State of New Mexico

Office ofthe Governor

Bill Richardson

Governor

December 26,2003

Mr. Richard E. Greene, Regional Administrator

U.S. Environmental Protection Agency, Region VI

1445 Ross Avenue, Suite 1200

Dallas, TX 75202-2733

SUBJECT: REQUEST FOR APPROVAL OF REVISION TO THE STATE

IMPLEMENTATION PLAN FOR AIR QUALITY

Dear Mr. Greene,

As provided by 40 CFR Part 51, Appendix V and 40 CFR Part 51, Subpart P, I am writing

to request approval 0 f t he attached documentation, which w ill 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 as the "Section 309 Regional Haze SIP element". Two companion regulations 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

Trading Program. The attached proposed SIP revision is applicable to Bernalillo County,

New Mexico.

The Albuquerque/Bernalillo County Air Quality Control Board (AQCB) approved these

proposed revisions to the SIP on November 12, 2003, after a public review period and

corresponding public hearings held on October 8, 2003 and November 12,2003. The two

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

requested SIP revision. ,,~

<..':) :' ,

To facilitate your review and processing, the following materials are enclosed:

I) SIP Completeness Checklists pursuant to 40 CFR 51, Appendix V

- -(J 7

(.")

"-, )

..-:-..,:

u,

0 r'0

'.:":

m

c

State Capitol • Room 400 • Santa Fe, New Mexico 87501 • 5°5-476-2200 • www.govemor.state.nm.us
-2-

2) Hearing records, including transcripts and exhibits

3) Comments received

December 24,2003

4) The final AQCB-approved SIP revision for Regional Haze, including the

two companion regulations.

5) Other supporting documentation

Your favorable consideration of this request is appreciated. If you have any questions,

please contact Alfredo Santistevan, Director 0 f t he Albuquerque Environmental Health

Department, at (505) 768-2600.

Sincerely,

Bill Richardson

Governor

State ofNew Mexico

cc: Alfredo Santistevan, Director, Albuquerque Environmental Health Department

Sandra Ely, Chief, Air Quality Bureau, New Mexico Environment Department

Enclosures
SECTION 309 REGIONAL HAZE

STATE IMPLEMENTATION PLAN ELEMENT:

ALBUQUERQUE/BERNALILLO COUNTY,

NEW MEXICO

,----------~

FINAL VERSION

Appendices

September 8, 2003

Revised October 5, 2003

City of Albuquerque Environmental Health Department

Air Quality Division

Control Strategies Section

Reviewed and Approved after Public Hearing by:

Albuquerque/Bernalillo County

Alf Quality Control Board (AQCB)

Approval Date: November 12, 2003
This document contains the

TECHNICAL SUPPORT DOCUMENT (TSD)

Appendices and the SIP APPENDICES.

The OTHER APPENDICES are in separate

documents.
TECHNICAL SUPPORT DOCUMENT (TSD)

(as listed in the August 27, 2003 draft final version)

Appendix A-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 Air Quality Modeling

2018 Base Case Emissions Used in Air Quality Modeling

2018 Scenario I Emissions Used in Air Quality Modeling

2018 Scenario 2 Emissions Used in Air Quality Modeling

2018 BART with Uncertainty Scenario Emissions Used in Air

Quality Modeling

2018 S02 Annex Milestones Scenario Emissions Used in Air

Quality Modeling

2018 Stationary Source 50% NOx Reduction Scenario

Emissions Used in Air Quality Modeling

2018 Stationary Source 50% PMlO Reduction Scenario

Emissions Used in Air Quality Modeling

2018 Stationary Source Simultaneous 25% NOx and 25%

PM10 Increase Scenario Emissions Used in Air Quality

Modeling

Clean Air Corridor Change in Emissions 1996 to 2018
Appendix A-TSO

Methods Used to Incorporate State and Local Control Programs

in WRAP Emissions Inventories

Overview:

The purpose of this appendix is to provide a list of state 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., December 2002, 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 of State 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 PM lO

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 Classifications ofPM-10 Nonattainment Areas, a group of twelve

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 agencies for each of the selected nonattainment areas.

Often the information was available via the Internet and the agency was able to provide the

web site address. Agency staff was 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).

Appendix A-ISO, Page 1
Pechan reviewed the gathered documents and prepared a series of tables 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 PM10 control efficiencies

by area that were applied as PM10 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 PM10 nonattainment areas, with the

control factors reflecting a higher control level in serious PM10 nonattainment areas than was

applied in moderate PM10 nonattainment areas.

