1000 Corporate Centre Drive 

One Meridian, Ste 250 

Franklin, Tennessee 37067 

(615) 771-2480 

SANDERS LEAD 

SIP AIR DISPERSION 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 

1 000 Corporate Centre Drive 

Suite 250 

Franklin, Tennessee 37067 

(615) 771-2480 

URS Project No.: 20499427.00001 
TABlE OF CONTENTS 

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 Contingency Trigger 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 

Major Control Equipment Installation Timeline 

Modeling Protocol 

Haul Road Workgroup Final Report 

Protocol to Support the use of Airport Meteorological Data for Sanders Lead Modeling 

S:\2012\Sanders Lead\427 _Consulting\01_Air\SIP\SIP Report Rev 1\Sanders SIP _Rev 2.doc 
SIP Anainment Demonstration Sanders Lead Companv 

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 of Pike 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 MODELING APPROACH 

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 of the 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. 

1 

S:\2012\Sanders Lead\427 _Consulting\01_Air\SIP\SIP Report Rev 1\Sanders SIP _Rev 2.doc 
SIP Anainment Demonstration Sanders Lead Companv 

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 of the 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 of the 

Troy, Alabama study site. This review, Protocol to Support the use of Airport Meteorological 

Data for Sanders Lead Modeling, is located in Appendix G. The review concluded that the 

Montgomery surface meterological data was representative of the 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 calculating the 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 of up 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 fence line 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. 

2 

S:\2012\Sanders Lead\427 _Consulting\01_Air\SIP\SIP Report Rev 1\Sanders SIP _Rev 2.doc 
... 

... 

SIP Attainment Demonstration Sanders Lead Company 

Table 1 - Pre-Construction Lead Emission Sources 

Emission 

Source ID Type Source Description 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 1 and 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 breaker to main building 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 of raw coke, limestone and scrap iron 0.0029 

Haul Road 5 Volume Delivery of batteries to Breaker 0.0052 

Source A Volume Shredding and Separation Fugitive 0.057 

Source B 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 of five {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 of the 

modeling parameters for each stack. For each of the 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 of actual 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 of Stack 1. 

3 

S:\2012\Sanders Lead\427 _Consulting\01_Air\SIP\SlP Report Rev 1\Sanders SIP _Rev 2.doc 
SIP Anainment Demonstration Sanders Lead Companv 

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 1 for the location of Stack 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 1 for the location of Stack 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 of Stack 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 

1 for the location of Stack 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 of the 

methodology used in calculating the parameters used in modeling the sources (both Operation 

and Haul Road sources). 

The emission rate for each of the 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 emission rate reflects 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 

S:\2012\Sanders Lead\427 _Consulting\01_Air\SIP\SIP Report Rev 1\Sanders SIP _Rev 2.doc 
SIP Anainment Demonstration Sanders Lead Companv 

The Pre-Construction model also incorporated a total of five ( 5) haul roads. Refer to Drawing 1 

for the location of on-site haul 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 of the report is located in 

Appendix F. Below is a summary of the Recommended Volume Source Configuration: 

• Adjacent Volume Source 

• Top of Plume Height- 1. 7 x VH 

• Volume Source Release Height- 0.5 x Top of Plume height 

• Width of Plume- VW + 6m for single lane roadways I Road Width+ 6m 

for two lane roadways. 

• Initial Sigma Z- Top of Plume I 2.15 

• Initial Sigma Y- Width of Plume 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. 

5 

S:\2012\Sanders Lead\427 _Consulting\01_Air\SIP\SIP Report Rev 1\Sanders SIP _Rev 2.doc 
SIP Anainment Demonstration Sanders Lead Companv 

Table 2- Post-Construction Lead Emission Sources 

Type Source Description 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 1 and 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/Shredder Building 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 breaker to main building 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 of raw coke, limestone and scrap iron 0.0029 

Haul Road 5 Volume Delivery of batteries to Breaker 0.0052 

Source A Volume Shredding and Separation Fugitive Enclosed 

Source B Volume De-casing of Industrial Batteries Enclosed 

Source C Volume Raw Material Storage Building Operations Enclosed 

SourceD Volume Furnace/Refining Building Operations Enclosed 

Point Sources: 

A total of nine (9) point sources were incorporated into the Post Construction model. Each of the 

point sources represented a stack at Sanders Lead; refer to Appendix A for a summary of the 

Post-Construction modeling parameters for each stack; refer to Drawing 2 (in Appendix B) for 

the location of all 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). 

6 

S:\2012\Sanders Lead\427 _Consulting\01_Air\SIP\SIP Report Rev 1\Sanders SIP _Rev 2.doc 
SIP Anainment Demonstration Sanders Lead Companv 

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 of 0.00043 gr/dscf and reflect an 8, 760 hours/year operating schedule. 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 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 of Stack 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 of 0.000087 gr/dscf and reflect an 8, 760 hours/year operating schedule. This value 

is about 5% higher than the average of the past 4 compliance tests on the sanitary baghouses. 

Refer to Drawing 2 for the location of Stack 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 of the 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 of Stack 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 of the past two compliance tests on this baghouse. Refer to Drawing 2 

for the location of Stack 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 HEP A filter and therefore this value should be easily met at all times in that the 

particle emissions from the HEP A should be lower than the rate expressed above. Refer to 

Drawing 2 for the location of New 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 HEP A filter and therefore this value should be 

easily met at all times in that the particle emissions from the HEP A should be lower than the rate 

expressed above. Refer to Drawing 2 for the location of New Stack 12. 

7 

S:\2012\Sanders Lead\427 _Consulting\01_Air\SIP\SIP Report Rev 1\Sanders SIP _Rev 2.doc 
SIP Anainment Demonstration Sanders Lead Comuanv 

New Stack 13 exhausts emissions from the Raw Material Storage Building. Projected emissions 

associated with this stack are based on a lead concentration of 0.000060 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 HEP A 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 of 0.000080 gr/dscf and 

reflect an 8,760 hours/year operating schedule. This cartridge-type baghouse will be followed by 

a HEP A filter and therefore this value should be easily met at all times in that the particle 

emissions from the HEP A should be lower than the rate expressed above. Refer to Drawing 2 

for the location of New Stack 14. 

