• Open Access

Sustainability impact assessment of increasing resource use intensity in forest bioenergy production chains

Authors


Wendelin Werhahn-Mees, tel. +491 796 558 221, fax +498 207 958 840, e-mail: werhahnw@hotmail.com

Abstract

Changing forest management practices towards more intensive biomass utilization for energy purposes will affect the sustainability of resource management. The Tool for Sustainability Impact Assessment was applied to evaluate the environmental, social, and economic sustainability impacts of the stepwise increased extraction of forest biomass of three typical Scandinavian Scots pine bioenergy production chains (BPCs). The assessed sources of the woody biomass were pellets as a by-product of the sawmilling industry, wood chips deriving from early whole-tree harvesting, and residues from final cuttings. Three commercially practiced BPCs were compared. By the additional extraction of biomass for heat production, the employment increased by 0.6 person-years 1000 m−3 solid wood chips, while there was a decrease in the costs and greenhouse gases emitted per unit of heat consumed. Furthermore this practice did not only add positive socio-economic but also positive environmental impacts on sustainability, particularly on the greenhouse gas balance and the energy efficiency ratio (input to output ratio along the BPC), which was determined to be 1–24. Potential drawbacks, on the other hand, include decreasing nutrient returns to the soil and the associated potential reduction in future stand productivity. Fertilization might be needed to maintain sustainable forest growth on poor sites.

Introduction

On a world-wide scale, energy production accounts for a large part of greenhouse gas (GHG) emissions with over 25% of the total emissions (Rogner et al., 2007). In order to reduce emissions, more and more emphasis is being placed on the use of renewable energies to replace fossil fuels (Hall & Scrase, 1998; Chum & Overend, 2001). For more than a decade the European Commission has placed an emphasis on the promotion of renewable energy for more than a decade already. The ‘White Paper on Renewable Sources of Energy’ established the goal to double the contribution of renewables from 6% in 1997 to 12% in 2010 (European Commission, 1997). Later, the; Renewable Energy Road Map; established a mandatory (legally binding) target of 20% for renewable energy's share of energy consumption in the EU by 2020 (European Commission, 2007).

Among the sources of renewable energy, wood is currently the most important in Europe with a share of over 50% of the total renewables (Bosch et al., 2007). Renewable energies from biomass, such as wood, have an advantageous CO2 balance, because atmospheric CO2 is sequestered in the regrowing biomass (Marland & Schlamadinger, 1995; Hall & Scrase, 1998). At the same time, the domestic production of bioenergy allows the dependency on foreign sources of energy to be reduced.

Among the different methods of using woody biomass for energy in Europe, the most common technologies outside of the forest industry are district heating and pellet ovens for heating households (Joelsson & Gustavsson, 2008). In recent years there has been a large increase in the production of pellets (Heinimö & Alakangas, 2006; Alakangas et al., 2007). While the industrial residues are already effectively utilized within the production chains, the potential for increasing production of wood-based depends on increasing the extraction of forest biomass, such as harvest residues (Hakkila, 2006). Biomass extraction for energy purposes has already increased rapidly in the Nordic countries during the past years (Hakkila, 2006; Trømborg et al., 2008). The most recent developments are the increased whole-tree harvesting in early thinnings and stump harvesting in final fellings of spruce stands (Laitila et al., 2008).

The increasing extraction of forest biomass is going to have various effects on forests and forestry in general. Positive effects are anticipated for the rural economy, e.g. by offering employment options for local entrepreneurs. However, depending on the implemented practice, there is a risk of negative effects with respect to other objectives of sustainable forest management (e.g. nutrient extraction, biodiversity) (European Environment Agency, 2007; Raulund-Rasmussen et al., 2008). It is therefore important to consider different aspects when planning and evaluating the sustainability impacts along the bioenergy production chain (BPC) of different energy production methods. Integrated assessment methods have been recently developed to enable the assessment of sustainability impacts (environmental, economic and social) of policies and management actions in sectors managing natural resources (Ewert et al., 2009; Lindner et al., in press).

In this study, the recently developed Tool for Sustainability Impact Assessment (ToSIA) (Lindner et al., in press) was used to assess and compare sustainability impacts of increasing biomass utilization with three alternative Scots pine (Pinus sylvestris L.)-based BPCs in Nordic countries. Technologies studied were selected from those that are in commercial use in the typical BPCs in the area. Technologies studied:

  • Pellet production from dry sawdust;
  • Early energy wood thinnings for the production of wood chips;
  • Extraction of harvest residues from final clear cutting for the production of wood chips.

The sustainability impact assessment takes the most common BPC for household heat production as a starting point – the pellet production from sawdust. Using secondary forest residues for bioenergy production is economically most attractive and there has been a very rapid development of production capacities in Scandinavia. In this region it can be assumed that all secondary forest residues are already used for material or energy use. Meeting ambitious bioenergy targets will only be possible by increasing the extraction of fresh biomass from the forests. In this study we focus on pine stands as pine is the predominant species in the Nordic countries. As stump harvesting is practiced mainly on spruce dominated stands (Laitila et al., 2008; Palander et al., 2009), this additional source of biomass was excluded from this study.

We aimed to investigate the effects of increasing intensity of forest biomass extraction for energy purposes on different indicators of sustainability. Specific research questions of this study were:

  • If we compare the alternative BPCs per unit of heat consumed, which chain has the best greenhouse gas (GHG) balance, and which chain has the best energy efficiency ratio?
  • Which chain has more positive effects on social and economic aspects, and what are the potential environmental trade-offs?

The results are presented and discussed in the light of developing methods for assessing technology options with respect to their sustainability impacts.

Materials and methods

BPCs

Three alternative Scandinavian Scots pine BPCs (Fig. 1) were compared in this study, representing a sequence with increasing utilization of forest biomass for bioenergy.

