AI-Powered Life Cycle Assessment and Carbon Intelligence

The aim of the AI-Powered Life Cycle Assessment and Carbon Intelligence workshop is to help participants understand and apply practical methods for assessing carbon emissions across product and process life cycles using LCA principles, carbon footprint modeling, AI-assisted data analysis, and dashboard-based sustainability decision-making.

The workshop focuses on enabling participants to calculate emissions, analyze sustainability datasets, identify carbon hotspots, compare reduction scenarios, and create simple carbon intelligence dashboards using tools such as Excel, OpenLCA, Python, Google Colab, Power BI, Google Sheets, and introductory Brightway2.

• Introduction to Life Cycle Assessment and its role in sustainability research
• Understanding product life cycle stages: raw materials, manufacturing, transport, use, and end-of-life
• Basics of carbon footprint modeling and environmental impact assessment
• Understanding activity data, emission factors, and carbon intensity
• Introduction to Scope 1, Scope 2, and Scope 3 emissions
• Role of AI and data analytics in improving LCA workflows
• Building a simple carbon calculation framework for product or process analysis

• 1: Excel-Based Carbon Footprint Calculation
• 2: Basic LCA Workflow Exploration in OpenLCA

• Introduction to sustainability and carbon datasets
• Preparing LCA and emission data for analysis
• Using Python for basic carbon data analysis
• Cleaning and organizing activity data and emission factors
• Identifying emission hotspots across materials, processes, and life cycle stages
• Visualizing carbon contribution and high-impact areas
• Introduction to AI-assisted emission prediction and ranking

• 1: Carbon Dataset Cleaning and Emission Calculation in Google Colab
• 2: Emission Hotspot Detection Using Python

• Understanding carbon intelligence dashboards for sustainability decision-making
• Key dashboard indicators: total emissions, stage-wise emissions, hotspots, and reduction potential
• Scenario comparison for carbon reduction planning
• Interpreting LCA and carbon analysis results for research and industry use
• Using dashboards for ESG reporting, product design, and sustainability communication
• Preparing simple recommendations based on emission hotspot analysis
• Developing a final mini project for AI-assisted carbon intelligence

• 1: Carbon Intelligence Dashboard Creation in Excel / Power BI
• 2: Mini Project: AI-Assisted Carbon Hotspot Detection and Sustainability Dashboard

• Understand the fundamentals of Life Cycle Assessment and carbon footprint modeling.
• Identify product life cycle stages such as raw materials, manufacturing, transport, use phase, and end-of-life.
• Explain the role of activity data, emission factors, carbon intensity, and Scope 1, Scope 2, and Scope 3 emissions.
• Build a basic carbon footprint calculation framework using Excel and Google Sheets.
• Explore LCA workflows using OpenLCA and introductory Brightway2 concepts.
• Clean and organize sustainability, activity, and emission datasets for analysis.

• Industry professionals, researchers, and sustainability analysts involved in environmental impact assessment or corporate ESG initiatives.
• PhD scholars, postgraduate students, and academics working on sustainability, energy, environmental science, or industrial process optimization.
• Data scientists, AI practitioners, and engineers interested in applying AI for carbon footprint analysis and life cycle assessment.
• Professionals and students looking to gain hands-on experience with AI-assisted LCA tools, carbon modeling, and sustainability dashboards.
• No prior advanced AI or LCA expertise is required, but a basic understanding of Excel, Python, or data handling will be helpful.

• Live & recorded sessions
• e-Certificate upon completion
• Post-workshop query support
• Hands-on learning experience