# StateofNewMexico Officeof theGovernor BillRichardson Governor



### December26,2003 Mr. RichardE. Greene,RegionalAdministrator U.S. EnvironmentalProtectionAgency,RegionVI 1445 RossAvenue, Suite 1200 Dallas,TX 75202-2733
SUBJECT: REQUEST FOR APPROVAL OF REVISION TO THE STATE IMPLEMENTATIONPLANFORAIRQUALITY DearMr. Greene, Asprovidedby40CFRPart51,AppendixVand40CFRPart51, SubpartP,Iamwriting torequestapproval 0

### f theattacheddocumentation, whichwill serve as the basis for a revision to the State Implementation Plan (SIP) for New Mexico. Specifically, I am submitting documentation that will serve to fulfill requirements of 40 CFR 51.309, known asthe "Section309RegionalHaze SIPelement". Twocompanionregulations are also being submitted. These are 20.11.21 NMAC, Open Burning and 20.11.46 NMAC, Sulfur Dioxide Emissions Inventory Requirements; Western Backstop Sulfur Dioxide TradingProgram. The attachedproposed SIPrevisionis applicableto BernalilloCounty, NewMexico. TheAlbuquerque/Bernalillo CountyAir Quality Control Board (AQCB) approved these proposedrevisions to the SIP on November 12, 2003, after apublic review period and correspondingpublichearingsheldonOctober8, 2003 andNovember 12,2003. Thetwo regulations, 20.11.21 NMAC and 20.11.46 NMAC were filed at the New Mexiw Sfllf,e Records Center. The effective date for these regulations is December 31, 20@. believe that the submitted materials provide adequate documentation to**sup~rtul,'e** 

### requestedSIPrevision.**,,~** <..':) :' , 

### Tofacilitateyourreviewandprocessing, thefollowingmaterials areenclosed: I) SIPCompletenessChecklistspursuantto40CFR51,AppendixV - -(J 7 (.") "-, )



### ..-:-..,: u, 0 r'0 '.:": 

## m c

StateCapitol • Room400 • 

### SantaFe,NewMexico 87501 • 5°5-476-2200 • 

### www.govemor.state.nm.us-2-



### 2) Hearingrecords, includingtranscripts andexhibits 3) Commentsreceived December24,2003



### 4) The final AQCB-approved SIP revision for Regional Haze, including the two companionregulations. 5) Othersupportingdocumentation Your favorable consideration ofthis request is appreciated. Ifyou have any questions, please contact Alfredo Santistevan, Director 0

### f the AlbuquerqueEnvironmentalHealth Department, at (505) 768-2600.
Sincerely,

BillRichardson Governor StateofNewMexico

cc: Alfredo Santistevan,Director,AlbuquerqueEnvironmentalHealthDepartment SandraEly, Chief,AirQualityBureau,NewMexicoEnvironmentDepartment
Enclosures

# SECTION 309 REGIONAL HAZE STATE IMPLEMENTATION PLAN ELEMENT: ALBUQUERQUE/BERNALILLO COUNTY, NEW MEXICO**,----------~**



## FINALVERSION Appendices

September8, 2003 Revised October5, 2003
City ofAlbuquerque Environmental Health Department AirQuality Division Control Strategies Section

Reviewed and Approved after Public Hearing by: Albuquerque/Bernalillo County Alf

## Quality Control Board (AQCB)
Approval Date: November 12, 2003

# Thisdocumentcontainsthe TECHNICALSUPPORTDOCUMENT(TSD) AppendicesandtheSIPAPPENDICES. TheOTHERAPPENDICESareinseparate documents.

### TECHNICAL SUPPORT DOCUMENT (TSD) (as listed in the August27, 2003 draftfinal version)

AppendixA-TSD
Appendix B-TSD Appendix C-TSD Appendix D-TSD Appendix E-TSD Appendix F-TSD Appendix G-TSD
Appendix H-TSD
Appendix I-TSD
Appendix

### J-TSD
Appendix K-TSD

Appendix L-TSD Methods Used to Incorporate State and Local Control Programs in WRAP Emissions Inventories Use of EPA Guidance and Best Practices 1996 Base Case Emissions Used in AirQuality Modeling 2018 Base Case Emissions Used in AirQuality Modeling 2018 Scenario I Emissions Used in AirQuality Modeling 2018 Scenario 2 Emissions Used in AirQuality Modeling 2018 BARTwith Uncertainty Scenario Emissions Used in Air Quality Modeling 2018 S02Annex Milestones Scenario Emissions Used in Air Quality Modeling 2018 Stationary Source 50% NOx Reduction Scenario Emissions Used in AirQuality Modeling 2018 Stationary Source 50% PMlO Reduction Scenario Emissions Used in AirQuality Modeling 2018 Stationary Source Simultaneous 25% NOxand 25% PM10 Increase Scenario Emissions Used in AirQuality Modeling Clean Air CorridorChange in Emissions 1996to 2018AppendixA-TSO Methods Used to Incorporate State and Local Control Programs in WRAP Emissions Inventories

Overview: The purpose ofthis appendix is to provide a listofstate and local emission control programs and assumptions included in the emissions inventories prepared by WRAP contractors for §309. Documentation about the details and assumptions for each emissions inventory are contained in the individual contractors' reports, listed as references in Appendix C of this document. Federal control programs and actions are published in the Federal Register, and are incorporated into EPA emissions models in most cases, and are not listed in this appendix. Area Sources: This information is from Chapter IV "Existing Source State Regulation Analyses, Weste rn Regional Air Partnership Emission Forecasts For 2018
- Final Report", E.H. Pechan & Associates, Inc., December2002, Pechan Rpt. No. 

### 02.12.003/9409.000. This chapter describes analyses of State and Local regulations affecting criteria pollutant emissions between 1996 and 2018. Results of these analyses are organized by pollutant: PMlO, followed by NO, regulations, followed by S02. These analyses were performed in order to update the lAS model control factors so that they would reflect the expected pollution reduction effects ofState and local regulations. PM10 : Many PMlO nonattainment areas are located in the Western United States. Federal, State, and local air pollution regulations and other initiatives likely to affect point and area PMlO sources were analyzed. The focus was on PMlO sources in nonattainment areas and the control measures that areas are implementing to bring their areas into attainment. It is not expected that attainment areas would implement post-1996 control measures for PMlO and that any pre-1996 regulation effects would already be incorporated in their 1996 emission estimates. Using EPA's web site ClassificationsofPM-10NonattainmentAreas, a group oftwelve nonattainment areas were selected for analyses (EPA, 2001b). The selected areas included all of the listed serious classification nonattainment areas - Clark County, NV; Coachella Valley, CA; Los AngeleslSouth Coast Air Basin, CA; Owens Valley, CA; Phoenix, AZ; and San Joaquin Valley, CA. The selected areas also included a sampling of moderate classification nonattainment areas in the WRAP States. For the moderate classification areas, selection was also based on availability of the needed information. The selected moderate classification nonattainment areas included Aspen, CO; Anthony, NM; Klamath Falls, OR; Salt Lake County, UT; Spokane County, WA; and Sheridan, WY. Area-specific PMlO control plans and information were collected and compiled from EPA Regional Offices, and State and local agenciesforeach ofthe selected nonattainmentareas. Often the information was available via the Internetand the agencywas able to provide the web site address. Agency staffwas also interviewed to gain insight into an area's particular nonattainment situation and learn about novel or unique control measures. EPA's web site Federat Register Notices Related to PM-10 Designations and Classifications was used to identify recent actions related to the selected nonattainment areas (EPA, 2001c).
AppendixA-ISO, Page 1Pechan reviewed the gathered documents and prepared a series oftables to summarize the control measure information for each nonattainment area. This information is summarized in Tables IV-3 through lV-g. Each table presents adopted measures for a different source category. Source categories include construction, residential wood combustion, vacant land/unpaved lots, open burning, agricultural tilling, salting/sanding of paved roads, and miscellaneous sources. For use in this analysis, the information about PM,o control measures by PM10 nonattainment area was translated into a set of PM 10 control efficiencies by area that were applied as PM 10 control factors in the 2018 emissions forecast. Each table identifies the nonattainment area and names the types of measures that the area uses to control emissions of PM 10. The assumed degree of control of road dust emissions in each PM10 nonattainment area is described in the mobile sources emissions inventory report (ENVIRON, 2003). For road dust emissions, PM control measures were applied to fugitive dust emissions from paved and unpaved roads in all PM 10 nonattainment areas, with the control factors reflecting a highercontrol level in serious PM 10 nonattainment areas than was applied in moderate PM10 nonattainmentareas.
Table IV·3 ". SCC ·2311010000 IConstruction

PM

.. Nooatlainmenl FIP Nonattainment Area County Slate Designalioo Control Measures Note 

## , 2 3 

# , 

# • 6 7 32003**CI~r1\Coun\y** NY Serious 

### , , , , 06065**C~;y~tleU<i** Vallt:oy Rivf.'fsiiJe Co CA Seritlus**0605~'** Los Angeles Soulh CDasl Los A.ngeles Ca. Or<iflge Co, CA SenoL.'$ Air**B<l~>If;** Ri"crsioe Co San Beman:hnoCo 04013 Pho(!l"'.ix MancupaCo AZ Serious 

### , , 06077 San JoaqlJinValley Fresro Co, Kern Co, Kings CA Senous 

### , , , , , , 

## , Cu, Madera Co, San JooaLJin Co.**Sl~msl<hls** Co, TLdare Co 35013 Afllj".or,y D01a Ar,a Co NM Mocerall' 

## , , , 

### , , , ,: 103t> t'.!"1rI1alh Falls Klamalt1 Co OF< Moccratl' 

## , 08097 A:;pen P,IJJrl Co CO MooeralE' 49035 Sallli'tkE' COLJfil)" LIT Mooeral:' 

### , , , , ,**~30G3** Spobne County \VA Mocerale 

### , , •

NOT[S**"l',lC"w(d'!~'c,-,** ::**.C~,** @'",c"" 3lillJ ih

..**··~~ 3~O~~1**  (.""1'"(>1 "iM'**";~'hdla'** 5·", "'<11.>';<"'"**€~cO)V""** P<'Wil'

....ciu**''''~op''~~e'**...**Ol'!:II'~1 ~~t<v'trl\'~fl**  t,

AppendixA-TSD, Page2Table IV-4 :CSCC

-2104008000 I Res;denl;al Wood Combustion

PM,. Nonal1ainment FlP Nonattainm911IArea County Stale Designation Control Measufes Note 1 2 3 4 5 04013 Phoer.ix Ma-icopa Co AZ**Seri~s** 

### , , , D6077 San JoaquinValley Fresno Co. Kern Co. CA Serious 

### , , 

## , , ,**KI~.9** Co. Mader& Co, San JoaQuin Co, Stanislaus Co. TWire Co 41D35 KJamalh Falls Klamath Co OR Moder.;le 

### , , Woodsto.'i! owners must regislertheir stoves Program 10 rep\<Jce woodStoW3 In 

# ""'" 00097 Aspen PllIoar: Co CO Moderate 

## , x 49035 salt lake County UT Moocr<ll.l:l x 

### , Solid fool burning deVICes must be registered. Ban**re~1e** of**un~hfled** p-c'oiou:sly used $OliO fuel bvmirlg de'tices 53063 SlX'karoeCount,' WA Moderate 

### ,

NOTUS 1**~I:l/l" l~"**  '-lIi.,ifns"lI"I"" 0(,,,,,,,,,,,1,,,,1 ,I"".,s**l.~S""lleh** t,**~nlu'~i** gili'.**J~N"-i>,,m ll~tlV""** **~~Cq,2lOn Qd~COI{"'I'**  l""" "\lmn'" (I{

...**~,!>~ r'~'n~'9** **~I'v'r.,,~** Table IV-5 Vacant Land, Unpaved Lots

PM" Nonallainrnenl FlP NonaliainmeotArea County Slate Desi9nalion ConlrolMeasure:. Note 2 

# " 5 6 32()OJ Clarl<, COL.'1l1i NV**S€riOlJ~** 06027 Owerr.:;**V~ley** Inyo Cu CA**Serio",~** 

### • Source, Owens dry lake bed, conlrol wilh shallow nOuiino;? OGOn S<Jf1 JO<lQ\..in \I<llley fresno Co "ern Co. CA Seriuus 

### , Kings Co. Maoera Co SanJoaqoln Co StanISlaus Co,TulareCo**3~13** Anlhony Donr, Ana Co NM MDderaW 

### ,**N0TE~ l"I<~-~~~lo\l"in,~U,** **~""'a** ..**,,!9'''~'' J"P".~\'t'I~'",ll** **""~ i"l~**  ..;"'tI**''''''''''ol'-~ ~_C!"'",;**  j{;t,; ." ,:.',,'"**~',-,'" I~**  t _l"".l U,"" ,,"u**,~,laG" ~,~**  'J**~'L\~ /~""-(,t"**  Table IV-6 SCC

-261000000 I Open Burning

PM,. NOllattoinmenl FlP NQIlaUaillmentArea County Stale Designation CQnlrol Measures Nole 

## , 2 

# , , Oe077 SanJoaqvifl Valley**fre~no** Co Kern Co. CA 5enolJs 

### , , • x Adcliticnal coorols

- Edv. Progam: reduce Kings Co, Madera acres burnK:, fuel loading, ane !oo Co San Joaquin Co consumption S18nlslaus CD.Tvlare Co 41035 Klamath falls Klamath Co OR MOderate 

### , Resloonbal**o~n** burning- 2610030000 53063 Spokane County WA Moderate 

### ,

N01Vl l"'-"'I",,'!>t,

..;S re :iJIlun<l\"""**il~ lu~",**  rem uv&<,**~I'wp.n~, ~i!** **i~lu ~",r)** **2~tlu"'t_~nllO** fHH'umll(J',---' J"'R

..**q"""~IH,,'h 4~Srno<.0**  ma',ag!lm0nt**j.>l~!\**

AppendixA-TSD, Page 3Table IV·7 sec -2801000003' Agricultural Tilting

FlP NonaHainment Area A,rt>B Description Stale PM,. Nonallainmenl Designation Control Measures 0'4013 Phoenix Mari:::opa Co AZ Serious USDA. Soil COl1seryaton Pliln 06077 San Joaquin Vallc!P' Fresno Co, Kern Co CA Serioull USDA Soil**Con5~r\latioll** Plan Kings Co. Madera Co San JOilqoin Co. Slanislaus Co, Tulare Co 35013 Anthony Dona Ana Co NM Moderate USDA Soil COl1ser

...-alon Plan

" Table IV-8 -SCC • 22940000021 Salling/Sanding Paved Roads

flP NonallainmentArea Area Descriplion State PM

.. Nonaltanmenl Designalion Control Maasures 06097 Asper. Piddn Co CO Moderate Gleanerwinter 5altingiSBr; ding m alerlfiIs 49035 Sail. Lake County VT ModerEllc Clesnerwinler salling/san ding m alena Is 56033 Citjl ofSheridall Sheridan Co INY Moaerale Clea nerwinlEf sanding materiab5 Regular rnainlenance am:::: watering of sandeC paved roads Table IV-9 Miscellaneous Sources**PM,~** Nonaltainment FlP Non.lltainmenl Area County State**~signation** Source / SCC Control 3200:' ClarkCounty NV 5enCJ.1S -Induslri.al SOlXceS'·· TIghlOO emission oft's:et requimmL'flts 06077 San Jom,uin V<llIey Fresno Co, Kern Co CA 5enOlis Callie Feedlols i Kings Co. Madera Co 2805Q(J 1000 S&rl JoElQUin Co Slanisoos**C~>-** TuI<lre Co 08097 JI..spen Pllkm Co CO Mooerate Restsurant grills.' ReqlJlfe conLrol devices 2810025000**4103~** KlalT1ilth Falls Klarn.nh Co OR Moderate: AgricultlJrBl bl.;rror.:;: i**Ye~r-rOl;nc** ban on 8grKultl'ldi**2801~,0000O** open burnin<;l 49035 Sail lake County UT Moderate Miningi 2325000000 Keep lailings IXlncwet ,19035 Salt lake County UT Moderate Re!menes Apply sulfur remO\.'al Lillil low-SO;;: Ci)l<Jl)"st technology Restrict burning or Uquic fuel 0_

Table IV·10 lists the control factors thatwere applied to the 2018 PM lO emissions in the listed PM lO nonattainment areas in the Western States. Some of the source categories that are included in the prior tables in this chapter are not included in the control factor file because their PMlO emissions are not accounted for in the point and area source inventories.

AppendixA·TSD, Page4Table 

### IV·l0 Area Source Control File for PM

Conlrol Factors for 2018 State 10 County 10 PM vNonaUainment Area SCC PM'D**PM2.~** Construction 32 003 Clark 2311010000 75 37,5 06 059 LA 2311010000 75 37,5 04 013 Phoenix 2311010000 375 18 75 06 077 SJV 2311010000 75 37.5 35 013 Anthony 2311010000 75 37,5 41 035 Klamath 2311010000 08 097 Aspen 2311010000 49 035 Sail Lake 2311010000 75 37.5 53 063 Spokane 2311010000 Agricultural Tilling 04 013 Phoenix 2801000003 20 20 06 077 SJV 2801000003 20 20 53 063 Spok.ane 2801000003 20 20

The control efficiencies and rule penetration values shown below are based on control measure evaluations performed by Pechan for EPA's regulatory analysis ofthe PM National Ambient Air Quality Standard, Control factor development is described by source category below: Construction Activity

- the numerous measures adopted to reduce fugitive dust PM emissions from construction activity were condensed in to two primary measures: a dust control plan and chemical stabilization, A typical dust control plan includes water treatment of disturbed soil and vacuum street sweeping of nearby paved areas, Control efficiency and rule penetration values are as follows:

Measure Dust control pJtJfI ChemJc..a1 stabitzalOn PM.a Conlrol E'jci0nt:y

75",.,., Rule PcncHalon PM" Control Effielorlt:y R:ulo Penotration

75%
Agricultural Tilling

- the typical measure in the PMlO nonattainment area plan s is soil _conservation plans, A 20 percent control efficiency is applied to both PMlO and PM,s emissions in areas that have these plans, This 20 percent control efficiency may be conservative for estimating emission reductions for areas like Maricopa County, Arizona where agricultural best management practices have been adopted,

AppendixA-TSD, Page5Prescribed Forest/Range and Agricultural Fire Smoke Management Programs: The following information is from "Integrated Assessment Update and 2018 Emissions Inventory for Prescribed Fire, Wildfire, and Agricultural Burning", Air Sciences Inc., originally published August 27, 2002, revisions in press, Project

### # 178-2.

Table 6.4: Summaryof PM,., Emissions from Prescribed Burning byState and Smoke Management (SM) Scenario. The Relative Emissions are Based on theTotal PM25 Emissions in the Wildfire Emissions Inventory.


