# BART CALPUFF
Class I Federal Area
Individual Source Attribution Visibility Impairment Modeling Analysis
for
Tri-State Generation & Tr ansmission Association Craig Station Units 1 and 2 (Revised)

March 3, 2006

Colorado Department of Pub lic Health & Environment

Air Pollution Control Division 4300 Cherry Creek Drive South Denver, Colorado 80246BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 iiBART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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. M ODELING P ROCESS O VERVIEW ....................................................................................................................8

2.2. V ISIBILITY C ALCULATIONS .............................................................................................................................8

3. SOURCE DESCRIPTION

............................................................................................................................... ...10

4. EMISSION ESTIMATES

............................................................................................................................... ....11

5. CALMET/CALPUFF MOD ELING METHODOLOGY ................................................................................14

5.1. CALMET/CALPUFF M ODEL S ELECTION ...................................................................................................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 N on-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. 98 th Percentile Methods

............................................................................................................................... .. 44

6. RESULTS

............................................................................................................................... ..............................46

6.1. R ESULTS

............................................................................................................................... ........................47

7. REFERENCES

............................................................................................................................... .....................52

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

Colorado Department of Public Health & Environment / Air Pollution Control Division March 3, 2006 iiiBART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 ivBART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 Av ailable Retrofit Technology (BAR T) for any BART-eligible source that ‘‘emits any air polluta nt which may reasonably be anti cipated to cause or contribute to any impairment of visibility” in any mandato ry Class I federal area. Pursuant to federal regulations, states have the option of exem pting a BART-eligible source from the BART requirements based on dispersion modeling demonstr ating that the source cannot reasonably be anticipated to cause or cont ribute to visibility impa irment in a Class I area.

The Division has proposed state regulations establishing criteria and procedures for determining which Colorado sources will be subj ect 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 Di vision 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 (B ART guideline), a BART-eligible source is considered to “contribute” to visibility impa irment in a Class I area if the modeled 98 th
percentile change in deciviews is equal to or greater than the “cont ribution threshold.” Any BART-eligible source determined to cause or cont ribute to visibility impairment in any Class I area is subject to BART. In th is report, the Division used a “contribution threshold” of 0.5 deciviews, as prescribed by the regula tory proposal pending before the Commission.

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

data to determine if the 98 th percentile 24-hour change in visi bility (delta-dec iview) from a BART-eligible source is equal to or greater th an a contribution thresh old 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 SO 2 , NOx, and direct PM10 emissions from all BART-eligible units at a given facility.

While the modeling results in th is 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 mode ling performed by the source operator will be subject to Division review and approval. Mo reover, the contributi on threshold and other criteria used for this modeling demonstration ha ve not been finalized and may change in the final rule adopted by the Commi ssion. Therefore, the results in this report are not a final agency action. Any source that the Division dete rmines 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 crit eria and procedures for determining which sources will be subject to the BART requirement.

The maximum 98 th percentile delta-deciview value from Craig Station Units 1 and 2 at any Class I federal area is 2.689 deciviews, assu ming natural background conditions and monthly

March 3, 2006 1BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 contri bution 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 c ontribution threshold of 0.5 deciviews.

March 3, 2006 2BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 Av ailable Retrofit Technology (BAR T) for any BART-eligible source that ‘‘emits any air polluta nt which may reasonably be anti cipated to cause or contribute to any impairment of visibility” in any mandato ry Class I federal area. Pursuant to federal regulations, states have the option of exem pting a BART-eligible source from the BART requirements based on dispersion modeling demonstr ating that the source cannot reasonably be anticipated to cause or cont ribute to visibility impa irment in a Class I area.

Federal regulations implementing the BART requ irement afford states some latitude in the criteria in determining whether a BART-eligible source is subject to BART. The Division has proposed state regulations estab lishing 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 CALPU FF 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 (B ART guideline), a BART-eligible source is considered to “contribute” to visibility impair ment in a Class I area if the modeled 98th percentile change in deciviews is equal to or greater than the “cont ribution threshold.” Any BART-eligible source determined to cause or cont ribute to visibility impairment in any Class I area is subject to BART. The Division ha s proposed a state regul ation establishing a

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

is 0.5 deciviews.

The Division has applied the CALPUFF modeling system with three y ears of meteorological data to determine if the 98th percentile 24-hour change in visibility (delta-decivi ew) from a BART-eligible source is equal to or greater th an a contribution thresh old 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 SO 2 , NOx, and direct PM10 emissions from all BART-eligible units at a given facility.

While the modeling results in th is 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. A ny subsequent modeling performe d by the source operator will be subject to Division review and approval. Moreover, the c ontribution threshold and other criteria used for this modeling demonstration ha ve not been finalized and may change in the final rule adopted by the Commi ssion. Therefore, the results in this report are not a final agency action. Any source that the Division dete rmines 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 crit eria and procedures for determining which sources will be subject to the BART requirement.

March 3, 2006 3BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 guidelin e 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 S OURCES “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 Cla ss I area. If you decide to ma ke 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 cont ribute to visibility impairment in at least one Class I are a. 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 indi vidual 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 dete rminations 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 discu sses several approaches that you can use to exempt sources from the BART determ ination process.

