ORIGINAL ARTICLE

Global warming potential factors and warming payback

time as climate indicators of forest biomass use

Kim Pingoud & Tommi Ekholm & Ilkka Savolainen

Received: 9 June 2011 / Accepted: 14 October 2011

# Springer Science+Business Media B.V. 2011

Abstract A method is presented for estimating the global warming impact of forest biomass

life cycles with respect to their functionally equivalent alternatives based on fossil fuels and

non-renewable material sources. In the method, absolute global warming potentials (AGWP) of

both the temporary carbon (C) debt of forest biomass stock and the C credit of the biomass use

cycle displacing the fossil and non-renewable alternative are estimated as a function of the time

frame of climate change mitigation. Dimensionless global warming potential (GWP) factors,

GWPbio and GWPbiouse, are derived. As numerical examples, 1) bioenergy from boreal forest

harvest residues to displace fossil fuels and 2) the use of wood for material substitution are

considered. The GWP-based indicator leads to longer payback times, i.e. the time frame

needed for the biomass option to be superior to its fossil-based alternative, than when just the

cumulative balance of biogenic and fossil C stocks is considered. The warming payback time

increases substantially with the residue diameter and low displacement factor (DF) of fossil C

emissions. For the 35-cm stumps, the payback time appears to be more than 100 years in the

climate conditions of Southern Finland when DF is lower than 0.5 in instant use and lower

than 0.6 in continuous stump use. Wood use for construction appears to be more beneficial

because, in addition to displaced emissions due to by-product bioenergy and material

substitution, a significant part of round wood is sequestered into wood products for a long

period, and even a zero payback time would be attainable with reasonable DFs.

Keywords Forest biomass . Bioenergy . Wood products . Climate impacts . GWP factors .

Biogenic C debt . Displacement of fossil GHG emissions . Material substitution . Pulse

response model

1 Introduction

Biomass is basically a renewable carbon- (C) neutral source of energy and materials when

emissions from biomass use are re-absorbed into the re-growth of new biomass. Thus, the C

Mitig Adapt Strateg Glob Change

DOI 10.1007/s11027-011-9331-9

K. Pingoud (*) : T. Ekholm : I. Savolainen

VTT Technical Research Centre of Finland, Tekniikantie 2, Espoo, P.O. Box 1000, FI-02044 VTT, Finland

e-mail: kim.pingoud@vtt.fi
dynamics of the biomass stocks differ essentially from those of permanent fossil

sources, which basically cannot be sequestered back into their original tectonic stocks.

In practice, the impact of biomass use on emissions is much more complex. For

example, the conversion of C-rich lands such as rainforests, peatlands, savannahs and

grasslands to produce food-crop-based biofuels causes a change in land use (LUC),

which may lead to a permanent loss of terrestrial C stocks. The biofuel C debt can be

high compared with the fossil C emissions that can be displaced annually by biofuels

(Fargione et al. 2008). Thus, compensation of the debt may take a long time and can be

described by ecosystem carbon payback time (Gibbs et al. 2008), which in the worst case

could be several centuries. On the other hand, biomass plantations on degraded land may

have a positive impact on the terrestrial C stocks, thus providing mitigation benefits in a

very short time frame.

Even more complex are the market-mediated responses that cause indirect land use

change (iLUC) that cannot be analysed with conventional life-cycle techniques. Increasing

biofuel demand influences crop prices. As a response to higher prices, forests and

grasslands may be converted into new cropland to replace the grain (or cropland) diverted

to biofuels (Searchinger et al. 2008; Hertel et al. 2010). According to a model prediction for

the 21st century (Melillo et al. 2009), iLUC due to biofuel expansion could be responsible

for up to twice as much carbon loss as direct LUC.

The C neutrality of bioenergy and, specifically, forest-based biomass has raised a

passionate debate in the US (see, e.g., Sedjo 2011) influenced by the Manomet (2010)

study and the articles by Searchinger et al. (2009) and Fargione et al. (2008). There is no

change in land use category (IPCC 2006) when forests are managed sustainably. In the

case of established management practices being applied, the process is usually climate

neutral over the rotation, as harvested biomass is replaced by the re-growth of new

biomass without any significant changes in terrestrial C stocks at landscape level.

However, in conventional forestry, the rotation length of a stand typically varies from a

decade to more than a century. Thus, in long rotations there is a significant temporal

imbalance or C debt between removal and re-growth at stand level or compared with

delayed or just stopped harvest. Furthermore, a change in forest management practices,

for instance, by decreasing the rotation length or increasing the use of harvest residues,

also has a long-term impact on the landscape-level terrestrial stock or the stand-level C

stock time-averaged over the rotation.

In addition to the biogenic C debt, the substitution impact has to be considered; i.e., how

much of the fossil C emissions could be displaced by the use of biomass when taking into

account all the emissions from the biomass production chain, including those from possible

fertilizer use. The two factors, the terrestrial C imbalance and the displaced fossil C

emissions, together determine the net C balance of the biomass use cycle with respect to its

fossil fuel-based alternative.

