# Technical Analysis for Arizona and Hawaii Regional

Haze FIPs : Task 7

: Five

- Factor BART Analysis for Chemical Lime Company Nelson, TEP Sundt (Irvington), and Catalyst Paper (Snowflake) Plants

Contract No: EP

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- 12 Version : 1

Prepared for: Thomas Webb

Air Planning Office U.S. EPA Region 9 75 Hawthorne Street San Francisco, CA 94105

Prepared by: Uma Shankar

, Elizabeth Adams, Mohammad Omary

,

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

Mark Lee , Juanita Haydel and Thomas Meyers ICF International

Jim Staudt Andover Technology Partners

Date delivered : October 9

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# Contents

Figures

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

Tab les

................................ ................................ ................................ ................................ ............ 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 Nelson Lime Units 2 and 3

................................ ................................ .................. 4

2.2.2 Sundt Unit 4

................................ ................................ ................................ ....... 14

2.2.3 Catalyst Paper (Snowflake) Pulp Mill , Units 1

- 3

................................ .............. 24

2.3 Conclusions

................................ ................................ ................................ ................... 36

References

................................ ................................ ................................ ................................ .... 38

Appendix A

Emissions Data Tables

Appendix B Andover Technology Partners Report Chapter 3: BART Analysis (NO
x 

### , SO 2 

### and PM)EMAQ LOE (EPA Contract EP

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# Figures

Figure 1. Nelson Lime Plant

................................ ................................ ................................ ........... 4

Figure 2. Sundt Plant

................................ ................................ ................................ ..................... 14

Figure 3. Power Boilers and Coal Pile at Catalyst Paper (Snowflake) Pulp Mill

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# Tables

Table 1. CIAs Within 300 km of CLC Nelson, Sundt and Catalyst Paper

................................ ..... 2

Table 2. Emissions and Controls at Nelson Lime Plant

................................ ................................ .. 4

Table 3. NO
x 

### Emission Reductions from Rotary K ilns with Various Control Technologies

......... 5

Table 4. NO
x 

### Control Technologies for Nelson Lime Units 2 and 3

................................ .............. 6

Table 5. SO 2 

### Emission Reductions from Rotary Kilns with Various Control Technologies

......... 7

Table 6. SO 2 

### Control Technologies for Nelson Lime Units 2 and 3

................................ .............. 8

Table 7. Control Scenarios Used in Nelson Lime Visibility Modeling

................................ .......... 9

Table 8. Stack Parameters for Nelson Lime Units 1

- 3

................................ ................................ ... 9

T able 9. 98th percentile Visibility Impairment ( 

- dv) f or Nelson Lime Scenarios Using IMPROVE Method 6 (a) and (b) Method 8(b)

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

Table 10(a) . Visibility Benefits (dv) of Control Options for IMPROVE Method 6(a)

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

Table 10(b). Visibility Benefits (dv) of Control Options for IMPROVE Method 8(b)

................ 12

Table 11. Control Eff

ectiveness (million $/dv) for the Calculation Methods of Table 9

............. 12

Table 12 . Control Effectiveness (million $/dv) Summary for the Calculation Method s

of T able 9

................................ ................................ ................................ ...................... 13

Table 13. Sundt Power Plant Data

................................ ................................ ................................ 14

Table 14. NO
x 

### Contol Technologies for Sundt Unit 4

................................ ................................ .. 16

Table 15. SO 2 

### Contol Technologies for Sundt Unit 4

................................ ................................ .. 17

Table 16. Control Scenarios Used in Sundt Visibility Modeling

................................ ................. 18

Table 17. Stack Parameters for Sundt Units 1

- 4

................................ ................................ ........... 18

Table 18. 98th percentile Visib ility Impairment ( 

- dv) for Sundt Scenarios Using

(a) IMPROVE Method 6(a) and (b) Method 8(b)

................................ ........................ 20

Table 19. Visibility Benefits (dv) of Control Options for the Calculation Methods of Table 18

. 21
Table 20. Control Effectiveness (million $/dv) for the Calculation Methods of Table 18

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

Table 18

................................ ................................ ................................ ........................ 23

Table 22. Catalyst Paper Boiler Data

................................ ................................ ............................ 24

Table 23. Evaluated NOx Control Technolog ies for Catalyst Paper

................................ ............ 25

Table 24. NO
x 

### Control Costs for Catalyst Paper Excluding Impact on Fly Ash

.......................... 26

Table 25. SO 2 

### BART Contr ols Evaluated for Catalyst Paper by Abitibi Bowater

....................... 28

Table 26. ATP Analysis of SO 2 

### BART Controls and Performance at Catalyst Paper

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### Table 27. Estimated Cost of a New Fabric Filter on Boiler #2 at Catalyst Paper

........................ 30

Table 28. Control Scenarios Used in Catalyst Paper Visibility Modeling

................................ ... 30

Table 29. Stack Parameters for Catalyst Paper Units 1

- 3

................................ ............................. 31

Table 30. 98th Percentile Visibility Impairment ( 

- dv) for Catalyst Paper Using

(a) IMPROVE Method 6(a) and (b) Method 8(b)

................................ ........................ 33

Table 31. Visibility Benefits (dv) of Control Options for the Calculation Methods of

Table 30

................................ ................................ ................................ ........................ 34
Table 32. Control Effectiveness (million $/dv) for the Calculation Methods of Table 30

........... 35
Table 33. Control Effectiveness Summary (million $/dv) for the Calculation Methods of

Table 30

................................ ................................ ................................ ........................ 36

Table A

- 1(a). NO
x 

### , SO 2 

### and PM Emission Inputs for Base and Control Scenarios for Nelson

Lime Visibility Modeling

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

- 2

Table A

- 1(b). Speciated PM Emission Inputs for Base and Control Scenarios for Nelson Lime

Visibility Modeling

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

- 3

Table A

- 2(a). NO
x 

### , SO 2 

### and PM Emission Inp uts for Base and Control Scenarios for Sundt

Unit 4 Visibility Modeling

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

- 4

Table A

- 2(b). Speciated PM Emission Inputs for Base and Control Scenarios for Sundt

Unit 4 Visibility Modeling

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

- 5

Table A

- 3(a). NO
x 

### , SO 2 

### and PM Emission Inputs for Base and Control Scenarios for Catalyst

Paper Visibility Modeling

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

- 6

Table A

- 3(b). Speciated PM Emission Inputs for Base and Control Scenarios for Catalyst Paper

Visibility Modeling

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

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# Document Change Record

Revision Date Remarks

0.1 October 9 , 2012 Draft version submitted to EPAEMAQ LOE (EPA Contract EP

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# 1 Introduction

This report describes the 5

- factor BART analyses of all technically feasible NO
x 

### control options

on the applicable units at the three facilities as listed below :

 Chemical Lime Company (CLC) Nelson Plant Units 2 and 3

 Sund t ( TEP Irvington) Generating Station Unit 4

 Catalyst Paper (Snowflake) Pulp Mill Units 2

. The five factors considered in these analyses are as follows:

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

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

, and
5. D egree of visibility improvement that may be reasonably expected from the use of
BART emissions controls.

Andover Technology Partners (ATP) estimate d the cost of compliance for thes e units using data provided by Arizona Department of Environmental Quality (ADEQ) and the EPA Control Cost
Manual (EPA, 2002 ) . With assistance from ICF, ATP also examine d data from EPA’s latest power sector modeling (I ntegrated Planning Model [IPM] ) method s 1



### , and other reasonable engineering methods to ensure consistency with the assumptions used in its control cost analyses. The control options were analyzed not only for th e feasibility of implementation but
also the first four factors listed above to esti mate the total cost per year of each control technology and the cost of control per year for each

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

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

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

, and EPA

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

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

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

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

- partitioning of HNO 3 

### between gas and particle based on 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 

- dv

, corresponding to the visibility

- impairing pollutant emission s reduction for each control option relative to the base configuration was used along with the

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

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### yearly cost of control to estimate the con trol cost effectiveness in $/dv at each CIA . It is also reported as the cost of the maximum dv benefit over all the CIAs, and for the dv benefit
summed over all the CIAs.



# 2 Work Performed and Deliverable Summary

In t he five

- factor analysis performed in this task ATP examined NO
x 

### , SO 2 

### and particulate matter (PM) control options and their costs for each of the three facilities considering the first
four factors listed in Section 1. UNC used t hese cost estimates along with it s visibility impact

assessment s 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 are provided in Section 2.1 . T he five

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



## 2.1 General Considerations for Visibility Modeling

In Task 4 of this WA UNC used a GIS software tool to determine the nea rest distance D ( km ) to the boundar ies of all the CIAs within a 300

- km radius of the major emitting facilities ; The 16 CIAs and their nearest mean distances (as determined in the Task 4 screening) from the applicable BART facilities are listed in Table 1. The domain description and Lambert
Conformal Conic (LCC) projection parameters to obtain the coordinates of the facilities and
CIAs came from meteorolog ical inputs for CALMET v5.8 provided by EPA from BART analysis by ENSR Corporation (ENSR, 2009) for the Navajo Generating Station for 200 1

- 2003 ; this domain and meteorological inputs were also used in the CALPUFF modeling in this task

.

Table 1. CIAs W ithin 300 km of CLC Nelson, Sundt and Catalyst Paper

CIA Short

Name State Applicable Plant(s) from

Nearest t o Farthest Respective Avg
Near Distance s (km)
Bryce Canyon brca UT Nelson 236

Chiricahua NM chir AZ Sundt, Cat

. Paper 145, 299

Chiricahua Wilderness chrw AZ Sundt 140

Galiuro Wilderness gali AZ Sundt, Cat. Paper 63, 211

Gila Wilderness gila NM Sundt, Cat. Paper 129 , 194
Grand Canyon NP grca AZ Nelson , Cat. Paper 25 , 204

Joshua Tree NP jotr CA Nelson 237

Mazatzal Wilderness maza AZ Cat. Paper, Sundt, Nelson 113, 201, 205
Mount Baldy Wilderness moba AZ Cat. Paper, Sundt 99, 231,

Petrified Forest NP pefo AZ Cat. Paper 39

Pine Mountain Wilderness pimo AZ Cat. Paper, Nelson, Sundt 136, 198, 246
Saguaro NP sagu AZ Sundt, Cat. Paper 26, 267

Sierra Ancha Wilderness sian AZ Cat. Paper, Sundt, Nelson 96, 178, 288
Superstition Wilderness supe AZ Ca t. Paper, Sundt, Nelson 135, 136, 285 Sycamore Canyon
Wilderness syca AZ Nelson, Cat. Paper 131, 154

Zion zion UT Nelson 183EMAQ LOE (EPA Contract EP

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### The CALPUFF model set

- up for the three facilities followed the guidance of the modeling protocol that was delivered to EPA on March 19, 2012 as a Task 5 deliverable. This modeling protocol invokes almost all the model input settings recommended in the WRAP BART Subject
Protocol ( 2006) inclu ded 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
CA LPUFF inputs through a series of test runs. Of note, CALPUFF modeling used a constant value of 1 ppb throughout for ammonia per EPA guidance

. The CALPUFF model was run in each year 2001

- 2003, and the outputs were processed in the POSTUTIL proce ssor to redistribute the HNO3 and PM nitrate using additional inputs. This step was necessitated by the limitations of CALPUFF v5.8 in modeling the gas

- particle partitioning and formation of particulate nitrate. The annual concentration files output by
POSTUTIL were combined in APPEND into a composite 3

- year concentration file for visibility post

- processing. CALPOST was used to determine the 98 th 

### percentile visibility impairment and the visibility benefits of control in the years 2001

- 2003, and in the composite period. Further facility

- specific details on the visibility analys e s are provided in Section 2.2

.



## 2.2 Five

- Factor Analyses

This section describes the control options analysis, followed by the details of the visibili ty 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. The costs of compliance and visibi lity 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 effectiveness values 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 p rovides a more realistic assessment of “ existing pollution control technology in use at e ach source ” than a uniform baseline for all units.

 The baseline emissions used in the CALPUFF modeling are not identical to those used in the control option s analyses because the BART Guidelines provide different methods for calculating baseline emis sions for these two purposes

.

 The baseline emission inputs for NO
x 

### and SO 2 

### u se the 24

- hour average emission rate from the highest emitting day of a representative baseline period (excluding periods of

start

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

.

 The baseline emission inputs for PM for visibility modeling are derived from the hourly plant heat input (from the CEMS database) multiplied b y emission limits specified in ADEQ’s BART determinations for these units

. This approach to estimating PM emissions accounts for the fact that EPA is proposing to approve ADEQ’s BART emission limits for PM at these units, and that these emission limits wil l go into effect prior to any NO
x 

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###  The control cost analysis uses annual average emission s (TPY) based o n actual emissions from a baseline period r epresenting a ntici pa ted future annual emissions

. The visibility impacts of the control scenarios are discussed in the sections on visibility and control effectiveness analysis for each facility.

2.2.1 Nelson Lime Units 2 and 3



## 2.2.1.1 General Plant Information

Nelson Lime plant (Figure 1) has two ro tary kilns subject to BART ( U nits 2 and 3) rated at 859 and 1,145 tons per day, respectively

. There are no additional PM controls at the facilites beyond baghouses (fabric filters [FF]), and the one on Kiln 1 has been more recently installed. 2 

### . Each
kiln emits through a separate chimney; Table 2 summarizes the emissions data for the facility.

Figure 1

. Nelson Lime Plant

Table 2. Emissions and Controls at Nelson Lime Plant

Nelson Kiln 1 Nelson Kiln 2 D ata Source
Maximum daily production, tons/da y 859 1,145 Nelson
BART
Submittal Emission Factors, lb/ton of product (lb/hr)
NO

x 

### 2.66 (95) 2.08 (99)
SO 2 

### 3.29 (118) 7.87 (375)
PM10 0.0423 (1.51) 0.0702 (3.35)
Controls Baghouse Baghouse, Multicyclone Permit

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## 2.2.1.2 NO

x 

## Control Options Analysis

Coal com bustion in t he Nelson Lime Plant kilns is the source of NO
x 

### emissions from this facility. It is unclear if any NO
x 

### controls are installed, and for the purposes of this study it will
be assumed that none are installed.



## 2.2.1.2.1 Available NO
x 

## Control Technologies

Tab le 3 shows technologies available for control of NO
x 

### from kilns and the expected percent
red uction

. As shown in the table , NO
x 

### reductions are possible through combustion controls or

t hr ough post

- combustion controls. This table was developed from data appli cable to Portland
Cement kilns.

