7272 E. I NDIAN S CHOOL R OAD

, S UITE 360

S COTTSDALE

, A RIZONA 85251

T ELEPHONE : 480-505-3900

F ACSIMILE : 480-505-3901

E RIC L. H ISER

D IRECT L INE : 480-505-3927

e-mail: ehiser@jordenbischoff.com 

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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 (A R) 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. Perciase pe and Blumenfeld:

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

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

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

Implementation Plans; Arizona; Regional Haze Stat e and Federal Implementation Plans” in the

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

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

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

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

unaffordable, requested clarificati on of the application of the BART limits to Apache Generating

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

provisions adopted as part of th e compliance provisions of the BA RT FIP. AEPCO also stated

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

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

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

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

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

they believe AEPCO’s tentativ e recommendation at the Februa ry 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 su fficient merit to warrant a formal proposal

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

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

setting forth its proposed a lternative 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 representa tives, AEPCO is proposing that the following

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

and 3 (“ST3”). AEPCO believes that this proposa l 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 fr om coal to natural gas on December 5,

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

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

combination of technologies and pollutant limits:

Particulate Matter: Pipeline Na tural Gas (“PNG”), 0.01 lb PM Total /MMBtu 30-day rolling

average, dropping to 0.008 lb PM Total /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/MMB tu 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 pipelin e failure, freeze-up or pipeline

compression failure that reduces gas volume or gas pressure below that

necessary for Apache Generating Stat ion gas generation. AEPCO must

discontinue coal firing as expeditiously as possibl e after restoration of

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

event more than 48 hours after re storation of such service.

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

process adjustments or add-on contro ls, 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 princi pal fuel, with natural gas and co-firing of

coal and natural gas as alternat ive operating scenarios, for ST 3. 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 PM Filterable /MMBtu 30-day

rolling average.

Sulfur Dioxide: SO 2 scrubbers, 0.15 lb/MMBtu, 30-day rolling average.

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

rolling average.

Flexibility Provision: AE PCO may comply with the BART c ontrols through any combination of

fuels, process adjustments, or a dd-on controls, provided that such

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

average basis) and complies with applicable regulations and permits and

AEPCO obtains any necessary preco nstruction or operating approvals.

EPA inquired whether AEPCO’s SNCR installati on 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 lik ely be on the order of 0.225 lb /MMBtu, but this cannot be

achieved on a 30-day rolling av erage in all cases and AEPC O is not proposing the 0.225

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

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

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

BART Timing

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

approval (for PM and SO 2 ) and FIP (for NOx), except that sp ecific deadlines are adjusted to

accommodate the ST2 conversion to natural gas, as follows:

ST1: Unchanged

ST2: NOx effective December 5, 2017

SO 2 0.15 lb/MMBtu effective December 5, 2016

SO 2 0.00064 lb/MMBtu effective December 6, 2017

PM 10-Filterable 0.03 lb/MMBtu effective December 5, 2016

PM 10-Total 0.01 lb/MMBtu effective December 5, 2017

PM 10-Total 0.008 lb/MMBtu effective December 5, 2018

ST3: NOx effective December 5, 2017

SO 2 effective December 5, 2016

PM 10-Filterable effective December 5, 2016

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

from the original SIP approval and FIP promul gation effective date, the implementation date

would be tolled on a day-by-day basis to account fo r 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 woul d be upon termination of the stay (assuming theSupplement to Petition for Administrative Reconsideration

Arizona Electric Power Cooperative, Inc.

May 29, 2013

Page 4

rule is upheld). If the proposal is invalidate d, 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, mon itoring, and our general understanding of

regional haze that the visibility benefits of its proposal will be better than t hose 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 re ductions 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 reducti ons 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 SO 2 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 1182.91Supplement 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 a lternative will result in reducing an estimated

1288 tons of SO 2 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 achie ves better than BART

levels of reduction. As discussed below, AEPCO’ s alternative also achiev es 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 Partners hip (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 EP A’s base case and SCR case and compared

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

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

comparison of the CALPUFF modeling re sults for both the average of the 98 th percentile for the

three years 2001-2003 or the 22 nd 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 NOxSupplement 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 “CAL PUFF Visibility Modeli ng of the AEPCO BART

Scenarios” dated May 10, 2013.

