2-18

Figure 2-11. Plot of the 728 precipitation stations for the CALMET subregional domains. 

200 400 600 800 1000 1200 1400 1600 1800 2000

LCC East (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

200

400

LCC North (km)

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

Elevation

(meters)

Domain 1

Domain 2

Domain 3

Domain 4

Domain 5

AL GA

TN

SC

NC

VA

FL

KY

MS

WV

-25

0.1

50

100

150

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

Appendix L2 

Regional Haze SIP for Florida

Page 101 of 266
2-19

Figure 2-12. Plot of 23 upper air stations for the CALMET subregional domains. 

200 400 600 800 1000 1200 1400 1600 1800 2000

LCC East (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

200

400

LCC North (km)

72201

72202

72206

72208

72210

72214

72215

72230

72233

72235

72240

72305

72317

72318

72327

72340

72402

72403

72426

74455 72520

74560

74794

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

Elevation

(meters)

Domain 1

Domain 2

Domain 3

Domain 4

Domain 5

AL GA

TN

SC

NC

VA

FL

KY

MS

WV

-25

0.1

50

100

150

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

Appendix L2 

Regional Haze SIP for Florida

Page 102 of 266
2-20

Figure 2-13. Plot of 12 buoy stations for the CALMET subregional domains. 

200 400 600 800 1000 1200 1400 1600 1800 2000

LCC East (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

200

400

LCC North (km)

41004

41008

42003

42007

42036 42039 42040

41008

44009

44014

41009

41012

42001

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

Elevation

(meters)

Domain 1

Domain 2

Domain 3

Domain 4

Domain 5

AL GA

TN

SC

NC

VA

FL

KY

MS

WV

-25

0.1

50

100

150

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

Appendix L2 

Regional Haze SIP for Florida

Page 103 of 266
2-21

Figure 2-14. Plot of MM5 12-km grid used in CALMET simulations for 2001 and 2002. 

200 400 600 800 1000 1200 1400 1600 1800 2000

LCC East (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

200

400

LCC North (km)

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

Elevation

(meters)

Domain 1

Domain 2

Domain 3

Domain 4

Domain 5

AL GA

TN

SC

NC

VA

FL

KY

MS

WV

-25

0.1

50

100

150

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

Appendix L2 

Regional Haze SIP for Florida

Page 104 of 266
2-22

Figure 2-15. Plot of MM5 36 km grid used in CALMET simulations for 2003. 

200 400 600 800 1000 1200 1400 1600 1800 2000

LCC East (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

200

400

LCC North (km)

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

Elevation

(meters)

Domain 1

Domain 2

Domain 3

Domain 4

Domain 5

AL GA

TN

SC

NC

VA

FL

KY

MS

WV

-25

0.1

50

100

150

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

Appendix L2 

Regional Haze SIP for Florida

Page 105 of 266
2-23

2.4 Air Quality Monitoring Data 

CALPUFF uses hourly ozone concentration measurements in the chemical transformation rates 

(SO2 to SO4, NOx to HNO3/NO3). The ambient ozone measurements are used in determining SO2

loss rates due to chemical transformation to sulfate and in determining NOx loss rates to nitrate. 

Ambient ozone monitoring data from the U.S. EPA AIRS and CASTNet networks were used to 

develop the hourly ozone monitoring data file (OZONE.DAT). 

All available ozone data within the VISTAS regional domain were assembled and processed. All 

ozone data were combined into OZONE.DAT files for each of the modeled years. These ozone 

data files were also part of the standard VISTAS data set available at http://www.src.com web 

page. Two types of runs were made for the purposes of the BART analysis. For the screening 

runs, 12-km CALMET regional domain was used and CALPUFF computational subdomains 

were created on the 12-km grid. For most of the sources, these CALPUFF computational 

subdomains corresponded to the sizes and location of the five 4-km subregional domains. In the 

refined runs, 4-km CALMET/CALPUFF subregional domains were used. For each of the five 

CALPUFF subregional modeling domains, as well as for the CALPUFF computational 

subdomains within the VISTAS regional domain, smaller OZONE.DAT files were extracted to 

include only those ozone monitoring stations that are located within the particular domain or 

subdomain and its vicinity. The extraction was performed using the program SUBDOMN, a 

utility program run through the CALPUFF GUI. Figure 2-16 shows locations of all ozone stations 

used in the CALPUFF modeling on the five subregional 4-km domains and computational 

subdomains on the 12-km grid. Total of 497 ozone stations are shown on this plot. The number of 

ozone stations (AIRS and CASTNet) used in each of the subregional domains are listed in Table 

A-2. 

For the base case simulations, a constant ammonia concentration of 0.5 parts per billion (ppb) 

was assumed as recommended by the Interagency Workgroup on Air Quality Modeling 

(IWAQM, 1998) for forested Class I areas. In this application of the model, the Ammonia 

Limiting Method (ALM) was not used. 

2.5 Class I Areas 

The Class I Areas within the VISTAS Region are: Breton Island, Brigantine, Cape Romain, 

Chassahowitzka, Cohutta, Dolly Sods, Everglades, Great Smoky Mountains, James River Face, 

Joyce Kilmer-Slickrock, Linville Gorge, Mammoth Cave, Mingo, Okefenokee, Otter Creek, 

Shenandoah, Shining Rock, Sipsey, St Marks, Swanquarter, Wolf Island. The receptor locations 

along with receptor elevations were available from the National Park Service (NPS). 

Appendix L2 

Regional Haze SIP for Florida

Page 106 of 266
2-24

Figure 2-16. Plot of the 497 ozone stations used for the CALPUFF simulations. 

200 400 600 800 1000 1200 1400 1600 1800 2000

LCC East (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

200

400

LCC North (km)

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

Elevation

(meters)

Domain 1

Domain 2

Domain 3

Domain 4

Domain 5

AL GA

TN

SC

NC

VA

FL

KY

MS

WV

-25

0.1

50

100

150

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

Appendix L2 

Regional Haze SIP for Florida

Page 107 of 266
2-25

Table 2-4. Number of Ozone Stations used in the Modeling. 

2001 2002 2003 

 Total AIRS CASTNet Total AIRS CASTNet Total AIRS CASTNet

Domain 1 63 62 1 65 64 1 63 62 1 

Domain 2 79 76 3 79 76 3 81 78 3 

Domain 3 276 250 26 273 246 27 271 244 27 

Domain 4 234 218 16 233 216 17 231 214 17 

Domain 5 299 271 28 297 269 28 297 269 28 

Appendix L2 

Regional Haze SIP for Florida

Page 108 of 266
2-26

2.6 Model Configuration and Settings for Initial Analysis 

VISTAS used CALMET Version 5.723 for the regional domain and CALMET Version 5.720 for 

the subregional domains. For CALPUFF runs, VISTAS used CALPUFF Version 5.754. These 

versions contain enhancements funded by the Minerals Management Service (MMS) and 

VISTAS. They were developed by TRC and they are maintained on the CALPUFF website 

(http://www.src.com) for public access. This version includes CALMET, CALPUFF, CALPOST, 

CALSUM, and POSTUTIL as well as the CALVIEW graphical user interface. 

The initial analysis for a specific source used a CALPUFF computational domain that included all 

Class I areas within 300 km of the source. These Class I areas are specified in the CALPUFF 

control file for analysis. This initial approach was designed to significantly reduce the CALPUFF 

simulation time by restricting the CALPUFF computational domain size to include only areas 

where significant impacts are feasible rather than the entire regional domain. CALPUFF allows 

its computational domain to be specified as a subset of the CALMET meteorological domain by 

settings within the CALPUFF input file. The advantage of selecting a smaller CALPUFF 

computational domain in the regional CALPUFF simulations is that CALPUFF run time is 

proportional to the number and residence time of the puffs on the domain (and other factors such 

as the number of receptors and the internal time step computed by the model). A CALPUFF 

domain covering an area 300 km from a source in all directions would involve only 50 x 50 

12-km grid cells, which would require modest computational resources. 

CALMET output files for the VISTAS regional domain shown in Figure 2-2 were provided to 

VISTAS by TRC. These files are in CALPUFF-ready format, and as such, no CALMET user 

inputs are required. An option in CALMET allows finer grid CALMET input files to be 

calculated from the 12-km CALMET files. 

The basic characteristics of the CALMET, CALPUFF and CALPOST configurations for the 

initial analyses are listed below. 

2.7 CALMET Modeling Configuration (12-km Initial Exemption Modeling) 

The CALMET model configuration for the regional CALMET simulations has been defined by 

TRC in collaboration with the VISTAS States. The basic model configuration followed the 

recommended IWAQM guidance (EPA, 1998; Pages A-1 through A-6), except as noted below. 

The basic features of the modeling simulation are the following: 

- Modeling period: 3 years (2001-2003) 

- Meteorological inputs: MM5 data provide initial guess fields in CALMET 

- CALMET grid resolution: 12-km (same Lambert Conformal coordinate system and grid cells 

as the 12-km 2001/2002 MM5 simulations) 

- CALMET vertical layers: 10 layers. Cell face heights (meters): 0, 20, 40, 80, 160, 320, 640, 

1200, 2000, 3000, 4000. 

Appendix L2 

Regional Haze SIP for Florida

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2-27

- CALMET mode: No-Observations mode including option to read overwater data directly 

from MM5. 

- Diagnostic options: IWAQM default values, except as follows: diagnostic terrain blocking 

and slope flow algorithms used for 2003 simulations (using 36-km MM5 data), but no 

diagnostic terrain adjustments in 2001 and 2002 simulation (using 12-km MM5 data) 

- CALMET options dealing with radius of influence parameters (R1, R2, RMAX1, RMAX2, 

RMAX3), BIAS, ICALM parameters are not used in No-Observations mode. 

- TERRAD (terrain scale) is required for runs with diagnostic terrain adjustments (i.e., the 

2003 simulations). Value of 15 km was determined from testing and used in modeling. 

- Land use defining water: JWAT1 = 55, JWAT2 = 55 (large bodies of water). This feature 

allows the temperature field over large bodies of water such as the Atlantic Ocean and the 

Great lakes to be properly characterized by buoy observations. 

