Brownfield Opportunities

Background

The question I set out to answer: Where are the contaminated and underused sites that could be redeveloped, and which of them already sit next to the power, water, and transport you'd need to actually build?

Brownfields, Superfund sites, and former defense lands are an underrated lever for reindustrialization and for bringing new power online. The same things that make a site good for energy redevelopment (proximity to transmission, substations, generation, and water) are what you need to host the load growth coming from AI and data centers. One site can support the AI build-out, bring new generation and industry online, and send jobs and cleanup to communities that have lived with the contamination for decades. EPA's own RE-Powering program already flags hundreds of these sites as redevelopment-ready, so there's a concrete list to start from.

How It Works

I vibe-coded the data pipeline and the dashboard, leaning on official federal sources so the map is defensible. The whole thing is static and refreshes from one command:

• Data sources: ~46,800 federally-tracked sites across EPA Superfund (NPL), EPA ACRES brownfields, USACE Formerly Used Defense Sites, and DOD BRAC, pulled from their official ArcGIS/REST services.
• Enrichment & scoring: a pure-Python spatial grid computes mile-precision distance from every site to the nearest transmission line (with kV), substation, power plant (with MW and fuel type), road, rail, and gas pipeline (HIFLD + Census TIGER), plus FEMA flood-zone classification. EPA's RE-Powering signals flag data-center-reuse candidates (≥50 acres with power and water), and EPA ECHO adds enforcement history.
• Narratives: Claude Haiku synthesizes each site's status, acreage, infrastructure, documents, and enforcement into a short buyer-oriented summary, cached by content-hash so re-runs only re-bill when the underlying data changes.
• UX: a Leaflet + Canvas map and a sortable table with filters, shareable URL state, CSV export, and a mobile bottom-sheet detail panel, all served as static files on GitHub Pages.

[View the Live Dashboard] | [View the Code]