Quantifying the climate effects of forest-based bioenergy

Quantifying the climate effects of forest-based bioenergy

13

Annette L. Cowie*,†,1, Miguel Branda˜o†,‡, Sampo Soimakallio†,§ *NSW Department of Primary Industries/School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia, †International Energy Agency (IEA) Bioenergy Task 38, ‡KTH—Royal Institute of Technology, Stockholm, Sweden, §Finnish Environment Institute (SYKE), Helsinki, Finland 1 Corresponding author: [email protected]

Chapter Outline 13.1 13.2 13.3 13.4 13.5

Introduction 399 The forest carbon cycle 400 The bioenergy life cycle 400 Forest bioenergy as a coproduct of forestry 401 Factors to consider in quantifying the climate effects of forest bioenergy

403

13.5.1 Life cycle perspective 403 13.5.2 Reference system 406 13.5.3 Land-use reference 406 13.5.4 Energy source displaced 406 13.5.5 Displacement value 407 13.5.6 Handling coproducts 407 13.5.7 Spatial boundary 407 13.5.8 GHGs and other climate forcers 408 13.5.9 Non-GHG climate forcers 408 13.5.10 Timing of emissions and removals 408 13.5.11 Metrics for climate change impact assessment 409 13.5.12 Temporal boundary of assessment 410 13.5.13 Indirect effects 411

13.6 Summary of recommendations 13.7 Conclusions 414 Acknowledgments 414 References 414

13.1

413

Introduction

Bioenergy has been promoted as a component of climate change and renewable energy policies in many countries. However, over recent years, the climate benefits of bioenergy systems have been increasingly questioned. Concern over the Managing Global Warming. https://doi.org/10.1016/B978-0-12-814104-5.00013-2 Copyright © 2019 Elsevier Inc. All rights reserved.

400

Managing Global Warming

effectiveness of agricultural bioenergy for climate change mitigation is mainly related to indirect land-use change (ILUC), the use of agrochemicals and loss of soil organic matter (e.g., [1,2]), while forest-based bioenergy has been challenged with claims that carbon losses from removal of biomass for energy from existing forests create a “carbon debt” (e.g., [3,4]). Some studies have suggested that the magnitude of the carbon loss may, in some circumstances, be so large that the payback period lasts several decades (e.g., [5,6]). Other studies demonstrate cases in which the initial carbon loss, if any, may be paid back after a few years of displacing fossil fuels (e.g., [7,8]). These widely divergent results present a confusing picture for policy makers and the energy industry. This chapter discusses the key issues in quantifying the climate effects of forest-based bioenergy and reasons for divergent results. We discuss the sensitivity of results to the selection of spatial and temporal boundaries, and the handling of coproduction of wood products and bioenergy. We consider how to include the timing of greenhouse gas (GHG) emissions and carbon sequestration in the assessment of the climate change impacts of forest-based bioenergy. Furthermore, the role of case-specific factors, non-GHG climate forcers, and the choice of metrics to measure climate impacts are considered. Finally, we provide recommendations to guide climate impact assessment of forest-based bioenergy. Our emphasis is on forest biomass used for combustion to produce electricity and/or heat, but the same principles apply to biomass used for other energy applications (liquid biofuels, gaseous fuels).

13.2

The forest carbon cycle

Sustainable bioenergy systems are commonly said to be carbon neutral because the carbon that is released during combustion had previously been sequestered from the atmosphere and will be sequestered again as the biomass is regrown. Forest biomass systems are effectively carbon neutral over time (leaving aside supply-chain emissions) if the forest sequesters the same amount of carbon in the following rotation as was released, so that the long-term average carbon stock remains constant. If the cycle of growth and harvest is sustained, biomass combustion simply returns to the atmosphere the CO2 that was absorbed as the plants grew, and there is no net release of CO2 from the forest. This is fundamentally different from the use of fossil fuels: burning fossil fuels releases CO2 that has been locked up for millions of years. It takes carbon that was securely stored in geological formations and adds it to the atmosphere. During human-relevant time scales, there is no significant geological sequestration of carbon from the atmosphere through natural processes.

13.3

The bioenergy life cycle

To understand the climate impacts of bioenergy, the full life cycle of the bioenergy system should be considered: the biomass procurement (e.g., growth and harvest in the forest), as well as the conversion to energy products, supply-chain emissions that arise from transport and processing [9]. Construction and demolition of facilities

Quantifying the climate effects of forest-based bioenergy

401

should also be included where applicable, e.g., establishment of forest roads and power distribution infrastructure. Fossil carbon emissions from forest-based bioenergy supply chains are typically a small percentage of the fossil GHG emissions displaced because supply-chain energy use is low [7,10,11], even where international transport is involved [12–14]. The climate impacts of bioenergy systems are mainly related to how the forest carbon cycle is affected by bioenergy, how efficiently biomass is used to create energy products, and the GHG intensity of the energy product displaced. These factors are discussed as follows.

13.4

Forest bioenergy as a coproduct of forestry

It is important to recognize that industrial forest bioenergy is commonly a coproduct of the forest industry, associated with the production of wood products (sawn timber, composite products, and paper). A large share of that energy, e.g., black liquor is used by the forest industry in wood processing. Additional biomass for energy may be derived from harvest slash (e.g., branches, tops, stumps) that would otherwise have decayed in the forest, or it may be obtained from surplus mill residues (saw dust, shavings, etc.) or construction waste. End-of-life wood products are also a possible source of biomass for energy, after using wood products to displace GHG-intensive building materials. Biomass for energy tends to be a low-value product compared with other forest products, and thus has traditionally not been the primary driver in determining forest management and harvest scheduling. Therefore, it is important to consider bioenergy from managed forests within the context of the forest products markets. On the other hand, ambitious targets and mandates to increase the use of bioenergy and various types of subsidies could make the direct use of low-quality roundwood for energy more common. When considered from a single-stand perspective, forest carbon stocks range widely between young and mature stages (Fig. 13.1A). However, a forest estate generally comprises a series of stands of different ages, harvested at different times, to produce a constant supply of logs. Therefore, in an ideal “normal” forest, when viewed across the estate, the carbon losses at harvest are balanced by gains in the growing stands, and the variations in C stock observed at stand level are smoothed out, so carbon stock of the whole forest is stable (Fig. 13.1B). The average carbon stock across the estate reflects the net effects of forest growth (influenced by climate and soil), forest management (that is, site preparation, planting, fertilizing, thinning, pruning, and harvesting), and natural disturbances such as fire, windthrow, and insect outbreaks. A key aspect governing the climate effect of bioenergy is the change (if any) in average carbon stock across the whole forest landscape resulting from forest bioenergy production. When a new harvest regime is introduced, this will be imposed sequentially as each stand is harvested. If the average carbon stock is different under the new regime, a new equilibrium will be reached after one rotation period. While a new forest management regime that extracts more biomass for bioenergy could reduce the carbon stock in the forest, this “GHG cost” (see Fig. 13.1) can be minimized by

402

Managing Global Warming Green: harvested for timber + bioenergy. Enhanced management after harvest increases C stock above original forest management (blue)

Single stand Blue: Reference, harvested for timber only

GHG cost Average C stock green stand

C stock Average C stock blue stand Average C stock red stand Red: harvested for timber + bioenergy. C stock reduced throughout the rotation compared with blue stand

ΔC: Additional biomass (residues) ΔC harvested for bioenergy. Decays on site in reference case.

