For this work, 17 bio-based fuels comprising 14 potential biomass feedstocks (raw, densified, and torrefied and densified) along with three traditional fossil fuels for comparison (Table 1) were considered. It should be noted that these biomass feedstocks cannot be directly used in modern transportation vehicles, but the study is concerned about the energy content of these biomass feedstocks for the BTD calculation. All these 17 bio-based fuels are solid fuels, except diesel fuel which is a drop-in liquid fuel with reference to which the BTDs of the rest (16) were calculated. Reported values for bulk densities and specific energies of biomass feedstocks often differ (e.g., baled biomass); therefore, averages of published values were used. Referenced bales were rectangular with dimensions of 0.91 × 1.22 × 2.44 m.

Specific energies (energy per unit mass) for some biomass feedstocks were calculated to maintain consistency throughout similar materials and mitigate discrepancies. Corn stover pellet (6.2% wet basis (w.b.) moisture) was used as the necessary reference material in specific energy calculation for the corn stover pellet (26% w.b.) and corn stover briquettes (Table 1). Similarly, corn stover bale (10% w.b.) was used as a reference for the other three corn stover bales with varying moisture contents (20–50% w.b.). Wood chips-50% were used as the reference for wood chips-12% and torrefied wood chips. Cattle feedlot compost was taken as the soil-surfaced feed pen, code HA-FB (Sweeten et al., 2006). Mass densities of Central Appalachian coal and North Dakota lignite were taken as the average values reported for bituminous coal and lignite, respectively (Engineering ToolBox, 2018).

Relevant biomass feedstock properties considered in this work, such as the bulk densities and specific energies at specific moisture contents, derived from published reports are presented in Table 1. Among the various biomass feedstocks, corn stover is one of the major feedstocks currently used for bio-based fuel production. Therefore, corn stover bales with different moisture contents were considered in the present study as different harvesting methods such as single- and multi-pass and wet and dry storage systems result in corn stover with moisture content in the range of 10–50% w.b. (Shinners et al., 2007). Furthermore, corn stover bales with moisture content in the range of 10–33% (w.b.) can be processed and used for pellet production (Tumuluru, 2023). In the case of pellets, two different types of pellets were considered: i) the conventional pelleting process produces pellets with a moisture content of about 6% w.b. (Tumuluru et al., 2010), whereas ii) the high-moisture pelleting process developed by the Idaho National Laboratory produces wood pellets with higher moisture content of typically approximately 26% w.b. before low-temperature drying (Tumuluru, 2016).

For some of the biomass feedstocks at several moisture contents, the material properties were calculated from the reported values by following the two steps: i) converting properties from the reference to bone dry moisture content (Eq. 1) and ii) obtaining the desired property through conversion from the bone dry to the desired moisture content (Eq. 2).

In such calculations, a simple linear variation of the properties with moisture was assumed without considering biomass’s volume swell/shrinkage due to moisture variation. The logic followed in the calculation was that the bone dry matter bulk density is considered directly proportional and the specific energy is considered inversely proportional to the dry matter component of biomass (1 − MC_ref) (Boundy et al., 2011) as expressed in the following relationship: BD dry = BD ref × 1 − MC ref ; SE dry = SE ref 1 − MC ref , (1) where BD_dry is the bone dry bulk density (kg/m³), BD_ref is the reference bulk density (kg/m³), MC_ref is the reference moisture content (w.b., decimal), SE_dry is the bone dry specific energy (MJ/kg), and SE_ref is the reference specific energy (MJ/kg). Then, these material properties at the required new moisture content using Eq. 1 are calculated as BD bio = BD dry 1 − MC ; SE bio = SE dry × 1 − MC , (2) where BD_bio is the biomass feedstock bulk density at the new moisture content (kg/m³), MC is the new moisture content (w.b., decimal), and SE_bio is the specific energy of the biomass feedstock at MC (MJ/kg). From Eq. 2, the effect of moisture content on biomass feedstocks can be observed as the higher moisture contents result in higher mass densities and lower specific energies.

