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Comparative analyses of forest fuels in a life cycle perspective with a focus on transport systems
Resources, Conservation and Recycling 52 (2008) 1190–1197
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Comparative analyses of forest fuels in a life cycle perspective with a focus on transport systems Lisa Näslund Eriksson ∗ Ecotechnology, Department of Engineering, Physics and Mathematics, Mid Sweden University, SE-831 25 Östersund, Sweden
a r t i c l e
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Article history: Received 18 April 2007 Received in revised form 31 March 2008 Accepted 18 June 2008 Available online 9 August 2008 Keywords: Chips Bundles Pellets Transportation Primary energy CO2 emissions Costs Dry-matter losses Life cycle perspective
a b s t r a c t Local, national and international transportation of forest fuels with regard to costs, primary energy use and CO2 emission was analysed. The main issue was the extent to which both mode and distance of transport affect the monetary cost, CO2 emission and primary energy use arising from the use of various types of forest residues for energy purpose. Local applications proved the most efficient options of those studied. Chipping of bundles at a terminal, for transport by rail and sea to national or international end-users, has low costs and produces only modest CO2 emissions. For the pellet options, the cost is about the same as for chipping, but require more primary energy and emit more CO2 . The traditional chipping system is more expensive than the other options. The costs of the international options over a transport distance of 1100 km vary between 21 and 28 D 2007 /MWh, whereas pellet options cost between 22 and 25 D 2007 /MWh. The primary energy required for transport of logging residues vis-à-vis pellets falls in the range 4–7% and 2–4%, respectively, of the bio-energy delivered. The primary energy needed to produce pellets gives them a lower fossil fuel substitution rate per hectare, compared with bundle systems. Similarly, for chip systems vis-à-vis bundle systems, the biomass delivered to the conversion plant is reduced by the greater physical dry-matter losses entailed by chipping systems in the forest-fuel chain. © 2008 Elsevier B.V. All rights reserved.
1. Introduction In the European Union, priority is given to the development and increased use of renewable energy sources, with a view to safeguarding supplies and to obtain environmental benefits. Bioenergy is already an important renewable energy source in some EU countries. In Sweden, of the total national energy supply, bio-fuel accounted for 18% or 111 TWh/year in 2006 (SCB, 2008b). Wood fuel is also being imported into Sweden (5–9 TWh/year in 2001 (SVEBIO, 2004)). The potential supply of wood fuel from Swedish forests has been estimated by some authors to 125 TWh/year (Lönner et al., 1998), and to 170 TWh/year with optimized spreading of forest fertilizers (Borjesson et al., 1997). The Swedish Commission on Oil Independence has estimated the potential energy supply from bio-fuel in Sweden to be 154 TWh in 2020 (Commission on Oil Independence, 2006). There is thus possibility for Sweden to produce more bio-energy. Current bio-energy systems in Sweden include satisfactorily functioning production of forest fuel, for example the use of sawmill residues and logging residues for district heating and/or electric-
∗ Tel.: +46 63 165535; fax: +46 63 165500. E-mail address: [email protected]. 0921-3449/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.resconrec.2008.06.009
ity generation. The possibility of exporting logging residues has also been investigated. Large-scale, long-distance transportation of bio-fuels is feasible in both economic and energy terms, as well as being attractive in terms of reducing greenhouse gas emissions (Hamelinck et al., 2004b). Long-distance international transport is necessary in order to supply biomass to energy importing regions in western Europe. Earlier studies have produced costings for different forest-fuel systems, especially on a local scale (Andersson et al., 2000; Glöde, 2000; Liss, 2003; Poikola, 2003). In Hamelinck et al. (2004a), the costs of differently refined Scandinavian forest fuels transported to The Netherlands were calculated (Table 1). There are also earlier studies on CO2 emissions from forest-fuel systems on different scales. In Wihersaari (2005), emissions in connection with collecting, chipping and transporting the residues on a local scale were estimated to about 4–7 kg CO2 eq1 per MWhchip (MWhchip = MWh of bio-fuel chips supplied to the conversion plant). Emissions for an alternative with logging residues transported as bales from Sweden to The Netherlands were calculated by Forsberg (1999) to be around 3.5 kg C/MWhchip . Analyses indicated that bio-fuels for energy could be transported from Scandinavia to the Netherlands
1
Carbon dioxide equivalent integrated over 100 years.
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Table 1 Recovery, processing and transportation costs (D 2007 /MWhchip ) for Scandinavian forest fuel transported to The Netherlands (Hamelinck et al., 2004a) Form
Transport mode
Cost
Pellets Pellets Chips Chips Bundles Bundles
Sea Rail Sea Rail Sea Rail
16 17 25 28 18 20
with moderate CO2 emissions (Forsberg, 2000). Forsberg (2000) suggested that long-distance transport (e.g. 1200 km) by sea adds little to total air borne emissions. Transportation chains differ as regards costs, energy use, material loss and applied logistics. In order to get comparable results for systems considering both costs and emissions between different forest-fuel systems on different scales, recovery systems and transportation chains need to be based on the same assumptions. In this study, local, national and international transportation of forest residues with regard to costs, primary energy and CO2 emissions was analysed and compared. As a case study example, logging residues from Jämtland, Sweden, were analysed. The fundamental question was the extent to which transport mode and transport distance affect the costs, primary energy use and CO2 emissions of converting forest residues into bundles, chips and pellets. The two systems analysed for recovering, storing and treating logging residues are chip and bundle. 2. Approach A system analysis was conducted for different transport systems for bundles, chips and pellets on local, national and international bases, including the means of recovery. A geographical outline of the systems studied is shown in Fig. 1. System boundaries for all options are described in Fig. 2. The systems start with logging residues spread out on the clear-cutting site and end when the biofuel is ready for combustion, as chips or pellets, at the conversion plant of the end-user. In the bundle systems, chipping takes place on a large scale at the end-user – if it has not already been done at a
Fig. 1. Geographical outline of the systems studied. Initial haul 80 km, hauling from Jämtland to coast (250 km), from coast to Stockholm region (400 km), from coast to The Netherlands (1100 km), from Jämtland to Stockholm region (600 km) and from Jämtland to The Netherlands (1100 km).
Fig. 2. Flow chart and system boundaries of studied systems. Transportation from terminal and pellets plant could be performed by road, rail and/or sea. The flow chart is valid for local, national and international destinations.
Table 2 Possible transportation chains and distances for local, national and international alternatives Scenario
Transportation chaina To terminal (by truck 80 km)b
To end-user Form
Mode
Loc a Loc b Loc c Loc d Loc e
Bundles Bundles Chips
Bundles Bundles Chips Chips Chips
Truck, 80 km Truck, 30 km Truck, 30 km Truck, 30 km Truck, 80 km
Nat a Nat b Nat c Nat d Nat e Nat f Nat g Nat h Nat i Nat j Nat k Nat l
Bundles Bundles Bundles Bundles Chips Chips Bundles Bundles Bundles Bundles Chips Chips
Bundles Bundles Chips Chips Chips Chips Bundles Bundles Chips Chips Chips Chips
Truck, 600 km Train, 600 km Truck, 600 km Train, 600 km Truck, 600 km Train, 600 km Train + ship, 250 + 400 km Truck + ship, 250 + 400 km Train + ship, 250 + 400 km Truck + ship, 250 + 400 km Train + ship, 250 + 400 km Truck + ship, 250 + 400 km
Int a Int b Int c Int d Int e Int f Int g Int h Int i
Bundles Bundles Bundles Bundles Bundles Bundles Chips Chips Chips
Bundles Bundles Bundles Chips Chips Chips Chips Chips Chips
Truck + ship, 250 + 1100 km Train + ship, 250 + 1100 km Train, 1100 km Truck + ship, 250 + 1100 km Train + ship, 250 + 1100 km Train, 1100 km Truck + ship, 250 + 1100 km Train + ship, 250 + 1100 km Train, 1100 km
a b
All transport distances also described in Fig. 1. A blank space means that truck transport is direct from field to end-user.
