Category Archives: Fertilization

Size of At-Plant Storage Yard

As an example, maximum at-plant storage for a three-day supply is calculated as follows.

1.75 racks/h x 72 h = 270 racks

Racks will be stacked two high in “units” with two rows of 24 spaces each, thus there are 48 storage spaces in each unit. Each unit stores 96 racks. Three units are required for a 270-rack storage.

If a seven-day at-plant storage is required, the total number of racks required is 630, or seven 96-rack units. This implementation of the rack system is not believed to be a cost effective choice. The rack system competes best when the racks are filled and emptied as


Figure 13.14 Bins being stacked in at-plant storage at a sugar mill in Texas.

many times as possible in a given time period, not when they are used as storage units. Other multibale handling units (Figure 13.10) are more suitable for a larger at-plant storage.

Economic Sustainability. of Cellulosic Energy. Cropping Systems

Kelly D. Zering

Department of Agricultural and Resource Economics, North Carolina State University, U. S.A.

15.1 Introduction

Cellulosic energy cropping systems can be sustained when economic incentives remain positive for each participant in the system. In other words, profit from an energy cropping system must equal or exceed profit from available alternatives for each component of the system. This chapter includes an overview of economic principles applied to sustainable energy cropping systems. Capital investment and risk are addressed in addition to recurring revenue and operating costs. Sustainable policy issues and non-market issues such as environmental protection, resource conservation and energy security are also presented. Implications of the comparative profitability requirement are presented for each link in the energy cropping supply chain. The interaction of prices and quantities supplied and demanded is a primary focus for each of the goods and services affected by sustainable energy cropping systems.

Economics is the study of resource allocation to maximize the welfare of people. Applica­tions range from (1) specific choices by individuals, to (2) decisions by a variety of business entities, (3) local, regional, national, and global market behavior, and (4) government poli­cies. In many economic applications, people are perceived to maximize their personal welfare or utility through their choices to invest, produce, save, or consume. People’s choices are constrained by the quantity of resources they have and by the level of available technology. Technology is defined here as the capacity to convert resources to goods and

Cellulosic Energy Cropping Systems, First Edition. Edited by Douglas L. Karlen. © 2014 John Wiley & Sons, Ltd. Published 2014 by John Wiley & Sons, Ltd.

services valued by people. As simplifying restrictions are relaxed, economic models are expanded to include optimization over time and to include risk and uncertainty. These basic ideas are applied to sustainable energy cropping systems in the following sections.

Sustainable systems are defined conceptually here as systems that are economically competitive, that are not dependent on excessive consumption of scarce resources, that are not dependent on excessive levels of detrimental emissions to the environment, and that are generally socially acceptable. Absolute thresholds for these definitions are not proposed here. Economic concepts of the trade-off between marginal changes in absolute thresholds and other determinants of human welfare are raised in this chapter.

Plantation Cropping Systems

It is not just trees as biomass for fuels that threatens forests and communities that depend on them. Many of the land acquisitions by foreign firms in Tanzania, for example, take land from traditional land holders and refugees for biofuel plantations [27]. The existing and proposed crops include jatropha, sugarcane, and white sorghum as well as oil palm and Croton magalocarpus, native to Burundi, Democratic Republic of Congo, Kenya, Malawi, Mozambique, Rwanda, Tanzania, and Uganda. The schemes that involved sugarcane and jatropha, an introduced species, acquired the most land. Sugarcane requires relatively productive land, while jatropha grows on marginal lands.

In the case of palm oil, land is often cleared for plantations of the export crop. As a result of concerns not only about ecosystem health but indigenous rights, particularly related to traditional communal land tenure, the Roundtable on Sustainable Palm Oil (RSPO) was developed. Of particular concern in land rights, which are part of all biomass fuel cropping systems, is that many of the issues revolve around who represents the impacted communities and exactly how to involve local stakeholders.

