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Python class regionalizing processes from the ecoinvent database using trade date from the UN COMTRADE database and common sense.

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Regioinvent

Regioinvent is a Python package for automatically connecting the ecoinvent database to BACI, a trade database.

Connecting to a trade database enables a more realistic description of average supply chains within the ecoinvent database through the introduction of consumption markets, based on international import data and production data. The result is a version of ecoinvent which almost does not rely on non-national processes such as RER, RoW or GLO.

Furthermore, since the resulting regionalized version of ecoinvent relies much less on broad regions, the regionalization of impacts can show its full potential. Therefore, Regioinvent also fully spatializes all relevant elementary flows and connects these spatialized elementary flows to regionalized life cycle impact assessment methods. Currently, only the IMPACT World+ LCIA method is available. Later on, we plan on adding ReCiPe and EF as well.

Showcase

To showcase what Regioinvent does, let's illustrate on an example: the production of diethanolamine in Sweden. The production of diethanolamine in ecoinvent is also available for RER and RoW.

Screenshot below shows the starting point of this example: the diethanolamine production process for Europe.

After running Regioinvent three types of processes are created.

  1. National production processes

Below you can see the example for the Swedish production but the code also created such production processes for many countries.

  1. National consumption markets

Below you can see the example for the Swedish consumption market but the code also created such consumption markets for many countries.

  1. A global export market

The global export market shows the biggest exporters of the commodity worldwide.

Regioinvent in your LCAs

Use the three types of processes generated with Regioinvent as follows:

  • If you know where the production of your commodity occurs, select the corresponding national production process. Either for the location exactly, or, if unavailable, the RoW version which is an aggregate of all the countries not being in the biggest producers.
  • If you don't know where the production of your commodity occurs, BUT you know where it was bought, rely on the consumption markets. These describe where the commodity should come from on average, given the trade of the region.
  • If you don't know anything about the process, you can either use the RoW or GLO process of ecoinvent, or rely on the global export process of Regioinvent as a proxy. Note however that it is an export market. It does not include the domestic production in the shares of that market.

Get started

To get started you can git clone this repository or simply download it.

You will need a few things to get started:

  • Have an ecoinvent license (obviously)
  • Download the BACI database that was already extracted. You can download it from here
  • Install brightway2 and have a brightway2 project with either ecoinvent3.9.1 cut-off or ecoinvent3.10 cut-off

Note that regioinvent currently only supports the ecoinvent 3.9.1/3.10 cut-off version and operates solely on brightway2 (NOT brightway2.5).

You can then follow the steps presented in the demo.ipynb Jupyter notebook.

Required python version: 3.11

How to use after running the code?

Once the regionalized version of ecoinvent is created on Python, you can export it to brightway2. You will then be able to perform your LCAs either through brightway2 or its GUI activity-browser as you would with the regular ecoinvent database.
Do note that calculations are longer with Regioinvent (~5 to 10 minutes calculation for the first run).
There are currently no support for other LCA software, as SimaPro and openLCA are not able to support the size of the database.

Overview of the methodology

  1. Closest available process in ecoinvent is copied and adapted for electricity, heat and waste inputs
  2. National consumption markets are created based on import and production data
  3. The national consumption markets are connected to the rest of the database
  4. Elementary flows are spatialized

For the detailed methodology, take a look at the Methodology.md file.

Adaptations

Support

Contact maxime.agez@polymtl.ca

Citation

Citing the code (take the correct version): https://doi.org/10.5281/zenodo.11836126
Citing the article: article currently in review
Citing BACI: Gaulier, G. and Zignago, S. (2010) BACI: International Trade Database at the Product-Level. The 1994-2007 Version. CEPII Working Paper, N°2010-23.

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Python class regionalizing processes from the ecoinvent database using trade date from the UN COMTRADE database and common sense.

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