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A COST-BENEFIT ANALYSIS OF THE DEEP-DRAFT DREDGINGOF COAL PORTS ON THE EAST AND GULF COASTS OF THE
UNITED STATES
by
Stephen C. Graves*Mel Horwitch*
Edward H. Bowman**
October 20, 1983 1496-83
*The Sloan School of Management, Massachusetts Institute of Technology**The Wharton School, University of Pennsylvania
A COST-BENEFIT ANALYSIS OF THE DEEP-DRAFT DREDGING OF COAL PORTS
ON THE EAST AND GULF COASTS OF THE UNITED STATES
by
Stephen C. Graves, The Sloan School, MIT
Mel Horwitch, The Sloan School, MIT
Edward I. Bowman, The Wharton School, University of Pennsylvania
October 20, 1983
PLEASE DO NOT REPRODUCE WITHOUT PERMISSION OF THE AUTHORS
Executive Summary
This study deals with the question of whether U.S. society as a whole
should invest in large-scale coal port development. The analysis takes a
total system perspective with regard to costs and benefits. The analysis
does not try to attribute the costs or benefits of dredging to the various
parties involved in the coal trade. Rather, the analysis assumes that
society, as a whole, will both pay the costs and receive the benefits from
dredging.
The study focuses specifically on the question of whether U.S. society
should finance the deep-draft dredging of coal ports on the East and/or Gulf
Coasts so that newly dredged ports can accommodate fully loaded, large (over
100,000 deadweight tons) coal-carrying colliers in order to export coal to
Western Europe.
Although keeping in mind the great complexity of the coal-port issue,
involving economic, logistical, and political factors as well as others, the
core of this analysis is based on a large number of different simulations
--in effect, scenarios-- using a mathematical programming model to perform
the various analyses. For each simulation the model "optimizes" the United
States-to-Western Europe coal trade for a given demand level and ocean
transportation cost structure. Considering only the ocean transportation
costs and port dredging costs, the model finds the least-cost solution for
satisfying export demand. Although the analysis is based on a relatively
simple model, we argue that the strength of the model is that it clearly
focuses upon the key tradeoff in the coal-port issue, namely the cost of
dredging versus the potential reduction in ocean transportation costs.
The major set of simulations included the ports of Baltimore, Hampton
Roads, Mobile, and New Orleans. In addition, a special set of runs also
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included the Port of New York. For our various demand scenarios we
aggregated the demand centers into two major and representative clusters:
Northwest Europe (Rotterdam) and Mediterranean Europe (Taranto, Italy).
The most striking aspect of our conclusions is the robustness of two
solutions: no dredging (the status quo) or dredge only Hampton Roads to 55
feet. If one is somewhat conservative regarding demand projections and
requires a relatively high hurdle rate for a societal return-on-investment,
then a no-dredging option makes a great deal of sense for American society
as a whole. But if one believes that coal demand will ultimately increase
at a medium or high rate or that we can accept a relatively lower societal
return-on-investment, then dredging only Hampton Roads is the clear choice
for a wide range of alternatives. Moreover, if one assumes that the long-
term growth of U.S. coal exports will continue, then dredging Hampton Roads
may also make sense as an "insurance policy," since this solution is also
economically sound under a wide number of conditions. The United States has
no deep-water coal port at present. Even when we include the option of
dredging the Port of New York in our analysis, the solution of dredging
solely Hampton Roads to 55 feet emerges as optimal under a number of likely
conditions.
The study lends support to those recommending caution in approaching
coal-port development. There was no justification for dredging all deep-
draft options simultaneously. In fact, what is very clear is that the con-
current dredging of more than one port is unwise unless one supports the
most optimistic projections for coal-export demand or relatively low real
interest rates over the long run. Moreover, under no condition that we
examined does it make sense to dredge either of the Gulf ports --Mobile or
New Orleans-- before dredging Hampton Roads or Baltimore.
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Acknowledgements
In the course of doing the initial field research and later data
collection, model building, and simulations for this report we were extremely
fortunate to have the cooperation and/or support of many organizations. We
must particularly thank several helpful officials, analysts, or managers in
the Illinois Central Gulf Railroad, the Norfolk and Western Railroad, A. T.
Massey Company, Ryan-Walsh Stevedoring Company, the Port of New Orleans
Authority, the U.S. Corps of Engineers in Washington and its District Offices
for Baltimore, Mobile, New Orleans, and Norfolk-Hampton Roads, the City of New
York, the New York Port Authority, Shell Coal International, R. S. Platou, IEA
Coal Research, the International Bulk Journal, and the Center for Energy
Policy Research at MIT. Of course, we take full and sole responsiblity for
our analysis and its conclusions.
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TABLE OF CONTENTS
Page
Executive Summary
Acknowledgements
Table of Contents
List of Tables
Section I. Introduction
Section II. The Model
A. Orientation of the Analysis
B. A General Discussion of the Model
C. Formulation of the Model
Section III. Data Used in the Analysis: Sources, Assumptions,and Discussion
A. Demand
B. Port Data: Cost of Capital, Capacity,and Dredging Costs
C. Ocean Transportation Cost Savings
Section IV. Model Runs with Hampton Roads, Baltimore, Mobile,and New Orleans
A. Overview of Model Runs
B. An Illustration
Section V. Model Runs that Include the Port of New York
Section VI. Conclusion
Tables
References
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i
iii
iv
V
1
7
7
8
13
17
17
18
20
25
25
25
29
31
36
77
LIST OF TABLES
Table
1. Trends in U.S. Coal Production and Exports
2. U.S. Bituminous Coal Exports, 1973-1981
3. U.S. Coal Exports: Comparison of EIA Projections With
Other Projections, 1985-2000
4. Survey of World Ports With Existing and Planned Operating
Channel Depths in Excess of 45 Feet
5. Cost Estimates: Deep-Draft Navigation Projects Over 45 Feet
6A. U.S. Metallurgical Coal Exports-Projections
6B. U.S. Metallurgical Coal Exports From Selected
U.S. Ports in 1981
7. Projected U.S. Steam Coal Exports From East Coast
and Gulf Ports: 1990
8. Projected U.S. Steam Coal Exports From East Coast
and Gulf Ports: 2000
9. U.S. Coal Export Demand Scenarios
10. Port Capacities
11. U.S. Coal Shipments
12. Dredging Depth Options and Costs
13. Ocean Transport Assumptions
14. General Relationships Between Port Draft and Ship Size
15. Assumptions Regarding the Relationships Between Port
Draft and Ship Size That Are Used in the Model
16. Assumptions for Transportation Costs of R.S. Platou
LIST OF TABLES(Continued)
Table
17. Ocean Transportation Cost:
"Low Cost Savings" Case
18. Ocean Transportation Cost:
Hampton Roads-Rotterdam Under
Hampton Roads-Rotterdam
Under "High Cost Savings" Case
19. Ocean Transportation Cost: Hampton Roads-Taranto,
Under "Low Cost Savings" Case
20. Ocean Transportation Cost: Hampton Roads-Taranto,
Under "High Cost Savings" Case
21. Ocean Transportation Cost: New Orleans-Rotterdam
"Low Cost Savings" Case
22. Ocean Transportation Cost: New Orleans-Rotterdam
Under "High Cost Savings" Case
23. Ocean Transportation Cost: New Orleans-Taranto, I
Under "Low Cost Savings" Case
24. Ocean Transportation Cost: New Orleans-Taranto, I
Under "High Cost Savings" Case
25. Ocean Transportation Costs
Italy
Italy
Under
taly
taly
26. Results of Model Runs
27. A Summary of Dredging Solutions in Tables 26A - 26G
28. Model Runs That Include the Port of New York
29. Dredging Solutions Under Various Transportation
Cost Savings for the Port of New York Over Hampton Roads
30. Cost Breakdown for Four Dredging Cases
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Section I
Introduction
The spectacular rise of the world's seaborne coal trade in the late
1970's and early 1980's is one of the most dramatic recent trends in the
whole field of energy. Signalling a new public awareness of this
development, the World Coal Study in mid-1980 called attention to the
emergence of a growing coal export market --describing coal as a "bridge to
the future"-- and predicted that world coal production would have to
increase 2.5 to 3 times between 1977 and 2000 to meet world energy
requirements. This overall growth, according to that report, would result
in a 15-fold rise in the world steam coal trade during that 23-year period.
(World Coal Study, 1980A and 1980B).
The prospect of the huge coal export market that the World Coal Study
identified has created a new set of challenges, opportunities, and threats
for the U.S. coal industry and for U.S. society as a whole. One major issue
that arose as a result of the surge in coal exports, and one that is still
with us today, is coal-port development. There are at least two related
major aspects of the coal-port expansion issue: (1) a possible lack of
capacity to meet near-term and long-term U.S. coal-export demand and (2) a
possible loss of world market share in the long-term. U.S. society now
faces the difficult and controversial tasks of evaluating the capability of
its present infrastructure for the export of coal and of determining the
societal cost-benefit of and strategy for investing in coal-port expansion.
This study focuses on an important part of the overall coal-port
societal-cost-benefit issue. The study deals with the specific question of
whether U.S. society, as a whole, should finance the deep-draft dredging of
coal ports on the East and/or Gulf Coasts so that newly-dredged ports can
accommodate fully-loaded, large* coal-carrying colliers for exporting U.S.
coal to Europe.** At present, no U.S. coal port can handle a fully-loaded,
large collier from berthside.
The coal-port issue is clearly a richly multifaceted one. The
complexity of the issue is due to several factors, including the apparent
suddenness of the growth of the world seaborne coal trade, the uncertainty
that now surrounds its future demand-growth pattern, the long-term nature of
important outcomes, and the wide array of nonmarket stakeholders who have
attempted, or may attempt in the future, to influence coal-port policy
making.
The abrupt surge in coal exports can be illustrated by a few
statistics. Worldwide, the total coal trade in 1960 was about 113.3 million
short-tons, in 1970 about 186.4 million short-tons, in 1979 about 252.4
million short-tons, and in 1980 about 282 million short-tons (ICE Report,
page 24; H. P. Drewry, page 11). In other words, between 1960 and 1970, the
world coal trade increased by practically two-thirds, and between 1970 and
1980 it grew again by over 50 percent. Indeed, from 1979 to 1980, the world
coal trade increased by about 11 percent. The cause of this spectacular
rise in the 1970's was the tremendous increase in the world steam coal
trade. In 1970, steam coal accounted for about 19 percent of the world
*"Large" is defined as over 100,000 DWT. DWT is a "deadweight ton" and isapproximately the volume of a metric ton; it is used to describe thecarrying capacity of colliers.
