BART CALPUFF 

Class I Federal Area 

Individual Source Attribution 

Visibility Impairment Modeling Analysis 

for 

Tri-State Generation & Transmission Association 

Craig Station Units 1 and 2

(Revised) 

March 3, 2006 

Colorado Department of Public Health & Environment 

Air Pollution Control Division 

4300 Cherry Creek Drive South 

Denver, Colorado 80246 
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 ii
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Table of Contents 

1. EXECUTIVE SUMMARY ...................................................................................................................................1

2. INTRODUCTION.................................................................................................................................................3

2.1. MODELING PROCESS OVERVIEW ....................................................................................................................8

2.2. VISIBILITY CALCULATIONS.............................................................................................................................8

3. SOURCE DESCRIPTION..................................................................................................................................10

4. EMISSION ESTIMATES...................................................................................................................................11

5. CALMET/CALPUFF MODELING METHODOLOGY ................................................................................14

5.1. CALMET/CALPUFF MODEL SELECTION ...................................................................................................15

5.1.1. CALMET .................................................................................................................................................15

5.1.1.1. CALMET Modeling Domain......................................................................................................................... 16

5.1.1.2. CALMET Performance Evaluation ............................................................................................................... 17

5.1.1.3. Terrain ........................................................................................................................................................... 18

5.1.1.4. Land Use........................................................................................................................................................ 18

5.1.1.5. CALMET ZFACE and ZIMAX Settings....................................................................................................... 20

5.1.1.6. CALMET BIAS Setting ................................................................................................................................ 21

5.1.1.7. CALMET RMIN2 and IXTERP Settings...................................................................................................... 21

5.1.1.8. CALMET Settings: R1, R2, RMAX1, RMAX2, RMAX3 ............................................................................ 21

5.1.1.9. CALMET Surface Stations............................................................................................................................ 21

5.1.1.10. CALMET Upper Air Stations........................................................................................................................ 22

5.1.1.11. CALMET Precipitation Stations.................................................................................................................... 22

5.1.1.12. CALMET Sample Input File ......................................................................................................................... 22

5.1.1.13. CALMET Parameter Summary ..................................................................................................................... 22

5.1.2. CALPUFF ...............................................................................................................................................24

5.1.2.1. Receptor Network and Class I Federal Areas................................................................................................ 24

5.1.2.2. CALPUFF Meteorology ................................................................................................................................ 25

5.1.2.3. CALPUFF Modeling Domain........................................................................................................................ 25

5.1.2.4. CALPUFF Parameter Summary .................................................................................................................... 26

5.1.2.5. Chemical Mechanism .................................................................................................................................... 26

5.1.2.6. Chemical Mechanism – Ammonia Sensitivity Tests ..................................................................................... 29

5.1.2.7. Ammonia Assumptions - Discussion............................................................................................................. 33

5.1.2.8. Ammonia Assumptions.................................................................................................................................. 34

5.1.2.9. Ozone Assumptions....................................................................................................................................... 35

5.1.3. CALPOST Settings and Visibility Post-Processing.................................................................................36

5.1.3.1. Natural Conditions - Determining Hygroscopic And Non-Hygroscopic Values For the Best 20% Visibility 

Days 37

5.1.3.1.1. Natural Background - Objective .................................................................................................................... 37

5.1.3.1.2. Natural Background - Discussion .................................................................................................................. 37

5.1.3.1.3. Natural Background - Method ....................................................................................................................... 37

5.1.3.2. CALPOST and POSTUTIL Parameters......................................................................................................... 40

5.1.3.3. 98th Percentile Methods ................................................................................................................................. 44

6. RESULTS.............................................................................................................................................................46

6.1. RESULTS .......................................................................................................................................................47

7. REFERENCES ....................................................................................................................................................52

APPENDIX A – NATURAL BACKGROUND VALUES .........................................................................................55

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 iii
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

APPENDIX B – MONTHLY F(RH) VALUES ..........................................................................................................63

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 iv
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

1. Executive Summary 

Federal law requires Best Available Retrofit Technology (BART) for any BART-eligible 

source that ‘‘emits any air pollutant which may reasonably be anticipated to cause or contribute 

to any impairment of visibility” in any mandatory Class I federal area. Pursuant to federal 

regulations, states have the option of exempting a BART-eligible source from the BART 

requirements based on dispersion modeling demonstrating that the source cannot reasonably be 

anticipated to cause or contribute to visibility impairment in a Class I area. 

The Division has proposed state regulations establishing criteria and procedures for 

determining which Colorado sources will be subject to the BART requirement. The Division’s 

proposal is scheduled for a March 16, 2006 hearing before the Air Quality Control 

Commission. In advance of the hearing, and in preparation for the submittal of a state 

implementation plan for regional haze, the Division has performed air quality modeling with 

the CALPUFF modeling system to assess which BART-eligible sources in Colorado are likely 

to be subject to BART based on the proposed state regulation. 

According to 40 CFR Part 51, Appendix Y (BART guideline), a BART-eligible source is 

considered to “contribute” to visibility impairment in a Class I area if the modeled 98th

percentile change in deciviews is equal to or greater than the “contribution threshold.” Any 

BART-eligible source determined to cause or contribute to visibility impairment in any Class I 

area is subject to BART. In this report, the Division used a “contribution threshold” of 0.5 

deciviews, as prescribed by the regulatory proposal pending before the Commission. 

The Division has applied the CALPUFF modeling system with three years of meteorological 

data to determine if the 98th percentile 24-hour change in visibility (delta-deciview) from a 

BART-eligible source is equal to or greater than a contribution threshold of 0.5 deciviews at 

any Class I area. This initial phase of the BART modeling process is referred to as the 

“subject-to-BART” analysis. The modeling includes SO2, NOx, and direct PM10 emissions 

from all BART-eligible units at a given facility. 

While the modeling results in this report may be used to support regulatory decision making, 

additional modeling performed by the Division or source operator may supersede the results. If 

additional modeling is performed, it should be consistent with recommendations in the 

Division’s modeling protocol. Subsequent modeling performed by the source operator will be 

subject to Division review and approval. Moreover, the contribution threshold and other 

criteria used for this modeling demonstration have not been finalized and may change in the 

final rule adopted by the Commission. Therefore, the results in this report are not a final 

agency action. Any source that the Division determines is subject to BART will receive a 

separate notice of the agency’s final determination. Such separate notice will occur after the 

Commission acts on the proposed regulations establishing criteria and procedures for 

determining which sources will be subject to the BART requirement. 

The maximum 98th percentile delta-deciview value from Craig Station Units 1 and 2 at any 

Class I federal area is 2.689 deciviews, assuming natural background conditions and monthly 

March 3, 2006 1
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

f(RH) values. The impact is above the contribution threshold of 0.5 deciviews. The maximum 

impact occurs at the Mount Zirkel Wilderness Area. For the three-year period modeled, there 

are 496 days with an estimated impact over the contribution threshold of 0.5 deciviews. 

March 3, 2006 2
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

2. Introduction 

Federal law requires Best Available Retrofit Technology (BART) for any BART-eligible 

source that ‘‘emits any air pollutant which may reasonably be anticipated to cause or contribute 

to any impairment of visibility” in any mandatory Class I federal area. Pursuant to federal 

regulations, states have the option of exempting a BART-eligible source from the BART 

requirements based on dispersion modeling demonstrating that the source cannot reasonably be 

anticipated to cause or contribute to visibility impairment in a Class I area. 

Federal regulations implementing the BART requirement afford states some latitude in the 

criteria in determining whether a BART-eligible source is subject to BART. The Division has 

proposed state regulations establishing criteria and procedures for determining which Colorado 

sources will be subject to the BART requirement. The Division’s proposal is scheduled for a 

March 16, 2006 hearing before the Air Quality Control Commission. In advance of the 

hearing, and in preparation for the submittal of a state implementation plan for regional haze, 

the Division has performed air quality modeling with the CALPUFF modeling system to assess 

which BART-eligible sources in Colorado are likely to be subject to BART based on the 

proposed state regulation. 

According to 40 CFR Part 51, Appendix Y (BART guideline), a BART-eligible source is 

considered to “contribute” to visibility impairment in a Class I area if the modeled 98th 

percentile change in deciviews is equal to or greater than the “contribution threshold.” Any 

BART-eligible source determined to cause or contribute to visibility impairment in any Class I 

area is subject to BART. The Division has proposed a state regulation establishing a 

“contribution threshold” of 0.5 deciviews. In this report, the assumed “contribution threshold” 

is 0.5 deciviews. 

The Division has applied the CALPUFF modeling system with three years of meteorological 

data to determine if the 98th percentile 24-hour change in visibility (delta-deciview) from a 

BART-eligible source is equal to or greater than a contribution threshold of 0.5 deciviews at 

any Class I area. This initial phase of the BART modeling process is referred to as the 

“subject-to-BART” analysis. The modeling includes SO2, NOx, and direct PM10 emissions 

from all BART-eligible units at a given facility. 

While the modeling results in this report may be used to support regulatory decision making, 

additional modeling performed by the Division or source operator may supersede the results. If 

additional modeling is performed, it should be consistent with recommendations in the 

Division’s modeling protocol. Any subsequent modeling performed by the source operator will 

be subject to Division review and approval. Moreover, the contribution threshold and other 

criteria used for this modeling demonstration have not been finalized and may change in the 

final rule adopted by the Commission. Therefore, the results in this report are not a final 

agency action. Any source that the Division determines is subject to BART will receive a 

separate notice of the agency’s final determination. Such separate notice will occur after the 

Commission acts on the proposed regulations establishing criteria and procedures for 

determining which sources will be subject to the BART requirement. 

March 3, 2006 3
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Relevant language from the BART guideline is included, below, to show the modeling 

recommendations in context. Other sections of this report explain how the Division 

implemented the recommendations. The BART guidelines set out 40 CFR Part 51, Appendix 

Y, provide in part: 

III. HOW TO IDENTIFY SOURCES “SUBJECT TO BART” 

Once you have compiled your list of BART-eligible sources, you need to determine whether 

(1) to make BART determinations for all of them or (2) to consider exempting some of them 

from BART because they may not reasonably be anticipated to cause or contribute to any 

visibility impairment in a Class I area. If you decide to make BART determinations for all 

the BART-eligible sources on your list, you should work with your regional planning 

organization (RPO) to show that, collectively, they cause or contribute to visibility 

impairment in at least one Class I area. You should then make individual BART 

determinations by applying the five statutory factors discussed in Section IV below. 

On the other hand, you also may choose to perform an initial examination to determine 

whether a particular BART-eligible source or group of sources causes or contributes to 

visibility impairment in nearby Class I areas. If your analysis, or information submitted by 

the source, shows that an individual source or group of sources (or certain pollutants from 

those sources) is not reasonably anticipated to cause or contribute to any visibility 

impairment in a Class I area, then you do not need to make BART determinations for that 

source or group of sources (or for certain pollutants from those sources). In such a case, 

the source is not “subject to BART” and you do not need to apply the five statutory factors 

to make a BART determination. This section of the Guideline discusses several approaches 

that you can use to exempt sources from the BART determination process. 

