SO2 Characterization Modeling Analysis for the 

H.A. Wagner and Brandon Shores Power Plants 

U.S. Environmental Protection Agency

Ambient Air Monitoring Program

Air and Radiation Management Administration

Maryland Dep

MARYLAND 

1800 Washington Boulevard | Baltimore, MD 21230 | www.mde.maryland.gov

410-537-3000 | 800

Lawrence J. Hogan, Jr., 

1 

Characterization Modeling Analysis for the 

H.A. Wagner and Brandon Shores Power Plants 

Prepared for: 

U.S. Environmental Protection Agency

Prepared by: 

Ambient Air Monitoring Program

Air and Radiation Management Administration

Maryland Department of the Environment

April 19, 2016

ARYLAND DEPARTMENT OF THE ENVIRONMENT 

1800 Washington Boulevard | Baltimore, MD 21230 | www.mde.maryland.gov

3000 | 800-633-6101 | TTY Users: 800-735-2258 

Lawrence J. Hogan, Jr., Governor | Boyd K. Rutherford, Lt. Governor

 Ben Grumbles, Secretary

Characterization Modeling Analysis for the 

H.A. Wagner and Brandon Shores Power Plants 

1800 Washington Boulevard | Baltimore, MD 21230 | www.mde.maryland.gov
2 

Table of Contents 

1 INTRODUCTION .............................................................................................................................. 3

1.1 Background ............................................................................................................................................... 3

2 MODELING PROCEDURES AND RESULTS ............................................................................... 4

2.1 Dispersion Model Selection ....................................................................................................................... 4

2.2 Emissions Data and Source Characterization ............................................................................................. 4

2.3 Good Engineering Practice (GEP) Analysis ............................................................................................ 5

2.4 Meteorological Data Processing ............................................................................................................... 6

2.5 Receptors to be Modeled .......................................................................................................................... 9

2.6 Model Configurations and Options ......................................................................................................... 9

2.7 Background Concentrations .................................................................................................................... 9

2.8 Results of SO2 Characterization Analysis ............................................................................................. 12

Figures 2-1 – 2-5 .................................................................................................................. 13 
3 

1 Introduction 

1.1 Background 

The United States Environmental Protection Agency (EPA) promulgated a 1-hour National 

Ambient Air Quality Standard (NAAQS) for SO2 in 2010. The 1-hour SO2 NAAQS has a level 

set at 75 ppb and the form of the standard is the average of the 99th percentile of the daily 

maximum 1-hour average concentrations realized in each of three consecutive calendar years 

(the “design value,” or DV). 

The EPA is implementing the 2010 1-hour SO2 National Ambient Air Quality Standard 

(NAAQS) in an approach that involves either a dispersion modeling or monitoring approach to 

characterize local SO2 concentrations near isolated emission sources. On March 20, 2015, EPA 

informed affected states that certain emission sources within their states will be addressed in an 

expedited round of designations under the 1-hour SO2 NAAQS due to terms of the SO2 Consent 

Decree negotiated between the Sierra Club and EPA.1

 The EPA intends to designate the affected 

areas as either “attainment” (same as “unclassifiable/attainment”), “nonattainment,” or 

“unclassifiable” by July 2, 2016 after a review of available modeling or monitoring data to 

support the SO2 concentration characterizations. 

One of the affected sources evaluated in this Consent Decree analysis is the H. A. Wagner 

Generating Station (“Wagner”). Due to its proximity to Wagner, the Brandon Shores Generating 

Station is also part of the SO2 characterization process. 

The Maryland Department of the Environment (MDE or the Department) has been working with 

Raven Power, owner of Wagner and Brandon Shores, with Raven Power’s consultant AECOM, 

and with EPA Region 3 to ensure the area around Wagner is characterized appropriately. In 

addition, the Crane Generating Station (Crane) and another minor source in the vicinity of the 

Wagner area were included in the modeling analysis. 

