# 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 5 1 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 it s July 1999 regional haze rule 1 

### . These

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

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

reduce visibility in PSD Class I areas. These poll utants include fine particulate matter (PM 2.5 

### ), and

compounds which contribute to PM 2.5 

### formation, such as nitrogen oxides, sulfur dioxide , certain

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

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

of controls the facilities must use.

1 

### Federal Register, 2005. EPA Regional Haze Regulati ons 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

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

this process, visibility computer modeling will ass ist in the identification of sources A subject to

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

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

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

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

sources A subject to BART @ (BART screening), and for determining the degree o f visibility

improvement related to the selection of BART contro l.

### 2

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

of visibility modeling are anticipated. In chronol ogical order, these are:

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

BART-applicable),

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

proposed BART control for each BART-applicable sour ce,
3) cumulative modeling to determine the combined ef fect of proposed BART controls for

BART-applicable sources in North Dakota, and

4) regional-scale modeling to determine if the comb ined 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 BAR T-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

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

BART controls.

### 3

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

sources are subject to BART. It is expected that B ART-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 ND DH 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 th e protocol outlined here. Because of this

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

individual protocols for their BART-related modelin g.

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

analysis to determine the combined effect of propos ed 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. T he final regional-scale modeling analysis to

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

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

WRAP is developing the protocol and establishing in put 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 pre viously 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 result s
(Section 4). Locations of BART-eligible sources wi th 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 Tesoro5123456km0 100 200 300 400Key1 Leland Olds Station/Stanton Station2 Milton R Young Station3 Heskett Station4 Coal Creek Station5 ACS Drayton6 ACS Drayton (modeled)BART-Eligible SourceLostwoodWilderness AreaTRNP South UnitTRNP North UnitTRNP Elkhorn Ranch UnitPSD Class I AreaBismarckNDDHModelingDomainFigure 1-1: BART-Eligible Sources and PSD Class IAreas

### 6

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

guideline states,

A 

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

emission limitations for fossil-fuel fired power pl ants 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 dis cretion to require use of the BART guideline for

all BART-eligible sources in North Dakota.

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

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

has implemented guidance outlined in the June 15, 2 005 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 cons istent 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.

3 

### NDDH, 2005. A Proposed Alternative Air Quality Mod eling Protocol to Examine the Status of Attainment of PSD Class I Increment. Nor th Dakota Department of Health, Bismarck, ND 58506.

### 7

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

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

Section 3 provides detailed information regarding m odeling system components and input data

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

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

NDDH contacts for questions on BART-related modelin g 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 BAR T-eligible sources (BART screening),

modeling methodology involves execution of an appro priate visibility model, then comparison of

model predictions with the BART applicability thres hold. 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 excep tion 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 contain ed within a subject facility must be modeled

together before comparing results with the BART app licability 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 b y unit.



# 2.1 BART Applicability Threshold

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

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

NDDH will follow recommendations in the June 15 BAR T guideline which states,

### 9

A 

### A single source that is responsible for a 1.0 deciv iew change or more should be considered

to A 

### cause @ 

### visibility impairment; a source that causes less t han a 1.0 deciview change may

still A 

### contribute @



### to visibility impairment and thus be subject to BA RT .... As a general

matter, any threshold that you use for determining whether a source A 

### contributes @



### to

visibility impairment should not be higher than 0.5 deciviews. @



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

A cause @ visibility impairment versus those sources which A contribute @ to visibility impairment in

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

which BART-eligible sources must apply BART. The N DDH 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 visibilit y improvement analyses, the BART guideline

specifies that only primary emissions need to be co nsidered. These primary emissions include SO 2 

### ,

NO x 

### , and direct particulate matter (PM) emissions spec ified as either coarse (PM 10 

### minus PM 2.5 

### ) or

fine (PM 2.5 

### ). If this distinction in size of PM emissions can not be made, it would be appropriate to

consider all PM 10 

### emissions as PM 2.5 

### .

The BART guideline also discusses VOC or ammonia em issions 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-relate d visibility modeling are discussed in detail in

Section 3.