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Table 3 Transportation chains and distances for national and international pellet options and harbour scenarios Scenario
Transportation chaina To terminal (by truck 80 km)b
Pnat a Pnat b Pnat cc Pint a Pint b Pint c Pint d Pint ec Pint fc Pint gc Hint ad Hint bd Hint cd Hint dd a b c d
Bundles
Bundles
To pellet plant Mode
Form
Mode
Bundles Chips Bundles
Truck, 80 km Truck, 80 km Train, 250 km
Pellets Pellets Pellets
Train, 600 km Train, 600 km Train, 400 km
Bundles Bundles Chips Chips Bundles Bundles Bundles
Truck, 80 km Truck, 80 km Truck, 80 km Truck, 80 km Truck, 250 km Truck, 250 km Truck, 250 km
Pellets Pellets Pellets Pellets Pellets Pellets Pellets
Train, 1100 km Train + ship, 250 + 1100 km Train, 1100 km Train + ship, 250 + 1100 km Ship, 1100 km Train, 1100 km Ship, 1100 km
Truck, 80 km
Bundles Chips Chips Pellets
Ship, 1100 km Ship, 1100 km Ship, 1100 km Ship, 1100 km
Bundles Bundles Chips Bundles
All transport distances also described in Fig. 1. A blank space means that truck transport was direct from field to end-user or pellets plant. Pellets plant located at the coast (250 km from clearcut site). Harbour scenarios. Initial hauling distance to terminal/pellets plant at the harbour was 80 km.
terminal. In the chip systems, chipping takes place at the roadside, near the clear-cut site. The pellets options are based on the bundle and chip alternatives. Bundle and chip systems that prove efficient in terms of cost and CO2 emissions will guide the selection of pellet options. Possible transportation chains for local, national and international options are shown in Tables 2 and 3. They consist of different transportation chains with combinations of transport forms and modes. In the importing country, the combustion utility is assumed to be located at the coast and have its own harbour facilities. Also, when rail transport is used, the train is assumed to discharge its load at the plant in question. In addition to the options with logging residues originating from Jämtland, a selection of international alternatives with a terminal or pellets production plant located by the coast close to the clear-cutting site was used for comparison in the analysis. Data from literature studies were used for the calculations and comparisons of costs, primary energy use and CO2 emissions. These emissions are based on primary energy use and reflect the amount of energy used and the particular fossil fuel used. Ash re-circulation was not included. Assumptions for calculations of primary energy use for trucks were based on Natural Resources Canada (2007), for forestry operations on Byhlin, 2005 (pers. comm.) and Andersson and Nordén (2000), and for ship and train on Carlsson-Kanyama and Faist (2000). In order to minimize biases in the comparisons, data for bundle and chip systems originating from the same study has been preferred and sources based on comparable assumptions have been chosen for the transport systems. Construction of infrastructure and production and maintenance of machinery were outside the system boundary, though road maintenance and operational costs were included (Liss, 2003), referred to here as “additional costs”. If logging residues were treated at a terminal after the initial haul, an extra cost of 0.67 D 2007 was added (Liss, 2003). In the calculations, energy content is: for bundles, 2.1 MWh/tonne (Liss, 2003); for chips 2.3 MWh/tonne (Liss, 2003); and for pellets, 5.0 MWh/tonne (Martinsson and Österberg, 2004). Bundle weight is assumed to be 550 kg, the moisture content 50% and one bundle corresponds to 1.15 MWh2 (Liss, 2003). The bundle
2
To end-user
Form
Lower heating value is used in all calculations.
is assumed to be 0.75 m in diameter and 3 m long (Hamelinck et al., 2004b), giving a volume of 1.3 m3 . During transportation of bundles, 20% of the load space between the bundles is considered to be empty space (Liss, 2003). Chips are also assumed to have a 50% moisture content, but for pellets the moisture content is assumed to be 11% (Martinsson and Österberg, 2004). As a functional unit, 1 MWh of delivered bio-fuels was used. Original costs used in the comparisons were adjusted for inflation to the year 2007, using the Swedish consumer price index (SCB, 2008a). The exchange rate of one D 2008 = 9.4 SEK is used. A coal-fired condensing plant using steam-turbines was assumed for the calculations of emissions from electricity generation. Fuel-cycle emissions were used for coal, diesel and light fuel oil (Gustavsson et al., 1995). The term G15 -hour is used in the assumptions for forestry operations and chipping. This is a forestry concept of a maximum of 15 min of break per work hour, implying 45 min of effective work time. A G0 -hour represents 60 min of effective work. One m3 s of forest fuel means 1 m3 of tipped material. 2.1. Road transport Data on costs for transportation by truck up to 200 km are available in Liss (2003). Estimates for longer hauls are made by extrapolation. The assumption is that for road transport there is a linear relationship between costs and distance (Ahlstedt and Nelldal, 2002; SIKA, 2006). To transport bundles, a round-wood truck with a total weight of 58 tonnes is assumed. On this truck, 70 bundles weighting 38.5 tonnes can be loaded (Johansson, 2000; Liss, 2003). For primary energy use for and emissions from loading and unloading, engines are assumed to idle on 10% energy consumption and emissions, compared with normal running (Forsberg, 1999). Data on load speed are from Liss (2003), where 71 bundles (mean) were loaded in 23 min and unloaded in 18 min. Thus our transport calculations are based on 70 bundles per load, but the loading times are based on 71 bundles average recalculated to 70 bundles. For cost calculations of all transportation of chips a special vehicle carrying 37.3 tonnes at 50% moisture content is assumed (99 m3 s) (Johansson, 2000; Liss, 2003). Loading speed of chips in a special vehicle is from Liss (2006), where 99 m3 takes 52 and 18 min
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Table 4 Details for different transportation modes and forms
Table 5 Productivity of different operations
Activity
Activity
Unit
Data
Bundling Forwarding, bundles Forwarding, loose Chipping roadside, loose Chipping terminal/end-user, bundles
No/G15 -hour No/G15 -hour m3 /load m3 /hour No/G15 -hour
20 25 30 40 80
Form Unit
Bundles 38.5 80.5
Chips 37.3 85.8
Pellets
Truck
Tonnes/load MWh/load
37.3 189
Train
Tonnes/load MWh/load
865 1810
942 2170
1000 5060
Ship
Tonnes/load MWh/load
2320 4850
2530 5810
4000 20240
for loading and unloading, respectively. For pellets transported by road, costs per MWh are calculated from transportation of chips, using the same figures for tonnes per load. For comparisons, see Table 4. Data on primary energy use for a heavy truck are from Canadian Vehicle Summary (Natural Resources Canada, 2007). For empty truck journeys, all energy use and emissions are reduced to 40%. These figures are used both for round-wood trucks and for special vehicles, both with a maximum load of 40 tonnes. Empty return journeys are assumed. 2.2. Rail transport Costs valid for rail transportation are taken or calculated from Hamelinck et al. (2004b), where cargo capacity was set at 1000 tonnes and 2500 m3 . Train costs often depend on train logistics, which can differ widely for the same transport route or distance, depending on the time and day when transportation is to take place. For the train calculations, generic km-costs and electricity use are assumed for all regions concerned; only differences in electricity costs yield regional differences (Hamelinck et al., 2004b). Data on electricity use for rail transport are taken from Forsberg (1999). For a train of 52 wagons and 40% degree of use (empty return transport), the energy supply, expressed as electricity, is 0.27 MJ/tonnekm, originating from NTM, 2000 (Carlsson-Kanyama and Faist, 2000). For emissions and primary energy use associated with loading and unloading, a mobile crane is used, which is assumed to have the same energy requirement as for a truck, above. 2.3. Sea transport Costs valid for a ship transportation of 1100 km are taken from Hamelinck et al. (2004b), where cargo capacities are set to 4000 tonnes and 6700 m3 , and the ship size and weight are comparable to the ship used by Forsberg (1999). Loading/unloading time is set to 60 m3 /h (Hamelinck et al., 2004b) for bundles, chips and pellets. Primary energy use applying to sea transport are originating from NTM, 2000 (Carlsson-Kanyama and Faist, 2000). A conventional vessel (> 8000 dwt) with ship size and weight assumed comparable to the ship used by Hamelinck et al. (2004b), with an energy consumption of 0.2 MJ ship fuel/tonnekm is assumed. 2.4. Forestry operations Material is assumed to be gathered over a 5 ha recovery area and is forwarded an average distance of 300 m to a roadside collection site (see e.g. Liss, 2003). Recovery of logging residues per ha is assumed to equate to 100 bundles per ha, or 115 MWh/ha. That equate to around 200 m3 stem volume per hectare. Data for the cost calculations of recovery operations, forwarding and local haulage are based on conditions in the Dalarna region. These conditions are