Besides low NOx burners (LNBs) , mid kiln firing (MKF) , mixing air technology (MAT),
Selective Non

- Catalytic Reduction ( SNCR ) and SCR are available . These can be combined for higher NO
x 

### reduction than possible individually

. S ince the two Nelson plant kilns are preheater kilns, the most likely location for SNCR reagent injection is the preheater, where there is likely
to be an available temperature window. For conservatism, it was assumed that SNCR in
combination with other tec hnologies provides a NO
x 

### reduction of 30% rather than 50%.

Table 3. NO
x 

### Emission Reductions from Rotary Kilns with Various Control Technologies †

NOx Control Technology Expected NOx Emissions Reduction (%)

Low

- NOx Burner (LNB) 30

Mid

- Kiln Firing 3 0
Mixing Air Technology (MAT) 3 30

SNCR

- Urea 50

SNCR

- Ammonia 50

SCR 80
† 

### Source : ILEPA (2007)



## 2.2.1.2.2 Feasible NO
x 

## Control Technologies

All of the technologies discussed in the BART study a re feasible

. However, since SCR has had
little or no known usage his tory on lime kilns, and a limited history in cement kilns, ATP regard ed this technology as unfeasible and d id not provide that evaluation. Also, since MKF with tires may not be an option for lime kilns

, and its capital cost is much higher than some of
the other combustion controls, it is not likely to be very economical and was thus not evaluated
further. MAT reduces NO
x 

### emissions

, but has a potential drawback in that it promot es gypsum formation in the product during SO 2 

### capture

.



## 2.2.1.2.3 Evaluation of NO
x 

## Contro l Technologies

There are limited data on cost for NO
x 

### controls for lime kilns, and thus much of this evaluation

was derived from data on cement kilns. In this case cost information developed for EPA’s Industrial Sector Integrated Solutions (ISIS) model was also used where applicable

. 4

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### Table 4 show s the results of comparison of NO
x 

### emissions for the two Nelson kiln s using feasible technologies. For conservatism in the cost estimates , it was assumed that LNB would be deployed in lieu of MAT to achieve 30% N O
x 

### reduction. Use of MAT rather than LNB would be less expensive, but increased gypsum formation in the product from SO 2 

### capture might be undesireable. I n the case of SNCR, a 50% reduction from uncontrolled levels was assumed . When combined with LNB

, ATP assumed an additional 30% reduction of NO
x 

### by
SNCR after the 30% reduction by LNB

, for a total 51% reduction (=1.00

– 0.7*0.7)

. In either case, 50% reduction should be achievable and the costs shown in Tables 4(a) and ( b ) are conservative

. Table 4

. NO
x 

### Con trol Technologies for Nelson Lime Unit s 2 and 3

Nelson Kiln 1 Nelson Kiln 2

LNB SNCR LNB and SNCR LNB SNCR LNB and SNCR

TPD Lime 859 859 859 1,145 1,145 1,145

Uncontrolled emissions Uncontrolled NOx,
lb/ton 2.66 2.66 2.66 2.08 2.08 2.08

PPH NOx 95 95 95 99 99 99 TPY NOx (90% capacity factor) 375 375 375 391 391 391

Controlled Emissions

Reduction 30% 50% 51% 30% 50% 51%
Controlled NOx, lb/ton 1.86 1.33 1.30 1.46 1.04 1.02

PPH NOx 67 48 47 69 50 49 TPY NOx (90% capacity factor) 263 188 184 274 196 192

Control Costs
Capital Cost $2,389,443 $679,055 $3,068,499 $2,857,256 $806,849 $3,664,105

Total Annualized Cost $396,129 $216,179 $597,335 $459,000 $235,465 $678,858
$/ton removed $3,518 $1,152 $3,121 $3,911 $1,204 $3,403 incremental, $/ton

rem oved $3,518

- $2,397* $2,553 * $3,911

- $2,857* $2,676*

*incremental cost compared to cost of LNB with 30% reduction since both of these provide roughly the same total
NOx reduction



## 2.2.1.2.4 Energy and Environmental Impacts

These technologies will have a very modes t energy impact, requiring some additional auxiliary
electrical load. NO
x 

### controls do have a potential environmental impact, but the extent of the negative impact is unclear . Modern burners have the benefit of much more advanced design
methods than those u sed in earlier equipment and may even reduce carbon levels in fly ash while reducing NO
x 

### . In cases where carbon increase s to untenable levels it can be mitigated by adjusting excess air levels , which will , however, have an adverse impact on NO
x 

### reduction. SNCR technolog y also has the potential to result in ammonia on fly ash (ammonia slip) , which may impact fly ash sales; however, this is dependent upon the coal fly ash pH and other factors.

4 Memo from J. Staudt to R. Strivastava, et. al., regarding “Costs and Performance of Controls

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### Ammonia slip can generally be controlled to leve ls that do not adv ersely impact fly ash sales

. EPRI performed a study in 2007 that examined the effects of ammonia slip from SCR systems and reached the conclusion that “The survey overwhelmingly indicated that ammonia contamination is not impacting the ability of plants to sell ash”. 5



## 2.2.1.3 SO 2 

## Control Options Analysis

SO 2 

### emissions from cement kilns are primarily from raw materials (limestone) rather than from
coal combustion, which is mostly captured in the kiln and ends up in the product

. However, fuel sulfur is more likely t o be emitted in the form of SO 2 

### in the case of lime kilns that try to avoid sulfur in the product, than in the case of cement kiln s . Changing raw material sources is generally not possible ; thus , “add

- on” controls are likely to be needed to reduce SO 2 

### emis sions.



## 2.2.1.3.1 Available SO 2 

## Control Technologies

Table 5 shows available SO 2 

### control technologies. As discussed earlier, MAT may reduce SO 2 

### , but as it increas es gypsum in the product, it is unclear if it would be deployed for a lime kiln.

Table 5

. S O 2 

### Emission Re ductions from Rotary Kilns with Various Control Technologies

Technology Percent Removal Mixing Air (MAT) Varies: assume

~ 30% Dry Lime Injection

~ 50% Dry Sorbent Injection (DSI) using SBC 75%

Dry FGD 90

- 95%

Wet FGD 95%



## 2.2.1.3.2 Feasible S O 2 

## Control Technol ogie s
All of the technologies are potentially feasible. Because FF is already installed on each kiln, a dry sorbent injection (DSI) system would likely be very effective. Lime and sodium bicarbonate (SBC) are potential DSI reagents, as is trona; however, S BC is preferable for SO 2 

### capture. In practice, L’Hoist, the owner of the Nelson Plant, may choose to use a highly activated lime hydrate that they manufacture

, in place of SBC , as it is capable of similar SO 2 

### removal rates

. DSI using SBC provides a reasona ble surrogate for estimating the control cost of DSI using activated lime hydrate. Dry FGD is iikely to require a second baghouse because there does not appear to be room to install an absorber between the preheater and the FF , particularly for
K iln 2, and in any event, there may not be adequate space under the existing baghouses for air slides or recycle systems that wo uld be used on a dry scrubber. Regardless, a dry FGD would provide similar SO 2 

### removal as a wet FGD, and was evaluated as a conservative ap proach. Wet lime or limestone FGD is feasible, and would be installed downstream of the existing baghouse.



## 2.2.1.3.3 Evaluation of S O 2 

## Control Technologies

Table 6 shows the estimated costs and emission rates for the three technologies evaluated for
the two kilns. D SI with SBC appears to have lower cost and higher reduction than dry lime injection (DLI), largely due to waste disposal costs associated with the higher material input for

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### DLI

. However this analysis does not account for any difference in disposal cost per ton of waste
for DLI versus SBC. Nor does it address any modifications to baghouse operation that may be

necessary as a resu lt of installing a DSI system. The wet scrubber has the highest removal, but also the highest cost. The SO 2 

### reductions possible wit h MAT will vary.

The wet FGD capital cost shown here may be overestimated because very limted data re available. Costs were developed from data on wet FG D costs for cement kilns, which are also
rather limi ted as few cement kilns are equipped with wet scrub bers. M ost cost information has been gle a ned from BACT analyses

, described in supporting documentation for the ISIS model

. 6



### Table 6. SO 2 

### Control Technologies for Nelson Lime Units 2 and 3

Nelson Kiln 1 Nelson Kiln 2

MAT Dry

Lime DSI with

SBC Wet FGD MA T Dry
Lime DSI with

SBC Wet FGD

Historical SO 2 , lb/ton 3.29 3.29 3.29 3.29 7.87 7.87 7.87 7.87

Historical SO 2 , pph 118 118 118 118 375 375 375 375

Percent Removal 30% 50% 75% 95% 30% 50% 75% 95%

Outlet SO 2 , pph 82.4 58.9 29.4 5.9 262.5 187.5 93.8 18.8

Outlet SO 2 , lb/ton 2.30 1.65 0.82 0.16 5.51 3.94 1.97 0.39
% change in stack Velocity No Change No

Change No

Change - 20% No Change No

Change No

Change - 20%

Exit temp No Change No

Change No

Change 130 F No Change No

Change No

Change 130 F

Impact on PM

s peciation No Change No

Change No

Change Yes

, FF plus

scrubber No

Change No

Change No

Change Yes, FF plus

scrubber
Capital Cost $754,196 $770,000 $409,382 8,082,077 $807,040 $1,940,000 $1,034,122 10,772,967

Annualized Costs $176,364 $545,415 $389,957 $1,3 69,380 $183,466 $1,502,933 $1,040,460 $1,958,408

TPY removed (90% capacity factor) 139 232 348 441 443 739 1109 1404

$/ton removed $1,266 $2,350 $1,120 $3,105 $414 $2,033 $938 $1,395

Incremental $/ton $1,266 $3,975 ($1,3 40) $10,550 $414 $4,463 ($1,251) $3,105



## 2.2.1.4 PM Control Options

The Nelson Plant already has fabric filters installed on both kilns. As a result there is no additional technology available that provides a higher degree of PM reduction than what is
alread y installed

.



## 2.2.1.5 Visibility Modeling

Although Nelson Lime Units 2 and 3 are the only units for which a BART determination is being made

, Unit 1 was included in the visibility modeling for a realistic representation of the plumes

. The EPA reviewed the control options presented in Table s 4 and 6 and provided a set of
control technology co nfigur ations for Nelson Lime U nits 2 and 3 for the visibility modeling. In

6 Memo from J. Staudt to R. Srivastava , E. Torrez, K. Barnett, Re: Wet Scrubber Cost Algorithms, Feb 26, 2010EMAQ LOE (EPA Contract EP

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### the following sections we describe the inputs used for Nelson Lime , and the control
effectiveness we e stimated in $/dv for each of these configurations

.

Table 7

. Control Scenarios Used in Nelson Lime V isibility M odeling

Control Option Unit 2 Unit 3 All Units All Units

Control (s)
Used 

- Emis (TPY) Control (s)
Used 

- Emis (TPY) 

- Emis (TPY) $/year

SO 2 NO

x SO 2 NO

x SO 2 NOx SO 2 +NO

x
Base Case 0 0 0 0 0 0 $0

Ctrl

- 1 DLS 232 0 DLS 739 0 971 0 $2,048,348

Ctrl

- 2 SBC Inj. 348 0 SBC inj. 1109 0 1457 0 $1,430,417

Ctrl

- 3 Wet FGD 441 0 Wet FGD 1404 0 1845 0 $3,327,788

Ctrl

- 4 0 0 Wet FGD 1404 0 1404 0 $1,958 ,408

Ctrl

- 5 Wet FGD 441 0 0 0 441 0 $1,369,380

Ctrl

- 6 MAT 139 0 MAT 443 0 582 0 $359,830

Ctrl

- 7 SNCR 0 187 SNCR 0 195 0 382 $451,644

Ctrl

- 8 LNB+SNCR 0 191 LNB+SNCR 0 199 0 390 $1,276,193



## 2.2.1.5.1 Stack Parameters

The stack parameter data for Nelson Lime Unit s 1

- 3 used in the visibility modeling were obtained from the ADEQ BART reports for Units 2 and 3 and from the WRAP Planning Inventory of 2002 for Unit 1. Table 8 summarizes the stack parameters input to CALPUFF. Also shown in Table 8 are the changes in the stack parameters when wet FGD control is implemented, as it changes both the plume exit velocity and the stack temperature.

Table 8. Stack Parameters for Nelson Lime Units 1

- 3



## 2.2.1.5.2 CALPUFF Emissions Inputs and Setup

EPA provided extensive guidance on the em issions data for all the BART sources analyzed in
this WA . These data are documented for each applicable facility and unit in Table B

- 1 of the modeling protocol submitted as a Task 5 deliverable, and in the supporting spreadsheet documentation for this rep ort

. The input data underwent extensive quality assur ance (QA) using scripts created for the purpose by UNC. T he emissions data sources are described below and the
data are shown in Table A

- 1 of Appendix A. :

 The only data available for this 3

- unit plant ar e the WRAP BART analysis data of 2007 (WRAP, 2007); these were used as baseline emissions for all pollutants for all units.EMAQ LOE (EPA Contract EP

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o 

### PM speciation information was obtained from the National Park Service (NPS) spreadsheet data for the relevant source type, in this case, "Coal Fired Rotary Lime Kiln Fabric Filter Example" (see http://www.nature.nps.gov/air/Permits/ect/docs/limeK/2006FinalCoalfiredRotar yLi meKilnFFSpeciation.xls ).

Following the CALPUFF modeling, the concentration files were input to the POSTUTIL processor for the repartitioning of nitrate between gas and particulate phases, as the version of
CALPUFF used does not have the advancements in chemistry available in the later versions. The POSTUTIL output concentration files for 2001

- 2003 were combined in the APPEND utility to produce a composite 3

- year file , which was provided along with the annual files for CALPOST visibility processing.