Ambitious climate targets such as the 2°C stabilization with global greenhouse gas

(GHG) emissions peaking within one decade (IPCC 2007a, p. 15, Table SPM5) emphasize

rapid reductions in emissions, which also makes the timing of emissions from biomass an

issue. Thus, the GHG indicators of the biomass use cycle should take into account the

mitigation time frame under consideration. Conventional GHG life cycle assessment (LCA)

of the biomass use cycle by the provision of one static emission factor is misleading and

unable to describe the real warming impacts of the biomass use cycle within the mitigation

time frame. The upfront emission profile of energy plantations with preceding conversion

of C-rich lands differs from that of the fossil fuel to be displaced and has been subject to

specific attention in the literature. In some standardized LCA guidelines (PAS 2050 2008)

Mitig Adapt Strateg Glob Change
and the EU Renewable Energy Directive (EU 2009), this momentary emission is amortized

over 20 years. A more realistic basis would be to apply dynamic LCA in which either the

cumulative emissions in time are considered (Schlamadinger and Marland 1996) or metrics

based on cumulative radiative forcing (CRF) / absolute global warming potential (AGWP)

within a time frame T is used (Kendall et al. 2009; Levasseur et al. 2010; O’Hare et al.

2009; Kirkinen et al. 2008; Repo et al. 2010).

In sustainable forestry, the upfront emission profile is different from LUC. Final

felling causes a similar C debt as that of land conversion but, in addition, the postharvest re-growth of the new stand has to be credited. Marland and Schlamadinger

(Schlamadinger and Marland 1996; Marland and Schlamadinger 1997) presented a

method by which the net effects of using forests, either for carbon sequestration or as a

source of bioenergy to displace fossil fuels, were described as a function of time. The

measure for net climate effects is the sum of the displaced emissions and carbon

sequestered into forest biomass. Note that the displaced fossil Ceq emissions are equal to

the fossil Ceq emissions of the functionally equivalent fossil energy system minus the

fossil Ceq emissions of the bioenergy system, e.g. due to harvest, transport and processing

of the biomass. The method can be used to assess the mitigation benefits of different

forest-use strategies in time. The essential parameter in the method is the fossil carbon

displacement factor (DF) describing the reduction in fossil Ceq emissions in proportion to

the biogenic C in the biomass feedstock. DF is a measure of the mitigation efficiency of

the biomass use cycle. This method is compatible with the so-called standard

methodology for the GHG balances of bioenergy systems compared with fossil energy

systems (Schlamadinger et al. 1997).

As shown by Marland and Schlamadinger, there are trade-offs between alternative

mitigation options of managed forests. The available alternatives are substitution (i.e.

use of harvested biomass to displace fossil fuels or energy-intensive materials), C

sequestration and, simply, conservation of forest biomass. The amount of the trade-offs

depends on many factors, such as the time frame of mitigation, rotation length and

biomass re-growth rate and DF. The use of fossil alternatives instead of biomass

sometimes provides near-term net GHG benefits, especially when DF is low and the

rotation is long. However, in the long term, the accumulating benefit of fossil fuel

substitution (i.e. avoidance of emissions from permanent tectonic C stocks) dominates

due to the saturation of the C sequestration alternative.

In place of considering the net C balance of the biomass system with respect to its fossil

reference, as done by Schlamadinger and Marland, a more realistic measure of the GHG

impacts would be net cumulative radiative forcing (CRF) in time due to biomass use, i.e.

the decrease in cumulative thermal energy radiation from the Earth to space within a given

time frame. The decrease is caused by a change in atmospheric greenhouse gas

concentrations due to the emission sources and sinks of biomass use.

The objective of this article is to present metrics with which the GHG impact of the

biomass life cycle can be related to that of a permanent fossil C emission. Global Warming

Potential (GWP) factors are derived that describe the CRF of the forest biomass life cycle–

within the time frame of interest starting at the point of harvest – in proportion to the CRF

of a fossil C emission at the initial time. Cherubini et al. (2011) presented a GWPbio factor

for the biomass resource. In this article we widen this approach to the biomass product life

cycle and displaced fossil C emissions. The GWP factors to be presented are analogous to

those derived for non-CO2 gases to convert them into CO2-equivalent fossil emissions. As

numerical examples, we use alternative forest biomass scenarios including both bioenergy

and long-lived wood products.

Mitig Adapt Strateg Glob Change
2 Method

The method in this article is aimed at estimating the warming impact of forest biomass

harvest and use with respect to its fossil C-based functionally equivalent alternatives. The

perspective is forward-looking, as nothing can be done to the past. The actions and choices

made from now on are relevant to climate change mitigation. The objective is to present

simple ex-ante indicators that would estimate the warming impact of a biomass use cycle in

advance, within the time frame of interest starting from the point of harvest. Biomass

harvest and use is assumed to represent the action having climate impacts with respect to

the no-harvest and non-use baseline. The method considers the warming impact of: 1) the

debt in the terrestrial C stocks due to biomass harvest and 2) the cooling impact of the

biomass use cycle due to displaced fossil C emissions and C sequestration of biomass

products. The C debt evolves in time depending on the development of the terrestrial C

stock in both the scenarios of a harvest and a no-harvest baseline, including re-growth of

new biomass. The C stock of biomass products and the displacement of emissions also vary

within the considered time frame.

To estimate the radiative forcing in time, a model for the removal of the atmospheric C is

needed. For this purpose, the impulse response model based on the Bern Carbon Cycle

Model 2.5CC given by the IPCC (2007b, p.213) is used (see Appendix 1 for details). The

impulse response describes the time behaviour of the atmospheric CO2 concentration due to

a CO2 pulse to the atmosphere. After the pulse, the atmospheric concentration declines due

to the removal of CO2 to the ocean and biosphere.

The warming impact of CO2 emissions is assessed using radiative forcing (RF) as an

indicator of heating power in the atmosphere-surface system. RF is calculated on the basis

of increased CO2 concentration. The unit of RF is typically Watts (W) per square metre

(m2

) of the surface of the Earth. RF describes the deviation in the radiation energy balance

of the atmosphere-surface system due to some considered factor such as increased

greenhouse gas concentration (IPCC 2007b; Monni et al. 2003).

