal-fired boiler 5,157 0 Shutdown (2003) Provide documentation

2 coal-fired boiler 4,942 0 Shutdown (2003) Provide documentation

3 coal-fired boiler 5,602 0 Shutdown (2003) Provide documentation

4 coal-fired boiler 5,577 0 Shutdown (2003) Provide documentation

5 coal-fired boiler 8,043 0 Shutdown (2003) Provide documentation

6 coal-fired boiler 16,097 0 Shutdown (2003) Provide documentation

1030011 PE BARTOW 1

oil/gas-fired 

boiler 6,483 0 Shutdown (2009) Provide documentation

2

oil/gas-fired 

boiler 6,149 0 Shutdown (2009) Provide documentation

3

oil/gas-fired 

boiler 11,249 0 Shutdown (2009) Provide documentation

Proposed Shutdown

110036 FPL PORT EVER 3

oil/gas-fired 

boiler 6,409 1,798

To be Shutdown 

(2013) Provide documentation

4

oil/gas-fired 

boiler 6,205 2,003

To be Shutdown 

(2013) Provide documentation

Subject to BART

250003 FPL TURKEY POINT 1

oil/gas-fired 

boiler 4,610 1,595

Subj. to BART -satisfies 

RP

2

oil/gas-fired 

boiler 4,327 1,576

Subj. to BART -satisfies 

RP

170004 PE CRYSTAL RIVER 1 coal-fired boiler 18,998 14,874

Subj. to BART -satisfies 

RP

2 coal-fired boiler 20,728 18,176

Subj. to BART -satisfies 

RP

0310045-B JEA NORTHSIDE 3

oil/gas-fired 

boiler 7,146 912

Subj. to BART -satisfies 

RP

330045 GULF POWER CRIST 7 coal-fired boiler 21,546 2,239

Subj. to BART -satisfies 

RP

810010 FPL MANATEE 1

oil/gas-fired 

boiler 13,930 3,481

Subj. to BART -satisfies 

RP

2

oil/gas-fired 

boiler 15,073 3,998

Subj. to BART -satisfies 

RP

1010017 PE ANCLOTE 1

oil/gas-fired 

boiler 13,879 3,325

Subj. to BART -satisfies 

RP

2

oil/gas-fired 

boiler 13,225 3,740

Subj. to BART -satisfies 

RP

4-Factor Analysis

10006 GRU DEERHAVEN 5 coal-fired boiler 6,969 3,161 Dry Scrubber No longer applicable

170004 PE CRYSTAL RIVER 3 coal-fired boiler 26,436 1,660 Wet Scrubber 4-factor analysis

4 coal-fired boiler 24,635 4,730 Wet Scrubber 4-factor analysis

0310045-A JEA ST JOHNS RIVER 16 coal-fired boiler 11,076 4,786 Wet Scrubber 4-factor analysis

17 coal-fired boiler 10,185 4,616 Wet Scrubber 4-factor analysis

0310045-B JEA NORTHSIDE 27 coal-fired boiler 5,090 1,584 Dry Scrubber No longer applicable

530021 FL CRUSHED STONE 18 coal-fired boiler 2,906 2,197 Dry Scrubber No longer applicable

1050004 LAKELAND MCINTOSH 6 coal-fired boiler 6,994 4,198 Wet Scrubber 4-factor analysis

1070025 SEMINOLE ELECTRIC 1 coal-fired boiler 10,912 8,483 Wet Scrubber 4-factor analysis

2 coal-fired boiler 12,775 8,477 Wet Scrubber 4-factor analysis

Non-EGU Boiler MACT

890003 Rock Tenn 15 coal-fired boiler 3,242 3,344 4-factor analysis

336,595 104,953

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Case-by-Case Reasonable Progress Analyses

A case-by-case reasonable progress analysis is required for all sources meeting the Florida 

criterion (Q/d > 50). In some cases, described below, sources have taken federally enforceable 

permit limitations that limit the source’s Q/d to less than 50. These sources are thus no longer 

subject to the reasonable progress requirements. In addition, a number of sources are subject to 

both the reasonable progress requirements and the Best Available Retrofit Technology (BART) 

requirements. For these sources, the BART determination will satisfy their reasonable progress 

requirements and no further reasonable progress review is necessary. For the remaining sources 

subject to the reasonable progress requirements, DEP has completed a review and determined 

appropriate SO2 emission controls considering the following four-factors:

• the costs of compliance

• the time necessary for compliance

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

• the remaining useful life of any potentially affected sources.

Applicability of Florida Crushed Stone, JEA Northside, and GRU Deerhaven

Three units have taken federally enforceable permit conditions that limit SO2 emissions such that 

they are no longer applicable to reasonable progress review.

Florida Crushed Stone-Central Power and Lime

Central Power and Lime is a coal-fired power boiler co-located with the Florida Crushed Stone 

(now CEMEX) cement plant. This unit has received a construction permit to convert the coalfired boiler to a biomass boiler, and is prohibited from burning coal once it makes the 

appropriate changes to the boiler to burn biomass. Ultra low sulfur distillate fuel oil will be used 

for start-up, shutdown, and bed stabilization. The commitments to execute these changes are 

contained in the federally enforceable construction permit, the essential parts of which are 

included in Exhibit 2. The result of these changes is that the source is no longer subject to the 

reasonable progress review. The maximum allowed SO2 emissions are now set at 591.3 tons per 

year. The distance to the nearest Class I area (Chassahowitzka NWA) is 22.4 kilometers. This 

results in a Q/d of 26.4, well below the applicability criterion of Q/d = 50 or greater. Thus, no 

further analysis of this source is required.

JEA Northside

Circulating Fluidized Bed Boiler 1 (emissions unit 27) is a coal, coal coated with latex, 

petroleum coke, and landfill gas fired circulating fluidized bed (CFB) boiler rated at 298 MW. 

Sulfur dioxide emissions are controlled by the injection of limestone into the CFB boiler beds. 

Residual SO2 emissions are further controlled by the use of an add-on spray dryer absorber 

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system. The federally enforceable SO2 emission limitation is 0.2 lb/MMBtu, 24-hour average, 

and 0.15 lb/MMBtu, 30-day rolling average. Annual emissions are thus limited to 1,816 tons 

SO2 per year.

Since 2002, the year for which data is used to determine applicability for reasonable progress 

review, permit conditions have been imposed on this unit that limit the annual emissions of SO2. 

In 2009, JEA requested and received the permit limitations listed above. The new, federally

enforceable limits result in the source no longer being subject to the reasonable progress review. 

The JEA Northside source is located 69.3 kilometers from the closest Class I area (Okefenokee 

NWA). With maximum allowable SO2 emissions of 1,816 tons, the applicability metric Q/d

equals 26.2, which is less than the Q/d= 50 or greater criterion. Thus, no further analysis of this 

source is required.

GRU Deerhaven

The coal-fired boiler number 2 (emissions unit 5) is a 251 MW (nominal) fossil fuel fired steam 

generator. Sulfur dioxide emissions are controlled with the use of a circulating dry scrubber. The 

scrubber is designed to achieve a target outlet SO2 emission rate of 0.12 lb/MMBtu. This 

scrubber came on-line in 2009, providing significant reductions in SO2. The basis for this unit to 

be subject to the reasonable progress four-factor review is that its Q/d ratio in 2002 was greater 

than 50 (6,969 tons/112.2 km = 62.12). Because of the addition of the scrubber, GRU has 

requested a federally enforceable permit condition that limits SO2 emissions to 5,500 tons per 

year, resulting in a maximum Q/d value of 49.0. A copy of the essential parts of the construction 

permit incorporating the lower limit is included in Exhibit 2. Thus, no further analysis of this 

source is required. 

Shutdowns of Reasonable Progress Sources

Nine units subject to reasonable progress review are shutdown. This includes six units at the 

Tampa Electric Gannon facility, shut down in 2003, and three units at the Progress Energy 

Bartow facility, shut down in 2009. The permits requiring the shutdown of these sources are 

included in Exhibit 2. 

Two additional units subject to the reasonable progress review will soon be shut down. These 

are units 3 and 4 at the Florida Power and Light Port Everglades facility (to be shut down in 

2013). A copy of DEP’s intent to issue a permit is included in Exhibit 2.

Four-Factor Reasonable Progress Determinations

Progress Energy Florida (PEF) Crystal River Units 3 and 4

Emissions units 3 and 4 are fossil fuel-fired electric utility steam generators, each rated at 760 

MW. Sulfur dioxide (SO2) emissions are controlled with wet flue gas desulfurization (FGD) 

systems, designed to reduce emissions by 97%. The federally enforceable permit condition is set 

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at 0.27 lb/MMBtu, based on a 30-day rolling average. The FGD systems came on line in 2009 

(unit 4) and 2010 (unit 3). 

Wet limestone FGD systems are considered by DEP to be the top level SO2 emissions control 

system for coal-fired boilers. The source considered the potential for additional SO2 reductions 

through the use of lower sulfur western coal but found that it would not be cost-effective.

Costs of Compliance – The source is already incurring the cost of the new FGD systems. While 

lower sulfur coal is potentially available from the Powder River Basin (PRB), PRB coal is subbituminous coal that has unique combustion characteristics that would require additional 

operational modifications to ensure continued safe and reliable unit performance. Moreover, the 

transportation of this coal from Wyoming to Florida would not only be cost prohibitive but also 

produce considerable secondary environmental impacts from unit trains travelling such a 

distance. Installing additional add-on controls for PRB firing would take, at a minimum, several 

years or longer due to PEF’s need to continue operating the units as base-load to supply reliable 

electric power to its customers.

Time Necessary for Compliance – The top level controls are already installed and are operating. 

No additional time for compliance is necessary.

Energy and Non Air Quality Environmental Impacts of Compliance – The top level controls are 

already installed, so no additional energy or non air quality environmental impacts would occur. 

The use of lower sulfur PRB coal could potentially include increased water use, additional solid 

wastes, secondary emissions caused by fuel transportation, and additional energy usage for 

control.

Remaining Useful Life – The source anticipates that these units will continue to operate for 

another 28 years.

In summary, DEP has determined that the existing FGD SO2 control systems meet the reasonable 

progress goals of the state’s regional haze plan for this planning period.

Seminole Electric Cooperative (SECI)

Seminole Generating Station (SGS) Units 1 and 2 are solid fuel, dry-bottom, wall-fired units each 

with a maximum heat input of 7,172 million British thermal units per hour (MMBtu/hr) generating 

736 MW each. Units 1 and 2 are currently authorized to burn coal as the primary fuel but are also 

authorized to burn a blend of coal and petroleum coke up to a maximum of 30 percent by weight 

petroleum coke. The maximum sulfur content of petroleum coke may not exceed 7.0 percent by 

weight on a dry basis. This sulfur content limit for petroleum coke is 2.3 times the design coal 

nominal sulfur content of 3.0 percent by weight. Units 1 and 2 are each equipped with SO2

continuous emissions monitoring systems as required by the Acid Rain Program.

In addition to electrostatic precipitators for control of particulate matter (PM), low-NOx burners, and 

selective catalytic reduction (SCR) for NOx control and an alkali injection system to control 

emissions of sulfuric acid mist, Units 1 and 2 are each equipped with wet FGD scrubbers to control 

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SO2 emissions. The original FGD controls (1984) were upgraded in 2010 to comply with CAIR and 

other air regulatory initiatives (e.g., the Clean Air Mercury Rule). Improvements to the FGD systems 

included scrubber module modifications, upgrades to the module's mist eliminator wash system, 

expansion of the oxidation air system, and upgrades to the existing sparger rings in the absorber 

recycle tanks. Following these upgrades, the allowable SO2emissions rate for Units 1 and 2 was 

reduced from 1.2 to 0.67 1b/MMBtu.

Wet FGD technology provides the highest SO2 removal efficiencies for coal-fired boilers. The SGS 

Unit 1 and 2 FGD control systems currently achieve approximately 92-percent SO2 removal. SECI 

proposes to make additional changes to Units 1 and 2 to achieve a minimum SO2 removal efficiency 

of 95 percent or, alternatively, an equivalent SO2 emissions rate of no more than 0.25 lb/MMBtu on a 

30-day rolling average basis for both units.

SECI is presently evaluating available options to achieve the proposed SO2 removal efficiency or 

emissions limit including, but not limited to, further modifications to the internal components of the 

FGD scrubbers, increase in limestone recirculation rates, and increased used of dibasic acid. SECI 

will complete its evaluation and provide DEP with the details of the selected option by March 1, 

2013. The amount of time required to implement the selected option and achieve the proposed SO2

emissions limits will depend on the option's design and if construction is required. Within 1 to 3 

years following option selection (i.e., no later than March 1, 2016), SECI will achieve either the 

proposed SO2 emissions limit or the removal efficiency requirements.

In general, wet limestone FGD systems are the top level SO2 control device for coal-fired utility 

boilers. To assure that these FGD systems remain operating at high performance levels, the 

company has agreed to upgrade the systems and take a federally enforceable permit condition to 

achieve 95 percent SO2 removal efficiency. This will result in an emissions rate of 0.25 

lb/MMBtu or better. In addition, the company is removing the option to burn petroleum coke. 

DEP has determined that the existing FGD controls, with the upgrades, meet the reasonable 

progress goals of the state’s regional haze plan.

Costs of Compliance – SGS units 1 and 2 both have the top level control device for coal-fired 

utility boilers. As such, no lower level control option was reviewed. However, certain upgrades 

are available to improve the FGD system to achieve 95 percent removal efficiency. While not 

quantified, the company has agreed to incur these costs.

Time Necessary for Compliance – The company has estimated that compliance with the 95 

percent SO2 removal efficiency will be achieved by March 2016.

Energy and Non Air Quality Environmental Impacts of Compliance – There are no additional 

energy and non air quality environmental impacts since the FGD system is already in place and 

operating.

Remaining Useful Life – These units are anticipated to continue operation indefinitely.

In summary, DEP has determined that the existing FGD SO2 control systems, with the described 

upgrades, meet the reasonable progress goals of the state’s regional haze plan for this planning 

105
period. The applicable sections of the federally enforceable permit conditions are located in 

Exhibit 2.

Lakeland McIntosh

Boiler Unit 3 (Emissions Unit 6) is a nominal 364 MW fossil fuel-fired steam generator that fires 

coal, coal and up to 20% petroleum coke (petcoke), low sulfur fuel oil (< 0.5% sulfur by weight), 

high sulfur fuel oil (> 0.5% sulfur by weight), and natural gas or propane. Sulfur dioxide (SO2)

emissions are controlled by a flue gas desulfurization (FGD) system. The maximum heat input 

rate is 3,640 million British thermal units per hour (MMBtu/hr). The federally enforceable SO2

emission limitation is 1.2 lb/MMBtu when burning only coal. When burning blends of 

petroleum coke the limit is 0.718 lb/MMBtu.

Unit 3 is currently equipped with a wet limestone FGD system to control SO2 emissions. Unit 3 

is subject to NSPS Subpart D, which has no minimum SO2 percent reduction requirements. 

However, the current Title V permit requires a 65 percent reduction in SO2 when the emissions 

are less than 0.75 lb/MMBtu and a 90 percent reduction when emissions are greater than or equal 

to 0.75 lb/MMBtu. Based on the actual SO2 emissions reported in 2002, the FGD system 

reduced SO2 emissions by 81 percent. The scrubber is of a tray tower type consisting of two 

absorber modules. Each module provides approximately 55 percent capacity of total unit output.

In general, wet limestone FGD systems are the top level control device for coal-fired utility 

boilers. However, the source considered several changes or upgrades to the FGD system to 

additionally reduce SO2 emissions. These included lower sulfur fuel, FGD modifications, and 

complete replacement of the FGD system. 

Costs of Compliance -- Among the authorized fuels for Unit 3, petcoke has the highest sulfur 

content, an average of 3.9 percent by weight. Bituminous coal, with an average of 1.8 percent 

sulfur, is the fuel with next highest sulfur content. Lakeland Electric is authorized to burn up to 

20 percent petcoke by weight with bituminous coal and, as a result, the average sulfur content of 

the combined fuel (coal and petcoke) can be as high as 2.22 percent (80 percent coal with 1.8 

percent sulfur and 20 percent petcoke with 3.9 percent sulfur) due to the high sulfur content of 

petcoke. Since coal is the most used fuel for Unit 3, petcoke (20 percent of coal) can contribute 

significantly to the total SO2 emissions from the unit. Lakeland Electric believes that curtailing 

petcoke firing is the most cost effective solution to reduce the sulfur content of fuel burned in 

Unit 3. It is estimated that 17 lb of SO2 would be reduced for every ton of coal burned instead of 

combined coal and petcoke (difference between 2.22 percent sulfur and 1.8 percent sulfur in 1 

ton of fuel). Costs were not provided by Lakeland Electric, but DEP assumes the cost of 

eliminating petcoke as an authorized fuel to be minimal.

The existing FGD system is a 30-year old Babcock & Wilcox design and is not designed to 

achieve 95 to 98 percent SO2 removal without significant major upgrades in the existing 

equipment. Based on very preliminary assessment, the removal efficiency of the FGD system 

may be increased to a maximum of 95 percent with equipment improvements involving the 

existing FGD absorbers, slurry systems, additive systems, reheat systems, and stack(s), which 

may cost as much as $25 million (Lakeland Electric estimate). A detailed engineering study will 

106
be needed to properly assess the cost of such an improvement. For example, a new landfill 

might be required since the solid waste disposal rate will increase with additional SO2

absorption. If dibasic acid is used in the scrubber to achieve higher removal efficiency, the issue 

of specific waste water treatment procedure will need to be addressed since the waste water will 

have dibasic acid in it. This unit emitted 6,994 tons of SO2 in 2002. Assuming the existing FGD 

provided 81% control, then an additional 14% control would reduce SO2 emissions by another 

5,153 tons. This would result in a cost effectiveness of approximately $4,852/ton (or greater) of 

reduction. DEP does not consider this a reasonable cost and therefore not necessary for 

achieving the reasonable progress goals for this planning period.

An additional/replacement wet-FGD system designed to achieve 98 percent SO2 removal would 

achieve the highest level of SO2 control while Unit 3 remains operating and available to provide 

electric power to its customers. To develop a cost of a replacement wet-FGD system, 

information developed for the recent CSAPR was used. Capital, fixed operation and 

maintenance (O&M), and variable O&M are available on a dollar per kilowatt basis as part of 

EPA’s Integrated Planning Model (IPM) Base Case v. 4.10 (September 1, 2010) for Transport 

Rule; Documentation; Chapter 5, Emission Control Technologies. These costs models were 

developed by engineering contractors such as Sargent & Lundy for the wet-FGD cost model as 

well as other control technologies. Additionally, cost factors and methodology from the EPA 

Cost Control Manual were used to develop annualized costs not included in the EPA IPM cost 

model. The annualized cost was based on the amount of historical operation in baseline year of 

2002 and is estimated to be about $36.3 million. The compliance target was an emission rate of 

0.063 lb/MMBtu, which is equivalent to 98 percent SO2 removal based on 2002 operation, the 

basis of the DEP baseline emissions. The cost effectiveness of about $5,804 per ton of SO2

removed was estimated using a reduction from the 2002 baseline year and an emission rate of 

0.063 lb/MMBtu. DEP does not consider this a reasonable cost and therefore not necessary for 

achieving the reasonable progress goals for this planning period.

Time Necessary for Compliance – The FGD system is already operating for this unit and no 

additional time is necessary for its operation. The options for upgrading the existing FGD and 

for replacing the existing FGD would both take three years or longer to complete. The option of 

reducing the potential fuel sulfur content could be completed immediately. 

Energy and Non Air Quality Environmental Impacts of Compliance -- The energy and non-air 

quality impacts associated with an additional/replacement wet-FGD system include additional 

limestone usage, disposal of FGD byproducts, increased water use, and additional energy. 

Wet-FGD requires about 3 percent of the energy of the unit for auxiliary power and 

backpressure. This is about 1.09 MW per ton of SO2 removed. The additional energy required 

to meet 0.063 lb/MMBtu with the reduction estimated using the 2002 baseline emissions is 6,822 

megawatt-hours (MWh). For each ton of SO2 removed, about 1.05 tons of limestone are 

required due to the reactivity and losses in the system. Approximately 2.34 tons of FGD 

byproducts are produced per ton of SO2 removed. For the estimated SO2 removed based on 2002 

emissions, an additional 6,572 tons of limestone would be required and 14,646 tons of 

byproducts generated. Additional process water would also be required and is estimated to be 50 

gallons per ton of SO2 removed. Based on the SO2 removed from the 2002 emissions, about 

107
312,953 gallons of additional water would be required. These additional impacts do not support

an additional/replacement wet-FGD system.

Remaining Useful Life – These units are anticipated to continue operation indefinitely.

In summary, DEP has determined that the existing FGD SO2 control system with the elimination 

of petcoke as an authorized fuel, meet the reasonable progress goals of the state’s regional haze 

plan for this planning period. A copy of the federally enforceable permit that eliminates petcoke 

as an authorized fuel is included in Exhibit 2.

JEA St. Johns River Power Park (SJRPP)

SJRPP Boilers 1 and 2 (Emissions Units 16 and 17) are fossil fuel-fired steam generators rated at 

679 MW each. The maximum heat input rate is 6,144 million British thermal units per hour 

(MMBtu/hr) per boiler. The boilers are fired with pulverized coal, a coal blend with a maximum 

of 30 percent petroleum coke (petcoke) by weight, natural gas, new No. 2 distillate fuel oil 

(startup and low-load operation), and “on specification” used oil. The maximum coal sulfur 

content shall not exceed 4.0 percent, by weight. The maximum sulfur content of the petcokecoal blend shall not exceed 4.0 percent, by weight. The maximum sulfur content of the No. 2 

fuel oil is 0.76 percent, by weight. The federally-enforceable permit conditions limit SO2

emissions to 1.2 lb/MMBtu (max two-hour average), and 0.76 lb/MMBtu (90% reduction of the 

potential combustion concentration); 30-day rolling average, when burning coal. 

Boilers 1 and 2 are currently equipped with wet limestone flue gas desulfurization (FGD)

systems to control SO2 emissions. The FGD systems are capable of up to 90 percent reduction in 

SO2 emissions with a maximum SO2 emission rate of 0.76 lb/MMBtu using the worst-case fuel. 

The scrubbers are of a tray tower type consisting of three absorber modules. Each module 

provides a 50-percent capacity of total boiler output. Additional equipment/processes supporting 

the scrubber system include limestone storage and handling, limestone slurry preparation system, 

slurry storage and transfer system, FGD blowdown, and gypsum dewatering, transfer, and 

storage.

In general, wet limestone FGD systems are the top level control device for coal-fired utility 

boilers. However, the source considered several changes or upgrades to the FGD system to 

additionally reduce SO2 emissions. These included lower sulfur fuel, FGD modifications, and 

complete replacement of the FGD system.

Costs of Compliance -- Increasing the existing SO2 removal efficiency of the FGD system is 

possible with equipment improvements involving the existing FGD absorbers, slurry systems, 

additive systems, reheat systems, and stack(s). The capital costs for the potential improvements 

are likely in the range of $10 million to $30 million per boiler. In conjunction with the 

equipment improvements, operating costs for increased SO2 removal will include fixed and 

variable operating costs from about $3 million per year per boiler to over $4.5 million per year 

per boiler. Depending upon the options selected, up to an additional 5 percent SO2 removal is 

possible. An engineering study has commenced that will include an evaluation of the sulfur 

108
content for the various range of fuels authorized for SJRPP and refine these very preliminary 

cost estimates. While these improvements look promising, DEP has determined that it is 

premature to rely on these improvements for reasonable progress.

To achieve greater SO2 reductions from the current equipment would require either add-on SO2

controls after the existing equipment or a replacement of the current FGD system with systems

designed to achieve 95 to 98 percent or greater SO2 removal. The existing FGD systems are not 

designed to achieve 95 to 98 percent SO2 removal without significant major upgrades in the 

existing equipment (e.g., absorber redesign to increase liquid to air ratio, construction of new wet 

stack, etc.). As a result, an additional/replacement wet-FGD system designed to achieve a total 

removal of 98 percent SO2 removal would achieve the highest level of SO2 control while Boilers

1 and 2 remain operating and available to provide electric power to its customers.

Wet-FGD has been a widely available control technology for SO2 removal over the last 30 years. 

To develop a cost of a replacement wet-FGD, information developed for the recent CSAPR was 

used. Capital, fixed operation and maintenance (O&M), and variable O&M are available on a 

dollar per kilowatt basis as part of EPA’s Integrated Planning Model (IPM) Base Case v. 4.10 

(September 1, 2010) for Transport Rule; Documentation; Chapter 5. Emission Control 

Technologies. These costs models were developed by engineering contractors such as Sargent & 

Lundy for the wet-FGD cost model as well as other control technologies. Additionally, cost 

factors from the EPA Cost Control Manual were used to costs not included in the EPA IPM cost 

model. EPA’s “Guidance for Setting Reasonable Progress Goals Under the Regional Haze 

Program” suggests that costs should be evaluated and cost estimates should be based on EPA’s 

Air Pollution Control Cost Manual. Annualized costs were developed using the methodology in 

the EPA Cost Control Manual.

Estimated costs and cost effectiveness are presented for an additional/replacement wet-FGD for 

either SJRPP Boiler 1 or 2 to achieve an SO2 removal of 98 percent, the highest level of control. 

Boilers 1 and 2 are identically designed units in close proximity that have a similar influence on 

visibility to Class I Areas. The annualized cost was based on the amount of historical operation 

in baseline year of 2002 and is estimated to be about $59.7 million. The cost effectiveness was 

determined against one half of the 2002 SO2 emissions since both Boilers 1 and 2 are identically 

designed. The compliance target was an emission rate of 0.053 lb/MMBtu, which is equivalent 

to 98 percent SO2 removal based on 2002 operation, the basis of the DEP baseline emissions. 

The cost effectiveness of about $6,383 per ton of SO2 removed was estimated using a reduction 

from the 2002 baseline year and an emission rate of 0.053 lb/MMBtu. To contrast the cost 

effectiveness from this baseline year, the cost effectiveness using the emissions for the latest 

year, 2011, was estimated. The cost effectiveness from the SO2 emissions in 2011 was estimated 

to be $11,921 per ton of SO2 removed. It should be recognized that the estimated costs are 

neither specific to SJRPP nor the layout of Boiler 1 nor 2. It may not be possible to install add-on 

SO2 equipment given the spatial constraints at the site. Notwithstanding, these cost effectiveness 

numbers are extremely high and considered unreasonable for SJRPP Boilers 1 and 2, which 

already have wet-FGD systems. DEP does not consider this a reasonable cost and therefore not 

necessary for achieving the reasonable progress goals for this planning period.

