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# OAR Box 1828 Prepped by Ollie Stewart



### Document

Number: 

# 291 ) IV-A- 1 Docket Number: 

# A-83-2 7

Printed 11/12/200811:12:58 AM Sheet 291 of 325P. 2 

# V 

# <>EP A Unite d State s Environmenta l Protectio n Agency 

## TE-/4 - J. Offic e o fAi r Qualit y Plannin g an d Standard s Researc h Triangl e Par k N C 2771 1 EPA-450/3-86-0'0 6

Jun e 198 6 Ai r 

# Regulator y Impac t Analysi s fo r Ne w Sourc e Performanc e Standards : Industrial Commercial Institutiona l Stea m Generatin g Unit s o f Greate r tha n 10 0 Millio n Btu/h r Hea t Inpu t

1 

## 1 iP. 3

« . 

### EPA-450/3-86-00 6 

# Regulator y Impac t Analysi s fo r Ne w Sourc e Performanc e Standards : Industrial-Commercial-lnstitutiona l Stea m Generatin g Unit s o fGreate r tha n 10 0

Millio n Btu/h r Hea t Inpu t

U

. S

. ENVIRONMENTA L PROTECTIO N AGENC Y

Offic e o f Ai ran d Radiatio n Offic e o f Ai rQualit yPlannin g an d Standard s Researc h Triangl e Park , Nort h Carolin a 2771 1

Jun e 198 6P. 4

Thi s repor t ha s bee n reviewe d b yth e Emissio n Standard s an d Engineerin g Divisio n o fth e Offic e o fAi rQualit yPlannin g an d Standards , EPA , an d approve d fo rpublication

. Mentio n o ftrad e name s o rcommercia l product s i s no t intende d t o constitut e endorsemen t o rrecommendatio n o f use . Copie s o fth e repor t ar e availabl e throug h th e Librar yService s Offic e (MD-35) , U.S

. Environmenta l Protectio n Agency , Researc h Triangl e Park , N.C

. 27711 , o rfro m Nationa l Technica l Informatio n Services , 528 5 Por t Roya l Road , Springfield , Virgini a 22161
.Content s P. 5

ROL E O F THI S DOCUMEN T EXECUTIV E SUMMAR Y I . Statemen t o f Need s an dConsequence s II . Alternative s Examine d A . Introductio n B

. N o Furthe rRegulatio n C

. Othe rRegulator yApproache s D

. Marke t Oriente d Approache s E

. Regulator yAlternative s Withi n th e Scop e o f Presen t Legislatio n III . Ai rQualit y Dat a A . Introductio n B . SO 4 Ai r Qualit y

Assessmen t C . SO 4 Ai r Qualit y

Result s D . P M Ai r Qualit y

Assessmen t E . SO 2 Ai r Qualit y

Assessmen t IV . Engineerin g Cost s A . Introductio n B

. Analytica l Framewor k V

. Economi cImpac t Analysi s A . Introductio n B . Majo r Stea m

User s C . Selecte dIndustrie s D . Conclusion s Pag e
vi vii i

- 1 I- l I- l I- l 1- 2 1- 2 1- 5
II- l II- l II- l II- 4 II- 6 11- 6 V- 1 V- 1 V- 1 V- 1 V- 1 V- 1 V- 2 V- 3P. 6

1 1 Page VI

. Benefi t Analyi s VI- 1 A

. Introductio n VI- 1 B

. Methodolog yVI- 2 C

. Stud ySelection , Application , Qualifications , VI- 8 an d Plausibilit yCheck s D

. Benefi t Analysi s Estimate s VI-3 2 VII

. Benefit-Cos t Analysi s VII- l

### m
Table s P. 7

Numbe r

3 4 5 6 7
8

I- l 1- 2 1- 3 ;i- 4
:i- 5 1- 6 [V- 1 [V- 2 [V- 3 VI- 1

VI- 2

VI- 3 VI- 4 Pag e

Nationa l Cos t Impact s o f Regulator y xi v Alternative s Industria l Boile r NSP S Potentia l Benefi t xv i Categorie s Annualize dBenefit s xvii i Averag e Benefit s Pe r To nxi x Incrementa l Benefit s Pe r To nx x Ne t Benefi t Analysi s x x Averag e Contro l Cos t Pe r To nan dBenefi t xx i Pe r To n Incrementa l Contro l Cos t Pe r To nan dBenefi t xxi i Pe r To n ASTRA P Matri x111- 3 199 5 Bas e Cas e Sulfat e Emission s 111- 5 199 5 Sulfat e Emissions , LS F Alternativ e 111- 7 199 5 Sulfat e Emission , Percen t Reductio n111- 8 Alternativ e ASTRA P 199 5 Estimate dVisibilit y 111- 9 Emission s Dat a Bases an dGrowt h111-1 0 Nationa l Cos t Impact s o f Regulator y IV- 4 Alternative s Averag e Contro l Cos t Pe r To nIV- 5 Incrementa l Contro l Cos t Pe r To nIV- 5 Industria l Boile r NSP S Potentia l VI- 5 Benefi t Categorie s Deman dEquation s fo r Whic hSO 2 I s VI-26,2 7 A Significan t Explantor y Variabl e Annualize dBenefit s VI-3 3 Averag e Benefit s Pe r Ton , SO 4 V1-3 4P. 8

I V Pag e VI- 5 Averag e Benefit s Pe rTon , P M VI-3 5 VI- 6 Averag e Benefit s Pe rTon , S0 2 VI-3 6 VI- 7 Averag e Benefit s Pe rTon , Tota l VI-3 7 VI- 8 Incrementa l Benefit s Pe rTon , Tota l VI-3 8 VII- 1 Ne t Benefi t Analysi s VII- 2 VI1- 2 Averag e Contro l Cos t Pe rTo n an d Benefi t VI1- 3

Pe rTo n VI1- 3 Incrementa l Contro l Cos t Pe rTo n an d Benefi t VI1- 3

Pe rTo nP. 9



### Figure s
N TM ^ Page VI_ 1 

### Descriptio no f A1 r Quality

Scenari o VI- 2
VI 

### " 2 

### Basi c Step s i nEstimatin

g Benefit s VI- 7 for A nIndividua l Stud

yP.1 0

v i ROL E O F THI S DOCUMEN T Thi s regulator y

impac t analysi s (RIA ) ha s bee nprepare dt o satisf y Executiv e Orde r 1229 1 (1981 ) whic hrequire s preparatio no f anRI A fo r ever y "majo r rule. " Th e propose dregulatio ni s a "majo r rule " becaus e i t coul d resul t i nindustry-wid e annualize dcosts , inth e fift hyea r afte r th e standard s g o int o effect , o f mor e tha n$10 0 millio ndollars . I ncomplianc e wit hth e Executiv e Order , thi s study evaluate s th e pro jecte dconsequence s o f alternativ e approache s t o regulatin g new , modified , an dreconstructe dindustria l steam generatin g units . I t consider s benefits , cost s an deconomi c impacts . Th e benefit-cos t analysi s portio no f th e RI A ha s no t playe dan

y rol e indevelopin g th e propose dstandards . Ther e ar e severa l simplifyin g assumption s whic hinherentl y limi t th e precisio no f thi s RIA . First , wherea s th e ai r qualit y modelin g procedure s use dar e animprovemen t ove r tha t use di nothe r simila r studies , the y remai nsubjec t t o simplifyin g assumption s regardin g growt hrate s an dstac k characteristics . Second , onth e benefi t analysi s side , ther e ar e many benefi t categorie s no t covere di nthi s analysi s an di nth e cas e o f th e SO 4 an dPM benefits , th e coverag e i s limite dt o th e 3 1 easter nstat e region . Ther e ar e othe r assumption s use dinthi s study whic har e detaile d i nth e appropriat e section s o f thi s RIA . Whil e thes e assumption s ar e necessar y

an dreasonable , the y

limi t th e precisio no f th e analysis .P-1 1

V I 1 REFERENCE

S
Executiv e Orde r1229 1 (1981)

. Federa l Register , Vol

. 48 , No

. 33
. I n Executiv e Orde r12291 , th e us e o f th e word s "majo rrule " refer s t o th e advers e economi cconsequence s of

. a regulation

.P.1 2

VI1 1

EXECUTIV E SUMMARY I . OVERVIE W A . Backgroun d Ne wsourc e performanc e standard s have bee n propose d limitin g emission s o f sulfu rdioxid e and particulat e matte rfro m new , modifie d o rreconstructe d industrial-commercial-institutiona l stea m generatin g unit s capabl e o f combustin g mor

e tha n 2 9 M

W (10 0 millio n Btu/hour ) hea t input

. Executiv e Orde r1229 1 state s tha t a RI Amus t be performe d o n anyregulatio n havin g an annua l effec t o n th e econom yo f $100 millio n o rmore . Thi s RI Awa s prepare d fo rth e purpos e o f fulfillin g thi s requirement

. I t shoul d be note d a t th e outse t tha t i n conductin g thi s analysi s a numbe ro f analytica l problem s ha d t o b e overcome . Som

e o f th e analytica l assumption s mad

e ma yaffec t th e fina l results

. Such assumption s ar e note d i n thi s Executiv e Summar yan d discusse d i n mor e detai l i n th e text
. B . Summar y

o f Finding s Thi s analysi s estimate s th e benefit s an dcost s o f two regulator y alternatives : 1 ) standard s base do nth e us e o f low

sulfu r fue l t o reduc e SO 2 emission s 2 ) standard s requirin g a percen t reductio ni nSOg emission s Th e cos t analysi s estimate dal l know nprivat e SO 2 contro l cost s tha t woul db e incurre da s a resul t o f eac ho f thes e regulator y alternatives . Th e benefi t analysi s estimate dth e potentia l SO 4 visibilit y improvement benefits , SO 2 relate dagricultur e benefits , residentia l material s damag e
an dmorbidit y

benefits , an

dPM reduce dmorbidit y

an dsoilin g benefit s o f bot hregulator y

alternatives . Potentiall y larg e benefi t categorie s suc hP.1 3

I X

a s commercia l an d industria l material s damag e an d aci d deposition , wer e no t estimated

. Other , mos t likel ysmaller , benefi t categorie s suc h as climat e effect s an d improve d transportatio n safety , hav e no t bee n include d either

. Th e ne t benefi t analysi s (benefit s minu s costs ) yielde d ambiguou s results

. Th e estimate d rang e o f ne t benefit s fo rth e lo wsulfu rfue l • alternativ e yielde d positiv e results

. Th e rang e o fne t benefit s fo rth e percen t reductio n alternativ e spanne d bot h positiv e an d negativ e ne t benefits

. Annualize d ne t benefit s i n th e yea r199 0 fo rth e lo wsulfu r fue l alternative , range d fro m fou rmillio n dollar s t o sixty-tw o millio n dollar s (198 3 dollars)

. I n 1990 , th e percen t reductio n alternativ e yielde d ne t benefit s rangin g fro m a negativ e forty-tw o millio n dollar s t o a positiv e forty-thre e millio n dollar s (198 3 dollars)

. I I

. STATEMEN

TO F NEE D AN D CONSEQUENCE

S O n Augus t 21 , 1979 , a priorit ylis t fo rdevelopmen t o fadditiona l ne wsourc e performanc e standard s wa s publishe d i n accordanc e wit h Section s 111(b)(1)(A ) an d 111(f)(1 ) o f th e Clea n Ai rAc t Amendments o f 1977
. Thi s lis t identifie d 5 9 majo rstationar ysourc e categorie s tha t wer e judge d t o contribut e significantl yt o ai rpollution

. Thi s lis t di d no t includ e utilit yboiler s sinc e ne wsourc e performanc e standard s ha d previousl y bee n develope d fo rthi s sourc e category
. Fossi l fuel-fire d industria l stea m generatin g unit s ranke d elevent h o n th e priorit ylis t o fsource s fo rwhic h ne

wsourc e performanc e standard s woul d b e established

. Fossi l fuel-fire d stea m generatin g unit s wer e th e highes t ranke d sourc e o f particulat e matte ran d sulfu rdioxid e emissions , an d th e secon d highes t ranke d sourc e o f nitroge n oxid e emission s whe n th e priorit ylis t o f sourc e categorie s wa s published

. Th e propose d standar d coul d reduc e emission s o f sulfu rdioxid e fro m a typica l industria l stea m generatin g uni t b ybetwee n 46 5 Mg/Yea rP.1 4

(51 0 tons/year ) an d 2,42 0 Mg/Yea r(2,67 0 tons/year) , dependin g o n uni t siz e an d typ e o f fue l fired

. Th e need fo rregulator yactio n arise s fro m th e failur e o f th e marke t syste m t o dea l effectivel ywit h ai rpollutio n a s a negativ e externality

. Industria l boiler s dispos e o f unwante d by-product s b yemittin g the m t o th e atmosphere

. Th e societa l cost s associate d wit h thos e emissions , i n term s o f healt h an d welfare , ar e no t full ypai d b yth e emitters

. Th e marke t plac e doe s no t functio n effectivel yo refficientl ywhe n eithe r tota l (privat e an d social ) cost s and/o rbenefit s ar e improperl yaccounte d for

. III

. ALTERNATIVES EXAMINED Executiv e Orde r1229 1 require s tha t th e followin g alternative s b e examined :
a ) n o furthe r regulation , b ) othe r regulator y approaches , c ) marke t oriente dapproache d d ) alternativ e approache s withi nth e scop e o f presen t legislation . Alternativ e a ) - - wa s no t foun dt o b e reasonabl e give nth e Administrator' s determinatio ntha t th e sourc e categor y contribute s significantl y t o ai r pollutio n whic hcoul dreasonabl y b e expecte dt o endange r publi c healt han d welfare . Alternativ e b ) —

Relianc e onBAC T an d LAE Rdeterminations , i nlie uo f NSP S fo r contro l o f steam generatin g emissions , wa s foundundesirable . Th e primar y

reaso nfo r thi s i s th e determinatio ntha t NSPS , i npractice , set s th e "floor " fo r BAC T an d LAE Rdeterminations . I nth e absenc e o f NSPS , th e BAC T an

d LAE Rcontro l level s woul dlikel y b e les s stringent . Alternativ e c ) - - Severa l marke t oriente dapproache s wer e considere d includin g pollutio ntaxes , charges , an d permits . Th e Clea nAi r Ac t explicitl y

require s (Sectio nIII ) tha t new , modified , an d reconstructe d steam generatin g unit s contro l emission s t o th e leve l achievabl e b y th eP.1 5

X I bes t demonstrate dtechnologica l system o f continuou s emissio nreduction , considerin g costs , nonai r qualit y health , an

denvironmenta l an

denergy impacts . Thi s effectivel y preclude s th e us e o f pollutio ntaxe s an d subsidie s a s alternative s t o NSP S unles s th e exac t leve l o f taxe s an d subsidie s coul db e establishe dtha t woul dachiev e pollutio nabatemen t equivalen t t o th e leve l achievabl e b y bes t demonstrate dtechnology . I n th e cas e o f permits , th e numbe r o f permit s an demissio nallowance s woul d hav e t o be correctl y

fixe di nadvance . Alternativ e d ) - - A

numbe r o f regulator y alternative s base do nth. e us e o f low

sulfu r fuel s t o reduc e SO 2 emission s o r th e us e o f flu e ga s desulfurizatio n(FGD ) system s t o achiev e a percen t reductio ni nSO 2 emission s wer e examine dindevelopin g th e propose dNSPS . Fo r purpose s o f thi s RIA , tw o alternativ e contro l level s wer e examine dan dcompare dt o th e regulator y

baseline . 1 ) Regulator y

Baselin e Define db

y existin g Stat e Implementatio nPlan s an dth e existin g NSP S fo r larg e stea m generatin g unit s o f mor e tha n7 3 M W (25 0 millio nBtu/hour ) hea t input . 2 ) Lo wSulfu rFue l Base donth e us e o f lo w sulfu r fue l t o reduc e emission s t o 34 4 ng SO2/ J(0. 8 l bS02/millio nBtu ) hea t inpu t fro m oi l combustio nan

dt o 51 6 n

g SO2/ J(1. 2 l bS02/millio nBtu ) hea t inpu t fro

m coa l combustion . 3 ) Percen t Reductio n

Base do nth e us e o f FG D system s t o achiev e a 9 0 percen t reductio ni nSO 2 emission s fro m bot hoi l an

dcoa l combustion . Thi s alternativ e woul dreduc e emission s fro m coa l combustio nt oP.1 6

XI I les s tha n25 8 n

g SO2/ J(0. 6 l bS02/millio nBtu ) hea t inpu t an d from oi l combustio nt o les s tha n12 9 ng SO2/ J(0. 3 l bS02/millio n Btu ) hea t input . IV . AI RQUALIT YDAT A Regiona l ai r qualit y

analysi s wa s conducte dusin g transfe r matrice s derive dfro

m th e Advance dStatistica l Trajector y Regiona l Ai r Pollutio n (ASTRAP ) model . ASTRA P i s a regiona l scal e SO 2 mode l tha t consider s transport , dispersion , chemica l transformatio nan dremova l o f sulfu r oxides . A s usedinthi s analysis , ASTRA P model s SO 2 source-recepto r relationship s i nth e 3 1 easter nstat e region . Sulfat e reduction s wer e estimate dfo r th e 3 1 easter nstates , fo r bot hregulator y alternative s considered , an

dcompare dt o th e 199 5 bas e case . Th e 199 5 bas e cas e wa s used , rathe r tha nth e mor e appropriat e 199 0 bas e case , becaus e i t wa s readil y availabl e i ncompute r for m an dther e i s a les s tha n2 % differenc e intota l emission s betwee nth e tw o cases . Th e percen t reductio n alternativ e yielde dth e larges t sulfat e reductions . Thes e estimate d sulfat e level s wer e usedt o calculat e visua l rang e improvement s du e t o eac hregulator y

alternative . Th e SO 4 change s fo r th e 3 1 easter nstate s wer e translate dint o TS P change s an

dPM benefit s wer e calculated . No estimate s o f PM ambien t ai r reduction s du e t o reductio no f PM emission s wer e include di nthi s analysis . Th e SO 2 ai r qualit y

analysi s wa s conducte dprimaril y usin g th e inventor y o f ne w industria l boiler s provide db y th e Industria l Fue l Choic e Analysi s Mode l (IFCAM) . SO 2 reduction s in199 0 wer e 170,00 0 ton s fo r th e low sulfu r fue l alternativ e an d240,00 0 fo r th e percent reductio nalternative . Inth e 3 1 easter nstates , fo r th e tw o regulator y

alternatives , SO 2 reduction sP.1 7

xii i were 120,00 0 ton s an d 175,00 0 ton s respectively

. Th e ton s reduce d i n th e 31-stat e regio n ar e relevan t fo rbot h th e SO 4 an d P M benefi t estimates

. V . ENGINEERINGCOST S •Nationa l cos t impact s du e t o th e regulator y alternative s fo r ne w industria l fossi l fuel-fire dstea m generatin g unit s wer e analyze dthroug h th e us e o f th e Industria l Fue l Choic e Analysi s Mode l (IFCAM) . IFCA M i s anenerg y

deman dmode l develope dt o evaluat e fue l choic e decision s i nth e industria l sector . IFCA M i s a highl y

disaggregate dproces s engineerin g mode l designe dt o analyz e factor s affectin g fue l choic e decisions . Tota l annualize dcost s an

dcontro l cost s ar e presente di nTabl e 1 . VI . ECONOMI C IMPAC T ANALYSI S A neconomi c analysi s wa s performe dt o determin e th e potentia l industry specifi c economi c impact s associate dwit hth e percen t reductio nregulator y alternative . Sinc e thi s contro l leve l wa s th e mos t stringen t analyzed , th e impact s fro

m th e lo w sulfu r fue l alternativ e woul dnecessaril y be les s severe , assumin g th e distributio no f cost s acros s affecte dindustrie s ar e th e same . Seve nindustrie s mos t likel y t o experienc e sever e impact s wer e analyzed . Produc t price s wer e projecte dt o increas e fro m les s tha n0.0 1 t o 0. 5 percen t i n199 0 fo r si xo f th e seve nindustries , assumin g ful l cos t pass-throug ho f increase dstea m costs . Cos t a s a percen t o f valu e adde d
wa s projecte dt o increas e b y abou t 0.0 1 t o 0. 9 percen t i n199 0 fo r thes e si xindustries , assumin g ful l cos t pass-throug ho f increase dstea m costs . Th e highes t increase s ar e projecte dfo r th e bee t suga r refinin g industr y du e t o th e fac t tha t th e produc t pric e i s lo w an dsteam cost s represen t a

n unusuall y

highproportio no f manufacturin g costs .P.1 8

XI V

Tabl e 1 NATIONA L COS TIMPACT S O F REGULATOR

YALTERNATIVES 1

. 2 (Million s 198

3 $ )
Regulator y Alternativ e Baselin e Lo w Sul fu r Fuel 3 Percen t Reduction ^ Annualize d Cost s ($/yr ) 3,39 6 3,45 4 3,53 1 A n Contro l nualize d

Cost s ($/yr) 5

— 58 13 5

1 Thes e annualize dcost s ar e i nJanuar y 198 3 dollar s an

dar e therefor e slightl y highe r tha nth e Jun e 198 2 cost s reflecte di nth e Preamble . 2 Assume dhig hoi l penetratio nscenari o - i.e. , assume dlowe r oi l price s tha n inth e highcoa l penetratio nscenario . 3 0. 8 l bS0 2 /Millio nBt u- Oi l 1. 2 l bS0 2 /Mil l ionBt u- Coa l 4 9 0 Percen t Reductio n 5 Thes e ar e th e contro l cost s associate dwit hth e steam generatin g uni t NSPS . The y ar e measure da s addition s t o th e baselin e costs .P.1 9

X V
I naddition , i t wa s conclude dtha t a 9 0 percen t reductio nrequiremen t woul dno t impai r th e abilit y o f firm s t o rais e sufficien t capita l t o construc t fossi l fuel-fire dstea m generatin g units . VII . BENEFI T ANALYSI S Th e benefi t analysi s quantifie s some o f th e economi c benefit s attribut abl e t o healt han

dwelfar e improvement s o f SO 2 reductions . Tw o regulator y alternative s wer e analyze d— low sulfu r fue l an

dpercen t reductio n- - an dcompare dt o th e regualtor y baseline . Benefi t coverag e include s visibilit y

improvemen t du e t o sulfat e (SO4 ) reductions , morbidit y reduction s an dhousehol dsoilin g reduction s du e t o reduce dlevel s o f PM , an dresidentia l material s damage , morbidity , an dagricultura l yiel dreduction s du e t o SO 2 reductions . Geographi c coverag e fo r SO 4 an dPM i s th e 3 1 easter nstat e region . Geographi c coverag e fo r SO 2 include s 11 3 area s wher e rre w industria l boiler s ar e projecte dt o b e buil t i n1990 . Al l benefit s ar e estimate d fo r th e yea r 199 0 - - tha t is , the y represen t th e benefit s tha t woul d
accru e fro

m al l boiler s subjec t t o th e NSPS , tha t wer e o nlin e i n1990 . Jus t a s importan t a s th e benefi t categorie s tha t ar e covere di npar t o r i n tota l ar e thos e categorie s no t covere da t all . Tabl e 2 list s al l potentia l benefi t categorie s fo r th e propose dstandard s an dindicate s whic hone s ar e analyze dinthi s RIA . A s ca nb e seen , ther e ar e many categorie s no t include di nthi s analysis . Althoug hth e inclusio no f thes e benefi t categorie s woul dundoubtedl y increas e th e benefi t numbers , th e magnitud e
« f thi s increas e i s no t known . Potentiall y significan t benefit s ar e omitte dfrom

th e nonhuma nbiologica l effect s categor y (e.g. , aci ddeposition )
an dfro m th e SO 4 healt heffect s category . Inaddition , fo r th e benefi t categorie s tha t ar e included , ther e remain s incomplet e coverage . Fo r example , th e SO 2 benefi t estimate s includ e calculation s fo r reduction sP.2 0

XV I
Tabl e 2 Industria l Boile r NSP S Potentia l Benefi t Categorie s

Healt hEffect s

- Mortalit y

Du e t o Chroni c Exposur e

- Mortalit y

Du e t o Acut e Exposur e

- Morbidit y

Du e t o Chroni c Exposur e

- Morbidit y

Du e t o Acut e Exposur e Soilin g an

dMaterial s Damag e

- Residentia l Facilitie s

- Commercial , Institutiona l an dIndustria l Facilitie s Climat e an

dVisibilit y

Effect s

- Loca l Visibilit y

- Non-Loca l Visibilit y

- Climat e

- Visibilit ya t Park s

- Transportatio n Safet y Non-Huma n Biologica l Effect s

- Agricultur e

- Forestr y

- Fishin g

- Ecosyste m SO ?