Volume Sources: 

A total of three (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 of on-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 order to 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 of 2005. 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 

S:\2012\Sanders Lead\427 _Consulting\01_Air\SIP\SIP Report Rev 1\Sanders SIP _Rev 2.doc 
-

SIP Attainment Demonstration Sanders lead Companv 

averages were then used to create 3-month rolling averages and from that the maximum 3-month 

rolling average for the entire period of data was determined and set as the background for lead. 

Based on results from the speciated PM2.5 data, ADEM determined that 0.009 ug/m3 provided a 

representative background concentration of lead 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 operating procedures, raw materials, and physical plant layout. 

The following items were considered when determining the control technology to apply: 

The process, operating procedures, and raw materials used by the source can affect the feasibility 

of carrying out process changes that reduce emissions and the selection of add-on emission 

control equipment. 

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 proposed measures to be employed, as well as a brief explanation of the 

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 of the control measures for attainment of the 2008 lead NAAQS are presented 

below. It is currently anticipated, if all goes according to schedule, that all of the modifications 

to the facility described in this document will be completed by December 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 HEP A filters will be installed to control emissions captured 

by the 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 (with HEPAs). 

Sanders Lead is proposing to relocate the industrial battery decasing 

operations to the inside of the existing raw material storage building. A 

9 

S:\2012\Sanders Lead\427 _Consulting\01_Air\SIP\SIP Report Rev 1\Sanders SIP _Rev 2.doc 
SIP Anainment Demonstration sanders Lead Companv 

Material Handling Operations 

Battery Breaker/Shredder 

Operations 

Enclose Baghouse Hoppers 

and Transport of Dust 

Improve Process Material 

Transport to Eliminate Leaded 

Outdoor Traffic 

Relocate and Contain Leaded 

Vehicle Maintenance 

Improved Watering 

new 60,000 ACFM collector with HEP A filters will be installed to 

control industrial battery decasing and raw material storage area. 

Sanders Lead is proposing to enclose the shredder building 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 existing baghouses. 

In order to eliminate leaded outdoor traffic, Sanders Lead is proposing 

to install building connection tunnel for the transport of group from 

shredder to 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 of the AERMOD modeling 

system: AERMET, a meteorological data preprocessor that incorporates air dispersion based on 

planetary boundary 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 

engineering practice (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 of the 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 of the study site (Troy AL). For a summary 

of Pre-Construction conditions, refer to Appendix A. 

10 

S:\2012\Sanders Lead\427 _Consulting\01_Air\SIP\SIP Report Rev 1\Sanders SIP _Rev 2.doc 
SIP Anainment Demonstration Sanders Lead Companv 

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 (Facility MET Data) 

5.0 CONTINGENCY PLAN 

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 meet reasonable 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 be taken by the state. Additionally, the plan should identify specific indicators or triggers that 

will be used to determine when the contingency measures are to be implemented. 

5.1 CONTINGENCY MEASURES 

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 

considered but not considered in the complinace demonstration include: 

1) Install HEP A filters on both sanitary baghouse systems (Stacks 4 and 4a) 

2) Install HEP A filters on the slag treatment building 

3) Raise stack height of the slag treatment building stack 

However, if an exceedance of the NAAQS occurs during any quarter following the 

implementation of all the controls included in this plan, Sanders Lead Company will 

immediately initiate an investigative study aimed at identifying the source of excessive emissions 

that may have contributed to the excursion so that controls, strategies, etc. may be developed to 

11 

S:\2012\Sanders Lead\427 _Consulting\01_Air\SIP\SIP Report Rev 1\Sanders SIP _Rev 2.doc 
SIP Anainment Demonstration Sanders Lead Companv 

eliminate the likelyhood of a reoccurrance of an exceedance. The results of the investigation and 

action to be taken, including a proposed timeline for implementation, would be submitted within 

180 days of notification by ADEM that the NAAQS limit had been exceeded. 

The full extent of the investigation is unknown at this time; however, as the above controls are 

finalized and operational, areas where additional work can be done may be more evident. Items 

under discussion at this time which may proved to provide some additional reductions include: 

1) addition of second gate on the south end of the property in order to direct significant 

traffic flow to an area futher away from the maximum lead impact areas 

2) planting of vegetation in specific areas to help control dust flow patterns and hopefully 

scavenge fugitive lead emissions 

3) re-evaluate material handling procedures, patterns, etc to determine if improvements can 

be made 

4) re-evaluate housekeeping procedures, including dust sweeping and collection equipment 

5) other improvements that may become evident based on potential source of lead emissions 

identified during investigation. 

5.2 CONTINGENCY TRIGGER LEVELS 

A contingency measure would be triggered upon failure to meet RFP requirements or failure to 

attain the 2008 lead NAAQS. 

6.0 REASONABLE FURTHER PROGRESS 

Section 172(c)(2) the Federal Clean Air Act (FCAA) requires areas that have been designated 

nonattainment for criteria pollutants to include a demonstration of reasonable further progress 

(RFP) in attainment demonstrations. RFP is defined in FCAA § 172(c)(2) as such annual 

incremental reductions in emissions of the relevant air pollution as are required by part D, or 

may reasonably be required by the United States EPA for the purpose of ensuring 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 County lead 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 of the 2008 lead NAAQS included in section 3.0 Control 

Measures/RACThave been modeled to achieve attainment of the 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. 

12 

S:\2012\Sanders Lead\427 _Consulting\01_Air\SIP\SIP Report Rev 1\Sanders SIP _Rev 2.doc 
APPENDIX A 

Input Parameters 
Sanders 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 

Stack 4a 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 1 Delivery 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 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 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 by 2.15. 

Release Height- calculated by dividing the height of volume in haft; this point is in the center of the 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 0.00032 
Sanders 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 Bag house 0.023 0.10 30.0 95.0 f--:-~~~-k 10 Stack . Point 596754.14 3517148.01 524.9 8,760 . 

New Stack 11 i Canopy Hoods Stack Point 596753.27 3517179.12 526.2 0.191 I 0.84 8,760 150.0 100.0 - --· 

' New Stack 12 I Battery 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 

Facility Drawings 
0 

"' 

------- 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 

Air Dispersion Modeling Assumptions 
... 