Table IV·3

". SCC ·2311010000 I Construction

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:hno Co

04013 Pho(!l"'.ix Mancupa Co AZ Serious , ,

06077 San JoaqlJin Valley 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,

Appendix A-TSD, Page 2
Table 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 Joaquin Valley 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 regisler their

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'karoe Count,' 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 Conlrol Measure:. 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

San Joaqoln Co

StanISlaus Co, Tulare Co

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 NQIlaUaillment Area County Stale Designation CQnlrol Measures Nole

, 2 , , Oe077 San Joaqvifl 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~!\

Appendix A-TSD, Page 3
Table 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 Nonallainment Area Area Descriplion State PM .. Nonaltanmenl Designalion Control Maasures

06097 Asper. Piddn Co CO Moderate Glea ner winter 5altingiSBr; ding m alerlfi Is

49035 Sail. Lake County VT ModerEllc Cles ner winler salling/san ding m alena Is

56033 Citjl of Sheridall Sheridan Co INY Moaerale Clea ner winlEf sanding materia b5

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:' Clark County 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 Mining i 2325000000 Keep lailings IXlnc wet

,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 that were 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.

Appendix A·TSD, Page 4
Table IV·l0

Area Source Control File for PM

Conlrol Factors for 2018

State 10 County 10 PM v NonaUainment 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 of the 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,

Appendix A-TSD, Page 5
Prescribed 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: Summary of PM,., Emissions from Prescribed Burning by State and Smoke Management

(SM) Scenario. The Relative Emissions are Based on the Total PM25 Emissions in the Wildfire

Emissions Inventory.

No Smoke Base Smoke Optimal Smoke

Management Management Management

Absolute Relative Absolute Relative Absolute Relative

State (tons x 1031 (~~) Itons x 10l ) (0,0) (tons x 103) (%)

Arizona 77.0 15 09.5 14 65.6 15

California 110.3 21 109.7 l'

~L 95.1 21

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 -0J. ' 1 5.8 1 5.1 1

:\e'..· .!vlexKo 74.5 14 74.4 15 63.6 14

;;:orth D.1kota 1.8 0.3 1.8 0.4 1.0 0.4

On:.ogon 48.1 9 46.7 Q 39.i Q

South Dakota ' - 0.7 3,(1 0.7 ."'\ ....

~'./ ,),,' 0.7

noh 46.4 9 45.7 () 38.5 Q

\Vt'\shington 25.S 5 ,- '1 .:..J._ 20.5

\'\'yoIlling 17.1 , 16.9 , .' ~, 16.2 4

TOTAL 522.6 510.4 445.2

Appendix A-TSD, Page 6
Table 6.5: Summary of PM2.5 Emissions from Agricultural Burning by State and Smoke Management

(SM) Scenario. The Relative Emissions are Based on the Total PM2.5 Emissions in the Wildfire

Emissions Inventory.

No Smoke Base Smoke Optimal Smoke

Management Management Management

Absolute Relative Absolute Relative Absolute Relative

State (tons x1031 (%) (tons x 103) (%) (tons x103) (%)

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

Korth Dakota 223 8.3 2.23 6.6 0.56 10.6

Oregon 6.78 253 2.3S 19.9 1.68 12.3

South D,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

Appendix A-ISO. Page 7
On-Road Mobile Sources:

This information is from "Development Of WRAP 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

Appendix A-TSD, Page 8
UT Utah

WvA Clark

WvA King

WA Snohomish

WA Spokane

FJl[A Pierce

Oxygenated Fuel:

For the WRAP modeling, the program in place in each of the mid- months of the 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 by the states.

Table 3-3 Oxygenated fuel inputs

Uanuary Oxygenated Fuel Inputs October Oxygenated 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 17 5 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 9
Uanuary Oxygenated Fuel Inputs October Oxygenated 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 of California Data:

California has different on-road mobile source control programs from the rest of the 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 sulfur gasoline fuel corresponding with the Tier 2 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 for the 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

Appendix A-TSD, Page 10
11M 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 projection years. For the remaining States with 11M or ATP programs modeled

in the 1996 base year modeling (Arizona, Idaho, New Mexico, and Nevada), the

same 11M and 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 of the VMT in each of the 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 for the remainder of

the VMT in each of these 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 for these counties in any of the 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 efficiency for 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 for these 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 for 2018.

Appendix A-TSD, Page 11
1996 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 of these control

programs. CARB provided 1996 off-road emissions estimates from their OFFROAD model

by equipment type, county, and season, with all applicable controls incorporated.

Appendix A-TSD, Page 12
Stationary 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., December 2002, 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) nonattainment for 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 number of 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 clear whether 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

EPA AP-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

o09 fO 09

0.09-0.2,:

0.05-01':

rJ 03-0.0C'

0.0·:-012

(j 3910.22

0.2410.22

01Iji01~,

O_09:0_0~'

o 39/0.22

n1l~i01~1

o_09,{).O~'

0.39/0.2::':

Units

Unc ontro lied ga sloil

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 struc ted by 1983: gas foil

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 S CR' gas /Iiouie'

>10 MW wi SCR gas/liqule

>- a 3 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 te st'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 clear whether 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

Appendix A-TSD, Page 14
emission 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 EPA AP-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 for this 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, except as noted.