X X SO 4 Othe r P M

XX XX X* X*

X* XX

N A N A X N A N A

* X X X *

* X X X

X X X X X

X X X X

N A N A N A N A
Xar e categorie s no t analyze dinthi s study . * ar e categorie s analyze di nthi s study . N A ar e categorie s no t applicabl e t o th e pollutant .P.2 1

xvi i i nresidentia l material s damage , bu t n o estimate s ar e include dfo r commercial , institutional , o r industria l facilitie s material s damage . Th e benefi t estimate s ar e exhibite di nTabl e 3 . Th e benefit s associate d wit hth e percen t reductio nalternativ e excee dth e benefit s associate dwit h th e low sulfu r fue l alternative . Thi s reflect s th e greate r improvemen t i n ai r qualit y

tha t ca nb e achieve dwhe npercen t reductio ni s required . Averag e
an dincrementa l benefit s pe r to nar e displaye di nTable s 4 an d5 , respectively . Th e averag e benefit s pe r to nar e extremel y simila r fo r th e regulator y alter natives . Wherea s th e annualize dbenefit s fo r th e percen t reductio nalternativ e
ar e approximatel y

33 % greate r tha nbenefit s fo r th e lo w sulfu r fue l alternative , th e ton s o f SO 2 reduce dunde r th e percen t reductio nalternativ e ar e als o approximatel y

30 % greate r tha nthos e unde r low sulfu r fuel . Consequently , th e benefi t pe r to nestimate s ar e almos t identical . VIII . BENEFIT-COS T ANALYSI S A ne t benefi t analysi s (benefit s minu s costs ) wa s conducte dfo r th e two regulator y

alternative s examined . A s ca nb e see ni nTabl e 6 , ther e
ar e case s wher e th e annualize dne t benefit s ar e negative . Tabl e 7 present s th e averag e cost s an dbenefit s pe r to nan dTabl e 8 present s th e incrementa l cost s an

dbenefit s pe r tonfo r th e percen t reductio nalternativ e ove r th e low sulfu r fue l alternative . Th e result s o f th e benefit-cos t analysi s depend , o f course , onth e validit y

an dscop e o f th e estimate s o f bot hbenefit s an dcost s associate d wit hth e regulator y alternatives . Th e wid e rang e o f variabilit y inth e estimate dbenefit s i s discusse di nChapte r VI . Limitation s als o exis t o n th e cos t side . Whil e al l know nprivat e contro l cost s associate dwit hth e regulator y

alternative s hav e bee nestimated , complet e coverag e o f al l privat e
an dsocia l cost s i s uncertain . Th e result s o f th e benefit-cos t analysi s ar e therefor e limite dinscope .Tabl e 3 Annualize

dBenefits * (Thousand s o f 198 3 dollars) 2

Benefi t Categor

y
SO 4 Visibilit

y Loca l Non-Loca l

P M Morbidit

y & Soilin

g
S0 2 Health SO 2 Welfare Material s Damag e Agricultur e
Tota l Lo w 1

8,00 0 3,00 0 23,00 0
2,00 0

26,00 0 

### 20 0
62,00 0 Sulfu

r Fi 2

21,00 0 11,00 0 25,00 0
2,00 0

2 6 ,00 0 

### 20 0
85,00 0 Regulator

y Alternative s Industria l Boile r SO ? iel 3 3

41,00 0 25,00 0
26,00 0 2,00 0

26,00 0 

### 20 0
120,00 0 Percen t Reduc t 1 2

12,00 0 4,00 0
35,00 0
2,00 0

40,00 0 

### 20 0
93,00 0 31,00 0

15,00 0
38,00 0 2,00 0

40,00 0 

### 20 0
126,00 0 ion 3 3

61,00 0 35,00 0
40,00 0
2,00 0

40,00 0 

### 20 0
178,00 0
1 Th e benefi t assessment only include s a subse t o f potentia l benefits . 2 Benefit s ar

e fo r th e yea r 1990 , i

n198 3 dollars . 3 A rang e of benefit s (1,2,3 ) i s presente

dfo r SO ^ an

dP M t o reflec t sensitivity analysi s o

nth e ai r qualit y modelin g an deconomi c valuatio ninputs . X <P.2 3

XI X Tabl e 4 Averag e Benefit s pe r Ton 1
Total s (SO4 . PM , an

dSO? ) Regulator y

B/ T Alternative 2 (198 3 $ ) Low Sulfu r Fuel/ 1 45 0 Low Sulfu r Fuel/ 2 64 0 Low Sulfu r Fuel/ 3 93 0 Percen t Reduction/ 1 47 0 Percen t Reduction/ 2 66 0 Percen t Reduction/ 3 95 0

1 Th e "ton s o f SO o reduced " use dt o calculat e B/ T diffe r betwee nSO * an d PM an dSO2 . Thi s reflect s difference s i ngeographi c coverage . SO 4 an dP M onl y cove r 3 1 easter nstat e region . 2 A rang e o f benefit s (1,2,3 ) i s presente dfo r SO 4 an dPM t o reflec t sensitivit y

analyse s o

nth e ai r qualit y

modelin g an

deconomi c valuatio n inputs .P.2 4

X X Tabl e 5 Incrementa l Benefit s pe rTon 1 » 2 Total s (S0 4 , PM , an d S0 2 ) '

Percen t Reduction/ 1 Percen t Reduction/ 2 Percen t Reduction/ 3 B/ T (198 3 $ ) 51 0 69 0 100 0

1 Percen t reductio nove r lo w sulfu r fuel . 2 Th e "ton s o f S0 2 reduced " use dt o calculat e B/ T diffe r betwee nSO 4 an dP M an dSO2 . Thi s reflect s difference s ingeographi c coverage . SO 4 an dP M onl y cove r the " 3 1 easter nstat e region . A rang e o f benefit s (1,2,3 ) i s presente dfo r S0 4 an dPM t o reflec t sensitivit y

analysi s onth e ai r qualit y modelin g an

deconomi c valuatio n inputs. -

Tabl e 6 Ne t Benefi t Analysi s (thousand s o f 198 3 dollars ) Regulator y Alternative 1 Lo wSulfu rFuel/ 1 Lo wSu l fu rFuel/ 2 Lo wSu l fu rFuel/ 3 Percen t Reduction/ 1 Percen t Reduction/ 2 Percen t Reduction/ 3 Tota l Annualize d Benefit s 62,00 0 85,00 0 120,00 0 93,00 0 126,00 0 178,00 0 Tota l Annualize d Contro l Cost s 58,00 0 58,00 0 58,00 0 135,00 0 135,00 0 135,00 0 Annualize d Ne t Benefit s 4,00 0 27,00 0 62,00 0 -42,00 0 -9,00 0 43,00 0

A rang e o f benefit s (1,2,3 ) i s presente dfo r SO 4 an dP M t o reflec t sensitivit y analysi s o

nth e ai r qualit y

modelin g an

deconomi c valuatio ninputs .P.2 5

XX I

Tabl e 7 Averag e Contro l Cos t Pe rTo n and Benefi t Pe rTon 1 (198 3 $ )
Averag e Averag e Regulator y

Alternative 2 C/ T B/ T

Lo w Sulfu r Fuel/ 1 34 0 45 0 Low Sulfu r Fuel/ 2 34 0 64 0 Low Sulfu r Fuel/ 3 34 0 93 0
Percen t Reduction/ 1 56 0 47 0 Percen t Reduction/ 2 56 0 66 0 Percen t Reduction/ 3 56 0 95 0

1 Th e "ton s o f SO 2 reduced " use dt o calculat e B/ T diffe r betwee nSO * an d P M an dSO2 . Thi s reflect s difference s ingeographi c coverage . SO 4 an d P M onl y cove r 3 1 easter nstat e region . 

### 2 A rang e o f benefit s (1,2,3 ) i s presente dfo r SO ^ an dPM t o reflec t sensitivit y

analysi s onth e ai r qualit y modelin g an

deconomi c valuatio n inputs .P.2 6

XX1 1

Tabl e 8 Incrementa l Contro l Cos t Pe r To nan dBenefi t Pe r To ni» 2 (198 3 $ )

Percent Reduction/ 1 Percent Reduction/ 2 Percent Reduction/ 3 Incrementa l
C/T 3 110 0 110 0 110 0 Incrementa l
B/T 3 

### 51 0 69 0 100 0

• Th e "ton s o f SO 2 reduced " use dt o calculat e B/ T diffe r betwee nSO * an d P M an dSO2 . Thi s reflect s differencie s i ngeographi c coverage . SO 4 an d P M onl y cove r 3 1 easter nstat e region . 2 A rang e o f benefit s (1,2,3 ) i s presente dfo r SO 4 an dPM t o reflec t sensitivit y analysi s o nth e ai r qualit y modelin g an

deconomi c valuatio ninputs . 3 Percen t reductio nove r lo w sulfu r fuel .P.2 7

x x m
IX . CAVEAT S AN DQUALIFICATION S Many caveat s an

dqualification s wit hregar dt o th e ai r qualit y modelin g an

dbenefi t analysi s ar e presente di nth e body o f th e RIA . Som e o f th e mor e importan t qualification s ar e mentione dbelow alon g wit hth e potentia l impact s onth e result s o f th e analysis . Th e mos t importan t qualificatio nconcern s th e benefi t coverage . A s ca nb e see ni nTabl e 2 ther e ar e many , potentiall y significan t categorie s omitte do r onl y

partiall y

covered. ' Thus , tota l benefit s wil l actuall y b e greate r tha nthos e reported , an dne t benefit s wil l b e larger . I t i s impossibl e t o kno

w th e magnitud e o f thi s effec t wit han y precision . Geographi c coverag e i s als o limited . Sinc e SO 4 andP M calculation s onl y includ e th e 3 1 easter nstates , potentiall y significan t benefit s from th e wester nstate s an dCanad a ar e omitted . Th e inclusio no f thes e area s i nth e benefi t calculation s coul donl y increas e th e annualize dbenefit s an dne t benefits .I- l

I . STATEMEN T O F NEED S AND CONSEQUENCE S Th e propose d standard s implemen t Sectio n 11 1 o f th e Clea n Ai rAc t an d ar e base d o n th e Administrator' s determinatio n tha t emission s fro m industrial-commercial-institutiona l stea m generatin g unit s cause , o r contribut e significantl yto , ai rpollutio n whic h ma yreasonabl yb e expecte d t o endange rpubli chealt h o rwelfare

. Th e inten t i s t o requir e new , modified , an d reconstructe d industrial-commercial-institutiona l stea m generatin g unit s t o contro l emission s t o th e leve l achievabl e b yth e bes t demonstrate d technologica l syste m o f continuou s emissio n reduction , considerin g costs , nonai rqualit yhealth , an d environmenta l an d energ y impacts

. Th e propose d standard s appl yt o stea m generatin g unit s capabl e o f combustin g mor e tha n 2 9 M W(10 0 millio n Btu/hour ) hea t input

. O n Augus t 21 , 1979 , a priorit ylis t fo rdevelopmen t o fadditiona l ne wsourc e performanc e standard s (NSPS ) was publishe d i n accordanc e wit h Section s 111(b)(1)(A ) an d 111(f)(1 ) o fth e Clea n Ai rAc t Amendments o f 1977
. Thi s lis t identifie d 5 9 majo rstationar ysourc e categorie s tha t wer e judge d t o contribut e significantl yt o ai rpollutio n tha t coul d reasonabl yb e expecte d t o endange rpubli chealt h o rwelfare

. Ne wsourc e performanc e standard s ha d previousl ybee n develope d fo rutilit yboiler s (se e EP A450/3-79-021)

. Fossi l fuel-fire d industria l stea m generatin g unit s ranke d elevent h o n thi s priorit ylis t o fsource s fo rwhic h ne w sourc e performanc e standard s woul d b e establishe d i n th e future

. Fossi l fuel-fire d industria l stea m generatin g unit s wer e th e highes t ranke d sourc e o f particulat e matte ran d sulfu rdioxid e emissions , an d th e secon d highes t ranke d sourc e o f nitroge n oxid e emission s whe n th e priorit ylis t o f sourc e categorie s no t regulate d b yNSP S wa s published

.P.2 9

1- 2
Fossi l an d nonfossi l fuel-fire d stea m generatin g unit s ar e significan t source s o femission s o f thre e majo rpollutants : particulat e matte r(PM) , sulfu rdioxid e (SO2) , an d nitroge n oxide s (NOx)

. A s discusse d i n "Prioritie s fo rNe

wSourc e Performanc e Standard s Unde rth e Clea n Ai rAc t Amendments o f 1977 " (EPA-450/3-78-019) , i n th e absenc e o fth e propose d standards , emission s fro m industrial-commercial-institutiona l stea m generatin g unit s wit h a hea t inpu t capacit yo f 3 throug h 7 3 M W(1 0 throug h 25 0 millio n Btu/hour ) woul d contribut e approximatel y9 percen t o fth e tota l nationa l SO

2 emission s fro m majo rsource s i n 1990
. Th e propose d regulatio n woul d requir e al l coal-fire d industrial commercial-institutiona l stea m generatin g unit s equippe d wit h conventiona l SO 2 emissio n reductio n technologie s t o achiev e a 9 0 percen t reductio n i n SO 2 emissio n an d mee t a n emissio n limi t o f 51 6 n g SO2/ J (1. 2 l b S02/millio n Btu ) hea t input

. Coal-fire d stea m generatin g unit s usin g a n emergin g technolog yfo rSO

2 contro l woul d b e require d t o achiev e a 5 0 percen t reductio n i n SO

2 emission s an d mee t a n emissio n limi t o f25 8 n g SO2/ J (0. 6 l b S02/mil 1 io n Btu ) hea t input

. Stea m generatin g unit s firin g mixture s o f coa l wit h an yothe rfue l (excep t oil ) an d havin g a n annua l capacit yutilizatio n facto rfo rcoa l o f les s tha n 3 0 percen t (0.30 ) woul d b e require d t o mee t a n SO 2 emissio n limi t o f 51 6 n g SO2/ J (1. 2 l b S02/millio n Btu ) hea t input

. Th e propose d standard s woul d requir e al l oil-fire d industrial commercial-institutiona l stea m generatin g unit s equippe d wit h conventiona l SO 2 emission s an d mee t a n emissio n limi t o f 34 4 n g S02/millio n Btu ) hea t input

. Oil-fire d stea m generatin g unit s usin g a n emergin g technolog yt o contro l SO

2 emission s woul d b e require d t o achiev e a 5 0 percen t reductio nP.3 0

1- 3 i n SO 2 emission s an d mee t a n emissio n limi t o f 17 2 n g SOg/ J (0. 4 l b S02/mi l 1 io n Btu ) hea t input

. Stea m generatin g unit s firin g oi l an d meetin g a n S0 2 emissio n limi t o f8 6 n g S0 2 / J (0. 2 l b S02/millio n Btu ) o r les s woul d no t b e require d t o achiev e a furthe rpercen t reductio n i n SO 2 emissions

. Th e emissio n limi t fo rstea m generatin g unit s firin g a mixtur e o f coa l an d oi l woul d b e determine d byproration

. Th e propose d standard s coul d reduc e emission s o f particulat e matte r fro m a typica l oil-fire d industrial-commercial-institutiona l stea m generatin g uni t b

yabou t 4 9 Mg/yea r(5 4 tons/year)

. I n th e fift h yea rafte rthi s NSP S become s applicable , nationwid e emission s o fSO

2 coul d b e decrease d b ybetwee n 240,00 0 an d 281,00 0 Mg/yea r (263,00 0 an d 310,00 0 tons/year ) compare d wit h projecte d emissio n level s unde rth e regulator ybaseline

. Nationa l ambien t ai rqualit ystandard s hav e bee n establishe d fo rSO 2 becaus e o fit s know n advers e effect s o n publi chealt h an d welfare

. Im pact s o f thi s pollutan t hav e bee n documente d i n th e SO 2 Criteri a Documen t prepare d unde rSectio n 10 8 o f th e Clea n Ai rAct

. Thes e effect s ar e th e primar ybasi s fo rth e determinatio n tha t emission s fro m industrial-commercia l institutiona l stea m generatin g unit s wil l continu e t o b e locate d i n urba n area s wher e a larg e populatio n .wil l b e expose d t o th e emissions

. Therefore , th e presen t concentratio n o f stea m generatin g unit s i n industrialize d urba n area s wil l continu e t o contribut e t o loca l an d regiona l ai rpollution

. Fo rthes e reason s th e sourc e categor yo f industrial-commercial-institutiona l stea m generatin g unit s wa s selecte d fo rdevelopmen t o fstandard s o f, performance

.P.3 1

1- 4
REFERENCE S
U.S . EPA (1985) . Standard s o f Performanc e fo r New Stationar y

Sources , Industrial-Commercial-Institutiona l Stea m Generatin g Units , Draf t Preamble .P.3 2

II- l II . ALTERNATIVE S EXAMINE D A . Introductio n Thi s sectio nbriefl y present s potentia l alternative s t o th e propose d regulation . Th e E.O . require s tha t EP A examin e regulator y alternative s tha t woul dmitigat e o r eliminat e th e environmenta l proble m a s describe d i nth e Statemen t o f Need s an dConsequences . Th e forma t o f thi s sectio n follow s th e requirement s o f E.O . 1229 1 tha t th e followin g alternative s b e examined : a ) n o furthe rregulation , b ) othe rregulator yapproaches , c ) marke t oriente d approaches , d ) alternativ e approache s withi n th e scop e o fpresen t legislation

. Althoug h E.O

. 1229 1 require s tha t al l alternative s b e examined , onl yth e mos t promisin g one s nee d b e analyze d i n detail

. B

. N o Furthe rRegulatio n Adecisio n no t t o furthe rregulat e stea m generatin g unit s woul d resul t i n a relianc e o n curren t contro l levels

. Th e regulator ybaselin e represent s th e curren t leve l o f contro l require d b yexistin g Stat e implementatio n plan s an d th e existin g NSP S (4 0 CF

R Par t 60 , Subpar t D ) applicabl e t o stea m generatin g unit s o f mor e tha n 7 3 M W(25 0 millio n Btu/hour ) hea t input

. I f onl ycurren t contro l level s wer e maintained , SO 2 emission s woul d b e 240,00 0 t o 281,00 0 Mg/yea r(263,00 0 an d 310,00 0 tons/year ) greate rtha n the ywoul d b e unde rth e propose d regulation , i n th e fift h yea rafte rproposal

. Th e Administrato rha s determine d tha t thi s leve l o fai rpollutio n coul d reasonabl yb e expecte d t o endange r publi chealt h an d welfare

. Fo rthi s reaso n thi s sourc e categor ywasP.3 3

II- 2 selecte dfo r developmen t o f standard s o f performance . Thi s optio ni s discusse di nlate r section s o f th e RI A a s th e baselin e fo r th e evaluatio n o f othe r regulator y

alternatives . C . Othe r Regulator y Approache s Th e regulator y

alternativ e t o NSP S fo r controllin g emission s fro m steam generatin g unit s i s relianc e onBes t Availabl e Contro l Technolog y (BACT ) an

d Lowes t Achievabl e Emissio nRequiremen t (LAER ) i nattainmen t an dnonattainmen t
area s respectively . BAC T an dLAE Rdetermination s ar e mad e o na cas e b

y cas e basis . Throug hreview an danalysi s o f curren t BAC T an dLAE Rlevel s i t ha s bee ndetermine dtha t th e applicabl e NSP S set s a "floor, " o r minimum , onth e leve l o f contro l tha t i s required . Therefore , th e existenc e an d stringenc y

o f th e applicabl e NSP S ha s a significan t influenc e onth e eventua l BAC T o r LAE Rdetermination . Th e importanc e o f NSPS s t o th e BAC T
an dLAE Rproces s take s oneve ngreate r significanc e i npractice , give n tha t th e majorit y

o f BAC T an

dLAE Rdetermination s appea r t o b e se t "b y default " equivalen t t o th e applicabl e NSPS . D . Marke t Oriente dAlternative s Ther e ar e severa l marke t oriente dapproache s tha t ca nb e considere d alternative s t o regulatin g steam generatin g unit s unde r NSPS . Thes e approache s includ e pollutio ntaxes , marketabl e permits , an dsubsidies . 1 ) Taxe s Thi s polic y

woul drequir e a ta xo neac huni t o f pollutio nemitted . Firm s woul dthe nchoos e th e amocm t o f pollutio nabatemen t tha t minimize d thei r tota l cost , includin g th e pollutio ntax . Pollutio ni s abate dunti l th e margina l cos t o f abatemen t i s equa l t o th e pollutio ntax . Th e regula tor y agenc y woul dhav e t o se t th e leve l o f th e ta xi na manne r tha t woul dII- 3

resul t i n th e desire d leve l o f ai rquality

. Whil e conceptuall ypossible , and i n term s o f economi cefficienc yappealing , th e pollutio n ta xtha t ensure s th e acceptabl e leve l o fai rqualit ywoul d hav e t o be don e o n a case-by-cas e basis

