Commercial profitability of offshore sand and gravel mining in southern California an analysis for new entries

[From the U.S. Government Printing Office, www.gpo.gov]

Commercial Profitability of Offshore Sand
and Gravel Mining in Southern California:
An Analysis For New Entries

by:

Massoud Mokhtari-Saghafi

and

Robert H. Osborne

USC-SG-R-06-81

SEA GRANT
REPRINT
SERIES

TN te for Mar1ne and Coastal Studies
291.5
University of Southern California
Los Angeles, California 90007
1980

Commercial Profitability of Offshore Sand
and Gravel Mining in Southern California:
An Analysis For New Entries

by:

Massoud Mokhtari-Saghafi

and

Robert H. Osborne

U11
USC-SG-R-06-81

This work is a result of research sponsored by NOAA Office of
Sea Grant, Department of Commerce; the Department of Boating
and.Waterways, State of California; and the California State
Lands Division.

This document was originally published in Oceans''80 by Murray
Publishing Co., Seattle, Washington.

It 'is reprinted with permission by:

Institute for Marine and Coastal Studies
University of Southern California
University Park
Los Angeles, CA 90007

COMMERCIAL PROFITABILITY OF OFFSHORE SAND AND GRAVEL MINING IN SOUTHERN CALIFORNIA:
AN ANALYSIS FOR NEW ENTRIES

Massoud Mokhtari-Saghafil and Robert H. Osborne 2

iDepartment of Economics and 2Department of Geological Sciences
University of Southern California
Los Angeles, CA 90007

ABSTRACT 2. SAND AND GRAVEL MARKET

Sand and gravel are primary resources used in many In general, the demand for sand and gravel depends
phases of construction and to maintain southern on the level of construction activity. Such acti-
California's valuable beaches and harbors. Depo- vity follows a seasonal pattern and so does the
sits of aleable-grade material under present poli- demand for sand and gravel, which peaks in summer
tical and economic conditions are becoming depleted. and declines in winter. Nearly 98% of the aggre-
Although many land-based deposits are lost to com- gate material used in southern California is con-
peting land uses and mining of such deposits is sumed by the construction industry.
generally opposed by urban communities, offshore
mining of sand and gravel for use as construction Due to the high unit storage cost, production of
aggregate is below the current rate of market sand and gravel is geared to match the demand, and
interest (10%). The reduced profitability of off- the market for this commodity is normally near the
shore mining is chiefly due to high initial capital equilibrium at the given price level. The total
outlay and relatively high operating costs. Invest- available reserves of material in the major produc-
ment in land-based deposits may be profitable under tion districts currently supplying Los Angeles
specified conditions. County is estimated to be approximately 620 x 106
tons. Average annual demand is estimated to be
approximately 21 x 106 tons. 1 Thus under the
current market conditions, known reserves will be
1. INTRODUCTION exhausted in 30 years.

In southern California, commercial sand and gravel The market price of sand and gravel has been rising
is produced entirely by open-pit mining of onshore continuously through time; however, the real price
alluvial deposits. The requisite technology is has had sluggish upward or even downward movements.
well known to the industry. In recent years, The market price in 1978 was over 111% higher than
increased socio-economic pressures have been the 1965 level, but the real price had increased
imposed on producers in some areas, e.g. in Los by only 3.2% in the same period. Table 1 presents
Angeles County. The high rate of urbanization, the consumption, market price, and real price of
limited reserves and increased operating costs as sand and gravel in the Los Angeles area.
well as social and environmental concerns have
encouraged some producers to seek new deposits for Transferring the material from the plant site to
future exploitation. Commercial mining of offshore the consumption area is an important part of the
sand and gravel deposits for construction aggregate marketing strategy. Transportation is normally
has been regarded as a possible alternative source done by trucks and trailers with a 25 ton average
for this commodity. capacity. Minimum transportation rates are set by
the Public Utility Commission on a zone to zone
The following research was conducted to evaluate basis -- Tariff 17A * The rate for a 25 mile dis-
the economic feasibility of mining offshore sand tance is $2.03 and for a 40 mile haul rises to
and gravel deposits in southern California, parti- $3.08 per ton. High unit weight, limited 'capa-
cularly in Santa Monica Bay. city and high transportation rate affects the pro-
ducer's choice of locations.
First, a brief description of the sand and gravel
market in southern California and Los Angeles 3. ECONOMIC MODELING: FIRST APPROXIMATION
County will be presented. Secondly, a conventional
onshore model will be discussed, and the rate of Suppose an entreprenure is considering (1) whether
return in such a model will be estimated. Finally, to invest in the sand and gravel production market;
the offshore mining case will be considered and and (2) if the answer is affirmative, whether to
compared to the onshore one. invest in an onshore or offshore mining operation.
The following economic models are offered for con-
sideration.

