### 1000 Corporate Centre Drive One Meridian, Ste 250 Franklin, Tennessee 37067 (615) 771-2480

SANDERS LEAD SIP AIRDISPERSION MODELING ANALYSIS OF RESULTS (REVISED)



### Prepared for 

### Sanders Lead Company Troy, Alabama
March 5, 2012 Revised July 17, 2012
Project Number: 20499427.00001

## REPORT



# SANDERS LEAD SIP AIR DISPERSION MODELING ANALYSIS OF RESULTS

Prepared for 

# Sanders Lead Company Troy, Alabama

March 5, 2012 Revised July 17, 2012

1000 Corporate Centre Drive Suite 250 Franklin, Tennessee 37067 (615) 771-2480 URS Project No.: 20499427.00001

# TABlEOFCONTENTS

1.0 INTRODUCTION ................................................................................................................. 1
2.0 MODELING APPROACH................................................................................................... 1 2.1 Model Methodology

....................................................................................................... 1 2.2 Meteorological Data
....................................................................................................... 1 

### 2.3 Receptor Grid

................................................................................................................. 2 2.4 Pre-Construction Source Characterizations and Emission Rates
................................... 2 2.5 Post-Construction Source Characterizations and Emission Rates
................................. 5 2.6 Background Lead Concentration

.................................................................................... 8 

### 3.0 CONTROL MEASURES/RACT

.........................................................................................9
4.0 ATTAINMENT DEMONSTRATION............................................................................... 10 4.1 Pre-Construction Model Results

.................................................................................. 10 4.2 Post-Construction Model Results

................................................................................. 11 

### 5.0 CONTINGENCY PLAN..................................................................................................... 11 5.1 Contingency Measures
................................................................................................. 11 5.2 ContingencyTrigger Levels

......................................................................................... 11 

### 6.0 REASONABLE FURTHER PROGRESS......................................................................... 12 6.1 RFP Demonstration

...................................................................................................... 12 

### LIST OFT ABLES TABLE I TABLE2 Pre-Construction Lead Emission Sources Post-Construction Lead Emissions Sources


### APPENDICES APPENDIX A APPENDIXB APPENDIXC APPENDIXD APPENDIXE APPENDIXF APPENDIXG Input Parameters Facility Drawings Air Dispersion Modeling Assumptions MajorControl Equipment Installation Timeline Modeling Protocol Haul Road Workgroup Final Report Protocol to Support the use ofAirport Meteorological Data for Sanders Lead Modeling

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# SIPAnainmentDemonstration Sanders LeadCompanv
1.0 INTRODUCTION Sanders Lead Company, Inc. (Sanders Lead) has retained URS Corporation (URS) to prepare a modeling analysis for lead emissions released from their facility located in Troy Alabama. The purpose of this document is to present to the Alabama Department of Environmental Management (ADEM) results from the air dispersion modeling analysis, as well as present the control measures and contingency options. The modeling procedures used to conduct the analysis were based on recommendations given in the ADEM PSD Air Quality Analysis AERMOD Modeling Guidelines (May 2008). In addition, modeling guidance contained in the U.S. EPA Guideline on Air Quality Models and the U.S. EPA New Source Review Workshop Manual were followed when applicable. On September 30, 2009, ADEM provided EPA input regarding the extent of potential nonattainment areas in Alabama for the new Lead National Ambient Air Quality Standards (NAAQS). The monitoring data indicated that a small portion ofPike County, Alabama did not meet the new lead NAAQS. As a result of the NAAQS violation of the 2008 lead standards, EPA designated the area as "nonattainment". It 

### should be noted that EPA completed lead designations in two rounds; in the first round, EPA designated "nonattainment" to any area that violated the 2008 lead standards based on data from 2007-2009. In the second round, EPA deferred the final designations decisions until October 2011, such that additional lead air quality data could be collected and evaluated. 

### 2.0 MODELINGAPPROACH 2.1 MODEL METHODOLOGY 

### The following modeling analyses were performed for the Sanders Lead Attainment Demonstration State Implementation Plan (SIP) for the 2008 Lead NAAQS. This modeling analysis follows the procedures detailed in the submitted modeling protocol (August 2009) which was approved by ADEM. A copy of the modeling protocol is located in Appendix E. URS used the most recent version of AERMOD (12060), AERMET (11059), AERMINUTE (11325), AERMAP (11103), AERSURFACE (08009) that was available during the time when each ofthe four (4) facility-wide air dispersion modeling studies for both Pre-Construction and Post-Construction conditions. The first modeling analysis examined current operating conditions at the facility (PreConstruction). In contrast, the second modeling analysis examined the effectiveness of implementing the control strategies discussed in Section 3 - Control Measures/RACT 

### of this submittal. The air dispersion modeling was used to validate whether the proposed control strategies would bring the facility's lead nonattainment designation into compliance with the 2008 lead NAAQS.

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2.2 METEOROLOGICAL DATA 

### Per ADEM's request, two (2) different meteorological datasets were applied to the Sanders Air Dispersion Model separately. Both sets used five years of National Weather Service (NWS) surface meteorological data from Montgomery, Alabama (WBAN # 

### 13895) and upper-air data from Birmingham, Alabama (WBAN # 

### 53823). The first dataset applied surface characteristics representative of the NWS site, while the other dataset applied surface characteristics representative ofthe study site (Troy, AL). URS used the new EPA AERSURFACE program (dated 08009) to also confirm what the aerial imagery of the area surrounding the facility indicated. That is the area surrounding the facility is largely rural in nature with greater than 50 percent of the area made up of trees and vegetation. A review of the the Montgomery meteorological data was completed in 2009 to determine if the data was representative ofthe Troy, Alabama study site. This review, Protocol to Support the use ofAirport Meteorological Data for Sanders Lead Modeling, is located in Appendix G. The review concluded that the Montgomery surface meterological data was representative ofthe study site. It 

### should be noted that since there have been no revisions to the AERSURFACE program since 2008, therefore we believe that the surface characteristics representative analysis completed in 2009 (refer to Appendix G) is still valid. Results from both the NWS and the study site were compared and the higher of the two concentrations was retained for calculatingthe design value. 

### 2.3 RECEPTOR GRID 

### A Cartesian receptor grid system was created to adequately assess air quality impacts in all directions from the Sanders Lead fence line to a distance ofup to 10 kilometers from the site. The grid system was created using the Universal Transverse Mercator {UTM) coordinate system. Discrete receptors were placed along the property grid fenceline at 1 00 meter spacing at 200 meter grid fenceline distance. In addition, receptors extended outward from the fenceline at 100 meter grid spacing at 1,000 meter distance; 500 meter grid spacing at 5,000 meter distance and 1,000 meter grid spacing at 10,000 meter distance. All receptors included terrain heights generated from the AERMAP terrain processor, utilizing NED terrain data. 

### 2.4 PRE-CONSTRUCTION SOURCE CHARACTERIZATIONS AND EMISSION RATES Table 1 

### summarizes the point (stacks) and volume (fugitives) sources that were modeled to simulate Pre-Construction conditions at the facility. Refer to Appendix A for a summary of stack parameters as well as fugitive source parameters for each of the Pre-Construction lead emission sources.

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# ...

... 

# SIPAttainmentDemonstration Sanders LeadCompany
Table 1 - Pre-Construction Lead Emission Sources Emission SourceID Type SourceDescription Rate (lb/hr) Stack 1 Point Blast Furnaces 1, 2 and Reverberatory Furnace 0.37 Stack 5 Point Blast Furnaces 3, 4 and Alloying Kettles 0.092 Stack4 Point Sanitary Baghouse for Furnaces 1and 2 and Alloying 0.068 Kettle Flue System Stack4a Point Sanitary Baghouse for Furnaces 3 and 4 and the Three 0.011 (3) Dust Bins Stack 10 Point Slag Treatment Building 0.026 Haul Road 1 Volume Material from breakerto mainbuilding 0.010 Haul Road2 Volume Material to Slag Treatment building 0.0014 Haul Road 3 Volume Raw material (coke, limestone, scrap iron) to main 0.00047 building Haul Road4 Volume Delivery ofraw coke, limestone and scrap iron 0.0029 Haul Road 5 Volume Delivery ofbatteries to Breaker 0.0052 Source A Volume Shredding and Separation Fugitive 0.057 SourceB Volume De-casing oflndustrial Batteries 0.222 Source C Volume Raw Material Storage Building Operations 0.0012 SourceD Volume Furnace/Refining Building Operations 0.17
Point Sources: A total offive {5) point sources were incorporated into the Pre-Construction model. Each ofthe point sources represented a stack at Sanders Lead; refer to Appendix A for a summary ofthe modeling parameters for each stack. For each ofthe five sources, the actual height and diameter were modeled. The stack exit temperature and velocity for each source was based on stack test data provided by Sanders Lead. It should be noted that stack test based exit temperatures, velocities, and emission rates were used for the Pre-Construction analysis because they were representative ofactual routine operations. Stack 1 exhaust emissions from Blast Furnace No. 1 and No. 2 and the Agglomeration Furnace. Emissions associated with Stack 1 are based on stack test data provided by Sanders Lead and reflect an 8,760 hours/year operating schedule. Refer to Drawing 1 (in Appendix B) for the location ofStack 1.

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Stack 5 exhaust emissions from Blast Furnace No. 3 and No. 4 and eight (8) Alloying Kettles. Emissions associated with Stack 5 are based on stack test data provided by Sanders Lead and reflect an 8,760 hours/year operating schedule. Refer to Drawing 1for the location ofStack 5. Stack 4 exhaust emissions from the sanitary hood system associated with Furnace Nos. 1 and 2 as well as the Alloying Kettles Heating System. Emissions associated with Stack 4 are based on stack test data provided by Sanders Lead and reflect an 8,760 hours/year operating schedule. Refer to Drawing 1for the location ofStack 4. Stack 4a exhaust emissions from the Sanitary Fugitive Emissions Collection. Emissions associated with Stack 4a are based on stack test data provided by Sanders Lead and reflect an 8,760 hours/year operating schedule. Refer to Drawing 1 for the location ofStack 4a. Finally, Stack 10 exhaust emissions from the Slag Treatment Facility, which includes a feeder, crusher, screen and mixer. Emissions associated with Stack 10 are based on stack test data provided by Sanders Lead and reflect an 8,760 hours/year operating schedule. Refer to Drawing 1for the location ofStack 10. Volume Sources: A total of nine (9) volume sources were incorporated into the Pre-Construction model. The volume sources can be further divided into two (2) categories which include: Operation volume sources and Haul Road volume sources; refer to Drawing 1 (in Appendix B) for the location of operations volume sources and on-site haul roads. Included in Appendix C is a summary ofthe methodology used in calculating the parameters used in modeling the sources (both Operation and Haul Road sources). The emission rate for each ofthe four (4) Operation volume sources were derived from actual building parameters and average lead concentrations per area sampling. Where required, assumptions were made in order to calculate the sources emission rate; these assumptions are summarized in Appendix C. The four (4) Operation volume sources included in the Pre-Construction model included:
Source A accounts for fugitive emissions from the Shredding and Separation Building operations. The emission rate for Source A reflects a 4,160 hours/year operating schedule. Source B accounts for fugitive emissions from the Decasing of Industrial Batteries operations. The emission rate for Source B reflects a 1,664 hours/year operating schedule. Source C accounts for fugitive emissions from the Raw Material Storage Building operations. The emissionratereflects an 8,760 hours/year operating schedule. Source D accounts for fugitive emissions from the Furnace and Refining Building operations. The emission rate reflects an 8,760 hours/year operating schedule. 4
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# SIPAnainmentDemonstration Sanders LeadCompanv
The Pre-Construction model also incorporated a total offive (5) haul roads. Refer to Drawing 1 for the location ofon-sitehaul roads as well as building locations. Haul Road 1 accounts for fugitive emissions originating from on-site vehicles traveling between the Breaker Building and the Main Building. Haul Road 2 accounts for fugitive emissions from on-site vehicles transferring material between the Main Building and the Slag Treatment Building. Haul Road 3 accounts for fugitive emissions from on-site vehicles transferring material (coke, limestone and scrap iron) to the Main Building for processing. Haul Road 4 accounts for fugitive emissions from off-site vehicles delivering raw coke, limestone and scrap iron. Haul Road 5 accounts for fugitive emissions from off-site vehicles delivering batteries to the Breaker Building. Haul road volume source parameters were determined following procedures recommended by the Haul Road Workgroup Final Report (November 2011). A copy ofthe report is located in Appendix F. Below is a summaryofthe Recommended Volume Source Configuration: • Adjacent Volume Source • Top ofPlume Height- 1.7 x VH • Volume Source Release Height- 0.5 x Top ofPlume height • Width ofPlume- VW + 6m for single lane roadways 

### I Road Width+ 6m for two lane roadways. • Initial Sigma Z- Top ofPlume I 

### 2.15 • Initial Sigma Y- Width ofPlume I 

### 2.15 • Emissions input as g/s 

## 2.5 POST-CONSTRUCTION SOURCE CHARACTERIZATIONS AND EMISSION RATES Table 2 summarizes the point (stacks) and volume sources (fugitives) oflead emissions that were modeled to simulate Post-Construction conditions at the facility. Refer to Appendix A for a summary of stack parameters as well as fugitive source parameters for each of the PostConstruction lead emission sources.

