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-D-07-102

Work Assignment: 5-12

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 Saravanan 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, 2012 
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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 Analysis
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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 .......................................................................... 29
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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. NOx Control Options Analysis for Springerville Units 1 and 2 (updated 9/30/2012)...... 5

Table 4. Base and Control Scenarios 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 Control Scenarios Corresponding to 

Table 6............................................................................................................................... 8

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

Table 11. NOx 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. 98th 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 Cholla 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. NOx Control Techhnologies for Sundt Units 1-3.......................................................... 18

Table 20. Base and Control Scenarios for NOx Used in Sundt Units 1-3 RP Analyses............... 19

Table 21. Stack Parameters for Sundt Units 1 - 3......................................................................... 19

Table 22. 98th 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 Sundt for the Control Scenarios 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). NOx Control Technologies for CalPortland Kilns 1-3 ............................................. 24

Table 28(b). NOx Control Technologies for CalPortland Kiln 4.................................................. 25

Table 29. Base and Control Scenarios for NOx Used in CalPortland Units 1-4 RP Analyses..... 26

Table 30. Stack Parameters for CalPortland Units 1-4................................................................. 26

Table 31. 98th 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 ............. 28
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Table 35. Phoenix Cement Kiln Data ........................................................................................... 29

Table 36. Estimated Emissions and Production Rates for Phoenix Cement Kilns 1-4................. 30

Table 37. NOx Control Options for Phoenix Cement Kiln 4 ........................................................ 31

Table 38. Base and Control Scenarios for NOx Used in Phoenix Cement Unit 4 RP Analyses... 32

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

Table 40. 98th 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). NOx, SO2 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). NOx, SO2 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). NOx, SO2 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). NOx, SO2 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). NOx, SO2 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-7
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Document Change Record

Revision Date Remarks

0.1 October 3, 2012 Draft version submitted to EPA
EMAQ LOE (EPA Contract EP-D-07-102) WA 5-12: Task 9 Five-Factor Analyses for RP Facilities

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1 Introduction

This report describes the 5-factor analyses of all technically feasible NOx 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 follows:

1. Cost of compliance;

2. Energy and non-air quality impacts of compliance;

3. Any existing pollution control technology in use at each source;

4. Remaining useful life of the source, and 

5. Degree of visibility improvement that may be reasonably expected from the use of 

emissions controls.

Andover Technology Partners (ATP) estimated the cost of compliance for these units using 

EPA Control Cost Manual (EPA, 2002), cost estimation methods based on the latest Integrated 

Planning Model [IPM]) documented online by EPA (2010), and other reasonable engineering 

approaches. The control options were analyzed not only for the feasibility of implementation 

but also the first four factors listed above to estimate the total cost per year of each control 

technology, and the cost of emission reductions in $/TPY for each.

Once all the feasible control options were identified, EPA reviewed and recommended control 

configurations on all applicable units to examine the visibility impacts of their emissions. UNC 

performed these impact assessments using the base configuration of existing controls as well as 

all EPA-approved control configurations for each BART facility at all Class I Areas (CIAs) 

within a 300-km radius through the use of dispersion modeling. Per EPA requirements these 

analyses 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 

CIAs.

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

phase-partitioning of HNO3 between gas and particle based on additional 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 NOx 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. 
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2 Work Performed and Deliverable Summary

In the five-factor analysis performed in this task ATP examined NOx 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 assessments performed by UNC 

for each facility to estimate the control option effectiveness in a combined metric specified by 

EPA, namely, $/dv. The overarching considerations for the visibility impact assessments, 

including the CIAs that are potentially affected by these facilities are provided in Section 2.1. 

The 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 distances to the boundaries

of CIAs within a 300-km radius of the major emitting facilities in Arizona. The 19 CIAs and 

their nearest mean distances (as determined in the Task 4 screening) from the applicable

facilities 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 analysis are from CALMET v5.8 inputs and outputs provided by EPA from a 

BART analysis for 2001-2003 performed by ENSR Corporation for the Navajo Generating 

Station (ENSR, 2009).