. 2 ) Permit s A permi t system

woul dallow

a pollutio nsourc e t o purchas e a permi t i norde r t o emi t a specifi c amoun t o f a pollutan t ove r a specifie d perio do f time a t a specifie dlocation . A fixe dnumbe r o f permit s woul d b e issue dan

dauctione dof f t o th e highes t bidders . Alternatively , th e permit s coul db e distribute damon g th e sources , wh o coul dthe ntrad e thes e permit s a s the y se e fit . I f th e numbe r o f permit s an demissio n' allowance s wer e correctl y fixe di nadvance , the nth e desire dai r qualit y woul db e achieved . Again , thi s ma y b e difficul t i narea s wit hnumerou s an ddivers e sources . 3 ) Subsidie s A subsidy system pay s source s fo r eac huni t o f pollutio ntha t the y d o no t emit . Thi s ca ntak e th e for m o f direc t payment s o r ta x credits . Subsidie s an dtaxe s ar e simila r i ntha t bot hincreas e th e opportunit y

cos t o f polluting . Eac huni t o f pollutio nemitte dha s attache d t o i t th e "cost " o f th e foregon e subsidy . Thus , th e subsidy i s simila r t o a tax , excep t i ntwo respects : (a ) Administratively , ther e i s th e proble m o f determinin g th e actua l abatemen t at eac hsource . Ther e mus t b e a determinatio no f wha t pollutio nlevel s woul dhav e bee ni nth e absenc e o f th e subsidy , an dthi s determinatio nmus t be adjuste da s condition s change . Thes e determination s ar e difficul t an dma y depen dupo ninformatio nP.3 5

II- 4 from th e polluter s wh o obviousl y hav e th e incentiv e t o understat e thei r intende demissions , (b ) Th e long-ru neffect s o f subsidie s ma y b e quit e differen t tha n fo r permit s o r taxe s sinc e th e forme r increas e profi t level s o r income s fo r pollutin g industrie s an dth e latte r decreas e them . Thus , i nth e long-run , subsidie s woul dresul t i nfirm s enterin g th e pollutin g industry , bu t permit s o r taxe s woul dcaus e firm s t o leave . Consequently , a fixe dsubsidy rat e woul dtendt o creat e pollutio nlevel s beyondthos e tha t ar e economicall y efficient . Also , subsidie s inth e for m o f investmen t ta x credits , woul dlikel y increas e dependenc e o ncapita l intensiv e solutions . 4 ) Marke t Oriente dApproache s an dClea nAi r Ac t Requirements . Th e Clea nAi r Ac t (Sectio nIII ) explicitl y require s tha t new , modified , an d reconstructe dstationar y source s suc ha s industrial-commercial-institutiona l stea m generatin g unit s contro l emission s t o th e leve l achievabl e b y th e bes t demonstrate dtechnologica l system o f continuou s emissio nreduction , considerin g costs , nonai r qualit y health , an

denvironmenta l an

denerg y impacts . Thi s preclude s th e us e o f pollutio ntaxe s a s alternative s t o NSP S unles s th e exac t leve l o f taxatio ncoul db e establishe dtha t woul d achiev e pollutio nabatemen t equivalen t t o th e leve l achievabl e b y bes t demonstrate dtechnology . Th e us e o f subsidie s an dpermit s ar e als o rejecte dbecaus e o f th e Ac t requirements . Inth e cas e o f permits , th e numbe r o f permit s an

demissio nallowance s woul dhav e t o b e correctl y fixe di nadvance , tha t woul dachiev e th e same leve l o f emissio ncontro l
a s woul dotherwis e b e achieve db y th e bes t demonstrate dtechnology .II- 5

E . Regulator y

Alternative s Withi nth e Scop e o f Presen t Legislatio n A rang e o f regulator y

alternative s ha s bee ncarefull y evaluate d base donth e us e o f low sulfu r fuel s t o reduc e SO 2 emission s o r th e us e o f flu e ga s desulfurizatio n(FGD ) system s t o achiev e a percen t reduction i nSO 2 emissions . A

tota l o f si xalternativ e contro l level s wer e examine d
an dcompare dt o th e regulator y baseline . Th e si xregulator y alternative s wer e eac hanalyze dunde r two differen t energ y scenarios . Thi s energ y sensitivit y

analysi s wa s performe dbecaus e th e magnitud e o f th e economic , environmental , an

denerg y impact s associate dwit hvariou s regulator y alternative s fo r ne

w stea m generatin g unit s i s primaril y a functio no f th e typ e o f fue l selecte dfo r eac ho f th e units . Th e typ e o f fossi l fue l selecte dfo r eac hne

w steam generatin g uni t i s a functio no f th e projecte d price s fo r coal , oil , an dnatura l gas , a s wel l a s th e cost s associate dwit h environmenta l regulations . Fo r mor e informatio nonth e energ y price s use di nthi s analysi s see , "Regiona l Forecast s o f Industria l Residua l Fue l Oi l an

dNatura l Ga s Prices, " Jul y 1984 . Th e highoi l penetratio n scenari o reflect s th e Agency' s bes t projectio no f futur e coal , oil , an d natura l ga s prices . Oi l price s ar e relativel y low an dnatura l ga s price s ar e generall y

a t o r abov e th e pric e o f low sulfu r residua l oil . Unde r thi s energ y

pric e scenari o residua l oi l an dnatura l ga s compet e fo r th e industria l steam

generatin g uni t energ y market , wit hresidua l oi l achievin g a slightl y

large r share . Coa l doe s no t effectivel y compet e i nthi s market . I nrespons e t o concern s tha t thi s energ y pricin g scenari o migh t underestimat e coa l penetratio ni nth e new industria l steam

generatin gP.3 7

II- 6 uni t energ y

market , a

nalternativ e energ y

scenari o wa s develope dt o yiel d highe r coa l penetration . Inthi s energy scenario , coa l price s wer e assume dt o remai nth e same a s thos e discusse dfo r th e highoi l penetratio n energ y scenario . Th e oi l price s usedwer e highe r tha nthos e use di nth e hig hoi l penetratio nscenari o an dwer e als o use dt o forecas t natura l ga s prices . I nthi s highcoa l penetratio nscenari o coa l andnatura l ga s compet e fo r th e steam generatin g uni t energ y marke t wit hcoa l capturin g a slightl y large r shar e tha nnatura l gas . Oi l doe s no t effectivel y compet e i nthi s marke t du e t o th e relativel y low coa l an dnatura l ga s prices . Fo r a mor e detaile ddiscussio no f th e regulator y alternative s an

dth e energ y scenario s se e th e Preambl e (EPA-450/3-82 - ) . Du e t o tim e an

dresourc e constraints , fo r purpose s o f thi s RI A tw o regulator y

alternative s wer e examined . Thes e regulator y alternative s wer e th e tw o mos t viabl e candidate s t o serv e a s th e basi s fo r th e propose d NSPS . Eac halternativ e i s analyticall y compare dt o th e curren t regulator y

baseline . Bot hregulator y alternative s wer e analyze dunde r th e highoi l penetratio nscenario . Thi s energ y scenari o wa s chose nbecaus e i t mos t accuratel y

reflect s curren t projection s o f futur e energ y prices . 1
. Regulator yBaselin e

Th e regulator y

baselin e i s define db y existin g Stat e Implemen tatio nPlan s an

dth e existin g NSP S (4 0 CFR , Par t 60 , Subpar t D ) fo r larg e stea

m generatin g unit s o f mor e tha n7 3 M W (25 0 millio n Btu/hour ) hea t input . 2
. Lo wSulfu rFue l Thi s alternativ e i s base do nth e us e o f lo

w sulfu r fue l t o reduc e emission s t o 34 4 n g SO2/ J(0. 8 l bS02/millio nBtu ) hea tP3 8

II- 7 inpu t fro

m oi l combustio nan

dt o 51 6 ng SO2/ J(1. 2 l bS02/millio n Btu ) hea t inpu t fro

m coa l combustion . 3 . Percen t Reductio n

Thi s alternativ e i s base donth e us e o f FG Dsystem s t o achiev e a 9 0 percen t reductio ni nSO 2 emission s fro m bot hoi l an

d
coa l combustion . Thi s alternativ e woul dgenerall y reduc e emission s fro m coa l combustio nt o les s tha n25 8 ng/ J(0. 6 l bS02/miliio n Btu ) hea t inpu t an

dfro m oi l combustio nt o les s tha n12 9 ng/ J (0. 3 l bS02/millio nBtu ) hea t input .P.3 9



### II- 8
REFERENCE S Regiona l Forecast s o f Industria l Residua l Fue l Oi l an d Natura l Ga s Price s Jul y198

4 Energ yan d Environmenta l Analysis , Inc

. fo rth e U.S

. Environ menta l Protectio n Agency

.P.4 0

III- l III . AI RQUALIT YDAT A A

. Introductio n Th e estimatio no f economi c benefit s fo r th e two regulator y alternative s require s th e calculatio no f change s i npopulatio nexposur e fro m th e baselin e t o eac halternative . This , i nterm , require s knowledg e o f projecte dai r qualit y changes . Thi s sectio nprovide s a descriptio no f th e thre e type s o f ai r qualit y dat a use dfo r th e benefi t analysis . Th e firs t i s SO 4 dat a use dfo r visua l rang e improvemen t benefits . Th e geographi c coverag e i s 3 1 easter nstates . Th e ai r qualit y

change s resul t fro

m industria l boile r complianc e wit hth e tw o regulator y

alternatives . PM

ai r qualit y

dat a i s use dt o estimat e PM relate dmorbidit y

ris kreductionan

dresidentia l soilin g reductio nbenefits . Th e geographi c coverag e fo r P M benefit s i s als o th e 3 1 easter nstat e region . Thi s secondtyp e o f ai r qualit y dat a use s th e firs t typ e o f ai r qualit y dat a a s a ninpu t bu t transform s th e change s i nSO 4 t o change s i n TSP . Th e thir dtyp e o f ai r qualit y dat a i s SO 2 informatio nuse dt o estimat e material s damag e reductions , agricultura l yiel dreductions , and morbidit y

reductionbenefits . Th e geographi c are a fo r th e SO 2 ambien t ai r qualit y

dat a i s 11 3 areas , sprea dacros s th e country , wher e new industria l boiler s ar e projecte dt o b e locate di n1990 . B . SO 4 Ai r Qualit y

Assessmen t Th e standard s analyze di nthi s RI A al l relat e t o th e loca l scal e impact s o f sulfu r oxid e sources . However , i t i s generall y recognize d that SO 2 emission s als o hav e regiona l scal e effects . I nth e atmospher e SO 2 ca nb e transforme dint o sulfate s (SO4 ) an dbot hca nb e transporte d fo r lon g distance s (>30 0 km) . A s a par t o f th e overal l RI A th e effec t o f SO 2 emission s reduction s onsulfate s an dvisua l rang e wer e modele donaP.4 1

III- 2 regiona l scale

. Th e modelin g o f source-recepto rrelationship s o n an y geographi cscal e an d fo ran ypollutan t i s difficul t an d involve s som e uncertainty

. Modelin g o f regiona l scal e transport , dispersion , chemica l transformatio n an d remova l o f sulfu roxide s i s quit e difficul t an d involve s a numbe ro f uncertainties

. Nevertheles s ove rth e pas t severa l year s a numbe ro f model s hav e bee n developed

. Althoug h n o model s hav e bee n teste d usin g a n adequat e arra yo f ai rqualit ymeteorolog ydata , comparison s o f mode l result s wit h long-ter m dat a sugges t tha t thes e model s ar e no wa t a stag e o f developmen t tha t the yca n b e use d t o provid e som e insigh t int o th e magnitud e an d natur e o f ai rqualit ychange s tha t migh t resul t fro m emissio n reductio n scenarios

. "Fo rpurpose s o fthi s RIA , transfe rmatrice s wer e derive d fro m th e Advance d Statistica l Trajector yRegiona l Ai rPollutio n (ASTRAP) mode l an d visua l rang e was estimate d outsid e th e model/matri x usin g th e matri xgenerate d SO 4 concentrations

. ASTRA P i s a regiona l scal e SO

2 mode l tha t consider s transport , dispersion , chemica l transfor matio n an d remova l o f sulfu roxides

. A s use d i n thi s analysis , ASTRA P model s SO

2 sourc e -recepto rrelationship s i n th e 31-easter n stat e region

. Adescriptio n o f th e ASTRA P matri xfollow s i n Tabl e III-l

. Transfe rmatrice s assum e tha t concentration s a t a give n recepto r equa l th e su m o f al l partia l contributions

. Thus , th e concentratio n C a t recepto rAcoul d b e represente d as : C A= T A 1 * E i + T A 2 * E 2 + .. . + T A J * E j wher e E j i s th e emissio n rat e fro m th e JJ H sourc e regio n an d T A j i s a propor tionalit ycoefficien t relatin g regio n Temission s t o regio n Aconcentrations

. An arra yo fthes e T A j coefficient s ca n b e generate d fro m runnin g th e ful l mode l an d constitute s a transfe rmatrix

. Transfe rmatrice s ar e extremel yinexpensiv e an d eas yt o appl ycompare d t o ful l regiona l scal e mode l runs . However , the yP.4 2

III- 3 TABLE III- l ASTRA P Matrix 1

1 ) 2 )

3 ) 4 )

5 ) 6 ) 7 )

8 ) CRITERI A Mode l Domai n Transformatio n Rates 2

Retur n Flow s Treatmen t o f Emissio n Release s Backgroun d Factor s Meteorolog y Wester n Stat e Emission s (Outsid e 31 - Stat e Region ) Canadia n Emission s ASTRA P
4 8 States , plu s Canad a Winte r0.5 3 Sprin g 1. 0 Summe r2. 0 Fal l 0. 7 Addresse s retur n flow s fro m Atlanti c Consider s lo wleve l release s a s wel l a s elevate d releases '
Non e 197 6 - 198 1 199 5 projected ; unchange d b yalternativ e

199 5 projected ; unchange d byalternativ e

1 Advance d Statistica l Trajector yRegiona l Ai rPollution

. 2 Expresse d a s %o fSO 2 converte d t o sulfat e pe rhour

. 3 Approximat e dail yaverages . Actua l rate s exhibi t stron g diurna l variation

.P.4 3

III- 4 als o carr y

wit hthem

a numbe r o f limitation s i nadditio nt o thos e inheren t t o th e model s themselves : o Th e matri xuse demploy s stat e leve l sourc e an drecepto r regions . Therefore , ther e i s som e "averagin g out " o f difference s whic hmigh t b e apparen t wit hth e fine r grid s use di nth e model s themselves . Thi s ma y b e a significan t limitatio ninthi s analysi s becaus e th e emissio nchange s bein g modele dvary fro m sourc e t o source , o Th e models/matrice s usedar e linear . Ther e i s substantia l dis agreemen t a s t o whethe r th e processe s bein g modele dar e i nfac t linear . I f non-linea r processe s wer e foun dthe nth e estimate s use dher e woul dno t b e accurate , o Inmodelin g SO 4 level s resultin g fro m th e two regulator y alternative s onl y

emissio nchange s inth e easter n3 1 stat e regio n wer e modeled . Wester nU.S . an dCanadia nemission s wer e modele d
a t thei r 199 5 bas e level . Thi s wa s don e becaus e th e dat a wa s readil y availabl e fo r th e 3 1 stat e region . I nconsiderin g th e benefit s calculation s an dresults , th e reade r shoul dkee pthes e limitation s inmind . A mor e complet e discussio no f regiona l modelin g an dtransfe r matrice s ca nbe foun

dinth e Memorandu

m o f Inten t onTransboundar y Ai r Pollutio n (1982) . C . SO 4 Ai r Qualit y Result s Th e 199 5 bas e cas e sulfat e emissions , estimate dfro m th e ASTRA P matrix , fo r th e 3 1 easter nstates , ar e displaye di nTabl e III-2 . Th e bas e cas e sulfat e estimate s represen t th e estimate dsulfat e level s associate d wit hnorma l growt han dretiremen t o f source s bu t wit hn o chang e inth e

### II1- 5 P.4 4

199 5 Bas e

STAT E

Alabam a Arkansa s Connecticu t De l awar e Florid a Georgi a 111inoi s Indian a Iowa Kentuck y Louisian a Main e Marylan d Massachusett s Michiga n Minnesot a Mississipp i Missour i Ne w Hampshir e Ne w Jerse y Ne w Yor k Nort hCarolin a Ohi o Pennsylvani a Rhod e Islan d Sout hCarolin a Tennesse e Vermon t Virgini a Wes t Vi rgini a Wisconsi n TABL E 111- 2

Cas e S u (pg/m 3 Ifat e Estimate s

S0 4 )

• ASTRA P

ug/m 3


### 5. 2 3. 1 8. 2 11. 5 

### 4. 0 5. 7 5. 5 8. 1 2. 7 8. 5 2. 6 3. 6 10. 9 

### 6. 5 4. 5 1. 4 3. 7 4. 0 5. 6 10. 5 

### 7. 5 7. 8 9. 6 11. 3 

### 7. 1 6. 8 6. 9 5. 1 9. 3 11. 5 

### 3. 1P.4 5

111- 6 regulator y

scenario . Tabl e 111- 3 represent s th e reductio ninsulfat e estimate s du e t o th e lo w sulfu r fue l regulator y alternative , alon g wit hth e percent chang e fro m th e 199 5 baseline . Tabl e II1- 4 represent s th e same informatio nfo r th e percen t reductio nalternative . A s expected , bot halternativ e contro l level s resul t i nSO 4 reductions , wit hth e percen t reductio nalternativ e resultin g i nth e larges t reductio nfrom th e 199 5 basecase . Th e estimate dsulfat e level s wer e intur nuse dt o calculat e visua l range . Thi s calculatio nuse s th e result s fro m th e ASTRA P mode l (Table s 111- 3 an

d111-4 ) wit hanaverag e nonsulfate/sulfat e ligh t extinctio nrati o
o f 1.25 . Th e estimate d199 5 baselin e visibilit y i s presente di nTabl e 111- 5 alon g wit hth e visibilit y improvement s du e t o th e lo w sulfu r fue l
an dpercent reductio nregulator y alternatives . D . P M Ai r Qualit y

Assessmen t Th e ai r qualit y

informatio ndevelope dfo r th e SO 4 benefi t assessmen t i s als o use dfo r th e PM benefi t assessment . Specifically , th e SO 4 change s fo r eac hstat e describe di nth e las t sectio nar e used . Th e SO 4 change s
ar e translate dint o TS P change s b y multiplyin g b

y 1. 4 fo r th e low

estimate , 1. 5 fo r th e middl e estimat e an d1. 6 fo r th e highestimate . Thes e factor s (Bachmann , 1985 ) ar e use dt o accoun t fo r th e weigh t o f ammoni a an dwate r chang e i nTS P weigh t associate dwit hth e chang e i nSO4 . N o estimate s o f direc t P M

emissio nreduction s fo r alternativ e standard s du e t o SO 2 control s
suc ha s scrubbin g wer e calculated . Therefor e no estimate s o f PM ambien t ai r reduction s du e t o reductio no f P M emission s ar e include di nth e analysis . E . SO 2 Ai r Qualit y Assessmen t Thi s sectio ndescribe s th e principa l procedure s an dassumption s use dt o calculat e th e SO 2 ai r qualit y impact s o f th e two regulator y alternatives . Th e firs t subsectio ndescribe s th e developmen t o f th e emission s inventory ,P.4 6



### III- 7

TABL E 111- 3 199 5 Sulfat e Emission s Lo w Sulfu r Fue l Alternativ e (ug/m 3 and% chang e from 199 5 Bas e Case )

STAT E ASTRA P yg/m 3 

### % Chang e Alabam a 5. 2 - . 8 Arkansa s 3. 1 -1. 3 Connecticu t 8. 2 - . 2 Delawar e 11. 5 - . 2 Florid a 3. 9 - . 6 Georgi a 5. 7 - . 5 11 1 inoi s 5_ 1 

### 5

_- . 3 Indian a 8. 1 - . 2 Iowa 2. 6 - . 8 Kentuck y 8. 5 - . 3 Louisian a 2. 5 -3. 9 Main e 3. 6 - . 1 Marylan d 1CL 9 - . 2 

### Massachusett s 57 5 - . 2 Michiga n4. 5 - . 3 Minnesot a 1. 4 - . 3 Mississipp i 3. 6 -1. 6 Missour i 4. 0 - . 9 Ne w Hampshir e 5^ 6 - . 2 Ne w Jerse y 10. 5 - . 2 Ne w Yor k7. 5 - . 2 Nort hCarolin a 7. 8 - . 4 Ohi o 9. 6 - . 3 Pennsylvani a 11. 3 - . 2 Rhod e Islan dIA - . 2 Sout hCarolin a 578 " - . 5 Tennesse e 6. 9 - . 5 Vermon t 5. 1 - . 2 Virgini a 9. 3 - . 3 Wes t Virgini a 11. 5 - . 3 Wisconsi n3. 1 - . 3P.4 7

III- 8

TABL E 111- 4 199 5 Sulfat e Emission s Percen t Reductio nAlternativ e (ug/m 3 and% chang e from 199 5 Bas e Case )
STAT E ASTRA P pg/m 3 %

