Assessing the merits of bioenergy by estimating marginal climate-change impacts

The baseline for the bioenergy scenario was a carbon-rich forest that maintained a high and steady level of carbon stocks (Fig. 1a). Although the forest was not sequestering any additional carbon, the large existing carbon store constituted a valuable environmental asset. In 2010, with the start of the bioenergy scenario, this forest was harvested, with 75 % of above-ground biomass burnt for bioenergy use, whilst 25 % of biomass were assumed to be unsuitable for harvesting and collection and were, instead, left as slash on the forest floor from where it slowly decayed over subsequent years. This included stumps, bark, leaves, cones and small branches and twigs. Soil carbon was assumed not to be affected by forest management (Johnson and Curtis 2001).

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When trees are harvested, their roots die and start to decay, with rates of decay and consequent carbon loss depending on species and environmental conditions. Coarse roots can typically account for 20–30 % of total tree biomass (Mokany et al. 2006). After harvesting the old forest, new trees were planted for a new forest rotation. After some time, here assumed to be 25 years, the new rotation forest could also be harvested, and the sequence could repeat itself. It was assumed that forest growth was sustainable in the sense that each rotation could achieve the same growth rate and carbon sequestration as the preceding one.

Figure 1 thus represents all changes to the carbon cycle that resulted from the decision to convert an established but non-productive forest into one used for bioenergy production. This firstly included changes at the stand level in various pools that responded to harvesting and subsequent regrowth, above-ground biomass, live and dead roots and slash on the forest floor. The wood available at each harvest could be used as bioenergy source. Without the use of bioenergy, end-use energy would have been generated from the use of fossil fuels, leading to an ongoing depletion of this global reservoir. Compared with that baseline, the saving of fossil fuels through substitution by bioenergy constituted a positive difference. From an atmospheric perspective, that saving was equivalent to carbon accumulation in a physical pool. It is therefore represented in Fig. 1a in the same units as the various stand-level pools. This is a useful way of using common units and a single diagram to summarise all relevant changes resulting from a bioenergy project.

Following Kirschbaum (2003b), the calculations here assumed a 50 % substitution efficiency. It means that 1 tC in harvested biomass could generate the same amount of end-use energy as could be generated by using 0.5 tC of fossil fuel. This value accounts for conversion efficiencies and all associated carbon emissions and energy losses incurred in the production chain of both fossil fuels and bioenergy. The 50 % substitution efficiency used here was relevant to one specific combination of the relevant factors. The usefulness of using bioenergy would be assessed differently under different conditions characterised by different substitution efficiencies. However, the present work focuses on the methodology that can be used for assessing the usefulness of bioenergy use. The parameters used here are simply an example selected to illustrate the application of the relevant accounting methodology.

The carbon contained in all forest carbon pools plus cumulative fossil-fuel savings could then be summed to result in the net carbon flux that ultimately affected atmospheric concentrations (Fig. 1b). Under the assumptions made here, there was no net biospheric carbon flux before the stand was harvested as the stand was assumed to have a zero carbon balance, and there was no fossil-fuel substitution. When the forest’s use for bioenergy began, 90 tC was initially burnt for bioenergy use. That was offset by a 45 tC ha⁻¹ saving through fossil-fuel substitution resulting in a net emission of 45 tC ha⁻¹.

In subsequent years, there was a further carbon efflux to the atmosphere from decaying slash and coarse roots. That efflux was balanced by carbon gain through the regrowth of new wood. At the end of the first rotation, the cumulative carbon balance nearly reached the zero line when the stand-level growth of new biomass carbon added to previous fossil-fuel savings. The next harvest turned the system into carbon deficit again, but from the end of the second rotation, the accruing fossil-fuel savings had shifted the system towards an overall positive carbon balance. It became negative immediately after each harvest, but from the fourth harvest onwards, it retained a positive carbon balance even through the periods immediately after each harvest.

The combined changes in stand-level carbon stocks plus fossil-fuel savings then constituted the combined CO₂ load to the atmosphere. Changes in atmospheric CO₂ concentrations (Fig. 2a) largely mirrored stand-level carbon changes (Fig. 1b), but the magnitude of changes was slightly reduced through global-carbon cycle feedback (Joos et al. 2013).

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In essence, any increase in atmospheric CO₂ concentration increases the effective concentration difference between the atmosphere and other global carbon reservoirs, principally the oceans. That increased concentration difference increases CO₂ uptake by the oceans and reduces the amount remaining in the atmosphere. The addition of 1 tC to the atmosphere, therefore, leads to an eventual increase in atmospheric CO₂ by less than 1 tC. Changes in atmospheric CO₂ concentrations are therefore smaller than the underlying changes in stand-level carbon stocks (Korhonen et al. 2002; Kirschbaum 2003a, b).

