# Technical Analysis for Arizona and Hawaii Regional **Haze FIPs :**  **Task 9**  **: Five** 

**- Factor**  **RP Analyses for**  **TEP Springerville, APS Cholla, TEP Sundt, CalPortland**  **Cement and Phoenix Cement Plants** 

Contract No: EP

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- 12 Version: 1

Prepared for: Thomas Webb Air Planning Office U.S. EPA Region 9 75 Hawthorne Street San Francisco, CA 94105

Prepared by: Uma Shankar

, Elizabeth Adams, Mohammad Omary

, Brian Naess and Sarav anan Arunachalam Institute for the Environment University of North Carolina at Chapel Hill

Mark Lee , Juanita Haydel and Thomas Meyers ICF International

Jim Staudt Andover Technology Partners

Date delivered : October 3 , 20 1 2EMAQ LOE (EPA Contract EP

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## Contents

Figures

................................ ................................ ................................ ................................ ........... iii

Tables

................................ ................................ ................................ ................................ ............ iv
Document Change Record

................................ ................................ ................................ .......... vi

1 Introduction

................................ ................................ ................................ ............................ 1

2 Work Performed and Deliverable Summary

................................ ................................ ...... 2
2.1 General Considerations for Visibility Modeling

................................ ............................. 2
2.2 Five

- Factor Analyses

................................ ................................ ................................ ...... 3 2.2.1 TEP Springerville Units 1 and 2

................................ ................................ .......... 4 2.2.2 APS Cholla Unit 1

................................ ................................ ............................. 10 2.2.3 TEP Sundt (Irvington) Units 1

- 3

................................ ................................ ..... 16 2.2.4 CalPortland Cement Rillito Plant Units 1

- 4

................................ .................... 22 2.2.5 Phoenix Cement Plant Unit 4

................................ ................................ ............ 29
2.3 Conclusions

................................ ................................ ................................ ................... 35

References

................................ ................................ ................................ ................................ .... 36
Appendix A
Emissions Data Tables
Appendix B Andover Technology Partners Report Chapter 5: Reasonable Progress AnalysisEMAQ LOE (EPA Contract EP

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## Figures

Figure 1. TEP Springerville Power Plant, Units 1 and 2

................................ ................................ 4 Figure 2. APS Cholla Power Plant

................................ ................................ ................................ 10 Figure 3. TEP Sundt (Irvington) Power Plant.

................................ ................................ .............. 17 Figure 4. Kilns at the CalPortland Cement Rillito Plant

................................ ............................... 23 Figure 5. Phoenix Cement Plant, Clarkdale, AZ

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## Tables

Table 1. CIAs Within 300 km of the Five RP Facilities.

................................ ................................ 2 Table 2. Springerville Power Plant Data

................................ ................................ ......................... 4 Table 3. NO x 

### Control Options Analysis for Springerville Units 1 and 2 (updated 9/30/2012)

...... 5 Table 4. Base and Control Sc enarios Used in Springerville RP Analyses

................................ ..... 6 Table 5. Stack Parameters for Springerville Units 1

- 4

................................ ................................ ... 7 Table 6. 98th percentile visibility impairment ( ∆

- dv) for Springerville base case and control scenarios: (a) IMPROVE Method 6(a); (b) IMPROVE Method 8(b).

.............................. 8 Table 7. Visibility Benefits (dv) for Springerville for the C ontrol Scenarios Corresponding to Table 6

................................ ................................ ................................ ............................... 8 Table 10. Cholla Unit 1 Data

................................ ................................ ................................ ........ 10 Table 11. NO x 

### Control Technologies for Cholla 1

................................ ................................ ....... 11 Table 12. Base and Control Scenarios Used in APS Cholla Unit 1 RP Analyses

........................ 12 Table 13. Stack Parameters for APS Cholla Units 1

- 4

................................ ................................ . 13 Table 14. 98 th 

### Percentile Visibility Impairment ( ∆

- dv) for Cholla 1 Base Case and Control Scenarios: (a) IMPROVE Method 6(a); (b) IMPROVE Method 8(b).

........................ 14 Table 15. Visibility Benefits (dv) for Chol la 1 for the Control Scenarios Corresponding to Table 14.

................................ ................................ ................................ ....................... 15 Table 16. Control Effectiveness (million $/dv) for the Calculation Methods of Table 14

........... 15 Table 17. Summary of Control Effectiveness for the Calculation Methods of Table 14

............. 16 Table 18. Sundt Power Plant Data

................................ ................................ ................................ 17 Table 19. NO x 

### Control Techhnologies for Sundt Units 1

- 3

................................ .......................... 18 Table 20. Base and Control Scenarios for NO x 

### Used in Sundt Units 1

- 3 RP Analyses

............... 19 Table 21. Stack Pa rameters for Sundt Units 1

- 3

................................ ................................ ......... 19 Table 22. 98 th 

### Percentile Visibility Impairment ( ∆

- dv) for Sundt Units 1

- 3 Base Case and Control Scenarios: (a) IMPROVE Method 6(a); (b) IMPROVE Method 8(b)

............ 20 Table 23. Visibility Benefits (dv) for S undt for the Control Scena rios Corresponding to Table 22

................................ ................................ ................................ ........................ 21 Table 24. Control Effectiveness (million $/dv) for the Calculation Methods of Table 22

........... 21 Table 25. Summary of Control Effectiveness for the Calculation Methods of Table 22

............. 22 Table 26. CalPortland Kiln Data

................................ ................................ ................................ ... 23 Table 27. Estimated Emissions and Production Rates for CalPortland Cement Kilns 1

- 4

........... 23 Table 28(a). NO x 

### Control Technologies for CalPortland Kilns 1

- 3

................................ ............. 24 Table 28(b). NO x 

### Control Technologies for CalPortland Kiln 4

................................ .................. 25 Table 29. Base and Control Scenarios for NO x 

### Used in CalPortland Units 1

- 4 RP Analyses

..... 26 Table 30. Stack Parameters for CalPortland Units 1

- 4

................................ ................................ . 26 Table 31. 98 th 

### Percentile Visibility Impairment ( ∆

- dv) for CalPortland Units 1

- 4 Base Case and Control Scenarios: (a) IMPROVE Method 6(a); (b) IMPROVE Method 8(b).

.... 27 Table 32. Visibility Benefits (dv) for CalPortland Units 1

- 4 for the Control Scenarios Corresponding to Table 31.

................................ ................................ .......................... 27 Table 33. Control Effectiveness (million $/dv) for the Calculation Methods of Table 31

........... 28 Table 34. Summary of Control Effectiveness for the Calculation Methods of Table 31

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### Table 35. Phoenix Cement Kiln Data

................................ ................................ ........................... 29 Table 36. Estimated Emissions and Production R ates for Phoenix Cement Kilns 1

- 4

................. 30 Table 37. NO x 

### Control Options for Phoenix Cement Kiln 4

................................ ........................ 31 Table 38. Base and Control Scenarios for NO x 

### Used in Phoenix Cement Unit 4 RP Analyses

... 32 Table 39. Stack Parameters for Phoenix Cement Kiln

................................ ................................ . 32 Table 40. 98 th 

### Percentile Visibility Impairment ( ∆

- dv) for Phoenix Cement Base Case and Control Scenarios: (a) IMPROVE Method 6(a); (b) IMPROVE Method 8(b).

........... 33 Table 41. Visibility Benefits (dv) for Phoenix Cement Kiln 4 for the Control Scenarios Corresponding to Table 40

................................ ................................ ........................... 33 Table 42. Control Effectiveness (million $/dv) for the Calculation Methods of Table 40

........... 34 Table 43. Summary of Control Effectiveness for the Calculation Methods of Table 40

............. 34 Table A

- 1(a). NO x 

### , SO 2 

### and PM emission inputs for base and control scenarios for TEP Springerville visibility modeling.

................................ ................................ ......... A

- 2 Table A

- 1(b). Speciated PM emission inputs for base and control scenarios for TEP Springerville visibility modeling.

................................ ................................ ............................... A

- 2 Table A

- 2(a). NO x 

### , SO 2 

### and PM emission inputs for base and control scenarios for APS Cholla Unit 1 visibility modeling.

................................ ................................ .................... A

- 3 Table A

- 2(b). Speciated PM emission inputs for base and control scenarios for APS Cholla Unit 1 visibility modeling.

................................ ................................ .................... A

- 4 Table A

- 3(a). NO x 

### , SO 2 

### and PM emission inputs for base and control scenarios for TEP Sundt Units 1

- 3 visibility modeling.

................................ ................................ ............... A

- 5 Table A

- 3(b). Speciated PM emission inputs for base and control scenarios for TEP Sundt Units 1

- 3 visibility modeling.

................................ ................................ ........................ A

- 5 Table A

- 4(a). NO x 

### , SO 2 

### and PM emission inputs for base and control scenarios for CalPortland Cement Units 1

- 3 and Unit 4 visibility modeling

................................ ............... A

- 6 Table A

- 4(b). Speciated PM emission inputs for base and control scenarios for CalPortland Cement Units 1

- 3 and Unit 4 visibility modeling

................................ ............... A

- 6 Table A

- 5(a). NO x 

### , SO 2 

### and PM emission inputs for base and control scenarios for Phoenix Cement Kiln 4 visibility modeling

................................ ................................ ....... A

- 7 Table A

- 5(b). Speciated PM emission inputs for base and control scenarios for Phoenix Cement Kiln 4 visibility modeling

................................ ................................ ..................... A

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## Document Change Record

Revision Date Remarks
0.1 October 3 , 2012 Draft version submitted to EPAEMAQ LOE (EPA Contract EP

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## 1 Introduction

This report describes the 5

- factor analyses of all technically feasible NO x 

### control options on the applicable units at the five facilities as listed below :

• TEP Springerville Units 1 and 2

• APS Cholla Unit 1

• TEP Sundt (Irvington) Units 1

- 3

• CalPortland Cement Rillito Plant Kilns 1

- 4

• Phoenix Cement Plant Kiln 4
The five factors considered in these analyses are as f ollows:

1. Cost of compliance; 2. E nergy and non

- air quality impacts of compliance; 3. A ny existing pollution control technology in use at each source ; 4. R emaining useful life of the source

, and 5. D egree of visibility improvement that may be reasonably expected from the use of emissions controls.
Andover Technology Partners (ATP) estimate d the cost of compliance for these units using EPA Control Cost Manual (EPA, 2002) , cost estimation methods based on the latest I ntegrated Planning Model [IPM] ) documented online by E PA (2010)

, and other reasonable engineering approaches . The control options were analyzed not only for th e feasibility of implementation but also the first four factors listed above to estimate the total cost per year of each control technology, and the co st of emission reductions in $/TPY for each

. Once all the feasibl e c ontrol options were identified, EPA reviewed and recommended control configurations on all applicable units to examine the visibility impact s of their emissions . UNC performed the se impact assessment s using the base configur ation of existing controls as well as all EPA

- approved control configurations for each BART facility at all Cla ss I Areas (CIAs) within a 300

- km radius through the use of dispersion modeling. Per EPA requirements t he se analys e s used the following models and processors

, and EPA

- provided meteorological inputs available from a previous BART analysis done by ENSR (2009) using CALMET version 5.8 :

• CALPUFF version 5.8 (v5.8) level 070623 puff dispersion model was used to estimate concentrations of visibility

- impairing pollutants emitted by each facility at the relevant CIA s.

• The POSTUTIL utility version 1.56 was used to adjust these concentrations for the phase

- partitioning of HNO 3 

### between gas and particle based on additi onal input information

.

• The adjusted concentrations were used in the CALPOST visibility post

- processor version 6.221 (v6.221) to calculate the visibility impairment in deciview (dv) relative to the background visibility at each CIA

. The change in deciview, or delta

- dv

, corresponding to the NO x 

### emission reduction for each control option relative to the base configuration was used along with the yearly cost of control to estimate the control option cost effectiveness in $/dv at each CIA, as a maximum of all the CIAs, and as a total over all the CIAs.EMAQ LOE (EPA Contract EP

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## 2 Work Performed and Deliverable Summary

In t he five

- factor analysis performed in this task ATP examined NO x 

### control options and their costs for each of the five facilities considering the first four factors listed in Section 1. These cost estimates have been used along with the visibility impact assessment s performed by UNC for each facility to estimate the control option effectiveness in a combined metric specified by EPA, namely, $/dv . The over arching considerations for the visibility impact assessments, including the CIAs that are potentially affect ed by these facilities are provided in Section 2.1

. T he five

- factor analyses for each plant are described in Section 2.2.



## 2.1 **General Considerations for Visibility Modeling** 

In Task 4 of this WA we used GIS software to determine the nearest distance s to the boundaries of CIAs within a 300

- km radius of the major emitting facilities in Arizona

. T he 19 CIAs and their nearest mean distances (as determined in the Task 4 screening) from the applicable fa cilities identified for Reasonable Progress analysis are listed in Table 1

. The domain description, Lambert Conformal grid specifications and meteorological inputs to CALPUFF required for this a nalysis are from CALMET v5.8 inputs and outputs provided by EPA from a BART analysis for 200 1

- 2003 performed by ENSR Corporation for the Navajo Generating Station (ENSR, 2009).

Table 1

. C IA s Within 300 k m o f the Five RP Facilities

.

CIA Short Name State Applicable Plant(s) from Nearest to Farthest Respective Avg. Near D istances (km)

Bandelier NM band NM Springerville 293 Bryce Canyon brca UT Phoenix 298 Capitol Reef care UT Cholla 294

Chiricahua NM chir AZ Sundt, CalPortland , Springerville 145

, 171 , 270

Chiricahua chrw AZ Sundt, CalPortland, Springerville 140

, 168 , 280

Galiuro gali AZ Sundt, CalPortland , S’ville, Cholla , Phoenix 63

, 71 , 222, 250

, 273

Gila gila NM Springerville, Cholla, Sundt, CalPortland 129 , 223

, 231 , 237 Grand Canyon grca AZ Phoenix , Cholla, Springerville 134 , 176, 286

Mazatzal maza AZ Phoenix, Cholla, CalPortland, Sundt, S’ville 55, 128, 170, 201

, 206

Mesa Verde meve CO Cholla 290 Mount Baldy moba AZ S’ville, Cholla, CalPortland, Sundt, Phoenix 62, 130, 223, 231, 246

Petrified Forest pefo AZ Cholla, Springerville, Phoenix , CalPortland 31, 61

, 190 , 290

Pine Mountain pimo AZ Phoenix , Cholla, CalPortland , S’ville, Sundt 52

, 150 , 214 , 231

, 246 Saguaro sagu AZ CalPortland, Sundt , Phoenix , S’ville, Cholla 10, 26

, 283

, 29 3

, 299

San Pedro Parks sape NM Springerville 273

Sierra Ancha sian AZ Cholla, Phoenix, CalPortland, S’ville, Sundt 127, 138, 153, 167, 178 Superstition supe AZ CalPortland, Sundt , Phoenix , Cholla , S’ville 108, 136 , 1 46

, 167 , 196 Sycamore Canyon syca AZ Phoenix , Cholla

, Springerville, CalPortland 13 , 146

, 253 , 287

Zion zion UT Phoenix 275EMAQ LOE (EPA Contract EP

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### The CALPUFF model set

- up for the five facilities followed the guidance of the modeling protocol that was initially delivered to EPA on March 19, 2012 as a Task 5 deliverable. This modeling protocol invokes almost all the model input settings provided in the WRAP BART Subject Protocol provided in its Appendix A. Differences in model set

- up from the recommendations of th e WRAP protocol due to the CALPUFF version used, or other direction from the EPA are noted in this protocol. UNC verified and reconciled any discrepancies in the CALPUFF inputs through a series of test runs. Of note, CALPUFF modeling used a constant value of 1 ppb throughout for ammonia per EPA guidance

. Further facility

- specific details on the visibility analysis performed under Task 9 are provided in Section 2.2

.


