2010 Primary Sulfur Dioxide (SO2) 

National Ambient Air Quality Standard (NAAQS)

Technical Analyses and Information Supporting the 

Designation Recommendation for Oklahoma

Source-Oriented SO2 Monitoring Placement for the Area of 

Muskogee, Oklahoma

Modeling Analysis Report

Prepared by the Engineering Section of the Permitting Unit

Air Quality Division

Oklahoma Department of Environmental Quality

September 4, 2015
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma i

TABLE OF CONTENTS

2010 Primary Sulfur Dioxide (SO2)............................................................................................. 1

National Ambient Air Quality Standard (NAAQS)................................................................... 1

Technical Analyses and Information Supporting the................................................................ 1

1. INTRODUCTION................................................................................................................... 1

1.1 Why Is A Monitoring Placement Modeling Analysis Being Conducted?.................... 1

1.2 What Is The Background For The Analysis?................................................................. 1

1.3 What Is The Background Of The Current Muskogee SO2 Monitor?.......................... 1

2. AIR DISPERSION MODELING SELECTION.................................................................. 2

2.1 What Is The Recommended Air Dispersion Model? ..................................................... 2

3. MODEL DOMAIN SETUP ................................................................................................... 3

3.1 How Was The Modeling Domain Established?.............................................................. 3

3.2 How Was The Receptor Grid Established?.................................................................... 3

3.3 What Emission Rates Were Used In The Modeling Analysis?..................................... 3

3.4 What Terrain Was Utilized For The Modeling Analysis? ............................................ 4

3.5 What Was The Domain Classification: Rural Or Urban?............................................ 4

4. SOURCE DATA...................................................................................................................... 4

4.1 What Are The Modeled Source Configurations And Source Types? .......................... 4

4.2 What Are The Effected Source Emissions Inputs?........................................................ 5

4.3 How Will GEP Stack Height Be Addressed? ................................................................. 5

4.4 Is Building Downwash Included In The Modeling Analysis?....................................... 5

5. METEOROLOGICAL DATA .............................................................................................. 6

5.1 What Meteorology Data Was Used? ............................................................................... 6

5.1.1 How Were Sites From The ISHD Evaluated? .................................................. 7

5.1.2 Was AERMINUTE Utilized In The Modeling Analysis.................................. 7
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma ii

5.1.3 What Is Oklahoma Mesonet Data And How Was It Utilized? ....................... 7

5.1.4 What Upper Air Data Was Used? ..................................................................... 7

5.1.5 How Were Surface Characteristics Determined? ............................................ 7

5.1.6 What Was Used To Determine The Surface Moisture Conditions?............... 8

6. MODEL ANALYSIS .............................................................................................................. 8

6.1 What Were The Initial Results Utilized In The Analysis?............................................ 8

6.2 Why Was Frequency Accounted For In The Analysis? ................................................ 9

6.3 How Was Frequency Analyzed Utilizing the MAXDAILY Option? ........................... 9

6.4 How Was Frequency Analyzed Utilizing The POSTFILE Option?............................. 9

7. RESULTS .............................................................................................................................. 10

7.1 What Are The Results From The Daily Scoring Analysis?......................................... 10

7.2 What Are The Results From The Hourly Scoring Analysis? ..................................... 11

7.3 How Does The Monitor Receptor Compare To The Scoring Analysis?.................... 13

8. SUMMARY ........................................................................................................................... 14

8.1 What Is The Summary Of This Analysis?.................................................................... 14

8.2 What Can Be Concluded From This Analysis ............................................................. 15

9. REFERENCES...................................................................................................................... 16

APPENDIX A DOMAIN LOCATION ............................................................................... A-1

APPENDIX B RECEPTOR GRID...................................................................................... B-1

APPENDIX C LAND COVER CLASSIFICATION (NLCD 1992)................................. C-1

APPENDIX D AERIAL IMAGE WITH FACILITY DATA ........................................... D-1

APPENDIX E SOURCE DATA .......................................................................................... E-1

APPENDIX F METEOROLOGICAL DATA ....................................................................F-1

APPENDIX G WIND ROSE................................................................................................G-1

APPENDIX H SURFACE CHARACTERISTICS ............................................................H-1
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma iii

APPENDIX I NORMALIZED DESIGN VALUE RESULTS.......................................... I-1

APPENDIX J TOP 200 RECEPTORS................................................................................ J-1

APPENDIX K MAXIMUM DAILY FREQUENCY .........................................................K-1

APPENDIX L MAX HOURLY FREQUENCY................................................................. L-1
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 1

1. INTRODUCTION

1.1 Why Is A Monitoring Placement Modeling Analysis Being Conducted?

This analysis is being conducted to identify suitable 1-hour SO2 source-oriented monitoring site 

locations for the 2017-2019 monitoring intended to satisfy the Data Requirements Rule in 

Muskogee County, Oklahoma.

1.2 What Is The Background For The Analysis?

Under the Clean Air Act (CAA), as amended in 1990 under Section 110 of the CAA (40 CFR 

Part 51, Subparts F & G), each state must develop a State Implementation Plant (SIP) describing 

how it will attain and maintain the NAAQS, which is required. In general, the SIP is a collection 

of programs, including:

• a monitoring program, which is a collection of monitoring devices throughout the country 

which provide actual measurements of the concentrations in the air, to identify whether 

an area is meeting the air quality standards, and if not, what reductions are needed to 

meet those standards; and

• air quality calculations and computer modeling, which are used to predict future trends 

and the effects of emissions reduction strategies.

On June 22, 2010, the United States (US) Environmental Protection Agency (EPA) revised the 

primary sulfur dioxide (SO2) National Ambient Air Quality Standard (NAAQS). The EPA 

promulgated a new 1-hour daily maximum primary SO2 standard at a level of 75 parts per billion

(ppb), based on the 3-year average of the annual 99th percentile of 1-hour daily maximum 

concentrations. 

