Portfolios selected the best mix of regionally differentiated scenarios for each of the three implementation levels, but these levels were developed independently for each scenario and their different ranges may affect their ranking. It is advantageous to generalize the existing results so that we can estimate the net change in GHG emissions for any implementation level within the modeled range. Figure 4a shows the dos070 cumulative mitigation potential (default implementation level, high substitution benefits) for each region plotted against the absolute value of the cumulative change in harvested wood (including roundwood and residues) relative parship zaloguj siÄ™ to the baseline, and although the regions differed in size and harvesting activity, there was a well-defined relationship for most scenarios. 4b, Additional file 1: Table S7) resulted in very similar regressions, indicating the cumulative mitigation potential could be estimated from the change in harvested wood (relative to the baseline). Slopes from the log–log regressions were close to -1 for the Higher Recovery scenario (between ? 0.5 and ? 1.2 for other scenarios), indicating a 1 MtCO2 increase in cumulative harvested wood in 2070 resulted in a change (relative to the baseline) of ? 1 MtCO2e in cumulative emissions in 2070. The Bioenergy scenario had the greatest variation amongst the regions, which was caused by the degree to which available biomass for bioenergy could meet the local heat demand and substitute high-emissions fossil fuels (See Additional file 2). Normalized net GHG reductions, defined as the net change in cumulative GHG emissions divided by the cumulative change in harvested wood for the Higher Recovery scenario were ? 1 for all implementation levels in most regions, while other scenarios had more regional variability (Additional file 1: Figure S5). (more…)
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