Training day on scenario-based LCA and prospective LCA: hands-on with wurst and premise

This repository holds the teaching material for the training day on wurst and premise dispensed at the Sustainable Systems Research Group (SSRG) at the University of Toronto, as well as at the Spring School in Quebec City.

Course objectives

The objective of this course is to provide an introduction to the LCA methodology and the tools used to perform it. The course will be divided in four parts:

1. Introduction to the wurst library.
2. Introduction to the premise library.
3. Practical session on scenario-based and prospective LCA.
4. If time allows, we will introduce the activity-browser library.

Course description

This course will introduce participants to prospective and scenario-based LCA, software to conduct it and large-scale manipulation of LCA databases. Hence, the course is divided in three parts.

The first part will be an introduction to the wurst library, which is a python library used to operate large-scale modification on LCA databases.

The second part will be an introduction to the premise library, which is a python library used to create and operate prospective LCA database based on IAM scenarios.

The third part will be a practical session where the participants will be able to build their own prospective scenarios using the premise library.

The fourth part will be an introduction to the activity-browser library, which is a graphical user interface for brightway.

Contact

In case of questions or issues with the instructions below, please contact: Romain Sacchi

License

Unless otherwise specified, all material in this repository is licensed under the BSD 3-clause license. See the LICENSE file for more information.

Requirements

We ask the participants to download and install Anaconda (or the Python environments manager of your choice) and Git before the course:

• Anaconda: https://www.anaconda.com/products/distribution
• Git: https://git-scm.com/downloads

Also, please download a copy of the ecoinvent database:

• go to https://ecoinvent.org/
• Login to ecoinvent v.3
• Files > Version 3.9.1 > ecoinvent 3.9.1_cutoff_ecoSpold02.7z

Unzip the file and place the folder in a location of your choice. You may download a different version of the database (3.7, 3.8), according to your current license (although choose the "cut-off by classification" system model).

Instructions

Once you have installed Anacoda on your computer, you may consider installing the libmamba solver in conda, for faster environment resolution. Open the terminal (Anaconda terminal in Windows) and run the following commands:

  conda install -n base conda-libmamba-solver
  conda config --set solver libmamba

Clone this repository onto your computer by running the following command in the terminal:

  git clone https://github.com/romainsacchi/wurst-premise-training-2024.git

Morning session

For the morning part of the course, we will use the wurst library. Hence, we ask the participants to install the wurst library and dependencies by running the corresponding conda recipe found under `environments/wurst_environment.yaml.

Using the terminal, navigate to the environments folder and run the following command:

  conda env create -f wurst_environment.yaml

This will create a conda environment called wurst with all the required dependencies.

Afternoon session

For the afternoon part of the course, we will use the premise library.

Using the terminal, navigate to the environments folder and run the following command:

  conda env create -f premise_environment.yaml