Protocol for BART-Related 

Visibility Impairment Modeling Analyses 

in North Dakota 

(Final)

November, 2005 

North Dakota Department of Health 

Division of Air Quality 

1200 Missouri Avenue 

Bismarck, ND 58506
Table of Contents

Page 

1 Overview 1 

2 Modeling Methodology 8 

2.1 BART Applicability Threshold 8 

2.2 Pollutants to Consider 9 

2.3 Visibility Modeling System 10 

3 Model Input Data/Settings 14 

3.1 CALMET Input 16 

3.1.1 Meteorological Data 17 

3.1.1.1 Mesoscale Model Data 17 

3.1.1.2 Surface Observations 17 

3.1.1.3 Upper-air Observations 20 

3.1.1.4 Precipitation Data 21 

3.1.2 Geophysical Data 21 

3.1.3 CALMET Control File Settings 23 

3.2 CALPUFF Input 27 

3.2.1 Emissions and Stack Data 27 

3.2.2 Ozone Background 29 

3.2.3 Ammonia Background 32 

3.2.4 Receptor Locations 33 

3.2.5 CALPUFF Control File Settings 35 

3.3 POSTUTIL Input 39 

3.4 CALPOST Input 40 

4 Model Execution and Output Interpretation 50 

 4.1 BART Screening 50 

4.2 Degree of Visibility Improvement 51 

4.3 CALBART Utility 54 

 

Appendix A NDDH PSD Class I Area Receptors 
1 

1 Overview 

On June 15, 2005, EPA issued final amendments to its July 1999 regional haze rule1. These 

amendments apply to the provisions of the regional haze rule that require emission controls known as 

Best Available Retrofit Technology, or BART, for industrial facilities emitting air pollutants that 

reduce visibility in PSD Class I areas. These pollutants include fine particulate matter (PM2.5), and 

compounds which contribute to PM2.5 formation, such as nitrogen oxides, sulfur dioxide, certain 

volatile organic compounds, and ammonia. The amendments include final guidelines, known as 

BART guidelines, for states to use in determining which facilities must install controls and the types

of controls the facilities must use. 

 

1

Federal Register, 2005. EPA Regional Haze Regulations and Guidelines for Best 

Available Retrofit Technology (BART) Determinations; Final Rule. Federal Register, July 6, 

2005, Vol. 70, No. 128, p. 39103-39172. 

The June 15 guidelines address how to identify BART-eligible sources, how to identify sources 

Asubject to BART@, and the BART determination including analysis of BART options. As part of 

this process, visibility computer modeling will assist in the identification of sources Asubject to 

BART@, and in the consideration of BART options to determine the degree of visibility 

improvement. The North Dakota Department of Health (NDDH) has established a protocol for 

BART-related modeling applicable to BART-eligible sources in North Dakota, which is the focus of 

this document. This protocol is intended to apply to visibility modeling for both identification of 

sources Asubject to BART@ (BART screening), and for determining the degree of visibility 

improvement related to the selection of BART control. 
2 

To ultimately determine compliance with Regional Haze visibility improvement goals, four phases 

of visibility modeling are anticipated. In chronological order, these are: 

1) single-source modeling to determine which BART-eligible sources are subject to BART (or 

BART-applicable), 

2) single-source modeling to determine the degree of visibility improvement attributable to 

proposed BART control for each BART-applicable source, 

3) cumulative modeling to determine the combined effect of proposed BART controls for 

BART-applicable sources in North Dakota, and 

4) regional-scale modeling to determine if the combined effect of proposed BART controls, and 

other emissions reductions, for all western states ultimately satisfies visibility improvement 

goals. 

The protocol outlined in this document applies only to the first two phases involving single-source 

modeling, that is, screening to determine which BART-eligible sources are subject to BART, and 

single-source modeling to determine the degree of improvement related to the proposed BART 

control. With the exception of emission rates and stack parameters, the methodologies for these first

two phases of modeling, including all model inputs, are identical. The NDDH recognizes that the 

Adegree of improvement@ modeling will be only one of several criteria used to establish optimum 

BART controls. 
3 

The NDDH will conduct visibility modeling to determine which North Dakota BART-eligible 

sources are subject to BART. It is expected that BART-applicable sources will want to conduct their 

own single-source modeling to determine the degree of visibility improvement, as they consider a 

variety of BART control options. Upon request, the NDDH will also perform the single-source 

degree of improvement modeling. Ultimately, the NDDH will review and verify all single-source 

degree of visibility improvement modeling analyses. Note that all BART-related single-source 

modeling for sources in North Dakota must follow the protocol outlined here. Because of this 

requirement, the NDDH will not expect companies which operate BART-eligible sources to provide 

individual protocols for their BART-related modeling. 

When all BART proposals have been submitted, the NDDH will conduct a cumulative modeling 

analysis to determine the combined effect of proposed North Dakota BART controls on visibility 

improvement in North Dakota Class I areas (Phase 3 modeling). A separate protocol for that analysis 

will be completed by the NDDH prior to modeling. The final regional-scale modeling analysis to 

ultimately determine compliance with visibility improvement goals (Phase 4 modeling) will be 

conducted by the Western Regional Air Partnership (WRAP) regional planning organization. 

WRAP is developing the protocol and establishing input data for that analysis. At this point, the 

timing of the WRAP regional-scale modeling analysis is unclear. Also unclear is the manner in 

which the NDDH cumulative analysis might interface with the WRAP regional-scale analysis. 

BART-eligible sources in North Dakota have been previously determined by NDDH, and are listed 

in Table 1-1. BART-related visibility modeling for North Dakota BART-eligible sources will focus 

on PSD Class I areas in North Dakota, which include the Theodore Roosevelt National Park (three 
4 

units) and the Lostwood Wilderness Area. Note that the three units of Theodore Roosevelt National 

Park will be treated as separate Class I areas for purposes of interpreting visibility modeling results 

(Section 4). Locations of BART-eligible sources with respect to PSD Class I areas in North Dakota 

are illustrated in Figure 1-1. 

Table 1-1 

 BART-Eligible Sources in North Dakota

Facility Operator

Leland Olds Station 1 

Leland Olds Station 2 

Basin Electric Power Coop. 

Milton R. Young Station 1 

Milton R. Young Station 2 

Minnkota Power Coop. 

Heskett Station 2 Montana-Dakota Utilities 

Stanton Station 1 Great River Energy 

Coal Creek Station 1 

Coal Creek Station 2 

Great River Energy 

Drayton Sugar Beet Processing American Crystal Sugar 

Mandan Refinery Tesoro 
5 

1

2

3

4

6 

0 100 200 300 

 Key 1 Leland Olds Station/ Stanton Station 2 Milton R Young Statio 3 Heskett Station 4 Coal Creek Station 5 ACS Drayton 6 ACS Drayton (modele

BART-Eligible Source

LostwoodWilderness Area

TRNP South Unit

TRNP North Unit

TRNP Elkhorn Ranch Unit

PSD Class I Area

 Bismarck

NDDHModeliDomain

Figure 1-1: BART-Eligible Sources and PSD Class I Areas
6 

Regarding the requirement to use the BART guideline for all BART-related visibility analyses, the 

guideline states, 

ASection 169A(b) requires us to issue guidelines for states to follow in establishing BART 

emission limitations for fossil-fuel fired power plants having a capacity in excess of 750 

megawatts .... For sources other than 750 megawatt power plants, however, states retain the 

discretion to adopt approaches that differ from the guidelines.@

In this matter, the NDDH has elected to use its discretion to require use of the BART guideline for 

all BART-eligible sources in North Dakota. 

The single-source modeling protocol outlined here provides sufficient detail to ensure consistency 

among BART-related analyses for sources in North Dakota. In developing this protocol, the NDDH 

has implemented guidance outlined in the June 15, 2005 rule. Where clarification was needed, this 

guidance has been augmented through communications with EPA and FLM=s.

2

 To the extent 

applicable, the NDDH BART modeling protocol is consistent with the North Dakota alternative 

protocol for PSD Class I increment analyses.3

 

2

EPA, 2005. Electronic message from Kathy Kaufman, Research Triangle Park, NC 

27711. 

3NDDH, 2005. A Proposed Alternative Air Quality Modeling Protocol to Examine the 

Status of Attainment of PSD Class I Increment. North Dakota Department of Health, Bismarck, 

ND 58506. 
7 

The remainder of this document describes the NDDH single-source visibility modeling protocol. 

Modeling methodology for BART-related visibility analyses is discussed in general in Section 2. 

Section 3 provides detailed information regarding modeling system components and input data 

requirements. Model execution and interpretation of output are discussed in Section 4. NDDH 

Class I area receptor coordinates/elevations are provided in Appendix A. 

NDDH contacts for questions on BART-related modeling and general Regional Haze issues are 

provided in Table 1-2. 

Table 1-2 

NDDH Contact Information

Name Task Phone E-mail

Dana Mount General Regional Haze 

Coordination 

(701)328-5150 dmount@state.nd.us

Tom Bachman Emissions/Rules/BART (701)328-5188 tbachman@state.nd.us

Steve Weber Modeling (701)328-5188 sweber@state.nd.us

Rob White Modeling (701)328-5188 rwhite@state.nd.us 
8 

2 Modeling Methodology

For the determination of BART applicability for BART-eligible sources (BART screening), 

modeling methodology involves execution of an appropriate visibility model, then comparison of 

model predictions with the BART applicability threshold. To determine the degree of improvement 

from selected BART options, the visibility model is executed again for post-BART control 

conditions, and results are compared with those for pre-BART conditions. In both cases, modeling is 

applied on a single facility basis. With the exception of emission rates and stack parameters, model 

settings and input data for both pre-BART and post-BART model runs are identical. 