Figure 1.

 The topologies of the Pellet Chain (P), the Pellet and Energy Wood Chain (PE) and the Pellet, Energy Wood and Harvesting Residues Chain (PEH). The arrows linking processes represent the material flow. The white processes are identical in all bioenergy production chains. In the P Chain lumberjacks cut the biomass in the young stand and left in the stand (processes highlighted in light grey), in PE/PEH Chain the biomass is harvested (grey process), in the PEH Chain the harvest residues from clear cut are removed as well (dark grey). The products pulpwood and sawlogs leave the chain. The indicator results of the processes where pulp or logs are included are allocated on a mass basis to the impacts of the energy wood.

  • (i)Pellet Chain (P Chain): BPC with pellet production from sawdust of the sawmill processes with consumption of pellets in single households; no biomass for wood chips production is extracted from the forest.
  • (ii)Pellet and Energy Wood Chain (PE Chain): BPC which in addition to the P Chain includes early whole tree thinnings for the production of wood chips, which are used for heat production and final consumption via district heating.
  • (iii)Pellet, Energy Wood and Harvest Residue Chain (PEH Chain): BPC which in addition to the PE Chain includes the extraction of the harvest residues from final clear cutting for the production of wood chips for heat production.

Table 1 shows the assumptions made for all process of all BPCs. The forest management processes (Processes 1–5) are identical for all chains. The forest management processes were defined and parameterized using data from Västerbotten in Sweden and North Karelia in Finland. The harvested pulpwood leaves the investigated BPC after forwarding (Processes 12 and 13); also the further processing of sawn timber after the sawmill (Process 19) is excluded.

Table 1.   Assumptions for the processes of all BPCs
ProcessesAssumptions
  1. Processes numbering on the left side; process names are shown in Fig. 1.

  2. BPC, bioenergy production chain; P Chain, Pellet Chain; PE Chain, the Pellet and Energy Wood Chain; PEH Chain, Pellet, Energy Wood and Harvesting Residues Chain.

1Regeneration of a new pine stand by scarification and planting at a spacing of 2.3 × 2.3 m
2Process describes stand growth until development phase young (age 5), 3 m3 ha−1, cut down and left on the stand
3Pine stand in the age of 6–25, very dense, average diameter 11 cm, height 13 m, basal area 25 m2, dominated by pine, birch and alder, in P Chain the biomass is cut down and left on stand, in PE and PEH Chains 90% of harvested biomass is extracted and chipped, 90 m3 ha−1 (whole-tree)
4Pine stand in the age of 26–50, thinning by machine, stand is treated one more time before the final cut, mainly pulp, some logs and some birch pulp, harvesting residues are left on stand, 54 m3 ha−1 (9 m3 ha−1 logs and 45 m3 ha−1 pulp) over bark
5Pine stand in the age of 51–85, clear cutting of stand, mainly log, some pulp, average volume between 165–170 m3 ha−1, in PEH Chain 90% of the harvesting residues are extracted and chipped, 120 m3 ha−1 log, 50 m3 ha−1 pulp over bark and harvesting residues 36 m3 ha−1
6Thinning of the stand (Process 2) by lumberjacks by chain saw, biomass is cut to waste
7Clearing of the stand by lumberjacks by chain saw, reduction from ca. 26 m2 basal area to 16 m2 ha−1, process only valid in P Chain
8Energy wood harvesting with feller buncher, results are based on productivity of Timberjack 720 accumulating felling head, data based on productivity per year
9Medium-sized harvester (John Deer 1270B), data based on average productivity of thinnings
10Large-sized harvester (John Deer 1470D), data based on average productivity of clear cutting
11Forwarding of biomass with a midsized forwarder, unloading the residues at roadside, building of proper storage piles, data based on average productivity, 10% loss biomass
12Forwarding of pulp and logs to roadside with midsized forwarder, data based on average productivity
13Forwarding of logs and pulp with large forwarder to roadside, data based on average productivity
14Storage and chipping of whole tree at the roadside, directly in wood chip trailer, Chipping managed by one person, truck-based chipper: Kesla Foresteri, loader: Kesla Foresteri 700, storage at the roadside, average storage time 1.5 years (assumed interest rate of 6%€20 m−3)
15Transport of timber with 60 t truck, transport distance one way 80 km, data based on average productivity and share of empty back haulage 100%
16Transport in regional power plant, average transport distance one way 40 km, moisture content of wood chips 35%, share of empty back haulage 100% and operating hour 4440 h yr−1
17Timber is measured and sorted, employment effect and energy consumption included in Process 19
18Wood chips are burned in a small-size heating plant, example Eno Energy Cooperative, boiler grate 1.2+0.8 MW, efficiency of plant 75% (including other transmission losses), moisture content of wood chips 35%, 2.2 MW h m−3 whole tree, no recycling costs for ash (returned to forest), 0.5 person-year employed, life time of facility 25 years and investment costs of ca. €650 000
19Midsized sawmill (ca. 750 000 m3 log input), output: 60% board, 5% waste and 35% sawdust (resource for pellet production) and moisture content of sawdust 20%
20Transport with 60 t truck, average transportation distance 80 km, 100% empty back haulage and operating hours 4440 h yr−1
21Pellet production facility with capacity of 25 000 t yr−1, electricity from grid and moisture content pellet 10% (Thek & Obernberger 2004)
22Transport of pellets to consumer with 60 t truck, average transport distance 85 km, back haulage 100% empty and operation hours around 4500 h yr−1
23Public and private houses are supplied with district heat in the municipality, €300 000 investment cost for pipeline system, heat losses 3% loss of total heat produced, length of network 2020 m and costs of radiator in household not included
24Investment cost of pellet boiler included installation (€20 000), 6 t yr−1 pellet consumption, life time boiler 30 years and efficiency of heating system 87.5%

ToSIA

The SIA for the studied chain was done using version 1.0 of ToSIA (Lindner et al., in press), which was developed in the EFORWOOD project (http://www.eforwood.org). ToSIA specifies the BPC as a chain of production processes from forest resources management to consumption and end-of-life of wood products and assesses sustainability impacts by quantifying and comparing a selection of sustainability indicators between BPC alternatives. The processes of the BPC are connected by input and output products (see fig. 3 in Lindner et al., in press). For example, in the PEH Chain the process Forwarding of biomass to roadside has the input products Whole-tree biomass and Harvest residues from clear cut, and the output product Biomass at roadside. The start of the investigated BPCs was set to forest regeneration, and the end to the energy consumption in private households.