### No Smoke BaseSmoke Optimal Smoke Management Management Management Absolute Relative Absolute Relative Absolute Relative State (tons x

### 1031**(~~)** 

### Itonsx 

### 10l) (0,0) 

### (tonsx

### 103) (%) Arizona 

### 77.0 15 09.5 14 65.6 15 California 

### 110.3 21 109.7 l' 

### 95.1 21**~L** Colo1"i\do 

### 25.0 5 24.S 21.6 Id.\ho 

### 47.1 9 47.1 <) 

### 39.9 () \1ontani\ 

### 40.0 8 39.1 S 

### 34.6 S :!\evi\d'l -0 

### 1 5.8 1 

### 5.1 1 J. ' 

### :\e'

..· 

### .!vlexKo 

### 74.5 14 

### 74.4 15 63.6 14 

### ;;:orthD.1kota 1.8 

### 0.3 1.8 

### 0.4 1.0 

### 0.4 On:.ogon 

### 48.1 9 46.7 Q 

### 39.i Q 

### SouthDakota 

### '

- 

### 0.7 3,(1 

### 0.7 ."'\ .... 

### 0.7**~'./** ,),,' 

### noh 46.4 

### 9 45.7 () 

### 38.5 Q \Vt'\shington 

### 25.S 5 ,- '1 

### 20.5 .:..J._ \'\'yoIlling 

### 17.1 

### , 16.9 , 

### 16.2 4 .'**~,** 

### TOTAL 

### 522.6 510.4 445.2

AppendixA-TSD, Page 6

### Table6.5:SummaryofPM2.5

### EmissionsfromAgricultural BurningbyStateandSmokeManagement (SM) Scenario. TheRelativeEmissionsareBasedontheTotalPM2.5

### Emissions intheWildfire Emissions Inventory.
NoSmoke BaseSmoke OptimalSmoke Management Management Management Absolute Relative Absolute Relative Absolute Relative State (tonsx

### 1031 

### (%) 

### (tonsx103) (%) 

### (tonsx

### 103 ) 

### (%) 

### Arizona 

### 0.21 0.8 0.21 0.9 0.07 1.0 Calif011lia 

### 8.05 30.0 7.00 26.0 2.20 33.3 Colorado 

### 001 <0.1 001 0.1 001 0.1 Idaho 

### 560 20.9 5.60 28.6 2.42 26.7 Montana 

### 0.D3 0.1 0.03 0.1 001 0.1 Kevada 

### 0.00 00 0.00 0.0 0.00 0.0 Kew**~lexico** 

### 0.04 0.1 0.04 0.1 0.01 0.2 KorthDakota 

### 223 8.3 2.23 6.6 0.56 10.6 Oregon 

### 6.78 253 

### 2.3S 19.9 1.68 12.3 SouthD,lkota 

### 0.56 2.1 0.56 1.9 0.16 ')'j _., 

### nah 

### 0.21 0.8 0.21 0.7 0.06 1.0 Washington 

### 291 109 "1 ,.- 

### 14.7 1.24 11.2**_.~"),)** 

### \\\'onutl'" 

### 0.19 0.7 0.19 0.5 0.05 0.9

. co 

### TOTAL 

### 26.83 21.02 8.45

AppendixA-ISO. Page 7On-Road Mobile Sources: This information is from "Development OfWRAP Mobile Source Emission Inventories", Pollack, 2003, in press.

1996 Control Programs: MOBILE6/PART5 inputs related to several on-road control programs were also included in the modeling. These control programs are area-specific (i.e., not applied nationally or regionwide), generally based on an area's ozone or CO nonattainment status. These programs include vehicle inspection and maintenance (11M) programs, oxygenated fuel programs, and Stage II (at-the-pump) vehicle refueling controls. Note that reformulated gasoline is not included in this list because none of the WRAP states had implemented a reformulated gasoline program by 1996. The default control program parameters were those in the 1996 NET. These were updated by the state and local air agencies in some cases. As described in Section 2, federal control programs are included in MOBILE6 and no additional inputs are needed to model these programs.
Inspection and Maintenance (11M) Programs: 11M program inputs are specific to each state or area implementing such a program. The default 11M program inputs were those from the 1996 NET, converted to MOBILE6 input format, along with the county coverage of these programs in the 1996 NET. Updated information on these programs was provided by Arizona, Colorado, Nevada, Oregon, Utah, and Washington. Table 3-2 lists the counties modeled with an 11M program in place. Table 3 2 Counties modeled with an inspection and maintenance program in 1996.


# - State 'countv 

## IAz Maricopa 

## IAz Pima K;O V\dams CO !Arapahoe CO Boulder CO Douglas CO lJefferson CO Denver CO EIPaso CO Larimer CO Weld 10 V\da NM Bernalillo NV Clark NV Washoe OR Clackamas OR [Jackson OR Multnomah OR Washington UT Davis UT Salt Lake UT Weber

AppendixA-TSD, Page 8UT Utah 

# WvA Clark 

# WvA King 

## WA Snohomish 

# WA Spokane FJl[A Pierce
Oxygenated Fuel: Forthe WRAP modeling, the program in place in each ofthe mid- months ofthe seasons was used (i.e., the program in place in January for the November to February winter season). Table 3-3 lists the counties that were modeled with oxygenated fuels and the inputs used to model these programs. The information in this table includes updated information on these programs provided bythe states. Table 3-3 Oxygenated fuel inputs Uanuary Oxygenated Fuel Inputs OctoberOxygenated Fuel Inputs lVIarket ShareIOxygen ContentMarket Share**~)(ygen** Content



### %) (%) %j %1 Ether

### ~Icohol Ether

### ~Icohol Ether

### ~Icohol Ether'

### ~Icohol State 1county Blend Blend Blend Blend Blend Blend Blend Blend 

## iAz Maricopa 17 83 

### Q.7 3.5 17 83 

### Q.7 G.5 

## IAz Pima 17 83 17.7 3.5 17 83 17.7 (35 CO IIIdams 175 75 

### 0.7 13.3 CO IIIrapahoe 

### 05 75 17.7 3.3 CO Boulder 175 75 1?7 3.3 CO Denver ?5 75 

## 12.7 (3.3 CO Douglas 25 75 17.7 (3.3 CO EIPaso 

## b 100 

### 0.7 12.7 

## b 100 12.7 17.7 CO Jefferson 

### 05 75 

## 12.7 33 CO Larimer 

### kJ 100 

## 12.7 2.7 

## P 100**~.7** 17.7 CO Wveld**~5** 75**~.7** 3.3 MT Missoula 

## b 100 17.7 3.5 0 100 17.7 (3.5 NV Clark 174 76 12.7 135 124 76 12.7 3.5 NV IWashoe f.:J5**~.7** 3.5 f.:J5 5 

## V 3.5 NM Bernalillo 15 85**~.7** 3.5 15 85 12.7 G5 OR Clackamas 

## b 100 

## 10 35 

## b 100 

## b 3.5 OR Uackson 

## 'if 100 

## 'if 3.5 

### kJ 100 K> G.5 OR Uosephine 

## b 100 

### kJ (3.5 

### kJ 100 K> G.5 OR Klamath 

## b 100 

## b 35 

## b 100 

## b 3.5 OR Multnomah 

## b 100 

## 'if 3.5 

## b 100 

## b 3.5 OR Washington K> 100 

### kJ 3.5 

## b 100 K> 3.5 OR rYamhili 

### kJ 100 

## b (3.5 

## P 100 

### kJ G.5 UT Utah 

## b 100 

## b 3.5 

## b 100 

## b 3.5 

# WvA Clark 

## 0 100 

## 0- 12.7 WA King 

## P 100 

## P 12.7 

# WvA Pierce 

## b 100 0 17.7 

# WvA Snohomish 

## b 100 

# P 12.7

Appendix A-TSD, Page 9Uanuary Oxygenated Fuel Inputs OctoberOxygenated Fuel Inputs

. ""'arket ShareOxygen ContentMarket Sharepxygen Content 

### %)

. %)

. %) %)
. .. Ether

### ~Icohol Ether

### ~Icohol Ether lA.lcohol iEther lA.lcohol State County Blend Blend Blend Blend Blend Blend IBlend Blend WA**~pokane** 

## p 100 0 3.2 

## P 100 

# P 3.5
Stage II Refueling Controls: Stage II controls were applied in the following counties: Maricopa County, AZ; Clark and Washoe Counties, NV; Multnomah County, OR; and Clark, King, and Pierce Counties, WA. The Oregon and Washington counties were modeled with a 95 percent Stage II control efficiency for light-duty gasoline vehicles and trucks and an 80 percent Stage II control efficiency for heavy-duty gasoline vehicles. Maricopa County, Clark County (NV), and Washoe County were modeled with a 50 percent control efficiency, 95 percent control efficiency, and 85 percent control efficiency, respectively, applied to both light and heavy vehicles. Processing ofCalifornia Data: California has different on-road mobile source control programs from the rest ofthe country. CARB has its own model that estimates the effects of these control programs. CARB provided 1996 on-road emissions estimates from EMFAC2000 model runs by vehicle class, county, and season, with all applicable controls incorporated.

Future Control Programs for 2003, 2008, 2013, and 2018: The effects of Federal on-road control programs are included in the MOBILE6 and modified PART5 models. The Federal control programs that started in or after 1996 that are treated as defaults in the MOBILE6/PART5 modeling are: National Low Emission Vehicle (NLEV) emission standards starting with the 2001 model year; Tier 2 emission standards starting with the 2004 model year; two phases of new heavy duty vehicle emission standards-one starting in the 2004 model year and the other starting in the 2007 model year; onboard diagnostics; and the Supplemental Federal Test Procedure (SFTP) rule. As discussed above, the low sulfurgasoline fuel corresponding with the Tier2 emission standards and the low sulfur diesel fuel corresponding with the heavy-duty vehicle 2007 emission standards were also modeled throughout the WRAP region. Also modeled as part of the default conditions in MOBILE6 are estimates of excess NO, emissions resulting from the use of defeat devices in heavy-duty diesel vehicles as well as the provisions to offset these excess emissions through early pull-ahead of the 2004 heavy-duty diesel emission standards and through low emission rebuilds of existing engines. All of these control programs were modeled using the MOBILE6 defaults and the modified PART5 model defaults, with no additional user input. In addition to the national on-road control programs, several area- specific control programs were included in the MOBILE6 modeling forthe projection years. These include 11M and ATP programs, oxygenated fuel programs, and Stage II refueling control programs. These were modeled as follows:

• 11M and ATP Programs

- County coverage of the 11M and ATP programs did not change from the 1996 base year modeling to the projection years. The counties with
AppendixA-TSD, Page 1011M andlor ATP programs are listed in Table 3-2 (above). The States of Colorado, Oregon, Utah, and Washington provided updates to the 11M or ATP program inputs for the projectionyears. Forthe remaining States with 11M orATP programs modeled in the 1996 base year modeling (Arizona, Idaho, New Mexico, and Nevada), the same 11Mand ATP program inputs were modeled in the projection years. It should be noted, however, that these programs did already include projection years in the inputs, with OBD testing starting with the 1996 model year. In both the base year modeling and the projection year modeling, the 11M programs in Washington were only applied to a fraction ofthe VMT in each ofthe five counties with an 11M program. These fractions that the 11M emission factors apply to were provided by Washington, and emission factors without 11M programs applied were modeled forthe remainderof the VMT in each ofthese counties.

• Oxygenated Fuel Programs

- Table 3-3 (above) lists the counties that were modeled with oxygenated fuel in the 1996 base year, as well as the corresponding inputs used to model the oxygenated fuel program in each county with MOBILE6. Several changes were made to these base year oxygenated fuel inputs for the projection years. For Utah County, Utah, the oxygen content of the oxygenated fuel was changed from 3.5 percent to 2.7 percent. For the counties with oxygenated fuel in Oregon, the oxygenated fuel program was eliminated from the 2008, 2013, and 2018 projection years. In Clark, King, Pierce, and Snohomish Counties, Washington, the oxygenated fuel program was discontinued after 1996, so no oxygenated fuel was modeled forthese counties in any ofthe projection years.

• Stage II Refueling Controls

- In the 1996 base year modeling, Stage II controls were applied in the following counties: Maricopa County, AZ; Clark and Washoe Counties, NV; Multnomah County, OR; and Clark, King, and Pierce Counties, WA. The only changes made for the projection year modeling were to add Stage II controls in Clackamas County and Washington Counties, in Oregon. The MOBILE6 inputs for modeling Stage II controls applied to these two counties were the same as those applied to Multnomah County in the 1996 base year modeling

- a 95 percent Stage II control efficiency for light-duty gasoline vehicles and trucks and an 80 percent Stage II control efficiencyfor heavy-duty gasoline vehicles. Processing of Future California Data: For California, CARB provided on-road emissions estimates from EMFAC2000 model runs for all four future years by vehicle class, county, and season with all applicable control programs incorporated.

Non-Road Mobile Sources: For non-road sources, 1996 emissions estimates are directly controlled by fuel input, as control technologies were not required forthese sources. 1996 state -level off-road fuel sulfur averages are shown below; there are some differences by counties within states and the county-specific sulfur contents were used in developing the 1996 emissions estimates. The fuel sulfur inputs were adjusted to reflect federal rules for gasoline and highway diesel fuels that become effective between 1997 and 2018. No additional control technologies were assumed for2018.

AppendixA-TSD, Page 111996 State Averages Highway Off-Highway Gasoline Sulfur(ppm) Diesel Sulfur (ppm) Diesel Sulfur(ppm) Arizona 213 338 2005 California 23 135 135 Colorado 195 335 4100 Idaho 285 380 3075 Montana 375 320 4100 Nevada 91 310 3400 New Mexico 303 310 4100 North Dakota 266 312 4175 Oregon 293 299 3400 South Dakota 238 320 4186 Utah 186 366 3955 Washington 281 301 3400 Wyoming 285 380 4100 California has somewhat different off-road mobile source control programs from the rest of the country, and CARB has its own internal model that esti mates the effects ofthese control programs. CARB provided 1996 off-road emissions estimates from their OFFROAD model by equipmenttype, county, and season, with all applicable controls incorporated.

AppendixA-TSD, Page 12Stationary Sources

- Existing Source State Regulation Analyses: This information is from Chapter IV "Existing Source State Regulation Analyses, Western Regional Air Partnership Emission Forecasts For 2018
- Final Report", E.H. Pechan & Associates, Inc., December2002, Pechan Rpt. No. 02.12.003/9409.000.
NO" The analysis of NO, emission regulations primarily examined ozone nonattainment areas. These are limited to California and Maricopa County (Phoenix), Arizona. Arizona: Portions of Maricopa County are (were) nonattainmentfor both ozone and PMlO. The primary ozone control measure adopted in Maricopa County was a 15 percent rate VOC emission reduction requirement of the CAA. This emission reduction has no direct impact on SO" NO,and PMlO emissions. There are a limited numberof NO, control requirements. California: In California, the thirty-frve (35) air pollution control districts have jurisdiction in imposing emission limits on point sources. The follOWing sections present the district NO, emission limits for turbines, boilers, internal combustion engines, and petroleum refineries. The fuel combustion sources (boilers, internal combustion engines, and turbines) are of particular interest in this study because they are the largest stationary source NO, emitters in California. The impact of these regulatory requirements was estimated as follows. Uncontrolled emission rates were estimated u sing EPA AP-42 uncontrolled emission factors, which are primarily listed in units of pounds per million British thermal units (lbs/MMBtu). EPA guidance was followed to convert these EPA emission factors into parts per million (ppm). This was done for comparison to the California district rules and Maricopa County rules that regulate emissions from these emission units in ppm. This method was used to estimate the likely level of control required by the California Air Pollution Control District (CAPCD) regUlations and Maricopa County, Arizona rules. The CAPCD point source regulations also apply to existing units, except as noted. Several CAPCD regUlations impose different NO, limits for units larger than 10 megawatts (MW) depending on whether they have an SCR control device. Since it is not clearwhether units in those districts with two sets of rules have installed SCR, to be conservative, the less restrictive emission limit is imposed (assuming no SCR). Gas Turbines: The first row of Table IV-11 lists the NO, emission factors for uncontrolled turbine units. They are provided for comparison with emission limits permitted from gas turbines as found by CAPCD. In some cases, CAPCDs impose different NO, emission limits on units with identical

Appendix A-TSD, Page 13

### Table IV-11 Turbine NO, Emission Limits'

District

Bay Area

Kern

MOJAOMD nonallainment area Monterey

PLAAPCO SACAOMD YSAOMD VENAPCO SCAOMO

SOAPeD

SJVUAPCO

TEHAPCO Comp liance Dale EPAAP-42 1997

1997 SCR 1997 SCR 1997 Westinghouse 1997 WestinghousE' 1995

199" 1997 1998 1997 1989

1999

- ne'l,' units 2001· existing unils 2001
- exisling units 2001

- eXisting units 1996-2000

No cate provlOcc NO.(ppm) 108/297

42' 15

9 10i.&O 9/25 96/114 20/42

42 65 901ga< fuel 225**1~O** poundsfhr 42/65 25/65 15/42 9/25

25 15
9 12

25/65 15142 9.