In the ENVIRON report, the AEPCO propos al is Version 2 of AEPCO Alternative

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

follows:

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

EPA BART SCR 98 th Percentile Avg 98 th 22 nd 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 98 th Percentile Avg 98 th 22 nd 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 0.795Supplement 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 98 th Percentile Avg 98 th 22 nd 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, AEPC O’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 ar eas show a marginal increase (of +0.004 and

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

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

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

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

EPA’s current BART FIP. AEPC O’s proposal thus achieves “bette r 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 nece ssarily representative of visi bility 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 AE PCO’s proposed alternativ e 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 98 th percentile basis), or -0.005 to -0.275 dv (22 nd high

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

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

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

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

clearly better than BART.

Finally, as ENVIRON notes in its two atta ched reports, the natu ral 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 gr eater improvements, as seen in Attachment C

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

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

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

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

inherent in the review of alternatives, AEPC O believes that the weight of the evidence

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

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

memorandum entitled “Updated PM 2.5 Emissions Factors for Natura l 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 bot h sulfate (derived in

part from SO 2 emissions) and particulate (der ived in part from direct PM 2.5 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 “SO 4 Extinction” and gray “CM (f or coarse matter) Extinction”

are generally much more si gnificant than the red “NO 3 Extinction” factor, based on the

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

“worst” days clearly shows the impact of SO 4 and CM versus NO 3 :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 imp act). 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 vi sibility by as much, or more than, equivalent

reductions in nitrate.

Third, the Arizona Regional Haze SIP found, a nd 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 SO 4 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 m onitoring data and general direction of

emissions reduction needed to achieve the natura l 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 th at its proposal, which substantially reduces

emissions of SO 2 and PM while increasing NOx emissions more modestly, will achieve “better

than BART” visibility improvement.

AEPCO therefore formally requests that EP A 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 reconsider ation, 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 lim its. GT1 is a simple cycle turbine that can

exhaust to the ST1 windbox; can be used to warmand 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 a ddressing this issue.

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

After reviewing the company's BART analysis, an d 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) w ith 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 alon e 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 wh ich ADEQ has requested parallel processing)

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

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

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

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

GT1 are clear.

Limit Achievability and Averaging

In its petition for administrative reconsid eration, AEPCO expresse d concern about the

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

violation of a limit when AEPCO has shutdown the unit causing the “average” limit to beSupplement 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 mainte nance is likely to cause increased problems,

including trips, upon restart, potentiall y prolonging the peri od 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 un it is operating is met when the operating

unit meets its individual NOx limits.

Proposed revisions to the existi ng FIP compliance language are att ached for EPA’s consideration

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

to the other utilities. AEPCO be lieves 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 achie ve 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 bur den 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 Se rvices, 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 consid eration and continued disc ussion to see if EPAProposed 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), t he

owner/operator of each coal-fired unit subject to this para graph (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, SO 2 or PM 10 in

excess of the following limitations, in pounds per millio n 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 SO 2 PM 10 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 MMBt u * 0.085 lb/MMBtu) + (Unit 3 MMBtu * 0.23

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

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

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

(B) each unit meets its indivi dual 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), t he owners/operators of each unit subject to this paragraph (f) shall

comply with the applicable PM10 and SO2 emissions limits su bmitted 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 re porting 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 PM 10 and SO 2 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 NO X and SO 24 1 —(i) Continuous emission monitoring system. (A) At all times

after the compliance date specified in paragraph (f)(4) of this section, th e 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 SO 2 , NO X , diluent, and stack gas volumetric flow rate from each unit. In addition, the

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

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

dioxide control device. Apache Unit 1 NO X 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 NO X and SO 2 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 cal culate 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 SO 2 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 NO X and SO 2 pounds per hour measurem ent and the heat input

measurement. The CEMs monitoring data shall not be bias adjusted. The inlet SO 2 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 calcu lations of relative accuracy for lb/hr of NO X , SO 2 and heat input shall

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

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

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

in 40 CFR Part 75, Appendix D.

(ii) Compliance determinations for NO X . (A) The 30-day rolling average NO X 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 NO X emitted during the current boiler-operating day (or most rece nt boiler-operating day if the unit is not in operation),

and the preceding twenty-n ine (29) boiler operatin g days, to calculate the total pounds of NO X 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 (o r most recent boiler operating day if the unit is not in

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

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

divide the total pounds of NO X 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 em ission rate, in pounds of NOx per MMBtu, for each

1 The Federal Register version states SO 4 , not SO 2

.Proposed FIP Language

Arizona Electric Power Cooperative, Inc.