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Table 2- Post-Construction Lead Emission Sources Type SourceDescription Emission Source ID Rate_Db/hr) Stack 1 Point Blast Furnaces 1, 2 and Agglomeration Furnace 0.258 Stack 5 Point Blast Furnaces 3 and 4 0.258 Stack 4 Point Sanitary Baghouse for Furnaces 1and 2 0.022 Stack 4a Point Sanitary Baghouse for Furnaces 3 and 4 0.022 Stack 10 Point Slag Treatment Building 0.023 New Stack 11 Point Canopy Hoods 0.191 New Stack 12 Point Breaker/ShredderBuilding 0.044 New Stack 13 Point Raw Material Storage 0.030 New Stack 14 Point Alloying Kettles 0.038 Haul Road 1 Volume Material from breakerto mainbuilding Enclosed Haul Road2 Volume Material to Slag Treatment building 0.0014 Haul Road 3 Volume Raw material (coke, limestone, scrap iron) to main Enclosed building Haul Road4 Volume Delivery ofraw coke, limestone and scrap iron 0.0029 Haul Road 5 Volume Delivery ofbatteries to Breaker 0.0052 Source A Volume Shredding and Separation Fugitive Enclosed Source B Volume De-casing ofIndustrial Batteries Enclosed Source C Volume Raw Material Storage Building Operations Enclosed SourceD Volume Furnace/Refining Building Operations Enclosed 

### Point Sources: A total ofnine (9) point sources were incorporated into the Post Constructionmodel. Each ofthe point sources represented a stack at Sanders Lead; refer to Appendix A 

### for a summary ofthe Post-Construction modeling parameters for each stack; refer to Drawing 2 (in Appendix B) for the location ofall nine (9) point sources. It 

### should be noted that the emission rates provided in Table 2 are based on anticipated future allowable emission, following installation of all improvements necessary to comply with the recently revised Secondary Lead MACT (40 CFR 63, Subpart X).

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# SIPAnainmentDemonstration SandersLeadCompanv
Stack 1 exhaust emissions from Blast Furnace Nos. 1 and No. 2 and the Agglomeration Furnace. Emissions associated with Stack 1 are based on the MACT future individual stack allowable lead concentration of0.00043 gr/dscfand reflect an 8,760 hours/year operating schedule. This value is about five times greaterthan the average ofthe past two compliance tests, and therefore should be an acceptable individual limit for future operations. Refer to Drawing 2 for the location of Stack 1. 

### Stack 5 exhaust emissions from Blast Furnace No. 3 and No. 4. Emissions associated with Stack 5 are based on the MACT future individual stack allowable lead concentration of0.00043 gr/dscf and reflect an 8,760 hours/year operating schedule. As with Stack 1, this value is about five times greater than the average of the past two compliance tests, and therefore should be an acceptable individual limit for future operations. Refer to Drawing 2 for the location ofStack 5. Stack 4 exhaust emissions from the sanitary hoods associated with Furnace Nos. 1 and 2. Emissions associated with Stack 4 are based on the future MACT average stack allowable lead concentration of0.000087 gr/dscfand reflect an 8,760 hours/year operating schedule. This value is about 5% higher than the average ofthe past 4 compliance tests on the sanitary baghouses. Refer to Drawing 2 for the location ofStack 4. Stack 4a exhaust emissions from the sanitary hoods associated with Furnace Nos. 3 and 4 as well as the three (3) Dust Storage Bins. Emissions associated with Stack 4a are based on the future MACT average stack allowable lead concentration of 0.000087 gr/dscf and reflect an 8,760 hours/year operating schedule. This value is about 5% higher than the average ofthe past four compliance tests on the sanitary baghouses, and 80% above the average of the last two performance tests on this baghouse. Refer to Drawing 2 for the location ofStack 4a. Stack 10 exhaust emissions from the Slag Treatment Facility, which includes a feeder, crusher, screen and mixer. Emissions associated with Stack 10 are based on a lead concentration of 0.000060 gr/dscf and reflect an 8,760 hours/year operating schedule. This value is about 20% higher than the average ofthe past two compliance tests on this baghouse. Refer to Drawing 2 for the location ofStack 10. New Stack 11 will exhaust emissions from the new canopy hoods currently being installed. Projected emissions associated with this stack are based on a lead concentration of 0.000075 gr/dscfand reflect an 8,760 hours/year operating schedule. This cartridge-type baghouse will be followed by a HEPA filter and therefore this value should be easily met at all times in that the particle emissions from the HEPA should be lower than the rate expressed above. Refer to Drawing 2 for the location ofNew Stack 11. New Stack 12 exhausts emissions from the Battery Breaker (Shredder) Building. Projected emissions associated with this stack are based on the future MACT average stack allowable lead concentration of 0.000087 gr/dscf and reflect an 8,760 hours/year operating schedule. This cartridge-type baghouse will be followed by a HEPA filter and therefore this value should be easily met at all times in that the particle emissions from the HEPA should be lowerthan the rate expressed above. Refer to Drawing 2 for the location ofNew Stack 12.

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# SIPAnainmentDemonstration Sanders LeadComuanv
New Stack 13 exhausts emissions from the Raw Material Storage Building. Projected emissions associated with this stack are based on a lead concentration of0.000060 gr/dscf and reflect an 8,760 hours/year operating schedule. This cartridge-type baghouse will be followed by a HEPA filter and therefore this value should be easily met at all times in that the particle emissions from the HEPA should be lower than the rate expressed above. Refer to Drawing 2 for the location of New Stack 13. New Stack 14 exhausts emissions from the Refining Building (Alloying Kettles). Projected emissions associated with this stack are based on a lead concentration of0.000080 gr/dscf and reflect an 8,760 hours/year operating schedule. This cartridge-type baghouse will be followed by a HEPA filter and therefore this value should be easily met at all times in that the particle emissions from the HEPA should be lower than the rate expressed above. Refer to Drawing 2 for the location ofNew Stack 14. Volume Sources: A total ofthree (3) volume sources were incorporated into the Post-Construction model. The volume sources included three (3) Haul Roads; refer to Drawing 2 (in Appendix B) for the location ofon-site haul roads as well as building locations. Haul Road 2 accounts for fugitive emissions from on-site vehicles transferring material between the Main Building and the Slag Treatment Building. Haul Road 4 accounts for fugitive emissions from off-site vehicles delivering raw coke, limestone and scrap iron. Haul Road 5 accounts for fugitive emissions from off-site vehicles delivering batteries to the Breaker Building. Haul road volume source parameters were determined following procedures recommended by the Haul Road Workgroup Final Report, as described in Section 2.4 above. It 

### should be noted that Sources A through D, as well as Haul Roads 1 and 3 have been eliminated from the Post-Construction model as the six (6) fugitive lead sources have been fully enclosed under negative pressure in orderto reduce facility wide fugitive lead emissions. 

### 2.6 BACKGROUND LEAD CONCENTRATION ADEM provided URS with a representative background concentration, based on PM2.5 speciated data from the Montgomery airport monitor. Using EPA's Air Quality System's (AQS) database, speciated PM2.5 data specifically for lead was obtained for the years 2006-2010 and the last 2 months of2005. The monitor used was the Montgomery site (01-101-1002) and the data for this monitor was collected every 6th day throughout the year. The speciated PM2.5 data was set up to collect every 6th day when concentrations were recorded. This data was then used to calculate monthly averages for the entire period. These monthly 8

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averages were then used to create 3-month rolling averages and from that the maximum 3-month rolling average for the entireperiod ofdata was determined and set as thebackground for lead. Based on results from the speciated PM2.5 data, ADEM determined that 0.009 ug/m3 provided a representativebackground concentration oflead for the area. 

## 3.0 CONTROL

## MEASURES/RACT EPA defines Reasonably Available Control Technology (RACT) as the lowest emission limitation that a particular source can meet by the application of control technology that is reasonably available considering technological and economic feasibility. The technology feasibility of applying an emission reduction method to a particular source considers the source's process and operatingprocedures, raw materials, and physical plant layout. The following items were considered when determiningthe control technology to apply: The process, operating procedures, and raw materials used bythe source can affect the feasibility of carrying out process changes that reduce emissions and the selection of add-on emission control equipment. The implementation ofRACT by the Sanders Lead facility provides enforceable and permanent emissions reductions needed to attain and maintain the lead NAAQS at this time. The following information details the proposed measures to be employed, as well as a briefexplanation ofthe control measure, as developed to date. Sanders Lead has developed a detailed "Lead Compliance Implementation Schedule" which details the installation timeline of the proposed measures in order to meet the implementation deadline; however, at the current time this is a developing document with some anticipated revisions as the project continues. Attached in Appendix D is the anticipated timeline for the major control equipment installation. The discussion ofthe control measures for attainment ofthe 2008 lead NAAQS are presented below. It 

### is currently anticipated, ifall goes according to schedule, that all ofthe modifications to the facility described in this document will be completed byDecember 31, 2012. 

### Description of Measure Control and Enclose Furnace Operations

Control and Enclose Refining Operations Combustion gases and Refining Kettle Hoods Relocate Industrial Battery Decasing and Enclose Raw 

### Explanation Sanders Lead is proposing to install canopy hoods over each blast furnace with supply air to reduce worker lead exposures. Additionally, the furnace building will be enclosed. A new 318,000 CFM baghouse followed by HEPA filters will be installed to control emissions captured bythe new hoods and building enclosure (including the kettle basement ventilation). Sanders Lead is proposing to enclose the refining building, including the elimination of sidewall fans. Area ventilation will be provided by the new 318,000 CFM baghouse discussed above. Sanders Lead is proposing to control the combustion gases and kettle hoods with a new 60,000 ACFM baghouse (withHEPAs). Sanders Lead is proposing to relocate the industrial battery decasing operations to the inside ofthe existing raw material storage building. A 

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Material Handling Operations Battery Breaker/Shredder Operations

Enclose Baghouse Hoppers and Transport ofDust Improve Process Material Transport to Eliminate Leaded Outdoor Traffic Relocate and Contain Leaded Vehicle Maintenance
Improved Watering new 60,000 ACFM collector with HEPA filters will be installed to control industrial battery decasing and raw material storage area. Sanders Lead is proposing to enclose the shredderbuilding and install a new 12,000 ACFM wet scrubber to control acid emissions from specific point locations within the Shredder Building. The exhaust from this scrubber along with building exhaust will be exhausted through a new 60,000 ACFM bag collector (with HEPAs). Sanders Lead is proposing to enclose the base ofbaghouses #1 and#5, including the access doors and removable panels on the units. Ventilation will be provided by ducting to existingbaghouses. In 

### order to eliminate leaded outdoor traffic, Sanders Lead is proposing to install building connection tunnel for the transport of group from shredderto the raw material storage building. Sanders Lead is proposing to install transfer points at the refining, smelting and raw material storage vehicle exits to maintain "leaded" vehicles inside the building. Sanders Lead is proposing to relocate leaded vehicle maintenance to a newly enclosed constructed area. Sanders Lead is proposing to develop an updated watering plan based on the new vehicle patterns and facility layout. The watering plan will include an improved floor wetting system inside and outside the building, as well as purchasing new wet sweepers for the outside buildings. 

### 4.0 ATTAINMENT DEMONSTRATION The dispersion modeling analysis was performed using the American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) modeling system. There are two input data processors that are regulatory components ofthe AERMOD modeling system: AERMET, a meteorological data preprocessor that incorporates air dispersion based on planetaryboundary layer turbulence structure and scaling concepts, and AERMAP, a terrain data preprocessor that incorporates complex terrain using United States Geological Survey (USGS) Digital Elevation Data. The Building Profile Input Program for Plume Rise Model Enhancements (BPIPPRM), a multi-building dimensions program incorporating the good engineeringpractice (GEP) technical procedures for PRIME applications was also used. Both the Pre-Construction and Post-Construction analyses used identical model programs, model settings, meteorological data, downwash data, and receptor grids. 