Biomass feedstock properties (Table 1) remain unchanged for the calculations with each mode of transportation. For each biomass feedstock, the energy in the feedstock was compared to the energy of the conventional fuel required to transport the biomass feedstock. The BTD is unique for each biomass feedstock and must incorporate the volume and mass limitations, as outlined previously, for each mode of transportation. The energy content of the transported biomass feedstock is calculated as E bio = min V × BD bio , PL × SE bio , (3) where E _bio is the energy content of the biomass feedstock transported (MJ), V is the volume limit of the transportation mode (m³), and PL is the legal payload limit (kg). Eq. 3 appropriately selects the right quantity of biomass feedstock transported based on existing volume or mass limitations.

The bulk densities and specific energies of the considered biomass feedstocks (BD_bio and SE_bio, respectively) and those of the transportation diesel fuel (BD_f and SE_f, respectively) were used to derive the energy required and BTDs of the selected modes of transport. Characteristic to the particular transport, different units were employed for the parameters (e.g., km/L for truck fuel consumption). Each mode of transport has a payload limit, and even though more mass can be transported in the available volume, this payload limit comes into effect based on the biomass feedstock transported. In this study, we have selected the truck and ship configurations that are commonly used for biomass transport. The focus of this research is to derive equations and understand BTD for various modes of transport. Although different units were employed for different parameters, the units of transport energy and BTDs were evaluated as “MJ” and “km,” respectively, for consistency. An alternative way of deriving the BTD, while showing the units, involved is presented in Supplementary Section S1.

The fuel efficiency and consumption values considered for each mode of transportation in the analysis along with their sources are provided in Table 2. The fuel efficiency data taken in the study incorporate the vehicle weight, air drag, and rolling friction for trucks and rails, or skin friction for ship transport. The rolling friction between asphalt and rubber was significantly higher than that for steel on steel; thus, rail transport gained efficiency by lower steady-state resistances and not stopping for long stretches. Larger rail freight capacities operate for a much longer stretch without stopping, improving fuel efficiency and making the rail transport of the cargo more efficient. These factors were considered when taking the fuel consumption of the transportation modes tested in this study.

The common modes of biomass feedstock transport are ship, train, truck, barge, ocean carrier, or a combination of various transportation modes. For example, when transporting biomass feedstocks over land, railroads tend to offer a lower cost per ton-mile, can handle large volumes, and can be the most environmentally responsible transportation mode. Exporting biomass feedstocks requires more than one shipping mode. Oftentimes, railroads will ship these products to ports where they are loaded onto ocean carriers for transport overseas. For example, wood pellets from the production site are transported to shipping terminals by rail and further transported to various domestic and international markets by ships (Searcy et al., 2014). The location of the biorefinery has a great impact on the supply chain logistics. Some of the biorefineries that use agricultural residues which are low in bulk density and specific energy are close to biomass production areas to reduce transportation costs, whereas some of the biomass feedstocks such as pellets which are high in bulk density and specific energy are not close to biomass production areas, but the higher bulk density and specific energy make them economical to transport to longer distances by truck, ship, or rail.

Volume and mass legal restrictions influence the transportation logistics. When the available transport volume is completely filled with feedstock and the weight limit has been reached or exceeded, then the transportation is said to be mass-limited, and the mass transported must be reduced. Conversely, when the available transport volume is completely filled with feedstock and the mass limit has not been exceeded, then the transportation is volume-limited as there is no room for more material despite the payload limit allowing to carry more. Therefore, in general, mass-limited transport (fully utilized) has greater potential for payload transfer, as it utilizes the maximum allowed payload, than volume-limited transport (underutilized).