On May 13, 2014, the EPA proposed the Data Requirements Rule (DRR) for the 1-Hour SO2

NAAQS. The final DRR was signed on August 10, 2015 and requires states to gather and 

submit to the EPA additional information characterizing SO2 air quality in areas with larger 

sources of SO2 emissions (79 FR 27445). In the DRR, air agencies have the choice to use either 

monitoring or modeling to characterize SO2 air quality in the vicinity of priority SO2 sources, 

and submit the modeling and/or monitoring to the EPA on a schedule specified by the rule.

1.3 What Is The Background Of The Current Muskogee SO2 Monitor?

The current source oriented SO2 monitoring site (40-101-0167) located in Muskogee, Oklahoma 

was established at its current location in 1981. EPA Region 6 issued a PSD permit (Permit No. 

PSD-OK-057) for Unit 6 at the OG&E Muskogee Generating Station on November 30, 1977. 

Modeling was included in the permit application which utilized the Tennessee Valley Authority 

(TVA) Climatological Dispersion model and the EPA CRSTER plume dispersion model. Output 

from these models and the EPA technical document “Optimum Site Exposure Criteria for SO2

Monitoring” (EPA-450/3-77-013), issued April 1977, were used to inform the Oklahoma State 

Department of Health, Air Quality Division where to locate the SO2 monitoring site.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 2

Locations of the maximum concentrations were calculated by the models utilizing representative 

atmospheric data, and with Units 4, 5, and 6 at 100% of their operating load. The table below 

shows the distance and direction information presented in the PSD permit application.

Table 1-1: PSD-OK-057 Modeling Results

Model Averaging 

Period

Unit 4 & 5 Unit 6

Distance Direction* Distance Direction*

(m) (°) (m) (°)

TVA Coning Maximum 2,500 N/A 4,500 N/A

TVA Fumigation Maximum 7,800 N/A 9,200 N/A

EPA CRSTER 3-hr 800 15 1,800 15

24-hr 3,500 1 1,300 8

N/A – Not Available.

* Direction is presented in degrees clockwise from north.

The SO2 monitoring site is currently located 3.7 km at a bearing of N19.1°W from the center of 

the three stacks for Units 4, 5, and 6 at the OG&E Muskogee Generating Station.

2. AIR DISPERSION MODELING SELECTION

2.1 What Is The Recommended Air Dispersion Model?

As described in the EPA SO2 NAAQS Designations Source-Oriented Monitoring Technical 

Assistance Document (Monitoring TAD), modeling to inform monitoring placement should 

follow the recommendations of the SO2 NAAQS Designations Modeling Technical Assistance 

Document (Modeling TAD). The modeling TAD essentially states that given the sourceoriented nature of SO2, dispersion models are appropriate air quality modeling tools to predict 

the near-field concentrations. Since the purpose of this analysis is to conduct modeling to inform 

monitor placement, the AMS/EPA Regulatory Model (AERMOD) was used, as suggested in the 

Monitoring TAD. AERMOD is the preferred air dispersion model because it is capable of 

handling rural and urban areas, flat and complex terrain, surface and elevated releases, and 

multiple sources (including, point, area, and volume sources), to address ambient impacts for the 

designations process.

The AERMOD modeling system includes the following components:

 AERMOD (Version 14134): the dispersion model;

 AERMAP (Version 11103): the terrain processor for AERMOD; and

 AERMET (Version 14134): the meteorological data processor for AERMOD.

Other components that were used:

 BPIPPRIME (Version 04274): the building input processor;

 AERMINUTE (Version 14337): a 1-minute ASOS winds pre-processor to AERMET;

 AERSURFACE (Version 13016): the surface characteristics processor for AERMET.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 3

3. MODEL DOMAIN SETUP

3.1 How Was The Modeling Domain Established?

The domain is centered over the OG&E Muskogee Generating Station. Based on EPA guidance, 

the general guideline for determining the distance between an affected source and its maximum 

ground level concentration is generally 10 times the stack height in flat terrain. However, the 

potential influence of terrain can impact the location and magnitudes of significant concentration 

gradients. The following table shows each emissions unit at the affected facility, the stack height 

for the emissions unit, and the expected distance to the expected maximum ground level 

concentration in flat terrain.

Table 3-1. Expected Distance to Maximum Modeled Concentrations of Affected Units

Company/Facility Stack Stack Height.

(ft)

Distance 

(km)

OG&E/Muskogee Generating Station Unit 4 350 1.07

Unit 5 350 1.07

Unit 6 500 1.52

The example presented in Appendix A of the Monitoring TAD suggests establishing a domain 

out to 20 km. However, since the maximum impact is expected to be between 1 km and 2 km, a

domain of 10 km was established. Figures showing the location of the domain with respect to 

the state and counties are included in Appendix A.

3.2 How Was The Receptor Grid Established?

A Cartesian receptor grid was generated from the fence line of the OG&E Muskogee Generating 

Station extended out to a distance of 10 km with a receptor spacing of 250 meters as suggested in 

the example presented in Appendix A of the Monitoring TAD.

Receptors in the generated grid that were within the fence lines of the modeled facilities and that 

are in areas not suitable for the placement of a permanent monitor such as open water (i.e., 

rivers, lakes, streams, ponds, etc.) were removed from the model.

In addition to the Cartesian receptor grid, an additional receptor was placed at the location of the 

existing 1-hour SO2 Muskogee monitor. Adding this receptor to the model will enable the 

analysis to compare the best modeled monitoring site locations with the existing Muskogee 

monitor location (Site ID 40-101-0167).

Figures showing the generated receptor grid are included in Appendix B. 

3.3 What Emission Rates Were Used In The Modeling Analysis?

Following the example in Appendix A of the Monitoring TAD, normalized emission rates were 

used in the model. Normalizing emissions inputs relies on the linear scalability of emission 
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 4

inputs to modeled concentrations and therefore provides relative model results to assess the 

location of maximum concentration gradients.

