Agricultural Systems 130 (2014) 55–66

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Agricultural Systems

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The farm to biorefinery continuum: A techno-economic and LCAanalysis of ethanol production from sweet sorghum juice

http://dx.doi.org/10.1016/j.agsy.2014.05.0160308-521X/� 2014 Elsevier Ltd. All rights reserved.

⇑ Corresponding author. Tel.: +1 (919) 515 6744; fax: +1 (919) 515 6719.E-mail addresses: krcaffre@ncsu.edu (K.R. Caffrey), mwveal@ncsu.edu (M.W.

Veal), mschinn@ncsu.edu (M.S. Chinn).

Kevin R. Caffrey, Matthew W. Veal, Mari S. Chinn ⇑Biological and Agricultural Engineering Department, North Carolina State University, Campus Box 7625, Raleigh, NC 27695, United States

a r t i c l e i n f o

Article history:Received 24 September 2013Received in revised form 23 May 2014Accepted 27 May 2014Available online 17 July 2014

Keywords:Value-added agricultureBioenergyLife cycle assessmentTechno-economic evaluationEnergy audit

a b s t r a c t

This paper describes the economic, environmental, and energy issues of the farm to biorefinery contin-uum related to production of ethanol from soluble sugars recovered from sweet sorghum using theBE3 (bioenergy economics, energy, and environmental) model methodology. A comparative analysis offive process configurations was conducted to determine how process decentralization affects the totalproduction system. An increased integration of on-farm processing resulted in a moderate increase inthe breakeven sales price of ethanol ($0.08/L), however the substantial increase in value-added agricul-tural practices (approximately 180%) can offer greater returns to the farm operation. Benefits outside thescope of this analysis related to decentralized processing include: increased rural development, reduc-tions in transportation requirements, additional income to farmers, and dissipation of some environmen-tal impacts. Using a single parameter sensitivity analysis for those process configurations the greatesteconomic impacts were found to be related to conversion efficiency, crop yield, and press efficiency. Con-servative values were used throughout the process modeling procedure (e.g. crop yield, Brix level of juice,conversion efficiency, and by-product usage), yet with system optimization, breakeven sales price couldbe significantly decreased.

� 2014 Elsevier Ltd. All rights reserved.

1. Introduction

Recent research efforts in bioenergy production around theworld have increased as a result of energy security concerns, ruraldevelopment initiatives, potential for economic growth, and thegeneral agreement within the scientific community on global cli-mate change and its widespread implications. The general trendof renewable energy production is increasing in the US with bio-mass sources, specifically biofuels, contributing to this trend (USEIA, 2012).

At this time the vast majority of biofuels produced in the USoriginate from commodity crops that have historically been culti-vated for food and animal feed purposes (corn based ethanol andsoybean based biodiesel). Concerns have been expressed thatcontinuing to increase biofuel production using these commoditycrops can contribute to global food shortages (known commonlyas the food vs. fuel debate) (HLPE, 2013). Other concerns relatedto biofuel production include relatively high production costs, in-direct land use changes (related to a potential reduction inxports of food products), low net energy returns, and various

environmental implications. The use of dedicated energy crops(e.g. summer/winter annuals, perennial grasses, and short rotationwoody crops) has the potential to increase domestic energy produc-tion without interfering with current agricultural practices. Meet-ing production mandates (USA, 2007) and developing other valueadded uses of these potential feedstocks has led to major researchefforts around the world focusing on issues related to biofuels.

Sweet Sorghum (Sorghum bicolor (L.) Moench), an annual C4grass, is a promising dedicated bioenergy feedstock that exhibitsmany beneficial traits (e.g. drought tolerance, adaptable to varioussoil types, high yielding, short growth cycle, and low nutrientrequirements) (Koppen et al., 2009). There are three main catego-ries of sorghum: grain, forage, and sweet. These traditional charac-terizations represent the typical end use of the material, with thesweet cultivars historically being cultivated as a feedstock forsyrup production. Though these characterizations represent thegeneral end use they should be treated as descriptive instead offixed terms (Whitfield et al., 2012). With technological advance-ment in processing and conversion, the unique composition of thiscrop (soluble sugar, starch, and lignocellulosic fractions) lendsitself to multiple end uses in production of food, animal feed, bio-energy, and industrial products.

Sweet sorghum was thought to have originated in Ethiopia andhas now demonstrated growth in many areas around the world

56 K.R. Caffrey et al. / Agricultural Systems 130 (2014) 55–66

from semi-arid to humid climates (Koppen et al., 2009). Specificcultivars have been developed for different regions for particularpurposes, such as M81E developed in Mississippi, US in 1981 foruse in energy markets (Broadhead et al., 1981). In processing ofsweet sorghum, the crop can be differentiated into four main car-bohydrate streams: sugar rich juice, seed heads rich in starch,leaves for lignocellulose, and stalk bagasse which can be furtherdivided into the pith and rind portions for lignocellulose. If har-vested using a forage chopper then the benefit of these biomassstreams could potentially be combined and processed accordinglyas a single bulk material. The relative simplicity of first generationbiofuel production (sugar and starch feedstocks) makes it possibleto consider value added processing at the farm. On-farm process-ing of sweet sorghum is promising as the sugars present in thejuice have shown favorable fermentability characteristics withminimal required inputs or change in pH, after crude filtration(Bridgers et al., 2011).

The potential of using multiple biomass streams from a singlesweet sorghum plant, supports a theoretical ethanol yield on anacreage basis that is competitive with other proposed ethanol feed-stocks (Table 1). In comparison to sugarcane, a major sugar basedethanol feedstock, sweet sorghum does not have the same climateconstraints and can be grown throughout much of the US. The abil-ity to generate favorable yields of sweet sorghum from marginalland (Whitfield et al., 2012) allows existing unused cropland tobe used by farmers without disrupting current land use operations,making it more attractive than maize. The multiple carbohydratestreams, and potential for a wide range of products, give sweet sor-ghum an advantage over switchgrass. Additionally the by-productsof juice extraction (bagasse) and fermentation (vinasse) are usefulas animal feed, pulp feedstock (bagasse only), biochemical/thermo-chemical bioenergy feedstock, and soil additive (vinasse only). Thefast growth rate and annual crop characteristics offer farmers theflexibility to grow multiple crops in a single season (double crop-ping), change crops easily with low investment risk (compared toperennials), include sweet sorghum in a crop rotation with a tradi-tional commodity or cash crop, and/or use rented agricultural landto expand cropland availability.

