# OAR Box 1706 Prepped by Ollie Stewart



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# 3 ) lll-B- 3 Docket Number: 

# A-98-1 3

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AM Sheet 3 of 142 P. 1P. 2


## RESEARC H TRIANGL E INSTITUT E 

# /SB Economi c Analysi s o f Ai rPollutio n Regulations : Propose d NESHA P fo rOrgani c Liquid s Distributio n

Fina l Repor t

Prepare d fo r Joh n L . Sorrel s U.S . Environmenta l Protectio n Agenc y Offic e o f Ai rQualit y Plannin g an d Standard s Innovativ e Strategie s an d Economic s Grou p (ISEG) (MD-15 ) Researc h Triangl e Park , N C 2771 1 Prepare d b y Katherin e Helle r Brook s M L Depr o Researc h Triangl e Institute Health , Social , an d Economic s Researc h Researc h Triangl e Park , N C 2770 9 EP A Contrac t Numbe r68-D-99-02 4 RT I Projec t Numbe r7647-002-13 4

Septembe r200 1

304 0 Cornwalli s Roa d Pos t Offic e Box 1219 4 • Researc h Triangl e Park , Nort h Carolin a 27709-219 4 US AP. 3

EP A Contrac t Numbe r 68-D-99-02 4 RT I Projec t Numbe r 7647-002-13 4 

# Economi c Analysi s o f Ai r Pollutio n Regulations : Propose d NESHA P fo r Organi c Liquid s Distributio n

l^e/ise ^ Fina l Repor t Septembe r200 1 Prepared fo r Joh n L . Sorrel s U.S . Environmenta l Protectio n Agenc y Offic e o f Ai rQualit y Plannin g an d Standard s Innovativ e Strategie s an d Economic s Grou p (ISEG )

(MD-15 ) Researc h Triangl e Park , N C 2771 1

Prepare d b y Katherin e Helle r Brook s M . Depr o Researc h Triangl e Institut e Health , Social , an d Economic s Researc h Researc h Triangl e Park , N C 2770 9



## 2-__.P. 4

CONTENTS Section Pag e 1 Introductio n an

d Executive Summar

y 1- 1 1. 1 Profil e ofth e Affecte d Industrie s 1- 1 1.2 Th e Cost s ofth e OL D NESHA P 1- 3 1. 3 Estimate d Economic Impact s o f th e OL D NESHA P 1-

4 1.3. 1 Marke

t Response s t o th e NESHA

P 1- 4 1.3.1. 1 Market

- and Industry-Level Impact s 1- 5 1.3.1. 2 Facility-Level Impact Result s 1- 6 1.3.1. 3 Company-Leve

l Impact s Result s 1- 6 1.3.1. 4 Socia

l Cost s 1- 7 2 Industr

y Profil e 2- 1 2. 1 Brie

f Description o

f Sourc e Categor

y 2- 1 2.1. 1 Curren

t Economi c Condition s and Trend s 2- 3 2.1.1. 1 Chemica

l Productio n 2- 3 2.1.1. 2 Petroleu

mRefinerie s 2- 3 2.1.1. 3 Liqui d an

d PetroleumTerminal s 2- 3 2.1.1. 4 Crud

e Oil Pipelin e Pumping an

d Breakou t Station s 2- 4 2.1. 2 Environmenta

l Concern s 2- 4 2. 2 Distributio n o

f Organi c Chemica

l Liquid s 2- 5 2.2. 1 Overvie

w o f Distributio n Servic e 2- 7 2.2.1. 1 Elasticit

y o f Suppl y .... : 2- 8 2.2. 2 Industr

y Organization 2- 9 2.2.2. 1 Facilitie s 2-1 1 2.2.2. 2 Fir

mCharacteristic s 2-1 3 2.2. 3 Use s an

d Consumer s 2-1 8 2.2.3. 1 Characterizatio n o f Demand—Derive

d Deman d Elasticit y 2-1 9 i nP. 5

2.2. 4 Market s 2-20 2.2.4. 1 Marke

t Volume s 2-2 0 2.2.4. 2 Marke

t Price s 2-2 1 2.2.4. 3 Futur

e Projection s 2-2 1 2. 3 Distributio n o

f PetroleumLiquid s 2-2 1 2.3. 1 Affecte

d Market s 2-2 1 2.3. 2 Production/Servic e Overvie w 2-2 2 2.3.2. 1 Elasticit

y o f Suppl y 2-2 4 2.3. 3 Industr

y Organizatio n 2-2 4 2.3.3. 1 Facilitie s 2-27 2.3.3. 2 Fir

mCharacteristic s 2-2 7 2.3. 4 Use s an

d Consumer s 2-3 4 2.3.4. 1 Characterizatio n o f Demand—Derived Demand Elasticit y 2-3 4 2.3. 5 Market s 2-3 6 2.3.5. 1 Marke

t Volume s 2-3 7 2.3.5. 2 Marke

t Price s 2-3 8 2.3.5. 3 Futur

e Projection s 2-3 8 Engineerin g Cos t

Analysi s 3- 1 3. 1 Contro l Cos t

Estimate s 3- 1 Economi c Impact

Analysis : Method s an

d Result s 4- 1 4. 1 Overview o

f Economic Modelin g Approache s 4- 1 4. 2 Conceptua

l Approac h 4- 2 4.2. 1 Operationa

l Mode l 4- 4 4.2.1. 1 Marke

t Suppl y 4- 4 4.2.1. 2 Marke

t Deman d 4- 4 4.2.1. 3 Contro l Cos t

Input s an d With-Regulatio n Equilibrium4- 4 4.2. 2 Result s 4- 5 4.2.3. 1 Market

- an

d Industry-Leve

l Impact s 4- 5 4.2.3. 2 Facility-Level Impact Results 4- 7 4.2.3. 3 Company-Leve

l Impacts Result s 4- 8 4.2.3. 4 Socia

l Cost s 4- 9

i vP. 6

5 Smal

l Busines s Impac

t Analysi s 5- 1 5. 1 Identifyin

g Smal l Businesse s 5- 1 5. 2 Screening-Leve

l Analysi s 5- 1 5. 3 Economic Analysi s 5- 2 5. 4 Assessmen

t 5- 2 Reference s R- 1 Appendice s

A Organic Liquid s Distributio n (OLD ) Methodology A- l B Economic Computation s B- l C OL D Economic Impact

Analysis : Sensitivit

y Analysi s fo

r Differen t Scenario s C- 1 D Mode

l Paramete r Sensitivit y Analysi s D- 1P. 7

LIS T O F FIGURE S Numbe r Pag e 2- 1 Distributio n o

f Organi c Chemica

l Liquid s Facilitie s tha

t Responded t o th e ICRSurve

y 2-1 4 2- 2 Th e Distributio n o

f Organi c Chemica

l Liquid s Facilitie s tha

t Responded to th e IC

RSurve y by Employmen

t 2-1 5 2- 3 Th e Sir e Distributio n o f Companie s tha

t ow n OL D Facilitie s tha

t Responde d to th e ICRSurve y and ar e Involve d i

n Chemica l Distribution , b

y 199 8 Sale s (i

n $1997 ) 2-1 6 2- 4 Siz e Distributio n o

f Companie s tha

t ow n OL D Facilitie s tha

t Responde d t o th e ICRSurve y and ar e Involve d in Chemica

l Distributio n .. . 2-1 7 2- 5 Distributio n o

f Companie s Owning Organi c Chemica l Liquid s Facilitie s tha t Responded t

o th e IC RSurvey , b

y Profi t Margi n 2-1 9 2- 6 Location o

f PetroleumLiquid s Distributor s tha t Responded to the ICRSurve y 2-2 8 2- 7 Th e Distributio n o

f PetroleumLiquid s Facilitie s tha t Responde d to th e ICRSurve y b y Employmen

t 2-2 9 2- 8 Th e Siz e Distributio n o f Companie s tha

t ow n OL D Facilitie s tha

t Responde d to th e ICRSurve y an d ar e Involve d i

n the Distributio n o

f Nongasoline PetroleumLiquids , b y 199 8 Sale s (i

n $1997 ) 2-3 2 2- 9 Siz e Distributio n o

f Companie s tha

t ow n OL D Facilitie s tha

t Responde d to the ICRSurve

y and ar e Involved i

n th e Distributio n o

f Nongasoline PetroleumLiquid s 2-3 3 2-1 0 Distributio n o

f Companie s Ownin

g PetroleumLiqui d Facilitie s tha t Responde d to th e IC RSurvey , by Profi t Margi n 2-3 5 4- 1 Marke

t Response s t o th e OL

D NESHA P 4- 3 5- 1 Distributio n o

f Complianc e CSRs b

y Industry : Control an

d MR RCost s (1997 ) 5-4 5- 2 Distributio n o

f Complianc e CSRs b

y Industry : MR

R Onl y Cost s (1997 ) 5- 5

v iP. 8

US T O F TABLE

S Numbe r Pag e 1- 1 Numbe

r o f Facilitie s Affecte

d b y OL D NESHAP , b y NAIC S Cod e 1-

2 1- 2 Per-Facilit

y an d Nationwid

e Control Costs by Mode

l Plan t (1997$/yr ) ". 1- 3 1- 3 Market-Leve

l Industr y Impact s o

f the Proposed OL

D NESHA P (1997$ ) 1- 5 2- 1 Nationwide HA

P Total s fro

mOL D Activitie s (tons/yr

) 2- 5 2- 2 Summar

y o f Facilit y Categories , Liquids , Mode s o f Transportation , an d Emission s Source s Covered b y the OL D Sourc e Categor

y 2- 6 2- 3 Principa

l OL D Facilit y Categorie s 2- 8 2- 4 Concentratio n Ratio s b y SI C Cod e 2-1 1 2- 5 Numbe

r o f Tota l OL D Facilitie s an

d Affecte d Facilities , 199

7 2-1 2 2- 6 Profi

t Margin s o

f Firm s tha t Responded t

o th e IC RSurve y an d tha t ow n Organic Chemica

l Liquid s Distributio n Facilitie s 2-1 8 2- 7 Organi c Chemica

l Marke t Volumes , 199

7 (IO 6 Mt ) 2-2 0 2- 8 PetroleumProduct s Produce d a t U.S . Refineries , 199

7 2-2 2 2- 9 Principa

l OL D Facilit y Categorie s 2-2 3 2-1 0 Concentratio n Ratio s by SI C Cod e 2-2 6 2-1 1 Numbe

r o f Tota l OL D Firm s an

d Affecte d Firms , 199 6 2-3 0 2-1 2 Small Busines s Siz e Standard s fo r OL D Industrie s 2-3 1 2-1 3 Profi

t Margin s o

f Firm s tha t ow n Organic Chemica

l Liquid s Distributio n Facilitie s tha

t Responded to th e IC

RSurve y 2-3 5 2-1 4 Estimate s o

f Pric e Elasticit

y o f Deman d fo r Petroleu mProduct s 2-3 6 2-1 5 PetroleumProduct

Marke t Volumes , 199

7 (IO 6 Mt ) 2-3 7 2-1 6 PetroleumConsumption an d Ne t Imports i n 199 7 an d 202 0 (IO 6 barrels/day ) 2-3 9 3- 1 Facilit

y and Nationwid

e Control Cost s fo

r th e Proposed OL

D MAC T 3- 3

v uP. 9

4- 1 Market-Leve

l Industr y Impact s o

f th e Proposed Organi c Liqui d Distributio n (OLD ) NESHAP : 1997 4- 6 4- 2 National-Level Industiy Impact s o f th e Proposed Organic Liqui d Distributio n (OLD ) NESHAP : 1997 4- 7 4- 3 Estimate d Company-Leve l Impact s o

f th e OL D NESHAP : 1997 4- 9 4- 4 Distributio n o

f Socia l Cost s Associate d wit

h Organi c Liquid s Distributio n (OLD ) NESHAP : 1997 4-1 0 5- 1 Complianc e CSR s fo r Companie s b y Industr

y an d Compan y Size : Contro l andMRRCosts(1997 ) 5- 3

vn iP.1 0

SECTIO N 1 INTRODUCTIO N AN

D EXECUTIV E SUMMAR Y
Under Titl e I I o f the Clea n Ai r Ac t (CAA ) Amendments o

f 1990 , th e Offic

e o f Ai r Qualit y Planning and Standard s (OAQPS ) i s developing anationa l emission standar

d fo r hazardou s ai

r pollutant s (NESHAP

) t o limi t ai r emission s fro

morganic liqui d distributio n activities . Industrie s tha t will b e affecte

d by thi s NESHA

P includ e chemica l manufacturers , liqui d terminals , petroleu m refiners , an

d pipeline owners an

d operators . The proposed NESHA P require s distributor s o

f nongasoline organi c liquid s to mee t emission standard s fo

r the releas e o

f hazardou s ai

r pollutant s (HAPs ) into th e environment . To mee t thes e standards , som

e firms will have t

o modif y their equipmen t and institut

e lea k detection an

d repai r procedures . Thes e change s result i n highe r cost s o f productio n fo

r th e affecte d producers . The

y ma y als o have broade

r societa l implication s becaus e thes e effect

s ar e transmitte d throug

h marke t relationship s t o their

customers . Thi s repor

t profile s th e affecte

d industrie s an

d analyze s the economi c impact s expecte d t o b e incurred as a result o f th e NESHAP . 1. 1 Profil e ofth e Affecte d Industries Th e organic liquid s distributio n (OLD ) sourc e categor y consist s o

f all th e sourc e categor

y operation s tha

t receive , store , an

d distribut e organi c liquid s (othe

r tha n gasoline ) throughou

t th e economy . T o provid

e dat ao n th e affecte

d industry , EP

A collecte d surve

y information fro

mOL D facilities . I

n thi s report , thes e surve

y dataar e scale d u p to reflect th e entir e affecte d univers e o

f facilities . EP

A estimate s tha

t 64 9 facilitie s will b e affecte d b y th e NESHAP . Tabl e 1- 1 show s a frequenc y distributio n o

f facilitie s by Nort

h America n Industr y Classification Syste

m(NAICS ) code . Facilitie s affecte

d ma y eithe r produce , consume , store , an d distribut e regulate d organi c liquids , or onl y stor e an d distribut e them . Th

e fou r majo r industrie s affecte

d by the NESHA

P ar e chemica l manufacturing , petroleu

mrefining , crude oil an

d natura l gas pipeline transportation 1 , an d liqui d terminalling an

d warehousing . Th e liquid s bein g distribute d fal l int o tw o broa d categories :

'Natura l ga s pipelin e distributio n i s no t affecte d b y thi s propose d rule .

1- 1 

# fP.1 1

Tabl e 1-1 . Numbe r

o f Facilitie s Affecte d b y OL D NESHAP , b y NAIC S Cod e

NAIC S Cod e 32 5 3241 1 49 3 4861 1 422,45 4 Tota l Descriptio n

Industrial Organi c Chemical Productio n Petroleu mRefinerie s Liqui d Terminal s Crud e Petroleu mPipeline s Petroleu man d Chemica l Terminal s Number o f Affecte d Facilitie s 37 0 11 0 94 3 5 4 0 64 9

• organi c chemicals , includin g syntheti c chemical s an d petrochemicals , an d

• petroleu mliquids , includin g crud e oil , natura l ga s liquids , an d nongasolin e refine d products . I n NAIC S 32 4 an d 325 , th e majorit y o f facilitie s emplo y mor e than 50 0 people . Withi n th e othe r NAIC S codes , however , man y facilitie s emplo y 2 5 o r fewe r people . Thirt y percen t

o f affecte d organi c chemica l producer s (NAIC S 325 ) an d 3 1 percen t o f facilitie s i n th e othe r

industr y group s ar e locate d i n Texas . Othe r state s wit h substanti anumber s o f

facilitie s includ e Louisiana , Alaska , Ohio , Illinois , an d Califomia . Firm s ownin g OL D facilitie s rang e fro msmal l single-facility specialize d distributor s t o larg e integrate d companie s tha t ow n numerou s productio n an d distributio n facilities . O f a n estimate d 20 8 (scaled ) affecte d companie s ownin g OL D facilities , onl y 2 8 ar e considere d smal l accordin g t o Smal l Busines s Administratio n (SBA ) criteria . O f OL D firms i n NAIC S 325 , mos t

hav e baselin e compan y sale s exceedin g $ 1 billion , an d baselin e employmen t exceedin g 10,00 0 employees . Amon g firms ownin g petroleu mOL D facilities , however , baselin e sale s vary mor e widely . Approximatel y 2 0 percen t hav e sale s les s than $5 0 million , whil e mor e tha n 6 5 percen t

hav e sale s exceedin g $ 1 billion . Man y firms i n th e affecte d industrie s ar e highl y integrated , bot

h verticall y an d horizontally . Thi s mean s the y ma y ow n numerou s affecte d facilities , an d tha t thei r distributio n facilitie s ar e a n integra l part

o f thei r overal l organi c liqui d operations . Fo r thi s reason , w e hav e pai d specia l attentio n in ou r analysi s t o th e impact s o n th e companie s ownin g th e OL D facilities . I n thes e integrate d firms, EP A expect s tha t man y o f th e distribution-onl y facilitie s in NAIC S 422,454,486 , an d 49 3 are not profi t center s fo r

th e firms tha t

ow n them , bu t 1- 2 

# 1 0P.1 2

instea d provid e aservic e to othe

r facilitie s owne

d b y th e firm, an d operat e as acost cente r fo r the firm. Thus , th e impacts o

f th e regulation wil

l b e evaluated i

n term s o f it s overal l impac t o n th e firm' s profitability , i

n addition t

o examining th

e impac t o n the profitabilit

y o f individua l facilities . For merchan t firms, however , tha

t ow n onl y distribution facilities , EP

A expect s tha

t the impac t o f the regulatio n will b e evaluated i n term s o f it s effec t o n facilit y profitability . 1. 2 Th e Cost

s o f the OL D NESHA

P Th e OL D rulemaking wil

l increas e the cost s o

f distributin g organi c liquids . Specifically , th e cost s o f severa l genera l type s o f businesse s ar

e expected t

o increase . Thes e businesse s include facilitie s tha

t manufactur

e an d distribut e organic chemical s and/or

nongasoline petroleu

mproduct s an d facilitie s tha

t specializ e i

n th e distribution o

f thes e products . O

f th e latte r facilities , som

e ar e owne d b y companie s tha

t als o manufactur

e th e products , whil e other s ar e independen

t businesse s tha t onl y distribut e th e products . Tabl e 1-

2 show s the estimate d cost s fo r mode l plants . Th e cost s ar e show n i n greate r detail i n Section 3 , an

d thei r allocation to actua

l plant s i s discussed i

n Appendi x B . Table 1-2 . Per-Facilit

y an d Nationwide Contro

l Cost s b y Mode l Plant(1997$/yr

) Mode l Plan t 28- 1 28- 2 28- 3 29- 1 29- 2 29- 3 42- 1 42- 2 42- 3 46- 1 46- 2 51- 1 51- 2 Numbe r o f

Facilitie s 195 105 7 0 5 4 3 0 2 7 2 5 3 1 3 8 2 6 3 5 2 4 17 Total Annua l Cos tpe r

Facility (range ) 16,300-120,11 2 15,700-116,81 8 15,700-156,59 9 47,500-58,26 8 15,700-78,37 8 15,700-93,09 4 16,400-147,33 1 16,400-185,42 5 16,400-379,22 4 13,300-164,20 0 13,300-149,70 0 16,400-142,66 8 16,400-136,41 4 Tota l Capital Cos tfo r al l Facilitie s 11,671,13 6 13,425,08 6 23,433,64 1 1,584,39 0 1,799,84 0 2,445,52 8 3,068,00 8 6,650,06 2 22,147,02 9 3,791,90 0 1,470,56 1 1,686,55 6 1,247,73 2 Tota l Annual Cos tfo r

al l Facilitie s 9,510,19 6 4,969,12 4 6,013,91 9 1,951,67 1 . 1,283,04 4 1,302,902 1,789,05 2 2,738,04 5 7,093,77 4 1,507,33 5 601,45 8 1,568,18 3 1,047,19 2 1- 3

/ /P.1 3

1. 3 Estimate d Economi c Impact s o f th e OLD NESHAP Sectio n 4 present s the economic impact analysi s method s an

d results . EP

A develope d a multi-market

partia l equilibriu msimulation mode

l i n whic h buyer s an

d seller s exer

t n o individua

l influenc e on marke

t price s o f tw o aggregate

d commoditie s potentially affected by th e rule—petroleuman

d chemica l products—an

d th e marke

t fo r distributio n services . Price s in thes e market s ar e set by the collectiv e action s o

f producer s an

d consumers , wh o tak

e the marke

t pric e a s agive n in makin g thei

r production an

d consumption choices . Figur e 4- 1 illustrate s thi s marke

t in which price s and quantitie s ar e determined b y th e intersectio n o f market supply and demand curves . Th e baselin e consist s o f amarke t pric e an d quantit y (P , Q ) tha

t i s determine d by th e downward-slopin g marke

t deman d curve (Dj ) an

d the upward-sloping marke t suppl y curv e (S,) . Wit h th e regulation , the cost s o f productio n increas e fo

r organi c liqui d supplier s becaus e the y incu r additiona l cost s associated wit

h th e proposed rule . Incorporatin g thes e regulator y contro l cost s i s represente d b y a n upwar d shif t (fro mS , t o S 2) ofth e aggregat e suppl y curv e b y th e per-unit complianc e cost . A t th e ne w equilibriumwit

h th e regulation , th e marke

t pric e increase s fro

mP , to P 2 an

d market output (a s determined fro

mthe marke

t deman d curve , D ) decline s fro

mq , t o q2 . Thi s illustrate s th e theor

y underlying estimation o

f th e economic impact s o

f th e rule . Not

e tha t EP A i s modelin g th e impact s ofth e rul e o n facilitie s an

d companie s tha

t bot h produc e an

d distribut e organi c liquid s b y examining th e change s i n marke t price s an d quantitie s for

th e liquid s bein g distributed . Fo r

integrate d organi c liqui d producers , distributio n operation s ar e acos t center , no t

a profi t center . Th e distributio n operation s ar e a n essentia l par t o f th e proces s o

f providin g th e delivere d liquid s to customers , but ar e no t require d to b e profitabl e i

f the y are to continue . Instead , th e companie s examine th

e impac t o f the propose d rul e o

n th e overall profitabilit

y o f thei r chemica l o r petroleumproduc t

operations . I

n the merchan

t distributio n sector , however , distributio n facilitie s ar e assumed t o operat

e as profi t centers ; tha

t is , the y continu e t o operat

e only i f they ar e profitable . 1.3.1 Market

Responses to the NESHAP Th e theor y presented above suggest s tha t producer s attemp t

to mitigate th e impact s o

f higher-cos t

productio n b

y shifting th e burde

n o n to othe r economi c agent s t o the extent th e marke t condition s allow . W

e woul d expect the mode l to project upwar d pressur e on price s a s producer s reduc e outpu

t rate s i n respons e to highe

r costs . Highe

r price s reduc e quantit

y demanded an

d 1- 4

#P.1 4

output fo r each product , leadin

g t o change s i

n economic surplu s t

o consumers an

d profitabilit

y o f firms. Thes e marke

t adjustments determin

e th e socia l costs o f th e regulation an

d it s distributio n acros s stakeholder s (producers an d consumers) . 1.3.1.1 Market- and

Industry-Level

Impacts Th e increased cos t

o f production du

e t o th e regulation i s expected to slightl y increas e the pric e o f petroleu man d chemica l product s an

d reduc e thei

r production/consumption fro mbaselin e levels . A s show

n i n Tabl e 1-3 , the regulator

y altemativ e i s projected to increas e price s b y les s tha n 0. 1 percent . Domestic production o f petroleu mproduct s decline s b

y 0.0 6 millio n metri c ton s an d domesti c chemica

l production decline s b

y 0.0 4 million metric tons . Suppl y fro mforeig n producer s (imports ) increase s b y 0.0 2 million metri c ton s in th e petroleu mmarke t an d 0.00 2 millio n metri c ton s i n th e chemica

l market , resultin g i

n ane t decline o f 0.0 4 an d 0.0 5 million metri c ton s respectively (les s tha

n 0.0 2 percent) . Suppl

y fro mmerchan

t distributor s decline s b

y approximatel

y 0.0 2 millio n metric tons , les s tha n 0.0 1 percent . Tabl e 1-3 . Market-Leve

l Industr y Impact s of th e Propose

d OL D NESHAP (1997$ )

Petroleu m Products Pric e ($/Mt ) Quantit y (10 s Mt/yr) Domesti c Foreig n Organi c Chemical Product s Pric e ($/Mt ) Quantit y (10 6 Mt/yr ) Domesti c Foreig n Merchan tDistributor s Pric e ($/Mt ) Quantit y (10 6 Mt/yr ) Absolute Chang e 0.0 1 -0.0 4 -O.0 6 0.0 2 0.0 5 -0.0 3 -0.0 4 0.0 1 0.0 4 -O.0 2 Percen tChang e 0.002 % -O.001 % -O.002 % 0.002 % 0.030 % -0.045 % -0.053 % 0.045 % 0.36 % -0.00 %

1- 5 

# / 3P.1 5

Revenue , costs , an

d profitabilit

y ofth e directl

y affecte d industr y als o chang e a s price s an

d productio n level s adjus

t t o increased cost s associated wit h compliance . Fo r

domesti c petroleum producers , operatin g profits ar e projected to decline b

y $8. 7 million (se e Tabl e 4-2) . For domesti c chemica l producers , operating profits ar e projected t

o decline b y $11. 4 million . Operatin g profit s earne d b y merchan t distributor s ar

e projected to increas e b

y $0. 3 million . 1.3.1.2 Facility-Level

Impact Results EP A estimate d quantit

y adjustments by affecte

d OL D facilities , i n respons e to th e cost s o f complianc e wit

h th e proposed rule . EP

A define d closur e o f a n OL D operatio n whe

n a n OL D facilit y i s projecte d to reduc e their quantit y distribute d b

y th e entir e amoun t o f their baselin e distribution . N o facilitie s ar e projected t o clos e their

OL D operation s i n respons e t o th e propose d rule . 1.3.1.3 Company-Level

Impacts Results For th e compan

y leve l analysis , EP

A computed the chang e in profit s associate d wit h th e regulatio n t o baseline company profits . A compan y ma y becom e unprofitabl e i

f th e predicte d chang e i n OL D facilit y profits eliminate s total

baseline profits of

the firm (i.e. , rati o = 10

0 percent) . Fo r

companie s incurring bot

h contro l an

d monitoring , recordkeepin g an d recording (MRR ) costs , profi

t change s rang e fro

m+0. 1 percen

t t o -32. 5 percent . Fo r

th e media n company , profit s decreas e b

y approximatel

y les s tha n 1.0 percent . No firms ar

e projecte d t o becom

e unprofitable a s aresult

o f the regulation . Fo r

companie s incurrin g MR

Rcost s only , profi

t change s rang e fro m+0. 2 t o -7. 3 percent . For

the media n company , profit s decreas e b y les s tha n 0. 3 percent . None o

f thes e firms ar

e projected t o becom

e unprofitable a s aresul t

o f th e regulation. Th e analysi s als o show s tha t impact s fo

r companie s withi

n mode l plant 42 , owner s o

f bul k liqui d terminals , ar

e relatively highe

r compared t o othe

r industr y groups . EP A als o peiformed ascreening analysi s to asses s th e impact s o f th e OL D NESHA

P o n smal l businesses . The results o

f thi s screenin g analysi s ar

e show n i n Sectio n 5 . EP

A examine d th e rati o o f complianc e cost s to baselin e compan y revenues , without

incorporatin g marke

t adjustment s to th e proposed rule . Seve

n o f th e companie s owning facilitie s respondin g t o the OL D questionnair

e ar e smal l businesses . Scaling thes e u p statistically t

o correspon d t

o th e univers e o

f companie s owning OL

D facilities , EP

A estimate d tha

t atota l o f 2 8 small companie s ow

n OL D facilities . O

f th e estimate d 2 8 smal

l firms, onl

y tw o ar e projecte d to incur

cost s exceedin g on

e 1- 6 

# /Hpercen

t o f thei r baseline revenues , an

d non e ar e projecte d t o incu r cost s exceeding three percen t o f baselin e revenues . Give

n th e relativel y lo w cost s an d th e smal l numbe r o f smal l companie s incurrin g them , EP A finds tha

t significan t economic impacts wil

l no t b e incurre d b

y asubstantia

l numbe r o f smal l businesses . 1.3.1.4 Social

Costs The valu e o

f aregulator

y actio n i s traditionall

y measured b

y the chang e i

n economic welfar

e tha t i t generates . Th e regulation' s welfar e impacts , o

r the socia l cost s require d to achieve environmenta

l improvements , wil

l extend t o consumers (customers ) an d producer s alike . Consumer s experienc e welfar e impacts du

e t o change s i

n marke t price s an d consumption level s associate d wit

h th e rule . Producers experienc e welfar e impact s resultin g fro

mchange s i

n profit s correspondin g wit

h th e change s i

n production level s an

d marke t prices . However , it

i s importan

t t o emphasiz e tha

t thi s measur

e doe s not includ e benefits tha

t occu r outsid e th e market , tha

t is , th e valu e o f reduce d level s o

f air pollution wit

h the regulation . The economi c analysi s account s fo r behaviora l response s by producer s an d consumer s to th e regulatio n (i.e. , shifting cost s to othe r economic agents) . Thi s approac h provide s insight s o

n ho w the regulator

y burde n i s distribute d acros s stakeholders . A s show n i n Tabl e 4-4 , th e economi c mode

l estimate s tota

l socia l cos t o f th e rul e o f $40. 7 millio n (1997$) . A s aresult o f highe r price s an d lowe r consumption levels , consumers (domesti c an d foreign) ar

e projected t o los e $23. 8 million , wit

h petroleu mconsumer s accounting fo r mor e tha n 5 0 percen

t o f th e total . Domesti c producer s los e $16. 9 millio n i n profits , wit

h chemica l producer s accounting fo

r 5 8 percen t o f th e total . Foreign producer s unambiguousl y gai n a s aresult

o f th e regulation , wit

h profit s increasing by 3. 0 million . Foreign producer s benefi t fro mhigher price s whil e no

t incurrin g contro l cost s associated wit

h th e proposed rule .

