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NDCmitiQ: a tool to quantify and analyse GHG mitigation targets

Günther, Annika; Gütschow, Johannes; Jeffery, M. Louise

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Content

  • Use of the software and output data, and support

  • Abstract

  • Notes

  • Target types

  • Share of emissions covered by an NDC

  • Quantification options, output files, and data format description

  • Data sources

  • Changelog

Use of the software and output data, and support

Before using the software NDCmitiQ, please read this document and the article describing the methodology. The article will be referenced here as soon as it is published.

Please notify us (annika.guenther@pik-potsdam.de) if you use the software or output data so that we can keep track of how it is used and take the information into consideration when updating and improving the software.

When using the software or output data (or one of its updates), please cite the DOI of the precise version. Please consider also citing the relevant original data sources when using the output data (see data sources section).

If you encounter possible errors or other things that should be noted or need support in using the software or output data or have any other questions regarding NDCmitiQ, please contact annika.guenther@pik-potsdam.de, or open an issue in the corresponding GitHub-repository.

Abstract

This software can be used to quantify emissions mitigation targets stated in the Nationally Determined Contributions (NDCs). The output includes national targets and emissions pathways and globally aggregated mitigated emissions pathways. Several quantification options are available, including, i.a., the five marker scenarios of the Shared Socioeconomic Pathways (SSPs) as baseline trajectories.

Notes

For details on how to run NDCmitiQ, please refer to the README.md-file in the main directory. Additional information is provided in the files requirements.txt, and /docs/build/html/index.html.

Please note that for members of the EU NDC, the single quantifications are based on assumed equal contributions by member states, and can therefore only be used as aggregated EU-wide emissions.

Target types

The following target types are distinguished in NDCmitiQ:

  • ABS: ABSolute target emissions

  • RBY: Relative reduction compared to Base Year

  • ABU: Absolute reduction compared to Business-as-Usual

  • RBU: Relative reduction compared to Business-as-Usual

  • AEI: Absolute Emissions Intensity target

  • REI: Relative reduction in Emissions Intensity compared to a base year or target year

  • NGT: Non-GHG Target (assuming baseline emissions)

Share of emissions covered by an NDC

We assessed the covered sectors and gases and derived estimates of the share of national emissions covered by an NDC. The data is stored in csv-files in the folder /data/preprocess/pc_cov_yyyymmdd_hhmm/ (calculation: /py_files/preprocessing_current_pc_cov.py).

Quantification options, output files, and data format description

NDCmitiQ contains several quantification options (i.a., regarding the input time series, or the prioritised target type). More details are available in /py_files/MODIFY_INPUT_HERE/input_DEFAULT_with_EXPLANATIONS.py. Here, the output is included for runs with different options (see /data/output/output_for_paper/, about 1min20s per run), with one folder per run. The folder name structure begins with ndcs_yyyymmdd_hhss_, followed by, e.g.:

  • SSP1 to SSP5: which SSP marker scenario is chosen for the run. This information is also important if the run is based on NDC emissions data (type_reclass), as not for all countries emissions data were provided, and the SSP baselines are used for the pathway construction.

  • typeMain: runs with type_main (main target type stated in the NDC), based on external emissions data (PRIMAP-hist v2.1 HISTCR and down-scaled SSP marker scenarios).

  • typeReclass: runs with type_reclass (reclassified target type, e.g., if the country has a base year target, but provides a quantification of the target emissions it can be reclassified as an absolute target), based on emissions data from the NDCs where possible.

  • pccov100: runs with an assumed coverage of 100%. Without pccov100: coverage based on estimated %cov (calculated from covered sectors and gases stated in the NDC and emissions data per sector and gas).

  • constEmiAfterLastTar: runs with assumed constant emissions after a Party’s last target year. Without constEmiAfterLastTar: instead of the emissions, the relative difference to the baseline is kept constant after the last target year.

  • BLForUCAboveBL: runs using the baseline emissions as the unconditional pathways for Parties without unconditional targets, even if the baseline is better than the conditional targets. Without BLForUCAboveBL: conditional worst pathway is used in this case instead of the baseline.

  • UNFCCC / FAO: runs using LULUCF (Land Use, Land-Use Change and Forestry) data with UNFCCC or FAO chosen as the primary prioritised data source (UNFCCC, CRF, BUR, FAO or FAO, CRF, BUR, UNCFFF). Without UNFCCC / FAO: prioritisation is CRF, BUR, UNFCCC, and FAO.

Per run, the single per-country targets can be found in ndc_targets.csv, the country-pathways are available in ndc_targets_pathways_per_country_used_for_group_pathways.csv, and the aggregated pathways are stored in ndc_targets_pathways_per_group.csv. Additionally, each of the folders contains the file log_file.md (information on the setup for the model run), and the sub-folder /per_country_info_on_target_calculations/ that provides per-country information on how exactly the national targets were quantified. The input that can easily be modified is: time series of emissions (exclLU and onlyLU), %cov (exclLU), population, and GDP, and information from the NDCs (exclLU: emissions excluding contributions from LULUCF, onlyLU: LULUCF emissions, GDP: Gross Domestic Product).

Data sources

The following data sources are used in the NDCmitiQ:

  • Downscaled RCP scenarios data

  • PRIMAP-hist v2.1 data

  • PRIMAP-hist SocioEco v2.1 data

  • PRIMAP-crf 2019 data

  • UNFCCC Nationaly Inventory Submissions 2019 data

  • BUR submissions data

  • EDGAR version 4.3.2 data, paper

  • FAOSTAT data

Changelog

Current version: contributions submitted prior to 17th April 2020.

Note: please do not consider the folder /data/other/.

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