AI-Powered Life Cycle Assessment for Sustainable Green Bioproducts

To equip researchers, industry professionals, and students with AI-enabled LCA skills for evaluating and improving the environmental performance of bioprocesses and biotechnology products, fostering sustainable innovation.

• Understand the principles of Life Cycle Assessment (LCA) in the context of green biotechnology.
• Explore AI and machine learning tools for environmental impact modeling and predictive analytics.
• Analyze and optimize bioprocesses for sustainability and efficiency.
• Evaluate environmental footprints of bio-based products from raw material sourcing to end-of-life.
• Integrate AI-driven insights to support eco-friendly product design and decision-making.
• Interpret LCA results to generate actionable recommendations for sustainable biotech innovation.

📅 Day 1: LCA Foundations and Bioproduct Mapping

• Introduction to Life Cycle Assessment for sustainable bioproducts
• Green biotechnology and bio-based product life cycles
• Goal and scope definition in LCA
• Functional unit and system boundary selection
• Cradle-to-gate, cradle-to-grave, and circular pathway concepts
• Life Cycle Inventory data requirements
• Supplier and value-chain data collection for LCA
• Introduction to product carbon footprinting
• Overview of AI-assisted LCA workflows

🛠️ Hands-on:

• Create a bioproduct life cycle map
• Define goal, scope, functional unit, and system boundary
• Prepare a basic Life Cycle Inventory data template

🧰 Tools Covered: Excel, OpenLCA, Python, AI-assisted LCA workflows

📅 Day 2: Carbon Footprint, Impact Assessment, and AI Prediction

• Life Cycle Inventory development
• Activity data and emission factors
• Product Carbon Footprint calculation
• Key impact categories: carbon, water, energy, waste, acidification, and eutrophication
• Hotspot identification in bioproduct life cycles
• Data quality, uncertainty, and assumptions
• Excel and Python for LCA data analysis
• Machine learning for environmental impact prediction
• Feature importance for sustainability decision-making

🛠️ Hands-on:

• Build a simplified LCI dataset
• Calculate product carbon footprint
• Create hotspot analysis charts
• Develop a simple AI/ML model for impact prediction

🧰 Tools Covered: Excel, Python, OpenLCA, Machine Learning, Data Visualization

📅 Day 3: Circularity, Digital Product Passport, and Reporting

• Scenario analysis for sustainable bioproduct design
• Bio-based vs fossil-based vs circular pathways
• End-of-life assessment: reuse, recycling, composting, biodegradation, and landfill
• Circular economy metrics for bioproducts
• Digital Product Passport for sustainability and traceability
• LCA interpretation and sustainability reporting
• Green claims validation
• Responsible use of AI tools in LCA documentation
• Mini-project: AI-powered LCA improvement proposal

🛠️ Hands-on:

• Compare alternative sustainability scenarios
• Create a circularity and end-of-life comparison sheet
• Prepare a Digital Product Passport-style template
• Draft a short LCA interpretation report

🧰 Tools Covered: Excel, OpenLCA, Python, Digital Product Passport Templates, AI Documentation Tools

• Industry Professionals in biotechnology, sustainability, or environmental management
• Academicians, Professors, and Researchers in life sciences, green chemistry, or biotech
• PhD Scholars and Postgraduate Students interested in sustainable bioprocess design and AI applications
• Professionals involved in product development, bioprocess optimization, and environmental impact assessment

• Participants will create:

  • Bioproduct life cycle map
  • Goal and scope definition sheet
  • Life Cycle Inventory template
  • Product Carbon Footprint calculation
  • Hotspot analysis chart
  • AI/ML-based impact prediction model
  • Circularity scenario comparison
  • Digital Product Passport-style template
  • Short LCA interpretation report