The implementation of RSPO standards has been fraught with challenges. The RSPO’s approach is pragmatic, as the diversity of actors and divergence of interests has necessitated a gradual, step-by-step approach to implementing change. Tensions exist between develop­ing country producers and developed country processors and retailers. Where standard-less market channels are still available, producers see no need to implement the very sustain­ability standards that they helped design as part of the RSPO process. NGOs criticize the pragmatic, stepwise approach and argue for more fundamental discussions regarding sus­tainability [28]. The legality and legitimacy of the RSPO is dependent on the inclusion of a wide variety of stakeholders and consensus-based decision making. However, pragmatic compromises often lead to a perceived undermining of the principles of sustainability. The resulting sustainability standards are less stringent. When NGOs feel like the key tenants of sustainability have been excluded, they refuse to endorse the standard, hence decreasing its legitimacy. This, in turn, compromises the legitimacy of the RSPO standard in the eyes of concerned external observers and the public [28].

As with many sustainability standards that involve resources on indigenous land, the RSPO strategy refers only to Free, Prior and Informed Consultation, despite continuing demands from indigenous peoples that only by adopting Free, Prior and Informed (FPI) Consent will fair and non-coercive negotiations between investors and affected communi­ties be possible. FPIConsent is currently under consideration in the ongoing formulation of the International Finance Corporation of the World Bank (IFC) Performance Standards strategy, and cannot be part of the palm oil strategy until this process is completed. Nor­man Jiwan of Indonesian NGO SawitWatch points out that “the IFC is a member of the RSPO, which recognizes FPIConsent, but the new strategy refers only to FPIConsulta — tion. This is effectively a breach of the RSPO code of conduct by the IFC, and means there will be far less incentive for IFC-backed companies to comply with the principles and criteria of FPIConsent” [29]. The difficulties of enforcement and the willingness of some signers of the RSPO to deviate from the principles and criteria undermine the legit­imacy of these sustainability standards, despite the massive efforts that have been put into developing them.

Effect of Source on Feedstock Quality

Because logging residues are often laid or piled on disturbed, exposed soil during harvesting and processing, either in-woods or at the roadside, and may also be dragged along skid trails during extraction, the ash content tends to be high and affects the quality and value of this feedstock source. It is especially important that machine operators know if logging residues are going to be used as biomass rather than burned for disposal because they can work to minimize contamination in piling, especially on the landing. A number of post-harvest methods for reducing ash content in order to meet quality specifications of different biofuel and bioenergy processes exist. The most common methods are: (1) using rotary trommel screens to reduce the percentage of fine, inorganic materials that damage mill dies and increase ash content, and (2) downstream blending of feedstock from different material sources to meet quality specification standards. For example, if ash content of a residue feedstock is 5% and needs to be at or below 2% ash to meet quality specs for a particular conversion process, blending of 20% logging residue with 80% cleaner feedstock (for example, a one-pass agricultural residue, or clean pulp chips in pre-processing) can achieve a blended fuel with quality specification of 1.8 % ash content, though using higher quality feedstock in blending is likely to drive up costs.

Regulating moisture content of woody biomass feedstock from logging residues is an important research and development area. Depending on the season of the year, local cli­mate, time between harvest and delivery, timing of processing, and species, the moisture content of cut slash and tops may vary from 12 to 50%. High or low moisture content may be desirable in final material specifications, depending on the conversion process. For example, aviation biofuels produced with a wet, thermochemical process are ultimately digested at high moisture content. For this reason, wetting dry feedstocks after transporta­tion may be desirable for some conversion processes. In contrast, densification of uniform feedstock biomass into energy pellets requires dry material. Dried, ground biomass that is stored for subsequent use may actually regain moisture from ambient air prior to conver­sion, necessitating proper storage. Reduction in moisture content tends to reduce per unit transportation costs for biomass and may increase its value if end users pay for feedstock on a dry basis. From a technical standpoint, developing logistic supply chains that deliver feedstock with appropriate moisture content requires development and validation of pre­dictive models that integrate tree and wood physiology (e. g., evapotranspirative drying as a function of local climate) with forest operations to consistently deliver a final product at required quality standards to meet conversion requirements. However, it may be more economically efficient to meet narrow feedstock specifications by centralized processing and drying at the facility rather than trying to meet them in the field.