A. What Steps Do I Follow to Determine Whether A Source or Group of Sources Cause or Contribute to Visibility Im pairment for Purposes of BART?

1. How Do I Establish a Threshold? One of the first steps in determining whethe r sources cause or contribute to visibility impairment for purposes of BART is to est ablish 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 t hus be subject to BART.

Because of varying circumstances affecting different Class I areas, the appropriate threshold for determinin g 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 de termining whether a source “c ontributes” to visibility impairment should not be hi gher than 0.5 deciviews.

In setting a threshold for “c ontribution,” you should consid er the number of emissions sources affecting the Class I areas at issue and the magnitude of the individual sources’

March 3, 2006 4BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 particu late matter (PM) emissions in determining

whether sources cause or contribute to visibility impairment, including both PM10 and PM2.5. Consistent with the approach for iden tifying your BART-eligible sources, you do

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

As explained in section II, you must use your best judgement to de termine whether VOC or ammonia emissions are likely to have an im pact on visibility in an area. In addition, although as explained in Secti on II, you may use PM10 an indicator for particulate matter in determining whether a source is BART e ligible, in determining whether a source contributes to visibility im pairment, you should distinguis h between the fine and coarse particle components of direct particulate emissions. Although both fine and coarse particulate matter contribute to visibility im pairment, the long-range transport of fine particles is of particular concern in the form ation 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 emitte d particulate matter (i.e. PM 10 vs. PM 2.5 ).

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 de termining 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 gui dance. You may also use other reasonable approaches for analyzing the visibility impacts of an individu al source or group of sources.

Option 1: Individual Source Attribution Approach (Dispersion Modeling) You can use dispersion modeling to determine that an individual s ource cannot reasonably be anticipated to cause or cont ribute to visibility impairment in a Class I area and thus is not subject to BART. Under this option, y ou can analyze an indivi dual source’s impact on visibility as a result of its emissions of SO 2 , NO
x and direct PM emissions. Dispersion modeling cannot currently be us ed 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 5BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 visibili ty and should therefore be subject to BART review, as explained in section II.A.3. above.

You can use CALPUFF 7 or other appropriate model to pred ict 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 sour ce’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 th e visibility assessments addressed in today’s rule, to account for the ch emical transformation of SO 2 and NO

x .

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

model: 1. Develop a modeling protocol.

Some critical items to include in the protocol are the mete orological and terrain data that will be used, as well as the source-specific information (stack height, temperature, exit velocity, elevation, and emission rates of applic able 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 Impacts 9 for parameter settings and me teorological data inputs. You may use other settings fr om those in IWAQM, but you sh ould 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 eff ects of the source. Fo r other Class I areas in relatively close proximity to a BART-elig ible 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 lo cate 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 expect ed plume release height. If the highest modeled effects are observed at the nearest Cl ass I area, you may choose not to analyze the other Class I areas any further as add itional 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 Ag ency, EPA-454/R- 98-019, December

1998.

March 3, 2006 6BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 recepto rs 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 situati on may call for the use of two different modeling approaches for the same Class I ar ea 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 sour ce-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, y ou 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 accep ted protocol and compare the predicted visibility impacts with your threshold for “contribution.”

You should calculate daily visibility values fo r each receptor as the change in deciviews compared against natural visibility c onditions. 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 calcula tion. To determine whether a source may reasonably be anticipated to caus e 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 norma l effects than would be typical of most facilities. We recommend that States use the 24 hour average actual em ission 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 98 th percentile value from your modeling is less than your contribution threshold, then you may conclude

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

March 3, 2006 7BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 SO 2 , NOx, and/or direct PM10, the constant

emission rates shown in section 4 are used in the CALPUFF mode ling system to estimate the daily change in visibility compared against natural background conditi ons (delta-deciview) at each Class I federal area in the modeling domain. The 98 th percentile delta-deciview value at each Class I area is compared to the “contribu tion threshold” to determine if the source contributes to visibility impairment.

The CALPUFF 1 modeling system consists of CALMET, CALPUFF, and CALPOST. CALMET is the meteorological model that gene rates hourly three-dimensional meteorological fields of variables such as wind and temp erature. CALPUFF simulates the transport, dispersion, and transformation of pollutants emit ted from the source and calculates hourly concentration and/or deposition flux values at each receptor in the modeling domain. CALPOST calculates time-averaged concentrat ion 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 fe deral documents, including:

 “Interagency Workgroup on Air Quality Modeling (IWAQM) Phase 2 Summary Report and Recommendations for Modeling Long Ra nge Transport Impacts” (IWAQM, 1998)

 “Federal Land Manager’s Air Quality Re lated Values Workgroup (FLAG): Phase I Report” (FLAG, 2000)

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

In general, visibility is charac terized 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 absorpti on by gases and particles.

