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Market Development Research |
Objective: Document the economic cost of establishment and management of 1870 acres of short-rotation hybrid poplar on farmer-owned Conservation Reserve Program land in Minnesota.
Approach/Background: WesMin RC&D has undertaken two main responsibilities in this scale-up effort. The first is operations management and oversight of 1870 acres of hybrid poplar plantings. The second is coordination and procurement of services, materials, and needs in establishing and maintaining these hybrid poplar plantings over a 14 county area. This effort will continue through the entire rotation length of the hybrid poplar crop.
WesMin also serves as the coordinating agency for Minnesota Department of Natural Resources, Electric Power Research Institute, US Forest Service Forestry Science Lab in Rhinelander, WI, and landowners. In this way WesMin acts by dispersing funds, and monitoring results, reporting on progress, conducting surveys, working out and refining procedural approaches, and documenting the actual cost of establishment of the hybrid poplar crop.
The project has evolved since 1994 and has documented what it takes to establish a hybrid poplar crop on CRP land. For 15 years prior to this, only smaller scale research and data were collected on experimental plantings of hybrid poplar of approximately 10 acres in size.. This larger effort documents establishment and management practices on nearly 2000 acres, 50 to 150 acres at a time.
Status/Accomplishments: As of September 1997, 1870 acres of hybrid poplar have been established within a 75 mile radius of Alexandria Minnesota. Planting was completed in two phases, one in 1994 of 1000 acres, and a second phase in 1995 of approximately 870 acres. A total of 19 landowners are currently involved, and have obtained through the Conservation Reserve Program, 5-year extensions of their CRP contracts by planting hybrid poplar. The CRP contracts will expire in 2001 when the majority of the trees are 7 years old.
There are no contracts for sale of the trees at harvest. The concept of growing wood as a cash crop in Minnesota has become more acceptable to many wood using industries in Minnesota. The wood fiber industry in Minnesota is facing reduced native Aspen stocks within the next 10 years. Two biomass to electric power proposals are being considered by Northern States Power in Minneapolis to meet Minnesota legislative mandates calling for production of 125mW of biomass power by 1998. Hybrid poplar from the Alexandria plantations could be used for this purpose.
Several other related projects outside the scope of this current project funding have been coordinated by the RC&D as well. A hybrid poplar grower’s cooperative is currently being established, water quality studies are underway that relate to planting hybrid poplar in place of agricultural crops in Minnesota. In addition, WesMin has conducted meetings and work groups and has met with local and national media in the coordination and dissemination of information concerning the scale-up effort and its participants.
Summary Date: September 1997
Objective: Evaluate available methodologies to assess the role of risk in farmer decisions to adopt new technologies.
Approach/Background: Current economic analysis of farmer adoption of bioenergy crops assumes that farmers will adopt these crops if the profit received from bioenergy crops is comparable to that which could be earned if the land were used for alternative purposes. However, bioenergy crops have different production characteristics and respond differently to weather than currently produced agricultural crops. Additionally, the markets for bioenergy crops differ from current crops resulting in prices that vary in response to a different set of factors. Thus bioenergy crops present a different risk profile than current agricultural crops. The impact that this will have on farmer decisions to adopt bioenergy crops needs to be assessed.
The project involves searching the literature for models that can be used to assess the role of risk on farmer adoption decisions. Among the methods to be examined are EV and MOTAD modeling, discrete stochastic sequential programming, and single index modeling systems (SIMS). Each methodology will be evaluated for data needs; strengths and weaknesses will be compared. Findings will be presented in a written report.
Status/Accomplishments: The literature search has begun and collection of studies utilizing each approach is underway.
Summary Date: September 1997
Objective: Respond to DOE requests for economic analysis in support of emerging analytical and policy priorities; conduct short-term analysis in support of other BFDP tasks; engage in technology transfer activities; and serve as an agricultural and economic consultant to DOE and BFDP.
Approach/Background: The focus of the task is to supply relevant economic and agricultural information on a timely basis to DOE, other BFDP activities, and to the public. Information provided takes many forms including (1) publication of technical and popular reports, (2) provision of information for fact sheets, (3) policy and project review, (4) development of spreadsheet models to support policy decisions, (5) preparation of agricultural and economic briefing papers, (6) presentations at meetings and conferences, and (7) development of a publicly-available user-friendly software program to estimate bioenergy crop production costs among others.
Status/Accomplishments: BIOCOST, a flexible user-friendly software program that estimates the cost of producing switchgrass and hybrid poplar in eight U.S. regions was released to the public. To date, 135 requests for the program have been received. Requests have come from universities, state and federal agencies, paper and pulp, environmental, energy, and agricultural companies, consulting firms, farmers, non- profit groups and several foreign countries (mainly Canada and European nations). Several journal articles, conference presentations, and other miscellaneous publications have resulted from analysis conducted.
