# Appendix L.8
TN BART Non-Exempt Demonstrations

### Alcoa BART Determination Report................

.. ......... ..... ........ ..... ..... . ............................. ................ ......... . ... . ....3

DuPont-Old Hickory Final BART Determination Report - Old Improve Equation........

.................... ..........199

DuPont-Old Hickory Final BART Determination Report - New Improve Equation...........

............... ...........291

DuPont-Old Hickory BART Determination Report - Revised Control Costs/Visibility Improvement and Proposed Control Strategy....................

............... ........301

Eastman Chemical BART Determination Report ..................................

..................... .......... .......................303

TVA-Cumberland BART Determination Report

............... .................. ..................... ............... ................ . ..... 349

EPA Region 4 comments on Alcoa ’s BART BART Determination Analysis

... ....... ..... . ... ................... ........367

EPA Region 4 c omments on DuPont-Old Hickory's Determination Analysis

............ ..................... .. . ..... . .... 377

EPA Region 4 comments on Eastman's BART Determination Analysis

....... .................. ....... ..................... 380

Alcoa Response to EPA Region 4 comments on Alcoa's BART Determination Analysis......... ...................390

Eastman Chemical Response to EPA Region 4 commentson Eastman Chemical's BART Determination.Analysis.........................................................

.................... ... 402

E astman Chemical Response to NPS comments

on Eastman Chemical 's BART Determination

. Analysis

. ..................................................... .................... ..... . 414

TVA Response to EPA Region 4 comments on TVA-Cumberland 's BART Determination Analysis

...... ...428

TN BART Schedule Letter to Alcoa..........................................................................................................

... .4 29

TN BART Schedule Letter to DuPont-Old Hickory................................................................................

.... ..4 32

TN BART Schedule Letter to Eastman Chemical.................................................................................

....... ..4 35

TN BART Schedule Letter to TVA...

.................................................................................................... ..... ....4 38

# BART Determination Report for Alcoa, Inc. – Tennessee Operations

March 2007

Prepared for: Alcoa, Inc. – Tennessee Operations Blount County, Tennessee

### BART DETERMINATION REPORT FOR ALCOA, INC. – TENNESSEE OPERATIONS BLOUNT COUNTY, TENNESSEE

Prepared for: Alcoa, Inc. – Tennessee Operations Blount County, Tennessee

Prepared by: URS Corporation 1093 Commerce Park Drive, Suite 100 Oak Ridge, Tennessee 37830 0702261

March 2007

### ii March 2007 

### TABLE OF CONTENTS

LIST OF FIGURES ................................................................................................................ ....... iv LIST OF TABLES................................................................................................................. ........ iv ACRONYMS....................................................................................................................... ............v EXECUTIVE SUMMARY ........................................................................................................... vi

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

2.0 IDENTIFICATION OF BART-ELI GIBLE UNITS AT ALCOA................................... 2-1

3.0 BART–ELIGIBLE EMISSION UNIT GROUP DESCRIPTION................................... 3-1 3.1 Primary Aluminum Reducti on Process Description............................................ 3-1 3.1.1 Existing Potline Emissions Control ......................................................... 3-4 3.1.2 Anode Bake Furnace Emissions Control ................................................. 3-5 3.2 Secondary Aluminum Reduction Process Description........................................ 3-7

4.0 BASELINE CONDITIONS AND VISIBI LITY IMPACTS FOR BART-ELIGIBLE UNITS.......................................................................................................................... .... 4-1 4.1 Refined Modeling Analysis .................................................................................4-1

5.0 BART ANALYSIS FOR BART-ELIGIBLE EMISSION UNITS.................................. 5-1 5.1 Available and Technically Feasible Emission Control Options .......................... 5-1 5.1.1 Potline Emissions and Existing Controls................................................. 5-1 5.1.2 Anode Bake Emissions and Existing Controls ........................................ 5-2 5.1.3 Potentially Applicable BART Control Options for SO 2 

### .......................... 5-2 5.1.4 Potentially Applicable BART Control Options for PM......................... 5-12 5.1.5 Potentially Applicable BA RT Control Options for NO X 

### ....................... 5-13 5.1.6 Summary of Technically Feasib le BART Control Options................... 5-15 5.2 Control Effectiveness for Feasible Options ....................................................... 5-16 5.2.1 SO 2 

### Wet Scrubbing................................................................................ 5-16 5.2.2 SO 2 

### Pollution Prevention ....................................................................... 5-19 5.2.3 Anode Bake Advanced Firing System................................................... 5-19 5.2.4 Evaluation of Cost and Other Impacts................................................... 5-19 5.2.5 Energy Impacts ...................................................................................... 5-23 5.2.6 Non-air Quality Environmental Impacts................................................ 5-23 5.2.7 Remaining Useful Life........................................................................... 5-24 5.3 Evaluate Visibility Impacts................................................................................ 5-24

6.0 DETERMINATION OF BART....................................................................................... 6-1 6.1 Aluminum Potlines ..............................................................................................6-1 6.2 Anode Bake Furnace............................................................................................ 6-1 6.3 Aluminum Reclamation Crusher, Delacquering Furnace 1, and Aluminum Reclamation Melting Furnaces 1 and 2 ............................................................... 6-2 6.4 Material Handling and Transfer Operations ........................................................ 6-2

7.0 REFERENCES ................................................................................................................ 7 -1

### iii March 2007 

### Appendix A: ALCOA BART MODELING PROTOCOL Appendix B: ALCOA BART MODELING REPORT Appendix C: WET SCRUBBER ECO NOMIC AND ENERGY IMPACT Appendix D: BUSINESS C ONFIDENTIAL INFORMATION

### iv March 2007 

### LIST OF FIGURES

1 Diagram of Potline 1 Primary Control System and Control Devices .............................. 3-6 2 Diagram of Potline 2 Primary Control System and Control Devices .............................. 3-6 3 Diagram of Anode Bake Furnace Control Device........................................................... 3-7 4 Wet Scrubber ................................................................................................................. .. 5-4

LIST OF TABLES

1 Primary Aluminum Reduction Emission Units , Alcoa Inc. – Tennessee Operations ..... 3-1 2 Baseline Conditions Modeling Input Data....................................................................... 4-2 3 Baseline Visibility Modeling Results .............................................................................. 4-4 4 RBLC Database Search Results fo r Primary Aluminum Facilities ............................... 5-10 5 SO 2 

### Post-Control Emission Rates.................................................................................. 5-18 6 Summary of the Impacts Analysis for SO 2 

### Control Scenarios ...................................... 5-22 7 SO 2 

### Post-Control Modeling Source Input Data............................................................. 5-25 8 SO 2 

### Controls — Visibility Modeling Results................................................................ 5-26

### v March 2007 

### ACRONYMS

acfm actual cubic feet per minute Alcoa Alcoa, Inc. – Tennessee Operations AWMA Air and Waste Management Association BACT Best Availabl e Control Technology BART Best Available Retrofit Technology CAA Clean Air Act dv deciview EPA U.S. Environmental Protection Agency ESP Electrostatic Precipitator FGD Flue Gas Desulfurization GSMNP Great Smoky Mountains National Park LAER Lowest Achievable Emissions Rate LSFO Limestone Slurry Forced Oxidation LSNO Limestone Slurry Natural Oxidation NO X 

### Nitrogen Oxides PM Particulate Matter PM 2.5 

### Particulate Matter less than 2.5 micrometers in diameter PM 10 

### Particulate Matter less than 10 micrometers in diameter ppm parts per million ppmv parts per million by volume RACT Reasonably Availa ble Control Technology RBLC RACT/BACT/LAER Clearinghouse SCR Selective Catalytic Reduction SNCR Selective Non-Catalytic Reduction SO 2 

### Sulfur Dioxide TDAPC Tennessee Division of Air Pollution Control UBC Used Beverage Can

### vi March 2007 

### EXECUTIVE SUMMARY

The Clean Air Act (CAA) requires the protecti on of visibility in 156 scenic areas across the United States. Under CAA Section 169A(b)(2)(A ), states must require certain existing stationary sources to install Best Availabl e Retrofit Technology (BART). Alcoa, Inc. – Tennessee Operations (Alcoa) is a “BART-eligib le” source. A BART determination is required because Alcoa emits air pollutants that may r easonably be anticipated to contribute to impairment of visibility in a Class I area.

The BART analysis contained herein review s the impact of the individual BART-eligible
emission units, identifies those units for whic h emission reductions would possibly improve visibility in impacted Class I areas, analyzes pollution preventi on and add-on control options for
these emission units, and evaluate s control option feasib ility and cost effectiveness. The BART evaluation was completed according to guidance pr ovided in 40 Code of Federal Regulations 51, Appendix Y.

A baseline Class I area visibility impact an alysis was performed on seven BART-eligible emission units using the Visibility Improvement - State and Tribal Association of the Southeast recommended CALPUF modeling protocol. These sources include potlines 1 and 2, the anode
bake furnace, an aluminum reclamation cr usher, delacquering furnace 1, and aluminum reclamation melting furnaces 1 and 2.

The modeled or projected 98 th 

### percentile visibility impact from each of the two potlines is approximately 0.53 deciviews (dv) in the Grea t Smoky Mountains Nationa l Park (GSMNP). The projected impact in other, more distant, Class I areas is lower. More th an 90% of the projected impact from the potlines is attributable to emi ssions from the potroom primary control devices, with the remainder from the potroom roofs. Mo re than 95% of the potroom primary control device impact is from emissions of sulfur dioxide (SO 2 

### ). The analysis of control options for potroom emissions determined that BART for potline SO 2 

### emissions is a pollution prevention limit of 3% sulfur in the calcined petroleum coke used to manufacture anodes (i.e., coke). This will limit potline SO 2 

### emissions below current potential emissions. BART for other pollutants

### vii March 2007 

### emitted from the potlines [particulate matter (PM) and nitrogen oxides (NO X 

### )] was determined to be the existing level of emission control.

The modeled or projected 98 th 

### percentile visibility impact from the anode bake furnace is approximately 0.23 dv in GSMNP, w ith lower projected impacts in other Class I areas. More than 92% of the anode bake furnace impact is from SO 2 

### emissions. The analysis of control options for the anode bake furnace determined that BART for bake furnace SO 2 

### emissions is a pollution prevention limit of 3% sulfur in th e coke. This will limit bake furnace SO 2 

### emissions below current potential emissions. BART for ot her pollutants emitted from the anode bake furnace (PM and NO X 

### ) was determined to be the exis ting level of emission control.

Projected impacts from the aluminum recl amation crusher, delacquering furnace 1, and aluminum reclamation melting furnaces 1 and 2 ranged from 0.000 to 0.005 dv in GSMNP. Considering the minimal contribution to visibili ty impairment (<0.005 dv) and the existing level
of emissions control, these emission sources we re excluded from furthe r engineering analysis

and BART was determined to be no further emissions control.

Additional BART-eligible emission units at the Alcoa facility include 21 material handling and transfer operations that support the primary alumin um ore reduction process. These emission units are relatively small particulate em ission sources that are co ntrolled with fabric

filters. Given the level of emissions and that fabric filters represent the best available control for these operations, these emission sources were excl uded from both visibility modeling and further engineering analysis. BART for these sources was determined to be the existing level of

emissions control.

### 1-1 March 2007 

### 1.0 INTRODUCTION

The Clean Air Act (CAA) requires the protecti on of visibility in 156 scenic areas across the United States. Under CAA Section 169A(b)(2)(A ), states must require certain existing stationary sources to install Best Available Retrofit Technology (BART). A “BART-eligible”

source is 1 of 26 identified source cate gories that has the potential to emit ≥ 250 tons/year of any air pollutant and was put in place during the 15-year inte rval between August 7, 1962, and August 7, 1977. BART is required when any s ource meeting this definition emits any air pollutant that may reasonably be anticipated to cause or cont ribute to any impairment of visibility in any Class I area.

### 2-1 March 2007 

### 2.0 IDENTIFICATION OF BART-E LIGIBLE UNITS AT ALCOA

Alcoa, Inc. – Tennessee Operations (Alcoa) op erates emission units that fall within the categories of primary aluminum ore reduction pl ants and secondary metal production facilities – 2 of the 26 identified source categories to whic h BART is applicable. The primary aluminum reduction emission unit groups at Alcoa were constructed in 1969 and 1972. The secondary aluminum reduction emission unit group at Alcoa wa s constructed in 1975. Based on these dates, the emission units in these gr oups were in existence on August 7, 1977, but were not in operation before August 7, 1962. The primary aluminum reduc tion emission unit group has the potential to

emit ≥ 250 tons/year of sulfur dioxide (SO 2 

### )

, 

### a visibility impairing pollu tant. As such, the Alcoa facility is defined as a BART-eligible source . Emission units within the primary aluminum reduction group and the emission units within th e secondary aluminum production group that were in existence between August 7, 1962 and A ugust 7, 1977, are the emission units at Alcoa that are BART-eligible.

### 3-1 March 2007 

### 3.0 BART–ELIGIBLE EMISSION UNIT GROUP DESCRIPTION

3.1 Primary Aluminum Reduction Process Description

Alcoa’s primary aluminum reduction operations include two potlines and an electrode manufacturing operation made up of a paste production and green anode baking operation.

The potline operation manufactures metallic al uminum by the electrolytic reduction of alumina in center-worked prebake cells. Direct electrical current, passing between anodes and the cathode, electrolytically re duces the alumina to aluminum and oxygen. Molten aluminum is deposited and accumulates over time at the catho de beneath a layer of molten cryolite bath. Periodically the molten aluminum is siphoned from beneath the cryolite bath and processed to achieve specific metal propertie s or is retained as pure aluminum. The product aluminum is solidified into intermediate or final products.

Anodes are manufactured in an ancillary on-site paste producti on plant. Calcined petroleum coke used to manufact ure anodes (i.e., coke) is crushe d and sized, reusable anode butt
material is crushed and sized, and both are mixe d together with pitch and formed into selfsupporting carbonaceous blocks called “green an odes.” The green anodes are then cured and baked in furnaces before being used in the aluminum reduction process.

Table 1 presents the individual emission units that are included in the primary aluminum reduction emission unit group and that were identified as BART-eligible emission units.

Table 1. Primary Aluminum Reduc tion Emission Units, Alcoa Inc. – Tennessee Operations

Emission Unit ID Emission Unit Description Visibility Impairing Pollutants Existing Pollution Controls 05-0008-81 Potline 1 Electrolytic reduction operations that convert alumina and other raw materials to molten aluminum in the potline. PM, SO 2 Reactor / Fabric Filter

05-0008-85 Potline 2 Electrolytic reduction operations that convert alumina and other raw materials to molten aluminum in the potline. PM, SO 2 Reactor / Fabric Filter

05-0008-18 Anode Baking Furnace This emission unit includes the 261N, 262N, and 262S anode baking furnaces, which are controlled by the A-446. PM, SO 2 , NO X Reactor / Fabric Filter

### 3-2 March 2007 

### Table 1. (Continued)

Emission Unit ID Emission Unit Description Visibility Impairing Pollutants Existing Pollution Controls 05-0008-02 Coke Unloading and Storage This emission unit includes operations that unload virgin coke from railcars and store it for feed to the Electrode Plant "A” operations. Emissions are controlled by dust collector 8. PM Fabric Filter

05-0008-03 Electrode Plant A This emission unit includes all operations controlled by baghouse 12, which include the screening and blending of virgin coke and ground anode butts and green scrap before feeding to the carbon paste mixers. PM Fabric Filter

05-0008-12 Stub Dipping This emission unit covers the operation where anode rods are dipped into a coating to ensure separation of cast iron. Volatile Organic Compounds

05-0008-14 Butts Blasting Butts blasting uses a blasting media to remove residual bath from the spent anodes following butts cleaning. Emissions are controlled via a dust collector. PM Fabric Filter

05-0008-16 Induction Furnaces This emission unit covers the process of melting cast iron and pouring it into the anodes to bond the rods to the anode blocks. Emissions are controlled via baghouse. PM, SO 2 Fabric Filter

05-0008-19 Ball Mill This emission unit receives carbon that is to be pulverized by the Electrode Plant "A” operations, crushes these, and returns the carbon fines. Emissions are controlled by dust collector 10. PM Fabric Filter

05-0008-20 Pitch Tanks Coal Tar Pitch Storage Tanks 217A, B, and C. Volatile Organic Compounds 05-0008-26 Stripping Presses This emission unit includes two stripping presses that remove the carbon and cast iron from the anode assemblies following the butts blasting operation. PM Fabric Filter

05-0008-30 Butts Intermediate Classifying System This emission unit is currently idled. When operable, it serves as a classifying system for intermediate-sized recycled carbon. Emissions are controlled via dust collector 9. PM Fabric Filter

05-0008-31 Ore Unloading, Trans. and Storage This emission unit covers unloading of raw materials, bulk storage of those materials, and transfer to the potline 1 and 2 material handling systems (process weight rate is 300 tons/hour). This emission unit includes soda storage tank 141L, conveyor B-4, conveyor B-4A, tower 3A, conveyor B-2, fresh ore tank 142N, fresh ore tank 142S, fresh ore tank 143N, fresh ore tank 143S, feed tank 141A, fluoride storage tank 141F, feed tank 141K, feed tower 2, rail unloading, and conveyor B-5 discharge/B-6. All emission points are controlled with dust collection except fluoride storage tank 141F and soda storage tank 141F, which are uncontrolled and identified as insignificant emission units. PM Fabric Filter

### 3-3 March 2007 

### Table 1. (Continued)

Emission Unit ID Emission Unit Description Visibility Impairing Pollutants Existing Pollution Controls 05-0008-33 Bath Crushing/ Crucible Digging This emission unit covers the operations receiving bath from butts cleaning and crucible digging, and includes bath crushing, storage, and mixing with alumina for return to the potlines, transfer, or sales. This emission unit includes a bucket fill station. PM Fabric Filter

05-0008-51 Carbon Reclamation This emission unit is baghouse controlled. The process weight rate 150,000 lb/hour. PM Fabric Filter

05-0008-54 Packing Material Handling This emission unit includes railcar unloading of virgin packing material and storage and transfer of clean and recycled packing material for use in the anode baking furnaces and is baghouse controlled. PM Fabric Filter

05-0008-62 Butts Cleaning Butts cleaning removes bath from the spent anodes and is the first step in the carbon reclamation process. This emission unit is baghouse controlled. PM Fabric Filter

05-0008-98 Initial Carbon Paste Mixing Operations and Green Mill Anode Forming This emission unit receives virgin and recycled carbon and mixe s these with pitch to form a paste. The paste is compacted into the shape of new green anodes. PM, Volatile Organic Compounds Reactor / Fabric Filter

05-0008-10 Potline I Material Handling (North Courtyard) Alumina feed tanks 142NE and 142NW, airlifts 142NE and 142 NW, and dust collectors. PM Fabric Filter

05-0008-39 Potline I Material Handling Alumina feed tanks 142SE and 142SW, airlifts 142SE and 142 SW, and dust collectors. PM Fabric Filter

05-0008-43 Potline I Material Handling Alumina feed fill station, air slide 101S, air slide 102S, air slide 101N, air slide 102N, north discharge air slide, and south discharge air slide. PM Fabric Filter

05-0008-44 Potline II Material Handling Conveying and storage of raw materials for potline 2. The emission unit includes air lift 146N, air lift 146S, air slide 103N, air slide 103S, air slide 104N, air slide 104S, ore tank 146N, and ore tank 146S. PM Fabric Filter

05-0008-47 143N-TP002 LII North Conveying of raw materials for potline 2. PM Fabric F ilter

05-0008-86 143S-TP002 LII South Conveying of raw materials for potline 2. PM Fabric F ilter

### 3-4 March 2007 

### Potlines 1 and 2 emit SO 2 

### and particulate matter (PM), and the anode bake furnace emits

lesser amounts of SO 2 

### , nitrogen oxides (NO X 

### ), and PM. These three emission units are already equipped with sophisticated emission control e quipment for PM, so the BART determination for these emission units focuses primarily on potential reductions for SO 2 

### and NO X


### .

The remaining 21 emission units identified in Table 1 are material handling and transfer operations that support the potlines and the anode bake furnace. Two of these support operations are negligible sources of vol atile organic compounds. Emissions from 19 of these support operations consist of relatively small amounts of PM that are controlled by fabric filter type control devices. Fabric filters effectively remove >99% of particulate emissions and, based on a control technology review, represent the best av ailable control for thes e types of material handling and transfer operations. Given the level of emissions and that fabric filters represent the
best available control, these emission sources were excluded from both visibility modeling and further BART engineering anal ysis. Based on visibility modeling results for the aluminum reclamation melting furnaces, which have a compar able PM emission rate, visibility impacts

from individual fabric f ilters are projected to be ≤ 0.01 deciviews (dv). BART for these support operations was determined to be the existing leve l of control.