.'25 42/65
9/25 Control Eff. 1/1 

## o 15-0.39 0.05-0 14 0.03-0.09 010f014 0.0910.09 0.89/039 0.19 10.15 0.39 0.22 0.84

0.39/0,22 O,24iO.22 O.14!O.1b 

## o09fO09 0.09-0.2,: 0.05-01':
rJ 03-0.0C' 0.0·:-012 (j 39 10.22 0.2410.22**01Iji01~, O_09:0_0~'**  

## o 39/0.22**n1l~i01~1** 

## o**_09,{).O~'** 0.39/0.2::': Units Uncontrolied gasloil 0.3-10MW >10 MWw!o SCR > 10MWw/ SCR
;:. 10 MW co-gen:gasJoil
> 10 MW oo-gen; gas/oil Constructed by 1983; gasloil Con structed by 1983: gasfoil Gas-fired Oil-fired SoCal Model LM 1500 All existing Ne'w or expanded 03-2 9 MW; gas/liquid 2-9-10 MW: gasiliquic >10 MW no SCR, gas/liouid >10 MW wi SCR gas/liGule 0.3-2.9 MW 2.9-10 MW no SCR & >60 rvlV\i combined cycle (ec) >2 9 MW >60 MW cc no**scr~** > 10 t

...1\N no SCR [; 3-29 MVv': gas/liquic**2_~j-1** (I MW : gas/IIGuie >10 M\N no SCR- gas/IiQuic >10 t

...1W W" SCR gasfliquic 0.3-1 (I rvlW

. gas/'liQuid ::- 10 rv1 W no SCR' gas/Iiouie' >10 MW wi SCR gas/liqule

>-

## a3 MW: gas.rliqulc

NOlES '1 rus f(>,P ltl'S/tn Is \1;<) em**<S~~:';()iI** t<'l cit>' !lm'[" (ronl tu rbl II C:'. 1 iltJ Je aw e llC,;u:;l<J!, k**ttK'~C** i;rmb. tr":rl dfltj' rOt 'SlTl ai, t;0i,J10! " illHl d u,'ng f1 Blum! y.fl cuflfwm eJ1l 0' g;!l ott test'fi'Q jH"fl(H:.It;,. A**~l'1Wl'l~** De ,;';{J'l ,j ton (d 1**~":.,,** 0 llygCll 'S I.J SUi'lI]'i c,tiHl**~['(c(!,'1 ~b** **Wrtl>~ef** mna:H1 tty VCI\.l1H! IIHHT!"!**~jlo** ....**~j** 1;:;' rcftncrytutd yas 1"1n;l
power ratings that differ only in whether they are equipped with SCR control technology. In all of these cases, those units without SCR control technology are allowed a higher 

### NO, emission limit Since it is not clearwhether most gas turbines are equipped with SCR or not, to be conservative the less restrictive emission limit assuming no SCR control is being used applies. With this information, the control effectiveness of the 

### NO, emission limits imposed in each CAPCD is identified. The control effectiveness is obtained by dividing the CAPCD imposed 

### NO, emission limits by the corresponding and applicable EPA AP-42 uncontrolled

AppendixA-TSD, Page 14emission factor. The CAPCD turbine regulations also apply to existing units, except as noted. Industrial Boilers: The lAS separately tracks emissions from industrial coal (incobo), natural gas (inngbo), oil (inoibo), and wood (inwobo) boilers. Table IV-12 lists the EPA 

### NO, uncontrolled emission factors used for these boilers. Also listed in Table IV-12 are the 

### NO, emission factor limits imposed on these boilers as found for some CAPCDs. These CAPCD regulations also apply to steam generators and process heaters, except as noted. The control effectiveness of these regulations is obtained by dividing the CAPCD imposed 

### NO, emission limits by the corresponding and applicable EPAAP-42 uncontrolled emission factor. Internal Combustion Engines: Table IV-13 lists the 

### NO, emission factors appearing in EPA AP-42 applicable to uncontrolled internal combustion units. Also listed in Table IV-13 are the emission limits imposed on these units within Maricopa County, Arizona and by CAPCD. With this information, one is able to identify the control effectiveness of the 

### NO, emission limits imposed within Maricopa County, Arizona and in each CAPCD. The control effectiveness is obtained by dividing the Maricopa County or CAPCD imposed 

### NO, emission limits by the corresponding and applicable EPA AP-42_uncontrolled emission factor. The CAPCD regulations also apply to existing units, except as noted. As previously noted, the base case emission inventory forthis study is 1996. Because some CAPCD regulations go into effect after 1996, it is expected that these post-1996 regulations will result in a corresponding emission reduction in those areas for these sources relative to 1996. This is captured by reporting the 

### NO, emission reduction expected in each region relative to 1996, where data are available to perform this task. We have also been able to identify the control effectiveness of the 

### NO, emission limits imposed in Maricopa County, Arizona and within each CAPCD. The control effectiveness is obtained by dividing the Maricopa County, Arizona and CAPCD imposed 

### NO, emission limits by the corresponding and applicable EPA AP-42 uncontrolled emission factor. The CAPCD regulations also apply to existing units, exceptas noted.

Appendix A-TSD, Page 15Table IV-12 Industrial Boiler. Steam Generator and Process Heater

### NO, Emission Limits'

OllstrlCt
Ul){;cnlrotcd

AVAPeD

EIOo!.!IOC
Grtl,yt**a~w**

MOlllfHey VENAPCD

C.i1 Ell'tHas, E! D<lla(J{;, MiIl;IIO:l.<1 Piacc' Nc. Si{:'lil Tuolumnl' MOJ/,QCD

S£.!APCO

S tlAAr.iMD CQm pllilllCO Oat

...
EPA AP·': i
1990-1993

199t:

1999

1992
1'1171
199£

19.]7**l~,jl**

1995**~ab** OHll:l'! rlafl**!l<l~**

lu:)t',l<JS Gtnt!' 'lil'1 I,:l<l;;**19~H:** nHI!{;f**SC\l'Lc~ 19~**  i lllill;".'**~~** ...J'<;'O:'**1':i!'!~·lt'SiL >If!~_**  ;;qu;;.1 l\flH' NC dilte !:H.::.•'Lled**N~l** dal"

.. Dh;VtjlJ<J

1991 'l1il,D' 5iJJ.j'Ce::. liJ98 mdL)'**!:ii},W';C~**
199f NO.**(pPITI"'~**

3D ",. 40



# '" 'C 14{l lbftv

iO 11£ He it-f/i'

"Ie 11 )"

YJ

3::

G,14 W:MM OtH (;,.1-'::18 itifMMUt.;**C.;:;~,** iIL"MMUtu JC 40

JG**g~j~** AG l¥jwa 7;:; 11 Reduc. to '9Ei Control E fl.

1.'1:'1

o 15- C,O"·C2H

C.1S 0.01;·0.29

0.35 c.,c

0.' (:-G,82

en.

V.20-'

0.1

::.1**G,:!~** <.i,10-C.!'!:! UnJ1I5'

gas.'iJqu ldJsohd

10 MMBttJ, gas ;1'10 MM8Iu;**Jlcn-9a~**

... ,5 MMBtu: gn > -5 MMBiu; non·gas

NewOf explilndoEl-tJ

,;. ,5 MMBltJ.**g-a~** ;I' 5MMBl.u. hquld

NtJw (X oEl-xpandad SOiHlI

Gbll&fawrfilC;i!lUS

;, 1.5 MMlltu G

.. aon-g<l:'

,. 5 MMBlu, ';las

"" 5 MMBlu, flvH-9nl.e.
J> 5 MMUtu, tilom<1Ss.

:;;> 5 MMBtu,**!-l')~ "~MMBlu.**  ,(,(lIl-gOl:' Fltlr{,>wum R!!f,4 Pc<I'Olt:l-U'll**R~J!"** Pc.lfu'l!u!T\ Hd:
> 4C MMO**I~,** 9tls'

,. MMBlu, 1l0n-QBs' J>:; MMBI\.l. gasiIQiI-g,as'

glH '!(llHd!stJhcl

SJUAPCD ,-.lot <Jj;p.:ud

.....Nol

of**I~** \11**h(]~,.** KC_f:l, KHlg CV'J'lI'!!':'>**19-9~ 199~** 
199;-2001 O.2D1tJ.lMME:ltcJ ::;5 1H 1til: 10/4C 1":**li15~ G.1o.-C.~::**  Q

..!.1.l 0.10 C.15 G.15io.n";-C.29**SClj~1** Q'Js d,slilata 01: te!i,dUl!llicl'l..ltK' o,; ;.30 MMBlu,**g<i:!o.inl)l~gOls.** ;.30 loAMBlu.Q<'lSiflOl<gas'

AppendixA-TSD, Page 16Table IV-12 (continued)

Oi!ilritt COin pli,Hlcc 0111(' NO, (ppmi,') Rpduc. to '9ij GDnl rot E ,t
StOAPCD 1'9"!L1 140lb/hf 1995-·1997 (19ft5 no.\', '997**~:XlSl!Hgi** JO or 0.036 jtJ:1Y1MOLu 40c." 0.052 Ib,lMMBl;J 0.15 0.04 i 029 All**f"t~.h}l** \n:I!!**.gd~** i'q;'..:di'&O!1d
TEHAPCD NO dale p!ovded 70 115 VCAPCD 1991-1i!92 .to**1994-129~** ::10
YSAOr.lJ 1ftJ$ 3D 40 0.35 0.10-0.82**C.1~** D.o..;·C.2B gf:lS IjQ'.lId or sulJd

"' !: I.1MBtu 1·5 MMOtu
gel I>**li~,,·gas**

NOTES 'TTl'S re-Plltsenls tlO tHn'$SiOn facio' J<mls t {1m**b-o,le~_** There ill{)**ei'.::;~pl[)n~** II: l1.et.l) uses.**~I'lma(i¥** to.r s.'llaii Cllldhr NMlgCfl{:YiJSos. A**fe1IHI!flt;flCOnd,~on** 013%**1):X)'9(!~1::S iJSJOi~y**  c-lcd.**~BO).** 0( c;aO!n**IN'''1~.** 'Bufj"'H50'lltj ·1.11.10 t'J "" MM Btu!i!' ihe P eirOleVIli R"f. Btl**~~,-:..alJi<)** so-:.:;L'1)fl ,So IOf oo,IVf$ !H1d::"**!()(;~':<s tl8"I~H~.**  to

... t;;)tj(!s;pond''lg**!Illm~** Ii:r trw:'> d,s!f:cl <I" 1l0l iJpPiy Ie Pi!LroW,-u'n Ref, l-(J<l,,];s ;'vld tr(>(;(}SS**II~-,;'Jlc<s** > 40 MMBlIJ and**~,.:1LJ1** pianl rcact.:."', C'0,k'j

Appendix A-TSD, Page 17

### Table IV-13 Internal Combustion Engine NO, Emission Limits'

Dilltrict Cillcndiu Year NO, (ppmv) Reductloll to

# ... Control E fl. Unit'S

Uoconlroled 500 Rlctl 700 l@CIn 1000 Diesel
Mam:u!'l, AZ N_ umls 213 Of 80% ,.0**Ci.31~O,43** RIch/lean 81O:l 0.81 50· 1 16 f1Pten 770 , 0.77 117

. 339 "0 (CI) 550 • 0.55 ::-400tlp(CJ)

AVAPCll 1YB1-1'ilY1 48 Of 91}% fed 1 0.096 RiCh 96**~f** 8U% f(!d 1 0.14 lean**1991;l20~** !b 0.375-0.75 0.036 OD72 > 500 "p 45 O,4l -0.94 U.045· u.o90 5Q·5DCnp**Ba~'** Area 1991 S6 t140 0.12 !**a.~·** RchILoilflNG**ooI~'** 210 f 1411 C.21 j C.14 RlchfLean Oh61

[! Om'Hli:**199~** 640 

# , 1 Rich 14e 

# , 1 70C 

# , C.7t Dies!!! 1991'**0_1~** a.HI Rich 150 (;.21 0.22 ltl<lfJ MiG o.e& C.60 D,estJ,

....0.:.,., No jillf! P1OIo'IL1Ct! !lC OJ 9{}% (ca_ tut R,ch > 250 'lP 125 cr eO% red C.1-fJ L4.·d'l > 2SG no bOO Of 30% red C.fiC Diesel > 2tlC np
MO.;AOr

...ll1 Ed::', (!1.'.:;U;) L tlD 01**g.D~-:'** led. D.1t R,t'! 1**:i9!J-~.;** ( I()' 140 0.' aD,,:

... 'ea iJ.2::.: Lf!<I!l SoGtJiG<I·,> 1<":i':H3· 700 {It 30%. !tH] G.i't DWSoe :iB PGL

MC'1llJ u ,)**22~** p;:Jfl"' HAb/C.J2iG.LJ Ah 14(: Ibin' Ne

.... 0'**t!~q)<I'11c(j** S.A.C/·.GM() 1i!:!:"

# , 'Ie !I:'[w'lI**~!\** (If**9iJ'~** UH] 1 t' E: H,,;ll llet!1e(l 125 0< £10%

## ,., 1 a 18 l(l-lJn WO 0< !:Ill";;, 'Ud 1 U 1," DUbe! ,en 1fr9 7

# .,**w"II'Y~** 2f**O.2··J.~ (j.a~**  RlCn.<lean f'Slj nc-uded**8~.** C.1 ::: C.D':" D'Qs.eHCll

SCAQMC'**19fJ~** 90 0' 80% led. 1 C.1 G RiCl1 150c: 70% HId. 1**O.£~** leClI1 :2t

..

"'J4 Jb**U.~4·** GAC O.DJ-6 0.012 > SOD tl,()**~5 O.3G·O.~O**  0.0

..5· O.G-ift SCI-SOO "V 2.DUG- , exceDll{ au Pc((atic 51 t;·:.l"Lr0i'.> lil!edt,-.;J S35-1S"J**P()r~n-i0CI** t'''Hl 201-0
SHAAQM[I 19'1'9 64G RIch :50·3:10 hp'l TEHAPCD 740 Lean (50-300 tlp) 600 0.60**DIOS~l** (50·300 ttp) 90 0.18 Rictl \:>300 "p) 1SC 0.22 loan p·300 npi 600 0.80 Duu.8i (>300 hpj

Appendix A-TSD, Page 18Table IV-13 (continued)**Di~lr** ...;;t Calendar Year NO. (ppmv) Reduction to '96 Control E ff. Unit's
S_:VUAflGO 19:'.16 90 Of Btl'\::. fcd 

# , (L 1G Ol-!HH RICh 1S0 or 70%. r,.,d. 1 0.22 lean 600**o~** 20'\(. roa 

# , O.fiC D,esel 199!i1/2001 50- or OO':f.**roo.~** 0.56 0.1 C OHIoU- RU::11 75 or 85%**[8d.~** O.St! 0.11 lelHi 80 OJ 90%**rtHI.~** (J .1.oi O.tlfl Diesel

SlOAPCD 20GO 50 I(}r 90% re-d. U.l C RIch 125 or 80% ((td. (1.1e**L~un** 600 or 30% 'ed. O.fiO DIesel
',leAPeD lyG4 or**2UG~** 25 or£16%**1'l~<l O.O~**  RJCfl .45 or 94"1<. Icd. 0.a7 Ll!Ian 80 Of 90% red D.D!'!**O;es~1** 50 or 96% IC{l**RI(;t1-Wast~** Gats 125 or 94% (@d Lean-Wasle Gal!>

YSAOMD**19H~ 6.40or9.~g"q.HI'**  

## , R'C!l 1'40 Cf 1G. , g.hpr1' 

# ,**l~~n** 100 Of 9.6**'J,~lnll** 1 C.lf Dll!ll;oj HhH 90l lS0! 600 lJ 15.' 021.1a.i.H: U ltlO2.2,10.tK: R Icri/L4l.a f•.o,es@1

'RC-pf£!I>I!'He!I**(.'nlli.~16fl** ffletor I,nills r.Oll" ,Il[('rn;) CC'I'lt.1clslu-n**I!f1Qmo~.** Rcducticrl5Ircd.\ ale from unconlfcli!c-d ;t·l'td,.. T ll'J: t! dr,"" 'J Jic:tl t:lK'fl'!> 10 t.ll(JS-'!' IHTl;t,. O' In

.. n!y 10' ,l; !lidO**~"1<J:\)1** {!tI!c' QtPI,:; 'i uSo{'::,. A fill t' rell{l.l (;01VJj**I~** 11 (;1 1**~~~ O,,,)·g~'·1**  UE.U<l11Y (;It!(L "N"L .CippiICHl!il' I" engHl(J$ (hY!HHJ D'i £)Uill/C "",lie, (];SI"Cl. 'AHQ'fl3 IN!,)) •• a u"lf!

..... 1l11 .a 1;.1(1)0c'lar9 e r ilfJ;j alte 'COO**i~:H'" ,'lle-'l~()**  oJe' oj WlitI**4-d~g** fe.t! ;njOC l0"J 11tn,n9**rc1.<J~-d** ""iF '!>iJL1.>fy M il"'A.\;J<i**Cet.H11~·.** A2 rogui<JI1Gl]!,

Industrial Reciprocating Engines, Including Natural Gas: Table IV-14 lists the 

### NO, emission factors permitted from natural gas and otherfuels used in reciprocating engines as reported by CAPCD. As shown below, only Santa Barbara County and San Diego County Air Pollution Control Districts apply specific 

### NO, emission factor limits from these types of units. Table IV-14 Industrial Reciprocating Engine NO" Emission Limits'

Districl COlllpliance Date**NO~** (ppmv) Control Eff. Unlis Uncc.nlroHee 500 

# , r":'1ch NG 62b 1 Lean NG 1000 1 Diesel Monterey 22!:, I)**~::5/0** ;"'\6JO.23 All ,ao lb·t;r New or expanoec SBCAPCD 19L:l.:**~O** or 90"',;, ree 0 10 Rich 12::. or BO"',{, rue 

# " 28 Lean 797 0 80 DIL"Sel SOAPeD No date providec 50 rich or**90~"** red 0,10 RichNG 125 lean or 80",,, r.?C 0.20 Lean NG 700 diesel 0,30 Diesel 2002- 2b or**96c~,,,** ree o OS· F<ich NG 65 or 90"';;' ree 010 Lean NG 53!". or**90~'c** reo 0.535 Diesel
I-.lOT!;.:? ·",,,s • ..,..;:;''''

....·''1''**H,~,** <,'''''eSs,,)''' f8t:lo-!.m'b h',If' '·f.O·c:,:-.>tOCf,bn-;j C"g"'o"**l~,,,,** n,""",''!'''''''''' c",n.d"l't'·" U:l-CIJ ". 1l'J ""., 0"yg,', t, <.:<", If.Hlt

AppendixA-TSD, Page 19Industrial Petroleum Refineries: The California Bay Area District imposed regulations limiting NO, emissions from boilers, steam generators, and process heaters in petroleum refineries. The limits imposed were 0.2 pounds per MMBtu in 1995 and 0.033 pounds per MM Btu in 1997. In other words, the Bay Area District decreased the allowable NO, emission factor from petroleum refineries by 83.5 percent from 1995 to 1997 (see Table IV-15).