The time integral of radiative forcing (RF) is a measure of the global warming energy

absorbed due to the additional GHG emission, also called cumulative radiative forcing

(CRF) or Absolute Global Warming Potential (AGWP). This cumulative warming impact,

within the time frame (0,T), can be assessed for the C emissions due to a unit fossil C

emission pulse released at time zero:

AGWPfosðTÞ 1⁄4 ZT

0

RF SfosðtÞ dt ð1Þ

where Sfos(t) is the atmospheric CO2 concentration due to the fossil C emission unit pulse.

After its release, the C impulse is gradually transferred to the ocean and biosphere in general

(Appendix 1), but there is no C uptake back to the original tectonic stocks. Thus, the fossil C

emission is often said to be permanent.

For a unit C pulse from biomass harvest at time zero (causing a temporary C debt of the

biomass stock), a similar equation can be presented:

AGWPbioðTÞ 1⁄4 ZT

0

RF Sð Þ bioðtÞ dt ð2Þ

where Sbio(t) is the atmospheric CO2 concentration due to the biomass unit C pulse so that in

addition to the normal atmospheric decay of the fossil C pulse as above, biomass re-growth

Mitig Adapt Strateg Glob Change
(e.g. growth of a new forest stand after the regeneration cut) also affects the concentration.

The value of this is highly dependent on the biomass re-growth rate. Other emission

components of biomass cultivation such as N2O from fertilizers and other climatic forcers

such as albedo effects (see, e.g., Bright et al. 2011) could basically also be included in the

AGWPbio(T).

Analogously to Eq. (2), the net cooling impact of using a unit of biogenic C at time zero

with respect to a functionally equivalent fossil-based service can be considered:

AGWPblouseðTÞ 1⁄4 ZT

0

RF SdisplðtÞ  þ RF SseqðtÞ   dt ð3Þ

where Sdispl(t) is the reduced atmospheric CO2 concentration due to displaced emissions in

both energy and material substitution, and Sseq(t) is the reduced CO2 concentration due to C

sequestration into biomass products. The functionally equivalent fossil service could be a

displaced fossil fuel or non-biogenic material with embodied fossil C emissions.

Summing up, Eqs. (2) and (3) give the net warming impact of the biomass use chain

compared with the functionally equivalent fossil chain. The time T when the sum is equal to

zero gives the cumulative warming payback time of the biomass chain with respect to its

fossil reference service.

The climate impact of the unit biomass C pulse (Eq. 2) and displaced emissions (Eq. 3)

can also be expressed in proportion to the climate impact of the fossil C unit pulse (Eq. 1).

The so-called GWPbio factor is defined (Cherubini et al. 2011) as the quotient of AGWPs in

Eqs. (2) and (1):

GWPbioðTÞ 1⁄4 AGWPbioðTÞ

AGWPfosðTÞ ð4Þ

GWPbio is dimensionless and a function of the mitigation time frame (0,T) under

consideration. It is analogous to the GWP factors describing the relative warming impact of

non-CO2 gases to that of CO2. Another GWP factor can be defined by considering, in

addition to just the C pulse due to biomass harvest, the net cooling impact due to the use of

harvested biomass:

GWPnetbioðTÞ 1⁄4 AGWPbioðTÞ þ AGWPbiouseðTÞ

AGWPfosðTÞ ð5Þ

1⁄4 GWPbioðTÞ þ GWPbiouseðTÞ ð6Þ

The first term in Eq. (6) is GWPbio. The second term, GWPbiouse , is the relative cooling

impact compared with the warming impact of the fossil pulse (Eq. 1). In the case that the

displacement of fossil C emission takes place immediately after biomass harvest:

GWPbiouseðTÞ1⁄4DF ð7Þ

where DF is the displacement factor (Schlamadinger and Marland 1996). GWPbiouse in Eq.

(7) is constant, as the displaced fossil C emissions have the same dynamics as the unit fossil

C emission. In this article, however, GWPbiouse covers a wider range of options than just the

displacement of fossil fuels, such as cascading use of biomass including material

substitution, temporal C stock of the biomass product and recycling into bioenergy. In

Mitig Adapt Strateg Glob Change
this latter case, GWPbiouse is a non-constant function of the time frame (0,T). The two GWP

terms in Eq. (6) are simple dimensionless indicators of the biomass use in climate change

mitigation within the given time frame related to the climate impacts of a fossil C pulse. As

GWPnetbio depends on T, the time T when GWPnetbio(T) = 0 is the cumulative-warming

payback time defined above.

In defining the GWP factors, an instant emission pulse at time zero is usually

considered. However, the approach could also be generalized to other cases such as step

emissions where a continuing biomass harvesting activity is started at time zero. Here a

fossil C step pulse must be used as the reference.

3 Results

3.1 Bioenergy from forest residues

The numerical example of bioenergy production from forest harvest residues is based on the

results of the study by Repo et al. (2010) in which the decay of Norway spruce (Picea

abies) branches and stumps of various diameters in time were estimated with the Yasso07

model (Yasso07 2011). The emission rates and decomposition dynamics of residues are

related to the climate conditions and the type of residues. The residue diameters considered

were 1, 2 and 5 cm for branches and 10, 20, 26 and 35 cm for stumps, and the assumed

climate conditions correspond to those of Southern Finland.

When calculating the indicators, it is assumed that in the baseline case the residues are

left on site and decomposed slowly to the atmosphere. In the bioenergy case, the residues

are combusted and emitted to the atmosphere in the year of harvest. The biogenic C debt is

the difference in C balance between the bioenergy and the baseline case. Two options are

considered: a pulse and a step use of residues. In the pulse option, residues containing 1 Mg

(=megagram or metric ton) of biomass C were harvested and used in 2010, causing a pulse

emission of bioenergy. In the step option, an activity was started in 2010 using annual

residues containing 1 Mg of biomass C, causing a step emission from bioenergy.