- Mixing height averaging parameter for the regional simulations determined by TRC based on 

sensitivity tests was MNMDAV=1. The purpose of the testing was to optimize the variable to 

allow spatial variability in the mixing height field, but without excessive noise. 

- Geophysical data for regional runs: SRTM30 30 arc-seconds terrain data, Composite Theme 

Grid (CTG) USGS 200m land use dataset. References for these and other CALMET datasets 

can be found on the CALPUFF data page of the official CALPUFF site 

(http://www.src.com). 

The CALMET input files with the complete set of model switch settings used for the regional 

simulations are provided on the VISTAS page of the CALPUFF web site. 

2.8 CALMET Modeling Configuration (4-km Refined Exemption Modeling) 

For the subregional CALMET simulations, the model configuration has also been defined by 

TRC in collaboration with the VISTAS States following the recommended IWAQM guidance 

(EPA, 1998; Pages A-1 through A-6), except as noted below. 

The basic features of the modeling simulation are the following: 

- Modeling period: 3 years (2001-2003) 

- Meteorological inputs: MM5 data provide initial guess fields in CALMET. Meteorological 

observational data are used in the Step 2 calculations. Overwater (buoy) data were used in 

addition to the hourly surface meteorological observations, precipitation observations and 

twice-daily upper air sounding data. 

- CALMET grid resolution: 4-km (same Lambert Conformal coordinate system as the 12-km 

2001/2002 MM5 simulations) 

Appendix L2 

Regional Haze SIP for Florida

Page 110 of 266
2-28

- CALMET vertical layers: 10 layers. Cell face heights (meters): 0, 20, 40, 80, 160, 320, 640, 

1200, 2000, 3000, 4000. 

- CALMET mode: Refined mode with all available observational data included in the Step 2. 

- Diagnostic options: IWAQM default values. 

- CALMET options dealing with radius of influence parameters: R1 = 5 km, R2 = 5 km, 

RMAX1 = 40 km, RMAX2 = 40 km, RMAX3 = 100 km, BIAS(NZ) = 10*0, ICALM = 0. 

- TERRAD (terrain scale) is required for runs with diagnostic terrain adjustments which was 

used for all years for the subregional domains. Value of 15 km was determined from testing 

and used in modeling. 

- Land use defining water: JWAT1 = 55, JWAT2 = 55 (large bodies of water). This feature 

allows the temperature field over large bodies of water such as the Atlantic Ocean and the 

Great lakes to be properly characterized by buoy observations. 

- Mixing height averaging parameter for the subregional simulations determined by TRC based 

on sensitivity tests was MNMDAV=1. The purpose of the testing was to optimize the 

variable to allow spatial variability in the mixing height field, but without excessive noise. 

- Geophysical data for regional runs: 3 arc-second USGS DEM terrain data set (SRTM30 data 

also used as a backup in case when 3 arc-second data are missing), CTG USGS 200m land 

use dataset. References for these and other CALMET datasets can be found on the CALPUFF 

data page of the official CALPUFF site (http://www.src.com). 

The CALMET input files with the complete set of model switch settings used for the 

subregional simulations are provided on the VISTAS page of the CALPUFF web site. 

2.9 CALPUFF Modeling Configuration (Initial Exemption Modeling) 

The CALPUFF model configuration for the regional CALPUFF initial simulations followed the 

recommended IWAQM guidance (EPA, 1998; Pages B-1 through B-8), except as noted below: 

- CALPUFF domain configured to include the source and all Class I areas within 300 km of 

the source plus 50 km buffer zone in each direction. CALPUFF is recommended for all 

source-receptor distances to be considered in the BART analyses. 

- Chemical mechanism: MESOPUFF II module 

- Species modeled: SO2, SO4, NOx, HNO3, NO3 and particulate matter in size categories of 

<0.625 μm, 0.625-1.0 μm, 1.0-1.25 μm, 1.25-2.5 μm, 2.5-6.0 μm and 6-10 μm aerodynamic 

diameters. As noted below, the particulate matter emissions by size category have been 

combined into the appropriate species for the visibility analysis (i.e., elemental carbon (EC), 

fine PM or “soil” (< 2.5 μm in diameter), coarse PM (between 2.5-10 μm in diameter) and 

organics (called secondary organic aerosols (SOA) in the CALPOST postprocessor). 

Appendix L2 

Regional Haze SIP for Florida

Page 111 of 266
2-29

- Emission rates for modeling based on EPA BART guidance, i.e., maximum 24-hour actual 

emission rate with normal operations from the highest emitting day of the meteorological 

period modeled (excluding days where start-up, shutdown or malfunctions occurred 

sometime during the day.) Note that potential emissions were used to determine if a source is 

BART-eligible, but 24-hour average maximum emissions were used for modeling purposes 

(70 FR 39162). Pollutants considered include SO2, H2SO4, NOx and PM10. 

Condensable emissions were considered as primary fine particulate matter and allocated 

equally to the two submicrometer-particle size classes. If actual source emissions data were 

not available, the modeling was based on permit limits. If source-specific size categories were 

not available, then AP-42 factors have been used for sources where AP-42 factors are 

available. For sources where AP-42 factors are not available, alternative approaches to 

speciation are given below. 

Excluded from the modeling were pollutants with plant-wide emissions less than de minimis 

levels (40 tons per year for SO2 and NOx and 15 tons per year for PM10). De minimis levels 

are plant wide for each visibility-impairing pollutant, so individual units have been modeled 

even if they have emissions below de minimis if the plant total is greater than de minimis. 

- Particulate emissions speciation: Break down, as appropriate, filterable and condensable 

particulate matter into the following species categories: elemental carbon (soot), “soil” (fine 

PM < 2.5 μm diameter), coarse particulate matter (2.5-10 μm diameter) and organics. The 

process is sketched in Figure 2-17 and illustrated in more detail in Table 2-5. Table 2-5 is an 

image of an interactive spreadsheet where cells shown in blue are inputs that user can make 

depending on the level of information available. If source-specific speciated emissions factors 

were not available, AP-42 factors or speciation information developed by the National Park 

Service (http://www2.nature.nps.gov/air/permits/ect/index.cfm) was used to estimate the PM 

speciation for many source sectors. 

Otherwise, assumptions were proposed by the source, and reviewed and approved by the 

State. Possible acceptable alternative approaches to estimating speciation include the 

following: 

- Speciation profiles developed by the SMOKE emissions model for use in VISTAS’ 

CMAQ regional air quality modeling (available at http://www.vistassesarm.org/BART/calpuff.asp). 

- The approach described in a memo available at http://www.vistassesarm.org/BART/calpuff.asp, which provides reasonably conservative estimates in 

situations where data are incomplete. 

- Class I receptors: used FLM Class I receptor list with receptor elevations provided (available 

from the NPS). 

- CALPUFF model options: used IWAQM (EPA, 1998) default guidance, including PasquillGifford dispersion coefficients. 

Appendix L2 

Regional Haze SIP for Florida

Page 112 of 266
2-30

- Ozone dataset – used observed ozone data for 2001-2003 from CASTNet and AIRS stations. 

Only non-urban ozone stations were used in the OZONE.DAT file. Monthly average ozone 

(backup) background values were computed based on daytime average ozone concentrations 

from the OZONE.DAT file (6am-6pm average ozone concentrations computed by month). 

- Background ammonia concentration: In CALPUFF, used constant (0.5 ppb) value for 

ammonia. 

- Puff representation: integrated puff sampling methodology. 

- Building downwash: Ignored building downwash unless source is within 50-km of a Class I 

area and the relevant state agency instructed the source to specifically consider building 

downwash. 

A sample CALPUFF input file with the complete set of recommended switch settings as used 

in the VISTAS BART modeling is provided on the VISTAS page of the CALPUFF web site 

(http://www.src.com). 

2.10 CALPOST and POSTUTIL Configuration (Initial Exemption Modeling) 

- Used Visibility Method 6 in CALPOST 

- Species considered in visibility analysis: SO4, NO3, EC, SOA (i.e., condensable organic 

emissions), soil, coarse PM 

- Natural background light extinction: A monthly average natural background as calculated by 

CALPOST under Method 6, based on annual average default natural conditions component 

concentrations and monthly average f(RH) values for the centroid of the Class I area, from 

Table A-3 in the natural conditions guidance document,. 

- Light extinction efficiencies: IMPROVE Methodology defined in FLAG (2000). 

- Nitrate repartitioning in POSTUTIL: Not used for the initial modeling. 

The initial run results were based on the highest change in light extinction (deciviews) from 

natural conditions over the three-year modeling period for each Class I area considered. Predicted 

changes exceeding the “contribution” threshold (0.5 deciviews) triggered a finer grid CALPUFF 

modeling analysis. 

Appendix L2 

Regional Haze SIP for Florida

Page 113 of 266
2-31

Figure 2-17. Speciation of PM10 emissions. The numbers in the bottom row are the extinction 

efficiencies applied in the standard IMPROVE extinction equations. 

PM10

(including H2SO4) 

Filterable Condensable 

EC PM2.5 PMC Inorganic PM

(including H2SO4) 

Organic PM 

SOIL 

1 

COARSE 

0.6 

EC 

10 

SO4

3 x f(RH)

SOIL 

(non-SO4 inorganic)

1 

OC 

4 

Appendix L2 

Regional Haze SIP for Florida

Page 114 of 266
2-32

Table 2-5. Example of Speciation of PM10 emissions. 

inputs in units 

of (g/s) H2SO4 PM10 PM2

PM10 and 

H2SO4 1.630 22.031 16.52

filterable 

condensable % 59% 

 12.998 

AP-42 

 coarse coarse soil soil soil soil EC EC EC EC H2SO4 OC  PM800 PM425 PM187 PM112 PM081 PM056 PM187 PM112 PM081 PM056 PM08

6.00 - 

10.00 

2.50-

6.00 

1.25-

2.50 

1.00-

1.25 

0.625-

1.00 

0.50-

0.625 

1.25-

2.50 

1.00-

1.25 

0.625-

1.00 

0.50-

0.625 

0.625

1.00 

16.3% 26.1% 23.9% 6.5% 12.0% 15.2% 23.9% 6.5% 12.0% 15.2% 50.0% 

96.3% 3.7% 

2.119 3.393 2.992 0.814 1.502 1.903 0.115 0.031 0.058 0.073 1.630 2.96

EC % of 

filterable and 

inorganic % of 

condensable 

 Inputs to POSTUTIL:  0.6 0.6 1 1 1 1 10 10 10 10 4 

coarse coarse soil soil soil soil EC EC EC EC OC 

PM800 PM425 PM187 PM112 PM081 PM056 PM187 PM112 PM081 PM056 PM0

2.119 3.393 2.992 0.814 2.242 2.643 0.115 0.031 0.058 0.073 2.96

Note: This table is an image of an interactive spreadsheet where values shown in blue are inputs that user can make depending on the level of information 

black are computed in the spreadsheet. 

