7272 E. INDIAN SCHOOL ROAD, SUITE 360 

SCOTTSDALE, ARIZONA 85251 

TELEPHONE: 480-505-3900 

FACSIMILE: 480-505-3901 

ERIC L. HISER 

DIRECT LINE: 480-505-3927 

e-mail: ehiser@jordenbischoff.com

LAW OFFICES

JORDEN BISCHOFF

& HISER, P.L.C.

 May 29, 2013 

The Honorable Robert Perciasepe The Honorable Jared Blumenfeld 

Acting Administrator Regional Administrator 

U.S. Environmental Protection Agency U.S. EPA, Region 9 

USEPA Ariel Rios Building (AR) 75 Hawthorne Street 

1200 Pennsylvania Avenue N.W. San Francisco, CA 94105 

Washington, DC 20004 

 Re: Supplement to Petition for Administrative Reconsideration 

 BART for Units 2 and 3, Apache Generating Station 

 77 Fed. Reg. 72512 (Dec. 5, 2012) 

Dear Messrs. Perciasepe and Blumenfeld: 

 On February 2, 2013, Arizona Electric Power Cooperative, Inc. (“AEPCO”) filed a 

petition for administrative reconsideration of the U.S. Environmental Protection Agency 

(“EPA”) final rule entitled “Approval, Disapproval and Promulgation of Air Quality 

Implementation Plans; Arizona; Regional Haze State and Federal Implementation Plans” in the 

Federal Register at volume 77, pages 72512 and following (the “Rule”). As part of the Rule, 

EPA promulgated a Federal Implementation Plan (“FIP”) establishing “best available retrofit 

technology” or “BART” for Apache Generating Station Steam Units 2 and 3 operated by 

AEPCO. In its petition, AEPCO provided information demonstrating that the FIP is 

unaffordable, requested clarification of the application of the BART limits to Apache Generating 

Station Steam Unit 1, and expressed concern about unintended consequences of averaging 

provisions adopted as part of the compliance provisions of the BART FIP. AEPCO also stated 

that it believed that EPA’s visibility objectives could be substantially met at less cost. 

 EPA graciously agreed to meet with AEPCO to discuss its petition on February 8, 2013, 

in Washington, DC, and then again in several subsequent conference calls. In these discussions, 

EPA and AEPCO have discussed, as AEPCO suggested on page 21 of its February 2, 2013 

petition, alternatives to the BART determined in the FIP. EPA technical staff has indicated that 

they believe AEPCO’s tentative recommendation at the February 8, 2013 meeting—a conversion 

of one of AEPCO’s units from coal to pipeline natural gas and use of selective non-catalytic 

reduction (“SNCR”) technology at the other—has sufficient merit to warrant a formal proposal 

for the Agency’s consideration. Accordingly, consistent with EPA Region 9’s request, AEPCO 

submits this supplement to its February 2, 2013 petition for administrative reconsideration 

setting forth its proposed alternative in more detail. 

 
Supplement to Petition for Administrative Reconsideration 

Arizona Electric Power Cooperative, Inc. 

May 29, 2013 

Page 2 

AEPCO’s Proposal for BART

 As discussed with EPA technical representatives, AEPCO is proposing that the following 

control technology be adopted as BART for Apache Generating Station Steam Units 2 (“ST2”) 

and 3 (“ST3”). AEPCO believes that this proposal will achieve equivalent, or better, visibility 

results than that promulgated by EPA in the Final Rule. 

BART for ST2

 AEPCO proposes to permanently convert ST2 from coal to natural gas on December 5, 

2017, with an exception for a limited emergency use in the event of disruption of the natural gas 

supply, which is discussed below. AEPCO proposes to establish BART as the following 

combination of technologies and pollutant limits: 

Particulate Matter: Pipeline Natural Gas (“PNG”), 0.01 lb PMTotal/MMBtu 30-day rolling 

average, dropping to 0.008 lb PMTotal/MMBtu 30-day rolling average 

effective December 5, 2018. 

Sulfur Dioxide: PNG, 0.00064 lb/MMBtu 30-day rolling average. 

Nitrogen Oxides: PNG, 0.085 lb/MMBtu 30-day rolling average. 

Emergency Provision: AEPCO will not operate ST2 on coal after the effective date of the BART 

determination except in the event of a supply disruption caused by natural 

gas supplier or transporter pipeline failure, freeze-up or pipeline 

compression failure that reduces gas volume or gas pressure below that 

necessary for Apache Generating Station gas generation. AEPCO must 

discontinue coal firing as expeditiously as possible after restoration of 

natural gas service at levels supporting continuous firing of ST2 and in no 

event more than 48 hours after restoration of such service. 

Flexibility Provision: AEPCO may comply with the BART limits through any combination of 

process adjustments or add-on controls, provided that such combination 

achieves the BART numeric limit (on a 30-day rolling average basis) and 

complies with applicable regulations and permits and AEPCO obtains any 

necessary preconstruction or operating approvals. 

BART for ST3

 AEPCO proposes to retain coal as the principal fuel, with natural gas and co-firing of 

coal and natural gas as alternative operating scenarios, for ST3. AEPCO proposes to establish 

BART as the following combination of technologies and pollutant limits: 
Supplement to Petition for Administrative Reconsideration 

Arizona Electric Power Cooperative, Inc. 

May 29, 2013 

Page 3 

Particulate Matter: Electrostatic precipitators (ESPs), 0.03 lb PMFilterable/MMBtu 30-day 

rolling average. 

Sulfur Dioxide: SO2 scrubbers, 0.15 lb/MMBtu, 30-day rolling average. 

Nitrogen Oxides: Low NOx Burners + Overfire Air + SNCR, 0.23 lb/MMBtu, 30-day 

rolling average. 

Flexibility Provision: AEPCO may comply with the BART controls through any combination of 

fuels, process adjustments, or add-on controls, provided that such 

combination achieves the BART numeric limit (on a 30-day rolling 

average basis) and complies with applicable regulations and permits and 

AEPCO obtains any necessary preconstruction or operating approvals. 

EPA inquired whether AEPCO’s SNCR installation might achieve a lower NOx rate over a 

longer average for modeling purposes. Based on input from FuelTech, AEPCO believes that 

overall NOx reductions would likely be on the order of 0.225 lb/MMBtu, but this cannot be 

achieved on a 30-day rolling average in all cases and AEPCO is not proposing the 0.225 

lb/MMBtu as a limit because of the uncertainty. AEPCO has also proposed to reduce the 

particulate matter limit for the natural gas unit from 0.01 lb PMTotal/MMBtu to 0.008 lb 

PMTotal/MMBtu. This reduction would become effective on December 5, 2018. 

BART Timing

AEPCO proposes to retain the current time line for implementation outlined in EPA’s SIP 

approval (for PM and SO2) and FIP (for NOx), except that specific deadlines are adjusted to 

accommodate the ST2 conversion to natural gas, as follows: 

ST1: Unchanged 

ST2: NOx effective December 5, 2017 

 SO2 0.15 lb/MMBtu effective December 5, 2016 

 SO2 0.00064 lb/MMBtu effective December 6, 2017 

 PM10-Filterable 0.03 lb/MMBtu effective December 5, 2016 

 PM10-Total 0.01 lb/MMBtu effective December 5, 2017 

 PM10-Total 0.008 lb/MMBtu effective December 5, 2018 

ST3: NOx effective December 5, 2017 

 SO2 effective December 5, 2016 

 PM10-Filterable effective December 5, 2016 

Additionally, should final approval of this proposal be delayed by more than six months 

from the original SIP approval and FIP promulgation effective date, the implementation date 

would be tolled on a day-by-day basis to account for the delay. Final approval would be defined 

as the effective date of EPA’s rule promulgating this proposal, unless stayed at the request of a 

third party, in which case final approval would be upon termination of the stay (assuming the 
Supplement to Petition for Administrative Reconsideration 

Arizona Electric Power Cooperative, Inc. 

May 29, 2013 

Page 4 

rule is upheld). If the proposal is invalidated, AEPCO must comply with the current BART FIP 

(and/or SIP, for non-NOx pollutants) within four and a half years. 

Justification

 AEPCO believes, based upon modeling, monitoring, and our general understanding of 

regional haze that the visibility benefits of its proposal will be better than those achieved by 

EPA’s existing FIP—e.g., that AEPCO’s proposal is “better than BART.” Better than BART 

results are achieved both by the emissions reductions resulting from AEPCO’s proposal and 

because the emissions results will better match Arizona’s “Uniform Rate of Progress” goals to 

achieve the ultimate congressional goal. 

Emissions Reductions Exceed Those Achieved Under EPA’s SCR BART FIP

 AEPCO has calculated the emissions reductions achieved from both EPA’s SCR BART 

FIP and AEPCO’s proposed alternative converting ST2 to pipeline natural gas and ST3 to SNCR 

using the same heat input rate as EPA did in the proposed and final rules and AEPCO’s 85% 

utilization factor for all cases. Using this approach, the AEPCO alternative achieves additional 

aggregate emissions reductions for SO2 and particulate matter that outweigh the increase in NOx 

emissions. This can be seen in the following table: 

Control Option Pollutant Unit 

Emissions 

Factor, 

lb/MMBtu 

Heat Rate 

MMBtu/hr 

Annual 

Capacity 

Factor 

Emissions 

lb/hr 

Emissions 

tpy 

Baseline NOx ST2 0.371 2316 0.85 859.24 3198.94 

Baseline SO2 ST2 0.15 2316 0.85 347.40 1293.37 

Baseline PM ST2 0.03 2316 0.85 69.48 258.67 

Baseline NOx ST3 0.438 2223 0.85 973.67 3624.99 

Baseline SO2 ST3 0.15 2223 0.85 333.45 1241.43 

Baseline PM ST3 0.03 2223 0.85 66.69 248.29 

Combined NOx 1832.91 6823.92 

Combined SO2 680.85 2534.80 

Combined PM 136.17 506.96 

EPA SCR NOx ST2 0.07 2316 0.85 162.12 603.57 

EPA SCR SO2 ST2 0.15 2316 0.85 347.40 1293.37 

EPA SCR PM ST2 0.03 2316 0.85 69.48 258.67 

EPA SCR NOx ST3 0.07 2223 0.85 155.61 579.34 

EPA SCR SO2 ST3 0.15 2223 0.85 333.45 1241.43 

EPA SCR PM ST3 0.03 2223 0.85 66.69 248.29 

Combined NOx 317.73 1182.91 
Supplement to Petition for Administrative Reconsideration 

Arizona Electric Power Cooperative, Inc. 

May 29, 2013 

Page 5 

Control Option Pollutant Unit 

Emissions 

Factor, 

lb/MMBtu 

Heat Rate 

MMBtu/hr 

Annual 

Capacity 

Factor 

Emissions 

lb/hr 

Emissions 

tpy 

Combined SO2 680.85 2534.80 

Combined PM 136.17 506.96 

AEPCO Proposal NOx ST2 0.085 2316 0.85 196.86 732.91 

AEPCO Proposal SO2 ST2 0.00064 2316 0.85 1.48 5.52 

AEPCO Proposal PM ST2 0.008 2316 0.85 18.53 68.98 

AEPCO Proposal NOx ST3 0.225 2223 0.85 500.18 1862.15 

AEPCO Proposal SO2 ST3 0.15 2223 0.85 333.45 1241.43 

AEPCO Proposal PM ST3 0.03 2223 0.85 66.69 248.29 

Combined NOx 697.04 2595.06 

Combined SO2 334.93 1246.95 

Combined PM 85.22 317.27 

Comparison 

NOx 

TPY SO2 TPY PM TPY Net Change 

EPA to Baseline -5641.02 0.00 0.00 -5641.02 

AEPCO to Baseline -4228.86 -1287.85 -189.69 -5706.41 

AEPCO to EPA 1412.15 -1287.85 -189.69 -65.39 

As can be seen from the calculations, AEPCO’s alternative will result in reducing an estimated 

1288 tons of SO2 and 190 tons of particulate matter compared to EPA’s BART FIP, while 

increasing NOx emissions by approximately 1412 tons/year, resulting in an aggregate emissions 

reduction of an additional 65 tons/year. AEPCO’s alternative thus achieves better than BART 

levels of reduction. As discussed below, AEPCO’s alternative also achieves superior visibility 

benefits. 

CALPUFF Modeling Shows “Better than Bart” Results

 Both EPA Region 9 and AEPCO’s consultant, ENVIRON (which assisted in the original 

Western Regional Air Partnership (WRAP) modeling effort), have conducted CALPUFF 

modeling of AEPCO’s emissions. Both EPA and ENVIRON used a common CALMET 

meteorological database and a common version of the CALPUFF model to minimize unintended 

differences. Additionally, ENVIRON ran EPA’s base case and SCR case and compared 

ENVIRON results to EPA, which showed good agreement, after adjusting a stack temperature 

correction from AEPCO. As noted in the ENVIRON report, AEPCO is using a direct 

comparison of the CALPUFF modeling results for both the average of the 98th percentile for the 

three years 2001-2003 or the 22nd high measurement over the 2001-2003 period for comparison 

with EPA’s SCR scenario modeled results to determine whether AEPCO’s proposed alternative 

results in better than BART results. Based on guidance provided by EPA, AEPCO is using NOx 
Supplement to Petition for Administrative Reconsideration 

Arizona Electric Power Cooperative, Inc. 

May 29, 2013 

Page 6 

values of 0.225 lb/MMBtu for its proposed SNCR alternative on ST3 rather than the 0.23 

lb/MMBtu 30-day rolling limit. While AEPCO’s vendor does not believe that AEPCO can 

achieve less than 0.23 lb/MMBtu during all 30-day periods, it does believe that, over time, 

AEPCO’s emissions are likely to be 0.225 lb/MMBtu or less. The details of the modeling are set 

forth in the attached ENVIRON report “CALPUFF Visibility Modeling of the AEPCO BART 

Scenarios” dated May 10, 2013. 

 In the ENVIRON report, the AEPCO proposal is Version 2 of AEPCO Alternative 

Control 9b. In Attachment E5, ENVIRON report sets forth the CALPUFF model results as 

follows: 

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

EPA BART SCR 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.790 2.147 1.996 1.978 1.996

Chiricahua Wild. 1.979 1.892 1.788 1.886 1.979

Galiuro Wild. 0.991 1.146 1.486 1.208 1.205

Gila Wild. 0.226 0.321 0.238 0.262 0.279

Mazatzal Wild. 0.167 0.172 0.130 0.156 0.147

Mount Baldy Wild. 0.102 0.132 0.092 0.109 0.114

Saguaro NP 1.308 1.460 1.495 1.421 1.463

Sierra Ancha Wild. 0.137 0.174 0.149 0.153 0.158

Superstition Wild. 0.317 0.307 0.314 0.313 0.315

Average 0.780 0.861 0.854 0.832 0.851

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

AEPCO Alt Cntl 9bv2 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.898 1.740 2.007 1.882 1.909

Chiricahua Wild. 1.852 1.837 1.863 1.851 1.852

Galiuro Wild. 0.959 0.952 1.421 1.111 1.135

Gila Wild. 0.292 0.342 0.226 0.287 0.295

Mazatzal Wild. 0.136 0.131 0.112 0.126 0.124

Mount Baldy Wild. 0.116 0.121 0.100 0.112 0.116

Saguaro NP 1.213 1.525 1.301 1.346 1.317

Sierra Ancha Wild. 0.132 0.139 0.118 0.130 0.128

Superstition Wild. 0.283 0.330 0.212 0.275 0.283

Average 0.765 0.791 0.818 0.791 0.795

 
Supplement to Petition for Administrative Reconsideration 

Arizona Electric Power Cooperative, Inc. 

May 29, 2013 

Page 7 

Difference in dv between EPA BART SCR and AEPCO Alternative Cntl 9b (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 0.108  ‐0.407 0.011  ‐0.096  ‐0.087

Chiricahua Wild.  ‐0.127  ‐0.055 0.075  ‐0.036  ‐0.127

Galiuro Wild.  ‐0.032  ‐0.194  ‐0.065  ‐0.097  ‐0.070

Gila Wild. 0.066 0.021  ‐0.012 0.025 0.016

Mazatzal Wild.  ‐0.031  ‐0.041  ‐0.018  ‐0.030  ‐0.023

Mount Baldy Wild. 0.014  ‐0.011 0.008 0.004 0.002

Saguaro NP  ‐0.095 0.065  ‐0.194  ‐0.075  ‐0.146

Sierra Ancha Wild.  ‐0.005  ‐0.035  ‐0.031  ‐0.024  ‐0.030

Superstition Wild.  ‐0.034 0.023  ‐0.102  ‐0.038  ‐0.032

Average  ‐0.015  ‐0.070  ‐0.036  ‐0.041  ‐0.055

In seven of the nine Class I Areas, AEPCO’s proposal achieves additional visibility 

improvements beyond what EPA’s BART FIP achieves. These improvements range from a low 

of -0.024 dv to a high of -0.097 dv. Only two areas show a marginal increase (of +0.004 and 

+0.025 dv) and these impacts are imperceptible and occur in areas where the Apache Station’s 

total BART-eligible contribution to visibility impairment is less than 0.3 dv. Critically, using 

EPA’s cumulative BART metric, AEPCO’s proposal would achieve a -0.367 dv (on Average 

98th percentile basis) or a -0.497 dv (on a 22nd high basis) improvement in visibility versus 

EPA’s current BART FIP. AEPCO’s proposal thus achieves “better than BART” results on even 

the most conservative basis. 

 As stated in the ENVIRON report, however, the use of the regulatory 1.0 ppb default 

ammonia concentration is not necessarily representative of visibility conditions in Arizona. 

Measured ammonia background values are available, as noted in the attached ENVIRON report 

and in prior comments by APS and SRP. If the variable, measured ammonia concentrations are 

used, improvements in visibility resulting from AEPCO’s proposed alternative are greater, as set 

forth in the ENVIRON report in Attachment D2. This shows improvements ranging from a low 

of -0.015 to a high of -0.25 dv (average 98th percentile basis), or -0.005 to -0.275 dv (22nd high 

basis) in all nine areas and the cumulative impact is -1.059 dv (average 98th percentile basis) or --

1.064 dv (22nd high basis). Using the more realistic, variable ammonia background suggests that 

visibility improvements will be considerably higher – approaching a full deciview, which is 

likely to be a perceptible improvement. AEPCO believes that a fully perceptible improvement is 

clearly better than BART. 

 Finally, as ENVIRON notes in its two attached reports, the natural gas particulate 

speciation data used in the existing Federal Land Manager (FLM) protocol substantially 

overstates the elemental carbon and organic carbon contributions from natural gas. As can be 

seen in Table 2b, the FLM protocol results in natural gas having higher carbon emissions than 

coal. EPA itself has changed these assumptions in the National Emissions Inventory (NEI) 
Supplement to Petition for Administrative Reconsideration 

Arizona Electric Power Cooperative, Inc. 

May 29, 2013 

Page 8 

program. Using the NEI protocol results in far greater improvements, as seen in Attachment C 

of the ENVIRON report. While AEPCO cannot commit to the NEI values (because of testing 

and compliance demonstration issues with the Methods), use of the NEI values strongly suggests 

that actual visibility improvements will be greater than the conservative results shown in 

Attachments E5 and D2. Based on this extensive modeling work, and the sensitivity analysis 

inherent in the review of alternatives, AEPCO believes that the weight of the evidence 

demonstrates that its proposal will achieve better visibility improvements than EPA’s current 

BART FIP. A discussion of the technical basis for the NEI is found in the attached ENVIRON 

memorandum entitled “Updated PM2.5 Emissions Factors for Natural Gas-Fired Boilers,” dated 

May 8, 2013. The modeling results are set forth in the aforementioned “CALPUFF Visibility 

Modeling of the AEPCO BART Scenarios” memorandum dated May 10, 2013. 