ToSIA calculates material flows through the production processes of the BPC and links the processes with the sustainability indicators reported per unit of material flow, e.g. Production cost in euro/m3. Conversion factors are used whenever the unit of the material flow changes, e.g. from m3 in a forwarding process to tons in a transport process (Table 2).

Table 2.   Conversion factors are needed to calculate material flows
ProductsUnitsConversion factor to
m3tt of C
Pine pulpwood, sawlogsm310.8170.215
Pine harvesting residues, full treem310.720.215
Whole tree wood chipsm310.5810.215
Sawn pine woodm310.450.215
Pine wood residues at pellet production facilityt10.5
Pelletst1.53810.450
Heat producedkW h0.0004550.0002640.000098

The yield level of final cutting for all BPCs is fixed to the equivalent of 1000 t of carbon (tons of carbon being the ToSIA internal calculation unit), in order to initialize the flow amounts of the calculations of the entire BPC. The harvest amounts were then converted to hectares by assuming an estate of normal forest (i.e. a fully regulated forest) consisting of a myriad of stands, with age classes covering the whole range from 0 years to clear-felling age (Davis et al., 1987). This resulted in a forest area of 1803 ha as the basis for indicator calculations in this study.

The sustainability assessment approach developed in the EFORWOOD project focuses on the impact assessment of changes in policies or management practices on sustainability (Päivinen et al., in press). As we are lacking sustainability thresholds for many indicators (e.g. GHG emissions), it is problematic to assess the sustainability of an individual BPC. However, comparing alternative BPCs with varying resource use intensity reveals the comparative sustainability impacts of the alternative resource uses and allows steering decision making to support sustainable development.

The sustainability indicators

For the present study, an indicator set was chosen based on indicators developed within the EFORWOOD project (Rametsteiner et al., 2008) (Table 3). The selected indicators characterize different aspects of sustainability (cf. Raulund-Rasmussen et al., 2008) and data were available to be used for our case study. Table 4 shows all indicator input data by process.

Table 3.   The indicator set used in the study with units and definitions
IndicatorUnitDefinition
  1. The values in the Table 2 are used to convert the amounts of products along the bioenergy production chain into different units, e.g. Pine sawlogs in m3 into t, factor 0.817 (t m−3).

Economic
 1. Production costsEuroLabour costs (cost incurred by the employer), energy costs (e.g. fuel costs in case of transportation), other productive costs (maintenance, general industrial costs, administrative costs, sales expenditures, etc.) and nonproductive costs (corporate taxes, capital charges, VAT and any other taxes or charges)
 2. Resource/Material usem3Material extracted from the forest
 3. Total heat consumption at use stageMJHeat in MJ consumed by households
Social
 4. EmploymentPerson-yearsAbsolute number (in full-time equivalents in reference year) which can be allocated to the particular process
 5. Wages and salariesEuroReported as gross earnings, i.e. before any deduction for tax or contributions to social security by the worker and the employer i.e. labour costs (cost incurred by the employer)
 6. Safety and healthAccidentsFrequency of occupational accidents and occupational diseases of all kinds as total number
Environmental
 7. Greenhouse gas emissionsTons of CO2 equivalentEmissions calculated as Global Warming Potential (GWP) for 100 years, forest management processes are excluded, after IPCC (2006) guidelines
 8. Transportt kmMovement of freight, integration of ‘loaded distance’ and ‘unloaded’ distance for road, all transport processes 100% empty back haulage, tons multiplied per distance in km
 9. Energy
  9.1 Energy useMJAll energy (diesel, electricity from grid and heat for drying in sawmill) used in processes
  9.2 Heat generation from renewablesMJHeat generated in processes from biomass without efficiency losses (e.g. efficiency of boiler and heating network)
 10. Average carbon storage in cut biomassTons of CAverage stock of carbon over the rotation of the forest stand in the decaying cut, 10% of total biomass over a 100-year rotation
 11. Maintenance of soil qualitykgOnly considered are the nutrients (nitrogen, phosphorus, potassium, calcium and magnesium) removed in the early thinning. Excluded are nutrients removed in the other thinnings and the final harvesting
Table 4.   Input data for the calculation of the indicators by process, indicator data are always given per process unit, e.g. Process number 9 Felling with large harvester and Indicator 1
Process
by
number
Indicator1. Production
costs
3. Total heat
consumption
at user stage
4. Employment5. Wages
and
salaries
6. Safety
and
health
7. Greenhouse
gas
emissions
8. Transport9.1 Energy
use
9.2 Heat
generation
from
renewables
10. Maintenance
of soil
quality
UnitEuroMJPerson-yearsEuroAccidentst of CO2 equivalentkmMJMJkg
  1. Production costs €8.1 m−3.