0197-7385180/0000-0055$00.75 9 1980 IEEE

Table 1. Aggregate Sales, Market and Constant Offshore Case: Santa Monica Bay Model I
1978 Prices of Sand and Gravel
Los Angeles County Santa Monica Bay deposits have several economic
ONS PRICES IN DOLLARS PER TON advantages which make this an area worthy of
YEAR MILLIONS OF T modeling (Fig. 1).
1965 CONSUMPTION* NOMINAL" CONSTANT 178' 1) Large deposits of sand and gravel occur in the
25.3 1.09 2.23 offshore area from Kings Harbor to Santa Monica.
1966 26.2 1.12 2.23 An offshore deposit extending from Marina del Re
1967 22.2 1.12 2.17 y
1968 23.7 1.24 2.29 to the Santa Monica pier contains from 18 x 106 d3
1969 22.9 1.10 1.96 to 66 x 106 yd3 of sand and gravel, of which
approximately 72% is suitable for construction
aggregate. Collectively, other deposits contain
1970 26.2 1.25 2.08 from 99 x 106 yd3 to 214 x 106 yd3 of dominant
1971 21.7 1.32 2.10 sand, of which 80% is suitable or marginally suit-
1972 21.3 1.37 2.08 able for beach restoration and nourishment.2, 3, 4
1973 22.2 1.49 2.14 2) The deposits are close to shore, which reduces
1974 21.6 1.63 2.14
the transporting cost and capital outlay reqi
1975 19.1 1.79 2.14 ment. 3) Water depth in this area is relatively
1976 21.1 2.09 2.38 low ( 5 to 15 fathoms), which decreases the ini-
1977 21.4 2.20 2.36 tial capital outlay requirement. 4)'The quali
ity
1978 21.6 2.30 2.30 of the material reduces the operating costs of
mining and production. 5) The district is close
*Source: U.S. Bureau of Mines to Los Angeles County markets, and is particularly
close to Los Angeles city markets. This provides
**Source: 1965-1973, California Division of mines producers some price advantages over operations
tComputed based on the general price level data located farther from these markets.
from "Statistical Abstract of the U.S.," Depart- The level of production and work schedule is
ment of Commerce, 1962-1979 Volumes.
1974-1978 estimates based on the U.S. Bureau of assumed to be the same as in the onshore case .
The desired combination of sand and gravel is
Mines Publications and on industry survey. assumed to be 45% and 55% respectively. The depo-
sits have been estimated to carry 65% sand and 35%
Onshore Model I gravel and the maximum dredging depth is assumed
to be 15 fathoms.
An average producer in Los Angeles County produces Dredging should vary between 1,200 and 1,600 tons/h
from 1.5 to 2 million tons of aggregate per annum. to satisfy 1.5 to 2.0 ton annual production.
Here, we consider both production levels. The work Dredging is done by a hopper dredge, equipped with
schedule is assumed to be 8 h/day, 5 days a week, a 22 in diameter pipe. The horse power required
and 50 weeks a year. If 90% of the material is for the dredging is about 2,000 bhp. The material
usable as final product, a maximum of 160 tons/h is transferred to-shore using barge's equipped with
should be mined to satisfy the maximum production
of 1,000 tons/h. A 6 yd3 bucket size electrical self-discharging facilities. The distance to shore
shovel and a dragline are used for mining. Trucks is about 4 mi and each round trip takes a maximum
and belt conveyors transfer material to the plant of 60 min. For a continuous production, three
for further processing. The total capital outlay barges with the total capacity of 2,500 tons are
for such a plant and equipment is estimated to be required. A belt conveyor transfers the material
approximately 8.95 million dollars invested as a over the 0.2 mi distance 'from the shore to the
plant for normal processing and stockpiling. The
lump sum in the beginning of the project. The total capital outlay for such equipment and normal
lifetime of the equipment is taken to be 20 years. size plant is estimated to be about $14.8 million
Depreciation is computed on a straight line basis invested as a lump sum in the beginning of the
and the scrap value of equipment is zero at the project. The operating cost is estimated to b
end of the twentieth year. A 55% tax rate on the e
net taxable income is imposed by the federal, state about $2.00/ton. Under the same market conditions
and local authorities. F.O.B. price of sand and as in the onshore model, rate of return will vary
gravel is estimated to be about $2.60/ton.5 from 1.9% to 3.85% depending on the annual produc-
Under the above conditions, the operating cost is tion level of 1.5 to 2 million tons.5
estimated to be about $1.75 per ton/year, and the 4. ECONOMIC MODELING: SECOND APPROXIMATION
gross operating income remains the same for twenty In the previous models for onshore and offshore
years. Operating costs include labor, energy, Sup- production, it was assumed that the operating
plies and maintenance, insurance, total taxes and income (price less operating cost)remains constant
royalties. The internal rate of return for the throughout the length of the project. In this
1.5 million ton annual production case is 7.9%, and part, this assumption is modified by allowing both
for the two million ton annual production case is pric.e and operating cost to change from year to
10.9% year.