A. What Steps Do I Follow to Determine Whether A Source or Group of Sources Cause 

or Contribute to Visibility Impairment for Purposes of BART? 

1. How Do I Establish a Threshold? 

One of the first steps in determining whether sources cause or contribute to visibility 

impairment for purposes of BART is to establish a threshold (measured in deciviews)

against which to measure the visibility impact of one or more sources. A single source that 

is responsible for a 1.0 deciview change or more should be considered to “cause” visibility 

impairment; a source that causes less than a 1.0 deciview change may still contribute to 

visibility impairment and thus be subject to BART. 

Because of varying circumstances affecting different Class I areas, the appropriate 

threshold for determining whether a source “contributes to any visibility impairment” for 

the purposes of BART may reasonably differ across States. As a general matter, any 

threshold that you use for determining whether a source “contributes” to visibility 

impairment should not be higher than 0.5 deciviews. 

In setting a threshold for “contribution,” you should consider the number of emissions 

sources affecting the Class I areas at issue and the magnitude of the individual sources’ 

March 3, 2006 4
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

 

impacts.5 In general, a larger number of sources causing impacts in a Class I area may 

warrant a lower contribution threshold. States remain free to use a threshold lower than 

0.5 deciviews if they conclude that the location of a large number of BART eligible sources 

within the State and in proximity to a Class I area justify this approach.6

2. What Pollutants Do I Need to Consider? 

You must look at SO2, NOx, and direct particulate matter (PM) emissions in determining 

whether sources cause or contribute to visibility impairment, including both PM10 and 

PM2.5. Consistent with the approach for identifying your BART-eligible sources, you do 

not need to consider less than de minimis emissions of these pollutants from a source. 

As explained in section II, you must use your best judgement to determine whether VOC or 

ammonia emissions are likely to have an impact on visibility in an area. In addition, 

although as explained in Section II, you may use PM10 an indicator for particulate matter 

in determining whether a source is BART eligible, in determining whether a source 

contributes to visibility impairment, you should distinguish between the fine and coarse 

particle components of direct particulate emissions. Although both fine and coarse 

particulate matter contribute to visibility impairment, the long-range transport of fine 

particles is of particular concern in the formation of regional haze. Air quality modeling 

results used in the BART determination will provide a more accurate prediction of a 

source’s impact on visibility if the inputs into the model account for the relative particle 

size of any directly emitted particulate matter (i.e. PM10 vs. PM2.5). 

3. What Kind of Modeling Should I Use to Determine Which Sources and Pollutants 

Need Not Be Subject to BART? 

This section presents several options for determining that certain sources need not be 

subject to BART. These options rely on different modeling and/or emissions analysis 

approaches. They are provided for your guidance. You may also use other reasonable 

approaches for analyzing the visibility impacts of an individual source or group of sources. 

Option 1: Individual Source Attribution Approach (Dispersion Modeling) 

You can use dispersion modeling to determine that an individual source cannot reasonably 

be anticipated to cause or contribute to visibility impairment in a Class I area and thus is 

not subject to BART. Under this option, you can analyze an individual source’s impact on 

visibility as a result of its emissions of SO2, NOx and direct PM emissions. Dispersion 

modeling cannot currently be used to estimate the predicted impacts on visibility from an 

individual source’s emissions of VOC or ammonia. You may use a more qualitative 

5

 We expect that regional planning organizations will have modeling information that identifies sources affecting 

visibility in individual class I areas. 

6

 Note that the contribution threshold should be used to determine whether an individual source is reasonably 

anticipated to contribute to visibility impairment. You should not aggregate the visibility effects of multiple sources 

and compare their collective effects against your contribution threshold because this would inappropriately create a 

“contribute to contribution” test. 

March 3, 2006 5
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

 

assessment to determine on a case-by-case basis which sources of VOC or ammonia 

emissions may be likely to impair visibility and should therefore be subject to BART 

review, as explained in section II.A.3. above. 

You can use CALPUFF7

 or other appropriate model to predict the visibility impacts from a 

single source at a Class I area. CALPUFF 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 long range transport of primary pollutants.8 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. 

There are several steps for making an individual source attribution using a dispersion 

model: 

1. Develop a modeling protocol. 

Some critical items to include in the protocol are the meteorological and terrain data that 

will be used, as well as the source-specific information (stack height, temperature, exit 

velocity, elevation, and emission rates of applicable pollutants) and receptor data from 

appropriate Class I areas. We recommend following EPA’s Interagency Workgroup on Air 

Quality Modeling (IWAQM) Phase 2 Summary Report and Recommendations for Modeling 

Long Range Transport Impacts9 for parameter settings and meteorological data inputs. 

You may use other settings from those in IWAQM, but you should identify these settings 

and explain your selection of these settings. 

One important element of the protocol is in establishing the receptors that will be used in 

the model. The receptors that you use should be located in the nearest Class I area with 

sufficient density to identify the likely visibility effects of the source. For other Class I areas 

in relatively close proximity to a BART-eligible source, you may model a few strategic 

receptors to determine whether effects at those areas may be greater than at the nearest 

Class I area. For example, you might chose to locate receptors at these areas at the closest 

point to the source, at the highest and lowest elevation in the Class I area, at the 

IMPROVE monitor, and at the approximate expected plume release height. If the highest 

modeled effects are observed at the nearest Class I area, you may choose not to analyze the 

other Class I areas any further as additional analyses might be unwarranted. 

7 The model code and its documentation are available at no cost for download from 

http://www.epa.gov/scram001/tt22.htm#calpuff . 

8 The Guideline on Air Quality Models, 40 CFR part 51, appendix W, addresses the regulatory application of air 

quality models for assessing criteria pollutants under the CAA, and describes further the procedures for using the 

CALPUFF model, as well as for obtaining approval for the use of other, nonguideline models. 

9 Interagency Workgroup on Air Quality Modeling (IWAQM) Phase 2 Summary Report and Recommendations for 

Modeling Long Range Transport Impacts, U.S. Environmental Protection Agency, EPA-454/R-98-019, December 

1998. 

March 3, 2006 6
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

You should bear in mind that some receptors within the relevant Class I area may be less 

than 50 km from the source while other receptors within that same Class I area may be 

greater than 50 km from the same source. As indicated by the Guideline on Air Quality 

Models, 40 CFR part 51, appendix W, this situation may call for the use of two different 

modeling approaches for the same Class I area and source, depending upon the State's 

chosen method for modeling sources less than 50 km. In situations where you are assessing 

visibility impacts for source-receptor distances less than 50 km, you should use expert 

modeling judgment in determining visibility impacts, giving consideration to both 

CALPUFF and other appropriate methods. 

In developing your modeling protocol, you may want to consult with EPA and your 

regional planning organization (RPO). Up-front consultation will ensure that key technical 

issues are addressed before you conduct your modeling. 

2. [Run model in accordance] with the accepted protocol and compare the predicted 

visibility impacts with your threshold for “contribution.”

You should calculate daily visibility values for each receptor as the change in deciviews 

compared against natural visibility conditions. You can use EPA’s “Guidance for 

Estimating Natural Visibility Conditions Under the Regional Haze Rule,” EPA-454/B-03-

005 (September 2003) in making this calculation. To determine whether a source may 

reasonably be anticipated to cause or contribute to visibility impairment at Class I area, 

you then compare the impacts predicted by the model against the threshold that you have 

selected. 

The 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 

start-up, shutdown, or malfunction. In addition, the monthly average relative humidity is 

used, rather than the daily average humidity – an approach that effectively lowers the peak 

values in daily model averages. 

For these reasons, if you use the modeling approach we recommend, you should compare 

your “contribution” threshold against the 98th percentile of values. If the 98th percentile 

value from your modeling is less than your contribution threshold, then you may conclude 

that the source does not contribute to visibility impairment and is not subject to BART.

March 3, 2006 7
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

 

2.1. Modeling Process Overview 

For each BART-eligible source that emits SO2, NOx, and/or direct PM10, the constant 

emission rates shown in section 4 are used in the CALPUFF modeling system to estimate the 

daily change in visibility compared against natural background conditions (delta-deciview) at 

each Class I federal area in the modeling domain. The 98th percentile delta-deciview value at 

each Class I area is compared to the “contribution threshold” to determine if the source 

contributes to visibility impairment. 

The CALPUFF1 modeling system consists of CALMET, CALPUFF, and CALPOST. 

CALMET is the meteorological model that generates hourly three-dimensional meteorological 

fields of variables such as wind and temperature. CALPUFF simulates the transport, 

dispersion, and transformation of pollutants emitted from the source and calculates hourly 

concentration and/or deposition flux values at each receptor in the modeling domain. 

CALPOST calculates time-averaged concentration and deposition flux values from the 

CALPUFF predictions and performs visibility calculations like those described in the section 

2.2. 

2.2. Visibility Calculations 

The general theory for performing visibility calculations with the CALPUFF modeling system 

is described in several federal documents, including: 

 “Interagency Workgroup on Air Quality Modeling (IWAQM) Phase 2 Summary Report 

and Recommendations for Modeling Long Range Transport Impacts” (IWAQM, 1998) 

 “Federal Land Manager’s Air Quality Related Values Workgroup (FLAG): Phase I 

Report” (FLAG, 2000) 

 “A User's Guide for the CALPUFF Dispersion Model” (Scire, 2000) 

In general, visibility is characterized either by visual range (the greatest distance that a large 

object can be seen) or by the light extinction coefficient, which is a measure of the light 

attenuation per unit distance due to scattering and absorption by gases and particles. 

Visibility is impaired when light is scattered in and out of the line of sight and by light 

absorbed along the line of sight. The light extinction coefficient (bext) considers light extinction 

by scattering (bscat) and light extinction by absorption (babs): 

bext = bscat + babs

The scattering components of extinction can be represented by these components: 

 light scattering due to air molecules = Rayleigh scattering = brayleigh

 light scattering due to particles = bsp

The absorption components of extinction can be represented by these components: 

 light absorption due to gaseous absorption = bag

1

 CALPUFF is a non-steady-state Lagrangian puff model. 

March 3, 2006 8
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

 light absorption due to particle absorption = bap

Particle scattering, bsp, can be expressed by its components: 

bsp = bSO4 + bNO3 + bOC + bSOIL+ bCoarse 

where: 

 bSO4 = scattering coefficient due to sulfates = 3[(NH4)2SO4]f(RH) 

 bNO3 = scattering coefficient due to nitrates = 3[NH4NO3]f(RH) 

 bOC = scattering coefficient due to organic aerosols = 4[OC] 

 bSOIL= scattering coefficient due to fine particles = 1[Soil] 

 bCoarse= scattering coefficient due to coarse particles = 0.6[Coarse Mass] 

Particle absorption from soot is defined as: 

 bap = absorption due to elemental carbon (soot) = 10[EC] 

The concentration values (in brackets) are expressed in micrograms per cubic meter. The 

numeric coefficient at the beginning of each equation is the dry scattering or absorption 

efficiency in meters-squared per gram. The f(RH) term is the relative humidity adjustment 

factor. 