# 2.3 Visibility Modeling System

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

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

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

CALPUFF 4 

### . As specified in the BART guideline,

A 

### CALPUFF is the best regulatory modeling application currently available for predicting a

single source =



### s contribution to visibility impairment and is curr ently the only EPA-approved

model for use in estimating single source pollutantconcentrations 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 SO 2 

### and NO x 

### . @

4 

### CFR, 2003. EPA Guideline on Air Quality Models. 4 0 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 C ALMET meteorological model 5 

### , the

CALPUFF dispersion model 6 

### , and the CALPOST post processing program. The CAL POST

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

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

method to address double-counting of available ammo nia for NO x 

### to NO 3 

### conversion chemistry in

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

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

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

accommodate pre-processing of meteorological and ge ophysical data for CALMET.

Appropriate versions of CALPUFF software for BART-r elated 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 enhancem ents, and appear to be consistent with the

versions being recommended by most Regional Plannin g 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 (Versio n 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<>

# ic~1l**~** b 

### 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 acc ommodate

large file sizes, however, it is recommended that t he 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, utilizi ng POSTUTIL, is recommended by NDDH. The

NDDH will be applying the ammonia limiting method i n BART-applicability analyses.

### 14 

# 3 Model Input Data/Settings

The CALPUFF modeling system includes the CALMET met eorological model, the CALPUFF

dispersion model, the CALPOST postprocessing progra m, 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 additiona l 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 domai n 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 positione d to encompass all North Dakota PSD Class I areas

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

domain is relatively large, the Lambert Conformal m ap 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 e astward to incorporate the Drayton plant, the

plant is located about 400 kilometers from the near est Class I area (Lostwood Wilderness Area), and15kmFigure 3-1: Gridded Modeling Domain0 100 200 300 400

### 16

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

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

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

(represented by the A ACS Drayton (modeled) @ source in Figure 1-1). This adjustment will provi de a

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

ensure conservative results.



# 3.1 CALMET Input

Input requirements for the CALMET model include var ious meteorological and geophysical data

sets, and a control input file with appropriate set tings. Required meteorological data include surfac e,
upper-air, and precipitation observations, and meso scale 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 observat ions), the EPA modeling guideline 4 

### recommends

A blending @ observations with the mesoscale model fields. The refore, the NDDH will include

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

observations and mesoscale model fields for three y ears (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 analy ses in North Dakota. Upon request, NDDH

will provide these meteorological and geophysical d ata sets.

### 17



## 3.1.1 Meteorological Data

3.1.1.1 Mesoscale Model Data

Mesoscale model wind fields used with CALMET are ba sed 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 wer e developed by a contractor 7 

### . 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 CAL MET. The domain of these hourly wind

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



## 3.1.1.2 Surface Observations

7 

### WindLogics, 2004. RUC Analysis-Based CALMET Meteor ological Data for the State of North Dakota. WindLogics, Inc., St. Paul, MN 55 108. 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 withi n or near the NDDH CALMET/CALPUFF

domain, although the specific number of stations va ried 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 Can ada. Location of these stations is shown in

Figure 3-2.

To compensate for well-documented deficiencies in A SOS 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 cove r) 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 co nvert to the format required by CALMET

(SURF.DAT). Standard methods were applied to provi de 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.

8 

### Atkinson, Dennis and Russell F. Lee, 1992. Procedu res for Substituting Values for Missing NWS Meteorological Data for Use in Regulato ry Air Quality Models.

9 

### EPA, 1987. On-Site Meteorological Program Guidance for Regulatory Modeling Application. Office of Air Quality Planning and St andards, Research Triangle Park, NC 27711.19BISFARDVLGFKRDRDIKJMSMIBMOTISNN60GGWGDVMLSBILSDYOLFJDNHONRAPABRPIRMBG2WXINLMSPSHRGCCYBRYENYQRYWGFigure 3-2: Surface / Upper-air Meteorological StationsSurface StationSurface + Upper-air Station

### 20



## 3.1.1.3 Upper-Air Observations

Upper-air observations for the three-year period 20 00-2002 were obtained from NOAA = s Forecast

Systems Laboratory (FSL) in Boulder, Colorado. Upp er-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 A NCDC CD-ROM @ . Data were obtained for six upper-air stations (N WS) located

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

Figure 3-2.