As the bioenergy industry matures it becomes more apparentthat the transportation sector has a major influence on operationsof a centralized processing facility. Biomass material is a low valueproduct with a low bulk density and conceptually grown on vari-ous small farm units around a central operating facility (Juddet al., 2012). In addition to this, in most rural areas roads do notrun straight into a central hub but add a good portion of distancedue to circuity. Farm size, road circuity, and the amount of crop-land available for bioenergy feedstock production varies aroundthe US, however independent of the location of interest, a

Table 1Potential annual ethanol yield range from sweet sorghum and other proposed feedstocks

Sugar

Sweet sorghum Material (dry tonne) 2.2–21.2g

Ethanol (L) 1223–11,787a

Switchgrass Material (dry tonne)Ethanol (L)

Maize Material (dry tonne)Ethanol (L)

Sugarcane Material (dry tonne) 3.90–29.41f

Ethanol (L) 2168–16,352a

a 56 L per bone dry tonne (sucrose) 730 L per bone dry tonne (starch) (corn grain is 5b 355 L per bone dry tonne (cellulosic) (US DOE, 2011a).c 15% of total dry weight is grain head (Whitfield et al., 2012).d Switchgrass yield (Wullschleger et al., 2010).e Corn grain and stover yield (Shinners and Binversie, 2007).f Sugarcane and sugar yield (NASS, 2013) Hawaii represents the high end of the specg Sweet sorghum and sugar yield (Smith et al., 1987).

reduction in transportation costs can result in significant savingsto the overall system.

Another issue with the current agronomic system is that manyfarmers grow a particular crop for on-farm use, sale to a commod-ity market, or for a specified contract. This gives the farmer little tono involvement in the system outside of their own farm, meaningthe farmer will make decisions to maximize annual profits inde-pendent of downstream conversion and purification operations. Astrong working relationship between the farmer and end productproducer is important for the efficient operation of a bioenergyproduction system. Increased on-farm processing may also resultin additional money flowing into rural areas, instead of a large por-tion going to a corporate holding which may be centered inanother location.

A continuum exists of farm operations from feedstock produc-tion to further bioenergy processing operations (e.g. syrup produc-tion, fermentation broth, ethanol). This is especially important forsweet sorghum due to its high aqueous sugar and moisture contentwhich contributes to rapid spoiling. One study showed that thereare significant sugar losses from forage chopped sweet sorghumwithin hours of harvest, with values decreasing to nearly zero after2 days (Lingle et al., 2012). Because of this potential spoilage, thesugar rich material needs to be processed into a stable form asquickly as possible. Worley and Cundiff (1991) state the three mainchallenges faced with sweet sorghum as a bioenergy feedstock:collection of carbohydrates, concentration into a storable form,and economically viable conversion. Full system modeling withintegrated economic, energy and environmental impacts can beused to compare a host of different system configurations for pro-duction of ethanol from sweet sorghum and effectively evaluateoptions to minimize such challenges.

The properties of sweet sorghum and the available juice presentunique opportunities for substantial on-farm processing for etha-nol production. The objectives of this work were to model and ana-lyze economic, environmental and energy considerations using fiveprocessing scenarios that vary in the role of on-farm operations(scenarios are characterized by farmgate product): 1. Ethanol, 2.Fermentation Broth, 3. Syrup, 4. Ensiled Biomass, and 5. Biomass.Production of dehydrated ethanol is the end product for each ofthe scenarios including process steps of: juice extraction, fermen-tation, purification, storage, and some form of transportation ofproducts between production facilities.

2. Materials and methods

The analysis in this paper used a per unit basis to calculateappropriate costs, environmental effects, and energy usage withthe BE3 (bioenergy economics, energy, and environmental) model

in the United States (hectare basis).

Starch Cellulosic Total (L)

0.87–2.50a,c,g 3.56–18.73g

635–1825a 1264–6649b 4727–16,036g

4.2–19.1d

1491–6781b 1491–67811.16–6.54a,e 9.31–13.82e

847–4774a 3305–4906b 6008–8599e,a,b

9.23–44.56f

3277–15,819b 4490–23,071f

0% starch, assumed for all grain heads) (Hofstrand, 2009).

trum (assume bagasse is 50% MC wet basis).

K.R. Caffrey et al. / Agricultural Systems 130 (2014) 55–66 57

which was developed specifically to assess the continuum from on-farm to biorefinery operations for ethanol production from sweetsorghum soluble sugars for the five scenarios. This modelingapproach determined ethanol breakeven sales price with a techno-economic evaluation, mid-point environmental impacts with a lifecycle analysis approach, and energy usage through an energy audit.The breakeven sales price was defined as a minimum pricerequired to recover production costs (production cost/total pro-duction quantity), excluding additional revenue.

This analysis should be viewed as a comparative modelingstudy and not as a detailed evaluation of the specific systemsdescribed. It was assumed that the biorefinery equipment usedin all of the processes would be used for other operations through-out the year. An example of this is the use of biorefinery dehydra-tion equipment outside the harvest window for processing sweetsorghum bagasse. Additional considerations (e.g. farm size, biore-finery size/operations, farm distribution, and farm/biorefinerylocation) would be needed to evaluate each of these scenarios asstandalone entities.

2.1. BE3 model development

The BE3 process model was developed within Microsoft Excel�

to manage data and calculate outputs throughout bioenergy pro-duction, differentiated by operation (e.g. farm, transport, biorefin-ery, by-product usage). Options for different equipment, materialrequirements, and losses, each with associated costs, energy valuesand environmental impacts, were included. Mass balance was fol-lowed throughout taking into account solid material on a dry massbasis and volumetric liquid fractions. Land area (hectare) was usedas a functional base unit for comparison purposes. Specific techni-cal barriers related to the modeled scenarios were negated andassumed to have been overcome through research prior to com-mercialization. These assumptions are detailed with the corre-sponding scenarios (e.g. at-farm dehydration and syrupfermentation).

The entire system was divided into four operations: Farm,Transportation, Biorefinery, and By-product Utilization. Resultsincluded: cost, energy source, commodity usage, environmentalimpacts, and energy usage. For evaluation purposes, a volumetriccomparison (liter to liter) against gasoline was used as well asthe reductions related to use of by-products from the process (lig-nocellulosic bagasse).

