2010 Primary Sulfur Dioxide (SO2)

National Ambient Air Quality Standard (NAAQS)

Technical Analyses and Information Supporting the

Designation Recommendation for Oklahoma

Comparison of Modeled and Monitored SO2 Concentrations

In Muskogee, Oklahoma

Prepared by the Engineering Section of the Permitting Unit

Air Quality Division

Oklahoma Department of Environmental Quality

August 26, 2015
Table of Contents

1. WHAT IS THE PURPOSE OF THIS REPORT? ..................................................................1

2 HOW WAS AREA SURROUNDING THE OG&E MUSKOGEE GENERATING 

STATION MODELED? .........................................................................................................2

2.1 What air dispersion model was utilized for the modeling air quality 

analysis?..................................................................................................................2

2.2 What receptors were utilized in the modeling air quality analysis? .................2

2.3 What terrain data was utilized for the modeling air quality analysis?.............2

2.4 What domain classification was utilized for the modeling air quality 

analysis?..................................................................................................................3

2.5 What sources were included in the modeling air quality analysis? ..................3

2.5.1 How were hourly emissions from the modeled sources determined?.......4

2.5.2 How was GEP stack height addressed? ....................................................5

2.6 Was building downwash included in the modeling analyses? ...........................5

2.7 What meteorological data was utilized in the modeling air quality 

analysis?..................................................................................................................5

2.7.1 How was the ISHD data processed? .........................................................6

2.7.2 Was AERMINUTE utilized in the modeling analysis? ............................6

2.7.3 What is Oklahoma Mesonet data and how was it utilized? ......................6

2.7.4 What upper air data was used?..................................................................7

2.7.5 How were surface characteristics determined?.........................................8

2.7.6 What was used to determine the surface moisture conditions? ................8

2.8 Was background monitoring data utilized in the modeling air quality 

analysis?..................................................................................................................8

3. WHAT WERE THE MONITORED IMPACTS? ..................................................................8

4. WHAT WERE THE MODELED IMPACTS AT THE MONITOR? ....................................9

5 WHAT STEPS WERE TAKEN TO EVALUATE THE DIFFERENCE OF THE 

MONITORED IMPACTS AND THE MODELED IMPACTS? ...........................................9

5.1 Was Representativeness of the Surface Meteorological Data Evaluated? .......9

5.2 Were the Effects of Terrain Evaluated? ............................................................10

5.3 Were the Sources of Upper Air Data Evaluated?.............................................11
5.4 How were the Modeled Ambient Impacts Compared to the Monitored 

Ambient Impacts?................................................................................................11

6. WHAT IS THE SUMMARY OF THE REVIEW OF MONITORED IMPACTS AND 

MODELED IMPACTS?.......................................................................................................13

7. WHAT REFERENCES WERE USED?...............................................................................14

APPENDICES

Appendix A – Land Use/Land Cover Aerial Photo

Appendix B – Aerial Photo Overlaid With Facility Data

Appendix C – Wind Roses (Blowing To)

Appendix D – Surface Characteristics

Appendix E – Modeling Versus Monitoring Graphs

Appendix F – Comparison of Hours with High Impacts at the Monitor with Sub-Hourly Impact, 

Meteorological, and Source Data

Appendix G – Comparison of Hours with Modeled and Monitored High Impacts
Muskogee Monitoring Versus Modeling Report Page 1

1. WHAT IS THE PURPOSE OF THIS REPORT?

On June 22, 2010, the Environmental Protection Agency (EPA) revised the primary sulfur 

dioxide (SO2) National Ambient Air Quality Standard (NAAQS). The EPA promulgated a new 

1-hour annual primary SO2 standard at a level of 75 parts per billion (ppb), based on the 3-year 

average of the annual 99th percentile of the daily maximum 1-hour average concentrations. The 

area designation process typically relies on air quality concentrations characterized by ambient

monitoring data to identify areas that are either meeting or violating the relevant standard. 

However, a hybrid approach using modeling and monitoring for the designation process was 

proposed because of the following:

 SO2 impacts are considered to be “source-oriented” rather than “regional” (peak

concentrations of SO2 are commonly caused by one or a few major point sources in an area 

and peak concentrations are typically observed relatively close to the source);

 Ambient SO2 concentrations can be modeled accurately using well understood air quality 

modeling tools; and

 Only approximately 35% of the monitoring network was addressing locations of maximum 

(highest) concentrations of specific sources or groups of sources.

On March 2, 2015, a Consent Decree (CD) was filed requiring the EPA to sign for publication in 

the Federal Register no later than sixteen (16) months from March 2, 2015, a notice of EPA’s 

promulgation of designations for the 2010 revised primary SO2 NAAQS, for undesignated areas 

which:

1) Based on air quality monitoring in the three (3) full calendar years preceding such deadline 

have monitored violations of the 2010 revised primary SO2 NAAQS; or

2) Contain any stationary source that has not been “announced for retirement” by the date of 

this Consent Decree, and that, according to the data in EPA’s Air Markets Database, either

a. Emitted more than 16,000 tons of SO2 in 2012, or

b. Emitted more than 2,600 tons of SO2 and had an annual average emission rate of 0.45 

lbs SO2/MMBTU or higher in 2012.

By September 18, 2015, the state may submit to EPA additional information regarding the 

affected facilities and for which updated air quality analyses have been used to characterize the 

air quality around the source either through monitoring, modeling, or a combination of modeling 

and monitoring. To support the designations previously submitted by the State of Oklahoma, an 

air quality analysis utilizing modeling was conducted to characterize the air quality of the areas 

containing affected sources. Modeling of the area surrounding the OG&E Muskogee Generating 

Station was one of the air quality analyses which were conducted. The area containing the 

OG&E Muskogee Generating Station is unique because it also has an ambient SO2 monitor 

which can also be utilized to characterize the area. However, when comparing modeled impacts 

to the monitored values from the Muskogee monitor (40-101-0167), there was poor correlation 

between the modeled impacts and the monitored values. This report discusses the analyses 

conducted concerning the modeling and trying to determine what may be contributing to the poor 

correlation between the modeled impacts and the monitored values.
Muskogee Monitoring Versus Modeling Report Page 2

2 HOW WAS AREA SURROUNDING THE OG&E MUSKOGEE 

GENERATING STATION MODELED?

Modeling of the area surrounding the OG&E Muskogee Generating Station was conducted 

utilizing 2012 to 2014 meteorological data and 2012 to 2014 actual emissions. The modeling 

was conducted in accordance with the SO2 NAAQS Designations Modeling Technical Assistance 

Document (December 2013).

2.1 What air dispersion model was utilized for the modeling air quality analysis?

Given the source-oriented nature of SO2, dispersion models are appropriate air quality modeling 

tools to predict the near-field concentrations. Therefore, for the area designations under the 2010 

1-hour SO2 primary NAAQS, the AMS/EPA Regulatory Model (AERMOD) was used to 

conduct the air quality analysis. 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).

The AERMOD modeling system includes the following components:

 AERMOD (Version 15181): the dispersion model;

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

 AERMET (Version 15181): the meteorological data processor for AERMOD.

For the OG&E Muskogee Generating Station these additional components were used in the 

modeling analysis:

 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;

2.2 What receptors were utilized in the modeling air quality analysis?

To simplify the comparison of predicted impacts from the modeling and the monitored 

concentrations, a single receptor at the location of the monitor was used. The monitor is located 

3.7 km north-northwest (341 degrees from the North) of the OG&E Muskogee facility.

2.3 What terrain data was utilized for the modeling air quality 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 area 

surrounding the OG&E Muskogee Generating Station is located in UTM Zone 15. All 

coordinates in the model were based on the North American Datum (NAD) 1927 (NAD27).
Muskogee Monitoring Versus Modeling Report Page 3

2.4 What domain classification was utilized for the modeling air quality analysis?

Determination of the whether or not the domain should be classified as urban or rural was based 

mainly on land use which is the preferred method. The land use in the area surrounding the 

OG&E Muskogee Generating Station is mainly classified as rural. Therefore, the modeling 

analysis utilized a rural classification. However, the potential effects of the “urban heat island 

affect” were reviewed because the OG&E Muskogee Generating Station is located next to a 

metropolitan area. An Aerial photo of the area surrounding the OG&E Muskogee Generating 

Station is included in Appendix B.

2.5 What sources were included in the modeling air quality analysis?

When determining which affected sources should be included in the modeling air quality analysis, all 

nearby sources were evaluated. Nearby sources are those sources within 50 km of the OG&E 

Muskogee Generating Station that could cause or contribute to a NAAQS violation in the vicinity of 

the OG&E Muskogee Generating Station. All natural gas fired sources were excluded from the 

modeling air quality analysis because they do not cause a significant concentration gradient at the 

monitor location. The modeling air quality analysis did not include intermittent emissions sources, 

such as emergency generators based on the recommendations in the March 1, 2011 memorandum 

“Additional Clarification Regarding Application of Appendix W Modeling Guidance for the 1-hour 

NO2 National Ambient Air Quality Standard.”