Appendix A-TSD, Page 15
Table 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'tHa s, 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~

1 99f

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"MM Utu

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

New Of explilndoEl-tJ

,;. ,5 MMBltJ. g-a~

;I' 5MMBl.u. hquld

NtJw (X oEl-xpandad SOiHlI

Gbll&fawr filC;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

1 til:

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 loA M Blu.Q<'lSiflOl<gas'

Appendix A-TSD, Page 16
Table 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

40 c." 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 f1P ten

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 t 140 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-lJ n

WO 0< !:Ill";;, 'Ud 1 U 1," DUbe! ,en

1 fr9 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

150 c: 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 18
Table IV-13 (continued)

Di~lr...;;t Calendar Year NO. (ppmv) Reduction to '96 Control E ff. Unit's

S_: VUA flGO 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. (1.1 e 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 1 G. , g.hpr1' , l~~n

100 Of 9.6 'J,~lnll 1 C.lf Dll!ll;oj

HhH 90l lS0! 600 lJ 15.' 021.1 a.i.H: U ltlO2.2,10.tK: R Icri/L 4l.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' Q tPI,:; '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)0 c'lar9 e r ilfJ;j alte 'COO i~:H'" ,'lle-'l~() oJe' oj W litI 4-d~g fe.t! ;njOC l0"J 11tn,n 9 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 other fuels 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. Un lis

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

Appendix A-TSD, Page 19
Industrial 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 of the 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 effort to reduce trans ported ozone concentrations in eastern States.

The primary focus for reducing NO, emission s was 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 Year 2007 Missouri inventory (see Table IV-16).

Appendix A-TSD, Page 20
Table 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

their future year emissions,

The Texas SIPs developed by the Texas Natural Resource Conservation Commission

(TNRCC) to reduce ozone concentrations in ambient air are 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 of these orders in terms of NO x emission 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 of this requirement is presented below.

Beaumont/Port Arthur:

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 Arthur to 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 21
Table IV-17

NO, Emission Reductions Required from Texas Sources

Ozone Nonattainment NO~ Emission Reduction

Area Cou nly

Beaumont/Port Arthur Hardin 40.0%

Beaumont/Port Arthur Jefferson 61.9%

Beaumont/Port Arthur Orange 365%

Dallas/F ort Worth Coltin, Dallas. Denlon, Tarrant Sou rce specific

HoustonfGalveslon Braz oria 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 Har fis 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 percent x (1 - 67 tJ 641 tn This 90 percent reduction

was applied uniformly to all point sources in the Houston/Galveston area counties shown in

Table IV-17<

Appendix A-TSD, Page 22
Dallas/Fort Worth:

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 inventory for 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 unit from 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

whether there is a typo in the Dallas/Fort Worth ozone SIP strategy.

Eastman Chemical:

Eastman Chemical operates a chemical plant in Harris County, Texas. Harris County is part

of the 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 of these 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 by TNRCC.

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 for grandfathered 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 by TNRCC from grandfathered non -utility sources equates to a 7.3 percent emission

Appendix A-TSD, Page 23
reduction 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 for Alcoa.

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 1996. It was 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.

Appendix A-TSD, Page 24
Table IV-18

Point Source S02 Emission Limits 1

State of California

2UC ppm &

2 1 l<yibl1 DroccSS('<!

2 SO PP1ll @ O'h 0,.

1000 ppm

0 ..5% S

SOD pvm & 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

19 U.

Unit Operation see Year SO,

CSIBiy§t ManufacUf\J)Q 1992 50 Ib!n~

Coile calCHlln g lOin 400 ppm & 250 Ib/lH

1983 BO% raa.

HUIO caglytc craoHH 1,000 prmv

19B, 132 Ihi 1000 ooucis feea

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. fa eliAy

.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)

SCAOMD S(!conaary t(J<Jd

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 M O..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 dlcct fer pi.a nts ...... nl; rl t!milloss '1 a rr 1CO in PCt {j~y of SO~

··fhere ale airier tLI:':(n:ill(jn~ lUI noted.

Appendix A-lSD, Page 25
Montana:

Lewis and Clark County (East Helena) (County Code: 30 -049)

These SO, emission limits were part of the 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 of Measure 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 of SIPs 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 whenever the 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

Daily Average 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. of tHl-'ft3h per aa y ("Ie3(.1'. !e 'Una (I d to the 'Ht3/£'S t ....he-itl to 8! 'tf.