The normalized emission inputs were generated by dividing the actual emission rates of each 

emission unit by the largest emission rate of all the emission units. Actual emission rates for 

OG&E were based on the 99th percentile of CEM data from 2012 to 2014. Actual emissions for 

nearby sources were based on the three year average of actual emission rates from each emission 

unit from 2012 to 2014.

3.4 What Terrain Was Utilized For The Modeling Analysis?

Terrain data was included in this modeling analysis. Terrain data was obtained from the USGS 

Seamless Data Server at http://viewer.nationalmap.gov/viewer/. The 1/3 arc-second NED data 

was obtained in the GeoTIFF format for use in AERMAP. Interpolation of receptor and source 

heights from the 1/3 arc-second NED elevation data was based on the current AERMAP 

guidance in Section 4.4 of the User’s Guide for the AERMOD Terrain Preprocessor (AERMAP) 

(EPA-454/B-03-0003, 10/2004). AERMAP uses a distance weighted bilinear interpolation 

method. The domain was located in UTM zone 15. All coordinates were based on the North 

American Datum (NAD) of 1927 (NAD27).

3.5 What Was The Domain Classification: Rural Or Urban?

Dispersing plumes encounter more turbulence in urban areas than in rural areas due to building 

wakes as well as warmer temperatures. The higher dispersion in urban areas causes plumes to 

spread more rapidly. The areas of maximum impact in urban areas occur closer to the source. 

Determination of whether the domain should be classified as urban or rural was based mainly on 

land use (the preferred method). However, the urban heat island affect was reviewed for the 

facility. After an analysis of the domain, it was determined to be predominantly classified as 

rural. An aerial photo indicating the area surrounding the facility is included in Appendix C.

4. SOURCE DATA

4.1 What Are The Modeled Source Configurations And Source Types?

Accurate characterization of the affected sources is critical to air quality modeling. Stack 

parameters and physical plant layout (building and fence line data) were submitted by the 

affected facility and surrounding facilities with significant emissions of SO2. The submitted data 

was then reviewed and checked for errors. All of the affected sources are point sources. The 

location (i.e. latitude and longitude or Universal Transverse Mercator (UTM) coordinates and 

datum) of the modeled emission unit stacks were also reviewed along with relative location of 

the stacks to nearby buildings or structures. Additional data required for the model was collected 

from the AQD Emission Inventory database. 

Figures showing the facility data overlaid onto aerial photos are included in Appendix D.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 5

4.2 What Are The Effected Source Emissions Inputs?

In addition to the three coal-fired boilers located at OG&E Muskogee, the modeling domain 

included all nearby sources within 50 km having significant SO2 emissions. Since the standard is 

based on a three year average, modeling was based on the most recent three years of actual 

emissions. Actual emissions data for input into AERMOD was generated for each source in the 

model by utilizing the average of the most recent three years of actual emissions and normalizing 

the values based on the maximum emission rate as suggested in the Monitoring TAD. Ambient 

impacts from natural gas-fired sources were analyzed using AERSCREEN to show that they do 

not have a significant concentration gradient within the modeling domain. Source data used in 

the model is presented in Appendix E.

4.3 How Will GEP Stack Height Be Addressed?

Good Engineering Practice (GEP) stack height is the minimum stack height needed to prevent 

the stack exhaust plume from being entrained in the wake of nearby obstructions. For the 

modeling to inform monitor placement process, actual stack heights were used for modeling 

actual emissions rather than following the GEP stack height policy. The GEP stack height policy 

uses GEP stack height for stack heights exceeding GEP and actual stack height for stacks below 

GEP. The use of actual stack heights in the modeling analysis more closely represents actual 

ambient air quality conditions from the affected sources. Since the purpose of the modeling is to 

identify the most suitable locations for permanent monitor placement, the model needs to reflect 

actual stack heights of influencing sources.

4.4 Is Building Downwash Included In The Modeling Analysis?

When one or more structures interrupt the wind flow, turbulent cavities are formed in the 

downwind side of the building. These cavities can cause a plume from a nearby stack to be 

forced down to the ground much sooner than it would have if the wind flow were uninterrupted. 

This effect is called building downwash. Pollutants emitted at a fairly low level (e.g., a roof, 

vent, or short stack) can be caught in the building downwash, affecting their dispersion. 

Modeling that includes calculations for building downwash gives a more accurate representation 

of pollutant impacts than does modeling that omits consideration of downwash effects.

A building is any physical obstruction to airflow at the modeled facility. A structure is a 

building or group of buildings determined to be important in downwash considerations. The 

dominant downwash structure is the structure that renders the highest GEP recommended stack 

height. If a stack is at GEP or higher, then downwash is not a factor. GEP stack height is 

calculated according to the following equation.

H  h 1.5L

where: H = Recommended stack height.

h = The distance from the highest point on a tier or building to ground level.

L = The lesser of the height or projected width for a particular tier or structure.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 6

Not only are accurate stack parameters important but so are accurate building parameters. 

Building parameters include location and orientation relative to stacks and building size. Other 

parameters include tier heights and coordinates. These parameters are input into BPIP-PRIME to 

calculate building parameters for AERMOD. Affected facilities have submitted information 

regarding buildings located on their property. This data was reviewed and included in the 

modeling analyses.

5. METEOROLOGICAL DATA

5.1 What Meteorology Data Was Used?

The 2012-2014 meteorological data from the National Weather Service (NWS) Automated 

Surface Observation Station (ASOS) located at the Davis Field Airport (KMKO) in Muskogee 

was utilized for the 2010 1-hour SO2 primary NAAQS designations modeling.