 As requested by EPA Region 9 staff, CALPUFF modeling results are submitted for 

AEPCO Control 9b version 2 only in the enclosed CD. 

AEPCO’s Alternative Better Meets Uniform Rate of Progress Needs

 Visibility monitoring data at the Chiricahua monitor shows that both sulfate (derived in 

part from SO2 emissions) and particulate (derived in part from direct PM2.5 emissions) are, 

historically, more significant contributors to regional haze in the Chiricahua National Monument 

and Wilderness Area than is nitrate (derived in part from NOx emissions). The following chart, 

taken from Arizona’s Regional Haze SIP, shows the relative contributions over time: 

As can be seen, both the yellow “SO4 Extinction” and gray “CM (for coarse matter) Extinction” 

are generally much more significant than the red “NO3 Extinction” factor, based on the 

IMPROVE dataset. Breaking this down into the regulatory division of the 20 percent “best” and 

“worst” days clearly shows the impact of SO4 and CM versus NO3: 
Supplement to Petition for Administrative Reconsideration 

Arizona Electric Power Cooperative, Inc. 

May 29, 2013 

Page 9 

Sulfate contributes 35.9% in best days and 27.2% in worst days, versus only 7.8 and 4.4% 

respectively for nitrate (nearly 5x and 6x the impact). CM contributes 18.7% in best days and 

28.9% in worst days, or nearly 2x and 6x the impact of nitrate. Reductions in sulfate and coarse 

material thus should be anticipated to improve visibility by as much, or more than, equivalent 

reductions in nitrate. 

 Third, the Arizona Regional Haze SIP found, and EPA agreed, that the Uniform Rate of 

Progress (URP) demands significantly greater emissions reductions in sulfate and coarse material 

than nitrate, as seen in the following chart from the Arizona Regional Haze SIP: 

The AEPCO proposal significantly advances progress toward the SO4 Extinction and CM 

Extinction goals compared to the existing EPA FIP. 
Supplement to Petition for Administrative Reconsideration 

Arizona Electric Power Cooperative, Inc. 

May 29, 2013 

Page 10 

Based on the EPA and ENVIRON modeling, the monitoring data and general direction of 

emissions reduction needed to achieve the natural condition goal, and the general understanding 

of atmospheric chemistry and the limitations of the existing modeling tools, AEPCO believes 

that the weight of the evidence demonstrates that its proposal, which substantially reduces 

emissions of SO2 and PM while increasing NOx emissions more modestly, will achieve “better 

than BART” visibility improvement. 

AEPCO therefore formally requests that EPA reconsider its existing BART FIP limits 

and replace them with its proposal set forth in this letter for the reasons stated above. 

Status of ST1/GT1

In its petition for administrative reconsideration, AEPCO noted that EPA’s question and 

answer document for the Arizona BART program implied that Apache Generating Station gas 

turbine #1 (GT1) is subject to the ST1 BART limits. GT1 is a simple cycle turbine that can 

exhaust to the ST1 windbox; can be used to warm and dry the ST1 boiler, or can run in standalone mode. AEPCO believes that GT1, when operating in stand-alone mode or for boiler 

warming and drying, is a simple cycle unit not subject to BART. AEPCO, EPA and ADEQ held 

a conference call on February 22, 2013 to discuss the status of units ST1 and GT1. ADEQ has 

noticed a SIP revision addressing this issue. 

ADEQ has proposed to clarify the ST1 BART determination as follows: 

After reviewing the company's BART analysis, and based upon the information above ADEQ has 

determined that, for Unit 1, BART for NOx is the installation of LNB with FGR (which will also burn 

No. 2 fuel oil with minor equipment change out) with a NOx emissions limit of 0.056 lb/MMBtu when 

burning PNG, and 0.06 lb/MMBtu when burning No. 2 fuel oil. It should be noted that the proposed 

BART limit for ST1 will apply when ST1 operates alone or if ST1 and GT1 are operated as a combined 

cycle operation. The proposed BART limit does not apply to (a) GT1 in stand-alone simple cycle 

operation or (b) ST1/GT1 when ST1 burners are shut off and ST1 is not producing electricity. 

Arizona Regional Haze SIP, submitted to EPA on April 29, 2013, page 110 of 174. EPA’s 

consent to ADEQ’s proposed SIP revision (for which ADEQ has requested parallel processing) 

would resolve AEPCO’s request for administrative reconsideration on this issue. 

AEPCO appreciates EPA’s statement in a recent proposal that it agrees with this 

proposed clarification. AEPCO requests that EPA repeat this consent to the ST1/GT1 

clarification in the final rule so that AEPCO’s compliance obligations with respect to ST1 and 

GT1 are clear. 

Limit Achievability and Averaging

 In its petition for administrative reconsideration, AEPCO expressed concern about the 

averaging limit and the potential impact on cycling units and the inequity of being held in 

violation of a limit when AEPCO has shutdown the unit causing the “average” limit to be 
Supplement to Petition for Administrative Reconsideration 

Arizona Electric Power Cooperative, Inc. 

May 29, 2013 

Page 11 

exceeded. As AEPCO noted, because the cross-unit average can only be brought back into 

compliance by restarting the unit not able to achieve the 0.07 lb/MMBtu limit, it creates 

tremendous pressure to shorten maintenance to bring the problem unit back up to restore 

compliance. Placing this pressure on unit maintenance is likely to cause increased problems, 

including trips, upon restart, potentially prolonging the period of noncompliance. 

 To resolve this problem, AEPCO proposes to revise the NOx determination along the 

following conceptual lines: 

(1) The following NOx BART limits are established: 

a. ST2: 0.085 lb NOx/MMBtu, 30-BOD rolling average (BODRA) 

b. ST3: 0.23 lb NOx/MMBtu, 30-BOD rolling average 

c. ST2/ST3: Limit = ((ST2 MMBtu, 30BODRA * 0.085 lb/MMBtu) + (ST3 

MMBtu, 30 BODRA * 0.23 lb/MMBtu))/(ST2 MMBtu, 30 

BODRA + ST3 MMBtu, 30BODRA), where BODRA = 30 Boiler 

Operating Day rolling average for that unit 

(2) Compliance during periods when both units are operating is demonstrated when either of 

the following conditions are met: 

a. The combined NOx emissions of both units meet the combined limit; or 

b. Each unit meets its individual NOx limit. 

(3) Compliance during periods when only one unit is operating is met when the operating 

unit meets its individual NOx limits. 

Proposed revisions to the existing FIP compliance language are attached for EPA’s consideration 

for the Apache Generating Station. AEPCO does not know whether this approach is acceptable 

to the other utilities. AEPCO believes that averaging is valuable to provide operating flexibility 

when a unit is brought back on-line and that the proposed methodology may lessen the number 

of times that AEPCO might need to rely upon the malfunction provisions, which makes the 

averaging proposal set forth herein preferable. 

 AEPCO requests that EPA substitute the proposed compliance methodology for that set 

forth in the existing BART FIP. 

 AEPCO hopes that this proposal meets with EPA’s approval. As can be seen, AEPCO 

believes that its proposal should achieve equivalent, and in fact likely superior, visibility gains to 

those that EPA would obtain under the NOx BART FIP. AEPCO can achieve these gains at 

considerably lower cost, lowering the burden on its members and rural Arizonans. 

 We look forward to EPA’s consideration of this proposal. Please contact Michelle 

Freeark, AEPCO’s Director of Environmental Services, at (520) 586-5122, or Eric Hiser, 

AEPCO’s air counsel, at (480) 505-3927, if you have any further questions or concerns about 

this proposal. We look forward to EPA’s consideration and continued discussion to see if EPA 

 

Proposed FIP Language 

Arizona Electric Power Cooperative, Inc. 

May 29, 2013 

Page 1 

PROPOSED FIP LANGUAGE 

(3) Federal emission limitations.—(i) NOX emission limitations. Except as provided in paragraph (iii), the 

owner/operator of each coal-fired unit subject to this paragraph (f) shall not emit or cause to be emitted NOX in 

excess of the following limitations, in pounds per million British thermal units (lb/MMBtu) from any group of coalfired units. Each emission limit shall be based on a rolling 30-boiler-operating day average, unless otherwise 

indicated in specific paragraphs. 

Group of coal-fired units Federal emission limitation 

Apache Generating Station

Units 2 and 3 .................... 0.070

Cholla Power Plant Units 2, 

3, and 4 ............................. 0.055 

Coronado Generating Station 

Units 1and 2 ...................... 0.065 

(ii) [No change] 

(iii) Apache Generating Station Units 2 and 3 shall not emit or cause to be emitted NOx, SO2 or PM10 in 

excess of the following limitations, in pounds per million British thermal units (lb/MMBtu) from each unit, or 

emit or cause to be emitted NOx from the combination of Units 2 and 3 in excess of the following limit defined 

by equation. Each emission limit shall be based on a rolling 30-boiler-operating day average, determined as 

follows: 

Apache Generating Station Limits, lb/MMBtu 

Unit NOx SO2 PM10 

Unit 2, Phase 1 NA 0.15 0.03 Filterable 

Unit 2, Phase 2 0.085 0.00064 0.01 Total 

Unit 2, Phase 3 0.085 0.00064 0.008 Total 

Unit 3, Phase 1 NA 0.15 0.03 Filterable 

Unit 3, Phase 2 0.23 0.15 0.03 Filterable 

Combined Units 2/3 * NA NA 

*Combined Units 2/3 NOx Limit = ((Unit 2 MMBtu * 0.085 lb/MMBtu) + (Unit 3 MMBtu * 0.23 

lb/MMBtu)/(Unit 2 MMBtu + Unit 3 MMBtu) 

Compliance during a boiler operating day when both units are operating is demonstrated when either of the 

following conditions are met: (A) the combined NOx emissions of Units 2 and 3 meet the combined limit; or 

(B) each unit meets its individual NOx limit. Compliance during a boiler operating day when only one unit is 

operating is demonstrated when the operating unit meets its individual NOx limit. 

(4) Compliance dates. (i) The owners/operators of each unit subject to this paragraph (f) shall comply with the NOX 

emissions limitations and other NOX related requirements of this paragraph (f) no later than December 5, 2017. 

(ii)(A) Except as provided in paragraph (B), the owners/operators of each unit subject to this paragraph (f) shall 

comply with the applicable PM10 and SO2 emissions limits submitted to EPA as part of the Arizona Regional Haze 

SIP in a letter dated February 28, 2011, and approved into the Arizona State Implementation Plan on December 5, 

2012, as well as the related compliance, recordkeeping and reporting of this paragraph (f) no later than the following 

dates: 

Table [delete AEPCO Unit 2 and Unit 3] 
Proposed FIP Language 

Arizona Electric Power Cooperative, Inc. 

May 29, 2013 

Page 2 

(B) The owner/operator of the Apache Generating Station Units 2 and 3 subject to this paragraph (f) shall 

comply with the applicable PM10 and SO2 emissions limits and the related compliance, recordkeeping and 

reporting requirements of this paragraph (f) no later than the following dates: 

Apache Generating Station Compliance Time Line 

Unit and Limits Compliance Date 

Unit 2, Phase 1 December 5, 2016 

Unit 2, Phase 2 December 5, 2017 

Unit 2, Phase 3 December 5, 2018 

Unit 3, Phase 1 December 5, 2016 

Unit 3, Phase 2 December 5, 2017 

Combined Units 2/3 December 5, 2017 

 (iii) [No change] 

(5) Compliance determinations for NOX and SO241

—(i) Continuous emission monitoring system. (A) At all times 

after the compliance date specified in paragraph (f)(4) of this section, the owner/operator of each coal-fired unit 

shall maintain, calibrate, and operate a CEMS, in full compliance with the requirements found at 40 CFR Part 75, to 

accurately measure SO2, NOX, diluent, and stack gas volumetric flow rate from each unit. In addition, the 

owner/operator of Cholla Units 2, 3, and 4 shall calibrate, maintain, and operate a CEMS, in full compliance with 

the requirements found at 40 CFR Part 75, to accurately measure SO2 emissions and diluent at the inlet of the sulfur 

dioxide control device. Apache Unit 1 NOX and diluent CEMs shall be operated to meet the requirements of Part 75. 

All valid CEMS hourly data shall be used to determine compliance with the emission limitations for NOX and SO2

in paragraph (f)(3) of this section for each unit. When the CEMS is out-of-control as defined by Part 75, that CEMs 

data shall be treated as missing data and not used to calculate the emission average. Each required CEMS must 

obtain valid data for at least 90 percent of the unit operating hours, on an annual basis. Apache Unit 2 is not 

subject to the requirements of paragraph (f)(5)(i) for SO2 upon its conversion to pipeline natural gas, but 

shall comply with paragraph (f)(5)(iii)(E). 

(B) The owner/operator of each unit with a CEMS subject to paragraph (f)(5)(i) shall comply with the quality 

assurance procedures for CEMS found in 40 CFR Part 75. In addition to these Part 75 requirements, relative 

accuracy test audits shall be calculated for both the NOX and SO2 pounds per hour measurement and the heat input 

measurement. The CEMs monitoring data shall not be bias adjusted. The inlet SO2 and diluent monitors required by 

this rule shall also meet the Quality Assurance/Quality Control (QA/QC) requirements of Part 75. The testing and 

evaluation of the inlet monitors and the calculations of relative accuracy for lb/hr of NOX, SO2 and heat input shall 

be performed each time the Part 75 CEMS undergo relative accuracy testing. In addition, relative accuracy test 

audits shall be performed in the units of lb/MMBtu for the inlet and outlet SO2 monitors at Cholla Units 2, 3, and 4. 

Heat input for Apache Unit 1 shall be measured in accordance with Part 75 fuel gas measurement procedures found 

in 40 CFR Part 75, Appendix D. 

(ii) Compliance determinations for NOX. (A) The 30-day rolling average NOX emission rate for each coal-fired unit, 

or each group of coal-fired units, shall be calculated for each calendar day, even if a unit is not in operation on that 

calendar day, in accordance with the following procedure: step one, for each unit, sum the hourly pounds of NOX

emitted during the current boiler-operating day (or most recent boiler-operating day if the unit is not in operation), 

and the preceding twenty-nine (29) boiler operating days, to calculate the total pounds of NOX emitted over the most 

recent thirty (30) boiler-operating day period for each coal-fired unit; step two, for each unit, sum the hourly heat 

input, in MMBtu, during the current boiler operating day (or most recent boiler operating day if the unit is not in 

operation), and the preceding twenty nine (29) boiler-operating days, to calculate the total heat input, in MMBtu, 

over the most recent thirty (30) boiler-operating day period for each coal-fired unit; step three, for each unit, 

divide the total pounds of NOX emitted by that unit from step 1 by the total heat input for that unit from step 

2 to calculate each unit’s 30-day rolling average NOx emission rate, in pounds of NOx per MMBtu, for each 

 

1

 The Federal Register version states SO4, not SO2. 
Proposed FIP Language 

Arizona Electric Power Cooperative, Inc. 

May 29, 2013 

Page 3 

calendar day; step four3, sum together the total pounds of NOX emitted from the group of coal-fired units over 

each unit’s most recent thirty (30) boiler-operating day period (the most recent 30 boiler operating day periods for 

different units may be different); step fivefour, sum together the total heat input from the group of coal-fired units 

over each unit’s most recent thirty (30) boiler-operating day period; and step sixfive, divide the total pounds of NOX

emitted from step four for each group of coal-fired units three by the total heat input from step fivefour for each 

group of coal-fired units, to calculate the 30-day rolling average NOX emission rate for each group of coal-fired 

units, in pounds of NOX per MMBtu, for each calendar day. Each 30-day rolling average NOX emission rate shall 

include all emissions and all heat input that occur during all periods within any boiler-operating day, including 

emissions from startup, shutdown, and malfunction. Compliance is demonstrated if either (I) each operating 

unit meets its individual NOX limit as calculated in step three or (II) if the group of operating coal-fired units 

meets its combined NOX limit as calculated in step six. 

(B) The 30-day rolling average NOX emission rate for Apache Unit 1 shall be calculated in accordance with the 

following procedure: step one, sum the total pounds of NOX emitted from the unit during the current boileroperating day and the previous twenty-nine (29) boiler-operating days; step two, sum the total heat input to the unit 

in MMBtu during the current boiler-operating day and the previous twenty-nine (29) boiler-operating days; and step 

three, divide the total number of pounds of NOX emitted during the thirty (30) boiler-operating days by the total heat 

input during the thirty (30) boiler operating days. A new 30-day rolling average NOX emission rate shall be 

calculated for each new boiler-operating day. Each 30-day rolling average NOX emission rate shall include all 

emissions and all heat input that occur during all periods within any boiler-operating day, including emissions from 

startup, shutdown, and malfunction. 

(C) If a valid NOX pounds per hour or heat input is not available for any hour for a unit, that heat input and NOX

pounds per hour shall not be used in the calculation of the 30-day rolling average. 

(iii) Compliance determinations for SO2. 

(A) [no changes] 

(B) [no changes] 

(C) [no changes] 

(D) [no changes] 

(E) Apache Unit 1 and Apache Unit 2 (after conversion to pipeline natural gas) shall demonstrate compliance 

with the SO2 limits through use of pipeline quality natural gas. 

 (6) Compliance determinations for particulate matter. Compliance with the particulate matter emission limitation 

for each coal-fired unit shall be determined from annual performance stack tests. Within sixty (60) days of the 

compliance deadline specified in paragraph (f)(4) of this section, and on at least an annual basis thereafter, the 

owner/operator of each unit shall conduct a stack test on each unit to measure PM10 using EPA Method 5, in 40 

CFR part 60, Appendix A, or Method 201A/202 in 40 CFR Part 51, Appendix M. Apache Unit 2, after conversion 

to pipeline natural gas, shall demonstrate compliance with its Phase 2 particulate matter emission limit within 

90 days of conversion to natural gas, and shall thereafter demonstrate compliance with its Phase 3 particulate 

matter emission limit within 60 days of the compliance deadline specified in paragraph (f)(4) of this section. 

Compliance for Apache Unit 2 shall be demonstrated using EPA Method 5, in 40 CFR part 60, Appendix A 

and Method 202, in 40 CFR Part 51, Appendix M, or EPA Method 201A/202 in 40 CFR Part 51, Appendix M. 

A test protocol shall be submitted to EPA and ADEQ a minimum of 30 days prior to the scheduled testing. The 

protocol shall identify which method(s) will be used to demonstrate compliance. Each test shall consist of three runs, 

with each run at least 120 minutes in duration and each run collecting a minimum sample of 60 dry standard cubic 

feet. Results shall be reported in lb/MMBtu using the calculation in 40 CFR Part 60 Appendix A Method 19. In 

addition to required annual stack tests, the owner/operator shall monitor particulate emissions for compliance with 

the emission limitations in accordance with theany applicable Compliance Assurance Monitoring (CAM) plan 

developed and approved in accordance with 40 CFR Part 64. The averaging time for any other demonstration of the 

PM10 compliance or exceedance shall be based on a 6-hour average. 
   

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May 10, 2013

MEMORANDUM

To:    Michelle Freeark, Arizona Electric Power Cooperative (AEPCO)

From:    Ralph Morris and Lynsey Parker

Subject:    CALPUFF Visibility Modeling of the AEPCO BART Scenarios

SUMMARY

Arizona Electric Power Cooperative (AEPCO) is proposing an alternative to EPA’s proposed Best

Available Control technology (BART) NOX emissions controls on their Apache ST2 and ST3 coal‐

fired electrical generating units (EGUs) located in southeast Arizona.  EPA’s BART Federal

Implementation Plan (FIP) requires AEPCO to install selective catalytic reduction (SCR) control

on both of Apache’s coal‐fired EGUs to achieve a NOX emissions rate of 0.07 lb/MMBtu.  The

AEPCO Alternative would convert one of the EGUs to natural gas (ST2) and install selective non‐

catalytic reduction (SNCR) control on the other unit (ST3).  AEPCO contracted with ENVIRON to

perform CALPUFF visibility modeling for the EPA SCR BART and AEPCO Alternative control

scenarios to estimate visibility impairment at Class I areas and demonstrate that the AEPCO

Alternative control scenario achieves greater visibility benefits than EPA’s SCR BART control

scenario and therefore is “Better than BART.”   