**In this study, we do not deal with the question of who should pay for thedeepening and maintenace of coal ports. Therefore, for example, we do notaddress the issue of devising an optimal user-fee policy. For a usefuldiscussion of that issue, see U.S. Department of Energy, May, 1983.
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seaborne coal trade; in 1980, this figure had grown to 38 percent (H. P.
Drewry, page 13).
A parallel pattern can be discerned for U.S. coal exports, as seen in
Table 1. Annual U.S. coal exports practically doubled between 1960 and
1970, and grew by over another 50 percent in the next 11 years. Although
the growth pattern is uneven, export coal's share of total U.S. production
has tended to increase: 8.7 percent in 1960, 11.8 percent in 1970, and 13
percent in 1982. As seen in Table 2, the proportion of metallurgical coal
has declined during the 1970's and early 1980's, as steam coa's share of
U.S. coal exports has risen. Note especially the dramatic increase from
1979 to 1980 of steam coal exports and its share of total experts, and an
even more spectacular increase from 1980 to 1981, when steam coal captured
about 40 percent of total U.S. coal exports.
This growth of both the world coal trade and of U.S. coal exports,
especially steam coal exports, in the long term is expected to continue.
One typical projection has the total world seaborne coal trade growing from
205.7 million short-tons in 1980, of which 78.1 million short-tons or 38.0
percent is steam coal, to 469.7 million short-tons in 1990, of which 282.7
or 60.2 percent is steam coal (H. P. Drewry, page 20). Similarly, dramatic
growth rates for U.S. coal exports have been projected, as seen in Table 3.
Forecasts for 1990 range from 99 million short-tons to 152 million short-
tons. (U.S. coal exports in 1982 were about 105 million short-tons and are
estimated at only 74 million short-tons for 1983.) (Evered, 1983; "For Coal
the Recovery is Heating Up Slowly," 1983.)
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The issue of U.S. coal-port capacity quickly emerged as a public
policy issue during 1979 and 1980, with the great rise of U.S. coal
exports. The rapid expansion of coal exports at that time appeared to
exceed the capacity of coal ports on the East Coast. Queues of ships, at
times as many as 90, waited to enter the ports, incurring demurrage charges
as highl as $15,000 per ship per day. However, by late 1981, more effective
scheduling procedures had essentially eliminated these lines. Still, due to
both this bottleneck experience and the growth projections of U.S.
coal-export demand, proposals emerged, and continue to emerge, for expanding
and dredging a number of U.S. coal ports.
The general argument usually put forth for dredging coal ports is that
in order for the United States to export coal to its full potential, it must
be able to accommodate large coal-carrying vessels and take advantage of the
resulting cost savings. As one study stated, "Whether the U.S. captures an
18 percent (at present) or a potential 38 percent share of this market will
depend upon how quickly it can develop its ports, thus demonstrating its
commitment to expand steam coal exports and enabling coal exporters to
negotiate long-term supply contracts with leading importing nations in
Western Europe and the Pacific Basin." (U.S. House, Port Development,
March, 1982, page 24.)
According to this report and others, large coal colliers are
accounting for a greater share of the coal seaborne trade due to the
economics of marine transportation. The transportation cost savings of
shipping coal in an 150,000 DWT ship instead of an 80,000 DWT vessel are
estimated by some to be as high as 40 percent, representing perhaps 6 to $8
per ton in the delivered cost of coal. Moreover, other coal-exporting
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nations are dredging ports or have deep-water ports, as do certain importing
countries. Table 4 provides a survey of deep-water ports. Table 5 provides
a listing of the proposed U.S. deep-draft navigation projects, estimated to
cost in total over 2 billion.
The coal-port question is also an intensely political and
controversial issue, with several ports competing for federal funds. A
major part of the debate is over the level and share of federal funding
(U.S. Department of Energy, May, 1983). Coal-port development seems to
involve public relations as much as economic analysis and has even become
intertwined with general issues related to economic recovery, international
trade, and national industrial policy. As one representative pro-dredging
argument states:
In light of these trends and conditions, the future of portdevelopment in the United States is at a crossroads. The U.S. has aunique opportunity to expand its steam coal exports with the potentialof emerging as the leading exporter of steam coal through the balanceof the century. Continued expansion of coal exports offers thepotential for an export-led domestic economic recovery, including theprospect of permanent equilibrium in our international trade balanceas early as 1995 through targeted trade pattern stabilization. Portdevelopment will generate thousands of new obs in the domesticeconomy and increase private income and governmental tax revenues atall levels. It will provide the needed impetus for revitalization ofour domestic transportation system by contributing to capitalinvestment in rail, port, and pipeline improvements.
However, in order to realize these national and regionaleconomic benefits, the U.S. must act expeditiously within the next 3to 5 years to develop deep-draft ports in response to work, coalmarket demand and international maritime operating requirements. Itmust do so in an era of Federal budgetary limits. The accomplishmentof this objective will require an unprecedented level of governmentaland private sector cooperation in port development. If the nationalsystem of deep-draft commercial ports is to meet the challenge ofincreased international trade and foreign waterborne commerce(particularly in dry-bulk commodities such as coal and grain), thenthe interrelated processes of deep-draft navigation improvement,project authorization and environmental assessment and regulatoryreview of new and existing deep-draft channels on both a port- andsystem-wide basis must be streamlined through meaningful proceduralreform. (U.S. House, Port Development, March, 1982, page 25.)
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In spite of the rhetoric, however, a careful assessment of the
coal-port issue from a societywide and total systems cost perspective still
remains to be done. Irrespective of who pays --government, users, or both--
U.S. society as a whole still should attempt to determine whether such an
investment or at what level such an investment makes sense. We aim to take
a societal cost-benefit perspective in beginning to provide at least partial
answers to these questions. We will try to use such a perspective in
focusing specifically on the coal-port dredging issue as it relates to the
East and Gulf Coasts.
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Section II
The Model
A. Orientation of the Analysis
To address the key issues of developing large deep-water coal
ports, which basically deals with the specific choice of dredging a
port or set of ports to some level of depth or not dredging at all, we
have used a mathematical programming model to perform a set of
analyses.
The examination takes a societal view and attempts to determine
which, if any, of the most likely dredging options can be economically
justified. The study is restricted to considering the export market
for coal from the East and/or Gulf Coasts to Western Europe. For this
export market, the model determines, under various demand and cost
scenarios, the most cost-effective solution, taking into account the
dredging options, for shipping coal to Europe from the East and/or
Gulf Coasts of United States.
The analysis takes a total system perspective with regard to
costs and benefits. Unlike several studies (e.g. U.S. Department of
Energy, May, 1983), the analysis does not try to attribute the costs
or benefits of dredging to the various parties involved in the coal
trade. Rather, the analysis assumes that society, as a whole, will
both pay the costs and receive the benefits from dredging.
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B. A General Discussion of the Model
To further describe the analysis, we need to introduce, at least
qualitatively, the model that underlies the analysis. A more formal
presentation of the model is given later.
The model addresses an optimization problem of the following
form:
Minimize "Total Annual Trans-Atlantic Shipping CostsPlus
Annualized Dredging and Maintenance Costs"
Subject to:
Satisfying a given Western European demand for U.S. coal - bothsteam and metallurgical.
Without exceeding given expected port throughput capacities atthe U.S. ports.
And ensuring that each U.S. port handles a given minimal amountof export coal.
The key inputs to the model are as follows:
(a) Per ton ocean shipping costs from each U.S. port to Europeandemand centers for each possible depth at the U.S. port.
(b) The dredging cost and annual maintenance cost for each dredgingoption at each port. The one-time dredging cost is annualizedby a capital cost rate that must also be an input.
(c) Expected annual demand for U.S. coal (steam and metallurgical)at each European demand center.
(d) Expected coal-handling capacity, measured in short-tons peryear, at each port that will be available for satisfyingEuropean demand.
(e) Expected minimum annual volume of export coal to Europe to behandled by each port.
The outputs from the model are:
(a) Specification for each port of the most cost-effective dredgingdecision (e.g., no dredging, dredge to 50 feet, or dredge to 55feet).
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(b) Specification of the most cost-effective flow of coal thatsatisfies the demand and capacity constraints of the model.That is, for each demand center the model specifies how muchwill be shipped to the demand center from each U.S. port.
While this model is reasonably straightforward, we are well
aware that there are more complex representations available. Yet,
after extensive discussions and consideration, we would contend that
such increasingly complex models are of little additional value in
considering the question of dredging. Moreover, our model has the
advantage of focusing on the most important aspects of coal port
development. In particular, with our model we can show under what
circumstances the transportation benefits from deeper ports ustify
the costs of dredging. This seems to us to be the key economic
tradeoff in the dredging controversy.
We offer the following observations with regard to the model,
its assumptions, and our use of the model:
(a) The model "optimizes" the U.S.-to-Europe coal trade for a given
demand and transportation cost structure. Consequently, the
analysis does not consist of one run of the model and one
solution. Rather, we use the model as an analytical tool for
looking at a wide range of possible scenarios. For instance, a
key input parameter that is varied is total European demand for
U.S. coal. We consider our various demand levels corresponding
to a series of forecasts that range from low-growth projections
for 1990 up to the most optimistic forecasts for 2000.
(b) The model itself is a static, single-period model that
"optimizes" over a one-year snapshot. Each model run, in
effect, represents one scenario. For instance, one run might
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represent the best forecasts for year 1995. Clearly, though,
the question of dredging is a dynamic, multi-year decision
problem. Indeed, some dredging proponents would say the
question is not whether to dredge, but when to dredge. We could
have formulated and developed a multi-period model rather than a
static, single-period model. However, we viewed such a task as
not being worth the substantial effort that would be required to
develop a dynamic model. Moreover, such an effort may even
unnecessarily complicate our main task. By running our static
model under a diverse array of possible scenarios we believe
that we accomplish, at least partially, a dynamic analysis and
sufficiently approximate such a more complex examination.
Indeed, as will be seen, the results of our various simulations
do suggest at what points in the near future and under what
circumstances various dredging options become economically
feasible. In fact, the likely set of options narrows
considerably and, as also will be seen, there actually seems to
be really only two "robust" solutions under a wide range of
conditions.