Chang e
Alabam a 5. 1 -1. 0 Arkansa s 3. 1 -1. 4 Connecticu t 8. 2 - . 4 Delawar e 11. 5 - . 4 Florid a 3. 9 - . 8 Georgi a 5. 7 - . 6 11 1 inoi s 5_J > - . 5 Indian a 8. 1 - . 4 Iowa 2. 6 -1. 0 Kentuck y 8. 5 - . 5 Louisian a 2. 5 -4. 0 Main e 3. 6 - . 3 Marylan d10. 9 - . 4 Massachusett s 57 5 - . 4 Michiga n4. 4 - . 6 Minnesot a 1. 4 - . 7 Mississipp i 3. 6 -1. 7 Missour i 4. 0 -1. 0 Ne w Hampshir e 5^ 6 - . 3 Ne w Jerse y 10. 5 - . 4 Ne w Yor k7. 5 - . 4 Nort hCaro l in a 7. 8 - . 7 Ohi o 9. 6 - . 4 Pennsylvani a 11. 3 - . 4 Rhod e Islan d7. 0 - . 4 Sout hCarolin a §7 7 - . 7 Tennesse e 6. 9 - . 6 Vermon t 5. 1 - . 3 Virgini a 9. 2 - . 5 Wes t Virgini a 11. 5 - . 4 Wisconsi n3. 1 - . 7- o ( U a. 4-> tz c u o t
_ c u

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^win(jiMOir^oocvirxNHivMTj-(jiONroir)OOoor^rHiHoo«toicovD< t MCVJ|v^iNr^r>.i^iji00C\lliOcfO\00iHrOiOiHa)l£l>DlO'Ji00VOir)rH<a-CJ10 0 rlHNCMHHHi-tHHHMtMIMHtMHHnlMlMHHHWHrinNHf- l

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Z 3 r —C-OCUr - CUr —c z o c u o < t < C C J O ll - CJ J t—it—it—i ^ J E < o

. o c u c z r - 1 0 2 1 t o • u • u c u t o •a 3 cz x : i o O i — < o > > c i - t/ > i o < o 2 1 S T c z I O CTI •r - sz u •r - s •r -

O . I O Q . • u ••- o tn tn m C U -r- c m tz vt •I—-rs. z : c u

c_ •r — J = t o •I —Q . t- E 3 < 0 o 3 : t o t o 2 •r - c u s : z : > > c u tn ^ t - c _ <u o O > - S 5 a i c u z zina
tr — o i

_ to o J = 4- > t
_ o z : o •r — J = O 10 " O •r - c z c z to I O «— > t o r —l— l > > V ) C U c z - o c z o C U J = Q . otina

9 - 9 o C

_ ( O t i -C T • u 3 o C D c u t o C O a ; c z c z c u 0 0 I — + J c o 

### E c u > to

-1— c •r - CT> C Z IO C- -r- •t —•!" - W l c > c •r - o CT>4-> O L tf) V )
. , - c u •• - > 3 3 l O CVJ - o o
l O c o

• u o c •r - c u

c n
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•»- > l O 3 in <v • u < o 3 t o c z o c c u CT> i O c _ c u > ( O c z i O tn cv 9
. 3 vt inP.4 9

111-1 0 th e secondth e determinatio no f th e stud y areas , an

d th e thir dth e modelin g approach . 1 . Emission s Inventor y
a ) Dat a Base s Fou rdat a base s wer e use d t o develo p th e emission s inventory : o Apoin t sourc e inventor ybase d o n MAP3 S (referre d t o a s th e EES inventory) , o Th e uni t inventor yo f utilitie s fro m th e Advance d Utilit ySimulatio n Mode l (AUSM)

. o Th e inventor yo f ne windustria l boiler s provide d by Energ yan d Environmenta l Analysi s (EEA) base d o n th e Industria l Fue l Choic e Analysi s Mode l (IFCAM) , o Th e curren t county-leve l are a sourc e inventor yfro m th e Nationa l Emission s Dat a Syste m (NEDS)

. Tabl e 111- 7 shows whic h dat a bas e was use d a s th e basi s fo rth e inventor yfo r differen t sources . TABLE 111- 6 Emission s Dat a Base s an d Growt h Sourc e Dat a Bas e Typ e Categor yAg e EE S EEAGrowt h (MAP3S ) AUSM (IFCAM ) NED S Applied ?

Poin t Utilit yExistin g xxN o N o N o xN o

Ye s Are a Al l xYe s

Utilit y Industria l boiler s Othe r Al l Existin g

Ne w Existin g Ne w

• -

- X

X

X X

XP.5 0

I 11-1 1 b ) Inventor y

Developmen t Th e developmen t o f th e inventor y ca nb e considere da s havin g take n plac e i na serie s o f steps . Utilit y dat a wa s take nfro m o f th e AUSM 2 uni t inventory . AUS M contain s dat a onindividua l utilit y boilers . Amon g othe r data , AUS M provides :
o Locatio nb

y stat e an

dcounty , o Plan t name , o Startu pyea r i f uni t i s a planne dne w unit , o Retiremen t year , an d
o Fue l an

dfue l consumptio ndata . However , AUS M

di dno t includ e th e stac kparameter s require dfo r modelin g no r
a complet e se t o f emissions . 1 . Stac kparameter s (height , temperature , diameter , volum e flow ) an d industria l steam

generatin g uni t emission s wer e adde dt o th e AUS M utilit y data . Th e value s use dwer e base doninformatio ni nth e Utilit y Boile r Backgroun dInformatio nDocumen t (EP A 450/3-79-021 ) an

dEP A engineerin g judgement . Emission s wer e base do na mode l 50 0 MMBtu/hou r boile r an dwer e mad e proportiona l t o capacity . I t wa s assume dtha t Subpar t Dapplie dt o utilit y boiler s wit hstartu pdate s betwee n197 7 an d1986 , inclusive , an d tha t Subpar t D a applie dt butilit y boiler s wit hstartu pdate s o f 198 7 an d beyond . Th e MAP3 S inventor y wa s develope db

y Brookhave nNationa l Laborator y unde r th e MAP3S/RAIN E program . Th e poin t sourc e dat a i nMAP3 S ar e base d primaril y

upo ndat a take nfro m EPA' s NEDS . Som e o f th e NED S dat a wer e revise do r supplemente ddurin g th e developmen t o f MAP3 S (Benkovitz , 1980) . I ndevelopin g th e EE S inventory , missin g dat a wer e defaulte dan dinconsisten tP.5 1

111-1 2 dat a wer e change d a s describe d i n Brubake ran d Smith , 1984
. Th e nomina l yea ro f thi s inventor yi s 1978
. 2
. Th e EES poin t inventor ywas use d a s th e basi cdat a se t fo r source s othe rtha n utilitie s an d industria l boilers

. Wher e possible , utilit yboiler s i n th e EES inventor ywer e replace d byutilit yboiler s fro m AUSM

. Thes e matche s wer e made base d o n state , county , plan t name , an d boile rsize

. Wher e matche s coul d no t b e made , th e EE S dat a was retained

. Th e retiremen t o rstartu p yea rwer e retaine d wit h th e utilit y boile rdat a base d o n AUSM

. 3
. Th e EE

Aindustria l boile rdat a was processe d t o ad d stac k parameter s (height , temperature , volum e flow ) base d o n informatio n i n th e Summar yo f Regulator yAnalysi s (EP A450/3-86- ) an d EP Aengineerin g judgement

. Cost s an d emission s wer e base d o n dat a i n th e EEA/IFCA M boile rfile

. Boiler s burnin g natura l ga s i n al l thre e case s (bas e case , lo wsulfu r fuel , an d percen t reductio n wer e delete d becaus e thei rSO 2 emission s ar e neg l igible

. 4
. Th e EE

Afile s locat e boiler s onl yb yfedera l region

. The yals o associat e eac h boile rwit h a 2-digi t SI C category
. Withi n a particula r SI C categor yan d region , th e EE Aboiler s wer e site d a t existin g plants

. Thi s sitin g wa

s accomplishe d i n stages
. First , th e tota l coa l an d oi l consumptio n (Btu's/year ) i n industria l boiler s was determine d fo reac h plan t i n th e region/SIC

. The n eac h EE Aboile rwa s randoml yassigne d t o a specifi cplan t wit h th e assignmen t weighte d b yth e consumptio n o f tha t boiler' s base-cas e fue l type
. Thus , i fplan t l' s industria l boiler s fire d twic e a s man

yBtu' s o fcoa l a s th e boiler s i n plan t 2 , plan t 1 woul d b e twic e a s likel ya s plan t 2 t o b e chose n a s th e sit e o fa particula r EE Aboile rfuele d bycoa l i n th e bas e case .111-1 3 5
. Th e source s i n th e EEA/MAP3 S wer e screene d t o eliminat e thos e wit h a maximu m 1-hou rS0 2 concentratio n exceedin g 450 0 pg/m 3

. Suc h larg e maximu m concentration s ar e believe d t o b e du e t o problem s i n th e dat a base

. 6
. Th e county-leve l are a sourc e emission s fro m NED S wer e use d withou t change

. A t thi s point , th e inventor yca n b e considere d a s consistin g o f th e following : o Ne windustria l boiler s fro m EEA/IFCA M wit h stac k parameter s adde d an d site d randoml ybyregion/SIC , o Utilit yboiler s fro m AUSM 2 wit h stac k

parameter s an d industria l stea m generatin g uni t emission s adde d an d includin g retiremen t an d startu p years , o Som

e additiona l utilit yboiler s tha t coul d no t b e matche d t o AUS M fro m th e EE

S inventory , o Othe rpoin t source s fro m th e EE S inventor ybase d o n MAP3 S wit h a 1-hou rSO

2 impac t <450 0 pg/m 3 , an d 0 County-leve l are a sourc e emission s fro m NEDS

. Thes e emission s wer e projecte d t o 199 0 an d th e 11 3 stud yarea s wer e identifie d prio rt o modeling

. C

. Projecte d Emission s I n projectin g emission s t o 1990 , n o growt h rat e wa s applie d t o th e followin g sourc e categorie s (Se e Tabl e II1-7) : 0 Utilit yboiler s becaus e growt h was assume d t o b e represente d adequatel yb

yth e AUS

M unit s schedule d t o start-u p befor e 1990 , 0 Industria l boiler s becaus e growt h was assume d t o b e represente d adequatel ybyth e boiler s i n th e EEA/IFCA M files , an dP.5 3

111-1 4

o Primar ycopper , lead , an d zin csmelter s fo rwhic h n o ne wsource s ar e anticipated

. A l l othe rpoin t sourc e growt h was assume d t o occu ri n place

. Growt h an d retiremen t wer e projecte d o n a source-by-sourc e basi s usin g two-digi t SI C state-specifi cgrowt h rate s an d two-digi t SI C national-averag e retiremen t value s (Smit h an d Brubaker , 1983)

. Th e projecte d growt h an d retiremen t wer e require d t o mee t applicabl e NSPSs

. I f a source' s base-yea remission s exceede d 10 0 T/yr , th e projecte d growt h an d retiremen t wer e assume d t o hav e t o mee t th e BACT

. NSPS' s wer e take n fro m EPA' s Cost-Effectivenes s Fil e (CEF ) an d BAC

Twas assume d t o b e th e averag e contro l o f th e SO 2 NSPS' s i n th e CE F (97.5 % removal)

. Are a source s wer e grow n a t state-specifi c populatio n growt h rates
. 2
. Determinin g Stud yArea s Th e 11 3 stud yarea s wer e chose n t o includ e al l th e plant s a t whic h EEA/IFCA M boiler s ha d bee n sited

. Th e stud yarea s wer e determine d manually

. An initia l attemp t was mad e t o locat e eac h EEA/IFCA M a t th e cente ro f a 6 0 k

m b y6 0 k

m squar e recepto rgri d wit h 6 receptor s alon g eac h edg e givin g a tota l o f 3 6 receptor s an d a gri d spacin g o f1 2 km , oriente d wit h tw o edge s runnin g north-south

. I n man ycases , however , thi s initia l locatio n was modifie d t o reduc e th e numbe ro f receptor s ove rwate ran d t o avoi d overlappin g grids

. Th e recepto rgrid s containe d fro m 24-4 8 receptors , ha d recepto rspacing s o f10-2 0 km , an d ha d dimension s o f fro m 4 8 t o 15 0 km

. Th e inventor yassociate d wit h eac h gri d fo rmodelin g purpose s include d th e poin t an d are a source s i n al l th e countie s withi n abou t 40-6 0 k m o f th e oute redge s o f th e recepto rgri d an d thu s include d mos t o f th e source s whic h woul d hav e a n appreciabl e impac t withi n a particula rrecepto rgrid

.P.5 4

111-1 5 I t shoul db e note dtha t a particula r source , includin g new EEA/IFCA

M boilers , coul db e include di nth e inventorie s o f 3 o r perhap s mor e study
areas . However , n o doubl e countin g occurre dbecaus e ther e wa s no overla p
o f th e recepto r grids . 3 . Ai r Qualit y

Modelin g
a ) Meteorologica l Dat a Meteorologica l dat a specifi c t o eac ho f th e 11 3 area s i nth e stud y
wa s no t readil y

available . Inlie uo f site-specifi c data , eigh t location s i nth e continenta l Unite dState s wer e selecte ds o a s t o incorporat e al l majo r geographi c variable s tha t migh t hav e a large , systemati c effec t o n loca l climate . Hourl y meteorologica l dat a wer e obtaine dfro m th e National Weathe r Servic e fo r thes e locations , an dwer e processe dusin g a modifie d versio no f th e U.S . EP A meteorologica l dat a processin g progra m (CRSTER ) t o produc e a datase t suitabl e fo r us e i nai r qualit y modeling . I norde r t o ru nth e ai r qualit y

mode l fo r some give nanalysi s area , th e mos t suitabl e o f thes e eigh t meteorologica l dat a set s wa s selected , base dupo n geographi c similarit y an dproximity , an

duse dwithou t furthe r modification . Th e eigh t location s use di nthi s stud y wer e Sa nFrancisco , CA ; Albuquerque , NM ; Ellswort hAFB , SD ; Columbus , OH ; Shreveport , LA ; Philadelphia , PA ; Washington , DC ; an

dJacksonville , FL . Anentir e yea r of hourl y meteorologica l dat a wa s availabl e fo r eac h mode l run . I norde r t o reduc e th e computin g time , s o tha t al l area s coul db e handle dwithi nth e scop e o f th e program , onl y ever y fift hda y
wa s actuall y

modeled . Thus , annua l or seasona l extrem e value s ma y hav e bee nunderestimate dan dmea nvalue s ar e subjec t t o uncertaintie s arisin g fro m thi s samplin g procedure .P.5 5

111-1 6 b ) Ai rQualit yMode l I n orde rt o mak

e reasonabl e estimate s o f th e require d ai rqualit y variable s fo reac h o f th e 11 3 area s withou t th e expenditur e o f unreasonabl e amount s o f compute rtime , a n approximat e procedur e wa s use d fo rth e estimatin g o f th e contribution s fro m th e mino rbackgroun d poin t sources . Briefly , al l "major " poin t sources , define d fo rthi s wor k a s thos e wit h emission s exceedin g 30 0 T/year , were modele d a s poin t sources . Th e remainin g mino rpoin t source s wer e treate d as clusters , identifie d base d o n physica l proximity , an d replace d b yan elliptical-shape d "area " source . Th e calculatio n o f th e 1-hou rSO 2 concentratio n a t a recepto rfro m a poin t sourc e wa

s don e usin g a recently-develope d expressio n fo rth e mea n concentration , give n tha t th e win d directio n i s onl yknow n t o withi n 1 0 degrees

. Th e formul a i s base d o n th e standar d Gaussia n model

. Th e dispersio n coefficient s an d plum e ris e value s use d were compute d usin g USEPA-approved algorithms

. Th e emissio n inventor yactuall yuse d i n a mode l ru n consisted , then , o f 1 ) ne wan d ol d utilitie s a s points , 2 ) ne

wEEA/IFCA

M boiler s a

s points , 3 ) ol d majo rpoin t source s (thos e wit h annua l emission s i n exces s o f300 T/year) , 4 ) elliptica l are a source s (simulatin g th e effect s o f mino rpoin t sources , i.e. , thos e wit h annua l emission s les s tha n 300 T/year ) an d 5 ) tru e are a sources , whose emission s were arbitraril yallocate d t o thos e o f th e elliptica l area s i n proportio n t o thei remissio n rates
.P.5 6

111-1 7 REFERENCE

S
Memorandu m o fInten t o n Transboundar yAi rPollutio n (1982)

. Atmospheri c Science s an d Analysi s Work Grou p 2 Fina l Report , Novembe r1982
. Bachmann , Joh n (1985)

. Memorandu m t o To m Walton

. Subject : Calculatio n o f Visua l Rang e Change s fro m Predicte d Sulfat e Changes

. Jun e 10 , 1985
. Benkovitz , C

. M

. (1980)

. Emissio n Inventor yProgres s Report , Brookhave n Nationa l Laborator yrepor t BNL-5137 8 UC-11 , Ne wYork

. Brubaker , K

. L. , an d A

. E. Smit h (1984)

. Ai rQualit yAnalyse s i n Suppor t o f Regulator yImpac t Analysi s fo rSO ? NAAQ S - Technica l Notes , unnumbered , Argonn e Nationa l Laborator yreport , Argonne , Illinois

. Smith , A

. E. , an d K

. C

. Brubake r(1983)

. Cost s an d Ai rQualit yImpact s o f Alternativ e Nationa l Ambien t Ai rQualit yStandard s fo rParticulat e Matte r- Technica l Suppor t Document , Argonn e Nationa l Laboraoty rRepor t ANL/EES-TM-229

.



# IIV- 1

IV . ENGINEERIN GCOST S A . Introductio n Nationa l cos t impact s o n ne windustria l fossi l fuel-fire d stea m generatin g unit s wer e analyze d throug h th e us e o fa compute rmode l calle d th e Industria l Fue l Choic e Analysi s Mode l (IFCAM)

. Thi s cos t analysi s i s describe d i n detai l i n "Projecte d Impact s o f Alternativ e Sulfu rDioxid e Ne wSourc e Performanc e Standard s fo rIndustria l Fossi l Fuel-Fire d Boilers, " Marc h 1985
. IFCA

M i s a n energ ydeman d mode l develope d t o evaluat e fue l choic e decision s i n th e industria l secto rove ra fiv e t o 15-yea rforecas t horizon

. IFCA

M i s a highl ydisaggregate d proces s engineerin g mode l designe d t o analyz e factor s affectin g fue l choic e decision s i n industria l boile renerg yapplications

. IFCA M assesse s th e impact s o f fou rset s o f factor s affectin g industria l fue l choice : fue l prices , Stat e an d Federa l energ yan d environmenta l polic yproposals , th e cost s associate d wit h firin g alternat e fuels , an d othe rke ymode l parameter s suc h a s th e expecte d siz e distributio n o f ne w industria l boilers

. Th e mode l i s capabl e o festimatin g th e energy , environmental , an d cos t impact s o falternativ e ai remissio n regulation s fo rne windustria l boilers

. B . Analytica l Framewor k IFCA M focuse s onboile r fue l choic e decision s betwee ncoal , oil , an d natura l gas . Th e mode l determine s fue l choice s fo r boiler s i neac ho f th e 1 0 Federa l region s usin g projecte dindustria l fue l price s an dtota l fossi l fue l deman dtha t primaril y hav e bee ngenerate db y th e U.S . Departmen t
o f Energ y

(DOE) . Fo r purpose s o f thi s analysis , th e mode l mus t distinguis h betwee nnew

industria l boilers , othe r proces s heaters , an dexistin gP.5 8

IV- 2
industria l boilers . Sinc e thi s i s a NSPS , th e onl y categor y

relevan t t o thi s analysi s i s th e ne w industria l boilers . A ver y disaggregat e representatio no f industria l energ y use s i s incorporate di nIFCAM . Energ y us e i s disaggregate dint o nin e industria l subsector s havin g differen t growt hrate s an dregiona l dispersions . Eac h
o f thes e industria l subsector s i s furthe r divide dint o boile r an dproces s hea t applications . Industria l boile r energy us e i s disaggregate db y ne w an dexistin g boiler s o f differen t size s an dcapacit y

utilization s rates . New an d existin g boiler s ar e classifie do nth e basi s o f th e typ e o f fue l the y
wer e designe dt o fir e an dwhethe r the y

ca nb e retrofitte dt o fir e alternativ e fuels . Eigh t siz e classe s ar e delineate dfo r boilers . Ther e
ar e fiv e capacit y

utilizatio nrat e categorie s fo r boilers . Th e fina l leve l o f disaggregatio nincorporate s regiona l detail . Industria l boile r fue l us e i s divide damon g Ai r Qualit y Contro l Region s (AQCR's) . Sinc e a larg e numbe r o f region s ar e considere db y IFCAM , th e mode l ca nportra y

th e variabilit y

i nth e environmenta l contro l cost s o f usin g th e variou s fuel s t o fir e boiler s locate dthroughou t th e country . Base do nth e characteristic s o f eac hcombusto r (size , operatin g rate , pollutio ncontro l requirements , etc.) , capita l an dnonfue l operatin g cost s ar e generate dfo r th e option s o f choosin g oil , gas , o r coal . Th e fue l typ e associate dwit hth e lowes t after-ta xpresen t valu e (includin g expecte dfue l expenses ) o f th e tota l cos t o f generatin g energ y ove r th e investmen t perio di s selected . A s a fina l output , th e mode l generate s tota l cost s (capital , annua l operating , maintenanc e an dfue l expenses ) o f usin g th e selecte dfossi l fue l t o generat e steam .P.5 9

IV- 3
Tabl e IV- 1 present s th e tota l annualize dcost s an dcontro l cost s fo r th e baselin e an

dtwo regulator y

alternative s examine dinthi s RIA . Eac halternativ e i s analyze dusin g th e hig hoi l penetratio nenerg y scenario . Th e incrementa l contro l cost s ove r baselin e fo r th e low sulfu r fue l alternativ e ar e $5 8 million . Fo r percen t reduction , th e incrementa l contro l cost s ove r baselin e ar e $13 5 million . Thes e cost s wil l b e use d inth e followin g section s t o analyz e economi c impact s an dt o calcualt e ne t benefits . Tabl e IV- 2 present s averag e cos t pe r to ndata , calculate d
ove r th e regulator y

baselin e an

dTabl e IV- 3 present s incrementa l cos t pe r to ndat a fo r th e percen t reductio nalternativ e calculate dove r th e low sulfu r fue l alternative .P.6 0



### IV- 4
Tabl e IV- 1 NATIONAL COS

TIMPACT

S O F REGULATOR

YALTERNATIVES 1 * 2 (Million s 198 3 $ )

Regulator y Alternativ e Baselin e Lo wSu l fu rFuel 3 Percen t Reduction * Annualize d Cost s ($/yr ) 3,39 6 3,45 4 3,53 1 Annualize d Contro l Cost s ($/yr) 5

— 58 13 5

1 Thes e annualize d cost s ar e i n Januar y198 3 dollar s an d ar e therefor e slightl y highe rtha n th e Jun e 198 2 cost s reflecte d i n th e Preamble