### 4.1 PRE-CONSTRUCTION MODEL RESULTS Below is a summary ofthe results from the facility-wide air dispersion modeling study for PreConstruction conditions. Per ADEM's request, two (2) different meteorological datasets were applied to the Sanders Air Dispersion Model separately. The first dataset applied surface characteristics representative of the National Weather Service (NWS) site, while the other dataset applied surface characteristics representative ofthe study site (Troy AL). For a summary ofPre-Construction conditions, refer to Appendix A.
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Maximum Background Total Standard Year Max. Jlglm3 Jlg/m3 Jlg/m3 Jlg/m3 Observed Pre-Construction (NWS MET Data) 5.280 0.009 5.30 0.15 2010 Pre-Construction (Facility MET Data) 3.637 0.009 3.65 0.15 2010


## 4.2 POST-CONSTRUCTION MODEL RESULTS Summarized in the table below are the results from the facility-wide air dispersion modeling study for Post-Construction conditions. As mentioned previously, two (2) meteorological datasets were applied to the Sanders Air Dispersion Model separately. The first dataset applied surface characteristics representative of the National Weather Service (NWS) site, while the other dataset applied surface characteristics representative of the study site (Troy AL). The modeling indicated that the facility, operating under Post-Construction conditions (refer to Appendix A) would meet the 

### 2008 Lead NAAQS for both MET datasets.

Post-Construction (NWS MET Data) Post-Construction (FacilityMET Data) 

## 5.0 CONTINGENCYPLAN Maximum Jlg/m3 0.144 0.139 Background Jlg/m3 0.009 0.009 Total Standard Year Max. Jlg/m3 Jlg/m3 Observed 0.15 0.15 2010 0.15 0.15 2010

SIP for nonattainment areas is required by §172(c)(9) of the FCAA to provide for specific measures to be implemented should a nonattainment area fail to meetreasonable further progress (RFP) requirements or maintain the 

### 2008 lead NAAQS by the attainment date set by the EPA. The contingency plan must be enforceable and should identify measures to be adopted, a schedule and procedure for adoption and implementation, and a specific time constraint on action to betaken bythe state. Additionally, the plan should identify specific indicators ortriggers that will beused to determine when the contingency measures are to be implemented. 

## 5.1 CONTINGENCYMEASURES Based on all the improvements that are planned for this facility (described above), it is believed that the new ambient air standard can be achieved on a consistent basis. Additonal controls being consideredbut not considered in the complinace demonstration include: 1) Install HEPA filters onboth sanitarybaghouse systems (Stacks 4 and 4a) 2) Install HEPA filters onthe slagtreatment building 3) Raise stack height ofthe slag treatmentbuilding stack However, ifan exceedance ofthe NAAQS occurs during any quarter following the implementation ofall the controls included in this plan, Sanders Lead Company will immediately initiate an investigative studyaimed at identifyingthe source ofexcessive emissions that mayhave contributed to the excursion so that controls, strategies, etc. maybe developed to11

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eliminate the likelyhood ofa reoccurrance ofan exceedance. The results ofthe investigation and action to be taken, including a proposed timeline for implementation, would be submitted within 180 days ofnotification by ADEM that the NAAQS limit had been exceeded. The full extent ofthe investigation is unknown at this time; however, as the above controls are finalized and operational, areas where additional work canbe done maybe more evident. Items under discussion at this time which mayproved to provide some additional reductions include: 1) addition ofsecond gate on the south end ofthe property in orderto direct significant traffic flow to an area futher away from the maximum lead impact areas 2) planting ofvegetation in specific areas to help control dust flow patterns and hopefully scavenge fugitive lead emissions 3) re-evaluate material handlingprocedures, patterns, etc to determine ifimprovements can be made 4) re-evaluate housekeeping procedures, including dust sweeping and collection equipment 5) 

### otherimprovements that maybecome evident based on potential source oflead emissions identified during investigation. 

## 5.2 CONTINGENCY TRIGGERLEVELS A contingencymeasure would be triggered upon failure to meet RFP requirements or failure to attain the 2008 lead NAAQS. 

## 6.0 REASONABLE FURTHERPROGRESS Section 172(c)(2) the Federal Clean Air Act (FCAA) requires areas that have been designated nonattainment for criteria pollutants to include a demonstration ofreasonable further progress (RFP) in attainment demonstrations. RFP is defined in FCAA §172(c)(2) as such annual incremental reductions in emissions ofthe relevant air pollution as are required by part D, or may reasonably be required by the United States EPA for the purpose ofensuring attainment of the applicable NAAQS by the applicable attainment date. As a result of an ambitious compliance schedule, yielding a significant reduction in lead emissions from the facility, it is presumed the following lead attainment demonstration for the 2008 Lead NAAQS would fulfill RFP for the Pike Countylead nonattainment area. 

## 6.1 RFP DEMONSTRATION As stated in the final lead rule (73 FR 67039), EPA concluded that it was appropriate that Reasonable Further Progress (RFP) be satisfied by the strict adherence to an ambitious compliance schedule which is expected to periodically yield significant emission reductions. The control measures for attainment ofthe 2008 lead NAAQS included in section 3.0 

### Control Measures/RACThave beenmodeled to achieve attainment ofthe 2008lead NAAQS as described in Air Dispersion Modeling. The stipulations require these control measures and resulting emissions reductions to be achieved as expeditiously as practicable.

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### APPENDIX A 

### Input ParametersSanders Lead Modeling Parameters • Pre-Construction

EastUTM North UTM Elevation Lead Emission Rate Operating Stack Stack Temp M-110 EU Description Source Type Schedule Height

m m It lbs/hr tonsJyr hrslyr It "f Stack 1 Blast Furnace #1 & Afterburner #2

• Stack Point ' 596668.57 3517149.10 ' 531.3 0.37 1.63 8,760 180.0 200

. Stack 5 Blast Furnace #3 & Afterburner #4 i Stack Point 596701.90 3517158.29 527.8 0.092 0.40 8,760 180.0 200 Stack 4 Blast Furnaces #1 and #2 Stack Point 596648.46 3517188.17 529.3 0.068 0.30 8,760 90.0 68 Stack4a Blast Furnaces #3 and #5 Stack Point 596744,42 3517284.12 530.4 0.011 0.05 8,760 90.0 68

. _stack 10 Slag Treatment with Baghouse Stack Point 596754.14 3517148.01 524.9 0.026 0.11 8,760 30.0 68

·-·-

EU Deseription Lead Emission Rate EastUTM North UTM Elevation Building Side Length Source Type Hours/Yr Height lbslhr I tonsJyr m m It It It

,..Source A**Shre~~i~** and Separation**Fugiti~e Fugi~!ye**  Volume 0.057 I 0.12 4,160 596819.35 3517177.44 532.4 28.2 115.2

Source B Decasing of Industrial Batteries**F~_!Jiv!"** Volume 0.22 0.19 1,664 596800.46 3517250.54 530.4 2.0 11.5 Source C**R~w** Material Storage Building Operations**_F.~:_~Qitive** Volume ! 0.0012 0.0054 9,760 596751.71 351727t.10 531.2 50.0 200.1**~----** i SourceD**Furn~ce/Refining** Buik:ling**~~_rations** F:'Qitive Volume 0.17 .J

____ ·- 0.76 8,760 596671.68 3517184.32 530.8 44.0 145.0

i Vehicle Release Vehicle Adjusted Road EU Description Lead Emission Rate Source Type Hours/Yr Height (X2) Height Width Width (+6m) Length lbslhr i tons/yr m m m m m Route t Material from breaker to main building (Bk:l.2) Fugiti':e Volume 0.0101 0.0442 8,760 7.0 3.5 3.1 9.1 79.5 Route 2 Material to Slag Treatment building Fugitive Volume 0.0014 ·. 0.0061 8,760 4.6 2.3 1.4 7.4 47.8 I Route 3 Raw material to main building (Bid.2) Fugitive Volume 0.00047 0.0020 8,760 7.0 3.5 3.1 9.1 91.5

Route 4 Delivery of raw coke, limestone and scrap iron**~--_£~itive** Volume 0.0029 i 0.0126 8,760 5.4 2.7 2.2 8.2 674.9 i Route 5 1Delivery of batteries to**Bre~~-~r -~-11Jitive**  Volume 0.0052 I 0.0226 8,760 8.2 4.1 2.6 8.6 605.0 Adjusted Width· is the actual width of the trucks (plus 6 meters), the additional width represents turbulence caused bythe vehicle as it moves along the road; width represents a side of the base of the volume Number of Volume Sources ·divide the length of the road by the adjusted width, the result is the maximum number of volume sources that could be used to represent the road. Height of Volume- the height will be equal to twice the height of the vehicle generating the emissions. Initial Horizontal Sigma
- calculated by dividing the adjusted width by 2.15. Initial Vertical Sigma- cak::ulated by dividing the height of the volume determined by2.15. Release Height- calculated by dividing the height of volume in haft; this point is in the center ofthe volume. Stack FloW Exit Diameter Velocity It acfm Ips 4.00 90,000 119.37 4.00 90,000 119.37 3.00 30,000 106.10 3.00 30,000 106.10 4.00 450,000 59.68

Initial Initial Lateral Dim Vertical Dim

26.78 13.12 2.67 0.92 46.54 23.26 33.72 20.45
Initial Horiz. Initial

### v!:~e II Emissions/ Vertical Sigma Sigma Sources I Receptor tpy 4.23 3.26 9 : 0.0051 3.44 2.14 6 : 0.00094 4.23

- 3.26

. 10 

# I 0.00020 3.81 2.51 82 0.00015 4.00 3.81 

### J
..**~o__j** 0.00032Sanders Lead Modeling Parameters: Post-Construction

I I I Operating Stack ' East UTM North UTM Elevation Lead Emission Rate ! Stack Temp ModeiiD EU Description Source Type Schedule Height I I m m ft lbslhr tons/yr hrsfyr ft "f Stack 1 Blast Furnace #1 & Afterburner #2 Stack Point 596668.57 3517149.10 531.3 0.258 1.13 8,760 180.0 220.0 Stack 5 Blast Furnace #3 & Afterburner #4 Stack Point 596701.90 3517158.29 527.8 0.258 1.13 8,760 180.0 220.0 Stack 4 Sanitary for 1 & 2 Stack Point 596648.46 3517188.17 529.3 0.022 0.10 8,760 90.0 100.0 Stack 4a Sanitary for 3 & 4**S!~~o~nt** 596694.54 3517251.20 530.4 0.022 0.10 8,760 90.0 100.0 r--:--·· Slag**Treatme~t** with Baghouse 0.023 0.10 30.0 95.0**f--:-~~~-k** 10 Stack

. Point 596754.14 3517148.01 524.9 8,760

. New Stack 11 iCanopy Hoods Stack Point 596753.27 3517179.12 526.2 0.191 I 0.84 8,760 150.0 100.0

- --· ' New Stack 12 IBattery Breaker Building Stack Point .Ji-?683445 3517202.87 532.4 0.044 0.19 8,760 90.0 80.0

.. --------- I New Stack 13 ,Raw Material Storage Stack ; Point 596814.34 3517277.66 529.7 ' 0.030 0.13 8,760 90.0 80.0**~**

New Stack 14 Alloying Kettles Stack i Point 596711.74 3517111.96 527.9 0.038 0.17 8,760 90.0 100.0

Vehicle Release Vehicle Adjusted EU Description Lead Emission Rate Elevation ' Source Type Hours/Yr Height (x2) Height Width Width(+6m) lbsfhr tonsfvr m m m m m**~~1Road2** Matenal to Slag Treatment building Fugitive j Volume 0.0014 0.0061 8,760 160.93 4.6 2.3 1.4 74 Haul Road 4 Delivery of raw coke, limestone and scrap iron Fugitive j Volume 0.0029 0.013 8,760 159.72 54 2.7 2.2 8.2 Haul Road 5 Delivery of batteries to Breaker Fug1tive Volume 0.0052 0.023 8,760 160.02 8.2 4.1 2.6 8.6 Adjusted Width -is the actual width of the trucks (plus 6 meters), the additional width represents turbulence caused by the vehicle as it moves along the road; width represents a side of the base of the volume Number of Volume Sources- divide the length of the road by the adjusted width. the result is the maximum number of volume sources that could be used to represent the road. Height of Volume- the height will be equal to twice the he1ght of the vehicle generating the emissions Initial Horizontal Sigma
- calculated by dividing the adjusted width by 2. 15. Initial Vertical Sigma- calculated by dividing the height of the volume determined by 2.15 Release Height- calculated by dividing the height of volume in half; this point is in the center of the volume Stack Exit Flow Diameter Velocity ft acfm Ips 4.0 90,000 119.4 4.0 90,000 119.4 30 30,000 82.5 3.0 30,000 82.5 4.0 45,000 59.7 11.0 318,000 55.8 4.5 60,000 62.9 4.5 60,000 62.9 4.5 60,000 629