The net biogenic C emission due to the pulse use of residues, i.e. the emission due to the

bioenergy pulse minus the terrestrial C emission in the no-use baseline (shown for the 5 cm

branches in Fig. 1a), was 1 Mg C in 2010 but just negative after that because of the

decomposition of residues in the no-use baseline. The reference fossil C pulse is simply the

1 Mg C emission in 2010, also shown in Fig. 1a. The atmospheric concentration Sbio(t) due

to the net biogenic C emission is then estimated using the pulse response model (Appendix 1)

and the cumulative warming impact AGWPbio(T) calculated by Eq. (2). Similarly, the fossil C

concentration Sfos(t) due to the fossil C pulse in Fig. 1a is estimated and AGWPfos(T) is

calculated by Eq. (1). The AGWP curves are shown in Appendix 1. The dimensionless

GWPbio (T) factor calculated by Eq. (4) is shown in Fig. 1b as a function of the time frame T.

The climate benefits of the biomass use cycle, characterized by the displacement factor

DF, are dependent on the biomass combustion efficiency and the fossil fuel displaced by

bioenergy. The magnitude of DF for a modern biomass boiler displacing coal combustion

could be 0.9 or even higher. For natural gas displacement, it would be in the order of 0.5.

For illustrative purposes in Fig. 1, it is simply assumed that DF = 0.6, which means that

with 1 Mg biomass C in harvest residues, 0.6 Mg C from fossil fuel is displaced. In the case

that energy displacement takes place immediately after the biomass harvest, GWPbiouse(T)

is constant in time and equal to −DF = −0.6. (The AGWPbiouse is shown in Fig. 8 of

Appendix 1.) Accordingly, GWPnetbio decreases to zero in 2028 so that the climate benefit

Mitig Adapt Strateg Glob Change
in terms of cooling (i.e. a negative value) with respect to the fossil energy alternative is

obtained in a time frame longer than 18 years (Fig. 1b).

The climate benefit criterion in the original method of Schlamadinger and Marland —

the sum of the biogenic C balance and cumulative displaced fossil emissions–is positive

already in 2019, after which there are climate benefits in terms of a positive

(terrestrial + tectonic) C stock with respect to the fossil fuel alternative (Fig. 1b).

Thus, the C balance payback time (9 years) is essentially shorter than the cumulative

warming payback time (18 years) of the present method. The results for other residue

diameters are similar.

Figure 2a illustrates how the biogenic C emissions from a step use of harvest residues are

related to branch and stump diameters. Estimating the concentrations Sbio(t) and Sfos(t) due to

the biomass C emission of the 5 cm branches and the fossil C step emission in Fig. 2a and

performing similar calculations to those in Fig. 1 with DF = 0.6 results in stepGWPbio(T),

stepGWPbiouse(T) and stepGWPnetbio in Fig. 2b. For comparison purposes, the sum of the

biomass C balance and cumulative displaced fossil emissions are presented. Both the C

balance payback time (21 years) and the warming payback time (32 years) are higher in this

step case than in the pulse case in Fig. 1.

One hundred years is a regularly applied time frame in climate policy, and the GWP

(100 years) factors a simplified way of describing the relative warming impact of non-CO2

GHGs in proportion to CO2 in emissions reporting. Applying this analogy to the biomass C

emissions from the use of harvest residues (Fig. 3) shows, for example, that the climate

Fig. 1 a Fossil C and biomass C (forest residue branches of Picea abies, 5 cm in diameter = B5) net

emissions to the atmosphere due to the energy production pulse. After the positive value in 2010, the

biogmass curve is negative. The biomass net curve is the remainder of the bioenergy emission pulse and slow

decay of forest residues on the cutting site. b Relative warming impacts described by GWPbio, GWPbiouse and

GWPnetbio calculated on the basis of the B5 net emission curve due to the energy production pulse. The

relative warming impact of the B5 net emission curve is about 0.4 over a 50-year time horizon (in 2060)

compared with a fossil emission pulse, if no displacement of fossil carbon is accounted for. If the

displacement factor is 0.6, a cooling benefit of 0.2 can be reached in 50 years (in 2060). The role of

displacement is crucial to the total net impact. The sum of terrestrial C stock and cumulative displaced

emissions is shown as the dashed line

Mitig Adapt Strateg Glob Change
impact of the use of 1 Mg C of 20 cm stumps corresponds to an instant fossil C emission of

approximately 0.4 Mg C and continuous 1 Mg C annual stump use to a 0.5 Mg C annual

fossil emission – excluding here the substitution benefits of bioenergy.

Energy substitution is taken into account in Fig. 4, which estimates the warming

payback time as a function of the displacement factor DF. The results illustrate the

sensitiveness of the climate benefit on the displacement factor DF. For example, energy use

of the largest stump fraction (35 cm) in the Repo et al. (2010) study only creates less

cumulative warming than the fossil fuel alternative after 100 years if DF is less than 0.5 in

instant use (Fig. 4a) or 0.6 in continuous use (Fig. 4b).