## 2.2 **Five**

**- Factor Analyses**  This section describes the control options analysis, followed by the details of the visibility modeling and the results of the five

- factor analysis for each facility. The visibility modeling used combinations of control technologies (control “scenarios”) s pecified by the EPA with respect to the emissions inputs , which were also provided by the EPA with extensive source documentation . The costs of compliance and visibility impacts for each scenario were estimated based on the following assumptions:

• The costs and emission reductions (in tons reduced) for the individual technologies that make up each control configuration are additive, i.e., the control scenario costs and emission reductions can be expressed, respectively, as the sum of the component technology costs, and the sum of the associated emission reductions (in tons reduced)

.

• The control efficiencies determined in the cost of control analyses are applicable to the baseline emission values used in the visibility modeling.

• The baseline periods used var y by source and unit, in order to account for differences in dates of installation of controls . This approach reflects a more realistic assessment of

“ existing pollution control technology in use at each source ” than using a uniform baseline for all units.

• The baseline emissions used in the CALPUFF modeling are not identical to those used in the control option s analyses because the BART Guidelines on which these analyses are based provide different methods for calculating baseline emissions for these two
pu rposes

.

• The baseline emission inputs for NO x 

### for the electricity generating facilities use the 24

- hour average emission rate from the highest emitting day of a representative most recently available baseline period (excluding start

- up, shutdown or malfunction). These data were extracted from the Clean Air Market Division ( CAMD ) Continuous Emission Monitoring System (CEMS) database

. CEMS data are also used for the cement kilns , as indicated by the Emission Inventory submittals.

• The baseline emission inputs for PM and SO 2 

### for purposes of visibility modeling are derived from the hourly plant heat input (from the CAMD CEMS database) multiplied by emission limits specified in ADEQ’s BART determinations for these units

.

• The control costs analys es use the annual average emission values in tons per year (TPY) based upon actual emissions from baseline period s that reflect future anticipated annual emissions

. Specifics of the emissions used and t he visibility impacts of base case and control scenarios are discussed in the sections on visibility and control effectiveness analysis for each facility.EMAQ LOE (EPA Contract EP

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### 2.2.1 TEP Springerville Units 1 and 2



## 2.2.1.1 General Plant Information Springerville power plant has four coal

- fired units. Units 3 and 4 have modern controls, and thus this analysis is focused on additional visibilty benefits that could be derived from controls on Units 1 and 2, shown in Figure 1

. These tangentially fired boilers (~ 400 MW each) have closely coupled overfire air (CCOFA) for NO x 

### control , and r ecent ly upgraded PM controls through the use of fabric filter s (FF ). SO 2 

### emissions from these units are also quite low through the use of dry Flue Gas Desulfurization (FGD); thus only NO x 

### controls are considered here

.

Figure 1

. TEP Springerville Power Plant, Units 1 and 2

Table 2

. Springerville Power Plant Data

Unit Capacity

Fuel 2008

- 2010 Reported Avg 2011 Reported Rates 2008

- 2011

NOx SO 2 NOx SO 2 Capac ity Factor
MW gross lb/MMBtu lb/MMBtu %
1 424.8 C 0.182 0.218 0.180 0.253 65%

2 424.8 C 0.190 0.185 0.188 0.167 70%



## 2.2.1.2 NO x 

## Control Options Analysis

2.2.1.2.1 Available NO x 

### Control Technologies
Springerville units have advanced combustion control technologies available (LNB and CCOFA). Thus additional NO x 

### contols may not be possible with combustion controls.EMAQ LOE (EPA Contract EP

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### 2.2.1.2.2 Feasible NO x 

### Control Technologies

Post

- combustion controls in the form of SNCR and SCR are both feasible for Springerville Units 1 and 2.



### 2.2.1.2.3 Evaluation of NO x 

### Control Technologies

For the cost estimates

, baseline emissions and capacity factors for all electric utility units were developed from historical data as follows:

• Baseline NO x 

### and SO 2 

### emission rates were from the 2008

- 2011 CAMD annual averages

.

• For SNCR the control efficiency was corrected to 30% per EPA feedback

, from the initial value 20%, consistent with ATP spreadsheet documentation for coal

- fired boilers

.

• For SCR the control efficiency was based on what is required to reduce the emission
factor from the baseline value (average of the 2008

- 2011 annual averages) to 0.05 lb/MMBtu, as reflected in Table 3 (72.4% for Unit 1 and 73.6% for Unit 2).

The estimated costs and control levels are shown in Table 3

. Table 3

. NO x 

### Control Options Analysis for Springerville Units 1 and 2 (updated 9/30/2012)

Springerville 1

– NOx Springerville 2

– NOx

SNCR SCR SNCR SCR
Capacity Factor 65% 65% 70% 70% Control Efficiency 30% 72%* 30% 74%*

Uncontrolled Rate
NOx Rate (lb/hr) 769 769 798 798 NOx Rate (lb/MMBtu) 0.18 0.18 0.19 0.19 NOx (TPY) 2189 2189 2448 2448

Controlled Rate
NOx Rate (lb/hr) 538 212 559 210 NOx Rate (lb/MMBtu) 0. 13 0.05 0. 13 0.05 NOx (TPY) 1532 605 1714 644

Tons/Year Removed 657 1584 734 1804 Total Cost, $/year $2, 494,309 $10,820,423 $2, 662

, 016 $10,976,219 $/Ton $ 3, 798 $6,829 $ 3,625 $6,085 $/Ton (incremental) $ 8,975 $ 7,774 * SCR is actually capable of 90% removal. The model that we used set a lower limit of 0.05 lb/MMBtu, but lower NOx levels should be achievable



### 2.2.1.2.4 Energy and Environmental Impacts of Control Options
Environmental impacts of SNCR and SCR are primarily due to ammonia slip. Generally, ammonia slip can be well controlled , and thus this is not a concern for adverse impacts on fly ash production. SCR will incur a dra ft loss that will increase parasitic loads of

~ 0.5% of plant output. SCR catalyst can be recycled and is theref ore not a significant concern.EMAQ LOE (EPA Contract EP

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## 2.2.1.3 Visibility Modeling

A ll four units at th is facility were included in the visibility modeling. T he baseline emiss ions and the control option scenarios were provided by EPA in spreadsheets 1



### , a nd included corrections to ATP’s reported control efficiencies as noted earlier and presented in the updated Table 3

. In the following sections we describe the inputs used for Sp ringerville , and the control effectiveness we estimated in $/dv for each of these control configuration s

. Table 4 provides the final list of control configurations , along with baseline emission values (converted to g/s from tons/day) to be used in the visibility modeling. The following specifications were provided for the emissions inputs by EPA:

• B aseline NO x 

### emission values were the maximum 24

- hr average emission rate selected from the highest emitting day during 2008

- 201 1 from CAMD for Un its 1 and 2.

• Units 3 and 4 used a constant NO x 

### rate specified by EPA

, corresponding to SCR and LNB controls for all scenarios

.

• SO 2 

### and PM values were also held at the EPA

- specified baseline for all units for all scenarios due to very low SO 2 

### and PM emiss ions through the use of dry lime FGD and FF on all units. F or SO 2 

### th e emissions specified were the 24

- hr average value for the maximum day from CEMS in the 2008

- 2011 period. PM emissions were specified as the 24

- hour average of the maximum heat input durin g this period multiplied by the respective unit’s emission factor.

o 

### PM speciation was based on the National Park Service (NPS) spreadsheet values for dry

- bottom coal

- fired boilers with FGD and fabric filter (FF) (see http://www.nature.nps.gov/air/Permits/ect/docs/coalBoiler/2006FinalDryBottomPC_ FGD_FFpmSpeciationProfile.xls ).

o 

### The heating value and sulfur content of the coal needed for PM speciation were provided by EPA for El Segundo Ranch coal (NM).

Table 4

. Base and Control Scenarios Used in Springerville RP Analyses

Controls Unit 1 Unit 2 All Units
Control Option ∆

- Emis sions (TPY ) Control Option ∆

- Emis sions (TPY ) ∆

- Emis sions (TPY ) $/year

Base Case LNB + CCSOFA 0 LNB + CCSOFA 0 0 $0
SNCR u.1&2 SNCR + LNB

+ CCOFA 657 SNCR + LNB

+ CCOFA 734 1391 $ 5,156,325 SCR u.1&2 SCR + LNB + CCOFA 1584 SCR + LNB + CCOFA 1804 3388 $21,796,642 

### All emission changes noted in Table 4 are taken from Table 3 for consistency with the cost analysis.



### 2.2.1.3.1 Stack Paramete rs The stack parameter data for Springerville Units 1

- 4 used in the visibility modeling were obtained from the Title V permit application for this plant through EPA

. Table 5 summarizes the stack parameters input to CALPUFF. Latitude and l ongitude coordinates were obtained

1 US EPA, RP_EGU_modeling_runs

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### from a conversion of UTM coordinates available in permit application; these were converted to Lambert Conformal Conic (LCC) projection coordinates with projection parameters from the Western Regional Air Partnership (WRAP) BART analysis for this facility.

Table 5

. Stack Parameters for Springerville Units 1

- 4



### 2.2.1.3.2 CALPUFF and POSTUTIL Inputs CALPUFF inputs for the Springerville emissions were provided by EPA as described previously

. These were input into a master spreadsheet (see Appendix A) for consolidation of the input data for QA and verification. The CALPUFF input prep aration for the 2001

- 2003 modeling period followed the procedure used in the Task 7 and Task 8 visibility analysis of six BART facilities under this WA. Discrete receptor data for the CIAs within the 300

- km radius of the Springerville plant were obtained f rom the NPS website of CIAs . Once the CALPUFF execution was completed for each of the years 2001

- 2003 , the concentration files were input to the POSTUTIL code with the option to repartition nitrate. The resulting annual concentration files were input to th e APPEND tool to prepare the composite 3

- year concentration file for use in CALPOST, along with the annual concentration files.



### 2.2.1.3.3 CALPOST Setup As with the CALPUFF modeling, the CALPOST post

- processing setup followed the WRAP BART Subject protocol ( WRAP, 2006)

. P ost

- processing of POSTUTIL output with CALPOST used the IMPROVE m ethod s 6 and 8 (submode 5) for calculation and comparison of the incremental visibility impairment ( ∆

- dv) relative to background at the affected CIAs. Each method used two sets of bac kground visibility c onditions at each CIA corresponding to (a) annual average background, and (b) 20% best background condition s. For both Method 6 and Method 8, CALPOST uses the input values of monthly

- average relative humidity adjustment factor f(RH) rat her than the hourly f(RH) values input on the VISB.DAT file generated by CALPUFF. The input data underwent extensive quality assu rance (QA) using customized Unix scripts.



### 2.2.1.3.4 Extraction of Visibility Results with POSTCALPOST

We extracted the results from the CALPOST visibility analysis for the four methods of calculating visibility using its Unix

- based extraction script named POSTCALPOST for submission to EPA in a tarfile of the modeling I/O. T he 98 th 

### percentile visibility impairment and benefits are summarize d here from Method 6(a) and 8(b) as defined above only for the composite 3

- year period (corresponding to the 22 nd 

### highest ∆− dv) ; visibility results for individual years for these two methods are available in supporting spreadsheets submitted with this report.

Unit # Longitude Latitude deg deg ft m ft m ft m F K ft/s m/s
1 -109.165727 34.317882 500.0 152.4 6980.0 2127.5 20.0 6.1 150.0 338.71 70.0 21.34
2 -109.166694 34.317897 500.0 152.4 6980.0 2127.5 20.0 6.1 150.0 338.71 70.0 21.34 3 -109.168084 34.317918 500.0 152.4 6980.0 2127.5 28.2 8.6 150.0 338.71 70.0 21.34
4 -109.168084 34.317918 500.0 152.4 6980.0 2127.5 28.2 8.6 150.0 338.71 70.0 21.34 Stack Height Stack Elevation Stack Diameter Stack Temperature Exit VelocityEMAQ LOE (EPA Contract EP

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### Table 6

. 98th p ercentile v isibility i mpairment ( ∆

- dv) for Springerville base case and control scenarios: (a) IMPROVE Method 6 (a) ; (b) IMPROVE Method 8(b)

.

(a) (b)



### Table 7

. Visibility Benefits (dv) for Springerville for the C ontrol S cenarios C orresponding to Table 6

(a) (b)



### From these results it can be seen that the maximum impairment using either method , and for all emission scenarios is seen in Gila Wilderness (gila) , followed by Mount Baldy (moba)

. Both methods show nearly all 15 CIAs with ≥ 0.5 ∆

- dv visibility impairment , with Method 8(b) estimat ing higher impairment than Method 6(a) and exceeding the impairment threshold at all CIAs for the base case

. The results are somewhat more mixed for the visibility benefit (d v) comparisons between Tables 7(a) and 7(b); SNCR controls show low er benefits compared to SCR with either method, but the differences become less significant at the farthest CIAs

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## 2.2.1.4 Control Effectiveness Results

In this section we examine the results for the control effectiveness in million $/dv, which is the dollars (i n millions) per year from Table 4 divided by the visibility improvement relative to base shown in Table 7 for each control scenario. The r esults are summarized in Table 8

. Table 8. Control Effectiveness ( m illion $/ d v) f or t he Calculation Methods o f Table 6

(a ) (b)



### Table 9. Summary o f Control Effectiveness for the Calculation Methods of Table 6

.

(a)

( b )



### In both visibility methods the SCR option for Units 1 and 2 are less effective (i.e., the cost per dv of visibility benefit) is greater

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### to Method 8(b) , because of the lower visibility benefits for the same technology and cost. This applies to both the CIA with maximum impact and summed over all CIAs (Table 9)

.

2.2.2 APS Cholla Unit 1



## 2.2.2.1 General Plant Information

The APS Cholla Plant has four units, of which Units 1 is being analyzed for RP . Figure 2 is a Google Earth image of the plant , and Table 10 provides general plant information for Cholla 1

, which is an ~ 110 MW tangentially fired boiler, equippe d with modern combustion controls (separated OFA [SOFA] and LNB) for NO x 

### . It also has a baghouse (FF) and a wet lime FGD system , thus PM and SO 2 

### controls are not being considered here

.