1ha393.00.00479900.0001970.0850
2ha
3ha
4ha
5ha
6ha216.71.0E–02191.72.8E–070.0491487
7ha500.01.0E–02442.31.9E–050.0491487
8m312.91.2E–043.82.8E–070.006786
9m38.14.6E–052.42.8E–070.005154
10m34.33.5E–051.12.8E–070.002527
11m36.05.0E–052.12.8E–070.0033432.82
12m33.95.0E–051.62.8E–070.003628
13m34.04.6E–051.52.8E–070.003436
14m37.13.3E–051.22.8E–070.003951
15t7.15.6E–052.31.2E–060.0087160100
16t9.81.2E–043.41.2E–060.00468060
17m30.39.5E–060.30
18m356.71.6E–044.92.8E–070.014807800
19m3139.36.0E–0414.02.8E–070.03592556468
20t9.63.8E–053.62.9E–070.0083160107
21m317.87.6E–053.32.8E–070.27131785
22t8.01.7E–042.72.9E–070.0083170116
23m320.578001.6E–044.9
24t180.114 8052.3E–040.00.031716 920

Economic indicators

Economic indicators selected for this study quantify the costs and material use of the production chain as well as the production of heat. The indicator Production costs includes all costs occurring in the individual processes. The following cost factors were considered in the calculation for the heating facilities (pellet and wood chips): (i) the investment costs (pellet boiler, heating centre with the network), (ii) labour costs (installation, maintenance) and (iii) the raw material costs. The assumption for the calculation of the investments costs was an interest rate of 5% over a lifetime of the infrastructure of 25 years. The costs for installing the heating system in the buildings were excluded in the BPC alternatives, as the investment is necessary for each heating system.

The indicator Resource use represents the total amount of extracted biomass from the forest for energy production. The indicator Total heat consumption at use stage is the heat that is finally received by the consumer (i.e. burning pellets at the home-scale or heat arriving from the heating plant).

Social indicators

Three social indicators were selected. The indicator Employment represents the employment effect (i.e. number of person-years) that is created in the production along the BPC. The Wages and Salaries are the gross income of the employees along the BPC proportional to the work done. With the indicator Safety and Health, the occupational accidents occurring are demonstrated.

Environmental indicators

For the study, five indicators representing different environmental aspects were selected.

The indicator GHG emissions quantifies the carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) emissions occurring in the processes along the BPC; the quantification follows the Intergovernmental Panel on Climate Change (IPCC) regulations (2006), except that the CO2 emitted through the combustion of the wood (wood chips and pellets) is not taken into account as an emission.

The environmental impacts of transport were measured with the indicator Transport. It represents the transport load expressed as a product of transport distance (unit km) and the total amount of material that was transported (unit ton). The average transportation distance applied in the indicator calculations for pellets and wood chips were 160–170 and 40 km, respectively (Table 4).

The indicator Energy use shows the energy consumption of production processes in MJ. The total of the indicator Energy use is the sum of all energy that was invested in the products until they reach their particular use stages – e.g. diesel consumption in the wood chip production, harvesting, forwarding, chipping and transporting to the heating plant or e.g. the electricity consumption in the pellet production and sawmilling process. The indicator Heat generation from renewables shows the theoretical heating value of the incinerated wood.

The indicator Average carbon storage in cut biomass shows roughly the average stock of carbon over the rotation of the forest stand in the decaying cut biomass that is left in the forest after harvest. Based on simulation studies in Nordic conditions, the average carbon stock of branches and needles left in forest as harvest residues has been calculated as about 10% over a 100-year rotation (see e.g. Palosuo et al., 2008). Here we applied this 10% of the carbon bound in the decaying biomass of cut trees from early thinning (P chain) and final harvest (PE and PEH chains) to calculate the average difference between the soil carbon stocks of the BPCs.

In the P Chain the decomposing material left in forest consists of biomass from clearing by lumberjacks and harvesting residues from clear cutting. In the PEH chain both energy wood from early thinnings and harvesting residues from clear cut are extracted for energy production. In calculating the biomass amounts left in forest, it was assumed that 10% of the potential energy wood cannot be extracted from the forest due to technical reasons, e.g. losses when forwarding biomass.

The Maintenance of soil quality quantifies the extraction of the most important nutrients (Nitrogen, Calcium, Potassium, Phosphorus, and Magnesium) that is due to the extraction of energy wood and harvest residues. In general, the nutrient depletion of forest stands caused by harvesting of sawlogs and pulpwood is marginal relative to the amounts extracted by the harvesting of energy wood (Hakkila, 1989) and identical for all chains. In the P Chain only pulpwood and sawlogs are extracted from the forest, where as the biomass remains in the stand. Hence the value of the indicator 10 for the P Chain was set 0. It has been calculated that there are about 2.82 kg total nutrients per m3 solid wood chips extracted when harvesting energy wood, using the EnerTree model (Röser et al., 2006) on the basis of the assumptions of the different forest management processes (see Table 1).

Data sources

The data used for the calculations of the wood chip production chain were collected and processed based on Finnish data (see e.g. Heikkiläet al., 2006; Laitila, 2006) and represent the situation in the year 2007. The set up of the chain was derived from the regional example of the wood chip utilization by the ‘Eno Energy Cooperative (http://www.enonenergia.fi)’, in the municipality of Eno in North Karelia, Finland, which is representative of a small-scale BPC in Scandinavia.

Furthermore, the data used for the harvesting, forwarding, chipping and transport processes were based on models developed by METLA (Finnish Forest Research Institute). The data used for the Process Pellet production were based on Thek & Obernberg (2004). The data for the sawmilling process were provided by VTT (Technical Research Centre of Finland) in the context of the EFORWOOD project.

Results processing

The calculated indicator results of each of the processes were aggregated along the chains by summing them. They were presented as totals and in relation to the heat consumed in use stage processes. The raw material costs from the BPC were only counted once (using the costs of the pellets or wood chips in the energy production stage) when summing up the total production costs.

