Crops of all types are typically produced for profit by a producer. Profit can be defined as the value of products produced minus the value of inputs used in production:

n = py ■ qy — px ■ qx (15.1)

where n = profit, py = price of product, qy = quantity of product, px = price of input, and qx = quantity of input.

Producer behavior is often represented as profit maximization in economic models. The amount of profit that producers can make is limited by several constraints and exogenous variables. Constraints include technology and quantities of resources or inputs available to the producer. Exogenous variables include prices for inputs and outputs on which the producer’s decisions have no significant market effect. Exogenous variables also include inputs such as temperature, sunlight, and rainfall that have no price, are beyond the control of the producer, and can have large effects on production and profit. Control variables (those affected by the producer’s decisions) include which type and variety of crop to produce and what quantities of variable inputs to use (area of land, machinery use, seed, fertilizers, crop protection and other chemicals, irrigation water, labor, management, insurance, other risk management aids, fuel and lubricants, other supplies, custom services, and others). Control variables also include intermediate and long-term variables, such as the type and quantity of land to own or rent, the type and capacity of machinery to own or lease, the type and amount of debt to incur, the type of human capital to acquire and maintain, and others. Included among control variables, too, are management decisions such as planting and harvesting dates that do not have specific prices attached but can have large effects on production and profit.

The Profit Maximizing Crop Producer’s Objective Function is:

Y X

Maximize: n = ^(py ■ qy) — ^(px ■ qx) (15.2)

y=1 x=1

Subject to: qy < f (qx) the technology constraint

qx < q*x constraints on the availability of some inputs py = p*y, px = p*x prices determined exogenously

where n, p, and q are profit, price, and quantity as in Equation 15.1, is the summation over all products (y) or over all inputs (x), f(qx) is a function of quantities of inputs (x) used that defines the maximum amount of product (y) that can be produced with current technology, and q* and p* are fixed quantities and prices that are exogenous to the producer.

The technology constraint embodies the biological relationships that define crop growth and product yield. Genetic stock of the plants, via seed, determines the maximum growth and yield possible. Most plants and animals are limited in their growth and yield by insufficient supply of one or more of the inputs or conditions for optimal growth. Much of modern agriculture and silviculture is dedicated to identifying those deficiencies and correcting them. Examples include various fertilizers, irrigation water and drainage, chemicals for plant protection from disease and weeds and pests, mechanical treatment of soils, and temperature and light control in greenhouses. Another important part of modern agriculture and silviculture is dedicated to development of genetically superior plants and animals. Sustainability in crop production is inseparable from production decisions and is discussed in a subsequent section.

Of the 12 Principles of the Roundtable for Sustainable Biofuels, six are clearly social (Legality, Planning, monitoring and continuous improvement, Human and labor rights, Local food security, and Land rights), while parts of the other criteria include social justice aspects. For example, small feedstock producers are exempt from greenhouse gas emis­sions, Criterion 3c. Biofuels’ contribution to climate change mitigation shall be improved over time. However, given the expenses involved in measuring and implementing climate change mitigation, exempting small producers makes sense. All the conservation criteria (Principle 7) take into account local communities as well as ecosystems. Principle 9, Water, includes “respect prior formal or customary water rights”. Principle 11 includes specific concern for the people place. “The use of technologies in biofuel production shall seek to maximize production efficiency and social and environmental performance, and minimize the risk of damages to the environment and people.”

A number of scholars have attempted to specify the criteria to be used to indicate social sustainability. Table 17.1 provides examples of potential social criteria proposed by Markevicius et al. [24] for the development of liquid biofuel standards. Much of biomass

for fuels is transformed into liquid fuels. These criteria are focused on the sustainability of local populations, and do not lend themselves to plantation systems.

Table 17.2 provides examples of social criteria proposed by Lewandowski and Faaij [30] for the development of biomass/bioenergy standards.