3.1.1 Existing Potline Emissions Control

The potlines at Alcoa consist of four potroom groups [i.e., “...a group of potroom segments ducted to a common control system” (40 Code of Federal Regulations 60.191)] of electrolytic reduction cells connected in series that produce molten aluminum. Each potline is comprised of 164 Alcoa technology reduction cells with 32 anodes per cell. Emissions from each potline group are captured and controlled with a primary control system. In both potlines, the primary control system is comprised of two control devices. Any uncaptured fume is emitted as fugitive secondary emissions through the r oof monitor atop the potroom buildings.

The primary control system employed at the Alcoa potlines is a fluid-bed reactor type system with fabric filtration downstream of the reactor beds. Smelting grade alumina is introduced into one end of the Alcoa designed A- 398 reactor. The alumina is fluidized by potline fume exhausted into the reactor through a series of perforated plates . Gaseous fluoride and a

### 3-5 March 2007 

### limited amount of SO 2 

### are adsorbed onto the alumina surface. Fabric filtration devices are positioned atop the reactor compartments to coll ect entrained alumina particles and other PM present in the gas stream. Total fluoride and part iculate removal efficiencies >99% are achieved by the control system.

Each potline primary control system at Alcoa consists of two dry alumina scrubber control devices as illustrated in Figures 1 and 2. Each control device has ei ght reactor sections, or compartments, and one or two stacks per compartment.

3.1.2 Anode Bake Furnace Emissions Control

As defined in the U.S. Environmental Protection Agency (EPA) National Emission

Standards for Hazardous Air Pollutants for Prim ary Aluminum Reduction Plants, Alcoa operates

one anode bake furnace. The anode bake furnac e is comprised of three in-ground, ring baking furnaces controlled by a common Alcoa design ed A-446 emission control device. The baking

furnace structure is a series of interconnected refractory flues c onnected to side main exhaust

manifolds. Products of combustion and other emi ssions created in the baking furnaces are drawn into the refractory flues and exhausted to the emission control equipment through a series of ducts. The furnaces are fueled with natural gas.

Emissions from the anode bake furnace are co llected and treated by an integrated system of ducting and pollutant control equipment. The control system employed at the Alcoa anode bake furnace is a multi-unit, fluid-bed reactor type system with fabric filtration downstream of the reactor beds. Smelting grade alumina is intr oduced into one end of the Alcoa designed A-446

reactors. The alumina is fluidi zed by an auxiliary fluidizing fa n blowing ambient air through a series of perforated plates in the bottom of th e reactor chamber. Anode bake furnace emissions are introduced into the fluidized bed through ex haust gas manifolds along each side of the reactor. A carefully metered amount of water is sprayed into the fluidized bed to control temperature. The fluid bed provi des a site for fluoride and SO 2 

### to react with the alumina and for the gas stream to be cooled. The fabric filtra tion devices are positioned atop the fluid beds to collect entrained alumina particles and other PM present in the gas stream.

### 3-6 March 2007 

### Figure 1. Diagram of Potline 1 Primary Control System and Control Devices

Figure 2. Diagram of Potline 2 Primary Control System and Control Devices

### 3-7 March 2007 

### The anode bake furnace primary control syst em consists of a single dry alumina scrubber control device with six reactor sections or comp artments. Each compartmen t on the anode furnace control device has one stack as illustrated in Figure 3.

Figure 3. Diagram of Anode Bake Furnace Control Device

3.2 Secondary Aluminum Reducti on Process Description

The secondary aluminum reduction operations include 10 distinct emission units. In cold metal crushing and conveying, used beverage cans (UBCs) are crushed and then conveyed to delacquering furnace 1 and delacquering furnace 2 for delacquering. The delacquered UBCs are then supplied to the melting furnaces (1, 2, and 3) where they are melted into molten aluminum.

Class I briquettes are charged into furn ace 4 where they are converted into molten aluminum. In skim cooling, impurities are sk immed from the top of the molten metal and transferred to a cooling area for subsequent recycling. The tilting rotary furnace remelts aluminum scrap and dross. Crucible heating hot tops are natural gas burn ers used for drying and

### 3-8 March 2007 

### preheating molten metal crucibles. Miscellaneou s burners are used for drying and preheating auxiliary equipment.

Of the emission units described above, th e crusher, delacquering furnace 1, melting furnace 1, and melting furnace 2 are the only emi ssion units that were in operation between August 7, 1962, and August 7, 1977, and are, therefore, BART-eligible emission units.

### 4-1 March 2007 

### 4.0 BASELINE CONDITIONS AND VISIBILI TY IMPACTS FOR BART-ELIGIBLE UNITS

Before beginning the five step case-b y-case BART analysis, CALPUFF modeling of

individual emission units was performed to evalua te the overall vi sibility impacts of BART-eligible

emission units and their individual relative contribution to the total visibility impact for baseline conditions. A modeling prot ocol was develope d by TRC Environmental Co rporation and submitted

to the Tennessee Division of Air Pollution C ontrol (TDAPC). This protocol is included as Appendix A to this report. All modeling performed in association with this BART determination was done by TRC Environmental Corporation.

Table 2 presents the baseline modeling source input data that were used in the CALPUFF model to forecast the visibility impacts. Per Section IV of 40 CFR 51 Appendix Y, baseline

emission rates used in the model were based on 24-hour average actual emissions from the highest emitting day. Screening runs were performed for 2001–2003 using the Visibility Improvement - State and Tribal Association of the Southeast 4-km reso lution CALMET Domain 3. Six Class I areas [Great Smoky Mountains Na tional Park (GSMNP), Cohutta Wilderness, Joyce Kilmer-Slickrock Wilderness, Linville Go rge Wilderness, Shining Rock Wilderness, and Mammoth Cave National Park] are located within the 300-km radius around the facility. The results of the screening run show that visibility impacts within Mammoth Cave National Park were <0.5 dv. The screening run revealed that Alco a emissions were not cont ributing to visibility impairment at Mammoth Cave, while impacts at the other Class I areas exceeded the 0.5 dv threshold. The remaining five Class 1 areas were included in a refined, 1-km resolution modeling analysis.

4.1 Refined Modeling Analysis

The CALPUFF modeling system was used for th e BART analysis for five Class I areas in

the 300-km radius of Alcoa. CALPUFF and its meteorological model CALMET are designed to handle the complexities posed by complex terr ain, long source receptor distances, chemical transformation and deposition, and other issues related to Cla ss I impacts. EPA adopted the CALPUFF modeling system as a guideline model for source-receptor dist ances >50 km and for4-2March 2007Table 2. Baseline Conditions Modeling Input DataIndexEmission Unit IDStack NameReleaseHeight (m)MonitorWidth (m)RoofMonitorArea (m2)Exit Velocity(m/s)Flowrate(m3/sec)Flowrate (stdm3/sec)Delta T(°K)BeginningUTM E/N(km)EndingUTM E/N(km)PM10-PM2.5(g/s)Solid PM2.5(g/s)Org.Condensables(g/s)SO2(g/s)NOX(g/s)L01TNPOT0045b_1 Potline 1,Room 118.57 3.05 1,194 1.34 1,599 1,448 22.5 231.5522,3963.2083231.5770,3962.76180.825 1.163 1.110 0.457 0.002L02TNPOT0045b_2 Potline 1,Room 218.57 3.05 1,194 1.34 1,599 1,448 22.5 231.5006,3963.2057231.5257,3962.75940.825 1.163 1.110 0.457 0.002L03TNPOTL2RM_3 Potline 2,Room 318.57 3.05 1,193 1.34 1,598 1,448 22.5 231.4504,3963.2030231.4755,3962.75640.722 1.018 0.972 0.457 0.001L04TNPOTL2RM_4 Potline 2,Room 418.57 3.05 1,193 1.34 1,598 1,448 22.5 231.3988,3963.2006231.4239,3962.75340.722 1.018 0.972 0.457 0.001IndexEmission Unit IDStack NameStack Height(m)StackDiameter(m)Stack Area(m2)Exit Velocity(m/s)Flowrate(m3/sec)Flowrate (stdm3/sec)ExitTemperature(°K)UTMEasting (km)UTMNorthing(km)PM10-PM2.5(g/s)Solid PM2.5(g/s)Org.Condensables(g/s)SO2(g/s)NOX(g/s)P01TNPOTL0045a_N A-398 Line 1North15.96 3.82 11.5 20.40 234 179 382.8 231.536 3963.050 0.024 0.013 0.200 30.0 0.163P02TNPOTL0045a_S A-398 Line 1South15.96 3.82 11.5 20.40 234 179 382.8 231.539 3962.923 0.024 0.013 0.200 30.0 0.163P03TNPOTL0048_N A-398 Line 2North22.60 4.88 18.7 10.32 193 150 377.5 231.433 3963.049 0.090 0.048 0.745 30.0 0.087P04TNPOTL0048_S A-398 Line 2South22.60 4.88 18.7 10.46 196 154 373.5 231.441 3962.916 0.090 0.048 0.745 30.0 0.087P05TNANOD0008_1 Bake Stack 1 22.15 1.22 1.17 11.46 13.4 11.3 347.0 231.421 3962.655 0.008 0.005 0.047 3.11 0.399P06TNANOD0008_2 Bake Stack 2 22.15 1.22 1.17 11.4613.4 11.3 347.0 231.421 3962.647 0.008 0.005 0.047 3.110.399P07TNANOD0008_3 Bake Stack 3 22.15 1.22 1.17 11.4613.4 11.3 347.0 231.422 3962.639 0.008 0.005 0.047 3.110.399P08TNANOD0008_4 Bake Stack 4 22.15 1.22 1.17 11.4613.4 11.3 347.0 231.422 3962.661 0.008 0.005 0.047 3.110.399P09TNANOD0008_5 Bake Stack 5 22.15 1.22 1.17 11.4613.4 11.3 347.0 231.423 3962.623 0.008 0.005 0.047 3.110.399P10TNANOD0008_6 Bake Stack 6 22.15 1.22 1.17 11.4613.4 11.3 347.0 231.423 3962.615 0.008 0.005 0.047 3.110.399P11TNCRSH0208 AluminumReclamationCrusher18.29 1.22 1.17 12.62 14.8 14.6 295.4231.300 3963.700 0.097 0.000 0.000 0.000 0.000P12TNDFRN0201 AluminumReclamationDelacqueringFurnace 122.86 1.45 1.65 16.10 26.6 6.7 1155.4231.315 3963.657 0.045 0.027 0.001 0.087 1.358P13TNMFRN0203 AluminumReclamationMeltingFurnace 120.73 1.92 2.90 10.46 30.3 16.9 524.3231.316 3963.617 0.128 0.076 0.002 0.003 0.214P14TNMFRN0204 AluminumReclamationMeltingFurnace 220.73 1.83 2.63 18.11 47.6 19.6 711.5231.282 3963.615 0.137 0.081 0.002 0.004 0.228

### 4-3 March 2007 

### use on a case-by-case basis in complex flow situa tions for shorter distan ces (Federal Register, April 15, 2003). CALPUFF was recommended for Cl ass I impact assessments by the Federal Land Managers Workgroup in 2000 and the Intera gency Workgroup on Air Quality Modeling in 1998. CALPUFF is recommended by EPA for BART analyses (Federal Register, July 6, 2005).

Calculation of the impact on light ex tinction is carried out in the CALPOST postprocessor. The procedure is consistent with the VISTAS modeling prot ocol (2005). In this analysis, the new IMPROVE equation is applied to determine the change in light extinction due to changes in component concentrations. CALPOS T Method 8 is used to compute the extinction change in deciviews. This method is an implementation of the new IMPROVE algorithm. It provides a better correspondence between the me asured visibility and that calculated from pollutant concentrations simulated by a model.

Refined modeling forecasts were prepared for visibility impact s at the Class I areas where

the combined emissions fro m the BART-eligible emission units we re forecast to be equal to or greater than the screening threshold limit of 0.5 dv. The complete Alcoa BA RT modeling report is contained in Appendi x B. The refined, 1-km mo deling predicted visib ility impacts from Alcoa emission units to be at a level equal to or greate r than the threshold limit of 0.5 dv at GSMNP and Joyce Kilmer-Slickrock Wilderness Ar ea. Table 3 presents the modeled 98 th 

### percentile total source visibility impact reported as deci views for 2001, 2002, an d 2003 at the Joyce- Kilmer/Slickrock and

GSMNP Class I areas. Because th e forecasted visibility impact in GSMNP was the higher of the
two Class I areas, individual em ission unit visibilit y impacts at GSMNP were evaluated to determine which units were forecasted to have the most impact. The modeled or projected 98 th


### percentile visibility impact from each of the two potlines is approximately 0.53 dv in GSMNP. More than 90% of the projected impact from the potlines is attributable to emissions from the potroom primary control devices, with the remai nder from the potroom roofs. More than 95% of the potroom primary control device impact is from emissions of SO 2 

### . The modeled or projected

98 th 

### percentile visibility impact from the anode bake furnace is approximately 0.23 dv in GSMNP. More than 92% of the anode bake furnace impact is from SO 2 

### emissions. Projected impacts from the aluminum reclamation crus her, delacquering furnace 1, and aluminum reclamation melting furnaces 1 and 2 ranged from 0.000 to 0.005 dv in GSMNP.4-4March 2007Table 3. Baseline Visibility Modeling ResultsPercentage of Species ContributionYearSource GroupModeled98thPercentile(deciview)Calculated98thPercentile(deciview)SO4NO3PM_FinePM_CoarseOrganicsGreat Smoky Mountains National Park2001 Total of Sources1.09291.77 0.15 1.23 0.42 6.402001 A398 P01-P020.44096.77 0.00 0.05 0.05 3.092001 A398 P03-P040.44096.77 0.00 0.05 0.05 3.092001 Bake P05-P100.14496.22 0.58 0.00 0.00 2.912001 Potrooms L01-L020.03114.09 0.00 18.79 5.37 61.742001 Potrooms L03-L040.03114.09 0.00 18.79 5.37 61.742001 Crusher P110.0000.00 0.00 0.00 0.00 0.002001 Reclamation Delacquering P120.00166.67 33.33 0.00 0.00 0.002001 Melting Furnace0.0010.00 0.00 66.67 33.30 0.002002 Total of Sources0.96688.89 0.17 1.35 0.61 8.892002 A398 P01-P020.38894.14 0.00 0.11 0.11 5.592002 A398 P03-P040.38894.14 0.00 0.11 0.11 5.592002 Bake P05-P100.13093.55 0.65 0.32 0.00 5.162002 Potrooms L01-L020.0277.69 0.00 20.00 7.69 64.622002 Potrooms L03-L040.0277.69 0.00 20.00 7.69 64.622002 Crusher P110.0000.00 0.00 0.00 100.00 0.002002 Reclamation Delacquering P120.00225.00 25.00 0.00 0.00 0.002002 Melting Furnace0.0020.00 0.00 40.00 40.00 0.002003 Total of Sources1.30986.69 0.69 1.62 0.81 9.882003 A398 P01-P020.48893.53 0.08 0.13 0.13 6.102003 A398 P03-P040.48893.53 0.08 0.13 0.13 6.102003 Bake P05-P100.23192.04 2.30 0.18 0.18 4.602003 Potrooms L01-L020.0456.36 0.00 20.00 8.18 65.452003 Potrooms L03-L040.0456.36 0.00 20.00 8.18 65.452003 Crusher P110.0000.00 0.00 0.00 100.00 0.002003 Reclamation Delacquering P120.00516.67 50.00 8.33 8.33 0.002003 Melting Furnace0.0040.00 20.00 40.00 30.00 0.004-5March 2007Table 3. (Continued)YearSource GroupModeled98thPercentiledeciviewJoyce-Kilmer/Slickrock2001 Total of Sources0.4742002 Total of Sources0.5492003 Total of Sources0.686

### 4-6 March 2007 

### The refined modeling results in Table 3 show visibility impacts <0.05 dv for the potroom

roofs and < 0.005 dv for the aluminum reclamation cr usher, delacquering furnace 1, and aluminum reclamation melting furnaces 1 and 2. The impact from each of these emission units is

< 10% of the facility-wide exemption level for BA RT applicability established by the State of

Tennessee. Reduction in emissions from these sour ces would not result in significant visibility improvement at GSMNP or Joyce-Kilmer/Slickroc k. The scope and cost analysis for the Alcoa

BART determination was focused on the em ission units predicted to contribute ≥ 0.05 dv to GSMNP visibility impairment.

The potroom A-398 reactors and the anode bake furnace show modeled 98 th 

### percentile visibility impacts of approximately 1.0 and 0.23 dv, respectively. Given these potential impacts,

a detailed retrofit control asse ssment was performed for the A-398 reactor portion of potlines 1

and 2 and the anode bake furnace.

### 5-1 March 2007 

### 5.0 BART ANALYSIS FOR BART- ELIGIBLE EMISSION UNITS

The results of the refined CALPUF modeling show that Alcoa’s potline reactors and anode bake furnace contribute to visibility impair ment in two Class 1 areas. The BART analysis completed for these emissions sources is described in this section. The analysis included review of available and technically f easible BART technologies (Steps 1 and 2), determination of

control effectiveness for feasible options (Step 3), evaluation of cost and secondary impacts for feasible alternatives (Step 4), and analysis of visibility imp act and improvements (Step 5).

5.1 Available and Technically Feasible Emission Control Options

Control options for the potline reactors and anode bake furnace are described separately in the following sections.

5.1.1 Potline Emissions and Existing Controls

Aluminum is manufactured in large electrolytic reduction cel ls called pots. Aluminum is produced from alumina in the pot as current is passed from a carbon anode to carbon blocks on the pot wall, which serve as the cathode. The anodes are made from pitch and coke. The major pollutants emitted from the cells are PM, hydrogen fluoride, SO 2 

### , and carbon monoxide. PM includes particulate fluoride, carbon dust, and alumina. SO 2 

### comes from the sulfur in the components used to make the anodes. NO X 

### emissions are minimal since there is no external fuel or combustion zone and there are no large so urces of nitrogen in the raw materials.

Emissions from the pots are collected by close capture hoods over each pot. The hoods enclose the pot as tightly as possi ble to collect off-gases, but se ctions may be removed to allow anodes to be changed. The off-gases are collected into manifolds that combine the gases from the individual pots. The temperature of the exhaust ga ses entering the control equipment is typically 150–300°F [Air and Waste Management Association (AWMA) 2000]. The combined gases are routed to a dry alumina scrubber. The dry alumin a scrubber design used at Alcoa is a fluid bed reactor containing alumina. PM from the pots and alumina from the reactors are removed by

### 5-2 March 2007 

### fabric filters located above the reactors. The sy stem at Alcoa is large, treating approximately 2,000,000 actual cubic feet per minute (acfm) of 200°F exhaust gases.

5.1.2 Anode Bake Emissions and Existing Controls

The green anode bake furnace structure is a series of interconn ected refractory flues

connected to side main exhaust manifolds. The furnaces are fueled with natural gas. Exhaust gases are routed so that flue gases preheat the ne xt section to be fired. Flue gases from the bake furnace contain PM, hydrogen fluoride, SO 2 

### , carbon monoxide, and hydrocarbons.

The emissions are controlled by dry scrubbers that are similar to those used on the potlines. The major difference is that the water is sprayed into the reactors to cool the gases from 300–450°F to 150–180°F (AWMA 2000) so that they can condense tar vapors on the alumina. The fluid bed in the reactor prov ides a site for fluoride and SO 2 

### to react with the alumina and for the gas stream to be cooled. The fabric filtra tion devices are positioned atop the fluid beds to collect entrained alumina particle s and other PM present in the ga s stream. The system at Alcoa treats approximately 170,000 acf m of 165°F exhaust gases.

