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 their magnitudes 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

Full documentation, tutorials, and examples are available at optimex.readthedocs.io.

• Getting Started
• Examples
• API Reference

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.

BSD 3-Clause License