There are a variety of harvesting systems in use in conventional forestry and short-rotation woody crop operations. This section describes the equipment used in conventional sawlog production operations from which thinning or logging residues may be derived, as well as short-rotation woody crop production equipment. When evaluating these equipment options working in sequence in biomass operations, the convention for establishing cost and production rates of equipment most commonly follows traditional machine rate methods, in which the hourly costs of equipment ownership and operation are partitioned into fixed and variable costs. Production functions are estimated using regression relationships developed from work sampling and time and motion field studies, with production in volume or mass per hour expressed as a function of stand (e. g., mean tree diameter, species, trees per hectare), site (average slope), equipment (machine payload capacity, horsepower), and operator variables as predictors. Logging costs for alternative supply chain components and equipment combinations are estimated by dividing machine rates, whether individually or summed over several machines, by the total production achieved in a specified time period. The result is cost per volume ($ m-3), or cost per unit mass ($ t-1). For example, if a feller-buncher has a machine rate cost of US$140 per hour to own and operate, and averages felling and bunching of 10 cubic meters per hour, then the total logging cost is estimated to be $140/10 = $14 m-3.

Operation of a farm or any business requires financing input purchases and asset utiliza­tion. Farmers may borrow large amounts of money or invest their own money to buy land. Agricultural land is an appreciating asset typically valued at many times the annual rent it can generate from agricultural use. Farmers also invest and may borrow money to buy machinery, such as tractors, trucks and equipment, and buildings, such as grain storage. Machinery and buildings are depreciating assets that may provide needed ser­vices over a number of years and may have a smaller resale value through time. Farmers also invest their own money or may borrow money to purchase operating inputs, such as seed, fertilizer, chemicals, and fuel, or to rent equipment or hire services during the grow­ing period. The money used to finance the purchase of operating inputs is referred to as operating capital.

All capital used in the farm business comes at a cost. The cost of capital is time dependent. Interest is charged at some rate per period of time for borrowed capital. Interest is foregone on money invested by the farmer in the business. The interest paid to lenders is visible as a cash expense while interest foregone on owned capital is an opportunity cost. Owned capital could be used to pay off other loans and avoid interest costs or it could be invested in interest-bearing accounts.

Capital is a limiting resource for businesses. Without capital, farmers are unable to acquire inputs needed for crop production. Lenders typically require security for the amounts they lend. Non-depreciating assets such as land are preferred collateral. Depreciating assets such as machinery and buildings may also have value as collateral. Lenders may accept an ownership interest in the growing crop as partial collateral for operating loans. Other assets, such as other real estate and savings accounts, also serve as collateral for borrowed money. Interest on capital appears in the enterprise budget both as an operating expense for operating capital and as a component of the amortization of investments in machinery and buildings.

The net worth of any business, including farm businesses, can be defined as the total value of assets minus the total value of debt. An important implication of risk in agriculture is that crop losses reduce the net worth of the farm business. When losses exceed net worth, the farm business may no longer be viable and may be foreclosed upon by lenders, may enter bankruptcy, or may simply be unable to finance new production. Farmers with smaller net worth relative to the size of their farm may find it more difficult to borrow money and may have to pay higher interest rates. Such farmers may also select less risky crop mixes or less risky input combinations in order to reduce the probability of financial collapse. Acquisition of new machinery to produce a new crop or the allocation of land to a new unproven crop may impose capital costs and risks that are unacceptable to low net worth farmers.

At its core, the primary challenge with commercializing energy crop production for bioen­ergy is minimizing risk. This includes risk to the producer, risk to the biomass conversion facility developer, and risk to the institution(s) financing the project. Understanding and mitigating these risks are a part of the commercialization process. There are three primary areas of risk with energy crop commercialization. They are:

• Land recruitment.

• Establishment and supply ramp up.

• Annual yield risk.

As discussed earlier, recruitment of land is critical to all other aspects of the commercial scale supply chain. If a project is unable to secure the required amount of land in a given area, the entire project could fail. Addressing this risk begins with adequate planning. Finding a qualified partner to conduct a feasibility study on land recruitment will be critical. Feasibility studies will allow for the evaluation of many aspects of a given area’s land use, agricultural infrastructure, and willingness of farmers and landowners to participate. A feasibility study will help identify potential issues with a given location prior to the start of a project and/or enable better site selection processes.

Recruitment risk can also be reduced through incentive programs, like BCAP, that reduce cost and risk to landowners and farmers. Particularly with perennial crops, reducing the up­front cost to landowners though such a program or by covering a portion of establishment costs through the project will enhance the project’s ability to recruit land.

