Dynamic LCA through temporal graph traversal: brightway2-temporalis

A library for the Brightway2 LCA calculation framework that allows for a specific kind of dynamic life cycle assessments.

Brightway2-temporalis is open source. Source code is available on bitbucket, and documentation is available on read the docs.

Brightway2-temporalis has the following abilities:

• Exchanges (technosphere inputs, and biosphere outputs) can be offset in time.
• Individual exchanges can be split into multiple time steps, creating a temporal distribution for each exchange.
• Inventory datasets can be given either relative or absolute dates and times.
• Characterization factors can vary as a function of time.
• Characterization factors can spread impact over time.

However, Brightway2-temporalis has the following limitations:

• Inventory datasets cannot change their inputs as a function of time. This limitation is necessary for the graph traversal to converge.
• Exchanges must be linear, as in normal matrix-based LCA.

See the example ipython notebook (nbviewer, html) for a real usage example.

Table of contents

• Strategy for dynamic LCA calculations
• Comparison with ESPA
  • Benefits of temporal graph traversal
  • Drawbacks of temporal graph traversal
  • Cut-off criteria
• Data formats
  • Inventory
  • Impact Assessment
• Gotchas
  • Temporal distributions sums are not checked
  • Processes with specific temporal distributions could be incorrectly excluded
• Technical guide
  • Impact Assessment methods
  • Dynamic Life Cycle Assessment
  • Timeline