Road Initial Horiz. Initial #of Emissions/ Vertical Volume Length Sigma Sigma Sources Receptor

m IDV 47.8 i 3.44 2.14 6**00009~-** ----- 674.9 ' 3.81 2.51 82 0.00015 i 605.0 i 4.00 3.81 70 0.00032

S:\2012\Sanders Lead\427_Consulting\01_Air\SIP\SIP Report Rev 1\Appendix A_lnput Parameters._POST rev 1.xls

### APPENDIXB FacilityDrawings0 

### "' 

# ------- Volume Source Dimensions Source ID Source A Source B Source C Source 0

Franklin, Tennessee Height (ft) Side Length (ft) 28.2 115 2.0 11.5 49.8 200 43.96 145 SANDERS LEAD TROY, ALABAMA

DRAWING 1 PRE-CONSTRUCTION SITE hAAP

### \ 

# \

i •

### APPENDIXC AirDispersion ModelingAssumptions

# ... ATTACHMENT C FUGITIVE EMISSION ASSUMPTIONS Sanders Lead Company ID Source Description Source A Shredding and Separation Fugitive Source A = Volumetric Flowfrom Egress Area *AverageLead Concentration 

### * 0.028317 I 10A6 

### *0.002205 Maximum Egress Area (jt 2 ) 1,000 Average Exit Velocity (mph) 6.6 Volumetric Flowfrom EgressArea (ft 3!h) 11,616,000 AverageLead Concentration (pg!m 3 ) 78.34 Source B Decasing ofIndustrial Batteries Source B =**213~g** X 1Nm3 X lib X 278784scf x 60min 1Nm3 35.31 scf**453592370~g** Imin lhr Maximum EgressArea Ui2 ) 480 Average Exit Velocity (mph) 6.6 Volumetric Flowfrom EgressArea (ft 3/min) 278,784 Average Lead Concentration (pglm 3 ) 213 Source C Raw Material Storage Building Operations Source C = (VMT/year 

### * Control Factor 

### * lbNMT) 12000) 

### *Lead Content Lead Content of PMon Roadways(%): 26% Control Factor (efficiency%): 90% SourceD Furnace/Refining Building Operations SourceD = Volumetric Flowfrom EgressArea *Average Lead Concentration 

### *0.028317 I IOA6 

### *0.002205 Average Exit Velocity (mph) 6.6 Volumetric Flowfrom Egress Area (ft"1/hr) 10,740,000 Average Lead Concentration (pglm 3 ) 200 Haul Road 1 Delivery ofmaterial from breakerto main building Route I= [[k(sL)]A0.91x (W)Al.02 ](1-PI4N) Particle Size Multiplier (k): 0.011 Average Vehicle Weight (W) (tons): 10 Road Surface Silt Loading (sL) (gfmA2): 0.60 Days/Yearwith at least 0.01 inches of Precipitation (P): 120 Number of days in averagingperiod (N): 365 Haul Road 2 Delivery ofmaterial to Slag Treatment building Route 2 = [[k(sL)]A0.91 x (W)A 1.02 ](1-P/4N) Particle Size Multiplier (k): 0.011 Average Vehicle Weight (W) (tons): 6 RoadSuiface Silt Loading (sL) (gfmA2): 0.6 Days/Year with at least 0.01 inches of Precipitation (P): 120 Number of days in averagingperiod (N): 365 Pb Emission Rate lbs!hr tons/yr 0.057 0.12

lbs!hr tons/yr 0.22 0.19

lbs!hr tons/yr 0.0012 0.0054

lbs!hr tonslyr 0.17 0.76

lbs!hr tons/yr 0.010 0.044

lbs!hr tons/yr 0.0014 0.0061ATTACHMENT C FUGITIVE EMISSION ASSUMPTIONS Sanders Lead Company Haul Road 3 Delivery ofraw material to main building Route 3 = [[k(sL)y0.91x (W)AI.02 ](1-P/4N) Particle Size Multiplier (k): 0.011 Average Vehicle Weight (W) (tons): 10 RoadSurface Silt Loading (sL) (g/mA2): 0.6 Days/Year with at least 0.01 inches of Precipitation (P): 120 Number of days in averagingperiod (N): 365 Haul Road4 Delivery ofraw coke, limestone and scrap iron Route 4 = [[k(sL)y0.91x (W)AI.02 ](1-P/4N) Particle Size Multiplier (k): 0.011 Average Vehicle Weight (W) (tons): 15 Road Surface Silt Loading (sL) (g/mA2): 0.6 Days/Year with at least 0.01 inches of Precipitation (P): 120 Number of days in averagingperiod (N): 365 Haul Road 5 Delivery ofbatteries to Breaker Building Route 5 = [[k(sL)y0.91x (W)Al.02 ](1-P/4N) Particle Size Multiplier (k): 0.011 Average Vehicle Weight (W) (tons): 15 RoadSurface Silt Loading (sL) (g/mA2): 0.6 DayslY earwith at least 0.0I inches of Precipitation (P) : 120 Number of days in averagingperiod (N): 365 lbslhr tons/yr 0.00047 0.0020

1bslhr tonslyr 0.0029 0.013

1bslbr tons/yr 0.0052 0.023

### APPENDIXD Major ControlEquipmentInstallation Timeline

### Sanders Lead Company- Lead Control Schedule

SANDERS I..EAO April 24, 2012

COMPANY Tiln=IT TeD-12. I Mar-12 Apr-12 May-12 Jun-12 Jul-12 1 Aug-12 Sep-12 Oct-12 Nov-12 Dec-12 

## ""' 1Control System (New Fabric Filter and Ventilation System) Fabrication Installation Start up lAIIey Building Emission Control System

(New Fabric Filter and Ventilation System Design 

# ........... Fabrication Installation Start Up

. , Breaker Building Emission Control System (New Scrubber and Fabric Filter and Ventilation System Design Fabrication Installation Start Up Raw Material Building Emission Control System (New Filtration System [Filtered Exhaust Units or Baghouse]) Design Fabrication Installation Start Up Lead Emission Control Actions Relocate Industrial Battery Decasing Inside Enclose Production Buildings Improve Outside Watering Plan Enclose Baghouse Hoppers and Dust Handling Improve Process Flow/Minimize Outside Lead Traffic I I I I I l

### APPENDIXE 

### ModelingProtocolSANDER'S LEAD SIP MODELING PROTOCOL IN ACCORDANCE WITH ADEM PSD AIR QUALITY ANALYSIS AERMOD MODELING GUIDELINES (MAY2008)

July 28, 2011 Revision 1January 20, 2012



# Sanders Lead Company Troy, Alabama

1

000 Corporate Centre Drive Suite 250 Franklin, Tennessee 37067 (615) 771-2480 URS Project No. 20499427.00001;._,.,



# .... "" 1.0 INTRODUCTION 1.1 Background 

### Sanders Lead Company (Sanders Lead) has retained URS Corporation (URS) to prepare a modeling analysis for lead emissions released from their facility located in Troy Alabama. The purpose ofthis document is to present to the Alabama Department of Environmental Management (ADEM) a detailed protocol ofthe modeling procedures that will be used to conduct the air quality dispersion modeling analyses. The modeling procedures used to conduct analysis were based on recommendations given inthe ADEM PSD Air QualityAnalysis AERMOD Modeling Guidelines (May 2008). Also, modeling guidance contained in the U.S. EPA Guideline on Air Quality Models and the U.S. EPA New Source Review Workshop Manual will be followed when applicable. 1.2 Problem Def"mitiou 

### On September 30, 2009, ADEM provided EPA input regarding the extent ofpotential nonattainment areas in Alabama for the new Lead National Ambient Air Quality Standards (NAAQS). The monitoring data indicated that a small portion ofPike County, Alabamadid notmeet the new lead NAAQS. As a result ofthe NAAQS violation ofthe 2008 lead standards, EPA designated the area 0.8 miles surrounding Sanders Lead located in Troy, AL as "nonattainment" in the first round ofdesignations. It 

### should be noted that the EPA completed lead designations in two rounds. In 

### the first round, the EPA designated as "nonattainment" any area that violated the 2008 lead standards based on data from 2007-2009. The EPA took an additional year to make final designations decisions for all other areas ofthe country to allow additional lead air quality data to be collected and evaluated. In 

### the second round, the EPA designated those remaining areas as meeting or not meeting the 2008 lead standards based ondata from 2008-2010. Sanders Lead developing mitigation measures for achieving compliance with the new lead NAAQS, and anticipate that with the implementation ofthese measures that ambient lead concentrations in the area will be significantly reduced and the new lead NAAQS will be attained. 2.0 SITE DESCRIPTION 

### The Sanders Lead facility is located at 1 Sanders Road, in Troy, Alabama. As shown in Figure 1 (refer to Appendix A), Troyis located in southeastern Alabama, in Pike County. Troy is located 70 kilometers southeast ofMontgomery, Alabama. Figure I displays the plant site on a 7.5 minute USGS map along with a depiction ofcurrent company owned plant boundaries. The city population ofTroyis approximately 13,935. According to the United States Census Bureau, the city has a total area of26.3 square miles (68.2 

### km2), 

### of which, 26.2 square miles ofitis land and 0.1 square miles ofit (0.36%) is water.

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_Consulting\0l_Air\Pb Modeling\Protocol\Modeling Protocol_ Rev !.doc2.1 Site Characteristics 

### As shown in Figure 2 (refer to Appendix A), Troy is located in a gently rolling area of Alabama with no local topographic features which appreciably influence weather and climate. During the months of June through September, inclusive, temperature and humidity conditions generally show little change from day to day. During the coldest months, December, January, and February, there arc frequent shifts between mild and moist air from the GulfofMexico and dry, cool continental air. From late June through the first half of August, nearly all precipitation is from local, mostly afternoon, thunderstorms, and there are apt to be considerable differences in day-to-day amounts of rainfall in different parts ofthe Troy area. In late August and in September, summer conditions oftemperature and humidity persist as air continues to drift in from the Gulf, but local thunderstorms become less frequent because ofthe shortening ofthe days and the decrease in heat received from the sun. As this late summer season progresses, the local climate gives way to thunderstorms which occur with cold fronts and occasional general rains associated with storms on the Gulf. All types and intensities ofrain, except the local thunderstorms of summer, may occur at any time from December through March or early April. Floods in the rivers are correspondingly most frequent during this period. Most rain from late April through early June is in the form of showers or thunderstorms occurring in advance of approaching cool fronts, which become weaker and less frequent as summer approaches. It is during this spring season, and during the late summer and early autumn, that droughts sometimes occur. Snow in Troy is important only as a curiosity. Nearthe facility, terrainhas gentleundulations. The approximate UTM coordinates ofthe facility are NAD27 Zone 16, 596.744 km east and 3517.284 km north, at an elevation of approximately 160 meters above mean sea level. Based on area classification systems recognized byEPA, the facility is located in a rural section ofthe state. EPA guidance shows two alternative procedures to determine whether the character ofan area is predominately urban or rural: (1) land use typing or (2) population density. The area classification system as described byAuerintheJournal ofApplied Meteorology, Vol. 17, pg. 636-643, 1978, Correlation ofLand Use and Cover with Meteorological Anomalies, is frequently used to classify the area. URS used the new EPA AERSURFACE program to also confirm what the USGS maps indicated. That is the area surrounding the facility is largely rural in nature with greater than 50 percent ofthe area made up oftrees and vegetation. For the landuse analysis, URS used a 3 km distance to evaluate surface roughness. URS understands that for developing surface boundary layer parameters for AERMET processing (stage 3) a one kilometer distance is required. Results using a one kilometer radius have been presented in a recent landuse protocol submittal to the ADEM. Results from the 3-km analysis indicate that urban dispersion adjustments based on population will not be needed for the lead modeling submittal.

