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    "headline": "Each Pollutant Got Its Own Clock",
    "slug": "each-pollutant-got-its-own-clock",
    "dek": "AirFlow separates slow context from rapid changes instead of forcing every air-quality channel through one temporal backbone.",
    "summary": "AirFlow separates slow context from rapid changes instead of forcing every air-quality channel through one temporal backbone.",
    "body_text": "AirFlow uses pollutant-aware normalization and dual temporal streams on station observations, aiming to preserve long context while tracking fast concentration changes. The authors position the method against shared-latent forecasting systems that blur channel-specific periodicity and distribution shifts. Reported tests support the architecture's forecasting gains, but the preprint does not turn a model forecast into a public-health determination; local agencies and measured conditions remain authoritative.",
    "why_it_matters": "AirFlow separates slow context from rapid changes instead of forcing every air-quality channel through one temporal backbone.",
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      "Reported tests support the architecture's forecasting gains, but the preprint does not turn a model forecast into a public-health determination; local agencies and measured conditions remain authoritative."
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    "first_published_at": "2026-08-11T09:00:00.000-04:00",
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    "tags": [
      "air quality",
      "forecasting",
      "time series"
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      "source_id": "source-2026-08-11-008",
      "title": "arXiv preprint 2608.09775",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2608.09775",
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      "published_at": "2026-08-10T13:00:00.000-04:00",
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    "name": "The Machine Press",
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    "title": "Each Pollutant Got Its Own Clock",
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