(c) With our model, we attempt to minimize the total cost of
dredging plus the total ocean transportation cost for moving
coal from the U.S. to Europe. No other costs are considered.
Consequently, in determining how the coal should optimally flow
to Europe, for cost reasons, we always prefer to ship from the
closer East Coast ports rather than the Gulf Coast ports, and
prefer to ship from a dredged East Coast port rather than a
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II
nondredged East Coast port. In essence, we assume that the
price of coal at the U.S. port, prior to shipment, is the same
for all ports under consideration. (This could easily be
changed to differentiate the price of coal according to port of
embarkation.) In addition, we do not distinguish between types
of coal, e.g., low-sulfur vs. high-sulfur. The model, though,
due to the port capacity restrictions* and due to the variety of
dredging options (i.e., a dredged Gulf Coast port might be
preferred to a nondredged East Coast port), does not allocate
all of the coal demand to the East Coast ports.
(d) In the model, we assume that the domestic U.S. logistical
infrastructure for moving coal from the mine to the port has
sufficient capacity and will not restrict the coal throughput at
any of the ports. Rather, the only constraint at each port is
the coal-handling capacity of that port's coal facilities.
(e) Similarly, we assume that both the European ports and the
European coal logistical infrastructure provide no constraints
to the movement of coal. Hence, if a U.S. port is dredged to 55
feet, then we assume that all coal that is shipped from that
port to Europe goes to European ports that are at least 55 feet
deep and can be transported efficiently to the ultimate user.
Consequently, we assume that we can fully exploit the potential
*The concept of port capacity is somewhat ambiguous, especially at a portlike New Orleans where extensive midstreaming is possible. Essentially,we use the general categories for capacity of "existing," "underway," and"planned," measured in tons per year, as given in the literature on coal-port development.
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benefits from dredging a U.S. port; that is, the dredged U.S.
port receives the largest ship possible and achieves the
greatest transportation savings for the coal that it ships. In
effect, we act as if Europe is fully-dredged and able to capture
the benefits of large vessels. We then ask what should the U.S.
dredging policy be. Therefore, if anything, there is an
implicit bias in favor of dredging, at least in the construction
of this model.
(f) We also assume no fleet constraints on the size and type of
ships for moviIg coal. All coal shipped from a U.S. port is
assumed to be shipped on the largest possible class of ship that
can enter the U.S. port (e.g., a Panamax vessel for a port with
a 40-foot draft), and hence goes at the lowest possible cost.
Again, it should be noted that this assumption also implicitly
is biased in favor of dredging.
(g) The analysis does not consider any non-coal benefits from
dredging, such as lower shipping costs for other commodities.
This is consistent with the view that the coal trade to Europe
is the primary ustification for dredging the ports of the East
Coast and Gulf Coast (Another recent study that takes a similar
position is U.S. Department of Energy, May, 1983).
(h) We assume that there are no benefits from dredging for U.S. coal
going to non-European destinations. However, we have reduced
the throughput capacity at each port by an amount corresponding
to the expected volume of coal going to non-European
destinations. We believe this assumption to be reasonable,
since the coal volume from the ports under consideration to
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non-European destinations, with the exception of Japan, is small
in nature and is unlikely to go in deep-draft ships due to port
and demand constraints on the receiving end.
The lack of benefits for the Japanese coal is less clear,
although we offer two comments. Firstly, from the East Coast
and Gulf Coast, any deep-draft ship could not go through the
Panama Canal and must make a much longer trip around Cape Horn.
Secondly, many experts expect that West Coast ports will handle
most of the projected growth in the Japanese steam coal trade.
In summary, we have taken a perspective that focuses on
what we believe to be the key tradeoff: the cost of dredging
versus the ocean transportation savings of moving coal from the
United States to Europe in large coal-carrying colliers. The
preceding observations and assumptions are made primarily to
highlight this tradeoff.
C. Formulation of the Model
In this section, we formulate the model in mathematical terms as
a mixed-integer linear program.
To formulate the model, we need to introduce the following
notation:
Indices:
i Will denote a port in United States;
k Will index the dredging options at a particular port, e.g.,
k = 1 : do nothing
k = 2 : dredge to 50'
k = 3 : dredge to 55';
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j Will denote a demand center, e.g., = 1 may index the demandfor coal in Spain;
I Is the number of U.S. ports under consideration;
Ki Is the number of dredging options at Port i;
J Is the number of demand centers.
Decision Variables
Yik = 0,1 Binary decision variable to denote whether Option k at Port iis chosen.
xijk - Continuous decision variable to denote the amount of coalgoing to Demand Center j from Port i, assuming that Option kis chosen for Port i (i.e., Yik = 1).
If Yik = O, then xijk = 0 for all j.
Parameters:
Dj Demand requirements (annual) for Demand Center j.
Sik Annual throughput capacity of coal at Port i under Option k;(this should reflect expected coal-handling facilities atPort i).
Li Minimum annual volume of coal that must be shipped from Port i.
Fik Annualized fixed cost for dredging Option k at Port i. Thiscost includes the annualization of the dredging cost plus the
annual maintenance cost. To annualize the dredging cost, wemultiply the one-time dredging cost by an assumedcost-of-capital percentage, which is parametrically varied.
Cijk Variable ocean-transportation cost (/ton) for shipping coalto Demand Center from Port i where dredging Option k is
chosen at Port i. This cost depends on the size of ship thatcan access Port i under Option k.
Now the model formulation is a mixed-integer linear program and can bestated as follows:
I K J
(1) Min Z EC ikYik C i jki jk)i=1 k=l j=l
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1l
subject to
I K(2) x DJ for J=1,2,...,J
il k=l1
(3) i Xijk - SikYik < 0 for i=l,2,...,I
J Kj=k i for i=1,2,...,I
Ki
(5) X Yik = for i=1,2,...,Ik=l
(6) Yik = 0, 1; xiJk 0 for all i, , k.
Explanation of formulation for each equation:
(1) Objective function is annualized fixed costs plus variable costs.
(2) This ensures that we satisfy demand requirements for all demandcenters.
(3) This ensures that we do not exceed capacity at a particularport. Also, it forces xijk to be zero, if Yik = 0.
(4) This ensures that each port ships a minimal amount of coal, asspecified by Li.
(5) This ensures that exactly one option is chosen for each port(including a "do nothing" option).
(6) Variable type specification. Yik are binary decisionvariables, while xijk are non-negative continuous variables.
The model is analogous to the standard model for a "capacitated
warehouse location problem" (CWLP) as treated in the management science
literature. (See, for example, Akinc and Khumawala, 1977 and Geoffrion and
McBride, 1978.) In a CWLP, the intent is to find the optimal warehouse
locations from a set of candidate warehouse locations, and then to determine
which customers are served by which warehouses. An optimal solution
-15-
minimizes the fixed cost of operating the warehouses, plus the variable cost
of satisfying customer demand from the various warehouses. Each warehouse
has a capacity limit on how much demand it can handle, and all customer
demand must be satisfied.
The model proposed here by (1) - (6) is very similar to a CWLP. At
each port, the dredging options correspond to the candidate warehouse
locations. The demand centers for coal are the warehouses' customers. The
allocation of coal demand to ports is made so that all demand is satisfied,
the capacity at each port is not exceeded, and the annual costs (fixed and
variable) are minimized.
We have implemented an adaptation of the solution procedure given by
Akinc and Khumawala, 1977 to solve the model (1) - (6). This solution
procedure is a branch-and-bound procedure in which bounds are generated by
solving a network-problem relaxation to the original problem (1) - (6).
-16-
Section III
Data Used in the Analysis: Sources, Assumptions, and Discussion
Our analysis uses various categories of data, including estimates and
assumptions of coal-export demand in Europe, estimates of U.S. coal-port
capacities, estimates of dredging costs at five ports (Hampton Roads,
Baltimore, Mobile, New Orleans, and, as a special case, the Port of New
York), ocean-transportation cost estimates, and cost-of-capital estimates.
What follows is a discussion of our data, the data sources, assumptions
concerning these data, and a description regarding the various data
scenarios used.
A. Demand
Tables 6 through 9 deal with our demand projections. Our
initial source for metallurgical demand projections are the actual
1981 metallurgical coal export figures broken down by destination of
shipment (International Coal Review, February 12, 1982). As seen in
Table 6A, for our base case we increased 1981 metallurgical coal
exports to Europe by ten percent. As seen in Tables 7 and 8, the
steam coal demand projections are based on the forecasts of the
Interim Interagency Coal Export (ICE) Task Force Report of January,
1981. Basically, the low, medium, and high projections were
calculated by taking the most likely steam coal import forecasts for
1990 and 2000 of each European coal-importing nation, and then
multiplying by the bottom, top, and mid-U.S. steam coal market share
projections for each country (ICE Report, January, 1981, pages 47, 48).
We then generate a set of demand scenarios by combining various
estimates of metallurgical and steam coal demand. For these demand
-17-
III
scenarios we aggregated the demand centers into two major and
representative demand clusters: Northwest Europe and Mediterranean
Europe. We use this aggregration because we are only concerned with
the Trans-Atlantic cost savings that result from dredging, and because
the geographic demand profile, as reflected broadly in terms of
transportation costs and coal-port location, appears to fit such a
two-region pattern.
Tables 9-A through 9-G list the various demand scenarios for
U.S. coal exports that are used in our analysis in order of increasing
magnitude. Generally, most coal-export forecasts generated by
responsible analysts are approximated in one or another of these
projections. Please note that we ignore Far East demand in most of
these projections. Currently, as much as 30 million short-tons per
year go to the Far East. However, we do take account of expected Far
East demand in our port capacity assumptions and demand projections.
B. Port Data: Cost of Capital, Capacity, and Dredging Costs
In characterizing the ports, we need to address the following
issues: the cost of capital, port capacity, forced throughput at each
port, dredging options, and investment and maintenance costs.
For the cost of capital, we used the following set of interest
rates: 7.5 percent (which corresponds to the Corps of Engineers'
interest rate), 10 percent (intermediate value), 12 percent (treasury
bond), and 15 percent (an approximate private sector investment hurdle
rate).