Time and Risk

As the discussion here has shifted from deterministic models of production and profit to stochastic models with risk, the dimension of time was made explicit in the crop production process. The time between the crop planting decision and the sale of the crop was identified as a source of risk. Time is a critical dimension of biological processes. Longer periods between the planting decision and final sale of the product may allow for increased risk. More shocks to production and to markets may occur over a longer period of time. Therefore, decisions that commit farmers’ resources over a longer period to production of a specific crop may entail more risk. A subsequent section examines risk mitigation. Time is also an important underlying factor in the finance of inputs, including operating inputs such as seed and fertilizer, as well as longer-term assets such as machinery and land.

Agronomic Efficiencies and Management

Once the dedicated energy crop has been chosen and established, the supply chain must have a robust agricultural infrastructure to support it. The selection of dedicated energy crop species and mix will impact the agricultural infrastructure required to economically and sustainably operate the supply chain. Some energy crops require little to no modification of existing planters, harvesting equipment, and transport systems, while others will require improved or new technologies to improve the economics of the supply system. Crops that are planted using rhizomes or other rooted stock matter are a good example of this. Traditional planting of crops like miscanthus have required significant labor and time.

Recent advancements, however, have shown automated planters not only reduced the cost of establishment but in many cases actually improve establishment success rate. Many herbaceous crops can be harvested with existing hay and forage equipment that is generally available throughout most agricultural communities. However, some crops may require more specialized and less common harvesting equipment. One example of this is sweet sorghum, which requires cane-type harvesters.

Biomass consumers will require their feedstocks to meet certain specifications, including cost, moisture, delivered form, and particle size. The consistency in delivered feedstock will be critical, not only to the operation of the conversion facility, but also to the cost of the feedstock. For example, facilities will not be designed to allow farmers to deliver different bale sizes to a singular processing line. Biomass preprocessing equipment will likely be designed for specific feedstocks and to prepare the required delivery format. Variation from that format could cause a disruption in the supply chain.

In this new industry, the first few commercial scale cellulosic-based facilities will require tightly managed and highly efficient supply chains to minimize feedstock costs. In most cases, it is envisioned that these supply chains will be managed by the facility itself, an independent third-party operator, or producers, in the form of cooperatives. Commercial scale facilities will likely require significant investment in agricultural equipment that would make it difficult for individual producers to participate in the initial phases. Facilities that require round bale package formats may be more suitable to smaller producers as the capital cost of equipment is relatively small and similar to their current forage management operations. Facilities requiring a large square bale format or a chopped form from a forage harvester would probably prevent smaller producers from operating on their own, as the capital cost for equipment could be anywhere from three to ten times higher than that for conventional round bales. In these scenarios, third-party custom operators or operators employed by the conversion facility itself would be required to meet all required feedstock specifications. Additionally, not all land recruited for bioenergy crop production will be actively farmed or have owners that have the capabilities to conduct the operations for energy crop production and, therefore, custom operators will be required in those scenarios.

In commercialized supply chains, it is likely that some energy crop production will be carried out by farmers while some will be carried out by custom operators. Each has its benefits. Individual farmers tend to have more focus on their particular production acres, leading to more timely attention to production issues. Working with many individual farmers also has its challenges. Maintaining consistency, particularly in harvest, of crop conditions and packaging is made increasingly difficult with more operators and different pieces of equipment. Custom operations, however, create certain levels of efficiencies that are required to reduce cost in feedstock production. They also provide consistency in operations across a broad portion of the land being used to produce energy crops. Fewer machinery operators can lead to improved ability to train and reduce variation between operations. The consistency in quality and delivery package is of utmost importance to end users. A commercial scale biomass supply chain must be designed to minimize variation so that processing of biomass feedstock can be optimized. Additionally, landowners who have no interest in performing management tasks on their own land will also require custom operations.

Commercial scale energy crop systems must be able to deliver consistent quality. Consistency in delivery format and condition is critical, especially for first-generation commercial operations. Biomass conversion facilities will require as little variability as possible, whether that be in the feedstocks’ form of packaging or composition characteris­tics of the incoming feedstock.