For BART screening, all BART-eligible units contained within a subject facility must be modeled 

together before comparing results with the BART applicability threshold. This would include, for 

example, both BART-eligible units of a power plant. To determine the degree of visibility 

improvement from selected BART options, however, it may be desirable to model units individually, 

as required improvement and BART options may vary by unit. 

2.1 BART Applicability Threshold

In general, to determine which BART-eligible sources must apply BART, single facility modeling 

results for PSD Class I areas are compared with a visibility threshold, expressed in deciviews. The 

NDDH will follow recommendations in the June 15 BART guideline which states, 
9 

AA single source that is responsible for a 1.0 deciview change or more should be considered 

to Acause@ visibility impairment; a source that causes less than a 1.0 deciview change may 

still Acontribute@ to visibility impairment and thus be subject to BART .... As a general 

matter, any threshold that you use for determining whether a source Acontributes@ to 

visibility impairment should not be higher than 0.5 deciviews.@

As a practical matter, the NDDH sees no reason to distinguish among BART-eligible sources which 

Acause@ visibility impairment versus those sources which Acontribute@ to visibility impairment in 

PSD Class I areas. Therefore, the NDDH will generally use a 0.5 deciview threshold to determine 

which BART-eligible sources must apply BART. The NDDH may reconsider the threshold value if 

subsequent multi-source modeling reveals difficulty in meeting visibility improvement goals. 

2.2 Pollutants to Consider

For both BART applicability and degree of visibility improvement analyses, the BART guideline 

specifies that only primary emissions need to be considered. These primary emissions include SO2, 

NOx, and direct particulate matter (PM) emissions specified as either coarse (PM10 minus PM2.5) or 

fine (PM2.5). If this distinction in size of PM emissions cannot be made, it would be appropriate to 

consider all PM10 emissions as PM2.5. 

The BART guideline also discusses VOC or ammonia emissions as possibly impacting visibility. 

For BART eligible sources in North Dakota, the NDDH considers these emissions (and associated 
10 

visibility impacts) to be negligible, and will not require inclusion of VOC or ammonia species in 

BART-related visibility analyses. 

Emission rates and stack parameters for BART-related visibility modeling are discussed in detail in 

Section 3. 

2.3 Visibility Modeling System

As shown in Figure 1-1, all BART-eligible sources will be located more than 50 kilometers from the 

nearest PSD Class I area in North Dakota. Source-receptor distances greater than 50 kilometers 

constitute long-range transport, and the EPA-approved model for long-range distances is 

CALPUFF4

. As specified in the BART guideline, 

ACALPUFF is the best regulatory modeling application currently available for predicting a 

single source=s contribution to visibility impairment and is currently the only EPA-approved 

model for use in estimating single source pollutant concentrations resulting from the longrange transport of primary pollutants. It can also be used for some other purposes, such as 

the visibility assessments addressed in today=s rule, to account for the chemical 

transformation of SO2 and NOx .@

 

4CFR, 2003. EPA Guideline on Air Quality Models. 40 CFR (Code of Federal 

Regulations) Part 51, Appendix W. 
11 

The NDDH therefore recommends and will use CALPUFF for BART-related modeling. 

The CALPUFF computer modeling system includes the CALMET meteorological model5, the 

CALPUFF dispersion model6, and the CALPOST post processing program. The CALPOST 

program accommodates the visibility calculations. For visibility analyses, the CALPUFF system 

also provides the optional POSTUTIL program. POSTUTIL implements the ammonia limiting 

method to address double-counting of available ammonia for NOx to NO3 conversion chemistry in 

CALPUFF. In the sequence of execution, POSTUTIL would follow CALPUFF and precede 

CALPOST. CALPUFF system execution is depicted schematically in Figure 2-1. Earth Tech (Earth 

Tech, Inc., Concord, MA), the primary model developer, also provides several utility programs to 

accommodate pre-processing of meteorological and geophysical data for CALMET. 

Appropriate versions of CALPUFF software for BART-related modeling are shown in Table 2-1. 

Note that these newer versions of CALPUFF software are not the same as versions utilized in the 

recent periodic review of PSD Class I increment in North Dakota. These newer versions, however, 

contain coding error corrections and other enhancements, and appear to be consistent with the 

versions being recommended by most Regional Planning Organizations for BART-related modeling. 

 The CALPUFF system software can be downloaded free of charge from the Earth Tech web site 

 

5

Earth Tech, Inc., 2000. A User=s Guide for the Calmet Meteorological Model (Version 

5). Earth Tech, Inc., Concord, MA 01742. 

6

Earth Tech, Inc., 2000. A User=s Guide for the Calpuff Dispersion Model (Version 5). 

Earth Tech, Inc., Concord, MA 01742. 
12 

Figure 2-1. Cal puff Processing to Compute Visibility Impacts 

( (ieophysica 

~ Data 

-{~-~--~~-~-~~---- -- ~~--

I " Ci\IMFT "' Meteorological / ~- Meteorological Model ~ 

Data 

' 

llourlv ~ Mctemolo<> b ic~1l Data Fields 

,} 

Ci\l J>\JFF Dispersion 

Model 

,if 

'iiourly Concentration::-' 

for all Pollutants 

__/ 

'if 

POSTUTIL: i\n1monia 

l_imiting Method 

'"' 

,----- --------- I lourly ( 'onccntrations 

with Nitrates Adjusted 

'if 

" Cl\IJ'OST , l'oslpn>ccss<>r 

,,. ~ 

24~hr dclta~clccivicw at ------

"---- Class I /\rcas ~-
13 

(www.src.com/calpuff/calpuff1.htm). For consistency and to ensure executables can accommodate 

large file sizes, however, it is recommended that the software be obtained directly from NDDH. 

 

 Table 2-1 

 CALPUFF System Versions 

 Applicable For BART Modeling

Program Version Level 

CALMET 5.53a 040716 

CALPUFF 5.711a 040716 

POSTUTIL 1.4 040818 

CALPOST 5.51 030709 

Application of the ammonia limiting method, utilizing POSTUTIL, is recommended by NDDH. The 

NDDH will be applying the ammonia limiting method in BART-applicability analyses. 
14 

3 Model Input Data/Settings

The CALPUFF modeling system includes the CALMET meteorological model, the CALPUFF 

dispersion model, the CALPOST postprocessing program, and (optionally) the POSTUTIL program 

which can be used to implement the ammonia limiting method in visibility analyses. Each of these 

modules includes a control file which contains user-selected settings to control processing during 

model execution. CALMET and CALPUFF have additional input data requirements. Input 

data/settings which are consistent with the use of these programs for BART-related visibility 

analyses in North Dakota are discussed in Sections 3.1 through 3.4. 

The CALMET/CALPUFF modeling domain preferred by the NDDH for BART-related modeling is 

illustrated in Figure 3-1. Dimensions of the domain are 639 kilometers east-west by 459 kilometers 

north-south, with a grid cell size of 3 kilometers. In the vertical, the domain is defined by twelve 

vertical layers. The domain is sized and positioned to encompass all North Dakota PSD Class I areas 

and BART-eligible sources (with exception noted below), with sufficient buffer area. Because the 

domain is relatively large, the Lambert Conformal map projection is used to better accommodate the 

earth=s curvature. 

As shown in Figure 1-1, the American Crystal Sugar Drayton plant is located outside of the NDDH 

modeling domain. Even if the domain was extended eastward to incorporate the Drayton plant, the 

plant is located about 400 kilometers from the nearest Class I area (Lostwood Wilderness Area), and 
15 

km

Figure 3-1: Gridded Modeling Domain

0 100 200 300 400
16 

this distance is beyond the accepted range of CALPUFF (about 300 kilometers). For modeling 

purposes, therefore, the NDDH will reposition the Drayton plant about 100 kilometers to the west, to 

create a virtual source located just inside the east boundary of the current modeling domain 

(represented by the AACS Drayton (modeled)@ source in Figure 1-1). This adjustment will provide a 

source-receptor distance more consistent with the documented limits of CALPUFF, and should 

ensure conservative results. 

3.1 CALMET Input

Input requirements for the CALMET model include various meteorological and geophysical data 

sets, and a control input file with appropriate settings. Required meteorological data include surface, 

upper-air, and precipitation observations, and mesoscale model output data fields. Geophysical input 

data include terrain elevation and land-use data. Though CALMET may be run with mesoscale 

model meteorological data, alone (i.e., no observations), the EPA modeling guideline4 recommends 

Ablending@ observations with the mesoscale model fields. Therefore, the NDDH will include 

observations in a blended approach. As required in the EPA modeling guideline, meteorological 

observations and mesoscale model fields for three years (2000-2002) will be used with CALMET. 

All meteorological and geophysical input data sets required for CALMET execution have been 

previously prepared for BART-related modeling analyses in North Dakota. Upon request, NDDH 

will provide these meteorological and geophysical data sets. 
17 

3.1.1 Meteorological Data

3.1.1.1 Mesoscale Model Data

Mesoscale model wind fields used with CALMET are based on the National Center for 

Environmental Predictions (NCEP) Rapid Update Cycle (RUC) forecast model. Mesoscale model 

fields in the MM5.DAT format required by CALMET were developed by a contractor7

. The 

contractor obtained and archived RUC hourly initial analyses from NCEP for years 2000 through 

2002. Resolution of these initial analyses was 40 km. The contractor used the ARPS Data 

Assimilation System (ADAS) to enhance resolution to 10 km, and converted the resultant hourly 

wind fields to the MM5.DAT format recognized by CALMET. The domain of these hourly wind 

fields is consistent with the CALMET/CALPUFF domain used by NDDH. 