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

CIA Short 

Name State Applicable Plant(s)from Nearest to Farthest

Respective Avg. Near 

Distances (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, 293, 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, 146, 167, 196

Sycamore Canyon syca AZ Phoenix, Cholla, Springerville, CalPortland 13, 146, 253, 287 

Zion zion UT Phoenix 275
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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 the 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”) specified 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 vary 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 options analyses because the BART Guidelines on which these analyses 

are based provide different methods for calculating baseline emissions for these two 

purposes. 

• The baseline emission inputs for NOx 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 SO2 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 analyses use the annual average emission values in tons per year 

(TPY) based upon actual emissions from baseline periods that reflect future anticipated 

annual emissions.

Specifics of the emissions used and the visibility impacts of base case and control scenarios are 

discussed in the sections on visibility and control effectiveness analysis for each facility.
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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 NOx control, and recently upgraded PM controls 

through the use of fabric filters (FF). SO2 emissions from these units are also quite low through 

the use of dry Flue Gas Desulfurization (FGD); thus only NOx 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 SO2 NOx SO2 Capacity 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 NOx Control Options Analysis

2.2.1.2.1 Available NOx Control Technologies

Springerville units have advanced combustion control technologies available (LNB and 

CCOFA). Thus additional NOx contols may not be possible with combustion controls. 
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2.2.1.2.2 Feasible NOx 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 NOx Control Technologies

For the cost estimates, baseline emissions and capacity factors for all electric utility units were 

developed from historical data as follows:

• Baseline NOx and SO2 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. NOx 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 draft loss that will increase parasitic loads of ~0.5% of plant 

output. SCR catalyst can be recycled and is therefore not a significant concern. 
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2.2.1.3 Visibility Modeling 

All four units at this facility were included in the visibility modeling. The baseline emissions 

and the control option scenarios were provided by EPA in spreadsheets1, and 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 Springerville, and the control 

effectiveness we estimated in $/dv for each of these control configurations.

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:

• Baseline NOx emission values were the maximum 24-hr average emission rate selected 

from the highest emitting day during 2008-2011 from CAMD for Units 1 and 2. 

• Units 3 and 4 used a constant NOx rate specified by EPA, corresponding to SCR and

LNB controls for all scenarios.

• SO2 and PM values were also held at the EPA-specified baseline for all units for all 

scenarios due to very low SO2 and PM emissions through the use of dry lime FGD and 

FF on all units. For SO2 the 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 during 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

∆-Emissions

(TPY)

Control 

Option

∆-Emissions

(TPY)

∆-Emissions

(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 Parameters

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 longitude coordinates were obtained 

 1 US EPA, RP_EGU_modeling_runs - EPA 20120816.xlsx
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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 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 within the 300-km radius of 

the Springerville plant were obtained from 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 the 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). Post-processing of POSTUTIL output with CALPOST 

used the IMPROVE methods 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 background visibility conditions at each CIA corresponding to 

(a) annual average background, and (b) 20% best background conditions. For both Method 6

and Method 8, CALPOST uses the input values of monthly-average relative humidity 

adjustment factor f(RH) rather than the hourly f(RH) values input on the VISB.DAT file 

generated by CALPUFF. The input data underwent extensive quality assurance (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. The 98th percentile visibility impairment and 

benefits are summarized here from Method 6(a) and 8(b) as defined above only for the 

composite 3-year period (corresponding to the 22nd 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 Velocity
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Table 6. 98th percentile visibility impairment (∆-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 Control Scenarios 

Corresponding 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)

estimating 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 (dv) 

comparisons between Tables 7(a) and 7(b); SNCR controls show lower benefits compared to 

SCR with either method, but the differences become less significant at the farthest CIAs. No

CIA shows a greater than 0.5 dv benefits from either method.
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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 (in millions) per year from Table 4 divided by the visibility improvement relative to base 

shown in Table 7 for each control scenario. The results are summarized in Table 8. 