Fig. 2 a Fossil C and biomass C (forest residue branches and stumps of various diameters) net emissions to

the atmosphere due to continuous energy production starting in 2010 (step function). b Relative warming

impacts described by stepGWPbio, stepGWPbiouse and stepGWPbionet calculated on the basis of the B5 net

emission curve due to continuous energy production starting in 2010 (step function). The relative warming

impact of the B5 net emission curve is about 0.5 over a 50-year time horizon compared with fossil energy

emission if no displacement of fossil carbon is accounted for. If the displacement factor is 0.6, a cooling

effect of 0.08 can be reached in 50 years. The sum of ecosystem carbon stock and cumulative displaced

emissions is shown as the dashed line

Fig. 3 GWPbio(100 year)

for different residues as a function of their diameter calculated

for pulse and stepwise energy

production

Mitig Adapt Strateg Glob Change
3.2 Stem biomass for long-lived wood products

In addition to energy use, climate benefits can potentially be obtained by material use of

forest biomass. Here, a modern wooden office building displacing a conventional concrete

one is considered. The details of the calculation of the DF factors and C stock of wood

products are given in Appendix 2 based on the LCA study by Häkkinen and Wirtanen

(2006). The main building material is assumed to be Scots pine (Pinus sylvestris) grown in

Southern Finland. The parts of the stem not applicable to long-lived materials are assumed

to be used for bioenergy. The growth curve for the stemwood of the pine stand (Fig. 5) is

estimated by the MOTTI simulator (Hynynen et al. 2005) whose data are based on test

areas in Finland comprising all age classes (Hynynen et al. 2002), though the

representativeness of data for stands older than 140 years is weak. The soil C balance is

excluded and only stemwood growth is considered. For simplicity, the thinning of forest

stands is also excluded. Applying the growth curve in Fig. 5, it is assumed that the point of

final felling can be varied. After felling, we assume that the re-growth follows the same

growth curve starting from time zero and that the C debt at felling is equal to the biogenic C

in stemwood.

Fig. 4 Cumulative warming payback time as a function of displacement factor DF for different

residue diameters (branches 1,

2 and 5 cm; stumps 10, 20, 26

and 35 cm) when the use is

instant (pulse energy production)

vs. continuous (stepwise

energy production)

Fig. 5 Development of the stem

biomass of a Scots pine

(Pinus sylvestris) stand without

thinnings estimated by the

MOTTI simulator (Hynynen et al.

2002, 2005). The dashed line

marks uncertain numbers beyond

a 140-year stand age

Mitig Adapt Strateg Glob Change
The pulse from the final felling of 1 Mg of biogenic C at stand age 80 (Fig. 6a) is slightly

positive within a decade of felling — a C debt with respect to the baseline of no-felling –

because the re-growth of the new stand is slower at the beginning than the growth of the old

stand after 80 years (cf. Fig. 5). Thereafter, the development of the new stand is faster, thus

forming a net C sink in proportion to no use. However, according to the estimates by the

MOTTI simulator, there does not appear to be a clear saturation point within the 200-year time

frame that is considered – but the data beyond 140 years should be assessed with caution. As

a consequence of the shape of the growth curve, the GWPbio factor (Fig. 6b) is even greater

than 1 in the beginning, after which it decreases due to the declining C debt caused by the regrowth. The uncertainty of the growth curve is reflected in GWPbio after 2070.

In the material substitution case, GWPbiouse (Fig. 6b) includes both the displacement of

fossil C emissions – due to the bioenergy use of by-products and recycled wood products –

and the temporary C stock of wood products (Eq. 3). It is not constant in time, such as in the

case of harvest residues used immediately for bioenergy. For illustrative purposes, we use an

underestimate of 50 years of the building use life. After decommissioning, wood materials are

recycled for bioenergy with a 50-year delay and the biomass C sequestered in wood products

displaces fossil C emissions with DF = 0.6. The GWPbiouse is close to −1 in the first 50 years

despite the moderate DF. This reflects the benefits of combined material and energy

substitution in climate change mitigation compared with the pure energy substitution. The

overall climate performance with respect to the concrete building is described by the indicator

GWPnetbio. Similarly to the forest residue case, the GWP-based metrics gives a longer

payback time (36 years) than the sum of the C stock and cumulative displaced emissions

(23 years). However, with a slightly higher DF for by-product bioenergy, in the order of 0.8,

the GWPnetbio would be negative already at the year of construction and the warming payback

time would be zero.

Another factor contributing negatively to climate benefits is the slow growth of the Scots

pine stand. In addition, there does not appear to be any clear saturation point for the growth

Fig. 6 a Net carbon emissions

due to biomass use pulse for

wooden building and energy (see

details in the main text). The net

emissions are the remainder of

the biomass carbon emissions in

the use case and the reference

case. b Relative warming impacts

described by GWPbio, GWPbiouse

and GWPnetbio for the material

displacement calculated based on

the net emission curve given in a)

and the LCA data given in

the Appendix 2. The sum of

ecosystem carbon stock and

cumulative displaced emissions is

shown as the dashed line

Mitig Adapt Strateg Glob Change
beyond the commercial rotation length. Consequently, GWPbio calculated as a function of

the stand age at final felling appears relatively insensitive to the felling age (Fig. 7).

In the shortest time frame, the cumulative warming impact is similar to the fossil C

emission because, within 20 years, the re-growth does not fill the C debt with respect to

the no-felling alternative.

4 Discussion and conclusions

The GWP metrics applied to the biogenic C debt was recently introduced by Cherubini et al.

