Biomass is a diffuse resource that requires significant investment to collect and transport to a biorefinery. There are numerous studies on biomass logistics. Recent developments in geographic information systems (GIS) and operations research (OR) allow for increasing level of detail in logistic studies. In general, logistic studies attempt to estimate the costs for biomass collection, storage, and transportation.

Researchers at Iowa State developed estimates for feedstock suppliers’ willingness to accept (WTA) selling price based on the following equation (Miranowski and Rosburg, 2010):

where CES stands for establishment and seeding costs, COpp represents land and biomass opportunity costs, YB is the biomass yield, CHM are harvest and crop maintenance costs, SF are stumpage fees, CNR are nutrient replacement costs, Cs is storage, DFC and DVC are the fixed and variable transportation costs, respectively, D is the distance to the biorefinery, and G are governmental incentives.

Biomass production incurs sunk costs in the form of establishment, opportunity, and nutrient replacement costs. Establishment costs can be ignored for biomass residue, but they are important for dedicated energy
crops. Biomass land and opportunity account for the loss revenue from growing alternative crops and land rental value. The removal of significant quantities of waste material would require nutrient addition in order to maintain soil quality.

Biomass collection varies between different types of feedstock. The corn, and sugarcane, industry has developed specialized machinery that collects grain at low cost: harvesting costs account for less than 15% of corn costs (Duffy, 2012). Collection costs for other types of feedstock have higher contributions to the overall cost. Harvesting cost estimates for corn stover, switchgrass, and miscanthus range between $14 and $84 per dry ton ($15 and $93 per dry ton) (Committee on Economic and Environmental Impacts of Increasing Biofuels Production, 2011), which could represent between 10 and over 80% of the delivered feedstock cost.

Cost estimates for biomass transport vary widely. They vary due to a lack of consistent data and because of the different methods employed. Transportation costs are typically reported as a total delivered cost or with fixed and variable components. DVC costs range between $0.09 and $0.60 per dry ton per mile ($0.06 and $0.41 per dry ton per km). DFC costs range between $4.80 and $9.80 per dry ton ($5.30 and $10.8 per dry ton).

Location is a major factor in the overall costs of delivering biomass to a facility. Land productivity, transportation networks, and storage facilities are a few of the parameters that vary significantly across various locations. GIS software provides display and analytical capabilities to investigate biomass supply chains. The US government provides a wealth of data in the form of GIS maps and dataset through their centralized portal www. data. gov. An example is shown in Fig. 2.3, which illustrates the distribution of total biomass resources in the US. There are high concentrations of biomass in the Midwest (stover), Pacific, Atlantic, and Gulf Coast (wood) regions, and around large metropolitan areas (MSW). This study estimates the biomass resources currently available in the United States by country. It includes the following feedstock categories: crop residues (5 year average; 2003­2007), forest and primary mill residues (2007), secondary mill and urban wood waste (2002), methane emissions from landfills (2008), domestic wastewater treatment (2007), and animal manure (2002). For more informa­tion on the data development, please refer to http://www. nrel. gov/docs/ fy06ostiZ39181.pdf. Although, the document contains the methodology for the development of an older assessment, the information is applicable to this assessment as well. The difference is only in the data’s time period.

The operations research field has developed mathematical formulas that evaluate biomass logistics within a geographical context. These formulas can estimate costs for a given region (city, municipality, county, state, agricultural district, nation, international) with improved relevance. Biomass supply formulations typically involve an objective function, several variables

2.3 US total biomass (grain, waste, wood) county-level supply (Milbrandt 2005, produced by the National Renewable Energy Laboratory for the US Department of Energy).

or parameters, and multiple constraints. For example, we could reduce

where i and j are subscripts representing biomass supply and biorefinery locations respectively, F is the amount of biomass shipped from i to j, n is the set of biomass supply counties, and m is the set of biorefinery locations. The Biomass constraint ensures that no more than the available amount of biomass gets shipped from a supply count, and the Demand constraint requires that the biorefinery receive enough biomass to satisfy their full capacity. This simple formulation can be expanded to include dynamic or temporal considerations, multi-level supply chains, and social and environmental parameters.