SOURCE SJ...1AOCIP, 2C1CO;;

Appendix A-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 boiler slack 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 S tacks. 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 ("Ii 1 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. F ractionator Feed Healec and

Recycle Hydrogen Healer

SOURCE. SMAOCiP,2COOL

Appendix A-TSD, Page 27
502 Emissions

Year SO,

Submitted for Emissions

Monlana Sulfllr and Cllemical Company Approval Unit of Measure Lim it

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.HtSrrotn 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 Dai Iy <- 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'

Slerr a Pacific PO\'1e r Com pany's ND rlh Va Imy 199~) Pound s 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 28
New 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 Und ihlted Off-Gas Year Emissions

Released Stream Adopted Unit of Measure Limit

>- 10 tons pel ;. 20 mole percent H::S 199~, Number of 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 m ole 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 ho urs <- 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 Ad opted I Un it of Measure I SO Emissions Limit

199:1 I NL:mber of pounds for every 100 pounds I <- 12

SOURce. NMED,1995

Appendix A-TSD, Page 29
Sulfuric Acid Production Units

so", Emissions

Sulfuric Acid ProducHon Units Year Adopted Unit of M eas ure SO Emissions Limit

Units locaed within the Pecos-Permian 1995 Pounos per hour <::: 575

Basin Intrastate Air Quality Control 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

Year Adopted Unit of Measure SO, Emissions Limit

1995 Pounds per hour (Annual average Emissions) <- 7000'

NOT E. El<.copl as prol/.(I€c'(j lor In SecllOfI 1 12 of Till e 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

Phil bps 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.

Appendix A-TSD, Page 30
Stationary 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., December 2002, Pechan Rpt. No. 02.12.003/9409.000.

In the original lAS model, future year forecasts of electric 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 boiler that 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 of the objectives of this 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 of the lAS industrial sources listed in Table V1. The lAS annual retirement rates for each sector were converted into the lifetime years

listed above by the following formula:

1 "_ . = Years Hetl remen t 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 of the different industrial sector units or plants were calculated or estimated.

Appendix A-TSD, Page 31
Table 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

Nitric Acid 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 and use, 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).

Appendix A-TSD, Page 32
Table V-2

Component Replacement Schedule for a Typical High Temperature,

High Pressure Boiler

Typi cal Life

(Years)

20

25

30

35

40

Component Replaced

Miscellaneous tubing

Atlempe ralar

Superheater (SH)

SH outlet header

Burne rs and throats

Rehealer

Primary economizer

Lower furnace

Cause for Replacement

Corrosion, erOSIOn, over-heat'19

Fatrg ue

Creep

Creep fatigcc

Overheating. corrosion

Creep

Corrosion

Overhea ling, corrosi on

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 of a 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 of the lifetime of an industrial boiler (Placet, 1980).

The Internal Revenue Service's "Publication 946: How to Depreciate Property" lists lifetimes

of industrial boilers from a depreciation point of view. 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 of the actual lifetime of a 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 represent a minimum lifetime estimate for industrial boilers.

Discussions were held with Bob Bessette of the Council of Industrial Boiler Owners (CIBO),

Randall Rawson of the American Boiler Manufacturers Association, Ian Lutes of Foster

Wheeler Corporation, and Brian Moore of the 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

Appendix A-TSD, Page 33
their units for fear of triggering new source review. Therefore, it would be expected that the

average lifetime of an industrial boiler would be less than that of a comparable utility boiler.

There are exceptions, of course, especially when industrial boilers are well maintained and

operated at lower pressures. Field erected units tend to have higher lifetimes than package

boilers for a variety 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 Cat ego 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

Appendix A-TSD, Page 34

Estimated Unit Lifetime (years)

45

4b

37 b

45

30

30

30

30

30

30

30

30
Example 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, new source 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] Em iSbioa.,; = 19Y6 E missHH1S (l - Fraetloll Retired) + lHHG Emissions (l\ ew Souree

Con 11'01 EffIciency) (G rowth FnetOl' - (1 - Fraclion Retired))

In the point source emission projections, there are three cases that all of the 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(' em iss'ion rates.

:.1. No iuil jal 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 of 2018 emissions are provided below for each of these three cases:

Cast' ] EXaITlIJk': 1\)96 NO., emissions = 'lAin ..tpv

Expected Het i:relllent Datt' =20;39

New Source Control Eiricipru;y =97 ppreent

~O]I' Ellli~sifms, = 5.·l:n tJl~' (1 - 0) + 5A:n t pv

(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 of existing 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 retirement date before 2018, all of the 2018 emissions are

at new source rates, which are 28 percent of existing source rates. The growth factor that is

applied to the new source emission rates incorporates 1996 activity, plus expected activity

increases from 1996 to 2018.