When conducting air dispersion modeling, the State of Oklahoma generally utilizes 

meteorological data from the following:

 Oklahoma Mesonet Surface Data;

 National Centers for Environmental Information (NCEI), formerly National Climatic Data 

Center (NCDC), Integrated Surface Hourly Database (ISHD) Surface Data; and

 Earth System Research Laboratory (ESRL) Global Systems Division (GSD), formerly 

Forecast Systems Laboratory (FSL), Upper Air (UA) data.

Oklahoma Mesonet data is usually incorporated to help make more accurate forecasts of ambient 

impacts from modeled sources. Incorporation of Oklahoma Mesonet data makes the AERMETprocessed meteorological data more accurate because the datasets contain sub-hourly values and 

the sites are usually closer to the areas being modeled. Standard ISHD surface data usually only 

contains a single two minute average recorded during an hour whereas Oklahoma Mesonet 

datasets contain twelve five minute averages for each hour. There are a large number of 

Oklahoma Mesonet stations, which increases the potential of an Oklahoma Mesonet 

meteorological station being closer to the area being modeled. Generally, the closer a 

meteorological station is to an area, the more representative the meteorological data is to the area 

being modeled.

There are two types of ISHD surface stations; ASOS and Automated Weather Observation 

Stations (AWOS). All ASOS stations started recording continuous sub-hourly (2-minute 

averages) wind data in 2005. However, sub-hourly wind data for AWOS stations is not 

available. If an ASOS station is closer or more representative than the nearest Oklahoma 

Mesonet station, data from the Oklahoma Mesonet is not incorporated into the AERMET 

processed meteorological data. Oklahoma Mesonet meteorological data was not utilized in this 

analysis because the ISHD ASOS KMKO Station data is closer to and more representative than 

the nearest Oklahoma Mesonet station and sub-hourly wind data is available for the KMKO 

station. Information for the selected sites is included in Appendix F. A wind rose for the 

KMKO station is contained in Appendix G.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 7

5.1.1 How Were Sites From The ISHD Evaluated?

The ISH data files were downloaded from the NCDC ISHD web site: 

ftp://ftp.ncdc.noaa.gov/pub/data/noaa. The ISH data was reviewed for completeness by 

evaluating the number of hours that were recorded and the number of cloud cover values that 

were recorded. The KMKO ASOS station (at approximately 13.4 km S31.0°W from the center

of the domain) was determined to be the most representative site for the domain. The data from 

KMKO did not have a significant number of missing values for individual variables. Therefore, 

no missing data replacement was performed.

5.1.2 Was AERMINUTE Utilized In The Modeling Analysis

For this ASOS site, AERMINUTE data was utilized to incorporate continuous sub-hourly wind 

data. The ASOS (6405) files were downloaded and then processed using AERMINUTE. The 

ASOS 1-minute files were downloaded from http://www1.ncdc.noaa.gov/pub/data/ for each year.

5.1.3 What Is Oklahoma Mesonet Data And How Was It Utilized?

The Oklahoma Mesonet is a world-class network of meteorological monitoring stations. The 

Oklahoma Mesonet is unique in its capability to measure a large variety of meteorological 

conditions at so many sites across an area as large as Oklahoma. Oklahoma Mesonet data is 

provided courtesy of the Oklahoma Mesonet, a cooperative venture between Oklahoma State 

University (OSU) and the University of Oklahoma (OU) and supported by the taxpayers of 

Oklahoma. At each site, the meteorological conditions are continuously measured and packaged 

into 5-minute observations. These 5-minute observations from the Oklahoma Mesonet were 

processed into an AERMET acceptable format. The meteorological data from sites surrounding 

KMKO were utilized to evaluate the wind flow patterns in the Muskogee area. The Porter 

Oklahoma Mesonet station (at approximately 25.6 km N72.5°W from the center of the domain) 

was determined to be the most representative Mesonet station for the domain.

5.1.4 What Upper Air Data Was Used?

Selection of appropriate ESRL UA data to use in the meteorological data set was primarily based 

on proximity to the domain and included a review for missing soundings. The ESRL UA 

stations usually take soundings twice a day. A single missing sounding can cause a whole day 

(24 hours) of missing meteorological data values. To reduce the number of missing 

meteorological data, replacement soundings were substituted for the missing soundings. The 

replacement soundings were selected from a site with similar thermodynamic profiles. Upper air 

data from the Norman (OUN) site in Oklahoma (at approximately 206.75 km S75.4°W from the 

center of the domain) was determined to be the most representative site for the domain.

5.1.5 How Were Surface Characteristics Determined?

When using AERMET, to process meteorological data for AERMOD, three surface 

characteristics (Albedo, Bowen Ratio, and Surface Roughness Length) must be determined for 
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 8

the meteorological station. Albedo is the fraction of total incident solar radiation reflected by the 

surface back to space without absorption. Bowen ratio, an indicator of surface moisture, is the 

ratio of sensible heat flux to latent heat flux. Surface roughness length is related to the height of 

obstacles to the wind flow and is an important factor in determining the magnitude of mechanical 

turbulence and the stability of the boundary layer. Albedo and Bowen Ratio are used for 

determining planetary boundary layer parameters for convective conditions driven by the surface 

sensible heat flux.

AERSURFACE uses land cover data from the U.S. Geological Survey (USGS) National Land 

Cover Data 1992 archives (NLCD92) to determine the land cover types for a specified location. 

AERSURFACE matches the NLCD92 land cover categories to seasonal values of Albedo, 

Bowen Ratio, and Surface Roughness and then calculates the surface characteristics for input 

into AERMET. NLCD92 data in GeoTIFF format was downloaded from the Multi-Resolution 

Land Characteristics (MRLC) Consortium at the following link: http://www.mrlc.gov/viewerjs/. 

Seasonal surface characteristics are included in Appendix H.