1- 7 

# /s-P.1 7

SECTIO N 2 INDUSTRY PROFIL E

Th e OL D NESHA P potentiall y affect s companie s an d facilitie s tha t distribut e petrochemical s an d petroleu mliquids . Industrie s tha t wil l b e affecte d b y thi s NESHA P includ e chemica l manufacturers , petroleu mrefiners , liqui d terminals , an d pipelin e owner s an d operator s (organi c liquid s othe r

than gasoline) . Informatio n o n th e affecte d facilities , companies , an d industrie s i s necessary i n determinin g th e effect s of aregulation. Thi s profil e describe s th e suppl y an d deman d o f

petrochemical s an d petroleu mliquids , th e facilitie s an d companie s tha t operat e withi n affecte d industries , an d th e marke t condition s i n thos e industries . Sectio n 2. 1 provide s abrie f descriptio n of

th e entir e OL D sourc e category . Section s 2. 2 an d 2. 3 focu s o n th e tw o primary facilit y categories—chemica l liquid s an d petroleu mliquids , whic h ar e briefl y describe d i n Sectio n 2.1 . Section s 2. 2 an d 2. 3 ar e bot h organize d a s follows : background , productio n overview , industry organization , characterizatio n o f use s an d consumers , an d marke t

information . Facilitie s that ma y distribut e eithe r

chemical s o r

petroleu mproduct s ar e discusse d i n Sectio n 2. 3 only , for convenience . 2. 1 Brie f

Descriptio n o f

Sourc e Categor y Th e OL D sourc e category consist s o f al l o f th e sourc e category operation s tha t receive , store , an d distribut e organi c liquid s throughou t th e economy . Fo r

th e purpose s o f

thi s maximu m achievabl e contro l technolog y (MACT ) standard , onl y thos e organi c liquid s wit h appreciabl e HA P conten t (beyon d trac e quantities ) ar e considere d t o b e "organi c liquids. " Thes e liquid s may consist o f pur e HA P chemical s (singl e HAP ) o r chemica l blends , refined petroleu mproducts , natura l ga s liquids , o r crud e oil . The y als o may consis t o f "appreciable " organi c HAP s blende d wit h inorganic , non-HA P liquid s (suc h a s water) . OL D operation s ar e carrie d ou t b y alarg e numbe r

o f industries . "Plan t

site s performin g OLD activitie s includ e thos e tha t produce , consume , o r

merel y stor e an d distribut e organi c liquids . Th e four principal industrie s wit

h th e greates t

volume s of

OL D operation s ar e chemica l 2- 1 

# / 7P.1 8

manufacturing , petroleu

mrefining , crud

e oil an d natura l gas liquid s pipelin e transportation , an d liqui d terminallin g an

d warehousing " (Abt, 1998) . Distribute d organic liquid s o f concer n i n thi s profile fal

l unde r tw o broa d categories :

• chemicals , including syntheti c chemical s an d petrochemical s (i.e. , chemical s manufactured fro

mcrud e petroleum) ; an

d

• petroleumliquids , including crud e oil , natura

l gas liquids , an

d nongasolin e refined products . Gasoline , which i s subject

t o the gasoline distributio n NESHAP , i s not covere d by th e OL

D sourc e category . Section s 2. 2 an

d 2. 3 2 provid

e amor e detaile d description o

f th e liquid s covere d b

y thi s regulation . Fo r th e purpose s o

f thi s regulation , distribution include s th e bul k transfe r o f a n organi c liqui d acros s aplan

t sit e boundary , eithe

r into or out o f th e plan t sit e (Abt , 1998) . Als o covered unde r thi s definition ar

e th e storag e o

f OL D liquid s afte

r receipt an d befor e distribution . No

t include d in th e OL

D sourc e categor

y ar e th e following activities : th e movemen t o f packaged liquid s (e.g. , drummed or

canne d liquids) ; an

y production , compounding , blending , o r packagin g activitie s a t OL D facilities ; an

d th e transportatio n o

f OL D liquid s fo

r activitie s othe

r tha n loadin g an

d unloading . Th e OL D activitie s described abov e tak e plac e a t site s tha t serv e a s distributio n point s fro m whic h organi c liquid s ca

n b e obtained fo

r furthe r us e an d processing . Distributio n activitie s ar e eithe r collocate d wit

h liqui d production operations , or the y ar e carrie d out

a t stand-alon e storag e an d distributio n terminals . Althoug h th e MACT standard s developed unde r thi s regulation will appl y to an y facilit y tha t receives , stores , and/or

distribute s nongasoline liquid s wit h HA P content , thi s profile focuse s o

n five categorie s o

f OL D facilitie s fo

r whic h model plant s wer

e developed :

• chemica

l production ,
• petroleumrefineries,

• liqui d terminal s

• crud e oil pipelin e pumping/breakou t stations , an

d

• petroleu

mterminals . 2- 2 

# liP.1 9

Thes e categorie s wer

e identifie d fro mEPA' s Apri

l 199 8 sourc e categor

y surve y as accounting fo

r the majorit y o f OL D HA P emission s (Gale Research , Inc. , 1999a,b,c) . 2.1.1 Current

Economic Conditions and Trends OL D distributio n points wil

l incu r the cost s ofthi s regulation ; therefore , thi s profile examine s th e curren t conditio n o

f th e OL D sourc e categor

y a s i t relate s to distributio n activities . Thi s section briefl y describe s recen

t trend s i n eac h o f the five principal , OL

D facilit y categories. 1 2.1.1.1 Chemical

Production Recen t trend s in th e chemica

l manufacturing industr

y includ e increase d capita

l spending an

d declinin g employment . I

n a n effor t to save mone

y an d increas e efficiency , man

y o f the activitie s associate d wit

h repackaging , blending , reformulating , bar-coding , testing , an d qualit y assuranc e have bee n outsourced . Tha

t is , contracte d ou

t t o third-pM y operators . Thi s trend has bee n growin g in th e chemica

l manufacturin

g business . Wit

h mor e o f thi s wor k being outsourced , manufacturers ' cost s ar

e decreasin g {Distribution, 1996) . 2.1.1.2 Petroleum Refineries Ove r th e pas t tw o decades , oil companie s hav e bee n closin g refineries tha

t ar e n o longe r profitable . T o avoi d expensive environmenta l cleanu p costs , companie s hav e starte d t o conver t th e refineries ' storag e tank s an

d t o operat e the ma s storag e an

d distributio n centers . However , i n recen t years , astabl e suppl

y marke t fo r crude oi l ha s led t

o areduction i

n oi l inventories , creatin g exces s storag e spac e a

t refineries. Refinerie s hav e responded to thi s situatio n b y leasin g out

thi s exces s spac e t

o thir d parties . Wit

h continue d merge

r an d cost-cuttin g activitie s i

n the sourc e category , i t

i s conceivabl e tha

t mor e exces s spac e will b e create d i n th e futur e an d mor e refinerie s wil l continu e to leas e increasing amount s o f storag e spac e a

t their installations . 2.1.1.3 Liquid

and Petroleum Terminals Th e bul k liqui d terminallin g industr

y i s undergoing change s as th e majo r manufacturer s o

f organic liquid s an

d chemical s ar

e restructurin g their

industrie s t

o mee t presen t an d futur e demands . Terminal s face adua

l challeng e i

n th e future . On e challeng e i s increasin g regulator y demand s tha

t

'Thi s discussio n i s largel y base d on th e Jul y 24,1998 , EP A memorandu mentitle d "Productio n Projection s fo r th e OL D Sourc e Category. " 2- 3 

# MP.2 0

are raisin g the cos t

o f operation fo

r refineries , chemica

l plants , an

d terminals . I

n addition , exces s storag e capacit

y a t petroleu mrefinerie s an

d newl y create d storag e capacit

y a t smalle r chemica l distributor s have started t

o directly compet

e wit h th e large r bul k terminals . Majo

r consolidation s withi n th e chemica

l industr y hav e als o affecte

d the bul k terminallin g industry . Majo r chemica l companie s have begu

n to consolidat

e their storag e requirement s b

y contractin g ou

t storag e t o outsid e firms tha

t operat e single-part

y terminals , rathe

r tha n spreadin g their

operation s acros s man

y terminals . 2.1.1.4 Crude Oil

Pipeline Pumping and

Breakout Stations The Federa

l Energy Regulator

y Commissio

n (FERC ) regulates interstat e pipelin e companies . Simila

r to som e o f th e othe r categories , thes e pipelin e companie s ar e experiencin g difficul t time s a s well . I

n 1997 earning s fro

moperation s wer

e down , following a2-yea

r trend . Th e effects o f warmer-than-norma

l weathe r durin g 199

7 i n Nort h Americ aals o caused oil deliverie s t o decrease . Thi s decreas e affecte d bot h operatin g revenue s an

d net incom e fo r pipelin e companie s (Oil & Gas Journal, 1998) . 2.1.2 Environmental

Concerns EP A ha s identified fou

r emissio n source s tha

t accoun t fo r th e majorit

y o f HA P emission s fro mOL D activities: 2

• storag e tanks ,
• liqui d transfe

r activitie s involvin g tan

k truck s an d railcar s Goadin

g racks) , an

d

• leak s fro

mequipmen

t component s (e.g. , pumps , valves) . Tabl e 2- 1 show s th e nationwide HAP total s fo r eac h industr y resulting fro

mthe differen

t emissio n sources . Storag e tank s emit 63,31 5 tons/y

r o f HAPs , accounting fo

r approximatel

y 7 0 percen

t o f

2 Originally , wastewater

an d semi-aqueou s wast e wer e als o believe d t o b e source s o f HA P emission s for

th e OL D sourc e category . However , response s t o th e OL D surve y indicate d tha t insufficient

informatio n i s availabl e t o determin e nonzer o MAC T floor s fo r wastewater . I n addition , th e surve y indicate d that semi-aqueou s wast e generate d fro

mOLD operation s i s generall y kep t i n close d container s onc e i t i s collected . Th e handlin g o f

thes e wastes , a

t bot h chemica l facilitie s an d refineries , i s alread y covere d unde r th e Resourc e Conservatio n an d Recover y Ac t (RCRA ) ("MAC T Floo r

Developmen t

for th e OL D Sourc e Category, " Memo , Ma

y 5,1999) . Consequently , emissio n source s associate d wit h wastewate r

and semi-aqueou s wast e are exclude d fro

mthi s analysis . 2- 4 

# IPP.2 1

Tabl e 2-1 . Nationwide HA P Totals fro

m OL D Activities (tons/yr) a

Industr y Segment Chemica l productio n Petroleum refiner y Liqui d terminal s Crud e oi l pipeline s Petroleu m terminal s Tota l No . o

f Majo r Source Facilitie s Nationwide

b 37 0 lll c 9 4 3 5 41 c 651 c Storage

Tank s 38,78 5 4,36 5 17,99 0 44 0 1,73 5 63,31 5 Loadin

g Rack s 4,66 0 2,100 2,89 0 a 26 0 9,91 0 Containe r

Fillin g 4 8 1 1
a 1 5 1 Equipmen

t Leak s 10,03 0 1,46 0 5,01 5 4 5 96 5 17,51 5 Total s

53,52 0 7,93 0 25,90 0 49 0 2,96 0 90,80 0

° Ther e are n o transfer

rac k o r containe r fillin g emission s a

t pipelin e facilities . b Estimate d numbe r

o f facilitie s base d o n industr y dat aand previou s NESHA P reports , a s describe d i n th e technical suppor

t document . Onl y 23 9 facilitie s returne d survey s o n thei r OLD activities . Emission s dat afo r th e nonrespondin g facilitie s wer e estimate d t o develo p th e estimat e o f nationwid e impacts . c EP A ha s recentl y determine d tha t tw o facilities , on e petroleu mrefiner y an d on e petroleu mterminal , ar e exemp t du e t o thei r

ver y smal l throughput . Thu s ther e ar e atotal o f 64 9 affecte d facilities , includin g 11 0 petroleu m refinerie s an d 4 0 petroleu mterminals . Source : U.S . Environmental Protectio n Agenc y (EPA) . 2000 . Technical Support Document

for the Organic Liquids Distribution (Non-gasoline) Industry. Washington , DC : U.S . Environmenta l Protectio n Agency , Offic e o f

Air Qualit y Plannin g an d Standards . th e tota l OL D sourc e category . Equipmen t leak s ar e th e next greates t sourc e o f HA P emissions , representing almos t

1 9 percen t o f th e sourc e categor

y total . Tabl e 2- 2 list s al

l o f th e facilit y categorie s as wel

l a s th e mode s o

f transportatio n employed an d the emissio

n source s covered by the OL D sourc e category . 2. 2 Distributio n o

f Organi c Chemica

l Liquid s Organic chemica

l liquid s includ

e syntheti c chemical s an

d petrochemical s (chemical s manufacture

d fro mcrude petroleum) . Syntheti c organic chemical s cove r awid e rang e o f 2- 5


## < * lP.2 2

Tabl e 2-2 . Summar

y o f Facilit y Categories , Liquids , Mode s o f Transportation , an

d Emissions Sources Covere d b y th e OL D Sourc e Categor

y Facilit y Categor y Chemica l productio n Petroleum refinerie s Liqui d terminal s

Crude oi l pipeline s

Petroleum terminal s Liquid s Handle d

Syntheti c chemical s Petrochemical s Crude oi l Natura l ga s liquids , (NGLs ) Nongasolin e refined product s Syntheti c chemical s Petrochemical s Crud e oi l Nongasolin e refine d product s Crude oi l

Crude oi l NGL s Nongasolin e refine d product s Mod e of Liqui d Transportatio n Tan k truc k Tan k ca r (railroad ) Sometime s pipeline s Pipelin e Tanke r ship s Barge s Tan k ca r Tan k truc k Tan k ca r Tan k truck s Pipelin e Tanke r ship s Barge s Tan k ca r Tan k truc k Tanke r ship Barg e Pipelin e Tan k ca r Tan k truc k Emissio n

Source s Storag e Umk

s Liqui d transfe

r Containe r filling Equipment

leak s Storag e tank s Liqui d transfe

r Containe r fillin g Equipment

leak s Storag e tank s Liqui d transfe

r Containe r fillin g Equipmen t leak s Storag e tank s Equipment

leak s Storag e tank s Liqui d transfe

r Containe r filling Equipment

leak s
Sources : Variou s backgroun d documents .

Gal e Researc h Inc . 1999b . "Pipelines , Crud e Petroleum. " Ward's Business Directory of U.S. Private and Public Companies: 1999. Detroit , Ml : Gale s Research , Inc . America n Petroleu mInstitute . Augus t 1998 . Heating Oil

in the United

States. intermediat

e products , includin g input s to the manufactur e o f syntheti c resins , plastic s materials , and nonvulcanize d elastomers , a s well as cycli c organi c intermediate s and dyes/pigments , an d aliphati c an d acryli c chemical s an

d solvents .

2- 6 

# irPetrochemical s ar e intermediat

e product s resulting fro

mth e refiner y process . Petrochemica

l feedstock s includ e naphtha , aliquid obtained fro mrefining crude oil , as wel l as product s recovere d fro

mnatura l gas an d refinery gase s (ethane , propane , an d butane) . Othe

r feedstock s includ e ethylene ; propylene ; normal

- an d iso-butylenes ; butadiene ; an d aromatic s suc

h a s benzene , toluene , an

d xylene . Th

e volum e o f petroleu mliquid s availabl e t

o the petrochemica

l industr y depend s primaril

y o n th e followin g three factors : crud

e petroleu minpu t t o refineries, refiner y proces s configuratio

n an d operating conditions , an

d the demand s an

d price s fo r napth aan d ga s oil i n thei r primar y fue l markets (DOE , EIA , 1999e) . Syntheti c chemical s ar

e associated wit

h the OL D sourc e categor

y whe n the y ar e distribute d fro msyntheti c organic chemica l manufacturin

g industr y (SOCMI ) facilitie s to liqui d terminals . Thes e chemical s ar

e typicall y transported by mean s o

f tan k truc k o r tan k car . Petrochemica

l feedstock s travel by variou s mode s throughou t thei r product life . The distributio n components associated wit h th e OL D sourc e categor

y ar e th e shipment s o

f feedstocks fro mrefinerie s t o liqui d terminal s an d SOCM I facilities . Mos t

often , petrochemical s travel by mean s o f tan k truc k or tan k car ; however , som

e SOCM I facilitie s have pipeline s by whic h their product s ar

e distributed . Syntheti c organic chemica

l an d petrochemica

l distributio n facilitie s ar

e mos t likely to b e classified unde

r th e thre e SI

C code s liste d in Tabl e 2-3 . The tabl e include s th e NAIC S code s tha t correspond t o th e affecte

d SIC-code

d industries . 2.2.1 Overview of

Distribution Service OL D distributio n i s aservic e tha t i s par t o f th e productio n proces s fo

r organi c liquids . Afte r arefining process , petrochemical s migh t b e distribute d to chemica

l production plant s fo

r processing int

o syntheti c chemicals , or

the y migh t b e transporte d to a

n independen

t liqui d termina

l fo r storag e befor

e furthe r processing . I

n addition , independen

t liqui d terminal s ma

y als o receive processed syntheti c chemical s fo r storage . Liquid s store d a

t independen

t liqui d terminal s migh

t b e transported t

o chemica l production plant s or

refinerie s fo

r furthe r processing , the

y migh t b e sen t to ablending/packaging/distribution facility , or the y migh t b e distribute d t o end user s (Abt , 1998) .

2-7 

## A ^P.2 4

Tabl e 2-3 . Principa l OL D Facility Categorie s SI C Cod e SI C Descriptio n NAIC S Code s NAIC S Descriptio n Chemica l Productio n (11 8 surve

y responses ) 282 1 Plastic s Materials , Syntheti c and Resins , and Nonvulcanizabl e Elastomer s 286 5 Cycli c Organi c Crude s and Intermediates , and Organi c Dye s an d Pigment s 32521 1 32519 2 3251 1 32513 2 286 9 Industria

l Organi c Chemicals , NEC 32518 8 3251 1 32519 3 3251 2 32519 9 Plastic s Materia l an d Resi n Manufacturin g Cycli c Crud

e and Pigment Manufacturin g Petrochemica

l Manufacturing 8 Syntheti c Organi c Dy e an d Pigmen t Manufacturin g All Other Basi c Inorgani c Chemica l Manufacturing " Petrochemica

l Manufacturing 8 Ethy l Alcoho l Manufacturin g Industria l Ga s Manufacturin g All Other Basi c Organi c Chemica

l Manufacturing 8

* Onl y par t

o f th e NAIC S industr

y i s mad e u p o f

facilitie s fro mth e correspondin g SIC-code d industry . Source : U.S . Censu s Bureau . Marc h 2000a . "198 7 SI C Matche d t o 199 7 NAICS. " <http://www.census.gov/epc d /naics/NSIC3 B JrTML> . A s obtaine d o n Marc h 13,2000 . 2.2.1.1 Elasticity of

Supply Th e suppl y elasticit y for

syntheti c organi c chemical s an d petrochemical s depend s o n th e ability an d willingnes s o f firms t o scal e u p productio n i n th e fac e o f highe r demand . Suppl y elasticit y refer s t o th e ratio o f

agive n percentag e chang e i n pric e t o aresultin g percentag e chang e i n quantit y supplied . At

agive n poin t

in time , firms ca n b e expecte d t o suppl y a n approximatel y profit

maximizin g quantity , give n thei r availabl e technology . Fo r agive n increas e i n th e pric e o f chemicals , th e increas e i

n quantit y supplie d wil l b e greate r whe n th e producer s of

that chemica l hav e exces s capacit y an d whe n ne w productio n line s for th e chemica l are eas y an d inexpensiv e t o establish . I n 2- 8 

## ?<iP.2 5

thi s analysis , EP

A aggregate s al

l organic chemica

l liquid s int

o asingle market , an

d incorporate s suppl y elasticitie s estimated fo

r othe r analyses . Th

e elasticit y o f suppl y fo r th e organic chemical s marke t i s assumed t

o be 1. 5 (organi c chemical s producers wil

l distribut e 1. 5 percen t mor e organi c liquid s fo r each 1 percen

t increas e i n price) . 2.2.2 Industry Organization Thi s subsection describe s the organization o f th e segment

s o f th e chemica

l industr y most likely t o b e affecte

d b y the NESHA

P regulation an

d provide s specific information o n affecte d OL D facilitie s an

d firms whe

n suc h informatio

n i s available . The sectio

n begin s wit

h adiscussion o

f marke t structure , followe

d b y informatio

n o n facilitie s tha

t distribut e organi c chemical s an

d the firms tha t ow n them . Th e structur

e o f th e affecte d market(s ) i s a

n importan t facto r i n estimatin g th e potentia

l impact s fro

maregulation . Fo

r example , in acompetitiv e marke t wher e eac h produce r ha s littl e marke t power , i t woul d b e difficul

t fo r a n affecte d firmto pas s o

n complianc e cost s to it s consumers . O

n the othe r hand , in a n industr y wit h ver y fe w producer s o r

wher e th e product s ar

e highl y differentiated , i

t ma y be possibl e fo

r affecte d firms t o recove r par t or al l o f th e complianc e cost s throug

h pric e increases . Th

e mos t importan t factor s determining th e competitiv e structur e o f a n industr y ar e th e numbe r o f producers , th e degre

e o f product differentiation , an

d th e presenc e o

f barrier s to entry . The remainde r o f thi s subsection provide s abrie f explanatio n o

f thes e factor s an

d discusse s th e competitiv e structur e o f th e OL D market s i

n term s o f each facto r (CMA , 1995a,b) . Thirty-one companie s produc e an d distribut e organic chemica

l liquids . Thes e companie s include man

y larg e integrate d chemica

l companies . Only on

e OL D compan y tha t distribute s organi c chemical s i s classified as asmall company . Product differentiation i s afor

mo f nonpric e competition used b

y firms t o establis h marke

t powe r i n aspecific produc t

market . Produc t differentiation ma

y resul t fro muniqu e produc t

characteristic s o

r fro mbrand recognition . I

n general , acompan y tha t sell s aproduct

wit h value d characteristic s tha t n o or fe w othe r product s posses s wil l have mor e marke t powe r tha n acompan

y tha t sell s aproduct

tha t ha s n o distinguishabl e characteristic s fro

mothe r product s i n the sam e market . Similarly , market powe r i s create d i

f customer s plac e ahighe

r value o n aproduc t

produced by aspecific company , or brand , eve

n thoug h th e product characteristic s ar

e identica l t o the product s produce d by othe r companies . Th e product s o f conce mto the OL

D sourc e categor

y ar e characterize d by ahig

h degree o f 2- 9


## PSP.2 6

homogeneity . Thus , bran

d loyalt y i s not expected t o b e a n importan

t facto r i n th e organi c chemical s marke t (CMA , 1995a,b ; Arnold , 1989 ; Gale Group , 1999 ; DOE , EIA , 1999e) . Th e numbe

r o f producers an

d the marke

t share s o f th e larges t

firm s ar e importan t determinant s o

f the degree o

f marke t powe r individua l firms ma y have . Th e ter

m"concentration " refer s to th e combined percentag e o f tota l outpu t accounted fo

r b y th e larges t

producer s in th e industry . For

example , th

e four-fir mconcentration rati o (CR4 ) refer s to th e marke t shar e o f th e fou r larges t firms. The highe

r the concentratio n ratio , th e mor e concentrate d th e industry . A marke t i s generall

y considered highl

y concentrated i

f the CR 4 i s greate r tha n 5 0 percent . Th e Herfindahl-Hirschman

n inde x (HHI) i s a

n alternativ e measur

e o f concentration . It

i s equa l t o th e su mo f th e square s o

f th e marke t share s fo r th e larges t

5 0 firms in th e industry . Th e highe r th e index , th e fewe

r th e numbe

r o f firms supplying the industr y an d th e mor e concentrate d th e industr

y i s a t th e top . The Justic e Departmen t use s th e HH

I fo r antitrus t enforcemen

t purposes . Th e benchmar k used b y th e Justic e Departmen

t i s 1,000 , wher

e an y industr y wit h a n HH I les s tha n 1,00 0 i s considere d to b e unconcentrated . The advantag e o f th e HH I ove r th e concentratio n rati o i s tha t th e forme r give s information abou

t the dispersion o

f market shar e among all tiie firms in th e industry , no t

jus t the larges t

firms (Arnold , 1989) . I n general , a

n industr y wit h alarg e numbe

r o f firms an d asmal l concentratio n will b e relatively mor

e competitiv e tha

n a n industr y wit h fe w firms and ahig

h concentration . Firm s tha

t operat e in amor e competitiv e marke

t will b e relativel

y mor e affecte d by ne w regulation s becaus e the y ar e les s likel y to b e abl e to pas s o

n complianc e costs . Tabl e 2- 4 show s concentratio n ratio s b y SI C cod e fo r th e affecte

d OL D industrie s fro

m th e 199 2 Economi c Census . Industr y concentratio n information i s no t ye t availabl e fo

r th e 1997 Economi c Census . Ratio s ar e include d fo

r th e censu s years 198 7 an

d 199 2 (wher

e possible) . For som e SI C codes , dat

aar e availabl e fo

r onl y 1992 . Th e number s i

n Tabl e 2- 5 sho

w that , b y an

d large , th e OL

D industrie s ar

e characterize d by alarg e numbe r o f firms and generall

y unconcentrated markets , indicatin g ahig h degree o f competitivenes s i

n their respective produc t markets . The chemica

l industr y i s undergoin g atrend o

f mergers , acquisitions , an

d genera l industr y consolidation . According t o a n analysi s by Speed (1999) , "th e marke t will [comprise ] fewe

r bu t large r companies , globa

l i n scope , an

d mor e focuse d i n their busines s pursuits. " 2-1 0 

## 2 bP.2 7

Tabl e 2-4 . Concentration Ratios b y SI C Code

8
SI C Code Tota l Number o f Yea r Firms 4 Fir m Chemica l Productio n 2821 : 2865 : 2869 : Concentration Ratio 8 Fir m 20 Fir

m 5 0 Fir

m Plastic s Materials , Syntheti c Resins , an d Nonvulcanizabl e Elastomer s 198 7 28 8 20 % 199 2 24 0 24 % 33 % 39 % 61 %

63 % Cycli c Organi c Crude s an

d Intermediates , Organi c Dye s and 198 7 13 1 34 % 199 2 15 0 31 % Industria l Organi c Chemicals , NE C 198 7 49 1 31 % 199 2 48 9 29 % 50 % 45 % 48 % 43 % 77 %

72 % 68 % 67 % 89 %

90 % Pigment s 96 % 94 % 86 % 86 % Herfindahl Hirschman

n Inde x 24 8 28 4 54 2 42 8 37 6 33 6

° Industr

y concentratio n informatio n i s no t ye t availabl e for

th e 199 7 Economi c Census . Source : U.S . Departmen t o f Commerce , Burea

u ofth e Census . 1992 . Economi c Census . Washington , DC : Governmen t

Printin g Office , <http://www.census.gov/epcd/www/92result.html> . Barrier s t o entr

y ar e the mechanism s through whic h th e tota l numbe r o f firms i n a n industr y ca n b e kept smal l an d ahig h degree o f marke t concentratio n ca

n exist . Wher

e barrier s to entr

y ar e present , ne w firms find i t

impossibl e or

unprofitable to ente

r the market . Barrier s t

o entr y therefor e creat e marke t powe r fo r th e firms tha

t alread y operat e i n th e market . Typically , barrier s to entr y exis t whe n industrie s ar

e capita l intensive , ar

e characterize d b

y significan

t economie s o

f scale , requir e specialize d knowledg e (e.g. , patents) , o r ar e subject t o governmen

t regulation (Speed , 1999) . Whil e relatively capital-intensive , chemica l production i

n genera l i s no t extremely specialized . Thus , th e Agenc y believe s th e barrier s t

o entr y ar e moderate . 2.2.2.1 Facilities Tabl e 2- 5 present s a

n overview o

f the tota l numbe r o f facilitie s fo

r eac h OL D NAIC S code , the tota

l numbe r o f firms potentially affecte

d by the OL

D sourc e category , an

d th e percentag e ofth e sourc e categor y potentially affected .