This modeling analysis was completed in consultation with EPA Region 3, to demonstrate that 

the size of the 1-hour SO2 nonattainment area proposed by EPA in their March 1, 2016 Draft 

Technical Support Document entitled “Area Designations for the 2010 SO2 Primary Ambient Air 

Quality Standard”2 should be reduced in size to the immediate area surrounding Wagner. This 

modeling analysis will use updated modeling procedures and the dispersion modeling results that 

are summarized in this appendix, to characterize SO2 concentrations in the area surrounding 

Wagner. 

 

1

See Case No.: 3:13-cv-3953-SI, in the United States District Court for the Northern District of California, San Francisco Division, 

filed March 2, 2015, available at http://www.4cleanair.org/sites/default/files/resources/Litigation-SO2-

Designations_Deadline_Suit-Final_CD-030215.pdf. 

2

 https://www3.epa.gov/so2designations/round2/03_MD_tsd.pdf 
4 

2 Modeling Procedures and Results 

2.1 Dispersion Model Selection 

This modeling analysis utilized the most recent version of the AERMOD dispersion model3

(Version 15181) to evaluate air quality impacts from the emission sources of interest. The 

AERMOD modeling system consists of two preprocessors and the dispersion model. AERMET 

is the meteorological preprocessor component and AERMAP is the terrain pre-processor 

component that characterizes the terrain and generates receptor elevations along with critical hill 

heights for receptors. 

2.2 Emissions Data and Source Characterization 

The most recent three years (2013-2015) of actual emissions data for Crane, Brandon Shores, 

and Wagner, data that Raven Power’s consultant AECOM submitted to MDE, were used in the 

1-hour SO2 source characterization modeling analysis as per the guidance in EPA’s SO2 NAAQS 

Designations Modeling Technical Assistance Document (TAD)4. Also, one additional source, 

Wheelabrator, was included in the modeling analysis. Actual emissions for the Wheelabrator 

source were not available, so the allowable emissions rate was used. Figure 2-1 (see the figures at 

the end of this appendix) shows the sources located in the Baltimore area. Table 2-1, on the next 

page, lists the sources and parameters modeled. Brandon Shores Units 1 and 2 exhaust to a 

common stack with height and internal exit diameter as reported in Table 2-1. When both units 

were operating, the combined emission rate, average flow rate and weighted average temperature 

were used in AERMOD, consistent with EPA Model Clearinghouse Memo 91-II-01. When Unit 

1 or 2 operated alone, the single flue diameter was used. AECOM updated the flue gas 

temperature and exit velocity data in the hourly emissions file. These data were derived via 

examination of 2013-2015 data collected using the certified flue gas flow monitors (CEMs data) 

installed in the Brandon Shores, Wagner, and Crane stacks. 

The stack temperature data includes several periods of erroneous temperature data for Wagner 

Unit 3. Four hours erroneously reported a temperature of 0 degrees F (March 21, 2013 Hour 8, 

June 12, 2013 Hour 9, August 8, 2013 Hour 19, and September 3, 2013 Hour 13). These values 

were replaced with the temperatures in the Department’s emissions inventory files (289.99 

degrees F / 416.48 K). 

Intermittent sources and transient conditions such as emergency generators, auxiliary boilers, and 

startup/shutdown operations were not modeled as explained in the March 2011 EPA guidance 

document5

for modeling 1-hour NO2 and SO2. These emission sources are of insufficient 

duration and frequency to affect NAAQS compliance. 

 

3

Available at http://www.epa.gov/ttn/scram/11thmodconf/presentations/1-5_Proposed_Updates_AERMOD_System.pdf. 

4

http://www3.epa.gov/airquality/sulfurdioxide/pdfs/SO2ModelingTAD.pdf

5

http://www3.epa.gov/scram001/guidance/clarification/Additional_Clarifications_AppendixW_Hourly-NO2- 

NAAQS_FINAL_03-01-2011.pdf
5 

Table 2-1: Emissions and Stack Parameters for Input to AERMOD 

a Actual hourly monitor values were used in the modeling, as provided by Raven Power 

b Wagner Units 1 and 4 are not equipped with stack flow meters. 

c Wagner Unit 2 emission rate was capped at 1.0 lb/MMBTU to represent future operations. 