Highway Hauling

The quickest way to communicate the key issues in highway hauling is with a simple analysis. The cost factors used in this example are representative, but they will be different in different local economies.

Truck cost is well defined by a mature trucking industry. Ownership cost plus operating cost (routine maintenance, driver labor cost, insurance, license, taxes, fuel) are known for short-haul operations. A truck can be used to haul gravel, logs, or hay bales and the short — haul cost ($/d) is approximately the same. The way to minimize truck cost ($/ton) is to maximize truck productivity (tons hauled per day, per week, or per year). Two issues are significant:

1. Tons per load.

2. Truck cycle time — time required to load, haul, unload, and return for the next load.

Hauling cost is defined here as loading cost plus truck cost plus unloading cost. The reader can quickly grasp the interaction of these three operations by considering the following example.

13.6.1 Truck Cost

Suppose it takes 40 minutes to load a truck and this truck travels 25 miles at an average speed of 45 mile/h. (This is a reasonable average speed for short hauls over rural roads.). It takes 40 min to unload the truck (no waiting in a queue) and then it returns 25 miles at 45 mile/h. The cycle time is 146 min = 2.4 h. In a 10-h workday, this truck can haul four loads.

Suppose the cost for the truck (ownership + operating) is $450/d and the cost of fuel is $3.50/gal. The truck averages 4 mile/gal, which is typical for short-haul operations. Fuel cost per load is:

(25 mile x 2)/(4 mile/gal) = 12.5 gal x $3.50/gal = $43.75/load The truck hauls four loads per day, thus the fuel bill is:

$43.75/load x 4 loads/d = $175/d

Total truck cost is:

$450/d (ownership + operating) + $175/d (fuel) = $625/d

If the load is 12 dry tons, the cost per dry ton is:


4 loads/d x 12 dry ton/load

Now suppose this same truck, hauling the same dry ton per load over the same distance, can be loaded in 10 min, not 40 min, and it is unloaded in 10 min, not 40 min. Now the cycle time is 86 min = 1.43 h and the truck can haul seven loads in a 10-h workday. (This comparison is an idealization — no travel delays are allowed, which is not realistic in a real-world situation. Also, the assumption that the truck never has to wait to be loaded and unloaded is unrealistic.)

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

$43.75/load x 7 loads/d = $306/d

Total truck cost is:

$450/d(ownership + operating) + $306/d (fuel) = $756/d The cost per dry ton is:


7 loads/d x 12 dry ton/load

Truck cost has been reduced from $13 to $9/dry ton, or 31%, by just loading the truck more quickly and unloading it more quickly.

Fuel cost ($306/d) is 40% of the truck cost. Fuel cost ($/dry ton) is a key parameter in the entire biomass logistics chain, not only truck cost, and it increases whenever the world market for transportation fuel produces a price increase. This linkage, more than any other single factor, limits the distance that raw biomass can be hauled, cost effectively, by truck.

Concentration Yards

It is possible to combine the maneuverability of small trucks with the long-haul efficiency of large semi-trailers by using a concentration yard to improve logistics [6]. Concentration yards, also known as sort yards for roundwood, are intermediate transfer points where material is collected. In the forest sector, they typically serve to improve logistics in transportation, processing, storage and marketing. For sites that are inaccessible to large chip vans, smaller trucks can be used to transport material over forest roads to a site with better road access. Biomass can then be transferred to large trucks with higher payloads to cover long on-road distances to end users. Similarly, when harvest sites are widely dispersed, difficult to access, and have relatively small amounts of material to process, it is costly to move processing equipment from site to site. In this case, logging residues and roundwood can be transported from harvest sites to a central location, stockpiled, and then processed in large volumes, which increases processing efficiency. This logic can also be applied to pretreatments, which are discussed in more detail later in this chapter. In some cases, processing and pretreatment equipment cannot be transported to harvest units due to poor road conditions or design limitations, making a concentration yard necessary. In both cases, gains in transportation and processing efficiency must be balanced against added handling costs, with concentration yards requiring additional unloading, handling, and re-loading components. In general, the costs of double handing low-value material like woody biomass are very difficult to recover by improving transportation efficiency, unless transportation costs are extremely high.