The total atmospheric extinction can be expressed as: 

bext = bSO4 + bNO3 + bOC + bSOIL+ bCoarse+ bap+ brayleigh

In this equation, the sulfate (SO4) and nitrate (NO3) components are referred to as hygroscopic 

components because the extinction coefficient depends upon relative humidity. The other 

components are non-hygroscopic. 

The variation of the effect of relative humidity on the extinction coefficients for SO4 and NO3 

can be determined in several ways. According to the BART guideline, monthly f(RH) values 

should be used. 

The CALPUFF modeling techniques in this report will provide ground level concentrations of 

visibility impairing pollutants. The concentration estimates from CALPUFF are used with the 

previously shown equations to calculate the extinction coefficient. 

As described in the IWAQM Phase 2 Report, the change in visibility is compared against 

background conditions. The delta-deciview, Δdv, value is calculated from the source’s 

contribution to extinction, bsource, and background extinction, bbackground, as follows:

Δdv = 10 ln((bbackground+ bsource)/ bbackground) 

 

March 3, 2006 9
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

3. Source Description 

The Craig Station is a coal-fired power plant with a total net electric generating capacity of 

1264 MW, consisting of three units, located at 2101 S. Ranney, in Craig. Units 1 and 2, rated at 

4,318 mmBtu/hour each (net 428 MW), are BART-eligible emissions units. Under a January 

2001 Consent Order, the existing ESPs were replaced with baghouses and the wet scrubbers 

were upgraded. The baghouses control PM emissions and limestone scrubbers control SO2

emissions. The units use low-NOx burners to control NOx emissions. In addition, over-fire air 

and related NOx control upgrades are in place to meet the requirements of the Consent Decree 

(CDPHE, 2005). 

March 3, 2006 10
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

 

4. Emission Estimates 

According to the BART guideline, “The 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 

start-up, shutdown, or malfunction.” 

Short-term emission rates (≤24-hours) for SO2, NOx, and PM10 (including condensible and 

filterable direct PM102

) were modeled since visibility impacts are calculated for a 24-hour 

averaging period. All BART-eligible units at the facility were modeled together in CALPUFF. 

The Division initially used allowable emission rates or federally enforceable emission limits. If 

24-hour emissions limits did not exist, limits of a different averaging period were used. 

Specifically, if limits did not exist, maximum hourly emissions based on emission factors and 

design capacity were used. 

If the source operator elects to develop emission rates for future subject-to-BART modeling, 

case-by-case procedures should be developed in consultation with the Division. In general, the 

following emission rates are acceptable: 

• Short-term (≤24-hours) allowable emission rates (e.g., emission rates calculated using 

the maximum rated capacity of the source). 

• Federally enforceable short-term limits (≤24-hours). 

• Peak 24-hour actual emission rates (or calculated emission rates) from the most recent 

3 to 5 years of operation that account for “high capacity utilization” during normal 

operating conditions and fuel/material flexibility allowed under a source's permit. In 

situations where a unit is allowed to use more than one fuel, the fuel resulting in the 

highest emission rates should be used for the modeling, even if that fuel has not been 

used in the last 3 to 5 years. 

If short-term rates are not available, emissions rates based on averaging periods longer than 24-

hours are acceptable only in cases where the modeling shows that the source has impacts equal 

to or greater than the contribution threshold. 

For Craig units 1 and 2, the modeled emission rates are shown in Table 1. The stack 

parameters are based on the best available information in Division files. To simplify the 

emissions estimation process, only filterable PM10 emissions were used because modeling 

with SO2, NOx, and filterable PM10 shows impacts equal to or greater than the contribution 

threshold. The basis for the emission rates are shown below: 

2

 Common speciated PM species for CALPUFF include fine particulate matter (PMF), coarse particulate matter 

(PMC), soot or elemental carbon (EC), organic aerosols (SOA), and sulfate (SO4). H2SO4, for example, is a PM10 

species emitted from coal-fired units that is typically modeled as SO4 in CALPUFF. 

March 3, 2006 11
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

 PM: 0.03 lb/mmBtu heat input - January 2001 Consent Decree 

 SO2 : 0.160 lb/mmBtu heat input on a 30 day rolling average - January 2001 

Consent Decree 

 NOx: 0.34 lbs/mmBtu heat input when burning coal, as estimated by the source 

operator to reflect peak 24 hour average emissions 

Table 1. Stack parameters and emission rates. 

Craig Station

Unit 1

Stack height 600 ft Stack height 182.9 m

Stack diameter 28 ft Stack diameter 8.53 m

Exit velocity 57.95 ft/s Exit velocity 17.66 m/s

Exit temperature 118 °F Exit temperature 321 K

UTM Easting 280421.16 m LCC X Easting -197.885 km

UTM Northing 4482341.4 m LCC Y Northing 151.799 km

Elevation 6345 ft Elevation 1934 m

Source: USGS Aerial Photo, NAD 83, Zone 13 N

Design Input Rate 4318 mmBtu/hr

SO2 Rate (30-day) 0.16 lb/mmBtu SO2 Rate 87.05 g/s

NOX Rate (3-hr) 0.34 lb/mmBtu NOX Rate 184.98 g/s

PM10 Rate (filterable only) 0.03 lb/mmBtu PM10 Rate 16.32 g/s

Source: Colorado Department of Public Health & Environment

Model Inputs

Source: APEN dated April 27, 2005

Stack Parameters

Emissions Information

Stack Location

Converted with CALPUFF Coords

March 3, 2006 12
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Craig Station

Unit 2

Stack height 600 ft Stack height 182.9 m

Stack diameter 28 ft Stack diameter 8.53 m

Exit velocity 57.95 ft/s Exit velocity 17.66 m/s

Exit temperature 118 °F Exit temperature 321 K

UTM Easting 280313.02 m LCC X Easting -197.996 km

UTM Northing 4482345.1 m LCC Y Northing 151.802 km

Elevation 6345 ft Elevation 1934 m

Source: USGS Aerial Photo, NAD 83, Zone 13 N

Design Input Rate 4318 mmBtu/hr

SO2 Rate (30-day) 0.16 lb/mmBtu SO2 Rate 87.05 g/s

NOX Rate (3-hr) 0.34 lb/mmBtu NOX Rate 184.98 g/s

PM10 Rate (filterable only) 0.03 lb/mmBtu PM10 Rate 16.32 g/s

Source: Colorado Department of Public Health & Environment

Model Inputs

Source: APEN dated April 27, 2005

Stack Parameters

Emissions Information

Stack Location

Converted with CALPUFF Coords

March 3, 2006 13
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

5. CALMET/CALPUFF Modeling 

Methodology 

In this CALPUFF application, the CALMET/CALPUFF model setup is based on the January 

2005 modeling performed by CH2M HILL for the Public Service Company Comanche Unit 3 

PSD permit application because it underwent extensive review by the Division and by Federal 

Land Managers as part of the PSD permitting process. The Division modified the CALPUFF 

input files to include three additional Class I areas. It has also been modified as necessary to 

account for PM10 speciation. An additional post-processing step with POSTUTIL has been 

added to implement ammonia limiting. The CALPOST model setup was changed to make it 

consistent with the U.S. EPA’s BART guideline. In addition, the Division reviewed available 

data to determine appropriate ammonia background values for various parts of Colorado. The 

Division also performed sensitivity tests to understand the response of the model to changes in 

ammonia background concentration levels. Since the currently available version of CALPOST 

does not generate 98th percentile results, the Division modified CALPOST to generate a file 

with a full distribution of daily delta-deciview values for each receptor. In addition, the 

Division wrote a FORTRAN processor to generate 98th percentile results. 

This report is intended to provide sufficient technical documentation to support the application 

of CALPUFF at distances up to 300 kilometers. While CALPUFF has also been used at 

source-to-receptor distances less than 50 kilometers for some receptors, there is a Class I area 

within the 50 to 300 km range from every BART-eligible source in Colorado. Impacts at Class 

I areas greater than 300 km may be used, but it should be recognized that the use of puff 

splitting in CALPUFF would provide more accurate results for Class I areas beyond 300km. 

According to “Interagency Workgroup on Air Quality Modeling (IWAQM) Phase 2 Summary 

Report and Recommendations for Modeling Long Range Transport Impacts” (IWAQM Phase 

2 Report): 

In the context of the Phase 2 recommendation, the focus of the visibility analysis is on haze. 

These techniques are applicable in the range of thirty to fifty kilometers and beyond from a 

source. At source-receptor distances less than thirty to fifty kilometers, the techniques for 

analyzing visual plumes (sometimes referred to as ‘plume blight’) should be applied. 

For the few cases where BART-eligible source-to-receptors distances are less than 50 

kilometers, both the topography and the meteorological fields are complex and the use of 

CALPUFF appears to be appropriate based on the possibility of recirculation, stagnation, and 

complex flows. The shortest source-to-receptor distance modeled is about 25 kilometers, but it 

involves an elevation change of about 3000 ft. In addition, in each case, only a portion of the 

Class I area is less than 50 km from the source; many of the receptors are greater than 50 km. 

If there were issues regarding the 50 km distance, PLUVUEII would be an appropriate model 

to consider for source-to-receptor distances less than 50 kilometers. 

March 3, 2006 14
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

 

5.1. CALMET/CALPUFF Model Selection 

The following model versions are used: 

 CALPUFF: July 2004 beta version 5.711a, level 040716

 CALMET: July 2004 beta version 5.53a, level 040716

 POSTUTIL: May 2003 version 1.31, level 030528

 CALPOST: July 2003 version 5.51, level 030709

o Modified by Division for this analysis:

 CALPOST_BART98_v3.EXE (version 5.51_CO_v3, level 030709)

 BART98_v3.EXE

The use of CALPUFF is recommended in 40 CFR 51 Appendix Y (BART guideline). The 

primary niche for CALPUFF is as a long-range transport model. It is a multi-layer, non-steadystate puff dispersion model that can simulate the effects of time- and space-varying 

meteorological conditions on pollutant transport, chemical transformations, vertical wind 

shear, and deposition (Scire, 2000). 

5.1.1. CALMET 

The MM5/CALMET meteorological fields have been generated for 1996, 2001, and 2002. 

CALMET is based on the Diagnostic Wind Model (Douglas, S. and R. Kessler, 1988). It 

has been significantly enhanced by Earth Tech, Inc (Scire, 2000). For this particular study, 

the model uses a Lambert Conformal Projection coordinate system to account for the 

Earth's curvature. 

CALMET uses a two-step approach to calculate wind fields. In the first step, an initialguess wind field is adjusted for slope flows and terrain blocking effects, for example, to 

produce a Step 1 wind field. In the second step, an objective analysis is performed to 

introduce observational data into the Step 1 wind field. 