T0

T1

T2

Time T3

(A) Landscape scale: Carbon stocks stable Purple: Enhanced forest management outweighs the effect of increased biomass removal

C stock

GHG cost (red cf blue) T0

T1

T2

Time T3

(B) Landscape scale: Carbon stocks increasing

Enhanced C sequestration

C stock Foregone C sequestration

(C)

T0

T1

T2

Time T3

Fig. 13.1 These graphs shows simplified representations of the carbon stocks in a managed forest. They do not show changes in rotation period nor do they show the carbon stock fluctuations around these simplified curves caused by climate variation and forest operations such as thinning. (A) shows the carbon stock (sum of carbon in trees, soil, and litter) of an individual stand, over successive rotations. The blue curve shows the reference scenario, a forest harvested for timber only. The other curves show two alternative scenarios, in which harvest residues (branches and tops), usually left in the forest, are removed for bioenergy at harvest, at time T1 and each successive harvest. The concept of “GHG cost” is illustrated in the red curve: the average carbon stocks are lower compared with the blue stand, due to removal of harvest residues, and, possibly, flow-on effects on soil carbon stocks and forest growth rate. In practice, the GHG cost also includes emissions from any fossil fuel used in the feedstock production, transport, and processing. The green curve illustrates how enhanced forest management can reduce the GHG cost. (B) and (C) show the total carbon stocks summed across a landscape of multiple stands at different stages in the rotation cycle, assuming that all stands follow either the blue, red, or green curves from (A). In reality, the forest carbon stock on the landscape level will reflect a mix of different management approaches applied to different stands, which may include adjustment to the rotation period. An additional curve, in purple, shows a scenario where changes in forest management across the forest landscape outweigh the effect of increased biomass removal for bioenergy, so that the forest carbon stock increases on landscape level.

Quantifying the climate effects of forest-based bioenergy

403

management practices that enhance growth and thus accelerate C uptake, such as improved site preparation, superior genetic material, and forest fertilization (illustrated by the purple curves in Fig. 13.1B and C). Where there is an increased demand for bioenergy and forest products, forest managers may choose to invest in intensified forest management to enhance growth rates and modify harvest schedules to produce more biomass, which may increase or decrease total forest carbon stocks compared to the case without bioenergy demand. Therefore, a key issue influencing the climate impact of bioenergy is management changes introduced to provide biomass for bioenergy in addition to other forest products, and the consequential impacts on forest carbon stock.

13.5

Factors to consider in quantifying the climate effects of forest bioenergy

Estimating the climate effects of bioenergy systems robustly is fraught with difficulties. To quantify the climate effects of bioenergy, it is critical to apply an approach that considers the whole bioenergy system including multiple life cycle stages, and all relevant climate forcers; is normalized to a functional unit that can be compared with other systems delivering and equivalent quantity of the same function; applies appropriate reference systems and system boundary, consistent with the goal and scope of the study; handles coproducts, and appropriate impact assessment metrics, as detailed here.

13.5.1 Life cycle perspective The assessment should consider the whole life cycle of the bioenergy system, using life cycle assessment (LCA) over the temporal scope determined (see Box 13.1). Unlike national GHG emission reporting and accounting (Box 13.2), which focuses on annual emissions and removals, LCA, as indicated by the name, considers the entire life cycle of a system studied (a product or service). The assessment should (C) shows a situation where the carbon stocks across the landscape are increasing, such as where the national estate is dominated by young stands; over time, the total carbon stocks increase as these stands mature. Although the total stocks continue to increase in all scenarios in (C), biomass removal can lead to “forgone sequestration” (red curve), though this can be reduced or avoided through enhanced forest management (green and purple curves). Note that the net GHG-mitigation potential of associated bioenergy systems also depends on the GHG displacement efficiency; i.e., a bioenergy system that is associated with declining forest carbon stocks (red curve) can deliver higher GHG mitigation than another bioenergy system that is associated with increasing forest carbon stocks (green or purple curves) if the latter has much lower GHG displacement efficiency. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) Source: Cowie A, Berndes G, Smith CT. On the timing of greenhouse gas mitigation benefits of forest-based bioenergy, IEA Bioenergy Executive Committee 2013. Available from http:// www.ieabioenergy.com/wp-content/uploads/2013/10/On-the-Timing-of-Greenhouse-GasMitigation-Benefits-of-Forest-Based-Bioenergy.pdf.

404

Managing Global Warming

Box 13.1 Life cycle assessment Life cycle assessment (LCA) is a framework for assessing the environmental impacts of product systems and decisions. The steps in LCA are (1) goal and scope definition, (2) life cycle inventory analysis (LCI), (3) life cycle impact assessment (LCIA), and (4) interpretation of the results. The results of LCA are expressed per functional unit (e.g., one MJ of bioenergy; 1 km driven by standard passenger vehicle under standard conditions). Due to the flexibility of the framework, LCA is suitable for small and large-scale product systems, and can be used to aid micro- and macro-level decisions [15]. LCA has been categorized into two main modeling techniques, namely, attributional LCA (ALCA) and consequential LCA (CLCA). Several definitions for ALCA and CLCA have been proposed and both methods have been applied differently between different studies [16,17]. The “Shonan Guidance Principles” [18] (pp. 132–133) state that ALCA is a “system modelling approach in which inputs and outputs are attributed to the functional unit of a product system by linking and/or partitioning the unit processes of the system according to a normative rule.” Conversely, CLCA is a “system modelling approach in which activities in a product system are linked so that activities are included in the product system to the extent that they are expected to change as a consequence of a change in demand for the functional unit” [18]. ALCA focuses on describing all the environmentally-relevant physical flows to and from a product system over its life cycle [19,20]. In contrast, CLCA aims to describe how environmentally relevant physical flows would respond (or would have responded) to a change [19], e.g. a decision to increase production of forest bioenergy. Essentially, ALCA aims to describe the environmental impacts of a system as a component of the total impact of human activities, whereas CLCA aims to answer the question “what happens if?”. Typically, average data are applied in ALCA, whereas marginal or incremental data are applied in CLCA [19]. Where a product is derived from a system with several outputs or functions, a method must be used to share the impacts among the products. Allocation based on an attribute such as energy content, mass, or value is used in ALCA as the basis for sharing impacts, whereas allocation is avoided in CLCA by giving credit to the product for products displaced by the co-product. Regardless of the modeling approach chosen, LCA fundamentally aims to describe the environmental impacts of a studied system. However, the system boundaries and other methodological choices, such as allocation and metrics applied in LCIA, vary depending on the goal and scope of the study.

