AI-Powered Life Cycle Assessment for Sustainable Green Bioproducts
Harness AI to Optimize Bioprocesses and Design Sustainable Bio-Based Products
- ModeVirtual / Online
- LevelAdvanced
- Fee₹2,499
About Workshop
This workshop introduces AI-driven Life Cycle Assessment (LCA) in green biotechnology, teaching participants to evaluate and optimize environmental impacts from bioprocess design to sustainable products. Through case studies and hands-on exercises, attendees will apply AI tools for process optimization and sustainability analysis to make data-driven, eco-friendly decisions.
Aim
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.
What Participants Will Learn
- 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.
Structure
📅 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
📅 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
📅 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
Important Dates
Registration Ends
5: 30 PM IST
Workshop Dates
2026-07-15
06:30 PM IST
06:30 PM IST
What You Will Gain
Outcomes
-
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
Who Should Attend
- 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