2-1 1



## ^ 7P.2 8

Tabl e 2-5 . Numbe r o f

Tota l OL D Facilitie s an d Affecte d Facilities , 199 7 NAIC S Cod e NAIC S Descriptio n Tota l Number o f Facilities 8 Tota

l Numbe r of Affected Facilities b % o

f Source Categor y tha t i s Affected Chemica l Productio n 32511 0 Petrochemica

l Mf g 32513 2 Syntheti c Organi c Dye s and

Pigment s 32519 2 Cycli c Organi c Crude s an d

Intermediate s 32519 3 Ethy l Alcoho l Mf g 32519 9 Al l Othe

r Basi c Organi c Chemica l Mf g 32521 1 Plastic s Materials , Syntheti c

and Resins , an

d Nonvulcanizabl e Elastomer s 5 4 11 2 5 0 3 8 67 6 53 2 37 0 25.3 %

8 U.S . Censu s Bureau . Augus t 1999c . "Cycli c Crud e an d Intermediat e Manufacturing. " 799 7 Economic Census, Manufacturing—Industry Series, E97M-3251I , Washington , DC : Govemmen t Printin g Office . b U.S . Environmenta l Protectio n Agenc y (EPA) . 2000 . Technical Support Document

for the Organic Liquids Distribution (Non-gasoline) Industry. Washington , DC : U.S . Environmental Protectio n Agency , Offic e o f Air Quality Plannin g an d Standards . Sources : U.S . Censu s Bureau . Augus t 1999a . "Al l Othe r

Basi c Inorgani c Chemica l Manufacturing. " 799 7 Economic Census, Manufacturing—Industry Series, E97M-3251I , Washington , DC : Governmen t Printin g Office . U.S . Censu s Bureau . Augus t 1999b . "Al l Othe r

Basi c Organi c Chemica l Manufacturing. " 799 7 Economic Census, Manufacturing—Industry Series, E97M-3251I , Washington , DC : Governmen t Printin g Office . U.S . Censu s Bureau . Augus t 1999d . "Ethy l Alcoho l Manufacturing. " 1997 Economic Census, Manufacturing—Industry Series, E97M-325II , Washington , DC : Governmen t Printin g Office . U.S . Censu s Bureau . Augus t 1999e . "Industria l Ga s Manufacturing. " 799 7 Economic Census, Manufacturing

—

Industry Series, E97M-325II , Washington , DC : Governmen t Printin g Office . U.S . Censu s Bureau . Augus t 1999f . "Petrochemica l Manufacturing. " 1997 Economic Census, Manufacturing

—

Industry Series, E97M-325II , Washington , DC : Govemmen t Printin g Office . U.S . Censu s Bureau . Augus t 1999h . "Plastic s Material an d Resi n Manufacturing. " 799 7 Economic Census, Manufacturing

— Industry Series, E97M-3251I , Washington , DC : Govemmen t Printin g Office . U.S . Censu s Bureau . Augus t 1999i . "Syntheti c Organi c Dy e an d Pigmen t Manufacturing. " 799 7 Economic Census, Manufacturing

— Industry Series, E97M-3251I , Washington , DC : Governmen t Printin g Office . 2-1 2 

# P0P.2 9

Althoug h EP A receive d survey s fro monl y abou t

3 2 percen t

(11 7 ou t of 370) 3 of th e univers e o f

organi c liquid s distributor s in th e chemical industry , a n examinatio n o f

th e dat aprovide d i n th e survey s doe s illustrat e genera l characteristic s of

thos e facilities . Th e figures an d table s in thi s sectio n includ e facilitie s classifie d i n NAIC S code s 325211 , i n additio n t o th e 11 7 facilitie s classifie d a s part

o f th e chemical industry . Facilitie s i n NAIC S cod e 32521 1 us e syntheti c organi c chemical s an d petrochemical s a s a n inpu t int o thei r productio n o f

variou s plasti c part s an d products . Th e dat apresente d her e ar e for th e 10 5 facilitie s (ou t

o f 121 ) wh o di d no t

reques t tha t thei r survey s b e considere d classifie d information . Figur e 2- 1 show s th e distributio n o f 10 5 organi c chemica l liquid s distributio n facilitie s acros s 2 6 states . Twenty-nin e percen t of organi c chemical liquid s distributio n facilitie s ar e locate d i n Texas , 9 percen t

ar e locate d i n Louisiana , an d 8 percen t ar e locate d i n Ohio . Capacit y utilizatio n at

organi c chemica l facilitie s i s abou t 8 0 percent . Th e OL D NESHA P i s specificall y conceme d with th e distributio n o f chemicals , rathe r

tha n thei r production . However , afacility' s ability t o stor e an d transfe r chemical s i s considere d i n th e calculatio n o f plan t capacity , s o th e dat abelo w provid e som e indicatio n o f storag e an d transfe r

capacity . Figur e 2- 2 show s almos t

al l organi c chemica l liquid s distributio n facilitie s emplo y mor e tha n 5 0 peopl e an d that

more than 3 5 percen t

o f thos e facilitie s emplo y a

t leas t 50 0 employee s each . 2.2.2.2 Firm Characteristics Althoug h facilitie s ar e th e physica l uni t regulate d b y th e OL D sourc e category , thi s regulatio n ma

y als o affect

th e firms that

ow n th e facilities . Firm s ar e legal busines s entitie s tha t hav e th e capacity t o conduc t

busines s transaction s an d mak e busines s decision s that affec t th e facility . In thi s analysis , th e term s firman d company ar e use d synonymously . Th e chemica l industry i s heavil y dominate d b y corporations , wit h few proprietorship s o r

partnerships .

3 Some portion s of

th e Technical Support

Documen t

(TSD ) repor

t that 11 8 facilitie s in SI C cod e 2 8 returne d surveys . However , th e repor t show s assigne d mode l plan t number s for

onl y 11 7 facilitie s i

n thi s SI C code. , (On e facility , numbere d 30-Q , wa s liste d in th e TS D bu t i s nonexisten t

i n th e databas e compile d fromIC R survey responses. ) Th e TS D faile d t o report amode l number

fo r plan t 32-E , whic h wa s i

n th e database . Facilit y 30- Q wa s exclude d fro manalysi s an d 32- E wa s included . 2-1 3



### O ^P.3 0

Figur e 2-1 . Distributio n o f Organi c Chemical Liquid s Facilitie s tha t Responde d t o th e IC RSurve y 2-1 4 

### -2, 0P.3 1

O 0 ) O ) n c C D o Im. u Q . 45 % 40 % 35 % - 30 % - 25 % - 20 % 15 % 10 % - | 5 % 0 % les s tha n 2 5 2 5 t o 5 0 5 0 t o 1 0 0 1 0 0 t o 25 0 25 0 t o 50 0 Employmen t Rang e ove r 50 0 Figur e 2-2 . Th e Distributio n o

f Organic Chemica

l Liquids Facilitie s tha

tResponded t

o th e IC RSurve y b y Employmen

t Source : Nonclassifie d response s t o th e 199 8 Industr y Specifi c Infonnatio n Collectio n Reques t fo r th e Developmen t

o f an Organi c Liquid s Distributio n Maximu mAchievabl e Contro l Technology . Fir msiz e i s importan

t whe n analyzing th e distributio n o f the regulation's financial impacts . Analysi s o f likel y impact s o

n smal l entitie s i s required unde

r th e Smal l Busines s Regulator

y Flexibilit y Enforcemen

t Ac t (SBREFA ) an d require s th e categorizatio n o f firms a s eithe

r smal l o r large . Th e Smal l Busines s Administration (SBA ) now publishe s genera

l siz e standar

d definition s fo

r smal l entitie s b y NAIC S code. 4 Th

e siz e standard s ar

e define d eithe r by employmen

t or b y annua l firmrevenue , depending o

n the NAIC S code . The SB A siz e definition s fo r all chemica

l industrie s i s defined in term s o f numbe r o f employees . Th

e siz e standar

d fo r thes e NAIC S categorie s range s fro m75 0 t o 1,00

0 employees . A s previousl

y stated , onl

y 11 7 facilitie s (or

3 2 percent

) o f a n estimate d 37 0 tha

t handl e organi c chemica l liquid s responde d t

o th e IC Rsurvey . Thos e facilitie s ar e owned by 3 1 differen

t firms. Onl y on e o f thos e 3 1 firms i s smal

l accordin g to th e SB A smal l busines s standards . Tha

t one smal l firmown s tw o facilitie s tha t distribut e organi c liquids . I

f the 12 1 facilitie s ar

e a n accurat e sample o f

4A s o f October 1,2000 , smal l busines s determination s ar e define d base d o n NAIC S code s rathe r than SI C codes . 2-1 5 

# 3 1P.3 2

th e actua l facilities , w e ca n conclud e tha t

onl y aver

y smal l shar e o f

al l affecte d facilitie s ar e owne d b y smal l businesses . Figure s 2- 3 an d 2- 4 sho w th e distributio n o f surveye d firms b y fir

msiz e a s measure d b y revenu e an d employment ; respectively . I n 1998 , th e majority o f

affecte d firms too k

i n mor e than $ 1 billio n in revenue s (approximatel y 8 7 percent ) an d employe d mor e tha n 10,00 0 peopl e (approximatel y 8 1 percent) .

70 %

w60 % | 50 % o 40 % - a 30 % 8 20 % C D 10 % 0 % Les s tha n $5Mto$5 0 $50Mt o $5 M $500 M $500Mt o $1Bt o $1 B $10 B Company Sales $10Bt o over$100 B $100 B Figur e 2-3 . Th e Siz e Distributio n o f Companie s tha tow n OL D Facilitie s tha tResponde d t o th e IC RSurve y an d ar e Involve d i n Chemica l Distribution , b y 199 8 Sale s (i n $1997 ) Sources : Du n & Bradstreet . 1999 . Compan y Capsules . A s availabl e o n EBSCO .

Gal e Group . 1999 . General Busines s Fil e International (formerl y Busines s ASAP) . Gal e Grou p Collections . A s obtaine d fromInfoTra c Web . <web6.infotrac.galegroup.com/itw> . Hoover' s Incorporated . 1999 . Hoover' s Company Profiles . Austin , TX : Hoover' s Incorporated . <http:/Avww.hoovers.com/> . Compan y websites . Compan y 10

k reports . U.S . Environmenta l Protectio n Agenc y (EPA) . 2000 . Technical Support Document

for the Organic Liquids Distribution (Non-gasoline) Industry. Washington , DC : U.S . Environmenta l Protectio n Agency , Offic e o f

Ai r Qualit y Plannin g an d Standards .

2-1 6

<l^P.3 3

70 % 60 % 

### I 50 % _L o 40 % C D ra 30 % -

I c C D U

. w C D ° - 10 % 0 % * 20 % 

# _•

_ les s tha n 50 0 50 0 t o 1,00 0 1,00 0 t o 5,00 0 5,00 0 t o

10,00 0 10,00 0 t o ove r100,00 0

100,00 0 Numbe r o

f Employee s Figur e 2-4 . Siz e Distributio n o f Companie s tha tow n OL D Facilitie s tha tResponde d t o th e IC RSurve y an d ar e Involve d i n Chemica l Distributio n Sources : Du n & Bradstree t 1999 . Compan y Capsules . A s availabl e o n EBSCO . Gal e Group . 1999 . Genera l Busines s Fil e International (formerl y Busines s ASAP) . Gal e Grou p Collections . A s obtaine d fromInfoTrac Web . <web6.infotrac.galegroup.com/itw> . Hoover' s Incorporated . 1999 . Hoover' s Compan y Profiles . Austin , TX : Hoover' s Incorporated . <http://www.hoovers.com/> . Compan y websites . Compan y 10

k reports . U.S . Environmental Protectio n Agenc y (EPA) . 2000 . Technical Support Document

for the Organic Liquids Distribution (Non-gasoline) Industry. Washington , DC : U.S . Environmental Protectio n Agency , Offic e o f

Ai r Qualit y Plannin g an

d Standards . Vertica l an d horizonta l integratio n ar e importan t

determinant s in analyzin g afirm's potential for impacts . Bot

h measure s ar e concerne d wit h th e type s o f

industrie s in whic h afirmoperates . Vertical integratio n refer s t o th e degre e t o whic h afirmoperate s facilitie s tha t ar e part o f th e sam e suppl y chain . Fo r

example , i f

th e sam e firmown s facilitie s i n th e petroleu mproduction , refining, an d transportatio n industries , i t woul d b e considere d verticall y integrated . Vertica l integratio n i s potentiall y importan t

i n analyzin g firm-level impact s becaus e aregulatio n coul d affec t averticall y integrate d firma

t mor e than on e level . Horizontal integratio n refer s t o th e scal e o f productio n i n a single-produc t

firmo r it s scop e i n amultiproduc t one . A single-produc t

firmi s considere d horizontall y integrate d if

i t own s mor e tha

n on e facility producin g th e sam e product , whic h ma y b e a n advantag e t o th e firm' s ability t o absor b cost s i f not al l o f th e facilitie s are subjec t

t o th e 2-1 7 

# 33P.3 4

regulatio n an d if

th e firmca

n shif t part s o f th e productio n t o th e unregulate d facilities . A multiproduc t

fir mi s considere d horizontall y integrate d i f i t own s facilitie s i n severa l unrelate d industries . Here , horizonta l integratio n ma y improv e afirm' s ability t o absorb complianc e cost s i f onl y on e o r

afe w o f th e industrie s in whic h th e fir moperate s are directl y affecte d b y th e regulation . Firm s producin g an d distributin g organi c chemica l liquid s are generall y integrate d both horizontall y an d vertically , whil e firms only distributin g organi c chemical s ar e not highl y integrated . Th e 3 1 firms tha t

are know n t o ow n chemica l facilitie s that wil l b e affecte d b y th e OL D NESHA P hav e a

n median (average ) profi t

margi n o f

5. 4 (5.3 ) percent . Tabl e 2- 6 show s th e average , median , minimum , an d maximu mprofi t margin s o f

thes e 3 1 firms. Figur e 2- 5 show s th e distributio n o f

profi t margin s amon g th e firms. Tabl e 2-6 . Profi tMargin s o f Firm s tha tResponded t o th e IC RSurve y an d tha tow n Organi c Chemica l Liquid s Distributio n Facilitie s

Media n 5.41 % Averag e 5.28 % Maximu m-4.09 % Minimu m11.83 % Source : Nonclassifie

d response s t o th e 199 8 Industr y Specifi c Informatio n Collectio n Reques t fo r th e Developmen

t o f a n Organi c Liquid s Distributio

n Maximu mAchievabl

e Contro l Technology . 2.2.3 Uses and

Consumers A s wit h petroleu mliquids , th e deman d fo r organi c chemical s depend s primaril y o n thei r en d use . Organi c chemicals , particularl y petrochemicals , play a n importan t

rol e i n society . Petrochemical s ar e usuall y a n intermediat e produc t

that i s converte d int o avariet y o f consume r

an d industrial products . Som e ofth e en d product s includ e plastics , antifreeze , syntheti c fibers, rubber , solvents , an d detergents . Highe r deman d fo r

thes e product s translate s int o highe r deman d fo r

thei r input s (EPA , 1995) . Thi s sectio n list s th e majo r consumer s o f

organi c chemicals , th e purpose s o f chemica l consumption , an d th e factor s affectin g th e elasticity o f deman d fo r

chemicals . Nearl y everyon e i s aconsume r o f chemical s i n som e way . Chemical s ar e use d a s input s int o th e majorit

y of manufacturin g industrie s both domesticall y an d internationally . A s wit h 2-1 8 

# 3^ iP.3 5

45 % 40 % - i | 35 % E 30 % o 25 % - C D g > 20 % - § 15 % £ 10 % 5 % - | 0 % <0 % 0%-3% 3%-5 % Profi t Margi n 5%-10 % >10% Figur e 2-5 . Distributio n o f Companie s Ownin g Organi c Chemica l Liqui d Facilitie s tha t Responde d t o th e IC RSurvey , b y Profi tMargi n Sources : Du n & Bradstreet . 1999 . Compan y Capsules . A s availabl e o n EBSCO .

Gal e Group . 1999 . Genera l Busines s Fil e Internationa l (formerly Busines s A S AP) . Gal e Grou p Collections . A s obtaine d fromInfoTrac Web . <web6.infotrac.galegroup.com/itw> . Hoover' s Incorporated . 1999 . Hoover' s Compan y Profiles . Austin , TX : Hoover' s Incorporated . <http://www.hoovers.com/> . Compan y websites . Company 10

k reports . U.S . Environmental Protectio n Agenc y (EPA) . 2000 . Technical Support Document

for the Organic Liquids Distribution (Non-gasoline) Industry. Washington , DC : U.S . Environmental Protectio n Agency , Offic e o f

Ai r Qualit y Plannin g and Standards . Du n & Bradstreet . 1997 . Industry Norms & Key Business Ratios. Desk-To p Editio n 1996-1997 . petroleu mproducts , th e market s fo r end-us e product s driv e th e deman d fo r individua l chemicals . Th e majo r

industria l consumer s o f

chemical s i n th e Unite d State s ar e housing , moto r vehicles , agriculture , tires , pape r

products , plasti c products , textil e mil l products , apparel , an d furnitur e an d fixture s (Oil

& Gas Journal, 1999) . 2.2.3.1 Characterization of Demand—Derived

Demand Elasticity A s wit h petroleu mproducts , th e pric e elasticit y of deman d for

chemical s depend s o n th e availability o

f substitutes , eithe r

substitut e product s for

th e sam e us e o r

alternativ e productio n processe s that

d o not nee d thi s chemical . Ther e ar e 6 5 HAP s covered ; sinc e th e availabilit y o f substitute s varie s amon g thes e chemicals , s o wil l thei r deman d elasticities . Fo r thi s analysis , 2-1 9 

# 3£~P.3 6

however , th e Agenc

y i s employin

g a n aggregated marke

t model , using ademan

d elasticit y estimate d fo

r anothe r analysi s ofth e chemica

l industry . Thi s deman

d elasticit y i s -1.5 , meanin g tha

t aon e percen t increas e i n th e pric e o f organic chemica

l liquid s would decreas e th

e quantit y demanded b y 1.

5 percent . 2.2.4 Markets A recen t stud y conducted b

y the Chemica

l Manufacturers Association (CMA ) showed tha

t U.S . shipment s o

f chemical s an

d allied product s fo

r 199 8 ha d increased b

y onl y 0. 6 percent compared t o the previou s year . Domesti c deman d was th e mai

n drive r o f thi s increas e a s export s decline d 2. 0 percent , th e resul t o f th e Asi acrisi s an

d the hig h U.S . dollar . Shipment s o f industria l chemicals , however , fel

l b y 6. 9 percent . Import s ros e 8. 5 percent , whic h le d to areduction i n th e trad e surplu s fro

m$19. 1 billion (1997 ) to $13. 4 billion (1998) . Deficit s occurred i n organi c chemicals , pharmaceuticals , and inorgani c chemicals . Th e CM A projected th e overall conditio n o f th e U.S . econom

y t o remain favorabl e through th e first half o f 2000 . Th e financial crisi s i

n Asi aha s com

e to a n end , an d export s rebounded through Jun e 2000 . Wit

h continue d expansio n o

f th e U.S . economy , overall growt h i n chemica

l an d allie d product s production volum e i s expecte d to b e 1. 3 percen t durin g 199 9 (CMA , 1999 ; CMA , 2000) . 2.2.4.1 Market Volumes Marke t volume s fo

r EPA' s analysi s wer

e compiled fro

mpublishe d reports o

f production , imports , an

d export s o

f al l th e chemical s produced o

r distribute d by OL

D facilitie s (ChemExpo , 2000) . Tabl e 2- 7 present s production , import s an d export s in th e aggregated organi c chemica l market , fo r chemical s affecte

d by th e OL

D NESHAP . Tabl e 2-7 . Organic Chemica l Marke tVolumes , 199

7 (IO 6 Mt ) Domesti c Suppl

y 19 1 Import s 1 1 Tota l 20 2 Sources : EP A OL

D Industr y Questionnair e Database ; ChemExpo . <http://www.chemexpo.com> . Report s fo r al l chemical s distribute d b y OLD facilities . Accesse d Jun e 2000 .

2-2 0 

# 3fcP.3 7

2.2.4.2 Market

Prices Th e baselin e marke t

pric e use d fo

r th e organi c chemical s market , $498.6 2 pe r metri c ton , was estimate d a s aquantity-weighte d averag e ofth e individua l chemical price s obtaine d fro m ChemExp o (ChemExpo , 2000) . 2.2.4.3 Future Projections Constant-dollar

shipment s o f

organi c chemical s ar e forecaste d t o increas e at les s tha n 5 percen t annuall y throug h 2002 . Thi s lo w growt h rat e i s expecte d t o resul t fro mslowin g U.S . domesti c market s an d competitio n fromforeig n producers . Competitio n i n th e chemica l industry i s no t onl y increasin g i n foreig n markets , bu t i n domesti c market s a s well . Whil e import s hav e grow n consistentl y sinc e 198 9 (an d no w accoun t for 1 7 percen t

o f demand) , export

prospect s hav e bee n les s positive . Th e Unite d State s i s expecte d t o remai n ane t exporte r bu t th e country' s trad e surplu s i s expecte d t o continu e t o declin e (U.S . Departmen t o f Commerce , 1998,2000) . 2. 3 Distributio n o f

Petroleu m Liquid s Petroleu mliquid s ar e mad e u p of anumbe r o f different liquids : crud e oil , natura l ga s liquids , an d nongasolin e petroleu mproducts . Tabl e 2- 8 show s th e distributio n of petroleu m product s i n 1997 . Sinc e gasolin e i s already covere d b y th e gasolin e distributio n NESHAP , thi s profil e discusse s th e tw o majo r categorie s o f

nongasolin e refined products—fuel s an d liquifie d petroleu mgase s (LPGs) . Th e mai n fue l product s include d i n th e OL D sourc e category ar e distillat e fuel oil , kerosene-typ e je t fuel , an d residua l fue l oil . Distillat e fuel oi l include s diese l oil , heatin g oils , an d industria l oils . I t

i s use d t o powe r

diese l engine s i n buses , trucks , trains , automobiles , an d othe r machinery . I

n addition , i t

i s use d t o heat

residentia l an d commercia l building s an d t o fire industria l an d electri c utility boilers . Kerosene-typ e je t fuel i s primaril y use d in commercia l airlines . Sometime s i t

i s blende d int o heatin g oi l an d diese l fue l durin g period s o f

extrem e col d weather . Residua l fue

l i s use d b y electri c utilitie s t o generat e electricity . I t i s als o use d a s fuel fo r

ships , industria l boile r

fuel , an d heatin g fuel in som e commercia l building s (DOE , EIA , 1999b) . 2.3.1 Affected

Markets Thre e type s o f

petroleu mliquid s ar e covere d b y th e OL D sourc e category—crud e oil , NGLs , an d refine d petroleu mproducts . Tabl e 2- 9 show s th e SI C code s an d NAIC S code s associate d wit

h thei r production . Sinc e crud e oi l an d NGL s ar e th e primary input s int o th e

2-2 1 

# 3 7P.3 8

Tabl e 2-8 . Petroleu mProduct s Produce d a t U.S . Refineries , 199 7 Petroleu mProduc t

Percen t Produce d Moto r gasolin e 45.7 % Distillate fue

l oil 22.5 % Je t fue l . 10.3 % Residua l fue l oi l 4.7 % Stil l ga s 4.4 % Petroleumcok

e 4.6 % Liquefie d petroleu mgase s 4.6 % Asphal t an d road Oi l 3.2 % Petrochemica

l feedstock s 2.9 % Lubricant s 1.2 % Other 1.4 % 'o Source : U.S . Departmen t o f Energy , Energ y Informatio n Administration . Jul y 1999b . Petroleum: An Energy Profile 1999. DOE/EIA-0545(99) . productio n o f

refine d petroleu mproducts , th e discussio n i n thi s sectio n focuse s o n th e consumer s of , deman d for , an d pric e elasticitie s o f th e refined petroleu mproduct s (DOE , EIA , 1999e) . Petroleu mliquid s ar e input s t o virtuall y every industry i n th e Unite d States . Crud e oi l become s gasoline , diese l fuel , an d je t fuel , whic h affect s th e transportatio n industry an d facilitate s th e distributio n o f

manufacture d good s an d th e transportatio n industry . Refinerie s separat e crud e oi l int o petrochemica l feedstock s tha t ar e use d a s input s i n th e chemica l industr y an d eventuall y becom e plasti c o r

syntheti c rubbe r

products , automobil e lubricant s o r antifreeze , cleanin g compounds , o r

cosmetics . LPG s als o becom e input s int o chemica l compound s o r fue l for househol d o r

far muse . 2.3.2 Production/Service Overview OL D distributio n i s aservic e tha t i s part of th e productio n proces s for petroleu mliquids . Organi c liquid s first

ente r th e pat h o f th e OL D sourc e category at th e poin t of custod y transfer , shortl y before th e refiner

y stage . Pipeline s carry crud e oi l and/o r NGL s fro mproductio n fields int o 2-2 2

^P.3 9

Tabl e 2-9 . Principa l OL

D Facilit y Categorie s SI C Cod e SI C Descriptio n NAIC S Code Petroleu mRefiner

y (5 6 surve

y responses ) 291 1 PetroleumRefining Liqui d Termina l (3 2 surve y responses ) 422 6 Specia

l Warehousin g an

d Storage , NEC 3241 1 4931 1 4931 9 Crud e Oi l Pipelin e Pumping/Breakou t Statio n (24 surve

y 461 2 Crude PetroleumPipeline s Petroleu mTermina l (1 0 surve y responses ) 516 9 517 1 Chemical s an

d Allie d Products , NEC PetroleumBul

k Station s an

d Terminal s 4861 1

4226 9 4227 1 45431 1 45431 2 NAIC S Descriptio n

Petroleu mRefinerie s Genera l Warehousin g an

d Storag e Othe r Warehousin g an

d Storag e responses ) Pipelin e Transportatio n o

f Crud e Oil Othe r Chemica l and Allie d Product s Wholesaler s PetroleumBul

k Station s and Terminal s Heatin g Oi

l Dealers * LP Ga s Sold Vi aRetai l Method "

* Onl y par

t o f thi s NAICS-code d industr y consist s o f

facilitie s that

woul d als o b e classifie d i n th e correspondin g SI C code . Source : U.S . Censu s Bureau . Marc h 2000a . "198 7 SI C Matche d t o 199 7 NAICS. " <http://www.census.gov/epcd/naics/NSIC3B.HTML> . A s obtaine d o n Marc h 13,2000 . th e refineries . Along th e way , th e liquid s ar e channeled through crud

e oil pipeline stations , whic h ar e use d fo r surg e capacity , sorting , measuring , rerouting , an d temporar y storag e o

f th e transporte d liquid . Crud

e oil pipelin e station s ar

e the first poin t o f OL D regulation fo

r petroleu mliquids . Fro mthe crud e oil pipelin e station , crude oil an d NGL s ar e transporte d to apetroleum refinery ; crud

e oil ca n als o b e transporte d to a

n independen

t liqui d termina

l (eithe r aliqui d termina

l o r apetroleu mterminal) . Petroleumrefinerie s proces s crud e oil and/o r NGL s int o refined petroleu mproduct s (includin g gasoline , distillat e fue l oil , residua

l fue l oil , liquified petroleumgases , an d petrochemicals) .

2-2 3 

# 3 1P.4 0

Afte r th e refinin g process , th e refined petroleumproduct s migh t b e distribute d t

o on e o f thre e destinations—refined petroleu mproduct s migh

t b e distribute d t o en

d user s belonging to differen t industrie s o

r the y migh t b e transporte d t

o a n independen

t liqui d termina

l fo r storag e befor

e furthe r processing . Liquid s store

d a t independen

t liqui d terminal s migh

t b e transporte d t

o chemica l productio n plant s o

r refineries fo

r furthe r processing , the

y migh t b e sen t to a blending/packaging/distributio n facility , or the y migh t be distribute d to en

d users . 2.3.2.1 Elasticity of

Supply The pric e elasticit

y o f supply , o r own-pric e elasticit

y o f supply , i s ameasur

e o f th e responsivenes s o

f producers t

o change s in th e pric e o

f aproduct . Th e pric e elasticit y o f suppl y indicate s th e percentag e chang e i n th e quantit

y supplie d o

f aproduct resultin g fro

meac h 1 percent chang e i n th e pric e o

f the product . The EI A fo r th e petroleu mrefinery NESHA

P (EPA , 1995 ) econometricall y estimate d th e pric e elasticit

y o f suppl y fo r five petroleumproduct s (moto r gasoline , je t

fuel , residua

l fue l oil , distillate fue

l oil , an d LPGs) . Th

e pric e elasticit

y o f suppl y fo r th e five petroleumproduct s wa s estimate d to b e 1.24 . Foreig n suppl y i s assumed t o have th e sam e pric e elasticit

y o f suppl y a s domesti c supply . A suppl

y elasticit y o f 1.2 4 i s considere d elastic , becaus e i n respons e to aone percent increas e i n the marke

t price , th e quantit

y of petroleu mproduct s woul d increas e by mor e tha n 1 percent . 2.3.3 Industry Organization Thi s section describe s th e organizatio n o f industrie s tha

t distribut e petroleumliquids , includin g marke

t structure , the characteristic s o f distributio n facilities , an

d th e firms tha

t ow n them . Overall , th e petroleu

mliquid s distributor s fac e alarg e degree o f competitio n fro

mfellow distributors . Thi s section describe s th e producers , produc t differentiation , market

concentration , and barrier s t

o entry . Supplier s i n the petroleu

mindustr y ca n b e divide d int

o tw o principa

l type s o f firms:

• "Majors " ar

e large companie s tha

t ar e typically full

y verticall y integrate d an

d operat e facilitie s i n al l ofth e differen

t petroleumsector s (i.e. , exploration , production , transportation , refining , and marketing) .

