v>EPA
United States
Environmental Protection
Agency
O'fice of
Policy Analysis
Washington, DC 20460
EPA-230-04-82-004
Water
Economic Analysis
of the Potential
Closure Impact
of the Final Steel Industry
Effluent Guidelines
Regulations
QUANTITY
-------
ECONOMIC ANALYSIS OF THE
POTENTIAL CLOSURE IMPACT
OF THE FINAL STEEL INDUSTRY
EFFLUENT GUIDELINES REGULATION
Environmental Protection Agency
Office of Policy Analysis
April 1982
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TABLE OF CONTENTS
A. EXECUTIVE SUMMARY 1
B. INTRODUCTION AND LIMITATIONS 3
C. SUMMARY OF METHODOLOGY AND RESULTS 5
D. PLANT MODELS AND ASSUMPTIONS 10
APPENDIX 1: SUMMARY OF SCREENING ANALYSIS 1-1
APPENDIX 2: PLANT MODEL CONFIGURATIONS 2-1
APPENDIX 3: SUMMARY OF MAJOR ASSUMPTIONS 3-1
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ECONOMIC ANALYSIS OF THE POTENTIAL CLOSURE IMPACT
OF THE FINAL STEEL INDUSTRY EFFLUENT GUIDELINES REGULATION
A. EXECUTIVE SUMMARY
As part of a larger analysis of the economic impact
of the steel industry effluent guidelines regulation
completed for the Agency by Temple, Barker and Sloane,
Putnam, Hayes & Bartlett has analyzed the potential
closure impact of increased costs associated with water
pollution control on 12 individual model steel plants.
The configurations of these model plants were patterned
after 12 specific domestic steel plants previously
identified as likely to be most seriously affected by the
regulation. The production cost estimates derived from
the plant models are based on the assumption that each
process in each plant model has national average operating
characteristics and that each plant must pay national
average prices for its inputs of raw materials and labor.
Therefore, production cost estimates should not be
attributed to the actual plant whose process configuration
forms the basis for the model.
The Operations Update Analysis prepared by EPA's
technical contractor provided estimates of the total
operating costs, including the capital recovery costs of
prospective additional investment, associated with
in-place, BPT and BAT levels of water pollution control
for each of the 12 model plants. For each model plant
analyzed, the increase in total operating costs, including
the capital recovery costs of additional investment
associated with meeting both the BPT and the BAT
standards, ranges from 0.06 to 0.64 percent of total
production cost and averages 0.21 percent. On a dollars
per shipment ton basis, the additional costs associated
with meeting both the BPT and the BAT standard range from
$0.21 to $2.60 per net ton and average only $0.82 per net
ton. On this basis, Putnam, Hayes & Bartlett has
concluded that the increases in operating and capital
costs associated with meeting this regulation would be
unlikely to force the closure of any of the model plant
configurations analyzed.
Partial closure (that is, closure of one or more
finishing mills) would be predicted if, as a result of
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compliance with the regulation, a finished product no
longer generates revenues in excess of variable production
costs plus avoidable cash fixed costs. For the 12 plants
analyzed, additional operating costs associated with
meeting both the BPT and BAT standards for the primary
coking, iron and steelmaking processes accounted for most
of the costs which could be allocated to a specific
process. Operating cost increases associated with
finishing processes generally reflect centralized
treatment facilities whose costs are borne by a number of
different finishing processes. The analysis did not
indicate any finishing processes for which the additional
operating costs attributable solely to that process were
sufficient to indicate a likelihood of partial closure.
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B. INTRODUCTION AND LIMITATIONS
As part of a larger analysis of the economic impact
of the steel industry effluent guidelines regulation
completed for the Agency by Temple, Barker and Sloane
(TBS) , Putnam, Hayes & Bartlett (PHB) analyzed the likely
impact of the regulation on individual steel plants. The
primary purpose of this analysis was to determine whether
increased costs associated with compliance with the BPT
and BAT limitations are likely to result in closures or
partial closures of those integrated steel plants covered
by the regulation. In order to perform this analysis, PHB
first undertook a broad screening analysis to determine
specific plants most likely to be seriously affected by
regulation. Various indicators of corporate financial
strength, product mix profitability, and relative
competitive strength by plant were reviewed in order to
rank actual steel plants by likely degree of impact.
Details of this analysis are given in Appendix 1 of this
report. Based on the results of the screening analysis,
12 plants were selected in consultation with, and with the
approval of EPA as likely to be most seriously affected by
the BPT and BAT steel industry regulation. The plants
selected for detailed analysis are listed below:
Company Plant
1. Bethlehem Steel Lackawanna, NY
2. Jones & Laughlin Cleveland, OH
3. Jones & Laughlin Indiana Harbor, IN
4. Kaiser Steel Fontana, CA
5. McLouth Steel Trenton, MI
6. National Steel Weirton, WV
7. Republic Steel- Gadsden, AL
8. Sharon Steel Farrell, PA
9. U.S. Steel Fairless, PA
10. U.S. Steel Geneva, UT
11. U.S. Steel Homestead, PA
12. Wheeling-Pittsburgh Steubenville, OH
PHB formulated 12 model steel plants based on the
configurations of production processes present at each of
these 12 specific domestic steel plants. For purposes of
this study, the production cost estimates derived from PHB
plant models are based on the assumption that each process
in each plant has national average operating
characteristics and that each plant must pay national
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average prices for its inputs of raw materials and labor.
Therefore, the production cost estimates derived in the
analysis should not be attributed to the actual plant
whose process configuration forms the basis for the model.
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C. SUMMARY OF METHODOLOGY AND RESULTS
The individual steel plant models developed by PHB
were designed to calculate the minimum cost of producing a
given mix of end products, assuming the input factor
costs, process configurations and capacity limitations
specified in the models. Production costs calculated in
the plant models reflect direct cash costs, including
cash overhead and allocated selling, administrative and
general expenses (S,G&A). Noncash costs such as
depreciation and indirect costs such as corporate interest
or taxes are not included in the plant model cost esti-
mates. Because 1980 was a relatively depressed year in
terms of shipment tonnage and because plant-specific
production data are available only from steel company 308a
responses covering the years 1974 to 1976, PHB has
attempted to determine an "average" expected tonnage level
and product mix for each plant based on the best
information currently available regarding the most likely
pattern of future shipments.*
The results contained in this study reflect 1980
input factor costs, i.e., labor costs, ore costs,
electricity costs, etc., and are expressed in 1980
dollars. All input factor prices reflect national
averages and are consistent with those in the TBS
industrywide impact study, except for purchased coke costs
which were not estimated by TBS. The use of national
average input factor prices is further discussed in
Appendix 3. The Cyrus Rice Division of MUS Corporation,
the Agency's technical contractor, provided estimates of
the total operating costs, including the capital recovery
costs of additional investment, associated with in-place,
BPT and BAT levels of water pollution control for each of
the 12 model plants. Capital recovery costs were
calculated using a capital recovery factor of 0.0899.
This factor reflects recent changes in the tax laws and is
consistent with the interest rate and debt-financing
* Obtaining more recent data would have required a new
data request imposing an additional burden on the
companies involved. In addition, these data are
generally considered to be extremely confidential.
Moreover, it would not have been possible to obtain
these data and to neet the court-ordered deadline of
31 January 1982.
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assumptions made in TBS' industrywide analysis. Estimates
of the total operating costs associated with in-place air
pollution control equipment were derived from estimating
equations developed for the Agency by PEDCo Environmental,
Inc.
The results of the analysis are summarized in Tables
C-l and C-2. As shown in Table Ol, for the 12 model
plants analyzed, the increase in total operating costs
associated with meeting the BPT limitations ranges from
zero to 0.20 percent and averages 0.07 percent. The
increase in total operating costs associated with meeting
both the BPT and the BAT limitations ranges from 0.06 to
0.64 percent and averages 0.21 percent. As shown in Table
C-2, on a dollars per shipment ton basis the additional
operating costs associated with meeting the BPT
limitations range from zero to $0.77 per net ton and
average $0.29 per net ton. The additional costs
associated with meeting both the BPT and the BAT
limitations range from $0.21 to $2.60 per net ton and
average $0.82 per net ton. On a dollars per shipment ton
basis, the largest impact of meeting the BAT limitations
is seen at the model configuration of the Republic Steel
Gadsden plant. The relatively high cost of $2.60 per ton
stems from an unusual need for a storm water diversion
system to reduce the volume of water that might flow
through various treatment processes.
On the basis of these results PHB concludes that the
increases in operating costs, including capital recovery
costs, associated with meeting the final steel industry
regulation would be unlikely to force the closure of any
of the model plant configurations analyzed.
Partial closure (that is, closure of one or more
finishing mills) would be predicted if, as a result of
compliance, a finished product no longer generates a total
contribution* in excess of its own avoidable cash fixed
costs. For the 12 plants analyzed, additional operating
costs associated with meeting both the BPT and BAT
limitations for the coking, iron and steelmaking processes
accounted for most of the costs which could be allocated
to a specific process. Operating cost increases
For purposes of this study, contribution is defined
as revenues less variable production costs.