. 2 Assume d hig h oi l penetratio n scenario

. 3 0. 8 l b SOo/Millio n Bt u - Oi l 1. 2 l b S02/Millio n Bt u - Coa l 4 9 0 percen t reduction

. 5 Thes e ar e th e contro l cost s associate dwit hsteam generatin g uni t NSPS . The y ar e measure da s addition s t o th e baselin e costs .P.6 1

IV- 5

Regulator y Alternativ e

Lo wSu l fu r Percen t Reductio n Tabl e IV- 2 Averag e Annualize d Cost s (thousand s o f 198 3 $ )
58,00 0 135,00 0 Contro l Cos t Pe r Ton s o f SO 2 Reduce d (thousands )

17 0 24 0 To n
C/

T

34 0 56 0

Tabl e IV- 3 

### 1 Incrementa l Contro l Cos t pe r To n Incrementa l Cost s (thousand s o f 198 3 $ ) Incrementa l Ton s SO 2 Reduce d(thousands ) C/ T

Percen t Reductio n 77,00 0 7 0
. 110 0

1 Percen t reductio n ove rlo wsulfu rfuel

.P.6 2



### IV- 6

REFERENCE S Projecte d Impact s o f Alternativ e Sulfu rDioxid e Ne wSourc e Performanc e Standard s fo rIndustria l Fossi l Fuel-Fire d Boiler s (Marc h 1985)

. Energ yan d Environmenta l Analysis , Inc

. fo rth e U.S

. Environmenta l Protectio n Agency

.P.6 3

V- 1
V . ECONOMI C IMPAC T ANALYSI S A

. Introductio n Adetaile d analysi s wa s undertake n t o asses s th e potentia l industry specifi ceconomi cimpact s associate d wit h th e mos t stringen t regulator y alternative—tha t requirin g a percen t reductio n i n SO 2 emissions

. Se e "Projecte d Impact s o f Alternativ e Sulfu rDioxid e Ne wSourc e Performanc e Standard s fo rIndustria l Fossi l Fuel-Fire d Boilers, " Marc h 1985
. Th e industry-specifi cimpact s associate d wit h th e lo wsulfu rfue l alternative , woul d therefor e b e les s tha n thos e discusse d below

. Th e potentia l industry-specifi ceconomi cimpact s wer e analyze d i n tw o phases

. Th e firs t phas e focuse d o n aggregat e economi cimpact s fo rmajo rsteam usin g industrie s an d th e secon d phas e focuse d o n selecte d industrie s tha t wer e considere d likel yt o experienc e th e mos t sever e economi cimpacts

. B

. Majo rStea m User s Potentia l impact s o n stea m cost s an d produc t price s wer e estimate d base d o n industry-wid e average s fo reigh t larg e industr ygroups . Th e group s selecte d fo ranalysi s accoun t fo rapproximatel y7 0 percen t o fdomesti cindustria l stea m consumption

. Thes e eigh t industr ygroup s were : food ; textiles ; paper ; chemicals ; petroleu m refining ; stone , cla yan d glass ; iro n an d steel ; an d aluminum

. Assumin g ful l cos t pass-throug h o f increase d stea m costs , produc t price s i n th e majo rindustr ygroup s woul d increas e byles s tha n 0.0 3 percent
. Thi s potentia l impac t represent s a maximu m produc t pric e increas e -becaus e o f th e ful l cos t pass-throug h assumption

. I n som e instances , increase d stea m cost s woul d no t b e completel ypasse d throug h t o produc t prices , an d therefore , th e impac t o n produc t price s woul d b e less

.P.6 4

V- 2 C

. Selecte d Industrie s Seve n industries , mos t likel yt o experienc e sever e impacts , wer e selecte d du e t o th e steam-intensiv e natur e o fthei roperatio n o rth e lo w. utilizatio n o fthei rstea m generatin g uni t capacity

. Thes e industrie s were : bee t suga rrefining ; frui t an d vegetabl e canning ; rubbe rreclaiming ; automobil e manufacturing ; petroleu m refining ; iro n an d stee l manufacturing ; an d liquo rdistilling

. Th e economi cimpac t analysi s examine d potentia l impact s o n prices , valu e added , profitability , an d capita l availability

. Thi s analysi s was base d o n "model " plant s an d "model " firm s representativ e o f eac h industry

. Produc t price s wer e projecte d t o increas e fro m les s tha n 0.0 1 t o 0. 5 percen t i n 199 0 fo ral l excep t th e bee t suga rrefinin g industry , assumin g ful l cos t pass-throug h o f increase d stea m costs
. Fo rthes e sam e seve n industries , valu e adde d was projecte d t o increas e byabou t 0.0 1 t o 0. 9 percen t i n 199 0 fo ral l excep t th e bee t suga rrefinin g industry , assumin g ful l cos t pass-throug h o f increase d stea m costs
. Fo rbot h produc t pric e an d valu e adde d impacts , th e highes t increase s ar e projecte d fo rth e bee t suga rrefinin g industry

. I n th e cas e o f produc t prices , thi s i s du e t o th e fac t tha t th e produc t pric e i s lo wan d stea m cost s represen t a n unusuall yhig h proportio n o f manufacturin g cost s i n th e bee t suga rrefinin g industry , compare d t o th e othe rindustrie s examined

. Similarly , valu e adde d impact s ar e highe rsinc e stea m cost s represen t a n unusuall yhig h proportio n o f th e non-ra wmateria l cost s o f manufacturin g th e produc t i n th e bee t suga rrefinin g industry , compare d t o th e othe rindustrie s examined

.P.6 5

V- 3
Base donth e same scenario s outline dabove , bu t assumin g "ful l cos t absorption " o f increase dsteam costs , retur nonasset s wa s projecte dt o decreas e b

y 0.0 3 t o 2. 8 percentag e points . Again , thes e potentia l impact s represen t "wors t case " projection s o f th e assumptio no f ful l cos t absorptio n o f th e increase dstea m costs . Cas hflo w coverag e ratio s an

dboo kdebt/equit y

ratio s showe d essentiall y

no chang e fo r an

y o f th e mode l firm s unde r two differen t debt/equit y

financin g strategies . Consequently , a percen t reductio n requiremen t woul dno t impai r th e abilit y o f firm s t o rais e sufficien t capita l t o construc t fossi l fuel-fire dsteam generatin g units . D . Conclusion s Th e industry-specifi c economi c impact s analysi s indicate s tha t a percen t reductio nrequiremen t woul dgenerall y increas e produc t price s an d valu e adde db

y les s tha n1 percen t i f al l stea m cos t increase s wer e passe d throug ht o produc t prices . Inaddition , assumin g absorptio no f al l stea m cos t increases , retur no nasset s woul dgenerall y decreas e b

y abou t 3 percentag e point s o r less . Cas hflo w coverag e an

dboo kdebt/equit y

ratio s showe dessentiall y

no change . Therefore , a percen t reductio nrequiremen t woul dno t impos e an

y capita l availabilit y constraint s o nfirms . A s mentione dearlier , a percen t reductio nrequiremen t i s th e mos t stringen t regulator y

alternativ e considered . Consequently , th e industry specifi c economi c impact s associate dwit hth e lo w sulfu r fue l regulator y alternativ e woul dbe les s sever e tha nthos e discusse dabove .P.6 6



### V- 4
REFERENCE S Projecte d Impact s o f Alternativ e Sulfu rDioxid e Ne wSourc e Performanc e Standard s fo rIndustria l Fossi l Fuel-Fire d Boiler s (Marc h 1985)

. Energ yan d Environmenta l Analysis , Inc

. fo rth e U.S

. Environmenta l Protectio n Agency

.P.6 7

VI- 1
VI . BENEFI T ANALYSI S
A . Introductio n Th e economi c benefit s associate dwit hth e Industria l Boile r SO 2 NSP S reflec t th e willingnes s t o pay b y individual s t o b e i na preferre dstat e (i.e. , cleane r air ) a s oppose dt o a les s preferre dstat e (i.e. , dirtie r air )
o f th e world . I nth e presen t analysis , th e les s preferre dstat e i s associate d wit hpre-NSP S conditions . I nparticular , i t i s assume dtha t industria l boiler s fo r whic hth e NSP S ar e app l icabi e ar e subjec t t o control s currentl y require db

y representativ e Stat e Implementatio nPlan s (SIPs) . Conversely , th e pos t NSP S scenario s reflec t jth e two regulator y

alternative s discusse d previously-lo w

sulfu r fue l an

dpercen t reduction . Althoug hth e NSP S are , b y design , technolog y

oriented , i t i s th e cas e tha t emission s reduction s achieve dtranslat e int o improvement s i nai r quality . I t i s th e reductio ninconcentration s associate dwit hth e NSP S tha t ar e th e sourc e o f th e economi c benefits . Figur e VI- 1 portray s th e situation . At tim e to , ambien t concentration s ina give nare a ma y b e Cg . Inth e absenc e o f additiona l control s beyondthos e currentl y i nplace , ne t growt ho f industria l boiler s i nth e are a wil l lea dt o highe r tota l emis sion s an dconsequentl y

greate r ambien t concentrations . Th e poin t (t]_ , C^ ) i s a nexampl e o f thi s possibility . I f additiona l contro l program s ar e instituted , emission s wil l b e reduce dove r some tim e path , an dambien t ai r qualit y wil l improve . Thi s i s show nb y poin t (t i C2 ) i nFigur e VI-1 . Th e are a whic hrepresent s th e improvemen t inai r qualit y i s th e sourc e o f th e benefi t estimates .VI- 2 P.6 8

Concentration s C 

## l +

C A• C 

## 2 + (t 0 .c 0 ) ^.'(t^.C- )

tia e Figur e VI-1 . Descriptio no f Ai r Qualit y Scenari o
Th e purpose s o f thi s chapte r ar e t o presen t th e analytica l methodolog y andresultin g benefi t estimate s fo r two o f th e regulator y alternative s bein g analyzed . Th e tw o alternative s ar e lo w sulfu r fue l andpercen t reduction . Th e estimate dbenefit s ar e fo r th e yea r 1990 . Tha t is , th e benefit s ar e calculate dconsiderin g al l boiler s online , fo r whic hth e NSP S
ar e applicable , i n1990 . Th e discussio nwhic hfollow s i s divide dint o section s o

nMethodology , Study Selection , Application , Qualification s an d Plausibilit y

Checks , andEstimates . B . Methodolog y Ideally , th e estimatio no f potentia l economi c benefit s woul db e accomplishe dusin g data , assumptions , an dmodelin g technique s develope d specificall y

fo r th e analyti c objective . I nth e cas e o f th e steam gene ratin g uni t NSPS , th e idea l approac hi s preclude db y projec t structure , time , andresourc e constraints . Therefore , estimate s ar e base dupo nexistin gP.6 9

VI- 3
studie s whic haddres s some aspect s o f th e healt ho r welfar e implication s
o f ambien t SO2 , SO 4 an dPM . Thi s approach , whic hinvolve s transformatio n
an dextrapolatio no f existin g researc han dstudies , canno t b e accomplishe d i na thoroug han

dcomprehensiv e manne r withou t firs t recognizin g th e many technica l problem s associate dwit hdrawin g inference s fro m studie s no t necessaril y

designe dfo r th e purpose s o f thi s analysis . Th e problem s stem fro m a variet y

o f sources , whic hinclud e limite dan dsometime s conflictin g scientifi c information , paucit y o f data , an

danalyti c technique s whic hhav e no t alway s bee nthoroughl y tested . Th e technica l problem s whic hexis t resul t i nuncertaint y regardin g th e magnitud e an dprecisio n
o f th e empirica l economi c benefi t estimates . I norde r t o dea l explicitl y wit hthi s uncertainty , th e extrapolatio napproac ht o benefi t estimatio n requires : 0 Identificatio nan dus e o f th e bes t dat a currentl y available ; 0 Accomplishmen t o f sensitivit y analysi s whe nalternativ e dat a
o r assumption s exist ; 0 Developmen t o f range s o f estimate s t o demonstrat e th e leve l o f uncertaint y

associate dwit hdifferen t assumptions . Th e abov e element s serv e a s th e basi s fo r th e analyti c strateg y tha t i s use dt o develo pestimate s o f th e benefit s fo r th e steam generatin g uni t NSPS . Th e approac hbegin s wit ha thoroug hliteratur e searc hfo r existin g studie s tha t coul dpossibl y be use di nth e extrapolatio nprocess . Th e quantitativ e relationship s whic har e containe di no r derive dfro m th e bes t o f th e availabl e studie s ar e the nuse dt o develo pth e benefit , estimate s presente di nthi s analysis . A summar y

descriptio no f th e approac huse di s presente di nsubsequen t paragraphs .P.7 0

VI- 4

1 ) Al l categorie s o f potentia l benefit s tha t migh t resul t fro m contro l strategie s neede dt o mee t th e alternativ e steam gene ratin g uni t SO ? NSP S ar e identified . A review o f th e SO 2 Criteri a Documen t an

dothe r report s provide da comprehensiv e listin g o f possibl e advers e effects . A listin g o f effect s categorie s i s presente di nTabl e VI- 1 below . 2 ) Th e existin g researc hliteratur e o nth e potentia l effect s i s identified , classifie dan dreviewed . Al l identifie dstudie s ar e screene do

nth e basi s o f severa l criteria , th e mos t notabl e o f whic har e analyti c qualit y an dpotentia l fo r extrapolatio no f estimate s fo r benefit s analysi s (e.g. , requisit e ai r qualit y dat a available) . A s a resul t o f thi s screenin g analysis , an d becaus e o f tim e an

dresourc e contraints , i t i s determine dtha t only some o f th e categorie s show ni nTabl e VI- 1 ca nb e estimated . Tabl e VI- 1 organize s th e potentia l benefit s b y pollutan t an

deffect s categories . T o compl y

wit hth e steam

generatin g uni t NSPS , eithe r complianc e fue l i s burne do r sulfu r dioxid e emissio ncontrol s ar e applied . Thes e intur nreduc e concentration s o f SO 2 directl y an dsulfate s an

dparticulat e matte r indirectl y (b y reducin g th e SO 2 precursor) . Furthermore , whe nscrubber s ar e use dt o reduc e SO 2 emission s fro

m oil-firedboilers , particulat e matte r emission s ma y als o b e reduce dbelow baselin e levels . Consequently , complianc e wit hth e Industria l Boile r NSP S ma y resul t i nindirec t an ddirec t reduction s inPM

concentrations . However , fo r purpose s o f thi s study PM benefit s ar e onl y

estimatedfo r th e indirec t reductions .P.7 1

VI- 5
Tabl e VI- 1 Industria l Boile rNSP S Potentia l Benefi t Categorie s Othe r SO ? SO AP M Healt h Effect s

- Mortalit yDu e t o Chroni cExposur e X X X

- Mortalit yDu e t o Acut e Exposur e X X X

- Morbidit yDu e t o Chroni cExposur e * X *

- Morbidit yDu e t o Acut e Exposur e * X * Soilin g an d Material s Damag e

- Residentia l Facilitie s

- Commercia l an d Industria l Facilitie s Climat e an d Visibilit yEffect s

- Loca l Visibilit y

- " Non-Loca l Visibilit y

- Climat e

- V i s i bi1it ya t Park s

- Transportatio n Safet y Non-Huma n Biologica l Effect s

- Agricultur e

- Forestr y

- Fishin g

- Ecosyste m * X

N A N A X N A N A

* X X X X

X

*

• X X X

X X X X *

X

X X X X X

N A N A N A N A

Xar e categorie s no t analyze di nthi s study . * ar e categorie s analyze di nthi s study . N A ar e categorie s no t applicabl e t o th e pollutant .P.7 2

VI- 6
Direc t P

M benefit s ar e attribute dt o th e particulat e matte r steam generatin g uni t NSP S (se e EPA-450/3-82-006a) . Th e coverag e o f benefit s i s als o limite dinothe r ways . Th e benefit s ar e ofte nincomplet e fo r thos e effect s categorie s wher e benefit s ar e measured . Fo r example , th e SO 2 material s damag e benefit s onl y

cove r th e residentia l sector . Commercial , industrial , an

dgovernmenta l facilitie s ar e omitted . Finally , a s note dpreviously , ther e ar e othe r categorie s o f effect s wher e no benefi t estimate s ar e made . Se e Tabl e VI-1 . 3 ) Benefit s estimate s ar e develope dusin g th e quantitativ e relationship s fro

m eac hindividua l study an dth e ai r qualit y improvement s postulate dfo r eac halternativ e standard . Thes e estimate s ar e accomplishe daccordin g t o a four-ste p procedur e a s show

ni nFigur e VI-2 . Th e firs t ste pi s t o identif y th e magnitud e o f th e ambien t ai r qualit y improvemen t tha t i s estimate dt o occu r ineac hare a an dyear . Thi s i s th e improvemen t achieve ddu e t o implementatio no f a particula r standard , relativ e t o a baselin e situatio nreflectin g control s a l read y i nplace . Th e secondste pinvolve s estimatin g th e healt han dwelfar e improvement s tha t migh t occu r a s a resul t o f th e improvemen t i n ambien t ai r quality . Thi s ste pmake s us e o f th e researc hfinding s extracte dfro

m th e literatur e review discusse dpreviously . Thes e finding s includ e eithe r linea r o r nonlinea r relationship s betwee n healt ho r welfar e statu s an dambien t concentration s o f SO 2 an d SO4 . Not e tha t estimate s ar e generall y require dfo r eac hare a an d yea r inwhic hther e i s a nai r qualit y

improvement .P.7 3

VI- 7

STE P 1 Identif y ai r qualit y

improvemen t i nare a i a t yea r t

STE P 2 Estimat e healt ho r welfar e improvemen t inare a i a t yea r t

3 a 3b 

# I

STE P 3 Estimat e economi c valu e o f th e healt h o r welfar e improvemen t fo r i , t



# V
STE P 4 Aggregat e ove r i t o obtai n regiona l total s

Figur e VI-2 . Basi c step s i nestimatin g benefit s fo r anindividua l study .P.7 4 *

VI- 8
Th e thir dste pi s t o imput e aneconomi c valu e t o th e estimate d change s inhealt han

dwelfar e statu s (Ste p3a) . Fo r some classe s o f benefit s i t i s possibl e t o estimat e economi c value s directl y from th e ai r qualit y

improvemen t (Ste p3b) . Th e househol dsecto r material s benefi t estimat e i s a nexampl e o f thi s approach . Studie s o f thi s typ e allow

direc t estimate s o f th e perceive deconomi c valu e o f environmenta l improvements . I nSte p4 , benefit s fo r eac hare a ar e summe dt o obtai ntotal s commensurat e wit hth e contro l strategy an dai r qualit y

data . 4 ) Tota l incrementa l benefi t estimate s ar e develope db y combinin g o r aggregatin g estimate s fro m th e appropriat e effect s categories . Tota l incrementa l benefi t estimate s fo r eac ho f th e alternativ e standard s unde r consideratio nar e require di norde r t o complet e a benefit-cos t analysi s o f th e variou s polic y alternatives . Th e estimate s ar e incrementa l inth e sens e the y ar e derive dfro

m th e ai r qualit y

chang e associate dwit hgoin g fro m presen t existin g SIP s t o control s require dfo r th e alternativ e NSP S analyzed . C . Study

Selection , Application , Qualification s an dPlausibilit y

Check s Th e procedure s usedt o selec t studie s a s a basi s fo r th e benefi t calculation s ar e identifie dinthi s section . Th e procedure s use dfo r applyin g th e selecte d studie s t o generat e benefi t estimate s ar e als o described . Inaddition , th e qualification s associate dwit heac happlicatio nan dth e plausibilit y

check s fo r resultin g benefi t estimate s ar e discussed . Th e sectio ni s organize db y th e pollutan t an

deffec t categor y

fo r whic hbenefit s ar e estimated .P.7 5

VI- 9
1
. SO 4 Relate d Benefit s a ) Visua l Rang e 1 ) Stud ySelectio n Becaus e visibilit yi s no t directl ytrade d i n existin g markets , benefi t estimatio n method s requir e th e establishmen t o f a hypothetica l marke t o ridentificatio n o fcomplementarit ybetwee n visua l rang e an d existin g markets

. Th e forme rmetho d manifest s itsel fi n contingen t rankin g an d contingen t valuatio n survey s elicitin g willingness-to-pa y estimate s fro m surve yrespondents

. Th e latte rmetho d generall yinfer s a relationshi p betwee n visua l rang e an d residentia l propert ymarket s o r visua l rang e an d th e cos t o f trave l t o alternativ e site s (e.g. , nationa l parks)

. Severa l visua l rang e studie s hav e bee n accomplishe d i n th e wester n U.S

. Th e contingen t valuatio n an d rankin g studie s generall yfocuse d o n use ran d existenc e value s a t nationa l park s (Row e e t al

. 1980 , Schulz e 1981 , Rae 1982)

. Th e wester n visua l rang e studie s als o include d contingen t propert yvalu e studie s fo rtw o urba n areas : th e Sout h Coasta l Ai rBasi n (Brookshire , e t al

. 1979 , 1980 ) an d th e Sa n Francisc o Ba yAre a (Loehman , e t al

. 1981)

. However , visua l rang e baseline s ar e vastl y differen t betwee n th e easter n an d wester n U.S. , a s ar e th e vistas

. Becaus e studie s ar e availabl e fo rth e easter n U.S

. an d tha t i s th e geographi cfocu s o f th e benefi t analysis , th e wester n studie s ar e no t used

. To date , thre e easter n visibilit ystudie s hav e bee n conducted

. One stud y(Randall , e t al

. 1981 ) assesse d th e willingness-to-pa yfo r visua l rang e improvemen t i n th e Chicag o area . Anothe revaluate d th e willingness-to-pa yfo rvisua l rang e improvemen t i n th e Cincinnat i are a (Rae , 1984)