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_Consulting\0l_ Air\Pb Modeling\Protocol\Modeling Protocol_Rev l.doc3.0 MODEL SELECTION 3.1 AERMOD Overview 

### The American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) modeling system shall be employed for the proposed Sanders Lead modeling analysis. AERMOD is a steady-state line Gaussian plume model that considers the effects of nighttime planetary boundary layer effects and daytime convective activities. AERMOD has many features that make it the preferred model ofchoice for this particularmodeling exercise; such features include the capabilityto model point, area and volume sources; inclusion ofbuilding downwash ofeffluent; and most importantly, AERMOD was recently identified as the "preferred" model in the U.S. EPA Guideline on Air QualityModels. 4.0 MODELING INPUT 4.1 DispersionModel 

### The modeling analysis will be performed using the most current version of the EPA AERMOD model (version 9.84). Currently, AERMOD is the preferred computer dispersionmodel for conductingrefined dispersion modeling. The AERMOD model will be used to model the individual point, area and volume sources in order to predict maximum ambient lead concentrations from the facility. The modeling options that will beused include the following:

o 

### Calculation ofaverage concentrations for each applicable averaging period;

o 

### Non-Urban dispersion conditions;

o 

### Regulatorydefault options;

o 

### Final plumerise;

o 

### Stack-tip downwash;

o 

### Buoyancy-induced dispersion;

o 

### Calms processingroutine;

o 

### Default wind profile exponents;

o 

### Default vertical potential temperature gradients;

o 

### "UpperBound" values for supersquat buildings;

o 

### No exponential decay; and

o 

### Terrain included.
4.2 Meteorological Data 

### National Weather Service data from the regional airport located in Montgomery, Alabama will be used for the modeling analysis. As recommended by ADEM, NWS !- 

### minute meteorological data from 2006 through 2010 shall be processed for this attainment demonstration. In the following sections, Section 4.2.1 describes why the data is considered "representative" for the modeling analysis; and Section 4.2.2 describes the process used
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_Consulting\0I_ Air\Pb Modeling\Protocol\Modeling Protocol_Rev !.docto make the determination that the area surrounding the facility should be considered "rural". 4.2.1 Data Representativeness Prior to conducting the modeling analysis, it is essential that the Meteorological data be representative of the meteorological conditions at Sanders Lead. ADEM AERMOD Modeling Guidelines define representativeness as "constructing a realistic planetary boundary layer (PEL) similarity profiles and adequately characterizing the dispersive capacity ofthe atmosphere. As such, the determination ofrepresentativeness should include comparison of the surface characteristics, Bowen ratio and albedo, between the NWS measurement site andthe source location". Coincidentally, in August 2009, URS provided ADEM with a Landuse Protocol (August 2009) which evaluated the site "representativeness" between Montgomery airport and the Sanders Lead facility. Sanders Lead duplicated the AERMET processing for one year (2005) but used boundary layer parameters generated by AERSURFACE based on land use patterns around the facility. The first quarter or first three months, of 2005 was modeled in AERMOD using the two meteorological data sets to understand the relative importance of these changes in AERSURFACE processing to predicted ambient concentrations. The initial modeling results indicate there would be about a 22 percent change in predicted concentrations using the different data sets. Although both data sets produce the same location ofmaximum impact, URS will provide the air dispersion results for both surface characteristics (Montgomeryairport and Sanders Lead site). 4.2.2Al!.'R.SURFACELanduseAnalysisforAERMET One ofthe more important inputs to an air quality dispersion model is the meteorological data. The meteorological data will dictate where emitted compounds will be transported based on information such as wind speed, wind direction, ambient temperature, and atmospheric surface boundary layer parameters which help define atmospheric stability and mixing height development. The more meaningful the meteorological inputs, the greater the likelihood ofuseful results. Recognizing that not all locations have access to meteorological data, EPA developed methods whereby data obtained not at the site, but from another locale, could be used ifshown to be reasonably representative ofconditions at the modeling site. This test ofrepresentativeness has been described in EPA guidance (Guideline on Air Quality Models) (40 CFR 51 Appendix W) and AERMOD/AERMET implementation guidance, including the most recent version issued March 19, 2009. The test ofrepresentativeness was originally intended in the Guideline on Air QualityModels to include both a spatial and temporal component together with a suitability component. In the EPA Meteorological Monitoring Guidance for Regulatory Modeling Applications, representativeness has been defined as "the extent to which a set of measurements taken in a space-time domain reflects the actual conditions in the same or different space-time domain taken on a scale appropriatefor a specific application. " The meteorological monitoring guidance continues to say that "

..foruse in air quality modelingapplications, Page 4 ofll S:\2012\Sanders Lead\427

_Consulting\01._Air\Pb Modeling\Protocol\Modeling Protocol_ Rev !.docmeteorological data should be representative ofconditions affecting the transport and dispersion of pollutants in the area ofinterest as determined by the locations ofthe sources and receptors being modeled. " Establishing representativeness balances the requirements ofthe modeling assessment with the reasonableness ofmeteorological data acquisition. Due to the fact that surface characteristics for both the Montgomery airport as well as the Sanders Lead site, it is believed that URS will satisfy the requirements of data representativeness, as results from both data sets will used in the following air dispersionmodeling analyses. 4.2.3AERSURF ACELanduseAnalysis for Urban/Rural Selection The ADEM requires an Auer land use analysis which uses USGS maps to make a rural/urban determination. From this review it was apparent the area within a 3-km radius of the facility is rural using Aucr techniques. To confirm this conclusion, the AERSURFACE program was also used using a 3-kmradius and the land use distribution was calculated and plotted. The plot clearly shows the large amount ofvegetation in the area. EPA modeling guidance provided in the AERMOD Implementation Guide (January 9, 2008) and the Guidelines on Air Quality Models (Appendix W) indicate that a population density greater than 750 people per square kilometerdetermines whetherthe urban dispersion option is selected in AERMOD. An initial population density value based on 2009 census data for Troy, Alabama obtained from http:lien.wikipedia.orglwiki/Troy,_ Alabama indicates a**~opulation** density of 204.3 people/km2• Since the EPA trigger of 750 people/km value is not exceeded, urban AERMOD options will not selected. 4.3 Receptors A Cartesian grid system shall be implemented with a 100 meter spacing receptor grid, in addition, a 300m x 300m grid will be included around each monitor. The grid system was centered at a location that was in the middle of company owned property. All receptors included terrain heights generated from the AERMAP. AERMAP has been revised (beginningwith version 9.84) to support processing ofterrain elevations from the National Elevation Dataset (NED) developed by the U.S. Geological Survey (USGS, 2002) (http://scamless.usgs.gov/website/seamless/viewer.htm). An important component ofthe NED data is that it is being actively supported and checked for quality; therefore, NED represents a more up-to-date and improved resource for terrain elevations for use with AERMAP. The NED data used for this modeling exercise included the following domains: Troy, Ansley, Banks, Brundidge, Brundidge NW, Goshen, Needmore, Saco and Youngblood. 4.4 Lead Emission Sources at Facility Table 1 is a list ofthe current stack parameters for the lead point sources located at the facility, as well as the fugitive lead emission sources. All emission rates used in the modeling will be clearly identified inthemodelingreport when submitted.

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# ...



# - TABLE 1 - Source ofEmissions at Sanders Lead Source ID Type Description Stack 1 Point Blast Furnaces I, 2 and Reverberatory Furnace Stack 5 Point Blast Furnaces 3, 4 and Alloying Kettles Stack 4 Point Sanitary Baghouse for Furnaces I and 2 Stack 4a Point Sanitary Baghousefor Furnaces 3 and 4 Stack 10 Point SlagTreatment Building**~** Roadway 1 Volume Material from breaker to main building (Bld.2) Roadway2 Volume Material to Slag Treatment building Roadway 3 Volume Raw material (coke, limestone, scrap iron) to main building (Bld.2)

.. Roadway4 Volume Delivery ofraw coke, limestone and scrap iron RouteS Volume Delivery ofbatteries to Breaker Source A Volume Shredding and Separation Fugitive Source B Volume Decasing oflndustrial Batteries Source C Volume Raw Material Storage Building Operations SourceD Volume Furnace/Refining Building Operations
4.5 Off-Site Emissions Inventory 

### Since lead emissions from Sanders Lead are expected to produce the largest concentration gradients for lead in the area, the value of modeling very small contributions from other, more distant lead sources it very limited. Therefore, other "offsite" lead sources will notbe modeled unless the ADEM specifically identifies an off-site source inresponse to this modelingprotocol. 4.6 BackgroundAir Quality Data An 

### ambient background concentration for lead will be added to the maximum predicted concentrations from all modeled sources to determine a final maximum ambient concentration. ADEM has provided a representative background concentration, based on PM2.5 speciated data from the Montgomery airport monitor-based on the following protocol: UsingEPA ·sAir Quality System's (AQS) database, speciatedPM2.5 data specifically for lead was obtained for the years 2006-2010 and the last 2 months of 2005. The monitor used was the Montgomery site (01-101-1002) and the datafor this monitor was collectedevery 61 h day throughout theyear. This data was then usedto calculate monthly averagesfor the entireperiod. These monthly averages were then used to create 3-month rolling averages and from that the maximum 3-month rollingaverage for the entireperiodof data was determinedandsetas the background for lead. 

### Based on results from the speciated PM2.5 data, ADEM has determined that 0.009 uglm3 provides arepresentative background concentration ofleadfor the area.

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# -
"" 4.7 Good Engineering Practice Stack Height Analysis For point sources located at the facility, a good engineering practice (GEP) stack height evaluation was conducted to determine ifbuilding wake effects allow a point source to be modeled at a height greater than 65-meters. The GEP formula stack height is expressed as the greater of65 meters orGEP = Hb 

### + 1.5L (where Hb is the buildingheight, and Lis the lesser of the building's height or maximum projected width). The procedures followed guidance given in the EPA Guideline for Determination of Good Engineering Practice Stack Height (Technical Support Document for the Stack Height Regulations) Revised (EPA- 450/4-80-023R) and the User's Guide to the Building Profile Input Program. BEEST software was utilized to determine calculated GEP stack heights and to develop direction specificbuilding dimensions for use in the dispersion model. There are no stacks with a stack height greaterthan 65 meters. The building wake and downwash effect analysis was applied to each point source that released lead emissions. For each building, an area of wake and downwash effects extends outward to a distance offive times L (the lesser ofthe maximum projected width orheight ofthe building) directly downwind from the leeward sideofthe building. Wake effects were assumed to occur if the emission source was located within a rectangle composed oftwo lines perpendicular to the wind direction, one at 5L downwind ofthe building and the other at 2L upwind ofthe building, and by two lines parallel to the wind direction, each at 0.5L away from each side of the building. As the wind direction rotates, the wake and downwash effect region ofinfluence changes and is combined to form a GEP 5L region ofinfluence in all wind directions. Any emission source within the region ofinfluence can be affected by wake and downwash effects. For buildings close to an emission source, wake and downwash effects were considered where the distance between the emission source and the nearest part ofthe building is less than or equal to 5L. When an emission source height is less than the calculated GEP height and is located within the region ofinfluence, direction-specific building and dispersion parameters are required in the modeling analysis. The AERMOD model uses downwash and cavity equations developed by the Electric Power Research Institute (EPRI) and this methodology is referred to as the "Prime" method when the physical stack height is less than 1.5 times the height ofthe building causing the maximum GEP height. The prime equations reduce plumerise due to initial plume dilution, enhance plume spread. The GEP analysis was conducted using the Building Profile Input Program -Prime (BPIPPRIME) program to demonstrate compliancewith stack height regulations (40 CFR Part 51). 4.8 Quarterly Lead Concentration Calculation Procedure Since the dispersion model AERMOD does not provide the ability to directly compute the 3-month rolling averages, results must go through a post-processing procedure. EPA's "LEADPOST"program which is a FORTRAN program designed to read monthly concentrations output from AERMOD and calculate the maximum rolling 3-month
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### average concentration for each receptor and overall maximum concentration (across all receptors and source groups). 5.0 REASONABLY AVAILABLE CONTROL TECHNOLOGY 

### EPA defines Reasonably Available Control Technology (RACD as the lowest emission limitation that a particular source can meet by the application ofcontrol technology that is reasonably available considering technological and economic feasibility. The technology feasibility of applying an emission reduction method to a particular source considers the source's process and operating procedures, raw materials, and physical plant layout. The following items were considered when determining the control technologyto apply: 1. The process, operating procedures, and raw materials used by the source can affect the feasibility ofcarrying out process changes that reduce emissions and the selection ofadd-on emission control equipment. 2. The operation of and longevity of control equipment can be significantly influenced bytheraw materials used and the process to whichit is applied. 3. The feasibility of modifYing processes or applying control equipment is also influencedbythephysical layout ofa particularplant. 4. The space available in which to carry out such changes may limit the choices of control. 5. Determinations oftechnological feasibility also consider adverse impacts on other resources. Ifa control technology increases pollution ofbodies ofwater, creates additional solid waste disposal, or exacerbates worker exposure problems; the technologymaynot be considered reasonably available. The implementation of RACT by the Sanders Lead facility provides enforceable and permanent emissions reductions needed to attain and maintain the lead NAAQS at this time. The following information details the currently anticipated measures to be employed, as well as a brief explanation of the control measures. Sanders Lead has developed a detailed "Lead Compliance Implementation Schedule" which details the installation timeline of the proposed measures in order to meet the implementation deadline.