Table 8. Control Effectiveness (million $/dv) for the Calculation Methods of Table 6

(a) (b)

Table 9. Summary of 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. Tables 8 and 9 show the highest $/dv (lowest effectiveness) at 

the CIAs farthest away, and Method 6(a) shows lower values of control effectiveness compared 
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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, equipped with modern combustion controls 

(separated OFA [SOFA] and LNB) for NOx. It also has a baghouse (FF) and a wet lime FGD 

system, thus PM and SO2 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

NOx SO2 NOx SO2

Capacity

Factor

MW gross lb/MMBtu lb/MMBtu %

1 113.6 C 0.188 0.118 0.220 0.202 86%

2.2.2.2 NOx Control Options Analysis

2.2.2.2.1 Available NOx Control Technologies

Since Cholla 1 already has some level of combustion controls the most effective additional 

controls are likely to be post-combustion.
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2.2.2.2.2 Feasible NOx Control Technologies

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

2.2.2.2.3 Evaluation of 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 as follows:

• Capacity factor was taken as the average of that estimated for the period 2008-2011 

using reported heat input and plant capacity information.

• NOx and SO2 emission rates were examined for the average period of 2008-2010 and 

2011. For NOx, the 2011 time frame was selected because it reflects operation of the 

Cholla units using advanced combustion controls, which is representative of anticipated 

annual emissions without additional post-combustion controls.

2

Table 11shows the NOx control options for Cholla 1 used in the RP visibility analyses. 

Table 11. NOx Control Technologies for Cholla 1

Cholla 1 – NOx

SNCR SCR

Capacity Factor 86% 86%

Control Efficiency 30.0% 77.3%*

Uncontrolled Rate

NOx Rate (lb/hr) 274 274

NOx Rate (lb/MMBtu) 0.220 0.220

NOx (TPY) 1032 1032

Controlled Rate

NOx Rate (lb/hr) 192 62

NOx Rate (lb/MMBtu) 0.154 0.050

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

2.2.2.2.4 Energy and Environmental Impacts of Control Options

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 are primarily due to ammonia slip; generally, 

 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 emissions 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 specified the baseline 

emissions and the control option scenarios, shown in Table 12, 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 NOx emissions are 

from a control case previously analyzed in the Task 8 BART analyses for these units, in 

which the maximum available NOx control (SCR) is applied on each at 83.5% control 

efficiency.

• For each of Units 1-4 the SO2 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 NOx emissions are for the current combustion controls (LNB and 

SOFA); they are reduced as appropriate for the NOx controls (SNCR and SCR) specified 

in Table 12 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 NOx baseline 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 SO2 emissions are specified as previously

• Control scenarios Ctrl2-3 and Ctrl2-4 apply SNCR and SCR controls, respectively, on 

Unit 1 with respect to the Rev Base-2 baseline NOx emissions. 

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

Control 

Option

Unit 1

Control

NOx D-Emis 

(TPY) $/year

Base LNB+SOFA 0 $0

Ctrl2-1 SNCR+LNB+SOFA 309 $999,045

Ctrl2-2 SCR+LNB+SOFA 797 $4,237,867

Rev Base-2 LNB+SOFA; FF

PM Spec 0 $0

Ctrl2-3 SNCR+LNB+SOFA 309 $999,045

Ctrl2-4 SCR+LNB+SOFA 797 $4,237,867

2.2.2.3.1 Stack Parameters

Table 13 lists stack parameters that APS transmitted to EPA on February 3 and amended March 

16, 2012. 
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Table 13. Stack Parameters for 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 

spreadsheets3. The input data were extensively quality-assured using customized Unix scripts.

The emissions data are also documented in Appendix A of this report.

