# Appendix H Reasonable Progress Goals and Long Term Strategies

### Table of Contents

1.0 Base G CAA Controls............................................................................................. 4

1.1 Point Source Controls ............................................................................................... 8 1.1.1 Electric Generating Units ................................................................................... 8

1.1.2 Non-EGUs ........................................................................................................ 14

1.2 Area Source Controls.............................................................................................. 15

1.3 Mobile Sources ....................................................................................................... 16

1.4 Non-Road Sources .................................................................................................. 16

1.5 Conclusion .............................................................................................................. 17

2.0 Uniform Rate of Progress ..................................................................................... 20

3.0 Georgia Tech Sensitivities .................................................................................... 22 3.1 Evaluation of Cape Romain .................................................................................... 22

4.0 Reasonable Progress Evaluation ........................................................................... 24

4.1 Area of Influence .................................................................................................... 24 4.2 Source Type Analysis ............................................................................................. 25 4.3 Area of Influence Data and Displays ...................................................................... 28 4.4 Importance of Pollutants other than Sulfate ............................................................ 33 4.5 Summary of Emission Inventories in Cost Curve Analysis .................................... 33 4.6 Application of AirControlNET Technologies ........................................................ 37 4.7 Development of AOI-Based Cost Curve ................................................................ 37

5.0 Reasonable Progress Assessment ......................................................................... 39

6.0 Four Factor Analysis ............................................................................................. 42 6.1 The Four Statutory Factors ..................................................................................... 42 6.1.1 The Cost of Compliance .................................................................................. 42 6.1.2 Time Necessary for Compliance ...................................................................... 42 6.1.3 Energy and Non-Air Quality Envi ronmental Impacts of Compliance ............. 43 6.1.4 Remaining Useful Life of the Source .............................................................. 43 6.2 Evaluating Four Statutory Factors For Specific SO 2 Emission Sources in Cape

Romain’s Area of Influence .......................................................................................... 43 6.2.1 Cost of Compliance.......................................................................................... 44 6.2.2 Time Necessary for Compliance ...................................................................... 45 6.2.3 Energy and Non-Air Environmental Impacts .................................................. 45 6.2.4 Remaining Useful Life ..................................................................................... 45 6.3 Process of Applyi ng Statutory Factors ................................................................... 45

7.0 Best Available Retr ofit Technology (BART) ....................................................... 48 7.1 Background ............................................................................................................. 48 7.2 Approach to Implementation of BART Requirements ........................................... 49

7.3 Identification of BART-Eligible Sources ......................................................... 49

7.4 Contribution Threshold........................................................................................... 50 7.5 Exemption of Point Source VOC for BART Purposes ........................................... 53

7.5.1 Method ............................................................................................................. 53

7.5.2 Conclusions ...................................................................................................... 54

7.6 Treatment of Ammonia ........................................................................................... 54

7.6.1 Method ............................................................................................................. 55

7.6.2 Conclusions ...................................................................................................... 568.0 Explanation of BART Exemption Modeling ........................................................ 57 8.1 Background ............................................................................................................. 57 8.2 South Carolina BART Source Exemption Modeling .............................................. 58 8.3 Use of the New IMPROVE Algorithm ................................................................... 61

8.4 Conclusions............................................................................................................. 63

9.0 BART Determinations and Conclusions ............................................................... 64

10.0 Final Long-Term Strategy and Reasonable Progress Goals ................................. 65 10.1 Long-Term Strategy .............................................................................................. 65

10.2 What Additional Emissions Controls Were Considered as Part of the Long Term Strategy for Visibility Improvement by 2018? ............................................................. 66 10.3 Reasonable Progress Goals ................................................................................... 67

## Appendices

Attachment H.1 – Memorandum of U nderstanding: SC DHEC and SCFC

Attachment H.2.a - Cost Effectiveness Curve Design

Attachment H.2.b – VISTAS Class 1 Federal Areas

Attachment H.2.c – VISTAS Control Options Spreadsheet

Attachment H.3 – Control Option Costs

Attachment H.4 – South Carolina’s Evaluation of Source Emissions for BART Eligibility

Attachment H.5 - BART Analysis Sensitivity Modeling

Attachment H.6 - BART Modeling Protocols and Demonstrations

Attachment H.7 – North Carolina’s Clean Smokestacks Act Implementation Plan

## 1.0 Base G CAA Controls

The purpose of this appendix is to outline S outh Carolina’s strategy for complying with the requirement to set and meet Reasonable Progress Goals (RPGs) as part of South Carolina’s Regional Haze SIP under 40 CF R 51.308(d)(1), and the requirements for establishing best availabl e retrofit (BART) controls under 40 CFR 51.308(e).

In the 1977 amendments to the Clean Air Act (CAA), Congress se t a national goal for visibility as “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 pollution.” The Regional Haze Rule (RHR) at Section 51.308(d) requires states to demonstrate reasonable progress towards meeting the 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 ra te of progress” toward natural conditions for each Class I area. This is known as the “g lidepath.” The RHR then requires states to establish RPGs for visibility improvement at each affected Class I area covering each approximately ten-year period until 2064. Th e first set of RPGs will comprise South Carolina’s Long Term Strategy (LTS) covering the period from the present until 2018. This appendix provides an overview of this first LTS. In addition, a specific component of each state’s first LTS is dictated by the specific BART requirements in 40 CFR 51.308(e). This appendix will al so include a discussion of our strategy for developing those BART requirements.

The LTS contains the following components:

1. Inventory of all controls required or expected under all federal and state regulations by 2009 and 2018.

2. Modeled expected visibility improvement from planned or existing (Base G) controls and Comparison of Base G re sults for 2018 to the uniform rate of progress, or “glidepat h,” for Cape Romain.

3. Discussion of emissions sensitivity model runs to help determine which pollutants and source categories are co ntributing the most to visibility impairment at Cape Romain (runs conducted by Georgia Institute of Technology).

4. Examination of SO2 Area of Influence (AOI) projections for Cape Romain, and also for any surrounding states’ Cl ass I areas whose AOI includes South Carolina counties, to determine which specific sources are most likely to be impairing visibility at specific Class I areas.

5. Application of the four “statutory factors,” listed in 40 CFR 51.308(d)(1)(i)(A) to those sources id entified in the previous step.

6. Identify control determination (based on the results of the four factor analyses) for specific sources.

7. Identify of BART-eligible sources.

8. Examine BART-exemption modeling for BART-eligible sources to include modeling demonstration of visibility im provement after inclusion of BART and reasonable progress c ontrol determinations.9. Determination of RPGs based on the visibility improvement expected by

2018.

Base G Planned and Existing Controls

2009 and 2018 controls include the following planned and existing state and federal

controls:

Clean Air Interstate Rule (CAIR) and Clean Air Mercury Rule (CAMR). CAIR will permanently cap emissions of sulfur dioxide (SO 2 ) and nitrogen oxides (NO X ) in the eastern U.S. When fully implemented, CAIR will reduce SO 2 emissions in these states by over 70 percent and NO X emissions by over 60 percent from 2003 levels. The Clean Air Mercury Rule will reduce utility emissions of mercury from 48 tons a year to 15 tons, a reduction of nearly 70 percent. While merc ury is not a visibility-impairing pollutant, CAMR establishes standards of performance th at limit mercury emissions from new and existing coal-fired power plants and creates a market-based cap-and-trade program that will reduce nationwide utility emissions of me rcury while simultaneously reducing sulfur

dioxide SO 2 and nitrogen oxides NO X emissions. Appendix M illustrates which sources within South Carolina’s AOI are subject to CAIR.

NO X SIP Call. Phase I of the NO X SIP call applies to certain Electric Generating Units (EGUs) and large non-EGUs, including large indu strial boilers/turbines and cement kilns. States in the VISTAS region affected by the NO X SIP call have developed rules for the

control of NO X emissions that have been approved by the EPA. This rule results in a 68 percent reduction in NO X emissions from large stationary combustion sources by 2006. For this analysis, we capped the emissions for NO X SIP call-affected sources at 2007 levels and carried forward the capped levels for the 2009/2018 future year inventories.

NC Clean Smokestacks Act. Under the act, enacted in 2002 , coal-fired pow er plants in North Carolina must achieve a 77 pe rcent cut in nitrogen oxide (NO X ) emissions by 2009 and a 73 percent cut in sulfur dioxide (SO 2 ) emissions by 2013.

Consent Agreements (Santee Cooper, TECO, VEPCO, Gulf Power Crist 7, and EKPC).

A 2004 EPA consent decree calls for Santee Cooper to: install and commence operation of continuous emission control equipment for PM/SO 2 /NO X emissions; comply with system-wide annual PM/SO 2 /NO X emissions limits; agree not to buy, sell, or trade

PM/SO 2 /NO X allowances allocated to Santee C ooper Systems in South Carolina as a result of said agreement; and comply with emission unit limits of said agreement.

Under a 2000 settlement agreement, Tampa Electric (Florida) will: install permanent emissions-control equipment to meet stringe nt pollution limits; implement a series of interim pollution-reduction measures to reduc e emissions while the permanent controls are designed and installed; and retire pollu tion emission allowances that Tampa Electric

or others could use/sell to others to em it additional pollution into the environment.Virginia Electric and Power Co. (VEPCO) ag reed to eliminate 237,000 tons of sulfur dioxide (SO 2 ) and nitrogen oxides (NO X ) emissions each year fr om eight coal-fired electricity generating plants in Virginia and West Virginia.

A 2002 agreement calls for Gulf Power to upgrade its operation to cut NO X emission rates by 61 percent at its Crist generating plant by 2007, with major reductions beginning in early 2005. The Crist plant is a significant source of NO X emissions in the Pensacola,

Florida area.

A July 2, 2007 consent agreement between the U.S. EPA and East Kentucky Power Cooperative (EKPC) requires the utility to reduce its emissions by 62,000 tpy (including 54,000 tons of SO 2 and 8,000 tons of NO X ) located in Indiana, Kentucky, Ohio, Virginia, and West Virginia. These reductions will be achieved by installing/operating selective catalytic reduction (SCR) technology; low-NO X burners, and PM and mercury

Continuous Emissions Monitors at the utility’s Spurlock, Dale and Cooper plants. According to the EPA, the plants’ total emissions will drop from between 50 and 75 percent from 2005 levels. As with all federa l consent decrees, EKPC is precluded from using reductions required under other programs, such as the Clean Air Interstate Rule.

One-hr ozone SIPs (Atlanta, GA / Bi rmingham, AL / Northern Kentucky). The purpose of these respective SIPs is to grant final appr oval to the request for redesignation of the 1- hour ozone NAAQS nonattainment ar ea to attainment. New SIPs have been submitted to the EPA for public comment and approval. These SIPs require NO X reductions from specific coal-fired power and address transportation plans in these cities.

NOx RACT in 8-hour Nonattainment Area SIPs. NC DENR applied NOX RACT to two

facilities located in the Charlotte nonattainme nt area: Philip Morris USA and Norandal

USA.

Heavy Duty Diesel (2007) Engine Standard. A PM emissions standard for new heavyduty engines of 0.01 grams per brake-horsepower- hour (g/bhp-hr) is to take full effect for 2007 model year diesel engines. This standard also requires reductions in NO X and nonmethane hydrocarbons (NMHC) of 0.20 g/bhp-hr and 0.14 g/ bhp-hr, respectively. These

NO X and NMHC standards for diesel engines will be phased in together between 2007 and 2010. Also, sulfur in diesel fuel must be lowered to enable modern pollution-control technology to be effective on these diesel-p owered trucks and buses. The 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 di esel, or LSD) to 15 parts per million (ultralow sulfur diesel, or ULSD).

Tier 2 Tailpipe . Tier 2 is a fleet averaging progr am, 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 manuf acturer sells each yearmust have average

NO X emissions below a specified value.Large Spark Ignition and Recreational Vehicle Rule. EPA has adopted new standards for emission of oxides of nitrogen (NO X ), hydrocarbons (HC), and carbon monoxide (CO) from several groups of previo usly unregulated non-road e ngines. Included in these sources are the Large Industrial Spark-Igni tion Engines and Recreational Vehicles. Spark-ignition non-road engines are those pow ered by gasoline, liquid propane gas, or compressed natural gas rated over 19 kilowatt s (kW) (25 horsepower). These engines are

used in commercial and industr ial applications, including fo rklifts, electric generators, airport baggage transport vehicl es, and a variety of farm an d construction applications. Recreational Vehicles include snowmobiles, off-highway motorcycles, and all-terrainvehicles. Rules were initiated in 2004 and are fully phased in by 2012.

Non-road Diesel Rule. This rule sets standards that will dramatically reduce emissions by over 90 percent from non-road diesel equipm ent and dramatically reduce sulfur levels by 99 percent from current levels in non-road di esel fuel starting in 2007. This rule will apply to most non-road diesel fuel in 2010 and to fuel in locomotives and marine vessels

in 2012.

Industrial Boiler/Process Heater MACT standards. The applied MACT control efficiencies were 4 percent for SO 2 and 40 percent for PM 10 and PM 2.5 . However, as of June 08, 2007, the Industrial Boiler/Process Heater MACT standard was vacated. A mandate without a stay was issued July 30, 2007. SC DHEC is upholding its state MACT regulation for industrial boilers, therefor e the affected facilities must comply with

the aforementioned efficiencies.

Combustion Turbine MACT. The projection inventories do not include the NO X cobenefit effects of the MACT regulations for Gas Turbines or stationary Reciprocating Internal Combustion Engines, which the 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 impl emented. We did not count reductions occurring before 2002.

Smoke Management Plan (SMP). The GCVTC Report outlined in the RHR notes that “emissions from fire (wildfire and prescribed fire) are an important episodic contributor to visibility-impairing aerosols.” As such, Section 51.309(d) (6) of the RHR requires that

each state consider and address the effects of smoke on visibili ty (especially when planning and issuing permits for prescribed fires). The SC Forestry Commission (SCFC) has developed (and recently revised as of August 2006) the Smoke Management Guideline for Vegetative Debris Burning Operations, which serves to regulate vegetative debris burning for forestry, agriculture, and wildlife purposes in the State of South Carolina. SC DHEC’s Bureau of Air Qualit y has developed a state air pollution control regulation (R. 61-62.2, Prohibition of Open Burn ing) that prohibits open burning of any/all household garbage, as well as open burning for the purpose of land clearing or right of way maintenance in areas other than predominantly residential, as well as openburning of residential constr uction waste from building and construction operations unless specific conditions are met.

When weighed together, these documents a ddress all sources of fire used for land management purposes within South Carolina an d effectively minimize visibility impacts while recognizing the important ecological role that fires can and do play. Appendix H.1 includes a memorandum of understanding be tween the SCFC and SC DHEC and represents the State’s collective commitment to develop a comprehensive approach to establish and maintain a smoke management plan.

Early Action Compacts (EAC). Forty-five of 46 counties in South Carolina, along with the Department and EPA Region 4, signed EA Cs in December 2002. By signing the EAC, EPA agreed to defer the effective date of the nonattainment designation for participating areas. The Department has b een working with the EPA, state and local governments, industry, environmental groups, a nd other interested parties to develop a strategy to reduce the pollu tion that creates ground-level ozone. In March 2004, participating EAC areas in South Carolina, s ubmitted local Early Ac tion Plans to include emission reduction strategies.