Processing of the upper-air data for CALMET input i nvolved 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 fil es, 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 c hecks, 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 generall y 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 recor ding stations located within or near the

NDDH CALMET/CALPUFF modeling domain, although the s pecific 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 substit utions were made for missing data,

because CALMET substitutes internally from the near est 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 NDD H derived terrain elevations from United States

Geological Survey (USGS) GTOPO30 data sets for Nort h 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 terr ain and land-use data were processed into the singl e
geophysical file (GEO.DAT) required by CALMET. NDD H assumed Earth Tech default values22Figure 3-3: Precipitation Stations..............................I"'............................................................I............I...I........................,...........I...I.......................................1...-...-..............................

### 23

relating surface roughness length, albedo, Bowen ra tio, soil heat flux, and leaf area index to land-us e

type.



## 3.1.3 CALMET Control File Settings

CALMET control file settings recommended for proces sing years 2000 through 2002 data for

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

Workgroup on Air Quality Modeling (IWAQM) 10 

### . IWAQM recommendations for CALMET control

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

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

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

application, and default values are therefore not p rovided.

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

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

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

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

background in the Table.

10 

### EPA, 1998. IWAQM Phase 2 Summary Report and Recomm endations 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 fiel d are equally weighted (km) 10

R2 Distance from an upper-air observation station at

which the wind observation and the first guess fiel d 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, re lated to parameterization of the meteorological gri d

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

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

observations, and terrain features in development o f the final wind field. Settings for these variabl es
are based on the NDDH alternative protocol for PSD Class I increment analyses. 3



### NDDH settings for IWAQM-defined variables are consi stent with IWAQM recommendations, with

limited exceptions as established in the alternativ e 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 bee n changed from 0 to 14, which reflects use of

MM5 format data (in this case RUC data) as the init ial 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 ave raging of mixing heights, MNMDAV and

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

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

maximum mixing height settings (ZIMAX/ZIMAXW) are i ncreased 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.

11 

### Holzworth, 1972. Mixing Heights, Wind Speeds, and Potential for Urban Air Pollution Throughout the Contiguous United States. EPA Publi cation 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 wi th 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 ozo ne
data before the model can be executed. A backgroun d ammonia value is also required.



## 3.2.1 Emissions and Stack Data

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

modeling primary pollutants SO 2 

### , NO x 

### , and PM 10 

### (coarse and fine) using maximum emission rates.

The guideline states,

A 

### The emissions estimates used in the models are inte nded to reflect steady-state operating

conditions during periods of high capacity utilizat ion. 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 eff ects than would be typical of most

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

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

of start-up, shutdown, or malfunction. @

### 28

Since the meteorological period modeled will be 200 0 through 2002, the NDDH requested

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

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

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

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

modeling recently completed by NDDH. 3 

### Entries for the dynamic stack parameters, exit ve locity and

exit temperature, reflect an average for the 2000-2 002 period.

Emission rates provided by BART-eligible source com panies, 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, P M 10 

### emission rates were calculated based on data

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

PM 10 

### emissions are PM 2.5 

### would be too conservative. Therefore, PM 2.5 

### 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 distribut ion of PM emissions at individual sources.

BART-applicable source companies are free to use th e 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. Buildin g downwash effects will not be considered in

the CALPUFF visibility analyses.

### 29

To determine the degree of visibility improvement f rom BART controls, the BART guideline

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

analysis from Tables 3-2 and 3-3. Post-control emi ssion 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 emiss ion rates, using the efficiency of the proposed

control equipment and/or process changes.

If CALPUFF multi-source analyses are eventually con ducted 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 emi ssion characterization may be more realistic for

determination of cumulative visibility impact.