2-2 4 

### (AOP.4 1

• "Independents " ar

e smaller , nonintegrated companie s tha t generall y specializ e i

n on e aspect , suc h a s crud e oi l exploration an

d productio

n o r product marketing (DOE , EIA , 1999e) . Historically , major

s hav e dominated th

e petroleu mindustry . However, the major s recently bega

n a trend o f selectiv e refining/marketin

g divestitur

e tha t reduced thei

r shar e o f U.S . refining capacit

y fro m7 2 percen

t i n 199 0 t o 5 4 percen

t i n 1998 . Ove

r the sam e period , th e shar

e o f th e independent s ros e fro

m8 percen

t to 2 3 percent . Petroleu mproducts ar

e produced according t

o qualit y grad e specification s an

d therefor e do no t var y muc h fro mon e another . Bran

d loyalt y i s not expected t o b e a n importan

t facto r i n th e petroleu mproducts marke

t (DOE , EIA , 1999e) . Tabl e 2-1 0 show s concentration ratio s b y SI C cod e fo r the affecte d OL D industrie s involved i n petroleu mproduct distribution , based o

n dat afro mth e 199 2 Economi c Census . (Concentration informatio

n by NAIC S cod

e fro mth e 199 7 Economic Censu s i s no t

ye t available. ) Industr y concentration information i s not ye t availabl e fo

r th e 199 7 Economi c Census . Ratio s ar e included fo

r the censu s year

s 1987 an d 199 2 (wher

e possible) , althoug

h onl y 199 2 dataar

e availabl e fo

r som e SI C codes . Th e numbers i

n Tabl e 3-7 sho

w that , b y an d large , th e petroleum liquid s distribution industrie s ar e characterize d b

y alarg e numbe

r o f firms an d generall y unconcentrated markets , indicating ahig h degre e o f competitivenes s i

n their respective produc t markets . Th

e exception i s crude oil pipelin e stations , whic h ha s relatively fe

w firms (52 ) an

d hig h concentration ratio s (aCR

4 o f 60. 3 percen

t and aCR 8 o

f 79. 7 percent) , indicatin g ahig h degre e o f concentration . Thes e numbers ar e not surprisin g give

n tha t th e pipelin e industr

y i s highl y capita l intensiv e (se

e discussion o

n barrier s to entry , above . I n addition , FER

C legislate s an

d monitor s the liquid s pipelin

e industries . FER

C ensure s fai

r acces s to pipelin e transportatio n a t reasonable rates . Interestingly , the vast

majorit y o f crude oil pipelin e companie s wit h corporat e office s i n th e Unite d State s ar e operate d as subsidiarie s o

f othe r corporat e entities , mostl

y majo r oil companies . Onl

y a fe w ofth e pipelin

e companie s ar

e independently liste d o

n an y stoc k exchang e (Gal e Research , Inc. , 1999b) . Recently , tw o trend s i

n th e petroleummarke

t have affecte

d th e numbe

r an d marke t share s o f firms—mergers/joint

venture s an

d divestitures . Ove

r the pas t fe w years , anumbe

r o f merger s an d joint venture s hav

e bee n undertake

n i n a n effor t t o cu t cost s an d increas e profitability . Thi s merge r activit y has occurred amon

g the larges t

firms (as bes t

illustrate d b

y th e recently approved 2-2 5

* / /P.4 2

Tabl e 2-10 . Concentratio n Ratio s b y SI C Code 3

Tota l SI C Number o f Code Yea r Firm s Petroleu m Refiner

y 2911 : PetroleumRefining

198 7 20 0 199 2 13 2 4 Fir m

32 % 30 % Concentratio n Rati o

8 Fir m

52 % 49 % 2 0 Fir

m

78 % 78 % 5 0 Fir

m

. 95 % 97 % Herfindahl Hirschmann Inde x

43 5 41 4 Liqui d Termina

l 4226 : Specia

l Warehousin g an

d Storage , NE C 199 2 1,21 2 27 % 36 % 50 % 64 % NA Crud e Oi l Pipelin e Statio n 4612 : Crude PetroleumPipeline s

199 2 5 2 60 % 80 % 97 % 10 % N A Petroleum Termina

l 5169 : Chemical s and Allie d Products , NEC

199 2 7,44 6 27 % 35 % 50 % 65 % NA 5171 : Petroleu mBul

k Station s and Terminal s 199 2 8,26 6 21 % 34 % 53 % 64 % N A

" Concentratio n informatio n b y NAIC S cod e fromth e 199 7 Economi c Censu s i s no t ye t available . Source : U.S . Departmen t o f Commerce , Burea

u o f th e Census . 1992 . Economi c Census . Washington , DC : Govemmen t

Printin g Office , <http://www.census.gov/epcd/www/92result.html> . acquisitio n o f

U.S.-base d Amoc o Corporatio n b y th e UK-base d Britis h Petroleu man d th e announce d mega-merge r

o f Exxo n an d Mobi l Corporation ) a s wel l a s amon g independen t refiner s an d marketer s (e.g. , th e independen t refiner/markete r

Ultramar Diamon d Shamroc k

[UDS ] acquire d Tota l Petroleu mNorth Americ ai n 199 7 an d announce d ajoin t ventur e with Phillip s Petroleu min Octobe r

1998 , whic h was late r

abandoned ) (DOE , EIA , 1999d) .

2-2 6 

## V(lP.4 3

A s explained above , barriers t o entr y ar e a n importan t componen

t o f th e marke t structure . A s indicate d above , commo n carrie r pipeline s i n th e Unite d State s ar

e governmen

t regulated due t

o th e industry' s structure , whic

h ca n be characterized as anatura l monopoly . Th

e crude oi l pipeline industr y i s capita l intensive . Start-u

p costs ar e high , an d entr y int o the industr

y i s restricted , as i s indicate d by th e smal

l numbe r o f firms operatin

g wit h headquarter s i

n th e United States . However , sinc e the day-to-da

y maintenanc e o

f capital-intensiv e industrie s tend s to b e relativel y moderate , successfu l companie s withi

n the pipeline industrie s have bee n able t o tak e advantag e o

f economie s o f scale . 2.3.3.1Facilities Althoug h EP A has received survey s fro

monl y abou t 4 5 percen t (12 6 ou t o f 281 ) o f the univers e o f OL D i n the petroleu

mindustry , a

n examination o

f th e dat aprovide d i

n th e survey s illustrate s genera

l characteristic s o

f thos e facilities . Th e dat

apresented her

e ar e fo r th e 11 8 facilitie s (ou t o f 126) who di d not

reques t tha t thei r survey s b e considere d classified information . Figur e 2- 6 show s tha

t ofth e 11 8 nonclassified facilities , 3 1 percen t o f petroleumliquid s distributor s ar

e located i n Texas , 1 2 percen

t ar e i n Louisiana , an

d 1 0 percen

t ar e locate d i n Alaska . Facilitie s i n NAIC S cod

e 3241 1 wer

e operating a

t 9 1 percen t capacit y i n 199 8 an d 199 7 according t

o th e U.S . Censu s Burea

u (U.S . Censu s Bureau , 1999f) . Figur e 2- 7 show s tha

t almos t 4 0 percen t o f facilitie s involved i

n the distributio n o

f petroleumliquid s employ fewe r tha n 2 5 peopl e on-site , while anothe

r 4 0 percen t o f facilitie s employ mor

e tha n 25 0 employee s each . 2.3.3.2 Firm Characteristics Tabl e 2-1 1 present s a

n overvie w o f th e tota l numbe r o f firms fo r eac h petroleumOL

D SIC code , the tota

l numbe r o f firms potentiall

y affecte d by th e OL

D sourc e category , and th e percentag e ofth e sourc e categor y potentially affected . The OL D sourc e categor

y i s heavil y dominated by firms organize d a s corporations . For example , i n 1987,17 7 o

f 20 0 petroleu

mrefineries (or

88. 5 percent

) wer e classified as corporations . I

n 1992,91 4 o

f 1,21 2 liqui d terminal s (or

75. 4 percent) , an

d 4 9 o f 5 2 crude oil pipeline station s (o

r 94. 2 percent

) wer e classified a s corporation s (DOE , EIA , 1999e ; Speed , 1999) .

2-2 7 

# H3P.4 4

Figur e 2-6 . Locatio n o

f Petroleu mLiquid s Distributor s tha t Responde d t o th e IC RSurve y 2-2 8 

# IHP.4 5

les s tha n 2 5 2 5 t o 5 0 5 0 t o 100 10 0 t o 25 0 25 0 t o 50 0 Employmen t Rang e ove r50 0 Figur e 2-7 . Th e Distributio n o f Petroleu m Liquid s Facilitie s tha

tResponde

d t o th e ICR Surve y b y Employmen t Source : Nonclassifie d response s t o ui e 199 8 Industr y Specifi c Infonnatio n Collectio n Reques t for th e Developmen t

o f a n Organi c Liquid s Distributio n MaximumAchievabl e Contro l Technology . Tabl e 2-1 2 present s th

e SB A smal

l busines s standard s fo

r th e OL D sourc e categor

y and als o show s th e numbe

r o f smal l firms i n th e industry . The SB A siz e definition s fo r mos t OL D industrie s i s define

d i n term s o f employees . The siz e standar d fo r thes e NAIC S categorie s range s fro m10 0 employee s in th e petroleumtermina l industr y t o 1,50 0 employee s fo

r petroleum refineries 5 an

d crud e oil pipeline stations . EPA' s surve

y o f OL D facilitie s provide s dat

ao n firms owning facilitie s affecte d b y th e OL D NESHAP . Th e 12

6 surveye d facilitie s ar

e owne d b y 4 5 companies . According t o SB A standards , 9 percen

t ( 4 ou t o f 45 ) o f thos e companie s ar

e small businesses .

5 I n additio n t o th e maximu mnumber o f employees , smal l petroleu mrefinin g firms ma y no t hav e mor e tha

n atota l inpu t capacit y of 75,00 0 barrel s per

da y o f petroleum-base d inputs , suc h a s crud e oil . 2-2 9

^ ^ ~P.4 6

Tabl e 2Figur<&ti*nlHirdbf-Ta ^ Mfert^dHifni^sll9^ftr msiz e a s measure d b y -firmr . tnn k

i n mm» - rpypniip , ,nn d nmplnymFn t Tri p mnjnrit y n f nffprtP. H firmr. tnn V i r i thn n $ 1 hillin n i n ravennps i n NAIC S Cod e NAIC S Descriptio n Tota l Numbe r of Tota l Numbe r

of Affected Establishments 8 Facilitie s % o f Sourc e Category tha t i s Affecte d Petroleu mRefiner

y 3241 1 PetroleumRefinerie s Liqui d Termina l 4931 1 Genera

l Warehousing an

d Storag e 4931 9 Othe

r Warehousing an

d Storag e 24 4 391 1 121 3 11 1

9 4 45.5 %

1.8 %

Crud e Oi l Pipelin e Statio n 4861 1 Pipelin e Transportatio n o f Crude Oil 482 3 5 7.3 % Petroleu mTermina l 4226 9 Othe

r Chemica l an d Allie d Product s Wholesaler s 4227 1 PetroleumBul

k Station s and Terminal s 45431 1 Heatin g Oi l Dealer s 45431 2 L P Ga s Dealer s 8,89 2 6,72 9 565 7 662 3 41 " 0.1 %

U.S . Censu s Bureau . Februar y 1998 . "Statistic s for

Industry Group s an d Industries. " 1997 Economic Census, Manufacturing—Industry Series , E97M-325II . Washington , DC : Governmen t Printin g Office . U.S . Censu s Bureau . September 1999g . "Petroleu mRefinery. " 1997 Economic Census/ Manufacturing—Industry Series. E97M-3251I , Washington , DC : Governmen t Printin g Office . U.S . Censu s Bureau . Januar y 2000c . "Transportatio n an d Warehousing. " 799 7 Economic Census, Manufacturing

—

Industry Series. E97M-3251I , Washington , DC : Governmen t Printin g Office . U.S . Censu s Bureau . Januar y 2000d . "Wholesal e Trade. " 199 7 Economi c Census , Manufacturing—Industr y Series . E97M-3251I , Washington , DC : Governmen t Printin g Office . U.S . Censu s Bureau . Marc h 2000b . "Retai l Trade. " 1997 Economic Census, Manufacturing

— Industry Series , E97M-325II . Washington , DC : Govemmen t Printin g Office . Thi s i s th e combine d estimate d number of affecte d facilitie s i n thi s industry .

2-3 0 

# HbP.4 7

Tabl e 2-12 . Smal l Busines s Siz e Standard s fo r OL D Industrie s NAIC S Cod e NAIC S Descriptio n SB A Smal l Busines s Standar d Petroleu mRefiner

y 3241 1 Petroleu

mRefinerie s Liqui d Termina

l 4931 1 Genera

l Warehousing an

d Storag e 4931 9 Othe

r Warehousing an

d Storag e 1,50 0 employee s an

d 75,00 0 barrel s pe r da y capacit y of petroleum-base d inputs 8 $18.5millionb Crud e Oi l Pipelin e Station 461 2 Crude Petroleu mPipeline s 1,50 0 employee s Petroleum Termina

l 4226 9 Chemical s an

d Allie d Products , NE C 4227 1 PetroleumBul k Station s an

d Terminal s 45431 1 Heatin g Oi

l Dealer s 45431 1 L P Ga s Dealer s 10 0 employee s 10 0 employee s $9. 0 million $5. 0 millio n

" Petroleum-base d input s includ e crud e oi l o r bon afide feedstocks . b Th e SB A smal l busines s standard fo r NAIC S cod e 49 3 represent s annua l firmrevenue . Fir msir e b y revenu e i s no t availabl e i n Statistics of

U.S. Businesses 1996. Sources : Small Busines s Administration . "Smal l Busines s Siz e Standard s Matche d t o Nort h American Industr y Classificatio n Syste mCode s Effectiv e Octobe r 1,2000. " Speed , Philli p J . "Th e Changin g Competitiv e Landscap e o f th e Chemical Industry. " Chemicalbond. <http://www.socma.org/bond/featurel.html> . A s obtaine d o n September 2,1999 . U.S . Departmen t

of Energy , Energ y Informatio n Administration . Jul y 1999b . Petroleum: An Energy Profile 1999. DOE/EIA-0545(99) . Washington , DC . 199 8 an d emplo y mor e tha n 5,00 0 people . Th e industr y exhibit s ahig h degre e o f vertica l integratio n wit

h man y firms operatin g i n mor e tha n on e secto r (DOE , EIA , 1999e) . Fo r example , th e crud e petroleu mpipelin e industry i s dominate d b y gian t oi l companie s wit

h asset s i n man y o f

th e downstreamsector s of

th e industry (Gal e Research , Inc. , 1999b) . Of th e tw o type s o f

petroleu m firms, major s ar e generall y fully integrate d an d operat e facilitie s i n al l th e differen t

sectors . Independents , o n th e othe r hand , are nonintegrate d an d generall y specializ e i n on e aspect , suc h a s

2-3 1 

# MyP.4 8

0 ) O ) C O c C D o w V a 70 % 60 % - 50 % - 40 % 30 % 20 % 10 % -\ 0 % 

# • • Less tha n $5Mto$5 0 $50Mt o $500 M t o $5 M $500 M $1 B $1 B t o $ 1 O B t o ove r $1 00 B $10 B $100

B Compan y Sales Figur e 2-8 . Th e Siz e Distribution o f Companies tha

tow n OL D Facilitie s thatResponde d t o th e IC RSurve

y an d ar e Involve d i n th e Distributio n of

Nongasolin e Petroleu

m Liquids , b y 1998 Sale s (i n $1997 ) Note : Sale s dat aar e fro m199 8 bu t were converte d int o 199 7 dollar s t o facilitat e compariso n wit h othe r figure s reporte d i n thi s profil e an d allo w eas y compariso n wit h estimate d complianc e costs , whic h ar e calculate d i n 199 7 dollars . Sources : Du n & Bradstreet . 1999 . Compan y Capsules . A s availabl e o n EBSCO .

Gal e Group . 1999 . Genera l Busines s Fil e Internationa l (formerl y Busines s ASAP) . Gal e Grou p Collections . .A

s obtaine d fromInfoTrac Web . <web6.infotrac.galegroup.com/itw> . Hoover' s Incorporated . 1999 . Hoover' s Compan y Profiles . Austin , TX : Hoover' s Incorporated . <http://www.hoovers.com/> . Compan y websites . Compan y 10

k reports . U.S . Environmenta l Protectio n Agenc y (EPA) . 2000 . Technical Support Document

for the Organic Liquids Distribution (Non-gasoline) Industry. Washington , DC : U.S . Environmenta l Protectio n Agency , Offic e o f

Ai r Qualit y Plannin g an d Standards . crude oil exploratio n an

d production o

r produc t marketing (DOE , EIA , 1999e) . Similarly , majo r petroleumcompanie s ar

e horizontally integrated , but th e smalle

r independen

t firms typically operat

e onl y on e refiner y each an d ar e therefor e not horizontally integrate d (EPA , 1995) . Throughou

t th e 1990s , th

e U.S . refining an

d marketin g industr

y wa s characterize d b

y unusuall y lo w product margins , lo

w profitability , selectiv e retrenchment , an d substantia l restructuring . Durin g 1997 , th e profitabilit y o f U.S . refining and marketin g wa s the highes t sinc e 2-3 2 

# MP.4 9

0 ) D ) C S 4 * * c o o 0 ) Q . 70 % 60 % 50 % 40 % 30 % 20 % - 10 % - 0 % les s tha n 50 0 50 0 t o 1,00 0 1,00 0 to

5,00 0 5,00 0 to

10,00 0 10,00 0 t o ove r 100,00 0

100,00 0 Numbe r o

f Employee s Figur e 2-9 . Siz e Distributio n o

f Companie

s tha tow n OL D Facilitie s tha

tResponde

d t o the IC RSurve y an d are Involved in the Distribution of Nongasoline Petroleu

m Liquids Sources : Dun & Bradstreet . 1999 . Company Capsules . A s availabl e o n EBSCO . Gal e Group . 1999 . General Busines s Fil e International (formerl y Busines s ASAP) . Gal e Grou p Collections . A s obtaine d fromInfoTra c Web . <web6.infotrac.galegroup.com/itw> . Hoover' s Incorporated . 1999 . Hoover' s Company Profiles . Austin , TX : Hoover' s Incorporated . <http://ww w .hoovers.com/> . Company websites . Company 10

k reports . U.S . Environmental Protectio n Agenc y (EPA) . 2000 . Technical Support Document

for the Organic Liquids Distribution (Non-gasoline) Industry. Washington , DC : U.S . Environmental Protectio n Agency , Offic e o f

Air Qualit y Plannin g an d Standards . 1989 , whic h was i n par t achieved b

y lo w energ y cost s as wel

l a s cost-cuttin g measures , including a numbe r o f mergers an

d join t venture s i n th e downstrea

msector (DOE , EIA , 1999d) . The crude petroleu mpipeline industr

y ha s experienced modes t

but stead y growt h sinc e 1993 . A s aresult, compan y profits have als o increased . Thi s trend ha s bee n aresult o f lowe r operating cost s an

d moderat e expanse s i

n deliverie s (Gal

e Researc h Inc. , 1999b ; DOE , EIA , 1999a) . During 1999 , Majo r U.S . energ

y companie s experienced "5 0 percen t increase s i

n cas h flow s fro

moil an d gas production, " bu

t profit s wer

e uneven , reflecting volatilit y i n petroleu mprice s (U.S . DOE , EIA , 2000 , 2001) . During 2000 , petroleu mproducer s almos t

uniforml y experience d tremendou s increase s i n profits ; fo

r some , recor

d level s o f ne t incom e wer e reported . For

asample o

f 1 1 majo r

2-3 3 

# ItP.5 0

oil companies , profits increased b y amounts ranging fro

m5 8 percen

t to 2,38 7 percent. 6 Th e averag e increas e i

n profits ove

r th e perio d 1999 to 2000 fo

r thes e oil companie s was 36 6 percent . Tabl e 2-1 3 show s that , fo

r the firms tha

t ow n the 12 6 facilitie s tha

t responded t

o the EP A survey, 7 th e averag e (median ) profi t margi n wa s (4.7 ) 4. 3 percent . Figur e 2-1 0 show s the distributio n o

f profi t margin s amon

g firms tha t ow n petroleu mliquid s distributors . 2.3.4 Uses and

Consumers Fiv e majo r economic sectors consum

e petroleumproduct s (DOE , EIA , 1999e) : th e residentia l sector , th e commercia

l sector , th e industria

l sector , th e transportatio n sector , an d th e electri c utilit

y sector . Th e deman

d fo r petroleu mproduct s i s influenced by severa l factors , includin g crud

e oil prices , economi c growt

h trends , an

d weathe r conditions . Lo

w oil price s ten d to stimulat e demand . Deman d als o increase s during period s o f economi c expansion , particularly in th e industria l an d transportatio n sectors . Economic expansion s lea d t o a n increas e i

n th e productio n o

f goods , whic

h contribute s in tur

n t o a n increas e i

n th e deman

d fo r transportatio n o

f ra w material s an

d th e deliverie s o

f finished products . Petroleu mdemand i s als o influenced b y weathe r conditions . Extrem e weathe r tend s t o eithe r increas e o r decreas e th e us e o

f heatin g oi l and electricity , whic h contribute s to th e deman

d fo r petroleu mproducts . Weathe

r ca n als o contribut

e t o th e seasona

l variation s i

n demand fo

r transportation fuel s (such a s gasoline) . 2.3.4.1 Characterization of Demand

— Derived Demand Elasticity Th e demand fo

r petroleu mi s als o influenced b y th e pric e o f petroleu mitself

an d th e pric e o

f availabl e substitutes . Th e degre e t o whic h th e pric e o

f petroleuminfluence s th e quantit y o f petroleumproduct s demanded i s calle d the pric e elasticit y o f demand . Generall

y speaking , th e pric e elasticit

y o f deman d represent s th e percentag e chang e i n the quantit

y demanded resultin g fro

m a1 percen

t chang e i n th e pric e o

f the product . Tabl e 2-1 4 list s th e pric e elasticitie s o f deman d fo r

6 Se e U.S . SE C 10- K

report s for

Amerad aHess , Anadarko , Atlanti c Richfield , Chevron , CITGO , Conoco , Exxo n Mobil , Occidental Petroleum , Phillip s Petroleum , Sunoco , and Texaco , <http://www.sec.gov/cgi-bin/srch

edgar x 'Forty-fiv e firm s own surveye d facilitie s distributin g petroleu mproduct s o r performin g merchan t

distribution . Profit , employment , an d sale s dat awere identifie d for onl y 4 3 o f

thos e facilities . 2-3 4 

# 5 0P.5 1

Tabl e 2-13 . Profi tMargin s o f Firm s tha tow n Organi c Chemica l Liquid s Distributio n Facilitie s tha tresponde d t o th e IC RSurve y

Media n Averag e Maximu m Minimu m 4.34 %

4.73 % 34.74 % -6.94 % Source : Nonclassifie d response s t o th e 199 8 Industry Specifi c Informatio n Collectio n Reques t fo r th e Developmen t

o f a n Organi c Liquid s Distributio n Maximu mAchievabl e Contro l Technology .
45 % 40 % | 35 % - E 30 % - o 25 % - % 20 % - g 15 % | 10 % -

I 5 % - 0 % 

# L M 

# •

<o % 0%-3% 3%-5% Profi t Margi n 5%-10% >10 % Figur e 2-10 . Distributio n o f Companie s Ownin g Petroleu m Liqui d Facilitie s tha t Responde d t o th e IC RSurvey , b y Profi tMargi n Sources : Du n & Bradstreet . 1999 . Compan y Capsules . A s availabl e o n EBSCO . Gal e Group . 1999 . General Busines s Fil e Internationa l (formerl y Busines s ASAP) . Gal e Grou p Collections . A s obtaine d fromInfoTra c Web . <web6.infotrac.galegroup.com/itw> . Hoover' s Incorporated . 1999 . Hoover' s Compan y Profiles . Austin , TX : Hoover' s Incorporated . <http://www.hoovers.com/> . Company websites . Company 10

k reports . U.S . Environmental Protectio n Agenc y (EPA) . 2000 . Technical Support Document

for the Organic Liquids Distribution (Non-gasoline) Industry. Washington , DC : U.S . Environmental Protectio n Agency , Offic e o f

Air Qualit y Plannin g and Standards . Dun & Bradstreet . 1997 . Industry Norms & Key Business Ratios. Desk-To p Editio n 1996-1997 . 2-3 5 

# SiP.5 2

Tabl e 2-14 . Estimates o

f Pric e Elasticit y o f Deman d for Petroleu

m Product

s Je t fue l : -0.1 5 Residua l fue l oi l -0.6 1 t o -0.7 4 Distillat e fue l oi l -0.5 0 t o -0.9 9 Liquifie d petroleu mgase s -0.6 0 t o -1. 0 Source : U.S . Environmental Protectio n Agenc y (EPA) . Jul y 1995 . Economic Impact Analysis for the Petroleum Refinery NESHAP, Revise d Draf t for Promulgation .

severa l o f th e majo r petroleu mproducts . I

n modelin g the demand fo

r th e composit

e petroleu m product , EP

A ha s assumed ademan

d elasticit y of-0.6 . Th e elasticit

y estimate s indicat

e tha t eac h o f thes e product s ha s inelasti c demand . Regulator y contro l cost s ar

e mor e likely t o b e pai d by consumer s o f product s wit

h inelasti c demand a s compare d to product s wit h elasti c demand , al

l othe r factor s hel d constant . Pric e increase s fo r product s wit

h inelasti c deman

d lea d t o revenue increase s fo

r th e producers . Thus , on

e ca n predic t tha t pric e increase s resultin g fro mimplementation o

f regulator y contro l cost s will lea

d t o highe r gros s revenue s fo

r the producer s (EPA , 1995) . Deman d become s mor

e elasti c wit

h th e availabilit

y o f substitute s and th e passag e o f time. I n th e shor t run , ther e ma y no t b e substitute s readily availabl e fo r consumption . However , ove r time, consumer s hav e the opportunit y to adjust t o th e pric e increas e and wil l see k alternatives . I

n th e cas e o f th e petroleu

mindustry , a s th e price s o

f crude oil an

d petroleumproduct s increase , consumer s ma

y no t b e able to respond immediately . Th e short-run demand elasticit y i s inelasti c becaus e petroleu

mplay s acritica

l rol e i n today' s lifestyle s (Oil

& Gas Journal, 1999) . A s time passes , consumer s ca

n adjus t to pric e changes , an

d consume r behavior ma y change , an

d th e pric e elasticit y o f demand wil

l b e higher . 2.3.5 Markets The petroleu

mindustr y i s amajo r sector i n th e U.S . economy . A significan t portion o f th e petroleu mconsumed domesticall

y i s imported . The industr

y experience d relativel

y hig h price s i n 199 6 an d 1997 ; however , petroleu

mprice s decline d substantially i n 199 8 (Gale Research , Inc. , 1999b) . 2-3 6 

# £?.2.3.5.1 Market Volumes Petroleu mrefinin g i s on e ofth e leadin g manufacturin g industrie s i n th e Unite d States . Th e valu e o f shipment s b

y th e petroleu mrefinin g industr y account s for

abou t 4 percen t ofth e valu e o f shipment s b y th e entir e manufacturin g secto r o f th e U.S . economy . In 1996 , th e valu e of shipment s b y th e petroleu mrefinin g industry wa s a n estimate d $15 8 billio n (DOE , EIA , 1999b) . Tabl e 2-1 5 show s domesti c productio n and consumption , imports , an d export s of th e aggregate d petroleu mproduc t i n 1997 . Tabl e 2-15 . Petroleu m Produc tMarke tVolumes , 199 7 (IO 6 Mt ) Domesti c Suppl y Import s Tota l L92 4 44 1 2,36 5 Source : EP A OLD industry Questionnaire Database ; ChemExpo . <http://www.chemexpo.com> . Report s fo r al l chemical s distribute d by OL D facilities . Accesse d Jun e 2000 . Foreig n trad e play s acritica l rol e in th e U.S . crud e oi l market , an d import s o f crud e oi l i n th e Unite d State s fa

r outweig h export s o f

crud e oil . Wit

h adeclin e in domesti c productio n an d a n increas e i n consumption , crud e oi l import s provid e th e missin g lin k a s U.S . oi l deman d continue s t o increase . U.S . import s o f crud e oi l hav e increase d 4 9 percen t i n th e las t

decad e alone . Import s o f refine d petroleu mproducts , on th e othe r hand , hav e decline d sinc e th e mid-1980s , accountin g for slightl y mor e tha

n one-thir d o f

total petroleu mimport s i n 1985 , bu t les s tha n one-fift h b y 199 7 (DOE , EIA , 1999a) . Althoug h th e Unite d State s i s ane t importe r of petroleum , som e export s o f crud e oi l an d petroleu mproduct s d o occur . Th e Unite d State s exporte d acombine d 1 millio n barrel s pe r da y o f crud e oi l an d petroleu mproduct s in 1997 , matchin g th e record leve l set i n 1993 . Th e five leadin g countrie s tha

t receiv e U.S . export s o f

petroleu mare Mexico , Canada , Japan , Republi c of Korea , an d Spain . Crud e oi l export s average d 110,00 0 barrel s pe r da y i n 1998 . Thi s averag e i s dow n fromit s pea

k i n 198 0 of 287,00 0 barrel s pe r

day . Produc t

export s hav e average d mor e tha n 600,00 0 barrel s pe r

da y sinc e 198 6 an d reache d 896,00 0 barrel s pe r da y i n 1997 , whe n the y accounte d for

mor e than 8 9 percen t

o f petroleu mexports . Thi s numbe r droppe d i n 199 8 t o 835,00 0 barrel s per

day , representin g 8 8 percent o f tota l petroleu mexports . Th e th.re e leadin g 2-3 7 