Four potential by-product uses were made available in themodel: Local Heat, Electricity Feedstock, Cellulosic Fuel Feedstock,and Animal Feed (Table 2). By-products were taken to the point offeedstock for the specific industry with no end use calculationsmade. Vinasse material (also known as stillage) resulting fromthe distillation process was considered to be land applied andthe relative increase in soil fertility was assumed to be equal tothe handling costs associated (environmental impacts and netenergy use for the vinasse were also assumed to be net neutral).

Table 2Crop production processes and by-product usage factors and considerations.

Fundamental processes By-pro

Factor Consideration FactorLand cost 55% rented MoistuInsurance Similar to commodities EnergyHeadlands 8% additional croplandNutrient application (lb./acre) N: 44.8, P: 89.7, K: 89.7, Lime: 172.6 Local hHerbicide Aatrazine (2.3 L/ha) ElectriSeed 2.8 kg/ha celluloYield 15.7 BDtonne/ha Feed

Vinass

Considerable information has been discovered about the use ofvinasse in the sugarcane ethanol industry (Tauk, 1982) but withthe lack of specific knowledge concerning sweet sorghum theabove assumption was used.

2.2. Techno-economic evaluation

Machine cost assumptions and product inputs were used todetermine the ethanol breakeven sales price required for each sce-nario. The process outlined in Edwards (2009) was used to deter-mine a per unit cost of each of the operations/processes. All farmequipment was determined on a per hectare basis, while applicableper unit values were used for other equipment (i.e. pumps on aliter basis). Industrial equipment was calculated similarly to farmequipment, with the addition of associated installation costs(Aden et al., 2002). Using values from Humbird et al. (2011), spe-cific processing values were updated to represent improved pro-cess design guidelines for ethanol conversion. Discrepancies infeedstock handling systems described between Aden et al. (2002)and Humbird et al. (2011), limited use of equipment specificationsfor this handling system. Neither Aden et al. (2002) nor Humbirdet al. (2011) were used as ‘blackbox’ models for operations of thebiorefinery; instead, specific equipment specifications from thereports were used, as applicable to the scenarios being evaluated.

Additional references that provided economic values are desig-nated in Additional References.

2.3. Life cycle assessment (LCA)

The general LCA methodology that follows ISO 14040 (ISO,2006a) and 14044 (ISO 2006b) is outlined in Fig. 1. A life cycleinventory was constructed using the NREL US Life Cycle InventoryDatabase (US DOE, 2011b) and the US Environmental ProtectionAgency (EPA)’s TRACI (Bare et al., 2003) impact assessment toolwas used to calculate mid-point environmental impacts (Table 3).The boundary of the LCA was set around fuels, fertilizer, and trans-portation. Areas such as machinery, externalities (e.g. below-ground carbon sequestration), additional impacts (e.g. water andland use), building supplies, crop management (e.g. nutrient vola-tilization/leachate, chemical displacement, etc.) and end-pointproduct usage were not considered in this analysis. Carbon dioxideproduction from fermentation was assumed to be marketed as aby-product, though no economic value was attributed due to lackof specific data on fermentation characteristics. A single iterationapproach was used to determine inventory values for each of theareas considered within the boundary of this study.

2.4. Process energy audit

An energy audit was conducted that focused on energy userelated to specific inputs (fertilizer, chemicals, and transport).Energy values related to machinery production, employee habita-

duct utilization

Considerationre content (wet basis) 22.7%Value 18.4 MJ/BDtonne

Economic basis Impact/energy Uniteat Natural gas Natural gas MJ (LHV)

city Coal Coal MJ (LHV)sic Corn stover Silage calc. BDtonne

Forage sorghum Silage calc. Wtonnee Land application

Goal and Scope DefinitionGoal

Use: Comparison of scenariosRationale: Quantitative assessment of environmental issuesAudience: Scientific communityPublic Disclosure: Yes

ScopeSystem: Sweet Sorghum ethanol productionFunction of systems: Ethanol productionFunctional unit: Land Area (hectare)System boundary: Fuels, Fertilizer, and TransportationAllocation procedure: Single allocationImpact categories/methodology: Mid-pointData requirements: Various (see text)Assumptions: Various (see text)Limitations: Various (see text)Data quality: Best publically available sourcesCritical review, if any: None (currently)Type/format of final report: Scientific Journal

Life Cycle Inventory Analysis (LCI)Data Collection: NREL US Life Cycle Inventory DatabaseData Calculation: Single iteration (imbedded energy uses)Allocation of Flows/Releases: By-Product as feedstock reduction

Life Cycle Impact Assessment (LCIA)Data Source: EPA TRACI model (mid-point assessment)

InterpretationFormat: Scientific Journal Publication

Fig. 1. Life cycle framework used for the BE3 model (modified from ISO 14040).

Table 3Mid-point environmental impacts.

Mid-point category Unit

Air emissionsGlobal warming kg CO2 equiv.Acidification kg H+ mole equiv.HH criteria kg PM10 equiv.Eutrophication kg N equiv.Ozone depletion kg CFC-11 equiv.Smog kg O3 equiv.Ecotoxicity PAF m3 dayHuman health (cancer/non-cancer) Cases

Water emissionsEutrophication kg N equiv.Ecotoxicity PAF m3 dayHuman health (cancer/non-cancer) Cases

WasteSolid waste-landfill kgSolid waste-tailings kgSolid waste-reuse kgChemical waste-landfill kg

Resource useCoal MJNatural gas MJCrude oil MJUranium oxide MJ

58 K.R. Caffrey et al. / Agricultural Systems 130 (2014) 55–66

tion, land use change (direct or indirect), and other contributingfactors were not considered in this analysis. Crop seed and fermen-tation yeast values were not included based on the assumptionthat these would be produced with existing equipment on site,with minimal energy requirements. Energy values were calculatedsimilar to the life cycle assessment methodology. Direct and pro-cess energy values (lower heating value (LHV) basis) used in themodel are listed in Table 4.

Values for transportation were taken from the TransportationEnergy Data Book (US DOE, 2012b), from which the tonne-kilome-

ter energy use associated with both solid and liquid transportationwas calculated. Based on average bulk densities and assumed truckload volume capacities and weight restrictions, truck capacitieswere assumed to be weight limited for liquids and volume limitedfor solids (at ½ weight capacity). Process energy values for chemi-cals and nutrients were calculated from values in Shapouri et al.(2002).