Table 10 provides the port capacity figures used in this
analysis. As noted before, the capacity figures are highly fluid;
-18-
and, as can be seen on Table 10, there can be a significant disparity
between the various reference sources. Much of this disparity is due
to differences in definition of the capacity categories. Also,
different sources accept different levels of credibility in listing
capacity-expansion plans. The three categories used in this study are
existing, underway, and planned. We generally use the categories
existing plus underway as a "base case". But other port capacity
projections are also used in some of our model simulations.
We also are aware that planned port capacity may actually be
very dependent on port dredging decisions. However, in our model
simulations, we ignore this possible relationship and assume that the
port capacity figures used in each of the various simulations will
occur regardless of dredging decisions. We make this assumption in
order to avoid generating results that choose dredging only because
the dredging option may be the only way to achieve the stipulated port
capacity for a simulation.
The model, if left totally unconstrained with regard to capacity
and throughput, would automatically allocate coal throughput to the
least costly port. Therefore, one or more ports could possibly ship
no coal at all under certain scenarios. For political, behavioral,
and practical reasons (and possibly economic ones would emerge as well
under more detailed case-by-case scrutiny), such a situation is
obviously unrealistic. In order to avoid such a circumstance, as seen
in Table 11, we have constrained our model by forcing a certain amount
of coal equal to European coal export shipments in 1981 as a minimum
bound through each of the four primary coal ports under consideration
-- IIampton Roads, Baltimore, Mobile, and New Orleans. Except for New
-19-
Orleans, which shipped only 3.8 million short-tons in 1980, the total
amount of coal shipped through each port in 1980 was about the same as
in 1981. The coal shipped from these four ports to non-European
destinations was primarily metallurgical coal for Japan. These
non-European shipments were subtracted from the capacity projections
at each port in order to give an effective capacity available for
European demand.
Table 12 provides the investment and annual maintenance cost
data for each dredging option (e.g. 45 feet, 50 feet, and 55 feet) for
each of the four ports*.
C. Ocean Transportation Cost Savings
To calculate ocean transportation cost savings resulting from
using a larger vessel, we need to know the distance traveled, the
speed of the ship or the number of days at sea, the relationship
between draft and ship size, and the various component cost factors
that make up total transportation costs.
We have used two representative European destinations, Rotterdam
in the northwest and Taranto, Italy in Mediterranean Europe. We
assign to each European country either the Rotterdam rate or the
Taranto rate as is indicated in Table 13. We assume that the
round-trip voyage period to Taranto is 5.5 days more than to
Rotterdam. (This additional time increment is based on a one-way
voyage length from Rotterdam to Taranto of about 990 nautical miles
and an average speed of 14.5 knots.) (H. P. Drewry, page 98.)
*Please note that Baltimore is authorized to be dredged only to a depth of50 feet.
-20-
In Table 14, we indicate the general relationship between draft
and ship size. In Table 15, we list the specific relationship that we
will assume in our model.
The derivation of ocean transportation costs is initially based
on the figures of the Norwegian shipping firm, R. S. Platou, and we
subsequently modified these figures using various assumptions. The
figures and derivations have also been compared to other published
figures, especially those of shipping consulting firm, H. P. Drewry.
A key aspect of the debate over ocean transportation cost savings,
from the use of large coal-carrying colliers involves determining the
size of benefits due to economies of scale that would result from
using big ships. High savings would mean full economies of scale,
both at sea and in loading and unloading in port. Analysts at Royal
Dutch Shell basically subscribe to this view. (Royal Dutch Shell
Telex of May 6, 1982, and discussions in London in June, 1982.) On
the other hand, both R. S. Platou and H. P. Drewry forecast lower cost
savings due primarily to an inability to obtain economies of scale in
port (R. S. Platou slides and discussions with R. S. Platou analysts
at MIT in 1982). H. P. Drewry also has identified alternate
cost-savings scenarios. (H. P. Drewry, pages 89-104.) In any event,
as will be seen, we can manipulate R. S. Platou's format so that, like
Shell's figures, high cost savings are generated.
Other aspects of our data base are worth noting. For example,
because R. S. Platou's construction and labor costs are based on
Norwegian industry figures, they are high relative to many other data
sources. Or, to take another example which has the opposite effect,
we may have overstated the savings from dredging since (as seen in the
-21-
Royal Dutch Shell costs) it may often have been cheaper to light load
a big ship (such as a 160,000-DWT collier), rather than fully load a
smaller, but still large, vessel (such as a 120,000 DWT collier) at a
particular draft (Royal Dutch Shell Telex of May 6, 1982 and
discussions in London). But we believe these and possibly other
specific or idiosyncratic aspects of our data base or data assumptions
will have little influence on our general findings because of the wide
range of simulations that were run.
R. S. Platou's original assumptions are given in Table 16. For
R. S. Platou, fuel and diesel oil costs depend primarily on days in
transit, the ship's speed, and size of ship; harbor fees depend only
on size of ship; operating and capital costs depend on total number of
voyage days, which is days in transit plus days in port, and on size
of ship. Therefore, the number of days in port affects only operating
and capital costs. In deriving our set of various ocean
transportation costs, we assume for a given size of ship that the
harbor fee is fixed, that operating and capital costs are directly
proportional to voyage days (which equal days at sea plus days in
port), and that fuel and diesel oil costs remain the same for
Rotterdam but will increase in proportion to total voyage days for
going to Taranto.
Table 17 is R. S. Platou's original calculation of the ocean
transportation costs for the voyage from Hampton Roads to Rotterdam.
It represents a "low cost savings" scenario.
To obtain a "high cost savings" scenario for the Hampton Roads-
Rotterdam route for, say, a 120,000 DWT vessel, as seen in Table 18,
we assume that there will be port-handling economies of scale for the
-22-
larger collier. In particular, we assume that the time to unload/load
a collier is independent of the collier's size. Accordingly, a ship
on the Hampton Roads-Rotterdam route spends 29 voyage days no matter
what the ship's size. We leave fuel oil, diesel oil, and harbor costs
unchanged. But we now reduce operating and capital costs by 29/32
since the number of voyage days is reduced from 32 to 29.
This contrasts with the assumptions of R. S. Platou, as
represented in the "low cost savings" scenario in Table 17, where the
assumption is.that the rate for load/unloading is constant for all
size ships so that a larger ship requires more days in port. In fact,
the whole issue of whether there are significant economies of scale
for days in port, which affects operating and capital costs figures,
is a key point of debate between those analysts, such as at R. S.
Platou, who tend to downplay the advantages of large coal-carrying
colliers and emphasize the lack of significant economies of scale for
load/unloading in port and those, such as at Royal Dutch Shell, who
tend to assume significant economies of scale for load/unloading in
port. (R. S. Platou slides and Telex from Royal Dutch Shell of
June 5, 1982.)
Let us now look at another example. In order to.decide the "low
cost savings" for the Hampton Roads-Taranto voyage for, say, a 120,000
DWT ship, we leave.harbor costs unchanged, but the voyage length is
now 37.5 days (5.5 days more days at sea than to Rotterdam).
Therefore, fuel oil, diesel oil, operating, and capital costs need to
include costs for the additional 5.5 days at sea over the costs for
the "low cost savings" Hampton Roads-Rotterdam voyage. The results
are seen on Table 19. Tables 17 through 24 provide the derivations
-23-
for "low" and "high cost savings" rates from both the East Coast
(Hampton Roads) and the Gulf (New Orleans) to either Northwest Europe
(Rotterdam) or Mediterranean Europe (Taranto). We assume that the
ocean transportation costs from Baltimore would be approximately the
same as from Hampton Roads and that the shipping costs from Mobile
would be approximately the same as from New Orleans. Table 25
summarizes the results of these derivations.
We note here that the critical input to our study is not the
absolute ocean transportation costs, but rather the relative savings
in ocean transportation costs due to the use of larger colliers.
These relative savings will dictate whether the costs of dredging can
be justified. Hence, in this light, the "low-savings" scenario
implies a $2.10 per short-ton savings from dredging a 40-foot draft to
a 55-foot draft for shipments from the East Coast to Northwest Europe
(Rotterdam); the "high-savings" scenario gives a $3.38 per short-ton
savings. A similar interpretation applies for the other cases.
-24-
Section IV
Model Runs With Hampton Roads, Baltimore, Mobile,
and New Orleans
A. Overview of Model Runs
We are now ready to run our model, but first let us offer some
comments. We will run the model under various scenarios and will
change assumptions concerning demand, cost of capital, port capacity,
and/or ocean transportation costs. The model will select the most
cost-effective route and will select the most cost-effective dredging
options where appropriate.
For each scenario, we also attempt to assess the sensitivity of
the solution to the cost parameters. First, for each simulation we
indicate the "Investment Range," that is, the percentage that all
investment and maintenance costs can be increased before the
no-dredging solution (i.e. the status quo) is preferred to the stated
optimal dredging policy. Second, we generate a "Breakeven Capital
Cost" percentage, which is the upper limit of the cost of capital for
the preferred dredging solution. Any cost of capital percentage
exceeding the breakeven implies that the no-dredging solution is
preferred. Tables 26-A through 26-G list the results of our model
runs.
B. An Illustration
In order to help understand our results, we offer an
illustration. Let us consider the first case in Table 26-B; here we-25-
take demand to be level B (from Table 9-B: 20 percent growth for
metallurgical coal; and midpoint projections for steam coal for 2000
from the ICE Report) and the ocean transportation costs to be the
"low-savings" case (from Table 25). Total European demand, therefore,
is 90.8 million short-tons per year. The port capacities (in million
short-tons per year) from Table 10 are:
Hampton Roads 126.8
Baltimore 53.6
Mobile 20.0
New Orleans 111.0
We also assume that a portion of this capacity must be used for
non-European coal demand, where the amount is set equal to the 1981
levels (from Table 11). This leaves an effective port capacity (in
million short-tons per year) for coal exports to Europe as follows:
Hampton Roads 105.7
Baltimore 48.5
Mobile 18.0
New Orleans 105.5
Clearly, there is more-than-adequate port capacity to meet the demand
level for this illustrative case.
Now, for each port we force a certain amount of the European
exports through that port, according to 1981 shipments (from Table
11). In total, 48.6 million short-tons are forced through the four
ports; the remaining demand of 42.2 million short-tons are allocated
-26-
to the ports by the model. If no dredging occurs, the model assigns
the demand as follows:
DestinationTo
Northwest MediterraneanFrom Europe Europe Total
Hampton Roads 39.8 33.3 73.1
Baltimore 7.8 0 7.8
Mobile 1.5 0 1.5
New Orleans 8.4 0 8.4
Total 57.5 33.3 90.8
The average cost is 10.02 per ton, assuming the "low-savings"
rates. We note that the demand assigned to Baltimore, Mobile, and New
Orleans occurs only due to the constraint that requires a minimal
level of throughput at these ports. If we did not have this
constraint, Hampton Roads will supply all demand.