. Athir d (Tolle ye t al

. 1984 ) assesse d th e willingness-to-pa yVI-1 0

fo r visua l rang e improvemen t ineac ho f si xcitie s (i.e. , Atlanta , Boston , Cincinnati , Miami , Mobile , an dWashington , D.C. ) a s wel l a s th e res t o f th e east . Al l o f th e easter nvisibilit y studie s use dcontingen t valuatio no r contingen t rankin g methods . Th e study

b y Tolle y e t al . i s chose nfo r thi s analysis . I t cover s mor e citie s an

dha s a large r sampl e siz e tha nth e othe r studies . I t als o enable s anassessmen t o f visua l rang e change s "locally " a s wel l a s othe r part s o f th e eas t (non-loca l changes) . 2 ) Applicatio n Th e visua l rang e benefi t assessmen t involve s two set s o f procedures . Th e firs t involve s usin g th e visua l rang e estimate s fo r eac ho f th e 3 1 state s (Chapte r 3 , Tabl e III-5 ) t o develo pestimate s o f "local " visua l rang e chang e an

d"non-local " visua l rang e change . Th e estimate dannua l visua l range chang e fo r eac hstat e i s use dfo r th e "local " change . Th e are a weighte daverag e visua l rang e chang e fo r th e 3 1 easter nstate s covere di nth e SO 4 ai r qualit y analyse s i s th e prox y fo r visua l rang e change s i nothe r part s o f th e eas t o r "non-local " visua l rang e change . Th e are a weighte daverag e visua l rang e fo r th e thirty-on e state regio n 3 1 i s compute db

y th e formul a V31E

= Z VjA j where : 1- 1 A 3 1 E V 31 E = 3 1 easter nstat e are a weighte daverag e visua l range . V-j = visua l rang e fo r state i . A-j = geographi c are a o f stat e i . ^31 E = tot. ^ geographi c are a o f th e 3 1 states . Th e Statistica l Abstrac t provide dpopulatio nestimate s fo r 198 0 and199 0
a s wel l a s househol destimate s fo r 198 0 fo r eac ho f th e 3 1 easter nP.7 7

VI-1 1 states
. T

o calculat e th e predicte d numbe ro f household s fo reac h o f th e 3 1 easter n state s fo r1990 th e followin g step s wer e taken

. Firs t th e 1980 rati o o f household s t o populatio n fo reac h stat e wa s determine d usin g th e formul a R S 8 Q = H^RCI where : PS 80 R s 8 o = rati o o f household s t o populatio ni nstat e s in198 0 H s 8 0 = number s o f household s i nstat e s i n198 0 Ps8 0 = populatio ni nstat e s in198 0 Th e numbe r o f household s fo r 199 0 andeac hstat e wer e the nestimate d usin g th e formul a H s g o = P s g o Rs8 0 where : H s t = househol di nstat e s i nyea r 199 0
p s t = populatio ni nstat e s inyea r 199 0 Rs8 0 = rati o o f 198 0 household s t o populatio ni nstat e s Th e secondse t o f procedure s entail s developin g visua l rang e improvemen t valuatio ncoefficient s fro m th e Tolle y

e t al . stud

y an dapplyin g them

t o th e predicte dvisua l rang e changes . Th e Tolle y e t al . study

calculate s th e mea nbid s fo r th e willingness-to-pa y fo r a 1 0 mil e (16. 1 kilometer ) improvemen t i

n"local " visua l rang e an dchange s inth e othe r part s o f th e east . Th e bid s vary widel y withi nan

dacros s th e si xstud y areas . Th e mea nbi dfo r a 1 0 mil e improvemen t in"local " visua l rang e goe s fro m $3.54/year/household/kilomete r i nCincinnat i t o $14.81/year/household / kilomete r i nWashington , D.C . T o reflec t some o f thi s variability , rang e an dmidpoin t benefi t estimate s ar e developed . Th e lowe r estimat e applie s th e Cincinnat i mea nbi dt o eac ho f th e 3 1 state s (i.e. , mea nbi dtime s th e ai r qualit y

chang e ineac hstat e time s th e populatio ni neac hstate )
a s a measur e o f th e willingness-to-pa y fo r "local " visibilit y changes . Similarly , th e Washington , D.C . mea nbi di s applie dt o eac hstat e t oVI-1 2

generat e th e highe restimate

. Th e mid-poin t estimat e i s derive d b y applyin g valuatio n coefficient s t o eac h o f th e 3 1 state s i n accordanc e wit h thei rnearnes s t o on e o f th e stud ycities

. Fo rexample , th e mea n bi d fo rWashington , D.C

. i s apportione d t o Virginia , Maryland , Delaware , etc
. Fo rth e change s i n visua l rang e i n othe rpart s o fth e eas t a simila r procedur e i s use d t o reflec t a rang e an d midpoin t estimate

. However , i t was necessar yt o compar e tw o type s o f bi d informatio n i n Tolle y e t al

. (1984)

. I n tha t study , th e exac t question s aske d surve yrespondent s wer e wha t woul d yo u b e willing-to-pa yfo ra visua l rang e improvemen t locall yan d fo ra visua l rang e improvemen t i n th e east
. Ther e i s overla p i nJthes e reveale d preferenc e bid s becaus e th e "local " are a i s a par t o f th e east
. To accoun t fo rthi s overlap , th e "local " bi d i s subtracte d fro m th e easter n bi d t o yiel d th e estimat e o fwillingness-to-pa yfo rvisua l rang e improvement s i n othe rpart s o fth e east
. Fo rexample , i n Cincinnati , th e mean bid s derive d fro m th e Tolle ye t al

. stud yar e $3.5 4 fo r"local " an d $4.5 7 fo reaster n visua l rang e improvements

. Th e valu e use d i n thi s analysi s fo rvisua l rang e improvemen t i n othe rpart s o f th e eas t i s $1.0 3 (i.e. , $4.5 7 - $3.54)

. Th e $1.0 3 valu e fro m Cincinnat i i s use d t o generat e th e lowe rbenefi t estimat e fo rvisua l rang e improvement s i n othe rpart s o f th e eas t whil e a valu e o f$7.4 4 (i.e. , $22.2 5 - $14.81 ) i s use d t o generat e th e highe restimate

. A n exampl e o fth e procedur e t o calculat e th e lo westimat e fo rloca l benefit s fo rth e lo wsulfu rfue l regulator yalternativ e i s describe d below

. Give n th e followin g dat a fo rAlabama : 198 0 populatio n - 3,890,000 ; 198 0 numbe ro f household s - 1,342,000 ; 199 0 projecte d populatio n - 4,214,000 ,VI-1 3

w e estimat e th e numbe ro f household s i n 199 0 t o b e 1,454,000
. Th e lo w estimat e fo rloca l benefit s i s th e lo wpredicte d chang e i n visua l rang e (. 1 km ) time s 1,454,00 0 household s time s $3.5 4 pe rhousehol d pe rkilomete r chang e (198 2 dollars ) time s th e 198 2 t o 198 3 Consume rPric e Inde xinflato r (1.0311311 ) o r$530,740

. Thi s numbe ri s th e estimat e o fbenefit s i n 199 0 expresse d i n constan t 198 3 dollar s fo rloca l visibilit yfo rAlabama

. 3 ) Qualification s an d Plausibilit yChecks Ther e ar e certai n factor s whic h sugges t tha t th e estimate s o fvisua l rang e improvemen t benefit s ar e understated

. Peopl e i n th e wes t ma yb e willing-to-pa yfo rvisua l rang e improvement s i n th e east , especiall ya t th e nationa l parks

. The yhav e no t bee n include d i n th e benefi t assessment
. Likewise , th e contro l strategie s implemente d i n th e 3 1 easter n state s coul d resul t i n visua l rang e improvement s i n Canad a an d certai n wester n states
. Thes e to o ar e omitte d fro m thi s analysis

. Finally , a commo n resul t o f th e visua l rang e studie s conducte d t o dat e i s tha t th e willingness-to-pa yfo ra n additiona l mil e o fvisua l rang e diminishe s a s visua l rang e increases

. I n othe rword s peopl e appea rt o b e willing-to-pa y mor e fo rth e firs t mil e o fvisua l rang e improvemen t tha n the yd o fo rth e second , o rthird

. Averag e visua l rang e i n th e easter n U.S

. i s abou t 1 0 mile s (1 6 kilometers)

. Th e Tolle yet
. al

. stud yposite d th e willingness to-pa yfo ra visua l rang e improvemen t o f1 0 mile s (fro m a bas e o f1 0 mile s t o a visua l rang e o f 2 0 miles)

. Consequently , th e willingness to-pa yfo rtha t firs t mil e o f visua l rang e improvemen t coul d b e greate r tha n ou restimat e whic h assume d a constan t bi d average d ove rth e 1 0 mile , change

. However , ther e ar e othe rfactor s whic h sugges t th e estimate s o f visua l rang e improvemen t benefit s ma yb e overstate d i n som e respects
.P.8 0

• VI-1 4
Fo r example , th e legitimac y o f th e benefi t estimate s i s dependen t i n par t o nth e abilit y

o f peopl e t o perceiv e th e projectedvisua l rang e improvements . Th e perceptio nthreshol dfo r a chang e invisua l rang e i s two t o fiv e percen t fo r a singl e visibilit y even t (EPA

Repor t t o Congress , 1979) . Dependin g o

nth e varianc e o f visua l rang e improvement s throug h th e year , th e perceptio nfacto r coul dinfluenc e th e benefi t estimate . Fo r purpose s o f thi s analysis , no threshol dwa s impose do nvisibilit y perception . Th e estimate s o f willingnes s t o pay fo r non-loca l change s ar e base d
ona nextrapolatio no f th e differenc e betwee nloca l an deaster nbid s pe r mil e chang e invisua l rang e fo r a te nmil e chang e an dapplie dt o a

naverag e chang e invisua l rang e fo r th e thirty-on e states . Thi s extrapolatio n presume s tha t th e spatia l distributio no f visua l rang e change s i s unim portan t an

dtha t th e averag e chang e i s wha t i s value dinth e bids . Thi s assumptio ni s ope nt o questio nan dles s confidenc e shoul db e place din non-loca l benefi t estimate s tha ninth e loca l benefi t estimates . Othe r qualification s t o th e visua l rang e benefi t estimate s includ e concer nabou t extrapolatin g th e contingen t valuatio nresult s fro m si x citie s t o othe r area s o f th e east . Thi s extrapolatio ninclude s urba nt o rura l extrapolatio nwhic hmay b e questionable . Attempt s t o asses s th e plausibilit y o f th e benefi t estimate s ar e limited . A

presurve y

study inCincinnat i (Rae , 1984 ) resulte dinmea n bi destimate s simila r t o thos e develope db y Tolle y et . al . However , du e t o possibl e informatio nbia s problems , th e fina l surve y b y Ra e i nCincinnat i yielde dmea nbi destimate s whic har e muc hhighe r tha nth e on e use din thi s study .P.8 1

VI-1 5 2
. P M Th e P M benefit s develope d i n thi s analysi s ar e derive d fro m willing ness-to-pa yestimate s i n th e for m o f dollars/pg/m 3 reductio n i n TSP

. Thes e estimate s i n tur n ar e derive d fro m earlie rAgenc ydirecte d studies , includin g th e P M NAAQ S RIA

. I n thi s sectio n th e stud yselection , application , qualificatio n an d plausibilit ychec k procedure s used i n th e P M NAAQ S wor k ar e briefl ysummarized

. I n additio n th e procedures , qualifications , an d plausibilit yo f usin g thos e studie s t o develo p estimate s o fP M benefit s associate d wit h th e stea m generatin g uni t NSP S ar e described

. a ) Chroni cMorbidit y 1 ) Study

Selectio n Th e epidemiologica l studie s amenabl e fo r benefi t analysi s i nthi s categor y includ e th e Ferri s e t al . (1962 , 1973 , an d1976 ) an

dCrocke r et . al . (1979 ) research . Th e longitutiona l studie s b y Ferri s e t al . (1962 , 1973 , an

d1976 ) i nBerlin , New Hampshir e wer e classifie db y th e criteri a documen t an dstaf f pape r a s usefu l fo r quantitativ e purpose s i nPM

standar dsetting . Th e cross-sectiona l study b y Crocke r e t al. , althoug hanalyticall y appealin g fro

m a benefi t analysi s perspective , wa s viewe da s no t quantitativ e fo r purpose s o f standar d settin g durin g th e developmen t o f th e SO 2 Criteri a Document . Th e Crocke r stud y yield s highe r benefi t estimates . However , th e Ferri s e t al . study i s adopte dfo r purpose s o f estimatin g PM benefit s associate d wit hth e SO 2 NSPS . 2 ) Applicatio n I nth e P M NAAQ S study , ai r qualit y concentratio nthreshold s ar e impose dt o avoi dgoin g outsid e th e TS P concentratio nrang e use db yP.8 2

VI-1 6
Ferri s e t al

. i n estimatin g th e concentratio n respons e relationship

. Th e healt h en d poin t use d b yFerri s e t al

. i s incidenc e o fchroni c respirator ydisease

. Afte rapplyin g th e Ferri s e t al

. concentration respons e relationship , th e Healt h Intervie wSurve yi s use d t o establis h a relationshi p betwee n th e chang e i n chroni crespirator ydiseas e incidenc e an d wor k

los s o rrestricte d activit ydays

. Th e geographi cuni t o f analysi s i s th e county
. Th e valuatio n o fchroni crespirator ydiseas e damage s include d a n assessmen t o flos t productivit y(i.e. , foregon e averag e dail ywage) , an d increase d medica l car e servic e charge s (i.e. , direc t medica l expenditures)

. O fcourse , th e benefi t o f decrease d P M concentration s ar e evaluate d a s th e reductio n i n th e aforementione d damages

. Benefit s ar e no t calculate d fo rreduction s i n pai n an d sufferin g prio ran d subsequen t t o th e receip t o fmedica l car e services

. Th e averag e pe rcapit a benefi t pe rpg/m 3 reductio n i n annua l TSP fo r th e countie s use d i n th e P M NAAQ S analysi s range d fro m $0.1 2 t o $0.1 8 fo rdirec t medica l expenditures , $0.1 5 t o $0.2 1 fo rreduce d wor k los s day s pe remploye d worker , an d $0.3 3 t o $0.4 9 pe rcapit a reductio n i n reduce d activit ydays

. 3 ) Qualification s an d Plausibilit yChecks Applyin g a stud ybase d o n a smal l are a i n Ne wHampshir e t o estimat e benefit s i n 3 1 easter n state s i s no t withou t uncertainty

. However , th e fac t tha t th e stud yi s judge d t o b e quantitativ e fo rpurpose s o f standar d settin g doe s sugges t som e underlyin g credibilit yi n th e benefi t estimates

. Eve n so , th e benefi t estimate s fo rthi s P M categor y ar e limited

. Fo rexample , n o valuatio n facto ri s applie d t o th e residua l pai n an d sufferin g category
.VI-1 7

b ) Acut e Morbidit y 1 ) Stud y

Selectio n Th e acut e morbidit y studie s amenabl e fo r benefi t analysi s includ e th e Same t et . al (1981 ) longitudina l epidemiologica l study i nSteuben ville , Ohi o an

dth e cros s sectiona l microepidemiologica l study b y Ostr o (1983) . Th e Same t et.al . study focuse do nth e relationshi po f emergenc y

roo m visit s t o acut e respirator y disease . Th e study wa s classifie db

y th e PM staf f pape r a s usefu l fo r determinin g concentra tion-respons e relationship s i nth e standar dsetting . Th e Ostr o study focuse do

nbroade r healt hen dpoint s whic hrelate dwor klos s an d restricte dactivit y day s du e t o respirator y diseas e t o TS P concentra tions . Th e Ostr o study wa s no t availabl e i ntim e fo r inclusio ni n th e P M Criteri a Documen t o r Staf f Paper ; bu t lik e som e othe r studie s publishe dlate r wa s regarde dhighl y enoug htha t th e Administrato r aske dfo r publi c commen t (P M NAAQ S Proposa l Preamble ) o nusin g th e study i nstandar dsetting . Th e Ostr o study

provide s a mor e complet e geographi c an dhealt h
en dpoin t assessmen t tha nth e Same t et . al . study an destimate s wor k los s an drestricte dactivit y day s directly . Hence , i t i s selecte d fo r us e i nestimatin g PM benefit s associate dwit hth e steam generatin g uni t NSPS . 2 ) Applicatio n Lik e th e chroni cmorbidit ybenefits , th e geographi cuni t o f analysi s i s th e county
. Similarly , th e damag e categorie s ar e los t productivity , reduce d non-wor k

da yactivities , an d increase d medica l car e servic e charges

. Furthermore , benefit s ar e no t calculate d fo rreductio n i n pai n an d sufferin g prio ran d subsequen t t o th e receip t o fmedica l car e services

.P.8 4



### VI-1 8
3 ) Qualification s Lik e al l epidemiologica l studies , ther e i s th e questio n o finferrin g causalit yfro m th e statisticall ysignifican t relationship

. However , unlik e man yothe repidemiologica l studies , Ostr o ha s relativel ybette rcontro l fo rpotentiall yconfoundin g factor s althoug h som e suc h a

s othe rpollutant s ar e omitted

. Ostr o use s annua l averag e TS P concentration s a

s th e measur

e fo rexposur e fo rth e two-wee k perio d fo rwhic h acut e illnes s i s examined

. Th e estimate d decreas e i n wor k los s days du e t o respirator ycause s fo ra 1 0 pg/m 3 decreas e i n TS P i s 3.6%
. Th e estimate d decreas e i n restricte d activitie s days du e t o respirator ycause s i s abou t 6.7 % fo ra 1 0 pg/m 3 decreas e i n TSP

. c ) Househol d Soilin g 1 ) Stud ySelectio n Th e studie s availabl e fo rbenefi t assessmen t includ e th e two Phila delphi a studie s b

yWatson-Jaksc h an d Cumming s e t al

. (1981 ) an d th e 2 4 SMS Alongitudina l stud yb yMathtec h (1982)

. Th e firs t two studie s ar e develope d fro m a soilin g surve y(Booze , Allen , Hamilto n 1970 ) designe d t o determin e out-of-pocke t cos t fo rai rpollutio n induce d soiling

. Watson-Jaksc h (1978 ) analyze d th e surve yresult s and foun d tha t althoug h cleanin g expenditure s di d no t chang e a welfar e los s coul d als o b e incurred

. Cumming s e t a l (1981 ) analyze d th e surve yan d foun d tha t b yimputin g a valu e fo rth e tim e o f th e do-it-yoursel f cleanin g activities , whic h varie d wit h pollutio n levels , welfar e losse s coul d als o be incurred

. Th e Mathtec h stud y(1982 ) i s reference d late ri n th e SO 2 sectio n o n material s damage

. A s wil l be indicate d there , th e approac h incorporate s a physica l damag

e functio n indirectl yi n th e structur e o fa n economi cdemandP.8 5

VI-1 9

an dsuppl y model . Withi ntha t framework , househol dbehavio r i nterm s o f soilin g perception , cleanin g activity , an dexpenditure s t o maintai na give ndegre e o f cleanlines s i s estimate deconometrically . Prices , environ menta l variables , an dsociodemographi c characteristic s ar e input s t o th e model . Th e Mathtec hmode l i s chose nbecaus e i t i s base donmor e recen t data , ha s broade r geographi c coverage , an duse s th e theoreticall y correc t measur e o f benefits , willingness-to-pay . 2 ) Applicatio n T o appl y th e mode l inth e P

M NAAQ S (Mathtech , 1983 ) analysis , value s o f prices , environmenta l variables , an dsocio-demographi c characteristic s fo r 49 1 countie s ar e pu t int o th e estimate dmode l at th e count y level . Th e benefit s ar e determine db y changin g th e valu e o f th e environmenta l variabl e (i.e. , TSP ) t o reflec t alternativ e SO 2 NSP S o r condition s wit han dwithou t TS P ai r qualit y improvements . 3 ) Qualificatio n an d Plausibilit y Th e Mathtec hmode l wa s pee r reviewe di na publi c foru m an da pane l o f expert s foun

dth e mode l an

dempirica l method s t o b e sound(Mathtech , 1982) . Th e predicte dleve l o f benefit s wa s judge dt o be reasonabl e a s a percen t o f househol dincome an drelativ e t o previousl y develope destimates . Th e mode l i s als o reference dinth e Criteri a Document . However , th e framewor k
o f th e Mathtec hhousehol dmode l doe s no t captur e soilin g relate dbenefit s suc ha s th e tim e cos t incurre dfo r th e do-it-yourselfer s o r th e residentia l locatio ndecision . Th e Mathtec hmode l i s limite di nothe r ways . .Fo r example , th e leve l o f detai l fo r th e dat a input s o f th e econometri c esti matio ncoul dhav e bee nmor e refine dinth e absenc e o f th e disclosur eP.8 6

VI-2 0 restriction s onth e Consume r Expenditur e Survey . Applicatio no f a mode l base don2 4 SMSA s t o 49 1 countie s i s no t withou t analyti c uncertainty , d ) Extrapolatio n 1 ) Metho d Th e studie s selecte dfo r estimatin g P M benefit s associate dwit hre duction s i nchroni c morbidity , acut e morbidity , an dhousehol dsoilin g wer e use di na relate dP M

generi c NSP S study

(Mathtec h1984) . Rathe r tha n applyin g thes e same studie s a t a micr o level , averag e benefit s estimate d fo r thi s PM

generi c NSP S stud

y ar e extrapolate dt o th e PM change s associate d wit hth e tw o regulator y alternatives . O f th e countie s covere di nth e re late dPM generi c NSP S study

49 1 ar e i nth e 3 1 easter nstate s addresse di n thi s analysis . Th e baselin e fo r th e PM generi c NSP S analysi s i s curren t PM SI P levels . Projecte dai r qualit y i s wit han

dwithou t 1 6 currentl y promulgate dP

M NSPSs . Th e chroni c an dacut e morbidit y

an dhousehol d soilin g benefit s accruin g i nth e yea r 1990 , t o th e populatio nprojecte dt o resid e i nthos e 49 1 counties , ar e calculate dfo r purpose s o f thi s analysis . Fo r eac hcounty , th e estimate dbenefit s ar e divide db y populatio nt o yiel d
a benefit/perso nfigure . This , i nturn , i s divide db y th e annua l chang e i nai r qualit y

t o yiel da benefit/percen t pg/m 3 reductio nTS P figure . Thes e figure s ar e summe dan ddivide db

y th e numbe r o f countie s (i.e . 491 ) t o giv e th e $/person/pg/m 3 reductio nTS P estimat e use di nthi s analysis . 2 ) Qualification s an dPlausibilit y

Check s T o th e exten t th e ai r qualit y scenari o i nth e PM

generi c NSP S analysi s i s differen t fro m tha t projecte dinth e SO 2 NSPS , analysi s

* Fo r example , controllin g SO 2 emission s result s i nlowe r fin e particl e (i.e. , £2. 5 um ) levels , whil e NSP S control s fo r PM emission s resul t i nlowe r concentration s o f othe r particl e size s inadditio nt o fine .P.8 7

