Editing IPCC:AR6/WGIII/Chapter-7 (section)

=== Box 7.7 | Climate Change Mitigation Value of Bioenergy and BECCS ===

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Besides emissions, and possible avoided emissions, related to the supply chain, the GHG effects of using bioenergy depend on: (i) change in GHG emissions when bioenergy substitutes another energy source; and (ii) how the associated land use and possible land-use change influence the amount of carbon that is stored in vegetation and ( [[#Calvin--2021|Calvin et al. 2021]] ) soils over time. Studies arrive at varying mitigation potentials for bioenergy and BECCS due to the large diversity of bioenergy systems, and varying conditions concerning where and how they are deployed (Elshout 2015; Harper et al.2018; [[#Muri--2018|Muri 2018]] ; Kalt et al.2019; [[#Brandão--2019|Brandão et al. 2019]] ; [[#Buchspies--2020|Buchspies et al. 2020]] ; [[#Cowie--2021|Cowie et al. 2021]] ; [[#Calvin--2021|Calvin et al. 2021]] ). Important factors include feedstock type, land management practice, energy conversion efficiency, type of bioenergy product (and possible co-products), emissions intensity of the products being displaced, and the land use/cover prior to bioenergy deployment ( [[#Zhu--2017|Zhu et al. 2017]] ; [[#Staples--2017|Staples et al. 2017]] ; [[#Daioglou--2017|Daioglou et al. 2017]] ; [[#Carvalho--2017|Carvalho et al. 2017]] ; [[#Hanssen--2020|Hanssen et al. 2020]] ; [[#Mouratiadou--2020|Mouratiadou et al. 2020]] ). Studies arrive at contrasting conclusions also when similar bioenergy systems and conditions are analysed, due to different methodologies, assumptions, and parametrization (Harper et al.2018; Kalt et al.2019; [[#Brandão--2019|Brandão et al. 2019]] ; Albers et al. 2019; [[#Buchspies--2020|Buchspies et al. 2020]] ; [[#Bessou--2020|Bessou et al. 2020]] ; [[#Rolls--2020|Rolls and Forster 2020]] ; [[#Cowie--2021|Cowie et al. 2021]] ).

Box 7.7, Figure 1 shows emissions associated with biomass supply (residues and crops grown on cropland not needed for food) in 2050, here designated emission-supply curves. The curves are constructed assuming that additional biomass supply consistently comes from the available land/biomass resource that has the lowest GHG emissions, for example, the marginal GHG emissions increase with increasing biomass use for bioenergy. Net negative emissions indicate cases where biomass production increases land carbon stocks.

One curve ( ''EMF-33'' ) is determined from stylised scenarios using IAMs ( [[#Rose--2020|Rose et al. 2020]] ). One of the two curves determined from sectoral models, ''Constant Land Cover'' , reflects supply chain emissions and changes in land carbon storage caused by the biomass supply system itself. These two curves are obtained with modelling approaches compatible with the modelling protocol used for the scenarios in the AR6 database, which accounts for the land-use change and all other GHG emissions along a given transformation trajectory, enabling assessments of the warming level incurred.

The ''Natural Regrowth'' curve attribute additional ‘counterfactual emissions’ to the bioenergy system, corresponding to estimated uptake of CO 2 in a counterfactual scenario where land is not used for bioenergy but instead subject to natural vegetation regrowth. This curve does not show actual emissions from the bioenergy system, but it provides insights in the mitigation value of the bioenergy option compared to alternative land-use strategies. To illustrate, if biomass is used instead of a primary energy source with emission factor 75 kgCO 2 GJ –1 , and the median values in the ''Natural Regrowth'' curve are adopted, then the curve indicates that up to about 150 EJ of biomass can be produced and used for energy while achieving higher net GHG savings than the alternative to set aside the same land for natural vegetation regrowth (assuming same conversion factor).

The large ranges in the bars signify the importance of uncertainties and how the biomass is deployed. Variation in energy conversion efficiencies and uncertainty about magnitude, timing, and permanence of land carbon storage further complicate the comparison. Finally, not shown in Box 7.7, Figure 1, the emission-supply curves would be adjusted downwards if displacement of emission intensive energy was included or if the bioenergy is combined with CCS to provide CDR.

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[[File:aca3a6d32b1ece26214b2545cb95dc9a IPCC_AR6_WGIII_Box_7_6_Figure_1.png]]
[[File:3e30f559ddbc39ff17217954b9448502 IPCC_AR6_WGIII_Box_7_7_Figure_1.png]]

'''Box 7.7, Figure 1 |''' '''Emissions associated with primary biomass supply in 2050 (residues and crops grown on cropland not needed for food), as determined from sectoral models (Daioglou et al. 2017; Kalt et al. 2020), and stylised scenarios from the EMF-33 project using Integrated Assessment Models (Rose et al. 2020).''' All methods include LUC (direct and indirect) emissions. Emissions associated with Natural Regrowth include counterfactual carbon fluxes (see text). The sectoral models include a more detailed representation of the emissions, including lifecycle emissions from fertiliser production. IAM models may include economic feedbacks such as intensification as a result of increasing prices. As an indication: for natural gas the emission factor is around 56, for coal around 95 kgCO 2 GJ –1 .