All other sources of SO2 were included in the modeling air quality analysis. A list of all sources in 

the modeling air quality analysis is given below.

Table 2.5-1. Location, Elevation, & Emissions of Modeled Sources

Easting Northing Elevation SO2

Source ID Facility (m) (m) (m) (lb/hr)

UNIT 4 OG&E Muskogee 293116.7 3959729.8 156.2 2,010.98

UNIT 5 OG&E Muskogee 293172.0 3959739.3 156.8 1,912.21

UNIT 6 OG&E Muskogee 293240.4 3959757.7 157.0 2,206.57

DAL20 Dalitalia 284208.4 3953784.7 171.2 0.11

DAL23 Dalitalia 284164.9 3953711.7 170.8 0.05

DAL29 Dalitalia 284093.8 3953787.7 171.0 0.09

BORSCRUB Boral 282161.2 3951159.0 183.5 43.60

GPSTACK1 Georgia Pacific 292555.0 3956494.1 161.9 85.33

GPSTACK3 Georgia Pacific 292594.0 3956513.0 162.0 412.56

OBFURNA Owens Brockway 288620.7 3960596.6 179.6 9.30

OBFURNB Owens Brockway 288656.6 3960582.4 180.0 18.61

M1 US Lime 334096.8 3940641.2 203.6 20.31

K1 US Lime 334000.6 3940571.3 204.5 0.17

UNIT 1 GRDA 294138.0 4007357.0 189.5 2,881.26

UNIT 2 GRDA 294211.0 4007262.0 188.8 922.97
Muskogee Monitoring Versus Modeling Report Page 4

Table 2.5-2. Stack Parameters of Modeled Sources

Stack 

Height

Stack 

Temp.

Stack 

Velocity

Stack 

Diameter

Source ID Facility (ft) (°F) (fps) (ft)

UNIT 4 OG&E Muskogee 350.0 264 44.96 24.0

UNIT 5 OG&E Muskogee 350.0 264 41.80 24.0

UNIT 6 OG&E Muskogee 500.0 264 55.01 21.5

DAL20 Dalitalia 46.3 130 29.80 5.0

DAL23 Dalitalia 46.0 130 45.08 2.7

DAL29 Dalitalia 51.3 130 24.10 5.4

BORSCRUB Boral 70.0 355 36.29 6.2

GPSTACK1 Georgia Pacific 260.0 353 28.46 10.0

GPSTACK3 Georgia Pacific 260.0 306 28.24 13.8

OBFURNA Owens Brockway 150.0 918 29.16 5.3

OBFURNB Owens Brockway 80.0 389 28.89 7.1

M1 US Lime 150.0 266 57.09 5.3

K1 US Lime 96.0 155 31.20 7.0

UNIT 1 GRDA 504.0 300 68.14 20.0

UNIT 2 GRDA 507.0 190 90.98 20.0

2.5.1 How were hourly emissions from the modeled sources determined?

Actual emission data for input into AERMOD was generated for each source included in the 

modeling analysis. Most electric generating units (EGU) have continuous emissions monitoring 

systems (CEMS). In the absence of CEMS data, simply dividing the annual emissions by the 

number of hours in the year is not an accurate representation of actual emissions. For affected 

sources without CEMS data, actual emissions were based on actual throughputs and the 

calculated SO2 emissions generally based on a mass balance. For sources that vary their operation 

throughout the year, AERMOD input variables were used to represent their actual operation 

throughout the year. Use of AERMOD input variables such as hour of day (HROFDY), hour of day 

and day of week (HRDOW), monthly hour of day and day of week (MHRDOW), were utilized to 

represent actual operation for those sources without CEMS data. Varying emissions were based on 

the available information such as production logs, fuel usage information, operating schedules, etc. 

CEMS data was used to generate hourly emissions files for those sources with CEMS using the 

following methodology:

Step 1: The emission data was downloaded from the Clean Air Markets Database (CAMD).

Step 2: The monthly data was combined generating annual emission data files for each source at 

an affected facility with CEMS data.

Step 3: There are three variables used in an hourly emission file, emissions, velocity, and 

temperature. These hourly values were generated from the CAMD datasets and 

formatted into the units used by AERMOD. The emissions were converted from the 

CAMD data lb/hr values into g/s. The heat input given in the CAMD data was used with 

Method 19, the CO2 concentration, and stack temperature from recent relative accuracy 

test audits (RATA), to generate the flow rate and resultant velocity. If a unit was 

operating it was assigned the normal stack temperature determined from RATA. For the 
Muskogee Monitoring Versus Modeling Report Page 5

OG&E Muskogee Generating Station hourly velocity and temperature data from the 

CEMS was used.

Step 4: The data was then reviewed for continuity and for missing data. If there was a single 

hour of missing data, it was replaced with the average of surrounding non-missing hours. 

For periods of missing data with more than a single missing value, operational data from 

the facility was reviewed to fill the missing hours.

2.5.1.1 What operational data was used from the RATA?

The stack parameters used to generate the hourly emission file for AERMOD from RATA are 

listed below. Only RATA data from the nearby EGU located at Grand River Dam Authority 

(GRDA) was utilized in generating the hourly emission file.

Table 2.7-1 Operational Stack Data from RATA

Stack Temp % Moisture % CO2

Station Unit 2012 2013 2014 2012 2013 2014 2012 2013 2014

GRDA Unit 1 312 2971281 11.72 11.86112.00 13.26 13.06112.86

GRDA Unit 2 192 198 193 15.93 15.86 15.05 12.21 11.71 10.85

1

- The average of 2012 and 2014.

2.5.2 How was GEP stack height 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 analysis, actual stack heights were used 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 modeled sources 

and the concentrations detected at the monitor would be reflective of the effect of emissions from 

the actual stack heights.

2.6 Was building downwash included in the modeling analyses?

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

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

Therefore, building downwash was included in the modeling analysis for the on-site buildings.

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. Facility data was reviewed and included in the 

modeling analyses.

2.7 What meteorological data was utilized in the modeling air quality analysis?

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.
Muskogee Monitoring Versus Modeling Report Page 6

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 AERMET 

processed 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 with the 

Muskogee area ambient air quality modeling analysis because the ISHD ASOS KMKO Station 

data is closer to and more representative than the nearest Oklahoma Mesonet Station and subhourly wind data is available for the KMKO Station. A wind rose for the KMKO station is 

contained in Appendix F.

2.7.1 How was the ISHD data processed?

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 (GF1) values 

that were recorded. The data from KMKO did not have a significant number of missing values

for individual variables. Therefore, no missing data replacement was performed.

2.7.2 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.

2.7.3 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 
Muskogee Monitoring Versus Modeling Report Page 7

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 five closest Mesonet sites in and around the Muskogee area are listed below. Wind roses for 

the specific stations are contained in Appendix F.

Table 2.7.3-1 Oklahoma Mesonet Stations Near Muskogee, Oklahoma

STNM ID Name City County LAT LON ELEV

(m)

DIST1

(km)

118 PORT Porter Clarksville Wagoner 35.8257 -95.5598 193 25.5

44 HASK Haskell Haskell Muskogee 35.7480 -95.6405 183 31.8

132 WEBR Webbers Falls Webbers Falls Muskogee 35.4890 -95.1233 145 33.8

92 TAHL Tahlequah Tahlequah Cherokee 35.9724 -94.9867 290 35.8

31 COOK Cookson Marble City Cherokee 35.6800 -94.8490 299 40.7

1

- Distance from the OG&E Muskogee Generating Station (35.79194, -95.28794).

2.7.4 What upper air data was used?

There are three ESRL RAOB weather stations within 300 km of the Muskogee area. These 

stations usually take soundings twice a day. The ESRL data files were downloaded from the 

ESRL ROAB web site: http://esrl.noaa.gov/raobs/. The specific sites and distance from the 

Muskogee area are shown below. The RAOB data from the Max Westheimer Airport (OUN)

located in Norman, Oklahoma was the upper air data utilized in the modeling analysis. The 

OUN site is the closest station to the Muskogee area. However, other ESRL stations (LZK) were 

evaluated to determine if they were more representative in terms of determining impacts within 

the Muskogee area.

Table 2.7.4-1 Upper Air Station Location and Elevation and Distance to Muskogee1

Location Call Sign LAT LON ELEV (m) DIST (km)

Norman OUN 35.23 -97.47 362 196

Springfield SGF 37.23 -93.40 394 247

Little Rock LZK 34.83 -92.27 172 295

1

- Distance from the KMKO Meteorological Station (35.6577, -95.3658).

The UA data was reviewed for missing soundings. A single missing sounding will 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. Each UA 

data station was assigned a primary and a secondary replacement UA station. The primary 

station is basically the station that is closest to the station being reviewed. Each replacement 

sounding was documented.
Muskogee Monitoring Versus Modeling Report Page 8

2.7.5 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 

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/.

