PlumeQuant: Uncertainty-aware consistency assessment of methane plume masks and emission-rate estimates

TL;DR — PlumeQuant is a diagnostic tool that stress-tests satellite-derived methane plume products, showing that published scalar quantities (mass enhancement, plume length, emission rate) do not uniquely determine the underlying plume mask. It matters for trustworthy greenhouse-gas monitoring, but is a domain remote-sensing/geoscience contribution rather than a core AI-advancement topic (hence "Other").

• Using 63 EMIT/Carbon Mapper plume records, the authors demonstrate equifinality: substantially different but plausible masks reproduce the same IME, plume length, and emission rate; the high-confidence core covers only a median 13% of the plausible footprint.
• A genetic-algorithm ensemble conditioned on published IME and plume length makes this ambiguity explicit, which is largest for weak, low-overlap plumes.
• A transparent "CM-like" mask (built without access to the reference mask/published values) reproduced published IME to +0.72% median, emission rate to +0.16%, and reached 0.843 median IoU against reference masks.
• The authors stress these are product-level consistency diagnostics, not independent validation, intended to flag weak/offset/ambiguous plumes for expert review.