EPA is performing similar CALPUFF modeling using the same CALPUFF modeling database as

ENVIRON.  The ENVIRON CALPUFF modeling was initially performed using all of the same

assumptions as used by EPA, except in the AEPCO Alternative control scenarios the exit

temperature in the natural gas‐fired ST2 was higher; EPA used the same exit temperature in

ST2 for both the coal and natural gas scenarios and one would expect natural gas effluent to be

hotter than coal.  For the EPA Base and EPA SCR BART scenarios, the ENVIRON CALPUFF

modeling duplicated EPA’s CALPUFF modeling results.  For EPA’s AEPCO Alternative Control 9

and 9b scenarios, there were slight differences in the visibility modeling results due to the

different ST2 exit temperature assumptions.  However, these differences were small,

sometimes higher and sometimes lower, and on average across the Class I areas they were

within ±5%.

ENVIRON then performed CALPUFF modeling using two technical enhancements to the

CALPUFF modeling assumptions:

 Use of monthly varying background ammonia concentrations as used in the Desert Rock

EGU PSD and Navajo Generating Station BART CALPUFF modeling that was agreed to by

the Federal Land Managers (FLMs); and

 Use of a new PM emissions rate for natural gas‐fired boilers based on more recent and

accurate test measurements that is the same PM emissions factor EPA uses in their

National Emissions Inventory (NEI).
    

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The most accurate representation of the AEPCO Alternative available using CALPUFF V5.8

modeling system is using the monthly background ammonia and the updated natural gas PM

emissions factor.  Using this configuration and the BART visibility metrics that consist of the

average of the 98th percentile (8th highest in a year) visibility metrics across the three years of

modeling (2001‐2003) and the 98th percentile using the three years of modeling together (22nd

highest over 3 years), CALPUFF estimates that the AEPCO Alternative results in greater visibility

improvement than the EPA BART SCR case at all of the Class I areas.  The deciview visibility

impairment impacts for the AEPCO Alternative are from 9% to 51% lower than the EPA BART

SCR Case with the AEPCO Alternative producing visibility improvements averaged across the

Class I areas of 31% and 33% better than the EPA BART SCR Case.  Thus, the AEPCO Alternative

is demonstrated to be Better than BART.

BACKGROUND

The Regional Haze Rule (RHR) goal is to achieve natural visibility conditions at Class I areas by

2064.  One component of the RHR is the BART program that implements BART emission

controls on specific existing point sources for emissions that have been shown to cause or

contribute to visibility impairment at a Class I area.  Such visibility precursor emissions include

sulfur oxides (SOX or SO2), oxides of nitrogen (NOX) and particulate matter (PM).

AEPCO Apache EGU

AEPCO operates the Apache Generating Station that consists of two ~175 Megawatt (MWe)

EGUs (Steam Units 2 and 3 or ST2 and ST3).  ST2 and ST3 are dual‐fired boilers that are designed

and permitted to operate on either coal or natural gas.  The Arizona Department of

Environmental Quality (ADEQ) has determined that the two Apache EGUs are BART‐eligible1.  

The U.S. Environmental Protection Agency (EPA) has determined that BART for the NOX

emissions from the two Apache coal‐fired EGUs is selective catalytic reduction (SCR) that

achieves a 0.07 lb/MMBtu NOX emissions rate on a 30‐boiler operating day average over ST2

and ST3.  AEPCO has proposed an alternative to EPA’s proposed BART controls that would

convert Apache ST2 to natural gas and install selective non‐catalytic reduction (SNCR) on ST3.  

Thus, the differences in visibility impacts due to the EPA SCR BART and AEPCO Alternative

control scenarios will hinge on the differences in visibility impacts associated with the different

SO2, NOX and PM emissions of the two control scenario, with the EPA SCR BART scenario having

lower NOX and the AEPCO Alternative scenario having lower SO2 emissions.

Better than BART

The Regional Haze Rule (RHR) has provisions for using visibility modeling to demonstrate that

“an emission trading program or other alternative measures achieve[s] greater reasonable

progress than would be achieved through installation and operation of BART” [40 CFR

§51.308(e)(2)].  As stated in 40 CFR §51.308(e)(3), dispersion modeling should be used to

demonstrate that the alternative to BART achieves “greater reasonable progress” by examining

                                                      

1 http://www.azdeq.gov/environ/air/haze/
    

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the changes in visibility impacts for the Worst and Best 20% days at each Class I area.  A two

pronged test is used to demonstrate that the Alternative is Better than BART:

1. Visibility does not decline in any Class I area; and

2. There is an overall improvement in visibility, determined by comparing the average

difference between BART and the Alternative over all affected Class I areas.

Since the single‐source BART visibility metric using CALPUFF V5.8 is the 98th percentile daily

change in Haze index, commonly referred to as deciview (Δdv), rather than the RHR reasonable

progress metric based on the Haze index averaged over the Worst and Best 20% visibility days

at a Class I area, it is unclear how the 40 CFR §51.308(e)(3) “Better than BART” test should be

applied for a single source.  In fact, it is likely that a single source will not have any contributions

to visibility impairment at a Class I area for many of the Worst and Best 20% days so that using

the RHR reasonable progress visibility metric may not be appropriate.  Thus, we are using the

BART visibility metrics to evaluate whether the AEPCO Alternative achieves equivalent or

greater visibility improvement at Class I areas than the EPA SCR BART scenario.

CALPUFF VISIBILILITY MODELING OF AEPCO APACHE EGUs

Both EPA Region 9 and ENVIRON are performing CALPUFF visibility modeling to estimate the

visibility impacts due to the AEPCO Apache EGUs under the EPA SCR BART and AEPCO

Alternative emission scenarios.  EPA suggested, and AEPCO agreed, to use a common CALMET

meteorological database as input to CALPUFF that was developed by ENSR/AECOM (2009) as

part of the BART analysis for the Navajo Generation Station (NGS).  ENSR/AECOM updated the

original CALMET/CALPUFF BART modeling database2 developed by the Western Regional Air

Partnership (WRAP).  Although EPA adopted the ENSR/AECOM (2009) CALMET database as the

meteorological inputs for their AEPCO CALPUFF modeling, some other aspects of the

ENSR/AECOM (2009) CALMET/CALPUFF were not adopted by EPA (e.g., monthly varying

background ammonia concentrations).

ADEQ concluded that AEPCO Apache Units (ST1, ST2 and ST3) were subject to BART3

.  However,

EPA also included ST1 in its CALPUFF visibility modeling analysis even though its BART limits are

not an issue.  Since the goal of the CALPUFF visibility modeling is to compare the visibility

benefits of the EPA BART and the AEPCO Alternative emissions scenarios and the emissions for

ST1 are held constant in all of the emission scenarios, then the inclusion of emissions from ST1

does not adversely affect the analysis.  In fact, it may provide a more accurate representation of

visibility impacts of emissions from ST2 and ST3 since the effects of emissions from ST1 will be

accounted for in the aerosol equilibrium calculations and competition for ammonia among

sulfate and nitrate due to all of the emissions from the Apache facility.

                                                      

2 http://pah.cert.ucr.edu/aqm/308/bart.shtml

3 ST1 is a natural gas fired boiler.  EPA promulgated ADEQ’s proposed BART limits.  The level of the limit for ST1 is

not an issue.
    

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Preliminary CALPUFF Visibility Modeling

Both EPA Region 9 and ENVIRON performed preliminary CALPUFF visibility modeling for an EPA

Base, EPA SCR BART (NOX control at 0.07 lb/MMBtu for both ST2 and ST3) and EPA’s versions of

the AEPCO Alternative case that corresponds to EPA’s Control 9 and 9b scenarios (i.e.,

conversion of ST2 to natural gas and SNCR on ST3).  ENVIRON also performed an AEPCO

Alternative scenario with updated PM emissions factor that lowered the ST2 natural PM

emissions factor from 0.010 to 0.00042 lb/MMBtu based on newer and more accurate test

methods.  ENVIRON then performed second versions (v2) of the EPA Control 9 and 9b scenarios

that lowered slightly the ST2 PM emissions from 0.010 to 0.008 lb/MMBtu and the ST3 NOX

emissions from 0.230 to 0.225 lb/MMBtu.  Table 1 summarizes the Apache ST2 and ST3

emission rates for the seven CALPUFF simulations performed by ENVIRON.

Table 1.  Emission rates in lb/MMBtu for AEPCO stacks ST2 and ST3 for each of the CALPUFF

modeling scenarios.

Scenario Stack SO2 NOX PM

EPA Base OFA ST2 0.150 0.371 0.030

ST3 0.150 0.537 0.030

EPA SCR BART ST2 0.150 0.070 0.030

ST3 0.150 0.070 0.030

EPA AEPCO Alternative Control 9 PNGf ST2 0.00064 0.085 0.010a

ST3 0.150 0.230 0.030

EPA AEPCO Alternative Control 9b PNGt ST2 0.00064 0.085 0.010b

ST3 0.150 0.230 0.030

AEPCO Alternative with Updated PM Factor ST2 0.00064 0.085 0.00042

ST3 0.150 0.230 0.030

AEPCO Alternative Control 9v2 PNGf ST2 0.00064 0.085 0.008a

ST3 0.150 0.225 0.030

EPA AEPCO Alternative Control 9bv2 PNGt ST2 0.00064 0.085 0.008b

ST3 0.150 0.225 0.030

a. Control 9 and 9v2 assume the PM emissions rate is just the filterable PM and uses the NPS speciation

spreadsheet to calculate the condensable portion of the PM emissions

b. Control 9b and 9bv2 assume the PM emissions rate is the total PM emissions (filterable plus condensable)

Table 2a displays the stack parameters and Table 2b displays the emission rates for the

ENVIRON CALPUFF modeling runs.  Table 2b contains emissions for five versions of the AEPCO

Alternative.  The first three versions of the AEPCO Alternative emission scenarios differ on how

the PM emissions are treated from the natural gas‐fired ST2 EGU.  EPA Control 9 scenario

assumes that the pipeline natural gas (PNG) fired ST2 0.01 lb/MMBtu PM emissions rate is just

the filterable portion of the PM emissions (PNGf) and uses the NPS PM speciation spreadsheet

for natural gas turbines4 to estimate the condensable component of the PM resulting in a net

total PM emissions rate of 0.04 lb/MMBtu.  EPA Control 9b scenario assumes that the ST2 0.01

                                                      

4 http://www.nature.nps.gov/air/permits/ect/ectGasFiredCT.cfm?CFID=5318051&CFTOKEN=bb591d8a00830488‐

94B1977A‐F3F6‐E4E3‐099C6FEA63BA2179
    

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lb/MMBtu emissions rate is the total PM emissions rate (PNGt).  The third AEPCO Alternative

presented in Table 2b uses an updated PM emissions rate for natural gas‐fired boilers of

0.00042 lb/MMBtu for total PM emissions.  This updated PM emissions rate for natural gas

fired boilers is based on more recent and accurate test data and EPA believes it is more

accurate and representative of PM emissions from natural gas combustion so it is used in EPA’s

National Emissions Inventory (NEI).  Justification for the new PM emissions rate for natural gas

fired boilers is provided below with more details provided in Morris and England (2013).  As

discussed above, the final two AEPCO Alternative are version 2 (v2) of the EPA Control 9 and 9b

scenarios that slightly lowered the ST2 PM and ST3 NOX emission rates.

Although AEPCO used the same emissions as EPA for the AEPCO Alternative EPA Control 9 and

9b scenarios, the exit temperature for ST2 was updated to reflect the hotter effluent from

burning natural gas instead of coal.  When EPA modeled the AEPCO Alternative in Control 9 and

9b they kept the exit temperature of ST2 at the same 330.4 degrees Kelvin (K) level as used

when ST2 is burning coal.  ENVIRON’s CALPUFF modeling used a higher exit temperature of

394.3 K that reflects the higher temperatures when natural gas is used over coal.  This results in

slight differences in the CALPUFF estimated visibility impacts in EPA’s and ENVIRON’s modeling

of the AEPCO Alternative for EPA Control 9 and 9b scenarios.   

Table 2a.  Stack parameters used in the AEPCO CALPUFF modeling.

Scenario Source X‐Coord

(km)

Y‐Coord

(km)

Hs

(m)

Elev

(m)

Ds

(m)

Vs

(m/s)

Ts

(K)

EPA Base Case ST1  ‐1213.03  ‐793.196 50.088 1278.03 2.438 27.61 352.59

ST2  ‐1213.03  ‐793.196 120.09 1280.16 5.05 17.68 330.37

ST3  ‐1213.03  ‐793.196 120.09 1280.16 5.05 17.68 330.37

EPA SCR BART

Case (0.07

lb/MMBtu)

ST1  ‐1213.03  ‐793.196 50.088 1278.03 2.438 27.61 352.59

ST2  ‐1213.03  ‐793.196 120.09 1280.16 5.05 17.68 330.37

ST3  ‐1213.03  ‐793.196 120.09 1280.16 5.05 17.68 330.37

EPA AEPCO

Alternative

Control 9

ST1  ‐1213.03  ‐793.196 50.088 1278.03 2.438 27.61 352.59

ST2  ‐1213.03  ‐793.196 120.09 1280.16 5.05 17.68 394.261a

ST3  ‐1213.03  ‐793.196 120.09 1280.16 5.05 17.68 330.37

EPA AEPCO

Alternative

Control 9b

ST1  ‐1213.03  ‐793.196 50.088 1278.03 2.438 27.61 352.59

ST2  ‐1213.03  ‐793.196 120.09 1280.16 5.05 17.68 394.261a

ST3  ‐1213.03  ‐793.196 120.09 1280.16 5.05 17.68 330.37

AEPCO

Alternative with

Updated PM

ST1  ‐1213.03  ‐793.196 50.088 1278.03 2.438 27.61 352.59

ST2  ‐1213.03  ‐793.196 120.09 1280.16 5.05 17.68 394.261a

ST3  ‐1213.03  ‐793.196 120.09 1280.16 5.05 17.68 330.37

a. Note that EPA’s CALPUFF modeling used a 330.37 K for ST2 on natural gas.

   
    

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Attachment A contains the CALPUFF modeling results at Class I areas for the EPA Base that

assumes Low NOX Burners (LNB) and Over‐Fired Air (OFA), EPA SCR BART (0.07 lb/MMBtu) and

two AEPCO Alternative EPA Control 9 and 9b emission control scenarios performed by EPA5 and

by ENVIRON.  Figure 1 displays the location of the AEPCO Apache facility and the nearby Class I

areas.  The EPA and ENVIRON CALPUFF modeling results for the EPA Base and EPA SCR BART

cases are almost identical, with just one minor difference in 2003 at one (Saguaro) Class I area

(see Attachments A1 and A2).  However, there are slight differences in the visibility (deciview)

impacts at the Class I areas for the AEPCO Alternative Control 9 and 9b CALPUFF runs due to the

different ST2 exit temperature assumptions used in the EPA (330.4 K) and ENVIRON (394.3 K)

CALPUFF modeling.  Attachments A3 and A4 displays the 98th percentile visibility metrics at

                                                      

5 EPA CALPUFF modeling results were taken out of a spreadsheet “Apache_SCR_and_Alt_visx_130318.xlsx” and is

identified as “draft, sjb 2013‐03‐18”.

Table 2b.  Emissions used in the AEPCO BART control scenarios (g/s).

Scenario Source SO2 SO4 NOX PMF PMC EC OC PMtot

EPA Base Case ST1 0.045 0.266 3.921 0.354 0.142 0.028 0.047 0.837

ST2 41.439 2.589 161.001 3.548 4.606 0.136 0.647 11.526

ST3 41.173 2.571 134.814 3.524 4.575 0.135 0.643 11.448

Total 82.657 5.426 299.736 7.426 9.323 0.299 1.337 23.811

EPA SCR BART

(0.07 lb/MMBtu)

Case

ST1 0.045 0.266 3.921 0.354 0.142 0.028 0.047 0.837

ST2 41.439 2.589 30.59 3.548 4.606 0.136 0.647 11.526

ST3 41.173 2.571 21.57 3.524 4.575 0.135 0.643 11.448

Total 82.657 5.426 56.081 7.426 9.323 0.299 1.337 23.811

EPA AEPCO

Alternative Control

9 (PNGf)

ST1 0.045 0.266 3.921 0.354 0.142 0.028 0.047 0.837

ST2 0.177 0.088 36.869 0 0 2.763 8.199 11.05

ST3 41.173 2.571 70.912 3.524 4.575 0.135 0.643 11.448

Total 41.395 2.925 111.702 3.878 4.717 2.926 8.889 23.335

Diff w/ EPA SCR  ‐49.9%  ‐46.1% 99.2%  ‐47.8%  ‐49.4% 878.6% 564.8%  ‐2.0%

EPA AEPCO

Alternative Control

9b (PNGt)

ST1 0.045 0.266 3.921 0.354 0.142 0.028 0.047 0.837

ST2 0.177 0.088 36.869 0 0 0.691 1.984 2.763

ST3 41.173 2.571 70.912 3.524 4.575 0.135 0.643 11.448

Total 41.395 2.925 111.702 3.878 4.717 0.854 2.674 15.048

Diff w/ EPA SCR  ‐49.9%  ‐46.1% 99.2%  ‐47.8%  ‐49.4% 185.6% 100.0%  ‐36.8%

AEPCO Alternative

with Updated PM

emissions rate for

ST2 (0.00042

lb/MMBtu)

ST1 0.045 0.266 3.921 0.354 0.142 0.028 0.047 0.837

ST2 0.177 0.008 36.869 0.02216 0 0.01508 0.07096 0.1162

ST3 41.173 2.571 70.912 3.524 4.575 0.135 0.643 11.448

Total 41.395 2.845 111.702 3.90016 4.717 0.17808 0.76096 12.4012

Diff w/ EPA SCR  ‐49.9%  ‐47.6% 99.2%  ‐47.5%  ‐49.4%  ‐40.4%  ‐43.1%  ‐47.9%
    

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Class I areas in deciview and their differences for the EPA and ENVIRON CALPUFF modeling of

Control 9 and 9b, respectively.  The percent differences in the deciview impacts between the

EPA and ENVIRON CALPUFF modeling for Control 9 and 9b are shown in, respectively, Tables 3a

and 3b.  The effects of the different ST2 exit temperature in the EPA and ENVIRON CALPUFF

modeling of Control 9 and 9b results in deciview increases by as much as 13% and decreases by

as much as ‐8%, with the average change across all Class I areas results in differences of less

than ±5%.

Figure 1.  Location of the AEPCO Apache EGUs (red star) and nearby Class I areas.
    

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Table 3a.  Percent differences in visibility impacts at Class I areas between EPA’s and AEPCO’s

CALPUFF modeling for AEPCO Alternative EPA Control 9 (PNGf) [see Attachment A3 for more

details].