## 3.2.2 Ozone Background

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

single constant background ozone value, or an input file of hourly ozone values commensurate with30Table 3-2BART Eligible SourcesScreening AnalysisEmission RatesCompanyUnitPM10(lb/hr)PM2.5(Fine)(lb/hr)PMCoarse*(lb/hr)SO2(lb/hr)NOx(lb/hr)Basin Electric Power Coop.Leland Olds 1155.216.5138.75,970.0813.0Basin Electric Power Coop.Leland Olds 2253.226.9226.312,205.03,959.0Minnkota Power Coop.M.R. Young 142.25.536.77,231.22,855.2Minnkota Power Coop.M.R. Young 2206.828.1178.76,879.05,364.2Montana Dakota UtilitiesHeskett 225.821.64.21,475.5302.8Great River EnergyStanton 131.81.929.93,418.0669.0Great River EnergyCoal Creek 1249.2101.9147.35,733.51,772.3Great River EnergyCoal Creek 2216.188.4127.74,969.31,822.4American Crystal SugarDrayton BoilerDrayton Lime Kiln**25.71.04.90.220.80.8197.00.2150.02.5TesoroMandan Ref CO Furn14.414.40.055.846.6*PM coarse = PM10- PM2.5**Entries reflect total for lime kiln emission points.31Table 3-3BART Eligible SourcesScreening AnalysisStack ParametersUnitXCoord.*(km)YCoord.*(km)StackHeight(m)BaseElevation(m)StackDiam.(m)ExitVelocity(m/s)ExitTemp.(K)Leland Olds 151.180365.146106.7518.35.319.7450.0Leland Olds 251.282365.080152.4518.36.725.0448.6M.R. Young 159.473341.39291.4597.45.818.5449.1M.R. Young 259.455341.308167.6597.47.619.2361.8Heskett 284.846319.40391.4514.83.717.4419.7Stanton 150.361365.70577.7518.34.619.9411.1Coal Creek 163.387376.062201.0602.06.725.9358.5Coal Creek 263.492376.068201.0602.06.724.9354.5Drayton Boiler**254.569521.64436.6245.12.421.7493.2Drayton L. Kiln**254.554521.65735.1245.10.321.0376.5Mandan Ref CO F.85.094317.51860.5518.52.4412.6333.0*Coordinates reflect North Dakota Lambert Projection.**The coordinates for Drayton boiler and lime kilnreflect the location of the repositioned virtual sources used for modeling. Stackparameters for the lime kiln reflect a composite ofall lime kiln emission points.

### 32

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

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

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

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

primary plume transport between major electric gene rating stations and Theodore Roosevelt National

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

Unit. As indicated in Section 3.2.5, a constant oz one 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 thes e ozone data into the input file required by

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

2002 will be provided upon request.



## 3.2.3 Ammonia Background

The need for ammonia background concentrations in C ALPUFF 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 pr edictions, the NDDH will be using monthly average

ammonia background values for BART-related visibili ty analyses.

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

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

### 33

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

2000) were filtered to eliminate data from wind dir ections 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 am monia 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 monitor ing site.



## 3.2.4 Receptor Locations

Receptor locations used by NDDH for PSD Class I are a 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

107 108 109 110 111 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

115 116 117 118 73

74 75

76 77 78

79 80 81 

## Figure 3-4: Receptor Locations - North Dakota Clas s 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 spe cies) in the vicinity of Class I areas are not expe cted

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

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

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

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

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

Appendix A. Receptor coordinates/elevation are als o 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 pro vide 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 se ttings

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 a djust a limited number of IWAQM-defined

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

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

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

background in the table.

Most of the user-defined settings recommended by ND DH 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 depos ition parameterization. The variable IRESPLIT is

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

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

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

mixing height. Variable MSPLIT is set to allow puf f 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 increm ent 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 meteorologica l variables in calculating dispersion, are also

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

background ozone and ammonia (variables BCKO3 and B CKNH3, 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/m 3 

### ) 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 mix ing 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 wi th NDDH settings will be provided upon request.