Quantifying the climate effects of forest-based bioenergy

405

Box 13.2 Bioenergy in national greenhouse gas inventories The Intergovernmental Panel on Climate Change (IPCC) develops the methods that are used by countries for their reporting under the UNFCCC and accounting under the Kyoto Protocol. The scope of these reports is annual greenhouse gas emissions and removals at national level. According to the IPCC guidelines for national GHG emission reporting, CO2 emissions from the combustion of biomass are counted as zero in the Energy sector [28]. This is to avoid double counting, because CO2 emissions from the harvest of forest biomass for energy are included in the Agriculture, Forestry and Other Land-Use (AFOLU) sector. (Formerly the emissions and removals from forestry were reported in the Land Use Land Use Change and Forestry (LULUCF) sector, which was separate from the Agriculture sector. These two sectors are now combined in the AFOLU sector.) Consequently, if all countries follow the IPCC guidelines and report to the UNFCCC, all emissions from the use of biomass for energy will be estimated and reported [29]. However, under the Kyoto Protocol to the UNFCCC only developed (“Annex I”) countries have commitments, and are required to account for their emissions against agreed targets. Developing countries do not have commitments, and any decline in forest carbon associated with harvest for biomass that is exported to Annex 1 countries from non-Annex 1 countries is excluded from accounting. Furthermore, reporting changes in forest carbon stock was optional for Annex I countries in the first commitment period (2008–12), so forest carbon losses from biomass harvest in Annex I countries were not accounted for by most countries. There was limited incentive to enhance forest carbon stocks due to national caps on forest sinks. These deficiencies have been partly addressed in the second commitment period of the Kyoto Protocol (2013–20), as accounting for “forest management” is now mandatory for Annex 1 countries. However, forest management emissions and removals are accounted relative to country-specific, projected reference levels representing the “business as usual” baseline. Consequently, harvesting of biomass may or may not create a debit, depending on the overall development of C stock and the agreed “forest management reference level.” It should be noted that not all developed countries are committed to the Kyoto Protocol and that the commitments have been defined only until 2020. The Paris Agreement, negotiated in 2015, will commence in 2020, and will cover developing and well as developed countries, so the loopholes noted here associated with incomplete coverage will be largely overcome. However, the rules for forests and bioenergy under the Paris Agreement have yet to be determined. The approach selected will influence the contribution of bioenergy to future targets for emissions reduction, and the incentives for bioenergy and forest sinks.

406

Managing Global Warming

include, as applicable, GHG emissions and removals related to raw material production, harvesting, transportation, biomass storage and conversion, and final fuel storage, distribution and use. Different amounts and types of fossil fuels and other inputs, such as fertilizers and processing chemicals, are used in different bioenergy systems, depending on the biomass source, energy conversion process, and product produced (i.e., heat, electricity, liquid biofuel). In addition, biomass harvesting influences forest carbon stocks, surface albedo properties, and possibly cloud formation and reflectivity. Biomass storage may cause process emissions.

13.5.2 Reference system To determine the climate change effects of bioenergy, the bioenergy system must be compared with a reference system. The choice of the “without bioenergy” reference scenario (or counterfactual), against which the bioenergy scenario is evaluated, is critical to the results. For forest-based bioenergy, the reference scenario should describe the alternative use of the forest, as well as the alternative energy source that is displaced by the bioenergy system.

13.5.3 Land-use reference Comparison with the reference land use allows the inclusion of impacts of change in land use or land management on C stock in biomass and soil. As with the bioenergy system, it is important to consider both management and natural factors in describing the forest carbon stocks in the reference system. This reference scenario may include forest management for a different mix of products and services, or preserving the forest for conservation. In assessing forgone sequestration, it should be recognized that sequestration rate slows as forests approach maturity, and that forests managed for conservation alone may have increased risk of disturbance, such as wildfire [21]. Due to uncertainties, especially those related to future systems, it may be relevant to consider several alternative reference land-use scenarios. The relevant reference land use will be determined by the purpose of the analysis. If the goal is to quantify the contribution of bioenergy as a component of all human activities (attributional approach—see Box 13.1), natural regeneration may be the appropriate reference, whereas if the goal is to estimate the effect of increasing production of bioenergy (consequential approach), the “most likely alternative” land use may be most suitable [22].

13.5.4 Energy source displaced The reference energy scenario should describe the energy source serving the equal function in the absence of bioenergy. Coal has a higher GHG intensity than natural gas, so displacing coal achieves greater GHG savings than displacing the same energy content of natural gas. In the attributional approach, the GHG intensity of the average electricity mix is typically used (e.g., [23]), but in the consequential approach the relevant reference energy source is the marginal supply that would be used if the

Quantifying the climate effects of forest-based bioenergy

407

bioenergy was not produced, that is, the source(s) that would respond to increases in demand for electricity. In some cases, the marginal supply could be another renewable energy source.

13.5.5 Displacement value The mitigation value of displacement will depend on the relative efficiency of conversion to energy product in the bioenergy and reference system, and the relative GHG emitted per MJ of energy product. The displacement value is often less than one because more CO2 is emitted per MJ from biomass compared with coal or gas, due to the difference in chemical composition. This does not necessarily mean that biomass is worse than coal, as some have claimed (e.g., [24]). The difference in climate change effect of bioenergy and fossil energy can only be determined by comparing the bioenergy system with the reference system, considering all the aspects listed here. The conversion efficiency of biomass to bioenergy greatly affects the climate effect. For example, conversion of biomass to bioliquids, while increasing the energy density and improving ease of transport and storage, is often less efficient than direct combustion of biomass for heat or power [25,26]. However, the actual displacement effect is determined by market-mediated forces - see indirect effects, later.