109
Time Necessary for Compliance – The existing FGD systems are already operating for these 

boilers and no additional time is necessary for their operation. The option for replacing the 

existing FGD systems would take three years or longer to complete. The option of making 

improvements to the existing FGD systems, including reducing the potential fuel sulfur content, 

could be implemented in a shorter time frame after JEA completes their evaluation.

Energy and Non Air Quality Environmental Impacts of Compliance -- The energy and non-air 

quality impacts associated with an additional/replacement wet-FGD system includes additional 

limestone usage, disposal of FGD byproducts, increased water use, and additional energy. WetFGD requires about 3 percent of the energy of the unit for auxiliary power and backpressure. 

This is about 1.09 MW per ton of SO2 removed. The additional energy required to meet 98 

percent SO2 removal from the 2002 baseline emissions is 10,189 MWh. 

For each ton of SO2 removed, about 1.05 tons of limestone is required due to the reactivity and 

losses in the system. Approximately 2.34 tons of FGD byproducts are produced per ton of SO2

removed. For the estimated SO2 removed based on 2002 emissions, an additional 9,815 tons of 

limestone would be required and 21,874 tons of byproducts generated. Additional process water 

would also be required and is estimated to be 50 gallons per ton of SO2 removed. Based on the 

SO2 removed from the 2002 emissions, about 467,389 gallons of additional water would be 

required. These additional impacts do not support an additional/replacement wet-FGD system. 

Remaining Useful Life – These units are anticipated to continue operation for at least another 20 

years.

In summary, DEP has determined that the existing FGD SO2 control systems meet the reasonable 

progress goals of the state’s regional haze plan. DEP recognizes that JEA is in the process of 

evaluating additional measures to reduce SO2 emissions in response to other federal regulations, 

but these measures are not necessary for the purpose of meeting the reasonable progress goals 

during the first planning period. 

Rock Tenn 

The No. 7 Power Boiler (Emissions Unit 15) is regulated under NSPS - 40 CFR 60, Subpart D, 

Standards of Performance for Fossil-Fuel-Fired Steam Generators for Which Construction Is 

Commenced After August 17, 1971. This emissions unit is fired primarily with coal, Nos. 2 and 

6 Fuel Oil, and natural gas may be fired during startup, shutdown, and malfunction, and at other 

times as needed for flame stabilization and to maintain steam production. The operation rate 

shall not exceed 1,021 MMBtu/hr (based on a 24-hour average). Sulfur dioxide (SO2) emissions 

shall not exceed 1.2 lb/MMBTU of heat input, 1,225.20 lb/hr and 5,366.38 TPY, derived from 

solid fossil fuel or solid fossil fuel and wood residue. SO2 emissions shall not exceed 0.8 

lb/MMBTU of heat input derived from liquid fossil fuel or liquid fossil fuel and wood residue. 

DEP recognizes that this unit is currently subject to the Industrial Boiler MACT rule. Any 

source subject to MACT standards must meet a level of control that is as stringent as the best 12 

percent of sources in the industry. While the MACT standard is for acid gases, rather than for 

SO2, DEP concludes that the SO2 emissions reductions expected to result from measures taken to 

110
comply with the MACT standards will meet the reasonable progress goals of the state’s regional 

haze plan. 

A streamlined control analysis was conducted by reviewing the supporting documentation 

regarding the emissions controls projected necessary to comply with the MACT standard. The 

control options potentially available include Dry Sorbent Injection/Fabric Filter (DIFF), wet 

scrubbing, or conversion to natural gas to meet the MACT standard. The supporting technical 

information document for the industrial boiler MACT standard concluded that the least cost 

option for this unit would be DIFF, and projected the need to install DIFF with a total capital 

control cost of $35,244,447, and a total annual control cost of $10,084,579. SO2 emissions are 

projected to be reduced by 68.6 percent. A wet scrubber, which was not projected to be needed 

to meet the MACT standard for this unit, could reduce emissions by 95 percent, but at a 

significantly higher cost. 

SO2 emissions from this unit in 2002 ( the year for which Florida used to determine applicability 

to the reasonable progress review) was 3,242 tons. This leads to a Q/d of 50.2, fractionally over 

the applicability threshold of 50. Based on the expected reduction of 68.6 percent from this 

baseline, the unit would reduce actual emissions by 2,224 tons per year. The resulting estimated 

cost effectiveness of DIFF for SO2 is over $4,500 per ton of SO2 removed. Further, installation 

of this control technology would bring the unit’s Q/d to well below the threshold of 50. While a 

wet scrubber would result in greater emissions reduction, its annual costs are anticipated to be 

substantially higher and less cost effective. 

In summary, DEP finds that further analysis would not identify an emissions control more 

stringent than what the MACT standard will require. DEP will review the status of Rock Tenn’s 

compliance with the MACT standard as part of the continuing periodic review process of the 

Regional Haze Rule. 

7.8 Best Available Retrofit Technology (BART) for Individual Sources 

Section 169A of the CAA directs states to assess certain large, older emission sources for 

additional controls in order to address visibility impacts. States are directed to conduct BART 

determinations for such sources in specific source categories, and which contribute to visibility 

impairment in Class I areas. The 1999 regional haze rule includes the BART requirement, and 

directs states to include BART in their regional haze SIPs. On July 6, 2005, EPA published a 

revised final rule, including Appendix Y to 40 CFR Part 51, the Guidelines for BART 

Determinations Under the Regional Haze Rule (hereinafter referred to as the “BART 

Guidelines”) that provides direction to states on determining which of these sources should be 

subject to BART, and how to determine BART for each source.

A BART-eligible source is one which has the potential to emit 250 tons or more of a visibilityimpairing air pollutant, was put in place between August 7, 1962 and August 7, 1977, and whose 

operations fall within one or more of 26 specifically listed source categories. Under the CAA, 

BART is required for any BART-eligible source that a state determines ‘‘emits any air pollutant 

111
which may reasonably be anticipated to cause or contribute to any impairment of visibility in any 

such area.’’ 

For those sources subject to BART, Section 169A(g)(7) of the CAA requires that states must 

consider the following factors in making BART determinations: (1) the costs of compliance, (2) 

the energy and non-air quality environmental impacts of compliance, (3) any existing pollution 

control technology in use at the source, (4) the remaining useful life of the source, and (5) the 

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

of such technology. 

7.8.1 BART-Eligible Sources in Florida

The following is a list of facilities with BART-eligible sources in Florida. DEP determined the 

list using information from the ARMS database, and modified through surveys sent to potential 

eligible sources and through public workshops held to develop the state BART rule.

112
FACILITY 

ID OWNER COMPANY NAME SITE NAME

1 0010006 CITY OF GAINESVILLE, GRU DEERHAVEN GENERATING STATION

2 0050009 ROCKTENN (STONE CONTAINER 

CORPORATION) PANAMA CITY MILL

3 0050014 GULF POWER COMPANY LANSING SMITH PLANT

4 0090006 FLORIDA POWER & LIGHT (PCC) CAPE CANAVERAL POWER PLANT

5 0090196 RELIANT ENERGY INDIAN RIVER, L.L.C. INDIAN RIVER PLANT - RELIANT

6 0110036 FLORIDA POWER & LIGHT (PPE) PORT EVERGLADES POWER PLANT

7 0170004 FLORIDA POWER CORPORATION CRYSTAL RIVER POWER PLANT

8 0250003 FLORIDA POWER & LIGHT (PTF) TURKEY POINT POWER PLANT

9 0310045 JEA NORTHSIDE/SJRPP

10 0310071 IFF CHEMICAL HOLDINGS, INC. IFF CHEMICAL HOLDINGS, INC.

11 0330040 SOLUTIA INC. SOLUTIA INC.

12 0330042 INTERNATIONAL PAPER COMPANY PENSACOLA MILL

13 0330045 GULF POWER COMPANY CRIST ELECTRIC GENERATING PLANT

14 0470002 WHITE SPRINGS AGRICULTURAL 

CHEMICALS,INC WHITE SPRS AG CHEM-SR/SC CMPLX

15 0510003 U.S. SUGAR CORP. CLEWISTON MILL CLEWISTON MILL AND REFINERY

16 0530010 CEMEX CEMEX

17 0570005 CF INDUSTRIES, INC., PLANT CITY 

PHOS PLANT CITY PHOSP

18 0570008 MOSAIC CARGILL--RIVERVIEW FACILITY

19 0570024 IMC PHOSPHATES COMPANY PORT SUTTON TERMINAL

20 0570039 TAMPA ELECTRIC COMPANY BIG BEND STATION

21 0610029 CITY OF VERO BEACH CITY OF VERO BEACH MUNICIPAL 

UTILITIES

22 0730003 CITY OF TALLAHASSEE ARVAH B.HOPKINS GENERATING STATION

23 0810010 FLORIDA POWER & LIGHT (PMT) MANATEE POWER PLANT

24 0850001 FLORIDA POWER & LIGHT (PMR) FPL / MARTIN POWER PLANT

25 0890003 ROCKTENN (SMURFIT STONE 

CORPORATION (US))

JSC-FERNANDINA BEACH PAPERBOARD 

MILL

26 0990016 ATLANTIC SUGAR ASSOCIATION ATLANTIC SUGAR MILL

27 0990019 OSCEOLA FARMS OSCEOLA FARMS

28 0990026 SUGAR CANE GROWERS CO-OP SUGAR CANE GROWERS CO-OP

29 0990042 FLORIDA POWER & LIGHT (PRV) RIVIERA POWER PLANT

30 0990045 LAKE WORTH UTIL. TOM G. SMITH PLANT

31 0990061 U.S.SUGAR CORP. BRYANT MILL U.S. SUGAR CORP. BRYANT MILL

32 1010017 FLORIDA POWER CORP. ANCLOTE POWER PLANT

33 1030011 FLORIDA POWER CORPORATION FPC-BARTOW PLANT

34 1050003 LAKELAND ELECTRIC CHARLES LARSEN MEMORIAL POWER 

PLANT

35 1050004 LAKELAND ELECTRIC C.D. MCINTOSH, JR. POWER PLANT

36 1050046 MOSAIC - BARTOW BARTOW

37 1050053 MOSAIC - GREEN BAY GREEN BAY PLANT

38 1050055 IMC PHOSPHATES COMPANY SOUTH PIERCE

39 1050059 MOSAIC - NEW WALES NEW WALES

40 1070005 GEORGIA-PACIFIC CORP. PULP/PAPER 

MILL PALATKA

41 1070014 FLORIDA POWER & LIGHT (PPN) PUTNAM POWER PLANT

42 1110003 FT PIERCE UTILITIES AUTHORITY H D KING PWR PLNT

43 1130003 STERLING FIBERS, INC. STERLING FIBERS, INC.

44 1130005 EXXONMOBIL PRODUCTION COMPANY ST REGIS TREATING FAC AND JAY GAS 

PLANT

45 1230001 BUCKEYE FLORIDA, LIMITED 

PARTNERSHIP PERRY

46 1290001 TALLAHASSEE CITY PURDOM 

GENERATING STA. PURDOM GENERATING STATI

113
The BART-eligible sources were identified using the methodology in the BART Guidelines. 

• One or more emissions units at the facility fit within one of the 26 categories listed in the 

BART Guidelines;

• The emission unit(s) were in existence on August 7, 1977 and began operation at some 

point on or after August 7, 1962; and 

• The limited potential emissions from all emission units identified in the previous two 

bullets were greater than 250 tons per year of any of these visibility-impairing pollutants: 

SO2, NOx, and PM10.

The BART Guidelines recommend addressing these visibility-impairing pollutants: SO2, NOx, 

and particulate matter, and suggest that states use their best judgment in determining whether to 

address VOC or ammonia emissions. Florida addressed SO2 and NOx, and used particulate 

matter less than 10 microns in diameter (PM10) as an indicator for particulate matter to identify 

BART-eligible units, as the BART Guidelines recommend. As discussed in detail in Appendix 

L, VISTAS modeling demonstrated that VOCs and ammonia from point sources are not 

significant for visibility impairment. For this reason Florida did not evaluate emissions of VOCs 

and ammonia in BART determinations.

7.8.2 Florida’s BART Rule

In support of the federal regional haze rule for the Best Available Retrofit Technology 

requirement, Florida developed state Rule 62-296.340, Florida Administrative Code. In this rule, 

DEP has adopted by reference the core of the federal rule, and included additional rule language 

to make certain decisions where the federal rule leaves options to the state. The rule also 

requires that BART-eligible sources submit a state construction permit application. In this 

application, the source must complete the BART analysis as required in the federal rule and 

recommend the BART controls or emission limitations consistent with that process. The state 

then makes the final BART determination and issues a construction permit making any changes 

federally enforceable.

The optional components or decisions in the state rule include the exclusion of volatile organic 

compounds (VOC) and ammonia from BART review, accepting BART equal to CAIR for 

electric generating units (thereby limiting BART for EGU’s to PM only), providing for de

minimis levels below which BART would not apply for that pollutant, and providing specific 

criteria for exemption from BART. A copy of the Florida BART rule is included in Exhibit 1.

Since the development of the Florida BART rule, EPA promulgated the Cross State Air Pollution 

Rule (CSAPR) as a successor to the CAIR program. The applicability of Florida to CSAPR 

would have changed relative to the CAIR rule. Under CSAPR, Florida would be subject only to 

the ozone season NOx emissions cap. The annual emission caps associated with SO2 and NOx 

would no longer apply in Florida. Thus, whereas CAIR can satisfy the BART requirements for 

these pollutants as originally relied upon in this SIP, CSAPR cannot. However, on August 21, 

2012, the D.C. Circuit Court vacated CSAPR and ordered EPA to continue implementing CAIR 

until a valid replacement could be implemented. Given the uncertainty over CAIR’s eventual 

replacement, Florida is not requesting EPA approval of Rule 62-296.340, F.A.C., to the extent it 

114
allows sources to rely on CAIR to comply with BART. However, it should be noted that CAIR 

will continue to be implemented – and its emission reductions realized – for several years, as 

EPA develops a replacement.

Outside of the Florida BART rule, and in response to the uncertainty over CAIR being replaced, 

DEP has completed source-specific BART determinations for the electric generating sources that 

had previously relied on CAIR. 

7.8.3 Determination of Sources Subject to BART in Florida

Under the federal Guidelines for Best Available Retrofit Technology Determinations (Appendix 

Y to Part 51, BART Guidelines), Florida may exempt sources from BART if they do not cause 

or contribute to visibility impairment in a Class I area. In accordance with the Florida BART 

rule exemptions, and the federal BART Guidelines, two exemption criteria were used to 

determine which BART-eligible sources could be exempted from the BART determination 

process. The first is based on meeting a simple emissions criterion applicable within two 

distances (50 km and 100 km) from any Class I area. Two of the BART-eligible sources meet 

this exemption. The second criterion is based on source-specific analyses to determine which 

sources cause or contribute to visibility impairment using the CALPUFF air quality model. A

CALPUFF modeling protocol developed by VISTAS was used to assure consistent and adequate

analysis and is included in Appendix L. In accordance with the Guidelines, and a Floridaspecific review of appropriateness (see Appendix L), a contribution threshold of 0.5 deciviews 

was used for determining which sources were subject to BART. 24 of the BART-eligible 

sources met this modeling exemption considering all three visibility impairing pollutants. 

Table 7.8.3-1 lists the facilities that were able to demonstrate exemption from BART based on 

CALPUFF modeling conducted using the VISTAS modeling protocol and the new IMPROVE 

equation. These modeling demonstrations were reviewed by DEP, and were also provided to 

the EPA Region 4 office and to the federal land managers for their review and comment. Based 

on these reviews, a number of BART-eligible sources had to correct and re-submit their 

demonstration modeling to comply with the modeling protocol. Eight BART-eligible sources 

made changes to their operation in order to meet the exemption criteria. These sources are 

Georgia Pacific-Palatka, Smurfit-Stone- Fernandina Beach, Smurfit-Stone – Panama City, 

Mosaic New Wales, Mosaic Riverview, CF Industries, OUC Indian River, and Progress Energy 

Florida Anclote. All of these changes have been incorporated into their permits and are federally 

enforceable. Additionally, two BART-eligible sources, Tampa Electric Company Big Bend and 

Gulf Power Crist, provided information showing that the existing controls at the subject units are 

the top level of control for each of the visibility pollutants, and, thus, full BART review is not 

necessary. Finally, documentation for the BART-eligible units that have shut down is included 

in Exhibit 2. 

Included in the table is the disposition of all the BART-eligible sources.

115
Table 7.8.3-1 BART-Eligible Sources and Their Disposition

FACILITY 

ID OWNER COMPANY NAME SITE NAME

Full 

BART 

Meets 

Modeling 

Exemption

Meets 

Model Rule 

Exempt.

Shut 

down

Max Visib 

Impact 

(dv)

10006 CITY OF GAINESVILLE, GRU DEERHAVEN GENERATING STATION x 0.205

50009 STONE CONTAINER CORPORATION PANAMA CITY MILL x 0.498

50014 GULF POWER COMPANY LANSING SMITH PLANT x

90006 FLORIDA POWER & LIGHT (PCC) CAPE CANAVERAL POWER PLANT x

90196 OUC INDIAN RIVER INDIAN RIVER PLANT x 0.167

110036 FLORIDA POWER & LIGHT (PPE) PORT EVERGLADES POWER PLANT x

170004 FLORIDA POWER CORPORATION CRYSTAL RIVER POWER PLANT x

250003 FLORIDA POWER & LIGHT (PTF) TURKEY POINT POWER PLANT x

310045 JEA NORTHSIDE/SJRPP x

310071 IFF CHEMICAL HOLDINGS, INC. IFF CHEMICAL HOLDINGS, INC. x 0.269

330040 SOLUTIA INC. SOLUTIA INC. x

330042 INTERNATIONAL PAPER COMPANY PENSACOLA MILL x 0.057

330045 GULF POWER COMPANY CRIST ELECTRIC GENERATING PLANT xxx 0.21

470002 WHITE SPRINGS AGRICULTURAL CHEMICALS,INC WHITE SPRS AG CHEM-SR/SC CMPLX x

510003 U.S. SUGAR CORP. CLEWISTON MILL U.S. SUGAR CLEWISTON MILL AND REFINERY x 0.265

530010 CEMEX CEMEX x

570005 CF INDUSTRIES, INC., PLANT CITY PHOS CF INDUSTRIES, INC., PLANT CITY PHOSP x 0.498

570008 MOSAIC RIVERVIEW x 0.494

570024 IMC PHOSPHATES COMPANY PORT SUTTON TERMINAL x

570039 TAMPA ELECTRIC COMPANY BIG BEND STATION xxx

610029 CITY OF VERO BEACH CITY OF VERO BEACH MUNICIPAL UTILITIES x 0.17

730003 CITY OF TALLAHASSEE ARVAH B.HOPKINS GENERATING STATION x 0.392

810010 FLORIDA POWER & LIGHT (PMT) MANATEE POWER PLANT x 0.458

850001 FLORIDA POWER & LIGHT (PMR) FPL / MARTIN POWER PLANT x 0.449

890003 SMURFIT STONE CORPORATION (US) JSC-FERNANDINA BEACH PAPERBOARD MILL x 0.495

990016 ATLANTIC SUGAR ASSOCIATION ATLANTIC SUGAR MILL x 0.49

990019 OSCEOLA FARMS OSCEOLA FARMS x 0.302

990026 SUGAR CANE GROWERS CO-OP SUGAR CANE GROWERS CO-OP x 0.467

990042 FLORIDA POWER & LIGHT (PRV) RIVIERA POWER PLANT x

990045 LAKE WORTH UTIL. TOM G. SMITH PLANT x 0.11

990061 U.S.SUGAR CORP. BRYANT MILL U.S. SUGAR CORP. BRYANT MILL x

1010017 FLORIDA POWER CORP. ANCLOTE POWER PLANT x 0.499

1030011 FLORIDA POWER CORPORATION FPC-BARTOW PLANT x

1050003 LAKELAND ELECTRIC CHARLES LARSEN MEMORIAL POWER PLANT x

1050004 LAKELAND ELECTRIC C.D. MCINTOSH, JR. POWER PLANT x 0.215

1050046 MOSAIC - BARTOW BARTOW x 0.144

1050053 MOSAIC - GREEN BAY GREEN BAY PLANT x 0.219

1050055 IMC PHOSPHATES COMPANY SOUTH PIERCE x 0.494

1050059 MOSAIC - NEW WALES NEW WALES x 0.496

1070005 GEORGIA-PACIFIC CORP. PULP/PAPER MILL GEORGIA-PACIFIC CORP. PULP/PAPER MILL x 0.48

1070014 FLORIDA POWER & LIGHT (PPN) PUTNAM POWER PLANT x 0.491

1110003 FT PIERCE UTILITIES AUTHORITY FT PIERCE UTIL/H D KING PWR PLNT x

1130003 STERLING FIBERS, INC. STERLING FIBERS, INC. x

1130005 EXXONMOBIL PRODUCTION COMPANY ST REGIS TREATING FAC AND JAY GAS PLANT x 0.39

1230001 BUCKEYE FLORIDA, LIMITED PARTNERSHIP BUCKEYE FLORIDA, LIMITED PARTNERSHIP x 0.284

1290001 TALLAHASSEE CITY PURDOM GENERATING STA. TALLAHASSEE CITY PURDOM GENERATING STATI x

TOTALS 12 24 2 8

xxx = BART satisfied by top-level control for SO2, NOx,PM

116
In summary, of the 46 sources that are BART-eligible, 26 have been determined to be exempt 

from BART, and 8 others have been shut down. The remaining 12 sources were required to

complete a BART determination for the applicable units or show that existing controls on the 

units are the top-level control. The following section discusses the results of the BART 

determinations. 

7.8.4 Determination of BART Requirements for Subject-to-BART Sources

Permit applications or BART analyses were received from each of the 12 subject-to-BART 

sources.

For each of the subject-to-BART sources, DEP has made a BART determination considering the 

five factors: (1) the costs of compliance, (2) the energy and non-air quality environmental 

impacts of compliance, (3) any existing pollution control technology in use at the source, (4) the 

remaining useful life of the source, and (5) the degree of improvement in visibility which may 

reasonably be anticipated to result from the use of such technology.

The BART determinations made by DEP are summarized below. The permits issued for these 

sources reflect the imposition of BART and are federally enforceable. 

7.8.4.1 CEMEX

BART-eligible Emissions Units

CEMEX operates an existing Portland cement plant with two Portland cement lines (Lines 1 and 2). 

These include: two Polysius GEPOL preheater kilns (Kilns 1 and 2); two clinker coolers and associated 

raw mills; finish mills; cement and clinker handling equipment; coal handling equipment; silos; and air 

pollution control devices. The nominal capacity of each kiln is 780,000 tons per year (TPY) of clinker. 

The facility is located at the existing plant which is located on U.S. highway 98, northwest of Brooksville, 

in Hernando County, Florida. The facility operates the following emissions units subject to the 

requirements of Rule 62-296.340(BART), F.A.C. 

The BART emissions units are part of Line 1: 

EU No. Emission Unit Description

002 No.1 Kiln Feed System (Baghouse D-31) – Pyroprocessing/Raw Mill System

003 Cement Kiln No. 1 (Baghouse E-55) – Pyroprocessing/Raw Mill System

004 Cement Plant Clinker Cooler No. 1 (Baghouse F-18) – Clinker Handling System

005 Finish Mills No. 1 and No. 2 with two dust collectors (Baghouse G-23) – Finish Mill System

006 Clinker Storage Silo Nos. 1 & 2 (Baghouse F-31) – Clinker Handling System

008 Baghouse No. F-17 of Kiln No.1 Blending Silo No. 1 – Cement Products is not BART-eligible

Baghouse No. E-36 of Kiln No 1. Blending Silo No. 2 – Cement Products is BART-eligible

009 Cement Plant STG Silos Dust Unit (Baghouse H-3) – Cement Products

011 Raw Material Storage Silos & Feed System (Baghouses C-11, C-11A)

117
Affected Pollutants

The affected visibility-impairing pollutants include NOX, PM10 and SO2.

Project Description and Status

On February 1, 2007, CEMEX submitted an application to satisfy the BART requirements. With the 

subsequent additional information received on September 5, 2007, DEP deemed the application complete. 

December 3, 2007, the applicant waived the 90 day processing clock until December 17, 2007. DEP

issued a draft air construction Permit No. 0530010-030-AC on December 17, 2008 with BART 

determinations. 

BART Determinations

The BART determination for different units at this facility are basically the top control 

technology currently being employed. The kiln was subjected to Prevention of Significant 

Deterioration (PSD) review and Best Available Control Technology determination (BACT) 

review since 1977 one or more times and the permitted values stand up very well compared to 

recent determinations made throughout the country even for Greenfield sites. We took those 

factors into consideration and determined it was not necessary to submit a full five factor 

analysis and determined that the controls in place constituted Best Available Retrofit Technology 

(BART).

Overall, the controls consist of highly effective sulfur dioxide scrubbing in the calciner, low raw 

material sulfur, fabric filter baghouses for particulate matter and selective non-catalytic reduction 

(SNCR) for nitrogen oxides control.

An identical kiln was built alongside Kiln 1 that underwent BACT in the early 80’s. Both kilns 

have since undergone BACT and have been subjected to enforcement actions leading to 

installation of present controls.

All controls including emission limits are federally enforceable.

BART controls follows:

NOX Kiln Controls: To control emissions of nitrogen oxides (NOX), CEMEX shall implement 

one of the following strategies:

a. To control emissions of nitrogen oxides (NOx), CEMEX shall operate the installed 

SNCR system as previously authorized by Permits 0530010-026-AC and 0530010-34-

AC. 

b. In lieu of a. above, CEMEX is authorized to install a selective catalytic reduction (SCR) 

system between the preheater and the raw mill to augment or replace the existing SNCR 

system. In the event the applicant chooses to install the SCR, installation and compliance 

with limit of 1.2 lb/ton of kiln preheater feed must be completed by October 31, 2013. 