The type of transport limitation is predominantly influenced by the bulk density of the transported material because the volume available and the allowed payloads are typically fixed for each type of transport. Thus, any biomass feedstock bulk density smaller than these limits will make the transport volume-limited and greater than these limits will make it mass-limited. It can be seen that a transport mode can be both mass- and volume-limited based on the biomass feedstocks transported, as illustrated by truck and ship modes presented in Table 2. The derived “bulk density limit” of the material transported from the payload allowed and volume data available as 223, 1,480, and 656 kg/m³ for truck, rail, and ship, respectively, can be used to readily identify the type of transport limitations given the bulk density of a biomass feedstock. Therefore, based on the rail bulk density limit of 1,480 kg/m³, which is greater than any biomass feedstock’s bulk density (Table 1), the rail transport will always be volume-limited (underutilized), while the truck and ship will be mass-limited for biomass feedstocks having moderate or higher densities (e.g., ≤410 kg/m³).

From the evaluated BTDs using Eqs 5, 7, 9 (example BTD calculations are shown in Supplementary Section S2), the ship was by far the most energy-efficient, despite being mass-limited for dense biomass feedstocks, with the largest BTDs (approximately two orders of magnitude difference) among transportation modes considered (Figure 1). This might be counterintuitive due to the large size of cargo used in ship transport (Table 3). The energy efficiency of ship transport was due to the freight capacity and the extended time taken for the trip. Ship transport takes significantly longer time than truck or rail, during which biomass feedstocks may degrade, and this time effect was not considered in the analysis. The results also show that rail transport was more efficient than trucks from the BTD standpoint.

Biomass feedstock properties, such as specific energy and bulk density, affect the BTD to a varying extent (Figure 1). Among all the transportation modes, the specific energy showed the obvious trend of direct variation with the BTD. However, the increased bulk density of the biomass feedstocks only contributed positively to the BTD in the initial range for truck (approximately ≤223 kg/m³) and ship (approximately ≤656 kg/m³) as these transports are both mass- and volume-limited depending on the bulk density of the biomass feedstock being transported. Rail transport, however, being only volume-limited, the BTD is not affected by bulk densities (Figure 1). This can also be seen from the unit of “kg km/L” for rail transport efficiency. The figure for rail transport shows no dependence on bulk density for BTD. This goes back to the explanation given previously that the BTD for rail transport does not depend on payload mass due to the mass being included in the efficiency term. Based on Eq. 7, only specific energy will affect the BTD for rail transport.

The surface plot of bulk density to specific energy and its impact on the BTD of the truck indicated that with an increase in the bulk density of the biomass feedstock up to 300 kg/m³, the BTD is higher, whereas further increasing the bulk density does not affect the BTD. On the other hand, increasing the specific energy increases the BTD at different bulk densities of the biomass feedstocks. In the case of rail transport, which is volume-limited, the bulk density does not impact the BTD, but the specific energy significantly impacts the BTD. The results for ship transport indicated that both bulk densities and specific energies significantly impact the BTD of biomass feedstocks, where increased bulk densities and specific energy increased the BTD transportation of the material.

The BTD profiles and patterns of the different biomass feedstocks and fossil fuels in the three modes of transportation show that truck and rail BTD profiles were similar, but these were different from the BTD profiles for ship, as shown in Figure 2. These BTD profiles clearly show the scale (how the three transportation modes compare among themselves—showing the dominance of ship) and the pattern (how studied biomass feedstocks compare with others—similarity between truck and rail) with each transportation mode.

On average, the rail can transport approximately 3 times farther and the ship can transport approximately 10 times farther than the truck. Compared to trucks, the larger rail freight capacities and their operation for a much longer stretch without stopping contribute to their efficiency. Given that the “start-up” after each “stop” was the most energy-intensive part of any transport and building momentum also consumed energy, rail transport reduced these energy losses better than trucks. However, maintaining momentum was much less energy-intensive and only involved overcoming the steady-state resistances. These include air drag and rolling friction for trucks and rails, or skin friction for ship transport. It follows the intuition that rolling friction between asphalt and rubber was significantly higher than that for steel on steel; thus, rail transport gained efficiency by lower steady-state resistances and not stopping for long stretches.

