## 2010 Primary Sulfur Dioxide (SO 2 

## )

National Ambient Air Quality Standard (NAAQS)

Technical Analyses and Information Supporting the Designation Recommendation for Oklahoma



## Source

- Oriented SO 2 

## 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 , 2015Source

- Oriented Monitori ng Placement for the Area of Muskogee, Oklahoma i 

## TABLE OF CONTENTS

2010 Primary Sulfur Dioxide (SO 2 )

................................ ................................ ............................. 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 SO 2 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 Analysi s?

................................ ............ 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

................................ .. 7Source

- Oriented Monitori ng 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

- 1Source

- Oriented Monitori ng 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

- 1Source

- Oriented Monitori ng 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 SO 2 source

- oriented monitoring site

locations for the 2017

- 2019 monitoring intended to s atisfy the Data Requirements Rule in Muskogee County, Oklahoma.

1.2 

### What Is The B ackground 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 (SO 2 ) National Ambient Air Quality Standard (NAAQS). T he EPA promulgated a new 1

- hour daily maximum primary SO 2 standard at a level of 75 parts per billion (ppb) , based on the 3

- year average of the annual 99 th percentile of 1

- hour d aily maximum

concentrations.

On May 13, 2014, the EPA proposed t he Data Requirements Rule (DRR) for the 1

- Hour SO 2 NAAQS

. The final DRR was signed on August 10, 2015 and require s states to gather and

submit to the EPA additional information characteriz ing SO 2 air quality in areas with larger

sources of SO 2 emissions (79 FR 27445). In the DRR, air agencies have the choice to use either monitoring or modeling to characterize SO 2 air quality in the vicinity of priority SO 2 sources, and submit the modeling and/or mo nitor ing to the EPA on a schedule specified by the rule.

1.3 

### What Is The Background Of The Current Muskogee SO 2 

### Monitor?

The current source oriented SO 2 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 i ncluded in the permit application which utiliz ed 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 SO 2 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 SO 2 monitoring site.Source

- Oriented Monitori ng Placement for the Area of Muskogee, Oklahoma 2

Locations of the maximum concentrations were calculat ed 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 SO 2 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 SO 2 NAAQS Designations Source

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

follow the recommendations of the SO 2 NAAQS Designations Modeling Technical Assistance Document (Modeling TAD)

. The modeling TAD essentially states that g iven the source

oriented nature of SO 2 , 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 designat ions 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 Monitori ng Placement for the Area of Muskogee, Oklahoma 3

3. 

### MODEL DOMA IN 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, s ince 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 di stance of 10 km with a r eceptor 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 SO 2 M uskogee 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 emissionSource

- Oriented Monitori ng 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 generat ed 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 99 th percentile of CEM data from 2012 to 2014. Actual emissions for nearby sources wer e 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 o f 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 urba n 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 t he 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 a s 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 SO 2

. 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 stac ks 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 ph otos are included in Appendix D.Source

- Oriented Monitori ng 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 SO 2 emissions. Since th e 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 ye ars 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 concentratio n 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 i s 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 fo llowing 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

am bient 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 Dow nwash 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 so oner 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.

Model ing that includes calculations for building downwash gives a more accurate representation of pollutant impacts than does modeling that omits consideration of downwash e ffects.

A building is any physical obstruction to airflow at the modeled facility. A s tructure 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 n ot a factor. GEP stack height is calculated according to the following equation.

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 Monitori ng 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 A irport (KMKO) in Muskogee

was utilized for the 2010 1

- hour SO 2 primary NAAQS designations modeling.

When conducting air dispersion modeling, the S tate of Oklahoma generally utilizes meteorological data from the following:

 Oklahoma Mesonet Surface Data;
 N ational 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 System s 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 AERMET

processed meteorological data mor e 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 c ontain 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

meteorolo gical 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 continuou s 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 inc orporated 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 Monitori ng Placement for the Area of Muskogee, Oklahoma 7

5.1.1 

### How Were Sites From The ISHD Evaluated?

The ISH data files were downloaded fr om the NCDC ISHD web site: ftp://ftp.ncdc.noaa.gov/pub/data/noaa

. The ISH data was re view ed 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 indivi dual 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

conditi ons 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 fr om 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 stat ion 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 s oundings 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 replacemen t 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 d omain.