## 2.2.1.5.3 CAL

POST Setup

As with the CALPUFF modeling, the CALPOST model setup followed the modeling protocol.
Post

- processing of POSTUTIL output with CALPOST used both IMPROVE Methods 6 and 8 (submode 5) for calculation and comparison of the incremental visibility impa irment ( 

- dv) relative to background at the affected CIAs. Each method used two sets of background visibility conditions in these assessments, corresponding to (a) annual average background, and (b) background visibility on the 20% best visibility days at the CIAs

. For both methods , CALPOST uses the input values of monthly

- average relative humidity adjustment factor f(RH)

, rather than the hourly values on the VISB.DAT file generated by CALPUFF. CALPOST input data were extensively quality

- assured using scripts creat ed for this purpose by UNC.



## 2.2.1.5.4 Extraction of Visibility Results with POSTCALPOST

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

- based extraction script named POSTCALPOST. The resul ts for the 98 th 

### percentile incremental visibility impairment 

- dv relative to background visibility at the 9 CIAs listed in Table 1 within 300

- km of Nelson Lime Plant for each year modeled (2001

- 2003)

, and for the composite 3

- year period are documented in the supporting spreadsheet documentation submitted with this report. The results in this report are from Method 6(a) and 8(b) for the composite 3

- year period 2001

- 2003. Table s 9 (a) and (b) summarize the incremental visibility impairment relative to backgro und ( 22nd highest 

- dv , corresponding to 98 th 

### percentile) at each CIA within 300 km of Nelson Lime Plant for the b ase c ase and controls
scenarios from Method 6(a) and Method 8(b) respectively.EMAQ LOE (EPA Contract EP

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### Table 9

. 98th p ercentile V isibility I mpairment ( 

- dv) for Nelson Lime S cenarios U sing

IMPROVE Method 6 (a) and (b) Method 8(b)

(a)

( b )



### The maximum impairment is seen from Table 9 to occur at Grand Canyon National Park (grca) using either calculation method, and is higher than 0.5 dv for all scenarios. IMPROVE Method 8(b) estimates equ al or higher impairment compared to 6(a) for all scenarios and CIAs, but the difference decreases with increasing distance from the CIAs. SNCR on both kilns appears to produce the least impairment at the most visibility

- impaired CIAs, but lower levels of
i mpairment are also seen for the use of wet FGD at the farther CIAs (e.g., Sierra Ancha).

Table 10 shows the greatest benefits occurring at (grca), but no CIA shows a benefit exceeding
the minimum of 0.5 dv. The SNCR controls with and without LNB show virt ually no benefit at the farther CIAs; SO 2 

### controls, and in particular, the use of wet FGD on both kilns seem to be more effective from the visibility perspective in these locations.

Table 10 (a)

. Visibility B enefits (dv ) of C ontrol Option s f or IMPROVE Met hod 6(a)

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### Table 10(b)

. Visibility Benefits (dv) of Control Options for IMPROVE Method 8(b)

(b)



## 2.2.1.6 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 7 divided by the visibility improvement relative to base
from Table 10 for each control scenario. The r esults are summarized for each CIA in Table 1 1

. In both visibility methods, at the worst impaired CIA (grca) the highest control effect iveness (i.e., lowest $/dv) values are with SNCR, and MAT. However, at most CIAs farther away from Nelson Lime, e.g., Pine Mountain and Sierra Ancha, the SO 2 

### control options of wet FGD on
Unit 3 and DSI with SBC are seen to be more cost effective than SNCR and MAT. This is
reflected in the difference between the effectiveness values for the maximum

- impact CIA and
the dv benefits summed over all CIAs in Table 12.

Table 1 1

. Control E ffectiveness (million $/dv) f or the C alculation M ethods of Table 9

(a)

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### Table 1 2

. Control E ffectiveness (million $/dv) Summary for the

Calculation Method s of Table 9

(a)

(b)



### Comparing t he results of Table12(a) and (b) for the control effectiveness using dv summed o ver all CIAs against that using the dv for the CIA with the maximum impact

, the wet FGD control
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### impact. At the CIA with maximum dv impact, the most cost

- effective controls are achieved with SNCR, followed by MAT, as estimated by either visibility method.

2.2.2 Sundt Unit 4



## 2.2.2.1 General Plant Information

Unit 4 of the Sundt plant (formerly Irvington) shown in Figure 2 is a coal

- fired boiler that was found to be subject to BART from our previous analyses in Task 6 of this WA. Table 13 displays the modeled and reported data for Sundt Unit 4 as an average over 2008

- 2010, and as an annual average averaged for 2011. The capacity factor , which is important in performing cost
effective ness calculations

, is determined by dividing total reported heat input by the potential heat input if the unit were operating at 100% capacity

, 36 5 days a year

. Sundt Unit 4 has a ba g house (FF) for PM control. In addition it is equipped with LNB and
overfi re air (OFA) for NO
x 

### control.

Figure 2

. Sundt Plant

Table 1 3

. Sundt Power Plant Data

Unit Capacity

Fuel 2008

- 2010 Reported Avg 2011 Reported
Rates 2008

-

2011

NO
x SO 2 NO
x SO 2 Capac ity
Factor

MW gross lb/MMBtu lb/MMBtu %

Unit 4 173.3 Coal 0.361 0.4 77 0.445 0.729 37%EMAQ LOE (EPA Contract EP

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## 2.2.2.2 NO

x 

## Control Options Analysis

2.2.2.2.1 Available NO
x 

## Control Technologies

Both combustion and post

- combustion controls are available.



## 2.2.2.2.2 Feasible NO
x 

## Control Technologies

Since Sundt 4 already has combustion controls by way of LNB and OFA, the focus of ATP’s cost analysis was on post

- combustion controls.



## 2.2.2.2.3 Evaluation of NO
x 

## Control Technologies

Although only post

- c ombustion controls were examined, some advanced forms of OFA may permit further reductions. The results of this evaluation are shown in Tabl e 14.

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

 The c apacity factor is the average of that estimated for the period 2008

- 2011 using reported heat input an d plant capacity information.

 NO
x 

### and SO 2 

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

- 2010 and
2011. T he 2011 rate was selected as the baseline rate for estimating cost effectiveness.

In addition, a capital recovery factor of 9.44% (equal t o 7% over 20 years) plus tax and insurance costs of 1.2% were assumed in the cost analysis. This rate for taxes and insurance differs from what is used for industrial sources per the EPA Air Pollution Control Cost Manual,
and is consistent with what has be en determined for electric generating units per the IPM
documentation. 7



## 2.2.2.2.4 Energy and Environmental Impacts

SNCR has negligible energy impact. SCR will incur an additional parasitic loss, mainly due to pressure drop across the SCR system, which is roughly eq ual to 0.59% of output. Although the
IPM calculations for which these algorithms were developed treated this not as a cost , but as a reduction in capacity

, in these calculations it has been treated as an increase in variable operating cost s

. 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.
A mmonia slip can be well controlled so that fly ash is not adversely impacted. SCR catalyst can be recycled and therefore is not a significant concern.

7 From Integrated Planning Model ver 4. 10 documentation

, page 8

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### Table 1 4

. NO
x 

### Contol Technologie s for Sundt Unit 4

Sundt 4

- NOx

SNCR SCR

Capacity Factor 37% 37%

Control Efficiency 30% 89%

Uncontrolled Rate

NOx Rate (lb/hr) 813 813

NOx Rate (lb/MMBtu) 0.445 0.445

NOx (TPY) 1318 1318

Controlled Rate

NOx Rate (lb/hr) 569 91

NOx Rate (lb/MMBtu) 0.31 0.05

NOx (TPY) 923 148

Tons/Year Removed 395 1,170
Total Cost, $/year $1,308,000 $5,712,715

$/Ton $3,307 $4,882

$/Ton (incr emental) $3,307 $5,686 * 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



## 2.2.2.3 SO 2 

## Control Options Analysis

SO 2 

### emission rates increased in 2011 from the 2008

- 2010 av erage, indicating a change in coal.



## 2.2.2.3.1 Available SO 2 

## Control Technologies

Available t echnologies for Sundt are DSI , wet and dry FGD , and a change to lower sulfur coal.



## 2.2.2.3.2 Feasible SO 2 

## Control Technologies

All of the available technologies are feasible. In fact, DSI is well suited to this unit since it is equipped with FF control

. A dry FGD at Sundt Unit 4 is assumed to include a new FF since
there is probably not enough space to install a new absorber between the boiler and the existing
FF. A wet FGD would be ins talled downstream of the existing FF

.



## 2.2.2.3.3 Evaluation of of SO 2 

## Control Technologies

A change in coal was not evaluated for cost since coal cost data was not available.

Table 15 shows the estimated cost of each of the SO 2 

### control technologies. In light of the l ow capacity factor and high capital costs of FGD , the two FGD approaches are much more expensive than DSI ( based on $/ton s SO 2 

### removed ). DSI is expected to have high control
efficienc y due to the existing FF

. The FGD removal efficiencies are limited by ass umptions in the Sargent & Lundy model developed for CAMD that was used for the FGD cost analysis

. In practice, we would expect both dry and wet FGD to achieve higher capture efficiencies and
therefore somewhat lower emissions levels , i.e., the Table 15 res ults are conservative

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### Table 15. S O 2 

### Contol Technologie s for Sundt Unit 4



## 2.2.2.3.4 Energy and Environmental Impacts of Cont rol Option s
The energy impacts of DSI are small. FGD will have significant energy impacts (over 1% of output) due to pressure loss across the FGD system, and the additional pumping power and auxiliary loads involved. Energy costs are included for each tech nology analyzed in Table 15.

DSI using trona or SBC will result in increased solids collected by FF. These sodium

- based materials may result in a by

- product with a water

- soluble component that may require some stabilization. The use of activated lime hydra te might avoid this problem. DSI has other benefits
to air emissions.

Both the wet and dry scrubbers will hav e waste product s . The dry scrubber waste is stable and
can be disposed of in landfills . The wet scrubber waste can be dewatered and sold to the

gyp sum market. More information on these impacts is available in Section 2.1.2 of the ATP report attached in Appendix B

.



## 2.2.2.4 PM Control Options

Sundt Unit 4 is equipped with FF , and there is no technology available that would provide a higher degree of PM reduct ion than a properly designed and operated FF

. Therefore, there are no changes assumed to the PM emission rates under the BART analysis. Sundt 4

– SO2

DSI Dry FGD Wet FGD Capacity Factor 37% 37% 37% Control Efficiency 75% 89% 92%

Uncontrolled Rate



### S O 2 

### Rate (lb/hr) 1333 1333 1333


### S O 2 

### Rate (lb/MMBtu) 0. 729 0.729 0.729


### S O 2 

### (TPY) 2160 2160 2160

Controlled Rate



### S O 2 

### Rate (lb/hr) 333 146 110


### S O 2 

### Rate (lb/MMBtu) 0.18 0.08 0.06


### S O 2 

### (TPY) 540 237 178

Tons/Year Removed 1620 1923 1982 % change stack velocity No Change

- 10%

- 20% Exit temp No Cha nge 175 F 130 F Impact on PM speciation No Change Yes, FGD plus FF Yes, FGD plus FF Total Cost, $/year $2,967,501 $12,553,539 $13,986,681
$/Ton $1,832 $6,529 $7,057 $/Ton (incremental) $1,832 $31,647 $24,189EMAQ LOE (EPA Contract EP

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## 2.2.2.5 Visibility Modeling

Sundt Unit 4 is subject to BART controls, but for realistic representation of the emission plumes a ll four units of the plant were included in the CALPUFF model inputs. EPA reviewed the control options presented in Tables 14 and 15 and recommended the control configurations for the modeling presented in Table 16. The following sections describe the cont rol scenarios,
and the input data assumptions and sources of data for the various visibility modeling components.

Table 16. Control Scenarios Used in Sundt Visibility Modeling

Control Option Unit 4 All Controls

SO 2 Control 

- Emis SO 2

(TPY) NO

x Control 

- Emis NO

x (TPY) SO 2 +NO

x



- Emis (TPY) $/year

Base Case LNB+OFA;

FF 0 LNB+OFA; FF 0 0 $0

Ctrl

- 1 DSI 1620

- 0 1620 $2,967,501

Ctrl

- 2 Dry FGD 1923

- 0 1923 $12,553,539

Ctrl

- 3 Wet FGD 1982

- 0 1982 $13,986,681

Ct rl

- 4 0 SNCR 395 395 $1,308,000

Ctrl

- 5 DSI 1620 SNCR 395 2015 $4,275,501

Ctrl

- 6 Dry FGD 1923 SNCR 395 2318 $13,861,539

Ctrl

- 7 Wet FGD 1982 SNCR 395 2377 $15,294,681

Ctrl

- 8 0 SCR 1170 1170 $5,712,715

Ctrl

- 9 DSI 1620 SCR 1170 2790 $8,680,216

Ctrl

- 10 Dry FGD 1923 SCR 1170 3093 $18,266,254

Ctrl

- 11 Wet FGD 1982 SCR 1170 3152 $19,699,396



## 2.2.2.5.1 Stack Parameters

Table 1 7 lists stack parameters for Sundt, taken from the National Emission Inventory 2008 Version 2; stack elevation was taken from the WRAP BART ana lysis of 2007 8 

### . The table includes changes in the exit velocity and temperature for each of the FGD control scenarios, as
recommended in Table 15.

Table 1 7

. Stack Parameters for Sundt Units 1

- 4

8 Summary of WRAP BART Modeling for Arizona, Draft #5, May 25, 2007. See http://pah.cert.ucr.edu/aqm/308/bart.shtmlEMAQ LOE (EPA Contract EP

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## 2.2.2.5.2 CALPUFF Emissions Inputs

The modeling requirements and data sources for emissions for Sundt Units 1

- 4 were specified by EPA. These data are documented in Table B

- 1 of the modeling protocol submitted as a
Task 5 deliverable, and in the supporting spreadsheet documentation for this report. They are
included for conve nience in Table A

- 2, Appendix A. The input data were extensively quality

assured using scripts created for this purpose by UNC. The emission data for Sundt were input
as follows:

 The baseline emission rates for NO
x 

### and SO 2 

### for all four units were obtained from CEMS for the average hourly emission rate of the maximum emission day during a period of continuous operation from 2008

- 2010. Units 1

- 3 of Sundt are natural

- gas fired boilers, and in all scenarios modeled their NO
x 

### and SO 2 

### emission rates were held at t heir
baseline values.

 The EPA’s initial guidance on th e emissions for these scenarios called for the use of the WRAP BART analysis (WRAP, 2007) for PM emissions from all units. However, that analysis covered only Unit 4 and one out of three of the natural gas

- fired units. Thus the WRAP emission rates were used only for Unit 4.

o 

### PM speciation for Unit 4 was derived using the NPS speciation spreadsheets for dry

bottom coal

- fired boiler with fabric filter (see http://www.nature.nps.gov/air/Permits/ect/docs/coalBoiler/2006FinalDryBottomPC_ FFpmSpeciationProfile.xls ).

o 

### The heating value , ash content and sulfur content of Rout Company (CO) coal needed for PM speciation were provided by EPA

.