In April 2015, Raven Power reduced SO2 emissions at Wagner Unit 2 by changing to Colorado

coal, a lower chlorine and lower sulfur bituminous coal that will comply with the Mercury and 

Air Toxics Standards (MATS) Rule. Figure 2-2 shows the comparison of megawatt (MW) output 

to SO2 emissions for January 1 – September 30, 2015. Maximum SO2 emissions before the 

change were on the order of 2,500 lb/hr and after the maximum emission rate has been less than 

1,500 lb/hr or less than 1.0 lb/MMBTU (~40% reduction in SO2 emissions) at the same MW 

output. Raven Power plans to continue burning this or similar coal in Wagner Unit 2 in order to 

meet MATS. For this modeling analysis no changes were made to the actual emissions for the 

Wagner, Brandon Shores and Crane sources. 

2.3 Good Engineering Practice (GEP) Analysis 

Federal stack height regulations limit the stack height used in performing dispersion modeling 

to predict the air quality impact of a source. Sources must be modeled at the actual physical 

stack height unless that height exceeds the Good Engineering Practice (GEP) formula stack 

height. If the physical stack height is less than the formula GEP height, the potential for the 

source's plume to be affected by aerodynamic wakes created by the building(s) must be 

evaluated in the dispersion modeling analysis. 

A GEP formula stack height analysis has been performed for sources of interest located at 

Brandon Shores, Wagner, and Crane in accordance with the EPA's "Guideline for 

Determination of Good Engineering Practice Stack Height” (EPA, 1985)6

. A GEP stack 

 

6

 Available at http://www.epa.gov/scram001/guidance/guide/gep.pdf. 

Stack

SO2

Emissions 

(g/s)

Stack 

Height 

(m)

Exit 

Diameter 

(m)

Exit 

Temperature 

(K)

Exit 

Velocity 

(m/s)

Crane Unit 1 Variablea107.59 3.328 Variablea

Variablea

Crane Unit 2 Variablea107.59 3.330 Variablea

Variablea

Brandon Shores 

Unit 1 Variablea

121.92 9.50 VariableaVariablea

Brandon Shores 

Unit 2 Variablea

121.92 9.50 VariableaVariablea

Brandon Shores 

Merged Stack Variablea

121.92 13.435 VariableaVariablea

Wagner Unit 1 Variablea87.48 3.099 330.00 30.48 

Wagner Unit 2 Variablea,c 87.48 3.100 Variablea

Variablea

Wagner Unit 3 Variablea105.46 4.215 Variablea

Variablea

Wagner Unit 4 Variablea104.24 5.334 610.93 35.357 

Wheelabrator 12.6 96.01 2.130 485.93 22.55 
6 

height is defined as the greater of 65 meters (213 feet), measured from the ground elevation of 

the stack, or the formula height (Hg), as determined from the following equation: 

Hg = H + 1.5 L 

Where, 

H is the height of the nearby structure which maximizes Hg, and 

L is the lesser dimension (height or projected width) of the building. 

For a squat structure, i.e., height less than projected width, the formula reduces 

to: 

Hg = 2.5H 

In the absence of influencing structures, a “default” GEP stack height is credited up to 65 

meters (213 feet). Both the height and the width of the building are determined through a 

vertical cross-section perpendicular to the wind direction. In all instances, the GEP formula 

height is based upon the highest value of Hg as determined from H and L over all nearby 

buildings over the entire range of possible wind directions. For the purposes of determining 

the GEP formula height, only buildings within 5L of the source of interest are considered. 

The GEP analyses were conducted with the latest version of the US EPA’s Building Profile 

Input Program software (BPIP-PRIME version 04274). 