The following are source category specific contro ls used to project future year emissions

inventories:

1.1 Point Source Controls

Different approaches were used for the E GU and the non-EGU sectors of the point source inventory:

• For the EGUs, the State relied primarily on the Integrated Planning Model (IPM) to project future generation as well as to calculate the impact of future emission control programs, including CAIR and CA MR. The IPM results were adjusted based on State and local (S/L) agency know ledge of planned emission controls at specific EGUs.

• For non-EGUs, we used recently updated growth and control data consistent with the data used in EPA’s CAIR analyses a nd supplemented these data with available S/L agency input and updated fuel use fo recast data for the U.S. Department of Energy.

For both sectors, we generated 2009 and 2018 inventories for a combined planned and existing control scenario. The planned and existing control scenarios account for post2002 emission reductions from promulgated and proposed federal, state, local, and sitespecific control programs as of July 1, 2004.

1.1.1 Electric Generating UnitsState and local (S/L) agencies specified a number of changes to the IPM results to better

reflect current information on when and where future controls would occur. These changes to the IPM results primarily invo lved state and local agency addition or

subtraction of future emission controls based on the best available data from state rules, enforcement agreements, compliance plans, permits, and discussions/commitments from individual companies.

Some adjustments were necessary in the model runs based on additional control information. A re-run (Base G2) was performed to account for these differences.

Table 1-1 lists adjustments to IPM control determinations specified by S/L agencies for

the Base G 2009/2018 EGU inventories. Table 1- 2 lists other adjustments to IPM results specified by S/L agencies for Base G 2009/2018 inventories.NOxEmission ControlsSO2Emission ControlsStatePlant Name and IDUnit2009201820092018IPMStateIPMStateIPMStateIPMStateALJames H. MillerORISID=60021 & 23 & 4SCRduringozoneseasonSCRduringozoneseasonSCRprobableyr rounddue toCAIRSCR yrroundfromConsentDecreeSCRduringozoneseasonSCRduringozoneseasonSCRprobableyr rounddue toCAIRSCR yrroundfromConsentDecreeNoneNoneNoneScrubberNoneNoneNoneScrubberBarry ORISID=31, 2, 345NoneNoneNoneSNCRSNCRNoneSCRSCRSCRSNCRSNCRSCRNoneNoneNoneNoneNoneNoneNoneScrubberScrubberNoneNoneNoneE C Gaston ORISID=261 - 45SCRSCRNoneSCRSCRSCRNoneSCRNoneScrubberNoneNoneScrubberScrubberNoneNoneGorgas ORISID=86 & 78 & 910NoneNoneSCRNoneNoneSCRNoneNoneSCRNoneNoneSCRNoneNoneNoneNoneScrubberScrubberNoneNoneScrubberNoneScrubberScrubberCharles R. LowmanORISID=5612 & 3NoneSCRNoneSCRNoneSCRNoneSCRNoneScrubberScrubberScrubberNoneScrubberScrubberScrubberGABowen ORISID=7031BLR2BLR3BLR4BLRSCRSCRSCRSCRSCRSCRSCRSCRSCRSCRSCRSCRSCRSCRSCRSCRIPM hadretrofitscrubbersbut littleemissionreductionsNoneNoneScrubberScrubberScrubberScrubberScrubberScrubberScrubberScrubberScrubberScrubberGAWansley ORISID=605212SCRSCRSCRSCRSCRSCRSCRSCRIPM hadretrofitscrubbersbut littleemissionreductionsScrubberNoneScrubberScrubberScrubberScrubberKraft ORISID=7331, 23NoneNoneNoneNoneNoneSCRNoneNoneNoneNoneNoneNoneNoneNoneNoneNoneMcIntoshORISID=61241NoneNoneSCRNoneNoneNoneNoneNoneYates ORISID=7281 2,34 – 7NoneNoneNoneNoneNoneNoneNoneNoneSCRNoneNoneNoneScrubberNoneNoneScrubberNoneNoneScrubberNoneScrubberScrubberNoneNoneHammondORISID=7081234NoneNoneNoneSCRNoneNoneNoneSCRSCRSCRSCRSCRSCRSCRSCRSCRNoneNoneNoneScrubberScrubberScrubberScrubberScrubberScrubberScrubberScrubberScrubberScrubberScrubberScrubberScrubberKYGhent ORISID=1356123, 4NoneNoneNoneSCRNoneSCRSCRSCRSCRSCRSCRSCRScrubberNoneNoneScrubberScrubberScrubberScrubberScrubberScrubberScrubberScrubberScrubberColemanORISID=1381C1C2C3NoneNoneNoneNoneNoneNoneSCRSCRSCRSCRSCRSCRNoneNoneNoneScrubberScrubberScrubberScrubberScrubberScrubberScrubberScrubberScrubberKYE W BrownORISID=1355123NoneNoneNoneNoneNoneNoneNoneSCRSCRNoneSCRSCRNoneNoneNoneScrubberScrubberScrubberNoneScrubberScrubberScrubberScrubberScrubberSCJefferies ORISID=331934SCRNoneNoneNoneSCRNoneNoneNoneNoneNoneNoneNoneNoneNoneNoneNoneWateree ORISID=3297WAT1WAT2SCRSCRSCRSCRSCRSCRSCRSCRNoneNoneScrubberScrubberNoneScrubberScrubberScrubberCanadys ORISID=3280CAN1CAN2CAN3NoneNoneNoneNoneNoneNoneNoneNoneNoneNoneNoneNoneNoneNoneNoneNoneNoneScrubberNoneNoneNoneNoneNoneScrubberRainey ORISID=7834CT1ACT1BNoneNoneSCRSCRNoneNoneSCRSCRNoneNoneNoneNoneNoneNoneNoneNoneTNKingston ORISID=34071 – 89SCRNoneSCRSCRSCRSCRSCRSCRNoneNoneNoneNoneScrubberScrubberScrubberScrubberJohnsonvilleORISID=34061 – 10SCRNoneSCRSCRNoneNoneNoneNoneWVWillow IslandORISID=39462SCRNoneSCRSCRScrubberNoneScrubberScrubberKammer ORISID=39471 -3SCRNoneSCRSCRScrubberNoneScrubberScrubberTable 1-2. Other Adjustments to IPM Results Specified by S/L Agencies for the Base

G 2009/2018 EGU Inventories.

State Plant Name & ID Unit Nature of Update/Correction

FL Central Power and

Lime

ORISID= 10333 GEN1 Central Power and Lime (ORIS10333) is a duplicate entry. This is point 18 in Florida Crushed Stone (12-053-0530021). Removed IPM emissions for Central

Power and Lime.

Cedar Bay Generating

ORISID=10672 GEN1 FLDEP disagrees with IPM projecti ons - no knowledge of expansion of this facility and the cogeneration facility shoul d not grow faster than the underlying industry. Cedar Bay is connected to Stone Container (12-031-0310067). Replaced IPM emissions with 2002 emissions for Cedar Bay (12-031- 0310337) times the growth factors for Stone Container.

Indiantown Cogeneration

ORISID=50976 GEN1 FLDEP disagrees with IPM projecti ons - no knowledge of expansion of this facility and the cogeneration facility shoul d not grow faster than the underlying industry. Indiantown is connected to Louis Dreyfus Citrus (12-0850850002). Replaced IPM emissions with 2002 emissions for Indiantown (12-085- 0850102) times the growth factors for Louis Drefus Citrus.

GA Bowen

ORISID=703 1BLR

2BLR

3BLR

4BLR IPM indicated retrofit scrubbers on all 4 units in 2009, but the IPM emissions showed little reductions from 2002 levels. Changed emissions to reflect scrubbers on 1BLR and 2BLR by 2009.

Wansley

ORISID=6052 1, 2 IPM indicated retrofit scrubbers on both units in 2009, but the IPM emissions

showed little reductions from 2002 leve ls. Changed emissions to reflect one scrubber on Unit 1 by 2009.

Riverside

ORISID=734 4 All of plant Riverside was retired from service June 1, 2005; emissions set to

zero in 2009 and 2018.

McIntosh

ORISID=727 CT10A CT10B

CT11A CT11B The McIntosh Combined Cycle facility became commercial June 1, 2005.

Added 346 tons of NO x and 121 tons of SO 2 per unit to the 2009 and 2018

inventories. Longleaf Energy

Station 1, 2 Longleaf Energy Station is being proposed by LS Power Development, Inc. GA specified that the emissions from this proposed plant be included in the 2018 projections. Boilers 1 and 2 added 1,882 tons of NO x and 3,227 tons of SO 2 per unit to the 2018 inventory.

R D Morrow
ORISID=6061 1, 2 Revised the 2018 emissions to reflect controls not indicated by IPM. The SO 2 emissions are much lower than IPM, but their expected NO x emissions are actually higher than IPM. The controls will be coming online 2009 or 2010, so the 2009 inventory did not change. MS

Jack Watson (2049) Victor J Daniel (6073) Chevron Oil (2047) All MS DEQ specified that the emission projections provided by the Southern Company for their units in Mississippi were to be used instead of the IPM

results.1.1.2 Non-EGUs

The general approach for assembling future y ear data was to use recently updated growth

and control data consistent with the data used in EPA’s Clean Air Interstate Rule analyses, supplement these data with availabl e stakeholder input, a nd provide the results for stakeholder review to ensure credibility.

MACTEC (MACTEC, 2006) used the same control programs for both the 2009 and 2018 non-EGU point inventory. Two control scenario s were developed: existing controls and planned controls. The ex isting control scenario accounts for post-2002 emission reductions from recently promulgated federal, state, local, and site-specific control programs. The planned control scenario a ccounts for proposed (but not final) control programs that are reasonably anticipated to result in post-2002 emission reductions.

Maximum achievable control technology (MAC T) requirements were also applied, as documented in the report entitled Control Packet Development and Data Sources, dated July 14, 2004. The point source MACTs a nd associated emission reductions were designed from Federal Register (FR) notices and discussions with EPA’s Emission Standards Division (ESD) staff. Reductions for MACT standards with an initial compliance date of 2001 or ea rlier were not included (assumi ng that the effects of these controls are already accounted for in the 2002 inventories supplie d by the States). Emission reductions were applied only for MA CT standards with an initial compliance date of 2002 or greater.

The final Phase II NOx SIP call rule was finalized on April 21, 2004. States had until April 21, 2005, to submit SIPs meeting th e Phase II NOx budget requirements. The Phase II rule applies to large IC engine s, which are primarily used in pipeline transmission service at compressor stations. Affected units were identified using the same methodology as was used by EPA in th e proposed Phase II rule (e.g., a large IC engine is one that emitted, on average, more than one ton per day during 2002). The final

rule reflects a control level of 82 percent for natural gas-fi red IC engines and 90 percent for diesel or dual fuel categories. Several st ate and local agencies provided more specific information on the anticipated controls at the compressor stations. This information was used instead of the default approach used by EPA in the proposed Phase II rule.

A summary of non-EGU point source control programs included in 2009/2018 projection

inventories include:

• Atlanta / Northern Kentucky / Birmingham 1-hr SIPs

• Industrial Boiler/Proc ess Heater MACT: The applie d MACT control efficiencies were 4 percent for SO 2 and 40 for percent for PM 10 and PM 2.5 to account for the co-benefit from installation of acid gas scrubbers and other control equipment to

reduce HAPs.• NO X SIP Call (Phase I- except where States have adopted Phase II already e.g. NC): Phase I of the NO X SIP call applies to certai n large non-EGUs, including cement kilns and large industrial boilers and turbines. States in the VISTAS region affected by the NO X SIP call have developed ru les for the control of NO X emissions that have been approved by EPA.

• Petroleum Refinery Initiative (October 1, 2003 notice; MS & WV): This initiative addresses the most significant Clean Air Act compliance concerns affecting the petroleum refinery industry. Since Decem ber 2000, 17 global refinery settlements have been reached with refiners representing nearly 77 percent of domestic refining capacity. Three re fineries in the VISTAS region are affected by two

October 2003 Clean Air Act settlements under the EPA Petroleum Refinery

Initiative. The refineries ar e: (1) the Chevron refinery in Pascagoula, MS; (2) the Ergon refinery in Vicksburg, MS; and (3 ) the Ergon refinery in Newell, WV.

• Reasonable Further Progress three per cent plans where in place for one-hour plans (Metropolitan Washington, DC, and Atlanta, GA).

• VOC 2-, 4-, 7-, and 10-year MACT Sta ndards: The point source MACTs and

associated emission reduc tions were designed from Federal Register (FR) notices

and discussions with EPA’s Emission Sta ndards Division (ESD) staff. We did not apply reductions for MACT standards with an initial co mpliance date of 2001 or earlier, assuming that the effects of th ese controls are already accounted for in the 2002 inventories supplied by the States.

• Combustion Turbine MACT: The projecti on inventories do not include the NO X co-benefit effects of the MACT regulat ions for Gas Turbines or stationary Reciprocating Internal Combustion Engine s, which EPA estimates to be small compared to the overall inventory.

• NO X SIP Call (Phase II – remain ing States & IC engines).

For more information on the development of point source inventories, see Appendix E.

1.2 Area Source Controls

Controls (including control efficiency, rule effectiveness and rule penetration) provided by the States or originally developed for us e in estimating projected emissions for U.S. EPA’s Heavy Duty Diesel (HDD) rulemaking em ission projections and used in the Clean Air Interstate Rule (CAIR) projections we re used to calculate controlled emissions.

The controls obtained by MACTEC (MACTE C, 2006) for the HDD rulemaking were controls for the years 20 07, 2020, and 2030. Since MACTEC was preparing 2009 and 2018 projections, control values for intermediate years were prepared using a straight-line interpolation of contro l level between 2007 and 2020.

State-submitted controls had precedence over the EPA-developed controls. Control measures submitted by SC DHEC include Stage I controls for gasoline dispensing facilities and open burning controls.South Carolina performs inspections on an (a pproximate) annual basi s for facilities with regulated underground storage tanks. Duri ng such inspections, SC DHEC inspectors look for the presence of and test the integr ity of any existing Stage I vapor recovery technology employed at the facilities. Stage I vapor recovery devices, when installed on underground storage tanks, reduce vapor emi ssions during the tank filling operations. Only a small minority of the current Sout h Carolina population of regulated underground storage tanks do not have Stage 1 vapor recovery devices.

In South Carolina, the South Carolina Depart ment of Agriculture is responsible for visiting all gasoline dispensing facilities and testing the fuels to ensure they meet the quality standards of the State. This includes testing to ensure the ultra-low sulfur diesel fuel standards are being met.

Open burning is treated as a means of waste disposal in rural areas. Materials burned generally include house hold trash, agricultural refuse, landscaping refuse, or scrap wood. The open burning emissions i nventory includes Source Classification Code (SCC) 2610030000, residential open burning of household waste and SCC 2610000100, and open burning of yard trimmings. Since it is il legal to burn within th e corporate limits, the rural population in each county is used to estimate emissions.

For more information on the development of area source inventories, see Appendix E.