3.1.1.2 Surface Observations

 

7WindLogics, 2004. RUC Analysis-Based CALMET Meteorological Data for the State 

of North Dakota. WindLogics, Inc., St. Paul, MN 55108. 

Concurrent surface observations for the three-year period 2000-2002 were obtained in surface hourly 

abbreviated format from the National Climatic Data Center (NCDC). Data were obtained for 

approximately 35 ASOS/manual stations located within or near the NDDH CALMET/CALPUFF 

domain, although the specific number of stations varied among the three years. The ASOS/manual 

observations reflect data from stations operated by the National Weather Service, Federal Aviation 
18 

Administration, U.S. Air Force, and Environment Canada. Location of these stations is shown in 

Figure 3-2. 

To compensate for well-documented deficiencies in ASOS cloud data above 12,000 feet, NDDH also 

obtained concurrent GOES ASOS satellite cloud data for all selected surface stations. The satellite 

hourly observations included cloud amount (sky cover) and cloud height (ceiling height) data above 

12,000 feet, and were therefore used to supplement the ASOS observations. 

NDDH prepared custom software to merge the ASOS and satellite data. Earth Tech utility software 

was then used to quality assure merged data, and convert to the format required by CALMET 

(SURF.DAT). Standard methods were applied to provide substitutions for missing data.8,9 The 

occurrence of missing data elements in the surface observations was generally very limited, and 

within the tolerances suggested by EPA. 

 

8Atkinson, Dennis and Russell F. Lee, 1992. Procedures for Substituting Values for 

Missing NWS Meteorological Data for Use in Regulatory Air Quality Models. 

9

EPA, 1987. On-Site Meteorological Program Guidance for Regulatory Modeling 

Application. Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711. 
19 

BIS

FAR

DVL

RDRGFK

DIK

JMS

MIB

MOT ISN

N60

GGW

GDV

MLS

BIL

SDY

OLF

JDN

HON

RAP

ABR

PIR

2WX MBG

SHR

GCC

YBR

YEN

YQR

YWG

Figure 3-2: Surface / Upper-air Meteorological Stations

Surface Station

Surface + Upper-air Station
20 

3.1.1.3 Upper-Air Observations

Upper-air observations for the three-year period 2000-2002 were obtained from NOAA=s Forecast 

Systems Laboratory (FSL) in Boulder, Colorado. Upper-air sounding files were downloaded from 

the FSL website (www.fsl.noaa.gov) in the original FSL format, which is accepted for CALMET 

input as the option ANCDC CD-ROM@. Data were obtained for six upper-air stations (NWS) located 

within or near the NDDH CALMET/CALPUFF domain. Location of these stations is shown in 

Figure 3-2. 

Processing of the upper-air data for CALMET input involved using Earth Tech utility software, 

running custom software written by NDDH staff, and manual editing of data files. The main Earth 

Tech program quality checked the upper-air data files, output error messages to identify problems in 

the data to be corrected by the user, and converted the data to the format required by CALMET. The 

NDDH custom software performed additional quality checks, and, combined with manual editing of 

data files, corrected additional errors or problems in the data and filled in for missing data when 

necessary. Substitutions for missing data generally followed standard EPA guidance.8,9 Upper-air 

soundings were processed up to the 500-mb level to accommodate mixing heights up to 4000 meters 

above ground level at Rapid City, South Dakota. In addition, the main Earth Tech processing 

program had to be modified slightly (corrected) to correctly read longitudes for Glasgow, Montana. 
21 

3.1.1.4 Precipitation Data

Hourly precipitation data for years 2000-2002 were obtained from NCDC in TD-3240 format. Data 

were included for approximately 90 NWS hourly recording stations located within or near the 

NDDH CALMET/CALPUFF modeling domain, although the specific number of stations varied 

among the three years. Location of these stations is shown in Figure 3-3. 

Earth Tech utility software was employed to quality assure the TD-3240 data, and process it into the 

format required by CALMET (PRECIP.DAT). No substitutions were made for missing data, 

because CALMET substitutes internally from the nearest available station, and the station resolution 

was relatively good (Figure 3-3). 

3.1.2 Geophysical Data

CALMET requires specification of terrain elevation, and parameters related to the land-use profile, 

for each grid cell in the modeling domain. The NDDH derived terrain elevations from United States 

Geological Survey (USGS) GTOPO30 data sets for North America central and mountain zones. 

Land-use profiles were derived from the USGS Global Data Set for North America. 

Using Earth Tech utility software, all gridded terrain and land-use data were processed into the single 

geophysical file (GEO.DAT) required by CALMET. NDDH assumed Earth Tech default values 
22 

Figure 3-3: Precipitation Stations 

... 

... 

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... 

... ... 

... 

I"' 

... 

... 

... ... 

... 

... ... 

... 

... 

... 

... 

... 

... 

...... ... 

... 

... 

... ... 

I ... 

... ... 

... I ... 

I 

... ... 

... ... ... 

... ...... 

,.. 

... ... 

... 

I 

... 

I 

... 

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1 ... 

- ... 

-

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... 
23 

relating surface roughness length, albedo, Bowen ratio, soil heat flux, and leaf area index to land-use 

type. 

3.1.3 CALMET Control File Settings

CALMET control file settings recommended for processing years 2000 through 2002 data for 

BART-related visibility analyses are generally consistent with guidance from the Interagency 

Workgroup on Air Quality Modeling (IWAQM)10. IWAQM recommendations for CALMET control 

file variable settings fall into two categories. IWAQM-defined variables are those for which 

IWAQM provides a default value as a general recommendation for all analyses. User-defined 

variables are those where IWAQM recognizes the input value will need to be tailored for a given 

application, and default values are therefore not provided. 

For BART-related visibility analyses, the NDDH has established appropriate settings for userdefined variables, and has determined the need to adjust a limited number of IWAQM-defined 

variables from recommended values, as discussed below. The CALMET control file user-defined 

settings, as well as the IWAQM-defined settings which have been adjusted by NDDH, are 

summarized in Table 3-1. IWAQM-defined settings adjusted by NDDH have a highlighted 

background in the Table. 

 

10EPA, 1998. IWAQM Phase 2 Summary Report and Recommendations for Modeling 

Long Range Transport Impacts. Publication No. EPA-454/R-98-019, Office of Air Quality 

Planning and Standards, Research Triangle Park, NC 27711. 
24 

Table 3-1 

 User-Defined and 

 Non-IWAQM Settings for 

 CALMET Control File

Variable Description Value

NSSTA No. of surface stations 32,41,40* 

NUSTA No. of upper-air stations 5 

NPSTA No. of precipitation stations 89,93,93* 

IBTZ Base time zone 7 

PMAP Map projection 

(LCC=Lambert Conformal Conic) 

LCC 

FEAST False easting at origin 0.0 

FNORTH False northing at origin 0.0 

RLAT0 Origin latitude of projection 44.0N 

RLON0 Central meridian of projection 102.0W 

XLAT1 Latitude of 1st standard parallel for projection 46.0N 

XLAT2 Latitude of 2nd standard parallel for projection 48.5N 

DATUM Datum-region for output coordinates NWS-27 

NX No. of X grid cells 213 

NY No. of Y grid cells 153 

DGRIDM Grid spacing (km) 3.0 

XORIGKM Southwest grid cell X coordinate -380 

YORIGKM Southwest grid cell Y coordinate 140 

NZ No. vertical layers 12 

ZFACE Cell face heights (m) 0.,20.,50.,90.,140.,200.,

270.,370.,500.,1000., 

1700.,2500.,4200. 

NOOBS No observation mode (0 = no) 0 
25 

Variable Description Value

IPROG Use MM5.DAT file as initial guess wind field 

(14=yes) 

14 

RMAX1 Max. radius of influence of surface observation 

(km) 

100 

RMAX2 Max. radius of influence of upper-air observation 

(km) 

200 

RMAX3 Max. radius of influence over water (km) 200 

TERRAD Radius of influence of terrain features (km) 10 

R1 Distance from a surface observation station at 

which the wind observation and the first guess field 

are equally weighted (km) 

10 

R2 Distance from an upper-air observation station at 

which the wind observation and the first guess field 

are equally weighted (km) 

10 

ISURFT Surface station number used for the surface 

temperature for the diagnostic wind field module 

(Bismarck) 

12,17,17* 

IUPT Upper-air station number used to compute the 

domain-scale temperature lapse rate for the 

diagnostic wind field module (Bismarck) 

1 

ZUPWND Bottom and top of layer through which the domainscale winds are computed (m) 1.,2500. 

MNMDAV Max. search distance (in grid cells) for spatial 

averaging of mixing ht. and temperature 

7 

ILEVZI Layer of winds used in upwind averaging of mixing 

heights 

3 

ZIMAX Maximum over land mixing height (m) 4000. 

ZIMAXW Maximum over water mixing height (m) 4000. 

* Values for years 2000, 2001, 2002 
26 

Most of the user-defined settings are intuitive, related to parameterization of the meteorological grid 

used with CALMET, as previously discussed. The remaining user-defined variables, (RMAX1, 

RMAX2, RMAX3, TERRAD, R1, R2) control the influence of mesoscale model data, station 

observations, and terrain features in development of the final wind field. Settings for these variables 

are based on the NDDH alternative protocol for PSD Class I increment analyses.3

NDDH settings for IWAQM-defined variables are consistent with IWAQM recommendations, with 

limited exceptions as established in the alternative protocol for PSD Class I increment analyses. 

