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

== 7.7 Knowledge Gaps ==

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Closing knowledge gaps and narrowing uncertainties are crucial to advance AFOLU mitigation. Knowledge gaps exist across a range of areas, from emissions accounting and mitigation measure development to integration of scientific and traditional knowledge and development and sustainable implementation strategies. The following are identified as priorities:

• Uncertainty in contemporary emissions and sinks within AFOLU is still high. There is ongoing need to develop and refine emission factors, improve activity data and facilitate knowledge exchange, concerning inventories and accounting. For example, insufficient knowledge on CO 2 emissions relating to forest management and burning or draining of organic soils (wetlands and peatlands), limits certainty on CO 2 and CH 4 fluxes.

'''•''' Improved monitoring of the land CO 2 balance is urgently needed, including impacts of land degradation and restoration efforts (e.g., in tropical and boreal regions), making use of combined remote sensing, artificial intelligence, ground-based and modelling tools ( [[#Grassi--2021|Grassi et al. 2021]] ). Improved estimates would provide more reliable projections of nationally determined contributions to emissions reduction and enhancement of sinks, and reconciliation of national accounting and modelling results ( [[#Nabuurs--2019|Nabuurs et al. 2019]] ).

'''•''' The future impacts of climate change on land systems are highly uncertain, for example, the role of permafrost thaw, tipping points, increased disturbances and enhanced CO 2 fertilisation ( [[#Friedlingstein--2020|Friedlingstein et al. 2020]] ). Further research into these mechanisms is critical to better understand the permanence of mitigation measures in land sector.

'''•''' There is need to understand the role of forest management, carbon and nitrogen fertilisation and associated interactions in the current forest carbon sink that has emerged in the last 50 to 70 years. These aspects are likely to explain much of the difference between bookkeeping models and other methodologies.

'''•''' Continued research into novel and emerging mitigation measures and associated cost efficiency (e.g., CH 4 inhibitors or vaccines for ruminants) is required. In addition to developing specific measures, research is also needed into best practice regarding implementation and optimal agricultural land and livestock management at regional and country level. Further research into the feasible mitigation potential of sustainable intensification in terms of absolute GHG emissions and appropriate policy mechanisms, is required to implement and advance this strategy.

'''•''' Research into accounting systems and policy options that will enable agricultural soil and forest carbon to be utilised as offsets (voluntary or regulatory) is needed to increase financing for land-based CDR. Design of incentives that consider local institutions and novel frameworks for cooperation between private finance and public governance can encourage investment. Equally, research to adjust or remove regulations and subsidy schemes that may hamper land-based mitigation efforts, is urgently required.

'''•''' Improving mitigation potential estimates, whether derived from sectoral studies or IAMs to account for biophysical climate effects, and impacts of future climate change (e.g., mitigation permanence), biodiversity loss and corresponding feedbacks is needed. IAM ‘usability’ can be enhanced by integrating a wider set of measures and incorporating sustainability considerations.

'''•''' Research into the feasibility of improving and enhancing sustainable agricultural and forestry value chains, provision of renewable products (building with wood) and the sustainability of bioenergy is critically important. Modelled scenarios do not examine many poverty, employment and development trade-offs, which are highly context specific and vary enormously by region. Trade-off analysis and cost-benefit analysis can assist decision-making and policy.

• In-depth understanding of mitigation-SDG interactions is critical for identifying mitigation options that maximise synergies and minimise trade-offs. Mitigation measures have important synergies, trade-offs and co-benefits, impacting biodiversity and resource-use, human well-being, ecosystem services, adaptation capacity and many SDGs. In addition to exploring localised economic implementation costs, studies are needed to understand how measures will impact and interact with wider environmental and social factors across localities and contexts.

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