Editing IPCC:AR6/WGIII/Chapter-10 (section)

=== Box 10.2 | Bridging Land Use and Feedstock Conversion Footprints for Biofuels ===

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Under specific conditions, biofuels may represent an important climate mitigation strategy for the transport sector ( [[#Daioglou--2020|Daioglou et al. 2020]] ; [[#Muratori--2020|Muratori et al. 2020]] ). Both the IPCC Special Report on Global Warming of 1.5°C and the IPCC Special Report on Climate Change and Land highlighted that biofuels could be associated with climate mitigation co-benefits and adverse side effects to many SDGs. These side effects depend on context-specific conditions, including deployment scale, associated land-use changes and agricultural management practices ( [[IPCC:Wg3:Chapter:Chapter-7#7.4.4|Section 7.4.4]] and Box 7.10). There is broad agreement in the literature that the most important factors in determining the climate footprint of biofuels are the land use and land-use change characteristics associated with biofuel deployment scenarios ( [[#Elshout--2015|Elshout et al. 2015]] ; [[#Daioglou--2020|Daioglou et al. 2020]] ). This issue is covered in more detail in Box 7.1. While the mitigation literature primarily focuses on the GHG-related climate forcings, note that land is an integral part of the climate system through multiple geophysical and geochemical mechanisms (albedo, evaporation, etc.). For example, Sections 2.2.7 and 7.3.4 in the AR6 WGI report indicate that geophysical aspects of historical land-use change outweigh the geochemical effects, leading to a net cooling effect. The land-related carbon footprints of biofuels presented in Sections 10.4–10.6 are adopted from [[IPCC:Wg3:Chapter:Chapter-7|Chapter 7]] ( [[IPCC:Wg3:Chapter:Chapter-7#7.4.4|Section 7.4.4]] , Box 7, and Figure 7.1). The results show how the land-related footprint increases due to an increased outtake of biomass, as estimated with different models that rely on global supply scenarios of biomass for energy and fuel of 100 exajoules (EJ). The integrated assessment models and scenarios used include the EMF 33 scenarios (IAM-EMF33), from partial models with constant land cover (PM-CLC), and from partial models with natural regrowth (PM-NGR). These results are combined with both biomass cultivation emission ranges for advanced biofuels aligned with [[#Koeble--2017|Koeble et al. (2017)]] , [[#El%20Akkari--2018|El Akkari et al. (2018)]] , [[#Jeswani--2020|Jeswani et al. (2020)]] , and [[#Puricelli--2021|Puricelli et al. (2021)]] and conversion efficiencies and conversion phase emissions as described in Table 10.5. The modelled footprints resulting from land-use changes related to delivering 100 EJ of biomass at global level are in the range of 3–77 gCO 2 -eq per MJ of advanced biofuel (median 38 gCO 2 -eq MJ –1 ) at an aggregate level for Integrated Assessment Models (IAMs) and partial models with constant land cover ( [[#Daioglou--2020|Daioglou et al. 2020]] ; [[#Rose--2020|Rose et al. 2020]] ). The results for partial models with natural regrowth are much higher (91–246 CO 2 -eq MJ –1 advanced biofuel). The latter ranges may appear in contrast with the results from the scenario literature in [[#10.7|Section 10.7]] , where biofuels play a role in many scenarios compatible with low warming levels. This contrast is a result of different underlying modelling practices. The general modelling approach used for the scenarios in the AR6 database accounts for the land-use change and all other GHG emissions along a given transformation trajectory, enabling assessments of the warming level incurred. The results labelled ‘EMF33’ and ‘partial models with constant land cover’ are obtained with this modelling approach. The results in the category ‘partial models with natural regrowth’ attribute additional CO 2 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. While the partial analysis provides insights into the implications of alternative land-use strategies, such analysis does not identify the actual emissions of bioenergy production. As a result, the partial analysis is not compatible with the identification of warming levels incurred by an individual transformation trajectory, and therefore not aligned with the general approach applied for the scenarios in the AR6 database.

More details on land-use change impacts and the potential to deliver the projected demands of biofuels at the global level are further addressed in Chapter 7. While, in general, the above results cover most of the variety of GHG range intensities of biofuel options presented in the literature, the more specific life cycle assessment (LCA) literature should be consulted when considering specific combinations of biomass feedstock and conversion technologies in specific regions.

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