2.5. Production scenarios

Five scenarios were defined to represent the continuum fromthe farm to the biorefinery (central operations) for production ofethanol from sweet sorghum juice (scenarios characterized byfarmgate product): 1. Ethanol, 2. Fermentation Broth, 3. Syrup, 4.Ensiled Biomass, and 5. Biomass. The agrarian nature of bioenergyproduction necessitates that certain processes are shared amongeach of the scenarios, referred to as crop production processes(Fig. 2a). Included in this analysis was the use of by-products cre-ated during the processes, which were assigned to various path-ways in each of the scenarios as related to the point ofproduction (Fig. 2b). Table 2 outlines important considerationsfor crop production processes and by-product usage as shown inFig. 2.

Independently of the scenario for juice conversion to ethanol, orother potential conversion processes, the material needs to gothrough certain processing operations at a farm site (whether thisis a large plantation or many scattered smaller farms). The cropproduction processes shown in Fig. 2a represent the operationsup to the harvest and in-field transport of the biomass materialsfrom the field. A forage chopper harvest system was selectedinstead of billet or whole stalks due to the maturity of the harvesttechnique and relative low cost. A general process flow for each ofthe by-product usage pathways is shown in Fig. 2b. The vinassewas assumed to be field applied for all scenarios, with the cost offield application balancing the economic benefit from improved

Table 4Energy audit data: lower heating values (LHV).

Category Direct energy (MJ/unit) Process energya (MJ/unit) Total energy (Btu/unit) Unit source

U.S. conventional diesel 35.8 2.8 38.6 L US DOE (2012a)Conventional gasoline 32.4 3.1 35.4 L US DOE (2012a)Liquefied petroleum gas (LPG) 23.7 7.0 30.65 L US DOE (2012a)Residual fuel oil 39.1 2.8 41.9 L US DOE (2012a)Natural gas 36.6 2.1 38.7 M3 US DOE (2012a)Electricity 3.6 0.4 4.0 kWh CalculatedBituminous coal 26.1 0.5 26.7 kg US DOE (2012a)Transportation NA NA 14.1 km US DOE (2012b)

Liquids NA NA 0.6 Tonne km CalculatedSolids NA NA 1.2 Tonne km Calculated

Nitrogen NA 0.7 40.7 kg Shapouri et al. (2002)Phosphorous NA 0.7 2.5 kg Shapouri et al. (2002)Potassium NA 0.7 5.5 kg Shapouri et al. (2002)Herbicide NA 0.7 261.6 kg Shapouri et al. (2002)Insecticide NA 0.7 269.4 kg Shapouri et al. (2002)

a Process energy calculated from using energy content and following the process similar to LCA data (nutrients and chemicals are direct from source).

(A) Crop Production Processes (B) By-Product Usage

Farm Land Use

Tandem Disk

Fertilizer Spreader

Bulk Cart

Row Crop Planter

Boom Sprayer

Row Cultivator

Forage Harvester

Forage Wagon

Farm

Key

Bagasse

Vinasse

Forage Wagon

Windrow

Round Baler

Outdoor Storage

Tractor w/Spear

Local Heat

Forage Wagon

Bunker Storage

Front End Loader

Forage Wagon

Animal Feed

Forage Wagon

Windrow

Square Baler

Telehandler

Bale Transportation

Cellulosic/Electricity Feedstock

Transportation

Vertical Plastic StorageLiquid

Transportation

Land Application

Fig. 2. Process flow of crop production processes and by-product usage [A – crop production processes, B – by-product usage].

K.R. Caffrey et al. / Agricultural Systems 130 (2014) 55–66 59

soil fertility, and thus negated in all scenarios. There are variousbenefits related to land application, including nutrient recycling(mainly potassium), increased pH, soil structure improvements,greater water retention, and development of some soil microbes(Amaral et al., 2008). High application rates of vinasse (greaterthan 300 m3/ha) have been shown to have the potential forgroundwater contamination issues (UNICA, 2007), though propersoil and water testing is important for all land application opera-tions. Although a simple process flow for land application of vin-asse is included in Fig. 2b, all costs, energy, and environmentalimpacts are assumed to be equivalent to the benefits. By-productusage for each of the scenarios was related to the location ofbagasse production (Fig. 3), with select process considerations forall scenarios given in Fig. 4.

The process flows in Fig. 3 do not represent all input valuesrequired in the model used for this analysis, but the primary equip-ment and processes used are presented for each scenario. The

different scenarios present various stages of operations at specificlocations from the farm to the central operations facility, withthe portion of the processing performed on the farm as opposedto a central operations facility shifting across the scenarios. Themajority of processing taking place at a central facility (Scenario5) is considered the norm for most bioenergy production processes.A basic process flow with some pertinent input parameters for theanalysis is shown in Fig. 4.

The first scenario represents complete production of ethanol atthe farm site (Fig. 3a). For this analysis it was assumed that amolecular sieve system could be incorporated to reach 99.5% pur-ity (required for the blending of ethanol with gasoline) at a costsimilar to that of an industrial facility. Though not taken intoaccount in this analysis, a more realistic process model mayrequire some broker, or integrator, that would deal with multiplesmall on-farm producers for aggregation, transportation, and addi-tional purification. This may be a third party entity, a larger farm

Permanent Liquid Storage

Crop Production Processes

Short Term Pile Storage

Roller Press

Vertical Plastic Storage

Fermentation

Distillation Column

Molecular Sieve

Ethanol Transport

A

Biomass Transport

Short Term Pile Storage

Belt Press

Fermentation

Distillation

Molecular Sieve

Permanent Liquid Storage

E

EA, B, C

Silage Storage

Ensiled Biomass Transport

D

Broth TransportB

B

Syrup Production

Permanent Liquid Storage

Syrup Transport

C

C

B, C, D, E

D

Transportation

Biorefinery

Farm

Key

Fig. 3. Process flow of selected scenarios (scenarios set as farmgate products, with corresponding bagasse use) [A – ethanol (local heat), B – fermentation broth (animal feed),C – syrup (electricity feedstock), D – ensiled biomass (cellulosic feedstock), E – biomass (cellulosic feedstock)].