When determining the surface roughness the default distance of 1 km was utilized. The surface 

characteristics of the individual stations are included in Appendix G.

2.7.6 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 nearest Oklahoma Mesonet station.

2.8 Was background monitoring data utilized in the modeling air quality analysis?

When evaluating modeled source impacts at the monitor to the monitored impacts, background 

concentrations were not added to modeled impacts. The main SO2 sources contributing to the 

impacts at the monitor were explicitly included in the modeling. Smaller sources of SO2

emissions such as natural gas fired sources do not have a significant concentration gradient and 

will not significantly impact the monitor. Therefore, background concentrations from another 

monitor representative of area sources of SO2 were not added to the modeled concentrations.

3. WHAT WERE THE MONITORED IMPACTS?

Monitoring data from the Muskogee monitor (40-101-0167) in the form of the standard is shown 

below. Only data meeting the minimum data collection requirements or the minimum percent 

observations were used when determining the design value.
Muskogee Monitoring Versus Modeling Report Page 9

Table 3-1 Monitor Site Location and Elevation

Location ID LAT LON ELEV (m)

Muskogee 0167 35.79313 -95.30228 158.5

Table 3-2 Monitoring Design Value

Pollutant Averaging Period Basis of Design Value

SO2 1-hour 3 year average of 99th Percentile 1-hour daily maximum

Table 3-3 Monitoring Site 40-101-0167 Design Value

Monitor ID 2012 2013 2014 3 Year

OBS 99th ppb OBS 99th ppb OBS 99th ppb Avg.

40-101-0167 285 H3H 63 365 H4H 37 357 H4H 48 49.3

The 2012 to 2014 three year average of the 99th percentile 1-hour daily maximum values is 49.3 

ppb which is approximately 129.2 μg/m3. The monitored concentration is approximately 66% of 

the NAAQS (75 ppb).

4. WHAT WERE THE MODELED IMPACTS AT THE MONITOR?

The modeled 2012 to 2014 three year average of the 99th percentile 1-hour daily maximum 

values is 149.5 μg/m

3 which is approximately 57.1 ppb. The modeled concentration is 

approximately 76% of the NAAQS (75 ppb). However, the modeled concentration is 15.7% 

different than the monitored concentration.

5 WHAT STEPS WERE TAKEN TO EVALUATE THE DIFFERENCE 

OF THE MONITORED IMPACTS AND THE MODELED IMPACTS?

5.1 Was Representativeness of the Surface Meteorological Data Evaluated?

The 2012-2014 wind roses for the five surrounding Oklahoma Mesonet meteorological stations,

the ISHD KMKO meteorological station, and the ambient air monitoring site (40-101-0167) 

were reviewed to determine the general wind pattern for the area. The majority of the wind roses 

for Oklahoma represent a N-S wind flow pattern. In the summer, the wind out of the S to SE

dominates. In the winter, the wind out of the N to NW dominates. A small percentage of the 

time the wind flows in an E-W direction.

However, due to terrain affects, there is a shift in the wind flow pattern south of Muskogee, 

Oklahoma from a N-S wind flow to an E-W wind flow. This can be seen in the Weber Falls, 

Oklahoma (WEBR) wind rose where the main wind flow comes from the ESE to SE direction 

and NW to NNW direction. As the wind moves toward Muskogee, the wind flow pattern is 

shifted back to the normal Oklahoma wind flow pattern as seen in the Davis Field (KMKO) wind 

rose where it comes from the SE to SSE direction and NNW to N direction. As the wind 

continues to move across the plains, the wind flow pattern spreads out as can be seen in the 

Porter, Oklahoma (PORT) and Haskell, Oklahoma (HASK) wind roses where the flow changes 

to a SSW to SE direction and NNE to NNW direction.
Muskogee Monitoring Versus Modeling Report Page 10

The Tahlequah, Oklahoma (TAHL) wind rose also shows a wider spreading of the wind pattern 

as the wind comes out onto the plains off the Cookson Hills. A similar affect can be seen in the 

wind flow pattern for the Muskogee ambient air monitor (0167).

The Cookson, Oklahoma (COOK) meteorological station located in the Cookson Hills has less of 

a spread than the sites located in the plains with the wind flow pattern from the SE to SSE 

direction and the NW to N direction. The general wind flow pattern for COOK is similar to the 

KMKO Station.

The meteorological data collected at the monitoring site does not meet the standard 

meteorological data collection requirements and was therefore not considered except as a means 

to compare and evaluate the KMKO station meteorological data. Based on a review of modeling 

conducted with the 0167 meteorological data, there was less correlation between the modeling 

results using the 0167 meteorological data than the meteorological data from the KMKO Station.

The Muskogee ambient air monitor (0167) is actually located slightly below the surrounding 

terrain at 520 feet with the wind measurement instrument located at a height of 20 feet. The 

surrounding terrain within 1 mile of the monitor ranges from 490 feet to 550 feet. The hills 

surrounding the area reach heights of 800 feet.

5.2 Were the Effects of Terrain Evaluated?

Muskogee, Oklahoma lies in a river valley and has a low elevation compared to the surrounding 

area. The Muskogee area is unique in that it is located north of the west end of the Arkansas 

Valley and is nestled in the hook of the west end of the Cookson Hills (Lower Buffalo 

Mountains). The Ozarks are made up of the Boston Mountains (Upper and Lower) and define 

the northern portion of the Arkansas River Valley. The Ouachita Mountains make up the 

southern portion of the Arkansas Valley. The Cookson Hills are flat-topped remnants of ancient 

plateaus and the Ouachita’s are folded ridges. To the east of Muskogee, the land opens up into 

prairie grassland. As the wind flows through the west end of the Arkansas River Valley, it meets 

the northern edge of the Ouachita Mountains and starts to flow toward the northwest in the open 

plains.

In the northeast corner of Muskogee, is the Three Rivers Area which is the confluence of the 

Arkansas River, the Neosho River, and the Verdigris River. The three rivers converge and 

continue on as the Arkansas River, which winds through the Cookson Hills. The east side of 

Muskogee is bordered by the Arkansas River and the Cookson Hills. In the southeast corner of 

Muskogee, the Arkansas River is bounded by local terrain (Devil’s Peak and Braggs Mountain) 

creating a small gap through which the surface wind is funneled.

The wind speed from each meteorological station varies and is mainly due to the surface 

roughness of the terrain surrounding the meteorological station. As the surface wind comes 

across rugged terrain, the average wind speed will be reduced as seen in the difference in the 

average wind speed of the KMKO Station and the COOK Station. However, terrain features can 

have other effects on wind speed such as funneling of surface winds between two hills and 

dropping of surface winds from mountainous areas into open plains.
Muskogee Monitoring Versus Modeling Report Page 11

The surface roughness of the individual meteorological stations was compared to the surface 

roughness of the facility being modeled. The surface roughness of the KMKO meteorological 

station was lower than the surface roughness generated by AERSURFACE for the facility. The 

surface roughness of all of the Oklahoma Mesonet stations was larger than the surface roughness 

generated by AERSURFACE for the facility. In order to review the surface roughness 

determination for the KMKO meteorological station, the area used to determine the surface 

roughness was expanded out to two kilometers (km). At 2 km, the surface roughness of the 

KMKO meteorological station closely resembled the surface roughness of the OG&E Muskogee 

facility.

5.3 Were the Sources of Upper Air Data Evaluated?

The three closest meteorological stations where upper air data is recorded are located 

approximately 200, 250 and 300 km from the Muskogee area. Muskogee is almost located 

equidistance between these locations. These large distances can lead to distinct differences when 

determining the structure of the atmosphere for the Muskogee area.

The meteorological station that has the closest elevation to the Muskogee area (~160 to 180

meters above sea level) is Little Rock, Arkansas (LZK). However, LZK is the farthest site from 

the Muskogee area. The Springfield, Missouri station (SGF) and the Norman, Oklahoma station 

(OUN) are at approximately the same elevation and are about 200 meters higher than the 

Muskogee area. However, SGF is 30 meters higher and 50 km distant than OUN. These larges 

differences in elevation can also lead to differences when determining the characteristics of the 

upper air in the Muskogee area.

Depending on the wind patterns for specific days one upper air station may be more 

representative than another upper air station (e.g. OUN may be more representative in the winter 

and LZK may be more representative in the summer). Therefore, use of a single location for a 

whole year may not yield representative modeling results which can lead to differences in 

modeled and monitored ambient impacts.

5.4 How were the Modeled Ambient Impacts Compared to the Monitored Ambient 

Impacts?

To review the correlation between the modeled and monitored ambient impacts, additional 

modeling was conducted changing a single variable to determine which variable had the most 

influence and brought the modeled ambient impacts closer to the monitored ambient impacts. 