SAN
SAN GABRIEL
FERNANDO MOUNTAINS
.50 VALLEY
... ...... @WERDUGO SAN
k@OUNTAINS
RAFAEL
HILLS
SANTA MONICA MOUNTAINS PUENTE
ELYSIAN HILLS
Pt HILLS
Dume. Sant@
LOS
SANTA 'Mon1co
90M MONICA ANGELES
SHELF BASIN

SANTA '. 'Manhattan
MONICA SHELF Beach
CANYON PROJECT N
0/ ok
REDONDO PAL S
PLATFORM E ES
H LLS.:-:-..--.
REDONDO
CANYON

0
N SAN
PEDRO
0 5 10 SHELF

Kilomete S

Figure 1. Location map showing the bathymetry and physiography of the study area. Note position of
depth contours.

The price of sand and gravel is assumed to be Table 2 represents our predictions or price and
governed by the following equation: operating costs for the next 20 years.
(1) Pt = Aeat(Pt_j)@
or taking the logarithm of both sides: Rates of Return for Onshore and Offshore Models II
(2) Ln(Pt) = a + at + @Ln(Pt_j)
where P is the price level of sand and gravel, and Given all the conditions described in the onshore
a, a, and @ are the parameters-of the equation that model 1, with the new price and operating cost
should be estimated, and t represents the time estimates, the internal rate of return for the 1.5
indicator. million ton production would be approximately 10%
and for the 2 million ton production case it would
The ordinary least square method was employed to reach the 12.5% level.
estimate the coefficients. The price equation then
can be written as: Under the same conditions specified for the off-
(3) Ln(Pt) = -0.0478 + 0.0308t + 0.586lLn(Pt-1) shore model I with the new price and operating
or: cost levels, the internal rates of return are 4.2%
(4) Pt = 0.9533eo.0308t(pt-1)0.5861 and 6.7% for the 1.5 and 2.0 million tons of pro-
R2 for the equation is 0.9. Data for the period duction respectively.
from 1965 to 1979 was used to estimate the coef-
ficients. 5. PROJECT EVALUATION

Using equations (3) or (4), the price of sand and We started the modeling procedures by putting the
gravel was forecast for the future. The base year entrepreneur in a decision making position facing
for this forecast is 1981. The price of sand and two questions: 1) whether to invest in the sand
gravel was estimated to reach $2.60/ton in 1980. and gravel production market, 2) if yes, which one
The operating cost for the onshore case was esti- to choose, onshore or offshore.
mated to reach $1.75/ton and for the offshore case
to be $2.00/ton in 1980. The answer to (2) is simple. As the study shows,
in all cases, rates of return for onshore models
Operating cost was assumed to increase at a rate are greater than for offshore models. This obvi-
approximately equal to the rate of inflation of ously implies that onshore mining has comparative
the producers price index. This rate was esti- economic advantages to offshore production, and
mated to average 7%/annum. therefore is more profitable. The answer to the
first question is not as clear as the second.
Rates of return, which were referred to in this