VI-2 1
biase s o f a

nunknow

ndirectio nwil l result . Furthermore , populatio n difference s betwee nth e 3 1 easter nstate s an dth e 49 1 countie s formin g th e basi s o f thi s analysi s coul dals o impar t biase s o f anunknow n direction . 3 . SO 2 Benefi t Assessmen t

Fo r purpose s o f thi s analysis , th e scop e o f coverag e o f SO 2 benefit s include s material s damag e (househol dsector) , acut e an dchroni c morbidity , an dagricultur e benefit s (soybeans , wheat , an doats) , a ) Material s Damag e 1 ) Study

Selectio n Ther e ar e two element s tha t ar e importan t i nselectin g model s tha t conside r material s damage . First , on e mus t evaluat e th e validit y
o f statistica l relationship s betwee nmeasure s o f physica l damag e (e.g. , corrosio nrates ) fo r a give nmateria l an dplausibl e explanator y factor s
suc ha s SO 2 concentration s an drelativ e humidity . Second , on e mus t conside r th e soundnes s o f th e procedure s use dt o impar t economi c valu e t o th e physica l damag e tha t i s caused . Th e firs t topi c require s a review an dcritiqu e o f th e literatur e on physica l damag e functions . Thes e function s hav e bee nreviewe di nth e Criteri a Documen t an dth e genera l consensu s i s tha t fairl y reliabl e damag e function s hav e bee ndevelope dfo r ferrou s metal s an dzinc . However , cur rentl y availabl e damag e function s fo r exterio r paints , stone , masonary , concrete , textile , leather , an dpape r ar e considere dno t t o b e a s wel l specified . Ther e ar e thre e genera l approache s tha t hav e bee nuse dt o valu e physica l damage . Tw o o f th e approache s us e th e physica l damag e function s directly . Thes e approache s hav e bee nclassifie da s th e valu e o f los tP.8 8

VI-2 2

materia l metho dan

dth e cos t o f ameliorative/preventiv e actio nmethod . Example s o f th e firs t approac hinclud e Salmon(1970 ) an dSR I (1981) . Example s o f th e secondvaluatio napproac hinclud e Fin ke t al . (1971 ) an d TR C (1981) . Th e thir dapproac hdoe s no t rel y o nphysica l damag e function s directly . Instead , economi c deman dan dsuppl y survey s ar e estimate da s factor s (Mathtech , 1982) . Not e however , tha t th e physica l damag e function s ca nprovid e supportin g informatio nonth e type s o f behaviora l response s implie db

y th e economi c analysis . A prim e concer ninselectin g benefi t model s fo r valuin g materia l damag e i s th e dat a requirements . Bot hvaluatio nmethod s tha t rel y explicitl y

onphysica l damag e function s requir e informatio no nmaterial s inventory , exposur e an ddistribution . Thes e dat a ar e mos t likel y availabl e onl y

wit hsignifican t approximatio nan dar e mos t certainl y availabl e wit hany

degre e o f accurac y

onl y fo r selecte dcitie s wher e material s survey s hav e bee nconducted . I t i s principall y fo r thi s reaso ntha t th e calculatio no f benefit s fro m reduce dmaterial s damag e i s limite dt o th e demand/suppl y mode l a s estimate db y Mathtech . Althoug hth e dat a usedinth e Mathtec hanalysi s ar e limite dinsome respect s an

dinterpretation s o f some o f th e implie dbehaviora l response s hav e bee nquestioned , th e theoretica l an dempirica l method s hav e bee njudge db

y severa l group s t o b e sound . Th e Mathtec hmode l i s a neconomi c deman dmode l whic hdescribe s relationship s betwee nSO 2
an dvariou s good s an

dservice s tha t ma y

b e purchase db

y a consumer . Thus , th e concentration-respons e functio nrelate s SO 2 directl y t o economi c parameters ; ther e i s no intermediat e calculatio no f physica l damage . Inadditio nt o reduce ddat a requirements , th e Mathtec hmode lP.8 9

VI-2 3

o f material s damag e inth e househol dsecto r ha s othe r positiv e attribute s tha t ar e no t share db y th e othe r valuatio napproaches . Th e metho do f benefi t calculatio ni s base donwillingnes s t o pay whic hi s th e theo reticall y

correc t procedur e fo r measurin g welfar e change . Also , th e Mathtec hmode l permit s consideratio no f substitutio npossibilities . 2 ) Applicatio n Deman dequation s ar e estimate dfo r seve ncommodit y groups : food , shelter , househol doperations , home furnishings , clothing , transportation , an dpersona l care . Tw o additiona l plausibl e deman dcategories , propert y expenditure s an

drecreatio nar e no t include dbecaus e o f dat a problems . Fo r eac ho f th e seve ncommodit y groups , fro

m 2 t o 5 good s ar e separatel y identifie dan

ddemandequation s ar e als o estimate dfo r eac ho f thes e goods . Fo r example , separat e equation s ar e estimate dfo r househol dtextiles , furniture , appliances , an dhousewar e inth e home furnishing s commodit y group . Inall , 2 1 deman dequation s fo r good s ar e estimated . Dat a fo r th e origina l estimatio no f th e househol dsecto r mode l wer e obtaine dfro

m severa l sources . Th e expenditur e dat a fo r individua l good s an dspecifi c SMSA' s ar e take nfro m th e U.S . Burea uo f Labo r Statistics , Consume r Expenditur e Surve y (1978) . Retai l pric e dat a fo r th e same SMSA' s an

dgood s ar e als o fro m a Burea uo f Labo r Statistic s publicatio n (1973) . Ai r qualit y

dat a ar e develope dfro m dat a maintaine db

y EP A on th e SAROADdat a base . Th e dat a bas e tha t i s constructe dcover s 2 4 SMSA' s wit hbudge t an denvironmenta l dat a representativ e o f condition s i n197 2 an

d1973 . I t i s assume dtha t th e preference s reveale di nth e 1972-7 3 dat a canbe applie dt o th e time perio dan darea s considere din th e cas e stud

y analysis . Tha t is , consume r preference s an drelativ e price s remai nunchanged .P.9 0

VI-2 4

Th e procedure s use dt o develo pestimate s o f benefit s ar e quit e com plex , involvin g simultaneou s evaluatio no f system s o f deman dequations . Th e majo r step s o f th e calculatio nroutin e ar e highlighte dbelow . Th e firs t ste pinvolve s aggregatio no f marke t dat a t o form pric e an

d quantit y indice s fo r th e 2 1 good s fo r whic hseparat e deman dequation s ar e t o b e estimated . Second , th e 2 1 good s ar e groupe dint o seve ncommodit y groups . Th e seve ncommodit y

group s ar e consisten t wit hth e majo r division s define db y th e Burea uo f Labo r Statistic s fo r househol dbudge t allocations . A s note dearlier , eac h.'O f th e seve ncommodit y group s contain s from 2 t o 5 goods . Th e thir dste pthu s involve s th e simultaneou s estimatio no f deman dequation s fo r eac hgoodina give ncommodit y group . I t i s a t thi s stag e tha t th e SO 2 variable s ar e entere dt o determin e whethe r the y ar e relevan t explanator y

variables . Inaddition , severa l socioeconomi c vari able s ar e als o considere dt o determin e whethe r the y hel pexplai nth e varia tio nindemand . Th e econometri c modelin g o f th e good s deman dequation s indicate dtha t S0 2 i s a significan t explanator y variabl e inthre e o f th e equations : hom e repai r activities ; textile s excludin g clothing ; an dtransportatio nser vices . Thes e equation s ar e reproduce di nTabl e VI-2 . Th e measur e o f SO 2 foundt o b e mos t robus t i s th e 24-hou r secondhig hfo r th e monito r re cordin g th e maximum

24-hou r secondhig hconcentratio namon g al l receptors. *

* Additiona l wor ki s underwa y t o estimat e th e deman dequation s usin g annua l averag e value s fo r th e pollutan t variable s an dt o tes t specificall y fo r no nlinearitie s i nth e pollutio neffect s ondemand .VI-2 5

Tabl e VI- 2 DEMAN D EQUATION

S FO RWHIC H SOj I S A SIGNIFICAN T EXPLANATOR Y VARIABL

E P.9 1

1 . Hoa s Repai r

X l " 0.2328 8 + 0.76 7 • (-33.31 4 • 0.0328 6 • SO, ) • Z .

- 0.232S S • (-133.2 7 + 0.1197 9 • TSP ) • Z j vhsr s X j - ths shsxs o f hoa s xspai r sxpsnditnrs s rslstir s t o al l szpsaditurs s fo

r shsltsr . Z j - ths rati o o

f th s hoa s rspai r prie s iads s to shslts r sxpsnditnrss . Z j - ths rsti o of th s utilit

y prie s inds

xt o shslts r szpsaditnxss . SO j • ths 2 4 hoar sseoa dhig hasasnr s o

f SO j fo

r ths aoaitor rseordia

g ths aaziaa a Ttia s o f thi s Taxiabl s withi nth s eaa s stud

y araa . TS P • th

s 2 4 hoa

xsseoa dhig hasaaax s o

f Tots l SaspsadsdPar tiealats s fo

xths aoaito

xrseordia

g ths aaziaa a Talus of thi s rsriabl s vithi a th s eas s stud

y arss . Thi s Tila s is dsfsaltsdto th

s curran

t priaar

y NAAQS . 2 . Tsztils s szeludia g elothia

g X ~ - 0.10643 6 + 0.8933 4 • (3.2330 2 + 0.02028 6 • SO. ) • Z ,

- 0.10643 6 • ((-21.379 6 - 37.893 4 • FAMS Z > 55.37 3 * REGION ) • Z 4 + (-50.043 4 • 10.339 5 • FAMS Z + 2.471 1 • REGION ) • ZP S - 7.3383 9 • Z 6 ) whsr s lm " th s shsr s o f tsztil s tzpsaditurs s relatiT s t o al l szpsaditurs s fo rhoa s furnishings . Z . • th s rati o o f th s tsztil s prie s inds z t o hoa s furnishin g szpsndituzss . Z j - th s rsti o o f th s furnitur s prie s inds z t o hoa s furaishia g szpsaditurss . 2aj • th s rati o o f

th s spplisae s prie s inds z t o hoa s furaishia g szpsaditurss .P.9 2



### VI-2 6

Tabl e VI- 2 (continued ) DEMAND EQUATION S FO RWHIC H SO j I S A SIGNIFICAN T EXPLANATOR YVARIABL E

Z 6 

## so 2

FAMS Z REGIO N a

a

a " th s rati o o f

th s hoassvsrs s prie s iads z t o hoa s furaishia g szpsaditurss . th s 2 4 hoa rsseoa d hig h asaaar s o f SO j fo rth s aoaito r rseordia g th s aaziaa aTalu s o f thi s rariabl s withi ath s eas s stud y arsa . faail y aizs . duaa y Tsriabl s fo rloeatio ao f eaa s stad y ars a (1-Northsae to rNozth Csatral * 0>othsrviss) . 3 . Traasporatio aSsrrics s

X 3 whsr s X

j 

## h H •

a

a

m 0.5346 6 + 0.4633 4 • (-675.60 9 + 37.185 3 • SO. ) • Z .

- 0.5346 6 • (-377.41 3 • 28.319 1 • TEMP ) • Z g th s shar s o f

gaaolia s szpsaditars s rslstir s t o sl l szpsaditurs s fo rtxaaapoxtatioa . th s xsti o of

th s gaaolia s pxie s iads z t o sl l txsaspoxtatio aszpsaditnxss . th s xati o o f

th s pxie s iads z fo x th s "other " txaaapoxtatio adsasa d eatsgox y t o sl l transportatio n sxpsnditnrss . SO j • th s 2 4 hoaxsseoa dhighasasax s o f SO j for th s aonito r

rseordia g th s aaziaa a rain s o f thi s variabl e withi nth s ess s stud

y srsa . TEM P - arsrsg s aaaaa l tsapsratar s i a dsgrss s Cslsius .P.9 3

VI-2 7
I t i s importan t t o not e tha t thes e equation s ar e estimate da s par t o f
a system o f deman dequations , an db y themselve s d o no t leaddirectl y t o a measur e o f benefit s fo r reduction s i nSO2 . Infact , a serie s o f step s i s require dbefor e benefit s canb e ascertained . Give nth e deman dequation s fo r goods , th e nex t ste pinvolves usin g thes e equation s t o defin e pric e an dquantit y

indice s fo r th e commodit y categor y inwhic hthey

hav e bee nplaced . Note , i nparticular , tha t th e pric e inde xfo r a commodit y wil l be sensitiv e t o th e leve l o f SO 2 tha t i s use dt o evaluat e th e good s deman dequations . Sinc e deman dfo r onl y thre e good s i s foun

dt o be associate dwit hSO2 , onl y thre e o f th e commodit y pric e indice s wil l b e dependen t onSO2 . However , sinc e th e seve ncommodit y group s als o for

m a deman dsystem , th e SO 2 variabl e indirectl y play s a rol e inth e overal l budge t allocatio nacros s commodities . Wit haggregat e pric e an dquantit y

indice s define dfo r th e commoditie s th e nex t ste pinvolves th e simultaneou s estimatio no f th e commodit y deman d functions . Wit hth e parameter s o f th e commodit y deman dfunction s identi fied , i t i s no

w possibl e t o calculat e benefits . Th e goa l i s t o us e th e commodit y

deman dfunction s t o defin e a nexpenditur e functio ntha t i s a functio no f SO2 . Thi s i s accomplishe dinth e followin g way . First , th e parameter s o f th e system o f commodit y

deman dfunction s ar e use dt o defin e a compensate dcommodit y deman dsystem . Th e compensate d
curve s resul t fro

m a consume r optimizatio nproble m i nwhic hth e consume r minimize s expenditure s subjec t t o a constan t leve l o f utility . Th e expen ditur e functio ni s the nforme da s th e inne r produc t o f th e commodit y compensate ddeman dfunctio nan dth e associate dpric e inde xfo r al l seve nP.9 4

VI-2 8
commodities . Thi s procedur e i s performe dwit hSO 2 firs t a t baselin e (pre-control ) level s an dthe na t th e two post-contro l level s - low sulfu r fue l an

dpercen t reduction . Th e differenc e betwee nth e tw o expenditur e function s i s a measur e o f th e compensatin g variation , a welfar e measur e tha t i s consisten t wit hth e correc t concep t o f a benefit s measure : willingnes s t o pay . 3 ) Qualificatio nan dPlausibilit y

Check s Usin g modele dai r qualit y receptor s rathe r tha nmonitore ddat a a s wa s use dinth e origina l stud y ma y bia s th e benefi t estimat e upward . Onl y residentia l materia l damag e i s estimated . Becaus e o f th e pollutio n inde xuse di nth e underlyin g study (24-hou r secondhig hfo r anSMSA )
an dth e geographi c uni t o f th e underlyin g study (SMSAs) , th e impac t o f applyin g thes e coefficient s t o a differen t are a ( a rectangula r gri d
aroundanindustria l boiler ) i s unclear . Fo r th e 11 3 study area s analyze d benefit s calculate dona per-househol dbasi s rang e fro m 0 t o $15.5 5 pe r yea r fo r bot hth e low sulfu r fue l an

dpercen t reductio nregulator y alternatives . Thi s rang e reflect s th e populatio ndistributio namon g 11 3 stud y areas , b ) Morbidit y 1 ) Study

Selectio n A larg e numbe r o f studie s wer e reviewe dt o identif y source s fo r benefi t function s relatin g SO 2 t o morbidity . Base donth e typ e o f exposure , th e studie s canb e divide dint o thre e categories :

Short-ter m

(1-hour) , Dail y (24-hour )VI-2 9

Short-ter m Exposur e Fo rth e short-ter m exposur e category , clinica l studie s ar e utilized

. I n th e relevan t rang e o f SO2 , th e majo reffect s occu ri n asthmatics

. Studie s o f thi s grou p examin e effect s o n bot h lun g functio n change s ar e difficul t t o value

. Ther e ar e n o estimate s o fwillingnes s t o payfo rthes e change s o ro fth e accompanyin g medica l costs
. Therefore , th e analysi s consider s onl yeffect s o n symptoms
. Th e ful l rang e o fclinica l studie s o f effect s o fSO 2 o n sympto m prevalenc e i s utilized

. Th e lower-boun d estimat e i s base d o n th e poole d result s o feigh t studies

. Th e upper-boun d estimat e i s base d o n wor k o f Kirkpatric k

e t al

. (1982)

. Dail yExposur e No microepidemiolog ystudie s wer e foun d t o b e directl yusabl e fo r estimatin g effect s o f dail yexposure . Amon g th e limitation s o f th e studie s wer e failur e t o deriv e quantitativ e concentration-respons e function s an d lac k

o f contro l o fconfoundin g factors

. Severa l macroepidemiolog ystudie s examin e th e relationshi p betwee n SO 2 an d th e numbe ro femergencyroo m visit s i n a n are a usin g time serie s regressio n analysis

. Th e studie s o f Mazumda ran d Sussma n (1981 ) an d Grave s e t al

. (1980 ) wer e selecte d t o develo p a rang e o f benefi t estimates

. 2 ) Applicatio n Fo r th e clinica l studie s a minimum estimat e o f zer o i s used . Th e maximum estimat e fo r eac hday' s symptom s i s $2 5 base do nunpublishe dwor k b y Dicki e an

dGerkin g an

dTolle y

an dBabcock . 3 ) Qualification s andPlausibilit y Check s T o estimat e th e benefit s usin g clinica l studies , assumption s abou tP.9 6

VI-3 0 activit y level s ar e derive dform th e origina l PM

exposur e analysis . Doin g thi s implicitl y

assume dth e same activit y pattern s fo r asthmatic s a s th e res t o f th e population . Inhale ddos e i s estimate dusin g anassume d ventilatio nrat e o f 4 0 liter s pe r minut e an da pea kconcentratio no f twic e th e hourl y

concentration . Th e symptom valuatio ni s anarbitar y escalatio n o f a study

valuin g simila r symptom s fo r th e genera l populatio nrathe r tha n fo r asthmatics , c ) Agricultur e 1 ) Study

Selectio n Th e selectio no f crop s fo r analysi s i s governe db y th e followin g criteria : o Cro psensitivit y

t o exposur e t o SO2 ; 0 Informatio navailabilit y fo r th e formulatio no f a dose-respons e function ; an d 0 Significan t economi c valu e o f th e crop . Base donapplicatio no f thes e criteria , soybeans , wheat , an doat s ar e selected . Fo r calculatio no f benefits , th e parameter s whic hdefin e th e respons e o f a cro pt o SO 2 shoul dreflec t it s economi c value . Yiel dca nb e give na valu e i neconomi c terms . Whil e folia r an dyiel deffect s ma y

occu r togethe r an

dmay , i nsome instances , b e highl y correlated , yiel drespons e canno t generall y b e accuratel y

extrapolate dfrom

observe dfolia r effect s o f variation s i nSO2 . Therefore , study

selectio ni s limite dt o studie s o f yiel deffects . Th e additiona l criteri a fo r stud y selectio nare : study focu s i s o nambien t SO 2 exposur e an

dothe r ambien t environmenta l factors ; contro l fo r th e impac t o f othe r confoundin g environmenta l condition s o nth e concentratio nrelationship ; an dplausibl e an

dquantifiabl e result s whic hca nb e use dt o develo p concentratio nrespons e functions .