The modeled ambient impacts were generated using the following combinations of 

meteorological data:

 KMKO Surface Data W/OUN Upper Air Data,

 KMKO Surface Data combined with wind data from the 40-101-0167 Monitoring Station 

W/OUN Upper Air Data;

 KMKO Surface Data W/LZK Upper Air Data; 

 KMKO Surface Data W/SGF Upper Air Data; 

 KMKO Surface Data W/OUN Upper Air Data W/2 km Surface Roughness;
Muskogee Monitoring Versus Modeling Report Page 12

 KMKO Surface Data W/LZK Upper Air Data W/2 km Surface Roughness;

 KMKO Surface Data W/OUN Upper Air Data W/ROTANG option at 5 degrees; and

 KMKO Surface Data W/OUN Upper Air Data W/ROTANG option at 10 degrees.

Table 5.5-1 Modeled Impacts Versus Monitored Impacts Using Various Inputs

Surface 

Station

Upper Air 

Station

Additional 

Data

Modeled 

Impacts 

(μg/m3)

Monitored 

Impacts 

(μg/m3)

% 

Difference

KMKO OUN 149.5 129.2 15.7

KMKO OUN 0167 188.7 129.2 46.1

KMKO LZK 145.4 129.2 12.5

KMKO SGF 147.0 129.2 13.8

KMKO OUN 2 km SR 137.0 129.2 6.0

KMKO LZK 2 km SR 137.0 129.2 6.0

KMKO OUN ROTANG5 138.3 129.2 7.0

KMKO OUN ROTANG10 159.0 129.2 23.1

The modeling scenarios closest to representing the design value recorded at the monitor were the 

modeling scenarios that increased the surface roughness to be more representative of the surface 

roughness at the site. However, while the three year average of the H4H was very close to the 

actual monitored impacts, the actual hourly impacts predicted at the monitor were not.

In order to evaluate the differences between and correlate the modeled and monitored ambient 

impacts on an hourly basis, predicted modeled ambient impacts for each hour were plotted with 

the monitored ambient impacts for each hour. Based on these graphs, it was determined that 

there was not a significant correlation between the modeled ambient impacts and the monitored 

ambient impacts. The modeled ambient impacts for each hour were also plotted using the 

monitored ambient impacts as the horizontal axis which should have generated a graph which 

can easily be used to correlate the values. Values that are equivalent will be plotted along a line 

with a slope of 1 (@ 45°) extending from the origin. Again these plots did not generate a straight 

line and confirmed that there was no correlation between the hourly modeled and monitored 

ambient impacts.

Finally, to evaluate what was producing the differences between the monitored concentrations 

and the modeled hourly concentrations, the meteorological data for the hours when the monitor 

was predicting high impacts and the hours when the model was predicting high impacts were 

reviewed. From this review the following was determined:

 The monitor was experiencing high impacts when the wind was blowing directly from the 

OG&E facility towards the monitor at 162 degrees.

 The monitor was experiencing high impacts when the average wind speed was 

approximately 5.2 m/s (Slightly Unstable to Neutral Conditions).

 The model was predicting high impacts at the monitor when the wind was blowing directly 

from the OG&E facility towards the monitor at 162 degrees.

 The model was predicting high impacts at the monitor when the average wind speed was 

approximately 2.2 m/s (Very Unstable to Unstable Conditions).
Muskogee Monitoring Versus Modeling Report Page 13

The modeling scenarios that predicted the highest impact were run with downwash and without 

downwash. Removing downwash from the model did not change the predicted design value of 

the model. However, removing downwash from the model did reduce the correlation between 

the modeled and monitored hourly values.

The surface roughness, wind speed, and wind direction significantly affect the modeling results. 

The inability of the AERMOD model to predict on an hour-by-hour basis what is occurring at the 

monitor suggests that there is some doubt concerning the representativeness of the 

meteorological data used in the modeling analysis.

6. WHAT IS THE SUMMARY OF THE REVIEW OF MONITORED 

IMPACTS AND MODELED IMPACTS?

The area surrounding the OG&E Muskogee Generating Station is not adequately characterized 

by the available meteorological data. The terrain effects on the wind direction and speed of the 

area surrounding the modeling domain are not adequately characterized by the area surrounding 

the NWS Station (KMKO). Also, the surface roughness at the NWS Station (KMKO) is not 

representative of the surface roughness of the modeling domain. Additional meteorological 

monitoring in the area of the OG&E Muskogee Generating Station is needed to address questions 

regarding meteorological data representativeness.

A meteorological station located at or near the center of the domain would enhance the accuracy 

of the modeling. The meteorological data should include upper air data to characterize the 

atmospheric conditions within the modeling domain. The station should be equipped with a 

meteorological tower of sufficient height to characterize the vertical structure of the atmosphere 

(100 m) or a SODAR (SOnic Detection And Ranging) instrument, radar wind profiler (RWP),

radio acoustic sounding systems (RASS), or similar instrument to characterize the 

thermodynamic structure of the lower layer of the atmosphere.
Muskogee Monitoring Versus Modeling Report Page 14

7. WHAT REFERENCES WERE USED?

 Additional Clarification Regarding Applicability of Appendix W Modeling Guidance for

the 1-hour NO2 NAAQS (March 1, 2011);

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

ndixW_Hourly-NO2-NAAQS_FINAL_03-01-2011.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

 SO2 NAAQS Designations Modeling Technical Assistance Document (December 2013);

o http://www.epa.gov/oaqps001/sulfurdioxide/pdfs/SO2ModelingTAD.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.
Muskogee Monitoring Versus Modeling Report

Appendix A – Land Use/Land Cover Aerial Photo
Muskogee Monitoring Versus Modeling Report Page A-1

OG&E – Muskogee Generating Station
Muskogee Monitoring Versus Modeling Report

Appendix B – Aerial Photo Overlaid With Facility Data
Muskogee Monitoring Versus Modeling Report Page B-1

OG&E – Muskogee Generating Station
Muskogee Monitoring Versus Modeling Report

Appendix C – Wind Roses (Blowing To)
Muskogee Monitoring Versus Modeling Report Page C-1

2012-2014 KMKO Wind Rose (Blowing To)
Muskogee Monitoring Versus Modeling Report Page C-2

2012-2014 0167 Wind Rose (Blowing To)
Muskogee Monitoring Versus Modeling Report Page C-3

2012-2014 PORT Wind Rose (Blowing To)
Muskogee Monitoring Versus Modeling Report Page C-4

2012-2014 HASK Wind Rose (Blowing To)
Muskogee Monitoring Versus Modeling Report Page C-5

2012-2014 WEBR Wind Rose (Blowing To)
Muskogee Monitoring Versus Modeling Report Page C-6

2012-2014 TALH Wind Rose (Blowing To)
Muskogee Monitoring Versus Modeling Report Page C-7

2012-2014 COOK Wind Rose (Blowing To)
Muskogee Monitoring Versus Modeling Report

Appendix D – Surface Characteristics
Muskogee Monitoring Versus Modeling Report Page D-1

Surface Characteristics

Albedo AVG Wet Dry Surface

OG&E

Winter 0.17 0.65 0.39 1.85 0.043

Spring 0.14 0.39 0.24 1.12 0.051

Summer 0.17 0.44 0.26 1.01 0.065

Fall 0.17 0.65 0.39 1.85 0.060

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

0167

Winter 0.17 0.64 0.37 1.47 0.021

Spring 0.14 0.37 0.24 0.93 0.027

Summer 0.18 0.43 0.28 1.01 0.064

Fall 0.18 0.67 0.37 1.47 0.064

PORT

Winter 0.18 0.73 0.39 1.77 0.026

Spring 0.15 0.36 0.23 1.01 0.042

Summer 0.18 0.45 0.28 1.16 0.183

Fall 0.18 0.73 0.39 1.77 0.183

HASK

Winter 0.18 0.72 0.39 1.78 0.023

Spring 0.15 0.35 0.22 1.00 0.035

Summer 0.19 0.46 0.28 1.22 0.157

Fall 0.19 0.72 0.39 1.78 0.157

WEBR

Winter 0.16 0.58 0.32 1.24 0.022

Spring 0.14 0.31 0.20 0.77 0.032

Summer 0.17 0.38 0.24 0.83 0.170

Fall 0.17 0.58 0.32 1.24 0.170

TAHL

Winter 0.17 0.79 0.40 1.98 0.036

Spring 0.15 0.41 0.24 1.16 0.053

Summer 0.18 0.43 0.27 1.13 0.219

Fall 0.18 0.79 0.40 1.98 0.219

COOK

Winter 0.17 0.95 0.40 1.97 0.090

Spring 0.15 0.63 0.29 1.44 0.139

Summer 0.16 0.33 0.22 0.70 0.382

Fall 0.16 0.95 0.40 1.97 0.382
Muskogee Monitoring Versus Modeling Report

Appendix E – Modeling Versus Monitoring Graphs
Muskogee Monitoring Versus Modeling Report Page E-1

2012 Monitor Versus Modeled Impacts (ppb)

KMKO – Hourly impacts at the monitor site predicted by AERMOD using KMKO meteorological data.

