- Email: [email protected]
Energy requirements for wood chip compaction and transportation
Fuel 262 (2020) 116618
Contents lists available at ScienceDirect
Fuel journal homepage: www.elsevier.com/locate/fuel
Full Length Article
Energy requirements for wood chip compaction and transportation Niccolò Pampuro, Giorgia Bagagiolo , Eugenio Cavallo ⁎
T
Institute for Agricultural and Earth Moving Machines (IMAMOTER), Italian National Research Council (CNR), Strada delle Cacce, 73, 10135 Torino (TO), Italy
GRAPHICAL ABSTRACT
ARTICLE INFO
ABSTRACT
Keywords: Briquette Densification process Compression energy Transport energy Woody biomass
Wood chips represent one of the most popular biomass fuel in latest cogenerating plants and in small heating systems. This fuel, being characterized by low bulk density, requires high transportation costs. This obstacle can be overcome by wood chips densification. The authors investigated the energy benefit of wood chips densification for transport operations for “short supply chain” as defined by the Italian government for the biomass fuel subsidy scheme. Three different woods (poplar, chestnut and a mixture of spruce and eastern white pine) chips and six different tractor’s trailed trailers were investigated. The total specific energy (kJ kg−1) required to transport a defined quantity of wood chips, the energy saving ratio (%) from chips’ compaction and the breakeven distance (km) between raw and compressed chips were calculated. The results highlights that densification process of wood chips is an interesting opportunity to improve the transport energetic convenience. The benefit of wood chips densification is strongly affected by raw wood chips density values and by trailer characteristics: the benefit is maximum when the density of compressed wood chips to be transported attains the vehicle theoretical density.
1. Introduction
this agreement fostered the renewable energy sources demand. As a result, the renewable energy production largely grew in the electricity, cooling/heating and transport sectors and, consequently, the forecast of renewable energy consumption by 2020 in the EU should slightly exceed the 20% target [2]. In 2018 the EU countries agreed to increase to 32% the binding EU target on renewable energy adopting the revised Renewable Energy Directive [3]. In the 2012, biomass and waste represented about two-thirds of the
The main target of the 20-20-20 of the European plan on climate change adopted by the European Union (EU) in 2009 was to reduce the greenhouse gas emissions by 20% compared to the 1990 levels, to increase the share of renewable energy to 20% of the total energy consumption and to achieve a 20% increase in energy efficiency by 2020 [1]. Since then European and national laws and rules issued according
⁎
Corresponding author. E-mail address: [email protected] (G. Bagagiolo).
https://doi.org/10.1016/j.fuel.2019.116618 Received 31 July 2019; Received in revised form 5 November 2019; Accepted 6 November 2019 Available online 15 November 2019 0016-2361/ © 2019 Elsevier Ltd. All rights reserved.
Fuel 262 (2020) 116618
N. Pampuro, et al.
renewable energy consumption of the EU [4] and, according to calculations from 2015 Eurostat data [5], the residential utilization represent half of total European bio-heat consumption. Among renewable energy sources, biomass use has been strongly encouraged in order to replace fossil fuels in many applications, from heating to electricity production [6]. Wood biomass are gaining in popularity for heating and power production, because of subsidies, taxexemptions and other incentives in application of schemes for CO2neutral energy and greenhouse gas emission reduction, environmental sustainability, and the desire to reduce dependence from fossil fuels [7–9]. Woody biofuel production consist of different operations: growing and harvesting biomass, converting biomass to bioenergy and bioproducts, and, finally, delivering end products to distribution centers or end users [10]. Comminution is an effective process to make wood fuels competitive with other energy sources: comminuted woodchips can feed automated chip-fed boilers, offering user-friendly operation [11]. New technologies and innovative solutions contribute to improve efficiency of the comminution process and, thus, increase the competitiveness of wood chips and the safety and comfort for the forestry workers [12–14]. However, as reported by a number of studies [15–19], along the woody biomass supply chain, biomass transport from comminution site to the end user is quite a critical point. In particular, the vehicles used must guarantee high versatility to operate under different working conditions and, at the same time, with low operating costs [15]. Several studies investigated the biomass supply chain and/or logistics optimization [20–23]. Most of the studies [24–27] focused on vehicles optimization and route planning for energy savings adopting models based on fuel consumption database and theoretical calculation. Wood chip can be transported by industrial vehicles and by agricultural trailers coupled with tractors [15]. Various studies on wood biomass supply reports trucks as the most effective road transportation systems [17,28,29]. However, trucks are generally suitable for on-road long distances transportations while their adoption is limited by the possibility to travel forest roads and to access forestry yards [16]. According the results from a survey by Spinelli and Hartsough on Italian chipping operation [30] wood chips are usually transported by trucks when distances are 30 km or above, while for shorter distances (3–4 km one way) most operators use farm tractors with PTO-powered trailers. Nevertheless, Manzone and Calvo [16] observed that the use of agricultural convoys (tractor plus trailer) has been increasing in the woodchip transportation on distances up to 70 km. The possibility of using standard equipment available in the farm and of directly loading in the field or comminution site play a key role in selecting agricultural trailers, even if with lower capacity than industrial convoys, to optimize logistic operations for wood chips transportation [31]. In case of comminuted woody biomass (eg. woodchips), characterized by low bulk density, transportation and storage phases can be further optimized through densification processes that can be used to produce a uniform material with favorable physical and mechanical effects on the fuel properties [23]. The densification process is widely adopted on a various set of agricultural particulate raw materials to enhance and make their characteristics more suitable for the final use [32–36]. According to Kaliyan and Vance Morey [32], typically, two techniques are used to compact particulate materials: tumble agglomeration and pressure agglomeration. With the tumble agglomeration the densified products are produced by means of typical movements of the bulk materials, containing a binder, in a specific equipment (e.g. balling discs, balling drums and balling cones) [32]. With the pressure agglomeration the density value of a bulk material is achieved applying a significant force in a confined volume [35]. Briquetting, the most common process to compact solid biofuels (e.g. wood chips), belong to pressure agglomeration technique. Densification processes, especially briquetting, improve combustion
properties of biomass [37–39] however, as reported by some authors [40,41], the densification processes require high energy input. Furthermore higher the density of the compacts greater their durability, as reported by Facello et al. [42] in a study on woodchip briquetting process. The present study investigates the possible beneficial effect of densification process on woodchip logistics comparing the energy required for transportation of raw and densified materials. The study does not approach economic analysis deferring this issue to further studies specifically conceived. Furthermore, the study aims at calculating the break-even-distance, the distance above which, the densification process became energetically profitable for the wood chips transportation. The investigation, unlikely previous studies, considers fuel consumption recorded on real tractor and trailer transport operation. The study considers three different woody materials and six different agricultural trailers. 2. Materials and methods The investigation has been performed considering to transport 100,000 kg of raw wood chips from a point A (for example a comminution site) to a point B (for example a storing site or a power station). The maximum distance has been set to 70 km: it is the maximum distance to comply with the definition of “short supply chain” according to the Italian regulation [43] to access the subsidies scheme for the renewable energy production from woody biomass. Besides that, this is a common condition considering wood chips, as fuelwood, are mostly used and traded locally for residential and “district heating” consumption [44]. Tractors and trailers are commonly adopted for agroforestry wood chip forwarding because they are more suitable to access rough terrain than trucks and because they are very common and cheap to recruit among agricultural and forestry operations [45]. Furthermore, tractors with trailers find growing application in transport of goods issued from the agricultural sector thanks to the technical solutions they are equipped with to attain high on-road speeds and the road regulations introduced in the last decades [9,46]. 2.1. Transportation data conditions The investigation is addressed at identifying a set of equations that can be applied to different kind of vehicle when the load capacity, the fuel consumption and average speed data are known. In this study, the fuel consumed for the transport has been measured with an experimental trial in real conditions on 3 km flat route. A 118 kW, 4 wheel-drive, and 19 gears full power-shift transmission tractor towing a 3 axles, 21 m3 volume trailer has been used. The consumption of the tractor was measured when towing the trailer at its maximum mass, 20,000 kg, and with the same trailer in empty condition, 7000 kg. The trailer adopted for the experimental trial (AgriReal in Table 1) comply with the Italian road rules (20,000 kg maximum mass) and has payload (13,000 kg) and empty mass (7000 kg) representative of the trailers in use in the Italian farms. Table 1 Main characteristics of the considered trailers. The theoretical density is the density at which both maximum load volume and load mass are reached.
2
Trailer
Volume [m−3]
Payload [kg]
Theoretical density [kg m−3]
AgriReal AgriTrailer1 AgriTrailer2 AgriTrailer3 AgriTrailer4 AgriTrailer5
21 25 30 35 40 42
13,000 13,000 13,000 13,000 13,000 13,000
619 520 433 371 325 310
Fuel 262 (2020) 116618
N. Pampuro, et al.
Tractor’s fuel consumption and vehicle speed were recorded from the tractor via CANBUS diagnostic connector [47]. Data were later analyzed with the Vector Canalyzer 8.0 suite. The tests have been replicated four times. The data obtained with AgriReal trailer have been used to calculate the values of fuel consumption for the investigated additional trailers (AgriTrailer# in Table 1) adopting the linear interpolation in Eq. (1).
Fr = k 0 + (1
Table 3 Coefficients values – km and c – required for Specific Compression Energy calculation depending on wood chips type [6]. Wood chips
CC PC MC
(1)
k 0)·Load/Load max,
where
Coefficient Km [kJ m3 kg−2]
c [kJ kg−1]
0.048 0.090 0.068
−9.2 −23.3 −16.0
Fr = fuel ratio used to scale the full load fuel consumption (0 ≤ Fr ≤ 1) k0 = fuel ratio measured with empty trailer Load = real trailer load Load max = maximum trailer load 2.2. Investigated vehicles Additional trailers (AgriTrailerl# in Table 1) with different volume of the container have been considered for the study. The different volumes of the container have been theoretically calculated varying the height of the sides of the trailer. Total mass and payload in all conditions are 20,000 kg and 13,000 kg respectively. For the study we defined the theoretical density [kg m−3] as the ratio between the payload and volume of the trailer. It is the minimum density that permit to completely exploit the transportation capacity of the trailers. Being the payload the same for all the different trailers the theoretical density varies according to their different capacities (Table 1).
Fig. 1. Fuel consumption reduction ratio as a function of load ratio.
2.4.1. Compression energy The compression energy is directly related to the target density [kg m−3] of the briquettes. The study takes into account only the energetic requirements needed by the densification process and does not consider accessory operations, such as drying. Eq. (3) defines the specific compression energy (Ecm specific) according to the results of the study conducted by Pampuro et al. [50] on densification process of similar raw material.