Percent Difference in EPA and AEPCO CALPUFF Results (AEPCO – EPA)

AEPCO Alt Cntl 9 (PNGf) 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM  ‐3.5%  ‐10.3%  ‐7.1%  ‐7.1%  ‐7.1%

Chiricahua Wild.  ‐7.7%  ‐5.8%  ‐7.2%  ‐6.9%  ‐6.8%

Galiuro Wild. 6.7%  ‐0.7%  ‐7.4%  ‐0.9%  ‐4.3%

Gila Wild. 12.0% 3.4% 11.8% 8.5%  ‐3.1%

Mazatzal Wild.  ‐2.2%  ‐0.6% 2.7%  ‐0.2% 0.0%

Mount Baldy Wild.  ‐1.5%  ‐1.4% 10.0% 2.0% 0.0%

Saguaro NP 0.2% 0.0%  ‐4.5%  ‐1.4%  ‐2.0%

Sierra Ancha Wild. 4.6%  ‐6.6%  ‐4.6%  ‐2.2% 0.0%

Superstition Wild.  ‐8.0% 7.5%  ‐2.9%  ‐0.9%  ‐1.6%

Average  ‐1.8%  ‐3.9%  ‐5.5%  ‐3.7%  ‐4.9%

Table 3b.  Percent differences in visibility impacts at Class I areas between EPA’s and AEPCO’s

CALPUFF modeling for AEPCO Alternative EPA Control 9b (PNGt) [see Attachment A4 for more

details].

Percent Difference in EPA and AEPCO CALPUFF Results (AEPCO – EPA)

AEPCO Alt Cntl 9b (PNGt) 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM  ‐1.5%  ‐11.6%  ‐3.3%  ‐5.3%  ‐2.9%

Chiricahua Wild.  ‐1.7%  ‐3.0%  ‐4.0%  ‐2.9%  ‐4.0%

Galiuro Wild.  ‐0.8%  ‐6.5%  ‐6.6%  ‐4.9%  ‐3.4%

Gila Wild. 13.4% 5.4%  ‐1.7% 6.2% 0.3%

Mazatzal Wild. 0.0% 0.0%  ‐1.7%  ‐0.5%  ‐3.9%

Mount Baldy Wild. 2.5%  ‐3.3% 5.8% 1.5% 2.5%

Saguaro NP  ‐1.8%  ‐2.4%  ‐2.3%  ‐2.2%  ‐3.2%

Sierra Ancha Wild. 3.7% 1.4%  ‐3.3% 0.8% 0.0%

Superstition Wild.  ‐1.0% 5.9%  ‐8.3%  ‐0.1%  ‐1.0%

Average  ‐0.7%  ‐4.5%  ‐3.9%  ‐3.0%  ‐3.0%
    

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Refined CALPUFF Visibility Modeling

More refined and accurate CALPUFF V5.8 modeling was conducted by making two sequential

updates to the CALPUFF modeling approach used by EPA:

 Use of monthly varying background ammonia concentrations, as used in the

ENSR/AECOM (2009) NGS BART modeling; and

 Use of updated natural gas combustion PM emissions factor as used by EPA in the

National Emissions Inventory (NEI).

The rationale and justification for these two updates are given below, with more details given in

ENSR/AECOM (2009) and Morris and England (2013).

Background Ammonia Concentration Update

The EPA regulatory version of CALPUFF (V5.8) has a known bias toward overestimating the

impacts of nitrate and resultant visibility impairment.  For example, Morris, Tana and Yarwood

(2003) found that the CALPUFF MESOPUFF‐II chemical transformation algorithm in CALPUFF

V5.8 overestimates nitrate formation during the day by a factor of 2 to 3 on average when

compared to a full‐science chemistry mechanism.  Morris and co‐workers (2006) evaluated the

CMAQ‐LISBON model that uses the CALPUFF MESOPUFF‐II chemical transformation module

against ambient air quality measurements and found that it overestimated the observed nitrate

concentrations by a factor of 2.8 on average; the standard CMAQ model with the full chemistry

predicted the average of the observed nitrate values to within 10%.  Scire, Wu and Strimaitis

(2013) evaluated CALPUFF over southwestern Wyoming and found that CALPUFF V5.8 with the

MESOPUFF‐II chemistry and 1 ppb background ammonia over‐predicted the observed nitrate

concentrations by a factor of 4 to 6.  They noted that “Substantially improved results were

obtained with the use of seasonally varying observed ammonia concentrations that ranged

from 0.43 ppb in the winter to 1.1 ppb in the summer.”   

Realizing that the use of monthly average background ammonia is more realistic and can partly

mitigate the large CALPUFF nitrate overestimation bias, ENSR/AECOM developed monthly

average background ammonia concentrations for their CALPUFF modeling of the proposed

Desert Rock Power Plant that they also used in their NGS BART CALPUFF modeling.  These

monthly average background ammonia values were reviewed and accepted by the Federal Land

Managers (FLMs).  Figure 2 below reproduces the Section from the ENSR/AECOM NGS BART

modeling report that explains and justifies the use of monthly background ammonia values.  

Consistent with Scire, Wu and Strimaitis (2006), ENSR/AECOM used lower monthly background

ammonia values in the winter (0.2 ppb) than summer (1.0 ppb).  This makes sense since a lot of

the ammonia emissions occur due to volatilization of livestock waste that is expected to be

greater in the warmer than cooler months.
    

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Figure 2.  Excerpt from ENSR/AECOM (2009) NGS BART CALPUFF modeling report justifying

the use of monthly background ammonia values for CALPUFF V5.8 modeling in Arizona.

Updated Natural Gas Combustion PM Emissions Factor

EPA’s modeling of PM emissions from the natural gas‐fired ST2 in the AEPCO Alternative

scenario assumed a 0.01 lb/MMBtu emissions rate.  This is a conservative estimate that is

consistent with EPA’s AP‐42 emissions factor report that assumes a 0.0075 lb/MMBtu PM

emissions rate for natural gas‐fired boilers that is 0.0019 lb/MMBtu filterable and 0.0056

lb/MMBtu condensable PM emissions6.  However, the sampling method used to develop the

AP‐42 PM emissions rate for natural gas boilers (typically Method 201a for filterable and

Method 202 for condensable) is known to have positive bias artifact that overstates actual PM

emissions.  More recent test data using more accurate measurement methods (e.g., dilution

chambers) have measured much lower PM emissions rates from natural gas combustion.  EPA

has adopted these lower PM emission rates for natural gas combustion and uses them in their

                                                      

6 http://www.epa.gov/ttnchie1/ap42/ch01/final/c01s04.pdf
    

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National Emissions Inventory (NEI7).  The updated natural gas‐fired boiler PM emissions factor

is 0.00042 lb/MMBtu, which is 23 to 95 times lower than the PM emissions assumed by EPA for

ST2 in their modeling of the AEPCO Alternative assuming that the 0.01 lb/MMBtu PM emission

factor represents the total (Scenario 9b) or just the filterable (Scenario 9) portion of the PM

emissions.  Details on the derivation and justification of the updated and more accurate PM

emissions factor for natural gas combustion in boilers is given in Morris and England (2013).

Refined CALPUFF Modeling Results using Monthly Background Ammonia

Attachment B displays the CALPUFF visibility modeling results at Class I areas for the EPA Base,

EPA SCR BART and the AEPCO Alternative Control 9 and 9b emission scenarios post‐processed

using the POSTUTIL processor with the monthly background ammonia concentrations (see

Figure 2).  Shown in these tables are the BART visibility metrics that include the 98th percentile

(8th highest) daily visibility impacts due to the Apache ST1, ST2 and ST3 emissions for each of

the three modeling years (2001‐2003), the average of the 98th percentile across the three

modeling years and the 98th percentile across all three years combined (i.e., the 22nd highest

daily visibility impacts in the three year period).  As discussed previously, the RHR has

procedures for estimating whether an alternative control scenario is “Better than BART” using

the RHR reasonable progress visibility metrics that are based on the Worst and Best 20%

visibility days, but that approach appears to be more appropriate when looking at BART across

all or many BART‐eligible sources.  When looking at a single source, the source may not even be

contributing to visibility impairment at a Class I area during many of the Worst and Best 20%

days.  Thus, we are evaluating the EPA BART and AEPCO Alternative visibility impacts using the

BART visibility metrics (i.e., 98th percentile daily visibility impacts in deciviews).

Tables 4a and 4b displays the percent differences in the CALPUFF BART visibility metrics at each

Class I area between the EPA SCR BART and the, respectively, AEPCO Alternative EPA Control 9

and 9b emission scenarios post‐processed using monthly background ammonia (AEPCO

Alternative – SCR/BART).  For the EPA Control 9 scenario that assumes the 0.01 lb/MMBtu PM

emissions scenario for ST2 operating using pipeline natural gas is just the filterable portion

(PNGf), the AEPCO Alternative (Control 9 PNGf) scenario estimates more visibility impairment

than SCR/BART scenario most of the time with an average increase of approximately 35‐37%.  

However, the AEPCO Alternative Control 9b that assumes the ST2 0.01 lb/MMBtu PM emissions

rate is the total PM (PNGt) estimates more visibility improvements than SCR/BART with the

AEPCO Alternative average visibility improvement over SCR/BART being 10‐12%.   

   

                                                      

7 See “PM EFs for Natural Gas Combustion at 2011 NEI website:  

http://www.epa.gov/ttnchie1/net/2011inventory.html
    

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Table 4a.  Percent difference in 98th percentile deciview impacts at Class I areas between EPA

BART SCR and AEPCO Alternative EPA Control 9 (PNGf) emissions scenario using AEPCO

CALPUFF results processed with monthly average background ammonia concentrations.

Percent Difference EPA BART SCR and AEPCO Alternative Cntl 9 (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 34.3% 21.8% 30.8% 28.8% 28.9%

Chiricahua Wild. 22.4% 32.5% 20.9% 25.2% 23.8%

Galiuro Wild. 26.0% 23.4% 31.7% 27.2% 20.3%

Gila Wild. 29.8% 41.7% 28.6% 34.0% 31.1%

Mazatzal Wild.  ‐8.0% 2.8%  ‐1.8%  ‐2.5% 0.7%

Mount Baldy Wild. 22.7% 2.3% 1.1% 8.2% 26.3%

Saguaro NP 35.8% 30.8% 33.4% 33.3% 31.6%

Sierra Ancha Wild. 10.7% 9.3%  ‐8.0% 3.9% 2.2%

Superstition Wild. 12.6% 10.0% 3.6% 8.7% 8.3%

Average 27.3% 25.6% 26.1% 26.4% 24.8%

Table 4b.  Percent difference in 98th percentile deciview impacts at Class I areas between EPA

BART SCR and AEPCO Alternative EPA Control 9b (PNGt) emissions scenario using AEPCO

CALPUFF results processed with monthly average background ammonia concentrations.

Percent Difference EPA BART SCR and AEPCO Alternative Cntl 9b (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM  ‐8.5%  ‐14.9%  ‐3.7%  ‐9.0%  ‐8.0%

Chiricahua Wild.  ‐9.0%  ‐6.3%  ‐9.6%  ‐8.2%  ‐10.2%

Galiuro Wild.  ‐15.0%  ‐15.1%  ‐12.8%  ‐14.2%  ‐14.2%

Gila Wild. 3.9%  ‐0.5%  ‐12.0%  ‐2.7%  ‐3.6%

Mazatzal Wild.  ‐28.3%  ‐26.2%  ‐25.0%  ‐26.6%  ‐23.4%

Mount Baldy Wild. 6.7%  ‐26.7%  ‐13.3%  ‐11.6%  ‐2.4%

Saguaro NP  ‐10.6%  ‐10.1%  ‐8.0%  ‐9.5%  ‐7.9%

Sierra Ancha Wild.  ‐20.7%  ‐23.6%  ‐37.8%  ‐26.9%  ‐25.5%

Superstition Wild.  ‐14.1%  ‐17.6%  ‐27.1%  ‐19.4%  ‐20.0%

Average  ‐10.0%  ‐11.8%  ‐9.6%  ‐10.5%  ‐10.2%

   
    

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Refined CALPUFF Modeling using Updated PM Emissions Factor for Natural Gas‐Fired Boilers

CALPUFF modeling was conducted for the AEPCO Alternative using the updated PM emissions

rate for the ST2 natural gas‐fired boiler (0.00042 lb/MMBtu).  Attachment C compares the

CALPUFF visibility results at Class I areas for the EPA SCR BART and the AEPCO Alternative with

updated PM emissions factor scenarios and their differences.  The percent differences in the

visibility results for the SCR/BART and AEPCO Alternative with updated PM emissions factor for

ST2 are shown in Table 5.  Using the average of the 98th percentile visibility metric across the

three years of modeling, the AEPCO Alternative has from 18.7% (Mount Baldy) to 51.0% (Sierra

Ancha) more visibility benefits than the EPA SCR BART case.  On average across the Class I areas

the AEPCO Alternative has 32.7% more visibility benefits than the SCR/BART case.

Similar results are seen using the 98th percentile across the three years of modeling (i.e., 22nd

highest in 2001‐2003) with the AEPCO Alternative having from 9.4% (Mount Baldy) to 50.0%

(Sierra Ancha) more visibility benefits than SCR/BART with an average of 31.0% more visibility

benefits than SCR/BART.

Table 5.  Percent difference in 98th percentile deciview impacts at Class I areas between EPA

BART SCR and AEPCO Alternative with Updated PM Emissions Factor (0.00042 lb/MMBtu) for

ST2 emissions scenario using AEPCO CALPUFF results processed with monthly average

background ammonia concentrations.

Percent Difference EPA BART SCR and AEPCO Alternative w/ PM (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM  ‐26.3%  ‐33.8%  ‐18.2%  ‐25.8%  ‐24.2%

Chiricahua Wild.  ‐26.8%  ‐20.6%  ‐25.5%  ‐24.3%  ‐28.3%

Galiuro Wild.  ‐39.9%  ‐40.3%  ‐29.9%  ‐36.2%  ‐39.4%

Gila Wild.  ‐15.7%  ‐16.7%  ‐28.6%  ‐19.7%  ‐18.4%

Mazatzal Wild.  ‐43.2%  ‐47.2%  ‐43.4%  ‐44.7%  ‐39.4%

Mount Baldy Wild. 1.9%  ‐40.6%  ‐19.5%  ‐18.7%  ‐9.4%

Saguaro NP  ‐37.2%  ‐30.7%  ‐27.1%  ‐31.3%  ‐29.6%

Sierra Ancha Wild.  ‐41.5%  ‐50.0%  ‐62.2%  ‐51.0%  ‐50.0%

Superstition Wild.  ‐36.1%  ‐36.4%  ‐56.0%  ‐42.3%  ‐40.1%

Average  ‐29.4%  ‐35.1%  ‐34.5%  ‐32.7%  ‐31.0%

   
    

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Version 2 of AEPCO Alternative Control 9 and 9b

The AEPCO Alternative Control 9v2 and 9bv2 used slightly lower PM emissions for ST2 and NOX

emissions for ST3 than the EPA Control 9 and 9b scenarios.  The Control 9v2 and 9bv2 CALPUFF

modeling results are given in Attachment D and Tables 6a and 6b.  AEPCO Alternative Control

9v2 has more visibility benefits than SCR BART at 2‐3 Class I areas and less benefits 6‐7 Class I

areas; on average Control 9v2 has13‐15% more visibility degradation than SCR BART (Table 6a).  

However, the AEPCO Alternative Control 9b has more visibility benefits than SCR BART at all of

the Class I areas and on average has 14% more visibility benefits than SCR BART (Table 6b).

Table 6a.  Percent difference in 98th percentile deciview impacts at Class I areas between EPA

BART SCR and AEPCO Alternative Control 9v2 (PNGf) emissions scenario using AEPCO

CALPUFF results processed with monthly average background ammonia concentrations.

Percent Difference EPA BART SCR and AEPCO Alternative Cntl 9v2 (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 21.1% 10.6% 21.0% 17.4% 15.7%

Chiricahua Wild. 12.3% 21.9% 11.9% 15.3% 13.8%

Galiuro Wild. 14.4% 12.1% 18.3% 15.1% 7.7%

Gila Wild. 18.8% 32.4% 15.0% 22.8% 22.3%

Mazatzal Wild.  ‐14.0%  ‐5.5%  ‐8.2%  ‐9.4%  ‐5.1%

Mount Baldy Wild. 19.6%  ‐5.3%  ‐6.7% 1.9% 19.2%

Saguaro NP 23.0% 18.8% 20.5% 20.7% 20.1%

Sierra Ancha Wild. 2.5%  ‐0.7%  ‐18.8%  ‐5.8%  ‐5.1%

Superstition Wild. 4.7% 1.5%  ‐3.6% 0.8%  ‐1.4%

Average 16.0% 14.8% 15.4% 15.4% 13.5%

Table 6b.  Percent difference in 98th percentile deciview impacts at Class I areas between EPA

BART SCR and AEPCO Alternative Control 9bv2 (PNGt) emissions scenario using AEPCO

CALPUFF results processed with monthly average background ammonia concentrations.

Percent Difference EPA BART SCR and AEPCO Alternative Cntl 9bv2 (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM  ‐11.7%  ‐18.8%  ‐6.4%  ‐12.2%  ‐11.2%

Chiricahua Wild.  ‐12.3%  ‐8.8%  ‐12.7%  ‐11.2%  ‐13.5%

Galiuro Wild.  ‐19.3%  ‐19.3%  ‐15.9%  ‐18.0%  ‐19.7%

Gila Wild. 0.0%  ‐2.7%  ‐14.9%  ‐5.5%  ‐5.9%

Mazatzal Wild.  ‐31.8%  ‐30.7%  ‐28.7%  ‐30.5%  ‐26.4%

Mount Baldy Wild. 5.2%  ‐29.6%  ‐15.7%  ‐13.6%  ‐4.2%

Saguaro NP  ‐14.8%  ‐13.7%  ‐11.1%  ‐13.1%  ‐11.1%

Sierra Ancha Wild.  ‐24.8%  ‐28.7%  ‐44.6%  ‐32.0%  ‐29.0%

Superstition Wild.  ‐17.9%  ‐21.6%  ‐31.7%  ‐23.6%  ‐24.5%

Average  ‐13.7%  ‐15.2%  ‐12.6%  ‐13.8%  ‐13.8%
    

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Use of Constant 1 ppb Background Ammonia

Attachment E compares the CALPUFF visibility modeling results for the EPA SCR BART scenario

with the five AEPCO Alternative emission scenarios only post‐processed using a constant 1 ppb

background ammonia concentration.  The difference in the EPA SCR BART and the five AEPCO

Alternative emission scenarios expressed as a percentage is given in Tables 7a‐e below.  When

assuming that the 0.01 or 0.008 lb/MMBtu PM emission rate is just the filterable portion of the

PM and using the NPS natural gas PM speciation profile (Control 9 and 9v2) the AEPCO

Alternative has on average across the Class I areas approximately 30% (Control 9) and 20%

(Control 9v2) more visibility impairment than EPA SCR BART scenario using a 1 ppb background

ammonia concentration (Tables 7a and 7d).  However, even when using a 1 ppb background

ammonia when the 0.01/0.008 lb/MMBtu PM emissions rate is assumed to be the total PM

then the AEPCO Alternative has 2‐3% (Control 9b; Table 7b) and 4‐5% (Control 9bv2; Table 7e)

more visibility benefits than EPA SCR BART.  The AEPCO Alternative with updated natural gas

PM emissions factor provides on average 14‐15% more visibility benefits than EPA SCR BART

scenario using 1 ppb background ammonia concentration (Table 7c).

Table 7a.  Percent difference in 98th percentile deciview impacts at Class I areas between EPA

BART SCR and AEPCO Alternative Control 9 (PNGf) emissions scenario using AEPCO CALPUFF

results processed with constant 1 ppb background ammonia concentration.