Page 8 ofll S:\2012\Sanders Lead\427

_Consulting\0l_ Air\Pb Modeling\Protocol\Modeling Protocol_Rev !.docDescription of Measure
Enclose Baghouse Hoppers and Transport ofDust

Control and Enclose Furnace Operations

Control and Enclose Refining Operations

Relocate Industrial Battery Decasing and Enclose Raw Material Handling Operations

Improve Process Transport to Eliminate OutdoorTraffic Material Leaded Explanation
Sanders Lead is proposing to enclose the base ofbaghouses #I and #5, including the access doors and removable panels on the units. Ventilation will be provided by dueling to existingbaghouses. Sanders Lead is proposing to install canopy hoods over each blast furnace with supply air to reduce worker lead exposures. A new hood will be installed over the reverb feed hopper. Additionally, the furnace building will be enclosed. A new approximately 318,000 CFM baghouse will be installed to control emissions captured by the new hoods andbuilding enclosure. Sanders Lead is proposing to enclose the refining building, including the elimination ofsidewall fans. As part ofenclosing the refining building, fast acting rollup doors will be installed. Area ventilation will be provided by negative on building provided by the additional baghouse capacity. Sanders Lead is proposing to relocate the industrial battery decasing operations to the inside of the existing raw material storage building. A new raw material receiving dock will also be constructed to connect with the east side of the raw material building. Sanders Lead is also proposing to install an enclosed vehicle washing system which will enclose the vehicle entrance to and from the storagebuilding. Fast acting rollup doors will also be installed at the raw material storage building. In order to eliminate leaded outdoor traffic, Sanders Lead is proposing to enclose the shredder building and the transport of group to shredder from raw material storage building. Sanders Lead is also proposing to enclose the collection and handling of water and lead runofffrom the shredder group pile. Sanders Lead is proposing the install transferpoints at the refining, Relocate and Contain Leaded smelting and raw material storage vehicle exits to maintain Vehicle Maintenance "leaded" vehicles inside the building. Sanders Lead is proposing to relocate leaded vehicle maintenance to a newly enclosed constructed area. Improved Watering Sanders Lead is proposing to develop an updated watering plan based on the new vehicle patterns and facility layout. The wateringplan will include an improved floor wetting system inside and outside the building, as well as purchasing new wet sweepers for the outside buildings.
6.0 CONTINGENCY MEASURES 

### Pursuant to Section 172 ofthe CAA, a set ofcontingency measures has been prepared that could be implemented ifrequired by a finding ofthe EPA Regional Administrator that a) the nonattainment area has failed to make Reasonable Further Progress (RFP), b) there is a failure to implement a control strategy to attain the NAAQS by the statutory Page 9 oflt S:\20 12\Sanders Lead\427

_Consulting\0I_Air\Pb Modeling\Protocol\Modeling Protocol_Rev l.doc

# ... deadline, or c) monitoring shows that the nonattainmcnt area has failed to attain the NAAQS bythe statutory deadline. 7.0 SUBMITTAL INFORMATION The Air Quality Impact analysis will include the following information as recommended bythe ADEM: 1) Description of model used and any special assumptions or options employed. Justification will be included for any usc of non-regulatory options. The BEEST proprietary software will beused to facilitate data input and process output. 2) Description of the meteorological input data used, with an explanation of any modification(s) will be provided. 3) A detailed analysis to demonstrate that the surface characteristics in the vicinity ofthe meteorological collection site (furnished by ADEM) arc representative of the surface characteristics in the vicinity ofthe facility. This information has bepreviously submitted and approved in a separate Landuseprotocol. 4) Overall description of the methodology used in performing the analysis. This will include all steps necessary for identifying the maximum ambient lead impact values and could beused for comparison with and ambient air quality standards ifneeded. 5) Tables identifying the maximum ambient levels (including receptor locations and year ofmeteorology) for quarterly averaging periods including the contribution ofthe facility to the maxima. 6) Figures of isopleths that illustrate the aerial extent of ambient levels. Location of maximum predicted concentrations will be clearly noted for comparison to the air quality standard for lead as needed. Figures will have a background illustrating terrain or other identifiable features, such as a U.S.G.S. Map, for easyorientation. 7) Appropriate model output files substantiating points ofconcern, as described in the text, will be submitted. 8) Source input parameters for all sources modeled will be reported. 9) Identification ofthe meteorologyused will be described. 1

0) List ofoptions used in the particularmodel run will be provided. II) Concentration tables for the "rolling" quarterly averaging period will bereported. 12) List ofoptions used in the particularmodel run will be provided.

Page 10 ofll S:\2012\Sandcrs Lead\427

_Consulting\0l_Air\Pb Modeling\Protocol\Modeling Protocol_Rev !.doc13) All modeling results will be submitted electronically and include all model input and output files from the AERMOD, AERMAP, AERMET programs and input/output files from utilitypreprocessors such as AERSURFACE, BPIP and LEADPOST. Sanders Lead requestthat these modeling procedures be approved so modeling canbegin. Sander Lead looks forward to working with the ADEM on this important modeling study. Please contact Mr. Steve Lund at (919) 461-1361 (steve _1und@URSCorp.com) on any technical modeling issues or Mr. Billy Nichols at (615) 224-2135 (Billy_Nichols@URSCorp.com) withrespect to facility operations and emissions.

Page 11 ofll S:\2012\Sanders Lead\427

_Consulting\01_Air\Pb Modeling\Protocol\Modeling Protocol_Rev !.doc

# APPENDIX A

# \ \\ \1· GEOLOGICAL SURVEY



# -.**,-.!.~** <,

## ..

-**-;.,t;;_,~·** 1 ,',,



## •

Sander's Lead Company, Inc. Troy, Alabama

### ~ Fnmldln,T..,._• JMB Date: eJZ0/11 BRN Date· 6120111 Project No. 20499427

FIGURE:

2

### APPENDIXF 

### HaulRoad Workgroup FinalReportUNITED STATES ENVIRONMENTAL PROTECnON AGENCY RESEARCH TRIANGLE PARK, NC 2n11


### March 2, 2012

MEMORANDUM 

### SUBJECT: Haul Road WorkgroupFinal Report Submissionto EPA-OAQPS FROM: TylerFox,

# Leader---(""~

# J'--=lf.- Air Quality Modeling Group, C439-0l TO: Regional OfficeModelingContacts OFFICE OF AIR QUALITY PLANNING

AND STANDARDS



### The challenge ofmodelingthe emissionsand 

### associated air

### quality impacts ofhaul roads has 

### been aparticularlyvexingproblem forthe dispersion modeling community. There is a large degree ofuncertainty inthe magnitude 

### ofthese fugitive dust emissions and subsequentlyinthe modeled estimates at near-sourcereceptor locations. Atthe 2009 Regional, State, and 

### Local Modelers' Workshop, EPA held an interactive session on bestmodeling practices ofbaulroads tbatwas 

### chaired by 

### Randy Robinson, USEPA Region

### 5, and 

### Mick Daye, USEPA Region 7to open up aconstructive dialogthroughoutthe regulatory dispersion modeling community onthe challenges ofcharacterizing and appropriately addressing the baul road fugitive emissions in a compliance demonstrationproject. Following this 2009 Workshop, the Haul Road Workgroup was 

### formed with acollectionoffederal, state, and 

### local governmentdispersion modelers. The goal ofthisWorkgroup wasto examine and

### betterunderstandhaul road characterizationissues and recommend amodeling methodologybacktothe 

### broaderdispersion modeling community. The Workgroupdecided to focus on the air

### quality modelingaspects and notaddress 

### the fugitive dust emissions factorissues. Areport outofthe Haul Road 

### Workgroup was 

### presented at the 

### 2010 Regional, State, and Local 

### Modelers' Workshop. Along withdiscussion amongstthe regulatory dispersionmodelers inattendance atthe2010Workshop, feedback and 

### comments were 

### solicited and accepted 

### on the 

### recommendations ofthe Workgroupthroughout 2010 and

### the first

### halfof2011. An

### update presentation on the Workgroup was given atthe 2011 Regional, State, and Local

### Modelers' Workshop with the 

### subsequentrelease ofa draft

### version ofthe 

### Haul Road Workgroup Final Report during the fall of2011.

### Attached to 

### this letter is the Haul Road Workgroup Final Reportthat

### provides a "best 

### practices guide" for modeling ofhaul road fugitive emissions in the AERMOD modeling system. This final report 

### is being shared withthe entire dispersion modeling communitypriorto the lOth Conference on AirQuality Models to promotebroaderconsideration and

### facilitate further comment. Please sendthis

### report to 

### yourstate, local and tribal agency modelers so thatthey can providereview and

### comment, as appropriate. The recommendations presented arenot an endorsement bythe 

### USEPA as the definitivemethodologyfor characterizing and addressing fugitive dustemissions from haul roads but shouldbe considereda best

### practice approach based onthe

### broadinvolvementofthe co-regulating community inthe 

### developmentofthis recommendation. We would liketo

### give special recognitiontothe 

### initiative and labors ofRandy

### Robinson andMick

### Daye in spearheadingthis initiative in 2009, chairingthe Haul 

### Road Workgroup, and developingthis

### final report. 

### We would also like to 

### thankall 

### ofthe 

### federal, 

### state, and local governmentdispersion modelers that 

### participated inthe 

### Workgroup and

### assisted inthe drafting ofthe

### final reportpresented in

### theattachment.

Attachment: Robinson and Daye December6, 201l memorandum withHaul Roads Workgroup Final Report included as an attached documentUNITED STATII**E~AL** PROTECTION AGENCY REGIONS 77WESTJACKSON BOUI..EVARD CHICAGO, IU!OII04-35110

IIEPLY TOTH!ATli!NTIOifOf': 

# MEMORANDUM SUBJECT: 

### FROM:
TO: Haul Road WorkgroupFinal Report

- /1**·~** 

### Randy Robinson. EPA

# Region~ ,. 

# ·.Fl. Jt' 

### MickDaye,BPARegion7

### ~£'**~** TylerFox. Leader,

### AirQualityModelingGroup George 

### Bridgers.ClearinghouseCoordinator,AirQuality

### Modeling Group

The

### pmposeofIbis memorandumis to

### tnmsmit

### the attachedbaul road

### modelingfinal report tothe

### AirQualityModeling

### Group. 

### The reportrepresents thecollectiveefforts of

### the 

### Haul Road Workgroup, which

### was formed 

### following abc

### 2009 Regional/StateJI..ocal Modeling Workshop. Theptupose

### of

### the

### wodcgroupwas to

### identifyaDd

### recommend aleclmically supportableapproach

### for modelinghaul road

### re-entiaineddust The

### attached document

### cOntaim a summary

### of

### the possibleoptionsfor

### Inodelingfugitive· road

### dust. a description

### oftheSCII5itivity modeling

### cooduNcd by

### lhe 

### workgroup. and

### a tiered set 

### ofrecommendatiODS 

### formodelinghaul rood 

### fugitiveemissions. The

### otherattachmentrontains 

### se.lected slides fromtbe haul road

### presentation atthe 2010

### Regional/StateJLocal

### modeling workshop. The

### Workgroup requests 

### AirQuality

### ModelingGroup review and distribution

### ofthe 

### recommendations docmnent to

### themodeling

### community. Thank }'OU and

### please contad

### ua ifyou 

### bave 

### any questions orrequire 

### additional infonnation.

## Haul Road Workgroup Recommendations November2011 Workgroup ChargeThe Haul Road Workgroup wasformally established shortly afterthe May 2009 RegionaVState/Local Workshop. Thepurpose ofthe workgroup is to identify and recommend a technically supportable approach formodelinghaul road re-entrained dust. Whileemission factors are a critical partofany roadway modeling exercise, this workgroupfeltthatemissions were outside our scope and did not engage in a review or evaluation ofavailable fugitive dustemission factors. Based onmodeling workand field study/journal article review, the following represents a recommendation for an approach to characterizing haul road fugitive emissions in AERMOD. SourceCharacterization

- The model to be used for modeling haul road fugitive dust emissions is AERMOD. There are several ways haul road fugitive dustemissions can be characterized in AERMOD, including area source, volume source, and series ofpoint sources. A line source algorithm is beingdeveloped but is notcurrently available. Each approachhasadvantages and disadvantages. The workgroup has considered each approach and a summary ofthe strengths andweaknesses is presentedbelow. Area source advantages:

• Can place receptors in ambientaircontained within the area source • Easyto replicate dimensions ofroadway in X and Y coordinates • Avoidstheneedto determine SigmaY values (Sigma Z valuesare optional) • Can utilize a Sigma Z value ifdesired, to reflect an initial, well-mixedplume • Area sources explicitly simulate a uniform emission density acrossthe roadway, which maybemore realistic in somerespects than otherapproaches. Area source disadvantages:

• Area source in AERMOD doesnot have the meander algorithm • Run times are generally longerthan other approaches Volume source advantages:

• Volume source in AERMOD contains meander algorithm • Conceptually, a volume source mimics an initial, well-mixed plume • Potentially faster run timethan area source'-IIIH! Volume source disadvantages:

• Concentrations arenotcalculated in a volume source exclusion zone o Exclusion zone is the region ( (2.I5 x Sigma Y) 

### + I meter)) from the centerofthe volume. Point Sourcewith downwash advantages:

• Precludesthe needto establish Sigmavalues; handled internally by downwash • Conceptually, consistentwith well-mixed plume • Can place receptors anywhere within roadway • Can be used for buildings nearroadways Point source with downwash disadvantages:

• Downwash algorithm in AERMOD does not contain meanderfor receptors within the wake • Technique would be newto modeling community • Additional assumptions required, includingbuilding (truck) size, stacktemp, velocity, height. • Potential issueswith BPIP used in thistechnique 

### Sensitivity analysis Early in theprocess, the workgroup conducted an AERMOD sensitivity analysisto examinechanges in haul road characterization inputs using volume and area source techniques. Limited, preliminarypoint sourcetechnique sensitivity runs were also conducted. Details ofthe sensitivity analyses are available at http://www.cleanairinfo.corn/regionalstatelocalmodelingworkshop/archive/20I0/Docume nts/Presentations/RSL20I0 HauiRoads.pdf. Thefollowing summarizes the setup and general conclusions. Analysis setup:

• Used AERMOD Version 09292 • I year ofmeteorological data (variety oflocations) • N-S andE-W crisscrossing road segments. Each 500m long, IOm wide. • FlatTerrain • Receptor Grids

- Cartesian and Polar; beginning as nearas possible tothe volume sources. I meter from edge ofarea source. No receptors within source. • Unit emission rate • Evaluated range ofvaluesfor top ofplumeheight, SigmaZ, Sigma Y, and release height. • Modeled using AdjacentVolume, Alternate Volume, andArea source representations. 2• Calculated results for annual ave, peak 1-hr, 8th H 1-hr, peak 24-hr, 8th H 24-hr • Point source modeling examined single vs multiple stacks and varying stack parameters.
General Conclusions:

• Increasing release height (and related Sigma Z) led to lower concentrations. • Increasing Sigma Y for alternate and adjacentvolume sources lowered concentrations. • For area source- increasingX dimension lowered concentrations at lowerrelease heights (i.e., Om and 0.5m). It had little impact at higher release heights (i.e, l.Sm and 3m). • Forarea source- adding a Sigma Z lowered concentrations for surface release heights, but generally increased concentrations athigherrelease heights • Forvolume runs, adjacent giveshigherconcentrationsthan alternate. • Point Source- limited, preliminary modeling shows some sensitivityto stack height and velocity • On-sitemeteorological data model runs showed sametrends as with National Weather Service data, although concentrations were higher with on-sitedata.


### Model/Monitor Comparison The workgroup was interested in locating field datato facilitate ourreview ofhaul road dispersion characteristics. Finding field data relevanttoourtaskwas difficult. While there are numerous field studies relevantto haul roads, thevast majority deal with monitoring designed to evaluate haul road emissionsratherthan dispersion characteristics. An evaluation conducted byOAQPS in 2006 examined haul road emissions from the Cordero Rojo Mine in Eastern Wyoming. The modeling looked at volume and area source configurations in AERMOD. The study, while limited, showed volume source characterizationsperforming slightly betterthan area source when compared tomonitored PM1 0 data. The analysis wasprimarily designedto examinethe impact ofthe meander algorithms. This is significant becausethe volume source approach incorporates meanderwhilethe area source approach does not. The difference in modelperformance was attributed to area source over-estimates due to lack of meanderupwind dispersion. Details ofthe Cordero Rojo Mine evaluation results can be found athttp://www.awma.org/events/confs/AQMODELS06/Session%204/4- Roger"/o20Brode.odf.



### 3

### HaulRoad Recommendations Definitions Duringtheworkgroup discussions and sensitivity modeling work, the following definitions were used; "VH"means vehicle height [-3m fortypical haul trucks; -10m for large mining trucks] "VW"meansvehicle width [-3m fortypical haultrucks; -10m for large miningtrucks] "VL"means vehicle length [-lOrn fortypical haul trucks; -20m for large miningtrucks] These definitions and associated dimensions were useful to the group as we discussed the various methods and developed the inputsto be used inthe sensitivity modeling. They shouldnot be treated as defaultvalues and/orused inplace ofsite specific dimensions available for individual modelingdemonstrations. 

### GeneralRecommendation Thefollowing represents a general recommendation for modelingofhaul road emissions. Therecommendation is notmeanttobeprescriptive; local conditions and specific information may leadto an alternative approach. However, the workgroup feels thatthe recommendation presentedbelow is reasonable, canbetechnically supported, and provides a level ofconservativenessgiventhe large amountofuncertainty associated withcharacterizingand simulatingdispersion offugitive emissionsresultingfrom haul roadtraffic. Concentrations mustbe calculated in areasthat areconsidered ambientair. 1



### • Volume Source- Recommend for all haul roads,except for cases where ambient airreceptors arewithin thevolume's exclusion zone (i.e., ( (2.15 

### x SigmaY)

### + I meter)) from the centerofthevolume.

Rationale: Volume source containsthe meander algorithm. Conceptually fits thephysical parameters associated with well-mixedplume. Limited model/monitorcomparison study information supports volume source Recommended Volume Source Configuration:

o Adjacent Volume Source

1Ambient Air is defined at40 CFRPart 50.1(e) and further clarified in aDecember 19, 1980 from Douglas Costleto SenatorJennings Randolph. See http://www.epa.gov/scram001/guidance/mch/ama4.txt 4o Top ofPlume Height2

- 1.7 x VH o Volume Source Release Height- 0.5 x Top ofPlume height o Width ofPlume- VW + 6m for single lane roadways IRoad Width+ 6m for two lane roadways3

. o Initial Sigma Z- Top ofPlume/2.15 AERMOD User's Guide, Table 3-1 for use when modeling multiple volumes. o Initial Sigma Y- Width ofPlume /2.15 AERMOD User's Guide, Table 3-1 o Emissions input as g/s

• The I.7 factor in the Top ofPlume Height equation above is supported by information in a 2005 Atmospheric Environment paperby Gillies, et. al, entitled Effect ofVehicle Characteristics on Unpaved Road Dust Emissions. • The Width ofPlumevalue is based on a conservative adaptation ofmonitor placement guidance from EPA's 1992 document, Guideline for Modeling Carbon Monoxide from Roadway Intersections. In that document, it is recommended that monitors not be placed nearerthan 3 meters from the roadway edgeto account for vehicle turbulence. Two-lane roadways are for cases with heavy two-way traffic where the combinedplumeneedsto be approximated. Agencies mayneed to considertraffic counts, vehicle width, road width, and the amount oftwo-way traffic, in orderto determine whetherthe roadway is best represented using single-laneor two-lane assumptions. While the workgroup's sensitivity analysis indicates increased volume source width leadsto decreased concentrations, our group didn't specificallyexamine single-lane versus two-lane roadways. One option is to model two-laneroadways astwo, single-lanevolume sources. • Forcases where ambientairreceptors fall within the volume source exclusion zone, a conservativevolume source approach would betoreduce the width ofplume dimensions enough sothattheambient airreceptors are not insidethe exclusion zone. Additionally, a mixofarea sources and volume sources may adequately allowfor consideration ofall ambient airreceptors. Area 

### Source- Recommended for haul roadswhereambientairreceptors are locatedwithin sourcedimensions. Rationale: Volume source doesn't allowplacement ofreceptors within exclusion zone. Area source can calculate concentrations atreceptors within source. Area source can simulate volume source with use ofsimilar release height and SigmaZ parameters.

2 Gillies, J.A., V. Etyemezian, H. Kuhns, D. Nikolic, D.A. Gillcte, 2005. EffectofVehicle Characteristics onUnpaved Road DustEmissions. Atmospheric Environment, 39, 2341-2347 3 EPA. 1992. Guideline forModeling Carbon Monoxide From Roadway Intersections. EPA-454/R-92- 005. http://www.epa.gov/scramOOI/guidance/guide/coguide.pdf 5Recommended Area Source Configuration

o Length

- length ofroadway segment (Aspectratio in AERMOD extended to 100:1 before warning is issued. See Model Change Bulletin #3, Miscellaneous item#10) o Width- VW

### + 6m for single lane IRoad Width

### + 6m for two-lane (same comment asfor volume, two single-lanes is an option) o Top ofplume height -1.7x VH o Release height- 0.5 x top ofplume height o Sigma Z- Top ofPlume height I 2.15 o Emissions input as 

### glslm2 

### Point Source- Theworkgroup is notforwarding any point sourcerecommendation atthis time. Thereare potential benefits to this approach, however, more study is needed.


### FutureEfforts The workgroup understands that efforts are underway on a line source algorithm to be included in AERMOD. The time frame for completionofthisworkmay be within the nextcoupleyears. A new line source algorithm would likely supplantthe need to model haul road fugitive dust emissions using eithervolume, area, orpoint sources. Point source modeling offugitive roadway emissions has somepotential benefits, as noted earlier in this paper. One example is the abilityto considerthe influence offacility structures located nearroadways when simulatingthe roadway fugitive dust in AERMOD. TheHaul Road Workgroup supports further study ofthis approach. More field studies examining initial plume dimensions are encouraged. Theeffects of vehicle speed on the initial plume dimensions is an area that should be investigated when, orif, more field studies are conducted.

6

### References Brode, R.W., Improved Algorithms for Modeling Impacts NearRoadways. MACTEC Federal Programs, Inc. A&WMA Specialty Conference, Denver, CO, Apri12006 EPA. 1992. Guideline for Modeling Carbon Monoxide From Roadway Intersections. EP A-454/R-92-005. http://www.epa.gov/scramOO!/guidance/ guide/coguide.pdf EPA. 1994. ModelingFugitive Dust Impacts from Surface Coal Mining OperationsPhase II. EPA-454/R-94-025 Eskridge, R. E., Thompson,R.S., 1982, Experimental and Theoretical Study ofthe Wake ofa Block-Shaped Vehicle in a Shear-Free BoundaryFlow. Atmospheric Environment, 16, 2821-2836 Fitz, D. R., 2001. Measurements ofPMIO and PM2.5 Emission Factors from Paved Roads in California. ContractNo. 98-723. California Air Resources Board, Monitoring and Laboratory Division Gillies, J.A., V. Etyemezian, H. Kuhns, D. Nikolic, D.A. Gillete, 2005. EffectofVehicle Characteristics on Unpaved Road DustEmissions. Atmospheric Environment, 39, 2341- 2347. Guideline on Air Quality Models, US Environmental Protection Agency, 40 CFRPart 51, Appendix W,November9, 2005.
Heinerikson, A., Goodman, A., Anderson, K., Analysis ofHaul road Emission TestData for DeterminingDispersionModeling Parameters. Trinity Consultants. Reed, W. R., Performance Evaluation ofa Dust-dispersion Model for Haul Trucks. National Institute for Occupational Safety and Health, Pittsburgh Research Lab. User's Guide for the AMS/EPA Regulatory Model- AERMOD, US Environmental ProtectionAgency, EPA-454/B-03-001, September2004. Westbrook, J.A., Sullivan, P.S., Fugitive Dust Modeling with AERMOD forPMIO Emissions from a Municipal Waste Landfill. Williams, D.S., Manoj, K.S., Ross, J., Particulate MatterEmission bya Vehicle Running on Unpaved Road. 2008. Atmospheric Environment, 42, 3899-3905.

7

### Select Slides from May 2010 RegionaVState/Local Workshop Presentation 

# SensitivityAnalysis Work

11 

### UsedAERMOD Version 09292
1111 

### 1year of meteorological data (variety of locations) 11 

### N-S and E-Wcrisscrossing road segments. Each 500m long, 10mwide. 11 

### Flat Terrain 11 

### Receptor Grids
- Cartesian and Polar; beginning as near as possible to the volume sources. 1 meterfrom edge ofarea source. No receptors within source.



# Cont.

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### Unit emission rate 11 

### Evaluated range ofvalues fortop ofplume height, Sigma Z, Sigma Y, and release height.
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### Modeled using Adjacent Volume, Alternate Volume, and Area source representations. 11 

### Calculated results for annual ave, peak 1hr, 8th H 1hr, peak 24hr, 8th H 24hr,

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13 

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### Vel. - 0.001

c

....... 7m Topot Plune/111m Pluna Wdlh 8th**H~Uhou'**Ave.