2.3. Investigated wood chips Chips from three different types of wood have been considered for the study: chestnut (Castanea sativa L.) (CC), hybrid poplar (Populus × euramericana Guiner) (PC) and a mixture of spruce (Picea abies L.) and eastern white pine (Pinus strobus L.) (MC). The characteristics of the wood chips are reported in Table 2. The wood chips moisture content has been determined according the American Society of Agricultural and Biological Engineers (ASABE) Standard S358.2 [48] while the bulk density of raw wood chips has been measured according to the ASABE Standard S269.4 [49].
Ecm specific = (km +c) where Ecm specific = Specific compression energy [kJ kg−1]; km = material-dependent coefficient [kJ m3 kg−2]; ρ = briquettes density [kg m−3]; c = material-dependent offset coefficient [kJ kg−1].
2.4. Energy calculation For the study we define the total energy (Et) (Eq. (2)) as the sum of the energy required for compressing wood chips (Ecm) into briquettes and the energy required for transportation (Etr):
Table 3 shows the coefficients values – km and c – of the wood chips considered in the study. km is the proportional coefficient between final density value and specific energy while c is an offset coefficient; it is negative because the initial density value is different from zero. The material-dependent coefficients were measured by Cavallo et al. (2017) in a study related to the effect of compressing pressure on briquettes made from the same three woody biomass (PC, CC; MC) considered in the present study. The compression energy (Ecm) is calculated according Eq. (4). Ecm is the energy required to densify a specific wood chips quantity [kg] producing briquettes with a specific density value [kg m−3]:
(2)
Et = Ecm + Etr where Et = Total energy [J]; Ecm = Compression energy [J]; Etr = Transport energy [J].
Ecm = Ecm specific·Wt = (km +c)·Wt
Table 2 Moisture content (%) and raw density values (kg m−3) of the investigated wood chips: chestnut (CC), hybrid poplar (PC) and Mixture of spruce and eastern white pine (MC). Mean value ± standard error of 3 replicates. Wood chips
ID
Raw density (kg m−3)
Moisture (%)
Chestnut Hybrid poplar Mixture
CC PC MC
212.0 ± 1.3 119.0 ± 0.5 152.0 ± 0.8
7.1 ± 0.1 7.9 ± 0.1 8.1 ± 0.1
(3)
(4)
where Wt = total amount of wood chips to be compressed [kg]. 2.4.2. Transport energy Eq. (5) defines the transport energy (Etr) as follow:
Etr = k v ·d·nt 3
(5)
Fuel 262 (2020) 116618
N. Pampuro, et al.
Table 4 Fuel ratio and fuel consumption in relation to load rate for the six considered trailers. PC
MC
Bulk Density
Load rate (Load/ Load Max) [kg m−3] [%] Agrireal
Fuel ratio Fuel consumption
CC
Bulk Density
–
[kg h−1]
Load rate (Load/ Load Max) [kg m−3] [%]
Fuel ratio Fuel consumption –
Bulk Density
Fuel ratio Fuel consumption
[kg h−1]
Load rate (Load/ Load Max) [kg m−3] [%]
–
[kg h−1]
Raw 119 Densified. 619
19.2% 100.0%
0.87 1.00
12.3 14.1
152 619
25.0% 100.0%
0.88 1.00
12.4 14.1
212 619
34.0% 100.0%
0.89 1.00
12.6 14.1
AgrTrailer1 Raw 119 Densified. 520
22.9% 100.0%
0.88 1.00
12.4 14.1
152 520
29.0% 100.0%
0.89 1.00
12.5 14.1
212 520
41.0% 100.0%
0.91 1.00
12.8 14.1
AgrTrailer2 Raw 119 Densified. 433
27.5% 100.0%
0.88 1.00
12.5 14.1
152 433
35.0% 100.0%
0.90 1.00
12.6 14.1
212 433
49.0% 100.0%
0.92 1.00
12.9 14.1
AgrTrailer3 Raw 119 Densified. 371
32.0% 100.0%
0.89 1.00
12.6 14.1
152 371
41.0% 100.0%
0.91 1.00
12.8 14.1
212 371
57.0% 100.0%
0.93 1.00
13.1 14.1
AgrTrailer4 Raw 119 Densified. 325
36.6% 100.0%
0.90 1.00
12.7 14.1
152 325
47.0% 100.0%
0.91 1.00
12.9 14.1
212 325
65.0% 100.0%
0.94 1.00
13.3 14.1
AgrTrailer5 Raw 119 Densified. 310
38.4% 100.0%
0.90 1.00
12.7 14.1
152 310
49.0% 100.0%
0.92 1.00
13.0 14.1
212 310
68.0% 100.0%
0.95 1.00
13.4 14.1
where
Ecm = compression energy; kv = specific vehicle energy; ntR = number of travels needed to move the specific amount (Wt) of raw wood chips; ntB = number of travels needed to move the specific amount (Wt) of densified wood chips.
kv = is a vehicle-dependent coefficient [MJ km−1], representing the specific vehicle energy in terms of energy per unit of distance. This parameter takes into account vehicle average fuel consumption (Fc) [kg h−1] as a function of loading conditions, vehicle speed (v) [km h−1] and fuel higher heating value (HHV) [MJ kg−1]; d = distance covered by the vehicle for wood chips transportation [km]; nt = number of travels.
When the distance is lower than dBE, the energy required for the densification is higher than the energy saved with transportation. On the contrary, at distances above the dBE the energy saved in transportation is higher than the energy used for densification.
More in detail, Eqs. (6) and (7) define kv and nt, respectively: (6)
kv = (Fc·HHV)/v
3. Results and discussion
In the present study, according to ORNL [51], the HHV value for commercial Diesel fuel is assumed equal to 45.6 MJ kg−1.
nt = Wt /WL = W/(V t L·
bk )
3.1. Measured parameters The average fuel consumption and speed calculated on data recorded for the AgriReal trailer in full load condition are 14.1 kg h−1 and 34.3 km h−1, respectively. The average fuel consumption calculated with the empty trailer is 16% lower than in full load trailer condition, corresponding to 11.8 kg h−1 (k0 = 0.84, in Eq. (1)). The reduced fuel consumption is mainly due to the lower tire rolling resistance, proportional to the vehicle mass [31]. The fuel consumption obtained with AgriReal with fully loaded trailer has been used as reference to calculate the fuel consumption in other load conditions and for other trailers (AgriTrailer#) with a linear interpolation between the unloaded and full load conditions (Fig. 1). The aerodynamic influence of different trailers has been neglected, due to the small differences in cross area and the relative low vehicle speed. The linear interpolation between unloaded and full load conditions calculated according Eq. (1) and used to compute the fuel consumption depending to the load conditions is reported in Fig. 1, where, k0, corresponding to unloaded condition, is 0.84. Table 4 reports the values of fuel consumption calculated according to load conditions. The physical characteristics (moisture and density) of raw chips is reported in Table 2. The chips’ moisture ranges from 7.1 to 8.1% while the densities of raw materials varies from 119 to 212 kg m−3. The moisture values are in line with those recommended by studies on densification processes to upgrade woody biomass fuels [52–54].
(7)
The amount of wood chips (Wt) is a fundamental parameter to calculate the number of travels (nt) needed to complete the wood chips transportation. nt represents an integer value (decimal value rounded to the nearest higher integer) directly linked to the physical loading capacity of the trailer used (weight limit WL [kg] and volume limit VL [m3]). In this study a single “travel” include the trip from the point A to the point B at full load condition and the trip back with empty load. The trailers characteristics, in particular mass and dimension limits are required to calculate WL as a function of material bulk density (ρbk [kg·m−3]) and max vehicle load volume VL [m−3]. The algorithm developed in this study has been adopted to calculate the numbers of travel required to move the Wt quantity respecting the weight and volume trailers limits for chips with bulk density in the range of 250 ÷ 1000 kg·m−3. 2.5. Break-even distance Break-even distance (dBE) can be assumed as the distance [km] where the totals energy required for raw and densified wood chips transportation are equal. It is defined in Eq. (8):
dBE = Ecm /k v (ntR
ntB)
(8)
where 4
Fuel 262 (2020) 116618
N. Pampuro, et al.
than the theoretical density of the transportation mean that will be adopted it implies an unjustified excess of energy consumption for briquetting than that required. In the present investigation, the minimum number of travels requested to move 100,000 kg of densified wood chips is equal to 8. Indeed, after exceeding the theoretical density values for each of the trailers considered the number of travels does not decrease further (Fig. 2). 3.3. Compression energy requirements The specific compression energy values required for compressing the three types of wood chips until the theoretical density values for the different trailers are achieved varies from 4.6 to 32.4 kJ kg−1 (Fig. 3). Compression energy requirements are affected by the target density of the woodchip briquettes and by the physical properties of the investigated materials [55]. For instance, to obtain woodchip briquettes with target density equal to 520 kg m−3 (AgriTrailer1), 23.5 kJ kg−1, 19.4 kJ kg−1 and 15.8 kJ kg−1 are required respectively for PC, MC and CC while to achieve the same target density compressing hops cones lower specific compression energy (14.2 kJ kg−1) was required [35],
Fig. 2. Numbers of travels requested to transport 100,000 kg of wood chips as a function of bulk density.
3.2. Number of travels requested for wood chips transportation As reported in Eq.5, transport energy is directly proportional to the numbers of travels necessary to move the investigated material from point A to point B. The number of travels decreases when the biomass density increases, as long as the maximum payload does not limit the load size (Fig. 2). Moreover the number of travels is affected by the trailers characteristics, namely by their payload. Indeed, AgrTrailer4 and AgrTrailer5, being characterized by high volume capacity, require less travels. Nevertheless, trailers characteristics can be neglected when density of briquettes from chips are equal to the theoretical density. This condition corresponds to the best exploitation of the volume of the trailer at the given density and maximum payload. So, to take advantages from wood chips densification in terms of number of travels reduction, for each trailer considered, the optimal wood chips briquettes density (the target density) should not be higher than the theoretical trailer density (Table 1). Achieving a briquettes density higher
3.4. Total energy requirements Table 5 reports the results from energetic analysis of wood chips transportation on a distance of 70 km. More in detail, for each investigated trailer and woody material, Table 5 presents a comparison between raw and densified wood chips. Results highlight that the total specific energy (Et specific) required to transport raw wood chips corresponds to the specific transport energy (Etr specific) values. Considering the densified wood chips, the Total Specific Energy (Et specific) includes also the Specific Compression Energy (Ecm specific) values. Total specific energy required to transport raw wood chips ranges from 920.0 kJ kg−1 to 479.1 kJ kg−1 for poplar wood chips, from 523.2 kJ kg−1 to 280.7 kJ kg−1 for chestnut wood chips and from 721.6 kJ kg−1 to 368.9 kJ kg−1 for mixture wood chips. With regard to
Fig. 3. Specific compression energy values (kJ kg−1) required for densifying the three investigated wood chips (PC, MC and CC) at the trailer theoretical density values.