5.1.3 Potentially Applicable BA RT Control Options for SO 2



### Sulfur in the anodes is oxidized, releasing SO 2 

### from the potlines as the anodes are consumed. Options for controlling SO 2 

### include both add-on controls and pollution prevention.

5.1.3.1 Add-on Emission Controls

Absorption and adsorption have be en used for the control of SO 2 

### emissions from numerous power utility and indus trial processes. As a result many commercialized control technologies have been used for SO 2 

### control. However, the practical application of these controls systems to the potline reactors and anode ba ke furnace is limited by the very low inlet SO 2 

### levels, in the range of 100 parts per million by volume (ppmv), and the expected range of gas conditions, including temperature, oxygen content, humidity, SO 2 

### /O 2 

### ratio, and gas impurities.

### 5-3 March 2007 

### Eight different SO 2 

### control options were considered as having potential practical application as part of the BART analysis. Two of these technologies have been applied to the

control of SO 2 

### emissions at aluminum smelters. Six of the control options use wet scrubbing and two use dry scrubbing technology. The eight potentially appli cable control options are:

• 

### Seawater scrubbing

• 

### Limestone slurry scrubbing with natural oxidation

• 

### Limestone slurry scrubbing with forced oxidation

• 

### Conventional lime wet scrubbing

• 

### Dual alkali sodium/lime scrubbing (dilute mode)

• 

### Conventional sodium scrubbing

• 

### Dry injection

• 

### Semi-dry scrubbing

5.1.3.1.1 Wet Scrubbing

The primary development of SO 2 

### control technology occurred because of the need to

control emissions from the coal -fired, electric ut ility power industry (AWMA 2000). The large volumetric size of the potroom exhaust (2,000,000 acf m) would require a system similar to those used in the electric utility power industry.

The typical temperature range for wet sc rubbers is 300–700°F. For utility combustion units, wet scrubbing systems have been instal led on systems as large as 1,500 MW. Sodium compounds, lime, or limestone can be used. However, the high solubility of sodium complicates disposal of waste and wastewater . The typical sorbent material is lime or limestone. Lime is generally easier to manage on-site but is signi ficantly more costly. Wet limestone scrubbing has a high capital and operating cost due to the hand ling of liquid reagent a nd waste, but is the preferred process for coal-fired utility power plan ts burning coal due to th e low cost of limestone and high removal efficiencies. Typical removal efficiencies are 80–95%. Approximately 85% of the flue gas desulfurization (FGD) systems inst alled in the United States are wet scrubber systems (EPA 2003c).

### 5-4 March 2007 

### In wet scrubbers, the waste gas enters a large vessel (spray tower or absorber), where it is sprayed with water slurry. Figure 4 is a simplif ied process flow diagram of a conventional wet

scrubber.

Inlet Gas Particulate Control Clean gas out Spray tower/absorber

Fly Ash Lime (stone) and Water Reaction Tank Calcium-based sorbent spray

Thickener

Filter

Solids

Stabilized Waste Lime

Blending Pugmill Reagent Supply Liquid Waste Stream



### Figure 4. Wet Scrubber

The calcium in the slurry reacts with SO 2 

### to form CaSO 3 

### . A portion of the slurry from the reaction tank is pumped into the thickener, where the solids settle before going to a filter for final dewatering to about 50% solids. In the utility industry, the CaSO 3 

### waste product is usually mixed with fly ash (approximately 1:1) and fixative lime (approximately 5%) and typically disposed of in landfills. Alternately, the fo rced oxidation process oxidize s the spent slurry to gypsum. Gypsum crystals dewater more efficiently and reduce the size of waste handling equipment. Depending on quality and demand, the gypsum may be commercially sold, eliminating the need for landfilling the waste product.

### 5-5 March 2007 

### Note that “mist eliminators” installed at the spray tower outlet or downstream ductwork remove droplets from the gas. In some power plan t installations, the gas is reheated to avoid corrosion downstream. Many scrubbers have gas bypassing capability, which can be used for gas reheating. If the wet scrubber is downstream of a high-efficiency particulate removal device [fabric filter or electrostatic precipitator (ESP) ], the particulate concentration may be higher leaving the scrubber than entering due to the solids in mist dropl ets that are carri ed out of the

scrubber.

Some disadvantages of using wet scrubbi ng techniques in many a pplications are the requirement to treat wastewater, components must be constructed from expensive alloys to resist corrosion, and energy use is much higher. A prac tical issue associated with a wet scrubber system is the complexity of the system. The space required for a wet system is substantial (i.e., large footprint), the systems require more ma intenance due to their complexity, and more personnel are required for their operation.

5.1.3.1.1.1 Seawater Scrubbing

Globally, once-through seawat er scrubbing has been inst alled at seven aluminum
smelters, none of which are in the United States . Seawater, which has a natural alkalinity, is pumped directly into a scrubbing tower through a system of spray nozzles where the atomized droplets make contact with the gas. The liquid effluent is discharged back into the ocean. Seawater scrubbing was automatically rejected as feasible because of Alcoa’s physical location.

5.1.3.1.1.2 Limestone Slurry Forced Oxidation

Limestone slurry forced oxidation (LSFO) is used extensively in the utility FGD market. The raw material is finely ground limestone. There are a number of suppliers of LSFO technology. The most commonly used equipment is an open, multi-level, countercurrent spray tower scrubber equipped with spray nozzles to in ject the limestone slurry droplets into the gas stream. Liquor is collected at th e bottom of the tower and sparge d with air to oxidize the calcium

sulfite to calcium sulfate to e nhance the settling properties of th e calcium sulfate. Recirculation pumps circulate the scrubbing li quor to the spray nozzles. SO 2 

### removal efficiencies of 90% have

### 5-6 March 2007 

### been achievable. The bleed from the scrubber is sent to a dewatering system to remove excess moisture. For an aluminum smelter, the pro cess will produce either solid gypsum waste or commercial-grade gypsum suitable for reuse as a cement additive. Only a very small purge or blowdown stream is required.

LSFO was determined to be a technically feasib le retrofit control option for the potroom reactor and the anode baking exhausts even thoug h it is not ideally suit ed for wet scrubbing due

to low SO 2 

### concentrations (<100 ppm).

5.1.3.1.1.3 Limestone Slurry Natural Oxidation

Limestone slurry natural oxidation (LSNO) is very similar to LSFO. The major difference is the absence of an oxidation stage. The gypsum/calcium sulfite product is essentially a waste product with limited possibilitie s of use for agricultural purposes.

5.1.3.1.1.4 Conventional Lime Wet Scrubbing

Conventional lime wet scrubbing is also similar to LSFO except that the raw material is hydrated lime or quick lime that is either slaked on-site or purchased in the slaked form. The system typically uses forced oxidation, although na tural oxidation is possible. The process will produce either solid gypsum waste or commercia l-grade gypsum suitable for reuse as a cement

additive.

5.1.3.1.1.5 Dual Alkali Sodium/Lime Scrubbing (Dilute Mode)

Dual alkali sodium/lime scrubbing (dilute mode ) uses a caustic sodium solution in the scrubber tower. A portion of the scrubbing liquid is discharged to a neutralization stage where lime slurry is used to regenerate the caustic, wh ich is returned to the scrubber. The bleed from the scrubber is sent to a dewatering system to produce a gypsum byproduct. The process will produce either solid gypsum waste or commercia l-grade gypsum suitable for reuse as a cement
additive. It should be noted, however, that dual alkali sodium/lime scrubbing (dilute mode) is not marketed today by major FGD vendors because the system is too complicated and expensive.

### 5-7 March 2007 

### 5.1.3.1.1.6 Conventional Sodium Scrubbing

Globally, this technology has been installed in at least 12 aluminum smelters. An alkaline solution of either soda ash or sodium hydroxi de is pumped into th e scrubbing tower and recirculated through a network of spray nozzles . Atomized droplets cont act the up-flowing gas containing SO 2 

### . Where this technology has been de ployed, the liquid effluent containing dissolved salts, including sodium and fluorides, has been discha rged into a large receiving stream or an open body of water without treatment.

5.1.3.1.2 Dry Scrubbing

5.1.3.1.2.1 Dry Injection

In dry injection, a reactive alkaline powder is injected into a furn ace, ductwork, or a dry reactor. Typical removal efficiencies with cal cium adsorbents are 50–60% and up to 80% with
sodium base adsorbents. However, as with wet scrubbing, disposal of waste using sodium adsorbents must consider their high solubil ity in water compared to those from calcium adsorbents. The temperature range where dr y scrubbing has been used is 300–1,800°F; the minimum temperature is 300–350°F. Dry systems ar e rarely used and according to EPA only 3% of FGD systems installed in the United States are dry systems (EPA 2003c). The dry waste material is removed using part iculate control devices such a fabric filter or an ESP.

Dry scrubbing downstream of the potline reactors and anode bake furnace fabric filters is not technically feasible because of th e low temperatures (<300°F) and low SO 2 

### concentrations (<110 ppm).

5.1.3.1.2.2 Semi-dry Scrubbing (Spray Dryer)

Semi-dry scrubbing is more commonly refe rred to as spray drying. Calcium hydroxide slurry (lime mixed with water) is introduced into a spray dryer to wer. Sodium compounds can be used, but as with the dry scrubbe r, the high solubility of the s odium-based waste products in water complicates disposal of the waste. The slurry is atomized and injected into a reactor with

### 5-8 March 2007 

### the exhaust gases, where droplets react with SO 2 

### as the liquid evaporat es. This system is categorized as a semi-dry system because the end product of the SO 2 

### conversion reaction is a dry material. The dry waste product is collected in the bottom of the sp ray dryer reactor, and a fabric filter or ESP downstream of the spray dryer removes the CaSO 3 

### , CaSO 4 

### , and unreacted lime. This air pollution control system uses water for evaporative cooling and for the SO 2 

### reaction. It operates in a temperature range of 300–350°F because the temperature of the gases must be high enough to evaporate the water portion of the sl urry. Approximately 12% of the FGD systems installed in the United States are spra y dry systems (EPA 2003c) with typical SO 2 

### removal efficiencies in the range of 80–90%. Unlike a wet scrubbing system there is no liquid blow-down stream from the dry system, and the collected solids are typically landfilled.

Spray dry scrubbing downstream of the potline reactors and anode bake furnace fabric filters is not technically f easible because of the low temperatures (<300°F) and low SO 2 

### concentrations (<110 ppm).

5.1.3.2 Pollution Prevention

The guidelines for BART determinations under the Regional Haze Rule recommend consideration of pollution prev ention options in addition to add-on controls. The primary opportunity for pollution prevention in the smelting process to minimize SO 2 

### emissions is through limitations on the sulfur content in the in coming coke. Coke is a major raw material used in the manufacture of green anodes. Green anodes are subsequently baked in a furnace prior to their use in the smelting process. The SO 2 

### emissions from the potlines and anode bake furnace at Alcoa are currently limited to 2,000 parts per million (ppm) [based on TDAPC Rule 1200-3-14- .03(3)]. However, physical and operational li mitations provide a more meaningful SO 2 

### potential emission limit for the potlines and anode ba ke furnace. The practical limitation on SO 2 

### from these emission units is determined using the ma ximum production capacity of the potlines/anode bake furnace and a maximum process sulfur cont ent of 3.5% in the incoming coke (3.5% sulfur in the coke is a general upper limit for producing good quality anode s). Alcoa’s current specification for incoming coke sulfur content is 3%.

### 5-9 March 2007 

### During the BART process, Alcoa evaluated the current levels of sulfur in coke used by

other aluminum smelters to determine whether a pollution prevention option using lower sulfur content coke would be a feasible BART option. Th is analysis indicated that certain smelters currently utilize coke with sulfur contents as low as 2%. Given th at sulfur contents lower than the current Alcoa specification are utilized, Alcoa undertook a low sulfur coke availability analysis to determine whether coke at leve ls below 3% would be available beyond 2013 when BART controls requirements are anticipated. C onfidential research info rmation belonging to the market analysts assisting with the preparation with the coke availability analysis is included in Appendix D. The coke availability and market an alysis has been submitted separately pursuant to the procedures of the State of Tennessee. The pr imary conclusions from this analysis indicate

that:

• 

### Coke is a byproduct of the oil refining pro cess. The sulfur content of the world’s crude oil supply has been and will continue increasing in sulfur content. Those refiners with coking capacity are minimizi ng their raw material costs by maximizing use of high sulfur crude oils to the optimal extent for their overall refinery design. The result will be a continuing increase in the sulfur content of available coke.

• 

### Coke is a relatively small, low revenue com ponent of the refinery’s product profile. As such, the aluminum industry has little influence in controlling the quantity, quality, and price of the c oke produced by refineries.

• 

### Growth in the aluminum industry has incr eased the demand for the limited quantities of coke and has driven prices for coke to unprecedented levels.

• 

### Prices for coke nearly doubled from 1994 to 2006.

• 

### The increased global growth in aluminum production will continue to outpace the production of coke.

• 

### Primary aluminum production is expect ed to grow at the rate of 3 ! 4% annually, resulting in a commensurate growth in demand for coke.

• 

### Coke providers are blending imported, high cost , lower sulfur coke with domestically sourced coke in attempts to meet the cu rrent specification requirements for coke.

• 

### Removal or reduction of the sulfur content of the coke once it has been received is not feasible.

• 

### Aluminum smelters are experimenting with alternative cokes and technologies that are outside of the traditional specifications to ensure continued aluminum production in the face of the changing characte ristics of this key raw material.

• 

### The deterioration in coke quality and the ti ghtness of supply is expected to continue for the foreseeable future.

• 

### The increased demand for coke will for ce the aluminum industry to accept lower quality coke with hi gher sulfur contents.

### 5-10 March 2007 

### Thus, based on the market and availability analysis of the future coke supply, Alcoa

determined that it is infeasible to consider coke at sulfur contents below 3% as a BART pollution prevention option because a supply of coke with sulfur contents below 3% cannot be ensured beyond 2013 when BART control requirements are an ticipated. These same market pressures are expected to force facilities curr ently using coke with sulfur c ontents below 3% to begin using higher sulfur content coke in the future. Although coke at sulfur contents below 3% is considered infeasible due to availability concerns, a pollu tion prevention option usin g coke with a sulfur

content of 3% was determined to be technically feasible.

5.1.3.3 Feasible Control Options from RBLC Database

A review or EPA’s RACT/BACT/LAER Clearinghouse (RBLC) database was also completed to determine which control technologies or techniques have b een utilized by primary aluminum ore reduction plants. Results from searching the RBLC are summarized in Table 4.

Table 4. RBLC Database Search Result s for Primary Aluminum Facilities

RBLC

ID Facility Last Update Process Pollutant Control Option Percent Efficient Emission LimitKY0070 NSA-A DIVISION OF SOUTHWIRE COMPANY 3/2/2004 POTLINE 5 SO 2 WET SCRUBBER a 93% 25.51 lb/hour

SC0037 ALUMAX OF SOUTH CAROLINA 9/17/2002 POTROOM GROUPS (4) PM EXISTING DRY ALUMINA SCRUBBERS (FABRIC FILTER) 5.9 lb/hour

SC0037 ALUMAX OF SOUTH CAROLINA 9/17/2002 POTROOM GROUPS (4) SO 2 LIMIT MAX % SULFUR OF ANODE COKE TO 2.95% LIMIT MAX % SULFUR OF ANODE PITCH TO 1.2% 271 lb/hour

SC0037 ALUMAX OF SOUTH CAROLINA 9/17/2002 ANODE BAKE PLANT SO 2 NO UPGRADE. LIMIT SULFUR CONTENT OF RAW MATERIALS 85.5 lb/hour

### 5-11 March 2007 

### Table 4. (Continued)

RBLC

ID Facility Last Update Process Pollutant Control Option Percent Efficient Emission LimitSC0037 ALUMAX OF SOUTH CAROLINA 9/17/2002 ANODE BAKE PLANT PM NO UPGRADE. LIMIT SULFUR CONTENT OF RAW MATERIALS 4.8 lb/hour

SC0037 ALUMAX OF SOUTH CAROLINA 9/17/2002 ANODE BAKE PLANT NO X NO UPGRADE. LIMIT SULFUR CONTENT OF RAW MATERIALS 9 lb/hour

KY0041 ARCO METALS CO. 12/18/2001 PRIMARY ALUMINUM REDUCTION POTLINE SO 2 FUEL SPEC: LOW S COKE AND PITCH (calc. 3% sulfur) 388 lb/hour

OR0002 ALUMAX PACIFIC CORP. 12/18/2001 ANODE COKE SO 2 3% S in cokeWA0003 ALCOA 12/18/2001 POTLINES 1,2,3 SO 2 FUEL SPEC: LIMIT S CONTENT IN COKE, RAW 3% S in coke

NC0003 ALCOA 1/28/2002 POT LINE 3 PM FABRIC FILTER 26 lb/hour

NC0003 ALCOA 1/28/2002 POT LINE 3 SO 2 321 lb/hourNC0003 ALCOA 1/28/2002 ANODE PRODUCTION SO 2 13 lb/hour

NC0003 ALCOA 1/28/2002 ANODE PRODUCTION PM 9 lb/hour

MO0036 NORANDA ALUMINUM, INC. 5/9/2006 POTLINE 1 AND 3 PM 10 Dry Scrubber 56.76/68.8 tons/year

a This wet scrubber is not actually used or required by permit.



### The data in the RBLC database support th e approach of limiting raw material sulfur content as a control option for the potlines and the anode bake furnace. Many facilities have

limited sulfur content in coke to limit SO 2 

### emissions. Two facilities have limits of 3% sulfur

content in coke and one has a 2.95% sulfur content limit. One fac ility is shown in the RBLC to

have a wet scrubber to control SO 2 

### emissions; however, an investig ation revealed that the wet scrubber was not required as part of a BACT de termination and that the facility currently does not operate a wet scrubber to control SO 2 

### emissions. The facility’s current Title V permit for “Potline 5” simply limits coke sulfur content to 3% and coal tar pitch sulfur to 0.8%.

### 5-12 March 2007 

### Dry alumina scrubbers (with fabric filters) are the controls that have been considered

BACT for PM.

5.1.4 Potentially Applicable BART Control Options for PM

Potentially applicable PM em ission controls are discusse d in the follow ing sections.

5.1.4.1 Fabric Filters

Fabric filters generally provi de high collection efficienci es for both coar se and fine (submicron) particles. They are relatively insensitive to fluctuations in gas stream conditions. Efficiency is relatively unaffected by large change s in inlet dust lo adings. Filter ou tlet air is very clean (EPA 2003b). Collect ed material is dry, which usually simplifies processing or disposal. Fabric filters are currently a pplied for controlling PM emissions from th e potrooms and anode baking.

5.1.4.2 Electrostatic Precipitators

ESPs are capable of very high removal effi ciencies for large and small particles (EPA 2003a). They offer control efficiencies that are co mparable to fabric filters. Because of their modular design, ESPs, like fabric filters, can be applied to a wide range of system sizes. The operating parameters that influence ESP performan ce include fly ash mass loading, particle size distribution, fly ash electrical re sistivity, and precipit ator voltage and current. Dusts with high

resistivities are not well-suited for collection in dry ESPs becau se the particles are not easily charged. This also affects the ash layers on th e collecting electrodes. An ESP is technically

feasible for control of PM fr om potrooms and anode baking.

5.1.4.3 Cyclones, Inertial Separators, and Wet Scrubbers

Cyclones and inertial separato rs are used for collection of medium-sized and coarse particles. Wet scrubbers generally remove large pa rticles but can remove small particles with the use of high pressure drops. However, none of th ese devices are as effective at removing small and submicron particles as fabric filters and ESPs (AWMA 2000).

### 5-13 March 2007 

### 5.1.5 Potentially Applicable BA RT Control Options for NO X



### Potentially applicable NO X 

### emission controls include co mbustion controls and postcombustion controls.

5.1.5.1 Combustion Controls

The concentration of NO X 

### in the potroom reactor exhaust is extremely low (<1 ppm)

because there is no external fuel or combustion z one and there are no large sources of nitrogen in the raw materials. Traditional methods of preventing NO X 

### formation using staged combustion or

low NO X 

### burners are not applicable.

NO X 

### emissions from anode baking depend on ope rating practices and burner controls. The traditional methods of preventing NO X 

### formation using staged combustion or low NO X 

### burners are not applicable because of the unique configuration of an anode baking ring furnace, with fuel injected at several points in narro w flues. However, advanced firing systems that measure and regulate fuel flow precisely usi ng a computerized contro l system may reduce NO X 

### emissions by reducing total fuel usage. Prevention of NO X 

### formation using advanced firing control is technically fe asible for anode baking.

5.1.5.2 Post-combustion Controls

Selective non-catalytic re duction (SNCR) and selectiv e catalytic reduction (SCR)

controls are discusse d in this section.