5.1.6 What Was Used To Determine The Surface Moisture Conditions?

The monthly rainfall for each Mesonet site was analyzed from the beginning of the establishment 

of the Mesonet program (approximately 20 years). The surface moisture conditions (Average, 

Wet, Dry) for each of the Oklahoma Mesonet stations for each month were then determined 

using the monthly rainfall amounts compared to the average rainfall. These determinations were 

based on the guidance contained in the AERSURFACE Users Guide. The Bowen Ratio was 

then assigned as either average, dry, or wet based on the monthly surface moisture conditions for 

each Oklahoma Mesonet station. The surface moisture conditions for the ISHD stations were 

attributed to the surface moisture conditions of the Porter Oklahoma Mesonet station. Moisture 

conditions for each month are also included in Appendix H.

6. MODEL ANALYSIS

6.1 What Were The Initial Results Utilized In The Analysis?

Results from the model were calculated based on the three year average of each year’s 4th daily 

highest 1-hour maximum concentration (99th percentile of daily 1-hour maximum 

concentrations). These results are referred to as the normalized design values (NDVs) since 

normalized emissions were used to calculate these values. The resulting NDVs range from 

0.20793 μg/m3to 0.63730 μg/m3. A figure showing a ratio of the NDV of each receptor 

compared to the overall maximum NDV is included in Appendix I. 

From these results, the top 200 receptors were selected for further analysis. The top 200

receptors with the highest NDV were chosen in order to include the receptor at the monitor 

location in the analysis which had a NDV rank of 127. A figure showing the location of these 

top 200 receptors in the modeled domain is included in Appendix J. The most distant receptor in 

the Top 200 is approximately 6.52 km from the center of the three stacks at the OG&E 

Muskogee Generating Station.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 9

6.2 Why Was Frequency Accounted For In The Analysis?

Simply using the largest NDVs to identify the best monitor locations is not sufficient enough to 

determine proper placement of a monitor site. Therefore, the number of times, or frequency, 

each receptor is calculated to have the maximum daily 1-hour concentration was also considered. 

To account for frequency in the analysis, two separate analyses were conducted on the top 200

receptors. The first analysis utilized the MAXDAILY option in AERMOD to output the 

maximum 1-hour concentration of each receptor for each day. The second analysis utilized the 

POSTFILE option in AERMOD to output the maximum 1-hour concentration of each receptor 

for each hour.

6.3 How Was Frequency Analyzed Utilizing the MAXDAILY Option?

In order to identify favorable locations for a 1-hour SO2 monitor, the NDV was further analyzed 

in conjunction with the MAXDAILY output file by using a scoring strategy to create a relative 

prioritized list of receptor locations. This scoring strategy follows the example in Appendix A of 

the Monitoring TAD. 

In the first step of this analysis, the NDVs were ranked in descending order (with the largest 

value having a rank of 1). In the second step, the results from the MAXDAILY output option 

were used to determine the number of days for which each receptor was the overall highest 1-

hour concentration for the day for the three modeled years. A figure showing the frequency of 

receptors having the maximum daily results is included in Appendix K. The receptors were then 

ranked in descending order (with the largest value having a rank of 1) based on each receptor’s 

frequency of days having the overall highest daily 1-hour concentration. The third step was to 

add these two ranks together to obtain a score. The scores were then ranked in ascending order, 

giving the lowest value (having the greatest significance) a rank of 1. This score rank was then 

utilized to identify the most favorable locations for a permanent 1-hour SO2 monitoring site.

6.4 How Was Frequency Analyzed Utilizing The POSTFILE Option?

Similarly to the frequency analysis utilizing the MAXDAILY output option in AERMOD, the 

NDV was further analyzed in conjunction with the POSTFILE output file by utilizing a scoring 

strategy to create a relative prioritized list of receptor locations. 

In the first step of this analysis, the NDVs were ranked in descending order (with the largest 

value having a rank of 1). In the second step, the results from the POSTFILE output option 

where used to determine the number of hours for which each receptor was the overall highest 1-

hour concentration for the hour for the three modeled years. A figure showing the frequency of 

having the maximum hourly results is included in Appendix L. The receptors were then ranked 

in descending order (with the largest value having a rank of 1) based on each receptors frequency 

of hours having the overall highest 1-hour concentration. The third step was to add these two 

ranks together to obtain a score. The scores were then ranked in ascending order, giving the 

lowest value (having the greatest significance) a rank of 1. This score rank was then utilized to 

identify the most favorable locations for a permanent 1-hour SO2 monitoring site.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 10

7. RESULTS

7.1 What Are The Results From The Daily Scoring Analysis?

The following figure shows the top 200 receptors ranked based on a scoring methodology 

utilizing the NDV and the frequency of days having the largest 1-hour normalized concentration.

Figure 7-1: MAXDAILY Scoring Analysis Results

A summary of the results from the MAXDAILY output file analysis for the top ten most suitable 

monitoring locations are presented in the following table. The top 10 receptors are shown simply 

to illustrate the scoring methodology.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 11

Table 7-1: MAXDAILY Output File Analysis Summary (Rank 1 – 10)

Easting in 

meters 

(NAD 27)

Northing 

in meters 

(NAD 27)

Distance 

from 

Facility1

(km)

Bearing 

from 

Facility2

NDV 

Rank

Daily 

Max 

Freq.

Count

Daily 

Max 

Freq. 

Rank

Receptor 

Score

Receptor 

Score 

Rank

293500 3961000 1.30 N14.6°E 2 41 2 4 1

293250 3961250 1.51 N3.0°E 1 28 10 11 2

293000 3961000 1.27 N7.8°W 4 29 7 11 3

293500 3960750 1.06 N18.0°E 8 29 8 16 4

293000 3961250 1.52 N6.5°W 6 28 11 17 5

293500 3961250 1.55 N12.2°E 3 22 17 20 6

293250 3961000 1.26 N3.5°E 7 23 15 22 7

292500 3955750 4.05 S9.6°W 16 30 6 22 8

292500 3955500 4.29 S9.0°W 9 12 24 33 9

293750 3961250 1.62 N20.9°E 21 26 12 33 10

1

– Distance is measured from the center of the stacks for OG&E Muskogee Units 4, 5, and 6.

