
Fall 1994
U.S. Department of Energy
Bioenergy Feedstock Development Program at
Oak Ridge National Laboratory
Energy Crops Forum was published periodically by the Bioenergy
Feedstock Development Program, Environmental Sciences Division, Oak Ridge
National Laboratory, managed by UT-Battelle, LLC., for the U.S. Department of
Energy under Contract No. DE-AC05-00OR22725.

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Table of Contents

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Marie Walsh, BFDP
Farmers, policymakers, and chemical and electrical companies are increasingly
interested in biomass energy systems due to the many air, soil, and water
quality benefits they offer. New policies to encourage biomass
commercialization and decisions to use or produce biomass will depend on its
economic competitiveness relative to other energy supplies. A major determinant
of competitiveness is the cost of producing the energy crop.
We have estimated switchgrass production costs in the Lake States (Michigan,
Minnesota, Wisconsin); Corn Belt (Iowa, Illinois, Indiana, Missouri, Ohio);
Southeast (Alabama, Georgia, South Carolina); Appalachia (Kentucky, North
Carolina, Tennessee, Virginia, West Virginia); North Plains (Kansas, Nebraska,
North Dakota, South Dakota); and South Plains (Oklahoma, Texas). These regions
correspond to the U.S. Department of Agriculture, Economic Research Service
major crop production regions. Switchgrass can be grown in other states as
well.
Switchgrass is not produced currently for commercial sale; historical production
cost data are not available. Production costs estimated in the analysis are
based on assumptions regarding likely management practices. Machinery
specifications are used to calculate the number of hours required for each
production operation. Costs per acre are calculated by multiplying the per-hour
machinery costs by the number of hours in operation. All input costs are in
1993 dollars.
The analysis does not include transportation costs from the site of production
to the end user. These costs are expected to be about $0.10 per dry ton per
mile for hauling distances of less than 50 miles.
Variable cash costs of production are presented in Table 1. Variable cash costs
are the out-of-pocket expenses of production and include expenditures for
seeds, fertilizers, chemicals, twine, machinery repair, and fuel and
lubrication. For short-run farmer decisions regarding which crop to plant each
year, variable cash costs are the most relevant costs.
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Table 1: Summary of Variable Cash Costs of Producing Switchgrass by Region
($/ac, $/dry ton, $/MBtu)* |
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Expected Range
of Yields
(dry tons/ac/yr) |
Estimated Average
Production Cost
($/ac) |
Estimated Costs
($/dry ton) |
Estimated Costs
($/MBtu)** |
| Lake States |
3-5
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51-58 |
17-12
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1.17-0.80 |
| Corn Belt |
5-7 |
57-67
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11-10
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0.80-0.66 |
| Southeast
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6-9 |
67-84 |
11-9 |
0.77-0.64 |
| Appalachia |
3-6 |
56-64 |
19-11 |
1.29-0.73 |
| North Plains |
3-6 |
43-65 |
14-11 |
1.00-0.74 |
| South Plains
|
4-7 |
62-80 |
16-11 |
1.08-0.79 |
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* The first number in each range corresponds to the lowest yield.
** Switchgrass is assumed to contain 14.5 MBtu per dry ton.
Full economic costs of production are provided in Table 2. Economic costs
include fixed cash costs (e.g., overhead costs associated with farm
maintenance, taxes and insurance, real estate interest costs, etc.) and the
opportunity costs of owned resources (e.g., depreciation on farm equipment, the
value of the producer's labor, the value of land, etc.), as well as the
variable cash costs. Economic costs are important for policy analysis and are
important considerations for the survivability and long-term potential of the
farm operation and the quality of life of the farm operator.
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Table 2: Summary of Full Economic Costs of Producing Switchgrass by Region
($/ac, $/dry ton, $/MBtu)* |
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Range of
Expected Yields
(dry tons/ac/yr) |
Estimated Average
Production Cost
($/ac) |
Estimated Costs
($/dry ton) |
Estimated Costs
($/MBtu)** |
| Lake States |
3-5
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187-200 |
62-40 |
4.29-2.74 |
| Corn Belt |
5-7 |
234-256 |
47-37 |
3.23-2.52 |
| Southeast
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6-9 |
169-206 |
28-23 |
1.94-1.58 |
| Appalachia |
3-6 |
162-175 |
54-29 |
3.73-2.03 |
| North Plains |
3-6 |
169-228 |
56-38 |
3.89-2.62 |
| South Plains
|
4-7 |
146-176 |
36-25 |
2.52-1.73 |
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* The first number in each range corresponds to the lowest yield.
** Switchgrass is assumed to contain 14.5 MBtu per dry ton.
Switchgrass is a perennial and, once established, can remain productive for many
years. The analysis assumes that switchgrass stands remain in production for 10
years. Establishment costs are annualized over the 10-year stand life using a
7.5 percent discount rate.
The analysis also assumes that switchgrass is produced by individual farm
operators who own the necessary equipment. Costs are estimated for two
different machinery complements a large-scale and a small-scale complement
typically associated with larger and smaller farms. The costs shown in Tables 1
and 2 are averages of the two estimates. If farm operators do not own haying
equipment (i.e., mowers, rakes, balers) and must rely on custom harvesting,
costs will be higher.