Appendix L2 Regional Haze SIP for Florida
3-1

3.0 MODELED FACILITIES FOR BART 

3.1 Visibility Results 

VISTAS provided a list of BART-eligible sources to TRC for the BART exemption modeling. Table 

3-1 lists the VISTAS states and number of sources modeled in each of the states. In this table, the 

number of sources that can be exempt from BART controls is also provided. Figure 3-1 shows location 

of the modeled BART sources. 

According to the VISTAS protocol, screening simulation results below 0.5 dv for all three years indicate 

that facility is not subject to BART controls. For facilities failing the screen, or those located relatively 

close to one or more Class I areas (usually within 50 km) the state has recommended immediately using 

the more refined 4-km CALMET meteorological grid. In the refined simulations, the 98th percentile 

value of prediction change in extinction (i.e., the 8th highest day) is compared to the 0.5 dv threshold. If 

the highest 98th percentile value during the three year simulation period is below the 0.5 dv threshold, 

the source is considered not subject to BART controls. 

In Alabama, 24 facilities were modeled with the total of 169 point sources. All Alabama facilities were 

modeled using the 12-km Regional CALMET domain and CALPUFF computational subdomain. 

Maximum predicted extinction change for 16 of these sources at each of the Class I areas were all below 

the 0.5 dv threshold value. For the remaining 8 sources the threshold value was exceeded for some or all 

of the Class I areas within 300 km from the source. For these 8 sources, refined modeling could be 

performed for further analysis, although due to the magnitude of the impacts, this was not done under 

VISTAS funding. 

In Florida, three facilities were modeled. One of them was modeled on the VISTAS CALMET 12-km 

regional domain and for that facility, maximum predicted extinction change was below the threshold 

value of 0.5 dv. The other two facilities were modeled on the subregional VISTAS 4-km Domain 2. The 

results of the modeling for these two facilities show that maximum predicted extinction change was 

below the threshold value of 0.5 dv for Class I areas that are not very close to these facilities. However, 

for each of these two facilities, for the Class I area that are within 50 km from the facilities the 8th 

highest day exceeds the 0.5 dv threshold value. 

In Georgia, seven facilities were modeled. One of the facilities was first modeled on the 12-km regional 

domain. Since the maximum predicted visibility impact was above the threshold in one of the Class I 

areas, modeling was redone on the 4-km subregional Domain 4. The 98th percentile in that run was well 

below the 0.5 dv threshold value. Two more facilities were modeled on the 4-km subregional Domain 4. 

For both of these facilities, the 98th percentile values were below the 0.5 dv threshold. Remaining four 

facilities were modeled on the 12-km regional domain only. Three of these passed the screening with 

maximum predicted visibility impacts below the threshold value. Predicted visibility impacts from one 

of those facilities were in exceedances of the threshold value of the 0.5 dv. For this facility, refined 

modeling could be performed for further analysis, but due to the magnitude of the impacts, this was not 

done under VISTAS funding. 

Appendix L2 

Regional Haze SIP for Florida

Page 116 of 266
3-2

Table 3-1 List of BART Eligible Facilities (Sources) Modeled. 

Number of sources 

modeled on a 12-km 

VISTAS Regional 

CALMET domain1

Number of sources with 

maximum change in 

deciviews < 0.5 dv 

(can be exempt from 

BART controls) 

Number of sources 

modeled on a 4-km 

VISTAS CALMET 

domains1

Number of sources with 

8th highest change in 

deciviews < 0.5 dv 

(can be exempt from 

BART controls) 

Alabama 24 (169) 16 (102) - - 

Florida 1 (4) 1 (4) 2 (12) 0 (0) 

Georgia 5 (19) 3 (9) 3 (10) 3 (10) 

Kentucky 9 (119) 7 (91) 2 (28) 2 (28) 

Mississippi 2 (6) 2 (6) - - 

North Carolina - - 1 (38) 1 (38) 

South Carolina 9 (43) 5 (16) 1 (5) 1 (5) 

Tennessee 6 (39) 6 (39) - - 

Virginia 3 (11) 1 (1) 1 (8) 1 (8) 

West Virginia 12 (120) 11 (83) - - 

 

Total 71 (530) 51 (351) 10 (101) 8 (89) 

1

 Values in brackets represent the number of individual point and line sources modeled.

Appendix L2 

Regional Haze SIP for Florida

Page 117 of 266
3-3

Figure 3-1. Locations of the modeled facilities in the VISTAS region. 

200 400 600 800 1000 1200 1400 1600 1800 2000

LCC East (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

200

400

LCC North (km)

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

Elevation

(meters)

AL GA

TN

SC

NC

VA

FL

KY

MS

WV

Everglades

Breton

Sipsey

Cohutta

Mammoth Cave

Mingo

Cape Romain

Chassahowitzka

Great Smoky Mountains

Joyce Kilmer-Slickrock

Linville Gorge

Okefenokee

Shining Rock

St Marks

Wolf Island

James River Face

Swanquarter

Shenandoah

Dolly Sods

Otter Creek

Brigantine

-25

0.1

50

100

150

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

Modeled BART Facility

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In Kentucky, nine facilities were modeled. As a screening run, all 9 facilities were modeled on the 

VISTAS CALMET 12-km regional domain. Maximum predicted extinction changes in each of the 

Class I areas for seven of these facilities were below the threshold value of 0.5 dv. For the remaining 

two facilities the threshold value was exceeded in some of the Class I areas. For these two facilities, 

refined modeling was performed on the 4-km subregional Domain 3 and Domain 5. The 98th percentile 

values in those runs were below the 0.5 dv threshold value. 

In Mississippi, two facilities were modeled, both using the 12-km regional domain. Maximum predicted 

extinction changes in each of the Class I areas for both of these facilities were below the threshold value 

of 0.5 dv. 

In North Carolina, one facility was modeled, using the 4-km Domain 5. The 8th highest values (98th

percentile) of the extinction change predictions were below the 0.5 dv threshold for all years and for 

each of the Class I areas. 

In South Carolina, 10 facilities were modeled. Nine of the facilities were modeled on the 12-km regional 

domain only. Five of these passed the screening with maximum predicted visibility impacts below the 

threshold value. Predicted visibility impacts from four of those facilities were in exceedances of the 

threshold value of the 0.5 dv. For these facilities, refined modeling could be performed for further 

analysis, but due to the magnitude of the impacts, this was not done under VISTAS funding. One of the 

facilities was modeled on the 4-km Domain 4. The 98th percentile in that run was well below the 0.5 dv 

threshold value. 

In Tennessee, six facilities were modeled with the total of 39 point sources. All Tennessee facilities 

were modeled using the 12-km Regional CALMET domain and CALPUFF computational subdomain. 

Maximum predicted extinction change for all of the Tennessee sources at each of the Class I areas were 

below the 0.5 dv threshold value. Ammonia emissions were modeled in one of Tennessee sources. 

In Virginia, three facilities were modeled. Initially, all three facilities were modeled on the VISTAS 

CALMET 12-km regional domain. For one of the facilities, maximum predicted extinction changes in 

each of the Class I areas were below the threshold value of 0.5 dv. For the remaining two facilities the 

threshold value was exceeded in one of the Class I areas for each facility. For one of these two facilities, 

modeling was redone on the 4-km Domain 5. The 98th percentile values in those runs were below the 

0.5 dv threshold value. 

In West Virginia, 12 facilities were modeled with the total of 120 point sources. All West Virginia 

facilities were modeled using the 12-km regional CALMET domain and CALPUFF computational 

subdomain. Maximum predicted extinction change for eleven of the Tennessee sources at each of the 

Class I areas were below the 0.5 dv threshold value. For one of the sources, the threshold value of 0.5 dv 

for extinction change was exceeded. For this facility, refined modeling could be performed for further 

analysis, although due to the magnitude of the impacts, this was not done under VISTAS funding. 

Overall, in all of the 10 VISTAS states 71 facilities were modeled on a 12 km VISTAS Regional 

CALMET domain (as shown in the last row of Table 3-1). The results of those CALPUFF runs show 

that 51 facility or 72% of the total number of modeled facilities passed the screening, while 20 facilities 

did not pass the screening. For four of those 20 facilities, refined modeling was performed. The 98th

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percentile values in those runs were all below the 0.5 dv threshold value. In addition, refined modeling 

was performed for six more facilities (screening runs were not performed for these sources). Only two 

of these six sources did not pass. In total out of 10 facilities for which refined modeling was performed, 

eight facilities or 80% of the total number of modeled facilities passed. 

It should be noted that in the screening approach, maximum visibility change is considered and 

compared against the 0.5 dv threshold value, not the 98th percentile. This is a conservative approach. If 

maximum value is above the threshold, refined modeling is performed to show compliance with BART. 

From the number of sources modeled in this study, it can be noted that screening approach provides 

very good estimate of the sources that could be screened out. Values with screening runs are not lower 

than with the refined runs. 

