Brightcon 2025, hackathon & courses in Grenoble and online

This study applies a combination of prospective and time-explicit life cycle assessment (LCA) to evaluate Ocean Alkalinity Enhancement (OAE) via Bipolar Membrane Electrodialysis (BPMED), an emerging carbon dioxide removal (CDR) technology. By combining prospective and time-explicit LCA, we developed a flexible, time- and location oriented LCA framework which captures both evolving background systems and the delayed, time-distributed nature of atmospheric CO₂ uptake, a key to accurately reflecting the environmental performance of OAE over time.
The methodological workflow integrates Brightway for core LCA modeling, Premise to generate future background scenarios based on the SSP2-RCP2.6 integrated assessment pathway, and a combination of Temporalis and Timex to structure foreground system changes and conduct time-explicit impact calculations. The cradle-to-grave analysis quantifies the environmental impacts of 1 tonne of CO₂-equivalent removal across ten global locations, incorporating a 2.5% annual learning rate for BPMED electricity consumption and location-specific decarbonization trajectories.
Results indicate that overall impact significantly decreases over time, reflecting the projected decarbonization of energy systems and background processes as projected by integrated assessment models (IAMs). Key carbon hotspots like precipitation softening remain dominant contributors throughout the period, as their chemical processes are mostly not addressed in IAMs. The integration of spatial analysis with prospective LCA reveals that regions like China undergo substantial reductions in climate intensity over time, while consistently low-carbon regions such as the Nordics exhibit smaller relative changes but maintain the lowest overall impacts throughout the study period.
This open-source setup provides a reproducible, interoperable framework aligned with industrial ecology principles, enabling detailed exploration of how both technological and systemic changes shape future environmental outcomes.