The SNCR system shall be used in the interim to meet the compliance dates and limits in 

Permits 0530010-026 and 0530010-34-AC. The injectors may be rearranged as needed 

to optimize the final configuration.

SO2 Kiln Controls: The present SO2 control system consisting of dry alkali and lime scrubbing 

in the kiln system and limestone scrubbing in the raw mill constitutes BART for EU 003. 

118
CEMEX shall continue to operate and maintain Kiln No. 1 as indicated in Permit 0530010-003-

AC (PSD-FL-233) and the current Title V permit. No later than January 1, 2014, the permittee 

shall also comply with time-averaged limits and monitoring requirements discussed further 

below. [Rule 62-296.340 (BART), F.A.C.]

PM/PM10 Kiln Standards: 

To control emissions of PM from Kiln No. 1 CEMEX shall continue to operate and maintain 

baghouse E-55 as required by Permit 0530010-003-AC (PSD-FL-233) and the current Title V 

permit.

To control emissions of PM from Cooler No. 1 CEMEX shall continue to operate and maintain 

baghouse F-18 as required by Permit 0530010-003-AC (PSD-FL-233) and the current Title V 

permit.

Baghouse Controls: Each emissions unit identified in the Table above shall control 

PM/PM10 by a baghouse system. Bags/filters in each baghouse control system shall be 

selected based on a PM design outlet specification of 0.01 grain (gr) per dry standard cubic 

foot (dscf) and a PM10 design outlet specification of 0.007 gr/dscf. Compliance shall be 

demonstrated by maintaining the appropriate records and by complying with the mass 

emission limits, opacity limits and test requirements as indicated in BART Permit 0530010-

30-AC. Records may include, but are not limited to, Specifications stated in Purchase 

Orders, Specifications provided by Suppliers at the time of Delivery, and Records required 

by the CEMEX O&M Plan.

Visibility: The applicant provided a Post-BART analysis for PM (finish mills) and NOX

reductions (kiln) with the addition of Indirect Firing and SNCR, permitted by DEP 12/22/06 

(Permit No. 0530010-026). These reduced emission rates provided a visibility impact of 0.933dv 

(8th highest, 98th percentile) and reduced the number of days above the visibility threshold by 

approximately 45%. 

Pre-BART and Post-BART Visibility Impacts

BART-Eligible 

Sources

Actual Visibility 

Impact (dv)*

Impact with 

Reductions (dv)*

Change in Visibility Impact 

(dv)

2001 1.457 0.933 0.524

2002 1.341 0.841 0.500

2003 1.354 0.848 0.506

*98th percentile 

Review

The BART determination summarizes a limit or a technology for different units as follows:

NOx Emissions Standard (VE) for Kiln 1:

Pollutant Emission Limit Averaging 

Time

Compliance 

Method Basis

NOX 2.0 lb/ton clinker 30-operating

day rolling CEMS Applicant Request, PSD Avoidance and BART

119
SO2 Emissions Standard (VE) for Kiln 1:

Pollutant Emission Limit Averaging 

Time

Compliance 

Method Basis

SO2

0.17 lb/ton clinker

24-operating

hour rolling CEMS BART 15 lb/hr @ 150 TPH of feed

16.5 lb/hr @ 165 TPH of feed

PM/PM10 and Visible Emissions Standards (VE) for Kiln 1 and Cooler 1:

EU No. Description Emission Limit lb/hr at 150 dry 

preheater feed

lb/hr at 165 

TPH dry 

preheater feed 

VE

003 Kiln No. 1 0.31 lb/ton clinker 27.0 29.7 10

004 Cooler No. 1 0.15 lb/ton clinker 13.6 14.9 10

PM/PM10 and Visible Emissions Standards (VE) for the Emissions units listed below:

EU No. Description BART limit

lb/hr (3-hr)

BART

Opacity

002 No.1 Kiln Feed System (Baghouse D-31)

Pyroprocessing / Raw Mill System 1.02 5%

005 Finish Mill No. 1 and No. 2 with two bag collectors

(Baghouse G-23) – Finish Mill System

9.0

(for each mill) 5%

006 Clinker Storage Silo Nos. 1 & 2 

(Baghouse F-31) Clinker Handling System 1.45 5%

008 Kiln No 1. Blending Silos 

[Baghouse No. (E-36)(silo 2)] Cement Products 1.02 5%

009 Cement Plant Storage Silos Dust Unit 

[Baghouse No. (H-3)(silos 1-5)] – Cement Products 5.0 5%

011

Raw Material Storage Silos 

(Baghouse C-11) – Raw Material Handling 1.29 5%

Transfer Belt 

(Baghouse C-11A) – Raw Material Handling 0.86 5%

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7.8.4.2 FPL Turkey Point

BART-eligible Emissions Units for the Turkey Point Power Plant

This facility consists of two residual fuel oil and natural gas-fueled 440 MW fossil fuel steam 

electrical generators (Units 1 and 2), five fuel oil-fired black start 2.75 MW diesel peaking 

generators supporting Units 1 and 2, a natural gas-fueled 1,150 MW combined cycle unit (Unit 

5), and associated equipment. The facility is located at 9700 SW 344 Street, in Homestead, 

Miami-Dade County. 

The facility operates the following emissions units subject to the requirements of the federal 

Regional Haze BART regulations: Unit 1 (EU001) and Unit 2 (EU002). Units 1 and 2 are fossil 

fuel fired steam electric generators consisting of boiler/steam generators which drive single 

reheat turbine generators with multi-cyclones, with fly ash reinjection, to control particulate 

matter emissions. 

Affected Pollutants

The affected (i.e., visibility-impairing) pollutants for this project are: sulfur dioxide (SO2), 

nitrogen oxides (NOX) and particulate matter (PM). 

Project Description and Status

In 2009, FPL received a BART determination for these BART eligible units, although only for 

PM, which imposed a 20% visible emissions (VE) limit, a 0.7% sulfur fuel oil restriction and 

upgrades to the multi cyclones to a 0.07 lb/MMBtu emission rate for particulate matter. In 

addition, a PM control device additive study was required and done in 2010 to determine if a 

0.05 lb/MMBtu emission rate could be achieved. The study results showed that the lower limit 

was not achievable using a calcium-based additive, although the results indicated a 15% 

emission reduction could be achieved using the additive at loads above 50% when using a 500 

ppm additive injection rate.

Due to the limited use of oil on Unit 1, the nearly negligible visibility impacts from PM, and the 

little incremental benefit of a new dust collector, FPL proposes to eliminate the requirement to 

install the 3.7 million dollar new dust collector (ESP) on Unit 1 and will continue to use the 

existing dust collector (multi-cyclone) to meet a limit of 0.07 lb/MMBtu as BART for this unit.

Subsequent to the request to change the PM BART limitations, FPL submitted a new proposed 

BART determination for DEP to consider that includes SO2 and NOx. Such a determination 

would eliminate all reliance on CAIR in meeting their BART obligations. 

Units 1 and 2 – BART Determination

121
The BART-eligible units are:

ID No. Emission Unit Description

001 Unit 1 is a 4,000 MMBtu/hr fuel oil-fired boiler (4,150 MMBtu/hr when firing natural gas).

002 Unit 2 is a 4,000 MMBtu/hr fuel oil-fired boiler (4,150 MMBtu/hr when firing natural gas).

Baseline Emissions

FPL evaluated the control options for PM, SO2 and NOx considering the baseline period of 2001 

- 2003 for emissions based on the maximum 24-hour averages for each pollutant during this 

period. The following uncontrolled emission rates were evaluated based on stack testing and 

CEMS data from Units 1 and 2 during this period:

Uncontrolled Emission Rates*

Pollutant Unit1 Unit 2

SO2 3,488 lb/hr 3,757 lb/hr

NOx 2,586 lb/hr 2,198 lb/hr

PM Filterable 144 lb/hr 144 lb/hr

*Emissions of all pollutants are higher for fuel oil firing; therefore, the emission rates above are 

for fuel oil firing and were the highest (24-hour average) emission rates measured by CEMS (for 

gaseous pollutants) and stack testing (PM) during the baseline period. 

PM Control Technology Review

Particulate matter is emitted from the stacks of Units 1 and 2 as a result of the firing of fuel oil 

and natural gas to generate electricity. Each unit is equipped with low NOx burners and 

Universal Oil Products (UOP) Air Correction Division multi-cyclones with ash reinjection. The 

multi-cyclones consist of two tubular mechanical dust collector modules with 695 tubes per 

collector.

Step 1. Identify all available retrofit control technologies. 

The available retrofit control technologies for these boilers include the following:

• Add wet scrubbers following the existing multi-cyclones.

• Add electrostatic precipitators (ESP) following the existing multi-cyclones.

• Add baghouses following the existing multi-cyclones.

• Replace the existing multi-cyclones with new state-of-the-art multi-cyclones.

Step 2. Eliminate technically infeasible options.

Baghouses and ESP are generally recognized as the top controls with removal efficiencies 

greater than 99%. In this case, wet scrubbers have not demonstrated equivalent levels of control 

for PM compared to the top controls. Baghouses are deemed not feasible based on tests 

conducted by FPL at the Sanford plant found that particles generated from the combustion of oilbased fuels caused considerable plugging of bags in pilot scale tests.

Step 3. Evaluate control effectiveness of remaining control technologies.

122
Based on information submitted by FPL, that includes proposals provided by air pollution 

control device vendors, the effectiveness of the potential PM control techniques and available 

options are as follows:

Control 

Technology

Options

Continuously 

Achievable

Emission Rate

Emissions 

From Both 

Units

tons/year 

Potential 

Reduction

tons/year

Percent

Reduction*

Existing Multicyclones 0.1 lb/MMBtu** 1,795 * 0 0

New ESP 0.03 lb/MMBtu 539 1,257 70%

Multi-cyclone with 

low sulfur fuel oil/

0.070 lb/MMBtu 1,257 539 30%

* Baseline / Historical Maximum

**May meet lower limits in conjunction with 0.7% sulfur fuel oil

Step 4. Evaluate the impacts of the remaining technologies and document the results.

Based on information submitted by the applicant (assuming a 20-year useful life and 7% annual 

interest rate), the following is a summary of the expected costs associated with the proposed 

control options:

Control Options

Unit 1 Unit 2

Annualized 

Cost

$/ton 

Removed

Annualized 

Cost

$/ton 

Removed

New ESP (0.030 lb/MMBtu) $6,676,195 10,623 $6,676,195 10,623

Multi-cyclone upgrade & 

Reduced Fuel sulfur % $961,552 3,568 $961,552 3,568

It should be noted that the estimated cost does not include any changes in construction associated 

with the close proximity of the nuclear units (i.e., Turkey Point Units 3 and 4). According to the 

applicant: 

• The location of the ESP construction for Units 1 and 2 would increase security requirements 

and potentially require approval from the Nuclear Regulatory Commission. 

• The energy required to operate two ESPs would be about 4,370 MW-hr per year for both 

units, or about 0.13 percent of gross generation. 

• Ash collected by the ESP would require landfilling if it could not be recycled. 

• It is estimated that 1,257 tons of ash would be generated from the ESPs requiring about 50 

truck trips per year to remove it from the site. 

• FPL has plans to shut down Unit 2 in the near future. Also, Units 1 and 2 are typically 

operated as cycling units rather than base-loaded units.

Step 5. Evaluate visibility impacts. (See Step 5 below)

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BART Determination for PM

Part of the BART analysis is to consider the remaining useful life of the BART eligible unit. 

FPL has proposed to permanently shut down Unit 2. DEP has established a permit condition 

requiring the permanent shut down of Unit 2. Based on the high cost for such a small 

improvement in visibility, the company claims it is cost prohibitive to add an ESP to Unit 1. 

Also, with the applicant proposing a restriction of oil firing to approximately 25% capacity factor 

on Unit 1, the emission reductions for a new ESP on Unit 1 are further diminished, resulting in 

an excessively high cost per ton of PM removed. As an alternative emission reduction strategy 

that involves PM emissions reductions, the company has proposed the use of low sulfur (0.7 

percent) residual fuel oil (vs. 1% sulfur oil used during the baseline period) and a reduction in the 

PM limit from the current allowable emission rate of 0.1 lb/MMBtu down to 0.07 lb/MMBtu, 

which is achievable with the existing multi-cyclones controls and the lower sulfur fuel oil. At a 

comparative cost of less than $3,600/ton of PM removed, this option is considered cost effective

given the source’s relatively close proximity to the nearest Class I area, and will produce a 

significant visibility improvement of 0.6 dv (i.e., 29 percent reduction in visibility impacts from 

base case). 

Therefore, DEP has determined that FPL’s proposal to meet 0.07 lb/MMBtu for PM with a 25% 

capacity factor limit for firing low sulfur fuel oil (0.7% sulfur) using the existing multi-cyclone 

controls on Unit 1 and shut down of Unit 2 is a reasonable PM control alternative that serves the 

overall intent of the BART regulations. 

SO2 and NOxControl Technology Review

FPL evaluated BART options for SO2 and NOx control. A 5-factor BART analysis was done for 

each of these pollutant as follows. 

Step 1. Identify all available retrofit control technologies. 

The available retrofit SO2 control technologies for these boilers include the following:

• Add wet or dry scrubbers for acid gas control.

• Low Sulfur Fuel Oil options at 0.7% and 0.3% sulfur content.

FPL evaluated the available control options for SO2 control and reviewed the EPA 

RACT/BACT/LEAR Clearinghouse for applications of the above options. A flue gas 

desulfurization (FGD) system (wet scrubber) is technically feasible to control acid gases on these 

oil and gas fired units. Although FPL found no determinations for oil and gas fired units 

employing FGD in the clearinghouse and the determinations found by the applicant have all been 

based on lower sulfur fuel oil options to reduce SO2 emissions.

The potential control options for NOx include:

• Retrofit Selective Catalytic Reduction (SCR).

• Retrofit Selective Non-catalytic Reduction (SNCR).

• Existing Low NOx Burners.

Step 2. Eliminate technically infeasible options.

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Although feasible, wet or dry scrubbers for SO2 controls have not been used for comparable units 

that fire gas and fuel oil as discussed in Step 1. A Dry scrubber combined with bag house 

controls does not appear to be feasible in this case since tests conducted by FPL at the Sanford 

plant found that particles generated from the combustion of oil-based fuels caused considerable 

plugging of bags in pilot scale tests. Compared to firing natural gas, fuel oil has significantly 

higher sulfur content and FPL has proposed to control SO2 by limiting fuel oil firing on Unit 1 to 

no more than a 25% capacity factor, and limit the sulfur content, which has a large impact on the 

feasibility of add-on controls. 

The limited capacity factor for fuel oil, the higher NOx producing fuel, makes the use of add on 

NOx controls infeasible. FPL currently employs Low NOx Burners on Unit 1 which minimize 

NOx formation in the combustion zone. Unit 1 is currently required to meet the emission limit 

based on Rule 62-296.570 F.A.C. for NOx RACT, which is 0.40 lb/MMBtu on gas and 0.53 

lb/MMBtu on fuel oil based on continuous emission monitoring (CEMS) and a 30-day rolling 

average.

FPL has proposed to permanently shut down Unit 2, so no control evaluation was required.

Step 3. Evaluate control effectiveness of remaining control technologies.

FPL judged the use of lower sulfur fuel oil a technically feasible option to reduce SOx emissions 

from Unit 1. From a baseline of 1% sulfur fuel oil that was used in the 2001-2003 time-frame, 

FPL considered firing fuel oil on Unit 1 with a limited 25% capacity factor, and at fuel oil sulfur 

levels of 0.7% and 0.3%. 

 

Control 

Technology

Options

Continuously 

Achievable

Emission Rate

Emissions 

From Both 

Units

(tons/year)

Potential 

Reduction

(tons/year)

Cost 

Effectiveness* 

($/ton)

Baseline 1% S fuel 

oil 

1.1 lb/MMBtu 13,281 * - -

0.7% S fuel oil 0.77 lb/MMBtu 10,675 2,606 19,197

0.3% S fuel oil 0.33 lb/MMBtu 4,575 8,706 16,044

* Baseline / Historical Maximum level for both units operating at 6,825 hrs/yr.

The above table indicates a relatively high cost effectiveness value for either the 0.7% or the 

0.3% sulfur fuel oil options. As part of an earlier PM control technology determination for 

BART, FPL currently has a permit limit for no higher than 0.7% sulfur fuel oil for Unit 1; 

therefore, the 0.7% sulfur fuel oil option is feasible even at the relatively high cost. 

125
Step 4. Evaluate BART for the remaining technologies and document the result. 

Although technically feasible to install, wet or dry scrubbers have not been cost effective for 

comparable units that fire gas and fuel oil. FPL cites capital cost estimates of between $40 and 

$100 million dollars for FGD controls. Therefore ,the use of add-on SO2 control options like 

FGD or dry scrubber (followed by a baghouse), are determined by DEP to be cost prohibitive, 

especially considering the restriction to 25% capacity factor for fuel oil use in Unit 1 as proposed 

by FPL.

FPL proposed that add on NOx controls (SCR or SNCR) are cost prohibitive due to the high 

capital cost (between $10 and $20 million) and the limited visibility benefit. Considering the 

Unit 1 limited capacity factor (25%) for fuel oil, which has higher NOx emissions, and the 

current price difference between natural gas and fuel oil that further minimizes the actual use of 

fuel oil, the high cost of add-on controls for NOx and SO2 cannot be justified. 

Step 5. Evaluate visibility impacts.

The initial (PM only) BART determination analysis predicted visibility improvement with the 

addition of ESP’s to both Units 1 and 2. Initial emission rates were determined from stack test 

data and AP-42 emission factors to reflect the maximum 24-hour average normal operation. 

Emissions were speciated into six particulate species with regards to specific size categories and 

modeled. Results of this initial modeling predicted a visibility improvement of 0.1 dv. 

The modeling results of visibility improvement were based on particulate matter and percent 

sulfur fuel content. Base case emission rates for this modeling analysis were based on an 

emission rate of 0.1 lb/MMBtu with a fuel oil sulfur fuel content of 1% or the allowable emission 

rates for Units 1 and 2. The base case was then compared to the proposed BART determination 

of 0.07 lb PM/MMBtu and a sulfur content of 0.7 percent. The results of these analyses are 

shown in the table below.

Control Technology PM Emission 

Rate

Sulfur Fuel 

Content

8th highest 

impairment

(2001)

8th highest 

impairment

(2002)

8th highest 

impairment

(2003)

Existing Base Case 0.1 

lb/MMBtu 1% 2.2 dv 1.8 dv 1.9 dv

Multi-Cyclones 0.07 

lb/MMBtu 0.7% 1.6 dv 1.3 dv 1.4 dv

The modeling results predict a 28 percent visibility benefit for the proposed sulfur reduction and 

PM emission rate of 0.07 lb/MMBtu. Visibility improvements will be extended beyond these 

modeling results with a limit on the amount of fuel oil used in a year, to no more than a 25% 

capacity factor for operation of Unit 1 on this fuel, and a permanent shut down of Unit 2.

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To calculate the visibility improvement due to the lower sulfur content fuel, first the baseline 

visibility impacts were estimated based on the maximum 8th highest 24-hour average visibility 

impacts, which is 5.96 dv. Since sulfate particles contributed to more than 90-percent of the total 

visibility impact, instead of using just the sulfate contribution, the total impact (due to all 

pollutants) was used as baseline. Future or controlled visibility impacts were estimated based on 

modeling the reduced SO2 emissions rates, which will result from the burning of lower sulfur oil. 

These rates were calculated by multiplying the SO2 emissions rates used in the baseline impact 

analysis by the ratio of the specific sulfur content (0.7% or 0.3%) and the baseline sulfur content 

(estimated to be 1-percent). Visibility improvements were determined by subtracting future dv 

impacts from the baseline dv impacts. 

The visibility cost effectiveness numbers were calculated from the annual costs and the visibility 

improvement in dv. Visibility cost effectiveness for switching from the approximate 1-percent 

sulfur currently used to 0.7-percent sulfur is more than $33 million/dv for a total visibility 

improvement of 1.5 dv. Incremental visibility cost effectiveness for switching to 0.3-percent 

sulfur fuel is $35 million/dv for an additional improvement of 2.5 dv. These visibility 

improvements are extremely small for a very large cost.

BART Determination for NOx and SO2

The baseline modeling showed that nitrates contributed less than 3 percent of the visibility 

degradation associated with the all emissions. Based on this relatively small modeled impact of 

NOx emissions on visibility and the excessively high cost of add-on control devices, DEP has

determined that additional NOx reductions are not required for this BART determination. 

Likewise, the high cost of add-on controls for SO2 reductions is also not justified. DEP has

determined that the following satisfies BART for the emissions of NOx and SO2: 

• Limiting the sulfur content of the fuel oil fired to 0.7%, by weight, and restricting the firing 

of fuel oil to an annual capacity factor of 25%, constitutes BART for emissions reductions of 

SO2 from Unit 1. 

• The existing low NOx burners designed to meet the Rule 62-296.570, F.A.C., NOx RACT 

standards, which are 0.40 lb/MMBtu on gas and 0.53 lb/MMBtu on fuel oil, on a 30 day 

rolling average, constitutes BART for emissions of NOx from Unit 1.

• The permanent shutdown of Unit 2. 

Conclusion

Considering the above analysis, DEP has determined that the level of control already in place for 

the affected pollutants NOx and PM are consistent with the original BART determination for 

Turkey Point Plant Unit 1. Additional control strategies are not cost-effective and are not 

required for these pollutants. BART for Sulfur dioxide is deemed to be limited operation on low 

sulfur fuel oil for Unit 1. As required in current state permits, emissions from Unit 1 at the FPL 

Turkey Point Plant will meet the BART requirements by restricted use of fuel oil to 8,760,000 

MMBtu/year heat input, equivalent to a capacity factor of 25%, and by employing the following 

operational and emission limiting standards:

• SO2: As soon as practicable, but not later than December 31, 2013, the sulfur content of 

the fuel fired in Unit 1 shall not exceed 0.7%, by weight. Upon reduction of the sulfur 

content of the fuel oil, SO2 emissions from Units 1 shall not exceed 0.77 lb/MMBtu, on a 

3-hour rolling average. The sulfur dioxide emission limitation shall apply at all times 

127
including startup, shutdown, and load change. Compliance shall be demonstrated 

through the use of the existing continuous emissions monitoring systems (CEMS). 

• NOx: NOx emissions from Unit 1 shall not exceed the following limits using the 

existing low NOx burners and based on a 30-day rolling average:

• Natural Gas Fuel Oil

lb/MMBtu 0.40 0.53

lb/hour 1,610 2,041 

• PM: Emissions of PM are limited to 0.07 lb/MMBtu when firing fuel oil. Limit met by 

firing natural gas, co-firing natural gas with fuel oil containing less than 0.7% sulfur, and 

through the use of multi-cyclones (mechanical dust collectors) and fly ash reinjection. 

Compliance demonstrated by stack tests when fuel oil is fired for more than 400 hours 

annually. 

For Unit 2, permit No. 0250003-018-AC requires the permanent shutdown as soon as practicable 

but no later than December 31, 2013. 

 

7.8.4.3 Progress Energy Crystal River

BART-eligible Emissions Units for the Progress Energy Crystal River Power Plant

Progress Energy Florida (PEF) operates an existing power plant known as the Crystal River Power Plant, 

which consists of four coal-fired fossil fuel steam generating (FFSG) units and associated equipment. The 

facility is located in Citrus County on Power Line Road, West of U.S. Highway 19, in Crystal River, 

Florida.

The facility operates the following emissions units subject to the requirements of the federal 

Regional Haze BART regulations: Unit 1 (EU001) and Unit 2 (EU002). Units 1 and 2 are 

tangentially-fired, dry-bottom boilers. The units may burn bituminous coal or bituminous coal

and bituminous coal briquette mixture. Distillate fuel oil may be burned as a startup fuel. Units

1 and 2 have a nominal generation capacity of 440.5 and 523.8 megawatts (MW), respectively. 

Affected Pollutants

The affected (i.e., visibility-impairing) pollutants for this project are: sulfur dioxide (SO2), 

nitrogen oxides (NOX) and particulate matter (PM).

Project Description and Status

PEF has provided two optional BART solutions. The first would install scrubbers and SCRs to these units 

by 2018 and would extend the life of these units. The second would shutdown these units by December 

31, 2020, with no new controls being installed. Because PEF is in the process of ownership change, and 

decisions on how these units will be addressed in response to other federal regulations is uncertain, PEF 

has requested that it have until January 1, 2015 to state which option it will pursue. 

Review for SO2

Step 1. Identify all available retrofit control technologies.

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The options presented by PEF for SO2 control included (1) switch to lower sulfur coal, (2) dry 

flue gas desulfurization (DFGD) lime spray dryer absorber (SDA), and (3) wet flue gas 

desulfurization (WFGD). All of the identified available retrofit SO2 control technologies are 

considered technically feasible for Units 1 and 2. These units are subject to NSPS Subpart Da.

Low Sulfur Coal. Units 1 and 2 currently burn bituminous coal, bituminous coal and bituminous 

coal briquette mixture, distillate (No. 2) or on-specification used fuel oil. No. 2 fuel oil is only 

used during start-up and flame stabilization. Unit 1 has maximum authorized heat input rate of 

3,750 MMBtu/hr. The maximum authorized heat input rate for Unit 2 is 4,795 MMBtu/hr. 

Switching to a lower-sulfur fuel will reduce SO2 emissions compared to baseline coal, with no 

modifications to the emission units.

DFGD Lime SDA. In a DFGD system, boiler flue gas mixes in a spray dryer with a mist of 

atomized fresh lime slurry. The types of DFGD systems typically installed on coal fired boilers 

are those utilizing either a SDA or a circulating dry scrubber (CDS). PEF discusses SDA control 

equipment but indicates the installation of the technology is a concern with respect to adequate 

available space and conditions of the units. The installation of dry scrubbers would also 

necessitate additional PM control to prevent significant emission increases.

WFGD. A WFGD system removes SO2 from the exhaust stream by contacting the flue gas with 

an alkaline reagent in an absorber to form sulfite and sulfate salts. Key WFGD process design 

variables include flue gas flow rate, liquid-to-gas ratio, recycle slurry pH, flue gas SO2

concentration, and solid concentration and retention time. The WFGD systems are typically 

located downstream of any PM control system. Induced draft fans are typically used to pull the 

boiler flue gas through the WFGD spray tower absorbers before the flue gas exits through the 

stack.