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Table C-l
IMPACT OF BAT STEEL INDUSTRY REGULATION ON AVERAGE
PRODUCTION COST PER NET TON BY PLANT
Average Production Cost per Net Ton nt
Various Levels of Control (1980 $/NT)
Model Configuration
(Company /Plant)
Bethlehem Steel/
Lackawanna
Jones & Laugh lin/
Cleveland
Jones & Laughlin/
Indiana Harbor
Kaiser Steel/
Fontana
t McLouth Steel/
>j Trenton
1 National Steel/
Weir ton
Republic Steel/
Gadsden
Sharon Steel/
Far re 11
U.S. Steel
Fairless
U.S. Steel/
Geneva
U.S. Steel/
Homestead
Whee ling-Pittsburgh/
Steubenville
In-Place
& Ad-
In-Place ditional
None
393
364
409
447
330
431
404
382
388
374
426
347
12-Plant Average Increase in
Air
394.83
364.30
410.36
449.80
330.37
432.13
405.71
382.59
388.85
375.47
426.63
348.37
Cost per
Air
395
364
411
450
330
432
406
382
389
376
427
349
Ton
.62
.46
.11
.14
.52
.75
.81
.88
.23
.45
.11
.10
All Air &
In-Placc
Water
397.80
365.12
412.30
451.76
333.99
433.96
405.12
383.80
390.82
375.57
426.84
351.58
After
BPT
398.
365.
412.
452.
334.
434.
405.
384.
391.
375.
427.
351.
38
16
50
39
12
11
39
15
59
57
04
73
Percentage Increase
in Production Costs*
After
BPT &
BAT
398.
365.
412.
452.
334.
434.
407.
384.
391.
376.
427.
352.
90
33
83
55
28
85
72
39
88
51
18
03
BPT
0.15
0.01
0.05
0.14
0.04
0.03
0.07
0.09
0.20
0.00
0.05
0.04
0.07
BAT
0.28
0.06
0.13
0.17
0.09
0.21
0.64
0. 15
0.27
0.25
0.08
0.13
0.21
Percentage increase Ln cost per ton relative to the all air plus in-place water pollution
control baseline cost.
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Table C-2
WATER POLLUTION CONTROL
ESTIMATED OPERATING AND CAPITAL RECOVERY COSTS
($ 1980/NT)
Model Configuration
(Company/Plant)
Bethlehem Steel/
Lacks wanna
Jones & Laughlin/
Cleveland
Jones & Laughlin/
Indiana Harbor
Kaiser Steel/
Fontana
McLouth Steel/
Trenton
, National Steel/
<* Weirton
Republic Steel/
Gadsden
Sharon Steel/
Farrell
U.S. Steel/
Fairless
U.S. Steel/
Geneva
U.S. Steel/
Homestead
Wheeling-Pittsburgh/
C +• A«l1>AV«*r 1 11*-*
Assumed
Shipment
Tonnage
(M NT)
2
2
2
1
1
2
0
1
2
1
2
2
.0
.2
.0
.6
.8
.6
.7
.1
.9
.7
.15
.05
Additional Treatment
Levels (Incremental)
In-Place
$2.
0.
1.
1.
3.
2.
-1.
0.
1.
-0.
-0.
2,
18
66
19
62
47
96
69*
92
59
88*
27*
48
BPT
$0
0
0
0
0
0
0
0
0
0
0
0
.58
.04
.20
.63
.13
.15
.27
.35
.77
.00
.20
.15
BAT
SO.
0.
0.
0.
0.
0.
2.
0.
0.
0.
0.
0.
52
17
33
16
16
74
33
24
29
94**
14
30
Total
Additional
Cost
$1
TT •*• •
0.
0.
0.
0.
0.
2.
0.
1.
0.
0.
0.
10
21
53
79
29
89
60
59
06
94
34
45
3 2-Plant Average Cost per Ton
$1.19
$0.29
$0.53
$0.82
* Negative operating costs result from credits for by-products such as mill scale,
acid, etc.
** Includes some consent decree requirements.
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associated with finishing processes susceptible to partial
closure generally reflect centralized treatment facilities
whose costs are borne by a number of different finishing
processes. The largest impact on a single finishing
process was approximately $438,000 per year in additional
operating costs associated with meeting the BPT
limitations at the rod mill at U.S. Steel's Fairless Hills
plant. The rod mill represents an unusual case where
geographical considerations require installation of
certain treatment facilities specifically to serve the rod
mill. Virtually all of this cost is a relatively fixed
cost associated with capital recovery and labor.
Therefore, the per unit contribution of rod output will
not be appreciably reduced. However, absorption of this
cost will require an additional contribution of
approximately $1.00 per ton based on an assumed shipment
tonnage of 400,000 tons. Operating the mill at its
reported capacity of 780,000 tons would reduce the impact
of the additional contribution to about $0.60 per ton.
Our analysis did not indicate any finishing processes for
which the .additional operating costs attributable solely
to that process were sufficient to indicate a likelihood
of partial closure.
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D. PLANT MODELS AND ASSUMPTIONS
1. The PHB Plant Models
The individual steel plant models formulated by PHB
are designed to calculate the minimum cost of producing a
given mix of end products, assuming the process
configurations and capacity limitations specified in the
models. The individual steel plant models were
constructed using the input factor usage rates and
material balance yields contained in the Arthur D. Little/
American Iron and Steel Institute database. This database
was initially developed by ADL with the cooperation of
AISI as part of ADL's 1975 industry study, "Steel and the
Environment — A Cost Impact Analysis." The database was
refined and updated as part of the 1973 ADL follow-up
study of the same title. The updated database reflects
1976 operating conditions and incorporates information
from 100 of the 129 AISI member plants. The 100 plants
that contributed to the updated database accounted for
about 87.7 percent of 1976 U.S. total raw steel capacity
and 83.6 percent of 1976 raw steel production.
The ADL/AISI database provides information on input
factor usage rates and material balance vields for each of
•27 distinct iron and steel production processes. The
ADL/AISI database summary available to the Agency reflects
the average operating characteristics of each process in
the database. Thus, the plant models developed bv PHB
based on this database calculate production costs assuming
that a plant has average operating characteristics for
each of the production processes contained in its
configuration.
Baseline production costs calculated bv the plant
models reflect direct cash costs, including allocated cash
overhead and selling, administrative and general expenses
(S,G&A). Noncash costs such as depreciation and indirect
costs such as corporate interest or taxes are not included
in these plant model cost estimates. The allocations of
overhead and S,G&A to various plants and processes reflect
the practices of the steel companies making the original
data submissions to ADL/AISI.
Although steel plant overhead and S,G&A expenses are
largely fixed costs with respect to tonnage, the ADL/AISI
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summary database reports these costs on a normalized "per
ton" basis. Thus, the magnitude of the overhead cost
component depends on the tonnage assumption used to
"reconstitute" the original total dollar figure. The
plant models incorporate an estimate of fixed overhead
derived by applying the ADL/AISI per ton overhead factors
to the tonnage flow at each process given an output level
and product mix which approximates that experienced in
1976 when the ADL/AISI database was compiled.
The plant models are based on the process
configurations and capacities reported for each plant in
the Operations Update Analysis prepared by the Cyrus Rice
Division of NUS Corporation. The process configurations
and capacities reported are based on 308a questionnaire
responses received from steel companies. Capacity figures
for "Phase I" iron and steelmaking processes were based on
reported rated capacities. Capacity figures for "Phase
II" finishing orocesses were based on peak actual
production.
The plant models reflect the minimum cost of
producing a specified tonnage and product mix. Because
1980 was a relatively depressed year in terms of shipment
tonnage (particularly for light flat-rolled products), and
because plant-specific production data are generally
available only from steel company 308a responses covering
the years 1974 to 1976, PHB determined an "average"
expected tonnage level and product mix for each olant
based on the best information currently available
regarding the most likely pattern of future shipments.
The finished product demands imposed on each olant model
to generate production cost estimates are summarized in
Table D-l on the following page.
In the case of the model patterned after the U.S.
Steel Homestead plant, a number of adjustments were
necessary to reflect more accurately the processes at that
plant. " The information compiled by the technical
contractor indicates that the Homestead/Rankin complex has
no coking or sintering capacity and only about 1.61
million tons of blast furnace hot metal capacity.