3.2 NOx Considerations in Respect to Visibility 

The contribution of absorption by gases (bag) has been examined for two hypothetical facilities with 

NOx-dominated emission profiles placed in Florida and Georgia (see Figure 3-2). In the FLAG (2000) 

report, it is suggested that bag is dominated by nitrogen dioxide and is considered negligible at large 

source-receptor distances. This assumption is tested at three Class I areas for Source #1 and five Class I 

areas for Source #2. The absorption term was computed using the maximum predicted 24-hour NOx

concentration at each Class I area multiplied by extinction efficiency of 0.17, as recommended in FLAG 

(2002). It was conservatively assumed that all NOx was in the form of NO2. Using a typical emissions 

profile it was found that in the near-field the contribution from NOx is significant for the hypothetical 

sources examined, being 10-14% for the sources less than 25 km away from the Class I area (Table 3-2 

and Table 3-3). For the Class I areas that are further away (200-290 km away), it was found that 

contribution was 2-5% which although small is still not negligible (Table 3-2 and Table 3-3). For a 

reference, emissions assumed for Sources 1 and 2 are given in Table 3-4 and Table 3-5. Source 1 was 

modeled on VISTAS subregional Domain 2, while Source 2 was modeled on Domain 4. 

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Figure 3-2. Locations of the two hypothetical NOx-dominated facilities and Class I areas in the NO2

absorption sensitivity tests. 

1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000

LCC East (km)

-1500

-1400

-1300

-1200

-1100

-1000

-900

-800

-700

-600

-500

-400

LCC North (km)

S1

S2

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

Elevation

(meters)

AL GA

SC

NC

FL

Cape Romain

Chassahowitzka

Okefenokee

St Marks

Wolf Island

-25

0.1

50

100

150

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

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Table 3-2. Hypothetical Source 1 – Visibility Results, Maximum 24-hr Contribution. 

Class I 

Area 

Julian 

Day 

Dist. 

(km) 

Bext 

(Model) 

(Mm-1) 

Bext 

(BKG) 

(Mm-1) 

Bext 

(Total) 

(Mm-1) 

% 

Change

of Bext

F(RH)

Bext 

SO4 

(Mm-1) 

Bext 

NO3 

(Mm-1) 

Bext 

OC 

(Mm-1)

Bext 

EC 

(Mm-1)

Bext 

PMC 

(Mm-1)

Bext 

PMF 

(Mm-1)

Bext 

NOx 

(Mm-1)

% 

Contribution 

of NO2

CHAS 250 15 2.457 21.46 23.917 11.45 4.1 0.138 0.206 1.113 0.077 0.042 0.882 0.333 13.6% 

OKEF 71 217 0.084 21.41 21.494 0.39 3.1 0.004 0.059 0.01 0.001 0.000 0.010 0.005 5.6% 

STMA 29 219 0.282 21.54 21.822 1.31 3.7 0.008 0.239 0.017 0.001 0.001 0.016 0.007 2.5% 

Table 3-3. Hypothetical Source 2 – Visibility Results, Maximum 24-hr Contribution. 

Class I 

Area 

Julian 

Day 

Dist. 

(km) 

Bext 

(Model) 

(Mm-1) 

Bext 

(BKG) 

(Mm-1) 

Bext 

(Total) 

(Mm-1) 

% 

Change

of Bext

F(RH)

Bext 

SO4 

(Mm-1) 

Bext 

NO3 

(Mm-1) 

Bext 

OC 

(Mm-1)

Bext 

EC 

(Mm-1)

Bext 

PMC 

(Mm-1)

Bext 

PMF 

(Mm-1)

Bext 

NOx 

(Mm-1)

% 

Contribution 

of NO2

CARO 240 260 0.098 21.22 21.318 0.46 4.1 0.070 0.004 0.007 0.004 0.002 0.011 0.004 3.6% 

CHAS 271 290 0.086 21.46 21.546 0.40 4.1 0.049 0.028 0.002 0.001 0.001 0.004 0.002 2.3% 

OKEF 345 63 0.846 21.41 22.256 3.95 3.6 0.355 0.339 0.044 0.025 0.018 0.065 0.063 7.4% 

STMA 322 263 0.132 21.54 21.672 0.61 3.7 0.044 0.066 0.006 0.004 0.002 0.011 0.003 2.6% 

WOLF 241 26 1.419 21.33 22.749 6.65 4.1 0.649 0.201 0.170 0.092 0.067 0.240 0.145 10.2% 

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Table 3-4. Hypothetical Source 1 – Stack Parameters and Emissions. 

Stack 

ID # 

Stack 

Height 

Base 

Elevation Diam. 

Gas Exit 

Velocity 

Stack 

Gas Exit 

Temp. 

SO2

Emis. 

SO4

Emis. 

NOx

Emis. 

PM10

Emis. 

PM2.5

Emis. 

 m m m m/s K g/s g/s g/s g/s g/s 

1 22.86 45.72 0.91 7.19 302.59 0 0 0 0.108 0.0578 

2 45.72 45.72 3.96 10.52 374.82 0.2604 0.1249 22.2138 0.9153 0.8624 

3 15.24 45.72 3.05 9.06 444.26 0 0 0 0.6694 0.6246 

4 21.34 45.72 0.79 14.35 366.48 0 0 0 3.8632 3.6051 

5 45.72 45.72 0.61 24.26 302.59 0 0 0 0.0392 0.0365 

6 65.84 45.72 0.61 24.26 302.59 0 0 0 0.2614 0.244 

7 42.67 45.72 0.67 26.73 338.71 0 0 0 0.0074 0.0069 

8 24.38 45.72 0.76 15.52 298.15 0 0 0 0.2276 0.1219 

9 24.69 45.72 0.52 12.04 314.82 0 0 0 0.0635 0.034 

10 9.75 45.72 0.61 24.26 294.26 0 0 0 0.272 0.1457 

Table 3-5. Hypothetical Source 2 – Stack Parameters and Emissions. 

Stack 

ID # 

Stack 

Height 

Base 

Elevation Diam. 

Gas Exit 

Velocity 

Stack 

Gas Exit 

Temp. 

SO2

Emis. 

SO4

Emis. 

NOx

Emis. 

PM10

Emis. 

PM2.5

Emis. 

 m m m m/s K g/s g/s g/s g/s g/s 

1 82.9 1.5 3.95 8.2 474 3.88 0.2204 10.4 2.61 1.6 

2 82.9 1.5 3.95 8.2 474 3.88 0.2204 10.4 2.61 1.6 

3 19.8 1.5 3.66 14.33 339 0 0 0 0.111 0.111 

4 80.5 1.5 1.04 18.6 350 0.16 0 0.35 2.1 1.9 

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3.3 “Q over D” analysis 

VISTAS States are using emissions (Q), expressed in units of tons per year, divided by distance from a 

Class I area boundary (D), expressed in units of kilometers, as a presumptive indicator that a BARTeligible source is subject to BART. If Q/D for SO2 is greater than 10 for 2002 actual annual emissions, 

then the State presumes that the source is subject to BART and no exemption modeling is performed 

using VISTAS funds. If the company agrees with this presumption, then the source can proceed to the 

BART determination using CALPUFF to evaluate impacts of control options and perform the 

engineering analyses. If the company disagrees, they may perform fine grid modeling to determine if its 

impact is <0.5 dv. 

For sources with Q/D less than or equal to 10, TRC was requested by VISTAS to assist States with the 

initial CALPUFF exemption modeling. Each State prioritized which sources were offered modeling by 

VISTAS. Note that VISTAS did not propose to use Q/D to exempt BART-eligible sources, but only to 

prioritize sources for modeling purposes. Thus this application is consistent with EPA guidance not to 

use Q/D for exemption purposes. 

Figure 3-3 and Figure 3-4 show “Q/D” plots. These plots were composed using the results for all 

modeled sources described in Section 3.1. In Figure 3-3, emissions comprise of SO2 and NOx, while in 

Figure 3-4 in addition to SO2 and NOx, PM10 is also included. In analyzing the Q over D plots, the sum 

of SO2+NOx emissions appears to be the overall best predictor of the total extinction. 

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Figure 3-3. Q/D plot where Q comprises of SO2 and NOx emissions. 

Figure 3-4. Q/D plot where Q comprises of SO2, NOx and PM10 emissions. 

Q = SO2 + NOx

0.000

0.125

0.250

0.375

0.500

0.625

0.750

0.875

1.000

1.125

1.250

1.375

1.500

1.625

0.0 10.0 20.0 30.0 40.0 50.0 60.0

Q/D

delta dv

2001

2002

2003

Q = SO2 + NOx + PM10

0.000

0.125

0.250

0.375

0.500

0.625

0.750

0.875

1.000

1.125

1.250

1.375

1.500

1.625

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0

Q/D

delta dv

2001

2002

2003

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3.4 Use of CMAQ for ALM analysis 

The use CMAQ output as background for nitrate particulates prediction in CALPUFF using the 

Ammonia Limiting Method (ALM) was evaluated using a 2002 CMAQ output run. A summary of this 

study is attached in Appendix C. 

First, CMAQ ammonia gas (NH3(g)) was compared to several sets of observations but the results show 

a significant CMAQ underprediction for NH3(g) at the sites evaluated. The first conclusion is that a 

direct use in CALPUFF of NH3(g) as predicted by CMAQ is not recommended because of this 

underprediction. 

In a second part of the analysis, sulfate (SO4), nitrate (NO3), nitric acid (HNO3) and total nitrate (HNO3

+ NO3) from the CMAQ model were compared against the IMPROVE and CASTNet measurements of 

these same pollutants over the Southeastern part of the United States. Good agreements between CMAQ 

and observations for sulfate and total nitrate and a somewhat overprediction of nitrate were encouraging 

results for the use of the CMAQ data to provide background pollutant concentrations. The NO3/HNO3

equilibrium parameterization in CALPUFF chemistry was also tested against the equivalent CMAQ 

parameterization and very good agreement was found between the two as it is shown in Figure 3-5. The 

background NO3 concentrations output of CALPUFF chemistry track very closely when compared to 

observations as do the CMAQ NO3 concentration predictions. This suggests that a repartitioning of 

HNO3 and NO3 within CALPUFF using the CMAQ data as background is feasible and consistent with 

the CMAQ chemistry. Therefore, the use of hourly CMAQ output to determine background 

concentrations in the CALPUFF system was recommended for ALM applications. The combination of 

CMAQ outputs concentrations of sulfate (SO4), total nitrate (NO3 +HNO3) and total ammonia (NH3(g) + 

NO3 +2SO4) represents a reliable estimate of background concentrations which will likely improve the 

quality of nitrate predictions in CALPUFF. 