5.1.5.3 Selective Non-Catalytic Reduction

SNCR is an add-on technique that involves injecting ammonia or urea into a specific temperature zone in a furnace or boiler . The ammonia or ur ea reacts with NO X 

### in the gas to produce nitrogen and water. SNCR typically provides 30–50% NO X 

### reduction. The effectiveness of SNCR depends on the temperature where reagents are injected, mixing of the reagent in the gas, residence time of the reag ent within the requir ed temperature window, and the ratio of reagent to NO X 

### . The required temperature window is 1,600–2,100°F. Typical uncontrolled NO X

### 5-14 March 2007 

### levels where this technology has been applied vary from 200 to 400 ppm. SNCR is less effective

at lower levels of uncontrolled NO X 

### (EPA 2003e).

The temperature of the potroom emission exhaust (<300°F) and NO X 

### concentration (<1 ppm) are outside the levels where SNCR coul d be used. Thus, SNCR is not technically feasible for the potroom exhaust.

The temperature of the anode baking emission exhaust (300–450°F) is below the temperature where SNCR could be used. Down stream of the reactor where tar vapors are removed, the temperature is 150–180°F, which is below the appropriate range. In addition, the

NO X 

### concentration (<20 ppm) is below the level where SNCR could be used. Thus, SNCR is not technically feasible for the anode baking exhaust.

5.1.5.4 Selective Catalytic Reduction

SCR is an add-on technique similar to SNCR that involves injecti ng ammonia into flue gas in the presence of a meta l-based catalyst to convert NO X 

### emissions to elemental nitrogen and water. The catalyst allows SCR systems to operate at much lower temperatures than SNCR; typical temperatures for SCR are 500–800°F, compared with 1,600–2,100°F for SNCR. The optimum temperature range is 700–750° F (EPA 2002). SCR is capable of NO X 

### reduction efficiencies in the range of 70–90% and can be used with NO X 

### concentrations as low as 20 ppm. However, higher NO X 

### levels result in increased performance (EPA 2003d).

The temperature of the potroom emission exhaust (<300°F) and NO X 

### concentration (<1 ppm) are outside the levels where SCR could be used. Thus, SCR is not technically feasible for the potroom exhaust.

The temperature of the anode baking emission exhaust (300–450°F) is below the temperature where SCR could be used. Downstream of the reactor where tar vapors are removed, the temperature is 150–180°F, which is belo w the appropriate range. In addition, the NO X 

### concentration (<20 ppm) is below the level wh ere SCR could be used. Thus, SCR is not technically feasible for the anode baking exhaust.

### 5-15 March 2007 

### 5.1.6 Summary of Technically Feas ible BART Control Options

5.1.6.1 Feasible BART Control Options for SO 2



### Two technically feasible options were identified for controlling SO 2 

### emissions from the potlines and anode baking:

• 

### Add a wet scrubber to the potline and/or anode bake furnace exhausts and

• 

### A pollution prevention option limiting the sulf ur content in the coke used to produce anodes to 3.0%.

These two options were evaluated further as part of the BART determination analysis.

5.1.6.2 Feasible BART Control Options for PM

Cyclones, inertial separators, wet scrubbers, ESPs, and fabric filters are all technically feasible for controlling potroom PM emissions. Ho wever, ESPs and fabric filters are superior devices for controlling fine PM.

Fabric filtration with dry alumina scrubbi ng has been widely used in the primary aluminum industry. Most smelters constructed wi thin the past 20 years have used dry alumina scrubbing with fabric filters to control emissions from potlines. A few plants use control systems consisting of ESPs to collect PM followed by spray towers to scrub gaseous fluoride. Wet systems have many disadvantages, such as co rrosion by hydrofluoric acid, scaling, and the requirement to treat wastewater. ESPs and wet systems are no longer installed on new smelters (AWMA 2000).

Dry scrubbers are widely used on anode bake furnaces because they provide effective removal of hydrocarbons, fluorides, and PM. We t systems have the same disadvantages for anode baking as for potlines, corrosion by hydrofluor ic acid, scaling, and th e requirement to treat wastewater. Dry scrubbers with fabric filte rs are a superior choice for anode baking.

### 5-16 March 2007 

### Given that fabric filters are already used for PM control and that these high-efficiency devices are superior or equal to other feasible control options, no fu rther analysis of PM controls was performed.

5.1.6.3 Feasible BART Control Options for NO X



### Since there is no external fuel or combustion zone in the smelting cells, there are no technically feasible pre-combustion NO X 

### controls. Likewise, there are no technically feasible add-on control options because of the temperat ure of the potroom exhaust (<300°F) and low

NO X 

### concentration (<1 ppm).

Advanced firing systems may prevent NO X 

### formation by reducing natural gas usage and are technically feasible for anode baking. Add-on c ontrols are not feasible at the furnace exhaust because of the temperature (<450°F) and presence of tar vapor. Add-on controls are not feasible downstream of the reactor because of the temperature (<180°F) and low NO X 

### concentration (<20 ppm).

The option for reducing NO X 

### formation through advanced firing systems was evaluated further as part of the BA RT determination analysis

5.2 Control Effectiveness for Feasible Options

Step 3 of the BART analysis is to evaluate the control effectiveness of the technically feasible control technologies.

5.2.1 SO 2 

### Wet Scrubbing

A wet scrubber was identified as a technically feasible add-on pollution control option to

reduce SO 2 

### from the potline reactors. Typical remova l efficiencies are 80–95%. Five vendors of this type of equipment were contacted about providing control equipment quotes and only two vendors responded. The vendors were provided with information on the volume and constituents of the gas stream exhausted from the Alcoa potline reactors. The responding vendors reported

### 5-17 March 2007 

### that 95% SO 2 

### removal was technically feasible. Accordingly, an SO 2 

### removal efficiency of 95% was used in the BART analysis for the wet scrubber control option.

Mist droplets will be a component of the ga s stream emitted from the scrubber. Solids in the droplets will become airborne PM when the water in the droplets evaporates. The PM

concentration in the outlet of the we t scrubber was predicted to be 20 mg/Nm 3 

### by one of the vendors. This compares to a c oncentration range of 1–5 mg/Nm 3 

### currently emitted from the existing potline control system. Consequently, th e wet scrubber option w ould cause an increase in PM from the potlines.

A wet scrubber was also identified as a technically feasible add-on pollution control option for the anode bake furnace since it has an SO 2 

### concentration and a temperature similar to the potline reactor exhaust. However, the anode bake furnace is a smaller source than the potlines because of the lower gas flow rate (2,000,000 acfm vs. 170,000 acfm). A separate vendor cost proposal was not obtained for the anode bake furnace, but an SO 2 

### removal efficiency

of 95% is assumed to be feasible.

Table 5 summarizes the SO 2 

### emission levels under the c ontrol scenarios considered for BART. The emissions represent the combined total emissions from the potline roof vents, the potline reactors, and the anode bake furnace for each scenario. Control Scenario 1 is the

utilization of coke with 3.5% sulfur and addition of a wet scrubber to th e potlines reactors. The emissions reductions achievable by wet scrubbing at the potlines were compared to current potential emissions because the scrubber would allow th e use of lower cost 3.5% coke in the

future. Control Scenario 2 is the utilization of coke with 3.0% sulfur and addition of a wet

scrubber to the anode bake furnace. The emission reductions achievable by wet scrubbing at the anode bake furnace were compared to 3% sulfur coke emissions; add-on controls at the anode bake furnace would only be implemented afte r the pollution prevention option because the pollution prevention option provides more SO 2 

### reduction at a lower cost . Control Scenario 3 is

the utilization of 3.0% su lfur coke without additional contro l equipment. The current potential

emissions with 3.5% sulfur coke are also listed.5-18March 2007Table 5. SO2Post-Control Emission RatesaSO2NOXPM2.5PM10ControlScenarioSO2ControlTechnologyEmissions(tons/year)% Reduction(Increase)bEmissions(tons/year)% Reduction(Increase)bEmissions(tons/year)% Reduction(Increase)bEmissions(tons/year)% Reduction(Increase)b1 3.5% SulfurCoke withPotlines WetScrubber1,202 81 101 0 815 (116) 924 (87)2 3.0% SulfurCoke withAnode BakeFurnace WetScrubber4,830 12c101 0 413 (10)c529 (7)c3 3.0% SulfurCoke Potlinesand AnodeBake Furnace5,517 14 101 0 377 0 494 0CurrentPotentialEmissions3.5% SulfurCoke Potlinesand AnodeBake Furnace6,436 101 377 494aEmission rates include the potline primary control system,the potline roof emissions, and the anode bake furnace.bCompared with current potential emissions unless noted.cCompared with 3.0% sulfur coke since this scenario would only occur with Control Scenario 3.

### 5-19 March 2007 

### 5.2.2 SO 2 

### Pollution Prevention

The pollution prevention option represents a 3.0% sulfur limit in the coke used to produce anodes. As shown in Table 5, this option would reduce future SO 2 

### emissions from the potlines and anode bake furnace by approxima tely 919 tons/year below current potential emissions. Current potential emissions are based on potline design production capacity and an
anode sulfur content of 3.5%, which is the practical upper limit for the Alcoa facility.

5.2.3 Anode Bake Advanced Firing System

NO X 

### emissions from the anode bake furnace could be reduced by incorporating an advanced firing system. Total gas usage is proj ected to be reduced by 20%, which would result in a corresponding 20% reduction in NO X 

### emissions, or approximately 17 tons/year.

5.2.4 Evaluation of Cost and Other Impacts

Costs of control, energy impacts, non-air qu ality environmental impacts, and remaining

useful life are evalua ted in this section.

5.2.4.1 Cost Impacts for Feasible Controls

5.2.4.1.1 Wet Scrubber Costs

The exhaust gases from each potline are routed to Alcoa A-398 dry alumina reactors located in the courtyards between the potrooms. There are four separate dry scrubbing centers within the courtyards. Potline gases currently ex haust to atmosphere from 48 stacks above the

fabric filters.

Five vendors of FGD systems were provide d information on facility layout and the volume and constituents of the gas stream e xhausted from the reactor stacks. Two vendors responded with a preliminary design and partial cost estimates for LSFO scrubbers. Lime- or
sodium-based scrubbers could also be used, but lime and sodium are less desirable reagents

### 5-20 March 2007 

### considering that these reagents are much more expensive. The high solubility of sodium compounds also would have higher solid and liqui d waste disposal cost because there is no receiving stream near the Alcoa facility wh ere sodium-containing wastewater could be discharged directly without pre- treatment. Other types of limest one-based scrubbers could also be used, and costs for these systems would be si milar. An advantage of the forced oxidation process is that the spent slurry is oxidized to gypsum, which dewa ters more efficiently, resulting in less waste materials requiring disposal. Thus, an LFSO scrubber was determined to be the most appropriate control de vice for the cost analysis.

Neither of the two vendors provided a comp rehensive installed cost estimate. Both preliminary designs were based on a central scru bbing center as the least cost approach, where exhaust from all four alumina dry scrubbing syst ems would be ducted to a centralized scrubbing system. Both design estimates were based on syst ems that would provide 100% availability of emissions control on each day of the year, give n that potlines cannot be easily shutdown and restarted for control system outages.

One vendor provided an estimate of the sc rubber equipment only. The other provided an “indicative price,” as an installed cost based on the scrubber equipment w ith installation assumed to be equal to the equipment cost. Important retr ofit considerations are (1) that gases must be collected from 48 individual stacks, (2) the syst em must simultaneously maintain balanced flow from multiple potline control devices, and (3) th e system installation would require transport of new components through narrow passages in the existing potline. Coordination of the equipment delivery and the daily work schedule of the po tline operation would also affect the control system installation.

One of the vendors recognized the complexity of this project, poi nting out in their proposal that an extensive engineering effort was needed because of space limitations, access limitations, uncertainty as to laydown areas, and uncertainty of ductwork and supports.

For Alcoa’s BART determination, the factored cost procedures in the EPA Cost Manual (EPA 2002) were used to estimate an installed cost using the equipment costs provided by the

### 5-21 March 2007 

### vendors. The cost estimates are included in Appendix C. The vendor proposals contain

confidential business information and th erefore are provided in Appendix D.

Table 6 summarizes the cost of installi ng and operating an LSFO wet scrubber on the potlines to remove 95% of the SO 2 

### . The cost is based on an average of the two proposals. The capital and total annualized costs are high at >$200,000,000 and $39,000,000 per year, respectively. The wet scrubbe r cost effectiveness is al so high at $7,500 per ton of SO 2 

### removed, assuming use of coke with 3.5% sulfur.

A separate vendor cost estimate was not obt ained for adding a wet scrubber to the anode

bake furnace. The SO 2 

### concentrations in the exhausts fr om the potlines and the anode bake furnace are similar, but the gas flowrates are different (170,000 acfm for the anode bake furnace and 2,000,000 acfm for the potlines). The capital cost of adding a wet scrubber to the anode bake furnace was estimated using the ratio of gas flow rates and a 0.8 exponent to adjust for economy of scale as described in the exponential capacity-ratio method in Perry's Chemical Engineers’

Handbook (Perry 1984). Other costs were estimated using the ratio of gas flowrates (170,000 acfm/2,000,000 acfm) or the ratio of the anode bake furnace and potlines uncontrolled SO 2 

### emission rates (723 tons/year and 5,509 tons/yea r). The bases of the costs are included in Appendix C.

The estimated installed capital cost to add a wet scrubber to remove 95% of the SO 2 

### from

the anode bake furnace exhaust would be $30,400,000 with an annualized cost of $5,600,000 per year. As shown in Table 6, the wet scrubber cost effectiveness is also high at $8,200 per ton of

SO 2 

### removed.

5.2.4.1.2 Coke Sulfur Limit

Alcoa is currently able to obtain coke with 3.0% sulfur with out incurring significant
additional cost. However, as low sulfur coke be comes more difficult to procure, the cost will

increase.5-22March 2007Table 6. Summary of the Impacts Analysis for SO2Control ScenariosControlScenarioControlTechnologyEvaluatedEmission Rate(tons/year)EmissionsReductions(tons/year)InstalledCapital Cost($000)TotalAnnualizedControl Costs($000)Incremental CostEffectiveness($ per ton ofpollutantremoved)EnergyImpact(000 kWhour/year)CollateralIncrease inotherPollutantsNon-Air QualityEnvironmentalImpacts1 3.5% SulfurCoke withPotlines WetScrubber1,202 5,234a$217,000 $39,000 $7,500 33,200 438 tons/yearof PM2.517,600 tons/yearof solid waste fordisposal180 milliongallons/yearmakeup waterusage2 3.0% SulfurCoke with AnodeBake FurnaceWet Scrubber4,830 687b30,400 5,600 8,200 2,800 36 tons/year ofPM2.52,300 tons/year ofsolid waste fordisposalc3 3.0 % SulfurCoke Potlinesand Anode BakeFurnace5,517 919CurrentPotentialEmissionsNone 6,436aCompared with potential emissions since 3.5% sulfur coke could be used.bCompared with 3.0% sulfur coke emissions since this scenario would only occur with Control Scenario 3.

### 5-23 March 2007 

### 5.2.4.1.3 Anode Bake Advanced Firing System

The cost of an advanced firing system fo r an anode bake furnace is approximately $2,750,000 compared to the cost of a standard firing system of $1,650,000. The advanced firing system is designed to reduce natural gas c onsumption by approximately 20% through improved operational control of the furnace and reduced maintenance cost. Over time, at current natural gas prices, the 20% reduction in natural gas usage would offset th e cost to install an advanced firing system.

5.2.5 Energy Impacts

A wet scrubber removes SO 2 

### by forcing the exhaust gas through a spray tower or absorber where it contacts water droplets that contain the unreacted lime or limestone. Energy is required to overcome the resistance of the scrubb er components as well as falling water droplets. A substantial amount of energy is associated with a fan to move approximately 2,000,000 acfm through the scrubber. The fan alone would require 1,730–1,960 kW. Other energy is required for the slurry pumps, instrument ation, and miscellaneous items (e.g., lighting). The total energy required, based on an average of the two proposal s, would be approximately 3,800 kW. As listed in Table 6, this is equivalent to 33,200,000 kW- hours of electricity per year. A wet scrubber on the anode bake furnace would add 2,800,000 kW-hours per year.

5.2.6 Non-air Quality Environmental Impacts

Both of the wet scrubber proposals were based on the LSFO process. This process oxidizes the spent slurry to gyps um, which may be landfilled or commercially sold. There is no way to know at this time whether the gypsum w ould have commercial value or whether there would be any demand for it. Therefore, it must be assumed that 17,600 tons of waste from the potlines wet scrubber and 2,300 tons of waste from the anode bake furnace wet scrubber would be landfilled each year.

It is estimated that 180 million gallons of water will be required annually to operate the potline wet scrubber at a cost of $270,000. This will significantly impact the community

### 5-24 March 2007 

### infrastructure in that this will increase daily water demand by approximately 4%. There will be relatively no impact due to water discha rge, at approximately 4 gallons/minute.

It is also estimated that 36 million kWh would be needed to operate the scrubbers annually. This would impact power demand in the community and therefore also have an environmental impact due to power production equivalent to adding over 3,000 new households in the community.

5.2.7 Remaining Useful Life

Alcoa has been in operation since 1913 and has produced ma ny different products for the construction, aerospace, military, consumer, and other markets. During that time, Tennessee Operations has evolved into one of the most mode rn aluminum fabricating facilities in the world. The facility intends to be in operation throughout the period of the Regional Haze Program.

5.3 Evaluate Visibility Impacts

Step 5 of the BART analysis involves evalua tion of visibility impact s. More specifically, this is an evaluation of the potential improveme nt in visibility resul ting from application of feasible pollution preventi on/add-on control options. Refi ned CALPUFF modeling of the individual emission units with the control op tions applied was performed. This modeling was accomplished according to modeling protocol that was developed and submitted to TDAPC (included as Appendix A). In ge neral, this modeling was the same as the baseline modeling except stack data and emission data associated wi th the application of the feasible pollution prevention/add-on controls were used as mode l inputs. Table 7 presents the post-control modeling source input data that were used in the CALPUFF model to forecast the change in visibility due to the applicat ion of these control options.

Table 8 presents the results of modeling with the two potline SO 2 

### control scenarios. The baseline modeling results i ndicate that the highest 98 th 

### percentile visibility impact from Alcoa’s BART-eligible sources at GSMNP with 3% su lfur in the coke was 1.309 dv. The post-control modeling results indicate that the highest 98 th 

### percentile visibility impact from Alcoa’s5-25March 2007Table 7. SO2Post-Control Modeling Source Input DataControlScenarioSO2ControlTechnologyStack No.LocationEasting(UTM)LocationNorthing(UTM)Height ofOpeningFromGround(m)StackLength/Width orDiameter(m)Velocity(m/sec)Exit GasTemperature(%K)PM10-PM2.5(g/s)SolidPM2.5(g/s)Org.Condensables(g/s)SO2(g/s)NOX(g/s)1 WetScrubber onPotlinesP15 231.485 3963.050 45.72 7.64 16.79309.0 0.0 14.6 0.0 6.0 0.52 3.0% SulfurCokePotline 1,Room 1231.5522,3963.2083231.5770,3962.761818.57 391/3.05 1.34 296 0.825 1.163 1.110 0.457 0.0022 3.0% SulfurCokePotline 1,Room 2231.5006,3963.2057231.5257,3962.759418.57 391/3.05 1.34 296 0.825 1.163 1.110 0.457 0.0022 3.0% SulfurCokePotline 2,Room 3231.4504,3963.2030231.4755,3962.756418.57 391/3.05 1.34 296 0.722 1.018 0.972 0.457 0.0012 3% SulfurCokePotline 2,Room 4231.3988,3963.2006231.4239,3962.753418.57 391/3.05 1.34 296 0.722 1.018 0.972 0.457 0.0012 3.0% SulfurCokeA-398 Line1 North231.536 3963.050 15.96 3.82 20.40 382.8 0.024 0.013 0.200 30.0 0.1632 3.0% SulfurCokeA-398 Line1 South231.539 3962.923 15.96 3.82 20.40 382.8 0.024 0.013 0.200 30.0 0.1632 3.0% SulfurCokeA-398 Line2 North231.433 3963.049 22.60 4.88 10.32 377.5 0.090 0.048 0.745 30.0 0.0872 3.0% SulfurCokeA-398 Line2 South231.441 3962.916 22.60 4.88 10.46 373.5 0.090 0.048 0.745 30.0 0.0872 3.0% SulfurCokeBake Stack1231.421 3962.655 22.15 1.22 11.46 347.0 0.008 0.005 0.047 3.11 0.3992 3.0% SulfurCokeBake Stack2231.421 3962.647 22.15 1.22 11.46347.0 0.008 0.005 0.047 3.110.3992 3.0% SulfurCokeBake Stack3231.422 3962.639 22.15 1.22 11.46347.0 0.008 0.005 0.047 3.110.3992 3.0% SulfurCokeBake Stack4231.422 3962.661 22.15 1.22 11.46347.0 0.008 0.005 0.047 3.110.3992 3.0% SulfurCokeBake Stack5231.423 3962.623 22.15 1.22 11.46347.0 0.008 0.005 0.047 3.110.3992 3.0% SulfurCokeBake Stack6231.423 3962.615 22.15 1.22 11.46347.0 0.008 0.005 0.047 3.110.3995-26March 2007Table 8. SO2Controls – Visibility Modeling Results200120022003ControlScenario No.SO2ControlTechnologyClass I AreawithGreatestImpactModeled 98thPercentileValue (dv)Number ofDaysExceeding 0.5dvModeled 98thPercentileValue (dv)Number ofDaysExceeding 0.5dvModeled 98thPercentileValue (dv)Number ofDaysExceeding 0.5dv1 Wet ScrubberPotlinesGSMNP 0.598 13 0.477 6 0.585 132 3.0% SulfurCokeGSMNP 1.092 38 0.966 40 1.309 49

### 5-27 March 2007 

### BART-eligible sources at GSMNP with wet sc rubbers installed on the potlines was 0.598 dv in 2001. While visibility impact modeling was not perf ormed to directly asse ss the potential impact

reduction due to installation of a wet scrubber on the anode bake furnace, the visibility impact reduction was estimated to be approximately 0.09 dv. This estimate was calculated based on the relative visibility impact reduction associated with installing wet scrubbers on the potlines.