2

– Bearing is measured from the center of the stacks for OG&E Muskogee Units 4, 5, and 6 from the North or South 

given an “X” amount of degrees toward the East or West direction.

Based on the results presented in the previous table, the top 10 most suitable 1-hour SO2 monitor 

locations appear to be within 1.06 km to 1.62 km of the facility and in a median direction 

between N 12.2°E and N 14.6°E. 

7.2 What Are The Results From The Hourly Scoring Analysis?

The following figure shows the top 200 receptors ranked based on a scoring methodology 

utilizing the NDV and the frequency of having the largest 1-hour normalized concentration.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 12

Figure 7-2: POSTFILE Scoring Analysis Results

A summary of the results from the POSTFILE output file analysis for the top ten most suitable 

monitoring locations are presented in the following table. The top 10 receptors are shown simply 

to illustrate the scoring methodology.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 13

Table 7-2: POSTFILE Output File Analysis Summary (Rank 1 – 10)

Easting in 

meters 

(NAD 27)

Northing 

in meters 

(NAD 27)

Distance

from 

Facility1

(km)

Bearing 

from 

Facility2

NDV 

Rank

Hourly 

Max 

Freq. 

Count

Hourly 

Max 

Freq.

Rank

Receptor 

Score

Receptor 

Score 

Rank

293000 3961250 1.52 N6.5°W 6 573 7 13 1

293000 3961000 1.27 N7.8°W 4 471 12 16 2

293500 3960750 1.06 N18.0°E 8 355 20 28 3

293250 3961250 1.51 N3.0°E 1 285 29 30 4

294000 3956250 3.59 S13.3°E 28 528 8 36 5

293500 3961250 1.55 N12.2°E 3 250 34 37 6

293500 3961000 1.30 N14.6°E 2 224 37 39 7

293750 3961250 1.62 N20.9°E 21 345 22 43 8

293000 3960750 1.03 N9.7°W 35 454 13 48 9

292500 3955750 4.05 S9.6°W 16 220 38 54 10

1

– Distance is measured from the center of the stacks for OG&E Muskogee Units 4, 5, and 6.

2

– Bearing is measured from the center of the stacks for OG&E Muskogee Units 4, 5, and 6 from the North or South 

given an “X” amount of degrees toward the East or West direction.

Based on the results presented in the previous table, the top 10 most suitable 1-hour SO2 monitor 

locations appear to be within 1.06 km to 1.62 km of the facility and in a median direction of N 

12.2°E.

7.3 How Does The Monitor Receptor Compare To The Scoring Analysis?

The current SO2 monitor location can also be compared to the overall scoring analysis results. A 

summary of the results for the receptor at the current SO2 monitoring site location are presented 

in the following table.

Figure 7-3: Results for Monitoring Site Location Receptor

Easting in 

meters 

(NAD 27)

Northing 

in meters 

(NAD 27)

Distance 

from 

Facility1

(km)

Bearing 

from 

Facility2

NDV 

Rank

Max Freq.

Count

Max Freq.

Rank

Receptor 

Score

Receptor 

Score 

Rank

291960 3963238 3.70 N19.1°W 127 0 Days 150 277 167

291960 3963238 3.70 N19.1°W 127 39 Hours 152 179 171

1

– Distance is measured from the center of the stacks for OG&E Muskogee Units 4, 5, and 6.

2

– Bearing is measured from the center of the stacks for OG&E Muskogee Units 4, 5, and 6 from the North or South 

an “X” amount of degrees toward the East or West direction.

Although a maximum daily concentration does not occur at the monitor location receptor, a 

maximum hourly concentration did occur at the receptor on 39 hours. The monitor is located 

2.72 km N34.5°W of the MAXDAILY Rank 1 receptor location. The monitor is located 2.24 

km N27.6°W of the POSTFILE Rank 1 receptor location.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 14

8. SUMMARY

8.1 What Is The Summary Of This Analysis?

The analysis was conducted utilizing the MAXDAILY and the POSTFILE output options in 

AERMOD. The POSTFILE analysis was conducted in addition to the MAXDAILY option 

recommended by the Monitoring TAD to compare the frequency of daily maximum 1-hour 

values to maximum 1-hour values. It is conceivable that a receptor location might observe 

multiple high concentrations in a single day. The MAXDAILY analysis takes only the highest 

concentration value for a single day. This analysis gives no additional weight to the receptor for 

additional highs at that receptor during the same day and can potentially skew the analysis. 

Analysis of the POSTFILE applies more weight to the frequency consideration in the scoring 

analysis. 

The two analyses might be expected to show different results since different weights are being 

applied to frequency. It should be noticed that eight (8) of the receptors were ranked in the top 

10 favorable receptor locations for both the MAXDAILY and POSTFILE analyses.

Table 8-1: Monitor Locations Ranked in the Top 10 for Both Analyses

Easting in 

meters 

(NAD 27)

Northing 

in meters 

(NAD 27)

Distance 

from 

Facility1

(km)

Bearing 

from 

Facility2

NDV 

Rank

Daily 

Max 

Freq.

Count

Daily 

Max 

Freq.

Rank

Hourly

Max 

Freq.

Count

Hourly 

Max 

Freq.

Rank

293250 3961250 1.51 N3.0°E 1 28 10 285 29

293500 3961000 1.3 N14.6°E 2 41 2 224 37

293500 3961250 1.55 N12.2°E 3 22 17 250 34

293000 3961000 1.27 N7.8°W 4 29 7 471 12

293000 3961250 1.52 N6.5°W 6 28 11 573 7

293500 3960750 1.06 N18.0°E 8 29 8 355 20

292500 3955750 4.05 S9.6°W 16 30 6 220 38

293750 3961250 1.62 N20.9°E 21 26 12 345 22

1

– Distance is measured from the center of the stacks for OG&E Muskogee Units 4, 5, and 6.

