AI-Powered Life Cycle Assessment for Carbon Footprint and ESG

Enable participants to leverage AI-powered digital tools to perform comprehensive LCA, identify carbon hotspots, and create actionable sustainability dashboards for research and industry applications.

• Understand LCA methodology, lifecycle boundaries, and environmental indicators.
• Apply AI/ML models for carbon footprint prediction and hotspot analysis.
• Build dashboards and decision-support systems for ESG and sustainability reporting.
• Integrate real-time data and scenario analysis into lifecycle decision-making.

📅 Day 1: Foundations of LCA and Environmental Data

• Importance of LCA in sustainability, ESG, and product design
• LCA phases: Goal & Scope, Inventory, Impact Assessment, Interpretation
• Life-cycle boundaries & environmental indicators (carbon, energy, water, emissions, waste)
• Scope 1/2/3 emissions and digital LCA workflows

🛠️ Hands-on:

• OpenLCA model exploration
• Carbon footprint calculation
• Data visualization

🧰 Tools Covered: OpenLCA, Brightway2, Python (Pandas, Plotly), Google Colab

📅 Day 2: AI & ML for Carbon Prediction and Hotspot Analysis

• Machine learning models: Regression & Clustering for environmental impact
• Hotspot detection and scenario-based LCA comparison
• Sensitivity, uncertainty, and optimization using AI
• Real-time data integration for dynamic sustainability decisions

🛠️ Hands-on:

• Regression & clustering models
• Hotspot analysis
• Genetic Algorithm optimization

🧰 Tools Covered: Python (Scikit-learn, DEAP), Brightway2, ThingSpeak, Google Colab

📅 Day 3: Sustainability Dashboards and AI-Enabled Decision Support

• Carbon intelligence dashboards: stage-wise emissions, hotspots, reduction potential
• ESG reporting, digital product passports, and circular economy strategies
• AI-powered LCA decision-support systems & climate scenario modeling
• Deployment considerations: data standardization, reproducibility, transparency

🛠️ Hands-on:

• Dashboard creation (Excel/Power BI/Streamlit)
• Mini project: AI-assisted carbon hotspot detection

🧰 Tools Covered: Streamlit, Excel, Power BI, Python, OpenLCA, Brightway2

• Sustainability professionals and ESG analysts
• Environmental engineers and researchers
• Data scientists focusing on sustainability or energy analytics
• Product designers, policy makers, and academic scholars interested in AI-driven lifecycle assessment

By the end of the workshop, participants will be able to:

• Conduct end-to-end LCA and environmental impact assessments.
• Predict carbon emissions and identify high-impact lifecycle stages using AI.
• Develop interactive dashboards for sustainability monitoring and reporting.
• Implement AI-assisted decision-making for circular economy and ESG initiatives.