Because the use of mesoscale meteorological data is now being generally recommended for longrange modeling analyses, the IPROG variable has been changed from 0 to 14, which reflects use of 

MM5 format data (in this case RUC data) as the initial guess wind field. The ZUPWND setting has 

been changed for consistency with default values in recent versions of CALMET (the IWAQM 

setting reflected defaults for an older version of CALMET). Based on visual feedback testing, 

IWAQM settings for variables related to spatial averaging of mixing heights, MNMDAV and 

ILEVZI, are adjusted to provide averaging over a larger area. Because the NDDH 

CALMET/CALPUFF modeling domain extends into the western part of the upper Great Plains, 

maximum mixing height settings (ZIMAX/ZIMAXW) are increased from 3000 to 4000 meters to be 

consistent with maximum mixing heights reported for this region.11 Note that the CALMET BIAS 

factors have no effect when mesoscale data are used as the initial guess wind field. 

 

11Holzworth, 1972. Mixing Heights, Wind Speeds, and Potential for Urban Air Pollution 

Throughout the Contiguous United States. EPA Publication No. AP-101, Office of Air Programs 
27 

Settings as discussed above are incorporated in the CALMET control file prepared by NDDH for 

BART-related visibility analyses. A sample file with NDDH settings will be provided upon request. 

3.2 CALPUFF Input

Along with the CALMET-processed meteorological data, CALPUFF requires the user to provide 

emissions and stack data, receptor locations, input control file settings, and (optionally) hourly ozone 

data before the model can be executed. A background ammonia value is also required. 

3.2.1 Emissions and Stack Data

To determine which BART-eligible sources are subject to BART, the BART guideline stipulates 

modeling primary pollutants SO2, NOx, and PM10 (coarse and fine) using maximum emission rates. 

The guideline states, 

AThe emissions estimates used in the models are intended to reflect steady-state operating 

conditions during periods of high capacity utilization. We do not generally recommend that 

emissions reflecting periods of start-up, shutdown, and malfunction be used, as such 

emission rates could produce higher than normal effects than would be typical of most 

facilities. We recommend that States use the 24-hour average actual emission rate from the 

highest emitting day of the meteorological period modeled, unless this rate reflects periods 

of start-up, shutdown, or malfunction.@
28 

Since the meteorological period modeled will be 2000 through 2002, the NDDH requested 

companies operating BART-eligible sources to provide maximum 24-hour emission rates (with 

exception of start-up, shutdown, and malfunction conditions) for this three-year period. Other stack 

data required by CALPUFF include stack height, stack diameter, exit velocity, exit temperature, 

location, and stack-base elevation. Entries for these stack parameters are taken from PSD increment 

modeling recently completed by NDDH.3 Entries for the dynamic stack parameters, exit velocity and 

exit temperature, reflect an average for the 2000-2002 period. 

Emission rates provided by BART-eligible source companies, and appropriate for BART-related 

visibility modeling, are shown in Table 3-2. When the BART-eligible source company only 

provided total particulate matter emission rates, PM10 emission rates were calculated based on data 

from recent Annual Emission Inventory Reports. Furthermore, the NDDH believes that assuming all 

PM10 emissions are PM2.5 would be too conservative. Therefore, PM2.5 emissions were calculated 

based on data in the 2004 Annual Emission Inventory Report. The NDDH recognizes that better data 

may become available on the particle size distribution of PM emissions at individual sources. 

BART-applicable source companies are free to use the better data in the BART-related modeling 

provided a justification is included as part of the BART analysis. 

Associated stack parameters for modeling are found in Table 3-3. Tables 3-2 and 3-3 provide the 

appropriate emission rates and stack data to use in the CALPUFF analyses to determine which 

BART-eligible sources are subject to BART. Building downwash effects will not be considered in 

the CALPUFF visibility analyses. 
29 

To determine the degree of visibility improvement from BART controls, the BART guideline 

recommends comparing results of pre-control modeling with results of post-control modeling. Precontrol emission rates and stack data would be equivalent to those used for the BART screening 

analysis from Tables 3-2 and 3-3. Post-control emission rates and stack data must be provided by the 

BART applicable source company as part of the BART analysis. Post-control emission rates are 

calculated as a percentage of the pre-control emission rates, using the efficiency of the proposed 

control equipment and/or process changes. 

If CALPUFF multi-source analyses are eventually conducted to address the combined effect of 

proposed BART controls, as alluded to in Section 1, it may be appropriate to reevaluate the use of 

peak 24-hour emission rates. Use of a non-peak emission characterization may be more realistic for 

determination of cumulative visibility impact. 

3.2.2 Ozone Background

CALPUFF utilizes background ozone values in its chemistry module. The model accepts either a 

single constant background ozone value, or an input file of hourly ozone values commensurate with 
30 

Table 3-2 

BART Eligible Sources 

Screening Analysis 

Emission Rates

Company Unit

PM10

(lb/hr)

PM2.5

(Fine) (lb/hr)

PM Coarse* (lb/hr)

SO2(lb/hr

Basin Electric Power Coop. Leland Olds 1 155.2 16.5 138.7 5,970Basin Electric Power Coop. Leland Olds 2 253.2 26.9 226.3 12,20Minnkota Power Coop. M.R. Young 1 42.2 5.5 36.7 7,231Minnkota Power Coop. M.R. Young 2 206.8 28.1 178.7 6,879Montana Dakota Utilities Heskett 2 25.8 21.6 4.2 1,475Great River Energy Stanton 1 31.8 1.9 29.9 3,418Great River Energy Coal Creek 1 249.2 101.9 147.3 5,733Great River Energy Coal Creek 2 216.1 88.4 127.7 4,969American Crystal Sugar Drayton Boiler 

Drayton Lime Kiln** 

25.7 1.0 

4.9 0.2 

20.8 0.8 

197.0 0.2 

Tesoro Mandan Ref CO Furn 14.4 14.4 0.0 55.8 

 *PM coarse = PM10 - PM2.5

**Entries reflect total for lime kiln emission points. 
31 

Table 3-3 

BART Eligible Sources 

Screening Analysis 

Stack Parameters

Unit

X Coord.* (km)

Y Coord.* (km)

Stack Height (m)

Base Elevation (m)

Stack Diam. (m)

Exit Veloci(m/s)

Leland Olds 1 51.180 365.146 106.7 518.3 5.3 19.7 Leland Olds 2 51.282 365.080 152.4 518.3 6.7 25.0 M.R. Young 1 59.473 341.392 91.4 597.4 5.8 18.5 M.R. Young 2 59.455 341.308 167.6 597.4 7.6 19.2 Heskett 2 84.846 319.403 91.4 514.8 3.7 17.4 Stanton 1 50.361 365.705 77.7 518.3 4.6 19.9 Coal Creek 1 63.387 376.062 201.0 602.0 6.7 25.9 Coal Creek 2 63.492 376.068 201.0 602.0 6.7 24.9 Drayton Boiler** 254.569 521.644 36.6 245.1 2.4 21.7 Drayton L. Kiln** 254.554 521.657 35.1 245.1 0.3 21.0 Mandan Ref CO F. 85.094 317.518 60.5 518.5 2.44 12.6 

 *Coordinates reflect North Dakota Lambert Projection. **The coordinates for Drayton boiler and lime kiln reflect the location of the repositioned virtual sources used parameters for the lime kiln reflect a composite of all lime kiln emission points. 
32 

the period of meteorological data. The NDDH uses the hourly ozone file option with CALPUFF, 

and would regard this as the appropriate implementation for BART-related visibility modeling (this 

is also the IWAQM default option). The hourly ozone file option is implemented using year 2000-

2002 hourly ozone data obtained from four NDDH monitoring sites located within the corridor of 

primary plume transport between major electric generating stations and Theodore Roosevelt National 

Park (TRNP). These monitoring sites include Hannover, Beulah, Dunn Center and TRNP South 

Unit. As indicated in Section 3.2.5, a constant ozone background value is also entered in the 

CALPUFF control file, so that it can be substituted when the hourly value is missing. 

The NDDH prepared software to merge and format these ozone data into the input file required by 

CALPUFF (OZONE.DAT). The NDDH CALPUFF-compatible hourly ozone files for years 2000-

2002 will be provided upon request. 

3.2.3 Ammonia Background

The need for ammonia background concentrations in CALPUFF is also related to chemistry 

processing. CALPUFF accepts either a single annual value, or twelve monthly averages. To achieve 

a more realistic seasonal progression of nitrate predictions, the NDDH will be using monthly average 

ammonia background values for BART-related visibility analyses. 

Monthly average ammonia concentrations suitable for visibility modeling in North Dakota are 

provided in Table 3-4. These values were derived from data collected at the State=s only ammonia 
33 

monitor located near Beulah. Hourly monitor data from years 2001-2002 (data not available for year 

2000) were filtered to eliminate data from wind directions associated with sources causing a local 

bias, then remaining data were processed to produce the monthly averages. The Table 3-4 values 

should be generally representative of background ammonia concentrations in western North Dakota. 

Table 3-4 

 Monthly Ammonia Background Concentrations*

Month Value (ppb)

Jan 

Feb 

Mar 

Apr 

May 

Jun 

1.22 

1.23 

1.60 

1.94 

2.29 

1.63 

Jul 

Aug 

Sep 

Oct 

Nov 

Dec 

1.65 

1.69 

0.98 

1.04 

1.37 

1.06 

 * Data reflect NDDH Beulah monitoring site. 