However, the U.S. Steel Homestead/Rankin complex, along
with other U.S. Steel plants in the Monongahela Valley, is
provided with coke and coke-oven gas from the nearby
Clairton coke plant. Also, the U.S. Steel Saxonburg
sinter plant provides large-scale sintering capability to
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Table D-l
FINISHED PRODUCT DEMAND (Millions of Net Tons)
10
I
C'luuj ««my / 1'lnnl
Hot-Rolled
llol-liolld.l Slionl Colil-ItaI It'll Tin Mill
Sliuclurals Sheet I'lck. I_OM ^"i _ j'lo-lifta C«l^?.'il. ?ffi
Vlntf
l«u«l Plate L'lfll-i-51L
SLt-el/
Junua & l.au.jlillii/
I mil Ana llarlKir
Kalbur Uloel/Fonlrtiia
M<.li>iii|l> Sleul/Tronloii
H.^lli.ii.il Sleel/Molt ton
H.'piit.l li. SI oel/i:.ulsil«--n
Uhiiion bti-el/ Km re 1 1
U.S. ULc-ol/Kali loss
tl S. SLfi'l/Cciiuva
II S. Sleul/lioraualed.l
Vlliui-l lii<|- I'll I slim ijli/
Slc'iilieiivl I lu
. J
1.0
1.0
.4
•I'.il a I
Tonuatju
2 O
2.2
.6 .2
.4 .1
.11 10
.9 .1
.2
.4 .1
7
.4 "»
.7
.4 .5 .3
.4 .2 .5
1.0 .4
.1 .1 -J
.4 .1
.5 -f. -2 .J .2 .«
.1 .4
1.4 05
2.0
1.6
I.B
2 f>
•'
1. 1
2.9
1 .'1
2 15
1.0
.05
2.05
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the U.S. Steel plants in the Monongahela Valley, including
the Homestead/Rankin complex. Furthermore, approximately
0.77 million tons of excess blast furnace capacity at the
Edgar Thomson Works in Braddock is available to Homestead
via submarine ladle car. Therefore, for purposes of this
studv, the Homestead plant configuration was modeled
assuming 2.38 million tons of hot metal capacity and
assuming that hypothetical 1.2 million ton coking and 1.08
million ton sintering facilities were available at the
Homestead site.
Process flow diagrams showing the plant configura-
tion, process capacities, end product mix and intermediate
process flows for each of the 12 plants PHB has modeled
are included in this study as Appendix 2. All figures are
given in millions of ' net tons. Within each box
representing a process step, figures to the left of the
slash represent the process operating level, while figures
to the right of the slash represent the assumed annual
capacity of the process. The notations S, iM and L
indicate whether the process is classified as a small,
medium or large one for purposes of applying the ADL/AISI
database.
2. Input Factor Costs
The plant model cost estimates reflect 1980 factor
costs and are expressed in 1980 dollars. With the
exception of purchased coke costs, factor costs were taken
from the Agency's Economic Analysis of Final Effluent
Limitations Guidelines. These factor costs reflect
national averages 'and are summarized below.
INPUT FACTOR COSTS (S 1980)
Labor 518.45/hr.
Ore See text below
Met. Coal $63.90/NT
Scrap S91.62/NT
Fuel S3.64/mmBTU
Power $0.034/KWH
Purchased Coke ?110.00/NT*
In addition to these input factor costs, the production
cost functions contained in the olant models also include
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a summation of the ADL/AISI estimated overhead and S,G&A
cost and maintenance, other raw materials, other utilities
and miscellaneous costs per ton for each process step.
These ADL/AISI 1976 dollar figures are the best available
data and were inflated to 1980 dollar values using the
price indices contained in the Agency's industrywide
study.
PKB used different ore cost figures for each plant to
reflect expected differences in the proportions of sinter,
lump ore and pellets used to charge the blast furnaces.
The ADL/AISI factor usage rates assume the following
standardized ore mix:
Ore Inputs Ore Cost
(NT/NT Hot Metal) ($ 1980/NT)
Pellets .86 $38.74
Sinter .45
Lump Ore .19 22.89
Total 1.50
For plants without a sinter strand, PHB assumed that
pellets would be substituted for sinter. For these
plants, an ore cost of $36.72/NT was used, based on the
following calculation:
[{(.86 + .45) * $38.74) + (.19 * $22.89)1/1.50 = $36.72
For plants with a sinter strand, PHB assumed that the
sinter strand would be operating at 85 percent capacity
utilization, the average "capacity utilization underlying
the ADL/AISI database. Remaining ore needs were balanced
with pellets, such that sinter, pellet, and lump ore
requirements totaled 1.5 times hot metal requirements.
Ore cost was then calculated as a weighted average, with
the lump ore and sinter proportion of total ore needs
valued at $22.89/NT and the pellet proportion valued at
$38.74/NT. The costs of processing the lump ore required
as input for the sinter strand is included in the
This estimate derived by PHB.
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production costs estimated by the models. The estimated
ore costs by model plant are summarized below:
Model Weighted Average
Company Plant Ore Cost (1980 $/NT)
Bethlehem Steel Lackawanna $31.19
Jones & Laughlin Cleveland 36.72
Jones & Laughlin Indiana Harbor 31.13
Kaiser Steel Fontana 29.78
McLouth Steel Trenton 36.72
National Steel Weirton 27.15
Republic Steel Gadsden 30.67
Sharon Steel Farrell 36.72
U.S. Steel Fairless 28.26
U.S. Steel Geneva 30.34
U.S. Steel Homestead 31.92
Wheeling- Steubenville 34.52
Pittsburgh
The price of purchased coke was based on production
costs indicated for on-site coke production, as well as
data collected on Form EIA 5, "Coke Plant Report
Quarterly" by the Energy Information Administration (EIA)
of the U.S. Department of Energy. The EIA data indicate
that purchased coke for blast furnace use had an average
price of about $100 per net ton in 1980. However, this
figure does not reflect transportation costs and is very
heavily influenced by transfer-pricing practices at
integrated steel works. The EIA data also indicate an
average 1980 merchant coke price of around $116 per net
ton. However, this figure is heavily influenced by
shipments of higher-grade foundry coke and does not
reflect transportation costs. In addition, the EIA data
are heavily influenced by spot prices whereas the plants
which rely on purchased coke generally purchase under
long-term contracts. PHB assumed that the purchased coke
price would be at least high enough such that the plants
with on-site cokemaking would choose to produce their own
coke, as opposed to purchasing off-site coke. On this
basis, PHB used a purchased coke price of $110 per ton
delivered, which is consistent with the range of EIA data.
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3. Capital Recovery Factor
The purpose of a capital recovery factor is to
annualize capital investment costs over the useful life of
an asset. Annualizing capital investment costs using a
capital recovery factor procedure is not the same as using
a deoreciation schedule to calculate depreciation expense
for accounting purposes. The purpose of a depreciation
schedule is to match the historic cost or book value of an
investment with accounting revenues occurring over the
useful life of the asset. A capital recovery factor
indicates the magnitude of a series of periodic cash flows
which, over the useful life of the asset, will have a
discounted present value equal to the discounted present
value of the investment. The discounted oresent value of
an investment is generally not the same as its book value
due to the impact of investment tax credits, tax-deduct-
ible noncash expenses such as depreciation and tax-deduct-
ible investment-related expenses such as interest and
property taxes.
In accordance with the assumptions contained in TBS1
study for EPA, PHB assumed that pollution control capital
expenditures would be financed 20 percent by corporate
debt and 80 percent by industrial revenue bonds. TBS
determined the interest rate on the corporate debt by
adding a premium of 2.7 percent to the inflation rate
assumed for the period 1981 to 1982. The tax-exempt
interest rate was assumed to be. two-thirds of the
nonexempt interest rate. A marginal income tax rate of
50.1 percent was assumed, based on a marginal federal rate
of 46 percent and a tax-deductible average state tax rate
of 7.55 percent. An investment tax credit of 10 percent
and the five-year capital recovery tax depreciation
factors were- assumed to apply to investments in pollution
control equipment associated with steel mill equipment. A
property tax" ra.te of 2.38 percent of net book value was
also assumed, based on 14-year straightline depreciation
for book purposes.
Given the assumptions listed above, the inflation
rate proiection of 9.4 percent for 1981 implies a weighted
average interest rate on pollution control debt of 8.91
percent:
(9.4 + 2.7) * .2 + .67 * (9.4 + 2.7) * .8 = 8.91%
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Using this discount rate to calculate the present value of
$1.0 million investment in pollution control equipment
vields an estimated present value of the outlay of
5351,020. Annualizing this outlay over a 14-year period
at the assumed rate of interest results in a level annual
payment of $44,854 after taxes, which implies an outlay of
$89,889 before taxes. Normalizing the before-tax outlay
by the initial investment of $1.0 million results in a
capital recoverv factor for pollution control equipment of
0.0899.
4. Pollution Control Costs
Estimates of the total operating and capital recovery
costs associated with in-place, BPT and BAT levels of
water pollution control for each of the 12 plants were
provided by the Cyrus Rice Division of NUS Corporation.
Capital recovery costs were calculated using a capital
recovery factor of 0.0899. PHB removed the caoital
recoverv cpmponent from the estimate of operating costs
for in-place equipment. In-place equipment represents a
sunk cost, rather than a current investment decision, and
thus provisions for capital recovery on incremental
investment do not applv. Table D-2 summarizes the
estimates of total operating costs associated with
in-place water treatment facilities, plus total operating
and capital recovery costs associated with BPT and BAT
levels of water pollution control. The estimates have
been inflated from 1978 dollars to 1980 dollars using an
inflation factor of 1.25. This factor is consistent with
the appropriate mix of price indices contained in the
industrywide analysis.
PHB added the figures shown in Table D-2 to the
production costs calculated by the plant models. Because
the treatment cost estimates are predicated on a higher
utilization than is likely to orevail in the near future,
the estimates shown in Table D-2 may somewhat overstate
the variable pollution control costs that might be
incurred at these plants. However, anv such
overestimation, while not significant, serves onlv to
reinforce PHB's conclusions.