As an alternative to hourly background data for ALM application, 2002 CMAQ monthly average 

background was also tested and can be viewed as a compromise solution to the issue of background if 

an hourly CMAQ dataset is not available. 

In addition, the substantial spatial and temporal variability found in CMAQ ammonia predictions (see 

Appendix C) implies that varying ammonia better reflects background ammonia than the constant value 

throughout the year and for the whole domain as recommended by the Federal Land Manager guidance. 

Further information on the use of CMAQ data and ALM with CALPUFF can also be found in EscoffierCzaja and Scire (2007). 

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Figure 3-5. Quantile-quantile plots of NO3 predictions (CMAQ in pink and from CALPUFF chemistry 

in blue) as a function of NO3 observations (CASTNet dataset at the top, weekly averages and 

IMPROVE dataset at the bottom, daily averages).

NO3 weekly average - Q-Q plot - year 2002

0

2

4

6

8

10

12

0 2 4 6 810 12

NO3 CASTNET observations (ug/m3)

NO3 MODEL simulations (ug/m3)

CALPUFF Chemistry

'CMAQ'

NO3 daily averaged - Q-Q plots - year 2002

0

2

4

6

8

10

12

14

16

0 2 4 6 8 10 12 14 16

NO3 IMPROVE observations (ug/m3)

NO3 MODEL simulations (ug/m3)

CALPUFF Chemistry

CMAQ

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4.0 UPDATE OF CALPUFF MODEL CODES 

4.1 Introduction 

Prior to June 2007, the EPA-approved version of CALPUFF was based on model codes dated July 2004. 

Over the period from July 2004 through August 2006, a number of enhancements and bug-fixes were 

made to the CALMET and CALPUFF models, culminating in the versions used by VISTAS for BART 

analyses: CALMET (v5.726) and CALPUFF (v5.756). The latest reviewed and approved update of the 

CALPUFF model codes by EPA was dated June 15, 2006, when they approved the changes documented 

in Model Change Bulletin (MCB) A (released on July 16, 2004). However, because these codes did not 

include MCB-B (released on December 16, 2005) or later MCBs, the EPA-approved codes contained 

known bugs for which the code fixes were also known. As a result, it was proposed in BART modeling 

protocols, including the VISTAS protocol, that the later model codes referred to as the VISTAS codes 

would be used for BART analyses. 

During the period from March through June 2007, working with EPA, TRC constructed a special 

version of the CALPUFF model, known as the “C” code (because it contained all bug fixes through 

MCB-C) starting with the July 2004 EPA-approved codes. The EPA-approved versions of CALMET 

(v5.53a) and CALPUFF (v5.711a) were updated by applying both MCB-B and MCB-C changes to 

create CALMET (v5.53c) and CALPUFF (v5.711c), which were called the C versions. This allowed a 

separation of any changes due to model enhancements from bug fixes to be identified and quantified. 

The result of this analysis was that all changes in the CALPUFF model from v5.711a to v5.756 were 

due to bug fixes, i.e., when the VISTAS version of CALPUFF was run with the same switch settings, 

input data and model options as the EPA-approved v5.711a code, the predicted concentrations with the 

VISTAS v5.756 code were the same. There were some changes in model results due to CALMET 

enhancements, and the C version of CALMET allowed for tests of these effects separate from the bug 

fixes. During the testing period of March-June 2007, EPA reviewed and approved the C code changes. 

Application of the EPA CALPUFF Evaluation Tool to compare results from CALPUFF (v5.711c) / 

CALMET (v5.53c) and CALPUFF (v5.756) / CALMET (v5.726) shows that the two versions of 

CALPUFF produce no difference in concentrations when the latter is run with options compatible with 

the C version. Differences are found between CALMET (v5.53c) and CALMET (v5.726) for the wind 

fields. The code associated with these differences has been isolated and applied to the CALMET 

(v5.726) code to create the C-equivalent version of CALMET referred to as EPA_CEQ. When run with 

options compatible with CALMET (v5.53c), EPA_CEQ CALMET produces results that are the same as 

those from CALMET (v5.53c). Otherwise, the output is consistent with CALPUFF (v5.756) / CALMET 

(v5.726). 

Since August 2006, additional bug-fixes have been made to both CALMET (v5.726) and CALPUFF 

(v5.756), and those that apply to the EPA C-versions are documented in Model Change Bulletin D 

(MCB-D). 

In collaboration with EPA, it was decided that the VISTAS codes served as the most appropriate 

starting point for the next version of the EPA-approved model codes (called v5.8). The v5.8 codes 

contain all known bug fixes and include many enhancements in terms of data formats, convenience 

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4-2

features (e.g., allowing multiple 3D.DAT files in a single run of CALMET) and additional quality 

assurance checks, as well as providing a framework for the evaluation of the new technical 

enhancements in the VISTAS code. EPA requested the introduction of a “regulatory option” in 

CALMET which checks for several switch settings: 

- Mixing height method (IMIXH=-1) to use the Maul-Carson method over land and the OCD method 

over water; 

- Overwater turbulence and flux calculations (ICOARE=0) to use the OCD method for turbulence and 

fluxes over water; 

- Sensible heat threshold variable (THRESHL=0.0) using a value of zero for the threshold sensible 

heat flux over land. 

In addition, two other relevant changes were made at EPA’s request to the VISTAS CALMET code in 

developing the v5.8 code: 

- The VISTAS CALMET code adopted a consistent set of similarity relations throughout the code. 

This affected some of the original model algorithms and was designed to make them consistent with 

the new COARE algorithms for the boundary layer added as an option enhancement. The VISTAS 

code was modified in v5.8 to use the original similarity relations when the COARE algorithm is not 

used. Although this introduces inconsistencies in the way calculations are performed, it maintains 

the prior calculation methods associated with earlier versions of the model. 

- Surface temperatures in the VISTAS code were computed based on a spatial interpolation of the 

surface station measurements. In the v5.8 code, the previous “nearest-station” technique was 

reintroduced in order to be consistent with the prior regulatory-approved versions of the code. This 

results in the temperature from the nearest surface station being assigned to a grid point rather than a 

spatial interpolation being done. 

In creating v5.8 of CALPUFF from the VISTAS code, a change was made at EPA’s request to make the 

default minimum σv values over water and land 0.5 m/s for all stabilities rather than 0.37 m/s over water 

and 0.5 m/s over land. Recent evaluation work with overwater and coastal tracer datasets (Scire et al., 

2005) suggested better model performance with the 0.37 m/s values, but in order to maintain 

consistence with prior versions of CALPUFF, the defaults were changed to their original values of 

0.5 m/s for both land and water. This is likely to result in greater dispersion over water than in the 

VISTAS code. 

These versions, CALMET (v5.8) and CALPUFF (v5.8) also include updates that check control file 

inputs for consistency with the EPA-approved configuration required to obtain the C-equivalent results 

and MCB-D changes. The v5.8 codes were officially approved by the EPA as the regulatory version of 

the models on June 29, 2007. 

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The next section summarizes the results of the application of the EPA Evaluation tool on two different 

versions of the model. The two versions of CALMET and CALPUFF used in the demonstration are 

referred to in the following way: 

CALMET v5.53c EPA CALMET with MCB-B and MCB-C Updates 

CALPUFF v5.711c EPA CALPUFF with MCB-B and MCB-C Updates 

CALMET v5.8 CALMET with v5.53c-Equivalent modifications and MCB-D Updates 

CALPUFF v5.8 CALPUFF with v5.711c-Equivalent modifications and MCB-D Updates 

The results of these demonstrations show that the CALPUFF changes result in concentration changes 

for certain source configurations and model options, while no change in concentrations are found for 

other configurations. These results are expected due to the nature of the bugs that have been addressed. 

Similarly, CALPUFF concentrations also change as a result of changes in CALMET, and these too are 

expected from the nature of the bugs that have been identified and addressed. 

4.2 Results using the EPA Evaluation Tool 

All 11 scenarios in the Evaluation Tool were processed to compare CALMET (v5.53c) / CALPUFF 

(v5.711c) to CALMET (v5.8) / CALPUFF (v5.8), and the results are presented in Table 4-1. No 

difference in concentrations was reported in Scenarios 03, 06, 07, 08, 09, 10, and 11. The secondary 

analysis feature of the Evaluation Tool was applied to Scenarios 01, 02, 04, and 05 to determine if 

concentration differences arise from just CALMET, just CALPUFF, or both CALMET and CALPUFF. 

Differences in Scenarios 04 and 05 arise from the CALPUFF MCB-D changes, not from the CALMET 

MCB-D changes. Differences in Scenarios 01 and 02 arise from both the CALPUFF MCB-D changes 

and the CALMET MCB-D changes. 

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Table 4-1 

EPA CALPUFF Evaluation Tool Results for 

CALPUFF (v5.711c) with CALMET (v5.53c) 

compared to 

CALPUFF (v5.8) with CALMET (v5.8)

Scenario Result 

01 Difference due to CALMET and CALPUFF (point source only) 

02 Difference due to CALMET and CALPUFF (point source only) 

03 No Differences 

04 Difference due to CALPUFF (point source only) 

05 Difference due to CALPUFF (point source only) 

06 No Differences 

07 No Differences 

08 No Differences 

09 No Differences 

10 No Differences 

11 No Differences 

Scenarios 01, 02, 04, and 05 include volume, point, and area sources. No chemical transformations and 

no removal mechanisms are simulated. Concentrations are extracted for averaging times of 1-hr, 3-hr, 

24-hr, and run-length (673-hr for Scenario 02, 720-hr for the others) and the peak values are reported by 

rank, using ranks 1, 2, 4, and 8. Note that the run-length can only provide the largest concentration 

(rank 1), and in these tests the run length is far shorter than that used in regulatory applications. 

Scenarios 01 and 02 use a large domain that is 960km on each side with an 80x80 grid of 12km cells. 

Sampling is done at the center of each grid cell excluding the outermost 2 rows and columns, resulting 

in a sparse receptor grid with 12km spacing. Scenarios 04 and 05 use much smaller domains with finer 

grid resolutions of 2km and 0.25km, respectively. Receptor spacing used in Scenarios 04 and 05 are also 

2km and 0.25km, respectively. 