11 

# - - .. 

# - - ,. ,. ,. ,. ,.



# -

# -

- General Conclusions for SensitivityAnalysisRuns

ill 

### lnaeasing RH (release height)always led

### to lower concentrations. ill 

### Increasing SigmaYforalt. andadj. volume sources loweredconcentrations.

1111 

### Forarea source- increasingXdimension lowered concentrations atO and0.5 RH, at 1.5 and3m RH, hadlittle impacton concentrations.

1111 

### Forarea source- addinga sigmaz lowered concentrationsforO RHs, but usuallyincreased concentrationsat 1.5and3.5 RHs, mixed results for 0.5mRH.



# Cont.

11 

### Forvolumeruns, adjacentgiveshigher concentrationsthan alternate. 11 

### PointSource-limited modelingshows sensitivitytostackheight; little sensitivity

### to stackdiameter. 11 

### On-sitemetdata runs showedsametrends asNWS, althoughconcentrations higherwith on-site.

12

### APPENDIXG Protocol to Support the use of AirportMeteorologicalData For Sanders LeadModeling

### Protocol to Support the use ofAirport Meteorological Data For Sanders Lead Modeling One ofthe more important inputs to an air quality dispersion model is the meteorological data. The meteorological data will dictate where emitted compounds will be transported based on information such as wind speed, wind direction, ambient temperature, and atmospheric surface boundary layer parameters which help define atmospheric stability and mixing height development. The more meaningful the meteorological inputs, the greater the likelihood ofuseful results. Recognizing that not all locations have access to meteorological data, EPA developed methods whereby data obtained not at the site, but from another locale, could be used if shown to be reasonably representative ofconditions at the modeling site. This test ofrepresentativeness has been described in EPA guidance (Guideline on Air Quality Models) (40 CFR 51 Appendix W) and AERMOD/AERMET implementation guidance, including the most recent version issued March 19, 2009. The test of representativeness was originally intended in the Guideline on Air Quality Models to include both a spatial and temporal component together with a suitability component. In the EPA Meteorological Monitoring Guidance for Regulatory Modeling Applications, representativeness has been defined as "the extent to which a set ofmeasurements taken in a space-time domain reflects the actual conditions in the same or different space-time domain taken on a scale appropriate for a specific application." The meteorological monitoring guidance continues to say that "

...for use in air quality modeling applications, meteorological data should be representative ofconditions affecting the transport and dispersion ofpollutants in the area ofinterest as determined by the locations ofthe sources and receptors being modeled." Establishing representativeness balances the requirements ofthe modeling assessment with the reasonableness of meteorological data acquisition. Because ADEM modeling guidance recommends meteorological data from the Montgomery Airport for sources located in Pike County, Alabama, it is assumed the data has previously undergone a "representativeness" review by ADEM. This ADEM review may have included a review ofmany similarities between a source located in a modeled county and the nearby airport. The similarities tests would have included potential effects ofterrain on regional flow patterns between the two sites and changes in climatology between the two areas. Because the Sanders Lead facility and Airport are both located in an area ofrelatively simple terrain, no major changes in regional air flow would be expected. Also, since the Airport and plant site are both located in the East GulfCoastal Plain region, only small changes in climatology qnd other weather related factors would be expected therefore the space-time domain factors should be representative. Localized differences in some surface boundary layer parameters (i.e., albedo, Bowen ratio, and surface roughness) between the two sites would be expected but not to a degree that would exceed changes in predicted concentrations often noted fromjustusing different years of meteorological data.Based on the presumed suitability ofthe meteorological data for sources located nearthe Montgomery Regional Airport, the ADEM processed the data using AERMET (version 06341) along with upper air data from Alabaster, Alabama, to form a 5-year meteorological record (2001-2005). The data was processed using geophysical surface parameters associated with the airport. This information was developed by using the AERSURFACE program which generates surface boundary layer parameters in the form ofalbedo, Bowen ratio, and surface roughness. For this protocol, Sanders Lead duplicated the AERMET processing for one year (2005) but used boundary layer parameters generated by AERSURFACE based on land use patterns around the facility. The first quarter or first three months, of2005 were modeled in AERMOD using the two meteorological data sets to understand the relative importance ofthe chances in AERSURFACE processing to predicted ambient concentrations. For this analysis, only point sources were evaluated. Emission rates used in this initial evaluation were based on current allowable emission estimates. These may or may not be a good estimate of "actual" potential emission rates from the facility. Actual emissions rates are under review, at this time. Using the allowable rates supplied a basis for conducting the modeling only. No actual concentration estimates are reported. Results are presented on a "relative" basis in the form ofconcentration isopleths. The initial modeling results indicate there would be about a 22 percent change in predicted concentrations using the different data sets. However, the location ofmaximum impact remains the same. The meteorological data with "site" geophysical surface parameters causes the higher predicted concentrations. This is understandable given the large changes in surface roughness between the airport and the plant site (see Table l and Figures l thru 4). It would be expected that elevated plumes would experience greater instability with greater surface roughness and therefore cause higher impacts near the plant site. Figure 5 displays the location ofmaximum impacts for the Ist quarter of2005. Both datasets produce highest values at the fence line and at the same receptor location. Table 1compares the differences in the boundary layer parameters at the airport and plant site. The information has been broken down into 12 sectors and 4 seasons. A strong indication ofthe representativeness ofdata collected at the airport for modeling the plant site is the relatively small change in predicted impacts from the AERMOD model using the two meteorological data sets. The airport data is considered "representative" since the location ofmaximum impacts are the same and a 22 percent change in predicted concentrations would be a reasonable variation frequently seen in year to year variation over long-term averaging periods when modeling. As recommended by the ADEM, both AERSURFACE data sets will be used for future modeling and the data set producing the highest predicted concentrations will be reported. This is a conservative modeling assumption.I

Table 1 AERSURFACE Processing Bowen Bowen Surface Surface

Surface Albedo Albedo Ratio Ratio Roughness Roughness Geophysical Season Airport Sanders Airport Sanders Airport Sanders Lead Lead Lead Parameters Sector I I 0.17 0.15 0.71 0.81 0.095 0.256 2 I 0.17 0.15 0.71 0.81 0.055 0.322 3 1 0.17 0.15 0.71 0.81 0.031 0.238 4 I 0.17 0.15 0.71 0.81 0.019 0.445 5 I 0.17 0.15 0.71 0.81 0.019 0.508 6 I 0.17 0.15 0.71 0.81 0.041 0.186 7 I 0.17 0.15 0.71 0.81 0.021 0.158 8 1 0.17 0.15 0.71 0.81 0.018 0.201 9 I 0.17 0.15 0.71 0.81 0.015 0.503 10 1 0.17 0.15 0.71 0.81 0.024 0.532 II 1 0.17 0.15 0.71 0.81 0.039 0.199 12 I 0.17 0.15 0.71 0.81 0.071 0.139 1 2 0.17 0.15 0.71 0.81 0.095 0.256 2 2 0.17 0.15 0.71 0.81 0.055 0.322 3 2 0.17 0.15 0.71 0.81 0.031 0.238 4 2 0.17 0.15 0.71 0.81 0.019 0.445 5 2 0.17 0.15 0.71 0.81 0.019 0.508 6 2 0.17 0.15 0.71 0.81 0.041 0.186 7 2 0.17 0.15 0.71 0.81 0.021 0.158 8 2 0.17 0.15 0.71 0.81 0.018 0.201 9 2 0.17 0.15 0.71 0.81 0.015 0.503 10 2 0.17 0.15 0.71 0.81 0.024 0.532 11 2 0.17 0.15 0.71 0.81 0.039 0.199 12 2 0.17 0.15 0.71 0.81 0.071 0.139 I 3 0.14 0.14 0.38 0.56 0.114 0.324 2 3 0.14 0.14 0.38 0.56 0.066 0.404 3 3 0.14 0.14 0.38 0.56 0.038 0.271 4 3 0.14 0.14 0.38 0.56 0.026 0.543 5 3 0.14 0.14 0.38 0.56 0.028 0.635 6 3 0.14 0.14 0.38 0.56 0.050 0.238 7 3 0.14 0.14 0.38 0.56 0.030 0.192 8 3 0.14 0.14 0.38 0.56 0.027 0.248 9 3 0.14 0.14 0.38 0.56 0.022 0.592AERSURFACE Processing Bowen Bowen Surface Surface

Surface Albedo Albedo Ratio Ratio Roughness Roughness Geophysical Season Airport Sanders Airport Sanders Airport Sanders Lead Lead Lead Parameters Sector 10 3 0.14 0.14 0.38 0.56 0.032 0.626 11 3 0.14 0.14 0.38 0.56 0.050 0.255 12 3 0.14 0.14 0.38 0.56 0.090 0.170 1 4 0.14 0.14 0.38 0.56 0.114 0.324 2 4 0.14 0.14 0.38 0.56 0.066 0.404 3 4 0.14 0.14 0.38 0.56 0.038 0.271 4 4 0.14 0.14 0.38 0.56 0.026 0.543 5 4 0.14 0.14 0.38 0.56 0.028 0.635 6 4 0.14 0.14 0.38 0.56 0.050 0.238 7 4 0.14 0.14 0.38 0.56 0.030 0.192 8 4 0.14 0.14 0.38 0.56 0.027 0.248 9 4 0.14 0.14 0.38 0.56 0.022 0.592 10 4 0.14 0.14 0.38 0.56 0.032 0.626 11 4 0.14 0.14 0.38 0.56 0.050 0.255 12 4 0.14 0.14 0.38 0.56 0.090 0.170Sanders Lead Troy, Alabama 

# URS
URS Corporation- North Carolina 1600Perimeter Park Drive Morrisvilfe, Nol1h Carolina 27560 Telephone (919)461-JJOO Fax (919)461-1415 

### Location ofAirport & 

### Site File No. 20499427 Figure ISanders Lead Troy, Alabama SCALE: as shown 

# URS
URS**Corpon~lion** • North Carolina /600 PerimeterPark Drive Morrisville, North Carolina 27560 Telephone (919)461-/JOO Fax (919)461-1415 DRAWN BY: SCL DATE: 8/4/09 CHECKED BY: DATE: 

### Aerials Extending 1-kmfrom Airport & Plant Site FILE NO. 2049942 FIG. NO. 2Sanders Lead Troy, Alabama SCALE: na 

# URS
URS Corporation

- North Carolina 1600PerimeterParle Drive Morrisville, North Carolina 27560 Telephone (919)461-1100 Fax (919)46/-1415 DRAWN BY: SCL DATE: 8/4/09 CHECKED BY DATE: 

## • Land use Classes 

# • 23 to 23 Ccmm..tndust!Trans 

# • 41 to 43 Fo...,. 81 to 82 PastureJHayJC rops 

# • 85 to 85 UrbanGrass 

# • 90 to 91 \Mlody/OtlerWetlan:::ls

FILE NO. 

### AERSURFACE Output Surface Roughness LanduseDistribution 2049942 FIG. NO. 

### Airport 3Sanders Lead Troy, Alabama SCALE: na 

# URS
URS Corporation

- North Carolina 1600PerimeterPark Drive Morrisl'ille, North Carolina 27560 Telephone (919)461-1100 Fax (9/9)461-1415 DRAWN BY: SCL DATE: 7/9/09 CHECKED BY: DATE: Landuse- Classes 

# • 11 to 11 

# • 21 to 22 

# • 23 to 23 33 to 33 

# • 41. to 43 81 to 82 

# • 85 to 85 

# • 91 to 92 wate•
C< Tc esidential anmJlndL.Et/Trans :ansitional Fo

### "'"' Pasb..reiHay/Crq)s U• W•

rb.., Grass oOOy/OtherWetlan::ls



### AERSURFACE Output FILE NO. 

### SurfaceRoughness 2049942 

### Landuse Distribution FIG. NO. 

### PlantSite (4 squarekilometerarea) 4Sanders Lead Troy, Alabama o·c--o o . 

# . \ 

# . 1 :1 1

,,0



# ""

SCALE not shown 

### .' 

## ,-.-
----

/ I /

With Site Landuse Data



## ,, Max. Location

'\



## .\

L-

.. / I

With Airport Data 

# URS
URS Corporation

- North Carolina 1600Perimeter Park Drive Mo"isville, North Carolina 27560 Telephone (919)461-1100 Fax (919)461-1415 DRAWN BY: SCL DATE: 8/4/09 CHECKED BY DATE: -..../\.



### Maximum Receptor Location 2005 1stQuarter (with Airport and Site Landuse) FILE NO. 2049942 FIG. NO. 5