In this application, the initial guess wind fields are based on 36-kilometer MM53

meteorological fields for 1996, 2001, and 2002 (i.e., IPROG=14). The MM5 files were 

provided to the Division by CH2M HILL as part of the Public Service Company (PSCo) 

Comanche Unit 3 PSD permit application. Alpine Geophysics extracted the MM5 data into 

a CALMET MM5.DAT format for 1996, 2001, and 2002. Both the 1996 and 2001 MM5 

data were generated by the U.S. EPA. The 2002 MM5 data was originally developed for 

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

The BART guideline does not specify the exact number of years of mesoscale 

meteorological data for use in CALPUFF. According to 40 CFR Part 51 Appendix W, the 

length of the modeled meteorological period should be long enough to ensure that worstcase meteorological conditions are adequately represented in the model results. The 

number of years of data needed to obtain a stable distribution of conditions depends on the 

variable of interest. U.S. EPA recommends that consecutive years from the most recent, 

readily available 5-year period are preferred. However, “less than five, but at least three, 

3

 Fifth-Generation NCAR/Penn State Mesoscale Model. 

March 3, 2006 15
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

years of meteorological data (need not be consecutive) may be used if mesoscale 

meteorological fields are available....” 

At the time of this analysis, five years of agency-approved mesoscale meteorological data 

were not readily available at reasonable grid resolutions for Colorado. While the Division 

has the national 80km 1990 MM4 and 80km 1992 MM5 data sets, use of the coarse 

resolution 1990 and 1992 data sets would not improve the accuracy of the modeling results 

in Colorado. 

5.1.1.1. CALMET Modeling Domain 

The modeling domain is shown in Figure 1. It is based on a Lambert Conformal 

Conic projection. As determined by CH2M HILL, the Standard Parallels within the 

domain are 1/6th and 5/6th of the north-to-south extent instead of the 30-degree and 

60-degree lines that are listed as defaults in CALMET. This was done to minimize 

distortion. See Figure 7 for specific parameter settings. 

The domain includes all Class I areas in Colorado with the exception of Mesa Verde 

NP. Mesa Verde was excluded because it is more than 300 km from all of the BARTeligible sources in Colorado and because the BART-eligible sources in Colorado 

would have higher impacts at other Class I areas. That is, impacts are Mesa Verde 

would not be the controlling 98th percentile values for this analysis. The domain does 

not include Class I areas in any nearby states because the 98th percentile impacts 

from Colorado’s BART-eligible sources are expected to be highest at Class I areas in 

Colorado. The CALMET domain includes almost the entire state of Colorado. It is 

about 480 km x 480 km in the longitudinal and meridonal directions, respectively, 

with 4-kilometer CALMET grid cells. 

March 3, 2006 16
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Figure 1. CALMET/CALPUFF modeling domain. 

5.1.1.2. CALMET Performance Evaluation 

The meteorological fields developed by the MM5/CALMET modeling system were 

evaluated by CH2M HILL for Xcel Energy as part of the PSCo Comanche Unit 3 

PSD permit. Specifically, “CH2M HILL examined vector plots of selected periods 

within the CALMET output for validation of the wind fields with the CalDESK 

(Environmodeling Ltda.) program (CH2M HILL, 2005).” The Division replicated the 

CALMET modeling and performed additional review of the meteorological fields 

with the Lakes Environmental CALPUFF View software package. In general, the 

meteorological fields were found to be reasonable given the 36km MM5 resolution, 

although model performance could be improved with better resolution 

MM5/CALMET fields and the inclusion of more observations in CALMET. 

March 3, 2006 17
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

5.1.1.3. Terrain 

Gridded terrain elevations for the modeling domain are derived from 3 arc-second 

digital elevation models (DEMs) produced by the United States Geological Survey 

(USGS). The files cover 1-degree by 1-degree blocks of latitude and longitude. 

USGS 1:250,000 scale DEMs were used. The elevations are in meters relative to 

mean sea level and have a resolution of about 90 meters, shown in Figure 2. 

Figure 2. CALMET Terrain. 

5.1.1.4. Land Use 

The land use data is based on the Composite Theme Grid format (CTG) using Level I 

USGS land use categories were “mapped into the 14 primary CALMET land use 

categories (CH2M HILL, 2005),” shown in Figure 3. The land use categories are 

described in Figure 4. 

March 3, 2006 18
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Figure 3. CALMET land use categories. 

Figure 4. Land use categories table from CALMET User's Guide. 

March 3, 2006 19
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

 

5.1.1.5. CALMET ZFACE and ZIMAX Settings 

Eleven vertical layers have been used with vertical cell face (ZFACE) heights at: 0, 

20, 100, 200, 350, 500, 750, 1000, 2000, 3000, 4000, and 5000 meters. 

ZIMAX was set to 4500 meters based on analyses of soundings for summer ozone 

events. The analysis suggests mixing heights in Denver are often well above the 

CALMET default value of 3000 meters during the summer. For example, on some 

summer days, ozone levels are elevated all the way to 6000 meters MSL or beyond 

during some meteorological regimes, including some regimes associated with high 

ozone episodes. A sounding from the evening of July 1, 2002 (see Figure 5), which is 

a day the 8-hour ozone standard was exceeded at Rocky Mountain National Park, 

suggests the mixing height was probably around 6000 meters MSL. The mixing 

height estimate is based on the relative uniformity of the water vapor mixing ratio 

below 6000 meters, the temperature profile, the inverted "V" in the sounding, and 

data from a NOAA ozonesonde from Boulder that shows relatively constant ozone 

levels with height. Although low mixing heights can occur during the summer, 

maximum summertime daytime mixing heights in the Denver area often range from 

about 12,000 feet (3700 m) to 20,000 feet (6000 m) MSL. Since the CALMET 

ZIMAX setting is above ground level (AGL), not above mean sea level (MSL), the 

maximum summer daytime mixing height range over the plains would be about 

15000 feet (4500 m) AGL. Thus, a ZIMAX setting of 4500 m is used. 

Figure 5. Example Denver summertime sounding. 

March 3, 2006 20
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

5.1.1.6. CALMET BIAS Setting 

The BIAS settings for each vertical cell determine the relative weight given to the 

vertically extrapolated surface meteorological observations and upper air soundings. 

The initial guess field is computed with an inverse distance weighting of the surface 

and upper air data. It can be modified by the layer-dependent bias factor (BIAS). The 

values for BIAS can range from –1.0 to 1.0. For example, if BIAS is set to +0.25, the 

weight of the surface wind observation is reduced by 25%. If BIAS is set to –0.25, 

the weight of the upper air wind observation is reduced by 25%. If BIAS is set to 

zero, there is no change in the weighting from the normal inverse distance squared 

weighting. As recommended by the NPS, the default values of 0.0 have been used for 

all 11 vertical layers in this analysis. 

5.1.1.7. CALMET RMIN2 and IXTERP Settings 

Vertical extrapolation of data from a surface station is skipped if the surface station is 

close to the upper air station. The variable RMIN2 sets the distance between an upper 

air station and a surface station that must exceeded in order for the extrapolation to 

take place. RMIN2 has been set to the default value of 4, as recommended by the 

NPS. The default value of –4 for IEXTRP is used. By setting IEXTRP to –4 (as 

opposed to +4), layer 1 data at upper air stations is ignored. When IEXTRP=±4, the 

van Ulden and Holtslag wind extrapolation method is used. The method uses 

similarity theory and observed data to extend the influence of the surface wind speed 

and direction aloft. 

5.1.1.8. CALMET Settings: R1, R2, RMAX1, RMAX2, RMAX3 

An inverse-distance method is used to determine the influence of observations in the 

Step 1 wind field. R1 controls weighting of the surface layer and R2 controls 

weighting of the layers aloft. For example, R1 is the distance from an observational 

station at which the observation and first guess field are equally weighted. In 

addition, RMAX1, RMAX2, and RMAX3 determine the radius of influence over 

land in the surface layer, over land in layers aloft, and over water, respectively. That 

is, an observation is excluded if the distance from the observational site to a given 

grid point exceeds the maximum radius of influence. As recommended by the NPS, 

R1 and RMAX1 have been set to 30 km so that the initial guess field does not 

overwhelm the surface observations. R2 is set to 50 km and RMAX2 is set to 100 

km. RMAX3 is not much of a factor in Colorado given the lack of large water 

bodies. RMAX3 is set to 500 km. 

5.1.1.9. CALMET Surface Stations 

Eleven surface stations shown in Figure 6 were used, including Alamosa (ALS), 

Colorado Springs (CYS), Denver (DEN), Eagle (EGE), Limon (LIC), Pueblo (PUB), 

Trinidad (TAD), Cheyenne (CYS), Laramie (LAR), Rocky Mountain NP (ROM), 

and Gothic (GTH). 

March 3, 2006 21
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Figure 6. Surface meteorological stations. 

5.1.1.10. CALMET Upper Air Stations 

Two upper air stations were included: Grand Junction and Denver. 

5.1.1.11. CALMET Precipitation Stations 

CH2M HILL obtained precipitation data from the National Climatic Data Center 

(NCDC). All available data in fixed-length, TD-3240 format were ordered for the 

modeling domain. CH2M HILL processed the data with the PXTRACT and 

PMERGE processors. Stations with incomplete or poor quality data for a given year 

were excluded. The number of stations used for each year is as follows (CH2M 

HILL, 2005): 

 1996 - 84 stations 

 2001 - 82 stations 

 2002 - 86 stations 

5.1.1.12. CALMET Sample Input File 

Figure 7 summarizes some of the key CALMET parameters. 

5.1.1.13. CALMET Parameter Summary 

Figure 7 summarizes some of the key CALMET settings. 

March 3, 2006 22
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Figure 7. CALMET parameter summary. 

March 3, 2006 23
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

5.1.2. CALPUFF 

The default technical options in CALPUFF were used, except as specified otherwise in this 

report. 

5.1.2.1. Receptor Network and Class I Federal Areas 

The modeling domain contains eleven Class I federal areas: 

 Flat Tops Wilderness Area 

 Rawah Wilderness Area 

 Mt Zirkel Wilderness Area 

 Weminuche Wilderness Area 

 Rocky Mountain National Park 

 Maroon Bells-Snowmass Wilderness Area 

 La Garita Wilderness Area 

 Great Sand Dunes National Park 

 West Elk Wilderness Area 

 Eagles Nest Wilderness Area 

 Black Canyon of the Gunnison National Park 

The discrete receptors for eight of the Class I federal areas were generated by the 

National Park Service (NPS) for CH2M HILL using the NPS Convert Class I Areas

(NCC) computer program. For the remaining three areas not included in the CH2M 

HILL modeling, receptors were generated by the Division with the NCC program. 

Receptor elevations provided by the NPS conversion program have been used. The 

receptors for each Class I area are shown in Figure 9

March 3, 2006 24
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Figure 8. Class I federal area receptors. 

All receptors are included in each CALPUFF simulation. In CALPOST, only the 

receptor ranges for specific Class I areas are processed. The range of receptors is 

shown in Figure 9. 

Figure 9. Receptor numbers for specific Class I federal areas. 