Summary Date: August 1997
Objective: Develop a integrated, processed-based simulation model of hybrid poplar plantations. Specifically, we are integrating a physiologically-based growth model for hybrid poplar into a field-scale model of soil erosion and productivity. The combined model will allow assessment of the productivity and environmental effects of short rotation plantations under different soil and climatic regimes.
Approach/Background: There is a strong developing interest in the use of fast-growing tree species, such as hybrid poplar, as a source of wood fiber, as an alternative energy source, and in the protection and conservation of agriculturally marginal or riparian lands. Hybrid poplars, when planted on appropriate sites, are capable of very high rates of biomass production, and, consequently, short rotation times. The use of these fast growing species on agricultural sites may accommodate, in part, the increasing demands on native forests of the Midwest. It is essential to consider, however, the regional-scale environmental effects of dedicating large areas of cropland to fiber and energy production. These effects include changes in potential soil erosion, evapotranspiration, and runoff of nitrates, phosphates, and other agricultural chemicals.
Over the past three years, researchers at NRRI, in conjunction with Oak Ridge National Laboratories, the USDA Forest Service North Central Forest Experiment Station, and the Grasslands Soil and Water Research Laboratory in Temple, TX, have been developing computer simulation models to assess poplar growth and changes in soil productivity. The ultimate objective is to develop a physiologically-based growth model for hybrid poplar to incorporate into EPIC, a field-scale simulation model of crop growth and soil processes.
The model will be driven by climatic and soil conditions, but will incorporate the genetic characteristics of different poplar clones as they relate to site conditions. To evaluate the model, we are using independent data from the network of hybrid poplar plantations currently established in Minnesota, Wisconsin and Iowa.
Status/Accomplishments: The ECOPHYS poplar growth model has been fully converted into a 32-bit C++ based object-oriented model. This conversion has allowed the model to be extended in time to multiple years and in space to multiple trees. To grow a tree through several seasons, we developed routines to simulate poplar growth through its various phenological stages, from the planting of a cutting, through budbreak, growth, budset, and leaf fall. A second major advance in the program was to allow simulation of branching. Each year produces a new order of branches. The object-oriented design allowed the original, single stem, ECOPHYS tree to become a ?current terminal' on a tree with multiple branches.
While the original ECOPHYS model was an above-ground tree only, the C++ version allows the growth of roots in three-dimensional space. Roots are characterized by length, diameter, and age. They grow as a function of the amount of carbohydrates received from the upper part of the tree, and can respond to differences in soil resources. To simulate soil processes, a detailed, three-dimensional soil water transport model was developed. The soil model divides a 100 x 100 x 200 cm soil slab into variable-sized cells (1-5 cm on a side) and uses water matric potential to distribute water and nutrients between cells. The model runs on an hourly timestep and accounts for surface evaporation, capillary rise from a water table, water distribution from irrigation lines, and water uptake into a plant root system.
In addition to expanding the single-tree component of the model, the object-oriented approach has allowed us to simulate multiple trees interacting in a patch. By scaling the model to a patch, we can make predictions on how trees compete for light and soil resources, and how plantation spacing effects productivity. Currently, we are testing a new light interception routine that allows us to calculate shading to a target tree based on the growth and arrangment of neighboring trees.
To integrate the ECOPHYS model with EPIC, we are developing an interface routine which allows both models to run concurrently on a Windows 95 or NT based computer. Information on weather is passed to ECOPHYS from EPIC, and tree biomass and leaf area are passed back to EPIC from ECOPHYS. The combined model will integrate the precision of a physiological-based process model with the regional assessment capabilities of EPIC. As such, the model will be an important tool for feasibility studies and environmental assessments.
Summary Date: September 1997
Objective: Estimate the plant-gate cost of producing fuel ethanol and the share of the total fuel ethanol market supplied by corn and several cellulosic feedstocks from 2000 to 2015, assuming moderate and optimistic feedstock supply and ethanol demand quantity scenarios.
Approach/Background: As a means to decrease carbon emissions and enhance energy security by displacing imported oil, the U.S. has supported the development of alternative fuels, including ethanol. Current fuel ethanol use in the U.S. is approximately 1.2 gallons, produced almost exclusively from corn. To meet carbon emission and oil displacement objectives, ethanol fuel use will need to be increased and will require production from cellulosic feedstocks in addition to corn. The purpose of this study is to evaluate how cellulosic materials might enter the feedstock mix as the fuel ethanol industry expands.