ATTACHMENT C 

FUGITIVE EMISSION ASSUMPTIONS 

Sanders Lead Company 

ID Source Description 

Source A Shredding and Separation Fugitive 

Source A = Volumetric Flow from Egress Area *Average Lead Concentration * 0.028317 I 10A6 * 0.002205 

Maximum Egress Area (jt 2 ) 1,000 

Average Exit Velocity (mph) 6.6 

Volumetric Flow from Egress Area (ft 3 !h) 11,616,000 

Average Lead Concentration (pg!m 3 ) 78.34 

Source B Decasing of Industrial Batteries 

Source B = 213~g X 1Nm3 X lib X 278784scf x 60min 

1Nm3 35.31 scf 453592370~g I min lhr 

Maximum Egress Area Ui 2 ) 480 

Average Exit Velocity (mph) 6.6 

Volumetric Flow from Egress Area (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 PM on Roadways(%): 26% 

Control Factor (efficiency%): 90% 

SourceD Furnace/Refining Building Operations 

SourceD = Volumetric Flow from Egress Area *Average Lead Concentration * 0.028317 I I OA6 * 0.002205 

Average Exit Velocity (mph) 6.6 

Volumetric Flow from Egress Area (ft"1/hr) 10,740,000 

Average Lead Concentration (pglm 3 ) 200 

Haul Road 1 Delivery of material from breaker to 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/Year with at least 0.01 inches of Precipitation (P): 120 

Number of days in averaging period (N): 365 

Haul Road 2 Delivery of material 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 

Road Suiface Silt Loading (sL) (gfmA2): 0.6 

Days/Year with at least 0.01 inches of Precipitation (P): 120 

Number of days in averaging period (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 0.0061 
ATTACHMENT C 

FUGITIVE EMISSION ASSUMPTIONS 

Sanders Lead Company 

Haul Road 3 Delivery of raw 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 

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 averaging period (N): 365 

Haul Road4 Delivery of raw 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 averaging period (N): 365 

Haul Road 5 Delivery of batteries 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 

Road Surface Silt Loading (sL) (g/mA2): 0.6 

Day slY ear with at least 0. 0 I inches of Precipitation (P) : 120 

Number of days in averaging period (N): 365 

lbslhr tons/yr 

0.00047 0.0020 

1bslhr tonslyr 

0.0029 0.013 

1bslbr tons/yr 

0.0052 0.023 
APPENDIXD 

Major Control Equipment Installation Timeline 
Sanders Lead Company- Lead Control Schedule SANDERS I..EAO COMPANY April 24, 2012 

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 

""' 1 Control 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 

Modeling Protocol 
SANDER'S LEAD SIP MODELING PROTOCOL IN 

ACCORDANCE WITH ADEM PSD AIR QUALITY ANALYSIS 

AERMOD MODELING GUIDELINES (MAY 2008) 

July 28, 2011 

Revision 1 January 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 of this document is to present to the Alabama Department of 

Environmental Management (ADEM) a detailed protocol of the 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 in the ADEM 

PSD Air Quality Analysis 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 of potential 

nonattainment areas in Alabama for the new Lead National Ambient Air Quality 

Standards (NAAQS). The monitoring data indicated that a small portion of Pike 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 

0.8 miles surrounding Sanders Lead located in Troy, AL as "nonattainment" in the first 

round of designations. 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 of the 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 on data from 2008-2010. 

Sanders Lead developing mitigation measures for achieving compliance with the new 

lead NAAQS, and anticipate that with the implementation of these 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), Troy is located in southeastern Alabama, in Pike County. 

Troy is located 70 kilometers southeast of Montgomery, Alabama. Figure I displays the 

plant site on a 7.5 minute USGS map along with a depiction of current company owned 

plant boundaries. The city population of Troy is 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 of it is land and 0.1 square miles of it (0.36%) is water. 

Page 1 ofll 

S:\20 12\Sanders Lead\427 _ Consulting\0 l_Air\Pb Modeling\Protocol\Modeling Protocol_ Rev !.doc 
2.1 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 Gulf of Mexico 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 of the Troy area. In late August and in September, summer 

conditions of temperature and humidity persist as air continues to drift in from the Gulf, 

but local thunderstorms become less frequent because of the shortening of the 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 of rain, 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. Near the facility, terrain has gentle undulations. 

The approximate UTM coordinates of the 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 by EPA, the facility is located in a 

rural section of the state. EPA guidance shows two alternative procedures to determine 

whether the character of an area is predominately urban or rural: (1) land use typing or 

(2) population density. The area classification system as described by Auer in the Journal 

of Applied Meteorology, Vol. 17, pg. 636-643, 1978, Correlation of Land Use and Cover 

with Meteorological Anomalies, is frequently used to classify the area. URS used the 

new EPA AERSURF ACE 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 

of the area made up of trees 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. 

Page 2 ofll 

S:\20 12\Sanders Lead\427 _ Consulting\0 l_ Air\Pb Modeling\Protocol\Modeling Protocol_ Rev l.doc 
3.0 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 of choice for 

this particular modeling exercise; such features include the capability to model point, area 

and volume sources; inclusion of building down wash of effluent; and most importantly, 

AERMOD was recently identified as the "preferred" model in the U.S. EPA Guideline on 

Air Quality Models. 

4.0 MODELING INPUT 

4.1 Dispersion Model 

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 

dispersion model for conducting refined 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 

be used include the following: 

o Calculation of average concentrations for each applicable averaging period; 

o Non-Urban dispersion conditions; 

o Regulatory default options; 

o Final plume rise; 

o Stack-tip downwash; 

o Buoyancy-induced dispersion; 

o Calms processing routine; 

o Default wind profile exponents; 

o Default vertical potential temperature gradients; 

o "Upper Bound" 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 

Page 3 ofll 

S:\20 12\Sanders Lead\427 _ Consulting\0 I_ Air\Pb Modeling\Protocol\Modeling Protocol_Rev !.doc 
to 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 of the atmosphere. As such, the determination of representativeness should 

include comparison of the surface characteristics, Bowen ratio and albedo, between the 

NWS measurement site and the 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 AERSURF ACE 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 of maximum impact, URS will provide the air dispersion results for 

both surface characteristics (Montgomery airport and Sanders Lead site). 