2.4 Meteorological Data Processing 

The meteorological data required for input to AERMOD were created with the latest version of 

AERMET (15181) using the adjusted u* option. This option is currently a beta non-guideline 

option; justification for its use is discussed below. Hourly surface observations from BaltimoreWashington International Thurgood Marshall Airport (BWI), MD along with concurrent upper 

air data from Sterling, VA were used as input to AERMET. The surface data (wind direction, 

wind speed, temperature, sky cover, and relative humidity) are measured 10 m above ground 

level. A wind rose for 2013-2015 is shown in Figure 2-3. 

AERMET requires specification of site characteristics including surface roughness (zo), 

albedo (r), and Bowen ratio (Bo). These parameters were developed according to the 

guidance provided by US EPA in the recently revised AERMOD Implementation Guide7

(AIG). 

The AIG provides the following recommendations for determining the site characteristics: 

1. The determination of the surface roughness length should be based on an inverse 

distance weighted geometric mean for a default upwind distance of 1 kilometer 

relative to the measurement site. Surface roughness length may be varied by sector 

 

7

 Available at http://www.epa.gov/ttn/scram/7thconf/aermod/aermod_implmtn_guide_19March2009.pdf. 
7 

to account for variations in land cover near the measurement site; however, the 

sector widths should be no smaller than 30 degrees.

2. The determination of the Bowen ratio should be based on a simple un-weighted 

geometric mean (i.e., no direction or distance dependency) for a representative 

domain, with a default domain defined by a 10-km by 10-km region centered on 

the measurement site. 

3. The determination of the albedo should be based on a simple un-weighted 

arithmetic mean (i.e., no direction or distance dependency) for the same 

representative domain as defined for Bowen ratio, with a default domain defined 

by a 10-km by 10-km region centered on the measurement site.

The AIG recommends that the surface characteristics be determined based on digitized land 

cover data. EPA has developed a tool called AERSURFACE that can be used to determine 

the site characteristics based on digitized land cover data in accordance with the 

recommendations from the AIG discussed above. Aersurface8

incorporates look-up tables of 

representative surface characteristic values by land cover category and seasonal category. 

AERSURFACE was applied with the instructions provided in the AERSURFACE User’s 

Guide. 

The current version of AERSURFACE (Version 13016) supports the use of land cover data 

from the USGS National Land Cover Data 1992 archives

9

 (NLCD92). The NLCD92 archive 

provides data at a spatial resolution of 30 meters based upon a 21-category classification 

scheme applied over the continental United States. The AIG recommends that the surface 

characteristics be determined based on the land use surrounding the site where the surface 

meteorological data were collected. 

As recommended in the AIG for surface roughness, the 1-km radius circular area centered at 

the meteorological station site can be divided into sectors for the analysis; the default 12 

sectors was used for this analysis. 

In AERSURFACE, the various land cover categories are linked to a set of seasonal surface 

characteristics. As such, AERSURFACE requires specification of the seasonal category for 

each month of the year. The following five seasonal categories are supported by 

AERSURFACE, with the applicable months of the year specified for this site. 

1. Midsummer with lush vegetation (June-August). 

2. Autumn with un-harvested cropland (September- November). 

3. Late autumn after frost and harvest, or winter with no snow (December - February) 

4. Winter with continuous snow on ground (none). 

5. Transitional spring with partial green coverage or short annuals (March - May). 

 

8

 Documentation available at http://www.epa.gov/ttn/scram/dispersion_related.htm#aersurface. 

9

See additional information at http://landcover.usgs.gov/natllandcover.php. 
8 

For Bowen ratio, the land use values are linked to three categories of surface moisture 

corresponding with average, wet, and dry conditions. The surface moisture condition for the 

site may vary depending on the meteorological data period for which the surface 

characteristics should be applied. AERSURFACE applies the surface moisture condition for 

the entire data period. Therefore, if the surface moisture condition varies significantly across 

the data period, then AERSURFACE can be applied multiple times to account for those 

variations. 