2

– Bearing is measured from the center of the stacks for OG&E Muskogee Units 4, 5, and 6 from the North or South 

an “X” amount of degrees toward the East or West direction.

Ideally, the most favorable receptor identified in the analysis would have both the highest NVD 

(a rank of 1) and the highest frequency of maximums (a rank of 1). Adding the NVD rank and 

maximum frequency rank together (as discussed in Section 6.3) would result in a score of 2, 

which is the lowest possible score for this analysis. 

The scoring analysis for the MAXDAILY output option resulted in a top score of 4 for the most 

favorable monitoring site location. The scoring analysis for the POSTFILE output option 

resulted in a score of 13 for the most favorable monitoring site location. This indicates that the 

most favorable monitoring site location (having a score rank of 1) did not have either the highest 
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 15

NDV or the highest frequency of maximums for the respective periods; however, the top 

receptor for both of the analyses were ranked within the top 10 for both frequency and NDV.

8.2 What Can Be Concluded From This Analysis

In general, the results for the top 200 receptors presented in the previous section indicate the 

most favorable monitoring locations are in the North East direction between 1.06 km to 1.62 km 

from the center of the three coal-fired unit stacks at the OG&E Muskogee Generating station.

The intention of this analysis was to perform modeling to provide information for favorable 

monitoring site locations. However, it is not certain the results are truly representative of the 

small area discussed herein, presently or in the future, for the reasons stated below (specifically, 

the questionable quality of meteorological data and impending installation of controls at OG&E 

Muskogee Generating Station). These results should only be considered as part of the evaluation 

to identify a suitable location for a monitor. Other aspects for proper siting of a monitor should 

be taken into consideration (such as spacing from potential obstructions, power supply, etc. as 

well as other considerations stated in 40 CFR Part 58, Subpart G, Appendix E).

Although the meteorological data set was developed using the most representative data available, 

it may not be truly representative of the overall domain. This is due to complex terrain features, 

atmospheric stability, and distance and location of the meteorological sites used in the 

development of the meteorological data set. A meteorological site located at or near the center 

of the domain would enhance the accuracy of the data. Additionally, modeling utilizing the 

meteorological data set developed from the 2012 to 2014 data may not be consistent with a 

meteorological data set utilizing data from past or future years.

The analysis performed is only reflective of the current source configuration for the domain. 

OG&E is required by the Regional Haze Program to install Best Available Retrofit Technology 

(BART) on Unit 4 and Unit 5. OG&E has committed to meet the federal emission limit of 0.06 

lb/MMBTUH by January 4, 2019, by converting Unit 4 and Unit 5 to natural gas. With the 

committed changes to these sources occurring in the future, monitor locations sited based on this 

analysis may not suitably represent the domain after emissions are reduced as a result of BART.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma 16

9. REFERENCES

 SO2 NAAQS Designations Modeling Technical Assistance Document (December 2013 

Draft);

o http://www.epa.gov/oaqps001/sulfurdioxide/pdfs/SO2ModelingTAD.pdf

 SO2 NAAQS Designations Source-Oriented SO2 Monitoring Technical Assistance 

Document (December 2013 Draft);

o http://www.epa.gov/oaqps001/sulfurdioxide/pdfs/SO2MonitoringTAD.pdf

 Guidance for 1-Hour SO2 NAAQS SIP Submissions (September 22, 2011);

o http://www.epa.gov/oaqps001/sulfurdioxide/pdfs/DraftSO2Guidance_9-22-11.pdf

 User’s Guide for the AMS/EPA Regulatory Model - AERMOD

o http://www.epa.gov/ttn/scram/models/aermod/aermod_userguide.zip

 User’s Guide for the AERMOD Meteorological Data Preprocessor (AERMET)

o http://www.epa.gov/ttn/scram/7thconf/aermod/aermet_userguide.zip

 AERMINUTE User’s Instruction

o http://www.epa.gov/ttn/scram/7thconf/aermod/aerminute_14337.zip

 AERSURFACE User’s Guide

o http://www.epa.gov/ttn/scram/7thconf/aermod/aersurface_userguide.pdf

 Guidance Concerning the Implementation of the 1-hour SO2 NAAQS for the Prevention of 

Significant Deterioration Program (August 23, 2010);

o http://www.epa.gov/region07/air/nsr/nsrmemos/appwso2.pdf

 Applicability of Appendix W Modeling Guidance for the 1-hour SO2 NAAQS (August 23, 

2010);

o http://www.epa.gov/ttn/scram/guidance/clarification/ClarificationMemo_AppendixW

_Hourly-SO2-NAAQS_FINAL_08-23-2010.pdf

 Data Requirements Rule for the 1-Hour Sulfur Dioxide (SO2) Primary National Ambient 

Air Quality Standards (NAAQS), Proposed (May 13, 2014);

o http://www.gpo.gov/fdsys/pkg/FR-2014-05-13/pdf/2014-09458.pdf
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma A-1

APPENDIX A DOMAIN LOCATION

Domain Location (State Level)

* Boundaries: Red – State of Oklahoma; Black - Oklahoma Counties; Yellow – Modeling Domain.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma A-2

Domain Location (County Level)

* Boundaries: Red – State of Oklahoma; Black - Oklahoma Counties; Yellow – Modeling Domain.

** Red fence line for OG&E Muskogee Generating Station

ADAIR

CHROKEE

WAGONER

MUSKOGEE

SEQUOYAH

MAYES

TULSA

OKMULGEE

MCINTOSH

ADAIR
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma B-1

APPENDIX B RECEPTOR GRID

10 km Receptor Grid

(excludes receptors within fence lines of significant SO2 sources)

* Red fence line identifies OG&E Muskogee Generating Station.