(2011). It results in GWPbio factors that are analogous to the GWP factors derived for non-CO2

GHGs. They are aimed at providing simple but realistic climate indicators in an LCA of

bioenergy systems. In this article, the metrics is extended by considering GWPbio– in addition

to pulse emission – for the biomass step emission and introducing the GWP factor for the

relative cooling impact of biomass-displacing fossil fuels or emission-intensive materials, called

GWPbiouse, the sum of GWPbio and GWPbiouse (= GWPnetbio) being an indicator of the net

climate benefits with respect to the fossil alternative. The consideration of the net GHG benefits

of biomass use is similar to the metrics of Schlamadinger and Marland (1996) in which the

cumulative displaced fossil C emissions due to biomass use are added to the biomass C balance

in time, forming an indicator of the overall C benefits in proportion to the fossil alternative.

The GWPbio factor takes into account the dynamics of the biomass C due to the re-growth

of biomass credited ex-ante. The analysis is forward-looking. No climate credits are given for

past C sequestration. The starting point of the estimated climate impacts is when the biomass

C stock is harvested and taken into use either as energy or materials. By the net GWP factor,

the climate impact of an instant biomass harvest and use cycle can be converted into a fossil

C pulse emission (or removal) whose cumulative warming impact is the same or,

alternatively, the continuous biomass harvest and use of an equivalent fossil C step emission.

The analysis is based on a presumed development of the terrestrial C stock following harvest

and thus involves uncertainties. It could be performed in a similar way at landscape level as at

stand level. The GWPbio and GWPbiouse are estimated as a function of the time frame T, but

the appropriate time frame T to be used is open to question. As a comparison, the 100-year

time period is used in national emission inventories when converting non-CO2 gas emissions

to CO2 equivalents, but the urgency of climate change mitigation may justify the use of even

shorter periods in the future.

By fixing the time frame T, two simple emission-related indicators are provided: one for

the biomass resource and the other for the biomass use cycle replacing fossil carbon,

Fig. 7 GWPbio for final felling

when the rotation length is

altered, based on the growth

curve of the Scots pine (Pinus

sylvestris) stand in Fig. 5. The

dashed line marks uncertain

numbers

Mitig Adapt Strateg Glob Change
relating them to the warming impact of a permanent fossil C pulse emission at time zero (or

to an emission step starting at time zero). One limitation of this approach is that pure C

sequestration without biomass use cannot be valued, but it could be described by the

AGWP (Eqs. 2 and 3). The advantage of using radiative forcing-based metrics, such as

GWP or AGWP metrics, instead of a cumulative net C balance is that non-CO2 gases and

non-GHG-based warming impacts such as albedo and particles could be included and that

the cumulative radiative forcing within a given time frame is likely to be a more realistic

warming indicator than just the net C balance. The GWP index would also provide a

physically-based discounting factor by which the cumulative warming impact of the

estimated future emissions in a fixed time horizon could be related to a permanent fossil

emission at initial time. Basically, the GWP approach could be applied generally in life

cycle assessment (LCA) to convert the emissions along the product life cycle to C (or CO2)

equivalent emissions or a C footprint. In the LCA application, no displaced emissions could

be included, however, only those from the product life cycle.

The numerical values in the figures of the article are relatively sensitive to the biomass

decay curves used in the calculations. The values employed in this article are based on

Repo et al. (2010). However, as a set of decay curves are used, they also give some range

for the results that can be used to describe their variability. Empirical results based on

measurement should be used in the future to estimate the appropriate values of the decay

curves as well their uncertainty ranges. Many of the results of this article are based on the

functional methodological formulation of the impacting processes and they are valid even

without exact numerical values of the biomass decay curves.

The results show that the warming payback time of the method presented is longer than

for the cumulative net C balance. This is due to the fact that during the C debt – emitted to

the atmosphere — a cumulative warming impact is built up that has not yet been

compensated for along with the zero net C balance. When fossil C displacement takes place

immediately after biomass harvest, GWPbiouse is constant and equal to -DF, where DF is the

displacement factor of the method of Schlamadinger and Marland (Schlamadinger and

Marland 1996; Marland and Schlamadinger 1997). In this case, the warming payback time

can easily be estimated as a function of DF.

Ideally, DF can be high even in pure energy use of wood, e.g. in the order of 0.9

when wood displaces coal in a modern combined heat and power plant also designed

for biomass or even more if peat is displaced. The energy substitution is not as

efficient when, for instance, wood-based biodiesel displaces fossil diesel with DF

estimates from 0.3 to 0.5 (Pingoud 2010; Soimakallio et al. 2009). However, in reality,

the situation may be more complex: the increased bioenergy supply may influence the

whole energy system due to market impacts, causing leakage when an additional 1 MJ of

bioenergy does not fully displace a 1 MJ of fossil fuels (Stoft 2010; Rajagopal et al.

2011). Along with the tightening climate policy, the energy system will also presumably

develop towards a lower C intensity, which may decrease the future displacement benefits

of additional biomass. When DF is low, the warming payback time for a continuous

bioenergy harvest of stumps appears to be significantly high, more than 100 years when

DF is less than 0.45. Thus a high DF, or equivalently GWPbiouse close to −1, is a

prerequisite of benefits in climate change mitigation within the short or medium term.

The material use of wood appears to provide beneficial GWPbiouse factors when realistic

model parameters are used because the advantage can be taken from many substitution

components simultaneously: C sequestration into long-lived materials, the displacement

of emission-intensive materials such as concrete and displacement of fossil fuels due to

bioenergy from by-product flows.

Mitig Adapt Strateg Glob Change
The dynamics of forest biomass and terrestrial C stocks, especially in boreal and

temperate regions, is relatively slow, leading to long rotation times and a slow decay of

harvest residues. The numerical results presented in this study could mainly be generalized

to forestry in boreal regions. The continuous activity of using forest harvest residues causes

a slow reduction in dead wood and soil C pools until a new regional scale equilibrium is

attained in the future. On the other hand, when the lower equilibrium is obtained, stopping

the activity of using forest harvest residues would create a new C sink.