Estimates of the operating costs associated with
in-place air pollution control equipment were derived fron
estimating equations contained in the Julv 1979 PEDCo
-17-
-------
Table D-2
WATER POLLUTION CONTROL
ESTIMATED OPERATING AND CAPITAL RECOVERY COSTS
($ 1980 M)
Additional
Treatment Levels
(Incremental)
Model Configuration
(Comoanv/Plant)
Bethlehem Steel/
Lackawanna
Jones & Laughlin/
Cleveland
Jones & Laughlin/
Indiana Harbor
Kaiser Steel/
Fontana
McLouth Steel/
Trenton
National Steel/
Weirton
Republic Steel/
Gadsden
Sharon Steel/
Farrell
U.S. Steel/
Fairless
U.S. Steel/
Geneva
U.S. Steel/
Homestead
Wheeling-Pittsburgh/
Steubenville
Total Ad-
ditional
In-Place
4
1
2
2
6
7
_ i
1
4
-1
-0
5
.36
.46
.38
.59
.24
.69
.18*
.01
.60
.49*
.58*
.08
1
0
0
0
0
0
0
0
2
0
0
0
BPT
.16
.09
.39
.90
.24
.39
.19
.39
.23
.00
.44
.30
BAT
1
0
0
0
0
1
1
0
0
1
0
0
.03
.38
.66
.25
.28
.93
.63
.26
.83"
.60**
.30
.61
Cost
2.
0.
1.
1.
0.
2.
1.
0.
3.
1.
0.
0.
19
47
05
15
52
32
82
65
06
60
74
91
* Negative operating costs result from credits for by-products
recovered such as mill scale, acid, etc.
*"* Includes some consent decree recuirements.
-18-
-------
Environmental, Inc. studv for the EPA entitled Development
of Air Pollution Control Cost Functions for the Integrated
Iron and Steel Industry.The estimates were derived using
the equationforthe level of control, RACT, BACT, or
LAER, " specified by PEDCo as corresoonding with the
requirement contained in the typical State Implementation
Plan (SIP) for each process with significant emissions,
both fugitive and stack. The cost estimates derived from
the PEDCo equations are based on the capacities of the
various processes in each plant configuration and have
been inflated from mid-1977 to 1980 dollars using a factor
of 1.25. Because the estimates given by the equations
reflect the cost of full compliance with the level of
control specified in the typical SIP, the estimates have
been adjusted to reflect the average L980 percentage of
compliance for each process reported in the industrvwide
studv in conjunction with the Division of Stationarv
Source Enforcement of EPA. These percentage of conpliance
figures are summarized in Table D-3. The estimates of
total operating costs for in-place air pollution control
are summarized in Table D-4.
-19-
-------
Table D-3
AIR POLLUTION CONTROL
PERCENTAGE OF COMPLIANCE FACTORS -- 1980
Percent of Comoliance
Process
Ore Yard
Coal Yard
Sintering
Coke Ovens
Blast Furnace
Open Hearth
Basic Oxygen
Electric Furnace
Continuous Casting
Primary Breaking
Pickling & Galvanizing
Other Finishing
Stack
95
90
80
NA
95
75
85
85
100
90
100
80
Fugitive
95
90
60
65
10
25
40
55
100
90
100
80
SOURCE: Temple, Barker & Sloane, Inc., in conjunction with the
Division of Stationary Source Enforcement of EPA.
-20-
-------
Table D-4
AIR POLLUTION CONTROL
ESTIMATED DIRECT OPERATING COSTS
Model Configuration
(Comoanv/Plant) (
Bethlehem Steel/
Lackawanna
Jones & Laughlin/
Cleveland
Jones & Laughlin/
Indiana Harbor
Kaiser Steel/
Fontana
McLouth Steel/
Trenton
National Steel/
Weirton
Republic Steel/
Gadsden
Sharon Steel/
Farrell
U.S. Steel/
Fairless
U.S. Steel/
Geneva
U.S. Steel/
Homestead
Wheeling-Pittsburgh/
Steubenville
Estimated
In-Place
Equipment
$ 1980 M)
3
0
2
4
0
3
1
0
2
-
2
1
2
.67
.66
.70
.50
.66
.00
.20
.65
.50
.51
.35
.80
Additional Total
Equipment Operating
Required Costs
(§ 1980 M) ($ 1980 M)
1
0
1
0
0
1
0
0
1
1
1
1
.57
.34
.52
.52
,
.27
.55
.76
.31
.07
.65
.03
.50
5
1
4
5
0
4
1
0
3
4
2
4
.24
.00
.22
.02
.93
.55
.96
.96
.57
.16
.38
.30
Total
Operating
Costs per
Shioment Ton
(S 1980/NT)
2
0
2
3
0
1
2
0
1
2
1
2
.62
.46
.11
.14
.52
.75
.81
.88
.23
.45
.11
.10
-21-
-------
SUMMARY OF SCREENING ANALYSIS APPENDIX 1
The broad screening analysis used to determine which
specific plants were most likely to be seriouslv affected
by the effluent guidelines regulations involved ranking
some 45 different plants of the 14 largest integrated
domestic steel companies according to each of three
indicative criteria. The three criteria used were product
mix profitability, plant competitiveness and companv
financial strength. Although relative rankings of the
plants were made for each criterion, the overall rating of
each plant was based on a somewhat subjective review which
attempted to take into consideration other relevant
factors which were not adequately reflected in the
analyses underlving the three specific rankings developed.
For example, the replacement potential for each plant by
another plant of the same companv was considered. If
other affiliated olants were able to provide similar
products to the same markets as the plant in question, its
vulnerability was increased.
The eventual selection of 12 specific plants was made
in consultation with and with the approval of the Agencv.
Table 2-1 summarizes the categorical rating of each plant
for each of the three indicative screening criteria.
Plants marked with an asterisk are those that wer«
eventually selected for further analysis of the likely
economic impact of the regulation.
-------
Table 1-1
SUMMARY OF PLANT SCREENING ANALYSTS
Plant
Financial Product Plant
Strength Mix Competitiveness
ARMCO A-
Ashland
Sutler
Houston
Kansas City
Middletown
BETHLEHEM B+
Bethlehem
Burns Harbor
Johnstown
*Lackawanna
Sparrows Point
Steelton
CF&I A-
Pueblo
INLAND A-
E. Chicago
INTERLAKE 3+
Riverdale
J&L/LTV C
Aliquippa
*Cleveland
Pittsburgh
*E. Chicago
Hennepin
KAISER C+
* Fontana
MC LOUTH C
* Trenton
B-
B-
B +
B+
B
A
B
B+
C+
B
B+
A-
B
B
B
B-
B
B
C
B-
3 +
B
B +
3-
B+
A
3 +
3-
3-
B
A-
3-
3 +
B
A-
3-
B
B
B
1-2
-------
Table 1-1
SUMMARY OF PLANT SCREENING ANALYSIS
(continued)
Plant
Financial
Strength
Product
Mix
Plant
Competitiveness
NATIONAL 3+
Granite City
Ecorse
*Weirton
Portage
REPUBLIC 3+
Buffalo
Canton
Cleveland
*Gadsen
S. Chicago
Warren
SHARON B
*Farrell
U.S. STEEL 3-
Baytown
Braddock
Duquesne
Fairfield
*Fairless
Gary
*Geneva
*Homestead
Lorain
S. Chicago
WHLG.-PITT. B
Monessen
*Steubenville
**ENVIRODYNE C
S. Chicago
C+
B-
C+
C
B
B
B-
B-
A-
B
B-
B +
3-
B
B
3
B
B+
3+
3+
B+
A
3-
3
B +
3 +
B-
B
3-
B +
B-
3-
3
3 +
B-
B +
.3-
3
B+
B-
3 +
3-
3-
B
B+
B-
3-
**
Not selected due to uncertainty surrounding
attempted reorganization under jurisdiction
of bankruptcy court.
1-3
-------
PRODUCT MIX PROFITABILITY
The product mix profitability portion of the
screening analysis attempted to develop an indication of
the profitability of each plant by categorizing the
products produced at each plant in terms of "average"
profitability. The "average" profitability of various
general steel products was determined by calculating the
cost of producing each product assuming a plant of
industry-average size, with a production-weighted mix of
furnace types and 1976 industry average charging ratios.
The cost of producing each product at this hypothetical
plant was calculated using the ADL/AISI database and 1978
factor prices. Costs per ton to produce each product were
then compared with the average prices per ton realized in
1973 for each general product category. The 1978 product
prices per ton were calculated from data contained in the
Department of Commerce publication MA-33B, "Current
Industrial Reports -- Steel Mill Products," by dividing
the value reported for shipments to other companies by the
reported tonnage shipped for each product category.
Dividing the difference between price per ton and cost per
ton (gross margin) by the price per ton resulted in an
approximate return on sales measure for each product
category. The products were then ranked in descending
order of return on sales. Rased on its relative ranking
in terms of return on sales, each product was then placed
into one of three general categories of profitability as
measured by return on sales. Products with the highest
indicated profitability were placed in Category A, less
profitable products in Category B and least profitable
products in Category C. The final step in the product mix
analysis was to apply the product profitability
categorization to the product mix at each specific plant
to obtain an average categorization (A, B or C) for each
specific plant.