5.1.2.2. CALPUFF Meteorology 

Refer to the CALMET section of the report for details. 

5.1.2.3. CALPUFF Modeling Domain 

The CALPUFF modeling domain is identical to the CALMET modeling domain. 

March 3, 2006 25
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

5.1.2.4. CALPUFF Parameter Summary 

Figure 10 summarizes some of the key CALPUFF settings. 

Figure 10. CALPUFF parameter summary. 

5.1.2.5. Chemical Mechanism 

The MESOPUFF II pseudo-first-order chemical reaction mechanism (MCHEM=1) is 

used for the conversion of SO2 to sulfate (SO4) and NOx to nitrate (NO4). Refer to 

the CALPUFF User’s Guide for a description of the mechanism (Scire, 2000). 

In the MESOPUFF II mechanism, the ammonia background concentration affects the 

equilibrium between nitric acid, ammonia, and ammonium nitrate. The equilibrium 

constant for the reaction is a non-linear function of temperature and relative humidity 

(Scire, 2000). Unlike sulfate, the calculated nitrate concentration is limited by the 

amount of available ammonia, which is preferentially scavenged by sulfate (Scire, 

2000). In particular, the amount of ammonia available for the nitric acid, ammonium 

nitrate, and ammonia reactions is determined by subtracting sulfate from total 

ammonia. 

While the chemical mechanism simulates both the gas phase and aqueous phase 

conversion of SO2 to sulfate, the aqueous phase method, which is important when the 

plume interacts with clouds and fog, can significantly underestimate sulfate 

formation. In this report, as recommended by the IWAQM Phase 2 report, the 

“nighttime SO2 loss rate (RNITE1)” is set to 0.2 percent per hour. The “nighttime 

March 3, 2006 26
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

NOx loss rate (RNITE2)” is set to 2.0 percent per hour and the “nighttime HNO3

formation rate (RNITE3)” is set to 2.0 percent per hour. 

According to the 1996 “Mt. Zirkel Wilderness Area Reasonable Attribution Study of 

Visibility Impairment. Volume II: Results of Data Analysis and Modeling - Final 

Report,” 

The CALPUFF chemical module is formulated around linear transformation rates for 

SO2 to sulfate and NOX to total nitrate. There are two options for specifying these 

transformation rates: 

Option 1: An internal calculation of rates based on local values for several controlling 

variables (e.g., solar radiation, background ozone, relative humidity, and plume NOX) 

as used in MESOPUFF-II. The parametric transformation rate relationships employed 

were derived from box model calculations using the mechanism of Atkinson et al. 

(1982). 

Option 2: A user-specified input file of diurnally varying but spatially uniform 

conversion rates. 

Morris et al. (1987) reviewed the MESOPUFF-II mechanism as part of the U.S. EPA 

Rocky Mountain Acid Deposition Model Assessment study. They found that it provided 

physically plausible responses to many of the controlling environmental parameters. 

However, the mechanism had no temperature dependence, which is an important 

factor in the Rocky Mountain region where there are wide variations in temperature. 

Furthermore, the MESOPUFF-II transformation scheme was based on box model 

simulations for conditions more representative of the Eastern U.S. than of the Rocky 

Mountains. 

The largest deficiency in the MESOPUFF-II chemical transformation algorithm is the 

lack of explicit treatment for in-cloud (aqueous-phase) enhanced oxidation of SO2 to 

sulfate. The MESOPUFF-II chemical transformation algorithm includes a surrogate 

reaction rate to account for aqueous-phase oxidation of SO2 to sulfate as follows: 

 Kaq = 3 × 10-8 × RH4 (%/hr) (B.2-1) 

Thus, at 100% relative humidity (RH), the MESOPUFF-II aqueous-phase surrogate 

SO2 oxidation rate will be 3% per hour. Measurements in generating station plumes 

suggest spatially- and temporally-integrated SO2 oxidation rates due to oxidants in 

clouds to be 10 times this value. 

Another issue is the amount of ammonia available for nitrate chemistry. According to 

a paper by EarthTech (Escoffier-Czaja and Scire, 2002), 

“In the CALPUFF model, total nitrate (TNO3 = HNO3 + NO3) is partitioned into 

each species according to the equilibrium relationship between HNO3 and NO3. 

This equilibrium varies as a function of time and space, in response to both the 

ambient temperature and relative humidity. In addition, the formation of nitrate is 

subject to the availability of NH3 to form ammonium nitrate (NH4NO3), the 

assumed form of nitrate in the model. In CALPUFF, a continuous plume is 

simulated as a series of puffs, or discrete plume elements. The total concentration 

March 3, 2006 27
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

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 order to properly account for ammonia 

consumption, a program called POSTUTIL was introduced into the CALPUFF 

modeling system in 1999. POSTUTIL allows total nitrate to be repartitioned in a 

post-processing step to account for the total amount of sulfate scavenging ammonia 

from all sources (both project and background sources) and the total amount of 

TNO3 competing for the remaining ammonia. In POSTUTIL, ammonia availability 

is computed based on receptor concentrations of total sulfate and TNO3, not on a 

puff-by-puff basis.” 

Ammonia-limiting methods have been used for repartitioning nitric acid and nitrate 

on a receptor-by-receptor and hour-by-hour basis to account for over prediction due 

to overlapping puffs in CALPUFF. Specifically, the use of the MNIRATE=1 option 

in POSTUTIL is acceptable. At this time, other ammonia-limiting methods, including 

iterative techniques that use observational data to resolve backward the 

thermodynamic equilibrium equation between NO3/HNO3 for each hour to minimize 

available ammonia, are not acceptable. Generally, for regulatory CALPUFF 

modeling in Colorado, techniques that assume the atmosphere is always ammonia 

poor are not acceptable, particularly in eastern Colorado. 

March 3, 2006 28
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

5.1.2.6. Chemical Mechanism – Ammonia Sensitivity Tests

To better understand the response of the modeling system to background ammonia 

when a single point source with significant emissions of SO2 and NOx is modeled, 

the Division performed sensitivity tests for a source in northeast Colorado and a 

source in northwest Colorado using the 2002 MM5/CALMET meteorology. In the 

test case, SO2, NOx, and filterable PM10 emissions were modeled. The ammonia 

background value was varied from 0 to 100 ppb. In the northeast Colorado test case, 

the SO2 emission rate is about 3 times higher than the NOx emission rate. In the 

northwest Colorado test case, the modeled NOx emission rate is about 4.4 times 

higher than the SO2 rate. 

In both cases, when the background ammonia concentration is zero, the model 

produces no nitrate, as expected; however, it produces sulfate. 

For the northeast Colorado sensitivity test (see Figure 11), where the modeled SO2

emission rate is significantly higher than the NOx emission rate, the change in 

visibility (delta-deciview) is not very sensitive to the background ammonia 

concentration across the range from 1.0 ppb to 100.0 ppb because of the high SO2

emission rates relative to NOx and the way sulfate is produced in the MESOPUFF II 

chemical mechanism. Visibility impacts drop significantly when the ammonia 

background is less than 1.0 ppb, but even at 0.0 ppb of ammonia, sulfate impacts 

remain relative high. 

Figure 11. Sensitivity of CALPUFF visibility impacts (delta-deciview) to 

ammonia backgrounds from 0 ppb to 100 ppb from a source with high SO2

emissions relative to NOx. 

March 3, 2006 29
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

For the northeast Colorado case, on days with the highest visibility impacts, the 

relative contribution of nitrate and sulfate vary (see Figure 12 and Figure 13), but 

most of the modeled visibility impairment is due to sulfate. When comparing these 

figures, be aware the relative rank for some days is different. For example, day 85 is 

the 2nd worst day for the 0.1 ppb ammonia case, but it’s the 3rd worst day for the 100 

ppb case. On the day with the highest impact (day 84), the contribution from sulfate 

is 98.8% for the 0.1 ppb ammonia case and 72.7% for the 100 ppb ammonia case. 

For the 8th high delta-deciview value, the contribution from sulfate is 86.3% for the 

0.1 ppb case and 67.9% for the 100 ppb case. 

Figure 12. Contribution of sulfate and nitrate to the modeled change in 

deciviews, assuming a background ammonia of 0.1 ppb in CALPUFF. 

Figure 13. Contribution of sulfate and nitrate to the modeled change in 

deciviews, assuming a background ammonia of 100 ppb. 

March 3, 2006 30
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

 

For the northwest Colorado sensitivity test (see Figure 14), where the modeled NOx 

emission rate is significantly higher than the SO2 emission rate, the change in 

visibility (delta-deciview) is not sensitive to the background ammonia concentration 

across the range from 10 ppb to 100 ppb. While there is a moderate drop in impacts 

when ammonia is dropped from 10 ppb to 1.0 ppb, the model is very sensitive to 

ammonia when the background ammonia level is less than 1.0 ppb. 

Figure 14. Sensitivity of CALPUFF visibility impacts (delta-deciview) to 

ammonia backgrounds from 0 ppb to 100 ppb from a source with high NOx 

emissions relative to SO2. 

March 3, 2006 31
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

For the northwest Colorado test case, according to CALPUFF as implemented here, 

impairment is primarily due to nitrate (see Figure 15 and Figure 16), but the 

contribution due to nitrate varies significantly depending on the assumed ammonia 

background level. For the 100 ppb background case, the nitrate contribution is 

greater than 90% for the top 20 days. However, for the 0.1 ppb case, the nitrate 

contribution varies from 43% to 81% for the top 20 days. 

Figure 15. Contribution of sulfate and nitrate to the modeled change in 

deciviews, assuming a background ammonia of 0.1 ppb in CALPUFF. 

Figure 16. Contribution of sulfate and nitrate to the modeled change in 

deciviews, assuming a background ammonia of 100 ppb in CALPUFF. 

Caution should be used when extrapolating the results of these tests to other 

CALPUFF applications. 

March 3, 2006 32
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Since the MESOPUFF II chemical mechanism used in this analysis depends on 

several parameters, including ozone and ammonia background concentrations, the 

methods for determining the background ozone and ammonia concentration fields are 

discussed in more detail in the next two sections. 

5.1.2.7. Ammonia Assumptions - Discussion 

In CALPUFF, as used in this application, the background ammonia concentration is 

temporally and spatially uniform. It is likely that some portions of the modeling 

domain are ammonia poor and some are ammonia rich. Thus, setting a domain-wide 

background is problematic. As discussed in the previous section, when modeling a 

single large source with high SO2 emission rates relative to NOx, the assumed 

background ammonia concentration is not a critical parameter for determining 

visibility impacts. 

According to the IWAQM Phase 2 Report, 

A further complication is that the formation of particulate nitrate is dependent on 

the ambient concentration of ammonia, which preferentially reacts with sulfate. The 

ambient ammonia concentration is an input to the model. Accurate specification of 

this parameter is critical to the accurate estimation of particulate nitrate 

concentrations. Based on a review of available data, Langford et al. (1992) suggest 

that typical (within a factor of 2) background values of ammonia are: 10 ppb for 

grasslands, 0.5 ppb for forest, and 1 ppb for arid lands at 20 C. Langford et al. 