Observations indicate that very old forests can also be net carbon sinks (Luyssaert et al.

2008). The Finnish data on which the MOTTI stand simulator is based (Hynynen et al.

2002) reveal that the growth of the Scots pine stand could continue for a very long time, far

beyond the rotation length in present forest management practices. The growth estimate of

the old stand beyond 140 years is uncertain due to limited statistics and in reality there is

also a risk of losing the big biomass stocks due to natural disturbances.

Thus, there are obvious paradoxes in the use of boreal forest biomass in climate change

mitigation that are less relevant in regions with short forest rotations, fast growth and a

rapid decay of forest harvest residues. Although biomass use can be C neutral over the long

rotation life cycle, it is still not climate neutral. Biomass use can be sustainable in the sense

that its use at landscape level is in balance with re-growth, but it is still worse for the

climate in the short and medium term than just conservation and the use of fossil-based

resources. The results question any rapid climate benefits when increasing the use of boreal

forest biomass. However, pure conservation would lead to the loss of the renewable

resource of energy and materials in the long run and a substitute for emission-intensive and

non-renewable natural resources, and it could be considered unsustainable, at least from the

economic viewpoint.

An open question is the optimal timing of using the C sink capacity of the boreal forests

at the expense of biomass production, which should also be considered from an economic

viewpoint. One long-term option would be to target win-win steady-state strategies that

would have better substitution benefits and higher equilibrium biogenic C stocks (Pingoud

et al. 2010) than in the prevailing baseline or business as usual. The above study indicated

that the highest substitution benefits are not necessarily obtained just by maximizing

biomass production but that the quality of biomass and its usability in the displacement of

fossil emissions are of the essence.

What conclusions could be drawn from the use of long-rotation biomass as a measure in

climate change mitigation? The appropriate baseline or reference case of forest use can be

discussed and questioned. However, any change in forest use has an impact on the C

balance in time. For instance, if forests at the landscape level functioned as a C sink,

increased use of biomass would decrease the sink in the short run with respect to the

baseline, which must be taken into account in any emission scenarios. The use of forest

biomass as a renewable resource must be defended, but it is not climate neutral or C neutral

in a shorter time frame, which means that fossil emissions must be cut even further to

obtain the set emission targets.

To summarize:

1) The urgent time frame of climate change mitigation makes the timing of emissions an

issue, including biogenic C emissions from land use change and even the C balance of

sustainable forestry. The mitigation time frame is of the same magnitude as the rotation

length of slow-growing boreal forests. Harvesting a stand causes a substantial C debt,

at least in the short run, with respect to a no-harvest baseline, the climate impact of

which should be taken into account within the mitigation time frame of interest. With a

Mitig Adapt Strateg Glob Change
limited forest land area, the trade-offs between increasing wood use vs. increasing C

sequestration into forest biomass need to be noted. There is a potential dilemma

between short-term climate benefits and long-term sustainable forestry.

2) The dynamics of tectonic fossil C stocks and renewable biogenic C stocks differ from

each other. By the GWP metrics, the estimated C emissions and future removals due to

the biomass C cycle can be converted into an equivalent fossil C emission in terms of the

same cumulative warming impact within the time frame of interest. The emission-related

indicator aims to provide a simpler and more illustrative measure than just the cumulative

radiative forcing applicable as, e.g., a C footprint indicator.

3) The overall climate impacts of the forest biomass cycle are determined by the C

dynamics of forestry and those of the wood use cycle. In this article, separate GWP

factors were derived for both parts. The climate benefits of wood use can be valued

based on the amount of fossil C emissions that can be displaced. Thus, the focus is on

relative climate impact due to the wood use cycle with respect to fossil C-based

alternatives. Wood use typically increases the net warming impact in the short run with

the benefits coming later. The results emphasize the importance of efficient wood use – in

terms of high fossil C displacement and C sequestration into long-lived wood products – as

a prerequisite to short warming payback times and thus high climate benefits, which may

even reduce the time to zero.

Acknowledgements The authors wish to thank Dr Jari Hynynen from the Finnish Forest Research Institute

(Metla) and Professor Lauri Valsta from the University of Helsinki for their assistance with the simulations

with the MOTTI model. Funding from the Sustainable Energy Programme (SusEn) of the Academy of

Finland is also gratefully acknowledged.

Appendix 1. The REFUGE3 model

This appendix describes the REFUGE 3 model that was used to calculate the atmospheric

concentrations and radiative forcing. The model calculates atmospheric concentrations

and radiative forcing for CO2, CH4 and N2O. The emissions discussed in the study are

added to a background of global emission pathways that correspond to emission levels that

would reach a 450 ppm-eq concentration target by 2100. The relative shares of CO2, CH4

and N2O in this background pathway have been approximated from a number of emissionreduction scenarios.

After its release into the atmosphere, a CO2 emission impulse is assumed to decay

according to the impulse response function reported by IPCC (2007b, page 213), an

approximation based on the Bern2.5CC carbon cycle model (Joos et al. 2001). An emission

pulse, regardless of its origin, is mixed in the atmosphere and, gradually, the increase in

atmospheric concentration is transferred partially to the ocean and the biosphere. The

resulting increase in atmospheric CO2 concentration S(t) is then defined by

SðtÞ 1⁄4 Zt

t0

Eð Þt a0 þX

3

i1⁄41

aieð Þ tt =bi

 !dt ðA1Þ

where E(t) is the annual emission level and the parameters of the impulse response function are

a0=0.217, a1=0.259, a2=0.338, a3=0.186; and b1=172.9 years, b2=18.51 years and b3=

1.186 years. To improve the computability of the convolution in (A1), a recursion formula of

Pingoud and Wagner (2006) has been used.

