Time-explicit life cycle optimization for transition pathways.
Current life cycle optimization tools collapse all emissions to a single point in time, hiding critical temporal interdependencies: life cycles are distributed across years or decades, and the production systems behind them are evolving. optimex jointly models both dimensions — when exchanges occur and how they change over time — to design pathways that respect time-specific and cumulative environmental constraints.
- Temporal Distribution — Maps life cycle exchanges across their actual timeframes via convolution, capturing time lags between construction, operation, and end-of-life
- Technology Evolution — Tracks vintage-dependent foreground improvements and links to prospective background databases reflecting supply chain decarbonization
- Flexible Operation — Separates capacity installation from operational dispatch, enabling vintage-specific merit order where cleaner cohorts are utilized first
- Dynamic Characterization — Retains emission timing for dynamic LCIA (e.g., Radiative Forcing, dynamic GWP), capturing how impacts accumulate over time
Time-explicit LCO reveals transition strategies invisible to static approaches:
- Strategic overcapacity — Early clean technology investment that offsets stranded fossil assets when net emission savings outweigh embodied impacts
- Vintage-specific dispatch — Emissions-aware merit order that preferentially utilizes cleaner technology cohorts
- Resource bottleneck navigation — Technology diversification driven by time-specific constraints on water, critical minerals, or other resources
- Cumulative budget compliance — Pathway verification against carbon budgets and absolute limits through exact emission timing
optimex is broadly applicable across sectors where temporal dynamics are decisive for sustainability:
- Evolving supply chains — Systems depending on electricity, steel, or hydrogen undergoing rapid decarbonization
- Early-stage technologies — Processes with significant vintage-dependent performance improvements (e.g., electrolyzers, DAC)
- Circular economy planning — Temporal mismatches between primary demand and secondary supply from long material residence times
- Time-resolved carbon accounting — Biogenic feedstocks, temporary carbon storage, or CO2 removal with varying temporal profiles
- Multi-regional supply chains — Sourcing across regions with divergent decarbonization trajectories
pip install optimexFull documentation, tutorials, and examples are available at optimex.readthedocs.io.
optimex builds on Pyomo and Brightway. For time-explicit LCA without optimization, see bw_timex.
- Timo Diepers (timo.diepers@ltt.rwth-aachen.de)
- Jan Tautorus (jan.tautorus@rwth-aachen.de)
Open an Issue or Send a Pull Request — contributions are welcome.