assumed to be the same as those in Jämtland region. Both areas are situated in the northern coniferous region and productivity could vary between different areas within the region. Costs for forestry operations are from Liss (2003). Calculations of emissions are based on assumptions in Liss (2003). For forwarding of bundles and loose material, a Timberjack 1410D is used. To compress bundles, a Timberjack 1410D equipped with a Fiberpac 370 is used. Productivity and fuel consumption are shown in Tables 5 and 6, respectively. 2.5. Chipping Costs for chipping are taken from Liss (2003). For calculation of emissions, a Bruks 803 ct attached to a Timberjack 1410D is assumed for the roadside chipping and a Bruks 1004 ct attached to a dumper is assumed for chipping at the conversion plant. The cost of chipping at a terminal was earlier estimated to be one-third of the cost of chipping roadside (Andersson et al., 2000). Productivities and fuel consumptions are shown in Tables 5 and 6, respectively. 2.6. Pellets production Costs of pellet production are according to Zakrisson (2002), in the Swedish case, but with the cost of raw materials from the present study, which gives 6.0 D 2007 /MWh. A similar assumption with a pellets production cost in Thek and Obernberger (2004) gives 6.2 D 2007 /MWh. Energy use for pellets production are according to Forsberg (1999, 2000), which includes chipping. Both for costs and for emissions, chipping has been subtracted from the sum and chipping emissions and costs corresponding to chipping conditions described above have been added. Also, the share of wood fuel, Table 6 Primary energy use in the studied systems Activity
Energy form
Primary energy use
Compressing (Andersson and Nordén, 2000) Forwarding (Byhlin, 2005, pers. comm.) Chipping at roadsidea Transport Truck (Natural Resources Canada, 2007) Train (Carlsson-Kanyama and Faist, 2000) Ship (Carlsson-Kanyama and Faist, 2000) Loading/unloading (Natural Resources Canada, 2007) Chipping at terminal (Andersson and Nordén, 2000) Chipping at end-user (Andersson and Nordén, 2000) Pelleting (Forsberg, 1999)
Diesel
12 l/h
Diesel
9.5 l/h
Diesel
9.5 l/h
Diesel
0.41 l/vehicle kmb
Electricity
0.075 kWh/tonnekmb
Ship fuel
0.056 kWh/tonnekm
Diesel
0.024 l/h
Diesel
50 l/G15 -hour
Diesel
50 l/G15 -hour
Electricity Diesel Wood
29 kWh/MWh 72 kWh/MWh 178 kWh/MWh
a b
Assumed. 0.41 l/km, 40 tonnes per load, 0.010 l/tonnekm, 0.10 kWh/tonnekm.
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Table 7 Physical dry-matter losses Activity
Loss (%)
Bundling Forwarding, bundles Forwarding, loose Storing, bundles Storing, loose Chipping bundles Chipping loose
2 0 2 2 15 5 10
Fig. 4. Costs and CO2 emissions for national options.
Fig. 3. Costs and CO2 emissions for local options.
used in Forsberg (1999) in the drying process, means that 18% of the energy in the incoming material is consumed, and is therefore considered a loss.
in cost, primary energy use and CO2 emissions as this distance increases or decreases. For comparison with the analysed international transportation chains starting with logging residues, from Jämtland, some harbour options are shown in Table 3 where the terminal is located by the coast, but still involves an initial haul of 80 km. These examples are adapted versions of the Loc a and Loc e options, but with international sea transport added. A pellets alternative, also shown, is an adapted version of the Pint g option. At the international end-user, a theoretical extra transport of 30 km from a harbour to the destination has been added in order to show the hypothetical effect of having to transport the bio-fuel by truck an extra distance from, for example, a harbour. 3. Results
2.7. Dry-matter losses Dry-matter losses occur mostly in the early stages of the forestfuel chain, from the forwarding of forest residues to, and including, storage at roadside (Forsberg, 2000). During storage, substantial dry-matter losses can occur due to biological activity, especially in the chipping system, due to the small particle size. Dry-matter losses in forestry operations are estimated from Forsberg (2000) and losses due to chipping are from Wihersaari (2005). Physical dry-matter losses used are shown in Table 7. 2.8. Sensitivity analyses A crucial cost in the transportation chain is the initial haulage from the forest. A sensitivity analysis considering initial haulage distance for bundles has been made in order to show the change
Costs and CO2 emissions per MWh supplied for local, national, international and pellets options are plotted in Figs. 3–6. At the local level (Fig. 3), the bundle system, i.e. bundles taken directly to the end-user (Loc a), is the most cost-effective option, but the corresponding chip system (Loc e) has the least CO2 emissions. On the national level (Fig. 4), chipping of bundles at a terminal and then transport by rail and sea to the end-user (Nat i) is a cost-effective system option, producing a moderate level of CO2 emissions. If these chips are transported by rail only (Nat d), the cost is only slightly higher, but the CO2 emissions are much greater. To chip biomass at the clearcut site and then transport the chips by rail and sea from the terminal to the end-user (Nat k) produces low CO2 emissions, but at a rather high monetary cost. On the international level (Fig. 5), the system with the lowest monetary cost and low emissions is bundles chipped at a terminal
Fig. 5. Costs and CO2 emissions for international options.
L.N. Eriksson / Resources, Conservation and Recycling 52 (2008) 1190–1197
Fig. 6. Costs and CO2 emissions for national (Pnat a–c, 600 km transport) and international (Pint a–g, 1100 km transport) pellets options. The bundle and chip systems that have proved efficient have steered the selection of pellets alternatives in order to reduce the number of possible pellets alternatives.
and then transported by rail and sea to the end-user (Int e). The transportation of chips from forest to terminal and then by rail and sea to the end-user (Int h) gives low CO2 emissions, but at a slightly higher cost. To transport bundles to a terminal and then by rail and sea to the end-user (Int b) also has a quite low cost and a moderate level of CO2 emissions. Among the national pellets options (Fig. 6), local transportation of bundles to a pellets plant and then transportation of pellets by rail to the end-user (Pnat a) is the most cost-effective option, but the corresponding chip system (Pnat b) gives less CO2 emissions. Internationally, hauling bundles to a local pellets plant, followed by transport of pellets by rail and sea to the end-user (Pint b) is the most cost-effective option. To transport chips to the local pellets plant and then by rail and sea (Pint d) produces much less CO2 , but at significantly higher cost. Transport of bundles 250 km to the coast by truck and then as pellets to end-user by ship (Pint g) produces low CO2 emissions, but at moderate cost. The primary energy use for the options studied ranges between 5–8% and 6–9% of the delivered bio-energy for logging residues and pellets options, respectively. Figs. 7–8 detail the costs, primary energy use and CO2 emissions per MWh supplied, for low cost and/or low CO2 emission options for all distances studied. Local options are the most efficient. The costs of national pellets, bundles or chips options are close, but pellets requires much more primary energy and produce more CO2 . International options too are similar in cost, but the pellets options require more primary energy. In Fig. 9, a cost breakdown diagram for the low cost and/or low CO2 emission options is shown. The cost of pellets production reduces the cost of hauling to the end-user, which could make international transportation of biomass as cost-effective as the national use of biomass.
