Brightcon 2026, hackathon and courses

Highlights

• Integration of the edges Python library into the BONSAI open-source
  framework for spatialized LCIA.
• Demonstrates how exchange-based LCIA
  enables geographically explicit impact assessment beyond global
  averages.
• Case study: quantifying how French consumption drives
  water scarcity in producer regions worldwide. Fully reproducible,
  open-source workflow supporting transparency and collaborative
  development.
• Provides a pathway to identify supply chain hotspots
  and policy-relevant environmental pressures using a fully open
  workflow.
• Concise Description

Concise Description

The growing need for geographically explicit Life Cycle Assessment (LCA) has highlighted the limitations of conventional impact assessment methods based on global average characterization factors. This study addresses these challenges by integrating the exchange-based Life Cycle Impact Assessment (LCIA) methodology (Sacchi et al., 2025) into the BONSAI framework, an open-source environmentally extended input-output database.

The approach is implemented using the Python library “edges”, enabling spatially explicit, context-sensitive, and scenario-based environmental assessments. Unlike traditional LCIA approaches, the exchange-based method accounts for the geographic origin of traded goods and intermediate exchanges, allowing the calculation of region-specific characterization factors that incorporate local environmental conditions (e.g., water scarcity) and supply chain dependencies.

The framework is applied to a case study of French consumption, focusing on water scarcity impacts embodied in global supply chains. By combining BONSAI consumption inventories, based on input–output modelling, which provides a robust representation of international trade flows and country-level demand, with edges-based LCIA methods, the study identifies critical regions and sectors contributing to water stress. This approach enables a more nuanced and geographically explicit understanding of environmental pressures linked to consumption.

This session demonstrates a reproducible workflow based on open-source tools (Python, BONSAI, edges), fostering transparency and enabling participants to extend the case study to other countries within their own practice. The work reflects the Brightcon spirit by promoting openness, methodological transparency, and collaborative development of LCA tools. Therefore also a notebook will be provided where participants can follow along and try themselves to start using edges with BONSAI data.