## Technical Analysis for Arizona and Hawaii Regional

**Haze FIPs :**  **Task 7**  **: Five**  **- Factor BART Analysis for**  **TEP Sundt (Irvington** 

**) Contract No:**  EP - D - 07 - 102 **Work A ssignment:**  5 - 12 **Version: 1**  **Prepared for:** Thomas Webb

Air Planning Office U.S. EPA Region 9 75 Hawthorne Street San Francisco, CA 94105 **Prepared by :**  Uma Shankar , Elizabeth Adams, Mohammad Omary ,

Brian Naess and Sarav anan Arunachalam Institute for the Environment University of North Carolina at Chapel Hill Mark Lee , Juanita Haydel and Thomas Meyers ICF International Jim Staudt Andover Technology Partners **Date delivered**  **:** October 9 , 20 1 2EMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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## Contents **Figures ................................**  **................................ ................................**  **................................ ...........**  **iii Tables**  **................................ ................................**  **................................ ................................**  **............ iv**  **Document Change Record ................................**  **................................ ................................**  **........... v**  **1 Introduction**  **................................ ................................**  **................................ ............................**  **1 2**  **Work Performed and Deliverable Summary ................................**  **................................ ......**  **2** 2.1 General Considerations for Visibility Modeling ................................ ............................. 2 2.2 Five - Factor Anal ys es ................................ ................................ ................................ ...... 3 2.2.1 Sundt Unit 4 ................................ ................................ ................................ ......... 4 2.3 Conclusions ................................ ................................ ................................ ................... 14 **References ................................**  **................................ ................................**  **................................ ....**  **15 Appendix A**  **................................ ................................**  **................................ ................................**  **.... 1**  Emissio ns Data Tables ................................ ................................ ................................ ............. 1 **Appendix B ................................**  **................................ ................................**  **................................ ....**  **1** Andover Technology

Partners Report Chapter 3: BART Anal ys is (NO x , SO 2 and PM) ....... 1EMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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## Figures Figure 2. Sundt Plant ................................ ................................ ................................ ....................... 4EMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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## Ta **bles** Table 1. CIAs Within 300 km of Sundt ................................ ................................ .......................... 2 Table 13. Sundt Power Plant Data ................................ ................................ ................................ .. 4 Table 14. NO x Contol Technologies for Sundt Unit 4 ................................ ................................ .... 6 Table 15. SO 2 Contol Technologies for Sundt Unit 4 ................................ ................................ .... 7 Table 16. Control Scenarios Used in Sundt Visibility Modeling ................................ ................... 8 Table 17. Stack Parameters for Sundt Units 1 - 4 ................................ ................................ ............. 8 Table 18. 98th percentile Visibility Impairment (  - dv) for Sundt Scenarios Using (a) IMPROVE Method 6(a) and (b) Method 8(b) ................................ ................................ ................................ . 10 Table 19. Visibility

Benefits (dv) of Control Options for the Calculation Methods of Table 18 . 11 Table 20. Control Effectiveness (million $/dv) for the Calculation Methods of Table 18 ........... 12 Table 21. Control Effectiveness (million $/dv) Summary for the Calculation Methods of Table 18 ................................ ................................ ................................ ................................ ................... 13 Table A - 2(a). NO x , SO 2 and PM Emission Inputs for Base and Control Scenarios for Sundt Unit 4 Visibility

Modeling ................................ ................................ ................................ ...................... 2 Table A - 2(b). Speciated PM Emission Inputs for Base and Control Scenarios for Sundt Unit 4 Visibility Modeling ................................ ................................ ................................ ......................... 3EMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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## Document Change Record **Revision Date**  **Remarks** 0.1 October 9 , 2012 Draft version submitted to EPAEMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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## 1 **Introduction** This report describes the 5 - factor BART anal ys es of all technicall y feasible NO x control options for Sundt ( TEP Irvington) Generating Station Unit 4 The five factors considered in these anal ys es are as follows: 1. Cost of compliance; 2. E nergy

and non - air quality

impacts of compliance; 3. Any existing pollution control technology in use at each source ; 4. R emaining useful life of the source , and 5. D egree of visibility

improvement that may be reasonably expected from the use of BART emissions controls. Andover Technology

Partners (ATP) estimate d the cost of compliance for these units using data provided b y 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] ) methods 1 , and other reasonable engineering methods to ensure consistency with the assumptions used in its control cost anal ys es. The control options were anal yz ed not only for th e feasibility of implementation but also the first four factors listed above to estimate the total cost per ye ar of each control technology

and the cost of control per ye ar 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 IAreas (CIAs) within a 300 - km radius through the use of dispersion modeling. Per EPA requirements the se anal ys e s used the fo llowing models and processors , and EPA - provided meteorological inputs available from a previous BART analy sis 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 .  Th e 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 t o the visibility- impairing pollutant emission s reduction for each control option relative to the base configuration was used along with the ye arl y cost of control to estimate the control 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.