Aggregated indicator results also included the sustainability impacts due to, for example, harvesting and transporting of sawlogs and pulpwood in the forwarding and harvesting processes. To be able to exclude those impacts we redefined the system boundaries by the allocation procedure developed for ToSIA (Palosuo et al., in press). This redefinition was done by applying carbon-based allocation as a close approximation for the mass-based allocation, as wood-based carbon is used as an internal unit for the material flow calculations of ToSIA. This means that the results presented in this paper only consider the resource used for the energy production, i.e. excluding the impacts due to the sawlogs and pulpwood. The processes affected by this procedure were the Processes 9, 10, 12, 13, 15, 17 and 19 (Fig. 1).

Sensitivity analysis

To assess the sensitivity of the indicator results to changes in two crucial variables – (i) the moisture content of the wood chips, and (ii) the transportation distance of the wood chips – a sensitivity analysis was carried out for the indicator results of the PEH Chain.

The moisture content of the chips determines how much energy can be produced from the chips, and the weight of the chips affects the energy used in transportation. Transport distance is an important variable affecting e.g. GHG emissions and energy use. The moisture content of the wood chips was varied from 20% to 60% (initial value applied 35%) following the typical values observed. Transport distance of the chips was varied from 20 to 100 km (initial value applied 40 km, which is the average in North Karelia, Finland and representative also in other parts of the region (Börjesson & Gustavsson, 1996).

Results

The aggregated indicator results are presented in Table 5. All indicators are presented as absolute totals aggregated along the whole BPC as well as relative to one unit of heat consumed, i.e. the aggregated indicator results divided by the Total heat consumed at use stage. Furthermore, the percentage change of the absolute and relative indicator results from P to PE and PEH Chain are presented in Table 6.

Table 5.   Economic, social and environmental indicator results calculated with ToSIA for the three BPCs; pellets chain (P Chain), pellets and energy wood chain (PE Chain) and pellets, energy wood and harvest residues chain (PEH Chain)
IndicatorP ChainPE ChainPEH ChainIndicator unit
TotalRelativeTotalRelativeTotalRelative
  1. Absolute values per indicator aggregated for the whole BPC in indicator units and the relative values per unit of heat consumed [i.e. the aggregated indicator results divided by the Total heat consumed at use stage (indicator 3)] are shown. All results are calculated for a specific year (2007) and the same forest resource area (1800 ha).

  2. BPC, bioenergy production chain; ToSIA, Tool for Sustainability Impact Assessment; na, not applicable.

Economic
 1. Production costs209 5510.032359 1110.021417 4240.019Euro (MJ−1)
 2. Resource/material use95614629991783976182m3 (TJ−1)
 3. Total heat consumption at use stage6 543 094na18 252 158na23 265 438naMJ
Social
 4. Employment1.101.68E–072.161.28E–072.991.37E–07Person-years (MJ−1)
 5. Wages and salaries26 9860.004159 0720.003574 1560.0034Euro (MJ−1)
 6. Safety and health0.00370.0005670.0079680.00047240.0086870.0003984Accidents (TJ−1)
Environmental
 7. Greenhouse gas emissions7010.61307.71537.0Tons CO2 equivalent (TJ−1)
 8. Transport279 11842 658367 06521 763409 12718 764t km (TJ−1)
 9. Energy
  9.1 Energy use2 306 0460.35242 732 6130.16202 774 3920.1272MJ (MJ−1)
  9.2 Heat generation from renewables7 933 5141.2122 271 5171.3229 128 8941.34MJ (MJ−1)
 10. Maintenance of soil quality0na5184na7663nakg
 11. Average carbon storage in cut biomass65na25na4naTons of C
Table 6.   Changes in % per indicator of PE and PEH Chain to the P Chain, for the absolute totals and the absolute relative to the heat consumed at use stage
IndicatorAbsolute change in %Relative change in %
PEPEHPEPEH
  1. P Chain, Pellet Chain; PE Chain, the Pellet and Energy Wood Chain; PEH Chain, Pellet, Energy Wood and Harvesting Residues Chain; na, not applicable.

Economic
 1. Production costs7199−34−40
 2. Resource/material use2143162225
 3. Total heat consumption at use stage158233nana
Social
 4. Employment96172−24−18
 5. Wages and salaries119175−15−18
 6. Safety and health115134−17−30
Environmental
 7. Greenhouse gas emissions87120−28−34
 8. Transport (road)3247−49−56
 9. Energy
  9.1 Energy use1820−54−64
  9.2 Heat generation from renewables181267910
 10. Maintenance of soil qualitynananana
 11. Average carbon storage in cut biomass−62−94nana

Economic indicators

The absolute totals of all three economic indicators, Production costs, Resource/Material use and Total heat consumption at use stage increased with the amount of biomass extracted. However, the increase of Total heat consumed (233%) was greater than the increase of the Production costs (99%) from the P Chain to the PEH Chain (Table 6). The costs per unit of heat consumed were clearly lower when additional woody biomass was extracted (Table 5).

Social indicators

The totals of all social indicators were higher for the PEH Chain than for the PE Chain and the P Chain (Table 5). Yet, the results per unit of heat consumed decreased the more biomass is extracted from the forest stand, with exception of the indicator Employment, which was smallest for the PE Chain. The total Employment increased by 96% for the PE Chain and by 172% for the PEH Chain compared with the P Chain. The Safety and health indicator (number of accidents) showed an increase from the P Chain to the PEH Chain, but the results per unit of heat consumed decreased.

