## APPENDIX E Surface Characteristics Re presentativeness Analysis

### Protocol to Support the use ofAirportMeteorological Data For Sanders Lead Modeling

One ofthe more importantinputs 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 layerparameters which help define atmospheric stability and mixing height development. The more meaningful the meteorological inputs, the greaterthe likelihood ofuseful results. Recognizing that not all locations have access to meteorological data, EPA developed methods whereby data obtained not at the site, butfrom another locale, couldbeused if shown to be reasonablyrepresentative ofconditions at the modeling site.
This test ofrepresentativeness has been described in EPA guidance (Guideline on Air Quality Models) (40 CFR 51 Appendix W) and AERMOD/AERMET implementation guidance, including the mostrecent version issued March 19, 2009. The test of representativeness was originallyintended in the Guideline on Air Quality Models to include both a spatial and temporal componenttogetherwith a suitability component. In the EPAMeteorological Monitoring Guidance for Regulatory Modeling Applications, representativeness has been defined as "the extent to which a set ofmeasurements taken in a space-time domain reflects the actual conditions in the same or different space-time domain taken on a scale appropriate for a specific application."
The meteorological monitoring guidance continues to saythat "

...for use in airquality modeling applications, meteorological data should be representative ofconditions affecting the transport and dispersion ofpollutants in the area ofinterest as determined by the locations ofthe sources and receptors being modeled." Establishingrepresentativeness balances the requirements ofthe modeling assessment with the reasonableness of meteorological data acquisition.
BecauseADEM modeling guidancerecommends meteorological data from the Montgomery Airport for sources located in Pike County, Alabama, itis assumed the data has previously undergone a "representativeness" review byADEM. This ADEMreview may have included areview ofmany similarities between a source located in a modeled county and the nearby airport. The similarities tests would have included potential effects ofterrain on regional flow patternsbetweenthe two sites and changes in climatology betweenthe two areas. Because the Sanders Leadfacility and Airport are both located in an area ofrelatively simple terrain, no major changes in regional airflow would be expected. Also, since the Airport and plant site are both located in the East GulfCoastal Plainregion, only small changes in climatology and other weather related factors would be expected therefore the space-time domain factors shouldbe representative. Localized differences in some surface boundary layerparameters (i.e., albedo, Bowen ratio, and surfaceroughness) between the two sites wouldbe expectedbut not to a degree that would exceed changes in predicted concentrations often noted fromjustusing different years of meteorological data.Based on the presumed suitability ofthe meteorological data for sources located nearthe Montgomery Regional Airport, the ADEM processed the data using AERMET (version 06341) along with upper air data from Alabaster, Alabama, to form a 5-year meteorological record (2001-2005). The data was processed using geophysical surface parameters associated with the airport. This information was developed byusing the AERSURF ACE program which generates surface boundary layer parameters in the form ofalbedo, Bowen ratio, and surface roughness.
Forthis protocol, Sanders Lead duplicated the AERMETprocessing for one year (2005) butused boundary layer parameters generated by AERSURFACEbased on land use patterns aroundthe facility.
The first quarter orfirst three months, of2005 were modeled inAERMOD using the two meteorological data sets to understand the relative importance ofthe chances in AERSURFACEprocessing to predicted ambient concentrations. Forthis analysis, only point sources were evaluated. Emissionrates used in this initial evaluation were based on current allowable emission estimates. These may ormay notbe a good estimate of "actual" potential emissionrates from the facility. Actual emissions rates are under review, atthis time. Using the allowablerates supplied abasis for conducting the modeling only. No actual concentration estimates are reported. Results are presented on a "relative"basis in the form ofconcentration isopleths.
The initial modeling results indicate there wouldbe about a 22 percent change in predicted concentrations using the different data sets. However, the location ofmaximum impactremains the same. Themeteorological 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 1and Figures 1thru 4). It wouldbeexpected that elevatedplumes would experience greater instability with greater surfaceroughness and therefore cause higherimpacts near the plant site. Figure 5 displays the location ofmaximum impacts for the 1st quarter of2005. Both datasets produce highest values at the fence line and at the samereceptorlocation.
Table 1compares the differences in the boundary layerparameters at the airport andplant site. The information has beenbroken down into 12 sectors and 4 seasons.
A strong indication ofthe representativeness ofdatacollected at the airport for modeling the plant site is the relatively small changeinpredicted impacts from the AERMOD model using the two meteorological data sets. The airport data is considered "representative" since the location ofmaximum impacts are the same and a 22 percent change in predicted concentrations would be areasonable variation frequently seen in year to yearvariation overlong-term averaging periods when modeling.
As recommendedbythe ADEM, both AERSURFACE data sets will be used for future modeling and the data set producing thehighest predicted concentrations will be reported. This is a conservative modeling assumption.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 1 1 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 I 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 1 0.17 0.15 0.71 0.81 0.041 0.186 7 I O.I7 O.I5 0.7I 0.81 0.02I O.I58 8 I O.I7 0.15 0.7I 0.8I O.OI8 0.201 9 I O.I7 O.I5 0.7I 0.81 0.015 0.503 IO I 0.17 O.I5 0.7I 0.81 0.024 0.532 11 I 0.17 0.15 0.71 0.8I 0.039 0.199 I2 I 0.17 O.I5 0.7I 0.81 0.07I 0.139 I 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 0.7I 0.8I 0.031 0.238 4 2 0.17 0.15 0.71 0.8I O.OI9 0.445 5 2 0.17 O.I5 0.7I 0.81 0.019 0.508 6 2 0.17 O.I5 0.7I 0.81 0.04I 0.186 7 2 O.I7 0.15 0.7I 0.8I 0.02I 0.158 8 2 O.I7 O.I5 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 0.8I 0.039 0.199 12 2 0.17 0.15 0.7I 0.8I 0.07I O.I39 1 3 O.I4 O.I4 0.38 0.56 0.1I4 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 O.I4 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 O.I4 O.I4 0.38 0.56 0.027 0.248 9 3 0.14 0.14 0.38 0.56 0.022 0.592AERSURFACE Processing Bowen Bowen Surface Surface