Fig. 7. Costs for least expensive and/or low CO2 emission options from Figs. 3–6.
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Fig. 8. Primary energy use (PE) and CO2 emissions for least expensive and/or low CO2 emission options from Figs. 3–6.
Long transportation distances that increase the time for biomass storage can lead to greater dry-matter losses due to biological activity in the transported biomass. What fraction of the fuel value is lost due to long-distance transportation is difficult to calculate due to shifting environmental conditions for the forest fuel along the transportation chain. However, the biological activity increases as the particle size in the stored material decreases. Storage of bundles leads to modest dry-matter losses, which are significantly less than those losses incurred by chip storage (Jirjis and Nordén, 2002). This means that in some cases, bundles could be preferable to chips in some of the examples highlighted in Figs. 7–9, especially as regards international alternatives (Int b vis-à-vis Int e and Int h). However, the assumption is that the duration of transportation is kept short, which means low losses. The sensitivity analysis of the initial hauling distance for bundles, considering cost, primary energy use and CO2 emissions as this distance increases or decreases, is shown in Fig. 10. If the ini-
Fig. 9. Cost breakdown for least expensive and/or low CO2 emission options.
Fig. 10. Sensitivity analysis considering transportation distance of initial haulage of bundles, as an example of the impact of distance choice on the final results. The diagram shows the interval of 50–200% of the distance chosen in the scenarios.
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lands is in the same range as the CO2 emissions from our international options. For a pellets alternative the corresponding figure is around 3.3 kg C/MWhchip , which is lower than in our study. In our adapted international harbour options, where the terminal or pellets production plant was moved to the coast, CO2 emissions decreased and reached the level in Forsberg’s results. In the pellets options, more primary energy is used, which reduces the desired substitution of fossil fuels per hectare. Also, the reduced CO2 emission from fossil fuel will be less (per hectare) than with the bundle and chip systems. Nevertheless, the replacement of fossil fuel per hectare is still high. Fig. 11. Costs and CO2 emissions for the international harbour scenarios. At enduser, a 30 km extra hauling distance has been added, where bundles (hint a), chips (hint b and c) and pellets (hint d) are transported.
tial haulage is halved – or doubled – the cost will decrease by 0.77 D 2007 /MWh (28%) or increase by 1.5 D 2007 /MWh (57%), respectively. Harbour alternatives are shown in Fig. 11. Their cost lie between 18 and 20 D 2007 /MWh, excluding the cost of an extra hauling distance. 4. Discussion Our results show that large-scale, long-distance transportation of bio-fuels from central Sweden has the potential to be feasible in both economic and energy respects, as well as attractive in terms of greenhouse gas emissions. However, primary energy use and CO2 emissions for local and national alternatives are lower, as also is the cost for the local alternatives. The costs for international options with traditional chip and bundle systems varied between 23–28 and 21–26 D 2007 /MWh, respectively, and for pellets options between 22 and 25 D 2007 /MWh. These figures approximate the results in Hamelinck et al. (2004a), thus supporting the impression of the costs associated with international transportation chains from Scandinavia to The Netherlands. When the terminal in the present study was moved to the coast, the cost for the bundle options became the same as in Hamelinck et al. (2004a) and the cost for chip options became even lower. In Hamelinck et al. (2004a) the biomass cost for bundles was about half the cost of chips, which could explain the considerable difference between the two systems in their calculation. Procurement costs differ for different species and productivity in different parts of the world. Comparisons of biomass costs could be made with for example solid biomass imported from Latin America delivered to a Dutch power station at about 8.3 D 2007 /MWh (energy crop logs, 20% moisture content) or methanol from Latin America delivered to Europe at 33–41 D 2007 /MWh (Hamelinck et al., 2004b). The results also show CO2 emissions of 1.0–4.9 kg C/MWh from transport systems for various alternatives for local and national transport of bio-fuel. In Wihersaari (2005), assumptions for harvesting and chipping methods and transportation distance were close to the local options in our study. Her evaluations of emissions from collecting, chipping and transporting the residues, viz. about 4–7 kg CO2 eq per MWhchip (around 1.0–1.7 kg C/MWhchip ), are close to the CO2 emissions of 1.5–3.0 kg C/MWh from our local options, thus supporting the impression of the amount of CO2 emissions associated with local transportation chains for logging residues. In Forsberg (Forsberg, 2000) the CO2 emission around 3.5 kg C/MWhchip , for an option with logging residue bales transported from Sweden to The Nether-
Acknowledgements We gratefully acknowledge financial support from the European Union, from Jämtland County Administrative Board and from Sveaskog AB.
References Ahlstedt L, Nelldal B-L. Industrispår - förutsättningar för utveckling. Stockholm: KTH Railway Group; 2002. p. 23. Andersson G, Nordén B, Fiberpac 370. Systemstudie komprimering avverkningsrester. Skogforsk, Uppsala, Sweden; 2000, p. 39. Andersson G, Nordén B, Jirjis R, Åstrand C. Buntning kan sänka kostnaderna för skogsbränsle. Skogforsk Resultat 2000;8:1–4. Borjesson P, Gustavsson L, Christersson L, Linder S. Future production and utilisation of biomass in Sweden: potentials and CO2 mitigation. Biomass Bioenergy 1997;13:399–412. Carlsson-Kanyama A, Faist M. Energy use in the food sector: a data survey. Environ Strategies Res - fms 2000:36. Commission on Oil Independence. Making Sweden an oil-free society. Stockholm, Sweden: Swedish Government Offices; 2006. p. 51. Forsberg G. Assessment of bioenergy systems. Uppsala, Sweden: Department of Forest Management and Products, Swedish University of Agricultural Sciences; 1999. Forsberg G. Biomass energy transport—analysis of bioenergy transport chains using life cycle inventory method. Biomass Bioenergy 2000;19: 17–30. Glöde D. Grot- och gagnvirkesskördaren—morgondagens skogsbränslesystem? Skogforsk Resultat 2000;9:1–4. Gustavsson L, Börjesson P, Johansson B, Svenningsson P. Reducing CO2 emissions by substituting biomass for fossil fuels. Energy 1995;20:1097–113. Hamelinck CN, Suurs R, Faaij A. Large scale and long distance biomass supply chains: logistics, costs, energy consumption, emission balances. In: Contributions of the Department of Science, Technology & Society, Copernicus Institute—Utrecht University, to the 2nd World Conference and Technology Exhibition on Biomass for Energy, Industry and Climate Protection; 2004a. Hamelinck CN, Suurs RAA, Faaij APC. International bioenergy transport costs and energy balance, in outlook for advanced biofuels. The Netherlands: Utrecht; 2004b. p. 55–82. Jirjis R, Nordén B. Lagring av buntat skogsbränsle - små substansförluster, inget arbetsmiljöproblem. Skogforsk Resultat 2002;12:1–2. Johansson J. Vidaretransport av skogsbränsle från ungskog med lastbil - kostnadsberäkningar. Garpenberg, Sweden: Dalarna University, Department of Industrial Forestry, Forest and Wood; 2000. Liss J-E. Kostnadsjämförelse mellan buntsystem och traditionella flissystem vid uttag av skogsbränsle. Garpenberg, Sweden: Dalarna University, Department of Mathematics, Natural Sciences and Engineering; 2003. p. 22. Liss J-E. Nytt fordon för transport av bränsleflis. Garpenberg, Sweden: Dalarna University, Department of Mathematics, Natural Sciences and Engineering; 2006. p. 13. Lönner G, Danielsson B-O, Vikinge B, Parikka M, Hektor B, Nilsson PO. Kostnader och tillgänglighet för trädbränslen på medellång sikt. Uppsala, Sweden: Department of Forest-Industry-Market Studies; 1998. p. 126. Martinsson L, Österberg S. Pelletering med skogsbränsle och salix som råvara. Stockholm, Sweden: Värmeforsk (Thermal Engineering Research Institute); 2004. p. 16. Natural Resources Canada. Canadian Vehicle Survey 2005 Summary Report. Natural Resources Canada’s Office of Energy Efficiency; 2007, p. 60. Poikola J. Practical experiences of large-scale production of forest chips. In: Proceedings from Bioenergy 2003. International Nordic Bioenergy Conference from 2nd to 5th of September 2003; 2003. p. 233–5. SCB. Consumer price index, 2008. Statistics Sweden; 2008a. SCB. Gross supply of energy annually, PJ. 2008. Statistics Sweden; 2008b.