# 3.3 POSTUTIL Input

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

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

Scire 12



### ,

12 

### Escoffier-Czaja, Christelle and J. Scire, 2002. Th e 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 Application s of Air Pollution Meteorology with the Air and Waste Management Association, American Meteorol ogical Society, J5.13. A 

### In CALPUFF, a continuous plume is simulated as a se ries 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 time s 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 tot al nitrate (HNO 3 

### + NO 3 

### ), not on a puff-bypuff basis. @



### Input required by POSTUTIL includes an input contro l file and the hourly concentration output file

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

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

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

3-4), and the appropriate setting for MNITRATE in B ART-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 n ame used in CALPUFF for coarse particulate,

and PMF representing the name used for fine particu late. 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 wi th 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 out put file from either CALPUFF or POSTUTIL.

### 41



# Figure 3-5: POSTUTIL Control Input File: Input Gro up 2

INPUT GROUP: 2 -- Species Processing Information

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

------------- Subgroup (2a)

-------------
The following NSPECINP species will be pr ocessed:

! 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 wr itten:

! 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 f or BART-related visibility analyses are

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

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

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

use of natural background for the 20 percent best v isibility days. The guideline also provides for th e
use of monthly average relative humidity (RH) value s for BART-related visibility analyses. The

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

(MVISBK = 6).

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

background concentrations of ammonium sulfate, ammo nium 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 A Guidance for Estimating Natural Visibility

Conditions Under the Regional Haze Program @ (2003) 13 

### . For each Class I area, this guidance

document provides separate deciview values represen tative of annual average natural background,

and natural background for the 20 percent best days

.

The EPA natural visibility guidance document does n ot provide speciated background concentrations

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

13 

### EPA, 2003. Guidance for Estimating Natural Visibil ity Conditions Under the Regional Haze Program. Office of Air Quality Planning and S tandards, Research Triangle Park, NC 27711.

### 43 

## Table 3-5 CALPOST Control File Settings

Variable Description Value

ASPEC Species to process VISIB

ILAYER Enter A 1" 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. Up on consultation with EPA and National

Park Service/Fish and Wildlife Service representati ves 14 

### , it was concluded that the annual

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

they converge to lower concentratons that produce t he 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 Cl ass I area.

The scaling procedure as applied by NDDH is illustr ated 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 de ciview value reflects natural background

components for the US west region. To obtain the s peciated 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 deci views and light extinction is expressed,

dv = 10 ln (b ext



### /10)

or

b ext



### = 10 exp (dv/10)

where

dv represents deciviews,

14 

### NDDH, 2005. Electronic message summarizing BART mo deling-related conferencecall discussion with representatives of EPA, Nation al Park Service, and Fish and Wildlife Service, August 31, 2005. b ext 

### represents total light extinction expressed in in verse 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 b ackground 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 back ground concentrations is:

b ext 

### = (3) f (RH) [ammonium sulfate] + (3) f (RH) [am monium nitrate] + (0.6) [coarse mass] + (4) [organic carbo n] + (1) [soil] + (10) [elemental carbon] + b ray



### where

bracketed quantities represent background concentra tions in μ g/m 3



### , values in parenthesis represent scattering efficien cies, f (RH) is the relative humidity adjustment factor ( applied to hygroscopic species only), b ray 

### 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 coe fficient 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 avera ge natural background concentrations to values representative of 20 percent best days.

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

natural background components in the natural visibi lity 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 be st 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 ( μ g/m 3 

## )

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 A Guidance for Estimating Natural Visibility Conditio ns Under the Regional Haze Program @ (EPA, 2003), Table 2-1. **From A Guidance for Estimating Natural Visibility Conditio ns 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 CALPO ST) 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 vis ibility conditions. One other setting needed for

CALPOST development of natural background is extinc tion due to Rayleigh scattering

(BEXTRAY), which should be left at the default valu e 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 A Guidance for Estimating Natural Visibility Conditio ns 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 inco rporated in the CALPOST control file developed by

the NDDH for BART-related visibility analyses. A s ample 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 A 24HR 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 establishe d 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 o f the year, and is not receptor specific. A 24-hou r
prediction greater than 0.5 delta-deciview at any r eceptor 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 da ily prediction).