Monitor – Hourly impacts measured at the monitor.

0

10

20

30

40

50

60

70

80

90

KMKO

Monitor
Muskogee Monitoring Versus Modeling Report Page E-2

2013 Monitor Versus Modeled Impacts (ppb)

KMKO – Hourly impacts at the monitor site predicted by AERMOD using KMKO meteorological data.

Monitor – Hourly impacts measured at the monitor.

0

10

20

30

40

50

60

70

80

90

KMKO

Monitor
Muskogee Monitoring Versus Modeling Report Page E-3

2014 Monitor Versus Modeled Impacts (ppb)

KMKO – Hourly impacts at the monitor site predicted by AERMOD using KMKO meteorological data.

Monitor – Hourly impacts measured at the monitor.

0

10

20

30

40

50

60

70

80

90

KMKO

Monitor
Muskogee Monitoring Versus Modeling Report Page E-4

0

20

40

60

80

100

120

0 20 40 60 80 100 120

KMKO

KMKO
Muskogee Monitoring Versus Modeling Report

Appendix F – Comparison of Hours with High Impacts at the Monitor with Sub-Hourly 

Impact, Meteorological, and Source Data
Muskogee Monitoring Versus Modeling Report Page F-1

2014 Monitor Data for Highest Monitored Impacts & Main Contributing Source Data for the Hour

Monitor Data Original 5-Minute On-Site Data Source Parameters

Conc. 5-Min Impact Missing WSPD WDIR TAIR RH ID Emissions Temp. Velocity

Year Month Day Hour ppbv Hour ppbv Code MPH DEG °F % g/s K m/s

2014 3 21 7 42 6:00 2 5 131 52 33 4 304.2 415 19.56

6:05 3 7 137 53 33 5 238.6 400 16.45

6:10 11 8 145 53 32 6 0.0 296 1.50

6:15 25 9 144 53 32 GP1 0.3 452 3.48

6:20 50 8 154 54 32 GP2 58.9 416 11.26

6:25 49 7 154 54 32

6:30 44 7 157 54 34

6:35 50 6 160 54 35

6:40 66 8 154 54 35

6:45 66 10 157 54 33

6:50 74 10 156 55 33

6:55 67 10 156 55 33

2014 3 21 8 58 7:00 59 11 158 55 32 4 304.6 417 21.03

7:05 65 9 161 55 33 5 237.3 398 17.04

7:10 49 9 164 55 35 6 0.0 296 0.62

7:15 24 11 162 55 35 GP1 0.3 452 3.48

7:20 15 10 162 55 35 GP2 58.9 416 11.26

7:25 41 8 161 55 35

7:30 72 8 153 56 35

7:35 82 8 153 56 34

7:40 80 9 157 56 34

7:45 85 9 157 56 34

7:50 AN 7 164 56 35

7:55 BA 9 164 56 36

2014 3 21 9 BF 8:00 BA 9 161 56 35 4 300.7 417 20.99

8:05 BA 11 166 57 35 5 237.9 399 16.84

8:10 BA 12 166 57 34 6 0.0 296 0.53

8:15 BA 11 163 57 34 GP1 0.3 452 3.48

8:20 BA 12 164 58 34 GP2 58.9 416 11.26

8:25 BA 11 168 58 34

8:30 BA 12 164 58 33

8:35 BA 11 161 58 33

8:40 BA 11 158 58 33
Muskogee Monitoring Versus Modeling Report Page F-2

Monitor Data Original 5-Minute On-Site Data Source Parameters

Conc. 5-Min Impact Missing WSPD WDIR TAIR RH ID Emissions Temp. Velocity

Year Month Day Hour ppbv Hour ppbv Code MPH DEG °F % g/s K m/s

8:45 BA 13 168 58 33

8:50 BA 13 164 59 33

8:55 BA 13 165 59 33

2014 3 31 3 10 2:00 2 11 147 60 43 4 194.1 406 14.77

2:05 2 14 146 60 43 5 16.1 375 9.19

2:10 4 12 153 60 43 6 210.6 398 16.12

2:15 4 11 150 60 43 GP1 17.5 452 15.74

2:20 3 12 149 60 43 GP2 31.5 416 6.12

2:25 3 12 152 59 43

2:30 5 11 150 59 44

2:35 13 11 150 60 44

2:40 15 12 149 60 43

2:45 14 10 150 60 44

2:50 23 10 152 60 44

2:55 36 11 152 60 44

2014 3 31 4 70 3:00 40 10 157 60 45 4 197.3 405 14.67

3:05 59 9 158 60 45 5 76.8 378 10.70

3:10 72 11 161 60 45 6 211.3 397 16.33

3:15 73 10 158 60 45 GP1 17.5 452 15.74

3:20 77 13 157 60 45 GP2 31.5 416 6.12

3:25 83 11 156 60 46

3:30 84 13 158 60 46

3:35 84 13 156 60 46

3:40 72 12 162 60 47

3:45 46 12 163 59 47

3:50 71 11 155 59 47

3:55 84 11 157 59 47

2014 3 31 5 33 4:00 74 11 162 59 48 4 215.7 404 15.34

4:05 64 12 159 59 49 5 86.5 386 10.69

4:10 65 12 158 59 49 6 251.5 395 18.45

4:15 59 11 164 59 49 GP1 17.5 452 15.74

4:20 42 11 168 59 50 GP2 31.5 416 6.12

4:25 26 12 166 59 50
Muskogee Monitoring Versus Modeling Report Page F-3

Monitor Data Original 5-Minute On-Site Data Source Parameters

Conc. 5-Min Impact Missing WSPD WDIR TAIR RH ID Emissions Temp. Velocity

Year Month Day Hour ppbv Hour ppbv Code MPH DEG °F % g/s K m/s

4:30 16 12 164 59 50

4:35 10 12 163 58 50

4:40 11 14 164 58 50

4:45 10 15 166 59 49

4:50 8 14 162 58 50

4:55 7 13 163 58 50

2014 6 16 21 23 20:00 8 10 150 82 61 4 312.4 435 22.87

20:05 7 9 154 82 62 5 341.4 424 22.70

20:10 7 10 148 82 62 6 324.1 430 22.27

20:15 7 11 152 82 62 GP1 13.2 452 8.80

20:20 10 11 153 82 63 GP2 51.3 416 9.89

20:25 11 11 158 82 63

20:30 15 11 153 82 62

20:35 28 10 155 82 63

20:40 35 10 155 82 64

20:45 56 11 152 82 64

20:50 49 10 152 82 64

20:55 48 12 150 82 64

2014 6 16 22 58 21:00 34 11 155 82 64 4 316.7 435 22.85

21:05 47 11 159 82 65 5 345.7 424 22.72

21:10 59 13 158 82 65 6 320.0 427 21.93

21:15 80 10 158 82 65 GP1 13.2 452 8.80

21:20 70 9 151 82 66 GP2 51.3 416 9.89

21:25 69 11 156 81 67

21:30 64 12 149 81 67

21:35 35 12 153 81 67

21:40 34 11 157 81 68

21:45 50 11 154 81 68

21:50 71 10 157 81 68

21:55 77 11 155 81 69

2014 6 16 23 67 22:00 80 11 153 81 69 4 316.0 434 22.45

22:05 91 11 154 81 69 5 365.8 424 22.70

22:10 89 11 157 81 69 6 322.2 427 21.92
Muskogee Monitoring Versus Modeling Report Page F-4

Monitor Data Original 5-Minute On-Site Data Source Parameters

Conc. 5-Min Impact Missing WSPD WDIR TAIR RH ID Emissions Temp. Velocity

Year Month Day Hour ppbv Hour ppbv Code MPH DEG °F % g/s K m/s

22:15 84 10 157 81 70 GP1 13.2 452 8.80

22:20 79 10 163 81 70 GP2 51.3 416 9.89

22:25 81 10 159 81 70

22:30 89 9 155 80 71

22:35 87 9 163 80 71

22:40 62 11 168 80 71

22:45 30 12 168 80 72

22:50 21 13 169 80 72

22:55 15 13 167 80 71

2014 6 16 24 14 23:00 12 11 167 80 72 4 351.4 433 22.49

23:05 11 11 166 80 73 5 382.8 423 22.50

23:10 9 11 166 80 73 6 247.0 424 17.97

23:15 9 10 172 80 73 GP1 13.2 452 8.80

23:20 10 10 163 79 74 GP2 51.3 416 9.89

23:25 12 12 163 79 74

23:30 10 11 161 79 74

23:35 11 8 161 79 74

23:40 12 5 149 79 75

23:45 19 6 149 78 76

23:50 26 7 151 78 76

23:55 30 7 149 78 77

WSPD - Wind Speed; WDIR - Wind Direction; TAIR - Temperature of Air; RH - Relative Humidity.

AN – Machine Malfunction.

BA - Maintenance/Routine Repairs.

