Editing IPCC:AR6/SRCCL/Chapter-2 (section)

=== 2.6.3 The contribution of response options to the Paris Agreement ===

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The previous sections indicated how land-based response options have the potential to contribute to the Paris Agreement, not only though reducing anthropogenic emissions but also for providing anthropogenic sinks that can contribute to “…a balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases in the second half of this century…” (Paris Agreement, Article 4). The balance applies globally, and relates only to GHGs, not aerosols (Section 2.4) or biophysical effects (Section 2.5).

The Paris Agreement includes an enhanced transparency framework to track countries’ progress towards achieving their individual targets (i.e., nationally determined contributions (NDCs)), and a global stocktake (every five years starting in 2023), to assess the countries’ collective progress towards the long-term goals of the Paris Agreement. The importance of robust and transparent definitions and methods (including the approach to separating anthropogenic from natural fluxes) (Fuglestvedt et al. 2018 <sup>[[#fn:r1910|1910]]</sup> ), and the needs for reconciling country GHG inventories and models (Grassi et al. 2018a <sup>[[#fn:r1911|1911]]</sup> ), was highlighted in Section 2.3 in relation to estimating emissions. Issues around estimating mitigation is also key to transparency and credibility and is part of the Paris Rulebook.

The land sector is expected to deliver up to 25% of GHG mitigation pledged by countries by 2025–2030 in their NDCs, based on early assessments of ‘Intended’ NDCs submitted ahead of the Paris Agreement and updates immediately after ( ''low confidence'' ) (Grassi et al. 2017 <sup>[[#fn:r1912|1912]]</sup> ; Forsell et al. 2016 <sup>[[#fn:r1913|1913]]</sup> ). While most NDCs submitted to date include commitments related to the land sector, they vary with how much information is given and the type of target, with more ambitious targets for developing countries often being ‘conditional’ on support and climate finance. Some do not specify the role of AFOLU but include it implicitly as part of economy-wide pledges (e.g., reducing total emission or emission intensity), a few mention multi-sectoral mitigation targets which include AFOLU in a fairly unspecified manner. Many NDCs include specific AFOLU response options, with most focused on the role of forests. A few included soil carbon sequestration or agricultural mitigation and a few explicitly mentioned bioenergy (e.g., Cambodia, Indonesia and Malaysia), but this could be implicitly included with reduced emissions in energy sectors through fuel substitution (see Cross-Chapter Box 7 and Chapter 6 for discussion on cross sector flux reporting). The countries indicating AFOLU mitigation most prominently were Brazil and Indonesia, followed by other countries focusing either on avoiding carbon emissions (e.g., Ethiopia, Gabon, Mexico, DRC, Guyana and Madagascar) or on promoting the sink through large afforestation programmes (e.g., China, India) (Grassi et al. 2017 <sup>[[#fn:r1914|1914]]</sup> ).

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'''Figure 2.28'''

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'''Global LULUCF net GHG flux for the historical period and future scenarios based on analyses of countries’ NDCs.The LULUCF historical data (blue solid line) reflect the following countries’ documents (in order of priority): (i) data submitted to UNFCCC (NDCs, 2015 GHG Inventories and recent National Communications ), (ii) other official countries’ documents, (iii) FAO-based datasets […]'''
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[[File:397d59e962853b3a03e2aeffc1d6652e Figure-2.28-1024x604.jpg]]

Global LULUCF net GHG flux for the historical period and future scenarios based on analyses of countries’ NDCs.The LULUCF historical data (blue solid line) reflect the following countries’ documents (in order of priority): (i) data submitted to UNFCCC (NDCs <sup>[[#fn:4|4]]</sup> , 2015 GHG Inventories <sup>[[#fn:5|5]]</sup> and recent National Communications <sup>[[#fn:6|6]]</sup> <sup>[[#fn:7|7]]</sup> ), (ii) other official countries’ documents, (iii) FAO-based datasets (i.e., FAO-FRA for forest (Tian et al. 2015)) as elaborated by (Federici et al. 2015), and (iv) FAOSTAT for non-forest land use emissions (FAO 2015). The four future scenarios reflect official countries’ information, mostly intended NDCs or updated NDCs available at the time of the analysis (Feb 2016), complemented by Biennial Update Reports <sup>[[#fn:8|8]]</sup> and National Communications, and show (i) the BAU scenario as defined by the country, (ii) the trend based on pre-NDC levels of activity (current policies in place in countries), and (iii) the unconditional NDC and conditional NDC scenarios. The shaded area indicates the full range of countries’ available projections (min-max), expressing the available countries’ information on uncertainties beyond the specific scenarios shown. The range of historical country datasets (dotted lines) reflects differences between alternative selections of country sources, in essence, GHG inventories for developed countries complemented by FAO-based datasets (upper range) or by data in National Communications (lower range) for developing countries.