Figure 2

. APS Cholla Power Plant

Table 10

. Cholla Unit 1 Data

Unit Capacity

Fuel 2008

- 2010 Reported Avg 2011 Reported Rates 2008

- 2011

NO x SO 2 NO x SO 2 Capac ity F

ac t or MW gross lb/MMBtu lb/MMBtu %

1 113.6 C 0.188 0.118 0.220 0.202 86%



## 2.2.2.2 NO x 

## Control Options Analysis

2.2.2.2.1 Available NO x 

### Control Technologies

Since Cholla 1 already has some level of combustion controls the most effective additional controls are likely to be post

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### 2.2.2.2.2 Feasible NO x 

### Control Technologies ATP’s analysis shows that both SNCR and SCR controls are feasible.



### 2.2.2.2.3 Evaluation of of NO x 

### Control Technologies For the purpose of cost estimation, baseline emissions and capacity factors for all electric utility units were developed from historical data as follows:

• Capacity factor was taken as the average of that esti mated for the period 2008

- 2011 using reported heat input and plant capacity information.

• NO x 

### and SO 2 

### emission rates were examined for the average period of 2008

- 2010 and 2011. For NO x 

### , the 2011 time frame was selected because it reflects operation of the Cholla units using adv anced combustion controls, which is representative of anticipated annual emissions without additional post

- combustion controls

. 2



### Table 1 1 shows the NO x 

### control options for Cholla 1 used in the RP visibility analyses

. Table 1 1. NO x 

### Control Technologies for Cholla 1

Cholla 1

– NOx
SNCR SCR Capacity Factor 86% 86% Control Efficiency 30.0% 77.3%*
Uncontrolled Rate

NO x Rate (lb/hr) 274 274

NO x Rate (lb/MMBtu) 0.220 0.220

NO x (TPY) 1032 1032
Controlled Rate

NO x Rate (lb/hr) 192 62

NO x Rate (lb/MMBtu) 0.154 0.050

NO x (TPY) 723 235

Tons/Year Removed 310 798

Total Cost, $/year $999,045 $4,237,867 $/Ton $3,226 $5,313 $/Ton (incremental) $3,226 $6,638 * SCR is actually capable of 90% removal. The model that we used set a lower limit of 0.05 lb/MMBtu, but lower NOx levels should be achievable



### 2.2.2.2.4 Energy and Environmental Impacts of Control Option s Energy impacts of SNCR are relatively modest; energy impacts of SCR are greater. SCR will incur a draft loss that will increase parasitic loads. This is typically in the range of 0.5% of output. Environmental impacts of SNCR and SCR ar e primarily due to am monia slip ; g enerally,

2 See BART Guidelines, 40 CFR Part 51, Appendix P, Section IV.D.4.d. (“The baseline emissions rate should represent a realistic depiction of anticipated annual emissions for the source. In general, for the existing sources subject to BART, you will estimate the anticipated annual emissions based upon actual emissi ons from a baseline period.”)

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### this can be well controlled. SCR catalyst can be recycled and is therefore not a significant

concern.



## 2.2.2.3 Visibility Modeling

All four units at Cholla were included in the visibility modeling. EPA specifi ed the baseline emissions and the control option scenarios, shown in Table 1 2, for the modeling . The emissions used for the various scenarios are as follows:

• For the scenarios labeled Base , Ctrl2

- 1 and Ctrl2

- 2 for Units 2

- 4 the NO x 

### emissions are from a control case previously analyzed in the Task 8 BART analyses for these units, in which the maximum available NO x 

### control (SCR) is applied on each at 83 .5 % control efficiency

.

• For each of Units 1

- 4 t he SO 2 

### and filterable PM emissions for all scenarios correspond

to the ADEQ permit emission limit of 0.15 and 0.015 lb/MMBtu respectively, multiplied by the maximum emission day’s heat input selected from 2008

- 2011.

• Unit 1 baseline NO x 

### emissions are for the current combustion controls (LNB and SOFA) ; they are reduced as appropriate for the NO x 

### controls (SNCR and SCR) specified in Table 1 2 for the Ctrl2

- 1 and Ctrl2

- 2 scenarios.

• A revised base case (Rev Base

- 2 ) is modeled and used as the baseline of comparison for the control options Ctrl2

- 3 and Ctrl2

- 4

. o post

- LNB NO x 

### ba seline emissions from the previous BART analysis are used for this case along with PM speciation from NPS for FGD

- FF for all four units (see http://www.nature.nps.gov/air/Permits/ect/docs/coalBoiler/2006FinalDryBottomPC_ FGD_FFpmSpeciationProfile.xls ); previously Unit 2 had scrubber PM speciation that resulted in lower PM concentrations

. o SO 2 

### emissions are specified as previously

• C ontrol scenario s Ctrl 2

- 3 and Ctrl2

- 4 apply SNCR and SCR controls, respe ctively, on Unit 1 with respect to the Rev Base

- 2 baseline NO x 

### emissions

.

Table 1 2

. Base a nd C ontrol S cenarios U sed i n APS Cholla Unit 1 RP Analyses

Control Option Unit 1

Control NOx D

- Emis (TPY) $/year

Base LNB+SOFA 0 $0

Ctrl 2

- 1 SNCR+LNB+SOFA 309 $999,045

Ctrl 2

- 2 SCR+LNB+SOFA 797 $4,237,867

Rev Base

- 2 LNB+SOFA; FF PM Spec 0 $0

Ctrl 2

- 3 SNCR+LNB+SOFA 309 $999,045

Ctrl 2

- 4 SCR+LNB+SOFA 797 $4,237,867



### 2.2.2.3.1 Stack Parameters

Table 1 3 lists stack parameters that APS transmitted to EPA on February 3 and amended March 16, 2012

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### Table 1 3

. Stack P arameters f or APS Cholla Units 1

- 4



### 2.2.2.3.2 CALPUFF Emissions Inputs

The modeling requirements and data sources for emissions were specified by EPA in spreadsheets 3



### . The input data were extensively quality

- assured using customized Unix scripts. The e missions data are also documented in Appendix A of this report

.

• Filterable PM emission rates were calculated from the maximum day’s hourly average heat i n put multiplied by the ADEQ permit emission limit (0.015 lb/MMBtu) in the two base

case s and all control scenarios for all units

.

o 

### PM speciation was calculated using the NPS spreadsheet data for filterable PM speciation for a dry

- bottom PC with FG D an d fabric filter (FF).

o 

### The heating value and sulfur content of the coal needed for PM speciation were provided by EPA for El Segundo Ranch coal (NM)

.



### 2.2.2.3.3 CALPOST Setup

T he CALPOST setup to calculate the visibility impact s for Cholla follow ed the steps describe d for Springerville in Section 2.2.1.3.3

, using customized scripts to create the I/O directories and QA the inputs

.



### 2.2.2.3.4 Extraction of Visibility Results with POSTCALPOST We extracted the results from the CALPOST visibility analysis for the four methods of cal culating visibility using its Unix

- based extraction script named POSTCALPOST for submission to EPA in a tarfile of the modeling I/O. The 98 th 

### percentile visibility impairment and benefits are summarized here from Method 6(a) and 8(b) only for the composite 3

- year period (corresponding to the 22 nd 

### highest ∆− dv); results for individual years are available in supporting spreadsheets submitted with this report.
Table 14 summarizes the visibility impairment results for the methods 6(a) and 8(b); Table 15 summarizes their visibility benefits for each control option. The Table 14 results show greater visibility impairment for Method 8(b) compared to Method 6(a).

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### Table 1 4

. 98 th 

### Percentile V isibility I mpairment ( ∆

- d v) f or Cholla 1 Base Case a nd Control Scenari os : ( a ) IMPROVE Method 6 ( a ); ( b ) IMPROVE Method 8( b ).

(a)

(b)



### The greatest visibility impairment is seen at Petrified Forest (pefo) , followed by Grand Canyon (grca) , for all scenarios using either method. As expected the impairment is much greater at all CIAs without BART on Units 2

- 4, with almost all CIAs above the 0.5 ∆

- dv threshold; the exception is Saguaro (sagu) , which is located almost at the periphery of the 3 00

- km radius assumed for the zone of Cholla’s influence. Also as expected, the impairment is lowest for SCR controls at all CIAs for either method.EMAQ LOE (EPA Contract EP

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### Table 1 5

. Visibility Benefits ( d v) f or Cholla 1 for the Control Scenarios Corresponding to Table 14.

( a ) (b)



### Table 15 shows the visibility benefits of the 4 control options examined for each method. No CIA experiences a benefit greater than 0.5 dv. The benefits are greatest at pefo and least at sagu

. They are uniformly greater for SCR compared to SNCR contr ols , and greater for the scenarios without BART controls on Units 2

- 4 , possibly because these cases also had the greatest impairment.



## 2.2.2.4 Control Effectiveness Results

Table 16. Control Effectiveness (million $/dv) for the Calculation Methods of Table 14

(a) (b)



### This section presents the analysis of the control effectiveness of each scenario in million $/dv at Cholla using the method described in Section 2.2.1.4. The results are summarized in Tables 16 and 17. Table 1 6 summarize s the control effectiveness in $/dv for each control scenario for each of the visibility methods at each CIA

. The greatest effectiveness (lowest $/dv) is obtained using SNCR without BART controls on Units 2

- 4. This holds for all CIAs, and especially for pefo, the most visibility

- impaired . Method 8(b) results in greater control effectiveness at pefo compared to Method 6(a) . The results are more varied at the less affected CIAs, e.g., Sycamore Canyon), which shows greater effectiveness with Method 6(a) than with 8(b) when Units 2

- 4 are not controlled

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### Table 17. Summary of Control Effectiveness for the Calculation Methods of Table 14

(a)

(b)



### 2.2.3 TEP Sundt (Irvington ) Units 1

- 3



## 2.2.3.1 General Plant Information Figure 3 shows a Google Earth image of the 4

- unit Sundt plant

. T he upper three natural gas

fired units are the ones of interest for the RP analysis . Plant data and capacity factors for this plant are provided in Table 18

. With regard to emissions for the RP units, 2008

- 2010 data were averaged and 2011 data are the average over that year. The c apacity factor is determined by dividing total reported heat input by the potential heat input if the unit were operating at 100%

ca pacity every day of the year. Capacity factor is an important in put for co st effectiveness calculations

. The Implied Emission Rate developed from the modeled rate assumes operation at full capacity, which may underestimate the actual emission rate at the time.EMAQ LOE (EPA Contract EP

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### Figure 3

. TEP Sundt ( Irvington) Power Plant.

Table 1 8

. Sundt Power Plant Data

Unit Capacity

Fuel 2008

- 2010 Reported Avg 2011 Reported Rates 2008

- 2011 Reported Avg

NO x SO 2 NO x SO 2 NO x Capac ity F

a ct or MW gross lb/MMBtu lb/MMBtu lb/MMBtu %

Unit 1 108.8 Natural gas 0.156 0.003 0.153 0.003 0.155 9%

Unit 2 108.8 Natural gas 0.170 0.003 0.146 0.003 0.164 10%

Unit 3 113.6 Natural gas 0.160 0.003 0.161 0.004 0.16 16%



## 2.2.3.2 NO x 

## Control Options Analysis

2.2.3.2.1 Available NO x 

### Control Technologies Availalble controls include combustion and post

- combustion controls.



### 2.2.3.2.2 Feasible NO x 

### Control Technologies

Examined technologies for the Sundt gas units 1

- 3 are ultralow NO x 

### burners (ULNB) , SNCR, and SCR. All of these are both available and feasible; however, they generall y would not be

u se d in combination for gas

- fired units. For example, SNCR becomes ine ffective at very low NO x 

### levels, such as those possible with ULNBs

. Thus it is assumed that each of these technologies would be used individually. Moreover, for ULNBs , it was not possible to perform a detailed analysis of the application of flue gas recirculation ; this control technology would require either internal or extern al flue gas recirculation.EMAQ LOE (EPA Contract EP

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### 2.2.3.2.3 Evaluation of of NO x 

### Control Technologies For the purpose of cost estimation, baseline emissions and capacity factors for all electric utility units were developed from historical data as follows:

• Capacity factor s were taken to b e the average of those esti mated for the period 2008

- 2011 using reported heat input and plant capacity information.
The results of the cost estimation are shown in Table 19. The relatively low capacity factors and low baseline NO x 

### leveles on Sundt 1

- 2 , ra nging from 9

- 10%, and the low capture rate for SNCR results in high cost of control in terms of $/ton of NO
x 

### . Sundt 3, with a somewhat higher capacity factor of 16% is somewhat more cost

- effective to control, with ULNB control cost at around $ 4,400/ton of NO x 

### . Table 19. NO x 

### Control Techhnologies for Sundt Units 1

- 3



### 2.2.3.2.4 Energy and Environmental Impacts

Combustion controls have a small e nergy impact

. The impacts of SNCR are relatively modest; energy impacts of SCR are greater. SCR will incur a draft loss that will increase parasitic loads. This is typically in the range of 0.5% of output.
Combustion controls have the potential to somewhat increase CO emissions, and this typically sets the limit for what NO x 

### reduction is possible for low NO x 

### burners

Environ mental impacts of SNCR and SCR are primarily due to ammonia slip. The main environmental concern is regarding fly ash odor and potential impact on fly ash sales/disposal. Generally, ammonia slip can be controlled to acceptable levels from both of these tec hnologies so that fly ash is not adversely impacted.
SCR catalyst can be recycled and therefore is not a significant environmental concern.



## 2.2.3.3 Visibility Modeling

All four units at the Sundt facility were included in the visibility modeling for realistic
rep resentation of the plumes . The EPA spreadsheets specifi ed the baseline emissions and the control option scenarios for the modeling as with the previous two facilities

. T he following SNCR ULNB SCR SNCR ULNB SCR SNCR ULNB SCR
Capacity Factor 9% 9% 9% 10% 10% 10% 16% 16% 16%
Control Efficiency 20% 61% 80% 20% 63% 80% 20% 63% 80%

**Uncontrolled Rate**
NOx Rate (lb/hr) 190 190 190 197 197 197 206 206 206
NOx Rate (lb/MMB 0.155 0.155 0.155 0.164 0.164 0.164 0.16 0.16 0.16
NOx (TPY) 75 75 75 86 86 86 144 144 144

**Controlled Rate**
NOx Rate (lb/hr) 152 74 38 157 72 39 165 77 41
NOx Rate (lb/MMB 0.12 0.06 0.03 0.13 0.06 0.03 0.13 0.06 0.03
NOx (TPY) 60 29 15 69 32 17 115 54 29

Tons/Year Remo 15 46 60 17 55 69 29 90 115

Total Cost, $/yea $349,480 $381,622 $1,230,047 $354,395 $381,813 $1,231,190 $391,743 $399,852 $1,273,573

$/Ton $23,284 $8,297 $20,488 $20,575 $6,991 $17,869 $13,585 $4,437 $11,042

$/ton incremental $1,037 $60,425 $733 $59,463 $132 $34,629 Sundt 1 - NOx Sundt 2 - NOx Sundt 3 - NOxEMAQ LOE (EPA Contract EP

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### sections describe the inputs used for the visibility modeling, and the control effectiveness estimated in million $/dv for the control configurations.