13.5.6 Handling coproducts As discussed earlier, bioenergy is often just one product from a managed forest. Biomass for bioenergy is typically a residue, while the high value sawlogs and pulp wood are the main drivers of management decisions, such as rotation length, stocking rate, and fertilizer regime. Coproducts from the multioutput system may displace other products, generating additional mitigation compared to a situation in which wood was not harvested [27]. For example, when biomass is pyrolyzed or gasified, a solid coproduct (biochar) is generated in parallel, which may be used as a soil amendment, thereby reducing fertilizer requirements. The avoided emissions from fertilizer manufacture can be credited to the bioenergy system.

13.5.7 Spatial boundary The spatial boundary is defined by the goal and scope, and can affect the results dramatically. In the case of long-rotation forestry, the regrowth phase may take many decades. The asynchrony between carbon emissions and sequestration, when considered on the basis of a single stand, has led to concerns that bioenergy does not necessarily deliver climate benefits in the short term: during the period between combustion and regrowth there is additional CO2 in the atmosphere, causing a warming effect. However, this single-stand perspective does not necessarily provide adequate understanding of the climate effects of a new policy to promote forest bioenergy.

408

Managing Global Warming

The appropriate boundaries of the assessment are determined by the purpose of the investigation. For example, a policy maker may be concerned with the impacts at a regional or national scale, so assessments to inform policy development should take place at that broad scale. On the other hand, an individual forest owner may be interested in knowing the effects at the estate level. When the assessment is undertaken for the purpose of product labeling, the scale of analysis applies to the system that produces that product.

13.5.8 GHGs and other climate forcers All climate forcers, such as albedo effects and emissions and removals of greenhouse gases, including CO2 and non-CO2 (e.g., CH4 from stored biomass, N2O from soil), should be included across the whole life cycle.

13.5.9 Non-GHG climate forcers Change in albedo (reflectance) from the land surface, which impacts energy balance, should be included in the assessment. In addition to the impact from emissions and sequestration of GHGs, bioenergy systems can affect climate through additional forcing processes, including direct impact on albedo (e.g., [30,31]). Harvest of forests in high latitudes or altitudes with snow cover can increase albedo, reducing global warming [32]. In some circumstances this effect is substantial, even counteracting negative impacts of a reduction in forest carbon stock [33]. However, according to [34], boreal forests double regional cloud condensation nuclei concentrations through emission of organic vapors and the resulting condensational growth of newly formed particles, having a significant cooling impact. Thus, harvesting of boreal forests reduces this cooling impact (thereby increasing warming), which compensates partly or completely the cooling impact of increased surface albedo. It should be noted that there are substantial knowledge gaps and uncertainties related to the complex interrelations between biogeochemical and physical climate forcings of forestry [34–36] . Bioenergy systems may also influence climate through emissions of aerosols, or black carbon, in different ways, depending on the technologies and scenarios considered [37].

13.5.10 Timing of emissions and removals Conventionally, in LCA, the timing of emissions and removals is not considered: the carbon footprint of a product is calculated by summing the emissions over the entire life cycle (e.g., [23]). The implication is that timing of emissions and removals has no impact on climate change outcomes. In contrast, many current climate change policies provide incentives to delay emissions or sequester carbon temporarily (such as for 100 years). Such policies could “buy time” that could allow society to develop and deploy low-carbon energy systems, and they could assist in avoiding “climate tipping points.” However, the timing and irreversibility of such tipping points are uncertain [38], and the climate impacts from delayed emissions may be problematic at later

Quantifying the climate effects of forest-based bioenergy

409

point in time. Some protocols acknowledge that time is significant, and therefore exclude emissions occurring after more than 100 years, or quantify such long-term emissions in a separate category (e.g., [39]). Furthermore, to achieve equilibrium temperature targets, the exact timing of CO2 emissions and removals may not be the most important consideration; rather, to mitigate climate change the most important action is to restrict the cumulative total GHG emissions in the longer term [38]. The more ambitious is the stabilization target (e.g., 1.5°C temperature increase), the deeper emission cuts are required [38]. Higher CO2 emissions in earlier decades require lower CO2 emissions later [38]. However, in the real world, the short- and long-term impacts are not typically independent from each other, due to relatively long economic lifetime of energy system structures [40]. Consequently, it is likely that achieving a 2°C target in practice will require CO2 emissions to peak very soon, with deep cuts in emissions in the following decades [38,40]. Furthermore, as the climate sensitivity to the increasing GHG concentrations is not well known, the hedging of climate sensitivity risk calls for deeper early reductions instead of postponing reduction measures [41]. When assessing the effectiveness of bioenergy in climate change mitigation, the timing of the CO2 emissions and C sequestration matters, depending on the given target and the resulting emission reduction window. For example, a forest bioenergy system causing more emissions than a fossil reference fuel in the beginning should possibly provide negative net emissions within the end of this century, in order to efficiently work in achieving the 2°C target (see Fig. 12.46a in [38]). Berndes et al. [42] proposed “GHG emissions space” as a concept to encourage consideration of emissions management in the context of longer-term temperature targets. Focusing on the accumulated emissions up to a given year, society may decide to invest a portion of the emission space, allowed within the GHG target, on the establishment of renewable energy systems. Short-term emissions resulting from the establishment of bioenergy systems may be justified as investment in creating a low-carbon energy system. However, it should be noted that if a bioenergy system does not provide enough emission reductions within the given temporal window, which depends on the given climate change mitigation target, the “invested emissions” will need to be counteracted by other means. This may be difficult, especially considering the ambitious stabilization targets, which require that emissions from the whole society must be cut sharply within the upcoming decades.

13.5.11 Metrics for climate change impact assessment When a pulse of CO2 is emitted to the atmosphere a fraction of the CO2 is taken up by the biosphere, some is dissolved in the ocean, and a fraction (15%–40%) remains in the atmosphere for up to 2000 years [43]. The climate effect of a pulse emission is quantified as the radiative forcing due to the perturbation. The commonly applied metric Global Warming Potential (GWP) quantifies the radiative forcing (extra energy retained) of a GHG pulse emission over a specified time period (commonly 100 years) in comparison with that of a pulse of CO2 emitted at time zero.