When dredging is permitted, the model finds that the dredging of
HIampton Roads from 45 feet to 55 feet can be justified provided that
the hurdle rate (the capital cost) for the investment is less than
14.2 percent. Otherwise, no dredging is the best solution. When
Hampton Roads is dredged, the assignment of demand does not change
from the no-dredging case.
To see why we can justify the dredging of Hampton Roads,
consider the cost savings. There will be a savings of .88 per
short-ton (9.11 minus 8.23) for the 39.8 million short-tons that go to
-27-
Northwest Europe; similarly, there will be a savings of 1.19 per
short-ton (10.52 minus 9.33) for the 33.3 million short-tons that go
to Mediterranean Europe. In total, the transportation cost savings
are 74.7 million per year. The one-time cost to dredge Hampton Roads
is $480 million, with an annual maintenance cost of $6.7 million. At
an annual capital cost of 14.2 percent, the annualized cost of
dredging, including maintenance, is 74.7 million. Hence, below this
capital cost the benefits of dredging outweigh the costs, and
vice-versa for a higher capital cost.
We must emphasize that in this analysis we view the ocean
transportation cost savings as the only benefit from dredging. But
one can incorporate other quantifiable benefits from dredging into
this analysis in a relatively straightforward manner.
Table 27 summarizes these results. Note especially the
prevalence of the no-dredging solution for low demand conditions and
the choice of dredging Hampton Roads to 55 feet under a wide range of
conditions. In Section VI we will discuss the implications of these
results.
-28-
Section V
Model Runs that Include the Port of New York
We also ran a special set of simulations that included coal-port plans
for the Port of New York (i.e. the proposed coal port of New York City and
the proposed coal port of the New York Port Authority). We decided to
generate an entirely separate set of simulations that included the Port of
New York because, although the Port of New York options were emerging at the
time of our analysis and were generating interest, they also appeared much
more uncertain, incomplete, and speculative than the plans for the other
four ports that we studied.* From an overall perspective, moreover, it may
be useful to see how the inclusion of a fifth port with somewhat different
characteristics affects the solutions of our analysis.
Based on discussions with relevant officials in the New York Port
Authority and the City of New York, the following assumptions for the Port
of New York coal ports were made: the investment cost for dredging is 200
million; the annual maintenance cost is 5 million; and the annual capacity
of the two Port of New York coal ports for export coal is 30 million
short-tons.
We also assumed that if no dredging takes place, then no coal ports at
the Port of New York would be constructed, and, hence, no coal exports from
this port would occur. For transportation rates, we performed two sets of
analyses based on our assumptions for transportation rates -- the first set
assumed that if the New York harbor is dredged, then the cross-Atlantic
*Indeed, these proposed port plans for the Port of New York were laterabandoned. But these plans, or similar plans, for the Port of New York maysomeday reappear.
-29-
rates would be comparable to those from Hampton Roads dredged to 55 feet.
This set only considered the case of "medium" transportation savings.
Tables 28-A through 28-G list the results of this set of runs.
In the second set of model runs, the assumptions were the same as in
Table 28 except that now the Port of New York is assumed to have a
transportation cost savings over Hampton Roads at 55 feet of anywhere from
no cost savings per ton to a savings of $4.00 per ton. Table 29 lists the
results of this set of the model runs. Note especially the continued
strength of the no-dredging solution at the low demand levels, and the
solution of dredging solely Hampton Roads to 55 feet at the low savings
levels. The implications of these results are discussed in Section VI.
-30-
Section VI
Conclusion
Before discussing the implications of our results and our general
conclusions, we want to reiterate that our societal cost-benefit examination
of the coal-port dredging question did not use a complex analytical model.
Rather we explicitly chose to rely on a relatively simple model that would
clearly highlight what we believe to be the key tradeoff: the cost of
dredging versus the possible ocean transportation cost savings.
Our results lead to a number of implications and general conclusions.
Certainly, the analysis lends support to those recommending caution in
approaching the funding of coal-port development (recent examples of other
studies taking a similar position include Evered, 1983, U.S. Department of
Energy, May, 1983, and U.S. General Accounting Office, August, 1983). Above
all, we found that we could not justify dredging simultaneously all dredging
options. This is because of the interdependence of the various ports. They
must share demand or compete for demand. In fact, it is only when we reach
a relatively high demand projection, Demand D, that our model indicates that
the optimal course of action is to dredge more than one port. Moreover,
such a solution is only generated when capital costs are lowered to ten
percent and transportation cost savings are "medium."
Perhaps even more striking is the robustness of two solutions: no
dredging (the status quo) or dredge only Hampton Roads to 55 feet. As seen
on Table 27, if one is both somewhat conservative regarding demand
projections (thereby adhering to Demand A) and also requires a relatively
high hurdle rate for a societal return-on-investment, then a no-dredging
option for the European coal market makes a great deal of sense for American
society as a whole.
-31-
But if one believes that European demand for U.S. coal will ultimately
increase at least to Demand B or that we can accept a lower societal
return-on- investment, then dredging only Hampton Roads to 55 feet is the
clear choice for a wide range of alternatives. We should also note that
Hampton Roads is preferred over Baltimore because Hampton Roads has more
capacity and is a deeper port.
In order to gain some perspective on the robustness of the solutions
resulting from our analysis, let us look at our results from a total annual
cost and annual savings viewpoint, as seen in Table 30.
This table gives the cost consequences for the no-dredging case, and
three dredging options over the seven demand cases. The three dredging
options are to dredge Hampton Roads to 55 feet; dredge Hampton Roads to 55
feet and Baltimore to 50 feet; and dredge Hampton Roads to 55 feet and New
Orleans to 55 feet. The ocean transportation costs are derived assuming the
"medium savings" rates.
Using Table 30, we can make some observations on the robustness of the
various options. Dredging Hampton Roads yields a reduction in ocean
transportation costs of 66 million per year over the no-dredging option for
the lowest demand case (Demand A: 60.5 million short-tons per year).
Savings in ocean transportation costs increase to $170 million per year for
the highest demand case (Demand G: 207.5 million short-tons per year).
Dredging Baltimore in addition to Hampton Roads gives some additional
savings in ocean transportation costs: an additional $8 million per year
for the lowest demand case, increasing to an additional 44 million per year
for the highest demand case. Hence, the incremental investment ($302
million) in dredging Baltimore would seem justifiable only if demand
projections were 160 million short-tons per year (i.e., Demand E) or
-32-
1I
higher. Dredging New Orleans in addition to Hampton Roads is viable only
for the highest demand cases (i.e., Demand F and Demand G). Annual demand
has to be on the order of 200 million short-tons per year before the
incremental savings in ocean transportation costs from dredging New Orleans
(in addition to Hampton Roads) can even cover the additional annual
maintenance costs for New Orleans, let alone provide a meaningful return on
the required investment to perform the dredging.
Furthermore, one can also support the dredging of Hampton Roads on
grounds that are not explicitly considered in the model. First, the whole
coal-port development issue is a long-term and complex one and should be
evaluated as a long-term and multifaceted investment. Such huge development
projects tend to take longer to be constructed than original projections
indicate, although they also tend to cost more than originally estimated
(Merrow, et.al., July, 1979). Although coal export demand, for example, may
be disappointingly low in, say, 1990, it may grow rapidly during the 1990's
and, therefore, be rather high in, say, the year 2000. In other words,
while there may be fluctuations in demand, we must emphasize possible
long-term patterns of demand. However, we must be careful not to choose
solutions that are far from those that can be economically ustified on a
societal cost-benefit basis. A recent study, for example, by maintaining
the current ratio of shipments of coal exports by ports, advocates dredging
New Orleans (Greer, 1983). This solution -dredging solely New Orleans--
was never preferred in any of our simulations.*
*Although we "force" a certain amount of coal through each of the fourexisting coal ports that we studied to account for political, logistical,and economic realities, we do not require the long-term maintenance of aspecific ratio of coal-export shipments by ports.
-33-
Another feature of the whole coal-export question is that the United
States now has no deep-water coal port. It may be prudent to have at least
one such port to serve the European coal market in order to capture the
benefits of a growth in demand at some point in the future and also to gain
experience in using such facilities. According to our analysis, dredging
Hampton Roads to 55 feet is the clear choice for at least the East Coast and
Gulf region for accomplishing such broad policy goals.
Even when we include the Port of New York in our analysis and then run
our model, the solution of dredging Hampton Roads to 55 feet emerges as
optimal under a number of likely conditions. As seen in Tables 28-A through
28-G, this solution is optimal at least through Demand C. As seen in Table
29, when the Port of New York has no cost savings over Hampton Roads, then
the dredging of Hampton Roads to 55 feet seems to dominate the dredging of
New York. (But then New York dominates Baltimore.) However, when the Port
of New York has some transportation savings over Hampton Roads, it is less
clear. It seems that if the savings are from t1.00 to 2.00 per ton, then
the Port of New York is either preferred to Hampton Roads or can be
justified along with Hampton Roads for several of the low demand scenarios.
When savings are more than $2.00 per ton, then the Port of New York is
preferred, although typically both can be
justified.
This study deals with a specific issue in one industry. However, at a
more general level, the way we structured the coal-port dredging question
--presenting a small number of variables and nominally simple alternatives
in formulating the problem and our model-- has highlighted some of the
classical problems of such society-wide policy issues as "national
industrial policy". We have actually found that such phenomena involve
-34-
alternative sets of different formulations, different answers, and different
beneficiaries.
To focus once more on the specific issue at hand -- coal-port
development on the East and Gulf Coasts, what is very clear and what emerges
unambiguously is that the concurrent dredging of more than one port is
unwise unless one supports the most optimistic projections for coal-export
demand or relatively low real interest rates over the long run. Moreover,
under no condition that we examined, does it make sense to dredge either of
the Gulf ports --Mobile or New Orleans-- before dredging Hampton Roads or
Baltimore.