These changes in atmospheric CO₂ concentration then cause radiative forcing (Fig. 2b), but the proportionality between CO₂ concentration and radiative forcing diminishes over time because radiative efficiency of CO₂ diminishes with increasing background CO₂ concentrations (Reisinger et al. 2011). This is further illustrated in Fig. 3, which shows radiative efficiency of CO₂, defined as the radiative forcing per unit of atmospheric CO₂, over the next 100 years under four different RCPs. Under RCP 6, radiative efficiency approximately halved over the next 100 years, with an even larger change under RCP 8.5. Reducing radiative efficiency significantly affects the warming calculated under future CO₂ concentrations.

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Radiative forcing was then summed over 100 years to generate a simple estimate of the effect of the chosen bioenergy scenario (Fig. 2c). Different sums were obtained for calculations done with constant background CO₂ concentrations (as is done for GWP calculations) and under changing background concentrations according to RCP 6. This pattern resulted because bioenergy use increased radiative forcing over the first 50 years and reduced radiative forcing over the next 50 years (Fig. 2b). As radiative efficiency decreased with increasing background CO₂ concentrations (Fig. 3), it diminished the importance of the negative radiative forcing over the second 50-year period compared to that of the increased radiative forcing over the first 50-year period. Calculations under constant background CO₂ concentrations therefore resulted in lower cumulative radiative forcing than calculations that included changing radiative efficiency with changing background concentrations (Fig. 2c).

Impacts related directly to temperature are the relevant measure for impacts such as heat waves and other extreme weather events. The rate of warming relates to impacts such as maladaptation of both natural and socio-economic systems, with slower rates of change allowing time for migration or other adjustments, whilst faster rates of change provide less scope for adjustments and equate to more severe impacts. Cumulative warming is related to impacts such as sea level rise, because sea level rise is related to both the magnitude of warming and the duration over which oceans and ice sheets are exposed to increased temperatures (see Kirschbaum 2014 for further discussion).

Radiative forcing (Fig. 2b) changed surface temperatures (Fig. 4a), from which rates of warming (data not shown) and cumulative warming (Fig. 4b) could be derived. Temperature changes followed radiative forcing but with additional delays due to the thermal inertia of the global climate system. Bioenergy use thus added to global warming over the first 50 years due to the large initial carbon loss, followed by cooling over the subsequent 50 years as cumulative fossil-fuel substitution increasingly began to dominate the combined carbon balance (see Fig. 1).

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That initial warming led to a broad peak in cumulative warming from about 2050 to 2070 (Fig. 4b). Subsequent cooling from about 2070 reduced cumulative warming, but it remained positive to the end of the 100-year assessment period. The patterns of temperature change and cumulative warming were similar to radiative forcing (Fig. 2b) and cumulative radiative forcing (Fig. 2c), respectively, but peaks were smoothed and shifted towards later periods by the thermal inertia of the global climate system. Thermal inertia also caused cumulative warming to remain positive up to 2110 (Fig. 4b), even though cumulative radiative forcing had already become negative by then (Fig. 2c).

The perturbations in temperature (Fig. 4a), rate of warming (data not shown) and cumulative warming (Fig. 4b) were then used to calculate impacts at corresponding times. However, units of additional perturbations had different impacts under different background conditions (Fig. 5). In essence, when background conditions are relatively mild, any marginal perturbation has little marginal impact, but when background conditions are more severe, the same marginal perturbation can have a proportionately much larger impact. Marginal warming impacts increased sharply over the 100-year assessment period, especially under RCP 8.5 (Fig. 5a). Changes were less extreme under RCP 6, but marginal impacts per unit of warming still increased more than sixfold between 2010 and 2109, whilst changes under RCP 4.5 were only moderate.

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Under higher RCPs, any marginal temperature change in the latter part of the next 100 years, therefore, had a much greater overall impact than the same marginal temperature change over the earlier parts of the next 100 years. This was important as bioenergy use in the specific illustrative scenario shown here effectively traded warming in one period against cooling in another. The pattern was even more extreme for cumulative-warming impacts than for direct-warming impacts, with the sensitivity of marginal impacts increasing more steeply towards the end of the assessment period (Fig. 5b). There were strong increases in marginal impacts from marginal increases in cumulative warming even under RCP 3. These increases in cumulative warming occurred because even though temperatures might stabilise under RCP 3, they are expected to stabilise at a level above pre-industrial values. This continued elevation of temperature continued to add to cumulative warming, leading to increasing sensitivity of marginal impacts to any further cumulative warming even under RCP 3.

For the calculation of marginal impacts at different times, the shape of the impact-perturbation relationship is thus critically important. Whilst it is generally accepted that impacts increase more than proportionately with their underlying perturbations, there is no consensus on the steepness of that relationship (Nordhaus 1994; Hammitt et al. 1996; Roughgarden and Schneider 1999; Tol 2012; Weitzman 2012, 2013; Lemoine and McJeon 2013; Kirschbaum 2014). For the work shown here, a relatively steep perturbation-impact function (a cubic relationship) was used to reflect the strongly non-linear nature of climate-change impacts (Weitzman 2012, 2013).