As such, the surface moisture condition for each season was determined by comparing 

precipitation for the period of data to be processed to the 30-year climatological record, 

selecting “wet” conditions if precipitation was in the upper 30th-percentile, “dry” conditions if 

precipitation was in the lower 30th - percentile, and “average” conditions if precipitation was 

in the middle 40th -percentile. The 30-year precipitation data set to be used in this modeling 

was taken from the National Climatic Data Center10. 

The monthly designations of surface moisture that were input to AERSURFACE are 

summarized in Table 2-2. 

Table 2-2: AERSURFACE Bowen Ratio Condition Designations

Month

Bowen Ratio Category

2013 2014 2015

January Wet Average Wet 

February Dry Wet Average

March Average Average Average

April Dry Wet Wet 

May Average Average Dry 

June Wet Wet Wet 

July Average Average Average

August Dry Wet Wet 

September Dry Average Average

October Wet Average Average

November Average Average Average

December Wet Average Wet 

 

10 http://www.ncdc.noaa.gov/cdo-web/
9 

2.5 Receptors to be Modeled 

Receptors were placed in nested Cartesian grids centered on the Fort Smallwood Complex and 

Crane with the following spacing: 

• Every 25 meters along the property boundary 

• Every 100 meters out to a distance of 2 km 

• Every 250 meters between 2 and 5 km, and 

• Every 500 meters between 5 and 10 km. 

Additional receptors were placed at the outer edges to the northwest of Wagner in order to make 

sure that the maximum 1-hour SO2 concentrations were accurately modeled. 

The original 10,600 receptors were included in the modeling grid. After the initial modeling 

showed high 1-hour SO2 concentrations to the northwest close to the modeling domain boundary, 

an additional 6,600 receptors were located there to assure the maximum 1-hour SO2

concentrations were modeled. This brought the total number of receptors used in this analysis to 

17,000. 

The current version of AERMAP has the ability to process USGS National Elevation Dataset 

(NED) data in place of Digital Elevation Model files. The appropriate file for 1-arc-second, or 

30-m, NED data were obtained from the Multi-Resolution Land Characteristics Consortium 

(MRLC) link at http://www.mrlc.gov/viewerjs/. 

Per EPA’s SO2 Technical Assistance Document for modeling11, receptors in inaccessible 

areas such as over water and on Aberdeen Proving Ground were removed for this modeling 

analysis as shown in Figure 2-4. 

2.6 Model Configurations and Options 

AERMET and AERMOD (Versions 15181) were run with the default options and the Adjust U* 

(ADJ_U*) option in AERMET. In accordance with Appendix W, Section 3.2.2, the Department 

has submitted a request to the EPA Region 3 Regional Administrator to be given approval to use 

the non-regulatory default ADJ_U* option in this modeling analysis.12

2.7 Background Concentrations 

The Beltsville, MD monitor (Site #24-033-0030), which is located about 33 km to the southwest 

of the Fort Smallwood Complex, was used to determine the uniform regional background 

 

11 https://www3.epa.gov/airquality/sulfurdioxide/pdfs/SO2ModelingTAD.pdf

12 Letter from Mr. Ben Grumbles (MDE Secretary) to Regional Administrator Mr. Shawn Garvin, April 14, 2016. See 

Appendix C of the document, “MDE Technical Support Document Regarding the Designation of the Area of the 

Herbert A. Wagner Generating Plant for 1-Hour Sulfur Dioxide.” 
10 

component for the NAAQS SO2 modeling. EPA’s March 2011 clarification memo13 regarding 1-

hour SO2 NAAQS modeling allows for an approach using the 99th percentile monitored values 

whereby the background values vary by season and by hour of the day. MDE used the AECOM 

approach and applied it to the modeling, using data from the 3-year period of 2013 – 2015. The 

SO2 concentrations that were used are listed in Table 2-3. According to the EPA’s “Table 5c. 