Visibility is impaired when light is scattere d in and out of the line of sight and by light absorbed along the line of sight. The light extinction coefficient (b ext ) considers light extinction by scattering (b scat ) and light extinction by absorption (b abs ):

b ext = b scat + b abs

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

 light scattering due to air mol ecules = Rayleigh scattering = b rayleigh

 light scattering due to particles = b sp

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

 light absorption due to gaseous absorption = b ag

1 CALPUFF is a non-steady-stat e Lagrangian puff model.

March 3, 2006 8BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 = b ap

Particle scattering, b sp , can be expressed by its components:

b sp = b SO4 + b NO3 + b OC + b SOIL + b Coarse

where:

 b SO4 = scattering coefficient due to sulfates = 3[(NH 4 ) 2 SO 4 ]f(RH)

 b NO3 = scattering coefficient due to nitrates = 3[NH 4 NO 3 ]f(RH)

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

 b SOIL = scattering coefficient due to fine particles = 1[Soil]

 b Coarse = scattering coefficient due to co arse particles = 0.6[Coarse Mass]

Particle absorption from soot is defined as:

 b ap = absorption due to elem ental carbon (soot) = 10[EC]

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

numeric coefficient at the be ginning 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:

b ext = b SO4 + b NO3 + b OC + b SOIL + b Coarse + b ap + b rayleigh

In this equation, the sulfate (SO4 ) and nitrate (NO3) components are referred to as hygroscopic components because the extinction coeffici ent 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 concentrat ion estimates from CALPUFF are used with the previously shown equations to calc ulate the extinction coefficient.

As described in the IWAQM Phase 2 Report, the change in visibility is compared against background conditions. The delta-deciview, Δ dv, value is calculated from the source’s contribution to extinction, b

source , and background extinction, b background , as follows:

Δ dv = 10 ln ((b background + b

source )/ b background )

March 3, 2006 9BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 w ith a total net electric generating capacity of 1264 MW, consisting of three units, located at 21 01 S. Ranney, in Craig. Un its 1 and 2, rated at 4,318 mmBtu/hour each (net 428 MW), are BART-e ligible 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 em issions and limestone scrubbers control SO 2 emissions. The units use low-NO

x burners to control NO

x emissions. In addition, over-fire air

and related NO

x control upgrades are in place to meet th e requirements of the Consent Decree (CDPHE, 2005).

March 3, 2006 10BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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, sh utdown, and malfunction be used, as such emission rates could produce higher than normal effect s than would be typical of most facilities. We recommend that States use the 24 hour aver age actual emission rate from the highest emitting day of the meteorological pe riod modeled, unless this rate reflects periods start-up, shutdown, or malfunction .”

Short-term emission rates ( ≤ 24-hours) for SO 2 , NOx, and PM10 (including condensible and

filterable direct PM10 2 ) 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 ra tes 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 emi ssion 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 calculate d 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 flexibil ity 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 avai lable, emissions rates based on averaging periods longer than 24- hours are acceptable only in cases where the mode ling shows that the source has impacts equal to or greater than th e contribution threshold.

For Craig units 1 and 2, the modeled emissi on rates are shown in Table 1. The stack parameters are based on the best available in formation in Division files. To simplify the emissions estimation process, only filterable PM10 emissions were used because modeling

with SO 2 , NOx, and filterable PM10 shows impacts equa l to or greater than the contribution

threshold. The basis for the emi ssion 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), orga nic aerosols (SOA), an d sulfate (SO4). H 2 SO 4 , for example, is a PM10 species emitted from coal-fired units that is typically modeled as SO4 in CALPUFF.

March 3, 2006 11BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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

 SO 2 : 0.160 lb/mmBtu heat input on a 30 da y rolling average - January 2001

Consent Decree

 NOx: 0.34 lbs/mmBtu heat input when bur ning 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

SO 2 Rate (30-day) 0.16 lb/mmBtu SO 2 Rate 87.05 g/s

NO X Rate (3-hr) 0.34 lb/mmBtu NO X Rate 184.98 g/s

PM 10 Rate (filterable only) 0.03 lb/mmBtu PM 10 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 12BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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

SO 2 Rate (30-day) 0.16 lb/mmBtu SO 2 Rate 87.05 g/s

NO X Rate (3-hr) 0.34 lb/mmBtu NO X Rate 184.98 g/s

PM 10 Rate (filterable only) 0.03 lb/mmBtu PM 10 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 13BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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/CA LPUFF 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 th ree additional Class I areas. It has al so been modified as necessary to account for PM10 speciation. An additional post- processing step with POSTUTIL has been added to implement ammonia limiting. The CA LPOST model setup was changed to make it consistent with the U.S. EPA’s BART guideline. In addition, the Divisi on reviewed available data to determine appropriate ammonia backgr ound values for various parts of Colorado. The Division also performed sensitivity tests to understand the response of th e model to changes in ammonia background concentration levels. Since the currently av ailable version of CALPOST does not generate 98 th percentile results, the Division modi fied CALPOST to generate a file with a full distribution of daily delta-decivi ew values for each receptor. In addition, the Division wrote a FORTRAN processor to generate 98 th percentile results.

This report is intended to provi de sufficient technical documenta tion 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 kilomete rs 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 pr ovide more accurate results for Class I areas beyond 300km.