3.2.4 Receptor Locations

Receptor locations used by NDDH for PSD Class I area modeling analyses are shown in Figure 3-4. 

Receptor spacing for all Class I areas is generally 2 kilometers (km). Given the minimum distance of 

BART-eligible sources from Class I areas in North Dakota (about 100 km), single-source 
34 

72

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

101

102 103

104

105

106

108 107

109

110

111

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

62

63

64

65

66

67

68

69

70 71

112 113

114

116 115

117

118

73

74

75

76

77

78

79

80

81

Figure 3-4: Receptor Locations - North Dakota Class I Areas

Lostwood 

Wilderness Area

TRNP North Unit

TRNP Elkhorn Ranch Unit

TRNP South Unit

0 5 10 15 20 km
35 

concentration gradients (for visibility-related species) in the vicinity of Class I areas are not expected 

to be significant, and the 2 km receptor grids should be adequate for visibility analyses. 

The BART guideline focuses on receptors at the nearest Class I area, only. Because all four Class I 

areas in North Dakota are located at relatively equal distances from BART-eligible sources, however, 

it is recommended that receptors for all Class I areas be accounted for in all BART-related visibility

analyses. Class I area receptor coordinates and elevation, as implemented by NDDH, are provided in 

Appendix A. Receptor coordinates/elevation are also found in the example CALPUFF control file 

discussed in Section 3.2.5. 

Note that receptor coordinates are provided in the same Lambert map projection as is used for source 

locations (Table 3-3). If needed, the NDDH can provide a utility (MAPCONI) to convert UTM or 

geographic coordinates to the North Dakota Lambert system. 

3.2.5 CALPUFF Control File Settings

CALPUFF control file settings recommended for BART-related visibility analyses are generally 

consistent with IWAQM guidance.10 IWAQM recommendations for CALPUFF control file settings 

fall into two categories. IWAQM-defined variables are those for which IWAQM provides a default 

value as a general recommendation for all analyses. User-defined variables are those where IWAQM 

recognizes the input value will need to be tailored for a given application, and default values are 

therefore not provided. 
36 

For BART-related visibility analyses, the NDDH has established appropriate settings for userdefined variables, and has determined the need to adjust a limited number of IWAQM-defined 

variables from recommended values, as discussed below. The CALPUFF control file user-defined 

settings, as well as the IWAQM-defined settings which have been adjusted by NDDH, are 

summarized in Table 3-5. IWAQM-defined settings adjusted by NDDH have a highlighted 

background in the table. 

Most of the user-defined settings recommended by NDDH are intuitive, involving variables related 

to defining the meteorological/computational grid, variables related to the Lambert map projection, 

and the use of default values for dry and wet deposition parameterization. The variable IRESPLIT is 

set such that puffs are eligible for splitting on any hour of the day. 

NDDH settings for IWAQM-defined variables are equivalent to IWAQM recommendations, with 

exception of settings for a limited number of variables related to puff splitting, dispersion, and 

mixing height. Variable MSPLIT is set to allow puff splitting, as this option is generally 

recommended when modeling source-receptor distances of 200 km or more. Based on performance 

testing of the CALPUFF model for PSD Class I increment modeling,3

 the NDDH uses adjusted 

settings for dispersion-related variables MDISP and MPDF, and for variables IVEG and 

ROLDMAX, as these adjustments provide better model performance. NDDH settings for MDISP 

and MPDF, reflecting the use of micro meteorological variables in calculating dispersion, are also 

more consistent with dispersion treatment in the local-scale model AERMOD. Values for 

background ozone and ammonia (variables BCKO3 and BCKNH3, respectively) are set to be 
37 

Table 3-5 

 User-Defined and Non-IWAQM Settings 

 for CALPUFF Control File

Variable Description Value 

IBTZ Base time zone 7 

NSPEC Number of chemical species 7 

NSE Number of chemical species emitted 4 

MSPLIT Allow puff splitting (1=yes) 1 

MDISP Method used to compute dispersion coefficients 2 

MPDF PDF used for dispersion under convective 

conditions (1=yes) 

1 

PMAP Map projection 

(LCC=Lambert Conformal Conic) 

LCC 

FEAST False easting at origin 0.0 

FNORTH False northing at origin 0.0 

RLAT0 Origin latitude of projection 44.0N 

RLON0 Central meridian of projection 102.0W 

XLAT1 Latitude of 1st standard parallel for projection 46.0N 

XLAT2 Latitude of 2nd standard parallel for projection 48.5N 

DATUM Datum-region for output coordinates NWS-27 

NX No. of X grid cells 213 

NY No. of Y grid cells 153 

NZ No. vertical layers 12 

DGRIDM Grid spacing (km) 3.0 

ZFACE Cell face heights (m) 0.,20.,50.,90.,140.,200

.,270.,370.,500.,1000., 

1700.,2500.,4200. 

XORIGKM Southwest grid cell X coordinate -380 

YORIGKM Southwest grid cell Y coordinate 140 
38 

Variable Description Value 

IBCOMP Southwest X-index of computational grid 20 

JBCOMP Southwest Y-index of computational grid 6 

IECOMP Northeast X-index of computational grid 213 

JECOMP Northeast Y-index of computational grid 153 

Dry Gas Dep. Chemical parameters of gaseous deposition 

species 

Model defaults 

Dry Part. Dep. Chemical parameters of particulate deposition 

species 

Model defaults 

IVEG Vegetative state in unirrigated areas (2=active 

and stressed vegetation) 

2 

Wet Dep. Wet deposition parameters Model defaults 

BCKO3 Monthly ozone background concentration (ppb) 30.0* 

BCKNH3 Monthly ammonia background concentration 

(ppb) 

Table 3-4 

XMAXZI Maximum mixing height 4000. 

IRESPLIT Hours when puff is eligible for vertical split hours 1-24 

ROLDMAX Vertical puff split allowed only when the ratio of 

last hour=s mixing height to max. mixing height 

experienced by the puff is smaller than this value 

0.33 

NSPLITH Number of puffs that result when a puff is split 

horizontally 

5 

SYSPLITH Minimum sigma-y (grid cell units) of puff before 

it may split horizontally 

1.0 

SHSPLITH Minimum puff elongation rate (SYSPLITH/hr) 

due to wind shear, before it may split horizontally

2.0 

CNSPLITH Minimum concentration (g/m3) in puff before it 

may split horizontally 

1.0E-07 

NREC Number of discrete receptors 99 

*Use same value for each month. 
39 

consistent with local monitoring data. Maximum mixing height (XMAXZI) is set to 4000 meters for 

consistency with CALMET settings. 

Settings as discussed above are incorporated in the CALPUFF control file developed by NDDH for 

BART-related visibility analyses. A sample file with NDDH settings will be provided upon request. 

3.3 POSTUTIL Input

The POSTUTIL processor provides repartitioning of total nitrate to adjust for possible double (or 

multiple) counting of ammonia in the CALPUFF chemistry. According to Escoffier-Czaja and 

Scire12

, 

 

12Escoffier-Czaja, Christelle and J. Scire, 2002. The Effects of Ammonia Limitation on 

Nitrate Aerosol Formation and Visibility Impacts in Class I Areas. Earth Tech, Inc., Extended 

abstract. 12th Joint Conference on the Applications of Air Pollution Meteorology with the Air 

and Waste Management Association, American Meteorological Society, J5.13. 

AIn CALPUFF, a continuous plume is simulated as a series of puffs, or discrete plume 

elements. The total concentration at any point in the model is the sum of the contribution of 

all nearby puffs from each source. Because CALPUFF allows the full amount of the 

specified background concentration of ammonia to be available to each puff for forming 

nitrate, the same ammonia may be used multiple times in forming nitrate, resulting in an 

overestimate of nitrate formation .... In POSTUTIL, ammonia availability is computed based 
40 

on receptor concentrations of total sulfate and total nitrate (HNO3 + NO3), not on a puff-bypuff basis.@

Input required by POSTUTIL includes an input control file and the hourly concentration output file 

from CALPUFF. Primary settings for the POSTUTIL control file include the ammonia background 

concentrations and a variable (MNITRATE) related to recomputing the nitrate partition. The 

monthly ammonia background concentrations are equivalent to the values used in CALPUFF (Table 

3-4), and the appropriate setting for MNITRATE in BART-related visibility analyses is >1'. Species 

processing information (POSTUTIL Input Group 2) for BART-related visibility analyses is specified 

as shown in Figure 3-5, with PMC representing the name used in CALPUFF for coarse particulate, 

and PMF representing the name used for fine particulate. Note that entries are not necessary for 

Subgroups 2.c and 2.d. All other POSTUTIL settings are intuitive, with some simply repeated from 

the CALPUFF control file. 

Settings as discussed above are incorporated in the POSTUTIL control file developed by NDDH for 

BART-related visibility analyses. A sample file with NDDH settings will be provided upon request. 

3.4 CALPOST Input

CALPOST produces summary 24-hour average visibility results (in delta-deciviews) which are 

compared to the BART-related thresholds (Section 2.1). Required input for CALPOST includes an 

input control file and the hourly concentration output file from either CALPUFF or POSTUTIL. 
41 

 Figure 3-5: POSTUTIL Control Input File: Input Group 2

 INPUT GROUP: 2 -- Species Processing Information 

 -------------- 

 ------------- 

 Subgroup (2a) 

 ------------- 

 The following NSPECINP species will be processed: 

 ! ASPECI = SO2 ! !END! 