1 Documentation of EPA IPM Base Case v4.10. http://www.epa.gov/airmarkets/progsregs/epa ipm/BaseCasev410.html#documentationEMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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## 2 **Work Performed**  **and Deliv erable Summar** **y** In the five - factor anal ys is 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 these cost estimates along with its visibility impact assessment s for each facility to estimate the control optio n effectiveness in a combined metric specified b y EPA, namely, $/dv . The overarching considerations for the visibility impact assessments are provided in Section 2.1 . T he five - factor anal ys es for each plant are described in Section 2.2. 

### 2.1 **General Considerati ons for Visibility Modeling**  In Task 4 of this WA UNC used a GIS software tool to determine the nearest distance D ( km ) to the boundaries 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 L ambert Conformal Conic (L CC) projection parameters to obtain the coordinates of the facilities and CIAs came from meteorolog ical inputs for CALMET v5.8 provided b y EPA from BART anal ys is 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 mod eling in this task . **Table 1.**  CIAs W ithin 300 km of Sundt

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

CIA **Short**

**Nam e**  **State** Bryce Canyon brca UT Chiricahua NM chir AZ Chiricahua Wilderness chrw AZ Galiuro Wilderness gali AZ Gila Wilderness gila NM Grand Canyon NP grca AZ Joshua Tree NP jotr CA Mazatzal Wilderness maza AZ Mount Baldy Wilderness mo ba AZ Petrified Forest NP pefo AZ Pine Mountain Wilderness pimo AZ Saguaro NP sagu AZ Sierra Ancha Wilderness sian AZ Superstition Wilderness supe AZ Sy camore Canyon Wilderness sy ca AZ Zion zion UTEMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

UNC -EMAQ 5 - 12 - 026. v1 3 October 9, 2012 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 an y discrepancies in the CALPUFF inputs through a series of test runs. Of note, CA LP UFF modeling used a constant value of 1 ppb throughout for ammonia per EPA guidance . The CALPUFF model was run in each y ear 2001 - 2003, and the outputs were processed in the POSTUTIL processor to redistribute the HNO3 and PM nitrate using additional inputs. This step was necessitated b y 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 - ye ar concentratio n file for visibility post - processing. CALPOST was used to determine the 98 th percentile visibility impairment and the visibility

benefits of control in the y ears 2001 - 2003, and in the composite period. Further facility - specific details on the visibility analy s e s are provided in Section 2.2 . 

### 2.2 **Five -**  **Factor Analyses** This section describes the control options anal ys is, followed b y the details of the visibility modeling and the results of the five - factor anal ys is for each facility . The visibility modeling used c ombinations of control technologies (control “scenarios”) specified by the EPA with respect to the emissions inputs. The costs of compliance and visibility impacts for each scenario were estimated based on the following assumptions:  The costs and emission reductions (in tons reduced) for the individual technologies that make up each control configuration are additive, i.e., the control scenario costs and emission reductions can be expressed, respectively , as the sum of the component technology

costs, and th e 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 dif ferences in dates of installation of controls . This provides a more realistic assessment of “ existing pollution control technology in use at each source ” than a uniform baseline for all units.  The baseline emissions used in the CALPUFF modeling are not ide ntical to those used in the control option s analy ses because the BART Guidelines provide different methods for calculating baseline emissions 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 were extracted from the EPA Clean Air Market Division (CAMD) Continuous Emission Mon itoring Sy stem (CEMS) database .  The baseline emission inputs for PM for visibility modeling are derived from the hourly plant heat input (from the CEMS database) multiplied by emission limits specified in ADEQ’s BART determinations for these units . This a pproach 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 will go into effect prior to an y NO x or SO 2 limitations resulting from EPA’s action.  The control cost analy sis uses annual average emission s (TPY) based on actual emissions from a baseline period representing anticipated future annual emissions .EMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

UNC -EMAQ 5 - 12 - 026. v1 4 October 9, 2012 The visibility

impacts of the control scenarios are discussed in the sections on visibility and control effectiveness analy sis for each facilit y. **2.2.1 Sundt Unit 4**  

### 2.2.1.1 **General Plant Information** Unit 4 of the Sundt plant (formerl y Irvington) shown in Figure 2 is a coal - fired boiler that was found to be subject to BART from our previous analy ses in Task 6 of this WA. Table 13 display s 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 effectiveness calculations , is determined by d ividing total reported heat input by the potential heat input if the unit were operating at 100% capacity , 36 5 day s a y ear . Sundt Unit 4 has a ba ghouse (FF) for PM control. In addition it is equipped with L NB and overfire air (OFA) for NO x control.