Crop Produc�on

Juice Extrac�on

Fermenta�on

Purifica�on

Ethanol Transport

Broth Transport

Syrup Produc�on

Syrup Transport

Fermenta�on Purifica�on

Ensilage Storage

Ensiled Biomass

Transport

Juice Extrac�on

Biomass Transport

Farm Transport Biorefinery TransportDistance: 80.5 km Distance: 161 km

Primary Fuel: Diesel Primary Fuel: Diesel Primary Fuel: Electricity Primary Fuel: Diesel

Fuel: Bagasse

Fuel: Bagasse

Efficiency.: 85% theore�cal

Yeast: 0.26 g/LTime: 5 day

Efficiency.: 55%

Efficiency.: 45%

Density: 1.41 kg/L

Density: 1 kg/L

Density: 95 kg/m3Sugar Loss: 30%

Syrup Brix: 45°

Scenario 1: Ethanol

Scenario 2: Fermenta�on Broth

Scenario 3: Syrup

Scenario 4: Ensiled Biomass

Scenario 5: Biomass Density: 95 kg/m3

Density: 0.79 kg/L

Efficiency.: 85% theore�cal

Yeast: 0.26 g/LTime: 1 day

Juice Brix: 10°

Juice Brix: 10°

Denaturant: 5% vol.

Denaturant: 5% vol.

Fig. 4. Simplified process flow of scenarios with pertinent inputs parameters.

60 K.R. Caffrey et al. / Agricultural Systems 130 (2014) 55–66

owner, an existing biorefinery operation, or the specific blendingoperation. With bagasse being available at the farm site it wasassumed that the producer would sell, or use, the material as a heatsource in the local area.

For the second scenario, the sorghum juice is fermented at thefarm site, then the fermentation broth is trucked to the biorefineryfor processing (Fig. 3b). There was the potential for some addi-tional processing of the fermentation broth at the farm to removesome moisture, thus reducing transportation costs, but this wasnot considered. The bagasse material from the farm was used asan animal feed material in the local area.

Scenario three assumes that each farm produces syrup, ormolasses, from their own sweet sorghum juice, then the syrup istransported to the biorefinery for rehydration and processing(Fig. 3c). The syrup production process was simplified to only anevaporation step, where in reality it would be closer to the processdescribed in Reddy et al. (2009) (e.g. chemical addition, froth

removal). With the long-term storability of syrup and reductionin transportation requirements, this scenario could be combinedwith cellulosic conversion, where the syrup may be incorporatedinto processing throughout the year. Though dilution of the syrupputs the sugar content to a level where microbial fermentation ispossible, difficulties can occur related to use of sugars potentiallyaltered during the evaporation process (Bridgers et al., 2011). Fur-ther research may be needed in the processing required to preparesyrup to ensure the integrity of the sugars present are maintained,these constraints were not taken into account in this analysis. Forthis scenario, bagasse was sold as an electricity feedstock, whetherthis is used at the biorefinery or at some third party site was notconsidered.

Scenarios four and five represent nearly full processing at thebiorefinery (Fig. 3d and e). The difference being that scenario fourhas the material stored as ensiled biomass at the farm prior totransport to the biorefinery, while scenario five incorporates the

Table 5Point of ethanol production economic results for each scenario (hectare basis) (original values).

Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5

Ethanol Fermentation broth Syrup Ensiled biomass BiomassEthanol produced (L) 1480 1487 1566 1292 2255Bagasse Sold (BD tonne) 11.4 13.8 15.0 14.5 15.2Bagasse use Heat Animal feed Electricity feedstock Cellulosic feedstock Cellulosic feedstockTotal production cost ($) $1932 $1799 $1645 $2055 $1927Bagasse value ($/BD tonne) $60 $63 $38 $46 $46Ethanol break-even ($/L equiv.)a $0.55 $0.41 $0.45 $0.70 $0.36

a On a volumetric LHV basis a gallon of ethanol has 65.75% of the energy of gasoline (ethanol 21.27 MJ/L, gasoline 32.36 MJ/L).

$0.84

$0.62 $0.69

$1.07

$0.54

$0.00

$0.20

$0.40

$0.60

$0.80

$1.00

$1.20

$0.00

$500.00

$1,000.00

$1,500.00

$2,000.00

$2,500.00

Ethanol Fermenta�on Broth

Syrup Ensiled Biomass

Biomass

Min

imum

Eth

anol

Sal

es P

rice

($/L

)

Proc

essi

ng C

ost (

$/ha

)

Net Ethanol Processing ($/ha) Baggasse Value ($/ha) Breakeven ($/L)

Fig. 5. Point of ethanol production process cost and minimum ethanol sales price(hectare basis).

K.R. Caffrey et al. / Agricultural Systems 130 (2014) 55–66 61

transport of fresh biomass to the biorefinery. Through the ensilageprocess, chopped biomass can be stored for long periods, but ensil-ing reduces biomass sugar content, affecting the amount of ethanolthat can be achieved. Schmidt et al. (1997) found that losses in thesoluble sugar content of sweet sorghum during ensiled storage canbe limited to 30%, through the use of specific enzymatic additives,or to zero through the use of formic acid. Use of formic acid as astabilizer was not included due to the cost and need for additionalresearch to determine operational considerations. As such, 70% ofthe sugar concentrations were assumed to be available in themodel for scenario four, resulting in the yield differences observed.Additional products derived from the enzymatic cocktail were notconsidered due to lack specific knowledge on composition and pro-cessing. Though some of the compounds produced from ensilage(e.g. acetic acid, lactic acid) have an inhibitory effect on fermenta-tion (Limtong et al., 2000) this was assumed to be able to be over-come through proper strain selection and enzymatic addition tothe ensilage process.

An increase in press efficiency was assumed for both of thesescenarios compared to that of on-farm operations due to theincrease in scale (Fig. 4). Use of high extraction efficiencies (45%on-farm, 55% biorefinery) on a mass basis were considered realisticfor this analysis since increases in efficiency are expected fromequipment commercialization. By-product bagasse material waspresent at the biorefinery already so material not used for processheat was used as a cellulosic feedstock on site for both scenarios.

Final results of this analysis were at the point of ethanol pro-duction, not at the point of use. This means that when comparedto gasoline on a per liter basis it does not take into account enduse (i.e. combustion), where major differences in some of theenvironmental impacts can be seen. The BE3 model was used todetermine values related to each of the scenarios. The model wasrun twice, using both original data (Aden et al., 2002) and updatedvalues (Humbird et al., 2011) focused on the biorefinery values, inwhich limited farm site calculations were updated (pump opera-tions and evaporation systems). Due to the large changes in the

updated report used from the National Renewable Energy Labora-tory (Humbird et al., 2011) it was deemed necessary to reportsome values from both runs of the model.