When WFGD systems are installed as a retrofit technology a new stack may be required due to 

corrosion concerns. Adequate space must be available for the ancillary equipment associated 

with the WFGD system including reagent grinding and slurry preparation, dry reagent storage 

area and reagent slurry storage tanks, and gypsum dewatering, storage, and handling equipment.

Step 2. Eliminate technically infeasible options.

PEF concludes all identified available retrofit SO2 control technologies are considered 

technically feasible for Units 1 and 2.

Step 3. Evaluate control effectiveness of remaining control technologies.

The PEF analysis states that the effectiveness of SO2 emission control by the use of a WFGD 

system is between 56 and 98 percent and a DFGD is between 70 and 96 percent. For the purpose 

of this analysis a 95% percent control is assumed. The effectiveness of SO2 emissions control by 

the use of low sulfur coal depends on the sulfur content of the lower sulfur coal that is available. 

PEF has indicated coal with sulfur contents of 0.68% and 0.35% is commercially available.

Step 4. Evaluate impacts and evaluate the results.

Cost of Compliance. 

129
Economic analyses were developed for fuel switch to lower sulfur coal and FDG options. The 

direct operating cost estimates were based on DFGD with a puff jet fabric filter along with an 

SCR system retrofit and conceptual design and cost estimate. The 0.68% sulfur fuel switch is 

estimated with an ESP upgrade. The 0.35% sulfur fuel switch cost factors include performance, 

coal handling performance, safety for 0.35% coal and the replacement of an ESP with baghouse. 

The tables below provide summaries of control costs related to Units 1 and 2.

TABLE A.

SO2 Control 

Technology

Capital Cost

($)

O&M

$ per year

Annualized Cost

$ per year

Baseline SO2 emissions TPY

Units 1 and 2

0.68% sulfur coal 155,250,000 11,610,000 97,477,223 38,250

0.35% sulfur coal 516,206,250 11,198,250 296,706,765 38,250

FGD/SCR 445,029,412 118,461,366 364,602,684 38,250

TABLE B.

SO2 Control 

Technology

Controlled SO2

Emission Rates

SO2 Emissions Reduction Cost Effectiveness

$/ton

TPY TPY Average Incremental

Units 1 and 2

0.68% sulfur coal 27,000 11,250 8,665 N/A

0.35% sulfur coal 18,000 20,250 14,652 22,137

FGD/SCR 1,913 36,338 10,034 N/A

Energy Impacts. The energy impacts associated with the use of lower sulfur coals, such as 

Powder River Basin (PRB) coal are due to the lower heating values compared to the current coal 

used in Units 1 and 2. The heating values of the coal currently used are approximately 12,000 

British thermal units per pound (Btu/lb) compared to the heating value of 8,500 Btu/lb for PRB 

coal.

The operation of the DFGD system imposes energy penalty due to the increased fan power 

required to compensate for the higher pressure drop of the absorber vessel.

Nonair-Quality Impacts. The DFGD technology would have non-air impacts due to the 

increased water use and the generation of additional solids. The fuel switch to a lower sulfur 

coal would have negligible non-air quality environmental impacts.

Remaining Useful Life. A PM BART permit was issued for Crystal River Power Plant Units’ 1 

and 2 on February 25, 2009 (Permit No. 0170004-017-AC), which imposed a revised allowable 

PM emission limit along with a cease operation date of December 31, 2020 for the coal fired 

units addressed in this BART analysis. For the low sulfur coal control options it is assumed that 

some level of capital improvement will be required for the current ESP upgrades to 

accommodate the 0.68% sulfur coal, and the replacement of the ESP’s with baghouses and other 

equipment modifications would be required for the firing of PRB coal. For this analysis it is 

assumed that ESP upgrades or replacement and other equipment modifications would not be 

complete until 2018. A similar determination for the installation of the DFGD controls for Units 

1 and 2 was made. Since the proposed unit retirement date is the end of 2020 this would result 

in a useful control option equipment life of two years.

Step 5. Evaluate visibility impacts.

130
To calculate the visibility improvement due to the lower sulfur coal and the DFGD control 

options, the baseline visibility impacts were estimated based on the maximum 8th highest 24 hour 

average visibility impacts which is 7.93 dv. Since sulfate particles contribute to more than 90% 

of the total visibility impact, instead of using the sulfate contribution alone, the total impact from 

all pollutants was used as a baseline.

The improvements in visibility were estimated based on modeling the reduced SO2 emission 

rates, which will result from the burning of lower sulfur coal and the installation of the FGD 

systems with 95% control efficiency. The emission rates were calculated by multiplying the SO2

emission rates used in the baseline impact analysis by the ratio of: 1) the specific sulfur content 

(0.68% or 0.35%) and the baseline sulfur content (1.02%) of the fuel sulfur option and 2) by the 

uncontrolled baseline and the estimated control efficiency of the add-on control equipment for 

the FGD option.

The visibility cost effectiveness for switching from 1.02% sulfur coal to 0.68% is more than 

$40.4 million/dv for a total visibility improvement of 2.41 dv. The incremental visibility cost 

effectiveness for switching to 0.35% sulfur coal is $145 million/dv for an additional 

improvement of 1.37 dv. The DFGD system installed on Units 1 and 2 would have a visibility 

cost effectiveness of $79.4 million/dv combined for an additional improvement of 4.59 dv. 

Selection of BART

PEF has determined that switching to a lower sulfur fuel or installing an FGD system is costprohibitive, based on a December 31, 2020 retirement date. Without this retirement date, PEF’s 

SO2 BART determination for the Crystal River Power Plant Units 1 and 2 is a SO2 emissions rate 

of 0.15 lb/MMBtu on a 30 day rolling average, or 95 percent control efficiency, which can be 

achieved with the use of sulfur dioxide controls such as DFGD system.

Review for NOX

Step 1. Identify all available retrofit control technologies.

The options presented by PEF for NOx control included (1) selective catalytic reduction (SCR) 

and (2) selective non-catalytic reduction (SNCR). Each of these technologies are 

considered technically feasible for units 1 and 2.

SCR

SCR is a process for controlling emissions of NOx from stationary sources. The basic principle 

of SCR is the reduction of NOx to N2 and H2O by the reaction of NOx and ammonia (NH3) 

within a catalyst bed. The primary reactions occurring in SCR require oxygen and performance 

is best at oxygen levels above 2 to 3 percent. The SCR catalyst typically has a finite life, and 

some NH3 slips through without being reacted.

SNCR

SNCR is a post-combustion NOx control technology that reduces NOx into nitrogen gas and 

water vapor by reacting the flue gas with a reagent. SNCR systems can either use ammonia or 

urea as reagents. The chemical reaction for this technology is driven by high temperatures, 

typically from 1,600 to 2,100°F, normally found in combustion sources. High temperature 

ionizes the NH3 or urea instead of using a catalyst or non-thermal plasma. The temperature 

window for SNCR is very important because of the following considerations:

131
_ If the temperature is too high more NOx is generated than is being chemically reduced.

Also, the reagent is oxidized and little or no reduction occurs.

_ At lower temperatures the reduction reactions are too slow and more ammonia “slips”.

Ammonia slip has the potential to affect boiler operation as well as ammonium bisulfate

formation on the downstream boiler components.

Although there are examples of SNCRs installed on coal-fired boilers, it is more common for 

smaller boilers in the 100 MW size range. Successful application of SNCR in large boilers may 

be hampered due to the following characteristics:

_ Limited access to appropriate temperature regions

_ Greater variations in combustion temperatures

_ Longer distances over which reagent must be delivered and mixed

_ Increased ammonia slip due to inefficient use of reagent

Step 2. Eliminate technically infeasible options.

Both SCR and SNCR are technically feasible for Crystal River Units 1 & 2. However for large 

pulverized coal fired boilers, SCR is a demonstrated technology and SNCR is not.

Step 3. Evaluate control effectiveness of remaining control technologies.

The PEF analysis states that the effectiveness of NOx emission control by SNCR technology is 

approximately 25 percent. Control effectiveness of SCR technology can be up to 90 percent.

Step 4. Evaluate impacts and evaluate the results.

Cost of Compliance

To develop a cost of SCR for Units 1 and 2, information developed for the recent Cross-State Air 

Pollution Rule (CSAPR) was used. Capital, fixed operation and maintenance (O&M) and 

variable O&M are available on a $/kW basis as part of EPA’s Integrated Planning Model (IPM) 

Base Case v. 4.10 (9-1-2010) for Transport Rule; Documentation; Chapter 5, Emission Control 

Technologies. These costs models were developed by engineering contractors such as Sargent & 

Lundy for the wet-FGD cost model. Capital cost of $193/kW and fixed O&M cost of $0.7/kW 

presented for 500 MW boiler size and 11,000 Btu/kWh option were used in the cost calculation. 

Additionally, cost factors from the EPA Cost Control Manual were used to costs not included

in the EPA IPM cost model. Annualized costs were developed using the methodology in the EPA 

Cost Control Manual. The estimated annualized cost for SCR is about $92.6 million with a cost

effectiveness of $8,244 per ton of NOx removed. The cost effectiveness was estimated based on 

90 percent control of baseline emissions, which was determined from the maximum annual 

actual emissions for Units 1 and 2 combined from the period 2001-2003.

Since a detailed engineering study and a vendor quote for SNCR systems for Crystal River Units 

1&2 are not available, the EPA IPM cost information for 100 MW boiler was scaled in the cost 

analysis to understand the magnitude of the cost effectiveness in the event the SNCR system is 

deemed practical by an engineering study. Using the ratio of cost information in the EPA IPM 

document for SNCR systems for fluidized bed type boilers of 100 MW and 500 MW sizes, a 

capital cost of $19/kW and fixed O&M cost of $0.2/kW were used in the cost analysis for 

132
SNCRs for Crystal River Units 1&2. Note that the cost analysis does not include costs for 

reagent tank, reagent distribution and control systems, CEMS for ammonia and NOx

emissions, or water treatment system if urea is used. Indirect operating costs such as property 

tax, insurance, and administrative costs were also excluded for the cost analysis. The estimated 

annualized cost for SNCR is about $8.4 million with a cost effectiveness of $2,687 per ton of 

NOx removed. The cost effectiveness was estimated based on 25 percent control of baseline 

emissions, which was determined from the maximum annual actual emissions for Units 1 and 2 

combined from the period 2001-2003.

Energy Impacts. The installation of SCR will result in a power requirement of about 0.6 percent 

due to the backpressure of the SCR catalyst and auxiliaries. This is about 50,700 MWh per year 

of lost energy. If a SNCR is installed, additional electrical power will be required to operate the 

reagent handling system. A water treatment system will be required if urea is used as a reagent, 

which will also need additional power.

Nonair-Quality Impacts. There would be some non-air quality impacts associated with the 

storage and handling of ammonia. If anhydrous or aqueous 29 percent ammonia were used a 

Risk Management Plan (RMP) under EPA rules to implement Section 112(r) of the Clean Air 

Act would be required. Using 19 percent ammonia or urea would not require an RMP.

Ammonia slip is an issue with both SCR and SNCR operation. Other issues associated with 

ammonia slip are odor and ammonium salt formation. If urea is used, water used with urea will 

have to be treated prior to releasing or re-using.

Remaining Useful Life. Based on the current permit, the Units 1 and 2 will cease to be operated 

as coal-fired units by December 31, 2020. Therefore, assuming the SCR or the SNCR systems 

will be operational by early 2018, only approximately 3 years of useful life will be left for the 

SCR/SNCR units and as a result, the cost analysis assumed only 3 years of remaining life.

Step 5. Evaluate visibility impacts.

To calculate the visibility improvement due to the SCR systems, first the baseline visibility 

impacts were estimated based on the maximum 8th highest 24-hour average visibility impact 

contributed by nitrate particles and NO2 (6.43 dv for 2003 with 29.5% contribution from nitrate 

and NO2). Instead of modeling the reduced NOx emission rate, future or controlled visibility 

impacts were estimated based on the baseline visibility impact and the ratio of reduced hourly 

NOx emissions rate and the baseline hourly NOx emission rate. Visibility improvements were 

determined by subtracting future dv impacts from the baseline dv impacts.

The visibility cost effectiveness numbers for SCR were calculated from the annual costs and the 

visibility improvement in dv. Visibility cost effectiveness for SCR is approximately $54.2 

million/dv (visibility improvement 1.71 dv). 

The visibility cost effectiveness for SNCR is approximately $17.7 million/dv (visibility 

improvement 0.47 dv). 

Selection of BART

133
PEF proposes the existing combustion process, LNBs, and use of good combustion practices as 

BART for NOx emissions from Units 1 and 2. DEP concurs, that under the option to shut down 

these units by December 31, 2020, this is the appropriate BART.

Review for PM

The visibility modeling analysis showed that even replacing the existing control devices with 

new ones that are designed to meet a limit of 0.015 lb/MMBtu would not result in more than a 

0.15 deciview (dv) change in visibility at the nearest Class I area. The applicant also expressed 

concern that the cost of substantially upgrading the existing PM controls or replacing them with 

new control devices would be extremely costly. Considering the age of the units and the very 

high cost of replacing the PM control devices, the applicant proposed instead to upgrade the 

existing ESP for Unit 2, reduce their allowable PM limit from 0.1 lb/MMBtu to 0.04 lb/MMBtu 

(average for both units), and to permanently cease operating the units as coal-fired boilers within 

seven years of the final compliance date of the BART regulations (end of year 2020).

Review

Step 1. Table C lists the control options that were identified.

Step 2. All control options identified in Table C are considered technically feasible.

Step 3. Table C identifies the control efficiency for each pollutant under each control 

optionidentified.

Step 4. Table C identifies the rank for total capital costs as well as the rank for overall control 

effectiveness ($/ton). Energy impacts were considered in the cost analysis. The applicant did 

not identify any adverse non-air quality environmental impacts from the control equipment 

options but did consider remaining useful life an issue.

Step 5. Table C identifies the estimated visibility change for each control option based on the 

applicant’s visibility modeling analysis using the CALPUFF model.

Based on the BART analysis for the Crystal River project, meeting an emissions standard of 

0.015 lb/MMBtu may be achieved by all proposed options; however, it is not cost effective to do 

so recognizing that these units are nearing the end of their useful life. As an alternative to 

potentially spending around $150 million to replace the particulate matter control devices on 

these old units in order to continue to operate them for many years beyond the BART 

implementation date, PEF has proposed to spend around $50 million to upgrade the existing ESP 

for Unit 2 in order to meet a proposed combined emissions limit from Units 1 and 2 of 0.04 

lb/MMBtu in order to operate them until the prescribed shutdown date. While historical tests on 

these units at full load and steady-state operation have shown them capable of emitting PM at 

levels less than 0.04 lb/MMBtu, normal operation tends to vary at levels less than full load, 

which results in emissions close to the permitted limit of 0.1 lb/MMBtu. Considering the age of 

the existing units, it is not reasonable to require the large capital expenditure needed to bring 

emissions down to levels achievable by new units and control devices given the very limited 

remaining useful life. Therefore, DEP agrees with PEF’s proposal for reducing particulate 

matter emissions from the current allowable emissions limit of 0.1 lb/MMBtu down to levels 

near what has been reported on the last five year’s stack tests (0.04 lb/MMBtu) with a 

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commitment cease operating these units as coal-fired boilers by December 31, 2020. However, 

DEP recognizes that under the option to continue operation, the installation of a DFGD system 

will necessitate additional PM control to avoid significant emission increases. 

 

Table C. Control Equipment Analysis

Control Option

Control Efficiency Cost Effectiveness 1 Capital Costs 2 Visibility Impacts

% Rank $/ton Rank $ Rank dv 

Change $/dv Change Rank

Bag House 

Conversion 94% PM10 1 30,582 2 71,775,596 2 -0.150 95,122,400 1

Polishing Bag 

House (following 

existing ESP)

88% PM10 3 40,354 3 73,131,683 3 -0.110 127,235,127 3

New ESP 90% PM10 2 49,274 4 144,223,206 4 -0.130 127,098,392 2

Rebuilt ESP 85% PM10 4 12,987 1 28,760,610 \1 -0.100 27,316,290 4

Notes:

1. Average annual cost per ton removed for both units assuming 7 year remaining life.

2. Total capital costs for both units.

CONCLUSION

Considering the above analysis, DEP concludes that additional control strategies for SO2and NOx

are not cost-effective if the units shutdown by December 31, 2020. However, a PM limitation of 

0.04 lb/MMBtu for the combined two units is deemed to be BART. Should PEF choose not to 

shutdown the Crystal River Power Plant Units 1 and 2, PEF must install SO2 and NOx control 

technology, meeting the limits listed below by January 1, 2018. Additional PM control, beyond 

the limit listed below, is not considered necessary for BART given the very small visibility 

improvement that would occur for the cost. However, the permit authorizing PEF to construct the 

SO2 control, should that option be selected, assumes this control to be a DFGD, and DEP will 

limit PM in this permit to 0.015 lb/MMBtu at both units. DEP has allowed PEF until January 1, 

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2015, to choose the BART option it wishes to follow. DEP believes that either option meets the 

BART regulations. 

SO2: The emission limit for Unit 1 and 2 is 0.15 lb/MMBtu or 95 percent reduction. 

[Established in Permit No. 0170004-036-AC] 

NOX: The emission limit for Unit 1 and 2 is 0.09 lb/MMBtu. [Established in Permit No. 

0170004-038-AC]

PM: Combined emissions from Units 1 and 2 shall not exceed 0.04 lb/MMBtu. Compliance 

demonstrated by stack test. [40 CFR 60, Subpart Da]

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7.8.4.4 PCS White Springs

BART-eligible Emissions Units

The applicant, White Springs Agricultural Chemicals, Inc., d/b/a PCS Phosphate, operates a 

phosphate fertilizer manufacturing complex in White Springs, Florida. The facility is located at 

15843 SE 78th Street, White Springs, Hamilton County. This site is located about 25 kilometers 

from the Okefenokee National Wilderness Area, a Class I Area. The facility operates the 

following listed emissions units that are subject to the requirements of Best Available Retrofit 

Technology (BART) as listed in Rule 62-296.340(BART), F.A.C.: 

BART Eligible Emissions Units at the PCS Phosphate Facility

EU No. Emissions Unit Description

001 #2 Phoshate Rock Grinder 

003 A Defluorinated Phosphate Plant (DFP) 

004 X Train (Dical Process)

008 Y Train - #1 Diammonium Phosphate (DAP) Plant

010 #1 Monoammonium Phosphate (MAP)/DAP – Storage Building

015 MAP/DAP Shipping & Screening Facility

021 C Sulfuric Acid Plant (SAP)

022 D SAP

032 Z Train - #2 DAP Plant

038 B DFP 

042 DFP Feed Prep

044 A & B DFP Coolers

054 Molten Sulfur System

062 DFP Silos

064 Swift Creek Mine Rock Dryer

065 Swift Creek Mine Silos

SAP C and D plants use the double absorption process to control sulfur dioxide emissions and 

demisters to control sulfuric acid mist emissions. 

All of the listed DAP/MAP plants include medium to high efficiency wet scrubbers that use 

phosphoric acid and then pond water to reduce F and PM from the reactor and granulators. They 

are also equipped with abatement scrubbers using fresh water for final cleanup. Emissions from 

the dryers, coolers, mills and screens are controlled by cyclones, wet scrubbers with phosphoric 

acid or pond water as the scrubbing medium, and by abatement scrubbers using fresh water.

A and B DFP Coolers (EU 044) and Swift Creek Mine Silos (EU 065) use wet cyclonic 

scrubbers with pond water as the scrubbing medium to control particulate matter emissions.

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A and B DFP Plants (EU 003 and 038, respectively) include cross-flow packed wet scrubber 

with pond water as the scrubbing medium to control particulate matter emissions.

X Train Dical Process (EU 004) rotary dryer include series of wet venturi and cyclonic scrubbers 

to control particulate matter emissions. 

The #2 Phosphate Rock Grinder (EU 001), X Train (EU 004) limestone handling, the DFP Feed 

Prep area (EU 042), DFP Product Silos (EU 062) include fabric filter baghouses designed to 

recover process or product raw materials and to control particulate matter emissions.

Swift Creek Mine Rock Dryer (EU 064) and Swift Creek Mine Silos (EU 065) include wet 

cyclonic scrubber to control particulate matter emissions. The Rock Dryer is fired primarily 

with natural gas. 

Affected Pollutants

The affected visibility-impairing pollutants include NOX, PM10 and SO2.

Project Description and Status

On February 1, 2007, PCS Phosphate submitted an application to satisfy the BART requirements. With 

the subsequent additional information received on September 4, 2007, DEP deemed the application 

complete. DEP issued a draft air construction Permit No. 0470002-055-AC on November 13, 2007 with 

BART determinations. PCS Phosphate filed a petition for formal administrative hearing on January 23, 

2008, after their request for extension of time to file an administrative hearing was denied by DEP. PCS 

Phosphate has been in negotiations with DEP to resolve the outstanding issues related to the proposed 

BART. PCS Phosphate resolved all the outstanding issues with DEP in letters dated December 16, 2008 

and January 20, 2009 to DEP. DEP will issue a revised draft BART construction permit which will 

incorporate the resolution of the outstanding issues as listed in PCS Phosphate’s December 16, 2008 and 

January 20, 2009 letters to DEP. 

BART Determinations

SAP Plants: At PCS Phosphate molten elemental sulfur is combusted to produce the source of 

the gaseous SO2 used to manufacture sulfuric acid. Thus SO2 is a valuable important 

intermediate raw material for the process. The key emissions are SO2, sulfur trioxide (SO3) and 

sulfuric acid mist (SAM or H2SO4). All are key intermediate raw materials or products as well 

as pollutants. NOX and minor amounts of PM from the sulfur source (typically combustion of 

molten sulfur) will also exit through the SAP stack. 

MAP/DAP Plants: At the PCS Phosphate’s MAP/DAP plants; phosphoric acid is reacted with 

ammonia to produce fertilizer. In the basic ammoniated phosphate process, anhydrous ammonia 

is reacted with phosphoric acid. The slurry produced by the ammoniation is then sprayed onto a 

bed of solids in the granulator and additional ammonia (if required) is added to complete the acid 

neutralization and produced the final product grade. 

The resulting slurry/solids mixture is dried in a fossil fuel fired direct contact rotary dryer. The 

dried solids are then screened to remove on size product. The product size material is cooled and 

then conveyed to storage. The over-sized and under-sized materials are crushed and recirculated 

through the granulator. 

The key pollutants from the DAP/MAP plants are fluoride (particulate and gaseous), other PM in 

the form of DAP and MAP, and also NH3.

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DFP Plants: At PCS Phosphate’s DFP Plants; phosphate rock is reacted with soda ash slurry and 

limestone. The resulting mixture is introduced into a natural gas fired, fluidized bed reactor. As 

the feed is introduced into the reactor a proportional amount of finished feed is discharged into a 

fluidized air cooler. In the cooler, material from the reactor and cyclone are cooled and 

transported to a holding bin. The product is screened and oversize material is sent to grinding 

roll mills for sizing.

X Train (Dical Process): In this process, limestone reacts with phosphoric acid in a pug mill. 

The resulting slurry is then dried in a direct contact rotary dryer fired with either natural gas or 

fuel oil. The rotary dryer is controlled by a system of wet venturi and cyclonic scrubbers. The 

dried solids are then screened to remove on-size product. The product size material is conveyed 

to storage. The over-sized and under-sized materials are crushed and recirculated to the pug 

mill. 

The initial modeling analysis indicated maximum visibility impacts of 3.07 dv during the period 

2001-2003. The 8th highest visibility impairment value for each of the three years is over the 

comparison threshold of 0.5 dv (range 1.63-1.77). The 22nd highest impairment is 1.72 dv. In 

addition, there are 87, 93 and 91 days (2001-2003) predicted to have visibility impairment of 

over 0.5 dv. The primary focus of the determination was on the effects of lower SO2, NOX and 

PM10 emissions. 

BART determinations are conducted on certain emission units constructed between 1962 and 

1977, during which time top/down case-by-case determinations for best available control 

technology (BACT) were not conducted. BACT is a requirement for projects subject to the rules 

for the prevention of significant deterioration (PSD) promulgated by EPA in January 1975. 

However since 1977 and most recently since the reference period 2001-2003 Line 1 has been 

subjected to a number of reviews that resulted in the installation of control equipment or 

inclusion of federally enforceable emission limits characteristic of BACT.

The BART process is described in 40 Code of Federal Regulation (CFR) Part 51, Appendix Y as 

follows: 

Step 1 - Identify all available retrofit control technologies;

Step 2 - Eliminate technically infeasible options;

Step 3 - Evaluate control effectiveness of remaining control technologies;

Step 4 - Evaluate impacts and document the results; and

Step 5 - Evaluate visibility impacts.

According to 40 CFR 51, Appendix Y, paragraph IV.D.9, there are circumstances under which it 

is not necessary to comprehensively complete each step of the BART analysis. Under such 

circumstances, it is allowable to skip the remaining analyses in this section, including the 

visibility analysis in Step 5. Furthermore, according to 40 CFR 51, Appendix Y, paragraph 

II.A.2, for an emissions unit which began operation within the 1962–1977 time window, but was 

modified (major) after August 7, 1977 such that controls were installed, the state will take this 

into account during the review process and may find that the level of controls already in place 

are consistent with BART.

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The applicant submitted the application on the basis of the original design, and the subsequent 

PSD/BACT review of similar emissions units at other facilities, like C.F. Industries SAPs B, C 

(2004-2007). The details of the previous reviews and specific additional enforceable conditions 

are given in the technical document accompanying the BART permit.

DEP finds that the levels of controls already in place are consistent with BART. The SAP 

emissions limits for SO2 can be further reduced by slight modifications to the converter as 

explained in the technical document accompanying the BART permit. The following emission 

limits comprise BART and were incorporated into the final BART permit:

SAP Plants

SO2 Emission Standards: 

Source Sulfur Dioxide (SO2) Emission Limits

SAP C1 3.5 lb SO2/ton of 100% H2SO4 and 335.4 lb/hr, 24-hour rolling average by

CEMS2

SAP D 3.5 lb SO2/ton of 100% H2SO4 and 335.4 lb/hr, 24-hour rolling average by 

CEMS2

1 The applicant is authorized to modify the converter tower to comply with the new BART 

emission limit for SO2. 