# S3P.5 4

petroleumproduct

exports , i n orde r o f volum e exported , ar

e petroleumcoke , distillat

e fue l oil , and motor gasolin e (DOE , EIA , 1999b,c) . 2.3.5.2 Market Prices Crude oil price s ar

e se t i n internationa

l marke t an d hav e bee n on agenera

l declin e sinc e 1981 . Th e Organization o

f Petroleu mExportin g Countrie s (OPEC ) ha s th e abilit y to influenc e oi l price s worldwide becaus e it s member s posses s suc

h alarg e portio n o

f th e world' s oil supply . I

f OPE C restrict s supply , price s increase . I f OPE C flood s th e marke

t wit h crude oil , price s decrease . Th e shar

p pric e decline i

n 199 8 wa s attributabl e t o plentiful crude oil supplie s (partly du e to Iraq' s increased production) . Ther e ha s als o bee

n agenera l trend o f pric e decline i

n petroleumproducts . Par

t o f thi s decline i s due to areduction in demand fro msufferin g Asia n economie s and adecreas e i

n U.S . deman

d fo r heatin g oil becaus e o

f unseasonabl

y war mweathe r (API , 1999) . I

n modelin g the marke

t fo r th e aggregat

e petroleumproduct , EP

A estimate d th e pric e o f th e composit

e commodit

y a s th e quantity-weighte d averag e ofth e petroleu mproduct s distribute d by OL

D facilities . Th

e marke t pric e use d in th e model i s $191.8 4 pe r metri c ton . 2.3.5.3 Future Projections Th e curren

t statu s o f th e potentially affecte

d industrie s i s importan

t t o establis h abaselin e fo r th e economi c impact

analysis . However , sinc e complianc e cost s will no t b e incurre d unti l som

e tim e i n th e future , i t

i s als o importan

t t o conside

r projection s o

f futur e economi c trend s whe

n estimatin g likely impacts o

f aregulation . Th e Energy Informatio

n Administratio n (EIA) publishe s th e Annua l Energy Outlook , which present s midter

mforecasts o

n energy supply , demand , and prices . Th e analysi s performed focuse s on areference cas e an

d fou r othe r case s tha t assum e highe r an d lowe r economi c growt

h and highe

r and lowe r worl d oil price s tha

n i n th e reference case . Th e projection s ar e based o n results fro

m EIA' s Nationa

l Energ y Modelin g Syste m(NEMS) . Information o

n petroleumfoun

d i n thi s sectio n i s base d on th e 199 9 Annua l Energy Outlook . Domesti c crud

e oi l production i s expecte d to continu e to decline throughou t the nex t 2 0 years . I t i s expecte d t

o decreas e b

y 1. 1 percen

t ayear , fro m6. 5 millio n barrel s pe

r da y i n 1997 to 5. 0 millio n barrel s pe

r da y i n 2020 . Thi s declin e i

n domesti c productio n will lea d t o adeclin e in domesti c petroleumsupply . Domestic suppl y i n 199 7 wa s 9. 4 million barrel s pe r day . I n NEMS' s 2-3 8

& \lo w pric e projection , suppl y drop s t o 7. 6 millio n barrel s per

da y i n 2020 ; i n it s hig h pric e projection , suppl y drop s t o 9. 3 millio n barrels . Domesti c consumptio n of petroleu mi s expecte d t o increas e ove r th e nex t 2 0 years . U.S . petroleu mconsumptio n i s projecte d t o increas e b y 6. 0 millio n barrel s pe r

da y betwee n 199 7 an d 202 0 i n th e referenc e case , 3. 9 millio n barrel s per da y i n th e lo w growt

h case , an d 8. 2 millio n in th e hig h growt

h case . Th e transportatio n secto r i s expecte d t o accoun t

fo r mos t o f th e increas e in petroleu mconsumption . However , achang e i n th e consumptio n patte mo f th e transportatio n secto r i s expecte d t o occur . Gasolin e accounte d fo r 6 5 percen t

of th e petroleu mconsume d fo r transportation . However , thi s share i s expecte d t o decreas e t o 6 1 percen t in 202 0 a s alternativ e fuel s are introduce d t o th e transportatio n market . Th e shar e of je t fuel i s expecte d t o increas e fro m 1 3 percen t t o 1 7 percen t

a s ai r trave l continue s t o expand . A s domesti c productio n continue s t o declin e an d domesti c consumptio n continue s t o grow , oi l import s wil l continu e t o increase . Th e projection s for ne t petroleu mimport s in 202 0 rang e fro m ahig h o f 18. 3 millio n barrel s pe r

da y in th e lo w oi l pric e cas e t o alo w of 14. 3 millio n barrel s pe r da y in th e lo w growt

h case . Thi s i s mor e tha

n doubl e th e 199 7 leve l o f 9. 2 millio n barrel s pe r

day . Tabl e 2-1 6 show s consumptio n an d net import s of

crud e oi l and petroleu mproduct s for 199 7 an d projection s for

2020 . Tabl e 2-16 . Petroleu m Consumptio n an d Ne tImport s i n 199 7 an d 202 0 (IO 6 barrels/day ) Yea r an d Projectio n 199 7 202 0 Projection s Referenc e Lo w oi l pric e Hig h oi l pric e Lo w growt

h Hig h growt

h Consumptio n

18. 6 24. 7 26. 0 24. 0 22. 5 26. 8 Ne tImport s

9. 2 16. 0 18. 3 14. 6 14. 3 17. 7 Ne tCrud e Import s

8. 1 12. 0 13. 1 11. 5 11. 4 12. 6 Ne tProduc t

Import s 1. 0 4. 0 5. 2 3. 1 2. 9 5. 1 Source : U.S . Department

of Energy , Energ y Informatio n Administration . 1999a . Annual Energy Outlook, 1999.

2-3 9



### vSS "P.5 6

A s discussed earlier , crud

e oil imports currentl

y accoun t fo r the majorit

y o f foreign import s o f petroleum . Crud

e oil i s expected t

o continu e a

s th e majo r componen

t o f petroleu mimports . However , the impor

t shar e o f refine d product s i s expected t o increas e i n th e future . Mor

e import s o f petroleu mproduct s will b e neede

d a s growt h i n deman d fo r refined product s exceed s th e expansion o

f domestic refining capacity . Futur e export s o

f petroleu mfro mthe United State s will depend on economi c condition s worldwid e an d the restrictions placed o

n trade bot h i n th e Unite d State s an

d abroad . Th e industrialize d countrie s will continu e t o b e th e majo r oil consumer s ove

r th e nex t 2 0 years . However , petroleu

mus e wil l increas e a

t th e fastest rat e i n developin g countries . The Unite d State s will continu e t o expor

t petroleumproduct s (especiall y th e heavy products , which ar e i n les s deman d i n thi s country ) (DOE , EIA , 1999c) . Oil price s hav e fluctuated greatl y in th e past , which make s futur e pric e projection s uncertain . However , futur

e oi l price s ar

e expected to b e highe

r tha n current prices . Th e lates t

yea r fo r whic h comprehensiv e dat

ai s available i s 1998 , ayea r which sa w uncharacteristically lo w price s fo r petroleum-base d products . Th e worl d pric e fo r crude oi l i s mos t

heavily influenced b y OPEC' s limit s o n production . A s o

f th e publication o

f thi s document , price s fo

r crude oil an

d petroleum

based product s ar

e muc h highe r tha n during the years presente d in th e table s i n thi s report. Increased worl d deman

d ha s no t bee n me t wit h production increases , resulting i n highe r prices . Th e referenc e cas e fo

r Oi l projects price s to rise by abou t 0. 9 percen

t ayear , reachin g $22.7 3 i n constan t 1997 dollar s i

n 2020 . I n nomina l dollars , th e reference cas e pric e exceed s $4 3 in 2020 . Th e low pric e cas e project s price s rising t o $14.5 7 b y 200 5 and remaining a t about tha t level until 2020 . The high pric e cas e ha s apric e rise o f abou t 2. 5 percen

t pe r yea r unti l 201 5 and the n remains a

t $29.3 5 unti l 2020 . Th

e levelin g of

f a t abou t $29.3 5 i n th e hig h pric e cas e i s du e t o th e marke t penetratio n o

f alternativ e energy supplie s tha t coul d becom

e economicall

y viabl e a t tha t pric e (DOE , EIA , 1999a) .

2-4 0

tO*SECTIO N 3 ENGINEERIN G COS T ANALYSI S

HA P emission s occur

a t several commo n point s durin g th e storag e an d distributio n o f organi c liquid s othe r

tha n gasoline . T o contro l thes e emissions , EP A ha s develope d MAC T floo r level s of contro l under

th e authority of

Sectio n 11 2 o

f th e CAA . Thi s sectio n summarize s EPA' s contro l cost s estimate s fo

r th e propose d rule . Th e Technical Support Documen t

(TSD ) contain s a detaile d discussio n o f

th e methodologie s use d t o develo p thes e cos t estimates . 3. 1 Contro l Cos tEstimate s Th e engineerin g analysi s identifie d 64 9 major source s that

ar e potentiall y affecte d b y th e rule . T o estimat e nationwid e costs , EP A develope d 1 3 mode l plant s wit h contro l cost s for

th e followin g emissio n points :

• storag e tanks ,

• carg o tan k

transfers , an d

• equipmen t

leaks . Th e cost s includ e capital cost s associate d wit h tank , rack , an d lea

k detectio n an d repai r

device s (appropriatel y annualize d usin g th e equipmen t lifetime an d discoun t

rate ) an d variabl e cost s associate d wit

h operatin g an d maintainin g pollutio n contro l device s an d othe r cost s associate d wit

h monitoring , recordkeeping , an d reportin g (MRR) . Th e Agenc y identifie d 42 9 facilities , o r 6 6 percen t ofth e tota l tha

t wil l incu r

contro l an d MR

Rcosts , wit

h th e remainin g 22 0 facilitie s incurrin g MRRcost s only .

3- 1



# ^ 7P.5 8

Th e nationwid

e complianc e cos t

estimate s fo

r the propose d rul e ar

e $41.3 8 million fo

r th e required control s (se

e Tabl e 3-1). 1 Thes e cost s ar e distribute d b

y industr y as follows : Mode l Plan t 2 8 Chemica

l Production—$20.4 9 millio n (49. 5 percent ) Model Plan

t 2 9 Petroleu

mRefineries—$4.5 4 millio n (11. 0 percent ) Mode l Plan t 4 2 Liqui d Terminals—$11.6 2 millio n (28. 1 percent) Mode l Plan t 4 6 Crud e Oi l Pipelines—$2.1 1 millio n (5. 1 percent) an d Mode l Plan t 5 1 Petroleu

mTerminals—$2.6 2 millio n (6. 3 percent ) EP A expresse d thes e control cost s o n aper-unit

basi s fo r input in th e marke

t mode l describe d in Appendi x A . EP A als o assigned representativ e costs to individua l facilitie s withi

n eac h industry , a s described i n Appendi x B . I n addition , th e Agenc

y assigned mode

l plant cost s t o eac h o f th e 24 8 surve y facilities 2 to comput

e cost-to-sale s ratio s (CSRs ) fo r facilitie s and thei

r ultimat e paren t companie s (se e Appendi

x B) .

'Althoug h mos t

o f EPA' s analysi s employ s NAIC S codes , mode l plant s wer e develope d base d o n th e SI C code s liste d i n th e facilities ' surve y response . 2 Th e Agenc y collecte d survey dat afo r 24 8 o f 64 9 potentiall y affecte d facilitie s (4 0 percent ) an d thes e ar e referre d t o a s th e "known " facilitie s in th e analysis . 3- 2 

# C #Tabl e 3-1 . Facility an d Nationwid e Contro l Cost s fo r th e Propose d OL D MAC T Tan k Tan

k Rac k Rac

k LDA

RLDA

RTrtta

l Annua

l Total Tota l Numbe r Capita

l Annua

l Capita l Annua

l Capita

l Annua

l Capita

l Control Capita l Annua

l o f Cos tper Cos tpe

r Co.stper Costper Costper Cos tpe r Co.stpe r Cos tper MR RAnnua l Total Ann . Cos tfo r Cos tfo r Mode l Facilitie s Facilit

y Facilit

y Facilit y Facilit

y Facilit

y Facilit

y Facilit

y Facilit

y Cost/Facil . Cost/Facil . Al l Facilitie s Al

l Facilitie s Plan tAffected (1997$ ) (S/yr) (1997$ ) ($/yr ) (1997$ ) ($/yr ) (1997$ ) ($/yr ) ($/yr ) ($/yr ) (1997$ ) ($/ yr ) 28- 1 6

7 0 0 0 0 0 0 2.50 0 0 16.300 16.30 0 167,50 0 1.092,10 0 8 5 . 0 0 0 0 7,35 0 22,78 5 9.85 0 22,78 5 18,500 41,28 5 837,25 0 3,509.22 5 4 0 200,25 2 -6,48 8 40.80 0 69,91 5 7,35 0 22.78 5 250.90 2 86,21 2 33.90 0 120.11 2 10.036,08 0 4.804,48 0 3 200.25 2 -6.48 8 0 0 7,35 0 22,78 5 210,10 2 16,29 7 18,50 0 34,79 7 630,30 6 104,39 1 Total s 19

5 11,671,13 6 9,510,19 6 28- 2 3 6 0 0 0 0 0 0 2,50 0 0 15.700 15.70 0 90,00 0 565.20 0 O J 4 6 0 0 0 0 7,35 0 22.78 5 9.85 0 22,78 5 18.500 41,28 5 453.10 0 1.899.11 0 i 2 1 505,13 2 -15.46 7 49.40 0 75,50 0 7,35 0 22,78 5 564,38 2 82,81 8 34,00 0 116,81 8 11.852,02 2 2.453.17 8

2 505.13 2 -15,46 7 0 0 7.35 0 22,78 5 514,98 2 7,31 8 18,500 25,81 8 1.029.964 51.63 6 total s ""10 5 ' ' " " 13,425,08 6 4,969,12 4 28- 3 "2 3 0 0 ~ 0 '"' " 0 0 0 2.50 0 0 15.70 0 15.70 0 57.50 0 361.10 0 3 2 0 0 0 0 11.79 8 87.75 2 14,29 8 87,75 2 18.50 0 106.25 2 457.53 6 3.400.06 4 1 4 1.458.72 9 -45.88 3 58.80 0 80.73 0 11.79 8 87,75 2 1,531,82 7 122,59 9 34,00 0 156,59 9 21.445,57 8 2.192,38 6 I 1.458.72 9 -45,88 3 0 0 11.79 8 87.75 2 1,473,02 7 41,86 9 18,50 0 60.36 9 1.473.02 7 60,36 9 Total s 7 0 23,433,64 1 6,013,91 9 fotih TM 370 " 48,529,86 3 20,493,23 9 fo r SI C 28 __ _ (continued )Tabl e 3-1 . Facilit y and Nationwid e Control Cost s for th e Propose d OLD MAC T (continued ) Tank Tank Rac

k Rac k LDARLDA RTota l Annua l Tota l Tota l Capita l Annua

l Capita l Annua l Capita

l Annua

l Capital Contro l Capita l Annua l Numbe r o f

Cos tpe r Cos tpe r Cos tpe r Cos tpe r Cos tpe r Cos tpe r Cos tpe r Cos tpe r MR RAnnua l Tota l Ann . Cos tfo r Cos tfo r Mode l FaciUUe

s FacUit

y FacUit

y FacUit y FacUit y FacUit

y FacUit

y FacUit

y FacUit

y Cost/FacU . Cost/FacU . Al l Facultie s AUFacUitie s Plan tAffected (1997$ ) ($/yr ) (1997$ ) (S/yr ) (1997$ ) (S/yr ) (1997$ ) ($/yr ) ($/yr ) ($/yr ) (1997$ ) ($/yr ) 29- 1 19 0 0 0 0 0 0 2,50 0 0

2 3 0 0 0 0 7,35 0 22,78 5 9,85 0 22,78 5 1 2 99,34 5 16,783 0 0 7,35 0 22,78 5 109,19 5 39,56 8 15.70 0 15,70 0 18,70 0 41,48 5 18,70 0 58,26 8 47.50 0 226,55 0 1,310,34 0 298,30 0

954,15 5 699,21 6 Total s 5 4 1,584,39 0 1,951,67 1 29- 2 1 0 0 0 0 0 0 0 2.50 0 0

1 2 0 0 0 0 7,35 0 22,78 5 9,85 0 22,78 5 8 197,23 0 36,79 3 0 0 7,35 0 22,78 5 207.08 0 59,57 8 _j ^ Total s 15,70 0 15,70 0 18.80 0 41.58 5 18,80 0 78,37 8 25.00 0 118,20 0 1,656,64 0 157,00 0

499,02 0 627,02 4 3 0 1,799,84 0 1,283,04 4 29- 3

42- 1 9

1 0 0 0 0 0 0 0 2,50 0 0

0 0 0 0 7,35 0 22,78 5 9,85 0 22,78 5 15,70 0 15,70 0 22,50 0 141,30 0 18,90 0 41,68 5 98,50 0 416,85 0 Total s Total s fo r SI C 2 9 8

2 7 11 1 280,71 6 51,40 9 0 0 7,35 0 22,78 5 290,56 6 74,19 4 18,90 0 93,09 4 2,324,52 8 2,445,52 8 5,829,75 8 744,75 2

1,302,90 2 4437,61 7 9 4 4 8 0

0 213,45 9 213.45 9 0

0 31.33 1 31,33 1 0

0 0 40,80 0 0

0 0 69,91 5 0

7,35 0 7.35 0 7,35 0 0 22.78 5 22.78 5 22,78 5 2,50 0

9.85 0 223,30 9 264,10 9 0

22,78 5 54,11 6 124,03 1 16,40 0

19.40 0 19,40 0 23,30 0 16.40 0

42,18 5 73,51 6 147.33 1 22,50 0

39,40 0 893,23 6 2,112,87 2 147,60 0

168,74 0 294,06 4 1,178,64 8 Total s 2 5 3,068,00 8 1,789,05 2Tabl e 3-1 . Facilit y an d Nationwid e Control Cost s fo r th e Proposed OL

D MAC T (continued )

U O I Mode

l Plan t 42- 2

Total s 42- 3

Total s Total s fo r SI C 4 2 46- 1

Total s 46- 2

Total s Total s fo r SI C 4 6 Numbe r

o f FaciUtie s Affected 1 0 7 1 0 4 3 1 1 3 8 1 2 5 3 8 9 4 9 11 6 2 6 3 3 3 9 3 5 Tank Capita l Cos tpe r Facilit y (1997 $ ) 0 0 423,15 8 423,15 8 0 0 1,238.32 6 1,238.326

0 0 600.32 5 0 0 467,98 7 Tank

Annua l Cos tpe r FacUit y ($/yr ) 0 0 63,94 0 63,94 0 0 0 187,64 2 187,64 2

0 0 127,61 5 0 0 112,21 6 Rac

k Capita l Cos tpe r Facilit y (199 7 $ ) 0 0 49,40 0 0 0 0 58,80 0 0

0 0 0 0 0 0 Rac k Annua l Cos tpe r FacUit y ($/yr ) 0 0 75,50 0 0 0 0 80,73 0 0

0 0 0 0 0 0 LDA R Capite l Cos tpe r FacUit y (199 7 $ ) 0 7,35 0 7,35 0 7,35 0 0 11.79 8 11.79 8 11.79 8

0 7,35 0 7,35 0 0 7,35 0 735 0 LDAR Annua l Cos tpe r FacUit y ($/yr ) 0 22,78 5 22,78 5 22,78 5 0 87,75 2 87.75 2 87,75 2

0 22,78 5 22,78 5 0 22,78 5 22.78 5 Tote l

Capita l Cos tpe r FacUit y (1997 $ ) 2,50 0 9,85 0 482,40 8 433,00 8 2,50 0 14,298 1,311,42 4 1,252,62 4

2,50 0 9,85 0 610,17 5 2,50 0 9,85 0 477,83 7 Annua

l Control Cos tpe r FacUit y < ($/yr ) 0 22,78 5 162,22 5 86,72 5 0 87.75 2 356.12 4 275,39 4

0 22,78 5 150,400 0 22,78 5 135,00 1 MR

R Annua l Cost/FacU. ($/yr ) 16,40 0 19,40 0 23,20 0 19,400 16.400 19,30 0 23,10 0 19,30 0

13.30 0 13,80 0 13,800 13,30 0 14.70 0 14,70 0 Tota

l Ann . Cost/FacU . . ($/yr ) 16,40 0 42,18 5 185,42 5 106,125 16,40 0 107,05 2 379,22 4 294,69 4

13,30 0 36.58 5 164,20 0 13,30 0 37,48 5 149,70 1 Tote l

Capital Cos tfo r \ U Facultie s (199 7 $ ) 25,00 0 68.95 0 4,824,08 0 1,732,03 2 6,650,06 2 32,50 0 114,38 4 15,737,08 8 6,263,12 0 22,147,09 2 31,865,16 2 22,50 0 108,35 0 3,661,05 0 3,791,90 0 7,50 0 29,55 0 1,433,51 1 1,470,56 1 5,262,46 1 Tote l

Annua l Cos tfo r A U Facultie s ($/yr ) 164,00 0 295,29 5 1,854,25 0 424,50 0 2,738,04 5 213,20 0 856,41 6 4,550,68 8 1,473,47 0 7,093,77 4 11,620,87 1 119,70 0 402,43 5 985,20 0 1^0733 5 39,90 0 112,45 5 449,10 3 601,45 8 2,108,79 3Tabl e 3-1 . Facilit y and Nationwid e Control Cost s fo r th e Propose d OL D MAC T (continued ) Tank Tan

k Rac

k Rack LDA RLDA RTote l Annual Tota l Tota l Numbe r Capital Annua l Capita

l Annua

l Capite l Annual Capital Contro l Capita l Annua l o f Cos tpe r Cos tper Cos tpe r Cos tpe r Cos tpe r Cos tpe r Cos tpe r Cos tpe r MR RAnnua l Total Ann . Cos tfo r Cos tfo r Model Facultie s FacUit y FacUit

y FaciUt

y Facilit

y FaciUt

y FacUit

y FacUit

y FacUit

y Cost/FacU . Cost/FacU . Al l Facultie s A U Facultie s Plan tAffecte d (1997$ ) (Vyr ) (1997$ ) ($/yr ) (1997$ ) ($/yr ) (1997$ ) ($/yr ) ($/yr ) (tfyr ) (1997$ ) ($/yr ) 51- 1 0 7,35 0 22,78 5 2,50 0

9,85 0 114,25 6 26,66 8 7,35 0 22,78 5 124,10 6 22,78 5 49.45 3 114,25 6 26,66 8 40,80 0 69,91 5 7,35 0 22,78 5 164,90 6 119,36 8 16,40 0 19,40 0 19,400 23,30 0 16,40 0

42,18 5 68,85 3 142,66 8 17,50 0

59,10 0 620,53 0 989,43 6 114,80 0

253,11 0 344,26 5 856,00 8 Totel s 2 4 1,686,56 6 1,568,18 3 O J 51- 2 O N 4 0 0 0

4 119,22 9 20,31 4 0 0 0 0 2,50 0 0 0 7,35 0 22,78 5 9,85 0 22,78 5 0 735 0 22,78 5 129,07 9 43,09 9 119,22 9 20,31 4 40,80 0 69,91 5 7,35 0 22,78 5 169,87 9 113,01 4 16,40 0 19,50 0 19,50 0 23,40 0 16,40 0

42,28 5 62,59 9 136,41 4 12,50 0

39,40 0 516,31 6 679,51 6 82,00 0

169,14 0 250,39 6 545,65 6 Total s Totel s fo r SI C 5 1 Gran d Total s 1 7

4 1 65 1 1,247,73 2 2,934,29 8 94,421,54 2 1,047,19 2

2,61537 5 41375,89 5 Note : Tw o facilities , on e i n Model Plan t 29-ND and on e i n Model Plant 51-1 , hav e bee n foun

d t o b e exemp t

du e t o their

ver y smal l throughput . Th e actua l gran d total number o f affected facilitie s i s 649 .SECTIO N 4 ECONOMI C IMPAC

T ANALYSIS : METHOD S AN D RESULT S Th e proposed NESHA

P require s distributor s o

f nongasolin

e organi c liquid s to mee

t emission standard s fo

r th e releas e o

f HAP s into the environment . T o mee t thes e standards , firms will hav e t

o modif y thei r plan t an d equipmen

t an d institut e lea k detectio n an

d repai r procedures . Thes e change s resul t i n highe r cost s o f production fo

r th e affecte d producers . The y ma y als o have broade

r societa l implication s becaus e thes e effects ar e transmitte d throug h m.arke t relationship s to thei

r customers . Th e OL D rulemaking wil

l increas e th e cost s o

f distributing organi c liquids . Specifically , th e cost s o

f severa l genera l type s o f businesse s ar

e expecte d to increase . Thes e businesse s includ

e facilitie s tha

t manufactur

e an d distribut e organic chemical s and/o

r nongasoline petroleu

mproduct s an

d facilitie s tha

t specializ e i

n th e distributio n o

f thes e products . O

f th e latte r facilities , som

e ar e owne d b y companie s tha

t als o manufactur

e th e products , whil e other s ar

e independen

t businesse s tha

t onl y distribut e th e products . 4. 1 Overvie

w o f Economic Modeling Approaches Severa l type s o f economic impact

modeling approache s hav e bee n developed to suppor t regulator y development . Model s incorporating differen t level s o f economi c decisionmaking ca

n generall y be categorize d as with behavio r response s (behaviora

l approach) an

d without behavior response s (nonbehavioral/accounting approach) . Th e behaviora

l approac h i s grounded i

n economi c theor

y relate d t o produce

r and consume r behavio r i n respons e t

o change s i

n marke t conditions . I

n essence , thi s approac

h model s th e expected reallocatio n o f society' s resource s i

n respons e t o aregulation . Th e behaviora l approac h explicitly model s th e change s i n marke t price s and production . Resulting change s i

n pric e an d quantit y ar e ke y input s into th

e determinatio n o

f anumbe r o f importan t phenomenai

n a n EIA , suc h a s change s i

n produce r surplus , change s i

n consume r surplus , an d ne t socia l welfar e effects . Fo r

example , alarg e pric e increas e ma y impl y tha t consumers bea

r alarg e shar

e o f th e regulator y burden , thereby mitigatin g th e impact o n
4- 1



## ^ 3P.6 4

producers ' profit s an

d plan t closures . Th

e following describe s th e method s an d result s o f thi s approach . I n contras t the nonbehavioral/accounting approac h essentially hold s fixed al

l interactio n betwee

n facilit y productio

n an d marke t forces . I n thi s approach , asimplifyin g assumption i s mad

e tha t the firmabsorb s all contro l costs , an d th e analysi s assesse s th e burde n o f th e contro l cost s unde

r thi s assumption . Typically , engineerin g contro l cost s ar e the n compare d to facility , company , or industr y sale s t o evaluat e th e regulation' s economi c impact . Th e Agenc

y employe d anonbehaviora

l approac h to conduc t

a n initia l screening analysi s o f impact s o n smal l businesse s (described i

n Section 5) . 4. 2 Conceptua

l Approac h EP A develope d asimple competitiv e marke t mode l i n which buyer s and seller s ar e pric e taker s i

n thre e commodit

y market s potentially affecte d b y th e rule : petroleumand chemica l product s an

d merchan t organi c liqui d distributio n services . Price s in thes e market s ar e se t b y th e collectiv e action s o

f producer s an

d consumers , who tak

e th e marke

t pric e a s a give n i n makin g their

productio n an d consumption choices . EPA' s model compare s baseline condition s in th e tw o product markets an

d th e merchan

t distributio n servic e marke

t to with

regulatio n condition s i

n thos e markets . Becaus e th e supplier s o f organi c chemical s an

d petroleumliquid s ar

e als o th e demander s o

f merchan t services , EP

A pai d particula

r attentio n to th e interaction s betwee

n the markets . Wit h th e regulation , the cost s o f production increas e fo

r organi c liqui d supplier s and distributor s becaus e the

y incu r additiona l cost s associate d wit

h th e propose d rule . Incorporatin g thes e regulator y contro l cost s i s represente d by a n upwar d shif t of th e aggregat

e suppl y curv e i n eac h o f th e three markets . I

n addition , th e increase d cost s incurre d b y organi c liqui d and petroleumproduct facilitie s reduces their

deman d fo r merchan t distributio n services . A t th e ne w equilibriumwit

h th e regulation , th e marke

t price s o f organi c chemical s an d petroleumproduct s increas e an d output i n thos e markets (a s determine d fro mth e marke

t deman d curve , D

M ) declines . I

n the marke

t fo r merchan t distributio n services , marke t quantit y declines . However , depending o n th e interaction o

f th e decreas e i

n deman d an d the decreas e i n suppl y i n tha t market , th e marke

t pric e ma y eithe r increas e o r

decrease . Figur e 4- 1 illustrate s the theor

y underlying estimation o

f th e economi c impact s o

f the rule .
4- 2 

### (s,(AP.6 5

a) Quantit

y o f organi c liqui d distribute

d b y SIC s 2 8 an

d 2 9

P,-T7 >

q/ t b) Quantit

y o f organic liquid s distributed b y merchan

tdistributors Figur e 4-1 . Marke tResponse s t o th e OL D NESHA P 4- 3



## &£-P.6 6

4.2.1 Operational

Model T o develop quantitativ e estimate s o f economic impacts , the Agenc y develope d a

n operationa l mode l using spreadshee

t software . A s described below an d i n detail i n Appendix A , thi s mode

l characterize s baseline suppl y an d deman d an d th e behaviora

l response s t o change s i n cost s and/o

r marke t prices . 4.2.1.1 Market

Supply For eac h organi c liqui d market , EP A define s marke

t suppl y a s the su mo f domesti c an d foreign supply . Domestic suppl y i s th e su mo f baseline quantitie s supplie d by facilitie s within th e market . EP