 As reliable PM emissions information was not available for Units 1

- 3, and their PM emission rates are very low compared to the NO
x 

### and SO 2 

### emissions from the facility, EPA eventually recommended that the PM em issions from Units 1

- 3 be set to zero. Thus no PM emissions or speciation data are provided for these units.

The CALPUFF modeling and the post

- processing of CALPUFF output files in POS TUTIL to provide concentration inputs to CALPOST followed the procedure described for Nelson Lime
in Section 2.2.1.5.2.



## 2.2.2.5.3 CALPOST Setup

T he CALPOST setup to calculate the visibility impact s for Sundt follow ed the steps described
for Nelson Lime in Section 2.2.1. 5.3

, using customized scripts to QA the large number of inputs , con sisting of 9 CIAs to be processed for the base case and 11 control scenarios

.



## 2.2.2.5.4 Extraction of Visibility Results with POSTCALPOST

UNC extracted the results from the CALPOST visibility analysis for the four methods of calculating visibility using POSTCALPOST . The results for the 98 th 

### percentile incremental visibility impairment 

- dv relative to background visibility at the 9 CIAs listed in Table 1
within 300

- km of the Sundt Plant for each year modeled (2001

- 2003), and for the composite
three

- year period are documented in the supporting spreadsheet documentation submitted with
thi s report. The results in this report are from Method 6(a) and 8(b) for the composite period
2001

- 2003. Tables 18(a) and (b) summarize the incremental visibility impairment relative toEMAQ LOE (EPA Contract EP

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### background (22nd highest 

- dv, corresponding to the 98 th 

### percentile) at each CIA within 300 km of the Sundt Plant for the base case and controls scenarios from Method 6(a) and Method 8(b) respectively.

Table 18 shows g reater visibility impairment for Method 6 (a) compared to Method 8 (b)

. The maximum visibility impairment due to Sundt is seen at Saguaro for both visibilit y methods. The lowest values of visibility impairment at this CIA are obtained with SCR controls combined
with DSI

. However, at CIAs that are farther away such as Mazatzal and Mount Baldy, the visibility impairme nt is least for SCR with (dry or wet) FGD controls.

Table 18. 98th percentile Visibility Impairment ( 

- dv) for Sundt Scenarios Using

(a) IMPROVE Method 6 (a) and (b) Method 8(b)

( a )

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### The above conclusion is confirmed by Table 19, which shows that th e visibility benefits are greatest at Saguaro for SCR combined with DSI, followed by only SCR control. This applies to both visibility methods. At the more distant CIAs, the benefits are comparable among several technologies, including, in addition to thes e, SO2 control options such as dry and wet FGD in combination with the post

- combustion NO
x 

### controls.

Table 19

. Visibility B enefits (dv) of C ontrol Option s f or the Calculation M ethods of Table 18

( a )

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## 2.2.2.6 Control Effectiveness Results

This section disc usses the control cost effectiveness in $/dv for each control option at each CIA,
at the CIA with the maximum dv impact, and for the dv impact summed over all CIAs. Tables 20(a) and (b) show the comparisons on a CIA

- specific basis. The most effective contr ol options when costs are considered are, in order, SNCR without and with dry FGD when considering impacts over all CIAs. At the most impaired CIA, SNCR is still the most cost

- effective, followed by SCR alone, and SCR combined with DSI. The post

- combustion NO
x 

### control outweighs the effectiveness of SO 2 

### controls, because of the higher NO
x 

### emissions and their commensurate impact as well as the control efficiencies of these technologies. These results hold for both visibility methods.

T able 20

. Control E ffect iveness (million $/dv) f or the Calculation Methods of Table 18

(a)

(b)



### The summary results are presented in Table 21. A comparison of the $/dv value using the summed visibility impacts over all CIAs shows that the SO 2 

### controls (DSI, wet and dry FGD)

a re clearly more cost

- effective for the CIAs farther away than for nearest ones, and that DSI is
much more cost

- effective at the nearest CIA in combination with SCR and SNCR, rather than as a sole control option. SCR, due to its much higher cost is not as c ost

- effective as SNCR despite its much greater control efficiency. Finally, Method 8(b) sho w s greater effectiveness than Method 6(a) for all control options and CIAs.EMAQ LOE (EPA Contract EP

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### Table 21

. Control E ffectiveness (million $/dv) Summary for the

Calculation Methods of T able 18

(a)

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### 2.2.3 Catalyst Paper (Snowflake) Pulp Mill, Units 1

- 3



## 2.2.3.1 General Plant Information

Figure 3 shows a Google Earth image of this three

- unit plant; all of which are power boilers

. Plant data and capacity factors for the plant are provided in Table 22

. Boiler #2 , subject to BART, is coal

- fired with a rated heat input of 1

, 132 MM Btu/hr when firing coal ; it may also

use residual oil. ATP’s analysis examined methods for reducing NO
x 

### and SO 2 

### at the mill.

Figure 3

. Power Boilers and Coal Pile at Catalys t Paper (Snowflake) Pulp Mill

Table 22

. Catalyst Paper Boiler Data

Data Element Data Source Boiler Type ( U nit 2) Wall Fired BART Submittal Boiler Heat Input Boiler 1: 523 MMBtu/hr with Nat Gas, 472 MMBtu/hr
with Oil Boiler 2: 1132 MMBtu/hr with Coal, 111 0 MMBtu/hr with
Oil Boiler 3: 337 MMBtu/hr with Nat Gas, 315 MMBtu/hr
with Oil Permit, page 45

Boiler Combustion Configuration Existing NOx Controls Unit 3 has a low NOx burner listed in their permit, the
other two have no NOx controls. Permit

Current NOx Emission Rate (lbs/MMBtu) Cap of 0.3 lb/MMBtu while burning oil in Unit 2. Cap of 0.7 lb/MMBtu while burning coal in Unit 2. Permit

Coal Type(s) Western Bituminous (Lee Ranch El Segundo) BART Submittal Ash Content (%) 17.9 BART Submittal
Sulfur Con tent (%) 1.03 BART Submittal Approx. Heating Value ( B tu/lb) 9290 BART Submittal
Additional Info rmation on Emissions Controls Slipstream Wet Alkaline Scrubber by Flakt (tray type)
installed on Unit 2 1990 must run 100% of the time.
Treats 43% of Unit 2 f

lue gas Permit and EIA
Form 860

SO 2 Emission Rate Cap of 1.0 lb/MMBtu while burning oil for Units 1&3, Cap of 0.8 lb/MMBtu while burning oil or coal for Unit 2 Permit

NO

x Emission Rate (unit 2) 0.70 lb/MMBtu BART Submittal
PM Emission Rate Cap of 0.10 lb/MMBtu Permit
PM controls

- efficiency

- calculated emissions rate

- typical emissions rate Hot Side ESP

– no conditioning
99.2% 0.154 lb/MMBtu (from efficiency and fuel) 0.02 lb/MMBtu (from 2005 EIA form 767) EIA Form 860,
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## 2.2.3.2 NO

x 

## Control Options Analysis

I n this section the results of ATP’s analysis of a prior BART study conducted by Abitibi
Bowater in January 2008 are presented. Based on this evaluation ATP made its final recommendations on control options and evaluated the cost of these controls for Catal yst Paper.



## 2.2.3.2.1 Available NO
x 

## Control Technologies

Technologies evaluated for AbitibiBowater in its BART analysis for NO
x , 

### and the projected
emissions reduction s are shown in Table 23 . They cover all major cate gories of NO
x 

### controls.



## 2.2.3.2.2 Feasible NOx Control Techn ologies

All of the technologies shown in Table 23 are feasible. The emissions targets developed by CH2MHill, Abitibi Bowater’s consultant who performed the BART analysis

, incorporate additional margin over that offered by the technology supplier that varie s by technology type.

Table 23. Evaluated NOx Control Technologies for Catalyst Paper



## 2.2.3.2.3 Evaluation of of NO
x 

## Control Technologies

ATP reviewed t he capital and operating costs directly associated with the NO
x 

### control technology analysis performed for Abit ibiBowater , along with energy and environmental impacts. These costs all appeared to be reasonable, with the exception of SCR catalyst replacement cost, which seemed high. For a boiler of the size of Boiler 2 at C atalyst P aper,

~ 150 m 3 

### of catalyst is expec ted (typically 1

- 1.5 m 3 

### per 1000 MMBtu/hr) . If half of that catalyst is replaced every two years, the cost is

~ 75 m 3 

### x $5000/m 3 

### or $375,000 every two years, i.e.,
less than $200,000 per year. Regenerated catalyst would reduce this cost by another

~ 40%, to about $120,000/year. Thus the $200,000 year ly cost for SCR catalyst shown in Table 24 is a
conservative estimate.

The capital recovery factor of 13.5% assumed by AbitibiBowater roughly adds up to the combination of debt service (7% over 20 years, or 9.44% annually) and taxes, insurance andEMAQ LOE (EPA Contract EP

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### administrative costs

. EPA ’s Control Cost Manual suggests using 4% of capital cost

, 9 

### resulting
in 13.44% total annual cost.

Abitibi Bowater further assumed an additional indirect cost to NO
x 

### control associated with all fly ash being disposed of rather than sold

. T he impact of NO
x 

### controls on fly ash is likely overstated, by this assumption. Thus ADEQ requested, and Abitibi Bowater provide d supporting information on their fly ash purchase agreement , but did not address why t hey all fly
ash was assumed to be unmarketable. As noted in Section 2.2.1.2.4, ammonia on fly ash can be controlled to levels that do not adversely impact fly ash sales.

For the purpose of this BART analysis, the additional margin on NO
x 

### emission reductio n assumed by Abitibi Bowater’s consulting engineer is assumed to provide adequate margin to allow for the possibility of operating at a higher NO
x 

### level than guaranteed by the supplier and for the likelihood of not having an impact on fly ash sales.

The co sts from Abitibi Bowater’s BART analysis were considered reasonable with the exception of the estimated impacts on fly ash. The costs from the BART analysis are shown in
Table 24 with the exception that the cost assigned to fly ash impacts from the NO
x 

### con trol are not included in the total cost and the estimate of $/ton of NO
x 

### removed. Another difference is the assumed capital recovery rate is 9.4% (consistent with 7% interest over 20 years) and an additional 4% for taxes, administrative , and insurance (per EPA’s control cost manual ) . The estimated $/ton of NO
x 

### removed is lower than what was estimated by Abitibi Bowater’s consultant, largely because of the difference in the way fly ash effects were addressed

. For the purpose of modeling, Cases 3 and 4 of Tab le 24 can be ignored since they would not be
selected on the basis of cost.



## 2.2.3.2.4 Energy and Environmental Impacts

Energy impacts have been evaluated and the cost shown as increased electrical load.

Environmental impacts of the combustion controls have a potent ial impact on fly ash; however, the original assumption made by Abitibi Bowater’s consultant that all of the fly ash would be affected is the worst case. In fact, many electric utility boilers firing many types of coals have
combustion NO
x 

### controls and sel l fly ash. Therefore, this assumption was considered an overstatement and ignored in this case.

Table 24

. NO
x 

### Control Cost s for Catalyst Paper Excluding Impact on Fly Ash

Case #

NO
x Control 1

OFA with Existing
Fan 2

LNB 3

MOBOTEC
ROFA 4

MOBOTEC
RO FA and
Rotamix
SNCR 5

LNB
w/OFA 6

LNB w/
OFA and
HERT
SNCR 7

LNB with
OFA and
SCR Heat Input Rate,
MMBtu/hr 1132 1132 1132 1132 1132 1132 1132 Capacity Factor 100% 100% 100% 100% 100% 100% 100% Heat Value,
Bu/lb 9,290 9,290 9,290 9,290 9,290 9,290 9, 290

9 EPA Air Pollution Control Cost Manual, Sixth Ed., 2002, Sect. 2.5.5.8, p p. 2

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NO
x Control 1

OFA with Existing
Fan 2

LNB 3

MOBOTEC
ROFA 4

MOBOTEC
RO FA and
Rotamix
SNCR 5

LNB
w/OFA 6

LNB w/
OFA and
HERT
SNCR 7

LNB with
OFA and
SCR
Historical Emissions Rate Modeled Rate, pph* 914 914 914 914 914 914 914
NOx (lb/MMBtu) 0.7 0.7 0.7 0.7 0.7 0.7 0.7 NOx, pph 792 792 792 792 792 792 792 NOx, TPY 3,471 3,471 3,471 3,471 3,471 3,471 3,471

Contro lled Emissions Rate

NOx (lb/MMBtu) 0.525 0.37 0.348 0.291 0.265 0.194 0.07 NOx, pph 594 419 394 329 300 220 79 NOx, TPY 2,603 1,835 1,725 1,443 1,314 962 347 NOx, Removed,
TPY 868 1,636 1,745 2,028 2,157 2,509 3,124

Percent
Removed 25% 47% 50 % 58% 62% 72% 90%
Total Installed
Cost $20,000 $1,462,02
0 $4,536,126 $5,964,840 $2,088,600 $2,792,400 $22,950,507
Fixed O&M $25,740 $84,221 $207,185 $228,616 $109,284 $119,841 $137,689
Non Fuel Var
O&M $1,802 $1,802 $468,389
Make U p Water $4,322 $499 $246,973
Urea/Ammonia $416,723 $347,240 $87,485 SCR Catalyst $200,000
Elect. Load $74,685 $323,637 $327,109 $3,472 $189,122

Annualized Capital $1,888 $138,004 $428,178 $563,039 $197,149 $263,583 $2, 166,366

Taxes, Admin,
Insurance $800 $58,481 $181,445 $238,594 $83,544 $111,696 $918,020

Net Cost $103,113 $280,706 $1,140,445 $1,780,204 $389,977 $848,133 $4,414,044

$/ton NOx $119 $172 $653 $878 $181 $338 $1,413

Incremental $/t on NOx $119 $231 $7,882 $2,264 ($10,784) $1,301 $5,800

* Modeled rate is the rate used by UNC in their historical modeling. Other historical rates are from AbitibiBowater BART study and may be more representative of average rate for the purpose of estimating cost effectiveness in $/ton
removed.



