Submitted as: model description paper 21 Jan 2021

Submitted as: model description paper | 21 Jan 2021

Review status: this preprint is currently under review for the journal GMD.

NDCmitiQ v1.0.0: a tool to quantify and analyse GHG mitigation targets

Annika Günther1, Johannes Gütschow1, and Mairi Louise Jeffery2 Annika Günther et al.
  • 1Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 601203, D-14412 Potsdam, Germany
  • 2NewClimate Institute, Schönhauser Allee 10–11, 10119 Berlin, Germany

Abstract. Parties to the Paris Agreement (PA, 2015) outline their planned contributions towards achieving the PA temperature goal to hold [...] the increase in the global average temperature to well below 2 °C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C (Article 2.1.a, PA) in their Nationally Determined Contributions (NDCs). Most NDCs include targets to mitigate national greenhouse gas (GHG) emissions, which need quantifications to assess, i.a., whether the current NDCs collectively put us on track to reach the PA temperature goals or the gap in ambition to do so. We implemented the new open-source tool NDCmitiQ to quantify GHG mitigation targets defined in the NDCs for all countries with quantifiable targets on a disaggregated level, and to create corresponding national and global emissions pathways. In light of the five-year update cycle of NDCs and the global stocktake, the quantification of NDCs is an ongoing task for which NDCmitiQ can be used, as calculations can easily be updated upon submission of new NDCs. In this paper, we describe the methodologies behind NDCmitiQ and quantification challenges we encountered by addressing a wide range of aspects, including: target types and the input data from within NDCs; external time series of national emissions, population, and GDP; uniform approach vs. country specifics; share of national emissions covered by NDCs; how to deal with the Land Use, Land-Use Change and Forestry (LULUCF) component and the conditionality of pledges; establishing pathways from single year targets. For use in NDCmitiQ, we furthermore construct an emissions data set from the baseline emissions provided in the NDCs. Example use cases show how the tool can help to analyse targets on a national, regional, or global scale, and to quantify uncertainties caused by a lack of clarity in the NDCs. Results confirm that the conditionality of targets and assumptions on economic growth dominate uncertainty in mitigated emissions on a global scale, which are estimated as 49.2–55.7 Gt CO2 eq AR4 for 2030 (10th/90th percentiles, median: 52.4 Gt CO2 eq AR4; excl. LULUCF and bunker fuels). We estimate that 77 % of global 2017 emissions were emitted from sectors and gases covered by current NDCs (excl. the USA).

Annika Günther et al.

Status: open (until 18 Mar 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2020-392', Anonymous Referee #1, 16 Feb 2021 reply
  • RC2: 'Comment on gmd-2020-392', Anonymous Referee #2, 17 Feb 2021 reply
  • CEC1: 'Comment on gmd-2020-392', Juan Antonio Añel, 03 Mar 2021 reply
    • AC1: 'Reply on CEC1', Annika Günther, 05 Mar 2021 reply

Annika Günther et al.

Data sets

NDCmitiQ: a tool to quantify and analyse GHG mitigation targets (Version v1.0.0) Annika Günther, Johannes Gütschow, and M. Louise Jeffery

Model code and software

NDCmitiQ: a tool to quantify and analyse GHG mitigation targets (Version v1.0.0) Annika Günther, Johannes Gütschow, and M. Louise Jeffery

Annika Günther et al.


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Short summary
The mitigation components of the Nationally Determined Contributions (NDCs) under the Paris Agreement are essential in our fight against climate change. Regular updates with increased ambition are requested, to limit global warming to 1.5–2 °C. The new and easy to be updated open-source tool NDCmitiQ can be used to quantify the NDCs' mitigation targets and construct resulting emissions pathways. In use cases, we show target uncertainties from missing clarity, data, and methodological challenges.