For NO X 

### , the advanced firing system is cost ne utral for the anode bake furnace and the visibility impact analysis predicts only a 0.001 dv improvement in visibility from use of this technology at the nearest Class I area (GSMNP). Based on the neg ligible change in visibility forecast resulting from the installation of an adva nced firing system, it was determined that this technology does not represent BART for the Alcoa anode bake furnace.

### 6-1 March 2007 

### 6.0 DETERMINATION OF BART

6.1 Aluminum Potlines

For potline SO 2 

### emissions, BART was determined to be a pollution prevention limit of

3% sulfur in the coke used to manufact ure anodes. This lim it will cap potline SO 2 

### emissions

below current allowable emissions. Use of wet scrubbing technology to reduce potline SO 2 

### emissions was rejected as BART due to excessive costs: total cost eff ectiveness of $7,500 per ton

of SO 2 

### removed and capital and total annualized costs of $200,000,000 and $39,000,000 per year, respectively.

For PM emissions, BART was determined to be the current level of control, which is the use of baghouses to control PM emissi ons from the alumina dry scrubbers.

There are no feasible tec hnologies for control of NO X 

### from the potlines; thus, BART for

NO X 

### was determined to be no controls.

6.2 Anode Bake Furnace

A pollution prevention limit of 3% sulfur in the coke was also determined to be BART

for anode bake furnace SO 2 

### emissions. The cost of wet scrubbing to reduce SO 2 

### emissions would be excessive at $8,200 per ton of SO 2 

### removed while providing minimal visibility improvement.

The existing level of control (based on baghouses on the alumina dry scrubbers) was

determined to be BART for PM emissions.

BART for bake furnace NO X 

### emissions was determined to be no controls. The use of an advanced firing system for reduced energy use was rejected as BART because the technology would result in negligible visibility improvement.

### 6-2 March 2007 

### 6.3 Aluminum Reclamation Crusher, Dela cquering Furnace 1, and Aluminum Reclamation Melting Furnaces 1 and 2

Based on the results of visibility impact modeling, BART for the aluminum reclamation crusher, delacquering furnace 1, and aluminum reclamation melting furnaces 1 and 2 was
determined to be the current level of emissions control for PM, NO X 

### , and SO 2 

### . The predicted visibility impact for these sources ranged from 0.000 to 0.005 dv, and further control of

emissions from these sources would therefore result in negligible visibility improvement.

6.4 Material Handling and Transfer Operations

PM emissions from 21 additional BART-eligible material handling and transfer operations are all controlled using fabric filt er technology. This existing level of emissions

control was determined to be BART for thes e material handling and transfer operations.

### 7-1 March 2007 

### 7.0 REFERENCES

AWMA 2000. Air Pollution Engineering Manual , Second Edition (formerly document AP-40), Air & Waste Management Association, John Wiley & Sons, 2000.

EPA 2003a. “Air Pollution Contro l Technology Fact Sheet – Dry Electrostatic Precipitator,” EPA-452/F-03-028, August 7.

EPA 2003b. “Air Pollution Contro l Technology Fact Sheet – Fa bric Filter,” EPA-452/F-03-025, August 7.

EPA 2003c. “Air Pollution Contro l Technology Fact Sheet – Flue Gas Desulfurization,” EPA452/F-03-034, August 8.

EPA 2003d. “Air Pollution Contro l Technology Fact Sheet – Sel ective Catalytic Reduction,” EPA-452/F-03-032, August 8.

EPA 2003e. “Air Pollution Control Technology Fact Sheet – Selective Non-Catalytic Reduction,” EPA-452/F-03-031, August 8.

EPA 2002. EPA Air Pollution Control Cost Manual, Sixth Edition, EPA/452/B-02-001, January 2002 (and updates).

Perry, Robert H. 1984. Perry’s Chemical Engineers’ Handbook , Sixth Edition, McGraw-Hill, August.

### Appendix A

ALCOA BART MODELING PROTOCOL

# Site-Specific Modeling Protocol for BART Analysis at Alcoa Inc. – Tennessee Operations’ South Plant, Blount County, Tennessee

June 2006

Prepared For:

Alcoa Inc.-Tennessee Operations Blount County, Tennessee

Prepared By:

TRC Environmental Corporation 116 John Street, Boott Mills South Lowell, Massachusetts 01852 (978) 970-5600i 

## TABLE OF CONTENTS

Page

1. INTRODUCTION 1-1

2. SOURCE DESCRIPTION 2-1

3. GEOPHYSICAL AND METEOROLOGICAL DATA 3-1 3.1 Terrain 3-1
3.2 Land Use 3-2
3.3 Meteorological Data Base 3-6

4. AIR QUALITY MODELING METHODOLOGY 4-1 4.1 Model Selection 4-1
4.1.1 Major Features of CALMET 4-2
4.1.2 Major Features of CALPUFF 4-4
4.2 Modeling Domain 4-9
4.3 Meteorological Modeling Options 4-9
4.4 Dispersion Modeling Options 4-10
4.5 Visibility Calculations 4-11

5. REFERENCES 5-1ii 

## LIST OF FIGURES

Page

Figure 2-1. Aerial photo of the facility with the potrooms and point sources underlined in red. 2-2

Figure 2-2. Alcoa South Plant layout in plant coordinates. 2-3

Figure 3-1 Terrain contour (m MSL) at 4 km resolution (VISTAS CALMET Domain 3) use for the screening run. 3-3

Figure 3-2 Terrain contour (m MSL) at 1 km resolution on the 334 km x 259 km CALMET and CALPUFF model domains. 3-4

Figure 3-3. Dominant Land Use categories at 1 km resolution on the 334 km x 259 km CALMET and CALPUFF model domains. 3-5

Figure 3-4 Surface, upper air, MM5 and precipitation st ations to be used in the 2001 modeling.. 3-122

Figure 3-5 Surface, upper air, MM5 and precipitation st ations to be used in the 2002 modeling.. 3-13

Figure 3-6 Surface, upper air, MM5 and precipitation st ations to be used in the 2003 modeling.. 3-14

Figure 3-7 Ozone stations, both CASTNet and AIRS proposed for the 2001 modeling. 3-17

Figure 3-8 Ozone stations, both CASTNet and AIRS proposed for the 2002 modeling. 3-18

Figure 3-9 Ozone stations, both CASTNet and AIRS proposed for the 2003 modeling. 3-19iii 

## LIST OF TABLES

Page

Table 2-1. Line Sources and Parameters used in CALPUFF 2-4

Table 2-2. Point Sources and Parameters used in CALPUFF 2-5

Table 2-3. Point and Line Source Emissions. 2-6

Table 2-4. PM 10 Speciation Assumptions. 2-7

Table 3-1. U.S. Geological Survey La nd Use and Land Cover Classification System 3-7

Table 3-2. Default CALMET Land Use categories an d associated geophysical parameters based on the U.S. Geological Survey Land Use classification system (14-Category System) 3-8

Table 3-3. Meteorological Data Sources and Parameters Available 3-9

Table 3-4. NWS Hourly Surface Stations for 2001, 2002 and 2003. 3-10

Table 3-5. Upper Air Stations for 2001, 2002 and 2003. 3-10

Table 3-6. Hourly NWS Precipitation Stations for 2001, 2002 and 2003. 3-11

Table 3-7. Ozone Stations for 2001, 2002 and 2003. 3-16

Table 4-1. Major Features of the CALMET Meteorological Model 4-3

Table 4-2. Major Features of the CALPUFF Model. 4-7

Table 4-3. Summary of Natural Background for Soil 4-14

Table 4-4. Monthly Site-Specific f(RH) Values based on the Centroid of the Area for Visibility Method 6 Application 4-14Introduction 1-1 

## 1. INTRODUCTION

TRC Environmental Corporation has developed a site-specific modeling protocol as required for the BART (Best Available Retrofit Technology) analysis for Alcoa Inc. – Tennessee Operations’ South Plant. This facility is situated in Blount County, Tennessee in Alcoa City north of Maryville west of the Appalachian Mountains not far from the Tennessee/North Carolina border. The Alcoa South Plant facility is a primary aluminum smelter and seconda ry aluminum production facility.

On July 6, 2005 the US Environment Protection Agency produced the Federal Register document, 40 CFR Part 51 in order to introduce new National Regional Haze Regulations for Best Available Retrofit Technology. The regional haze rule requires States to submit implementation plans (SIPs) to address regional haze visibility impairment in 156 Federally-protected parks and wilderness areas, commonly referred to as “Class 1 Areas”. The final rule included a requirement for BART for certain large stationary sources that were put in place between 1962 and 1977. The regional haze rule uses the term “BART-eligible source” to describe those sources which have the potential to emit 250 t ons or more of a visibility-impairing air pollutant, were put in place between A ugust 7, 1962 and Augus t 7 1977 and whose operations fall within one or more of 26 specifically listed source categories, of which Primary Aluminum Ore Reduction Plants are one.

BART review is required when the so urce emits any air pollutant which may reasonably be anticipated to cause or contribut e to any impairment of visibility in any Class 1 area. In identifying a level of control of BART, States are required by section 169A(g) of the CAA to consider; (a) the costs of compliance, (b) the energy and non-air quality environmental impacts of compliance, (c) any existing pollution control technology in use at the source, (d ) the remaining useful life of the source and (e) the degree of visibility improvement which may reasonably be anticipated from the use of BART.

The purpose of the modeling is to assess th e ambient air quality impacts of sulfur dioxide (SO 2 ), particulate matter (PM) and nitrogen oxides (NO x ) emissions and compare the impacts to Significant Impact Levels (SILs) at all the Class I areas located within a radius of 300 km of the facility. A total of six Class I areas are located within this radius: Mammoth Ca ve National Park, Great Smoky Mountains National Park, Linville Gorge Wilderness Area, Shining Rock Wilderness Area, Cohutta Wilderness Area and Joyce-Kilmer-Slickrock Wilderness Area. A screening run on a 4-km resolution domain has determined that there will be no exceedances of a 0.5 deciview screening th reshold at the most distant Class I area (Mammoth Cave National Park), so this Class I area is not subject to further analysis. A set of refined modeling simulations on a high resolution (1-km) grid will be conducted to evaluate impacts at the five remaining Class I areas.Introduction 1-2 The topography of the screening domain area c onsists of gentle rolling terrain on its west side where elevation of the land ranges from ~120m in the southwest to ~ 300 m in the North. A much higher elevation terrain crosses the domain from the northeast corner to the center southern portio n of the domain. This is the southern part of the Appalachian Mountains, w hose peaks can reach 2000 meters. The refined domain will be a zoom on the southe rn part of the Appalachian Mountains including the highest complex terrain areas. As a result, there is a strong potential for terrain effects, both on the meteorological fields and in terms of plume-terrain interaction effects. A non-steady-state modeling approach is useful in this assessment to properly evaluate the air qua lity impacts of the proposed sources. The CALMET and CALPUFF non-steady-state models (Scire et al., 2000a,b) are proposed for the modeling analysis. The U.S. Environmental Protection Agency (USEPA) has proposed the CALPU FF modeling system as a Guideline Model for Class I impact assessments and other long range transport applications or near field applications involving complex flows (USEPA, 2000), and the model is recommended by both the Federal Land Ma nagers Air Quality Workgroup (FLAG, 2000) and the Interagency Workgroup on Air Quality Modeling (IWAQM, 1998). CALPUFF is specifically recommended by the USEPA for BART analyses ( Federal Register , 6 July 2005).

CALMET is a diagnostic meteorological model that produces three-dimensional wind fields based on parameterized treatments of terrain effects such as slope flows, terrain blocking effects, and kinematic e ffects. Meteorological observations were used to determine the wind field in areas wh ere the observations were representative. Hourly meteorological data produced by the Mesoscale Model, Version 5 (MM5) on a 12 km grid was in CALMET for 2001 and 2002 to define the initial guess wind fields before CALMET’s terrain adjustment s were computed. For 2003, MM5 fields produced on a 36 km grid were used fo r the initial guess fields. Because of the proximity of the Alcoa facility to the Great Smoky Mountains National Park and the expected terrain influences, these CALMET simulations used the 4-km grid resolution domain (Domain 3) prepared for VISTAS are used in the screening analysis. In a refined simulation, a 1-km gr id will be used to better resolve the terrain effects on the wind and pollutant dispersion.

CALPUFF is a non-steady-state puff dispersion model. It accounts for spatial changes in the CALMET-produced meteorological fields, variability in surface conditions (elevation, surface roughness, vegetation type, etc.), chemical transformation, wet removal due to rain and snow, dry depos ition, and terrain influences on plume interaction with the surface. CALPUFF contains a module to compute visibility effects, based on a hu midity-dependent relationship between particulate matter concentrations and light extinction, as well as wet and dry acid deposition fluxes. The screening and refine d meteorological and dispersion modeling simulations will be conducted for a thr ee-year period (2001, 2002 and 2003). SO 2 ,Introduction 1-3 PM, and NO x , emissions and their secondary pr oducts resulting from chemical conversions from the Alcoa facility will be modeled at receptors in the Class I areas and their impacts on visibility will be evaluated.

This report outlines the techniques and data sources proposed for the BART analyses. The screening modeling is conducted in acco rdance with the procedures outlined in the VISTAS modeling protocol, although due to the proximity of the facility to the closest Class I area, the 4-km VISTAS Domain 3 is used. The refined analysis is based on the use of a more detailed analysis using procedures detailed in this sitespecific protocol. In Section 2, a genera l description of the study area and the source configuration is provided. Descriptions of the site characteristics and the data bases (meteorological, geophysical, and aerometric) used in the analysis are provided in Section 3. Section 4 includes an ove rview of the CALMET and CALPUFF models, and the parameters proposed for the analysis.Source Description 2-1 

## 2. SOURCE DESCRIPTION

The Alcoa South Plant facility is a primary aluminum smelter and secondary aluminum production facility located in Blount County, Tennessee west of the Appalachian Mountains not far from the Tennessee/North Carolina border.

A BART applicability analysis was comple ted for the facility to determine those sources subject to the BART analysis. The BART-eligible sources include two potlines (4 potrooms), an anode bake furnace, an aluminum scrap crusher, a delacquering furnace, and 2 aluminum scrap melting furnaces. Figure 2-1 displays an aerial photo of the facility with the potrooms and other point sources outlined.

Since the Facility is located less than 5 0km away from the Great Smoky Mountains National Park Class I area, downwash will be applied. The building parameters were computed in a previous study dated December 1999. The building downwash only for the Aluminum Reclamation Crusher has been recomputed in this application, since this stack was not modeled in the previ ous study. It emits PM only. Figure 2-2 displays in plant coordinate the location of the buildings, potrooms and stacks.

Table 2-1 lists the line source parameters while Table 2-2 shows the source parameters for the point sources. Table 2-3 summarizes the line and point source emission rates for the modeled pollutants and Table 2-4 summarizes the particulate speciation for all the sources. Note that coarse particulates are defined as particulates in the size range of 10 microns to 2.5 microns while fine particulates are equal to or less than 2.5 microns (i.e PM 2.5 ). The particulate matters provided are already in three categories: PM10-PM2.5, Solid PM2.5 and organic condensable. For modeling purposes, particulate matters are divided into 6 size categories: PM800 (6-10μm), PM425 (2.5-6μm), PM187 (2.5-1.24μm), PM112 (1-1.24μm), PM081 (0.62-1μm) and PM056 (0.5-0.62μm). PM provided will be partitioned the following way:

1- PM10-PM2.5 will be half in PM800 and half in PM425 and then added to form PMC – Coarse particulate matter with an extinction efficiency of 0.6

2- Solid PM2.5 will be half in PM081 a nd half in PM056 and then added to form SOIL – Fine particulate matter with an extinction efficiency of 1.0

3- Organic Condensable will be separated half in PM081 and half in PM056 and then added to form SOA – Organi c carbon with an extinction efficiency of 4.0Source Description 2-2 Figure 2-1 . Aerial photo of the facility with the potrooms and point sources underlined in red plotted in Geographic Coordinates. -83.985 -83.98 -83.975 -83.97 -83.965 -83.96 Longitude (in degree) 35.77 35.775

35.78Latitude (in degree) ALCOA South Plant in Blount County, Alcoa city north of Maryville

Geographic Projection, units: degree (dd) Datum: NAD83Source Description 2-3 Figure 2-2 . Alcoa South Plant layout in plant coordinates – North represents the north of the plant. -400 -200 0 200 Y-East Plant Coordinates (in meters) -600 -400 -200 0 200 400 600 800 1000X-North Plant Coordinates (in meters) 