• Filterable PM emission rates were calculated from the maximum day’s hourly average heat 

input multiplied by the ADEQ permit emission limit (0.015 lb/MMBtu) in the two base 

cases 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 FGD and 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

The CALPOST setup to calculate the visibility impacts for Cholla followed the steps described

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 

calculating visibility using its Unix-based extraction script named POSTCALPOST for 

submission to EPA in a tarfile of the modeling I/O. The 98th 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 22nd 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 14. 98th Percentile Visibility Impairment (∆-dv) for Cholla 1 Base Case and Control 

Scenarios: (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 300-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.
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Table 15. Visibility Benefits (dv) for 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 controls, 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 16 summarizes 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. Table 17 shows the summary results over the sum of all CIAs and at the area 

with the maximum impact (pefo). 
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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. The upper three natural gasfired 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 capacity factor is determined by 

dividing total reported heat input by the potential heat input if the unit were operating at 100% 

capacity every day of the year. Capacity factor is an important input for 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.
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Figure 3. TEP Sundt (Irvington) Power Plant.

Table 18. Sundt Power Plant Data

Unit Capacity

Fuel

2008-2010 

Reported Avg

2011 Reported 

Rates

2008-2011

Reported Avg

NOx SO2 NOx SO2 NOx

Capacity 

Factor

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 NOx Control Options Analysis

2.2.3.2.1 Available NOx Control Technologies

Availalble controls include combustion and post-combustion controls. 

2.2.3.2.2 Feasible NOx Control Technologies

Examined technologies for the Sundt gas units 1-3 are ultralow NOx burners (ULNB), SNCR, 

and SCR. All of these are both available and feasible; however, they generally would not be 

used in combination for gas-fired units. For example, SNCR becomes ineffective at very low 

NOx 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 external flue gas recirculation.
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2.2.3.2.3 Evaluation of 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 as follows:

• Capacity factors were taken to be the average of those estimated 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 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 control, with ULNB control cost at 

around $ 4,400/ton of NOx.

Table 19. NOx Control Techhnologies for Sundt Units 1-3

2.2.3.2.4 Energy and Environmental Impacts 

Combustion controls have a small energy 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 NOx reduction is possible for low NOx burners

Environmental 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 technologies 

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 

representation of the plumes. The EPA spreadsheets specified the baseline emissions and the 

control option scenarios for the modeling as with the previous two facilities. The 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 - NOx
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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 NOx emission rate 

in all the scenarios. 

Unit 1-3 NOx emissions reductions rely upon a base case annual emission factor 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 Units 1-3, these have PM emission 

values set to 0 in the base and control cases. SO2 emissions for Units 1-3 were held constant at 

the baseline levels from the previous BART analysis. Due to the low SO2 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 previous 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 NOx emission reductions on these units.

• In addition to the SCR control specified for NOx on Unit 4, Ctrl2-1 also uses dry sorbent 

injection (DSI) control for SO2 on this unit.

• Ctrl2-2 for Unit 4 uses base case values for NOx, and DSI controls for SO2.

Table 20. Base and Control Scenarios for NOx 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 

guidance. 

Table 21. 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

Stack Height Stack Elevation Stack Diameter Stack Temperature Exit Velocity
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report. We performed extensive QA of these inputs using customized Unix scripts to ensure 

compliance with the data on the spreadsheets4 provided by EPA. 

2.2.3.3.3 CALPOST Setup

We followed the modeling protocol delivered with the Task 5 report in setting up the 

CALPOST inputs for each of the 10 CIAs within 300 km of the Sundt 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 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 the CALPOST

inputs. 

2.2.3.3.4 Extraction of Visibility Results with POSTCALPOST

Table 22 summarize the results for the 98th 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) results 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 22. 98th Percentile Visibility Impairment (∆-dv) for 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 Effectiveness 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 each 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 effectiveness is greatest when SCR is applied on Unit 4.

