Life Cycle Optimization (LCO) with PULPO

PULPO is a python package for Life Cycle Optimization (LCO) based on life cycle inventories. It is intended to serve as a platform for optimization tasks of varying complexity.

The package builds on top of the Brightway LCA framework as well as the optimization modeling framework Pyomo.

✨ Capabilities

Applying optimization is recommended when the system of study has (1) many degrees of freedom which would prompt the manual assessment of a manifold of scenarios, although only the “optimal” one is of interest and/or (2) any of the following capabilities makes sense within the goal and scope of the study:

• Specify technology and regional choices throughout the entire supply chain (i.e. fore- and background), such as choices for the production technology of electricity or origin of metal resources. Consistently accounting for changes in the background in “large scale” decisions can lead to significantly different insights.

• Specify constraints on any activity in the life cycle inventories, which can be interpreted as tangible limitations such as raw material availability, production capacity, or environmental regulations.

• Optimize and/or constrain any impact category for which the characterization factors are available.

• Specify supply values instead of final demands, which can become relevant if only production values are available (e.g. here).

💬 Support

If you have any questions or need help, do not hesitate to contact us:

• Fabian Lechtenberg (fabian.lechtenberg@chem.ethz.ch)