### Building locations and BART point sources locations in Plant CoordinateSource Description 2-4Table 2-1. Line sources and parameters used in CALPUFFSourceIDEmissionUnit ID #Stack NameReleaseHeight(m)MonitorWidth(m)ExitVelocity(m/s)Delta T (ExitT – Tair)(oK)BeginUTME/N (km)EndingUTME/N (km)Begin LCCE/N (km)EndingLCC E/N(km)L01 TNPOT0045b_1 Potline#1 Room 1 18.57 3.05 1.34 22.5 231.5522,3963.2083231.5770,3962.76181166.7654, -383.20761166.8666, -383.6421L02 TNPOT0045b_2 Potline#1 Room 2 18.57 3.05 1.34 22.5 231.5006,3963.2057231.5257,3962.75941166.7153, -383.2191166.8168, -383.6533L03 TNPOTL2RM_3 Potline#2 Room 3 18.57 3.05 1.34 22.5 231.4504,3963.2030231.4755,3962.75641166.667, -383.231166.768, -383.665L04 TNPOTL2RM_4 Potline#2 Room 4 18.57 3.05 1.34 22.5 231.3988,3963.2006231.4239,3962.75341166.617, -383.2421166.718, -383.677Notes:L01-L04: F’ = 761.6 m4/s3; Ave. line source width = 3.05m; Ave. building dimension =480.67m; H = 18.57m, W = 22.65m;Ave. building separation =28.55mThe Release height (m), Monitor width (m), Exit Velocity (m/s) and Exit Temperature (oK) were all taken from the 1999 ALCOA Tennessee studyThe coordinates are displayed inUTM17 NAD27 datum taken from “Stacks_Model_TNBART_Oct2005_rev1.xls” and in Lambert conformal projection in NWS-84, standardparallel 33N, 45N, origin: 40N, 97W (projection of CALMET/CALPUFF run). They show a slight shift from the aerial photo, but were kept as is because the aerialphoto is not adequate to digitalize all individual stacks.Notes1. Source information from “Stacks_Model_TNBART_Oct2005_rev1.xls”transmitted in the email from Mike Palazzolo to Joe Scire dated May 16, 20062L01-L04: Average Line Source Buoyancy Parameter (F') CalculationF'= [gLWmw(Ts-Ta)]/Ts= 761.6 m4/s3whereg = acceleration of gravity = 9.81 m/s2L = line source length = 480.67 mWm= line source width = 3.05 mw = line source exit velocity = 1.34 m/sTs= line source exit temperature = oKTa= ambient air temperature = oKTs- Ta=ΔT = 22.5 oKSource Description 2-5Table 2-2. Point sources and parameters used in CALPUFF.IndexEmissionUnit ID #Stack NameStackHeight(m)StackDiameter(m)ExitVelocity(m/s)ExitTemp(oK)UTMEasting(km)UTMNorthing(km)LCCEasting(km)LCCNorthing(km)P01 TNPOTL0045a_N A398 Line 1 North 15.96 3.82 20.40 382.8 231.536 3963.050 1166.777 -383.366P02 TNPOTP0045a_S A398 Line 1 South 15.96 3.82 20.40 382.8 231.539 3962.923 1166.802 -383.49P03 TNPOTL0048_N A398 Line 2 North 22.60 4.88 10.32 377.5 231.433 3963.049 1166.676 -383.385P04 TNPOTL0048_S A398 Line 2 South 22.60 4.88 10.46 373.5 231.441 3962.916 1166.707 -383.514P05 TNANOD0008_1 Bake Stack #1 22.15 1.22 11.46 347.0 231.421 3962.655 1166.732 -383.774P06 TNANOD0008_2 Bake Stack #2 22.15 1.22 11.46 347.0 231.421 3962.647 1166.734 -383.782P07 TNANOD0008_3 Bake Stack #3 22.15 1.22 11.46 347.0 231.422 3962.639 1166.736 -383.789P08 TNANOD0008_4 Bake Stack #4 22.15 1.22 11.46 347.0 231.422 3962.661 1166.732 -383.768P09 TNANOD0008_5 Bake Stack #5 22.15 1.22 11.46 347.0 231.423 3962.623 1166.74 -383.805P10 TNANOD0008_6 Bake Stack #6 22.15 1.22 11.46 347.0 231.423 3962.615 1166.741 -383.813P11 TNCRSH0208 Aluminum ReclamationCrusher18.29 1.22 12.62 295.4 231.300 3963.700 1166.434 -382.768P12 TNDFRN0201 Aluminum ReclamationDelacquering Furnace #122.86 1.45 2.19 1155.4 231.315 3963.657 1166.456 -382.808P13 TNMFRN0203 Aluminum ReclamationMelting Furnace #120.73 1.92 10.46 524.3 231.316 3963.617 1166.464 -382.847P14 TNMFRN0204 Aluminum ReclamationMelting Furnace #220.73 1.83 18.11 711.5 231.282 3963.615 1166.431 -382.854UTM 17 Coordinates correspond to a datum of NAD27; LCC coordinates are in datum NWS-84.Source Description 2-6Table 2-3. Point and Line source emissions.SourceIDEmissionUnit ID #Stack NamePM10-PM2.5g/sSolidPM2.5g/sOrg. Condensablesg/sSO2g/sNOxg/sL01 TNPOT0045b_1 Potline#1 Room1 0.926 1.305 1.246 0.430 0.002L02 TNPOT0045b_2 Potline#1 Room2 0.926 1.305 1.246 0.430 0.002L03 TNPOTL2RM_3 Potline#2 Room 3 0.843 1.189 1.135 0.429 0.001L04 TNPOTL2RM_4 Potline#2 Room 4 0.843 1.189 1.135 0.429 0.001P01 TNPOTL0045a_N A398 Line 1North 0.099 0.052 0.818 28.248 0.163P02 TNPOTP0045a_S A398 Line 1South 0.099 0.052 0.818 28.248 0.163P03 TNPOTL0048_N A398 Line 2North 0.104 0.055 0.859 28.161 0.087P04 TNPOTL0048_S A398 Line 2South 0.104 0.055 0.859 28.161 0.087P05 TNANOD0008_1 Bake Stack#1 0.008 0.005 0.047 1.679 0.079P06 TNANOD0008_2 Bake Stack#2 0.008 0.005 0.047 1.679 0.079P07 TNANOD0008_3 Bake Stack#3 0.008 0.005 0.047 1.679 0.079P08 TNANOD0008_4 Bake Stack#4 0.008 0.005 0.047 1.679 0.079P09 TNANOD0008_5 Bake Stack#5 0.008 0.005 0.047 1.679 0.079P10 TNANOD0008_6 Bake Stack#6 0.008 0.005 0.047 1.679 0.079P11 TNCRSH0208 Aluminum Reclamation Crusher 0.097 0 0 0 0P12 TNDFRN0201Aluminum ReclamationDelacquering Furnace #10.045 0.027 0.001 0.087 1.358P13 TNMFRN0203Aluminum ReclamationMelting Furnace #10.128 0.076 0.002 0.003 0.214P14 TNMFRN0204Aluminum ReclamationMelting Furnace #20.137 0.081 0.002 0.004 0.228Source Description 2-7Table 2-4. PM10speciation assumptions.Coarse Filterable PMFine Filterable PMCondensable PMFilterable+CondensableSourceIDCoarseFilterablePMFineFilterablePMCondensablePMTotal(Filterable+Cond) PM6-10μm2.5-6μm1.25-2.5μm1.00-1.25μm0.625-1.00μm0.500-0.625μm0.625-1.00μm0.500-0.625μm0.625-1.00μm0.500-0.625μm(g/s) (g/s) (g/s)(g/s)(g/s)(g/s)(g/s)(g/s)(g/s)(g/s)(g/s)(g/s)(g/s)(g/s)L010.926 1.305 1.2463.4770.4630.463000.65250.65250.6230.6231.27551.2755L020.926 1.305 1.2463.4770.4630.463000.65250.65250.6230.6231.27551.2755L030.843 1.189 1.1353.1670.42150.4215000.59450.59450.56750.56751.1621.162L040.843 1.189 1.1353.1670.42150.4215000.59450.59450.56750.56751.1621.162P010.099 0.052 0.8180.9690.04950.0495000.0260.0260.4090.4090.4350.435P020.099 0.052 0.8180.9690.04950.0495000.0260.0260.4090.4090.4350.435P030.104 0.055 0.8591.0180.0520.052000.02750.02750.42950.42950.4570.457P040.104 0.055 0.8591.0180.0520.052000.02750.02750.42950.42950.4570.457P050.008 0.005 0.0470.060.0040.004000.00250.00250.02350.02350.0260.026P060.008 0.005 0.0470.060.0040.004000.00250.00250.02350.02350.0260.026P070.008 0.005 0.0470.060.0040.004000.00250.00250.02350.02350.0260.026P080.008 0.005 0.0470.060.0040.004000.00250.00250.02350.02350.0260.026P090.008 0.005 0.0470.060.0040.004000.00250.00250.02350.02350.0260.026P100.008 0.005 0.0470.060.0040.004000.00250.00250.02350.02350.0260.026P110.097 0 00.0970.04850.048500000000P120.045 0.027 0.0010.0730.02250.0225000.01350.01350.00050.00050.0140.014P130.128 0.076 0.0020.2060.0640.064000.0380.0380.0010.0010.0390.039P140.137 0.081 0.0020.2200.06850.0685000.04050.04050.0010.0010.04150.0415Geophysical and Meteorological Data 3- 1 

## 3. GEOPHYSICAL AND METEOROLOGICAL DATA

Screening runs were performed for 2001- 2003 using the VISTAS 4-km resolution CALMET Domain 3. Six Class I areas, Grea t Smoky Mountains National Park, Cohutta Wilderness, Joyce Kilmer-Slickrock Wilderness, Linville Gorge Wilderness, Shining Rock Wilderness and Mammoth Cave National Park, ar e located within the 300-km radius around the facility as it is displayed on Figure 3-1. The red outline represents the VISTAS 4-km CALMET domain, the black circle is the 300-km limit around the South Plant facility showing the Class I areas to include in the scr eening analysis, the purple outline represents the CALPUFF computation domain. The results of the screening run show that Mammoth Cave National Park does not have any exceedance s of the 0.5 dv screening threshold. The highest impacts at Mammoth Cave using the VISTAS visibility procedures (Method 6, annual average natural background) were 0.17, 0.30 and 0.35 dv for 2001-2003, respectively. As a result, Mammoth Cave is not subject to further analysis. The highest impact at the other Class I areas exceeded th e 0.5 dv threshold, so these five Class I areas will be included in the refined modeling analysis.

Since the South Plant facility distance to the closest receptors in the Great Smoky Mountains National Park is less than 30 km a nd because of the complexity of the terrain in this area, a refined run with higher grid resolu tion will be performed as described hereafter. The refined run will include the five remain ing Class I areas when Mammoth Cave National Park is excluded.



### 3.1 Terrain

Gridded terrain elevations for the proposed refined modeling domain are derived from 3 arc-second digital elevation models (DEMs) produced by the United States Geological Survey (USGS). Data are provided in files c overing 1 degree by 1 degree blocks of latitude and longitude. The 1-degree DEMs are produced by the Defense Mapping Agency using cartographic and photographic sources. USGS 1:250,000 scale topographic maps are the primary source of 1-degree DEMs.

One degree DEM data consists of an array of 1201 by 1201 elevations referenced on the geographic (latitude/longitude) coordinate system of the World Geodetic System 1972 Datum. Elevations are in meters relative to mean sea level, and the spacing of the elevations along each profile is 3 arc-s econds, which corresponds to a spacing of approximately 90 meters.

The proposed CALMET computational domain for the refined run will be a 1-km resolution domain covering part of Tennessee and North Caro lina states. This domain covers an area of 334 km by 259 km (Figure 3-2) which includes the 5 Class I areas discussed earlier and the South plant facility with a buffer zone of 50 km on each side of the domain. The terrain is rather complex with the south part of the Appalachian Mountains range crossing the domain from North East to South West. Several valley can be described and the highest peaks can reach 2000 meters. Figure 3-2 shows contours of the terrain averaged to 1 km.Geophysical and Meteorological Data 3- 2 The USGS elevation records located within each grid cell in the computational domain were averaged to produce a mean elevation at each grid point. Adequate representation of the important terrain features and valleys associated with the Class 1 area and the surrounding area are captured by the 334 x 259 grid cells, a workable number of cells. The CALPUFF computational domain will be the same as the CALMET domain. The CALMET domain extends beyond the Class I areas in order to provide an adequate buffer zone at the boundaries, and to allow the effects of flow curvature and possible small-scale recirculation to be evaluated.



### 3.2 Land Use

The USGS Land Use data in the vicinity of th e facility will be used to produce a gridded field of dominant Land Use categories. The Land Use data proposed for the analysis are the Composite Theme Grid land use data (CTG) from the USGS, at a resolution of 200 m.

Land use data were processed to produce a 1 km resolution gridded field of fractional Land Use categories. The 37 USGS Land Use categories were then mapped into 14 CALMET LU categories. Surface properties such as al bedo, Bowen ratio, roughness length, and leaf area index were computed proportionally to the fractional LU. The USGS Land Use categories are described in Table 3-1. Table 3-2 displays the 14 CALMET land use categories and their associated geophysical para meters. Figure 3-3 show the dominant land use categories to be used in the modeling.Geophysical and Meteorological Data 3- 3 Figure 3-1. Terrain contours (m MSL) at 4 km resolution (VISTAS CALMET Domain 3) use for the screening run. The 12 Class I areas located in the domain are shown. The six Class I areas within the black circle (300-km radius around South Plant facility) are used in the screening run. The purple line delimits the CALPUFF computational domain for the screening run. 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 LCC East (km) -600 -500 -400 -300 -200 -100 0 100LCC North (km)

33.N 35.N 37.N 39.N

91.W 89.W 87.W 85.W 83.W 81.W 79.W

-1 100 300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500 2700 2900 3100 3300 3500 3700 3900 4500

Terrain (m) Cohutta W Dolly Sods W

Great Smoky Mountains NP James River Face W

Joyce-Kilmer-SlickRock W Linville Gorge W
South Plant Mammoth Cave NP

Mingo W Otter Creek W

Shenandoah NP

Shining Rock W

Sipsey W 

### 1

2

1 - CALMET VISTAS domain 3 2 - CALPUFF computational domain LCC Origin: 40.00N, 97.00W

Datum: NWS-84 Matching Parallels: 33.00N, 45.00N 

### V ISTAS 4-km resolution CALMET DOMAIN 3 including all 12 Class I areas on the Domain

Class I areasGeophysical and Meteorological Data 3- 4 Figure 3-2. Terrain contours (m MSL) at 1 km resoluti on on the 334 km x 259 km CALMET and CALPUFF model domains. The five Class I areas to be modeled in the refined run and the facility are also shown.

1100 1150 1200 1250 1300 1350 1400 LCC East (km) -500 -450 -400 -350 -300LCC North (km)

35.N 36.N .

.

. . LCC Origin: 40N, 97W

Datum: NWS-84 Matching Parallels: 33N, 45N False Easting: 0 False Northing: 0 -1 100 300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500 2700 2900 3100 3300 3500 3700 3900 4500 

### Terrain of the refined Domain with 5 Class I areas included 1km resolution domai n - 334 x 259 cells

South Plant

Cohutta W Joyce Kilmer-Slickrock Shining Rock W Linville Gorge W

Great Smoky Mountains NPGeophysical and Meteorological Data 3- 5 Figure 3-3. Dominant Land Use categories at 1 km resolution on the 334 km x 259 km CALMET and CALPUFF model domains. The five Class I areas to be modeled in the refined run and the facility are also shown. 1100 1150 1200 1250 1300 1350 1400 LCC East (km) -500 -450 -400 -350 -300LCC North (km)

35.N 36.N .

.

. . LCC Origin: 40N, 97W

Datum: NWS-84 Matching Parallels: 33N, 45N False Easting: 0 False Northing: 0 

### LandUse categories of the refined Domain with 5 Class I areas included 1km resolution domain - 334 x 259 cells

South Plant

Cohutta W Joyce Kilmer-Slickrock Shining Rock W Linville Gorge W

Great Smoky Mountains NP

10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100Geophysical and Meteorological Data 3- 6 

### 3.3 Meteorological Data Base

The wind fields in the modeling domain are e xpected to be variable. Depending on the location, some of the observational data is onl y representative of a small area around itself. The local terrain is expected to influence the local flow, much of the structure in the wind fields will be determined by CALMET using its diagnostic wind field module, rather than being driven by observations.

The CALMET model requires meteorological information from the surface and upper air as well as geophysical information about the Land Use and terrain heights. Specifically, CALMET requires surface observations of wind speed, wind direction, temperature, cloud cover, ceiling height, surface pressure, relative humidity, and precipitation type (e.g., snow, rain, etc.). These variables are routinely me asured at the National Weather Service (NWS) surface stations. The upper air data will include twice-daily observations of vertical profiles of wind speed, wind direction, temperature, a nd pressure. In addition, hourly precipitation measurements will be included in the m odeling and are required for wet deposition calculations in CALPUFF. Three-dimensional gridded data from the prognostic numerical model MM5 are also included with two differe nt resolution, 12-km for 2001 and 2002 and 36-km for 2003. Table 3-3 lists the types of observational and modeled data available that will be used in the modeling. There are ar ound 12-13 surface meteorological stations in the refined run that are proposed located within the modeling domain (Table 3-4). The surface data will be extracted from the VISTAS surface standard dataset available on http://www.src.com . Upper air data closer to the refined domain will be selected from the VISTAS Domain 3 dataset (Table 3-5). The 4 u pper air stations selected are located outside the modeling refined domain.

Approximately 32-33 precipitation stations are available for use in the modeling (Table 3- 6). These data will be also extracted as a subdomain of VISTAS standard precipitation dataset. Figures 3-4 to 3-6 shows the locations and spatial coverage of all of these stations for 2001, 2002 and 2003.Geophysical and Meteorological Data 3- 7 Table 3-1. U.S. Geological Survey Land Use and Land Cover Classification System

Level I Level II 10 Urban or Built-up Land 11 12 13 14 15 16 17 Residential Commercial and Services Industrial Transportation, Communications and Utilities Industrial and Commercial Complexes Mixed Urban or Built-up Land Other Urban or Built-up Land 20 Agricultural Land 21 22

23 24 Cropland and Pasture Orchards, Groves, Vineyards, Nurseries, and Ornamental Horticultural Areas Confined Feeding Operations Other Agricultural Land 30 Rangeland 31 32 33 Herbaceous Rangeland Shrub and Brush Rangeland Mixed Rangeland 40 Forest Land 41 42 43 Deciduous Forest Land Evergreen Forest Land Mixed Forest Land 50 Water 51 52 53 54 55 Streams and Canals Lakes Reservoirs Bays and Estuaries Oceans and Seas 60 Wetland 61 62 Forested Wetland Nonforested Wetland 70 Barren Land 71 72 73 74 75 76 77 Dry Salt Flats Beaches Sandy Areas Other than Beaches Bare Exposed Rock Strip Mines, Quarries, and Gravel Pits Transitional Areas Mixed Barren Land 80 Tundra 81 82 83 84 85 Shrub and Brush Tundra Herbaceous Tundra Bare Ground Wet Tundra Mixed Tundra 90 Perennial Snow or Ice 91 92 Perennial Snowfields GlaciersGeophysical and Meteorological Data 3-8Table 3-2. Default CALMET Land Use Categories and Associated Geophysical Parameters based on the U.S. Geological Survey Land UseClassification System (14-Category System)Land Use TypeDescriptionSurfaceRoughness (m)AlbedoBowen RatioSoil HeatFlux ParameterAnthropogenicHeat Flux (W/m2)Leaf AreaIndex10 Urban or Built-up Land 1.0 0.18 1.5 .25 0.0 0.220Agricultural Land -Unirrigated0.25 0.15 1.0 .15 0.0 3.0-20*Agricultural Land - Irrigated 0.25 0.15 0.5 .15 0.0 3.030 Rangeland 0.05 0.251.0 .15 0.0 0.540 Forest Land 1.0 0.10 1.0 .15 0.0 7.050 Water 0.001 0.10 0.0 1.0 0.0 0.054 Small Water Body 0.001 0.10 0.0 1.0 0.0 0.055 Large Water Body 0.001 0.10 0.0 1.0 0.0 0.060 Wetland 1.0 0.10 0.5 .25 0.0 2.061 Forested Wetland 1.0 0.1 0.5 0.25 0.0 2.062 Nonforested Wetland 0.2 0.1 0.1 0.25 0.0 1.070 Barren Land 0.05 0.30 1.0 .15 0.0 0.0580 Tundra .20 0.30 0.5 .15 0.0 0.090 Perennial Snow or Ice.05 0.70 0.5 .15 0.0 0.0*Negative values indicate "irrigated" land useGeophysical and Meteorological Data 3- 9 Table 3-3. Meteorological Data Sources and Parameters Available

Type of Dataset Frequency Source Parameters

Surface obs. Hourly NWS Wind speed, wind direction, temperature, ceiling height, cloud cover, relative humidity, surface pressure, precipitation type Upper Air Twice-daily NWS Soundings of wind speed, wind direction, temperature, and pressure Precipitation Hourly NWS Hourly precipitation
amounts
Modeled Profiles EPA MM5 for 2001, 2002 and 2003 Hourly Hourly, gridded fields of winds, temperature, pressure, and humidity and liquid water content on 12 km grid for 2001 and 2002. Hourly gridded fields on a 36-km grid for 2003.Geophysical and Meteorological Data 3- 10 Table 3-4. NWS Hourly Surface Stations for 2001, 2002 and 2003

.

WMO INIT Station Name State Year Latitude Longitude Elevation (0.1 m) LCC X 1 (km) LCC Y 1 (km)

722154 KDNN Dalton GA 01,02,03 34.717 -84.867 216 1102.564 -510.885 723048 K6A3 Andrews NC 01 35.2 -83.867 518 1185.117 -445.273 723118 KCEU Clemson-Oconee Co A SC 01,02,03 34.667 -82.867 271 1283.806 -490.111 723119 KGMU Greenville Downtown SC 01,02,03 34.850 -82.350 319.4 1327.112 -462.648723120 KGSP Greer Greenv’lSpartanbrg AP SC 01,02,03 34.90 -82.217 291.7 1338.156 -455.227

723124 KGRD Greenwood AP SC 01,02,03 34.233 -82.15 192 1356.201 -527.227 723125 KAND Anderson County AP SC 01,02,03 34.5 -82.717 231.6 1300.218 -506.274 723144 KFQD Rutherfordton NC 01,02,03 35.433 -81.933 329 1353.882 -392.747 723145 KHKY Hickory Regional AP NC 01,02,03 35.733 -81.383 348.4 1397.141 -351.662 723148 KMRN Morganton/Lenior AP NC 01,02,03 35.817 -81.6 4 1376.347 -345.806 723150 KAVL Asheville Regional AP NC 01,02,03 35.433 -82.533 652.3 1300.433 -401.509 723183 KTRI Bristol TRI City AP TN 01,02,03 36.467 -82.400 457.2 1293.970 -286.574 723246 KOQT Oak Ridge TN 01,02,03 36.017 -84.233 277 1139.638 -360.373 723260 KTYS Knoxville Mcghee Tyson AP TN 01,02,03 35.817 -83.983 293.2 1164.964 -379.127

1 Datum is NWS-84

Table 3-5. Upper Air Stations used for 2001, 2002 and 2003

.