## 2.2.3.3 SO 2 

## Control Options Analysis

2.2.3.3.1 Available SO 2 

## Control Technologies

The Abitibi Bowater BART analysis also included evaluation of SO 2 

### control tech nologies. In this case only two options were considered in their analysis : (1) upgrade of the existing caustic wet scrubber, which only treats up to 43% of the flue gas as needed to ensure that the unit
emissions remain below the permitted limit of 0.8 lb/MMBtu, and (2) addition of a second sodium wet FGD system that w ould allow treatment of 100% of the flue gas, as shown in
Table 25. This is not a comprehensive lis t of possible control options. Other control options include dry FGD, which would offer the advantages of reduced water consumption, lower operating costs du e to less expensive lime reagent

, and much less costly disposal of waste,
much lower PM emissions, and elimination of liquid waste

. H owever, dry FGD would not provide the same level of SO 2 

### removal and would have a higher capital cost than the wet
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### allow segregation of fly ash with the hot

- side electrostatic precipitator s (ESPs) for sale into the
concrete market. Another available technology is lower sulfur coal.

Ta ble 25. SO 2 

### BART Controls Evaluated for Catalyst Paper by Abitibi Bowater



## 2.2.3.3.2 Feasible S O 2 

## Control Technologies

All of the available technologies are feasible.



## 2.2.3.3.3 Evaluation of S O 2 

## Control Technologies

An order of magnitude estimate of the cost of a dry FGD sys tem was developed by scaling the published cost information on the Turbosorp dry scrubber installed at the Greenidge power plant, and this is provided in an Excel workbook as supporting documentation for this report

. Table 26 compares control costs for all feasible control technologies. Total costs are shown as
well as costs of controls relative to historical costs. The proposed costs relative to historical
costs and proposed emissions reductions versus historical emissions are used to calculate the $/ton o f SO 2 

### removed.

Table 26. ATP Analysis of SO 2 

### BART Controls and Performance at Catalyst Paper

Parameter Case

Historical 1 Case

Historical 2 Case

1

Scrubber Upgrade Case

2

Replace with new Dry Lime
Scrubber Case

3
Add ’l Sodium
Scrubber and Up graded
Scrubber

Heat Input Rate, MMBtu/hr 1132 1132 1132 1132 1132 Capacity Factor 100% 100% 100% 100% 100% Heat Value, Bu/lb 9,290 9,290 9,290 9,290 Coal Sulfur, % 1.03% 1.03% 1.03% 1.03% Uncontrolled SO2, lb/MMBtu 2.22 2.22 2.22 2.22
Uncontrolle d Annual SO2 Emissions, tons 10,994 10,994 10,994 10,994
Historical Emissions Rate Modeled Rate, pph * 555 555 555 555 555 SO2 (lb/MMBtu) 0.799 0.799 0.799 0.799 0.799 SO2, pph 904 904 904 904 904 SO2, TPY 3,962 3,962 3,962 3,962 3,962
Controlled Em issions Rate SO2 (lb/MMBtu) 0.80 0.80 0.74 0.111 0.04 SO2, pph 904 904 837 126 50 SO2, TPY 3,962 3,962 3664 550 220 SO2 Removed, TPY 0 0 298 3,412 3,742EMAQ LOE (EPA Contract EP

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Parameter Case

Historical 1 Case

Historical 2 Case

1

Scrubber Upgrade Case

2

Replace with new Dry Lime
Scrubber Case

3
Add ’l Sodium
Scrubber and Up graded
Scrubber

Percent Removed from
historical 0 0 7.5% 86.1% 94.5%

% change in stack velocity none none None

- 1 0%

- 20% Exit temp No change No change No change 175 F 130 F

Impact on PM speciation? none none none Yes

– add FF Yes

- all gas
scrubbed Total Installed Cost $650,000 $32,949,187 $15,650,000

Fixed O&M $60,665 $60,665 $60,665 $1,123,555 $90,99 8
Non Fuel Var O&M $42,102 $42,102 $42,102 $236,704 $84,204 Make Up Water $47,801 $115,960 $102,767 $15,780 $170,530
Reagent $691,653 $2,308,793 $2,308,793 $2,278,391 $3,395,285 Scrubber Waste Disposal $937,462 $3,129,323 $3,129,323 $669,604 $4,601,946 Fly Ash Disp/Lost Ash ($889,759) ($1,400,085) ($1,400,085) ($1,400,085) ($1,400,085)

Elect. Load $673,696 $673,696 $673,696 $852,134 $640,312 Annualized Capital $0 $0 $61,355 $3,110,170 $1,477,249 Taxes, Admin, Insuranc e $0 $0 $26,000 $1,317,967 $626,000 Annual Cost, incl ash $1,563,620 $4,930,454 $5,004,616 $8,204,221 $9,686,439 Cost of Control (note

– fuel costs are not shown, all control estimates assume the same fuel as Historical 2)
Net Cost, $/yr, grea ter than Historical 2 $74,162 $3,273,767 $4,755,985 $/ton of SO2 removed compared to historical $249 $960 $1,271 Incr. $/ton of SO2 removed $249 $1,027 $4,495
* Modeled rate is the rate used by UNC in their historical modeling. Other hist orical rates are from AbitibiBowater BART study and may be more representative of average rate for the purpose of estimating cost effectiveness in $/ton removed



## 2.2.3.4 PM Control Options Analysis

The permitted PM emissions rate for Catalyst Paper is 0.1 lb/MMBt u; however, the recently proposed industrial boiler MACT has a PM em ission limit of 0.044 lb/MMBtu. It is unclear if
this will motivate the installation of a new FF system. Since boiler # 2 has a hot

- side ESP, upgrade of the ESP is not a likely an option. Therefore a FF is a viable option, and would ideally be installed downstream of a dry FGD system

, or upstream of a wet FGD system ; cost of
the long ductwork that this will require has been included in the capital cost . The FF with the dry FGD program at th e Greenidge plant was seen in tests to produce an emission rate of
0.001 lb/MMBtu. Typical guarantee values might be in the range of 0.015 lb/MMBtu or less

. An estimate of a dry FGD system was developed for estimating the cost of a system placed after
the scrubbed and unscrubbed gas streams are joined and prior to the chimney. The estimated
cost is shown in Table 27

, as ~$21M to install a FF

, which is about two

- thirds the cost of a dry
scrubber with FF . It should also be not ed that when a dry scrubber is in stalled with FF for SO 2 

### control, the PM control is a cobenefit of installing the dry scrubber. For this reason a DLS , as described in Table 26 would be very beneficial for both SO 2 

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### Table 27. Estimated Cost of a New Fabric Filter on Boiler # 2 at Catalyst Paper

ACFM $ 408,300 Total Capital Requirement $21,413,481 Annualized Capital $2,021,281 Taxes, Admin, Insurance $856,539.25

M aintenance $509,604 Variable Operating Cost $427,038

Total Cost $3,814,463 Rated MMBtu/hr 1132
Modeled Rate, pph * 113 Current PM Rate, lb/MMBtu 0.1 pph 113.2

TPY 496 Rate with new FF, lb/MMBtu 0.015 pph 16.98

TPY 74
Percent Reduced 85% Tons reduced per year 421
Total Annualized Cost $3,814,463 $ per ton reduced $9,051

* Modeled rate is the rate used by UNC in their historical modeling. Other historical rates are

based on permit limit.



## 2.2.3.4.1 Energy and Environmental Impacts

A new FF will require an additional booster fan and power, as well as compressed air, and the

co sts of these a re included in the analysis. The new FF will also improve capture of mercury
and other toxic materials

.



## 2.2.3.5 Visibility Modeling

EPA reviewed the control options presented in Table s 2 4, 26 and 27, and provided a set of control technology combinations for Cataly st Paper Unit 2 for the visibility modeling. Table 2 8 provides the final list of eight control configurations used in the visibility modeling . They represent incremental controls on SO 2 

### and NO
x 

### up to the maximum controls (Ctrl

- 7), and the impact of these w hen combined with a new fabric filter (Ctrl

- 8) . To bracket the emission
reductions achievable Ctrl

- 3 also examines the benefit of FF as the only control in effect. The emissions inputs for the modeling are discussed in Section 2.2.3.5.2.

Table 2 8

. Control Scenarios Used in Catalyst Paper Visibility ModelingEMAQ LOE (EPA Contract EP

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## 2.2.3.5.1 Stack Parameters

Stack parameters for Catalyst Paper Unit 2 and the stack elevations for all units were taken from the ADEQ BART report

. All other parameters were taken from the NEI 2008 Version 2. In addition to the base case values for the stack parameters, Table 29 also includes the changes in stack temperature and exit velocity for the control cases involving scrubber installation, per the guidance of Table 26.

Table 29

. Stack Parameters for Catalys t Paper Units 1

- 3



## 2.2.3.5.2 CALPUFF Emissions Inputs

Emission requirements for CALPUFF modeling were specified by the EPA , and are tabulated in
Table B

- 1 of the modeling protocol submitted as a Task 5 deliverable, and in the master spreadsheet documentation for t his report , excerpted in Appendix A, Table A

- 3

. We performed extensive QA of these inputs using customized scripts that we have developed. The following is a summary of the data sources and assumptions used in emission inputs for the CALPUFF modeling for C atalyst Paper :

 The NO
x 

### , SO 2 

### and PM baseline emissions for the uncontrolled Unit 1 were calculated by using their capacity heat inputs (472 MMBtu/hr and 315 MMBtu/hr respectively)

, multiplied by the ir respective ADEQ permit emission limits (lb/MMBtu) as des cribed in
the Title V submittal

. For Unit 3 EPA provided the permit emission limits.

 Unit 2 NO
x 

### , SO 2 

### and PM baseline emissions were obtained from the WRAP BART analysis report of 2007 10



### .

o 

### Unit 2 OFA with hot

- side ESP and FGD; as an exact speciation profile m atch is not available in the NPS PM speciation spreadsheets, the PM speciation was specified as an average of the speciation profiles for a dry

- bottom coal

- fired boiler with ESP and

FGD, and one with ESP (see http://www.nature.nps.gov/air/Permits/ect/docs/coalBoiler/2006FinalDryBottomPC_ FGD_ESPpmSpeciationProfile.xls and http://www.nature.nps.gov/air/Permits/ect/docs/coalBoiler/2006FinalDryBottomPC_ ESPpmSpeciationProfile.xls

o 

### Units 1 and 3 used the speciation profile of an industrial residual oil boiler (see http://www.nature.nps.gov/air/Permits/ect/docs/oilBoiler/2006FinalUncontrolledInd ustrialResOilBlrpmSpeciationProfile.xls )

.

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### The CALPUFF modeling and the post

- processing of CALPUFF output files in POSTUTIL to provide concentration inputs to CALPOST followed the procedure described for Nelson
Lime in Section 2.2.1.5.2.



## 2.2.3.5.3 CALPOST Setup

There are 1 2 CIAs within 300

- km of Catalyst Paper ; we followed the modeling protocol delivered with the Task 5 report in setting up the CALPOST inputs for each CIA using the 4 visibility methods mentioned in the previous sections. Due to the large number of post

processing runs required for the 8 control options for each of the 12 CIAs , we used customized scripts to set up the inputs and extensively QA them

.



## 2.2.3.5.4 Extraction of Visibility Results with POSTCALPOST

UNC extracted the results from the CALPOST visibility analysis for the four methods of calculating visibility using POSTCALPOST. The results for the 98 th 

### percentile incremental visibility impairment 

- dv relative to background visibility at the 12 CIAs listed in Table 1
within 300

- km of the Catalyst Paper Pulp Mill for each year modeled (2001

- 2003), an d for the composite period are documented in the supporting spreadsheet documentation. The results in this report are from Method 6(a) and 8(b) for the composite period 2001

- 2003. Table 30
summarize s the incremental visibility impairment relative to backgr ound (22nd highest 

- dv, corresponding to the 98 th 

### percentile) at each CIA within 300 km of Catalyst Paper for the base
case and controls scenarios from Method s 6(a) and Method 8(b).EMAQ LOE (EPA Contract EP

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### Table 30

. 98th P ercentile V isibility I mpairment ( 

- dv) for Catalyst Paper U sing

(a) IMPROVE Method 6 (a) and (b) Method 8(b)

(a)

(b)



### In both methods the maximum visibility impairment occurs at Petrified Forest (pefo) NP. Greater visibility impairment is seen using Method 8(b) than with Method 6(a). On average, three out of 12 CIAs see a grea ter than 0.5

- dv impairment with either method. As discussed in
Section 2.2.3.4 the use of FF produces the least impairment, but SCR and SNCR also show strong reduction in the impairment at all CIAs relative to the base case.

Ctrl

- 2 with sodium scrubbers an d a scrubber upgrade is seen to have worse impairment than the base case. An examination of this case found that the stack parameters could be incorrectly specified for Ctrl

- 2 and Ctrl

- 3. At the time of this reporting, the issue had not been resolved
satis factorily, and these two cases should be ignored pending a correction to these results.EMAQ LOE (EPA Contract EP

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### Table 31

. Visibility B enefits (dv) of C ontrol Options f or the
Calculation M ethods of Table 30

(a)

(b)



### Table 31 summarizes the visibility benefits of these control o ptions in dv relative to the base
case for each of the visibility methods. Clearly SCR with FF, followed by SCR without FF and with the full complement of SO2 controls provide the greatest visibility benefits, and FF controls added to these other technolog ies show a greater than 0.5 dv benefit at 2 out of the 12 CIAs (pefo, sian). Method 8 shows greater benefits compared to Method 6, both summed over
all CIAs

, and as a maximum at pefo

. 