Significant risk is also associated with crop establishment and ramp up in yields to meet the demands of the biomass conversion facility at start-up. With perennial crops, the maximum yield of the crop is not reached until three years after establishment. This extended maturation of the plant requires commercial biomass supply chain developers to carefully plan establishment activities with the construction and subsequent start-up of additional biomass conversion facilities. Regardless of how well establishment is planned, several factors could disrupt the process and delay biomass supplies. Establishment of crops like switchgrass and miscanthus is not an easy task. As discussed in other chapters, precipitation, weed control, and other factors can make establishment difficult. If an acre of biomass crop is not successfully established and must be replanted, there will be an automatic delay in maturation of the crop by one year; this will thus affect anticipated delivery of biomass to the conversion facility.

To reduce establishment risk in energy crops, several best management practices should be employed. Firstly, areas with high populations of weed species known to compete with the target crop should be avoided. For all land types, site preparation in advance of planting can improve the likelihood of success significantly by reducing potential weed issues before they occur. Utilizing quality planting stock from reputable sources is also important. Seeded species require high germination rates for success and rhizome-type planting materials need to receive good care through rhizome harvesting and storage to enable adequate planting success. Finally, establishment-year management must be diligently carried out. Addressing competition issues and other fleld-by-fleld management concerns in a timely manner will significantly increase the likelihood of success. Additional tools, such as an increase in availability of applicable herbicides, will aid in management success.

The final key risk category is year-to year-variation in energy crop yield. While dedi­cated energy crops are more resistant to drought and other climactic factors, they are still susceptible. A drought that would wipe out a corn or soybean crop may reduce perennial energy crop yields by 20-30% [12]. Generally there will still be an adequate harvest and the stand will survive, but biomass yield will be reduced. There are also risks for pests and diseases that may impact the yield of dedicated energy crops. Planning to mitigate risk for this variation in yield, regardless of the source, will be difficult. As biomass conversion projects develop, energy crop production will be carefully monitored to match the annual volume of material required to operate a facility. Due to land and crop establishment costs, many projects will not have the ability to “overplant” a buffer supply to mitigate variation in yield from year to year. Therefore, planning to carry inventory over from year to year to buffer feedstock shortfalls is one method of addressing the risk. Identifying and plan­ning conversion facilities for alternative feedstocks to augment primary supplies is another method. Developing a diverse portfolio of feedstocks is a broad, impactful tool to help ensure long-term success for commercial energy crop systems.

Additional risks, those that may not be directly tied to energy crop supply chains, exist and can dramatically impact the overall biomass-based industry. These risks include the stability or lack thereof in state and federal policies related to bioenergy. Policies, such as the Renewable Fuel Standard (RFS), can successfully generate market demand for biomass and subsequent products. However, as of 2013, the RFS and other biomass related programs, such as BCAP, continue to be a controversial mandate in the political arena. The policy climate presents significant risk to the industry as a change in the policy or even discussion about changing the policy can impact capital investment availability and markets for existing facilities. Additionally, some sectors of the biomass-based conversion industry are operating or planning to operate technologies that remain relatively unproven in the market place. Inherent risk is associated with using new technologies at a commercial scale. With the reliance of some biomass-based industries on perennial energy crops, the failure of a conversion technology may leave a large island of biomass energy crops stranded without a significant market for use. Creating multiple markets and outlets for the biomass will significantly reduce risk associated with policy and technologies by providing biomass producers with alternatives.

Biomass conversion facilities that have the ability to accept multiple types of feedstocks will have inherently lower feedstock risks. This is a key method of risk mitigation. Fewer acres of each individual crop will reduce yield variation and production risks. An ability to use other feedstocks when a particular one falls short on supply provides adequate back up to keep the conversion facility in operation. A diverse feedstock supply can also reduce feedstock costs by decreasing storage and other production system costs. Without any question, management strategies that accommodate diverse feedstocks are the primary method for reducing risk in energy crop supply chains.

The second overarching method to reducing risk in commercial dedicated energy crop supply chains is improvement in energy crop genetics. These improvements will be critical, just as they have been for corn and soybean. Significant yield gains have been made in the last 10 years through genetic resistance to drought, disease, and other pests affecting those crops. Similar improvements are now being incorporated into energy crop production and additional, significant improvements are expected in the next several years. Improvements in yield alone will reduce risk from all factors. Less land will be required to produce the same amount of biomass while fewer acres planted reduces establishment and annual variation risk. Other genetic traits and factors, such as herbicide resistance and improved nutrient use efficiencies, will also help reduce establishment and yield risk.