# Station Name WBAN# WMO# Latitude Longitude LCC X 1 LCC Y 1 Elevation (deg) (deg) (km) (km) (m)

1 Peachtree City, GA

FFC 53819 72215 33.35 -84.56 1150.994 -657.420 246

2 Greensboro, NC

GSO 13723 72317 36.08 -79.95 1516.732 -290.880 277

3 Roanoke/Blacksburg, VA

RNK 53829 72318 37.20 -80.41 1453.770 -176.566 648

4 Nashville, TN

BNA 13897 72327 36.25 -86.57 929.093 -361.386 180

1 Datum is NWS-84Geophysical and Meteorological Data 3- 11 Table 3-6. Hourly NWS Precipitati on Stations for 2001, 2002 and 2003

.

Station ID State Year of Longitude Latitude LCC X 1 LCC Y 1 Data (deg) (deg) (km) (km)

91619 GA 01,02,03 34.412N 83.207W 1257.438 -522.814 91863 GA 02,03 34.759N 84.765W 1111.152 -505.028 91998 GA 01,02,03 34.450N 83.855W 1198.178 -527.400 92479 GA 01,02,03 34.572N 84.000W 1183.123 -515.908 92578 GA 01,02,03 34.417N 84.118W 1174.885 -534.457 94651 GA 01 34.456N 84.456W 1143.661 -534.485 96091 GA 01,02,03 34.929N 83.396W 1231.787 -468.722 98935 GA 01,02,03 34.721N 83.722W 1205.839 -495.903 157677 KY 01,02,03 36.667N 84.483W 1107.585 -292.208 310300 NC 01,03 35.432N 82.537W 1300.094 -401.676 310301 NC 01,02,03 35.600N 82.533W 1297.500 -383.243 310312 NC 01,02,03 35.883N 81.950W 1344.151 -343.838 310967 NC 01,02,03 36.069N 81.352W 1393.513 -314.528 314764 NC 01,02,03 35.433N 82.234W 1327.075 -397.187 317845 NC 01,02,03 35.314N 81.534W 1391.626 -399.719 318448 NC 01,02,03 35.567N 82.383W 1311.423 -384.698 380613 SC 01,02,03 34.601N 82.434W 1323.974 -491.127 381770 SC 01,02,03 34.660N 82.824W 1287.801 -490.270 383747 SC 01,02,03 34.885N 82.224W 1337.797 -456.971 384581 SC 01,02,03 34.983N 83.067W 1260.431 -458.293 385017 SC 01,02,03 34.499N 82.022W 1362.944 -496.200 385278 SC 01,02,03 34.792N 83.246W 1247.555 -481.693 386831 SC 01,02,03 34.882N 82.719W 1293.409 -464.465 388707 SC 01,02,03 34.949N 82.443W 1317.009 -453.167 388951 SC 01,02 34.398N 82.230W 1345.997 -510.354 401094 TN 01,02,03 36.473N 82.404W 1293.512 -285.975 401978 TN 01,02,03 35.029N 84.724W 1110.822 -474.866 402934 TN 01,02,03 36.142N 82.426W 1297.430 -322.459 404950 TN 01,02,03 35.818N 83.986W 1164.682 -379.056 406272 TN 01,02,03 36.169N 83.402W 1210.771 -332.974 406750 TN 01,02,03 36.023N 84.233W 1139.545 -359.715 407850 TN 01,02,03 35.766N 84.777W 1095.105 -394.595 407884 TN 01,02,03 36.416N 82.984W 1243.498 -300.302 408766 TN 01,02,03 36.249N 84.697W 1095.011 -340.636

1 Datum is NWS-84Geophysical and Meteorological Data 3- 12 Figure 3-4 . Surface, upper air, MM5 and precipitation stations to be used in the 2001 modeling. The five Class I areas and the facility are also shown. 1000 1100 1200 1300 1400 1500 LCC East (km) -600 -500 -400 -300 -200LCC North (km)

-1 100 300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500 2700 2900 3100 3300 3500 3700 3900 4500

Terrain (m)

LCC Origin: 40.00N, 97.00W

Datum: NWS-84 Matching Parallels: 33.00N, 45.00N Upper air stations Surface stations precipitation stations 

### Surface stations, Precipitation stations and Upper air station s over CALMET domain - year 2001

MM5 grid points over the domainGeophysical and Meteorological Data 3- 13 Figure 3-5 . Surface, upper air, MM5 and precipitation stations to be used in the 2002 modeling. The five Class I areas and the facility are also shown.

1000 1100 1200 1300 1400 1500 LCC East (km) -600 -500 -400 -300 -200LCC North (km)

-1 100 300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500 2700 2900 3100 3300 3500 3700 3900 4500

Terrain (m) Surface stations, Precipitation stations and Upper air station s over CALMET domain - year 2002

Upper air stations Surface stations Precipitation stations LCC Origin: 40.00N, 97.00W

Datum: NWS-84 Matching Parallels: 33.00N, 45.00N

MM5 grid points over the domainGeophysical and Meteorological Data 3- 14 Figure 3-6 . Surface, upper air, MM5 and precipitation stations to be used in the 2003 modeling. The five Class I areas and the facility are also shown. 1000 1100 1200 1300 1400 1500 LCC East (km) -600 -500 -400 -300 -200LCC North (km)

-1 100 300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500 2700 2900 3100 3300 3500 3700 3900 4500

Terrain (m) Surface stations, Precipitation stations and Upper air station s over CALMET domain - year 2003

Upper air stations Surface stations Precipitation stations LCC Origin: 40.00N, 97.00W

Datum: NWS-84 Matching Parallels: 33.00N, 45.00N

MM5 grid points over the domainGeophysical and Meteorological Data 3- 15 3.4 Air Quality Monitoring Data

CALPUFF uses hourly ozone concentration measur ements in the chemical transformation rates (SO 2 to SO 4 , NO x to HNO 3 /NO 3 ). The ambient ozone measurements are used in determining SO 2 loss rates due to chemical transfor mation to sulfate and in determining
NO x loss rates to nitrate. Ambient ozone monitoring data for 2001, 2002 and 2003 were extracted from the U.S. EPA AIRS and CASTN et networks and were used to develop hourly ozone monitoring data files for the each year of the modeling analysis. Data for VISTAS Domain 3 was extracted from the standard ozone dataset available on the TRC CALPUFF web site ( http://www.src.com ) to create the hourly ozone file. A total of ~35 monitoring stations, listed in Table 3-7, were available for use in the modeling. See Figures 3-7 to 3-9 which show the locations of each of the available stations for each year to be modeled.Geophysical and Meteorological Data 3- 16 Table 3-7. Ozone Stations for 2001, 2002 and 2003

.

Network Year ID Latitude Longitude UTM X (km) UTM Y (km)

AIRS 01,02,03 130850001 34.37778N 84.05611W 1181.109 -537.962 AIRS 01,02,03 132130003 34.785N 84.62695W 1123.221 -500.474 AIRS 01,02,03 210130002 36.60806N 83.73695W 1174.094 -289.300 AIRS 01,02,03 370110002 35.97167N 81.93417W 1343.932 -333.920 AIRS 01,02,03 370210030 35.5N 82.6W 1293.290 -395.136 AIRS 01,02,03 370270003 35.93583N 81.53028W 1380.288 -331.779 AIRS 03 370750001 35.25793N 83.79562W 1190.583 -437.988 AIRS 01,02,03 370870004 35.50528N 82.96472W 1260.708 -399.683 AIRS 01,02,03 370870035 35.37917N 82.7925W 1278.227 -411.081 AIRS 01,02,03 370870036 35.59N 83.0775W 1249.225 -391.967 AIRS 01,02,03 370990005 35.52445N 83.23612W 1236.198 -401.313 AIRS 01,02,03 371730002 35.43551N 83.4437W 1219.158 -413.859 AIRS 01,02,03 371990003 35.73774N 82.28523W 1317.069 -364.619 AIRS 01,02,03 450010001 34.32556N 82.38611W 1333.182 -520.586 AIRS 01,02,03 450070003 34.775N 82.49028W 1315.835 -472.896 AIRS 01,02,03 450210002 35.13028N 81.81639W 1369.841 -424.079 AIRS 01,02,03 450730001 34.805N 83.2375W 1248.103 -480.151 AIRS 01,02,03 450770002 34.68607N 82.83866W 1286.031 -487.622 AIRS 01,02,03 450830009 34.98861N 82.07555W 1349.239 -443.444 AIRS 01,02,03 470010101 35.965N 84.22334W 1141.302 -365.953 AIRS 01,02,03 470090101 35.63139N 83.94361W 1171.408 -398.967 AIRS 01,02,03 470090102 35.60306N 83.78361W 1186.118 -399.997 AIRS 01,02 470630003 36.30778N 83.13448W 1232.073 -314.190 AIRS 01,02,03 470650028 35.07639N 85.15167W 1071.664 -474.795 AIRS 01,02,03 470651011 35.14028N 85.17W 1069.096 -467.990 AIRS 01,02,03 470890002 36.11445N 83.60111W 1194.058 -341.582 AIRS 01,02,03 470930021 36.08472N 83.76473W 1180.059 -346.975 AIRS 01,02,03 470931020 36.01944N 83.87361W 1171.459 -355.536 AIRS 01 470931030 35.89834N 83.95722W 1165.967 -369.882 AIRS 01,02,03 471210104 35.28889N 84.94611W 1087.033 -449.008 AIRS 01,02,03 471550101 35.69667N 83.60972W 1200.089 -387.457 AIRS 01,02,03 471550102 35.56278N 83.49806W 1212.219 -400.643 CASTNet 01,02,03 COW137 35.0608N 83.4305W 1226.514 -454.742 CASTNet 01,02,03 PNF126 36.1058N 82.0454W 1331.666 -320.908 CASTNet 01,02,03 GRS420 35.6331N 83.9422W 1171.507 -398.762 CASTNet 01,02,03 SPD111 36.47N 83.8268W 1168.403 -305.576Geophysical and Meteorological Data 3- 17 Figure 3-7 . CASTNet and AIRS ozone stations proposed for the 2001 modeling. The five Class I areas in the domain and the facility are also shown. 1100 1150 1200 1250 1300 1350 1400 LCC East (km) -500 -450 -400 -350 -300LCC North (km)

-1 100 300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500 2700 2900 3100 3300 3500 3700 3900 4500

Terrain (m)

LCC Origin: 40.00N, 97.00W

Datum: NWS-84 Matching Parallels: 33.00N, 45.00N Ozone stations Ozone stations location over CALMET domain - y ear 2001Geophysical and Meteorological Data 3- 18 Figure 3-8 . CASTNet and AIRS ozone stations proposed for the 2002 modeling. The five Class I areas in the domain and the facility are also shown. 1100 1150 1200 1250 1300 1350 1400 LCC East (km) -500 -450 -400 -350 -300LCC North (km)

-1 100 300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500 2700 2900 3100 3300 3500 3700 3900 4500

Terrain (m)

LCC Origin: 40.00N, 97.00W

Datum: NWS-84 Matching Parallels: 33.00N, 45.00N Ozone stations Ozone stations location over CALMET domain - y ear 2002Geophysical and Meteorological Data 3- 19 Figure 3-9 . CASTNet and AIRS ozone stations proposed for the 2003 modeling. The five Class I areas in the domain and the facility are also shown. 1100 1150 1200 1250 1300 1350 1400 LCC East (km) -500 -450 -400 -350 -300LCC North (km)

-1 100 300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500 2700 2900 3100 3300 3500 3700 3900 4500

Terrain (m)

LCC Origin: 40.00N, 97.00W

Datum: NWS-84 Matching Parallels: 33.00N, 45.00N Ozone stations Ozone stations location over CALMET domain - y ear 2003Air Quality Modeling Methodology 4- 1 

## 4. AIR QUALITY MODELING METHODOLOGY

4.1 Model Selection

The terrain of the region, the large sour ce-receptor distances, and the importance of chemical transformation, wet deposition, and dr y deposition were principal factors in the selection of a modeling approach. The terra in considerations included the need to incorporate terrain channeling effects on the flow field, diurnally varying slope flows (downslope at night, upslope during the day), and representing the strong spatial variability of the wind fields over relativel y short distances. The ability to treat plume interactions and plume impingement on terrain above stack height was also important.

The CALPUFF modeling system (Scire et al., 2000a,b) is proposed for the BART analysis for the six Class I areas in the 300-km radius of Alcoa South Plant facility. CALPUFF and its meteorological model CALMET, are designed to handle the complexities posed by complex terrain, the long source receptor distan ces, chemical transformation and deposition, and other issues related to Class I impacts. The CALPUFF modeling system has been adopted by the U.S. EPA as a Guideline Model for source-receptor distances greater than 50 km, and for use on a case-by-case basis in complex flow situations for shorter distances (Federal Register, April 15, 2003a). CALPUFF is recommended for Class I impact assessments by the Federal Land Managers Wo rkgroup (FLAG, 2000) and the Interagency Workgroup on Air Quality Modeling (IW AQM, 1998). CALPUFF is recommended by the USEPA for BART analyses ( Federal Register , 6 July 2005).

CALMET is a diagnostic meteorological mode l that produces three-dimensional wind and temperature fields and two-dimensional fields of mixing heights and other meteorological fields. It contains slope flow effects, terrai n channeling, and kinematic effects of terrain. CALPUFF is a non-steady-state Gaussian puff model. It includes algorithms for building downwash effects as well as chemical transfor mation, wet deposition, and dry deposition. One capability of CALPUFF not found in many specialized models such as CTDMPLUS is the ability to treat the combined effects of multiple processes (e.g., building downwash effects in complex terrain; dry deposition and overwater dispersion, etc.). A complete summary of the capabilities and features of CALMET and CALPUFF is provided in Sections 4.1.1 and 4.1.2.

Regulatory models such as the Industrial Source Complex Short Term (ISCST3) model have several important limitations for this study. One critical limitation is that ISCST3 is a steady-state, straight line plume model that cannot respond to the significant terrain-induced spatial variability to the wind fields that domin ate transport in the vicinity of the Class I areas. ISCST3 uses spatially-invariant wind fields based on single-station wind observations. Also, the steady-state formul ation does not account for causality effects, which can be important for source-receptor distances greater than a few kilometers.Air Quality Modeling Methodology 4- 2 4.1.1 Major Features of CALMET

The CALMET meteorological model consists of a diagnostic wind field module and micrometeorological modules for overwater and overland boundary layers. When using large domains, the user has the option to ad just input winds to a Lambert Conformal Projection coordinate system to account for Earth's curvature. The diagnostic wind field module uses a two-step approach to the computation of the wind fields (Douglas and Kessler, 1988). In the first step, an initial-gu ess wind field is adjusted for kinematic effects of terrain, slope flows, and terrain blocking effects to produce a Step 1 wind field. The second step consists of an objective analysis pr ocedure to introduce observational data into the Step 1 wind field to produce a final wind field.

The major features and options of the meteorological model are summarized in Table 4-1. The techniques used in the CALMET m odel are briefly described below.

Step 1 Wind Field

Kinematic Effects of Terrain : The approach of Liu and Yock e (1980) is used to evaluate kinematic terrain effects. The domain-scale winds are used to compute a terrain-forced vertical velocity, subject to an exponentia l, stability-dependent decay function. The kinematic effects of terrain on the horizontal wind components are evaluated by applying a divergence-minimization scheme to the in itial guess wind field. The divergence minimization scheme is applied iteratively until the three-dimensional divergence is less than a threshold value.

Slope Flows : The slope flow algorithm in CALMET has recently been upgraded (Scire and Robe, 1997). It is based on the shooting flow algorithm of Mahrt (1982). This scheme includes both advective-gravity and equilibrium flow regimes. At night, the slope flow model parameterizes the flow down the sides of the valley walls into the floor of the valley, and during the day, upslope flows are parameterized. The magnitude of the slope flow depends on the local surface sensible heat flux an d local terrain gradients. The slope flow wind components are added to the wind fi eld adjusted for kinematic effects.

Blocking Effects : The thermodynamic blocking effects of terrain on the wind flow are parameterized in terms of the local Froude number (Allwine and Whiteman, 1985). If the Froude number at a particular grid point is less than a critical value and the wind has an uphill component, the wind direction is adjusted to be tangent to the terrain.Air Quality Modeling Methodology 4- 3 Table 4-1. Major Features of the CALMET Meteorological Model

Boundary Layer Modules of CALMET

- Overland Boundary Layer - Energy Balance Method - Overwater Boundary Layer - Profile Method

- Produces Gridded Fields of: - Surface Friction Velocity - Convective Velocity Scale - Monin-Obukhov Length - Mixing Height - PGT Stability Class - Air Temperature (3-D) - Precipitation Rate

• Diagnostic Wind Field Module of CALMET - Slope Flows

- Kinematic Terrain Effects - Terrain Blocking Effects - Divergence Minimization - Produces Gridded Fields of U, V, W Wind Components - Inputs Include Domain-S cale Winds, Observations, and

(optionally) Coarse-Grid Prognostic Model Winds - Lambert Conformal Projection CapabilityAir Quality Modeling Methodology 4- 4 Step 2 Wind Field

The wind field resulting from the adjustments described above of the initial-guess wind is the Step 1 wind field. The second step of the procedure involves the introduction of observational data into the Step 1 wind field through an objective analysis procedure. An inverse-distance squared interpolation scheme is used which weighs observational data heavily in the vicinity of the observational station, while the Step 1 wind field dominates the interpolated wind field in regions with no observational data. The resulting wind field is subject to smoothing, an optional adjustment of vertical velocities based on the O'Brien (1970) method, and divergence minimization to produce a final Step 2 wind field.

CALMET Boundary Layer Models

The CALMET model contains two boundary laye r models for application to overland and overwater grid cells.

Overland Boundary Layer Model : Over land surfaces, the energy balance method of Holtslag and van Ulden (1983) is used to comput e hourly gridded fields of the sensible heat flux, surface friction velocity, Monin-Obukhov length, and convective velocity scale. Mixing heights are determined from the comput ed hourly surface heat fluxes and observed temperature soundings using a modified Ca rson (1973) method based on Maul (1980). Gridded fields of Pasquill-Gifford-Turner ( PGT) stability class and optional hourly precipitation rates are also determined by the model.

Overwater Boundary Layer Model : The aerodynamic and thermal properties of water surfaces suggest that a different method is best suited for calculating the boundary layer parameters in the marine environment. A profile technique, using air-sea temperature differences, is used in CALMET to compute the micrometeorological parameters in the marine boundary layer.

An upwind-looking spatial averaging scheme is optionally applied to the mixing heights and 3-dimensional temperature fields in orde r to account for important advective effects.

4.1.2 Major Features of CALPUFF

By its puff-based formulation and through the use of three-dimensional meteorological data developed by the CALMET meteorological mode l, CALPUFF can simulate the effects of time- and space-varying meteorological conditio ns on pollutant transport from sources in complex terrain. The major features and options of the CALPUFF model are summarized in Table 4-2. Some of the technical algorithms are briefly described below.

Complex Terrain: The effects of complex terrain on puff transport are derived from the CALMET winds. In addition, puff-terrain inte ractions at gridded and discrete receptor locations are simulated using one of two algorithms that modify the puff-height (either that of ISCST3 or a general "plume path coefficien t" adjustment), or an algorithm that simulates enhanced vertical dispersion derived from the weakly-stratified flow and dispersion moduleAir Quality Modeling Methodology 4- 5of the Complex Terrain Dispersion Model (CTDMPLUS) (Perry et al., 1989). The puffheight adjustment algorithms rely on the recepto r elevation (relative to the elevation at the source) and the height of the puff above the surface. The enhanced dispersion adjustment relies on the slope of the gridded terrain in th e direction of transport during the time step.