Table IV-15 Industrial Petroleum Refinery NO, Emission Limits'

Calendar Year
1995
1997 Control Factor
1.00 NO, (Ibs.MMBtu)

NOTES. 'lhl$ fep fHSMlls UW.l (X'·fllr()j**()fll!ct''''tHW~S** d**m"lISS,~>'1S** f**f{~'11 t.flt~**  rMiI'u·y, ;t SCly-::. nohmg al.HHJL hi(! Ylowth**1J11ef~oorf** o\J(p\Jt.**"h~** (!).c,u(J'!:!-:!>c.arlJ-o'i l'TlOOOl(U::Iil ICD) t>o.ieHio

Oil and Gas Production Facilities: None ofthe documents checked on-line included any information about regulated NO, or PM emissions. The documents related to oil and gas production had to do with leak detection and repair, which affects VOC emissions. Missouri: Missouri is included in this analysis because its emissions are within the WRAP Region modeling domain. EPA's (1999b) Regional Transport NO, State Implementation Plan (SIP) proposed to reduce NO, emissions within many States east of the Rocky Mountains, including Missouri, in an effortto reduce trans ported ozone concentrations in eastern States. The primary focus for reducing NO, emission swas from electric gene rating units (EGUs). For EGU point sources, base year 1995/1996 NO, emissions were used to develop an Integrated Planning Model (IPM) Year 2007 emission inventory. For Missouri, the IPM Year 2007 summer emission inventory for EGU point sources equaled 82,097 tons. The EPA 2007 NO, control case was then developed by unit by applying rPM growth factors to the unit emission rate for the 1995/1996 base year. Emissions from EGUs greater than 25 MW equivalents were then limited to 0.15 Ibs NOx/MMBtu. Units 25 MW equivalents or smaller were left at their 2007 base case NO, emission rate. For Missouri, the resulting IPM NO, control Year 2007 summer emission inventory for EGU point sources equaled 24,216 tons. Thus, the EPA analysis called for a 70 percent reduction in EGU 2007 NO, emissions relative to the IPM base case Year2007 Missouri inventory (see Table IV-16).

AppendixA-TSD, Page 20Table IV-16

, NO, Emission Reductions Required from EGUs in Eastern Missouri Counties

Description 20071PM 2007 IPM with contro Is % Emission Reduclion NO Emissions 82,097 Ions 24,216 Ions 70% = 1000;. x (1

- 24,216i82,097)

Texas: Texas is included in this analysis because its emissions are within the WRAP Region modeling domain, Recent revisions to the SIPs for the major ozone nonattainment areas in Texas have added many regulations that require stationary source NOx emitters to reduce theirfuture yearemissions, The Texas SIPs developed by the Texas Natural Resource Conservation Commission (TNRCC) to reduce ozone concentrations in ambient airare very source -specific. There are three ozone nonattainment areas of note in Texas: (1) BeaumonUPort Arthur; (2) Houston/Galveston; and (3) Dallas/Fort Worth. The SIPs developed for these areas require a reduction in NOx emissions from specific point sources or uniformly across a source category as described below. In addition, TNRCC entered into orders requiring Alcoa and Eastman Chemical to reduce NOx and VOC emissions for the purpose of revising its SIP for ozone. The effect ofthese orders in terms of NO xemission reductions is also included in this analysis. There is also a TNRCC SIP requirement that utility and grandfathered non -utility sources in Eastern and Central counties of Texas reduce emissions. The recommended implementation ofthis requirement is presented below.

Beaumont/PortArthur: The BeaumonUPort Arthur ozone nonattainment area includes Hardin, Jefferson, and Orange counties. TNRCC (2000a) believes Tier 1 reductions in NOx emissions from these three counties will be enough for BeaumonUPort Arthurto attain the 1 -hour ozone standard. The Tier 1 reductions amount to a 40,6 percent, 61.9 percent, and 36.5 percent reduction in NOx emissions from point sources in Hardin, Jefferson, and Orange counties (see Table IV17). TNRCC (2000) reports that these reductions are equivalent to requiring a 50 percent emission reduction from utility sources and a 20 percent emission reduction from four (4) refineries and fifteen (15) chemical plants. These NOx reductions of 40.6 percent, 61.9 percent, and 36.5 percent from point sources in Hardin, Jefferson, and Orange counties were uniformly applied to all point sources in this ozone nonattainment area.

AppendiX A-TSO, Page 21Table IV-17 NO, Emission Reductions Required from Texas Sources

Ozone Nonattainment**NO~** Emission Reduction Area Counly Beaumont/Port Arthur Hardin 40.0% Beaumont/Port Arthur Jefferson 61.9% Beaumont/Port Arthur Orange 365%

Dallas/Fort Worth Coltin, Dallas. Denlon, Tarrant Sou rce specific HoustonfGalveslon Brazoria 90% Houston/Galveston Chambers 90% HoustonfGalveslon Fort Bend 90% HoustonlGalveston Galveston 90% HouslonfGalveston Harris 90% Houston/Galveston Liberty 90% Houston/Galveston Montgomery 90% Houston/Galveston Waller 90%

Alcoa boilers (3) Milam 19.-6%

Cement Kilns Bexar. Comal. Elli.< Hays. McLennan Incorporated in the Dallas/ForI Worth emission reduction requirement Eastman Chemical Harfis Incorporaled in lhe HoustoniGalveston emission reducton requirem cnt Cenlral & Eastern Atascosa. Bastrop, Bexar. Brazos Calhoun 50% for utiUies; InclJSlry and UtiWes Crerokee. Fannin Fayelle. Freeslone. 7.3'Jc for remaining sources Goliac Gregg, Grimes, Harrison. Henaersor1. Hood. HvnL Lamar, Limeslone. Marion McLennan

...lilarl'i. Morris, Nueces, Pa rker Rec River, Robertson. Rusk, TilliS. Travis, Victoria. Wharlon
Houston/Galveston: The Houston/Galveston ozone nonattainment area includes Brazoria, Chambers, Fort Bend, Galveston, Harris, Liberty, Montgomery, and Waller counties< For point sources, TNRCC compiled a 2007 future year NO, emission inventory equal to 564 and 641 tpy (TNRCC, 2000b) for Phase II and Phase III base cases. TNRCC also compiled a 2007 future year control case NO, inventory< This control case inventory contained 64 and 67 tpy (TNRCC, 2000b) of point source NO, emissions, respectively, for Phase II and Phase III scenarios. The difference in the 2007 base case and control case amounts to a 90 percent reduction in NO, emissions from point sources within Houston/Galveston ozone nonattainment area counties (see Table IV-17)< (The 90 percent reduction is calculated from the Phase III scenario as follows: 90 percent

# =100 percentx (1

- 67 

### tJ641 tn This 90 percent reduction was applied uniformly to all point sources in the Houston/Galveston area counties shown in Table IV-17<

AppendixA-TSD, Page 22Dallas/FortWorth: Appendix F of the Dallas/Fort Worth ozone nonattainment demonstration (TNRCC, 1999a) identifies NO, control factors proposed for specific industrial boilers and engines and EGUs in that area. These unit specific reductions were applied to estimate 2018 NO, emissions. Alcoa: Alcoa operates a plant in Milam County, Texas. A TNRCC order with Alcoa limits future maximum NO, emissions from Alcoa's 3 boilers to 13,622.4 tpy. This equals a 19.6 percent NO, emission reduction relative to the emission inventoryfor these three boilers in the WRAP database for 1996. These reductions were applied in the forecast year. Cement Kilns: Appendix F of the Dallas/Fort Worth ozone nonattainment demonstration (TNRCC, 1999a) identifies 11 cement kilns modeled as part of the proposed Dallas/Fort Worth NO, emission reduction strategy. The level of NO, controls required by TNRCC ranged by unitfrom 6 to 66 percent. These controls were applied on a unit-by-unit basis as reported by TNRCC. However, one of the four Texas Industries (Ellis County) cement kilns identified by TNRCC as requiring control was not listed in the WRAP 1996 emission inventory. 

### It is unclear whether the WRAP emission inventory missed counting emissions from a cement kiln, or whetherthere is atypo in the Dallas/FortWorth ozone SIP strategy. Eastman Chemical: Eastman Chemical operates a chemical plant in Harris County, Texas. Harris County is part ofthe Houston/Galveston ozone nonattainment area. A TNRCC order requires this Eastman Chemical plant to reduce NO, emission s from 14 units by 1,671.5 tpy. Thirteen of the 14 units are to be retired. Because the retirement ofthese units would also reduce emissions of other pollutants, these specific units in the WRAP database for Eastman Chemical were retired. Because the unit specific codes in the WRAP database and the TNRCC unit identifiers for Eastman Chemical did not match, this required some judgment to determine which units in the WRAP database best matched those identified byTNRCC. Industry and Utility Units in Central and Eastern Texas: As part of the Houston/Galveston area SIP, TNRCC (1999b) emission reduction requirements applicable outside the nonattainment counties and within Central and Eastern Texas: added the following NO, Houston/Galveston area

• 50 percent reduction of NO, emissions from all utility stationary sources, and

• 30 percent reduction of NO, emissions from remaining grandfathered sources. The 50 percent reduction was applied uniformly to all utility stationary sources in Central and Eastern Texas. The 30 percent NO, reduction requirement from grandfathered sources is difficult to simulate, because the identity of the grandfathered sources was not provided by TNRCC. An analysis was made to determine how this information could be adapted and applied uniformly. The analysis made use of a NO, emissions data file forgrandfathered and nongrandfathered sources. The Alcoa boilers (3) mentioned above are thought to represent a part of the non-utility grandfathered sources in Central and Eastern counties of Texas. When the Alcoa boilers emission reduction requirement is removed, the 30 percent reduction required byTNRCC from grandfathered non-utility sources equates to a 7.3 percent emission
AppendixA-TSD, Page 23reduction requirement from all non-utility sources in Central and Eastern Texas. The 7.3 percent reduction was applied uniformly to all non-utility point sources, except forAlcoa. 

### 502 , The analysis of existing source State regulations affecting S02 emissions in the WRAP States focused on identifying the regulations that were recent enough that existing sources would not have responded to them by 1

### 996. Itwas also recognized that regulations affecting the largest point source S02 emitters would be most important to the forecast. This evaluation focuses on non-utility sources. Utility units are affected by the Federal Acid Rain Program, but as is explained in Chapter Vlt, future year utility S02 and NO, emission estimates incorporate 

### 2018 utility unit values that were prepared under a separate study. The tables in the following pages report the recent S02 emission regulations for the WRAP States that have S02 nonattainment areas, or regulations that affect the major sources in their States. 

### California: Table 

### IV-18 lists the S02 emission factor limits found on-line as reported by CAPCD. The emission limits found cover a range of unit operations or in some cases cover all unit operations possible. 

### Arizona: Arizona air pollution control regulations restrict copper smelter S02 emissions by facility as shown below. Of the listed Arizona copper smelters, only ASARCO-Hayden and Phelps Dodge-Miami are currently operating. 

## so, Emission L irnits SO, Emissions Copper Smelter (PoLIn ds per ho ur) r,'lagma Copper Com pany. San Manuel Division**18.27~,** ASARCO. Inc

.. Haycen 

### 9.521 ASARCO. Inc. Ray Mines Division 

### 7.790 Cyprus Miami Mining Corporation. Miami 

### 3.163 Phelps Dodge CorporatiJn New Cornelia Branch 

### 8.900 Phelps DOdge CorporatiJn. Morenci Bram;h 

### 10.505

SOURCE. ClEQ.2{](J1.

AppendixA-TSD, Page 24

### Table IV-18 Point Source S02 Emission Limits 1 

### State of California

2UC ppm & 2 1 l<yibl1 DroccSS('<!

2SO PP1ll @ O'h 0,.

1000 ppm

0

..5% S SODpvm & 200 lbilif 0.8 Iw'M Mew (,quid 1.2 ibiM MOtu :<>0.111 300 ppm

2uaD DoDm 2DO:.J ppm

SG-G ppn; 2000 pP1l1 sot: c;}m t 20.(: Joitl' 2Dna p::;rn &. 20C llii'tl' 

### sec porn S 19B lbinr 300 ppm @ 1t: '\. 0,. SOU [li1ill & 1{H! lliill' 5UO ppm &. 1iJ8 jltffp 2000 ppm &. 2C!.l ;bit'l' ]00 ppm

Hf'!11 1**91~** 1::;.'f 1981**1V~2 HI~2**  19U. Unit Operation 

### see Year SO, CSIBiy§t ManufacUf\J)Q 1992 50**Ib!n~**

Coile calCHllng lOin 400 ppm &250 Ib/lH 1983 BO% raa.
HUIO caglytc craoHH 1,000 prmv 19B, 132 Ihi1000 ooucisfeea Fre'6tl fruit sufuHng 20-30 bltotl of f1'U 01 G'H'llurbCl€l' 150 ppm @1S%01 Fu.cl Combustvn u.g
.. 19713 0.56 lb.tM MBtti soli:! 'n':X[.o!,)l()l: LOO**1tJ./h~** sioo m Q@001. faeliAy

.A.tI ot11er 0p(llalicns ftot

felofe'l coo tl{} rem L,qJJd boi ltn,.oopt n11!1l!

(lIiJnufaG\ured**8u~1H** COfrijHltl(H:!S) S(!conaary t(J<Jd SCAOMD

Distrlc.t

VENAPC[' 881 Area IMAPCU

AV".PCO B.ayAri.!<! H.i"'.PC [i MOJAOM[i SlOt-,peD**Ba.~·** ArCiJ IMAPel'l SLO.A.PCO VEf>lAPC['

Bulle COlu'!.Ei feallHi!f R",'u' GrHil( Bas!!; McntfttJi'j" SJUAPCD

Ko-rn MHndcClfl(] No Snflan<J

NiL**CU{j~,1** f:!<Jy Are<J SDAPeD AVAPCD**CBid~e,.as** EDAPCD M<!Iflp(JM No. Sl6-fU

Placer ll.iQiUmll{' IMAPCD SDAPeo Bll}' Arei! Bay Area AVAPCD SCAOMD Bay**A(t~a** SCAOMD

Bay,I:'!"."ii**Sll"",,~C** l) A'.iAPCO MO

..iI>.QMD SC,A,OM U IMp-.peD StO.AYC[1

NOTES 'T!'1i!!!; 1'l"P1t:lSdnts tnt:' (!llbSSiOn foctur**Im~b. ~Not**  in dlcctfer pi.ants

...... nl; rl t!milloss

# '1 arr 1CO in PCt**{j~y** of**SO~** ··fhere ale airier**tLI:':(n:ill(jn~** lUI noted.

AppendixA-lSD, Page 25Montana: Lewis and Clark County (East Helena) (County Code: 30 -049) These SO, emission limits were partofthe SIP submitted by the State of Montana, and have been included in the Federally (EPA) approved SIP (SMAOCIP, 1995).

SO, Emissions Year 502 Emissions ASARCO Lead Smeller Adopted Unit ofMeasure Limit Sulfuric Acid Plant Stack 1995 Daily Emissions·Tons <- 4.30 per Calendar Day Sinter Plant Stack 1995 DaHy Emissions-Tons <- 60.27 per Calendar Day Blast Furnace Stack 1995 Daily Emissions-Tons <= 29.64 per Calendar Day ConcentratE' Storage and Handing 1995 Tons per**Cal~ndar** Day <= 0.552 Building Slack Crushing Mil**Baghous~** Slack-1 1995 Tons per**Cal~ndar** Day <=0.19 Crushing MiN Baghouse Slack=2 1995 Tons per Calendar Day <- 0 37

SOURCE. SMAQCIP, 19'J5. Yellowstone County (County Code: 30-111): These SO, emission limits were part ofSIPs submitted by the State of Montana but have not been approved by EPA. Therefore, these limits are State-enforceable only. In addition, the following emission limits will apply whenever the Yellowstone Energy Limited Partnership (YELP) facility receives Exxon Coker unit flue gas, or wheneverthe Exxon Coker unit is not in operation (SMAOCIP, 2000a). S0.l Em issions Year SO, EXXOll PE'lroleull1 Refinery- SllbrniHed Emissions YELP Facility for Approval Unit of M eaSllre Limit Refinery Fuel Gas Combustion 2000 Daily Emissions-T()ns per Calencar Day < 0.37 F-2 CruCleiVacuL:m Heater Stack 2000 Daily Emissions-Toil'S per Calendar Day < 1.09 Flue Catalytic Cracking (FCC) CO Boiler Stackl

DailyAverage FCC Fresh reed Rate**(~;BD):**

Less than 12"999 2000**Dail~'** Emissions+Tons per Calenaar Day <= 2355 13,000 to , 3.999 2000 Daily Emissions-Tons per CalencarDay <= 24.21 14.000 to 14.999 2000 Daily Emission.s-Tons per Calendar Day ..:= 24**~11** 15.000 to , S.999 2000 Daily Ernlssions-Tons per Calendar Day <= 24.52 16.000 to 16.999 2000 Daily Emissions-Tons per Calendar Day <= 24.89 Greater then 17.000 2000 Daily Emissions- Tons per Calendar Day <= 25.12

NOTE:::.