Appendix A·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 start date/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 of their

capacity each year. this calculation is expected to provide a reasonable simulation of existing

source retirement, new source grow1h when spread over a broad geographic region, like the

WRAP States.

Implications of Retirement 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"k lyear

2000

f

2005 2010 2015 2020

Calendar Year

Appendix A-TSD, Page 36
Appendix B-TSD

Use of EPA Guidance and 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, as well as in Appendix M of this document.
Appendix C-TSD

1996 Base Case 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 as the 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 is found on the WRAP website 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

for forest/range prescribed fire and agricultural fire.

The 2018 base case modeling run emissions spreadsheet is found on the WRAP website at:

htlp:llwrapair.org/309/documents/FinaIDocs/2018 Base Case Final.xls.
Appendix E-TSD

2018 Scenario I Emissions Used in Air Quality Modeling

The following spreadsheet details 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 of the 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

improvement from implementation of §309 programs.

The 2018 Scenario 1 modeling run emissions spreadsheet is found 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 spreadsheet details 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

improvement from implementation of §309 programs.

The 2018 Scenario 2 modeling run emissions spreadsheet is found on the WRAP website at:

http://wrapair.org/309/documents/FinaIDocs/2018 Scenario 2 Fina1.xls.
Appendix G-TSD

2018 BART with Uncertainty Scenario Emissions Used in Air Quality 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 of this document. Fire emissions in the spreadsheet below are typical wildfire, and

the 2018 base case emissions for foresVrange prescribed fire and agricultural fire. The

BART with Uncertainty Scenario was compared using air quality modeling to the S02 Annex

Milestones Scenario, and the results are discussed in Chapter 4 of this document.

The 2018 BART with 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 Air Quality 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 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 S02

Annex Milestones Scenario was compared using air quality modeling to the BART with

Uncertainty Scenario, and the results are discussed in Chapter 4 of this document.

The 2018 S02 Annex Milestones Scenario modeling run emissions spreadsheet is found on

the WRAP 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 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 foresUrange prescribed fire and agricultural fire. The

2018 Stationary Source 50% NO, Reduction Scenario was modeled to satisfy requirement of

§309, and the results are discussed in Chapter 4 of this document.

The 2018 Stationary Source 50% NO, Reduction Scenario modeling run emissions

spreadsheet is found on the WRAP website at:

http://wrapair.org/309/documents/FinaIDocs/2018 NOx 50percent Decrease Stationary So

urces Final.xls.
Appendix J-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 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 foresUrange prescribed fire and agricultural fire. The

2018 Stationary Source 50% PM,o Reduction Scenario was modeled to satisfy requirement

of §309, and the results are discussed in Chapter 4 of this document.

The 2018 Stationary Source 50% PMlO Reduction Scenario modeling run emissions

spreadsheet is found on the WRAP 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 Air Quality Modeling

The following spreadsheet details emissions used in the 2018 Stationary Source

Simultaneous 25% NO. and PM10 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

PM10 Increase Scenario was modeled to satisfy requirement of §309, and the results are

discussed in Chapter 4 of this document.

The 2018 Stationary Source Simultaneous 25% NO. and PM10 Increase Scenario modeling

run emissions spreadsheet is found on the WRAP website 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 air corridor, 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

·500000 to ·250000

o ·2500 00 tv·1 000 00

o ·1000.00 to ·500 00

o ·50000 to 0.00

o 000t050000

o 500 00 to 1000 00

[] 1000 0010 2500 00

2500.00 to 5000 00

500000 to 791535

S02 DIfference Mlleslone-198(,

Number of valu,:,s 71

Sum tJ.377 7<168<1386377

Ivlinlmum -509061414923499

~"'axlmurn273648093624 77:'

Mean 6165840132516024

....

b

t:"'.",

..

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

and 1996 base.

Appendix L-TSD, Page 1
...

•

2018-1996 NOX

Number of values 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 00 to -100000

o -1000.00 to -500 00

D -50000 to (JOO

D 000 to 500 00

o 500 00 to 100000

100000 to 250000

• 2500 00 to 5000.00

• 500000 to 791535

(~--------\

,

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

Appendix L-TSD, Page 2
\lOC DifferencE'

2018'1996

GCVTC Clean Air Corridor

-844398 to -500000

-500000 to -2500.C:)

bI -2500 00 to -1000 00

o -100000 to -50000

ID -500 00 to 0 00

o 0 00 to SOO 00

o 50000 to 1000 00

trl 100000 to 2500.00

2500.00 to 5000 00

5000.00 ~o 7915 35

2018-1996 \lOC

l\lumber of values 71

Sum -55028,6971227195

I\~inlrnurn -8443,98234351755

!vlaxlmum 80.3988889846232

Mean -775052072150979

~rl\\.