5
Raw Densified
Raw Densified
Raw Densified
Raw Densified
Raw Densified
Raw Densified
AgriReal
AgriTrailer1
AgriTrailer2
AgriTrailer3
AgriTrailer4
AgriTrailer5
119.0 309.5
119.0 325.0
119.0 371.4
119.0 433.3
119.0 520.0
119.0 619.0
Density [kg m−3]
PC Etr specific [kJ kg−1] 920.0 192.5 765.7 192.5 655.4 192.5 567.3 192.5 501.1 192.5 479.1 192.5
nt
41 8
34 8
29 8
25 8
22 8
21 8
Et specific [kJ kg−1] 920.0 224.9 765.7 216.0 655.4 208.2 567.3 202.6 501.1 198.5 479.1 197.1
Ecm specific [kJ kg−1] 0.0 32.4 0.0 23.5 0.0 15.7 0.0 10.1 0.0 6.0 0.0 4.6
152.0 309.5
152.0 325.0
152.0 371.4
152.0 433.3
152.0 520.0
152.0 619.0
Density [kg m−3]
MC
16 8
17 8
19 8
22 8
27 8
32 8
nt
368.9 192.5
390.9 192.5
435.0 192.5
501.1 192.5
611.3 192.5
721.6 192.5
Etr specific [kJ kg−1]
0.0 5.0
0.0 6.1
0.0 9.3
0.0 13.5
0.0 19.4
0.0 26.1
Ecm specific [kJ kg−1]
368.9 197.6
390.9 198.6
435.0 201.8
501.1 206.0
611.3 211.9
721.6 218.6
Et specific [kJ kg−1]
212.0 309.5
212.0 325.0
212.0 371.4
212.0 433.3
212.0 520.0
212.0 619.0
Density [kg m−3]
CC
12 8
12 8
14 8
16 8
19 8
23 8
nt
280.7 192.5
280.7 192.5
324.8 192.5
368.9 192.5
435.0 192.5
523.2 192.5
Etr specific [kJ kg−1]
0.0 5.7
0.0 6.4
0.0 8.6
0.0 11.6
0.0 15.8
0.0 20.5
Ecm specific [kJ kg−1]
280.7 198.2
280.7 198.9
324.8 201.1
368.9 204.1
435.0 208.3
523.2 213.0
Et specific [kJ kg−1]
Table 5 Main parameters (density and nt) and energetic components (Etr specific and Ecm specific) affecting the total specific energy (Et specific) required to transport 100,000 kg of wood chips from comminution site to end user site (70 km) in raw and densified condition. Reported values have been calculated for the three different investigated woody material (CC: chestnut; MC: mixture of spruce and eastern white pine; PC: poplar) and for the six different considered trailers (AgriReal, AgriTrailer1, AgriTrailer2, AgriTrailer3, AgriTrailer4 and AgriTrailer5). nt: number of travel requested to transport 100,000 kg of wood chips from comminution site to end user site (70 km) in raw and densified condition. Etr specific: specific transport energy required to transport 1.0 kg of the investigated material from comminution site to end user site (70 km) in raw and densified condition. Ecm specific: specific compression energy required to densified 1.0 kg of the investigated material. Et specific: total specific energy required to transport 1.0 kg of the investigated material from comminution site to end user site (70 km) in raw and densified condition.
N. Pampuro, et al.
Fuel 262 (2020) 116618
Fig. 4. Comparison between the amount of total energy required to transport 100,000 kg of densified wood chips and the same quantity of raw chips (a: poplar wood chips; b:chestnut wood chips; c: mixture of spruce and eastern white pine wood chips) with different trailers from comminution site to end user site (70 km). The black lines represent the average energy saved.
densified wood chips transportation, total specific energy ranges from 213.0 kJ kg−1 to 198.2 kJ kg−1 for chestnut wood chips, from 224.9 kJ kg−1 to 197.1 kJ kg−1 for poplar wood chips and from 218.6 kJ kg−1 to 197.6 kJ kg−1 for mixture wood chips. The energy saving ratio represents the most important parameter to evaluate the energetic convenience of wood chips densification. The amount of energy saved moving for 70 km 100,000 kg of densified chestnut, poplar and a mixture of wood chips and the same quantity of raw chips with different trailers is presented in Fig. 4. The average energy saved values (grey line in Fig. 4 a-b-c) have been calculated as the ratio between total specific energy required to transport densified wood chips and total specific energy required to transport raw wood chips.
6
Fuel 262 (2020) 116618
N. Pampuro, et al.
chips have different angular coefficients because of the different number of travels requested to transport woody material in different forms: 23 and 8 travels for raw and densified conditions, respectively.
Table 6 Break-even distances (km), as a function of target density, investigated woody material and considered trailers. Trailer
Target density [kg m−3]
CC [km]
MC [km]
PC [km]
Agrireal AgrTrailer1 AgrTrailer2 AgrTrailer3 AgrTrailer4 AgrTrailer5
619 520 433 371 325 310
4.3 4.6 4.6 4.6 5.1 4.5
3.5 3.2 3.1 2.7 2.2 2.0
3.1 2.9 2.4 1.9 1.3 1.1
4. Conclusion The results of the investigation show that densification is a suitable process to improve the energetic balance of wood chips transportation when tractor and trailers are used. According to the results, the benefit is unquestionable when for transport distances are above 5 km. For distances below this threshold, the benefit of compaction should be analyzed being the advantage of wood chips densification strongly affected by the density of raw biomass and by the characteristics of the trailer adopted for the transport. Additional studies are necessary to further investigate how other conditions of these two aspects affect the energetic benefit of row wood chips compaction. Moreover the study indicates that the energetic benefit is maximum when the biomass density to be transported is equal to the vehicle theoretical density. At this conditions, the energy being used for compression is purely addressed at transport optimization, without taking into account other aspect, such as the quality of the briquettes, of the densification process. The results of this study give a first and broad indications, from the energetic point of view, of the condition to take into account to adopt densification processes of wood chips and to select the more appropriate tractor and trailer for their transportation. The outcome of the study, and the method adopted to achieve it, is not limited to the biomass, and the woodchip investigated in the present study, but it can be applied to all the circumstances when a transport of raw material is required and to explore the possible benefit of its densification. The results of the study is based exclusively on energy balance in order to assess more objectively the benefit of densification. Nevertheless, under an economic point of view results might vary because of energy prices, labour costs and local contexts. Further studies should be addressed at investigate how these aspects affect the convenience of the wood chips briquetting for energy use.
The obtained results highlighted that the wood chips transportation takes an advantage from densification saving up to 75.6%, 69.7% and 59.3% of energy for PC, MC and CC respectively. This saving is due to the reduction of the numbers of travels required for the transportation of the different materials. For this reason, it is possible to affirm that the densification process allows to better exploit trailer load capacity and make more energetically efficient, and finally more sustainable, the biomasses supply chain. 3.5. Break-even distance Break-even distance represents a parameter to evaluate the energetic benefit of wood chips densification. The break-even distance calculated for all the investigated combination of trailers and materials are reported in Table 6. Break-even point ranges from 1.1 to 5.1 km. It is a wide range, depending on the characteristics of raw woody materials, target briquette densities and trailers’ payload. As a sample result, Fig. 5 graphically reports the total specific energy requested to transport chestnut chips with AgriReal trailer; the two lines represent the energy requested to transport the raw and densified (619 kg m−3) chips at a distance up to 30 km. The two lines intersect at 4.3 km, representing the breakeven point. This means, for this specific case, that for transport distance above 4.3 km the compression process is energetically favorable while when the distance is below this threshold, it is not. Lines representing transport energy for raw and densified wood
Fig. 5. Total specific energy and break-even distance (dBE) to transport with AgriReal chestnut chips in raw (black line) and densified at 619 kg m−3 (grey line) and the relative compression energy (dashed line).