4.2.2 Al!.'R.SURFACE Landuse Analysis for AERMET 

One of the 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 of useful 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 of conditions 

at the modeling site. This test of representativeness 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 of measurements 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, 

Page 4 ofll 

S:\20 12\Sanders Lead\427 _ Consulting\01._ Air\Pb Modeling\Protocol\Modeling Protocol_ Rev !.doc 
meteorological data should be representative of conditions affecting the transport and 

dispersion of pollutants in the area of interest as determined by the locations of the 

sources and receptors being modeled. " Establishing representativeness balances the 

requirements of the modeling assessment with the reasonableness of meteorological 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 

dispersion modeling analyses. 

4.2.3 AERSURF ACE Landuse Analysis 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-km radius and the land use distribution 

was calculated and plotted. The plot clearly shows the large amount of vegetation 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 kilometer determines whether the 

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 (beginning with version 9.84) to support processing of terrain 

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 of the 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 of the 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 in the modeling report when submitted. 

Page 5 ofll 

S:\20 12\Sanders u:ad\427 _ Consulling\0 I_ Air\Pb Modeling\Protocol\Modeling Protocol_ Rev !.doc 
... 

-

TABLE 1 - Source of Emissions 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 Baghouse for Furnaces 3 and 4 

Stack 10 Point Slag Treatment 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 of raw coke, limestone and scrap iron 

RouteS Volume Delivery of batteries 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 not be modeled unless the ADEM specifically identifies an off-site 

source in response to this modeling protocol. 

4.6 Background Air 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: 

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 of 2005. The 

monitor used was the Montgomery site (0 1-10 1-1002) and the data for this monitor 

was collected every 61

h day throughout the year. This data was then used to calculate 

monthly averages for the entire period. These monthly averages were then used to 

create 3-month rolling averages and from that the maximum 3-month rolling average 

for the entire period of data was determined and set as the background for lead. 

Based on results from the speciated PM2.5 data, ADEM has determined that 0.009 uglm3 

provides a representative background concentration oflead for the area. 

Page 6 ofll 

S:\20 12\Sanders Lead\427 _ Consulting\0 I_ Air\Pb Modeling\Protocoi\Modeling Protocol~ Rev !.doc 
-

"" 

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 if building 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 of 65 meters or GEP = Hb + 1.5L (where Hb is the building height, 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 specific building dimensions for use in the dispersion model. There are 

no stacks with a stack height greater than 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 of five times L (the lesser of the maximum projected width 

or height of the building) directly downwind from the leeward side of the building. Wake 

effects were assumed to occur if the emission source was located within a rectangle 

composed of two lines perpendicular to the wind direction, one at 5L downwind of the 

building and the other at 2L upwind of the 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 down wash effect region of influence changes and is combined to 

form a GEP 5L region of influence in all wind directions. Any emission source within 

the region of influence 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 of the 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 of influence, 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 of the building causing the maximum GEP height. The prime 

equations reduce plume rise due to initial plume dilution, enhance plume spread. 

The GEP analysis was conducted using the Building Profile Input Program -Prime 

(BPIPPRIME) program to demonstrate compliance with 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 

Page 7 ofll 

S :120 12\Sanders Lead\427 _ Consulting\0 I_ Air\Pb Modeling\Protocol\Modeling Protocol_Rev !.doc 
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 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 operating procedures, raw materials, and 

physical plant layout. The following items were considered when determining the 

control technology to apply: 

1. The process, operating procedures, and raw materials used by the source can 

affect the feasibility of carrying out process changes that reduce emissions and the 

selection of add-on emission control equipment. 

2. The operation of and longevity of control equipment can be significantly 

influenced by the raw materials used and the process to which it is applied. 

3. The feasibility of modifYing processes or applying control equipment is also 

influenced by the physical layout of a particular plant. 

4. The space available in which to carry out such changes may limit the choices of 

control. 

5. Determinations of technological feasibility also consider adverse impacts on other 

resources. If a control technology increases pollution of bodies of water, creates 

additional solid waste disposal, or exacerbates worker exposure problems; the 

technology may not 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:\20 12\Sanders Lead\427 _ Consulting\0 l_ Air\Pb Modeling\Protocol\Modeling Protocol_ Rev !.doc 
Description of Measure 

Enclose Baghouse Hoppers and 

Transport of Dust 

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 

Outdoor Traffic 

Material 

Leaded 

Explanation 

Sanders Lead is proposing to enclose the base of baghouses #I and 

#5, including the access doors and removable panels on the units. 

Ventilation will be provided by dueling to existing baghouses. 

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 and building enclosure. 

Sanders Lead is proposing to enclose the refining building, 

including the elimination of sidewall fans. As part of enclosing 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 storage building. 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 runoff from the shredder group pile. 

Sanders Lead is proposing the install transfer points 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 

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. 

6.0 CONTINGENCY MEASURES 

Pursuant to Section 172 of the CAA, a set of contingency measures has been prepared 

that could be implemented if required by a finding of the 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\0 I_ Air\Pb Modeling\Protocol\Modeling Protocol_Rev l.doc 
... 

deadline, or c) monitoring shows that the nonattainmcnt area has failed to attain the 

NAAQS by the statutory deadline. 

7.0 SUBMITTAL INFORMATION 

The Air Quality Impact analysis will include the following information as recommended 

by the 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 be used 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 of the 

meteorological collection site (furnished by ADEM) arc representative of the surface 

characteristics in the vicinity of the facility. This information has be previously submitted 

and approved in a separate Landuse protocol. 

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 be used for comparison with and ambient air quality standards if needed. 

5) Tables identifying the maximum ambient levels (including receptor locations and year 

of meteorology) for quarterly averaging periods including the contribution of the 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 easy orientation. 

7) Appropriate model output files substantiating points of concern, as described in the 

text, will be submitted. 

8) Source input parameters for all sources modeled will be reported. 

9) Identification of the meteorology used will be described. 

1 0) List of options used in the particular model run will be provided. 

II) Concentration tables for the "rolling" quarterly averaging period will be reported. 

12) List of options used in the particular model run will be provided. 

Page 10 ofll 

S :\2012\Sandcrs Lead\427 _ Consulting\0 l_Air\Pb Modeling\Protocol\Modeling Protocol_Rev !.doc 
13) 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 utility preprocessors such as AERSURFACE, BPIP and LEADPOST. 

Sanders Lead request that these modeling procedures be approved so modeling can begin. 

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) with respect to facility operations and emissions. 