Given the results and overall ranking of the BTD of different biomass feedstocks and their properties (Figure 2; Table 2), the efficient transportation between the start and end destinations should be a combination of modes of transportation based on feasibility (geographical and existing transportation network). It makes sense that rail transport is not ideal for only a few miles of transport. It should be realized that with the ship, and sometimes with the rails, truck transport may be added to deliver the biomass feedstocks to the biorefinery. Future analysis is needed to optimize the transportation methods by integrating the three modes of transportation based on their availability and the distance the biomass feedstocks is transported involving the existing transportation network.

In order to quantify the effect of changing moisture of biomass feedstocks on the BTDs (Figure 3), the case of corn stover bales between 10% and 50% w.b. moisture contents was considered (Table 1). The corn stover bales data were further analyzed to understand the impact of moisture on BTD using trucks, rail, and ships. Figure 3 shows how the BTD changes with the moisture content for the corn stover bales in the moisture content range of 10–50% w.b. The changes in the bulk density (BD_bio) and specific energy (SE_bio) in the corn stover bales were calculated based on Eqs 1, 2. These equations calculate the bulk density and specific energy based on simple linear variation with respect to moisture content but do not consider the biomass’s volume swell/shrinkage due to moisture variation. It is clear from Table 1 that the bulk density of the corn stover biomass increases with an increase in the moisture content, whereas the specific energy decreases. These changes in the bulk density and specific energy with moisture (considered in the calculation) have impacted the BTD of the corn stover bales (Figure 3).

From the results, it is very clear that for the ship, which is volume-limited, the BTD increases with an increase in the moisture content of up to 30% w.b. (an increase of approximately 26%), whereas further increasing the corn stover bale moisture content to 50% w.b. decreases the BTD values (a decrease of approximately 9.8% from the moisture content of 30–50% w.b.). Regarding rail, which is volume-limited, the BTD decreases by approximately 45% with an increase in the corn stover bale moisture content from 10 to 50% w.b. For truck transportation, which is mass-limited, the increase in the corn stover bale moisture content from 10 to 40% w.b. increases the BTD values from 20,866 to 21,780 km (4.3% increase), and further increasing the corn stover bale moisture content to 50% w.b. decreases the BTD values to approximately 15,556 km [a decrease of approximately 28% compared to BTD values at 10% w.b. moisture content]. The BTD data calculated with respect to moisture should be further cross-validated with the actual bulk and specific energy of the corn stover bales at different moisture contents.

Since trucks and ships were influenced by both mass and volume limitations, with moisture content affecting these, an optimum moisture content might exist for efficient biomass feedstock transport. For these modes with corn stover, when the moisture is too low, the transport is volume-limited, and the total material transported is lower than the full payload capacity. When the moisture is too high, the transport is mass-limited for truck and ship transport, where the material transported is lower than the full volume capacity of the transportation mode. Overall, efficient transportation occurs when the mass- and volume-limited transportation modes coincide, maximizing the amount of material that is being transported.

Rail transport is impacted by moisture due to the inclusion of mass in the efficiency (units: kg km/L) as high moisture increases the overall mass and reduces the net dry matter transported and the biomass feedstock energy content. Thus, the rail transport being volume-limited, a specified volume of biomass feedstock will represent a certain mass and its corresponding BTD, based on the nature of the biomass feedstock, irrespective of the bulk density. By increasing the moisture of the biomass feedstock, the specific energy (SE_bio) is reduced (Table 1), which eventually reduces the fuel efficiency of rail transport (η _r). According to Eq. 7, the BTD or rail decreases linearly with decreased rail transport efficiency.

As observed with corn stover bales (Figure 3), similar results for other biomass feedstocks with moisture variation can be expected. The corn stover bale moisture content and BTD were further modeled, which can help predict the BTD values of corn stover bales in the moisture content range of 10–50% w.b. The fitted polynomial models (Table 4) have adequately described (R ² ≥ 0.92) the BTD with the three transportation modes as a function of moisture content. These models can be useful in calculating the BTD of the corn stover, most abundant agricultural feedstock, at commonly occurring moisture contents of this feedstock.