Subgrid Scale Complex Terrain (CTSG): An optional module in CALPUFF, CTSG treats terrain features that are not resolved by the gridded terrain field, and is based on the Complex Terrain Dispersion Model (CTDMPLUS) (Perry et al., 1989). Plume impingement on subgrid-scale hills is evaluated at the CTSG subgroup of receptors using a dividing streamline height (H d ) to determine which pollutant material is deflected around the sides of a hill (below H d ) and which material is advected over the hill (above H d ). The local flow (near the feature) used to define H d is taken from the gridded CALMET fields. As in CTDMPLUS, each feature is modeled in isolation with its own set of receptors.

Puff Sampling Functions: A set of accurate and computationally efficient puff sampling routines are included in CALPUFF which solv e many of the computational difficulties encountered when applying a puff model to nea r-field releases. For near-field applications during rapidly-varying meteorological cond itions, an elongated puff (slug) sampling function may be used. An integrated puff approach may be used during less demanding conditions. Both techniques reproduce contin uous plume results under the appropriate steady state conditions.

Building Downwash: The Huber-Snyder and Schulman-Scire downwash models are both incorporated into CALPUFF. An option is provi ded to use either model for all stacks, or make the choice on a stack-by-stack and wind sector-by-wind sector basis. Both algorithms have been implemented in such a way as to a llow the use of wind direction specific building dimensions. CALPUFF also includes the PRIME building downwash module.

Dispersion Coefficients: Several options are provided in CALPUFF for the computation of dispersion coefficients, including the use of turbulence measurements ( σ v and σ w ), the use of similarity theory to estimate σ v and σ w from modeled surface heat and momentum fluxes, or the use of Pasquill-Gifford (PG) or McElroy-Pooler (MP) dispersion coefficients, or dispersion equations based on the Complex Terrain Dispersion Model (CTDM). Options are provided to apply an averaging time correction or surface roughness length adjustments to the PG coefficients.

Overwater and Coastal Interaction Effects: Because the CALMET meteorological model contains both overwater and overland boundary layer algorithms, the effects of water bodies on plume transport, dispersion, and de position can be simulated with CALPUFF. The puff formulation of CALPUFF is designed to handle spatial changes in meteorological and dispersion conditions, including the abrupt changes that occur at the coastline of a major body of water.

Dry Deposition: A full resistance model is provided in CALPUFF for the computation of dry deposition rates of gases and particulate ma tter as a function of geophysical parameters, meteorological conditions, and pollutant speci es. Options are provided to allow userAir Quality Modeling Methodology 4- 6 specified, diurnally varying de position velocities to be used for one or more pollutants instead of the resistance model (e.g., for sens itivity testing) or to by-pass the dry deposition model completely. For particles, source-speci fic mass distributions may be provided for use in the resistance model.

Wind Shear Effects: CALPUFF contains an optional puff splitting algorithm that allows vertical wind shear effects across individual pu ffs to be simulated. Differential rates of dispersion and transport among the "new" puffs generated from the original, well-mixed puff can substantially increase the effective ra te of horizontal spread of the material.

Wet Deposition: An empirical scavenging coefficient approach is used in CALPUFF to compute the depletion and wet deposition fl uxes due to precipitation scavenging. The scavenging coefficients are specified as a func tion of the pollutant and precipitation type (i.e., frozen vs. liquid precipitation).

Chemical Transformation: CALPUFF includes options for parameterizing chemical transformation effects using the five species scheme (SO 2 , SO = 4 , NO x , HNO 3 , and NO − 3 ) employed in the MESOPUFF II model or a set of user-specified, diurnally-varying transformation rates.Air Quality Modeling Methodology 4- 7 Table 4-2. Major Features of the CALPUFF Model

.

• Source types - Point sources (constant or variable emissions) - Line sources (constant or variable emissions) - Volume sources (constant or variable emissions) - Area sources (constant or variable emissions)

• Non-steady-state emissions and meteorological conditions - Gridded 3-D fields of meteorological variables (winds, temperature) - Spatially-variable fields of mixing height, friction velocity, convective velocity scale, Monin-Obukhov length, precipitation rate - Vertically and horizontally-var ying turbulence and dispersion rates - Time-dependent source and emissions data for point, area, and volume sources - Temporal or wind-dependent scaling fa ctors for emission rates, for all source types

• Interface to the Emissions Production Model (EPM) - Time-varying heat flux and emi ssions from controlled burns and wildfires

• Efficient sampling functions - Integrated puff formulation - Elongated puff (slug) formulation

• Dispersion coefficient ( σ y , σ z ) options - Direct measurements of σ v and σ w - Estimated values of σ v and σ w based on similarity theory - Pasquill-Gifford (PG) dispersion coefficients (rural areas) - McElroy-Pooler (MP) disper sion coefficients (urban areas) - CTDM dispersion coefficients (neutral/stable)

• Vertical wind shear - Puff splitting - Differential advection and dispersion

• Plume rise - Buoyant and momentum rise - Stack tip effects - Building downwash effects - Partial penetration - Vertical wind shear

• Building downwash - Huber-Snyder method - Schulman-Scire method - PRIME method

• Complex terrain - Steering effects in CALMET wind field - Optional puff height adjustment: ISC3 or "plume path coefficient" - Optional enhanced vertical dispersion (neutral/weakly stable flow in CTDMPLUS)Air Quality Modeling Methodology 4- 8 Table 4-2. Major Features of the CALPUFF Model (Cont’d)

• Subgrid scale complex terrain (CTSG option) - Dividing streamline, H d , as in CTDMPLUS: - Above H d , material flows over the hill and experiences altered diffusion rates - Below H d , material deflects around the hill, splits, and wraps around the hill

• Dry Deposition - Gases and particulate matter - Three options: - Full treatment of space and time vari ations of deposition with a resistance model - User-specified diur nal cycles for each pollutant - No dry deposition

• Overwater and coastal interaction effects - Overwater boundary layer parameters - Abrupt change in meteorological conditions, plume dispersion at coastal boundary - Plume fumigation

• Chemical transformation options - Pseudo-first-order ch emical mechanism for SO 2 , SO = 4 , NO x , HNO 3 , and NO − 3 (MESOPUFF II method) - Pseudo-first-order chemical mechanism for SO 2 , SO = 4 , NO, NO 2 HNO 3 , and NO − 3 (RIVAD/ARM3 method) - User-specified diurnal cycles of transformation rates - No chemical conversion

• Wet Removal - Scavenging coefficient approach - Removal rate a function of precipitation intensity and precipitation type

• Graphical User Interface - Point-and-click model setup and data input - Enhanced error checking of model inputs - On-line Help files

• Interface Utilities - Scan ISCST3 and AUSPLUME meteorological data files for problems - Translate ISCST3 and AUSPLUME input files to CALPUFF input formatAir Quality Modeling Methodology 4- 9 

### 4.2 Modeling Domain

CALMET and CALPUFF use terrain-following coordi nates. In order to cover a large enough area for the refined analysis, a modeling domain of 334 x 259 grid cells, uniform in the horizontal with a spatial resolution of 1km is proposed. In the vertical, a stretched grid is proposed with finer resolution in the lower layers and somewhat coarser resolution aloft thus allowing adequate representation of the mi xed layer. The ten vertical levels were centered at: 10, 30, 60, 120, 240, 480, 920, 1600, 2500 and 3500 meters.

CALPUFF will be run for three years, 2001, 2002 and 2003. A network of discrete receptors derived from the list of receptors de veloped by the National Park Service (NPS) will be located within the boundaries of the five Class I areas, Great Smoky Mountains National Park, Linville Gorge, Shining Ro ck, Cohutta and Joyce Kilmer-Slickrock Wilderness Areas.



### 4.3 Meteorological Modeling Options

Initial Guess Field

MM5 data will be used to define the initia l guess field for the CALMET simulations. For 2001 and 2002 hourly MM5 data with an interv al of 12 km and 34 ve rtical levels will be used as the initial guess wind field. MM5 data w ith an interval of 36 km and 34 vertical levels will be used as the initial guess wind field for 2003.

Step 1 Field: Terrain Effects

In developing the Step 1 wind field, CALMET adjusts the initial guess field to reflect kinematic effects of the terrain, slope flows a nd blocking effects. Sl ope flows are a function of the local slope and altitude of the nearest crest. The crest is defined as the highest peak within a radius TERRAD around each grid point. A value of TERRAD of 15 km was determined based on an analysis of the scale of the terrain and will be used in the CALMET simulations. The Step 1 field produces a flow field consistent with the fine-scale CALMET terrain resolution (1 km).

Step 2 Field: Objective Analysis

In Step 2, observations are incorporated into the Step 1 wind field to produce a final wind field. Each observation site influences the fi nal wind field within a radius of influence (parameters RMAX1 at the surface and RMAX2 aloft). Observations and Step 1 field are weighted by means of parameters R1 at the surface and R2 aloft: at a distance R1 from an observation site, the Step 1 wind field and th e surface observations are weighted equally. RMAX1 and RMAX2 will be set to large values (40 km), while small values of R1 and R2 (5km) will be used in order to limit the infl uence of observations on the grid so that important terrain effects are not smoothed out.Air Quality Modeling Methodology 4- 10 

### 4.4 Dispersion Modeling Options

The CALPUFF simulations will be conducte d using the following model options:

- Gaussian near-field distribution - Transitional plume rise - Stack tip downwash - Pasquill-Gifford (PG) dispersion coefficients (rural areas), McElroy-Pooler

coefficients (urban areas) - Transition of σ y to time-dependent (Heffter) growth rates - Partial plume path adjustment for terrain - Wet deposition, dry deposition, and chem ical transformation will be considered

The CALPUFF computational grid will be the same as the meteorological grid. The modeling domain includes a buffer zone of at least 50 km around the source area and beyond the borders of the Class I areas. This e liminates edge effects and allows pollutants involved in flow reversals to be brought back into the Class I area.

Two important computational parameters in CALPUFF are XMXLEN (maximum length of an emitted puff, in grid units) and XSAMLEN (maximum travel distance of a puff, in grid units, during one time step). Both of these variables will be set to 1.0 in the CALPUFF simulations in order to allow the strong wind channeling effects to be accounted for in the puff trajectory calculations. The first parameter ensures that the length of an emitted puff does not become so large so that it cannot r espond to changes in the wind field on the scale of the meteorological grid. The model automatically increases the frequency of puff releases to ensure the length of a single puff is not larger than the grid size. The second parameter decreases the internal time step to ensure the travel distance during one time step does not exceed the grid size.

The partial plume path adjustment option w ill be used in CALPUFF for this analysis (MCTADJ=3). The CALMET wind field incorporat es the effect of the terrain on the plume trajectories. The plume path coefficient is used to characterize the local effect on groundlevel concentrations. The default plume path co efficients (PPC) used for this analysis are listed below:

Stability Class A B C D E F
PPC 0.5 0.5 0.5 0.5 0.35 0.35

Deposition and chemical transformation effect s will be modeled using the default dry deposition model, the scavenging coefficient wet removal module, and the default chemical transformation mechanism. Eleven species will be modeled with CALPUFF for this analysis: SO 2 , SO 4 , NO x , HNO 3 , NO 3, and six subcategories of PM 10 , (PM 800 , PM 425 , PM 187 , PM 112 , PM 081 , PM 056 ). Of these eleven species, three are emitted by the Alcoa sources: SO 2 , NO x , PM 10 , with PM 10 being divided into the six subcategories described above. The chemical mechanism computes transformation rates of SO 2 to SO 4 and NO x to NO 3 /HNO 3 .Air Quality Modeling Methodology 4- 11 Hourly measured ozone concentrations will be provided in an external OZONE.DAT file for use with the chemical transformation module. These ozone concentrations, along with radiation intensity, will be used as surrogates for the OH concentration during the day when the gas phase free radical chemistry was active.

To allow for flexibility each source will be modeled by group of same emission rates and their source contributions were summed at the end.



### 4.5 Visibility Calculations

Calculations of the impact of the simu lated plume particulate matter component concentrations on light extinction is carried out in the CALPOST postprocessor. The procedures will be consistent with the VI STAS modeling protocol (VISTAS, 2005). The equation used is the usual IMPROVE/EPA e quation which is applie d to determine the change in light extinction due to changes in component concentrations. Using the notations of CALPOST, the formula is the following:

B ext = 3f(RH)[(NH 4 )2SO 4 ] + 3f(RH)[NH 4 NO 3 ] + 4[OC] + 1[Soil] + 0.6[Coarse Mass] +10[EC] + b ray
The concentrations, in square brackets, are in μ g/m 3 and b ext is in units of Mm -1 . The Rayleigh scattering term (b ray ) has a default value of 10 Mm -1 , as recommended in EPA guidelines for tracking reasonable progress (EPA , 2003a). Note that organic carbon (OC) consists of condensable par ticulates which are assumed to be split evenly between the lowest two particle size categories. Soil is fine particulates which is defined as PM 2.5 . These species are created through scaling and summing of the various CALPUFF output files using the POSTUTIL program.

There are a few important differences in detail and in notation between the CALPOST formula for estimating light extinction and that of IMPROVE and EPA. First, the OC in the formula above represents organic carbonaceous matter (OMC in IMPROVE’s notation), which is 1.4 times the OC (i.e. organic carbon alone) in the IMPROVE formula. The EC above in synonymous with LAC in the IMPR OVE formula. New implementations were added in CALPOST regarding the choice of f(RH) curve. One can now choose from IMPROVE f(RH) curve, whose values are doc umented in the December 2000 FLAG report, EPA f(RH) curve, as documented in EPA’s regional haze guidance documents, 2003 and IWAQM 1998 f(RH) curve. Also, CALPOST set s the maximum relative humidity at 98 percent by default (although the user can cha nge it), while the EPA guidance now caps it at 95 percent.

The haze index (HI) is calculated from the extinc tion coefficient via the following formula:

HI = 10 ln(b ext /10)Air Quality Modeling Methodology 4- 12 Where HI is in units of deciviews (dv) and bext is in Mm -1 . The impact of a source is determined by comparing HI for estimated na tural background conditions with the impact of the source and without the impact of the source

.
CALPOST Method 6 will be used to compute the extinction change in deciviews consistent with the procedures outlined in the VISTAS modeling protocol.

A monthly background concentration must be en tered into the CALPOST input control file. This background concentration is entered only fo r SOIL. The way it is computed makes it suitable to represent background light extinc tion for all particulates (hygroscopic + nonhygroscopic) at the same time when multip lied by an extinction coefficient of 1.

From the natural background light extinction shown in Table 4-3, taken from Appendix B of the Guidance for Estimating Natural Visib ility Conditions Under the Regional Haze Program (September 2003) and based on the annual average natural background for example in Mammoth Cave National Park, the value of the Haze Index (HI) for the annual average is equal to 7.69 dv. It can be conve rted to the total background light extinction b back for the annual average using the following equation:

10 

### 10 HI

back 

### e b

⋅ =

Where HI is Haze Index expressed in units of deciviews (dv).

Therefore, total b back for the annual average in Mammoth Cave, including the Rayleigh scattering coefficient is calculated as

1 10 69

. 7 

### 58

. 21 10
− 

### = ⋅ = Mm e b back

soil soil ray back 

### b b b b + = + = 10

,

Where 1 

### 10
− 

### = Mm b ray and soil 

### b represents the extinction for all particulates in the background (hygroscopic or non-hygroscopic).

Hence,

1 

### 58

. 11
− 

### = Mm b soil

And since the extinctio n coefficient for soil soil 

### C is 1.0, the monthly background concentration for soil (BKSOIL) to be put in CALPOST is 11.58 μ g/m 3 for every month. Indeed,



### BKSOIL C b soil

soil 

### ⋅ =Air Quality Modeling Methodology 4- 13 Table 4-3 provides the backgr ound soil values used in th e CALPOST processing for the 6 Class I areas within the 300 km circle ar ound the facility while Table 4-4 provides the monthly f(rh) values based on the centroid of th e Class I area as required for application of Method 6. The monthly f(RH) values for each month are extracted from Appendix A of Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Program (September 2003)

.
The highest predicted light extinction change value expressed in deciviews will then be compared to the threshold value of 0.5 deci views for the screening run. However, the 8 th highest (98 th percentile) predicted light extinction cha nge will be compared to the threshold value of 0.5 deciview for the refined run, while the 100 th percentile was compared to the 0.5 deciview value for the screening run.Air Quality Modeling Methodology 4- 14 Table 4-3. Summary of Natural Background for Soil

Class I area Annual b ext (Mm -1 ) Annual HI (dv) Bsoil (Mm -1 ) Great Smoky Mountains NP 21.38 7.60 11.38

Linville Gorge W 21.36 7.59 11.36

Shining Rock W 21.40 7.61 11.40

Joyce-Kilmer SlickRock W 21.40 7.61 11.40

Cohutta W 21.38 7.60 11.38

Mammoth Cave NP 21.58 7.69 11.58

Source: Guidance for Estimating Natural Visi bility Conditions Under th e Regional Haze Program (S eptember 2003), Appendix B.

Table 4-4. Monthly Site-Specific f(RH) values based on the Centroid of the Area, for Visibility Method 6 application

Class I area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Great Smoky
Mountains NP 3.3 3.0 2.9 2.7 3.2 3.9 3.8 4.0 4.2 3.8 3.3 3.4

Linville Gorge W 3.3 3.0 3.0 2.7 3.3 3.9 4.1 4.5 4.4 3.7 3.2 3.4
Shining Rock W 3.3 3.0 2.9 2.7 3.4 3.9 4.1 4.5 4.4 3.8 3.3 3.4
Joyce KilmerSlickRock W 3.3 3.1 2.9 2.7 3.3 3.8 4.0 4.2 4.2 3.8 3.3 3.5

Cohutta W 3.3 3.1 3.0 2.8 3.4 3.8 4.0 4.2 4.2 3.8 3.4 3.5

Mammoth Cave NP 3.4 3.1 2.9 2.6 3.2 3.5 3.7 3.9 3.9 3.4 3.2 3.5

Source: Guidance for Estimating Natural Visibilit y Conditions Under the Regional Haze Program (September 2003), Appendix A,

Table A-3.References 5- 1 

## 5. REFERENCES

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Carson, D.J., 1973: The development of a dry, inversion-capped, convectively unstable boundary layer. Quart. J. Roy. Meteor. Soc., 99 , 450-467.

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Earth Tech, 2001. Mustang Energy Company, L. L. C. Mustang Electric Generating Station, Unit # 1, McKinley County, New Mexico. Class I Air Quality Modeling Protocol, Concord, MA.

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R.J. Yamartino, E.M. Insley, 1989: User's Guide to the Complex Terrain Dispersion Model Plus Algorithms for Unstable Situa tions (CTDMPLUS) Volume 1: Model Description and User Instructions. EPA/600/8-89/041, U.S. Environmental Protection Agency, Research Triangle Park, NC.

Scire, J.S. and F.R. Robe, 1997: Fine-Scale Application of the CALMET Meteorological Model to a Complex Terrain Site. Pape r 97-A1313. Air & Waste Management Association 90th Annual Meeting & Exhibiti on, Toronto, Ontario, Canada. 8-13
June 1997.References 5- 2 Scire, J.S., D.G. Strimaitis, and R.J. Yamar tino, 2000a: A User’s Guide for the CALPUFF Dispersion Model (Version 5). Earth Tech, Inc., Concord, MA

Scire, J.S., F.R. Robe, M.E. Fernau, and R. J. Yamartino, 2000b: A User’s Guide for the CALMET Meteorological Model (Version 5) . Earth Tech, Inc., Concord, MA.

Smrz, R., 1998: Updated Class I Receptor Li st and SLVs. Tennessee Department of Environment and Conservation, Division of Air Pollution Control, Nashville, TN. April 6, 1998.

Stelson, A. W. and J. H. Seinfeld, 1982: Re lative humidity and temperature dependence of the ammonium nitrate dissociation constant. Atmos. Environ., 16 , 983-992.

U.S. Department of Agriculture (USDA) Forest Service, Screening Methodology for Calculating ANC Change to High Elevati on Lakes, User’s Guide dated January
2000.

U.S. Environmental Protection Agency (EPA), 1998: Interagency Workgroup on Air Quality Modeling (IWAQM), Phase 2 Report: Summary Report and Recommendation for Modeling Long Range Transport and Impacts on Regional Visibility. EPA-454/R-98-019.

U.S. Environmental Protection Agency (EPA), 2000: Federal Register Notice dated April 21, 2001.

U.S., Environmental Protection Agency (EPA ), 2003: Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Program. EPA-454/B-03-005, September 2003.

VISTAS, 2005: Protocol for the Application of the CALPUFF Model for Analysis of Best Available Retrofit Technology (BART).