~~.,

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

Appendix L-TSD, Page 3
PM10 Difference

2018-1996

GCVTC Clean Air Corndor

• -2757 00 to -2000 00

-2000.00 to -150000

o -1500.00 to -100000

o -1000.00 to -500 00

o -50000 to 000

o 000 to 2~O 00

o 25000 {Q 500 00

50000 to 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 \

\

. \

I
PM2 5 DifferencE'

2(118-1996

GCVTC CIE':ln An Corndor

• -610.00 to -50000

500 00 to -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

• 100000 to 200000

2000 00 to 3381:~ 1:11)

Pf\.12.5 2018-1896

Number of values 71

Sum 12702 337832927~1

rl1lrilrnum -609 13852855864

Maxi mu m3385.58803138402

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
Appendix A-SIP

Appendix B-SIP

Appendix C-SIP

Appendix D-SIP

Appendix E-SIP

Appendix F-SIP

Appendix G-SIP

Appendix H-SIP

Appendix I-SIP

Appendix J-SIP

Appendix K-SIP

SIP APPENDICES

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

Projection of Improvement in 16 Class I Areas

Analysis of the Clean Air Corridor (CAG)

Mobile Sources: 2003 Interim Progress Report

(The body of the SIP document contains this information)

Fire Programs

(The body of the SIP document contains this information)

Dust Impact Assessment and Contribution to Impairment

(The body of the SIP document contains this information)

Pollution Prevention-Summary of Renewable Energy and

Energy Conservation Programs in the State

(The body of the SIP document contains this information)

Evaluation of Additional Recommendations from the GCVTC

(The body of the SIP document contains this information)

SIP Strategies Developed through Interstate Coordination

(The body of the SIP document contains this information)

Geographic Enhancements-Model MOA between Federal Land

Management Agency and State-optional

(Not included)

Long-Term Strategies and Visibility Improvement Expected for

Additional Class I Areas-optional

(Not applicable)

Summary of Emission Inventory and Tracking Programs
Appendix 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 I Areas on the Colorado Plateau resulting from the

implementation of all 309 control strategies.

Scenarios:

The RMC modeled two scenarios. Scenario 1 is designed to assess the effect of the

GCVTC-recommended control strategies, implementation of the 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). 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 (see further discussion 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 likely to 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 improvement for the average 20% best visibility days (in dV).

Note that Worst days 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 results for the San Pedro Parks Wilderness Area in New Mexico.

Appendix A-SIP, Page 1
Table 2a. Projected Visibility Improvement at the 16 Colorado Plateau Class I Areas in 2018

on the Average 20% Worst Visibility 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% Worst Days' (20% Worst Days' 1997-2001 Case

Monitoring (20% Worst Visibility for all Visibility for all

Data Days' §309 Control §309 Control

Colorado Plateau State (20% Worst Visibility for Strategies (S02 Strategies (S02

Class I Area 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

Black Canyon of

Gunnison NP CO 11.30 10.90 10.76 10.60

Flat Tops

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

Appendix A-SIP, Page 2
Table 2b. Projected Visibility Improvement at the 16 Colorado Plateau Class I Areas in 2018,

on the Average 20% Best Visibility 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 Visibility for all Visibility for all

§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

Flat Tops 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

Appendix A-SIP, Page 3
Scenarios & Specific Control Strategies Modeled:

The following is an analysis of visibility improvement from §309 control strategies in 2018. As

noted, visibility improvement for the 16 Colorado Plateau Class I Areas was modeled for the

following two scenarios:

Scenario 1 is designed to assess the effect of the GCVTC-recommended control strategies,

comparing the 1996 modeled base case to the visibility improvement resulting from the

implementation of the 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, but are 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, except the

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 of WRAP Modeling:

Presented below are modeling results projecting visibility improvement in 2018, resulting

from implementation of the §309 Control Strategies for the 16 Class I Areas 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, Worst 20% and Best 20% visibility days.

On the average 20% Worst visibility days, projected improvement from 1997-2001 to 2018

Scenario 1 at the 16 Class I Areas 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 of 2.11 dV at Zion 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 % of the Class I

areas on the Colorado Plateau.

A comparison of the visibility estimates for 2018 Scenarios 1 and 2 at the 16 Class I Areas

on the Colorado Plateau for the Worst 20% (Table 30) and Best 20% (Tabie 31) days reveals

Appendix A-SI P, Page 4
that 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 scena rios. 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

1986 E: ']:;,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 for the Worst 20% and Best 20% 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 under the 2018 Base Case

conditions, and it is not surprising that the modeling projects that visibility would degrade at

this Class I Area. Use of the corrected NONROAD model, accounting for potential low sulfur

diesel regulations for non-road sources, and account for 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 at all 16 areas.