(1992) provide strong evidence that background levels of ammonia show strong 

dependence with ambient temperature (variations of a factor of 3 or 4) and a strong 

dependence on the soil pH. However, given all the uncertainties in ammonia data, 

IWAQM recommends use of the background levels provided above, unless specific 

data are available for the modeling domain that would discredit the values cited. It 

should be noted, however, that in areas where there are high ambient levels of 

sulfate, values such as 10 ppb might overestimate the formation of particulate 

nitrate from a given source, for these polluted conditions. Furthermore, areas in the 

vicinity of strong point sources of ammonia, such as feed lots or other agricultural 

areas, may experience locally high levels of background ammonia. 

The Northern Front Range is assumed to be ammonia rich. “Sulfate along the 

Northern Front Range is completely neutralized by available ammonium and is 

present in the form of ammonium sulfate....The Northern Front Range is ammonia 

rich. There was sufficient ammonia, on most days during winter, to completely 

neutralize available nitric acid (NFRAQS, 1998).” 

For northeast Colorado, a background ammonia concentration of 30.4 μg/m3 (about 

44 ppb) or less appears to be reasonable based on measurements for this modeling 

study. According to monitoring conducted for NFRAQS, 

• "With respect to gaseous measurements, only ammonia was acquired at all nine 

sites with the denuder difference method at the Brighton and Welby sites and 

with the filter-pack method (i.e., impregnated cellulose-fiber filters behind 

Teflon-membrane filters) at the other sites. Average ammonia concentrations 

March 3, 2006 33
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

were 30.4 ± 53.4 μg/m3 at the core sites and 10.3 ±12.6 μg/m3 at the satellite 

sites. The large standard deviation is mainly due to elevated ammonia 

concentrations found at the Evans site. Maximum 24-hour ammonia 

concentrations were 187.0 ± 5.4 μg/m3 at the Evans core site on 01/17/97 and 

66.7 ± 3.5 μg/m3 at the Masters site on 01/20/97. Figure 6.3-5 shows that 

during the mid-January episode, 24-hour ammonia concentrations varied by 

orders of magnitude at the nine NFRAQS sites."

• "For the 6- and 12-hour samples, Figure 6.4-3[not included in this report]

ammonia concentrations were rather consistent throughout the day, with 

apparent site -to-site and season-to-season variation. Average ammonia 

concentrations at the Brighton site were double those at the Welby site during 

Winter 97. Summertime ammonia concentrations were ~1 to 2 μg/m3 higher 

than the wintertime at the Welby site. Since ammonia concentrations closely 

reflect the vicinity of the sampling area, site-to-site variations were more 

pronounced than seasonal or diurnal variations. This is evidenced by the graph 

in Figure 6.4-4[not included in this report], which shows ammonia 

concentrations were factors of 10 to 20 higher at the Evans site than at most of 

the other sites during Winter 97. Elevated concentrations exceeded 50 μg/m3 on 

20% of the days at the Evans site. Twenty-four hour ammonia concentrations at 

the Masters and Longmont sites were also factors of 5 to 10 higher than at the 

other sites." 

For other areas like northwest Colorado, an annual background ammonia concentration 

of about 1 ppb or less is probably more reasonable, based on ammonia measurements 

from the Mt. Zirkel Visibility Study.

In the Aerosol Evolution Model (AEM) simulations done for the Mt Zirkel Study for 

a specific period, “base case background air concentrations for ammonia were assumed 

to be 0.5 μg/m3 and 30 ppbv for ozone, consistent with measured values at the Hayden 

VOR site.” An ammonia concentration of 0.5μg/m3 is about 0.7 ppb. 

In the CALPUFF modeling section of the Mt Zirkel Study report, 

“The CALPUFF default value for background ammonia concentrations of 10 ppb 

was also considered far too high as a representative area-average. Measurements 

from the Buffalo Pass and Gilpin Creek sites were used to adjust ammonia 

concentration to episode and site-mean values.” 

Based on a review of CALUFF files used for the Mt. Zirkel Study, for the August 

simulations, the assumed ammonia background (BCKNH3) was 1.6 ppb; for the 

October simulation, the assumed background was 0.5 ppb; and for the September 

simulation, the assumed background was 0.8 ppb. 

5.1.2.8. Ammonia Assumptions 

Based on information in the previous section, for sources located in northeast 

Colorado and along the South Platte River, a domain-wide ammonia background 

March 3, 2006 34
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

value of 44 ppb is used. For sources located in northwest Colorado, a background 

ammonia concentration of 1.0 ppb is used. For sources located in southeastern 

Colorado and for source located along the Arkansas River, a background value of 10 

ppb is used. 

5.1.2.9. Ozone Assumptions 

According to the IWAQM Phase 2 Report, 

CALPUFF provides two options for providing the ozone background data: (1) a 

single, typical background value appropriate for the modeling region, or (2) hourly 

ozone data from one or more ozone monitoring stations. The second and preferred 

option requires the creation of the OZONE.DAT file containing the necessary data. 

For the Demonstration Assessment, the domain was large (700 km by 1000 km) 

such that the second option was necessary. The IWAQM does not anticipate such 

large domains as being the typical application. Rather, it is anticipated that the 

more typical application will involve domains of order 400 km by 400 km or 

smaller. But even for smaller domains, the ability to provide at least monthly 

background values of ozone is deemed desirable. The problem in developing time 

(and perhaps spatial) varying background ozone values is having access to 

representative background ozone data. Ozone data are available from EPA’s 

Aerometric Information Retrieval System (AIRS); however, AIRS data must be used 

with caution. Many ozone sites are located in urban and suburban centers and are 

not representative of oxidant levels experienced by plumes undergoing long range 

transport.

In this study, “CH2M HILL obtained hourly ozone data from the following stations 

located within the modeling domain for some or all of the years 1996, 2001, and 

2002: 

• Gothic (Gunnison County, Colorado) 

• Rocky Mountain National Park 

Additional, hourly data for 1996, 2001, and 2002 were provided to CH2M HILL by 

the APCD for the following stations along the Front Range: 

• Greeley 

• Highlands Ranch 

• Colorado Springs 

Data recovery for the years 2001 and 2002 for the Greeley station was very low, and 

therefore data from the nearby Fort Collins station were used instead. Any data 

missing from the hourly records were replaced with a domain-wide default 

concentration of 60 parts per billion (ppb), as determined by the APCD/NPS (CH2M 

HILL, 2005).” 

March 3, 2006 35
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

5.1.3. CALPOST Settings and Visibility Post-Processing 

The CALPUFF results have been post-processed with a modified version of CALPOST 

(version 5.51_CO_v3, level: 030709), POSTUTIL (version 1.31, level 030528), and 

BART98_v3. The CALPOST modifications were performed by the Division and do not 

affect any of the calculations in CALPOST for the deciview values used in this report; 

however, some simple calculations were done within CALPOST in order to output deltadeciview values (instead of percent change values) for the individual species that contribute 

to the overall delta-deciview value, but these values are not used for the subject-to-BART 

modeling. Otherwise, the CALPOST code modification consists of a “write” statement and 

supporting code. It outputs all daily delta-deciview values for every receptor to a file called 

“deciview24.dat.” The 98th percentile values are computed from “deciview24.dat” by a 

separate FORTRAN processor (BART98_v3) written by the Division specifically for this 

analysis. 

For the initial modeling analysis, all PM10 was assumed to have a extinction efficiency of 

1.0 since the contribution of direct PM10 emissions is expected to be relatively small 

compared to visibility impairment caused by SO2 and NOx emissions. However, if 

modeled impacts were below the contribution threshold, condensible and filterable PM10 

emissions were quantified and speciated or a sensitivity test was performed to determine if 

PM10 speciation could change the outcome of the analysis. If speciated PM10 emissions 

were modeled, the following species were considered: fine particulates (PMF), coarse 

particulates (PMC), elemental carbon (EC), organic carbon (SOA), and sulfate (SO4). To 

see how PM10 was modeled for this source, refer to sections 4 and 5.1.3.2. 

In this study, to calculate background light extinction, MVISBK has been set to 6. That is, 

monthly RH adjustment factors are applied directly to the background and modeled sulfate 

and nitrate concentrations, as recommended by the BART guideline. The RHMAX 

parameter, which is the maximum relative humidity factor used in the particle growth 

equation for visibility processing, is not used when method 6 is selected. Similarly, the 

relative humidity adjustment factor (f(RH)) curves in CALPOST (e.g., IWAQM growth 

curve and the 1996 IMPROVE curve) are not used when MVISBK is equal to 6. 

The natural background is based on the 20 percent best visibility days, as recommended by 

the BART guideline preamble: 

Finally, these BART guidelines use the natural visibility baseline for the 20 percent 

best visibility days for comparison to the "cause or contribute" applicability 

thresholds. We believe this estimated baseline is likely to be reasonably 

conservative and consistent with the goal of natural conditions (70 FR 39125). 

The method for estimating natural background is presented in section 5.1.3.1. Specifically, 

for hygroscopic components, BKSO4 in CALPOST has been set to 0.0893 for all months. 

For non-hygroscopic components, BKSOIL has been set to 1.620 for all months. The 

BKSO4 and BKSOIL values have been computed specifically for the Colorado Class I 

areas in the modeling domain. 

March 3, 2006 36
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

The extinction due to Rayleigh scattering (i.e., the scattering of light by natural particles 

much smaller than the wavelength of the light) has been set to 10 Mm-1 (BEXTRAY = 

10.0). 

5.1.3.1. Natural Conditions - Determining Hygroscopic And NonHygroscopic Values For the Best 20% Visibility Days 

5.1.3.1.1. Natural Background - Objective 

 The spreadsheet shown in Figure 17 was created to determine the hygroscopic 

(3[BKSO4]) and non-hygroscopic (equivalent to [BKSOIL]) portions of natural 

background for the best 20% visibility days (Best Days) at all Class I areas in 

Colorado's BART modeling. These concentrations, [BKSO4] and [BKSOIL], are 

used in CALPOST with monthly relative humidity adjustment factors (f(RH)) to 

determine monthly natural background visibility that would, on average, represent 

the average natural background visibility for the best 20% days in EPA's “Guidance 

for Estimating Natural Visibility Conditions Under the Regional Haze Program” 

(EPA, 2003). 

5.1.3.1.2. Natural Background - Discussion 

“Guidance for Estimating Natural Visibility Conditions Under the Regional Haze 

Program” (EPA, 2003), section 2.4, describes the calculation of the annual average 

background extinction (in 1/Mm) for a Class I area using the area's annual f(RH) 

and average natural concentrations based on the area's geographic location (east 

versus west). Annual average background extinction values (in 1/Mm) are 

converted to annual average Haze Index (HI) values (in deciview or dv). Then, the 

average HI value for the 20% best visibility days (Best Days (dv)) is estimated from 

10th percentile of the annual average HI value for a Class I area assuming normal 

distribution. Thus, no average natural concentrations are provided for determining 

extinction for the 20% best visibility days. 