## 2.2.3.6 Control Effectiveness Results

This section summarizes the control effec tiveness in $/dv (millions) for the control options modeled. Table 32 shows these results for each CIA and control option for the two calculation methods, and as before, Method 8(b) shows greater effectiveness (lower values) compared to Method 6(a). The ef

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### scenarios, and due to the lower costs, the use of FF alone has the highest cost effec tiveness of all control configurations, both when the dv impact of control is summed over all CIAs and when the maximum impact is used.

Table 32

. Control E ffectiveness (million $/dv) f or the
Calculation Methods of Table 30

(a)

(b)



### These results are su mmarized in Table 33, and show the change in the effectiveness of certain technologies when considering all areas vs. the most impaired. It is clear that FF is the most

cost

- effective, even when used alone, due to the relative low cost compared to the visi bility
benefit ; its effectiveness is greatly enhanced with post

- combustion NO
x 

### controls (SCR) . It is
found to be the most effective technology whether the impact is the sum over all CIAs or at the most impaired CIA. Scrubbers are in general found to be lea st cost

- effective unless combined with other technologies. The relative merits of these control technologies do not change significantly as the distance to the CIA increases.EMAQ LOE (EPA Contract EP

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### Table 33

. Control E ffectiveness Summary (million $/dv) f or the
Calculation Metho ds of Table 30

( a )

( b )



## 2.3 Conclusi ons

The five

- factor BART analysis of the three facilities Chemical Lime Nelson, Sundt Unit 4 and Catalyst Paper Pulp Mill led to the following conclusions:

 The visibility i mpacts are greatest for each facility at the nea rest 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 due to controlsEMAQ LOE (EPA Contract EP

- D

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- 102) WA 5

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- Factor BART Analysis Report

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. v1 37 October 9 , 2012 

### at the three facilities are, respectively, Gran d Canyon, Saguaro and Petrified Forest

. Sierra Ancha shows the least impact/benefit from control options at Nelson Lime

, Mount Baldy

, the least impacts due to Sundt, and Saguaro

, the least impact from Catalyst Paper

.

 The following are the technologies found to be most cost

- effective at the highest impact CIA at each facility:

o 

### SNCR ( on both BART un it s) at Nelson Lime

o 

### SNCR

, and S N CR in combination with DSI at Sundt Unit 4, followed by SCR
with DSI

o 

### Fabric filter at Catalyst Paper; however, i ts cost

- effectiveness is somewhat
diminished w hen used in combination with SCR despite the visibility benefit

, due to the relatively high cost of SCR.

 In the case of Nelson Lime and Sundt 4 the control effectiveness of SO 2 

### controls such as wet and dry FGD is greater at the CIAs farther away from the so urce. NOx control technologies such as SCR and SNCR have a lot more effectiveness at nearby CIAs

.

 FF is the most effective control technology available for Catalyst Paper. SCR and SNCR
can be even more effective when combined with FF

.

 Visibility Method 8(b) estimates greater impairment and shows greater benefits of control options in almost all case relative to Method 6(b).EMAQ LOE (EPA Contract EP

- D

- 07

- 102) WA 5

- 12: Task 7 Five

- Factor BART Analysis Report

UNC

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. v1 38 October 9 , 2012 

# References

ENSR, 2009: Revised BART Analysis for the Navajo Generating Station Units 1

- 3 , ENSR Corporation, Document No. 05830

- 01 2

- 300, January 2009, Salt River Project

– Navajo Generating Station, Tempe, AZ.

EPA

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

02

- 001 , U.S. Environmental Protection Agency.

IL EPA , 2007: Technical Support Documenta tion for C ontrol of N itrogen Oxide Emissions from Lime Kilns”, June 2007 , AQPSTR 07

- 04, Illinois Environmental Protection Agency.

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

.
W estern R egional A ir Partnership (WRAP) Regional Modeling Center , 2006: CALMET/CALPUFF Protocol for BART Exemption Screening Analysis for Class I Areas in
the Western United S tates . 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_Prot ocol_Aug15_2006.pdf

# Appendix A
Emissions Data TablesUNC

- EMAQ 5

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

Table A

- 1(a). NO
x 

### , SO 2 

### and PM E mission I nputs for B ase and Control S cenarios for Nelson Lime V isibility M odelingEMAQ LOE (EPA Contract EP

- D

- 07

- 102) WA 5

- 12: Task 7 Five

- Factor BART An alysis Report

UNC

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- 3 October 9 , 2012 

### Table A

- 1(b). Speciated PM E mission I nputs for B ase and C ontrol S cena rios for Nelson Lime V isibility M odelingEMAQ LOE (EPA Contract EP

- D

- 07

- 102) WA 5

- 12: Task 7 Five

- Factor BART An alysis Report

UNC

- EMAQ 5

- 12

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- 4 October 9 , 2012 

### Table A

- 2 (a). NO
x 

### , SO 2 

### and PM E mission I nputs for B ase and Control S cenarios for Sundt Unit 4 V isibility M odelingEMAQ LOE (EPA Contract EP

- D

- 07

- 102) WA 5

- 12: Task 7 Five

- Factor BART An alysis Report

UNC

- EMAQ 5

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- 5 October 9 , 2012 

### Table A

- 2 (b). Speciated PM E mission I nputs for B ase and C ontrol S cenarios for Sundt Unit 4 V is ibility M odelingEMAQ LOE (EPA Contract EP

- D

- 07

- 102) WA 5

- 12: Task 7 Five

- Factor BART An alysis Report

UNC

- EMAQ 5

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- 6 October 9 , 2012 

### Table A

- 3 (a). NO
x 

### , SO 2 

### and PM E mission I nputs for B ase and Control S cenarios for Catalyst Paper V isibility M odeling

Table A

- 3 (b). Speciated PM E mission I nputs for B ase and C ontrol S cenarios for Catalyst Paper V isibility M odeling

# Appendix B

Andover Technology Partners Report Chapter 3 : BART Analysis (NO x 

## , SO 2 

## and PM)

### 3

- 1 www.AndoverTechnology.com Chapter 3. BART Analysis (NOx, SO2 and PM)

Task 7: Determine BART Control Options (SO2, NOx, PM)

Under this task, Andover Technology Partners will conduc t a full 5

- factor BART analysis of all technically feasible control options for

 Catalyst Paper, boiler #2

 Chemical Lime Company (Nelson Lime Plant), and

 Sundt (Unit 4).

Andover Technology Partners will review the submitted BART analysis from Catalyst Pape r and Chemical Lime Company to evaluate if costs shown are permissible under BART guidance.

Cost estimates performed in this section utilize methods consistent with the US EPA Control Cost Manual, 11 

### cost estimating methods used in EPA’s latest Integrated P lanning Model (IPM)

methods 12 

### , and other reasonable engineering methods.

.

11 EP A. 2002. EPA Air Pollution Control Cost Manual (Sixth Edition). EPA/452/B

- 02

- 001

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

ipm/BaseCasev410.html#documentation

### 3

- 2 www.AndoverTechnology.com

3.1 Catalyst Paper, Snowflake, AZ

Catalyst Paper operates a pulp mill in Snowflake, AZ that generates pulp from recycled newsprint and makes new newsprint, corrugated box, pu rchased pulp and other products. Three power boilers are operated on site. The power boilers are pictured in Figures 3

- 1 a and b
and additional data is shown in Table 3

- 1. Boiler #2 is coal fired with a rated heat input of 1132
million Btu/hr when firin g coal. It may also fire residual oil. In January 2008 AbitibiBowater Inc. (then owner of the mill) submitted a BART analysis of the mill. This analysis examined methods for reducing NOx and SO2 at the mill.

Figures 3

- 1 a and b. The power boilers and c oal pile at Catalyst Paper

.

http://www.renegy.com/project_snowflake.html

### 3

- 3 www.AndoverTechnology.com

The following sections will comment on the BART analysis submitted by Abitibi Bowater in January 2008 and will make re commended BACT emissions rates and estimates of costs.

Table 3

- 1. Data for Catalyst paper

Data Element Data Source Boiler Type (unit 2) Wall Fired BART Submittal Boiler Heat Input Boiler 1: 523 MMBtu/hr with Nat Gas, 472 MMBtu/hr with Oil

Boiler 2: 1132 MMBtu/hr with Coal, 1110 MMBtu/hr with Oil Boiler 3: 337 MMBtu/hr with Nat Gas, 315 MMBtu/hr with Oil Permit, page 45

Boiler Combustion Configuration Existing NOx Controls Unit 3 has a low NOx burner listed in their permit, the other two have no NOx c ontrols. Permit

Current NOx Emission Rate (lbs/MMBtu) Cap of 0.3 lb/MMBtu while burning oil in Unit 2. Cap of 0.7 lb/MMBtu while burning coal in

Unit 2. Permit

Coal Type(s) Western Bituminous (Lee Ranch El Segundo) BART Submittal Ash Content (%) 17.9 BA RT Submittal Sulfur Content (%) 1.03 BART Submittal Approx. Heating Value (btu/lb) 9290 BART Submittal

Additional Info on Emissions
Controls Slipstream Wet Alkaline Scrubber by Flakt (tray type) installed on Unit 2 1990 must run 100%
of the time. Treat s 43% of Unit 2 flue gas Permit and EIA

Form 860

SO2 Emission Rate Cap of 1.0 lb/MMBtu while burning oil for Units 1&3, Cap of 0.8 lb/MMBtu while burning oil or coal

for Unit 2 Permit

NOx Emission Rate (unit 2) 0.70 lb/MMBtu BART Submittal

PM Emission Rate Cap of 0.10 lb/MMBtu Permit
PM controls

- efficiency

- calculated emissions rate

- typical emissions rate Hot Side ESP

– no conditioning

99.2% 0.154 lb/MMBtu (from efficiency and fuel) 0.02 lb/MMBtu (from 2005 EIA form 767) EIA Form 860, 767

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3.1.1 NOx C ontrol

Available Technologies

–

Technologies evaluated in the BART analysis for controlling NOx and the projected emissions reduction found in the BART analysis are shown in Table 3

- 2. In general this is a comprehensive list of available NOx controls for this type of boiler. There are no major control categories missing from this list.

Feasible Technologies

-

All of the technologies shown are feasible. The emissions targets developed by CH2MHill incorporate additional margin over that offered by the t echnology supplier that varies by technology type.

Table 3

- 2. Catalyst Paper Evaluated NOx Technologies for BART.

Evaluation of Technologies

-

The capital and operating costs directly associated with the NOx control technology analysis

were reviewed as well, along with energy and environmental impacts. These costs all appeared to be reasonable, with the exception of SCR catalyst replacement cost, which seemed high. For a boiler the size of Boiler 2 at catalyst paper, roughly 150 cubic meters of catalys t is expected (typically 1

- 1.5 cubic meters per 1000 MMBtu/hr). If half of that catalyst is replaced every two years, the cost is about 75 m 3 

### x $5000/m3 or $375,000 every two years, or under $200,000 per year. Regenerated catalyst would drop the cost of that by another 40% or so, to about $120,000/year. As a result, $200,000 per year for catalyst is a conservative estimate.

The capital recovery factor assumed by AbitibiBowater of 13.5% is roughly equivalent to the combination of debt service (7% over 20 years, or 9.44% annually) and taxes, insurance and

### 3

- 5 www.AndoverTechnology.com

administrative costs, and the EPA Air Pollution Control Cost Manual suggests using 4% of capital cost. 13 

### This results in 13.44% total annual cost.

Abitibi Bowater further assumed an additional indirect cos t to NOx control. Abitibi Bowater assumed that with NOx control all fly ash would be disposed of rather than sold. This assumption regarding the impact of NOx controls on fly ash is likely overstated, and ADEQ had asked Abitibi Bowater to provide support ing information. Abitibi Bowater provided supporting information on their fly ash purchase agreement, but this did not address why they assumed that all fly would be unmarketable.

NOx controls do have a potential impact, but the negative impact is by no means certain. Modern burners have the benefit of much more advanced design methods than those used in original equipment and may even improve (reduce) carbon levels in fly ash while reducing NOx. In cases where carbon levels do increase they can be miti gated by adjusting excess air levels if it does become a problem. Increasing excess air levels, however, will have an impact on NOx reduction. SNCR and SCR technologies also have the potential to result in ammonia on fly ash, which may impact fly ash sa les; however, this is dependent upon the coal fly ash pH and other factors. Ammonia slip can generally be controlled to levels that do not impact fly ash. EPRI performed a study in 2007 that examined the effects of ammonia slip from SCR systems and

reach ed the conclusion that “The survey overwhelmingly indicated that ammonia contamination is not impacting the ability of plants to sell ash”. 14



### For the purpose of this BART analysis, the additional margin on NOx emission reduction assumed by Abitibi Bowater’ s consulting engineer is assumed to provide adequate margin to allow for the possibility of operating at a higher NOx level than guaranteed by the supplier and for the likelihood of not having an impact on fly ash sales.

The costs from Abitibi Bowater’s BA RT analysis were considered reasonable with the exception of the estimated impacts on fly ash. The costs from the BART analysis are shown in Table 3

- 3 with the exception that the cost assigned to fly ash impacts from the NOx control are not

included in th e total cost and the estimate of cost in $/ton of NOx removed. Another difference is the assumed capital recovery rate is 9.4% (consistent with 7% interest over 20 years) and there is an additional 4% for taxes, admin, and insurance (per the EPA air pollu tion control cost manual. The estimated $/ton of NOx removed is lower than what was estimated by Abitibi Bowater’s consultant, largely because of the difference in the way fly ash effects were

addressed.

For the purpose of modeling, Cases 3 and 4 of Table 3

- 3 can be ignored since they would not
be selected on the basis of cost.

Energy and Environmental Impacts

–

Energy impacts are evaluated and the cost shown as increased electrical load.

