Inspiration
Decarbonization projects like carbon capture, hydrogen, and synthetic fuels depend heavily on siting. But finding viable locations that combine CO₂ sources, industrial demand, infrastructure, and regulatory fit is tedious and manual. We realized that acetic acid production, a chemical process rich in concentrated CO₂ emissions, often coexists with broader petrochemical activity making it a valuable siting signal.
What it does
AI-powered tool to find optimal sites where acetic acid and chemical facilities overlap, based on permitting, logistics, incentives, and community sentiment with focus on EU.
Challenges we ran into
- There are no public API for acetic acid facilities especially in the EU
- Facility-level data is fragmented and often paywalled, especially for specialty chemicals
- Matching datasets (by location, activity type, or operator) required a lot of cleaning and cross-referencing
- Building an MVP without access to proprietary databases like GlobalData was tough but rewarding
Accomplishments that we're proud of
We assembled a working MVP that maps and scores industrial zones using open data and built a pipeline to scale across countries and adapt to other CO₂-rich processes. We also designed a modular system that could integrate with emissions APIs or commercial datasets in the future
What we learned
We learnd that Acetic acid production is a strong siting signal for industrial decarbonization projects.Developers and regulators are also missing tools that connect CO₂ source mapping with commercial and regulatory fit
What's next for LambCo
We want to add a real AI/ML model to optimize site scoring based on historical project success, infrastructure proximity, and cost data and also integrate real-time emissions, permitting zones, and power market prices. In addition, we also want to partner with chemical industry stakeholders and decarbonization startups to test site selection tools.
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