 

For background extinction computation methods 2, 3, and 6 in CALPOST, 

background extinction is calculated with user-supplied monthly concentrations of 

SO4, NO3, PM coarse, organic carbon, soil, and elemental carbon species. In 

practice, concentrations for only 2 species, SO4 ([BKSO4]) and soil ([BKSOIL]), 

are supplied in the CALPOST input file to represent hygroscopic and nonhygroscopic portions of background extinction, respectively. 

To determine background extinction for the BART analysis with CALPOST, 

average natural concentrations that represent average natural background visibility 

for the best 20% days need to be determined. 

5.1.3.1.3. Natural Background - Method 

Following EPA's approach of using regional average natural concentrations and the 

concept of using simplified inputs in CALPOST, the same hygroscopic (3[BKSO4]

best20) and non-hygroscopic ([BKSOIL]best20) values would be used in CALPOST for 

all Class I areas in Colorado's BART modeling. 

March 3, 2006 37
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

The spreadsheet calculates an average background (dv) based on monthly 

background extinction (1/Mm) for each Class I area in Colorado's BART modeling 

using the following equations: 

1. Monthly background extinction in 1/Mm (bextmonth) = 3[BKSO4]best20f(RH) 

+ [BKSOIL] best20 + Rayleigh 

2. Annual average background extinction in 1/Mm (bextannual_ave) = (bextJan + 

bextFeb + ... + bextDec)/12 

3. Calculated Best Days in dv = 10ln(bextannual_ave/10) 

EPA guidance provides f(RH) values based on the centroid of the Class I area (see 

Appendix B – Monthly f(RH) Values) and a Best Days (dv) value for each of the 

Class I areas (see Appendix A – Natural Background Values). 

The hygroscopic (3[BKSO4]) and non-hygroscopic ([BKSOIL]) values determined 

yielded the lowest sum of the absolute differences between the published Best Days 

(dv) and calculated Best Days (dv) for all Class I areas in the analysis: 

 where: n = number of Class I areas in analysis 

The "hygro (3[BKSO4])" and "non-hygro ([BKSOIL])" values of 0.268 and 1.620 

were calculated in Microsoft Excel using the "solver add-in" tool for optimization 

and equation solving (Figure 17). As can be seen from the “difference” values in 

Figure 17, the annual 20% best visibility days background concentrations for each 

Class I area calculated with this method are within 0.01 deciviews or less of the 

annual 20% best visibility days background values recommended by EPA. For 

CALPOST, the hygroscopic component of extinction is divided by 3 (the extinction 

coefficient of sulfate and nitrate) and input as BKSO4 (i.e., BKSO4 = 0.268/3 = 

0.0893). The non-hygroscopic component is used directly (i.e., BKSOIL = 1.620). 

March 3, 2006 38
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Figure 17. Spreadsheet showing the "hygro (3[BKSO4])" (0.268)and "nonhygro ([BKSOIL])" (1.620) values calculated in Microsoft Excel using the 

"solver add-in" tool for optimization and equation solving. 

March 3, 2006 39
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

5.1.3.2. CALPOST and POSTUTIL Parameters 

For this modeling analysis, if PM10 speciation was performed (see section 4), then 

example #1 from this section was used. If PM10 speciation was not performed, then 

example #2 from this section was used. In example #1, fine particulate emissions are 

speciated into PMF, PMC, EC, SOA, and SO4 and explicitly included as species in 

CALPUFF. Emission rates for each species are included in CALPUFF. Figure 18

summarizes some of the key CALPOST settings. The monthly f(RH) values 

(RHFAC), which are different for each Class I area, are from Appendix B – Monthly 

f(RH) Values. 

Figure 18. CALPOST - key parameters (example #1 setup). 

March 3, 2006 40
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

POSTUTIL is used to compute the partition for the total concentration fields with 

MNITRATE=1 and the appropriate ammonia background concentration. The 

ammonia background concentration, BCKNH3, in POSTUTIL is the same as the 

background value presented in section Figure 18. In POSTUIL, the input species 

include SO2, SO4, NOX, HNO3, NO3, SOA, PMF, PMC, and EC and the output 

species include SO4, HNO3, NO3, SOA, PMF, PMC, and EC. Key POSTUTIL 

parameters are shown in Figure 19. 

Figure 19. POSTUTIL - key parameters for cases with nitrate partitioning and 

speciated PM10 concentrations (example #1 setup). 

March 3, 2006 41
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

In example #2, PM10 is included as a species in CALPUFF and ammonia limiting is 

performed. The CALPOST setup is the same as the example #1 setup (see Figure 18) 

except LVPMC=F, since there are is no coarse PM, and SPECPMF=SOIL because 

the PM10 emissions from CALPUFF are reallocated to the species SOIL and EC in 

the first of two POSTUTIL runs. The first POSTUTIL setup (see Figure 20) was 

intended to provide a post-processing opportunity to divide the PM10 concentrations 

into SOIL and EC components; however, in the setup shown in Figure 20, all of the 

PM10 was allocated to SOIL and none was allocated to EC. 

Figure 20. POSTUTIL setup for simulations where PM10 is divided into SOIL 

and EC species (example #2 setup). 

March 3, 2006 42
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

In the second POSTUTIL setup for example#2, POSTUTIL is used to compute the 

partition for the total concentration fields with MNITRATE=1 and the appropriate 

ammonia background concentration. The ammonia background concentration, 

BCKNH3, in POSTUTIL is the same as the background value presented in section 

5.1.2.8. In this POSTUIL setup, the input species include SO4, NO3, HNO3, EC, 

SOIL, and SOA and the output species include SO4, NO3, HNO3, EC, SOIL, and 

SOA. Key POSTUTIL parameters are shown in Figure 19. 

Figure 21. POSTUTIL setup for simulations where ammonia limiting is 

performed using the output file generated from the POSTUTIL setup in Figure 

20 (example#2 setup). 

March 3, 2006 43
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

5.1.3.3. 98th Percentile Methods 

According the BART guideline: 

...you should compare your “contribution” threshold against the 98th percentile of 

values. If the 98th percentile value from your modeling is less than your contribution 

threshold, then you may conclude that the source does not contribute to visibility 

impairment and is not subject to BART. (70 FR 39162) 

The BART guideline does not contain a specific method for calculating the “98th

percentile value” and CALPOST version 5.51 does not generate a 98th percentile 

delta-deciview value. Consequently, the Division developed a FORTRAN program 

(BART98_v3) to compute 98th percentile results. The program implements several 

methods because, at the time the code was written, U.S. EPA had not yet specified 

an explicit method for determining the 98th percentile value. 

The U.S.EPA recommends using the 98th percentile value from the distribution of 

values containing the highest modeled delta-deciview value for each day of the 

simulation from all modeled receptors at a given Class I area. The 98th percentile 

delta-deciview value can be determined in several ways: 

 The 8th highest value for each year modeled 

 The 3-year average of the annual 8th high values 

 The 22nd highest value for the 3-year modeling period 

The highest value from the methods above is compared to the contribution threshold. 

The contribution threshold has an implied level of precision equal to the level of 

precision reported from CALPOST. Specifically, the 98th percentile results are 

reported to three decimal places. 

The Division’s processor BART98_v3 calculates the 98th percentile value with the 

method recommended by U.S. EPA. The Division refers to the method as the “dayspecific method” or “method 1.” The first step in the method is to find the highest 

modeled delta-deciview value for each day of the simulation from all modeled 

receptors for the selected time period. While this set of delta-deciview values is 

generated by CALPOST in an unranked format, the Division’s processor 

BART98_v3 outputs all daily delta-deciview values for each receptor from 

CALPOST and finds the highest impact for each day. Next, the processor ranks the 

daily delta-deciview maxima in descending order for the number of days processed 

in CALPOST. Then, the processor determines the 98th percentile value from the 

distribution of ranked modeled daily maximum values, irrespective of receptor 

location. For example, for a 365-day simulation, the 98th percentile value would be 

the 8th highest modeled delta-deciview value from the list of ranked delta-deciview 

values. That is, the top 7 days are ignored, even though the values being ignored 

may be at different receptors. Similarly, for a 3-year period, the 98th percentile 

would be the 22nd highest modeled delta-deciview value. 

March 3, 2006 44
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

The processor BART98_v3 also generates 98th percentile values using the “receptorspecific method” or “method 2.” This method, which calculates 98th percentile 

values on a receptor-by-receptor basis, is not used for the subject-to-BART 

modeling in Colorado. 

In order to make the processor more general and to handle missing data, the “8th

high” (for one year) and “22nd high” (for 3 years) values recommended by U.S. EPA 

are not hardwired into the processor; rather, the processor contains an algorithm that 

calculates the appropriate “nth high” value from the distribution of data. The 8th high 

and 22nd high values recommended by U.S. EPA are consistent with the values that 

would be generated from the equations in 40 CFR 50 Appendix N - “Interpretation 

of the National Ambient Air Quality Standards for PM2.5” – for determining 98th

percentile values for PM2.5 monitoring. Thus, the Appendix N method is used in the 

processor. For the exact algorithm, see Appendix N, the BART98_v3 source code, 

or the BART98_v3 “readme” file. 

March 3, 2006 45
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

6. Results 

The CALPUFF modeling results include eleven of the twelve Class I areas in Colorado. Mesa 

Verde was excluded because it is more than 300 km from all of the BART-eligible sources in 

Colorado. In addition, the BART-eligible sources in Colorado would have higher impacts at 

other Class I areas. That is, impacts at Mesa Verde would not be the controlling 98th percentile 

values for this analysis. The modeling domain does not include Class I areas in any nearby 

states because the maximum 98th percentile impact from the Craig Station is expected to occur 

at a Class I area in Colorado. 

The results for source-to-receptor distances beyond 300 kilometers may be used, but they may 

overestimate impacts because puff splitting has not been used. The model setup used here 

should provide reasonable estimates for source-to-receptor distances up to 300 kilometers. 

Figure 22 shows the 50km and 300 km radius circles around the modeled BART-eligible 

source. 

Figure 22. Class I areas within 50 and 300 kilometers of the BART-eligible source. 

March 3, 2006 46
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

6.1. Results 

The Division has applied the CALPUFF modeling system with three years of meteorological 

data to determine if the 98th percentile 24-hour change in visibility (delta-deciview) from a 

BART-eligible source is greater than a contribution threshold of 0.5 deciviews at any Class I 

area. This initial phase of the BART modeling process is referred to as the “subject to BART” 

analysis. The modeling includes SO2, NOx, and direct PM10 emissions from all BARTeligible units at a given facility. 

While the modeling results in this report may be used to support regulatory decision making, 

additional modeling performed by the Division or source operator may supersede the results in 

this report. If additional modeling is performed, it should be consistent with recommendations 

in the Division’s modeling protocol. Any subsequent modeling performed by the source 

operator will be subject to Division review and approval. Moreover, the contribution threshold 

and other criteria used for this modeling demonstration have not been finalized and may 

change in the final rule adopted by the Commission. Therefore, the results in this report are 

not a final agency action. Any source that the Division determines is subject to BART will 

receive a separate notice of the agency’s final determination. Such separate notice will occur 

after the Commission acts on the proposed regulations establishing criteria and procedures for 

determining which sources will be subject to the BART requirement. 