**Figu re**  **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 0.477 0.445 0.729 37%EMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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### 2.2.1.2 **NO x**  

### Control Options Analysis **2.2.1.2.1 Available NO**  **x** 

### Control Technologies Both combustion and post - combustion controls are available. 

### 2.2.1.2.2 **Feasible NO x**  

### Control Technologies Since Sundt 4 alread y has combustion controls by way of LNB and OFA, the focus of ATP’s cost anal ys is was on post - combustion controls. 

### 2.2.1.2.3 **Evaluation of NO x**  

### Control Technologies Although onl y post - c ombustion controls were examined, some advanced forms of OFA may permit further reductions. The results of this evaluation are shown in Table 14. For the cost estimation, baseline emissions and capacity factors for all electric utility units were developed from historical data as follows:  The c apacit y factor is the average of that estimated for the period 2008 - 2011 using reported heat input and plant capacity in formation.  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 to 7% over 20 ye ars) plus tax and insurance costs of 1.2% were assumed in the cost anal ys is. 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 been determined for e lectric generating units per the IPM documentation. 2 

### 2.2.1.2.4 **Energy and Environmental Impacts** SNCR has negligible energy impact. SCR will incur an additional parasitic loss, mainly due to pressure drop across the SCR sy stem, which is roughl y equal to 0.59% of out put. Although the IPM calculations for which these algorithms were developed treated this not as a cost , but as a reduction in capacit y , 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 fl y ash odor and potential impact on fly ash sales/disposal. Ammonia slip can be well controlled so that fly ash is not adversel y impacted. SCR cataly st can be recycled and therefore is not a significant concern.

2 From Integrated Planning Model ver 4.10 documentation, page 8 - 11 : 0.30% for insurance and 0.90% for taxes.EMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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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 (incremental)** $3,307 $5,686 * SCR is actually capable of 90% removal. The model that we used set a low er limit of 0.05 lb/MMBtu, but low er NOx levels should be achievable 

### 2.2.1.3 **SO 2**  

### Control Options Analysis SO 2 emission rates increased in 2011 from the 2008 - 2010 average, indicating a change in coal. 

### 2.2.1.3.1 **Available SO** **2** 

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

### 2.2.1.3.2 **Feasible SO** **2** 

### Control Technologies All of the available technologies are feasible. In fact, DSIis 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 probabl y not enough space to install a new absorber betwe en the boiler and the existing FF. A wet FGD would be installed downstream of the existing FF . 

### 2.2.1.3.3 **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 o f each of the SO 2 control technologies. In light of the low 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). DSIis expected to have high control efficienc y due to the existing FF . The FGD removal efficiencies are limited by assumptions in the Sargent & Lund y model developed for CAMD that was used for the FGD cost anal ys is . In practice, we would expect both dry and wet FGD to achieve higher capture efficiencies and there fore somewhat lower emissions levels , i.e., the Table 15 results are conservative .EMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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**Table 15.** S O 2 Contol Technologie s for Sundt Unit 4



### 2.2.1.3.4 **Energy and Environmental Impacts of Control Option s**  The energy

impacts of DSIare small. FGD will have significant energy impacts (over 1% of output) due to pressure loss across the FGD s ys tem, and the additional pumping power and auxiliary loads involved. Energy

costs are included for each technology analyzed in Table 15. DSIusing 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 h ydrate might avoid this problem. DSIhas 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 landf ills . The wet scrubber waste can be dewatered and sold to the gy psum market. More information on these impacts is available in Section 2.1.2 of the ATP report attached in Appendix B . 