Mitig Adapt Strateg Glob Change
In the calculations, the biogenic C emission pulse was followed by a sink due to the re-growth

of biomass. This sink reduces the level of global emissions in the REFUGE3 model and, in

principle, it is accounted for simply as a series of gradually declining negative emission impulses

in (A1). Therefore, the total concentration impact of biomass use as energy is a combination of

the emission and subsequent sinks, and the atmospheric CO2 dynamics for both the emissions

and sinks.

The atmospheric CO2 concentration C(t) then induces radiative forcing (RF), with the

expression Ramaswamy et al. (2001, p. 358)

RFðtÞ 1⁄4 a lnð Þ CðtÞ=C0 ; ðA2Þ

where C0 corresponds to the atmospheric CO2 concentration before 1850 (278 ppm assumed)

and α=5.35 W/m2

. An additional concentration pulse S(t) adds to the background

concentration Cbg(t) so that C(t)=Cbg(t)+S(t), where Cbg(t) is an generic estimate for a

global 450 ppm-eq concentration pathway. As the formula for RF is non-linear, the marginal

increase in RF from a marginal emission impulse depends on when the emission is released,

as the global background CO2 concentration varies over time. However, this effect is only

minor and the change in RF for an emission impulse released in 2000 (i.e. when the

atmospheric concentration is the lowest) is roughly 10% higher than when the impulse is

released during the latter part of the century when the concentration is highest. Therefore, our

illustrative emission impulse, released in 2010, should be applicable throughout the time

frame used with reasonable accuracy.

As an example, the cumulative radiative forcing (CRF) or AGWP calculations of the energy

use of 5 cm diameter branches (related to Fig. 1) are shown in Fig. 8. Note that when the

displacement factor DF = 0.6 and there are no fossil C emissions of the bioenergy system then

Fig. 8 Cumulative radiative forcing (CRF), i.e. AGWP, as a function of the timeframe (2010, t) for the unit

pulse emission of 1 Mg fossil C at 2010 (AGWPfos), 1 Mg of biomass C debt due to harvest of 5 cm branches at

2010 (AGWPbio) and the displaced fossil C emissions at 2010 (AGWPbiouse) when DF = 0.6. Note that

AGWPbiouse / AGWPfos = −0.6. In the simple case when fossil C emissions of the bioenergy system are zero,

the AGWP of the functionally equivalent fossil energy system is the dashed line and equal to -AGWPbiouse .

The warming payback time is the time when the AGWPbio curve cuts the AGWP curve of the functionally

equivalent fossil energy system

Mitig Adapt Strateg Glob Change
the C pulse from the fossil fuel energy system, functionally equivalent to the bioenergy

system, is 0.6 Mg C.

Appendix 2. Estimation of GWPbiouse in combined material and energy substitution

The estimation of the GWPbiouse of material substitution in this study is based on the data of

the life cycle assessment (LCA) of Häkkinen and Wirtanen (2006) in which a modern wood

office building, the research centre of the Finnish Forest Research Institute in Joensuu, was

compared with a functionally equivalent (fictional) concrete building of a conventional

design (Table 1). The numbers are thus case-specific but characterize the factors involved in

material substitution.

The GWPbiouse is estimated as follows: assuming a C content of 0.5, 305 Mg C is

sequestered in long-lived wood structures. By using wood as a construction material instead

of concrete, 597 Mg CO2eq emissions or 163 Mg C were saved. Assuming that 40% of the

stem biomass is used in the long-lived structures and the rest, 60%, — the by-product

flow – is used as bioenergy, it implies that the total stemwood consumption is equal to

763 Mg C, and the by-product flow 458 Mg C. Part of the latter goes to the energy required

for processing the wood materials and the rest can be used to displace fossil fuels

elsewhere. By assuming that all the renewable primary energy consumed in wood building

is wood-based and that the average moisture content of the by-products (bark, chips,

sawdust) is 50% with a specific heat value of 16.6 GJ/(Mg dry matter), 114 Mg dry matter

wood or 57 Mg biomass C of by-products is consumed as the internal process energy of

wood materials. Thus, 401 Mg biomass C can be used to displace fossil energy elsewhere.

Assuming DF = 0.6 for this energy substitution, 240 Mg C fossil emissions could be

displaced. Thus, the total reduction in C emissions at the year of harvest/construction would

be equal to 708 Mg C of which 43% consists of biomass C sequestered into long-lived

material, 23% of material substitution and 34% of energy substitution. The reduction would

represent 93% of the biogenic C stock of the stemwood consumed.

For illustrative purposes it is assumed that the lifetime of the building would be (just)

50 years after which the demolished wood structures would be recycled into bioenergy. If

DF at 2060 were equal to 0.6, 183 Mg C could be displaced so that the net emission would

be 122 Mg C, or 16% of the biomass C of the stemwood.

Table 1 LCA data of the wood office building of the Finnish Forest Research Institute (Metla) and of its

functionally equivalent concrete alternative (Häkkinen and Wirtanen 2006)

Wood building Concrete building

Total weight (Mg) 1920 4710

Weight of wood structures (Mg) 610 0

Non-renewable primary energy (GJ) 3460 7430

Renewable primary energy (GJ) 1880 540

Total (GJ) 5340 7970

Emissions (Mg):

Mg CO2 320 804

Mg CH4 0.63 1.27

Mg N2O 0.01 0.33

Total (Mg CO2eq) 336 933

Mitig Adapt Strateg Glob Change
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