To successfully commercialize the energy crop supply system for a given consumer, project participants, financiers, and others will all be evaluating risk throughout the system. Careful thought and pre-planning of the energy crop supply chain can mitigate a significant amount of problems downstream.

18.3 Conclusion

Commercializing dedicated energy crop supply chains is not an easy task. Significant hur­dles must be addressed to be successful. The good news is that a broad array of research and development (R&D) efforts have been and are underway. Government agencies, universi­ties, and private companies have all made significant investments in developing systems by which energy crop supply chains can be commercialized. Significant research and develop­ment activities have occurred and are occurring in herbaceous energy crops and dedicated woody crops in all sectors of the United States and abroad. These R&D activities have gen­erated a strong base of knowledge and expertise that commercial entities are now beginning to utilize at the commercial scale. It is projected that the United States could produce over one billion tons of biomass between 2025 and 2030 [13]. To produce that much biomass in a sustainable manner will require planning, a broad array of skills, and sound risk man­agement, as well continual improvement of the entire supply chain during the next decade. As the first few commercial scale projects begin operation in 2014 and 2015, all of the knowledge and skills developed will be put to the test. With the extensive work that has gone on in the past decade, we are well positioned to make the commercialization of dedicated energy crops a great success, a success that will benefit generations to come.

References

Now suppose the bulk density of the load is increased by 20%. The load is increased from 12 to 14.4 dry ton, and the cost per dry ton (10 min load, 10 min unload) is reduced from $9 to $7.50.

We are now ready to address a very important issue in logistics system design. It is obvious that increasing bulk density increases dry tons per load. (The volume of the truck is fixed by highway regulations.) But what is the cost of increasing the bulk density? In this example, suppose the cost of increasing the bulk density is $2.75/dry ton, and no cost benefit is assigned in loading or unloading operations for the higher bulk density material. The reduction in truck cost is only $9.00-7.50 = $2.50/dry ton. This means that $2.75 has been incurred in densification cost to save $2.50 in truck cost, thus the total delivered cost increased by $0.25/dry ton. It is better, just considering truck cost, to haul the raw biomass without densification.

13.6.2 24-h Hauling

Now suppose the same truck in the above example hauls the same dry ton per load over the same distance (10 min load, 10 min unload) and operates continuously 24 h/d. The truck can now haul 16.7 loads in a 24-h workday as compared to seven loads in a 10-h workday. (It is acceptable to use the 16.7 loads, since the truck is operating continuously. It can average 16.7 loads/d over some chosen time period.) The labor cost increases because operators must be hired for three 8-h shifts plus the maintenance cost per day increases due to more miles traveled per day. Use $800/d as the cost for the truck.

The truck hauls 16.7 loads per day, thus the fuel bill is:

$43.75/load x 16.7 loads/d = $731 /d

Total truck cost is:

$800/d(ownership + operating) + $731/d (fuel) = $1531 /d The cost per dry ton is:

$1531/d

16.7 loads/d x 12 dry ton/load

The truck cost has been reduced from $13 to $7.64/dry ton, or 41%, by operating 24 h/d rather than 10 h/d.

Why not design logistics systems to operate 24 h/d? The issue in feedstock logistics is not the unloading at the receiving facility — the plant operates continuously so the receiving facility can certainly operate continuously. The issue is loading the trucks. No one has devised a system to load trucks at night at some remote location. An example will be shown later for trailers loaded during the day and pulled during the night, so that the same truck tractor is used for 24-h hauling.

The issue of trucks operating on rural roads at night is unresolved. This may be accepted, or it may not; there is little experience to establish a precedent.

14.8.1 Mechanical and Chemical Pretreatments

Communition of woody biomass through chipping, grinding and shredding increases its bulk density, which improves transportation efficiency by allowing trucks to carry heavier payloads. Such processing also improves handling and storage by reducing particle size and increasing homogeneity, allowing material to be more efficiently handled by loaders, conveyors and other equipment. In the context of woody biomass logistics, pretreatment generally includes additional processing that further improves the transportation, handling, storage and end use characteristics of biomass feedstocks beyond typical communition methods. Physical, chemical and thermal pretreatments are all technically possible but vary significantly in their operational characteristics and commercial potential.