A obtained questionnair

e datao n baselin e quantitie s o

f liquid s distribute d b

y asample o

f facilities , an

d estimate d the quantitie s distribute d by th e rest ofth e estimate d univers e o

f OL D facilitie s a s described i

n Appendix B . Eac

h suppl y function' s parameter s wer

e calibrate d using baseline production , pric e data , an d th e responsivenes s o

f suppl y t o change s i

n pric e (suppl

y elasticity) . 4.2.1.2 Market

Demand Simila r to supply , th e Agenc

y modeled tw o aggregat

e consumer s (domesti c and foreign ) i n eac h product market , and domesti c deman d fo r distribution , wit

h downward

slopin g demand curve s tha

t ar e consisten t wit h th e theor y o f demand . Thi s characterizatio n simply indicate s tha

t consumptio

n o f commoditie s i s hig

h a t lo w price s an

d lo w a t hig h prices . Th e Agency constructed deman d function s fo

r eac h consume r usin g baselin e quantity , pric e data , an

d assumption s abou

t th e responsivenes s t

o change s i

n pric e (demand elasticity) . EP

A obtained estimated deman d elasticitie s fo

r th e liqui d market s frompreviou s EP A economi c impact

analyses . The elasticit

y o f deman d fo r distributio n services , lik

e th e demand itself

, i s derived fro

mth e deman

d fo r th e liquid s being distributed . 4.2.1.3 Control

Cost Inputs and

With-Regulation Equilibrium Th e proposed OL

D NESHA

P will increas e th e cos t

o f distributin g organi c liquids , which will increas e th e cost s o f facilitie s producin g organi c liquid s bot h directly (becaus e they als o distribut

e organic liquids ) an

d indirectly (becaus e the

y purchas e merchan

t distributio n services , whos e cost s will als o increas e due t o th e proposed regulation) . Th e increase d cos t

an d reduced quantit

y o f organi c liquid s distribute d by producing facilitie s als o reduces th e deman

d fo r merchan t distributio n services . EPA' s analysi s estimate s th e

4- 4

(*(*P.6 7

adjustmen t i n equilibriu

mquantit y a t eac h distribution facilit

y an d i n eac h market , using the mode l describe d i

n Appendi x A . Man y o f th e facilitie s potentiall

y affecte d b y the propose

d regulation ar

e located i n l-hou r ozone nonattainmen

t areas . Thes e facilitie s probabl y hav e man y o f the control s an

d processe s o

n whic h th e estimated cost s o

f compliance ar

e based i n plac e a t baseline . The cost s o f complianc e fo

r thes e facilitie s woul

d likel y b e muc h lowe r tha n th e cost s estimate d b y EPA . The

y woul d therefor e incu r lowe r impacts a s aresult

o f the regulation , an

d th e marke t adjustments would be somewha t smaller . To accoun

t fo r thes e differences , EP

A conducte d tw o sensitivit

y analyses . Sensitivit

y Analysi s A decrease s estimate d complianc e cost s fo r facilitie s locate d i

n l-hour ozone nonattainmen

t areas by th e amoun

t o f lea k detection an

d repair (LDAR ) cost s an d MR Rcosts . Sensitivit

y Analysi s B reduce s their

cost s by the amoun

t o f MR Rcost s only . Th

e result s o f thes e tw o sensitivit

y analyse s ar

e show n i n Appendi x C . 4.2.2 Results The theor y presented above suggest s tha t producers attempt

to mitigat e th e impact s o

f higher-cos t

production b y shiftin

g th e burde

n o n t o othe r economic agent s to th e exten t th e marke t condition s allow . W

e would expec t

th e mode l to project upwar d pressur e o n price s fo r merchan t distribution service s a s producer s reduc e outpu t rate s i n response to highe

r costs . Increased pric e o

f merchan t services , plu s direc t

cost s o f complianc e fo

r organi c liqui d producer s tha

t als o distribute , results in increased price s fo r organi c liquid s a s producer s reduce outpu

t rate s t o respond to highe

r costs . Highe

r price s reduce quantit

y demanded an

d outpu t fo r organic liquids , leading to change s i n economic surplu s t o consumer s and profitabilit y o f firms. Reduced productio n o f organic liquid s reduces th e deman d fo r merchan t distribution services . Thes e interacting marke t adjustments determine th e socia l cost s o f th e regulation an

d it s distributio n acros s stakeholder s (producer s an d consumers) . 4.2.3.1 Market- and

Industry-Level

Impacts The increased cos t

o f productio n due t

o the regulation i s expecte d to slightly increas e th e pric e o f petroleu man d chemica l product s an

d reduce thei

r production/consumptio n fro m baseline levels . A s show

n i n Tabl e 4-1 , the regulator

y altemativ e i s projecte d t o increas e price s b y les s tha n 0.0 2 percen

t i n th e market s fo

r petroleu mproduct s an

d organi c chemicals . Domestic productio

n o f petroleu mproduct s decline s by 0.05 5 millio n M t an d domesti c chemica l productio n decline s by 0.03 5 million Mt . Suppl y fro mforeig n producer s (imports ) 4- 5

Cr-?P.6 8

Tabl e 4-1 . Market-Leve

l Industr y Impact s of th e Propose d Organic Liquid Distributio n (OLD ) NESHAP : 199 7

Petroleu mProduct s Pric e ($/metri c ton ) Quantit y (IO 6 metri c tons/yr

) Domestic Foreig n Chemical Product s Pric e ($/metri c ton ) Quantit y (IO 6 metri c tons/yr

) Domestic Foreign Distributio n Service s Pric e ($/metri c ton ) Quantit y (IO 6 metri c tons/yr

) Baseline

$191.8 4 2,36 5 1,92 4 44 1 $498.6 5 20 2 19 1 1 1 $12.3 2 36 8 Wit h

Regulatio n $191.8 5 2,36 5 1,92 4 44 1 $498.7 0 20 2 19 1 1 1 $12.3 6 36 8 Chang < Absolute $0,00 5 -0.0 4 -O.0 5 0.0 1 $0,05 4 -0.0 3 -0.0 3 0.0 0 $0.0 4 -0.0 2 Relativ e

0.003 % -0.002 % -0.003 % 0.003 % 0.011 % -0.016 % -0.018 % 0.016 % 0.356 % -O.004 % increase s by 0.01 5 million M t i n the petroleu

mmarke t and 0.00 2 million M

t i n th e chemica

l market , resultin g in anet

declin e o f 0.0 4 million M

t and 0.03 3 millio n M

t respectively (les s tha n 0.0 2 percent) . I

n the marke

t fo r merchan t distributio n services , equilibriumquantit y i s projecte d t o declin e b y 0.01 6 million Mt , les s tha n 0.0 1 percent , an

d marke t pric e i s projecte d to increas e by $0.04 , les s tha n 0. 5 percent . Revenue , costs , an

d profitabilit

y o f the directly affecte

d industr y als o chang e a s price s an d productio n level s adjust

t o increased cost s .associate

d wit h compliance . For

domesti c petroleu mproducers , operating profits ar e projected t o declin e by $8. 7 million (se e Tabl e 4-2) . Operatin g profi

t losse s ar e th e ne t result o f thre e effects : decreased revenue , reduction s i n productio n cost s a s outpu t declines , an

d increased contro l costs . For domesti c chemica

l producers , operatin g profit s ar e projected t o decline by $11. 4 million .

4- 6

is_<ZP.6 9

Tabl e 4-2 . National-Leve l Industr y Impact s o f th e Propose d Organi c Liqui d Distributio n (OLD ) NESHAP : 199 7 Absolute Chang e Petroleu m Revenue -$0.1 3 Cost s $8.6 1 Operating Profi

t -$8.7 4 Facilitie s 0 Chemical s Revenue -$6.9 4 Cost s $4-5 1 Operatin g Profi t - $ 11.45 Facilitie s 0 Distributio n Service s Revenu e $15.9 4 Costs $15.6 1 Operating Profi

t $0.3 3 Facilitie s 0 Tota l Revenu e $8.8 7 Cost s $28.7 3 Operatin g Profi t -$19.8 6 Facilitie s 0

4.2.3.2 Facility-Level

Impact Results Usin g th e quantit y adjustmen t equatio n show n i n Appendi x A , EP A estimate d eac h facility' s adjustmen t

t o th e propose d regulation. First , EP A estimate s th e chang e i n th e facility' s quantity distributed . EP A the n combine s th e estimate d decreas e i n quantity , couple d wit

h th e chang e i n th e marke t pric e fo r th e commodity distributed , t o estimat e th e facility' s chang e i n revenue. Detaile d informatio n abou t facility-leve l profitability was unavailabl e fro mIC R surve y responses . However , Agenc y estimate d th e chang e i n eac h facility' s profit , usin g th e followin g formula : 4-7



### <£< ?P.7 0

AT I = (A p - c.)-q. , + 0.5(A

p - C;)-Aq . (4.1 ) Thi s formul aestimate s the facility' s chang e in produce r surplu s based o

n th e chang e i

n th e marke t pric e and th e facility' s quantit y an d complianc e costs . Facilit

y cost s ar e estimate d b

y subtracting estimate d with-regulation facilit y profit s fro

mwith-regulatio n facilit

y revenues . EP A the n aggregate d th e change s i

n facilit y revenues, costs , and profit s acros s facihtie s i n eac h marke t t o estimate national-leve

l industr y impact s show

n i n Tabl e 4-2 . I n th e petroleummarkets , revenue s fel l slightly , an

d cost s increased , s o tha

t overall , profit s decrease d b y approximatel y $8. 7 million . I

n th e chemical s market , revenue s fell b y $6. 9 million , and cost s increased b y $4. 5 million , s o tha

t overall profit s fel

l $11. 4 million . For th e merchan

t distributors , revenues increased by $15. 9 millio n and cost s increase d by $15. 6 million , s o profit s increased slightly , b y $0. 3 million . Nationwide , profit s fel l b y nearl y $2 0 millio n acros s al

l thre e affecte

d sectors . 4.2.3.3 Company-Level

Impacts Results T o analyz e th e impacts o

f th e propose d rul e o

n the companie s ownin g affecte d facilities , EP

A estimate d the change i

n profit s the

y would experienc e a s aresult ofth e regulation . Thes e result s ar e show n i n Tabl e 4-3 . Generally , th e propose d regulatio n i s projected t o result

in sligh t reduction s i

n th e profit s o

f companie s ownin g OL

D facilities . N o compan y tha t wa s profitabl e a

t baseline i s projected t

o becom e unprofitabl e du e to th e regulation . Ofth e 4 1 companie s ownin g facilitie s analyze

d in th e market

model , tw o ar

e projected to experienc e increased profit s as aresult ofth e regulation . Onl

y on e compan

y i s projecte d t o experienc e areduction i n profit s o f mor e tha n $0. 5 million . Eighteen ar e projected to experienc e reduction s i n profit s les s tha

n $0. 1 million , an

d anothe r 1 3 ar e projecte d to experienc e reduction s i n profit s betwee

n $0. 1 millio n an

d $0. 3 million . Th e remaining seve

n companie s ar

e projected t o experienc e reductions in profit s o f betwee n $0. 3 millio n an d $0. 5 million . I n additio n t o th e companie s owning facilitie s include d i n th e market

model , th e companie s owning th e Trans-Alask aPipeline (TAP

) wil l als o b e impacted . (Th

e TA P wa s omitted fro mth e marke

t impacts mode

l becaus e the volum

e o f petroleumtransferred vi ath e pipeline i s s o large , an

d becaus e it

i s no t really competin

g wit h othe r pipelin e facilitie s

4- 8 

## -JOP.7 1

Tabl e 4-3 . Estimate d Company-Level Impact s o f th e OLD NESHAP : 199 7 Chang e i n Profit s ($10 6 million ) Numbe r o f Companie s Positiv e 2 Betwee n -0. 1 an d 0 1 8 Between-0. 3 and-0. 1 1 3 Between-0. 5 and-0. 3 7 Greate r tha n -0. 5 1 Tota l 4 1 affected. ) EP

A analyze d th e impacts o

f th e proposed rule o

n the compan

y owning the TA

P by comparing th e cost s o

f complianc e wit

h compan y sales . Affecte

d TA P facilitie s include 1 1 pipeline pum

p station s an

d the Valdez Marine Terminal . The TA P i s owned b

y the Alyesk aPipelin e Company , th

e majo r partne r i n whic h i s BP-Amoco . T o b e conservative , EP A compare d the TAP' s cost s wit h the revenues o

f BP-Amoco , ignorin g revenue s o f othe r partners . Th e TA

P i s estimated t

o incu r $2. 7 million to compl

y wit h th e regulation, whic

h i s 0.00 4 percent of Amoco' s annua

l sales . I f revenue s o

f othe r pipelin e owner s wer

e included , the estimate d cost s o

f th e proposed rul e would represen t a n eve n smalle r share . EP A thu s believe s tha

t th e proposed rul e wil

l not impos e significan

t impact s o n th e owner s o

f th e TAP . I n addition to analyzin

g impacts o

n companie s i

n general , EP

A als o examined th e impact s o f th e regulation o

n smal l businesses . Thi s analysi s i s presente d i n Section 5 . 4.2.3.4 Social Costs Th e valu e o

f aregulatory action i s traditionally measured b y th e chang e i

n economi c welfar e tha t i t generates . The regulation's welfar e impacts , o r

th e socia l cost s required t o achieve environmenta

l improvements , wil

l exten d to consumer s an

d producer s alike . Consumers experienc e welfar e impact s du e to change s i

n marke t price s and consumption level s associate d wit

h the rule . Producers experienc e welfar e impact s resulting fro

mchange s i n profit s corresponding wit

h th e change s i

n production level s an

d marke t prices . However , it i s importan

t to emphasiz e tha

t thi s measur

e doe s not include benefit s tha

t occu r outside th e market , tha

t is , the value o

f reduced level s o

f ai r pollutio n wit

h the regulation . The economi c analysi s account s fo r behaviora l response s b

y producer s an

d consumer s t o th e regulation (i.e. , shiftin

g cost s t o othe r economi c agents) . Thi s approach provide s 4- 9 

## 7 / 

## £?3P.7 2

insight s o n ho w th e regulator y burde n i s distributed acros s stakeholders . A s show n i n Tabl e 4-4 , the economi

c mode l estimate s the tota

l socia l cos t o f the rul e o f $41. 4 million . A s aresult o f highe r price s an d lowe r consumption levels , consumers (domesti c an d foreign ) ar

e projected t o los e $21. 8 million , wit

h chemica l consumers accounting fo

r 8 0 percen t ofth e total . Domesti c producers los e $22. 3 million i n profits , wit

h chemica l producer s accountin g fo r 8 5 percen t o f the total . Foreign producer s unambiguousl y gai n a s aresult

o f th e regulatio n wit

h profits increasin g by $2. 7 million . Thes e producers benefit fro mhighe r price s wit h additiona

l contro l cost s associated wit h production . Tabl e 4-4 . Distributio n o f Socia l Cost s Associate

d wit h Organic Liquid s Distributio n (OLD ) NESHAP : 199

7 Value ($10Vyr ) Chang e i n Consumer Surplus Petroleu m Chemica l Chang e in Producer Surplus Domestic Producer s Petroleum Chemica l Distributio n Service s Foreign Producer s Petroleu m Chemica l Tota l Socia l Cost -$23.7 7 -$12.8 0 -$10.9 7 -$16* 9 -$19.8 6 -$8.7 4 -$11.4 5 $0.3 3 $2.9 7 $2.3 9 $0.5 8 -$40.7 0

4-1 0 

## ? 2SECTION S SMAL L BUSINES S IMPACT ANALYSI S Although environmenta

l regulation s ca

n affec t al l businesses , small businesse s ma y have specia l problem s complyin

g wit h suc h regulations . Th

e Regulator

y Flexibilit

y Ac t (RFA) o f 1980 require s tha

t specia l consideratio

n b e give n to smal l entitie s affecte

d by federa

l regulations. Th

e RF A wa s amended i

n 1996 b y th e Smal l Busines s Regulator

y Enforcemen

t Fairnes s Ac

t (SBREFA) to strengthe

n it s analytica

l an d procedura

l requirements . Unde

r SBREFA , th e Agenc

y must perfor maregulator

y flexibilit y analysi s fo

r rule s tha t wil l hav e asignifican

t impac t o n a substantia l numbe r o f smal l entities . Thi s section focuse s o n th e complianc e burde

n fo r th e smal l businesse s t o determin

e whethe r thi s propose d rul e i s likely t o impos e asignifican t impac t o n a substantia l numbe r ofth e affecte

d smal l entitie s (SISNOSE

) withi n thi s industry . 5. 1 Identifyin g Smal

l Businesse s Th e Smal l Busines s Administration (SBA ) define s asmal

l busines s i

n term s o f th e sale s o

r employmen

t o f the ownin g entity . Thes e threshold s var y by industr

y an d ar e evaluate d based o

n th e industr y classification (NAIC S code ) o f th e affecte d facility . EP

A identified 2 6 differen

t four

digit SI C codes , an

d a n eve n large r numbe r o f NAIC S codes , fo

r th e affecte d companies . Th e siz e standard s fo

r thes e industrie s rang e fro

mamaximu

mo f 10 0 t o 1,50 0 employee s or

fro ma maximu mo f $ 5 millio n t o $18. 5 millio n i

n revenues . Based o

n th e reporte d compan

y employmen

t or revenu e an

d SI C size standards , EP

A classifie d seve

n o f the 6 5 know

n companie s i

n th e surve

y as small , or

10. 6 percen

t o f the total . Using th e scaling method s describe d i n Appendix B , the Agenc y estimate d tha

t 2 8 smal l firms ar e potentially affecte

d by th e rule : 1 9 smal

l firm s incu

r contro l an d MR Rcosts , an d 9 smal l firms incu

r onl y MR Rcosts . 5. 2 Screening-Leve

l Analysi s For th e purpose s o

f assessing the potentia

l impact o f thi s rul e o n thes e smal

l businesses , th e Agenc y calculate d th

e shar e o f th e annua l complianc e cos t

relativ e t o baselin e sale s fo

r each company . Whe

n acompan

y own s mor

e tha n on e affecte d facility , the cost s fo

r eac h facilit y i t own s ar e summe d t o develo p th e numerator

Ofth e tes t ratio . Fo r thi s screening-level analysis , annua l complianc e cost s wer

e define d a s the engineerin g contro l cost s imposed o n thes e companies ; thu s 5- 1



## •z aP.7 4

the y d o no t reflec t the change s i

n productio

n expecte d t o occu r i n respons e t o imposing thes e cost s an d the resultin g marke

t adjustments . A s show

n i n Tabl e 5-1 , the Agenc

y estimate d 1 7 o

f th e 1 9 smal l firms incurrin g control an

d MR Rcost s hav

e CSR s betwee

n 0 an d 0. 5 percent . The remainin g tw o smal l firms incu

r cost s tha t ar e betwee n 1 an d 3 percen t o f sales . Bot

h o f thes e firms ar

e classified i n mode l plan t grou p 4 2 (NAIC S 493) . I

n addition , al

l o f th e nin e small firms incurrin g onl y MR Rcost s (no

t displayed i

n Tabl e 5-1 ) hav

e CSR s betwee

n 0 an d 0. 5 percent . Therefore , a tota l o f 2 6 o f the 2 8 smal

l firms ar e affecte d les s tha n 0. 5 percen

t o f sales . Th e distributio n o

f CSR s (bot h contro l an

d MR Rcost s an d MR Ronl y costs ) presente d i

n Figure s 5- 1 an

d 5- 2 als o show s tha t small firms ar

e no t disproportionatel

y affecte d compared t o larg e firms . 5. 3 Economic Analysi s The Agenc

y als o examined th e economic impact s o n smal l businesse s unde

r with-regulatio n condition s expecte d to result fro mth e rule . Unlik

e the screening analysi s describe d above , thi s approac h examine s small busines s impacts i n ligh t o f th e expecte d behaviora

l response s o

f producer s an

d consumer s a s described i

n Sectio n 4 . For smal l companie s facing contro l an d MR R costs , profit s decline fro

m<0.0 1 to 32. 5 percent . Th e media n smal l company' s profit s decline b y approximatel

y 3 percent . Fo r

smal l companie s facin

g MR Rcost s only , profit

change s rang e fro

m +0. 1 to -7. 3 percent . Th e media n smal l company' s profits declin e by les s tha n 0. 5 percent . No facilitie s owne

d b y small businesse s ar

e projected t

o close . I n addition , n o small firms becom e unprofitable as aresult

o f incurring the complianc e cost s o f thi s regulation . 5. 4 Assessmen

t The RF A generall y require s a

n agenc y t o prepar e aregulator

y flexibilit y analysi s o

f an y rul e subject t o notic e an

d commen t rulemaking requirement s unde r th e Administrativ e Procedur e Ac t o r an y othe r statut e unles s th e agenc

y certifie s tha

t the rul e will no t

have asignifican

t economi c impact o n asubstantia

l numbe r o f smal l entities . Smal

l entitie s include smal

l businesses , smal

l organizations , an d smal l governmenta

l jurisdictions . Fo r purpose s o

f assessin g the impacts o

f today' s propose d rul e on smal l entities , smal l entit y i s define d as

5- 2



### 7*7Tabl e 5-1 . Compliance CSR s for Companies b

y Industr y an d Compan

y Size : Control an d MR

RCost s (1997) "

Ln i Mea

n Median Maximu m Minimu m

Tota l Complianc e cost s ar e <1 % o f sale s Complianc e cost s ar e il t o 3 % o f

sale s Complianc e cost s ar e i.3% o f sale s Mode l Plan t

Grou p 2 8 Smal l Larg e 0.13 % 0.01 % 0.13 % <0.0l % 0.13 % 0.02 % 0.13 % <0.01 % Mode l Plan t Grou p 2 8 Smal l Larg e 2 5 3 2 5 3 0 0 0 0 Mode l Plan t Grou p 2 9 Smal l Larg e 0.09 % <0.01 % 0.09 % <0.01 % 0.18 % 0.02 % <0.01 % <0.01 % Mode l Plan t Grou p 2 9 Smal l Larg e 3 1 6 3 1 6 0 0 0 0 Summar y Statistic s Mode l Plan t Grou p 4 2 Smal l Larg e 1.14 % 0.20 % 1.14 % 0.04 % 2.11 % 1.21 % 0.17 % <0.01 % Mode l Plan t Grou p 4 6 Smal l Larg e N A N A N A N A Numbe r o f

Companie s Mode ! Plan t Grou p 4 2 Smal l 4 2 2 0 Larg e 2 9 2 7 2 0 Mode l Plan t Grou p 4 6 Smal l Larg e 0 3 0 3 0 0 0 0 0.01 %

<0.01 % 0.01 % <0.01 % 5 Mode l Plan t

Grou p 5 1 imal l Larg e N A 0.01 % N A 0.01 % N A 0.02 % N A <0.01 % Mode l Plan t Grou p 5 1 Smal l Larg e 1 0 1 9 0 1 9 1 0 0 0 0 Al l Affecte d

Industrie s Smal l Larg e 1 9 12 0 17 11 8 2 2 0 0
N A = No tavailabl e Facilitie s were assigne d t o model plant

s 28,29,42,46 , an

d 5 1 depending o n th e OL D activit y takin g plac e a

tth e facility . Thes e two-digi t SI C mode l plant s d o notalway s correspond t o th e SI C o r NAIC S cod e for th e paren tcompany ownin g th e plant. Th e determinatio n o f small busines s status i s based o n th e paren tcompany' s NAIC S code .

0\P.7 6

100 % 80 % £ 60 % o 3 2 40 % u . 20 % 0 %

100 % 80 % | T 60 % 3 £ 40 % u . 20 % 0 % 

# I
0 % >0-0.5 % >0.5

- >1.0

- >3.0

- >5.0

- >10.0

- >20.0 %

1.0 % 3.0 % 5.0% 10.0 % 20.0 % CS R Rang e a ) Smal l Companie s



### II 1 = 

### 1 = 

## a ® 0 % >0-0.5 % >0.5 - >1.0 - >3.0 -

1.0 % 3.0 % 5.0 % >5.0 - >10.0 - >20.0 % 10.0 % 20.0 % • SI C 2 8

• SI C 2 9 0 SI C 4 2 m SI C 4 6

• SI C 5 1

• SI C 2 8

• SI C 2 9 S SI C 4 2 § SI C 4 6

• SI C 5 1

CS R Rang e b ) Larg e Companie s Figur e 5-1 . Distributio n o

f Complianc

e CSR s b y Industry : Control an

d MR RCost s (1997 ) Note : SIC s 28,29,42,46 , an d 5 1 reflec t th e mode l plant s t o whic h facilitie s ar

e assigned .

5- 4



## "T r / O100 % 80 % + — | T 60 % •{

— 3 « 40 % -Iu . 20 % 0 % 0 % >0-0.5 % >0.5 - 1.0 % >1.0 - >3.0 - >5.0 - >10.0 - >20.0 % 3.0 % 5.0 % 10.0 % 20.0 % CS R Rang e a ) Smal l Companie s • SI C 2 8 D SI C 2 9 0 SI C 4 2 S SI C 4 6 • SI C 5 1

100 % 80 %

« 60 % 0 ) 3 £ 40 % u . 20 % 0 % • SIC 2 8 D SI C 2 9 S SI C 4 2 B SI C 4 6 • SI C 5 1

0 % >0-0.5 % >0.5 - >1.0 - >3.0 -

1.0 % 3.0 % 5.0 % >5.0 - >10.0 - >20.0 % 10.0 % 20.0 % CS R Rang e b ) Larg e Companie s Figur e 5-2 . Distributio n o

f Complianc

e CSR s b y Industry : MR

ROnl y Cost s (1997 )

5- 5

-?- >P.7 8

• asmal l busines s whos e paren

t compan y ha s fewe r tha n 10 0 o r 1,50 0 employees , depending o

n siz e definitio

n fo r th e affecte d SI C o r NAIC S code , or

amaximu mo f $ 5 million t o $18. 5 million i

n revenues ;

• asmal l governmenta

l jurisdictio n tha

t i s agovemmen

t o f acity , county , town , schoo l distric t o r specia l distric t wit h apopulation o

f les s tha n 50,000 ; an

d

• asmal l organization tha

t i s an y not-for-profi

t enterpris e independentl

y owned and operated an

d i s no t dominan t i n it s field. I t shoul d b e noted tha

t companie s i

n 2 6 four-digi

t SIC code s an

d 4 2 NAIC S code s ar

e affecte d b y thi s propose d rule , an

d th e smal l busines s definition applied to eac h industr y by SIC cod

e o r NAIC S code i s tha

t liste d i n the SB A siz e standard s (1 3 CF R121) . For

mor e information o

n siz e standard s fo

r particula r industries , pleas e refe

r t o th e economic impac t

analysi s i n th e docket . Afte r considerin g th e economi c impacts o f th e proposed rul e o

n small entities , EP

A certifie s tha t thi s action wil

l no t have asignifican

t economic impact

o n asubstantia

l numbe r o f small entities . We hav e determine d tha

t onl y 2 8 small firms i

n the industrie s affecte

d by thi s rul e ma

y b e affected . Ou t o f th e 2 8 affecte

d smal l firms, only tw o firms ar

e estimated t o have complianc e cost s tha t exceed 1 percen

t o f their revenues. Th e reported impact s o n the smal l firms ar e therefor e no t considere d t

o b e significant . I

n addition , the rule i s likel

y t o als o increas e profit s a

t th e man y smal l firms no t affecte d b y th e rul e du

e to th e ver

y sligh t increas e i n marke t prices . Finally , whil e ther

e i s adifferenc e betwee

n th e media

n complianc e cost-to-sale s estimate s fo r the affecte d smal l and larg e firms (0.2 6 percen

t compared t

o 0.0 1 percen

t fo r the larg e firms), n o smal

l or larg e firms ar

e expecte d t o clos e i

n respons e to incurrin g th e complianc e cost s associate d wit h thi s rule . Therefore , th

e affecte d smal l firms ar e not disproportionately affecte

d b y thi s rul e a s compared t o th e affected larg e firms. I t als o should b e noted tha

t th e result s o

f thi s smal l busines s analysi s ar

e th e sam e regardless o f whic h industria l classification (SIC or

NAICS ) i s used . Althoug h thi s proposed rul e will no t have asignifican

t economi c impac t

o n asubstantia

l numbe r o f smal l entities , EP

A nonetheles s has tried t

o reduc e th e impact

o f thi s rul e o n small entities . I n addition , i

n thi s rule th e Agency i s applying th e minimu mleve l o f contro l to affecte

d source s allowed b

y the CAA . W

e continu e t

o be intereste d i

n th e potentia

l impact s o

f th e proposed rul e o

n smal l entitie s an

d welcom e comment s o

n issue s related t

o suc h impacts . 5- 6

•?£ •REFERENCE S

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Basi c Organi c Chemica l Manufacturing. " 1997 Economic Census, Manufacturing—Industry Series, E97M-3251I , Washington , DC : Governmen t

Printin g Office . U.S . Censu s Bureau . Augus t 1999c . "Cycli c Crud e an d Intermediat e Manufacturing. " 1997 Economic Census, Manufacturing—Industry Series, E97M-3251I , Washington , DC : Governmen t

Printin g Office . U.S . Censu s Bureau . Augus t 1999d . "Ethy l Alcoho l Manufacturing. " 1997 Economic Census, Manufacturing

—

Industry Series, E97M-3251I , Washington , DC : Govemmen t Printin g Office . U.S . Censu s Bureau . Augus t 1999e . "Industria l Gas Manufacturing. " 1997 Economic Census, Manufacturing—Industry Series, E97M-3251I , Washington , DC : Govemmen t Printin g Office . U.S . Censu s Bureau . Augus t 1999f . "Petrochemica l Manufacturing. " 1997 Economic Census, Manufacturing—Industry Series, E97M-325II , Washington , DC : Govemmen t Printin g Office . U.S . Censu s Bureau . Septembe r 1999g . "Petroleu mRefinery. " 1997 Economic Census, Manufacturing—Industry Series. E97M-3251I , Washington , DC : Governmen t Printin g Office . U.S . Censu s Bureau . Augus t 1999h . "Plastic s Materia l an d Resi n Manufacturing. " 1997 Economic Census, Manufacturing

— Industry Series, E97M-3251I , Washington , DC : Governmen t

Printin g Office .