### 2.2.1.4 **PM Control Options** Sundt Unit 4 is equipped with FF , and there is no tec hnology available that would provide a higher degree of PM reduction than a properly designed and operated FF . Therefore, there are no changes assumed to the PM emission rates under the BART anal ys is. **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 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 $13,986,681 **$/Ton** $1,832 $6,529 $7,057 **$/Ton (incremental)** $1,832 $31,647 $24,189EMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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### 2.2.1.5 **Visibility Modeling** Sundt Unit 4 is subject to BART controls, but for realistic representation of the emission plumes all 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 control 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**  **- Em**  **is SO 2** 

**(TPY) NO**  **x Control**   **- Em**  **is NO**  **x (TPY)**  **SO 2**  **+NO x** 

 **- Em**  **is (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 Ctrl - 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 

### 2.2.1.5.1 **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 anal ys is of 2007 3 . 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

3 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-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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### 2.2.1.5.2 **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 convenience in Table A - 2, Appendix A. The input data were extensively qualit y assured using scripts created for this purpose b y 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 their baseline values.  The EPA’s initial guidance on th e emissions for these scenarios called for the use of the WRAP BART analy sis (WRAP, 2007) for PM emissions from all units. However, that anal ys is covered only

Unit 4 and one out of three of the natural gas - fired units. Thus the WRAP emission rates were used onl y 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/2006FinalDryBottomP C_ 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 facilit y, EPA eventually

recommended that the PM emissions from Units 1 - 3 be set to zero. Thus no PM emissions or speciation data are provided for these units. Following the CALPUFF modeling, the con centration 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 conc entration files for 2001 - 2003 were combined in the APPEND utility to produce a composite 3 - ye ar file, which was provided along with the annual files for CALPOST visibility

processing. 

### 2.2.1.5.3 **CALPOST Setup** As with the CALPUFF modeling, the CALPOST model setup fol lowed 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 impairment (  - 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 day s at the CIAs. Fo r both methods, CALPOST uses the input values of monthly - average relative humidity adjustment factor f(RH), rather than the hourly

values on the VI SB .DAT file generated by CALPUFF. CALPOST input data were extensively

quality - assured using scripts created f or this purpose by

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### 2.2.1.5.4 **Extraction of Visibility Results with POSTCALPOST** UNC extracted the results from the CAL POST visibility

anal ys is for the four methods of calculating visibility

using POSTCALPOST. The results for the 98 th percentile incremental visi bility impairment  - dv relative to background visibility at the 9 CIAs listed in Table 1 within 300 - km of the Sundt Plant for each ye ar modeled (2001 - 2003), and for the composite three - ye ar 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 period 2001 - 2003. Tables 18(a) and (b) summarize the incremental visibility impairment relative to background (22nd highest  - dv, corresponding to the 98 th percentile) at each CI A within 300 km of the Sundt Plant for the base case and controls scenarios from Method 6(a) and Method 8(b) respectivel y. Table 18 shows greater 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 Bald y, the v isibility impairment 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 )

(b)EMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

UNC -EMAQ 5 - 12 - 026. v1 11 October 9, 2012 The above conclusion is confirmed b y Table 19, which shows that the 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 these, 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 )

**(**b **)**EMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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### 2.2.1.6 **Control Effectiveness Results**  This section discusses 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 control 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 b y 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 ffectiveness (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) are clearl y 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 t o its much higher cost is not as cost - effective as SNCR despite its much greater control efficiency . Finall y, Method 8(b) sho w s greater effectiveness than Method 6(a) for all control options and CIAs.EMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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**Table 21**  **.** Control E ffectiveness (million $/dv) Summary for the

Calculation Methods of Table 18

(a)

(b)EMAQ LOE (EPA Contract EP-D - 07- 102) WA 5 - 12: Task 7 Five -Factor BART Analysis Report

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### 2.3 **Conclusi ons**  The five - factor BART analy sis of Sundt Unit 4 led to the following conclusions:  The visibility

i mpacts are greatest for each facility at the nearest CIAs, and the control options are least effective (greatest in million $/dv) at the farthest ones.  The following are the technologies found to be most cost - effective at the highest impact CIA at each fa cility : o SNCR , and S N CR in combination with DSI at Sundt Unit 4, followed by SCR with DSI  In the case of Sundt 4 the control effectiveness of SO 2 controls such as wet and dry FGD is greater at the CIAs farther away from the source. NOx control technologies such as SCR and SNCR have a lot more effectiveness at nearb y C IAs .  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 -EMAQ 5 - 12 - 026. v1 15 October 9, 2012 

## References ENSR, 2009: Revised BART Analysis for the Navajo Generating Station Units 1 - 3 , ENSR Corporation, Document No. 05830 - 012 - 300, January 2009, Salt River Project