'''Critical assessment and conclusion''' ''.'' Recent estimates of technical biomass potentials constrained by food security and environmental considerations fall within previous ranges corresponding to ''medium agreement'' , (e.g., [[#Turner--2018b|Turner et al. 2018b]] ; [[#Daioglou--2019|Daioglou et al. 2019]] ; [[#Wu--2019|Wu et al. 2019]] , Hansen et al.2020; [[#Kalt--2020|Kalt et al. 2020]] ) arriving at 4–57 and 46–245 EJ yr –1 by 2050 for residues and dedicated biomass crops, respectively. Based on studies to date, the technical net CDR potential of BECCS (including LUC and other supply chain emissions, but excluding energy carrier substitution) by 2050 is 5.9 (0.5–11.3) GtCO 2 yr –1 globally, of which 1.6 (0.5–3.5) GtCO 2 yr –1 is available at below USD100 tCO 2 –1 ( ''medium confidence)'' ( [[#Lenton--2010|Lenton 2010]] ; [[#Koornneef--2012|Koornneef et al. 2012]] ; [[#McLaren--2012|McLaren 2012]] ; [[#Powell--2012|Powell and Lenton 2012]] ; [[#Fuss--2018|Fuss et al. 2018]] ; [[#Turner--2018a|Turner et al. 2018a]] ; [[#Hanssen--2020|Hanssen et al. 2020]] ; [[#Roe--2021|Roe et al. 2021]] ) (Figure 7.11). The equivalent economic potential as derived from IAMs is 1.8 (0.2–9.9) GtCO 2 yr –1 (Table 7.3).

Technical land availability does not imply that dedicated biomass production for bioenergy and BECCS is the most effective use of this land for mitigation. Further, implications of deployment for climate change mitigation and other sustainability criteria are context dependent and influenced by many factors, including rate and total scale. While governance has a critical influence on outcome, larger scale and higher expansion rate generally translates into higher risk for negative outcomes for GHG emissions, biodiversity, food security and a range of other sustainability criteria (Searchinger 2017; [[#Vaughan--2018|Vaughan et al. 2018]] ; [[#Rochedo--2018|Rochedo et al. 2018]] ; [[#de%20Oliveira%20Garcia--2018|de Oliveira Garcia et al. 2018]] ; [[#Daioglou--2019|Daioglou et al. 2019]] ; [[#Junginger--2019|Junginger et al. 2019]] ; Galik et al. 2020; [[#Stenzel--2020|Stenzel et al. 2020]] ).

However, literature has also highlighted how the agriculture and forestry sectors may respond to increasing demand by devising management approaches that enable biomass production for energy in conjunction with supply of food, construction timber, and other bio-based products, providing climate change mitigation while enabling multiple co-benefits including for nature conservation ( [[#Nabuurs--2017|Nabuurs et al. 2017]] ; [[#Parodi--2018|Parodi et al. 2018]] ; [[#Springmann--2018|Springmann et al. 2018]] ; [[#Rosenzweig--2020|Rosenzweig et al. 2020]] ; [[#Clark--2020|Clark et al. 2020]] ; [[#Favero--2020|Favero et al. 2020]] ; [[#Hanssen--2020|Hanssen et al. 2020]] ) ( [[#7.4|Section 7.4]] and Cross-Working Group Box 3 in Chapter 12).

Strategies to enhance the benefits of bioenergy and BECCS include (i) management practices that protect carbon stocks and the productive and adaptive capacity of lands, as well as their environmental and social functions ( [[#van%20Ittersum--2013|van Ittersum et al. 2013]] , [[#Gerssen-Gondelach--2015|Gerssen-Gondelach et al. 2015]] ; [[#Moreira--2020b|Moreira et al. 2020b]] ) (ii) supply chains from primary production to final consumption that are well managed and deployed at appropriate levels ( [[#Fajardy--2018|Fajardy et al. 2018]] ; [[#Donnison--2020|Donnison et al. 2020]] ); and (iii) development of a cross-sectoral agenda for bio-based production within a circular economy, and international cooperation and governance of global trade in products to maximise synergies while limiting trade-offs concerning environmental, economic and social outcomes ( ''very high confidence'' ). Finally, the technical feasibility of BECCS depends on investments in and the roll-out of advanced bioenergy technologies currently not widely available ( [[#Baker--2015|Baker et al. 2015]] ; Daioglou et al. 2020b).

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