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

(a) (b)
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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 1-3are somewhat high cost as seen in the $/ton 

reduction figures in Table 25, due to the low capacity factors and low NOx 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 Plant (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 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. However, all 4 kilns are being 

included in this RP analysis.
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Figure 4. Kilns at the CalPortland Cement Rillito Plant

Table 26. CalPortland Kiln Data5

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 NOx combustion controls, but it is unlikely that kilns 1-3 have any NOx controls

Table 27. Estimated Emissions and Production Rates for CalPortland Cement Kilns 1-4 

Kilns1-3 (each)* Kiln 4 Units Source

NOx Rate 8.70 3.59 lb/ton clinker EPA6

TPY clinker 121,000 969,000 Ton/yr PCA5

TPY clinker 143,157 1,053,932 Ton/yr EPA6

TPY NOx 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 NOx Control Options Analysis

2.2.4.1.1 Available NOx 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 NOx combustion controls in the calciner. Thus low NOx calciner is another option for kiln 

4. The cost of a Low NOx Calciner (LNC) is expected to be in the same range as MAT 7.

2.2.4.1.2 Feasible NOx 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, mid-kiln firing 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 further NOx 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 NOx 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% 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 information on Table 28(a) is per kiln.

Table 28(a). NOx 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 77
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Table 28(b). NOx 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 

SO2 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 dispersion 

calculations. The calculation steps are described in Section 2.2.4.2.2. 

For Kilns 1-3, maximum 24-hr average baseline emissions needed for the visibility modeling 

are based on NOx and SO2 emission factors representing the highest values reported over 2005-

2007, which was the most recent 3-year period of continuous operation. Annual emissions 

needed for the control cost estimates on these units were based on the NOx and SO2 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. The 

annual emission values used in the cost estimates for this unit are based on emission factors for 

NOx and SO2 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 filterable PM emission rate is limited to 0.008 gr/dscf. The EPA6 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.

 6 RP_Cement_modeling_runs - EPA 20120912.xlsx

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, 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 336 336 240 235
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The emissions for the NOx control cases are specified below, and tabulated in Table 29; in the 

base and control scenarios, EPA specified that the emissions of Units 1-3 should be lumped 

together as one source 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.

Table 29. Base and Control Scenarios for NOx 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 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 EPA6. 

Per EPA’s specification the emissions of Units 1-3 were combined in CALPUFF 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 of 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_modeling_runs - EPA 20120912.xlsx

Base 0 0 0 $0 $0

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 Velocity
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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 Visibility Results with POSTCALPOST

Table 31 summarizes the results for the 98th 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. 98th Percentile Visibility Impairment (∆-dv) for CalPortland Units 1-4 Base Case and 

Control Scenarios: (a) IMPROVE Method 6(a); (b) IMPROVE Method 8(b).

(a) (b)

Table 32. Visibility Benefits (dv) for CalPortland Units 1-4 for the Control Scenarios 

Corresponding to Table 31.

(a) (b)
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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 on 

Units 1-3.

Table 32 shows the greatest visibility benefits, as expected, at the most significantly impaired 

CIAs, 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 presented 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 separately 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 33 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 Table 31

(a)
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(b)

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 Association 8 on kiln capacity and characteristics are shown in Table 35.

Figure 5. Phoenix Cement Plant, Clarkdale, AZ

Table 35. Phoenix Cement Kiln Data5

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.
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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 NOx Control Options Analysis

2.2.5.1.1 Available NOx 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 NOx 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 availability 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 NOx reductions through MAT or LNC.

2.2.5.1.3 Evaluation of Control Technologies

Table 37 provides NOx control technologies and cost estimates for Phoenix Cement Kiln 4. 

Information on the type of NOx control technologies 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% NOx reduction, 

although for cost estimations LNB is more conservative. For 50% NOx reduction, both SNCR 

and SNCR in combination 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% NOx 

reduction; therefore in combination with combustion controls it should certainly be capable of 

that 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.

 6 US EPA, RP_Cement_modeling_runs - EPA 20120912.xls 5 Portland Cement Association, “US and Canadian Portland Cement Industry: Plant Information Summary”, 

December 31, 2006.
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Table 37. NOx Control Options for Phoenix 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 measures has a modest energy impact. MAT can have a beneficial 

impact on CO and SO2 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 NOx controls at 

Phoenix Cement Plant. The NOx and SO2 emission rates for this plant 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. Annual emissions needed for the cost estimates were also 

based on emission factors representing the average over this entire period. However the average 

clinker production rate used in converting these emission factors to annual emission rates for

SO2and NOx excluded the lower production rates from 2008-2010 as not being representative of 

future operations. 