According to “ Interagency Workgroup on Air Qualit y Modeling (IWAQM) Phase 2 Summary Report and Recommendations for Modeli ng Long Range Transport Impacts ” (IWAQM Phase 2 Report): In the context of the Phase 2 recommendation, the fo cus of the visibility analysis is on haze. These techniques are applicable in the range of thirty to fifty kilo meters and beyond from a source. At source-receptor distanc es 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 meteor ological fields are complex and the use of CALPUFF appears to be appropria te 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 dist ance, PLUVUEII would be an appropriate model to consider for source-to-receptor distances less than 50 kilometers.

March 3, 2006 14BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 (v ersion 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 tran sport 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 transpor t, 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 Mode l (Douglas, S. and R. Kessler, 1988). It has been significantly enhanced by Earth Tec h, Inc (Scire, 2000). For this particular study, the model uses a Lambert Conformal Projecti on coordinate system to account for the

Earth's curvature.

CALMET uses a two-step approach to calculate wind fields. In the fi rst step, an initialguess wind field is adjusted for slope flows and terrain blocki ng effects, for example, to produce a Step 1 wind field. In the second ste p, an objective analysis is performed to

introduce observationa l data into the Step 1 wind field.

In this application, the initial guess wind fields are based on 36-kilometer MM5 3
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 Pub lic Service Company (PSCo) Comanche Unit 3 PSD permit application. Alpi ne 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 th e exact number of years of mesoscale meteorological data for use in CALPUFF. A ccording to 40 CFR Part 51 Appendix W, the length of the modeled meteorol ogical 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 th at consecutive years from the most recent, readily available 5-year period are preferred. However, “less th an five, but at least three,

3 Fifth-Generation NCAR/Pen n State Mesoscale Model.

March 3, 2006 15BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 199 2 MM5 data sets, use of the coarse resolution 1990 and 1992 data sets would not imp rove 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 HI LL, the Standard Pa rallels 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 list ed 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 Co lorado with the excep tion 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 98 th percentile values for this analysis. The domain does

not include Class I areas in a ny nearby states because the 98 th percentile impacts from Colorado’s BART-eligible sources are expe cted 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 longitudina l and meridonal directions, respectively, with 4-kilometer CALMET grid cells.

March 3, 2006 16BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 examin ed vector plots of selected periods within the CALMET output for validation of the wind fields with the CalDESK (Environmodeling Ltda.) program (CH2M HI LL, 2005).” The Division replicated the CALMET modeling and performed additional re view of the meteorological fields

with the Lakes Environmental CALPUFF View software package. In general, the meteorological fields were found to be reasonable given th e 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 17BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 el evations 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 18BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 19BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 w ith 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 an alyses of soundings for summer ozone events. The analysis suggests mixing he ights in Denver are often well above the

CALMET default value of 3000 meters duri ng 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, incl uding 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 exceed ed at Rocky Mountain National Park, suggests the mixing height was probabl y 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 mixi ng 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 f eet (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 20BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 de termine the relative weight given to the vertically extrapolated surface meteorol ogical observations and upper air soundings. The initial guess field is computed with an inverse distance wei ghting of the surface and upper air data. It can be modified by th e 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 de fault 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 ski pped if the surf ace station is close to the upper air stati on. The variable RMIN2 sets the distance between an upper

air station and a surface stati on that must exceeded in order for the extrapolation to take place. RMIN2 has been set to the de fault 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 ai r stations is ignored. When IEXTRP= ± 4, the van Ulden and Holtslag wind extrapolat ion method is used. The method uses similarity theory and observed data to ex tend 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 dete rmine the influence of observations in the Step 1 wind field. R1 controls weighti ng 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 firs t 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 distan ce 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 st ations shown in Figure 6 were used, including Alamosa (ALS), Colorado Springs (CYS), Denver (DEN), Eagl e (EGE), Limon (LIC), Pueblo (PUB), Trinidad (TAD), Cheyenne (CYS), Laramie (LAR), Rocky Mountain NP (ROM), and Gothic (GTH).

March 3, 2006 21BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 U pper Air Stations Two upper air stations were include d: Grand Junction and Denver.

5.1.1.11. CALMET Preci pitation Stations CH2M HILL obtained precipitation data fr om the National Climatic Data Center (NCDC). All available data in fixed-le ngth, TD-3240 format were ordered for the modeling domain. CH2M HILL processe d the data with the PXTRACT and PMERGE processors. Stations with incomple te or poor quality data for a given year

were excluded. The number of stations us ed 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 22BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 23BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 el even 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 Cl ass 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 remaini ng 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 24BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 identi cal to the CALMET modeling domain.