# 4.1 BART Screening

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

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

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

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

screening are found in the summary section at the b ottom of the A 24HR 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 T heodore 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 scre ening. Model execution and results are needed

for both pre-BART control and post-BART control sce narios, 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 a ppropriate metric. The BART guideline states:

A 

### Assess the visibility improvement based on the mode led change in visibility impacts for the

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

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

frequency, magnitude, and duration components of im pairment. @



### Consistent with the goals stated in the BART guidel ine, the NDDH recommends the following

specific approaches for evaluating the degree of vi sibility improvement from BART controls:

### 52

$ Compare the 98 th 

### percentile delta-deciview prediction from pre-cont rol 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 A duration @ , the maximum number of

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

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

modeling), compare the 90 th 

### percentile delta-deciview prediction from pre-cont rol and postcontrol modeling scenarios (i.e., average of the 20 percent worst days).

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

data.

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

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

of controls for individual species. When evaluatin g visibility improvement for individual species,

the following should be considered.

$ To maintain reasonable balance in the CALPUFF chemi stry, all four species (SO 2 

### , NO X 

### , PM

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

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

tested species, while the emission rate for other s pecies 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-spe cies testing, the reactive species SO 2 

### and

NO X 

### may be grouped separately from the non-reactive sp ecies PM coarse and PM fine

(primary only) in the post-control input file. Tha t 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 sp ecies SO 2 

### and NO X 

### , and the other virtual

source would include emission rates for non-reactiv e 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 th e species being tested is non-reactive, then

post-control stack paramters would be entered for t he 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 coa rse for the post-control scenario should be

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

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

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

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

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

improvement should be evaluated for the entire faci lity.

### 54

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

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

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

concert with the review of other prescribed analyse s 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 pro gram. CALBART processes the hourly

output file from either CALPUFF or POSTUTIL to prov ide 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 mode l 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 res ults for all Class I areas in a single execution.

CALBART requires an input control file which must b e 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 en sure 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.56Figure4-1:CAL BART OutputExampleCALBART-SummaryofVisibilityResultsfor24-hrDelta-DeciviewGenericSourceforYear2000MeteorologicalDataTitlelinesfromCALPUFF(POSTUTIL)outputfile:GenericSource-BARTProtocol-Postutil1.4Year2000CalmetMet.Data-RUC2dMesoscaleData-Monthly NH3BARTProtocolReceptors(99)SEQND%ofModeledExtinctionbySpeciesDELTA-DVDV(Total)DV(BKG)YEARDAYRECEPRECEPF(RH)%_S04%N03%_PMC%PMFTRNPSOUTHUNITLargestDelta-DV98th%tileDelta-DV90th%tileDelta-DV6.4161.5960.5418.6503.8722.6472.2342.2762.106NumberofdayswithDelta-Deciview>0.50:39NumberofdayswithDelta-Deciview>1.00:2220007420003162000239MaxnumberofconsecutivedayswithOelta-Deciview>0.50:3TRNPNORTHUNITLargestDelta-DV98th%tileDelta-DV90th%tileDelta-DV5.2582.2690.4467.4924.5022.5522.2342.2342.106NumberofdayswithDelta-Deciview>0.50:32NumberofdayswithDelta-Deciview>1.00:172000362000542000248MaxnumberofconsecutivedayswithOelta-Deciview>0.50:2TRNPELKHORNRANCHLargestDelta-DV98th%tileDelta-DV90th%tileDelta-DV6.3471.4140.4008.5813.6472.5272.2342.2342.127NumberofdayswithDelta-Deciview>0.50:26Nutube.t.u[w.iL.hDella-Dt:<..:iv.iew>1.00:11200020002000746698MaxnumberofconsecutivedayswithOelta-Deciview>0.50:2LOSTWOODNWALargestDelta-DV98th%tileDelta-DV90th%tileDelta-DV6.6612.1210.7928.9374.2892.9592.2752.1672.167NumberofdayswithDelta-Deciview>0.50:52NumberofdayswithDelta-Deciview>1.00:3120004720002162000215l-taxnumberofconsecutivedayswithDelta-Deciview>0.SO:5484552828271909090979591102451067171607272727977732.803.002.202.802.802.202.802.802.302.902.402.4069.8056.9684.3752.5871.8932.0071.1964.4562.6092.3169.1173.1930.1242.8915.4547.1427.9166.3128.7435.4237.257.5430.6826.210.050.120.130.210.171.290.050.090.110.110.180.440.030.030.050.070.040.400.030.040.040.040.030.16