Appendix A-SIP, Page 6
Appendix B-SIP

Analysis of Clean 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

recommendations2 found that clean air corridors exist and that, generally, clean air comes to

the Colorado Plateau from the northwest.

Analysis of CACs:

Using one of the proposed corridor alignments examined by the Meteorology Subcommittee,

a corridor that would protect the 30% cleanest days on the Colorado Plateau, SSC Research

and Consulting conducted an economic and demographic evaluation of the corridor to

determine whether emissions increases expected by 2040 would approach 25%.

According to its projections, emissions are not expected to increase 25% by 2040. 3 The

boundaries of the 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 of the 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 of southern Washington and southwestern Montana from the corridor.

These areas are far from 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 of Sox 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 or close to the Clean

Air Corridor; those are depicted next.

An alternative analysis of clean air corridors for the 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 that the corridor from the SSC report is mostly a subset of the boundaries of Green,

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 Visibility Transport Commission. "Recommendations for Improving Western

Vistas". Western Governors' Association. Denver, CO. June 1996.

3 BBC Report, page 111-5

Appendix B-SIP, Page 1
The Clean Air Corridor for

Section 309 of the Regional Haze Rule

Legend

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Appendix B-SIP. Page 2
Figure 25: Clean Air Corridor - WRAP (blue) - GCVTC/BBC (red) and Colorado Plateau

Class I areas (green)

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r--------

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Appendix B-SIP, Page 3
Figure 26:

(green)

Clean Air Corridor - Green, et al. (red) and Colorado Plateau Class I areas

Appendix B-SIP, Page 4
Figure 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 1996 to 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 of the 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 a fuel sulfur content of more than 3,000 ppm to 15 ppm) before 2018 according to

announcements by EPA to develop new engine certification standards for non-road vehicles

and equipment. Thus, 5% should be viewed as an upper bound 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

'PM1O 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, Page 6
S02 Difference

Mlleslones-1996

GCVTC Gean AIr Corridor

• -509100 to -5000 00

-500000 to ·)500 00

EJ -250000 to ·100000

D ·100000 to ·50000

o ·500 OOto 000

o 000 to SOO.OO

o 50000 to 1000.00

1000.00 to 250000

• 2500.00 to 500000

• 5000(;() to 791535

SUi Difference M11&stone-10':l6

Number of values 71

Sum 4377 74684386377

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 7
NOX Difference

20181996

GCVTC Clean .A.ir Corridor

• -7347.74 to -500000

-500000 to -2500.00

D -250000 to -100000

o -100000 to -500.00

o -50000 to 000

o 000 10 500 00

o 500.00 to 1000.00

1000.0010250000

• 2500 00 to 5000 00

• 500000 to 791535

2018-199G NOX

Number of values 71

Sum -380723930836459

Minimum -7347.7366638261

Maximum7915.34510900202

Mean -536.230888502055

...

)

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

Appendix B-SIP, Page 8
\lOC Dlff':'i·ence

.\ 2018-1996

GCVTC Gean Air Corndor

•• -844398 to -5000 00

-5000 00 to -250000

CJ -250000 to -100000

o -100000 to -50000

D -50000 to 0 00

o 000 to 500 00

o 50000 to 1000.00

100000 to 2500 00

• 250000 to 500000

• 500000 to 791535

2018-1996 \Joe

Number of values 71

Jurn ·550286971227195

Minimum -8443.98234351755

Maxlmu m 803988889846232

tv18an .775052072150979

M!>

l

r~t....--,.c~~

J

,

Figure 30: voe emission difference, by county, 2018 projections and 1996 base

Appendix B-SIP. Page 9
PM10 Difference

2018-1996

GCVTC Ot<Cln Air Corndor

• -2757 00 to -2000 00

-200000 to -1500 00

EJ -1500 00 to -1000 00

o -100000 to -500 00

o -5Ct) 00 to 000

o a 00 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

Maximum 3210.90373021597

Mean 21.<1.353533543021

...

)

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

Appendix B-SIP, Page 10
PM2.5 Difference

20\3-1996

GCVTC Clean Air Corridor

• -61000 to -SOOOO

-500.00 to -25000

-25000tc -100.00

o -10000 [0 -5000

o -50.00 to 000

o 000 to 25000

o 250.00 to 500 00

- 50000 to 1000.00

• 100000 to 2000.00

• 2000.00 to 3386.00

PM] 5 2018.1996

Number of values 71

Sum 127023378329279

Minimum -60913852855864

Maxiir;u m 338558803138402

Mean 178906166660957

l

....