 ! ASPECI = SO4 ! !END! 

 ! ASPECI = NOX ! !END! 

 ! ASPECI = HNO3 ! !END! 

 ! ASPECI = NO3 ! !END! 

 ! ASPECI = PMF ! !END! 

 ! ASPECI = PMC ! !END! 

 ------------- 

 Subgroup (2b) 

 ------------- 

 The following NSPECOUT species will be written: 

 ! ASPECO = SO2 ! !END! 

 ! ASPECO = SO4 ! !END! 

 ! ASPECO = NOX ! !END! 

 ! ASPECO = HNO3 ! !END! 

 ! ASPECO = NO3 ! !END! 

 ! ASPECO = PMF ! !END! 

 ! ASPECO = PMC ! !END! 
42 

CALPOST control file settings recommended by NDDH for BART-related visibility analyses are 

summarized in Table 3-6. The BART guideline specifies that daily (24-hour) visibility values should 

be calculated for each receptor as the change in deciviews (delta-deciview) compared against natural 

background visibility conditions. More specifically, the preamble to the final BART rule specifies 

use of natural background for the 20 percent best visibility days. The guideline also provides for the 

use of monthly average relative humidity (RH) values for BART-related visibility analyses. The 

preference for monthly average relative humidity implies the use of CALPOST visibility Method 6 

(MVISBK = 6). 

In order to develop background conditions for visibility Method 6, CALPOST requires monthly 

background concentrations of ammonium sulfate, ammonium nitrate, coarse particulate mass, 

organic carbon, soil, and elemental carbon. Annual averages reflective of natural background 

conditions for these species are found in EPA=s AGuidance for Estimating Natural Visibility 

Conditions Under the Regional Haze Program@ (2003)13. For each Class I area, this guidance 

document provides separate deciview values representative of annual average natural background, 

and natural background for the 20 percent best days. 

The EPA natural visibility guidance document does not provide speciated background concentrations 

(above) representative of the 20 percent best days, as would be needed for implementation of 

 

13EPA, 2003. Guidance for Estimating Natural Visibility Conditions Under the Regional 

Haze Program. Office of Air Quality Planning and Standards, Research Triangle Park, NC 

27711. 
43 

Table 3-5 

CALPOST Control File Settings

Variable Description Value

ASPEC Species to process VISIB 

ILAYER Enter A1" to process concentrations in CALPUFF 

hourly file 

1 

A Scaling factor 0.0 

B Scaling factor 0.0 

LBACK Add hourly background concentration F 

RHMAX Maximum relative humidity 95.0 

LBSO4 Include modeled sulfate? T 

LVNO3 Include modeled nitrate? T 

LVOC Include modeled organic carbon F 

LVPMC Include modeled coarse particles T 

LVPMF Included modeled fine particles T 

LVEC Include modeled elemental carbon F 

LVBK Include background in output tables F 

EEPMC Extinction efficiency for PM coarse 0.6 

EEPMF Extinction efficiency for PM fine 1.0 

EEPMCBK Extinction efficiency for background PM coarse 0.6 

EESO4 Extinction efficiency for ammonium sulfate 3.0 

EENO3 Extinction efficiency for ammonium nitrate 3.0 

EEOC Extinction efficiency for organic carbon 4.0 

EESOIL Extinction efficiency for soil 1.0 

EEEC Extinction efficiency for elemental carbon 10.0 

MVISBK Visibility calculation method 6 
44 

Variable Description Value

RHFAC Monthly RH adjustment factor Table 3-8 

BKSO4 Background ammonium sulfate conc. Table 3-7* 

BKNO3 Background ammonium nitrate conc. Table 3-7* 

BKPMC Background coarse particulate conc. Table 3-7* 

BKOC Background organic carbon conc. Table 3-7* 

BKSOIL Background soil conc. Table 3-7* 

BKEC Background elemental carbon Table 3-7* 

BEXTRAY Extinction due to Rayleigh scattering 10.0 

* Use same value for each month. 
45 

CALPOST Method 6 consistent with the BART rule. Upon consultation with EPA and National 

Park Service/Fish and Wildlife Service representatives

14, it was concluded that the annual 

concentrations (Table 2-1 in guidance document) should be scaled back, in equal proportion, until 

they converge to lower concentratons that produce the deciview value specified for the 20 percent 

best days (guidance document Appendix B) to provide the necessary CALPOST input. The scaling 

procedure would be conducted separately for each Class I area. 

The scaling procedure as applied by NDDH is illustrated here for Theodore Roosevelt National Park 

(TRNP). From Appendix B in the natural visibility guidance document, the deciview value for 

annual average natural conditions at TRNP is 4.75, and the deciview value for the 20 percent best 

days is 2.19. Note that the TRNP annual average deciview value reflects natural background 

components for the US west region. To obtain the speciated background concentrations 

representative of the 20 percent best days at TRNP, the deciview value (2.19) must first be converted 

to light extinction. The relationship between deciviews and light extinction is expressed, 

dv = 10 ln (bext/10) 

or 

bext = 10 exp (dv/10) 

where 

dv represents deciviews, 

 

14NDDH, 2005. Electronic message summarizing BART modeling-related conferencecall discussion with representatives of EPA, National Park Service, and Fish and Wildlife 

Service, August 31, 2005. 

bext represents total light extinction expressed in inverse megameters (Mm-1). 
46 

Using this relationship with a deciview value of 2.19, one obtains a light extinction value of 12.45 

Mm-1. Next, the natural visibility guidance document background concentrations for annual average 

(Table 2-1, west) are adjusted in order to provide the extinction value just determined (12.45 Mm-1). 

 The relationship between light extinction and background concentrations is: 

bext = (3) f (RH) [ammonium sulfate] + (3) f (RH) [ammonium nitrate] + 

 (0.6) [coarse mass] + (4) [organic carbon] + (1) [soil] + 

 (10) [elemental carbon] + bray

where 

bracketed quantities represent background concentrations in μg/m3

, 

values in parenthesis represent scattering efficiencies, 

f (RH) is the relative humidity adjustment factor (applied to hygroscopic species only), 

bray is light extinction due to Rayleigh scattering (10 Mm-1 used for all Class I areas). 

Substituting the annual average natural background values and TRNP f (RH) from the natural 

visibility guidance document, and including the coefficient for scaling, one obtains 

12.45 = (3) (2.56) [0.12] X + (3) (2.56) [0.1] X + (0.6) [3.0] X + (4) [0.47] X + 

 (1) [0.5] X + (10) [0.02] X + 10 

where 

X represents scaling factor to convert annual average natural background concentrations to 

values representative of 20 percent best days. 

Solving for X provides a value of 0.403. This scaling factor was applied to the annual average 

natural background components in the natural visibility guidance document (Table 2-1, west region) 
47 

to obtain background components for the 20 percent best days for TRNP. The scaling procedure was 

repeated for Lostwood Wilderness Area. 

Results of the scaling procedure are shown in Table 3-7, which includes speciated natural 

background concentrations representative of annual average visibility, 20 percent best days for 

Theodore Roosevelt National Park, and 20 percent best days for Lostwood Wilderness Area. Note 

that west region natural conditions are assumed for North Dakota Class I areas. The Table 3-7 

Table 3-7 

 Natural Levels of Aerosol Components 

 (μg/m3

)

Component

Annual Average 

West Region *

20% Best Days 

Theodore 

Roosevelt NP

20% Best Days 

Lostwood 

NWA

Ammonium sulfate 0.12 0.048 0.049 

Ammonium nitrate 0.10 0.040 0.041 

Organic carbon mass 0.47 0.189 0.190 

Elemental carbon 0.02 0.008 0.008 

Soil 0.50 0.202 0.203 

Coarse mass 3.00 1.209 1.215 

Natural deciview** 2.19 2.21 

*From AGuidance for Estimating Natural Visibility Conditions Under the Regional Haze Program@

(EPA, 2003), Table 2-1. 

**From AGuidance for Estimating Natural Visibility Conditions Under the Regional Haze Program@

(EPA, 2003), Appendix B. 
48 

values for 20 percent best days should be used for BART-related analyses. The same value is used 

for each month in the CALPOST control file. 

Monthly RH adjustment factors (RHFAC input in CALPOST) for Theodore Roosevelt National Park 

and Lostwood Wilderness Area BART-related analyses are provided in Table 3-8. These values are 

also from the EPA guidance document for natural visibility conditions. One other setting needed for 

CALPOST development of natural background is extinction due to Rayleigh scattering 

(BEXTRAY), which should be left at the default value of 10.0. 

Table 3-8 

 Monthly RH Adjustment Factors*

Month

Theodore Roosevelt 

NP

Lostwood 

NWA

Jan 

Feb 

Mar 

Apr 

May 

Jun 

2.9 

2.8 

2.8 

2.3 

2.3 

2.5 

3.0 

2.9 

2.9 

2.3 

2.3 

2.6 

Jul 

Aug 

Sep 

Oct 

Nov 

Dec 

2.4 

2.2 

2.2 

2.3 

3.0 

3.0 

2.7 

2.4 

2.3 

2.4 

3.2 

3.2 

* From AGuidance for Estimating Natural Visibility Conditions Under the Regional Haze 

Program@ (EPA, 2003) 
49 

The remainder of CALPOST control file settings are intuitive, and mirror settings in the CALPUFF 

control file. Settings as discussed above are incorporated in the CALPOST control file developed by 

the NDDH for BART-related visibility analyses. A sample file with NDDH settings will be 

provided upon request. 
50 

4 Model Execution and Output Interpretation

For BART-related single-source visibility analyses in North Dakota, the CALPUFF modeling system 

should be executed with input data and settings as described in Section 3. Delta-deciview results 

necessary for comparison with visibility thresholds are obtained from the A24HR VISIBILITY 

(deciview)@ table in the CALPOST output file. 