Environmental indicators

The total GHG emissions of the PE and PEH Chains were 87% and 120% larger than those of the P Chain, respectively (Table 6). When considering the indicator results per unit of heat consumed, the emissions were smaller by >30% from P to PEH Chain (Table 5). The additional need for transportation rose by almost 50% when all biomass is extracted from the forest stand (PEH Chain). However, when dividing the total transportation by the additional heat used by the single households, the transportation decreases by >50% for the PEH Chain (Table 5).

The Energy use of the additional processes of the chipping chain was very small in comparison to the energy use of the pellet production, which is indicated by the increase of 20% only for the total Energy use from the P Chain to the PEH Chain (Table 6). The Heat generation indicator, on the other hand, demonstrates that the difference between the theoretical heating value of the material and the final heat consumption at the use stage was larger in the PEH Chain (1.34) than in the P Chain (1.21) (Table 5).

The result of the indicator Maintenance of soil quality for the P Chain is zero, as the harvest residues from clear cutting and thinnings were left in the forest (i.e. nutrient extraction of sawlogs, pulpwood excluded). The amount of fresh whole-tree biomass finally extracted from the forest stand was about 1840 solid m3 in the PE Chain and about 2720 solid m3 in the PEH Chain. Hence, the nutrient extraction amounted to 5.2 and 7.7 t, respectively (Table 5).

In the PEH Chain only 4 t of C are left on the forest stand as not all biomass can be harvested (Table 1), whereas 65 t of C are left in the forest in the P Chain. The Average carbon storage in cut biomass was therefore >15 times higher for the P Chain than for the PEH Chain.

Sensitivity analysis

In comparison to the PEH Chain baseline (wood chip moisture content 35%) the total heat consumption at the use stage increased by 9% for wood chips with a lower moisture content (wood chip moisture content 20%). For wood chips with a higher moisture content, the heat generated and then consumed at the use stage decreased by 3% (Table 7). With increased transportation distance, the GHG emissions and the energy use increased by 7% and 5%, respectively. For both parameters, the greatest impact of changes was observed for the transport indicator. Those indicators not affected at all by the changes (i.e. indicators 2, 10 and 11) were excluded from the sensitivity analysis.

Table 7.   Results of the sensitivity analysis (SA) of the PEH Chain applied for two parameters, the moisture content and transport distance in km of the wood chips
IndicatorMoisture content (%)Transport distance (km)
206020100
  1. Results are presented as changes in % from the baseline (PEH Chain, moisture content 35%, average transport distance 40 km). Zero values indicate that there is no difference between alternative and baseline.

  2. PEH Chain, Pellet, Energy Wood and Harvesting Residues Chain.

Economic
 1. Production costs−1201
 3. Total heat consumption at use stage9−300
Social
 4. Employment−1100
 5. Wages and salaries−1100
6. Safety and health−3300
Environmental
 7. Greenhouse gas emissions−11−27
 8. Transport (road)−45−1648
 9. Energy
  9.1 Energy use01−25
  9.2 Heat generation from renewables4−900

Discussion

Economic sustainability

The impacts on economic sustainability were assessed using the production costs, resource use, and the total heat consumed at the use stage. In particular the production costs are relevant because they give clear information on the competitiveness of the energy sources.

Considering the absolute indicator results, the PEH Chain had larger material/resource use, production costs, and heat produced and consumed than the P Chain. This is reasonable, because the additional processes of the PEH Chain (P Chain 18 vs. PEH 23 processes) create costs, use more raw material, and therefore increase the total costs of the combined chain. However, the costs per unit of heat consumed for the combined chains (PE and PEH) were notably lower, which indicates that the combined chains have an economic advantage. This reflects that the technology used in the wood chip production is less complex than pellets when burned for energy.

In our example chains, the pellet production includes three transport processes until the product reaches the consumer, whereas the wood chips are transported only once and the average transport was only 40 km (cf. Börjesson & Gustavsson, 1996). Besides the harvesting, the transport distance is the main constraint for the economic efficiency of the wood chip production (Hakkila, 2003). Another major factor for the economic efficiency of wood chip production for energy purposes are state subsidies, for example in Finland and Germany (Faaij, 2006; Heikkiläet al., 2007). In Finland, about one-third of the energy wood harvesting costs are covered from subsidies of the Finnish state (in our example, 10 EUR of 32.8 EUR per solid m3). Without the state subsidies and at current wood chip prices, the utilization of harvesting residues for wood chips production could only be profitable in a limited way.

Social sustainability

The indicators employment, wages, and health were selected to cover the social aspects of sustainability. In particular the employment effect and associated wages and salaries of such production chains are an important factors supporting sustainable development in rural areas in Nordic countries.

The employment, wages and salaries as well as the occupational accidents increased for the combined chains in totals, but were smaller per unit of heat consumed. The employment effect of the additional extraction of biomass for heat production was very positive. The BPC alternative where all biomass was extracted from the forest stand (PEH Chain) created significant additional employment. The result of 0.62 employees a year per 1000 solid m3 harvested is in accordance with other studies (see e.g. Ahonen, 2004).

If we compare the employment of the chains per unit heat consumed the value decreases from the P to the PEH Chain. This is due to the fact that the additional employment of the wood chip production is relatively higher (increase by about 40% from PE to PEH) than the amount of heat produced (increase by about 30% from PE to PEH), if the harvesting amount of energy wood is increased. However, even if the employment per unit of heat consumed decreases from P to PEH Chain, the additional establishment of about two person-years in the PEH Chain (i.e. 0.6 person-year 1000 m−3 solid wood chips) still has a significant regional socio-economic impact.

Environmental sustainability

The environmental sustainability of the studied chains was assessed with indicators related to GHG emissions, transport needs and energy use, carbon stock of decomposing material and effects on soil quality. Because of a lack of suitable data an indicator on biodiversity was not included in this study. Other studies have indicated that biodiversity may be negatively affected by more intense biomass extraction (Eggers et al., 2009; Verkerk et al., 2009).