Page 11 ofll 

S:\20 12\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 

Haul Road Workgroup Final Report 
UNITED STATES ENVIRONMENTAL PROTECnON AGENCY 

RESEARCH TRIANGLE PARK, NC 2n11 

March 2, 2012 

MEMORANDUM 

SUBJECT: Haul Road Workgroup Final Report Submission to EPA-OAQPS 

FROM: Tyler Fox, Leader---(""~ J'--=lf.-

Air Quality Modeling Group, C439-0l 

TO: Regional Office Modeling Contacts 

OFFICE OF 

AIR QUALITY PLANNING 

AND STANDARDS 

The challenge of modeling the emissions and associated air quality impacts of haul roads 

has been a particularly vexing problem for the dispersion modeling community. There is a large 

degree of uncertainty in the magnitude of these fugitive dust emissions and subsequently in the 

modeled estimates at near-source receptor locations. At the 2009 Regional, State, and Local 

Modelers' Workshop, EPA held an interactive session on best modeling practices ofbaul roads 

tbat was chaired by Randy Robinson, USEPA Region 5, and Mick Daye, USEPA Region 7 to 

open up a constructive dialog throughout the regulatory dispersion modeling community on the 

challenges of characterizing and appropriately addressing the baul road fugitive emissions in a 

compliance demonstration project. Following this 2009 Workshop, the Haul Road Workgroup 

was formed with a collection offederal, state, and local government dispersion modelers. The 

goal of this Workgroup was to examine and better understand haul road characterization issues 

and recommend a modeling methodology back to the broader dispersion modeling community. 

The Workgroup decided to focus on the air quality modeling aspects and not address the fugitive 

dust emissions factor issues. 

A report out of the Haul Road Workgroup was presented at the 2010 Regional, State, and 

Local Modelers' Workshop. Along with discussion amongst the regulatory dispersion modelers 

in attendance at the2010 Workshop, feedback and comments were solicited and accepted on the 

recommendations of the Workgroup throughout 2010 and the first half of2011. An update 

presentation on the Workgroup was given at the 2011 Regional, State, and Local Modelers' 

Workshop with the subsequent release of a draft version of the Haul Road Workgroup Final 

Report during the fall of2011. 
Attached to this letter is the Haul Road Workgroup Final Report that provides a "best 

practices guide" for modeling of haul road fugitive emissions in the AERMOD modeling system. 

This final report is being shared with the entire dispersion modeling community prior to the lOth 

Conference on Air Quality Models to promote broader consideration and facilitate further 

comment. Please send this report to your state, local and tribal agency modelers so that they can 

provide review and comment, as appropriate. The recommendations presented are not an 

endorsement by the USEPA as the definitive methodology for characterizing and addressing 

fugitive dust emissions from haul roads but should be considered a best practice approach based 

on the broad involvement of the co-regulating community in the development of this 

recommendation. 

We would like to give special recognition to the initiative and labors of Randy Robinson 

and Mick Daye in spearheading this initiative in 2009, chairing the Haul Road Workgroup, and 

developing this final report. We would also like to thank all of the federal, state, and local 

government dispersion modelers that participated in the Workgroup and assisted in the drafting 

of the final report presented in the attachment. 

Attachment: Robinson and Daye December 6, 201 l memorandum with Haul Roads 

Workgroup Final Report included as an attached document 
UNITED STATII E~AL PROTECTION AGENCY 

REGIONS 

77WEST JACKSON BOUI..EVARD 

CHICAGO, IU!OII04-35110 

IIEPL Y TO TH! ATli!NTIOif Of': 

MEMORANDUM 

SUBJECT: 

FROM: 

TO: 

Haul Road Workgroup Final Report - /1 ·~ 

Randy Robinson. EPA Region~ ,. ·.Fl. Jt' 

MickDaye,BPARegion7 ~£' ~ 

Tyler Fox. Leader, Air Quality Modeling Group 

George Bridgers. Clearinghouse Coordinator, Air Quality Modeling Group 

The pmpose of Ibis memorandum is to tnmsmit the attached baul road modeling final 

report to the Air Quality Modeling Group. The report represents the collective efforts of the 

Haul Road Workgroup, which was formed following abc 2009 Regional/StateJI..ocal Modeling 

Workshop. The ptupose of the wodcgroup was to identify aDd recommend a leclmically 

supportable approach for modeling haul road re-entiained dust 

The attached document cOntaim a summary of the possible options for Inodeling fugitive· 

road dust. a description of the SCII5itivity modeling cooduNcd by lhe workgroup. and a tiered set 

of recommendatiODS for modeling haul rood fugitive emissions. The other attachment rontains 

se.lected slides from tbe haul road presentation at the 2010 Regional/StateJLocal modeling 

workshop. The Workgroup requests Air Quality Modeling Group review and distribution of the 

recommendations docmnent to the modeling community. 

Thank }'OU and please contad ua if you bave any questions or require additional 

infonnation. 
Haul Road Workgroup Recommendations 

November 2011 

Workgroup ChargeThe Haul Road Workgroup was formally established shortly after the May 2009 

RegionaVState/Local Workshop. The purpose of the workgroup is to identify and 

recommend a technically supportable approach for modeling haul road re-entrained dust. 

While emission factors are a critical part of any roadway modeling exercise, this 

workgroup felt that emissions were outside our scope and did not engage in a review or 

evaluation of available fugitive dust emission factors. Based on modeling work and field 

study/journal article review, the following represents a recommendation for an approach 

to characterizing haul road fugitive emissions in AERMOD. 

Source Characterization - The model to be used for modeling haul road fugitive dust 

emissions is AERMOD. There are several ways haul road fugitive dust emissions can be 

characterized in AERMOD, including area source, volume source, and series of point 

sources. A line source algorithm is being developed but is not currently available. Each 

approach has advantages and disadvantages. The workgroup has considered each 

approach and a summary of the strengths and weaknesses is presented below. 

Area source advantages: 

• Can place receptors in ambient air contained within the area source 

• Easy to replicate dimensions of roadway in X and Y coordinates 

• Avoids the need to determine Sigma Y values (Sigma Z values are optional) 

• Can utilize a Sigma Z value if desired, to reflect an initial, well-mixed plume 

• Area sources explicitly simulate a uniform emission density across the roadway, 

which may be more realistic in some respects than other approaches. 

Area source disadvantages: 

• Area source in AERMOD does not have the meander algorithm 

• Run times are generally longer than 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 time than area source 
'-IIIH! 