410

Managing Global Warming

Usually in LCA the GWP (100 years) is applied to calculate the CO2 equivalent (CO2-eq.) of non-CO2 GHGs, and the climate effect is quantified as the total of GHG emissions and removals over the entire life cycle (e.g., [23]) or over the first 100 years of the life cycle of a product (e.g., [39]). Several authors have proposed alternative methods for estimating potential climate impacts of GHG emissions, for application in LCA that do account for the timing of GHG emissions and removals [44]. Clift and Branda˜o [45] developed the method adopted in the first version of the UK’s carbon footprint guideline Publicly Available Specification for the assessment of the life cycle greenhouse gas emissions of goods and services “PAS2050” [46]. Two subsequently published approaches, Levasseur et al. [47] and Cherubini et al. [48], are essentially equivalent to that of Clift and Branda˜o [45]. Levasseur et al. [47] developed the “dynamic LCA” approach, which quantifies the radiative forcing resulting from an emission according to when it occurs within a defined assessment period, and assigns a reduced impact if emissions are delayed within this period. Cherubini et al. [48] proposed and Guest et al. [49] demonstrated a method, which quantifies the radiative forcing over the assessment period due to the combined effects of a pulse emission from combustion of biomass, followed by CO2 removal due to the presumed regrowth. They apply a modified characterization factor “GWPbio” that reflects this temporal profile of radiative forcing in comparison with a pulse emission of fossil CO2, and varies with rotation length of the forest system. It should be noted that this metric does not aim to capture the forest carbon stock change between a bioenergy production scenario compared to a forest reference scenario without the studied bioenergy production, but rather it quantifies the climate effects of actual carbon emissions and the assumed subsequent sequestration. Thus, Pingoud et al. [50] extended the “GWPbio” concept to produce a metric that assesses the climate impacts in comparison to a reference system that includes the alternative use of the forest. An alternative metric to GWP now gaining traction is the global temperature potential (GTP), which quantifies the effect of GHG emissions on the global temperature at a specified time [51]. GTP is thus more closely related than GWP to the impact of climate change on human and natural systems. Cherubini et al. [52] assessed bioenergy systems and demonstrated that long-rotation forest systems show greater climate change mitigation potential when assessed by GTP than by GWP. Furthermore, we should bear in mind that the impact pathway from GHG emissions to climate impacts goes through emissions, increased atmospheric concentrations, radiative forcing, temperature increase, and other impacts (such as storms, droughts). Choosing the appropriate metrics depends finally on the goal and scope of the study. There is no one metric that gives the complete picture; thus, it may be relevant to apply several metrics to improve understanding of the factors that influence the outcomes, and the sensitivity of results to alternative metrics. GWP (100 years) is still widely used in policy frameworks, but it is worth recognizing that the preferred metrics might change.

13.5.12 Temporal boundary of assessment Typically, in LCA, the assessment starts at the “cradle,” which commonly includes raw material extraction. In relation to bioenergy, it is debated whether the time period of assessment should commence when the forest was planted, or at the time of harvest.

Quantifying the climate effects of forest-based bioenergy

411

Fundamentally, this depends on the question posed. If the biomass is produced from reforestation undertaken to meet later bioenergy demand, then the initial removal of CO2 from the atmosphere as the plants grow before first harvest may be included as part of the bioenergy life cycle. In such a case, a decision to afforest can be combined with a decision to harvest. However, what was considered optimal at some point in time (i.e., afforestation followed by harvest) is not necessarily optimal in the future (i.e., although originally planted for future harvest for bioenergy, it may be decided at the point of harvest that retaining the forest gives greater climate and other benefits). Thus, the impacts of the decision to harvest may also be of interest, independent of the prior decision to afforest and subsequently harvest. These two temporal boundaries can result in very different conclusions. If the biomass is extracted from existing forests, choosing the appropriate time horizon for the assessment is challenging: should the assessment start at the time of harvest, or after harvest, for example? If forest management is changed in advance of the first harvest as a consequence of bioenergy demand, then it may be appropriate to start the accounting clock at the time management was changed. An example of such a change is when forest owners choose to skip precommercial thinning in order to produce a larger bioenergy harvest in later thinning operations. On the other hand, it may be difficult to verify for what purpose the forests have previously been managed. Consequently, for existing forests, both the retrospective and prospective perspectives in accounting may be relevant, as for biomass derived from afforestation or reforestation. The relevant temporal boundary depends on the purpose of the assessment. The avoided emissions from fossil fuel substitution increase over time as more biomass displaces more fossil fuel. At the same time, carbon cost resulting from increased harvest of forests typically becomes lower over time. Therefore, the time frame chosen to assess the climate impacts has a significant impact on the results and could even turn around the conclusions drawn.

13.5.13 Indirect effects Comprehensive assessment of the short- and long-term climate effects from expansion of bioenergy systems requires a consequential modeling approach that considers the land, forest products, energy sectors, as well as socioeconomic and biogeophysical effects. This is necessary in the development of policy to inform decisions on appropriate scales of expansion of bioenergy systems and optimal use of biomass for competing energy and material products. As bioenergy and wood products are interrelated industries, a full understanding of the impacts related to forest bioenergy requires understanding also of the impacts related to industrial wood use. A strategic and rationalized cascading use of biomass, first for materials and subsequently for energy, allows for higher GHG benefits through multiple substitutions compared with direct use of newly harvested wood for energy [53,54] (Pingoud et al. 2010, Gustavsson et al. 2006). In addition, GHG savings from substituting other materials by wood materials may be significantly larger than substituting fossil fuels by bioenergy [55,56] . However, the various possibilities of wood use, as well as the complexity of identifying the displaced construction material, make it difficult to generalize the GHG savings from substitution by wood products.

