REMIND-MFA

REMIND-MFA includes top-down prospective material flow analysis (MFA) models for the basic materials cement, plastics, and steel. It is designed to provide material demands and flows for the integrated assessment model REMIND, and to provide global context for the scenario analysis in the TRANSIENCE project.

REMIND-MFA has global coverage. Per default, it runs in 21 world regions. However, due to its flexible design and madrat-based data input, both regional and temporal resolution can be adapted easily.

Installation

REMIND-MFA dependencies are managed with uv.

To install, clone the repository and run

uv sync

from the repository's main directory. This installs the project together with some development dependencies. For a minimal installation, you can run uv sync --no-dev instead.

For development, it may be convenient to check out the flodym repository in the same parent directory as remind-mfa and uncomment the tool.uv.sources section in pyproject.toml to point to the local flodym repository. This will install flodym in editable mode, allowing you to use and test local changes to flodym.

If you prefer pip, you can still use it as a fallback:

python -m pip install .

Run

To run a model, run

uv run run_remind_mfa.py [path to config]

from the main directory, where [path to config] is the path to a configuration file, such as config/steel.yml.

You can change parameters for the run in these configuration files located in the config folder.

Currently, all implemented models require data which is not part of the repository, such that running the models will yield an error.

The data required to run the models is planned to be made accessible in the near future.

If you have access to the PIK cluster, you can obtain the data as follows:

• Clone the data repository into the same parent directory as remind-mfa:

git clone https://gitlab.pik-potsdam.de/simson_data/remind_mfa_data.git

• Set the environment variable MADRAT_OUTPUTFOLDER to a folder where the madrat output data should be stored (it can be a relative path), e.g., export MADRAT_OUTPUTFOLDER=madrat_output. Alternatively, you can set the environment variable in a .env file in the main directory of the repository.
• If you're not running remind-mfa on the cluster, then copy the madrat output data to the local madrat folder by running

uv run scripts/copy_madrat_archive.py config/steel.yml <hpc> /p/projects/rd3mod/inputdata/output_1.27

where <hpc> is the ssh address/alias of the PIK cluster.

Acknowledgements

We gratefully acknowledge funding from the TRANSIENCE project, grant number 101137606, funded by the European Commission within the Horizon Europe Research and Innovation Programme, from the Kopernikus-Projekt Ariadne through the German Federal Ministry of Education and Research (grant no. 03SFK5A0-2), and from the PRISMA project funded by the European Commission within the Horizon Europe Research and Innovation Programme under grant agreement No. 101081604 (PRISMA).