R- 3


# « 1P.8 2

U.S . Censu s Bureau . August 1999i . "Syntheti c Organic Dy e an d Pigmen t Manufacturing. " 799 7 Economic Census, Manufacturing

— Industry Series, E97M-3251I , Washington , DC : Govemmen

t Printing Office . U.S . Censu s Bureau . Marc

h 2000a . "198 7 SI

C Matched to 199

7 NAICS. " <http://www.census.gov/epc d /naics/NSIC3B.HTML> . A s obtaine d o n Marc h 13,2000 . U.S . Censu s Bureau . Marc

h 2000b . "Retai l Trade. " 1997 Economic Census, Manufacturing

—

Industry Series, E97M-3251I . Washington , DC : Governmen t Printin g Office . U.S . Censu s Bureau . Januar y 2000c . 'Transportatio n an d Warehousing. " 1997

Economic Census, Manufacturing

— Industry Series. E97M-3251I , Washington , DC : Govemmen t Printin g Office . U.S . Censu s Bureau . Januar y 2000d . "Wholesal e Trade. " 1997 Economi c Census , Manufacturing—Industr

y Series . E97M-3251I , Washington , DC : Governmen t Printin g Office . U.S . Departmen

t o f Commerce , Burea

u o f th e Census . 1992 . Economi c Census . Washington , DC : Governmen

t Printing Office , <http://www.census.gov/epcd/www/92result.html> . U.S . Departmen

t o f Commerce , Burea

u o f th e Census . 1998 . U.S. Industry and Trade Outlook 1998: Chemicals and

Allied Products. Washington , DC : Governmen t Printin g Office . U.S . Departmen

t o f Commerce , Burea

u o f th e Census . 2000 . U.S. Industry and Trade Outlook 2000: Chemicals and

Allied Products. Washington , DC : Governmen t Printin g Office . U.S . Departmen

t o f Energy , Energ

y Information Administration . 1999a . Annual Energy Outlook, 1999. U.S . Departmen

t o f Energy , Energ

y Information Administration . July 1999b . Petroleum: An Energy Profile 1999. DOE/EIA-0545(99) . Washington , DC . U.S . Departmen

t o f Energy , Energ

y Information Administration . Jun e 1999c . Petroleum Supply Annual 1998. Volum

e 1 . DOE/EIA-0340(98)/1 . Washington , DC .

R- 4



### ^ £ 

### &"Z~P.8 3

U.S . Departmen

t o f Energy , Energ

y Informatio

n Administration . 'Th e U.S . Petroleu mRefinin g an d Gasolin e Marketin

g Industry. " Recent

Structural

Changes in U.S. Refining: Joint Ventures, Mergers, and

Mega-Mergers, <http://www.eia.doe.gov/emeu/fihance / usi&to/downstream/> . A

s obtained o

n Jul y 9,1999d . U.S . Departmen

t o f Energy , Energ

y Informatio

n Administration . 'Th e U.S . Petroleu mRefinin g an d Gasolin e Marketing Industry. " Overview of Domestic Petroleum Refining and Marketing. <http://www.eia.doe.gov/emeu/finance/usi&to/downstream/> . A s obtained o n July 9,1999e . U.S . Departmen

t o f Energy , Energ

y Informatio

n Administration . 2000 . EI A Report . "Majo

r U.S . Energ y Companie s Cu

t Expenditure s fo

r Oil an d Gas Exploratio n an

d Developmen

t Despit e Surg e i n Oi l Price s an d Cas h Flow. " <http://www.eia.doe.gov/neic/press/pressl73.html> . U.S . Departmen

t o f Energy , Energ

y Informatio

n Administration . Januar

y 2001 . Performance Profiles of

Major Energy Producers, 1999. <http://tonto.eia.doe.gov/FTPROOT/financial/020699.pdf> . U.S . Environmenta

l Protection Agenc

y (EPA) . July 1995 . Economic Impact Analysis for the Petroleum Refinery NESHAP, Revise d Draf t fo r Promulgation . U.S . Environmenta

l Protectio n Agenc

y (EPA) . June 24,1998 . Memorandum . "Productio n Projection s fo

r th e OL D Sourc e Category. " U.S . Environmenta

l Protectio n Agency (EPA) . Ma y 5,1999 . Memorandum . "MAC T Floo r Developmen

t fo r th e OL D Sourc e Category. " U.S . Environmenta

l Protectio n Agenc

y (EPA) . 2000 . Technical Support Document

for the Organic Liquids Distribution (Non-gasoline) Industry. Washington , DC : U.S . Environmenta

l Protectio n Agency , Office o f Air Qualit y Plannin g an

d Standards . U.S . Internationa

l Trade Commission , Datawe b database , <www.dataweb.usitc.gov> .

R- 5 

# S BAPPENDI X A ORGANI C LIQUID S DISTRIBUTIO N (OLD ) METHODOLOG Y Th e primar

y purpos e fo

r the EI A fo r th e proposed OL

D rul e i s to "describ e an

d quantify " th e reallocation o f society' s resources i

n respons e to th e regulatory action . T o develop thes e estimates , we use d abasi c framewor

k tha t i s consisten

t wit h othe r EIA s performed b y ISEG . Thi s approac h employ s standar

d microeconomic concept s t o mode l behaviora l responses expected t

o occu r wit h regulation . EP A compared baseline condition s i n tw o organi c liqui d product markets (chemical s and petroleumproducts ) an d aservic e marke

t (distribution ) i

n 1997 wit h with-regulation condition s i

n the sam e markets . B y including th e servic e market , we placed particula r emphasi s on th e interaction s betwee n th e marke

t fo r organi c liqui d product s and th e marke t fo r distributio n services . The propose d regulation "wil l increas e the cost s o

f performin g distributio n services . Thi s wil l increas e the cost s o

f facilitie s producing organi c liquids , eithe r directl y or indirectly . Fo r

example , cost s wil

l increas e fo

r chemica l an d petroleu mmanufacturing companie s performing on-sit e distributio n services . We assumed tha t al l producer s o

f organi c liquid s perfor

mon-sit e distribution , eithe

r whil e bringing their

organi c liqui d input s into th e facility , while sending thei r organi c liqui d product s ou

t o f the facility , o

r both . Cost s wil l als o increas e fo

r stand-alone distributio n servic e providers , bot h independen

t merchan t distributio n facilitie s an

d captiv e distributio n facilitie s owned by th e sam e companie s producing th e organi c liquids . The increas e i n th e pric e o

f merchan t distributio n service s will indirectly increas e the cost s o f chemica l and petroleumproducer s purchasing distributio n services . Figur

e 4-1 , i n Section 4 , illustrate s th e interactin g marke t responses. Thi s methodolog

y pla n describe s th e propose d mode l i n detail an d discusse s ho

w th e Agenc y

• characterize d th e suppl

y and demand o

f th e affecte d commoditie s an

d service s a

t the marke t level , A- l 

## ss~P.8 5

• linked thre e standar

d partia l equilibriu

mmodel s b

y specifyin g the interaction s betwee n suppl y function s an

d the n solving fo

r price s an d quantitie s acros s all market s simultaneously , • introduce d apolicy "shock " i n the mode

l wit h contro l cost s inducin g shifts in th e affecte d suppl y functions , an

d

• used asolution algorith

mto determine ane

w with-regulatio n equilibrium , A. 1 Baselin e Dat

a Se t ISE G collecte d th e followin

g marke t information t o characteriz e th e baseline :

• Market

quantities —Using response s fro mthe EP A industr y survey , th e Agenc

y identifie d know

n facilitie s producing petroleu man d chemica l product s potentially affecte d by th e proposed rule . Quantitie s fo r unknow n facilitie s wer

e developed usin g th e procedur

e describe d i

n Appendi x B . Impor

t an d expor t quantitie s fo

r thes e commoditie s wer

e collecte d fro

mChemExpo . Domesti c and impor t quantitie s wer

e aggregated to develop baselin e marke t quantitie s fo

r th e petroleum and chemica

l market s (se e Tabl e A-l) . Th e marke t quantit y o f distributio n service s was computed by multiplying th e estimate d shar e (a ) o f th e organi c liqui d product

distribute d by merchan

t servic e provider s an

d th e tota l baseline quantitie s o

f th e know n an d unknow n facilities . Usin g dat

acontaine d i

n th e facilit y database , the Agency estimate d a= 17.4% . • Market

prices —Petroleuman

d chemica l price s wer

e collecte d fro

mth e Chemica

l Marke t Reporter . A weighted averag e pric e fo r eac h aggregat e market was computed based o

n th e petroleuman

d chemica l quantities . Absen

t datao n th e marke t pric e fo r distributio n services , w e assumed tha t th e market

pric e i s set

by th e highes t

unit cos t servic e supplier . Using a

n engineering cos t

function 1 and quantitie s fo

r servic e providers , th e baseline marke t pric e fo r service s was estimate d to b e $12.3 2 pe

r metri c ton . • Supply and

demand elasticities —For th e chemica

l and petroleumindustries , w e utilize d industr

y (SIC ) elasticitie s gathere d fro mpreviou s EP

A economi c impact s analyse s (EPA , 1995 ; Shapiro , 1987) . Forth e distributio n servic e industry , w e assumed asuppl

y elasticit y o f one . Th e mode

l doe s no t specif y a n exogenou s deman d functio n fo r service s becaus e thi s deman d i s derive d fro

mth e suppl

y decision s o

f th e chemica

l an d petroleumproducers . Tabl e A- 2 show s th e elasticitie s used .

'Th e engineering cos t

functio n use d fo r thi s analysi s i s as follows : TC = 598(q/29) 08

.

A- 2Tabl e A-l . Baselin e Dat a Set , 199 7

Market Averag e Pric e

($/metri c ton ) Domesti c

Productio n (IO6 metri c tons ) Import s

(10 * metri c tons ) Export s

(10 * metri c tons ) Petroleu m$191.8 4 Chemica l $498.6 5 Distributio n Service s $12.3 2 1,92 4 19 1 36 8 44 1

1 1 N A 2 5

8 N A

Tabl e A-2 . Suppl y an d Deman d Elasticitie s Use d i n th e Marke tMode l

Marke t Petroleu m Chemica l Distributio n Service s Suppl y 1. 2 1. 5 1 Deman d -0. 6 -1. 5 derived deman

d

A. 2 Marke tfo r Organi c Liqui d Product s A.2.1 Market

Supply Marke t suppl y fo r

th e organi c liqui d produc t marke t i ca n b e expresse d as : Q S i = E q

, + «F j= l wher e S i q j = produc t

(i ) suppl y fro mplan t

(j) , an d S i q F= produc t

(i ) suppl y fro mforeig n source s (imports) . (A.1 )

A- 3 

## S 7P.8 7

A.2.1.1 Domestic Facility-Level Supply Domesti c facilitie s will b e affecte d by th e chang e i

n cost s o f distributio n on-sit

e an d by change s i

n the pric e fo

r distribution services . Foreig n producer s do no t

face additiona

l cost s o f production wit

h regulation . However, thei r outpu t decision s ar

e affecte d b y pric e change s expected to resul

t fro mth e regulation . The facilit y surve y di d provide sufficien

t information o

n baseline revenues , costs , o r profits . Therefore , estimate s o f the chang e i

n supply wer

e generated as follows :

S i Si % = °j0 1 + £ ' Si Ap r Cj-aAp s

PiO 1 j (A.2 )

wher e Si qj ! i s th e wit h regulatio n suppl y fo r facilit y j , S i qj 0 i s th e baselin e suppl y fo r facilit y j ,

e 5 1 i s th e domesti c suppl y elasticity , AP j i s chang e i n pric e fo r marke t i ,

c j i s th e per-uni t

contro l cost s fo r

facilit y j , ai s th e shar e o f

outpu t distribute dthroug h merchan t terminals , Ap sv c i s th e chang e i n th e pric e o f merchan t

services , an d P i 0 i s th e baselin e pric e fo r marke t i .

A- 4



### 8V *A.2.1.2 Foreign Supply (imports)

Foreig n producers d

o no t face additiona

l cost s o f production wit

h regulation . However , their

outpu t decision s ar

e affecte d b y pric e change s expecte d to resul t fro mth e regulation . Therefore , change s imports wer e modele d as follows : „Si

_s

/ MFI ~ QFO 1 + e Si 1 + Pi0) . (A.3 ) wher e Si qF , i s the wit

h regulation import s fo

r marke t i , S i q r o i s the baseline import s fo r marke t i , e i s the foreig

n suppl y elasticity , Ap ; i s th e chang e i n pric e fo r marke t i , an d Pi o i s th e baseline pric e fo

r marke t i . A.2.2 Market

Demand Marke t demand fo

r marke t i ca n be expresse d as the su

mo f domesti c an

d foreig n demand , tha

t is , 

### Q K

### = q2L * q ? (A.4 ) wher e q d0 ' mi s the domesti c deman

d an d q F ' i s th e foreig

n demand (or

exports) . A.2.2.1 Domestic Demand Change s i n domesti c demand fo

r eac h marke t was compute d a s follows :

A- 5

# &P.8 9

Di _Di ^doml " QdomO ' 1 + r] D ' ' * ( _M _.» < 

### { 

### p»)\ (A.5 )

wher e D i qdom , i s th e wit

h regulation deman

d fo r marke t i , D i qdom 0 i s th e baseline domesti c consumption fo r market i , r j i s th e domestic deman d elasticity , Ap j i s th e change in pric e fo r marke t i , an d Pi o i s th e baseline pric e fo

r marke t i . A.2.2.2 Foreign Demand

(Exports) Change s i n domestic deman

d fo r eac h marke t wa s compute d a s follows :

D i Di Q F= °FO 1 + n

, Di 1 + Ap ,

>i0)\ (A.6 ) wher e D i q F 1 i s the wit

h regulatio n export s fo

r marke t i , D i q r o i s the baseline export s fo r marke t i , •r j i s the foreig

n deman d elasticity , Ap. ; i s the chang e i

n pric e fo r marke t i , an d
A- 6



### ^OP.9 0

PJ O i s th e baselin e pric e fo r marke t i . A. 3 Marke tfo r Ol d Distributio n Service s A.3.1 Market

Supply Marke t suppl y for

OLD distributio n service s ca n b e expresse d a s

j= l wher e (A.7 )

q . B, c = suppl y fromplan t

(j ) providin g distributio n services . A.3.1.1 Domestic Facility-Level Supply

S i Si qj i = a j0 1 + e s /

• / \ PiO J . (A.8 )
wher e S

i qj , i s th e wit

h regulation suppl y fo r

facility j , S i q j 0 i s th e b.aselin e suppl y for facility j , e S l i s th e domesti c suppl y elasticity , Ap sv c i s th e chang e i n pric e for th e servic e market , C j i s th e per-uni t

contro l cost s for

facility j , an d P svc 0 i s th e baselin e pric e for th e servic e market .

A- 7 

## 11P.9 1

A.3.2 Market

Demand Q D ~ = E qj Dsvc (A.9 ) j= l A s note d above , deman

d fo r service s i s derive

d for mth e suppl

y decision s o

f chemica l an d petroleumproducers . Therefore , individua l facilit y demand , q . " vc , i s computed a s follows : Dsvc S i , . , _ . q j = a-q

j (A.10 )



### <\ZA- 8APPENDI X B ECONOMIC COMPUTATION S
T o prepar e th e baseline fo

r the economic impac

t analysi s o f th e OL D NESHAP , EP

A used datafro

mavariet y o f sources , including publicl

y availabl e dataon th e chemica l an d petroleu mindustry , publicl

y available dat

ao n distribution firms .an

d th e independen

t liqui d terminals , and dat

aprovided b

y respondent s to th

e Agency' s Organic Liqui d Distributio n Questionnaire . T o establis h th e baseline fo r eac h affecte d facilit y an d sector , EP

A needed to estimat e

• baselin e quantit

y o f product (chemica l or petroleu mliquid ) a

t eac h facilit y an d fo r th e secto r a s awhole ;

• baselin e quantit

y distribute d throug

h captiv e distributio n system , fo r eac h facilit y and sector-wide ;

• baselin e quantit

y distribute d throug

h merchan t distributors , fo

r eac h facilit y an d sector-wide ; an

d

• baselin e pric e o

f chemicals , petroleu

mliquids , and merchan

t distributio n services . B. l Baselin e Quantities of Chemicals an

d Petroleu m Liquid s Distribute d b

y Eac h Facilit y Al l organi c liquid s produce d an d marketed i

n th e Unite d State s mus t

b e distributed . Thus , EP A expect s tha

t al l organi c liquid s (excep

t gasoline ) sol d i

n th e United State s will b e affecte d by th e proposed OL

D NESHAP . EP

A ha s dataon organi c liquid s distributio n facilitie s responding t

o th e OL D questionnaire , an

d th e quantitie s o

f organi c liquid s the

y distribute . The questionnair e dat aprovid e information o

n asubse t o f organi c liquids , distribute d b

y asubse t o f organi c liqui d distributors . T o construc t th e model' s baseline , EP

A first examined the databas e information , the n developed ametho d fo

r estimatin g the volum

e o f organic liquid s distribute d by th e "unknown " organi c liquid s distributio n facilities . Thi s sectio n describe s thes e methods .

B- l 

# ? 3P.9 3

B.l.l Quantities of

Organic Liquids Distributed Onsite and Off-site by Known OLD Facilities T o comput

e th e baseline quantit

y o f product distribute d a

t eac h facility , EP

A bega n wit h th e OL D questionnair

e databas e informatio

n o n quantitie s o

f eac h organi c liqui d transferre d a

t eac h facility . EP

A first designated eac

h product distribute d b

y thes e "known " facilitie s a s eithe

r organi c chemica

l o r petroleu mliquid , the

n aggregated acros s product s to estimat e th e quantit

y o f chemical s and/o

r petroleu mproduct s distribute d a

t eac h know n facility . Facilitie s i n mode l plan t group s 2 8 an

d 2 9 ar e assumed t o bot

h produc e an

d distribut e organi c liquids . The increased cost s associated wit h the proposed regulatio n ar e assumed to directly increas e their

cost s o f supplying delivere d organi c liquid s t o th e organi c liqui d market s they serve . Facilitie s i n mode l plan t group s 42,46 , an

d 5 1 offe r off-sit e distributio n service s to th e producer s an d consumers o

f organi c liquids . EP

A doe s no t

hav e sufficien

t datat o b e abl e t o determine whic h o f th e off-sit e supplier s o

f OL D service s offe

r their distributio n service s to eac

h organic liqui d producer . Thus , EP A ha s assume d tha

t all o f th e off-sit e distributio n facilitie s ar

e merchan t supplier s o

f distributio n services , who suppl y thes e service s t o th e distributio n market . Similarly , EP A i s no t abl e to determin e which o

f th e organi c liqui d producer s purchas e off-sit e distributio n service s an d which one s suppl y thei r organi c liquid s directly to customers . EP A ha s computed th e shar

e o f organi c liqui d distributio n tha

t take s plac e a

t off-sit e facilitie s (17. 4 percent

) an d assume s tha

t all organi c liqui d producer s distribut

e 17. 4 percen

t o f their output throug h off-sit e distributors . Thi s i s clearly asimplification tha

t reduces th e variabilit

y o f secondar y impact s o

f th e NESHA

P o n organi c liqui d producers . I

n the absenc e o

f mor e detaile d information , however , it i s a reasonabl e simplifyin

g assumption . Fo r the marke t model , EP

A assume s tha

t companie s owning mor

e tha n one OL D facilit y regar d their individua l facilitie s a s par

t o f asingl e integrate d productio n and distributio n operation . Thus , w e mode l suppl y a t th e compan

y level , rather

tha n a t th e facilit y level , b y summin

g th e quantitie s distribute d a t al l facilitie s owned by acompan y withi n eac

h mode l plant group . Thi s i s probabl

y asimplificatio n i

n tha t companie s woul d conside

r th e profitabilit y o f individua l facilitie s incurrin g unusuall y hig h complianc e cost s i

n additio n t

o considerin g th

e profitabilit

y o f the overall operation .

B- 2

% ,B.l.2 Estimating Quantities of Organic Liquids Distributed by Unknown OLD Facilities T o complet

e th e baselin e characterization o

f quantitie s o

f organi c liquid s distribute d by OL D facilities , EP

A create d pseudo-facilitie s an

d assigne d quantitie s o

f organic liquid s t

o them . EP A ha s a n estimat e o f th e numbe r o f OL D facilitie s represente d b

y eac h mode l plant . Subtractin g know

n OL D facilitie s fro

mthe databas e tha

t ar e assigned to eac

h mode l plan t fro mth e tota l numbe r represented b

y eac h mode l plan t yield s a n estimate d numbe

r o f unknown plant s i

n amode l plan t group . The unknow

n facilitie s ar

e divided betwee

n thos e incurrin g only monitoring , recordkeeping , an d reportin g cost s (MRR-onl y facilities ) an

d thos e incurrin g cost s o

f complianc e contro l an

d MR Rcosts . Tabl e B- l present s th e numbe r o f know n and unknow

n facilitie s by mode

l plan t group . Tabl e B-l . Numbe

r o f Know n an d Unknow

n Facilitie s b

y Mode l PlantGrou

p Mode l Plan t Grou p 28 29 4 2 4 6 5 1 Tota l Tota

l Facilities 37 0 11 0 94 3 5 4 0 64 9 Know

n Facilities 53 33 1 8 7 5 11 6 Unknow

n Facilities Incurring Contro l an d MR RCost s 19 1 3 8 4 4 1 6 2 2 31 1 MRR-Onl y Facilities 12 6 38 3 2 1 2 12 22 0 EP A use d atwo-ste p proces s to estimat

e th e quantit

y o f organi c liquid s distribute d b y th e unknow

n facilities . First , fo

r mode l plan t group s 2 8 an

d 29 , EP A assigned quantitie s randoml y ove r the interva

l betwee n th e minimu

mand maximu

mquantitie s distribute d b

y facilitie s i n eac h mode l plan t group . Then , EP

A estimate d the tota

l quantit y o f merchan t distributio n service s demande d by thes e unknow

n facilitie s i

n model plan

t group s 2 8 an

d 2 9 b y multiplying thei

r tota l distributio n time s 0.174 . EP A allocate d employmen

t to the unknow n facilitie s within eac

h mode l plant grou p randoml y ove r th e rang e o

f actua l employmen

t fo r know n facilitie s i

n eac h mode l plant grou p an d allocate d the merchan

t distributio n quantit

y to thes e facilitie s proportiona l t o thei r estimate d employment . I n th e absenc e o

f informatio n abou t compan y ownershi

p o f th e unknow

n facilities , EP A make s th

e conservativ e assumption tha t th e facilitie s ar

e owne d b y single-facilit

y B- 3P.9 5

companies . Thi s mean s tha t th e companie s ownin g th e unknow n facilitie s ar e modele d a s bein g smalle r

tha n th e companie s ownin g th e know n facilities , o n average . I t shoul d b e note d that

EP A analyze d th e Trans-Alask aPipelin e (TAP ) differentl y fro mothe r

merchan t distributors . Accordin g t o th e OL D database , th e TA P distribute s 715,851,79 4 M t

pe r year , 5 5 time s th e tota l fo r al l othe r mode l plan t

grou p 4 6 firms . Thi s volum e o f

crud e oi l als o represents mor e than hal f o f th e tota l marke t

quantit y o f

petroleu m product s distribute d in th e U.S . i n ayear . Clearly , th e TA P i s completel y different fro mth e othe r "merchant " distributor s i n ou r database . Fo r

thi s reason , EP A ha s chose n t o model th e impact s o f

th e NESHA P on th e TA P separatel y fromth e marke t model . Th e impac t

o f th e propose d rul e o n th e owner s o f th e TA P wil l b e approximate d b y examinin g th e cost s o f th e rul e fo r th e TA P a s ashar e o f

th e baselin e compan y revenue s o f th e larges t

shareholde r

i n th e consortiu mtha t

own s an d operate s th e TA P (BP/Amoco) . B. 2 Marke tPrice s o f Organi c Liquid s an d Distributio n Service s EP A obtaine d dat ao n product-specifi c price s for organi c liquid s mentione d i n th e OL D database . EP A estimate s th e marke t pric e for organi c chemical s a s th e quantity

weighte d averag e o f

th e price s fo r

organi c liquid s designate d a s organi c chemicals . Similarly , EP A estimate s th e marke t pric e fo r petroleu mliquid s a s th e quantity-weighte d average o f

th e price s for

organi c liquid s designate d a s petroleu mliquids . Th e marke t

pric e o f organi c liqui d distributio n service s wa s foun d b y first estimatin g th e cos t o f OL D services , the n settin g th e pric e equal t o th e maximu maverag e cost . Th e cost s o f distributio n service s wer e estimate d base d o n loading , unloading , an d tan k storag e costs , scale d t o th e volum e o f liqui d distributed . Baselin e cost s o f merchan t distributio n service s rang e fro m$1.68/M t t o $12.32/Mt . Th e baselin e marke t pric e o f distributio n service s i s thu s se t

a t $12.32/Mt . B. 3 Complianc e Cost s pe r Facilit y EP A estimate d cost s o f

complyin g with th e propose d rul e base d o n 1 3 mode l plants , an d assigne d eac h know n facility t o amode l plant . Withi n eac h mode l plant , arang e o f complianc e cost s are possibl e dependin g o n th e baselin e equipmen t an d processe s i n plac e at afacility . EP A ha s estimate d cost s fo r facilitie s tha

t wil l onl y hav e t o implemen t MRR . Al l o f th e MRR-onl y facilitie s fal l withi n th e unknow n facilit y group . Fo r

facilitie s needin g t o implement

contro l an d MRR , EP A ha s estimate d cost s tha t reflec t thi s rang e o f

complianc e experiences , bu t

i s unabl e t o determin e whic h specifi c cost s withi n amode l plan t appl y t o a B- 4



### ^7& _particula r know n facility . To implemen

t th e economic impac

t analysis , EP

A ha s therefor

e assigned th e media

n control an

d MR Rcomplianc e cost

fo r eac h mode l plan t t o al l know n facilitie s assigne d t

o tha t mode l plan . EP A the n allocated th

e residua l cost s acros s the unknow n facilitie s simulated fo

r eac h mode l plan t grou p code , base

d o n th e tota l numbe r o f facilitie s withi n eac

h mode l plan t incurring th e high , low , o

r mediu mcost s fo r tha t mode l plant , show

n i n Tabl e 3-1 . Becaus e th e cost s ar e randoml y assigne d to individua

l simulate d facilities , EP

A ma y b e over - o r under-estimating the cost s o f complianc e tha

t would b e experienced b y plant s suc

h a s thos e simulate d fo

r thi s analysis . Becaus e som

e ofth e OL

D facilitie s ar

e located i n ozon e nonattainmen

t areas , an d woul d therefor e b e likel y t o have LDA

Ran d MR Roperation s i

n effec t a t baseline , EP

A als o prepared sensitivit

y analyse s tha

t reduc e the cost s o

f complianc e fo

r eac h facilit y locate d withi n anonattainmen

t are ab y the amoun

t o f MR Rcost s an d b y the su mo f MR Ran d LDA R costs . B.3.1 Scaling Nonbehavioral Impacts to Provide Industry-Wide Estimates O f th e 65 1 facilitie s potentially affecte d by the rule , 43 1 ar

e estimate d to incu

r cost s fo r control an d MRR . For

the nonbehaviora

l analysis , o

f compan y impact s used i

n th e SBREF A screening analysis , EP

A di d not creat e simulated facilities . Instead , EP A compute d scaling factors relating the numbe r o f know n facilitie s to th e tota

l numbe r o f facilitie s within eac h mode l plan t grou p (se e Tabl e B-2) : N , n i (B.l ) wher e N j = numbe

r o f facilitie s estimate d t o incu

r complianc e cost s fo

r contro l an

d MR R fo r mode l plan t grou p i , an d n s = numbe

r o f know n facilitie s i

n mode l plan t grou p i . Usin g thes e scaling factors , w e estimat e th e impact s incurred b

y th e all 43 1 facilitie s tha t have cost s fo

r contro l an d MRR . Not

e that , becaus e th e numbe

r o f know n facilitie s i

n mode l plan t grou p 4 6 exceed s the numbe

r i n th e engineering cos t

analysis , w e scal e impact s dow n fo r thi s mode l plan t group . Thi s metho d als o assume s tha t the 18 3 facilitie s estimate d t o incu r cost s fo r control an d MR Rtha t ar e unknow n ar e simila r to the know

n facilitie s i

n th e sam e mode l plan t group . B- 5 

### <? 7P.9 7

Tabl e B-2 . Facility Count s an d Scalin g Facto r for eac h Model PlantGrou

p

Mode l plantgroup Numbe r o f Facilities in Mode l Plan tGroup , Numbe

r o f Facilities in Accordin g t o CostMode

l Plan tGrou p i n Analysis Database Scaling Facto r 2 8 2 9 4 2 4 6 5 1 24 4 73 6 2 2 3 29 12 0 5 9 3 2 2 7 10 2.033

1.23 7 1.93 7 0.85 1 2.90 0 I n additio n to th e 18 3 facilitie s accounted fo r using the scalin g factor s above , ther e ar e 220 facilitie s projecte d t

o incu r onl y MR Rcosts . T o estimat

e th e cost s fo

r these , w e us e a differen t scalin g facto

r (see Tabl e B-3) . First , w e estimat e tes t ratio s fo r know n facilitie s b

y mode l plan t group , usin g onl

y the MR Rcosts . The

n we scal e thos e result s using th e rati o M L

n i (B.2 ) wher e M ; = numbe

r o f facilitie s estimate d to incu

r onl y MR Rcost s in model plan

t grou p i , and n j = numbe

r o f know n facilitie s i

n mode l plan t grou p i . Using thi s method , w e estimat e impact s tha

t woul d b e incurred b

y all facilitie s i

n eac h mode l plan t grou p cod e incurrin g onl

y MR Rcosts . Thi s metho d assume s tha t th e facilitie s incurring onl y MR Rcost s ar e simila r to the know

n facilitie s i

n th e sam e mode l plant grou p code .