7
Fuel 262 (2020) 116618
N. Pampuro, et al.
Funding
2018;35:786–94. https://doi.org/10.1016/S0961-9534(01)00050-2. [23] Annevelink B, Anttila P, Väätäinen K, Gabrielle B, García-Galindo D, Leduc S, et al. Modeling Biomass Logistics. Model. Optim. Biomass Supply Chain. Top-Down Bottom-up Assess. Agric. For. Waste Feed., 2017, p. 79–103. doi: 10.1016/B978-012-812303-4.00004-5. [24] Rodias E, Berruto R, Busato P, Bochtis D, Sørensen CG, Zhou K. Energy savings from optimised in-field route planning for agricultural machinery. Sustain 2017:9. https://doi.org/10.3390/su9111956. [25] Rodias EC, Lampridi M, Sopegno A, Berruto R, Banias G, Bochtis DD, et al. Optimal energy performance on allocating energy crops. Biosyst Eng 2019;181:11–27. https://doi.org/10.1016/j.biosystemseng.2019.02.007. [26] Whittaker C, Shield I. Biomass Harvesting, Processing, Storage, and Transport. OPET Report 5. Elsevier Inc.; 2017. doi: 10.1016/B978-0-08-101036-5.00007-0. [27] Rodias EC, Sopegno A, Berruto R, Bochtis DD, Cavallo E, Busato P. A combined simulation and linear programming method for scheduling organic fertiliser application. Biosyst Eng 2019. https://doi.org/10.1016/j.biosystemseng.2018.11. 002. [28] Fan KQ, Zhang PF, Pei ZJ. An assessment model for collecting and transporting cellulosic biomass. Renew Energy 2013;50:786–94. https://doi.org/10.1016/j. renene.2012.08.022. [29] Ko S, Lautala P, Handler RM. Securing the feedstock procurement for bioenergy products: a literature review on the biomass transportation and logistics. J Clean Prod 2018;200:205–18. https://doi.org/10.1016/j.jclepro.2018.07.241. [30] Spinelli R, Hartsough B. A survey of Italian chipping operations. Biomass Bioenergy 2001;21:433–44. https://doi.org/10.1016/S0961-9534(01)00050-2. [31] Tabarés JLM, Ortiz L, Granada E, Viar FP. Feasibility study of energy use for densificated lignocellulosic material (briquettes). Fuel 2000;79:1229–37. https://doi. org/10.1016/S0016-2361(99)00256-2. [32] Kaliyan N, Vance Morey R. Factors affecting strength and durability of densified biomass products. Biomass Bioenergy 2009;33:337–59. https://doi.org/10.1016/j. biombioe.2008.08.005. [33] Miao Z, Phillips JW, Grift TE, Mathanker SK. Energy and pressure requirement for compression of Miscanthus giganteus to an extreme density. Biosyst Eng 2013;114:21–5. https://doi.org/10.1016/J.BIOSYSTEMSENG.2012.10.002. [34] Pampuro N, Preti C, Cavallo E. Recycling pig slurry solid fraction compost as a sound absorber. Sustain 2018:10. https://doi.org/10.3390/su10010277. [35] Pampuro N, Busato P, Cavallo E. Effect of densification conditions on specific energy requirements and physical properties of compacts made from hop cone. Energies 2018:11. https://doi.org/10.3390/en11092389. [36] Pampuro N, Bagagiolo G, Priarone PC, Cavallo E. Effects of pelletizing pressure and the addition of woody bulking agents on the physical and mechanical properties of pellets made from composted pig solid fraction. Powder Technol 2017;311:112–9. https://doi.org/10.1016/j.powtec.2017.01.092. [37] Roy MM, Corscadden KW. An experimental study of combustion and emissions of biomass briquettes in a domestic wood stove. Appl Energy 2012;99:206–12. https://doi.org/10.1016/J.APENERGY.2012.05.003. [38] Smit HC, Meincken M. Time/temperature combustion profiles of various woodbased biofuels. Biomass Bioenergy 2012;39:317–23. https://doi.org/10.1016/J. BIOMBIOE.2012.01.021. [39] Suhartini S, Hidayat N, Wijaya S. Physical properties characterization of fuel briquette made from spent bleaching earth. Biomass Bioenergy 2011;35:4209–14. https://doi.org/10.1016/J.BIOMBIOE.2011.07.002. [40] Pampuro N, Facello A, Cavallo E. Pressure and specific energy requirements for densification of compost derived from swine solid fraction. Spanish J Agric Res 2013;11:678–84. https://doi.org/10.5424/sjar/2013113-4062. [41] Tabil LG, Sokhansanj S. Process conditions affecting the physical quality of alfalfa pellets. Appl Eng Agric 1996;12:345–50. https://doi.org/10.13031/2013.25658. [42] Facello A, Pampuro N, Manzone M, Balsari P, Cavallo E. Wood chips compaction: first energetic analysis. Appl Math Sci 2014;8:6547–54. https://doi.org/10.12988/ ams.2014.46454. [43] Decreto Ministeriale 13/12/2011. Bando POI Energie Rinnovabili e risparmio energetico 2007-2013 (Biomasse) – Ministero dello Sviluppo Economico, Italian Parliament. European Parliament Directive 2009/28/EC. 2011. [44] Proskurina S, Junginger M, Heinimö J, Tekinel B, Vakkilainen E. Global biomass trade for energy—Part 2: Production and trade streams of wood pellets, liquid biofuels, charcoal, industrial roundwood and emerging energy biomass. Biofuels, Bioprod Biorefining 2019;13:371–87. https://doi.org/10.1002/bbb.1858. [45] Spinelli R, Magagnotti N, Cavallo E, Capello G, Biddoccu M. Reducing soil compaction after thinning work in agroforestry plantations. Agrofor Syst 2018. https:// doi.org/10.1007/s10457-018-0279-6. [46] Cavallo E, Ferrari E, Coccia M. Likely technological trajectories in agricultural tractors by analysing innovative attitudes of farmers. Int J Technol Policy Manag 2015;15:158. https://doi.org/10.1504/IJTPM.2015.069203. [47] Tarighi J, Ghasemzade H, Bahrami M, Abdollahpour S, Mahmoudi A, Cultrera A, et al. No Title. Biol Forum – Int J 2015;7:734–8. [48] American Society of Agricultural and Biological Engineers (ASABE). ASAE S358. 2—Moisture Measurement—Forages. Am. Soc. Agric. Biol. Eng. Stand., St. Joseph, MI, USA: 2006, p. 608. [49] American Society of Agricultural and Biological Engineers (ASABE). ASAE S269. 4—Cubes, pellets and crumbles—Definitions and methods for determining density, durability and moisture content. Am. Soc. Agric. Biol. Eng. Stand., St. Joseph, MI, USA: 2007, p. 624–6. [50] Pampuro N, Facello A, Cavallo E. Energy and pressure requirements for compression of swine solid fraction compost. J Agric Eng 2013;44:531–4. https://doi.org/ 10.4081/jae.2013. (s1):e105. [51] Boundy RG, Diegel SW, Wright LL, Davis SC. Lower and Higher Heating Values of Gas Liquid and Solid Fuels. Biomass energy data B. Ed. 4. (No. ORNL/, Oak Ridge, TN (United States): Oak Ridge National Lab.(ORNL); 2011, p. 188. doi: 10.2172/
This research received no external funding. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements The authors thank Alessio Facello (former research fellow at CNRIMAMOTER) for data recording during the experimental trial. References [1] Directive 2009/28/EC of the European Parliament and of the Council of 23 April 2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing Directives 2001/77/EC and 2003/30/EC. 2009. [2] European Commission. Summary of the Member State forecast documents. 2019. https://ec.europa.eu/energy/sites/ener/files/dir_2009_0028_article_4_3_forecast_ by_ms_symmary.pdf (accessed May 30, 2019). [3] Directive (EU) 2018/2001 of the European Parliament and of the Council of 11 December 2018 on the promotion of the use of energy from renewable sources. 2018. [4] European Commission. Biomass 2019. https://ec.europa.eu/energy/en/topics/renewable-energy/biomass (accessed September 20, 2019). [5] European Bioenergy Day. What is the EU-28 Bioenergy Consumption? 2019. http:// www.europeanbioenergyday.eu/bioenergy-facts/bioenergy-in-europe/what-is-theeu28-bioenergy-consumption/ (accessed May 20, 2019). [6] Cavallo E, Pampuro N. Effects of compressing pressure on briquettes made from woody biomass. Chem Eng Trans 2017;58:517–22. https://doi.org/10.3303/ CET1758087. [7] Flinkman M, Sikkema R, Spelter H, Jonsson R. Exploring the drivers of demand for non-industrial wood pellets for heating. Balt For 2018;24:86–98. [8] Johnston CMT, van Kooten GC. Economics of co-firing coal and biomass: an application to Western Canada. Energy Econ 2015;48:7–17. https://doi.org/10.1016/ J.ENECO.2014.11.015. [9] Capros P, Mantzos L, Parousos L, Tasios N, Klaassen G, Van Ierland T. Analysis of the EU policy package on climate change and renewables. Energy Policy 2011;39:1476–85. https://doi.org/10.1016/J.ENPOL.2010.12.020. [10] Golecha R, Gan J. Biomass transport cost from field to conversion facility when biomass yield density and road network vary with transport radius. Appl Energy 2016;164:321–31. https://doi.org/10.1016/j.apenergy.2015.11.070. [11] Facello A, Cavallo E, Magagnotti N, Paletto G, Spinelli R. The effect of chipper cut length on wood fuel processing performance. Fuel Process Technol 2013;116:228–33. https://doi.org/10.1016/j.fuproc.2013.07.002. [12] Spinelli R, Cavallo E, Facello A. A new comminution device for high-quality chip production. Fuel Process Technol 2012;99:69–74. https://doi.org/10.1016/j. fuproc.2012.01.034. [13] Ferrari E, Spinelli R, Cavallo E, Magagnotti N. Attitudes towards mechanized cut-tolength technology among logging contractors in Northern Italy. Scand J For Res 2012;27:800–6. https://doi.org/10.1080/02827581.2012.693192. [14] Micheletti Cremasco M, Giustetto A, Caffaro F, Colantoni A, Cavallo E, Grigolato S. risk assessment for musculoskeletal disorders in forestry: a comparison between RULA and REBA in the manual feeding of a wood-chipper. Int J Environ Res Public Health 2019:16. https://doi.org/10.3390/ijerph16050793. [15] Manzone M, Balsari P. The energy consumption and economic costs of different vehicles used in transporting woodchips. Fuel 2015;139:511–5. https://doi.org/10. 1016/j.fuel.2014.09.003. [16] Manzone M, Calvo A. Woodchip transportation: Climatic and congestion influence on productivity, energy and CO2 emission of agricultural and industrial convoys. Renew Energy 2017;108:250–9. https://doi.org/10.1016/j.renene.2017.02.074. [17] Han SK, Murphy GE. Solving a woody biomass truck scheduling problem for a transport company in Western Oregon, USA. Biomass Bioenergy 2012;44:47–55. https://doi.org/10.1016/j.biombioe.2012.04.015. [18] Wolfsmayr UJ, Rauch P. The primary forest fuel supply chain: a literature review. Biomass Bioenergy 2014;60:203–21. https://doi.org/10.1016/j.biombioe.2013.10. 025. [19] Atashbar NZ, Labadie N, Prins C. Modelling and optimisation of biomass supply chains: a review. Int J Prod Res 2018;7543:1–25. https://doi.org/10.1080/ 00207543.2017.1343506. [20] Malladi KT, Sowlati T. Biomass logistics: a review of important features, optimization modeling and the new trends. Renew Sustain Energy Rev 2018;94:587–99. https://doi.org/10.1016/j.rser.2018.06.052. [21] Acuna M, Mirowski L, Ghaffariyan MR, Brown M. Optimising transport efficiency and costs in Australian wood chipping operations. Biomass Bioenergy 2012;46:291–300. https://doi.org/10.1016/j.biombioe.2012.08.014. [22] Mihelič M, Spinelli R, Poj A, Ranta T, Pari L, Brambilla M, et al. An assessment model for collecting and transporting cellulosic biomass. Biomass Bioenergy
8
Fuel 262 (2020) 116618
N. Pampuro, et al. 930823. [52] Li Y, Liu H. High-pressure densification of wood residues to form an upgraded fuel. Biomass Bioenergy 2000;19:177–86. https://doi.org/10.1016/S0961-9534(00) 00026-X. [53] Obernberger I, Thek G. Physical characterisation and chemical composition of densified biomass fuels with regard to their combustion behaviour. Biomass
Bioenergy 2004;27:653–69. https://doi.org/10.1016/j.biombioe.2003.07.006. [54] Tumuluru JS, Wright CT, Hess JR, Kenney KL. A review of biomass densification systems to develop uniform feedstock commodities for bioenergy application. Biofuels, Bioprod Biorefining 2011;5:683–707. https://doi.org/10.1002/bbb.324. [55] Mani S, Tabil LG, Sokhansanj S. Evaluation of compaction equations applied to four biomass species. Can Biosyst Eng/Le Genie Des Biosyst Au Canada 2004;46:55–61.