1.3 Mobile Sources

Local controls included vehicle emissions insp ection (i.e., I/M) programs, Stage II vapor recovery programs, anti-tampering programs, et c. By nature, the assumptions used for the 2002 initial base year inve ntory vary across the VISTAS region, but the presumption is that these data accurately reflected each State’s situat ion as it existed in 2002. If a State had no plans to ch ange program requirements between 2002 and 2018, the 2002 program descriptions were maintained. Ho wever, if a State planned changes, then information was requested on those plans. In the final implementation of the inventory, where applicable, Stage II controls were ex ercised in the area so urce component of the inventory, since the units used to develop Stage II refuel ing estimates are different

between MOBILE6 and the NONROAD models.

For more information on the development of mobile source inventories, see Appendix D.

1.4 Non-Road Sources

Using the 2002 base year emissions inventor y for aircraft, locomotives, and commercial marine vessels (CMV) prepared as describe d earlier in this doc ument, corresponding emission projections for 2009 and 2018 were developed. Detailed inventory data (both before and after controls) for these same emission sources for 1996, 2010, 2015, and

2020 were obtained from the EPA's Clean Air Interstate Rule (CAIR) Technical SupportDocument. Using these data, combined grow th and control factors for the period 2002- 2009 and 2002-2018 were estimated using strai ght-line interpola tion between 1996 and2010 (for 2009) and 2015 and 2020 (for 2018). This is done at the State-county-SCCpollutant level of detail. According to EPA documentation, the CAIR baseline emissions include the impacts of the Tier 4 (T4) non -road diesel rulemaking, which implements a low sulfur fuel requirement that affects both future CMV and locomotive emissions.

For more information on the development of non-road source inventories, see Appendix

D.

1.5 Conclusion

In conclusion of this discussion on source sector controls, Figures 1-1 through 1-4 depict pollutant totals for NH 3 , PM 2.5 , NO X , and SO 2 for the various sectors by state for 2002, 2009, and 2018 Base G2 modeling. “Miscellaneous ” refers to EPA Ti er 1 categories and include area sources (agriculture, fire, and fugitive dust emissions) not identified in previous categories.

Figure 1 -1 Annual NH 3 emissions – Base G2. 0 20 40 60 80 100 120 140 160 180 200

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Figure 1 – 2 Annual PM 2.5 emissions – Base G2

Figure 1 - 3 Annual NO X emissions – Base G2Figure 1 - 4 Annual SO 2 emissions – Base G2

## 2.0 Uniform Rate of Progress

The linear rate of improvement sufficient to attain natural cond itions by 2064 is referred to as the “uniform rate of pr ogress” or “glide path.” The ba seline represents the starting point from which reasonable progress will be measured. There are two baseline values for each Class I area. Using 2000-2004 Inte ragency Monitoring of Protected Visual Environments (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 aver age deciview value for the worst days. Extinction from individual PM components is calculated from the IMPROVE equation (EPA, 2003; Hand and Malm, 2006). EPA defi ned target natural conditions in 2064 for each Class I area (EPA, 2003). For each VISTAS Class I area a baseline visibility using 2000-2004 IMPROVE data and uniform rate of progress was established, using EPA default assumptions for calculating visibility and natural background. Most recently, the scientific community has reviewed the assump tions used to calculate current and natural background visibility and has agreed to revised methods (Hand and Malm, 2006, Pitchford, 2006). VISTAS intends to present both the original a nd revised methods to calculate visibility and visibility improve ment. Figure 2.1 illustrates the average 20 percent worst visibility days in the 2000-2004 baseline period for Cape Romain (ROMA), the target natural condition in 2064 for the 20 percent worst days, and the incremental deciview changes assuming a unifo rm rate of progress between current and natural conditions in 2064, using the original method for calcula ting visibility. The term Method 1prediction in Figure 2.1 refers to EPA’ s default assumptions. This is known as the “glide path.”

### Uniform Rate of Reasona ble Progress Glide Path Cape Romain - 20% Data Days

New IMPROVE Equation, 12 km grid

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Figure 2-1. CMAQ 2018 Base G2 Results Compared to Uniform Rate of Progress at Cape Romain.

## 3.0 Georgia Tech Sensitivities

Georgia Tech performed emission sensitivit ies to examine the impact of emission reductions on regional haze, annual PM 2.5 , and 8-hour ozone concentrations using CMAQv4.4_SOAmods on the VISTAS 12-km modeling domain, using the 2009 OTW (on the way) BaseD emissions. Once the key pollutants contributing to visibility impairment at each Class I area were iden tified, the sources or source categories responsible for emitting these pollutants or pollutant precursors were determined. Emissions sensitivity analyses were conduc ted using CMAQ with 2009 Base D inventory and consider 30 percent reductions from ma jor pollutants and source categories. The sensitivity runs were initially designed to consider pollutant contributions in 2009 to

PM 2.5 in urban areas; results were also considered for Clas s I areas even though the full benefit of controls anticipated by 2018 are no t included in these sensitivity analyses. Results are qualitatively similar to previous sensitivity results using an earlier (Base A) 2018 inventory. While the 2009 sensitivity anal yses cannot be used to judge absolute

contributions from each state or source sector , the results do indica te relative level of response among pollutants, sectors, and geographic areas.

3.1 Evaluation of Cape Romain

Figure 3-1 shows the results of emissions se nsitivity run for Cape Romain (ROMA) for summer. CMAQ was run using 30 percent re ductions from the 2009 Base D inventory assumptions for implementing existing state and federal regulations for major source categories of SO 2 , NO X , and PM. The results identify ge ographic origins for visibilityimpairing pollutants and serve as a good starting point when considering potential air quality benefits from additional controls for specific source sectors in VISTAS states or neighboring RPOs. The greatest benefits at Cape Romain in 2009 are projected to come from further reducing SO 2 from electric generating utilities (EGUs). Supplementary, smaller benefits are projected from additional SO 2 emission reductions from non-utility, industrial point sources. Reductions of NO X emissions from point sources (EGU and non-EGU) or ground-level sources (on-road vehi cles, off-road engines, and area sources) and reductions of primary carbon from point or ground-level sources are projected to be significantly less beneficial than reductions in SO 2 emissions.

## Cape_Romain, SC (Summer)

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Figure 3-1. Sources of Various Visibili ty-reducing Pollutants - Cape Romain Summer Using 2009 Base D Emissions.

Reductions in anthropogenic VOC emissions show no response in visibility, while a 30

percent reduction in biogenic VOC emissions re sults in a measurable improvement. However, controlling the VOCs from vegetation is not possibl e or appropriate. For this sensitivity run, further reducing SO 2 emissions from electricity generating utilities in South Carolina and Georgia would have the gr eatest benefit for Cape Romain; reductions from electric generating utiliti es in other VISTAS states would have additional but smaller benefits at Cape Romain. Approximate ly one half of the benefit at Cape Romain

from further SO 2 emission reductions would come from outside VISTAS states, with the majority coming from boundary conditions.

## 4.0 Reasonable Progress Evaluation

4.1 Area of Influence

The objective of the VISTAS Area of Influen ce analysis is to id entify the geographic source regions that are contribu ting to visibility impairment at the Class I areas on the 20 percent worst visibility days. This information will be used by the State as part of the evaluation and demonstration of reasonable pr ogress toward visibility improvement at Cape Romain.

VISTAS’ contribution assessment based on IMPROVE monitoring data (Brewer and Adlhoch, 2005) demonstrated that ammonium sulfate is the major contributor to PM 2.5 mass and visibility impairment at Class I ar eas in the VISTAS and neighboring states. As illustrated in Figure 4-1, on the 20 percent wo rst visibility days in 2000-2004, ammonium sulfate accounted for greater than 70 percent of the calculated light extinction at Class I areas in the Southern Appalachians and grea ter than 60 percent of the calculated light

extinction for coastal sites in the VISTAS st ates (excepting Everglades). In contrast, ammonium nitrate contributed less than five percent of the calculated light extinction at VISTAS Class I areas on the 20 percent worst visibility days. (Nitrate has a somewhat larger contribution on 20 percent worst days at Class I areas in neighboring states to the VISTAS region.) Particulate organic ma tter (organic carbon) accounted for 10-20 percent of light extinction on 20 percent wors t visibility days (except Everglades where organic carbon accounted for 40 percent).Figure 4 - 1 Average Extinction for 20% Worst Visibility Days in 2000-2004 using New IMPROVE Equation (data from VIEWS Sep 2006).

VISTAS emissions sensitivity analyses using the CMAQ regional air quality model project that reductions in SO 2 emissions from Electric Ge nerating Utilities (EGU) and non-EGU industrial point sources will result in the greatest improvements in visibility at

VISTAS Class I areas. EGU and non-E GU industrial point sources comprise 95 + percent
of the SO 2 emissions inventory in the VISTAS stat es. The emissions sensitivity analyses also indicate that improvements in visibility from reductions in NO X or primary carbon emissions from ground-level sources or point sources would be small. Based on these analyses, VISTAS states chose to focus thei r reasonable progress ev aluation for the first regional haze SIP on potential controls of SO 2 emissions from EGU and non-EGU point sources. To select the specific point sources that would be considered for each Class I area, states first identified the geographic areas that most likely influence visibility in each Class I area and then identified the major SO 2 point sources in th at geographic area.

4.2 Source Type Analysis

The following analyses are illu strative of an in itial approach from September 2005 to evaluate potential cont rol strategies. These analyses rely on the 200 km area surrounding

the Class I area and use the Base F4 model run.

VISTAS’ emissions inventory for the simplest area of influence, the 200 km concentric circle, indicated for Cape Romain in 2018 that fuel combustion from electric utilities and industrial processes produces the majority of the remaining SO 2 emissions (Table 4-1), with 86 percent of 2018 SO 2 total coming from fuel combustion.

Table 4-1. Source types 2018 Base G2 modeling ROMA – Percentage

Tier VOC NO X CO SO 2 PM 10 PM 2.5 NH 3 Fuel Comb. Elec. Util. 0 20 1 46 8 16 1

Fuel Comb. Industrial 1 17 2 34 3 5 0

Fuel Comb. Other 4 5 2 6 4 7 1 Chemical& Allied Product Mfg 1 1 0 4 1 1 1 Metals Processing 0 0 0 1 0 0 0

Petroleum & Related Ind. 0 0 0 0 0 0 0

Other Ind. Processes 6 6 1 6 8 9 2

Solvent Utilization 40 0 0 0 0 0 0 Storage & Transport 7 0 0 0 0 1 0 Waste Disposal & Recycling 4 3 7 1 7 15 0 Highway Vehicles 19 25 41 1 1 1 11 Off-highway 14 19 32 1 2 4 0

Miscellaneous 4 3 14 1 65 40 84SC DHEC defined its AOI to identify source regions for which additional controls might be considered and that are likely to have th e greatest impact on Cape Romain. To better

understand the sources that should be consider ed in a four factor analysis for reasonable progress, VISTAS contracted ENVIRON to partner with VISTAS’s Data Analysis contractor, Air Resource Speci alists (ARS), to provide SO 2 Areas of Influence for each o the VISTAS, and six neighboring, Class I Fede ral areas. ARS gene rated meteorological back trajectories for IMPROVE sites in VISTAS and neighboring states. Back trajectory analyses use interpolated measured or modele d 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. Back trajectories account for the impact of wind direction and wind speed on delivery of emissions to the receptor, but do not account for chemical transformation and dispersion

of emissions.

Trajectories were generated using the Hybr id-Single Particle La grangian Integrated Trajectory (HYSPLIT) mode l developed by the National Oceanic and Atmospheric Administration’s (NOAA) Air Resources Labora tory (ARL). HYSPLIT uses archived three-dimensional meteorological fields ge nerated from observations and short-term forecasts. HYSPLIT can be run to generate forward or backward trajectories using several available meteorological archives.

The data archives used in this analysis were the National Weather Service's National

Centers for Environmental Prediction Eta Data Assimilation System (EDAS). The EDAS fields are archived by the ARL across the con tinental U.S., including a buffer zone, at a horizontal resolution of 80 km before 2004, and at a horizontal resolution of 40 km starting in 2004.

The major model parameters selected for this analysis include those listed in Table 4-2.

Table 4-2. Back Trajectory Model Paramete rs Selected for VISTAS AOI Analysis

The choice of these parameters affects the trajectories generated and the final attribution analyses. In particular, trajectories tend to become increasingly uncertain the further back in time they are used. Vertical motion in the model is sometimes best represented by following actual vertical motion measurements (represented by mode l data), surfaces of constant entropy, or surfaces of constant pressure, depending on the meteorological conditions at a given location and time. The im pact of receptor height (or end height) on an individual trajectory is also important. Low-ending trajectories represent air parcelsnearer to ground level and high-ending tr ajectories may represent more accurate boundary layer flow above the local terrain.

For the years 2000-2004, back trajectories we re computed for the following IMPROVE sampling sites in and around the VISTAS region:

1. Breton, LA (BRET1) 2. Brigantine NWR, NJ (BRIG1) 3. Cadiz, KY (CADI1) 4. Caney Creek, AR (CACR1) 5. Cape Romain NWR, SC (ROMA1) 6. Chassahowitzka NWR, FL (CHAS1) 7. Cohutta, GA (COHU1) 8. Dolly Sods Wilderness, WV (DOSO1) 9. Everglades NP, FL (EVER1) 10. Great Smoky Mountains NP, TN (GRSM1) 11. Hercules-Glades, MO (HEGL1) 12. James River Face Wilderness, VA (JARI1) 13. Linville Gorge, NC (LIGO1) 14. Mammoth Cave NP, KY (MACA1) 15. Mingo, MO (MING1) 16. Okefenokee NWR, GA (OKEF1) 17. Shenandoah NP, VA (SHEN1) 18. Shining Rock Wilderness, NC (SHRO1) 19. Sipsy Wilderness, AL (SIPS1) 20. St. Marks, FL (SAMA1) 21. Swanquarter, NC (SWAN1) 22. Upper Buffalo Wilderness, AR (UPBU1)

Based on the five (5) years of individual b ack trajectories, ARS generated extinctionweighted residence time data for each IMPROVE site. Each hourly trajectory point was tagged with its associated sample (or end) date. Back trajectories with end dates corresponding to the 20 percent worst visibi lity days were weighted with calculated extinction values and summed into one-degree horizontal grid cells of latitude and longitude.

Extinction data is based on the IMPROVE Re gional Haze Rule dataset from November 2005, and is calculated based on the original IMPROVE algorit hm. For sites with less than three complete years of data, ARS developed and applied a data substitution protocol to fill missing data. Organic carbon and elemental carbon values were filled based on correlations to hydrogen and sulfate va lues for the same site. Other components were filled based on data from nearby sites.

Trajectory data were weighted by tota l extinction, and by extinction components including ammonium sulfate (AmmSO 4 ), ammonium nitrate (AmmNO 3 ), particulate organic material (POM), Light Absorbing Ca rbon (LAC), Soil, and Coarse Mass (CM).Weighting trajectories for the 20 percent wo rst days by sulfate extinction gave greater importance to days influenced by SO 2 emissions and lesser importance to days influenced by organic carbon emissions. This allowed a geographic area of influence to be

identified based on sulfate contributions and not skewed by contributions from fire.

These data files were provided to ENVIRON. ENVIRON was charge d with developing residence time plots to define the geographic area with highes t probability of influencing the receptor on the 20 percent worst days dominat ed by sulfate. Residence time over an area is indicative of general flow patterns, but since it does not acc ount for emissions and removal processes, it does not necessarily imply specific areas contributed significantly to haze compounds at a receptor site.