The study is conducted in three parts. First, national feedstock supply curves (quantities and their associated price) are estimated for several potential feedstocks (corn, hybrid poplar, hybrid willow, switchgrass, softwood forest wastes, hardwood forest wastes, corn stover, wheat straw, and municipal solid wastes). Feedstock supply curves are estimated for the years 2000, 2005, 2010, and 2015 under moderate and optimistic scenarios. Maximum available quantities of feedstocks are determined.
Next, the feedstock supply curves are transformed into ethanol supply curves using conversion efficiencies (gallons of ethanol/dry ton feedstock) and conversion costs supplied by the National Renewable Energy Laboratory. Conversion costs include capital and operating costs, and a lignin (for electricity production) co- product credit.
Lastly, the least cost combination of feedstocks subject to ethanol demand quantities and maximum available feedstock supply and ethanol quantities is estimated using a linear programming model. The model includes consideration of durable asset investments. Ethanol demand quantities are supplied by Argonne National Laboratory.
Status/Accomplishments: Optimistic and moderate supply curves have been estimated for the nine feedstocks for each of the four time frames. All feedstock supply curves have been transformed into ethanol supply curves. A draft report of the development of the supply curves has been completed. The linear programming model has been constructed and preliminary results estimated. For example, the estimated least cost combination of feedstocks under an optimistic ethanol demand growth scenario and an optimistic feedstock scenario are as follows: in 2000, ethanol from corn predominates, with a small quantity of demand met by ethanol produced from forest residues. By 2005, agricultural residues begin meeting the majority of the increasing ethanol demand, with small quantities of ethanol produced from forest residues and energy crops (switchgrass). By 2010, agricultural residues still predominate, but increasing quantities of ethanol are produced by energy crops (both switchgrass and SRWC). By 2015, energy crops are being used to produce nearly as much ethanol as wastes.
In addition to this study, the estimated feedstock and ethanol supply curves are being used in the Transition to Alternative Fueled Vehicles Study supported by the DOE Office of Policy, an NREL project evaluating the carbon mitigation potential of renewable energy sources, and are being considered for inclusion in the DOE- EIA National Energy Model.
Summary Date: August 1997
Objective: Develop a GIS-based state-level modeling system for predicting:
Use the system to analyze the cost and supply of switchgrass in 5 southeastern states (AL, FL, GA, SC, and TN) and 7 midwestern states (IA, KS, MN, MO, ND,NE and SD). In particular to evaluate the effect of plant demand on marginal delivered costs and assumptions on farmers willingness to dedicate land to switchgrass production.
Approach/Background: The cost of energy crop feedstock supply will be a function of the price needed to induce the farmer to produce energy crops (farmgate price) and the cost of transporting those crops to the conversion facility (transport cost). The farmgate price will be a function of the return the farmer would otherwise expect from the land, the yield of the energy crop, and the cost of growing the energy crop ( labor, equipment, seed, chemical inputs etc) and the risk the farmer is willing to take. The transport cost will be a function of the travel time and the travel distance from the farm to the conversion facility. All of these factors (with the possible exception of farmer risk) have geographic specificity. If policymakers are to design appropriate policies to encourage bioenergy based on energy crops, and if entrepreneurs are to support bioenergy, they will need some information on the variability in feedstock supplies (both cost and amount) due to spatial variability in potential energy crop yields, farmer's expectation for profit and transport costs.
This project has developed a GIS (Geographic Information System) modeling system which characterizes the potential farmgate price and supply of energy crops at a one kilometer resolution across a single state. It then uses a road network model to first predict the lowest cost of hauling the supply from any point in the state to any other point in the state, second the marginal cost of supplying a specified amount of energy crop biomass to any location in the state and finally the location and marginal cost of supply of all facilities of a specific demand level that could be simultaneously supplied within the state. The system outputs include maps and statistical analyses of the predicted supplies and the environmental effects of procuring those supplies ( changes in erosion, soil nutrient loss, runoff).
The modeling system is designed to be highly flexible with regards the input variables so that it can be updated as new information arrives. It was also designed to run in a variety of modes ranging from simple county-specific input from the ORECCL database to soil-specific input derived from the USDA EPIC (Erosion Productivity Impact Calculator) model.
Status/Accomplishments: The basic modeling system is completed (with the exception of the environmental module) and running on the Oak Ridge National Laboratory, Environmental Sciences Division's GIS system. Switchgrass and conventional crop parameters have been developed for 7 midwest and 5 southeast states. The model takes about 2 hours to run on a Sun Sparc 10 workstation. The model has been run for all the states (but Kansas) at two facility demand levels - 100,000 tonne/yr and 630,000 tonnes/yr assuming farmers if offered a competitive price would grow switchgrass as a major crop (be willing to dedicate up to 50% of their land to switchgrass production). The modeling system has been presented at two international meetings and two national meetings.