In the analysis, fields are prepared for planting by plowing and disking. Weed
control is important for establishment; herbicide applications are included.
Phosphorous, potassium, and lime are added as needed before planting; levels
assumed in the analysis are typical of those used for other crops in the
region.
In the years following establishment, nitrogen fertilizer is applied in
quantities sufficient to replace that removed as a result of harvesting;
quantity applied is generally about 0.5
Only one harvest per year is assumed. Harvest costs are adjusted for yield. As
yields increase, the per acre harvesting cost correspondingly increases, but
the per ton harvesting cost decreases.
The yields used in the analysis are based on research plot data and expert
opinion. Yields are expected to be low during the establishment year, increase
during years 2 and 3, and maintain a relatively constant annual yield in years
4 through 10. Harvesting losses of about 5 to 7 percent of growth have been
included in the analysis. Long-term storage losses, expected to be about 10 to
13 percent for bales stored outside on the ground, are not included in the
analysis.
Production costs for each farm operation will vary from these estimated costs
depending on local conditions and management practices. However, the estimated
production costs provide a basis for analyzing the regional costs and
profitability of switchgrass production in the United States. The complete
study, with documentation of data and methodology, will be published as an ORNL
report some time in 1995.
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Victor D. Phillips, Wei Liu, and Robert A. Merriam; College of Tropical
Agriculture and Human Resources, University of Hawaii at Manoa, Honolulu, HI
96822
A research team in the College of Tropical Agriculture and Human Resources at
the University of Hawaii at Manoa has developed a decision support system for
those interested in short-rotation, intensive-culture (SRIC) forestry on former
sugarcane and pineapple plantation lands to produce a variety of wood products,
including renewable biofuels. The system has three integrated components: (1)
empirical SRIC yield models of promising tropical hardwoods (Eucalyptus spp.)
that were constructed using growth data, site characteristics, and management
variables from field trials in Hawaii; (2) a SRIC biomass system model of
production costs, including establishment, maintenance, harvesting, transport,
and storage; and (3) a geographical information system to extend the analysis
to areas where no field trials exist and to present the results as a map. Our
system can predict the potential biomass supply (dry ton) and delivered cost
($/dry ton) of Eucalyptus spp. at potentially available locations for tree
plantations on both an island-wide scale for general land-use planning and a
specific-site scale for field-level recommendations.
The Hilo coast plantations that were modeled could provide more than 1.8 million
dry tons over 7 years; most of the feedstock would cost under $36/dry ton.
Using an optimized SRIC management strategy that recommends a planting density
of 578 trees/acre and 7 years of age at harvest, the average cost of chips
delivered to the Pepeekeo factory is $36/dry ton. The least-cost production
target is the minimum delivered cost of E. saligna from the Hilo coast
plantation to the bioconversion facility achieved by optimizing growing space
and rotation age. A prediction of the potential biomass supply of E. saligna
from the Hilo coast indicates that 220,000 dry tons/year could be produced at
$36/dry ton. Sensitivity analyses revealed that delivered cost is affected
mostly by biomass yield and harvesting costs.
These results were then used with specific bioconversion processes for
estimating the costs of manufacturing energy products at a plant capacity of 25
million gallons/year for ethanol and methanol fuels and 25 MWe for electricity.
Calculations for ethanol production were based on a simultaneous
saccharification and fermentation system that would produce 100 gallons
ethanol/dry ton and would require approximately 245,000 dry tons of feedstock
annually. Calculations for methanol production were based on a low-pressure
indirect gasifier with hot-gas conditioning and methanol synthesis that would
provide 86 gallons methanol/dry ton and would require approximately 148,000 dry
tons of feedstock annually. Electricity calculations were based on a fixed-bed
gasifier coupled to an open-cycle turbine that would generate 393 kWh/dry ton
feedstock and would require approximately 110,000 dry tons of feedstock
annually.
Preliminary levelized cost estimates are $1.21/gallon for ethanol, $0.80/gallon
for methanol, and $0.071/kWh for electricity. For comparison, the prices of the
current sources of energy in Hawaii are roughly $1.51/gallon for unleaded
regular gasoline and $0.10 0.12/kWh for electricity generated by burning
residual fuel oil, which fluctuates between $15 20/barrel.
In Hawaii, the SRIC biomass system model can reliably estimate yield and
optimized economic costs of tropical hardwood production at the state, county
(island), and plantation (field) levels. The decision-support tools and
information are useful to land owners and decision-makers in evaluating the
economic viability of short-rotation forestry in Hawaii, including growing
biomass crops for manufacturing energy products. This methodology is readily
transferable to other areas of the United States and to the rest of the world.
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Nathan Rice; University of Wisconsin, Stevens Point
In July 1994, Audubon ornithologist Wayne Hoffman and I conducted the second of
two bird surveys for the BFDP in switchgrass plantings near Centerville, Iowa.
The study site contains nearly 400 acres of switchgrass. It is owned by the
Iowa Department of Natural Resources and is managed as public hunting land.