.r 10m t!MI IUh;JWing unn", Cn

....**~'** CO Bu./ltl**~.** Fe C co B lIule!, F -2 C,'..I dO!\' ilCUU lrl ti .J.<Hct. 1'.:) UWI. f-3 X UlbL, f**-~** \.I nIL. F -HiLl \.I'}:I. f..2C 1 Ull il. F-2(]2 \.II, 'L r -402 "n '1. f -551 u Inl.**f·fi~** 1 lJ

....'1 .•] [1(1 :1>liJfl**d!j~'** tl(,<,ltJ: HI) UI!o'(' t(3-8. ,:,-)illl 11
-, I.e .:J.l,1j SO.,'I'lm,,,,

...wn b!lhb "j}!\l I'W FCC CO D-01W-! !otaco;: ll.'Ii)'J**tl~ .:J(Jtcrnllll.~::l**  by Ih<:**Dil1f~'** Average rcc h<Jsh h::led Ratti, C**"J)r.!s.:s~:** ;J ;n U1U;J 3el!1{1S. oftHl-'ft3h per aa y ("Ie3(.1'. !e 'Una (I d to the 'Ht3/£'St

....he-itl to 8! 'tf.
SOURCE SJ...1AOCIP, 2C1CO;;

AppendixA-TSD, Page 26**SO~** Emissions Year SO, Submitted for Emissions YELP Approval Unit of Measure Limit Boiler slack emissions-when either the Exxon 2000 Daily Emissions-Tons 8.16 Coker Unit is not operating or the Exx.on Coker per Calendar Day Unit is cperating and YELP is receilling the Exx.on Coker flue gas YELP boilerslack emissions-when the Exxon 2000 Daily Emissions-Tons 5.27 Coker Unit is operating and YELP is not per Calendar Day receivilg the Exxon Coker Hue gas
SOURCE' SMAOCIP.20000l.
S0.l Emissions Year SO, Submitted Emissions Cenex Petroleum Refinery for Approval Unit of Measure Limit FCC Regenerator/CO Boiler Slack 1998 Dally Emissions-Tons per < 8.57 Calendar Day Old SRU Tail Gas Oxidizer Stack 1998 DallyEmissions-Tons per <-11.66 Calendar Day HDS Complex 

## sr,u Slack 1998 Dail,.'Emissions-Tofls per <- (I 17 Calendar Day Emissions from the Combustion Sources 1998 Combinec <- 12 Of (#3, #4. an d 115 Boiler Stacks. an C Main Daily Emissions-Tons per Crude Healer Slack) f=uel Gas Fired Calenaar Day Sources. ant the Combustion of Sour Volater Stripper Overhead Gases in the Main Crude Heater
SOURCl. $MAQCIP.2:.;OJL
SOl Emissions Year SO, Submitted for Emissions Conoco Petroleum Refil1ery Approval Unit of Measure Limit Main Boiler House Stack 1998 Daily**Emissions-Ton~,** per <- 3,86 Calenoar Day' FCC Stack 1998 Daily Emisslons-Tons per <- 3_95 Ca.lendar Day Jupiter**Su~ur** SRU Slack 1998 Daily Emissions-Toos I:'er <- 0 30 Calendar Day Process Heaters ("Ii1 1/2. #4. #5.#10. 1998 Combined Daily < 0.35 #11. # 12. #13. #14 #15. # 16.#17. #18. Emissions-Tons per #19. #20. #21.#22. #23. #2J). Cok.er Calendar Day Healer. Fractionator Feed Healec and Recycle Hydrogen Healer

SOURCE. SMAOCiP,2COOL

Appendix A-TSD, Page 27502 Emissions Year SO, Submitted for Emissions Monlana Sulfllr and Cllemical Company Approval Unit of Measure Limit SRU 100 Meter Stack' 1998 Daily Emissions-Tons <- 14.31 per Calendar Day SRU 30 Meter Stack 1998 Daily Emissions-Tons <- 0.048 per Calendar Day

NOTE Wl1enevllH**SO~@IlI\$IU.HtS** rrotn either ttl

... Rail!()ad Holier, lhe H-1 UnIt, Ifh'! H '·A Ulblt the H1·1 Un!!. or t!1e tl1 -ZUnit IH'l exlHHJstmg Unougtltfl@ SRU 30 meleJ slaCk,
SOURCt.: SMAOCIP,2lJ-OOb,
S02 Emissioos Year S0, Submitted for Emissions Weslern Sugar Approval Unit of Measure Limit Boiler House Sac}., 1998 Daily Emissions-Tons <- 3.42 per Calendar Day Easl Dryer Stack and Vlesl Dryer Stack 1998 Com bined DaiIy <- 0.354 Emissions-Tons per Calendar Day

SOURCE. SMAQClP',2ilOOl;

Nevada: Nevada State SO, regulations were summarized as follows: SOt Emissions SO, Year Emissions Sources Adopted Unit of Measure Limit Gabbs Plant of BasIc Refractories, Air QualiLy 199b Pouncs per MMBtl, <- 0.26 Hegion 148, Basin 122. Gabbs Valley Nevaaa Power Company's Reid Garaner Power 1995 Pounes per MMBlu <-= 275 Station_ Pov.'er Generating Unh, Number 1. 2. anc 3 Air**Qua~ty** Control Regbn 13.Basin218. California \.'Vash Nevaoa Power Company's Reic Garaner Power 1995 Pounas per M MBtu <- 0.145 Station. PO\''l'er G eneraling Unit Number';, Air Ouality Control Region 13. Basin 218. Califo rnia Wash' Slerra Pacific PO\'1e r Com pany's ND rlh Va Imy**199~)** Pounds per MMBlu <- 0.3 PO\'o'er Station. Power Generating Unit 2. Air Quality Control Regier; 147 Basin 64. Clovers**Area~**
NOll S 'llH! cfh::::ltlncycl th{! captJre of**Su~tJr** musl be m;l'tlt-llllUd aL i) mfHmum of**B~** P{!<!Ccflt uase<l on o:J**J{}<la~'** wllmg a..-aro\Jc. "lfJ{! ofka.!f1c'lollhe cal"t.i((J of SuitJ-t f!l>.JslllC ma'l1t-JJ1I(J!J fll ;) !11l!HllUm of 10**p~lcanl** IJ-asoo on tl 30-<lay totIng a..-c'<lgc

Appendix A-TSD, Page 28New Mexico: Coal Burning Equipment (After December 31, 1984, the owner or operator of a coal burning station that has two or more units 0 f existing coal burning equipment that have a rated heat capacity greater than 250 MMBtus per hour has an 502 emission limit of 17,900 pounds per hour, which is averaged over any three-hour period and determined on a total station basis (NMED, 1995).) 

### SO, Emissions Year Adopted 

## I Unit of Measure 

### SO Emissions Limit 1985 

## I Pounds per Hour 

### 17.900

SOURCE. NMEO.1995.
Natural Gas Processing Plants SO Emissions SO, Average SOl Undihlted Off-Gas Year Emissions

Released Stream Adopted Unit of Measure Limit >- 10 tons pel ;. 20 mole percent H::S**199~,** Numberof pounds for <- 10 day (lpd) every 100 pounos >- 10 tpc <= 20 mole percent H;:S**199~** Number of pounDs for <- 12 every 100 paLlnes 7.5 <- 10tpc > 20 mole perce nt**H~S 199~**  Number of pounds fOf <- 10 every 100 pounds 7.5.:.: 10 tpc < 20 m ole perce nl H,2S 1995 Number of pounds for < 12 every 100 pounds**SOUI~Cl** NMELJ.19St.
Petroleum Refineries 

### SO, Emissions Year Adopted 

## I Unit of Measure 

### SO, Emissions Limit 

### 1995 

## I Tons per 24 hours <- 

### 5

SOURCE. r'llM[O.1995.

Sulfur Recovery Plants (This limit applies to plants where fabrication, erection, or installation commenced before August 14, 1974. 

### SO, Emissions Year Adopted 

## I Unit of Measure 

## I SO Emissions Limit 199:1 

## I NL:mber of pounds for every 100 pounds 

### I <- 12

SOURce. NMED,1995

AppendixA-TSD, Page 29SulfuricAcid Production Units 

### so", Emissions Sulfuric Acid ProducHon Units Year Adopted Unit of M easure SO Emissions Limit Units locaed within the Pecos-Permian 1995 Pounos per hour <::: 575 Basin Intrastate AirQualityControl Region 1 Units locaed outside the Pecos-Permian 1995 Pounds per hour <- 680 Basin Intrastate At Quality Control Region
NOl E: 'W:ttl a mm<fTIum stack OOlgtlt of 4(} mete!s
SOURCE NMED. 1995. Nonferrous Smelters SO, Emissions YearAdopted Unit of Measure SO, Emissions Limit 

### 1995 Pounds per hour (Annual average Emissions) <- 

### 7000'

NOTE. El<.copl as prol/.(I€c'(j lor In SecllOfI 1 12 of Tille 20, Chaphff 2, Part 41 11 lhi! Nt!'w MelocCI**A(jrrtlnlstr.attV~ CoCl~**  fNMED. 19"J5).
SOURCE. NMED.1995.

Utah: The SIP for Utah was last approved by EPA on July 8, 

### 1994, except for the Amoco Oil Company submission.

SOt Emissions Year S02 Emissions Point Source Adopled Unit of Measure Limit Amoco Oil Company Pencing Tons per year <- 1.964 KennecDtt Utah Co pper Srne lter- 1994 Tons per year !annual average) <-14,191 Main Stac,",**Cry~.en F~efinilg.**  Inc**199·~** Tons per year < 183 Chevron U.S.A. Inc 1994 Tons per year < 1.731

SOl Emissions Year S02 Emissions Point SourcE! Adopted Unit 01 Measure Limit Philbps 66 Company 199. Tons per year <-1.762 Flyng J Inc. 1994 Tons per year <- 824.8

SOURce USIP, 199..: After gathering the above information about Slate regulations, the S02 emission limits were compared with the S02 emissions in the WRAP 

### 1996 point source file for affected facilities. In all cases, it was found that emission points/facilities were in compliance with these 502 regulations. Therefore, no additional S02 controls were placed on point sources in the 

### 2018 emission forecast.

AppendixA-TSD, Page 30Stationary Sources

- Retirement Factors, Unit Lifetime Analysis: This information is from Chapter V "Retirement Factors

- Unit Lifetime Analysis, Western Regional Air Partnership Emission Forecasts For 2018
- Final Report", E.H. Pechan & Associates, Inc., December2002, Pechan Rpt. No. 02.12.003/9409.000. In the original lAS model, future yearforecasts ofelectric utility emissions used estimates of the date of initial operation and expected unit lifetimes in years to determine when existing source emission rates were likely to be replaced with new source emission rates. So, for example, if an oil-fired utility boiler began operating in 1970, it would be expected to be replaced by a new boilerthat emits at NSPS/BACT level emission rates in 2000 at the end of its 3D-year lifetime. For non-utility units, the lAS model includes the effects of retirements using an annual rate. So, each unit in any source category has the same annual retirement rate applied. For example, the annual retirement rate for industrial boilers in the lAS model has been 0.6 percent per year. If this retirement rate were applied to the 1996 to 2018 forecast horizon that is being used for this project, then 12.4 percent of industrial boiler capacity would be retired during this 22-year period. One ofthe objectives ofthis project was to establish projection methods for the largest non-utility units that parallel those used for utilities. This requires gathering and using information about the year of initial operation for individual non-utility units and expressing non-utility unit lifetimes in years. The year of initial operation data gathering activity is described in Chapter II. This chapter describes the effort to establish appropriate lifetime estimates for the source categories (scc_ ids) in the lAS model. Industrial Sources: This section deals with estimating the lifetimes ofthe lAS industrial sources listed in Table V1. The lAS annual retirement rates for each sector were converted into the lifetime years listed above bythe following formula: 

## 1 "_

. = Years 

## Hetlrement Hate We consulted several other data sources, such as Internal Revenue Service Publications, Bureau of Economic Analysis (BEA) depreciation schedules, other industry publications, and estimates provided by authorities in different sectors, to estimate the actual lifetimes of the different industrial sector units or plants. The following sub sections describe how the lifetimes ofthe different industrial sector units or plants were calculated or estimated.

Appendix A-TSD, Page 31Table V-1 Industrial lAS Source Group Retirement/Lifetime Years

Annual Equivalent Retirement Lifetime Sector Scc_id Rate (Years) Source Industrial Boilers (Fuel inngbo 0.6**(l,~** 167 Industrial Combustion Emissions (ICE) Model combustion) incobo inwolJO inoibo inothr Inngre Copper Smelters mcopp 1,20/0 83 NEMS Model (ahar Primary Metals secor) Oil and Gas Production inoipr 2.3% 43 NEMS Model (Msc. ManufactUring) (except Sweetening Plants), Ingspr Solvents, Other NEC. Inngcm inngfl Refineries inpere NitricAcid Plants Inpepr Gas Production-Sweetening inchem 1.9% 53 NEMS Model (Buk Chemicals sector) Plants longs¥: Organic Chemical Storage inorc1l Gasoline Storage magpe

Industrial Boilers: The annual retirement rates used in the original lAS model for industrial fuel combustors or industrial boilers are taken from a U.S. energy model named the ICE model. The ICE model was developed and applied as part of the National Acid Precipitation Assessment Program (NAPAP) emission and control techniques evaluation process. The assumed lAS annual industrial boiler retirement rate of 0 .6 percent converts into a lifetime of 167 years. However, other data sources present boiler lifetimes that are much lower, and these estimates are presented next. According to Steam/its generation anduse, the degree of pressure and heat associated with a boiler, along with its design, function, and operation affect boiler lifetime. Industrial boilers operating at pressures above 1,200 psi (pounds per square inch, absolute or difference) and 900 F (482 C) final steam temperature undergo more complicated aging mechanisms than lower temperature boilers (Stultz, 1992). The high pressures and associated high furnace wall temperatures make these units more susceptible to water side corrosion. Table V-2 presents the component replacement sequence for a typical high pressure, high temperature boiler (Stultz, 1992).

AppendixA-TSD, Page 32Table V-2 Component Replacement Schedule for a Typical High Temperature, High Pressure Boiler

Typical Life (Years) 20 25

30 35 40 Component Replaced Miscellaneous tubing Atlemperalar Superheater (SH) SH outlet header Burne rs and throats Rehealer Primary economizer Lower furnace Cause for Replacement Corrosion, erOSIOn, over-heat'19 Fatrgue Creep Creep fatigcc Overheating. corrosion Creep Corrosion Overhealing, corrosion
In the case of a typical high temperature, high -pressure boiler, most boiler pressure part components have been replaced after 40 years of operation. However, the aging process and rate of component degradation differ from boiler to boiler. Moreover, the actual component life of a boiler is highly variable depending on the specific design, operation, maintenance, and fuel (Stultz, 1992). In another analysis, Teknekron Research Inc. assumed a 30-year boiler lifetime when calculating the retirement rate ofa boiler in its report "Review of Modeling Activities Related to New Source Performance Standards for Industrial Boilers" (Placet, 1980). However, it was also found that some boilers over 70 years old were still in use, with no plans to retire them. Therefore, Teknekron suggested an approximate boiler lifetime of 40 years as a reasonable estimate ofthe lifetime ofan industrial boiler(Placet, 1980). The Internal Revenue Service's "Publication 946: How to Depreciate Property" lists lifetimes of industrial boilers from a depreciation pointofview. The IRS uses a system called Modified Accelerated Cost Recovery System (MACRS) to depreciate assets. According to this system, a class life of 28 years is estimated for the asset category "Central Steam Utility Production and Distribution." In addition, 20-year and 28 -year recovery periods are estimated for the General Depreciation System (GDS) and Alternative Depreciation System (ADS), respectively (IRS, 2000). The lifetime years used in the depreciation schedules in this publication may not be directly representative ofthe actual lifetime ofa boiler. Therefore, we presume that these lifetimes represent a minimum lifetime estimate for industrial boilers. This same issue arose in interpreting the BEA 's depreciation schedules. These schedules estimate a service life of 32 years for "Steam Engines and Turbines" (Fraumeni, 1997). Again, since this depreciation lifetime may not directly represent the actual lifetime of a boiler, these lifetimes might representa minimum lifetime estimate for industrial boilers. Discussions were held with Bob Bessette ofthe Council of Industrial Boiler Owners (CIBO), Randall Rawson of the American Boiler Manufacturers Association, Ian Lutes of Foster Wheeler Corporation, and Brian Moore ofthe Hartford Steam Boiler Company. The opinion among this group was that while industrial boiler lifetimes could range from 30 to 100 years, the majority of these boilers stay in service from 35 to 60 years. Industrial boilers generally have less focus on maintenance than utility boilers. Utility boilers, as a rule, are optimally maintained. In some cases, industrial boiler owners are reticent to perform maintenance on

AppendixA-TSD, Page 33their units for fear of triggering new source review. Therefore, it would be expected that the average lifetime of an industrial boilerwould be less than that of a comparable utility boiler. There are exceptions, of course, especially when industrial boilers are well maintained and operated at lowerpressures. Field erected units tend to have higher lifetimes than package boilers foravariety of reasons. Through discussions with staff at the U.S. Department of Energy, it was determined that the most comprehensive data source about expected unit lifetimes by source type was Energy and Environmental Analysis's Industrial Sector Technology Use Mod el (ISTUM). The estimated lifetimes by industrial sector technology from ISTUM (EEA, 2001) range from 20 years for refinery heaters and distillation units to 30 years for industrial boilers. However, there is evidence that the equipment turnover in these industries is not nearly as rapid as ISTUM predicts. Pechan's recommendation based on the evidence provided by the boiler industry representatives is that a 45-year lifetime be used for all industrial boilers in the emission forecasts to 2018. This is 1.5 times the lifetime used by the ISTUM model. It is also recommended that the lAS model lifetimes for other industrial sector technologies be 1.5 times the ISTUM values. This makes the lifetimes for most refinery equipment 30 years, and makes the cement kiln lifetimes 37.5 years. Making these changes provides a more conservative estimate of future year WRAP State emissions. A summary of estimated unit lifetimes by industrial source category is provided in Table V-3. Table V-3 Summary of Estimated Unit Lifetimes by Industrial Source Category

Source Catego ry Industrial boilers
Li me co lcltl ing
Cement making
Lime calcining (paper)
Refineries

- disldlation
Refineries· crGcking
RefinerieS

- alkylation
Refineries

- tlydrogen production
RefinerieS

- tlydrotrealing Refineries reforming
Refineries other petroleum prodUG ts Refineries

- generic carriers

AppendixA-TSD, Page 34 Estimated Unit Lifetime (years) 45
4b
37 b 45 30
30
30
30
30
30
30
30Example Calculations The lAS model algorithms are applied to estimate 2018 emissions given the primary variables affecting emissions in that year, which are: 1996 emissions, unit date of initial operation, expected unit lifetime or retirement rate, newsource control efficiency, and growth rates/factors. The base lAS algorithm for performing emission forecasts to 2018 at the unit level is shown in the equation below. 20] EmiSbioa.,; = 19Y6 EmissHH1S (l - Fraetloll Retired) 

### + lHHG Emissions (l\ew Souree Con11'01 EffIciency) (G rowth FnetOl'

- (1

- Fraclion Retired))


### In the point source emission projections, there are three cases that all ofthe sources fall into. These three cases are listed below:

l. 'I'll(' inillHl datc' ofoperntion is known. but lh" unit hai' nol retin·d hy :2018. 2. The initial date of**olH~rnl'ion** is known and l.he unit's emissions ha Ve**bet~n** fully replflcpd**h~'** new soure(' emiss'ion rates. :.1. No 

### iuiljal date of**OIH~rfltion** is Hvnilablf', so**r(~tITenH'nt rat(~8**  are**lL8l~d** to distinguish existing v (,t.';';us uew**BOUre(~ l~missioll**  fraetions. Example calculations of2018 emissions are provided belowforeach ofthese three cases:



### Cast' ] EXaITlIJk': 1\)96 NO. emissions 

### = 'lAin 

### tpv 

### , 

## .. Expected 

### Heti:relllent Datt'

# =20;39 New Source Control Eiricipru;y

# =97 ppreent**~O]I' Ellli~sifms,**  

### = 

## 5.·l:n**tJl~'** (1

- 

### 0) 

### + 5A:n tpv 

### (O.O:\) (l.G7:}

- (l-U))**~OL" Emi~~i(jns,**  

### =**5.~:;7 tJl~'**  + 

### 109**tp~** 

### = ;).';'lG**tp~** In this example, because the unit is expected to still be operating in 2018, the existing source portion of the SO, emissions (5,437 tpy) remains thl'l same as in 1996. Any increase in activity at this facility is estimated to occur at new source emission rate levels, which are 3 percent ofexisting source rates. 