March 3, 2006 25BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 chemi cal reaction mechanism (MCHEM=1) is

used for the conversion of SO 2 to sulfate (SO4) and NOx to nitrate (NO4). Refer to

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

In the MESOPUFF II mechanism, the amm onia background concentration affects the equilibrium between nitric acid, ammonia, and ammonium nitrate. The equilibrium

constant for the reaction is a non-linear func tion of temperature and relative humidity (Scire, 2000). Unlike sulfate, the calculated nitrate concentration is limited by the amount of available ammonia, which is pr eferentially sc avenged 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 SO 2 to sulfate, the aqueous phase me thod, which is important when the plume interacts with clouds and fog, can significantly unde restimate sulfate formation. In this report, as recomm ended by the IWAQM Phase 2 report, the “nighttime SO 2 loss rate (RNITE1)” is set to 0.2 percent per hour. The “nighttime

March 3, 2006 26BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 HNO 3 formation rate (RNITE3)” is set to 2.0 percent per hour.

According to the 1996 “Mt. Zirkel Wilder ness 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

SO 2 to sulfate and NO X

to total nitrate. There are two options for specifying these transformation rates:

Option 1: An internal calculation of ra tes based on local values for several controlling variables (e.g., solar radiation, background ozone, relative humidity, and plume NO X ) as used in MESOPUFF-II. The parametric tr ansformation 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 Assessm ent study. They found that it provided physically plausible responses to many of th e controlling environmental parameters. However, the mechanism had no temperatu re dependence, which is an important factor in the Rocky Mountain region where ther e are wide variations in temperature. Furthermore, the MESOPUFF-II transform ation scheme was based on box model simulations for conditions more representative of the East ern U.S. than of the Rocky

Mountains.

The largest deficiency in the MESOPUFF-II chemical transforma tion algorithm is the lack of explicit treatment for in-cloud (aqueous-phase) enhanced oxidation of SO 2 to sulfate. The MESOPUFF-II chemical trans formation algorithm includes a surrogate reaction rate to account for aqueous-phase oxidation of SO 2 to sulfate as follows:

K aq = 3 × 10 -8 × RH 4 (%/hr) (B.2-1)

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

SO 2 oxidation rate will be 3% per hour. Me asurements in generating station plumes suggest spatially- and temporally-integrated SO 2 oxidation rates due to oxidants in

clouds to be 10 times this value.

Another issue is the amount of ammonia av ailable for nitrate chemistry. According to a paper by EarthTech (Escoffier-Czaja and Scire, 2002),

“In the CALPUFF model, total nitrate (T NO3 = HNO3 + NO3) is partitioned into each species according to the equilibri um 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 forma tion 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 discre te plume elements. The total concentration

March 3, 2006 27BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 acc ount for the total amount of sulfate scavenging ammonia from all sources (both project and ba ckground sources) and the total amount of TNO3 competing for the remaining ammoni a. In POSTUTIL, ammonia availability is computed based on receptor concentra tions of total sulfa te and TNO3, not on a puff-by-puff basis.”

Ammonia-limiting methods have been used fo r 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. Specifi cally, the use of the MNIRATE=1 option in POSTUTIL is acceptable. At this ti me, other ammonia-limiting methods, including iterative techniques that use observati onal data to resolve backward the thermodynamic equilibrium equation between NO 3 /HNO 3 for each hour to minimize available ammonia, are not acceptable. Generally, for regulatory CALPUFF modeling in Colorado, techniques that assu me the atmosphere is always ammonia poor are not acceptable, particul arly in eastern Colorado.

March 3, 2006 28BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 re sponse of the modeling system to background ammonia when a single point source with significant emissions of SO 2 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, SO 2 , NOx, and filterable PM10 emissi ons were modeled. The ammonia background value was varied from 0 to 100 ppb. In the northeast Colorado test case,

the SO 2 emission rate is about 3 times highe r than the NOx emission rate. In the northwest Colorado test case, the modele d NOx emission rate is about 4.4 times higher than the SO 2 rate.

In both cases, when the background ammoni a 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 SO 2 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 SO 2 emission rates relative to NOx and the way sulfate is produced in the MESOPUFF II chemical mechanism. Visibility impact s 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 impact s (delta-deciview) to ammonia backgrounds from 0 ppb to 100 ppb from a source with high SO 2 emissions relative to NOx.

March 3, 2006 29BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 nitr ate 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 2 nd 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 a nd 72.7% for the 100 ppb ammonia case.

For the 8 th high delta-deciview value, the contri bution 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 30BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 SO 2 emission rate, the change in visibility (delta-deciview) is not sensitive to the background a mmonia 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 ammoni a level is less than 1.0 ppb.

Figure 14. Sensitivity of CALPUFF visibility impact s (delta-deciview) to ammonia backgrounds from 0 ppb to 100 ppb from a source with high NOx

emissions relative to SO 2 .

March 3, 2006 31BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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. Ho wever, 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 extrapolat ing the results of these tests to other CALPUFF applications.