412

Managing Global Warming

If land use on a particular parcel of land changes from food production to production of biomass, including wood for bioenergy, land use elsewhere might change to meet the demand for food. This land-use change elsewhere is known as indirect land-use change, and should be included in the assessment of the impacts of bioenergy. However, estimating ILUC is another methodological issue for which consensus remains elusive among scientists, partly because ILUC, by definition, cannot be verified nor ascribed directly to a bioenergy system. Several methods exist; those based on general or partial equilibrium modeling remain the most popular in a policy-making context, while biophysical models also exist for the same purpose (e.g., Schmidt et al. [57]). The critical question for policymakers should be: will bioenergy incentives facilitate or hinder capacity to stabilize the global climate, preventing warming in excess of 2°C (or 1.5°C)? The answer will depend on how bioenergy incentives affect forest carbon stocks (at the landscape scale), and how they influence fossil-fuel emissions. The impact on forest carbon is location specific, influenced by environmental and socioeconomic factors including forest type, climate, forest ownership, and the character and product portfolio of the associated forest industry. Furthermore, the forest carbon stock response to changes in forest management and harvesting in turn depends on the characteristics of the forest ecosystem. The impact on fossil-fuel emissions will depend on how bioenergy availability impacts on use of fossil fuels. The phenomenon of rebound should be acknowledged: due to impacts of bioenergy on prices of fossil fuels, bioenergy does not necessarily displace the same amount of fossil-fuel energy products [58]. More importantly for long-term climate stabilization, bioenergy incentives may influence investment in fossil-fuel technology and infrastructure. Bioenergy could play an important role in transition to low-carbon energy systems, by providing dispatchable power that can stabilize electricity grids, enabling expansion of other intermittent renewables (solar and wind power). When considering the climate effects of single bioenergy systems in the prevailing or assumed economic conditions, independent from market responses, an attributional modeling perspective may be more appropriate than consequential modeling. In this case, market-mediated effects are excluded (see Box 13.1). Examples of such cases might be the calculation of the carbon footprint of a bioenergy product to assess compliance within a scheme, or to label a product. The results of the assessment can be expressed in different ways (Cherubini et al., 2013). For comparison between energy products, the result is expressed as GHG intensity per functional unit (ISO, 2013). It is often relevant also to consider the change in emissions per unit of biomass resource consumed, or per unit land area. The mitigation value is determined by the net effect of avoided emissions and the “GHG cost.” GHG costs arise from emissions from fossil-fuel use along the supply chain, and any decline in the C stock of the forest due to biomass harvest. If the GHG cost is lower than the fossil-fuel emissions avoided by the bioenergy system, there will be an immediate benefit. This could be the case when forest residues are harvested and effectively used to substitute fossil fuels (e.g., [59,60]). If the forest carbon stock is reduced, there will be a delay until the savings from avoided fossil-fuel emissions lead to a net reduction in atmospheric CO2 (e.g., [3]); and the temporary

Quantifying the climate effects of forest-based bioenergy

413

increase in atmospheric CO2 will cause global warming. This is typically the situation when growing trees are harvested for energy, as harvesting results in the immediate release of C previously stored in trees, and also in forgone C sequestration if trees would have continued to grow [6,59,60]. The overall forest carbon stock may still increase in the bioenergy scenario, but at a slower rate compared to the absence of harvesting for bioenergy; bioenergy is in this case also associated with forgone carbon sequestration, which should be taken into account when evaluating the net GHG effect (e.g., [61,62]).

13.6

Summary of recommendations

It is proposed that, in order to understand the climate change effects of forest-based bioenergy systems, the following approach should be applied: l

l

l

l

l

l

l

l

l

l

l

l

l

l

define precisely the question to be answered; consider bioenergy production in comparison to a reference system in which the assessed bioenergy is not produced; accurately define the reference forest management and energy systems with which bioenergy is compared and consider alternative reference scenarios whenever appropriate (typically there are uncertainties that need to be considered); consider whether stand or landscape-level analysis is appropriate, and choose the spatial boundary accordingly; recognize that individual harvest decisions are made at stand level while at landscape, regional, or national levels may be more appropriate in order to consider the impacts of the forest economy, as management responds to market forces; assess the impact of timing of emissions and sequestration; consider whether a retrospective or prospective approach is relevant, and choose the temporal boundary accordingly, acknowledging that as the short-term and long-term climate impacts can be significantly different, the time horizon adopted can substantially influence the conclusions drawn; recognize that biomass for bioenergy is typically only one component of a range of products harvested from a managed forest; consider all factors that influence forest carbon stocks, including forest management (silviculture, harvest), also natural biotic and abiotic forces (e.g., edaphic, climate, disturbance events); commence accounting at the time that management changes in response to bioenergy demand, while acknowledging that the chosen perspective, i.e., retrospective or prospective, might impact on this choice; recognize that the earth climate system is altered not only by CO2, but also by changes in the atmospheric concentration of other gases and aerosols, in solar radiation and in land surface albedo, so the effects of all climate forcers influenced by forest cover and forest management should ideally be included; recognize that the climate effect of bioenergy is influenced by market-mediated forces, that impact land use, energy use, forest management, and the wood products sector; recognize that a comprehensive analysis of climate impacts of bioenergy is complex and likely to be subject to significant uncertainties and sensitivities; and note that the result is specific to each situation.

414

Managing Global Warming

There are some knowledge gaps that remain to be filled, to enable greater understanding of the climate impacts of bioenergy. These include the need for (i) studies clarifying how the energy and forestry sectors, including forest management, respond to changing forest product markets; (ii) empirical data on forest product supply and demand and land use at resolution that enables comprehensive analyses of alternative scenarios; (iii) studies integrating forest/bioenergy systems modeling with Earth systems/climate science/energy system/integrated assessment modeling; and multidisciplinary research into the interpretation and translation of insights from scenario modeling into policy guidance for management of land use and energy system [63].

13.7

Conclusions

Quantifying the climate effects of forest-based bioenergy is a complex endeavor and is fraught with challenges. Methodological choices influence the results and the related conclusions dramatically. These choices depend on the goal and scope of the study, and are related to the definition of spatial and temporal system boundaries and climate metrics. A comprehensive understanding of the climate effects of bioenergy systems requires a combination of biophysical, climate, and socioeconomic models, including effects on parallel industries (e.g., wood products, agriculture, and energy), in order to robustly inform policy development. The timing of emissions and sequestration is important when assessing the effectiveness of bioenergy in climate change mitigation, in particular concerning ambitious stabilization targets (e.g., 1.5°C temperature increase) requiring rapid and deep cuts in GHG emissions and increase in carbon sinks [64]. When planning policies, it is very important to recognize that short- and long-term climate impacts of bioenergy might be very different. A shift to a sustainable bioenergy production system resulting in significant climate benefits in the long-term might also result in less beneficial or even harmful short-term impacts. This can be considered as an investment, acknowledging that the related short-term climate impacts should be reduced by other means, particularly if aiming to achieve ambitious climate targets in the short term.

Acknowledgments We thank G€oran Berndes and Tat Smith for their comments on earlier versions of this paper, and IEA Bioenergy for permission to utilize material from [65].

References [1] Fargione J, Hill J, Tilman D, Polasky S, Hawthorne P. Land clearing and the biofuel carbon debt. Science 2008;319:1235–8. [2] Searchinger T, Heimlich R, Houghton RA, Dong FX, Elobeid A, Fabiosa J, Tokgoz S, Hayes D, Yu TH. Use of U.S. croplands for biofuels increases greenhouse gases through emissions from land-use change. Science 2008;319:1238–40. [3] Hudiburg TW, Law BE, Wirth C, Luyssaert S. Regional carbon dioxide implications of forest bioenergy production. Nat Clim Chang 2011;1(8):419–23.