May 29, 2013

Page 3

calendar day; step four 3 , sum together the total pounds of NO X 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 five fou r, 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 six five , divide the total pounds of NO X emitted from step four for each group of coal-fired units three by the total heat input from step five four for each

group of coal-fired units, to calculate the 30-day rolling average NO X emission rate for each group of coal-fired

units, in pounds of NO X per MMBtu, for each calendar day. Each 30-day rolling average NO X 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 NO X limit as calculated in step three or (II) if the group of oper ating coal-fired units

meets its combined NO X limit as calculated in step six.

(B) The 30-day rolling average NO X emission rate for Apache Unit 1 shal l be calculated in accordance with the

following procedure: step one, sum the total pounds of NO X emitted from the unit during the current boileroperating day and the previous twenty-nine (29) boiler-operatin g 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 NO X emitted during the thirty (30) boiler-operating days by the total heat

input during the thirty (30) boiler opera ting days. A new 30-day rolling average NO X emission rate shall be

calculated for each new boiler-operating day. Each 30-day rolling average NO X 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 NO X pounds per hour or heat input is not available for any hour for a unit, that heat input and NO X pounds per hour shall not be used in the calculation of the 30-day rolling average.

(iii) Compliance determinations for SO 2

. (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) sh all demonstrate compliance

with the SO 2 limits through use of pipe line 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 paragrap h (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 wi th its Phase 2 particulate matter emission limit within

90 days of conversion to natural ga s, and shall thereafter demonstrate comp liance with its Phase 3 particulate

matter emission limit within 60 days of the compliance deadline specified in pa ragraph (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 dem onstrate compliance. Each test shall consist of three runs,

with each run at least 120 minutes in duration and each ru n 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 mon itor particulate emissions for compliance with

the emission limitations in accordance with the any 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.773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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1 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) NO X 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 NO X 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).773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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2 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 98 th percentile (8 th highest in a year) visibility metrics across the three years of

modeling (2001

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

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 (SO X or SO 2 ), oxides of nitrogen (NO X ) 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

‐ eligible 1

. The U.S. Environmental Protection Agency (EPA) has determined that BART for the NO X

emissions from the two Apache coal

‐ fired EGUs is selective catalytic reduction (SCR) that

achieves a 0.07 lb/MMBtu NO X 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

SO 2 , NO X and PM emissions of the two control scenario, with the EPA SCR BART scenario having

lower NO X and the AEPCO Alternative scenario having lower SO 2 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/773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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3 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 98 th percentile daily

change in Haze index, commonly referred to as deciview ( Δ dv), 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 database 2 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 BART 3

. 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.773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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4 Preliminary CALPUFF Visibility Modeling

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

Base, EPA SCR BART (NO X 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 NO X

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 SO 2 NO X 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 0.010 a

ST3 0.150 0.230 0.030

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

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 0.008 a

ST3 0.150 0.225 0.030

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

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 turbines 4 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/ectGasF iredCT.cfm?CFID=5318051& CFTOKEN=bb591 d8a00830488

‐

94B1977A

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5 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 NO X 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 17.68 394.261 a

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 17.68 394.261 a

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 17.68 394.261 a

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.773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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

assumes Low NO X 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 EPA 5 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 98 th 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 SO 2 SO 4 NO X 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%

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7 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.773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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8 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) 98 th Percentile Avg 98 th 22 nd 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) 98 th Percentile Avg 98 th 22 nd 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%

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9 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.773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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10 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 emissions 6

. 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.pdf773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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11 National Emissions Inventory (NEI 7 ). 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 98 th percentile

(8 th 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 98 th percentile across the three

modeling years and the 98 th percentile across all three years combined (i.e., the 22 nd 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., 98 th 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/ttnchie 1/net/2011inventory.html773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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12 Table 4a. Percent difference in 98 th 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 98 th Percentile Avg 98 th 22 nd 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 98 th 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 98 th Percentile Avg 98 th 22 nd 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%

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13 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 98 th 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 98 th percentile across the three years of modeling (i.e., 22 nd

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 98 th 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 98 th Percentile Avg 98 th 22 nd 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%