Concentration yards can also provide off-site storage of raw material, either in its raw or processed/pretreated form. This may be an attractive option in areas affected by seasonal road restrictions that limit access to material at harvest sites for part of the year. In addition, though less relevant for woody biomass than for high value roundwood products, concentra­tion yards can be used to improve efficiency in product marketing by separating aggregate deliveries of logs from harvest sites into fuelwood, pulpwood, and different grades of sawlogs for shipment to different facilities [7]. Typically, this is done on the log landing or at a facility that uses its log yard as a sort yard, shipping loads of logs to other facili­ties, but there are some conditions where it may make sense to incorporate this approach into woody biomass logistics. As with the storage and processing aspects of concentration yards, the added costs must be weighed against added revenues of product sorting and marketing. Though they are used in road-based logistics systems, concentration yards are a necessity when woody biomass is going to be transported by rail or ship. Though extremely rare because of its unfavorable economics, biomass removals by helicopter also require a concentration yard. For railroad transportation, rail-side concentration yards allow material to be stored on site and transferred efficiently into rail cars and shipped after sufficient material is stockpiled.

Greenhouse Gas Effects

Life cycle GHG emissions from a fuel source refer to the aggregate GHG production from both direct and significant indirect sources. The definition of life cycle greenhouse gas emissions established by the USEPA states that:

The term ‘life cycle greenhouse gas emissions’ means the aggregate quantity of greenhouse gas emissions (including direct emissions and significant indirect emissions such as significant emissions from land use changes),… related to the full fuel life cycle, including all stages of fuel and feedstock production and distribution, from feedstock generation or extraction through the distribution and delivery and use of the finished fuel to the ultimate consumer, where the mass values for all greenhouse gases are adjusted to account for their relative global warming potential [3].

Greenhouse gas emissions are expressed in mass of CO2 equivalent emissions per unit of fuel energy (typically kg CO2 eq per mmBTU), and are generally compared to a gasoline or diesel baseline scenario. This explains the “well to wheel” GHG reference within the RFS2 regulations, and is the reason approved biofuels must achieve at least a 60% GHG reduction compared to baseline scenarios. For cellulosic based biofuels, life cycle GHG emissions include those associated with growing, transporting, and converting feedstocks, as well as effects due to indirect land use changes and changes in soil carbon. Because cellulosic-based processes are just coming on-line in 2013 as this chapter is being written, the best projections for the United States are based on environmental analyses prepared by the USEPA [1] for the RFS2 mandate. Based on this analysis, switchgrass had net GHG emissions of —110% or -72%, for biochemical or thermochemical conversion, respectively. By comparison, corn stover had net GHG emission reductions of —129% or —92%, for biochemical or thermochemical conversion, respectively. Overall, a reduction in net GHG emissions of greater than 100% means the entire system will store carbon. Compared to the 2006 baseline, diesel from a Fischer-Tropsch process had net GHG emissions of —71% for switchgrass and —91% for corn stover. Estimates were made by the USEPA only for these two feedstocks because there was insufficient data for other cellulosic feedstock sources.

Although net GHG emissions of other crops are not as well understood as switchgrass, estimates have been made for other perennials that may be used for cellulosic feedstocks. In a study of 10 Midwestern states, Gelfand et al. [10] estimated that about 25% of the RFS2 mandated supply of liquid biofuels could be produced on 11 million ha of marginal and under-utilized land by growing successional mixes of herbaceous plants or hybrid poplar (Populus spp.) plantations. Both crops had net GHG emissions of —105% or less. Modeling of these areas indicated that enough feedstock could be grown within 80 km of potential biorefineries to produce these fuel amounts using secondary succession vegetation. Using marginal agricultural lands that are not in current crop production or which have low yields for conventional crops reduces both the carbon debt and the indirect land use effects of conversion of land use to cellulosic bioenergy crops [10].

In many cases, net GHG reduction depends on the type of energy sources used in the conversion facility. For instance, ethanol production from switchgrass can emit fewer GHGs by combusting the lignin component to produce the facility’s steam and electricity needs and thus eliminating the need for external energy sources [11,12].