Volume source disadvantages: 

• Concentrations are not calculated in a volume source exclusion zone 

o Exclusion zone is the region ( (2.I5 x Sigma Y) + I meter)) from the 

center of the volume. 

Point Source with downwash advantages: 

• Precludes the need to establish Sigma values; handled internally by downwash 

• Conceptually, consistent with well-mixed plume 

• Can place receptors anywhere within roadway 

• Can be used for buildings near roadways 

Point source with downwash disadvantages: 

• Downwash algorithm in AERMOD does not contain meander for receptors within 

the wake 

• Technique would be new to modeling community 

• Additional assumptions required, including building (truck) size, stack temp, 

velocity, height. 

• Potential issues with BPIP used in this technique 

Sensitivity analysis 

Early in the process, the workgroup conducted an AERMOD sensitivity analysis to 

examine changes in haul road characterization inputs using volume and area source 

techniques. Limited, preliminary point source technique sensitivity runs were also 

conducted. Details of the sensitivity analyses are available at 

http://www .cleanairinfo.corn/regionalstatelocalmodelingworkshop/archi ve/20 I 0/Docume 

nts/Presentations/RSL20 I 0 HauiRoads.pdf. The following summarizes the setup and 

general conclusions. 

Analysis setup: 

• Used AERMOD Version 09292 

• I year of meteorological data (variety of locations) 

• N-S and E-W crisscrossing road segments. Each 500m long, I Om wide. 

• Flat Terrain 

• Receptor Grids - Cartesian and Polar; beginning as near as possible to the volume 

sources. I meter from edge of area source. No receptors within source. 

• Unit emission rate 

• Evaluated range of values for top of plume height, Sigma Z, Sigma Y, and release 

height. 

• Modeled using Adjacent Volume, Alternate Volume, and Area 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 adjacent volume sources lowered 

concentrations. 

• For area source- increasing X dimension lowered concentrations at lower release 

heights (i.e., Om and 0.5m). It had little impact at higher release heights (i.e, l.Sm 

and 3m). 

• For area source- adding a Sigma Z lowered concentrations for surface release 

heights, but generally increased concentrations at higher release heights 

• For volume runs, adjacent gives higher concentrations than alternate. 

• Point Source- limited, preliminary modeling shows some sensitivity to stack 

height and velocity 

• On-site meteorological data model runs showed same trends as with National 

Weather Service data, although concentrations were higher with on-site data. 

Model/Monitor Comparison 

The workgroup was interested in locating field data to facilitate our review of haul road 

dispersion characteristics. Finding field data relevant to our task was difficult. While 

there are numerous field studies relevant to haul roads, the vast majority deal with 

monitoring designed to evaluate haul road emissions rather than dispersion 

characteristics. An evaluation conducted by OAQPS 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 characterizations performing slightly better than area source when 

compared to monitored PM 1 0 data. The analysis was primarily designed to examine the 

impact of the meander algorithms. This is significant because the volume source 

approach incorporates meander while the area source approach does not. The difference 

in model performance was attributed to area source over-estimates due to lack of 

meander upwind dispersion. Details of the Cordero Rojo Mine evaluation results can be 

found at http://www.awma.org/events/confs/ AQMODELS06/Session%204/4-

Roger"/o20Brode.odf. 

3 
Haul Road Recommendations 

Definitions 

During the workgroup discussions and sensitivity modeling work, the following 

definitions were used; 

"VH" means vehicle height [-3m for typical haul trucks; -10m for large mining trucks] 

"VW" means vehicle width [-3m for typical haul trucks; -10m for large mining trucks] 

"VL" means vehicle length [-lOrn for typical haul trucks; -20m for large mining trucks] 

These definitions and associated dimensions were useful to the group as we discussed the 

various methods and developed the inputs to be used in the sensitivity modeling. They 

should not be treated as default values and/or used in place of site specific dimensions 

available for individual modeling demonstrations. 

General Recommendation 

The following represents a general recommendation for modeling of haul road emissions. 

The recommendation is not meant to be prescriptive; local conditions and specific 

information may lead to an alternative approach. However, the workgroup feels that the 

recommendation presented below is reasonable, can be technically supported, and 

provides a level of conservativeness given the large amount of uncertainty associated 

with characterizing and simulating dispersion of fugitive emissions resulting from haul 

road traffic. Concentrations must be calculated in areas that are considered ambient air. 1 

• Volume Source- Recommend for all haul roads, except for cases where 

ambient air receptors are within the volume's exclusion zone (i.e., ( (2.15 x 

Sigma Y) + I meter)) from the center of the volume. 

Rationale: 

Volume source contains the meander algorithm. 

Conceptually fits the physical parameters associated with well-mixed plume. 

Limited model/monitor comparison study information supports volume source 

Recommended Volume Source Configuration: 

o Adjacent Volume Source 

1 Ambient Air is defined at 40 CFR Part 50.1 (e) and further clarified in a December 19, 1980 from 

Douglas Costle to Senator Jennings Randolph. See http://www.epa.gov/scram001/guidance/mch/ama4.txt 

4 
o Top of Plume Height2 - 1.7 x VH 

o Volume Source Release Height- 0.5 x Top of Plume height 

o Width of Plume- VW + 6m for single lane roadways I Road Width+ 6m 

for two lane roadways3

. 

o Initial Sigma Z- Top of Plume /2.15 AERMOD User's Guide, Table 3-1 

for use when modeling multiple volumes. 

o Initial Sigma Y- Width of Plume /2.15 AERMOD User's Guide, Table 

3-1 

o Emissions input as g/s 

• The I. 7 factor in the Top of Plume Height equation above is supported by 

information in a 2005 Atmospheric Environment paper by Gillies, et. al, entitled 

Effect of Vehicle Characteristics on Unpaved Road Dust Emissions. 

• The Width of Plume value is based on a conservative adaptation of monitor 

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 nearer than 3 meters from the roadway edge to account for 

vehicle turbulence. Two-lane roadways are for cases with heavy two-way traffic 

where the combined plume needs to be approximated. Agencies may need to 

consider traffic counts, vehicle width, road width, and the amount of two-way traffic, 

in order to determine whether the roadway is best represented using single-lane or 

two-lane assumptions. While the workgroup's sensitivity analysis indicates 

increased volume source width leads to decreased concentrations, our group didn't 

specifically examine single-lane versus two-lane roadways. One option is to model 

two-lane roadways as two, single-lane volume sources. 