2 This BART determination requires an SO2 CEMS to be used to demonstrate continuous 

compliance with the SO2 emission standards and limitations specified above.

NOX Emission Standards: 

Source Nitrogen Oxides (NOX as NO2) Emission Limits

SAP C (EU 

021)

0.14 lb NOX/ton of 100% H2SO4. Testing using EPA Method 7E shall 

be done upon request by DEP. 

SAP D (EU 

022)

0.14 lb NOX/ton of 100% H2SO4. Testing using EPA Method 7E shall 

be done upon request by DEP. 

PM/PM10 - Opacity (VE) Standard

As determined by EPA Method 9, visible emissions from the two SAP shall not exceed the 

current 10% opacity limits based on a 6-minute average.

DAP/MAP Plants

PM/PM10 Emissions Standard: 

Emissions of particulate matter (PM) and particulate matter with a mean diameter of 10 microns 

or less (PM10) shall not exceed the following limits based on the average of three test runs as 

determined by EPA Methods 5. 

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Source Particulate (PM/PM10) Emission Limits

DAP/MAP Y (EU 008) 9.2 lb/hr by annual 3-hr stack test

DAP/MAP Z (EU 032) 9.2 lb/hr by annual 3-hr stack test

DAP/MAP Y – Storage Building (EU 010) 4.7 lb/hr by annual 3-hr stack test

DAP/MAP – Shipping & Screening (EU 

015)

1.46 lb/hr by annual 3-hr stack test

To control emissions of particulate matter (PM/PM10), the permittee shall operate and maintain 

the existing process and pollution control technology for each of the DAP/MAP plants. The 

applicant is authorized to make improvements to the process and pollution control equipment for 

the purposes of reliably meeting the new BART PM/PM10 emission limits given above.

SO2 and NOX Controls and Emission Standards: 

To control SO2 and NOX emissions from DAP/MAP Plants Y and Z, the permittee shall continue 

to use natural gas in the dryers with 1.5 weight percent sulfur fuel oil as backup. No numerical 

emission limit is established.

DFP Plants

PM/PM10 Emissions Standard: 

Emissions of particulate matter (PM) and particulate matter with a mean diameter of 10 microns 

or less (PM10) shall not exceed the following limits based on the average of three test runs as 

determined by EPA Methods 5. 

Source Particulate (PM/PM10) Emission Limits

A DFP (EU 003) 14.1 lb/hr by annual 3-hr stack test

B DFP (EU 038) 14.1 lb/hr by annual 3-hr stack test

DFP Feed Prep (EU 042) 4.5 lb/hr by annual 3-hr stack test

A and B DFP Coolers (EU 044) 17.5 lb/hr by annual 3-hr stack test

To control emissions of particulate matter (PM/PM10), the permittee shall operate and maintain 

the existing process and pollution control technology for each of the DAP/MAP plants. The 

applicant is authorized to make improvements to the process and pollution control equipment for 

the purposes of reliably meeting the new BART PM/PM10 emission limits given above.

SO2 and NOX Controls and Emission Standards: 

To control SO2 and NOX emissions from A and B DFP Plants, the permittee shall continue to use 

natural gas in the dryers with 1.5 weight percent sulfur fuel oil as backup. No numerical 

emission limit is established.

X Train (Dical Process):

PM/PM10 Emissions Standard: 

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Emissions of particulate matter (PM) and particulate matter with a mean diameter of 10 microns 

or less (PM10) shall not exceed the following limits based on the average of three test runs as 

determined by EPA Methods 5. 

Source Particulate (PM/PM10) Emission Limits

X Train (EU 004) 18 lb/hr by annual 3-hr stack test

SO2 and NOX Controls and Emission Standards: 

To control SO2 and NOX emissions from X Train, the permittee shall continue to use natural gas 

in the dryers with 1.5 weight percent sulfur fuel oil as backup. No numerical emission limit is 

established.

Swift Creek Mine:

PM/PM10 Emissions Standard: 

Emissions of particulate matter (PM) and particulate matter with a mean diameter of 10 microns 

or less (PM10) shall not exceed the following limits based on the average of three test runs as 

determined by EPA Methods 5. 

Source Particulate (PM/PM10) Emission Limits

Swift Creek Mine Rock Dryer (EU 064) 17.3 lb/hr by annual 3-hr stack test

Swift Creek Mine Silos (EU 065) 6.27 lb/hr by annual 3-hr stack test

SO2 and NOX Controls and Emission Standards: 

To control SO2 and NOX emissions from the Swift Creek Mine Rock Dryer, the permittee shall 

continue to use natural gas in the dryers with 1.5 weight percent sulfur fuel oil as backup. No 

numerical emission limit is established.

Shipping Units

Particulate Matter Emissions Limit: A Visible Emissions Standard of 5% Opacity for each 

baghouse.

7.8.4.5 City of Tallahassee Purdom

BART-eligible Emissions Units

The City of Tallahassee operates the existing Sam O. Purdom Generating Station, which is an existing 

power plant located in Wakulla County at 667 Port Leon Drive in St. Marks, Florida. Unit 7 at this 

facility is a BART-eligible unit that is fired primarily with fuel oil and natural gas. The unit began 

operation in 1966 and is a 621 MMBtu per hour steam generator paired with a nominal 44 MW steamelectrical generator.

Affected Pollutants

The affected visibility-impairing pollutants include NOX, PM10 and SO2. 

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Project Description and Status

On January 31, 2007, the City of Tallahassee submitted an application to satisfy the BART requirements. 

The application was made complete with additional information provided on March 4, 2007. DEP issued 

a draft air construction Permit No. 120001-008-AC on May 24, 2007 requiring that Unit 7 permanently 

cease operation no later than December 31, 2013 to satisfy BART. No comments were received on the 

draft permit and a final permit was issued on September 11, 2007 requiring permanent shutdown of Unit 

7.

BART Determination

The following permit condition represents the BART determination for Unit 7 at the Purdom 

Generating Station:

Review

Because the applicant requested a complete and permanent shut-down of the unit thus 

eliminating all emissions from the unit, no further BART analysis was required. 

7.8.4.6 Tampa Electric Big Bend

BART-eligible Emissions Units

Tampa Electric Company (TEC) operates four solid fuel-fired electrical generating units (EGUs) at its Big 

Bend Station locoated in North Ruskin, Hillsborough County, Florida. The Big Bend Station is a nominal 

2,028 MW electric generation facility, with units 1, 2, 3, and 4 having maximum heat input rates of 4,037, 

3,996, 4,115, and 4,330 million British thermal units per hour (MMBtu/hr), respectively. The primary 

fuel is coal. Units 1, 2, and 3, meet the requirements of a BART-eligible unit.

Affected Pollutants

The affected visibility-impairing pollutants include NOx, PM10 and SO2. 

BART Determination

Appendix Y to Part 51 provides guidelines for BART determinations under the regional haze 

rule. It states that if a BART-eligible source has controls already in place which are the most 

stringent controls available, then it is not necessary to comprehensively complete the BART 

analysis. Further, the preamble to the rule states if a BART-eligible source was modified after 

August 7, 1977, and if such a modification was a major modification that resulted in the 

installation of controls, “the State will take that into account during the review process and may

find that the level of controls already in place are consistent with BART.” Based on the review 

below, DEP concludes that the TEC BART-eligible emission units 1, 2, and 3 all currently have 

the most stringent controls for SO2, NOx, and PM10. As such, the existing controls represent the 

BART determination. Exhibit 2 contains the source’s request for this determination, along with 

its analysis of existing controls. 

143
Review

Big Bend Station Units 1, 2, and 3 are presently equipped with a comprehensive suite of 

emission control systems to reduce emissions of PM10, SO2, and NOx. TEC entered into 

agreements with DEP and EPA to reduce emissions at the Big Bend Stations. These judicially 

enforceable agreements (DEP’s Consent Final Judgment and EPA’s Consent Decree) required 

minimization and monitoring of PM emissions, upgrades to the FGD scrubbers, and reductions 

in NOx emissions through the installation of SCR systems.

Electrostatic Precipitators – PM10 Controls

Units 1, 2, and 3 are each equipped with electrostatic precipitators (ESPs). Through the Consent 

Decree and Consent Final Judgment, TEC was required to complete a Best Available Control 

Technology (BACT) analysis for upgrading each ESP. This analysis resulted in physical 

upgrades to the ESPs and development of Best Operational Practices (BOPs), resulting in a high 

level of PM removal and low emission rates. The PM emission limit is 0.03 lb/MMBtu.

Wet Flue Gas Desulfurization – SO2 Controls

Units 1, 2, and 3 are each equipped with wet flue gas desulfurization (FGD) scrubbers to control 

SO2 emissions. The Consent Decree and Consent Final Judgment required upgrades to the 

scrubbers resulting in high SO2 removal rates. Each unit is required to remove at least 95 percent 

of the SO2 entering the FGD scrubbers.

Selective Catalytic Reduction – NOx Controls

Units 1, 2, and 3 are each equipped with selective catalytic reduction (SCR) technology to 

control NOx emissions. The Consent Decree and Consent Final Judgment required reductions in 

NOx emission rates. TEC installed SCR control systems on each unit, resulting in high NOx 

removal rates. The NOx emissions limit is 0.12 lb/MMBtu.

Conclusion

The DEP concludes that the existing controls and emissions limits imposed on the TEC Big 

Bend units 1, 2, and 3, as required by the Consent Decree and Consent Final Judgment, are the 

top level of control for this source. Further, these controls are BACT-level and meet the 

presumptive BART levels contained in the regional haze rule.

7.8.4.7 Gulf Power Crist

BART-eligible Emissions Units

Gulf Power, a Southern Company operates the existing Crist Electric Generating Plant, which is 

located in Escambia County, on Pate Road, off of 10 Mile Road on Governors Bayou, North of 

Pensacola, Florida. The Crist Electric Generating Plant consists of four active fossil fuel fired 

steam generators (boilers) and three fly ash silos. Boilers 4 and 5 were Acid Rain Phase I 

substitution units and boilers 6 and 7 were Acid Rain Phase I units. All four boilers are subject 

to the Acid Rain Phase II requirements and are also regulated under the Cross State Air Pollution 

Rule (CAIR). Pulverized coal is the primary fuel for boilers 4, 5, 6 and 7. Natural gas, fuel oil, 

and on-specification used oil are used as supplemental fuels in all four of the units.

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Boilers 6 and 7 have the potential to emit 250 tons or more of a visibility impairing air pollutant, 

were placed into operation between August 7, 1962 and August 7, 1977, and are included within 

one of the 26 specifically listed source categories. Therefore, the facility operates the following 

emissions units subject to the requirements of Rule 62-296.340(BART), F.A.C.: Unit 6 (EU006) 

and Unit 7 (EU007).

Affected Pollutants

The affected visibility-impairing pollutants include NOx, PM10 and SO2.

Project Description 

On May 21, 2012, Gulf Power submitted an application to satisfy the Crist Electric Generating Plant, 

Units 6 and 7 BART requirements. Gulf Power asserts that the existing emission controls in use at Crist 

satisfy BART requirements for Units 6 and 7 as a result of utilizing top level controls and/or complying 

with better than BART alternatives. DEP has reviewed Gulf Power’s proposal in making its 

determination.

Gulf Power previously submitted BART exemption modeling in 2007 for PM which demonstrated Units 6 

and 7 visibility impacts were well below the visibility impairment threshold of 0.5 deciviews. This PM 

modeling was conducted prior to the installation of the wet FGD system, the SCR system, and 

reconstructed ESP for Unit 6.

BART Determination

Review for NOx: NOx emissions from Units 6 and 7 are controlled by Foster Wheeler Low 

NOx Burners and by a Selective Catalytic Reduction (SCR) system designed to achieve no less 

than an 85% reduction in NOx emissions as measured across the SCR unit inlet and outlet. The 

SCR system consists of a plate type structure arranged in four layers fabricated to applying 

ceramic catalyst material to a perforated stainless steel mesh grid plate. The SCR for Unit 7 

came on line in 2005, and for Unit 6 in 2012.

The current permit limit for emissions of nitrogen oxides (NOx) from the combined operation of 

Units 4, 5, 6, and 7 shall not exceed 0.2 lb/MMBtu heat input based on a 30-day rolling average 

except for periods when Unit 7 is shutdown. DEP believes that SCR technology with 

combustion controls represents the top level control for NOx. As such, no further controls are 

deemed appropriate for BART. 

Review for SO2: The permittee operates a wet FGD system to control SO2 emissions from Units 

4 - 7. Units 4 - 7 share a common stack under normal conditions with the wet FGD system in 

operation. The wet FGD system is based on the Model CT-121 wet FGD process licensed from 

Chiyoda Corporation. The system consists of a single scrubber reactor vessel and supporting 

subsystems for transport and processing flue gas exhaust, limestone, gypsum, or other solids, and 

water. The wet FGD system is designed to remove 95% SO2 emissions. Since the wet FGD was 

installed on a common stack for Units 4-7 additional SO2 emission reductions occur. 

DEP believes that wet FGD systems are the top level SO2 control for electric utility boilers. The 

system installed by Gulf Power came on-line in late 2009. As such, no further controls are 

deemed appropriate for BART.

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Review for PM: PM emissions from Unit 6 are controlled by a cold side electrostatic 

precipitator (Wheelabrator Model # HaRDE). PM emissions from Unit 7 are controlled by cold 

side electrostatic precipitators designed by Alstom Power Inc.

The permit limit for particulate matter emissions shall not exceed 0.1 pound per million Btu heat 

input, as measured by applicable compliance methods.

DEP believes that PM control using ESP’s is the top level control for electric utility boilers. As 

such, no further controls are deemed appropriate for BART.

Conclusion

The top level emissions control technology sited above are currently installed and operating on 

Units 6 and 7 at Crist, therefore no additional time is required for complying with BART. There 

are no additional energy and non-sir quality environmental impacts associated with these two 

units as the aforementioned top controls are in place. DEP has determined that Gulf Power’s 

Crist Electric Generating Plant Units 6 and 7 are utilizing top level controls for the affected 

pollutants SO2, NOx and PM. Federally enforceable Title V Permit emission limits are currently 

established. 

7.8.4.8 FPL Martin

BART-eligible Emissions Units for the Martin Power Plant

This facility consists of two oil and natural gas fired conventional fossil fuel steam electric 

generating stations (Units 1 and 2), two oil and natural gas fired combined cycle units (Units 3 

and 4), four oil and natural gas fired combined-cycle combustion turbines (Unit 8), and 

associated support equipment. The Martin Plant is located 7 miles North of Indiantown on State 

Road 710, Indiantown, in Martin County. 

The facility operates the following emissions units subject to the requirements of the federal 

Regional Haze BART regulations: Unit 1 (EU001) and Unit 2 (EU002). Units 1 and 2 are fossil 

fuel fired steam electric generators consisting of boiler/steam generators which drive single 

reheat turbine generators, and are equipped with low nitrogen oxides (NOX) dual fuel firing 

burners to reduce emissions of NOX, and multi-cyclones, with fly ash reinjection, to control 

particulate matter emissions. The maximum capacity of each generator is 863.3 megawatts 

(MW).

Affected Pollutants

The affected (i.e., visibility-impairing) pollutants for this project are: sulfur dioxide (SO2), 

nitrogen oxides (NOX) and particulate matter (PM). 

Project Description and Status

FPL submitted a BART applicability determination to DEP to address the BART requirements. 

Review for SO2

Step 1. Identify all available retrofit control technologies.

The options presented by FPL for SO2 control included (1) use of low sulfur fuel, and (2) flue 

gas desulfurization (FGD), including dry sorbent injection. Two grades of low sulfur fuel oil are 

146
discussed: 0.3% and 0.7%. These units are subject to the NSPS Subpart Da limit of 0.8 lb 

pound of SO2 per million British thermal units (lb/MMBtu) when firing fuel oil. FPL fires 

blends of natural gas and/or fuel oil as needed in order to comply with this SO2 limit.

Low Sulfur Fuel. Units 1 and 2 currently burn natural gas, distillate (No. 2) or residual (No. 6) 

fuel oil. The sulfur content of residual oil available in the marketplace can range from 0.3 

percent to more than 2 percent. The facility’s Title V permit contains the following requirements 

concerning fuels: The only fuels allowed to be burned are low sulfur fuel oil containing a 

maximum of 0.7% sulfur content, by weight; natural gas; or, a mixture of low sulfur fuel oil 

containing a maximum of 1.0% sulfur content, by weight, and natural gas in a ratio that shall not 

exceed the sulfur dioxide emission limiting standard of 0.80 lb/MMBtu heat input. 

Switching to a lower-sulfur fuel oil can reduce SO2 emissions; however, the cost of 

implementing the change depends on both the product price difference and the difference in 

delivery cost (if any). The refined oil products that are readily available to the Martin plant 

without special order only include 0.3% and 0.7% sulfur grades. 

The use of a lower sulfur fuel (i.e., switch from 0.7% to 0.3% sulfur grade) is considered to be a 

technically feasible option to reduce SO2 emissions. 

Step 2. Eliminate technically infeasible options.

Flue Gas Desulfurization. The BART analysis submitted by FPL (analysis) discussed various 

post-combustion control technologies that rely on chemical reactions within the control device to 

reduce the concentration of SO2 in the flue gas. These included the calcium-based wet 

lime/limestone FGD system and dry FGD systems (e.g., dry sorbent injection). The analysis 

points out that use of post-combustion controls are typically applied to coal-fired boilers and not

to oil-fired units due to chemical reaction technology considerations and efficiencies. DEP

agrees with this finding. Wet or dry FGD systems, typically used for coal-fired boilers, are not a 

feasible option for oil/gas-fired utility boilers.

Step 3. Evaluate control effectiveness of remaining control technologies.

The FPL analysis states that the effectiveness of SO2 emissions control using lower sulfur fuel 

depends on product availability and economic feasibility. Switching from 0.7% sulfur fuel oil to 

0.3% sulfur fuel oil is a control method that can result in lower emissions of SO2 with no added 

capital investment. 

Step 4. Evaluate impacts and evaluate the results.

Cost of Compliance - Fuel Cost

The analysis indicates that the current cost of 0.7% sulfur fuel oil is $114.63 per barrel, and the 

current cost of 0.3% sulfur fuel oil is $124.63. No other cost components (e.g., equipment, 

operation, and maintenance) are expected to be affected if the switch to lower sulfur fuel is 

made. Using appropriate heat input and hours of operation data results in a cost differential of 

$190,328,407 annually.

•

Cost Effectiveness

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Based on company data, the “pounds of SO2 in a barrel of oil” is as follows: (8.1 lb/gal *42 

gal/bbl*2 lb SO2/lb S* fraction of S in oil); thus, at 0.7 percent sulfur oil = 4.763 lb SO2/bbl and at 

0.3 percent sulfur oil = 2.041 lb SO2/bbl.

Given the company-provided cost for oil of $114.63/bbl for 0.7 percent sulfur oil and $124.63/bbl for 

0.3 percent sulfur oil, and noting that the cost of per ton of emissions can be determined as (change in 

$/bbl / change in lb SO2/bbl) * 2000 lb/ton, the cost per ton of emissions to change from 0.7 percent 

fuel oil to 0.3 percent is $7,348/ton.

Step 5. Evaluate visibility impacts.

Using the CALPUFF air quality model indicates that the modeled baseline visibility impact 

using the current permit limit of 0.8 lb/MMBtu (which is assured by firing fuel oil containing 

0.7% sulfur) is 2.3 deciview (dv). The analysis also indicates that the total modeled visibility 

improvement considering 0.3% sulfur fuel would be 1.07 dv, for a modeled improvement of 1.23 

dv. The resulting average visibility improvement cost effectiveness is calculated at nearly $155 

million/dv. FPL concludes that this visibility improvement is extremely small for a very large 

cost, therefore, switching to 0.3% sulfur fuel is cost prohibitive.

Selection of BART

Because the cost of improvement is extremely high for switching to the 0.3% sulfur fuel, this 

option is cost prohibitive. FPL proposed that the current operating practice of using 0.7% sulfur 

fuel oil burned alone, or co-fired with the requisite amount on natural gas in order to comply 

with the NSPS limit of 0.8 lb/MMBtu be considered as BART for SO2 emissions for Units 1 and 

2. DEP concurs. 

Review for NOX

Step 1. Identify all available retrofit control technologies.

The Martin Plant units are currently equipped with multiple NOX emissions control methods 

including: Flue gas recirculation, overfire air systems, staged combustion and low-NOX burners. 

The only available additional option identified in the FPL analysis was the addition of a selective 

catalytic reduction (SCR) system. 

Step 2. Eliminate technically infeasible options.

The FPL analysis did not identify any technically infeasible options.

Step 3. Evaluate control effectiveness of remaining control technologies.

Using the direct and indirect capital costs and the operation and maintenance costs for a SCR 

system from a study conducted in 2006 for Martin Units 1 and 2, a BART cost effectiveness 

calculation was performed. A pollution control efficiency of 90 percent was used for the SCR 

system.

Step 4. Evaluate impacts and evaluate the results.

Considering the minimal impact on visibility from the reduction of NOX, the further addition of 

add-on controls, it is not reasonable to expend resources on additional NOX reductions. To show 

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how expensive additional NOX control could be, the option of adding a selective catalytic 

reduction (SCR) system was evaluated. A selective catalytic reduction (SCR) system, will 

require a direct capital investment of approximately $100 million per unit. Using the direct and 

indirect capital costs and the operation and maintenance costs for a SCR system from a study 

conducted in 2006 for Martin Units 1 and 2, a BART cost effectiveness of $5,323 per ton was 

calculated.

Step 5. Evaluate visibility impacts.

Based on the CALPUFF modeling results, only 6 to 7 percent of the total visibility impact on the 

closest class 1 area is attributable to the NOX emissions from these units. The visibility 

improvement was estimated at 0.15 deciviews, resulting in the visibility cost effectiveness of

approximately $203 million per deciview. This is a very large cost for a very small reduction in 

visibility impact. FPL’s opinion was that a SCR is not cost-effective BART for NOX emissions 

for Units 1 and 2.

Selection of BART

FPL proposed that the existing NOX reduction practices in use, which consist of flue gas 

recirculation, overfire air systems, staged combustion and low-NOX burners low NOX burners, 

and good combustion practices, be considered as BART for NOX emissions for Units 1 and 2. 

DEP concurs.

Review for PM

Step 1. Identify all available retrofit control technologies.

FPL identified ESP as a possible retrofit control for these units. 

Step 2. Eliminate technically infeasible options.

The FPL analysis did not identify any technically infeasible options.

Step 3. Evaluate control effectiveness of remaining control technologies.

ESP’s are common particulate controls on utility boilers with control effectiveness 98 percent. 

FPL currently has future plans to install electrostatic precipitators (ESP) for the purpose of 

controlling PM. Capital cost of each unit is approximately $55.6 million. Installation dates are 

expected to be in 2014.

Step 4. Evaluate impacts and evaluate the results.

Records of actual reported annual emissions reveal that PM emissions from Unit 1 for 2010 were 

311 tons, and from Unit 2 were 247 tons. Assuming a collection efficiency of 98% for an ESP, 

these emissions could be reduced by a total of 547 tons for the year, assuming the equipment is 

installed. This results in a ratio of $111.2 million/547 tons reduced = $203,000/ton reduced of 

PM for the first year. Assuming operation of the ESP equipment for 10 years drops the ratio to 

$20,300/ton per year. This result assumes the capital cost is amortized over the 10 years. This 

calculation also assumes no maintenance and operating costs which, of course, is unrealistic. 

Therefore, the addition of ESP’s to these units is not considered cost effective pursuant to the 

BART review process.

Step 5. Evaluate visibility impacts.

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The baseline CALPUFF visibility modeling showed that only 4 to 6 percent of the total visibility 

degradation from Martin is due to PM emissions from Martin. This translates into less than 0.1 

deciview impact at any of the Class I areas. The FPL analysis concluded that control of PM 

emissions will not provide a meaningful reduction in visibility impacts due to units 1 and 2. 

Conclusion

Considering the above analysis, DEP has determined that the levels of controls already in place 

for the affected pollutants SO2, NOX and PM are consistent with BART for the Martin Plant. 

Additional control strategies are not cost-effective and are not required. Emissions units 1 and 2 

at the FPL Martin Plant meet the BART requirements by continuing to comply with the 

following operational and emission limiting standards:

SO2: 0.80 lb/MMBtu when firing liquid fossil fuel, met by firing natural gas, co-firing natural 

gas with fuel oil containing less than 1% sulfur, or firing fuel oil alone containing less than 

0.7% sulfur. Compliance demonstrated by continuous emissions monitoring systems 

(CEMS). [40 CFR 60, Subpart D]

NOX: 0.2 lb/MMBtu when firing natural gas, 0.3 lb/MMBtu when firing fuel oil, pro-rated 

based on heat input when co-firing gas and oil. Limits are met through the use of flue gas 

recirculation, overfire air systems, staged combustion and low-NOX burners. Compliance 

demonstrated by continuous emissions monitoring systems (CEMS). [40 CFR 60, Subpart 

D]

PM: 0.1 lb/MMBtu when firing fuel oil. Limit met by firing natural gas, co-firing natural gas 

with fuel oil containing less than 1% sulfur, or firing fuel oil alone containing less than 0.7% 

sulfur, and through the use of multi-cyclones (mechanical dust collectors) and fly ash 

reinjection. Compliance demonstrated by stack tests when fuel oil is fired for more than 400 

hours annually. [40 CFR 60, Subpart D]

7.8.4.9 FPL Manatee

BART-eligible Emissions Units for the Manatee Power Plant

This facility consists of two oil and natural gas fired conventional steam electric generating units

(Units 1 and 2), “4 on 1” gas-fired combined cycle unit (Unit 3A-3D) and miscellaneous 

insignificant emissions units. The Manatee Plant is located at 19050 State Road 62, Parrish, 

Florida, in Manatee County. 

The facility operates the following emissions units subject to the requirements of the federal 

Regional Haze BART regulations: Unit 1 (EU001) and Unit 2 (EU002). Units 1 and 2 are fossil 

fuel fired steam electric generators consisting of boiler/steam generators which drive single 

reheat turbine generators, and are equipped with electrostatic precipitators, flue gas recirculation 

system, reburn and staged combustion. Units 1 and 2 are each nominal 800 MW (900 MW gross 

capacity).