B- 6 

### <\<hTabl e B-3 . Scalin g Factor s fo r Facilitie s Incurrin g Onl y MR RCost s

Mode l Plant Grou p Cod e Numbe

r o f Facilitie s i n Numbe

r o f Facilitie s i n Mode l Plan t Grou p Mode

l Plan t Grou p i n Wit h Onl y MR RCost s Databas e Scalin g Facto r 2 8 2 9 4 2 4 6 5 1 12

6 3 8 3 2 1 2 1 2 12

0 5 9 3 2 2 7 1 0 1.05 0 0.64 4 1.00 0 0.44 4 1.20 0 B. 4 Company-Leve l Factors : Cost-to-Sale s Ratio s (CSRs ) an d Scalin g Factor s T o asses s th e potentia l economi c impac t o f th e rul e o n companies , th e Agenc y calculate d acost-to-sale s ratio a s follows : CS R(% ) = 

# Ec f

l i= l Sale s 10 0 (B.3 )

wher e SC f

l i s th e su mofth e annua l contro l cos t for al l facilitie s owne d b y compan y p an d sale s i s th e tota l revenue for compan y p . Baselin e compan y profi t

margin s wer e collecte d fro msecondary sourc e dat a(se e Sectio n 2) . I

f thes e margin s wer e no t

available , a

n industr y profi t

margi n (D& B retum-onsales ) wa s use d fo r

th e company . With-regulatio n profi t margin s wer e compute d b y subtractin g th e CS Rfro mth e baselin e profi t margin . B.4.1 Scaling Company Impacts to Provide Industry-Wide Estimates T o estimat e compan y impact s o n a n industry-wid e basis , th e Agenc y use d ascalin g proces s similar

t o th e approac h use d for

facilities . First , w e assig n acompan y mode l plan t grou p base d o n th e mode l plan t grou p fo r th e larges t

numbe r o f facilitie s owne d b y th e company . Next , w e comput e th e averag e numbe r o f facilitie s pe r

compan y b y mode l plan t group , base d on th e facilitie s an d companie s i n th e databas e a s follows : B- 7 

## f< ?P.9 9

(B.4 ) wher e F = numbe

r o f firms , n = numbe

r o f facilities , an

d k = know n facilitie s i

n database . We the n creat e acompan

y scalin g facto

r fo r eac h mode l plan t grou p by dividin g th e tota

l numbe r o f facilitie s (wit

h contro l an

d MR Rcost s o r MR Rcost s only ) by th e averag e numbe r o f facilitie s pe

r company . Thi s metho d provide s a n estimat e o f the tota l numbe r o f companie s i

n tha t mode l plan t group . F t = n . (B.5 )

wher e F = numbe

r o f firms, n = numbe

r o f facilities , k = know

n i n database , an

d t = tota

l numbe r affected . Next , we comput

e th e scalin g facto

r fo r th e mode l plan t grou p a s the rati o o

f th e estimate d tota l numbe r o f companie s divide d by th e companie s i n th e database .

B- 8

/oop. 1

S = (B.6 ) Finally , w e tabulat

e the cost-to-sale s an

d profi t margi n result s b y mode l plan t grou p an d scal e it u p using th e scaling factor .

B- 9

/OlP. 2

APPENDI X C OL D ECONOMI C IMPAC T ANALYSIS : SENSITIVIT Y ANALYSI S FO R DIFFEREN T SCENARIO S

T o provid e a

n alternativ e se t

o f result s tha

t incorporat e differin g assumption s abou t baselin e control s at

affecte d plants , EP A conducte d sensitivity analysis , varyin g th e cost s assigne d t o facilitie s dependin g on whethe r the y ar e locate d in NAAQ S ozon e nonattainmen t areas . EP A expect s tha t

facilitie s locate d i n l-hou r NAAQ S ozon e nonattainmen t area s wil l hav e MR

Ran d perhap s als o LDA Roperation s i n effec t at baseline . Suc h facilitie s woul d not incu r th e full estimate d complianc e costs , bu t rathe r the y woul d incu r

th e estimate d tota l annua l cos t minu s eithe r monitorin g recordkeepin g an d reportin g an d lea k detectio n an d repai r

cost s (Sensitivit y Scenari o A ) o r tota l annual cost s minu s monitoring , recordkeepin g an d reportin g (Sensitivit y Scenari o B) . Thi s appendi x present s result s o f thes e sensitivity analyses . Table s C- 1 throug h C- 3 presen t th e result s o f Sensitivity Scenari o A , an d Table s C- 4 throug h C- 6 presen t th e result s of

Sensitivit y Scenari o B . Overall , if facilitie s i n NAAQ S ozon e nonattainmen t area s hav e monitoring , recordkeeping , an d reportin g operation s i n plac e a t baselin e (Sensitivit y Scenari o B) , th e socia l cos t o f th e propose d rul e wil l b e $39. 7 millio n instea d o f $40. 7 million . Operatin g profit s wil l fal l b y $19. 4 millio n nationwid e a s oppose d t o $19. 9 million . Pric e an d outpu t change s wil l als o b e somewha t diminished . If

i n fac t affecte d facilitie s locate d i n NAAQ S ozon e nonattainmen t area s hav e both lea k detectio n an d repai r

an d monitoring , recordkeeping, an d reportin g operation s i n effec t at baseline , estimate d impact s ofth e propose d rul e wil l b e eve n smaller . Socia l cos t wil l b e $38. 2 millio n rathe r

tha n $40. 7 million , an d profit s wil l fal l b y $18. 7 millio n rathe r than $19. 9 million .

C- 1 

### /t>2>P. 3

Tabl e C-1 . Market-Leve l Industr y Impact s o f th e Propose d Organi c Liqui d Distributio n (OLD ) NESHAP : 199 7 Sensitivit y A : N o LDARo r

MR Rfo r Nonattainmen t

Are aFacilitie s With Chang e Jaseline $191.8 4 2,36 5 1,924 44 1 $498.6 5 20 2 19 1 1 1 $12.3 2 36 8 Regulatio n

$191.8 4 2,36 5 1,924 44 1 $498.7 0 20 2 19 1 1 1 $12.3 6 36 8 Absolut e

$0,00 5 -O.0 4 -0.0 5 0.0 1 $0,05 2 -0.0 3 -0.0 3 0.0 0 $0.0 4 -0.0 1 Relativ e

0.003 % -0.002 % -0.003 % 0.003 % 0.010 % -0.016 % -0.017 % 0.016 % 0.329 % -0.004 % Petroleu m Product s Pric e ($/metri c ton ) Quantit y (IO 6 metri c tons/yr ) Domesti c Foreig n Chemical Product s Pric e ($/metri c ton ) Quantit y (IO 6 metri c tons/yr ) Domesti c Foreig n Distributio n Service s Pric e ($/metri c ton ) Quantit y (IO 6 metri c tons/yr )

C-2 

### /CQP. 4

Tabl e C-2 . National-Leve l Industr y Impact s o f th e Propose d Organic Liqui

d Distribution (OLD ) NESHAP : 199

7 Sensitivit y A : N o LDA Ro r MR Rfo r Nonattainmen

t Are aFacilitie s Absolut e Chang e Petroleu m Revenu e -$0.1 2 Costs $7.9 2 Operatin g Profi t -$8.0 4 Facilitie s 0 Chemical s Revenu e -$6.6 0 Costs $4.3 3 Operatin g Profi t -$10.9 4 Facilitie s 0 Distributio

n Service s Revenu e $14.7 5 Cost s $14.5 1 Operatin g Profi t $0.2 4 Facilitie s 0 Tota l Revenu e $8.0 3 Costs $26.7 7 Operatin g Profi t -$18.7 4 Facilitie s 0

C- 3

/ # &P. 5

Tabl e C-3 . Distributio n o f Socia l Cost s Associate

d wit h Organic Liquid s Distributio n (OLD ) NESHAP : 199

7 Sensitivity A : N o LDA

Ro r MR Rfo r Nonattainment

Are aFacilitie s

Valu e ($107yr ) Chang e i n Consume r Surplu s -$22.1 8 Petroleu m-$11.7 4 Chemical -$10.4 5 Chang e i n Produce r Surplu s -$16.0 0 Domesti c Producer s -$18.7 4 Petroleu m-$8.0 4 Chemica l -$10.9 4 Distributio n Service s $0.2 4 Foreig n Producer s $2.7 4 Petroleu m$2.1 9 Chemica l $0.55 Tota l Socia l Cos t-$38.2 0

C- 4



### /°GP. 6

Tabl e C-4 . Market-Leve l Industr y Impact s o f th e Propose d Organi c Liqui d Distributio n (OLD ) NESHAP : 199

7 Sensitivity B : N o MR

Rfo r Nonattainment

Are aFacilitie s Chang e Jaselin e $191.8 4 2,36 5 1,92 4 44 1 $498.6 5 20 2 19 1 1 1 $12.3 2 36 8 Regulatio n

$191.8 5 2,36 5 1,924 44 1 $498.7 0 20 2 19 1 1 1 $12.3 6 36 8 Absolut e

$0,00 5 -0.0 4 -O.0 5 0.0 1 $0,05 3 -O.0 3 -0.0 3 0.0 0 $0.0 4 -0.0 2 Relativ e

0.003 % -0.002 % -0.003 % 0.003 % 0.011 % -0.016 % -0.018 % 0.016 % 0.347 % -0.004 % Petroleu m Product s Pric e ($/metri c ton ) Quantity (IO 6 metri c tons/yr) Domestic ' Foreig n Chemica l Product s Pric e ($/metri c ton ) Quantity (IO 6 metri c tons/yr ) Domesti c Foreig n Distributio n Service s Pric e ($/metri c ton ) Quantity (IO 6 metri c tons/yr )

C- 5

/ © 7P. 7

Tabl e C-5 . National-Leve l Industr y Impact s o f th e Propose d Organi c Liqui d Distributio n (OLD ) NESHAP : 199 7 Sensitivit y B : N o MR Rfo r Nonattainmen

t Are aFacilitie s Absolut

e Chang e Petroleu m Revenu e -$0.1 3 Cost s $8.3 7 Operatin g Profi t -$8.5 0 Facilitie s 0 Chemical s Revenu e -$6.7 9 Cost s $4.4 5 Operatin g Profi t - $ 11.2 4 Facilitie s 0 Distributio

n Service s Revenu e $15.5 6 Costs $15.2 7 Operatin g Profi t $0.2 9 Facilitie s 0 Tota l Revenu e $8.6 4 Cost s $28.0 8 Operatin g Profi t -$19.4 4 Facilitie s 0

C- 6

ID3P. 8

Tabl e C-6 . Distribution o f Socia l Cost s Associate

d wit h Organic Liquid s Distribution (OLD ) NESHAP : 199

7 Sensitivit y B : N o MR

Rfo r Nonattainmen t

Are aFacilitie s Valu e ($10 6 /yr ) ~ Chang e i n Consume r Surplu s -$23.1 6 Petroleu mr-$12.4 1 Chemical -$10.7 4 Chang e i n Produce r Surplu s -$16.5 6 Domesti c Producer s -$19.4 4 Petroleu m-$8.5 0 Chemica l -$11.2 4 Distributio n Service s $0.2 9 Foreig n Producer s $2.8 8 Petroleu m$2.3 1 Chemical $0.5 7 Tota l Socia l Cos t-$39.7 0

C- 7

/<p qP. 9

APPENDI X D MODE L PARAMETE RSENSITIVIT Y ANALYSI S

A s note d i n Appendi x A , suppl y an d deman d elasticity estimate s fo r th e petroleu m an d chemica l market s wer e obtaine d fro mpreviou s EP A economi c impact s analyse s (EPA , 1995 ; Shapiro , 1987) . Althoug h thes e elasticity estimate s see mreasonably, EP A conducte d a sensitivity analysi s o f

thes e parameter s t o captur e abroade r rang e of relevan t values . In addition , give n th e uncertainty regardin g th e valu e of th e baselin e marke t

prices , w e als o teste d th e model' s sensitivity t o change s i n thes e values . Th e ke y results results ar e discusse d below :

• The social

cost estimate remains essentially unchanged under all scenarios —As show n i n Table s D- 1 an d D-2 , th e social cost s vary b y 0. 1 percen t o r les s i n eac h sensitivity run .

• The distribution of

costs across producers and consumers depends on the relative supply and

demand elasticities —The stakeholde r with th e les s elasti c response (i n absolut e value ) t o margina l change s i n pric e wil l bea r mor e o f th e regulatory burden . Thi s ca n b e demonstrate d b y examinin g th e followin g results derive d fro masimpl e mathematica l mode l o f ta x incidence: 1 (D.la ) d p D . d c dp s d c e s e Si -n D



### _n D £ Si -Tl D (D.lb )

'Derivation ofthi s result

ca n b e foun d i n intermediat

e microeconomi c textbook s suc h a s Nicholson (1998) . D- 1

/ / /( * Tabl e D-1 . Sensitivit y Analysi s of Chemica l Marke t

Parameter s

O i Suppl y Elasticit y Deman d Elasticit y Chemica l Pric e Closure s Chemica l Chang e i n Consume r

Surplu s Petroleu m Chemica l Chang e i n Produce r

Surplu s Domesti c Producer s Petroleu m Chemica l Distributio n Service s Foreig n Producer s Petroleu m Chemica l Tota l Socia l Cos t Bas e Cas e 1. 5 -1. 5 $49 9

0

-$23.7 7 -$12.8 0 -$10.9 7 -$16.8 9 -$19.8 6 -$8.7 4 -$11.4 5 $0.3 3 $2.9 7 $2.3 9 $0.5 8 -$40. 7 Case l

1.5 -1. 5 $37 4 (-25% )

- 1 Percen t Differ Valu e enc e -$23.7 5 -0.1 % -$12.7 8 -0.1 % -$10.9 7 0.0 % -$16.8 8 -0.1 % -$19.8 4 -0.1 % -$8.7 3 -0.1 % -$11.4 2 -0.3 % $0.3 1 -7.5 % $2.9 6 -0.1 % $2.3 8 -0.1 % $0.5 8 0.0 % -$40. 6 -0.1 % Cas e 2 1.5 -1. 5 $62 3 (+25% ) 0 Percen t Differ Valu e enc e -$23.7 8 0.0 % -$12.8 1 0.1 % -$10.9 8 0.0 % -$16.9 0 0.1 % -$19.8 7 0.1 % -$8.7 5 0.1 % -$11.4 7 0.2 % $0.3 5 4.5 % $2.9 7 0.1 % $2.3 9 0.1 % $0.5 8 0.0 % -$40. 7 0.1 % Cas e 3 0. 8 -0. 8 $49 S

0 Valu e -$23.8 0 -$12.8 2 -$10.9 8 -$16.9 2 -$19.8 9 -$8.7 6 -$11.5 0 $0.3 7 $2.9 7 $2.3 9 $0.5 8 -$40. 7 Percen t

Differ enc e 0.1 % 0.2 % 0.0 % 0.2 % 0.2 % 0.2 % 0.4 % 10.5 % 0.1 % 0.2 % 0.0 % 0.1 % Cas e 4

0. 8 -1. 5 $49 9
0 Percen t Differ Valu e enc e -$20.4 5 -$12.8 1 -$7.6 4 -$20.2 7 -$23.0 6 -$8.7 5 -$14.6 6 $0.3 5 $2.7 9 $2.3 9 $0.4 0 -$40. 7 -14.0 %

0.1 % -30.4 % 20.0 % 16.1 % 0.1 % 28.1 % 7.2 % -5.9 % 0.1 % -30.4 % 0.1 % Cas e 5

0. 8 -2. 2 $499 . 0 Percen t Valu e Differ-enc e -$18.6 6 -$12.8 1 -$5.8 5 -$22.0 5 -$24.7 5 -$8.7 5 -$16.3 5 $0.3 5 $2.7 0 $2.3 9 $0.3 1 -$40. 7 -21.5 %

0.1 % -46.7 % 30.5 % 24.6 % 0.1 % 42.8 % 5.4 % -9.0 % 0.1 % -46.7 % 0.1 % (continued )Tabl e D-1 . Sensitivity Analysi s o f Chemica l Marke t

Parameter s (continued )

I Suppl y Elasticit

y Demand Elasticit

y Chemica l Price Closure s Chemical
Chang e in Consume r Surplu s Petroleum Chemical Chang e i n Produce r Surplu s Domesti c Producers Petroleum Chemical Distributio n Service s Foreig n Producers Petroleu m Chemical Tota l Socia l Cos t Cas e 6 1.5 -0. 8 $49 9 0 Percen t Valu e -$27.1 3 -$12.8 1 -$14.3 2 -$13.5 4 -$16.6 8 -$8.7 5 -$8.2 9 $0.3 5 $3.1 4 $2.3 9 $0.7 6 -$40. 7 Differ enc e 14.1 % 0.1 % 30.4 % -19.9 % -16.0 % 0.1 % -27.6 % 6.1 % 6.0 % 0.1 % 30.4 % 0.0 % Cas e 7

1. 5 -2. 2 $49 9 0 Percen t ] Valu e -$21.6 9 -$12.7 9 -$8.9 0 -$18.9 8 -$21.8 3 -$8.7 4 -$13.4 1 $0.3 2 $2.8 5 $2.3 9 $0.4 7 -$40. 7 Differ enc e -8.8 % -0.1 % -18.9 % 12.3 % 9.9 % -0.1 % 17.2 % -3.8 % -3.7 % -0.1 % -18.9 % 0.0 % Cas e 8

2. 2 -0. 8 $49 9

- 2 Percen t Differ Valu e enc e -$28.8 9 21.5 % -$12.8 1 0.1 % -$16.0 9 46.6 % -$11.7 3 -30.6 % -$14.9 7 -24.6 % -$8.7 5 0.1 % -$6.5 6 -42.7 % $0.3 4 3,4 % $3.2 4 9.1 % $2.3 9 0.1 % $0.8 5 46.6 % -$40. 6 -0.1 % Cas e 9 2. 2 -1. 5 $49 9

- 2 Percen t Valu e -$25.8 3 -$12.7 9 -$13.0 4 -$14.7 9 -$17.8 6 -$8.7 3 -$9.4 5 $0.3 1 $3.0 7 $2.3 8 $0.6 9 -$40. 6 Differ enc e 8.7 % -0.1 % 18.8 % -12.4 % -10.0 % -0.1 % -17.5 % -4.8 % 3.6 % -0.1 % 18.9 % -0.1 % Cas e 1 0

2. 2 -2. 2 $49 9

- 2 Percen t Valu e Differ-enc e -$23.7 4 -$12.7 8 -$10.9 7 -$16.8 8 -$19.8 4 -$8.7 3 -$11.4 1 $0.3 0 $2.9 6 $2.3 8 $0.5 8 -$40. 6 -0.1 %

-0.2 % -0.1 % -0.1 % -0.1 % -0.2 % -0.3 % -10.4 % -0.1 % -0.2 % -0.1 % -0.1 %



### wTabl e D-2 . Sensitivity Analysi s of Petroleu mMarke t

Parameter s Suppl y Elasticit

y Deman d Elasticit

y Chemical Pric e Closure s Petroleu m Chang e in Consume r Surplu s Petroleum Chemical Chang e in Produce r Surplu s Domesti c Producers Petroleu m Chemical Distributio n Service s Foreign Producers Petroleu m Chemical Tota l Socia l Cos t Bas e Cas e 1.2 -0. 6 $19 2

0
-$23.7 7 -$12.8 0 -$10.9 7 -$16.8 9 -$19.8 6 -$8.7 4 -$11.4 5 $0.3 3 $2.9 7 $2.3 9 $0.5 8 -$40. 7 Case l

1. 2 -0. 6 $14 4 (-25% )

- 1 Percen t Differ Valu e enc e -$23.7 4 -0.1 % -$12.7 7 -0.2 % -$10.9 7 0.0 % -$16.9 1 0.1 % -$19.8 7 0.1 % -$8.7 2 -0.3 % -$11.4 5 0.0 % $0.2 9 -11.8 % $2.9 6 -0.2 % $2.3 8 -0.2 % $0.5 8 0.0 % -$40. 7 0.0 % Cas e 2 1. 2 -0. 6 $24 0 (+25% ) 0 Percen t Differ Valu e enc e -$23.7 9 0.1 % -$12.8 1 0.1 % -$10.9 8 0.0 % -$16.8 9 0.0 % -$19.8 6 0.0 % -$8.7 6 0.2 % -$11.4 5 0.0 % $0.3 5 7.1 % $2.9 7 0.1 % $2.3 9 0.1 % $0.5 8 0.0 % -$40. 7 0.0 % Cas e 3 0. 7 -0. 2 $19 2

0 Valu e -$25.9 5 -$14.9 7 -$10.9 8 -$14.7 4 -$18.1 1 -$7.0 5 -$11.4 5 $0.3 9 $3.3 7 $2.7 9 $0.5 8 -$40. 7 Percen t

Differ enc e 9.2 % 17.0 % 0.0 % -12.8 % -8.8 % -19.3 % 0.0 % 18.9 % 13.7 % 17.0 % 0.0 % 0.0 % Cas e 4

0. 7 -0. 6 $19 2

0 Percen t Differ Valu e enc e -$21.3 3 -$10.3 5 -$10.9 8 -$19.3 6 -$21.8 7 -$10.7 8 -$11.4 5 $0.3 6 $2.5 1 $1.9 3 $0.5 8 -$40. 7 -10.3 %

-19.1 % 0.0 % 14.6 % 10.1 % 23.3 % 0.0 % 10.1 % -15.4 % -19.1 % 0.0 % 0.0 % Cas e 5

0. 7

- 1 $19 2

0 Percen t Valu e Differ-enc e -$18.8 9 -$7.9 1 -$10.9 8 -$21.8 0 -$23.8 5 -$12.7 5 -$11.4 5 $0.3 5 $2.0 5 $1.4 8 $0.5 8 -$40. 7 -20.6 %

-38.2 % 0.0 % 29.0 % 20.1 % 45.9 % 0.0 % 5.4 % -30.7% . -38.2 % 0.0 % 0.0 % (continued )Tabl e D-2 . Sensitivity Analysi s o f Petroleu mMarke t

Parameter s (continued )

O I Suppl y Elasticity Deman d Elasticity Chemical Pric e Closure s Petroleu m Chang e i n Consume r Surplus Petroleu m Chemica l Chang e i n Produce r Surplu s Domestic Producers Petroleu m Chemical Distributio n Service s Foreig n Producers Petroleu m Chemical Tota l Socia l Cos t Cas e 6 1. 2 -0. 2 $19 2 0 Percen t Valu e -$27.4 6 -$16.4 9 -$10.9 8 -$13.2 0 -$16.8 6 -$5.7 8 -$11.4 5 $0.3 7 $3.6 5 $3.0 7 $0.5 8 -$40. 7 Differ enc e 15.5 % 28.8 % 0.0 % -21.8 % -15.1 % -33.9 % 0.0 % 12.0 % 23.2 % 28.8 % 0.0 % 0.0 % Cas e 7

1. 2

- 1 $19 2 0 Valu e -$21.4 3 -$10.4 6 -$10.9 7 -$19.2 3 -$21.7 6 -$10.6 2 -$11.4 5 $0.3 1 $2.5 3 $1.9 5 $0.5 8 -$40. 7 Percen t

Differ enc e -9.8 % -18.3 % 0.0 % 13.9 % 9.6 % 21.5 % 0.0 % -7.6 % -14.7 % -18.3 % 0.0 % 0.0 % Cas e 8

1. 8 -0. 2 $19 2

- 2 Valu e -$28.2 6 -$17.2 8 -$10.9 8 -$12.3 9 -$16.2 0 -$5.0 9 -$11.4 5 $0.3 5 $3.8 0 $3.2 2 $0.5 8 -$40. 7 Percent

Differ enc e 18.9 % 35.0 % 0.0 % -26.6 % -18.4 % -41.7 % 0.0 % 4.4 % 28.2 % 35.0 % 0.0 % 0.0 % Cas e 9

1. 8 -0. 6 $19 2

- 2 Percen t Differ Valu e -$25.3 4 -$14.3 7 -$10.9 7 -$15.3 1 -$18.5 7 -$7.4 2 -$11.4 5 $0.3 0 $3.2 6 $2.6 8 $0.5 8 -$40. 7 enc e

6.6 % 12.3 % 0.0 % -9.4 % -6.5 % -15.1 % 0.0 % -9.8 % 9.9 % 12.3 % 0.0 % 0.0 % Cas e 1 0

1. 8

- 1 $19 2

- 2 Percen t Valu e Differ-enc e -$20.5 1 -$9.5 4 -$10.9 7 -$20.1 4 -$22.5 0 -$11.2 7 -$11.4 4 $0.2 2 $2.3 6 $1.7 8 $0.5 8 -$40. 7 -13.7 %

-25.4 % 0.0 % 19.2 % 13.3 % 29.0 % 0.0 % -33.2 % -20.5 % -25.4 % 0.0 % 0.0 %



## 1

# 2 P.1 4

dp s d c d P D d c 

### _ n D 

### e s (D.lc ) wher e dp A D = pric e pai d b

y consumers dp AS =pric e received by supplier s d c = per-uni

t contro l cost s e A s =elasticit

y o f suppl y n A d =elasticit

y o f deman d For example , i

n the bas e cas e fo

r the chemica

l market , bot

h suppl y an d deman d elasticit y ar e equa l (1.5 , -1.5) . Using Eq . (D.1) , w e find tha t th e per-unit

contro l cost s i s spli t betwee n consumer s and producer s equally . I n cas e 6 , we assum

e consumer s ar

e les s responsiv e t o change s i

n pric e (i.e. , th e deman

d elasticit y to -0.8) . Using Eq . (D.1) , w e conclude tha

t consumer s would bea

r roughl y two-third s o

f th e contro l cost s unde

r thi s assumption , an

d the los s i n consume r surplu s increase s b y 3 0 percent . • Closure projections slightly increase —one closur e ma y occu r i n eac h marke t i f w e reduc e th e baseline pric e b y 25 percent . Tw o closure s ma y occu r whe n th e suppl y parameter s i s mor

e elasti c relative to th e bas e case .

D- 6

/ ifc