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 precalciner with FF. 

The emissions for the NOx control cases are specified as follows, and tabulated in Table 38; in 

the base and control scenarios:

• Ctrl-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.
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Table 38. Base and Control Scenarios for NOx Used in Phoenix Cement Unit 4 RP Analyses

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 39. 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 EPA6

. 

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 98th 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 - EPA 20120912.xls

Control 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 Velocity
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Table 40. 98th Percentile Visibility Impairment (∆-dv) for 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 controls provide the greatest benefit of all technologies, as confirmed by the results 

in Table 41.

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

Corresponding to Table 40

(a) (b
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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)

Tables 42 and 43 separately present the control effectiveness for MAT and LNB due to their 

difference in cost. They show that the greatest 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. LNB is found to be the least effective control technology due to its 
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relatively high cost. Method 8(b) is found to be more effective than Method 6(a) due to its 

greater visibility benefits.

2.3 Conclusions

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

conclusions:

• The visibility impacts are greatest for each facility at the nearest CIAs, and the control 

options are least effective (greatest in million $/dv) at the farthest ones. The CIAs which 

experience the greatest visibility impacts and show the greatest benefits are listed below

for the respective facilities; the number of CIAs with impairment > 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 controls on Kilns 1-3 using Method 

8(b) (3 of 12), and

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

• Tables 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 compared to LNB and SCR

o MAT control compared to LNB and SNCR
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References

EPA, 2010: Documentation of EPA’s IPM Base Case v4.10, U.S. Environmental Protection 

Agency. http://www.epa.gov/airmarkets/progsregs/epaipm/BaseCasev410.html#documentation

EPA, 2002: EPA Air Pollution Control Cost Manual (Sixth Edition), Report No. EPA/452/B02-001, U.S. Environmental Protection Agency. 

ENSR, 2009: Revised BART Analysis for 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 

Reliability 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
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This appendix provides the emissions data for CALPUFF modeling of the base case(s) and control scenarios analyzed for the three 

EGU facilities. These data were extracted from a master spreadsheet that is being delivered as part of the documentation for this task. 

Table A-1(a). NOx, SO2 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. 
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Table A-2(a). NOx, SO2 and PM emission inputs for base and control scenarios for APS Cholla Unit 1 visibility modeling. 
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Table A-2(b). Speciated PM emission inputs for base and control scenarios for APS Cholla Unit 1 visibility modeling. 
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Table A-3(a). NOx, SO2 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. 
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Table A-4(a). NOx, SO2 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 modeling 
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Table A-5(a). NOx, SO2 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 controls:

• 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 Gas)

• 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) 

methods8

, 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/epaipm/BaseCasev410.html#documentation
5-3 www.AndoverTechnology.com

5.1 Arizona Portland Cement Company, 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 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 

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 expected 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 kiln, not total for the three kilns.

 10 US EPA, RP_Cement_modeling_runs - EPA 20120912.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 SO2 emissions. SNCR and SCR can result in ammonia slip, which is generally 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 characteristics 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”, 

December 31, 2006.
5-7 www.AndoverTechnology.com

Table 5-5. Estimated Uncontrolled Emissions 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 the 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 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 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 Cement 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 combustion 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 20120912.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 SO2 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
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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 Absorbers with a reverse air baghouses for SO2 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 SO2 NOx SO2

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 

parasitic 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-fired 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 Cholla 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 

performing 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 

possible 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 data 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 factors 

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 control, 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.

Combustion 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 

typically 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 aspirated15 and have an ebullient-cooled, 

co-generation system that produces both heat 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 Wastewater 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 Maintainer, 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 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.

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 gas 

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 injection. 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 efficiency, 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 provide 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 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). However, it was made an emergency 

generator21 and may not operate enough to warrant retrofit.

 18 Email from GE, September 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 nonOEM 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 show 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.

Water 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 at 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 leanburn 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 level 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 efficiency, 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 leanburn 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

Tables 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, Clark 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