Baseline emissions for units 1

- 4 as specified by the EPA were taken from the period 2008

- 2010 from prior BART eligibility study for Sundt by UNC. Unit 4 was held at this NO x 

### emission rate in all the scenarios.

Unit 1

- 3 NO x 

### emissions reductions rely upon a base case annual emission facto r calculated as the average of the CAMD 2008

- 2011 annual average values. The emissions reductions from the use of ULNB were such that the controlled emission factor would be reduced to 0.06 lb/MMBtu

. Due to the lack of reliable PM emissions for U nits 1

- 3

, these have PM emission values set to 0 in the base and control cases. SO 2 

### emissions for U nits 1

- 3 were held constant at the baseline levels from the previous BART analysis . Due to the low SO 2 

### emissions and the use of a baghouse (FF) for PM controls, these two pollutants are not considered in the Unit 1

- 3 control scenarios. PM emissions for Unit 4 were from the WRAP BART analysis per EPA specification, and PM speciation for this unit used the FF speciation for a dry

- bottom coal

- fired boiler as in our previou s BART analysis.
The emissions for the control cases are specified as follows, and tabulated in Table 20:

• Ctrl2

- 1 and Ctrl2

- 2 use identical controls on Units 1

- 3, in the form of ULNB, and thus yield identical control costs and NO x 

### emission reductions on th ese units.

• In addition to the SCR control specified for NO x 

### on Unit 4, Ctrl2

- 1 also uses dry sorbent injection (DSI) control for SO 2 

### on this unit

.

• Ctrl2

- 2 for Unit 4 uses base case values for NO x 

### , and DSI controls for SO 2


### .

Table 2 0

. Base and Control Scenarios for NO x 

### Used in Sundt Units 1

- 3 RP Analyses



### 2.2.3.3.1 Stack Parameters

Stack parameters for Sundt were taken from previous WRAP BART analysis per EPA
g uidance.

Table 2 1

. Stack Parameters for Sundt Units 1

- 3



### 2.2.3.3.2 CALPUFF Emissions Inputs

The EPA specified emission requirements for the CALPUFF modeling . The emissions data are also documented in Appendix A, and in the supporting spreadsheet documentation for this Base Base Case 0 Base Case 0 Base Case 0 0 $0

Ctrl2-1 ULNB + SCR u.4 46 ULNB + SCR u.4 54 ULNB + SCR u.4 90 190 $1,163,287

Ctrl2-2 ULNB 46 ULNB 54 ULNB 90 190 $1,163,287 Control NOx ∆ -Emis (TPY) $/year Unit 3 Units 1-3

Control Control NOx ∆ -Emis (TPY) NOx ∆ -Emis (TPY) NOx ∆ -Emis (TPY) Control Option Unit 1 Unit 2

Unit # LON LAT deg deg ft m ft m ft m F K ft/s m/s
Unit 1 -110.9049 32.16011 130.0 39.62 2608.0 794.92 10.52 3.21 260.0 399.82 29.0 8.84
Unit 2 -110.9049 32.16011 130.0 39.62 2608.0 794.92 10.82 3.30 260.0 399.82 27.0 8.23
Unit 3 -110.9049 32.16011 144.0 43.89 2608.0 794.92 12.31 3.75 246.0 392.04 29.0 8.84
Unit 4 -110.9049 32.16011 248.0 75.59 2608.0 794.92 10.28 3.13 287.0 414.82 79.0 24.08 Exit Velocity Stack Diameter Stack Height Stack Elevation Stack TemperatureEMAQ LOE (EPA Contract EP

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### report. We performed extensive QA of these inputs using customized Unix scripts to ensu re compliance with the data on the spreadsheets 4 

### provided by EPA

.



### 2.2.3.3.3 CALPOST Setup

W e followed the modeling protocol delivered with the Task 5 report in setting up the CALPOST inputs for each of the 10 CIA s within 300 km of the Sundt plant. Results are avail able for each of the years 2001

- 2003 and the composite period 2001

- 2003 using four visibility methods. They are reported here for two methods, namely, Method 6(a) and Method 8(b) mentioned in the previous sections for the composite period . Due to the large number of post

- processing runs required, we used customized scripts to extensively QA th e CALPOST inputs.



### 2.2.3.3.4 Extraction of Visibility Results with POSTCALPOST

Table 2 2 summarize the results for the 98 th 

### percentile visibility impairment due to Sundt within the composite three

- year period from 2000

- 2003 at all the affected CIAs

. In both visibility methods the maximum visibility impairment occurs at Saguaro (sagu)

, followed by Galiuro (gali) ; both CIAs are in close proximity to Sundt . Method 8 (b) resu lts show greater visibility impairment than Method 6 (a), as noted in the case of the previous RP facilities. SCR controls (Ctrl2

- 1) result in less impairment than in the case of the uncontrolled Unit 4 (Ctrl2

- 2).

Table 2 2

. 98 th 

### Percentile V isibility I mpairment ( ∆

- d v) f or Sundt Units 1

- 3 Base Case and Control Scenarios : ( a ) IMPROVE Method 6 (a); (b) IMPROVE Method 8(b)

(a) (b)

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### Table 23

. Visibility Benefits (dv) for Sundt for the Control Scenarios Corresponding to Table 22

(a) (b)



### The visibility benefits of controls exceed 0.5 dv for the 2 worst impaired CIAs (sagu , gali) when using SCR on Unit 4 . The benefits are higher for Method 8(b) than for Method 6(a) for this CIA , but the difference is slight for the less impaired CIAs.



## 2.2.3.4 Control Effectivene ss Results This section presents the analysis of the control effectiveness of each scenario in million $/dv at Sundt using the method described in Section 2.2.1.4. The results are summarized in Tables 24 and 25. Table 24 presents the $/dv for ea ch control scenario at each CIA. The greatest control effectiveness is for sagu and gali, with Method 8(b) showing slightly greater effectiveness. The differences between the two methods are more significant for CIAs with lower effectiveness. The control effectiven ess is greatest when SCR is applied on Unit 4

. Table 24. Control Effectiveness (million $/dv) for the Calculation Methods of Table 22

( a ) (b)EMAQ LOE (EPA Contract EP

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### Table 25

. Summary of Control Effectiveness for the Calculation Methods of Table 22

( a )

(b)



### Table 25 summarizes the effectiveness of these control options in millions of $/dv, for the maximum impairment area, and the sum over all CIAs

. As pointed out in the ATP analysis in Section 2.2.3.2.3, the ULNB controls on Units 1

- 3 are somewhat high cost as seen in the $/ton reduction figures in Table 25 , due to the low capacity factors and low NO x 

### baseline values. Thus the control effectiveness is low compared to other facilities analyzed. Method 8 (b) shows slightly greater effectiveness compared to Method 6 (a) , both on an average

, and for the dv sum over all the CIAs

. The use of SCR on Unit 4 is seen to be more than twice as effective as for the case of no controls on Unit 4

.

2.2.4 CalPortland Cement Rillito Plant Units 1

- 4 Formerly known as Arizona Portland Cement, the CalPortland Cement Rillito P lant (Figure 4) has three long kilns and one precalciner kiln

. The type and rated capacities are shown in Table 26

. It is currently understood that these kilns have fabric filters, but have no SO 2 

### or NO x 

### controls. It is understood that the three smaller kilns are not currently being operated and it is unclear if the se three kilns will be operated in the future. However, all 4 kilns are being included in this RP analysis.EMAQ LOE (EPA Contract EP

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### Figure 4. Kilns at the CalPortland Cement Rillito Plant

Table 26. CalPortland Kiln Data 5

Year on Line Fuel Type Capacity, TPD Capacity, 1000 TPY 1949 CGk Long DRY 408 121 1951 CGk Long DRY 408 121 1955 CGK Long DRY 408 121 2002 CGKA PreCaliner 3084 969 Fuels: C=Coal; G=Gas; K=Coke; A=Alternative 

### Facility emissions data developed by EPA for this facility are presented in Table 27. Annual emissions estimates and emission rates were determined by estimating a representative output (tons of clinker per year) from reported data and multiplying by representative emission rate in lb/ton. With regard to existing controls, kiln number 4 is new enough that it likely has some form of low NO x 

### combustion controls, but it is unlikely that kilns 1

- 3 have any NO x 

### controls

Table 27. Estimated Emissions and Production Rates for CalPortland Cement Kilns 1

- 4

Kilns1

- 3 (each)* Kiln 4 Units Source

NO
x Rate 8.70 3.59 lb/ton clinker EPA 6

TPY clinker 121,000 969,000 Ton/yr PCA 5

TPY clinker 143,157 1,053,932 Ton/yr EPA 6

TPY NO
x 623 1,894 Ton/yr Calculated

* Data for kilns 1

- 3 is per kiln, not total.

5 Portland Cement Association, “ US and Canadian Portland Cement Industry: Plant Information Summary”, December 31, 2006.

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## 2.2.4.1 NO x 

## Control Options Analysis

2.2.4.1.1 Available NO x 

### Control Technologies Available Technologies include MAT, LNB, mid

- kiln firing, SNCR, and SCR, and combinations of these technologies. In addition, kiln 4, as a precalciner kiln, could implement low NO x 

### combustion controls in the calciner. Thus low NOx cal ciner is another option for kiln 4. The cost of a L ow NOx C alciner (LNC) is expected to be in the same range as MAT 7



### .



### 2.2.4.1.2 Feasible NO x 

### Control Technologies All of the technologies cited above are feasible. mid

- kiln firing provides similar levels of reduction as other combustion technologies such as MAT

, but is more costly than MAT unless alternative fuels are available. Since information regarding the availability of alternative fuels (such as tires) was not available, m id

- k iln f iring was not evaluated. LNC is feasible for kiln 4. SCR, while available, has had very limited use on cement kilns and will not be evaluated further. For kiln 4, it is unclear if it currently has LNB with indirect firing

. If it already has such controls, it could likely still achieve f urther NO x 

### reductions through MAT or LNC.



### 2.2.4.1.3 Evaluation of Control Technologies

Tables 28 ( a ) and 28( b ) show estimated cost of controlling NO x 

### from the CalPortland Cement Kilns. LNB is more expensive than MAT or LNC for kiln 4 and it would therefore be conservative to use that as the basis for 30% reduction, although MAT may be applicable at a lower cost. SNCR can be used to provide 50% NO x 

### reduction whether used alone or in combination with combustion controls (assumed here to be LNB, although MAT m ay be applied at a lower cost). The cost and emissions information on Table 28(a) is per kiln

. Table 28 (a)

. NO x 

### Control Technologies for CalPortland Kilns 1

- 3

(a)

7 Memo from J. Staudt to R. Srivastava, S. Vijay, E. Torres, Re: Costs and Performance of Controls

– revised from comments, March 10, 2009 at page 14 

### MAT LNB SNCR LNB and SNCR capital $676,001 $2,708,493 $383,535 $3,092,028
Annualized Capital $63,810 $255,663 $36,203 $291,866 FOM (incl. admin, insu $102,045 $183,345 $90,347 $198,686
Reagent $115,120 $80,584
Total Cost, $/year 

### $165,855 $439,008 $241,669 $571,136

Percent Reduced 30% 30% 50% 51%

tons reduced 187 187 312 318 $/ton reduced $887 $2,349 $776 $1,798 Incremental $/ton (compared to MAT) $608 $3,098 Incremental $/ton (compared to LNB) ($1,584) $1,010 lb/hr emission rate 111 111 79 77EMAQ LOE (EPA Contract EP

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### Table 28 (b)

. NO x 

### Control Technologies for CalPortland Kiln 4

(b)



### 2.2.4.1.4 Energy and Environmental Impacts All these technologies can have a modest impact. MAT can have a beneficial impact on CO and SO 2 

### emissions. SNCR and SCR can result in ammonia slip, which is generally well controlled

, and therefore not a major concern

.


## 2.2.4.2 Visibility Modeling

The modeling included emission inputs from all four kilns. However, due to special requirements for capturing the output concentration files from CALPUFF for later sensitivity studies that may be done by EPA, the CALPUFF setup involved two streams of dispersio n calcu lations. The calculation steps are described in Section 2.2.4.2.2.

For Kilns 1

- 3, maximum 24

- hr average b aseline emissions needed for the visibility modeling are based on NO x 

### and SO 2 

### emission factors representing the highest value s reported over 20 05

- 2007, which was the most recent 3

- year period of continuous operation . A nnual emissions needed for the control cost estimates on these units were based on the NO x 

### and SO 2 

### emission factors representing the average over the reported emission inventory (EI) values for 2005

- 2007

. For Kiln 4, the maximum 24

- hr average emission inputs needed for the visibility modeling were taken from the WRAP BART modeling for this facility, and converted from g/s to TPY. T he annual emission values used in the cost estima tes for this unit are based on emission factors for NO x 

### and SO 2 

### that represent the average of values reported over the entire 2005

- 2010 period.
Due to the installation of a baghouse (FF) on each kiln per a Consent Decree of January 11, 2011, the filterabl e PM emission rate is limited to 0.008 gr/dscf. The EPA 6 

### provided a conversion of this value into lb/hr and g/s using stack exit temperatures and flow rates. PM emission factors for Kiln 1

- 3 used the NPS spreadsheets for a dry cement kiln with FF, and for Unit 4, the spreadsheet for a precalciner with FF.

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Annualized Capital $112,165 $323,515 $126,144 $449,659 FOM (incl. admin, insur, taxe $122,536 $212,098 $128,460 $265,553
Reagent $349,978 $244,985
Total Cost, $/year $234,701 $535,613 $604,583 $960,197

Percent Reduced 30% 30% 50% 51%

tons reduced 568 568 947 966 $/ton reduced $413 $943 $638 $994 Incremental $/ton (compared to MAT) $976 $1,824 Incremental $/ton (compared to LNB) $182 $1,067 lb/hr emission rate 336 336 240 235EMAQ LOE (EPA Contract EP

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### The emissions for the NO x 

### control cases are specified below , and tabulated in Table 29; in the base and control scenarios , EPA specified that the emissions of U nits 1

- 3 should be lumped together as one sou rce due to identical stack parameters and control technology on each

.

• Ctrl2

- 1uses LNB or MAT controls (as both have the same control efficiency) on each of Units 1

- 3, and baseline emissions on Unit 4.

• Ctrl2

- 2 uses SNCR controls on each of Units 1

- 3, and baseline emissions on Unit 4.

• Ctrl2

- 3 uses baseline emissions on Units 1

- 3, and LNB or MAT controls on Unit 4.

• Ctrl2

- 4 uses baseline emissions on Units 1

- 3, and SNCR control on Unit 4.

• Costs are shown separately in the last two columns of Table 29 for MAT and for LNB for Ctrl2

- 1 and Ctrl2

- 3; the control cost is repeated in these columns for Ctrl2

- 2 and Ctrl2

- 4 strictly for consistency, as the only control for these scenarios is SNCR.

Tab le 29. Base and Control Scenarios for NO x 

### Used in CalPortland Units 1

- 4 RP Analyses



### 2.2.4.2.1 Stack Parameters Stack parameters for CalPortland were taken from the facility’s Kiln 5 Class permit application, Appendix G, Table G3

- 1, and provided to us by EPA. They are listed in Table 30.