The limiting factors for each combination of moisture, biomass feedstock, and transportation method influence the logistics decision (Figure 4). For example, corn stover bales are volume-limited for moisture contents less than 20% w.b., whereas above this moisture content for truck transport, the transportation is mass-limited. Torrefied wood chips, however, are mass-limited for truck transport and volume-limited for ship and rail transport. All feedstocks considered were volume-limited for rail transport. This was because of the large payload limits on railcars. In the case of commercial wood pellets and torrefied wood pellets, both the truck and ship are mass-limited, whereas the rail is volume-limited. Fossil fuels such as different coals (Central Appalachian coal and North Dakota lignite) and diesel fuel also have similar trends like commercial and torrefied wood pellets. For instance, a railcar can carry materials with a bulk density of up to approximately 1,500 kg/m³, and no biomass feedstocks will reach this density and thus represent the underutilization of rail transport. For volume-limited transport, any pretreatment (e.g., torrefaction) resulting in higher densities will increase the BTD, representing a logistic opportunity. The underutilized transportation space needs to be optimized for better logistics advantage.

Biomass feedstock is typically grown in regions with low population densities. These regions can be far from the refineries or power plants. A comparison of the BTDs of truck transport for a truck filled to its allowable limit using various biomass feedstocks within the perimeter of the US was performed. This analysis was useful for understanding the feasibility of transporting various biomass feedstocks to the stakeholder’s processing facility locally within a state or transported interstate (Figure 5). For this analysis, the US perimeter was considered 14,452 km (Beaver, 2018), which is the approximate coastline of the 48 contiguous US states excluding Alaska and Hawaii. The results present the BTD pattern for 1 US ton as well as a whole truckload of bio-based fuels considered in terms of direct distance (km) and US perimeter to allow for easy unit mass (1 US ton and whole truckload) comparison. Interestingly, the BTD pattern was different for cases of the volume-limited biomass feedstocks, such as corn stover bales-10% w.b. and -20% w.b. (low bulk density materials), compared to a similar pattern (Figure 5) otherwise for mass-limited transport.

Among the biomass feedstocks considered, the torrefied pellets had the highest BTD and therefore can be transported around the US perimeter the most, namely, 2.88 times. This was mainly due to the relatively high specific energy and high bulk density of torrefied pellets. As bales, pellets, and briquettes have nearly the same specific energies, the driving factor in their comparison was the bulk density. Feedlot compost has the lowest specific energy and was mass-limited for trucks as shown previously (Figure 4). Even with these considerations, feedlot compost can be transported approximately 0.9 times around the US perimeter before reaching its BTD. This means that the feedlot compost originating in the Central US can be transported anywhere in the US and still have a net calorific value.

Overall, for the biomass feedstocks considered (14), excluding coal, the equivalent US perimeter transport distance varies from 0.9 to 2.88 times (Figure 5). This conceptual result also demonstrates that interstate biomass feedstock transport is highly practical based on the BTDs as interstate distances are significantly lower than the US perimeter. Thus, biomass-derived bio-based fuels in loose and all densified forms considered could be transported practically to all 48 contiguous US states. Furthermore, the location of biorefineries can be optimized to minimize the hauling distances, resulting in increased net energy in logistics. Regardless of the location of the biorefinery, interstate truck transport, as a single mode of transportation based on net energy in the biomass feedstock, was found not to be a limiting factor.

In the present study, the estimated BTDs presented for various biomass feedstocks and fossil fuels were based on inroad transportation logistics only. The inclusion of other energies of related biomass harvesting, preprocessing, and pretreatments like baling, densification, torrefaction, storage, handling, and biofuel conversion will make the analysis more comprehensive and reflective of the whole supply chain. The results of the present study may not provide rational upper bounds on the distances that biomass feedstocks may be economically transported; however, these data should help in making informed decisions as transportation economics are directly influenced by BTDs. In addition, the results should help identify limitations on biomass feedstock transport, leading to biomass utilization feasibility.