March 3, 2006 32BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 mechanis m 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 am monia rich. Thus, setting a domain-wide background is problematic. As discussed in the previous section, when modeling a single large source with high SO 2 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 particul ate nitrate is dependent on the ambient concentration of ammonia, which preferentially reacts with sulfate. The ambient ammonia concentration is an input to the model. Accura te specification of this parameter is critical to the accu rate estimation of particulate nitrate concentrations. Based on a review of ava ilable data, Langford et al. (1992) suggest that typical (within a factor of 2) bac kground values of ammonia are: 10 ppb for grasslands, 0.5 ppb for forest, and 1 ppb for ar id lands at 20 C. Langford et al. (1992) provide strong evidence that backg round levels of ammonia show strong dependence with ambient temper ature (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 l evels provided above, unless specific data are available for the m odeling domain that would disc redit the values cited. It should be noted, however, that in areas wh ere 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 ne utralized by available ammonium and is present in the form of a mmonium sulfate....The Northe rn Front Range is ammonia rich. There was sufficient ammonia, on mo st days during winter, to completely

neutralize available nitr ic acid (NFRAQS, 1998).”

For northeast Colorado, a background ammonia concentration of 30.4 μg/m 3 (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 met hod at the Brighton and Welby sites and with the filter-pack method (i.e., impregnated cellul ose-fiber filters behind Teflon-membrane filters) at the other s ites. Average ammonia concentrations

March 3, 2006 33BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 site s 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 we re 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 are a, site-to-site variations were more pronounced than seasonal or diurnal variat ions. 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 hi gher 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. Twen ty-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 re asonable, 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 concentr ations for ammonia were assumed

to be 0.5 μ g/m 3 and 30 ppb

v for ozone, consistent with me asured values at the Hayden

VOR site .” An ammonia co ncentration of 0.5 μ g/m 3 is about 0.7 ppb.

In the CALPUFF modeling section of the Mt Zirkel Study report, “The CALPUFF default value for backgr ound ammonia concentrations of 10 ppb was also considered far too high as a re presentative area-average. Measurements from the Buffalo Pass and Gilpin Cre ek sites were used to adjust ammonia concentration to episod e and site-mean values.”

Based on a review of CALUFF files used for the Mt. Zirkel Study, for the August simulations, the assumed ammonia b ackground (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 s ection, for sources lo cated in northeast Colorado and along the South Platte Ri ver, a domain-wide ammonia background

March 3, 2006 34BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 lo cated 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 prov iding the ozone background data: (1) a single, typical background value appropria te for the modeling region, or (2) hourly ozone data from one or more ozone mon itoring stations. The second and preferred option requires the creation of the OZON E.DAT file containing the necessary data. For the Demonstration Assessment, th e domain was large (700 km by 1000 km) such that the second option was necessa ry. The IWAQM does not anticipate such large domains as being the typical applica tion. Rather, it is anticipated that the more typical application will involve dom ains of order 400 km by 400 km or smaller. But even for smaller domains, th e ability to provide at least monthly background values of ozone is deemed de sirable. The problem in developing time (and perhaps spatial) varying backgr ound ozone values is having access to representative background ozone data. Oz one 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 expe rienced by plumes undergoing long range

transport.

In this study, “ CH2M HILL obtained hourly ozone dat a from the following stations located within the modeling domain fo r 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 Co llins 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 35BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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-proce ssed with a modified version of CALPOST (version 5.51_CO_v3, level: 030709), POSTUT IL (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 fo r 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 va lues) for the individual species that contribute to the overall delta-deciview value, but thes e values are not used for the subject-to-BART modeling. Otherwise, the CALPOS T code modification consists of a “write” statement and supporting code. It outputs all da ily delta-deciview values for ev ery receptor to a file called

“deciview24.dat.” The 98 th percentile values are com puted from “deciview24.dat” by a separate FORTRAN processor (BART98_v3) writ ten by the Division spec ifically 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 emi ssions is expected to be relatively small compared to visibility impairment caused by SO 2 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 cons idered: 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 b ackground light extincti on, MVISBK has been set to 6. That is, monthly RH adjustment factors are applied di rectly to the background and modeled sulfate and nitrate concentrations, as recomme nded by the BART guideline. The RHMAX parameter, which is the maximum relative hum idity 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 percen t 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 estimate d baseline is likely to be reasonably

conservative and consistent with the goal of natural conditions (70 FR 39125).

The method for estimating natural ba ckground is presented in section 5.1.3.1 . Specifically, for hygroscopic components, BKSO4 in CALPOS T 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 com puted specifically for the Colorado Class I areas in the modeling domain.

March 3, 2006 36BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 (equivale nt to [BKSOIL]) portions of natural background for the best 20% vi sibility days (Best Days) at all Class I areas in Colorado's BART modeling. These concen trations, [BKSO4] and [BKSOIL], are used in CALPOST with monthly relative humidity adjustment factors (f(RH)) to determine monthly natural background visibi lity 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 Cla ss I area using the area's annual f(RH) and average natural concentrations base d on the area's geographic location (east versus west). Annual average back ground 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 con centrations are provided for determining extinction for the 20% best visibility days.

For background extinction computati on methods 2, 3, and 6 in CALPOST, background extinction is calcula ted with user-supplied m onthly concentrations of SO4, NO3, PM coarse, organic carbon, soil, and elemental carbon species. In practice, concentrations for only 2 speci es, SO4 ([BKSO4]) and soil ([BKSOIL]), are supplied in the CALPOST input file to represent hygroscopic and nonhygroscopic portions of backgr ound extinction, respectively.