BF - Precision/Zero/Span

4, 5, 6 - OG&E Electrical Generating Units 4, 5, & 6, respectively.

GP1, GP2 - Georgia Pacific Stacks 1 and 2, respectively.

The hourly values for the monitor data are shifted one hour because the monitor time is 0-23 hours and the modeling time is 1-24 hours.

The data includes the hour prior to and the hour after the highest impacts.

The hours with the highest impacts are highlighted.
Muskogee Monitoring Versus Modeling Report Page F-5

2013 Monitor Data for Highest Monitored Impacts & Main Contributing Source Data for the Hour

Monitor Data Original 5-Minute On-Site Data Source Parameters

Conc. 5-Min Impact Missing WSPD WDIR TAIR RH ID Emissions Temp. Velocity

Year Month Day Hour ppbv Hour ppbv Code MPH DEG °F % g/s K m/s

2013 3 7 10 22 9:00 1 12 164 48 35 4 0.0 282 0.60

9:05 1 12 154 48 34 5 223.8 402 17.51

9:10 4 11 156 49 34 6 240.1 410 19.88

9:15 5 10 162 49 34 GP1 14.1 452 9.37

9:20 4 12 162 50 33 GP2 49.6 416 9.60

9:25 11 14 161 50 33

9:30 13 13 166 50 33

9:35 15 11 163 51 33

9:40 30 10 177 51 32

9:45 60 10 171 52 32

9:50 48 14 180 52 31

9:55 70 12 175 52 31

2013 3 7 11 45 10:00 69 13 182 52 31 4 0.0 283 0.44

10:05 89 15 178 53 30 5 232.5 404 18.11

10:10 66 13 177 53 31 6 242.5 413 20.22

10:15 77 13 177 53 30 GP1 14.1 452 9.37

10:20 59 13 171 53 30 GP2 49.6 416 9.60

10:25 26 15 180 53 30

10:30 52 13 175 53 30

10:35 35 12 178 53 31

10:40 46 13 179 54 31

10:45 11 13 180 54 31

10:50 8 15 182 54 30

10:55 6 15 189 54 31

2013 3 7 12 30 11:00 11 12 174 54 31 4 0.0 283 0.38

11:05 16 11 179 55 31 5 238.2 408 19.08

11:10 31 12 181 55 31 6 244.3 414 20.12

11:15 51 13 177 55 30 GP1 14.1 452 9.37

11:20 20 13 182 55 30 GP2 49.6 416 9.60

11:25 54 12 177 56 30

11:30 35 10 168 56 30

11:35 27 14 185 56 29

11:40 13 12 181 57 30

11:45 10 11 169 57 29
Muskogee Monitoring Versus Modeling Report Page F-6

Monitor Data Original 5-Minute On-Site Data Source Parameters

Conc. 5-Min Impact Missing WSPD WDIR TAIR RH ID Emissions Temp. Velocity

Year Month Day Hour ppbv Hour ppbv Code MPH DEG °F % g/s K m/s

11:50 32 13 167 57 29

11:55 57 14 177 57 29

2013 5 27 22 39 21:00 31 13 158 77 62 4 0.0 308 0.07

21:05 35 11 158 77 62 5 258.5 429 24.13

21:10 39 11 159 77 62 6 292.3 416 21.64

21:15 35 14 165 77 61 GP1 13.5 452 9.01

21:20 42 15 161 77 61 GP2 61.0 416 11.63

21:25 46 16 160 77 61

21:30 35 15 162 78 61

21:35 40 14 160 77 61

21:40 45 14 160 77 62

21:45 47 11 158 77 62

21:50 41 10 153 77 64

21:55 34 10 161 76 65

2013 5 27 23 46 22:00 40 12 161 76 64 4 0.0 308 0.00

22:05 47 13 159 76 64 5 219.5 431 21.13

22:10 50 14 159 76 63 6 237.5 411 18.88

22:15 55 14 162 77 62 GP1 13.5 452 9.01

22:20 52 12 156 77 63 GP2 61.0 416 11.63

22:25 62 11 160 76 64

22:30 57 11 159 77 63

22:35 62 10 155 76 64

22:40 57 10 154 76 64

22:45 31 11 152 76 64

22:50 21 14 151 76 64

22:55 17 13 149 76 64

2013 5 27 24 9 23:00 12 14 156 76 64 4 0.0 308 0.09

23:05 11 13 147 76 64 5 176.6 425 18.21

23:10 9 15 147 76 63 6 165.1 402 15.44

23:15 7 12 149 76 63 GP1 13.5 452 9.01

23:20 8 14 154 76 63 GP2 61.0 416 11.63

23:25 8 11 154 76 63

23:30 8 12 155 76 63

23:35 9 12 155 76 63

23:40 8 10 152 76 63
Muskogee Monitoring Versus Modeling Report Page F-7

Monitor Data Original 5-Minute On-Site Data Source Parameters

Conc. 5-Min Impact Missing WSPD WDIR TAIR RH ID Emissions Temp. Velocity

Year Month Day Hour ppbv Hour ppbv Code MPH DEG °F % g/s K m/s

23:45 9 13 154 76 63

23:50 10 14 151 76 63

23:55 9 11 159 76 62

WSPD - Wind Speed; WDIR - Wind Direction; TAIR - Temperature of Air; RH - Relative Humidity.

4, 5, 6 - OG&E Electrical Generating Units 4, 5, & 6, respectively.

GP1, GP2 - Georgia Pacific Stacks 1 and 2, respectively.

The hourly values for the monitor data are shifted one hour because the monitor time is 0-23 hours and the modeling time is 1-24 hours.

The data includes the hour prior to and the hour after the highest impacts.

The hours with the highest impacts are highlighted.
Muskogee Monitoring Versus Modeling Report Page F-8