4.3 Area of Influence Data and Displays

The primary objective of the Area of Influence (AOI) displays and data sets are to assist the State in focusing its reasonable progres s analysis on those geographic regions and source categories which most impact a particul ar Class I Area. The sources of data used in these analyses include back-trajector y residence time data, provided by ARS and described above, and the VISTAS 2002 and 2018 36-km gridded emissions data (Base G, Aug 2006 inventory version).

Extinction weighted back-traje ctory residence time plots we re provided by ARS for all Class I Areas in the VISTAS region as well as for the surrounding neighboring states. These trajectories were proce ssed on an un-projected (i.e., geodetic lat/long 1 degree by 1 degree) grid and transferred to ENVIRON for further GIS processing and analysis. Backtrajectories were run for 100- meter and 500-meter start heights. Because the backtrajectories were to be combined with gridded emissions data, the first step in the analysis and GIS processing involved re -projecting these data to the Inter-RPO Unified Lambert Conformal Projection domain. Once the data we re re-projected, the data were mapped to the 36-km grid cells in the RPO projection using an area-weighted mapping routine. The re-projected extinction weighted back-traject ory residence times were then plotted on the VISTAS 12-km modeling domain. As sulfate is the primary visibility impairing component of the total extinc tion in the Southeast, the SO 4 -weighted residence time trajectories were chosen as the basic data set for display. For clarity, these data are scaled by the maximum value of the total extinct ion-weighted residence time within the modeling domain. The 100-km and 200-km distan ces from the Class I area were labeled.

Using the trajectories with the 100-m start height, the State has defined the SO 2 Areas of Influence as the area with grid cells s howing 10 percent (area shaded in yellow in following plots) or greater residence time (the frequency that winds pass over that area on the way to the Class I area on the 20 percen t worst days dominated by sulfate) for the period 2000-2004. Residence time over an area is i ndicative of general flow patterns, but

since it does not account for emissions and removal processes, it does not necessarily imply specific areas contribu ted significantly to haze co mpounds at a receptor site.Figure 4.2 is an extinc tion-weighted residen ce time plot for Cape Romain for 100-m and 500-m trajectory start heights.

Figure 4-2. Cape Romain SO 4 Extinction-Weighted Residence Time Plots for the

Period 2000-2004.

As an aid to the analysis, all regions with sc aled residence time values greater than five percent and greater than ten percent were noted on the display. Finally, county boundaries were overlaid to identify those co unties and 36-km modeling grid cells for which the extinction-weighted residence time back-trajectories exceeded five percent and ten percent. These data we re then exported as comma-delimited ASCII data files for further analyses. These residence time displays are used primarily to determine the regions (counties and/or grid cells) impacti ng each Class I Area. The next step in the analysis is to determine the potential imp act from emission sources within the regions identified from the extinction-weighted b ack-trajectory residen ce time displays and analyses.

Previous VISTAS contribution assessment, em issions sensitivity modeling, and inventory analyses have indicated that SO 4 is the largest contributor to haze on the 20 percent worst visibility days and that elec tric generating utilities and industrial point sources are the largest contributors to SO 4 levels at the Class I areas. These two source categories make up 95 percent of the VISTAS SO 2 inventory. Therefore these two source categories were identified as the highest priority for evalua tion of reasonable progress in 2018 at the Class

I areas.The potential impacts of SO 2 point source emissions for each Class I Area are determined by combining gridded emissions data and wei ghted back-trajectory residence times for the 36-km grid cells. The analysis was carried out with both the 2002 and 2018 base year emission inventories. Figures 4-3 and 4-4 display the gridded point source SO 2 emissions from the VISTAS modeling databases, for 2002 and 2018, respectively. These data were processed by summing all vert ical layers for each grid column and then summing across all days to obtain annual emission to tals for each grid cell.

Figure 4-3. Annual point source SO 2 emissions for the VISTAS region for in tons/year. (2002 BaseG)Figure 4-4. Annual point source SO2 emi ssions for the VISTAS region for in tons/year (2018 BaseG).

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 between grid cell centers, in kilometers. For the grid cell containing the Class I Area monitor, a weighting of 1/9 was applied. The distance-weighted point source SO 2 emissions are then combined with the gridded extinction-weighted back-trajector y residence times at a spatial resolution of

36-km.

The final step in the development of the disp lays and datasets involve the combination of the residence times and gridded emission data. The distance weighted (1/d) gridded point

source SO 2 emissions are multiplied by the total extinction-weighted back-trajectory residence times (SO 2 * Bext-weighted RT * (1/d)) on a grid cell by gr id cell basis. These results are then normalized by the domain-wide total and displayed as a percentage. The analysis is carried out for both the 2002 and 2018 base year inventories. Figure 4-5 displays the result of this final analysis st ep. Note that the outlined regions (in red and light orange) represent the extent of the > 10 percent and >5 percent sulfate extinctionweighted residence times, determined from the first step in the analysis. As with the residence time analysis, the results of the combined distance-weighted SO 2 emissions and extinction-weighted residence times are ove rlaid with county boundari es and exported to

comma-delimited ASCII data files for further analyses of emissions and control options for specific sources.To understand how emissions are predicted to change, the following figure compares

2002 and 2018 SO 2 multiplied by residence time.



### Comparison 2002 vs 2018 SO2 Emissions * Residence

Time Using 100 m Start Height 

### – Cape Romain, SC

2018 SO2 emissions 2002 SO2 emissions

Green circles indicate 100-km an d 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 = 56%

Figure 4- 5. Cape Romain 2002 and 2018 SO 2 Distance Weighted Emissions * SO 4 Extinction Weighted Residence Time Plots.

VISTAS states evaluated these plots of re sidence time weighted by sulfate extinction plots of gridded SO 2 emissions and defined the SO 2 Areas of Influence as those areas with residence time greater than 10 percent, ba sed on trajectories with start height of 100- m and four start times per day.

Extinction-weighted residence plots for Cape Romain indicate that the areas of probable

influence for sulfate contributi on to visibility impairment ar e similar to those for nitrate contribution even though the visibility impact of nitrate is an order of magnitude smaller than that of sulfate. From these plots we can initially conclude that it is appropriate to

focus on sources that contribute to sulfate concentrations a nd that sources near a Class I area are more likely to cont ribute to visibility impairment than more distant sources.

Gridded SO 2 emissions for the sulfate extinction-w eighted residence time plots indicate that large emissions sources at great distance from the Class I area can contribute to visibility impairment on some 20 percent worst days.4.4 Importance of Pollutants other than Sulfate

For completion, the following is a brief di scussion of the importance of other PM components and contributing source categories. When NO X controls are considered, 38 percent of NO X is from point sources, 40 percen t is from highway vehicles, and 15 percent is from nonroad engines. Elevated organic carbon (OC) and elemental carbon (EC) are indicators of fire. Some states may need to consider emissions from residential wood burning, forest fires (wild and prescrib ed), land clearing, a nd agricultural burning.

Nitrate (NH 4 NO 3 ) levels in winter can be significant and are dependent on the availability

of NH 3 ; 80 percent of NH 3 is from area sources (e.g. agriculture). Given that sulfates contribute the majority of visibility impair ment at Cape Romain on the 20 percent worst visibility days, SC DHEC believes it is appropriate to focus on SO 2 reductions in this first Regional Haze SIP.

4.5 Summary of Emission Inventories in Cost Curve Analysis

A necessary component of c ontrol strategy design is a thorough review of the emission inventories that are used in the modeling of th e future year base case. These inventories can shed light on the residual em issions from sources or sour ce categories defined to be within areas of transport or impact of a Cl ass I area. The most current (BaseG fall 2006) VISTAS future year (2018) base case and 2002 base year emissions were used to conduct this control cost analysis. For purposes of listing sources within the Area of Influence, data were provided for all sources with emissions over distance (Q/d) greater than 5 and maximum residence time (RTmax) greater than five. States independently defined the criteria for selecting which sources from th is list would be considered for reasonable

control measures.

The NIF-formatted and SMOKE-ready modeli ng files for both 2002 and 2018 base year

and base cases were obtai ned from VISTAS emissions development and modeling

contractors and converted to annual emi ssions and summed for the geography and

domain of interest.

Tables 4.3 and 4.4 present the State breakdown of these emissions for the entire VISTAS domain. Because the SMOKE-ready files were used in this analysis, the particulate matter transport factor (0.90 times inventor y values) is included in the PM emission

summaries. This factor is a pplied to account for the removal of a substantial portion of fugitive dust emissions near a source by surround ing vegetation and structures when such emissions are used in regiona l scale modeling analyses.

Table 4 – 3. VISTAS 2002 Base Year Annual Emissions SummaryTable 4 - 4. VISTAS 2018 Base Case Annual Emissions Summary

This review was conducted in a top down fashi on starting with an analysis of the major source categories in the domains of interest to determine which major categories had the highest residual contribution to the area. On ce the highest source types were identified, subcategories within those source types were reviewed. Again, a ranking of the highest residual sub source types was performed and additional analyses on these categories were conducted. Using the extinc tion weighted analysis, th ese emission reviews and summaries like those presented in Figure 4-25, VISTAS made a decision to further review only point source c ontrols in increment to the Clean Air Act scenario.

In addition to reviewing the residual emission categories in the future year base, it was important to identify reductions that had al ready occurred within each category or at specific units. This allowed VISTAS States to determine if certain source categories that had yet to be controlled under the future year base case had the potential for reduction or if source types already reduced had reached th e full cost-effective (i.e., did states take advantage of this step of the analysis) potential.

Finally, once each subcategory was identified, unit level tables of emission comparisons from 2002 to 2018 were developed, allowing VIST AS States to review existing emission reductions and providing the ability to assign new cost-effective controls to units usingthe best control for the scenario. These tables presented comp arisons of 2002 and 2018 emission levels, for SO 2 , and future year control technology assignment (by IPM forecasting and State modificat ion) for point sources. N on-EGU unit-specific technology assignments were identified using the contro l efficiency tables provided by the VISTAS emissions inventory contractor, MACTEC.

Ultimately, the final control strategy decisi ons will include the application of BARTsubject source reductions in th e future year base case.

Figure 4 – 6. VISTAS Base G2 SO 2 Emission Contribution by Major Source Sector.

The 2018 IPM file used by VISTAS for EG U sources (RPO 2.1.9) was obtained and matched to the 2018 base case inventory of EGU sources. This step was conducted to ensure that incremental controls assigned to these source types did not duplicate existing base case assumptions. Because IPM does not assign a control efficiency with each control device applied to any SO 2 or NO X SC DHEC made some assumptions (based on IPM documentation) as to what pollutant-spe cific level of reduction was applied in the future year base case runs. These assumpti ons, by primary and secondary control device

code combinations for SO 2, are presented in Table 4-5.

Table 4 – 5. IPM Post Processing A ssigned Device Codes and Applied SO 2 Control

EfficienciesSince many of the control technology contro l cost equations within AirControlNET require additional unit-level characteristic da ta, we also made matches of the SMOKE IDA files to VISTAS NIF, EPA NEI, or EPA CAMD CEM data sets to obtain these variables when missing. Unit level boiler cap acity (MMBtu/hr) or NETDC (MW) values are required for capital and operating and main tenance cost calculations for many of the

SO 2 applied technologies. In cases where th ese nameplate capacity values could not be identified, emission weighted capacitie s (based on the final EPA 2002 NEI) were assigned to boilers using a primary (highest emitting) SCC. Table 4-6 presents these weighted capacities. Additionally, stack flow, sulfur content, and primary SCC assignment were necessary to cross-reference available incremental control technologies to the base case emissions inventory data. These variables were obtained where matches could be found, in priority order of VISTAS, CAMD, and other EPA datasets, respectively.

Table 4 - 6. Emission Weight ed NETDC (MW) Association4.6 Application of AirControlNET Technologies

AirControlNET is a control technology analysis tool developed to support the EPA in its analyses of air pollution polic ies and regulations (Pechan, 2 005). The tool provides data on emission sources, potential pollution cont rol measures and emission reductions, and the costs of implementing those controls.

The core of AirControlNET is a relational data base system in which control technologies

are linked to sources within EP A emissions inventories. The system contains a database of control measure applicability, efficien cy, and cost information for reducing the emissions contributing to ambien t concentrations of ozone, PM 10 , PM 2.5 , SO 2 , and NO X , as well as visibility impairment (regional ha ze) from point, area, and mobile sources.

PM 10 and PM 2.5 as included in AirControlNET repres ent primary emissions of PM. The

control measure data file in AirControlNET not only includes the technology's control efficiency and calculated emission reductions fo r that source, but also estimates the costs (annual and capital) for applicati on of the control measure.

Since available versions of AirControlNET contain the pr eprocessed application of control technologies to a predetermined set of EPA emission inventories, direct use of the model in this analysis was not possible. However, Alpine receive d approval from EPA’s Innovative Strategies and Economics Group (ISEG) to modify the AirControlNET version 4.1 source code (Sorrels, 2006) and data ta bles in order to make it useful to this study. The results of the applica tion of this modified version of the code still retain the applicability, efficiency, and cost information from the unmodified version of the source code, but were thereafter applied to the VI STAS modeling inventories with updated price

index scalars to reflect c ontrol costs in 2005-dollars.

Using the modified invent ories identified above, we ran every available SO 2 control strategy in AirControlNET agai nst the EGU and non-EGU point source inventories to develop a master list of available, incremental control strategies for the entire VISTAS 36-km domain necessary for VISTAS States to design command-and-control or costeffectiveness based control stra tegies by source or domain.

4.7 Development of AOI-Based Cost Curve

Each Class I area in the VISTAS modeling dom ain had an associated AOI as identified

earlier in this document. In order to be st determine where emission reduction has the greatest benefit, this geography was designed to limit the available source type list from including all sources within the entire domain.

These marginal cost curves include the application of all available control measures to all applicable point sources within the AOI. The curves will allow VISTAS States to determine if--based on the generic application of SO 2 control technologies from the associations originally developed in Ai rControlNET and improved upon with stakeholder input will help—attainment of reasonable further progress emission reduction objectivescan be enhanced while presumably minimizi ng the number and type of controlled sources

in each AOI.

Using a geocoded county list from these AOI s, SC DHEC compared the master list of incremental control measures from all point sources located within the boundaries of the AOIs. This list was then sorted by incremental cost-effectiveness (marginal cost) basis to

determine the most cost effective control suite available to attain emission reduction targets for SO 2 within each AOI. Each individual source had its own corresponding cost

effectiveness curve.

In aggregate, the results of these applications are SO 2 emission cost curves for all EGU and non-EGU point sources within the geographic domain of the AOI. Incremental controls on area and mobile sources were not considered in this analysis. An illustrative example of the steps involved with the cost effectiveness curve de sign can be found in

Attachment H-2.a of this document.

With each AOI cost curve, additional metr ics calculated for the distance from the emission release point to the Class I area IMPROVE monitor (in km), the 2018 residual emissions and distance (Q/d) or squared distance (Q/d^2), and the normalized 2018 SO 2 point source emissions times distance-weight ed residence time (RTMax) values for the county in which the emission re lease point was located were calculated for incremental

review and consideration. SC DHEC used th ese values to further determine control strategy development for Cape Romain.