Quantifying the climate effects of forest-based bioenergy

415

[4] Schulze E-D, K€orner C, Law BE, Haberl H, Luyssaert S. Large-scale bioenergy from additional harvest of forest biomass is neither sustainable nor greenhouse gas neutral. GCB Bioenergy 2012;4:611–6. [5] Walker T, Cardellichio P, Colnes A, Gunn J, Kittler B, Perschel B. Forest Guild, In: Recchia C, Saah D, editors. Natural Capital Initiative, Biomass sustainability and carbon policy study. Manomet Center for Conservation Sciences; 2010. Available at http://www. biomassthermal.org/programs/documents/20_BiomassSustainabilityCarbon.pdf. [6] Pingoud K, Ekholm T, Soimakallio S, Helin T. Carbon balance indicator for forest bioenergy scenarios. GCB Bioenergy 2016;8(1):171–82. [7] Lamers P, Junginger M. The ‘debt’ is in the detail: a synthesis of recent temporal forest carbon analyses on woody biomass for energy. Biofuels Bioprod Biorefin 2013;7:373–85. [8] Gustavsson L, Haus S, Ortiz CA, Sathre R, Le Truong N. Climate effects of bioenergy from forest residues in comparison to fossil energy. Appl Energy 2015;138:36–50. [9] Ter-Mikaelian MT, Colombo SJ, Chen J. The burning question: Does forest bioenergy reduce carbon emissions? A review of common misconceptions about forest carbon accounting. J Forestry 2015;113:57–68. [10] Eriksson L, Gustavsson L. Costs, CO2- and primary energy balances of forest-fuel recovery systems at different forest productivity. Biomass Bioenergy 2010;34:610–9. [11] Lindholm EL, Berg S, Hansson PA. Energy efficiency and the environmental impact of harvesting stumps and logging residues. Eur J For Res 2010;129:1223–35. [12] Hamelinck CN, Suurs RA, Faaij AP. International bioenergy transport costs and energy balance. Biomass Bioenergy 2005;29:114–34. [13] Gustavsson L, Eriksson L, Sathre R. Costs and CO2 benefits of recovering, refining and transporting logging residues for fossil fuel replacement. Appl Energy 2011;88:192–7. [14] Hoefnagels R, Resch G, Junginger M, Faaij A. International and domestic uses of solid biofuels under different renewable energy support scenarios in the European Union. Appl Energy 2014;131:139–57. [15] EC-JRC-IES, European Commission—Joint Research Centre—Institute for Environment and Sustainability. International reference life cycle data system (ILCD) handbook— general guide for life cycle assessment—detailed guidance. First edition. EUR 24708 EN. Luxembourg. In: Publications Office of the European Union. 2010. [16] Soimakallio S, Cowie A, Branda˜o M, Finnveden G, Ekvall T, Erlandsson M, Koponen K, Karlsson PE. Attributional life cycle assessment: Is a land-use baseline necessary? Int J Life Cycle Assess 2015;20(10):1364–75. [17] Zamagni A, Guinee J, Heijungs R, Masoni P, Raggi A. Lights and shadows in consequential LCA. Int J Life Cycle Assess 2012;17:904–18. [18] UNEP/SETAC Life Cycle Initiative, Global guidance principles for life cycle assessment databases (Shonan Guidance Principles), 2011. [19] Finnveden G, Hauschild MZ, Ekvall T, Guinee J, Heijungs R, Hellweg S, Koehler A, Pennington D, Suh S. Recent developments in life cycle assessment. J Environ Manag 2009;91:1–21. [20] Curran MA, Mann M, Norris G. The international workshop on electricity data for life cycle inventories. J Clean Prod 2005;13(8):853–62. [21] Ximenes FA, George BH, Cowie A, Williams J, Kelly G. Greenhouse gas balance of native forests in New South Wales, Australia. Forests 2012;3:653–83. [22] Koponen K, Soimakallio S, Kline KL, Cowie A, Branda˜o M. Quantifying the climate effects of bioenergy—choice of reference system. Renew Sust Energ Rev 2018;81:2271–80. [23] ISO. ISO/TS 14067:2013 greenhouse gases—C footprint of products—requirements and guidelines for quantification and communication. Switzerland: International Organization for Standardization; 2013.

416

Managing Global Warming

[24] Upton J. What’s worse than burning coal? Burning wood 2014. http://grist.org/climateenergy/whats-worse-than-burning-coal-burning-wood/. [25] Soimakallio S, M€akinen T, Ekholm T, Pahkala K, Mikkola H, Paappanen T. Greenhouse gas balances of transportation biofuels, electricity and heat generation in Finland—dealing with the uncertainties. Energy Policy 2009;37(1):80–90. [26] Soimakallio S. Toward a more comprehensive greenhouse gas emissions assessment of biofuels: the case of forest-based Fischer–Tropsch diesel production in Finland. Environ Sci Technol 2014;48(5):3031–8. [27] Soimakallio S, Saikku L, Valsta LT, Pingoud K. Climate change mitigation challenge for wood utilization—the case of Finland. Environ Sci Technol 2016;50:5127 5134. [28] Houghton J, Meira Filho L, Lim B, Treanton K. Mamaty I. In: Revised 1996 IPCC guidelines for national greenhouse gas inventories. 1997. [29] IPCC 2014a. Frequently asked questions. http://www.ipcc-nggip.iges.or.jp/faq/faq.html [30] Georgescu M, Lobell D, Field C. Direct climate effects of perennial bioenergy crops in the United States. Proc Natl Acad Sci 2011;108:4307–12. [31] Loarie S, Lobel l, Asner G, Mu Q, Fiel C. Direct impacts on local climate of sugar-cane expansion in Brazil. Nat Clim Chang 2011;1:105–9. [32] Bright R, Astrup R, Strømman A. Empirical models of monthly and annual albedo in managed boreal forests of interior Norway. Clim Chang 2013;120(1–2):183–96. [33] Bright R, Strømman A, Peters G. Radiative forcing impacts of boreal Forest biofuels: A scenario study for Norway in light of albedo. Environ Sci Technol 2011;45:7570–80. [34] Spracklen D, Bonn B, Carslaw K. Boreal forests, aerosols and the impacts on clouds and climate. Philos Trans R Soc A Math Phys Eng Sci 2008;366(1885):4613–26. [35] Bonan G. Forests and climate change: forcings, feedbacks and the climate benefits of forests. Science 2008;320:1444–9. [36] Anderson R, Canadell J, Randerson J, et al. Biophysical considerations in forestry for climate protection. Front Ecol Environ 2010;9:174–82. [37] Kupiainen K, Klimont Z. Primary emissions of fine carbonaceous particles in Europe. Atmos Environ 2007;41(10):2156–70. [38] Collins, M., R. Knutti, J. Arblaster, J.-L. et al. (2013). “Long-term climate change: Projections, commitments and irreversibility,” Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, et al. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. pp 1029–1136. [39] BSI. (2011). PAS 2050:2011 specification for the assessment of the life cycle greenhouse gas emissions of goods and services (PAS 2050). British Standards Institution, London. [40] IPCC, 2014b: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schl€omer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. [41] Ekholm T. Hedging the climate sensitivity risks of a temperature target. Clim Chang 2014;127(2):153–67. [42] Berndes G, Bird N, Cowie A. Bioenergy, land use change and climate change mitigation: Report for policy advisors and policy makers, IEA Bioenergy: ExCo 2010;2010:03. http:// www.ieabioenergy.com/publications/bioenergy-land-use-change-and-climate-changemitigation/.