# Appendix A

NDDH PSD Class I Area Receptors

### NON

- GR I DDED ( DIS CR E T E ) RECEP TO R DA T

A

Receptor N

o. X U T

M C

oord i nate ( km)



### T

RNP South Un i t Recept o r s :

1 2 3 

### 4 5 6 7 8 9 10 11 12 13 1 4 1 5 1 6 17 18 19 20 2 1 22 23 24 25 26 27 28 29 30 3 1 32 33 3 4 3 5 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,

- 11 8.0
,

- 118 .0,

- 118. 0,

- 118.0,

- 11 8.0,

- 11 6.0,

- 116.0,

- 116 .0,

- 1 16.0,

- 11 6.0
,

- 11 4. 0,

- 114.0,

- 114 .0
,

- 114. 0,

- 114. 0,

- 112

. 0,

- 112.0,

- 112. 0,

- 112. 0,

- 11 2.0,

- 110.0,

- 110

. 0,

- 11 0.0
,

- 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 U TM 

### Coo rdina t e { km l

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 E l 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 5 6 ' 761

. 3, 758

. 2, 771. 0, 796

. 2, 774.3, 8 1 9.0
, 839

. 3, 836

. 4, 

### Heigh t 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

- 12 1.608, 335.052, 777

. 3, 0

. 000! !END ! 102 X

- 11 8.992
, 337.441, 771

. 4, 0

. 000! END ! 103 X

- 11 6.94 5, 337.384, 734.8, 0.000! END ! 1 04 X

- 112.965, 335.621, 728.7, 0.000 ! END ! 105 X

- 107.0 51, 333.744, 746

. 3, 0.000! END ! 106 X

- 102.388, 329 .593, 770

. 0
, 0

. 000! END ! 107 X

- 1 00.8 52, 322.428, 853. 9, 0.000 ! END ! 1 08 X

- 1 02.9 5 6, 322.371, 850

. 2, 0.000!

. END ! 109 X

- 110.9 1 8, 324.760, 750

. 5, 0.000! !END ! 110 X

- 115

. 58 1, 326.352, 752.8, 0

. 000! !END ! 111 X

- 119.447, 332.550, 765.9, 0

. 000 ! !END !

T RNP North Unit Recept o 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, 4 00. 0' 6 14.6, 0

. 000! !END ! 

### so X

- 1 08.0, 402.0, 68 4. 0
, 0.000! !END ! 5 1 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, 4 02.0, 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, 61 5

. 3, 0

. 000! !END ! 59 X

- 1 0 4 .0, 4 02.0, 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, 4 02.0, 624.6, 0

. 000 ! !END ! 66 X

- 100.0, 404.0, 651

. 3, 0

. 000! !END ! 67 X

- 98.0, 4 00.0, 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, 4 02.0, 677.4, 0.000 ! 1 END ! 112 X

- 107.8 58
, 404.020, 771.2, 0.000! END ! 11 3 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 ! 11 6 X

- 1 00.9 42
, 398.243, 674

. 5, 0.000! END ! 117 X

- 109.587
, 399.044, 677

. 7' 0.000!

. END ! 118 X

- 109

. 5 87, 4 01.026, 749.2, 0

. 000! !END !

TRNP E lkho rn Ranch Receptor:
72 ! X = - 122.581, 361. 58 0, 64 7

. 7' 0

. 000 ! !END !

L os t 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 ! !EN D ! 76 X

- 34. 0
, 516. 0' 725 .0, 0

. 000 ! !END !