2012 Monitor Data for Highest Monitored Impacts & Main Contributing Source Data for the Hour

Monitor Data 0167 Data Source Parameters

Conc. 5-Min Impact Missing WSPD WDIR ID Emissions Temp. Velocity

Year Month Day Hour ppbv Hour ppbv Code MPH DEG g/s K m/s

2012 1 15 11 27 10:00 2 12 153 4 205.2 396 18.62

10:05 5 5 221.5 387 15.91

10:10 7 6 325.4 393 20.59

10:15 10 GP1 14.0 452 9.31

10:20 24 GP2 54.6 416 10.52

10:25 34

10:30 31

10:35 15

10:40 27

10:45 75

10:50 39

10:55 62

2012 1 15 12 80 11:00 66 14 168 4 209.9 396 18.28

11:05 66 5 223.8 389 15.98

11:10 68 6 277.6 390 17.45

11:15 76 GP1 14.0 452 9.31

11:20 99 GP2 54.6 416 10.52

11:25 86

11:30 70

11:35 51

11:40 72

11:45 79

11:50 93

11:55 136

2012 1 15 13 39 12:00 89 12 165 4 187.7 398 16.99

12:05 28 5 184.6 390 15.02

12:10 25 6 218.2 385 14.42

12:15 37 GP1 14.0 452 9.31

12:20 53 GP2 54.6 416 10.52

12:25 40

12:30 23
Muskogee Monitoring Versus Modeling Report Page F-9

Monitor Data 0167 Data Source Parameters

Conc. 5-Min Impact Missing WSPD WDIR ID Emissions Temp. Velocity

Year Month Day Hour ppbv Hour ppbv Code MPH DEG g/s K m/s

12:35 47

12:40 6

12:45 16

12:50 33

12:55 77

2012 1 15 18 5 17:00 5 12 154 4 180.3 392 16.55

17:05 2 5 159.4 387 13.83

17:10 5 6 193.0 378 12.55

17:15 17 GP1 14.0 452 9.31

17:20 10 GP2 54.6 416 10.52

17:25 16

17:30 5

17:35 2

17:40 2

17:45 1

17:50 2

17:55 2

2012 1 15 19 68 18:00 3 11 157 4 204.0 392 17.47

18:05 8 5 213.8 387 15.51

18:10 11 6 246.4 381 15.01

18:15 18 GP1 14.0 452 9.31

18:20 98 GP2 54.6 416 10.52

18:25 91

18:30 59

18:35 81

18:40 105

18:45 114

18:50 114

18:55 115

2012 1 15 20 65 19:00 125 10 162 4 184.2 393 16.97

19:05 72 5 207.1 390 15.37

19:10 21 6 212.0 383 13.92
Muskogee Monitoring Versus Modeling Report Page F-10

Monitor Data 0167 Data Source Parameters

Conc. 5-Min Impact Missing WSPD WDIR ID Emissions Temp. Velocity

Year Month Day Hour ppbv Hour ppbv Code MPH DEG g/s K m/s

19:15 76 GP1 14.0 452 9.31

19:20 78 GP2 54.6 416 10.52

19:25 69

19:30 74

19:35 66

19:40 73

19:45 44

19:50 35

19:55 55

2012 1 15 21 27 20:00 67 9 158 4 171.0 392 16.58

20:05 55 5 204.3 391 15.25

20:10 35 6 195.0 381 13.19

20:15 16 GP1 14.0 452 9.31

20:20 13 GP2 54.6 416 10.52

20:25 35

20:30 37

20:35 19

20:40 13

20:45 9

20:50 8

20:55 24

2012 5 23 10 22 9:00 27 13 166 4 202.0 400 16.93

9:05 12 5 0.0 304 0.00

9:10 3 6 360.1 422 24.05

9:15 6 GP1 13.5 452 9.03

9:20 10 GP2 50.3 416 9.79

9:25 8

9:30 17

9:35 20

9:40 7

9:45 27

9:50 66

9:55 58
Muskogee Monitoring Versus Modeling Report Page F-11

Monitor Data 0167 Data Source Parameters

Conc. 5-Min Impact Missing WSPD WDIR ID Emissions Temp. Velocity

Year Month Day Hour ppbv Hour ppbv Code MPH DEG g/s K m/s

2012 5 23 11 69 10:00 98 13 161 4 205.9 402 17.33

10:05 98 5 0.0 305 0

10:10 109 6 365.9 361 23.98

10:15 65 GP1 13.5 452 9.03

10:20 81 GP2 50.3 416 9.79

10:25 33

10:30 40

10:35 64

10:40 92

10:45 58

10:50 42

10:55 50

2012 5 23 12 32 11:00 68 13 157 4 206.8 406 17.60

11:05 84 5 0.0 306 0.0

11:10 11 6 366.8 423 24.04

11:15 12 GP1 13.5 452 9.03

11:20 26 GP2 50.3 416 9.79

11:25 12

11:30 13

11:35 44

11:40 30

11:45 11

11:50 23

11:55 51

WSPD - Wind Speed; WDIR - Wind Direction; TAIR - Temperature of Air; RH - Relative Humidity.

4, 5, 6 - OG&E Electrical Generating Units 4, 5, & 6, respectively.

GP1, GP2 - Georgia Pacific Stacks 1 and 2, respectively.

The hourly values for the monitor data are shifted one hour because the monitor time is 0-23 hours and the modeling time is 1-24 hours.

The wind speed data for the monitor was not available in 5-minute intervals for 2012.

The data includes the hour prior to and the hour after the highest impacts.

The hours with the highest impacts are highlighted.
Muskogee Monitoring Versus Modeling Report

Appendix G – Comparison of Hours with Modeled and Monitored High Impacts
Muskogee Monitoring Versus Modeling Report Page G-1

2014 Monitored Impact/Modeled Impact at Monitor & Associated Surface Meteorological Data

Sensible 

Heat 

flux

Surface 

Friction 

Velocity

Convective 

Velocity 

Scale

Vertical 

Potential 

Temp. 

Gradient

Height of 

Convectively 

Generated 

Boundary 

Layer

Height of 

Mechanically 

Generated 

Boundary 

Layer

MoninObukhov 

Length

Surface 

Roughness 

Length

Modeled Monitor H u* w* VPTG Zic Zim L zo

YR MO DY HR ppb ppb Station W/m2 m/s m/s K/m m m m m

14 3 21 8 9 58 KMKO 6.6 0.347 0.241 0.007 74 490 -558.5 0.023

0167 6.4 0.272 0.238 0.016 74 341 -277.2 0.027

14 3 31 4 2 70 KMKO -35.4 0.327 -9 -9 -999 450 87.2 0.023

0167 -33.6 0.312 -9 -9 -999 418 79.4 0.027

14 6 16 22 0 58 KMKO -36.6 0.350 -9 -9 -999 498 104.1 0.037

0167 -37 0.357 -9 -9 -999 511 108.3 0.064

14 6 16 23 4 67 KMKO -39.2 0.375 -9 -9 -999 552 119.2 0.037

0167 -36.3 0.350 -9 -9 -999 497 104.2 0.064

2014 Monitored Impact/Modeled Impact at Monitor & Associated Surface Meteorological Data

Bowen 

Ratio Albedo

Wind 

Speed

Wind 

Direction Temperature

Relative 

Humidity Pressure

Cloud 

Cover

Modeled Monitor Bo r Ws Wd temp rh pres ccvr

YR MO DY HR ppb ppb Station m/s deg. K % mb tenths

14 3 21 8 9 58 KMKO 0.33 0.32 5.21 161 284.9 46 990 0

0167 0.37 0.31 3.94 160 286.2 35 988 9

14 3 31 4 2 70 KMKO 0.33 1 5.44 157 287.5 55 989 0

0167 0.37 1 5.1 159 288.5 46 988 0

14 6 16 22 0 58 KMKO 0.30 1 5.33 155 299.2 76 991 0

0167 0.28 1 4.92 155 300.5 67 989 0

14 6 16 23 4 67 KMKO 0.30 1 5.65 160 298.8 81 991 0

0167 0.28 1 4.84 162 300.1 71 990 0
Muskogee Monitoring Versus Modeling Report Page G-2

2013 Monitored Impact/Modeled Impact at Monitor & Associated Surface Meteorological Data

Sensible 

Heat 

flux

Surface 

Friction 

Velocity

Convective 

Velocity 

Scale

Vertical 

Potential 

Temp. 

Gradient

Height of 

Convectively 

Generated 

Boundary 

Layer

Height of 

Mechanically 

Generated 

Boundary 

Layer

MoninObukhov 

Length

Surface 

Roughness 

Length

Modeled Monitor H u* w* VPTG Zic Zim L zo

YR MO DY HR ppb ppb Station W/m2 m/s m/s K/m m m m m

13 3 7 11 5 45 KMKO 83.2 0.51 0.806 0.01 225 874 -142.9 0.023

0167 108.1 0.436 0.936 0.01 270 689 -68.2 0.027

13 5 27 23 0 46 KMKO -39.4 0.376 -9 -9 -999 553 118.7 0.023

0167 -35.7 0.342 -9 -9 -999 481 98.7 0.027

2013 Monitored Impact/Modeled Impact at Monitor & Associated Surface Meteorological Data

Bowen 

Ratio Albedo

Wind 

Speed

Wind 

Direction Temperature

Relative 

Humidity Pressure

Cloud 

Cover

Modeled Monitor Bo r Ws Wd temp rh pres ccvr

YR MO DY HR ppb ppb Station m/s deg. K % mb tenths

13 3 7 11 5 45 KMKO 0.33 0.15 7.48 153 285.4 37 1002 0

0167 0.37 0.15 6.03 178 285.1 30 1001 0

13 5 27 23 0 46 KMKO 0.33 1 6.11 154 296.4 78 987 0

0167 0.37 1 5.49 156 297.7 64 986 0
Muskogee Monitoring Versus Modeling Report Page G-3

2012 Monitored Impact/Modeled Impact at Monitor & Associated Surface Meteorological Data

Sensible 

Heat 

flux

Surface 

Friction 

Velocity

Convective 

Velocity 

Scale

Vertical 

Potential 

Temp. 

Gradient

Height of 

Convectively 

Generated 

Boundary 

Layer

Height of 

Mechanically 

Generated 

Boundary 

Layer

MoninObukhov 

Length

Surface 

Roughness 

Length

Modeled Monitor H u* w* VPTG Zic Zim L zo

YR MO DY HR ppb ppb Station W/m2 m/s m/s K/m m m m m

12 1 15 12 0 80 KMKO 97.3 0.522 0.781 0.007 175 907 -130.7 0.016

0167 91.8 0.430 0.759 0.005 171 676 -77.4 0.021

12 1 15 19 0 68 KMKO -31.8 0.289 -9 -9 -999 373 67.2 0.016

0167 -31.2 0.284 -9 -9 -999 364 65.3 0.021

12 1 15 20 0 65 KMKO -31.7 0.287 -9 -9 -999 370 66.5 0.016

0167 -27.5 0.250 -9 -9 -999 300 50.4 0.021

12 5 23 11 11 69 KMKO 266.4 0.526 1.887 0.005 888 915 -48.0 0.023

0167 251.6 0.440 1.790 0.005 805 700 -29.8 0.027

2012 Monitored Impact/Modeled Impact at Monitor & Associated Surface Meteorological Data

Bowen 

Ratio Albedo

Wind 

Speed

Wind 

Direction Temperature

Relative 

Humidity Pressure

Cloud 

Cover

Modeled Monitor Bo r Ws Wd temp rh pres ccvr

YR MO DY HR ppb ppb Station m/s deg. K % mb tenths

12 1 15 12 0 80 KMKO 0.72 0.21 8.11 143 284.2 40 1000 0

0167 0.64 0.2 6.26 168 284.9 32 1003 0

12 1 15 19 0 68 KMKO 0.72 1 5.19 155 284.2 46 995 0

0167 0.64 1 4.92 157 285.9 36 998 0

12 1 15 20 0 65 KMKO 0.72 1 5.17 152 284.2 46 995 0

0167 0.64 1 4.47 162 285.4 39 998 0

12 5 23 11 11 69 KMKO 1.03 0.14 7.37 152 301.4 48 985 0

0167 0.93 0.14 5.81 161 299.2 42 988 0
Muskogee Monitoring Versus Modeling Report Page G-4

2014 Monitored Impact/Modeled Impact at Monitor & Associated Surface Meteorological Data

Sensible 

Heat 

flux

Surface 

Friction 

Velocity

Convective 

Velocity 

Scale

Vertical 

Potential 

Temp. 