Table 30. Stack Parameters for CalPortland Units 1

- 4



### 2.2.4.2.2 CALPUFF and POSTUTIL Inputs
The EPA specified emission requirements for the CALPUFF modeling. The emissions data are also documented in Appendix A, and in the supporting sprea dsheet documentation for this report. We performed extensive QA of these inputs using customized Unix scripts to ensure compliance with the data on the spreadsheets provided by EPA 6



### . Per EPA’s specification the emissions of Units 1

- 3 were combined in CALP UFF inputs as a single source. Also, as separate CALPUFF output concentration files were requested by EPA for the resulting two sources (Units 1

- 3 and Unit 4) we set up CALPUFF run directories for CalPortland in two streams, one for each source. The rest o f the CALPUFF input preparation for the 2001

- 2003 modeling period followed the procedure used in the Task 7 and Task 8 visibility analysis of six BART facilities under this WA. Discrete receptor data for the CIAs

6 RP_Cement_mode ling_runs

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Ctrl2-1 LNB or MAT 561 0 561 $497,565 $1,317,024

Ctrl2-2 SNCR 936 0 936 $725,007 $725,007

Ctrl2-3 0 LNB or MAT 568 568 $234,701 $535,613

Ctrl2-4 0 SNCR 947 947 $604,583 $604,583 $/year if using MAT Control Option $/year if using LNB All Units

Control Unit 4 D

- Emis (TPY) D

- Emis (TPY) Control Units 1-3 D

- Emis (TPY)

Unit # LON LAT deg deg ft m ft m ft m F K ft/s m/s
Unit 1-3 -111.14965 32.40767 75.0 22.86 2060.0 627.89 10.0 3.05 425.00 491.48 52.70 16.06
Unit 4 -111.14977 32.40760 75.0 39.62 2060.0 627.89 16.0 4.88 399.99 477.59 47.83 14.58 Stack Height Stack Elevation Stack Diameter Stack Temperature Exit VelocityEMAQ LOE (EPA Contract EP

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### within the 300

- km radius of the CalPortland plant were obtained from NPS. The two sets of CALPUFF outputs were combined first in POSTUTIL for each scenario, and the nitrate was repartitioned between gas and particle phases in a subsequent POSTUTIL run for each scenario.



### 2.2.4.2.3 CALPOST Setup

We followed the modeling protocol delivered with the Task 5 report in setting up the CALPOST inputs for each of the 12 CIAs within 300 km of the CalPortland Cement Rillito plant. Results are available for each of the years 2001

- 2003 and the composite period 2001

- 2003 using four visibility methods. They are reported here for Method 6(a) and Method 8(b) for the composite period. Due to the large number of post

- processing runs required, we used customized scripts to extensively QA the CALPOST inputs.



### 2.2.4.2.4 Extraction of Visibil ity Results with POSTCALPOST

Table 31 summarize s the results for the 98 th 

### percentile visibility impairment due to CalPortland within the composite three

- year period from 2000

- 2003 at all the affected CIAs for the base case and control options

. Table 32 summarizes the visibility benefits for the control scenarios.

Table 31

. 98 th 

### Percentile V isibility I mpairment ( ∆

- d v) f or CalPortland Units 1

- 4 Base Case and Control Scenarios : ( a ) IMPROVE Method 6 (a); (b) IMPROVE Method 8(b).

(a) (b)



### Table 32

. Visibili ty Benefits (dv) f or CalPortland Units 1

- 4 for the Control Scenarios Corresponding to Table 31.

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### Table 31 shows the greatest impairment due to CalPortland at Saguaro for both visibility methods. The differences in impairment when applying the same control technology on Units 1

- 3 vs. Unit 4 are slight, and the impairment is greater in the case of controls on Unit 4 than o n Units 1

- 3.

Table 32 shows the greatest visibility benefits, as expected, at the most significantly impaired CIA s, namely, sagu, gila and gali, with the controls on Units 1

- 3 providing greater visibility benefits than on Unit 4 using the same technology.



## 2.2.4.3 Control Effectiveness Results The results of the control effectiveness in $/dv (millions) for CalPortland are pre sented in Tables 33 and 34. Table 34 presents the control effectiveness at each CIA, and Table 34 summarizes the results for the CIA with the maximum deciview impact, and for deciview impact summed over all CIAs.

Table 33. Control Effectiveness (million $/ dv) for the Calculation Methods of Table 31

(a) (b)



### Table 33 and 34 separate ly report the control effectiveness between MAT and LNB controls due to their difference in cost. They show that the greatest effectiveness is for MAT on Unit 4, followed by SNCR on Unit 4 . Table 3 3 shows that the control effectiveness for MAT is the greatest at the most significantly impaired CIAs nearby (sagu, gila and gali) and much less at the CIAs farther away such as pefo and Sierra Ancha (sian) ; LNB on Units 1

- 3 is the least effective. Method 8(b) is more effective than Method 6(a) due to its greater visibility benefits.

Table 34

. Summary of Control Effectiveness for the Calculation Methods of Ta ble 31

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### 2.2.5 Phoenix Cement Plant Unit 4 At Phoenix Cement, one new precalciner kiln replaced older kilns and is the only kiln in operation at this site. The facility as seen in Google Maps is shown in Figure 5. Data from the Portland Cement Associat ion 8 

### on kiln capacity and chara cteristics are shown in Table 35

.

Figu re 5. Phoenix Cement Plant, Clarkdale, AZ

Table 35

. Phoenix Cement Kiln Data 5



### Year on Line Fuel Type Capacity, TPD Capacity, 1000 TPY 2002 CK PreCaliner 2721 912 Fuels: C=Coal; G=Gas; K=Coke; A=Alternative
The reported emissions and kiln data are shown in Table 36. Annual emissions and emission rates were estimated using a representative output (tons of clinker per year) from reported data and multiplying by representative emission rate in lb/ton.

8 Portland Cement Association, “ US and Canadian Portland Cement Industry: Plant Information Summary”, December 31, 2006.EMAQ LOE (EPA Contract EP

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### Existing controls likely include some form of combustion controls since the kiln is only ten years old, but it is unclear at this time if LNB with indirect firing is currently utilized at the kiln.

Table 36. Estimated Emissions and Production Rates for Phoenix Cement Kilns 1

- 4

Kiln 4 Units Source
NOx Rate 3.25 lb/ton clinker EPA 6



### TPY clinker 888,680 Ton/yr PCA 5



### TPY clinker 996,265 Ton/yr EPA 6



### TPY NOx 1,620 Ton/yr Calculated



## 2.2.5.1 NO x 

## Control Options Analysis

2.2.5.1.1 Available NO x 

### Control Technologies
Available technologies include MAT, LNB, Mid

- Kiln firing, LNC, SNCR, and SCR, and combinations of these technologies.



### 2.2.5.1.2 Feasible NO x 

### Control Technologies
All of these technologies are feasible except possibly LNB, if it is already deployed. Mid

- kiln firing provides similar levels of reduction as other technologies such as MAT but is more costly than MAT unless alternative fuels are available, which can make mid

- kiln firing very attractive. Since information regarding the availabili ty of alternative fuels (such as tires) was not available, mid kiln firing was not evaluated. SCR, while available, has had very limited experience on cement kilns and a more comprehensive technical review should be performed prior to using this approach. It is unclear if the kiln currently has LNB with indirect firing. If it already has such controls, it could likely still achieve further NO x 

### reductions through MAT or LNC.



### 2.2.5.1.3 Evaluation of Control Technologies
Table 37 provides NOx control technologies and co st estimates for Phoenix Cement Kiln 4. Information on the type of NO x 

### control technolo gies currently deployed on this kiln was not available. It is likely that the kiln uses some form of low

- NOx technology, although it is unclear what form is used.. Shown in this table are MAT or LNC, LNB, SNCR alone (50% reduction) and LNB plus SNCR. MAT or LNC and LNB are both shown to provide 30% NO x 

### reduction, although for cost estimations LNB is more conservative. For 50% NO x 

### reduction, both SNCR and SNCR in combinati on with combustion controls (in this case LNB, with MAT or LNC as a less expensive alternative) are shown. SNCR is by itself expected to be capable of 50% NO x 

### reduction; therefore in combination with combustion controls it should certainly be capable of th at level of reduction (given a 30% reduction from combustion controls and an additional 30% from SNCR). Thus a more conservative control cost estimate for 50% reduction would result from LNB in combination with SNCR.

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### Table 37

. NO x 

### Control Options for Pho enix Cement Kiln 4

Item **MAT or LNC LNB**  **SNCR LNB and SNCR**  

### capital $1,155,839 $3,300,783 $1,268,764 $4,569,547 Annualized Capital $109,103 $311,571 $119,762 $431,333
FOM $121,239 $207,037 $125,756 $257,787 Reagent $299,348 $209,543
Total Cost

, $/year 

### $230,342 $518,607 $544,866 $898,663
Percent Reduced 30% 30% 50% 51%
tons reduced 486 486 810 826 $/ton reduced $474 $1,067 $673 $1,088 Incremental $/ton (compared to MAT) $971 $1,964
Incremental $/ton (compared to LNB) $81 $1,117

lb/hr emission rate 288 288 205 201



### 2.2.5.1.4 Energy and Environmental Impacts

Each of the evaluated control measur es has a modest energy impact. MAT can have a beneficial impact on CO and SO 2 

### emissions. SNCR and SCR can result in ammonia slip, which is generally well controlled

.


## 2.2.5.2 Visibility Modeling
The visibility modeling considered the single kiln that is being evaluated for NO x 

### controls at Phoenix Cement Plant. The NO x 

### and SO 2 

### emission rates for this p lant for the maximum 24

- hour
average were based on the highest value from the entire 2005

- 2010 period of available data from the facility’s EI submittals. A nnual emission s needed for the cost estimates were also based on emission factors representing the a verage over this entire period. However the average clinker production rate used in converting these emission factors to annual emission rates for SO 2 

### and NO x 

### excluded the lower production rates from 2008

- 2010 as not being representative of future operation s. PM emission rates were calculated by the EPA using the PM emission factors averaged over the EI values for the years 2005

- 2010, and the flow rate and stack parameters from the facility EI submittals. PM speciation used the NPS spreadsheet for a precalc iner with FF.

The emissions for the NO x 

### control cases are specified as follows, and tabulated in Table 38; in the base and control scenarios:

• Ctr l

- 1 uses LNB or MAT on Kiln 4 (they both have 30% control efficiency).

• Ctrl

- 2 uses SNCR on Kiln 4.

• Costs are shown separately in the last two columns of Table 38 for MAT and for LNB for Ctrl

- 1; the control cost is repeated in these columns for Ctrl2 strictly for consistency, as the only control for this case is SNCR.EMAQ LOE (EPA Contract EP

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### Table 38. Base and Control Scenarios for NO x 

### Used in Phoenix Cement Unit 4 RP Analys e s



### 2.2.5.2.1 Stack Parameters
Stack parameters for Phoenix Cement were provided by EPA from the Title V permit application Permit No. 35426, submitted June 29, 2006. They are shown in Table 39.

Table 3 9

. Stack Parameters for Phoenix Cement Kiln



### 2.2.5.2.2 CALPUFF Emissions Inputs
The EPA specified emission requirements for the CALPUFF modeling. The emissions data are also documented in Appendix A, and in the supporting spreadsheet documentation for this report. We performed extensive QA of these inputs using customized Unix scripts to ensure compliance with the data on the spreadsheets provided by EPA 6



### .



### 2.2.5.2.3 CALPOST Setup We followed the modeling protocol delivered with the Task 5 report in setting up the CALPOST inputs for each of the 12 CIAs within 300 km of the Phoenix Cement Plant. Results are available for each of the years 2001

- 2003 and the composite period 2001

- 2003 using four visibility methods. They are reported here for Method 6(a) and Method 8(b) for the composite period. We used customized scripts to extensively QA the CALPOST inputs.



### 2.2.5.2.4 Extraction of Visibility Results with POSTCALPOST

Table 40 summarizes the results for the 98 th 

### percentile visibility impairment due to Phoenix Cement within the composite three

- year period from 2000

- 2003 at all the affected CIAs for the base case and control options. Table 41 summarizes the visibility benefits for the control scenarios.

6 US EPA, RP_Cement_modeling_runs

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### D

- Emis (TPY) if using MAT if using LNB

Base 0 $0 $0

Ctrl-1 LNB or MAT 486 $230,342 $518,607

Ctrl-2 SNCR 810 $544,866 $544,866 Control Option Unit 4 $/year

Unit # LON LAT deg deg ft m ft m ft m F K ft/s m/s
Kiln 4 -112.08302 34.77763 213.25 65.0 3816.57 1163.29 9.09 2.77 211.73 373.0 66.6 20.3 Stack Height Stack Elevation Stack Diameter Stack Temperature Exit VelocityEMAQ LOE (EPA Contract EP

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### Table 40

. 98 th 

### Percentile V isibility I mpairment ( ∆

- d v) f or Phoenix Cement Base Case and Control Scenarios : ( a ) IMPROVE Method 6 (a); (b) IMPROVE Method 8(b).

(a) (b)



### Table 40 shows the greatest visibility impairment due to Phoenix Cement at Sycamore Canyon for all scenarios and both methods. The impairment is greater for Method 8(b) than for Method 6(a). SNCR co ntrols provide the greatest benefit of all technologies, as confirmed by the results in Table 41.

Table 41

. Visibility Benefits (dv) f or Phoenix Cement Kiln 4 for the Control Scenarios Corresponding to Table 40

(a) (bEMAQ LOE (EPA Contract EP

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## 2.2.5.3 Control Effectiveness Results
The results of the control effectiveness in $/dv (millions) for Phoenix Cement are presented in Tables 42 and 43 . Table 42 presents the control effectiveness at each CIA, and Table 43 summarizes the results for the CIA with the maximum deciview impact, and for the deciview impact summed over all CIAs.

Table 42. Control Effectiveness (million $/dv) for the Calculation Methods of Table 40

(a) (b)



### Table 43. Summary of Control Effectiveness for the Calculation Methods of Table 40

(a)

(b)



### Table s 42 and 43 separate ly present the control effectiveness for MAT and LNB due to their difference in cost. They show that the great est effectiveness is for MAT , followed by SNCR. Table 42 shows that the control effectiveness for MAT is the greatest , i.e., has lowest $/dv values at the most significantly impaired CIAs ( Sycamore Canyon ) and much less at the farther CIAs such as sagu and sian

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### relatively high cost . Method 8(b) is found to be more effec tive than Method 6(a) due to its greater visibility benefits.



