📅 Day 1: Digital LCA Foundations, Environmental Data and Open-Source LCA Workflows
- Importance of Life Cycle Assessment in sustainability research, ESG reporting, product design, and climate decision-making
- Core LCA phases: goal and scope definition, life-cycle inventory, impact assessment and interpretation
- Cradle-to-grave, cradle-to-gate, gate-to-gate and circular life-cycle boundaries
- Environmental indicators: carbon footprint, energy use, water use, emissions, waste, toxicity and resource depletion
- Introduction to open-source LCA tools and databases for academic and industry applications
- Data quality, assumptions, allocation, system boundaries and uncertainty in LCA studies
- Role of digital LCA in sustainable product development, green manufacturing and environmental policy
🛠️ Hands-on:
- Hands-on 1: Professional LCA Model Exploration using openLCA
- Hands-on 2: Environmental Impact Data Exploration and Visualization
🧰 Tools Covered: openLCA, GLAD / Public LCA Dataset, Google Colab, Python, Pandas, Matplotlib / Plotly
📅 Day 2: AI-Powered Carbon Prediction, Hotspot Analysis and Scenario-Based LCA
- Role of AI, machine learning and data analytics in environmental impact intelligence
- Feature engineering for LCA datasets, emission factors and sustainability indicators
- Predictive modeling for carbon footprint, energy demand and environmental impact estimation
- Machine learning models for impact prediction using lifecycle input parameters
- Lifecycle hotspot analysis for identifying high-impact materials, processes and stages
- Scenario-based LCA comparison: conventional vs low-carbon vs circular design alternatives
- Sensitivity analysis for understanding which assumptions influence LCA outcomes most
- Uncertainty analysis in environmental assessment and responsible interpretation of results
🛠️ Hands-on:
- Hands-on 1: Carbon Footprint Prediction Model using Machine Learning
- Hands-on 2: Scenario-Based Hotspot, Sensitivity and Optimization Analysis
🧰 Tools Covered: Google Colab, Python, Pandas, Scikit-learn, Brightway / Brightway2, Plotly
📅 Day 3: Sustainability Dashboards, ESG Reporting and Digital LCA Decision-Support Systems
- Digital transformation of LCA and sustainability reporting workflows
- Environmental intelligence dashboards for carbon, emissions, energy and lifecycle-stage monitoring
- Using LCA outputs for ESG reporting, carbon disclosure and sustainability communication
- Circular economy strategies: reuse, recycling, remanufacturing, resource recovery and product redesign
- Digital product passports and traceability for lifecycle sustainability intelligence
- AI-powered LCA decision-support systems for research and industry use cases
- Future trends: prospective LCA, climate scenario modeling, ESG analytics and automated sustainability platforms
- Deployment challenges: transparency, reproducibility, data standardization, model bias and scalability
🛠️ Hands-on:
- Hands-on 1: Sustainability Intelligence Dashboard for LCA and ESG Metrics
- Hands-on 2: Mini Project: AI-Enabled Digital LCA Decision-Support System
🧰 Tools Covered: Streamlit Community Cloud / Local Streamlit, Google Colab, Python, Scikit-learn, openLCA, Brightway Dataset