### C'",f' EX'''lll)](''**!~H)G** 

### 1\'0, emissions =**~,!j:l1** 

### tP)' EXI"'ClN! HdH'ctndll 

### Dalc' =**2(1(1~** :\l'W 

### Source' Control 

### EfIieipIH'-." = 

### 72 pereent**~(nl'** 

### Emissions =**~.9:ll** tpl' (1

- 1) 

### + 1,9:H (0.28) (1.719

- (J. 

### I))**=()~1.'lOG** 

### = 1.406 t p\ Because this unit has an expected retirementdate before 2018, all ofthe 2018 emissions are at new source rates, which are 28 percent ofexisting source rates. The growth factor that is applied to the new source emission rates incorporates 1996 activity, plus expected activity increasesfrom 1996 to 2018.

AppendixA·TSD, Page 35**C~asc;J Ex;]mph~':**  

### l\O Sp('eific 8t,Jrl. D.fltefHetirement DatL'**~(~W** SfJUl'{x' Conti'oI Efficiency 

## =GO pcrecnt 2D18 Emissions

# =2.74::**tp~·** (I

..7m3.» 

### + 2.74:1 (D.·I) (1.(;:),1

. (I

..7:3:1:(1) =,:12 + 1.5(J(J tpy

= 2.2:3:1**tp~** With no specific startdate/retirement date available, the retirement rate is applied in a way to capture the percentage 0 f existing capacity in this industry that is expected to retire each year over the 22-year forecast horizon. In this example. 73 percent of the 1996 capacity is estimated to have been retired by 2018. While, in reality, units do not retire a fraction oftheir capacity each year. this calculation is expected to provide a reasonable simulation ofexisting source retirement, new source grow1h when spread over a broad geographic region, like the WRAP States. Implications ofRetirement Assumptions in lAS The practical result of using the revised estimates of unit lifetimes by source category and technology is that future emissions are lower for source categories with significant differences between new and existing source emission rates. Figure V-1 presents an example 1996 to 2018 S02 emissions path using the previous industrial boiler lAS retirement rate of 0.6 percent per year compared with the new retirement rate of 2.2 percent per year. This is a source category where the new source S02 control efficiency is 90 percent, so the faster the existing units retire, the more rapid the decline in future S02 emissions. A 2.0 percent per year new source growth rate is used in this example. So, a 1,000 tpy S02 source in 1996 would be estimated to have 2018 emissions of 936 tpy if the prior lAS retirement rate was used. The emission forecasting methods applied in this study yield a 2018 emissions estimate of 619 tpy. This is a significant reduction in future emissions from this source category compared with prior methods. Figure V-1 Industrial Boiler Llfetilne Effects on Emission Forecasts 1100

1000 >; 

## g; 900 

# '" C 0 'iii 000 .!!! E w 

# o' 700 VJ
600

500 1995 Retirement R9hts -----<>-- O.6'}b lyear

._..."._- 2.2"klyear

2000 f 2005 2010 2015 2020

Calendar Year

Appendix A-TSD, Page 36

### Appendix B-TSD Use ofEPA Guidanceand Best Practices

The WRAP and its contractors followed EPA emissions inventory guidance and best emissions inventory development practices, EPA modeling guidance, and used professional judgment in preparing technical analyses for §309. Specific references to EPA guidance documents are listed throughout the earlier chapters, usually as web addresses and report titles, aswell as in Appendix M ofthis document.

### AppendixC-TSD 1996 BaseCase Emissions Used in Air Quality Modeling

The following spreadsheet details emissions used in the 1996 base case modeling run. These are not the emissions used in the 1996 base case model performance evaluation run, where the model-predicted results are compared to monitoring data. The emissions following are used asthe basis of"projected visibility improvement", requirement of §309, for the 16 Colorado Plateau Class I areas. Fire emissions in the spreadsheet below are typical wildfire, and the 2018 base case emissions for foresVrange prescribed fire and agricultural fire. The 1996 base case modeling run emissions spreadsheet isfound onthe WRAPwebsite at: http://wrapair.org/309/documents/FinaIDocs/1996 Base Case Final.xls.\ 

### Appendix 0-TSO 

### 2018 Base Case Emissions Used in Air Quality Modeling

The following spreadsheet details emissions used in the 2018 base case modeling run. The emissions following are based on "rules and regulations on the books" as of 2001. Fire emissions in the spreadsheet below are typical wildfire, and the 2018 base case emissions forforest/range prescribed fire and agricultural fire. The 2018 base case modeling run emissions spreadsheet isfound ontheWRAP websiteat: htlp:llwrapair.org/309/documents/FinaIDocs/2018 Base Case Final.xls.

### Appendix E-TSD 2018 Scenario I Emissions Used in AirQuality Modeling The following spreadsheetdetails emissions used in the 2018 Scenario 1 modeling run. The emissions following are based on "rules and regulations on the books" from the 2018 base case, plus adoption ofthe S02 Annex Milestones and Pollution Prevention programs across the Grand Canyon Visibility Transport Commission 9-state region. Fire emissions in the spreadsheet below are typical wildfire, and the 2018 base case emissions for forest/range prescribed fire and agricultural fire. Scenario 1 is the first of two projections of visibility improvementfrom implementation of§309 programs. The 2018 Scenario 1 modeling run emissions spreadsheet isfound on the WRAP website at: http://wrapair.org/309/documents/FinaIDocs/2018 Scenario 1 Final.xls.

### Appendix F-TSD 2018 Scenario 2 Emissions Used in Air Quality Modeling The following spreadsheetdetails emissions used in the 2018 Scenario 2 modeling run. The emissions following are based on "rules and regulations on the books· from the 2018 base case, adoption of the S02 Annex Milestones and Pollution Prevention programs across the Grand Canyon Visibility Transport Commission 9-state region, as well as adoption of the Enhanced Smoke Management Programs across the Grand Canyon Visibility Transport Commission 9-state region, based on the 2018 Optimal Smoke Management emissions inventories for forest/range prescribed fire and agricultural fire. Typical wildfire emissions were used in this scenario. Scenario 2 is the second of two projections of visibility improvementfrom implementation of§309 programs. The 2018 Scenario 2 modeling run emissions spreadsheet isfound on the WRAPwebsite at: http://wrapair.org/309/documents/FinaIDocs/2018 Scenario 2 Fina1.xls.

### Appendix G-TSD 2018 BART

### with Uncertainty Scenario Emissions Used in AirQuality Modeling The following spreadsheet details emissions used in the 2018 BART with Uncertainty Scenario modeling run. The emissions following are based on analyses described in Chapter 1 ofthis document. Fire emissions in the spreadsheet belowaretypical wildfire, and the 2018 base case emissions for foresVrange prescribed fire and agricultural fire. The BARTwith Uncertainty Scenario was compared using airquality modeling to the S02 Annex Milestones Scenario, and the results are discussed in Chapter4ofthisdocument. The 2018 BARTwith Uncertainty Scenario modeling run emissions spreadsheet is found on the WRAP website at: htlp://wrapair.org/309/documents/FinaIDocs/2018 BARTwUncertainty Final.xls.

### Appendix H-TSD 

### 2018 S02 Annex Milestones Scenario Emissions Used in AirQuality Modeling The following spreadsheet details emissions used in the 2018 S02 Annex Milestones Scenario modeling run. The emissions following are based on analyses described in Chapter 1 ofthis document. Fire emissions in the spreadsheet below are typical wildfire, and the 2018 base case emissions forforest/range prescribed fire and agricultural fire. The S02 Annex Milestones Scenario was compared using air quality modeling to the BART with Uncertainty Scenario, and the results are discussed in Chapter4 ofthis document. The 2018 S02 Annex Milestones Scenario modeling run emissions spreadsheet is found on theWRAP website at: htlp:llwrapair.org/309/documents/FinaIDocs/2018 S02 Annex Milestones Final.xls.

### Appendix I-TSD 2018 Stationary Source 50% NOx Reduction Scenario Emissions Used in Air Quality Modeling

The following spreadsheet details emissions used in the 2018 Stationary Source 50% NO, Reduction Scenario modeling run. The emissionsfollowing are based on analyses described in Chapter4 ofthis document. Fire emissions in the spreadsheet below are typical wildfire, and the 2018 base case emissions forforesUrange prescribed fire and agricultural fire. The 2018 Stationary Source 50% NO, Reduction Scenario was modeled to satisfy requirement of §309, andthe results are discussed in Chapter4 ofthis document. The 2018 Stationary Source 50% NO, Reduction Scenario modeling run emissions spreadsheet isfound ontheWRAPwebsite at: http://wrapair.org/309/documents/FinaIDocs/2018 NOx 50percent Decrease Stationary So urces Final.xls.

### AppendixJ-TSD 2018 Stationary Source 50% PM10 

### Reduction Scenario Emissions Used in Air Quality Modeling The following spreadsheet details emissions used in the 2018 Stationary Source 50% PM lO 

### Reduction Scenario modeling run. The emissionsfollowing are based on analysesdescribed in Chapter 4 ofthis document. Fire emissions in the spreadsheet below are typical wildfire, and the 2018 base case emissions forforesUrange prescribed fire and agricultural fire. The 2018 Stationary Source 50% PM,o 

### Reduction Scenario was modeled to satisfy requirement of§309, and the results arediscussed in Chapter4 ofthis document. The 2018 Stationary Source 50% PMlO 

### Reduction Scenario modeling run emissions spreadsheet isfound ontheWRAP website at: http://wrapair.org/309/documents/FinaIDocs/2018 PM

### 10 50percent Decrease Stationary S ources Final.xls.

### Appendix K-TSD 2018 

### Stationary Source Simultaneous 25% NOx

### and 25% 

### PM10 Increase Scenario Emissions Used in AirQuality Modeling The following spreadsheet details emissions used in the 2018 Stationary Source Simultaneous 25% NO. and PM 10 

### Increase Scenario modeling run. The emissions following are based on analyses described in Chapter 4 of this document. Fire emissions in the spreadsheet below are typical wildfire, and the 2018 base case emissions for forest/range prescribed fire and agricultural fire. The 2018 Stationary Source Simultaneous 25% NO. and PM 10 

### Increase Scenario was modeled to satisfy requirement of §309, and the results are discussed in Chapter4 ofthis document. The 2018 Stationary Source Simultaneous 25% NO. and PM10 

### Increase Scenario modeling run emissions spreadsheet isfound on the WRAPwebsite at: htlp:llwrapair.org/309/documents/FinaIDocs/2018 PM10 25percent and NOx 25percent In crease Stationary Sources Final.xls.

### Appendix L-TSD Clean Air Corridor Change in Emissions 1996 to 2018

The projected changes in emissions, within the clean aircorridor, are show spatially in the following figures for S02, N02 , YOC, 

### PMIQ, and 

### PM2
.5.

S02 DifferenCE: Milestones-1996 GCVTC ClE-an Air Corridor

• -5091 00 (0-500000 ·500000to ·250000 

# o ·2500 00tv·1 000 00 

# o ·1000.00to ·50000 

# o ·50000to 0.00 

# o 000t050000 

# o 500 00to 1000 00 [] 1000 0010 2500 00 2500.00 to 5000 00 500000to 791535

S02 DIfference Mlleslone-198(, Numberofvalu,:,s 71 Sum tJ.377 7<168<1386377 Ivlinlmum -509061414923499**~"'axlmurn** 27364809362477:' Mean 6165840132516024 .... b t:"'.",



# ..

S02 emission difference, by county, 2018 projections with WRAP S02 Annex Milestones 

### and 1996base.

Appendix L-TSD, Page 1

## ... 

# •

2018-1996 NOX Numberofvalues 71 SUm -38072.3930836458 MlnlmUll1

-72.477366638261 M3Xlmurn791534510900202 M88n

-536 230883502055 NOX Difference

2018-1996 GCVTCCIE-81l Air Corridor

• -7347 74 to -5000.00 -5000.00 to -250000

-2500 00to -100000 

# o -1000.00 to -500 00 

## D -50000 to (JOO 

## D 000 to 500 00 

# o 500 00 to 100000 100000to 250000

• 2500 00to 5000.00

• 500000to 791535**(~--------\** ,



### NO

### xemission difference, by county, 2018 projections and 

### 1996base

Appendix L-TSD, Page 2\lOCDifferencE' 2018'1996 GCVTC Clean Air Corridor -844398 to -500000 -500000 to -2500.C:) 

## bI

- 2500 00 to -1000 00 

# o -100000to -50000 

## ID -500 00to 000 

# o 0 00 to SOO 00 

# o 50000 to 1000 00 

## trl 100000to 2500.00 2500.00 to 500000 5000.00**~o** 7915 35

2018-1996\lOC l\lumber ofvalues 71 Sum -55028,6971227195**I\~inlrnurn** -8443,98234351755 !vlaxlmum80.3988889846232 Mean -775052072150979

# ~rl\ \.**~~.,**

VOC emission difference, by county, 2018 projections and 1996 base

Appendix L-TSD, Page 3PM10 Difference 2018-1996 GCVTC Clean Air Corndor

• -2757 00to -2000 00 -2000.00to -150000 

# o -1500.00to -100000 

# o -1000.00to -500 00 

# o -50000 to 000 

# o 000to**2~O** 00 

# o 25000 {Q 500 00 50000to 1000.00 1000 00 to 2000 00

• 200000 to 3211 00

F'M10 2018·1996 Number ofvalue-s 71 Sum 15219.1008815545 Minimum -2756 14486240593 Maximum3210.90373021597 Mean 214353533543021



### PM 10

### emission difference, by county, 2018 projections and 1996 base

Appendix L·TSD, Page 4 .... 1I**t;~** II>



### 1 \ 

### \

. \



### IPM2 5 DifferencE' 2(118-1996 GCVTC CIE':ln An Corndor

• -610.00 to -50000 500 00to -25000 

# o -250 00 to -10000 

## D -100 00 to -5000 

## D -50 00 10 000 

# D 000 to 25000 

## D 250.00 to 50000**~'oo** 00 to 100000

• 100000to 200000 2000 00to**3381:~** 1:11)

Pf\.12.5 2018-1896 Number ofvalues 71 Sum 12702**337832927~1** rl1lrilrnum -609 13852855864 Maximum3385.58803138402 Mo::an 178.906166660957



### PM2.5

### emission difference, by

### county, 2018 projections and 1996 base

Appendix L-TSD. Page 5 

# ... a



# ..Appendix L-TSD, Page 6

### AppendixA-SIP Appendix B-SIP AppendixC-SIP
Appendix D-SIP
Appendix E-SIP
Appendix F-SIP

Appendix G-SIP
Appendix H-SIP
Appendix I-SIP

AppendixJ-SIP

Appendix K-SIP 

### SIP APPENDICES (as listed in the July 10, 2003 SIP template)

Projection of Improvement in 16Class IAreas Analysis ofthe Clean Air Corridor (CAG) Mobile Sources: 2003 Interim Progress Report (The bodyofthe SIP document contains this information) Fire Programs (The bodyofthe SIP documentcontains this information) Dust ImpactAssessment and Contribution to Impairment (The bodyofthe SIP documentcontains this information) Pollution Prevention-Summaryof Renewable Energyand EnergyConservation Programs in the State (The bodyofthe SIP documentcontains this information) Evaluation ofAdditional Recommendations from the GCVTC (The bodyofthe SIP documentcontains this information) SIP Strategies Developed through Interstate Coordination (The bodyofthe SIP documentcontains this information) Geographic Enhancements-Model MOA between Federal Land ManagementAgency and State-optional (Not included) Long-Term Strategies and Visibility Improvement Expected for Additional Class IAreas-optional (Not applicable) Summaryof Emission Inventoryand Tracking ProgramsAppendix A-SIP Projection of Improvement in 16 Class I Areas

Overview: The Western Regional Air Partnership (WRAP) Regional Modeling Center (RMC) has analyzed visibility changes in the 16 Class IAreas on the Colorado Plateau resulting from the implementation ofall 309 control strategies.

Scenarios: The RMC modeled two scenarios. Scenario 1 is designed to assess the effect of the GCVTC-recommended control strategies, implementation ofthe following GCVTC strategies: the S02 Annex Milestones, the regional pollution prevention program, maintenance of existing base smoke management (BSM) programs, and accounting forthe 2018 base case emissions (known and adopted federal, tribal, state, and local control programs in the contiguous WRAP region). Scenario 2 is designed to assess the effect ofthe implementation ofEnhanced Smoke Management Programs (ESMP), as reflected in the Fire Emissions Joint Forum's 2018 Optimal Smoke Management (OSM) inventory. ESMPs were recommended by GCVTC and are required in §309 (seefurtherdiscussion later in this Appendix). Note that the WRAP did not model visibility improvements resulting from the implementation of control strategies by a specific state or tribe. Such emissions changes and the resulting visibility changes are so small they are likelyto be undetectable.
Projected Visibility Changes: The RMC modeled visibility at the 16 Class I areas on the Colorado Plateau for the 2018 Scenario 1 and Scenario 2 control strategies. Tables 2a and 2b on the following pages display the visibility improvements from the 1997-2001 baseline period to 2018 under Scenario 1 and 2 conditions. Table 2a contains projected visibility improvement for the average 20% worst visibility days (measured in deciView), and Table 2b contains projected visibility improvementforthe average 20% best visibility days (in dV). Note that Worstdays are those in which visibility is the most impaired. Best days are those in which visibility is the least impaired. These tables are also contained in the Albuquerque/Bernalillo County's Regional Haze SIP document, as is a discussion of the modeling resultsforthe San Pedro Parks Wilderness Area in New Mexico.

