HackerPapers

arXiv:2608.22153physics.ao-ph

Quantifying AI data center nitrogen oxide (NO$_x$) emissions from space

Kevin D. Gauld, Daniel J. Varon, Nicholas Balasus, Daniel H. Cusworth

HN submission. Found in a submission link or body. Submitters do not count as commenters in the main ranking; a submission is not an endorsement.

Abstract

AI data center power demand is spurring rapid deployment of on- and near-site natural gas turbines. The resulting nitrogen oxide NO$_x$ pollution is a growing concern but has not previously been quantified with atmospheric observations. Here we demonstrate space-based detection and quantification of NO$_x$ emissions from the SpaceXAI Colossus 2 power plant in Southaven, Mississippi. Using observations from the geostationary TEMPO satellite instrument, we detect a strong increase in local mean NO$_2$ column concentrations after the plant began operations in late 2025. We then use TEMPO to estimate two-week-average NO$_x$ source rates from August 2025 to August 2026, calibrating against continuous emission monitoring system (CEMS) data from US power plants. TEMPO first detected NO$_x$ emissions in December 2025 at 530$\pm$220 kg h$^{-1}$. We find that emissions increased through August 2026, averaging 870$\pm$165 kg h$^{-1}$ after February 2026, roughly 19$\pm$4 times higher than expected from the facility's March 2026 permit for 41 turbines operating under best available control technology (BACT) requirements ($\sim$47 kg h$^{-1}$). Emissions at the expected level would be undetectable by our TEMPO analysis.

arXiv comments
Journal reference
DOI
Subjects
physics.ao-phAtmospheric and Oceanic Physics

On Hacker News

No comments linking this paper were found in the collected sources. Found in 1 HN submission from Aug 2026 to Aug 2026. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments0 threads

No comments linking this paper were found in the collected sources. Open submission discussions.

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.