Percent Difference EPA BART SCR and AEPCO Alternative Cntl 9 (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 38.2% 22.6% 32.0% 30.5% 32.0%

Chiricahua Wild. 31.7% 28.4% 40.4% 33.4% 29.1%

Galiuro Wild. 47.7% 35.1% 19.6% 32.2% 29.6%

Gila Wild. 66.4% 47.7% 42.0% 51.3% 40.5%

Mazatzal Wild. 11.4% 5.2% 14.6% 10.0% 9.5%

Mount Baldy Wild. 30.4% 11.4% 30.4% 22.7% 25.4%

Saguaro NP 40.4% 40.1% 26.9% 35.6% 31.0%

Sierra Ancha Wild. 26.3% 5.2% 2.0% 10.4% 5.1%

Superstition Wild. 21.8% 35.5% 8.9% 22.0% 22.5%

Average 37.3% 29.8% 29.0% 31.9% 29.5%
    

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Table 7b.  Percent difference in 98th percentile deciview impacts at Class I areas between EPA

BART SCR and AEPCO Alternative Control 9b (PNGf) emissions scenario using AEPCO CALPUFF

results processed with constant 1 ppb background ammonia concentration.

Percent Difference EPA BART SCR and AEPCO Alternative Cntl 9b (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 6.0%  ‐13.8% 2.2%  ‐2.0%  ‐1.4%

Chiricahua Wild.  ‐2.5%  ‐0.1% 5.0% 0.8%  ‐2.6%

Galiuro Wild. 1.0%  ‐10.3%  ‐2.0%  ‐3.8%  ‐1.5%

Gila Wild. 19.1% 6.3%  ‐1.2% 8.2% 7.1%

Mazatzal Wild.  ‐14.0%  ‐20.4%  ‐10.1%  ‐15.1%  ‐12.4%

Mount Baldy Wild. 12.0%  ‐6.1% 9.2% 4.5% 2.8%

Saguaro NP  ‐2.9% 4.9%  ‐7.7%  ‐1.7%  ‐5.5%

Sierra Ancha Wild.  ‐0.6%  ‐17.5%  ‐19.1%  ‐12.2%  ‐16.3%

Superstition Wild.  ‐6.2% 7.5%  ‐28.7%  ‐8.0%  ‐5.7%

Average 0.9%  ‐4.4%  ‐1.3%  ‐1.7%  ‐2.7%

Table 7c.  Percent difference in 98th percentile deciview impacts at Class I areas between EPA

BART SCR and AEPCO Alternative with updated PM emissions factor emissions scenario using

AEPCO CALPUFF results processed with constant 1 ppb background ammonia concentration.

Percent Difference EPA BART SCR and AEPCO Alternative PM Update (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM  ‐3.2%  ‐29.1%  ‐6.4%  ‐12.4%  ‐10.6%

Chiricahua Wild.  ‐16.6%  ‐12.0%  ‐3.9%  ‐10.8%  ‐15.4%

Galiuro Wild.  ‐17.9%  ‐28.5%  ‐11.6%  ‐18.3%  ‐15.8%

Gila Wild. 19.1% 0.3%  ‐14.1% 2.8%  ‐4.6%

Mazatzal Wild.  ‐32.6%  ‐38.5%  ‐23.5%  ‐32.0%  ‐22.8%

Mount Baldy Wild. 11.0%  ‐12.2% 4.9% 0.9% 0.8%

Saguaro NP  ‐11.0%  ‐1.0%  ‐23.9%  ‐11.4%  ‐20.4%

Sierra Ancha Wild.  ‐19.1%  ‐31.7%  ‐30.0%  ‐26.9%  ‐29.8%

Superstition Wild.  ‐22.9% 1.5%  ‐51.9%  ‐20.5%  ‐15.7%

Average  ‐10.4%  ‐16.8%  ‐17.8%  ‐14.3%  ‐14.9%
    

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Table 7d.  Percent difference in 98th percentile deciview impacts at Class I areas between EPA

BART SCR and AEPCO Alternative Control 9v2 (PNGf) emissions scenario using AEPCO

CALPUFF results processed with constant 1 ppb background ammonia concentration.

Percent Difference EPA BART SCR and AEPCO Alternative Cntl 9v2 (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 29.5% 12.0% 23.4% 21.1% 21.3%

Chiricahua Wild. 22.6% 19.8% 31.1% 24.4% 19.8%

Galiuro Wild. 36.8% 21.9% 11.8% 21.8% 20.5%

Gila Wild. 48.7% 34.0% 29.8% 36.9% 31.2%

Mazatzal Wild. 6.6%  ‐2.9% 6.2% 3.0% 2.0%

Mount Baldy Wild. 24.5% 3.0% 23.9% 15.6% 18.4%

Saguaro NP 28.3% 32.0% 14.2% 24.6% 23.0%

Sierra Ancha Wild. 18.2%  ‐1.7%  ‐3.4% 3.7%  ‐3.2%

Superstition Wild. 15.1% 28.0%  ‐2.2% 13.5% 15.9%

Average 27.5% 19.9% 19.5% 22.1% 20.3%

Table 7e.  Percent difference in 98th percentile deciview impacts at Class I areas between EPA

BART SCR and AEPCO Alternative Control 9bv2 (PNGf) emissions scenario using AEPCO

CALPUFF results processed with constant 1 ppb background ammonia concentration.

Percent Difference EPA BART SCR and AEPCO Alternative Cntl 9bv2 (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 4.7%  ‐16.9% 0.4%  ‐4.0%  ‐3.6%

Chiricahua Wild.  ‐5.2%  ‐2.4% 3.2%  ‐1.5%  ‐5.4%

Galiuro Wild.  ‐2.4%  ‐13.9%  ‐3.9%  ‐6.6%  ‐4.8%

Gila Wild. 19.6% 4.9%  ‐3.9% 7.0% 4.4%

Mazatzal Wild.  ‐17.4%  ‐24.6%  ‐13.0%  ‐18.6%  ‐15.3%

Mount Baldy Wild. 11.0%  ‐8.1% 7.0% 2.9% 1.5%

Saguaro NP  ‐5.7% 3.4%  ‐11.4%  ‐4.2%  ‐8.1%

Sierra Ancha Wild.  ‐3.1%  ‐20.5%  ‐21.5%  ‐14.9%  ‐19.6%

Superstition Wild.  ‐9.3% 5.9%  ‐33.2%  ‐10.6%  ‐8.8%

Average  ‐1.5%  ‐6.8%  ‐3.6%  ‐4.0%  ‐5.4%
    

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DISCUSSION OF RESULTS

Much of the discussion and CALPUFF modeling sensitivity analysis given above relates to PM

emissions from the natural gas‐fired ST2 in the AEPCO Alternative.  This was because of the

uncertainty and bias in these PM emissions estimates, not because of their importance in

impairing visibility in the southwest.  In fact, the WRAP Subject‐to‐BART CALPUFF visibility

modeling of the AEPCO Apache EGU found that the maximum visibility impairment (98th

percentile averaged across 2001‐2003) at any Class I area (Chiricahua NM 45 km away) due to

Apache’s SO2, NOX and PM emissions were, respectively, 1.24, 1.12 and 0.02 deciviews.  That is,

the Apache PM emissions represent less than 2% of the visibility impairment of its SO2 or NOX

emissions.  Thus, the real question in evaluating whether the AEPCO Alternative has more

visibility benefits than the EPA SCR BART scenario revolves around the trade‐offs between the

visibility impairment of the higher NOX emissions in the AEPCO Alternative versus the higher

SO2 emissions in the EPA SCR BART emissions scenarios.

Table 8 lists the total SO2 and NOX emissions from Apache ST1, ST2 and ST3 for the EPA SCR

BART and Apache Alternative emission scenarios and compares them with the total SO2 and

NOX emissions for Arizona from the WRAP Plan02d (representing 2000‐2004 baseline) and the

Prp18b (2018) emissions scenarios that were downloaded from the WRAP TSS website8

.  For

both Apache control scenarios, the Apache SO2 and NOX emissions represents less than 5% of

the total 2018 emissions in Arizona (and even less for Plan02d).

Table 8.  Comparison of the Apache EPA SCR BART and AEPCO Alternative SO2 and NOX

emissions with total emissions in Arizona (tons per year).

Scenario SO2 (tpy) NOX (tpy)

EPA SCR BART 2,873.3 1,949.5

AEPCO Alternative 1,439.0 3,883.0

Arizona (Plan02d) 104,327.1 344,100.8

Arizona (Prp18b) 70,854.9 101,972.9

Figure 3 displays the daily visibility impairment at the Chiricahua Class I area for the three

modeling years (2001‐2003).  The results for other Class I areas in the region are similar.  The

visibility impairment due to SO2 emissions (yellow) is always much greater than that due to NOX

emissions (red).  There is evidence of days with high visibility impairment due to dust (large soil

and coarse mass identified by brown and grey colors) and fires (large organic and elemental

carbon identified by green and black colors).  The annual average visibility extinction at

Chiricahua Class I area for the 2000‐2011 12‐year period is given in Figure 4.  Visibility extinction

due to SO2 emissions (ammonium sulfate in yellow) is approximately a third of the total

extinction ranging from a low of 26% in 2011, which appears to be a higher fire influenced year,

to a high of 42% in 2005, with a 12‐year average contribution of 35%.  The contribution of NOX

emissions (ammonium nitrate in red) to total visibility extinction, on the other hand, is much

smaller ranging from 4.9% (2008) to 7.2% (2004) of the total extinction with an average of 5.7%.  

                                                      

8 http://vista.cira.colostate.edu/TSS/Results/Emissions.aspx
    

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In fact, despite NOX emissions being 3.3 (Plan02d) to 1.4 (Prp18b) times higher than SO2

emissions in Arizona (Table 8), visibility impairment due to SO2 emissions is from 4.6 (2002) to

7.8 (2008) times greater than visibility impairment due to NOX emissions at Chiricahua.  This is

due in part because SO2 emissions are converted to particulate sulfate that impairs visibility,

whereas NOX emissions are converted to nitric acid that does not impair visibility, which in turn

can be converted to particulate nitrate assuming ammonia is present and the right

meteorological conditions occur.  And the hot dry and low ammonia conditions of the desert

southwest favor more of the converted NOX emissions staying as nitric acid rather than

converting to particulate nitrate.

Given that SO2 emissions are more important than NOX emissions in producing visibility

impairment in the southwest U.S., then one would expect that the AEPCO Alternative would

result in more visibility improvements than the SCR BART scenario.  Thus, the conclusion that

the AEPCO Alternative is “Better than BART” is consistent with our understanding of visibility

impairment at Class I areas in the southwestern U.S.  

   
    

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Figure 3.  Daily visibility extinction during 2001 (top), 2002 (middle) and 2003 (bottom) at the

Chiricahua Class I area.
    

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Figure 4.  Measured annual visibility extinction at Chiricahua Class I area for 2000‐2011.

   
    

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REFERENCES

ENSR/AECOM.  2009.  Revised BART Analysis for the Navajo Generating Station Units 1‐3.  ENSR

Corporation, Document No. 05830‐012‐300.  (http://en3pro.com/wp‐

content/uploads/2011/02/BART‐Analysis‐by‐ENSR‐JAN‐09.pdf).

Morris, R., C. Tana and Greg Yarwood.  2003.  Evaluation of the Sulfate and Nitrate Formation

Mechanisms in the CALPUFF Modeling System.  Presented at Guideline on Air Quality

Models – An A&WMA Specialty Conference.  Mystic, Connecticut.  October 22‐24, 2003.

Morris, R., S. Lau, B. Koo, A. Hoats and Greg Yarwood.  2006.  Further Evaluation of the

Chemistry Algorithms used in the CALPUFF Modeling System.  Presented at Guideline on

Air Quality Models:  Application and FLAG Developments – An A&WNA Specialty

Conference.  Denver, Colorado.  April 26‐28, 2006.

Scire, J.S., Z.‐X. Wu and D.G. Strimaitis.  2006.  Implementation and Evaluation of ISORROPIA in

CALPUFF.  Presented at A&WMA Conference Guideline on Air Quality Models:  The Path

Forward, Raleigh, North Carolina.  March 19‐21, 2013.

USEPA.  2011.  Regional Haze Rule (RHR).  40 CFR 51.308.  July 1, 2011 edition.  

(http://www.gpo.gov/fdsys/pkg/CFR‐2011‐title40‐vol2/pdf/CFR‐2011‐title40‐vol2‐

sec51‐308.pdf).

USEPA.  2005.  Demonstration that CAIR Satisfies the “Better‐than‐BART” Test As Proposed in

the Guidelines for Making BART Determinations.  EPA Docket Number: OAR‐2003‐0053‐

YYYY.  March.  (http://www.epa.gov/cair/pdfs/finaltech04.pdf).

USEPA.  2011.  Regional Haze: Revisions to Provisions Governing Alternatives to Source‐Specific

Best Available Retrofit Technology (BART) Determinations, Limited SIP Disapprovals, and

Federal Implementation Plans.  40 CFR Parts 51 and 52.  EPA‐HQ‐OAR‐2011‐0729; FRL‐

9614‐7.  Federal Register / Vol. 76, No. 251 / Friday, December 20, 2011 / Proposed

Rules.  (http://www.gpo.gov/fdsys/pkg/FR‐2011‐12‐30/pdf/2011‐33586.pdf).

   
    

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Attachment A

Comparison of EPA and AEPCO CALPUFF Modeling Results

Visibility Method 8 using Best 20% Days Visibility Background

Constant 1 ppb Background Ammonia Concentrations

A1:  EPA Base Case (OFA)

A2:  EPA SCR (0.07 lb/MMBtu) Case

A3:  EPA AEPCO Alternative Control 9 (ST2 PNGf and ST3 SNCR)

A4:  EPA AEPCO Alternative Control 9b (ST2 PNGt and ST3 SNCR)

   
    

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Attachment A1:  EPA and AEPCO CALPUFF Results for EPA Base Case (OFA).

EPA CALPUFF Results Impact in Deciviews: EPA Base with Ammonia = 1ppb

EPA Base Case (OFA) 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 3.210 3.270 3.503 3.328 3.409

Chiricahua Wild. 3.404 3.387 3.464 3.418 3.464

Galiuro Wild. 1.805 2.113 2.615 2.178 2.219

Gila Wild. 0.673 0.753 0.500 0.642 0.629

Mazatzal Wild. 0.299 0.268 0.231 0.266 0.277

Mount Baldy Wild. 0.285 0.282 0.239 0.269 0.282

Saguaro NP 2.299 2.767 2.386 2.484 2.485

Sierra Ancha Wild. 0.287 0.304 0.275 0.289 0.287

Superstition Wild. 0.609 0.684 0.494 0.596 0.612

AEPCO CALPUFF Results Impact in Deciviews: EPA Base with Ammonia = 1ppb

EPA Base Case (OFA) 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 3.210 3.270 3.503 3.328 3.409

Chiricahua Wild. 3.404 3.387 3.464 3.418 3.464

Galiuro Wild. 1.805 2.113 2.615 2.178 2.219

Gila Wild. 0.673 0.753 0.500 0.642 0.629

Mazatzal Wild. 0.299 0.268 0.231 0.266 0.277

Mount Baldy Wild. 0.285 0.282 0.239 0.269 0.282

Saguaro NP 2.299 2.767 2.441 2.502 2.493

Sierra Ancha Wild. 0.287 0.304 0.275 0.289 0.287

Superstition Wild. 0.609 0.684 0.494 0.596 0.612

Difference in EPA and AEPCO CALPUFF Results (AEPCO – EPA)

EPA Base Case (OFA) 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 0.000 0.000 0.000 0.000 0.000

Chiricahua Wild. 0.000 0.000 0.000 0.000 0.000

Galiuro Wild. 0.000 0.000 0.000 0.000 0.000

Gila Wild. 0.000 0.000 0.000 0.000 0.000

Mazatzal Wild. 0.000 0.000 0.000 0.000 0.000

Mount Baldy Wild. 0.000 0.000 0.000 0.000 0.000

Saguaro NP 0.000 0.000 0.055 0.018 0.008

Sierra Ancha Wild. 0.000 0.000 0.000 0.000 0.000

Superstition Wild. 0.000 0.000 0.000 0.000 0.000

   
    

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Attachment A2:  EPA and AEPCO CALPUFF Results for EPA SCR Case (0.07 lb/MMBtu)

EPA CALPUFF Results Impact in Deciviews: EPA Base with Ammonia = 1ppb

EPA SCR Case 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.790 2.147 1.996 1.978 1.996

Chiricahua Wild. 1.979 1.892 1.788 1.886 1.979

Galiuro Wild. 0.991 1.146 1.486 1.208 1.205

Gila Wild. 0.226 0.321 0.238 0.262 0.279

Mazatzal Wild. 0.167 0.172 0.130 0.156 0.147

Mount Baldy Wild. 0.102 0.132 0.092 0.109 0.114

Saguaro NP 1.308 1.460 1.495 1.421 1.463

Sierra Ancha Wild. 0.137 0.174 0.149 0.153 0.158

Superstition Wild. 0.317 0.307 0.314 0.313 0.315

AEPCO CALPUFF Results Impact in Deciviews: EPA Base with Ammonia = 1ppb

EPA SCR Case 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.790 2.147 1.996 1.978 1.996

Chiricahua Wild. 1.979 1.892 1.788 1.886 1.979

Galiuro Wild. 0.991 1.146 1.486 1.208 1.205

Gila Wild. 0.226 0.321 0.238 0.262 0.279

Mazatzal Wild. 0.167 0.172 0.130 0.156 0.147

Mount Baldy Wild. 0.102 0.132 0.092 0.109 0.114

Saguaro NP 1.308 1.460 1.495 1.421 1.463

Sierra Ancha Wild. 0.137 0.174 0.149 0.153 0.158

Superstition Wild. 0.317 0.307 0.314 0.313 0.315

Difference in EPA and AEPCO CALPUFF Results (AEPCO – EPA)

EPA Base Case (OFA) 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 0.000 0.000 0.000 0.000 0.000

Chiricahua Wild. 0.000 0.000 0.000 0.000 0.000

Galiuro Wild. 0.000 0.000 0.000 0.000 0.000

Gila Wild. 0.000 0.000 0.000 0.000 0.000

Mazatzal Wild. 0.000 0.000 0.000 0.000 0.000

Mount Baldy Wild. 0.000 0.000 0.000 0.000 0.000

Saguaro NP 0.000 0.000 0.000 0.000 0.000

Sierra Ancha Wild. 0.000 0.000 0.000 0.000 0.000

Superstition Wild. 0.000 0.000 0.000 0.000 0.000

   
    

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Attachment A3:  EPA and AEPCO CALPUFF Results for AEPCO Alternative Control 9.

EPA CALPUFF Results Impact in Deciviews: EPA Base with Ammonia = 1ppb

AEPCO Alt Cntl 9 (PNGf) 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 2.561 2.904 2.822 2.762 2.822

Chiricahua Wild. 2.807 2.571 2.692 2.690 2.727

Galiuro Wild. 1.366 1.559 1.909 1.611 1.629

Gila Wild. 0.331 0.458 0.298 0.362 0.404

Mazatzal Wild. 0.190 0.182 0.145 0.172 0.161

Mount Baldy Wild. 0.135 0.149 0.108 0.131 0.143

Saguaro NP 1.834 2.044 1.982 1.953 1.955

Sierra Ancha Wild. 0.165 0.195 0.159 0.173 0.166

Superstition Wild. 0.417 0.385 0.352 0.385 0.392

AEPCO CALPUFF Results Impact in Deciviews: EPA Base with Ammonia = 1ppb

AEPCO Alt Cntl 9 (PNGf) 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 2.474 2.633 2.634 2.580 2.634

Chiricahua Wild. 2.606 2.430 2.511 2.516 2.554

Galiuro Wild. 1.464 1.548 1.777 1.596 1.562

Gila Wild. 0.376 0.474 0.338 0.396 0.392

Mazatzal Wild. 0.186 0.181 0.149 0.172 0.161

Mount Baldy Wild. 0.133 0.147 0.120 0.133 0.143

Saguaro NP 1.837 2.045 1.897 1.926 1.916

Sierra Ancha Wild. 0.173 0.183 0.152 0.169 0.166

Superstition Wild. 0.386 0.416 0.342 0.381 0.386

Difference in EPA and AEPCO CALPUFF Results (AEPCO – EPA)

AEPCO Alt Cntl 9 (PNGf) 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM  ‐0.087  ‐0.271  ‐0.188  ‐0.182  ‐0.188

Chiricahua Wild.  ‐0.201  ‐0.141  ‐0.181  ‐0.174  ‐0.173

Galiuro Wild. 0.098  ‐0.011  ‐0.132  ‐0.015  ‐0.067

Gila Wild. 0.045 0.016 0.040 0.034  ‐0.012

Mazatzal Wild.  ‐0.004  ‐0.001 0.004 0.000 0.000

Mount Baldy Wild.  ‐0.002  ‐0.002 0.012 0.003 0.000

Saguaro NP 0.003 0.001  ‐0.085  ‐0.027  ‐0.039

Sierra Ancha Wild. 0.008  ‐0.012  ‐0.007  ‐0.004 0.000

Superstition Wild.  ‐0.031 0.031  ‐0.010  ‐0.003  ‐0.006

   
    

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Attachment A4:  EPA and AEPCO CALPUFF Results for AEPCO Alternative Control 9b.