L.N. Eriksson / Resources, Conservation and Recycling 52 (2008) 1190–1197 SIKA. Transportkostnader för företag i norra Sverige. Swedish Institute for Transport and Communications Analysis Stockholm; 2006. p. 48. SVEBIO Trädbränslen - en viktig del av energisystemet. Fokus Bioenergi, 2; 2004. Thek G, Obernberger I. Wood pellet production costs under Austrian and in comparison to Swedish framework conditions. Biomass Bioenergy 2004;27:671–93.
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Wihersaari M. Greenhouse gas emissions from final harvest fuel chip production in Finland. Biomass Bioenergy 2005;28:435–43. Zakrisson M. Internationell jämförelse av produktionskostnader vid pelletstillverkning. Uppsala, Sweden: Swedish University of Agricultural Sciences, Department of Forest Management and Production; 2002. p. 66.
Contents lists available at ScienceDirect
Resources, Conservation and Recycling journal homepage: www.elsevier.com/locate/resconrec
Comparative analyses of forest fuels in a life cycle perspective with a focus on transport systems Lisa Näslund Eriksson ∗ Ecotechnology, Department of Engineering, Physics and Mathematics, Mid Sweden University, SE-831 25 Östersund, Sweden
a r t i c l e
i n f o
Article history: Received 18 April 2007 Received in revised form 31 March 2008 Accepted 18 June 2008 Available online 9 August 2008 Keywords: Chips Bundles Pellets Transportation Primary energy CO2 emissions Costs Dry-matter losses Life cycle perspective
a b s t r a c t Local, national and international transportation of forest fuels with regard to costs, primary energy use and CO2 emission was analysed. The main issue was the extent to which both mode and distance of transport affect the monetary cost, CO2 emission and primary energy use arising from the use of various types of forest residues for energy purpose. Local applications proved the most efficient options of those studied. Chipping of bundles at a terminal, for transport by rail and sea to national or international end-users, has low costs and produces only modest CO2 emissions. For the pellet options, the cost is about the same as for chipping, but require more primary energy and emit more CO2 . The traditional chipping system is more expensive than the other options. The costs of the international options over a transport distance of 1100 km vary between 21 and 28 D 2007 /MWh, whereas pellet options cost between 22 and 25 D 2007 /MWh. The primary energy required for transport of logging residues vis-à-vis pellets falls in the range 4–7% and 2–4%, respectively, of the bio-energy delivered. The primary energy needed to produce pellets gives them a lower fossil fuel substitution rate per hectare, compared with bundle systems. Similarly, for chip systems vis-à-vis bundle systems, the biomass delivered to the conversion plant is reduced by the greater physical dry-matter losses entailed by chipping systems in the forest-fuel chain. © 2008 Elsevier B.V. All rights reserved.
1. Introduction In the European Union, priority is given to the development and increased use of renewable energy sources, with a view to safeguarding supplies and to obtain environmental benefits. Bioenergy is already an important renewable energy source in some EU countries. In Sweden, of the total national energy supply, bio-fuel accounted for 18% or 111 TWh/year in 2006 (SCB, 2008b). Wood fuel is also being imported into Sweden (5–9 TWh/year in 2001 (SVEBIO, 2004)). The potential supply of wood fuel from Swedish forests has been estimated by some authors to 125 TWh/year (Lönner et al., 1998), and to 170 TWh/year with optimized spreading of forest fertilizers (Borjesson et al., 1997). The Swedish Commission on Oil Independence has estimated the potential energy supply from bio-fuel in Sweden to be 154 TWh in 2020 (Commission on Oil Independence, 2006). There is thus possibility for Sweden to produce more bio-energy. Current bio-energy systems in Sweden include satisfactorily functioning production of forest fuel, for example the use of sawmill residues and logging residues for district heating and/or electric-
∗ Tel.: +46 63 165535; fax: +46 63 165500. E-mail address: [email protected]. 0921-3449/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.resconrec.2008.06.009
ity generation. The possibility of exporting logging residues has also been investigated. Large-scale, long-distance transportation of bio-fuels is feasible in both economic and energy terms, as well as being attractive in terms of reducing greenhouse gas emissions (Hamelinck et al., 2004b). Long-distance international transport is necessary in order to supply biomass to energy importing regions in western Europe. Earlier studies have produced costings for different forest-fuel systems, especially on a local scale (Andersson et al., 2000; Glöde, 2000; Liss, 2003; Poikola, 2003). In Hamelinck et al. (2004a), the costs of differently refined Scandinavian forest fuels transported to The Netherlands were calculated (Table 1). There are also earlier studies on CO2 emissions from forest-fuel systems on different scales. In Wihersaari (2005), emissions in connection with collecting, chipping and transporting the residues on a local scale were estimated to about 4–7 kg CO2 eq1 per MWhchip (MWhchip = MWh of bio-fuel chips supplied to the conversion plant). Emissions for an alternative with logging residues transported as bales from Sweden to The Netherlands were calculated by Forsberg (1999) to be around 3.5 kg C/MWhchip . Analyses indicated that bio-fuels for energy could be transported from Scandinavia to the Netherlands
1
Carbon dioxide equivalent integrated over 100 years.
L.N. Eriksson / Resources, Conservation and Recycling 52 (2008) 1190–1197
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Table 1 Recovery, processing and transportation costs (D 2007 /MWhchip ) for Scandinavian forest fuel transported to The Netherlands (Hamelinck et al., 2004a) Form
Transport mode
Cost
Pellets Pellets Chips Chips Bundles Bundles
Sea Rail Sea Rail Sea Rail
16 17 25 28 18 20
with moderate CO2 emissions (Forsberg, 2000). Forsberg (2000) suggested that long-distance transport (e.g. 1200 km) by sea adds little to total air borne emissions. Transportation chains differ as regards costs, energy use, material loss and applied logistics. In order to get comparable results for systems considering both costs and emissions between different forest-fuel systems on different scales, recovery systems and transportation chains need to be based on the same assumptions. In this study, local, national and international transportation of forest residues with regard to costs, primary energy and CO2 emissions was analysed and compared. As a case study example, logging residues from Jämtland, Sweden, were analysed. The fundamental question was the extent to which transport mode and transport distance affect the costs, primary energy use and CO2 emissions of converting forest residues into bundles, chips and pellets. The two systems analysed for recovering, storing and treating logging residues are chip and bundle. 2. Approach A system analysis was conducted for different transport systems for bundles, chips and pellets on local, national and international bases, including the means of recovery. A geographical outline of the systems studied is shown in Fig. 1. System boundaries for all options are described in Fig. 2. The systems start with logging residues spread out on the clear-cutting site and end when the biofuel is ready for combustion, as chips or pellets, at the conversion plant of the end-user. In the bundle systems, chipping takes place on a large scale at the end-user – if it has not already been done at a
Fig. 1. Geographical outline of the systems studied. Initial haul 80 km, hauling from Jämtland to coast (250 km), from coast to Stockholm region (400 km), from coast to The Netherlands (1100 km), from Jämtland to Stockholm region (600 km) and from Jämtland to The Netherlands (1100 km).