• For cases where ambient air receptors fall within the volume source exclusion zone, a 

conservative volume source approach would be to reduce the width of plume 

dimensions enough so that the ambient air receptors are not inside the exclusion zone. 

Additionally, a mix of area sources and volume sources may adequately allow for 

consideration of all ambient air receptors. 

Area Source- Recommended for haul roads where ambient air receptors are 

located within source dimensions. 

Rationale: 

Volume source doesn't allow placement of receptors within exclusion zone. 

Area source can calculate concentrations at receptors within source. 

Area source can simulate volume source with use of similar release height and 

Sigma Z parameters. 

2 Gillies, J.A., V. Etyemezian, H. Kuhns, D. Nikolic, D.A. Gillcte, 2005. Effect of Vehicle Characteristics 

on Unpaved Road Dust Emissions. Atmospheric Environment, 39, 2341-234 7 3 EPA. 1992. Guideline for Modeling Carbon Monoxide From Roadway Intersections. EP A-454/R-92-

005. http://www.epa.gov/scramOOI/guidance/guide/coguide.pdf 

5 
Recommended Area Source Configuration 

o Length - length of roadway segment (Aspect ratio 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 I Road Width + 6m for two-lane (same 

comment as for volume, two single-lanes is an option) 

o Top of plume height -1.7 x VH 

o Release height- 0.5 x top of plume height 

o Sigma Z- Top of Plume height I 2.15 

o Emissions input as glslm2 

Point Source- The workgroup is not forwarding any point source recommendation 

at this time. There are potential benefits to this approach, however, more study is 

needed. 

Future Efforts 

The workgroup understands that efforts are underway on a line source algorithm to be 

included in AERMOD. The time frame for completion of this work may be within the 

next couple years. A new line source algorithm would likely supplant the need to model 

haul road fugitive dust emissions using either volume, area, or point sources. 

Point source modeling of fugitive roadway emissions has some potential benefits, as 

noted earlier in this paper. One example is the ability to consider the influence of facility 

structures located near roadways when simulating the roadway fugitive dust in 

AERMOD. The Haul Road Workgroup supports further study of this approach. 

More field studies examining initial plume dimensions are encouraged. The effects of 

vehicle speed on the initial plume dimensions is an area that should be investigated when, 

or if, more field studies are conducted. 

6 
References 

Brode, R.W., Improved Algorithms for Modeling Impacts Near Roadways. 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. Modeling Fugitive Dust Impacts from Surface Coal Mining OperationsPhase II. EPA-454/R-94-025 

Eskridge, R. E., Thompson, R.S., 1982, Experimental and Theoretical Study of the Wake 

of a Block-Shaped Vehicle in a Shear-Free Boundary Flow. Atmospheric Environment, 

16, 2821-2836 

Fitz, D. R., 2001. Measurements ofPMIO and PM2.5 Emission Factors from Paved 

Roads in California. Contract No. 98-723. California Air Resources Board, Monitoring 

and Laboratory Division 

Gillies, J.A., V. Etyemezian, H. Kuhns, D. Nikolic, D.A. Gillete, 2005. Effect of Vehicle 

Characteristics on Unpaved Road Dust Emissions. Atmospheric Environment, 39, 2341-

2347. 

Guideline on Air Quality Models, US Environmental Protection Agency, 40 CFR Part 51, 

Appendix W, November 9, 2005. 

Heinerikson, A., Goodman, A., Anderson, K., Analysis of Haul road Emission Test Data 

for Determining Dispersion Modeling Parameters. Trinity Consultants. 

Reed, W. R., Performance Evaluation of a 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 

Protection Agency, EPA-454/B-03-001, September 2004. 

Westbrook, J.A., Sullivan, P.S., Fugitive Dust Modeling with AERMOD for PMIO 

Emissions from a Municipal Waste Landfill. 

Williams, D.S., Manoj, K.S., Ross, J., Particulate Matter Emission by a Vehicle Running 

on Unpaved Road. 2008. Atmospheric Environment, 42, 3899-3905. 

7 
Select Slides from May 2010 RegionaVState/Local Workshop Presentation 

Sensitivity Analysis Work 

11 Used AERMOD Version 09292 

1111 1 year of meteorological data (variety of 

locations) 

11 N-S and E-W crisscrossing road segments. 

Each 500m long, 10m wide. 

11 Flat Terrain 

11 Receptor Grids - Cartesian and Polar; 

beginning as near as possible to the volume 

sources. 1 meter from edge of area source. 

No receptors within source. 

Cont. 

11 Unit emission rate 

11 Evaluated range of values for top of plume 

height, Sigma Z, Sigma Y, and release 

height. 

1111 Modeled using Adjacent Volume, Alternate 

Volume, and Area source representations. 

11 Calculated results for annual ave, peak 1 hr, 

8th H 1hr, peak 24hr, 8th H 24hr, 
Receptors and Roadway 

. ... ... . . . . ... . . . ... ·: . ... . . .. ii ... . . . ... . . . . . . .. . . . . . .. . . . :· . ~ '• . • . . . . • . . ! . . . .. . . . . . . :·: l . . . . . . . . . . . . . . . . ~! . . . ... . . . . ... :·: . :. :-_.:•: -

I ... . . . . - . .. . . . . . . . . . . . . . . . . . . . . . . . :.: . : . . . . . . .. 1 . . . . . . . .. . i ·- . . . . -.. .. . . ~ . . . . . . , . ·= . . . ... . ... . . . =· . ... . . : •! . .. . . ,, . . ... . .. . . . ... . . . . .. . ... . 

i.j, Matrix of Values for Analysis 

Top of Plume Height /2.15 

10m/2.15 16m/2.15 

Top of Plume Height /2 

2 
I 

I 

~--~---- ------~-~~- -----

0 

t4 

05 t5 25 

._.._ltllgt ... 

35 5 

7.44 

3 

OSglaY=t4n 

DRi=On 
i 

Ill 

I 

0 

f 

\4 

05 35 

4 

5 

D9g111Y=1An 

09g111Y= 

DRi=1. 

ORi=2 

1Ri=3 

1Ri=5n 
.. 