9
Contents lists available at ScienceDirect
Fuel journal homepage: www.elsevier.com/locate/fuel
Full Length Article
Energy requirements for wood chip compaction and transportation Niccolò Pampuro, Giorgia Bagagiolo , Eugenio Cavallo ⁎
T
Institute for Agricultural and Earth Moving Machines (IMAMOTER), Italian National Research Council (CNR), Strada delle Cacce, 73, 10135 Torino (TO), Italy
GRAPHICAL ABSTRACT
ARTICLE INFO
ABSTRACT
Keywords: Briquette Densification process Compression energy Transport energy Woody biomass
Wood chips represent one of the most popular biomass fuel in latest cogenerating plants and in small heating systems. This fuel, being characterized by low bulk density, requires high transportation costs. This obstacle can be overcome by wood chips densification. The authors investigated the energy benefit of wood chips densification for transport operations for “short supply chain” as defined by the Italian government for the biomass fuel subsidy scheme. Three different woods (poplar, chestnut and a mixture of spruce and eastern white pine) chips and six different tractor’s trailed trailers were investigated. The total specific energy (kJ kg−1) required to transport a defined quantity of wood chips, the energy saving ratio (%) from chips’ compaction and the breakeven distance (km) between raw and compressed chips were calculated. The results highlights that densification process of wood chips is an interesting opportunity to improve the transport energetic convenience. The benefit of wood chips densification is strongly affected by raw wood chips density values and by trailer characteristics: the benefit is maximum when the density of compressed wood chips to be transported attains the vehicle theoretical density.
1. Introduction
this agreement fostered the renewable energy sources demand. As a result, the renewable energy production largely grew in the electricity, cooling/heating and transport sectors and, consequently, the forecast of renewable energy consumption by 2020 in the EU should slightly exceed the 20% target [2]. In 2018 the EU countries agreed to increase to 32% the binding EU target on renewable energy adopting the revised Renewable Energy Directive [3]. In the 2012, biomass and waste represented about two-thirds of the
The main target of the 20-20-20 of the European plan on climate change adopted by the European Union (EU) in 2009 was to reduce the greenhouse gas emissions by 20% compared to the 1990 levels, to increase the share of renewable energy to 20% of the total energy consumption and to achieve a 20% increase in energy efficiency by 2020 [1]. Since then European and national laws and rules issued according
⁎
Corresponding author. E-mail address: [email protected] (G. Bagagiolo).
https://doi.org/10.1016/j.fuel.2019.116618 Received 31 July 2019; Received in revised form 5 November 2019; Accepted 6 November 2019 Available online 15 November 2019 0016-2361/ © 2019 Elsevier Ltd. All rights reserved.
Fuel 262 (2020) 116618
N. Pampuro, et al.
renewable energy consumption of the EU [4] and, according to calculations from 2015 Eurostat data [5], the residential utilization represent half of total European bio-heat consumption. Among renewable energy sources, biomass use has been strongly encouraged in order to replace fossil fuels in many applications, from heating to electricity production [6]. Wood biomass are gaining in popularity for heating and power production, because of subsidies, taxexemptions and other incentives in application of schemes for CO2neutral energy and greenhouse gas emission reduction, environmental sustainability, and the desire to reduce dependence from fossil fuels [7–9]. Woody biofuel production consist of different operations: growing and harvesting biomass, converting biomass to bioenergy and bioproducts, and, finally, delivering end products to distribution centers or end users [10]. Comminution is an effective process to make wood fuels competitive with other energy sources: comminuted woodchips can feed automated chip-fed boilers, offering user-friendly operation [11]. New technologies and innovative solutions contribute to improve efficiency of the comminution process and, thus, increase the competitiveness of wood chips and the safety and comfort for the forestry workers [12–14]. However, as reported by a number of studies [15–19], along the woody biomass supply chain, biomass transport from comminution site to the end user is quite a critical point. In particular, the vehicles used must guarantee high versatility to operate under different working conditions and, at the same time, with low operating costs [15]. Several studies investigated the biomass supply chain and/or logistics optimization [20–23]. Most of the studies [24–27] focused on vehicles optimization and route planning for energy savings adopting models based on fuel consumption database and theoretical calculation. Wood chip can be transported by industrial vehicles and by agricultural trailers coupled with tractors [15]. Various studies on wood biomass supply reports trucks as the most effective road transportation systems [17,28,29]. However, trucks are generally suitable for on-road long distances transportations while their adoption is limited by the possibility to travel forest roads and to access forestry yards [16]. According the results from a survey by Spinelli and Hartsough on Italian chipping operation [30] wood chips are usually transported by trucks when distances are 30 km or above, while for shorter distances (3–4 km one way) most operators use farm tractors with PTO-powered trailers. Nevertheless, Manzone and Calvo [16] observed that the use of agricultural convoys (tractor plus trailer) has been increasing in the woodchip transportation on distances up to 70 km. The possibility of using standard equipment available in the farm and of directly loading in the field or comminution site play a key role in selecting agricultural trailers, even if with lower capacity than industrial convoys, to optimize logistic operations for wood chips transportation [31]. In case of comminuted woody biomass (eg. woodchips), characterized by low bulk density, transportation and storage phases can be further optimized through densification processes that can be used to produce a uniform material with favorable physical and mechanical effects on the fuel properties [23]. The densification process is widely adopted on a various set of agricultural particulate raw materials to enhance and make their characteristics more suitable for the final use [32–36]. According to Kaliyan and Vance Morey [32], typically, two techniques are used to compact particulate materials: tumble agglomeration and pressure agglomeration. With the tumble agglomeration the densified products are produced by means of typical movements of the bulk materials, containing a binder, in a specific equipment (e.g. balling discs, balling drums and balling cones) [32]. With the pressure agglomeration the density value of a bulk material is achieved applying a significant force in a confined volume [35]. Briquetting, the most common process to compact solid biofuels (e.g. wood chips), belong to pressure agglomeration technique. Densification processes, especially briquetting, improve combustion
properties of biomass [37–39] however, as reported by some authors [40,41], the densification processes require high energy input. Furthermore higher the density of the compacts greater their durability, as reported by Facello et al. [42] in a study on woodchip briquetting process. The present study investigates the possible beneficial effect of densification process on woodchip logistics comparing the energy required for transportation of raw and densified materials. The study does not approach economic analysis deferring this issue to further studies specifically conceived. Furthermore, the study aims at calculating the break-even-distance, the distance above which, the densification process became energetically profitable for the wood chips transportation. The investigation, unlikely previous studies, considers fuel consumption recorded on real tractor and trailer transport operation. The study considers three different woody materials and six different agricultural trailers. 2. Materials and methods The investigation has been performed considering to transport 100,000 kg of raw wood chips from a point A (for example a comminution site) to a point B (for example a storing site or a power station). The maximum distance has been set to 70 km: it is the maximum distance to comply with the definition of “short supply chain” according to the Italian regulation [43] to access the subsidies scheme for the renewable energy production from woody biomass. Besides that, this is a common condition considering wood chips, as fuelwood, are mostly used and traded locally for residential and “district heating” consumption [44]. Tractors and trailers are commonly adopted for agroforestry wood chip forwarding because they are more suitable to access rough terrain than trucks and because they are very common and cheap to recruit among agricultural and forestry operations [45]. Furthermore, tractors with trailers find growing application in transport of goods issued from the agricultural sector thanks to the technical solutions they are equipped with to attain high on-road speeds and the road regulations introduced in the last decades [9,46]. 2.1. Transportation data conditions The investigation is addressed at identifying a set of equations that can be applied to different kind of vehicle when the load capacity, the fuel consumption and average speed data are known. In this study, the fuel consumed for the transport has been measured with an experimental trial in real conditions on 3 km flat route. A 118 kW, 4 wheel-drive, and 19 gears full power-shift transmission tractor towing a 3 axles, 21 m3 volume trailer has been used. The consumption of the tractor was measured when towing the trailer at its maximum mass, 20,000 kg, and with the same trailer in empty condition, 7000 kg. The trailer adopted for the experimental trial (AgriReal in Table 1) comply with the Italian road rules (20,000 kg maximum mass) and has payload (13,000 kg) and empty mass (7000 kg) representative of the trailers in use in the Italian farms. Table 1 Main characteristics of the considered trailers. The theoretical density is the density at which both maximum load volume and load mass are reached.
2
Trailer
Volume [m−3]
Payload [kg]
Theoretical density [kg m−3]
AgriReal AgriTrailer1 AgriTrailer2 AgriTrailer3 AgriTrailer4 AgriTrailer5
21 25 30 35 40 42
13,000 13,000 13,000 13,000 13,000 13,000
619 520 433 371 325 310
Fuel 262 (2020) 116618
N. Pampuro, et al.
Tractor’s fuel consumption and vehicle speed were recorded from the tractor via CANBUS diagnostic connector [47]. Data were later analyzed with the Vector Canalyzer 8.0 suite. The tests have been replicated four times. The data obtained with AgriReal trailer have been used to calculate the values of fuel consumption for the investigated additional trailers (AgriTrailer# in Table 1) adopting the linear interpolation in Eq. (1).
Fr = k 0 + (1
Table 3 Coefficients values – km and c – required for Specific Compression Energy calculation depending on wood chips type [6]. Wood chips
CC PC MC
(1)
k 0)·Load/Load max,
where
Coefficient Km [kJ m3 kg−2]
c [kJ kg−1]
0.048 0.090 0.068
−9.2 −23.3 −16.0
Fr = fuel ratio used to scale the full load fuel consumption (0 ≤ Fr ≤ 1) k0 = fuel ratio measured with empty trailer Load = real trailer load Load max = maximum trailer load 2.2. Investigated vehicles Additional trailers (AgriTrailerl# in Table 1) with different volume of the container have been considered for the study. The different volumes of the container have been theoretically calculated varying the height of the sides of the trailer. Total mass and payload in all conditions are 20,000 kg and 13,000 kg respectively. For the study we defined the theoretical density [kg m−3] as the ratio between the payload and volume of the trailer. It is the minimum density that permit to completely exploit the transportation capacity of the trailers. Being the payload the same for all the different trailers the theoretical density varies according to their different capacities (Table 1).
Fig. 1. Fuel consumption reduction ratio as a function of load ratio.
2.4.1. Compression energy The compression energy is directly related to the target density [kg m−3] of the briquettes. The study takes into account only the energetic requirements needed by the densification process and does not consider accessory operations, such as drying. Eq. (3) defines the specific compression energy (Ecm specific) according to the results of the study conducted by Pampuro et al. [50] on densification process of similar raw material.