## 2.3 **Conclusi ons** 
The five

- factor BART analysis of the five facilities that we analyzed led to the following conclusions:

• The visibility i mpacts are greatest for each facility at the nearest CIAs, and the control options are least effective (greatest in million $/dv) at the farthest ones. T he CIAs which experience the greatest visibility impacts and show the greatest benefits are listed below for the respective facilities ; the number of CIAs with impai rment > 0.5 dv due to that facility, averaged over all scenarios

, is listed in parentheses

o 

### for Springerville, Gila (14 of 15) ;

o 

### for Cholla Unit 1, Petrified Forest (10 of 13) ;

o 

### for Sundt, Saguaro (2 of 10) ;

o 

### for CalPortland, Saguaro ; Gila in the case of cont rols on Kilns 1

- 3 using Method 8(b) (3 of 12) , and

o 

### for Phoenix Cement, Sycamore Canyon ( 2 of 12)

• Table s 9, 17, 25, 34, and 43 summarize the aggregated results for each facility as a sum over all the relevant CIAs of the $/dv (in millions) for each control option for Method 6 (a) and Method 8(b)

. In general

, the control effectiveness increases for

o 

### the nearest CIAs

o 

### SNCR control com pared to LNB and SCR

o 

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## References

EPA, 2010: Documentati on of EPA’s IPM Base Case v4.10, U.S. Environmental Protection Agency. http://www.epa.gov/airmarkets/progsregs/epa

ipm/BaseCasev410.html#documentation

EPA

, 2002 : EPA Air Pollution Control Cost Manual (Sixth Edition) , Report No. EPA/452/B

02

- 001 , U.S. Environmental Protection Agency.
ENSR, 2009: Revised BART Analysis fo r the Navajo Generating Station Units 1

- 3 , ENSR Corporation, Document No. 05830

- 012

- 300, January 2009, Salt River Project

– Navajo Generating Station, Tempe, AZ.
Staudt, J., and C. Erickson, 2008: Selective Catalytic Reduction System Performance and Relia bility Review . Presented at the 2008 International Power Generation Conference, December 2

- 4, 2008, Orlando, FL

. Western Regional Air Partnership (WRAP), 2006: CALMET/CALPUFF Protocol for BART Exemption Screening Analysis for Class I Areas in the Western United States . Western Regional Air Partnership Air Quality Modeling Forum, Regional Modeling Center, August 15, 2006; http://pah.cert.ucr.edu/aqm/308/bart/WRAP_RMC_ BART_Protocol_Aug15_2006.pdf

## Appendix A **Emissions Data Tables**EMAQ LOE (EPA Contract EP

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### This appendix provides the emissions data for CALPUFF modeling of the base case(s) and control scenarios analyzed for the thr ee EGU facilities. These data were extracted from a master spreadsheet that is being delivered as part of the documentation for thi s task.

Table A

- 1(a). NO x 

### , SO 2 

### and PM emission inputs for base and control scenarios for TEP Springerville visibility modeling.

Table A

- 1(b). Speciated PM emission inputs for base and control scenarios for TEP Springerville visibility modeling.EMAQ LOE (EPA Contract EP

- D

- 07

- 102) WA 5

- 12: Task 9 Five

- Factor Analys e s for RP Facilities

UNC

- EMAQ 5

- 12

- 0 25 .v 1 

### A

- 3 October 3, 2012 

### Tabl e A

- 2(a). NO x 

### , SO 2 

### and PM emission inputs for base and control scenarios for APS Cholla Unit 1 visibility modeling.EMAQ LOE (EPA Contract EP

- D

- 07

- 102) WA 5

- 12: Task 9 Five

- Factor Analys e s for RP Facilities

UNC

- EMAQ 5

- 12

- 0 25 .v 1 

### A

- 4 October 3, 2012 

### Table A

- 2(b). Speciated PM emission inputs for base and control scenarios for APS Cholla Unit 1 visibility modeling.EMAQ LOE (EPA Contract EP

- D

- 07

- 102) WA 5

- 12: Task 9 Five

- Factor Analys e s for RP Facilities

UNC

- EMAQ 5

- 12

- 0 25 .v 1 

### A

- 5 October 3, 2012 

### Table A

- 3(a). NO x 

### , SO 2 

### and PM emission inputs for base and control scenarios for TEP Sundt Units 1

- 3 visibility modeling.

Table A

- 3(b). Speciated PM emission inputs for base and control scenarios for TEP Sundt Units 1

- 3 visibility modeling.EMAQ LOE (EPA Contract EP

- D

- 07

- 102) WA 5

- 12: Task 9 Five

- Factor Analys e s for RP Facilities

UNC

- EMAQ 5

- 12

- 0 25 .v 1 

### A

- 6 October 3, 2012 

### Table A

- 4 (a). NO x 

### , SO 2 

### and PM emission inputs for base and control scenarios for CalPortland Cement Units 1

- 3 and Unit 4 visibility modeling

Table A

- 4 (b). Speciated PM emission inputs for base and control scenarios for CalPortland Cement Units 1

- 3 and Unit 4 visibility mod elingEMAQ LOE (EPA Contract EP

- D

- 07

- 102) WA 5

- 12: Task 9 Five

- Factor Analys e s for RP Facilities

UNC

- EMAQ 5

- 12

- 0 25 .v 1 

### A

- 7 October 3, 2012 

### Table A

- 5 (a). NO x 

### , SO 2 

### and PM emission inputs for base and control scenarios for Phoenix Cement Kiln 4 visibility modeling

Table A

- 5 (b). Speciated PM emission inputs for base and control scenarios for Phoenix Cement Kiln 4 visibility modeling

## Appendix B

**Andover Technology Partners Report Chapter**  **5 :**  **Reasonable Progress Analysis**

### 5

- 2 www.AndoverTechnology.com 5. Reasonable Progress Analysis

Task 9: Conduct Reasonable Progress Analysis for Four Class I Areas

Under this task, Andover Technology Partners conducted a four

- factor analysis of sources to identify whether there are additional reasonable NOx controls available.

For the following sources, Andover Technology Partners identified and evaluated NOx cont rols:

• Arizona Portland Cement Plant

• Phoenix Cement Plant

• Springerville Generating Station, Units 1 & 2

• Cholla Power Plant, Unit 1

• Sundt Generating Station Units 1, 2, & 3

• Ina Road Sewage Plant (Pima County)

• Williams Compressor Station (El Paso Natural G as)

• Flagstaff Compressor Station (El Paso Natural Gas)

• Tucson Compressor Station (El Paso Natural Gas)

Cost estimates performed in this section utilize methods consistent with the US EPA Control Cost Manual, 7 cost estimating methods used in EPA’s latest Integrated Planning Model (IPM)
methods 8 , and other reasonable engineering methods and are described in greater detail in associated spreadsheets provided with this document.

7 EPA. 2002. EPA Air Pollution Control Cost Manual (Sixth Edition). EPA/452/B

- 02

- 001
8 Documentation of EPA IPM Base Case v4.10. http://www.epa.gov/airmarkets/progsregs/epa

ipm/BaseCasev410.html#documentation

### 5

- 3 www.AndoverTechnology.com 5.1 Arizona Portland Cement Com pany, Rillito, AZ

This facility, shown in Figure 5

- 1 has three long dry kilns and one precalciner kiln. The type and rated capacities are shown in Table 5

- 1. It is currently understood that these kilns have fabric filters, but have no SO2 or NOx controls. It is understood that the three smaller kilns are not currently being operated and it is unclear if these three kilns will be operated in the future.

Figure 5

- 1. Arizona Portland Cement Company, Rillito Plant

.

Table 5

- 1. Kilns at the Arizona Portland Cement Plant 9

Year on Line Fuel Type Capacity, TPD Capacity, 1000 TPY
1949 CGk Long DRY 408 121
1951 CGk Long DRY 408 121
1955 CGK Long DRY 408 121
2002 CGKA PreCaliner 3084 969 Fuels: C=Coal; G=Gas; K=Coke; A=Alternative

Facility emissions data was developed by EPA, and this is shown in Table 5

- 2. Annual emissions estimates and emission rates were determined by estimating a representative output (tons of clinker per year) from reported data and multiplying by representat ive emission rate in lb/ton.

With regard to existing controls, kiln number 4 is new enough that it likely has some form of low NOx combustion controls, but it is unlikely that kilns 1

- 3 have any NOx controls.

9 Portland Cement Association, “ US and Canadian Portland Cement Industry: Plant Information Summary”, December 31, 2006.

### 5

- 4 www.AndoverTechnology.com Table 5

- 2. Estimated emissions and production rates for Arizona Portland Cement Kilns
1

- 4

Kilns 1

- 3

(each)* Kiln 4 Source

NOx Rate 8.70 3.59 lb/ton clinker EPA 10

TPY clinker 121,000 969,000 Ton/yr PCA 9

TPY clinker 143,157 1,053,932 Ton/yr EPA 10

TPY NOx 623 1,894 Ton/yr Calculated

* Data for kilns 1

- 3 is per kiln, not total.

5.1.1 NOx Controls

Available Technologies

Available Technologies include MAT, LNB, Mid Kiln firing, SNCR, and SCR, and combinations of these technologies. In addition, kiln 4, as a calciner kiln, could implement low NOx combustion controls in the calciner. So, low NOx calciner is another option for kiln 4. The cost of a low NOx calciner (LNC) is expec ted to be in the same range as MAT. 11

Feasible Technologies

All of these technologies are feasible. Mid Kiln firing provides similar levels of reduction as other combustion technologies such as MAT but is more costly than MAT unless alternative fuels are available. Since information regarding the availability of alternative fuels (such as tires) was not available, Mid Kiln Firing was not evaluated. LNC is feasible for kiln 4. SCR, while available, has very limited experience on cement kilns and will not be evaluated further. For kiln 4, it is unclear if it currently has LNB with indirect firing If it already has such controls, it could likely still achieve further NOx reductions through implementation of MAT or LNC.

Evaluation of Technologies

Tables 5

- 3a and 5

- 3b show estimated cost of controlling NOx from the Arizona Portland Cement Kilns. LNB is more expensive than MAT or LNC (for kiln 4) and it would be conservative to use that as the basis for 30% reduction, although MAT may actually be applicable at a lower cost. SNCR can be used to provide 50% NOx reduction whether used alone or in combination with combustion controls (assumed here to be LNB, although MAT may be applied at a lower cost). The cost and emissions informaton on Table 5

- 3a is per kil n, not total for the three kilns.

10 US EPA, RP_Cement_model ing_runs

- EPA 20120 912 .xls

11 Memo from J. Staudt to R. Srivastava, S. Vijay, E. Torres, Re: Costs and Performance of Controls

– revised from comments, March 10, 2009 at page 14

### 5

- 5 www.AndoverTechnology.com Energy and Environmental Impacts of NOx Control Measures

Each of these measures has a modest energy impact. MAT can have a beneficial impact on CO and SO 2 emissions. SNCR and SCR can result in ammonia slip, which is ge nerally well controlled.

Table 5

- 3a. NOx Controls for Kilns 1

- 3 (values shown are **per** kiln)

MAT LNB SNCR LNB and SNCR capital $676,001 $2,708,493 $383,535 $3,092,028 Annualized Capital $63,809.67 $255,663 $36,203 $291,866 FOM (incl. admin, insur, taxes) $102,045 $183,345 $90,347 $198,686

Reagent $115,120 $80,584
Total Cost, $/year $165,855 $439,008 $241,669 $571,136

Percent Reduced 30% 30% 50% 51%

tons reduced 187 187 312 318 $/ton reduced $887 $2,349 $776 $1,798 Incremental $/ton (compared to MAT) $608 $3,098

Incremental $/ton (compared to LNB) - $1,584 $1,010

lb/hr emission rate 111 111 79 77

Table 5

- 3b. NOx Controls for Kiln 4

MAT or LNC LNB SNCR LNB and SNCR

capital $1,188,275 $3,427,320 $1,336,373 $4,763,693
Annualized Capital $112,165 $323,515 $126,144 $449,659 FOM (incl. admin, insur, taxes) $122,536 $212,098 $128,460 $265,553

Reagent $349,978 $244,985
Total Cost, $/year $234,701 $535,613 $604,583 $960,197

Percent Reduced 30% 30% 50% 51%

tons reduced 568 568 947 966 $/ton reduced $413 $943 $638 $994 Incremental $/ton (compared to MAT) $976 $1,824

Incremental $/ton (compared to LNB) $182 $1,067

lb/hr emission rate 336 336 240 235

### 5

- 6 www.AndoverTechnology.com 5.2. Phoenix Cement, Clarkdale, AZ

At Phoenix Cement, one new kiln replaced older kilns, so that only one precalciner kiln remains in operation at this site. The Phoenix Cement facility is shown in Figure 5

- 2 and data from the Portland Cement Association on kiln capacity and characteristic s are shown in Table 5

- 4

Figure 5

- 2. Phoenix Cement, Clarkdale, AZ

Table 5

- 4 Phoenix Cement Plant Kiln 12

Year on Line Fuel Type Capacity, TPD Capacity, 1000 TPY
2002 CK PreCaliner 2721 912 Fuels: C=Coal; G=Gas; K=Coke; A=Alternative

The reported emissions and kiln data are shown in Table 5

- 5. Annual emissions estimates and emission rates were determined by estimating a representative output (tons of clinker per year) from reported data and multiplying by representative emission rate in lb/ton.

Existing controls likely include some form of combustion controls since the kiln is only ten years old, but it is unclear at this time if LNB with indirect firing is currently utilized at the kiln.

12 Portland Cement Association, “ US and Canadian Portland Cement Industry: Plant Information Summary”, Decemb er 31, 2006.

### 5

- 7 www.AndoverTechnology.com Table 5

- 5. Estimated Uncontrolled Emission s Rates

NOx Rate 3.25 lb/ton clinker EPA 13

TPY clinker 888,680 Ton/yr PCA 12

TPY clinker 996,265 Ton/yr EPA 6

TPY NOx 1,620 Ton/yr Calculated

5.2.1 NOx Controls

Available Technologies

Available Technologies include MAT, LNB, Mid Kiln firing, low NOx Calciner (LNC), SNCR, and SCR, and combinations of these technologies.

Feasible Technologies

All of these technologies are feasible except possibly LNB if it is already deployed. Mid Kiln firing provides similar levels of reduction as other technologies such as MAT but is more costly than MAT unless alternative fuels are available, which can make mid kiln firing very attractive. Since information regarding th e availability of alternative fuels (such as tires) was not available, Mid Kiln Firing was not evaluated. SCR, while available, has limited experience on cement kilns and a more comprehensive technical review should be performed prior to utilizing this ap proach.

It is unclear if the kiln currently has LNB with indirect firing If it already has such controls, it could likely still achieve further NOx reductions through implementation of MAT or LNC.

Evaluation of Technologies

Information on the type of NOx control technologies currently deployed on this kiln was not available. It is likely that the kiln utilizes some form of low NOx technology, although it is unclear what form is used.. Table 5

- 6 shows estimated cost of controlling NOx from the Phoenix Cem ent kiln. Shown here are MAT or LNC, LNB, SNCR alone (50% reduction) and LNB plus SNCR. MAT or LNC and LNB are both shown for 30% reduction, although for cost estimating LNB should be used since it is more conservative. For 50% NOx reduction, both SNCR and SNCR in combination with combustion controls (in this case LNB, but MAT or LNC are possible alternatives that would be less expensive) are shown. Although SNCR is generally expected to be capable of 50% NOx reduction alone, in combination with combust ion controls it would certainly be capable of 50% NOx reduction (30% reduction from combustion controls plus an additional 30% from SNCR). Therefore, a more conservative estimate of control costs for 50% reduction would result from the combination of LNB with SNCR.

13 US EPA, RP_Cement_modeling_runs

- EPA 20120 912 .xls

### 5

- 8 www.AndoverTechnology.com Energy and Environmental Impacts of NOx Control Measures

Each of these measures has a modest energy impact. MAT can have a beneficial impact on CO and SO 2 emissions. SNCR and SCR can result in ammonia slip, which is generally well
controlled . Table 5

- 6 shows the results of a cost analysis for Phoenix cement.