The environmental module is currently being fine-tuned and should be completed by the end of September 1997. Switchgrass production in Kansas, Louisiana, Wisconsin will be analyzed in late 1997. Woody energy crop production will be analyzed using ORECCL yield and production cost estimates in early 1998.
Summary Date: September 1997
Objective: Develop a county-level database which compiles current information on land availability and rents, energy crop yields, and production costs. Database should be readily accessible to the general public via a down-loadable file off the Internet.
Approach/Background: State energy offices, farmers, and energy entrepreneurs need easy access to the available information on energy crop costs and supplies. Furthermore, they need that information with as much geographic specificity as possible. Prior to this project, gathering such information required tapping into multiple databases developed by USDA, calling researchers on energy crops for yield estimates, and running economic analyses to figure production costs.
This project pulled together previously published information on cropland and pasture acreages, developed estimates of energy crop yields under common management assumptions, derived county-level land rent values, and ran the energy crop yields and land rent values through the most current production cost model to estimate production costs at a county-level. Because yields may vary widely, a median, upper and lower yield values and their associated production costs were developed. Switchgrass, hybrid poplar and willow were energy crops selected for inclusion in the database.
Data from a variety of sources was combined into an Excel spreadsheet in which every row represented a county and every column represented a unique variable describing some element of land availability, energy crop yields or energy crop production costs. This spreadsheet was also converted into an ASCII file and a transportable SAS file. Data from the United States Department of Agriculture was used to characterize the land base in each county that might be used to produce energy crops. Experts in energy crop production were queried from across the country and switchgrass and hybrid poplar plot data were used to generate broad regional estimates of crop yield and yield variation. County-level estimates of land rent were calculated using published state cash rent values and an indice of farmland value within the county. The energy crop production model BIOCOST was used to characterize energy crop production costs given the predicted yields and land rents.
Status/Accomplishments: The database is completed and located at the ORNL Biomass Feedstock Development Program's Internet site (http://www.esd.ornl.gov/bfdp/oreccl). The database is accompanied by a file describing the variables and their origin. The database was presented at Bioenergy 96 (Nashville, September 1996) and the 3rd Biomass Conference of the Americas (Montreal, August 1997).
Summary Date: September 1997
Objective: Develop an analytical framework to analyze the economics of bioenergy crop production and its implications for the agricultural sector. The analysis will (1) estimate quantities of bioenergy crops produced under alternative energy/bioenergy crop price levels, (2) estimate changes in agricultural cropland use resulting from the introduction of bioenergy crops, (3) estimate the impact of agricultural and economic policy scenarios on the adoption of bioenergy crops, and (4) estimate the economic impact on the agricultural sector, of introducing bioenergy crops.
Approach/Background: A key issue in the use of dedicated bioenergy crops to produce power and fuels is the potential competition for agricultural land between bioenergy crops and conventional crops. Questions include (1) where and how many acres of cropland will be available to produce bioenergy crops, (2) what prices will be needed to entice farmers to adopt bioenergy crops, (3) what impacts will bioenergy crop production have on the prices and quantities of conventional crops, and (4) how might different policies affect the interaction of conventional and bioenergy crops. To address these issues, POLYSYS, a multi-product, multi-sector, and multi-region agricultural model will be modified to include bioenergy crops. POLYSYS was developed and is maintained by the University of Tennessee Agricultural Policy Analysis Center and is used for policy and economic analysis by the USDA Economic Research Service.
With input from DOE and USDA, the project will identify production costs, expected average yields, and POLYSYS regions appropriate for the production of switchgrass, hybrid poplar and willow. DOE models such as BIOCOST, and databases such as ORECCL will be used to estimate bioenergy crop production costs and yields, and identify areas where bioenergy crops can be produced. Databases, such as the 1992 National Resources Inventory and the 1992 Census of Agriculture, will be used to characterize the land base identified as suitable for bioenergy crop production. Expected bioenergy crop yields will be adjusted to account for differences in soil productivity. Competition for land by conventional and bioenergy crops will be evaluated on a relative profitability basis. Once POLYSYS is modified, a set of key exogenous parameters will be identified and introduced to simulate the impacts of alternative scenarios/policies. The response to changes in these parameters will be tested and their results validated. The resulting system will be made available to the BFDP.
Status/Accomplishments: The project is in its initial phase; bioenergy crop yield and production cost data is being gathered and land suitable for bioenergy crop production is being identified and characterized.
Summary Date: August 1997
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File Created: October
13, 1997; Last updated: Thursday, 11-Nov-1999 10:23:33 EST