EPA CALPUFF Results Impact in Deciviews: EPA Base with Ammonia = 1ppb

AEPCO Alt Cntl 9b (PNGt) 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.968 1.991 2.122 2.027 2.016

Chiricahua Wild. 1.946 1.945 1.990 1.960 1.990

Galiuro Wild. 1.014 1.051 1.545 1.203 1.221

Gila Wild. 0.258 0.332 0.238 0.276 0.306

Mazatzal Wild. 0.141 0.135 0.117 0.131 0.132

Mount Baldy Wild. 0.115 0.127 0.097 0.113 0.115

Saguaro NP 1.278 1.598 1.380 1.419 1.401

Sierra Ancha Wild. 0.131 0.140 0.124 0.132 0.131

Superstition Wild. 0.296 0.318 0.234 0.283 0.296

AEPCO CALPUFF Results Impact in Deciviews: EPA Base with Ammonia = 1ppb

AEPCO Alt Cntl 9b (PNGt) 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.939 1.784 2.054 1.926 1.960

Chiricahua Wild. 1.913 1.889 1.914 1.905 1.913

Galiuro Wild. 1.006 0.987 1.450 1.148 1.181

Gila Wild. 0.298 0.351 0.234 0.294 0.307

Mazatzal Wild. 0.141 0.135 0.115 0.130 0.127

Mount Baldy Wild. 0.118 0.123 0.103 0.115 0.118

Saguaro NP 1.255 1.560 1.349 1.388 1.357

Sierra Ancha Wild. 0.136 0.142 0.120 0.133 0.131

Superstition Wild. 0.293 0.338 0.216 0.282 0.293

Difference in EPA and AEPCO CALPUFF Results (AEPCO – EPA)

AEPCO Alt Cntl 9b (PNGt) 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM  ‐0.029  ‐0.207  ‐0.068  ‐0.101  ‐0.056

Chiricahua Wild.  ‐0.033  ‐0.056  ‐0.076  ‐0.055  ‐0.077

Galiuro Wild.  ‐0.008  ‐0.064  ‐0.095  ‐0.056  ‐0.040

Gila Wild. 0.040 0.019  ‐0.004 0.018 0.001

Mazatzal Wild. 0.000 0.000  ‐0.002  ‐0.001  ‐0.005

Mount Baldy Wild. 0.003  ‐0.004 0.006 0.002 0.003

Saguaro NP  ‐0.023  ‐0.038  ‐0.031  ‐0.031  ‐0.044

Sierra Ancha Wild. 0.005 0.002  ‐0.004 0.001 0.000

Superstition Wild.  ‐0.003 0.020  ‐0.018 0.000  ‐0.003
    

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Attachment B

Comparison of AEPCO’s CALPUFF Visibility Results for EPA BART SCR (0.07 lb/MMBtu) and

AEPCO Alternative Control 9 (PNGf) and 9b (PNGt)

Visibility Method 8 using Best 20% Days Visibility Background

Monthly Varying Background Ammonia Concentrations (ENSR/AECOM, 2009)

B1:  EPA BART SCR vs. AEPCO Alternative Control 9 (PNGf))

B2:  EPA BART SCR vs. AEPCO Alternative Control 9b (PNGt)

   
    

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Attachment B1:  EPA BART SCR vs. AEPCO Alternative Control 9 (PNGf) monthly ammonia.

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

EPA BART SCR 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.657 1.820 1.747 1.741 1.747

Chiricahua Wild. 1.834 1.651 1.622 1.702 1.788

Galiuro Wild. 0.886 1.047 1.156 1.030 1.096

Gila Wild. 0.218 0.278 0.227 0.241 0.251

Mazatzal Wild. 0.150 0.145 0.110 0.135 0.136

Mount Baldy Wild. 0.097 0.132 0.089 0.106 0.099

Saguaro NP 1.185 1.263 1.349 1.266 1.263

Sierra Ancha Wild. 0.122 0.151 0.138 0.137 0.138

Superstition Wild. 0.277 0.269 0.278 0.275 0.277

Average 0.714 0.751 0.746 0.737 0.755

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

EPA AEPCO Alt Cntl 9 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 2.225 2.217 2.285 2.242 2.252

Chiricahua Wild. 2.245 2.188 1.961 2.131 2.214

Galiuro Wild. 1.116 1.292 1.522 1.310 1.318

Gila Wild. 0.283 0.394 0.292 0.323 0.329

Mazatzal Wild. 0.138 0.149 0.108 0.132 0.137

Mount Baldy Wild. 0.119 0.135 0.090 0.115 0.125

Saguaro NP 1.609 1.652 1.799 1.687 1.662

Sierra Ancha Wild. 0.135 0.165 0.127 0.142 0.141

Superstition Wild. 0.312 0.296 0.288 0.299 0.300

Average 0.909 0.943 0.941 0.931 0.942

Difference in dv between EPA BART SCR and AEPCO Alternative Cntl 9 (Alt – SCR)

   98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 0.568 0.397 0.538 0.501 0.505

Chiricahua Wild. 0.411 0.537 0.339 0.429 0.426

Galiuro Wild. 0.230 0.245 0.366 0.280 0.222

Gila Wild. 0.065 0.116 0.065 0.082 0.078

Mazatzal Wild.  ‐0.012 0.004  ‐0.002  ‐0.003 0.001

Mount Baldy Wild. 0.022 0.003 0.001 0.009 0.026

Saguaro NP 0.424 0.389 0.450 0.421 0.399

Sierra Ancha Wild. 0.013 0.014  ‐0.011 0.005 0.003

Superstition Wild. 0.035 0.027 0.010 0.024 0.023

Average 0.195 0.192 0.195 0.194 0.187
    

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Attachment B2:  EPA BART SCR vs. AEPCO Alternative Control 9b (PNGt) monthly ammonia.

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

EPA BART SCR 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.657 1.820 1.747 1.741 1.747

Chiricahua Wild. 1.834 1.651 1.622 1.702 1.788

Galiuro Wild. 0.886 1.047 1.156 1.030 1.096

Gila Wild. 0.218 0.278 0.227 0.241 0.251

Mazatzal Wild. 0.150 0.145 0.110 0.135 0.136

Mount Baldy Wild. 0.097 0.132 0.089 0.106 0.099

Saguaro NP 1.185 1.263 1.349 1.266 1.263

Sierra Ancha Wild. 0.122 0.151 0.138 0.137 0.138

Superstition Wild. 0.277 0.269 0.278 0.275 0.277

Average 0.714 0.751 0.746 0.737 0.755

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

EPA AEPCO Alt Cntl 9b 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.467 1.489 1.662 1.539 1.567

Chiricahua Wild. 1.632 1.514 1.434 1.527 1.562

Galiuro Wild. 0.719 0.852 0.961 0.844 0.909

Gila Wild. 0.229 0.276 0.192 0.232 0.239

Mazatzal Wild. 0.111 0.106 0.083 0.100 0.104

Mount Baldy Wild. 0.105 0.096 0.077 0.093 0.096

Saguaro NP 1.014 1.096 1.205 1.105 1.132

Sierra Ancha Wild. 0.094 0.112 0.090 0.099 0.102

Superstition Wild. 0.233 0.217 0.200 0.217 0.217

Average 0.623 0.640 0.656 0.639 0.659

Difference in dv between EPA BART SCR and AEPCO Alternative Cntl 9b (Alt – SCR)

98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM  ‐0.190  ‐0.331  ‐0.085  ‐0.202  ‐0.180

Chiricahua Wild.  ‐0.202  ‐0.137  ‐0.188  ‐0.176  ‐0.226

Galiuro Wild.  ‐0.167  ‐0.195  ‐0.195  ‐0.186  ‐0.187

Gila Wild. 0.011  ‐0.002  ‐0.035  ‐0.009  ‐0.012

Mazatzal Wild.  ‐0.039  ‐0.039  ‐0.027  ‐0.035  ‐0.032

Mount Baldy Wild. 0.008  ‐0.036  ‐0.012  ‐0.013  ‐0.003

Saguaro NP  ‐0.171  ‐0.167  ‐0.144  ‐0.161  ‐0.131

Sierra Ancha Wild.  ‐0.028  ‐0.039  ‐0.048  ‐0.038  ‐0.036

Superstition Wild.  ‐0.044  ‐0.052  ‐0.078  ‐0.058  ‐0.060

Average  ‐0.091  ‐0.111  ‐0.090  ‐0.097  ‐0.096
    

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Attachment C

Comparison of AEPCO’s CALPUFF Visibility Results for EPA BART SCR (0.07 lb/MMBtu) and

AEPCO Alternative with Updated PM Emissions Factor for ST2 (0.00042 lb/MMBtu)

Visibility Method 8 using Best 20% Days Visibility Background

Monthly Varying Background Ammonia Concentrations (ENSR/AECOM, 2009)

C1:  EPA BART SCR vs. AEPCO Alternative with Updated PM Emissions Factor for ST2

   
    

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Attachment C1:  EPA BART SCR vs. AEPCO Alternative with Updated PM monthly ammonia.

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

EPA BART SCR 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.657 1.820 1.747 1.741 1.747

Chiricahua Wild. 1.834 1.651 1.622 1.702 1.788

Galiuro Wild. 0.886 1.047 1.156 1.030 1.096

Gila Wild. 0.218 0.278 0.227 0.241 0.251

Mazatzal Wild. 0.150 0.145 0.110 0.135 0.136

Mount Baldy Wild. 0.097 0.132 0.089 0.106 0.099

Saguaro NP 1.185 1.263 1.349 1.266 1.263

Sierra Ancha Wild. 0.122 0.151 0.138 0.137 0.138

Superstition Wild. 0.277 0.269 0.278 0.275 0.277

Average 0.714 0.751 0.746 0.737 0.755

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

AEPCO Alt w/ Updated PM 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001‐03 2001 ‐2003

Chiricahua NM 1.27 1.32 1.44 1.34 1.37

Chiricahua Wild. 1.40 1.34 1.26 1.33 1.35

Galiuro Wild. 0.60 0.70 0.87 0.72 0.74

Gila Wild. 0.18 0.23 0.17 0.20 0.21

Mazatzal Wild. 0.10 0.10 0.07 0.09 0.10

Mount Baldy Wild. 0.10 0.09 0.07 0.09 0.09

Saguaro NP 0.81 0.93 1.02 0.92 0.93

Sierra Ancha Wild. 0.08 0.10 0.08 0.09 0.09

Superstition Wild. 0.19 0.19 0.17 0.18 0.19

Average 1.27 1.32 1.44 1.34 1.37

Difference in dv between EPA BART SCR and AEPCO Alternative w/ PM (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001‐03 2001 ‐2003

Chiricahua NM  ‐0.39  ‐0.50  ‐0.30  ‐0.40  ‐0.38

Chiricahua Wild.  ‐0.44  ‐0.31  ‐0.37  ‐0.37  ‐0.44

Galiuro Wild.  ‐0.29  ‐0.34  ‐0.29  ‐0.31  ‐0.36

Gila Wild.  ‐0.04  ‐0.05  ‐0.06  ‐0.05  ‐0.04

Mazatzal Wild.  ‐0.05  ‐0.05  ‐0.04  ‐0.04  ‐0.04

Mount Baldy Wild. 0.00  ‐0.04  ‐0.02  ‐0.02  ‐0.01

Saguaro NP  ‐0.38  ‐0.34  ‐0.33  ‐0.35  ‐0.34

Sierra Ancha Wild.  ‐0.04  ‐0.06  ‐0.06  ‐0.05  ‐0.05

Superstition Wild.  ‐0.08  ‐0.08  ‐0.11  ‐0.09  ‐0.09

Average  ‐0.19  ‐0.20  ‐0.17  ‐0.19  ‐0.19
    

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Attachment D

Comparison of AEPCO’s CALPUFF Visibility Results for EPA BART SCR (0.07 lb/MMBtu) and

AEPCO Alternative Control 9v2 (PNGf) and 9bv2 (PNGt)

Visibility Method 8 using Best 20% Days Visibility Background

Monthly Varying Background Ammonia Concentrations (ENSR/AECOM, 2009)

D1:  EPA BART SCR vs. AEPCO Alternative Control 9v2 (PNGf))

D2:  EPA BART SCR vs. AEPCO Alternative Control 9bv2 (PNGt)

   
    

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Attachment D1:  EPA BART SCR vs. AEPCO Alternative Control 9v2 (PNGf) monthly ammonia.

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

EPA BART SCR 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.657 1.820 1.747 1.741 1.747

Chiricahua Wild. 1.834 1.651 1.622 1.702 1.788

Galiuro Wild. 0.886 1.047 1.156 1.030 1.096

Gila Wild. 0.218 0.278 0.227 0.241 0.251

Mazatzal Wild. 0.150 0.145 0.110 0.135 0.136

Mount Baldy Wild. 0.097 0.132 0.089 0.106 0.099

Saguaro NP 1.185 1.263 1.349 1.266 1.263

Sierra Ancha Wild. 0.122 0.151 0.138 0.137 0.138

Superstition Wild. 0.277 0.269 0.278 0.275 0.277

Average 0.714 0.751 0.746 0.737 0.755

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

AEPCO Alt Cntl 9v2 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 2.318 2.006 2.013 2.114 2.044

Chiricahua Wild. 2.427 2.059 2.013 1.815 1.962

Galiuro Wild. 1.356 1.014 1.174 1.368 1.185

Gila Wild. 0.336 0.259 0.368 0.261 0.296

Mazatzal Wild. 0.178 0.129 0.137 0.101 0.122

Mount Baldy Wild. 0.127 0.116 0.125 0.083 0.108

Saguaro NP 1.678 1.457 1.501 1.626 1.528

Sierra Ancha Wild. 0.162 0.125 0.150 0.112 0.129

Superstition Wild. 0.365 0.290 0.273 0.268 0.277

Average 0.994 0.828 0.862 0.861 0.850

Difference in dv between EPA BART SCR and AEPCO Alternative Cntl 9v2 (Alt – SCR)

   98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 0.349 0.193 0.367 0.303 0.275

Chiricahua Wild. 0.225 0.362 0.193 0.260 0.247

Galiuro Wild. 0.128 0.127 0.212 0.156 0.084

Gila Wild. 0.041 0.090 0.034 0.055 0.056

Mazatzal Wild.  ‐0.021  ‐0.008  ‐0.009  ‐0.013  ‐0.007

Mount Baldy Wild. 0.019  ‐0.007  ‐0.006 0.002 0.019

Saguaro NP 0.272 0.238 0.277 0.262 0.254

Sierra Ancha Wild. 0.003  ‐0.001  ‐0.026  ‐0.008  ‐0.007

Superstition Wild. 0.013 0.004  ‐0.010 0.002  ‐0.004

Average 0.114 0.111 0.115 0.113 0.102
    

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Attachment D2:  EPA BART SCR vs. AEPCO Alternative Control 9bv2 (PNGt) monthly ammonia.

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

EPA BART SCR 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.657 1.820 1.747 1.741 1.747

Chiricahua Wild. 1.834 1.651 1.622 1.702 1.788

Galiuro Wild. 0.886 1.047 1.156 1.030 1.096

Gila Wild. 0.218 0.278 0.227 0.241 0.251

Mazatzal Wild. 0.150 0.145 0.110 0.135 0.136

Mount Baldy Wild. 0.097 0.132 0.089 0.106 0.099

Saguaro NP 1.185 1.263 1.349 1.266 1.263

Sierra Ancha Wild. 0.122 0.151 0.138 0.137 0.138

Superstition Wild. 0.277 0.269 0.278 0.275 0.277

Average 0.714 0.751 0.746 0.737 0.755

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

AEPCO Alt Cntl 9bv2 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.422 1.441 1.612 1.492 1.521

Chiricahua Wild. 1.581 1.474 1.392 1.482 1.513

Galiuro Wild. 0.690 0.820 0.938 0.816 0.864

Gila Wild. 0.218 0.268 0.188 0.225 0.233

Mazatzal Wild. 0.109 0.103 0.081 0.098 0.102

Mount Baldy Wild. 0.103 0.095 0.076 0.091 0.094

Saguaro NP 0.969 1.058 1.168 1.065 1.094

Sierra Ancha Wild. 0.091 0.108 0.088 0.096 0.100

Superstition Wild. 0.225 0.210 0.193 0.209 0.210

Average 0.601 0.620 0.637 0.619 0.637

Difference in dv between EPA BART SCR and AEPCO Alternative Cntl 9bv2 (Alt – SCR)

98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM  ‐0.235  ‐0.379  ‐0.135  ‐0.250  ‐0.226

Chiricahua Wild.  ‐0.253  ‐0.177  ‐0.230  ‐0.220  ‐0.275

Galiuro Wild.  ‐0.196  ‐0.227  ‐0.218  ‐0.214  ‐0.232

Gila Wild. 0.000  ‐0.010  ‐0.039  ‐0.016  ‐0.018

Mazatzal Wild.  ‐0.041  ‐0.042  ‐0.029  ‐0.037  ‐0.034

Mount Baldy Wild. 0.006  ‐0.037  ‐0.013  ‐0.015  ‐0.005

Saguaro NP  ‐0.216  ‐0.205  ‐0.181  ‐0.201  ‐0.169

Sierra Ancha Wild.  ‐0.031  ‐0.043  ‐0.050  ‐0.041  ‐0.038

Superstition Wild.  ‐0.052  ‐0.059  ‐0.085  ‐0.065  ‐0.067

Average  ‐0.113  ‐0.131  ‐0.109  ‐0.118  ‐0.118
    

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Attachment E

Comparison of AEPCO’s CALPUFF Visibility Results for EPA BART SCR (0.07 lb/MMBtu) and the

Various AEPCO Alternative Scenarios using Constant 1 ppb Ammonia

Visibility Method 8 using Best 20% Days Visibility Background

Constant 1 ppb Background Ammonia Concentration

E1:  EPA BART SCR vs. AEPCO Alternative Control 9 (PNGf))

E2:  EPA BART SCR vs. AEPCO Alternative Control 9b (PNGt)

E3:  EPA BART SCR vs. AEPCO Alternative w/ Updated PM Factor

E4:  EPA BART SCR vs. AEP Alternative Control 9v2 (PNGf))

E5:  EPA BART SCR vs. AEPCO Alternative Control 9bv2 (PNGt)

   
    

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Attachment E1:  EPA BART SCR vs. AEPCO Alternative Control 9 (PNGf) constant ammonia.