Appendix A-SIP, Page 1

### Table 2a. Projected Visibility Improvementatthe 16 Colorado Plateau Class IAreas in 2018 on the Average 20% Worst Visibility Days, resulting from implementation of "All §309 Control Strategies" 2018Scenarios 1 and 2. Modeling Results (deciviews) 2018 Base 2018 Scenario 1 2018 Scenario 2 (20% Worst Days' (20% Worst Days' 1997-2001 Case Monitoring (20% Worst Visibility forall Visibilityforall Data Days' §309 Control §309 Control Colorado Plateau State (20% Worst Visibility for Strategies (S02 Strategies (S02 Class IArea Annex Milestones Annex Milestones Days' all controls and Pollution and Pollution Visibility

- "on the Prevention) with Prevention) with deciviews) books" as of Base Smoke Optimal Smoke 2002) Management) Management) Grand Canyon NP AZ 12.30 11.62 11.56 11.51 Mount Baldy Wilderness AZ 14.30 12.22 12.02 11.96 Petrified Forest NP AZ 13.00 11.99 11.82 11.74 Sycamore Canyon Wilderness AZ 15.40 11.63 11.51 11.48 BlackCanyon of Gunnison NP CO 11.30 10.90 10.76 10.60 FlatTops Wilderness CO 10.50 11.04 10.91 10.73 Maroon BellsSnowmassWA CO 10.60 11.15 11.00 10.84 Mesa Verde NP CO 13.10 12.24 12.03 11.84 West Elk Wilderness CO 10.60 11.19 10.99 10.84 Weminuche Wilderness CO 11.30 11.08 10.89 10.72 San Pedro Parks Wilderness 

### NM 10.70 12.33 12.12 11.71 Arches NP UT 12.10 12.41 12.29 12.15 Bryce Canyon NP UT 11.80 12.26 12.24 11.95 Canyonlands NP UT 12.10 12.41 12.31 12.18 Capitol Reef NP UT 12.10 12.51 12.49 12.36 Zion NP UT 13.60 12.13 12.09 12.03

AppendixA-SIP, Page 2Table 2b. Projected Visibility Improvement at the 16 Colorado Plateau Class I Areas in 2018, on the Average 20% BestVisibility Days, resulting from implementation of"All §309 Control Strategies"" 2018 Scenarios 1 and 2. Modeling Results (deciviews) 2018 Base 2018 Scenario 1 2018 Scenario 2 (20% Best Days' (20% Best Days' 1997-2001 Case Monitoring (20% Best Visibilityforall Visibility forall §309 Control §309 Control Colorado Plateau Data Days' Strategies (S02 Strategies (S02 Class I Area State (20% Best Visibility for Annex Milestones Annex Milestones Days' all controls and Pollution and Pollution Visibility

- "on the Prevention)with Prevention)with deciviews) books" as of 2002) Base Smoke Optimal Smoke Management) Management) Grand Canyon NP AZ 4.80 4.76 4.72 4.64 Mount Baldy AZ 5.50 5.49 5.46 5.36 Wilderness Petrified Forest AZ 6.50 5.18 5.14 5.10 NP Sycamore Canyon AZ 6.30 4.85 4.82 4.75 Wilderness Black Canyon of CO 4.60 3.89 3.83 3.75 Gunnison NP FlatTops CO 3.10 3.96 3.90 3.81 Wilderness Maroon Bells- CO 3.10 3.90 3.85 3.80 Snowmass WA Mesa Verde NP CO 5.50 4.40 4.38 4.33 West Elk CO 3.10 3.89 3.83 3.74 Wilderness Weminuche CO 4.60 3.97 3.92 3.82 Wilderness San Pedro Parks 

### NM 4.00 5.59 5.51 5.36 Wilderness Arches NP UT 5.50 4.85 4.72 4.61 Bryce Canyon NP UT 4.30 3.91 3.92 3.89 Canyonlands NP UT 5.60 4.87 4.76 4.67 Capitol Reef NP UT 5.60 4.85 4.85 4.75 Zion NP UT 5.90 3.81 3.79 3.75

AppendixA-SIP, Page 3Scenarios 

### &Specific Control Strategies Modeled: The following is an analysis ofvisibility improvementfrom §309 control strategies in 2018. As noted, visibility improvementforthe 16 Colorado Plateau Class I Areas was modeled for the following two scenarios: Scenario 

### 1 is designed to assess the effect ofthe GCVTC-recommended control strategies, comparing the 1996 modeled base case to the visibility improvement resulting from the implementation ofthe following GCVTC strategies: the S02 Annex Milestones, the regional pollution prevention program, maintenance of existing base smoke management (BSM) programs, and accounting for the 2018 base case emissions (known and adopted federal, tribal, state, and local control programs in the contiguous WRAP region). Visibility changes resulting from regional implementation of state pollution prevention programs were modeled by the Regional Modeling Center, as part of the other §309 control strategies. Visibility changes resulting from implementation of pollution prevention programs by individual states or tribes were not modeled. Emissions changes from state or tribal pollution prevention programs, and the resulting visibility changes are small, based on the regional pollution prevention emissions analysis, butare accounted for in the regional modeling. Scenario 2 is designed to assess the effect of the implementation of Enhanced Smoke Management Programs (ESMP), as reflected in the Fire Emissions Joint Forum's 2018 Optimal Smoke Management(OSM) inventory. ESMPs were recommended by GCVTC and are required in §309. Scenario 2 uses the emissions inventories from Scenario 1, exceptthe OSM inventory was substituted for fire emissions. Thus, the results for Scenario 2 are a comparison of visibility changes resulting from emission reductions between the 2018 BSM and 2018 OSM fire inventories.

Results ofWRAP Modeling: Presented below are modeling results projecting visibility improvement in 2018, resulting from implementation ofthe §309 Control Strategies forthe 16 Class IAreas on the Colorado Plateau. Using the procedures for projecting changes in visibility discussed in Chapter 1, visibility at the 16 Class I Areas on the Colorado Plateau was estimated for the 2018 Scenario 1 and Scenario 2 control strategies. Tables 30 and 31 display the improvements in visibility from the 1997-2001 baseline period to 2018 under Scenario 1 and 2 conditions for the, respectively, Worst20% and Best20% visibility days. On the average 20% Worst visibility days, projected improvement from 1997-2001 to 2018 Scenario 1 atthe 16 Class IAreas on the Colorado Plateau range from a maximum reduction of 3.89 dV at Sycamore Canyon National Park in Arizona to a maximum increase of 1.42 dV at San Pedro Parks Wilderness in New Mexico. On the Worst 20% days, Scenario 1 shows improving visibility at half and degradation in visibility for the other half of the 16 Colorado Plateau Class I areas. On the average 20% Best visibility days, projected change from 1997-2001 to 2018 Scenario 1 ranged from a maximum reduction of2.11 dV atZion National Park in Utah to a maximum increase of 1.51 dV at San Pedro Parks Wilderness Area in New Mexico. On the Best 20% days, Scenario 1 improves visibility conditions a % ofthe Class I areas on the Colorado Plateau. A comparison ofthe visibility estimates for 2018 Scenarios 1 and 2 at the 16 Class I Areas on the Colorado Plateau forthe Worst20% (Table 30) and Best20% (Tabie 31) days reveals
AppendixA-SIP, Page 4that 2018 Scenario 2 always estimated reduced (improved) visibility as compared to 2018 Scenario 1. That is, the Optimal Smoke Management (OSM) programs produces visibility improvements over the Base Smoke Management (BSM) programs across all 16 Class I areas for both the Worst 20% and Best 20% days.
Explanation of Modeling Results: The reason why visibility is projected to improve in some areas and degrade in others is due to the assumptions regarding the growth of emissions and the implementation of all controls "on-the-books" in 2002, as well as artifacts of the June 2000 version of the EPA NONROAD model. Figure 

### 2 below displays the differences in S02 emissions between the 1996 and 2018 Base Case emissions scenarios. Due to the implementation of S O2 controls on the Navajo and Mojave electrical generating units (EGUs) between 1996 and 2018, there are projected to be large reductions in S02 emissions in the counties in Arizona and Nevada that contain these two point sources. However, in many of the counties where there are not reductions in point source S02 emissions, S02 emissions are projected to increase. As discussed in more detail in Section 4, this is due in part to increased activity in non- road mobile source equipment, the assumed continued use of high sulfur diesel fuel in non-road sources and errors in the June 2000 NONROAD model that overstated non-road equipment activity as well as S02 emissions from non-road equipment.

2('168358 CaS8 MII·IUS 1986E: ']:;,E' C6S", UIIII HI lonslye-ar

Figure 2: Differences in count average S02 emissions between the 1996 Base Case and the 2018 Base Case emissions scenarios

Appendix A-SIP, Page 5

### The Class I Areas where visibility is improved forthe Worst 20% and Best20% days (Tables 2a and 2b) include ones in Arizona and southern Utah in close proximity of the large S02 reductions from controls on the Navajo EGU and downwind from the large S02 reductions at the Mojave EGU in southern Nevada and in California. Whereas, the Class I Areas where visibility is projected to degrade are near counties where S02 emissions are estimated to increase due to the assumed increases in S02 emissions from the non- road mobile source sector. For example, the San Pedro Parks Wilderness Area in New Mexico lies in and near counties that are projected to have increases in S02 emissions underthe 2018 Base Case conditions, and it is not surprising thatthe modeling projects that visibility would degrade at this Class IArea. Use ofthe corrected NONROAD model, accounting for potential lowsulfur diesel regulations for non-road sources, and accountfor other local (e.g., 8-hour ozone and fine particulate) and regional (e.g., CSI, regional transport rule) in the 2018 projections would like produce improvements atall 16areas.

AppendixA-SIP, Page 6

### Appendix B-SIP Analysis ofClean Air Corridors (CACs)

Introduction: The Clean Air Act Amendments of 1990 specifically require that visibility transport commissions address "the establishment of clean air corridors, in which additional restrictions on increases in emissions may be appropriate to protect visibility in affected Class I Areas."' The Grand Canyon Visibility Transport Commission (GCTVC) in its recommendations2found that clean aircorridors exist and that, generally, clean aircomes to the Colorado Plateau from the northwest.


### Analysis ofCACs: Using one ofthe proposed corridor alignments examined bythe Meteorology Subcommittee, a corridorthatwould protectthe 30% cleanest days on the Colorado Plateau, SSC Research and Consulting conducted an economic and demographic evaluation of the corridor to determine whetheremissions increases expected by2040 would approach 25%. According to its projections, emissions are not expected to increase 25% by 2040. 3 The boundaries ofthe corridor defined in the report are shown in Figure 25. The WRAP adopts this boundary because of the extensive demographic, economic, and air quality impact analysis performed on this corridor and the subsequent review and approval, including the consensus reached by the Grand Canyon Visibility Transport Commission. This is a slight modification ofthe boundary used in the SSC Report. The grid cells used by the GCVTC did not follow state or county boundaries, and for ease of administration, the WRAP has removed small areas ofsouthern Washington and southwestern Montanafrom the corridor. These areas are farfrom the Colorado Plateau and it is unlikely that emissions increases in these small areas would affect the Class I Areas on the Plateau. Also, the WRAP boundary includes all ofSox Elder, Tooele and Grand Counties in Utah, Wasco and Sherman Counties in Oregon, and Cassia and Lemhi Counties in Idaho; these counties were not included within the SSC boundary. Several dozen tribal reservations are located within orclose to the Clean AirCorridor; those are depicted next. 

### An alternative analysis ofclean aircorridors forthe Grand Canyon was performed (Green, et aI., 1996). This analysis was based on an analysis of back trajectories during times when low concentrations were measured on the IMPROVE aerosol monitor at Grand Canyon National Park. The clean air corridor defined from this analysis is shown in Figure 26. An overlay of the boundaries of these two potential definitions of the corridors (Figure 27) indicates thatthe corridorfrom the SSC report is mostlya subset ofthe boundaries ofGreen, et al. The exception is the westernmost edge of Nevada and small area in south -central Oregon.

1 42 U.S.C. 2169B(d)(2)(A). 2 Grand Canyon VisibilityTransportCommission. "Recommendationsfor ImprovingWestern Vistas". Western Governors' Association. Denver, CO. June 1996. 3 BBC Report, page 111-5
Appendix B-SIP, Page 1The Clean Air Corridorfor Section 309 ofthe Regional Haze Rule

Legend E:il Reservation

_ Reser'vation in Of "5 krn from the Ciecll\All CorridQ' CJIMV\P**Clea~** Air ({Jmdor /V Inlerstate Hlghv/ay "!loft,;**t-q:.K,;wI.t\·~:IH."lI,,.~.,..,,.,<:~edlrQ"'''I.O'-,.** !:Ac

...**~_~'O.I"oon** .."<:dt·(

... 4

....**(nd.co;"tr.M'l~ll'Un't.C:~~'W"...u~-;.\!l:~Al:;** ••**t"t~~ltwlwocltl:.<:~f_l...ew-~. ~"Of~**  .:AMt·

..1I111**1~=** .:,." .c:* _"o.-•••**:o.~** .**-~**

## ..**..-,~** 

## .....

# __..

# _- --.""'



# _ .....,. 

# ._-- ",.-..**~~_** 

### .. .. 

# ....-,..-......,....

.... d"

...... rige

.. "."**-":--~**

### .. '**~.~::~..:..** _'ot;"

......-...........

__'JO_••**_.'~'_** JIo._.,_"_.

• .- "'T.••**~_** -**8r{~~:~::.-_**

### ..**:~'.~;{~:~ ~~'"::';:.:.::**  ...**~_** .•..

# ---

# ~r:~~

# ..
_ . ..
_ ".

__ _ •.·

__ r_ 

# --- ,--

..........

# ----- ---:-£::!::::.£

..."

...........

# _**~-** 

# -_

.......,.,...

.........**,..~**....•. :>'_'.a

... . 

# _ ..- .:,;

# _ .....

### _ ......

, . 

### ......**_..,~_** .... •Oil=_

....... ".........,--_.



### .....

## _-....**~-** ....**~--_** ..,,-.-- 

# ._---_.-

.... 

### ....... . .......__._**u-._.~**.._ ),- :-'H_• .
_

..
__.&,. 

# ,---**~.** E:l7..'!:'.?' 

# -**~'~.~~"'Y".I"'-** 

# -_
.

_

# --

..........

# _'

.. ,._..""


### ..

# _.- -..0_:0.

...........

._ 0' ,....

## _ .....

........., ,.."

..,_J.o.<o,. ,-_,_te" ,_e

__ ..,.
__...._.u, """""--"'--'
.

## ..-._
.....**~.\~::~an;** ....,,_.;;J,**-'-"~** ....._."-0

..... _. ""--'-"--"',

_ 

### ....-,

### ... 

# --_

. 

# ..-

.........

## -•...

-....-.....-.

....._J

...



### .......

# -**--~** 

# --_ "-
"-0 r SOl

...... ..-

### ..

# _ .......-.-


# --- ----.---
..... t.

..
_ """".

........

### _ . 

## . 

# _-..

# -

..

## _ . 

## ..-,-

....-,...-

### ...... ,-..". 

### .._'-


### ..

# -

..**_~** 

# ..-
. 

## .._._.... 

### .**-,,~-** 

# _ _

....

' 

# -

'- . ;... .. 

### .............**!::::~:.**

### ... "'" -.....-....."-

..-. 

# ...**:::::...~~** ....."

............-. • .**b:....:-:~~i~**....'"..-.

.....

# _--'-

..

........'-1_

....-

...... 1•**.-.~."_.** ..........

# _-

.....-**::::"..:.:~~l~~:**

.......

## .-._.. '" 

## --"

-.. ___tt.

__



# _

.......,...

____.•

__ "

... 10.- " .**!:7:~** ;:::..:.:....

__.. t_ 

# -_._
..

## ..-. ·_'

....·......1·_ 

# _.**~_.** _t
......**J.~_** 

### ,,,. ! •• J • ,,,, 

## ._,- ,-- -.... 

### .. '.' ·"'-**_~11** .... 

# _**--.~**



# __**.~**.. 

# ----_

..

### _ ...• Sro- ...-• :7:

....: :.:1:.··-

',-_"

__ '--"'''''''-h


## . 

# __ .


# .. ''-''


# _ -

._ ........ "'--0- 

## :;:**:;::.:~:E=:** 

## .. 

# .. .,


# ..



# - .

Appendix B-SIP. Page 2Figure 25: Clean Air Corridor

- WRAP (blue)

- GCVTC/BBC (red) and Colorado Plateau Class I areas (green)

### ~-



# l r--------**~ I ~--'--__t__+--L~+_~~LL___.__j~_=__________1**  

# } 

# ) (\

# (

i



# (\\'-..

### -~ I (

### '-----------.

..;;..

0. \ ....----...**"t;~ ~,-** 

## '\

Appendix B-SIP, Page 3Figure 26: (green) Clean Air Corridor

- Green, et al. (red) and Colorado Plateau Class Iareas

Appendix B-SIP, Page 4Figure 27: Comparison of Clean Air Corridor Boundaries

- GCVTC/BBC report (Blue), Green, et al. (Red), and Colorado Plateau Class I areas (green)
Changes in Modeled Emissions: Emission changes within the clean air corridor between the 1996 base year and the projection year of 2018, including the 

### S02 Annex Milestones case, are shown in Table 32. The WRAP Regional Modeling Center reports the following with respect to changes in emissions from 1996to 2018: PM lO and PM25 emissions are expected to increase about 7% and 18%, respectively. NOx and VOC, however, are expected to decrease about 15% and 26%, respectively. 

### S02 emissions are expected to increase about 5% within the corridor, even with the declining milestones ofthe backstop market trading program. Overall, 

### S02 emissions are expected to decline by 17% in the 13-state GCVTC region by 2018, and the fact that the projections
Appendix B-SIP, Page 5

### show a 5% increase in S02 

### within the clean air corridor is a result of non-road sources burning high-sulfur diesel fuel. This source of S02 

### is expected to be drastically reduced (e.g., from afuel sulfurcontentofmore than 3,000 ppm to 15 ppm) before 2018 according to announcements by EPAto develop newengine certification standards for non-road vehicles and equipment. Thus, 5% should be viewed as an upperbound on the possible increase.