Changes in concentration due to CALPUFF MCB-D updates (available from http://www.src.com) are 

found for one or more of the point sources in these scenarios, and none of the other sources. None of 

these point sources is modeled with downwash, so the only MCB-D change that would lead to a 

difference should be the change associated with resetting plume rise to final rise as soon as a puff enters 

a calm region. For confirmation, this one MCB-D change was removed in a test version of CALPUFF 

(v5.8), and Scenarios 01, 02, 04, and 05 were rerun using CALMET (v5.53c) files to remove CALMET 

changes from this test. The result showed no differences compared to CALPUFF (v5.711c), thereby 

confirming the source of the differences found. 

Changes in concentration due to CALMET MCB-D updates are found in two scenarios. Scenario 01 

uses no prognostic data and so it is expected to be influenced by few MCB-D changes. Given that it 

includes overwater cells, two model changes related to the overwater boundary layer apply. Both of 

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4-5

these changes were removed in a test version of CALMET (v5.8), which was then applied to 

Scenario 01. The results confirmed that these (one or both) lead to the differences noted. Scenario 02 is 

the only one that uses the no-observations mode (NOOBS=2), so it relies on the use of prognostic data 

as input and is therefore subject to several of the MCB-D changes. Because MM5 land use is not read, 

no cells are treated as water when computing MM5 profiles near the surface. This scenario also uses 

ITPROG=2, which affects the temperature profile assigned to CALMET layers within the mixed layer. 

The magnitude of the "High Values by Rank" concentration changes, expressed as the percent change 

from the base system CALMET (v5.53c) / CALPUFF (v5.711c) to the beta system CALMET (v5.8) / 

CALPUFF (v5.8), for the MCB-D changes in Scenarios 01, 02, 04, and 05 range between: 

 Scenario 01 -0.077% to 0.34% 

 Scenario 02 -10.4% to 1.56% 

 Scenario 04 -0.00% to 0.53% 

 Scenario 05 -0.003% to 0.004% 

The range listed is obtained from the extreme values over all averaging times and ranks. These are all 

very small with the exception of Scenario 02. Because of the sparse 12km sampling grid used in this 

scenario, it is not surprising that changes in the CALMET boundary layer and meteorological profiles 

can shift CALPUFF impact areas resolved by the sampling grid. 

The results of these demonstrations show that the CALMET and CALPUFF changes result in 

concentration changes for certain source configurations and model options, while no change in 

concentrations are found for other configurations. These results are expected due to the nature of the 

bugs that have been addressed and the configuration of the test scenarios. 

4.3 Analysis of Typical Class I Impacts 

The EPA Evaluation Tool is useful for diagnostic tests of model differences. However, it does not 

measure the likely consequences in terms of regulatory compliance decisions because many of the tests 

involve non-regulatory model switches and the run lengths are short, varying from just 48 hours to one 

month. In addition, the standard EPA runs do not involve chemical conversion or the calculation of 

visibility or deposition. (Scenario 11 of the EPA set was added to include chemistry, but it does not 

include the calculation of deposition fluxes or visibility.) 

An example of a more typical Class I impact analysis has been applied with a major source of SO2, NOx

and PM10, with a comparison of the effects on SO2,NOx and PM10 concentrations, sulfur and nitrogen 

deposition fluxes and visibility using Method 6 as recommended for BART analyses. In these tests, full 

year simulations were conducted to allow a more accurate determination of the regulatory consequences 

of model changes. 

In these tests, a realistic typical power plant source was placed in Virginia and the impacts at six Class I 

areas evaluated. The year 2001 was modeled for a source with emissions of 95 g/s (SO2), 79 g/s (NOx), 

4 g/s (H2SO4) and 39 g/s (PM10) emitted from a tall stack (152m). The results of a comparison of 

predicted concentrations for the year 2001 for SO2, NOx and PM10 concentrations is shown in Table 4-2. 

Appendix L2 

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4-6

For the short-term concentrations (i.e., 3-hour and 24-hour averaging times), the concentrations are the 

highest second-high values predicted at each Class I area. The highest value for each version is 

highlighted in bold. 

In general, the predicted impacts with the new EPA-approved v5.8 model codes are lower than those 

obtained with the VISTAS codes. The primary reason for this is not a code change, but a change in the 

preferred model setting requested by EPA to use an overland mixing height threshold of 0.0 rather than 

the 0.05 W/m3

 over land. This results in generally higher mixing heights with the v5.8 version of 

CALMET, which tends to produce more dilution over long range transport distances and therefore 

lower predicted impacts. Other factors can also play a role, so the impact vary, but with other things 

being equal, the tendency is for higher mixing heights to produce lower impacts. 

As shown in Tables 4-2 to 4-4, the changes in predicted SO2, PM10 and NOx concentrations are 

generally small, especially when comparing the overall highest predicted values over all Class I areas. 

For example, the highest predicted 3-hour average SO2 impacts vary from 1.014 ug/m3

 (VISTAS) to 

0.98 ug/m3

 (EPA). For 24-hour average SO2 concentrations, the highest value are 0.252 ug/m3

(VISTAS) vs. 0.249 ug/m3

 (EPA) and for annual averages the highest SO2 concentrations are 0.016 

ug/m3

 (VISTAS) and 0.015 ug/m3 (EPA). Similar results are presented for PM10 and NOx in the tables. 

For the annual sulfur and nitrogen deposition fluxes (Table 4-5 and Table 4-6), the highest values are 

unchanged in going from the VISTAS model codes to the v5.8 EPA-approved codes, although some of 

the lower deposition values change slightly at some Class I areas. Again the trend is that the VISTAS 

codes produce higher impacts than those predicted by the new EPA-approved codes. 

The predicted visibility impacts (percent change in extinction) using Method 6 is presented in Table 4-7. 

The values listed are the highest predicted change in Bext at each Class I area. The results from show 

lower impacts with the new EPA-approved v5.8 codes. 

Although it is difficult to generalize, the results of this full-year analysis of concentration, deposition 

flux and visibility impacts at six Class I areas shows a tendency for the VISTAS code to be conservative 

relative to the v5.8 EPA-approved codes. In addition, in most cases, the differences between model 

versions are relatively small. 

Appendix L2 

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4-7

Table 4-2. Comparison of Predicted SO2 Concentrations (μg/m3) at Six Class I Areas for Different Model Versions. 

H2H 3-hour SO2 H2H 24-hour SO2 H1H Annu

Class I Area VISTAS 

MET/PUFF 

Ver. C 

MET/PUFF 

Ver. 5.8 

MET/PUFF 

VISTAS 

MET/PUFF 

Ver. C 

MET/PUFF 

Ver. 5.8 

MET/PUFF 

Vistas 

MET/PUFF 

Ver. 

MET/PU

James River 0.390 0.385 0.387 0.138 0.130 0.130 0.009 0Shining Rock 0.445 0.453 0.453 0.103 0.086 0.086 0.007 0Cohutta 0.293 0.282 0.281 0.074 0.066 0.066 0.003 0Linville Gorge 1.014 0.972 0.972 0.252 0.249 0.249 0.016 0Joyce Kilmer 0.539 0.528 0.527 0.140 0.131 0.132 0.005 0Great Smoky 0.979 0.980 0.980 0.226 0.220 0.220 0.013 0

Table 4-3. Comparison of Predicted PM10 Concentrations (μg/m3) at Six Class I Areas for Different Model Versions. 

H2H 24-hour PM10 H1H Annual PM10

Class I Area VISTAS 

MET/PUFF 

Ver. C 

MET/PUFF 

Ver. 5.8 

MET/PUFF 

VISTAS 

MET/PUFF 

Ver. C 

MET/PUFF 

Ver. 5.8 

MET/PUFF 

James River 0.072 0.066 0.066 0.005 0.005 0.005 Shining Rock 0.056 0.043 0.043 0.004 0.004 0.004 Cohutta 0.046 0.038 0.038 0.002 0.002 0.002 Linville Gorge 0.110 0.110 0.110 0.008 0.007 0.007 Joyce Kilmer 0.071 0.064 0.064 0.003 0.003 0.003 Great Smoky 0.105 0.100 0.100 0.007 0.006 0.006 

Appendix L2 Regional Haze SIP for Florida
4-1

Table 4-4. Comparison of Predicted NOx Concentrations (μg/m3) for Different Model Versions. 

H1H Annual NOx - 2001 

Class I Area VISTAS 

MET/PUFF 

Ver. C 

MET/PUFF 

Ver. 5.8 

MET/PUFF 

James River 0.0021 0.0020 0.0020 

Shining Rock 0.0013 0.0012 0.0012 

Cohutta 0.0003 0.0003 0.0003 

Linville 

Gorge 0.0046 0.0044 0.0044 

Joyce Kilmer 0.0011 0.0011 0.0011 

Great Smoky 0.0038 0.0037 0.0037 

Table 4-5. Comparison of Predicted Sulfur Deposition Fluxes (kg/ha/yr) at Six Class I Areas for Different 

Model Versions. 

Table 4-6. Comparison of Predicted Nitrogen Deposition Fluxes (kg/ha/yr) at Six Class I Areas for 

Different Model Versions. 

2001 

Sulfur VISTAS 

MET/PUFF 

Version C 

MET/PUFF 

Version 5.8 

MET/PUFF 

James River 0.013 0.012 0.012 

Shining Rock 0.008 0.007 0.007 

Cohutta 0.003 0.003 0.003 

Linville Gorge 0.020 0.020 0.020 

Joyce Kilmer 0.005 0.005 0.005 

Great Smoky 0.011 0.010 0.010 

2001 

Nitrogen VISTAS 

MET/PUFF 

Version C 

MET/PUFF 

Version 5.8 

MET/PUFF 

James River 0.005 0.004 0.004 

Shining Rock 0.002 0.002 0.002 

Cohutta 0.001 0.001 0.001 

Linville Gorge 0.007 0.007 0.007 

Joyce Kilmer 0.001 0.001 0.001 

Great Smoky 0.003 0.003 0.003 

Appendix L2 

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4-2

Table 4-7. Comparison of Predicted Visibility Impacts at Six Class I Areas for Different Model Versions. 

(Version C results are not available). The values shown are the highest percent change in 

extinction (Bext). 