Gradient

Height of 

Convectively 

Generated 

Boundary 

Layer

Height of 

Mechanically 

Generated 

Boundary 

Layer

MoninObukhov 

Length

Surface 

Roughness 

Length

Modeled Monitor H u* w* VPTG Zic Zim L zo

YR MO DY HR ppb ppb Station W/m2 m/s m/s K/m m m m m

14 1 10 14 97 0 KMKO 32.9 0.168 0.587 0.017 215 176 -12.5 0.016

0167 30.0 0.213 0.522 0.016 165 237 -28.3 0.021

14 3 4 13 46 4 KMKO 99.3 0.294 1.054 0.033 420 384 -22.8 0.023

0167 133.8 0.226 1.19 0.033 448 260 -7.7 0.027

14 6 25 9 54 1 KMKO 73.2 0.222 0.814 0.009 262 251 -13.2 0.037

0167 71.0 0.221 0.780 0.009 237 250 -13.5 0.037

14 8 13 9 46 1 KMKO 88.7 0.166 0.876 0.006 269 163 -4.6 0.037

0167 82.1 0.165 0.851 0.006 267 161 -4.9 0.037

2014 Monitored Impact/Modeled Impact at Monitor & Associated Surface Meteorological Data

Bowen 

Ratio Albedo

Wind 

Speed

Wind 

Direction Temperature

Relative 

Humidity Pressure

Cloud 

Cover

Modeled Monitor Bo r Ws Wd temp rh pres ccvr

YR MO DY HR ppb ppb Station m/s deg. K % mb tenths

14 1 10 14 97 0 KMKO 1.94 0.21 2.28 162 284.2 100 982 10

0167 1.47 0.2 2.94 167 284.5 91 980 10

14 3 4 13 46 4 KMKO 0.33 0.15 3.93 161 275.4 49 999 0

0167 0.37 0.15 2.64 175 275 47 998 0

14 6 25 9 54 1 KMKO 0.30 0.20 2.57 171 299.9 73 996 0

0167 0.28 0.19 2.57 171 299.8 70 995 0

14 8 13 9 46 1 KMKO 0.50 0.21 1.70 153 296.4 63 999 0

0167 0.43 0.20 1.70 153 296.0 62 998 0
Muskogee Monitoring Versus Modeling Report Page G-5

2013 Monitored Impact/Modeled Impact at Monitor & Associated Surface Meteorological Data

Sensible 

Heat 

flux

Surface 

Friction 

Velocity

Convective 

Velocity 

Scale

Vertical 

Potential 

Temp. 

Gradient

Height of 

Convectively 

Generated 

Boundary 

Layer

Height of 

Mechanically 

Generated 

Boundary 

Layer

MoninObukhov 

Length

Surface 

Roughness 

Length

Modeled Monitor H u* w* VPTG Zic Zim L zo

YR MO DY HR ppb ppb Station W/m2 m/s m/s K/m m m m m

13 7 21 11 64 2 KMKO 41.2 0.163 0.740 0.007 347 174 -9.3 0.037

0167 13.7 0.120 0.422 0.013 193 108 -11.2 0.064

13 7 25 9 59 2 KMKO 96.9 0.194 0.959 0.005 324 204 -6.6 0.037

0167 36.3 0.179 0.564 0.006 176 181 -13.9 0.037

13 8 12 9 63 2 KMKO 93.8 0.182 0.921 0.005 296 186 -5.7 0.037

0167 57.6 0.136 0.627 0.005 152 121 -3.9 0.064

13 12 10 13 61 2 KMKO 66.7 0.217 0.776 0.017 252 243 -13.8 0.016

0167 79.6 0.202 0.848 0.016 275 218 -9.3 0.021

2013 Monitored Impact/Modeled Impact at Monitor & Associated Surface Meteorological Data

Bowen 

Ratio Albedo

Wind 

Speed

Wind 

Direction Temperature

Relative 

Humidity Pressure

Cloud 

Cover

Modeled Monitor Bo r Ws Wd temp rh pres ccvr

YR MO DY HR ppb ppb Station m/s deg. K % mb tenths

13 7 21 11 64 2 KMKO 0.50 0.19 1.82 169 299.2 84 992 10

0167 0.43 0.18 1.21 9 297.6 85 991 10

13 7 25 9 59 2 KMKO 0.50 0.21 2.08 160 298.1 93 996 0

0167 0.43 0.20 2.08 160 298.8 78 995 9

13 8 12 9 63 2 KMKO 0.50 0.21 1.91 159 300.9 81 995 2

0167 0.43 0.20 1.18 183 300.8 74 994 8

13 12 10 13 61 2 KMKO 0.41 0.21 2.98 158 272.5 56 1008 0

0167 0.37 0.20 2.53 183 271.6 52 1006 0
Muskogee Monitoring Versus Modeling Report Page G-6

2012 Monitored Impact/Modeled Impact at Monitor & Associated Surface Meteorological Data

Sensible 

Heat 

flux

Surface 

Friction 

Velocity

Convective 

Velocity 

Scale

Vertical 

Potential 

Temp. 

Gradient

Height of 

Convectively 

Generated 

Boundary 

Layer

Height of 

Mechanically 

Generated 

Boundary 

Layer

MoninObukhov 

Length

Surface 

Roughness 

Length

Modeled Monitor H u* w* VPTG Zic Zim L zo

YR MO DY HR ppb ppb Station W/m2 m/s m/s K/m m m m m

12 2 14 13 60 23 KMKO 134.0 0.239 0.918 0.016 204 280 -9.0 0.016

0167 126.2 0.191 0.886 0.017 196 201 -4.9 0.021

12 5 5 8 65 0 KMKO 89.0 0.222 0.851 0.013 244 251 -10.8 0.023

0167 86.0 0.133 0.836 0.013 241 117 -2.4 0.027

12 7 13 8 76 1 KMKO 105.0 0.158 0.886 0.007 235 151 -3.4 0.037

0167 91.4 0.156 0.823 0.007 217 148 -3.7 0.037

12 9 26 9 60 0 KMKO 83.2 0.131 0.921 0.014 333 115 -2.4 0.031

0167 78.7 0.131 0.900 0.014 328 114 -2.5 0.031

12 11 24 10 67 0 KMKO 85.4 0.167 0.768 0.018 190 163 -4.9 0.031

0167 78.2 0.165 0.730 0.018 179 161 -5.2 0.031

12 12 7 15 91 2 KMKO 21.7 0.117 0.613 0.009 374 97 -6.5 0.016

0167 19.7 0.116 0.585 0.009 357 96 -7.1 0.016

12 12 7 16 116 0 KMKO 7.0 0.083 0.424 0.009 384 58 -7.3 0.016

0167 6.3 0.083 0.404 0.009 365 57 -7.9 0.016
Muskogee Monitoring Versus Modeling Report Page G-7

2012 Monitored Impact/Modeled Impact at Monitor & Associated Surface Meteorological Data

Bowen 

Ratio Albedo

Wind 

Speed

Wind 

Direction Temperature

Relative 

Humidity Pressure

Cloud 

Cover

Modeled Monitor Bo r Ws Wd temp rh pres ccvr

YR MO DY HR ppb ppb Station m/s deg. K % mb tenths

12 2 14 13 60 23 KMKO 0.72 0.19 3.15 158 280.4 73 993 5

0167 0.64 0.18 2.24 182 279.9 67 996 5

12 5 5 8 65 0 KMKO 1.03 0.19 2.78 156 294.2 93 990 0

0167 0.93 0.19 1.34 142 296.4 68 993 0

12 7 13 8 76 1 KMKO 1.42 0.24 1.55 162 299.9 70 995 0

0167 1.01 0.23 1.55 162 299.2 67 998 0

12 9 26 9 60 0 KMKO 0.72 0.23 1.28 170 297.5 63 994 5

0167 0.64 0.22 1.28 170 297.5 63 994 5

12 11 24 10 67 0 KMKO 1.94 0.25 1.79 155 276.4 50 1007 0

0167 1.47 0.24 1.79 155 276.4 50 1007 0

12 12 7 15 91 2 KMKO 1.94 0.24 1.5 167 287.5 86 987 10

0167 1.47 0.23 1.5 167 287.5 86 987 10

12 12 7 16 116 0 KMKO 1.94 0.31 1.08 166 288.1 83 988 10

0167 1.47 0.30 1.08 166 288.1 83 988 10