Surface Albedo Albedo Ratio Ratio Roughness Roughness Geophysical Season Airport Sanders Airport Sanders Airport Sanders Lead Lead Lead Parameters Sector 10 3 0.14 0.14 0.38 0.56 0.032 0.626 11 3 0.14 0.14 0.38 0.56 0.050 0.255 12 3 0.14 0.14 0.38 0.56 0.090 0.170 1 4 0.14 0.14 0.38 0.56 0.114 0.324 2 4 0.14 0.14 0.38 0.56 0.066 0.404 3 4 0.14 0.14 0.38 0.56 O.D38 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 O.Q28 0.635 6 4 0.14 0.14 0.38 0.56 0.050 0.238 7 4 0.14 0.14 0.38 0.56 0.030 0.192 8 4 0.14 0.14 0.38 0.56 0.027 0.248 9 4 0.14 0.14 0.38 0.56 0.022 0.592 10 4 0.14 0.14 0.38 0.56 0.032 0.626 11 4 0.14 0.14 0.38 0.56 0.050 0.255 12 4 0.14 0.14 0.38 0.56 0.090 0.170Sanders Lead Troy, Alabama URS Corporation

- North Carolina 1600PerimeterParkDrive Morrisville, North Carolina 27560 Telepllone (919)461-1100 Fax (919)461-1415 SCALE: DRAWN BY: SCL DATE: 8/4/09 NA CHECKED BY: DATE: 

### Location ofAirport & 

### Site File No. 20499427
Figure 1SandersLead Troy, Alabama SCALE: as shown White line = 1 km 

# URS

URS Corporation

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

### Aerials Extending 1-kmfrom Airport & 

### PlantSite FILE NO.
2049942 FIG. NO. 260

50

SandersLead Troy, Alabama SCALE: na 

# URS

URS Corporation

- North Carolina 1600PerimeterParkDrive Morrisville, North Carolina 27560 Telephone (919)461-IIOO Fax(919)461-1415 DRAWN BY: SCL DATE: 8/4/09 CHECKED BY: DATE: Ill Land use Classes 

# • 23 to 23 Ccmmllndustffrans IIIII 41 to 43 Fore.t .81 to 82 P.asture1Hay/Crops II 85 to 85 UrbanGrass 

# • 90 to 91 \1\body/OiherWetlan:ls

FILE NO. 

### AERSURFACE Output SurfaceRoughness LanduseDistribution 2049942 FIG. NO. 

### Airport

kil 3SandersLead Troy, Alabama SCALE: na 

# URS

URS Corporation- North Carolina 1600PerimeterParkDrive Morrisville, North Carolina 27560 Telephone (919)461-1100 Fax(919)461-1415 DRAWN BY: SCL DATE: 7/9/09 CHECKED BY: DATE: Landuse. Classes 11 to 11 llilll 21 to 22 

# • 23 to 23 33 to 33 

# • 41. to 43 81 to 82 Ill 85 to 85 

# • 91 to 92 Water esidential cem m.-1ndustn-ral"lS ransitional T F p u ors asture/Hay/Crcps rb.:n Grass Woo:ly/OtherWetlards



### AERSURFACE Output FILE NO. 

### SurfaceRoughness 2049942 

### LanduseDistribution FIG. NO. 

### PlantSite (4 squarekilometer area) 4Sanders Lead Troy, Alabama SCALE notshown \u

/ I ,./A-·

/
With Site Landuse Data

0 0

... Max. Location

Max. Location

I i.-

-- - -- ) / I \---

With AirportData 

# URS

URS Corporation
- North Carolina 1600PerimeterParkDrive Morrisville, Norlh Carolina 27560 Telepho11e (919)461-1100 Fax(919)461-1415 cl

A

- - - - -- - ----

Maximum Receptor Location

DRAWN BY: SCL DATE: 8/4/09 2005 1st Quarter (with Airport and Site Landuse) CHECKED BY: DATE: FILE NO.
2049942 FIG. NO.
5