Seven fields on this site were separated into two survey areas. Area one
included a newly planted switchgrass field (points 1 and 2), a switchgrass
field planted in 1993 (points 3 and 4), and a switchgrass planting harvested in
1993 (points 5-8). Vegetation at points 1 and 2 was approximately 2 feet high
and contained 90% switchgrass stems. Weeds grew where switchgrass had not
established. Common yellowthroats were the most commonly observed bird in this
area, although the number of birds detected was low.
At points 3 and 4 the vegetation was more than 3 feet tall and was again mainly
switchgrass. Dickcissels, common yellowthroats, and a few grasshopper sparrows
were observed. Points 5-8 contained little switchgrass. Only 30% of the area,
typically lowland, had vigorously growing switchgrass; the majority of the site
had been invaded by weeds. This area had the highest singing male densities of
dickcissels and grasshopper sparrows.
Points 1 and 2 in the second study area were located in a field planted with big
bluestem and switchgrass. Vegetation height ranged from 2-4 feet. Sedge wrens,
common yellowthroats, and dickcissels were common at these points. Points 3 and
4 were planted with switchgrass on upland areas and orchard grass in lower
areas. The switchgrass was approximately 3 feet high. Flocks of more than 100
red-winged blackbirds were sighted at these points along with numerous
forest-edge species (northern cardinal, gray catbird, and brown thrasher). The
third field (points 5-7) had been planted in 1993 with switchgrass that was now
more than 4 feet high. Sedge wrens, dickcissels, and red-winged blackbirds were
the most abundant birds at these points. Points 8 and 9 were located near a
small stand of trees and the previously mentioned switchgrass field. Forest
birds (northern cardinal, northern oriole, black-capped chickadee, house wren,
and downy woodpecker) were common at these points.
Sedge wrens and grasshopper sparrows should be considered as indicators of
habitat quality when evaluating the habitat value of herbaceous energy crops.
Sedge wrens preferred lush, dense, lowland switchgrass sites while the
grasshopper sparrows tended to inhabit drier, upland sites. Both species are in
decline and their presence in switchgrass plantings is an indication that
herbaceous energy crops can potentially provide usable habitat for wildlife.
Information gained from these surveys has highlighted areas in need of further
study and has provided baseline data for comparison with scale-up projects. In
all cases, breeding grassland bird densities were higher in 1994 than in 1993.
This is most likely a function of the weather and the age and size of the
grass. More research is needed on larger, more intensively managed switchgrass
fields. Research should also be considered on multiple species plantings and
grasses should also be considered.
[Editor's note: Nate was participating in the Science and Engineering Research
Semester at ORNL. Contact the Oak Ridge Institute for Science and Education at
P.O. 117, Oak Ridge, Tennessee 37831-0117, 865-576-3427 for information about
this program.]
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The Biofuels Feedstock Development Program (BFDP) is soliciting your advice and
suggestions about establishing a biomass job bank. We frequently receive
resumes from people seeking employment and occasional notices about employment
opportunities in biomass energy.
This situation has led us to believe that there is a need for a forum in which
to post information about biomass-related jobs and job hunters. One option is
to add a positions open section to the Biofuels Information Network's Worldwide
Web server.
BFDP is also interested in expanding the Biofuels Information Network's links to
other services on the Internet especially in the areas of agriculture,
economics, climate, utilization, environment, and policy. Please send your
suggestions and comments about either or both of these needs to bfdp@ornl.gov
or to the address listed at the end of the newsletter.
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Wright, L.L. and W.G. Hohenstein (ed.). 1994. Dedicated feedstock supply
systems: Their current status in the U.S.A. Biomass and Bioenergy:6(3).
This special issue contains articles on woody and herbaceous species under
consideration as energy crops, production technologies, environmental
considerations, land availability, and economics analyses.
U.S. Department of Energy, Biofuels System Division. 1994. Biofuels: Project
Summaries. DOE/CH10093-297. 121 pages. This report contains summary
sheets for each project funded and/or in existence during Fiscal Year 1993
(October 1, 1992 through September 30, 1993).
U.S. Department of Energy, Biofuels System Division. 1994. Biofuels: A Win-Win
Strategy. Stabilizing Global Climate Change While Acheiving a Sustainable
Energy Future. 15 pages.
Phillips, V.D., W. Liu, R.A. Merriam, and D. Singh. 1994. Potential for
short-rotation intensive-culture hardwood production in Hawaii. Agricultural
Systems 46:33-57.
Liu, W., R.A. Merriam, V.D. Phillips, and D. Singh. 1993. Estimating
short-rotation Eucalyptus saligna production in Hawaii. Bioresource
Technology 45:167-176.
Phillips, V.D., W. Liu, R.A. Merriam, and D. Singh. 1993. Biomass system model
estimates of short-rotation hardwood production in Hawaii. Biomass and Bioenergy
5(6):421-429.
Liu, W., V.D. Phillips, and D. Singh. 1992. A spatial model for the economic
evaluation of biomass production systems. Biomass and Bioenergy 3(5):345-356.
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