Fig. 2. Flow chart and system boundaries of studied systems. Transportation from terminal and pellets plant could be performed by road, rail and/or sea. The flow chart is valid for local, national and international destinations.
Table 2 Possible transportation chains and distances for local, national and international alternatives Scenario
Transportation chaina To terminal (by truck 80 km)b
To end-user Form
Mode
Loc a Loc b Loc c Loc d Loc e
Bundles Bundles Chips
Bundles Bundles Chips Chips Chips
Truck, 80 km Truck, 30 km Truck, 30 km Truck, 30 km Truck, 80 km
Nat a Nat b Nat c Nat d Nat e Nat f Nat g Nat h Nat i Nat j Nat k Nat l
Bundles Bundles Bundles Bundles Chips Chips Bundles Bundles Bundles Bundles Chips Chips
Bundles Bundles Chips Chips Chips Chips Bundles Bundles Chips Chips Chips Chips
Truck, 600 km Train, 600 km Truck, 600 km Train, 600 km Truck, 600 km Train, 600 km Train + ship, 250 + 400 km Truck + ship, 250 + 400 km Train + ship, 250 + 400 km Truck + ship, 250 + 400 km Train + ship, 250 + 400 km Truck + ship, 250 + 400 km
Int a Int b Int c Int d Int e Int f Int g Int h Int i
Bundles Bundles Bundles Bundles Bundles Bundles Chips Chips Chips
Bundles Bundles Bundles Chips Chips Chips Chips Chips Chips
Truck + ship, 250 + 1100 km Train + ship, 250 + 1100 km Train, 1100 km Truck + ship, 250 + 1100 km Train + ship, 250 + 1100 km Train, 1100 km Truck + ship, 250 + 1100 km Train + ship, 250 + 1100 km Train, 1100 km
a b
All transport distances also described in Fig. 1. A blank space means that truck transport is direct from field to end-user.
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Table 3 Transportation chains and distances for national and international pellet options and harbour scenarios Scenario
Transportation chaina To terminal (by truck 80 km)b
Pnat a Pnat b Pnat cc Pint a Pint b Pint c Pint d Pint ec Pint fc Pint gc Hint ad Hint bd Hint cd Hint dd a b c d
Bundles
Bundles
To pellet plant Mode
Form
Mode
Bundles Chips Bundles
Truck, 80 km Truck, 80 km Train, 250 km
Pellets Pellets Pellets
Train, 600 km Train, 600 km Train, 400 km
Bundles Bundles Chips Chips Bundles Bundles Bundles
Truck, 80 km Truck, 80 km Truck, 80 km Truck, 80 km Truck, 250 km Truck, 250 km Truck, 250 km
Pellets Pellets Pellets Pellets Pellets Pellets Pellets
Train, 1100 km Train + ship, 250 + 1100 km Train, 1100 km Train + ship, 250 + 1100 km Ship, 1100 km Train, 1100 km Ship, 1100 km
Truck, 80 km
Bundles Chips Chips Pellets
Ship, 1100 km Ship, 1100 km Ship, 1100 km Ship, 1100 km
Bundles Bundles Chips Bundles
All transport distances also described in Fig. 1. A blank space means that truck transport was direct from field to end-user or pellets plant. Pellets plant located at the coast (250 km from clearcut site). Harbour scenarios. Initial hauling distance to terminal/pellets plant at the harbour was 80 km.
terminal. In the chip systems, chipping takes place at the roadside, near the clear-cut site. The pellets options are based on the bundle and chip alternatives. Bundle and chip systems that prove efficient in terms of cost and CO2 emissions will guide the selection of pellet options. Possible transportation chains for local, national and international options are shown in Tables 2 and 3. They consist of different transportation chains with combinations of transport forms and modes. In the importing country, the combustion utility is assumed to be located at the coast and have its own harbour facilities. Also, when rail transport is used, the train is assumed to discharge its load at the plant in question. In addition to the options with logging residues originating from Jämtland, a selection of international alternatives with a terminal or pellets production plant located by the coast close to the clear-cutting site was used for comparison in the analysis. Data from literature studies were used for the calculations and comparisons of costs, primary energy use and CO2 emissions. These emissions are based on primary energy use and reflect the amount of energy used and the particular fossil fuel used. Ash re-circulation was not included. Assumptions for calculations of primary energy use for trucks were based on Natural Resources Canada (2007), for forestry operations on Byhlin, 2005 (pers. comm.) and Andersson and Nordén (2000), and for ship and train on Carlsson-Kanyama and Faist (2000). In order to minimize biases in the comparisons, data for bundle and chip systems originating from the same study has been preferred and sources based on comparable assumptions have been chosen for the transport systems. Construction of infrastructure and production and maintenance of machinery were outside the system boundary, though road maintenance and operational costs were included (Liss, 2003), referred to here as “additional costs”. If logging residues were treated at a terminal after the initial haul, an extra cost of 0.67 D 2007 was added (Liss, 2003). In the calculations, energy content is: for bundles, 2.1 MWh/tonne (Liss, 2003); for chips 2.3 MWh/tonne (Liss, 2003); and for pellets, 5.0 MWh/tonne (Martinsson and Österberg, 2004). Bundle weight is assumed to be 550 kg, the moisture content 50% and one bundle corresponds to 1.15 MWh2 (Liss, 2003). The bundle
2
To end-user
Form
Lower heating value is used in all calculations.