Table 2. Price and Cost Predictions Table 3. Project Evaluation and Summary-
PRICE OPERATING COST OPERATING COST Production Rate Project Evaluation:
YEAR LEVEL ONSHORE - $/TON OFFSHORE - $/TON Models 106 of Rejected (R), Accepted
Tons/Year Return (A), Accepted with Low
1980 2.60 1.75 2.00 % Risk (A*)
1981 2.65 1.87 2.14
1982 @.74 2.00 2.28 Onshore 1.5 7.9 R R R R R
1983 2.86 2.14 2.45 1 2.0 10.9 A A A A A
1984 3.03 2.28 2.62 Onshore 1.5 10.0 A A A A* R
1985 3.23 2.45 2.80 11 2.0 12.5 A A A A A
1986 3.45 2.62 3.00
1987 3.70 2.80 3.21 Offshore 1.5 1.9 R R R R R
1988 3.97 3.00 3.43 1 2.0 3.9 R R R R R
1989 4.26 3.21 3.68
Offshore 1.5 4.2 R R R R R
1990 4.66 3.43 3.93 11 2.0 6.7 R R R R R
1991 4.96 3.68 4.20
1992 5.30 3.93 4.50 Interest
1993 5.68 4.20 4.82 Rate
1994 6.09 4.50 5.16 Low- 8.75 9.25 10.55
Average- <_ _* *_ 4.
1995 6.55 4.82 5.52 High Low Average High
1996 7.02 5.16 5.90
1997 7.54 5.52 6.30
1998 8.08 5.90 6.76 5. CONCLUSIONS
1999 8.59 6.30 7.23
The results of this study indicate that although
2000 9.30 6.76 7.73 investment in an onshore sand and gravel operation
might be economically advisable under certain con-
ditions, high initial capital outlay and relatively
paper and which were calculated for different high operating costs argue against offshore mining
models and under different assumptions, are for construction aggregate under present economic
basically rates at which the discounted future conditions. Utilization of known reserves, socio-
income stream of a project equals its cost. This economic conditions and changing environmental
rate alone has little practical significance for attitudes may make offshore production for con-
an entrepreneur unless it is compared to some struction aggregate more attractive in the future.
other economic indicators. The reason is that the
investor not only wants to know if a certain pro- 6. REFERENCES
ject is profitable in absolute terms, but also
wants to find out if it is profitable relative to 1. Evans, J. R., Anderson, T. P., Manson, M. W.,
other investment opportunities available to him. Maud, R. L., Clark, W. B., and Fife, D. L., Aggre-
gate in the Greater Los Angeles Area, California,
The indicator used in cost-benefit analysis is California State Division of Mines and Geology
the expected future rate of interest. If the Special Report 139, 1979, 96 p.
rate of return of a project is higher than the
expected future rate of interest, the project is 2. Osborne, R. H., Scheidemann, R. C., Jr.,
economically profitable and should be chosen. Nardin, T. R., Harper, A. S., Brodersen, K. L,
Hence, an important step in the evaluation of a Kabakoff, J., and Waldron, J. M., Potential sand
project is to estimate this rate. In this study, and gravel resources in Santa Monica and San Pedro
the following steps were taken to accurately Bays, southern California: IEEE Proc. Vol., Oceans
estimate this rate: 1) A lower bound, and upper '79, San Diego, 1979, p. 590-597.
bound and a mid-range value for the money market
interest rate were defined. 2) using the time 3. Osborne, R. H., Scheidemann, R. C., Jr.,
series data, and models similar to equation (1), Nardin, T. R., and Harper, A. S., Quaternary stra-
the future trends of the low, middle, and high tigraphy and depositional environments, Santa
values for the interest rate were forecast. Monica Bay, southern California, in Field, M. E.,
3) Using the forecasted values, the average Bouma, A. H, Colburn, I. P., Doug-las, R. G., and
expected future low, middle, and high values of Ingle, J. C., eds., Quaternary depositional envi-
the interest rate were computed. These values ronments 'of the Pacific coast: Pacific Section,
are: low - 8.73%; middle - 9.28%; and high - S.E.P.M., Los Angeles, California, 1980, p. 143-
10.55%. Allowing 0.5% for estimation and/or cal- 156.
culation error, the average expected rate of
interest is approximately 10%. Having the rates 4. Osborne, R. H., Scheidemann, R. C., Jr.,
of return and the expected rate of interest Nardin, T. R., Harper, A. S., Brodersen, K. L.,
permits one to address question (1). Table 3 Kabakoff, J., and Waldron, J. M., Occurrence and
summerizes our analyses. sedimentological characteristics of offshore sand

and gravel bodies in Santa Monica and San Pedro
Bays, and their suitability as a source of mate-
rial for beach nourishment and construction aggre-'
gate: Univ. Southern California Sea Grant Publi-
cation, in preparation.

5. Saghafi, Massoud, and Osborne, R. H., An eco-
nomic appraisal of mining offshore sand and gravel
deposits, Santa Monica Bay, southern California:
Univ. Southern California Sea Grant Publication,
in press.

This work is a result of research sponsored by NOAA
Office of Sea Grant, Department of Commerce; the
Department of Boating and Waterways, State of
California; and the California State Lands
Division.

Reprinted from OCEANS '80, an international forum on Ocean engineering in the '80s.

Printed by Murray Publishing Co. Seattle, Washington

OAA COASTAL SERVICES CTR LIBRARY

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