I! llfti-Qn - I 1111=1 

1111= 

-· -!in 

5 
30000 

r 

' I 

Am Source -1STD1H_BOTH 

Ro..t Dlmenak)n Change 

0.5 15 

rt. .... Nlligbl ... ) 

ArN!Iour<o -1ST01 H_IIOTH 

Chonglng- Holght 

NoSigmoZ 

6 

3.5 

DRH•O.Om 

ORH• O.&n 

.RH .. Him 

•RHz3.5rn 
-· ··--t-· ...__. ....... ·--·· , ...... ) 

.-...,.a .. ~-· .tno,,.. ooc-TM .. _;z.:; .... _ ........ -, ... 

Adj8cent Volume 

Annual Average 

....,.. __ .._.__,., !.ar<.~o ... """'''' 

,.,..,,.,~ r a.-.. -,.,...,- "«;~ 

ele ... Ht.- &n I Sigma Z- 4.86/ Sigma V- 4.86 

·--~ ..... _ ........ MAX. CONCENTRATION - 89 ug/m3 

7 

= 
c ... study 

7m Top of Plume/10m Plume Width 

8lh High 24-llour Ave. 

Scenarios 

Adjoc:Ht¥1-

1-llr Avonlgo ........ 

8 
·JID 

--

1-illl-·46$ 

VOlume Source 

•Ill 

9 

0 

~aa•e~n 

-....a.+TUt•n 

t.+lkm 

........ -:~» ...... -+-Miiue•n 

w.n. 7.«••• 

---u .. •& 

11.118••• 
Haul Road as Point Sources 

13 Ran AERMOD using point sources to 

represent haul road 

r! Flatterrain 

~a Assume building with dimensions of 3m x 3m 

x 1Om -oriented along roadway. 

1!11 Locate point at each comer of building- 384 

total stacks. 

ra 1 g/s emissions distributed among stacks 

Continued ... 

n Stack height= 1.5m and 3.5m 

ffi! Temperature= ambient 

m Velocity= .001 m/s 

s Diameter= 0.5m 

lrJ Receptors- cart. -start 11m from center of 

road at 25m resolution plus 1 0 degree polar 

at 250m at 50 m resolution 

10 
., ..... 

POINT SOURCE WITH DOWNWASH .. -···- ------ -··-· -----·-----· Annual Avenage lack Ht.- 1.5m I Dlam. - 0.5m I Ambient T I Vel. - 0.001 

c ....... 7m Top ot Plune /111m Pluna Wdlh 

8th H~Uhou' Ave. 

11 

--

.. 

--,. 

,. 

,. 

,. 

,. 

-
-

-

General Conclusions 

for Sensitivity Analysis Runs 

ill lnaeasing RH (release height) always led to lower 

concentrations. 

ill Increasing Sigma Y for alt. and adj. volume sources 

lowered concentrations. 

1111 For area source- increasing X dimension lowered 

concentrations atO and 0.5 RH, at 1.5 and 3m RH, 

had little impact on concentrations. 

1111 For area source- adding a sigma z lowered 

concentrations forO RHs, but usually increased 

concentrations at 1.5 and 3.5 RHs, mixed results for 

0.5mRH. 

Cont. 

11 For volume runs, adjacent gives higher 

concentrations than alternate. 

11 Point Source -limited modeling shows 

sensitivity to stack height; little sensitivity to 

stack diameter. 

11 On-site met data runs showed same trends 

as NWS, although concentrations higherwith 

on-site. 

12 
APPENDIXG 

Protocol to Support the use of Airport Meteorological Data 

For Sanders Lead Modeling 
Protocol to Support the use of Airport Meteorological Data 

For Sanders Lead Modeling 

One of the 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 of useful 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 of conditions at the modeling site. 

This test of representativeness 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 of measurements 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 of conditions 

affecting the transport and dispersion of pollutants in the area of interest as determined by 

the locations of the sources and receptors being modeled." Establishing representativeness 

balances the requirements of the 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 of many similarities between a source located in a modeled 

county and the nearby airport. The similarities tests would have included potential effects 

of terrain 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 of relatively 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 Gulf Coastal 

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 from just using different years of 

meteorological data. 
Based on the presumed suitability of the meteorological data for sources located near the 

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 

of albedo, 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, of 2005 were modeled in AERMOD using the two 

meteorological data sets to understand the relative importance of the 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 of concentration 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 of maximum 

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 of maximum impacts for the I st quarter of 2005. 

Both datasets produce highest values at the fence line and at the same receptor location. 

Table 1 compares 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 of the representativeness of data 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 of maximum 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 0.592 
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 

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 0.170 
Sanders Lead 

Troy, Alabama 

URS URS Corporation- North Carolina 

1600 Perimeter Park Drive 

Morrisvilfe, Nol1h Carolina 27560 

Telephone (919)461-JJOO Fax (919)461-1415 

Location of Airport 

& Site 

File No. 

20499427 

Figure I 
Sanders Lead 

Troy, Alabama 

SCALE: 

as shown 

URS URS Corpon~lion • North Carolina 

/600 Perimeter Park 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-km from Airport & 

Plant Site 

FILE NO. 

2049942 

FIG. NO. 

2 
Sanders Lead 

Troy, Alabama 

SCALE: 

na 

URS URS Corporation - North Carolina 

1600 Perimeter Parle 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 P astureJHayJC rops 

• 85 to 85 Urban Grass 

• 90 to 91 \Mlody/Otler Wetlan:::ls 

FILE NO. 

AERSURFACE Output 

Surface Roughness 

Landuse Distribution 

2049942 

FIG. NO. 

Airport 3 
Sanders Lead 

Troy, Alabama 

SCALE: 

na 

URS URS Corporation - North Carolina 

1600 Perimeter Park 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: 

Lan duse- 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 

w ate• 

C< 

Tc 

esidential 

anmJlndL.Et/Trans 

:ansitional 

Fo "'"' Pa sb..reiHay/Crq)s 

U• 

W• 

rb.., Grass 

oOOy/OtherWetlan::ls 

AERSURFACE Output FILE NO. 

Surface Roughness 2049942 

Landuse Distribution FIG. NO. 

Plant Site 

(4 square kilometer area) 4 
Sanders 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 

1600 Perimeter 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 1st Quarter 

(with Airport and Site Landuse) 

FILE NO. 

2049942 

FIG. NO. 

5