Quantifying the climate effects of forest-based bioenergy

417

[43] Ciais, P., C. Sabine, G. Bala, L. et al. (2013). “Carbon and other biogeochemical cycles,” Climate. Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. et al. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. pp 465–570. [44] Branda˜o M, Levasseur A, Kirschbaum MUF, et al. Key issues and options in accounting for carbon sequestration and temporary storage in life cycle assessment and carbon footprinting. Int J Life Cycle Assess 2013;18:230–40. [45] Clift R, Branda˜o M. Carbon storage and timing of emissions—a note by Roland Clift and Miguel Branda˜o. Guildford, UK: University of Surrey, Centre for Environmental Strategy Working Paper 02/08; 2008. [46] BSI. PAS 2050:2011 specification for the assessment of the life cycle greenhouse gas emissions of goods and services (PAS 2050). London: British Standards Institution; 2008. [47] Levasseur A, Lesage P, Margni M, et al. Considering time in LCA: Dynamic LCA and its application to global warming impact assessments. Environ Sci Technol 2010;44 (8):3169–74. [48] Cherubini F, Peters GB, Bernsten T, et al. CO2 emissions from biomass combustion for bioenergy: atmospheric decay and contribution to global warming. GCB Bioenergy 2011;3(5):413–26. [49] Guest G, Cherubini F, Strømman AH. Global warming potential of carbon dioxide emissions from biomass stored in the Anthroposphere and used for bioenergy at end of life. J Ind Ecol 2013;17(1):20–30. [50] Pingoud K, Ekholm T, Savolainen I. Global warming potential factors and warming payback time as climate indicators of forest biomass use. Mitig Adapt Strateg Glob Chang 2012;17(4):369–86. [51] Myhre G, Shindell D, Breon F-M, et al. Anthropogenic and natural radiative forcing. In: Stocker TF, Qin D, Plattner G-K, et al., Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press; 2013. [52] Cherubini F, Bright RM, Strømman AH. Global climate impacts of forest bioenergy: What, when and how to measure? Environ Res Lett 2013;8(1)014049. [53] Pingoud K, Pohjola J, Valsta L. Assessing the integrated climatic impacts of forestry and wood products. Silva Fennica 2010;44(1):155–75. [54] Gustavsson L, Pingoud K, Sathre R. Carbon dioxide balance of wood substitution: Comparing concrete- and wood-framed buildings. Mitig Adapt Strateg Glob Chang 2006;11 (3):667–91. [55] Sathre R, O’Connor J. Meta-analysis of greenhouse gas displacement factors of wood product substitution. Environ Sci Pol 2010;13:104–14. [56] Kurz W, Smyth C, Lemprie`re T. Climate change mitigation through forest sector activities: principles, potential and priorities 1. Unasylva 2016;67:61. [57] Schmidt JH, Weidema BP, Branda˜o M. A framework for modelling indirect land use changes in life cycle assessment. J Clean Prod 2015;99:230–8. [58] Smeets E, Tabeau A, van Berkum S, Moorad J, van Meijl H, Woltjer G. The impact of the rebound effect of the use of first generation biofuels in the EU on greenhouse gas emissions: A critical review. Renew Sust Energ Rev 2014;38:393–403. [59] Agostini A, Giuntoli J, Boulamanti A, Marelli L, editors. Carbon accounting of forest bioenergy. Conclusions and recommendations from a critical literature review. JRC technical reports. Report EUR 25354 EN. European Commission: Joint Research Centre; 2013.

418

Managing Global Warming

[60] Matthews, R., Sokka, L., Soimakallio, S., Mortimer, N., Rix, J., Schelhaas, M.-J., Jenkins, T., Hogan, G., Mackie, E., Morris, A. and Randle, T. 2014. Review of literature on biogenic carbon and life cycle assessment of forest bioenergy. Final Task 1 report, DG ENER project, ‘Carbon impacts of biomass consumed in the EU. The Research Agency of the Forest Commission. May 2014. [61] Kallio AMI, Salminen O, Siev€anen R. Sequester or substitute—consequences of increased production of wood based energy on the carbon balance in Finland. J For Econ 2013;19 (4):402–15. [62] Siev€anen R, Salminen O, Lehtonen A, Ojanen P, Liski J, Ruosteenoja K, Tuomi M. Carbon stock changes of forest land in Finland under different levels of wood use and climate change. Ann For Sci 2014;71(2):255–65. [63] Cowie, A. L., Branda˜o, M., Fritsche, U.R., Berndes, G., Junginger M. and Smith C.T. 2017 Forests, bioenergy and climate change mitigation. Report of a workshop held Vols. 19–20 May 2014, Copenhagen: IEA Bioenergy. Available from http://task38.ieabioenergy.com/ wp-content/uploads/2017/01/Copenhagen_Workshop_Report.pdf [64] Rockstr€om J, Gaffney O, Rogelj J, Meinshausen M, Nakicenovic N, Schellnhuber HJ. A roadmap for rapid decarbonization. Science 2017;355(6331):1269–71. [65] Cowie A, Berndes G, Smith CT, On the timing of greenhouse gas mitigation benefits of forest-based bioenergy, IEA Bioenergy Executive Committee 2013. Available from http:// www.ieabioenergy.com/wp-content/uploads/2013/10/On-the-Timing-of-GreenhouseGas-Mitigation-Benefits-of-Forest-Based-Bioenergy.pdf