## 5.0 Reasonable Progress Assessment

The State concluded that SO 2 emissions from EGU and non-EGU point sources in geographic Areas of Influence (AOI) are so urces to consider for further controls. VISTAS developed source matrices for SO 2 AOI for Cape Romain, using data delivered by ENVIRON for 2002 and 2018 SO 2 emissions multiplied by SO 4 extinction weighted residence time plots.

Spreadsheets were developed for each Class I area with:

• Plant name

• Point ID

• Tons SO2 projected for 2018

• Q (tons)

• Current control efficiency, CE (percent)

• Stationary source distance to Class I area, d (km)

• Analysis of emissions per distance from source, Q/d and Q/d 2

• RTMax, the maximum percentage of time th at winds pass over that area on the way to the Class I area on the 20 worst days

The ranking refers to the sour ce rank by Q/d when sources fro m all states are included.

In an analysis of emissions per distance from source, Q/d 2 is more representative when d is less than 20 km because plumes are still dispersing in two dimensions. After about 100 km, plumes only disperse in one dimension. The distance calculation is based on a single stack at a unit (when more than one are repres ented in the inventory) and is calculated in

distance in km to the IMPROVE monitor at each Class I area. The residence time for the county where the source is loca ted was reviewed. It was ge nerally agreed that states

would focus on those sources where RT max was equal to or greater than 10 percent. A

second matrix for sources in the SO 2 AOI was developed for sources with a 2018 Q/d > 5 when d was greater than 100 km, Q/d 2 > 0.03 when d was less than 20 km, and Q/d > 5 or Q/d 2 > 0.03 when d was 20-100 km (these values were chosen arbitrarily to limit the

number of sources on the list and focus on those that are most influential).

Next, SC DHEC elected to focus on those units that contributed greater than or equal to 0.01 percent sulfate visibility impairment at Cape Romain for several reasons.

SC DHEC chose to adopt the one percent th reshold based on the precedence established by other Federal programs.

1. The BART rule specifies that a maximum im pact of 0.5 dv is an acceptable threshold for establishing significance. This threshol d equates to roughly a 5 percent change in visible perception. This same significance level is used in the Prevention of Significant Deterioration/ New Source Review program for th e visibility air quality related value.2. The NOx SIP Call laid out a significance le vel for Section 126 petitions of 4 parts per million (ppm), that being the level to which a State's contribution to another state's ozone problem was considered signifi cant. Four ppm represents approximately 3.75 percent of the 1-hour ozone standard, which was in place at the time EPA promulgated the NO X SIP

Call.

3. For the CAIR rule, a PM contribution of 0.2 μg/m 3 was used to demonstrate a significant impact, which is 1.3 percent of the annual PM 2.5 standard of 15 μg/m 3

.

4. Lastly, when human health standards (NAAQS ) are proposed signif icant impact levels are assigned, which allow sources to determine their significance on air quality in the

area around their facilities. Sources that de monstrate that their "contribution" from the new or modified sources is less than these significance levels do not have to complete any further modeling. The SILS repr esent a percentage of the NAAQS.

After looking at all averaging periods for th e criteria pollutants, SC DHEC determined that the one percent threshol d proposed for reasonable further progress was as protective as or more protective than the significant im pact levels. The most restrictive threshold

identified was for NO X , which has a NAAQS of 100 μg/m 3 and a significance level of 1 μg/m 3 , which represents one pe rcent of the total.

Finally, SC DHEC considered available reso urces to evaluate the sources in Cape Romain’s sulfate AOI. SC DHEC recognized that there was neither sufficient time nor

resources available to evaluate all units w ithin a given AOI. Th erefore, a threshold

needed to be established to determine wh ich units would be evaluated. SC DHEC believes the one percent threshold is appropriate, given the contribution to the total visibility impairment at Cape Romain, and the limited resources av ailable to conduct the unit-by-unit evaluation for reasonable progress.

Table 5-1 shows the analysis for Cape Romain EGU sources that met the above criteria. The full spreadsheets containing all VISTAS Class I area result s can be found in

Attachment H-2.b.

Table 5-2. EGU Sources in South Carolina’s Sulfate AOI.

State Plant Point

ID 2018 Q (tons) CE (%) d (km) Q/d Q/d^2 RTMax Fraction

SC SANTEE COOPER

JEFFERIES 3 6,761 0 45.80 147.61 3.22 72.76 0.114308

SC SANTEE COOPER

JEFFERIES 4 6,609 0 45.80 144.30 3.15 72.76 0.111745

SC SANTEE COOPER

CROSS 001 719 95 63.26 11.37 0.18 72.76 0.046944

SC SANTEE COOPER

CROSS 002 3,280 87 63.26 53.43 0.84 72.76 0.046944

SC SANTEE COOPER

CROSS 3 3,835 0 63.26 60.62 0.96 72.76 0.046944

SC SCE&G:CANADYS 01 5,203 0 91.25 57.02 0.62 72.55 0.044029SC SCE&G:CANADYS 02 5,144 0 91.12 56.45 0.62 72.55 0.043588

GA SAVANNAH

ELECTRIC:

MCINTOSH STEAM –

ELEC SG01 7,015 0 155.93 44.99 0.29 31.04 0.014863

This spreadsheet was developed to incl ude each area source with Q/d > 5 or Q/d 2 > 0.03, indicating the plant name, industry descrip tion, emissions projections for 2018, current control efficiency (CE percent), distan ce from Class I Fede ral area, Q/d, Q/d 2 , RT average, RT maximum, Q/d*RT, and the fract ion a single source cont ributes to the total Q/d*RT for a Class I Federal area.

Control efficiency percent is important because it gives a se nse of which facilities are already controlled and by what percent, and wh ich facilities may be cont rolled further.

Next, an analysis of control options, generic co sts of controls, and co st per ton for various units contributing greater than one percent to a ny Class I Federal ar ea was developed. Spreadsheets containing unit-level emissions and other associated data for the Class I

Federal areas was matched with data from AirControlNET (Pechan, 2005) to give SO 2 control efficiency, annual SO 2 emissions reduction from 2018 Base Case, total annualized cost (in 2005 dollars ), and cost per t on reduced for applic ation of specific

control measures.

SC DHEC reviewed the sources, emissions , control options, and costs from the SO 2 AOI

matrices and defined sources for which the F our Factor Analysis was to be conducted. The same few categories of point sour ces contribute to the majority of SO 2 emissions, (fuel combustion from electric utilities and fu el combustion from industrial sources), with

little contribution from other sources. Ther efore, SC DHEC eliminated other source categories from the Four Factor Analysis. SC DHEC next looke d at source-specific costs, existing controls, re maining useful life, envir onmental and energy impacts.

## 6.0 Four Factor Analysis

Section 169A(g)(1) of the Clean Air Act (CAA) and 40 CFR 51.308(d)(1)(i)(A) outline four statutory factors that ha ve been identified as mandatory for purposes of establishing a reasonable progress goal for any mandatory Cl ass I Federal area within a State: cost of compliance, time necessary for compliance, energy and non-air quality environmental impacts of compliance, and remaining useful life of any existing s ource subject to such requirements. These statutory factors would be specific to the sour ces being considered

for additional controls.

6.1 The Four Statutory Factors

6.1.1 The Cost of Compliance

The “cost of compliance” is a factor used to determine whether compliance costs for sources are reasonable compared to the emi ssion reduction and visi bility improvement they will achieve. Note that visibility improve ment is not only relate d to tons of pollutant removed, but also involves how the pollu tant or chemical compound affects the

extinction coefficient in each Class I Fede ral area. For example, on a pound to pound comparison, sulfate particulate im pairs visibility greater than does coarse particulate.

Costs should be determined for one-time capital costs, as well as ongoing annual operation and maintenance costs.

6.1.2 Time Necessary for Compliance

The “time necessary for compliance” factor may be used to adjust the reasonable progress goals to reflect the degree of im provement achievable w ithin the long-term strategy period (as opposed to the improveme nt expected at full implementation of a control measure) if the time needed for full compliance exceeds the length of the longterm strategy period. For instance, if the implementation of a control measure could not be completed within the sche dule outlined by the c ontrol strategy, the RPG should reflect what visibility improvement could be e xpected within the strategy period.

For example, if construction labor availability constraints preclude the installation of

controls at all sources of a particular category within the LTS period, the RPG should reflect the visibility improvement anticipat ed from installation of controls at the percentage of sources that co uld be controlled within the strategy period. (The SIP could

still include control strate gies that extend beyond the 2 018 milestone; in the above example, the visibility improvement anticipat ed from installation of controls at the percentage of sources that could not be cont rolled within the first strategy period would have to be applied in a later SIP).6.1.3 Energy and Non-Air Quality Envi ronmental Impacts of Compliance

The “energy and non-air quality environmental impacts of compliance” factor is meant to consider whether the energy requirements of the contro l technology result in energy penalties or benefits. For ex ample, controls on diesel engines may decrease the overall efficiency and require a signifi cant increase in diesel fuel consumption. The State should also consider any significant or unusual non-ai r environmental impacts, such as a waste stream that may be generated by a particular control technology.

6.1.4 Remaining Useful Life of the Source

The statutory factor of the “remaining useful life of the source” is applicable only to those measures that would requ ire retrofitting of control devices (or possibly production changes) at existing sources. In such cases, th is factor should be treated as one element of the overall cost analysis. For purposes of this analysis, the remaining useful life is the difference between the year of the reasonable progress analysis and the date the facility permanently stops operations. The remain ing useful life of a source affects the

annualized costs of retrofit controls.

6.2 Evaluating Four Statutory Factors For Specific SO 2 Emission Sources in Cape

Romain’s Area of Influence

The next step is to identify emission reducti ons that have already occurred within each source category and at specific units. Unit le vel tables of emission comparisons from 2002 to 2018 were developed, al lowing VISTAS States to review existing emission reductions. These tables assigned future ye ar control technology from IPM forecasting

and State modification for EGU and from cont rol efficiency tables for Non-EGU point

sources.

Once emission control profiles for specific un its were defined, the next step is to determine what, if any, additional control meas ures would feasibly be available, and to assign costs to those control measures. For EGUs, the 2018 IPM file used by VISTAS

for EGU sources was obtained and matched to the 2018 base case inventory of EGU sources. This step was conducte d to ensure that incrementa l controls assi gned to these source types did not duplicate existing base case assumptions. For non-EGUs, VISTAS used EPA’s AirControNET database, modified for the VISTAS emission inventories.

The core of AirControlNET is a relational data base system in which control technologies

are linked to sources within EP A emissions inventories. The system contains a database of control measure applicability, efficiency, and cost information for reducing emissions.

The control measure data file in AirC ontrolNET includes not only the technology's control efficiency, and calculat ed emission reductions for that source, but also estimates the costs (annual and capital) for application of the control measure.

Using the modified inventories identifi ed above, VISTAS ran every available SO 2 control strategy in AirControlNET agai nst the EGU and non-EGU point source inventories to develop a master list of incr emental control strategies for each unit in the VISTAS 36-kmdomain. For the sources within the AOI for Ca pe Romain, the master list of incremental

control measures was sorted to determine th e costs of incremental control measures. These data were combined in a master spr eadsheet with the distance from the emission release point to the Class I area IMPROVE monitor (in km), the 2018 residual emissions and distance (Q/d) or squared dist ance (Q/d^2), and the normalized 2018 SO 2 point source emissions times distance-weighted residence time (RTMax) values for the county in which the emission release point was locat ed. South Carolina evaluated these control measures and costs as part of their review of the statutory factors for reasonable further

progress.

The Regional Haze Rule requires that st ates consider the following factors and

demonstrate how these factors were taken into consideration in sel ecting the reasonable progress goal:

• Costs of compliance;

• Time necessary for compliance;

• Energy and non-air quality environmen tal impacts of compliance; and

• Remaining useful life of any potentially affected sources.

6.2.1 Cost of Compliance

As defined in Section 7.5.5, coal -fired electric utilities and coal-fired industrial boilers are the largest source categories contributing to SO 2 in 2018 in the Areas of Influence defined for Cape Romain. Industrial boilers using oil and commercial and institutional boilers using coal or oil ha d small contributions to SO 2 in 2018.

Sulfur dioxide emissions from utility, industria l, commercial, or institutional boilers can be controlled either by switchi ng the fuel source to a lowe r sulfur fuel content or by installing post-combustion controls. Costs vary by fuel source and boiler type and require source specific analyses for accuracy.

Bituminous coal is commonly burned in boilers in the eastern U.S. Switching to another

bituminous coal with lower sulfur conten t or blending bituminous coals can reduce SO 2 emissions with the least impact to boiler pe rformance. While sub-bituminous coal has a

lower sulfur content than bitu minous coal, it also has a lowe r heat rate, and therefore, more coal has to be burned to generate the same energy output. For boilers that are designed for bituminous coal, only a small frac tion of the fuel can be switched to low

sulfur sub-bituminous coal without affec ting boiler operations. Costs of boiler

modifications to accommodate low sulfur s ub-bituminous coal may make switching to sub-bituminous coal impractical. Contract in itiation and termination costs, differential fuel prices and heat rates, transportation co sts, and modification to boiler operations, fuel handling and waste handling systems will have to be considered specific to each source.

Flue-gas desulfurization (FGD) is the co mmon post-combustion control for coal-fired boilers. Flue gas is passed through an absorb ent for sulfur dioxide (generally limestone or lime) in either a wet sc rubber, dry scrubber, or spra y dryer. A calcium sulfatebyproduct is produced that may be further processed to pr oduce gypsum as a commercial byproduct. Costs of flue-gas desulfurization include initial construction costs and ongoing operational and maintenance costs for th e absorber tower, sorbent handling, and waste product handling facilities. Costs per ton vary with bo iler size, type, and facility citing considerations.

For oil-fired boilers, lower sulfur oil may be an option. Costs need to consider differential fuel prices and heat rate, boiler modifications , fuel handling costs, and maintenance costs. Conceptually, post-combus tion controls can be used for oil boilers, but there is little preceden ce for such installations.

6.2.2 Time Necessary for Compliance

For fuel switching, the time necessary to termin ate existing fuel contr acts and initiate new

contracts needs to be considered. Genera lly, two to three years may be required. Instillation of post-combustion controls will require three or more years depending on market availability of labor and materials and utility system-wide priorities. Time necessary for compliance will need to be refined for specific sources.

6.2.3 Energy and Non-Air Environmental Impacts

Switching to low sulfur fuel or installi ng post-combustion controls may reduce boiler heat rate and energy output. Scrubbers and spray dryers wi ll require additional safeguard for fuel handling and waste handling syst ems to avoid additional non-air quality environmental impacts such as increases effl uent in waste water discharges and storm

water run-off. These factors will need to be considered for specific to individual sources. Carbon dioxide is emitted as a byproduct of FGD, therefore impacts of increased carbon emissions will need to be considered, particularly if carbon emissions are limited in the future under climate change mitigation strategies.

6.2.4 Remaining Useful Life

Remaining useful life is specific to the facili ty for which controls are considered.