** Black fence lines indicate other significant SO2 sources within receptor grid.

*** Green receptor located at Muskogee SO2 monitor location.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma B-2

Revised 10 km Receptor Grid

(excludes receptors not suitable for permanent monitor placement)

* Red fence line identifies OG&E Muskogee Generating Station.

** Black fence lines indicate other significant SO2 sources within receptor grid.

*** Green receptor located at Muskogee SO2 monitor location.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma C-1

APPENDIX C LAND COVER CLASSIFICATION (NLCD 1992)

Land Cover Imagery for Muskogee, Oklahoma Area

* Red fence line identifies OG&E Muskogee Generating Station.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma D-1

APPENDIX D AERIAL IMAGE WITH FACILITY DATA

OG&E – Muskogee Generating Station

* Blue – Buildings; Red – Fence line; Yellow – Point Sources.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma E-1

APPENDIX E SOURCE DATA

Modeled Emission Points and Stack Parameters

Source ID Facility Easting1 Northing1 Elevation Stk Ht Stk Temp Velocity Stk Dia SO2

(m) (m) (m) (m) (K) (m/s) (m) (g/s)

UNIT 4 OG&E Muskogee 293116.7 3959729.8 156.2 106.68 437.04 26.62 7.32 0.96950

UNIT 5 OG&E Muskogee 293172.0 3959739.3 156.8 106.68 429.26 25.79 7.32 0.93782

UNIT 6 OG&E Muskogee 293240.4 3959757.7 157.0 152.40 418.71 32.35 6.55 1.00000

DAL20 Dalitalia 284208.4 3953784.7 171.2 14.11 336.20 9.08 1.51 0.00000*

DAL23 Dalitalia 284164.9 3953711.7 170.8 10.97 520.20 24.84 0.62 0.00000*

DAL29 Dalitalia 284093.8 3953787.7 171.0 15.64 335.37 7.35 1.63 0.00000*

BORSCRUB Boral 282161.2 3951159.0 183.5 21.34 452.59 11.06 1.89 0.01291

GPSTACK1 Georgia Pacific 292555.0 3956494.1 161.9 79.25 451.48 8.67 3.05 0.02527

GPSTACK3 Georgia Pacific 292594.0 3956513.0 162.0 79.25 425.37 8.61 4.20 0.12218

OBFURNA Owens Brockway 288620.7 3960596.6 179.6 45.72 765.37 8.89 1.62 0.00275

OBFURNB Owens Brockway 288656.6 3960582.4 180.0 24.38 471.48 8.81 2.16 0.00551

M1 US Lime 334096.8 3940641.2 203.6 45.73 403.00 17.40 1.63 0.00601

K1 US Lime 334000.6 3940571.3 204.5 29.27 341.33 9.51 2.13 0.00005

UNIT 1 GRDA 294138.0 4007357.0 189.5 153.62 422.04 20.77 6.10 0.85326

UNIT 2 GRDA 294211.0 4007262.0 188.8 154.53 360.93 27.73 6.10 0.27333

1

– UTM coordinates (Zone 15) are relative to NAD 27 datum.

* Emissions relative to other facilities within the domain were so small that the normalized emission rates did not register.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma F-1

APPENDIX F METEOROLOGICAL DATA

Site and Location Information

Meteorological Network Oklahoma Mesonet ISHD ESRL

Meteorology Type Surface Surface Upper Air

Site Name Porter Davis Field/Muskogee Norman

Site Call Sign PORT KMKO OUN

USAF --- 723556 ---

Latitude (NAD 83) 35.8257 35.6577 35.23

Longitude (NAD 83) -95.5598 -95.3658 -97.47

County Wagoner County, Oklahoma Muskogee County, Oklahoma Oklahoma County, Oklahoma

Elevation (m) 193 183.5 ---
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma G-1

APPENDIX G WIND ROSE

2012-2014 KMKO Wind Rose
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma H-1

APPENDIX H SURFACE CHARACTERISTICS

Modeling Domain Surface Characteristics

Albedo Bowen Ratio 

(Average)

Bowen Ratio 

(Wet)

Bowen Ratio 

(Dry)

Surface 

Roughness

KMKO

Winter 0.18 0.72 0.41 1.94 0.016

Spring 0.14 0.33 0.22 1.03 0.023

Summer 0.19 0.50 0.30 1.42 0.037

Fall 0.19 0.72 0.41 1.94 0.031

Modeling Domain Moisture Conditions1

Year 2012 2013 2014

January A W D

February A W D

March W A A

April D W A

May D A W

June D A W

July D A W

August A A A

September A D A

October D A W

November D A A

December D W A

1

– Moisture conditions based on rainfall data from the Porter Oklahoma Mesonet station.

A – Average (precipitation in the middle 40th percentile);

D – Dry (precipitation in the lower 30th percentile);

W – Wet (precipitation in the upper 30th percentile).
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma I-1

APPENDIX I NORMALIZED DESIGN VALUE RESULTS

Ratio of the NDVs (based on max NDV)

* Red fence line identifies OG&E Muskogee Generating Station.

** Black fence lines indicate other significant SO2 sources within receptor grid.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma J-1

APPENDIX J TOP 200 RECEPTORS

Location of top 200 NDV Receptors

* Red fence line identifies OG&E Muskogee Generating Station.

** Green receptor located at Muskogee SO2 monitor location.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma K-1

APPENDIX K MAXIMUM DAILY FREQUENCY 

MAXDAILY Maximum 1-Hour Concentration Count

* Red fence line identifies OG&E Muskogee Generating Station.
Source-Oriented Monitoring Placement for the Area of Muskogee, Oklahoma L-1

APPENDIX L MAX HOURLY FREQUENCY

POSTFILE Maximum 1-Hour Concentration Count

* Red fence line identifies OG&E Muskogee Generating Station.