Affected Pollutants

The affected (i.e., visibility-impairing) pollutants for this project are: sulfur dioxide (SO2), 

nitrogen oxides (NOX) and particulate matter (PM). 

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Project Description and Status

Review for SO2

Step 1. Identify all available retrofit control technologies.

The options presented by FPL for SO2 control included (1) use of low sulfur fuel, and (2) flue 

gas desulfurization (FGD), including dry sorbent injection. Two grades of low sulfur fuel oil are 

discussed: 0.3% and 0.7%. These units are subject to the NSPS Subpart D limit of 0.8 lb pound 

of SO2 per million British thermal units (lb/MMBtu) when firing fuel oil. FPL fires blends of 

natural gas and/or fuel oil as needed in order to comply with this SO2 limit.

Low Sulfur Fuel. Units 1 and 2 currently burn natural gas, distillate (No. 2) or residual (No. 6) 

fuel oil. The sulfur content of residual oil available in the marketplace can range from 0.3 

percent to more than 2 percent. 

Switching to a lower-sulfur fuel oil can reduce SO2 emissions; however, the cost of 

implementing the change depends on both the product price difference and the difference in 

delivery cost (if any). The refined oil products that are readily available to the Manatee Plant

include 0.3% and 0.7% sulfur grades. The total annual cost of switching Units 1 and 2 from the 

fuel currently used to 0.7% sulfur fuel oil is more than $85 million, and from the fuel oil 

currently used to 0.3% sulfur fuel oil is more than $240 million.

The use of a lower sulfur fuel (i.e., switch from 1.0 % to 0.7% or 0.3% sulfur grade) is 

considered to be a technically feasible option to reduce SO2 emissions due to the zero capital 

recovery cost and no capital investment only differential fuel cost. 

Step 2. Eliminate technically infeasible options.

Flue Gas Desulfurization. The BART analysis submitted by FPL discussed various postcombustion control technologies that rely on chemical reactions within the control device to 

reduce the concentration of SO2 in the flue gas. These included the calcium-based wet 

lime/limestone FGD system and dry FGD systems (e.g., dry sorbent injection). The analysis

points out that use of post-combustion controls are typically applied to coal-fired boilers and not 

to oil-fired units due to chemical reaction technology considerations and efficiencies. This fact, 

coupled with high capital costs (ranging between $40 and $100 million), led FPL to the 

conclusion that installation of a FGD system would be cost prohibitive. This option was 

therefore rejected in the BART analysis. 

FPL provided detailed cost information but cautioned for illustrative purposes generic wet-FGD 

cost estimates have been developed. Annualized costs are based on cost information provided in 

EPA’s Integrated Planning Model (IPM) Base Case v. 4.10 (9-1-2010) for Transport Rule; 

Documentation; Chapter 5, Emission Control Technologies, Table 5-4. These costs are 

extremely high without even considering additional retrofit costs that is expected for adding 

FGD systems at Manatee. It may not even be possible or technically feasible to construct wetFGD system at Manatee without major demolition efforts that would affect the continued 

operation of these units.” DEP agrees that wet or dry FGD systems are typically used for coalfired boilers and not oil/gas-fired boilers.

Step 3. Evaluate control effectiveness of remaining control technologies.

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The FPL analysis states that the effectiveness of SO2 emissions control using lower sulfur fuel 

depends on product availability and economic feasibility. Switching from 1.0 % sulfur fuel oil to

0.7% or 0.3% sulfur fuel oil is a method that can result in lower emissions of SO2 with no added 

capital investment. 

Step 4. Evaluate impacts and evaluate the results.

Cost of Compliance - Fuel Cost

Based on the information provided by FPL, the current 1.0% sulfur fuel cost is $109.05 per 

barrel (bbl) (42 gallons). The analysis indicates that the current cost of 0.7% sulfur fuel oil is 

$114.63 bbl, and the current cost of 0.3% sulfur fuel oil is $124.63 bbl. No other cost 

components (e.g., equipment, operation, and maintenance) are expected to be affected if the 

switch to lower sulfur fuel is made. Using appropriate heat input and hours of operation results 

in a cost differential of $87,181,773 for 0.7% sulfur fuel oil and $243,421,511 for 0.3% sulfur 

fuel oil.

Cost Effectiveness

Based on company data, the “pounds of SO2 in a barrel of oil” is as follows: (8.1 lb/gal *42 

gal/bbl*2 lb SO2/lb S* fraction of S in oil); thus, at 1.0 percent sulfur fuel oil =6.804 lb SO2/bbl, and 

at 0.7 percent sulfur oil = 4.763 lb SO2/bbl and at 0.3 percent sulfur oil = 2.041 lb SO2/bbl.

Given the company-provided cost for oil of $109.05/bbl for 1.0 percent sulfur oil, $114.63/bbl for 0.7 

percent sulfur oil, and $124.63/bbl for 0.3 percent sulfur oil, and noting that the cost of per ton of 

emissions can be determined as (change in $/bbl / change in lb SO2/bbl) * 2000 lb/ton, the cost per 

ton of emissions to change from 1 percent fuel oil to 0.7 percent is $5,468/ton, the cost per ton to 

change from 1 percent to 0.3 percent is $6,542/ton, and the cost per ton of emissions to change from 

0.7 percent fuel oil to 0.3 percent is $7,348/ton.

Step 5. Evaluate visibility impacts.

Using the CALPUFF air quality model indicates that the modeled baseline visibility impact 

using the current permit limit (firing fuel oil containing 1.0% sulfur) is 4.07 deciview (dv). The 

analysis also indicates that the total modeled improvement in visibility considering 0.7 % sulfur 

fuel would be 0.87 dv and 0.3% sulfur fuel would be 2.38 dv. The resulting average visibility 

improvement cost effectiveness is calculated at nearly $100 million/dv burning 0.7% sulfur fuel 

and $102 million/dv burning 0.3% sulfur fuel. FPL concludes that this visibility improvement is 

extremely small for a very large cost, therefore, switching to 0.3% sulfur fuel is cost prohibitive.

Selection of BART

Because the cost of improvement is extremely high for switching to the 0.3% sulfur fuel, this 

option is cost prohibitive. FPL proposed that the switch from the current 1.0% sulfur fuel to 

0.7% sulfur fuel oil burned alone, or co-fired with the requisite amount on natural gas in order to 

comply with the NSPS limit of 0.8 lb/MMBtu be considered as BART for SO2 emissions for 

Units 1 and 2. DEP concurs. 

Review for NOX

Step 1. Identify all available retrofit control technologies.

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The Manatee Plant units are currently equipped with multiple NOX emissions control methods 

including: Flue gas recirculation, overfire air systems, staged combustion, low-NOX burners and 

reburn. The only available additional option identified in the FPL analysis was the addition of a

selective catalytic reduction (SCR) system. 

Step 2. Eliminate technically infeasible options.

The SCR system is technically feasible.

Step 3. Evaluate control effectiveness of remaining control technologies.

Using the direct and indirect capital costs and the operation and maintenance costs for a SCR 

system from a study conducted in 2006 for Manatee Units 1 and 2, a BART cost effectiveness 

calculation was performed. The annualized cost of the purchase and operation of an SCR system 

on both units is calculated as $31M. A pollution control efficiency of 90 percent was used for 

the SCR system. With this efficiency, a NOx reduction of 8,229 tons per year would occur. This 

results in a cost effectiveness of $3,776/ton.

Step 4. Evaluate impacts and evaluate the results.

Based on the modeling results, only 6 to 17 percent of the total visibility impact on the closest 

Class I area is attributable to the NOX emissions from these units. Considering the minimal 

impact on visibility from the reduction of NOX, the further addition of add-on controls, FPL 

believes it is not reasonable to expend resources on additional NOX reductions. To show how 

expensive additional NOX control could be, the option of adding a selective catalytic reduction

(SCR) system was evaluated.

Step 5. Evaluate visibility impacts.

Based on a capital expenditure of approximately $100 million per unit and annual operating costs 

of roughly $6 million, the analysis indicated that, “the visibility cost effectiveness is 

approximately $66 million per deciview ... this is a very large cost for an insignificant amount of 

reduction in visibility impact.” FPL’s concludes, a SCR is therefore not cost effective as BART 

for NOX emissions for Units 1 and 2

Selection of BART

FPL proposed that the existing controls of low NOx burners, reburn, overfire air system, staged 

combustion, and flue gas recirculation along with good combustion practices, be considered as 

BART for NOX emissions for Units 1 and 2. DEP concurs.

Review for PM

Step 1. Identify all available retrofit control technologies.

FPL has been permitted to remove the existing cyclones with ESPs for the purpose of controlling PM 

emissions from Units 1 and 2. The in-service dates for the ESPs for Units 1 and 2 are the third quarter of 

2012 and fourth quarter of 2013, respectively. Permit No. 0810010-016-AC also requires a stricter PM 

emissions standard for Units 1 and 2. ESP’s are generally considered to be the top-level control for 

PM emissions from electric utility boilers. As such, no additional retrofit technologies were 

considered.

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Step 2. Eliminate technically infeasible options.

The FPL analysis did not identify any technically infeasible options.

Step 3. Evaluate control effectiveness of remaining control technologies.

Because the top-level control technology is being installed, no additional control strategies were 

evaluated.

Step 4. Evaluate impacts and evaluate the results.

Because the top-level control technology is being installed, no additional control strategies were 

evaluated.

Step 5. Evaluate visibility impacts.

The analysis concluded that additional control of PM emissions will not provide a meaningful 

reduction in visibility impacts due to units 1 and 2. FPL proposes the ESP’s are the BART for 

PM emissions from Units 1 and 2. DEP concurs. 

Conclusion

Considering the above analysis, DEP has determined that the levels of controls already in place, 

or soon to be in place, for the affected pollutants NOX and PM are consistent with BART for the 

FPL Manatee Plant. Additional control strategies are not cost-effective and are not required. 

DEP has also determined SO2 emissions and visibility impacts can be further reduced by 

switching from 1.0% sulfur fuel oil to 0.7% sulfur fuel oil alone or co-fired with natural gas. 

FPL has recently submitted a permit application to DEP asking for a natural gas capacity 

increase from 5,670 MMBtu/hr to 8,650 MMBtu/hr, which is equivalent to the oil-firing permit 

capacity. This alone will reduce SO2, PM, and NOx emissions from Units 1 and 2. FPL Manatee 

Plant Units 1 and 2 meet the BART requirements by recent upgrades to the emission units and 

firing a 0.7% sulfur fuel oil. The following operational and emission limiting standards for FPL 

Manatee Units 1 and 2 are:

SO2: Sulfur dioxide emissions rate from each fossil fuel fired steam electric generator Units 1 

and 2 shall not exceed 0.80 lb/MMBtu during any rolling 12 months. 

[Application No. 0810010-017-AC and Rule 62-210.200(PTE), F.A.C.]

NOX: Emissions shall not exceed 0.3 lb/MMBtu. Limits are met through the use of flue gas 

recirculation, overfire air systems, reburn, staged combustion and low-NOX burners. 

Compliance demonstrated by continuous emissions monitoring systems (CEMS). [40 CFR 

60, Subpart Da]

PM: Emissions shall not exceed 0.03 lb/MMBtu during normal operation. Compliance 

demonstrated by stack test. [40 CFR 60, Subpart Da]

7.8.4.10 Lakeland Electric McIntosh

Unit 1 is a pre-NSPS boiler with a nominal rating of 985 MMBtu/hr heat input (natural gas) and 

90 MW and is fired by natural gas and fuel oil. It has no pollution controls. Unit 2 is a NSPS 

Subpart D boiler with a nominal rating of 1,185 MMBtu/hr heat input (natural gas) and includes 

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flue gas recirculation (FGR) for NOX controls and no add-on PM controls. The C.D. McIntosh 

Jr. Power Plant is located at 3030 East Lake Parker Drive in Lakeland, Polk County. 

Affected Pollutants

The affected (i.e., visibility-impairing) pollutants for this project are: sulfur dioxide (SO2), 

nitrogen oxides (NOX) and particulate matter (PM). 

Project Description and Status

Lakeland Electric (LE) submitted a BART applicability determination to DEP to address the BART 

requirements. The following sections describe site specific conditions which are considered in making 

DEP’s BART determination.

There are three PSD Class I areas located within 300 km of the McIntosh facility: 

• Chassahowitzka National Wilderness Area (NWA) – 91 km 

• Everglades National Park (NP) – 249 km 

• Okefenokee NWA – 277 km 

The analysis was performed for only the Chassahowitzka NWA, which is the nearest and the 

only Class I area where the visibility impacts were predicted to be higher than 0.5 dv.

Review for SO2

Step 1. Identify all available retrofit control technologies.

The options presented by LE for SO2 control included (1) use of low sulfur fuel, and (2) flue gas 

desulfurization (FGD), including dry sorbent injection. Unit 2 is currently limited to 0.7% fuel 

oil and LE staff evaluated the option of utilizing this low sulfur fuel oil in Unit 1. Unit 1 is 

subject to the Florida SIP limit of Rule 62-296.405(1)(c)1.a F.A.C. which limits emissions to 

2.75 pound of SO2 per million British thermal units (lb/MMBtu) when firing fuel oil. Also, the 

upcoming Utility MACT discussed in the previous section effectively limits the operation of 

Units 1 and 2 to approximately an 8% capacity factor on fuel oil (starting in 2015). 

Low Sulfur Fuel Option: Unit 1 currently burns natural gas and fuel oil. The sulfur content of 

residual fuel oil available in the marketplace can range from 1 percent to more than 2 percent. 

The facility’s Title V permit contains the following requirements concerning fuel oil: For Unit 1, 

the sulfur content of the as-fired No. 6 fuel oil shall not exceed 2.5 percent, by weight if the SO2

continuous emissions monitor system is not used for compliance. Switching to a lower-sulfur 

fuel oil can reduce SO2 emissions; however, the cost of implementing the change depends on 

both the product price difference and the difference in delivery cost (if any). The refined oil 

products evaluated for the McIntosh plant Unit 1 was 0.7% sulfur grade fuel oil (which is the 

same grade of fuel used in the newer boiler, Unit 2). 

The use of a lower sulfur fuel (i.e., switch from 2.5 % to 0.7% sulfur grade) is considered to be a 

technically feasible option to reduce SO2 emissions. 

Step 2. Eliminate technically infeasible options.

Flue Gas Desulfurization. The BART analysis submitted by LE discussed various postcombustion control technologies that rely on chemical reactions within the control device to 

reduce the concentration of SO2 in the flue gas. These included the calcium-based wet 

155
lime/limestone FGD system and dry FGD systems (e.g., dry sorbent injection). The analysis 

points out that use of post-combustion controls are typically applied to coal-fired boilers and not 

to oil-fired units due to chemical reaction technology considerations and efficiencies. 

DEP agrees that add-on controls like FGD in this case is not a viable option for Unit 1 or Unit 2 

which will have a limited capacity factor (effectively 8%) for fuel oil. Comparable oil and gas 

fired boilers do not employ add-on sulfur controls for BACT, but rather utilize low sulfur fuel oil 

as a means of reducing emissions. Again, it may not even be possible or technically feasible to 

construct wet-FGD system at the existing McIntosh units without major demolition efforts that 

would affect the continued operation of these units. DEP agrees that wet or dry FGD systems are

typically used for coal-fired boilers, and are not considered appropriate technology for oil/gasfired boilers like McIntosh Units 1 and 2.

Step 3. Evaluate control effectiveness of remaining control technologies.

The LE analysis states that the effectiveness of SO2 emissions control using lower sulfur fuel 

depends on product availability and economic feasibility. Switching from 2.5 % sulfur fuel oil to 

0.7% sulfur fuel oil on Unit 1 is a control method that can result in lower emissions of SO2 with 

no added capital investment. Unit 2 currently is restricted by permit to 0.7% fuel oil. The 

reduction in sulfur content from 2.5% to 0.7% for Unit 1 has a control effectiveness that reduces 

emission by more than one half compared to the currently fired high sulfur fuel oil.

Step 4. Evaluate impacts and evaluate the results.

Cost of Compliance - Fuel Cost

The analysis indicates that the current cost of 2.5 % sulfur fuel oil is $19.65 per MMBtu 

compared to the current cost of 0.7% sulfur fuel oil at $21.87 per MMBtu of the fuel oil. No 

other cost components (e.g., equipment, operation, and maintenance) are expected to be affected 

if the switch to lower sulfur fuel is made. Using appropriate heat input and hours of operation 

data results in a cost differential of $8,345,694 annually.

Cost Effectiveness

Based on company data, the “pounds of SO2 per MMBtu” is as follows: (8.3 lb/gal / 0.15 

MMBtu/gal *2 lb SO2/lb S* fraction of S in oil); thus, at 2.5 percent sulfur fuel oil =2.767 lb 

SO2/MMBtu, and at 0.7 percent sulfur oil = 0.775 lb SO2/MMBtu.

Given the company-provided cost for oil of $19.649/MMBtu for 2.5 percent sulfur oil, and 

$21.871/MMBtu for 0.7 percent sulfur oil, and noting that the cost of per ton of emissions can be 

determined as (change in $/MMBtu / change in lb SO2/MMBtu) * 2000 lb/ton, the cost per ton 

of emissions to change from 2.5 percent fuel oil to 0.7 percent is $2,231/ton.

Cost of Compliance – Scrubber

To develop a cost of wet-FGD for Units 1 and 2, information developed for the recent CSAPR 

was used. Capital, fixed operation and maintenance (O&M), and variable O&M are available on 

a dollar per kilowatt basis as part of EPA’s Integrated Planning Model (IPM) Base Case v. 4.10 

(September 1, 2010) for Transport Rule; Documentation; Chapter 5, Emission Control 

Technologies. These costs models were developed by engineering contractors such as Sargent & 

Lundy for the wet- FGD cost model. Additionally, cost factors from the EPA Cost Control 

Manual were used to costs not included in the EPA IPM cost model. Annualized costs were 

developed using the methodology in the EPA Cost Control Manual. This control alternative 

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allows the use of high sulfur fuel oil and assumes a 98-percent removal for the maximum annual 

SO2 emissions for Units 1 and 2 over the period 2001 through 2003. The annualized cost is 

$36.2 million with an average cost effectiveness of about $13,200 per ton of SO2 removed. 

It should be recognized that that the estimated costs are not specific to the McIntosh Plant nor the 

layout of Units 1 and 2. LE indicates that it may not be possible to install add-on SO2 equipment 

given the spatial constraints at the site. Notwithstanding, LE believes the cost effectiveness is 

extremely high and unreasonable as BART.

Step 5. Evaluate visibility impacts.

Using the CALPUFF air quality model indicates that the modeled baseline visibility impact 

using the current permit limit of 2.75 lb/MMBtu for Unit 1 (which is assured by firing fuel oil 

containing 2.5 % sulfur) and Unit 2 on low sulfur fuel oil is 1.62 deciview (dv). The analysis 

also indicates that the total modeled visibility improvement considering 0.7% sulfur fuel for 

Unit 1 would be a modeled improvement of 0.74 dv. The resulting average visibility 

improvement cost effectiveness is calculated at $11.3 million/dv. LE concludes that this 

visibility improvement is very small for a very large cost, therefore, switching to 0.7% sulfur 

fuel is cost prohibitive. LE has opted to utilize the low sulfur fuel oil in Unit 1 even at this high 

cost, to be consistent with the fuel used in Unit 1.

Selection of BART

LE proposed that new shipments of fuel oil for Unit 1 will be limited to 0.7% sulfur content, the 

same as in Unit 2 and proposed this low sulfur fuel oil control option for both units as BART. 

DEP concurs and establishes that new shipments of fuel oil shall be limited to 0.7% sulfur as this 

BART determination for Units 1 and 2. A federally enforceable permit condition assures this 

determination. 

Review for NOX

Step 1. Identify all available retrofit control technologies.

The McIntosh Plant Unit 1has no controls for NOX emission other than best operating practices 

for good combustion. As mentioned previously, Unit 2 has FGR controls for NOX and currently 

meets a relatively low permit limit for NOX of 0.2 lb/MMBtu. This is considered very good 

control for Unit 2. This analysis will therefore cover Unit 1 as the worst case for NOX controls. 

LE evaluated control methods including: Selective Catalytic Reduction (SCR) and Selective 

Non-Catalytic Reduction (SNCR). The temperature window for SNCR is very important 

because outside of it, either more NH3 slips through the system, or more NOx is generated than 

is being chemically reduced. NH3 slip has the potential to affect boiler operation as well as 

ammonium bisulfate formation on the downstream boiler components. SNCR is selective in that 

the reagent reacts primarily with NOX.

Step 2. Eliminate technically infeasible options.

SNCR has been demonstrated as a feasible NOx control technology for oil-fired boilers. 

However, an optimum temperature range is important for the SNCR reaction to occur and an 

engineering study must be conducted to learn the feasibility of SNCR systems for Units 1 and 2. 

Therefore the only available additional option identified in the LE analysis was the addition of a 

selective catalytic reduction (SCR) system.

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Step 3. Evaluate control effectiveness of remaining control technologies.

Control efficiency achieved by a SCR system is estimated to be 80 percent, on average. Control 

efficiency achieved by a SNCR system is estimated to be in the range 50 to 60 percent. SCR is 

assumed to be the top ranked add-on NOx control technology for Units 1 and 2. 

Step 4. Evaluate impacts and evaluate the results.

Using the direct and indirect capital costs and the operation and maintenance costs for a SCR 

system from the EPA Fact Sheet for NOx controls LE found that the capital costs and operational 

costs are relatively high. The annualized cost was found to be $2.7 million and the cost 

effectiveness of SCR was estimated to be $5,241/ton with a pollution control efficiency of 80 

percent for the system. The installation of SCR will result in a power requirement of about 0.6 

percent due to the backpressure of the SCR catalyst and auxiliaries. This is about 2,800 MWh per 

year of lost energy.

There would be some non-air quality impacts associated with the storage and handling of NH3. 

If anhydrous or aqueous 29 percent NH3 were used, a Risk Management Plan (RMP) under EPA 

rules to implement Section 112(r) of the CAA would be required. Using 19 percent NH3 or urea 

would not require an RMP. If 19 percent aqueous NH3 were used, the amount would be 994 

TPY for the maximum NOx reduction. This is about 238,000 gallons, requiring about 34 tanker 

loads per year.

There are no current plans for Unit 1 and 2’s retirement.

Step 5. Evaluate visibility impacts.

Based on the modeling results, only about 19% of the total visibility impact on the closest class I 

area is attributable to the NOX emissions from these units. Based on a capital expenditure and 

annual costs of approximately $2.7million/yr for Unit 1 or Unit 2 and operating and maintenance 

costs contributing to the annual cost of SCR controls, the analysis indicated that the visibility 

cost effectiveness is cost prohibitive and would exceed a cost effectiveness of $11 million per 

deciview for a visibility improvement of only 0.25 dv. This is a very large cost for a relatively 

small amount of reduction in visibility impact. 

Selection of BART

LE’s opinion was that a SCR is not cost-effective as BART for NOX emissions in this case. DEP

agrees and establishes that BART in this case is the current limit of 0.2 lb/MMBtu for NOX for 

Unit 2 and no add-on NOX control for Unit 1, but further purchase of fuel oil for this unit will be 

limited to no more than 0.7 percent sulfur.

Review for PM

These units don’t currently have add-on PM controls.

Step 1. Identify all available retrofit control technologies.

LE evaluated add-on controls including fabric filters, ESPs and wet scrubbers to control PM 

emissions.

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Step 2. Eliminate technically infeasible options.

The LE analysis identified fabric filters and wet scrubbers as technically infeasible options. The 

use of a fabric filter baghouse depends on site specific exhaust characteristics such as particulate 

loading, temperature, and moisture content. Condensation of moisture may cause crusty caking 

or plugging of the fabric or require special additives. There is also a potential fire hazard in a 

baghouse if a spark or flame is accidentally admitted. For large oil-fired boilers like the LE units 

the use of a fabric filter control device is not common. Also, the PM from firing fuel oil can be 

sticky which can cause problems with cleaning fabric filters. Likewise, wet scrubbers like 

Venturi scrubbers were evaluated although they are not commonly used for large oil fired units 

like Units 1 and 2. In this case the waste water disposal problem made this option infeasible for 

these units. Therefore the options of baghouse or wet scrubber are not found to be technically 

feasible in this case and the only feasible control option for PM was found to be an ESP.

Step 3. Evaluate control effectiveness of remaining control technologies.

An ESP control is considered to be the most common and technically feasible option for LE

units. ESPs are also ranked very high in terms of control efficiency greater than 99 percent. 

Other technologies have not demonstrated equivalent levels of control for PM compared to an 

ESP in this application.

Step 4. Evaluate impacts and evaluate the results.

The capital and annualized costs for an ESP are significant. The estimated costs were developed 

from information available from recent Golder projects and EPA’s cost control manual. The EPA 

cost control manual was also used where individual cost factors were required and to develop the 

annualized cost. The estimated annualized cost for ESP is about $3 million with a cost 

effectiveness of $65,865 per ton of PM removed. Other factors like operating costs and 

remaining useful life are shown below.

The installation of ESP will result in a power usage of about 0.3 percent due to electric field 

current usage and backpressure. This is about 1,400 MWh per year of lost energy. 

There would be some non-air quality impacts associated with the disposal of ash that would have 

to be disposed of at a Class I landfill. 

As reported by LE, there are no current plans for Unit 1 or 2 retirement and the current 

authorizations/permits limit operation on fuel oil for these units beginning in 2015. 

Installation of an ESP would require about two years for construction based on experience from 

recent retrofit projects. It is therefore apparent to DEP, based on the costs and the limited use of 

fuel oil for Unit 1 and 2, that the addition of an ESP is not considered cost effective after 

evaluating these unit specific factors.

Step 5. Evaluate visibility impacts.

LE modeling found that PM only contributes about 5% of the total visibility impact from Units 1and 2. 

To calculate the visibility improvement due to controlling PM using an ESP, first the baseline visibility 

impacts were estimated based on the maximum 8th highest 24-hour average visibility impact contributed 

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by PM particles (1.617 dv for 2002 with 6.2% contribution from PM). Instead of modeling the reduced 

PM emission rate, future or controlled visibility impacts were estimated based on the baseline visibility 

impact and the ratio of reduced hourly PM emissions rate and the baseline hourly PM emission rate. The 

reduced PM emission rate was estimated based on a potential emission rate of 0.03 lb/MMBtu and the 

heat input capacity of Unit 1and 2. Visibility improvements were determined by subtracting future dv 

impacts from the baseline dv impacts. 