13 EPA Air Pollution Control Cost Manual, Sixth Ed. , 2002, Sect. 2.5.5.8, p p. 2

- 34
14 http://my.epri.com/portal/server.pt?Abstract_id=000000000001014269

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Environmental impacts of the combustion controls are potential impac t to fly ash; however, the original assumption made by Abitibi Bowater’s consultant that all of the fly ash would be impacted is a worst case. In fact, many electric utility boilers firing many types of coals have combustion NOx controls and sell fly ash. Therefore, this assumption is overstated and is ignored in this case.

Table 3

- 3. Catalyst Paper

– NOx Control Costs, excluding impact on fly ash

Case # 1 2 3 4 5 6 7

NOx Control OFA with Existing

Fan LNB MOBOTEC

ROFA MOBOTEC

ROFA and

Rotamix

SNCR LNB w/OFA LNB wOFA

and HERT

SNCR LNB with OFA

and SCR

Heat Input Rate, MMBtu/hr 1132 1132 1132 1132 1132 1132 1132 Capacity Factor 100% 100% 100% 100% 100% 100% 100% Heat Value, Bu/lb 9,290 9,290 9,290 9,290 9,290 9,290 9,290
Historical Emissions Rate
Mod eled Rate, pph* 914 914 914 914 914 914 914 NOx (lb/MMBtu) 0.7 0.7 0.7 0.7 0.7 0.7 0.7 NOx, pph 792 792 792 792 792 792 792 NOx, TPY 3,471 3,471 3,471 3,471 3,471 3,471 3,471

Controlled Emissions Rate

NOx (lb/MMBtu) 0.525 0.37 0.348 0.291 0.2 65 0.194 0.07 NOx, pph 594 419 394 329 300 220 79 NOx, TPY 2,603 1,835 1,725 1,443 1,314 962 347 NOx, Removed,

TPY 868 1,636 1,745 2,028 2,157 2,509 3,124
Percent Removed 25% 47% 50% 58% 62% 72% 90%
Total Installed

Cost $20,000 $1,462,020 $4,536,126 $5,964,840 $2,088,600 $2,792,400 $22,950,507

Fixed O&M $25,740 $84,221 $207,185 $228,616 $109,284 $119,841 $137,689

Non Fuel Var O&M $1,802 $1,802 $468,389 Make Up Water $4,322 $499 $246,973 Urea/Ammonia $416,723 $347,24 0 $87,485 SCR Catalyst $200,000

Elect. Load $74,685 $323,637 $327,109 $3,472 $189,122

Annualized Capital $1,888 $138,004 $428,178 $563,039 $197,149 $263,583 $2,166,366

Taxes, Admin,

Insurance $800 $58,481 $181,445 $238,594 $ 83,544 $111,696 $918,020

Net Cost $103,113 $280,706 $1,140,445 $1,780,204 $389,977 $848,133 $4,414,044

$/ton NOx $119 $172 $653 $878 $181 $338 $1,413

Incremental $/ton NOx $119 $231 $7,882 $2,264 ($10,784) $1,301 $5,800

* Modele d rate is the rate used by UNC in their historical modeling. Other historical rates are from AbitibiBowater BART study and

may be more representative of average rate for the purpose of estimating cost effectiveness in $/ton removed.

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3.1.2 SO 2 

### Control

A vailable Technologies

The Abitibi Bowater BART analysis also included evaluation of SO 2 

### control technologies.

In this case only two options were considered in their analysis, upgrade of the existing caustic

wet scrubber (which only treats up to 43% of th e flue gas as needed to remain below the

permitted limit of 0.8 lb/MMBtu), and addition of a second sodium wet FGD system that would

allow treatment of 100% of the flue gas, as shown in Table 3

- 4. This is not a comprehensive list

of possible control optio ns. Other control options include dry FGD, which would offer the

advantages of reduced water consumption, lower operating costs due to less expensive lime

reagent and much less costly disposal of waste, much lower PM emissions, and elimination of

liquid w aste; however, it would not provide the same level of SO 2 

### removal and would have a

higher capital cost than the wet scrubber option that Abitibi Bowater evaluated. Use of the dry

scrubber would also continue to allow segregation of fly ash with the hot si de ESPs for sale into

the concrete market. Another available technology is lower sulfur coal.

Feasible Technologies

–

All of the available technologies are also feasible.

Evaluation of Technologies

-

A rough, order of magnitude estimate of the cost of a dry FGD system was developed by

scaling the published cost information on the Turbosorp dry scrubber installed at the Greenidge

power plant, and this is provided in an Excel workbook.

Table 3

- 5 compares control costs for available and feasible control tec hnologies. Total

costs are shown as well as costs relative to historical costs. The costs relative to historical

costs and emissions reductions versus historical emissions are used in the $/ton of SO 2



### removed calculation.

Energy Impacts

Each of the metho ds has significant energy load, and the cost of this is estimated.

Environmental Impacts

Both wet scrubber options produce subtantial amounts of liquid waste that must be

disposed of. The dry scrubber produces a stable, dry product that is readily dispose d of. The

dry scrubber will also significantly reduce PM emissions.

### 3

- 8 www.AndoverTechnology.com Table 3

- 4. Catalyst Paper SO2 Technologies evaluated by Abitibi Bowater for BART

Table 3

- 5. SO2 Control Costs and Performance at Catalyst Paper

Catalyst Paper Case Case Case Case Cas e

Historical 1 Historical 2 1 2 3

SO2 Control Scrubber Upgrade Replace with new Dry Lime
Scrubber Add'l Sodium

Scrubber and Upgraded
Scrubber
Heat Input Rate, MMBtu/hr 1132 1132 1132 1132 1132 Capacity Factor 100% 100% 100% 100% 100% Heat Value, Bu /lb 9,290 9,290 9,290 9,290 Coal Sulfur, % 1.03% 1.03% 1.03% 1.03% Uncontrolled SO2, lb/MMBtu 2.22 2.22 2.22 2.22
Uncontrolled Annual SO2 Emissions, tons 10,994 10,994 10,994 10,994
Historical Emissions Rate Modeled Rate, pph * 555 555 555 555 555 SO2 (lb/MMBtu) 0.799 0.799 0.799 0.799 0.799 SO2, pph 904 904 904 904 904 SO2, TPY 3,962 3,962 3,962 3,962 3,962
Controlled Emissions Rate SO2 (lb/MMBtu) 0.80 0.80 0.74 0.111 0.04 SO2, pph 904 904 837 126 50 SO2, TPY 3,962 3,962 3664 550 220

SO2 R emoved, TPY 0 0 298 3,412 3,742 Percent Removed from
historical 0 0 7.5% 86.1% 94.5%

% change in stack velocity none none None

- 10%

- 20% Exit temp No change No change No change 175 F 130 F

Impact on PM speciation? none none none Yes

– add FF Yes

- all g as scrubbed Total Installed Cost $650,000 $32,949,187 $15,650,000

Fixed O&M $60,665 $60,665 $60,665 $1,123,555 $90,998

Non Fuel Var O&M $42,102 $42,102 $42,102 $236,704 $84,204 Make Up Water $47,801 $115,960 $102,767 $15,780 $170, 530 Reagent $691,653 $2,308,793 $2,308,793 $2,278,391 $3,395,285 Scrubber Waste Disposal $937,462 $3,129,323 $3,129,323 $669,604 $4,601,946 Fly Ash Disp/Lost Ash ($889,759) ($1,400,085) ($1,400,085) ($1,400,085) ($1,400,085)

Elect. Load $67 3,696 $673,696 $673,696 $852,134 $640,312 Annualized Capital $0 $0 $61,355 $3,110,170 $1,477,249 Taxes, Admin, Insurance $0 $0 $26,000 $1,317,967 $626,000 Annual Cost, incl ash $1,563,620 $4,930,454 $5,004,616 $8,204,221 $9,686,439 Cost of Control (note

– fuel costs are not shown, all control estimates assume the same fuel as Historical 2)
Net Cost, $/yr, greater than Historical 2 $74,162 $3,273,767 $4,755,985

$/ton of SO2 removed compared to historical $249 $960 $1,271 Incr. $/ton of SO2 removed $249 $1,027 $4,495

* Modeled rate is the rate used by UNC in their historical modeling. Other historical rates are from AbitibiBowater BART st udy and may be more representative of average rate for the purpose of estimating cost effectiveness in $/ton removed

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3.1.3 PM Emissions

The permitted PM emissions rate is 0.1 lb/MMBtu; however, the recently proposed industrial
boiler MACT has a PM emission limit of 0.044 lb/MMBtu. It is unclear if this will motivate the

installatio n of a fabric filter system. Since boiler 2 has a hot

- side ESP, upgrade of the ESP is not likely an option. Therefore a fabric filter is a viable option that would ideally be installed downstream of a dry FGD system or upstream of a wet FGD system (in th e capital cost, long ductwork has been priced in). The fabric filter with the dry FGD program at the Greenidge plant tested to produce an emissions rate of 0.001 lb/MMBtu. Typical guarantee values might be in the range of 0.015 lb/MMBtu or less. An est imate of a dry FGD system was developed for the purpose of estimating the cost of a system placed after the scrubbed and unscrubbed gas streams are joined and prior to the chimney. The estimated cost is shown in Table 3

- 6, or roughly $21 million to instal l a fabric filter, or roughly two

- thirds the cost of a dry scrubber with a fabric filter. It should also be considered that when a dry scrubber is installed, including a fabric filter, for SO 2 

### control, the PM control is a cobenefit of installing the dry scrubber. For this reason a dry scrubber, as described in Table 3

- 5, would be very beneficial for both SO 2 

### and PM control.

Table 3

- 6. Estimated cost of new fabric filter on boiler 2

ACFM 408,300 Total Capital Requirement $21,413,481 Annualized Capital $2,021,281 Taxes, Admin, Insurance $856,539.25

maintenance $509,604 Variable Operating Cost $427,038

Total Cost $3,814,463 Rated MMBtu/hr 1132 Modeled Rate, pph * 113 Current PM Rate, lb/MMBtu 0.1 pph 113.2

TPY 496 Rate with new FF, lb/MMBtu 0.015 pph 16.98

TPY 74
Percent Reduced 85% Tons reduced per year 421
Total Annualized Cost $3,814,463 $ per ton reduced $9,051 * Modeled rate is the rate used by UNC in their historical modeling. Other historical rates are

based on permit limit.

Energy and Environmental Impacts

The fabric filter will require an additional booster fan and power, as well as compressed air, and the costs of these are porvided for. The fabric filter will also improve capture of mercury and other toxic materials.

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3.2 Nelson Lime Plant

Nelson lime plant, pictured in Figure 3

- 2, has two preheater rotary kilns, rated at 859 and 1,145 tons per day, respectively. The facilities have no additional controls beyond PM controls (both have baghouses, with kiln 1 a more recently installed baghouse). 15 

### Emission rates from the Chemical Lime BART study are shown in Table 3

- 7. Each kiln emits through a separate chimney.

Figure 3

- 2. Nelson Lime Plant

Table 3

- 7. Emissions and Emission Controls at Nelson L ime Plant

Nelson Kiln 1 Nelson Kiln 2 Info. Source
Maximum daily production, tons/day 859 1,145 Nelson

BART
Submittal Emission Factors, lb/ton of product (lb/hr)

NOx 2.66 (95) 2.08 (99)

SO2 3.29 (118) 7.87 (375)

PM10 0.0423 (1.51) 0.0702 (3.35)

Controls Baghouse Baghouse, Multicyclone Permit

15 BART Applicability Modeling Analysis, Chemical Lime Company, Nelson, AZ , September 2007

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3.2.1 NOx Emissions and Controls

Fuel fired at the plant is coal. The coal contributes to NOx emissions formed from combustion. It is unclear if any NOx controls are installed, and for the purpose of this study it will be assumed

that none are installed.

Available Technologies

–

Table 3

- 8 shows technologies available for control of NOx from kilns and the expected percent reduction. As shown, NOx reductions are possible through combustion controls or possibly through post

- combustion controls. This table is developed from data applicable to Portland
Cement kilns.

Besides low NOx burners, mid kiln firing, mixing air technology SNCR and SCR are possible technologies. These technologies can be combine d for higher NOx reduction than possible using one technology alone. Because the two Nelson plant kilns are preheater kilns, the most likely location for SNCR reagent injection is the preheater, where there is likely to be an available temperature window. To be conservative, when combined with other technologies, it is assumed that SNCR provides 30% reduction rather than 50% reduction.

Feasible Technologies

–

All of the technologies listed in Table 3

- 8 are potentially feasible; however, since SCR has no known experience on lime kilns and very limited experience with cement kilns, it will be regarded as not feasible and will not be evaluated further. Also, since Mid Kiln Firing with tires may not be an option for lime kilns and the capital cost is much hi gher than some of the other combustion controls, it is not likely to be as economical as some of the other controls and will not be evaluated further. MAT will produce NOx reductions, but also reduces SO 2 

### emissions by promoting formation of gypsum in the product, which may be undesireable. So, MAT may be attractive from the perspective of emissions reduction but unattractive for other reasons.

TABLE 3

- 8: NOx Emissions Reduction from Rotary Kilns with

Various NOx Control Technologies 16
NOx Control Technolog y Expected NOx Emissions Reduction (%)

Low

- NOx Burner (LNB) 30
Mid

- Kiln Firing 30 Mixing Air Technology (MAT) 17 30 SNCR

- Urea 50 SNCR

- Ammonia 50
SCR 80

16 

### “ TECHNICAL SUPPORT DOCUMENT For CONTROL OF NITROGEN OXIDE EMIS SIONS From Lime Kilns” AQPSTR 07

- 04, June 2007, ILLINOIS ENVIRONMENTAL PROTECTION AGENCY

17 http://www.cadencerecycling.com/papersbrochures.html

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Evaluation of Technologies

- There is limited data on cost for NOx controls for lime kil ns, and much is derived from data for cement kilns. In this case cost information developed for EPA’s Industrial Sector Integrated Solutions (ISIS) model will be used where applicable. 18



### Tables 3

- 9a and b show the results of comparison of NOx emissions f or the two Nelson kilns using feasible technologies. To be conservative from the perspective of cost, it was assumed that LNB would be deployed in lieu of MAT to achieve 30% NOx reduction. Use of MAT rather than LNB would be less expensive, but increased gypsum in the product from SO 2 

### capture might be undesireable. In the case of SNCR, it is assumed that it achieves 50% reduction from uncontrolled levels and when combined with LNB will provide an additional 30% reduction after LNB has reduced NOx by 30% for a total of 51% reduction. In either case, 50% reduction

should be achievable and the costs shown in Tables 3

- 9a and b should be conservatively high.