Table 2 and Figure 23 show the 98th percentile daily delta-deciview values for each Class I 

area in the modeling domain. The 98th percentile delta-deciview value is determined several 

ways: 

 The 8th highest value for each year modeled 

 The 3-year average of the annual 8th high values 

 The 22nd highest value for the 3-year modeling period 

The highest value from the methods above is compared to the contribution threshold. The 

contribution threshold has an implied level of precision equal to the level of precision reported 

from CALPOST. Specifically, the 98th percentile results are reported to three decimal places. 

The maximum 98th percentile delta-deciview value from Craig Station Units 1 and 2 at any 

Class I federal area is 2.689 deciviews, assuming natural background conditions and monthly 

f(RH) values. The impact is above the contribution threshold of 0.5 deciviews. The maximum 

impact occurs at the Mount Zirkel Wilderness Area. For the three-year period modeled, there 

are 496 days with an estimated impact over the contribution threshold of 0.5 deciviews. 

Table 3 shows the summary report generated by the Division’s 98th percentile postprocessor 

(BART98_v3) for the maximum 98th percentile value. Figure 24 and Figure 25 show the 

distribution of delta-deciview values used to generate the maximum 98th percentile value. 

Figure 24 shows the top 25 delta-deciview values at the Class I federal area with the maximum 

impact from this BART-eligible source.

March 3, 2006 47
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Table 2. Maximum 98th percentile value, 98th percentile values calculated with several 

methods, and the number of days the impact is equal to or greater than 0.5 deciviews for the 

entire period modeled. 

2.689

BART-eligible source name:

19961 2001 2002

3-year 

Average

Flat Tops WA 2.093 1.615 2.095 1.934 1.996 168

Rawah WA 1.587 1.393 1.929 1.636 1.588 190

Mt Zirkel WA 2.131 2.226 2.689 2.349 2.315 496

Weminuche WA 0.172 0.097 0.194 0.154 0.165 4

Rocky Mountain NP 1.753 1.267 1.935 1.652 1.765 205

Maroon Bells-Snowmass WA 0.983 0.621 0.563 0.722 0.652 37

La Garita WA 0.279 0.154 0.234 0.222 0.205 3

Great Sand Dunes NP 0.468 0.323 0.360 0.384 0.403 11

West Elk WA 0.566 0.505 0.433 0.501 0.515 26

Eagles Nest WA 1.560 1.106 1.211 1.292 1.260 109

Black Canyon of the Gunnison NP 0.467 0.265 0.338 0.357 0.382 17

CALPUFF Individual Source Attribution Analysis

Craig Station - Units 1 & 2

Maximum 98th Percentile Value =

8th High Delta-Deciview Value

22nd High DeltaDeciview Value 

from 3-year 

Modeling Period

1 1996, 2001, and 2002 are the years of meteorological data modeled. 

Class I federal area

98th Percentile Daily Change in Visibility from BART-Eligible 

Source Compared Against Natural Background Conditions

Number of 

Days Impact 

>0.5dv (1996, 

2001, 2002)

March 3, 2006 48
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Figure 23. Comparison of 98th percentile daily change in visibility values (delta-deciviews). The 

highest value is compared to the contribution threshold of 0.5 deciviews.

March 3, 2006 49
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Table 3. Summary report with results from the Division’s 98th percentile postprocessor 

(BART98_v3) that correspond to the maximum delta-deciview value from Table 2. The 98th

percentile value from “Method 1” (in bold) corresponds to the method recommended by U.S. EPA.

Title from CALPOST: 

APCD BART - Mt Zirkel WA (MOZ); 2/22/06 v1_so2at0.16NOxat0.34_mnitrate1ppb 

MVISBK=6; EPA2003 centroid monthly f(RH); EPA2003 20%bestdays natural backgrd 

2002 36km MM5, 4km CALMET, hourly ozone; BART-eligible source= CRAIG 

Days processed: 364 

Receptors processed: 253 

CALPOST species: ALL 

Contribution threshold: 0.5 

Summary of delta-deciview results: 

The 'High 1st High' from the model is: 3.489 dv 

 Number of days 'High 1 High' delta-deciview => 0.5: 199 

 Number of days 'High 1 High' delta-deciview => 1.00: 96 

98th Percentile Results: 

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

Method 1. DAY-SPECIFIC - closest modeled value: 

 The ' 8 High' value from the model is: 2.689 dv

 at receptor 3021 on day 118(2002) 

Method 2a. RECEPTOR-SPECIFIC - closest modeled value: 

 The 'High 8 High' value from the model is: 2.041 dv 

 at receptor 2868 on day 325(2002) 

 Number of days with delta-deciview => 0.5: 198 

 Number of days with delta-deciview => 1.00: 95 

Method 2b. RECEPTOR-SPECIFIC - Weighted Average at X[(n+1)p]: 

 The calculated 98th percentile value 

 using a weighted averaging method is: 2.050 dv 

 at receptor 2868 

 using days 12(2002) and 325(2002) 

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

March 3, 2006 50
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Figure 24. Distribution of delta-deciview values used to generate the maximum 98th percentile value. 

YEAR DAY RECEPTOR DV(Total) DV(BKG) DELTA DV F(RH) %_SO4 %_NO3 %_OC %_EC %_PMC %_PMF

2002 359 2948 5.463 1.974 3.489 2.1 13.11 85.07 0 0 0 1.82

2002 38 2880 5.175 1.996 3.179 2.2 14.75 84.68 0 0 0 0.57

2002 335 3075 4.907 1.974 2.932 2.1 9.33 89.78 0 0 0 0.89

2002 34 3075 4.894 1.996 2.898 2.2 14.56 84.88 0 0 0 0.56

2002 332 2880 4.84 1.974 2.866 2.1 11.01 86.83 0 0 0 2.16

2002 30 2855 4.749 1.996 2.753 2.2 10.62 85.03 0 0 0 4.34

2002 293 2949 4.653 1.93 2.723 1.9 20.07 79.15 0 0 0 0.77

2002 118 3021 4.663 1.974 2.689 2.1 11.02 84.89 0 0 0 4.08

2002 145 2852 4.457 1.996 2.461 2.2 13.94 83.72 0 0 0 2.34

2002 124 2855 4.32 1.996 2.324 2.2 7.85 87.48 0 0 0 4.67

2002 344 3011 4.285 1.974 2.311 2.1 9.64 89.05 0 0 0 1.31

2002 360 2868 4.242 1.974 2.268 2.1 8.63 87.81 0 0 0 3.56

2002 298 3075 4.092 1.93 2.162 1.9 10.59 86.24 0 0 0 3.17

2002 341 3075 4.075 1.974 2.101 2.1 9.22 89.47 0 0 0 1.31

2002 84 3075 4.042 1.952 2.09 2 11.32 86.58 0 0 0 2.1

2002 12 2868 4.05 1.996 2.054 2.2 11.58 87.69 0 0 0 0.73

2002 325 2868 4.016 1.974 2.041 2.1 10.67 87.59 0 0 0 1.73

2002 137 2855 4.013 1.996 2.017 2.2 11.59 86.75 0 0 0 1.66

2002 326 2915 3.976 1.974 2.002 2.1 9.79 89.47 0 0 0 0.74

2002 255 3011 3.94 1.952 1.988 2 9.08 87.74 0 0 0 3.18

2002 85 2852 3.91 1.952 1.958 2 12.86 84.85 0 0 0 2.28

2002 292 2855 3.878 1.93 1.948 1.9 20.83 77.8 0 0 0 1.37

2002 51 2852 3.94 1.996 1.944 2.2 5.78 89.7 0 0 0 4.52

2002 297 3032 3.832 1.93 1.901 1.9 12.23 83.26 0 0 0 4.51

2002 302 2915 3.83 1.93 1.9 1.9 10.98 85.65 0 0 0 3.36

Figure 25. Top 25 delta-deciview (DELTA DV) values from the Mt Zirkel Wilderness Area for the 

year with the highest 98th percentile value.

March 3, 2006 51
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

7. References 

Colorado Department of Public Health and Environment. “Operating Permit 96OPMF155 for 

Tri-State Generation & Transmission Association Craig Station Units 1 And 2.” May 1, 2005. 

CH2M HILL. “Application for Permit to Construct Unit 3, Comanche Generating Station, 

Pueblo, Colorado.” Submitted by Public Service Company of Colorado, Prepared by CH2M 

HILL, January 2005. 

Escoffier-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, Norfolk, VA, Amer. Meteor. Soc, J5.13. 

Douglas, S. and R. Kessler, 1988. User's Guide to the Diagnostic Wind Model (Version 1.0). 

Systems Applications, Inc., San Rafael, CA. 

“Federal Land Manager’s Air Quality Related Values Workgroup (FLAG): Phase I Report,” 

U.S. Forest Service, National Park Service, U.S. Fish and Wildlife Service, December 2000. 

“Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule.” EPA454/B-03-005. September 2003. 

“Guidance for Tracking Progress Under the Regional Haze Rule.” U.S. EPA, EPA-454/B-03-

004. September 2003. 

“Interagency Workgroup on Air Quality Modeling (IWAQM) Phase 2 Summary Report and 

Recommendations for Modeling Long Range Transport Impacts.” EPA-454/R-98-019, 

December 1998. 

“Mt. Zirkel Wilderness Area Reasonable Attribution Study of Visibility Impairment. Volume 

II: Results of Data Analysis and Modeling - Final Report.” Prepared by John G. Watson, et al, 

Prepared for Colorado Department of Public Health and Environment, 1996. 

“Northern Front Range Air Quality Study Final Report.” Prepared for Colorado State 

University, Prepared by John G. Watson, Eric Fujita, Judith C. Chow Barbara Zielinska 

(Desert Research Institute), L. Willard Richards (Sonoma Technology, Inc.), William Neff 

(NOAA), David Dietrich (Air Resource Specialists, Inc.), 1998.

Scire J.S., D.G. Strimaitis, R.J. Yamartino. “A User's Guide for the CALPUFF Dispersion 

Model.” Earth Tech, Concord, MA, January 2000. 

March 3, 2006 52
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Scire J.S., F. Robe, F.E.. Fernau, R.J. Yamartino. “A User's Guide for the CALMET 

Meteorological Model.” Earth Tech, Concord, MA, January 2000. 

March 3, 2006 53
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 54
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Appendix A – Natural Background Values 

March 3, 2006 55
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 56
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 57
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 58
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 59
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 60
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 61
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 62
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

Appendix B – Monthly f(RH) Values 

March 3, 2006 63
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis for 

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 64
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis f

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 65
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis f

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 66
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis f

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 67
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis f

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 68
BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis f

Tri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised) 

Colorado Department of Public Health & Environment / Air Pollution Control Division 

March 3, 2006 69