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 forSource

- Oriented Monitori ng 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 th e 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 convec tive 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 matche s 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 Characte ristics (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 analyz ed 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 amount s 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 Oklaho ma 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 4 th daily highest 1

- hour maximum concentration (99 th percentile of daily 1

- hour maximum concentrations). The se r esults are referred to as the normalized design values (NDVs) since

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

0. 20793 μg/m 3 to 0. 63730 μg/m 3

. A figure showing a ratio of the NDV of each receptor compared to t he 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 approximate ly 6 .52 km from the center of the three stacks at the OG&E Muskogee Generating Station.Source

- Oriented Monitori ng Placement for the Area of Muskogee, Oklahoma 9

6.2 

### Why Was Frequency Accounted For In The Analysis?

Simply using the largest NDV s to i dentify the best monitor locations is not sufficient enough to determine proper pla cement of a monitor site. Therefore, the num ber 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 o f 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 SO 2 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.

I n the first step of this analysis, the NDVs were ranked in des cending 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 t hree 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 SO 2 monitoring site.

6.4 

### How Was Frequency Analyzed Utilizing The POSTFILE Option?

Similarly to the frequency analysis utilizing the MAXDAILY output option in AE RMOD, 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 w as 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 valu e 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 valu e (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 SO 2 monitoring site.Source

- Oriented Monitori ng 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 Monitori ng 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 Facility 1

(km) Bearing

from Facility 2 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 SO 2 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 T he Results F rom T he 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 Monitori ng 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 Monitori ng 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 Facility 1

(km) Bearing

from Facility 2 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 SO 2 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 SO 2 monitor location can also be compared to the overall scoring analysis results. A

summary of the results for the receptor at the current SO 2 mo nitoring 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 Facility 1

(km) Bearing

from Facility 2 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 15 2 179 171

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 tow ard 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 Monitori ng 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 sing le 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 sho w 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 Facility 1

(km) Bearing

from Facility 2 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 t he 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.

T he 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 highestSource

- Oriented Monitori ng Placement for the Area of Muskogee, Oklahoma 15

NDV or the highest frequency of maxi mums 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, t he results for the top 200 receptors presented in the pre vious section indicate the

most favorable monitoring locations are in the North Ea st direction b etween 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 favo rable 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). T hese results should only be considered as part of the evaluation to identify a suitabl e 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).

A lthough 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 mete orological 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.

T he analysis performed is only reflective of the current source configuration for the domain

. OG&E is required by the Regional Haze Prog ram 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 , 201 9 , 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 Monitori ng Placement for the Area of Muskogee, Oklahoma 16

9. 

### REFERENCES

 SO 2 NAAQS Designations Modeling Technical Assistance Document (December 2013 Draft);

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

 SO 2 NAAQS Designations So urce

- Oriented SO 2 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 Regulator y 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/s cram/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 SO 2 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 SO 2 NAAQS (August 23, 2010);

o http://www.epa.gov/ttn/scram/gui dance/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.pdfSource

- 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 ADAIRSource

- 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 SO 2 sources)

* Red fence line identifies OG&E Muskogee Generating Station. ** Black fence lines indicate other significant SO 2 sources within receptor grid.

*** Green receptor located at Muskogee SO 2 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 SO 2 sources within receptor gr id.

*** Green receptor located at Muskogee SO 2 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 Easting 1 Northing 1 Elevation Stk Ht Stk Temp Velocity Stk Dia SO 2 (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 RoseSource

- 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 Conditions 1

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 40 th percentile);

D

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

W

– Wet (precipitation in the upper 30 th 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 SO 2 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 SO 2 monitor location.Source

- Oriented Monitoring Placement for the Area of Muskogee, Oklahoma K

- 1

APPENDIX K MAX IMUM 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.