2001 

Method 6 VISTAS 

MET/PUFF 

Version C 

MET/PUFF 

Version 5.8 

MET/PUFF 

James River 7.4 NA 6.8 

Shining Rock 4.9 NA 4.0 

Cohutta 4.7 NA 3.8 

Linville Gorge 8.3 NA 7.9 

Joyce Kilmer 7.1 NA 6.8 

Great Smoky 8.8 NA 8.1 

Appendix L2 

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5-1

5.0 REFERENCES 

Escoffier-Czaja C. and J.S. Scire, 2007: Use of Eulerian Model Outputs as Background Concentrations for 

Nitrate Predictions in CALPUFF System, 11th International Conference on Harmonisation within 

Atmospheric Dispersion Modelling for Regulatory Purposes, Cambridge, England, 2-5 July, 2007 

(http://www.harmo.org/Conferences/Proceedings/_Cambridge/publishedSections/Op058-062.pdf) 

FLAG, 2000. Federal Land Manager' Air Quality Related Values Workgroup (FLAG). Phase I Report. U.S. 

Forest Service, National Park Service, U.S. Fish and Wildlife Service. 

Scire, J.S., D.G. Strimaitis, and R.J. Yamartino, 2000a: A User’s Guide for the CALPUFF Dispersion Model 

(Version 5). Earth Tech, Inc., Concord, MA 

Scire, J.S., F.R. Robe, M.E. Fernau, and R.J. Yamartino, 2000b: A User’s Guide for the CALMET 

Meteorological Model (Version 5). Earth Tech, Inc., Concord, MA. 

Scire, J.S., D.G. Strimaitis and F. R. Robe, 2005: Evaluation of Enhancements to the CALPUFF Model for 

Offshore and Coastal Applications. Proceedings of the 10th International Conference on 

Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes. Sissi (Malia), 

Crete, Greece. 17-20 October 2005. 

VISTAS, 2005: Protocol for the Application of the CALPUFF Model for Analysis of Best Available Retrofit 

Technology (BART). Visibility Improvement State and Tribal Association of the Southeast 

(VISTAS). Revision 3.2, August 31, 2006. Available from: http://www.vistassesarm.org/documents. 

U.S. Environmental Protection Agency (EPA), 1998: Interagency Workgroup on Air Quality Modeling 

(IWAQM), Phase 2 Report: Summary Report and Recommendation for Modeling Long Range 

Transport and Impacts on Regional Visibility. EPA-454/R-98-019. 

U.S. Environmental Protection Agency (EPA), 2003a: Revision to the Guideline on Air Quality Models: 

Adoption of a Preferred Long Range Transport Model and Other Revisions; Final Rule. 40 CRF 51. 

Federal Register, April 15, 2003, 68, 72, pp 18440-18482. 

U.S. Environmental Protection Agency (EPA), 2003b: Guidance for Estimating Natural Visibility 

Conditions Under the Regional Haze Program. EPA-454/B-03-005, September 2003. 

U.S. Environmental Protection Agency (EPA), 2005: Regional Haze Regulations and Guidelines for Best 

Available Retrofit Technology (BART) Determinations; Final Rule, 40 CFR 41. Federal Register, 

July 6, 2006, 70, 128, pp 39104-39172. 

Appendix L2 

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A-1

APPENDIX A – LAND USE AND STATION DATA FOR REGIONAL 

SUBDOMAINS 

• Plots of Land Use Subregional Domains. 

• Tables of Upper Air Stations and Buoys. 

Appendix L2 

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A-2

Figure A-1. Land Use for the CALMET/ CALPUFF Domain 1. The Class I areas are also shown. 

500 600 700 800 900

LCC East (km)

-1100

-1000

-900

-800

-700

-600

-500

LCC North (

km)

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

LA

AL

TN

MS

Breton

Sipsey

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

Urban/

built-up land

Agricultural

land

Rangeland

Forest land

Water

Wetland

Barren land

Tundra

Snow / Ice

Appendix L2 

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A-3

800 900 1000 1100 1200 1300 1400 1500 1600 1700

LCC East (km)

-1500

-1400

-1300

-1200

-1100

-1000

-900

-800

LCC North (km)

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

FL

MS AL GA

Everglades

Chassahowitzka

St Marks

Okefenokee

Wolf Island

Breton

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

Urban/

built-up land

Agricultural

land

Rangeland

Forest land

Water

Wetland

Barren land

Tundra

Snow / Ice

Figure A-2. Land Use for the CALMET/ CALPUFF Domain 2. The Class I areas are also shown. 

Appendix L2 

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A-4

Figure A-3. Land Use for the CALMET/ CALPUFF Domain 3. The Class I areas are also shown. 

600 700 800 900 1000 1100 1200 1300 1400 1500

LCC East (km)

-600

-500

-400

-300

-200

-100

0

100

LCC North (km)

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

TN

KY

WV

VA

NC

MS AL GA SC

Mammoth Cave

Mingo

Great Smoky Mountains

Joyce Kilmer-Slickrock

Linville Gorge

Shining Rock

James River Face

Dolly Sods

Otter Creek

Cohutta

Sipsey

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

Urban/

built-up land

Agricultural

land

Rangeland

Forest land

Water

Wetland

Barren land

Tundra

Snow / Ice

Appendix L2 

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A-5

Figure A-4. Land Use for the CALMET/ CALPUFF Domain 4. The Class I areas are also shown. 

700 800 900 1000 1100 1200 1300 1400 1500 1600 1700

LCC East (km)

-1200

-1100

-1000

-900

-800

-700

-600

-500

-400

-300

-200

LCC North (km)

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

FL

GA

TN

SC

NC

VA

KY

MS AL

Chassahowitzka

St Marks

Okefenokee

Wolf Island

Cape Romain

Sipsey

Cohutta

Joyce Kilmer-Slickrok

Great Smoky Mountains

Shining Rock

Linville Gorge

Breton

Mammoth Cave

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

Urban/

built-up land

Agricultural

land

Rangeland

Forest land

Water

Wetland

Barren land

Tundra

Snow / Ice

Appendix L2 

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A-6

Figure A-5. Land Use for the CALMET/ CALPUFF Domain 5. The Class I areas are also shown. 

1100 1200 1300 1400 1500 1600 1700 1800 1900

LCC East (km)

-600

-500

-400

-300

-200

-100

0

100

200

LCC North (km)

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

GA

SC

NC

TN

VA

WV

KY

Cape Romain

Cohutta

Joyce 

Kilmer-Slickrok

Great Smoky 

Mountains

Shining Rock

Linville Gorge

Swanquarter

James 

River Face

Shenandoah

Otter Creek Dolly Sods

Brigantine

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

Urban/

built-up land

Agricultural

land

Rangeland

Forest land

Water

Wetland

Barren land

Tundra

Snow / Ice

Appendix L2 

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A-7

Table A-1 Upper Air Stations used in the Subregional Modeling 

 WMO INIT Station Name Latitude (deg.) Longitude (deg.) 

72230 BMX Birmingham (Shelby Apt) 33.10 -86.70 

72233 SIL Slidell 30.33 -89.82 

72235 JAN Jackson/Thompson Fld 32.32 -90.07 

72240 LCH Lake Charles 30.12 -93.22 

72327 BNA Nashville 36.25 -86.57 

Domain 1 

72340 LZK N Little Rock 34.83 -92.27 

72201 EYW Key West Int Ap 24.55 -81.75 

72202 MFL Miami/Fl Intl Univ 25.75 -80.38 

72206 JAX Jacksonville 30.43 -81.70 

72210 TBW Tampa Bay/Ruskin 27.70 -82.40 

72214 TLH Tallahasee Fl Us 30.38 -84.37 

72215 FFC Peachtree City 33.35 -84.56 

72230 BMX Birmingham (Shelby Apt) 33.10 -86.70 

72233 SIL Slidell 30.33 -89.82 

72235 JAN Jackson/Thompson Fld 32.32 -90.07 

Domain 2 

74794 XMR Cape Kennedy 28.48 -80.55 

72208 CHS Charleston 32.90 -80.03 

72215 FFC Peachtree City 33.35 -84.56 

72230 BMX Birmingham (Shelby Apt) 33.1 -86.70 

72235 JAN Jackson/Thompson Fld 32.32 -90.07 

72317 GSO Greensboro 36.08 -79.95 

72318 RNK Roanoke/Blacksburg 37.20 -80.41 

72327 BNA Nashville 36.25 -86.57 

72340 LZK N Little Rock 34.83 -92.27 

72403 IAD Sterling(Wash Dulles) 38.98 -77.47 

72426 ILN Wilmington 39.42 -83.82 

72520 PIT Pittsburgh/Moon Township 40.53 -80.23 

74455 DVN Davenport Municipal Ap 41.60 -90.57 

Domain 3 

74560 ILX Lincoln-Logan County Ap 40.15 -89.33 

72206 JAX Jacksonville 30.43 -81.70 

72208 CHS Charleston 32.90 -80.03 

72210 TBW Tampa Bay/Ruskin 27.70 -82.40 

72214 TLH Tallahasee Fl Us 30.38 -84.37 

72215 FFC Peachtree City 33.35 -84.56 

72221 VPS Valparaiso/Elgin Afb 30.52 -86.58 

72230 BMX Birmingham (Shelby Apt) 33.10 -86.70 

72233 SIL Slidell 30.33 -89.82 

72235 JAN Jackson/Thompson Fld 32.32 -90.07 

72305 MHX Morehead City/Newport 34.70 -76.80 

72317 GSO Greensboro 36.08 -79.95 

72318 RNK Roanoke/Blacksburg 37.20 -80.41 

Domain 4 

72327 BNA Nashville 36.25 -86.57 

72208 CHS Charleston 32.90 -80.03 

72215 FFC Peachtree City 33.35 -84.56 

72305 MHX Morehead City/Newport 34.70 -76.80 

72317 GSO Greensboro 36.08 -79.95 

72318 RNK Roanoke/Blacksburg 37.20 -80.41 

72402 WAL Wallops Island 37.93 -75.48 

72403 IAD Sterling(Wash Dulles) 38.98 -77.47 

72426 ILN Wilmington 39.42 -83.82 

Domain 5 

72520 PIT Pittsburgh/Moon Township 40.53 -80.23 

Appendix L2 

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A-8

Table A-2 Buoys used in the Subregional Modeling 

Station 

number Buoy name 

Latitude 

(deg.) 