The profitability categorization of each of 10
general products is summarized in Table 2-2. The very low
or negative margins associated with tin mill products and
galvanized products indicates that it is probably not
economic to produce these products at a plant which does
not have below average production costs as a result of
economies of larger scale operations or technologically
superior processes, such as continuous casters and basic
oxygen furnaces. The imoact of these plant-specific
1-4
-------
Table 1-2
RETURN ON SALES FOR INDUSTRY AVERAGE PLANT
Percentage Return on Sales*
Product Category A Category B Category C
Seamless Tube .64
Wire .29
Structurals .26
Welded Pipe .21
Bar and Rod .14
Hot Rolled Sheet .14
Plates .12
Cold Rolled Sheet .07
Tin Mill Products .03
Galvanized Products -.01
NOTE: Intraproduct category mix differences, esoecially for
pipe/tube and wire, may preclude cost and price from
being exactly comparable. The puroose of this
analysis is net to compute a precise margin for each
product but rather to group them into three general
categories according to profitability.
Price per ton minus cost per ton divided by price per
ton.
1-5
-------
indicators of lower production costs was considered in the
plant competitiveness analysis described below.
The average profitability categorization for each
plant is given in Table 2-3 on the following pages. Due
to the lack of detailed information on the volume of
production for each product at each plant, the '"averaging"
process involved in this analysis is more of a qualitative
than a quantitative exercise.
PLANT COMPETITIVENESS
The second indicative criterion used to rank plants
according to their likely degree of profitability was a
measure of plant competitiveness. As mentioned above,
scale of operations and type of technology used to produce
steel can have an impact on profitability independent of
product nix. In general, larger capacity blast furnaces,
the absence of open hearth steelmaking, extensive use of
continuous casting and the presence of on-site cokemaking
tend to indicate lower cost steel production and therefore
enhanced competitiveness. Table 2-4 summarizes a number
of key competitive indicators for each plant. Due to the
essentially qualitative nature of the data, the overall
competitiveness ranking derived from these indicators is
essentiallv a qualitative ranking, from A for the most
competitive through C for the least competitive in terms
of technology and configuration.
COMPANY FINANCIAL STRENGTH
The third indicative criterion PHB examined in order
to determine the vulnerability of a given plant was the
financial condition of its parent company. The companv
financial strength analysis focused on various financial
ratios which serve as indicators of profitability,
leverage and liquidity on a corporatewide basis. Gross
margin and return on equity were used as measures of
profitability, while debt to capitalization and cash flow
to long-term debt (Beaver's Ratio) were used as measures
of financial leverage. Days cash was used as a measure of
liquidity.
The company financial strength analysis involved
calculating the five ratios mentioned above for each of 14
1-6
-------
Table 1-3
PRODUCT MIX PROFITABILITY BY PLANT
Plant
Products1
Profitability
ARMCO
Ashland
Butler
Houston
Kansas City
Middletown
BETHLEHEM
Bethlehem
Burns Harbor
Johnstown
Lackawanna
Sparrows Point
Steelton
CFS.I
pueblo
INLAND
E. Chicago
INTERLAKE
Riverdale
J&L
Aliquippa
Cleveland
Pittsburgh
E. Chicago
Hennepin
HRS, CRS, galvanized
HRS, CRS
Plate, structural, bar, weld pipe
Bar/rod, wire
HRS, CRS, galvanized, weld pipe
Structural
Plate, HRS, CRS, TMP
Bar/rod, wire
CRS, bar, galvanized
Plate, HRS, CRS, TMP, rod, wire
weld pipe
Bar, rail, weld pipe
Rail, structural, bar/rod, wire
HRS, CRS, galvanized, bar,
structural, plate
HRS, CRS, weld pipe
HRS, CRS, TMP, bar/rod, weld pipe
seamless tube
HRS, CRS
Bar
HRS, CRS, TMP, galvanized, weld
pipe, seamless tube
CRS, galvanized
B-
B-
B +
B +
B
A
B
3 +
C +
B
B+
A-
B
3
B-
3
3
C
* In approximate order o£ volume
1-7
-------
Table 1-3
PRODUCT MIX PROFITABILITY BY PLANT
(continued)
Plant
Products*
Profitabilitv
KAISER
Fontana
MC LOUTH
Trenton
NATIONAL
Granite City
Ecorse
Weirton
Portage
REPUBLIC
Buffalo
Canton
Cleveland
Gadsen
S. Chicago
Warren
SHARON
Farrell
U.S. STEEL
Bay town
Braddock
Duquesne
Fairfield
Fairless
Gary
Geneva
Homestead
Lorain
S. Chicago
HRS, plate, weld pipe, TMP,
galvanized B
HRS, CRS B-
HRS, CRS, galvanized C+
HRS, CRS 3-
HRS, CRS, galvanized C+
CRS, TMP, galvanized C
Bar B
Bar B
HRS, CRS, galvanized, bar B-
HRS, CRS, galvanized, plate 3-
Bar/rod, seamless tube, wire A-
HRS, CRS, galvanized, bar,
weld pipe 3
HRS, CRS, galvanized 3-
Plate, weld pipe B+
HRS, TMP, CRS 3-
Bar 3
HRS, CRS, TMP, galvanized,
structural, rail, bar B
HRS, CRS, TMP, galvanized,
bar/rod, weld pipe, wire 3
HRS, CRS, TMP, galvanized, bar, plate
rail, seamless tube, weld pipe 3
HRS, plate, structural, weld pipe 3+
Plate, structural 3+
Bar/rod, CRS, seamless tube, wire B+
Plate, structural, rod, rail 3+
* In approximate order of volume.
1-8
-------
Table 1-3
PRODUCT MIX PROFITABILITY BY PLANT
(continued)
Plant
Products'
Profitability
WHEELING-
PITTSBURGH
Monessen
Steubenville
WISCONSIN/
ENVIRODYNE
S. Chicago
Rail
HRS, CRS, TMP, galvanized
Bar
A
B-
* in approximate order of volume,
1-9
-------
Table 1-4
INDICATORS OF PLANT COMPETITIVENESS
Plant
Arm co
Ashland, KY 2.2
Butler, PA 1.0
Houston, TX 1.5
Kansas City, MO 1.6
Middletown, OH 3.5
Bethlehem
Bethlehem, PA 3.4
Burns Harbor, IN 5.3
Johnstown, PA 1.2
Lackawanna, NY 2.0
Sparrows Point, MD 7.0
Steelton, PA 1.4
CF&l
Pueblo, CO 1.9
Inland
East Chicago, IL 9.0
Interlake
0
0
0
0
35
0
0
0
0
50
0
27
100
0
0
0
65
100
100
0
100
50
0
68
7L
EF
%
0
100
100
100
0
0
0
100
0
0
100
% of
Cap.
Cont.
Cast.
0
50
0
28
20
0
19
0
0
0
0
Ave.
Blast
Furn.
Size
1.0
N/A
.8
N/A
.67
.88
1.8
N/A
1.0
1.3
N/A
Coke
Cap.
0
0
.4
0
1.5
2.0
1.6
.4
1.4
2.6
0
32
26
18
.25
.72
3.2
2.0
0
.8
0
2.0
3.5
3.5
0
4.2
6.3
0
1.0
6.5
0
N/A
.50
N/A
.75
.57
.46
N/A
.33
.41
N/A
.80
50
Riverdale, IL
.9
100
.60
.5
1.2
,42
-------
Table 1-4
INDICATORS OF PLANT COMPETITIVENESS
(continued)
Hot Strip Mill
ant Cap.
Built
Cont .
Pick
Mod. ?
Comp.
Cont. Census
? Region
Trans .
Mode
Comp.
Rating
Armco
Ashland, KY 1.8
Butler, PA .9
Houston, TX N/A
Kansas City, MO N/A
Middletown, OH 2.4
Bethlehem
Bethlehem, PA N/A
Burns Harbor, IN 3.5
Johnstown, PA N/A
f.ackawanna, NY 2.4
Sparrows Point, MD 3.1
Steel ton, PA N/A
CF&I
Pueblo, CO N/A
Inland
East Chicago, It, 4.5
Interlake
1953
1957
1968
1966
1966
1935
1948
1964
1965
Y
N
N
N
N
Y
Y
Y
Y
Y
ESC
MA
WSC
WNC
ENC
River
Rail
Sea
River
Rail
B-
B +
B
B +
B-
N
Y
N
N
Y
N
Y
Y
Y
Y
Y
Y
MA
ENC
MA
MA
SA
MA
Rail
Lake
Rail
River
Sea
Rail
B+
A
Bl-
B-
B-
B-H
N
MTN
ENC
Rail
Lake
B
A-
Riverdale, IL.
.6
N
ENC
River
B-
-------
Table 1-4
Plant
Raw
Steel
Cap.
INDICATORS OF PLANT COMPETITIVENESS
(continued)
OH
BOF
EF
%
% of
Cap.
Cont.
Cast.
Ave .
Blast
Furn.
Size
Coke
Cap.
Blast
Furn.
Cap.
Coke
Cap./
Blast
Furn.
Cap.