The shape of the perturbation-impact function therefore has a strong bearing on future impact assessments. A steep perturbation-impact relationship shifts the importance of extra warming to times when background temperatures are already high. This has also been shown to have a strong influence on the relative importance of CH₄ and CO₂, with steeper perturbation-impact relationships increasing the relative importance of long-lived greenhouse gases (Kirschbaum 2014). The steepness of the perturbation-impact relationship also influenced the marginal impacts caused by emissions/removals at different times. As bioenergy use affects the timing of emissions and removals, changing impact sensitivity has a strong bearing on ultimate calculated marginal impacts.

Calculated temperature changes (from Fig. 4) were then combined with relative impacts per units of warming (from Fig. 5) to calculate marginal impacts under the bioenergy scenario over the next 100 years for each of the three distinct kinds of climatic impacts (Fig. 6). Marginal impacts were primarily driven by positive or negative temperature changes (Fig. 4), but their magnitude was modified by changing marginal impact sensitivity over time (Fig. 5).

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Consequently, even though the warming caused by the carbon release from the initial harvest was greater than the cooling calculated at the end of the 100-year period (Fig. 4a), the impact of the later cooling was about five times as large as the warming impact over the first two rotations. Rate-of-warming impacts followed a similar pattern, but positive and negative impacts were more similar because their impact sensitivity is not expected to increase as steeply as those underlying direct-warming impacts because of lesser changes in the underlying perturbations (data not shown).

Cumulative-warming impacts remained positive to the end of the 100-year assessment period (Fig. 6). Even though the cumulative warming attributable to the bioenergy project was decreasing sharply by the end of the century (Fig. 4b), its impact was still increasing up to about 2095 because its marginal impact sensitivity increased more strongly (Fig. 5b) than the decrease in the underlying perturbation.

Under the base conditions (RCP 6, I = P³), total radiative forcing was increased by the equivalent of burning only enough fossil-fuel carbon to produce just 1 tCO₂ in 2010. That means that the extra radiative forcing over the first 50 years through the loss of forest biomass was almost exactly balanced by the negative radiative forcing through accumulating fossil-fuel substitution benefits over the second 50-year period (Fig. 2b, c). The effect became more positive under higher-concentration RCPs because radiative efficiency decreased more sharply under higher RCPs (Fig. 3), rendering the later period of negative radiative forcing less effective than under lower RCPs.

In terms of direct-temperature and rate-of-warming impacts, the bioenergy scenario reduced impacts under the base conditions by the equivalent of −49 and −33 tCO₂ ha⁻¹, respectively. Even though the 100-year sum of radiative forcing was virtually unchanged under the bioenergy scenario, warming impacts were reduced because the cooling occurred at a time with much greater marginal impact sensitivity to changes in the underlying perturbations. This pattern was further heightened under higher-concentration RCPs because the increase in marginal impact sensitivity became stronger under higher background concentrations (Fig. 5).

In contrast to direct-temperature and rate-of-warming impacts, cumulative-warming impacts increased under the bioenergy scenario, with an increase in impacts by the equivalent of about 50 tCO₂ ha⁻¹ with similar values under all RCPs and impact-perturbation relationships (Table 1). The calculated impact was relatively insensitive to the underlying RCP because highest cumulative warming occurred at an intermediate length of time (Fig. 4b) so that the positive and negative effects of increasing impact sensitivity over time largely cancelled out in the calculation of total cumulative-warming impacts.

Taking an average of the three individual impacts (CCIPs; Kirschbaum 2014) resulted in a combined impact that ranged from increasing impacts by the equivalent of 26 tCO₂ ha⁻¹ under RCP 3 to reducing them by −20 tCO₂ ha⁻¹ under RCP 8.5, and with impacts becoming more negative with increasing steepness of the perturbation-impact relationship. The changes in CCIPs with RCPs and steepness in the impact-perturbation relationship were due to changes in direct-warming and rate-of-warming impacts, whilst cumulative-warming impacts changed little with RCP or steepness of the impact-perturbation relationship.

These differences are important because they show that an assessment of the merits of bioenergy must be made within the context of specific assumptions about likely background future concentration pathways. The same bioenergy option may increase climate-change impacts under a sustainable concentration pathway whilst usefully helping to reduce impacts under higher-concentration pathways. Similarly, the bioenergy scenario will increase impacts if an appropriate impact-perturbation relationship is judged to be fairly flat (I = P²), given that warming and cooling at different times contribute similarly to the total. If a steep relationship (I = P⁴) is used, instead, it would be concluded that bioenergy can usefully reduce impacts because the cooling contribution towards the end of the 100-year assessment period is weighted more heavily than the warming contribution at the beginning of the period.