Monitoring Site Listing for Sulfur Dioxide 1-Hour NAAQS”,14 the completeness criteria for 

2013 and 2014 (Column W) are satisfied, therefore, the Beltsville 1-hour SO2 monitoring data is 

complete and is acceptable to use in the modeling. For 2015, the Beltsville monitor recorded 

data for 8,334 hours (95% complete). 

 

 

13 Available at http://www.epa.gov/ttn/scram/guidance/clarification/Additional_Clarifications_AppendixW_HourlyNO2-NAAQS_FINAL_03-01-2011.pdf.

14 See http://www3.epa.gov/airtrends/pdfs/SO2_DesignValues_20122014_FINAL_8_3_15.xlsx. 
11 

Table 2-3: 1-hr SO2 Ambient Background Concentrations for Beltsville Monitor (2013-2015) 

Hour 

3-Year Averaged 

Hourly Values for 

Winter (μg/m3) 

3-Year Averaged 

Hourly Values for 

Spring (μg/m3) 

3-Year Averaged 

Hourly Values for 

Summer (μg/m3) 

3-Year Averaged 

Hourly Values for 

Fall (μg/m3) 

1 10.31 6.81 3.14 6.38 

2 6.46 8.21 2.27 4.93 

3 11.79 8.30 2.88 3.49 

4 11.09 7.07 3.23 3.58 

5 10.74 6.81 2.79 3.76 

6 12.58 7.07 2.79 3.93 

7 11.62 8.47 4.10 3.49 

8 10.92 7.07 7.16 4.37 

9 10.57 12.31 7.51 6.72 

10 13.54 11.79 8.82 10.13 

11 17.64 11.27 9.26 13.27 

12 14.50 10.65 6.55 14.76 

13 15.55 13.10 6.38 11.96 

14 13.45 12.14 7.77 10.65 

15 12.93 10.39 5.24 9.34 

16 13.54 9.08 5.76 10.65 

17 13.45 11.35 5.76 8.56 

18 11.53 14.24 4.10 7.16 

19 14.58 11.70 3.58 5.94 

20 14.50 9.34 3.23 4.54 

21 12.75 8.12 3.41 4.80 

22 11.79 8.03 3.14 5.33 

23 15.72 8.21 2.97 4.45 

24 11.53 6.55 3.06 4.28 

 
12 

2.8 Results of SO2 Characterization Analysis 

The results of this SO2 characterization analysis using modeling can inform the decision as to 

proper designation of the Wagner area for the 1-hour SO2 NAAQS based on three years (2013-

2015) of actual emissions for Wagner, Brandon Shores and Crane. This modeling process has 

some conservative features included, such as: 

• Use of allowable emission rates for background sources (Wheelabrator). 

• Use of actual emissions for Wagner Unit #2, 1-hour SO2 emissions have been 

dramatically reduced by the use of low chlorine coal, with low sulfur content, for 

compliance with MATS. 

Therefore, with these conservative assumptions, the modeling results show that the 99th

percentile peak daily 1-hour maximum concentration around Wagner modeled to be 255.58 

μg/m3 (including background) which exceeds the 1-hour SO2 NAAQS of 196.2 μg/m3. 

However, also based on modeling, the 1-hour SO2 nonattainment area should be limited to only 

the area immediately surrounding Wagner. Provided in Figure 2-5 is the area not 

demonstrating compliance with the 1-hour SO2 NAAQS. 

 
13 

Figures 2-1 – 2-5

 

Wagner 

Brandon Shores 

Crane 

Wheelabrator 

Figure 2-1. Locations of SO2 Sources Used in the Modeling Analysis
Figure 2-2: Wagner Unit 2 Emission Reductions in 2015

14 
15 

Figure 2-3. BWI Airport Wind Rose
16 

Figure 2-4. Receptor Locations
17 

Figure 2-5. 99th Percentile SO2 Modeling Results Using Adjust U*