I
\~>
ro
Jones &
Laughlin (LTV)
Aliquippa, PA
Cleveland, OU
Pittsburgh, PA
East Chicago, IL
Honncpin, IL
Kaiser
Fontana, CA
McLouth
Trenton, MI
National
Granite City, IL
Ecorse, MI
Weirton, WV
Portage, IN
Republic
Buffalo, NY
Canton, OH
Cleveland, OH
Gadsden, AL
South Chicago, IL
Warren, OH
3.5
3.1
1.8
5.5
0
0
0
0
45
N/A
100
81
0
55
N/A
0
19
100
0
N/A
13
0
0
0
N/A
.72
.90
N/A
.88
N/A
1.2
0
1.3
1.2
0
3.6
1.8
0
3.5
0
.33
0
N/A
.34
N/A
3.6
2.4
0
100
75
25
13
90
.68
,85
1.1
.6
2.7
1.7
.41
.35
2.5
6.2
4.0
0
0
0
0
N/A
100
80
100
N/A
0
20
0
N/A
40
22
34
0
.90
.93
.75
N/A
.7
1.6
1.4
0
1.8
3.7
3.0
0
.39
.43
.47
N/A
1.0
1.5
4.4
1.5
2.0
2. J
0
0
39
0
0
0
100
0
61
90
GO
LOO
0
100
0
10
40
0
0
53
23
0
0
I)
.40
N/A
.60
.40
1.3
1.30
.3
.2
1.5
1.8
.4
.6
.8
0
3.0
.8
1.3
1.3
.38
N/A
.50
1.00
.31
.46
-------
Table 1-4
INDICATORS OF PLANT COMPETITIVENESS
(continued)
i
i-j
u>
Hot Strip Mill
Plant
Jones &
Laughlin (LTV)
Aliquippa, PA
Cleveland, OH
Pittsburgh, PA
East Chicago, IL
Hennepin, IL
Kaiser
Fontana, CA
McLouth
Trenton, MI
National
Granite City, IL
Ecorsc, MI
Weir ton, WV
Portage, IN
Kepublic
Buffalo, NY
Canton, OM
Cleveland, OH
Gadsden, AL
South Chicago, TL
Warren, OH
Cap.
1.6
3.4
N/A
5.0
N/A
1.8
2.4
2.4
4.4
3.1
N/A
N/A
N/A
3.0
1.3
N/A
1.7
Built Mod.
1957
1964
1968
1950 1957
1954
1967
1961
1927 1955
1957 1967
1961
Cont.
Pick
p
N
Y
N
Y
Y
Y
Y
N
Y
Y
Y
N
N
Y
Y
N
Y
Comp.
Cont.
?
Y
Y
N
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N
Y
Census
Region
MA
ENC
MA
ENC
ENC
PAC
ENC
ENC
ENC
SA
ENC
MA
ENC
ENC
ESC
ENC
ENC
Trans
Mode
Comp.
Rating
Rail
Lake
River
Lake
Rail
Rail
Lake
Rivet-
Lake
River
Rail
Lake
Rail
Lake
Rail
Lake
Rail
B +
B
A-
B-
B
B
B
B +
B +
B-
B
B-
B +
B-
B-
B
B +
-------
Table 1-4
INDICATORS OF PLANT COMPETITIVENESS
(continued)
Plant
Sharon
Farrell, PA
U.S. Steel
Raw
Steel
Cap^
1.6
Baytown, TX
Brarldock, PA
Duquesne, PA
Fairfield, AL
Fairless Hills, PA
Gary, IN
Geneva, UT
Homestead, PA
Lorain, Oil
South Chicago, IL
Wheeling-Pittsburgh
Monessen, PA
Steubenville, OH
OH
BOF EF
% %
% of
Cap.
Cont.
Cast.
Ave .
Blast
Furn.
Size
Coke
Cap.
Blast
Furn .
Cap.
Coke
Cap./
Blast
Furn .
Cap.
1.6
2.8
Wi scons in/En virodyne
South Chicago, IL. 1.2
0
0
63
37
.50
100
100
100
0
0
0
0
23
.50
.48
.27
.5
1.3
.3
1.0
1.5
2.4
.8
N/A
2.0
2.5
3.0
3.5
4.1
8.0
2.8
4.0
3.0
5.2
0
0
0
0
82
0
100
100
0
0
0
100
83
100
0
100
0
0
100
78
100
0
17
0
18
0
0
0
0
22
0
0
0
0
7
25
0
0
0
21
N/A
.63
.75
.45
.97
.59
.67
.58
.54
.82
0
1.9
1.2
1.8
1.0
3.6
1.3
1.5
1.5
0
0
2.5
1.5
2.7
2.9
6.5
2.0
2.0
2.7
4.1
N/A
.77
.77
.67
.34
. 55
.65
.77
.56
0
.33
.54
.38
-------
Table 1-4
INDICATORS OF PLANT COMPETITIVENESS
(continued)
Plant
Hot Strip Mill
Cap.
Built
Cont. Comp.
Pick Cont. Census
Mod.
? ? Region
Trans.
Mode
Comp .
Rating
I
M
l/l
Sharon
Farrell, PA
U.S. Steel
.5
Baytown, TX N/A
Braddock, PA 2.6
Duquesne, PA N/A
Fairfield, AL 1.6
Kairless Mills, PA 3.1
Gary, IN 5.0
Geneva, UT N/A
Homestead, PA N/A
Lorain, OH N/A
South Chicago, IL N/A
Wheel ing-Pittsburgh
Moner.sun, PA N/A
Steubenville, OH 2.6
Wisconsin/Envirodyne
South Chicago, IL N/A
1931
1938
1937
1953
1967
1962
1968
1926
1957
Y
Y
N
N
N
Y
MA
MA
ENC
ENC
Rail
River
River
Lake
B-
N
Y
N
Y
Y
Y
N
N
N
N
N
Y
N
Y
Y
Y
N
Y
Y
Y
WSC
MA
MA
ESC
MA
ENC
MTN
MA
ENC
ENC
Rail
River
River
Rail
River
Lake
Rail
River
Rail
Lake
B+
B-
B
B +
B-
B
B-
B-
B
B+
B-
B-
-------
ma^or steel-producing corporations for the years 1977,
1978 and 1979. The only significant tonnage producer
omitted was Ford, which does not report any separate
information on its steel operations. Each of the five
ratios mentioned above was calculated for each firm for
each year. Based on the relative magnitude of each ratio
for each year, each company was assigned a categorical
rating, A, B or C. Each company's rating for each ratio
was then combined into an overall rating reflecting a
qualitative "average" of the ratings assigned to each
individual ratio. Tables 2-5 through 2-9 summarize the
five financial ratios and the categorical ratings for each
firm. Table 2-10 summarizes the overall categorical
rating of each firm's financial strength.
1-16
-------
Table 1-5
FINANCIAL STRENGTH: GROSS MARGIN (%}
Armco
Bethlehem
CF&I
Envirodyne
Inland
Interlace
Kaiser
LTV
McLouth
National
Republic
Sharon
U.S. Steel
Whig.-Pitt.
MEASURE VALUE AND RATING
.1977
11.
9.
9
4
(B
)
(C)
N/A
13.
14.
21.
8.
6.
4.
7.
14.
12.
13.
6.
7
6
1
7
4
0
7
7
4
3
4
(B
)
(A)
(A)
(C
)
(C)
(C
(C
(A
(B
(3
(C
)
)
)
)
)
)
1978
15.
15.
15.
5.
17.
19.
8.
7.
9.
13.
16.
17.
13.
10.
6
5
2
8
5
2
2
1
5
4
7
5
9
2
(A
(A
)
)
(A)
(C)
(A
(A
(C
)
)
)
(C)
(C
(3
(A
(A
(3
(B
)
)
)
)
)
)
1979
15
14
15
(3
14
19
7
9
9
11
15
14
13
12
.0
.9
. 5
.1)
.6
.5
.9
.6
.8
.8
.0
.6
.2
.1
(A)
(A)
(A)
(C)
(A)
(A)
(C)
(C)
(C)
(B)
(A)
(A)
(B)
(B)
OVERALL
RATING
A-
B +
A
0
A
A
C
C
C
B-
A
A-
B
B-
A
B
C
> 14
10 - 14
< 10
1-17
-------
Table 1-6
FINANCIAL STRENGTH: ROE (1)
MEASURE VALUE AND
1977 ^9_78_
Armco
Bethlehem
CF&I
Envirodyns
Inland
Interlace
Kaiser
LTV
McLouth
National
Republic
Sharon
U.S. Steel
Whig. -Pitt.
8.
(16.
3
5)
(A)
(C)
N/A
(29.
7.
6.
1.
(17.
(8.
4.
3.
10.
2.
(7.
7)
8
1
0
9)
9)
7
1
1
7
5)
(C)
(B)
(B)
(C)
(C)
(C)
(B)
(C)
(A)
(C)
(C)
12
9
5
.6
.5
.8
(A)
(A)
(B)
N/A
12
3
2
7
6
9
7
16
4
5
.6
.4
.7
.6
.0
.4
.9
.4
.6
.4
(A)
(C)
(C)
(B)
(B)
(A)
(B)
(A)
(C)
(B)
RATING
1979
12.
