Quantification of NDC GHG target emissions (NDCmitiQ)

NDC: Nationally Determined Contribution. GHG: Greenhouse Gas.

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• Quantification of the NDC GHG mitigation target emissions per country, and the national emissions pathways and aggregated global emissions pathways.
• Per country the un-/conditional best/worst target emissions are calculated.
• Target emissions are calculated using the NDC emissions data when available (type_reclass) or one can perform comparison runs with other input data (type_main).
• Emissions are calculated in- or excluding LULUCF, depending on a Party's NDC, and the opposite case is derived from this quantified target.
• The information that we retrieved from within the NDCs is stored in /data/input/infos_from_ndcs_default.xlsx.
• The preprocessing is based on output from the MATLAB-based PRIMAP Emissions Module. The output and preprocessed data are available in the repository. If one has access to the MATLAB PRIMAP Emissions and Climate Modules, after running NDCmitiQ, one can estimate the end-of-century warming from the constructed emissions pathways.
• We hope that in the future it will be possible for a broader community to use the entire suite of tools, not only NDCmitiQ. This needs a porting and open-sourcing of the functionalities from MATLAB to Python.

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How-to for different steps of the modeling chain from baseline data over mitigated emissions pathways to temperature estimates

If you have access to the MATLAB-based PRIMAP Emissions Module you can do the following (get the baseline data from the PRIMAP Emissions Module Database):

• In the PRIMAP Emissions Module run ndcs_get_all_data_agu.m to write out all the tables needed for the quantifications from the PRIMAPDB to /data/preprocess/matlab_tables as csv-files. These tables are available in the repository, so one can skip this step.
• Open a python console and go to the folder py_files (all of the following is run using python3):
  • Run preprocessing_general.py to create the input needed for the quantifications. It is saved in /data/preprocess/preprocess. The preprocessed data are available in the repository.
  • Run preprocessing_current_pc_cov.py, which will store the tables with the covered part of emissions per country in /data/preprocess/pc_cov_yyyymmdd_hhmm. The preprocessed data are available in the repository.
  • Put the new folder-name preprocess_yyyymmdd_hhmm into setup_metadata.py (folder_preprocess = 'preprocess_yyyymmdd_hhmm').

If you do not have access to the MATLAB tools, you can do the following (running NDCmitiQ, code can be run without catching the input data from the MATLAB-based PRIMAP Emissions Module, as the input tables are stored in the repository).

• Open a python console and go to the folder py_files (all of the following is run using python3):

  • Go to /MODIFY_INPUT_HERE and copy the file input_default.py and adjust it as you wish. What can be modified are the following input parameters (for more detail please check input_DEFAULT_with_EXPLANATIONS.py):

    • Chose SSP marker scenario (for additional down-scaled SSP scenarios one would need to do further implementations)
    • Chose for which countries to calculate the targets (else: baseline emissions used)
    • Which target type(s) to prioritise
    • Prioritisaton of emissions baselines from NDCs or from the SSPs
    • Set coverage to 100% (for certain / all countries)
    • How to extend the emissions pathways after last target year (constant_percentages or constant_emissions)
    • Whether to use the baseline as unconditional pathway even if the baseline lies below the conditional pathway (for countries without unconditional target)
    • Strengthen targets by a certain percentage
    • Define groups for which the aggregated pathways should be calculated

  • Go to _to_be_run.py and put in the input-file(s) that you wish to work with (main_ndc_quantifications('input_default', '')) and run python3 _to_be_run.py.

    Or using Spyder with a Python 3 console, with the work-path \ndc_quantifications\py_files run from main_ndc_quantifications import main_ndc_quantifications and then main_ndc_quantifications('input_default', '').

  • The output (emissions targets per country, per-country pathways, global pathways) is stored in /data/output/.

If you have access to the MATLAB-based PRIMAP Emissions and Climate Module you can do the following:

• After the calculations are finished, one can estimate end of the century temperatures using the Matlab PRIMAP Emissions Module and Climate Module (calculate_NDC_impacts_agu.m).

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Further information can be found in /docs/build/html/index.html or /docs/build/latex/ndcmitiq.pdf (produced with /py_files/additional_scripts/make_documentation.py).

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The python code is stored in a Spyder project (/py_files/*).

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Information on the national emissions and targets based on emissions data provided in the NDCs is stored in /py_files/ndcs__target_calculations_for_input_xlsx/, containing single .py-files per country. Here, e.g., (i) the target emissions are calculated if a country provides baseline emissions in the NDC, or (ii) the LULUCF emissions for a year are calculated if an NDC gives the emissions inclLU and exclLU, or (iii) the baseline emissions are calculated from single sectoral emissions, if the sum is not provided, and (iv) further similar calculations are performed.

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When modifying and adding folders and files in the repository, please consider the following:

• When adding a new folder in /py_files or its sub-folders, and if the new folder contain .py-files that should be available to the module, please add a __init__.py file (empty, or containing code such as from .file_name import function_name, with the file_name being the .py-file name in which a function is stored, and function_name being the function name, defined by def function_name(variables)).
• When adding a new file or folder that should only be available locally on your machine and not in the online repository, add a .gitingore file including the files / folders that should be ignored. If you add a new folder with .py-files, please add a .gitingore file containing /__pycache__/* to ignore the folder __pycache__ that will be produced when running your code.
• In .py-files stored in /py_files/, and the sub-folders /preprocessing/, /main_functions/, and /MODIFY_INPUT_HERE/, please use the following code for comments that should be included in the documentation: """\ncomment\n""" (\n denotes a new line). To check which functions are considered in the documentation go to /py_files/additional_scripts/make_documentation.py (files = [...]).

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When changing code, data, etc., please consider whether information on the changes should be included in the changelog for an updated release on zenodo zenodo. Check and update the content of /zenodo/document_for_zenodo_updates.md and use the content of this file as field "description" on zenodo for a new zenodo-release. Then save a copy of the file with the version number of the release.