The visibility cost effectiveness numbers were calculated from the annual costs and the visibility 

improvement in dv. Visibility cost effectiveness for an ESP is more than $41.7 million/dv (visibility 

improvement 0.07 dv) This is a very large cost for an small amount of visibility improvement. 

As the pollutant and visibility cost effectiveness values above indicate, the cost of adding an ESP to either 

unit is extremely high for a very small improvement in visibility. As a result, it is concluded that adding 

additional PM controls is cost prohibitive and LE proposes the existing PM emissions limits as BART 

limits for Unit 1 and 2. The existing PM emissions limits are 0.1 lb/MMBtu for normal operation and 0.3 

lb/MMBtu for soot-blowing operation on Unit 1 and Unit 2 has a limit of 0.1 lb/MMBtu at all times. 

Conclusion

Considering the above analysis, DEP has determined that limited use of 0.7% sulfur fuel oil and 

the levels of controls already in place for the affected pollutants SO2, NOX and PM are consistent 

with BART for the McIntosh Plant Units 1 and 2. Additional control strategies are not costeffective and are not required. Emissions Unit 1 at the Lakeland Electric McIntosh Plant 

currently meets the BART requirement by continuing to comply with the following operational 

and SIP emission limiting standards:

SO2: 0.80 lb/MMBtu when firing fuel oil, met by firing natural gas, co-firing natural gas with 

fuel oil, or firing fuel oil alone containing not more than 0.7 % sulfur. Compliance 

demonstrated by continuous emissions monitoring systems (CEMS).

NOX: 0.20 lb/MMBtu when firing natural gas or firing fuel oil for Unit 2 by use of the existing 

FGR controls. Compliance is demonstrated by continuous emissions monitoring systems 

(CEMS). 0.46 lb/MMBtu for Unit 1 when firing natural gas, fuel oil, or used oil. 

PM: 0.1 lb/MMBtu when firing fuel oil and 0.3 lb/MMBtu for sootblowing for Unit 1 and 0.1 

lb/MMBtu for Unit 2 at all times. These limits are met by firing natural gas, co-firing natural 

gas with fuel oil, or firing fuel oil alone containing less than 0.7% sulfur.

7.8.4.11 JEA Northside

BART-eligible Emission Unit at the Northside Power Plant

The existing Boiler No. 3 is a pre-NSPS boiler with a nominal rating of 564 MW and fired by 

natural gas, landfill gas, No. 6 residual fuel oil, and used oil. Emissions from the NGS Boiler 

No. 3 are uncontrolled. The Northside Generating Station (NGS) Plant is located at 4377 

Heckscher Drive, Jacksonville, in Duval County. 

Affected Pollutants

The affected (i.e., visibility-impairing) pollutants for this project are: sulfur dioxide (SO2), 

nitrogen oxides (NOX) and particulate matter (PM). 

Project Description and Status

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JEA submitted a BART applicability determination to DEP to address the BART requirements. The 

following site specific conditions are considered in making DEP’s BART determination in this case:

Northside Unit 3 is located at a JEA power plant that has two other units which were repowered 

and converted to circulating fluidized bed boilers. These two units (Units 1 and 2) fire mainly 

petroleum coke and coal (about 10%) fuel blends. As part of the repowering of NGS Units 1 and 

2, JEA made a voluntary community commitment of reducing emissions of SO2, NOX and PM to 

10 percent below the 1994 and 1995 baseline years used in the permitting of the repowering 

project. This effectively reduced operation of Unit 3 when the new repowered units became 

operational. Based on the operation of Unit 3 on oil, the limiting pollutant is NOX, which is 

capped or limited by permit to 3,600 tons/year for Units 1, 2 and 3 over a 12-month rolling 

average. This limitation for NGS Units 1-3 is also a federally enforceable permit limit and 

contained in the Title V Permit No. 0310045-030-AV as Condition G.11.b. 

Based on the operation of Unit 3 in 2002, this annual limit for NOX limits the SO2 emission from 

oil firing to about 9,000 tons/year if Units 1 and 2 are not operating. This is equivalent to a 

capacity factor of about 21 percent at the authorized emission rate. If Units 1 and 2 are fully 

operational (the usual case), then Unit 3 is limited to a maximum of 3,506 tons/year based on the 

operational profile in 2002. This is equivalent to a capacity factor of about 8 percent at the 

authorized emission rate. As a result, and by virtue of the community commitment, and federally 

enforceable permit limits on annual emissions, the actual capacity factor of Unit 3 on oil is 

limited to approximately 8%. 

Review for SO2

Step 1. Identify all available retrofit control technologies.

JEA identified the following potential retrofit technologies for SO2 control (1) use of low sulfur 

fuel, and (2) flue gas desulfurization (FGD), including dry sorbent injection. This unit is subject 

to the Florida SIP limit of Rule 62-296.405(1)(c)1.a F.A.C. which limits emissions to 1.98 lb 

pound of SO2 per million British thermal units (lb/MMBtu) when firing fuel oil. 

Unit 3 currently burns natural gas, landfill gas, distillate (No. 2) or residual (No. 6) fuel oil or 

used oil. The sulfur content of residual fuel oil available in the marketplace can range from 1 

percent to more than 2 percent. The facility’s Title V permit contains the following requirements 

concerning fuel oil: “For Boiler No. 3, the sulfur content of the as-fired No. 6 fuel oil shall not 

exceed 1.8 percent, by weight, if the SO2 continuous emissions monitor system is temporarily 

inoperative.” Switching to a lower-sulfur fuel oil can reduce SO2 emissions; however, the cost of 

implementing the change depends on both the product price difference and the difference in 

delivery cost (if any). The refined oil products evaluated for the Northside plant was 1% sulfur 

grade fuel oil. 

The use of a lower sulfur fuel (i.e., switch from 1.8% to 1% sulfur grade) is considered to be a 

technically feasible option to reduce SO2 emissions. 

Step 2. Eliminate technically infeasible options.

Flue Gas Desulfurization. The BART analysis submitted by JEA (analysis) discussed various 

post-combustion control technologies that rely on chemical reactions within the control device to 

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reduce the concentration of SO2 in the flue gas. These included the calcium-based wet 

lime/limestone FGD system and dry FGD systems (e.g., dry sorbent injection). The analysis 

points out that use of post-combustion controls are typically applied to coal-fired boilers and not 

to oil-fired units due to chemical reaction technology considerations and efficiencies. 

DEP agrees that add-on controls like FGD in this case is not a viable option for Unit 3 which has 

a limited capacity factor (effectively 8%) for fuel oil. JEA listed the comparable BACT 

determinations for SO2 controls on oil and gas fired boilers and showed that none of the 

comparable oil and gas fired boilers employed add-on sulfur controls for BACT, but rather 

utilized low sulfur fuel oil as a means of reducing emissions. It may not even be possible or 

technically feasible to construct wet-FGD system at Northside without major demolition efforts 

that would affect the continued operation of this unit. DEP agrees with this finding. 

Step 3. Evaluate control effectiveness of remaining control technologies.

The JEA analysis states that the effectiveness of SO2 emissions control using lower sulfur fuel 

depends on product availability and economic feasibility. Switching from 1.8% sulfur fuel oil to 

1% sulfur fuel oil is a control method that can result in lower emissions of SO2 with no added 

capital investment. Control effectiveness is proportional to the fuel sulfur content. 

Step 4. Evaluate impacts and evaluate the results.

Cost of Compliance - Fuel Cost

The analysis indicates that the current cost of 1.8% sulfur fuel oil is $2.067 per gallon compared 

to the current cost of 1% sulfur fuel oil at $2.54 per gallon. No other cost components (e.g., 

equipment, operation, and maintenance) are expected to be affected if the switch to lower sulfur 

fuel is made. Using appropriate heat input and hours of operation data results in a cost 

differential of $33,681,924 annually.

Cost Effectiveness

Based on company data, the “pounds of SO2 in a gallon of oil” is as follows: (8.3 lb/gal *2 lb 

SO2/lb S* fraction of S in oil); thus, at 1.8 percent sulfur fuel oil =0.2988 lb SO2/gal, and at 1.0 

percent sulfur oil = 0.1660 lb SO2/gal.

Given the company-provided cost for oil of $2.067/gal for 1.8 percent sulfur oil, and $2.544/gal 

for 1.0 percent sulfur oil, and noting that the cost of per ton of emissions can be determined as 

(change in $/gal / change in lb SO2/gal) * 2000 lb/ton, the cost per ton of emissions to change 

from 1.8 percent fuel oil to 1.0 percent is $7,184/ton.

Step 5. Evaluate visibility impacts.

Using the CALPUFF air quality model indicates that the modeled baseline visibility impact 

using the current permit limit of 1.98 lb/MMBtu (which is assured by firing fuel oil containing 

1.8% sulfur) is 3.61 deciview (dv). The analysis also indicates that the total modeled visibility 

improvement considering 1% sulfur fuel would be a modeled improvement of 1.08 dv. The 

resulting average visibility improvement cost effectiveness is calculated at $31.1 million/dv. 

JEA concludes that this visibility improvement is extremely small for a very large cost, therefore, 

switching to 1% sulfur fuel is cost prohibitive.

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Selection of BART

Because the cost of improvement is relatively high for switching to the 1% sulfur fuel, this 

option is deemed cost prohibitive. JEA proposed that the current operating practice of using no 

more than 1.8% sulfur fuel oil burned alone, or higher sulfur fuel oil co-fired with the requisite 

amount on natural gas in order to comply with the SIP limit of 1.98 lb/MMBtu be considered as 

BART for SO2 emissions for Unit 3 at Northside. DEP concurs. 

Review for NOX

Unit 3 is currently equipped with Low-NOx Burners (LNB) NOx control technology.

Step 1. Identify all available retrofit control technologies.

JEA evaluated control methods including: Selective Catalytic Reduction (SCR) and Selective 

Non-Catalytic Reduction (SNCR). The temperature window for SNCR is very important 

because outside of it, either more NH3 slips through the system, or more NOx is generated than 

is being chemically reduced. NH3 slip has the potential to affect boiler operation as well as 

ammonium bisulfate formation on the downstream boiler components. SNCR is selective in that 

the reagent reacts primarily with NOX.

Step 2. Eliminate technically infeasible options.

The use of SNCR was not found to be feasible after JEA conducted a feasibility study on this 

unit and found that the temperature window for the conversion reaction of SNCR was not 

available on this unit. The only available additional option identified in the JEA analysis was 

the addition of a selective catalytic reduction (SCR) system

Step 3. Evaluate control effectiveness of remaining control technologies.

SCR NOx control effectiveness is nominally reviewed at 80 percent, typical of these units. At 

the 80 percent control level, emission reductions of NOx from Unit 3 would be approximately 

1,137 tons annually. This value is based on the base load operation of Units 1 and 2 at this 

facility since the three units have a total emissions cap of 3,600 tons per year. 

Step 4. Evaluate impacts and evaluate the results.

Using the direct and indirect capital costs and the operation and maintenance costs for a SCR 

system from the EPA Fact Sheet for SO2 controls JEA found that the capital costs would be as 

much as $30 million dollars for this unit that currently fires mainly natural gas, a fuel with lower 

NOX emissions compared to fuel oil, and the unit currently meets a SIP limit of 0.3 lbs/MMBtu 

for NOX. The cost effectiveness of SCR was estimated to exceed $4500 /ton with a pollution 

control efficiency of 80 percent for the system.

Step 5. Evaluate visibility impacts.

Improvement in visibility, based on air quality modeling, with the inclusion of an SCR control is 

approximately 0.26 deciviews. Based on a capital expenditure of approximately $30 million for 

Unit 3 and operating and maintenance costs contributing to the annual cost of SCR controls, the 

analysis indicated that the visibility cost effectiveness is cost prohibitive and would exceed a cost 

effectiveness of $20 million per deciview. This is a large cost for the amount of improvement in 

visibility. JEA’s conclusion was that a SCR is therefore not cost-effective as BART for NOX

emissions in this case. 

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Selection of BART

Considering the relatively small impact on visibility from the reduction of NOX compared to SO2

in this case, JEA concluded that add-on controls are cost prohibitive and it is not reasonable to 

expend resources on additional NOX reductions in this case. DEP agrees that no add on NOX

controls are justified in this case for Unit 3 that mainly fires natural gas and meets a SIP limit of 

0.3 lbs/MMBtu for NOX.

Review for PM

Step 1. Identify all available retrofit control technologies.

JEA evaluated add-on controls including fabric filters, ESPs and wet scrubbers to control PM 

emissions.

Step 2. Eliminate technically infeasible options.

The JEA analysis identified fabric filters and wet scrubbers as technically infeasible options. 

The use of a fabric filter baghouse depends on site specific exhaust characteristics such as 

particulate loading, temperature, and moisture content. Condensation of moisture may cause 

crusty caking or plugging of the fabric or require special additives. There is also a potential fire 

hazard in a baghouse if a spark or flame is accidentally admitted. For large oil-fired boilers like 

the NGS Unit 3, the use of a fabric filter control device is not common. Also, the PM from firing 

fuel oil can be sticky which can cause problems with cleaning fabric filters. Likewise, wet 

scrubbers like Venturi scrubbers were evaluated although they are not commonly used for large 

oil fired units like Unit 3. In this case the waste water disposal problem and the relatively high 

operating and maintenance costs made this option infeasible for Unit 3. Therefore the options of 

baghouse or wet scrubber are not found to be technically feasible in this case.

Step 3. Evaluate control effectiveness of remaining control technologies.

An ESP control is considered to be the most common and technically feasible option for NGS 

Unit 3. ESPs are also ranked very high in terms of control efficiency greater than 99 percent. 

Other technologies have not demonstrated equivalent levels of control for PM compared to an 

ESP in this application. The potential reduction in PM emissions is estimated to be 449 tons per 

year.

Step 4. Evaluate impacts and evaluate the results.

The estimated costs were developed from information available from recent Golder projects and 

EPA’s cost control manual. The EPA cost control manual was also used where individual cost 

factors were required and to develop the annualized cost. JEA estimated the total capital cost of

an ESP at approximately $60 million. The estimated annualized cost for ESP is about $8.1 

million with a cost effectiveness of $18,083 per ton of PM removed. However considering the 

limited use of fuel oil under the JEA community commitment (federally enforceable limit/cap on 

emissions), the cost effectiveness is actually about $29,000 per ton of PM removed. Other 

factors like operating costs and remaining useful life are shown below.

The installation of ESP will result in a power usage of about 0.3 percent due to electric field 

current usage and backpressure. This is about 3,600 MWh per year of lost energy. 

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There would be some non-air quality impacts associated with the disposal of ash. From 148 to 63 

tons of fly ash would have to be disposed of at a Class I landfill. 

As reported by JEA, there are no current plans for Unit 3’s retirement and the current 

authorizations/permits limit operation on fuel oil for this 35 year old unit. Installation of an ESP 

would require about two years for construction based on experience from recent retrofit projects

Step 5. Evaluate visibility impacts.

To calculate the visibility improvement due to controlling PM using an ESP, first the baseline visibility 

impacts were estimated based on the maximum 8th highest 24-hour average visibility impact contributed 

by PM particles (3.611 dv for 2003). The PM fraction accounted for 5 percent of the total or 0.18 dv. 

Instead of modeling the reduced PM emission rate, future or controlled visibility impacts were estimated 

based on the baseline visibility impact and the ratio of reduced hourly PM emissions rate and the baseline 

hourly PM emission rate. The reduced PM emission rate was estimated based on a potential emission rate 

of 0.03 lb/MMBtu and the heat input capacity of Unit 3. The visibility improvement associated with an 

ESP was determined by subtracting future dv impacts from the baseline dv impacts. The estimated 

improvement is 0.10 dv. 

The visibility cost effectiveness numbers were calculated from the annual costs and the visibility 

improvement in dv. Visibility cost effectiveness for an ESP is more than $78 million/dv JEA concludes 

that this is a very large cost for a small amount of visibility improvement. 

Conclusion

Considering the above analysis, DEP has determined that limited use of fuel oil and the levels of 

controls already in place for the affected pollutants SO2, NOX and PM are consistent with BART 

for the Northside Plant Unit3. Additional control strategies are not cost-effective and are not 

required. Emissions Unit 3 at the JEA Northside Plant will meet the BART requirement by 

continuing to comply with the following operational and SIP emission limiting standards:

SO2: 1.98 lb/MMBtu when firing fuel oil, met by firing natural gas, co-firing natural gas with 

fuel oil, or firing fuel oil alone containing not more than 1.8% sulfur. Compliance 

demonstrated by continuous emissions monitoring systems (CEMS).

NOX: 0.30 lb/MMBtu when firing natural gas or firing fuel oil. Limits are met through the use 

of best operating practices for good combustion. Compliance is demonstrated by continuous 

emissions monitoring systems (CEMS). 

PM: 0.1 lb/MMBtu when firing fuel oil and 0.3 lb/MMBtu for sootblowing. These limits are 

met by firing natural gas, co-firing natural gas with fuel oil, or firing fuel oil alone containing 

less than 1.8% sulfur.

7.8.4.12 Gulf Power Smith

BART-eligible Emissions Units for the Gulf Power Lansing Smith Plant

This facility consists of two coal-fired steam generators (Units 1 and 2), two simple cycle 

peaking units, two combined cycle combustion turbines, and miscellaneous insignificant 

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emissions units. The Lansing Smith Plant is located at 4300 County Road 2300, Southport, 

Florida, in Bay County. 

The facility operates the following emissions units subject to the requirements of the federal 

Regional Haze BART regulations: Unit 1 (EU001) and Unit 2 (EU002). Units 1 and 2 are 

tangentially-fired, dry-bottom boilers, and both are equipped with hot and cold side electrostatic 

precipitators (ESP) and selective non-catalytic reduction (SNCR). Unit 1 is also equipped with 

low NOx burners (LNB) with high momentum injection ports, and Unit 2 has LNB with an 

overfire air control system. 

DEP asked Gulf Power to provide a proposed BART determination for these units. We have 

reviewed Gulf Power’s proposal and have used it as we deemed appropriate in making DEP’s 

BART determination.

Affected Pollutants

The affected (i.e., visibility-impairing) pollutants for this project are: sulfur dioxide (SO2), 

nitrogen oxides (NOX) and particulate matter (PM). 

Project Description and Status

Gulf Power submitted a BART analysis to DEP to address the BART requirements. 

Review for SO2

Step 1. Identify all available retrofit control technologies.

The options presented by Gulf Power for SO2 control included (1) switch to lower sulfur coal, 

(2) dry sorbent injection (DSI) with use of lower sulfur coal, (3) dry flue gas desulfurization 

(DFGD) lime spray dryer absorber (SDA), and (4) wet flue gas desulfurization (WFGD). All of 

the identified available retrofit SO2 control technologies are considered technically feasible for 

Units 1 and 2. 

Low Sulfur Coal. Units 1 and 2 currently burn coal, distillate (No. 2) or on-specification used 

fuel oil. No. 2 fuel oil is only used during start-up and flame stabilization. Combustion of onspecification used oil is limited to no more than 50,000 gallons per calendar year per boiler. Unit 

1 has maximum authorized heat input rates of 1,944.8 MMBtu/hr for coal, and 153 MMBtu/hr 

for No. 2 fuel oil and on-specification used oil. Maximum authorized heat input rates for Unit 2 

are 2,246.2 MMBtu/hr for coal and 76 MMBtu/hr for No. 2 fuel oil and on-specification used oil. 

Switching to a lower-sulfur fuel, such as coal will reduce SO2 emissions compared to baseline 

coal, with no modifications to the emission units.

Dry Sorbent Injection with the use of Low Sulfur Coal. DSI is a DFGD technology that uses an 

alkaline reagent to absorb SO2. Gulf Power proposes the use of trona, which is a more expensive 

reagent but is highly reactive and can be used to achieve the SO2 removal efficiency needed to 

meet BART depending on the injection rate and the boiler flue SO2 concentration.

DSI control technology injects reagent (e.g.,trona) directly into the boiler flue gas in the 

ductwork between the air heater and the particulate collection device. The sulfite/sulfate salts 

reaction products are then removed by a downstream PM control device. Since a gas/sorbent 

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contacting vessel is not required, the DSI capital costs are lower, less physical space is required, 

and exhaust duct modifications are simpler compared to a DFGD lime SDA system. The reagent 

costs are higher and SO2 control efficiencies are lower using the DSI/trona technology. Gulf 

Power noted lime was considered as a component of the MATS compliance approach, but for 

BART using trona instead of lime would achieve further reductions in SO2 emissions.

DFGD Lime SDA. In a DFGD system, boiler flue gas mixes in a spray dryer with a mist of 

atomized fresh lime slurry. The types of DFGD systems typically installed on coal fired boilers 

are those utilizing either a SDA or a circulating dry scrubber (CDS). Gulf Power considered

both types of control equipment but concludes that the SDA and the CDS technologies have 

similar concerns with respect to adequate available space upstream of the existing PM control 

device for the installation of new equipment and the need for a larger capacity PM control 

device.

WFGD. A WFGD system removes SO2 from the exhaust stream by contacting the flue gas with 

an alkaline reagent in an absorber to form sulfite and sulfate salts. Key WFGD process design 

variables include flue gas flow rate, liquid-to-gas ratio, recycle slurry pH, flue gas SO2

concentration, and solid concentration and retention time. The WFGD systems are typically 

located downstream of any PM control system. Induced draft fans are typically used to pull the 

boiler flue gas through the WFGD spray tower absorbers before the flue gas exits through the 

stack.

When WFGD systems are installed as a retrofit technology a new stack may be required due to 

corrosion concerns. Adequate space must be available for the ancillary equipment associated 

with the WFGD system including reagent grinding and slurry preparation, dry reagent storage 

area and reagent slurry storage tanks, and gypsum dewatering, storage, and handling equipment.

Step 2. Eliminate technically infeasible options.

Gulf Power concludes all identified available retrofit SO2 control technologies are considered 

technically feasible for Units 1 and 2. However, DFGD lime SDA is considered an inferior 

technology compared to WFGD and was not evaluated further for the following reasons: (1) 

WFGD will achieve higher SO2 removal, (2) DFGD lime SDA technology is difficult to apply as 

a retrofit to existing boilers due to space considerations, (3) with the increased PM loading a new 

PM control device will need to be installed, (4) with the inclusion of the cost of a baghouse for 

the DFGD lime SDA option, WFGD will achieve greater emissions reduction at a lower cost 

compared to the DFGD line SDA system. 

Step 3. Evaluate control effectiveness of remaining control technologies.

The Gulf Power analysis states that the effectiveness of SO2 emissions control using lower sulfur 

coal is a method that can result in lower emissions of SO2 with no added capital investment. The 

removal efficiency for Units 1 and 2 by switching to lower sulfur coal would give an estimated 

25% SO2 reduction. The use of DSI with trona injection combined with coal would have an 

estimated SO2 removal efficiency of 48%, based upon testing completed by Southern Company. 

The control effectiveness of the WFGD system is estimated at 90 to 95% SO2 removal for Units 

1 and 2. This is the expected range based on meeting a 0.15 lb/MMBtu limit that takes into 

account startup, shutdown, and malfunction. The use of 0.15 lb/MMBtu results in an 

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approximately 89.5 percent reduction from the baseline emissions on an annual basis. On the 

maximum actual short-term (24-hour) basis, used in the visibility assessment, the reduction of 

SO2 using the 0.15 lb/MMBtu factor results in a 93 and 91.5 percent reduction at Units 1 and 2, 

respectively. 

Step 4. Evaluate impacts and evaluate the results.

Cost of Compliance. 

Economic analyses were developed for the DSI plus low-sulfur coal and WFDG options. No 

additional costs are associated with the switch to low-sulfur coal. The capital cost of the DSI and 

the operation and maintenance (O&M) costs associated with lime injection will be incurred as a 

possible MATS compliance plan, additional cost associated with the DSI option is the difference 

in O&M costs for the use of trona instead of lime. However, for the purpose of developing the 

BART costs, DEP has estimated the total and annualized cost for DSI based on data from a 

recent analysis, “IPM Model – Revisions to Cost and Performance for APC Technologies, Dry 

Sorbent Injection Cost Development Methodology, Final, August 2010” by Sargent and Lundy, 

LLC. WFGD costs were estimated based on a 20 year control system life, 7% interest rate, and 

energy penalty of 4 MW. GP developed the WFGD costs based on the $/kW cost of the most 

recent WFGD under construction in the Southern Company system. This cost of 649.7 $/kW was 

derived from the detailed budget estimate for this ~500 MW unit. To develop the WFGD costs 

for each Smith unit, the derived $/kW value was multiplied times the gross rating of each unit. 

The resulting wet scrubber costs for each of the Smith units is considered conservative since no 

economy of scale adjustments were made for the smaller Smith units. The fixed O&M was 

assumed to be 2% of the direct capital costs. This fixed O&M assumption is generally consistent 

with the Electric Power Research Institute (EPRI) methodology to estimate fixed O&M. The 

O&M estimate represents annual maintenance cost for labor and materials. The variable O&M 

cost components included were limestone reagent and gypsum handling. Limestone reagent cost 

assumed for the coastal region is $75/ton delivered to the site. Gypsum handling costs were 

assumed at $3/ton. Parasitic power was not included in the VOM cost, but is treated separately as 

an energy cost penalty. Fuel switch to lower sulfur coal has no additional costs, therefore no 

further economic analysis was conducted by Gulf Power. The tables below provide summaries 

of control costs related to Units 1 and 2.

