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October - December 2006
Haul time was increased by 25 percent to account for operational delays. Service areas are calculated based on haul time in 15-minute intervals using the ArcGIS Network Analyst Service Area Calculator. The resulting service area polygons are exported as shapefiles.
Service area polygons were combined with county polygons using the Union function and clipped to the area of interest. A new floating point field called NewArea was added. The new area for each feature in the service areacounty union was calculated. A text field called ConCat was added, and county identifier field (FIPS) was concatenated with the service area haul time field (ToBreak) to create the FIPS-ToBreak field.
A table summary was performed based on the ConCat field to include the original area average and the sum of the NewArea field. The summarized table was imported to Microsoft Excel so the percentage of each county in each haul time category could be calculated by dividing the NewArea field by the original area for each FIPS-ToBreak record. This area percentage was used to estimate the percentage of each biomass resource type by each haul time category in each county. An Excel pivot table was used to calculate the estimated total of each biomass resource in each haul time category.
The procurement, harvest, and transportation costs were summed to calculate the total delivered cost of each woody biomass resource within a given haul time category. Ranking these resource haul time categories from lowest cost to highest cost yielded the estimated progression of most to least economically available woody biomass resources. Under these cost assumptions, urban wood waste requiring a one-way haul up to 90 minutes is cheaper than other woody biomass resources with shorter haul times.
Supply Curve Construction Using Excel
With the information on quantities, distribution, procurement, harvest, processing, and transport costs for each woody biomass resource, supply curves can be constructed. A supply curve is a basic economic tool used to express the price of a resource at a given quantity of demand. Supply curves can be plotted in Microsoft Excel as a scatterplot or by using the Macro Economic Supply Curve Chart Excel add-in. Supply curves were plotted so that the x-axis was the cumulative total amount of woody biomass with each additional resource-haul time category and the y-axis was the total delivered cost. Units were expressed based on energy content of the biomass; however, these could have been expressed as units of mass.
Typical demand was estimated in the range of 2 to 4 trillion British thermal units (BTUs) to produce approximately 20 to 40 megawatts (MW) of electricity (or enough electricity to power between 8,000 and 16,000 households in the southern United States). For the 27-county average cost curve, quantities in this range cost $1.57 to $1.91 per gigajoule (GJ-1) or $1.66 to $2.01 per thousand thousand BTUs (MMBTU-1) which is competitive with current coal energy costs. Under the average curve, demand up to 4 trillion BTUs can be met with urban wood residues within a 135-minute haul, and forestry residues and stumps within a 45-minute haul, with no need to harvest additional trees.
These supply curves illustrate the local economic availability of woody biomass resources and prices that might be paid as a function of demand. Further results and a sensitivity analysis are included in a pending U.S. Forest Service general technical report. Project conclusions include the following points:
About the Authors
Matthew Langholtz, postdoctoral research associate, and Douglas Carter, associate professor, are with the School of Forest Resources and Conservation, University of Florida, Gainesville, Florida. Matt Marsik is a Ph.D. candidate in the Department of Geography, University of Florida, and Richard Schroeder is president of BioResource Management, Inc., Gainesville, Florida.
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