๐Ÿ“ฐ Press Release

DC Hub Launches Air Permitting Intelligence on the Land & Power Map

Every US data-center parcel now returns live EPA nonattainment status, 23,319 AQS monitor design values, Federal Class I proximity, and expected permitting pathway

INFRASTRUCTURE April 15, 2026

DC Hub today announced the general availability of Air Permitting Intelligence on its Land & Power Map, bringing real-time federal air-quality and permitting data to every parcel evaluation across the continental United States. For the first time, data-center developers can see PM10, PM2.5, ozone, and GHG permitting constraints at the moment of site selection โ€” rather than discovering them nine to eighteen months into project engineering, after significant capital has already been committed.

The new layer ships with 113 live EPA Green Book nonattainment polygons, 23,319 active AQS monitor design values, and all 83 federally-designated Class I areas with 300-kilometer Federal Land Manager consultation buffers. Every parcel click returns a composite 0-to-100 Air Permitting Score, weighted across seven factors including ozone nonattainment (25%), PM2.5 nonattainment (25%), PM10 nonattainment (10%), nearest monitor design values (15%), Class I proximity (10%), NEI cumulative source density (10%), and state agency permitting posture (5%).

Air permitting is the single largest determinant of timeline and cost for any data center with on-site combustion, which is nearly all of them. A typical 100 megawatt campus installs 50 to 80 megawatts of diesel backup generator capacity, and above roughly 100 tons-per-year of NOx emissions in an ozone nonattainment area, the project crosses the threshold into Nonattainment New Source Review. That triggers a Lowest Achievable Emission Rate requirement plus the obligation to purchase emission offsets from existing sources, typically adding 9 to 18 months to permitting and 2 to 8 million dollars in offset costs for a mid-sized site.

The platform also surfaces state-specific permitting context for all 50 states plus the District of Columbia. Virginia's streamlined Loudoun County data-center pathway, California's unique complexity across CARB and regional air districts, and Texas's Standard Permit framework are all reflected in the scoring and guidance. Each parcel returns its expected permitting pathway โ€” Minor Source, Synthetic Minor, NNSR, or PSD โ€” with an estimated offset cost range where applicable, drawing on classification-specific NOx thresholds from 40 CFR 51.165.

In parallel with the user-facing launch, DC Hub has exposed the capability as its 21st MCP tool: get_air_permitting(lat, lon, capacity_mw). Claude, ChatGPT, Cursor, Gemini, Copilot, and any other MCP-speaking agent can now query parcel-level air-permitting intelligence directly, making DC Hub the first platform to surface this dataset to the autonomous-agent ecosystem.

Quote from Jonathan Martone, DC Hub:
"Air permitting has been a persistent blind spot in the site-selection process. Developers would ink a Letter of Intent, engage engineering, and only discover six months later that their parcel fell inside a PM10 nonattainment area requiring offsets they hadn't budgeted for. Bringing this data to the map โ€” and to every AI agent that helps our users make decisions โ€” collapses that feedback loop from months to seconds."

Data sources include the EPA Green Book ArcGIS REST service for nonattainment polygons (refreshed weekly), the EPA AQS Data Mart API for monitor design values (refreshed daily), 40 CFR 81 for the Federal Class I legal list, EPA NEI for stationary source emissions, and curated state SIP databases reviewed quarterly.

Air Permitting Intelligence is available now to all DC Hub Enterprise subscribers at no additional cost, accessible through the Environmental & Risk layer panel on the Land & Power Map at dchub.cloud/land-power-map. The API is available to Developer and Pro tier subscribers under /api/infrastructure/air-permitting/, and the MCP tool is discoverable in the DC Hub MCP registry alongside the existing 20 tools.