The energy efficiency ratio, which is the relation of energy used along the production chain (e.g. harvesting, forwarding and transport) to the final heat consumed (input to output), of the studied chains were notably different. The P Chain required about 35%, the PE Chain 16% (pellet and wood chip production), and the PEH Chain only 13% energy input of the heat consumed. The positive energy efficiency ratio of the chains including the chipping (PE and PEH) is mainly because the necessary energy input to produce wood chips is relatively lower compared with the energy-intensive pellet production. Fig. 2 illustrates that the energy use (e.g. diesel consumption in transportation and harvesting process) is almost the same for all chains, whereas the heat generation increases.

Figure 2.

 Results of the energy use, generation and consumption of the different chains in TJ. The energy use is similar for all chains; the heat generation is more than three times higher in the PEH as in the P Chain. The difference between heat generation and heat consumption represents the energy loss of the heating system (efficiency of heating systems). P Chain, Pellet Chain; PEH Chain, Pellet, Energy Wood and Harvesting Residues Chain; PE Chain, the Pellet and Energy Wood Chain.

Wihersaari (Wihersaari, 2005b) has reported values from 1.9% to 2.6% energy use of the total energy output for typical fuel chip production chains in Finland. In this study, the coefficient for the wood chip production only was in the similar range with 4.0% for the PE Chain and 3.5% for the PEH Chain, i.e. energy efficiency ratio excluding pellet production.

The Pine timber conversion at sawmill and the process Pellet production both have high-energy consumption. The energy in both processes is mainly needed for the drying of the wood and running of the machines (saws, pellet mill). The sawmilling process consumes 1.3 TJ (result allocated to pellets only) and the pellet production about 0.8 TJ energy (electricity), which accounts together for approximately 90% of the total energy use of the P Chain.

In total, for both combined chains the emitted GHG increase significantly; however, the more relevant emissions per unit of heat consumed decreased, as the increase of heat produced and consumed was disproportionately larger. The reason for the relatively high emissions of the P Chain mirrors the high energy use that was discussed above. However, the major part of the energy generation in the sawmill derived from wood residues in the own heating plant, and that energy was counted as CO2 neutral. Important sources of emissions were also the numerous transport processes, as the average transportation distance from the pellet mill to the customer is 170 km.

It should be noted that due to their different characteristics [i.e. stable/low moisture content and high specific density (kg/m3)] pellets serve different purposes in the energy markets than wood chips. A major advantage of pellets is the fact that they can be easily transported and offered to international markets, which is not feasible with wood chips. The transportation of wood chips is very costly due to their low density; in addition, moist chips usually start to degrade if they need to be stored for a considerable time, resulting in material losses and a decrease of fuel quality (Nurmi, 1999; Wihersaari, 2005a). The technical drying of wood chips is not feasible. Therefore wood chip markets are limited to the local and regional scale. Furthermore district heating networks are only cost efficient, if the distance between the objects connected to the heating network is relatively small. Remote single households, however, could be heated with pellets.

In Sweden district heating systems have been recognized as an effective means of reducing CO2 emissions, when compared with the electrically heated houses and competitive with pellet boiler systems when the district heating is based on biomass (Joelsson & Gustavsson, 2008). It can be questioned, however, if direct burning of sawmilling residues is environmentally the best option. It has been argued that the residues should be better used first as wood product (e.g. as chipboard in the construction sector) and burned afterwards (cf. Cowie & David Gardner, 2007). The carbon mitigation effect is considerably larger, if wood is used to replace e.g. concrete as building material than if the wood is used directly as biofuel (Sathre & Gustavsson, 2006).

Intensified biomass extraction for the energy production decreases the biomass carbon stock left in the forest. In this study, this decrease was estimated based on the model results of Palosuo et al. (2008) to be about 10% of the extracted amount, which for the PEH Chain meant 65 t of carbon less than for the P Chain (total biomass remaining in the forest stand). However, if we compare this figure with the amount of the avoided emissions (290 t of carbon when calculating only the direct CO2 emissions from burning coal to produce the same additional amount of energy), we notice that the total effect of this decreased carbon stock in forest was only about 15% of the avoided emissions. Thus, from a climate retention point of view, the combined chain (PEH) can be seen as more favourable than the P Chain combined with fossil energy sources to cover the additional energy produced in the PEH Chain.

The nutrients extracted by conventional thinnings and/or final cuttings to remove sawlogs and pulpwood do not lead to significant increment losses and are thus of minor importance compared with the biomass extraction performed in the PE Chain and PEH Chain (cf. Sverdrup & Rosen, 1998). As a consequence of biomass extraction there may be a decrease in the forest growth in the long-term, depending on the particular forest soils (Samuelsson, 2002; Egnell & Valinger, 2003; Powers et al., 2005; Richardson, 2006; Stupak et al., 2007). Therefore, fertilization to compensate for nutrient losses is recommended if a greater part of the needles are extracted (cf. recommendations for the extractions of forest fuel by the National Board of Forestry in Sweden in 2002 (Skogsstyrelsen). However, the need for fertilization is very much dependent on the existing supply of nutrients in the soil. In nitrogen-rich forest lands, the extraction might even have a positive effect on fresh water biogeochemistry due to reduced nitrogen induced acidification (Samuelsson, 2002). In our reference region these conditions are rather rare, therefore compensation fertilizing ought to be carried out especially when biomass extractions might occur more than once during the rotation period. It should also be noted that application of fertilizer to compensate for nutrient losses has additional impacts on sustainability (e.g. biodiversity) that has not been considered in this study (see e.g. Karltun et al., 2008). Soil nutrition is thus one of the key constraints to consider when assessing the sustainability of the intensified biomass extraction from forests (Raulund-Rasmussen et al., 2008).