is assumed to be 0.75 m in diameter and 3 m long (Hamelinck et al., 2004b), giving a volume of 1.3 m3 . During transportation of bundles, 20% of the load space between the bundles is considered to be empty space (Liss, 2003). Chips are also assumed to have a 50% moisture content, but for pellets the moisture content is assumed to be 11% (Martinsson and Österberg, 2004). As a functional unit, 1 MWh of delivered bio-fuels was used. Original costs used in the comparisons were adjusted for inflation to the year 2007, using the Swedish consumer price index (SCB, 2008a). The exchange rate of one D 2008 = 9.4 SEK is used. A coal-fired condensing plant using steam-turbines was assumed for the calculations of emissions from electricity generation. Fuel-cycle emissions were used for coal, diesel and light fuel oil (Gustavsson et al., 1995). The term G15 -hour is used in the assumptions for forestry operations and chipping. This is a forestry concept of a maximum of 15 min of break per work hour, implying 45 min of effective work time. A G0 -hour represents 60 min of effective work. One m3 s of forest fuel means 1 m3 of tipped material. 2.1. Road transport Data on costs for transportation by truck up to 200 km are available in Liss (2003). Estimates for longer hauls are made by extrapolation. The assumption is that for road transport there is a linear relationship between costs and distance (Ahlstedt and Nelldal, 2002; SIKA, 2006). To transport bundles, a round-wood truck with a total weight of 58 tonnes is assumed. On this truck, 70 bundles weighting 38.5 tonnes can be loaded (Johansson, 2000; Liss, 2003). For primary energy use for and emissions from loading and unloading, engines are assumed to idle on 10% energy consumption and emissions, compared with normal running (Forsberg, 1999). Data on load speed are from Liss (2003), where 71 bundles (mean) were loaded in 23 min and unloaded in 18 min. Thus our transport calculations are based on 70 bundles per load, but the loading times are based on 71 bundles average recalculated to 70 bundles. For cost calculations of all transportation of chips a special vehicle carrying 37.3 tonnes at 50% moisture content is assumed (99 m3 s) (Johansson, 2000; Liss, 2003). Loading speed of chips in a special vehicle is from Liss (2006), where 99 m3 takes 52 and 18 min
L.N. Eriksson / Resources, Conservation and Recycling 52 (2008) 1190–1197
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Table 4 Details for different transportation modes and forms
Table 5 Productivity of different operations
Activity
Activity
Unit
Data
Bundling Forwarding, bundles Forwarding, loose Chipping roadside, loose Chipping terminal/end-user, bundles
No/G15 -hour No/G15 -hour m3 /load m3 /hour No/G15 -hour
20 25 30 40 80
Form Unit
Bundles 38.5 80.5
Chips 37.3 85.8
Pellets
Truck
Tonnes/load MWh/load
37.3 189
Train
Tonnes/load MWh/load
865 1810
942 2170
1000 5060
Ship
Tonnes/load MWh/load
2320 4850
2530 5810
4000 20240
for loading and unloading, respectively. For pellets transported by road, costs per MWh are calculated from transportation of chips, using the same figures for tonnes per load. For comparisons, see Table 4. Data on primary energy use for a heavy truck are from Canadian Vehicle Summary (Natural Resources Canada, 2007). For empty truck journeys, all energy use and emissions are reduced to 40%. These figures are used both for round-wood trucks and for special vehicles, both with a maximum load of 40 tonnes. Empty return journeys are assumed. 2.2. Rail transport Costs valid for rail transportation are taken or calculated from Hamelinck et al. (2004b), where cargo capacity was set at 1000 tonnes and 2500 m3 . Train costs often depend on train logistics, which can differ widely for the same transport route or distance, depending on the time and day when transportation is to take place. For the train calculations, generic km-costs and electricity use are assumed for all regions concerned; only differences in electricity costs yield regional differences (Hamelinck et al., 2004b). Data on electricity use for rail transport are taken from Forsberg (1999). For a train of 52 wagons and 40% degree of use (empty return transport), the energy supply, expressed as electricity, is 0.27 MJ/tonnekm, originating from NTM, 2000 (Carlsson-Kanyama and Faist, 2000). For emissions and primary energy use associated with loading and unloading, a mobile crane is used, which is assumed to have the same energy requirement as for a truck, above. 2.3. Sea transport Costs valid for a ship transportation of 1100 km are taken from Hamelinck et al. (2004b), where cargo capacities are set to 4000 tonnes and 6700 m3 , and the ship size and weight are comparable to the ship used by Forsberg (1999). Loading/unloading time is set to 60 m3 /h (Hamelinck et al., 2004b) for bundles, chips and pellets. Primary energy use applying to sea transport are originating from NTM, 2000 (Carlsson-Kanyama and Faist, 2000). A conventional vessel (> 8000 dwt) with ship size and weight assumed comparable to the ship used by Hamelinck et al. (2004b), with an energy consumption of 0.2 MJ ship fuel/tonnekm is assumed. 2.4. Forestry operations Material is assumed to be gathered over a 5 ha recovery area and is forwarded an average distance of 300 m to a roadside collection site (see e.g. Liss, 2003). Recovery of logging residues per ha is assumed to equate to 100 bundles per ha, or 115 MWh/ha. That equate to around 200 m3 stem volume per hectare. Data for the cost calculations of recovery operations, forwarding and local haulage are based on conditions in the Dalarna region. These conditions are
assumed to be the same as those in Jämtland region. Both areas are situated in the northern coniferous region and productivity could vary between different areas within the region. Costs for forestry operations are from Liss (2003). Calculations of emissions are based on assumptions in Liss (2003). For forwarding of bundles and loose material, a Timberjack 1410D is used. To compress bundles, a Timberjack 1410D equipped with a Fiberpac 370 is used. Productivity and fuel consumption are shown in Tables 5 and 6, respectively. 2.5. Chipping Costs for chipping are taken from Liss (2003). For calculation of emissions, a Bruks 803 ct attached to a Timberjack 1410D is assumed for the roadside chipping and a Bruks 1004 ct attached to a dumper is assumed for chipping at the conversion plant. The cost of chipping at a terminal was earlier estimated to be one-third of the cost of chipping roadside (Andersson et al., 2000). Productivities and fuel consumptions are shown in Tables 5 and 6, respectively. 2.6. Pellets production Costs of pellet production are according to Zakrisson (2002), in the Swedish case, but with the cost of raw materials from the present study, which gives 6.0 D 2007 /MWh. A similar assumption with a pellets production cost in Thek and Obernberger (2004) gives 6.2 D 2007 /MWh. Energy use for pellets production are according to Forsberg (1999, 2000), which includes chipping. Both for costs and for emissions, chipping has been subtracted from the sum and chipping emissions and costs corresponding to chipping conditions described above have been added. Also, the share of wood fuel, Table 6 Primary energy use in the studied systems Activity
Energy form
Primary energy use
Compressing (Andersson and Nordén, 2000) Forwarding (Byhlin, 2005, pers. comm.) Chipping at roadsidea Transport Truck (Natural Resources Canada, 2007) Train (Carlsson-Kanyama and Faist, 2000) Ship (Carlsson-Kanyama and Faist, 2000) Loading/unloading (Natural Resources Canada, 2007) Chipping at terminal (Andersson and Nordén, 2000) Chipping at end-user (Andersson and Nordén, 2000) Pelleting (Forsberg, 1999)
Diesel
12 l/h
Diesel
9.5 l/h
Diesel
9.5 l/h
Diesel
0.41 l/vehicle kmb
Electricity
0.075 kWh/tonnekmb
Ship fuel
0.056 kWh/tonnekm
Diesel
0.024 l/h
Diesel
50 l/G15 -hour
Diesel
50 l/G15 -hour
Electricity Diesel Wood
29 kWh/MWh 72 kWh/MWh 178 kWh/MWh
a b
Assumed. 0.41 l/km, 40 tonnes per load, 0.010 l/tonnekm, 0.10 kWh/tonnekm.
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Table 7 Physical dry-matter losses Activity
Loss (%)
Bundling Forwarding, bundles Forwarding, loose Storing, bundles Storing, loose Chipping bundles Chipping loose
2 0 2 2 15 5 10
Fig. 4. Costs and CO2 emissions for national options.