Table 5

- 6. NOx Control options for Phoenix Cement

MAT or LNC LNB SNCR LNB and SNCR capital $1,155,839 $3,300,783 $1,268,764 $4,569,547 Annualized Capital $109,103 $311,571 $119,762 $431,333

FOM $121,239 $207,037 $125,756 $257,787
Reagent $299,348 $209,543
Total Cost, $/year $230,342 $518,607 $544,866 $898,663

Percent Reduced 30% 30% 50% 51%

tons reduced 486 486 810 826 $/ton reduced $474 $1,067 $673 $1,088
Incremental $/ton (compared to MAT) $971 $1,964

Incremental $/ton (compared to LNB) $81 $1,117

lb/hr emission rate 288 288 205 201

### 5

- 9 www.AndoverTechnology.com 5.3 Springerville Power Plant, units 1&2

There are four coal fired units at Springerville. Units 3 and 4 are new units and have modern controls. Of interest are units 1 and 2 pictured in Figure 5

- 1. These are tangentially fired boilers of roughly 400 MW that have close

- coupled overfire air for NOx control and recently upgraded 1980’s vintage Joy

- Niro Spray Dryer Absorber s with a reverse air baghouses for SO 2 and PM control. According to EIA form 860, the capture efficiency of the SDA is 61.3%, but it was recently improved to 90%+ capture efficiency. Table 5

- 7 shows recent plant data.

Figure 5

- 3. Springerville 1 & 2

Table 5

- 7. Springerville 1 and 2 Power Plant Data

Unit Capacity

Fuel 2008

- 2010 Reported Avg 2011 Reported
Rates 2008

- 2011

NOx SO 2 NOx SO 2 Capac.
Fctr.
MW gross lb/MMBtu lb/MMBtu %

1 424.8 C 0.182 0.218 0.180 0.253 65%

2 424.8 C 0.190 0.185 0.188 0.167 70%

### 5

- 10 www.AndoverTechnology.com 5.3.1 NOx Controls

Available Technologies

Springerville units have advanced combustion controls, so additional NOx reduction may not be possible with combustion controls. Additionally, post

- combustion controls might be applied

– SNCR or SCR. Both of these technologies are available.

Feasible Technologies

Post combustion controls are certainly feasible at Springerville units 1 and 2.

Evaluation of Technologies

Table 5

- 8 shows the comparative cost and performance of feasible NOx reduction technologies for Springerville 1 & 2.

Energy and Environmental Effects

Both SNCR and SCR can produce ammonia slip, but this is generally well controlled. SCR catalyst can be recycled and therefore is not a concern. SCR will produce an increase in parasi tic load of roughly 0.50% of plant output.

Table 5

- 8. Springerville 1 & 2 NOx Control

Springerville 1

– NOx Springerville 2

– NOx

SNCR SCR SNCR SCR Capacity Factor 65% 65% 70% 70% Control Efficiency 30% 72% 30% 74%

**Uncontrolled Rate**
NOx Rate (lb/hr) 769 769 798 798 NOx Rate (lb/MMBtu) 0.18 0.18 0.19 0.19 NOx (TPY) 2189 2189 2448 2448

**Controlled Rate**
NOx Rate (lb/hr) 538 212 559 210 NOx Rate (lb/MMBtu) 0.13 0.05 0.13 0.05 NOx (TPY) 1532 605 1714 644

Tons/Year Removed 657 1584 734 1804

Total Cost, $/year $2,494,309 $10,820,423 $2,662,016 $10,976,219
$/Ton $3,798 $6,829 $3,625 $6,085 $/Ton (incremental) $8,975 $7,774 * SCR is actually capable of 90% removal. The model that we used set a lower limit of 0.05 lb/MMBtu, but lower NOx levels should be achievable

### 5

- 11 www.AndoverTechnology.com 5.4 Cholla 1

Cholla power plant was pictured in Figure 4

- 2. Cholla 1 is a roughly 110 MW unit that has a baghouse and a lime wet FGD system. It is a tangentially

- fire d boiler with modern combustion controls. Cholla 1 data is shown in Table 5

- 9.

Table 5

- 9. Cholla Unit 1 Data

Unit Capacity

Fuel 2008

- 2010 Reported Avg 2011 Reported
Rates 2008

- 2011

NOx SO2 NOx SO2 Capac.
Fctr.
MW gross lb/MMBtu lb/MMBtu %

1 113.6 C 0.188 0.118 0.220 0.202 86%

5.4.1 NOx Controls

Available NOx Control Technologies

Since Cholla 1 already has combustion controls, post combustion controls

– SNCR and SCR

- are available and more likely to provide significant reductions.

Feasible NOx Control Technologies

Both SNCR and SCR are feasible.

Evaluation of NOx Control Technologies

For the purpose of cost estimation, baseline emissions and capacity factors for all electric utility units were developed from historical data in this manner.

• Capacity factor is the average of that estimated for the period 2008

- 2011 using reported heat input and plant capacity information.

• NOx emission rates were examined for the average period of 2008

- 2010 and 2011. For NOx, the 2011 time frame was selected. This period reflects operation of Cholla unit 1 using advanced combustion controls, which is representative of anticipated annual emissions without additional post

- combustion controls. 14



## 1.1 14 

## See BART Guidelines, 40 CFR Part 51, Appendix P, Section IV.D.4.d. (“The baseline emissions rate should represent a realistic depiction of anticipated annual emissions for the source. In general, for the existing sources subject to BART, you will estimate the anticipated annual emissions based upon actual emissions from a baseline period.”)

### 5

- 12 www.AndoverTechnology.com Table 5

- 10 shows the results of analysis of SNCR and SCR for the Cho lla unit 1.

Energy and Environmental Effects

Both SNCR and SCR can produce ammonia slip, but this is generally well controlled. SCR catalyst can be recycled and therefore is not a concern. SCR will produce an increase in parasitic load of roughly 0.50% of plant output.

Table 5

- 10 Cholla 1 NOx Controls

Cholla 1

– NOx

SNCR SCR
Capacity Factor 86% 86% Control Efficiency 30% 77%*

**Uncontrolled Rate**
NOx Rate (lb/hr) 274 274 NOx Rate (lb/MMBtu) 0.22 0.22 NOx (TPY) 1032 1032

**Controlled Rate** 
NOx Rate (lb/hr) 192 62 NOx Rate (lb/MMBtu) 0.15 0.05 NOx (TPY) 723 235

Tons/Year Removed 310 798

Total Cost, $/year $999,045 $4,237,867
$/Ton $3,226 $5,313 $/Ton (incremental) $3,226 $6,638 * SCR is actually capable of 90% removal. The model that we used set a lower limit of 0.05 lb/MMBtu, but lower
NOx levels should be achievable

### 5

- 13 www.AndoverTechnology.com 5

- 5. Sundt 1

- 3

Table 5

- 11 shows the modeled and reported data for Sundt units 1

- 3, the upper three units in Figure 5

- 4. 2008

- 2010 data was averaged and 2011 data is the average over that year. Capacity factor is determined by dividing total reported heat input by the potential heat input if the unit were operating at 100% capacity 365 days a year. Capacity factor is important in
pe rforming cost effectiveness calculations. The Implied Emission Rate developed from the modeled rate assumes operation at full capacity, which may underestimate the actual emission
rate at the time.

Figure 5

- 4. Sundt Power Plant.

Table 5

- 11. Sundt Power Plant Data

Unit Capacity

Fuel 2008

- 2010 Reported Avg 2011 Reported
Rates 2008

- 2011 Reported Avg

NOx SO2 NOx SO2 NOx Capac.
Fctr.
MW gross lb/MMBtu lb/MMBtu lb/MMBtu %

Unit 1 108.8 Natural gas 0.156 0.003 0.153 0.003 0.155 9%

Unit 2 108.8 Natural gas 0.170 0.003 0.146 0.003 0.164 10%

Unit 3 113.6 Natural gas 0.160 0.003 0.161 0.004 0.16 16%

### 5

- 14 www.AndoverTechnology.com Available Controls

Available controls include combustion controls and post

- combustion controls.

Feasible Controls

Examined here for gas units (1

- 3) are ultralow NOx burners, SNCR, and SCR. All of these are both available and feasible; however, they generally would not be utilized in combination for gas fired units. For example, SNCR becomes ineffective at very low NOx levels, such as those
po ssible with ultra low NOx burners. Therefore, it is assumed that each of these technologies would be used individually. Moreover, for ultra low NOx burners, it was not possible to perform a detailed analysis of the application of flue gas recirculation. Ultra low NOx burners would require either internal or external flue gas recirculation.

Evaluation of NOx Controls

For the purpose of cost estimation, baseline emissions and capacity factors for all electric utility units were developed from historical da ta in this manner.

• Capacity factor and NOx will be the average of that estimated for the period 2008

- 2011 using reported heat input and plant capacity information.

The results of the cost estimation are shown in Table 5

- 12. The relatively low capacity fa ctors and low baseline NOx leveles on Sundt 1

- 2 , ranging from 9

- 10%, and the low capture rate for SNCR results in high cost of control in terms of $/ton of NOx. Sundt 3, with a somewhat higher capacity factor of 16% is somewhat more cost effective to co ntrol, with ULNB control cost at around $4400/ton of NOx.

Energy and Environmental Effects

Combustion controls have a small energy effect. SCR will incur an additional parasitic loss due to the pressure loss that is roughly equal to 0.50% of output.

Combu stion controls have the potential to increase CO emissions somewhat, and this typically sets the limit for what NOx reduction is possible for low NOx burners.

SNCR and SCR can cause ammonia slip, which is emitted to the atmosphere. Ammonia slip is typical ly controlled to acceptable levels.

SCR catalyst can be recycled, and is not a disposal problem.

### 5

- 15 www.AndoverTechnology.com Table 5

- 12 . NOx Control for Sundt Units 1

- 3.

Sundt 1

- NOx Sundt 2

- NOx Sundt 3

- NOx

SNCR ULNB SCR SNCR ULNB SCR SNCR ULNB SCR
Capacity Factor 9% 9% 9% 10% 10% 10% 16% 16% 16%
Control Efficiency 20% 61% 80% 20% 63% 80% 20% 63% 80%

**Uncontrolled Rate**
NOx Rate (lb/hr) 190 190 190 197 197 197 206 206 206
NOx Rate (lb/MMBtu) 0.155 0.155 0.155 0.164 0.164 0.164 0.16 0.16 0.16
NOx (TPY) 75 75 75 86 86 86 144 144 144

**Controlled Rate**
NOx Rate (lb/hr) 152 74 38 157 72 39 165 77 41
NOx Rate (lb/MMBtu) 0.12 0.06 0.03 0.13 0.06 0.03 0.13 0.06 0.03
NOx (TPY) 60 29 15 69 32 17 115 54 29

Tons/Year Removed 15 46 60 17 55 69 29 90 115

Total Cost, $/year $349,480 $381,622 $1,230,047 $354,395 $381,813 $1,231,190 $391,743 $399,852 $1,273,573
$/Ton $23,284 $8,297 $20,488 $20,575 $6,991 $17,869 $13,585 $4,437 $11,042
$/ton incremental $1,037 $60,425 $733 $59,463 $132 $34,629

### 5

- 1 www.AndoverTechnology.com 5

- 6 Ina Road Wastewater Facility

Ina Road wastewater facility has seven rich burn IC engines that burn a mixture of natural gas
and on

- site generated methane. The engine types are summarized in Table 5

- 13. Waukesha VHP7100G engine/generator packages are normally aspirated 15 and have an ebullient

- cooled,

co

- generation system that produces both hea t and electricity. The heat warms water for use by digesters to produce methane gas that’s consumed as fuel by the engines. Roughly 30% of the fuel used is self

- generated biofuel with the balance natural gas. Average power output is 2.5 MW and the plant expects to use these units for another 25 years. 16 According to US EPA’s NEEDS database, each engine

- generator produces 590 kW (790 bhp), a reported heat rate of 13,298 Btu/kW, and a NOx emission rate of 2.271 lb/MMBtu. 17

Table 5

- 13. Data for Ima Road Wast ewater Facility.

Data Info Source Engine type 7 Waukesha rich

- burn engines 590 kW, installed 1977 NEEDS v 4.10 and Waukesha
Maintainer
NOx Rate Potential to Emit (PTE): 576.58

tons PTE is potential emissions with no controls, if all equipment runs
24 hrs/day, 365 days/year (Permit)
SO2 Rate PTE: 113.1 tons Permit
PM Rate PTE: 2.28 tons Permit Existing Emissions Controls None Permit

Available NOx Controls

Available NOx controls include

• Air/Fuel Ratio Adjustment

• Ignition Timing Retard

• Prestratified Charge

• Low Emission Combustion

• Non

- selective Catalytic Reduction

Feasible NOx Controls

15 www.dresserwaukesha.com/documents/8009_1010.pdf

16 Source: “Maintenance Helps Million Hour Engines Thrive At Tucson Wastewater Cogeneration Plant”, Waukesha Maintaine r , October 2003 | volume 24 | issue 3 http://files.harc.edu/Sites/GulfCoastCHP/CaseStudies/TucsonAZMillionHour.pdf

17 US EPA, NEEDS, v 4.10

### 5

- 2 www.AndoverTechnology.com At this time there is no reason to believe that any of these technologies are not feasible; however, due to the age of the engines it is possible that prestratified charge retrofit kits may not be available and low emissions combustion retrofit may not be possible or economically viable. Low emission combustion retrofit of rich

- burn engines involves almost completely rebuilding the engine. Of the high NOx reduction methods, the only method that is certain to be feasible is
Non

- Selective Catalytic Reduction.

Evaluation of NOx Control Methods

Table 5

- 14 shows estimated cost effectiveness for three possible control approaches.

• Air

- Fuel Ration Controller with High Energ y Injection (A/F & HEI)

• Pre

- Stratified Charge (PSC)

• Non

- Selective Catalytic Reduction (NSCR) Details regarding cost and emissions estimates are in workbooks included with this report.

Table 5

- 14. Evaluation of NOx Reduction at Ina Road Wastewater Facility

A/F & HEI PSC NSCR
HP 1,000 1,000 1,000 Initial NOx g/hp

- h 16 16 16 NOx Reduction 25% 85% 95% Outlet NOx, g/hp

- h 12.00 2.40 0.80 NOx Reduced (TPY) 39 131 147 Capital Cost, $/bhp $82 $176 $95 Capital Cost, $ $82,000 $176,000 $95,000
Annualized Cost 7,740 16,613 8,967 Admin, Taxes, Insurance $3,280 $7,040 $3,800 Fixed Operating Cost $12,533 $12,533 $12,533 Variable Operating Cost, Catalyst $5,595
Total Annual Cost $23,554 $36,186 $30,896 Cost of control, $/ton $610 $276 $211
Incremental $/ton $136

- $342

Energy and Environmental Effects

NSCR will reduce fuel efficiency somewhat, as will most of the in

- cylinder NOx reduction methods. However, NSCR has the benefit of reducing other emissions, including CO, while the
in

- cylinder methods largely risk higher CO emissions.

### 5

- 3 www.AndoverTechnology.com 5.7 Williams Compressor Station

Table 5

- 15 shows the equipment at this facility that includes a range of rich

- burn and lean

- burn reciprocating internal combustion engines (RICE) and one combustion turbine for g as compression, and a rich burn engine and a smaller gas turbine for auxiliary use (presumably generator drive). The rich burn engine is an emergency generator.