10.
7.
9
7
2
(A)
(B)
(B)
N/A
10.
11.
9.
24.
5.
8.
8.1
22.
(6.
12.
0
9
3
9
0
9
8
0)
5
(B)
(A)
(B)
(A)
(C)
(B)
(B)
(A)
(C)
(A)
OVERALL
RATING
A
B
B
C
B+
B
O
B
C+
B +
B-
A
C
B
Inflation
6.0
7.3
8.9
B = Within two points of inflation
1-18
-------
Table 1-7
FINANCIAL STRENGTH: DEBT TO CAPITALIZATION (%}
Armco
Bethlehem
CF&I
Envirodyne
Inland
Interlace
Kaiser
LTV
McLouth
National
Republic
Sharon
U.S. Steel
Whig.-Pitt.
MEASURE VALUE AND RATING
1977
31 (A)
30 (A)
N/A
89 (C)
35 (A)
22 (A)
35 (A)
79 (C)
44 (3)
36 (3)
25 (A)
17 (A)
31 (A)
38 (B)
1978
28
30
29
124
34
31
42
76
42
34
24
17
29
35
(A)
(A)
(A)
(C)
(A)
(A)
(B)
(C)
(B)
(A)
(A)
(A)
(A)
(A)
1979
25
28
28
187
33
29
39
69
40
32
22
66
32
30
(A)
(A)
(A)
(C)
(A)
(A)
(B)
(C)
(B)
(A)
(A)
(C)
(A)
(A)
OVERALL
RATING
A
A
A
C
A
A
B +
C
B
A-
A
C
A
A-
A
B
< 35
35-50
> 50
1-19
-------
Table 1-8
FINANCIAL STRENGTH: BEAVER RATIO
Arraco
Bethlehem
CF&I
Envirodyne
Inland
Interlace
Kaiser
LTV
McLouth
National
Republic
Sharon
U.S. Steel
Whig.-Pitt.
MEASURE VALUE AND RATING
1977
.15
.03
N/A
0
.22
.17
.07
.02
.01
.18
.20
.20
.14
.03
(3)
(C)
(C)
(A)
(3)
(C)
(C)
(C)
(B)
(B)
(B)
(C)
(C)
1978
.36
.30
.38
(.07)
.28
.17
.05
.04
.13
.20
.29
.32
.15
.14
(A)
(A)
(A)
(C)
(A)
(3)
(C)
(C)
(C)
(B)
(A)
(A)
(B)
(C)
1979
.33
.33
.43
(.14)
.24
.19
.17
.11
.14
.20
.24
.09
.14
.22
(A)
(A)
(A)
(C)
(A)
(B)
(B)
(C)
(C)
(B)
(A)
(C)
(C)
(A)
OVERALL
RATING
A-
B +
A
C
A
B
C+
C
C
B
A-
B-
C+
B-
A
B
C
> .20
.15-.20
< .15
1-20
-------
Table 1-9
FINANCIAL STRENGTH: DAYS' CASH
MEASURE VALUE AND RATING
1977 1978 1979
OVERALL
RATING
Armco
Bethlehem
CF&I
Envirodyne
Inland
Interlace
Kaiser
LTV
McLouth
National
Republic
Sharon
U.S. Steel
Whig.-Pitt.
4
16
21
20
8
7
31
4
5
(C)
(A)
(A)
(A)
(B)
(B)
(A)
(C)
(C)
N/A
7
15
12
14
C
B
A
(B)
(A)
(A)
(A)
< 5
5 -
> 10
13
18
13
2
15
9
20
8
8
26
11
5
13
16
10
(A)
(A)
(A)
(C)
(A)
(B)
(A)
(B)
(B)
(A)
(A)
(C)
(A)
(A)
5
16
16
2
3
4
46
4
4
11
8
79
11
23
(C)
(A)
(A)
(C)
(C)
(C)
(A)
(C)
(C)
(A)
(B)
(A)
(A)
(A)
B-
A
A
B-
B
B-
A
C +
C +
A
B +
B+
A
A
1-21
-------
Table 1-10
FINANCIAL STRENGTH SUMMARY
Arirco
Bethlehem
CF&I
Envirodyne
Inland
Interlake
Kaiser
LTV
McLouth
National
Republic
Sharon
U.S. Steel
Whig. -Pitt.
ROE
A
B
B
f\
v_
B+
B
C +
B
C+
B +
B-
A
C
B
Gross
Margin
A-
B +
A
C+
A
A
C
C
C
B-
A
A-
B
B-
Debt/
Cap.
A
A
A
C
A
A
B+
C
B
A-
A
C
A
A-
Days '
Cash
B-
A
A
B-
B
B-
A
C+
C+
A
B+
B+
A
A
Beaver
Ratio
A-
B+
A
C
A
B
C+
C
C
B
A-
B-
C-i-
3-
Overall
A-
B +
A-
C
A-
B-i-
C +
C
C
34-
B +
B
3-
B
1-22
-------
PLANT MODEL CONFIGURATIONS APPENDIX 2
-------
BETHLEHEM STEEL
LACKAWANNA
Final Oana.ic
Total -inal Senand:
2 0 .VC*T fnisned products.
2-2
-------
JONES & LAUGHLIN
CLEVELAND
Coke \
f MA
Ore
2.747/NA
J
\
Final Denar.d
.9
-:3S ? 5 O Fi.ial. Demand
C?S ?inal Demand
1.0
?ocal Final Daaand 2 2 MNT finsr.ed products.
(a) Process ronstrainei -a ocarace at at leas: .3 MNT level,
a binding constrai-c.
2-3
-------
JONES & LAUGHLIN
INDIANA HARBOR
Total Final Samara: 2.0 MMT iir.isred products
Sote: Seaaless oipe mill (capacity: .31 MNT) omiteed
from this aodel. Mill uses billets provided by
another plane.
2-4
-------
KAISER STEEL
FONTANA
s
Coke
•97/1.50
Sinter
U19/l.4l
M
•IBS ? S 0 Final 3emand
.1
7S "inal Demand
. 5
3ALV Final
Demand
.2
,TMP Final Canand
Tocai Tir.al Oenand 1.8 -o:T fi.iisnad ?r=duc-s.
* Process operating at capacity.
2-5
-------
McLOUTH STEEL
TRENTON
R£ Final Demand
.3
P * 0 Fnai Demar.c
1.0
Total Final Oemarra. 1.3 »IT iinisr.ed products.
(a) Constrained :o produce -at least .3MNT, a oinding constraint
2-6
-------
NATIONAL
WEIRTON
Coke
1.67/2>96
L
Sinter
2.57/2 99
L
Total Tnal Oenand- 2.6 "NT fnished ?r
-------
REPUBLIC STEEL
• GADSDEN
Coke
•42/.37
V
SLncer
•47'.55
s
'LATE Fnal Demand
Total final Oa.nand- ,7 MNT finished produces.
2-8
-------
^
?ur.
^
SHARON
FARRELL
3F
•90/1.02
S
30?
l- 14/1.28
S
T
.i23/
M
.423
?!.nai Detia-.d
PS ? 5 0 ?inai Demand
2
?S ?i.ial Seitand
IALV. r--.--al Oen-and
Total "nal Denana: -1.1 MNT finisned products.
Process Dperacng ac capacity.
2-9
-------
U.S. STEEL
FAIRLESS
Demand
.2
Tonal Fir.al Demand. 2.9 XST ::.-iis.-.ed produces.
Procass operating at capacity.
(a) Modelled as a small HSM.
(b) xiodelled as a bar
2-10
-------
U.S. STEEL
GENEVA
STRUCT.<
Final
Demand
4
3 loom Mill
•43/.87
M
Structural
riSS Final Demand, S
?late "all*
, « •
.40/NA
Demand
?ioe ".ill
•[0/ 13
S
Oaaand
To;al Final demand: 1.7 >CIT Ji.i-sr.ed products.
loz strip -.ill -nodelied -is a combination of J.OL Strip Mill
ana Place Mill.
2-11
-------
U.S. STEEL
HOMESTEAD
=L.VT£ ? S 0 fi.-al Zetland
Total T.nal Oenanci: :.1S JSiT f.nisnad products.
* Includes excess blase furnace caaacicy available
ac Edgar Thomson Horks, Sraddock, ?A.
**Hypotnetlcal facility.
2-12
-------
WHEELING-PITTSBURGH
STEUBENVILLE
Coke (?)
l'2l'l.64
M
1
Sinter (F)
0.47/
S
0.55
Scrap
1.00/NA
M
|
3F (S)
)
3F (M) *
1.53/
M
1.53
2.89/
3.12
Final 2enand
1.0
? S O "i.nal Oeiiand
5
iCSS fi.-.ai Oenand
.3
-V Final Deaa-vJ
.05
7ocal Final Deoiarc- 2.05 :-»T f-.iished products.