SO2 

Control 

Technology

Capital Cost

($)

O&M

$ per 

year

Energy 

Cost

$ per year

Annualized 

Cost

$ per year

Baseline 

SO2

emissions 

TPY

Baseline heat 

input 

MMBtu/yr

Unit 1

DSI plus 

low-sulfur

coal

11,751,000 883,047 Minimal 1,992,319 8,711 12,225,282

WFGD 111,748,400 2,196,10

2

1,771,737 14,516,098 8,711 12,225,282

Unit 2

DSI plus 

low-sulfur

coal

10,672,148 929,241 Minimal 1,936,692 9,220 12,856,565

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WFGD 133,188,500 2,420,94

9

1,593,028 16,586,029 9,220 12,856,565

SO2 

Control 

Technology

Controlled SO2

Emission Rates

SO2 Emissions Reduction Cost Effectiveness

$/ton

lb/MMBtu TPY TPY Average Incremental

Unit 1

DSI plus 

low-sulfur

coal

0.74 4,536 4,175 477 N/A

WFGD 0.15 917 7,794 1,862 3,461

Unit 2

DSI plus 

low-sulfur

coal

0.74 4,770 4,451 435 N/A

WFGD .015 964 8,256 2,009 3,850

Energy Impacts. The energy impacts associated with the DSI technology are minimal compared 

to WFGD, which will impose an energy penalty of 4 MW per unit. The energy penalty is due to 

the increased fan power required to compensate for the higher pressure drop of the absorber 

vessel. Other energy uses associated with WFGD operations include reagent preparation, 

recirculation pumps, dewatering of spent reagent, and material handling. The energy penalties 

result in costs due to the purchase of replacement power and capital recovery for additional 

generation capacity.

Nonair-Quality Impacts. The DSI technology will produce a dry solid waste comprised of a 

mixture of spent reagent and flyash. WFGD will generate a wet sludge of spent reagent that will 

require disposal. WFGD will also require substantial amounts of water and will generate a 

wastewater stream that will require treatment.

Remaining Useful Life. No adjustments were made to the annualized costs based on the 

conservative premise that the useful lives of Unit 1 and 2 will be as long as the 20 year capital 

recovery period of the WFGD control equipment.

Step 5. Evaluate visibility impacts.

Modeling was conducted in accordance with the approved BART modeling protocol to 

determine the improvement in visibility at the St. Marks NWR for the three BART SO2 control 

technologies evaluated. To determine visibility impacts for each unit, modeling was conducted 

separately for Units 1 and 2 for each control technology evaluated. For each Unit 1 model run, 

the modeled SO2 emissions rate for the Unit 1 and 2 common stack was the sum of: (a) the Unit 

1 controlled SO2 emissions rate, and (b) the Unit 2 baseline SO2 emissions rate. The same 

approach was used for Unit 2.

The improvements in visibility compared to baseline levels due to reductions in Unit 1 SO2

emissions range from 0.37 dv for the switch to low-sulfur coal to 0.67 dv for WFGD for the 

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maximum 8th highest and from 0.34 dv and 0.51 dv, respectively for the 22nd highest over 3 

years. Unit 2 improvements in visibility compared to baseline levels due to reductions in SO2

emissions range from 0.27 dv for the switch to low-sulfur coal to 0.61 dv for WFGD for the 

maximum 8th highest and from 0.24 dv and 0.45 dv respectively for the 22nd highest over 3 

years. The use of WFGD instead of DSI plus low-sulfur coal option results in an incremental

improvement in visibility of only 0.19 dv for Unit 1 and 0.22 dv for Unit 2 for the maximum 8th

highest and only 0.07 dv for Unit 1 and 0.09 dv for Unit 2 for the 22nd highest over 3 years. 

Selection of BART

Gulf Power’s SO2 BART determination for the Lansing Smith Plant Units 1 and 2 is a SO2

emissions rate of 0.74 lb/MMBtu on a 30 day rolling average which can be achieved with the use 

of DSI with trona as the alkaline reagent. The average cost effectiveness of the DSI plus lowsulfur coal option is approximately four times lower than the WFGD with no adverse energy and 

nonair quality impacts. The incremental cost effectiveness of WFGD compared to the DSI plus 

low-sulfur coal option exceeds $3,400 per ton of SO2 removed.

Gulf Power concluded the DSI (trona) plus low-sulfur coal option is the best option due to its 

substantially lower cost, decreased energy cost and nonair-quality impacts and the minimal 

additional visibility improvements that will occur with WFGD. DEP concludes that while the 

cost of a FGD is reasonable, the visibility improvement obtained for this cost, 

$21,665,818/deciview for Unit 1 and $27,190,211/deciview for Unit 2, is not cost effective. 

Therefore, DEP concurs that the appropriate BART determination is the DSI (trona) plus lowsulfur coal option.

Review for NOX

Gulf Power’s Lansing Smith Plant Units 1 and 2 are currently equipped with low NOx burners 

(LNB) with high momentum injection ports. Unit 2 has LNB’s with an overfire air control 

system. In addition to LNB technology, both units have SNCR for additional NOx control. The 

NOx combustion controls on Units 1 and 2 were installed in response to CAIR.

Units 1 and 2 are currently equipped with NOx combustion controls and SNCR, this suite of 

controls serves as the baseline and the focus of the NOx BART analysis was confined to the 

evaluation of selective catalytic reduction (SCR) technology.

Step 1. Identify all available retrofit control technologies.

The Lansing Smith Plant units are currently equipped with multiple NOX emissions control 

methods including: overfire air control system, low-NOX burners, and SNCR. The only 

available additional option identified in Gulf Power’s analysis is the addition of a selective 

catalytic reduction (SCR) system.

Step 2. Eliminate technically infeasible options.

Gulf Power’s analysis did not identify any technically infeasible options.

Step 3. Evaluate control effectiveness of remaining control technologies.

Using the direct and indirect capital costs and the operation and maintenance costs for a SCR 

system, a BART cost effectiveness calculation was performed. A pollution control efficiency of 

90 percent was used for the SCR system.

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Step 4. Evaluate impacts and evaluate the results.

Cost of Compliance.

SCR costs were estimated based on a 20-year control system life, 7% interest rate, and energy 

penalty of 1 MW. The tables below provide summaries of control costs related to Units 1 and 2. 

The Baseline NOx control technology includes current combustion controls plus SNCR.

NOx Control 

SCR

Capital Cost ($) O&M Cost

$ per year

Energy Cost

$ per year

Annualized Cost

$ per year

Unit 1 65,950,000 1,277,953 442,934 7,945,908

Unit 2 74,940,000 1,427,537 398,257 8,899,381

NOx Control 

SCR

Baseline Heat

Input

Controlled NOx

Emission Rates

NOx Emissions 

Reduction

Average Cost 

Effectiveness

MMBtu/yr lb/MMBtu TPY TPY $ per ton

Unit 1

Baseline 12,225,282 0.34 2,047 N/A N/A

SCR 12,225,282 0.07 428 1,619 4,907

Unit 2

Baseline 12,856,565 0.27 1,729 N/A N/A

SCR 12,856,565 0.07 450 1,279 6,957

Energy Impacts. The energy impacts associated with the SCR system is estimated at 1 MW for 

each unit. The SCR systems will require additional electricity to run pumps and extra fan 

horsepower to overcome the high pressure drop in the systems.

Nonair-Quality Impacts. The current SNCR and potential SCR systems require storage and 

handling of ammonia. There is also a potential of excess ammonia injection which leads to 

ammonia slip and is emitted into the atmosphere.

Remaining Useful Life. No adjustments were made to the annualized costs based on the 

conservative premise that the useful lives of Unit 1 and 2 will be as long as the 20 year capital 

recovery period of the SCR control equipment.

Step 5. Evaluate visibility impacts.

Gulf Power indicates the contribution of Units 1 and 2 NOx emissions to visibility impairment 

are low. Baseline visibility impacts due to NOx emissions are only 3.9% of the total baseline 

impact. The same modeling approach described for the SO2 BART analysis was used for NOx. 

The modeled results indicate there will be little to no improvement in visibility compared to 

baseline levels due to the installation of SCR technology. For Unit 1 the highest improvement in 

baseline visibility is 0.01 dv for the maximum 8th highest. For Unit 2 the model results for the 

maximum 8th highest impact show no improvement in the baseline visibility.

Selection of BART

Gulf Power proposed that the existing controls such as, low NOx burners, overfire air system, 

and SNCR along with good combustion practices, be considered as BART for NOX emissions for 

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Units 1 and 2. This determination was based on the cost effectiveness of $5,000 per ton for Unit 

1 and $7,000 per ton for Unit 2 with little to no visibility impact with the installation of an SCR 

system. DEP concurs with Gulf Power.

Review for PM

Lansing Smith Plant Units 1 and 2 are equipped with highly efficient hot and cold side ESPs that 

achieve very low PM emission rates. The current PM controls serve as a baseline in the BART

analysis.

Step 1. Identify all available retrofit control technologies.

The PM BART analysis for Units 1 and 2 was conducted for only the most stringent control 

technology, a fabric filter technology such as a bag house compared to the existing ESPs.

Step 2. Eliminate technically infeasible options.

Gulf Power’s analysis did not identify any technically infeasible options

Step 3. Evaluate control effectiveness of remaining control technologies.

The collection efficiencies for the fabric filter technology are on the order of 99% for particulate 

smaller than 2.5 microns.

Step 4. Evaluate impacts and evaluate the results.

Cost of Compliance.

Fabric filter technology costs were based on a 20 year control system life, 7% interest rate, and 

an energy penalty of 1MW. The table below provides a summary of the cost effectiveness for 

PM control technologies. Baseline controls for PM in the table below are based on the hot and 

cold side ESP currently installed on Units 1 and 2.

PM Control 

Technology

Capital Cost O&M Cost Energy Cost Annualized Cost

$ $ $ per year $ per year

Unit 1 35,776,000 957,056 442,934 4,776,887

Unit 2 42,640,000 1,182,527 398,257 5,605,574

PM Control 

Technology

Annualized 

Cost

Baseline 

Heat Input

Controlled PM 

Emission Rates

PM 

Emission 

Reduction

Average Cost 

Effectiveness

$ per year MMBtu/yr lb/MMBtu TPY TPY $ per ton

Unit 1

Baseline N/A 12,225,282 0.015 92 N/A N/A

Fabric filter 4,776,887 12,225,282 0.008 48 44 108,566

Unit 2

Baseline N/A 12,856,565 0.014 88 N/A N/A

Fabric filter 5,605,574 12,856,565 0.008 51 37 153,268

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Energy Impacts. The energy impacts associated with the fabric filter system is estimated at 1 

MW for each unit. The fabric filters increase the pressure drop in the boiler exhaust system 

requiring extra fan horsepower needed to overcome the increased pressure drop.

Nonair-Quality Impacts. The higher PM removal efficiency will increase the amount of solid 

waste that will need to be disposed of at an onsite or off sight landfill.

Remaining Useful Life. No adjustments were made to the annualized costs based on the 

conservative premise that the useful lives of Unit 1 and 2 will be as long as the 20 year capital 

recovery period of the SCR control equipment.

Step 5. Evaluate visibility impacts.

The analysis concluded further control of PM emissions will not provide a meaningful reduction 

in visibility impacts due to Units 1 and 2. The baseline visibility impacts due to PM emissions 

are only 1.3% of the total baseline impact. To determine the visibility impacts the same 

modeling approach was used for PM as used for SO2 and NOx. It was demonstrated no 

improvements in visibility for both the maximum 8th highest and highest 22nd impacts compared 

to baseline levels due to the use of fabric filter technology.

Selection of BART

The average cost effectiveness of fabric filters is $108,566 per ton removed for Unit 1 and 

$153,268 per ton removed for Unit 2. Gulf Power proposes the EPS’s currently installed on 

Units 1 and 2 are considered BART; therefore, no additional add-on control technologies are 

required and will not result in any meaningful reduction in visibility impacts. DEP concurs.

Conclusion

Considering the above analysis, DEP has determined that the levels of controls already in place 

for the affected pollutants NOX and PM are consistent with BART for the Gulf Power’s Lansing 

Smith Plant. Additional control strategies are not cost-effective and are not required due to the

lack of visibility impact. DEP has also determined SO2 emissions and visibility impacts can be 

further reduced by switching to lower sulfur coal along with the installation of DSI using trona as 

a reagent. Gulf Power’s Lansing Smith Plant Units 1 and 2 meet the SO2 BART requirements by 

installing DSI/trona system and switching to lower sulfur coal. In order to coordinate this 

strategy with other regulatory obligations, Gulf Power is given a compliance date of March 31, 

2016. The BART operational and emission limiting standards for Lansing Smith Units 1 and 2 

are:

SO2: The emission limit for Unit 1 is 0.74 lb/MMBtu and Unit 2 is 0.74 lb/MMBtu. 

NOX: The combined NOx emissions from Units 1 and 2 shall not exceed 4,700 tons during any 

consecutive 12 month rolling total as determined by CEMS data reported to the EPA Acid 

Rain database. [40 CFR 60, Subpart Da]

PM: Emissions shall not exceed 0.1 lb/MMBtu. Compliance demonstrated by stack test. [40 

CFR 60, Subpart Da]

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8.0 REASONABLE PROGRESS GOALS

The Regional Haze Rule at 40 CFR 51.308(d)(1) requires states to establish reasonable progress 

goals for each Class I area within the state (expressed in deciviews) that provide for reasonable 

progress towards achieving natural visibility. In addition, EPA released guidance on June 7, 

2007 to use in setting reasonable progress goals. The goals must provide improvement in 

visibility for the most impaired days, and ensure no degradation in visibility for the least 

impaired days over the State Implementation Plan (SIP) period. The state must also provide an 

assessment of the number of years it would take to attain natural visibility conditions if 

improvement continues at the rate represented by the reasonable progress goal.

In accordance with the requirements of 40 CFR 51.308(d)(1), this Regional Haze 

Implementation Plan establishes reasonable progress goals for each Class I area in Florida. To 

calculate the rate of progress represented by each reasonable progress goal, DEP compared 

baseline visibility conditions to natural visibility conditions in each class I area and determined 

the uniform rate of visibility improvement (in deciviews) that would need to be maintained 

during each implementation period in order to attain natural visibility conditions by 2064. 

Through VISTAS, we modeled the expected visibility improvements under existing federal and 

state regulations, BART determinations in Florida and neighboring states, and any additional 

control measures found to be reasonable to implement in this review period. All of these 

elements are part of the long-term strategy. These modeling results were used to set the 

reasonable progress goals. Since not all expected reductions were included in the final modeling 

runs (due to timing of the runs to be complete in time for SIP submittals), reductions will likely 

be greater when all BART reductions and reasonable measures are taken into account.

The reasonable progress goals shown in Table 8.0-1 reflect the results of the final VISTAS 

modeling analysis for each of the Florida Class I areas. Visibility improvement is expected to 

follow the nominal uniform rate of progress for achieving the long-term goal by 2064. 

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Table 8.0-1. Florida Reasonable Progress Goals

Visibility (dv) Baseline (00-04) Natural Conditions 2018 Reasonable Progress 

Goals

Class I Area Best 

20%

Worst 

20%

Best 

20%

Worst 

20%

Best 20% Worst 20%

Chassahowitzka 15.51 25.75 5.91 11.03 13.91 22.27

Everglades 11.69 22.30 5.21 12.09 11.46 19.90

Saint Marks 14.37 26.31 5.39 11.67 12.80 23.01

Worst 20 Percent Days

Class I Area Uniform Rate 

of Progress 

(dv/yr)

2018 Uniform 

Rate of 

Progress (dv)

2018 Predicted 

Rate of 

Progress (dv/yr)

2018 Predicted 

Visibility (dv)

Chassahowitzka 0.25 22.31 0.25 22.27

Everglades 0.17 19.92 0.17 19.90

Saint Marks 0.24 22.89 0.24 23.01

Best 20 Percent Days

Class I Area Uniform Rate 

of Progress 

(dv/yr)

2018 Uniform 

Rate of 

Progress (dv)

2018 Predicted 

Rate of 

Progress (dv/yr)

2018 Predicted 

Visibility (dv)

Chassahowitzka 0.00 15.51 0.11 13.91

Everglades 0.00 11.69 0.02 11.46

Saint Marks 0.00 14.37 0.11 12.80

9.0 MONITORING STRATEGY

The State Implementation Plan is to be accompanied by a strategy for monitoring regional haze 

visibility impairment. Specifically, the Regional Haze Rule states at 40 CFR 51.308(d)(4):

“(4) Monitoring strategy and other implementation plan requirements. The State must 

submit with the implementation plan a monitoring strategy for measuring, characterizing, 

and reporting of regional haze visibility impairment that is representative of all 

mandatory Class I Federal areas within the State. This monitoring strategy must be 

coordinated with the monitoring strategy required in §51.305 for reasonably attributable 

visibility impairment. Compliance with this requirement may be met through 

participation in the IMPROVE network. The implementation plan must also provide for 

the following:

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(i) The establishment of any additional monitoring sites or equipment needed to 

assess whether reasonable progress goals to address regional haze for all 

mandatory Class I Federal areas within the State are being achieved.

(ii)-(vi) [Other implementation plan requirements that pertain to reporting and use 

of monitoring data and an emission inventory.]”

Such monitoring is intended to provide the data needed to satisfy four objectives:

1. Track the expected visibility improvements resulting from emissions reductions 

identified in this SIP. 

2. Better understand the atmospheric processes of importance to haze

3. Identify chemical species in the ambient particulate matter and relate them to 

emissions from sources

4. Evaluate regional air quality models for haze and construct relative response factors 

(RRFs) for using those models

The primary monitoring network for regional haze, both nationwide and in Florida, is the 

IMPROVE network. Given that IMPROVE monitoring data from 2000-2004 serve as the 

baseline for the regional haze program, the future regional haze monitoring strategy must 

necessarily be based on, or directly comparable to, IMPROVE. The IMPROVE measurements 

provide the only long-term record available for tracking visibility improvement or degradation 

and therefore Florida intends to rely on the IMPROVE network for complying with the regional 

haze monitoring requirement in the Regional Haze Rule. 

There are currently 3 IMPROVE sites in the state. In addition, as Table 1 shows, an IMPROVE 

site just across the border in Georgia serves as the monitoring site for both the Okefenokee and 

Wolf Island Class 1 areas, both of which lie in Georgia. 

Class I Area IMPROVE Site Designation

Everglades National Park (FL) EVER

Chassahowitzka Wilderness Area (FL) CHAS

St. Marks Wilderness Area(FL) SAMA

Okefenokee Wilderness Area (GA) OKEF

Wolf Island Wildlife Refuge (GA) OKEF

Table 1. Class I areas in Florida and IMPROVE monitors that represent conditions at 

each of them.

In addition, DEP and the local air agencies in the state operate a fairly comprehensive PM2.5 

network of the filter based Federal reference method monitors, Federal equivalent method 

continuous monitors (BAMs) and continuous mass monitors (TEOMs), filter based speciated 

monitors. A map of the various locations around the state is included in Figure 9.1. These 

176
PM2.5 measurements help DEP characterize air pollution levels in areas across the state, and 

therefore aid in the analysis of visibility improvement in and near the Class I areas.

Figure 9. 1 PM2.5 Monitoring Network in Florida

The IMPROVE measurements are central to Florida’s regional haze monitoring strategy, and it is 

difficult to visualize how the objectives listed above could be met without the monitoring 

provided by IMPROVE. Any reduction in the scope of the IMPROVE network in Florida would 

jeopardize the state’s ability to demonstrate reasonable progress toward visibility improvement 

in some of its Class I areas. 

Data produced by the IMPROVE monitoring network will be used nearly continuously for 

preparing the 5-year progress reports and the 10-year SIP revisions, each of which relies on 

analysis of the preceding five years of data. Consequently, the monitoring data from the 

IMPROVE sites needs to be readily accessible and to be kept up to date. Presumably, IMPROVE 

will continue to process information from its own measurements at about the same pace and with 

the same attention to quality as it has shown in the recent past. 

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10.0 INTERSTATE CONSULTATION

The VISTAS states have jointly developed the technical analyses to define the visibility 

improvement by 2018 under existing federal and state regulations compared to the uniform rate 

of progress, SO2 Areas of Influence for each Class I area, and methods to prioritize contributions 

from individual sources within the Areas of Influence. The states collectively accept the 

conclusions of these analyses.

In December 2006 the VISTAS State Air Directors held their first formal consultation meeting to 

review the Base G modeling results and the SO2 Areas of Influence analyses. The Air Directors 

agreed to look at reasonable control measures for sources on the lists for the SO2 Areas of 

Influence. Each state would consider sources within their state and would identify sources in 

neighboring states that they would like to have that neighboring state consider. States 

acknowledged that the review process would differ among states since some Class I areas are 

projected to see visibility improvements near the uniform rate of progress while most Class I 

areas are projected to have greater improvements than uniform rate of progress. 

In April 2007, representatives of all the Regional Planning Organizations (RPO), including 

VISTAS, met with the federal land managers (FLM) in Lakewood, Colorado to brief them on the 

technical work completed for the regional haze SIPs. The FLM’s and the RPO’s consulted on 

what needed to be in the regional haze SIPs. A summary of the meeting is located in Exhibit 3.

In May 2007, the VISTAS State Air Directors met for their second formal interstate consultation. 

States shared their lists of sources in their state and neighboring states for each Class I area. 

They also shared their criteria for listing sources and their plans for further interstate 

consultation. 

In June 2007, the VISTAS states met with the Federal Land Managers specifically for the 

purpose of consulting on the state’s visibility plans. A summary of this meeting is included in 

Exhibit 3. 

DEP has evaluated the impact of Florida sources on Class I areas in neighboring states. Both 

Georgia and Louisiana have class 1 areas within 300 kilometers of Florida sources. 

Considerable progress in improving visibility is expected in each of these Class I areas from 

existing regulatory programs (e.g. CAIR, etc.). DEP has consulted with the responsible states 

regarding its impacts on these Class I areas and the strategy we have for further reducing Florida 

source’s impact on visibility in these areas. Consultation reports and letters may be found in 

Exhibit 3.

11.0 COMPREHENSIVE PERIODIC IMPLEMENTATION PLAN 

REVISIONS

40 CFR 51.308(f) requires DEP to revise its regional haze implementation plan and submit a 

plan revision to EPA by July 31, 2018, and every ten years thereafter. In accordance with the 

178
requirements listed in Section 51.308(f) of the federal rule for regional haze, Florida commits to 

revising and submitting this regional haze implementation plan by July 31, 2018 and every ten 

years thereafter.

In addition, Section 51.308(g) requires periodic reports evaluating progress towards the 

reasonable progress goals established for each mandatory Class I area. In accordance with the 

requirements listed in Section 51.308(g) of the federal rule for regional haze, the DEP commits 

to submitting a report on reasonable progress to EPA every five years following the initial 

submittal of the SIP. The report will be in the form of a SIP revision. The reasonable progress 

report will evaluate the progress made towards the reasonable progress goal for each mandatory 

Class I area located within Florida and in each mandatory Class I area located outside Florida

which may be affected by emissions from within Florida. 

The requirements listed in 51.308(g) include the following:

1. Description of the status of implementation;

2. Summary of emission reductions achieved thus far, including especially the status of 

implementation of the CAIR compliance plans for EGUs compared to the control 

assumed in the modeling. [DEP recognizes that the 2018 projections of EGU controls 

from the IPM runs represent one solution to how the CAIR requirements will be met. By 

the time of the first periodic report, DEP anticipates that the actual compliance strategy 

for the various utility companies will be much more defined. An assessment of those 

actual compliance plans will be done for the first periodic report.]

3. Assessment of changes in visibility conditions at each class I area (current vs. baseline), 

expressed as 5-year averages of annual values for 20 percent best and worst days;

4. Analysis of emission changes over the 5-year period, identified by source or activity;

5. Analysis of any significant changes in or out of the state which have impeded progress;

6. Assessment of the sufficiency of the implementation plan to meet RPGs;

7. Review and any modifications to our visibility monitoring plan.

All requirements listed in 40 CFR 51.308(g) shall be addressed in the SIP revision for reasonable 

progress.

DEP also commits to ongoing consultation with the FLMs throughout the implementation 

process, including annual discussion of the implementation process and the most recent 

IMPROVE monitoring data and VIEWS data.

There are several technical improvements that are recommended in the emissions inventory and 

air quality models that are used to support regulatory decisions for regional haze. These 

improvements recommended, as funding is available, to support the next long term strategy. The 

following is an overall summary; Appendix K contains a fuller discussion of possible technical 

improvements.

First and foremost, continued improvements are needed in the integrated one-atmosphere air 

quality models that are used to project air quality responses to emissions reductions. As our 

understanding of partitioning between gaseous and aerosol phases improves, this understanding 

needs to be reflected in the models. Improvements can also be made in how the models handle 

individual pollutants. Sulfate performance for the CMAQ regional air quality model is good 

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overall. However sulfate deposition is frequently overestimated in the models, particularly in the 

summer months. At the coastal sites, when winds are blowing from the Gulf of Mexico or 

Atlantic Ocean, CMAQ underestimates measured sulfate at the monitors. CMAQ’s processes 

also should be reviewed for sulfate formation over water. Nitrate is overestimated by the model 

in the winter and underestimated in the summer, although summer monitored values of nitrate 

are very low. Additional improvements in seasonal allocation of ammonia emissions would 

improve model estimates of ammonium nitrate formation. Organic carbon is generally 

underestimated in the summer months. Improvements are needed in the characterization of both 

primary carbon emissions and formation of secondary organic carbon. 

Other improvements needed include better tools for organic carbon source apportionment, and 

more consistent measurement techniques between rural and urban monitoring networks. To 

improve our understanding of the contribution of fire from natural forest fires, prescribed 

burning, land clearing, and agricultural burning, states need improved record keeping. 

Additional improvements to international emissions inventory are also needed, to improve our 

understanding of boundary conditions for our modeling domain and of the contributions from 

international emissions to pollutant concentrations at the VISTAS Class I areas. 

12.0 DETERMINATION OF ADEQUACY OF THE EXISTING PLAN

Depending on the findings of the five-year progress report, Florida commits to taking one of the 

actions listed in 40 CFR 51.308(h). The findings of the five-year progress report will determine 

which action is appropriate and necessary.

List of Possible Actions – 40 CFR 51.308(h)

1) DEP determines that the existing SIP requires no further substantive revision in order to 

achieve established goals. DEP provides to the Administrator a negative declaration that 

further revision of the SIP is not needed at this time.

2) DEP determines that the existing SIP may be inadequate to ensure reasonable progress 

due to emissions from other states which participated in the regional planning process. 

DEP provides notification to the Administrator and the states that participated in regional 

planning. DEP collaborates with states through the regional planning process to address 

the SIP’s deficiencies.

3) DEP determines that the current SIP may be inadequate to ensure reasonable progress 

due to emissions from another country. DEP provides notification, along with available 

information, to the Administrator.

4) DEP determines that the existing SIP is inadequate to ensure reasonable progress due to 

emissions within the state. DEP will revise its SIP to address the plan’s deficiencies 

within one year.

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