### VI-3 1

Applicatio n o f thes e criteri a yielde d a verylimite d numbe ro f studie s fo reac h crop . Th e majo rstud yused fo rsoybean s i s fro m Spruge l e t al

. (1980)

. Fo roat s an d wheat , th e principa l sourc e i s a serie s o f report s b y Guderia n and Stratman n (196 2 an d 1968)

. 2 ) Applicatio n Averag e ai r qualit y

fo r eac hrecepto r are a fo r th e same par t o f th e growin g seaso na s th e underlyin g stud y use s i s applies . Th e estimat e i s restricte dt o ai r qualit y change s withi nth e underlyin g stud y range . Zer o i s useda s th e minimu m estimate . Th e maximu m estimat e applie s th e dos e respons e functio no f th e stud y varieta l t o al l o f tha t crop . One-hal f th e maximu m estimat e i s use dfo r th e middl e estimate . 3 ) Qualification s an dPlausibilit y

Check s Th e analysi s value s yiel dchange s a t recen t stat e marke t prices . N o attemp t i s mad e t o adjus t fo r pric e change s tha t migh t resul t fro m nationwid e yiel dchanges . N o change s incroppin g pattern s ar e factore dint o th e analysis . N o attemp t i s mad e t o valu e contribution s t o yiel dfo r sulfu r deficien t soils . Th e yiel dfunction s onl y conside r averag e sulfat e concentration s fo r th e growin g seasons . Thi s ignore s impact s o f th e time patter no f exposur e (e.g . siz e an

dtimin g o f peaks) , th e impac t o f othe r pollutants , an d interaction s wit hothe r determinant s o f yiel dsuc ha s temperature , light , soil , an

dagricultura l practice . Th e choic e o f functiona l for m fo r th e yiel dfunctio nwa s necessaril y mad e wit ha very

limite dse t o f dat a points . Th e yiel dchange s ar e sensitiv e t o th e functiona l form .P.9 8

VI-3 2 D . Benefi t Analysi s Estimate s Th e benefi t estimate s ar e exhibite dinTabl e VI-3 . Range s ar e presente d fo r SO 4 an

dPM estimate s t o reflec t th e uncertaint y concernin g ai r qualit y an deconomi c valuation , a s discusse dinIII- B an dVI-C , respectively . Th e benefi t categorie s estimate dinclud e increase dloca l an dnon-loca l visibilit y du e t o SO 4 reductions , reduce dchroni c an dacut e morbidity , an dreduce d househol d(residential ) soilin g du e t o PM reductions , an

ddecrease dhousehol d secto r material s damag e du e t o SO 2 reductions . Th e SO 4 an dPM benefi t estimate s ar e fo r th e 3 1 easter nstat e region , whil e th e SO 2 benefi t estimate s ar e nationwide . Th e benefit s associate dwit hth e percen t reductio nregulator y alternativ e excee dth e benefit s associate dwit hth e lo w sulfu r fue l alternative . Thi s reflect s th e greate r improvemen t inai r qualit y tha t ca nb e achieve d whe npercen t reductio ni s required . Table s VI- 4 - VI- 6 repor t th e averag e benefit s pe r to no f SO 2 reduced . Fo r SO 4 an

dPM , onl y

th e ton s reduce dfro m th e 3 1 easter nstate s ar e considered . Fo r SO2 , ton s reduce dfro m al l 11 3 area s wher e new industria l boiler s wer e placed , ar e calculated . Th e benefit s pe r to nar e extremel y simila r fo r bot hlo w sulfu r fue l
an dpercen t reduction , a s ca nb e see ni nTabl e VI-7 . Th e annualize d benefit s an

dth e ton s o f SO 2 reduce dfo r th e percen t reductio nalternativ e ar e approximatel y

3 0 - 33 % greate r tha nthos e fo r th e lo w sulfu r fue l alternative . Consequently , th e benefi t pe r ton s estimate s ar e almos t identical . Tabl e VI- 8 present s incrementa l benefit s pe r to no f percen t reductio nove r th e low sulfu r fue l alternative .Tabl e VI- 3 Annualize

dBenefits * (Thousand s o f 198 3 dollars) 2

Benefi t Categor

y
S0 4 Visibility Loca l Non-Loca l

P M Morbidity

& Soilin

g SO 2 Health SO 2 Welfar e Material s Damag e Agricultur e
Tota l 

### Lo w 1

8,00 0 3,00 0
23,00 0 2,00 0

26,00 0 

### 20 0
62,00 0 Regulator y ATterna t Industria l Boile r Sulfu r F 

### 2

21,00 0 11,00 0
25,00 0 2,00 0

26,00 0 

### 20 0
85,00 0 

### ue

l 3

41,00 0 25,00 0
26,00 0 2,00 0

26,00 0 

### 20 0
120,00 0 ives 3

S0 2
Percen t Reduc t 

### 1

12,00 0 4,00 0
35,00 0 2,00 0

40,00 0 

### 20 0
93,00 0 

### 2

31,00 0 15,00 0
38,00 0 2,00 0

40,00 0 

### 20 0
126,00 0 

### io

n 3

61,00 0 35,00 0
40,00 0 2,00 0

40,00 0 

### 20 0
178,00 0 j

1 Th e benefi t assessment onl y include s a subse t of potentia l benefits . 2 Benefit s are fo

r th e yea r 1990 , i

n198 3 dollars . A rang e of benefit s (1,2,3 ) i s presente dfo r SO 4 an

dP M to reflec t sensitivit y analysi s o

nth e ai r qualit

y modelin

g an deconomi c valuatio ninputs . 1 C J C JP.10 0

VI-3 4
Tabl e VI- 4 Averag e Benefit s pe rTo n SO 4 (Tota l Visibil i Regulatory 1 Alternativ e Lo wSulfu rFuel/ 1 Lo wSu l fu rFuel/ 2 Lo wSu l fu rFuel/ 3
Percen t Reduction/ 1 Percen t Reduction/ 2 Percen t Reduction/ 3 ty )
(tho u Annualize d Benefit s sand s o f1983$ ) 11,00 0 32,00 0 66,00 0 16,00 0 46,00 0 96,00 0 Ton s S0 2 2 Reduce d (thousands ) 12 0 12 0 12 0
17 5 17 5 17 5 B/

T 9 0 27 0 55 0
9 0 26 0 55 0

1 Arang e o f benefit s (1,2,3 ) i s presente d fo rS0 4 t o reflec t sensitivit y analysi s o n th e ai rqualit ymodelin g an d economi cvaluatio n inputs

. 2 Ton s reduce d calculate d onl yfo r3 1 easter n stat e region

.VI-3 5 p. i

Particulat e Matte r Regulatory 1 Alternativ e Lo wSu i fu rFuel/ 1 Lo wSulfu rFuel/ 2 Lo wSu i fu rFuel/ 3 Percen t Reduction/ 1 Percen t Reduction/ 2 Percen t Reduction/ 3 Tabl e VI- 5 Averag e Benefit s pe rTo n

Annualize d Benefit s (thousand s o f 1983$ ) 23,00 0 25,00 0 26,00 0 35,00 0 38,00 0 40,00 0 Ton s S0 2 2 Reduce d (thousands )
12 0 12 0 12 0
17 5 17 5 17 5 B/

T
19 0 21 0 22 0
20 0 22 0 23 0

1 Arang e o f benefit s (1,2,3 ) i s presente d fo rP M t o reflec t sensitivit y analysi s o n th e ai rqualit ymodelin g an d economi cvaluatio n inputs

. 2 Ton s reduce d calculate d onl yfo r3 1 easter n stat e region

.P. 2

VI-3 6

Tabl e VI- 6 Averag e Benefit s pe r To n 

### SO ; Annualize d Ton s SO-? 1 Regulator yBenefit s Reduce d Alternativ e (thousand s o f 1983$ ) (thousands ) B/ T
Lo wSulfu rFue l 28,00 0 17 0 17 0

Percen t Reductio n 42,00 0 24 0 18 0

1 Ton s reduce d calculate d fo ral l 11 3 area s analyzed

.-EA
_

VI-3 7
Tabl e VI- 7 Averag e Benefit s pe rTo n Total s (SOA , PM , an d SO?) Regulatory 1 B/ T Alternativ e (198 3 $ )
Low Sulfu r Fuel/ 1 45 0 Low Sulfu r Fuel/ 2 64 0 Low Sulfu r Fuel/ 3 93 0
Percen t Reduction/ 1 47 0 Percen t Reduction/ 2 66 0 Percen t Reduction/ 3 95 0

1 A rang e o f benefit s (1,2,3 ) i s presente dfo r S0 dan dPM t o reflec t sensitivit y

analysi s o

nth e ai r qualit y

modelin g an

deconomi c valuatio ninputs .

Tabl e VI- 8

Incrementa l Benefit s pe r Ton 1
Total s (S0 4 , PM , an dS0 2 ) 2 B/ T (198 3 $ ) Percen t Reduction/ 1 51 0 Percen t Reduction/ 2 69 0 Percen t Reduction/ 3 100 0

1 Percen t reductio nove r lo w sulfu r fuel . 2 A rang e o f benefit s (1,2,3 ) i s presente dfo r S0 4 an dP M t o reflec t sensitivit y

analysi s o

nth e ai r qualit y

modelin g an

deconomi c valuatio n inputs .P. 4

VI-3 8
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VI-3 9

Hobart , J.M. , R.L . Horst , Jr. , K.M . Brennan , E.H . Manuel , Jr. , e t al . (1984) . Benefi t Analysi s o f Nationa l Ai r Qualit y Standard s fo r Sulfu r Dioxide . Repor t b

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dStandards , Researc hTriangl e Park , NC , December . Horst , R.L. , J.M . Hobart , E.H . Manuel , Jr. , K.M . Brennan , M.C . Duff , an d G.D . Labovic h(1985) . Benefit-Cos t Analysi s o f Selecte dNew Sourc e Performanc e Standard s fo r Particulat e Matter . Repor t prepare db y Mathtech , Inc . fo r th e Environmenta l Protectio nAgenc y unde r Contrac t No . 68-02-3553 , July . Kirkpatrick , M.B. , Sheppard , D. , Nadel , J.A. , an dBoushey , H.A. , (1982) . Effec t o f Oronasa l Breathin g Rout e onSulfu r Dioxide-Induce dBron choconstrictio ninExcercisin g Asthmati c Subjects . America nRevie w o f Respirator y

Diseases , 125:627-631 . Loehman , E. , Boldt , D. , an dChaikin , K. , (1981) . Measurin g th e Benefit s o f Ai r Qualit y Improvement s inth e Sa nFrancisc o Bay Area , SR I 8962 . Manuel , E.H. , Jr. , R.L . Horst , Jr. , K.M . Brennan , e t al . (1982) . Benefit s Analysi s o f Alternativ e Secondar y Nationa l Ambien t Ai r Qualit y Stand ard s fo r Sulfu r Dioxide s an dTota l Suspende dParticulates , Volum e II . Fina l repor t b

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Standard s fo r Sulfu r Dioxid e an dTota l Suspende d Particulates . Fina l repor t prepare dfo r U.S . Environmenta l Protectio n Agenc y unde r Contrac t No . 68-02-3392 . Researc hTriangl e Park , N.C . Mathtech , Inc. , (1983) . Benefi t an dNe t Benefi t Analysi s o f Alternativ e Nationa l Ambien t Ai r Qualit y Standard s fo r Particulat e Matter . Prepare d fo r th e U.S . Environmenta l Protectio nAgency , Offic e o f Ai r Qualit y Plannin g an

dStandard s unde r Contrac t No . 68-02-3826 . Mathtech , Inc. , (1984) . Benefi t Cos t Analysi s o f Selecte dNew Sourc e Performanc e Standard s fo r Particulat e Matter . Draf t Fina l Repor t Propose dfo r U.S . Environmenta l Protectio nAgency , Offic e o f Ai r Qualit y Plannin g an

dStandard s unde r Contrac t No . 68-02-3553 , Resarc hTriangl e Park , N.C . Mazumdar , S . an

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m th e Pittsburg hstudy . Proceeding s o f th e 74t h Annua l Meeting , Ai r Pollutio nContro l Association , Philadelphia , Pa . Jun e 21-12 . 1981 . Ostro , B . Th e Effect s o f Ai r Pollutio no nWor kLos s an

dMorbidity , Journa l o f Environmenta l Economic s an dManagemen t 10:71-78 . Decembe r 1983 .^

VI-4 0

Rae , D. , (1982) . "Th e Valu e t o Visitor s o f Improvin g Visibilit y a t Mes a Verd e an

dGrea t Smoke y

Nationa l Parks, " a pape r presente da t a Nationa l Par kServic e Conference , Keyston e Colorado , May , late r publishe di n Rober t Row e an

dLaurain e Chestnut , eds. , Managin g Ai r Qualit y an dSceni c Resource s a t Nationa l Park s andWildernes s Areas , Westvie w Press , Boulder , Colorado , 1983 . Rae , D. , Charle s Rive r Associates , (1984) . Benefit s o f Visua l Ai r Qualit y I n Cincinnat i Result s o f a Contingen t Rankin g Survey , draf t report , Electri c Powe r Researc hInstitute , Projec t #1742 . Randall , A. , Hoehn , J. , an dTolley , G . "Th e Structur e o f Contingen t Markets : Result s o f a Recen t Experiment, " a pape r presente da t th e America n Economi c Associatio nMeetings , Decembe r 1981 . Rowe , R.D. , d'Arge , R. , an dBrookshire , D. , (1980) . A nexperimen t onth e economi c valu e o f visibility . Journa l o f environmenta l economic s an dmanagemen t 7:1-19 . Salman , A . System s Analysi s o f th e Effec t o f Ai r Pollutio no nMaterials , Fina l Repor t fo r th e Nationa l Ai r Pollutio nContro l Associatio nunde r Contrac t No . CPA-22-69-113 . Januar y 1970 . Samet , J.M. , Speizer , F.E. , Bishop , Y. , Spengler , J.D. , an dFerris , Jr. , B.G. , (1981) . Th e relationshi pbetwee nai r pollutio nan demergenc y

roo m visit s i nanindustria l community . J . Ai r Pollut . Contro l Assoc . 31:236-240 . Schulze , W.D. , Brookshire , D.S. , Walther , E. , an dKelley , K. , (1981) . Method s developmen t fo r environmenta l contro l benefit s assessment . Vol . X : Th e benefit s o f preservin g visibilit y i nth e nationa l parkland s o f th e Southwest . Washington , D.C : U.S . Environmenta l Protectio nAgency , Offic e o f Researc han dDevelopment . Sprugel , D.G. , Miller , J.E. , Muller , R.N. , Smith , H.J. , an dXerikos , P.B. , (1980) . Sulfu r Dioxid e Effect s o nYiel dan

dSee dQualit y

i nField GrownSoybeans . Phytopathology , 70:1129-1133 . SRI , Inc . A

nEstimat e o f th e Non-Healt hBenefit s o f Meetin g th e Secondar y Nationa l Ambien t Ai r Qualit y Standards . Prepare dfo r th e Nationa l Commissio no

nAi r Quality , Januar y 1981 . Tolley , G. , Randall , A. , Bloomquist , G. , Fabian , R. , Fishelson , G. , Frankel , A. , Hoehn , J. , Krumm , R., Mensah , E. , an dSmith , T . Establishin g andValuin g th e Effect s o f Improve dVisibilit y i nEaster nUnite dStates , Offic e o f Researc han dDevelopment , Environmenta l Protectio nAgency , Marc h1984 . Tolley , G . an

dBabcock , C , (1986) . Draf t - Valuatio no f Reduction s in Huma nHealt hSymptom s an dRisks . USEP A

Gran t No . CR-811053-01-0 .P. 7

VI-4 1

TR C (1981) . Benefi t Mode l fo r Pollutio nEffect s o nMaterial . Fina l repor t prepare dfo r U.S . Environmenta l Protectio nAgenc y unde r Contrac t No . 68-02-3447 . Researc hTriangl e Park , N.C . 27711 . U.S . Burea uo f Labo r Statistic s (1973) . Averag e Retai l Price s o f Selecte d Commoditie s &

Services . U.S . Governmen t Printin g Office , Washington , DC . U.S . Burea uo f Labo r Statistic s (1978) . Consume r Expenditur e Survey : Integrate dDiar y

an dIntervie w

Surve y Data , 1972-73 . Bulleti n1992 , U.S . Governmen t Printin g Office , Washington , D.C . U.S . Environmenta l Protectio nAgency , Offic e o f Ai r Qualit y Plannin g an

d Standards . Protectin g Visibility , A nEP A Repor t t o Congress . EPA 450/5-79-008 . Octobe r 1979 . U.S . Environmenta l Protectio nAgency , Offic e o f Ai r Qualit y Plannin g an

d Standards . Revie w

o f th e Nationa l Ambien t Ai r Qualit y Standard s fo r Sulfu r Oxides : Assessmen t o f Scientifi c an dTechnica l Information , OAQP S Staf f paper . Novembe r 1982 . Watson , W.D. , Jr. , an dJaksch , J.A. , (1978) . Househol dcleanin g cost s an d ai r pollution . Presente da t th e 71s t Annua l Meeting , Ai r Pollutio n Contro l Association , Houston , Texas , Jun e 25-30 . Pape r No . 78-52.3 .VII- 1

VII . BENEFIT-COS T ANALYSI S Thi s chapte r compare s th e cos t o f contro l fo r th e alternativ e regulation s t o th e benefit s estimate dfo r SO4 , PM , an dSO2 . Tabl e VII- 1 present s th e re sult s o f th e ne t benefi t analysi s (benefit s minu s costs) . Tabl e VI1- 2 an d Tabl e VI1- 3 presen t a compariso no f averag e an dincrementa l benefi t pe r to n an dcos t pe r to nestimates , respectively . A s ca nb e see nb

y examinin g Tabl e VII-1 , ther e ar e case s wher e th e annualize dne t benefit s ar e negative . Indrawin g an y conclusion s fro

m thi s table , th e reade r shoul dkee psevera l factor s i nmind . Foremost , ther e ar e many benefi t categorie s no t include dinthi s analysis . Tabl e VI-1 , pag e VI- 5 list s al l potentia l benefi t categorie s fo r th e propose dstandard s an d indicate s whic hone s ar e analyze dinthi s RIA . O f th e benefi t categorie s tha t ar e included , ther e remain s incomplet e coverage . Fo r example , th e SO 2 benefi t estimate s onl y includ e calculation s fo r reduction s inresidentia l material s damage . No calculation s ar e include dfo r commercia l o r industria l facilities . Potentiall y significan t benefit s ar e no t include dfro m th e non-huma nbiologica l effect s categor y (e.g. , aci ddeposition ) an dfro m th e SO 4 mortalit y

category . Inaddition , geographi c coverag e i s limited . Th e SO 4 an dP M benefi t calculation s onl y

includ e th e 3 1 easter nstates . Potentiall y significan t benefit s fro

m th e wester nstate s an dfro m Canad a ar e no t included . Anothe r importan t consideratio ni s tha t th e RI A compare s a rang e o f benefi t estimate s t o a singl e cos t estimate . Thi s inherentl y implie s a greate r confidenc e leve l inth e cos t estimat e tha nmay b e justified . I f cost s wer e als o presente da s a rang e o f estimates , t o reflec t uncertaintie s inth e underlyin g assumptions , th e compariso no f benefit s an dcost s woul db e mor e valid .VI1- 2
Tabl eVII- 1 Net Benefi t Analysi s (thousand s o f 1983 dollars ) P. 9

Regulatory 1 Alternativ e Lo wSulfu rFuel/ 1 Lo wSulfu rFuel/ 2 Lo wSulfu rFuel/ 3
Precen t Reduction/ 1 Percen t Reduction/ 2 Percen t Reduction/ 3 Tota l Annualize d Benefit s 62,00 0 85,00 0 120,00 0 93,000 , 126,00 0 178,00 0 Tota l

Annualize d Contro l Cost s 58,00 0 58,00 0 58,00 0 135,00 0 135,00 0 135,00 0 Annualize d

Ne t Benefit s 4,00 0 27,00 0 62,00 0 -42,00 0

- 9,00 0 43,00 0

1 A rang e o f benefit s (1,2,3 ) i s presente dfo r SO 4 an d PM t o reflec t senstivit y

analys i onth e ai r qualit y modelin g an

d economi c valuatio n inputs .P.1 0

VII- 3
Tabl e VI1- 2 Averag e Contro l Cos t Pe rTo n an d Benefi t Pe rTo n



### (198 3 $ ) Averag e Averag e Regulator y

Alternative 1 C/ T B/ T

Low Sulfu r Fuel/ 1 34 0 45 0 Low Sulfu r Fuel/ 2 34 0 64 0 Low Sulfu r Fuel/ 3 34 0 93 0
Percen t Reduction/ 1 56 0 47 0 Percen t Reduction/ 2 56 0 66 0 Percen t Reduction/ 3 56 0 95 0
1 A rang e o f benefit s (1,2,3 ) i s presente dfo r S0 4 an dPM t o reflec t sensitivit y

analysi s onth e ai r qualit y modelin g an

deconomi c valuatio n inputs .

Tabl e VII- 3

Incrementa l Contro l Cos t Pe r To nan dBenefi t Pe r Ton 1 (198 3 $ )

Percent Reduction/ 1 Percent Reduction/ 2 Percent Reduction/ 3 Incremental 2 C/ T 110 0 110 0 110 0 Incrementa l 2 B/ T 

### 51 0 69 0 100 0

1 A rang e o f benefit s (1,2,3 ) i s presente dfo r S0 4 an dPM t o reflec t sensitivit y

analysi s onth e ai r qualit y modelin g an

deconomi c valuatio n inputs . 2 Percen t reductio nove r lo w sulfu r fuel .p.1 1

VII- 4 Du e t o th e limite dbenefi t coverag e an dgeographic/tempora l scop e o f thi s RIA , i t i s impossibl e t o dra w soundconclusion s a s t o whethe r th e propose dstandard s wil l leadt o a welfar e improvemen t fo r societ y relativ e t o th e baselin e situation . Thi s RI A ha s no t bee ndesigne do r intende dt o portra y

a complet e pictur e o f al l potentia l benefits . N o attemp t ha s bee nmad e t o quantitativel y calculat e al l benefi t categories . Thus , tota l benefit s wil l actuall y b e greate r tha nthos e reported , an dne t benefit s wil l b e larger . Whil e th e directio no f chang e inth e benefi t calculation , du e t o th e additio no f ne w benefi t categorie s i s known , th e magnitud e o f th e increas e i s unknown .P.1 2

TECHNICA L REPOR

TDATA (Please read

Instructions on the reverse before completing) 1 . REPOR TNO . EP A 450/3-86-00 6 3 . RECIPIENT' S ACCESSIO N NO . 4 . TITL E AN O SUBTITL E RegulatoryImpac t Analysi s fo r Ne w Sourc e Performanc e Standards : Industrial-Commercial

Institutiona l Stea

mGenerating Unit s o f Greate r Tha n 10 0 Millio n Btu/h r Hea t Inpu t 5 . REPOR TDAT E Jun e 198 6 6 . PERFORMIN G ORGANIZATIO N COO E

7 . AUTHOR(S ) 8 . PERFORMIN G ORGANIZATIO N REPOR TNO .

9 . PERFORMIN G ORGANIZATIO N NAM E AN O ADDRES S Offic e o f Ai r Qualit yPlanning an d Standard s U.S . Environmenta l Protectio n Agenc y Researc h Triangl e Park , N.C . 2771 1 10 . PROGRA M ELEMEN TNO . 11 . CONTRACT/GRAN TNO .

12 . SPONSORIN G AGENC YNAM E AN D ADDRES S DA Afo r Ai r Qualit yPlanning an d Standard s Offic e o f Ai r an

d Radiatio n U.S . Environmenta l Protectio n Agenc y Researc h Triangl e Park , N.C . 2771 1 13 . TYP E O F REPOR TAN D PERIO D COVERE D Draf t 14 . SPONSORIN G AGENC YCOD E EPA/200/0 4
15 . SUPPLEMENTAR YNOTE S

16 . ABSTRAC T Ne wsourc e performanc e standard s limiting emission s o f sulfu r dioxid e (SO. ) hav e bee n propose d fo r ne windustrial-commercial-institutiona l stea mgenerating unit s wit h hea t inpu t capacitie s abov e 10 0 millio n Btu/hour . Executiv e Orde r 1229 1 state s tha t a regulator

yimpac t analysi s (RIA ) mus t b e performe d o n an yregulatio n havin g a n annua l effec t o n th e econom yo f $10 0 millio n o r more . Thi s RI Awa s prepare d t o fulfil l thi s requirement . Th e analysi s estimate s th e benefit s an d cost s o f tw o regulatoryalternatives : lo w sulfu r fuel-base d standard s an d standard s requiring a percen t reductio n i n SO . emissions . Thi s documen t describe s th e methodolog yuse d i n estimating th e benefit s an d present s th e result s o f th e analysis .

17 . KE YWORD S AN D DOCUMEN TANALYSI S DESCRIPTOR S b.lDENTIFIERS/OPE N ENDE D TERM S c . COSAT i licld/Grou p Ai r pollutio n Standard s o f performanc e Stea mgenerating unit s Industria l boiler s Majo r rul e Benefit s analysi s Ai r pollutio n contro l SO . benefit s 13 B

18 . DISTRIBUTIO N STATEMEN T Releas e unlimite d 19 . SECURIT YCLAS S (This Report! Unclassifie d 2 1 . NO . O F PAGE S 10 8 20 . SECURIT YCLAS S (This page) 22 . PRIC E Unr-lass-tf-fp H EP A For m 2220- 1 (Rev . 4-77 ) PREVIOU S EDITIO N I S OBSOLET E