F- Follansoae
Process operating at capacity
1" Mingo J'-nc.ion
5= Stsuaenville
2-13
-------
SUMMARY OF MAJOR ASSUMPTIONS APPENDIX 3
Standard economic theory suggests that a plant or
individual production process within a plant is most
likely to be closed if the present value of expected
future cash flows attributable to the continued operation
of the plant or process does not exceed the amount of
fixed cash costs that can be avoided by closure less the
present value of postponing closure costs. Pollution
control regulations increase the expected fixed and
variable costs of operating a given plant or process by
imposing the additional costs of operations, maintenance
and capital recovery associated with the required
pollution control equipment. To the extent that these
increased costs for a given plant or process are
sufficient to change management's expectations regarding
the likelihood that future contributions will exceed
avoidable fixed costs, the pollution control requirements
may contribute to a decision to close the plant or
process.
Applying the general economic theory of plant or
process closures to the task of predicting actual industry
behavior in the face of a new environmental regulation is
complicated by two basic problems: 1) lack of access to
the same information available to industry decision
makers, and 2) differing expectations regarding the
future. This studv has, of necessity, utilized a number
of assumptions in order to cope with these inherent
problems. The purpose of this appendix is to list these
assumptions, explain why each was made, and provide a
-------
justification for the conclusions that have been drawn
from the analysis in terms of these assumptions.
1. AVERAGE OPERATING CHARACTERISTICS
FOR EACH PROCESS
Due to the unavailability of confidential, plant-
specific production cost data, PHB formulated the 12
individual steel plant models using the input factor usage
rates and material balance yields contained in the
ADL/AISI industry summary database made available to the
Agency by the AISI. The ADL/AISI industry summary
database reflects the average operating characteristics of
each process across all plants in the original database.
Therefore, use of the ADL/AISI database entails the
implicit assumption that each process at each plant has
industry-average operating characteristics. This assump-
tion is justified on the grounds that the ADL/AISI
industry summary database constitutes the best available
information. Furthermore, basing a closure impact study
on plant models reflecting industry-average operating
characteristics for each process tends to distinguish
plants which are marginal because of operating
inefficiencies relative to the rest of the ir.duscry from
those that are marginal due to the impact of the
regulation.
2. EACH PLANT PAYS AVERAGE PRICES
FOR FACTOR INPUTS
Due to the unavailability of plant-specific input
factor cost data, PHB estimated production costs for each
of the 12 plants modeled using the average input factor
coses contained in the Agency's industrywide study. These
costs tend to reflect national averages, or else regional
averages corresponding to the principal steelmaking areas
of Chicago, Cleveland and Pittsburgh. In the case of
labor, the figure contained in the current nationwide
United Steelworkers of America contract was used. In the
case of raw materials, power and fuel, various regional
averages were used on the grounds that these constitute
the least speculative figures available. In addition,
basing a closure impact study on trie assumption that each
plant pays average prices for factor inputs tends to
distinguish plants which are marginal because they cannot
3-2
-------
obtain their inputs at prices similar to those paid by
their principal competitors from those that are marginal
due to the impacts of the regulation.
Determining the exact prices being paid at a
particular plant for raw material inputs, such as ore,
coal and purchased coke, is complicated by the fact that
most steelmakers either purchase these materials under
long-term contracts, or control their own sources of these
materials through full or partial ownership in iron mines,
coal mines, coke batteries located at affiliated plants
and even the railroads used to transport these materials.
This integration results in transfer prices which are
based on accounting practices rather than market value.
Furthermore, maximum efficiency in cokemaking and
ironmaking often requires blending of raw materials from
several different sources. The phenomena of long-term
contracts, captive control and blending make any outside
attempt to ascertain potential differences in raw
materials costs between individual plants extremely
speculative.
In the case of purchased scrap and electric power,
somewhat more definitive statements cars be made regarding
the likely source of the input and its probable cost. The
cost of both of these inputs varies substantially bv
region. In the case of scrap, the price used reflects the
average reported price for •? 1 heavy melting steel scrap
for Pittsburgh, Chicago and Philadelphia. Although Kaiser
Steel's Fontana plant is located in southern California
and Republic Steel's Gadsden plant is located in Alabama,
neither of these plants operates a scrap-intensive
electric furnace shop. Thus any error introduced by the
use of the average scrap price from other regions is
likely to be very small.
A similar argument holds in the case of electricity.
Electricity prices were calculated as total utility
revenues divided by total utility energy sales to
commercial and industrial large power users in the East
North Central region of the country. Although the Fontana
and Gadsden plants are located outside of this region,
neither plant ooerates a power-intensive electric furnace
shop. Thus any error introduced by use of an electricity
price derived from other regions is likely to be small.
3-3
-------
3. PLANT-SPECIFIC PRODUCT MIX AMD
GRADE MIX ASSUMPTIONS
Plant-specific information regarding finished product
mix and grade mix (carbon, alloy or stainless steels) is
generally considered by steel companies to be extremely
confidential information. The most recent plant-specific
production data available for purposes of this study is
that contained in the company's original responses to 308a
questionnaires which cover the years 1974 through the
first half of 1976. Given the shifts in the pattern of
product demand since 1976, particularly for such products
as seamless and welded pipe, which are now in considerable
demand, as opposed to automotive flat rolled sheet, which
is currently in a very depressed market, it was necessary
to make some adjustments to the likely product mix
produced at each plant in order to reflect more accurately
the probable expectations of management. With regard to
grade mix, the ADL/AISI industry summary database was
compiled based on the industry-average production grade
mix"" in 1976, which has not changed substantially in recent
years. Thus it was assumed that each plant modeled
produces approximately the industry-average grace mix, an
assumption which was true as of 1976, but may have changed
in the intervening years. The smaller capacity plants,
such as Sharon, have the potential to increase their
presence in the markets for stainless and alloy specialty
steels. In the absence of specific data to the contrary,
PHB has assumed an industry-average grade mix and the
demand-adjusted product mix shown in Table D-i.
4. AIR POLLUTION CONTROL COSTS
In the absence of plant-specific information
regarding the operating costs of air pollution control
equipment (both that already in place and that expected to
be installed), PHB assumed that these costs could be
derived from the estimating equations contained in the
July 1979 PEDCo Environmental, Inc. study for the EPA
entitled Development of Air Pollution Control Cost
Functions for the Integrated Iron and Steel Industry. The
estimates were derived using the equation for the level of
control, RACT, BACT, or LAER, specified by PEDCo as
corresponding with the requirement contained in the
typical State Implementation Plan (SIP) for each process
with significant emissions, both fugitive and stack. The
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cost estimates derived from the PEDCo equations are based
on the capacities of the various processes in each plant
configuration and have been inflated from mid-1977 to 1980
dollars using a factor of 1.25.
The preceding assumptions are sufficient to calculate
production costs for each of the plant configurations of
interest, assuming industry average operating
characteristics and national average factor input prices.
However, there is some uncertainty associated with these
estimates, due mainly to the age of the ADL/AISI database.
Yields, material usages, and labor productivity may have
changed since the data were collected.
In addition to these cost uncertainties, two other
factors which are difficult to estimate are important to a
closure analysis. The first of these is contingent
liabilities associated with closure.
Although closure of a plant results in the avoidance
of costs associated with continued production there
usually are additional costs incurred to accomplish the
closure. Contingent liability costs associated with plant
closure in the iron and steel industry typically include
severance pay, the cost of funding pension and disability
insurance liabilities and the cost of settling outstanding
rav material supply contracts. These costs may or may not
be exceeded bv the salvage or market value of the plant's
assets. In the case of U.S. Steel in 1979 and Bethlehem
Steel in 1977, these closure costs far exceeded the
salvage value. If the present value of the contingent
liabilities associated with closure exceed the realizable
present value of the closed plant assets, closure costs
will represent a loss to the firm and each year's decision
to operate the plant will have the benefit of postponing
the realization of these closure costs. In general, a.
decision to operate the plant will be justified provided
that the loss from operations does not exceed the present
value of the benefit achieved by postponing closure costs.
The magnitude of the present value benefit associated with
postponing closure depends on the magnitude of the
contingent liabilities net of salvage value and the
discount rate attributable to company funds.
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The relative magnitudes of the contingent
liabilities, plant salvage values and the discount rate
attributable to company funds vary greatly according to a
number of plant and company specific factors. As a
result, the value of postponing closure is very difficult
to estimate without access to company confidential data.
The second factor is the amount of ongoing investment
necessary to maintain plant or process efficiency and
hence profitability. These scheduled cash outflows are
properly taken into account in a closure analysis.
However, the schedule and magnitude of such maintaining
investment varies widely by plant and by process and
cannot be reliably estimated without access to company
confidential data.
A classical closure analysis would have been
difficult without access to company-specific confidential
data. In view of this fact, an analysis of the per
shipment ton cost impacts of the regulation was
undertaken. The results of this analysis indicate that
the per ton costs of the regulation are very small
relative to the total variable costs of steel production.
Independent of che uncertainty in production costs,
deferred closure benefits, and prospective .maintaining
investment, it is extremely unlikely that the added cost
due to the regulation, averaging only $0.82 per shipment
ton, would by itself result in a closure decision. The
results of this cost-based analysis are sufficient to
support the conclusion that no closure decisions would be
likely to result." Thus it was not necessary to obtain
these plant-specific, confidential data, or to complete a
classical closure analysis.
This is not to say that no closures will occur at
these plants, but rather that the regulation is very
unlikely to be the cause of any such closure.
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