The transport indicator Transport has a direct effect on other indicators like energy use, costs and GHG emissions. In particular with longer transport distance or larger freight related to utilization of wood chip for heat production, the energy use, costs and GHG emissions increase steadily as was shown in the sensitivity analysis. Because of the high specific density of pellets, sustainability indicator results of the P chain were less sensitive to changes in the transport distance than in the combined chains. Within this analysis, the average distance for wood chip transport to the district heating plant was one of the key factors influencing the sustainability impacts, affecting especially GHG emissions and energy use. The sustainability of a district heating system is thus strongly influenced by the availability of sufficient regional biomass resources.

In principle, the PEH Chain was the most favourable in terms of costs, employment, energy use and GHG emissions; however it results in a decreased amount of carbon and nutrients in the soil.

Evaluation of the results and the method

The results of this study demonstrate large sustainability impacts of the additional removal of forest-based biomass for domestic heating. For most indicators the differences between the alternative BPCs were clear. However, it should be noted, that the results are case-specific and account only for this very restricted group of heat consumers. The definition of system boundaries, the set up of the BPCs and other assumptions affect the indicator results. More general information can be reached for example by identifying those assumptions for which the results are most sensitive (Table 7). In our sensitivity study for two variables (moisture content of wood chips and transport distance), we noted that their effect on most of the indicators was minor. The moisture content of the chips and transport distance both mainly affected the transport indicator, GHG emissions and energy use.

We have shed light on selected sustainability impacts of increased utilization of forest biomass for energy purposes using separate indicators. Based on these results, it is difficult to rank overall sustainability of the BPCs. That could be done applying methods such as the multicriteria analysis (Kangas & Kangas, 2005) or cost–benefit analysis (Nas, 1996), which was beyond the scope of this study.

The sawmill process was detected to be a hot spot of energy use in the pellet production. If a value-based allocation would have been selected instead of the carbon-mass-based allocation to differentiate the impacts due to energy production from the impacts due to sawlogs or pulpwood, the impacts reported for different BPCs would be partially different. Value-based allocation typically gives only minor weight to the subproducts (see e.g. Dove & Boustead, 1998). The relative changes between the P Chain and the PE or PEH Chain would have been stronger, as less sustainability impacts of the harvesting, forwarding, transport and sawmilling would have been allocated to the pellet production. However, the value-based allocation has major disadvantages, as the economic values are dependent on the prevailing conditions at markets and are therefore highly variable. Also, the relative prices among different product groups of forest products can vary quite considerably as recently documented in the fluctuations of the energy wood prices vs. pulpwood prices (see e.g. Hawkings, 2009). The relative order of impacts between BPCs, however, would remain unchanged when selecting a different allocation criterion.

The results of the SIA analysis are also dependent on the selection of indicators. Indicators should be closely related to goals and objectives set for the activities being examined. The three dimensions of sustainability – economic, social and environmental – are widely used as a basis for indicator selection.

Many other relevant sustainability aspects can be assessed with criteria and indicators (Hall, 2001, Howell et al., 2008, Rametsteiner et al., 2008). But it should be recognized that SIA as applied in this study requires considerable amounts of data. Data availability may limit the choice of suitable indicators for the assessment. Further challenges are data handling as well as assuring data quality and consistency. Experience shows that providing complete indicator data often requires making some additional assumptions that add uncertainty to the results. Nevertheless, the policy targets to consider sustainable development in all economic activities (European Commission, 2005; Tscherning et al., 2008) created a need for science-based knowledge in the field of SIA. This study provided a quantified SIA of typical forest biomass utilization for energy production in Scandinavia. More studies are needed to accumulate reference data for a broader range of resource management conditions, covering other forest types, other biomass sources (e.g. stumps), different regions, and comparisons with nonwood bioenergy chains (cf. Sheehan, 2009). Furthermore, a comparison with a fossil fuel chain would be of interest. However, such a comparison is not currently feasible with the chosen tool, as ToSIA has so far only been tested for biomass-based supply chains.

Conclusions

It can be concluded that the extraction and chipping of biomass for heat production in addition to the production of pellets for domestic heating has significant socio-economic, but also environmental advantages on sustainability. The employment effect of about 0.6 person-years 1000 m−3 and the substitution of fossil fuels creates added value relevant for rural areas. The short transport distances of the resources used and the distribution of the heat over the clean-exhaust district heating network give this additional utilization of forest resources an advantage. Especially the results related to the energy efficiency ratio of the chipping shows the benefits of the utilization of wood for energy purposes in comparison to other renewables. With an energy efficiency ratio of 1–24 of the additional chipping chain, energy derived from forests proves to be an outstanding source of energy. Furthermore, it does not compete with food production nor does it have other negative effects (e.g. intensification of farming, changing landscapes) as does bioenergy derived from agricultural land (Tilman et al., 2009).

On the other hand, possible negative impacts on sustainability were detected in the issues of losses of nutrient and the consequent risk of degradation of the forest stand. In order to compensate for nutrient losses, already poor soils should be treated with fertilizer. Furthermore, there is still little experience of the impacts on biodiversity of this recent, but rapidly growing, use of biomass. The effects of the decreasing amounts of dead wood created by the decaying cut biomass left in the forest stand on forest biodiversity should be studied further.

The applied approach to study the impacts of the increased utilization of forest biomass on the selected indicator highlights different aspects of sustainability of the BPCs. Using science-based knowledge can support the further implementation of sustainable development in the forest-based sector.

Acknowledgements

This work was funded by the European Commission (FP6) through the EFORWOOD project (Project no. 518128).

We are grateful to Staffan Berg (Sweden) and Jarmo Säkkinen (Metsäliitto) for contributing data for the analysis and thank Tim Green for checking the English language.

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