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

EPA BART SCR 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.790 2.147 1.996 1.978 1.996

Chiricahua Wild. 1.979 1.892 1.788 1.886 1.979

Galiuro Wild. 0.991 1.146 1.486 1.208 1.205

Gila Wild. 0.226 0.321 0.238 0.262 0.279

Mazatzal Wild. 0.167 0.172 0.130 0.156 0.147

Mount Baldy Wild. 0.102 0.132 0.092 0.109 0.114

Saguaro NP 1.308 1.460 1.495 1.421 1.463

Sierra Ancha Wild. 0.137 0.174 0.149 0.153 0.158

Superstition Wild. 0.317 0.307 0.314 0.313 0.315

Average 0.780 0.861 0.854 0.832 0.851

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

AEPCO Alt Cntl 9 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 2.474 2.633 2.634 2.580 2.634

Chiricahua Wild. 2.606 2.430 2.511 2.516 2.554

Galiuro Wild. 1.464 1.548 1.777 1.596 1.562

Gila Wild. 0.376 0.474 0.338 0.396 0.392

Mazatzal Wild. 0.186 0.181 0.149 0.172 0.161

Mount Baldy Wild. 0.133 0.147 0.120 0.133 0.143

Saguaro NP 1.837 2.045 1.897 1.926 1.916

Sierra Ancha Wild. 0.173 0.183 0.152 0.169 0.166

Superstition Wild. 0.386 0.416 0.342 0.381 0.386

Average 1.071 1.117 1.102 1.097 1.102

Difference in dv between EPA BART SCR and AEPCO Alternative Cntl 9 (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 0.684 0.486 0.638 0.603 0.638

Chiricahua Wild. 0.627 0.538 0.723 0.629 0.575

Galiuro Wild. 0.473 0.402 0.291 0.389 0.357

Gila Wild. 0.150 0.153 0.100 0.134 0.113

Mazatzal Wild. 0.019 0.009 0.019 0.016 0.014

Mount Baldy Wild. 0.031 0.015 0.028 0.025 0.029

Saguaro NP 0.529 0.585 0.402 0.505 0.453

Sierra Ancha Wild. 0.036 0.009 0.003 0.016 0.008

Superstition Wild. 0.069 0.109 0.028 0.069 0.071

Average 0.291 0.256 0.248 0.265 0.251
    

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Attachment E2:  EPA BART SCR vs. AEPCO Alternative Control 9b (PNGt) constant ammonia.

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

EPA BART SCR 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.790 2.147 1.996 1.978 1.996

Chiricahua Wild. 1.979 1.892 1.788 1.886 1.979

Galiuro Wild. 0.991 1.146 1.486 1.208 1.205

Gila Wild. 0.226 0.321 0.238 0.262 0.279

Mazatzal Wild. 0.167 0.172 0.130 0.156 0.147

Mount Baldy Wild. 0.102 0.132 0.092 0.109 0.114

Saguaro NP 1.308 1.460 1.495 1.421 1.463

Sierra Ancha Wild. 0.137 0.174 0.149 0.153 0.158

Superstition Wild. 0.317 0.307 0.314 0.313 0.315

Average 0.780 0.861 0.854 0.832 0.851

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

AEPCO Alt Cntl 9b 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.939 1.784 2.054 1.926 1.960

Chiricahua Wild. 1.913 1.889 1.914 1.905 1.913

Galiuro Wild. 1.006 0.987 1.450 1.148 1.181

Gila Wild. 0.298 0.351 0.234 0.294 0.307

Mazatzal Wild. 0.141 0.135 0.115 0.130 0.127

Mount Baldy Wild. 0.118 0.123 0.103 0.115 0.118

Saguaro NP 1.255 1.560 1.349 1.388 1.357

Sierra Ancha Wild. 0.136 0.142 0.120 0.133 0.131

Superstition Wild. 0.293 0.338 0.216 0.282 0.293

Average 0.789 0.812 0.839 0.813 0.821

Difference in dv between EPA BART SCR and AEPCO Alternative Cntl 9b (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 0.149  ‐0.363 0.058  ‐0.052  ‐0.036

Chiricahua Wild.  ‐0.066  ‐0.003 0.126 0.019  ‐0.066

Galiuro Wild. 0.015  ‐0.159  ‐0.036  ‐0.060  ‐0.024

Gila Wild. 0.072 0.030  ‐0.004 0.033 0.028

Mazatzal Wild.  ‐0.026  ‐0.037  ‐0.015  ‐0.026  ‐0.020

Mount Baldy Wild. 0.016  ‐0.009 0.011 0.006 0.004

Saguaro NP  ‐0.053 0.100  ‐0.146  ‐0.033  ‐0.106

Sierra Ancha Wild.  ‐0.001  ‐0.032  ‐0.029  ‐0.021  ‐0.027

Superstition Wild.  ‐0.024 0.031  ‐0.098  ‐0.030  ‐0.022

Average 0.009  ‐0.049  ‐0.015  ‐0.018  ‐0.030
    

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Attachment E3:  EPA BART SCR vs. AEPCO Alternative with Update PM Emissions.

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

EPA BART SCR 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.790 2.147 1.996 1.978 1.996

Chiricahua Wild. 1.979 1.892 1.788 1.886 1.979

Galiuro Wild. 0.991 1.146 1.486 1.208 1.205

Gila Wild. 0.226 0.321 0.238 0.262 0.279

Mazatzal Wild. 0.167 0.172 0.130 0.156 0.147

Mount Baldy Wild. 0.102 0.132 0.092 0.109 0.114

Saguaro NP 1.308 1.460 1.495 1.421 1.463

Sierra Ancha Wild. 0.137 0.174 0.149 0.153 0.158

Superstition Wild. 0.317 0.307 0.314 0.313 0.315

Average 0.780 0.861 0.854 0.832 0.851

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

AEPCO Alt PM Update 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.73 1.63 1.87 1.74 1.79

Chiricahua Wild. 1.66 1.67 1.71 1.68 1.68

Galiuro Wild. 0.81 0.87 1.32 1.00 1.02

Gila Wild. 0.28 0.32 0.21 0.27 0.27

Mazatzal Wild. 0.12 0.12 0.10 0.11 0.12

Mount Baldy Wild. 0.12 0.12 0.10 0.11 0.12

Saguaro NP 1.17 1.44 1.17 1.26 1.19

Sierra Ancha Wild. 0.11 0.13 0.11 0.12 0.12

Superstition Wild. 0.25 0.31 0.20 0.25 0.27

Average 1.73 1.63 1.87 1.74 1.79

Difference in dv between EPA BART SCR and AEPCO Alternative PM (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM  ‐0.06  ‐0.52  ‐0.13  ‐0.24  ‐0.21

Chiricahua Wild.  ‐0.32  ‐0.23  ‐0.08  ‐0.21  ‐0.30

Galiuro Wild.  ‐0.18  ‐0.28  ‐0.17  ‐0.21  ‐0.19

Gila Wild. 0.06 0.00  ‐0.03 0.01  ‐0.01

Mazatzal Wild.  ‐0.05  ‐0.05  ‐0.03  ‐0.04  ‐0.03

Mount Baldy Wild. 0.01  ‐0.02 0.01 0.00 0.00

Saguaro NP  ‐0.14  ‐0.02  ‐0.32  ‐0.16  ‐0.28

Sierra Ancha Wild.  ‐0.03  ‐0.05  ‐0.04  ‐0.04  ‐0.04

Superstition Wild.  ‐0.07 0.01  ‐0.11  ‐0.06  ‐0.05

Average  ‐0.09  ‐0.13  ‐0.10  ‐0.10  ‐0.12
    

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Attachment E4:  EPA BART SCR vs. AEPCO Alternative Control 9v2 (PNGt) constant ammonia.

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

EPA BART SCR 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.790 2.147 1.996 1.978 1.996

Chiricahua Wild. 1.979 1.892 1.788 1.886 1.979

Galiuro Wild. 0.991 1.146 1.486 1.208 1.205

Gila Wild. 0.226 0.321 0.238 0.262 0.279

Mazatzal Wild. 0.167 0.172 0.130 0.156 0.147

Mount Baldy Wild. 0.102 0.132 0.092 0.109 0.114

Saguaro NP 1.308 1.460 1.495 1.421 1.463

Sierra Ancha Wild. 0.137 0.174 0.149 0.153 0.158

Superstition Wild. 0.317 0.307 0.314 0.313 0.315

Average 0.780 0.861 0.854 0.832 0.851

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

AEPCO Alt Cntl 9v2 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 2.318 2.405 2.464 2.396 2.421

Chiricahua Wild. 2.427 2.266 2.344 2.346 2.370

Galiuro Wild. 1.356 1.397 1.661 1.471 1.452

Gila Wild. 0.336 0.430 0.309 0.358 0.366

Mazatzal Wild. 0.178 0.167 0.138 0.161 0.150

Mount Baldy Wild. 0.127 0.136 0.114 0.126 0.135

Saguaro NP 1.678 1.927 1.708 1.771 1.799

Sierra Ancha Wild. 0.162 0.171 0.144 0.159 0.153

Superstition Wild. 0.365 0.393 0.307 0.355 0.365

Average 0.994 1.032 1.021 1.016 1.023

Difference in dv between EPA BART SCR and AEPCO Alternative Cntl 9v2 (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 0.528 0.258 0.468 0.418 0.425

Chiricahua Wild. 0.448 0.374 0.556 0.459 0.391

Galiuro Wild. 0.365 0.251 0.175 0.264 0.247

Gila Wild. 0.110 0.109 0.071 0.097 0.087

Mazatzal Wild. 0.011  ‐0.005 0.008 0.005 0.003

Mount Baldy Wild. 0.025 0.004 0.022 0.017 0.021

Saguaro NP 0.370 0.467 0.213 0.350 0.336

Sierra Ancha Wild. 0.025  ‐0.003  ‐0.005 0.006  ‐0.005

Superstition Wild. 0.048 0.086  ‐0.007 0.042 0.050

Average 0.214 0.171 0.167 0.184 0.173
    

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Attachment E5:  EPA BART SCR vs. AEPCO Alternative Control 9bv2 (PNGt) constant ammonia.

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

EPA BART SCR 98th Percentile Avg 98th 22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.790 2.147 1.996 1.978 1.996

Chiricahua Wild. 1.979 1.892 1.788 1.886 1.979

Galiuro Wild. 0.991 1.146 1.486 1.208 1.205

Gila Wild. 0.226 0.321 0.238 0.262 0.279

Mazatzal Wild. 0.167 0.172 0.130 0.156 0.147

Mount Baldy Wild. 0.102 0.132 0.092 0.109 0.114

Saguaro NP 1.308 1.460 1.495 1.421 1.463

Sierra Ancha Wild. 0.137 0.174 0.149 0.153 0.158

Superstition Wild. 0.317 0.307 0.314 0.313 0.315

Average 0.780 0.861 0.854 0.832 0.851

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

AEPCO Alt Cntl 9bv2 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 1.898 1.740 2.007 1.882 1.909

Chiricahua Wild. 1.852 1.837 1.863 1.851 1.852

Galiuro Wild. 0.959 0.952 1.421 1.111 1.135

Gila Wild. 0.292 0.342 0.226 0.287 0.295

Mazatzal Wild. 0.136 0.131 0.112 0.126 0.124

Mount Baldy Wild. 0.116 0.121 0.100 0.112 0.116

Saguaro NP 1.213 1.525 1.301 1.346 1.317

Sierra Ancha Wild. 0.132 0.139 0.118 0.130 0.128

Superstition Wild. 0.283 0.330 0.212 0.275 0.283

Average 0.765 0.791 0.818 0.791 0.795

Difference in dv between EPA BART SCR and AEPCO Alternative Cntl 9bv2 (Alt – SCR)

AEPCO CALPUFF Results 98th Percentile Avg 98th   22nd high

Class I Area 2001 2002 2003 2001 ‐2003 2001 ‐2003

Chiricahua NM 0.108  ‐0.407 0.011  ‐0.096  ‐0.087

Chiricahua Wild.  ‐0.127  ‐0.055 0.075  ‐0.036  ‐0.127

Galiuro Wild.  ‐0.032  ‐0.194  ‐0.065  ‐0.097  ‐0.070

Gila Wild. 0.066 0.021  ‐0.012 0.025 0.016

Mazatzal Wild.  ‐0.031  ‐0.041  ‐0.018  ‐0.030  ‐0.023

Mount Baldy Wild. 0.014  ‐0.011 0.008 0.004 0.002

Saguaro NP  ‐0.095 0.065  ‐0.194  ‐0.075  ‐0.146

Sierra Ancha Wild.  ‐0.005  ‐0.035  ‐0.031  ‐0.024  ‐0.030

Superstition Wild.  ‐0.034 0.023  ‐0.102  ‐0.038  ‐0.032

Average  ‐0.015  ‐0.070  ‐0.036  ‐0.041  ‐0.055
   

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May 8, 2013

MEMORANDUM

To:    Michelle Freeark, Arizona Electric Power Cooperative (AEPCO)

From:    Ralph Morris and Glenn England

Subject:    Updated PM2.5 Emissions Factors for Natural Gas‐Fired Boilers

SUMMARY

AEPCO is proposing an alternative to EPA’s proposed Best Available Retrofit Technology (BART)

NOX emissions controls on their Apache ST2 and ST3 coal‐fired electrical generating units

(EGUs).  EPA’s proposed BART scenario would install selective catalytic reduction (SCR) on both

of Apaches coal‐fired EGUs, whereas the AEPCO Alternative would convert one of the units to

natural gas (ST2) and install selective non‐catalytic reduction (SNCR) on the other unit (ST3).  

AEPCO needs to demonstrate that their Alternative control scenario produces equivalent or

better visibility improvements at Class I areas than the EPA SCR BART control scenario.  This

demonstration needs to account for the tradeoffs in visibility impacts associated with the

AEPCO ST2 and ST3 SO2, NOX and PM emissions for the EPA SCR BART scenario (lower NOX)

versus AEPCO Alternative (lower SO2).  The CALPUFF dispersion model (V5.8) is used to

calculate the visibility impacts at Class I areas for the EPA SCR BART and AEPCO Alternative

emission scenarios.

One key assumption in comparing the visibility impacts of the EPA BART and AEPCO Alternative

emission scenarios is the level of PM emissions from the natural gas fired ST2 EGU in the AEPCO

Alternative.  EPA’s CALPUFF modeling of natural gas‐fired ST2 in the AEPCO Alternative initially

used a PM emissions factor of 0.01 lb/MMBtu that is based on EPA’s AP‐42 emissions factor

report.  EPA’s CALPUFF modeling performed sensitivity tests assuming that the 0.01 lb/MMBtu

emissions factor was just the filterable portion of the PM and was the total PM emissions

(filterable plus condensable).  When assuming that the 0.01 lb/MMBtu PM emissions factor is

just the filterable portion of the PM, EPA used the NPS speciation profiles for natural gas that

assumes the condensable PM emissions is three times the filterable component (i.e., 0.04

lb/MMBtu total emissions).  It should be noted that the AP‐42 PM emissions factors for total,

filterable and condensable PM emissions are 0.0075, 0.0019 and 0.0056 lb/MMBtu,

respectively1.   

The data used to develop the AP‐42 natural gas combustion PM emissions factor are outdated,

sparse and based on test data that are highly influenced by positive measurement bias.  As part

of the development of the National Emissions Inventory (NEI), EPA provided guidance for

updated natural gas PM emissions factors based on newer measurement technology that is

more sensitive and accurate and does not exhibit the positive measurement bias artifact.  EPA’s

                                                      

1 http://www.epa.gov/ttnchie1/ap42/ch01/final/c01s04.pdf
    

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new natural gas combustion total PM10 emissions factor is 0.00042 lb/MMBtu2.  The use of the

updated natural gas PM emissions factor will result in a more accurate assessment of the

visibility benefits of the AEPCO Alternative emissions control for the Apache EGU.

BACKGROUND

The Regional Haze Rule (RHR) goal is to achieve natural visibility conditions at Class I areas by

2064.  One component of the RHR is the Best Achievable Retrofit Technology (BART) program

that implements BART emission controls on specific existing point sources for emissions that

have been shown to cause or contribute to visibility impairment at a Class I area.  Such visibility

precursor emissions include sulfur oxides (SOX or SO2), oxides of nitrogen (NOX) and particulate

matter (PM).

Arizona Electric Power Cooperative (AEPCO) operates the Apache Electrical Generation Unit

(EGU) that consists of two ~175 Megawatt (MWe) electrical generating boilers (Stacks 2 and 3;

ST2 and ST3).  The two Apache EGUs (ST2 and ST3) are duel‐fired boilers that are designed to

operate on either coal or natural gas, with coal being the primary fuel that they are permitted

to use.  The Arizona Department of Environmental Quality (ADEQ) has determined that the two

Apache EGUs are BART‐eligible.  The U.S. Environmental Protection Agency (EPA) has

determined that BART for the NOX emissions from the two Apache coal‐fired EGUs is selective

catalytic reduction (SCR) that achieves a 0.07 lb/MMBtu NOX emissions rate.  AEPCO has

proposed an alternative to EPA’s proposed BART controls that would convert Apache ST2 to

natural gas and install selective non‐catalytic reduction (SNCR) on ST3.  Thus, the differences in

visibility impacts due to the EPA BART and AEPCO Alternative control scenarios will hinge on the

differences in visibility impacts associated with the different SO2, NOX and PM emissions of the

two control scenario, with the EPA BART scenario having lower NOX and the AEPCO Alternative

scenario having lower SO2 emissions.

Both EPA Region 9 and ENVIRON for AEPCO are performing CALPUFF visibility modeling to

estimate the visibility impacts due to the AEPCO Apache EGUs under the EPA BART and AEPCO

Alternative emission scenarios.  One important input is the amount PM emissions from natural

gas‐fired boilers associated with the AEPCO Alternative proposal to switch ST2 from coal to

natural gas.  AP‐42 and most measurements using EPA methods show that condensable PM

dominates total measured PM emissions from natural gas‐fired sources (Corio and Sherwell,

2000).  EPA has been using a PM emissions factor based on the old (1990) Method 202 which

significantly overstates condensable PM emissions from natural gas‐fired sources because of

known SO2/sulfate interference and sensitivity issues.  The natural gas PM emissions factor has

been updated and the latest emissions inventories developed by EPA (e.g., 2011 NEI) use a

more accurate and much lower PM emissions factor for natural gas boilers.  This Memorandum

describes the new natural gas PM emissions factor and explains why it should be used to obtain

a more accurate assessment of the visibility benefits of the AEPCO Alternative BART control.

                                                      

2 See tab “Final table with NG Adjustments” of spreadsheet

“natgas_procgas_lpg_pm_efs_not_ap42_032012_revisions.cls” under “PM EFs for Natural Gas Combustion” on

2011 NEI website (http://www.epa.gov/ttnchie1/net/2011inventory.html)
    

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PRIMARY PM EMISSIONS FROM NATURAL GAS‐FIRED BOILERS

Primary particulate matter (PM) emissions from gas‐fired external combustion sources (such as

the Apache ST2 and ST3 boilers when operated on natural gas) are extremely low over a wide

range of normal operating conditions.  EPA’s Compilation of Emission Factors ‐ commonly

known by its EPA report number, AP‐42 – provides emission factors for particulate matter (PM)

emissions from natural gas‐fired external combustion sources (USEPA, 1998a).  The data used

to generate these emission factors are outdated, sparse and based on test methods that are

subject to uncontrolled, positive measurement bias.  EPA derived an alternative, lower gas‐fired

boiler primary PM2.5 emission factor for use in National Emissions Inventories (NEIs), based on

newer test measurements using a more sensitive and accurate research method. ENVIRON

recommends using the newer emission factor for the AEPCO Alternative scenario, which we

consider to be more representative of actual PM10/PM2.5 emissions from gas‐fired external

combustion sources, for assessing air quality and visibility impacts associated with changes in

source emissions.