– Navajo Generating Station, Tempe, AZ. EPA , 2002 : EPA Air Pollution Control Cost Manual (Sixth Edition) , Report No. EPA/452/B 02 - 0 01 , U.S. Environmental Protection Agency . IL EPA , 2007: Technical Support Documentation for C ontrol of N itrogen Oxide Emissions from L ime Kilns”, June 2007 , AQPSTR 07 - 04, I llinois Environmental Protection Agency . Staudt, J., and C. Erickson, 2008: Selective Catalytic Reduction Sy stem 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/CALPUF

F Protocol for BART Exemption Screening Analysis for Class I Areas in the Western United States . Western Regional Air Partnership Air Qualit y Modeling Forum, Regional Modeling Center, August 15, 2006; http://pah.cert.ucr.edu/aqm/308/bart/WRAP_RMC_BART_Protocol_Aug15_2006.pdf

## Ap **pendix A**  **Emissions Data Tables**UNC

-EMAQ 5 - 12 - 026.v1 A - 2 October 9, 2012 This appendix provides the emissions data for CALPUFF modeling of the base case(s) and control scenarios anal yz ed for the thr ee facilities. These data were extracted from a master spreadsheet that is being delivered as part of the documentation for this ta sk. **Table A -**  **2 (a).**  NO x , SO 2 and PM E mission Inputs 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 Analysis Report

UNC -EMAQ 5 - 12 - 026.v1 A - 3 October 9, 2012 **Table A -**  **2 (b).**  Speciated PM E mission Inputs for B ase and C ontrol S cenarios for Sundt Unit 4 V isibility M odeling

## Ap **pendix B**  **Andover Technology Partners Report Chapter 3**  **: BART Analysis**  **(NO x**  

### , SO **2** 

### and PM)3 - 2 **www.AndoverTechnology.com Chapter 3. BA**  **RT An**  **alysis (NOx, SO2 and PM) Task 7: Determine BA**  **RT Control Options (SO2, NOx, PM)** Under this task, Andover Technology Partners will conduct a full 5 - factor BART analysis of all technically feasible control options for  Sundt (Unit 4). Cost estimates performed in this section utilize methods consistent with the US EPA Control Cost Manual, 4 cost estimating methods used in EPA’s late st Integrated Planning Model (IPM) methods 5 , and other reasonable engineering methods.

.

4 EPA. 2002. EPA Air Pollution Control Cost Manual (Sixth Edition). EPA/452/B - 02 - 001 5 Documentation of EPA IPM Base Case v4.10. http://www.epa.gov/airmarkets/progsregs/epa ipm/BaseCasev410.html#documentation3 - 3 **www.AndoverTechnology.com**

**3.3 H. Wilson Sundt Power Plant**  H. W ilson 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%3 - 4 **www.AndoverTechnology.com**

**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 controls. 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.  Capacity 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 2011 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 insurance 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. 6 Energy Effects SNCR has negligible 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 developed for, rather as a reduction in capacity, it has been treated as an increase in variable operating cost for these calculations.

6 From Integrated Planning Model ver 4.10 documentation , page 8 - 11 . 0.30% for insurance and 0.90% for taxes.3 - 5 **www.AndoverTechnology.com**

Environmental Impacts Environmental impacts of SNCR and SCR are primarily due to ammonia slip. The main environmental concern is regarding fly ash odor and potential impact o n f ly 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 significant concern. **Table 3 -**  **13.** NOx Control for Sun dt 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, $/y**

**ear** $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 achievable3 - 6 **www.AndoverTechnology.com**

**3.3.2 SO**  **2 Control**  SO 2 emission rates increased in 2011 from the 2008 - 2010 average, indicating a change in coal. Available Technologies 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 has 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 o f 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 technologies. 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 efficien cies due to the fabric 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 somewhat 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 out put) due to pressure loss across the FGD system and due to additional pumping power and other auxiliary loads. In all cases energy costs are included 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 benefi ts 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 informatio n is available in Section 2.1.2.3 - 7 **www.AndoverTechnology.com Table 3**  **- 14**  . SO 2 Control for Sundt 4 **Sundt 4 –**  **SO2** DSI Dry FGD Wet FGD Capacity Factor 37% 37% 37% Control 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) 540 237 178 **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, $/y**

**ear** $2,967,501 $12,553,539 $13,986,681 **$/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 designed and operated fabric filter. Therefore, there are no changes to PM emission rates under the BART anal ysis.