Additional references that provided process modeling valuesare designated in Additional References.

2.6. Sensitivity analysis

A single parameter economic sensitivity analysis was conductedin MATLAB

�using a modified version of the BE3 model. The model

was recoded into MATLAB�

for its ability to quickly compute mod-ified parameters across a wide range of scenarios and by-productutilization pathways. Microsoft Excel

�was used as the primary

modeling environment to allow a user friendly interface, but MAT-LAB

�was incorporated for the sensitivity analysis due to its robust

computational capabilities. The sensitivity of economics alone waschosen instead of energy or any of the environmental impacts, dueto its importance to producing biofuels at or below current fossilfuel prices. An inclusive single ranked parameter combining eco-nomics, environmental impacts, and energy was not included, withuser-defined metric weighting assumed to be outside the scope ofthis analysis. The scenarios selected (Fig. 3) represented a contin-uum from farm to biorefinery operations and were considered incombination with each by-product utilization pathway listed inTable 2. The minimum ethanol sales price change was determinedfrom a 10% modification in select parameters: conversion effi-ciency, crop yield, press efficiency, fertilizer cost, diesel fuel cost,and material loss.

3. Results

3.1. Economic analysis

A major difference in the assumptions used in these calcula-tions between the central operations and de-centralized (on-farm)operations, was the press efficiency. As seen in Fig. 4, the central-ized operations (Scenario 4 and Scenario 5) used a press efficiency(i.e. juice extraction) of 55% of the total mass of forage choppedsweet sorghum, while the other farm-scale press operations used45% (Scenario 1, Scenario 2, and Scenario 3). This was used to rep-resent the difference in scale and efficiency between on-farm andindustrial processing equipment. This effect was observed in thelarge difference in ethanol yield among the scenarios, assuminguniform sugar content in the juice (Table 5). The loss of solublesugars during the ensilage process as part of scenario four also con-tributed to a lower ethanol yield (Table 5).

There was a range of ethanol production values (1292–2255 L),total production costs ($1645–2055 per hectare), and bagasse val-ues ($38–63 per bone dry tonne) across the five scenarios investi-gated (Table 5). A consistent metric for comparison acrossscenarios was the use of the ethanol breakeven sales price shownin Fig. 5, which ranged from $0.54 to $1.07 per liter.

The breakeven sales price of ethanol in each of the scenarioswas relatively high compared to the $0.46/L goal of the Office of

62 K.R. Caffrey et al. / Agricultural Systems 130 (2014) 55–66

Biomass Programs Multi-year Performance Plan (US DOE, 2011a)but the values shown for scenario five were comparable to the$0.57/L minimum ethanol sales price reported by Humbird et al.(2011) for cellulosic production of ethanol from corn stover(Fig. 5). The values shown in scenario four were considerablyhigher than the rest of the values (Fig. 5) due to the high cost ofensiled storage, and the reduction in free sugar content duringthe ensilage process (Schmidt et al. 1997).

When using select updated values from Humbird et al. (2011)compared to model values generated using Aden et al. (2002)(Fig. 5), all scenarios except for scenario one showed an increasein total production costs. This reduction in scenario one was attrib-uted to a reduction in pump costs related to on-farm processing.The greatest increase ($361/ha) in production cost using updatedvalues was seen for scenario three due to an increase in the costof evaporation equipment. Limited updated values from Humbirdet al. (2011) were incorporated due to the shift in processing sys-tem configuration, which did not reflect well with the sorghumjuice conversion scenarios.

3.2. Environmental Impacts

Select environmental impacts were compared among the sce-narios to further investigate the continuum from farm to biorefin-ery operations (Fig. 6). On a liter to liter basis of gasolineequivalents, all scenarios showed higher levels of eutrophication(air) and ozone depletion values than gasoline due to the highamount of diesel required for operations and nutrient production(Fig. 6b and d). Ethanol production compared to gasoline showedreduced solid waste and fossil fuel depletion for all scenarios(Fig. 7a and c).

(A) Solid Waste- Landfill (kg/ha) (B)

(C) Fossil Fuel Depletion (MJ/ha) (D) Ozo

-150

-100

-50

0

50

100

150

200

250

300

350

Solid

Was

te (k

g/ha

)

00.10.20.30.40.50.60.70.80.9

1

Euto

rphi

cati

on a

ir (k

g N

eq/

ha)

-4.E+07

-3.E+07

-2.E+07

-1.E+07

0.E+00

1.E+07

2.E+07

3.E+07

4.E+07

5.E+07

6.E+07

7.E+07

Foss

il Fu

el D

eple

tion

(MJ/

ha)

0.0E+00

5.0E-07

1.0E-06

1.5E-06

2.0E-06

2.5E-06

3.0E-06

3.5E-06

Ozo

ne D

eple

tion

(kg

CFC-

11 e

q/ha

)

Fig. 6. Select point of ethanol production environmental impacts (hectare basis) [A – solidair].

Scenario one showed a net reduction in solid waste and fossilfuel depletion (Fig. 6a and c) due to its by-product use as a localheating product (replacing natural gas). Use of scenario one wasproblematic as a comparison to other scenarios because of thepotential technological constraints of ethanol purification on thefarm scale. Producing ethanol on-farm from sweet sorghum juicehas been shown to be feasible (Bridgers et al., 2011) but purifica-tion to 99.5% may still be problematic (or at least extremely costly).

3.3. System differentiation

The analysis of a system as a cumulative unit sheds light onwhat is encompassed in generating the final end product; howeverthe actual system is comprised of various unit operations that varyin impact. One way to differentiate and break down the operationsof the system scenarios described in this work was by location ofoperations: farm site, transportation, biorefinery, and by-productutilization. It was feasible to assume the by-products would beprocessed at either the farm site or biorefinery but since this oper-ation varied among the scenarios it was important that it be trea-ted as an independent operation. The costs and energy utilized wasdifferentiated by location for each of the scenarios (Fig. 7).

Regardless of scenario, a large portion of the total process costoccurs at the farm site (37–92% of total costs) (Fig. 7b). An increasewas seen in both transportation and biorefinery costs as the systemmoved more towards fully centralized operations. Energy utiliza-tion was dominated by the transportation sector (Fig. 7b) exceptfor scenario one, where only a finished product was transported.The general trend among scenarios was similar between differen-tiated energy and costs, yet transportation dominated energy useas the system moved towards central operations (Fig. 7a and b).