When end users of woody biomass have feedstock specifications that are outside tradi­tional parameters for chips and hog fuel, additional drying, milling, chipping and screening can be used as pretreatments. For example, many distributed scale gasification systems require clean, dry, microchips as a preferred feedstock (e. g., low ash, bark-free chips less than 3 cm in size and 10% water by weight). The equipment to produce this high quality of feedstock from woody biomass is commercially available and widely deployed in industrial settings. More intensive debarking, chipping and screening are easily accomplished on a log landing, though these steps obviously incur additional costs. In-woods pelletization has also been explored as a pretreatment option, but remains difficult to do efficiently at distributed scales. Similarly, chemical pretreatments are widely used by cellulosic ethanol operations to reduce lignin content and improve sugar yields, but these techniques are not easily mobilized for field applications and typically involve liquid waste management and reprocessing that is almost impossible to do efficiently away from a large-scale facility. In contrast, there has been growing interest in using mobile thermal pretreatment technologies close to the harvest site to further improve transportation efficiency and produce renew­able high-value bioproducts that can be shipped efficiently to distant markets, especially in areas characterized by long transportation distances. Though discussed here as a pretreat­ment option, thermochemical pretreatments can also be classified as biomass conversion technologies, especially when deployed at larger centralized facilities (Chapter 2).

Conversion of cropland to WSG such as switchgrass can increase infiltration and improve soil structure over time with measurable changes generally taking place over 6-15 years [13,14]. Changes in soil hydraulic properties under warm season bioenergy grasses will depend on grass species, soil type, climate, and management [7]. In a study of both hybrid poplar plantations and switchgrass plantings in north-Central Minnesota, Coleman et al. [15] showed that a combination of variable native soil organic carbon (SOC) levels and slow rates of SOC change made it difficult to verify soil carbon sequestration in the first 12 years of short-rotation poplar plantations. Conversion of cropland to short-rotation poplar only led to increases in soil carbon on poorer soils that were marginal for agriculture [15]. It is likely that SRWC plantations will only change SOC over multiple rotations as the influence of larger structural roots on SOC becomes more important [16].

The use of buffers can enhance environmental sustainability of row-crop systems [17,18], and may be a source of bioenergy feedstock because of the perennial characteristics of the species generally recommended for these buffers. Furthermore, while streamside and other riparian buffers may not be appropriate places for bioenergy crops because of the frequency of harvest, bioenergy plantations would likely require smaller buffers than annual crops [19].

Concern about soil erosion in biomass production systems dates back at least 25 years and is likely the greatest threat to sustainability of soil resources on which cellulosic bioenergy feedstocks generally depend [20]. Soil erosion may be reduced by as much as an order of magnitude in SRWC, compared to annual crops, although the establishment phase of the woody crops may leave considerable bare ground until a canopy and leaf litter layer are established [21]. Establishing SRWC with cover crops reduced erosion by 35­64% compared to SRWC without cover crops [22], with better erosion control for winter annual ryegrass (Lolium multiflorum) than for perennials fescue (Festuca arundinacea) or lespedeza (Lespedeza cuneata). During the first year of establishing SRWC, a poplar planting without a winter cover had higher erosion than either poplar with a fescue cover or no-till corn [21]. Nyakatawa et al. [23] found similar high erosion rates early in the establishment of sweetgum (Liquidambar styraciflua) plantations. Even in the first year of establishment, sites in the southern United States showed lower erosion from poplar plantations than from conventional tilled cotton (Gossypium hirsutum) and corn [21, 24]. After the establishment phase, well-managed WSG and SRWC species can be managed to provide year-round cover and reduce soil erosion compared to annual crops [7, 25]. As with woody crops, the establishment phase of WSG is critical to soil erosion. Management is also critical for WSG in that they should not be harvested at heights below 0.1 m in order to retain erosion control and soil building benefits [7].

There is a general consensus that conversion of cropland to perennial bioenergy crops (SRWC or perennial WSG) will result in an increase in soil carbon sequestration, but the conversion of grassland may not be as beneficial [26,27]. Soil carbon concentrations will not increase indefinitely, as eventually a new, higher carbon equilibrium will be achieved, although it is not clear how long this process will take [28]. Assessment of SOC changes under perennial bioenergy crops for a range of soils, climates, and management practices should be a research priority because of the importance of soil carbon accumulation on the potential net greenhouse gas measures of bioenergy crops [7].