To determine background extinction for the BART analysis with CALPOST, average natural concentrations that repr esent 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 CA LPOST, 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 37BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 aver age background (dv) based on monthly background extinction (1/Mm) for each Cla ss I area in Colorado's BART modeling using the following equations:

1. Monthly background extinction in 1/Mm (bext month ) = 3[BKSO4] best20 f(RH) + [BKSOIL] best20 + Rayleigh 2. Annual average background extinction in 1/Mm (bext annual_ave ) = (bext Jan + bext Feb + ... + bext Dec )/12

3. Calculated Best Da ys in dv = 10ln(bext annual_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-hygrosco pic ([BKSOIL]) values determined yielded the lowest sum of the absolute di fferences between the published Best Days (dv) and calculated Best Days (dv) for all Class I areas in the analysis:

where: n = number of Cl ass I areas in analysis

The "hygro (3[BKSO4])" and "non-hygr o ([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 decivi ews or less of the annual 20% best visibility days back ground values recommended by EPA. For CALPOST, the hygroscopic component of ex tinction is divided by 3 (the extinction coefficient of sulfate and nitrate) a nd input as BKSO4 (i.e., BKSO4 = 0.268/3 = 0.0893). The non-hygroscopic component is us ed directly (i.e., BKSOIL = 1.620).

March 3, 2006 38BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 calc ulated in Microsoft Excel using the "solver add-in" tool for optimi zation and equation solving.

March 3, 2006 39BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 perf ormed (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 partic ulate emissions are speciated into PMF, PMC, EC, SOA, and SO 4 and explicitly incl uded as species in CALPUFF. Emission rates for each sp ecies 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 parame ters (example #1 setup).

March 3, 2006 40BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 comput e the partition for the total concentration fields with MNITRATE=1 and the appropriate a mmonia background concentration. The ammonia background concentration, BCKNH3, in POSTUTIL is the same as the background value pres ented 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 pa rameters for cases with nitrate partitioning and speciated PM10 concentrat ions (example #1 setup).

March 3, 2006 41BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 speci es 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 reallo cated 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 opport unity 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 simulati ons where PM10 is divided into SOIL and EC species (example #2 setup).

March 3, 2006 42BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 fiel ds with MNITRATE=1 and the appropriate ammonia background concentration. The ammonia background concentration, BCKNH3, in POSTUTIL is the same as th e 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 simu lations where ammonia limiting is performed using the output file generated from the POSTUTIL setup in Figure

20 (example#2 setup).

March 3, 2006 43BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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. 98 th Percentile Methods According the BART guideline:

... you should compare your “contribution” th reshold against the 98t h percentile of values. If the 98 th percentile value from your modeli ng is less than your contribution threshold, then you may conclude that the source does not contri bute to visibility impairment and is not subject to BART. (70 FR 39162)

The BART guideline does not contain a specific method for calculating the “98 th
percentile value” and CALPOST vers ion 5.51 does not generate a 98 th percentile delta-deciview value. Consequently, the Division developed a FORTRAN program (BART98_v3) to compute 98 th percentile results. The program implements several methods because, at the time the code wa s written, U.S. EPA had not yet specified an explicit method for determining the 98 th percentile value.

The U.S.EPA recommends using the 98 th percentile value from the distribution of values containing the highest modeled de lta-deciview value for each day of the simulation from all modeled receptors at a given Class I area. The 98 th percentile

delta-deciview value can be de termined in several ways:

 The 8th highest value for each year modeled

 The 3-year average of the annual 8 th high values

 The 22 nd 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 le vel of precision equal to the level of precision reported from CALP OST. Specifically, the 98 th percentile results are reported to three decimal places.

The Division’s processor BART98_v3 calculates the 98 th percentile value with the method recommended by U.S. EPA. The Divisi on refers to the method as the “dayspecific method” or “method 1.” The first st ep 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 unranke d format, the Division’s processor BART98_v3 outputs all daily delta-decivi ew 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 98 th percentile value from the

distribution of ranked mode led daily maximum values, irrespective of receptor location. For example, for a 365-day simulation, the 98 th percentile value would be

the 8 th highest modeled delta-deciview value from the list of ra nked delta-deciview values. That is, the top 7 days are igno red, even though the values being ignored may be at different receptors. Similarly, for a 3-year period, the 98 th percentile

would be the 22 nd highest modeled delta-deciview value.

March 3, 2006 44BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 98 th percentile values using the “receptorspecific method” or “method 2.” This method, which calculates 98 th 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 “8 th
high” (for one year) and “22 nd 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 “n th high” value from the distribution of data. The 8 th high

and 22 nd 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 St andards for PM2.5” – for determining 98 th
percentile values for PM2.5 monitoring. Thus , the Appendix N method is used in the processor. For the exact algorithm, s ee Appendix N, the BART98_v3 source code, or the BART98_v3 “readme” file.

March 3, 2006 45BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 incl ude eleven of the twelve Cla ss I areas in Colorado. Mesa

Verde was excluded because it is more than 300 km from all of the BA RT-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 98 th percentile values for this analysis. The modeling domain does not include Class I areas in any nearby

states because the maximum 98 th percentile impact from the Crai g Station is expected to occur

at a Class I area in Colorado.