2.3. Investigated wood chips Chips from three different types of wood have been considered for the study: chestnut (Castanea sativa L.) (CC), hybrid poplar (Populus × euramericana Guiner) (PC) and a mixture of spruce (Picea abies L.) and eastern white pine (Pinus strobus L.) (MC). The characteristics of the wood chips are reported in Table 2. The wood chips moisture content has been determined according the American Society of Agricultural and Biological Engineers (ASABE) Standard S358.2 [48] while the bulk density of raw wood chips has been measured according to the ASABE Standard S269.4 [49].
Ecm specific = (km +c) where Ecm specific = Specific compression energy [kJ kg−1]; km = material-dependent coefficient [kJ m3 kg−2]; ρ = briquettes density [kg m−3]; c = material-dependent offset coefficient [kJ kg−1].
2.4. Energy calculation For the study we define the total energy (Et) (Eq. (2)) as the sum of the energy required for compressing wood chips (Ecm) into briquettes and the energy required for transportation (Etr):
Table 3 shows the coefficients values – km and c – of the wood chips considered in the study. km is the proportional coefficient between final density value and specific energy while c is an offset coefficient; it is negative because the initial density value is different from zero. The material-dependent coefficients were measured by Cavallo et al. (2017) in a study related to the effect of compressing pressure on briquettes made from the same three woody biomass (PC, CC; MC) considered in the present study. The compression energy (Ecm) is calculated according Eq. (4). Ecm is the energy required to densify a specific wood chips quantity [kg] producing briquettes with a specific density value [kg m−3]:
(2)
Et = Ecm + Etr where Et = Total energy [J]; Ecm = Compression energy [J]; Etr = Transport energy [J].
Ecm = Ecm specific·Wt = (km +c)·Wt
Table 2 Moisture content (%) and raw density values (kg m−3) of the investigated wood chips: chestnut (CC), hybrid poplar (PC) and Mixture of spruce and eastern white pine (MC). Mean value ± standard error of 3 replicates. Wood chips
ID
Raw density (kg m−3)
Moisture (%)
Chestnut Hybrid poplar Mixture
CC PC MC
212.0 ± 1.3 119.0 ± 0.5 152.0 ± 0.8
7.1 ± 0.1 7.9 ± 0.1 8.1 ± 0.1
(3)
(4)
where Wt = total amount of wood chips to be compressed [kg]. 2.4.2. Transport energy Eq. (5) defines the transport energy (Etr) as follow:
Etr = k v ·d·nt 3
(5)
Fuel 262 (2020) 116618
N. Pampuro, et al.
Table 4 Fuel ratio and fuel consumption in relation to load rate for the six considered trailers. PC
MC
Bulk Density
Load rate (Load/ Load Max) [kg m−3] [%] Agrireal
Fuel ratio Fuel consumption
CC
Bulk Density
–
[kg h−1]
Load rate (Load/ Load Max) [kg m−3] [%]
Fuel ratio Fuel consumption –
Bulk Density
Fuel ratio Fuel consumption
[kg h−1]
Load rate (Load/ Load Max) [kg m−3] [%]
–
[kg h−1]
Raw 119 Densified. 619
19.2% 100.0%
0.87 1.00
12.3 14.1
152 619
25.0% 100.0%
0.88 1.00
12.4 14.1
212 619
34.0% 100.0%
0.89 1.00
12.6 14.1
AgrTrailer1 Raw 119 Densified. 520
22.9% 100.0%
0.88 1.00
12.4 14.1
152 520
29.0% 100.0%
0.89 1.00
12.5 14.1
212 520
41.0% 100.0%
0.91 1.00
12.8 14.1
AgrTrailer2 Raw 119 Densified. 433
27.5% 100.0%
0.88 1.00
12.5 14.1
152 433
35.0% 100.0%
0.90 1.00
12.6 14.1
212 433
49.0% 100.0%
0.92 1.00
12.9 14.1
AgrTrailer3 Raw 119 Densified. 371
32.0% 100.0%
0.89 1.00
12.6 14.1
152 371
41.0% 100.0%
0.91 1.00
12.8 14.1
212 371
57.0% 100.0%
0.93 1.00
13.1 14.1
AgrTrailer4 Raw 119 Densified. 325
36.6% 100.0%
0.90 1.00
12.7 14.1
152 325
47.0% 100.0%
0.91 1.00
12.9 14.1
212 325
65.0% 100.0%
0.94 1.00
13.3 14.1
AgrTrailer5 Raw 119 Densified. 310
38.4% 100.0%
0.90 1.00
12.7 14.1
152 310
49.0% 100.0%
0.92 1.00
13.0 14.1
212 310
68.0% 100.0%
0.95 1.00
13.4 14.1
where
Ecm = compression energy; kv = specific vehicle energy; ntR = number of travels needed to move the specific amount (Wt) of raw wood chips; ntB = number of travels needed to move the specific amount (Wt) of densified wood chips.
kv = is a vehicle-dependent coefficient [MJ km−1], representing the specific vehicle energy in terms of energy per unit of distance. This parameter takes into account vehicle average fuel consumption (Fc) [kg h−1] as a function of loading conditions, vehicle speed (v) [km h−1] and fuel higher heating value (HHV) [MJ kg−1]; d = distance covered by the vehicle for wood chips transportation [km]; nt = number of travels.
When the distance is lower than dBE, the energy required for the densification is higher than the energy saved with transportation. On the contrary, at distances above the dBE the energy saved in transportation is higher than the energy used for densification.
More in detail, Eqs. (6) and (7) define kv and nt, respectively: (6)
kv = (Fc·HHV)/v
3. Results and discussion
In the present study, according to ORNL [51], the HHV value for commercial Diesel fuel is assumed equal to 45.6 MJ kg−1.
nt = Wt /WL = W/(V t L·
bk )
3.1. Measured parameters The average fuel consumption and speed calculated on data recorded for the AgriReal trailer in full load condition are 14.1 kg h−1 and 34.3 km h−1, respectively. The average fuel consumption calculated with the empty trailer is 16% lower than in full load trailer condition, corresponding to 11.8 kg h−1 (k0 = 0.84, in Eq. (1)). The reduced fuel consumption is mainly due to the lower tire rolling resistance, proportional to the vehicle mass [31]. The fuel consumption obtained with AgriReal with fully loaded trailer has been used as reference to calculate the fuel consumption in other load conditions and for other trailers (AgriTrailer#) with a linear interpolation between the unloaded and full load conditions (Fig. 1). The aerodynamic influence of different trailers has been neglected, due to the small differences in cross area and the relative low vehicle speed. The linear interpolation between unloaded and full load conditions calculated according Eq. (1) and used to compute the fuel consumption depending to the load conditions is reported in Fig. 1, where, k0, corresponding to unloaded condition, is 0.84. Table 4 reports the values of fuel consumption calculated according to load conditions. The physical characteristics (moisture and density) of raw chips is reported in Table 2. The chips’ moisture ranges from 7.1 to 8.1% while the densities of raw materials varies from 119 to 212 kg m−3. The moisture values are in line with those recommended by studies on densification processes to upgrade woody biomass fuels [52–54].
(7)
The amount of wood chips (Wt) is a fundamental parameter to calculate the number of travels (nt) needed to complete the wood chips transportation. nt represents an integer value (decimal value rounded to the nearest higher integer) directly linked to the physical loading capacity of the trailer used (weight limit WL [kg] and volume limit VL [m3]). In this study a single “travel” include the trip from the point A to the point B at full load condition and the trip back with empty load. The trailers characteristics, in particular mass and dimension limits are required to calculate WL as a function of material bulk density (ρbk [kg·m−3]) and max vehicle load volume VL [m−3]. The algorithm developed in this study has been adopted to calculate the numbers of travel required to move the Wt quantity respecting the weight and volume trailers limits for chips with bulk density in the range of 250 ÷ 1000 kg·m−3. 2.5. Break-even distance Break-even distance (dBE) can be assumed as the distance [km] where the totals energy required for raw and densified wood chips transportation are equal. It is defined in Eq. (8):
dBE = Ecm /k v (ntR
ntB)
(8)
where 4
Fuel 262 (2020) 116618
N. Pampuro, et al.
than the theoretical density of the transportation mean that will be adopted it implies an unjustified excess of energy consumption for briquetting than that required. In the present investigation, the minimum number of travels requested to move 100,000 kg of densified wood chips is equal to 8. Indeed, after exceeding the theoretical density values for each of the trailers considered the number of travels does not decrease further (Fig. 2). 3.3. Compression energy requirements The specific compression energy values required for compressing the three types of wood chips until the theoretical density values for the different trailers are achieved varies from 4.6 to 32.4 kJ kg−1 (Fig. 3). Compression energy requirements are affected by the target density of the woodchip briquettes and by the physical properties of the investigated materials [55]. For instance, to obtain woodchip briquettes with target density equal to 520 kg m−3 (AgriTrailer1), 23.5 kJ kg−1, 19.4 kJ kg−1 and 15.8 kJ kg−1 are required respectively for PC, MC and CC while to achieve the same target density compressing hops cones lower specific compression energy (14.2 kJ kg−1) was required [35],
Fig. 2. Numbers of travels requested to transport 100,000 kg of wood chips as a function of bulk density.
3.2. Number of travels requested for wood chips transportation As reported in Eq.5, transport energy is directly proportional to the numbers of travels necessary to move the investigated material from point A to point B. The number of travels decreases when the biomass density increases, as long as the maximum payload does not limit the load size (Fig. 2). Moreover the number of travels is affected by the trailers characteristics, namely by their payload. Indeed, AgrTrailer4 and AgrTrailer5, being characterized by high volume capacity, require less travels. Nevertheless, trailers characteristics can be neglected when density of briquettes from chips are equal to the theoretical density. This condition corresponds to the best exploitation of the volume of the trailer at the given density and maximum payload. So, to take advantages from wood chips densification in terms of number of travels reduction, for each trailer considered, the optimal wood chips briquettes density (the target density) should not be higher than the theoretical trailer density (Table 1). Achieving a briquettes density higher
3.4. Total energy requirements Table 5 reports the results from energetic analysis of wood chips transportation on a distance of 70 km. More in detail, for each investigated trailer and woody material, Table 5 presents a comparison between raw and densified wood chips. Results highlight that the total specific energy (Et specific) required to transport raw wood chips corresponds to the specific transport energy (Etr specific) values. Considering the densified wood chips, the Total Specific Energy (Et specific) includes also the Specific Compression Energy (Ecm specific) values. Total specific energy required to transport raw wood chips ranges from 920.0 kJ kg−1 to 479.1 kJ kg−1 for poplar wood chips, from 523.2 kJ kg−1 to 280.7 kJ kg−1 for chestnut wood chips and from 721.6 kJ kg−1 to 368.9 kJ kg−1 for mixture wood chips. With regard to
Fig. 3. Specific compression energy values (kJ kg−1) required for densifying the three investigated wood chips (PC, MC and CC) at the trailer theoretical density values.