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14 Version 2 of AEPCO Alternative Control 9 and 9b

The AEPCO Alternative Control 9v2 and 9bv2 used slightly lower PM emissions for ST2 and NO X

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 98 th 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 98 th Percentile Avg 98 th 22 nd 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 98 th 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 98 th Percentile Avg 98 th 22 nd 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%

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15 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 98 th 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 98 th Percentile Avg 98 th 22 nd 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%773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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16 Table 7b. Percent difference in 98 th 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 98 th Percentile Avg 98 th 22 nd 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 98 th 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 98 th Percentile Avg 98 th 22 nd 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%

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17 Table 7d. Percent difference in 98 th 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 98 th Percentile Avg 98 th 22 nd 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 98 th 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 98 th Percentile Avg 98 th 22 nd 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%

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18 

### 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 (98 th

percentile averaged across 2001

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

Apache’s SO 2 , NO X 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 SO 2 or NO X

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 NO X emissions in the AEPCO Alternative versus the higher

SO 2 emissions in the EPA SCR BART emissions scenarios.

Table 8 lists the total SO 2 and NO X emissions from Apache ST1, ST2 and ST3 for the EPA SCR

BART and Apache Alternative emission scenarios and compares them with the total SO 2 and

NO X emissions for Arizona from the WRAP Plan02d (representing 2000

‐ 2004 baseline) and the

Prp18b (2018) emissions scenarios that were downloaded from the WRAP TSS website 8

. For

both Apache control scenarios, the Apache SO 2 and NO X 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 SO 2 and NO X emissions with total emissions in Arizona (tons per year).

Scenario SO 2 (tpy) NO X (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 SO 2 emissions (yellow) is always much greater than that due to NO X

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 SO 2 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 NO X

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.e du/TSS/Results/Emissions.aspx773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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19 In fact, despite NO X emissions being 3.3 (Plan02d) to 1.4 (Prp18b) times higher than SO 2

emissions in Arizona (Table 8), visibility impairment due to SO 2 emissions is from 4.6 (2002) to

7.8 (2008) times greater than visibility impairment due to NO X emissions at Chiricahua. This is

due in part because SO 2 emissions are converted to particulate sulfate that impairs visibility,

whereas NO X 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 NO X emissions staying as nitric acid rather than

converting to particulate nitrate.

Given that SO 2 emissions are more important than NO X 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.773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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20 Figure 3. Daily visibility extinction during 2001 (top), 2002 (middle) and 2003 (bottom) at the

Chiricahua Class I area.773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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21 Figure 4. Measured annual visibility extinction at Chiricahua Class I area for 2000

‐ 2011.773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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22 

### 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 ).773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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23 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)773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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24 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) 98 th Percentile Avg 98 th 22 nd 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) 98 th Percentile Avg 98 th 22 nd 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) 98 th Percentile Avg 98 th 22 nd 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 0.000773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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25 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 98 th Percentile Avg 98 th 22 nd 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 98 th Percentile Avg 98 th 22 nd 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) 98 th Percentile Avg 98 th 22 nd 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 0.000773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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26 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) 98 th Percentile Avg 98 th 22 nd 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) 98 th Percentile Avg 98 th 22 nd 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) 98 th Percentile Avg 98 th 22 nd 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

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27 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) 98 th Percentile Avg 98 th 22 nd 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) 98 th Percentile Avg 98 th 22 nd 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) 98 th Percentile Avg 98 th 22 nd 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

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28 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)773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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29 Attachment B1: EPA BART SCR vs. AEPCO Alternative Control 9 (PNGf) monthly ammonia.

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

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

98 th Percentile Avg 98 th 22 nd 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 0.187773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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30 Attachment B2: EPA BART SCR vs. AEPCO Alternative Control 9b (PNGt) monthly ammonia.

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

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

98 th Percentile Avg 98 th 22 nd 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

‐ 0.096773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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31 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 ST2773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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32 Attachment C1: EPA BART SCR vs. AEPCO Alternative with Updated PM monthly ammonia.

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

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

‐ 0.19773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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33 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)773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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34 Attachment D1: EPA BART SCR vs. AEPCO Alternative Control 9v2 (PNGf) monthly ammonia.

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

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

98 th Percentile Avg 98 th 22 nd 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 0.102773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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35 Attachment D2: EPA BART SCR vs. AEPCO Alternative Control 9bv2 (PNGt) monthly ammonia.