The key decision points for the design of a logistics system for a bioenergy plant operating 24/7 year-round are summarized as follows:

1. A complete logistics system is defined as one that begins with the biomass standing in the field and ends with a stream of size-reduced material entering a bioenergy plant for 24/7 operation. Optimizing one unit operation in isolation may increase the cost of an “upstream” or “downstream” operation such that total delivered cost is increased.

2. Herbaceous biomass is harvested only part of the year, thus storage is always a part of the logistics system. A cost effective logistics system provides for efficient flow of material into, and out of, storage.

3. Just-in-time (JIT) delivery of feedstock provides for a minimum at-plant storage cost and is preferred by plant designers. Since JIT delivery is not practical for typical biomass logistics systems, there is always a cost trade-off between the size of at — plant storage and the other design parameters needed to insure a continuous feedstock supply. Having known quantities of biomass in SSLs provides a Feedstock Manager an opportunity to minimize the at-plant storage cost.

4. Farmgate contracts that require a winter harvest must compensate for the loss of yield incurred by the delayed harvest.

5. Uncoupling of the unit operations in the logistics chain can provide an advantage.

(a) Baling uncouples the harvesting and in-field hauling operations. When the har­vesting operation is not constrained by in-field hauling, both unit operations can proceed at maximum productivity.

(b) When truck loading is uncoupled from hauling, the loading crew never has to wait for a truck to arrive and the truck never has to wait to be loaded.

6. Truck cost is the largest component of total cost in most logistics systems, thus it is essential to maximize truck productivity (tons hauled per unit time) by increasing tons/load and loads/day. A 10-min load time and a 10-min unload time is a desired goal for increasing loads/day.

7. The multibale handling unit was developed to solve the rapid load, rapid unload challenge.

8. Twenty-four-hour hauling can minimize truck cost ($/ton). The challenge is to find a way to load the trucks at night at a remote location.

9. The design of the receiving facility, because of the need to unload trucks quickly, is critical in the design of a complete logistics system.

10. Assigning different unit operations to different entities in the business plan can lower average delivered cost. For example, it is more efficient to pool all farmgate activities into a farmgate contract and have a hauling contractor handle all load-haul activities. This division is defined as a division between “agricultural” and “industrial” opera­tions. One key benefit achieved is in the capitalization of the equipment. Load-haul contractors can afford to invest in industrial-grade, high-capacity equipment designed for year-round operation as compared to farmgate contractors who will use their equip­ment 400 hours (or less) per year.

11. A biomass logistics system must be structured such that information technologies (GPS, bar codes, entry of data over cell phone network) and optimization routines developed for other logistics systems can be used to optimize asset utilization in real time.

Appendix 13.A Cost to Operate Workhorse Forklift (Example for Equipment Cost Calculations)

Machine selected for this study: Taylor Model TX 360M

$154 400 15 000 h

24 h/d, 7 d/wk, 47 wk/y = 7896 h 8% r = 0.08 $0.80/$100 value/y

x 0.80 = $1232/y

where

Co = ownership cost percentage (dec),

Sv = salvage value (dec), n = machine life (y), r = interest rate (dec), and K2 = factor for taxes and insurance (dec). K2 = 0.01 + 0.008 = 0.018 [3]

Annual ownership cost ($/h):

$81,004

7896

Operating Cost ($/h):

R/M + Fuel + Labor = Total

3 + 12 x 1.02 + 20 = $34.10/h

Ownership + Operating = Total

10.26 + 34.10 = $44.36/h

Total cost ($/dry ton):

Plant averages 23 dry ton/h $44.36/h

= $1.93/dry ton

Appendix 13.B Operational Plan for “Rack System” Example B.1 Operation Plan for SSL Loading

Ideally, the rack-loading operation at the SSL can load 16 bales in a rack in 20 minutes. This is a design goal which has not yet been attained with actual equipment. Discussion of how it might be achieved is presented later.

In a workday with 10 productive hours (600 min), a 20-min/rack operation can theo­retically load 30 racks, or 15 truckloads. An actual operation, given the reality of field conditions, cannot sustain this productivity. For this analysis, it is reasonable to assume that a mature operation can average 70% of the theoretical productivity. The number of loads/day/operation used for this analysis is 15 x 0.7 = 10.5 loads/d. The number of loading operations required is then

53 loads/d required at plant = 5 operations averaging 10.5 loads/d

This means that loading operations will be operating at five different SSLs for each workday and each will load, on average, 21 racks/d. Time to move the loading operation from one SSL to the next is not dealt with in this analysis, so the 21 racks/d productivity, averaged over an entire year, may be optimistic.