Eutrophication- air (kg N equivalent/ha)

ne Depletion- air (kg CFC-11 equivalent/ha)

Total

By-Product Reduction

Ethanol Fraction

Gasoline Equivalent (L to L)

waste-landfill, B – eutrophication-air, C – fossil fuel depletion, D – ozone depletion-

(A) Differentiated Energy Use (MJ/ha) (B) Differentiated Processing Cost ($/ha)

0.E+00

1.E+04

2.E+04

3.E+04

4.E+04

5.E+04

6.E+04

Farm Transporta�on Biorefinery By-Product Usage

Ener

gy U

se (M

J/ha

)

$0

$200

$400

$600

$800

$1,000

$1,200

$1,400

$1,600

$1,800

$2,000

Farm Transporta�on Biorefinery By-Product Usage

Proc

ess

Cost

($/h

a)

Ethanol

Fermenta�on Broth

Syrup

Ensiled Biomass

Biomass

Fig. 7. Select point of processing cost and energy use per sector (hectare basis) [A – differentiated energy use, B – differentiated processing cost].

K.R. Caffrey et al. / Agricultural Systems 130 (2014) 55–66 63

This same trend in significance of influence of transportation-related values was observed in both the total and differentiatedproportion of CO2 equivalents produced for each of the scenarios(Fig. 8).

The assumed transportation distance between the farm andbiorefinery may be considered relatively high (80.5 km) for someregions and supply chains (Fig. 4). Using a circuity factor of 1.2(Ballou et al. 2002), this amounts to an approximately 100 kmradial collection area. This area would produce enough biomass

Ethanol (1134

Fermentation Broth (1491 kg CO 2 eq

(D)Ensiled Biomass (1926 kg CO2 equiv.

3%0%

14%

Farm Site Transportation Bio

66%

28%

3% 3%

41%

45%

7%7%

(B)

(A)

Fig. 8. Point of ethanol production global warming potential for each scenario by differeensiled biomass, E – biomass].

material to supply a 1683 MT/day cellulosic facility (25% agricul-tural land, 5% inclusion rate, 350 day/year operation, 15 dry MT/ha). With similar potential ethanol yields for sweet sorghumbetween soluble sugar and cellulosic portions (Table 1), thiswas considered a realistic assumption. Calculations of CO2 equiv-alent production from Fig. 8 for scenario five at half that distance(40.25 km) estimated a total of 1585 kg CO2 equivalents per hect-are, with transportation accounting for 34% of the total value.This still showed that transportation was a major contributor to

kg CO 2 equiv.)

uiv.) (C) Syrup (1415 kg CO2 equiv.)

) (E)Biomass (2127 kg CO2 equiv.)

83%

refinery By-Product Utilization

60%24%

4%12%

33%

51%

8%8%

ntiated location (hectare basis) [A – ethanol, B – fermentation broth, C – syrup, D –

64 K.R. Caffrey et al. / Agricultural Systems 130 (2014) 55–66

the global climate change metric and there are benefits associ-ated with decentralized production on a land area basis (perhectare basis). When values were recalculated at this lower trans-portation distance for scenario two (1282 kg CO2 equiv./hectare)and scenario five (1585 kg CO2 equiv./hectare) on a per unit eth-anol basis, increased centralized processing from scenario five(0.70 kg CO2 equiv./L) reduced values compared to that of sce-nario two (0.86 kg CO2 equiv./L). The reduced transportation dis-tance (40.25 km) decreased the CO2 equiv. per unit ethanol ratioof scenario two to scenario five from 0.94 to 0.81 (80.5 km: 0.94/1, 40.25 km: 0.7/0.86). This reduction in emission ratio demon-strates the importance of the impact of transportation on the cen-tralized processing scenarios.

3.4. Sensitivity analysis

Using breakeven sales price, the average cost to produce dehy-drated ethanol was lowest using biorefinery operations (Table 6).The choice in by-product utilization pathway had a major impact,with local heat production having an average 16% reduction fromthe mean breakeven sales price and electricity feedstock having a21% increase (Table 6). Assuming a dehydrated ethanol sales priceof $0.57/L (Humbird et al. 2011) the only scenarios that showed apositive economic gain were biorefinery operations (excludingcoupling with electricity feedstock), farm fermentation withlocal heat production, and syrup production with local heatproduction.

Though a number of factors exist that can affect the final break-even sales price, six were chosen for sensitivity analysis: diesel fuel($/L), fertilizer cost ($/ha), press efficiency (% weight removal), con-version efficiency (% of theoretical conversion rate), crop yield (BDtonne/ha), and material losses (% weight or volume). Each of theseparameters was analyzed to determine the effect of a ten percentmodification (+/-) on the breakeven sales price. These parameterswere modified within the model boundary and their effects onother parameters was not determined (e.g. an increase in dieselcost would increase fertilizer costs, the additional cost requiredto achieve a higher press efficiency, etc.). The greatest average costreduction across all scenarios and by-product utilization pathways

-$0.10 -$0.05 $0.00 $0.05

Change in Price from Mean ($/L)

Parameter 10% increase

Fig. 9. Breakeven ethanol production cost sensitivity analysis (BEPC mean

Table 6Scenario and by-product utilization comparisons.

Scenario Mean breakeven ($/L)

Farm production $0.85Farm fermentation $0.69Syrup production $0.67Ensilage storage $0.79Biorefinery operations $0.57

would be seen from an increase in conversion efficiency and thelowest from a decrease in material losses (Fig. 9).

From the results shown in Fig. 9, it was seen that the greatestreductions were observed in areas where further research anddevelopment can have the greatest impact: press efficiency, con-version efficiency, and crop yield. Cost of diesel fuel and fertilizerwere considered outside the control of the producer and had lim-ited impact while material lost during processing was shown tohave a minor effect on the ethanol breakeven sales price.

4. Discussion

The current vision for bioenergy is the production of biofuels atcentrally located facilities producing fuel year round. For starchbased commodity crops, like corn, this has been shown to be suc-cessful in areas such as the Midwestern US. When working withcrops high in soluble sugars, such as sweet sorghum, there arepotential challenges to centralized operations, but an increasedviability for decentralized processing. The authors recognize thatthe addition of a biorefinery (or increased on-farm production)can have external benefits to the community both economicallyand socially. Though worthy of additional research, external com-munity benefiters were considered to be outside the scope of thisanalysis. There are however, a number of benefits in a move fromlarge, centrally-located biorefineries to a de-centralized systemthat are briefly discussed qualitatively, including reduced indus-trial safety concerns, reduction in transportation needs, farmerbuy-in, increased rural development, and reduced environmentalimpacts.