J

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

Emissions Tracking System:

The preamble of the R HR 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 air days (defined as the average of the 20% clearest days) in any of the 16

Class I Areas." The actual requirements state that the §309 SIP or TIP must describe and

provide for implementation of comprehensive emission tracking strategies for CAC to ensure

that the visibility does not degrade on the least -impaired days at any of the 16 Class I Areas.

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. bar graph and pie chart) formats and allow queries of the same information

including presentation in GIS format, in addition to the standard reports:

• A summary report of the 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 of the 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 of the comparison of the annual summed total emissions for all six

source categories and all of the pollutants for the same types of political boundaries,

as well as the entire CAC and the corresponding base year total emissions.

(See Documentation section below)

Analysis of Emissions Growth Within and Outside of the CAC

As part of the next round of analysis 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 of emissions inventories. These source apportionment exercises will identify the

source regions and categories causing visibility impairment at 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 of the

source apportionment exercises will address emissions growth both inside and surrounding

the CAC, as well as the impact on visibility at affected Class I Areas.

Other Clean 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 near the 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 effect on Grand Canyon National Park.

The factors identified by Green, et aI., low emissions of air pollutants, enhanced dispersion

of air pollutants due to higher average ventilation (wind speed multiplied by mixing depth),

and increased removal of pollutants due to precipitation, combined with the frequency of

transport from this region make it relatively unique.

Appendix B-SIP, Page 12
Findings:

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 I Areas of the 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 at this time that is impairing

air quality within the CAC sufficient to cause any visibility impairment in any of the 16

Class I Areas of the 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:

• For the Best 20% visibility days, improvements occurred in 9 out of 16 Areas (56%).

• For the Worst 20% of visibility days, improvements occurred in 12 out of 16 Areas

(75%).

For other Class I Areas in the 9-state region (less California), Albuquerque/Bernalillo County

notes the following:

• For the Best 20% visibility days, improvements occurred in 24 out of 40 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 of the clean air corridor, projections of emissions growth inside and

outside the boundary, and if other corridors exist. This paper was based on the work of the

Grand Canyon Visibility Transport Commission Meteorological Subcommittee, and updated

with 1996 inventories used by WRAP.

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 paper found 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, but will be re -evaluated in 2008.

Note that the EDMS to be developed is described in a draft technical report to 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 14
Appendix K-SIP

Summary of Emission Inventory & Tracking Programs

The following is a summary of each of the 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 Chapter 3 of the TSD for further 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 inventory and tracking system for fire sources for VOC, NOx, EC and

OC, and PM fine. using the WRAP Fire Tracking System Policy. Describe any changes you

will be making in your state to improve your current 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 how these emissions will be evaluated by your state 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 your state. 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 of the S02 emission reductions achieved from

1990 to 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. for the Western

Governors' Association; Denver, CO, May 2002.

Appendix K-SIP, Page 1
Appendix 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 ATS). This report describes how emissions,

allocations, and transactions will occur if the backstop trading program is triggered. You will

need to include this report a technical support document to the SIP.

Appendix K·SIP, Page 2
OTHER APPENDICES

(as included by the local authority)

Appendix A-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 Sulfur Dioxide (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, June 5,2003. (a.k.a.-The Annex)

Appendix J-O Revisions to the Regional Haze Rule to Correct Mobile Source

Provisions in Optional Program for Nine Western States and Eligible

Indian Tribes within that Geographic Area, Final Rule, July 3, 2003.

Appendix K-O WRAP policy report Fire Tracking 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 Programs for

Visibility. November 12, 2002.

Appendix N-O WRAP report Annual Emission Goals for Fire Policy. April 2, 2003.

Appendix 0-0 State of New Mexico Appendix-Pollution Prevention (P2)
OTHER APPENDICES

(as included by the local authority)

Appendix A-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 0-0 tJl\ ~u';;af6e~,~eOURt~ Western Backstop Sulfur Dioxide (S02)

Trading Program Regulation (draft), 2g.~.4S ~JMAe ....,.2. .i I NM t.c.

Appendix E-O Western Backstop Sulfur Dioxide (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, June 5,2003. (a.k.a.-The Annex)

Appendix J-O Revisions to the Regional Haze Rule to Correct Mobile Source

Provisions in Optional Program for Nine Western States and Eligible

Indian Tribes within that Geographic Area, Final Rule, July 3, 2003.

Appendix K-O WRAP policy report Fire Tracking 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 Programs for

Visibility, November 12, 2002.

Appendix N-O WRAP report Annual Emission Goals for Fire Policy, April 2, 2003.

Appendix 0-0 State of New Mexico Appendix-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 Context of Reasonably Attributable BART, May 22, 2003.

EPA Completeness Criteria for the Regional Haze SIP

References
OTHER APPENDICES are in Separate Documents