The results for source-to-receptor distances be yond 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 ki lometers of the BART-eligible source.

March 3, 2006 46BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 y ears of meteorological

data to determine if the 98 th percentile 24-hour change in visi bility (delta-dec iview) from a BART-eligible source is greater than a contri bution threshold of 0.5 deciviews at any Class I area. This initial phase of the BART modeling process is referre d to as the “subject to BART” analysis. The modeling includes SO 2 , NOx, and direct PM10 emissions from all BARTeligible units at a given facility.

While the modeling results in th is 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 modeli ng is performed, it should be cons istent with recommendations in the Division’s modeling protocol. Any s ubsequent modeling performed by the source operator will be subject to Di vision review and approval. More over, the contribution threshold and other criteria used for this modeling de monstration have not been finalized and may change in the final rule adopted by the Commission. Therefore, th e 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 regula tions establishing criteri a and procedures for determining which sources will be subject to the BART requirement.

Table 2 and Figure 23 show the 98 th percentile daily delta-deciview values for each Class I area in the modeling domain. The 98 th percentile delta-deciview value is determined several

ways:

 The 8th highest value for each year modeled

 The 3-year average of the annual 8 th high values

 The 22 nd highest value for the 3-year modeling period The highest value from the methods above is compared to the cont ribution threshold. The contribution threshold has an implied level of pr ecision equal to the leve l of precision reported from CALPOST. Specifically, the 98 th percentile results are repor ted to three decimal places.

The maximum 98 th percentile delta-deciview value from Craig Station Units 1 and 2 at any Class I federal area is 2.689 deciviews, assu ming natural background conditions and monthly f(RH) values. The impact is above the contri bution 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 c ontribution threshold of 0.5 deciviews.

Table 3 shows the summary report generated by the Division’s 98 th percentile postprocessor (BART98_v3) for the maximum 98 th percentile value. Figure 24 and Figure 25 show the

distribution of delta-deciview values used to generate the maximum 98 th percentile value. Figure 24 shows the top 25 delta-decivie w values at the Class I federal area with the maximum impact from this BART-eligible source.

March 3, 2006 47BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 98 th percentile value, 98 th percentile values calculated with several methods, and the number of days the impact is eq ual to or greater than 0.5 deciviews for the entire period modeled.

2.689 BART-eligible source name:

1996 1 2001 2002 3-year Average

Flat To p s 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

Rock y 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

Ea g les Nest WA 1.560 1.106 1.211 1.292 1.260 109

Black Can y on 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

Modelin g 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 48BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 98 th percentile daily change in visibi lity values (delta-deciviews). The highest value is compared to the co ntribution threshol d of 0.5 deciviews.

March 3, 2006 49BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 result s from the Division’s 98 th percentile postprocessor (BART98_v3) that correspond to the maximum delta-deciview value from Table 2 . The 98 th
percentile value from “Method 1” (in bold) corr esponds 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 50BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 51BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 Associat ion 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 Servi ce Company of Colorado, Prepared by CH2M HILL, January 2005.

Escoffier-Czaja, Christelle and J. Scire, 2002. “The Effects of Ammoni a Limitation on Nitrate Aerosol Formation and Visibility Impacts in Class I Areas.” Earth Tech, Inc., Extended

abstract. 12th Joint Conference on the A pplications of Air Polluti on 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 Relate d 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 Re gional Haze Rule.” U.S. EPA, EPA-454/B-03- 004. September 2003.

“Interagency Workgroup on Air Quality M odeling (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 Attrib ution Study of Visibility Impairment. Volume II: Results of Data Analysis and Modeling - Final Report.” Prep ared by John G. Watson, et al, Prepared for Colorado Department of Public Health and Environment, 1996.

“Northern Front Range Air Qu ality Study Final Report.” Pr epared for Colorado State University, Prepared by John G. Watson, Eric Fujita, Judith C. C how Barbara Zielinska (Desert Research Institute), L. Willard Richards (Sonoma Technology, Inc.), William Neff (NOAA), David Dietrich (Air Reso urce 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 52BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 53BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 54BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 55BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 56BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 57BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 58BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 59BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 60BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 61BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 62BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 63BART CALPUFF Class I Federal Area Individual Source A ttribution Visibility Impairme nt 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 64BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis forTri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised)Colorado Department of Public Health & Environment / Air Pollution Control DivisionMarch 3, 200665BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis forTri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised)Colorado Department of Public Health & Environment / Air Pollution Control DivisionMarch 3, 200666BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis forTri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised)Colorado Department of Public Health & Environment / Air Pollution Control DivisionMarch 3, 200667BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis forTri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised)Colorado Department of Public Health & Environment / Air Pollution Control DivisionMarch 3, 200668BART CALPUFF Class I Federal Area Individual Source Attribution Visibility Impairment Modeling Analysis forTri-State Generation & Transmission Association - Craig Station Units 1 and 2 (Revised)Colorado Department of Public Health & Environment / Air Pollution Control DivisionMarch 3, 200669