6.3 Process of Applying Statutory Factors

SC DHEC has just completed the Reasonabl e Progress Assessment for the first regional haze SIP. The following was SC DHEC’s Process on Reasonable Progress Assessment for the current time period (from the present to 2018):

Step 1: Determine Pollutants of ConcernVISTAS evaluated the species contribution on the 20 percent worst visibility days and concluded that sulfate accounted for greater than 70 percent of the visibility impairing pollution. The VISTAS States concluded that controlling SO 2 emissions was the appropriate step in addressing the reas onable progress assessm ent for 2018. VISTAS’ findings were consistent w ith the findings of the Sout hern Appalachian Mountain Initiative (SAMI). SAMI confirmed that sulf ate particles account for the greatest portion of the haze affecting Class I areas in the Southern Appalachian region and that these sulfates were produced in large part from SO 2 emissions from coal combustion.

Step 2: Determine which source sectors s hould be evaluated for reasonable progress.

Since SO 2 point source emissions in 2018 are proj ected to represent greater than 95 percent of the total SO 2 emissions inventory, the VISTAS States conc luded that the focus should be on electric generating unit (E GU) and non-EGU point sources of SO 2 emissions.

Step 3: Determine if the Clean Air Interstate Rule (CAIR) is sufficient for reasonable progress for subject EGUs.

SC DHEC evaluated the amount of SO 2 reduction from the EGU sector resulting from the implementation of CAIR. Sulfur dioxide emission reductions that ha ve been predicted by IPM to meet the CAIR requirements are not as certain due to the current rule’s reliance on unchecked trading and the use of banked Title IV allowances. SC DHEC intends to re-evaluate the IPM predictions of SO 2 reductions for CAIR at the time of our next periodic report in 2012 to ensure that the re ductions currently predicted by IPM for CAIR are in fact taking place where they are expected and needed. Based on the controls predicted by IPM under CAIR, we have conc luded that at this time these existing regulatory programs constitute reasonable meas ures for South Carolina EGUs during this first assessment period (betw een baseline and 2018).

Step 4: Determine which emission units should be evaluated based on impact.

SC DHEC calculated the frac tional contribution from all emission units within the SO 2 Area of Influence for Cape Romain and identified those emission units with a contribution of one percent or more.

Step 5: Evaluate the four factors. Each emission unit identified in Step 4 ab ove was evaluated usi ng the statutory and regulatory factors of: 1) cost of compliance, 2) time necessary for compliance, 3) the energy and non-air quality environmental impact s of compliance, and 4) the remaining

useful life of the emissions unit. SC DHEC believes that the cost of compliance is typically the dominant factor in whether a source will be required to install controls. Therefore, more emphasis was placed on cost of control as part of this reasonable progress assessment, as compared to the other three statutory factors. In addition, the SC

DHEC believes that the fifth f actor, visibility improvement, is considered by focusing the

evaluation on those units that contribute at l east one percent to visibility impairment at Cape Romain.For the limited purpose of evaluating the cost for the reasonable progress assessment in this first regional haze SIP, SC DHEC believes it is not equitable to require non-EGUs to bear a greater economic burden than EGUs fo r a given control stra tegy. The facility-byfacility and system-wide costs for impleme nting the Clean Smoke Stacks Act (included as Attachment H.7) were used by SC DHEC as justification of typical costs. The costs ranged from $912 to $1,922 dollars per ton of SO 2 removed, and the average costs per system ranged from $1,231 to $1,375 dollars per ton of SO 2 removed. These costs were estimated using the capital co sts from the CSA 2006 compliance plans, and the projected operating costs provided by Duke Energy and Progress Energy. The costs were evaluated on the same terms as the AirControlNet cost estimates so that they are directly comparable to the cost estimates for the non-EGU units in South Carolina.

SC DHEC focused the reasonabl e progress assessments on specific units at the following

non-EGU facilities in the S outh Carolina and Georgia:

• MeadWestvaco, SC

• International Paper, Georgetown, SC

• Giant Cement, SC

• International Paper, Savannah, GA

• Holcim: Holly Hill, SC

• DAK Americas, SC

The following sources were then asked to con duct a four-factor analysis. Each of the four factor analyses are disc ussed in more detail in Appendix N of South Carolina’s Regional Haze SIP.

## 7.0 Best Available Retrofit Technology (BART)

7.1 Background

As required by the CAA, the EPA included in the final regional haze rule a requirement for Best Available Retrofit Technology (BART) for certain large sta tionary sources that were placed in operation between 1962 and 1977. The BART-eligible sources are those sources that have the potential to emit 250 to ns or more of a visibility-impairing air pollutant; were placed in operation be tween 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 BA RT-eligible source that a State determines ‘‘emits any air pollutant which may reasonably be anticipated to cause or contribute to any impairment of visibility in any such area.’’ Accordingly, fo r stationary sources meeting these criteria, States must addre ss the BART requirement when they develop regional haze SIPs. The EPA has set guidan ce for identifying BART -eligible sources in 40 CFR Part 51 Appendix Y.

A BART-eligible source that is responsible for a 1.0 deciview (dv) change or more is considered to “cause” visibility impairme nt. Although the appropriate threshold may vary, the guidelines state that the contribut ion threshold used for BART applicability should not be higher than 0.5 deciviews. Thus a BART-eligible source that is responsible for a 0.5 dv change or more is considered to “contribute” to visibility impairment. Any

source determined to cause or contribute to vi sibility impairment in any Class I Federal area is subject to BART.

The guidelines direct that States should include SO 2 , NO X , and direct particulate matter (PM) emissions (including both PM 10 and PM 2.5 ) in determining whether sources cause or contribute to visibility impa irment. States may use thei r best judgment to determine whether VOC or ammonia emissions are likely to have an impact on vi sibility in an area.

To determine which BART-eligible sources ar e subject to BART, states have several options. A state may consider all BART-elig ible sources subject to BART; may perform analysis showing that the full group of BART-eligible sources in a State cumulatively may not be reasonably anticipated to cause or contribute to any visibility impairment in any Class I Federal areas; or may consider the individualized c ontribution of a BARTeligible source to determine whether a specifi c BART-eligible source is subject to BART.

Sources that are subject to BART must undergo a BART determination. 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 complia nce, (3) any existing pollution control technology in use at the source, (4) the remain ing useful life of the source, and (5) the degree of improvement in visibility that may reasonably be anticipated to result from the use of such technology.To demonstrate the degree of improvement in visibility from various BART control options, the States may run CALPUFF or anot her appropriate disper sion model to predict visibility impacts. Scenar ios would be run for the pre- controlled and post-controlled

emission rates for each of the BART cont rol options under review. The maximum 24-

hour emission rates would be modeled for a period of three or five years of meteorological data. States have the flexibil ity to develop their own methods to evaluate

model results.

7.2 Approach to Implementati on of BART Requirements

In order to meet the SIP submittal deadline, South Carolina has used a multifaceted approach to implementation of the federal regional haze rule BART requirements. The approach consists of source identification efforts; use of a permitting process to establish any resulting BART limits for inclusion in the SIP submittal (as well as participation in VISTAS BART subgroup to resolve technical issues spanning states in the VISTAS region); and ongoing consultation with affect ed sources, the EPA and FLMs throughout the BART process.

7.3 Identification of BART-Eligible Sources

EPA provided guidance for identifying BART-e ligible sources in 40 CFR Part 51, Appendix Y. South Carolina has followed th is guidance in identifying its BART-eligible

sources. The South Carolina 2002 air emissions inventory was reviewed to determine the population of potential BART-eligib le sources. The data were initially queried for any sources emitting SO 2 , NO X , PM 10 , VOC, or ammonia. The da ta set was refined based on emission rates, whether emission units fit in any of the twenty-six (26) listed source categories for BART, and available informa tion obtained through both review of permit and inspection reports and discussion with the Bureau of Air Quality’s permitting and regional office staff familiar with the facilities.

An information packet on BART was sent, an d additional information was collected from the remaining sources regarding potential emissions and BART eligibility from the standpoint of source category and date criteria. Through this iterative review process, thelist of potential BART-eligible sources was pared down to the twenty-one (21) BARTeligible sources listed below.

South Carolina BART-Eligible Sources:

ALBEMARLE CORP.

BOWATER INC. PAPER/PULP

BP AMOCO CHEMICAL-COOPER RIVER PLANT

DAK AMERICAS

EASTMAN CHEMICALINTERNATIONAL PAPER GEORGETOWN MILL

INVISTA MAY PLANT

INVISTA SARL SPARTANBURG (FORMERLY KOSA: ARTEVA)

ISG GEORGETOWN

MEADWESTVACO KRAFT MILL

MILLIKEN CHEMICAL: DEWEY PLANT

OWENS CORNING: ANDERSON

RHODIA CHARLESTON

SANTEE COOPER GRAINGER

SANTEE COOPER JEFFERIES

SANTEE COOPER WINYAH

SCE&G CANADYS

SCE&G WATEREE

SCE&G WILLIAMS

STONE CONTAINER FLORENCE

WELLMAN INC PALMETTO PLANT

A spreadsheet of some of the State’s BART-e ligible source emissions and distance to

Class I areas is included as Attachment H.4.

South Carolina BART-eligible sources were pr esumed to be subject to BART but were provided the opportunity to submit modeling de monstrations showing that they did not contribute to visibility impairment, i.e., ha d less than 0.5 deciview s (dv) impact, on any Class I area within 300 km and thus could be exempt.

7.4 Contribution Threshold

Determining whether a source causes or contribute s to visibility impairment is one step in the BART review process. The Guidelines for BART Determinations Under the Regional
Haze Rule state that, “A single source that is re sponsible for a 1.0 deciview change or

more should be considered to ‘cause’ visi bility impairment.” The guideline document also states that “the appropriate threshold for determining whether a source ‘contributes to visibility impairment’ may reasonably diffe r across states...” but, “As a general matter, any threshold that you use for determining wh ether a source ‘contrib utes’ to visibility impairment should not be higher than 0.5 decivi ews.” The rationale for these instructions is provided in the preamble to the BART guidance in the statement, “If ‘causing’ visibility impairment means causing a humanly perceptible change in visibility in virtually all situations (i.e., a 1.0 deciview change ), then ‘contributi ng’ to visibility impairment must mean having some lesser im pact on the conditions affecting visibility

that need not rise to th e level of human perception.” The guidance document itself also states that, “States remain free to use a threshold lower than 0.5 deciviews if they conclude that the location of a large number of BART-eligible sources within the State and in proximity to a Class I ar ea justify this approach.”The EPA’s documents strive to set these thresholds in the context of the human perception of visibil ity change. As noted above, th e EPA considers a 1.0-deciview change in visibility to be humanly percepti ble “in virtually all situations.” Also, the preamble to the BART guidance cites an anal ysis in an appendix of a NAPAP (National Acid Precipitation Assessment Program) report, which asserts that “changes in light extinction of five percent will evoke just noticeable changes in most landscapes” (Malm, 1990). (A five percent change is approxi mately 0.5 dv.) But, as noted above, the preamble also states that perceptibility is not a prerequisite for choosing a contribution threshold. Putting all this together, it appears that “causing” visibility impairment means having a humanly perceptible impact (for whic h EPA considers the practical threshold to be 1.0 dv) while “contributing” to visibility impairment means having a smaller impact (for which the EPA considers th e threshold to be 0.5 dv or so me smaller value) that may or may not be humanly perceptible.

The EPA argues that a contribu tion threshold of less than 0.5 dv impact per source is appropriate when multiple sources contribute, in order to limit the combined effect of these sources. As an example, EPA asserts th at if there were 100 s ources, each affecting visibility by 0.1 dv (presumably an imperceptib le amount), and the total impact would be 10 dv (which can be expected to be quite perceptible). The point being is that multiple sources can cause a larger impact than a single one. For BART purposes, visibility impacts are calculated as 24-hour averages of 1-hour plume impacts, so if the plumes from the various sources each impact the point of interest at some time during a 24-hour period (not necessarily all at the same hour), then the 24-hour average will reflect their combined impact.

The Regional Haze rule gives the states consid erable flexibility in determining a BART exemption threshold, stating only that a stat e should not set a thre shold higher than 0.5 dv, while indicating, as mentioned above, that the state should consider the number of emission sources affecting the Class I Fede ral area, the magnitude of the sources’ impacts, and the location of the sources. Th e number of BART sources and the different methods available for exemption by a source makes a straightforward, apples-to-apples determination of a proper threshold problem atic. In fact, give n the state’s limited resources, it would be impossible to consid er every source and every situation in a comprehensive manner. SC DHEC decided that a stepwise, common-sense approach would satisfy the requirements of the rule while at the same time making the decision making process manageable.

EPA has agreed that CAIR satisfies BART for SO 2 and NO X for those EGU facilities covered under the CAIR rule even though these EGUs could continue to affect visibility at Class I areas. In many cases, modeled impa cts for these EGUs will continue to be greater than 1.0 dv, or be define d as causing visibility impairment. Thus, for this first evaluation period, it appears th at the reasonableness of the BA RT process is a key factor in the determination rather than trying to establish a level of controls whereby each source will have a visibility impact at the Class I Federal area below the level of “causing” visibility impairment , much less contributing to visibility impairment. It should be recognized that, at some level, any source will contribute to visibilityimpairment if considered as part of a larger group. Since the BART rule allows for the exemption of a source, however, and EPA agrees that CAIR facilities that may impact a

Class I area above the 1.0 dv leve l can be exempted, it is clear that the rule intends that a source can be exempted even if that source’s impact when considered in aggregate with other sources might model above the 1.0 dv level. It seems clear that the total number of facilities impacting a Class I Federal area at one time is a key consideration in determining the BART exemption threshold.

For the eight facilities impacting the Wo lf Island Class I Federal area, SC DHEC concluded that the EPA suggest ed contribution threshold of 0.5 dv was appropriate in this situation based on a qualitative analysis of these facilities and their predicted visibility impacts. None of the eight facilities in que stion are in close proximity to Wolf Island, with the closest being just over 200 km awa y. Considering results of the visibility impacts modeling conducted, w ith four of the facilities reporting a 12 km screening (maximum) impact well below 0.5 dv and the other four reporting 4 km refined modeling impacts (98th percentile) belo w 0.3 dv, SC DHEC agrees with the state of Georgia that a 0.5 dv threshold is appropriate for the Wolf Island Class I Federal area and a lower

threshold was not warranted.

For the fourteen facilities impacting the Cape Romain Class I Federal area, a more detailed analysis was performed. Of the f ourteen facilities, tw o (SCE&G Williams and Wateree) performed a four-factor analysis a nd did not exempt. Of the remaining twelve facilities, only six (MeadWestvaco, DAK Am ericas, Santee Cooper Jeffries, Santee Cooper Winyah, International Paper Georgeto wn, and ISG Georgetown) were in close proximity to Cape Romain. For these six fa cilities, SC DHEC performed an analysis of the overlap in modeling impacts at Cape Ro main. For this analysis, SC DHEC compiled the 8th highest impacts for ea ch of the modeled years ( 2001, 2002, and 2003) to see what kind of overlap there was predic ted on these days. It is important to note that, for this modeling, maximum predicted 24- hour emission rates were use d. In actual operation, it is highly unlikely that each facility would be operating such that the maximum 24-hr emissions occurred at the same time. Thus, it is very likely that the actual combined impact at the class I area would be less th an the sum of combined impacts from these facilities. Nevertheless, th ese 8th highest modeling days resulted in a total of 132 modeled days. Of the 132 days, there were on ly a total of 12 days were two or more facilities overlapped (five days in 2001, four in 2002, and three in 2003) and only one day over the three years where three facilities overlapped. Thus, the overall impact from these facilities is relatively spread out, with very little overlap and certainly much fewer days of overlap than the 100 days used by EPA in the BART rule. In addition, a 0.5 dv

threshold is consistent with the 0.5 dv threshol d that all of the other VISTAS states intend to adopt for the Class I Federal areas in their st ates. In view of all this, a 0.5 dv threshold is appropriate and a lower threshold is not warranted.

