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Projecting Cropped Biomass Supplies: The Landowner Factor

New York biomass study focuses on landowner choices and preferences in determining how much biomass can be grown and at what cost.
By Dan Conable and Tim Volk
A reliable and affordable biomass supply is the starting point for any biofuel or bioenergy project. Although the level of detail in biomass supply shed assessments has increased in recent years, all the standard approaches ignore an essential element-the opinions and preferences of the people who own and make decisions about the land.


Understanding a Local Biomass Supply Shed

When Ray Cross, president of Morrisville State College, undertook a comprehensive review of energy use by his school's central New York campus, a biomass-fueled heat and power plant was an obvious option. "It fits our tradition as an agricultural college, and also our educational strategy of exposing students to the challenges of implementing new technologies in real-world settings," Cross says. The campus is surrounded by a mixture of farm and forest land. It is also eight miles up the road from Colgate University, which has used wood chips as a primary heat source for more than 20 years. "With a neighboring college already getting most of its heat from wood and new forest-based energy projects springing up all over the region, it made sense for us to look into cropped biomass as our fuel source," he says. "We seemed to have an adequate land base, but we didn't have a good sense of how biomass would fit into the mix of existing uses for that land, let alone the underlying relationship between the price we could pay and what our area could supply."

The question of where biomass crops fit into a complex mixture of overlapping agricultural and "lifestyle" uses for rural land has also intrigued the Farm Viability Institute, a nonprofit organization that has funded applied agricultural research in New York State since 2004. "After several years of supporting field testing of biomass crops in different climate zones, we're beginning to get a handle on production costs," says Tom Sleight, the institute's executive director. "However, in a state where upwards of one-third of the active agricultural land and a larger share of the idle land is not owned by a farmer, model crop budgets only take you so far. When does it become interesting for a commercial farmer to aggregate enough land to set up an efficient production unit? Will nonfarmers be receptive to the longer lease terms that perennial energy crops require?"

With funding from the Farm Viability Institute, Cato Analytics LLC undertook a biomass supply assessment covering all the agricultural land within 25 miles of Morrisville, utilizing a new methodology initially developed in another supply shed with support from the New York State Energy Research and Development Authority. This research strategy emphasizes an "overlay" that most GIS assessments fail to include: the landowner choices and preferences that will control how much biomass will be grown and what it will cost.


A Field-by-Field Approach

The team began by identifying properties with 10 acres or more of agricultural land from satellite land cover and tax roll land use data. "The published accuracy of the National Land Cover Data Base classification of agricultural land in the Northeast is about 80 percent," says Stephen Steh-man, the project's statistician, "which was considered suitable for constructing a reasonably accurate list of candidate properties." A stratified sample was drawn from nearly 7,000 properties that met the coarse land cover/land use criteria. Owners of properties in this sample were invited to participate in the study, with the offer of an assessment of the biomass crop production potential of their individual properties in exchange for a face-to-face interview.

Properties whose owners agreed to participate were located from tax roll data and mapped onto aerial photos. A GIS specialist outlined and numbered each field, measured its area, and identified its dominant soil type. "This was an essential starting point," explains Chuck Kyle of Cato Analytics, who served as field director of the project, "because we know from previous studies that landowners may be willing to do something with one particular field that they wouldn't consider on another. This is true both for farmers and non-farmers, and these are things you can't figure out from standard GIS data."

After the properties and fields had been mapped, a field technician visited the properties, noting the current use of every field, along with drainage and other conditions relevant to its biomass crop production potential. Crop yield models were used to estimate what each field might be able to produce in three perennial crop categories-shrub willow, warm season grasses and cool seasons grasses-taking into consideration soil type, climate zone, drainage, estimated fertilizer requirements and other agronomic factors. As this work was getting underway, team members built crop budget models, incorporating local farmer input to make sure they accurately represented costs in the region.

Structured face-to-face interviews with each landowner began with an informal exploration of the property's ownership history, current uses, and the owner's plans and ideas for the future. The discussion then progressed to whether the owner would consider committing his or her property, field by field, to any of the biomass crop options.

The interviewer's first goal was to learn whether each field was "in play" or "out of play" for each of three perennial energy crop systems. "Every landowner has a different story, and so does each field," Kyle says. "How far is the field from the house? Is its current use vital to the owner's agricultural business, or to a particular recreational use?"

Using an Excel workbook with each field's productive potential and the crop budgets already loaded, the interviewer could explore the roadside price at which the landowner would consider producing each of the three crops with his or her own resources. The workbook was constructed with macros that could simulate the cash flow and cumulative net returns for an energy crop on the acreage in play at varying hypothetical roadside price levels. Another tool captured the minimum rent at which the owner would commit the land to biomass production by a third party under a multiyear lease.


Linking Supply and Price

After two months of field work, the team had determined whether more than 1,300 individual fields, located throughout the study region, might supply biomass, how much they could supply, and at what minimum price. An expansion of data from this randomly-selected set of study properties provided a projection of total regional supplies, by price, for each type of biomass.

"This is the first time we have seen a local biomass supply analysis that produces a cost curve, rather than a total biomass supply number, disconnected from someone's estimate of a standard cost of production," says Larry Martin, vice president of O'Brien & Gere, the engineering firm that is performing the energy analysis for Morrisville College. "This is enormously useful when you're doing a feasibility study and evaluating multiple solutions and technologies. What we need to know is what a future plant will have to pay for a type of fuel, connected to the availability of that source."

While these cost curves were the study's "bottom line," byproducts included a fine-grained analysis of current land use, the quality of land in the total agricultural land base, rents, ownership patterns, and the dimensions and dispersion of fields that might be available to produce biomass. Although this study covered only perennial grasses and short-rotation woody biomass, the methodology is adaptable to other energy crop options, as well as crop residues.

"I don't know how a project developer could design a biomass crop procurement strategy in upstate New York without the kind of information about the potential production area that this study has given us," Cross says. The same may be true for crop-based biomass projects in many other parts of the United States, where land ownership patterns and the motivations of individual landowners are as diverse as the landscape itself.


Dan Conable is a partner in Cato Analytics LLC. Reach him at contact@catoanalytics.com. Timothy Volk is co-director for the sustainable energy program in the Center for Sustainable and Renewable Energy at the State University of New York College of Environmental Sciences and Forestry. Reach him at tavolk@esf.edu.
 

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