The BART guideline states that the 98th percentile of 24-hour CALPUFF modeling results should be 

compared with the contribution threshold established by the State for purposes of determining BART 

applicability. Upon clarification from EPA and FLM=s

14, the context of the 98th percentile 24-hour 

delta-deciview prediction is with respect to days of the year, and is not receptor specific. A 24-hour 

prediction greater than 0.5 delta-deciview at any receptor in a Class I area would constitute a day of

exceedance, and up to 7 days of exceedance would be allowed per year per Class I area (i.e., the 98th 

percentile is approximated by the eighth-highest daily prediction). 

4.1 BART Screening

To complete the BART screening analysis for North Dakota sources, CALPUFF (and optionally 

POSTUTIL) is executed for each year of meteorological data processed with CALMET (2000-2002). 

 And for each year of CALPUFF (POSTUTIL) hourly output, CALPOST is executed separately for 

receptor groups representing each Class I area. Delta-deciview modeling results applicable to BART 

screening are found in the summary section at the bottom of the A24HR VISIBILITY (deciview)@
51 

table in the CALPOST output file. If the number of days with delta-deciview prediction greater than 

0.5 is more than 7, for any year of meteorological data for any Class I area, the source is concluded to 

be BART-applicable. Note that the three units of Theodore Roosevelt National Park are treated as 

separate Class I areas for BART-related visibility analyses. 

4.2 Degree of Visibility Improvement

For analyses to determine the degree of visibility improvement due to BART controls, the modeling 

system is executed as described above for BART screening. Model execution and results are needed 

for both pre-BART control and post-BART control scenarios, to allow comparison of CALPOST 

delta-deciview predictions for both scenarios. The context of this comparison is not specifically 

defined, leaving it to the State to determine the appropriate metric. The BART guideline states: 

AAssess the visibility improvement based on the modeled change in visibility impacts for the 

pre-control and post-control emission scenarios. You have flexibility to assess visibility 

improvement due to BART controls by one or more methods. You may consider the 

frequency, magnitude, and duration components of impairment.@

Consistent with the goals stated in the BART guideline, the NDDH recommends the following 

specific approaches for evaluating the degree of visibility improvement from BART controls: 
52 

$ Compare the 98th percentile delta-deciview prediction from pre-control and post-control 

modeling scenarios. 

$ Compare the number of days of exceedance of the 0.5 delta-deciview threshold for precontrol and post-control scenarios (to address Aduration@, the maximum number of 

consecutive days of exceedance should also be reported for both scenarios). 

$ For consistency with goals of the Regional Haze program (and WRAP regional-scale 

modeling), compare the 90th percentile delta-deciview prediction from pre-control and postcontrol modeling scenarios (i.e., average of the 20 percent worst days). 

Again, these comparisons would be made for each Class I area and for each year of meteorological 

data. 

While the above comparisons are proposed in the context of total deciview improvement attributable 

to BART controls for all species combined, it may be desirable to also test the relative effectiveness

of controls for individual species. When evaluating visibility improvement for individual species, 

the following should be considered. 

$ To maintain reasonable balance in the CALPUFF chemistry, all four species (SO2, NOX, PM 

coarse, PM fine) should be included in the model input files for pre-control and post-control 

scenarios. The post-control input file should reflect the BART-control emission rate for the 

tested species, while the emission rate for other species remains at pre-control levels. Postcontrol input file stack parameters should reflect post-control values for the tested species. 
53 

$ Alternatively, to refine the accuracy of single-species testing, the reactive species SO2 and 

NOX may be grouped separately from the non-reactive species PM coarse and PM fine 

(primary only) in the post-control input file. That is, the BART-applicable source unit would 

be configured as two virtual co-located sources in the post-control input file. One virtual 

source would include emission rates for reactive species SO2 and NOX, and the other virtual 

source would include emission rates for non-reactive species PM coarse and PM fine. If the 

species being tested is reactive, then post-control stack parameters (for the tested species) 

would be entered for the reactive virtual sources, and pre-control stack parameters would be 

entered for the non-reactive virtual source. If the species being tested is non-reactive, then 

post-control stack paramters would be entered for the non-reactive virtual source, and precontrol stack parameters would be assigned for the reactive virtual source. 

$ If information on particle size distribution is not available for the post-control scenario for 

primary particulate, the ratio of PM fine to PM coarse for the post-control scenario should be 

considered equivalent to the PM ratio for the pre-control scenario (Table 3-2). 

Whether testing degree of visibility improvement for ensemble species or for one species at a time, 

testing should be conducted separately for each BART-applicable unit within a facility. When 

testing for individual species is complete, the overall degree of visibility improvement should be 

evaluated for each unit. When testing for individual units is complete, the degree of visibility 

improvement should be evaluated for the entire facility. 
54 

It is not the intent of the NDDH to develop specific thresholds for the comparisons of modeled 

visibility impact recommended above. Rather, the degree of visibility improvement represented by 

these modeled comparisons (and possibly others) will be evaluated in a qualitative manner, in 

concert with the review of other prescribed analyses of BART control options (i.e., technology 

available, cost of compliance, etc.), to establish an appropriate BART control. 

4.3 CALBART Utility

To expedite recommended comparisons for determining the degree of visibility improvement, the 

NDDH has developed the CALBART utility software program. CALBART processes the hourly 

output file from either CALPUFF or POSTUTIL to provide the 24-hr delta-deciview metrics 

recommended for assessing the degree of visibility improvement due to BART controls. CALBART 

replaces CALPOST in the sequence of visibility model processing. CALBART produces deltadeciview results equivalent to CALPOST (i.e., when CALPOST input is set as prescribed in Section 

3.4), but in a summarized format which includes results for all Class I areas in a single execution. 

CALBART requires an input control file which must be named >CALBART.INP'. The file includes 

three lines: 

 

Line 1 - Title (up to 80 characters) 

Line 2 - File name and path for CALPUFF (POSTUTIL) output file (up to 40 characters) 

Line 3 - Beginning year, julian day, and hour for the CALBART run (free format, time must be 
55 

 equal to or later than that specified in the CALPUFF or POSTUTIL input file; also, the 

 hour should always be specified as '0' to ensure that calendar days are simulated) 

An example of CALBART output (file CALBART.LST) is provided in Figure 4-1. The CALBART 

software will be provided upon request. 

 
56 

Figure 4-1: CAL BART Output Example 

CALBART - Summa ry o f Vi sibi l i t y Resul t s f o r 2 4 - h r De l ta- Deci vie w 

Ge neric Sour c e f o r Yea r 2 000 Met e o ro l og ica l Da ta 

Ti tle l i nes from CALPUFF (POSTUTI L) out p ut f i l e : 

Ge neric Sour c e - BART Prot o c o l - Pos t ut i l 1. 4 

Year 2 000 Ca l met Met. Da ta - RUC2d Mesos cal e Da t a - Mont h l y NH3 

BART Protocol Re c epto r s (99) 

SEQ ND % o f Model e d Extin

DELTA- DV DV(Tot a l ) DV(BKG) YEAR DAY RECEP RECEP F (RH) %_ S04 % N0 3 

TRNP SOUTH UNI T 

Lar g e st Del ta- DV 

98th %til e De l ta- DV 90th %til e De l ta- DV 

6 . 416 

1 . 596 

0. 541 

8.650 

3. 872 

2.647 

2 . 234 2 . 276 2 . 1 06 

Number o f days wi th De l t a - De civi e w > 0. 50: 39 

Number o f days wi th De l t a - De civi e w > 1.00: 22 

2000 7 4 2000 316 2000 239 

Max number o f c onsecutive day s wi th Oelta- De c i vie w > 0 .50 : 3 

TRNP NORTH UNI T 

Lar g e st Del ta- DV 

98th %til e De l ta- DV 90th %til e De l ta- DV 

5 .258 

2 .269 

0. 446 

7.492 

4 .502 

2.552 

2 . 234 2 . 234 2 . 1 06 

Number o f days wi th De l t a - De civi e w > 0. 50: 32 

Number o f days wi th De l t a - De civi e w > 1.00: 1 7 

2000 36 2000 54 2000 24 8 

Max number o f c onsecut ive day s wi th Oelta- De c i vie w > 0 .50 : 2 

TRNP ELKHORN RANCH 

Lar g e st Del ta- DV 

98th %til e De l ta- DV 90th %til e De l ta- DV 

6 . 34 7 

1. 414 

0. 400 

8.581 

3. 647 

2.52 7 

2 . 234 

2 . 234 2 . 127 

Number o f days wi th De l t a - De civi e w > 0. 50: 26 Nu tube.t. u [ w.i L.h Del l a - Dt:<..:iv .iew > 1.00: 1 1 

2000 2000 2000 

7 4 

66 

9 8 

Ma x number o f c onsecut ive da y s wi th Oelta- De c i vie w > 0 .50 : 2 

LOSTWOOD NWA 

Lar g e st Del ta- DV 

98th %til e De l ta- DV 

90th %til e De l ta- DV 

6 .661 

2 . 12 1 

0.792 

8.937 

4 .289 

2.959 

2 . 275 2 . 1 67 2 . 1 67 

Number o f days wi th De l t a - De civi e w > 0. 50: 52 Number o f days wi th De l t a - De civi e w > 1 .00: 3 1 

2000 4 7 2000 2 1 6 2000 2 1 5 

l-ta x number o f c onsecut ive da y s wi th Del ta- De c i vie w > 0 . SO: 5 

48 4 5 

52 

82 82 

71 

90 90 90 97 

9 5 9 1 

1 02 

45 

1 06 

71 71 60 72 72 72 

79 77 73 

2. 80 

3.00 

2.20 2. 80 2. 80 2.20 2. 80 2. 80 2. 30 2.90 2. 40 2. 40 

69.80 

56 .96 

8 4 . 37 

52 . 58 

71.89 

32 .00 

7 1 . 19 

64 . 45 

62.60 

92.31 

69. 11 

7 3 . 19 

30. 1 2 

42 .89 

1 5 . 4 5 

47. 1 4 

27 .91 

66. 31 

28.74 

35 . 4 2 37.25 

7. 54 

30.68 

26.21 
Appendix A 

NDDH PSD Class I 

Area Receptors
 

NON-GRI DDED (DISCRETE) RECEPTOR DATA 

Receptor 

No. 