As a result, SC DHEC concluded that the EPA-suggested contribu tion threshold of 0.5 dv was appropriate in this situation since there are a limited number of out of state sources that impact Cape Romain.7.5 Exemption of Point Source VOC for BART Purposes

The State of South Carolina has determined through modeling that Volatile Organic Compounds (VOC) from point sources are not anticipated to cause or contribute significantly to any impairment of visibility at Cape Roma in and should be exempt for BART purposes.

7.5.1 Method

The State of South Carolina determined thr ough modeling that VOCs from point sources are not anticipated to cause or contribute significantly to any impairment of visibility at Cape Romain.

Modeling was conducted through VISTAS. VISTAS is a collaborative effort of state governments, tribal governments, and various federal agencies established to initiate and

coordinate activities associated with the ma nagement of regional haze, visibility and other air quality issues in the Southeastern United States. VISTAS contracted with Georgia Institute of Technology to perform model sensitivity runs to determine the impact of point source VOCs on vi sibility in Class I areas.

Georgia Tech performed emission sensitivit ies to examine the impact of emission reductions on regional haze, annual PM 2.5 , and 8-hour ozone concentrations using CMAQv4.4_SOA_mods on the VISTAS 12-km modeling domain, which uses the 2009 OTW (on the way) BaseD emissions. One su ch sensitivity run reduced anthropogenic, point source VOCs by 100 percent. The pur pose was to quantify the impact of VOC

emissions from VISTAS BART sources on Class I areas.

The chart below illustrates the VOC contri butions for each of the following Class 1

Federal areas:

BRET = Breton, LA BRIG = Brigantine NWR, NJ CACR = Caney Creek, AR
CHAS = Chassahowitzka, FL
COHU = Cohutta, GA DOSO = Dolly Sods, WV EVER = Everglades, FL GRSM = Great Smoky Mountains National Park
HEGL = Hercules Glade, MO
JARI = James River Face, VA LIGO = Linville Gorge, NC
MACA = Mammoth Cave, KY MING = Mingo, MO
OKEF = Okefenokee, GA ROMA = Cape Romain, SCSAMA = Saint Marks, FL
SHEN = Shenandoah, VA SHRO = Shining Rock, NC SIPS = Sipsey Wilderness, AL SWAN = Swanquarter, NC UPBU = Upper Buffalo Wilderness, AR
WOLF = Wolf Island, GA

Figure 7 - 1. Maximum Point VOC Impact

7.5.2 Conclusions

The results show that the maximum impact from eliminating all point source VOC

emissions in the VISTAS 12-km domain is less than a 0.5 dv for all Class I areas in the

VISTAS domain. VISTAS and the State of South Carolina conclude that VOCs from point sources are not a visibility impairing pollutant for BART purposes and that BARTeligible sources do not need to consider VOC emissions.

7.6 Treatment of Ammonia

Similar to its treatment of VOCs, EPA guidanc e allows States the discretion to decide

whether or not ammonia emissions are to be considered for BART purposes based on

evaluations of the contributions of the emissions to haze at Class I areas in their areas of influence. One approach a State can use to determine whether applying BART will be needed is to evaluate the haze impacts of all current emissions from all BART-eligiblesources in the State. If the impact from all sources in the state is less than the contribution threshold established by the Stat e (0.5 dv for South Carolina), then source by source analysis for BART is not needed.

SC DHEC has determined through modeling that, with one excep tion, ammonia (NH 3 ) emissions from point sources are not anticipa ted to cause or contribute significantly to any impairment of visibility in Cape Romain and should be exempt for BART purposes.

7.6.1 Method

The State of South Carolina determined thr ough modeling that ammonia emissions from point sources are not anticipate d to cause or contribute signif icantly to any impairment of visibility at Cape Romain with the exception of one large point sour ce in close proximity.

VISTAS contracted with Georgia Institute of Technology to perform model sensitivity runs to determine the impact of point source ammonia on visibility in Class I areas.

Georgia Tech performed emission sensitivit ies to examine the impact of emission reductions on regional haze using CMAQv4.5 with SOA_mods on the VISTAS 12-km modeling domain, using the VISTAS 2009 OTW (on the way) Base F4 emissions. One such sensitivity run reduced BART-eligib le source ammonia by 100 percent. The purpose was to quantify the impact of amm onia emissions from VI STAS BART sources on Class I areas. Two episode s were examined: June 1 - July 10, 2002 and November 19 - December 19, 2002. The approach included calc ulating the extinction coefficient in dv (deciviews), then determining the maximum im pact of BART-eligible source ammonia. The chart below, taken from the VISTAS report BART in the VISTAS Region: Sensitivity to VOC, NH3, and Primary PM Emissions (included as Attachment H-5), shows the impact on the following twenty-two Class I Federal areas within the VISTAS domain.

During the periods modeled, th e ammonia emissions from all BART-eligible sources

contributed more than 0.5 dv to haze at Mammoth Cave National Park (MACA), Kentucky; Mingo Wilderness (MING), Missouri, Cape Romain National Wildlife Refuge Area (ROMA) South Carolina; and Swanqua rter National Wildlife Refuge (SWAN),

North Carolina.

The majority of ammonia emissions in VIST AS region come from four BART-eligible

sources as shown in Table 7-1 below.

Table 7 - 1. Major BART NH 3 Sources in the VISTAS Region

Facility State NH 3 Emissions (tons/year) Distance to Nearest
Class I Federal Area MeadWestvaco SC 130 29 PCS Phophate NC 206 31 PCS Nitrogen TN 1252 180PCS Nitrogen GA 1765 220

Analyses of spatial and temporal distributions of ammonia concentrations indicate that the primary point source ammonia contributor to Cape Romain haze is the Meadwestvaco Plant in North Charleston, South Carolina. Me adwestvaco is located 29 km from Cape

Romain.

The Regional Haze Regulations and Guidelines for Best Available Retrofit Technology (BART) Determinations final rule states that, “In regard to ammonia, we believe there is sufficient uncertainty about emission invent ories and about the potential efficacy of

control measures from location to location su ch that the most appropriate approach for States to take is a case-by-case appro ach...Thus, while ammonia can contribute to visibility impairment, we believe the de cision whether to cons ider ammonia as a visibility-impairing pollutant in a specific case where a potential BART source actually emits more than 250 tons per year of ammoni a is best left to the State” (FR 70 39114). As Table 7.1 indicates, Meadwestvaco’s BA RT-eligible units emit approximately 130 tons/year of NH 3

.

7.6.2 Conclusions

The BART requirements of the regional haze ru le allow states to determine whether or

not ammonia is to be considered a visibili ty impairing pollutant to be addressed for BART purposes. NH 3 emissions from BART sources may impair visibility; however the majority of NH 3 emissions in the VISTAS region are from a few BART sources. Removal of the large NH 3 emission sources results in mi nimal impact on visibility at Class I areas in the VISTAS region. At thei r discretion, states may ask those few large

sources to evaluate NH 3 impacts and potential controls for NH 3 . Based on annual CMAQ sensitivity analyses of the impacts of a mmonia emissions as well as current emission rates, South Carolina determined that requiring Meadwestvaco to model ammonia impacts is not necessary at this time.

## 8.0 Explanation of BART Exemption Modeling

8.1 Background

SC DHEC opted to consider its BART-elig ible sources subject to BART unless the source demonstrated exemption via modeling. BART-eligible sources can be excluded from BART determinations by demonstrating that the source cannot be reasonably expected to cause or contribute to visibility impairment in a Class I area. The threshold for determining that a source causes visibility impairment is set at 1.0 dv change from

natural conditions over a 24-hour averaging period. The BART guidelines also propose that the threshold at which a source may “cont ribute” to visibility impairment should not be higher than 0.5 deciviews; however, depending on factors affecting a specific Class I area it may be set lower than 0.5 deciviews.

As stated in the BART regulation the EPA’s preferred approach for determining cause or

contribution is an assessment with an ai r quality model such as CALPUFF or other appropriate model followed by comparison of the estimated 24-hour visibility impacts against a threshold above estimated natural cond itions to be determined by the State. The

EPA recommends that the 98 th percentile value from the modeling be compared to the

State’s chosen contribution threshold to dete rmine if a source doe s not contribute to visibility impairment and thus is not subject to BART. Comparison of the 98 th percentile value to the threshold must be made for each Class I area. For an annual period, this implies the eighth highest 24-hour value at a particular Class I area is compared to the contribution threshold. For a three-year modeling period, the 98 th percentile value may be interpreted as the high est of the three annual 98 th percentile values at a particular Class

I area or the 22 nd highest value in the combined three year record, whichever is more

conservative.

SC DHEC worked with the regional planning organizati on (RPO) VISTAS on development of the VISTAS Protocol for the Application of the CALPUFF Model for Analyses of Best Available Retrofit Technology (BART) (Attachment H-6). The common protocol was established to provide th e basis for a common understanding among the organizations performing BART analyses or reviewing BART modeling results in the VISTAS region.

The VISTAS protocol desc ribes common procedures fo r carrying out air quality modeling to support BART determinations that are consistent with the 40 CFR Part 51, Appendix Y guidelines. The protocol provides a consis tent model (CALPUFF) and modeling guidelines for BART determinati ons, clearly delineated modeling steps, a common CALPUFF configuration, guidance for site-specific modeling, and common expectations for reporting model results. De tails of the CALPUFF system can be found in Chapter 3 of the VISTAS protocol. Speci fic recommendations for its application for BART purposes are found in Chapter 4, and sp ecific information that should be included in site-specific protocols is found in Chapter 5.VISTAS contracted EarthTech to develop a version of the CALPUFF model appropriate for BART purposes. The VISTAS versi on of the CALPUFF model is CALPUFF

Version 5.754 and CALMET Version 5.7.

For BART modeling purposes, VISTAS made publicly available 12-km CALMET output files for the entire VISTAS modeling domai n (eastern United States) and provided CALMET output files for five 4-km grid subdomains covering the VISTAS states and VISTAS Class I areas. To generate the CA LMET input files, the VISTAS contractor used the MM5 databases developed by EP A for 2001, VISTAS for 2002, and Midwest RPO for 2003. For the 12-km grid large domai n covering the entire VISTAS region, the “No-Obs” setting was used. For the 4- km grid available surface and upper air

observations were used in a ddition to MM5 meteorological model outputs. Specific model settings were provided with the CA LMET files and via the CALPUFF website so that work could be replicated.

For CALPUFF modeling, source emissions were to be defined using the maximum 24- hour actual emission rate during no rmal operation for the most re cent three or five years.

If maximum 24-hour actual emissions were not available, continuous emission data permit allowable emissions, potential emissions , and emission factor s from AP-42 source profiles could be used as available.

Key points on specific CALPUFF, CALPOST, and POSTUTIL configuration that were to be used for BART modeling are:

• After running CALPUFF for an individual facility, NO 3 should be repartitioned in

POSTUTIL.

• Ozone data from non-urban monitors s hould be used as the background ozone input.

• The Pasquill-Gifford disper sion method should be used.

• In CALPOST Method 6 with monthly aver age RH for calculating extinction as recommended by EPA should be used.

• EPA default calculations of light extinction under curre nt and natural background conditions should be used. In addition, a source may also calculate visibility using the recently revi sed IMPROVE algorithm.

Additional discussion of the CALPUFF model and VISTAS recommended settings can be found in the VISTAS prot ocol in Attachment H-6.

8.2 South Carolina BART Source Exemption Modeling

SC DHEC requested that sources within South Carolina follow the VISTAS modeling protocol in development of their site specifi c protocols and explain any deviations that they proposed to use. In the site-specific modeling demonstrations submitted by South Carolina’s BART-eligible sources, the CALPU FF model incorporating three years of preprocessed MM5 meteorological data was used to evaluate the deciview change compared to natural background conditions at each of the Class 1 areas within 300 km of the source. The 4-km MM5 dataset prepared by VISTAS was used. The 98 th percentile delta-deciview (dv) value was determined at each Class 1 area and compared to the 0.5

dv contribution threshold.

Fourteen (14) of the twenty-one (21) facili ties submitted site-specific modeling protocols and subsequent modeling demonstrations based upon the VISTAS modeling protocol. The site-specific protocols as well as the demonstrations are found in Attachment H-6. The protocols and demonstrations were reviewed by SC DHEC’s Modeling Section within the Bureau of Air Quality (BAQ) a nd also shared with both EPA and FLMs for

their review and comment. Their comments were shared with the facilities.

The individual facility modeling demonstra tions were also shared with both EPA and

FLMs for their review and comment. The resu lting comments were in turn shared with

the facilities. SC DHEC worked with EP A and FLMs throughout the process to resolve many of the issues and concerns reflected in their comments. SC DHEC BAQ staff

reviewed the demonstrations to determin e whether the sources have less than 0.5 deciview (dv) impact on any Class I area within 300 km of the source. Sources demonstrating less than 0.5 dv impact are cons idered exempt. Sour ces contributing 0.5 dv impact or greater are cons idered subject to BART and are thus required to proceed with an analysis of what control measures, if any, constitute BART for the source.

Review of the demonstrations submitted led to the determination th at the BART-eligible

sources at nineteen of the tw enty-one facilities in Table 8-1 should be exempt from BART determination requirements. Base d upon these demonstrations, SC DHEC initially proposed exemption of sources at nineteen facilities. Table 8-1 below provides a summary of the impacts of each facility’s BART-eligible source on the Class I Federal

areas affected.

Table 8 - 1. BART Modeling Results

Facility Class I Area* Impact (Change in dv)

Albemarle VOC Exempt BP Amoco Chemical - Cooper

River Plant VOC Exempt

Rhodia – Charleston VOC Exempt

Eastman Chemical VOC Exempt INVISTA – Spartanburg VOC Exempt

Stone Container – Florence Cape Romain 0.375** ISG Georgetown Cape Romain 0.279 Owens Corning – Anderson VOC Exempt Milliken Chemical – Dewey VOC Exempt

DAK Americas Cape Romain

Wolf Island 0.471

MeadWestvaco Corp. Cape Romain 0.438Okefenokee

Wolf Island SCE&G – Canadys Cape Romain

Okefenokee

Wolf Island 0.341

International Paper - Georgetown Cape Romain

Wolf Island 0.456

Wellman – Palmetto Cape Romain Linville Gorge Shining Rock 0.224

INVISTA - Camden Plant Cape Romain

Great Smokies Linville Gorge Shining Rock 0.244

Bowater Cape Romain

Great Smokies Joyce Kilmer Linville Gorge Shining Rock 0.381

Santee Cooper – Jefferies Cape Romain

Wolf Island 0.318

SCE&G – Williams Cape Romain

Okefenokee

Wolf Island 1.83

Santee Cooper – Winyah Cape Romain

Wolf Island 0.476

Santee Cooper – Grainger Cape Romain Swanquarter 0.235**

SCE&G – Wateree Cape Romain

Great Smokies Linville Gorge Shining Rock

Wolf Island 0.72

* Class I Federal areas w ithin 300 km of the source ** Screening modeling max impact

Six of South Carolina’s BART-eligible s ources are EGUs. Cons istent with BART regulation requirements and EPA guidance, BART-eligible sources at electric utilities complying with EPA’s Clean Air Interstate Rule (CAIR) that wished to demonstrate exemption were allowed to model only dire ct PM fine emissions . Compliance with

CAIR constitutes BART for these sources for emissions of NO X and SO 2

.