Fig. 3. Costs and CO2 emissions for local options.
used in Forsberg (1999) in the drying process, means that 18% of the energy in the incoming material is consumed, and is therefore considered a loss.
in cost, primary energy use and CO2 emissions as this distance increases or decreases. For comparison with the analysed international transportation chains starting with logging residues, from Jämtland, some harbour options are shown in Table 3 where the terminal is located by the coast, but still involves an initial haul of 80 km. These examples are adapted versions of the Loc a and Loc e options, but with international sea transport added. A pellets alternative, also shown, is an adapted version of the Pint g option. At the international end-user, a theoretical extra transport of 30 km from a harbour to the destination has been added in order to show the hypothetical effect of having to transport the bio-fuel by truck an extra distance from, for example, a harbour. 3. Results
2.7. Dry-matter losses Dry-matter losses occur mostly in the early stages of the forestfuel chain, from the forwarding of forest residues to, and including, storage at roadside (Forsberg, 2000). During storage, substantial dry-matter losses can occur due to biological activity, especially in the chipping system, due to the small particle size. Dry-matter losses in forestry operations are estimated from Forsberg (2000) and losses due to chipping are from Wihersaari (2005). Physical dry-matter losses used are shown in Table 7. 2.8. Sensitivity analyses A crucial cost in the transportation chain is the initial haulage from the forest. A sensitivity analysis considering initial haulage distance for bundles has been made in order to show the change
Costs and CO2 emissions per MWh supplied for local, national, international and pellets options are plotted in Figs. 3–6. At the local level (Fig. 3), the bundle system, i.e. bundles taken directly to the end-user (Loc a), is the most cost-effective option, but the corresponding chip system (Loc e) has the least CO2 emissions. On the national level (Fig. 4), chipping of bundles at a terminal and then transport by rail and sea to the end-user (Nat i) is a cost-effective system option, producing a moderate level of CO2 emissions. If these chips are transported by rail only (Nat d), the cost is only slightly higher, but the CO2 emissions are much greater. To chip biomass at the clearcut site and then transport the chips by rail and sea from the terminal to the end-user (Nat k) produces low CO2 emissions, but at a rather high monetary cost. On the international level (Fig. 5), the system with the lowest monetary cost and low emissions is bundles chipped at a terminal
Fig. 5. Costs and CO2 emissions for international options.
L.N. Eriksson / Resources, Conservation and Recycling 52 (2008) 1190–1197
Fig. 6. Costs and CO2 emissions for national (Pnat a–c, 600 km transport) and international (Pint a–g, 1100 km transport) pellets options. The bundle and chip systems that have proved efficient have steered the selection of pellets alternatives in order to reduce the number of possible pellets alternatives.
and then transported by rail and sea to the end-user (Int e). The transportation of chips from forest to terminal and then by rail and sea to the end-user (Int h) gives low CO2 emissions, but at a slightly higher cost. To transport bundles to a terminal and then by rail and sea to the end-user (Int b) also has a quite low cost and a moderate level of CO2 emissions. Among the national pellets options (Fig. 6), local transportation of bundles to a pellets plant and then transportation of pellets by rail to the end-user (Pnat a) is the most cost-effective option, but the corresponding chip system (Pnat b) gives less CO2 emissions. Internationally, hauling bundles to a local pellets plant, followed by transport of pellets by rail and sea to the end-user (Pint b) is the most cost-effective option. To transport chips to the local pellets plant and then by rail and sea (Pint d) produces much less CO2 , but at significantly higher cost. Transport of bundles 250 km to the coast by truck and then as pellets to end-user by ship (Pint g) produces low CO2 emissions, but at moderate cost. The primary energy use for the options studied ranges between 5–8% and 6–9% of the delivered bio-energy for logging residues and pellets options, respectively. Figs. 7–8 detail the costs, primary energy use and CO2 emissions per MWh supplied, for low cost and/or low CO2 emission options for all distances studied. Local options are the most efficient. The costs of national pellets, bundles or chips options are close, but pellets requires much more primary energy and produce more CO2 . International options too are similar in cost, but the pellets options require more primary energy. In Fig. 9, a cost breakdown diagram for the low cost and/or low CO2 emission options is shown. The cost of pellets production reduces the cost of hauling to the end-user, which could make international transportation of biomass as cost-effective as the national use of biomass.
Fig. 7. Costs for least expensive and/or low CO2 emission options from Figs. 3–6.
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Fig. 8. Primary energy use (PE) and CO2 emissions for least expensive and/or low CO2 emission options from Figs. 3–6.
Long transportation distances that increase the time for biomass storage can lead to greater dry-matter losses due to biological activity in the transported biomass. What fraction of the fuel value is lost due to long-distance transportation is difficult to calculate due to shifting environmental conditions for the forest fuel along the transportation chain. However, the biological activity increases as the particle size in the stored material decreases. Storage of bundles leads to modest dry-matter losses, which are significantly less than those losses incurred by chip storage (Jirjis and Nordén, 2002). This means that in some cases, bundles could be preferable to chips in some of the examples highlighted in Figs. 7–9, especially as regards international alternatives (Int b vis-à-vis Int e and Int h). However, the assumption is that the duration of transportation is kept short, which means low losses. The sensitivity analysis of the initial hauling distance for bundles, considering cost, primary energy use and CO2 emissions as this distance increases or decreases, is shown in Fig. 10. If the ini-
Fig. 9. Cost breakdown for least expensive and/or low CO2 emission options.
Fig. 10. Sensitivity analysis considering transportation distance of initial haulage of bundles, as an example of the impact of distance choice on the final results. The diagram shows the interval of 50–200% of the distance chosen in the scenarios.
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lands is in the same range as the CO2 emissions from our international options. For a pellets alternative the corresponding figure is around 3.3 kg C/MWhchip , which is lower than in our study. In our adapted international harbour options, where the terminal or pellets production plant was moved to the coast, CO2 emissions decreased and reached the level in Forsberg’s results. In the pellets options, more primary energy is used, which reduces the desired substitution of fossil fuels per hectare. Also, the reduced CO2 emission from fossil fuel will be less (per hectare) than with the bundle and chip systems. Nevertheless, the replacement of fossil fuel per hectare is still high. Fig. 11. Costs and CO2 emissions for the international harbour scenarios. At enduser, a 30 km extra hauling distance has been added, where bundles (hint a), chips (hint b and c) and pellets (hint d) are transported.
tial haulage is halved – or doubled – the cost will decrease by 0.77 D 2007 /MWh (28%) or increase by 1.5 D 2007 /MWh (57%), respectively. Harbour alternatives are shown in Fig. 11. Their cost lie between 18 and 20 D 2007 /MWh, excluding the cost of an extra hauling distance. 4. Discussion Our results show that large-scale, long-distance transportation of bio-fuels from central Sweden has the potential to be feasible in both economic and energy respects, as well as attractive in terms of greenhouse gas emissions. However, primary energy use and CO2 emissions for local and national alternatives are lower, as also is the cost for the local alternatives. The costs for international options with traditional chip and bundle systems varied between 23–28 and 21–26 D 2007 /MWh, respectively, and for pellets options between 22 and 25 D 2007 /MWh. These figures approximate the results in Hamelinck et al. (2004a), thus supporting the impression of the costs associated with international transportation chains from Scandinavia to The Netherlands. When the terminal in the present study was moved to the coast, the cost for the bundle options became the same as in Hamelinck et al. (2004a) and the cost for chip options became even lower. In Hamelinck et al. (2004a) the biomass cost for bundles was about half the cost of chips, which could explain the considerable difference between the two systems in their calculation. Procurement costs differ for different species and productivity in different parts of the world. Comparisons of biomass costs could be made with for example solid biomass imported from Latin America delivered to a Dutch power station at about 8.3 D 2007 /MWh (energy crop logs, 20% moisture content) or methanol from Latin America delivered to Europe at 33–41 D 2007 /MWh (Hamelinck et al., 2004b). The results also show CO2 emissions of 1.0–4.9 kg C/MWh from transport systems for various alternatives for local and national transport of bio-fuel. In Wihersaari (2005), assumptions for harvesting and chipping methods and transportation distance were close to the local options in our study. Her evaluations of emissions from collecting, chipping and transporting the residues, viz. about 4–7 kg CO2 eq per MWhchip (around 1.0–1.7 kg C/MWhchip ), are close to the CO2 emissions of 1.5–3.0 kg C/MWh from our local options, thus supporting the impression of the amount of CO2 emissions associated with local transportation chains for logging residues. In Forsberg (Forsberg, 2000) the CO2 emission around 3.5 kg C/MWhchip , for an option with logging residue bales transported from Sweden to The Nether-
Acknowledgements We gratefully acknowledge financial support from the European Union, from Jämtland County Administrative Board and from Sveaskog AB.
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