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Figure 2.28 shows the CO <sub>2</sub> mitigation potential of NDCs compared to historical fluxes from LULUCF. <sup>[[#fn:3|3]]</sup> It shows future fluxes based on current policies in place and on country-stated Business As Usual (BAU) activities (these are different from current policies as many countries are already implementing polices that they do not include as part of their historical business-as-usual baseline) (Grassi et al. 2017). Under implementation of unconditional pledges, the net LULUCF flux in 2030 has been estimated to be a sink of –0.41 ± 0.68 GtCO <sub>2</sub> yr <sup>–1</sup> , which increases to –1.14 ± 0.48 GtCO <sub>2</sub> yr <sup>–1</sup> in 2030 with conditional activities. This compares to net LULUCF in 2010 calculated from the GHG Inventories of 0.01 ± 0.86 GtCO <sub>2</sub> yr <sup>–1</sup> (Grassi et al. 2017 <sup>[[#fn:r1915|1915]]</sup> ). Forsell et al. (2016) <sup>[[#fn:r1916|1916]]</sup> similarly find a reduction in 2030 compared to 2010 of 0.5 GtCO <sub>2</sub> yr <sup>–1</sup> (range: 0.2–0.8) by 2020 and 0.9 GtCO <sub>2</sub> yr <sup>–1</sup> (range: 0.5–1.3) by 2030 for unconditional and conditional cases.

The approach of countries to calculating the LULUCF contribution towards the NDC varies, with implications for comparability and transparency. For example, by following the different approaches used to include LULUCF in country NDCs, Grassi et al. (2017) <sup>[[#fn:r1917|1917]]</sup> found a three-fold difference in estimated mitigation: 1.2–1.9 GtCO <sub>2</sub> -eq yr <sup>–1</sup> when 2030 expected emissions are compared to 2005 emissions, 0.7–1.4 GtCO <sub>2</sub> -eq yr <sup>–1</sup> when 2030 emissions are compared to reference scenarios based on current policies or 2.3–3.0 GtCO <sub>2</sub> -eq yr <sup>–1</sup> when compared to BAU, and 3.0–3.8 GtCO <sub>2</sub> -eq yr <sup>–1</sup> when based on using each countries’ approach to calculation stated in the NDC (i.e., when based on a mix of country approaches, using either past years or BAU projections as reference).

In exploring the effectiveness of the NDCs, SR15 concluded “[e]stimates of global average temperature increase are 2.9°–3.4°C above preindustrial levels with a greater than 66% probability by 2100” (Roberts et al. 2006 <sup>[[#fn:r1918|1918]]</sup> ; Rogelj et al. 2016 <sup>[[#fn:r1919|1919]]</sup> ), under a full implementation of unconditional NDCs and a continuation of climate action similar to that of the NDCs. In order to achieve either the 1.5°C or 2°C pathways, this shortfall would imply the need for submission (and achievement) of more ambitious NDCs, and plan for a more rapid transformation of their national energy, industry, transport and land use sectors (Peters and Geden 2017 <sup>[[#fn:r1920|1920]]</sup> ; Millar et al. 2017 <sup>[[#fn:r1921|1921]]</sup> ; Rogelj et al. 2016 <sup>[[#fn:r1922|1922]]</sup> ).

Response options relying on the use of land could provide around a third of the additional mitigation needed in the near term (2030) to close the gap between current policy trajectories based on NDCs and what is required to achieve a 2°C (&gt;66% chance) or 1.5°C (50–66% chance) pathway according to the UNEP Emissions Gap Report (Roberts et al. 2006 <sup>[[#fn:r1923|1923]]</sup> ). The report estimates annual reduction potentials in 2030 from agriculture at 3.0 (2.3–3.7) GtCO <sub>2</sub> -eq yr <sup>–1</sup> , a combination of ‘uncertain measures’ (biochar, peat-related emission reductions and demand-side management) at 3.7 (2.6–4.8) GtCO <sub>2</sub> -eq yr <sup>–1</sup> ; forests at 5.3 (4.1–6.5) GtCO <sub>2</sub> -eq yr <sup>–1</sup> , bioenergy at 0.9 GtCO <sub>2</sub> -eq yr <sup>–1</sup> and BECCS at 0.3 (0.2–0.4) GtCO <sub>2</sub> -eq yr <sup>–1</sup> (UNEP 2017 <sup>[[#fn:r1924|1924]]</sup> ) (Table 4.1). These response options account for 35% of potential reduction (or 32% without bioenergy and BECCS) out of a total (all sector) potential of 38 (35–41) GtCO <sub>2</sub> -eq yr <sup>–1</sup> . The potentials estimated in the UNEP Emissions Gap Report are based on the technical potential of individual response options from literature including that presented in Section 2.1. CDR related to land use, while not a substitute for strong action in the energy sector, has the technical potential to balance unavoidable emissions that are difficult to eliminate with current technologies ( ''high confidence'' ), with early action avoiding deeper and more rapid action later ( ''very high confidence'' ) (Strefler et al. 2018 <sup>[[#fn:r1925|1925]]</sup> ; Elmar et al. 2018 <sup>[[#fn:r1926|1926]]</sup> ; SR15).

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