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Nature Climate Change | Article

National post-2020 greenhouse gas targets and diversity-aware leadership

Journal name:
Nature Climate Change
Volume:
5,
Pages:
1098–1106
Year published:
DOI:
doi:10.1038/nclimate2826
Received
Accepted
Published online

Abstract

Achieving the collective goal of limiting warming to below 2 °C or 1.5 °C compared to pre-industrial levels requires a transition towards a fully decarbonized world. Annual greenhouse gas emissions on such a path in 2025 or 2030 can be allocated to individual countries using a variety of allocation schemes. We reanalyse the IPCC literature allocation database and provide country-level details for three approaches. At this stage, however, it seems utopian to assume that the international community will agree on a single allocation scheme. Here, we investigate an approach that involves a major-economy country taking the lead. In a bottom-up manner, other countries then determine what they consider a fair comparable target, for example, either a ‘per-capita convergence’ or ‘equal cumulative per-capita’ approach. For example, we find that a 2030 target of 67% below 1990 for the EU28, a 2025 target of 54% below 2005 for the USA or a 2030 target of 32% below 2010 for China could secure a likely chance of meeting the 2 °C target in our illustrative default case. Comparing those targets to post-2020 mitigation targets reveals a large gap. No major emitter can at present claim to show the necessary leadership in the concerted effort of avoiding warming of 2 °C in a diverse global context.

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  1. Global 2025/2030 GHG emission waypoints implied by the IPCC 2[thinsp][deg]C carbon budget of 1,010 GtCO2.
    Figure 1: Global 2025/2030 GHG emission waypoints implied by the IPCC 2 °C carbon budget of 1,010 GtCO2.

    a, Historical GHG emissions and harmonized future scenarios from the IPCC AR5 scenario database (thin lines) and RCP scenarios (thick grey lines). Our default waypoints are indicated as well as a 50% reduction compared to 1990 by 2050 (60% reduction compared to 2010). b, 2030 GHG emission waypoints derived by quantile regression of GHG emissions in 2030 versus the scenarios cumulative emissions from 2012–2100—distinguishing between scenarios that imply negative fossil CO2 emissions (orange circles) or not (blue circles). c, Same as b, but for 2025 GHG emissions.

  2. Re-analysis of the IPCC allocation database and our country-level allocations in comparison for USA and China.
    Figure 2: Re-analysis of the IPCC allocation database and our country-level allocations in comparison for USA and China.

    a, Global 2025 GHG emissions relative to 2010 levels (left axis) and 1990 levels (right axis) in the IPCC allocation regime database collected in ref. 11, distinguished by their respective IPCC WG3 stabilization categories Cat0 to Cat4 (colour codes as in b). Studies that explored multiple stabilization levels are connected (grey lines). The horizontal axis shows cumulative GHG emissions between 2012 and 2049, with the range between 1.34 and 1.50 TtCO2eq (trillion tonnes CO2 eq) highlighted (grey vertical band) as the range between medians of a quantile regression at the 1,010 GtCO2 budget across the IPCC AR5 scenario database without and with negative fossil CO2 emissions, respectively. b, Same as a, but for 2030. c,d, Same as a and b, respectively, but for GHG emissions of USA and China on the y-axis (derived as ~90% fractions of the North American and East Asian regions, Supplementary Information). Colour codes as in b. e,f, Same as c and d, but complemented by extrapolation of single-stabilization level studies, and three of our country-level allocation regimes (Supplementary Information). Colour codes reflect different allocation regimes in e and f (see legend in f).

  3. Illustration of the /`diversity-aware leadership[rsquor] concept in contrast with self-differentiation.
    Figure 3: Illustration of the ‘diversity-aware leadership’ concept in contrast with self-differentiation.

    a, Self-differentiation under a joint target C leads to the collective target C being exceeded. b, A collective target enhancement could ensure the self-differentiation still achieving the collective target C. c, A ‘diversity-aware’ leadership country A could set a target so that with self-differentiation of ‘follower’ countries (committing to a ‘comparable’ level of effort under their chosen allocation approach) would still ensure achieving the collective target C. Mathematical formulation in Supplementary Information.

  4. Global GHG emissions in 2010 and allocations with respect to 2010 for 2025, if countries follow either USA, EU or China as potential leadership countries.
    Figure 4: Global GHG emissions in 2010 and allocations with respect to 2010 for 2025, if countries follow either USA, EU or China as potential leadership countries.

    a, Global 2010 GHG emissions shares by individual G20 countries or the respective remainders of IPCC’s ten world regions (each region with their distinct colour). b, 2025 GHG emissions allocations with respect to 2010 if countries follow the USA INDC announcement (here shown for an intermediate 27% reduction below 2005 by 2025). c, 2025 GHG emissions allocations, if USA assumes a ‘leadership’ 2 °C compatible target of −54% by 2025. d, 2030 GHG emissions with respect to 2010 if countries follow ‘comparable’ reductions to the EU28 target of 40% below 1990 levels. e, Same as d, in the case that the EU28 assumes a target of 67% below 1990, so that global GHG emissions are returning back to 1990 levels (22% below 2010). f, Same as d, if countries follow a potential Chinese increase of GHG emissions by 35% until 2030 with comparable targets, resulting in 33% higher global emissions by 2030 compared to 2010 levels. g, Same as e, but countries follow a 2 °C compatible leadership target of −32% by China. World emissions changes with respect to 2010 are provided at the centre of the circles for b to g.

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Author information

Affiliations

  1. Australian-German Climate & Energy College, The University of Melbourne, Parkville 3010, Victoria, Australia

    • Malte Meinshausen &
    • Yann Robiou du Pont

  2. Potsdam Institute for Climate Impact Research (PIK), Telegraphenberg, 14412 Potsdam, Germany

    • Malte Meinshausen,
    • Louise Jeffery &
    • Johannes Guetschow

  3. Energy Program, International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361 Laxenburg, Austria

    • Joeri Rogelj

  4. Institute for Atmospheric and Climate Science, ETH Zurich, Universitaetsstrasse 16, CH-8092 Zurich, Switzerland

    • Joeri Rogelj

  5. Climate Analytics, 10969 Berlin, Germany

    • Michiel Schaeffer

  6. New Climate Institute, D-50667 Cologne, Germany

    • Niklas Höhne

  7. Environmental Systems Analysis Group, Wageningen University, PO Box 47, 6700 AA Wageningen, The Netherlands

    • Niklas Höhne

  8. PBL Netherlands Environmental Assessment Agency, 3720 AH Bilthoven, The Netherlands

    • Michel den Elzen

  9. Institute for European Studies, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium

    • Sebastian Oberthür

  10. Seminar für Statistik, ETH Zurich, Rämistrasse 101, 8092 Zürich, Switzerland

    • Nicolai Meinshausen

Contributions

All authors contributed to interpreting the results and writing the manuscript. M.M. designed the study and performed the calculations. Y.R.d.P. assisted in data management. N.M. provided the quantile regression method. J.R. compared the 2025 and 2030 waypoints to the UNEP GAP Report estimates. L.J. programmed the GDR allocation approach and J.G. downscaled RCP emissions scenarios using SSP data to the national level for the RCPs. L.J. and J.G. contributed the composite PRIMAP4 data (Supplementary Information). M.d.E. and N.H. compiled the allocation database used in IPCC. M.S. complemented the IPCC AR5 scenario database emissions pathways with missing gases.

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The authors declare no competing financial interests.

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