AI-Driven Green Ammonia: Electrolyzer Pathways, Storage Logistics, Carbon Intensity and LCOA

To give participants a practical, end-to-end understanding of green ammonia as fuel and fertilizer—covering electrolytic production, safe storage and logistics, and LCOA/CI modeling for bankable project decisions.

• Understand key electrolytic pathways (PEM/alkaline/SOEC) and their integration with ASU and Haber–Bosch/e-Haber.

• Size core units (electrolyzers, ASU, synthesis loop, storage) and develop first-cut LCOA estimates.

• Compare storage, transport, and end-use options for ammonia as fuel and fertilizer.

• Quantify carbon intensity (CI) and identify main technical and commercial LCOA/CI drivers.

• Build and test a decision-ready LCOA/CI model to support bankable green ammonia projects.

• Professionals in renewable energy, hydrogen, ammonia, and fertilizer industries

• Chemical, mechanical, energy, and process engineers (plant design, operations, EPC)

• Project developers, consultants, and investors evaluating green ammonia projects

• Researchers and postgraduate students in energy systems, climate tech, and process engineering

• Policy, sustainability, and ESG professionals working on low-carbon fuels and fertilizers

• Understand electrolytic green ammonia production pathways and their safe integration with ASU, Haber–Bosch/e-Haber, and renewables.

• Evaluate storage and transport options and compare green ammonia end-uses as fuel (engines, turbines, fuel cells) and as fertilizer.

• Build and refine an Excel-based LCOA and carbon intensity (CI) model with key sensitivities (power price, CF, stack life, incentives).

• Assess project bankability and prepare a concise investment-style memo highlighting CI, LCOA range, and major risks/mitigations.