-35-
Table 1
Trends in U.S. Coal Production and Exports(Million Short-Tons)
TotalProduction
(estimated)
434.3420.4439.0477.2504.2527.0546.8564.9556.7571.0612.7560.9602.5598.6610.0654.6684.9697.2670.2781.1829.7820.1833.0
Total
Exports
38.036.441.251.350.952.250.851.052.057.972.458.057.254.061.166.860.654.741.066.491.7112.5108.0
Percentage
Exports
of Total
8.7%
8.7%9.4%10.8%10.1%9.9%9.1%9.0%9.3%
10.1%11.8%10.3%9.5%9.0%
10.0%10.2%8.8%7.8%6.1%8.5%
11.1%13.7%13.0%
SOURCES: U.S. Department of Energy, Quarterly Coal Report: January -March, 1982, DOE/EIA-0121 (82/10) (Washington, D.C.: GovernmentPrinting Office, August, 1982), page 63; personal communicationwith U.S. Department of Energy on January 13, 1983.
-36-
Year
19601961196219631964196519661967196819691970197119721973197419751976197719781979198019811982
Table 2
U.S. Bituminous Coal Exports, 1973-1981(Million Short-Tons)
MetallurgicalCoal Exports_
42.651.651.647.841.929.850.763.165.2
Steam CoalExports
10.38.3
14.111.611.810.014.126.845.0
Total
Exports
52.959.965.759.453.739.864.889.9
110.2
Steam Coalas a
Percentageof Total
Exports
19.5%13.6%21.5%19.5%22.0%25.1%21.8%29.8%40.8%
SOURCE: U.S. Department of Energy, U.S. Coal Exports: Projections andDocumentation, #DOE/ElA-0137 (Washington, D.C.: GovernmentPrinting Office, March, 1982), page 5.
-37-
Year
197319741975197619771978197919801981
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Table 4
Survey of World Ports with Existing and PlannedOperating Channel Depths in Excess of 45 Feet
Port
Japan:KimitsuKashimaMuroranKawasakiMizushimaFukuyamaChibaTobataKakoganaOita
United Kingdom:HunterstonPort TalbotRedcar
The Netherlands:Rotterdam
ProposedIJmulden
Federal Republic ofGermany:WilhelmshavenHamberg
France:Le HarveProposed
MarseilleDunkerque
ProposedNates St-NazaireFos
Italy:Taranto
MaximumDraft
in Feet
59.0457.0052.4867.0052.4852.4855.7657.0052.4879.00
95.1246.9752.97
68.0072.0052.00
47.0047.00
45.9252.4861.0045.9275.4451.0057.00
52.00
Port
Belgium:Antwerp
Finland: PortSweden:
GoteborgOxelosund
Denmark:AabenraaStignaes
Spain:BarcelonaGijon-MuselSaguntoCarboneras
Yugoslavia:RiJeka
Australia:Abbots PointHay PaintNewcastlePort KemblaGladstone
South Africa:Richards Bay
ProposedCanada:
Quebec CityVancouverPrince Rupert
Poland:Gdansk
U.S.S.R.:Vostochnyy
SOURCE: U.S. Congress House, Port Development, 97th Congress, 2ndReport 97-454, Port I (Washington, D.C.: House Committeeand Fisheries, March 9, 1982), page 28.
Session,on Marine
-39-
MaximumDraft
in Feet
54.0051.00
56.0072.00
55.0049.00
127.0050.0049.0055.00
51.00
72.0056.0054.0053.0054.00
56.0075.00
48.0065.0065.00
50.00
50.00
ooc rs - L) I
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Table 6A
U.S. Metallurgical Coal Exports - Projections
(Million Short-Tons)
Base Year
1981
AustriaBel/LuxDenmarkFinlandFranceGreeceIrelandItalyThe NetherlandsNorwaySpainSwedenUnited Kingdom
West Germany
Total
Japan
03.0.4
04.8.1.3
6.62.8.32.71.11.91.9
25.9
10%
03.3.4
05.3.1.3
7.33.1.33.01.22.12.1
28.5
21.9
Table 6B
U.S. Metallurgical Coal Exports to Europe fromSelected U.S. Ports in 1981
(Million Short-Tons)
BaltimoreHampton RoadsMobileNew Orleans
Total
4.112.61.32.8
20.8
SOURCE: International Coal Review, February 12, 1982.
-41-
20%
03.6.5
05.8.1.4
7.93.4.4
3.21.32.32.3
31.2
Table 7
Projected U.S. Steam Coal Exports From
East Coast and Gulf Ports: 1990
(Million Short-Tons)
Low Medium High
Austria 0 1.0 2.0
Bel/Lux 2.6 3.8 5.1
Denmark .8 2.8 4.8
Finland 1.4 1.8 2.1
France 2.9 4.2 5.7
Greece .4 1.0 1.6
Ireland .4 .8 1.2
Italy 3.9 5.9 7.8
The Netherlands .8 1.9 3.0
Norway .2 .3 .4
Spain 1.8 2.7 3.6
Sweden 0 1.7 3.3
United Kingdom .8 1.0 1.2
West Germany 1.6 3.1 4.7
17.6 32.0 46.5
SOURCE: U.S. Department of Energy, (Draft) Interim Report of theInteragency Coal Export Task Force, January, 1981, pages 47, 48.
-42-
111
Table 8
Projected U.S. Steam Coal Exports fromEast Coast and Gulf Ports: 2000
(Million Short-Tons)
Low Medium--_
AustriaBel/Lux
DenmarkFinlandFranceGreeceIrelandItalyThe NetherlandsNorwaySpainSwedenUnited KingdomWest Germany
01.42.22.64.6.3.47.51.8.5
6.0015.9
34.2
2.64.92.23.39.21.21.38.84.4.9
6.64.11.38.8
59.6
5.1
8.42.23.913.72.02.110.07.01.37.28.11.511.7
84.2
SOURCE: U.S. Department of Energy, (Draft) Interim Report of theInteragency of Coal Export Task Force, (ICE Report), pages 47, 48.
-43-
Table 9
U.S. Coal Exports Demand Scenarios(Million Short-Tons)
Demand A
MetallurgicalCoal
SteamCoal Total
Northwest Europe 19.2 17.5
Mediterranean Europe 9.3 14.5
28.5 32.0
Assumptions: - 10% growth for Metallurgical Coal- Midpoint projections for 1990 from ICE Report
Demand B9-B
MetallurgicalCoal
SteamCoal
Northwest Europe 21.0 36.5
Mediterranean Europe 10.2 23.1
31.2 59.6
Assumptions: - 20% growth for Metallurgical Coal- MidpoinL projections for 2000 from ICE Report
Demand C9-C
MetallurgicalCoal
Northwest Europe
Mediterranean Europe
21.0
10.2
31.2
SteamCoal
51.6
32.6
84.2
36.7
23.8
60.5
Total
57.5
33.3
90.8
Total
72.6
42.8
115.4
Assumptions: - High-range Steam Coal projections for 2000 fromSteam Coal.
ICE Report
-44-
9-A
Table 9(cont.)
Demand D9-D
MetallurgicalCoal
Northwest Europe
Mediterranean Europe
21.0
10.2
31.2
SteamCoal
67.4
42.6
110.0
Total
88.4
52.8
141.2
Assumptions: - Steam Coal increased by about 25 million short-tons over
Demand C.
Demand E9-E
MetallurgicalCoal
Northwest Europe
Mediterranean Europe
21.0
10.2
31.2
SteamCoal
82.7
52.3
135.0
Total
103.7
62.5
166.2
Assumptions: Steam coal is increased by 25 million short-tons overDemand D. Higher steam coal projections for U.S. coal towestern Europe, which is comparable to U.S. Department ofEnergy, U.S. Coal Exports: Projections and Documentation,March, 1982 (133 million short-tons for the year 2000), page23 and ICE Report on page 102 (145 million short-tons forEurope in 2000).
-45-
Table 9(cont.)
Demand F
MetallurgicalCoal
NorthwestEurope
MediterraneanEurope
Assumptions: Steam coal is increased by 25 million short-tons over Demand E.
Demand G
9-G
MetallurgicalCoal
Northwest Europe 21.0 109.1 130.1
Mediterranean Europe 10.2 67.2 77.4
31.2 176.3 207.5
Assumptions: "Best case" steam coal projections for U.S. exports to Europefor Ray Long, Constraints on International Trade in Coal,draft report (London: IEA Coal Research, May, 1982), page83. Converted 160 million metric tons to 176.3 millionshort-tons.
-46-
9-F
21.0
10.2
31.2
SteamCoal
99.0
61.0
160.0
Total
120.0
71.2
191,2
SteamCoal Total
Table 10
Port Capacity
(Million Short-Tons Per Year)
Existing** Underway**
Hampton Roads 61.8 16.0(61.8)* (17.0)*
Baltimore 16.6 22.0(16.6)* (22.0)*
Mobile 5.0 4.0(11.0)* (14.0)*
New Orleans 16.0 15.0(18.0)* (55.0)*
SOURCE: U.S. Congress, House, Port Development, pages 86-87.
Planned
49.0(37.0)*
15.0(6.0)
11.0 (0)*
80.0(41.0)*
* The categorization and estimation of port capacity is somewhatidiosyncratic and variable. For example, contrast the capacity figuresin parenthesis, which are from the U.S. Maritime Administration (U.S.Maritime Administration, "Loading Terminals", pages 62-63), with the U.S.House figures.
** Base Case: Existing plus Underway
-47-
Table 11
1981 Coal Shipments
(Million Short-Tons)
Total Coal
Shipped
1981
Total Coal
Exports to
Non-Europe
1981
European-Bound
Coal "Forced"
Through Port in
Model as a Minimum
Export Level
Hampton Roads 52.0 21.1
Baltimore 12.9 5.1
Mobile 3.5 2.0
New Orleans 13.9 5.5
SOURCE: International Coal Review, February 12, 1982.
-48-
30.9
7.8
1.5
8.4
Table 12
Dredging Depth Options and Costs(Millions of 1981 U.S. Dollars)
Depth to be Dredged
45 Feet 50 Feet
Hampton Roads:Investment costAnnual maintenance cost
Baltimore:Investment costAnnual maintenance cost
Mobile:Investment costAnnual maintenance cost
New Orleans:Investment costAnnual maintenance cost
3104.3
151.9
2441.5
22536
301.51.8
3051.9
32271
55 Feet
4806.7
NA *NA *
4072.5
435113
SOURCE: Discussion and telephone interviews with officials in theappropriate U.S. Corps of Engineers District Offices for each ofthe four ports.