Longitude 

(deg.) 

42007 Biloxi 22 nm South-Southeast of Biloxi, MS 30.09 88.77 

42039 Pensacola - 115NM East Southeast of Pensacola, FL 28.79 86.02 Domain 1 

42040 Mobile South 64 nm South of Dauphin Island, AL 29.18 88.21 

41008 Grays Reef - 40 NM Southeast of Savannah, GA 31.40 80.87 

41009 Canaveral 20 NM East of Cape Canaveral, FL 28.50 80.17 

41012 St. Augustine, FL 40NM ENE of St Augustine, FL 30.00 80.60 

42001 Mid Gulf 180 nm South of Southwest Pass, LA. 25.90 89.67 

42003 E Gulf 260 nm South of Panama City, FL 26.07 85.94 

42007 Biloxi 22 nm South-Southeast of Biloxi, MS 30.09 88.77 

42036 W. Tampa 106NM West Northwest of Tampa, FL 28.50 84.52 

42039 Pensacola - 115NM East Southeast of Pensacola, FL 28.79 86.02 

Domain 2 

42040 Mobile South 64 nm South of Dauphin Island, AL 29.18 88.21 

Domain 3 none 

41004 Edisto - 41 NM Southeast of Charleston, SC 32.50 79.09 

41008 Grays Reef - 40 NM Southeast of Savannah, GA 31.40 80.87 

42007 Biloxi 22 nm South-Southeast of Biloxi, MS 30.09 88.77 

42036 W. Tampa 106NM West Northwest of Tampa, FL 28.50 84.52 

42039 Pensacola - 115NM East Southeast of Pensacola, FL 28.79 86.02 

Domain 4 

42040 Mobile South 64 nm South of Dauphin Island, AL 29.18 88.21 

41008 Grays Reef - 40 NM Southeast of Savannah, GA 31.40 80.87 

44009 Delaware Bay 26 NM Southeast of Cape May, NJ 38.46 74.70 Domain 5 

44014 Virginia Beach 64 NM East of Virginia Beach, VA 36.61 74.84 

Appendix L2 

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B-1

APPENDIX B – MEMO ON CALMET OBS/NO-OBS MODES 

Appendix L2 

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B-2

Comments on Observations vs. No-Observations 

Mode in CALMET 

J. Scire 

Earth Tech, Inc. 

August 2, 2005

The CALMET meteorological model accepts observational data in the form of hourly surface observations of 

winds, temperature, pressure and cloud data, hourly precipitation observations, and twice-daily upper air 

sounding data of winds, pressure and temperature. In addition, CALMET allows three-dimensional gridded 

fields of data from prognostic numerical weather forecast models such as the Mesoscale Model Version 5 

(MM5) and the Rapid Update Cycle (RUC) model. The three dimensional prognostic meteorological fields 

include winds, temperature, humidity and liquid water content data such as precipitation and cloud water. 

CALMET can be run in a mode using observations only (Obs-mode), prognostic data only (No-Obs mode) or 

both sets of data (hybrid mode). There are two forms of the hybrid mode – one where the prognostic data can 

replace certain types of observational data entirely (Partial No-obs mode) such as upper air observations, 

precipitation data or cloud data and a second form where the prognostic data is used to supplement observational 

data. 

In the VISTAS BART modeling, Task 2 involves running CALMET using a regional 12-km resolution 

CALMET domain (Figure 1) and Task 3 consists of developing sub-regional domains at a higher (4 km or 

better) grid resolution. The regional domain includes all of the southeastern United States. MM5 data at 36-km 

or 12-km grid spacing are available that covers the entire regional domain. Sub-regional domains will be 

defined for specific BART sources. In particular, higher resolution CALMET simulations are likely to be 

required for Class I areas located in complex terrain and possibly coastal regions. One issue is the CALMET 

mode to be used in the regional and sub-regional CALMET simulations. The inclusion of the observational data 

has both advantages and drawbacks. The considerations include the following: 

(a) Time and space resolution of observational data. While all meteorological observations are useful in hybrid 

mode, the upper air wind observational data are normally the least resolved spatially and temporally. Upper air 

observational data is available at roughly 12-hourly intervals. The typical spacing between upper air soundings 

is over order several hundred kilometers. CALMET will perform a time interpolation of wind data between the 

sounding intervals. This linear time-interpolated wind data is likely to miss important patterns of wind variation 

at scales less than 12 hours. In Obs mode, the spatial interpolation uses an objective analysis procedure to 

define an initial guess field, followed by diagnostic adjustments for terrain effects by CALMET. On the 12-km 

resolution regional domain, terrain effects seen by the model will be reduced due to the coarse grid resolution. 

(b) Time and space resolution of 3-D prognostic data. The time and spatial resolution of the three-dimensional 

gridded MM5 meteorological fields is better than that from the surface and upper air observational network. 

Upper air soundings are available at 12-hr intervals and are widely distributed. Surface observations have 

hourly time resolution but are still more spatially distributed than the MM5 fields that are available at either 36-

km or 12-km grid resolution. 

Appendix L2 

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B-3

Figure 1. VISTAS 12 km regional CALMET modeling domain. 

In addition, rather than just two soundings per day at irregularly spaced intervals separate by several hundred km 

as in the upper air observational dataset, the MM5 dataset essential provides hourly “soundings” over a regular 

grid at hourly intervals. In particular, the better time resolution of the prognostic model fields is likely to better 

characterize the time variation of wind flows in the regional domain. However, on smaller scales, the MM5 data 

may miss important local flow features that are captured by the hourly surface observational network. 

(c) Representativeness of observational data. On the regional domain, relatively large values of the radius of 

influence parameters that determine the relative weight of observations vs. gridded prognostic meteorological 

data are needed in order for the observational data to be relevant in the determination of the final wind fields. 

These weighting parameters in CALMET are applied throughout the modeling domain. In a large, regional 

domain such as anticipated for the Task 2 modeling, large values of the radius of influence parameters may not 

be appropriate because in the complex terrain areas (and also possibly in coastal areas) of the domain, the spatial 

representativeness of the observations may be limited. Small values of the radius of influence parameters makes 

the weight given to the observations limited, and the final wind fields would be determined mainly by the initial 

guess field derived from the prognostic meteorological fields. 

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B-4

(d) Discrepancies between prognostic winds and observations. The CALMET diagnostic wind field module 

resolves discrepancies between the prognostic model-derived initial guess fields and the observations by giving 

greater weight to the observations in the “vicinity’ of the observations (the “vicinity” is defined by the user 

using the radius of influence parameters) and greater weight to the prognostic wind fields in portions of the 

domain away from the observations. Although the prognostic model simulation reflects observational data 

through the use of four-dimensional data assimilation of analysis fields in the MM5 simulations, there will 

sometimes be discrepancies between the observations (which may reflect a very localized flow) and the 36-km 

or 12-km resolved MM5 winds. Sometimes the differences are due to poor time resolution of the observational 

data such as 12-hourly sounding data linear time-interpolated to hourly intervals. In particular, the blending of 

the MM5 data with the observations can lead to wind structures which may not be realistic under some 

conditions. 

(e) Model biases. The MM5 model predictions of winds and temperatures may contain biases relative to the real 

atmosphere. In particular, MM5 sometimes underestimates the frequency of light wind and calm wind 

conditions and possibly underestimates the strength of the nocturnal surface temperature inversion. These 

biases may be most important for near surface sources when relative coarse grid resolution is used. 

(f) Level of effort vs. benefit. The preparation of observational datasets for CALMET on large regional 

domains involves a considerable effort due to the large number of surface, precipitation and upper air stations 

involved. The question is whether the effort associated with the preparation of this dataset is worthwhile given 

that the regional winds may be adequately or even better characterized by the 3-D prognostic model dataset than 

time- and space-interpolated observational data, especially above the surface where sounding data is fairly 

sparse spatially and poorly-resolved in time. 

Recommendations 

Given the considerations presented above, it is recommended that the regional VISTAS CALMET simulations 

be conducted in No-Observations mode using the highest resolution MM5 data available for each year modeled. 

The draft BART modeling protocol will address appropriate applications for CALMET using a 12-km grid 

resolution and criteria to determine if 12-km or a finer grid resolution is appropriate for modeling purposes. It is 

also recommended that sub-regional CALMET domains be modeled using the hybrid mode where the MM5 

datasets are used to define the initial guess fields, but surface and upper air observational data are used to refine 

the meteorological parameters locally in the vicinity of the observational sites. 

The regional wind patterns are likely to be adequately characterized by the MM5 simulations. Many 

observations, especially surface observations, may reflect local conditions on a scale smaller than the grid 

resolution of the regional domain. The introduction of the local observations into the regional modeling domain 

may extend the influence of the observational data beyond its true representativeness and result in internally 

inconsistent flow features. In particular the time interpolation of the 12-hourly upper air sounding data may 

wash out structure in the MM5 fields that are appropriate to retain. Given that the regional modeling domain 

includes areas of complex terrain, coastal regions and relatively flat terrain, a single set of representative weights 

that allows significant influence of the observations where appropriate, will involve a considerable effort and 

substantial testing. The internally consistent MM5 fields are considered likely to be appropriate for the regional 

simulations, and the incremental benefit of adding the observational data into the regional CALMET simulations 

is not considered worthwhile. 

Appendix L2 

Regional Haze SIP for Florida

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B-5

However, on the smaller sub-regional domains, with the higher CALMET grid resolution and the smaller 

domain size, more control over the region of influence of the meteorological observations can be achieved. It is 

easier for the diagnostic model to allow the local flow observations to have appropriate influence in the vicinity 

of the observation, but allow terrain-adjusted flow to dominate away from the observations. Given that the subregional domains will be used especially in complex flow situations (complex terrain and coastal regions), the 

relatively coarse-scale MM5 simulations are less likely to be adequate, and the introduction observational data is 

more likely to achieve improvements in the resulting meteorological fields. 

Appendix L2 

Regional Haze SIP for Florida

Page 150 of 266