Table 32: Changes in CAC Emissions by 2018 (including milestones) from 1996 

### Point Area On Road Non Road Paved Unpaved Total S02 

### 1996 51,413 9,260 2,065 10,838 0 0 73,576 2018 45,330 10,614 413 21,596 0 0 77,954 2018-1996-6,082 1,354 -1,652 10,758 0 0 4,378 NOx 

### 1996 85,782 12,935 93,581 64,462 0 0 256,762 2018 109,863 17,576 28,692 62,557 0 0 218,689 2018-199624,080 4,641 -64,889 -1,905 0 0 -38,072 'PM 1O 

### 1996 27,055 142,776 3,872 5,952 5,740 47,733 233,128 2018 32,748 154,966 2,640 6,763 12,402 38,828 248,347 2018-19965,692 12,190 -1,232 811 6,662 -8,904 15,219 PM25 

### 1996 11,987 41,595 3,495 5,487 1,435 7,160 71,160 2018 14,583 52,069 2,058 6,228 3,101 5,824 83,863 2018-19962,595 10,474 -1,438 740 1,665 -1,336 12,702 VOC 1996 5,993 95,921 69,899 38,535 0 0 210,349 2018 7,921 95,515 22,651 29,233 0 0 155,321 2018-19961,927 -406 -47,248 -9,301 0 0 -55,029 The projected changes in emissions, within the clean air corridor, are show spatially in Figures 28 through 32 for S02, N02,

### VOC, PM 1O, 

### and PM25
.



### Appendix B-SIP, Page6S02 Difference Mlleslones-1996 GCVTC Gean AIr Corridor

• -509100to-500000 -500000to ·)50000 

## EJ -250000 to ·100000 

## D ·100000to·50000 

# o ·500 OOto 000 

# o 000toSOO.OO 

# o 50000 to 1000.00 1000.00to 250000

• 2500.00 to 500000

• 5000(;() to 791535

SUi Difference M11&stone-10':l6 Numberof values 71 Sum 437774684386377 Minimum -509061414923498**r,~aXlmum** 273648093624772 kli.-.:m 616584062516024 

# L ... 

# •

Figure 28: S02 emission difference, by county, 2018 projections with WRAP 802 Annex Milestones and 1996 base

Appendix B-SIP, Page 7NOX Difference 20181996 GCVTCClean .A.ir Corridor

• -7347.74to -500000 -500000to -2500.00 

## D -250000to -100000 

# o -100000to -500.00 

# o -50000to 000 

# o 000 10500 00 

# o 500.00 to 1000.00 1000.0010250000

• 2500 00 to 5000 00

• 500000to 791535

2018-199G NOX Number ofvalues 71 Sum -380723930836459 Minimum -7347.7366638261 Maximum7915.34510900202 Mean -536.230888502055 

# ... )

Figure 29: NOxemission difference, by county, 2018 projections and 1996 base

Appendix B-SIP, Page 8\lOCDlff':'i·ence .\ 2018-1996

GCVTC Gean Air Corndor

•• -844398 to-500000

-5000 00 to -250000 

## CJ -250000to -100000 

# o -100000 to -50000 

## D -50000to 000 

# o 000 to 500 00 

# o 50000 to 1000.00 100000 to 250000

• 250000 to500000

• 500000 to 791535

2018-1996\Joe Numberofvalues 71 Jurn ·550286971227195 Minimum -8443.98234351755 Maxlmum803988889846232 tv18an .775052072150979 

# M

!> 

# l 

# r**~t....--,.c~~** J



# ,

Figure 30: 

## voe emission difference, by county, 2018 projections and 1996 base

Appendix B-SIP. Page 9PM10 Difference 2018-1996 GCVTC Ot<Cln Air Corndor

• -2757 00to-2000 00

-200000 to -1500 00 

## EJ

-1500 00 to -1000 00 

# o -100000 to -500 00 

# o - 5Ct) 00 to 000 

# o a00 to 250 00 

# o 25000 to 50000 50000 tu 100000

• 1000.00 to 2000 00

• 200000 to 321100

PM10 2018-1996 Number otvc1lues 71 Sum 1521910088155.<15 Minimum ·2I56.1.<1486240593 Maximum3210.90373021597 Mean 21.<1.353533543021 

# ... )

Figure 31: PM lO emission difference, by county, 2018 projections and 1996 base

Appendix B-SIP, Page 10PM2.5 Difference 20\3-1996 GCVTC Clean Air Corridor

• -61000to -SOOOO -500.00to -25000 -25000tc -100.00 

# o -10000 [0 -5000 

# o -50.00to 000 

# o 000 to 25000 

# o 250.00 to 500 00

- 50000 to 1000.00

• 100000to 2000.00

• 2000.00to 3386.00

PM] 5 2018.1996 Number ofvalues 71 Sum 127023378329279 Minimum -60913852855864 Maxiir;um338558803138402 Mean 178906166660957 

# l .... J

Figure 32: PM25 emission difference, by county, 2018 projections and 1996 base

Emissions Tracking System: The preamble of the RHR defines a Clean Air Corridor (CAC) as "a region that generally brings clean air to a receptor region", and also says "the requirement to track emissions will enable states to quickly determine if changes in patterns of emissions will reduce the number of clean airdays (defined as the average ofthe 20% clearest days) in any ofthe 16 Class 

### I Areas." The actual requirements state that the §309 SIP or TIP must describe and provide for implementation ofcomprehensive emission tracking strategies for CAC to ensure that the visibility does not degrade on the least-impaired days at any ofthe 16 Class IAreas. Using the most recent emission inventory data available through the Emissions Data Management System (EDMS), the WRAP will produce a report for each five-year implementation plan revision (2007-8, 2013, and 2018) on the current and projected emissions in the CAC and in areas surrounding the corridor and compare these emissions to a 1996 baseline, as part of a larger source apportionment exercise managed by the Technical Oversight Committee (described in the next section).

Appendix B-SIP, Page 11

### The EDMS will have the capability to produce the following special reports in tabular and simple plots (i.e. bargraph and pie chart) formats and allow queries ofthe same information including presentation in GIS format, in addition to the standard reports: • Asummary report ofthe annual summed total emissions for all six source categories

and all of the pollutants by county/state and tribal lands, as well as for the entire CAC. • A summary report ofthe annual summed total emissions for all six source categories

and all of the pollutants for the same types of political boundaries surrounding the CAC. • A summary report ofthe comparison ofthe annual summed total emissions for all six

source categories and all ofthe pollutants forthe same types of political boundaries, as well as the entire CAC and the corresponding base yeartotal emissions. (See Documentation section below) Analysis of Emissions Growth Within and Outside ofthe CAC As partofthe next round ofanalysis and preparation for regional haze SIPs due in 2007-08, the Technical Oversight Committee will be conducting 2 separate visibility source apportionment exercises (described in the WRAP 2003-08 Strategic Plan), integrating analytical results from aerosol and meteorological monitoring, air quality modeling, and preparation ofemissions inventories. These source apportionmentexercises will identifythe source regions and categories causing visibility impairmentat Class I areas. As part of those source apportionment exercises, the TOC will analyze the changes in emissions for the counties and tribal lands within the CAC, as well as those counties and tribal lands surrounding the CAC. Better emissions inventory data expected to be available each time, as the TOC iterates through these 2 exercises. Specific results from each ofthe source apportionment exercises will address emissions growth both inside and surrounding the CAC, as well as the impacton visibility at affected Class IAreas.

OtherClean Air Corridors: Other than the various options for selection of a CAC for Grand Canyon National Park, shown above, no other corridors have been identified. If the growth of visibility impairing emissions in the corridor identified remains protective of the Grand Canyon National Park, then it should be protective of the other Colorado Plateau Class I Areas. Localized emissions nearthe Class I Areas within the CAC, however, may have more effect on those Class I Areas. Similarly, disproportionate emissions growth in the southern portion of the corridor may have more effecton Grand Canyon National Park. The factors identified by Green, et aI., lowemissions ofairpollutants, enhanced dispersion ofairpollutantsdueto higheraverage ventilation (wind speed multiplied by mixing depth), and increased removal ofpollutants dueto precipitation, combined with the frequency of transportfrom this region make it relatively unique.

AppendixB-SIP, Page 12Findings: With respect to Clean Air Corridors (CACs), Albuquerque/Bernalillo County has determined the following:

• No significant emissions growth is occurring at this time that is causing visibility impairment in the 16 Class IAreas ofthe Colorado Plateau.

• Emissions growth in the Clean Air Corridor, identified by the GCVTC and studied by the WRAP, does not adversely affect the Colorado Plateau Federal Class 

### I Area in New Mexico-the San Pedro Parks Wilderness Area.

• Emissions growth in the CAC does not adversely affect the other fifteen Class 

### I Areas on the Colorado Plateau.

• Outside the CAC there is no emissions growth occurring atthis time that is impairing airqualitywithin the CAC sufficientto cause anyvisibility impairment in any ofthe 16 Class 

### IAreas ofthe Colorado Plateau.

• Outside the CAC identified above, there is no emissions growth occurring that is impacting or could begin to impact the Class 

### I Areas within the Clean Air Corridor itself. For the Class 

### I Areas on the Colorado Plateau, Albuquerque/Bernalillo County note s the following:

• Forthe Best20% visibility days, improvements occurred in 9 outof 16Areas (56%).

• For the Worst 20% of visibility days, improvements occurred in 12 out of 16 Areas (75%). ForotherClass 

### IAreas in the 9-state region (less California), Albuquerque/Bernalillo County notesthe following:

• Forthe Best20% visibility days, improvements occurred in 24 outof40 Areas (60%).

• For the Worst 20% of visibility days, improvements occurred in 29 out of 40 Areas (73%).

Documentation: The 

### WRAP's "Policy Paper on Clean Air Corridors" addresses all requirements related to identifying the boundary ofthe clean aircorridor, projections ofemissions growth inside and outside the boundary, and ifothercorridors exist. This paperwas based on the work ofthe Grand Canyon Visibility Transport Commission Meteorological Subcommittee, and updated with 1996 inventories used byWRAP. The paper found that there is only one clean air corridor, and concludes that patterns of growth in and adjacent to the corridor are not causing significant emissions increases, and consequently no adverse visibility impact on any of the 16 Class I areas of the Colorado Plateau. The paperfound that only 4% emissions growth was likely to occur, as compared

Appendix B-SIP, Page 13

### to the GCVTC work that indicated it would take at least a 25% increase to result in perceptible visibility impact (0.7 deciview). Because no impairment of air quality in the corridor was identified, no further visibility analysis or additional emission reduction measures are needed now, butwill be re-evaluated in 2008. Notethatthe EDMS to be developed is described in a drafttechnical reportto the Emissions Forum: Needs Assessment for Evaluation and Design of an Emissions Data Reporting, Management. and Tracking System, (EA Engineering, Science, and Technology, June 26, 2003).

Appendix B-SIP, Page 14Appendix K-SIP Summary of Emission Inventory 

### & Tracking Programs

The following is a summary of each ofthe emission inventory and tracking requirements in Section 309 for clean air corridors, mobile sources, fire sources, road dust and stationary sources. They are labeled as Appendices K-1 through K-6. (Note: the "Complete Citation of Stationary Source Requirements in Section 309(h) and 309(1)" is Appendix N-T in the nontechnical appendices).
Appendix K-1: Description of Comprehensive Emissions Tracking Program for Clean Air Corridor (CAC). Describe the system the WRAP Emissions Forum has developed for conducting comprehensive emissions tracking for the CAC. Oregon, Idaho, Nevada and Utah will also need to describe more details on how the tracking program will be applied to the portion of the CAC in their own state. If any of these four CAC states do not follow 309, then this appendix needs to describe how the absence of a comprehensive emissions tracking in any one state will be addressed. See Chapter3ofthe TSD forfurther information. Appendix K-2: Mobile Source Emission Trends. List all the new federal engine and fuel standards recently adopted by EPA in the country, and how the state intends to submit emission inventories that will demonstrate that statewide mobile source emission levels are declining for each listed pollutant, in 2008, 2013, and 2018. Appendix K-3: Fire Emission Inventory and Tracking Program. Describe how your state intends to implement an emission inventoryand tracking system forfire sources forVOC, NOx, EC and OC, and PM fine. using the WRAP Fire Tracking System Policy. Describe any changes you will be making in yourstate to improve yourcurrent system to be consistent with this policy. Appendix K-4: Road Dust Emission Inventory and Tracking Program. (See also Appendix F). Describe the process that will used by the WRAP to compile and track road dust emissions in each state, and howthese emissions will be evaluated by yourstate working (with assistance from the WRAP) in the future to determine if road dust is a significant contributor to visibility impairment. Appendix K-5: Stationary Source Emission Inventory and Tracking. Section C provides most of the information on emissions inventory and tracking methods related to stationary sources that will be used by yourstate. In this appendix you need to describe the process the WRAP will be follOWing at the regional level to detennine compliance with the S02 milestones. In addition, you will need to provide a summary ofthe S02 emission reductions achieved from 1990to 2000, as described in the template language in Section 3C(d) ofthis document. This information can be found in the report entitled Year 2000 Point Source SO, Emissions Analysis - 9 State Western Region Report, E.H. Pechan & Associates, Inc. forthe Western Governors' Association; Denver, CO, May 2002.

Appendix K-SIP, Page 1Appendix K-6: Western Emissions Backstop (WEB) Emissions and Allowance Tracking System (EATS) Analysis. This report was prepared by the WESTAR Model Rule/MOU Working Group, and is referred to in Section C, Stationary Sources, in the Template Language under C2 

### WEB Allowance Tracking System (WEB A

### TS). This report describes how emissions, allocations, and transactions will occur ifthe backstop trading program is triggered. You will need to include this reportatechnical support documenttothe SIP.

Appendix K·SIP, Page 2

### OTHER APPENDICES (as included by the local authority)

AppendixA-O Final Regional Haze Rule (RHR) (FR Vol. 64, 

### No. 126, 

### July 1, 1999) 

### Appendix B-O State of New Mexico Letter-Decision to Pursue 309 

### Appendix C-O Albuquerque/Bernalillo County Open Burning/Smoke Management Regulation (draft), 20.11.21 

### NMAC Appendix D-O 

# NI\ AIllaqaelqaetBelli!llille GQURtv,

### Western Backstop Sulfur Dioxide (S02) Trading Program Regulation (draft), 20.11.46 

### NMAC Appendix E-O Western Backstop SulfurDioxide (S02) Trading Program Model Rule Appendix F-O General Definitions in the RHR Appendix G-O Complete Citation of Stationary Source Requirements in Section 309 

### (h) and 309 (f) 

### Appendix H-O WRAP report Stationary Source NOx and PM Emissions in the WRAP Region: An Initial Assessment of Emissions, Controls and Air Quality Impacts (draft), May30, 2003. 

### Appendix 1-0 Revisions to the RHR to Incorporate Sulfur Dioxide Milestones and Backstop Emissions Trading Program for Nine Western States and Eligible Indian Tribes within that Geographic Area, FR Vol. 68, 

### No. 108, 

### June 5,2003. 

### (a.k.a.-The Annex) AppendixJ-O Revisions to the Regional Haze Rule to Correct Mobile Source Provisions in Optional Program for NineWestern States and Eligible Indian Tribes within that GeographicArea, Final Rule, July3, 2003. 

### Appendix K-O WRAP policy report FireTracking Systems, April 2, 2003. 

### Appendix L-O State ofNew Mexico Smoke Management Program (SMP)- Emission Factors and Calculations Appendix M-O WRAP policy report Enhanced Smoke Management Programsfor Visibility. November 12, 2002. 

### Appendix N-O WRAP reportAnnual Emission Goalsfor Fire Policy. April 2, 2003. 

### Appendix 0-0 State of New MexicoAppendix-Pollution Prevention (P2)

### OTHER APPENDICES (as included by the local authority)

AppendixA-O Final Regional Haze Rule (RHR) (FR Vol. 64, No. 126, July 1, 1999) Appendix B-O Stateof New Mexico Letter-Decision to Pursue 309 Appendix C-O Albuquerque/Bernalillo County Open Burning/Smoke Management Regulation (draft), 20.11.21 NMAC Appendix 0-0 

# tJl\**~u';;af6e~,~eOURt~** Western Backstop Sulfur Dioxide (S02) Trading Program Regulation (draft),**2g.~.4S ~JMAe**  

# ....,.2.

.i INM

### t.c. Appendix E-O Western Backstop SulfurDioxide (S02) Trading Program Model Rule Appendix F-O General Definitions in the RHR Appendix G-O Complete Citation of Stationary Source Requirements in Section 309 (h) and 309 (f) 

### Appendix H-O WRAP report Stationary Source NOx and PM Emissions in the WRAP Region: An Initial Assessment of Emissions, Controls and Air Quality Impacts (draft), May 30, 2003. Appendix 1-0 Revisions to the RHR to Incorporate Sulfur Dioxide Milestones and Backstop Emissions Trading Program for Nine Western States and Eligible Indian Tribes within that Geographic Area, FR Vol. 68, No. 108, June5,2003. (a.k.a.-TheAnnex) AppendixJ-O Revisions to the Regional Haze Rule to Correct Mobile Source Provisions in Optional Program for NineWestern States and Eligible Indian Tribes within that GeographicArea, Final Rule, July3, 2003. Appendix K-O WRAP policy report FireTracking Systems, April 2, 2003. Appendix L-O State of New Mexico Smoke Management Program (SMP)- Emission Factors and Calculations Appendix M-O WRAP policy report Enhanced Smoke Management Programsfor Visibility, November 12, 2002. Appendix N-O WRAP reportAnnual Emission Goalsfor Fire Policy, April 2, 2003. Appendix0-0 State of New MexicoAppendix-Pollution Prevention (P2)

### Appendix P-O
Appendix 

### 0-0 Appendix R-O 

### OTHER APPENDICES-continued: (as 

### included by the local authority)

WRAP report Recommendations for Making Attribution Determinations in the Contextof ReasonablyAttributable BART, May22, 2003. EPACompleteness Criteriaforthe Regional Haze SIP References

# OTHERAPPENDICESareinSeparateDocuments