For gaseous fuels, primary particles originate from sulfur in the fuel, a very small fraction of

which may be converted to sulfuric acid aerosol, and from soot and certain semi‐volatile

organic compounds that may be both generated and consumed during the combustion process

under some conditions.  Mineral matter and ash that contribute to particulate emissions from

coal‐ and oil‐fired combustion sources are absent from natural gas fuels.  Substantially all of the

primary particles emitted from gas‐fired external combustion sources are expected to be equal

to or smaller than 2.5 micrometers aerodynamic diameter (PM2.5) because they form via

nucleation and condensation of vapors as the gases cool in the process and atmosphere.   

At 40 CFR 51, §51.50, U.S. EPA defines primary particles as follows: “Particulate Matter (PM).

Particulate matter is a criteria air pollutant. For the purpose of this subpart, the following

definitions apply:

(1) Filterable PM2.5 or Filterable PM10: Particles that are directly emitted by a source as a

solid or liquid at stack or release conditions and captured on the filter of a stack test

train.  Filterable PM2.5 is particulate matter with an aerodynamic diameter equal to or

less than 2.5 micrometers.  Filterable PM10 is particulate matter with an aerodynamic

diameter equal to or less than 10 micrometers.

(2) Condensable PM: Material that is vapor phase at stack conditions, but which condenses

and/or reacts upon cooling and dilution in the ambient air to form solid or liquid PM

immediately after discharge from the stack.  Note that all condensable PM, if present

from a source, is typically in the PM2.5 size fraction, and therefore all of it is a component

of both primary PM2.5 and primary PM10.

(3) Primary PM2.5: The sum of filterable PM2.5 and condensable PM.
    

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(4) Primary PM10: The sum of filterable PM10 and condensable PM.”

PM EMISSIONS TEST METHODS

Because EPA defines primary particles in terms of material collected in a stack test train, it’s

important to consider the test methods upon which PM emission factors are based.  Filterable

PM and condensable PM are defined entirely by the test methods used to measure them.  

There are two types of test methods for particulate matter considered here:

 Hot filter/iced impinger methods; and

 Dilution methods.

Hot Filter/Iced Impinger Methods

These methods draw a stack gas sample through a heated filter and then through a series of

iced impingers to cool the sample and collect condensed vapors.  The material on the filter and

upstream is termed filterable or “front half” PM and the material in the impingers is termed

condensable or “back half” PM.  The amount of material collected is determined by weighing

(gravimetrically).  EPA first promulgated Method 5 for measuring PM emissions from stationary

sources in 1977 (USEPA, 1977; 40 CFR 60, Appendix A).  EPA Method 5 determines total PM

collected in a sampling probe and on a heated filter and, optionally, in iced impingers placed

downstream of the filter.  In the impingers, the filtered sample gas bubbles through chilled

water to cool the gas to 20°C or lower, causing certain constituents with dew points above this

temperature, such as sulfuric acid, to condense and become captured in the impinger liquid.  

The liquid solutions optionally may be evaporated and dried, and the mass of the dried residue

determined gravimetrically to determine condensable PM.  Prior to passage of PM10 ambient

air quality standards in 1986, few states and regions required measurements of condensable

PM because it was considered an insignificant part of total particulate emissions.   

In 1991, with the advent of PM10 ambient air quality standards, EPA promulgated Method 202

for determining condensable particulate matter (USEPA, 1991), in part because it recognized

that condensable PM would comprise a more significant fraction of PM10 than total PM.  The

method specified similar iced impinger equipment as used in Method 5, with the addition of an

optional filter (seldom used), and specified a different procedure for analyzing the sample

which defined organic and inorganic condensable PM fractions by first extracting the liquid

impinger sample with a solvent.  The method also allowed a variety of options intended to

capture various state and local regulatory agency practices.  During Method 202 development,

EPA observed interferences from sulfur dioxide gas (SO2) and volatile organic compounds, and

the method specifies an optional post‐test purge of the sampling train to minimize these

interferences (DeWees et al., 1989, 1990).  Others subsequently reported significant positive

bias in Method 202 results from SO2 when testing coal fired power plants (Filadelfia et al., 1996)

and cement plants (Holder et al., 2001).   

In 2010, EPA revised its test methods for PM10 to add filterable PM2.5 capability to Method 201A

and revise Method 202 substantially (USEPA, 2010; 40 CFR 51, Appendix M).  The revised
    

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Method 202 adds a condenser coil and a filter to the condensable sampling equipment, and the

impingers are initially dry rather than charged with water.  The modifications were made to

minimize gas‐liquid contacting thought to be a cause of positive measurement bias. Results

with the revised Method 202 for gas‐fired combined cycle plants have been varied and, while it

shows promise of producing more accurate results, the variability of results remains large

relative to the measured concentrations (Brooks et al., 2012; Haywood et al., 2012).

Dilution Test Methods

Dilution methods cool hot exhaust gas samples by mixing the gas with filtered air, both cooling

and diluting the gas, and collecting particles in the diluted sample on a filter.  Dilution methods

collect filterable and condensable PM together on the same filter, without distinguishing

between them.  Dilution methods also duplicate conditions under which particles form as they

mix and cool in the atmosphere near the stack, producing test results that are consistent with

EPA’s definition of primary particles at 40 CFR 51, §51.50.  Dilution test methods are the

international standard for measuring particulate matter in mobile source engine tests and have

been so for several decades (e.g., ISO 8178).  Although dilution methods reproduce conditions

that govern particle formation in the atmosphere near the stack much more accurately than

hot filter/iced impinger methods, they have not been widely used for stationary sources

because the equipment is considered too bulky to transport and/or too complex to operate

under field conditions at stationary sources.  

As support for new National Ambient Air Quality Standards for PM2.5 grew in the 1990’s,

researchers began to develop and apply portable dilution samplers for characterizing fine

particle emissions from stationary sources (e.g., Hildemann et al., 1989). Dilution samplers were

used extensively in the 1990’s and 2000’s to characterize fine particles from a wide variety of

sources, including detailed chemical and physical attributes (e.g., Chow et al., 2004).  England

and Loos (1999) reported results of tests on a gas‐fired refinery process heater and a gas‐fired

refinery boiler showing much higher levels of particulate matter measured using EPA Methods

201A1/202 compared with simultaneous measurements using a research dilution method.  The

difference was attributed to the Method 201A/202 condensable PM results, which accounted

for effectively all of the PM measurable by these methods and was comprised primarily of

sulfate.  Wien et al. (2001) reported results of laboratory experiments and field tests showing

that 50‐100 percent of the sulfate in condensable PM measured using Method 202 on gas‐fired

refinery boilers and process heaters could be attributed to sulfate formed in the measurement

process during sample collection and storage prior to analysis caused by sulfur dioxide gas (SO2)

in the sample.  SO2 does not condense at atmospheric conditions and therefore does not

contribute to primary (condensable) PM emissions. Such measurement artifacts are absent in

dilution methods, thus providing an explanation for the large difference in PM emissions

measured by the two methods.  U.S. EPA subsequently developed a conditional test method for

determining PM10 and PM2.5 emissions from stationary sources by dilution sampling (USEPA,

2004), but this has not been widely applied and it lacks sufficient sensitivity for gas‐fired

sources (Matis et al., 2008; England et al., 2010).
    

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PM2.5 EMISSION FACTORS

U.S. EPA published emission factors for particulate matter from gas‐fired external combustion

sources in Compilation of Emission Factors, AP‐42 (U.S. EPA, 1998a).  The AP‐42 emission

factors are based on 21 tests of approximately 10 different units for filterable particulate

matter and only 4 tests for condensable particulate matter of an unreported number of units

(most likely one or two) performed between 1990 and 1995 (USEPA, 1998b).  The AP‐42 natural

gas PM emission factors (as shown in Table 1a) indicate that 75 percent of total PM emissions

are from condensable PM.  Corio and Sherwell (2000) noted that condensable PM comprised

50‐90 percent of total PM10 emissions in tests of several gas‐fired sources and pointed out

anomalies suggesting positive bias in Method 202 results.  England et al. reported new PM2.5

emission factors for gas‐fired combustion sources based on results from tests of several gas‐

fired boilers, refinery process heaters, and other sources using a research dilution method

(England et al, 2004a,b; England et al., 2007).  The emission factors for natural gas‐fired boilers

and process heaters (Table 1c) are a factor of 22 to 84 lower than those published in AP‐42.  

U.S. EPA used the results of these same tests to develop new, more accurate PM2.5 emission

factors for gas‐fired sources that have been used in National Emission Inventories (NEIs)

starting in 2004 and continuing to the 2011 NEI currently under development (U.S. EPA, 2012).

The emission factors for PM10 and PM2.5 given by EPA are a factor of 15 and 18, respectively,

lower than those published in AP‐42.   

Although England and USEPA used the same test results, the emission factors are slightly

different because of differences in approach.  Yet, both derived PM2.5 emission factors that are

at least an order of magnitude lower than those given in AP‐42.  Because the overwhelming

significance of condensable PM measurement artifacts for gas‐fired sources was discovered

subsequent to publication of PM emission factors in AP‐42, emissions estimates based on AP‐42

will be significantly higher than actual emissions.  More recent tests using dilution methods that

simulate conditions in the stack gas plume as it mixes with the atmosphere indicate that actual

PM2.5 emissions from natural gas combustion are substantially lower than AP‐42 would predict.  

Because dilution methods are not affected by the artifacts inherent in hot filter/iced impinge

methods, ENVIRON considers emission factors based on dilution methods to be more accurate.  

Therefore, ENVIRON recommends using EPA’s NEI primary PM2.5 emission factor for modeling

the visibility impacts of AEPCO Alternative.
    

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USE OF UPDATED PM2.5 EMISSIONS FACTORS IN CALPUFF

A 0.00042 lb/MMBtu natural gas PM2.5 emissions factor for ST2 in the AEPCO Alternative would

correspond to a PM2.5 emissions rate of 0.0209 lb/hr and 0.1160 gm/s using the maximum daily

heat rate of 2192.583 MMBtu/hr for AEPCO Apache ST2.  England and co‐workers (2007)

reported PM2.5 speciation profiles for gas‐fired boilers using the dilution measurement

technology of 61% OC, 13% EC, 6.9% SO4 and the remainder (19.1%) as various elements.  Note,

this speciation profile is applicable only to PM emission factors derived from dilution methods.

This results in the following PM2.5 emissions for CALPUFF modeling of the natural gas‐fired St2

EGU in the AEPCO Alternative emissions scenario:

OC    = 0.07076 gm/s

EC    = 0.01508 gm/s

SO4    = 0.00800 gm/s

Other PM2.5 = 0.02216 gm/s

   
    

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REFERENCES

API.  2001a. Gas‐Fired Boiler – Test Report Site A: Characterization of Fine Particulate Emission

Factors and Speciation Profiles from Stationary Petroleum Industry Combustion Sources,

Publication No. 4703, American Petroleum Institute, Washington, D.C.

API.  2001b. Gas‐Fired Heater – Test Report Site B: Characterization of Fine Particulate Emission

Factors and Speciation Profiles from Stationary Petroleum Industry Combustion Sources,

Publication No. 4704, American Petroleum Institute, Washington, D.C.

API.  2001c. Gas‐Fired Steam Generator – Test Report Site C: Characterization of Fine

Particulate Emission Factors and Speciation Profiles from Stationary Petroleum Industry

Combustion Sources, Publication No. 4712, American Petroleum Institute, Washington,

D.C.

Brooks, J., England, G.C., Hogan, J. and Ponder, T.  2012. Evaluation of New Methods for

Determining Filterable and Condensable PM10/2.5 Emissions from Natural Gas‐Fired

Combined Cycle Power Plants, in proceedings of the 105th Annual Conference &

Exhibition, Air & Waste Management Association, Pittsburgh, Pennsylvania.

Chow, J.C., J.G. Watson, H. Kuhns, V. Etyemezian, D.H. Lowenthal, D. Crow, S.D. Kohl, J.P.

Engelbrecht, M.C. Green.  2004. Source Profiles for Industrial, Mobile, and Area Sources

in the Big Bend Regional Aerosol Visibility and Observational Study, Chemosphere

54:185–208.  

Corio, L.A.; Sherwell, J. In‐Stack Condensible Particulate Matter Measurements

and Issues; J. Air & Waste Manage. Assoc. 2000, 50:207‐218.Dewees, W.G., Steinberger, S.C.,

Plummer, G.M., Lay, L.T., McAlister, G.D. and Shigehara, R.T.  1989. Laboratory and Field

Evaluation of the EPA Method 5 Impinger Catch for Measuring Condensable Matter

from Stationary Sources, in proceedings of the EPA/A&WMA Symposium on

Measurement of Toxic and Related Air Pollutants, EPA Report No. 600/89‐060, Air &

Waste Management Association, Pittsburgh, Pennsylvania.

DeWees,W.G. and Steinsberger, K.C.  1990. Test Report: Method Development and Evaluation

of Draft Protocol for Measurement of Condensible Particulate Emissions, EPA‐450/4‐90‐

012, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina.  

England, G.C. and Loos, K.R.  1999. Tests for Fine Particulate Source Profiles and Emission

Factors for Gas‐Fired Combustion Equipment, in proceedings of the specialty conference

on The Emission Inventory: Regional Strategies for the Future, Air & Waste Management

Association, Pittsburgh, Pennsylvania..

England, G.C.  2004a. Development of Fine Particulate Emission Factors and Speciation Profiles

for Oil and Gas‐fired Combustion Systems, Final Report, New York State Energy Research

and Development Authority, Albany, New York, New York.

http://www.nyserda.ny.gov//sitecore/content/Home/Publications/Research‐and‐

Development ‐ Technical‐Reports/Environmental‐Reports/EMEP‐Publications/EMEP‐

Final‐Reports.aspx (accessed March 8, 2013).
    

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England, G.C.  2004b. Development of Fine Particulate Emission Factors and Speciation Profiles

for Oil and Gas‐fired Combustion Systems, Final Report, California Energy Commissions,

Sacramento, California. http://www.energy.ca.gov/pier/project_reports/CEC‐500‐2005‐

032_to_44.html (accessed March 8, 2013).

England, G.C., J.G. Watson, J.C. Chow, B. Zielinska, M‐C. O. Chang, K. Loos, and G.M. Hidy.  2007.  

Dilution‐Based Emissions Sampling from Stationary Sources: Part 2. Gas‐fired

Combustors Compared with Other Fuel‐fired Systems, J. Air & Waste Manage. Assoc.,

57:79‐93.

England, G.C. and Brooks, J.  2010. Estimated PM10 Emission Quantitation Limits using

Traditional and Dilution Methods at a Gas‐Fired Combined Cycle Plant, in proceedings of

the Symposium on Air Quality Measurement Methods and Technology, Air & Waste

Management Association, Pittsburgh, Pennsylvania.

Filadelfia, E. J. and McDannel, M. D.  1996. Evaluation of False Positive Interferences Associated

with the Use of EPA Method 202, in proceedings of the 89th Annual Meeting and

Exhibition, Air and Waste Management Association, Pittsburgh, Pennsylvania.

Haywood, J.M., Kagolanu, R., Mahew, W. and Liang, K.  2012. Revised USEPA Particulate Matter

Testing Methodology Evaluated on a Gas Turbine, in proceedings of the 105th Annual

Conference & Exhibition, Air & Waste Management Association, Pittsburgh,

Pennsylvania.

Hildemann, L.M., Cass, G.R. and Markowski, G.R.  1989. A dilution stack sampler for organic

aerosol emissions: Design, characterization, and field tests. Aerosol Sci. and Technol.

10:193‐204.

Holder, T.E., Goshaw, D.G. and Richards, J.R.  2001. Artifact Formation in Method 202 Sampling

Trains Used to Measure Condensible Particulate Matter Emissions from Portland

Cement Kilns, in proceedings of the 94th Annual Conference & Exhibition, Air & Waste

Management Association, Pittsburgh, Pennsylvania.

Matis, C., G.C. England, K. Crosby and G. Rubenstein. 2008. Field Demonstration of a Dilution‐ 

Based Particulate Measurement System, in proceedings of the Symposium on Air

Quality Measurement Methods and Technology, Air & Waste Management Association,

Pittsburgh, Pennsylvania.  

USEPA.  1977. Federal Register, 42:41754

USEPA.  1991. Federal Register, 56:65433.

USEPA.  1998a. Section 1.4 – Natural Gas Combustion, in Compilation of Air Pollutant Emission

Factors, 5th ed: EPA AP‐42, United States Environmental Protection Agency, Research

Triangle Park, North Carolina.

USEPA. 1998b. Emission Factor Documentation for AP‐42 Section 1.4 Natural Gas Combustion,

Compilation of Air Pollutant Emission Factors, 5th ed: EPA AP‐42, United States

Environmental Protection Agency, Research Triangle Park, North Carolina.
    

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USEPA.  2004. Conditional Test Method 39: Measurement of PM2.5 and PM10 Emissions by

Dilution Sampling (Constant Sampling Rate Procedures), Revised 7/04, U.S.

Environmental Protection Agency, Research Triangle Park, North Carolina.

http://www.epa.gov/ttn/emc/ctm.html (accessed March 8, 2013)

USEPA.  2010. Methods for Measurement of Filterable PM10 and PM2.5 and Measurement of

Condensable PM Emissions From Stationary Sources, Federal Register, 75:244 80118.

USEPA.  2012. PM Emission Factors for Natural Gas Combustion, U.S. Environmental Protection

Agency, Research Triangle Park, North Carolina.

http://www.epa.gov/ttn/chief/net/2011inventory.html (accessed March 8, 2013).

Wien, S., G.C. England, K.R. Loos, and K. Ritter.  2001. Investigation of Artifacts in Condensable

Particulate Measurements for Stationary Combustion Sources, in proceedings of the

94th Annual Conference and Exhibition, Air & Waste Management Association,

Pittsburgh, Pennsylvania.  

Wien, S., England, G.C. and Chang, M.C.  2003. “Development of Fine Particulate Emission

Factors and Speciation Profiles for Oil and Gas‐fired Combustion Systems, Topical

Report: Test Results for a Gas‐Fired Process Heater (Site Alpha),” prepared for: U.S.

Department of Energy, National Energy Technology Laboratory, Pittsburgh, PA; Gas

Research Institute, Des Plaines, Illinois; and American Petroleum Institute, Washington,

D.C.  http://www.nyserda.ny.gov//sitecore/content/Home/Publications/Research‐and‐

Development‐Technical‐Reports/Environmental‐Reports/EMEP‐Publications/EMEP‐

Final‐Reports.aspx (accessed March 8, 2013).

Wien, S., England, G.C. and Chang, M.C.  2004b. “Development of Fine Particulate Emission

Factors and Speciation Profiles for Oil and Gas‐fired Combustion Systems, Topical

Report: Test Results for a Gas‐Fired Process Heater with Selective Catalytic Reduction

(Site Charlie),” prepared for: U.S. Department of Energy, National Energy Technology

Laboratory, Pittsburgh, PA; Gas Research Institute, Des Plaines, Illinois; and American

Petroleum Institute, Washington, D.C.  

http://www.nyserda.ny.gov//sitecore/content/Home/Publications/Research‐and‐

Development‐Technical‐Reports/Environmental‐Reports/EMEP‐Publications/EMEP‐

Final‐Reports.aspx (accessed March 8, 2013).

Wien, S., England, G.C. and Chang, M.C.  2004c. “Development of Fine Particulate Emission

Factors and Speciation Profiles for Oil and Gas‐fired Combustion Systems, Topical

Report: Test Results for Dual Fuel‐Fired Commercial Boiler at Site Delta,” prepared for:

U.S. Department of Energy, National Energy Technology Laboratory, Pittsburgh, PA; Gas

Research Institute, Des Plaines, Illinois; and American Petroleum Institute, Washington,

D.C. http://www.nyserda.ny.gov//sitecore/content/Home/Publications/Research‐and‐

Development‐Technical‐Reports/Environmental‐Reports/EMEP‐Publications/EMEP‐

Final‐Reports.aspx (accessed March 8, 2013).