5
Raw Densified
Raw Densified
Raw Densified
Raw Densified
Raw Densified
Raw Densified
AgriReal
AgriTrailer1
AgriTrailer2
AgriTrailer3
AgriTrailer4
AgriTrailer5
119.0 309.5
119.0 325.0
119.0 371.4
119.0 433.3
119.0 520.0
119.0 619.0
Density [kg m−3]
PC Etr specific [kJ kg−1] 920.0 192.5 765.7 192.5 655.4 192.5 567.3 192.5 501.1 192.5 479.1 192.5
nt
41 8
34 8
29 8
25 8
22 8
21 8
Et specific [kJ kg−1] 920.0 224.9 765.7 216.0 655.4 208.2 567.3 202.6 501.1 198.5 479.1 197.1
Ecm specific [kJ kg−1] 0.0 32.4 0.0 23.5 0.0 15.7 0.0 10.1 0.0 6.0 0.0 4.6
152.0 309.5
152.0 325.0
152.0 371.4
152.0 433.3
152.0 520.0
152.0 619.0
Density [kg m−3]
MC
16 8
17 8
19 8
22 8
27 8
32 8
nt
368.9 192.5
390.9 192.5
435.0 192.5
501.1 192.5
611.3 192.5
721.6 192.5
Etr specific [kJ kg−1]
0.0 5.0
0.0 6.1
0.0 9.3
0.0 13.5
0.0 19.4
0.0 26.1
Ecm specific [kJ kg−1]
368.9 197.6
390.9 198.6
435.0 201.8
501.1 206.0
611.3 211.9
721.6 218.6
Et specific [kJ kg−1]
212.0 309.5
212.0 325.0
212.0 371.4
212.0 433.3
212.0 520.0
212.0 619.0
Density [kg m−3]
CC
12 8
12 8
14 8
16 8
19 8
23 8
nt
280.7 192.5
280.7 192.5
324.8 192.5
368.9 192.5
435.0 192.5
523.2 192.5
Etr specific [kJ kg−1]
0.0 5.7
0.0 6.4
0.0 8.6
0.0 11.6
0.0 15.8
0.0 20.5
Ecm specific [kJ kg−1]
280.7 198.2
280.7 198.9
324.8 201.1
368.9 204.1
435.0 208.3
523.2 213.0
Et specific [kJ kg−1]
Table 5 Main parameters (density and nt) and energetic components (Etr specific and Ecm specific) affecting the total specific energy (Et specific) required to transport 100,000 kg of wood chips from comminution site to end user site (70 km) in raw and densified condition. Reported values have been calculated for the three different investigated woody material (CC: chestnut; MC: mixture of spruce and eastern white pine; PC: poplar) and for the six different considered trailers (AgriReal, AgriTrailer1, AgriTrailer2, AgriTrailer3, AgriTrailer4 and AgriTrailer5). nt: number of travel requested to transport 100,000 kg of wood chips from comminution site to end user site (70 km) in raw and densified condition. Etr specific: specific transport energy required to transport 1.0 kg of the investigated material from comminution site to end user site (70 km) in raw and densified condition. Ecm specific: specific compression energy required to densified 1.0 kg of the investigated material. Et specific: total specific energy required to transport 1.0 kg of the investigated material from comminution site to end user site (70 km) in raw and densified condition.
N. Pampuro, et al.
Fuel 262 (2020) 116618
Fig. 4. Comparison between the amount of total energy required to transport 100,000 kg of densified wood chips and the same quantity of raw chips (a: poplar wood chips; b:chestnut wood chips; c: mixture of spruce and eastern white pine wood chips) with different trailers from comminution site to end user site (70 km). The black lines represent the average energy saved.
densified wood chips transportation, total specific energy ranges from 213.0 kJ kg−1 to 198.2 kJ kg−1 for chestnut wood chips, from 224.9 kJ kg−1 to 197.1 kJ kg−1 for poplar wood chips and from 218.6 kJ kg−1 to 197.6 kJ kg−1 for mixture wood chips. The energy saving ratio represents the most important parameter to evaluate the energetic convenience of wood chips densification. The amount of energy saved moving for 70 km 100,000 kg of densified chestnut, poplar and a mixture of wood chips and the same quantity of raw chips with different trailers is presented in Fig. 4. The average energy saved values (grey line in Fig. 4 a-b-c) have been calculated as the ratio between total specific energy required to transport densified wood chips and total specific energy required to transport raw wood chips.
6
Fuel 262 (2020) 116618
N. Pampuro, et al.
chips have different angular coefficients because of the different number of travels requested to transport woody material in different forms: 23 and 8 travels for raw and densified conditions, respectively.
Table 6 Break-even distances (km), as a function of target density, investigated woody material and considered trailers. Trailer
Target density [kg m−3]
CC [km]
MC [km]
PC [km]
Agrireal AgrTrailer1 AgrTrailer2 AgrTrailer3 AgrTrailer4 AgrTrailer5
619 520 433 371 325 310
4.3 4.6 4.6 4.6 5.1 4.5
3.5 3.2 3.1 2.7 2.2 2.0
3.1 2.9 2.4 1.9 1.3 1.1
4. Conclusion The results of the investigation show that densification is a suitable process to improve the energetic balance of wood chips transportation when tractor and trailers are used. According to the results, the benefit is unquestionable when for transport distances are above 5 km. For distances below this threshold, the benefit of compaction should be analyzed being the advantage of wood chips densification strongly affected by the density of raw biomass and by the characteristics of the trailer adopted for the transport. Additional studies are necessary to further investigate how other conditions of these two aspects affect the energetic benefit of row wood chips compaction. Moreover the study indicates that the energetic benefit is maximum when the biomass density to be transported is equal to the vehicle theoretical density. At this conditions, the energy being used for compression is purely addressed at transport optimization, without taking into account other aspect, such as the quality of the briquettes, of the densification process. The results of this study give a first and broad indications, from the energetic point of view, of the condition to take into account to adopt densification processes of wood chips and to select the more appropriate tractor and trailer for their transportation. The outcome of the study, and the method adopted to achieve it, is not limited to the biomass, and the woodchip investigated in the present study, but it can be applied to all the circumstances when a transport of raw material is required and to explore the possible benefit of its densification. The results of the study is based exclusively on energy balance in order to assess more objectively the benefit of densification. Nevertheless, under an economic point of view results might vary because of energy prices, labour costs and local contexts. Further studies should be addressed at investigate how these aspects affect the convenience of the wood chips briquetting for energy use.
The obtained results highlighted that the wood chips transportation takes an advantage from densification saving up to 75.6%, 69.7% and 59.3% of energy for PC, MC and CC respectively. This saving is due to the reduction of the numbers of travels required for the transportation of the different materials. For this reason, it is possible to affirm that the densification process allows to better exploit trailer load capacity and make more energetically efficient, and finally more sustainable, the biomasses supply chain. 3.5. Break-even distance Break-even distance represents a parameter to evaluate the energetic benefit of wood chips densification. The break-even distance calculated for all the investigated combination of trailers and materials are reported in Table 6. Break-even point ranges from 1.1 to 5.1 km. It is a wide range, depending on the characteristics of raw woody materials, target briquette densities and trailers’ payload. As a sample result, Fig. 5 graphically reports the total specific energy requested to transport chestnut chips with AgriReal trailer; the two lines represent the energy requested to transport the raw and densified (619 kg m−3) chips at a distance up to 30 km. The two lines intersect at 4.3 km, representing the breakeven point. This means, for this specific case, that for transport distance above 4.3 km the compression process is energetically favorable while when the distance is below this threshold, it is not. Lines representing transport energy for raw and densified wood
Fig. 5. Total specific energy and break-even distance (dBE) to transport with AgriReal chestnut chips in raw (black line) and densified at 619 kg m−3 (grey line) and the relative compression energy (dashed line).