There are several options for a rack design. For this example, we chose the Side-load Option. It assumes a telehandler with special attachment will pick up two bales per cycle (Figure 13.B.1) and load these bales into the side of the rack while it remains on the trailer. We use the assumption that the average productivity that can be achieved under production conditions is 34 min/rack. Time required to load the two racks on a trailer is 68 min. Remember, this is the assumed average load time for year-round operation.

SSL operations — the loading of the trucks — is the most difficult challenge in the design of a cost-effective biomass logistics system. It is difficult to reduce the cost of these operations because the labor productivity (tons handled per worker per hour) tends to be low.

We choose to uncouple the SSL loading and hauling operations. This means we want a system where the truck does not have to wait for racks to be loaded in order to pick up the trailer. Also, the SSL crew does not have to wait for a truck to arrive to have a trailer with empty racks to fill.

The day-haul operations are uncoupled by providing two extra trailers at the “day haul” SSL, and the night-haul operations are uncoupled by providing nine extra trailers at the “night haul’ SSL. Each truck tractor then has a total of 11 extra trailers in the system. This is probably not an optimal (least cost) approach, but it does provide a reasonable starting point for this example.

A widely used tool for evaluating the potential costs, revenues, and profit from crop production is the enterprise budget. Crop enterprise budgets are typically customized to local production conditions. The Ag Risk and Farm Management Library [1] provides links to a variety of enterprise budgets and most United States state agricultural extension services have sample crop budgets available [2]. Budgets for non-traditional crops may be more difficult to find and may be based on smaller samples of actual production data.

Each enterprise budget represents a single point on a profit function (Equation 15.2). A specified quantity of product and a specified quantity of each included input are multiplied by specified prices, respectively, and summed to obtain estimates of revenue, cost, and net returns to excluded inputs and profits. Most published enterprise budgets are not intended to predict costs, revenues and profit for each or any producer. Instead, they are intended as a somewhat typical guideline and as a starting point for use by producers to adapt to their own production and market conditions. Enterprise budgets may embody generally recommended practices and input levels to produce the optimal yield of a selected crop in a selected location for a specific year or season. Farms vary widely in terms of area farmed, topography, soil type, crop mix, machinery complement (age, capacity, equipment type), labor availability, managerial expertise, weather and other factors. Management decisions are likely to deviate from initial plans as weather, markets, and other variables deviate from “normal” during the growing period. Lazarus [3] provides an example of an enterprise budget for a single season crop: corn for grain and for corn stover.

Several characteristics of enterprise budgets are notable. The revenue section of the budget lists each of the products of the crop that generate revenue, such as grain and stover. The cost section of the budget lists each input with quantities, prices, and cost. The cost section may separate costs of single use inputs (seed, fertilizer, chemicals, custom services, etc.) from costs of owning machinery and equipment and from costs of labor, management, and land. The single use inputs are typically cash expenses for farmers while the other inputs may be owned and contributed, shared with other crops, financed with borrowed money, or residual claimants on net revenue. The net returns section of the budget lists the balance after costs have been subtracted from revenue. Net returns equates to profit if all costs have been subtracted or it may represent a net return to inputs that have not been included as costs: typically management and land. In order to facilitate analysis of profit maximizing decisions, enterprise budgets should accurately portray the quantity and price or value of each product and of each input used to produce the crop.

Olson [4] provides a thorough overview of farm management issues and methods.

15.1.1 Stover as a Co-Product of Corn Grain

Cellulosic energy crops can be categorized as co-products or dedicated crops and as single season (e. g. corn) or perennial (e. g. switchgrass) or multiseason crops (e. g. trees). Corn stover is a single season, co-product crop. The revenue from a co-product must meet two conditions for economic feasibility. Firstly, the sum of revenues from all co-products of the crop must exceed the sum of costs of production. Secondly, the revenue from each co-product must exceed the additional costs of producing that co-product. In the example from Lazarus [3], the revenues from stover as a co-product of corn grain are $126 per acre (at $70 per ton) and marginal costs are $89 per acre, including $33 for fertilizer, $41 for machinery with labor, and $14 for transport, generating a net return of $37 per acre. The addition of a profitable co-product can increase the profitability and competitiveness of an existing crop.