On March 8, 2007, South Carolina submitted to EPA a parallel processing request for its version of CAIR. South Carolina subsequent ly received comments from EPA on this rule on May 23, 2007. Although the Department in tends to accommoda te EPA's proposed changes, the South Carolina Administra tive Procedures Act, which sets forthrequirements for promulgating new or revised regulations, requires an extensive review period. The Department does intend to purs ue incorporation of these changes and will commence that process as soon as possible. South Carolina's CAIR became stateeffective on June 22, 2007. EPA has indicated it is willing to provide South Carolina with abbreviated SIP approval for its version of CAIR (submitted to EPA as a final package on August 16, 2007). The proposed revi sions, however, do not affect the CAIR

allocation schedule and do not have a dir ect impact on existing BART-eligible EGUs; therefore, no BART compliance issues are expected for South Carolina EGUs.

A number of the BART-eligible EGUs in S outh Carolina have already installed or are installing scrubbers to control SO 2 and selective catalytic reduction (SCRs) to control

NO X . Table 8-2 below summarizes the status of controls on these BART-eligible EGUs.

Table 8-2. South Carolina BART-Eligible EGU Compliance Summary

Plant Name Units Plant Type Existing NOx Control Existing SO2

Control Projected

Controls

SANTEE

COOPER -

JEFFERIES 3 O/G Steam ESPs (1969/75) N/A N/A

SANTEE

COOPER -

JEFFERIES 4 O/G Steam ESPs (1970/75) N/A N/A

SCE&G

WATEREE WAT1 Coal Steam SCR(2002)/Low No x burners(1997)/FF( 1998)/ESP(1982) N/ A FGD (2009)

SCE&G

WATEREE WAT2 Coal Steam SCR(2002)/Low No x burners(1998)/FF( 1998)/ESP(1986) N/ A FGD (2009)

SCE&G

WILLIAMS WIL1 Coal Steam SCR(2002)/Low Nox burners(1998)/ESP( 1984) N/A FGD (2009)

SANTEE

COOPER -

WINYAH 1 Coal Steam S CR (2003)/ESP(1971) FGD 2007) Upgrade FGD efficiency to 95% by 2009

8.3 Use of the New IMPROVE Algorithm

During the regional haze SIP development process, the IMPROVE Steering Committee

made recommendations for a new IMPROVE equation. Among other things, the new equation includes components that take into account the eff ects of sea salt and site specific Rayleigh scattering. These are importa nt components to appropriately consider

for South Carolina’s coastal and several other facilities. Additional discussion of the new IMPROVE equation can be found in Appendix O.

VISTAS contracted Dr. Ivar Tombach to develop a post processor to allow CALPOST outputs to be used with the new IMPROVE equation. SC DHEC submitted to U.S. EPA Region 4, a request for approval to use th e new IMPROVE equation and postprocessor developed by Dr. Tombach in BART modeling. A discussion of the rationale for use ofthe new IMPROVE equation follows. The new IMPROVE postprocessor and

instructions are included in the request to EPA for approval of its use in Attachment O.

Rationale for Need for Use of New IMPROVE Equation . The new IMPROVE equation is a much better representation of the effects of particulate matter on light extinction than the old equation and takes into account the latest scientif ic understanding of several

parameters.

1. The new algorithm overcomes biases of the old algorithm on the haziest days and the clearest days as demonstrated by comparing the measured light extinction from nephelometers at Class I areas to li ght extinction calculat ed using each of the equations.

2. The new algorithm recognizes spatial and te mporal variation in light extinction as

size distribution of the aerosol changes by increasi ng extinction efficiency as sulfate, nitrate and organics concentrations increase.

3. The new algorithm incorporates a term to re flect the contribution of fine sea salt and its hygroscopic growth with increasing relative humidity recognizing research findings showing that fine sea salt can be an importa nt contributor to light

extinction in coastal areas.

4. The new algorithm reflects research fi nding that the mass concentration of particulate organic matter in rural areas is greater than represented by the old equation.

5. The new algorithm includes a NO 2 term to represent times when light absorption by NO 2 is a meaningful contribut or to light extinction.

6. The new algorithm incorporates site-specific Rayleigh scattering values to better represent sites close to sea level or with very hot or cold climates.

With this combination of revisions to the IMPROVE equation, the resulting apportionment of extinction to various com ponents is more accurate on the haziest and clearest days. This is important for the de velopment of emission control strategies since the benefits of control of concentrations of each species will be represented more correctly with the new algorithm

A majority of South Carolina’s BART eligible sources are located in coastal areas. The ability to appropriately represent the contributio n of sea salt for these sources is important in determining their contribution to haze and evaluating the benefit of potential control strategies. U.S. EPA Region 4, the National Park Service, and the US Fish & Wildlife Service determined that adding site-specific da ta to account for the impact of sea salt and Rayleigh scattering to the old IMPROVE equation is not appropr iate, but rather the entire new IMPROVE equation should be used. The spreadsheet developed by Dr. Tombach to implement the entire new IMPROVE equa tion for use with CALPUFF contains a

modification of CALPOST that calculates the light extinction from the CALPUFF output. In their review of the spreadsheet a nd supporting documentation, EPA Region 4 staff commented that the VISTAS methodology contai ned in the spreadsheet developed by Dr. Tombach appropriately implements the featur es of the new IMPROVE equation, with the exception of the nitrogen dioxide term. EP A Region 4 further stated that with theaddition of their recommendation for addressing the NO 2 term, the VISTAS methodology to incorporate the new IMPROVE equation is acceptable on a case-by-case basis upon consultation with the EPA Regional Office.

South Carolina’s request and approval to use the new IMPROV E equation for BART purposes is found in Attachment O.

8.4 Conclusions

In total, nineteen of South Carolina’s twenty-one BART-eligible sources were able to demonstrate that they did not cause or contri bute to visibility impairment in any Class I

area within 300 km of the sour ce. At least 10 of those sources used the new IMPROVE equation in efforts to demonstrate exemption. The two facilities that were not able to show they were exempt through modeling we re SCE&G Williams and SCE&G Wateree. However, these sources are subject to CAIR . SC DHEC has determined that CAIR is equivalent to BART level cont rols. Therefore, no BART de terminations are required for

these facilities.

## 9.0 BART Determinations and Conclusions

As stated earlier in the narrative of this appendix, only tw o of South Carolina’s twentyone BART-eligible sources failed to exempt out of BART through modeling. However, as they are subject to CAIR, and South Caro lina has determined that implementation of CAIR is equivalent to BART for SO 2 and NO X . The BART determinations for PM for

these sources found no reasonabl e control measures are ava ilable. In addition, DAK Americas, LLC., has opted to accept emission li mitations for its Cooper River Facility in its Part 70 Air Quality Operating Permit (Conditions 5.E.34 and 6.B.51) so as to demonstrate exemption from further BART an alysis. These complete list of BART determinations are included as Appendix H-6.

## 10.0 Final Long-Term Strategy and Reasonable Progress

Goals

As stated in section 2.0 above, the regiona l haze rule requires States to establish reasonable progress goals, expr essed in deciviews, for visi bility improvement at each affected Class I area covering each (approxima tely) 10-year period until 2064. This first set of reasonable progress goals must be me t through measures contained in the state’s long-term strategy covering the period from the baseline until 2018. This section discusses development of South Carolina’s long-term strategy.

10.1 Long-Term Strategy
Ammonium sulfate is the most important cont ributor to visibility impairment and fine particle mass on the 20 percent worst and 20 percent best vi sibility days at Cape Romain. Sulfate levels on the 20 percent worst days account for 60-70 percent of the visibility impairment. Across the VISTAS region, sulf ate levels are higher at the Southern Appalachian sites than at the coastal sites. On the 20 percent clearest days, sulfate levels are more uniform across the region. Reduction of SO 2 emissions would be the most effective means of reducing ammonium sulfate. Ninety-five percent of SO 2 emissions in

North Carolina are attributable to electric generating fa cilities and i ndustrial point sources. Thus, the long-term strategy for this first Regional Haze SIP focused on

reductions in SO 2 emissions. There are significant control programs in place in South Carolina and the region to reduce SO 2 emissions between the baseline period and 2018. Most notably, CSA and CAIR are predicted to result in the greatest reduction from EGU

SO 2 emissions in South Carolina.

Visibility improvements on the 20 percent worst days at Cape Romain are expected to be better than the uniform rate of progress glidepath by 2018 based solely on reductions from existing and planned emissions controls. The percentage of the target reduction achieved for Cape Romain on the 20 per cent worst days using the new IMPROVE algorithm is approximately 110 pe rcent. This means that the rate of improvement is at least 10 percent greater than the uniform ra te of progress by 2018. In fact, visibility improvements at most of the coastal Class I Fe deral areas are projecte d to be better than the uniform rate of progress.

In addition to improving visibility on the 20 pe rcent worst visibility days, states are also required to protect visi bility on the 20 pe rcent best days at the Class I Federal areas. Visibility on the 20 percent best days is projected to improve in 2018 at all VISTAS

Class I Federal areas as a result of th e 2018 Base G2 emissions reductions. The percentage of the target achieved for Cape Ro main is about -10 percent. Zero percent change would mean no change in visibility; while -10 percent means that visibility is better than no change or a 10 percent improvement has occurred.10.2 What Additional Emission s Controls Were Considered as Part of the Long Term Strategy for Visibility Improvement by 2018?

Section 308(d)(3)(v) of the regional haze rule lis ts several factors that must be addressed

in each SIP. These factors include the role of fire at Class I Federal areas and status of state planning for smoke management, the role of dust and fine so il at Class I Federal areas and status of state plans to mitigate emissions from construction activities, and the

role of NH 3 and potential benefits if emissions fr om agricultural sources were mitigated.

Section 51.308(d)(1) of the final RHR requires that a State establish “reasonable progress goals” for each Class I Federal area within th e state. In establishing reasonable progress goals, the CAA provided analytical requirements for setting these goals (know as the four factors) which include: the cost of complia nce, the time necessary for compliance, the energy and non-air quality environmental im pacts of compliance, and the remaining useful life of any existing source su bject to such requirements.

In developing South Carolina’s reasonabl e progress goals, VISTAS, in November 2006, contracted with Alpine Geophysics to develop a cost control analysis that showed various control options for sources with in an area of influence for Cape Romain and other Class I

areas.

Since sulfate is the predominant cause of vi sibility impairment in the VISTAS region,

South Carolina and the other VISTAS states decided to concentrate on reduction of SO 2 , the precursor to sulfate formation, during this first planning period. As such, the cost

control list was sorted for the SO 2 emissions (Q) of each source divided by the distance (d) in kilometers to each class one area, or Q/d, and maximum residence time, RTmax. All sources with a Q/d greater than or equal to five and an RTmax greater than or equal to 10 percent were added to the list for further consideration because it has been determined that these sources may contribute to visibi lity impairment on the 20 percent worst days.

Sources meeting these criteria include:

• Santee Cooper – Jefferies, South Carolina

• Santee Cooper – Cross, South Carolina

• SCE&G – Canadys, South Carolina

• International Paper – Georgetown, South Carolina

• Giant Cement, South Carolina

• Holcim Holly Hill, South Carolina

• MeadWestvaco, South Carolina

• DAK Americas, South Carolina

• International Pa Savannah Electric – McIntosh, Georgia

• International Paper – Savannah, Georgia

A cost threshold of $2,000.00 per ton for controls was then applied. Of the remaining facilities, all EGUs subject to CAIR were not considered as part of South Carolina’scontrol strategy because CAIR makes substantial SO 2 emission reductions and SO 2 is the leading pollutant that cont ributes to visibility impa irment at Cape Romain.

SC DHEC multiplied the Q/d factors and th e RTmax factors for all sources within a sulfate AOI for a given Class I area, then calculated a total and divided each product by

that total to estimate the fracti onal contribution of each unit. Only the units with fractions of 0.01 or above (or greater th an or equal to one percen t contribution) were then evaluated using the four factor analysis.

Under South Carolina’s approach, facili ties whose costs fa ll below the $2,000.00

threshold amount established were asked to conduct a four factor analysis. These

facilities include:

• MeadWestvaco, SC

• International Paper, Georgetown, SC

• Giant Cement, SC

• International Paper, Savannah, GA

• Holcim: Holly Hill, SC

• DAK Americas, SC

The final four-factor analysis for the rema ining non-EGU sources was performed by the

facilities and reviewed by the Department.

The results of the four factor analyses (contained in Appendi x N) indicate that no

additional controls are reasona ble at this time. However, further future reductions by way of additional controls have been disc ussed and will be evaluated during the next planning stage.

10.3 Reasonable Progress Goals

The Regional Haze Rule at 40 CFR section 51.308(d)(1) requires States to establish reasonable progress goals for each Class I area within the state (expr essed 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 visibil ity conditions if improvement co ntinues 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 pr ogress goals for South Carolina’s Class I Federal Area, Cape Romain. To calculate the rate of progress represented by each reasonable progress goal, SC DHEC compared baseline visibility conditions to natural visibility conditions at Cape Romain and determined the uniform rate of visibilityimprovement (in deciviews) that would need to be maintained during each implementation period in order to attain natural visibility conditions by 2064.

These controls were modeled in CMAQ as partof the long-term strategy. The modeling

results were used to set the final reasonabl e progress goal. Prelim inary results confirm what SC DHEC knows, that the final reasonable progress goals are at le ast as stringent as the Base G2a modeling results and are slight ly more stringent when other reasonable

measures are taken into account.

VISTAS has demonstrated that the 2018 Base G2a control scenario provides for an improvement in visibility better than the uni form rate of progress for Cape Romain for the most impaired days over the period of the implementation plan and ensures no degradation in visibility for the least impaired days over the same period. In addition, SC DHEC expects that IMPROVE monitoring result s for 2018 will at that time be used to establish a new baseline for the next planni ng period. Table 10-1 lists South Carolina’s Reasonable Progress Goals.

Table 10-1. Reasonable Progress Goals for South Carolina

Class I Area Baseline Visibility (20% Worst Days) Reasonable Progress Goal (Deciview Improvement Expected by

2018, 20% Worst Days) Baseline Visibility (20 % Best Days) Reasonable Progress Goal (Expected Visibility Degradation, 20% Best Days)

Cape Romain 26.5 22.7 (3.8) 14.2 12.7 (1.5)

In conjunction with VISTAS, a final CM AQ modeling run were performed in the

fall/winter of 2007 to account for the cumulati ve benefits of the Base G2a emissions controls, BART controls, and additional meas ures to achieve reas onable progress by 2018. Preliminary results from this analysis show that South Carolina’s aforementioned reasonable progress goals for Ca pe Romain are reasonable and appropriate for this initial planning stage.