All numbers are as of October, 1981.
*Baltimore is only authorized to dredge up to 50 feet.
-49-
Port
Table 13
Ocean Transport Assumptions
Comparable
Rate
Austria TBel/Lux RDenmark TFinland TFrance RGreece TIreland RItaly TThe Netherlands RNorway TSpain RSweden TUnited Kingdom RWest Germany R
T = Taranto, Italy R = Rotterdam
We assume that all countries will have 55 feet draft coal ports and willtherefore, be able to receive as large a colliers that can be loaded andshipped from a fully dredged (i.e. 55 feet) U.S. port on the East and Gulfcoasts.
-50-
Table 14
General Relationships Between Port Draft and Ship Size
Port Draft
40 feet
45 feet
50 feet
55 feet
Ship Size
60,000 - 70,000 DT
75,000 - 90,000 DWT
100,000 - 120,000 DWT
130,000 - 175,000 DWT·
SOURCE: H. P. Drewry, pages 73, 90; discussions with R. S. Platou and slidesof R. S. Platou.
-51-
Table 15
Assumptions Regarding the Relationships Between PortDraft and Ship Size That Are Used in the Model
Port Draft Ship Size
40 feet
42 feet
45 feet
50 feet
55 feet
64,000 DWT (Panamax)
75,000 DWT (Panamax)
90,000 DWT (Coal Collier)
120,000 DWT (Bulk)
160,000 DWT (Coal Collier)
-52-
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Table 25
Ocean Transportation Costs
(Dollars Per Short-Ton)
Destination: Northwest Europe Mediterranean Europe
(Rotterdam)
"Low
(Taranto)
"High
Cost Savings Scenarios* Savings" Savings" Savings" Savings"
25-A East Coast
Size (DWT) Draft (Feet)
64,000
75,00090,000
120,000160,000
4042455055
25-B Gulf Coast
Size (DWT) Draft (Feet)
64,00075,00090,000
120,000160,000
4042455055
*We will also take the midpoints of thesewhich we term "Medium Savings."
-62-
rates for a third set of rates,
"Low "High
10.339.519.11
8.668.23
10.339.518.648.126.95
12.0611.1110.529.999.33
12.0611.119.889.267.62
12.4311.4110.7910.269.61
12.4311.4110.329.718.33
14.1913.2412.2211.6110.74
14.1913.2411.5710.879.00
Table 26
Results of Model Runs
26-A
Assumptions:Port Capacity: Existing and Underway
Demand: A
Transportation Cost: "Low Savings"Cost/Ton*
Capital Dredging with Without Investment**Cost Decisions Dredging Dredging Range
15% - - 10.2612% - - 10.2610% - - 10.267.5% HR - 55' 10.22 10.26 5.5%
Breakeven Capital Cost = 8%***
Transportation Cost - "Medium Savings"Cost/Ton
Capital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% - 10.0612% HR - 55' 10.04 10.06 1.8%10% HR - 55' 9.88 10.06 19.7%7.5% HR - 55' 9.69 10.06 53.3%
Breakeven Capital Cost = 12.2%
Transportation Cost = "High Savings"Cost/Ton
Capital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 9.74 9.86 9.1%7.5% HR - 55' 9.15 9.86 101.2%
Breakeven Capital Cost = 16.5%
* - Cost/ton is the total Trans-Atlantic transportation cost plusannualized investment plus maintenance costs for new dredging dividedby total tons of coal shipped.
** - Investment Range is the maximum percent that the dredging investmentplus maintenance costs may increase before the no dredgiag option ispreferred.
*** - Breakeven Capital Cost is the lowest capital cost at which a dredgingdecision is preferred to a no-dredging option.
-63-
Table 26(contd.)
26-B
Demand: B
Port Capacity: Existing, Underway and Planned (and for all remaining cases)
Transportation Cost = "Low Savings"
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% -- 10.02
12 HR - 55' 9.91 10.02 16.1%10% HR - 55' 9.80 10.02 35.6%7.5% HR - 55' 9.67 10.02 74.8%
Breakeven Capital Cost = 14.2%
Transportation Cost = "Medium Savings"
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 9.48 9.81 38.0%7.5% HR - 55' 9.08 9.81 154.4%
Breakeven Capital Cost = 21.2%
Transportation Cost = "High Savings"
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 8.88 9.58 81.1%
7.5% HR - 55' 8.48 9.58 233.8%
Breakeven Capital-Cost = 28.3%
-64-
Table 26(contd.)
26-C
Demand: C
Transportation Cost = "Low Savings"
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 9.76 9.94 26%
7.5% HR - 55' 9.45 9.94 132%
Breakeven Capital Cost = 19.3%
Transportation Cost = "Medium Savings"
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 9.15 9.72 83.5%
7.5% HR - 55' 8.84 9.72 238.0%
Breakeven Capital Cost = 28.7%
Transportation Cost = "High Savings"
-~~~~~~~ ~~Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 8.52 9.48 141%
7.5% HR - 55' 8.21 9.48 344%
Breakeven Capital Cost = 38.1%
-65-
Table 26(contd.)
26-D
Demand: D
Transportation Cost = "Low Savings"
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 9.73 9.94 39%
7.5% HR - 55' 9.47 9.94 156%
Breakeven Capital Cost = 21.4%
Transportation Cost "Medium Savings"
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 9.17 9.74 102%
12% HR - 55' 9.07 9.74 147%
10% HR - 55', B - 45' 8.99 9.74 148%
7.5% HR - 55', B - 50' 8.88 9.74 179%
Breakeven Capital Cost for HR - 55' = 31.8%
Transportation Cost = "High Savings"
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 8.61 9.53 165%
12% HR - 55', B - 45' 8.48 9.53 177%
10% HR - 55', B - 45' 8.39 9.53 227%
7.5% HR - 55', B - 50' 8.27 9.53 264%
Breakeven Capital Cost for HR - 55' = 42.1%
-66-
Table 26(contd.)
26-E
Transportation Cost = "Low Savings"
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 9.79 10.00 43%
12% HR - 55', B - 50' 9.69 10.00 50%
10% HR - 55', B - 50' 9.59 10.00 77%
7.5% HR - 55', B - 50' 9.48 10.00 129%
Breakeven Capital Cost for HR - 55' = 22%
Transportation Cost = "Medium Savings"
Cost/Ton
Capital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55', B - 50' 9.26 9.82 73%
7.5% HR - 55', B - 50' 8.91 9.82 224%
Breakeven Capital Cost = 26.8%
Transportation Cost = "High Savings"
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55', B - 50' 8.70 9.63 124%
7.5% HR - 55', B - 50' 8.34 9.63 320%
Bieakeven Capital Cost for HR - 55', B - 50' = 35.0%
-67-
`-`~�'�I~�"""""""""""""""
Table 26(contd.)
26-F
Transportation Cost = "Low Savings"
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 10.19 10.38 46%
12% HR - 55', B - 50', 10.09 10.38 39%M - 50'
10% HR - 55', B - 50', 9.98 10.38 59%M - 55'
7.5% HR - 55', B - 50' 9.82 10.38 107%M - 55'
Breakeven Capital Cost = for HR-55', B-50', M-55' = 16.5%
Transportation Cost = "Medium Savings"Cost/Ton
Capital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR- 55', B - 50' 9.72 10.22 76%
12% HR - 55', B - 50', 9.54 10.22 85%M - 50'
10% HR - 55', B - 50', 9.41 10.22 118%M - 55'
7.5% HR - 55', B - 50', 9.25 10.22 183%M - 55'
Breakeven Capital Cost = for HR-55', B-50', M-55' = 23.1%
Transportation Cost = "High Savings"Cost/Ton
Capital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55', B - 50', 9.16 10.06 90%M - 55'
7.5% HR - 55', B - 50', 8.69 10.06 260%M - 55'
Breakeven Capital Cost = 29.5%
-68-
.1 --l' --I - .1 -1 - - - l' ' ,~ ---- --- --- , -- -- -- --- -- - --- - --- -- .1 .I- - - -
26-G
Transportation Cost = "Low Savings"
Cost/Ton
Capital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55', NO - 45' 10.32 10.58 36%
12% B - 50', HR - 55', 10.21 10.58 47%NO - 45'
10% B - 50', HR - 55', 10.11 10.58 68%NO - 45'
7.5% B - 50', HR - 55', 9.99 10.58 103%NO - 45'
Breakeven Capital Cost for B - 50', HR - 55', NO - 45' = 20.3%
Transportation Cost = "Medium Savings"
Cost/Ton
Capital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% B - 50', HR - 55', 9.83 10.43 64%NO - 45'
7.5% B - 50', HR - 55', 9.46 10.43 167%NO - 45'
Breakeven Capital Cost 28.1%
Transportation Cost = "High Savings"
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55', NO - 55' 9.19 10.28 88%
7.5% HR - 55', NO - 55' 8.86 10.28 156%
Breakeven Capital Cost = 41.3%
-69-
Table 27
A Smunmary of Dredging Solutions in Tables 26A - 26G
Demand Levels and TransportationCost Savings Levels
15%
A - "Low Savings"
A - "Medium Savings"A - "High Savings"B - "Low Savings"B - "Medium Savings"B - "High Savings"C - "Low Savings"C - "Medium Savings"C - "High Savings"D - "Low Savings"D - "Medium Savings"
D - "High Savings"
E - "Low Savings"
E - "Medium Savings"
E - "High Savings"
F - "Low Savings"
F - "Medium Savings"
F - "High Savings"
G - "Low Savings"
G - "Medium Savings"
G - "High Savings"
HR - 55'
HR - 55'HR - 55'
HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'
Demand and TransportationCapital Cost Levels
12%
HR - 55'
HR - 55HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'
HR - 55' HR - 55'B - 45'
HR - 55' HR - 55'B - 50'
HR - 55' HR - 55'B - 50' B - 50'
HR - 55' HR - 55'B - 50' B - 50'
HR - 55' HR - 55'B - 50'M - 50'
HR - 55' HR - 55'B - 50' B - 50'
M - 50'HR - 55' HR - 55'B - 50' B - 50'M - 55' M - 55'HR - 55' B - 50'NO - 45' HR - 55'
NO - 45'B - 50' B - 50'HR - 55' HR - 55'NO - 45' NO - 45'HR - 55' HR - 55'NO - 55' NO - 55'
10%
HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'B - 45'