Cost Analysis for 24-h Hauling Using Rack System Concept

The costs given in this section are presented without supporting detail. They were calculated using the procedures given in the ASABE Machinery Management Standard [3]. They are “best estimates” given current cost parameters. It is unlikely significant $/h cost reductions can be achieved for the various machines. All costs are given on a $/dry ton basis for operation of a bioenergy plant consuming 23 dry ton/h. The real challenge is to find a way that machine productivity (tons/operating hour) can be increased.

Some additional detail on the functionality of the various unit operations in the rack system logistics chain is given in Appendix 13.B. This detail will benefit those who

want a better understanding of the opportunities for improved productivity in individual operations.

13.9.1 Truck Cost Excluding Fuel

The assumed truck cost (tractor and trailer for hauling the two racks) is $630/d for a 24-h workday, which includes ownership plus operating cost, plus labor, but excluding fuel. Truck cost, excluding fuel, is:

Подпись: $4.49/dry ton$630/d

11.5 loads/d x 12.2 dry ton/load

13.9.2 Truck Fuel Cost

Fuel cost for the 25.4 mi average haul distance is

Подпись:(25.4 mile x 2)/(4 mile/gal) = 12.7 gal x $3.50/gal

Подпись: $3.64/dry ton$44.45/load

12.2 dry ton/load

13.9.3 Total Truck Cost

Total truck cost is:

Ownership and operating + Fuel = Total

4.49 + 3.64 = $8.13/dry ton

13.9.4 Load, Unload Operations

1. Handling racks at plant — 1.93 (workhorse forklift) + 1.02 (backup forklift) = $2.95/ dry ton

2. SSL operation — 3.66 (telehandler) + 0.98 (extra trailers) = $4.64/dry ton

3. Rack cost — cost of 230 racks = $1.80/dry ton

4. Storage yard at processing plant — $0.13/dry ton

5. Conveyor entering plant — $0.28/dry ton.

13.9.5 Size Reduction

Unroller-chopper — $5.76/dry ton

The costs given in Table 13.1 are grouped as follows:

Rack cost — All costs associated with the ownership and maintenance of the racks. Loading cost — All costs associated with the loading of bales into racks. These costs are referred to as “SSL operation costs”.

Table 13.1 Total cost for hauling, receiving facility operations, and size reduction for Rack System Concept example — 24-h hauling.


Cost ($/dry ton)



Loading at SSL



Extra drop-deck trailers


Truck cost


Unloading at plant

Workhorse forklift


Backup forklift


At-plant storage (Gravel lot with lighting)


Conveyor into plant


Unroller-chopper (Initial size reduction)




Truck cost — All costs associated with the ownership and operation of the trucks. Receiving Facility cost — All costs associated with the unloading of racks from trucks, placement of racks onto conveyor (or placement in at-plant storage), conveyor operation, operation of at-plant storage, and removal of racks from at-plant storage and placement on trucks for return to SSL.

Size reduction — All costs associated with the unloading of bales from the rack, operation of conveyor for single file delivery of bales to a size reduction machine, and operation of machine for initial size reduction.

Costs are as follows: truck (34%), SSL operations (20%), receiving facility operations (14%), size reduction (24%), and racks (8%). It is clear why the Rack System Concept was organized to maximize truck productivity — truck cost is the largest cost component. Truck cost plus SSL operations are $12.77/dry ton, or 54% of total cost. The receiving facility cost is $3.37/dry ton, only 14% of total cost. As with all other multibale handling system concepts, the Rack System Concept provides an opportunity for minimizing cost between the plant gate and the size reduction unit operation.

The total cost shown in Table 13.1 does not include the farmgate contract cost (production, harvesting, in-fleld transport, storage in SSL, profit to producer). The farmgate contract cost can be estimated from local data for production, harvest, and ambient storage of round bales of hay. In the Southeast United States, the key issue relative to the hay cost comparison is the difference in yield — switchgrass will yield about 4 ton/acre as compared to traditional hay species that yield about 2 ton/acre.