Safety is of great importance in the agricultural sector. Farmoperations are allowed a lenient level of safety regulations in com-parison to industrial facilities relative to specific codes and stan-dards (e.g. OSHA exemptions). The reduction in scale on farmreduces many potential safety concerns that would be vital whenassessing a large biorefinery operation. Though this study doesnot try to quantify this area, it can be inferred that the move to amore decentralized production system would have a reduction inthe total cost related to safety concerns.

A major source of cost, energy use, and environmental impactsis associated with transportation. The biomass material proposed

$0.10

Material Loss (variable)

Diesel Fuel ($0.69/L)

Fer�lizer Cost ($1507/ha)

Press Efficiency (45% farm/55% industrial)

Crop Yield (15.7 BD tonne/ha)

Conversion Efficiency (85% of theore�cal)

Value (base value)10% decrease

$0.71/L, st. dev. $0.14/L) (error bars represent one standard deviation).

By-product utilization Average change (%)

Electricity feedstock 23.7Cellulosic feedstock 0.0Animal feed �0.6Local heat �15.0

K.R. Caffrey et al. / Agricultural Systems 130 (2014) 55–66 65

for use in bioenergy production generally is high in moisture con-tent and low in bulk density, reducing load capacity on a weightbasis. This is especially true for sweet sorghum. It also requirescontinual system optimization to ensure that the transportationnetwork is run efficiently. Processing sweet sorghum into a liquidproduct allows the loads to weigh out and reduce total transporta-tion requirements. Increasing ethanol concentration in solutioncan also reduce the amount of water being shipped. The transpor-tation sector has major impacts on all metrics of interest necessi-tating mitigation strategies including reduction of travel distance,increased bulk density, and transportation of increasingly pro-cessed material.

Moving to a more farm-based system also allows for increasedbuy-into the total production system by individual farmers. Value-added agricultural processing would require the purchase andmaintenance of some specific equipment related to bioenergy pro-duction instead of expecting the farmers to simply cultivate feed-stock. This does have some drawbacks related to increasedfarmer economic involvement and risk, yet it also allows for thepotential for a higher return on investment compared to a tradi-tional agronomic system.

Production of bioenergy has been portrayed as a potential boonfor rural communities. In general any large agricultural businesswill tend to increase rural development, but the more money thatflows to the individual farmer the greater the probability of thatmoney being reinvested in that community. In context to this anal-ysis there was a substantial decrease ($581/ha) in the processingcost at the farm site from scenario five (biomass) compared to sce-nario two (fermentation broth) (Fig. 7). This resulted in a total sys-tem cost increase of $128/ha or a per unit decrease in $0.08/Lbetween these scenarios. So a moderate increase in total end prod-uct breakeven sales price (between Scenario 2 to Scenario 5)resulted in a major increase in income to farmers through value-added agriculture using a decentralized system (approximately1.8 times the farm production cost).

Though some environmental impacts, such as global warmingpotential, must be accounted for regardless of spatial location oth-ers may be reduced due to the use of a de-centralized processingsystem. The environmental impact categories of HH Criteria andSmog were two of these areas. Both of these are problems in urbanareas where concentrations in the air can reach critical levels thatare harmful before dissipating through natural means. If these arereleased in rural areas the concentrations may never reach harmfullevels before dissipation. Though this study looked at overall envi-ronmental impacts using a mid-point method, the actual end-points may be significantly lower with a decentralized system.

Individual management of operations by farmers will presentits own set of problems for the overall bioenergy system, regard-less of level of processing (i.e. fuel grade ethanol, distilled juice, fer-mented broth, etc.). It is envisioned that an aggregator system,similar to that of the hog and chicken industries, would be imple-mented, where a centralized entity would deal with the industrial-ized portions of the process and support the farmers. This mayresult in reduced commodity costs, such as fertilizer and dieselfuel, optimized transportation networks for reduced costs, andassistance with reductions in material losses. Benefits from theaggregation system could reduce costs and allow for increased effi-ciency of production scenarios where additional value added farmprocessing is required (modeled Scenarios 1–3).

Many obstacles still face the bioenergy industry, but the use of adecentralized processing system can yield many benefits (e.g.increased rural development and additional farmer income). Sweetsorghum is a unique dedicated energy crop rich in soluble sugarsthat can be grown throughout the Southeastern US, yet with itsbenefits also come technical barriers that need to be addressedprior to industrialization. Considerations related to scenarios in

Fig. 2 investigated in this analysis used conservative assumptions(e.g. crop yield, Brix level of sorghum juice, conversion efficiency,and by-product usage) which, when modified may significantlyreduce breakeven sales price. With additional value-added agricul-tural practices, increases in energy density of products from thefarmgate can reduce transportation costs and increases farmerincome. Though the breakeven sales price of ethanol from centraloperations (Scenario 5) was lowest compared to the other scenar-ios, additional considerations outside the bounds of this studywould suggest that increased farm processing is an attractiveoption for the production of ethanol from sweet sorghum.

5. Conclusions

Sweet sorghum has the potential to have a significant contribu-tion to bioenergy production in the United States. Production ofethanol is commonly thought of as an industrial process, but withthe use of a decentralized processing system this analysis hasshown a moderate increase in ethanol breakeven sales price candramatically increase the portion of processing that can be per-formed on the farm. There are major benefits related to a decen-tralized processing system that should be considered in thedevelopment of sustainable and effective bioenergy productionsupply chains not only from an economic standpoint, but in termsof energy and environmental impact as well.

Acknowledgements

This material is based upon work supported in part by the Bio-fuels Center of North Carolina. Any opinions, findings, conclusionsor recommendations expressed in this publication are those of theauthor(s) and do not necessarily reflect the views and policies ofthe Biofuels Center of North Carolina. The authors would like tothank Anthony Turhollow (Oak Ridge National Laboratory Bioener-gy Resource and Engineering Systems Group) for providingresources and recommendations for modeling input assistance.Special thanks to Matthew Whitfield for suggestions and editorialreview.

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