AEPCO CALPUFF Results Impact in Deciviews: Monthly Ammonia

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

98 th Percentile Avg 98 th 22 nd 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

‐ 0.118773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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36 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)773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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37 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 98 th Percentile Avg 98 th 22 nd 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 98 th Percentile Avg 98 th 22 nd 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 98 th Percentile Avg 98 th 22 nd 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 0.251773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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38 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 98 th Percentile Avg 98 th 22 nd 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 98 th Percentile Avg 98 th 22 nd 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 98 th Percentile Avg 98 th 22 nd 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

‐ 0.030773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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39 Attachment E3: EPA BART SCR vs. AEPCO Alternative with Update PM Emissions.

AEPCO CALPUFF Results Impact in Deciviews: 1 ppb Ammonia

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

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40 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 98 th Percentile Avg 98 th 22 nd 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 98 th Percentile Avg 98 th 22 nd 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 98 th Percentile Avg 98 th 22 nd 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 0.173773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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41 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 98 th Percentile Avg 98 th 22 nd 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 98 th Percentile Avg 98 th 22 nd 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 98 th Percentile Avg 98 th 22 nd 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

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1 May 8, 2013



### MEMORANDUM

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

From: Ralph Morris and Glenn England

Subject: Updated PM 2.5 Emissions Factors for Natural Gas

‐ Fired Boilers



### SUMMARY

AEPCO is proposing an alternative to EPA’s proposed Best Available Retrofit Technology (BART)

NO X 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 SO 2 , NO X and PM emissions for the EPA SCR BART scenario (lower NO X )

versus AEPCO Alternative (lower SO 2 ). 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,

respectively 1

.

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.pdf773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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2 new natural gas combustion total PM 10 emissions factor is 0.00042 lb/MMBtu 2

. 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 (SO X or SO 2 ), oxides of nitrogen (NO X ) 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 NO X emissions from the two Apache coal

‐ fired EGUs is selective

catalytic reduction (SCR) that achieves a 0.07 lb/MMBtu NO X 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 SO 2 , NO X and PM emissions of the

two control scenario, with the EPA BART scenario having lower NO X and the AEPCO Alternative

scenario having lower SO 2 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 SO 2 /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_n ot_ap42_032012_revisions.cls” under “PM EFs for Natural Gas Combustion” on

2011 NEI website (http://www.epa.gov/ttnchie1/ net/2011inventory.html)773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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3 

### 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 PM 2.5 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 PM 10 /PM 2.5 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 (PM 2.5 ) 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 PM 2.5 or Filterable PM 10 : 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 PM 2.5 is particulate matter with an aerodynamic diameter equal to or

less than 2.5 micrometers. Filterable PM 10 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 PM 2.5 size fraction, and therefore all of it is a component

of both primary PM 2.5 and primary PM 10

.

(3) Primary PM 2.5 : The sum of filterable PM 2.5 and condensable PM.773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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4 (4) Primary PM 10 : The sum of filterable PM 10 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 PM 10 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 PM 10 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 PM 10 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 (SO 2 ) 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 SO 2 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 PM 10 to add filterable PM 2.5 capability to Method 201A

and revise Method 202 substantially (USEPA, 2010; 40 CFR 51, Appendix M). The revised773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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5 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 PM 2.5 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 (SO 2 )

in the sample. SO 2 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 PM 10 and PM 2.5 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).773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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6 

### PM 2.5 

### 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 PM 10 emissions in tests of several gas

‐ fired sources and pointed out

anomalies suggesting positive bias in Method 202 results. England et al. reported new PM 2.5

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 PM 2.5 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 PM 10 and PM 2.5 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 PM 2.5 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

PM 2.5 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 PM 2.5 emission factor for modeling

the visibility impacts of AEPCO Alternative.773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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7 

### USE OF UPDATED PM 2.5 

### EMISSIONS FACTORS IN CALPUFF

A 0.00042 lb/MMBtu natural gas PM 2.5 emissions factor for ST2 in the AEPCO Alternative would

correspond to a PM 2.5 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% SO 4 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

SO 4 = 0.00800 gm/s

Other PM 2.5 = 0.02216 gm/s773 San Marin Drive, Suite 2115, Novato, CA 94998 P: 415

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10 

### 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

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