X UTM 

Coordi nate 

(km) 

TRNP South Uni t Receptor s : 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

1 4 

1 5 

1 6 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

28 

29 

30 

31 

32 

33 

3 4 

35 

36 

37 

38 

39 

40 

41 

42 

43 

44 

45 

46 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

- 1 20.0, 

- 120 . 0, 

- 118.0 , 

- 118 .0, 

- 118. 0, 

- 118.0, 

- 118.0, 

- 116.0, 

- 116.0, 

- 116 .0, 

- 116.0, 

- 116.0 , 

- 114. 0, 

- 114.0, 

- 114 .0 , 

- 114. 0, 

- 114. 0, 

- 112 . 0, 

- 112.0, 

- 112. 0, 

- 112. 0, 

- 112.0, 

- 110.0, 

- 110 . 0, 

- 110.0 , 

- 110.0, 

- 110.0, 

- 1 08 . 0, 

- 1 08.0, 

- 1 08.0, 

- 108.0, 

- 108 . 0, 

- 106.0, 

- 1 06 . 0 , 

- 106.0, 

- 106.0, 

- 106 . 0, 

- 1 04.0, 

- 1 04.0, 

- 1 0 4 . 0 , 

- 104 . 0, 

- 102 . 0, 

- 1 02.0, 

- 102.0, 

- 1 00.0, 

- 1 00.0 , 

Y UTM 

Coordinat e 

{kml 

334.0, 

336.0, 

328.0, 

330 . 0, 

332.0, 

334.0, 

336.0 , 

328.0, 

330.0, 

332.0, 

334.0, 

336. 0' 

326.0, 

328.0, 

330 . 0' 

332 . 0, 

334.0, 

326.0, 

328.0, 

330. 0, 

332.0, 

334.0, 

326.0, 

328.0, 

330.0, 

332.0, 

33 4. 0, 

324.0, 

326.0, 

328.0, 

330.0, 

332.0 , 

324.0, 

326.0, 

328.0, 

330.0, 

332.0, 

324.0, 

326.0, 

328.0, 

330.0, 

324.0, 

326.0, 

328.0, 

324.0, 

326 . 0' 

Ground 

El evation 

(m) 

801.5, 

743 . 4, 

737 . 9, 

793. 8' 

757 . 7, 

817 . 3, 

782 . 7, 

719.7, 

715.9, 

745.1, 

764 . 1, 

686.7 , 

767.7, 

735 . 0, 

683.9 , 

7 46 . 0, 

685 . 3 , 

749.2, 

728 . 1, 

725.0' 

7 07 . 9 , 

736 . 5, 

794.3' 

731 . 1, 

758.7, 

742.3, 

767 . 4, 

818 . 4, 

7 40.2, 

728 .2, 

760.7, 

755 . 4, 

790.0, 

762 . 8, 

733 . 4, 

825.7, 

772 . 3, 

7 56 ' 

761 . 3, 

758 . 2, 

771. 0, 

796 . 2, 

774.3, 

81 9.0 , 

839 . 3, 

836 . 4, 

Height 

Above Ground 

( m} 

0.000! 

0 . 000! 

0 . 000! 

0.000 ! 

0.000! 

0 . 000! 

0 . 000! 

0.000! 

0.000! 

0.000 ! 

0 . 000! 

0 . 000! 

0 . 000 ! 

0.000! 

0.000! 

0 . 000! 

0 . 000! 

0.000 ! 

0 . 000! 

0 . 000! 

0.000! 

0 . 000! 

0.000 ! 

0 . 000! 

0 . 000! 

0.000! 

0.000! 

0.000 ! 

0 . 000! 

0 . 000! 

0.000 ! 

0 . 000! 

0.000! 

0 . 000! 

0 . 000! 

0.000 ! 

0 . 000! 

0.000 ! 

0.000! 

0.000! 

0 . 000 ! 

0 . 000! 

0 . 000! 

0.000 ! 

0.000! 

0 . 000 ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

END ! 

END ! 

END ! 

END ! 

END ! 

END ! 

END ! 

END ! 

.END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 

!END ! 
 

101 X - 121.608, 335.052, 777 . 3, 0 . 000! !END ! 

102 X - 118.992 , 337.441, 771 . 4, 0 . 000! END ! 

103 X - 116.945, 337.384, 734.8, 0.000! END ! 

1 04 X - 112.965, 335.621, 728.7, 0.000 ! END ! 

105 X - 107.051, 333.744, 746 . 3, 0.000! END ! 

106 X - 102.388, 329 .593, 770 . 0 , 0 . 000! END ! 

107 X - 1 00.852, 322.428, 853. 9, 0.000 ! END ! 

1 08 X - 1 02.95 6, 322.371, 850 . 2, 0.000! . END ! 

109 X - 110.91 8, 324.760, 750 . 5, 0.000! !END ! 

110 X - 115 . 581, 326.352, 752.8, 0 . 000! !END ! 

111 X - 119.447, 332.550, 765.9, 0 . 000 ! !END ! 

TRNP North Unit Recepto r s: 

47 X - 108.0, 396.0, 608.7, 0.000 ! !END ! 

48 X - 108.0, 3 98. 0' 604 . 3, 0 . 000! !END ! 

49 X - 108.0, 400. 0' 614.6, 0 . 000! !END ! 

so X - 1 08.0, 402.0, 684. 0 , 0.000! !END ! 

51 X - 106.0, 396.0, 621 . 5, 0.000! !END ! 

52 X - 106 . 0, 3 98. 0' 774. 0, 0.000 ! !END ! 

53 X - 1 06.0, 400.0, 598 . 2, 0 . 000! !END ! 

54 X - 1 06.0, 402.0, 736.4, 0 . 000! !END ! 

55 X - 106.0, 4 0 4. 0, 690.9, 0.000 ! !END ! 

56 X - 104 . 0, 396.0, 648 . 7' 0 . 000! !END ! 

57 X - 104. 0' 398. 0, 768.0, 0.000! !END ! 

58 X - 1 04.0 , 400.0, 615 . 3, 0 . 000! !END ! 

59 X - 1 0 4 .0, 402.0, 622 . 0 , 0 . 000! !END ! 

60 X - 104.0, 404.0, 763.1, 0.000 ! !END ! 

61 X - 102.0, 400.0, 671 . 9, 0 . 000! !END ! 

62 X - 102.0, 4 02. 0' 719.8, 0 . 000! !END ! 

63 X - 1 02.0, 404.0, 629.9, 0.000! !END ! 

6 4 X - 1 0 0 . 0 , 4 00.0, 5 94 . 8, 0.000! !END ! 

6 5 X - 100 . 0, 402.0, 624.6, 0 . 000 ! !END ! 

66 X - 100.0, 404.0, 651 . 3, 0 . 000! !END ! 

67 X - 98.0, 400.0, 593.7, 0.000 ! !END ! 

68 X - 98.0, 402.0, 725 . 3, 0.000! !END ! 

69 X - 96 . 0, 400.0, 591 . 2, 0 . 000! !END ! 

70 X - 96.0 , 4 02. 0' 692.3, 0 . 000! !END ! 

71 X - 9 4 .0, 402.0, 677.4, 0.000 ! 1END ! 

112 X - 107.858 , 404.020, 771.2, 0.000! END ! 

113 X - 98.243, 403.809, 687 . 9, 0.000! END ! 

114 X - 94.447, 400.520, 594 . 6, 0 . 000! END ! 

115 X - 98.960, 398.200, 712 . 1, 0 . 000! END ! 

116 X - 1 00.942 , 398.243, 674 . 5, 0.000! END ! 

117 X - 109.587 , 399.044, 677 . 7' 0.000! . END ! 

118 X - 109 . 587, 401.026, 749.2, 0 . 000! !END ! 

TRNP Elkhorn Ranch Receptor: 

72 ! X = - 122.581, 361. 580, 64 7 . 7' 0 . 000 ! !END ! 

Lost wood NWA Receptors: 

73 X - 36.0, 516.0, 724 . 9, 0 . 000 ! !END ! 

74 X - 36 . 0 , 518.0, 724 . 4, 0 . 000 ! !END ! 

75 X - 36 . 0, 520.0, 740 . 4, 0.000 ! !END! 

76 X - 34. 0 , 516. 0' 725 .0, 0 . 000 ! !END !