Table 5

- 15 Equipment at Williams Compressor Station

Recip/CT Rich Burn/Lean
Burn HP (each) # units year in
service Recip Clark TLA

- 6 Lean 2000 4 1956 Recip Clark TLA

- 10 Lean 3400 1 1963

CT GE M5322R 32,000 1 1993 Ingersoll

- Rand PSVG

- 10 (aux) Rich 530 Solar Saturn (aux) 837 1

Available Technologies

There are a number of technologies available that are identified in Table 2

- 6 for lean burn engines that include, air/fuel ratio adjustment, high energy ignition, low emission combustion (aka

– “clean burn”) retrofit, or SCR.

For the combustion turbines, both can accept water i njection. Dry Low NOx retrofit of the GE M5322R will require conversion from a regenerated cycle to a simple cycle because the regenerated cycle preheats the combustion air to the combustor using exhaust. A simple cycle conversion would reduce cycle effi ciency, increasing heat rate from roughly 7070 to 8700 Btu/kW

- hr. 18 The GE M5322R is suitable for conventional SCR because the exhaust temperature is rated at 666°F. 19 Also, upgrade of the existing combustor liners to GE’s LHE liners, if available, may p rovide modest NOx reduction for the GE turbine. 20

According to Solar, they do not offer a dry low NOx option for the Saturn. As a simple cycle engine, the Solar turbine would require high

- temperature catalyst if SCR were deployed.

The IR PSVG

- 10 engine wou ld accept any of the rich burn technologies listed on page 2

- 6, providing that the retrofit kits are available from the manufacturer (this is the case with clean burn retrofits and prestratified charge, in particular). However, it was made an emergency
ge nerator 21 and may not operate enough to warrant retrofit.

18 Email from GE, Septemb er 14, 2012

19 Brooks, F., “GE Gas Turbine Performance Characteristics”, GER

- 3567H

20 Email from GE, September 18, 2012

21 Addenda (Significant Revision) #40117 to Operating Permit #28162 for El Paso Natural Gas Company

### 5

- 4 www.AndoverTechnology.com Feasible Technologies

The large reciprocating engine and the large CT are, by far, the largest sources of NOx on the site. For the IC engines, the options are:

• A/F ratio controller and high energy ignition (A/F & HEI)

• Low Emission Combustion retrofit (shown as LEC1, LEC2 and LEC3 depending upon controlled level achieved)

• SCR The most likely technologies would include:

• Replacement of updated combustor liners for a modest improvement in NOx perhaps (GE is looking into availability of liner for this application and I have contacted a non

OEM vendor for information). Therefore, it is not certain that these liners are available, and vendors are looking into it. Costs and performance are also uncertain at this point.

• Water injection

• Simple Cycle conversion with DLN

• SCR

– using conventional SCR catalyst

Details regarding cost and emissions estimates are in workbooks included with this report.

Evaluation of NOx Control Methods

Tables 5

- 16a, b, and c sho w estimated cost effectiveness for different options for the reciprocating engines and the large combustion turbine.

Energy and Environmental Effects

SCR has the risk of ammonia slip; however, that is generally well controlled. It will have a very
small impact on turbine output, as the turbine already has significant back

- pressure from the regenerator.
The DLN with the simple cycle conversion on the combustion turbine causes a large increase in fuel demand (over 20%) due to the increase in heat rate.

Wate r injection will require adequate water supply and water treatment. Water availability would have to be evaluated further.

### 5

- 5 www.AndoverTechnology.com Table 5

- 16a. Cost Effectiveness, Clark TLA

- 6, average cost per engine

– four engines A/F & HEI LEC 1 SCR LEC 2 LEC 3
HP 2000 2000 2000 2000 2000 Initial NOx g/hp

- h 15 15 15 15 15 NOx Reduction 25% 80% 90% 90% 97% Outlet NOx, g/hp

- h 11.25 3.00 1.50 1.50 0.50 NOx Reduced (TPY) 72 232 261 261 280 Capital Cost, $/bhp $100 $969 $890 $1,313 $1,338 Capital Cost, $ $200,000 $1,937,500 $1,780,000 $2,625,000 $2,675,000
Annualized Cost $18,879 $182,886 $168,019 $247,781 $252,501 Admin, Taxes, Insurance $8,000 $77,500 $71,200 $105,000 $107,000 Fixed Operating Cost $12,533 $12,533 $12,533 $12,533 $12,533 Variable Operating Cost Reagent $0 $0 $50,584 $0 $0 Variable Operating Cost, Catalyst 7460 Total Annual Cost $39,412 $272,920 $309,797 $365,315 $372,034 Cost of control, $/ton $544 $1,178 $1,188 $1,401 $1,329 Incremental $/ton $1,466 $1,273* $3,190* $348 *Compared to LEC1

Table 5

- 16b. Cost Effectiveness, Clark TLA10

A/F & HEI LEC 1 SCR LEC 2 LEC 3
HP 3,400 3,400 3,400 3,400 3,400 Initial NOx g/hp

- h 16 16 16 16 16 NOx Reduction 25% 81% 90% 91% 97% Outlet NOx, g/hp

- h 12.00 3.00 1.60 1.50 0.50
NOx Reduced (TPY) 131 427 473 476 509 Capital Cost, $/bhp 100 $969 $890 $1,313 $1,338 Capital Cost, $ $340,000 $3,293,750 $3,026,000 $4,462,500 4,547,500 Annualized Cost 32,094 310,907 285,633 421,228 429,252 Admin, Taxes, Insurance $13,600 $131,750 $121,040 $178,500 $181,900 Fixed Operating Cost $12,533 $12,533 $12,533 $12,533 $12,533 Variable Operating Cost Reagent $0 $0 $91,726 $0 $0 Variable Operating Cost, Catalyst $12,682
Total Annual Cost $58,227 $455,190 $523,614 $612,262 $623,685 Cost of control, $/ton $443 $1,067 $1,108 $1,286 $1,226 Incremental $/ton $1,343 $1,489* $3,190* $348 *Compared to LEC1

### 5

- 6 www.AndoverTechnology.com Table 5

- 16c. Cost Effectiveness, GEM5322R

Liner Upgrade* Water Injection DLN/Simple Cycle** SCR
MW 22 22 22 22
NOx Rate (pph) 144 144 144 144 NOx Reduction 25% 80% 0.875 90% Outlet NOx (pph) 108.00 28.80 18.00 14.40 NOx Reduced (TPY) 158 505 552 568 Capital Cost, $/kW $10 $74.54 $165 $158 Capital Cost, $ $220,000 $1,639,968 $3,633,691 $3,471,468
Annualized Cost 20,766 154,801 $342,995 327,682 Admin, Taxes, Insurance $8,800 $65,599 $145,348 $138,859 Fixed Operating Cost $58,227 $42,393 $181,685 $62,596 Variable Operating Cost Reagent/Water/fuel $0 $168,455 $816,747*** $168,096

Variable Operating Cost, Catalyst $110,000

Total Annual Cost $87,793 $431,248 $1,486,774 $807,233 Cost of control, $/ton $557 $855 $2,694 $1,422 Incremental $/ton $990 $3,549

- $43,096 *Availability, cost and performance of combustor liner upgrade are uncertain and need to be evaluated further. **Capital Cost information was not available. It is assumed that this costs three times the expected incremental cost of DLN for a 25 MW class GE turbine. ***This is additional fuel cost resulting from conversion to simple cycle a t an assumed $2.60/MMBtu price for fuel and 100% capacity factor.

### 5

- 7 www.AndoverTechnology.com 5.8 Flagstaff Compressor Station

Table 5

- 17 shows the equipment at this facilities that includes a range of rich

- burn and lean

burn reciprocating internal combustion engines (RICE).

Table 5

- 17. Equipment at Flagstaff Compressor Station

Recip/CT Rich /Lean HP (each) # units year in
service Recip Clark TCV

- 16 Lean 5500 1 1964 Recip Clark TCV

- 16 Lean 5500 1 1966 Recip Cummins G12 rich 184

Available Technologies

There are a number of technologies available that are identified in Table 2

- 6 for lean burn engines that include, air/fuel ratio adjustment, high energy ignition, low emission combustion (aka

– “clean burn”) retrofit, or SCR.

The Cummins G12 engine would accept any of the rich burn technologies listed on page 2

- 6, providing that the retrofit kits are available from the manufacturer (this is the case with clean burn retrofits and prestratified charge, in particular).

Feasible Technologies

The large reciprocating engines are, by far, the largest sources of NOx on the site. For the lean burn IC engines, the options evaluated are:

• Air

- Fuel Ration Controller with High Energy Injection

• Low Emission Combustion retrofit (shown as LEC1, LEC2 and LEC3 depending upon
controlled l evel achieved)

• SCR For the rich burn engine the options evaluated are:

• Air

- Fuel Ration Controller with High Energy Injection (A/F & HEI)

• Pre

- Stratified Charge (PSC)

• Non

- Selective Catalytic Reduction (NSCR) Details regarding cost and emissions estimates are in workbooks included with this report.

Evaluation of NOx Control Methods

Tables 5

- 18 a and b show estimated cost effectiveness for different options for the reciprocating engines.

Energy and Environmental Effects

### 5

- 8 www.AndoverTechnology.com NSCR has a modest impact on engine effic iency, but reduces CO and other emissions.

Table 5

- 18a. Cost Effectiveness, Clark TCV

- 16, average cost per engine

- two engines A/F & HEI LEC 1 SCR LEC 2 LEC 3
HP 5500 5500 5500 5500 5500 Initial NOx g/hp

- h 15.00 15.00 15.00 15.00 15.00 NOx Reduction 25% 80% 90% 90% 97% Outlet NOx, g/hp

- h 11.25 3.00 1.50 1.50 0.50 NOx Reduced (TPY) 199 637 717 717 770 Capital Cost, $/bhp 100 $969 $890 $1,313 $1,338 Capital Cost, $ 550,000 $5,328,125 $4,895,000 $7,218,750 $7,356,250
Annualized Cost 51,916 $502,937 $462,053 $681,399 $694,378 Admin, Taxes, Insurance $22,000 $213,125 $195,800 $288,750 $294,250 Fixed Operating Cost $12,114 $12,114 $12,114 $12,114 $12,114 Variable Operating Cost Reagent $0 $0 $139,107 $0 $0 Variable Operating Cost, Catalyst $20,515
Total Annual Cost $86,030 $728,176 $829,589 $982,263 $1,000,742 Cost of control, $/ton $432 $1,143 $1,157 $1,370 $1,300 Incremental $/ton $1,466 $1,273* $3,190* $348 *compared to LEC1

Table 5

- 18b. Cost Effectiveness, Cummins G12

A/F & HEI PSC NSCR
HP 184 184 184 Initial NOx g/hp

- h 7.1 7 7 NOx Reduction 25% 85% 95% Outlet NOx, g/hp

- h 5.31 1.06 0.35 NOx Reduced (TPY) 3 11 12 Capital Cost, $/bhp 82 176 $95.00 Capital Cost, $ $15,088 $32,384 $17,480
Annualized Cost 1,424 3,057 1,650 Admin, Taxes, Insurance $604 $1,295 $699 Fixed Operating Cost $13,600 $13,600 $13,600 Variable Operating Cost, Catalyst $0 $0
Total Annual Cost $1,029 Cost of control, $/ton $15,628 $17,952 $16,979 Incremental $/ton $1,678 $1,420

### 5

- 9 www.AndoverTechnology.com 5.9 Tuscon Compressor Station

Table 5

- 19 shows the equipment at this facilities that includes a range of rich

- burn and lean

burn reciprocating internal combustion engines (RICE).

Table 5

- 19. Equipment at Tuscon Compressor Station

Recip/CT Rich Burn/Lean
Burn HP (each) # units year in
service Recip Cooper GMV

- 10TF Lean 1071 17 1950
Recip Ingersoll

- Rand PVG

- 8 Rich 370 4 1947

Available Technologies

There are a number of technologies available that are identified in Table 2

- 6 for lean burn engines that include, air/fuel ratio adjustment, high energy ignition, low emission combustion (aka

– “clean burn”) retrofit, or SCR.

The Ingersoll

- Rand PVG

- 8 engine would accept any of the rich burn technologies listed on page
2

- 6, providing that the retrofit kits are available from the manufacturer (this is the case with clean burn retrofits and prestratified charge, in particular).

Feasible Technologies

The large reciprocating engine are, by far, the largest sources of NOx on the site. For the lean burn IC engines, the options evaluated are:

• Air

- Fuel Ration Controller with High Energy Injection

• Low Emission Combustion retrofit (shown as LEC1, LEC2 and LEC3 depending upon controlled level achieved)

• SCR For the rich burn engines the options evaluated are:

• Air

- Fuel Ration Controller with High Energy Injection (A/F & HEI)

• Pre

- Stratified Charge (PSC)

• Non

- Selective Catalytic Reduction (NSCR) Details regarding cost and emissions estimates are in workbooks included with this report.

Evaluation of NOx Control Methods

Table s 5

- 20 a and b show estimated cost effectiveness for different options for the reciprocating engines.

Energy and Environmental Effects

### 5

- 10 www.AndoverTechnology.com NSCR has a modest impact on engine efficiency, but reduces CO and other emissions.

Table 5

- 20a. Cost Effectiveness, Cl ark GMV

- 10F, average cost per engine

- seventeen engines A/F & HEI LEC 1 SCR LEC 2 LEC 3
HP 1071 1071 1071 1071 1071 Initial NOx g/hp

- h 13 13 13 13 13 NOx Reduction 25% 77% 90% 88% 96% Outlet NOx, g/hp

- h 9.75 3.00 1.30 1.50 0.50 NOx Reduced (TPY) 34 103 121 119 129 Capital Cost, $/bhp 100 $759 $890 $805 $850 Capital Cost, $ 107,100 $813,400 $953,190 $862,400 $910,000
Annualized Cost 10,109 $76,779 $89,974 $81,404 $85,898 Admin, Taxes, Insurance $4,284 $32,536 $38,128 $34,496 $36,400
Fixed Operating Cost $12,533 $12,533 $12,533 $12,533 $12,533 Variable Operating Cost Reagent $0 $0 $23,476 $0 $0

Variable Operating Cost, Catalyst $3,995

Total Annual Cost $26,927 $121,849 $168,106 $128,434 $134,831 Cost of control, $/ton $801 $1,178 $1,389 $1,080 $1,043 Incremental $/ton $1,360 $2,631* $425* $619 *Compared to LEC1

Table 5

- 20b. NOx Reduction for Ingersoll

- Rand PVG

- 8 A/F & HEI PSC NSCR
HP 370 370 370 Initial NOx g/hp

- h 7.1 7 7 NOx Reduction 25% 85% 95% Outlet NOx, g/hp

- h 5.31 1.06 0.35 NOx Reduced (TPY) 6 22 24 Capital Cost, $/bhp $82 $176 $95 Capital Cost, $ $30,340 $65,120 $35,150
Annualized Cost 2,864 6,147 3,318 Admin, Taxes, Insurance $1,214 $2,605 $1,406 Fixed Operating Cost $158 $158 $158 Variable Operating Cost, Catalyst $2,070
Total Annual Cost $4,235 $8,909 $6,952 Cost of control, $/ton $669 $414 $289 Incremental $/ton $308

- $773