Table 3

- 9a. NOx Control Technologies for the Nelson Lime Kiln 1

Nelson Kiln 1

LNB SNCR LNB and S NCR

TPD Lime 859 859 859

Uncontrolled emissions

Uncontrolled NOx, lb/ton 2.66 2.66 2.66

PPH NOx 95 95 95

TPY NOx (90% capacity factor) 375 375 375

Controlled Emissions

Reduction 30% 50% 51%

Controlled NOx, lb/ton 1.86 1.33 1.30

PPH NOx 67 48 47

T PY NOx (90% capacity factor) 263 188 184

Control Costs

Capital Cost $2,389,443 $679,055 $3,068,499

Total Annualized Cost $396,129 $216,179 $597,335

$/ton removed $3,518 $1,152 $3,121

incremental, $/ton removed $3,518

- $2,397* $2,553*

*incremental cos t compared to cost of LNB with 30% reduction since both of

these provide roughly the same total NOx reduction

18 Memo from J. Staudt to R. Strivastava, et. al., regarding “Costs and Performance of Controls

– revised from

c omments”, March 10, 2009 (part of ISIS development data)

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Energy and Environmental Impacts

These technologies will have a very modest energy impact, requiring some additional auxiliary

electrical load

.
SNCR has the potential for ammonia slip emissions. However, experience with cement kilns has demonstrated that these are generally well controlled.

Table 3

- 9b. NOx Control Technologies for the Nelson Lime Kiln 2

Nelson Kiln 2

LNB SNCR LNB and SNC R

TPD Lime 1,145 1,145 1,145

Uncontrolled emissions

Uncontrolled NOx, lb/ton 2.08 2.08 2.08

PPH NOx 99 99 99

TPY NOx (90% capacity factor) 391 391 391

Controlled Emissions

Reduction 30% 50% 51%

Controlled NOx, lb/ton 1.46 1.04 1.02

PPH NOx 69 50 4 9

TPY NOx (90% capacity factor) 274 196 192

Control Costs

Capital Cost $2,857,256 $806,849 $3,664,105

Total Annualized Cost $459,000 $235,465 $678,858

$/ton removed $3,911 $1,204 $3,403

incremental, $/ton removed $3,911

- $2,857* $2,676*

*incremental cost compared to cost of LNB with 30% reduction since both of

these provide roughly the same total NOx reduction

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3.2.2 SO 2 

### Emissions

SO 2 

### emissions from cement kilns are primarily from raw materials (limestone) rather than coal
because most SO 2 

### from f uel combustion is captured in the kiln and ends up in the product. However, for lime kilns, that try to avoid having sulfur in the product, fuel sulfur is more likely to
be emitted in the form of SO 2 

### than for a cement kiln. Changing raw material sources is generally not possible. Therefore, “add on” controls are likely to be necessary to reduce SO 2 

### emissions.

Available Technologies

Table 3

- 10 shows available technologies. As discussed earlier, mixing air technology may actually reduce SO 2 

### somewhat. Bec ause this increases the gypsum loading in the product somewhat, it is unclear if this would be deployed for a lime kiln.

Table 3

- 10 Available SO 2 

### Controls

Technology Percent Removal Mixing Air (MAT) Varies: assume about 30%
Dry Lime Injection About 50% Dry Sorbent Injection (DSI) using SBC 75%

Dry FGD 90

- 95%

Wet FGD 95%

Feasible Technologies.

All of the technologies are potentially feasible. Because a fabric filter is already installed on each kiln, a dry sorbent injection system would likely be very effective. Lime and sodium bicarbonate (SBC) are potential DSI reagents, as is trona; however, SBC is preferable for SO 2 

### capture. In practice, L’Hoist, the owner of the Nelson Plant, may choose to use a highly activated lime hydrate that they manufa cture in place of SBC that is capable of similar removal rates as SBC. Nevertheless, DSI using SBC provides a reasonable estimate of cost for DSI using activated lime hydrate. Dry FGD is iikely to require a second baghouse because there does not appear t o be room to install an absorber between the preheater and the fabric filter, particularly for kiln 2, and in any event, there may not be adequate space under the existing baghouses for air slides or recycle systems that would be used on a dry scrubber. R egardless, a dry FGD would provide similar SO 2 

### removal as a wet FGD. So, a wet limestone FGD will be evaluated as a conservative approach. Wet lime or limestone FGD is feasible, and would be installed downstream of the existing baghouse.

Evaluate Technol ogies

Table 3

- 11 shows the estimated costs and emission rates for the three technologies evaluated for the two kilns. The DSI with SBC appears to have lower cost and higher reduction than dry lime injection. This is largely the result of the higher waste disposal costs associated with the

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higher material input for the DLI. This analysis does not factor in any difference in disposal cost per ton of waste for dry lime versus SBC. Not addressed in this analysis are modifications to baghouse operation that may be necessary as a result of installing a DSI system. The wet scrubber has the highest removal, but also the highest cost. The SO 2 

### reductions possible with MAT will vary.

The wet FGD capital cost shown here may be too high. Unfortunately, there is ve ry limted data available. Costs were developed from informaiton on wet FGD costs for cement kilns, which in itself is rather limited. Very few cement kilns are equipped with wet scrubbers. So, most cost information has been gleened from BACT analyses as described in supporting documentation
for ISIS. 19



### Table 3

- 11 Evaluation of SO 2 

### Controls

Nelson 1 Nelson 2

MAT Dry Lime DSI with

SBC Wet FGD MAT Dry Lime DSI with

SBC Wet FGD

Historical SO2, lb/ton 3.29 3.29 3.29 3.29 7.87 7.87 7.87 7.87

Historical S O2, pph 118 118 118 118 375 375 375 375

Percent Removal 30% 50% 75% 95% 30% 50% 75% 95%

Outlet SO2, pph 82.4 58.9 29.4 5.9 262.5 187.5 93.8 18.8

Outlet SO2, lb/ton 2.30 1.65 0.82 0.16 5.51 3.94 1.97 0.39
% change in stack Velocity No Change No

Change N o

Change - 20% No Change No Change No Change

- 20%

Exit temp No Change No

Change No

Change 130 F No Change No Change No Change 130 F

Impact on PM speciation No Change No

Change No

Change Yes

FF plus
scrubber No

Change No Change No Change Yes, FF plus
scrub ber
Capital Cost $754,196 $770,000 $409,382 8,082,077 $807,040 $1,940,000 $1,034,122 10,772,967

Annualized Costs $176,364 $545,415 $389,957 $1,369,380 $183,466 $1,502,933 $1,040,460 $1,958,408

TPY removed (90% capacity factor) 139 232 348 441 443 739 1109 1404

$/ton removed $1,266 $2,350 $1,120 $3,105 $414 $2,033 $938 $1,395

Incremental $/ton $1,266 $3,975 ($1,340) $10,550 $414 $4,463 ($1,251) $3,105



### 3.2.3 PM Emissions

The Nelson Plant already has fabric filters installed on both kilns. As a result there is no additional technology available that provides a higher degree of PM reduction than what is already installed

.

19 Memo from J. Staudt to R. Srivastava , E. Torrez, K. Barnett, Re: Wet Scrubber Cost Algorithms, Feb 26, 2010

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3.3 

### H. Wilson Sundt Power Plant

H. Wilson Sundt (Sundt) unit 4 requires a BART analysis, and it is the unit that is located at the bottom of Figure 3

- 3. Table 3

- 12 shows the modeled and reported data for Sundt unit 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.

Sundt 4 is coal fired. Sundt Unit 4 is also equipped with a fabric filter, low NOx burners and

overfire air.

Figure 3

- 3. Sundt Power Plant.

Table 3

- 12. Sundt Power Plant Data

Unit Capacity

Fuel 2008

- 2010 Reported Avg 2011 Reported

Rates 2008

-

2011

NO x SO 2 NO x SO 2 Capacity

Factor

MW gross lb/MMBtu lb/MMBtu %

Unit 4 173. 3 Coal 0.361 0.477 0.445 0.729 37%

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3.3.1 NOx Control

Available Controls

Available controls include combustion controls and post

- combustion controls.

Feasible Controls

Because Sundt 4 already has combustion controls, the focus will be post

- combustion co ntrols.

Evaluation of NOx Controls

Sundt 4 is reported to already have low NOx burners and Overfire Air, and emissions rates are consistent with that level of control for a wall fired boiler. Therefore, only post

- combustion controls are examined, although some advanced forms of OFA may permit further reductions.

Results are shown in Table 3

- 13.

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

 Capa city factor will be the average of that estimated for the period 2008

- 2011 using reported heat input and plant capacity information.

 NOx and SO 2 

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

- 2010 and 2011. In the case of Sundt Unit 4, the 20 11 rate was selected as the baseline rate for estimating cost effectiveness.

Also, a capital recovery factor of 9.44% (equal to 7% over 20 years) plus tax and insurance costs of 1.2% were assumed in the cost analysis. This charge rate for taxes and insura nce differs from what is used for industrial sources per the EPA Air Pollution Control Cost Manual and is consistent with what has been determined for electric generating units per the Integrated Planning Model documentation. 20



### Energy Effects

SNCR has negl igible energy impact. SCR will incur an additional parasitic loss, mainly due to pressure drop across the SCR system, that is roughly equal to 0.59% of output. Although this is not treated as a cost in the IPM calculations that these algorithms were deve loped for, rather as a reduction in capacity, it has been treated as an increase in variable operating cost for these

calculations.

20 From Integrated Planning Model ver 4.10 documentation

, page 8

- 11 . 0.30% for insuranc e and 0.90% for taxes.

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Environmental Impacts

Environmental impacts of SNCR and SCR are primarily due to ammonia slip. The main

environmental conc ern is regarding fly ash odor and potential impact on fly ash sales/disposal. Generally, ammonia slip can be well controlled from both of these technologies so that fly ash is not adversely impacted.

SCR catalyst can be recycled and therefore is not a sig nificant concern.

Table 3

- 13. NOx Control for Sundt 4

Sundt 4

- NOx

SNCR SCR

Capacity Factor 37% 37%

Control Efficiency 30% 89%

Uncontrolled Rate

NOx Rate (lb/hr) 813 813

NOx Rate (lb/MMBtu) 0.445 0.445

NOx (TPY) 1318 1318

Control led Rate

NOx Rate (lb/hr) 569 91

NOx Rate (lb/MMBtu) 0.31 0.05

NOx (TPY) 923 148

Tons/Year Removed 395 1,170

Total Cost, $/year $1,308,000 $5,712,715

$/Ton $3,307 $4,882
$/Ton (incremental) $3,307 $5,686
* 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

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3.3.2 SO 2 

### Control

SO 2 

### emission rates increased in 2011 from the 2008

- 2010 average, indicating a change in coal.

Available T

echnologies

Available Technologies for Sundt 4 include dry sorbent injection, wet FGD and dry FGD. Sundt could also change to lower sulfur coal.

Feasible Technologies

All of the above available technologies are also feasible. In fact, since Sundt 4 ha s a fabric filter, dry sorbent injection may be well suited to this unit. A dry FGD is assumed at Sundt 4 to include a new fabric filter since there likely is not enough space to install a new absorber between the boiler and the existing fabric filter. A wet FGD would be installed downstream of the existing fabric filter.

Evaluation of Technologies

A change in coal was not evaluated for cost since coal cost data was not available.

Table 3

- 14 shows the estimated cost of each of the SO 2 

### control technolog ies. In light of the low capacity factor at Sundt 4 and the high capital costs of FGD, the two FGD approaches are significantly more expensive (on a $/ton of SO 2 

### removed basis), than DSI. DSI is expected to deliver high removal efficiencies due to the fa bric filter.

The FGD removal efficiencies are limited by assumptions in the Sargent & Lundy model developed for EPA’s Clean Air Markets Division that was used for the FGD cost analysis. In practice, we would expect both dry and wet FGD to achieve somewha t lower emissions levels (and higher capture efficiencies). In this respect these results are conservative.

Energy Impacts

The energy impacts of dry sorbent injection are small. FGD will have significant energy impacts (over 1% of output) due to pressure loss across the FGD system and due to additional pumping power and other auxiliary loads. In all cases energy costs are in cluded in the results of Table 3

- 14.

Environmental Impacts

DSI using trona or sodium bicarbonate will result in increased solids collected by the fabric filter. These sodium based materials may result in a by

- product with a water soluble component that may require some stabilization. Activated lime hydrate, if used, might avoid that issue. DSI has other benefits to air emissions as described in Section 2.1.2.

Both the wet and dry scrubbers will have a by

- product. The dry scrubber by product is stable and can be landfilled. The wet scrubber waste can be dewatered and sold to the gypsum market. More information is available in Section 2.1.2.

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- 14 . SO 2 

### Control for Sundt 4

Sundt 4

– SO2

DSI Dry FGD Wet FGD
Capacity Factor 37% 37% 37%

Con trol Efficiency 75% 89% 92%



### Uncontrolled Rate SO2 Rate (lb/hr) 1333 1333 1333 

### SO2 Rate (lb/MMBtu) 0.729 0.729 0.729 

### SO2 (TPY) 2160 2160 2160



### Controlled Rate SO2 Rate (lb/hr) 333 146 110 

### SO2 Rate (lb/MMBtu) 0.18 0.08 0.06 

### SO2 (TPY) 5 40 237 178

Tons/Year Removed 1620 1923 1982

% change stack velocity No Change

- 10%

- 20%

Exit temp No Change 175 F 130 F

Impact on PM speciation No Change Yes, FGD plus FF Yes, FGD plus FF

Total Cost, $/year $2,967,501 $12,553,539 $13,98 6,681

$/Ton $1,832 $6,529 $7,057

$/Ton (incremental) $1,832 $31,647 $24,189



### 3.3.3 PM Control

Sundt 4 is equipped with a fabric filter, and there is no technology available that would provide a higher degree of PM reduction than a properly designe d and operated fabric filter. Therefore, there are no changes to PM emission rates under the BART analysis.