HR - 55'B - 45'
HR - 55'B - 50'
HR - 55'B - 50'
HR - 55'B - 50'
HR - 55'B - 50'M - 55'
HR - 55'B - 50'M - 55'
HR - 55'B - 50'M - 55'B - 50'
HR ' 55'NO - 45'B - 50'HR - 55'NO - 45'HR - 55'NO - 55'
-70-
7.5%
HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'HR - 55'B - 50'HR - 55'B - 50'
HR - 55'B - 50'
HR - 55'B - 50'
HR - 55'B - 50'
HR - 55'B - 50'M - 55'
HR - 55'B - 50'M - 55'HR - 55'B - 50'M - 55'B - 50'
HR - 55'NO - 45'B - 50'
HR - 55'NO - 45'HR - 55'NO - 55'
9
t
Table 28
Model Runs that Include the Port of New York
Assumptions:
- Transportation Savings for the Port of New York are Comparableto Hampton Roads
- Ocean Transportation Cost: "Medium Savings" for all runs
28-A
Demand A:
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% - 10.06
7.5% HR - 55' 9.68 10.06 53%
Breakeven Capital Cost = 12.2%
28-B
Demand: B
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 9.48 9.81 38%
7.5% HR - 55' 9.08 9.81 154%
Breakeven Capital Cost 21.2%
-71-
II'
Table 28(contd)
28-C
Demand: C
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 9.15 9.72 83%
7.5% HR - 55' 8.84 9.72 238%
Breakeven Capital Cost = 28.7%
28-D
Demand: D
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55' 9.17 9.74 102%
12% HR - 55', NY - 68' 9.03 9.74 107%
10% HR - 55', NY - 68' 8.93 9.74 142%
7.5% HR - 55', NY - 68' 8.81 9.74 208%
-72-
Breakeven Capital Cost for HR - 55', NYC - 68' = 26.7%
Table 28(contd)
28-E
Demand: E
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55', NY - 68' 9.14 9.82 99%
12% HR - 55', NY - 68' 9.01 9.82 143%
10% HR - 55', NY - 68' 8.93 9.82 184%
7.5% HR - 55', NY - 68', 8.83 9.82 220%B - 45'
Breakeven Capital Cost for HR - 55', NY - 68' = 31.7%
28-F
Demand: F
Cost/Ton
Capital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55', NYC - 68', 9.20 10.22 142%B - 45'
12% HR - 55', NYC - 68', 9.05 10.22 170%B - 50'
10% HR - 55', NYC - 68', 8.95 10.22 218%B - 50'
7.5% HR - 55', NYC - 68', 8.82 10.22 307%B - 50'
-73-
Breakeven Capital Cost for HR - 55', NYC - 68', B - 50' 34.8%
Table 28(contd)
28-G
Demand: G
Cost/TonCapital Dredging With Without InvestmentCost Decisions Dredging Dredging Range
15% HR - 55', NYC - 68', 9.43 10.43 130%B - 50'
12% HR - 55', NYC - 68' 9.28 10.43 130%B - 50', M - 55'
10% HR - 55', NYC - 68' 9.15 10.43 172%B - 50', M - 55'
7.5% HR - 55', NYC - 68', 8.98 10.43 250%B - 50', M - 55'
Breakeven Capital Cost for HR - 55', NYC - 68'M - 55', B - 50' = 30.0%
-74-
Table 29
Dredging Solutions Under Various Transportation Cost Savingsfor the Port of New York Over Hampton Roads
Assumptions:
Demand = A
15%
12%
10%
7.5%
Demand = B
15%
12%
10%
7.5%
Demand = C
15%
12%
10%
7.5%
Demand = D
15%
12%
10%
7.5%
- Transportation Savings = "Medi
- Include Port of New York
Port of New York Transportation Savings
Save Save Save0 $.50/Ton tl.00Ton
HR
HR
HR
NO DRE
HR
HR
HR
HR
HR
HR
HR
HR
HR
HR
HR
HR
Both
Both
NY
HR
HR
HR
HR
HR
HR
HR
Bot
Bot]
Bot
Bot)Both
DGING
NYC
HR
HR
NY
NY
Both
Both
HR
Both
Both
Both
h Both
h Both
h Both
h Both
.um"
Over Hampton Roads
Save$2.00/Ton
NY
NY
NY
Both
NY
NY
Both
Both
Both
Both
Both
Both
Both
Both
Both
Both
-75-
Save
4 .00/Ton
NY
NY
NY
Both
NY
NY
Both
Both
Both
Both
Both
Both
Both
Both
Both
Both
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-76-
References
Akinc, U. and B. Khumawala, "An Efficient Branch and Bound Algorithm for theCapacitated Warehouse Location Problem," Management Science, Vol. 23,No. 6 (February, 1977), pp. 585-594.
Coal Week International, January 12, 1983.
"Commission Releases Dravo Report Which Reviews Coal Port," WW/S WorldPorts, April/May, 1982.
Dunbar, Frederick, "The Coal Boom: Will it Last?," WWS/World Ports,
April/May, 1982, pp. 41-44.
Evered, J. Erich, "Statement Before the U.S. House Committee on MerchantMarine and Fisheries," Subcommittee on Merchant Marine, April 21, 1983.
"For Coal the Recovery is Heating Up Slowly", Business Week, August 1, 1983,pp. 89-90.
Geoffrion, A. and R. McBride, "Lagrangean Relaxation Applied to CapacitatedFacility Location Problems," AIIE Transactions, Vol. 10, No. 1 (March,1978), pp. 40-47.
Greer, Boyce I., The Effect of Port User Fees on U.S. Coal Exports, #E-83-04(Cambridge, MA: Energy and Environmental Policy Center, JFK School ofGovernment, Harvard University, March, 1983).
H. P. Drewry, Ltd., Ocean Shipping of Coal: See Transportation Methods,Constraints and Costs, (London: HPD Shipping Publications, 1981).
ICF, Inc., Potential Role of Appalachian Producers in the Steam Coal ExportMarket: Task #1 - International Steam Coal Trade Analysis preparedfor the Appalachian Regional Commission, November, 1981.
ICF, Inc. and J. P. Coal Associates, Market Guide for Steam Coal Exportsfrom Appalachian, prepared for the Appalachian Regional Commission,March, 162.
International Coal Review, National Coal Association, February 12, 1982.
Long, R. A., Contraints on International Trade in Coal, Draft ReportNo. G3/92 (London: IEA Coal Research, May, 1982).
Madison, Christopher, "Money for Deeper U.S. Coal Ports - Needed or JustMore Pork Barrel," National Journal, February 7, 1981, pp. 225-228.
Merrow, Edward W., Stephen W. Chapel, and Christopher Worthing, A Review ofCost Estimation in New Technologies: Implications for Energy ProcessPlants, #R-2483-DOW (Santa Monica, Cal.: The Rand Corporation, July,1979).
-77-
---- ��------�--�--------
Ill
References(contd.)
National Coal Association, NCA News Release of June 25, 1982.
New York City and New York Port Authority, discussions with variousofficials in the spring and summer of 1982.
R. S. Platou, various slides and discussions at MIT in 1982.
Royal Dutch Shell, Telexes of May 6 and June 5, 1982 and discussions inLondon in June, 1982.
U.S. Congress, House, Port Development, 97th Congress, 2nd Session, Report97-454, Part I (Washington, D.C.: House Committee on Merchant Marineand Fisheries, March 9, 1982).
U.S. Congress, Senate, National Harbors Improvement and Maintenance Act of1981, Report of the Committee on Environment and Public Works, 97thCongress, 1st Session, Calendar No. 418, Report No. 97-301 (Washington,D.C.: Government Printing Office, 1981).
U.S. Corps of Engineers, discussions with officials at district offices forBaltimore, Mobile, New Orleans, and Norfolk-Hampton Roads in the Springand Summer of 1982.
U.S. Department of Energy, Energy Information Administrations, CoalDistribution: January-December, 1981, #DOE/ETA-0125(81/4Q) (Washington,D.C.: Energy Information Administration, April, 1982).
U.S. Department of Energy, Energy Information Administrations, Office ofCoal, Nuclear, Electric and Alternate Fuels, Port Deepening and UserFees: Impact on U.S. Coal Exports, #DOE/EIA-0400 (Washington, D.C.:Energy Information Administration, May, 1983).
U.S. Department of Energy, Energy Information Administration, Office of CoalNuclear, Electric and Alternate Fuels, Quarterly Coal Report:January-March, 1982, #DOE/EIA-0121 (82/1Q) (Washington, D.C.: EnergyInformation Administration, August, 1982).
U.S. Department of Energy, Energy Information Administration, Office ofCoal, Nuclear, Electric and Alternate Fuels, personal discussion withMs. Mary Hutlzer, head of Data Analysis and Forecasting Branch on.January 13, 1983.
U.S. Department of Energy, Energy Information Administration, Office ofCoal, Nuclear, Electric, and Other Fuels, U.S. Coal Exports:Projections and Documentation, #DOE/EIA-0317 (Washington, D.C.: EnergyInformation Administration, March, 1982).
U.S. Department of Energy, Interagency Coal Export Task Force, (Draft)Interim Report of the Interagency Coal Export Task Force, January,1981. (Also known as the "ICE Report .)
-78-
References(contd.)
U.S. General General Accounting Office, Prospects for Long-Term Steam CoalExports to European and Pacific Rim Markets, #GAO/NSIAD-83-08(Washington, D.C., General Accounting Office, August 4, 1983).
U.S. Maritime Administration, "Loading Terminals: Existing and Potential,"WWS/World Ports, April/May 1982, pp. 61-65.
"Unveil Coal Industry Plan Which May End Impasse Over Port User Fees,"WWS/World Ports, April/May, 1982, p. 49.
U.S. Office of Technology Assessment, Coal Exports and Port Development: ATechnical Memorandum, (Washington, D.C.: Government Printing Office,April, 981).
Waters, W. G., II, "Transportation and Market Prospects in the World CoalTrade," The Logistics and Transportation Review, Vol. 18, No. 2 (1982),pp. 139-167.
World Coal Study, Coal-Bridge to the Future (Cambridge Mass: Ballinger,1980). (1980A).
World Coal Study, Fugure Coal Propects: Country and Regional Assessments(Cambridge, Mass: Ballionger, 1980).(1980B).
-79-
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