7
Fuel 262 (2020) 116618
N. Pampuro, et al.
Funding
2018;35:786–94. https://doi.org/10.1016/S0961-9534(01)00050-2. [23] Annevelink B, Anttila P, Väätäinen K, Gabrielle B, García-Galindo D, Leduc S, et al. Modeling Biomass Logistics. Model. Optim. Biomass Supply Chain. Top-Down Bottom-up Assess. Agric. For. Waste Feed., 2017, p. 79–103. doi: 10.1016/B978-012-812303-4.00004-5. [24] Rodias E, Berruto R, Busato P, Bochtis D, Sørensen CG, Zhou K. Energy savings from optimised in-field route planning for agricultural machinery. Sustain 2017:9. https://doi.org/10.3390/su9111956. [25] Rodias EC, Lampridi M, Sopegno A, Berruto R, Banias G, Bochtis DD, et al. Optimal energy performance on allocating energy crops. Biosyst Eng 2019;181:11–27. https://doi.org/10.1016/j.biosystemseng.2019.02.007. [26] Whittaker C, Shield I. Biomass Harvesting, Processing, Storage, and Transport. OPET Report 5. Elsevier Inc.; 2017. doi: 10.1016/B978-0-08-101036-5.00007-0. [27] Rodias EC, Sopegno A, Berruto R, Bochtis DD, Cavallo E, Busato P. A combined simulation and linear programming method for scheduling organic fertiliser application. Biosyst Eng 2019. https://doi.org/10.1016/j.biosystemseng.2018.11. 002. [28] Fan KQ, Zhang PF, Pei ZJ. An assessment model for collecting and transporting cellulosic biomass. Renew Energy 2013;50:786–94. https://doi.org/10.1016/j. renene.2012.08.022. [29] Ko S, Lautala P, Handler RM. Securing the feedstock procurement for bioenergy products: a literature review on the biomass transportation and logistics. J Clean Prod 2018;200:205–18. https://doi.org/10.1016/j.jclepro.2018.07.241. [30] Spinelli R, Hartsough B. A survey of Italian chipping operations. Biomass Bioenergy 2001;21:433–44. https://doi.org/10.1016/S0961-9534(01)00050-2. [31] Tabarés JLM, Ortiz L, Granada E, Viar FP. Feasibility study of energy use for densificated lignocellulosic material (briquettes). Fuel 2000;79:1229–37. https://doi. org/10.1016/S0016-2361(99)00256-2. [32] Kaliyan N, Vance Morey R. Factors affecting strength and durability of densified biomass products. Biomass Bioenergy 2009;33:337–59. https://doi.org/10.1016/j. biombioe.2008.08.005. [33] Miao Z, Phillips JW, Grift TE, Mathanker SK. Energy and pressure requirement for compression of Miscanthus giganteus to an extreme density. Biosyst Eng 2013;114:21–5. https://doi.org/10.1016/J.BIOSYSTEMSENG.2012.10.002. [34] Pampuro N, Preti C, Cavallo E. Recycling pig slurry solid fraction compost as a sound absorber. Sustain 2018:10. https://doi.org/10.3390/su10010277. [35] Pampuro N, Busato P, Cavallo E. Effect of densification conditions on specific energy requirements and physical properties of compacts made from hop cone. Energies 2018:11. https://doi.org/10.3390/en11092389. [36] Pampuro N, Bagagiolo G, Priarone PC, Cavallo E. Effects of pelletizing pressure and the addition of woody bulking agents on the physical and mechanical properties of pellets made from composted pig solid fraction. Powder Technol 2017;311:112–9. https://doi.org/10.1016/j.powtec.2017.01.092. [37] Roy MM, Corscadden KW. An experimental study of combustion and emissions of biomass briquettes in a domestic wood stove. Appl Energy 2012;99:206–12. https://doi.org/10.1016/J.APENERGY.2012.05.003. [38] Smit HC, Meincken M. Time/temperature combustion profiles of various woodbased biofuels. Biomass Bioenergy 2012;39:317–23. https://doi.org/10.1016/J. BIOMBIOE.2012.01.021. [39] Suhartini S, Hidayat N, Wijaya S. Physical properties characterization of fuel briquette made from spent bleaching earth. Biomass Bioenergy 2011;35:4209–14. https://doi.org/10.1016/J.BIOMBIOE.2011.07.002. [40] Pampuro N, Facello A, Cavallo E. Pressure and specific energy requirements for densification of compost derived from swine solid fraction. Spanish J Agric Res 2013;11:678–84. https://doi.org/10.5424/sjar/2013113-4062. [41] Tabil LG, Sokhansanj S. Process conditions affecting the physical quality of alfalfa pellets. Appl Eng Agric 1996;12:345–50. https://doi.org/10.13031/2013.25658. [42] Facello A, Pampuro N, Manzone M, Balsari P, Cavallo E. Wood chips compaction: first energetic analysis. Appl Math Sci 2014;8:6547–54. https://doi.org/10.12988/ ams.2014.46454. [43] Decreto Ministeriale 13/12/2011. Bando POI Energie Rinnovabili e risparmio energetico 2007-2013 (Biomasse) – Ministero dello Sviluppo Economico, Italian Parliament. European Parliament Directive 2009/28/EC. 2011. [44] Proskurina S, Junginger M, Heinimö J, Tekinel B, Vakkilainen E. Global biomass trade for energy—Part 2: Production and trade streams of wood pellets, liquid biofuels, charcoal, industrial roundwood and emerging energy biomass. Biofuels, Bioprod Biorefining 2019;13:371–87. https://doi.org/10.1002/bbb.1858. [45] Spinelli R, Magagnotti N, Cavallo E, Capello G, Biddoccu M. Reducing soil compaction after thinning work in agroforestry plantations. Agrofor Syst 2018. https:// doi.org/10.1007/s10457-018-0279-6. [46] Cavallo E, Ferrari E, Coccia M. Likely technological trajectories in agricultural tractors by analysing innovative attitudes of farmers. Int J Technol Policy Manag 2015;15:158. https://doi.org/10.1504/IJTPM.2015.069203. [47] Tarighi J, Ghasemzade H, Bahrami M, Abdollahpour S, Mahmoudi A, Cultrera A, et al. No Title. Biol Forum – Int J 2015;7:734–8. [48] American Society of Agricultural and Biological Engineers (ASABE). ASAE S358. 2—Moisture Measurement—Forages. Am. Soc. Agric. Biol. Eng. Stand., St. Joseph, MI, USA: 2006, p. 608. [49] American Society of Agricultural and Biological Engineers (ASABE). ASAE S269. 4—Cubes, pellets and crumbles—Definitions and methods for determining density, durability and moisture content. Am. Soc. Agric. Biol. Eng. Stand., St. Joseph, MI, USA: 2007, p. 624–6. [50] Pampuro N, Facello A, Cavallo E. Energy and pressure requirements for compression of swine solid fraction compost. J Agric Eng 2013;44:531–4. https://doi.org/ 10.4081/jae.2013. (s1):e105. [51] Boundy RG, Diegel SW, Wright LL, Davis SC. Lower and Higher Heating Values of Gas Liquid and Solid Fuels. Biomass energy data B. Ed. 4. (No. ORNL/, Oak Ridge, TN (United States): Oak Ridge National Lab.(ORNL); 2011, p. 188. doi: 10.2172/
This research received no external funding. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements The authors thank Alessio Facello (former research fellow at CNRIMAMOTER) for data recording during the experimental trial. References [1] Directive 2009/28/EC of the European Parliament and of the Council of 23 April 2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing Directives 2001/77/EC and 2003/30/EC. 2009. [2] European Commission. Summary of the Member State forecast documents. 2019. https://ec.europa.eu/energy/sites/ener/files/dir_2009_0028_article_4_3_forecast_ by_ms_symmary.pdf (accessed May 30, 2019). [3] Directive (EU) 2018/2001 of the European Parliament and of the Council of 11 December 2018 on the promotion of the use of energy from renewable sources. 2018. [4] European Commission. Biomass 2019. https://ec.europa.eu/energy/en/topics/renewable-energy/biomass (accessed September 20, 2019). [5] European Bioenergy Day. What is the EU-28 Bioenergy Consumption? 2019. http:// www.europeanbioenergyday.eu/bioenergy-facts/bioenergy-in-europe/what-is-theeu28-bioenergy-consumption/ (accessed May 20, 2019). [6] Cavallo E, Pampuro N. Effects of compressing pressure on briquettes made from woody biomass. Chem Eng Trans 2017;58:517–22. https://doi.org/10.3303/ CET1758087. [7] Flinkman M, Sikkema R, Spelter H, Jonsson R. Exploring the drivers of demand for non-industrial wood pellets for heating. Balt For 2018;24:86–98. [8] Johnston CMT, van Kooten GC. Economics of co-firing coal and biomass: an application to Western Canada. Energy Econ 2015;48:7–17. https://doi.org/10.1016/ J.ENECO.2014.11.015. [9] Capros P, Mantzos L, Parousos L, Tasios N, Klaassen G, Van Ierland T. Analysis of the EU policy package on climate change and renewables. Energy Policy 2011;39:1476–85. https://doi.org/10.1016/J.ENPOL.2010.12.020. [10] Golecha R, Gan J. Biomass transport cost from field to conversion facility when biomass yield density and road network vary with transport radius. Appl Energy 2016;164:321–31. https://doi.org/10.1016/j.apenergy.2015.11.070. [11] Facello A, Cavallo E, Magagnotti N, Paletto G, Spinelli R. The effect of chipper cut length on wood fuel processing performance. Fuel Process Technol 2013;116:228–33. https://doi.org/10.1016/j.fuproc.2013.07.002. [12] Spinelli R, Cavallo E, Facello A. A new comminution device for high-quality chip production. Fuel Process Technol 2012;99:69–74. https://doi.org/10.1016/j. fuproc.2012.01.034. [13] Ferrari E, Spinelli R, Cavallo E, Magagnotti N. Attitudes towards mechanized cut-tolength technology among logging contractors in Northern Italy. Scand J For Res 2012;27:800–6. https://doi.org/10.1080/02827581.2012.693192. [14] Micheletti Cremasco M, Giustetto A, Caffaro F, Colantoni A, Cavallo E, Grigolato S. risk assessment for musculoskeletal disorders in forestry: a comparison between RULA and REBA in the manual feeding of a wood-chipper. Int J Environ Res Public Health 2019:16. https://doi.org/10.3390/ijerph16050793. [15] Manzone M, Balsari P. The energy consumption and economic costs of different vehicles used in transporting woodchips. Fuel 2015;139:511–5. https://doi.org/10. 1016/j.fuel.2014.09.003. [16] Manzone M, Calvo A. Woodchip transportation: Climatic and congestion influence on productivity, energy and CO2 emission of agricultural and industrial convoys. Renew Energy 2017;108:250–9. https://doi.org/10.1016/j.renene.2017.02.074. [17] Han SK, Murphy GE. Solving a woody biomass truck scheduling problem for a transport company in Western Oregon, USA. Biomass Bioenergy 2012;44:47–55. https://doi.org/10.1016/j.biombioe.2012.04.015. [18] Wolfsmayr UJ, Rauch P. The primary forest fuel supply chain: a literature review. Biomass Bioenergy 2014;60:203–21. https://doi.org/10.1016/j.biombioe.2013.10. 025. [19] Atashbar NZ, Labadie N, Prins C. Modelling and optimisation of biomass supply chains: a review. Int J Prod Res 2018;7543:1–25. https://doi.org/10.1080/ 00207543.2017.1343506. [20] Malladi KT, Sowlati T. Biomass logistics: a review of important features, optimization modeling and the new trends. Renew Sustain Energy Rev 2018;94:587–99. https://doi.org/10.1016/j.rser.2018.06.052. [21] Acuna M, Mirowski L, Ghaffariyan MR, Brown M. Optimising transport efficiency and costs in Australian wood chipping operations. Biomass Bioenergy 2012;46:291–300. https://doi.org/10.1016/j.biombioe.2012.08.014. [22] Mihelič M, Spinelli R, Poj A, Ranta T, Pari L, Brambilla M, et al. An assessment model for collecting and transporting cellulosic biomass. Biomass Bioenergy
8
Fuel 262 (2020) 116618
N. Pampuro, et al. 930823. [52] Li Y, Liu H. High-pressure densification of wood residues to form an upgraded fuel. Biomass Bioenergy 2000;19:177–86. https://doi.org/10.1016/S0961-9534(00) 00026-X. [53] Obernberger I, Thek G. Physical characterisation and chemical composition of densified biomass fuels with regard to their combustion behaviour. Biomass
Bioenergy 2004;27:653–69. https://doi.org/10.1016/j.biombioe.2003.07.006. [54] Tumuluru JS, Wright CT, Hess JR, Kenney KL. A review of biomass densification systems to develop uniform feedstock commodities for bioenergy application. Biofuels, Bioprod Biorefining 2011;5:683–707. https://doi.org/10.1002/bbb.324. [55] Mani S, Tabil LG, Sokhansanj S. Evaluation of compaction equations applied to four biomass species. Can Biosyst Eng/Le Genie Des Biosyst Au Canada 2004;46:55–61.
9