Based on this research, it can be concluded that each biomass feedstock has an optimum bulk density for transportation. If the biomass feedstock is dried too much (less bulk density), the transportation is volume-limited, and when the material is too wet (higher bulk density), the transportation is mass-limited. Mass-limited transportation, satisfying the payload limitation, is the most efficient mode. Therefore, the material should be processed (e.g., densification) so as to make the transportation mass-limited, whereas the volume-limited transportation represents underutilization of the allowable payload. Thoreson et al. (2014) suggested that bulk densities of approximately 270–370 kg/m³ are necessary to fill the truck full to its load capacity. The conventional pelleting process which produces pellets with densities of approximately 650–700 kg/m³ may not be the right technology to transport pelleted biomass using trucks. Although it reduces the transportation cost, it may not offset the pelleting costs incurred during the conventional pelleting process (Schill, 2014).

To overcome these limitations, novel energy-efficient biomass preprocessing and pretreatment technologies should be developed to reduce the preprocessing cost and make transportation more energy-efficient. Tumuluru (2023) recently tested high-moisture pelleting at pilot and commercial scales on corn stover bales and found that the process reduces the pelleting production energy by approximately 70% compared to conventional technology followed by the industry but can help produce pellets which can meet the transportation requirements by trucks. This will coincide with the concept of minimum energy required to dry the material in preparation for transport. Furthermore, the thermal pretreatment technologies, such as torrefaction, pyrolysis, and gasification, which make bio-based fuels high in specific energy, can help improve transportation efficiencies. Future research should consider the optimum moisture and density the raw biomass material should have and incorporate factors such as material degradation and storage time requirements.

Knowledge and understanding of the transportation BTD of various biomass feedstocks help plan the layout of the biorefineries to increase sustainability and optimize the cost of transportation during their design phase. The BTD analysis provided in this paper can help the policymakers understand how the energy content in the biomass and transportation BTD calculation can be factored into the net-zero emissions in the complete supply chain analysis. The BTD of various biomass feedstocks can help plan the carbon debt that can be incurred by the transportation of biomass-based material from managed forests, cropland, and other preprocessing satellite locations.

To make better sense of the truck-based BTD results, they have to be overlaid on the existing road network, and this may constitute another practical future study. Likewise, rail transport should be evaluated on the existing railway infrastructure. Combining modes of transportation will provide a more accurate transportation profile that can then be optimized. Future studies should include the energy required for preparing the biomass materials, including processes such as harvesting, drying, chipping, grinding, densification, torrefaction, and other preprocessing and pretreatment technologies that are used to make the biomass into a ready-to-convert feedstock for bio-based fuels and biopower generation. Future studies on BTD calculations should also be focused on the material losses due to material degradation, and combining the different modes of transport can help maximize the distance transported with minimum energy. Furthermore, the impact of fuel efficiency of trucks as well as specific road conditions, weather, and truck size should be evaluated in the future. Studies related to how trucks and ships with varying sizes and efficiencies impact the BTD can be part of future studies.

In this initial study, we have designed the framework for understanding the transportation BTD of various biomass feedstocks. It is believed that the introduction of the concept and understanding of BTD, developed in this study, serves the purpose of the initial outcome. Future analysis should include how biomass preprocessing and pretreatment technologies impact the transportation BTD and sensitivity analysis of significantly influencing factors. Regarding truck transport, specific types of trucks (semi-trailers, flatbeds, step decks, dry vans, reefers, box trucks, and tankers) will be best suited to a specific type of biomass feedstock (e.g., loose crop residues, wood chips vs. densified pellets, and briquettes), and a more complete analysis of the combinations of truck and biomass feedstock types should be considered for future research. Another aspect of practical interest is the economics component; similar to BTD, a break-even cost can be derived for the different biomass feedstocks. Such a logistical economic analysis will eventually influence the decision on the biomass feedstock selection, and the mode of transport should be considered for future research. A full-scale sensitivity analysis that incorporates inter-variable dependence, such as fuel properties and fuel efficiency, needs to be performed to understand the sensitivity of the various factors influencing the BTDs of various biomass feedstocks.